Schedule for Presentation Meeting of Master-Degree Thesis in 2016
International Program of Maritime & Urban Engineering
Date :
Venue :
Name

July 26 (Tuesday) starting from 10:00
S1-312 Lecture Room

No.

Time

Supervisor

Title of thesis

Chairman1

10:00 – 10:25

Wardi Syafri

SanadaShear Performance of RC Columns with Wide Hoop Spacing at Mechanical
Splices

Kashiwagi

2

10:25 – 10:50

Han Htoo Htoo Ko

Fujikubo

Collapse Analysis of Ship Hull Girder Using Idealized Structural Unit Method

Kashiwagi

3

10:50 – 11:15

Thet Zaw Htet

Umeda

Probabilistic Prediction of Broaching and Broaching-induced Roll for Ships with
Twin Propellers and Twin Rudders

Kashiwagi

4

11:15 – 11:40

Muhajjir

Aoki

Study on Sediment Transport around Lampulo Fishing Port on Banda Aceh Coast

Kashiwagi

Lunch Break5

13:00 – 13:25

Wicaksono Ardhana

Kashiwagi

6

13:25 – 13:50

Truong Quang Tho

Toda

7

13:50 – 14:15

De Gracia Claude Luis
CarlosOsawa

Wave-Induced Steady Forces and Seakeeping Performance of an Advancing Shipin Oblique Seas
The EFD and CFD Study of the Bulbous Rudder with Asymmetric Horizontal Fins
with Different Angles of Attack in Ship and Propeller Wake Field of KVLCC2 Tanker
A Study on Influence of the Difference in Heading Models on Fatigue Assessment
Results

Kita
Kita
Kita

Break
8

14:30 – 14:55

Ruiz Valdes Hector
OlmedoOsawa

9

14:55 – 15:20

Dewantara Ryan Putra

Suzuki10

15:20 – 15:45

Pinzon Acosta Cesar De
Jesus

Hasegawa

11

15:45 – 16:10

Felipe Rodrigues Modesto

Toda

Prediction of Distortion Produced in Welded Structures during Straightening
Process using the Inherent Strain Method
Guidance and Control of Autonomous Underwater Vehicle SOTAB-I and Its
Application to Data Assimilation
Artificial Neural Network Application for Parameter Prediction of Heat Induced
Distortion as an Inverse Problem
The Influence of Side Hull Location and Ship Speed on the Ship Wave Pattern of a
Trimaran with Wigley Hull Form

Meeting for Evaluation: From 16:30 at S1-323 Meeting Room
Members are Steering committee members and the supervisors

Doi
Doi
Doi
Doi

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Shear Performance of RC Columns with
Wide Hoop Spacing at Mechanical Splices
Syafri Wardi
Concrete Structure Laboratory, Department of Architecture Engineering
Key Words: Reinforced concrete, Mechanical splice, Shear strength, Performance evaluation, Structural test

1. Introduction
The application of a mechanical coupler to screw thread bar
jointing has steadily expanded in recent years because of its simple
installation. However, there are some problems in the applicationof this type of jointing to reinforced concrete (RC) members. The
shear reinforcements must be placed on the couplers to satisfy theminimum spacing demand, as shown in Fig. 1.a. Consequently, inthe construction process, different sizes of hoops/stirrups must be
considered on and off the couplers because they have a larger
diameter than the longitudinal reinforcement. Moreover, inpractical design, when the hoops/stirrups are placed on the couplers,
the longitudinal reinforcements may be rearranged on the innerside to satisfy the minimum concrete cover demand, which results
in a loss of flexural resistance. Therefore, it will be effective forboth practical design and construction to intensively arrange thehoops/stirrups at both ends of the mechanical couplers, as shownin Fig. 1.b, if its negative effects are appropriately evaluated.

coupler jointing, shear span-to-depth ratios of 1.0, 1.5, and 2.0, andshear reinforcement ratios of 0.3, 0.6, and 1.2.
Displacement-controlled reversed cyclic loads were applied tothe specimens using a horizontal jack under a constant axial loadequal to 20% of the column compressive strength applied by two
vertical jacks.
2.2 Experimental Results
All specimens exhibited the shear failure mode. Comparing the
failure processes between the specimens without and withmechanical couplers which have the same shear span ratio andshear reinforcement ratio exhibited almost similar behavior: initial
bending cracking, shear cracking, bonding cracking, and yieldingof shear reinforcement prior to that of longitudinal reinforcement.
The maximum strengths of several columns with couplers
decreased slightly from the wide hoop spacing at mechanicalsplices. The maximum reduction of the shear strengths of columns
with couplers was observed approximately 12% lower comparedto that of without couplers. The specimens with the highest shear
reinforcement ratio were more significantly affected because thespacing of the normal shear reinforcement was considerably
smaller than the coupler length. Therefore, structural indicesconsidering the wide hoop spacing are proposed in the following
chapter.

3.
(a) Conventional arrangement (b) Proposed arrangement
Fig. 1 Conventional and proposed hoop arrangement.
The same type of hoop arrangement was proposed and applied
to precast concrete members with splice sleeve joints at themember ends1). The behavior appeared to be affected by both shear
and bending moments because the splice sleeve joints were placedat the member ends. In contrast, in the current study, mechanicalcouplers with relatively shorter lengths were installed in cast-inplace RC members beyond the plastic hinge regions, which may
limit the negative effects on the shear performance. The intensive
stirrup arrangement was also applied to cast-in-place RC beams
and experimentally verified the low shear performance reduction2).
This study focuses on the applicability of the intensive hooparrangement to cast-in-place RC columns.

2.

Shear Strength Evaluation of Shear-Critical RC
Columns with Wide Hoop Spacing at Mechanical
Splices

3.1. Previous Shear Strength Models
Many researchers have proposed shear strength models for RC
columns over the past few decades. Three existing models were
evaluated in this study: the Japanese Design Guideline AIJ 1990
model3), revised UCSD model4), and ASCE/SEI 41-06 model5).
3.2. Proposal of Indices to Consider Wide Hoop Spacing
Two variables were proposed to consider the effects of the widehoop spacing at mechanical splices: an equivalent area of shear
reinforcements (𝐴𝑣𝑒 ) and an equivalent spacing between shear
reinforcements (𝑠𝑒 ).

Experiments of Shear-Critical RC Columns with
Wide Hoop Spacing at Mechanical Splices

2.1. Specimens and Loading System
Sixteen shear-critical column specimens with a scale of 1/2 wereprepared. Eight columns were designed with continuous
longitudinal reinforcements functioning as benchmark specimens.
The other eight columns were designed using mechanical couplers
for jointing longitudinal reinforcements in which hoops are moved
to the top and bottom ends of the couplers, as shown in Fig. 1.b.
All of the couplers in these columns were placed at the middle
height to simulate typical construction conditions. The
experimental parameters included the absence or presence of(a) Column with normalhoop spacing at
mechanical splices(b) Column with thewide hoop spacing at
mechanical splices

Fig. 2 Proposed variable.
The proposed variables were defined as the following equations
as well as shown in Fig. 2:

𝐴𝑣𝑒 = 𝐴𝑣 . 𝑛ℎ ⁄2(1)
𝑠𝑒 = (𝑙 ′ + 𝑠′)⁄2(2)where 𝐴𝑣 is area of a set of normal hoop; 𝑛ℎ is the number ofhoops intensively arranged (moved from the joint region); 𝑙 ′ =𝑙 + 𝑑𝑠 . 𝑛ℎ ⁄2 ; 𝑑𝑠 is diameter of hoops; and 𝑠 ′ is the spacing
between the centers of intensive hoops and normal hoops.
The proposed indices are applied to replace 𝐴𝑣 and 𝑠(spacing of normal hoops) in revised UCSD model and ASCE/SEI
41-06 model and to replace the shear reinforcement ratio 𝑝𝑤 =𝐴𝑣𝑒 ⁄𝑏. 𝑠𝑒 in AIJ 1990 model, where 𝑏 is the column width.
3.3. Applicability of the Proposed Indices to Shear Strength
Evaluation
The shear strengths of the column specimens were evaluated by
the previous shear strength evaluation models with and without
consideration of the proposed indices. Focusing on the normal
columns without couplers, the revised UCSD model resulted in thebest agreement with the experimental strengths, whereas both AIJ
1990 and ASCE/SEI 41-06 models resulted in underestimations.
The revised UCSD model was selected for the following shear
strength evaluation in this study. The application of the proposed
indices to this model provided the mean value of ratio ofexperimental to calculated strength of 0.99 with coefficient ofvariant of 0.08.

envelope. The shear capacity was obtained using the revised UCSD
model while applying the proposed indices in Sections 3.2. The
column flexural performance was idealized in a typical manner for
conventional columns without a mechanical coupler. The ultimate
displacement of the flexure-dominated columns were estimated asa displacement at the onset of longitudinal reinforcement
buckling6). Figure 3 compares the calculated shear and flexural
performance curves with the skeleton curves from the experiments.

4.

6.

Experiments of Ductile RC Columns with Wide
Hoop Spacing at Mechanical Splices

4.1. Specimens and Loading System
Six specimens with a scale of 1/2 were designed to investigate
the applicability of the proposed evaluation method to practical
shear design for ductile columns. Four columns had coupler
jointing placed out of plastic zone, one specimen had coupler
jointing with overlapping with the plastic zone at 1.0 D from theend of column, and one specimen had continuous longitudinal
reinforcements without splices. All specimens had the shear spanto-depth ratio of 1.5. A common arrangement of longitudinal
reinforcements was applied to all columns. The specimens were
designed with variations in the shear reinforcement ratio from
0.3% to 1.3%. All specimens were expected to yield in flexure prior
to failing in shear.
The specimens were subjected to varying axial loads, whichwere controlled by the applied lateral loads. An initial axial load
was equal to 10% of the column compressive strength representing
the long-term axial stress of the column. The axial load was varied
up to ± 15%, which resulted in total axial loads of -5% and +25%of the compressive strength in tension and compression,respectively, considering a realistic axial load range for typicalexterior columns.
4.2. Experimental Results and Discussions
The specimens exhibited flexure-shear failure and ductile
flexural failure. The specimens with the same amount of shear
reinforcement, exhibited similar experimental behavior andperformance. However, the joint located closer to the flexural
hinge at the column bottom reduced the ultimate displacement byapproximately 4% compared to that of those with joint located outof plastic zone.

5.

Seismic Performance Evaluation of Ductile RC
Columns with Wide Hoop Spacing at Mechanical
Splices

Seismic performance of RC columns can be estimated by
combining the shear strength envelope with the flexural capacity(a) Flexure-shear column(b) Flexure-column

Fig. 3 Estimated performance curves.

Conclusions

The following conclusions were obtained from this study:
1. The experimental study of the first series verified that theapplication of RC columns with wide hoop spacing at
mechanical splices had limited negative effects and reduced theshear strength of shear-critical columns by up to 12%.
2. Two structural indices for evaluating the shear strength ofcolumns with the proposed hoop arrangement were presented toconsider the reduction in shear strength.
3. The experimental study of the second series confirmed that theapplication of the proposed hoop arrangement had less negative
effects on the seismic performance of ductile-RC columns if thelocation of rebar jointing was outside of the plastic zone.
4. The proposed shear strength evaluation method had strong
applicability to estimate the seismic performance of ductile RC
columns with the proposed hoop arrangement.

