Kohiyama, Masayuki



Faculty of Science and Technology, Department of System Design Engineering (Yagami)



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Message from the Faculty Member 【 Display / hide

  • 技術者は、コミュニケーション能力、問題発見・解決能力、リーダーシップを兼ね備えるべきだと考えています。技術者の信頼が高まることで、優れたプロダクトがより普及し、社会を豊かにできるからです。これらを養うため、研究では徹底的な議論を期待します。

Profile Summary 【 Display / hide

  • This laboratory focuses on performance-based design and optimal design of structures that realize architectural and civil engineering structures with the performance demanded by the users and owners. In order to design the society that has the secure and resilient mechanisms against disasters, the disaster reduction systems and disaster-resistant housing and communities are extensively studied, in which risk evaluation and damage estimation of structures take a leading part.

Career 【 Display / hide

  • 1995.04

    Engineer, Architectural and Engineering Design Group, Kajima Corporation

  • 1996.04

    Research Engineer, Kajima Technical Research Institute, Kajima Corporation

  • 1999.04

    Research Scientist, Earthquake Disaster Mitigation Research Center, Riken

  • 2001.04

    Research Associate, Institute of Industrial Science, The University of Tokyo

  • 2004.04

    Postdoctoral Fellow of Japan Society of Promotion of Science, and Visiting Associate Professor of Stanford University

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Academic Background 【 Display / hide

  • 1993.03

    Kyoto University, Faculty of Engineering, School of Architecture

    University, Graduated

  • 1995.03

    Kyoto University, Graduate School of Engineering, Department of Architecture and Architectural Engineering

    Graduate School, Completed, Master's course

Academic Degrees 【 Display / hide

  • Doctor of Informatics, Kyoto University, Dissertation, 2002.03

Licenses and Qualifications 【 Display / hide

  • first-class registered architect, 1998.02


Research Areas 【 Display / hide

  • Structural engineering/Earthquake engineering/Maintenance management engineering (Structural Engineering, Earthquake Engineering, Maintenance Management Engineering)

  • Building structures/Materials (Building Construction/Material)

  • Social systems engineering/Safety system (Social System Engineering/Safety System)

  • Natural disaster / Disaster prevention science (Natural Disaster Science)

Research Keywords 【 Display / hide

  • Earthquake Engineering

  • Architectural Structural Engineering

Research Themes 【 Display / hide

  • 設備被害を軽減するブロードキャスト対応制震システム, 


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  • Cooperative Control of a Building Structure and Multiple Instruments to Enhance Sustainability of their Functions, 


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  • Autonomous Cooperative Control of a Building-Elevator System Under Long Period Ground Motion, 


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    In order to reduce elevator rope damage in a high-rise building due to an earthquake, cooperative control of vibration controllers for a building and elevator rope is studied.


Books 【 Display / hide

  • 都市・建築レジリエンスデザイン入門

    小檜山 雅之,ホルヘ・アルマザン,紙田 和代, 慶應義塾大学出版会, 2020.10

  • Guidebook of Recommendations for Loads on Buildings

    Architectural Institute of Japan, Architectural Institute of Japan, 2016.02

    Scope: pp. 1-6

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  • High-Performance Computing for Structural Mechanics and Earthquake/Tsunami Engineering

    Makoto Ohsaki, Tomoshi Miyamura, Masayuki Kohiyama, Takuzo Yamashita, and Hiroshi Akiba, Springer International Publishing, 2015.11

    Scope: Seismic Response Simulation of Building Structures (pp. 105-139)

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    In this chapter, we present an overview of the E-Simulator for application to seismic response analysis of building structures. Accuracy and computational performance of simulation using the E-Simulator are discussed through examples of seismic response analysis of a four-story steel frame, buckling analysis of a column, and simulations of static cyclic responses of a composite beam and an exterior wall. Results of seismic response analysis with fixed base as well as soil-structure interaction analysis are presented for a high-rise building frame. Computational performance using the K computer is also discussed.

  • Recommendations for Loads on Buildings (2015)

    Architectural Institute of Japan, Architectural Institute of Japan, 2015.02

    Scope: pp. 95-112

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  • Excelで学ぶ地震リスク評価

    小檜山 雅之, 技報堂出版, 2011.08

    Scope: 4章 フラジリティと損傷度の評価, pp. 39-61

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    日本建築学会荷重運営委員会信頼性工学利用小委員会が,建築工学における確率・統計の利用の普及活動の一環として出版。地震リスク評価について,いくつかの例題をExcel を使って解くことで,ひととおり学べる内容となっている。4章フラジリティと損傷度の評価の執筆を担当。

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Papers 【 Display / hide

  • Experiment of torsional response induced by the Q–delta resonance

    Mizutori F., Kohiyama M.

