Print ISSN 0033-9008
Online ISSN 1880-1765

Aug. 2024 Vol. 65 No. 3
CONTENTSPAPERS
Study on Interlocking Devices in a Cloud Computing Environment I O
Design Method for Corrosion of Reinforcing Bars in Concrete Structures by Water
Penetration and Carbonation Progress I
Development of Automatic Generation of Maintenance Worker Schedule Using Tabu
Search O R
Development of Safety Check Support Device for Drivers Using Side Cameras on
Rolling Stock O
Rolling Stock Scheduling Algorithm for Temporary Timetable After Natural Disaster O
Cage Wear Prediction for Traction Motor Bearings of Railway Vehicles Based on
Measurement of Contact Force between Rolling Element and Cage R

REVIEWS
Outline of Design Standard and Commentary for Railway Structures (Concrete
Structures) I N
Introduction Manual for Natural Frequency Identification System of Bridge Piers by
Constant Microtremor Measurement I

SUMMARIES
Summaries of RTRI REPORT (in Japanese)

H Human factors
I Infrastructure
N Natural hazards
O Operations
R Rolling stock
T Technical system integration and interactionPrintISSN 0033-9008

August 2024 Vol. 65 No. 3

Online ISSN 1880-1765

CONTENTSPAPERS
155 Study on Interlocking Devices in a Cloud Computing Environment I O································································································N.TERADA, S.SHIOMI, T.TOYAMA
162 Design Method for Corrosion of Reinforcing Bars in Concrete Structures by Water Penetration andCarbonation Progress I·········································································· S.TODOROKI, T.ISHIDA, H.UEDA, T.TADOKORO
170 Development of Automatic Generation of Maintenance Worker Schedule Using Tabu Search O R························································································· T.KOKUBO, S.KATO, T.NAKAHIGASHI
176 Development of Safety Check Support Device for Drivers Using Side Cameras on Rolling Stock O······················································································· W.GODA, H.MUKOJIMA, N.NAGAMINE
182 Rolling Stock Scheduling Algorithm for Temporary Timetable After Natural Disaster O····································································· S.KATO, T.NAKAHIGASHI, T.KOKUBO, J.IMAIZUMI188 Cage Wear Prediction for Traction Motor Bearings of Railway Vehicles Based on Measurement of Contact
Force between Rolling Element and Cage R··············································D.SUZUKI, K.TAKAHASHI, Y.OKAMURA, F.ITOIGAWA, S.MAEGAWAREVIEWS
195 Outline of Design Standard and Commentary for Railway Structures (Concrete Structures) I N··································································K.WATANABE, T.TADOKORO, M.IKEDA, M.OKAMOTO
201 Introduction Manual for Natural Frequency Identification System of Bridge Piers by Constant
Microtremor Measurement I······························································································· S.WATANABE, H.IRI, S.FUJIWARA
SUMMARIES
207 Summaries of RTRI REPORT (in Japanese)

H Human factors
I Infrastructure
N Natural hazards
O Operations
R Rolling stock
T Technical system integration and interaction

PAPER

Study on Interlocking Devices in a Cloud Computing Environment
Natsuki TERADA
Shunsuke SHIOMI
Takashi TOYAMA
Signalling Systems Laboratory, Signalling and Operation Systems Technology Division
We report on our study and proposal for interlocking devices in a cloud computing environment. This
proposal realizes resilience, reduces time and cost of replacement, and provides interlocking processes as aservice. The proposed system has the feature of processing interlocking logics of different stations
independently. Furthermore, the proposed system has three layers: terminal devices to interface track
circuits, signals, and switches, etc., logic units to process interlocking logics, and controllers to assign theinterlocking table to logic units. We defined the specifications for terminal devices, logic units andcontrollers, and verified them.
Key words: interlocking device, cloud computing, interlocking as a service, segment, asynchronous logic
1. Introduction
Interlocking devices control physical devices such as signals
and switches with safety integrity, based on the command of train
movements and train locations. Interlocking functions are achieved
with relays and/or computers. Conventional relay interlocking devices are installed at individual stations or parts of a station. Overthe past few years, however, computer-based interlocking devices
have become more widespread. Although computer-based interlocking devices were initially installed at individual stations, centralized computer-based interlocking devices controlling several
stations along sections of a line have recently been developed andbrought into service. This centralization of interlocking devices isan effective way to reduce the burden of maintenance, especially on
low density lines.
By extending the concept of centralized interlocking devices
and introducing the concept of cloud computing, the authors aredeveloping an interlocking device system which can operate in acloud computing environment. This enables the interlocking function to be supplied to many stations across different lines [1]. This
report describes the concept of the cloud-based interlocking system
environment and issues which remain to be solved. We then propose
a comprehensive cloud-based interlocking device system structureand describe the function of its sub components. Finally, we describe the possibilities of realization based on simulations.
2. Concept of cloud-based interlocking devices
2.1 Current situation regarding interlocking devices in Japan
Interlocking devices are classified as mechanical interlocking
devices, relay based interlocking devices and electronic (or solidstate) interlocking devices. Currently, 40% of interlocking devices
used by JR companies are electronic. Since interlocking devices
were installed in Japan for the first time in 1985, older devices on
the network will soon need to be replaced. 80% of older relay-type
interlocking devices are on smaller train operator networks, andmost of these are estimated to be over 50 years old. However, replacement of interlocking devices, which involves system design,
installation, changing connections and device verification, is labor
intensive. Therefore, there is a strong need to reduce the burden ofwork involved for their replacement.
In general, interlocking devices are installed at individual staQR of RTRI, Vol. 65, No. 3, Aug. 2024

tions. However, recently, centralized interlocking devices have beendeveloped and introduced to control several stations along a certain
line [2-4]. While the centralized interlocking device with logic unit
are installed in one place, terminals are installed at each station instead of a logic unit to interface with physical devices such as signals and switches. The logic units and terminals are connected with
communication lines. The interlocking tables at each station are assembled into one interlocking table and processed with the logic
unit. These kinds of interlocking devices have been introduced on
low density lines [2, 3] and some high speed lines [4].
In addition, network based interlocking devices have been developed and introduced [5], in which physical devices are connectedwith object controllers over the network, not peer to peer.
2.2 Problem of interlocking devices and cloud computing eElectronic interlocking devices are generally installed at stations or along the wayside to control. When a large disaster and/or
ground fault occurs, whole system is severely damaged and system
repair is time consuming. In addition, replacement of interlocking
devices is labor intensive. Installation of an electronic interlocking
device, requires preparation of the new device, installation andchecking of the interlocking logic, installation of the device at theside of the existing device, and then wiring of the device to existing
connectors. For a small company, not only is the cost of replacement
unaffordable, but also they often lack the capacity to plan and carryout the replacement.
In the case of cloud computing services however, which provide large scale computational resources remotely, customers canaccess servers regardless of their actual location or computationalsituation. These kinds of services provide robust systems against
disaster and the need for replacement, which is also favorable in thelight of the safety integrity required of interlocking devices. Therefore, we will explore how a cloud-based interlocking device service
changes railway operations, and how the technology is provided.
2.3 Schematic presentation of “Interlockings as a Service”
Figure 1 illustrates the concept of interlockings as a service.
Logical parts of interlocking functions, currently distributed at eachstation, are concentrated in an “Interlocking Center.” The interlocking center is relocatable and can be located where the risk of disasters is low. Interlocking centers can also be distributed depending on
available networking conditions, optimizing robustness against di155

sasters.
Large railway operating companies which own their own interlocking devices can benefit from ease of replacement and robustness
against disasters. On the other hand, small railway operating companies, who do not have their own devices, can receive “Interlocking
as a Service” from large railway operating companies or service
providers including signal device suppliers. Small companies would
thus pay a fee for this service to the larger railway operating companies, enabling the larger companies to improve the financial returnon their own equipment. The impact of the system is expected to be
as follows:(1) Resilience against disasters
If logical controllers for interlocking functions are located indisaster-free areas, when disasters and/or accidents do happen, it
will be easier to repair interlocking functions in stations, since thelogical components will be safe. Even if a signal house is severely
damaged, it will be enough to repair the terminals and connections.
In addition, repairs to remedy degraded conditions will be available
using radio when cables between terminals and devices are damaged.
(2) Reduction of replacement cost
Replacement of interlocking devices is resources and labor intensive. In the case of electronic interlocking device replacement inparticular, a new device must be prepared and its programs, andconnection with field devices must be checked. If an old device isobsolete, compatibility must be ensured between the old device andthe new device. On the other hand, when interlocking function processing can switch from one server to another, seamless replacement
is possible. Server-based interlocking functions can thus reduce thereplacement cost and in turn problems related to concerns about
serviceable life of interlocking devices.
(3) Interlocking as a Service
This technology enables a new business model of “Interlocking
as a Service,” in which function of interlocking logic process ismade accessible over the network for a subscription. Especially forsmall railway operating companies, this removes the burden ofmaintenance and replacement of signalling devices, results in reduction of demand for human resources.
2.4 Overseas versions of the concept
There are also some proposals for “Interlocking as a Service”
outside of Japan. In Europe, the systems are developed in which
existing electronic and centralized interlocking devices are com-bined with physical devices over an IP-network. DSTW (Digitales
Stellwerk, or digital interlocking) by Deutsch Bahn [6] and SIMIS
IaaS by Siemens [7] are examples. DSTW carries out centralized
maintenance work and remote control by arranging several electronic interlocking devices in one place.
3. Proposal on basic structure of interlocking devices on cloudcomputing environments
This section examines the current process associated with electronic interlocking devices, and identifies issues for consideration in
the development of cloud-based interlocking devices systems.
3.1 Procedure of current interlocking devices
Usually, logical units for electronic interlocking devices comprise a program and interlocking table which are stored in ROM or
flash memory. The program and interlocking table are loaded into
RAM, and processed according to the stored program. Objects ofinterlocking tables are fixed to specific stations, which cannot bechanged dynamically.
Input from / output to field devices and processing of logic are
cyclically executed in the designed cycle. Even with many objects,
all input/outputs and logic processing is executed once in the cycle.
Therefore, suspension of just one station requires suspension of allother stations controlled by that interlocking device. When a smallchange needs to be made to logic at one station, not only is suspension of the whole station required, but also the influence of thechange on the other stations has to be checked.
Current electronic interlocking devices have 2 or 3 logic units
which compare processing output, enabling a transition to a safe
state when an incompatibility is detected. This fail-safe architecture
includes special devices to achieve safety. In addition, when different logic units are to be compared over the network, network delays
must be considered.
For this reason, when communication over the network is used,current electronic interlocking devices restrict the delay to within
specified limits.
Based on the above considerations, technology described below has to be developed to enable a cloud-based interlocking device
system for realizing “Interlocking as a Service”:(1) A method to independently process logic from different stations(2) A structure which enables cooperation of many logic units, andprocessing under the structure(3) A method to accept delay over the network
In addition, when we realize a large scale system, technology toachieve a fail-safe outcome by using Commercial Off the Shelf(COTS) CPUs is required. In our proposal, the architecture is basedon a logic unit with fail-safe CPUs, because achieving fail-safe withgeneral COTS CPUs [8] is not current practice.
3.2 Method to process each station’s logic independently

Fig. 1 Projected image for realization of “Interlocking asa Service”
156

As mentioned, each station’s logic is required to be processedindependently. As a result of our study, we propose to divide thecycles of the processor into segments, as shown in Fig. 2. A segment
represents a certain processing capability. The number of segmentsthat one processing unit can handle differs depending on the capacity of the processor. In Fig. 2, segment #2 is used to process interlocking function of Station A, while two segments #3 and #4 areused for Station B. The common procedure in segment #1 and #8
QR of RTRI, Vol. 65, No. 3, Aug. 2024

rently, all the network requires is sufficient bandwidth for communications. Radio connections are also possible. For security, appropriate technical security mitigations are required in accordance withthe type of network used.
3.4 Development of interlocking logic less affected by communication delay

Fig. 2 Concept of segment, or divided resource of logic
units
includes checking the cycle, input/output and memories.
3.3 Structure enabling cooperation of multiple logic units andprocessing under the structureInterlocking devices in a cloud computing environment provide interlocking functionality for multiple stations by a combination of many logic units. This system requires a function to allocate
processing resources to each station. An additional function is required to reallocate processing to alternative available resources incase of a logic unit failure. We propose controllers, which aim to
execute the above functions. The controllers allocate logic unit processing resources, monitor the health of logic units, keep interlocking tables and upload the tables to the logic units. If there is morethan one controller, the controllers share the status of logic units,
allocation table and interlocking tables. They work cooperatively.
The proposed controllers enable scalability of the system. We
can increase the number of logic units according to the required resources. The controllers also enable partial suspension of work on
logic units, and logic units can be replaced without halting the wholesystem.
The proposed structure of interlocking devices is shown in
Fig. 3. The system is composed of three layers: terminals to interface with physical devices, logic units, and controllers. There are
two networks: controller network and interlocking network. Cur-

Fig. 3 Three layered structure of cloud-based interlocking system
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Current electronic interlocking devices assume that the state ofphysical devices is collected within a certain time period, i.e., synchronously, and logic is processed cyclically. Any delay or packet
loss of the state of objects causes processing to halt. Therefore,
communication and terminal delays need to be allowed within specified time limits, to enable reasonable performance and reliability.
Imposing a zero-delay precondition in this system would be
difficult for networks to implement. In addition, considering costand maintainability of the system, other available communication
methods can be envisaged, including radio communication. Therefore, to take into account the need to work with real communication
networks, we should assume that logic units and physical devices
are asynchronous. The logic needs to be configured such that delay
or lack of status information has less impact on interlocking logic.
The main concept which we propose is based on three-value
logic in which an extra “undetermined” state is considered. Some
outputs of logical calculations are deterministic even if some inputs
are undetermined. We can expect that the influence of delay is reduced introducing three-value logic. In addition, it is not required tochange formulas used in the interlocking logic, which means current
interlocking table data can be used as it is.
Figure 4 shows an example of asynchronous interlocking incontrast with current logic. Current logic determines the output at
00:10 when each value of A and B is determined, while asynchronous logic determines the output at 00:08 when only the value of A
is determined.
4. Specification of components
We defined the specification of components mentioned above.

Fig. 4 An example of asynchronous logic
157

In this chapter we consider the specifications of controllers, logic
units and terminals associated issues.
4.1 Specifications of Controllers
Controllers have following functions: sharing interlocking tables and list of logic units as databases, making allocation tables of
how the logic units and its segments are allocated to the interlocking
table, and monitoring the health of logic units and other controllers
as well their own health. Relationships between controllers andlogic units can be arbitrary, but we suppose that for each logic unit,
only one controller is connected to the unit, i.e., the relationship is
one controller to ‘n’ logic units.
4.1.1 Monitoring health of controllers and sharing of data
Each controller monitors the health of the other controllers, andshares a list of controllers and logic units with their status, interlocking tables and allocation tables. The procedure of monitoring healthand data sharing is executed simultaneously, and it is based on thepolling from the primary controller to the secondary controllers asshown in Fig. 5.
One controller is elected and acts as the primary and the othercontrollers act as the secondary. However, any of the controllers canbe the primary. The primary controller sends secondary controllers
a list of controllers and logic units with their status, list of interlocking tables, and allocation tables. Each secondary controller checks
the list, updates the status of logic units in responsibility, and returns
the list of new data when it has newer data. When there is data thatthe secondary needs, the secondary controller requests the primarycontroller to send the data. On the other hand, when the primarycontroller receives information about new data, it requests the secondary controller to send the data.
When there is no response from one of the secondary controllers for a specified time, the primary controller determines that thesecondary controller has failed. On the other hand, when a secondary controller does not receive any information from the primarycontroller, the secondary controller determines that the primarycontroller has failed. When the primary controller fails, a new primary controller is elected from among the secondary controllers.
4.1.2 Election of primary controller
Determining rules to elect the primary controller. In principle,

one of the servers stands as a candidate for the primary controller,
and the rest approves. However, if some of the servers are not active
or are disconnected, the candidate cannot receive an answer from allof the other servers, therefore the approval of all other servers is notmandatory. From the point of view of non-active servers, the role ofthe primary controller may turn to another controller during non-active time. In this case the secondary controller receives an answer
from the unexpected server. In addition, if there is no inquiry fromthe expected server, the secondary controller changes recognition ofprimary to the new primary controller.
It is noted that if the ‘health’ of the server is determined by theexistence of messages, then a server failure cannot be distinguishedfrom a connection failure. If controllers are split into two or moreclusters due to the trouble in the network, another secondary controller is elected in the cluster without the primary controller, even if
the original primary controller is active. In this case when the network is resumed, the primary controllers arbitrate, and one of the
primary controllers remains as the primary. In order to activate thearbitration, the inquiry of the primary controller is continued to thecontrollers recognized as nonactive, and the servers answer the inquiry. When the network is resumed after the split, the primarycontrollers send messages of inquiry to each other, which makes
them aware of existence of the other primary controller and need forarbitration.
If there is an inquiry from the other primary controller to activate the arbitration procedure and one of the primary controllers
remains as the primary controller. The primary controllers exchange
the information on the arbitration procedure, and inform the secondary controllers which one remains as the primary controller.
4.1.3 Monitoring health of logic units
Another important function of controllers is to monitor logic
units. The controllers communicate with the logic units under their
responsibility. The communication is based on the polling from thecontroller and to the logic units. The controller sends the allocationtable. The logic unit responds to the inquiry by sending the status of
itself and the segment. The version of interlocking table is specified
in the allocation table and the data is requested by the logic unit
during the processing of the segment.
4.1.4 Supervision controller to back up monitoring function ofcontrollers
If a controller fails, the health monitoring function for logic
units also fails. In order to cover the failure of the health monitoring
function, supervision controllers are arranged in the controller network. A supervision controller is a controller which monitors thehealth of logic units. Supervision controllers are connected not only
to the controller network, but also to the logic unit network. Supervision controllers monitor messages in the logic unit network anddetermine the health of logic units by analyzing messages. Eachsupervision controller monitors a part of a logic unit because monitoring whole logic units is not feasible.
Even if a controller fails, logic units under the controller continue to work. However, it is not possible to allocate a new segment
or to release segment related to logic units under the failed controller. In this case, if another failure happens in one of the logic units,
the supervision controller finds the failure, and the primary controller can allocate a new segment to another working logic unit.

Fig. 5 Procedure of checking health of controllers andsharing data
158

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4.2 Specification of logic units
Logic units receive the state of the physical device via terminals and the network, process the interlocking logic and send thecommand to the device. The main function of logic units consists ofa segment function and processing interlocking logic. Figure 6
shows the state diagram of logic units. When interlocking tablechanges, current interlocking devices are reset. On the other hand,interlocking devices in the cloud computing environment do notreset themselves and are partially initialized for each station.

Fig. 6

State diagram of logic units

4.2.1 Process and protection of segment
We studied the partition and protection of computational resources of logic units from the point of view of minimizing the interaction between segments.
The processing of large-scale logic requires more than one
segment. Therefore, the group of segments for processing the logic
for a certain station are defined as a “task.” The task is identified bycontext ID, which is given by a controller.
The logic unit with segments is a kind of multi-task system.
However, within the segments the single thread process is adopted
to ensure safety, which is often used in interlocking devices. The
basic function of logic units is to switch to the processing of segments in a certain period. The processing of segments is supposed tofinish within the specified period. Even if a problem occurs, the basic function of the logic unit forces task switching, or pre-emption.
Memory is allocated independently to each segment, and theallocated memory of one segment is not accessed by the other segments. The allocation is based on segment, but not on task, which
does not require the continuity of segment, i.e., fragmentation ofsegment is accepted. The internal state of a segment is loaded into
the allocated memory before each processing of segment switches.
Figure 7 shows the state diagram of segment. The life cycle ofa segment shown in Fig.7 is described as follows. First, the segment
is initialized. If the interlocking table is not found in the logic unit,
the table is requested from the controller. If the interlocking table isloaded in the logic unit, the logic is initialized and ready to processuntil the segment is released by the order of the controller.

Fig. 7 State diagram of segment
units determine the result of the part in which required input is collected. Even if a part of the status has not arrived, the irrelevant part
is not affected. Logics with a time-stamped value are advantageousin that there is less inconsistency due to time difference.
Four kinds of time stamp are used in the proposed logic: realtime, internal front time, internal rear time, and referenced time.
Internal rear time means the newest time at which all of input/output
values are determined, i.e., the values are determined earlier than theinternal rear time. Internal front time is the time at which the logic
units received the newest value, i.e., calculation of the values at alater time than the internal front time is not required because status
is not expected to be determined due to the lack of information. The
referenced time is the time at which the calculation of the logic istargeted at. Figure 8 shows an example of the four times. Three ofthe four times without a real time are based on the time-stamp. As
shown in Fig.8, the calculation is executed with referenced time
between internal front and rear time. When some input/outputs are
determined at some time, or new values are received, internal front
and rear times are updated. In addition, timeout is applied to determine the lack of information.

4.2.2 Asynchronous process of interlocking logic
We define more concretely asynchronous logic mentioned in
Section 3.4, especially on the concept of time. In the logic, timestamped state is exchanged between logic units and terminals. Logic
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Fig. 8 Four internal times of a logic unit159

4.3 Specification of terminals
The terminals interface with physical devices such as track
circuits, signals and point machines. They control physical devices
and receive the status of physical devices. The main functions are as
follows: (a) receiving control from logic units, (b) processing control according to the priority, (c) checking consistency between
controls from logic units, (d) controlling physical devices, and (e)obtaining status of physical devices.
Terminals are arranged in two ways to cope with multiple cases. The first is centralized control in which one terminal is arrangedin the signal house or signal box and many physical devices arecontrolled by the terminal. The second is distributed control inwhich the terminal is integrated into the physical device or installed
alongside it.
When inconsistency is detected between the controls of different logic units, an abnormality is detected. This detection function isbuilt into the supervision controller introduced in section 4.1.
4.3.1 Receiving and processing control from logic units
Commands from logic units are received by the terminals regardless of the object of the control. The terminal process is cyclical. In the first step of the cycle, the terminal checks the object of thecommand. If the object is the device under the management, theterminal controls the device. If not, the command is neglected.
4.3.2 Checking command and controlling physical device
Usually, the logic is processed by more than one logic unit,
controls are also sent from more than one logic unit. The terminal
selects a control taking into account the priority added in the control.
Controls are time-stamped, and if the control with same time stampfrom different terminals are different, the terminal detects the abnormality and informs the supervision controller.
The terminals check the status of the physical device and send
it to the logic units. If a mismatch is detected between inputs fromthe different segments, the mismatch is notified to the supervisioncontroller. It has been noticed that the information may be delayed
and asynchronous, therefore mismatches based on to the time-stampof the control as shown in Fig. 9. In Fig. 9, the logic units relatedwith mismatches are determined to have failed.