References
1) Yoshino, T., Kobayashi, K. and Ase, M., (1996). “Intensive
shear reinforcing method for PCA Members with Splice sleevejoint.” In: 11th WCEE, Paper No. 1209.
2) Sanada, Y., Konishi, D., Khanh, N. and Adachi, T., (2011).
“Experimental study on intensive shear reinforcement for RC
beams with mechanical couplers.” In: Proceedings of fib
Symposium PRAGUE, 1, 547-550.
3) Architectural Institute of Japan (AIJ), (1990). “Design
guidelines for earthquake resistant reinforced concrete buildings
based on ultimate strength concept” [in Japanese].
4) Kowalsky, M. and Priestley, M.J.N., (2000). “Improved
analytical model for shear strength of circular reinforced
concrete columns in seismic regions.” ACI Structural Journal,
97 (3), 388-396.
5) ASCE/SEI 41-06, (2007). “Seismic Rehabilitation of Existing
Buildings.” American Society of Civil Engineers.
6) Berry, M.P. and Eberhard, M.O., (2005). “Practical performancemodel for bar buckling.” Journal of Structural Engineering,131(7), 1060-1070.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Collapse Analysis of Ship Hull Girder Using
Idealized Structural Unit Method
Han Htoo Htoo Ko
Ship Structural Integrity Subarea, Department of Naval Architecture and Ocean Engineering
Key Words: Ship Hull Girder Strength, Collapse Analysis, Idealized Structural Unit Method, ISUM plate element

1. Introduction

on the result and it can also reduce the computational time.

In order to predict the collapse behavior of a ship hull girder inwaves including the post-collapse behaviors required for astructural risk assessment, a coupled system of motion/collapse
analyses of a hull girder was developed in my laboratory. The
rigid body motion and hydrodynamics load distribution is
calculated by SSODAC (Shell Structure Oriented Dynamic
Analysis Code) and the structural collapse behavior by ISUM
(Idealized Structural Unit Method).
In this study, after joining the development of the pre/postprocessor to automate the input data generation between two
analysis codes, I performed the collapse analysis of a 5250 TEU
containership, and investigated the collapse behavior. Throughthe process of the analysis, the need for the improvement of
ISUM plate element has been noted for modeling some parts ofship structure, so that it has rotational nodal DOFs as well as thetranslation DOFs. So, as the second part of the study, I developed
a new ISUM plate element and examined the applicability
through a comparison with the analytical solution of elastic large
deflection behavior of a simple plate model.

2.2 Wave load analysis

2. SSODAC/ISUM System
2.1 Collapse analysis of structure

Hydrodynamic scattering are analyzed on Singularity
Distribution Method (SDM). Shell Structure Oriented Dynamic
Analysis Code (SSODAC) calculates time history of pressure
distribution on the hull surface, rigid body motions and resulting
inertia force distribution on cargo, ballast water, etc. Linear
potential theory is employed in the present study.
2.3 Work flow procedure of system
Figure 2 shows the work flow procedure of the system.
Create the mesh model by pre-processor

Shell model

Mass model

ISUM model

Mass Distribution(light weight, cargo load)
Rigid body motion
and water pressure
distribution

Idealized Structure Unit Method (ISUM) is similar to the
traditional Finite Element Method (FEM). Basically, there are
two kinds of elements, ISUM beam element and ISUM plateelement. The element size of ISUM is larger than those of FEM.
One of the main feature is that initial imperfections of the element
can be considered in the element modelling.

Total load distribution
including inertia force
input for each node
Collapse behavior
Fig. 2 Work flow procedure

3. Container Ship Analysis
A 5250TEU container ship is used for the analysis. Principal
particulars are as shown in the Table 1.
Table 1 Principal particulars of the model for analysis
Length
267.00 m

Breadth39.80 mDepth
23.60 mDraft
12.50 mFig.1 ISUM plate system
Figure 1 shows the ISUM plate element system. A rectangularplate is divided into three ISUM plate elements. The origin ofeach plate is at the edge of the whole plate panel. Each plate node
has 3 translational degree of freedom in x, y and z direction
namely un, vn and wn which means that plate itself does not havebending stiffness. Since the stiffeners are attached to the plate,neglecting the rotational degree of freedom does not have effect

The miship part is modelled by the ISUM elements while theothers are by the conventional elastic shell elements. Small meshsize is used in the ISUM part, but it is much coaser than that
required in the elastoplastic analysis by the conventional shellelement. Initial deflection of elements are also assigned.
Wave load of 20 time steps are applied to the model. Head sea
condition is used and wavelength is the same as the ship length.
Pressure distribution of the hogging mode is shown in Fig. 4.

 u   2 w   1  w  2 
x

 z
 
  
2
v
  x   2  x    x  2   2 w  y   
1  w  z y   u v   y 2    
2 y 
 xy    y  y   
 

2
    2 z  w   w w xz  u w   xy   x y  yz   y  y  
 

0

  0
 

 v w   0
 

0



 y
y 


Fig. 3 Container ship modelFig.4 Pressure distribution of hogging condition(2)

where w is the sum of local panel deflection nodal deflection wL,
given by the analytical function of panel collapse mode and theoverall deflection given by the nodal displacement, wn.

3.1 Result of container ship analysis
Global deformation of ship can be seen in Fig. 5 and also
half-model deformation is shown in Fig. 6.

4.1 Validation of new ISUM element
In order to validate the new ISUM plate element, as afundamental case, the elastic deflection behavior of two-edge
simply supported plate under longitudinal thrust is analyzed asshown in Fig.8. The corresponding analytical solution is given byw

Fig.5 Global deformation of container shipa0
1   /  cr(3)

where σcr is elastic buckling stress and a0 is the maximum initialdeflection of sinusoidal mode.

Fig.6 Bottom deformed shape at midship part (half-model)

Fig.8 Two edge simply-supported plate under thrust
Comparison between analytical solution and simulation resultshows a good agreement as shown in Fig.9.

Fig.7 Bending moment and curvature curve
Figure.7 shows the bending moment-curvature curves obtainedby the pure bending analysis and the wave load analysis. The
latter includes the effect of lateral pressure on the bottom, andhence the bending capacity is slightly smaller than that of the purebending case.

4. Improved ISUM Element

5. Conclusions

In order to make it easier to generate the element mesh in theunstiffened part of ship, new ISUM plate element with rotational
DOFs is developed. The nodal displacements are interpolated bybilinear function Ni asu  4
 ui  4  yi 
 
 


 v    Ni  vi    zNi  xi  w i 1  w  i 1
 0 
 
 i



Fig. 9 Average Stress and Deflection Curve(1)

Strain increment equation of newly developed element
becomes1)
2)

The ultimate strength was not attained under the
maximum wave height of 20m in the present study.
New ISUM element gives a good prediction of plate
buckling behavior and can be utilized in the unstiffened
panel of the ship.

References
Fujikubo, M. and Kaeding, P., 2002, New simplified approachto collapse analysis of stiffened plates, Marine Structures,
Vol.15, pp 251-283.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Probabilistic Prediction of Broaching and Broaching-induced Roll for
Ships with Twin Propellers and Twin Rudders
Thet Zaw Htet
Ship Design Subarea, Department of Naval Architecture and Ocean Engineering
Key Words: Calm-water Manoeuvring Coefficients, Broaching-induced roll, Broaching Probability, Tumblehome

1. Introduction

3. Comparison with free running model tests

Accurate prediction of broaching for ships in regular andirregular waves is still a challenge, especially for ships with twin
propellers and twin rudders because of the emergence of apropeller and rudder as a result of large rolling due to broaching.
As ships having twin propellers and twin rudders, ONR
tumblehome topside vessel1) and ONR flare topside vessel2) weremajor subject ships. By taking into account the propeller andrudder emergence, agreements between model experiments andthe numerical simulation have been significantly improved 1) for
flare vessel but still some disagreement can be found for the ONR
tumblehome topside vessel2).
Therefore, to predict the probabilities of broaching andbroaching-induced roll for a tumblehome vessel and a flare vessel,
it is necessary to improve the model for a tumblehome first.
For investigating the previous modeling of ONR tumblehome
vessel, an inconsistent approach which considers the nonlinear
manoeuvring coefficients but neglects all other higher orderterms2) was used. However, it is not guaranteed whether this kindof partial consideration of higher order order terms leads to agood result. Therefore, in this study, the simulation model for the
tumblehome vessel was attempted to improve by examining afactor in the modeling, i.e. non-linearity of calm-water forces andmoments and the effect of this factor was explored with existingand newly executed free-running model experiments.

3.1 In regular waves
The numerical simulations were executed by using the above
mentioned model with and without nonlinear terms of calm-water
manoeuvring coefficients and then compared with the existing
free-running model experiments conducted by Hashimoto et al6).

Fig. 1 Comparison between experiments and calculations
without nonlinear calm water manoeuvring
coefficients for wave steepness of 0.05 andwavelength to ship length ratio of 1.25.

2. Estimation method for broaching probability
The broaching probability in irregular seas could be estimatedby integrating the probability density function of local wave
height and local wavelength3) within the broaching region
obtained by the use of a time-domain simulation model1) in
regular waves. The simulation model is based on a coupled surgesway-yaw-roll MMG-type manoeuvring model4) with a PD
autopilot and wave-induced forces and moments, which are
estimated with a linear slender body theory under low encounterwave frequency5). For the amplitude of the wave-induced forces,
empirical corrections based on captive tests6) were added.
Assuming that wave steepness and wave-induced motions except
for the roll are small, the interaction between wave andmanoeuvring forces are ignored as higher order term. The
propeller and rudder emergence2) are taken into account. The roll
damping coefficients are obtained by conducting roll decay tests.
In both simulations and experiments, broaching, surf-riding andcapsizing were judged with a qualitative judging criterion
proposed by Umeda and Hashimoto7). The ITTC(1973) spectrum
and a wave staticstics for the North Atlantic are used in this work.

Fig. 2 Comparison between experiments and calculations
with nonlinear calm water manoeuvring
coefficients for wave steepness of 0.05 andwavelength to ship length ratio of 1.25.
The results shown in Figs. 1-2 indicate that the calculation
without nonlinear terms of calm-water manoeuvring forces
provides better agreement with the experiments.
The reason of reducing broaching region with nonlinear termsof calm-water manoeuvring forces is that the contribution of these
nonlinear manoeuvring coefficients in yaw act in the direction forincreasing damping so that broaching could be prevented.
The reason of increasing capsizing region with nonlinear
terms of calm-water is that, when the ship is surf-ridden, all of
the calm-water manoeuvring nonlinear terms in sway equations ofmotion could induce an additional moment toward capsizing.
3.2 In irregular waves

Fig. 4 Broaching probability in the North Atlantic.