    The Structural Design of Tall and Special Buildings (Wiley)  30 ( 4 )  2021.03

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  15417794

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    Because of geometric nonlinearities, vibrations in two horizontal directions can generate a torsional moment that induces a torsional response, even in a structure with no eccentricity; we term this phenomenon Q–Δ effect. In this study, the torsional response caused by the Q–Δ resonance was investigated by performing a shaking table test that involves a single-layer symmetric specimen. The specimen was designed and fabricated by focusing on one of two resonance conditions. Its moment of inertia was adjustable by changing locations of weights, and the natural frequency in the torsional mode could be modified. We developed a numerical model of the specimen, in which the columns connected to the slab were integrated into an elastic Euler beam. It was confirmed that the torsional response increased near the predicted Q–Δ resonance point. In addition, the acceleration at the corner of the slab was significantly increased. The formulated equations of motion provided a better prediction of the actual phenomena. Because the specimen corresponds to a stiff and slender high-rise building when converted into a full scale, the result suggests a need to be aware of the risk of torsional response increase due to the Q–Δ resonance.

  • Deep neural network for detecting earthquake damage to brace members installed in a steel frame

    Yamashita, T., Kohiyama, M., Oka, K.

    Japan Architectural Review (Wiley)  4 ( 1 ) 56 - 64 2021.01

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  2475-8876

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    We are developing an artificial intelligence system for structural health monitoring that can detect local damage in a building structure by using the E‐Simulator numerical simulation system that is being developed by the Japanese National Research Institute for Earth Science and Disaster Resilience. In this study, we confirmed the applicability of a multiclass classifier using a deep neural network to address the problem of identifying damage patterns in braces installed in a steel frame. Experimental data obtained from shaking table tests were used for training and testing. Cross-validation tests were conducted for several cases with different numbers of sensors, sensor degrees of freedom, and nodes in the hidden layers of the network. The results demonstrated that the accuracy of the damage pattern detection from the constructed classifier exceeded 77% when the appropriate hidden layers were selected and reached 87.9% for the best case.

  • Volcanic Hazard Map of Mt. Fuji Using Augmented Reality

    Masayuki KOHIYAMA, Tatsumi AKAHORI, Mitsuhiro YOSHIMOTO, Tomohiro KUBO

    Journal of Social Safety Science (Institute of Social Safety Science)   ( 37 ) 147 - 155 2020.11

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  1345-2088

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    The volcanic hazard map is one of the effective proactive measures for volcanic disasters. However, the general public has little interest in the hazard maps because it is not easy to understand them. To address this problem, this study develops a volcanic hazard map using augmented reality (AR). The effectiveness of the proposed AR hazard map was verified through the workshops held in Fujiyoshida City, in which participants actually used the prototype map. As a result, it was clarified that the AR hazard map could effectively supplement a printed hazard map and it was also found that the display switching function of the hazards was particularly effective for promoting understanding.

  • A Framework of Disaster Imagination Game by Residents for Developing Next-Generation Leaders for Volcanic Disaster Reduction

    Honoka TAKASHIMA, Masayuki KOHIYAMA, Mitsuhiro YOSHIMOTO, Tomohiro KUBO

    Journal of Social Safety Science (Institute of Social Safety Science)   ( 37 ) 175 - 185 2020.11

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  1345-2088

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    In order to reduce volcanic disasters, it is important for residents to practice mutual assistance, which can be led by a voluntary disaster reduction group. However, many communities lack the human resources for their future leaders. To address this issue, we created a framework of disaster imagination game to develop next-generation leaders. The effectiveness of the game was verified through workshops held in Fujiyoshida City. The framework allows residents to train independently by using a web application software.