Fig. 9Failure detection by supervision controller

4.3.3 Specification of supervision controller on the interlocking
network
In addition to the other controllers, the supervision controller
monitors the health of logic units. The supervision controller also
checks the health of logic units and the network health based on an160

analysis of communication between logic units and terminals. Supervision controllers also receive information about lack or inconsistency of control detected by terminals.
These abnormalities are delivered to other controllers via thecontroller network.
5. Verification of specification by simulation
5.1 Verification of controller
The behavior of controllers is verified using model checking.
We used SPIN [9], which is a traditional model checking tool originally developed as a verification tool for communication protocols.
We checked the functions of monitoring health and election of a newprimary controller when the primary controller stops or the network
splits.
5.2 Verification of synchronous logic
We made a simulator of asynchronous logic, and confirmed
feasibility of our proposal by the simulator. In the simulator, scenarios including delays were set and simulation was carried out in realconditions.
This section introduces a case study of train movement tracking. The tracking logic of train movement expresses the status oftrack circuits in five states. A logic is incorporated that when theinterval between the breaking of the preceding track circuit and thatof the track circuit itself, the state of track circuit is determined to be
erroneous, i.e., it is not a normal train movement. We confirmed that
this logic works well when an interval of 0.5 seconds with a delay of
1 second delay occurs against an error detection threshold of 0.9
seconds. In this way, the asynchronous logic is applicable to thelogics including time judgement.
5.3 Verification of whole system
We constructed a simulator on a PC, which focuses mainly on
communication between components, and simulates the controllers,
the logic units and the terminals, as well as communications between them.
For the function of controllers, the simulator simulates controller or logic unit failures as well as network separation and re-unification. When failure of controller or separation of networks happens, a new master controller is elected. When unification of
network occurs, the primary controllers are unified. The reallocationof segment also works for both a controller and a logic unit under
the controller.
For control and status information, communications are simulated, such as control from the logic units to the terminal, and statusof physical device via terminal to logic units. When a failure of one
logic unit happens, the supervision controller detects the failure andinforms the controller.
Precise logical process is not simulated, but control based on
the asynchronous logical calculation is simulated. The simulator
also has the function of analyzing the influence of a communication
delay.
For example, when a controller fails, reallocation of segments
is executed as follows. The controller detects its own failure andanother segment is allocated by the primary controller. The logic
controller starts working with the newly allocated segment and the
new allocation table is shared by other controllers.
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6. Conclusion

References

We proposed a cloud-based interlocking device, in which interlocking logics for multiple stations are independently processed,
and partially stopped for maintenance or upgrade purposes. The
proposed system is structured in three layers: controllers to allocatecomputational resources to interlocking logics, logic units to process interlocking logics, and terminals (i.e., object controllers) tointerface with physical devices.
The cycles of logic units are divided into segments, and thelogic units process the segments independently. The allocation isscheduled by controllers, and the allocation tables and interlocking
tables are shared by controllers. Controllers also monitor the healthof logic units. Supervision controllers are provided to back up the
failure of controllers. The number of the logic units can be increased
as required, i.e., our proposal is scalable.
We also proposed asynchronous interlocking logics to reduce
the requirements of delay based on the three-value logics considering an “undetermined” state.
Our verification is currently limited to a simulation. However,
our concept is not only applicable to interlocking devices, but also
to a wide range of railway signalling systems. Our plan is to realize
the interlocking function of a new train control system in the way
we proposed in this paper.
The final form of our concept will be realized using COTS
CPU, which is not practical for now. In this case, the logic units will
be virtualized on cloud computing environments enabling more
flexibility. Currently, our focus will be studying how to achieve failsafe mode using COTS CPU.

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J-RAIL 2017, S2-5-2, Dec. 2017 (in Japanese).
[2]	Okutani, T., Shimazoe, T., “Development of Centralized
Interlocking System for Railway Signalling and its Evaluation,”Transactions of IEE Japan, Vol. 119-D, pp. 1307-1314, Nov
1999 (in Japanese. Extend Summary in English available).
[3]	Nakano, H., 「加古川線CTC化（線区集中連動方式）」,
鉄道と電気技術, Vol. 15, No. 11, 2004 (in Japanese).
[4]	Ono, S., 「九州新幹線（博多・新八代間）集中連動方式の開発と実用化」, 鉄道と電気技術, Vol. 24, No. 8, pp. 1116, 2013 (in Japanese).
[5]	Nishiyama, J., Kunifuji, T., 「ネットワーク信号制御システ
ム―システム概要とモニターラン試験について―」, 鉄道と電気技術, Vol. 17, No. 4, 2006 (in Japanese).
[6]	Kaldenbach, A., “Die Digitale LST bei der DB Netz AG Eine
Einführung in die Digitale Stellwerkstechnik,” Fachvortrag BF
Bahnnen, 2019 (in German).
[7]	Siemens, Trackguard® Simis Interlocking as a Service (SIaaS),
https://www.mobility.siemens.com/ch/en/portfolio/rail/automation/interlocking-systems.html, 2018 (visited on 17/8/2020).
[8]	Takashi, T., Fukumoto, S., “A Fundamental FMEA of Railway
Signaling Systems Using Majority Voting over Networks,” IEICE
Technical Report, Vol. 120, No. 288, DC2020-67, pp. 43-48, 2020
(in Japanese).
[9]	Holzman, G. J., The SPIN Model Checker, Addison-Wesley,
2004.

Authors
Natsuki TERADA, Dr.Eng.

Senior Chief Researcher, Signalling Systems
Laboratory, Signalling and Operation
Systems Technology Division
Research Areas: Signalling Systems, Track
Circuits, Automatic Train Control System

Takashi TOYAMA

Assistant Senior Researcher, Signalling
Systems Laboratory , Signalling andOperation Systems Technology Division
Research Areas: Signalling Systems, Track
Circuits, Automatic Train Control System

Shunsuke SHIOMI

Senior Chief Researcher, Head of Signalling
Systems Laboratory, Signalling andOperation Systems Technology Division
Research Areas: Signalling Systems, Point
MachineQR of RTRI, Vol. 65, No. 3, Aug. 2024

161

PAPER

Design Method for Corrosion of Reinforcing Bars in Concrete Structures
by Water Penetration and Carbonation Progress
Shuntaro TODOROKI
Concrete Structures Laboratory, Structures Technology Division
Tetsuya ISHIDA
Department of Civil Engineering, The University of Tokyo
Hiroshi UEDA
Materials Technology Division
Toshiya TADOKORO
Concrete Structures Laboratory, Structures Technology Division
The effect of water and carbonation on the corrosion of reinforcing bars in concrete was investigated byfield surveys on members with different levels of supplied water. In addition, a design method to suppress
corrosion of reinforcing bars due to water penetration was verified by comparing the cover depth where
spalling of concrete occurred and the design cover depth determined by taking carbonation into account.
Even if the un-carbonation depth (= cover depth―carbonation depth) is less than 10 mm, when water is not
supplied, the probability of spalling is lower and the corrosion rate of reinforcing bars is slower, so it isimportant to consider the effect of supplied water on corrosion of reinforcing bars. It was also confirmed thatthe design method based on corrosion of reinforcing bars due to water penetration is applicable.
Key words: r ailway concrete structures, corrosion of reinforcing bars, supplied water, carbonation of
concrete
1. Introduction
As the corrosion of reinforcing bars in concrete structures progresses, it may cause a spalling of the concrete due to corrosion expansion or a decrease in the load bearing capacity due to a lack of
the cross section of reinforcing bars, and so on. Therefore, suppressing the progression of corrosion is important to ensure the durabilityof concrete structures.
Immediately after construction, reinforcing bars in concrete,that remains alkaline, are less likely to corrode. However, as theconcrete around the reinforcing bars becomes neutralized by carbon
dioxide penetrating through the concrete surface, corrosion becomes more likely. For this reason, carbonation of concrete has traditionally been used as an indicator to prevent corrosion of reinforcing bars. For example, in design, the cover depth (distance from theconcrete surface to the reinforcing bar surface) has been set to prevent the area around the reinforcing bars from becoming neutralized
during the design lifetime. On the other hand, oxygen and water are
also essential for reinforcing bars to corrode.
In the design method that uses carbonation as an index (referred
to as “study on carbonation” in [1] (see Appendix)), when the concrete surface is dry without water supply from rain, etc., the carbonation depth is calculated to be large (Fig. 1), and therefore it isjudged that corrosion and spalling are likely to occur. On the other
hand, in real field situations, it has been pointed out that, althoughcarbonation is certainly less likely to progress in areas that are exposed to water and get wet, contrary to the design, more spalling due
to corrosion occurs [2] (Fig. 2). In other words, using carbonation as
an indicator may result in a response that contradicts what actuallyoccurs.
Consequently, to clarify the effect of water on corrosion, which
is known about so far mainly based on experience, data related to162

corrosion, such as the rate of corrosion, was obtained and estimatedfrom a field survey on members with different levels of water supply(Chapter 2), and the effects of water and carbonation on corrosion
were analyzed (Chapter 3). In addition, as a design method that is
consistent with the real situation, rather than carbonation, we aim to
introduce a “study on the corrosion of reinforcing bars due to water
penetration” that directly evaluates the corrosion of reinforcing bars
and takes into account the effect of water. The applicability of the“study on the corrosion of bars due to water penetration” was verified by comparing the cover depth of areas where spalling occurred
and the design cover depth determined from the “study on carbonation” and the “study on the corrosion of reinforcing bars due towater penetration” (Chapter 4).

Fig. 1 Supplied water and calculated value of carbonation depth
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2. Survey overview
2.1 Target of survey
Table 1 shows an overview of the members targeted for surveys. The target members are outdoor structures, exposed to theoutside air and made of reinforced concrete. These are the outside ofcolumns and handrail walls of rigid frame viaducts, which are generally exposed to rainwater (referred to in this paper as “presence of
supplied water”), and the bottom of the intermediate slabs of a rigid
frame viaduct and the bottom of the main beams of T shaped girders,which are comparatively less likely to be exposed to water (referred
to in this paper as “absence of supplied water”). In addition, waterleakage marks due to poor drainage were found on the outside of thecolumns within a range of 0.5 m to 1.5 m from the bottom of thehorizontal beam and on the bottom of the intermediate slab within arange of 4.4 m to 5.0 m from the side of the longitudinal beam
(Fig. 3). Details of shapes and reinforcing bar arrangements of themembers are given in [4]. Viaducts A to D in [4] and A to D in thispaper are the same.
Furthermore, the target structures are located in areas that are
not affected by freezing and thawing or airborne salt, and no deterioration in concrete quality due to poor construction such as cold
joints or rock pockets was observed. The chloride ion concentrationin the concrete which derived from materials such as the use of sea
sand was less than 0.4 kg/m3, and the effect of chloride ions on corrosion is small.
2.2 Method of survey
2.2.1 How to obtain data
As shown in Fig. 4, a mesh is created directly above the outermost reinforcing bar (the hoop reinforcing bars in Fig. 4). Regarding
each mesh unit as one exposed test specimen, data were obtained
and analyzed from several exposed test specimens with different
cover depths, carbonation depths, and presence or absence of spalling. Cover depths were the measured values for the meshes on thesurvey line and the interpolated values for other meshes from themeasured values based on previous research [5]. Carbonation
depths were the measured values obtained in the vicinities of theTable 1

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Fig. 2 Supplied water and spalling of concrete [3]meshes.
Cover depths were measured using an electromagnetic induction method. The carbonation depth was the average value of distances from the concrete surface to the coloring point at four locations (top, bottom, left and right) in the holes, after spraying a 1%
phenolphthalein solution into drill holes with a diameter of approximately 24 mm.
2.2.2 Method for estimating the corrosion rate of reinforcing
bars
Figure 5 shows the method for estimating the corrosion rate ofreinforcing bars. Visual inspection (Fig. 5(i)) and spalling prediction(Fig. 5(iii)) were carried out for each mesh shown in Fig. 4. Then,the corrosion rate is calculated (Fig. 5(v)) so that the patterns formedby the spalling areas and sound areas (Fig. 5(ii) and 5(iv)) match. If
the age of each mesh at the time of spalling can be determined, thecorrosion rate can be calculated for each mesh using a spalling prediction model. However, since the age at the time of spalling is unknown, we decided to estimate the corrosion rate based on the surface pattern formed by spalling areas and sound areas.
The spalling prediction model requires settings for the corrosion rate, and the corrosion depth when spalling occurs. The corrosion rate was assumed to be constant, similar to the corrosion rate

Outline of members targeted for surveys

163

Fig. 4 Method of data
Fig. 3 Appearance of outer of columns and acquisition bottom
of intermediate slabs

Fig. 5

Method for estimating the corrosion rate of reinforcing bars

equation used in the “study on corrosion of reinforcing bars due towater penetration” verified in Chapter 4. For the equation of thecorrosion depth Δrsp when spalling occurs, an equation was used thattargets a cover of 30 mm or less, which is similar to the spalling locations in this survey [6].
3. Effect of water and carbonation on corrosion
3.1 Cover depth, un-carbonation depth, and supplied water inpresence/absence of spalling
Figure 6 shows the relationship between the cover depth at164

spalling areas or sound areas and the un-carbonation depth (the value obtained by subtracting the carbonation depth from the cover
depth). At the bottom of the main beam (d), areas where repairs
were thought to have been carried out for deterioration caused bycorrosion of reinforcing bars, such as cross-sectional repairs, areshown separately from spalling.
Spalling occurred on all members with an un-carbonation depthof less than 10 mm. The maximum un-carbonation depth at whichspalling occurred was 1 to 10 mm on the outside of columns, theoutside of handrail walls, and the bottom of intermediate slabs in thepresence of supplied water. Whereas it was less at the bottom of intermediate slabs and the bottom of main beams in the absence of
supplied water, at −5 mm and 3mm respectively. Even if the cover
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Fig. 6

Cover depth and un-carbonation depth in presence/absence of spalling

depth and un-carbonation depth were small, there were many soundareas on the bottom of intermediate slabs and main beams in theabsence of supplied water compared to the outside of columns andhandrail walls in the presence of supplied water.
3.2 Probability of spalling at different levels of supplied water
Figure 7 shows the relationship between cover depth or un-carbonation depth and the probability of spalling. The probability ofspalling was calculated by dividing the number of meshes in thespalling area within each 5 mm classification (0 mm to 5mm, 5 mm
to 10 mm, follows in the same way) by the total number of meshes
in the sound and spalling areas. The repaired areas on the bottom of
the main beam were categorized as spalling areas. Focusing on the
cover depth, the shallower the cover depth, the higher the probability of spalling. Spalling tended to occur when the cover was less
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than 30 mm at the time of the surveys, regardless of whether water
was supplied or not.
Focusing on the un-carbonation depth, the probability of spalling increases when the un-carbonation depth is less than 10 mm on
the outside of columns and handrail walls in the presence of supplied water. On the bottom of the intermediate slab and on the bottom of the main beam in the absence of supplied water, when theun-carbonation depth is less than 10 mm, the probability of spallingincreases as with the presence of supplied water. A characteristicfeature is that the probability of spalling in the absence of supplied
water is lower than in the presence of supplied water, even when theun-carbonation depth is less than 10 mm. These results were obtained at different parts of different structures, and the qualities ofmaterials and environments are not the same, so they cannot beeasily compared. However, the same results were obtained in real
surveys of members with and without supplied water in the same165

Fig. 7

Cover depth, un-carbonation depth and probability of spalling

structure [7].
Comparing the probability of spalling on the bottom of the intermediate slab at the same cover depth with and without waterleakage marks, it is found that the probability of spalling is higher inareas where water leakage marks were observed.
3.3 Relationship between presence/absence of supplied water,
un-carbonation depth, and corrosion rate
Figure 8 shows the relationship between the presence and absence of supplied water, the un-carbonation depth, and the corrosion
rate. The average corrosion rate of the outside of handrail walls andcolumns in the presence of supplied water is 0.9 × 10−3 mm/year (0.4
× 10−3 to 1.4 × 10−3 mm/year), and the average corrosion rate of thebottom of main beams and intermediate slabs in the absence of supplied water was 0.7 × 10−3 mm/year (0.3 × 10−3 to 1.0 × 10−3 mm/year). The members surveyed in this paper were those where spalling had occurred and cover depth was less than 30 mm. Therefore,
even members which, on visual inspection, appeared to have nosupplied water, may in fact have been in conditions where water
could be easily supplied by rain blow-in or the effect of moistureabsorption and condensation. Nevertheless, the corrosion rate in theabsence of supplied water was on average 0.8 times slower than thatin the presence of supplied water. Since there is a possibility thatwater may be supplied from these sources even in those members
where it is thought that there will be no supplied water, it is considered a safe design judgement to set the corrosion rate of the members in the absence of supplied water to be the same as that in thepresence of supplied water.
The corrosion rate of reinforcing bars on the outside of thecolumns and the intermediate slabs where water leakage marks wereobserved due to poor drainage, was faster than average corrosion
rates of members in the presence and absence of supplied water, at
0.8 to 1.8 × 10−3 mm/year. In general, carbonation does not proceed
easily in members that are easily exposed to water. But in members
166

showing water leakage marks due to poor drainage, carbonation
progress before poor drainage occurs, and water is supplied due topoor drainage. As a result of this, the corrosion rate may have increased.
From Sections 3.1 to 3.3, even when the un-carbonation depth
is less than 10 mm, the probability of spalling is lower and the corrosion rate is slower in the absence of supplied water than those in
the presence of supplied water. So, it is important to consider theeffect of water on corrosion of reinforcing bars.
4. Applicability of “study on the corrosion of reinforcing bars
due to water penetration”
4.1 Cover depth in spalling areas and design cover depth determined by the “study on corrosion of reinforcing bars due towater penetration”
Figure 9 shows the cover depth of the spalling areas, excluding
areas displaying marks of water leakage due to poor drainage. Since
it is unknown how many years a building had been in service when
the spalling occurred, the age at the time of the surveys was plotted.
In addition, based on the “study on the corrosion of reinforcing bars
due to water penetration” (“verification of the corrosion depth ofsteel materials” shown in the Japan Society of Civil Engineers’Standard Specifications for Concrete Structures (Design Edition)[8]), the corrosion depth obtained by multiplying the corrosion rate
sdy by the design life t is taken as the design value (1), the limit value(2) is determined, and the design cover depth when sd /slim is 1.0 isshown in the figure. This equation is formulated on the assumptionthat water supplied by rainfall is the main cause of corrosion, andtakes into account corrosion progress due to repeated dry and wet
cycles.

sd = γw × sdy × t
(1)QR of RTRI, Vol. 65, No. 3, Aug. 2024

Fig. 8Un-carbonation depth and corrosion rate in presence/absence of supplied water

Fig. 9 Cover depth in spalling areas and design cover depth determined by “study on the corrosion of reinforcing bars
due to water penetration”

slim = 3.81 × 10-4 × c
(2)if c > 35 mm，slim = 1.33 × 10-2Here,
sd : design value of corrosion depth of reinforcing bars (mm)slim : limit value of corrosion depth of reinforcing bars (mm)γw : safety factor considering variation in design value sd, generalQR of RTRI, Vol. 65, No. 3, Aug. 2024

ly 1.15.
sdy : design value of corrosion depth per year (referred to as corrosion rate in this paper) (mm/year)		 sdy = 1.9 × 10−4 × exp (−0.068 × (c − Δce)2/qd2)c: design cover depth (mm)Δce : construction error of cover depth (mm). 5 mm for intermediate slab, 10 mm for others167

: design value of water penetration rate coefficient of concrete(mm/ hour)		qd = γc × qk
γc : safety coefficient for concrete, generally 1.3.
qk : characteristic value of water penetration rate coefficient of
concrete (mm/ hour)
qk = 31.25 × (W/B)2
W/B : water to binder ratio. The minimum and maximum value ofthe estimated value from the carbonation depth of the spallingarea (calculated by *** in Table 1), with an upper limit of75%.
t: design life (year). In Fig. 9, time in-service.
qd

As can be seen from the figure, the cover in the spalling areas is
generally smaller than the design cover determined by the “study on
the corrosion of reinforcing bars due to water penetration.” On theoutside of the columns, spalling occurred in some areas with a cover
depth of 20 mm to 30 mm, which was larger than the design cover
depth determined by the “study on the corrosion of reinforcing bars
due to water penetration.” The estimated W/B of the outside of thiscolumn is large. So, it is possible that a lower quality concrete wasused, which differs from the current type found in new structures.
Despite this, the rate of spalling at a cover depth of 20 mm to 30 mm
is small, less than 5%.
4.2 Design cover depth determined by “study on carbonation”
and “study on the corrosion of reinforcing bars due to water
penetration”
Figure 10 shows a comparison of the design cover determinedby the “study on carbonation” [1] (see Appendix) and the “study on
the corrosion of reinforcing bars due to water penetration” (see Section 4.1). The design cover determined by a study on corrosion ofsteel due to water penetration is 30 mm or more (W/B = 40% to60%). This is larger than that determined by the “study on carbonation” in the presence of supplied water (βe = 1.0). The design coverdetermined by the “study on the corrosion of reinforcing bars due towater penetration” is 30 mm or more (W/B = 40% to 60%). This islarger than that determined by the “study on carbonation” in thepresence of supplied water. On the other hand, the design cover by
the “study on carbonation” is determined so that the un-carbonation
depth would be more than 10 mm during the design life. So, if thedesign cover determined by the “study on the corrosion of reinforcing bars due to water penetration” is ensured, the un-carbonation
depth during the design life remains more than 10 mm.
If the un-carbonation depth is more than 10 mm, the pH aroundthe reinforcing bars has not decreased, and it is thought that thecorrosion rate will not increase due to a decrease in pH around thereinforcing bars [9]. Therefore, when determining a design coverbased on the “study on the corrosion of reinforcing bars due to water
penetration,” it is thought that the design cover can be determined inconsideration of the effect of carbonation.
The design cover determined by the “study on carbonation” inthe absence of supplied water is larger at W/B = 45% or more thanthe design cover determined by the “study on the corrosion of reinforcing bars due to water penetration.” According to Chapter 3, in
the absence of supplied water, the probability of spalling is lower
and the corrosion rate is slower than in the presence of supplied
water. Therefore, it makes sense that the design cover depth in theabsence of supplied water is smaller than that in the presence of
supplied water. In the design, even for members that are not supposed to be exposed to rain, the design cover depth must be determined in consideration of the fact that water may be supplied due to,for example, water from facilities under rigid frame viaducts, rain
blowing in, water penetration from other parts, moisture absorption,
dew condensation, and so on.
5. Conclusion
The effect of water and carbonation on the corrosion of reinforcing bars in concrete was investigated by field surveys on members under different levels of supplied water. In addition, the applicability of the “study on the corrosion of reinforcing bars due towater penetration” was verified by comparing the cover depth where
spalling of concrete occurred and the design cover depth determinedby the “study on carbonation.”(1) It is important to consider the effect of supplied water on corrosion of reinforcing bars, because even when the remaining
un-carbonation depth is less than 10 mm, if there is no water
exposure, the probability of spalling is lower and the corrosion
rate of reinforcing bars is slower than that in the presence of
supplied water.
(2) It was confirmed that the cover depth in the areas where spallingFig. 10 Design cover depth determined by “study on carbonation” and “study on the corrosion of reinforcing bars due
to water penetration”
168