Fig. 3 Comparison in broaching probability in irregularwaves between experiments and calculations withand without nonlinear manoeuvring coefficients.
The free-running model experiment in irregular waves was
newly conducted and the simulation results with and without
nonlinear manoeuvring coefficients were compared with the 95%
confidence intervals of experimental result of broachingprobability which is 0.02255 as shown in Fig. 3. This indicatesthe calculation results without nonlinear maneuvering coefficients
exist inside the range, whereas the calculation results withnonlinear terms are outside.
The reason of obtaining better results without nonlinear calmwater manoeuvring coefficients can be presumed as follows. The
effect of nonlinear terms of calm-water manoeuvring coefficientscannot be denied, but it could be cancelled out by other terms
such as higher order terms of wave effects on manoeuvring
coefficients, which were not taken into account8). As a result,these nonlinear terms of calm-water manoeuvring coefficients
could cause additional damping not to result in broaching.

4. Assessment of broaching danger in actual seas
For the assessment of broaching danger in actual seas, acomparison study of probabilistic prediction of broaching andbroaching-induced roll, which is larger than 50 degrees, are done
for the ONR tumblehome and flare vessels. Here, the probabilities
for both vessels are calculated without nonlinear calm-water
manoeuvring coefficients.
As shown in Fig. 4, the broaching probability of the flare
vessel is larger than that of tumblehome for the Froude number of
0.35 or over as the same with we observed in the experiments.
Here, the reason why broaching probability decreases for Fn=0.4
and 0.45 for the tumblehome and for Fn=0.45 for the flare is that,the ship speed is higher than the critical speed for broaching sothat the ship could escape from the broaching.

Fig. 5 Probability of broaching-induced roll angle exceeding
50 degrees in the North Atlantic.
As shown in Fig. 5, for the probability of roll angle exceeding
50 degrees, the probability of the tumblehome vessel is muchhigher than that of flare because of the smaller righting arm due
to its shape6).

5. Conclusions
For the ONR tumblehome topside vessel, the simulation
without nonlinear terms of calm-water manoeuvring forces
provides better agreements with the free-running modelexperiments in regular and irregular waves than that withnonlinear terms.
Although the broaching probability of the tumblehome issmaller than that of the flare, the tumblehome is more dangerous
because of its higher probability of broaching-induced roll angle
exceeding 50 degrees.

References
1)
2)

3)
4)
5)
6)
7)
8)

Umeda N, Usada S et al: (2016) JMST, 21:23-27.
Umeda N, Furukawa T et al: (2014) Proceedings of 30th
ONR Symposium on Naval Hydrodynamics, Hobart,
USB disk.
Longuet-Higgins MS: (1983) Proceedings of the Royal
Society of London, Series A389:241-258.
Hirano, M: (1980) J Soc Nav Arch Jpn, 147:144-153.
Umeda N et al: (1995) Proceedings of the International
Symposium on Ship Safety in a Seaway, 14.1-18.
Hashimoto H et al: (2011) JMST 16:448-461.
Umeda N, Hashimoto H: (2002) JMST 6:111-121.
Araki M et al: (2012) J of JASNAOE, 14:85-96.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Study on Sediment Transport around Lampulo Fishing Porton Banda Aceh Coast
MuhajjirLand Development and Management Area Laboratory, Department of Civil Engineering
Key Words: Port, field study, sediment transport, morphological changes

1. Introduction

Lampulo Ocean Fishing Port (PPS Lampulo) with the area of
50 ha is located on the coast of Banda Aceh, Indonesia. The
fishing port was built since 2006 and the development will beadvanced to gradually until 20301). During the developing phaseof the port in the coastal zone, it is necessary to comprehend thepotential risk of sedimentation and erosion. This is related to theprojected dredging interval and volume of the basin. The
development of Lampulo Port will cause the significant impact oncoastal morphology. In addition, the presence of estuary Kr. Aceh
next to the Port added the issues of sedimentation and erosion due
to tidal currents and waves. This is certainly a serious problem
that needs to be considered so that the sustainable development of
this port can run optimally without causing a significant effect on
the environment. Considering the issues, the main purpose of thisresearch is to investigate the on morphology changes of the bed
sea profile and the shoreline change due to the port construction.

2. Methodology

2.1 Field Measurement

Field measurement (Fig.1) was carried out for 15 days from
August 22nd, 2015 by setting measuring equipment at thelocation: 755965E and 617600N with the water depth of 4.2 m.
The measurement consisted of water level, pressure, current,
bathymetry, and sediment sampling. In addition, historical winddata (1999-2009) gained by BMKG Aceh were also considered as
primary data. Some of those data were used to support simulation
model and partly used to validate the model itself.

Fig.1 Field measurement activities

2.1 Delft3D Simulation Model

Delft3D is an open source windows-based program used formodeling the change of coastal morphology. In order to complete
the field study, the model simulation was performed by couplingof Delft3D-FLOW and Delft3D-WAVE systems. The simulation
was carried out for three scenarios which corresponded to West,
Northwest and North wave direction for 2 year simulation. The
data gained from the field were used in Delft3D numericalprogram as follows: 1) topography, 2) wind, 3) bathymetry, 4)
tidal, 5) current, 6) wave, 7) sediment.

with distribution of 29.18 % and 25.3 % respectively. However inthe wave forecasting, three cardinal directions were used: West,
North West, and North, in which the wind blew from the ocean.
Wave forecasting was calculated by using the Eq. (1) proposed by
the US Army Corps of Engineer2). Wave forecast showed that the
average of significant wave height and period for West, NorthWest and North were (0.26 m: 2.2s), (0.21m: 1.9s) and (0.18:1.8s)
respectively. Results of wave forecasting are shown in Fig.2(1)

Fig.2 Significant wave height and period yearly by forecating

b.

Tide

Fig.3 Tidal data of field measurement
As the result of the tidal analysis, the high tide occurred 2
times a day. This showed that the semi-diurnal components M2and S2 which were influenced by the moon was more dominant
than the diurnal components K1 and O1 influenced by the sun.
MSL (mean sea level) obtained from the measurement was 4.35m, HHWL (highest high water level) = 5.30 m, and LLWL
(Lowest low water level) = 3.58m.

c.

Wave

Fig.4 shows the wave condition on the field. Large values ofwave period indicate that the wave at the location was relatively
long waves, whereas the wave period given by wave forecasting
was short. In term of the wave height, it could be seen that thewave height during measurement period was small.

3. Results of Field Measurementa.

Wind data

Wind data were used for wave forecasting in this study. The
wind from that the South East and West directions were dominantFig.4 Significant wave height and period by measurement

This is supported by the wave forecasting results shown in
Fig.2 which indicated the wave condition at Lampulo waters wascalm. This sea was calm because reduction of energy from West
direction due to existence of four islands on West side (close sea)
as shown in Fig. 5(a) and the fetch length of Northwest and North
were large (duration limited) as shown in Fig. 5(b)North West

Wave

Port

North

(b)
(a)
Fig.5 Wave barrier (a) Fetch length of North West and Northwave direction (b)d. Comparison between wave forecasting and wave
measurement

In order to prove wave forecasting result in the previous
section, the forecasted and the measured result were compared.
Wave height and period have correlation to wind speed as shownin Fig. 6. However, the wave height and period measured arescattered disproportionately to the wind speed data. It indicatedthat the waves at Lampulo waters were not generated locally, but
the generated far in the ocean. Further, the ocean waves
propagated and generated variants in wave height and wave
period toward shallow waters. In conclusion, instead of inaccurate
wave forecasting, the measured data were used as input data forsimulation model. The wave data used in simulation model were
the waves generated by West, Northwest and North.

Fig.7 The comparison of tide-induced water level and current
between the model and the field measurement
The second validation was carried out by comparing themagnitude and heading of the current. The current data used tovalidate was only influenced by tide. The result showed that thevalues, pattern and heading current predicted by the model was
close enough to the real current on the field (See Fig. 7). Thus thesimulation was conducted reasonably.

5.

Result of Simulation

Result of simulation showed the change in morphology ofseabed at the points as shown in Fig.6 (a). The changes at Point-B
and Point-D indicated erosion with the depth of 0.4 m and 1.5 m
respectively. The Point-C experienced a fairly small
sedimentation of 1.6 x 10-4 m. Point-A and Point-Device
Placement water depth did not change at all. Furthermore, total
erosion and sedimentation of domain were 786132.18 m3 and2351864.71 m3 respectively. The difference between them was-1564992.84 m3. As a result, the phenomenon of sedimentation
dominated during two years of simulation. It was confirmed byprevious research3)(b)(a)
Fig.6 Observation point of simulation (a) and shoreline change (b)e.

Fig.6 The comparison between wave and wind data

Current

Comparison of waves, current and tide were done todetermine the factor having greater influence on current
formation. As shown in Fig.7, the wave pattern showed nicecorrelation to the current pattern. It was signed by the increasing
and decreasing of both wave and current simultaneously. On theother hand the tide did not contribute dominantly to fluctuation of
the current. It was showed by fluctuation of current which was
not followed by the fluctuation of the tide.

4.

Fig.7 The comparison of wave, current and tide data

Validation

Validation of the model was first done by comparing thevalue and pattern of water level generated by the tide between
model and field.

In addition, shoreline change due to sedimentation anderosion was occurred in three main parts as shown in Fig. 6 (b).
Detail I and II in the figure were marked by shoreline advance ofapproximately 8 m and 9 m respectively, while Details III
informed shoreline retreat of 6 m.

6.

Conclusion

7.

References

1. The waves at Lampulo waters were calm, it is due to the wave
barrier on the West side of the port and small wind speed.
Additionally the current was dominantly influenced by thewaves.
2. The wave forecasting was not useful to apply in thesimulation, because it was uncorrelated with the measured
waves.
3. The presence of Lampulo Fishing Port influences themorphology change such as shoreline and bed sea profile.
1. DKP Aceh. 2012. Fisheries Data Statistics of Aceh. 2012. DKP
Aceh: Banda Aceh. [In Indonesian]
2. SPM. 1984. Shore Protection Manual. Vol.1,4thed. Washington,
D.C.: U.S. Army Engineer Waterways Experiment Station.
3. Rasyif, TM. 2012. Numerical Simulation: The Influences ofTidal Current Against potential of Sedimentation and Erosion
Adjacent Estuary of Kr. Aceh. Thesis Syiah Kuala University :Banda Aceh [In Indonesian]International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Wave-Induced Steady Forces and Seakeeping Performanceof an Advancing Ship in Oblique Seas
Ardhana Wicaksono
Ocean Space Development Subarea, Department of Naval Architecture and Ocean Engineering
Key Words: Steady horizontal forces, steady yaw moment, oblique waves, Kochin function, enhanced unified theory.

