Name YOSHIDA Ikumasa
Official Title Professor
Affiliation Urban and Civil Engineering
Profile My specialty is application of Bayesian inference, random field theory, Gaussian process regression, theories of inverse problem and data science technologies to geotechnical and structural engineering problems. These research is useful for health monitoring, risk management and reliability engineering of infra-structures.
Research Field(Keyword & Summary)
  1. 1. Spatial variability of geotechnical properties

    The risk of failure for a geotechnical structure significantly depends on the properties of the surrounding soil. Understanding spatial variability of geotechnical properties is thus important for geotechnical applications. We propose a method for estimating the spatial variability at arbitrary locations using Gaussian process regression with the superposition of multiple Gaussian random fields.

  2. 2. Bayesian Bridge Weigh-In-Motion (BWIM)

    BWIM systems use the bridge as a scale to measure the weight of vehicles passing over it. BWIM technology has attracted attention as a promising tool for bridge design optimization, overweight enforcement, fatigue prediction and maintenance planning. We proposed Bayesian bridge weigh-in-motion (BBWIM), which combines static BWIM and the probabilistic inverse problem, which includes a broad class of inverse problems such as the Kalman filter.

  3. 3. Reliability Estimation of Existing Structures

    The main research topics in this item are to develop the methodology to estimate limit state probability updated by inspection or test data. Inspection or test data of specific site as well as latest knowledge of degrading mechanism should be considered in order to perform accurate reliability estimation of existing structures. The formulation with sequential Monte Carlo simulation (SMCS) or Particle Filter is introduced for updating of model parameters and limit state probability. This is applied for RC structure with chloride deterioration and settlement of ground.

Representative Papers
  1. 1) Yoshida, I, Tomizawa, Y., Otake, Y., Estimation of trend and random components of conditional random field using Gaussian process regression, Computers and Geotechnics, vol.136, 2021.8
  2. 2) Zhu, Y., Sekiya, H., Okatani, T., Yoshida, I. and Hirano, S. Acceleration-based deep learning method for vehicle monitoring, IEEE Sensors Journal, pp.1-1, 2021.5. DOI: 10.1109/JSEN.2021.3082145
  3. 3) Yoshida, I. and Shuku, T. 2021. Soil Stratification and Spatial Variability Estimated Using Sparse Modeling and Gaussian Random Field Theory, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ.Eng. 7(3). 2021.9
  4. 4) Yoshida, I., Sekiya, H. and Mustafa, S., Bayesian Bridge Weigh-In-Motion and Uncertainty Estimation, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., 2021.1, 7(1): 04021001
  5. 5) Shinoda, M., Nakajima, S., Watanabe, K., Nakamura, S. and Yoshida, I., Practical seismic fragility estimation of unreinforced and reinforced embankments in Japan, Geosynthetics International, Vol.28, No.1, 2020.1
  6. 6) Shuku, T., Phoon, K-K. and Yoshida, I., Trend estimation and layer boundary detection in depth-dependent soil data using sparse Bayesian lasso, Computers and Geotechnics, vol.128, 2020.12, 103845
  7. 7) Yoshida, I. and Shuku, T., Bayesian Updating of Model Parameters by Iterative Particle Filter with Importance Sampling, ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, ASCE-ASME J. Risk Uncertainty Eng. Syst., Part A: Civ. Eng., 6(2), 2020.6
  8. 8) Susumu Nakamura, Ikumasa Yoshida and Masuhiro Beppu, Approach to Assess Influence of Earthquake-Induced Slope Collapse on Nuclear Power Plant Facilities, Journal of Earthquake and Tsunami, 12(4), 2018.8. (DOI: 10.1142/S1793431118410117)
  9. 9) Ikumasa Yoshida, Yosuke Tasaki, Yu Otake, Stephen Wu, Optimal Sampling Placement in a Gaussian Random Field Based on Value of Information, Journal of Risk and Uncertainty Analysis, ASCE, 2018.9
  10. 10) Diaz De La O, F. A., Garbuno-Inigo, A., Au, S. K., and Yoshida, I., Bayesian updating and model class selection with Subset Simulation. Computer Methods in Applied Mechanics and Engineering, 317, 1102-1121. doi:10.1016/j.cma.2017.01.006
Grant-in-Aid for Scientific Research Support: Japan Society for Promotion of Science (JSPS)
Recruitment of research assistant(s) Yes (1)
Affiliated academic society (Membership type) (1)JSCE, (2)JGS, (3)JAEE
Education Field (Undergraduate level) Earthquake Engineering, Engineering and Ethics, Mathematical Statistics,
Education Field (Graduate level) Advanced Applied Mathematical Statistics, Adv