Article
Engineering, Manufacturing
P. Honarmandi, R. Seede, L. Xue, D. Shoukr, P. Morcos, B. Zhang, C. Zhang, A. Elwany, I. Karaman, R. Arroyave
Summary: The Eagar-Tsai (E-T) model in the context of 3D printing was studied systematically from an uncertainty quantification/propagation (UQ/UP) perspective. Model parameters were calibrated against experimental data using Markov Chain Monte Carlo (MCMC) sampling, and posterior distributions of parameter values were propagated. It was found that discrepancies between predicted and measured melt pool depths existed under keyholing conditions, but a physics-based correction improved agreement with experiments without increasing model complexity significantly.
ADDITIVE MANUFACTURING
(2021)
Article
Engineering, Mechanical
P. L. Green, L. J. Devlin, R. E. Moore, R. J. Jackson, J. Li, S. Maskell
Summary: This paper discusses the optimization of the 'L-kernel' in Sequential Monte Carlo samplers to improve performance, resulting in reduced variance of estimates and fewer resampling requirements.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Civil
Jia-Hua Yang, Heung-Fai Lam, Yong-Hui An
Summary: The paper proposes a new two-phase adaptive MCMC method to address the problem of determining the posterior probability density function (PDF) in Bayesian model updating. By using a parameter-space search algorithm and a weighted MCMC algorithm, samples in the regions of high probability can be generated adaptively without going through computationally demanding multiple levels.
ENGINEERING STRUCTURES
(2022)
Review
Green & Sustainable Science & Technology
D. Hou, I. G. Hassan, L. Wang
Summary: Building Energy Model (BEM) calibration is crucial for accuracy, with recent focus on stochastic Bayesian inference calibration. However, confusion remains regarding theory, strengths, limitations, and implementations. Selecting appropriate mathematical models and tools poses a challenge.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Engineering, Mechanical
Adolphus Lye, Alice Cicirello, Edoardo Patelli
Summary: This tutorial paper reviews the use of advanced Monte Carlo sampling methods in Bayesian model updating for engineering applications, introducing different methods and comparing their performance. Three case studies demonstrate the advantages and limitations of these sampling techniques in parameter identification, posterior distribution sampling, and stochastic identification of model parameters.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Geological
Zening Zhao, Surya Sarat Chandra Congress, Guojun Cai, Wei Duan
Summary: The study proposed a Bayesian inference approach combined with total probability theorem to obtain the updated distributions of c(h) from a limited number of test data, recommending the use of model M-2 for calculating c(h).
Article
Meteorology & Atmospheric Sciences
Xiaohan Yu, Xiankui Zeng, Dongwei Gui, Xiaolan Li, Qiqi Gou, Dong Wang, Jichun Wu
Summary: This study projected flash droughts in the headstream area of the Tarim River Basin using the VIC model and found that the frequency and intensity of flash droughts are expected to increase in the future, especially in the alpine region. The CMIP6 model was identified as the most important source of uncertainty in flash drought projections.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
(2023)
Article
Ecology
Luiza Guimaraes Fabreti, Sebastian Hoehna
Summary: This study explores different methods for assessing convergence in phylogenetics, including deriving a threshold for minimum effective sample size and converting tree samples into traces of absence/presence of splits for standard ESS computation. The Kolmogorov-Smirnov test is suggested for assessing convergence in distribution between replicated MCMC runs, while potential scale reduction factor is deemed biased for skewed posterior distributions. Additionally, the study introduces a method for computing distribution of differences in split frequencies, highlighting the importance of using the 95% quantile for checking convergence in split frequencies.
METHODS IN ECOLOGY AND EVOLUTION
(2022)
Article
Engineering, Geological
Liang Han, Lin Wang, Wengang Zhang, Zhixiong Chen
Summary: This study presented a database of UCS from four sites in the Bukit Timah Granite formation in Singapore, and used Bayesian method and MCMC algorithm to quantitatively evaluate the uncertainties of statistical characteristics of UCS. The results showed significant statistical uncertainties of the three statistical characteristics of BTG rocks, which somewhat rely on the selection of basic parameters and autocorrelation function classes.