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had occurred was generally smaller than the design cover depth
determined by the “study on the corrosion of reinforcing bars
due to water penetration.” It was also confirmed that if the design cover depth determined by the “study on the corrosion ofreinforcing bars due to water penetration” with a design life of
100 years is ensured, the “study on carbonation” will also besatisfied. Therefore, as a design method for corrosion of reinforcing bars due to water penetration and concrete carbonation,
it is considered that it is possible to determine the design cover
depth using the “study on the corrosion of reinforcing bars due
to water penetration” instead of the “study on carbonation.”
Appendix “study on carbonation”
In the “study on carbonation” [1], the design cover depth is set sothat the remaining un-carbonation depth is at least 10mm (yg ≤ ylim).
Figure 10 shows the design cover depth when yg / ylim is 1.0.

yg = γcb × αd × t
(A1)ylim = c − ∆ce − ck
(A2)
Here,
yg : estimated value of carbonation depth of concrete (mm)ylim : limited value of carbonation depth of concrete (mm)γcb : safety factor considering variation in estimated value yd, generally 1.15.
αd : estimated value of carbonation rate coefficient (mm/ year )		
αd = αk × βe × γc
αk : characteristic value of carbonation rate coefficient (mm/ year )		αk = γp × αp
γp : coefficient related to the accuracy of αp. In general, 1.1 whenusing the estimation equation αp listed below.
αp : predicted value of carbonation rate coefficient (mm/ year )		
αp = −3.57 + 9.0 × W/B
W/B : water to binder ratio
βe : coefficient related to the degree of the effect on the environment when members tend to be wet, 1.0 and dry, 1.6.
γc : safety coefficient for concrete. In general, 1.0. In members
where quality of concrete may deteriorate due to bleeding,
1.3.
t: design life (year)c: design cover depth (mm)Δce : construction error of cover depth (mm)ck : un-carbonation depth (mm). In general, 10mm
References[1]	Railway Technical Research Institute, Design Standards forRailway Structures and Commentary (Concrete Structure),
Maruzen co., Ltd, Tokyo, pp. 222-233, 2004 (in Japanese).
[2]	Ishibashi, T., Furuya, T., Hamazaki, N., and Suzuki, H.,“Investigation of falling on concrete fragments from RC
structures,” Journal of Materials, Concrete Structures andPavements, No. 711/V-56, pp. 125-134, 2002.8 (in Japanese).
[3]	Ueda, H., Iijima, T., and Suzuki, H., “Investigating the effect ofwater penetration into concrete structures,” RRR, No. 71, No. 6,
pp. 20-23, 2014 (in Japanese).
[4]	Todoroki, S., Ishida, T., Tadokoro, T., and Ueda, H., “Effect ofwater migration and carbonation progress on rebar corrosion
rate in concrete,” Journal of Japan Society of Civil Engineers,
Ser. E2 (Materials and Concrete Structures), Vol. 75, No. 4, pp.
226-238, 2019 (in Japanese).
[5]	Matsushita, M., Todoroki, S., Tadokoro, T, and Ishida, T.,“Estimation method of cover depth for vertical members of RC
structures,” Proceedings of the Japan Concrete Institute, Vol.
40, No. 2, pp. 1303-1308, 2018 (in Japanese).
[6]	Kadono, T., Todoroki, S., Watanabe, K., and Tadokoro, T.,“Analytical study on rebar corrosion depth threshold initiatingcracks and spalling of cover concrete affected by rebar
placement of RC members,” Concrete Structure Scenarios,
JSMS, Vol. 18, pp. 161-166, 2018 (in Japanese).
[7]	Tabata, K., Ishibashi, N., Todoroki, S., and Tadokoro, T.,“Effects of rain exposure and concrete quality on spalling of
cover concrete based on investigation of railway RC viaducts,”
Proceedings of the Annual Meeting of Japan Society of Civil
Engineers, Vol. 75, V-168, 2020 (in Japanese).
[8]	Japan Society of Civil Engineers, Standard Specifications forConcrete Structures (Design Edition) established in 2017, 2018
(in Japanese).
[9]	Todoroki, S., Ueda, H., Ishida, T., and Tadokoro, T., “Effects ofsupplied water and PH around reinforcing bars on the spalling
occurring due to corrosion,” Proceedings of the Japan Concrete
Institute, Vol. 43, No. 1, pp. 467-472, 2021 (in Japanese).

Authors
Shuntaro TODOROKI, Dr.Eng.

Senior Researcher, Concrete Structures
Laboratory, Structures Technology Division
Research Areas: Design Methods for Railway
Concrete Structures
Tetsuya ISHIDA, Ph.D.

Professor, Department of Civil Engineering,
The University of Tokyo
Research Areas: Multi-scale Modeling of
Cementious Materials and Structures

QR of RTRI, Vol. 65, No. 3, Aug. 2024

Hiroshi UEDA, Dr.Eng.

Director, Head of Materials Technology
Division
Research Areas: Durability of Concrete andRelated Materials.
Toshiya TADOKORO, Dr.Eng.

Senior Chief Researcher, Head of Concrete
Structures Laboratory, Structure Technology
Division
Research Areas: Design Methods for Railway
Concrete Structures

169

PAPER

Development of Automatic Generation of Maintenance Worker Schedule Using Tabu Search
Tatsuya KOKUBO
Satoshi KATO
Taichi NAKAHIGASHI
Transport Operation Systems Laboratory, Signalling and Operation Systems Technology Division
Maintenance worker schedules are daily schedules for teams performing inspection and maintenancework such as cleaning of rolling stock during turnaround operations at terminal stations. Since theseschedules vary from day to day according to changes in rolling stock operations, they have to be created foreach day. We have therefore proposed a method for automatically generating maintenance worker schedules
using tabu search. In this paper, to confirm the effectiveness of the proposed method, we compared an actual
schedule with schedules generated using proposed method. The results indicated that the proposed method
could generate a practical solution within 3 minutes.
Key words: maintenance worker scheduling, rolling stock scheduling, metaheuristics, tabu search, mixed
integer programming
1. Introduction
When trains providing high-end services turnaround at a terminal station, maintenance such as cleaning and inspection of rollingstock is required. Maintenance is carried out by teams of workers(referred to as “a set”), and the daily maintenance work plan foreach set is shown in a maintenance worker schedule. The maintenance worker schedule is prepared each day in accordance with train
schedules and rolling stock schedules that vary from day to day.
Currently, maintenance worker schedules are prepared manually byskilled planners. However, because of multiple constraints on theworkload of maintenance workers, it takes several hours to prepare
one day’s schedule, which is labor intensive. This has created a needfor automatic generation of the maintenance worker schedule for
improving labor-saving.
There has not been reported existing studies on the automatic
generation of the maintenance worker schedule. The maintenanceworker scheduling problem is similar to a shift scheduling problem[1], a flow-shop scheduling problem, a job-shop scheduling problem[2], and a crew scheduling problem [3]. The shift scheduling problem and the crew scheduling problem basically minimize the number of staff. The flow-shop scheduling problem and the job-shop
scheduling problem generally minimize the time required for all
work, since the order in which each job is processed is predetermined. However, it is considered difficult to apply the existingstudies to the problem of maintenance worker scheduling, because
this problem has a given number of sets but no predetermined orderof maintenance tasks. Moreover, it is necessary to consider specificconditions such as differences in the number of maintenance tasks
carried out by each set, and different time intervals required forteams moving track to track between maintenance interventions.
For practical purposes, it is important for the automatic generation of maintenance worker schedules to take less than 3 minutes tocalculate, have a small number of parameters, and output the same
results for the same input data. In addition, depending on the input
data, there may not be a feasible solution that satisfies all the constraints. After analyzing actual maintenance worker schedules (referred to as “actual schedules”) we identified two types of constraints: high priority non-relaxable constraints and low priority relaxable constraints.
Based on these requirements, we developed a generation method using tabu search (referred to as “TS”), a metaheuristics methodthat can automatically generate maintenance worker schedules in 3
170

minutes (referred to as “proposed method”) [4, 5, 6]. To confirm theeffectiveness of the proposed method, we compared it with actual
schedules and maintenance worker schedules generated by mixed
integer programming (referred to as “MIP”) [6].
2. Overview of maintenance worker schedulingThis chapter provides on overview of maintenance worker
scheduling and definitions of terms. The train that needs maintenance is given, and a start time of each maintenance intervention isdetermined by an arrival time of the train. The number of sets per
day is predetermined, and each set is classified (referred to as“group”) according to the time of day (AM/PM).
Figure 1 shows an example of the input data for generating themaintenance worker schedule. 14 trains are shown in Fig. 1, with 2groups, 4 sets, and maintenance from 2M to 28M. Figure 1 shows
the maintenance schedule for one day for each “track No.”. “2M”
etc. is a train number, the light blue time zone indicates maintenanceof the corresponding train, and the track number and work time are
given. The bottom of Fig. 1 shows the available and unavailable
time for each set indicated by “group No.” and each set indicated by“set No.”. “B” and “M” are breaks and meetings time (referred to as“fixed time”), and the start and end times are given. Fixed time isdefined only between maintenance interventions, and one or more
fixed times are defined for each set. “S” is the preparation time after
start time, “F” is the preparation time before finish time, “I” is the
preparation time before fixed time, and “R” is the preparation timeafter fixed time, and each required time is given. Excluding these
preparation time and fixed time, maintenance are performed for all
trains.
Figure 2 shows an example of the maintenance worker schedule based on the input data in Fig. 1. The planner assigns each maintenance intervention to one of the sets in Fig. 1, excluding the
preparation time and fixed time. “t” is an interval required for moving from one track to the next between maintenance interventions(referred to as “track interval”). In addition, when a certain amountof time cannot be ensured between the end time of the maintenancework or the end time of track interval and the start time of the next
maintenance work (referred to as “continuous work”), the additionaltime described in “a” must be ensured. The additional time is added
after the track interval to the next maintenance work, and corresponds to a restroom break, etc.
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Fig. 1

Fig. 2

An example of input data for generating maintenance worker schedule

An example of a maintenance worker schedule based on input data in Fig. 1

Fig. 3 An example of a graph with candidate nodes andarcs expressing a maintenance worker schedule
3. Modeling of a maintenance worker scheduling problem
3.1 Data Structure
In this paper, the maintenance worker schedule is represented
by applying a graph with nodes and arcs. Figure 3 shows an exampleof the graph expressing the maintenance worker schedule. There are
four types of nodes: “maintenance work node” corresponding toeach maintenance intervention, “start node” corresponding to each
set and indicating the start of work, “finish node” indicating thefinish of work, and “fixed work node” corresponding to each fixed
work in each set. In addition, “start time” and “end time” are definedfor each node. The maintenance work node and fixed work node are
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defined by the start time and end time of the corresponding maintenance work and fixed work. The start time of the start node is defined as the corresponding start time of each set. The end time of theend node is defined as corresponding end time of each set. In addition, the start and end times of the start and end nodes are defined as
the same time.
With the exceptions noted below, for any two nodes, if the start
time of one is equal to or later than the end time of the other, thelatter node is extended to the former. The exceptions are: arcs fromany node to the start node, arcs from the finish node to any node,arcs between finish nodes, arcs between different sets of fixed work
nodes, arcs between the start node and fixed work nodes, and arcs
between the finish node and fixed work nodes. Each arc has time
information calculated as the start time of the destination node minus the end time of the source node. In this paper, the arcs are defined even in the case where the track interval time, each preparation
time, or the additional time are insufficient, so that the graph canviolate the low priority for relaxable constraints in order to satisfy
the high priority for non-relaxable constraints.
3.2 Constraints
Constraints can be divided into three major types: “constraints
related to assignment,” “constraints related to number of maintenance interventions,” and “constraints related to time.” The constraints are shown below.
(1) Constraints related to assignment
Constraint 1: Maintenance work assignment
171

Only one set is assigned to each maintenance work.
Constraint 2: Maintenance intervention order of assignment The first maintenance intervention is assigned to the set withthe earliest start time and fixed work end time. The last maintenance intervention is assigned to the set with the last start
time and fixed work end time.
(2) Constraint related to the number of maintenance interventions
Constraint 3: Upper limit of the number of maintenance works The number of maintenance interventions assigned to one set
in a day is within the predefined threshold.
Constraint 4: U pper limit on the difference in the number ofmaintenance interventions per set within thegroup The difference in the number of maintenance interventions
per set within the group is within the predefined threshold.
Constraint 5: U pper limit on the difference in the number ofmaintenance interventions between groups The difference in the number of maintenance interventions
for each set between groups is within the predefined threshold.
(3) Constraints related to time
Constraint 6: Track interval time
 If movement between tracks is required between maintenance interventions, the required track interval time to allow
for movement is ensured.
Constraint 7: P reparation time after start time and before finishtime After start time of each set and before finish time of each set,
the required preparation time is ensured.
Constraint 8: P reparation time for interruption and resumption Before fixed work of each set and after fixed work of eachset, the required preparation time is ensured.
Constraint 9: Additional time
 Additional time is ensured after track interval time for moving between tracks from one continuous maintenance intervention to the next. Specifically, if the interval between theend time of the track interval time and the start time of thenext maintenance intervention is less than CX minutes and CY
consecutive maintenance interventions are performed, additional time CZ minutes are ensured after the next maintenance intervention. There are also multiple combinations of
CX, CY, and CZ.
Among these constraints, constraints 1 to 5 are high priority for
non-relaxable constraints, constraints 6 to 9 are low priority for relaxable constraints. We analyzed actual schedules and found thatsatisfying high priority constraints is important from a practicalpoint of view.
3.3 Objective function
In this problem, it is necessary to assign maintenance considering the equalization and reduction of the workload of maintenanceworkers. In addition, the number of sets and the start time and finish
time of each set (available working time period) are given. Therefore, in this paper, evaluation value terms of an objective function
are the variance of the number of maintenance interventions in each
set for the purpose of workload equalization, the total track interval
time and additional time in all sets for the purpose of workload reduction. Furthermore, the objective function value is the sum ofeach term of the objective function multiplied by a weighting coefficient, and minimized.
As discussed in Chapter 1, depending on the input data, there is172

a possibility that a feasible solution that satisfies all the constraints
may not exist. For practical purposes, even in such cases, it is desirable to return a maintenance worker schedule such that high priority
constraints are satisfied, and low priority constraints are violated,rather than judging it to be infeasible. Therefore, in order to output
maintenance worker schedule in practice, a penalty is defined basedon the amount of violation calculated from the predefined thresholdof each constraint and other factors. The penalty that is multipliedby the weighting coefficient is added as a penalty term to the objective function. The penalty for constraint 1 is the number of unassigned maintenance works. The penalty for constraint 2 is the number of combinations that violate the maintenance work order. The
penalty for constraints 3 to 5 and 7 to 9 is the sum of the squares ofviolations from predefined thresholds for each constraint, in order toprevent the large violations from predefined thresholds for eachconstraint. The penalty for constraints 6 is the sum of the fourth
power of the violation from the predefined threshold. Moreover,each penalty is multiplied by the weighting coefficient to consider
the priority of constraints. Specifically, the weighting coefficient ofhigh priority constraint 1 to 5 are determined to be large values. The
objective function is shown below:9

(1)min 1 1 + 2 2 + 3 3 +=1

t1: Variance of the number of maintenance in each set
t2: Total track interval time
t3: Total additional time
w1, w2, w3: Weighting coefficient for each term
(w1 + w2 + w3 = 1)
en: Penalty for constraint n (n = 1, . . ., 9)
pn: Weighting coefficient for each penalty term

4. Maintenance worker scheduling problem using tabu search
4.1 Tabu search
Tabu search (TS) is a metaheuristics technique proposed byFred Glover, a general method for solving combinatorial optimization problems [7]. TS performs the search using a tabu list (TL) thatsaves the most recently searched solutions. In a TL, the number ofsolutions to be saved is determined by the pre-defined TL length(TLL), and no transitions to solutions contained in the TL are allowed. TS generalizes a local search method and improves solutions
by generating neighborhood solutions from the current solution andmoving to the best neighborhood solution, which is not tabu. Although the local search method must stop searching if all the neighborhood solutions are not superior to the current solution, TS cancontinue searching by moving to the best neighborhood solution,
which is not tabu even if the best solution is not superior to the current solution. In addition, there is no guarantee that TS will always
generate an optimal solution due to the nature of the metaheuristics.
In general, TS is a widely used method in many problems because it
is known to be able to generate good quality solutions to large-scale
problems in a short computation time.
The aspiration level, which is known to enable efficient searches in general, is applied to the proposed method [7]. The aspirationlevel is that the point with the better total objective function value
among the candidates for the neighborhood solutions at the next
point is adopted even if it is tabu.
The procedure for TS in the proposed method is shown below.
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Step. 1 Generate an initial solution (see Section 4.2). The initialsolution is used as a tentative solution. The number ofsearches iter = 1.
Step. 2 Generate neighborhood solutions from the tentative solution(see Section 4.3). However, if maintenance to be exchanged
by generating the neighborhood solutions is included in the
TL, or if the objective function value is higher than a bestsolution, it is not generated as a neighborhood solution.
Step. 3 Among the neighborhood solutions, the solution with thebest objective function value is selected and used as the tentative solution in the next iteration. Maintenance that has
been exchanged by the generating neighborhood solution are
put in the TL.
Step. 4 I f iter reaches the preset itermax, the best solution is outputted,
and the process is terminated. Otherwise, set iter = iter + 1
and go back to Step. 2.
4.2 Generation of an initial solution
In generation of the initial solution process, a “current node” isupdated for each set. The current node is defined the node with theslowest end time among the nodes assigned to each set. The algorithm for generating an initial solution is shown below:
Step. 1.1 Assign the corresponding start node to every set. Update
the current node as the start node of every set.
Step. 1.2 Select the set among all sets with the earliest end time of
the current node. However, the set whose current node isthe end node is not selected. Among the maintenance work
nodes connected to the arc from the current node, themaintenance node that is not assigned to any set and has
the shortest time between the current node and the maintenance node is selected. If it cannot be extracted, go to Step.
1.5.
Step. 1.3 If the end time of the extracted maintenance work node
exceeds the start time of one of the unassigned fixed work
nodes corresponding to the set selected in Step 1.2, go to
Step 1.4. If it exceeds the start time of the end node corresponding to the set selected in Step 1.2, go to Step 1.5.
Otherwise, assign the extracted maintenance work node,
update the current node, and go to Step 1.6.
Step. 1.4 Assign the fixed work node, update the current node, andgo to Step 1.6.
Step. 1.5 Assign the end node and update the current node.
Step. 1.6	When all sets of current nodes have become end nodes,
output the initial solution, calculate the total objectivefunction value based on (1), and terminate the process.
Otherwise, go back to Step. 1.2.
4.3 Generation of neighborhood solutions
This paper proposes three generating neighborhood solutions
to improve all evaluation values and to resolve all constraint penalties except constraint 1. The generating neighborhood solution 1
contributes to the improvement of each evaluation value of the objective function related to time and the penalty related to time. On
the other hand, it does not contribute to the improvement of each
evaluation value and penalties related to distribute the number ofmaintenance works, since the number of maintenance to be improved is not exchanged. The generating neighborhood solution 2
and 3 contribute to the improvement of all evaluation values andpenalty except constraint 1. These three generating neighborhood
solutions allow for extensive searches and increase the likelihood of
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obtaining the best solution. Figure 4 shows an example of a tentative
solution.
Generating neighborhood solution 1: 1-1 exchange Figure 5 shows an example of a neighborhood solution generated by the “1-1 exchange.” One maintenance work nodeof the set is exchanged with the interchangeable maintenancenode of another set at the same time zone.
Generating neighborhood solution 2: 2-1 exchange Figure 6 shows an example of a neighborhood solution generated by the “2-1 exchange.” Two maintenance work nodesof the set are exchanged with the interchangeable maintenance node of another set at the same zone.
Generating neighborhood solution 3: 1-0 insertion Figure 7 shows an example of a neighborhood solution generated by the “1-0 insertion.” One maintenance work node of
the set is inserted between two other maintenance work
nodes of another set at the same time zone.

Fig. 4 An example of an original solution.

Fig. 5 An example of a neighborhood solution generated by the “1-1 exchange.”

Fig. 6 An example of a neighborhood solution generated by the “2-1 exchange.”

