Article
Engineering, Mechanical
Kai Cheng, Zhenzhou Lu, Sinan Xiao, Jingyu Lei
Summary: This paper introduces a generalized subset simulation (GSS) method for estimating small failure probability by modifying failure threshold and amplifying input variables to decompose the problem into a series of simple integrals. Two coordinate rotation schemes are used to detect important directions in high-dimensional space, transforming high-dimensional integrals into low-dimensional ones for efficient estimation. Two MCMC algorithms within GSS are introduced for low-dimensional and high-dimensional problems respectively for testing performance using benchmark examples.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Physics, Multidisciplinary
Jinn-Wen Wu, Hong-Yuan Xu, Yu-Pin Luo, Ming-Chang Huang
Summary: This paper establishes and analyzes the conditions on the stationary and state-varying transition probabilities in the corresponding discrete-time Markov chains, which lead to the occurrence of uniform collective behaviors. It introduces a new measure called the minimal time-interval of coherent transmission of informations to qualitatively characterize the convergence speed towards a uniform collective behavior. The numerical calculations on the proposed models show that this measure is consistent with the geometric distance of the corresponding network of dynamical system.
CHINESE JOURNAL OF PHYSICS
(2022)
Article
Computer Science, Information Systems
Fuan Xiao, Xiaowu Li, Kun Tang
Summary: This paper proposes a security-aware spectrum sharing scheme for wireless-powered cognitive radio networks with non-orthogonal multiple access. The scheme ensures the safety of confidential signals by introducing a secondary transmitter and artificial noise interference. By optimizing power allocation and noise power level, the transmission performance of the system can be improved.
COMPUTER COMMUNICATIONS
(2022)
Article
Engineering, Chemical
Sotaro Kojima, Jongwoo Park, Eli A. Carter, Krista S. Walton, Matthew J. Realff, David S. Sholl, Tomoyuki Yajima, Junpei Fujiki, Yoshiaki Kawajiri
Summary: Quantitative analysis of inconsistencies between experimental and simulated adsorption isotherms was conducted using Bayesian estimation with parameter uncertainties as probability distributions. The method utilized Markov Chain Monte Carlo to analyze multiple datasets, including a publicly available database. By setting simulation data as the reference, the discrepancies between experimental measurements and molecular simulation predictions were quantified. Applying this approach to CO2 adsorption isotherms on zeolite 13X and MIL-101(Cr), the differences were successfully quantified and experimental data sets that aligned with simulation were identified.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Antonio Pepiciello, Fabrizio De Caro, Alfredo Vaccaro, Sasa Djokic
Summary: This paper introduces the widely used Markov Chain-based models in power system applications and proposes a Markov Chain transient analysis framework that uses affine arithmetic to handle data uncertainties.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Water Resources
Hamed Sahranavard, Ali Mohtashami, Ehsan Mohtashami, Abolfazl Akbarpour
Summary: In this research, a simulation-optimization model called MLPG-MTLBO is used to estimate aquifer parameters on two aquifers. The model combines the meshless local Petrov-Galerkin simulation with the modified teaching-learning-based optimization algorithm. The results show that the MLPG-MTLBO model is accurate in estimating the aquifer parameters and can be applied to real field aquifers.
APPLIED WATER SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Jianghui Sang, Yongli Wang, Weiping Ding, Zaki Ahmadkhan, Lin Xu
Summary: This paper presents a reward shaping method called HGT, which propagates reward information through hierarchical graph topology to shape potential functions for complex tasks. Compared to cutting-edge RL techniques, HGT achieves faster learning rates in experiments on Atari and Mujoco tasks.
PATTERN RECOGNITION
(2023)
Article
Computer Science, Interdisciplinary Applications
Wei Cao, Annan Zhou, Shui-Long Shen
Summary: Geological uncertainty widely impacts the deformation and stability of geotechnical structures, with the coupled Markov chain (CMC) model being a common method to simulate strata variability. In this study, an analytical method for estimating the horizontal transition probability matrix (HTPM) is proposed to enhance the CMC model in simulating geological uncertainty based on given borehole data, showing good agreement with real values and insensitivity to borehole schemes.
COMPUTERS AND GEOTECHNICS
(2021)
Article
Computer Science, Information Systems
Zhixin Tie, Dingkai Zhu, Shunhe Hong, Hui Xu
Summary: An improved MCMC algorithm called TST-MCMC is proposed in this study to efficiently sample hierarchical random graphs, enhancing the feasibility and effectiveness of the algorithm.