GEORISK-ASSESSMENT AND MANAGEMENT OF RISK FOR ENGINEERED SYSTEMS AND GEOHAZARDS
(2022)
Article
Engineering, Multidisciplinary
Ke Zhang, Kailun Su, Yunhan Yao, Qingsong Li, Suan Chen
Summary: This paper presents a dynamic evaluation model of Markov chain Monte Carlo (MCMC) roundness error measurement uncertainty based on a stochastic process. The model samples the stochastic process using the MCMC method and calculates the state transition function to reflect the autocorrelation characteristics of the parameters. A comparison between high-precision and low-precision measurements verifies the accuracy and stability of the model, showing that the MCMC method is consistent with the traditional GUM method and Monte Carlo method. The MCMC method based on the stochastic process achieves dynamic evaluation of roundness error measurement uncertainty, obtaining accurate results and improving the evaluation accuracy.
Article
Mathematics, Interdisciplinary Applications
Juan P. Madrigal-Cianci, Fabio Nobile, Raul Tempone
Summary: In this work, a class of multilevel Markov chain Monte Carlo (ML-MCMC) algorithms based on independent Metropolis-Hastings proposals is presented, analyzed, and implemented for Bayesian inverse problems. The algorithm aims to construct highly coupled Markov chains together with the standard multilevel Monte Carlo method to achieve better cost-tolerance complexity. The effectiveness of the proposed method is demonstrated through convergence analysis and numerical experiments on various academic examples.
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION
(2023)
Article
Agriculture, Dairy & Animal Science
M. A. Stephen, C. R. Burke, N. Steele, J. E. Pryce, S. Meier, P. R. Amer, C. V. C. Phyn, D. J. Garrick
Summary: In this study, the genetic and phenotypic relationships between anogenital distance (AGD) and body stature and fertility traits in dairy cattle were characterized. The results showed that AGD is a moderately heritable trait and is associated with reproductive success in lactating cows.
JOURNAL OF DAIRY SCIENCE
(2023)
Article
Mathematics, Applied
Hillary R. Fairbanks, Umberto Villa, Panayot S. Vassilevski
Summary: This work introduces a new hierarchical multilevel method for generating Gaussian random field realizations in a scalable manner, which is tested in a multilevel MCMC algorithm to explore its feasibility.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2021)
Article
Engineering, Marine
Mohammad Yazdi, Faisal Khan, Rouzbeh Abbassi
Summary: Microbiologically influenced corrosion (MIC) is a significant cause of hazardous hydrocarbon release and fires. A new MIC management methodology using Continuous Bayesian Network (CBN) technique with Hierarchical Bayesian Analysis (HBA) is proposed in this paper to accurately monitor MIC activity and develop effective strategies. The integration of HBA and CBN helps overcome limitations and uncertainties in the Bayesian network, providing precise parameters values for failure probability and MIC occurrence rate.
Review
Statistics & Probability
Christopher Nemeth, Paul Fearnhead
Summary: MCMC algorithms are considered the gold standard technique for Bayesian inference, but the computational cost can be prohibitive for large datasets, leading to the development of scalable Monte Carlo algorithms. One type of these algorithms is SGMCMC, which reduces per-iteration cost by utilizing data subsampling techniques.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2021)
Article
Environmental Sciences
Jing Yang, Ming Ye, Xingyuan Chen, Heng Dai, Anthony P. Walker
Summary: This study develops a new total-effect process sensitivity index to identify influential processes under model uncertainty, considering uncertainty in process models and model parameters. The total-effect process sensitivity index includes both first-order sensitivity index for measuring the importance of individual processes and higher-order indices that account for process interactions.
WATER RESOURCES RESEARCH
(2022)
Article
Geosciences, Multidisciplinary
Ahmed S. Elshall, Ming Ye, Sven A. Kranz, Julie Harrington, Xiaojuan Yang, Yongshan Wan, Mathew Maltrud
Summary: The ensemble method of prescreening-based subset selection is proposed to improve ensemble predictions of Earth system models (ESMs). The method categorizes the independent ensemble members based on their ability to reproduce specific features of interest, and updates the ensemble size by selecting subsets that enhance the ensemble prediction performance. This method is applied to improve the prediction of red tide along the West Florida Shelf in the Gulf of Mexico, and the results demonstrate the importance of prescreening-based subset selection with decision relevant metrics in identifying non-representative models and improving ensemble prediction.