Fig. 7 An example of a neighborhood solution generated by the “1-0 insertion.”
5. Case study
5.1 Case study condition
To confirm the effectiveness of the proposed method, a casestudy is conducted using actual train schedules and rolling stock
schedules for three days. Specifically, the maintenance worker
schedule [I] generated by the proposed method is compared with theactual schedule [II] and the maintenance work schedule [III] generated by MIP. For details of MIP formulation, see to Reference 7.
Input data used for case study is 99 trains and 7 sets (small
scale) for Case 1; 120 trains, 8 sets (medium scale) for Case 2; and173

147 trains, 9 sets (large scale) for Case 3. In addition, following
conditions are determined in common for each case.
• Upper limit of the number of maintenance works: 18• Upper limit on the difference in the number of maintenance workwithin the group: 2• Upper limit on the differencein the number of maintenance work
between groups: 2• Preparation time: 10 to 20 minutes• Track interval time: 0 to 3 minutes• Additional time 1: CX = 4, CY = 2, CZ = 5• Additional time 2: CX = 7, CY = 5, CZ = 10
Table 1 shows weighting coefficients for the objective function
for case study. Weight coefficients for each penalty in the objectivefunction are set with the aim of generating the maintenance worker
schedule that satisfies high priority constraints 1 to 5 more than low
priority constraints 6 to 9. Parameters of TS are set to the TLL of 50
and the iteration of 5,000. It is important for practical purposes that
automatic generation of the maintenance worker schedule takes lessthan 3 minutes to calculate, all cases’ upper limit of computation
time is set 3 minutes. The case study software has been developed
using C language (Microsoft Visual Studio 2019) on a PC (Intel
Core i7-8700 (3.20 GHz) CPU and 64 GB memory) and used themathematical optimization solver Gurobi (Optimizer 9.5.110) [8] tosolve MIP.
5.2 Case study results
Table 2 shows the objective function value, each evaluation
value, and each penalty by the actual schedule (I), the proposed
method (II), and MIP (III) in each case. In Table 2, each evaluation
value and each penalty with high priority constraints of the proposed
method are listed in red bold face.
In Case 1, the proposed method reduces the track interval timeby 31 minutes and increases the additional time by 5 minutes compared with the actual schedule. In Case 2, the proposed method increases the track interval time by 3 minutes and reduces the additional time by 15 minutes compared with the actual schedule. In
Case 3, the proposed method reduces the track interval time by 36
minutes and the additional time by 70 minutes compared with theTable 1

actual schedule. Therefore, the proposed method reduces both the
track interval time and the additional time by the actual schedule, sothat it is confirmed that the proposed method can generate a maintenance worker schedule that reduces the workload on maintenanceworkers.
The proposed method can generate the best solution in the practical computation time of about 1 minute for all cases. In addition,
the proposed method can generate practical solutions in all cases,
because the penalty terms corresponding to high priority constraints
1 to 5 are all zero. Since the most important practical aspects of thisproblem are that computation time is less than 3 minutes and thathigh priority constraints 1 to 5 are satisfied, results indicate that the
proposed method can generate the practical maintenance worker
schedule in practical time.
In Cases 1 and 2, maintenance worker scheduling by MIP generate solutions with the objective function value lower than those of
the actual schedule and the proposed method. But in all cases, theoptimal solution by MIP cannot be generated in computation time of
3 minutes. In Case 3, the total objective function value is clearly
inferior, but at the 3 minutes stage, the dual gap representing theaccuracy of the solution is extremely large, confirming that the computation time is clearly insufficient. In addition, high priority constraints 1 to 5 are violated, and no practical solution are created.
Therefore, MIP cannot generate practical solutions on days withmany trains within a practical computation time, because it cannot
satisfy high priority constraints.
In conclusion, the proposed method can generate maintenanceworker schedules that satisfy high priority constraints 1 to 5 andreduce the track interval time and the additional time, within 3 minutes computation time in each case. This indicates that the proposed
method will be effective in practice.
6. Conclusions
Maintenance worker schedules are the daily schedules produced for each worker set, allowing them to carry out inspection andmaintenance work such as cleaning of rolling stock during turnaround operations at terminal stations. The maintenance worker

Weighting coefficients for the objective function for case study.

Table 2 The value of each evaluation value term of the objective function and amount of deviation from the predefined
threshold for each constraint.

174

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schedule is prepared every day in accordance with train and rollingstock schedules that vary day to day. Currently, maintenance worker
schedules are prepared manually by skilled planners, but because ofmultiple constraints on the workload of maintenance workers, ittakes several hours to prepare one day’s schedule, which is labor
intensive. This calls for automatic generation of maintenance worker schedules to save labor.
This paper describes the development of automatic generationof maintenance worker schedules by TS. To confirm the effectiveness of the proposed method, we compared schedules it producedwith the actual schedules and maintenance worker schedules generated by MIP. Results indicate that the proposed method can generate
practical maintenance worker schedules that satisfy high priority
constraints and reduce track interval times and the additional time,within 3 minutes computation time. This therefore indicates that the
proposed method is effective in practice.
References[1]	Korte, B. and Vygen, J., “Combinatorial Optimization,” SpringerVerlag Berlin Heidelberg, 2006.

[2]	Baker, K. R., “Introduction to Sequencing and Scheduling,”
Jhon Wiley, 1974.
[3]	Abbink, E., Fischetti, M., Kroon, L., Kroon, T., and Vromans,
M., “Reinventing crew scheduling at Netherlands railways,”
Interface, Vol. 35, No. 5, pp. 393-401, 2005.
[4]	Kokubo, T., Kato, S., Nakahigashi, T., Takeuchi, Y., and Tanaka,
S., “Application of Tabu Search to an Automatic Creation
Method for Maintenance Worker Diagram,” in Proceedings ofthe IEEJ TER, 22-063, 2022 (in Japanese).
[5]	Kokubo, T., Kato, S., Nakahigashi, T., Takeuchi, Y., and Tanaka,
S., “Automatic Creation Method for Maintenance Worker
Schedules by Tabu Search that Allows Constraint Violations,”in Proceedings of the IEEJ IASC, R5-12, 2022 (in Japanese).
[6]	Kokubo, T., Kato, S., Nakahigashi, T., Takeuchi, Y., and Tanaka,
S., “Automatic Creation Method for Maintenance Worker
Schedules by Tabu Search that Allows Constraint Violations,”
J-RAIL, S5-1-2, 2022 (in Japanese).
[7]	Glover, F. and Laguna, M., “Tabu Search,” Kluwer Academic
Publishers, 1997.
[8]	Gurobi Optimizer: https://www.octobersky.jp/products/gurobi(Reference date : April 24, 2024) (in Japanese).

Authors
Tatsuya Kokubo

Researcher, Transport Operation Systems
Laboratory, Signaling and Operation Systems
Technology Division
Research Areas: Transportation Planning,
Maintenance Worker Scheduling

Taichi NAKAHIGASHI

Researcher, Transport Operation Systems
Laboratory, Signaling and Operation Systems
Technology Division
Research Areas: Transportation Planning,
Train Rescheduling

Satoshi KATO

Senior Chief Researcher, Transport Operation
Systems Laboratory, Signaling and Operation
Systems Technology Division
Research Areas: Transportation Planning,
Mathematical Optimization

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175

PAPER

Development of Safety Check Support Device for Drivers Using Side Cameras on Rolling Stock
Wataru GODA
Hiroki MUKOJIMA
Nozomi NAGAMINE
Image Analysis Laboratory, Information and Communication Technology DivisionThis paper presents the development of a safety check support device aimed at further enhancing
platform safety checks using side cameras installed on rolling stock. The device employs deep learningbased image processing techniques to detect passenger approach on platforms in real-time from camera
footage, notifying the driver to assist with safety checks. Additionally, the device is equipped with automatic
passenger counting functionality at each station. An overview of the developed device and the results ofevaluation experiments are provided.
Key words: side cameras on rolling stock, one-man operation, object detection, image processing, deep learning
1. Introduction
On driver-only operated trains, passenger safety checks are
currently carried out visually by the driver using platform mirrors ormonitors etc. The recent introduction of side cameras has begun insome driver-only operated sections as a new visualization method
for the drivers. In these sections, footage from side cameras is displayed in the driver’s cab. This allows the driver to check the safetyof the platform before the train departs.
To further improve safety through the use of side cameras, wehave developed a device that detects passengers on platforms who
may be approaching the train in real-time using image processing
technology, and notifies the driver to assist with safety checks.
Using the device can reduce the burden on the driver to checkthe safety during door operations, as well as enable the monitoringof passengers approaching too close to a moving train on the platform, which was previously undetectable, thereby enhancing overall safety. Figure 1 presents an overview of the entire system.
As well as assisting with safety checks, this device can also
provide an automatic passenger counting function. It automaticallycounts the number of passengers boarding and alighting at eachstation, and can save the data in CSV format or similar. This detailed
data can be used as a decision-making basis for operational matterssuch as timetable management, fleet size settings, and the further
extension of driver-only operated sections.
In this paper, we describe an overview of the side cameras in
Chapter 2, explain the proposed algorithm in Chapters 3 and 4, present the implementation of the algorithm in the device in Chapter 5,
and show the results of performance evaluation of the device in
Chapter 6. Finally, in Chapter 7, we summarize the conclusions.
2. Side Cameras
Each vehicle is equipped with four side cameras: one on eachcorner. Figure 2 shows a top view of the vehicle. The circular symbols represent the side cameras, and the arrows indicate the direction of the cameras. Each camera is installed at approximately theheight of the top of doors and is positioned at an angle that allows
the entire platform to be monitored from an elevated perspective.
The monitor in the driver’s cab displays footage from the cameras facing towards the rear of the train, in relation to the directionof travel. When the train stops at a station and the doors open, thecamera footage is automatically displayed, and after departure thedisplay is turned off when the vehicle exceeds a certain speed. The
176

Fig. 1 The entire system

Fig. 2 Placement of side cameras on vehicle
footage from the cameras on the platform side is also displayed.
3. Safety check support algorithm
3.1 Overall processing flow
The safety monitoring algorithm using the image from sidecameras on the platform side consists of the following four mainprocesses (Fig. 3). First, passengers appearing in the footage fromcameras on the platform side are detected using image processing
using deep learning. Secondly, to estimate the approach status of thepassengers, the coordinates of each detected person inside the image
are converted to real-world coordinates, and the distance to the veQR of RTRI, Vol. 65, No. 3, Aug. 2024

can be observed that the detected passengers are outlined withbounding boxes.
3.3 Coordinate transformation

Fig. 3

Safety check support method processing flow

hicle is calculated. Finally, based on the calculated distances of thepassengers and a predetermined threshold, the driver receives a notification such as “caution” or “danger.”
The specific contents of the processes are described in the following sections.
3.2 Passenger detection
Passenger detection is carried out on the acquired camera footage
using a model created by deep learning. The model was developed todetect passengers as targets for detection, including people (full bodyand head), wheelchairs, baby strollers, and white canes, which werelearned through deep learning. A total of 60,734 image data were used
for training, including 36,000 images from a proprietary dataset captured by the Railway Technical Research Institute, as shown in theexample in Fig. 4, and an additional 24,734 image data from open
data such as the COCO dataset [1] containing images of people.
Figure 5 shows the detection process in the experimental environment at the Railway Technical Research Institute. From Fig. 5, it

The center of the bottom edge of the bounding boxes for eachdetected passenger is defined as the foot coordinate. Using projective transformation [2], the platform overhead coordinates corresponding to the real distance are calculated for these foot coordinates. Any point Xcam ∈ ℝ2 on the plane captured in the camera
coordinate system is considered as a corresponding point Xreal ∈ ℝ2
in the real-world coordinate system. At this point, the mapping between two points is represented by a homography matrix H ∈ ℝ3×3
(where one of the elements is 1), as shown below.

′

real
cam
=
(1)

′

′

1

real
(2)
real =′

Here, ℝ is the set of real numbers, and W' ∈ ℝ satisfies W' ≠0. From the above equation, since there are eight unknown variables, H is uniquely determined if there are four points corresponding to Xcam and Xreal.
The formula for conversion to real-world coordinates, thereby,
can be obtained using the four vertices of boxes covering several
braille blocks (hereinafter referred to as braille blocks) with known
real sizes and the corresponding four points of the braille blocks on
the image.
The conversion formula is calculated once for each camera, andas long as the camera installation position is fixed and the height ofthe station platform surface meets the standard criteria, the conversion formula can be considered the same for each station.
Furthermore, the conversion formula can also be automaticallycalculated using AR markers [3]. By actually performing projective
transformation, the coordinates can be converted to correspond toreal-world distances, as shown in Fig. 6.
3.4 Coordinate transformation
To check the safety over a vehicle length of approximately 20
meters, coordination processing of the two cameras is carried out.
The detection area of the two cameras is set to cover a range longer
than half the vehicle length, as shown in Fig. 7. The reason for set-

Fig. 4

Examples of the created training data

Fig. 5

Examples of the detected passengers

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Fig. 6 Passenger detection and calculation of real-world
coordinates
177Fig. 8 Processing flow of the boarding and alighting
passenger counting algorithm

Fig. 7Dual-camera coordination processing

ting the detection area in this way is that the position calculation
accuracy decreases as the person is farther away from the camera, so
the detection area is set on the side closer to the respective camera.
Moreover, the hatched area in Fig. 7, which is the overlapping
detection area of both cameras, exists near the center of the vehicle.
This is to prevent detection omissions near the boundary. Although
there is a possibility of detecting the same person twice in the overlapping detection area, this redundancy is on the safe side and does
not pose any operational issues.
3.5 Approaching determination
In terms of determining the threshold for proximity warning on
platforms, while it is generally considered safe inside the brailleblocks and unsafe outside (toward the platform edge), this cannot be
used as a unified standard. This is because the precise installation
positions of braille blocks can vary from station to station, and somestations may not have them installed at all. Therefore, instead ofusing the presence or absence of braille blocks as the criterion, thenotification of passenger proximity is defined solely based on the
distance between passengers and the train.
The following provisional criteria have been adopted:● 100 cm or less from the vehicle (assuming a gap of 20 cm between
the vehicle and the platform, and a distance of 80 cm from theplatform edge to the braille blocks) is considered “danger.”● Between 100 cm and 140 cm from the vehicle (assuming a widthof 40 cm for the braille blocks with inner lines) is considered a“caution” area.
● Any distance greater than 140 cm from the vehicle is considered“safe.”
These criteria can be changed arbitrarily.

detection method, target detection is performed using deep learning-based image processing, followed by tracking of the detectedindividuals. This allows the trajectories of the detected targets to beobtained. Next, for the detected individuals, the direction and number of passengers passing through the set door position, are determined to count the number of passengers boarding and alighting.
Finally, the passenger count data are output in a format such as CSV.
In the following sections, we discuss the specific details of theprocessing. However, since passenger detection is the same as forthe safety check support algorithm this part of the explanation isomitted.
4.2 Tracking
For the detected individuals, tracking is performed by associating detections of the same person across consecutive frames. We
adopted the ByteTrack [4] algorithm for tracking. In ByteTrack, asshown in Fig. 9, even if a person previously detected with high confidence temporarily has a lower detection confidence due to occlusion or other factors, their position can be estimated by tracking
based on the predictions from previous frames. This is achieved byutilizing the appearance similarity and motion consistency of thedetected person across frames. Additionally, the processing time for
ByteTrack is 1-3 ms per frame, enabling real-time tracking.
4.3 Boarding and alighting countAs shown in Fig. 10, a reference line (green line in Fig. 10) is
set for each door to be counted. The direction and number of times
this reference line is crossed are measured to count the number ofpassengers boarding and alighting. When counting, two points are
set as tracking points, as shown by the orange and yellow points in
Fig. 11. The primary tracking point for counting is the center pointof the bottom edge of the head bounding box (yellow point in

4. Passenger counting algorithm
4.1 Overall processing flow
The passenger counting algorithm using side cameras consistsof three main processes, as shown in Fig. 8. Similar to the passenger
178

Fig. 9 Tracking using ByteTrack
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Fig. 10 
Setting the doors forcounting (the individuals in the image are
test-related personnel)

Fig. 11 Definition of
tracking points

Fig. 11), as it is more likely to be visible even in crowded situations.
As a backup feature in case the head is not detected, a secondary
tracking point (orange point in Fig. 11) is set at a height of 5/6 of thewhole body from the reference coordinate. This height is based on
the assumption that an average human body is approximately sevenheads tall, taking into account the slightly shorter appearance due tothe downward angle of the camera.

to be installed in each vehicle, it is desirable to realize each unit at
the lowest possible cost, as a large number of devices will be required depending on the number of vehicles. The cost hurdle in thiscase is the use of deep learning-based detection. This processing
typically requires a large amount of parallel computing and the incorporation of expensive image processing semiconductors such as
GPUs into the device.
To avoid this, we optimized the deep learning-based detection
for speed, creating a model that can perform detection using only aCPU. This was achieved by applying lightweight techniques calledknowledge distillation and pruning, as shown in Fig. 13, to ahigh-performance model that was trained normally. As a result, deeplearning-based detection can be performed in about 20 ms using only
one CPU, and the entire process can be completed within 100 ms.
Therefore, by using only a CPU as the processing unit of thedevice, it became possible to eliminate the need for a dedicatedcooling fan, enabling miniaturization, low noise, improved vibration resistance (compliant with JIS E4031 “Rolling stock equipment― Vibration and shock testing methods”), and other benefits. Basedon the above considerations, the appearance (Fig. 14) and specifications (Table 1) of the developed prototype safety check support device are shown. The LTE router functionality also enables thetransmission of detection results and passenger count data to railway company’s headquarters.

5. Development of onboard device
5.1 Overall device configuration
The overall configuration of the proposed equipment is shownin Fig. 12. The cameras, cables, video recording device, and display
device shown in the figure are existing facilities pre-installed as partof the current side camera system. Our device, which implements
the algorithms described in Chapter 3 and 4, is added to this existing
equipment to introduce the new functionality.
5.2 Device design
When designing the equipment, considering that one device isFig. 13 Accelerating the deep learning modelFig. 12Overall system configuration

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Fig. 14 Appearance of the safety check support device
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Table. 1 Specifications of the safety check support device

5.3.2 Notifying the driver
The proximity warning from the device is notified via existing
video display such as tablet terminal. Figure 16 shows the display
method created for check purposes. The frame display and audio
notifications are made according to the approach status, such as“caution” or “danger.” Additionally, the type of detected target (person, wheelchair, stroller, white cane) can also be displayed (shownas white text within the screen in Fig. 16). The current display method is provisional and can be customized individually according tothe operational methods and safety considerations of each operator.
6. Performance evaluation
6.1 Evaluation for proximity warning

5.3 Collaboration with existing side camera system
To properly execute the proximity detection and passenger
counting functions, the equipment needs to be connected and linked
to the existing side camera system. The necessary collaboration includes determining the timing for activating each function and notifying the driver when necessary. Each of these aspects is explained
below.
5.3.1 Activation timing
The timing of the activation of the processes is shown in
Fig. 15. The vehicle status information is received from the existing
system and four timing criteria are used: platform entry, door opening, door closing, and platform exit. For proximity warning notifications, during passenger boarding and alighting between door opening and closing, it is normal behavior for passengers to enter thecaution or danger zones. Therefore, there is no need to issue caution
or danger notifications during this timing; the timing when notification is required is when no passengers are boarding or alighting between platform entry and platform exit. Accordingly, notifications
are turned off during boarding and alighting. On the other hand, forpassenger counting, the processing is turned off during platform
entry and platform exit, as no passengers should be boarding or
alighting during these timings.

Fig. 15
180

Timing of processing execution

To evaluate the performance of the proposed device, a prototype device was connected to a Series 815 train pre-equipped with aside camera system. A test run was conducted for the duration of tworound trips (daytime and nighttime) covering 11 stations on the JR
Kyushu Kagoshima Line (Yatsushiro - Kumamoto) using a test train(Fig. 17).
The footage of 22 station stops during the test run was analyzed, and the detection rate was evaluated. Here, the false detection
rate is defined as the ratio of the number of frames where a notification was issued despite a safe situation to the total number of frames
in safe situations. Similarly, the missed detection rate is defined as
the ratio of the number of frames where no notification was issued
despite an approach beyond the braille blocks to the total number offrames with such approaches.
The false detection rate was 0.02%, and the missed detection

Fig. 16 Example of a display screen for the driver (individuals in the image are test-related personnel)

Fig. 17 Scene from running test (individuals in the image
are test-related personnel)
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rate was 3.80%. The most common cases of missed detection were
for white canes. However, since white canes are mostly present simultaneously with people, proximity warning can be issued as longas the person with the cane is detected. Taking this into account andexcluding white canes, the false detection rate was 0.02%, and themissed detection rate was 1.75%. Furthermore, when the detection
targets were limited to people, for which a larger amount of training
data are available, the false detection rate was 0.00%, with no
missed detections lasting more than 5 frames (0.5 seconds), and themissed detection rate was 0.36%. For wheelchairs and strollers,performance is expected to improve by increasing the amount oftraining data to a level similar to that for people.
6.2 Evaluation of passenger count
The performance of passenger counting was evaluated using
recorded video data. Video data from 558 station stops on the Hohi
Line (Kumamoto - Higoozu), where Series 815 trains are in operation, were used. The data included various conditions such as differences in timing, from the first train to the last train, differences inweather conditions (sunny, cloudy, rainy, thunderstorms), indoor
and outdoor platform environments, and differences in station structures (side and island platforms). Since each vehicle of the Series
815 trains has three doors on the platform side, the front door andthe middle door are designated in order of proximity to the camera(referred to as Door 1 and Door 2, respectively, in Fig. 10). Since thedetection areas of the two side cameras overlap around the middle
door, passengers boarding and alighting at the middle door are detected by both cameras, resulting in a double count. To compensate
for this, the average or maximum of the two counts is used. In thiscase, the average value was adopted.
For the evaluation, the cumulative counts by visual confirmation and the device output were compared, and the accuracy (device
count / visual count) was summarized for each door, as shown in
Table 2.
From Table 2, excluding the middle door alighting count, theerror rate was lower than 5%. On the other hand, the error rate forthe middle door alighting count was 15%, which is significantly
higher than the others. This is due to the influence of the ByteTrackalgorithm. While ByteTrack can estimate the position by tracking
even if a target that has been previously detected is temporarily occluded and its confidence decreases, it does not handle cases where
the target is occluded and cannot be detected upon initial appearance. Therefore, for alighting at the middle door, there is a higher

Table. 2 Accuracy of boarding and alighting passenger
counting for each door

possibility of the initial appearance being occluded by people infront, leading to more missed detection cases.
The overall accuracy of the system is considered to be of practical use, considering that high frequency counts are possible bydistinguishing between boarding and alighting at each station.
7. Conclusion
Aiming to further enhance safety check by utilizing side cameras, we have developed a device that detects the presence of passengers on the platform who may approach the train in real-timefrom camera footage using image processing technology based on
deep learning, and notifies the crew member, assisting in safety
check. Furthermore, this device is not only for safety check but also
has the function of automatically counting the number of passengers
boarding and alighting at each station. In the future, we plan to makefinal adjustments for practical implementation.
References[1]	Lin, T., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan,D., Dollár, P., Zitnick, C. L., “Microsoft coco: Common objects
in context,” Proceedings of the European Conference on
Computer Vision, pp. 740-755, 2014.
[2]	Yoshino, J., Nagamine, N., Mukojima, H., Goda, W., “Calculation
Method of Image Transformation Parameters for Side Cameras
on Rolling Stocks Using AR Markers,” TER-21-067, 2021.
[3]	Forsyth, D., and Ponce, J., “Computer vision: a modern
approach,” Prentice hall professional technical reference, 2002.
[4]	Zhang, Y., Sun, P., Jiang, Y., Yu, Y., Yuan, Y., Luo, P., Liu, W.,
Wang, X., “BYTETrack, Multi-object tracking by associating
every detection box,” arXiv preprint arXiv:2110.06864, 2021.