  • Seismic Response Control of an Instrument With Casters Using Computer Vision Based on Reinforced Learning of Dynamic Analysis Results Considering Friction


    Journal of Structural Engineering (Architectural Institute of Japan)  66B   305 - 314 2020.03

    Research paper (scientific journal), Joint Work, Accepted,  ISSN  09108033

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    We developed a computer vision system to control the seismic response of medical equipment with casters in a building subjected to earthquake excitation. The controller employs a neural network and the reinforced learning was conducted based on dynamic simulations of a controlled equipment under building floor motion. In the dynamic simulations, we used Open Dynamics Engine, which is a simulator library of three-dimensional rigid body dynamics, and we introduced a friction model to simulate the dynamic behavior of the casters. To validate the proposed system, we conducted shaking table tests and it was confirmed that the proposed control could successfully suppress the response of the equipment.

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Papers, etc., Registered in KOARA 【 Display / hide

Reviews, Commentaries, etc. 【 Display / hide

  • 座談会:震災復興から考えるレジリエントな社会

    菅原 昭彦,福迫 昌之,紙田 和代,小檜山 雅之,厳 網林

    三田評論 (慶應義塾大学出版会)   ( 1253 ) 10 - 26 2021.03

    Introduction and explanation (bulletin of university, research institution), Joint Work,  ISSN  1343-618X

  • Editorial: Innovative methodologies for resilient buildings and cities

    Takewaki I., Kohiyama M., Trombetti T., Tesfamariam S., Lu X.

    Frontiers in Built Environment (Frontiers in Built Environment)  5 2019.07

  • 細分化された学問と分断された世界をつなぐ

    Masayuki KOHIYAMA

    ACe 建設業界 (一般社団法人日本建設業連合会)  80   26 - 26 2017.12

    Introduction and explanation (commerce magazine), Single Work,  ISSN  21861862

  • 東日本大震災・熊本地震災害の教訓を生かした建築・まちづくり~建物の「社会性」向上に向けて~

    Masayuki KOHIYAMA

    月刊不動産流通 (不動産流通研究所)   ( 419 ) 8 - 9 2017.04

    Introduction and explanation (commerce magazine), Single Work,  ISSN  0286-388X

  • 阪神・淡路大震災20 年シンポジウム「地震被害の軽減に向けた研究者たちのメッセージ―阪神・淡路大震災20 年:地震関連科学の到達点と新たな決意―」開催報告

    Masayuki KOHIYAMA

    JAEE Newsletter (Japan Association for Earthquake Engineering)  4 ( 1 ) 9 - 12 2015.04

    Introduction and explanation (scientific journal), Single Work

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Presentations 【 Display / hide

  • ねじれ2次モードのQ—Δ共振の検証実験と有限要素モデルによる再現解析


    日本地震工学会・大会-2020 (オンライン開催) , 2020.12, Oral Presentation(general)

  • Interpretation of Deep Neural Network for Damage Pattern Classification Using Phase Plane

    Kumagai, T., Kohiyama, M., Yamashita, T.

    7th Asian-Pacific Symposium on Structural Reliability and Its Applications (APSSRA2020) (The University of Tokyo (online conference)) , 2020.10, Oral Presentation(general)

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    The author’s research group has proposed a damage pattern classification method using a deep neural network (DNN) for monitoring the structural health of a building. We aimed to make the DNN for damage pattern classification, more accountable using the “interpretation” and “explanation” methods. We proposed generating input data that maximize the classification probability of each damage pattern, called a prototype, and drew a trajectory on a two-dimensional phase plane of appropriately selected state variables with color information on the degree of influence on the classification. We applied the proposed method to DNNs for damage classification of a wooden structure and a steel frame. The acceleration–velocity plane provided useful information about the mechanical characteristics of the DNN used in the damage pattern classification, and we thus demonstrated the effectiveness of the proposed method.

  • Wireless Seismic Response Control of an Instrument with Casters Based on Reinforced Learning Considering Stochastic Models of Computer Vision

    Wakabayashi, K., Kohiyama, M., Eguchi, R., Takahashi, M.

    7th Asian-Pacific Symposium on Structural Reliability and Its Applications (APSSRA2020) (The University of Tokyo (online conference)) , 2020.10, Oral Presentation(general)

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    We developed a computer-vision-based system to control the response of medical instruments with casters in a building subjected to earthquake excitation. The controller employed a neural network, and reinforced learning based on the dynamic simulations of a controlled instrument under building floor motion was conducted. In the dynamic simulations, we used the Open Dynamics Engine, which is a simulator library of three-dimensional rigid body dynamics and introduced a friction model to simulate the dynamic behavior of the casters. To accurately simulate the dynamic behavior of the controlled instrument, we considered the control delay of the proposed system and introduced stochastic models of errors to identify the displacement of the instrument using computer vision. To validate the proposed system, we performed dynamic simulations of a controlled instrument under building floor motion. It was revealed that the instrument response was significantly suppressed by introducing the stochastic model of errors in the training of NN. This result suggests the usefulness of stochastic models in enhancing the performance of reinforced learning based on dynamic simulations.