1. Introduction
A ship sailing in natural sea will experience a series of
motions which brings into play first- and second-order forces andmoments. Added resistance, steady sway force, and yaw moment,
are known to significantly influence the overall ship performance.
Early development of theoretical analysis was provided by
1)
2)
Maruo and Newman for the drift force in the horizontal plane3)and yaw moment. Kashiwagi proposed another analysis method
4)for the yaw-moment formula at forward speed. Later, Kashiwagi
proposed the Enhanced Unified Theory (EUT) taking account of
bow-wave diffraction by including 𝑛1 -term in the body boundary
condition, which improved the estimation of the added resistance.
In this paper, wave-induced motions, steady forces and yaw
moment, and forward-speed effect are inspected with emphasis on
oblique waves by means of New Strip Method (NSM) and EUT.

2. Calculation Method
2.1 Formulation
Let us consider a ship advancing at forward speed 𝑈 into aplane progressive wave of amplitude 𝐴, circular frequency 𝜔0
and wavenumber 𝑘0 as shown in Fig. 1. Due to the incident
waves with angle 𝜒, the ship experiences motions about its mean
position with encounter frequency ω. By linear justification, thevelocity potential can then be defined asΦ 𝑇 (x, y, z, t) = 𝑈[Φ𝐷 (𝑥, 𝑦, 𝑧) + 𝜙𝑠 (𝑥, 𝑦, 𝑧)] + Φ(𝑥, 𝑦, 𝑧, 𝑡)(1)

Here Φ 𝑇 , Φ𝐷 , and 𝜙𝑠 denote the velocity potentials of the total
flow, steady basis flow, and steady disturbance, respectively. To
obtain the unsteady velocity potential Φ, the EUT is applied as
derived in upcoming sections.
2.2 Wave-Induced Steady Forces and Moment
After solving boundary-value problems for the unsteadyvelocity potentials, the second-order wave-making steady forces
and moment can be computed with formulas in Kashiwagi 3):
𝑅
𝜌𝑔𝐴2

=

1

𝑘

4𝜋𝑘0

𝑘

∞

1
[− ∫−∞+ ∫𝑘 3 + ∫𝑘 ]2{|𝐶(𝑘)|2 + |𝑆(𝑘)|2 }4

𝜅(𝑘−𝑘0 cos 𝜒)

𝑑𝑘

(2)

√𝜅 2−𝑘 2
𝑘1
𝑘3∞=−[− ∫−∞ + ∫𝑘 + ∫𝑘 ] ℑ{2𝐶(𝑘)𝑆∗ (𝑘)}𝜅𝑑𝑘
𝜌𝑔𝐴2
4𝜋𝑘0
2
4
sin 𝜒
𝑘1
𝑘3
∞
𝜅
2
{|𝐶(𝑘)|+[− ∫−∞ + ∫𝑘 + ∫𝑘 ]+ |𝑆(𝑘)|2 } 2 2 𝑑𝑘 (3)
4𝜋
√𝜅 −𝑘
2
4
𝑀𝑧
1
𝑘1
𝑘
∞
=−
[− ∫−∞+ ∫𝑘 3 + ∫𝑘 ] ℜ{𝐶′(𝑘)𝑆∗ (𝑘)
𝜌𝑔𝐴2
4𝜋𝑘0
2
4
1
∗ (𝑘)𝑆′(𝑘)}𝜅𝑑𝑘
𝐶− 2 sin 𝜒ℜ[𝐶 ′ (𝑘0 , 𝜒) + 𝑖𝑆′(𝑘0 , 𝜒)
𝐹𝑦

1

1

𝑘 cos 𝜒00

+ 𝑘 (𝜏 + 0 𝐾) 𝐻(𝑘0 , 𝜒)](4)with τ and κ being the Hanaoka’s parameter and 3D wave
number, respectively. 𝑘1 to 𝑘4 are the k-waves system that
represents the wave pattern around the hull.

Fig. 1 Coordinate system and notations.
2.3 Enhanced Unified Theory and Kochin Function
The wave amplitude functions 𝐶(𝑘) and 𝑆(𝑘) in (2) to (4),are defined as symmetric and antisymmetric components of shipgenerated progressive waves, respectively, with respect to theship’s y-center plane. As the symmetric component can be
expressed as
𝐶(𝑘) = 𝐶7 (𝑘) −

𝜔𝜔0
𝑔

𝑋

∑𝑗=1,3,5 𝑗 𝐶𝑗 (𝑘)𝐴(5)Based on EUT, 𝐶𝑗 (𝑘) can be computed by
𝐶𝑗 (𝑘) = ∫𝐿 𝑄𝑗 (𝑥)𝑒 𝑖𝑘𝑥 𝑑𝑥(6)

𝑄𝑗 (𝑥) represent the 𝑥-axis linear source strength (𝑧 = 0 on thefree surface) in the outer solution. This is then determined as asolution of integral equation to be attained through matching
between inner and outer solutions, that can be written as𝑖𝜎

𝑄𝑗 (𝑥) + 2𝜋 (1 − 𝜎3∗) ∫𝐿 𝑄𝑗 (𝜉)𝑓(𝑥 − 𝜉)𝑑𝜉3

= 𝜎𝑗 (𝑥) +𝑈𝜎̂ (𝑥)
𝑖𝜔 𝑗

(7)

𝑖

𝑄7 (𝑥) + 𝜎7 {𝑄7 (𝑥)ℎ1 (𝜒) − ∫𝐿 𝑄7 (𝜉)𝑓(𝑥 − 𝜉)𝑑𝜉 }𝜋= 𝜎7 𝑒 𝑖𝑙𝑥ℎ1 (𝜒) = csc(𝜒) cosh−1(|sec 𝜒|) − ln(2| sec 𝜒|)

(8)
(9)

in respect to the radiation and diffraction. 𝑓(𝑥 − 𝜉) include 3D
and forward-speed effects. 𝜎𝑗 (𝑥) and 𝜎̂𝑗 (𝑥) denotes 2D Kochinfunctions from the particular solution of the inner problem.
The inner solution can be given in the form𝑈𝜙j (𝑥; 𝑦, 𝑧) = 𝜑j (𝑦, 𝑧) + 𝑖𝜔 𝜑̂𝑗 (𝑦, 𝑧)+𝐶𝑗 (𝑥){𝜑3 (𝑦, 𝑧) − 𝜑3∗ (𝑦, 𝑧)}
𝜙7 (𝑥; 𝑦, 𝑧) = −𝑒−𝑘0𝑧+𝑖𝑙𝑧(10)

cos(𝑘0 𝑦 sin 𝜒)+𝐶7 (𝑥){𝜓2𝐷 (𝑦, 𝑧) + 𝑒 −𝑘0𝑧+𝑖𝑙𝑧 cos(𝑘0 𝑦 sin 𝜒)}𝑒 𝑖𝑙𝑥 (11)The first line on the right-hand side of (10) and (11) represents
the particular solution and the second depicts homogenous
solution. Also, 𝜓2𝐷 is solved to retain the contribution of
𝑛1 -term to approximate the bow wave diffraction in thelongitudinal direction.

3. Ship Model and Experiment
The ship in concern is a bulk carrier named JASNAOE-BC084,
320 m long, 58 m wide, and 20.8 m deep, with 𝐶𝐵 = 0.84. Hercross sections are projected to the length as in Fig. 2.
The experiment was done in the tank of Mitsubishi Heavy
Industries. Measurement was done at 𝐹𝑛 = 0.00~0.1239 in 𝜒 =30°~180°, with λ⁄𝐿 = 0.4~1.5. Incident waves were recorded by
two methods: near-field (ENC) and far-field (STN), by probes
installed on the carriage and on tank’s sides, respectively.

Fig. 2 Body plan of JASNAOE-BC084.

4. Computed and Measured Steady Forces
Forces and moment at 𝐹𝑛 = 0.0367 are shown in Fig. 3. The
agreement is observed to be fairly good with some issues.
In oblique waves for a real ship, symmetric and antisymmetricwaves component are incorporated simultaneously to the results.
This is indicated by coupling of hydrodynamic forces, itscorresponding motions, and resulting wave amplitude functions
that are fundamental in a prediction of steady forces and moment.
At certain λ⁄L, the wave amplitudes recorded by far- andnear-field probes vary significantly. This trend is remarkable
when the incident waves are disturbed by significant
ship-generated steady and unsteady waves which are dominant incertain wave conditions. As an example at 𝐹𝑛 = 0.1239, on theadded resistance in moderate speed, the STN recorded notably
smaller incident wave amplitudes than the ENC which is
proportional to larger nondimensionalized 𝑅 values measured by
STN. The far-field probes measured the incident waves affectedby dissipated waves.

5. Effect of Forward Speed to the Steady Forces
The forward speed dependence is inspected on three
representative λ⁄𝐿s equal to 0.6, 1.0, 1.5. For example, the yaw
moment case in λ⁄𝐿 = 1.0 is shown in Fig. 4. Along with the
speed rise, Doppler effect will take place, τ shift to the longer
λ⁄𝐿, that cause a drastic change of wave pattern around the hull.

6. Discussions and Conclusions
The findings in this study may be summarized as follows: EUT solutions are inspected to predict the steady horizontal
forces and yaw moment better than NSM to a certain extent.

 In shorter waves, steady forces have been observed to increases
along with the speed, then reach a certain value, and became
constant. Diffraction part is dominant and is strongly correlated
to ship ends’ geometry in the computation. Therefore, rigorous
evaluation of source strength on a real-shaped ship is crucial.
 From λ⁄L ≈1.0 to the long waves, steady forces are mainly
contributed by the radiation Kochin functions that are fairly
sensitive to the speed. In oblique waves, an improvement on
the estimation of hydrodynamic forces and motions is required.
 Employment of two methods in measuring the incident wave
amplitudes is beneficial in the physical understanding of
ship-wave interaction problem.

Fig. 3 𝑅𝐴𝑊 , 𝑌𝐴𝑊 , 𝑁𝐴𝑊 at 𝐹𝑛 = 0.0367.

References
1)
2)
3)
4)

Maruo, H.: Bull of Fac of Eng, YNU, pp.73-91, 1960.
Newman, J.N.: JSR, Vol.11, No.1, pp 51-60, 1967.
Kashiwagi, M.: Schiffstechnik, Vol.39, No.1, pp 3-16, 1992.
Kashiwagi, M.: Trans of WJSNA, No.89, pp 77-89, 1995.
Fig. 4 Forward-speed dependence of 𝑁𝐴𝑊 at 𝜆⁄𝐿 =1.0.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

The EFD and CFD Study of the Bulbous Rudder with Asymmetric
Horizontal Fins with Different Angles of Attack in Ship and Propeller
Wake Field of KVLVV2 Tanker
Truong Quang Tho
Hull Form Design Sub-Area, Department of Naval Architecture and Ocean Engineering
Key Words: Energy-Saving devices (ESDs), Rudder-Bulb-Fin system (RBFS), Computational Fluid Dynamic (CFD), EFD, calm-water

1. Introduction
With the recent rapid price increase of fuel as well as the fuelshortage and the greenhouse effect has escalated rapidly. In the
shipbuilding industry and the operating will also not be an
exception. In order to solve those problems, many Energy-Saving
devices (ESDs) have been designed and installed on the ship in
general as well as around propeller in particular. One of thosesolutions is the Rudder-Bulb-Fin system (RBFS) which is an ESD
installed on a rudder. The horizontal fins on the both sides of
rudder bulb share the same foil section, but the suction side faces
are different. With the recent growth of Computational Fluid
Dynamic (CFD), CFD has been chosen to become the suitable
method to solve in this project. The rudder bulb can reduce thepropeller hub vortex and the fins produce thrusts in the rotationalflows generated by the propeller. The installation angle of fin
around -2 to 1 degree with 1-degree increment for the fins on theboth sides have been done to find out the best energy effect fin.
Validating the results by comparing with experiment result is anabsolute necessary. Thus, the experiment was conducted attowing tank of Osaka University (EFD) using KVLCC2 shipmodel for zero degree of fin installation angle.