Authors
Wataru GODA

Researcher, Image Analysis Laboratory,
Information and Communication Technology
Division
Research Areas: Image Processing,Information Technology

Nozomi NAGAMINE, Ph.D.

Senior Chief Researcher, Head of Image
Analysis Laboratory, Information andCommunication Technology Division
Research Areas: Image Processing,Information Technology

Hiroki MUKOJIMA

Researcher, Image Analysis Laboratory,
Information and Communication Technology
Division
Research Areas: Image Processing,Information Technology

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181

PAPER

Rolling Stock Scheduling Algorithm for Temporary Timetable After Natural Disaster
Satoshi KATO
Taichi NAKAHIGASHI
Tatsuya KOKUBO
Transport Operation Systems Laboratory, Signalling and Operation Systems Technology Division
Jun IMAIZUMI
Toyo University
This paper focuses on rolling stock scheduling after a large-scale natural disaster. In general, atemporary timetable is generated when sections of a line are partially disrupted by damage caused by thenatural disaster. The next step is to generate a rolling stock schedule that is as close as possible to theoriginal schedule at the time of timetable revision. We propose a two-phase rolling stock schedulingalgorithm based on a mathematical programming method to cope with the temporary timetable. In addition,
we confirm that the proposed algorithm can produce a practical rolling stock schedule in terms of evaluation
criteria and computational time.
Key words: rolling stock scheduling, temporary timetable, disaster, duty, roster, mathematical programming
1. Introduction
In order to operate railway trains, it is necessary to prepare not
only train timetables but also several related schedules. One of themis a rolling stock schedule, which determines the schedule of rollingstock to be used to realize daily train operation. It is required topropose an efficient rolling stock schedule to make effective use oflimited resources [1].
When some sections of a line are partially disrupted due todamage caused by a large-scale natural disaster, it is necessary to
prepare a temporary timetable and a corresponding rolling stock
schedule plan. In such cases, the schedule plan needs to be preparedeach time the operating section is gradually expanded according to
the restoration status. This places a heavy burden on the schedule
planners to prepare a tentative schedule plan due to the limited time
available. In addition, it is desirable to avoid changes in the planeach time the operating section is expanded. Since the original timetable will be restored when operations have finally resumed on all
sections, it is preferable for the tentative schedule at each stage to be
similar to the original schedule.
In this paper, we focus on the preparation of rolling stock
scheduling after a large-scale natural disaster. Then, we propose analgorithm that can automatically generate a rolling stock schedule ina short time by utilizing mathematical optimization. In addition, weshow the results of case studies based on actual disrupted cases toconfirm the effectiveness of the proposed algorithm.
2. Rolling stock scheduling after a large-scale natural disaster2.1 Rolling stock schedule
A rolling stock schedule is produced by assigning rolling stock
to all trains shown on a train timetable. Specifically, it consists of a“duty” which is a schedule for each working day and a “roster”
which is a circulation schedule that defines the order of the duty. In
the duty generation phase, it is necessary to consider the interval
time between two consecutive trains. In the roster generation phase,the end station of one duty and the start station of the next duty mustcoincide. Otherwise, an empty run has to be inserted if necessary. In
addition, the end station of the last duty of the roster should coincide
182

with the start station of the first duty to guarantee circularity.
An important consideration of rolling stock scheduling is totake into account the inspection cycle of the vehicles. This paper
focuses on pre-departure inspections and regular inspections. The
former is for functional checks with a periodicity of a few days. The
latter is for detailed checks with a periodicity of several tens of days.
The location and timing of each inspection should be determined sothat each inspection can be carried out to satisfy the interval conditions.
In general, a roster is created for each type of rolling stock in
the lowest operational cars that are not further divided. Each typegenerally consists of several cars, called “unit” in this paper. Eventhe same type of car is treated differently if the number of cars andequipment specifications are different. Here, we define “unit type”
as a concept that identifies the type of car determined by the typeand number of cars, and we need to create a roster for each unit type.
On some lines in Japan, splitting and combining are applied. A
set of rolling stock consisting of one or more units assigned to eachtrain is called a “composition.” Here, splitting means to split a composition into two or more separate units, and combining means to
combine two or more separate units together. Splitting and combining allow flexible adjustments of traffic capacity. However, it requires additional time and work of operators at a station or a rollingstock depot, so it is desirable to reduce splitting and combining.
Figures 1 and 2 show an example of a rolling stock schedule.
Figure 1 shows an example of duties on the diagram, where a circle
means the start of a duty and a triangle means the end of a duty. The
trains with double lines mean that the two units are operating in a
combined formation. Splitting of units takes place after the operation of 102M, 105M and 57M. On the other hand, combining ofunits takes place before the operation of 105M, 102M and 56M.
Figure 2, on the other hand, shows an example of a roster. The train
number (F) means the front side of the train and (B) means the rearside of the train. The pre-departure inspections are then included induties 3, 5, and 7. Since the units are assigned in the order of theroster, the inspection is carried out once every three days in unit type
1. Similarly, the inspection is carried out once every two days in unit
types 2 and 3. The number of days in a roster means the number ofunits required, and in this example, each unit type requires 3 units, 2
units, and 2 units, respectively. It is therefore desirable to reduce thenumber of duties in terms of efficient use of railway resources.
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Fig. 1

Example of rolling stock duties
Fig. 3 Example of expansion of operating section
section resumes operation after 10 days, but the expansion of theoperating section may be further subdivided.
2.3 Related work

Fig. 2

Example of rolling stock rosters

2.2 Transportation planning after a large-scale natural disaster
When railway tracks and facilities at stations and rolling stock
depots are damaged due to a large-scale natural disaster, operations
may be suspended for a long period of time. In such a case, a schedule planner prepares a temporary train timetable and a rolling stock
schedule based on the restoration plans. But in many cases, theiroperations resume within just a few days, so the schedule plannerhas to prepare a plan within a short period of time. In addition, whenseveral sections of a line are damaged, the operating section may be
expanded sequentially according to the scale of the damage andpriority level of restoration. A transportation plan must be createdeach time the operating section is expanded, which is hard work forthe schedule planner.
Figure 3 shows an example of the expansion of operating sections. In this example, the regular operating section is between stations A and H. The sections between stations C and D, and between
stations F and G are suspended due to the disaster. On the first dayof resumed operation, the service operates between stations A and C,
and between stations D and F (the sections between stations C andD, and between stations F and H are suspended). Assuming that therolling stock depot is adjacent to station E, the trains operating between stations A and C cannot return to the rolling stock depot,
which may result in “isolated sections.” In this example, the entire
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There are many previous works of research related to rollingstock scheduling during timetable revision, for example, Alfieri etal. [2], Cacchiani et al. [3], Giacco et al. [4], etc. In recent years,
there have been a few studies based on Japanese railway lines. For
example, Imaizumi et al. [5] decompose the problem into creating
duties and rosters, and formulate it as a mathematical optimization
problem, respectively. Nishi et al. [6] propose a solution method thatcombines a column generation method and heuristics, considering
inspection interval constraints. Kato et al. [7] model the problem asa Traveling Salesman Problem (TSP) based on Giacco et al. [4], andpropose a method to reduce splitting and combining.
On the other hand, there are no studies that specifically focus onrolling stock scheduling after a disaster. Although previous studies
on timetable revision can be referred to as a method for generating arolling stock schedule, it is necessary to propose a new algorithm fora temporary timetable after a disaster.
3. Rolling stock scheduling algorithm after a large-scale disaster3.1 Problem definition
Based on the characteristics of disaster situations described in
Chapter 2, we define the problem addressed in this paper. Assumptions and constraints are as follows:a) The minimum and maximum number of cars assigned toeach train are given.
b) Information on whether two different trains are to be connected directly or via an empty run is given.
c) Each unit type has a maximum number of available limit.
d) Stations at which units can be split and combined are given.
e) The possibility of combining between two unit types is given.
f) For each unit type, the possible operating lines and trainsthat can be assigned are given.
g) The pre-departure inspection and the regular inspection
183

shall be carried out every specified number of days. The regular inspection shall include the pre-departure inspection.
h) The possible stations where the pre-departure inspection
and the regular inspection can be performed are given. For eachstation, there are several time periods for inspection depending on
the type of inspection. In addition, there is a maximum number ofunits for inspection allowed for each time period.
i) The maximum number of trains able to stay at each station is
given. Basically, when a train arrives at a station, the number oftrains staying at the station is counted as one. However, if splitting
is necessary to allocate the units to other trains, this is assumed totake place at the time of arrival. In this case, if a train consisting of
two units is split, the number of trains staying at the station is counted as two. On the other hand, it is assumed that combining takes
place before departure.
We consider the number of duties, the number of times there
are splitting and combining, and the distance of empty runs as evaluation criteria. These are also important in the rolling stock scheduling during timetable revision. In addition, we introduce an original
concept called “schedule difference” to evaluate the closeness of thecreated schedule to the original schedule.
3.2 Concept of schedule difference
The concept of schedule difference is illustrated in Fig. 4. The
left figure shows the rolling stock schedule produced at the time of
the train timetable revision, which is called the “basic schedule.”
The right figure shows the rolling stock schedule created after thedisaster, which is called the “temporary schedule.” This is an example of a situation where train operations are resumed only between
Stations B and D. In this example, we can see that although the turnback stations are different, both the basic schedule and the temporary schedule have a turn-back of 102M-103M. Thus, if the turnback trains are the same, there is no schedule difference even if theturn-back stations are different. On the other hand, if the turn-backtrains are different, there is a schedule difference.
In this paper, we seek a rolling stock schedule with as few
schedule differences as possible. Eventually, the train operation will
return to the basic schedule after the operating section has been extended. Therefore, considering differences from the basic schedulein the initial stage of resumption will reduce schedule changes
during the extension of the operating section and enable a smooth
return to the basic schedule.
3.3 Solution approach
In this paper, we apply mathematical optimization to the production of the rolling stock schedules. There are two solution approaches: the “simultaneous method,” which simultaneously generates the set of duties and the set of rosters based on the train
timetable, and the “two-phase method,” which first generates the setof duties and then uses the generated duty to generate the set ofrosters.
Since the rolling stock schedule is completed by generating not
only the duty but also the roster, the simultaneous method is preferable from the viewpoint of total optimization. However, because of
the difficulties of the problem size, the two-phase method is also a
promising option from a practical point of view. In this paper, since
we assume a time-constrained situation after a disaster, we adopt thetwo-phase method that allows a short computational time.
The procedure of the proposed algorithm is shown below.
Step 1: Preprocessing
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Fig. 4 Example of schedule differences
We check the train timetable if any sections have been disrupted by the disaster. If so, the problem is divided into sub-problems
for each section. We then carry out the process from Step 2 for eachsection.
Step 2: Duty generation algorithm
We generate a set of duties for each unit type. The duty generation problem is modeled in the same way as a multi-commodity
network flow problem.
Step 3: Roster generation algorithm
We generate a roster for each unit type using the set of duties
obtained in Step 2. The roster generation problem is modeled in thesame way as in treating a TSP.
As discussed in Section 3.1, the number of times there are splitting and combining is the evaluation criterion that should be reduced
as much as possible. Splitting and combining take place during andbetween two duties, and the number of times there are splitting andcombining is reduced with the following methods:・ The duty generation algorithm generates a set of duties toreduce splitting and combining in a duty.
・ The roster generation algorithm generates a roster to reduce splitting and combining between two duties.
It is also necessary to determine the position of units such as“front” and “back” in the composition. In this paper, we consider the
position as follows.
・ The duty generation algorithm does not take into accountthe position in the composition. The algorithm detects the
splitting and combining of each train and calculates thenumber of times splitting and combining have taken place.
・ The roster generation algorithm requires the position ofeach unit in the composition to calculate the number oftimes there are splitting and combining between duties.
After the duty generation algorithm, the position of each
unit in the composition is determined by a rule such as
reversing the position when the turn-back takes place. And
these positions are used as input to the roster generation
algorithm.
The time interval constraints for the pre-departure inspection
and the regular inspection are taken into account in the roster generation algorithm. However, since the output of the duty generation
algorithm is the input to the roster generation algorithm, if the required number of inspections is not included in the result of the duty
generation algorithm, the roster generation problem will be infeasible. Therefore, the required number of pre-departure inspections
and regular inspections should be included according to the numberof duties to be created for each unit type in the duty generation algoQR of RTRI, Vol. 65, No. 3, Aug. 2024

rithm. This will ensure feasibility in the roster generation problem.
3.4 Duty generation algorithm
In this paper, we apply the multi-commodity network flow
problem that is often used in rolling stock scheduling (e.g., Cacchiani et al. [3] ). We can model the duty generation problem byconsidering commodities as unit types and flows as duties.
There are four types of nodes on the network as follows:(i) Departure node, which refers to the departure of each train
at the starting station(ii) Arrival node, which refers to the arrival of each train at theending station(iii) Start node, which refers to the start of the duty(iv) End node, which refers to the end of the duty
In addition, there are five types of arcs on the network as follows:(i) Train arc, which refers to a train and is drawn from the departure node to the arrival node for the train.
(ii) Connection arc, which refers to a connection between different trains and is drawn from the arrival node to the departurenode when the connection is possible (stations are coincident andthe interval time is sufficient)(iii) Inspection arc, which refers to an inspection and is drawn
from the start or arrival node to the departure node when an inspection is possible(iv) Start arc, which is drawn from the start node to the departure node(v) End arc, which is drawn from the arrival node to the end
node
The cost of the train arc associated with a commercial train is
set to 0; otherwise, it is set to α (this is a weight parameter). The costof the connection arc is set to 0 if the connection is the same as thebasic schedule; otherwise, it is set to β (this is also a weight parameter) taking into account the schedule difference. The cost of thestart arc is set to 1. The cost of all other arcs is set to 0.
Figure 5 shows an example of a network for a multi-commodity network flow model. Several flows of each unit type move fromthe start node to the end node on this network. These flows ensurethat each train is allocated a number of cars greater than the minimum number of cars and less than the maximum number of cars.
The following is an outline of the formulation as a mathematical optimization problem (see Ref. [8]) for details).
<Objective function>
Total cost of the arc + γ × the number of times there are splitting
and combining during the duty (to be minimized)
Note that γ is a weight parameter.
<Constraints>
・ Flow matching constraints (the number of flows enteringand exiting each node is the same except at the start andend nodes)・ Upper and lower limits on the number of cars assigned toeach train
・ Upper limits on the number of duties for each unit type・ Inspection interval constraints of pre-departure inspection
and regular inspection・ Upper limit on the number of simultaneous inspections of
pre-departure inspection and regular inspection・ Logical constraints for detecting splitting or combining ina duty・ Forbidding combining between two unit types which cannot be connected
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Fig. 5 Example of network for multi-commodity network
flow model・ Upper limit on the number of trains that can be staying at
each station
・ Constraints for possible values of each variable
3.5 Roster generation algorithm
We model the roster generation problem as a TSP. A TSP can bemodeled as a network in which duties are represented as nodes andconnections between duties as arcs. Here, the minimization of the
distance of empty runs can be achieved by taking the distance into
account in the cost of the arcs.
In addition, we aim to reduce splitting and combining between
two duties. In this paper, we apply the idea described in Ref. [7]. We
provide information about the number of units and the position of
the first and last trains of the duty corresponding to each node. Here,the position means the geographical information; for example, it isdefined as 1, 2, ... from the west side of the composition. If the number of units or the position differs among the nodes to which eacharc connects, we add the cost of splitting or combining to the arc.
Otherwise, we use logical constraints to determine whether splitting
or combining takes place. If splitting or combining is required, we
add the cost of splitting or combining to the arc.
Figure 6 shows an example network of the TSP model. In thisexample, five duties are created in the duty generation algorithm ofStep 2. The start and end times, and the start and end stations of each
duty are given, so that it is possible to determine whether or not
empty runs take place between two nodes. Duty 3 and 4 include a
pre-departure inspection, and arcs connecting to these nodes areshown in red. We seek the least-cost cyclic path that passes throughall nodes once and satisfies the inspection constraints on this network.
The following is an outline of the formulation as a mathematical optimization problem (see Ref. [8] for details).
<Objective function>
The distance of empty runs between duties + δ × the number oftimes there are splitting and combining between duties (to be minimized)
Note that δ is a weight parameter.
<Constraints>
・ Cyclic constraints (only one arc entering each node is selected, and only one arc exiting from each node is selected)
・ Subtour elimination constraints
・ Inspection interval constraints of pre-departure inspection・ Logical constraints for detecting splitting and combining
185

Table 1 Characteristics of each instance using casestudies.

Fig. 6

・

Example of traveling salesman model

between duties
Constraints on possible values of each variable

4. Case study
4.1 Lines and settings
In order to evaluate the effectiveness of the proposed method,
we show the result of a case study with the restoration phase after alarge-scale natural disaster that actually occurred in the past. We
compare the actual rolling stock schedule and the plan created by
the proposed method for the temporary timetable at that time.
In this case, the operating section has been extended over several phases. Among them, we test the proposed algorithm using
three temporary timetables (called instances (a)-(c)). Instance (a) is
the initial stage of the resumption of operations, instance (b) is a few
days later, and instance (c) is a few days after instance (b). The number of trains and unit types are shown in Table 1 as the scale of the
problem. While there is almost no change in (a) and (b), both thenumber of trains and the number of unit types increase in (b) and (c).
The reason for this is that the operating section is extended to thestation adjacent to a rolling stock depot in (c), which allows a large
number of trains to operate on the line.
In order to compare the results as closely as possible with theactual schedule at that time, we set the minimum and maximum
number of cars for each train, the unit types that could be assigned,
etc., based on the basic schedule and the actual schedule at that time.
The weight parameters of the objective function in the formulation
are uniformly set to α = 0.001, β = 0.001, γ = 0.1, δ = 0.01. We use
a PC with Core i7-8700K CPU and 64 GB memory for the calculations and use Gurobi Optimizer 9.5.1 [9]) to solve the mathematicaloptimization problem.
4.2 Results of computational experiments
Table 2 shows the results of applying the proposed algorithm toinstances (a), (b), and (c). The number of duties, the number of times
there are splitting and combining, the distance of empty runs, andthe number of schedule differences are shown in the table as evaluation criteria. In addition, each index of the actual schedule at thattime is also shown. The maximum calculation time for the duty
generation is set to 3,600 seconds. We can obtain an optimal solu186

tion in less than 1 second in the roster generation problem.
We can find that all evaluation criteria are almost the same or
reduced compared with the actual schedule at that time in instances(a) and (b), so the result indicates that an efficient schedule has been
generated. On the other hand, in instance (c), although the numberof duties is the same, the number of times there are splitting andcombining, and the distance of empty runs have increased comparedwith the actual schedule at that time, indicating that the createdschedule is not efficient. In particular, the distance of empty runs has
increased significantly. The reason for this is that the number of unit
types is high and the number of duties for each type is relatively
small in instance (c), so that the distance of empty runs increases
when a roster is created from the generated duties. In addition, the
GAP, which is an index for the calculation accuracy of a mathematical optimization problem, remains high even after 3,600 seconds.
Therefore, we can find that the problem size of instance (c) is relatively large.
Based on the above, we try to fix the number of duties uniformly to reduce the computational load as much as possible. This reduction in the number of evaluation criteria allows for a more efficient
search. As a result, a more efficient schedule can be obtained.
Table 3 shows the results when the number of duties in instance (c)is fixed at 72 to 74. The maximum calculation time for the duty
generation is set to 3,600 seconds, as before. We can find that thesolutions can be obtained even when the number of duties is fixed at
73 and 74 duties. Although the number of times there are splitting
and combining, and the distance of empty runs are the same orslightly greater than those in the schedule at that time, the number ofduties is small. So, the solution with a fixed number of duties can be
acceptable. Therefore, it is a very effective way to fix the number ofduties and narrow the feasible region to create an efficient rollingstock schedule.
5. Conclusions
In this work, we focus on rolling stock scheduling after a largescale disaster, and develop an automatic scheduling algorithm basedon a mathematical optimization method for the temporary timetable.
The proposed algorithm makes it possible to generate a rolling stock
schedule that is as close as possible to the original schedule at thetime of the train timetable revision.
We adopt a two-phase method in which the process is divided
into generating duties and generating rosters. The duty generation
problem is modeled as a multi-commodity network flow problem.
Then, the roster generation problem is modeled as a Traveling
Salesman Problem. In addition, we show the results of case studies
using data from real lines and real disrupted cases due to a largescale natural disaster and confirm that the proposed algorithm cangenerate a practical rolling stock plan in a short time. In the future,
we will apply the proposed method to other lines and put it into
practical use as soon as possible.
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Table 2

Table 3Results of instances (a), (b) and (c)Results of instance (c) fixed the number of duties

References[1]	Reuther, M. and Schlechte, T., “Optimization of rolling stock
rotations,” In Borndörfer, R., Klug, T., Lamorgese, L., Mannino,C., Reuther, M., and Schlechte, T. (Eds.), Handbook of
optimization in the railway industry, pp. 243-264, Springer
International Publishing, 2018.
[2]	Alfieri, A., Groot, R., Kroon, L., and Schrijver, A., “Efficient
circulation of railway rolling stock,” Transportation Science,Vol. 40, No. 3, pp. 378-391, 2006.
[3]	Cacchiani, V., Caprara, A., and Toth, P., “Solving a real-world
train-unit assignment problem,” Mathematical Programming,Vol. 124, pp. 207-231, 2010.
[4]	Giacco, G., Ariano, A. D., and Pacciarelli, D., “Rolling stockrostering optimization under maintenance constraints,” Journalof Intelligent Transportation Systems, Vol. 18, No. 1, pp. 95105, 2014.
[5]	Imaizumi, J., Yamagishi, Y., and Morito, S., “A two-phasemathematical programming approach for rolling stock

circulation problem,” Transactions of the Operations ResearchSociety of Japan, Vol. 53, pp. 14-29, 2010 (in Japanese).
[6]	Nishi, T., Ohno, A., Inuiguchi, M., Takahashi, S., and Ueda, K.,“A combined column generation and heuristics for railway
short-term rolling stock planning with regular inspection
constraints,” Computers and Operations Research, Vol. 81, pp.
14-25, 2017.
[7]	Kato, S., Fukumura, N., Morito, S., Goto, K., and Nakamura,N., “A mixed integer linear programming approach to a rollingstock rostering problem with splitting and combining,”
presented at the 8th International Conference on Railway
Operations Modelling and Analysis, Norrkoping, Sweden, June
17-20, 2019.
[8]	Kato, S., Imaizumi, J., Nakahigashi, and T., Kokubo, T.,“Optimization approach to rolling stock scheduling for timetabletemporarily changed due to disaster,” IEEJ Journal of Industry
Applications, Vol. 143, No. 5, pp. 405-416, 2023 (in Japanese).
[9]	Gurobi Optimizer, https://www.gurobi.com/solutions/gurobioptimizer/ (Reference date: June 4, 2024).

