Bridge weigh-in-motion considering dynamic response in observation noise with application to multiple driving conditions

In addition to causing a static response when traversing a bridge, moving vehicles also produce a dynamic response, which is thought to be one of the factors adversely affecting the accuracy of bridge weigh-in-motion approaches. This paper proposes a novel method for improving the accuracy of such approaches. Rather than modeling the dynamic response directly, the proposed model considers it as noise with autocorrelation. A Bayesian inference approach is considered as it allows a rational way of assimilating data into the model. Here, the dynamic response is considered in the form of a covariance matrix of observation noise, composed of the residuals of the measured and calculated responses, in a Bayesian framework. In a validation study using actual measured data, it was confirmed that the estimation of axle weights in the presence of multiple vehicles was significantly improved. From the result, it can be concluded that proper modeling of the dynamic response in observation data leads to more accurate weigh-in-motion estimates of axle weights and GVW, particularly when complicated vehicle travel is involved. A comparison of static and dynamic influence lines is also discussed using actual measured data. It is shown that the weights estimated by the dynamic influence line are generally more accurate than those by the static influence line when correlation of noise is not considered. The dynamic component in influence line can be interpreted as a regularization term. The proposed method, which uses static influence line and covariance matrix considering correlation of noise, is more accurate than the method with dynamic influence line and also, it does not cause any bias.journal articl

Tribochemical investigation of Cr-doped diamond-like carbon with a MoDTC-containing engine oil under boundary lubricated condition

Cr-doped diamond-like carbon (Cr-DLC) coatings were deposited and investigated for their tribological properties. A hybridized deposition technique consisted of a bipolar plasma-based ion implantation and deposition (PBII&D) and magnetron sputtering was used for the deposition. Raman spectra revealed an increase of ID/IG upon the Cr introduction, indicating the embedded CrCx act as catalysts to produce sp2 sites. The coefficients of friction (COF) were effectively reduced once MoDTC was added to the base oil. X-ray photoelectron spectroscopy (XPS) confirmed the presence of MoO3, MoS2, and MoS2−xOx in the MoDTC-derived tribofilm. The contribution of MoS2−xOx decreased with the Cr content, suggesting that the wear particles of CrCx intervenes in the process of MoDTC decomposition by preventing the oxidation of MoS2 sheets.journal articl

X 線回折法による鉄鋼材料の転位特性解析の基礎的研究

東京都市大学博士（工学）2022年度(令和4年)doctoral thesi

Dielectric relaxation processes observed in hydroxypropyl Cellulose − Ethanol solutions

We performed dielectric measurements of hydroxypropyl cellulose (HPC) − ethanol solutions with various HPC concentrations at various temperatures. A symmetric primary relaxation process reflecting the motion of ethanol molecules was observed in the high-temperature range. Below 250 K, additional relaxation processes appeared on the low-frequency side of the primary process observed at high temperatures. The molecular mechanism of this separation behavior of the relaxation processes can be explained in terms of the fragmentation of the hydrogen bonding network of ethanol molecules caused by the impregnation of HPC molecules into the hydrogen bonding network of the ethanol molecules. Below 250 K, each fragment forms a larger fragment through hydrogen bonding with the HPC molecules, and the motion of these large fragments leads to an additional low-frequency relaxation process. In addition, the obtained dielectric parameters were compared with the spatial scale of the liquid crystal structure obtained by synchrotron small-angle X-ray scattering (SAXS) measurements.journal articl

筋電気刺激を用いた指関節の制御

東京都市大学博士（工学）2022年度(令和4年)doctoral thesi

行為分解木手法を用いたものづくり中小企業におけるイノベーション 思考モデルの開発 －山形県の企業を事例として－

東京都市大学博士（環境情報学）2022年度（令和4年）doctoral thesi

Bayesian updating of model parameters using adaptive Gaussian process regression and particle filter

Bayesian model updating provides a powerful framework for updating and uncertainty quantification of models by making use of observations, following probability rules in the treatment of uncertainty. Particle filter (PF) and Bayesian Updating with Structural Reliability method (BUS) have been developed by researchers as promising computational tools for this purpose. However, reducing computational cost in the updating process, especially for complex models, remains one of the key challenges. Surrogate model approach achieves this by appropriately replacing, possibly adaptively, the evaluation of the original computationally costly models with approximate ones that are much less costly. This study proposes an efficient method to estimate the posterior probability density function (PDF) of model parameters by using a surrogate model constructed using adaptive Gaussian Process Regression and PF. Of critical importance is the development of ‘learning function’, which finds the location of large values of posterior PDF and avoids those that have been visited. The proposed methodology is illustrated using a single-variable example and compared with PF and BUS. Its application is illustrated through an example of structural dynamics and another one on settlement prediction by soil–water coupled FEM with Cam-clay model.journal articl

Estimation of engineering bedrock layer utilizing ground surface elevation in Gaussian process regression

An understanding of the ground structure has a significant impact on the performance of any structure built. Many cases of substantial inclination and settlement of buildings due to insufficient understanding have been reported. In the early stages of design, it is often difficult to estimate the depth to the bedrock layer over a wide area from a very limited number of borings. It is known that the elevation of the engineering bedrock layer and ground surface elevation are highly correlated. Ground surface elevation are useful as information on the elevation of the engineering bedrock layer because such data are available in the early stages. This paper proposes a methodology for estimating the spatial distribution of the engineering bedrock layer by utilizing the ground surface elevation in Gaussian process regression. We focus on the tendency of the engineering bedrock layer to be close in elevation to the ground surface when the slope angle is large. If the slope angle is below a certain value, the ground surface elevation is considered to have no significant information for engineering bedrock estimation and is excluded from observation. The estimation accuracy is evaluated by cross-validation, and the effectiveness of the proposed method is discussed.journal articl

自転車における技術革新と社会システムとの相互関係に関する考察

東京都市大学博士（環境情報学）2022年度（令和4年）doctoral thesi

認知症高齢者グループホームにおけるサインを媒体とした環境構築に関する研究

東京都市大学博士（工学）2022年度(令和4年)doctoral thesi