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Name MARUYAMA Osamu
Official Title Professor
Affiliation Urban and Civil Engineering
E-mail omaruya@tcu.ac.jp
Web
  1. https://www.risys.gl.tcu.ac.jp/Main.php?action=01&type=detail&tchCd=5001273
Profile My research field is the application of probability theory to civil engineering.　Specifically, the development of the basic theory of probability theory or optimization method and its application to actual phenomena.　In the health monitoring of existing structures, the Kalman filter is used to estimate the dynamic characteristics of structures.　We are also researching a method for calculating the failure probability of structures that are subject to external load.　Regarding the problem of aging deterioration of structures, we developed a method to estimate the near future state using stochastic differential equations.　These research results are used for structure maintenance or risk assessment.　The research target is structures such as water supply systems, tunnels, and bridges that are spatially expansive.
Research Field(Keyword & Summary)
  1. (1)A stochastic model for deterioration process

    We propose a probabilistic model for describing temporal variation of damage accumulation in age civil engineering structute. The proposed model is based upon a stochastic differential equation driven by a Poisson white noise, whose solution process represents a damage accumulation.

  2. (2)Probable Maximum Loss Index of Water Supply System

    Probable maximum loss index is employed to evaluate the seismic risk of water supply system. An alternative method is proposed to avoid the complicated event tree analysis and evaluate probable Maximum Loss index of the high order water supply network system.

Representative Papers
  1. (1) Kernel Regression Estimator for Damage States of Tunnel Lining Concrete, 13th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP13), May 2019
  2. (2) Stochastic Interpolation of Damage States in Tunnel Lining Concrete, 12th Int. Conf. on Structural Safety and Reliability (ICOSSAR2017), Aug. 2017
  3. (3) Visualization system for bridge deformations under live load based on multipoint simultaneous measurements of displacement and rotational response using MEMS sensors, Engineering Structures, Vol.146, No.1, May 2017.
  4. (4) A Mixed Poisson Model for Random Damege Accumulation of Tunnel Concrete Linings, Theoretical And Applied Mechanics JAPAN, Vol.62, No.1 2014/7
  5. (5) A Stochastic model for deterioration process of tunnel lining concrete in cold regions, Engineering Structures, 11th International Conference on Structural Safety and Reliability (ICOSSAR2013), June,2013
  6. (6) Stochastic Interpolation of Spatial Random Fields by BF/MCF-ISM, Jour. of Engineering Mechanics, ASCE, Vol.134, No.2, Feb. 2008.
  7. (7) Adaptive Identification of Autoregressive Process, Journal of Engineering Mechanics, ASCE, Vol.117, No.7, July 1991.
  8. (8) Program EXKAL2 for Identification of Structural Dynamic Systems, Journal of Engineering Mechanics, Technical Report NCEER-89-0014, National Center for Earthquake Engineering Research, State University of New York at Buffalo, May 1989.
  9. (9) Fundamentals of System Identification in Structural Dynamics, Probabilistic Engineering Mechanics, Vol.4, No.4, April, 1989.
  10. (10) Identification of Running Load and Beam System, Journal of Engineering Mechanics, ASCE, Vol. 113, No.6, June 1987.
Grant-in-Aid for Scientific Research Support: Japan Society for Promotion of Science (JSPS) https://nrid.nii.ac.jp/nrid/1000050209699/
Recruitment of research assistant(s) No
Affiliated academic society (Membership type) (1) Japan Society of Civil Engineers (member)
(2) Japan Association for Earthquake Engineering (Member)
Education Field (Undergraduate level) System Identification
Education Field (Graduate level) Baysian Updating Theory, Signal Proccesing

Affiliation