Authors
Satoshi KATO

Senior Researcher, Operation Systems
Laboratory, Signalling and Operation
Systems Technology Division
Research Areas: Transportation Planning,
Mathematical Optimization
Jun IMAIZUMI, Dr.Eng.

Professor, Toyo University
Research Areas: Operations Research,
Scheduling

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Taichi NAKAHIGASHI

Researcher, Operation Systems Laboratory,
Signalling and Operation Systems
Technology Division
Research Areas: Transportation Planning,
Train Rescheduling
Tatsuya KOKUBO

Researcher, Operation Systems Laboratory,
Signalling and Operation Systems
Technology Division
Research Areas: Transportation Planning,
Maintenance Worker Scheduling

187

PAPER

Cage Wear Prediction for Traction Motor Bearings of Railway Vehicles
Based on Measurement of Contact Force between Rolling Element and Cage
Daisuke SUZUKI
Ken TAKAHASHI
Yoshiaki OKAMURA
Lubricating Materials Laboratory, Material Technology Division
Fumihiro ITOIGAWA
Satoru MAEGAWA
Nagoya Institute of Technology, Department of Electrical and Mechanical Engineering
Traction motor bearings of railway vehicles are used at high rotational speeds and under light loads, sothat their life is determined by cage wear rather than raceway flaking. In this study, the contact forces
between the rolling elements and the cage were measured to predict cage wear. As a result, the magnitude,
duration, and frequency of the forces were obtained. In addition, the forces were integrated with time toobtain impulses to show the relationship between impulses and cage wear.
Key words: machine element, tribology, traction motor, cylindrical roller bearing, cage wear
1. Introduction
Traction motor bearings support the rotor of traction motors ofrailway vehicles. Because these bearings are operated at high rotational speeds and under light loads, they are often replaced due tocage wear (wear life) rather than raceway flaking (fatigue life).
Consequently, bearings must be replaced in a much shorter timethan the calculated fatigue life [1]. However, there is no method forpredicting cage wear under such operating conditions, making it
difficult to determine the appropriate bearing life. Since cage wear
occurs at the contact area between the rolling elements and the cage,
it is necessary to measure and analyze the motion and the contact
force between the rolling elements and the cage for predicting cagewear.
The rotational speed of the traction motor bearing varies widely
depending on the acceleration and deceleration of the railway vehicles. It is known that when a bearing is used over a wide range ofrotational speeds, the cage whirl motion changes with the rotational
speed [2]. The cage whirl motion at low rotational speeds is in asmall oscillating state. As the rotational speed increases, the cage
whirl motion becomes a circular motion through a transient state.
Because the contact force between the rolling element and the cageis affected by the cage whirl motion, it is necessary to observe thecontact force over a wide range of rotational speeds, including thetransition of the cage whirl motion. There have been several studies
on measurement of the contact force between a rolling element anda cage in rolling bearings [3, 4]. However, the contact force wasmeasured with the constraining cage whirl motion, and there havebeen no cases in which the contact force has been measured andanalyzed under the condition of cage whirl. In this study, a measurement system capable of simultaneously measuring contact force andcage whirl motion without constraining the cage whirl motion isconstructed to conduct measurements over a wide range of rotational speeds. Based on the measurement results, the volume of cage
wear is discussed [5].

Generally, deep groove ball bearings and cylindrical roller bearings
are used in traction motor bearings, among which cylindrical roller
bearings are targeted in this study. The bearing number is NU214,
which is widely used in traction motor bearings. The inner ring,outer ring and rollers are made of bearing steel, and the cage is madeof high-strength brass. Because the cage is guided by the rolling elements, the cage does not contact any parts other than the rollers.
The target bearings are designed for traction motors, but their specifications are almost the same as those of general-purpose products.
In order to eliminate the influence of the roller diameter variation on
the measurement, the roller diameter difference among each otherwas kept below 2 μm in the bearing.
2.2 Method for measuring contact force
The contact forces between the roller and the cage were measured directly by two small load cells (LMA-A-100NM81Z050,
KYOWA ELECTRONIC INSTRUMENTS CO., LTD.) attached to
one of the 16 pockets as shown in Fig. 1. The curved surfaces of thecage pocket were removed by machining and load cell attachment
points were provided. The load cells were bonded to these points sothat they were parallel to each other and the distance between themwas equal to the diameter of the cage pocket. These load cells canmeasure two types of forces at the front and rear of the cage pocket.
Table 1 Specifications of target bearing

2. Materials and methods
2.1 Target bearing
The specifications of the target bearing are shown in Table 1.
188

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In this paper, the force that the roller pushes the cage in the directionof cage rotation is referred to as the “force to accelerate the cage”
and the force that the roller pushes the cage in the opposite directionof cage rotation is referred to as the “force to decelerate the cage.”
Figure 1 shows these forces when the direction of cage rotation is
forward (counterclockwise). It also shows the coordinate system
and angles used to display the measurement results. The angle isdefined as 0° at the center of the no-load zone (vertically above);
180° at the center of the load zone (vertically below). It should be
noted that the angle increases with the direction of rotation.

affected by cage deformation and roundness. However, they do notaffect the relative comparison of measurement results because theseare sufficiently small compared to cage whirl motion and the same
cage is used for all measurements.

2.3 Method for measuring cage whirl motion
The cage whirl motion was measured by two laser displacement meters (LK-G35A, KEYENCE CORPORATION) attached tothe housing as shown in Fig. 2. One of the two laser displacement
meters measured displacement in the x-direction and the other in they-direction. The bearing housing and the outer ring were machinedwith the minimum necessary notches that would not interfere withthe laser beams. Although the displacement that should be measured
is at the center of the cage, the displacement measured with thismeasuring system is strictly different from the cage center displacement because the displacement is measured at the outer diameter ofthe cage and the displacements in the x and y directions are not independent (when the cage moves in the x-direction, the measured
displacements change not only in the x-direction but also in they-direction). However, since the outer diameter of the cage is sufficiently large compared with the diameter of the cage whirl motion,
the accuracy of the cage whirl motion measurement is sufficienteven if this difference is ignored. This measurement system is also

Fig. 2 Method for measuring cage whirl motion
2.4 Method for measuring contact force without constraining
cage motion
Figure 3 shows a schematic diagram of a test rig capable ofmeasuring the contact force between the roller and the cage without
constraining the motion of the cage. The test rig allows the test bearing to rotate at any rotational speed and radial load within specifications. The shaft, one end of which is directly connected to the motor
by a coupling, is supported by a test bearing and a support bearing(a). The rotational speed is controlled by a programmable logic controller (hereinafter referred to as PLC), and the r adial load is applied
by a spring through the support bearings (b) of the shaft. The radialload direction is vertically downward, and the load zone of the test
bearing is also vertically downward (around 180° in Fig. 1). In order
to wire the load cells attached to the rotating cage without constraining the motion of the cage, a rotor synchronized in rotation with thecage was placed in front of the cage, and the wiring was made fromthe load cells to this rotor. The wires are thin and light enough sothat their tension does not restrict the motion of the cage. These
wires are connected from the rotor to the load cell amplifier via aslip ring. Synchronization between the cage and the rotor wasachieved by sending a command for the cage rotational speed, measured by the photoelectric sensor, from the PLC to the servo motor
used to rotate the rotor. Both the measured contact force between theroller and the cage and the cage whirl motion are simultaneously
recorded in a data logger.
2.5 Measurement conditions

Fig. 1

Method for measuring contact force

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Measurement conditions are listed in Table 2. The radial load
was set at 970 N, which is the weight of the rotor supported by thebearings in the traction motor. This load is approximately 1.2% of
the basic dynamic load rating of the test bearing (83500 N). Lithium
complex soap grease was used for lubrication. A thin layer of grease
was applied to the inner ring and then spread over each part of the189

Fig. 3

Schematic diagram of test rig

bearing by rotating the bearing so that the amount of grease was theminimum required for lubrication. The direction of rotation wasboth forward and reverse, and the rotational speed was varied from500, 1000, 2000, 3000 and 4000 /min to check the effect of rotational speed on the contact force between the roller and the cage. If
similar data can be obtained in both directions of rotation, it can beshown that there is no bearing misalignment or load cell instrumentation error. Data were recorded at a sampling frequency of 10 kHz
until the cage reached 100 rotations under each condition.
Table 2

Measurement conditions

3. Results
3.1 Contact force between roller and cage
Figure 4 shows the measurement results of the contact force
between the roller and the cage at rotational speeds of 1000 /min and3000 /min. Here, the time when the pocket is positioned at 0° as
shown in Fig. 1 is set to 0 s, and the measurement results until thecage completes one rotation are shown for each direction of rotation
and rotational speed. Because the time required for the cage to complete one rotation is the same as the time calculated from the theoretical rotational speed of the cage, cage slip does not occur. In eachgraph, the black line in the top row indicates the “force to accelerate
the cage” and the red line in the bottom row indicates the “force todecelerate the cage.” The area corresponding to the load zone isshaded. The graphs represent 10 rotations of the 100 rotations of thecage that were measured under each condition. The “force to accelerate the cage” tends to be generated continuously from the center tothe exit of the load zone. This is because the roller is accelerated by
the traction of the inner and outer rings in the load zone and contacts
the front part of the cage pocket. On the other hand, the “force todecelerate the cage” tends to be generated intermittently after exiting the load zone. This is because the roller is repeatedly decelerated
by the oil pressure force and accelerated by the contact with the back190

part of the cage pocket. At a rotational speed of 1000 /min, the“force to accelerate the cage” is also generated from the entry to thecenter of the load zone. This is considered to be caused by the cage
pushing the roller that is difficult to enter the load zone, but the reason why the roller is difficult to enter the load zone and the reason
why this does not occur at other rotational speeds are unknown.
Next, in order to evaluate not only the contact force but also thecontact time, the contact force measurement results in Fig. 4 were
integrated with time to obtain the impulse. Figure 5 shows an example of the change in the impulse during one rotation of the cage
when the rotational speed is 1000 /min and 3000 /min. All 100 cage
rotations measured are shown. Because the trend was the same regardless of the direction of rotation, only the results for forward rotation are shown in Fig. 5. Integration was started just before eachforce was generated. The “force to accelerate the cage” started theintegration when the roller passed through the entrance of the loadzone, and the “force to decelerate the cage” started the integration
when the roller passed through the exit of the load zone. The area
corresponding to the load zone is also shaded. The impulse obtained
from the “force to accelerate the cage” increased rapidly from thecenter to the exit of the load zone and then remained almost constant. In addition, during the 100 rotations of the cage, there arecases where the impulse increases significantly and other cases
where it does not. These results indicate that the momentum exchange between the roller and the cage caused by the “force to accelerate the cage” is mostly generated in the load zone and is notalways generated with each cage rotation. On the other hand, theimpulse obtained from the “force to decelerate the cage” gradually
increases from the exit of the load zone. At a rotational speed of1000 /min, the impulse becomes constant after the roller passes
through half of the no-load zone, while at a rotational speed of​3000 /min, the impulse continues to increase. In summary, the momentum exchange between the rollers and the cage due to the “force
to decelerate the cage” occurs intermittently until the rollers and thecage reach the same speed or until the roller reaches the load zone,
and is a highly reproducible phenomenon for each cage rotation.
Based on the above results, Fig. 6 shows the result of averaging
the impulse per cage rotation for each measurement condition. The
error bars in the figure indicate the standard deviations (note: negative values are not measured). The impulses per cage rotation obtained from the “force to accelerate the cage” and the “force to decelerate the cage” are close, with both decreasing up to 2000 /min
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Fig. 4

Measurement result of contact force

Fig. 5

Impulse obtained from contact force

191

and remaining almost constant above that. Considering that the rotational speed of the cage is almost constant and that the cage is not
subjected to any external force other than that from the rollers, thecloseness of these values is considered reasonable. Furthermore, thestandard deviation of the impulse obtained from the “force to accelerate the cage” is larger. This is because the work to accelerate thecage does not always occur in all the cage pockets, but occurs in thecage pocket located in the load zone when the cage rotational speed
decreases slightly.
3.2 Cage whirl
Figure 7 shows the measurement results of the cage whirl motion. This figure shows the measurement results for 10 rotations of
the cage under the conditions of each rotational speed according to
the coordinate system shown in Fig. 1 and Fig. 2. Note that the cage
rotates counterclockwise during forward rotation and clockwise
during reverse rotation. In forward and reverse rotation, the cage
whirl motions show almost the same behavior in y-axis symmetry
with respect to each other. The cage whirl motion oscillates mainly
to the left and right in the lower part of the figure under the condition
that the rotational speed is less than 1000 /min. This is because thecage hangs down with the roller at about 0° and oscillates to the leftor right. As the rotational speed increases, the center of this oscillation moves in the direction of the cage rotation, and the cage whirl
motion becomes circular when the rotational speed exceeds 3000 /min. At a rotational speed of 2000 /min, the cage whirl motion is in
the above two transition states. As the rotational speed increases, themain force that translates the cage changes from gravity and contact
force with the rollers to centrifugal force generated by the weight
imbalance of the cage, which is considered to have changed theshape of the cage whirl motion. In addition, because the cage whirl
motion changes with the rotational speed, it is thought that a measurement system that does not constrain the cage can be achieved.


4. Discussion
The volume of cage wear V is discussed based on the measurement results. Assuming that the wear type of the cage is adhesive
wear, V follows Archard’s equation [6] shown below.

Fig. 7
192

Fig. 6 Impulse per cage rotation(1)=

where K is the wear coefficient, W is the load, L is the sliding
distance and H is the hardness of the softer material (in the case ofthis study, the hardness of the cage). Since K and H do not vary with

Measurement result of cage whirl motion
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the measurement conditions, V is proportional to WL. In the case ofcage wear, W is the contact force between the roller and the cage F,
which varies with time and is not a constant value. Therefore, toobtain WL from the varying F, F was integrated with L. Since L is
obtained by the product of the circumferential speed of the rollersrω (where r is the roller radius and ω is the angular velocity of theroller) and time t, WL is given by the following equation.


=

=

∙

(2)

From (2), WL is the product of the impulse caused by F and rω.
In order to compare V per cage rotation Vrot between each measurement condition, WL per cage rotation WLrot was obtained and isshown in Fig. 8. To obtain WLrot, the impulse per cage revolution
shown in Fig. 6 and the theoretically calculated rω were used. WLrot
obtained from the “force to accelerate the cage” and the “force todecelerate the cage” both show a tendency to increase in proportion
to the rotational speed. However, WLrot at rotational speed of 500 /min and 1000 /min is above the straight line approximating the origin and the values at rotational speed of 2000 /min to 4000 /min.
From the above, it can be seen that Vrot decreases as the rotational
speed decreases, but the degree of the decrease is smaller at 500 /min and 1000 /min. This result is due to the relatively greater effectof gravity acting on the rollers at lower rotational speeds (see Ref.

[7] for details). From the above, if K is determined, V can be predicted quantitatively. Even if K is not determined, it is possible to predict how much V will change when the operating conditions arechanged.
5. Conclusions
To predict cage wear in traction motor bearings, it is necessary
to measure and analyze the motion and contact force between theroller and the cage. For this purpose, a measurement system wasconstructed to simultaneously measure the contact force and thecage whirl motion without constraining the cage motion. Using theconstructed system, measurements were made over a wide range ofrotational speeds. In addition to the measurement, the relationshipbetween the contact force and the cage wear was discussed. As aresult, the following findings were obtained.
(1) As a result of the contact force measurements, the “force toaccelerate the cage” occurred continuously from the center tothe exit of the load zone. This is because the roller is accelerated by the traction of the inner and outer rings in the load zone
and contacts the front part of the cage pocket. On the other
hand, the “force to decelerate the cage” occurred intermittently
after exiting the load zone. This is because the roller is repeatedly decelerated by the oil pressure force and accelerated by
the contact with the back part of the cage pocket.
(2) The result of integrating the contact force measured in (1) withtime to obtain the impulse per cage revolution showed that theimpulse per cage rotation obtained from the “force to accelerate the cage” and the “force to decelerate the cage” were close,
both decreasing up to 2000 /min of rotational speed and almost
constant above that.
(3) The cage whirl motion oscillated mainly to the left and right in
the lower part under the condition that the rotational speed isless than 1000 /min. As the rotational speed increased, thecenter of this oscillation moved in the direction of the cage
rotation, and the cage whirl motion became circular when therotational speed exceeded 3000 /min. At a rotational speed of2000 /min, the cage whirl motion was in the above two transition states.
(4) Assuming that the volume of cage wear V is proportional to the
product of the contact force and the sliding distance WL, WL
was derived using the impulse obtained in (2). As a result, V
per cage rotation is considered to increase as the rotational
speed increases.
References

Fig. 8WL per cage rotation

QR of RTRI, Vol. 65, No. 3, Aug. 2024[1]	International Organization for Standardization, “Rolling
bearings - Dynamic load ratings and rating life,” ISO 281: 2007,2007.
[2]	Tada, S., “Analysis of sound, vibration and motion cages duringhigh-speed rotation,” KOYO Engineering Journal, No. 160E,
pp. 29-36, 2002.
[3]	Kakuta, K., “The Effects of Misalignment on the Forces Acting
on the Retainer of Ball Bearings,” Journal of Basic Engineering,Vol. 86, No. 3, pp. 449-454, 1964.
[4]	Stacke, L-E. and Fritzson, D., “Dynamic behavior of rolling
bearings: simulations and experiments,” Proceedings of theInstitution of Mechanical Engineers, Part J: Journal ofEngineering Tribology, Vol. 215, No. 6, pp. 499-508, 2001.
193

[5]	Suzuki, D., Takahashi, K., Itoigawa, F. and Maegawa, S.,“Contact forces between roller and cage pocket in cylindricalroller bearings (Consideration based on dynamic behavior
between roller and cage),” Transactions of the JSME, Vol. 88,
No. 911, DOI:10.1299/transjsme.22-00153, 2022 (in Japanese).
[6]	Archard, J.F., “Contact and Rubbing of Flat Surfaces,” Journalof Applied Physics, Vol. 24, No. 8, p. 981, 1953.
[7]	Suzuki, D., Takahashi, K., Itoigawa, F. and Maegawa, S.,“Study on Cage Wear of Railway Traction Motor Bearings
Based on Analysis of Rolling Element Motion,” Machines, Vol.
11, No. 6, p. 594, DOI:10.3390/machines11060594, 2023.

Authors
Daisuke SUZUKI, Dr.Eng.

Assistant Senior Researcher, Lubricating
Materials Laboratory, Material Technology
Division
Research Areas: Tribology, Machine
Elements, Rolling Bearings
Ken TAKAHASHI, Ph.D.

Senior Researcher, Lubricating Materials
Laboratory, Material Technology Division
Research Areas: Tribology, Machine
Elements, Rolling Bearings

Fumihiro ITOIGAWA, Dr.Eng.

Professor, Department of Electrical andMechanical Engineering, Nagoya Institute ofTechnology
Research Areas: Manufacturing and
Production Engineering, Design Engineering,
Machine Elements and Tribology
Satoru MAEGAWA, Dr.Eng.

Associate Professor, Department of Electricaland Mechanical Engineering, Nagoya
Institute of Technology
Research Areas: Design Engineering,
Machine Elements and Tribology

Yoshiaki OKAMURA, Ph.D.

Senior Chief Researcher, Head of Lubricating
Materials Laboratory, Material Technology
Division
Research Areas: Tribology, Machine
Elements, Rolling Bearings

194

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REVIEW

Outline of Design Standard and Commentary for Railway Structures (Concrete Structures)
Ken WATANABE
Concrete Structures Laboratory, Structures Technology Division
Toshiya TADOKORO
Concrete Structures Laboratory, Structures Technology Division (Former)
Manabu IKEDA
Structural Mechanics Laboratory, Railway Dynamics Division
Masaru OKAMOTO
Steel and Hybrid Structures Laboratory, Structures Technology Division (Former)
Design Standard and Commentary for Railway Structures (Concrete Structures) was revised in Januaryof 2023. In this revision, in addition to reorganization of the previous design standards established mainlyfor each type of structure and material, the introduction of the latest verification techniques has made thedesign standards easier to use. The application of the revised design standards to design practice will
improve railway structures.
Key words: concrete structures, basic principle, structural units, parts/members
1. Introduction
A notification for “Design Standards for Railway Structures(Concrete Structures)” was issued in December 2022. This paper
presents an overview of the revision of the “Design Standard forRailway Structures and its Commentary (Concrete Structures)” [1](hereinafter referred to as “the Standard”), which was published in
January 2023.
2. Background of the revision
2.1 Technical standard system for design of railway structures
The “Ministerial Ordinance to Provide Technical Standards forRailways” [2] (hereinafter referred to as “Ministerial Ordinance on
Technical Standards”) was revised to the performance-based designin December 2001. The Ministerial Ordinance on Technical Standards stipulates in Article-1 that the objective of the ordinance is “toensure safe and stable transportation, thereby contributing to thepromotion of welfare of the public.” That is to say, Article-1 of thisStandard requires infrastructure, rolling stock, etc. to be compatible
with train operations, etc. to ensure the safety of people and facilities, while being technically and economically feasible. Article-24of the ordinance stipulates the function of railway civil structures:that “earthworks, bridges, tunnels, and other structures shall be capable of withstanding anticipated loads; and not impede the runningsafety of rolling stock due to displacement of the structure caused bytrain loads, impacts, etc.
The Design Standard for Railway Structures and its Commentary (hereinafter referred to as the “Design Standard”) is an interpretation standard (notification). It is a non-mandatory, numerically
expressed, practical interpretation of the Ordinance of the Ministryof Engineering Standards, and a commentary that summarizes therationale for the interpretation standard and concept, etc. All DesignStandards were changed to performance-based design by FY2022.