FRONTIERS IN EARTH SCIENCE
(2022)
Article
Water Resources
Xiaoping Zhang, Yan Zhu, Jing Wang, Lili Ju, Yingzhi Qian, Ming Ye, Jinzhong Yang
Summary: The study introduces a new method GW-PINN for solving groundwater flow equations with wells without labeled data. By employing different constraints and sampling strategies, GW-PINN demonstrates strong capabilities in capturing hydraulic head changes and reducing sampling points in groundwater flow simulations.
ADVANCES IN WATER RESOURCES
(2022)
Article
Agronomy
Wei Mao, Yan Zhu, Jingwei Wu, Ming Ye, Jinzhong Yang
Summary: This study evaluated the effects of limited irrigation on water movement and salt accumulation in agricultural areas. The results showed that limited irrigation led to a decline in groundwater level, increased soil salt storage, and a threat of soil salinization.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Agronomy
Tianxing Zhao, Yan Zhu, Ming Ye, Jinzhong Yang, Biao Jia, Wei Mao, Jingwei Wu
Summary: Accurate estimation of phreatic evapotranspiration (ET) is crucial for water resource management and prevention of soil salinization. This study developed a new approach based on NDVI and measured water table depths to estimate the spatial-temporal distribution of phreatic ET. The results matched well with the groundwater balance model and showed the importance of phreatic ET in supporting crop growth and the ecological environment in arid areas.
AGRICULTURAL WATER MANAGEMENT
(2022)
Article
Environmental Sciences
Ahmed S. Elshall, Ming Ye, Sven A. Kranz, Julie Harrington, Xiaojuan Yang, Yongshan Wan, Mathew Maltrud
Summary: Earth system models are valuable tools for climate services, but their potential for regional environmental management is yet to be fully explored. This article demonstrates the use of high-resolution models to study the Florida Red Tide and establishes a causal link between the position of Loop Current and red tide occurrences. The study highlights the prospects of utilizing publicly available data for regional management and discusses the importance of stakeholder participation in future model development.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Mathematics, Interdisciplinary Applications
Jing Hu, Qimin Zhang, Anke Meyer-Baese, Ming Ye
Summary: In this paper, two classes of mathematical models associated with Alzheimer's disease (AD) are developed, considering reaction-diffusion, delay and random disturbances. The stability of the equilibrium and the Hopf bifurcation in the deterministic AD model are analyzed. The finite-time contractive stability (FTCS) for the stochastic AD model modulated by Markov switching process is investigated, focusing on the influence of uncertain factors in the environment on AD.
INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS
(2022)
Article
Engineering, Civil
Qi Liu, Heng Dai, Dongwei Gui, Bill X. Hu, Ming Ye, Guanghui Wei, Jingxiu Qin, Jin Zhang
Summary: This study used wavelet analysis to evaluate the effects of flow regimes of ecological water transport projects (EWTP) on ecohydrological system dynamics. The results showed that the restoration flow exhibited seasonal periodicities different from natural streams, leading to distinct groundwater dynamics and mismatched growth rhythm of riparian vegetation. Two designed flow schemes based on time lags between flow and vegetation growth were proposed to optimize the EWTP and improve ecosystem restoration efficiency. The NARX network was used for ecological restoration prediction, showing a significant increase in restoration flow compared to the original flow. The methodologies used in this study are rigorous and applicable to other EWTPs.
JOURNAL OF HYDROLOGY
(2022)
Article
Engineering, Civil
Mengqin Wang, Yan Zhu, Tianxing Zhao, Lihong Cui, Wei Mao, Ming Ye, Jingwei Wu, Jinzhong Yang
Summary: Field experiments were conducted to analyze the non-synchronized movement of soil water and salt during freezing-thawing periods, with a focus on soil salt composition and convection-diffusion theory. The results shed light on the mechanisms underlying soil water and salt dynamics in agricultural systems with shallow groundwater tables.
