Browsing by Author "Hsiao, Chin-Tsai"

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Constructing the Apparent Geological Model by Fusing Surface Resistivity Survey and Borehole Records
(2019-07-01)
Tsai, Jui-Pin
;
Chang, Ping-Yu
;
Yeh, Tian-Chyi J.
;
Chang, Liang-Cheng
;
Hsiao, Chin-Tsai
We constructed an apparent geological model with resistivity data from surface resistivity surveys. We developed a data fusion approach by integrating dense electrical resistivity measurements collected with Schlumberger arrays and wellbore logs. This approach includes an optimization algorithm and a geostatistic interpolation method. We first generated an apparent formation factor model from the surface resistivity measurements and groundwater resistivity records with an inverse distance method. We then converted the model into a geology model with the optimized judgment criteria from the algorithms relating the apparent formation factors to the borehole geology. We also employed a non-parametric bootstrap method to analyze the uncertainty of the predicted sediment types, and the predictive uncertainties of clay, gravel, and sand were less than 5%. Overall, our model is capable of capturing the spatial features of the sediment types. More importantly, this approach can be arranged in a self-updated sequence to enable adjustments to the model to accommodate newly collected core records or geophysical data. This approach yields a more detailed apparent geological model for use in future groundwater simulations, which is of benefit to multi-discipline studies.
Features of spatiotemporal groundwater head variation using independent component analysis
(2017-04-01)
Hsiao, Chin-Tsai
;
Chang, Liang-Cheng
;
Tsai, Jui-Pin
;
Chen, You-Cheng
;
土木工程學系
The effect of external stimuli on a groundwater system can be understood by examining the features of spatiotemporal head variations. However, the head variations caused by various external stimuli are mixed signals. To identify the stimuli features of head variations, we propose a systematic approach based on independent component analysis (ICA), frequency analysis, cross-correlation analysis, well selection strategy, and hourly average head analysis. We also removed the head variations caused by regional stimuli (e.g., rainfall and river stage) from the original head variations of all the wells to better characterize the local stimuli features (e.g., pumping and tide). In the synthetic case study, the derived independent component (IC) features are more consistent with the features of the given recharge and pumping than the features derived from principle component analysis. In a real case study, the ICs associated with regional stimuli highly correlated with field observations, and the effect of regional stimuli on the head variation of all the wells was quantified. In addition, the tide, agricultural, industrial, and spring pumping features were characterized. Therefore, the developed method can facilitate understanding of the features of the spatiotemporal head variation and quantification of the effects of external stimuli on a groundwater system. (C) 2017 Elsevier B.V. All rights reserved.
Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management
(2012-03-01)
Chang, Liang-Cheng
;
Chu, Hone-Jay
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Hsiao, Chin-Tsai
;
土木工程學系
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Department of Civil Engineering
This study integrates an artificial neural network (ANN) and constrained differential dynamic programming (CDDP) to search for optimal solutions to a nonlinear time-varying groundwater remediation-planning problem. The proposed model (ANN-CDDP) determines optimal dynamic pumping schemes to minimize operating costs and meet water quality requirements. The model uses two embedded ANNs, including groundwater flow and contaminant transport models, as transition functions to predict groundwater levels and contaminant concentrations under time-varying pumping. Results demonstrate that ANN-CDDP is a simplified management model that requires considerably less computation time to solve a fine mesh problem. For example, the ANN-CDDP computing time for a case involving 364 nodes is 1/26.5 that of the conventional optimization model.
Optimal planning of a dynamic pump-treat-inject groundwater remediation system
(2007-09-01)
Chang, Liang-Cheng
;
Chu, Hone-Jay
;
Hsiao, Chin-Tsai
;
土木工程學系
;
Department of Civil Engineering
This study integrates the genetic algorithm (GA) and constrained differential dynamic programming (CDDP) to design the pump-treat-inject system. The proposed model. considers both the cost of installing wells (fixed cost) and the operating cost of pumping, injection and water treatment. To minimize the total cost white meeting the water quality constraints, the model can compute the optimal number and locations of wells, as welt as the associated optimal pumping and injection schemes. Various numerical cases reveal that the requirement to balance the total volume between pumping and injection can significantly influence the final optimal design. (C) 2007 Elsevier B.V. All rights reserved.