茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」

茨城大学工学部附属
防災セキュリティ技術教育研究センター
２０１６年度報告書

茨城大学重点研究プロジェクト「知的で持続可能な社会基盤および防災セキュリティ技術創出事業」
平成 28 年度報告書刊行にあたって
プロジェクト代表

呉智深

本研究課題は，平成 23 年 4 月に課題募集プロポーザルとその審査により茨城大学重点研究課題として認定され，工学部，教育学部および茨城大学センター教員から構成される異分野研究者の集う場として活動が始まりました．本年度は活動 5 年目を迎えることとなりました．
この報告書では，学術誌論文をはじめとする研究成果に加えて，参加メンバーの学術企
画の開催や参加，受賞例についても整理しましたが，「防災セキュリティ技術」という学際領域に類するテーマが示すように，昨年度に引き続き，多種多様な研究活動とその成果を収めてきたことがわかりました．
2016 年を顧みますと，4 月 14 日に熊本県益城町で最大震度７の地震が発生し，また，同月 16 日には同じ熊本地方を最大震度 7.3 の地震が発生した．季節が過ぎ，夏になると，台風がかつて無い移動経路を示し，3 つの台風が北海道に上陸，地すべり被害が野菜等農作物に甚大な被害が発生しました．このように，我々市民生活が営まれる都市域は，予想もしえない甚大な自然災害に見舞われる可能性が示されたと言えます．
このような状況をいかに早く察知し，安全で安心な都市を作ってゆくのか．防災セキュ
リティ教育研究センターだけではなく，日本の防災研究の永遠の課題なのかもしれません．
そのような中ではありますが，本誌では 2016 年度の我々の取り組みをご報告させて頂きました．類する教育研究を行っている皆様の何らかの参考になれば幸いです．
末筆とはなりますが，茨城大学重点研究課題として採用頂き，茨城大学の代表する研究
課題の 1 つとして諸方面の応援と援助を頂きました茨城大学に心から感謝申し上げますとともに，必ずしも十分でなかった研究交流にも関わらず，本誌に示す多大なる研究成果を上げている参加メンバーに心から敬意と謝意を表します．
今後の研究活動への努力をお約束し，関連する皆様に感謝を申し上げますとともに，ここに平成 28 年度の研究成果を報告させて頂きます．

平成 29 年 3 月吉日
プロジェクト代表
呉 智深茨城大学工学部附属防災セキュリティ技術教育研究センター
プロジェクト参加教員(2016 年度)

呉智深（工学部都市システム工学科・教授・センター長）

齋藤修（防災セキュリティ教育研究センター・特命教授・副センター長）

鎌田賢（工学部情報工学科・教授・副センター長）

桑原祐史（広域水圏環境科学教育研究センター・教授・センター幹事）

沼尾達弥（工学部都市システム工学科・教授）

今井

洋

原田

隆郎

（工学部都市システム工学科・准教授）

横田浩久（工学部電気電子工学科・准教授）

湊

淳

武田

茂樹

澁澤

進

（工学部情報工学科・教授）

羽渕 裕真（工学部情報工学科・教授）

外岡秀行（工学部情報工学科・教授）

車谷麻緒（工学部都市システム工学科・准教授）

石田智行（工学部情報工学科・助教）（工学部電気電子工学科・教授）（理工学研究科・教授）（工学部メディア通信工学科・教授）

－目次－

1. 活動概要－１－

2. 研究報告
Saifeldeen, M. A., Fouad, N., Huang, H., & Wu, Z.,
Advancement of long-gauge carbon fiber line sensors for strain
measurements in structures,
Journal of Intelligent Material Systems and Structures,
1045389X16665974 (2016-8).
－5－
Hiroshi Noguchi, Yasuhiro Ohtaki and Masaru Kamada,A university information system made robust against natural
disasters by taking advantage of remotely distributed campuses,
International Journal of Space-Based and Situated Computing, 6(3),147-154 (2016-11).
－15－

3.プロジェクト業績
活動実績
－23－
業績一覧
－26－

1.活動概要

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

防災セキュリティ教育研究センター 平成２８年度活動計画・実施結果調書
１． 技術・研究開発分野
担当者氏名：呉 智深
Email：zhishen.wu.prof@vc.ibaraki.ac.jp
・計画名：社会基盤を対象とした維持管理および防災/減災へ向けたセンサ技術・空間情報応用研究
・システムとしての防災・減災技術の確立検討（企業・自治体・学術連携）実施予定時期：平成 28 年 4 月 1 日～平成 29 年 3 月 31 日
１． 実施内容：・センサ技術の開発
光ファイバセンサ・カーボンファイバセンサ・RFID タグ・UAV・防災/気象用センサ
IC タグ（水位・加速度・傾斜・降雨・大気関連）
・センサデータの安定した通信/解析技術の開発と省電力化推進
マルチホップ通信による耐災害メッセージングシステム
・センサ技術の現地実証の推進と課題抽出
老朽化したインフラ構造物の災害リスクを考慮した維持管理計画（継続課題）
・アウトリーチとしての防災・減災、それらを含む環境教育の実施
・地元企業・学校等との学術連携実現
・他大学・企業・自治体連携での研究資金獲得
・自治体との各種連絡会議推進（茨城県・日立市・ひたちなか市等）
・国際共同研究を実施（アメリカ、英国、イタリア、中国、韓国等）
・大型プロジェクトを申請
２． 実施体制（注：外部の人も含む）
責任者：呉 智深（センター長）
メンバ：齋藤 修, 鎌田 賢，沼尾 達弥，今井 洋，羽淵 裕真，渋沢 進，湊 淳，横田 浩
久，原田 隆郎，武田 茂樹，外岡 秀行，桑原 祐史，車谷 麻緒，石田智行（茨城高専・東北大学・東京大学・青山学院大学の教員の正式参加を調整中）
３． 実施における課題： ・・・調整が必要な事項、予算計画など。ない場合は、特になしとする。
特になし．
４． 実施結果（年度末に記載）（結果） 現在の記述は途中経過なので年度末状況を書く必要あり。
・茨城県・水戸市連携による、内水氾濫監視システムの実証実験推進（H29 年 2 月より開始）
・茨城県との連携による UAV のダム長寿命化への応用検討（H27 年 7 月以降に実施）
・茨城県との連携による常陸大宮、引田橋における加速度センサ設置による橋梁長寿命化対応実証実験（H26 年 6 月より継続中）
・株式会社 KSK 構造診断研究所との連携による新潟県、国道 18 号妙高大橋における光ファイバ
センサ設置による橋梁健全性評価手法の実証実験（H287 年 11 月より実施）
・株式会社 KSK 構造診断研究所との連携による川根大橋におけるカーボンファイバセンサ設置
による橋梁振動モニタリング実証実験（H28 年 12 月より実施）
・中国の蘇通長江大橋（橋梁管理局と協力）でのインフラ構造物の早期損傷検知実験（H28 年 11月より実施）

1茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

青山学院大学：UAV 飛行におけるプロトコル確立研究連携
東京大学・長岡技術大学：橋梁長寿命化についての情報交換会
ひたちなか市立外野小学校・前渡小学校での環境・情報特別授業実施（H27 年 9 月）
宮城県名取市閖上地区の UAV による震災被害地アーカイブ映像撮影 宮城教育大学との連携
宮城県女川町・石巻市連携による地盤沈下調査（来年度継続）・UAV による震災アーカイブ映像撮影
日本地球惑星連合(JPGU)2015：セッション「UAV が拓く新しい世界」コンビーナとして UAV の活用を推進。
茨城県生活環境部・土木学会茨城支部・㈱新星コンサルタント等において UAV 操作指導・安全教
育を実施。
常総市水害（９月１０日）の UAV による調査・記録・分析に協力（国交省委託事業の一環）（課題）
少々，計画したイベントが多いため，絞り込む事も重要と考える．

６．その他（参考資料、報告書など）（注）複数の計画がある場合は、必要に応じて欄を追加する。

2

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

２．人材育成担当者氏名： 呉 智深
１． 計画名・実施予定時期

Email： zhishen.wu.prof@vc.ibaraki.ac.jp

計画名：「社会基盤を対象とした維持管理」に関する授業の学部～社会人への展開
実施予定時期：平成 28 年 4 月 1 日～平成 29 年 3 月 31 日
２． 実施内容：
下記の学内授業実施および学生国際会議企画を行い、研究で得た最新情報を学部学生へフィードバックし、また、社会人ドクターの教育を通じて高度化する．
①学部学生に対する教育
通信理論，ソフトウェア実現，空間情報工学②大学院博士前期課程学生に対する教育
構造物の数値解析法，衛星画像および地理情報の解析法，社会基盤情報処理特論③社会人（専門技術者向）に対する教育
土木学会茨城会で行っているイブニングセミナ(地域の技術者対象)に防災・センシン
グ関連で講座を出す④その他：小中高校への環境。防災教育の提供
３． 実施体制（注：外部の人も含む）
責任者：呉 智深（センター長）
メンバ：鎌田 賢，齋藤 修, 沼尾 達弥，今井 洋，羽淵 裕真，渋沢 進，湊 淳，桑原 祐史，
横田 浩久，原田 隆郎，武田 茂樹，外岡 秀行，車谷 麻緒，石田 智行
４． 実施における課題： ・・・調整が必要な事項、予算計画など。ない場合は、特になしとする。
特になし

５． 実施結果（年度末に記載）（結果）現在の記述は途中経過なので年度末状況を書く必要あり。
・茨城県「いばらき近未来実証推進事業」プロジェクト推進委員会委員（アドバイザー）として、UAV を含むロボット実証試験に安全管理・実証方法についてアドバイスを行っている（齋藤、桑原、
鎌田）。

（課題）
特になし
６．その他（参考資料、報告書など）

3茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

３．資金獲得担当者氏名： 呉 智深
１． 計画名・実施予定時期
・・

Email：zhishen.wu.prof@vc.ibaraki.ac.jp

計画名：大型プロジェクトの獲得
実施予定時期：平成 27 年 4 月 1 日～平成 28 年 3 月 31 日

２． 実施内容：
科研費はセンターメンバー個々人がチャレンジすることとし，それ以外の大型プロジェクト（国土交通省，経済産業省，総務省）に，共同研究等で関係のある産官学学外機関との連携を取り，チャレンジする．
昨年度に不採択となった概算要求書をベースとして生かす。
３． 実施体制（注：外部の人も含む）
責任者：呉 智深（センター長）
メンバ：鎌田 賢，齋藤 修, 沼尾 達弥，今井 洋，羽淵 裕真，渋沢 進，湊 淳，桑原 祐史，
横田 浩久，原田 隆郎，武田 茂樹, 外岡 秀行，車谷 麻緒，石田 智行
４． 実施における課題： ・・・調整が必要な事項、予算計画など。ない場合は、特になしとする。
大型プロジェクトの申請に関する作業時間をより確保する必要がある。

５． 実施結果（年度末に記載）（結果）現在の記述は途中経過なので年度末状況を書く必要あり。・平成 26 年度募集 SCAT 研究費助成獲得 青山学院大学戸辺教授との連名「複数異種 UAV 間協調動作プロトコルの開発と広域環境観測への応用」
複数の UAV を協調動作させる。防災への応用が期待できる。（H27 年度から 3 年）
また，年度末に小額の外部資金による成果を重ねることにより，NEC との大型共同研究に発展し
実現した．
（課題）
特になし
６．その他（参考資料、報告書など）

42.研究報告（H28 年度参加教員発表の代表的な学術論文集）

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

Original Article

Advancement of long-gauge carbon
fiber line sensors for strain
measurements in structures