Article
Computer Science, Interdisciplinary Applications
Christian H. Weiss, Murat Caner Testik, Annika Homburg
Summary: This study is a first step towards analyzing the effects of parameter estimation on the monitoring of autocorrelated count processes, focusing on factors like dispersion and model structures. The results suggest that the dispersion of the count process is a key parameter in chart design, and for low-dispersion scenarios, the impact of parameter estimation on design parameters may vanish.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Max Nendel
Summary: This work provides an overview of nonlinear expectations and their connection to other concepts describing model uncertainty within a probabilistic framework. The focus is on imprecise versions of stochastic processes, particularly imprecise Markov chains, discussing both basic properties and construction methods under nonlinear expectations. Illustrations using countable state space and discussions on dual representations and differential equations are presented to demonstrate the concepts discussed.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2021)
Article
Green & Sustainable Science & Technology
Channpisey Nop, Rasha M. Fadhil, Koichi Unami
Summary: This study establishes a Markov chain model for rainfall time series in temperate climates and employs stochastic dynamic programming to optimize the operation of rainwater harvesting systems. The transition probabilities of the model are based on gamma distribution assumptions with two parameters, contributing to stabilizing the optimal policy.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Mathematics, Applied
Xie Yuquan, Nie Dalu, Zhu Yin
Summary: This paper investigates the symmetry of two parameters s, t>0 for a two-parameter homogeneous transition function and yields some important and interesting results.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2021)
Article
Energy & Fuels
Xiaoyan Qiu, Hang Zhang, Yiwei Qiu, Yi Zhou, Tianlei Zang, Buxiang Zhou, Ruomei Qi, Jin Lin, Jiepeng Wang
Summary: Utility-scale hydrogen production via alkaline electrolysis is an effective way to reduce carbon emissions in various industries. The efficiency, flexibility, and safety of the alkaline electrolysis system are influenced by electrochemical, thermal, and mass transfer dynamics. However, the lack of a comprehensive parameter estimation method has hindered the accuracy and adaptability of existing models. To address this, a fast and accurate parameter estimation method based on Bayesian inference and Markov chain Monte Carlo is proposed. Experimental results demonstrate the effectiveness of this method in improving estimation accuracy and providing fault diagnosis and sensitivity analysis for alkaline electrolysis systems.
Article
Computer Science, Interdisciplinary Applications
Chao Fu, Xiaoyi Ding, Wenjun Chang
Summary: This paper proposes a multi-criteria decision model with interval numbers based on the Markov chain to generate a stable solution for a multi-criteria decision-making problem with unknown decision parameters. The existence and uniqueness of the stable solution are theoretically proven, and the effectiveness and applicability of the model are validated through case comparison.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Environmental
Ziqi Ma, Zhenxue Dai, Xiaoying Zhang, Chuanjun Zhan, Huili Gong, Lin Zhu, Corey D. Wallace, Mohamad Reza Soltanian
Summary: The accuracy of flow and contaminant transport prediction in subsurface formations is significantly affected by heterogeneity. The study found that the model can accurately predict plume spreading when the spatial correlation structure is well defined. Moreover, the upscaled dispersivity is mainly influenced by the cross-transition probability structure.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2022)
Article
Geosciences, Multidisciplinary
Chuanjun Zhan, Zhenxue Dai, Mohamad Reza Soltanian, Xiaoying Zhang
Summary: This study develops an inversion framework that combines stochastic and deep-learning models to overcome limitations in identifying subsurface sedimentary structures. The framework generates structure samples required by deep-learning models through stochastic models and reduces uncertainty using the trained deep-learning model. It successfully estimates subsurface sedimentary structures using available observations.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Geosciences, Multidisciplinary
Wen Zhang, Jia Wang, Jianping Chen, Mohamad Reza Soltanian, Zhenxue Dai, Giday WoldeGabriel
Summary: This article discusses the impact of the Indian summer monsoon on precipitation in the Indian subcontinent and the world's population, and proposes a proxy based on mass-wasting for studying the paleo-hydrogeology of the Southeast Tibetan Plateau and reconstructing the variability of ISM intensity in the past 130,000 years. The research suggests that mass-wasting events provide sufficient samples for paleoclimate research and are prone to dramatic climate changes.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Chemistry, Physical
Reza Ershadnia, Mrityunjay Singh, Saeed Mahmoodpour, Alireza Meyal, Farzad Moeini, Seyyed Abolfazl Hosseini, Daniel Murray Sturmer, Mojdeh Rasoulzadeh, Zhenxue Dai, Mohamad Reza Soltanian
Summary: Transitioning to renewable energies is crucial for addressing climate change and establishing a sustainable energy system. However, the fluctuation in availability of renewable energy sources poses a challenge of demand and supply imbalance. In this study, we investigate the injection, storage, and production of green hydrogen (H2) in a three-dimensional heterogeneous aquifer system, considering factors such as anisotropy ratio, temperature, relative permeability hysteresis, well perforation placement, and cushion gas type. Our findings suggest that successful H2 recovery depends on the aquifer's anisotropy, temperature, injection and production strategies, as well as the use of low-density and low-viscosity cushion gas.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Engineering, Environmental
Xiaoying Zhang, Zheng Wang, Paul Reimus, Funing Ma, Mohamad Reza Soltanian, Baoshan Xing, Jianzheng Zang, Yu Wang, Zhenxue Dai
Summary: This study investigates the concurrent transport of plutonium (Pu) species in the subsurface environment and reveals the sorption behavior of each species. The experimental results show that the transport behavior of Pu is affected by its oxidation states and species. The model developed in this study can describe the sorption of Pu species occurring either on fracture surfaces or in the rock matrix. Moreover, the study finds that the sorption rate of all Pu species tends to decrease with increasing time scales.
