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In this study, a method for predicting unsteady aerodynamic forces under different initial conditions using a limited number of samples based on transfer learning is proposed, aiming to avoid the need for large-scale high-fidelity…

Fluid Dynamics · Physics 2024-05-27 Wen Ji , Xueyuan Sun , Chunna Li , Xuyi Jia , Gang Wang , Chunlin Gong

Indentation tests are largely exploited in experiments to characterize the mechanical and fracture properties of the materials from the resulting crack patterns. This work proposes an efficient theoretical and computational framework, whose…

Materials Science · Physics 2023-06-26 Maria Rosaria Marulli , Jacopo Bonari , Josè Reinoso , Marco Paggi

A powerful and flexible approach to structured prediction consists in embedding the structured objects to be predicted into a feature space of possibly infinite dimension by means of output kernels, and then, solving a regression problem in…

Machine Learning · Statistics 2020-11-03 Luc Brogat-Motte , Alessandro Rudi , Céline Brouard , Juho Rousu , Florence d'Alché-Buc

In this paper, we present a 2D numerical model developed to simulate the dynamics of soft, deformable particles. To accommodate significant particle deformations, the particle surface is represented as a narrow shell composed of mass points…

Computational Physics · Physics 2025-04-01 Yohann Trivino , Vincent Richefeu , Farhang Radjai , Komlanvi Lampoh , Jean-Yves Delenne

Analytical expressions for the axial and transverse acoustic radiation forces as well as the radiation torque per length are derived for a rigid elliptical cylinder placed arbitrarily in the field of in plane progressive, quasi-standing or…

Classical Physics · Physics 2020-07-21 F. G. Mitri

The force transmitted from the front tires to the steering rack of a vehicle, called the rack force, plays an important role in the function of electric power steering (EPS) systems. Estimates of rack force can be used by EPS to attenuate…

Systems and Control · Electrical Eng. & Systems 2020-07-14 Akshay Bhardwaj , Daniel Slavin , John Walsh , James Freudenberg , R. Brent Gillespie

Cutting planes are a key ingredient to successfully solve mixed-integer linear programs. For specific problems, their strength is often theoretically assessed by showing that they are facet-defining for the corresponding mixed-integer hull.…

Discrete Mathematics · Computer Science 2020-11-13 Matthias Walter

During brittle crack propagation, a smooth crack front curve frequently becomes disjoint, generating a stepped crack and a material ligament that unites the newly formed crack fronts. These universal features fundamentally alter the…

Computational Engineering, Finance, and Science · Computer Science 2025-07-30 Xinyue Wei , John M. Kolinski

This paper investigates the problem of impact-time-control and proposes a learning-based computational guidance algorithm to solve this problem. The proposed guidance algorithm is developed based on a general prediction-correction concept:…

Machine Learning · Computer Science 2021-05-31 Zichao Liu , Jiang Wang , Shaoming He , Hyo-Sang Shin , Antonios Tsourdos

Neural networks have emerged as a powerful paradigm for tasks in high energy physics, yet their opaque training process renders them as a black box. In contrast, the traditional cut flow method offers simplicity and interpretability but…

Machine Learning · Computer Science 2025-12-18 Jing Li , Hao Sun

Cracks, the major vehicle for material failure, tend to accelerate to high velocities in brittle materials. In three-dimensions, cracks generically undergo a micro-branching instability at about 40% of their sonic limiting velocity. Recent…

Soft Condensed Matter · Physics 2017-12-06 Chih-Hung Chen , Eran Bouchbinder , Alain Karma

The etching process is one of the most important processes in semiconductor manufacturing. We have introduced the state-of-the-art deep learning model to predict the etching profiles. However, the significant problems violating physics have…

Machine Learning · Statistics 2021-04-07 Sanghoon Myung , Hyunjae Jang , Byungseon Choi , Jisu Ryu , Hyuk Kim , Sang Wuk Park , Changwook Jeong , Dae Sin Kim

A self-learning optimal control algorithm for episodic fixed-horizon manufacturing processes with time-discrete control actions is proposed and evaluated on a simulated deep drawing process. The control model is built during consecutive…

Systems and Control · Computer Science 2020-01-07 Johannes Dornheim , Norbert Link , Peter Gumbsch

In this paper, we describe an algorithm, based on the well-known Unscented Quaternion Estimator, to estimate external forces and torques acting on a quadrotor. This formulation uses a non-linear model for the quadrotor dynamics, naturally…

Robotics · Computer Science 2016-08-03 Christopher D. McKinnon , Angela P. Schoellig

The impact forces generated by the impact of a breaking wave are poorly understood. These impulsive hydrodynamic loads to a ship's hull are of short duration relative to ship motions and buoyant wave loads and often result in extremely high…

Combining experiments with artificial intelligence algorithms, we propose a new machine learning based approach to extract the cellular force distributions from the microscope images. The full process can be divided into three steps. First,…

The current landscape in time-series forecasting is dominated by Transformer-based models. Their high parameter count and corresponding demand in computational resources pose a challenge to real-world deployment, especially for commercial…

Machine Learning · Computer Science 2024-12-18 Nicholas Kiefer , Arvid Weyrauch , Muhammed Öz , Achim Streit , Markus Götz , Charlotte Debus

Ultimately, brittle fracture involves breaking atomic bonds. However, we still lack a clear picture of what happens in the highly deformed region around a moving crack tip. Consequently, we still cannot link nano to atomic-scale phenomena…

Materials Science · Physics 2024-07-22 Oriol Gavalda-Diaz , Max Emmanuel , Katharina Marquardt , Eduardo Saiz , Finn Giuliani

We use a model whose rules were inspired by population genetics, the random capability growth model, to describe the statistical details observed in experiments of fragmentation of brittle platelike objects, and in particular the existence…

Statistical Mechanics · Physics 2016-12-21 M. A. F. Gomes , Viviane M. de Oliveira

While there are a number of models that tackle the problem of calculating friction forces on the atomic level, providing a completely parameter-free approach remains a challenge. Here we present a quasi-static model to obtain an…

Mesoscale and Nanoscale Physics · Physics 2014-11-19 Michael Wolloch , Gregor Feldbauer , Peter Mohn , Josef Redinger , András Vernes