Journal of Intelligent Material Systems
and Structures
1–10
Ó The Author(s) 2016
Reprints and permissions:sagepub.co.uk/journalsPermissions.nav
DOI: 10.1177/1045389X16665974
jim.sagepub.com

Mohamed A Saifeldeen1, Nariman Fouad1, Huang Huang2 and Zhishen
Wu1

Abstract
This article proposes a new technique that advances long-gauge carbon fiber line sensor technology, with and without
post-tensioning of the sensor, to measure changes in strain levels in structural areas. Carbon fiber line sensors were fabricated to produce a slim high-strength sensor with a diameter of less than 1.4 mm using a carbon fiber tow with a widthof 6 mm. A theoretical analysis of these sensors as well as several series of experiments was conducted to investigate
the effect of fiber arrangement on the error compensation of the carbon fiber line sensors. The results revealed thatusing two sets of carbon fiber line sensors, one as an active sensor and the other to compensate the errors of the first,
is an effective method when both sensors have a convergent fiber arrangement and change in resistance. A posttensioning method was implemented to enhance the overall behavior of the sensor. The results showed that the posttensioning method yields significant improvement in the linearity and cyclic ability up to 6000 microstrains and reduces
the fluctuation errors in the change in resistance from 60.031% to 60.007%. Finally, the possibility of repairing damaged
carbon fiber line sensors is also discussed.
Keywords
Carbon fibers, sensors, resistivity, post-tension, strain measurements

Introduction
In recent decades, carbon fiber–reinforced plastics(CFRP) have been widely investigated and applied in
the aerospace, civil engineering, and auto industries
because of their superior strength, stiffness-to-weightratios, low density, long-term durability, and high resistance to chemical corrosion. In addition to theseadvantageous properties, another important characteristic of CFRPs is their favorable electrical conductivity
and piezoresistivity (Schueler et al., 2001; Wu andYang, 2006; Yang et al., 2006). In general, the resistivity of CFRPs increases linearly with applied tension
and decreases linearly under compression, demonstrating piezoresistive effects. These electrical properties
produce resistance variations in CFRPs undergoingchanges in their mechanical, chemical, and thermal
environments and thus render CFRPs potentially applicable as sensors of strain, stress, bio-feedback, damage,chemical exposure, and temperature (Ogi and Takao,
2005; Park et al., 2005; Shui and Chung, 1996; Wang
and Chung, 2006; Wu et al., 2005, 2007).
Sensors can be separated into two types based on
their gauge length: point sensors and long-gauge

sensors. Point sensors are typically mounted near key
parameters, as they have high sensitivity and precision.
However, these sensors are expensive and are not suitable for detecting parameters in a large area or global
sensing. In contrast, long-gauge sensors can be used for
global sensing, which is useful for providing a comprehensive evaluation of the integrity of a structure(Huang and Wu, 2010).
Huang et al. (2010, 2012) studied the electrical sensing properties of CFRP strips to produce a CFRP
strip long-gauge sensor for measuring low strain levels.
It was found that the effective sensing behavior of a
CFRP strip is related to its effective gauge length, andthe transverse connection in a CFRP strip affects the1

Department of Urban and Civil Engineering, Ibaraki University, Hitachi,
Japan
2
Key Laboratory of Concrete and Prestressed Concrete Structure of the
Ministry of Education, Southeast University, Nanjing, China
Corresponding author:
Zhishen Wu, Department of Urban and Civil Engineering, Ibaraki
University, Hitachi 316-8511, Japan.
Email: zhishen.wu.prof@vc.ibaraki.ac.jp

Downloaded from jim.sagepub.com by guest on September 1, 20165

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

2

Journal of Intelligent Material Systems and Structureslinear strain response, especially when sensing is in alow strain range. The strain response properties of
CFRP strips became more linear when the width-tolength ratio decreased. Moreover, when the gauge
length of a CFRP strip was 500 mm or longer, its strain
response exhibited a good linear relationship with theapplied strain even at the low strain level of 200 microstrains. The strain response of a 500-mm-long CFRP
strip maintained stable linearity throughout exposure
to long-term cyclic tensile strain.
The change in resistance DR/R of a carbon fiber(CF) sensor is inversely proportional to the change intemperature because of the negative temperature
resistivity of micro-CF. The measured signal fromthe CF sensors is related to the change in strain on
the structural object but is also impacted by undesired effects from conditions such as temperature andhumidity. CFs used continuously as the strain sensing
elements in CF sensors clearly exhibit thermoelectriceffects, reducing the reliability of the results calculated from these measurement signals (Huang et al.,2011; Huang and Wu, 2010). For carbon fiber line
(CFL) sensors, the relationship between the change
in resistance (DR/R), the applied strain e, and theexternal errors (e) can be expressed as follows, where
Gf is the gauge factorDR= G f 3 ð e + eÞRð1ÞThis problem of dual sensitivity to strain and othereffects has plagued CFL sensors, and compensation forthis error is necessary to advance a CFL sensor thatyields effective and reliable strain measurements.
Selecting and applying an appropriate compensating
CF sensor is crucial to achieve improvement in theaccuracy of results. The compensation sensor must be
fabricated from the same material and have the same
physical properties and gauge length as the active sensor and must only be subjected to interference effects
and never to any quantity of applied strain (e).
Huang and Wu (2012) also developed a signal processing method used to treat the structural strain
responses of long-gauge CF sensors for static anddynamic strain measurements. This static denoising
method is based on measuring the error range of CF
sensors, as determined over long-term continuous loading and unloading experiments. For the experiment
involving one-measure-time each second, the influenceof noise on CF sensors followed a normal distribution,with a standard deviation of 650 microstrains. For theexperiment involving 25-measure-time each second, thesignals were concentrated in a smaller range, and theprobability density showed a clear increase. For signal
selection based on multiple measuring times, the measured error range of CF sensors was consolidated from
650 to 610 microstrains.

This article presents a new approach for obtaining along-gauge CFL sensor. The theoretical and experimental investigations discussed here clarified the effect offiber arrangement on the error compensation of CFL
sensors. Furthermore, a post-tensioning method was
implemented to enhance the sensing behavior and cyclic
ability of the CFL sensor under conditions of low andhigh strain. Finally, the possibility of repairing damaged CFL sensors is also discussed.

Theoretical background on the measuring
circuit
The principle behind the operation of CFL sensors isbased on establishing a relationship between the change
in resistance DR/R and the strain e. The resistance of a
CFL sensor can be expressed as
R=r3

 
L
A

ð2Þ

where r is the resistivity, L is the effective gauge lengthof the sensor, and A is the cross-sectional area of thesensor. DR/R can be expressed asDR
Dr DL DA
=f
,
,
R
r L A

ð3Þ

According to the piezoresistive effect of semiconductor materials, the change in resistivity has a muchgreater effect than simple changes in geometry on
DR/R (Huang and Wu, 2010). The DR/R of the sensor
can therefore be expressed as
DR Dr
ﬃ
R
r

ð4Þ

Equation (4) represents the ideal condition, in which
all the micro-CFs are ideally aligned and separated by
epoxy resin, and the transverse electrical contact’s contribution to the sensor’s conductivity can be neglected.
Then, the electrical resistance can be obtained by theparallel circuit approach from (Yang and Wu, 2003)
R0 =

Rf
nf

ð5Þ

where R0 is the initial resistance of the CFL sensor, Rf
is the resistance of one microfiber, and nf is the numberof fibers in the sensor. In fact, owing to manufacturing
defects inherent in CFL production, the arrangementof the microfibers in each sensor is different. To reflect
practical conditions, DR/R can be written asDRDr= ð 1  hÞ
R
r

ð6Þ

where h is a coefficient that reflects the transverse
electrical contact’s contribution to the sensor’s

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3

Table 1. Properties of carbon fiber tow and epoxy resin.
Material

Thickness(mm)

Tensilestrength

Tensilemodulus (GPa)Tensileelongation (%)

Volume resistivity(O cm)

Carbon fiber T700SC
Epoxy resin FR-E3P

0.136

4.9 GPa51.9 MPa

230
3.43

2.1
1.513

1.6 3 1023
1010–1020

conductivity. Thus, for any given strain level, DR/R
differs from one sensor to another, as does the gauge
factor.
By applying the Wheatstone bridge circuit to measure
the total output signal of the active and compensation
sensors, the change in resistance can be expressed asDR= Gfw 3 ðew + ew Þ  Gfc ec
Rð7Þwhere Gfw , ew , and ew are the gauge factor, applied
strain, and external effects errors of the active sensor,
respectively; and Gfc and ec are the gauge factor andexternal effect errors of the compensation sensor,
respectively. Under ideal conditions, when (1) the compensation sensor is subjected to only external effects,(2) both sensors have the same gauge factor Gf , and (3)both sensors undergo the same external effects, theerrors due to external effects will be effectively eliminated, and the output signal will be related to theapplied strain only.
As described in this section, the two sensors will not be
identical because of differences in their fiber arrangements, resulting in differences in their DR/R and gauge
factors. Thus, errors caused by external effects will not be
entirely removed; however, these errors can be reducedby choosing a compensation sensor with a gauge factor
that converges on the gauge factor of the active sensor.

Experimental procedure and materials
The CF’s transverse connection, or tow, consists ofnumerous continuous microcarbon fibers. Each fiber
can be considered as a sensing cell, such that the CF
sensor’s output signal is the integrated response fromall of the sensing cells. Under ideal conditions, a CF
tow can be considered a parallel circuit that is composed of large numbers of micro-CFs. Under actual
conditions, the microfibers are not completely straightened or arranged in parallel due to manufacturing
defects, such as misalignment and breakage of fibers.
Because the fiber distribution in this transverse connection introduces variability, the CFs of the samples inthis study were pre-tensioned for 24 h under 500 microstrains to make the fibers as straight as possible.
Subsequently, to produce a CFL sensor with a gauge
length of 500 mm, both ends were fully filled with conductive resins to improve the electrical contacts to each

Figure 1. Schematic of the CFL sensor in its processing fixture.

of the CFs in the cross section and to avoid the errors
from contact resistance between CFs and the electrodes(Park et al., 2005), and then, the electrodes were connected to the conductive resin at both ends of the CFs
with tin solder and copper cables. The CFs were thenimpregnated with epoxy resins and collected together
manually to form a CFL sensor with a diameter ofapproximately 1.4 mm. Furthermore, the ends of the
fixture used to hold the CFs in place were made ofbasalt fiber–reinforced polymer (BFRP) sheets andwere bigger than the ends of the measurement sensor,
thus providing enough bonding force to form the CFL
sensor. The impregnated CFL sensor was cured at atemperature of approximately 45°C for 3 days, maintaining the sensor under tension until it was completely
hardened. Finally, the tensile stress was released andthe CFL sensor was ready to be installed at its measurement location, as shown in Figure 1. For all of theexperiments in this study, the CFL sensors were
installed on homogenous elastic glass fiber plates.
The CF tow used in this study was T700SC, produced by Toray Industries, Inc. The epoxy resin used
was FR-E3P, produced by Nippon Steel Composite
Co., Ltd, a bonding material approved by the Japan
Society of Civil Engineers. The properties of thesematerials are shown in Table 1.
To measure and monitor electrical strain, a CFL sensor must be connected to an electrical circuit that is capable of measuring changes in resistance corresponding tostrain. A data measurement system was constructed witha Wheatstone measuring bridge connecting the active
and compensation sensors, as shown in Figure 2.