  • Experiment on Torsional Response of Symmetric Structure Induced by Q–Δ Resonance,

    Mizutori, F., Yokoyama, H., Kohiyama, M.

    17th World Conference on Earthquake Engineering (17WCEE) (Sendai, Japan) , 2020.09, Oral Presentation(general)

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    Proceedings published in September, 2020
    Conference postponed one year
    Sendai, Japan
    Paper ID: 2c-0204, pp. 1-12

  • Study on Visual Interpretation and Explanation Method for Deep Neural Network to Classify Building Damage Patterns Based on Acceleration Response

    KUMAGAI Takuma, KOHIYAMA Masayuki, YAMASHITA Takuzo

    Summaries of Technical Papers of Annual Meeting, Architectural Institute of Japan, 2020.07, Other, Architectural Institute of Japan

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    Vol. 構造II, pp. 1067-1068

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Research Projects of Competitive Funds, etc. 【 Display / hide

  • Resilient Vibration Control Method Considering Functional Continuity and Rapid Restoration


    MEXT,JSPS, Grant-in-Aid for Scientific Research, 小檜山 雅之, Grant-in-Aid for Scientific Research (B), Principal Investigator

  • Broadcast Responsive Vibration Control System to Reduce Damage to Facilities


    MEXT,JSPS, Grant-in-Aid for Scientific Research, 小檜山 雅之, Grant-in-Aid for Scientific Research (B), Principal Investigator

Intellectual Property Rights, etc. 【 Display / hide

  • 振動制御システム

    Application No.: 2011-157501  2011.07 

    Announcement No.: 特開2013-23844   

    Registration No.: 5828699  2015.10

    Patent, Joint, National application

  • 建物データポリゴン化システム、その方法および建物データポリゴン化プログラム

    Application No.: 特願2001-23850  2001.01 

    Announcement No.: 特開2002-230589  2002.08 

    Registration No.: 3394525  2003.01

    Patent, National application

  • フランジ付中間鋼板を使用した積層ゴム支承

    Application No.: 特許出願平9-66319  1997.03 

    Announcement No.: 特許公開平10-266624  1998.10 

    Patent, National application


Courses Taught 【 Display / hide











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Courses Previously Taught 【 Display / hide

  • Probability and Statistics

    Keio University, 2014, Spring Semester, Major subject, Lecture

  • 社会・経済・文化と工学

    Keio University, 2014, Autumn Semester, Major subject

  • 設計・計画の最適化数理

    Keio University, 2014, Autumn Semester, Major subject, Lecture

  • 空間設計製図I

    Keio University, 2014, Autumn Semester, Major subject, Seminar

  • 理工学基礎実験

    Keio University, 2014, Autumn Semester, Major subject, Laboratory work/practical work/exercise

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Social Activities 【 Display / hide

  • National Research Institute for Earth Science and Disaster Resilience

  • Lecturer of Group Training Course of Seismology and Earthquake Engineering

    International Institute of Seismology and Earthquake Engineering, Building Research Institute,  (Building Research Institute (Tsukuba, Ibaraki))


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    Subject: Structural Response Control

  • National Research Institute for Earth Science and Disaster Resilience

  • National Research Institute for Earth Science and Disaster Prevention

  • 総務省消防庁「東日本大震災の被害状況や消防機関等による活動に係る調査事業」編集会議メンバー


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Memberships in Academic Societies 【 Display / hide

  • Architectural Institute of Japan

  • Japan Society of Civil Engineers

  • Earthquake Engineering Research Institute

  • Institute of Social Safety Science

  • Japan Association for Earthquake Engineering


Committee Experiences 【 Display / hide

  • 2021.04

    荷重運営委員会信頼性工学利用小委員会委員, 日本建築学会

  • 2021.04

    荷重運営委員会委員, 日本建築学会

  • 2019.10

    企画運営委員会レジリエント建築タスクフォース委員, 日本建築学会

  • 2019.06

    論文集編集委員会委員長, 日本地震工学会

  • 2019.05

    理事, 日本地震工学会

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