Article
Engineering, Marine
Shi-Ming Chen
Summary: Physical forcings play a role in water exchange in coral reef atolls, with characteristics influenced by atoll morphology and local atmospheric and hydrographic conditions. A study on Dongsha atoll investigated the impact of tides, wind, and waves on water exchange, finding that wind and waves have a stronger effect than tides. Wind and wave directions significantly affect the spatial distribution of residence time and age, suggesting significant seasonal variability in hydrodynamic processes. This study highlights different circulation patterns in atoll systems under calm weather and strong wind/wave influences.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Civil
Yuqing Qiu, Hongli Ji, Chongcong Tao, Chao Zhang, Jinhao Qiu
Summary: An adaptive parameter optimization algorithm (APOA) is proposed for simultaneous force history and location identification, aiming to improve efficiency in modeling whole plate structures under sparse calibration conditions. The effectiveness of the method is verified through numerical simulations and experimental impact tests, showing good performance in force locating stability, time history estimation accuracy, and adaptability under sparse calibration.
ENGINEERING STRUCTURES
(2023)
Article
Computer Science, Theory & Methods
Evelyne Hubert, Michael F. Singer
Summary: Sparse interpolation involves recovering a function as a linear combination of basis functions from a limited number of evaluations, with applications in multivariate functions and various types of basis functions. In addition to studied cases like the monomial basis and exponential functions, generalized multivariate Chebyshev polynomials defined by root systems have connections to topics like Fourier analysis and Lie algebras. A deterministic algorithm has been proposed to recover a function as a linear combination of a limited number of such polynomials.
FOUNDATIONS OF COMPUTATIONAL MATHEMATICS
(2022)
Article
Computer Science, Software Engineering
Tanaboon Tongbuasirilai, Jonas Unger, Christine Guillemot, Ehsan Miandji
Summary: This paper presents a novel sparse non-parametric BRDF model derived using a machine learning approach. The model represents the space of possible BRDFs by training dictionaries under a sparsity constraint, resulting in high-quality representations with minimal storage requirements and an inherent clustering of the BDRF-space. The model can be reused for a wide variety of measured BRDFs and is flexible in incorporating new unobserved data sets, parameterizations, and transformations. Additionally, the model allows for smooth interpolation of any two or more BRDFs in the coefficient space.
ACM TRANSACTIONS ON GRAPHICS
(2022)
Article
Geosciences, Multidisciplinary
Christo Rautenbach, Julia C. Mullarney, Karin R. Bryan
Summary: Effective and accurate ocean and coastal wave predictions are crucial for engineering, safety, and recreational purposes. The study found that a computational node configuration of six threads/cores produced the most effective computational set-up for 1-week wave hindcasts. Further research is needed to understand the relationship between computational domain size and optimal parallel computational threads/cores for efficient simulations.
GEOSCIENTIFIC MODEL DEVELOPMENT
(2021)
Article
Mathematics, Applied
Thomas C. H. Lux, Layne T. Watson, Tyler H. Chang, Yili Hong, Kirk Cameron
Summary: Advancements in data availability have led to more accurate models in all scientific fields. Interpolation has advantages in handling high-dimensional approximation problems, as demonstrated in this paper with a novel and insightful error bound for linear interpolation.
NUMERICAL ALGORITHMS
(2021)
Article
Thermodynamics
M. Sontheimer, A. Kronenburg, O. T. Stein
Summary: A sparse-Lagrangian particle implementation of the MMC-LES model for two-phase flows is developed with the aid of CP-DNS. The model accurately reproduces mean and rms of mixture fraction, but temperature may be significantly underpredicted. Minimization based on stochastic particle temperature improves agreement between the MMC-LES model and CP-DNS.
PROCEEDINGS OF THE COMBUSTION INSTITUTE
(2021)
Article
Computer Science, Theory & Methods
Tian Xia, Gelin Fu, Chenyang Li, Zhongpei Luo, Lucheng Zhang, Ruiyang Chen, Wenzhe Zhao, Nanning Zheng, Pengju Ren
Summary: Sparse Matrix-Vector Multiplication (SpMV) is a challenging task for modern CPUs due to its high sparsity and irregularity. Researchers try to improve SpMV performance, but the interactions and restrictions among software and hardware factors in complex CPU microarchitectures make optimization difficult. This paper thoroughly studies SpMV execution on modern CPUs and proposes a comprehensive performance model. The model accurately captures critical factors and relationships, enabling the optimization of SpMV kernels. Experimental results demonstrate the effectiveness of the proposed model, with the optimized SpMV kernel outperforming state-of-the-art approaches.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
S. Akhavan, F. Baghestani, P. Kazemi, A. Karami, H. Soltanian-Zadeh
Summary: The goal of dictionary learning algorithms is to factorize the matrix of training signals into a dictionary matrix and a sparse coefficient matrix. However, in some signals, there is a hidden Markov model dependency. This study proposes an approach to improve the performance of dictionary learning algorithms in such scenarios.
DIGITAL SIGNAL PROCESSING
(2022)
Article
Computer Science, Interdisciplinary Applications
Sanae Elmisaoui, Saad Benjelloun, Moulay Abdellah Chkifa, Abderrazak M. Latifi
Summary: This paper develops accurate surrogate models for first-principles models in phosphate ore dissolution. The surrogate models are based on sparse multivariate polynomial interpolation, aiming to reduce computational time while preserving monotonicity and positivity. The models approximate temporal profiles of concentrations, particle size, and liquid film thickness. Inputs include particle size distribution, initial acid concentration, and hydrodynamic conditions. Simulations in MATLAB demonstrate high efficiency, both in terms of accuracy and computation time, highlighting the strength of the surrogate modeling methodology.
COMPUTERS & CHEMICAL ENGINEERING
(2023)
Article
Mathematics, Applied
Karine Fouchet
Summary: We compute an asymptotic formula for the supremum of the resolvent norm over a given condition, and prove that it is achieved on the unit circle by an analytic Toeplitz matrix.
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Hao Sun, Junting Chen
Summary: This paper proposes a method that combines interpolation and matrix completion to reconstruct a propagation map from sparse measurements. The method enriches matrix observations and utilizes the statistics of the interpolation error, resulting in improved propagation map reconstruction performance.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Geochemistry & Geophysics
Xiao Niu, Lihua Fu, Wanjuan Zhang, Yanyan Li
Summary: In the context of seismic data interpolation, utilizing sparse and low-rank priors or constraints is crucial for achieving a better fit and reducing multiple solutions. Considering additional information leads to more accurate reconstructions. Our proposed joint sparse and low-rank priors (JSLRP) model outperforms classic low-rank methods on synthetic and field 3-D seismic data.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Lionel Renault, Patrick Marchesiello
Summary: Ocean tides can drag the atmosphere and cause tidal winds, which have implications for climate and energy in many shelf regions.
COMMUNICATIONS EARTH & ENVIRONMENT
(2022)
Article
Engineering, Multidisciplinary
Mohammad Hossein Naderi, Hessam Babaee
Summary: Stochastic reduced-order modeling based on time-dependent bases has been successful in capturing low-dimensional manifold from stochastic partial differential equations (SPDEs). A new adaptive sparse interpolation algorithm is proposed to enable stochastic ROMs to achieve computational efficiency for nonlinear SPDEs. The algorithm constructs a low-rank approximation for the SPDE using the DEIM method, and it does not require any offline computation, allowing it to adapt to transient changes on-the-fly. The algorithm achieves computational speedup by adaptive sampling of the state and random spaces, resulting in significant reduction in computational cost for various test cases.
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
(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)