2. Methods
The objective ship is the KRISO Very Larger Crude Carrier
which called KVLCC2, working at full scale speed 15.5 knots.
The length between forward and aft perpendicular is 3.2 meters.
Ship beam, draft and displacement are 0.5 (m), 0.208 (m) and
0.313 ( m 3 ), respectively. The longitudinal center of buoyancy islocated in front of mid-ship 3.48% of ship length. The experiment
was carried out in the towing tank of Osaka University with fully
loaded condition at Froude number equals to 0.142 corresponding
to model speed 0.795 m/s and Reynold number equals 2.05e6
corresponding to the 3.2m long ship model.
CFDSHIP-IOWA version 4.5 is used for numerical prediction inpresent research. It is an incompressible URANS/DES solver
designed for ship hydrodynamics. The momentum equations weresolved with the body force distribution representing propeller
effect as the source terms. The computational domain extends
from -0.5<x/L<2.35, -1<y/L<1 and -1<z/L<0.22, where L is ship
length. For inlet boundary condition, the free stream inflow
velocity is set as non-dimensional ship speed (u/U0=1). The exit
boundary condition is used for the outlet. The far field boundary
conditions are implemented on the domain top and bottom. Zerogradient boundary condition is implemented on the domain sides.
No-slip boundary condition is applied for all the solid surfaces. A
slip boundary condition with u/U0=0 and (v/U0 and w/U0) basedon propeller angular velocity;
is imposed on the hub

surface,is the radius at the grid point on the hub surface
and n is the propeller revolution rate.

3. Results
3.1 Flow field analysis
In figure 1, the flow field is extracted from the section at the
AP position (x/L=1) across the rudder surface. We can see fromthe figure that the hub vortex would tend to move to the left side.
The vortices are truncated by the fins in, the starboard side,
especially. The hub vortex location is lowered due to the fin andbulb. The hub vortex area is smaller and axial velocity in its coredecreases.
Figure 2 plots the axial velocity contours limited to u/U0=1.1
along several x/L sections across the portside and starboard side
fin. The tip vortex is observed clear on the portside fin. It
indicates the positive pressure difference between upper andlower surface is pushing the fin upward. The fluid flows acrossfrom pressure side to suction side indicating a lift loss. The hub
vortex is mainly attached under the starboard of bulb surface. On
the other hand, a larger area of flow separation under the
starboard fin (pressure side) near the root appears. The tip vortex
is relatively smaller compared with the portside one. It implied
the larger drag on the fin. Thus, this ESD (0-degree angle ofattack) configuration is not an optimal design, especially for the
starboard side fin. It is necessary to understand the flow angle ofattack into the fin.
3.2 Self-propulsion factors
The self-propulsion factors would be validated against
measured data in Table 1. There is a comparison between thenormal rudder and rudder-fin case. With the appearance of a bulb
and fins on the rudder, thrust deduction increases around 2%,
wake factor decreases 2% in simulation and 5% in experiment;
hence the hull efficiency increases 4% in simulation and 7% inexperiment.
The total resistance with the propeller for different angles ofattack is illustrated in Table 2. Besides that, the total resistancewithout propeller also was found out in order to estimate theself-propulsion factors. The lowest resistance R=5.6508 shows
the best angle of attack; zero degree for portside and -1 degree forstarboard side. By comparing with R=5.784 of normal rudder, thetotal resistance is reduced about 2.3% by the best angle of attackand 1.8% by zero angle of attack.
The self-propulsion factors in Table 3 also indicate the same
best angle of attack. The thrust deduction (1-t) increases around
3% comparing with zero angle of attack case and 4.9% comparing

with normal rudder case.
Table 1 Self-propulsion factors
1-t

1-w

H

CFD-Normal

0.76430.4601

1.6612

CFD- Fin

0.77970.4527

1.722

EFD-Normal

0.77880.44681.7431EFD-Fin

0.79530.42511.8710

Table 2 Total resistance for different angles of attack
Resistance R[N]Angle of
Attack(deg.)[starboard
side]

(a)

Angle of Attack (deg.) [portside]
-2

-1

0

1

-2

5.66285.65395.65995.6611-1

5.70915.70855.65085.659305.66325.66555.68075.71641

5.72205.67125.72465.6701

Table 3 Self-propulsion factors for different angles of attack
Self-propulsion factors

1-t
Angle
of
Attack(deg.)[starboa
rd side]1-w

HAngle of Attack (deg.) [portside]
-2

-1

0

1

-2

0.79090.80350.79120.8012-10.79050.79360.80370.783600.79440.80210.77970.7881

10.77680.80220.79090.8030-2

0.45310.44830.45320.4533-1

0.45290.44870.44830.453300.44830.44830.45270.45361

0.45350.44830.45360.4530-21.7454

1.79211.74591.7674-1

1.7453

1.76851.79251.728801.77181.78941.72221.73731

1.71301.78951.74371.7726(b)Fig. 1 Axial velocity profiles and cross flow vectors at x/L=1 forrudder-fin simulation (a) and experiment (b)4. Conclusions
This research concentrated on the different benefits among theangles of attack which adjusted from -2 to 1 degree with 1-degreeincrement for both sides. The best angle of attack has been found.
The rudder-fin-bulb system shows the lower resistance and betterself-propulsion factors than the normal rudder. The numericalresults including rudder flow field and self-propulsion factors had
been validated by experimental data for the fins with zero angleof attack firstly. The larger flow separations were found out near
the root while the smaller flow separations near the tip. On thecontrary for the best angle of attack; zero degree for portside and-1 degree for starboard side; very small flow separation near theroot, however, the flow separation near the tip becomes larger. By
this point, the plan for the future is beginning to take shape in the
researcher’s mind.

Fig. 2 Velocity sections along fin chord-wise direction

References
1) Kim, JH, Choi, JE, Choi, BJ, and Chung, SH (2014). "Twisted
Rudder for Reducing Fuel-Oil Consumption," Int J Nav Archit
and Ocean Eng, Vol 6, pp 715-722.
2) Choi, YB (2008) "Energy Saving Devices," SNAME Tech
Section 2008-2009, Greece.
3) Kaoru Aoyagi,B.S. thesis, Osaka University.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

A Study on Influence of the Difference in Heading Models on Fatigue
Assessment Results
Luis De Gracia
Ocean Material Engineering Subarea, Department of Naval Architecture andOcean Engineering
Key Words: fatigue, crack propagation, storm model, wave direction, crack propagation retardation.

Introduction

In order to improve the preciseness of ship’s fatigue
assessment, fatigue crack propagation (FCP) analysis has been
proposed as a rational approach for fatigue assessment of ship
structure member. The crack propagation behavior strongly
depends on the load sequence. The accuracy of fatigue crack
propagation analysis depends on the emulation capability of realload sequence. Nowadays, wave models based on various
sources of wave data (satellite measurement, hindcast andonboard measurement) are available and can be used to simulate
wave load history.
Tomita1),2),3) proposed ‘storm model’ which can simulate thewave load sequence experienced by ocean-going ships.
Kawabe4) and Prasetyo5),6) modified Tomita’s model so thatstorm waveforms were given by significant wave height
sequence and the variation of storm duration can be taken into
account. In this conventional storm models, ‘all headings model’
was adopted in sea keeping analyses. In order to fully examine
the effectiveness of the conventional storm models, acomparative study on fatigue assessment results which takes into
account the relative heading angle’s occurrence probability isnecessary.
In this study, SN and FCP based fatigue assessments of thewelded joint in a container ship which sails on North Atlanticroute are performed. Two routes with large and small heading
angle variations are assumed. The occurrence probability
distribution of wave direction is determined by using JWA
hindcast data. Stress sequences are generated by Prasetyo’sstorm model. Analyses wherein the variation in wave direction’s
occurrence probability is considered (‘real headings model’) ornot (‘all-headings model’) are performed. FCP analyses are
performed considering plasticity-induced crack closure by using
FASTRAN-II. Fatigue crack propagation lives andcharacteristics of crack propagation retardation due to excessive
loads are compared. Based on these results, the influence of thedifference in load sequence model on FCP-based fatigue
assessment result is discussed.

2.

Wave Model

Let 𝜃, 𝛼 and 𝜒 be the wave direction, ship’s heading angle
and relative heading angle. In conventional ship’s fatigue
assessment, the stress response is calculated by using ‘allheadings model’ in which 𝜒 is given by a uniform random
number. This simplification might deteriorate the preciseness offatigue assessment. The 𝜒’s occurrence probability,𝑓𝜒 , can becalculated from 𝜃’s occurrence probability, 𝑓𝜃 , which can be

determined from the hindcast data. 𝑓𝜃 ’s examples are shown in
Fig. 1. North Atlantic Ocean is divided into three zones: Northside (NS), Mid side (MS) and South side (SS), and f isdetermined for each zone. In Fig. 1 it is shown that the prevailing𝜃 ranges from 240º to 360º. Also shown is that the 𝜃’s variationin the north side is small compare to that in the south side.
North Side
330°

0°2.0E+06

Mid SideSouth Side30°

1.5E+06300°

60°

1.0E+06
5.0E+05270°

90°

0.0E+00

240°

120°
210°

150°
180°

Fig. 1. Wave occurrence probability distribution, 𝑓𝜃 , obtainedby hind cast data in the North Atlantic Ocean.

3.

Stress Response

3.1 Relative heading angle sequence
Let TS be the mean wave period. Sequences of (, Hs, TS) are
generated for the given ship’s voyage history by using Prasetyo’sstorm model5).  is determined by random number selection withf determined in the previous chapter, and  is calculated by Eq.
(1) at each time.



(1)
     f can be determined by analyzing the generated  sequence.
Let f,AH be f derived from all heading model, and fRH be thatderived from the hindcast’s wave direction data.
500000Sourthern RouteReal headings modelAll headings model

400000300000fχ

1.