Article
Environmental Sciences
Wanli Ren, Reza Ershadnia, Corey D. Wallace, Eric M. LaBolle, Zhenxue Dai, Felipe P. J. de Barros, Mohamad R. Soltanian
Summary: This study investigates the dispersion and mixing behavior of solute in a heterogeneous aquifer using high-resolution and three-dimensional numerical simulations. The results show that meter-scale heterogeneity plays a significant role in solute transport processes, and effective dispersion is more sensitive to the spatial organization of sedimentary facies types.
WATER RESOURCES RESEARCH
(2022)
Article
Environmental Sciences
Chuanjun Zhan, Zhenxue Dai, Mohamad Reza Soltanian, Felipe P. J. de Barros
Summary: Reliable characterization of subsurface structures is crucial for earth sciences and related applications. Data assimilation-based identification frameworks, coupled with non-isothermal flow and transport simulations, can accurately estimate subsurface structures using available observations. Results show that including dynamic observations improves structure identification and reduces uncertainty. Furthermore, the deep learning-based framework outperforms stochastic methods in accurately identifying subsurface structures.
WATER RESOURCES RESEARCH
(2022)
Article
Energy & Fuels
Yanwei Wang, Zhenxue Dai, Li Chen, Xudong Shen, Fangxuan Chen, Mohamad Reza Soltanian
Summary: A multi-scale model is developed to describe CO2 transport and storage in shale reservoirs with a multi-stage fractured horizontal well. The study proposes a workflow for evaluating CO2 storage capacity, based on the established model. The findings suggest that CO2 storage capacity is influenced by various factors, and the storage capacity can increase significantly at high injection pressures.
Article
Engineering, Civil
Wanli Ren, Heng Dai, Songhu Yuan, Zhenxue Dai, Ming Ye, Mohamad Reza Soltanian
Summary: Lagrangian-based transport models can effectively study mass transport processes in aquifer systems. This study identifies the key uncertain inputs for non-reactive and sorptive solute dispersivity through a global sensitivity analysis. The results show that sorptive solute dispersivity is most sensitive to in-facies mean Kd, while non-reactive plume dispersivity is most sensitive to in-facies mean K and other facies properties.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Environmental
Sida Jia, Zhenxue Dai, Zhichao Zhou, Hui Ling, Zhijie Yang, Linlin Qi, Zihao Wang, Xiaoying Zhang, Hung Vo Thanh, Mohamad Reza Soltanian
Summary: Physical heterogeneities are prevalent in fracture systems and have a significant impact on transport processes in aquifers. Upscaling solute transport parameters is an effective method for studying variability in heterogeneous aquifers. This paper develops conceptual models for upscaling conservative transport parameters, focusing on dispersivity. The proposed Lagrangian-based transport model is validated and compared against experimental results, showing good agreement.
Article
Computer Science, Artificial Intelligence
Shadfar Davoodi, Hung Vo Thanh, David A. Wood, Mohammad Mehrad, Valeriy S. Rukavishnikov, Zhenxue Dai
Summary: Ongoing anthropogenic carbon dioxide emissions cause severe air pollution and complex changes in the climate. Geological CO2 storage offers a promising solution by removing some of the CO2 emissions. This study models the solubility and trapping efficiency of CO2 in saline aquifers using machine learning and deep learning algorithms, and finds that the LSSVM model delivers the most accurate predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Geochemistry & Geophysics
Huichao Yin, Gaizhuo Zhang, Qiang Wu, Shangxian Yin, Mohamad Reza Soltanian, Hung Vo Thanh, Zhenxue Dai
Summary: This study proposes an innovative data-driven approach for predicting mining water inrush using field 3-D microseismic monitoring data. The approach couples machine learning and deep learning models to analyze microseismic events, preprocesses the data using DBSCAN and RANSAC algorithms, and detects anomalies using LSTM, AE, iForest, and LSTM+iForest models. The study accurately predicts a major water inrush incident hours prior to its occurrence and suggests future studies to evaluate and calibrate the deep learning models using microseismic datasets from different mining operations.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Engineering, Environmental
Xiaoying Zhang, Fangfei Cai, Funing Ma, Paul Reimus, Linlin Qi, Di Lu, Mohamad Reza Soltanian, Zhenxue Dai
Summary: This study investigated the co-transport behavior of radionuclides and colloids in different types of granite minerals. It found that the presence of colloids enhanced the transport of strontium and different minerals showed different retardation levels. Potassium feldspar was less affected by colloids due to its strong cation exchange capacity.
JOURNAL OF HAZARDOUS MATERIALS
(2024)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)