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2.2 History of Revision of Design Standards for Railway Concrete Structures
Table 1 shows the evolution of the technical standards for railway concrete structures. Initially, the design and construction of
concrete structures was left to the discretion of engineers. In 1914, a
corpus of knowledge on reinforced concrete bridges was established, signaling the beginning of a harmonized approach. This
formed the basis for the Standard Specifications for Concrete Structures of the Japan Society of Civil Engineers (JSCE). These standards were published in two volumes in 1955: the first volume on
general provisions covered specifications for common themes suchas loads and stresses; and the second volume on specific provisions,covered details about characteristics of specific members such as
slabs, beams, and columns. In 1970, standards for conventional andShinkansen lines were integrated. Following two further revisions,in 1992, the “Design Standards” adopted a limit state design method. The allowable stress design method, which had been used until
then, is a design method that verifies that the stress acting on eachsection of a member is less than or equal to the allowable stress ofthe material constituting the member. On the other hands, the limit
state design method sets limit states for each required performanceand verifies that the limit values set for each limit state are satisfied.
As a result of this change, safety coefficients were set for each action, material, and structural analysis method, etc. This made iteasier to integrate technological advances. In addition, it made relatively easier for designers to be more clearly aware of the conditionof structures from the verification results.
In response to performance requirements of the Ministerial
Ordinance on Technical Standards, the Design Standards for Railway Structures and its Commentary (Concrete Structures) [3] (hereinafter referred to as the 2004 Concrete Standard), revised in 2004,
introduced performance-based design. This is a design method inwhich the required performance of structures is specified, and thelimit state design method is followed as a verification method. It isalso a design method that is more flexible for the adoption and application of new materials and structures, is conducive to interna195

Table 1

Revision history of Design Standards for Railway Concrete Structures, etc.

tional harmonization, and is highly compatible in maintenance. This
standard, revised in 2023, follows the performance-based designand has been revised in accordance with the issues and policies described in the following sections.
2.3 Issues surrounding railway concrete structures
The following is a list of recent issues surrounding railway
concrete structures with expected responses:●	 Design standards today are organized according to type ofstructural material, such as concrete structures, steel structuresand composite structures, etc., by type of structure, such as
tunnels, etc., or by actions and type of verification, such as
displacement limitations and seismic design. This categorization approach complicates application of these designs in practice. In response to this complexity, it would be clearer for design standards to be grouped type of structure, and for the
relationship to be clarified between structures and different
parts and materials that make up the railroad system.
●	There is an absence of a uniform approach to design and design
related action in the current design standards [4]: this should be
addressed by adopting common design concepts and referring
to a common set of basic themes and topics for railway structures that constitute the railway system.
●	Structural plans which establish the types, specifications, etc.
196

of structures as a preliminary stage of verification should be
included, in order to facilitate the design of practical structures
which meet performance requirements.
●	In order to design safe and economically viable concrete structures, the scope of application of conventional standard verification methods needs to be clarified. This would allow the latest analytical methods to be applied to complex structures andactions for which conventional verification methods are nolonger suitable.
●	In response to changes in the type of aggregates used on a daily
basis and durability problems of concrete structures, steps
should be taken to ensure the serviceable-life performance ofstructures by design, which takes into account local conditions,such as the characteristics of the materials at the construction
site and the effects of weather during service.
●	Design methods should consider questions about actual construction, and take into account conditions needed for construction and the problem of shrinking numbers of construction
workers.
●	Considering the damage caused by the 2011 off the Pacificcoast of Tohoku Earthquake and the 2016 Kumamoto Earthquake, structure designs should be conducive to early restoration in the wake of increasingly sever natural disasters.
Following the identification of these issues, a “Committee on
Design Standards for Railway Concrete Structures” was established
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in FY2016 and studied these issues for four years.
3. Outline of the revision
3.1 Basic policy
It is now over 18 years since the 2004 Concrete Standards were
published. Therefore, it was decided they should be reviewed in thelight of latest technology and other developments related to concrete
structures. It was also decided that the structure of presenting thesestandards should change in a way which enable railway structures tofunction more organically as a railway system. In light of the rapidchanges in social conditions and the circumstances surrounding therailway business as shown in 2.3, efforts were made to review therailway-specific technologies and supplement them with the latest
technologies, referring to the research results of the Railway Technical Research Institute and the JSCE Standard Specifications forConcrete (Design) [5], etc., enacted in 2017. In addition, as a standard for interpretation, we have tried to show concrete figures andspecifications. On the other hand, in cases where it is difficult toshow with concrete figures and specifications, we have tried to show
design methods and methods of verification, etc. [1].
3.2 Overall structure of the design standards
The railway system is composed of railway structures such as
bridges, earth structures, and tunnels. Consequently, it makes sense
for them to share a common set of basics such as design concepts,
setting of performance requirements, and verifications. Therefore,
the new standards discuss basic principles [4] for all structures andreorganize the system of design standards. Specifically, a new chapter of basic principles (Layer-1) was added to summarize the design
basics for all railway structures covered by the design standard, notlimited to concrete structures. The structures and structural units(Layer-2) summarizes matters related to the design of structures andstructural units. This chapter creates the link between the common
basic principles and the design of each structure. The section onparts and members (Layer-3) specifies materials and structures necessary for design, and summarizes matters related to the design ofparts and members that constitute structural units (Fig. 1). This

Standard consists of the following four parts.
●	Part I Basic Principles: specifies matters common to the designof railway structures, such as required performance and design
service life. [4]●	Part II Bridge Structures: Based on Part I, the structural planning, actions, structural analysis, and verification methods forbridges (including elevated bridges) are specified. [6]●	Part III Concrete Structures: Based on Part I and Part II, theapplicable requirements, response values, limit values, etc. are
specified for each part and member of concrete structures. [7]●	Part IV Bearing Structures: Based on Part I and Part II, the applicable requirements, response values, limit values, etc. forbearings of concrete bridges are specified. It is assumed that therequirements will be applied to bearings for steel and composite bridge structures in the future. [8]In principle, the verification of bridge structures is performedon the structural units of the bridge, such as bridge girders, piers,
etc., in accordance with the Part II Bridge Structures. When verification is performed on structural units, the bridge mass is considered
to satisfy verification by making sure that all structural units satisfy
verification. However, under general design conditions, as in thepast, verification may be performed on structural units such as
beams, bearings, piers, footings, piles, and so on. In this case, thestructural unit satisfies the verification requirements by making surethat all parts and members satisfy the verification requirements inaccordance with the Part III Concrete Structures and the Part IV
Bearing Structures.
Figure 2 shows how the 2004 Concrete Standard and related
standards have been transferred to the various parts of this standard.
Other items related to the part II, III, and IV from the related standards [9]-[14] have been transferred in the respective sections. In
addition, Part I Basic Principles was based on all the design standards [9]-[18].
3.3 Basis of design
The term “railway system” is newly defined with reference to
the Ordinance of the Ministry of Technical Standards. In the designof the structure, the required performance and its level shall be defined according to the purpose as a railway system and the functionof the structure, and the structural plan, investigation and structuralFig. 1 System of design standards
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197

Fig. 2Major transfers from the 2004 Concrete Standard and related standards to this standard

details shall be established and verified. Here, although the structural planning is not described in the 2004 Concrete Standard, it wasadded in recognition that it is important for designing better structures. From the viewpoint of realizing a sustainable society, “compatibility with society”[4] and from the viewpoint of crisis resistance to prevent catastrophic damage to structures, “redundancy androbustness” [4] shall be required in structural planning and in setting
the required performance level.
3.4 Design methods for safety, etc.
In order to design safe and economically viable concrete bridges, the latest methods are described for complex structures and actions to which conventional verification methods cannot be applied.
In Part II Bridge, bridge structures are classified into structuralunits (girders, piers, abutments) and parts/members (beams, slabs,
foundation structures, bearings, etc.), so that each verification method is presented according to each classification. Verifications focusing on bridges or each structural unit enables more rational verification for non-stationary structures such as ramen viaducts, forexample, because the failure of one member does not immediately
lead to the limit state of the structure.
In Part III Concrete Structures, a method [19] for calculating
the design shear capacity of bar members with fixed supports at bothends, assuming members of a ramen viaduct, was introduced forshear capacity used in verifying the failure of concrete members,
etc. This method allows the shear span ratio to be calculated fromthe shear capacity of a bar member with fixed supports at both ends.
This method allows the shear reinforcement bars to have a greater
effect when the shear span ratio is smaller than that of bar members
under simply supported conditions with the same cross-sectional
properties. Furthermore, a verification method based on nonlinear
finite element analysis has been introduced and made applicable inaccordance with the JSCE Standard Specifications for Concrete[Design Edition] [5] enacted in 2017. The verification methods have198

been enhanced and made more sophisticated, allowing for more rational verification and more labor-saving verification for structureswith a proven track record. Engineers will thus be able to use theircreativity to develop flexible design solutions.
3.5 Design method considering regional specificity, aging axis,
etc.
Design methods considering the time axis and the study on
durability were reviewed. In the concrete structures section, a formula for calculating the shrinkage strain of concrete that can take
into account the effects of rainfall conditions at the construction siteand shrinkage of aggregate [20] and a new structural analysis method for predicting the long-term deformation of PC girders due toshrinkage and creep were presented. In the study on steel corrosion,
the previous “study on neutralization” was changed to “study on
corrosion of steel due to water penetration” [21], and the limit values of chloride ion concentration were updated to values corresponding to various cement and water binder ratios.
3.6 Design methods considering construction
In part III Concrete Structures, the introduction of technologies
that contribute to reliable construction and design methods that promote such technologies are described, including optimization of reinforcement quantity in precast structures and member joints [22],use of high-strength materials [23], evaluation of initial cracking
and long-term behavior of structures based on the construction process, and others.
3.7 Design methods for easily recoverable concrete structures
Based on the damage caused by the 2011 off the Pacific coast of
Tohoku Earthquake and the 2016 Kumamoto Earthquake, this section presents design methods for concrete structures that can be
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easily and quickly restored and whose performance can be ensured
even after recovery following an earthquake.
In Part II Bridge, aspects related to recovery and restoration,such as securing access roads and work yards for restoration workand controlling damage in areas that are difficult to repair, examples
of items that should be considered in the structural planning stage ofbridge structures are presented. In Part IV Bearing structures, forexample, it is shown that, in the case of a stopper embedded in abearing section, damage should be controlled at a point where it iseasy to repair, such as damage which occurs first to the front side of
the girder seat before the loose side of the girder end, rather thandamage occurring first at the loose side of the girder end, where repair work would be difficult. A more accurate calculation method forthe bearing capacity of embedded stoppers has been developed [24]that takes into account the arrangement of steel bars and other factors. The method makes it possible to control damage at points thatare easy to repair during earthquakes without increasing the amountof steel bars embedded in the stopper, thereby reducing restoration
costs and other expenses.
4. Summary
In this revision, the previous design standards, which were established mainly for each type of structure and material, were reorganized and the latest verification techniques were introduced toenable railway structures to function more organically as a railway
system. In addition, design calculation examples and design tools
will be developed sequentially. Amid demands for a sustainable society, it is hoped that the application of this standard to design practice will contribute to building better railway structures unconstrained by conventional forms. It is noted that the specific contentsof each item will be reported in detail in a separate paper.
Acknowledgment
This paper was discussed by the Committee on Standards for
Design of Concrete Structures. The authors would like to acknowledge the efforts of the committee chairman Dr. Junichiro Niwa (thenprofessor at Tokyo Institute of Technology), the secretary general
Dr. Tadatomo Watanabe (then vice president of Hokubu Consultants), and all the committee members and secretaries for their deliberations.
References[1]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Concrete
Structures), Maruzen Publishing, 2023 (in Japanese).
[2]	Ministry of Land, Infrastructure, Transport and Tourism,
Railway Bureau, Technical Standards for Railways (Civil
Engineering), Fourth Edition, 2023 (in Japanese).
[3]	Ministry of Land, Infrastructure, Transport and Tourism, andRailway Technical Research Institute, Design Standards forRailway Structures and Commentary (Concrete Structures),
Maruzen Publishing, 2004 (in Japanese).
[4]	Tadokoro, T., Watanabe, K., Ikeda, M. and Okamoto, M.,
Design Standard and Commentary for Railway Structures(Concrete Structures) Outline of “Part I:General Principles,”QR of RTRI, Vol. 65, No. 3, Aug. 2024

RTRI Report, Vol. 37, No. 11, pp. 7-13, 2023 (in Japanese).
[5]	Japan Society of Civil Engineers, Standard Specifications forConcrete Structures -2007 [Design], Maruzen Publishing, 2018
(in Japanese).
[6]	Watanabe, K., Ikeda, M. and Okamoto, M., Design Standard
and Commentary for Railway Structures (Concrete Structures)
Outline of “Part II: Bridge Structures,” RTRI Report, Vol. 37,
No. 11, pp. 15-23, 2023 (in Japanese).
[7]	Watanabe, K., Nakata, Y. and Todoroki, S., Design Standard
and Commentary for Railway Structures (Concrete Structures)
Outline of “Part III: Concrete Structure,” RTRI Report, Vol. 37,
No. 11, pp. 25-33, 2023 (in Japanese).
[8]	Ikeda, M., Tadokoro, T., Todoroki, S. and Toyooka, A., DesignStandard and Commentary for Railway Structures (Concrete
Structures) Outline of “Part IV: Bearing Structures,” RTRI
Report, Vol. 37, No. 11, pp. 35-40, 2023 (in Japanese).
[9]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary(Displacement limits), Maruzen Publishing, 2006 (in Japanese).
[10]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Seismic
Design), Maruzen Publishing, 2012.
[11]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (SteelConcrete Hybrid Structures), Maruzen Publishing, 2016 (inJapanese).
[12]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Foundation
Structures), Maruzen Publishing, 2012 (in Japanese).
[13]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Steel andComposite Structures), Maruzen Publishing, 2009 (in Japanese).
[14]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Earth
Retaining Structures), Maruzen Publishing, 2012 (in Japanese).
[15]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Earth
Structures), Maruzen Publishing, 2007 (in Japanese).
[16]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Cut andCover Tunnel), Maruzen Publishing, 2021 (in Japanese).
[17]	Ministry of Land, Infrastructure, Transport and Tourism (MLIT)
and Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Shield
Tunnel), Maruzen Publishing, 2022 (in Japanese).
[18]	Ministry of Land, Infrastructure, Transport and Tourism(MLIT), Railway Technical Research Institute (ed.), DesignStandards for Railway Structures and Commentary (Mountain
Tunnel), Maruzen Publishing, 2022 (in Japanese).
[19]	Nakata, Y., Watanabe, K., and Tadokoro, T., “Calculation
equation of shear capacity for RC beams subjected to fix
supported at both ends,” the 77th Annual Conference of JSCE,
2022, V-621 (in Japanese).
[20]	Watanabe, K., Nakamura, M., Ishida, T. and Watanabe, T.,
199

“Prediction Equation for Shrinkage Strain of Concrete
Considering the Effect of Mixed Cement,” RTRI Report, Vol.
37, No. 1, pp. 11-19, 2023 (in Japanese).
[21]	Todoroki, S., Ishida, T., Ueda, H. and Tadokoro, T., “Design
Method for Corrosion of Reinforcing Bars in Concrete
Structures by Water Penetration and Carbonation Progress,”
RTRI Report, Vol. 37, No. 10, pp. 1-8, 2023 (in Japanese).
[22]	Nakata, Y., Watanabe, K. and Tadokoro, T., “Influence ofStructural Details of Beam-to-column Joint in RC Viaducts on
Capacity,” RTRI Report, Vol. 37, No. 1, pp. 29-35, 2023 (inJapanese).

[23]	Sato, Y., Nakata, Y., Tadokoro, T. and Watanabe, K., “Thedamage properties and the applicability of deformation
performance calculation formula of RC columns using highstrength rebar,” Proc. of the JCI, Vol. 44, No. 2, pp. 175-180,2022 (in Japanese).
[24]	Todoroki, S., Mori, Y., Tadokoro, T. and Watanabe, K.,“Equation for Design Strength of Embedded Part of Square
Steel Stopper in Railway Bridge,” RTRI Report, Vol. 37, No. 1,
pp. 1-9, 2023 (in Japanese).

Authors
Ken WATANABE, Ph.D.
Senior Chief Researcher, Head of Concrete
Structures Laboratory, Structures Technology
Division
Research Areas: Design and Maintenance ofConcrete Structures

Manabu IKEDA, Dr.Eng.

Toshiya TADOKORO, Dr.Eng.

Masaru OKAMOTO, Dr.Eng.

Senior Chief Researcher, Head of Concrete
Structures Laboratory, Structures Technology
Division (Former)
Research Areas: Design and Maintenance ofConcrete Structures

200

Senior Chief Researcher, Head of Structural
Mechanics Laboratory, Railway Dynamics
Division
Research Areas: Hybrid Structures, Steel
Structures
Senior Chief Researcher, Head of Steel andHybrid Structures Laboratory, Structures
Technology Division (Former)
Research Areas: Hybrid Structures, Concrete
Structures

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REVIEW

Introduction Manual for Natural Frequency Identification System of Bridge Piers by
Constant Microtremor Measurement
Satoshi WATANABE
Hiroki IRI
Shoma FUJIWARA
Geo-hazard and risk mitigation Laboratory, Disaster Prevention Technology Division
In recent years, disasters have frequently occurred due to rapid river flooding and prolonged high waterlevels caused by typhoons and localized heavy rainfall. It is, therefore, necessary to establish a method formonitoring the destabilization of river piers during periods of rising water. In response to this need, we have
prepared an introduction manual for a natural frequency identification system, which includes an algorithm
for identifying the natural frequencies of piers from microtremor measurements, the basic specifications ofacceleration sensors required to construct a microtremor measurement system, the application conditions of
this system, and methods for evaluating the measurement results.
Key words: natural frequency, micro tremor, acceleration sensor, introduction manual

1. Introduction
In recent years, disasters have frequently occurred due to rapid
river flooding and prolonged high water levels caused by typhoons
and localized heavy rainfall. As a result, the ground around the foundations of piers located in rivers is scoured by rising water, resulting
in frequent disasters such as sinking, tilting, and overturning ofpiers. These disasters can cause catastrophic accidents such as derailments or and overturning of trains into rivers, depending on thecircumstances. It will therefore become even more important tomonitor the stability of piers during periods of rising water.
The impact vibration test method [1] is used to evaluate thesoundness of piers. This method identifies the natural frequency,
which is an index of soundness, by directly vibrating the piers witha weight, and evaluates the soundness of the piers based on the degree of decrease in the value. However, since this method requires
hitting the piers with a heavy weight, it is difficult to measure thenatural frequency when the water level is rising. Therefore, we havedeveloped a method to continuously measure the natural frequencies of piers by constantly measuring the microtremors [2, 3, 4]. As
a result of this research, an algorithm was developed to identify thenatural frequencies of piers by measuring microtremors at two locations at the top of the piers. The algorithm was applied to a model
test and a part of a real pier in service, and the identification of thenatural frequencies was confirmed to be feasible [5, 6]. A method
was also developed to improve the identification accuracy whenusing a low-cost accelerometer as the measurement sensor [7].
In order to promote the use of the natural frequency identification system that utilizes the results of these developments, we drafted an introduction manual. The manual includes the natural frequency identification algorithm, the basic specifications of acceleration
sensors required to construct the constant-microtremor measurement system, the application conditions of the above system, and themethod for evaluating measurement results. This paper describes
the contents of the manual in detail.

significance of the microtremor measurement and the contents ofthe manual, and Chapter 2 and subsequent chapters describing thespecific scope of application, the natural frequency identification
algorithms, and other details.
3. Scope of application of the constant microtremor measurement method
Chapter 2 of the manual describes the features of the constantmicrotremor measurement method as well as the foundation structures to which it is applied and points to be considered in its application. The following is an overview of the contents.
Unlike the impact vibration test, the constant microtremor mea-

2. Organization of manual
The chapter structure of the manual is shown in Fig. 1. The
manual consists of seven chapters, with Chapter 1 summarizing the
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Fig. 1 Manual Chapter Structure
201

surement method does not require excitation by blows. However,since this method utilizes constant microtremors, which are minutevibration phenomena, the scope of application is more limited thanthat of impact vibration tests. Therefore, the method is not likely to
be applicable to the following piers: A: piers whose natural frequencies are difficult to identify even with impact vibration tests, B: pierswith large damping constants, and excitation frequencies which are
not clear, and C: piers in which the predominant frequencies of girders and ancillary structures exist near the natural frequencies.
This method is applicable to “spread foundations,” “spreadfoundations with wooden piles,” and “Caisson with superficial
foundation.” In principle, this method does not apply to piers, ramen-type structure, abutments, and other earth-retaining structures
for rivers and waterways constructed after 1976, when the Cabinet
Order concerning Structural standards for River Administration Facilities was established and enforced.
If the target structure has tall piers, piers with a large degree ofobliquity, piers supporting truss girders or long bridges, short piers
and thick soil cover, or elevated bridges, it is recommended to confirm or obtain new impact vibration test data in advance. It is also
recommended to examine whether the piers do not have the vibration characteristics of A to C above.

direction to the bridge axis is used as a basis. The procedure for
identifying natural frequencies using this method is as follows andthe procedure is shown in Fig. 2.
I. Measure the microtremors of the horizontal and verticalcomponents perpendicular to the bridge axis at both ends of the piertops.
II. The position of the center of rotation of the rocking vibration is obtained from the geometric relationship between the Lissajous angle plotted as the locus of the horizontal and vertical components at each microtremor sensor and the sensor installation interval.
Based on the aforementioned assumptions, the vertical componentof the rocking vibration is obtained from the difference of the vertical components of the microtremors at both ends, and the horizontal
component of the rocking vibration is calculated from the same
geometric relationship (Fig. 3). The horizontal component of theground vibration (input waveform) is obtained by subtracting the
calculated horizontal component of the rocking vibration from the

4. Natural frequency identification algorithm [3][8]Chapter 3 of the manual covers details of the identification algorithm.
This method assumes that the pier vibration (response waveform) measured at the top of the piers is the sum of the ground vibration and the pier rocking vibration in response to the ground vibration. Since most of the tilting of piers due to scour occurs in the
upstream direction of the river due to the restraint effect of thegirders, the evaluation of natural frequencies in the perpendicularFig. 2202

Fig. 3 Conceptual diagram of primary vibration of bridge
pier [3]The procedure of natural frequency identification algorithm
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horizontal component of the microtremor measured on the pier.
III. The Fourier amplitude ratio (transfer function) is calculated by dividing the Fourier amplitude of the horizontal componentof the microtremors measured on the piers by the Fourier amplitudeof the horizontal component of the ground vibration estimated in II.
IV. Apply the theoretical solution of the vibration model withthe damping constant expressed in (1) to the calculated Fourier amplitude ratio (transfer function). Find the frequency at which thecoefficient of determination is maximum.
2

⃓
2hf
⃓
1+
f0
xa ( ) ⃓
⃓
=⃓
(1)
2
2
2
xg ( ) ⃓⃓2hf⃓ 1- f+f0
f0⎷Here, xa( f ) is the Fourier amplitude of the horizontal vibration of
the bridge pier, and xg( f ) is the Fourier amplitude of the vertical vibration of the bridge pier. xa( f ) xg( f ) is the Fourier amplitude ratio (transfer function). And where f is the frequency (Hz), f0 is the natural frequency of the bridge pier (Hz), and h is the damping constant.
The basic principles of the identification method are as described in I to IV above, but the actual algorithm implements multiple arithmetic operations to improve the identification accuracy andautomatic calculation of natural frequencies based on the processing
flow. For details, please refer to Ref. [8]. The details necessary to
implement these processes in the identification system are also described in detail in the manual.
The evaluation of the soundness of pier foundations based onnatural frequencies in the manual is based on the evaluation of natural frequencies in impact vibration tests [9].