2000001000000030

6090 120 150 180 210 240 270 300 330
χ's (degrees)Fig. 2. Relative heading angle experienced in the southernroute.
In Fig. 2 it is shown that f is nearly uniform while fRH
shows large variation. The frequency shows gradually changes

in the southern route. This is due to the large variance in the
ship’s heading angle in this route.
3.2 Target structure and stress response
Fatigue assessment of the welded joint in the longitudinal
stiffener on the upper deck of the 2800 TEU container ship is
performed. Let Δ𝑆 denotes the hotspot stress range.
Δ𝑆 sequence is generated assuming that ℎ𝑆 obeys Rayleighdistribution. The R parameter is determined by using ISSC’s
wave spectrum. (𝐻𝑆 , 𝑇𝑆 , 𝜒) sequences are generated by using all
and real headings model. Let PEX , AH (∆S) and PEX , RH (∆S) be∆S’s probability of exceedance for the cases of all headings andreal headings model. Fig. 3 shows a comparison of PEX , AH (∆S)
and PEX , RH (∆S) for the southern route. It is shown that thedifference in PEX (∆S) is encountered when the wave directivity
is neglected for the southern route. This leads to the small
difference in the SN-based fatigue damage analysis results.
100

200

1-F

0.1 0

300

∆S (MPa)
400

500

Real headings modelAll headings model

0.001

failure lives, 𝐿𝑓 , estimated by fatigue damage calculations.
The statistics of calculated 𝐿𝑃 are listed in Table 2, whichshows that there is a tendency that the crack propagation
retardation for real headings model is stronger than that for all
headings model. This is because excessive loads occur more
frequently in real headings case than in all headings case. Let
LP , AH and LP , RH be LP for all headings and real headings
models. In Table 2 is observed that LP , AH < LP , RH for bothroutes, and the difference is larger in the southern route, on which
the difference in PEX (∆S) is large. Above results show that asubstantial difference (at least 16% under conditions chosen) inestimated fatigue life may be encountered when the headings
model is changed from the all-headings to real-headings.
Table 2. Comparison of propagation life by FASTRAN II.
Northern RouteSouthern Route
Crack
propagation
LP , RH
LP , AH
LP , RH
LP , AH
life LP (year)
Shortest
0.04
0.04
2.86
1.12
Longest
3.89
3.68
11.08
8.24
Mean
2.38
2.05
6.68
4.18
Std. dev.
0.75
0.74
1.67
1.48

0.000015.

0.0000001
1E-09

Southern RouteFig. 3. Long term exceedance probability of stressexperienced by a ship which sails in the south route.

4.

Fatigue Assessment

4.1 Cumulative fatigue damage
The fatigue life under random loading is calculated based onlinear cumulative damage (Palmer-Miner’s rule) during 10 years,
D10 years . In Table 1 it is shown that the differences in cumulative
damage is about 4% in the northern route, while the difference isabout 10% for the southern route, if the all headings and real
headings models results are compared.
Table 1. Comparison of fatigue damages in 10 years
calculated by storm model and DnV CN. 30.7.
Route
North
South
Directional
RealAllRealAllmodelheadings headings headings headings
D10YR-mean
2.84
2.94
1.62
1.79
Lfmean (year)
3.51
3.39
6.15
5.57
4.2 Fatigue crack propagation lives
The fatigue crack propagation (FCP) analyses are performedby using FASTRAN-II, which is based on the crack closure
concept. Let c and a, be the depth and half surface length of ahalf-ellipsoid crack, and t the base plate thickness. An initial
surface crack with c=a=0.2mm is assumed because this is theminimum detectable crack size. The stress intensity factors (SIF)
at the deepest point and the crack mouth are calculated by
WES2805 formula. For the target joint, the main plate thickness
t is 12mm. Let 𝐿𝑃 denote the crack propagation life up to thebase plate penetration. The structural stress concentration factor,
𝐾𝑆 , is set to 1.52 so that the mean 𝐿𝑃 becomes comparable with

Conclusions

Fatigue assessments of the welded joint in the 2800 TEU
container ship which sails on North Atlantic routes are performed.
Two routes with large and small heading angle variations are
considered. Stress sequences are generated by Prasetyo’s storm
model, and the relative heading angle is determined by using allheadings and real headings models. S-N analyses based on DnV
CN 30.7 and FCP analyses using FASTRAN-II are performed.
As results, followings are found:(1) The difference in heading model affect the fatigue
assessment result. The difference in fatigue lives between allheadings and real-headings models is at most about 60% underconditions chosen.
(2) Under conditions chosen, the effect of the difference on
SN-based fatigue assessment is small, compare to those obtainedin estimated fatigue propagation lives.
(3) Further researches on the development of advanced wave
load sequence model which can take into account weather
routing and whipping / springing vibration is needed.

6.

References

1) Tomita Y., Hashimoto K., Osawa N. 2002. ASTM STP 439.
2) Tomita Y., Kawabe H., Fukuoka T. 1992. Proceeding of 6th
PRADS, vol. 2, 1992, pp. 2792-2805.
3) Tomita Y., Matoba M., Kawabe H. 1995. Marine Structure,
Vol.8, 1995, pp.407-422.
4) Kawabe H., Syuuji O., Masayoshi O. 2003. Journal of theSociety of Naval Architects of Japan, 193, 2003, pp.39-47.
5) Prasetyo F. 2013. Ph.D. thesis, Osaka University, Japan.
6) Prasetyo F., Osawa N., Kobayashi T. 2012. Proceeding of
22nd ISOPE Conference IV, pp 709-712.
7) Mao, W., Pratsetyo F., Ringsberg J., Osawa N. 2013.
Proceedings of 32nd OMAE Conference, Volume 2A: Safety
and Reliability, pp v02at02a010.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Prediction of Distortion Produced in Welded Structures during
Straightening Process using the Inherent Strain Method
Hector Ruiz

Ocean Material Engineering Subarea, Dept. of Naval Architecture and Ocean Engineering
Key Words: Distortion, inherent strain, straightening, finite element method, Gauss-Legendre quadrature

1. Introduction

Welding is the most widely used assembly method available toindustries in the construction of ships and offshore platforms.
However, this method always produces a certain amount ofdistortion that will not only degrade the performance but also
increase the building cost of the structure, and it should bestraightened.
Straightening is performed by mechanical or thermal
techniques. The principal mechanical technique is pressing, but it
is difficult to apply it to 3-D structure such as ship block.
Therefore, mainly thermal techniques are adopted in shipyards.
These techniques create irreversible strain (inherent strain) into
the component. This is achieved by locally heating the material toa temperature where the heated material with lower yield stressexpands against the surrounding cold, higher yield strength
material, causing compressive plastic strain in the hot material.
When the component is cooled, the heated area shrinks andinherent strain is generated. Spot, line or wedge-shaped heating
techniques are usually applied in thermal straightening.
In order to optimize the straightening process, it is necessary to
predict the distortion due to straightening. Numerical simulation
is now reliable and fast allowing efficient study of many cases.
Further it does not have the scatter usually found in physicaltesting. Murakawa [1] developed a thermal elastic plastic based
and inherent strain based welding simulation FE code JWRIAN.
Coarse shell FE elements are used in JWRIAN analyses.
This drastically reduces the manpower needed for modelingand computer resources needed for calculation, and practicalapplication of welding simulation in production shop floor has
been realized. However, it is not easy to perform straightening
analysis using JWRIAN
distributes over a range much smaller than element sizes suitablefor welding simulation. Further heating lines on plate fields may
be applied at an angle to stiffeners and therefore to elementboundaries. To avoid having to use much finer meshes, it isneeded to develop a numerical technique which can calculate theinitial strain force due to straightening inherent strain confinedwithin a narrow region.
simulation code JWRIAN is modified so that inh
equivalent nodal forces are calculated in cases where the inherent
strain confines within a narrow region whose size issmaller/narrower than element size. The validity of the developed
ransverse
bending due to gas line heating calculated by three-dimensional
thermal-elastic-plastic analysis and that calculated by thedeveloped system.

2. Inherent strain

The distortion and residual stress produced during local heating
are caused by the irreversible strain (inherent strain) formed
during the plastic deformation process [2]. Both distortions andresidual stress can be predicted by elastic analysis in which theinherent strain is introduced as initial strain. The total strain
can be decomposed into the sum of elastic strain, plastic,
thermal strain, creep strainand phase transformation
strainEq. (1). Noting that the deformation and the stress areproduced by the total and elastic strain, Eq. (1) can be rearranged
into Eq. (2).
(1)
(2)

3. Elastic FE based on inherent strain

Normally coarse shell FE elements are used in JWRIAN
analyses, four node shell elements are used, Fig. 1. There is aneed to develop a numerical technique which can calculate theinitial strain force due to straightening inherent strain that isconfined within a narrow region. In this study asubsystem is developed which can calculate the initial strain force
due to straightening heating.
In the developed code, the initial strain force vector and element
stiffness-linear term which includes stresscomponents are integrated using higher order (e.g. 20 x 20 x 6 for
4-nodes shell elements) Gauss-Legendre quadrature while otherquantities are evaluated by using ordinary order (2 x 2 x 2)
quadrature.
In JWRIAN-HI, the element stiffness matrix and equivalent nodal
force due to inherent strain are calculated by the equations below:(3)(4)
where, [KJL] is the element stiffness, [Bb] the nonlinear
displacement-strain matrix of Mindlin plate for large deflection
problem, [D] the stress-strain matrix, NJ and NL the shapefunction, xi the coordinates,
ij the three in-plane stresscomponent inh the inherent strain and {Finh} equivalent nodal
force due to inherent strain.

-Legendre
quadrature (see Fig. 2) while other quantities are evaluated byusing ordinary order (2 x 2 x 2) quadrature (see Fig. 1).
A 3-dimensional thermal-elastic-plastic FE analysis of the line
heating process of a rectangular thick steel plate is performed, andthe calculated 3-dimensional plastic strain components ( xx andyy) on the cross section are given to the shell integration points.
This mean that the out-of-plane and shear components ( zz, xy,
xz andyz) are neglected in the Elastic Analysis.

integ. points, with a max. integ. point space near to 8mm. getting
almost constant value until S smaller than 13mm.

Fig. 4 Z-displacement comparison.
Table 1 Comparison between TEPA and partial heating.

Fig. 1 Shell Element (2x2Gauss Integration Point)

Fig. 2 Shell element (High
Order Integration Point).

4. Numerical analysis

Thermal-Mechanical behavior during welding and heatstraightening are analyzed using uncoupled thermal/mechanicalformulation, Ueda and Yamakawa [3]. However, the uncoupledformation considers the contribution of the transient temperaturefield to strains and stresses developed through thermal expansion,and temperature-dependent physical and mechanical properties.

5. Interpolation of the inherent strain

Fiv
zz.is neglected),
are taken from the center of each element once completed
the mechanical analysis.
Fig. 3 shows the inherent strain interpolation plotted
over the cross sectional inherent strain distribution, for a
Gauss integration points arrangement of 4x4x4 points.
50mm

Fig. 3 Gauss integration point arrangement, using high-order.

6. Elastic analysis

The second stage of this research consists in show theeffectiveness of JWRIAN-HI, which is verified by comparing theobtained transverse bending angle with TEPA result, whilechanging element size, Gauss integration point arrangement andheating directions. Fig. 4 shows the Z-displacement comparison
between elastic analysis results and TEPA result. Where you can
see a large different is obtained, because the edge effect is notconsidered. Table 6 shows the result when the edge effect isconsidered. Fig. 5 shows the accuracy of the results with different

Fig. 5 Max. Gauss integration point space vs theta.

