Article
Engineering, Civil
Xu Gao, Tian-Chyi Jim Yeh, E-Chuan Yan, Yu-Li Wang, Yonghong Hao
Summary: This study discusses the relationship between hydraulic conductivity and hydraulic head through hydraulic measurements and conditional mean analysis methods such as Kriging and inverse modeling. By comparing the effects of different methods, the importance of conditional effective K in predicting heads is highlighted.
JOURNAL OF HYDROLOGY
(2021)
Article
Engineering, Mechanical
Zhibao Zheng, Hongzhe Dai, Yuyin Wang, Wei Wang
Summary: This paper introduces a new numerical scheme for simulating stochastic processes based on their specified marginal distribution functions and covariance functions. By generating stochastic samples to meet target marginal distribution functions and using an iterative algorithm to match the simulated covariance function to the target, the proposed method can accurately represent stochastic samples in series forms. The approach is applicable to non-stationary non-Gaussian stochastic processes and is demonstrated through three examples to be accurate and efficient.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Mathematics, Interdisciplinary Applications
Natalie Rauter
Summary: This study presents a modeling approach for short fiber-reinforced composites that considers microstructure information, generating random fields using correlation functions and conducting linear elastic numerical simulations at different scales. Experimental validation on the mesoscale shows good conformity with numerical simulations, and comparison with tensile tests suggests that three-dimensional information of microstructure probabilistic characteristics is required for accurate numerical modeling on the component level.
COMPUTATIONAL MECHANICS
(2021)
Article
Engineering, Mechanical
Hui Xu, Mircea D. Grigoriu
Summary: This study uses diffusion processes with linear drift and translations to fit wind pressure time series, and shows that these processes accurately characterize the extremes of the wind record.
PROBABILISTIC ENGINEERING MECHANICS
(2023)
Article
Engineering, Multidisciplinary
Yi Gao, Yang Jiao, Yongming Liu
Summary: This paper introduces a novel methodology for probabilistic material reliability analysis considering fine-scale microstructure stochasticity, addressing challenges of handling uncertainties and dimensionality for probabilistic solvers. By utilizing analytical and hierarchical uncertainty quantification methods and forming a probabilistic solver with adjoint first-order reliability method, the proposed approach demonstrates high efficiency in solving high-dimensional material reliability problems.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Statistics & Probability
Efstathios Paparoditis, Han Lin Shang
Summary: This paper proposes a bootstrap procedure for constructing prediction bands for a stationary functional time series. The procedure effectively models the dependence structure of the underlying process and estimates the prediction error distribution by generating functional replicates. It also introduces prediction bands based on a consistent estimation of the conditional distribution of the prediction error process.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
(2023)
Article
Computer Science, Interdisciplinary Applications
Petr Henys, Miroslav Vorechovsky, Michal Kuchar, Axel Heinemann, Jiri Kopal, Benjamin Ondruschka, Niels Hammer
Summary: This study investigated the variability in bone density at different locations using a random field model and found that average bone density can be well simulated with a Gaussian random field. The proposed model enhances computational biomechanical models and represents a step forward in in-silico medicine.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Geochemistry & Geophysics
Chuandong Jiang, Yunzhi Wang, Ruixin Miao, Qi Wang, Xinlei Shang, Baofeng Tian, Qingming Duan, Tingting Lin
Summary: Magnetic resonance tomography (MRT) is a powerful tool for groundwater detection, but existing inversion methods have limitations in handling high heterogeneity and uneven water content distribution. This study proposes a Bayesian inversion approach based on geostatistics to improve the accuracy of imaging results and quantify the uncertainty. The method uses prior geological data to generate stochastic realizations and employs a modified Markov chain Monte Carlo strategy to obtain posterior probability distributions. Comparing with the QT method, the Bayesian method shows superior performance in imaging subsurface aquifers with uneven water content distribution.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Engineering, Multidisciplinary
Christos Nastos, Dimitrios Zarouchas
Summary: The paper proposes a sophisticated numerical tool for stochastic finite element analysis in composite structures, which distributes stochastic mechanical properties along the domain of a composite structure. The tool utilizes Karhunen-Loeve expansion and Latin Hypercube Sampling methods to calculate stochastic stiffness matrices and conducts probabilistic analysis of different failure modes in composite structures.