Discussions
The effect of gauge factor on the compensation
methodTo study the effect of the change in the gauge factor on
the compensation method, three sensors CFL1, CFL2,

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Journal of Intelligent Material Systems and Structures

Figure 3. DR/R of CFL1, CFL2, and CFL3 relative to thereference strain.

Figure 2. Connection of the active and compensation sensors
with a Wheatstone bridge.

and CFL3 were tensioned individually under 750 microstrains, and their measured DR/R signals were compared with the strain gauge as a reference strain.
Figure 3 shows the behavior of the three sensors tested,
and it is clear from the results that CFL1 and CFL2 hadconvergent DR/R, whereas DR/R for both of these sensors diverged from that of CFL3.
In these experiments, the same CFL1 was tested
three times under a cyclic loading–unloading tension
test from 0 to 750 me with a loading rate of 1 kN/min(strain rate of 185 me/min) under a stable laboratory
conditions (18°C–20°C and 25%–30% relative humidity). The first test (group S1) did not include a compensation sensor. For the second and third tests (groups S2and S3), the same sensor used in group S1 was connected with CFL2 and CFL3 as compensation sensors,
respectively.
From Figure 4(a) to (d), the cyclic behavior of CFL1
exhibited some error, which can be considered to be
due to the external effects discussed in section‘‘Introduction.’’ To reduce these errors, a compensation
sensor was connected with the active sensor in groups
S2 and S3. Strain signal measurements of group S2
showed good stability, and the DR/R error was reduced
from 0.022% to 0.007%, a reduction percentage of
68.2%. On the other hand, for group S3, the DR/R
error was reduced by a small value: from 0.022% to0.015%, a reduction percentage of 31.8%. From thecomparison of the three groups S1, S2, and S3 shown in
Figure 4(d), it can be concluded that use of a compensation sensor with a gauge factor closer to that of theactive sensor can reduce the DR/R error significantly.
These results are consistent with the theoretical
approach in section ‘‘Theoretical background on themeasuring circuit.’’

Performance of CFL sensors under different strainlevelsThe behavior of group S2 was studied under different
strains to define the sensor’s error in the full range ofstrain levels. Thus, a cyclic tension test was applied inseven strain ranges to determine the cyclic behavior of
the sensor. The tension loading–unloading cycle wasrepeated 30 times under each strain level: 300, 500, 750,
1000, 2000, 3000, and 4000 microstrains. All ranges
were tested under approximately the same environmental conditions and load rating.
Figure 5(a) shows the relationship between the average DR/Rs over 30 loading cycles for each of the strainlevels, relative to the reference strain. It is clear from
Figure 5 that under higher applied strain, the measured
signal exhibits poor linearity, showing instead a curvature that increases as the strain reaches maximum levels. Furthermore, the slope of the curvature increases
with the increase in the strain value, and then, it gradually stabilizes in strain levels higher than 3000 microstrains, and it seems to be constant which has
approximately average value of about 0.00049. To
examine the relationship between signal fluctuationand maximum strain level from low to high strain levels, Figure 5(b) shows the distribution of the measured
signal’s fluctuation through the 30 loading–unloading
cycles for each of the seven experimental strain ranges.
The errors of the signals under the different strain levels follow a normal distribution curve; this normal distribution lies entirely within the range of random
extended signal fluctuation. Figure 5 shows that there
is no significant change in signal fluctuation for the
first three strain levels (300, 500, and 750 microstrains);
the errors then increase with increasing strain until anupper limit of 3000 microstrains, after which the error
appears to stay approximately constant. Table 2 illustrates the fitted equations and errors at each of thestrain ranges; the errors were calculated to represent a
95% of the normal distribution, as calculated by standard deviations.

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5

Figure 4. DR/R of CFLs under conditions of cyclic loading: (a) for group S1, (b) for group S2, (c) for group S3, and (d) the errors in
DR/R for each group.

Figure 5. (a) The CFL sensor’s average DR/R over 30 loading cycles from 300 to 4000 me and (b) the errors in DR/R of the CFL
sensor under different strain levels.

During the fabrication of the CFL sensors, the CFs
were pre-tensioned so that all of the microfibers were as
straight as possible; in fact, however, not all of the microfibers could be completely straightened and would therefore not be pre-tensioned. As a result, at the beginning of
the tests, the tension force F was not evenly distributed
to all of the microfibers. Each fiber received a different
magnitude of the force (F1, F2, ., Fn), and some fibers
did not receive any force (F = 0) because of the windingof the fibers upon themselves. As the force of applied
tension increased, some of the wound fibers also began
to receive force, becoming active microfibers. Thus, thegauge factor of the active sensor differed from the compensation sensor, causing additional errors in themeasured signal. These errors increased with increased
applied strain, until reaching a limit at which the most of
microfibers were active fibers. The incremental increasein error therefore has an upper limit above which it will
not increase.
Regarding the curvature trend that appeared in themeasured DR/R of the signals under high levels of
applied strain, this phenomenon is considered to becaused by creep deformation from the resin, relaxationof the polymer matrix resin which is a viscoelastic material, and a slight elongation of the microfibers themselves. Inasmuch as the sensor was fixed from bothends on the glass fiber test plate, the slight elongationthat occurred prevented full tensioning of the sensor on

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Journal of Intelligent Material Systems and Structures

Table 2. The results of tests of the CFL sensor under different strain levels.
Maximum strain (me)Maximum DR/R (%)

Fitted equations

Errors DR/R (%)

300
500
750
1000
2000
3000
4000

0.091
0.152
0.224
0.33
0.75
1.195
1.61

DR/R = 0.0003 3 e 2 0.0065
DR/R = 0.0003 3 e 2 0.0076
DR/R = 0.0003 3 e 2 0.0124
DR/R = 0.0004 3 e 2 0.0007
DR/R = 0.0004 3 e 2 0.0782
DR/R = 0.0004 3 e 2 0.126
DR/R = 0.0004 3 e 2 0.1693

60.0057
60.0063
60.0072
60.01160.021460.0289
60.031

CFL: carbon fiber line.

the plate, resulting in poor sensor sensitivity to low
strains.

Post-tensioning method to enhance the behavior of
CFL sensor
The tensioned fibers of fiber-reinforced plastic (FRP)
composites did not exhibit creep, whereas significant
creep occurred in the resin; therefore, the creep strain
in the entire FRP material can be very limited if thefibers in the FRP are sufficiently straight (Everett,1996). However, limitations of the production technology result in unevenness from fiber movements, such as
local bending and skewedness, which are unavoidable.
The elimination of creep deformation in the resin
would allow stress to be uniformly transferred throughthe resin (Soudki, 1998). Therefore, it was consideredthat the unevenness of the fibers could be adjusted bypost-tensioning along the axial direction of the longitudinal fibers. The resin in the CFL sensor continues toundergo creep deformation when it is subjected to asustained load, allowing the possibility that the fibers
could interact in the resin. During this post-tensioning
process, the fibers tend to straighten because of resin
creep, and their previously occurring unevenness canbe adjusted, as shown in Figure 6.
To achieve this purpose, the CFL active and compensation sensors were post-tensioned after hardening
using a tensile testing machine under a stress level of
0.60 fu for 3 h. Subsequently, the sensors were installed
on a glass fiber test plate, as before. The results of the
post-tensioning test are shown in Figure 7, in which it
can be seen that the creep in the CFL sensor increased
with increased loading time until 2 h, after which thecreep remained constant. Therefore, 2 h of loading
eliminated errors from resin creep.
Tests of the sensor under the same seven strain levels
were repeated to verify the enhancement percentage ofthe post-tensioning method. Figure 8 shows the performance of the sensors under the different strain levels,and the high degree of linearity of the post-tensioned
CFL sensor is evident from Figure 8 for all strain levels
from low to high. In addition to the enhanced linearity,
the errors in DR/R were decreased, becoming constantFigure 6. Mechanism of the post-tensioning process.

Figure 7. Results of post-tensioning tests of the CFL sensor.

at all strain levels, as apparent from Figure 8 andTable 3.
As a result of the post-tensioning of the CFL sensor,
most of the microfibers were sufficiently straightened
because of resin creep, and the previous unevenness offibers was adjusted, resulting in a more uniform load
carrying capacity. Moreover, the gauge factor of theactive and compensation sensors will be constant andstable at any strain level; consequently, the errors in themeasured signal can be limited and stabilized. From
the fitted equations in Table 3, the gauge factor at any
strain level has a constant value of 5, and 95% of theerrors are within approximately 60.007% (approximately 614 microstrains). Finally, Figure 9 shows acomparison between the errors of the measured signal

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7

Table 3. Results of tests of the post-tensioned CFL sensor under different strain levels.
Maximum strain (me)Maximum DR/R (%)

Fitted equations

Errors DR/R (%)

300
500
750
1000
2000
3000
4000

0.152
0.248
0.36
0.484
1.006
1.51
2.02

DR/R = 0.0005 3 e 2 0.0092
DR/R = 0.0005 3 e 2 0.0098
DR/R = 0.0005 3 e 2 0.0167
DR/R = 0.0005 3 e 2 0.0271
DR/R = 0.0005 3 e 2 0.0364
DR/R = 0.0005 3 e 2 0.0432
DR/R = 0.0005 3 e 2 0.0575

60.0069
60.00760.007160.0068
60.0068
60.00760.0072

CFL: carbon fiber line.

Figure 8. (a) The post-tensioned CFL sensor’s average DR/R over 30 loading cycles from 300 to 4000 me and (b) fluctuation errors
in DR/R of the post-tensioned CFL sensor under different strain levels.

of the standard and post-tensioned CFL sensors undereach strain level.
The measuring error of a CFL sensor generally
includes a systematic error and a random error. The
systematic error is a basic measure of sensor performance; on the other hand, the random error is generally caused by unstable external conditions, and it isdifficult to forecast but can easily be reduced using themulti-measuring method in Huang and Wu (2012). By
increasing the number of measurements taken in 1 sfrom 1 to 25, the total error can be reduced to 65
microstrains, as shown in Figure 10.

Efficiency of the post-tensioned CFL sensor underhigh strains
Two specimens of post-tensioned CFL sensors were
utilized to clarify the efficiency of the post-tensioning
method in measuring high strain levels and elucidate
the effects of post-tensioning on the gauge factor. The
first specimen was tested under cyclic loading–unloading tensile strain, after having already beentested up to 4000 microstrains in the investigation discussed in section ‘‘Post-tensioning method to enhance
the behavior of CFL sensor.’’ The rate of loading
increased gradually by increments of 1000 microstrains
to evaluate the limits of the sensor’s cyclic ability andthe linearity of its signals. As is evident from

Figure 9. Comparison of the errors in the measured signal of
the standard and post-tensioned CFL sensors under each strainlevel.

Figure 10. Comparison of the fluctuation errors whenmeasurements are taken from 1 to 25 times a second.

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Journal of Intelligent Material Systems and Structures

Figure 11. The post-tensioned CFL sensor’s average DR/R over 30 loading–unloading cycles under high strains of (a) 5000 me, (b)6000 me, (c) 7000 me, and (d) 8000 me.

Figure 12. Signal fluctuation errors of the post-tensioned CFL
sensor under higher strain levels.