7. Conclusions

It has been demonstrated that the developed element andnumerical technique, which calculate the initial strain force due tothe straightening inherent strain confined within a narrow region
can successfully recreate the three dimensional TEPA behavior.
In this study, it is shown that with a maximum integration point
in-plane interval of 13mm or less, the transverse bending
becomes almost constant, it means that at least 1/5 of the inherent
strain breadth obtained in the TEPA, should have integration
points (at least 5 int. points in the heating width) to get accurate
results in the elastic analysis.
With the heating conditions used in this study it has been foundthat shell elements with a width of 50mm is enough to recreate
the TEPA, considerably decreasing the computational effort.

References
1)

Concept of inherent strain, inherent
stress, inherent deformation and inherent force for prediction
et al. (Trans. JWRI,
39, 2, pp. 103-105, 2010)2) Murakawa H, Computational Welding Mechanics andConcept of Inherent Strain for Industrial Applications,
Materials Science Forum, 539-543 (207), pp.181-186.
3)
hermal Stress Analysis
of Metals with Temperature Dependent Mechanical2, No 2, pp.90-10.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Guidance and Control of Autonomous Underwater Vehicle SOTAB-I
and Its Application to Data Assimilation
Ryan Putra Dewantara
Marine Mechanical System Engineering Subarea Laboratory,
Department of Naval Architecture and Ocean Engineering
Key Words: AUV, SOTAB-I, guidance, control, data assimilation

1. Introduction
Spills and blowouts of oil and gas from the seabed disasters
cause enormous damage to the environment as well as to themarine and human life. Early detection and monitoring systems
should be deployed around the area where underwater releases ofoil and gas first occurred, to prevent them from spreading andcausing further damage over time. A rapid inspection of the area
by detecting chemical substances and collecting oceanography
data could enhance the accuracy of oil and gas behavior
prediction or ocean model through data assimilation process. An
autonomous underwater vehicle (AUV) called the Spilled Oil and
Gas Tracking Autonomous Buoy system (SOTAB-I) was
developed to perform in-situ measurements of oceanographic data
as well as chemical substances using underwater mass
spectrometry (UMS) 1).
The objectives of this research are as follows:(1) To develop an adequate guidance and control system of
SOTAB-I through simulations and field test experiments.
(2) To propose and perform a preliminary study of the applicationof SOTAB-I to data assimilation.

2. Overview of SOTAB-I
An overview of SOTAB-I is shown in Fig. 1. SOTAB-I is 2.5
m long and weighs 325 kg. It is able to descend in water as deep
as 2,000 m and ascend by adjusting its buoyancy using a
buoyancy control devices. It can change its orientation throughtwo pairs of moveable wings and move in horizontal and verticaldirections using two pairs of horizontal and vertical thrusters.

SOTAB-I is also fitted with a UMS to measure the dissolved gas
and oil in the water. Additionally, the robot is equipped with acamera and a stroboscope for taking pictures.

3. Guidance and Control.
3.1 Operational modes
There are three main operation modes in SOTAB-I 2):(1) Manual mode
SOTAB-I will be controlled manually through the GUI.
(2) Survey mode(a) Vertical water current distribution measurement mode
The robot measures the water velocity and follows thevertical axis by adjusting its buoyancy level.
(b) Rough guidance mode
By repeating descending and ascending on an imaginary
circular cylinder centered at the blowout position, therobot collects rough data of water, spilled oil, and gas.
(c) Precise guidance mode
Robot will perform detailed measurement by repeating
descending and ascending within the plumes.
These modes are based on the depth, altitude, and heading
control, which will be discussed in the next section.
(3) Photograph mode
SOTAB-I will move laterally using horizontal thrusters andtaking pictures of the seabed around the blowout area.
3.2 Depth and altitude control
In this research, a progressive depth control and altitudecontrol for SOTAB-I was developed, as shown by the block
diagram in Fig. 2. The control system is divided into four steps,
depending on the robot location during its descending mission:
START
Step
1

CertainregionStep
2

Variabletarget
depth

Step
3

Fig. 1 Overview of SOTAB-I.
SOTAB-I is equipped with a global positioning system (GPS)receiver and ultra-short baseline (USBL) system for positioning.
The vertical position of SOTAB-I in the water is given by depth
data from CTD sensor, while at the same time it is also measuring
temperature and conductivity (salinity) of the water. The Doppler
velocity logger (DVL) is able to measure the robot’s altitude andvelocities when it is within the bottom tracking altitude fromseabed. SOTAB-I’s orientation and motion are given by thecompass and the Inertial Measurement Unit (IMU). The robot isable to measure the magnitude and orientation of water current
layers by using an acoustic Doppler current profiler (ADCP).

Depth control with time estimation

Near
seabedregionStep Altitude
stabiliza
4tion

ASCENDING

Fig. 2 Block diagram of SOTAB-I depth and altitude control.
Step 1: Safe region between sea surface until a certain depth
Step 2: Deeper region where seabed might be expected.
Step 3: Near the seabed, within the bottom tracking altitude.
Step 4: Altitude stabilization around the set target altitude.
The first three steps adopt the ‘depth control with time
estimation’ method. It controls the output of the buoyancy control
device by taking into account the time needed to reach the target
depth and for changing the buoyancy level. SOTAB-I will haveenough time to adjust its buoyancy level when approaching thetarget depth or altitude. For the 4th step, the heuristic control
method for altitude stabilization is adopted. After a period, it will
start the ascending process by increasing its buoyancy level.
3.3 Heading control
The heading of SOTAB-I can be controlled by changing theangle of two pairs of movable wings located on top of SOTAB-I.
The wing control formulas for heading control are as follow
𝐷𝐸𝐿𝑇𝑋 = 𝛼 sin(𝜓𝑡 − 𝜓)
𝐷𝐸𝐿𝑇𝑌 = 𝛼 cos(𝜓𝑡 − 𝜓)

(1)
(2)

assimilation was performed using incremental four-dimensionalvariational (I4D-Var) scheme included in ROMS. The model
domain covers the U.S. West Coast with resolution 30 x 30 km
with 30 vertical layers in the s-coordinate system. The time span
is between 3-6 January 2004. Only temperature data obtained
from observations by CTD (168 samples, vertically distributed at
10 observation points) and satellites SST (4962 samples, surface
temperature, horizontally distributed) were used for data
assimilation. The comparison results between free run without
data assimilation and with data assimilation are shown in Fig. 4.

Where, 𝛼 is the wing angle, 𝜓𝑡 is target azimuth, and 𝜓 iscurrent azimuth (yaw). The X direction refers to the East-Westdirection, while Y direction refers to the North-South direction.

.

4

.2.

1

4. Experimental Results

1000

2000

Fig. 4 Results of 4 Jan 2004. Left: free run, Right: assimilatedFree run

6
4
2
0

300

200
200
300
100

400

0.5

1
1.5
RMSE (oC)2

2.5

Fig. 5 RMSEs of each CTD observational points

Heading (deg)Depth (m)

8

3000

100

Data assimilated

10

0
400

...8

9

10

Time (s)0.

3Observation Point

Field experiment was conducted in Toyama Bay on June 11th,
2015, by using a ship of the National Institute of Technology,
Toyama College, called Wakashio-maru. The experiment site was
located at 36°52'N, 137°11'E with a water depth of around 560 m.
The depth control with time estimation scheme was deployed,with a target depth of 400m and target azimuth 60° during
ascending. The vertical water current distribution measurementmode was used in the experiment. The results are shown in Fig. 3.
In this experiment was able to smoothly reach the target depthwith a slight overshoot of 2.8 m. The experimental result wasvery similar with the simulation result. As shown by the headingline in Fig. 3, when the heading control was activated during
ascending, SOTAB-I was able to stabilize its azimuth at a certain
direction. However, there is still some difference with the target
azimuth. This might happen due to strong water current effect.
0

.
6. 7
5

The circled areas in Fig. 4, where some of CTD observations
located, show quite significant difference between the free run
and data assimilated model. The root mean square error (RMSE)
of each observational points have been calculated, and theassimilated model shows in average -60.3% decrease in RMSE.

6. Conclusions

500

0
Experimental depth

Simulated depth

Heading

Fig. 3 SOTAB-I Experimental results

5. Data Assimilation
To expand the applications of SOTAB-I, new applications
have been proposed in this research. During surveying operation,
SOTAB-I is able to collect some oceanographic data andchemical properties of oil and gas. These data can be used fordata assimilation to improve the prediction accuracy of: 1) ocean
model, 2) oil and gas behavior model. A preliminary study to
perform data assimilation of the ocean model has been conductedusing Regional Ocean Modeling System (ROMS). ROMS is afree-surface, hydrostatic, three-dimensional model using a terrain
following coordinate system for vertical discretization 3). Data

Through guidance and control, the field test results showedthat SOTAB-I was able to operate successfully. The depth control
simulation was able to simulate similar behavior of SOTAB-I.
However, improvements for the heading control should be made.
A preliminary study of performing data assimilation to an
ocean model has been conducted. The use of data collected by
SOTAB-I for data assimilation might have significant impact.

References
1) Choyekh, M., Kimura, R., Akamatsu, T., Kato, N., Senga, H.,
Suzuki, H., ....Sakagami, N. ISOPE, Vol.1, pp.695-702, 2013.
2) Choyekh, M., Ukita, M., Kimura, R., Kato, N., Senga,
H., ...Sakagami, N. ISOPE, Vol.1, pp.624-631, 2014.
3) Okada, T., Irie, M., Nishida, S. ISOPE, Vol.3, pp.1023-1029,
2014.

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

Artificial Neural Network Application for Parameter Prediction of Heat
Induced Distortion as an Inverse Problem
Cesar De Jesus Pinzon Acosta
Ship Design Laboratory, Department of Naval Architecture & Ocean Engineering
Key Words: Inverse Problem, Neural Networks, Heat Induced Distortion, Line Heating.

1. Introduction

3. Forward and Inverse Problems

For many decades line heating has been used as a method forforming three dimensional surfaces in the shipbuilding industry,
however the procedure is often done manually depending on theskill of experienced workers. Therefore this dependency results ina low productivity rate for shipyards which leads to high cost.
The prediction of the distortion produced by line heating havebeen studied for several years. However, it is a highly nonlinear
problem consisting of many factors such as the amount of heat,
the plate thickness, the speed of the heating source and secondary
factors like the cooling method, residual stress, etc. [1]. In orderto analyze this phenomena it is required to have an appropriate
mathematical tool dealing with all the variables involved in thisproblem.
Finite element method (FEM), through a three dimensional
thermal elastic plastic analysis, is the tool for it, but due to thecomplexity of the problem, it takes long computational time [2].
Final plate deformation have been successfully predicted by using
an ANN model [3], however this ANN model is only able topredict the final deformation of a flat plate due to a line heatingprocess. By this limitation, the ANN model cannot be used to
predict the required heating conditions to produce an arbitrary
deformation in the plate, which is often requested, in the
shipbuilding industry. In this study in order to improve thisproblem, another ANN model is proposed and discussed.