COMPOSITES PART B-ENGINEERING
(2022)
Article
Construction & Building Technology
Ping Xiang, Wei Huang, Lizhong Jiang, Dagang Lu, Xiang Liu, Qing Zhang
Summary: This paper presents an analytical formula for predicting the rail deformation caused by concrete creep, which is then applied as an irregularity excitation to the train track-bridge coupled system. The Karhunen-Loève expansion method is adopted to represent the random track irregularity that considers creep deformation. The stochastic dynamic analysis method is used to analyze the dynamic responses of different train speeds and bridge creep deformations, showing high agreement with the Monte Carlo method.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Thermodynamics
Sufia Khatoon, Jyoti Phirani, Supreet Singh Bahga
Summary: We propose a fast Bayesian inference framework for solving inverse heat conduction problems. The framework combines polynomial chaos expansions and dimensionality reduction based on Karhunen-Loeve expansion to generate efficient surrogate models. We demonstrate the potential of this approach using three model problems for heat flux estimation.
APPLIED THERMAL ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Puneet Pasricha, Song-Ping Zhu, Xin-Jiang He
Summary: This paper examines the impact of liquidity on the pricing of European options and introduces a new pricing formula that considers market liquidity risk. The accuracy and convergence speed of the formula are demonstrated through numerical experiments. The formula's properties are investigated through comparisons with Monte-Carlo simulation results.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Mechanical
Romes A. Borges, Luiz F. F. Rodovalho, Thiago de P. Sales, Domingos A. Rade
Summary: This paper addresses the stochastic modeling and characterization of the influence of thermal stresses on the natural frequencies of thin rectangular plates subject to space-dependent temperature fluctuations modeled as stationary two-dimensional Gaussian random fields. The study utilizes a dynamic model based on the classical Kirchhoff plate theory and the Karhunen-Loeve expansion to estimate the statistics of random natural frequencies. Results reveal the significant impact of space-dependent temperature uncertainty on the vibration and buckling behavior of plates.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Mathematics, Applied
V. Bevia, J. Calatayud, J. -c. Cortes
Summary: This paper presents new probabilistic results for a class of random two-dimensional homogeneous heat equations with mixed homogeneous Dirichlet and Neumann boundary conditions. Pointwise convergent approximations for the main moments and density of the solution are constructed.
APPLIED MATHEMATICS LETTERS
(2023)
Article
Engineering, Mechanical
Ming-Na Tong, Yan-Gang Zhao, Zhao Zhao
Summary: A novel method combining Karhunen-Lo & egrave;ve expansion with L-moments-based Hermite polynomial model is proposed for simulating strongly non-Gaussian and non stationary processes. The method effectively transforms non-Gaussian processes into Gaussian processes and addresses incompatibilities that may occur in strongly non-Gaussian processes.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Environmental Sciences
Nandita Gaur, Binayak P. Mohanty
WATER RESOURCES RESEARCH
(2019)
Article
Geochemistry & Geophysics
Gurjeet Singh, Narendra N. Das, Rabindra K. Panda, Andreas Colliander, Thomas J. Jackson, Binayak P. Mohanty, Dara Entekhabi, Simon H. Yueh
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2019)
Article
Environmental Sciences
Zhenlei Yang, Binayak P. Mohanty, Yalchin Efendiev, Zhuping Sheng
WATER RESOURCES RESEARCH
(2019)
Article
Environmental Sciences
Dhruva Kathuria, Binayak P. Mohanty, Matthias Katzfuss
WATER RESOURCES RESEARCH
(2019)
Article
Geochemistry & Geophysics
Maheshwari Neelam, Andreas Colliander, Binayak P. Mohanty, Michael H. Cosh, Sidharth Misra, Thomas J. Jackson
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2020)
Article
Environmental Sciences
M. Hong, B. P. Mohanty, Z. Sheng
WATER RESOURCES RESEARCH
(2020)
Article
Environmental Sciences
Vinit Sehgal, Nandita Gaur, Binayak P. Mohanty
Summary: Understanding the seasonal patterns of global surface soil moisture drydowns is crucial for various applications in hydrology, meteorology, agriculture, and the environment. This study developed a data-driven approach to parameterize the drydown pathways at each SMAP footprint, revealing significant interseasonal variability and the influence of soil texture and climate on soil water retention and drydown parameters. This research represents a significant step towards scale-specific, effective soil hydrologic parameterization for diverse applications.