350

Δ R/R - Strain
Stress - Strain

8

300
250

CFL Linear stage

6200

Gf = 5

150

4

100

2

CFL Non-linear
stage

0
0

2000

4000

6000

8000

Stress σ (MPa)10

Δ R/R %

Figures 11(a) to (d) and 12, the post-tensioned CFL
sensor functioned well until 6000 microstrains, above
which the sensor signal exhibited poor linearity relative
to the reference strain, and the error clearly increased
at the higher levels. It is evident from Figures 11 and12 that the loading trend converged with the unloading
trend until 6000 microstrains, above which the unloading trend neutralized and began to change its slope.
This phenomenon can be considered a result of theinitiation of microfracture to some of the microfibers.
By means of loading–unloading tension cycles, thedamage increases gradually resulting in stiffness reduction and some residual increase in the electrical resistance, which caused a small amount of randomvariation in the resistivity of the sensor during loading
and unloading.
The second post-tensioned specimen was tensioned
directly to an adequate strain of approximately
10,000 microstrains to investigate the overall behavior
and changes in the gauge factor values relative to thereference strain gauge. The result clarified that the valueof the gauge factor deviated substantially between 6000
and 7000 microstrains, as is apparent from Figure 13.
The results from this second specimen’s limits of linearity and gauge factor are compatible with the first specimen, at 6000 microstrains and 5, respectively.
For the second specimen, some cracks and separation between the microfibers occurred when the specimen was loaded with 10,000 microstrains, as shown in
Figure 14. This specimen was tested again under 30

50

0
10000

Reference SG (με)

Figure 13. Performance of the post-tensioned CFL sensor up
to 10,000 microstrains.

cycles of loading under approximately 5000 microstrains, 50% of the maximum strain. Because of the

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Saifeldeen et al.

9repaired sensor was then determined. Figure 15 showsthat the signal from the repaired sensor exhibited good
linearity until 3000 microstrains, after which the sensor
lost stability and linearity and fluctuation errors
increased.
Figure 16 shows a comparison of the post-tensioned
CFL sensor before and after the repair, demonstratingthat the sensor exhibited excellent linearity before any
damage but showed poor linearity after damage, relative to the reference strain, with fluctuation errors in
DR/R increased to a high value of 0.0255%. Figure 16
also shows that the repaired sensor had the same gauge
factor as the normal mode of the post-tensioned sensor
until 3000 microstrains. Moreover, the errors werereduced to 0.0105%. In general, it can be said that it ispossible to repair the CFL sensor if its fibers are microdamaged by stress or external effects.

Figure 14. Optical photographs of the CFL sensor (a) after
damage under 10,000 microstrains and (b) after repair.

separation between the fibers, the stress transferred into
the fibers irregularly, affecting the stability of the measured signal. Therefore, a method of repairing the sensor is needed to control the regularity of stresstransferring into the fibers. For this purpose, the sensor
was repaired by re-impregnating the collected microfibers with epoxy resin. The cyclic behavior of theConclusion
This article presents a new technique for measuring
strain levels with a CFL sensor. The CFL sensor was
fabricated manually to produce a long-gauge line sensor
with a small diameter of less than 1.4 mm. The sensing
errors of the CFL sensors were studied theoreticallyFigure 15. (a) The repaired CFL sensor’s average DR/R over 30 loading cycles from 500 to 5000 me and (b) error comparison of
the post-tensioned CFL sensor before and after the repair under different strain levels.

Figure 16. Comparison of the post-tensioned, damaged, and repaired cases of the CFL sensor: (a) average DR/R over 30 cyclicloading tests up to 5000 me and (b) signal fluctuation errors in DR/R.

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10

Journal of Intelligent Material Systems and Structuresand experimentally. Some important conclusions canbe drawn as follows:
1.

2.

3.

4.

5.

The output signal of CF sensors needs to becompensated with an associated compensation
sensor to reduce the undesired effects fromexternal conditions. It has been demonstrated
that a compensation sensor with a fiber arrangement and gauge factor that converges on thoseof the active sensor effectively reduces error.
The CFL sensor signal demonstrates good linearity with the applied strain under low strainlevels; however, some curvature appeared andincreased under higher strain levels. The signal
fluctuation errors increased with increased
applied strain levels up to 3000 microstrains,
and then, the signal fluctuation error appears toremain constant.
A method of post-tensioning to control the initial creep of the CFL sensor was applied by tensioning the CFL sensor for 3 h under sustained
stress of 0.60 fu. The results showed that the
post-tensioning method can significantly
enhance the linearity of the measured signals
and can eliminate or reduce errors.
The post-tensioned CFL sensor exhibits a good
cyclic ability and stable gauge factor up to6000 microstrains and can reduce the fluctuation errors in the DR/R from 60.031% to60.007%. Beyond 6000 microstrains, the sensor
exhibits poor linearity relative to the reference
strain.
Further results showed that the sensor can be
repaired if some damage to the microfibers has
occurred; the repaired CFL sensor can be reusedfor strain measurements up to 3000 microstrains
with acceptable errors.

Declaration of Conflicting Interests
The authors declared no potential conflicts of interest withrespect to the research, authorship, and/or publication of thisarticle.

Funding
The author(s) declared no potential conflicts of interest withrespect to the research, authorship, and/or publication of thisarticle.

References
Everett RK (1996) Quantification of random fiber arrangements using a radial distribution function approach. Journal of Composite Materials 30(6): 748–758.

Huang H and Wu ZS (2010) Small signal recognition system
of CFRP strips during low strain rate tensile testing. Journal of Applied Mechanics 13: 963–970.
Huang H and Wu ZS (2012) Static and dynamic measurementof low-level strains with carbon fibers. Sensors and Actuators A: Physical 183: 140–147.
Huang H, Wu ZS and Yang C (2010) Formulation in sensor
performance of self-sensing carbon fiber slip in low levelstrains by curve fitting. In: Proceedings of the 3rd Asia
Pacific workshop on structural health monitoring(APWSHM), November 2010, Tokyo, Japan.
Huang H, Wu ZS and Yang C (2011) An integrated monitoring system for damage detection by carbon fibers and optical fibers. In: Proceedings of the 8th international workshop
on structural health monitoring (IWSHM) 13–15 September, Stanford, USA.
Huang H, Yang C and Wu ZS (2012) Electrical sensing properties of carbon fiber reinforced plastic strips for detecting lowlevel strains. Smart Materials and Structures 21(3): 035013.
Ogi K and Takao Y (2005) Characterization of piezoresistance behavior of a CFRP unidirectional laminate. Composites Science and Technology 65(2): 231–239.
Park JM, Li SI and Choi JH (2005) Cure monitoring and residual stress sensing of single carbon fiber reinforced epoxy
composites using electrical resistivity measurement. Composites Science and Technology 65(3): 571–580.
Schueler R, Joshi SP and Schulte K (2001) Damage detectionin CFRP by electrical conductivity mapping. Composites
Science and Technology 61(6): 921–930.
Shui X and Chung DDL (1996) A piezoresistive carbon filament polymer-matrix composite strain sensor. Smart
Materials and Structures 5(2): 243.
Soudki KA (1998) FRP reinforcement for prestressed concrete structures. Progress in Structural Engineering andMaterials 1(2): 135–142.
Wang S and Chung DDL (2006) Self-sensing of flexural
strain and damage in carbon fiber polymer–matrix composite by electrical resistance measurement. Carbon 44(13):2739–2751.
Wu ZS and Yang CQ (2006) Electrical and mechanical characterization of hybrid CFRP sheets. Journal of Composite
Materials 40(3): 227–244.
Wu ZS, Shao YX, Iwashita K, et al. (2007) Strengthening of
preloaded RC beams using hybrid carbon sheets. Journalof Composite Materials 11: 299–307.
Wu ZS, Yang CQ, Harada T, et al. (2005) Self-diagnosis of
structures strengthened with hybrid carbon-fiber reinforced polymer sheets. Smart Materials and Structures
14(3): S39.
Yang CQ and Wu ZS (2003) Theoretical/experimental investigations on electrical resistance change of carbon fibers.
In: Proceedings of the first International Conference ofstructural health monitoring and intelligent infrastructure,
Tokyo, Japan, 13–15 November, pp. 1295–1301.
Yang CQ, Wu ZS and Ye LP (2006) Self-diagnosis of hybrid
CFRP rods and as-strengthened concrete beams. Journalof Intelligent Material Systems and Structures 17: 609–618.

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This is the authors' final submitted version of the paper published by Int. J. of Space-Based and Situated Computing, 20161Vol.6, No.3, pp.147 - 154. http://dx.doi.org/10.1504/IJSSC.2016.10001161

A university information system made robust
against natural disasters by taking advantage of
remotely distributed campuses
Hiroshi Noguchi
Center for Information Technology,
Ibaraki University,
Hitachi 316-8511, Japan
Fax: 81-294-38-5158
E-mail: hiroshi.noguchi.daemon@vc.ibaraki.ac.jp

Yasuhiro Ohtaki
Center for Information Technology,
Ibaraki University,
Hitachi 316-8511, Japan
Fax: 81-294-38-5158
E-mail: yasuhiro.ohtaki.lcars@vc.ibaraki.ac.jp

Masaru Kamada*
Department of Computer and Information Sciences& Center for Information Technology,
Ibaraki University,
Hitachi 316-8511, Japan
Fax: 81-294-38-5158
E-mail: masaru.kamada.snoopy@vc.ibaraki.ac.jp*Corresponding author
Abstract: We present an information system designed for a university on the basis of its
experiences with the 2011 east Japan earthquake. This system has two levels of security:(1) The web site for public relations and the e-mail systems for communications thatwill work continuously even in the case of commercial power failure. (2) The personal
computer systems that will be down during power failure but will restart working without
any loss of data as soon as the power supply is back. The former has been implemented by
employing a private cloud computing platform and a public one in combination. To thelatter, the same cloud-computing approach was not applicable because it causes latency
and extra cost of communications in the normal time to keep the frequently accessed data
in a cloud storage. Fortunately, this particular university has three campuses so far awaythat one may be destroyed by a single disaster but the other two will survive. Taking
advantage of the remote campuses, we designed and implemented a ﬁle storage systemthat keeps the original copy on-premise in a campus and its backup copy in one of theother two campuses. Its operations have shown that the communication traﬃc among thecampuses increased only by half in order to keep the data safe against natural disasters.
Keywords: disaster robustness; business continuity planning; distributed data backup.
Reference to this paper should be made as follows: Noguchi, H., Ohraki, Y. and
Kamada, M. (20??) ‘A university information system made robust against natural
disasters by taking advantage of remotely distributed campuses’, Int. J. Space-Based andSituated Computing, Vol. x, No y, pp. aa–bb.
Biographical notes: Hiroshi Noguchi received his bachelor’s degree in mathematics from
Chuo University in 1986. On ﬁnishing his master’s degree in economics at the Universityof Tsukuba, he joined Ibaraki University where he is currently a lecturer with the Center
for Information Technology.
Yasuhiro Ohtaki received his bachelor’s degree from the University of Tsukuba in 1989,
and his Ph.D (in engineering) from the same university in 1994. In the same year, hestarted working at Ibaraki University where he is currently a lecturer with the Center for
Information Technology. His current research interests include applied cryptography andcomputer forensics.

c 2013 Inderscience Enterprises Ltd.
Copyright 15茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

2
Masaru Kamada received his bachelor’s (1984) and doctoral (1988) degrees in engineeringfrom the University of Tsukuba and worked for the same university as a faculty member.
In 1992, he joined Ibaraki University where he is currently a professor of computer scienceand the director of the Center for Information Technology. He has been serving Sampling
Theory in Signal and Image Processing as its secretary since 2003 and he has been an
associate editor of the IEEE Transactions on Industrial Electronics since 2009. Besides
information systems, he is working also on signal and image processing.