In the case of the thermal elastic plastic analysis, the model isable to predict the inherent distortion for a given plate thickness
and heating speed. This type of problems, where the cause isgiven and the effect is determined is known as forward problem
as it is presented in Fig. 1. On the other hand the prediction of theheating speed by using the actual deformation of the plate and its
thickness is an inverse problem where the effect is given and thecause is estimated.

2. Gas Heating FEM Analysis
The process of forming a plate for a given heating conditions
can be viewed as the process to deform a plate into a desired
shape by giving the heating conditions, using the shrinkage andthe angular distortion induced by the heating and cooling process.
In order to get an accurate representation of the line heatingprocess, a thermal elastic plastic FEM analysis is performed,
where a gas heating torch proposed by Osawa et al. [4], ismodeled as the heat source model. Thermal elastic plastic
analysis can be divided in two steps: the thermal analysis, where
the heat source is applied to the model and the mechanicalanalysis where the four inherent deformation components are
obtained.
In this study, square plate model (1200 mm) is generated forthe analysis. Moreover the attention is focused in the process ofdeforming plates with a thickness from 10 to 50 mm as they are
more difficult to deform by using the line heating process.
Considering that, the maximum temperature of the plate should
be kept below 800 C [5], the effect of the heating speed with thesurface temperature is evaluated. As a result, the heating speed
used to train the ANN model is restricted to a range over 12mm/s.

Fig. 1 Forward and Inverse Problems.
Inverse problems is generally difficult, because it may nothave unique solution, furthermore inverse problem has adeductive nature rather than the inductive nature of forward
problem. To overcome this situation ANN is used based on its
ability to approximate unknown input-output mapping.

4. Artificial Neural Network Development
To perform the inverse problem analysis, the ANN model
uses the inherent distortion predicted in the forward problem asshown in the Fig. 2. From the figure, it can be seen that the plate
thickness is taken as an input parameter since the plate thickness
is known beforehand as well as the inherent deformation
components, then the ANN model will be able to predict theheating speed required to deform the plate with the desiredconditions.

Fig. 2 Proposed ANN model.
4.1 Topology
The performance of the ANN model will depend on thechosen topology. For simplicity of the ANN model, one hidden
layer is selected as it is shown in Fig. 2, the number of neurons in
the hidden layer is evaluated so as to get the best performance of
the ANN model. After evaluating several models, it is noticed

that beyond five neurons in the hidden layer, the performance of
the ANN model does not improve drastically, thus five neurons
are selected for the hidden layer.

speed even for untrained cases.

40

4.2 Training Data

FEM Model
ANN Model

35

Heating Speed (mm/s)

The training data play a key role in the development of themodel. During the training stage of the ANN model, it is noticed
that not only the size but also the quality of the data have apositive impact in the performance of the model.
Once the thermal elastic plastic analysis is completed, theresults are evaluated to discard the noisy data. As a result, 120
cases are selected as the training data. Then the data is normalized
to enhance the training process. Besides the training data, anotherset of data is prepared for the purpose of testing the tolerance ofthe model (unseen set), i.e. this set is not used to train the network,
but to confirm the performance of the untaught cases.

30
25
20
15
10

Plate Thickness: 10 mm-0.0035-0.0020-0.0015-0.0010-0.0005

Fig. 4 ANN model prediction for longitudinalbending intermediate points.
40

Heating Speed (mm/s)

Considering that the training data is divided randomly into
three subsets each time the ANN model is trained, different neuralnetworks trained on the same problem can give different outputs
for the same input. Thus several candidates are evaluated in order
to select the ANN model with the best performance. Once the
ANN model is selected, the response of the ANN model isevaluated in terms of: the training set and the unseen set.

FEM Model
ANN Model

35
30
25
20
15
10

Plate Thickness: 11 mm-0.0035

5.1 Training Set-0.0030-0.0025-0.0020-0.0015-0.0010Longitudinal Bending (rad)In order to have a complete view of the response of the ANN
model, the error generated by predicting the training data ismeasured and plotted as shown in Fig. 3 from the figure is noticed
that the error in the prediction is almost below 2%, thus it proves
the good performance for almost the given conditions.
5
Heating Speed
43

Error (%)

-0.0025

Longitudinal Bending (rad)5. Model Validation

2
1
0
0

-0.0030

20

40

60

80

100

120

140

ANN Output

Fig. 3 ANN model response.
5.2 Unseen Set
From Fig. 4, the relationship of the heating speed and thelongitudinal bending from a plate of 10 mm thickness is presented,
the figure depicts the response of the ANN model for conditions
that were not considered in the training data. As it is seen, theresponse correctly matches with the FEM analysis.
From Fig. 5, the relationship of the heating speed with thelongitudinal bending is presented again but this time is evaluatedfor an 11 mm plate thickness, it can be observed the good
estimation of the ANN model for intermediate values of plate
thickness. To confirm this results, several cases (square symbols)
are calculated by the FEM model for an 11 mm thickness plate.
The ANN model has a good capability to predict the heating

Fig. 5 ANN model prediction for plate
thickness intermediate points.

6. Conclusions
The required heating speed for a given plate thickness withcertain deformation is accurately predicted by an ANN modelthrough an inverse problem analysis. This model is capable topredict the heating speed by using the plate thickness and the four
components of inherent deformation at the middle of the plate.
From this study, the following conclusions are drawn:
ANN model can successfully solve line heating distortion as aninverse problem.
The topology and the training data used in the ANN model
have greatly affect the performance of the model.
The developed ANN model can successfully predict theheating speed to obtain certain distortion for a given steel plateeven for conditions outside the training data.

References
1)

2)
3)
4)

5)

Tango, Y, Ishiyama, M, Nagahara, S, Nagashima, T and
Kobayashi, J.: Journal of the Society of Naval Architects ofJapan, Vol. 193, pp. 85-95 (2003)
Vega, A.: Thesis, Osaka University (2009)
Pinzon, C., Plazaola, C., Banfield, I., Fong, A. and Vega, A.:
Ship Science & Technology, Vol 6, No. 12 (2012)
Osawa, N. Hashimoto, K. Sawamura, J. Kukuchi, J.,
Deguchi, Y. and Yamaura, T.: CMES, Vol. 20, No. 1,
pp.45-53 (2007)
Blandon, J., Osawa, N., Masanori, S., Rashed, S. and
Murakawa, H.: Proc. of The Twenty-fifth IOPEC, Kona,
Hawaii (2015)

International Course of Maritime & Urban Engineering / Abstract of Master Thesis

July 22, 2016

The Influence of Side Hull Location and Ship Speed on the Ship Wave
Pattern of a Trimaran with Wigley Hull Form
Felipe Rodrigues Modesto

Hull Form Design Sub-Area, Department of Naval Architecture and Ocean Engineering
Key Words: Trimaran, CFD, Ship Wave, Wigley hull

1. Introduction

Trimarans are well known for applications where high speeds
are required. To optimize this effect and the general performanceis necessary to know the best arrangement between the main hulland the two side hulls. For this initial study, CFD simulation wasused to analyze the wave pattern according the ship speed(Froude number Fn = 0.1, 0.5 and 0.767) and the position of sidehulls using η=0.45m and ξ=0m (A1), 2m (C), -1m (D). The test
condition and definition of the side hull position (η, ξ) is based on
Nozawa at el. (2007) as shown in Fig. 1.

pitch and heave were considered in order to obtain sinking andtrim in calm water. The flow field is solved in inertial earth-fixed
coordinate and ship motion is solved in non-inertial ship fixed
coordinate.

Fig. 2 Computational domain and grid system

3. Results

3.1 Single Wigley HullFig. 1 Trimaran hull arrangement
The trimaran is composed of three Wigley hull was proposed(Nozawa at el., 2007): 2m long main hull and 1m long side hulls.
The hull is described as a mathematical equation:y22B   2x    2z  
1     1    
2   L    d  First, a single Wigley hull is used to validate simulated wave
pattern and ship wave length. As shown in Fig. 3 the Kelvin wave
system including divergent and transverse waves are clear
observed. The wave length is a function of the Froude number:
 / L  2Fr 2 .

(1)

where B is the ship beam, L is the ship length and d is the shipdraft. (x,y,z) is the coordinate point on the ship hull. Firstly, asingle Wigley hull will be used to validate the wave pattern.

2. CFD Method

The grid was generated using Gridgen with 7 blocks (two foreach hull and the background) in a total of 6.5 million points. The
computational domain is defined in -0.5<x<3, -1.5<y<1.5 and-1<z< 0.2 as shown in Fig. 2. About the boundary conditions, theinlet had free stream speed inflow (the ship speed), the outlet hasexit condition, the sides boundaries are zero gradient and the top
and bottom have far field conditions. The overset grid wasassemble using Suggar library.
The software used for viscous flow simulation was
CFDSHIP-IOWA V4.5 and it’s based on 2nd order finite
difference method. With 6 degrees of freedom, in this study only

Fig. 3 Wave pattern for a single Wigley hull at Fr=0.767

3.1 Trimaran in different ship speed

In the trimaran case, larger wave lengths as the Froude number
increases is observed as shown in Fig. 4. Different from theclassic Kelvin wave system, the ship waves generated by the main
hull and side hulls would interact. In the highest Froude number,the divergent wave generated in the main hulls bow hits the side

hull bow. The wave trough appears between hulls and the large
wave trough area in the stern extends downstream at high speeds.

positioned behind the main hull. The distance the main hull andside hull is η=0.45m for all cases. The considered Froude number
is 0.767. The results are presented in Fig. 5.
For C hull, the divergent wave crest of the side hull bows
extends into the main hull bow. Compared with A1 hull, the wave
amplitude is smaller and the wave propagates in smaller area
behind the ship. For D hull, the side hulls run in the wave troughgenerated by the main hull. It implies that the hull wet area isreduced resulting in the lower friction. From the wave patternobservation, we believe the arrangements like C and D hull could
reduce the wave making resistance of a trimaran. This was also
concluded by Nozawa et al. (2007).

Fig. 5 Trimaran wave pattern for different side hull arrangement
at Fr=0.767. Top: C hull; bottom: D hull

4. Conclusions
Fig. 4 Trimaran wave pattern at different ship speed:
Fr=0.1, 0.5 and 0.767, top to bottom, respectively

3.1 Trimaran with different side hull positions

For different arrangements, A1 hull (ξ=0m) is the same
position used in the speed analysis. For C hull (ξ=2m) the sidehulls are ahead the main hull and for D hull (ξ=-1m) they are

The wave pattern has been simulated successfully by CFD for
single Wigley hull and trimarans. It is possible to reduce the wave
making resistance by a proper hull arrangement for a Trimaran.

Reference

1) Nozawa, K., Hayakawa, I., and Tsujiuchi, Y: Conf. of
JASNAOE, Vol.4, pp.21-24, 2007.