6. Construction of the microtremor measurement system
6.1 Sensor specifications
Chapter 5 of the manual organizes the selection of velocity andacceleration sensors in terms of the accuracy and performance required for each sensor.
In selecting the specifications of each sensor, the characteristicsof the sensor must be such that the natural frequency identification
algorithm can be sufficiently applied. In the manual, the specifications of velocity sensors used in the development phase are presented as a reference. It also summarizes the specifications required foracceleration sensors, which are considered advantageous in terms of
cost reduction. The specifications of the acceleration sensors considered are described below.
6.2 Synchronization accuracy
In applying the natural frequency identification algorithm, it isnecessary to ensure high synchronization performance for each sensor. In addition, accelerometers with the smallest possible error between individual sensors should be selected. Specifically, the sensors should have (1) low internal noise, (2) digital output function
without AD conversion or AD conversion function with low noise,and (3) output of each axis between sensors should match when installed in the same location. The manual shows the synchronization
accuracy as a guideline for applicability (Fig. 4).

5. Construction of the microtremor measurement system
Chapter 4 of the manual describes the construction of a continuous microtremor measurement system.
When designing the system, it is necessary to consider the microtremor sensor, the data recording unit, and the power supply, andwhen installing the measurement system, it is necessary to consider
the exposed environment on the bridge. Table 1 shows the items to
be considered in the manual and their contents.
Table 1 Main considerations for system construction
and outline of the study

Fig. 4 Image of the degree of agreement and applicability of microtremor waveforms
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203

6.3 External noise
Together with the specification characteristics regarding theinternal noise of each accelerometer, it is necessary to eliminate theinfluence of external noise in the construction of the measurement
system. The manual gives specific noise levels to which the identification algorithm can be applied.
6.4 Resolution
In order to investigate the effect of the minimum resolution of
the accelerometer (corresponding to the minimum sensitivity of thesensor) on the accuracy of the identification, we compared the iden-

Fig. 5

Waveforms with varying resolution waveforms

Fig. 6
204

tified natural frequencies and the coefficient of determination of thetheoretical solution fitting by generating data with a stepwisechange in the minimum resolution with respect to the original waveform. The results showed that a minimum resolution of 50 µG (approximately 3% of the amplitude RMS value of the measured
waveform under all drilling conditions) is recommended (Fig. 5).
6.5 Applicability based on the shape of the transfer function
The applicability of the algorithm was verified based on the
shape of the transfer function obtained by the identification algorithm. The ratio of the mean value of the total amplitude ratio areaof the Fourier amplitude ratio in the transfer function to the peakvalue of the amplitude ratio (amplitude index) was employed as anindicator (Fig. 6). We organized the relationship between this index
and the coefficient of determination during fitting with the theoretical solution.
As a result, the natural frequency can be identified in the range
where the amplitude index exceeds five, and the identification accuracy improves when the amplitude index exceeds eight (Fig. 7).
When applying this method, it is recommended that the applicabilityof the identification algorithm is determined after the waveform of
the transfer function has been obtained by preliminary measurements or other means.

Fig. 7 Relationship between the coefficient of determination and amplitude index

Definition of amplitude index
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6.6 Example of acceleration sensor specifications
As an example of accelerometer selection, Table 2 lists themain specifications of the accelerometers used in the study of thenatural frequency identification algorithm.
7. Results of experiments
Chapters 6 and 7 of the manual summarize the measurement
conditions and installation methods and their considerations, respectively (Fig. 8, Fig. 9). The main items described in the manualare shown in Table 3. Examples of fixing and protection of microtremor sensors are also introduced.

quencies can be confirmed easily and quickly even in remote locations. This will contribute to improving the level of social services
provided by public transportation systems, such as the dissemination of operation information and the maintenance of inspection andrepair systems. This manual is available from the Ministry of Land,
Infrastructure, Transport and Tourism. The contents of the manual
may be added to or revised in the future as new knowledge emerges.
Acknowledgment
This research was supported by the public works under Ministry of Land, Infrastructure, Transport and Tourism (JPJ002223).

8. Summary
This paper describes a manual to introduce a natural frequency
identification system using constant microtremor measurement. Byutilizing the latest IoT-related technologies, changes in natural freTable 2

Specifications of the selected example sensor

Fig. 9 Precautions for installation of microtremor sensors
Table 3 Main description of measurement conditions
and installation method

Fig. 8 Example of measurement system installation (Inthe case of battery-powered system)
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205

References[1]	Nishimura, A. and Tanamura, S., “Study on Integrity Assessmentof Railway Bridge Foundation,” RTRI Report, Vol. 3, No. 8, pp.
41-49, 1989 (in Japanese).
[2]	Keyaki, T., Watanabe., S., Miyashita, Y. and Ota, N.,“Specification Technique of Natural Frequency Based on The
Microtremor Measured at The Both Side of a Bridge Pier,”
Journal of railway engineering, JSCE, Vol. 20, pp. 61-68, 2016
(in Japanese).
[3]	Keyaki, T., Yuasa, T., Naito, N., and Watanabe, S., “Soundness
Evaluation Method of the Ground around the Pier Foundation
against Scouring by Microtremor Measurements at Both Sidesof the Bridge Piers,” Japanese Geotechnical Journal, Vol. 13,
Issue 4, pp. 319-327, 2018 (in Japanese).
[4]	Watanabe, S., Naito, N., Yuasa, T., and Keyaki, T., “Applicabilityof a New Natural Frequency Identification Method Using
Microtremors to Actual Bridges,” Japan Society of Civil
Engineers 2019 Annual Meeting, 3-206, 2019 (in Japanese).
[5]	Watanabe, S., Naito, N., Keyaki, T., and Yuasa, T., “Verificationof Identifying Method for Natural Frequencies by Model Bridge

Piers with Different Cross Sections,” The 54th Japan National
Conference on Geotechnical Engineering, pp. 1175-1176, 2019
(in Japanese).
[6]	Naito, N., Watanabe, S., Nunokawa, O., and Keyaki, T.,“Influence of different ground materials on vibration
characteristics of bridge pier model on spread foundation,” The54th Japan National Conference on Geotechnical Engineering,pp. 1177-1178, 2019 (in Japanese).
[7]	Naito, N., Watanabe, S., Nunokawa, O., and Keyaki, T., “A
Study on Improvement of Identification Accuracy of NaturalFrequencies of Piers due to Microtremors,” Japan Society of
Civil Engineers 2022 Annual Meeting, III-37, 2022 (inJapanese).
[8]	Watanabe, S., Keyaki, T., Naito, N., and Yuasa, T., “Automatic
Identification Method for Natural Frequency of Bridge Piers byMicrotremor Measurement at Both Sides on the Bridge Crown,”
RTRI Report, Vol. 33, No. 9, pp. 11-16, 2019 (in Japanese).
[9]	Railway Technical Research Institute, Maintenance Standards
for Railway Structures and Commentary (Foundation and Earth
Pressure Resistant Structure), Maruzen Publishing Co., Ltd.,Tokyo, JAPAN, pp. 169-171, 2010 (in Japanese).

Authors
Satoshi WATANABE

Senior Chief Researcher, Head of Geo-hazard& Risk Mitigation Laboratory, Disaster
Prevention Technology Division
Research Areas: River Disaster Prevention,
Slope Disaster Prevention

Shoma FUJIWARA

Researcher of Geo-hazard & Risk Mitigation
Laboratory, Disaster Prevention Technology
Division
Research Areas: River Disaster Prevention,
Slope Disaster Prevention

Hiroki IRI

Researcher of Geo-hazard & Risk Mitigation
Laboratory, Disaster Prevention Technology
Division
Research Areas: River Disaster Prevention,
Slope Disaster Prevention

206

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SUMMARIES

Summaries of Papers in RTRI REPORT (in Japanese)
Effect of Track Structure Condition on Limit Valuefor Uneven Displacement at Bridge Boundary
Shintaro MINOURA, Manabu IKEDA, Munemasa
TOKUNAGA(Vol.38, No.5, 1-9, 2024.5)

a complete solution has not yet reached at the peak of fallen leaves season.

In the Design Standards for Railway Structure and Commentary (con-of particle apply. A correlation was also observed between the number ofcrete structure) provides a guideline on the limit values for uneven displace-holes penetrated by particles remaining on the paper tape and the tangen-ment (angular bent / misalignment) of the track surface with regard to thetial force. In particular, a relatively good correlation was found between therecoverability of track damage at normal conditions and during earth-estimated area of the holes and the tangential force. These results will con-quakes. However, in recent years, the fastening intervals and support stiff-

tribute to design and performance evaluation of particle for improving adhe-ness of real railway lines have often differed from the assumptions whension between wheel and rail.

Therefore, the authors conducted a brake test to investigate the influence ofparticle amount and particle size on the tangential force. The test was conducted with paper tape attached to the rail for simulating leaves on the rail.
The test results showed that the tangential force increased with the amountcalculating the reference limit values in the aforementioned design standard. In addition, there is a possibility that the limit values for recoverability can be increased by selecting appropriate track structure conditions at
the time of design. In this study, we sort out the track conditions that are
dominant over the limit values and evaluate the influence of various parameters such as the track support stiffness and the fastening interval on thelimit value of track maintenance and recoverability.

Fundamental Study on Contact Force Estimation
Method of Pantograph/Catenary Systems using Kalman Filter
Shigeyuki KOBAYASHI, Yoshitaka YAMASHITA(Vol.38, No.6, 7-13, 2024.6)
The contact force between overhead wires and pantographs is an important indicator for evaluating the current collection performance. This study

Proposal for Excitation Acceleration in Vibration
Endurance Testing of Signaling Equipment
Yoshikazu OSHIMI, Shunsuke SHIOMI, Tsuyoshi KAMIYA, Ryuto ISSHIKI(Vol.38, No.5, 11-16, 2024.5)

proposes to use a Kalman filter as a model-based approach to estimate the

Signaling equipment is installed at a place where vibrations occur during

effect of measurement error, modeling error and variance of the contact

the passage of trains over rails, sleepers, and roadbeds. It is therefore neces-

force on the contact force estimation. A finite element model of the panto-sary to design signaling equipment taking into account the influence of vi-

graph is then used to investigate the effect of modeling errors on the accu-

bration to avoid damage due to vibration. In recent years, the installationracy of contact force estimation.

contact force. In this paper, an external force identification method based on
an augmented state-space equation is applied to solve the dynamics of pantographs. First, the validity of the proposed method is verified through bysimulations based on a 2-degree-of-freedom model, in order to clarify theenvironment of signaling equipment has changed due to the speedup of
trains and changes in tracks and structures. However, the details of vibration propagation to signaling equipment have not been investigated so far.
In addition to current issues, this paper reports on a guideline for vibration
acceleration amplitude in vibration endurance testing.

Calculation Method for Expansion and Contractionof the Spring Tension Balancer
Koki SATO, Yoshitaka YAMASHITA(Vol.38, No.5, 17-23, 2024.5)

Development of Low Strength Stabilization Method
for Fouled Ballasted Tracks
Takahiro KAGEYAMA, Takahisa NAKAMURA, Masaru
HOJO, Fumika TAJIMA(Vol.38, No.6, 15-21, 2024.6)
As ballast on railway track is more crushed and grained, settlement of the
track tends to occur even if after tamping, so that maintenance frequency
increases. Although the basic measure to reduce the maintenance frequency
is replacing the ballast with new ballast, the cost is high. Then, a low-cost

It has been reported that tension balancers, in some cases, may reach its

method for reducing the settlement without replacing the ballast has been

movable limit. One of the causes is thought to be the creeping move of over-required. Therefore, the authors developed a low-strength stabilization

head contact lines. In addition, if expansion or contraction characteristics

method for reducing settlement without replacing the ballast. In this study,

due to temperature at each of both ends of overhead contact lines are not

we confirmed the effectiveness of the developed method for reducing settle-

identical, it may also cause the tension balancers to reach its movable limit.

ment through laboratory tests. In addition, we conducted field tests on a

However, phenomena based on these causes have not been sufficiently in-commercial line to verify the effectiveness for reducing settlement.

vestigated, so that it is required to clarify the phenomena. Therefore, we
conducted numerical calculations and field tests to clarify the factors thatcause the creeping move of overhead contact lines and the generation ofdifferences in temperature expansion/contraction characteristics of tension
balancers at each of both ends.

Increase of Tangential Force by Ceramic Particles
on the Low Adhesion Condition
Shinya FUKAGAI, Takemasa FURUYA, Ryo TAKANO(Vol.38, No.6, 1-6, 2024.6)

Survey on Railway Customers’ Consciousness ofCleaning Quality in Men’s Restrooms in Railway
Stations
Takashi KYOTANI, Yoshiki IKEDA, Hiroshi OISHI, Tamami KAWASAKI(Vol.38, No.6, 23-30, 2024.6)
In order to extract factors that affect customers’ evaluation of men’s restrooms in railway stations, we conducted surveys on railway customers’
consciousness of cleaning quality in men’s restrooms in railway stations.

Vehicle slipping and sliding caused by fallen leaves especially in autumn

Statistical processing of the survey results revealed that two indicators,

is an important issue that needs to be resolved in terms of safety and on-“odor satisfaction” and “urine stains on skirting boards,” affect the users’

time operation. Though the equipment which apply ceramic particles be-

evaluation of whether they would like to use the same restroom again. It

tween rail and wheel of vehicle to increase the adhesion has been developed,

also became clear that men’s restrooms with dry cleaning in railway sta-

QR of RTRI, Vol. 65, No. 3, Aug. 2024

207

tions had statistically significantly better evaluations than men’s restrooms

was verified by numerical simulations, and it was confirmed that the re-with wet cleaning in railway stations from the viewpoint of odor.

quired performance was achieved with the design while satisfying the constraints of the system.

Evaluation of Spatial and Temporal Variation of Site
Effects on Superficial Subsurface Structure
Seiji TSUNO, Masahiro KORENAGA, Reo KOBAYASHI,
Hiroaki YAMANAKA(Vol.38, No.6, 31-36, 2024.6)
We investigated the spatial and temporal variation of site amplification
characteristics based on observation data from high-sampling continuous

Study on the Occurrence Conditions of Squeal Noiseand High frequency Noise in a Railway Curved Section
Takeshi SUEKI, Yasuhiro SHIMIZU, Takuma NITTA, Kentarou TAKAI(Vol.38, No.7, 9-16, 2024.7)

borehole seismic observations and geophysical surveys, as well as using

When a train passes through a curved track, squeal noise (below 10 kHz)wave propagation theory, to improve the accuracy of earthquake groundand high frequency noise (above 10 kHz) are often observed. Measurements

motion evaluation. Furthermore, in the vicinity of the observation site at theof these noises were carried out on commercial lines to understand the gen-foot of Mt. Mannichi, where bedrock is exposed, we extracted the relation-

eration of the noises. It is found that these noises vary from wheel to wheel,ship between the spatial variation in the epicenter azimuth of site amplifi-

having large dispersion. The analysis results showed that these noises arecation and the irregularly shaped underground structure.

prominent when the outer wheel flanges contact the outer rail at specificpassing velocities. In contrast to that, these noises become lower when a

Increased Perception of Workload and Related Cognitive Functions in Drivers with Aging
Ryo NAKAMURA, Ayanori SATO, Takayuki MASUDA,
Yasuhiro KITAMURA, Munendo FUJIMICHI, Ayano
SAITO(Vol.38, No.6, 37-43, 2024.6)
With aging, the physical and cognitive functions generally tend to decline.

train is running at balancing speed in curves.

Improvement of Skeleton Curves for Nonlinear Dynamic Analysis Employing Single Degree of Freedom Model of Railway Bridges and Viaducts
Kengo NANAMI, Kimitoshi SAKAI(Vol.38, No.7, 17-22, 2024.7)

However, taking appropriate measures, it is possible for elderly train driv-

A dynamic analysis employing the nonlinear single degree of freedom

ers to continue their duties safely and confidently. Therefore, the first step

(SDOF) model is generally used to carry out the seismic design of railway

was to obtain fundamental data for examining measures needed to enablebridges and viaducts. Although structures are represented with bi-linear

senior drivers to continue train driving. Based on a survey result on thetype skeleton curve in the model, it does not necessarily reproduce the non-perceived burden of train driver’s tasks, we identified the tasks that become

linear behavior of the structure obtained from the pushover analysis. Espe-

more burdensome with aging. Furthermore, it was revealed that the in-cially, the response values calculated by the method are largely different

crease in burden of these tasks is associated with age-related declines infrom those obtained from the precise model for small and medium earth-visual function, attention, decision-making skill and reaction time.

quakes. In this study, a new skeleton curve employing the ellipse function
was proposed to improve the precision of dynamic response in regions at

Estimation of the Price Elasticity of Demand forGreen-Car in Commuting Train
Ryosuke MATSUMOTO(Vol.38, No.6, 45-51, 2024.6)
The fare of local train Green-car (higher-class car) seats will affect not
only its demand, but also that of regular car of the same train. Therefore, it
is important to estimate the impact of the price change on the Green-car
demand, especially during weekdays’ commuting time when the overcrowding is at a high level. This research focuses on a Green-car’s two-stage pric-around yielding. It was confirmed that the non-linier response estimated by
the SDOF model with proposed curve showed good agreement with thatfrom precise dynamic analysis.

Estimation Method of Melting Volume of Current
Collecting Materials at Contact Loss Point by using
φ-θ Theory
Chikara YAMASHITA, Koki NEMOTO, Takuya OHARA(Vol.38, No.7, 23-28, 2024.7)

ing structure where the price jumps by JPY210 when travel distance ex-

In order to control electric wear of current collecting materials such as

ceeds 50km. Then, this research estimates the price elasticity using

contact wire and contact strip in electric railways, it is necessary to under-

regression discontinuity design. The estimation results show that the elas-stand the relationship between current and melting volume at a contact loss

ticity is significantly larger than one, which means that the price sensitivity

point. In this paper, we propose a method for estimating melting volume of

to demand is at a high level. Pricing decisions should be made carefully

contact wire whose film resistance is taken into account, based on the φ-θbased on the estimation results of price elasticity and the current over-theory. To verify the proposed method, we carried out wear tests under two

crowding degree of regular cars and Green-cars.

current conditions to measure melting depth, melting radius, and melting
volume. The wear test results showed that experimental values of melting

Design Method for Power Generation Systems forDiesel Vehicles Using a Permanent Magnet Synchronous Machine and a Full-Bridge Rectifier
Minoru KONDO(Vol.38, No.7, 1-8, 2024.7)
This paper describes a design optimization method for power generation
systems for diesel vehicles consisting of a permanent magnet synchronousmachine, a full-bridge rectifier and phase shift capacitors inserted between

volume of the contact wire were in the range where contact boundary factor
α was estimated from 0.90 to 0.94.

A Study on Parameter Setting for Deformation Characteristics for Dynamic Grand Response Analysis
Keigo TSUKIOKA, Yasutomo YAMAUCHI, Masanori YAMAMOTO, Tomoya ONODERA, Jun IZAWA(Vol.38, No.7, 29-35, 2024.7)

them. By combining an analysis method for the proposed systems and a

A dynamic ground response analysis has been used in practice as a recom-

multi-objective optimization method, a trial design optimization was carried

mended method for seismic design of railway structures in Japan. The

out with the aim of minimizing indicators related to reducing the size and

GHE-S model, which can precisely reproduce the deformation characteris-weight of the system. Furthermore, the performance of the optimized design

tics of soils from small to large shear strain levels, is applied to the analyses.

208

QR of RTRI, Vol. 65, No. 3, Aug. 2024

The parameters of the GHE-S model are usually set by designers according
to the deformation characteristics obtained from laboratory tests. Therefore,
the accuracy of the analysis is greatly dependent on how the parameters are
set and how the deformation characteristics are obtained. Consequently,
this paper examines how to set up the deformation characteristics of soils ina ground response analysis.

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209

Editorial Board

Chairperson: Kimitoshi ASHIYA
Co-Chairperson: Hisayo DOI
Editors: Ryohei IKEDA, Fumiko MORIMOTO, Nozomi NAGAMINE, Daisuke SUZUKI, Erimitsu
SUZUKI, Kenichiro AIDA, Munemasa TOKUNAGA, Fumihiro URAKAWA, Kazuhide YASHIRO

第 65 巻Vol. 65, No. 3

第3号

2024 年 8 月 1 日

発行

Published date: 1 August 2024

監修・発行所：公益財団法人鉄道総合技術研究所

Supervision/Publisher: Railway Technical Research Institute〒 185-8540

Address: 2-8-38 Hikari-cho, Kokubunji-shi, Tokyo 185-8540, Japan

東京都国分寺市光町 2-8-38

発行人：芦谷公稔

Issuer: Dr. Kimitoshi ASHIYA

問い合わせ：鉄道総研広報

Contact us: Public Relations, Railway Technical Research Institute
Mail Address: rtripr@rtri.or.jp

Copyright © 2024 Railway Technical Research Ins titute, Tokyo JAPAN All rights reserved.

Printed in Japan