1 Introduction
earthquake can destroy data on the disk drives if it takes
place just beneath the server room. Local fire hazards or
floods can cause the same result. Data loss can give much
more serious damages to the business of universities thanthe physical damages to the buildings.
It is the diﬃcult time in disasters when wereally need the means of public relation and personalcommunications. But the information systems of theuniversity were completely out of operation for days
due to the power failure. The main electricity were notavailable for three days in Hitachi and two days in Mitoand Ami.
We really needed to announce what to do with theentrance examination scheduled on the next day of theearthquake. It was obvious that we could not do it asscheduled. But we had to announce how many days it
would be put oﬀ or if it should be cancelled. We set up
an emergency web site (Matsumoto, 2011) on a cloudservice2 to post announcements to the students and theemployees. The temporary IP address was registered to
the DNS server so that the accesses to the old regularsite be directed to the emergency site. This emergency
site helped people get informed of the announcementsfrom the university for a few days until the regular
web site came back to operation. Then we suﬀered fromanother problem that the wrongly cached DNS records
in diﬀerent internet service providers kept pointing the
emergency site. The heroic emergency site became aghost web site that confused people by showing outdated
information persistently.
On the basis of those bitter experiences, we haveredesigned and implemented the information system of
our university. This system has two levels of security: (1)The web site for public relations and the e-mail systems
for communications that will work continuously even in
the case of power failure. (2) The personal computer
systems that will be down during power failure but will
restart working without any loss of data as soon as thepower supply is back.
The rest of this paper is organized as follows: In
Sections 2 and 3, we review the information systems
and networks of this particular university, and thelessons learnt from the mega disaster caused by the 2011
earthquake, respectively. In Sections 4 and 5, we describe
two kinds of solutions for the business continuity plan of
the university: Uninterrupted web and mail servers; anddistributed file backup system, respectively. In Section 6,

The 2011 east Japan earthquake hit the north east partof Japan on March 11th including the three campuses of
Ibaraki University1 in Fig. 1. The buildings in Hitachi
campus were severely damaged, in some cases, deep into
their structural frameworks. Those in Mito and Ami
campuses were also strongly shaken but less damaged forthey were located relatively away from the epicenters.
The main server computers were placed in Hitachi
campus where the college of engineering is hosted. The
server racks were so firmly fixed to the basement thatthey did not fall. But they were shaken so badly that wethought the hard disk drives must have been destroyed.
After the main electricity got back in several days, wewere relieved and even surprised to know that the disks
were not damaged at all. Probably the arms in the drives
were already retracted in response to the preceding
smaller vibrations while the huge main shakes weretraveling from the distant epicenters. Even a smaller

Hitachi campus
30km
Mito campus
50km

Ami campus

Figure 1

Three major campuses of Ibaraki University

This map shows the geographic outline of the islands anddoes not indicate the territory of any specific country.

16茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

A university information system made robust against natural disasters

3 Lessons from mega disaster and new
policyInternet (via SINET)

The 2011 earthquake severely damaged Hitachi campus
but fortunately claimed no casualties. We lost watersupply for more than 10 days, which greatly aﬀected ourlife. However, in the aspect of communications, the mostdiﬃcult situation was caused by the power failure forthree days. The main web server and the mail server forthe staﬀ were completely down when we really needed topost announcements and discuss recovery plans to copewith the severe disaster.
The emergency web site (Matsumoto, 2011) set up on
a cloud service2 was barely fulfilling the public relations.
But it took some time for this new web site to start
operating while people needed information as soon as
possible to know what was going on. Besides, after the
regular web site came back into operation, the emergency
site had suddenly become a ghost web site that confused
people by showing outdated information persistently due
to the wrongly cached DNS records in diﬀerent internet
service providers. It is a “public secret” that most of
the commercial internet service providers do not observe
the standard of the TTL (time-to-live) parameter of any
DNS records. It is true that some cached DNS records
were diﬀerent from a base station to another of the same
cellular carrier in the same region at the time of the lastdisaster.
It is the only and best policy to keep the regular web
server working throughout the disaster. The same is trueof the mail servers. We have never heard of temporary
mail services that can substitute existing mail services of
the regular use. They are useless because we do not havea means to identify the new mail addresses of students
and colleagues.
The other information systems such as PCs and fileservers in the universities do not have to keep operating
throughout the disaster since the school can be closed
after sending students safely toward home. Operationsof the PCs and file servers can be resumed when people
come back to the school as long as we have the data
preserved.
Loss of data is better than loss of lives, but it isworse than damaged buildings and destroyed computers.
It can take an enormous amount of time or may be even
impossible to reproduce the lost data.
We learnt that an information system really strong
against mega disasters needs to have the following two
features:

Hitachi campus

Mito campus

Ami campus
Figure 2

3

Network connections among the campuses.

we evaluate the file backup system through its operationin practice. Section 7 mentions several related works andSection 8 gives a concluding remark.

2 Information systems and networks of
Ibaraki University before the disaster
This university has three major remote campuses asshown in Fig. 1. The center for information technology
is located in Hitachi campus where the computers havebeen historically used much more actively than the othertwo campuses. That is the reason why the connection
to the Internet is going through the firewall system in
Hitachi as shown in Fig. 2. The campuses are connectedin the star-shaped topology via the wide-area ethernet
at the speed of 1Gbps with the interfaces of L3 switches.
Each campus has a file server that stores the home
directory of all the users in the campus. The home
directory is mounted on the PC when the user logs on
and also stores mails to be referred to by the mail server
for the students there. The file server also stores thesystems and the data for the virtual servers on the real
server computers managed by VMware.
The campuses have been often struck by power failure
for a short time due to local thunder storms. Eachcampus has one of the IdP server systems so that thecampus can be indiﬀerent to power failure of othercampuses. From time to time, we had power failure at
Hitachi campus where the mail server for the staﬀ andthe main web servers are hosted. But the black out did
not last more than half an hour.
That was strong enough against small disasters. But
the story was diﬀerent in the case of mega disaster.

(1) The web site for public relations and the e-mailsystems for personal communications that will
work continuously without interruption even in thecase of power failure.
(2) The personal computer systems that will be down
during power failure but will restart working
without any loss of data as soon as the power
supply is back.

17

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

4
The former can be implemented simply by employing
the recent private or public cloud systems.
The latter requires an idea. If we employ the cloudservice to keep the data safe in preparation for possible
mega disasters, the data exchange between the local
PC and the remote cloud causes longer latency andheavier traﬃc than necessary in the normal time. The
users should suﬀer from slow response of the PC due tothe latency in data retrieval from the remote storage.
Frequent data exchanges between the PC and theremote storage should require wide bandwidth that will
eventually increase the communications cost or slow
down the data transfers.
In order to store the data in a safe place while
keeping the data readily accessible at the on-premise
file server, we can exploit the three remotely distributed
campuses connected by the 1Gbps wide-area ethernet in
the particular case of Ibaraki University. The local fileserver stores the data for the local users in each campus
as it has been practiced normally. Let its duplicate copy
be stored in a fellow file server in another campus.
Then, at least one copy of the data will survive strong
earthquakes just beneath the file server even if it would
not give time to retract the disk arms. That will survive
also local fire and flood.

is the simplest and aﬀordable solution by virtue of theacademic discount oﬀered by Microsoft.

5 Distributed file backup system
Each campus has a file server Model VNX5300
from EMC (EMC, 2011) that stores the data to bepreserved. They include the work space of students,
electronic contents for the classes, and documents forclass management. They are crucial for continuationof teaching activities through small or middle scaledisasters or their quick recovery after mega disasters.
If we send the frequently updated large data toa remote backup server outside the university inanticipation of possible mega disasters, the data transferfrom the local server to the remote server causes heavy
traﬃc in the network in the normal time. However, thefear of losing important data has been driving several
Japanese universities to start a coalition to keep the dataof one another (Kumagai et al., 2012) despite the extra
cost for communications and storage.
In the case of Ibaraki university where we havebeen suﬀering from the overhead cost for managing
remote campuses, we have a good set of three campuses

Hitachi campus
4 Uninterrupted
serverWeb

serverandMailoriginal copy
duplicate copy

The web and mail services can be interrupted for a shorttime in the normal time for people usually accept regularserver maintenance. On the contrary, those services
should not be interrupted in the very time of disastersince the latest information is crucial for the people
to make decisions in emergency. Probably for the same
reason, the cellular carriers have some key base stations
supported by local electricity generators to be robust
against commercial power failures.
The web site can work continuously without
interruption only if the server stays physically healthy
and the power is uninterrupted even in the case ofcommercial power failure. There are roughly two kinds ofsolutions by means of private and public cloud systems
operated at some data centers.
The main web server of Ibaraki university has
been moved into a private cloud system set up in acontainerized data center built in one of the campuses.
It is designed to survive the strongest earthquakes in thehistory of Japan and supplied with main electricity by
the dedicated generator. The DNS servers are extended
to include the secondary DNS service hosted in a public
cloud service. We are planning to move the web server
further to a public cloud service.
The mail system has emigrated to the cloud service
Microsoft Oﬃce 3653 . The IdP servers are extended toinclude a slave server also in a public cloud service. That

generationalarchiveremote copy

Mito campus
original copy
duplicate copy
generationalarchiveremote copy

Ami campus
original copy
duplicate copy
generationalarchiveremote copy
Figure 318

Structure of the copies.

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

A university information system made robust against natural disasters
geographically apart from one another. We have only
to synchronize the original copy of the data withits duplicate copy in another campus. We can keepthem in the plain format without any encryptionthat is mandatory for the coalition of several diﬀerent
universities.
The backup data is a simple duplicate copy of theoriginal one. A system image of the virtual machine
and its data partition in the backup can migrate onto a
diﬀerent real server to start working even in the case ofphysical damage on the original server.
Figure 3 shows a schematic diagram of the three
file servers. Each disk system is partitioned into thefour regions: original copy, local duplicate copy, remote
duplicate copy, and local generational archive.
The local duplicate copy is just for increasing therobustness against malfunction of the disk systems. The
file server VNX5300 oﬀers the capability of updating the
local duplicate copy immediately when the original copy
is modified.
The remote duplicate copy in another campus is also
updated by the same mechanism except that the updates
take place not immediately but every 10 minutes. This
time interval of 10 minutes is a parameter that can betuned in accordance with the real situation. A too shortinterval may increase the base load traﬃc. A too longinterval may cause a burst traﬃc to transfer piled up
updates at a time.
The local generational archive stores an ordinary
incremental backup data from which users can reverse
their file operations.
No data are encrypted since everything is under
the control of the same institute. Nor are they evencompressed. Backup data in the same plain format as theoriginal are advantageous to save computational load forencryption and compression, and troubles for decryption
and extraction in case the backup copy is needed inemergency.

Figure 4

5

Averaged peak traﬃc of the day without (2011)
and with (2012) the remote backup system.

The traﬃc has increased by roughly 1.5 times in total.
But it stays less than 1M Bytes per second. For the widearea ethernet connecting the campuses at the maximum
speed of 1G bits per second, the new traﬃc rate is amoderate good figure not too low nor high.
The time interval of synchronization is a parameterthat can be varied in accordance with the situation. In
the fall semester of 2015, traﬃc trends in the typical busy
days of the week, Tuesday and Thursday, were measured
for various synchronisation intervals during the day time.
Figures 5 to 9 show traﬃc trends during the day timein one day of either Tuesday or Thursday when thesynchronisation interval was set as 2, 5, 10, 20 or 40
minutes. hose intervals were chosen to form a roughly
doubling sequence starting at 2 minutes. We did not dare
to attempt the 1 minute interval that we thought too
frequent.
The case of 10 minutes in Fig. 7 can be regarded as
an exceptionally busy day when the students happened
to be extraordinarily active in computer usage because
the peak, average and even lowest traﬃc rates are
exceptionally high. In this case, the traﬃc is persistently
high around the average 21.4MBps throughout the day
time and makes two peaks reaching higher than 30MBps.
It drops only once at 16:30 in the evening with a notch
down only to 12MBps when we had a ten-minute break
between the classes.
In the other cases, the traﬃc goes sharply up anddown making peaks as high as 30MBps and deep notches
as low as 5MBps probably in response to the teachers’
instructions for file operations in the classrooms. The
high traﬃc tends to appear at the end of classes and the
low traﬃc does during the breaks between classes.
Except for the case of Fig. 7, the lowest traﬃc appears
as notches in Figs. 5, 6, 8 and 9 at roughly the same levelof 5MBps. The frequent synchronization by the intervalof 2 minutes caused the highest average traﬃc rate of
21.3MBps in Fig. 5. The average traﬃc rate follows thetendency of going down to 20.9MBps for the 5 minutes
interval in Fig. 6 and to 18.5MBps for the 20 minutes
interval in Fig. 8 as the synchronization interval getslonger.