WATER RESOURCES RESEARCH
(2021)
Article
Geosciences, Multidisciplinary
Zhenlei Yang, Binayak P. Mohanty, Xin Tong, Xingxing Kuang, Ling Li
Summary: The study aimed to predict relative air permeability in disturbed soils by combining traditional and fractal water retention curves with permeability equations. It was found that for disturbed soils, air permeability is mainly controlled by pore tortuosity-connectivity rather than pore size distribution implied from the water retention curves. Choosing an appropriate permeability equation is crucial for accurately predicting relative air permeability.
GEOPHYSICAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Suraj Jena, Binayak P. Mohanty, Rabindra K. Panda, Meenu Ramadas
Summary: Machine learning algorithms were used to develop a robust model for predicting saturated hydraulic conductivity (Ks) based on eight selected predictors, achieving accurate and cost-effective estimation in this study. The model outperformed existing PTFs both within and outside the study region, marking it as a superior and generalizable PTF for Ks estimation in various parts of the world.
WATER RESOURCES RESEARCH
(2021)
Article
Environmental Sciences
Vinit Sehgal, Nandita Gaur, Binayak P. Mohanty
Summary: Flash droughts are characterized by sudden onset and rapid intensification, and can be assessed in near-real-time using global surface soil moisture data from the SMAP satellite. A new method involving the development of the Flash Drought Stress Index (FDSI) using SMS and RRD parameters shows high skill in forecasting vegetation health.
WATER RESOURCES RESEARCH
(2021)
Article
Water Resources
Suraj Jena, Rabindra Kumar Panda, Meenu Ramadas, Binayak P. Mohanty, Alok Kumar Samantaray, Susanta Kishore Pattanaik
Summary: This study evaluated the temporal variability in depth to groundwater in the State of Odisha, India from 1995 to 2015, identifying both rising and declining trends. Land use/ land cover was found to be the dominant factor influencing groundwater depth variability, highlighting the need for impact assessment studies in locations with significant trends. This approach can greatly contribute to planning and management for achieving groundwater sustainability in data-scarce regions.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2021)
Article
Engineering, Civil
Yongchul Shin, Binayak P. Mohanty, Jonggun Kim, Taehwa Lee
Summary: We developed a multi-model approach to simulate soil moisture dynamics, taking into account uncertainties in both physical and optimization model structures. The approach performed well in testing transferability under different weather conditions, but overfitted parameters from the optimization model structures can reduce transferability. Additionally, estimated soil hydraulic properties during dry years may not accurately represent wetness conditions during wet years.
JOURNAL OF HYDROLOGY
(2023)
Article
Agronomy
Deanroy Mbabazi, Binayak P. Mohanty, Nandita Gaur
Summary: This study developed a new algorithm to generate high spatio-temporal (daily 30 m resolution) evapotranspiration (ET) by fusing eddy covariance and Landsat ET data within large agricultural fields. The ETFUSE algorithm was found to be statistically similar to standardized Penman-Monteith ET (ETPM) and spline interpolated alfalfa reference fraction ET (ETRF) for various land covers and growing seasons.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Filippo Miele, Paolo Benettin, Simiao Wang, Ivan Retti, Mitra Asadollahi, Manon Frutschi, Binayak Mohanty, Rizlan Bernier-Latmani, Andrea Rinaldo
Summary: Redox cycles measured through soil redox potential are associated with soil microbial activity. This study investigates the interplay between soil moisture and redox potential dynamics by manipulating hydrologic and geochemical conditions in soil column installations. The findings highlight the importance of understanding joint hydrologic flow/transport and redox processes in predicting redox potential changes and the minimum amount of biogeochemistry needed for characterizing electron donors/acceptors responsible for redox patterns. The study's results improve our understanding of how and where activity hotspots develop within soil microbial communities.
WATER RESOURCES RESEARCH
(2023)
Article
Meteorology & Atmospheric Sciences
M. Hong, B. P. Mohanty
Summary: This study aims to present a novel hydrologic structure that enables the application of hydraulic groundwater theory to large-scale hydrologic predictions. By integrating the BE3S representation scheme into the National Water Model and applying it to three major basins in Texas, noticeable improvements in streamflow predictions were observed for aquifers with higher nonlinearities. This demonstrates the enhancement of subsurface hydrology and the applicability of the Boussinesq theory-based depiction of the stream-hillslope continuum.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2023)