JOURNAL OF HYDROLOGY
(2022)
Article
Mathematics, Applied
Wenrui Li, Ming Ye, Qimin Zhang, Meyer-Baese Anke, Yan Li
Summary: This paper introduces a periodic averaging method for impulsive stochastic age-structured population models in a polluted environment. It demonstrates the uniqueness of the solutions and the mean-square convergence criteria of numerical solutions, and validates the efficiency of the method through a simulation example.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2022)
Article
Engineering, Mechanical
Jing Hu, Qimin Zhang, Anke Meyer-Baese, Ming Ye
Summary: In this paper, a stochastic model is proposed to describe the dynamics of substances related to Alzheimer's disease. The theoretical results are validated by numerical simulations.
NONLINEAR DYNAMICS
(2022)
Article
Environmental Sciences
Ahmed Elshall, Ming Ye, Sven A. Kranz, Julie Harrington, Xiaojuan Yang, Yongshan Wan, Mathew Maltrud
Summary: This article discusses the advantages and considerations of optimal model weighting in addressing specific application problems. It uses a case study of red tide prediction to illustrate the findings. The study highlights the importance of prescreening-based subset selection in optimal model weighting.
Article
Engineering, Civil
Yan Zhu, Tianxing Zhao, Wei Mao, Ming Ye, Xudong Han, Biao Jia, Jinzhong Yang
Summary: A modified UBMOD flow model was developed to accurately estimate soil water content and water table depth in arid agricultural areas with shallow water table depth. The model incorporates the impact of capillary rise and calculates water table depth using the water table depth fluctuation analysis. The results demonstrated its effectiveness and low computational cost, making it a valuable tool for hydrodynamic studies in areas with shallow water table depths.
JOURNAL OF HYDROLOGY
(2023)
Article
Engineering, Civil
Mengqin Wang, Yan Zhu, Wei Mao, Ming Ye, Jinzhong Yang
Summary: Current research on soil salt movement during the freeze and thaw period has focused mainly on total salt concentration, neglecting the phase change of multi-component salts. This study investigated the potential transport capability of soil water and salt ions in the frozen layer using chemical characteristics and solute convection-diffusion theory. Field experiments were conducted to measure changes in total soil water, soil salt, and its ion components. The results showed different migration directions and quantities of various salt ions due to concentration gradients and diffusion coefficients, with Na+, Cl-, and SO42- exhibiting larger potential convection and dispersion quantities than Ca2+, Mg2+, and HCO3-. This study provides a new perspective on soil salt movement in frozen agricultural areas with shallow groundwater tables.
JOURNAL OF HYDROLOGY
(2023)
Article
Mathematics, Applied
Yanyan Du, Ming Ye, Qimin Zhang
Summary: In this paper, a stochastic population-toxicant model with cross-diffusion is developed and the local boundedness of strong solutions is studied. The existence of a global martingale solution in a Hilbert space is obtained using the Galerkin approximation method, the tightness criterion, and the energy estimation.