6 Experiments
The traﬃc observed at the inter-campus L3 switches
before and after the deployment of new backup system
in March 2012 is plotted in Fig. 4. It includes that forordinary activities of accessing data, such as web pages
across the campuses, other than the synchronization ofdata storage. Here we see how much the new systemincreased the whole traﬃc. The traﬃc was measured
during the two semesters in the school year of 2011 andthose in that of 2012. In the period of the measurement,
the time interval of synchronization was set to theconstant value of 10 minutes.
The measured traﬃc was averaged for the same dayof the week in the semester periods. Variations from day
to day of the week depend mainly on the change in thetimetable of the classes.

19茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

6
MBps
35
peak =30.8MBps
30

MBps
35
peak =31.5MBps

25

25

20

20

15

15

10

30

average =21.3MBps

10

5

5

0
10:30

Figure 5

12:30
14:30
Time of the day

0
10:30

16:30

Traﬃc trend for the synchronization intervalof 2 minutes.

Figure 7

12:30
14:30
Time of the day

16:30

Traﬃc trend for the synchronization intervalof 10 minutes.

MBps
35
peak =31.7MBps

MBps
35

30

30 peak =28.1MBps

25

25

20

20

15

15
10

average =21.4MBps

10

average =20.9MBps

5

5
0
10:30

Figure 6

average =18.5MBps

12:30
14:30
Time of the day

0
10:30

16:30

Figure 8Traﬃc trend for the synchronization intervalof 5 minutes.

12:30
14:30
Time of the day

16:30

Traﬃc trend for the synchronization intervalof 20 minutes.

MBps
35
peak =31.8MBps

On the contrary, the highest peak of 31.8MBps wasobserved for the synchronization interval of 40 minutes
in Fig. 9 and the second highest peak of 31.7MBps wasfor 20 minutes in Fig. 8. Those high peaks must havebeen caused by burst traﬃc of large updated data of
which synchronization was suspended for a longer time.
On the basis of those example data, we may say the
optimal choice of the synchronization interval is around 5
minutes in this fall semester. But, of course, the optimal
choice depends on the user activities in the day or evenin the hour. We need some intelligent methods in orderto estimate the optimal value of the synchronizationinterval adaptively. At the same time, we can also saythat the choice of the synchronization interval does not
so wildly push the peak and average up to an intolerable
level.

30
25
20
15
10

average =20.6MBps

5
0
10:30

Figure 9

20

12:30
14:30
Time of the day

16:30

Traﬃc trend for the synchronization intervalof 40 minutes.

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

A university information system made robust against natural disasters

7

7 Related works
There have been diﬀerent solutions for file backup
systems designed against mega disasters.
The simplest solution is schematized in Fig. 10 and
employs a commercial cloud storage (Iwano et al., 2013)
hosted at a remote place. The duplicate copy on aremote cloud storage can be synchronized to the dataon the local storage from time to time through asecure channel like SSL. We do not have to encrypt the
backup data in the case that the contract secures theirprivacy. If the privacy level does not meet the standardof the university, we have to encrypt the files before
sending them to the remote side and we can downgrade
the channel security. Frequent synchronization increases
the computational and communications cost. It is
recommended for the universities to send data at night
when the computational and communications resources
are more available.
In order to lower the communications cost, a pairof universities have been practicing the mutual backup
storage service in Fig. 11. We have to encrypt thefiles before sending them to the other side. The
two universities should trust each other in regard of
the maintenance of the storage devices. In order not
to bother the network traﬃc of each other, it isrecommended for the universities to send data only atnight.
There is an advanced scheme (Kumagai et al.,2012) for mutual data backup among not so trusting
universities by means of (n, t)-threshold secret sharing
scheme that can be applied to a coalition of n universities
as shown in Fig. 12. A university, owner of a file, makes
n shares of the file and sends them to the other n − 1universities. The file can be recovered from its t shareseven if n − t shares are lost accidentally or due to megadisasters. The file is kept secret unless t universities
betray the owner at the same time. There is even amore advanced version for the use on cloud storage
service (Ohigashi et al. , 2014). These are the mostwidely applicable schemes at the cost of calculating theshares and communicating more data for the sake ofredundancy.
In the particular case of Ibaraki university, we
happened to have remotely distributed campuses in thesame organization as depicted in Fig. 13. The system
simply keeps a duplicate copy of the file at anothercampus. By virtue of this simplicity, the synchronizationof data can be made as frequently as almost in realtime. The experience reported in this paper will beof reference to other universities having two or morecampuses moderately apart from each other.

remote cloud storage

plain or encrypted
duplicate copy
through secure or
ordinary channel
at night

on site storage

Figure 10

Employment of a commercial remote cloudstorage.

encrypted duplicate copy
through ordinary channel
at night

Figure 11

8 Conclusions
Through the bitter experiences during the disaster inMarch 2011, we have redesigned the information system

21

Mutual back up storage between two
universities trusting each other.

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

8
for Ibaraki university. The web site and e-mail systems
were moved to the private and public cloud services sothat they will never be interrupted again. The file servers
are made secure by keeping a duplicate copy in anothercampus which is located more than 30 km away.
Taking advantage of the remote campuses, we
designed and implemented a file storage system thatkeeps the original copy on-premise in a campus andits backup copy in one of the other two campuses. Its
operations have shown that the communication traﬃcamong the campuses increased only by half in order tokeep the data safe against natural disasters.
Additional experiments for various values of thesynchronization interval have indicated the tendency
that the shorter intervals cause the higher average traﬃc
and a very long interval causes a high peak traﬃc toexchange data updates suspended for the long interval.
At the same time, it has also been confirmed that the
choice of the synchronization interval does not so wildly
push the peak and average up to an intolerable level for
current practice with this particular university.
There must be the optimal choice of thesynchronization interval that depends on the user
activities in the day or even in the hour. We need someintelligent methods in order to estimate the optimalvalue of the synchronization interval adaptively, whichis left for further research in the future.

(n, t)-thresholdsecret sharing scheme
through ordinary channel
at night

Figure 12

Mutual back up storage among not sotrusted universities.

References
Matsumoto, N. (2011), ‘Letter from the President of
Ibaraki University’, VIOPS Virtualized Infrastructure
Operators group, http://www.viops.jp/2011/03/post12.html, March 2011.
EMC (2011) ‘EMC VNX5300 Storage’, http://www.emcstorage.co.uk/emc-vnx-5300-emc-vnx5300-vnx5300storage, 2011.
Iwano, M. et al. (2012) ‘Demonstration of non-stop backup
system for business continuity plan’, IEICE Technical
Report, Vol.112, No.22, 111-116, May 2012.
Kumagai, K. et al. (2013) ‘A distributed file management
system based on identity federation’, IPSJ Technical
Report, Internet and Operation Technology(IOT),
Vol.2012-IOT-18, No.8, June 2012.
Ohigashi, T. et al. (2014) ‘Implementation and evaluationof secure outsourcing scheme for secret sharing
scheme on cloud storage services’, The IEEE 38th
International Computer Software and Applications
Conference Workshops (COMPSACW), July 2014.

Hitachi campus
30km
Mito campus
50km

Ami campus

Figure 13

Note

Near real-time back up storage among remote
campuses of the same university.

1

http://www.ibaraki.ac.jp/
http://cloudpack.jp/
3https://products.oﬃce.com/
222

3.プロジェクト業績

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

活動実績【都市インフラの強靭化技術開発】
炭素繊維やパサルト繊維による構造補強材の高性能化により、インフラ構造物の耐震性やResilience（自己回復性）向上手法を開発し、都市インフラの強靭化技術に関する取り組みを行っており、産学連携を検討している。
（呉教授）【都市インフラモニタリングや知能化による高度化センサ技術の開発】
1) 光ファイバセンサ方式とカーボンファイバセンサ方式による長寿命・高性能化された分
布型領域センサの実製作・性能究明および実用性を実験室レベルで検討した。
２）領域センサにより得られるひずみ分布の直接利用により、構造物の早期損傷検知に対する各種指標を検討した。
３）開発したセンサ、装置、検知アルゴリズムを基に、早期損傷検知システムを開発し、茨城県内の RC 桁橋、新潟県内の既損傷 PC 箱桁橋、東北新幹線高架橋、中国の蘇通大橋（１０００ｍ級長大橋）など既設構造物のリアルタイム健全性評価システムの検証を進めている。
４）高度化された光ファイバ分布センシング技術による広域地圏環境（河川堤防・地すべり）防災システムの構築に関する産官学連携プロジェクトを開始し、基礎検討を行っている。
（呉教授）【センサデータの安定した通信/解析技術の開発と省電力化推進】
1) 大規模災害により、電源インフラが完全消失した状況において、市民にどのように、情報を伝達するか、また市民の安否情報をどのように収集するかについて研究を進めている。内部電源を必要としない UHF 帯 RFID を利用している。（武田教授）【老朽化したインフラ構造物の災害リスクを考慮した維持管理計画】
1) 橋梁の（異常監視）ヘルスモニタリングシステムの実証実験を常陸大宮市の引田橋での継続的に実施した。（齋藤特命教授,原田准教授, 鎌田教授）
2) ひたちなか海浜鉄道湊線での企業との傾斜計の実証実験を推進．本件は 10 月に茨城県土木部との連携で常陸大宮地区の地すべり危険地域への応用予定（齋藤特命教授）
3) 構造物の耐久性設計に資する高度化シミュレーション技術を開発している（車谷准教授）

23茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター【UAV を活用した新たな空間情報の防災システムへの活用と超小型衛星との連携】
1) 茨城県生活安全部と UAV による安全監視・不法投棄防止システムの実現の連携検討を開始した。（齋藤特命教授）
2) 宮城教育大学との UAV を用いた空間環境情報可視化と津波災害地域の空撮を行った。
（齋
藤特命教授）
3) 宮城県石巻市、女川町での空撮による災害地域の土地利用変化、震災遺構の映像保存プ
ロジェクトをスタートさせた。（齋藤特命教授）【アウトリーチとしての防災・減災、それらを含む環境教育の実施】
1) ひたちなか市外野小学校、前渡小学校にて環境・情報教育を実施した。（齋藤特命教授）
2) (社)次世代センサ協議会第 44 回センサ＆アクチュエータ技術シンポジウムにて UAV と防災について講演した。（齋藤特命教授）【災害時および平常時等における情報共有法】
1) 防災情報を配信する方法には、インターネットやＦＭ放送、拡声器などを利用する方法があるが一長一短がある。そこで追加手段の１つとして交通信号機を配信局として用いる方法を研究している。特に、光点滅（ＬＥＤのオンオフ、人間の目ではそのオンオフは感知できない）による光ワイヤレス通信の高信頼化について検討している。
2) 大規模震災では、集中制御が基となる携帯網・ワイヤレス通信網では情報共有は難しい
また、信号機等の停電により大規模な車両渋滞が生じると考えられる。その渋滞車両を積極的に通信局として利用するネットワーク網を構築する研究を進めている。ＭＡＣプ
ロトコルとして、変形２進カウントダウン法を考案している。（羽渕裕真教授）【地元企業・学校等との学術連携実現】
1) 土木部河川課ダム砂防室との連携により，UAV によるダム堤体表面のクラックマップ生成について連携して研究した。（齋藤特命教授）【地域社会活動】1) 鎌田

