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Technologies and lifestyles have been increasingly geared toward consumerism in recent years. Accordingly, it is both the price and the delivery time that matter most to the ultimate customers of commercial enterprises. Consequently, the…

Systems and Control · Electrical Eng. & Systems 2022-09-02 Sina Aghakhani , Mohammad Sadra Rajabi

In this paper a problem of numerical simulation of hydraulic fractures is considered. An efficient algorithm of solution is proposed for the plain strain model of hydraulic fracturing. The algorithm utilizes a FEM based subroutine to…

Mathematical Physics · Physics 2022-05-26 Michal Wrobel , Panos Papanastasiou , Daniel Peck

Simulating 2D flow in fractured crystalline rock requires 2D stochastic discrete-fracture matrix (DFM) models. To obtain the simulation statistics of interest at an affordable computational cost, we aim to use the multilevel Monte Carlo…

Analysis of PDEs · Mathematics 2024-04-24 Martin Špetlík , Jan Březina , Eric Laloy

Traditional materials discovery approaches - relying primarily on laborious experiments - have controlled the pace of technology. Instead, computational approaches offer an accelerated path: high-throughput exploration and characterization…

Materials Science · Physics 2018-11-23 Corey Oses

Business environments characterized by intermittent demand, high variability, and multi-step planning require model selection procedures aligned with future operational horizons rather than static test-horizon evaluation. Because no…

Machine Learning · Computer Science 2026-04-23 Adolfo González , Víctor Parada

The aim of this work was to predict the probability of the spread of rock formations with hydrocarbon-collecting properties in the studied coastal area using a stack of machine learning algorithms and data augmentation and modification…

Geophysics · Physics 2023-01-10 Dmitry Ivlev

Ensuring consistent product quality in modern manufacturing is crucial, particularly in safety-critical applications. Conventional quality control approaches, reliant on manually defined thresholds and features, lack adaptability to the…

Machine Learning · Computer Science 2026-04-09 Bernd Hofmann , Patrick Bruendl , Huong Giang Nguyen , Joerg Franke

Data-driven flood forecasting methods are useful, especially for the rivers that lack hydrological information to build physical models. Although these former methods can forecast river stages using only past water levels and rainfall data,…

Geophysics · Physics 2021-04-07 Shunya Okuno , Koji Ikeuchi , Kazuyuki Aihara

Shear dilation based hydraulic stimulations enable exploitation of geothermal energy from reservoirs with inadequate initial permeability. While contributing to enhancing the reservoir's permeability, hydraulic stimulation processes may…

Geophysics · Physics 2018-08-01 Eren Ucar , Inga Berre , Eirik Keilegavlen

Manufacturability assessment is a critical step in bridging the persistent gap between design and production. While artificial intelligence (AI) has been widely applied to this task, most existing frameworks rely on geometry-driven methods…

Artificial Intelligence · Computer Science 2026-01-13 Masoud Deylami , Negar Izadipour , Adel Alaeddini

This dataset contains 10,000 fluid flow and heat transfer simulations in U-bend shapes. Each of them is described by 28 design parameters, which are processed with the help of Computational Fluid Dynamics methods. The dataset provides a…

Fluid Dynamics · Physics 2023-08-31 Jens Decke , Olaf Wünsch , Bernhard Sick

The use of machine learning algorithms to predict behaviors of complex systems is booming. However, the key to an effective use of machine learning tools in multi-physics problems, including combustion, is to couple them to physical and…

Various engineering systems such as naval and aerial vehicles, offshore structures, and mechanical components of motorized systems, are exposed to fatigue failures due to stochastic loadings. Methods for early failure prediction are…

Machine Learning · Computer Science 2021-04-06 Maor Farid

In this work we propose a novel algorithm for multiple-event localization for Hydraulic Fracture Monitoring (HFM) through the exploitation of the sparsity of the observed seismic signal when represented in a basis consisting of space time…

Geophysics · Physics 2013-05-13 Gregory Ely , Shuchin Aeron

Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of machinery. Majority of these machines comprise rotating components and are called rotating machines. The engineers' top priority is to maintain…

Artificial Intelligence · Computer Science 2022-06-29 Shreyas Gawde , Shruti Patil , Satish Kumar , Pooja Kamat , Ketan Kotecha , Ajith Abraham

The rapid growth of artificial intelligence (AI)-driven data centers is reshaping electricity demand patterns. This is achieved by introducing fast, multi-gigawatt load ramps that challenge the stability and resilience of modern power…

Systems and Control · Electrical Eng. & Systems 2026-01-22 Sharaf K. Magableh , Caisheng Wang , Oraib Dawaghreh

The rapidly evolving fields of Machine Learning (ML) and Artificial Intelligence have witnessed the emergence of platforms like Hugging Face (HF) as central hubs for model development and sharing. This experience report synthesizes insights…

Software Engineering · Computer Science 2024-02-13 Joel Castaño , Silverio Martínez-Fernández , Xavier Franch

Experimentally [1-38] and computationally [39-50] validated machine learning (ML) articles are sorted based on the size of the training data: 1-100, 101-10000, and 10000+ in a comprehensive set summarizing legacy and recent advances in the…

Materials Science · Physics 2023-03-20 Sterling G. Baird , Marianne Liu , Hasan M. Sayeed , Taylor D. Sparks

Human-robot collaborative manufacturing, a core aspect of Industry 5.0, emphasizes ergonomics to enhance worker well-being. This paper addresses the dynamic human-robot task planning and allocation (HRTPA) problem, which involves…

Artificial Intelligence · Computer Science 2026-04-17 Jintao Xue , Xiao Li , Nianmin Zhang

The computational complexity of calculating phase diagrams for multi-parameter models significantly limits the ability to select parameters that correspond to experimental data. This work presents a machine learning method for solving the…

Computational Physics · Physics 2026-05-01 V. A. Ulitko , D. N. Yasinskaya , S. A. Bezzubin , A. A. Koshelev , Y. D. Panov
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