APPLIED MATHEMATICS LETTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Jeffrey Wade, Christa Kelleher, Barret L. Kurylyk
Summary: This study developed a physically-based water temperature model coupled with the National Water Model (NWM) to assess the potential for water temperature prediction to be incorporated into the NWM at the continental scale. By evaluating different model configurations of increasing complexity, the study successfully simulated hourly water temperatures in the forested headwaters of H.J. Andrews Experimental Forest in Oregon, USA, providing a basis for integrating water temperature simulation with predictions from the NWM.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Shaun SH. Kim, Lucy A. Marshall, Justin D. Hughes, Lynn Seo, Julien Lerat, Ashish Sharma, Jai Vaze
Summary: A major challenge in hydrologic modelling is producing reliable uncertainty estimates outside of calibration periods. This research addresses the challenge by improving model structures and error models to more reliably estimate uncertainty. The combination of the RBS model and SPUE produces statistically reliable predictions and shows better matching performance in tests.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Juan Pedro Carbonell-Rivera, Javier Estornell, Luis Angel Ruiz, Pablo Crespo-Peremarch, Jaime Almonacid-Caballer
Summary: This study presents Class3Dp, a software for classifying vegetation species in colored point clouds. The software utilizes geometric, spectral, and neighborhood features along with machine learning methods to classify the point cloud, allowing for the recognition of species composition in an ecosystem.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhi Li, Daniel Caviedes-Voullieme, Ilhan Oezgen-Xian, Simin Jiang, Na Zheng
Summary: The optimal strategy for solving the Richards equation numerically depends on the specific problem, particularly when using GPUs. This study investigates the parallel performance of four numerical schemes on both CPUs and GPUs. The results show that the scaling of Richards solvers on GPUs is influenced by various factors. Compared to CPUs, parallel simulations on GPUs exhibit significant variation in scaling across different code sections, with poorly-scaled components potentially impacting overall performance. Nonetheless, using GPUs can greatly enhance computational speed, especially for large-scale problems.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Ludovic Cassan, Leo Pujol, Paul Lonca, Romain Guibert, Helene Roux, Olivier Mercier, Dominique Courret, Sylvain Richard, Pierre Horgue
Summary: Methods and algorithms for measuring stream surface velocities have been continuously developed over the past five years to adapt to specific flow typologies. The free software ANDROMEDE allows easy use and comparison of these methods with image processing capabilities designed for measurements in natural environments and with unmanned aerial vehicles. The validation of the integrated algorithms is presented on three case studies that represent the targeted applications: the study of currents for eco-hydraulics, the measurement of low water flows and the diagnosis of hydraulic structures. The field measurements are in very good agreement with the optical measurements and demonstrate the usefulness of the tool for rapid flow diagnosis for all the intended applications.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Mariia Kozlova, Robert J. Moss, Julian Scott Yeomans, Jef Caers
Summary: This paper introduces a framework for quantitative sensitivity analysis using the SimDec visualization method, and tests its effectiveness on decision-making problems. The framework captures critical information in the presence of heterogeneous effects, and enhances its practicality by introducing a formal definition and classification of heterogeneous effects.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Chad R. Palmer, Denis Valle, Edward V. Camp, Wendy-Lin Bartels, Martha C. Monroe
Summary: Simulation games have been used in natural resource management for education and communication purposes, but not for data collection. This research introduces a new design process which involves stakeholders and emphasizes usability, relevance, and credibility testing criteria. The result is a finalized simulation game for future research.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Tao Wang, Chenming Zhang, Ye Ma, Harald Hofmann, Congrui Li, Zicheng Zhao
Summary: This study used numerical modeling to investigate the formation process of iron curtains under different freshwater and seawater conditions. It was found that Fe(OH)3 accumulates on the freshwater side, while the precipitation is inhibited on the seaward side due to high H+ concentrations. These findings enhance our understanding of iron transformation and distribution in subterranean estuaries.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Grant Hutchings, James Gattiker, Braden Scherting, Rodman R. Linn
Summary: Computational models for understanding and predicting fire in wildland and managed lands are becoming increasingly impactful. This paper addresses the characterization and population of mid-story fuels, which are not easily observable through traditional survey or remote sensing. The authors present a methodology to populate the mid-story using a generative model for fuel placement, which can be calibrated based on limited observation datasets or expert guidance. The connection of terrestrial LiDAR as the observations used to calibrate the generative model is emphasized. Code for the methods in this paper is provided.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Saswata Nandi, Pratiman Patel, Sabyasachi Swain
Summary: IMDLIB is an open-source Python library that simplifies the retrieval and processing of gridded meteorological data from IMD, enhancing data accessibility and facilitating hydro-climatic research and analysis.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)
Article
Computer Science, Interdisciplinary Applications
Pengfei Wu, Jintao Liu, Meiyan Feng, Hu Liu
Summary: In this paper, a new flow distance algorithm called D infinity-TLI is proposed, which accurately estimates flow distance and width function using a two-segment-distance strategy and triangulation with linear interpolation method. The evaluation results show that D infinity-TLI outperforms existing algorithms and has a low mean absolute relative error.
ENVIRONMENTAL MODELLING & SOFTWARE
(2024)