賢：第 38 回全国高等学校総合文化祭「いばらき総文祭 2014」コンピュータ部門のプログラミングコンテストにおいて、予選・本選（平成 26 年 7 月 28 日（月）29 日（火））の審査委員を務めた。本選ではデモ展示も行った。

24茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター【他大学・企業・自治体連携での研究資金獲得】
1) 東北大学と共同で申請した科研費（挑戦的萌芽）「地盤中の間隙水の挙動調査」採択（東北大学風間基樹教授, 茨城大学安原一哉名誉教授, 鎌田賢教授）（齋藤修特命教授の企
画・アレンジによる）において、地中埋め込み型の土砂内水流・水圧センサと無線モジ
ュールを開発した。
2) シンポジウム「SICE 計測部門セミナー 都市のスマートセンシング」を企画して開催した。（齋藤特命教授）
http://rcl.it.aoyama.ac.jp/sice-sss/sice_seminar_20140917.html【自治体との各種連絡会議推進（茨城県・日立市・ひたちなか市等）】
1) 茨城県商工労働部、土木部、企画部、生活安全部との定期情報交換（齋藤特命教授）（鎌田教授, 桑原教授は随時参加）
2) ひたちなか市長との情報交換会 1 回／年度（齋藤特命教授）（鎌田教授, 桑原教授は随時参加）【国際共同研究を実施（中国、韓国等）】
1) センシング技術による地下鉄防災システムの高度化に関する共同研究を英国のケンブリッジ大学、長大橋の長寿命化に関する研究を中国の東南大学、光ファイバ技術による高速道路橋の長期モニタリングに関してアメリカＦＨＷＡ（連邦道路管理局）橋梁の長期性能検討プロジェクトチームなどと共同研究により推し進めている。（呉教授他）【大学院生の教育】
1) ５名の社会人博士課程入学者をリクルートした 2013 年度につづき、2014 年度には 3 名の社会人博士課程入学者をリクルートした。（齋藤特命教授）センター教員の連携による指導体制を構築している。2016 年度

修了１名。

25

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

業績一覧【原著論文】
1) Saifeldeen, M. A., Fouad, N., Huang, H., & Wu, Z., "Advancement of long-gauge carbon fiberline sensors for strain measurements in structures", Journal of Intelligent Material Systems andStructures: 1045389X16665974, Aug 2016.
2) Saifeldeen, M. A., Fouad, N., Huang, H., & Wu, Z. S., "Stabilization of electrical sensing
properties of carbon fiber sensors using pre-tensioning approach", Smart Materials andStructures 26.1: 015012, Dec 2016.
3) Fouad, N., Saifeldeen, M. A., Huang, H., & Wu, Z. S., "Early corrosion monitoring of reinforcing
steel bars by using long-gauge carbon fiber sensors", Journal of Civil Structural Health
Monitoring 6.4: 691-701. , Aug 2016.
4) Fouad, N., Saifeldeen, M. A., Huang, H., & Wu, Z. S, " Corrosion monitoring of flexural
reinforced concrete members under service loads using distributed long-gauge carbon fiber
sensors", Structural Health Monitoring (掲載決定)
5) Ibrahim, A., Fahmy, M., Wu, Z, "3D finite element modeling of bond-controlled behavior of steel
and basalt FRP-reinforced concrete square bridge columns under lateral loading", Composite
Structures, Vol. 143, pp. 33–5220, May 2016.
6) Hiroshi Noguchi, Yasuhiro Ohtaki and Masaru Kamada: A university information system maderobust against natural disasters by taking advantage of remotely distributed campuses,
International Journal of Space-Based and Situated Computing, 6(3), 147-154 (Nov. 2016).
7) Xiaolei Li, Osamu Saitou, Erjing Zhou and Masaru Kamada: A low cost library navigation system
by using Android devices and FeliCa cards, International Journal of Space-Based and SituatedComputing, 6(3), 155-164 (Nov. 2016).
8) Erjing Zhou, Michitoshi Niibori, Shusuke Okamoto, Masaru Kamada and Tatsuhiro Yonekura:
IslayTouch: an educational visual programming environment for tablet devices, International
Journal of Space-Based and Situated Computing, 6(3), 183-197 (Nov. 2016).
9) Sheik Arick Hasan, Kazuki Kamata, Toshiya Watanabe, Susumu Shibusawa, Masaru Kamada,
Tatsuhiro Yonekura and Minoru Yamada: Recognition of antagonistic exercise using a depth
image sensor, International Journal of Advances in Electronics and Computer Science, 3(4),14-20 (Apr. 2016)10) 清水隆行, 鈴木貴之, 武田茂樹, 鹿子嶋憲一, 梅比良正弘, “移動体通信用逆L型プロー
ブ給電水平偏波無指向性アンテナ,” 信学論B, vol.J99-B, no.9, pp.693-704, Sept. 2016.
11) 小林有理, 馮東方, 武田茂樹, 鹿子嶋憲一, 梅比良正弘, “バッテリーレスUHF帯無線傾斜/振動センサタグの提案," 土木学会論文集F3(土木情報学), March 2017.（採録決定）26茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

12) D.D.G.L. Dahanayaka, B.D.C. Perera, M.J.S. Wijeyaratne, and H. Tonooka, Monitoring
eutrophication trends in Bolgoda North Lake, Sri Lanka by Satellite Remote Sensing, Turkish
Journal of Fisheries and Aquatic Sicences, 16, 3, , 2016年9月
13) 車谷麻緒，小林賢司，安藏 尚，岡崎 慎一郎，廣瀬壮一, "損傷モデルによる内部ひび割れを有する鉄筋コンクリート中の塩化物イオン濃度の定量的評価",土木学会論文集A2（応用力学)，72/ 2, I_313-I_322, 2017/01/29.
14) 相馬悠人，根本優輝，車谷麻緒, "コンクリートの破壊力学に基づく損傷モデルを用いたせん断補強筋の異なるRCはりの3次元破壊シミュレーション",土木学会論文集A2（応用力学)，72/ 2, I_247-I_255, 2017/01/29.
15) 西口浩司，車谷麻緒，岡澤重信，坪倉 誠, " Phantom-node法に基づく非圧縮性オイラー型有限要素法による固体接触解析",土木学会論文集A2（応用力学)，72/ 2, I_143-I_154,
2017/01/29.
16) H. Yokota, K. Higuchi, Y. Imai, “Light propagation characteristics in photonic crystal fibers
with α-power profiles of air hole diameter distributions and their application to fiber collimator”,
Jpn. J. Appl. Phys., Vol. 55, No. 8S3, 08RE10 (Aug. 2016)17) H. Yokota, H. Yashima, Y. Imai, Y. Sasaki, “Coupling characteristics of fused optical fiber
coupler formed with single-mode fiber and photonics crystal fiber having air hole collapsed
taper”, Advanced in OptoElectronics, Vol. 2016, Article ID 6219895 (Nov. 2016)18) H. Yokota, Y. Kameda, Y. Imai, "Optical characteristic variations in gamma ray irradiatedpolarization-maintaining optical fibers”, Opt. Rev., Vol. 24, DOI: 10.1007/s10043-016-0302-y(Feb. 2017)【招待講演】
1） Kurumatani, M., Terada, K., Kato, J., Kyoya, T., Kashiyama, K. . “Crack propagation
analysis using an isotropic damage model based on fracture mechanics for concrete”.7th
Korea-Japan Workshop on Computational Mechanics, April, 2015 (Busan, Korea).
2） Kurumatani, M., Abe, S., Nemoto, Y., Soma, Y., Henmi, N.：A method for fracture simulationof reinforced concrete using a damage model based on fracture mechanics for concrete, 3rdInternational Workshops on Advances in Computational Mechanics, October, 2015 (Ryogoku,
Japan).

27

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター【国際会議発表】
1) Fouad N, Saifeldeen MA, Huang H, and Wu ZS. (2016) “Development of Long-gauge Carbon
Fiber Stain Sensors for Structural Health Monitoring” Proc. of 3rd International Conference on
Structural Health Monitoring and Integrity Management, Chengdu, China.
2) Masaru Kamada and Kunimitsu Takahashi: Locally supported bivariate splines in piecewise
constant tension, Proceedings of the 2016 International Conference on Advances in Electrical,
Electronic and System Engineering (ICAEESE 2016), Putrajaya, Malaysia, 444-449 (Nov. 2016).
3) Masaru Kamada: Islay– An educational programming tool based on state diagrams (invated talk),
Proceedings of the 2016 International Conference on Advances in Electrical, Electronic andSystem Engineering (ICAEESE 2016), Putrajaya, Malaysia, 229-231 (Nov. 2016).
4) Ryosuke Iiya, Erjing Zhou, Michitoshi Niibori, Masaru Kamada, Osamu Saitou and Susumu
Shibusawa: A handy real-time location system for community bus service, The 5th International
Workshop on Web Service and Social Media (WSSM 2016), Proceedings of the 19thInternational Conference on Network-Based Information Systems (NBiS 2015), Ostrava, Czech,(Sep. 2016).
5) Daiki Ito, Michitoshi Niibori and Masaru Kamada: A real-time web-cast system for classes in the
BYOD style, The 5th International Workshop on Web Service and Social Media (WSSM 2016),
Proceedings of the 19th International Conference on Network-Based Information Systems (NBiS2015), Ostrava, Czech, (Sep. 2016).
6) Marina Nakano, Emi Masuda and Masaru Kamada: A Structure Editor for the English Language,
The 5th International Workshop on Web Service and Social Media (WSSM 2016), Proceedings ofthe 19th International Conference on Network-Based Information Systems (NBiS 2015), Ostrava,
Czech, (Sep. 2016).
7) Shumpei Fujii, Michitoshi Niibori and Masaru Kamada: A Preliminary Experiment of Tweet
Filtering by Back Propagation, The 5th International Workshop on Web Service and Social
Media (WSSM 2016), Proceedings of the 19th International Conference on Network-BasedInformation Systems (NBiS 2015), Ostrava, Czech, (Sep. 2016).
8) K. Kagoshima, M. Uchida, S. Takeda and M. Umehira, "Investigation on the reactance loadingand EM coupling feed for a design of a dual frequency planar antenna," Proc. IEEE-APS Topical
Conference on Antennas and Propagation in Wireless Communications, pp.30-33, Sept. 20169) Toshiya Watanabe, Kazuki Kamata, Sheik Arick Hasan, Susumu Shibusawa, Masaru Kamada,
Tatsuhiro Yonekura, and Minoru Yamada, (2016), Design of an Antagonistic Exercise Support
System Using a Depth Image Sensor, Pervasive Health 2016, DOI:
10.4108/eai.16-5-2016.2263317.

28茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

10) Ryousuke Iiya, Erjing Zhou, Michitoshi Niibori, Masaru Kamada, Osamu Saitou, and Susumu
Shibusawa, (2016), A Handy Real-Time Location System for Community Bus Service, The 19thInternational Conference on Network-Based Information Systems, pp.507-509.
11) Susumu Shibusawa, Toshiya Watanabe, Kazuki Kamata, Sheik Arick Hasan, Masaru Kamada,
Tatsuhiro Yonekura, and Yukari Ohashi, (2016), Development of an Antagonistic Exercise
Support System Using a Depth Image Sensor, The First International Workshop on Smart
Sensing Systems, pp.265-268.
12) Sheik Arick Hasan, Takahiro Fukuda, Toshiya Watanabe, and Susumu Shibusawa, (2017),
Recipe-Recommendation System Based on Physical-Characteristics Recognition Using a Depth
Image Sensor, International Conference on Recent Innovations in Engineering and Technology,
pp.24-29.
13) M. Asaki, and H. Tonooka, Analysis of radiometric accuracy of ASTER band 11 for cold targets,
Proc. of the 12th International Student Conference at Ibaraki University (ISCIU12), , , 28-29,
2016年12月.
14) J. Yamamoto, and H. Tonooka, Applicability of the deep learning to cloud discrimination ofsatellite images, Proc. of the 12th International Student Conference at Ibaraki University(ISCIU12), , , 34-35, 2016年12月.
15) T. Sugamiya, and H. Tonooka, Evaluation of consistency in radiance between Terra andAqua/MODIS in the 10 to 13 μm region, Proc. of the 12th International Student Conference at
Ibaraki University (ISCIU12), , , 38-39, 2016年12月【学会発表 (国内、国際)】
1) 市川智紀, 武田茂樹, 鹿子嶋憲一, 梅比良正弘, "図書館での蔵書管理におけるUHF帯ダ
イポールタグの読み取り特性に関する検討," 信学技報, AP2016-26, pp.56-60, May 2016.
2) 小林有理, 馮東方, 武田茂樹, 鹿子嶋憲一, 梅比良正弘, "バッテリーレスUHF帯無線傾斜/震動センサタグ," 土木情報学シンポジウム, vol.41, pp.47-50, Sept. 20163) 加藤篤, 外岡秀行, 位相限定相関法による衛星画像マッチングにおける雲混入の影響評
価, 日本リモートセンシング学会誌, 36, 5, 527-533, 2016年11月
4) 外岡秀行, 朝木萌奈, 菅宮岳, 酒井理人, 中右浩二, 粂田綾香, 加藤創史,

ALOS-2/CIRC及びCALET/CIRCの校正検証活動, 日本リモートセンシング学会第61回学術講演会論文集, pp. 81-82, 2016年11月.
5) 山本純平, 外岡秀行, ディープラーニングによる衛星画像の雲判別の可能性, 日本リモートセンシング学会第61回学術講演会論文集, pp. 179-180, 2016年11月.
6) 朝木萌奈, 外岡秀行, 低温域におけるASTER/TIRの再校正の検討, 日本リモートセンシ
ング学会第61回学術講演会論文集, pp. 225-226, 2016年11月.

29茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

7) 榑林雄飛, 外岡秀行, 高分解能衛星画像の影解析及び3Dモデリングによる低層住宅地における建物階数推定, 日本リモートセンシング学会第61回学術講演会論文集, pp. 203-204,
2016年11月.
8) 菅宮岳, 外岡秀行, 10～13μm帯におけるTerra/MODIS及びAqua/MODIS間の相互校正の試み (3), 日本リモートセンシング学会第61回学術講演会論文集, pp. 227-228, 2016年11月.
9) 高橋有真, 外岡秀行, ASTER/TIR画像による油膜の厚さ及び温度の同時推定の試み (3),
日本リモートセンシング学会第61回学術講演会論文集, pp. 3-4, 2016年11月.
10) 須佐綾太, 外岡秀行, 熱赤外マルチスペクトル画像を用いた薄氷分類の試み (3), 日本
リモートセンシング学会第61回学術講演会論文集, pp. 229-230, 2016年11月.
11) 朝木萌奈, 外岡秀行, GOES-14/ImagerによるALOS-2/CIRCの相互校正結果, 日本リモー
トセンシング学会第60回学術講演会論文集, pp.177-178, 2016年5月.
12) 田川博務, 外岡秀行, 日立LNG基地におけるASTER/TIR画像を用いた遺伝的アルゴリズ
ムによる熱異常解析, 日本リモートセンシング学会第60回学術講演会論文集, pp.173-174,
2016年5月.
13) 菅宮岳, 外岡秀行, 10～13μm帯におけるTerra/MODIS及びAqua/MODIS間の相互校正の試み (2), 日本リモートセンシング学会第60回学術講演会論文集, pp.175-176, 2016年5月.
14) 高橋有真, 外岡秀行, ASTER/TIR画像による油膜の厚さ及び温度の同時推定の試み (2),
日本リモートセンシング学会第60回学術講演会論文集, pp.171-172, 2016年5月.
15) 榑林雄飛, 外岡秀行, 高分解能衛星画像の影解析及び3Dモデリングによる建物の高さ推定, 日本リモートセンシング学会第60回学術講演会論文集, pp.123-124, 2016年5月.
16) 須佐綾太, 外岡秀行, 熱赤外マルチスペクトル画像を用いた薄氷分類の試み (2), 日本
リモートセンシング学会第60回学術講演会論文集, pp.7-8, 2016年5月.
17) 作山卓也、原田隆郎、笹生周平，鋼橋点検時における下地処理を省略した応急的塗装に関する研究，Ⅵ-577、pp.1153-1154，土木学会第71回年次学術講演会(平成28年9月)
18) 高橋 亨、原田隆郎，ドライバの生体脈波による高速道路走行時のストレス評価に関する研究，Ⅵ-769、pp.1537-1538，土木学会第71回年次学術講演会(平成28年9月)
19) 北村耕一、上野臺英孝、萩谷陽平、今村明登、原田隆郎，既設橋梁の腐食部に対する応
急的な補修塗装手法に関する研究，Ⅵ-588、pp.1175-1176，土木学会第71回年次学術講演会(平成28年9月)20) 土屋嘉則、梅原郁弘、藤井裕士、白旗弘実、原田隆郎，既設橋梁における鋼製排水溝を用いた排水構造の提案とライフサイクルコスト評価，Ⅵ-581、pp.1161-1162，土木学会第71回年次学術講演会(平成28年9月)21) 清水和弘、土屋嘉則、白旗弘実、原田隆郎，桁橋端部の水じまい処理によるライフサイ
クルコスト評価，Ⅵ-582、pp.1163-1164，土木学会第71回年次学術講演会(平成28年9月)30茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

22) 横田浩久, 樋口恵一, 今井洋, “GI 型フォトニック結晶ファイバの伝搬特性に対する空孔径対ピッチ比の影響”, 2016年電子情報通信学会ソサイエティ大会予稿集, B-13-24(2016年9月)
23) 若宮達也, 横田浩久, 今井洋, “カスケードファイバブラッググレーティングを用いた高感度放射線センシング”, 平成28年度 電気学会東京支部茨城支所研究発表会講演予稿
集, IBK-16-049 (2016年12月)
24) 横田浩久, 若林美月, 樋口恵一, 今井洋, “ファイバ長許容誤差に優れたコリメータ用
GI型フォトニック結晶ファイバの設計”, 電子情報通信学会技術報告 光ファイバ応用技
術研究会 OFT2016-37 (2017年1月)25) 佐野智彦, 横田浩久, 今井洋, “フォトニック結晶ファイバ光減衰器の作製及び曲げによる減衰量調整”, 第64回応用物理学会春季学術講演会講演予稿集, 16a-316-2 (2017年3月)【受賞等】
1) 呉教授が、建設に関する繊維複合材料国際学会（International Institute for FRP in
Construction、IIFC、本部：カナダ）の IIFC メダル賞を受賞した。IIFC メダル賞は、同学会の最高位賞と位置付けられており、2006 年の設立以降、2 年に 1 人が選ばれ、日本からの受賞は呉教授が初めてとなった。

【競争的資金獲得】
1.採択された競争的資金等の外部資金
1) 電気通信普及財団 研究助成金, 「消失通信路に耐性のある光無線ターボ符号システムに関する研究」 1,000,000 円, 2015 年度, 研究代表者: 羽渕裕真
2) 受託研究 JAXA, 「地球観測用小型赤外カメラ(CIRC)に関する校正検証」、平成 27 年度, 研
究代表者: 外岡秀行
3) 受託研究 宇宙システム開発利用推進機構, 「ASTER 画像の信頼性・利用性の向上に関する研究」、平成 27 年度, 研究代表者: 外岡秀行.
4) 民間企業との共同研究, 「スマートグラスの処理、チューニング方法等の助言」 , 研究代表者:
鎌田賢
5) 民間企業との共同研究, 「路面状態センシング方式と放射分光応用に関する研究」, 研究代表
者: 外岡秀行
6) 民間企業との共同研究, 「AI 技術を利用した水害対処の研究」, 研究代表者: 桑原祐史
7) 千葉大学との共同研究, 「生活環境圏における CO2 濃度の計測と検証」, 研究代表者: 桑原祐史

31茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
防災セキュリティ技術教育研究センター

8) 地域法人との共同研究, 「訪日外国人観光客を対象とした AR スマホアプリ（iOS 版）の研究開発」, 研究代表者: 石田智行
9) 地域法人との共同研究, 「訪日外国人観光客を対象とした AR スマホアプリ（Android 版）の研究開発」, 研究代表者: 石田智行
2.採択された科学研究費補助金
1） 科研費 基盤（C） （研究課題番号 16K06528）
生活環境圏における CO2 濃度の地域性に着目した新たな緑地評価指標の提案 桑原祐史（茨城大学） 分担 久世宏明 （千葉大学）
研究期間

2016 年 4 月 1 日～2019 年 3 月 31 日

研究費総額 4,550,000 円
2） 科研費 基盤（B） （研究課題番号 15H02693）
大規模災害時の劣悪通信環境で繋がる次世代ネバー・ダイ・ネットワークとその応用
代表

柴田義孝（岩手県立大学）

研究期間

分担

石田智行（茨城大学）

2015 年 4 月 1 日～2018 年 3 月 31 日

研究費総額 7,150,000 円
3） 科研費 挑戦的萌芽研究 （研究課題番号：26630215）
課題名

地盤中の水の挙動の調査を格段に進展できるワイヤレスマルチセンサの開発

への挑戦
代表 風間基樹（東北大学） 分担 安原一哉, 鎌田賢（茨城大学）
研究期間

2014 年 4 月 1 日～2017 年 3 月 31 日

研究費総額 4,915,000 円
4） 科研費 基盤研究（C） （研究課題番号：26420409）
課題名
代表

可変張力つき 2 変数スプラインの導出とその画像補間への応用
鎌田賢（茨城大学）

研究期間
研究費総額

2014 年 4 月 1 日～2017 年 3 月 31 日
1,700,000 円

32

茨城大学重点研究「知的で持続可能な社会基盤および防災セキュリティ技術研究創出事業」
茨城大学工学部附属防災セキュリティ技術教育研究センター
２０１６年度報告書
発行日

平成 29 年 4 月

発行者

茨城大学 工学部 都市システム工学科
教授 呉 智深〒316-8511 日立市中成沢町 4-12-1
Tel: 0294-38-5179 Fax: 0294-38-5268※禁無断転載茨城大学重点研究
http://www.ibaraki.ac.jp/generalinfo/activity/researching/juuten/

茨城大学工学部附属教育研究センター
http://www.eng.ibaraki.ac.jp/research/centers/index.html

防災セキュリティ技術教育研究センター
http://www.ibaraki.ac.jp/research/centers/disaster/index.html