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We apply the Bayesian model selection method (based on the Bayes factor) to optimize $\sqrt{s_\mathrm{NN}}$-dependence in the phenomenological parameters of the (3+1)-dimensional hybrid framework for describing relativistic heavy-ion…

Nuclear Theory · Physics 2026-03-02 Syed Afrid Jahan , Hendrik Roch , Chun Shen

This paper introduces a novel Bayesian approach to detect changes in the variance of a Gaussian sequence model, focusing on quantifying the uncertainty in the change point locations and providing a scalable algorithm for inference. Such a…

Methodology · Statistics 2025-03-04 Lorenzo Cappello , Oscar Hernan Madrid Padilla

The advances in variational inference are providing promising paths in Bayesian estimation problems. These advances make variational phylogenetic inference an alternative approach to Markov Chain Monte Carlo methods for approximating the…

Populations and Evolution · Quantitative Biology 2023-09-12 Amine M. Remita , Golrokh Vitae , Abdoulaye Baniré Diallo

Plasma-terminating disruptions in future fusion reactors may result in conversion of the initial current to a relativistic runaway electron beam. Validated predictive tools are required to optimize the scenarios and mitigation actuators to…

Plasma Physics · Physics 2022-08-04 Aaro Järvinen , Tünde Fülöp , Eero Hirvijoki , Mathias Hoppe , Adam Kit , Jan Åström

The variational approach to fracture is effective for simulating the nucleation and propagation of complex crack patterns, but is computationally demanding. The model is a strongly nonlinear non-convex variational inequality that demands…

Numerical Analysis · Mathematics 2016-05-18 Patrick E. Farrell , Corrado Maurini

Bayesian predictive inference propagates parameter uncertainty to quantities of interest through the posterior-predictive distribution. In practice, this is typically performed using a two-stage procedure: first approximating the posterior…

Machine Learning · Statistics 2026-05-06 Nan Feng , Xun Huan

Fatigue fracture in ductile materials, e. g. metals, is caused by cyclic plasticity. Especially regarding the high numbers of load cycles, plastic material models resolving the full loading path are computationally very demanding. Herein, a…

Materials Science · Physics 2019-10-24 Martha Seiler , Thomas Linse , Peter Hantschke , Markus Kästner

We have developed a simulation technique that uses non-linear finite element analysis and elastic fracture mechanics to compute physically plausible motion for three-dimensional, solid objects as they break, crack, or tear. When these…

Graphics · Computer Science 2023-03-21 James F. O'Brien , Jessica K. Hodgins

Structural equation models are commonly used to capture the relationship between sets of observed and unobservable variables. Traditionally these models are fitted using frequentist approaches but recently researchers and practitioners have…

Methodology · Statistics 2023-02-22 Khue-Dung Dang , Luca Maestrini

We present a new method to invert variable stress changes of fractures from InSAR ground displacements. Fractures can be either faults or magma intrusions, embeded in a 3D heterogeneous crust with prominent topographies. The method is based…

Geophysics · Physics 2022-12-07 Farshid Dabaghi , Oliver Bodart , Valérie Cayol

Fracture mechanics is crucial for many fields of engineering, as precisely predicting failure of structures and parts is required for efficient designs. The simulation of failure processes is, from a mechanical and a numerical point of…

Materials Science · Physics 2022-06-15 Sebastian Pech , Markus Lukacevic , Josef Füssl

The modeling of coupled fluid transport and deformation in a porous medium is essential to predict the various geomechanical process such as CO2 sequestration, hydraulic fracturing, and so on. Current applications of interest, for instance,…

Analysis of PDEs · Mathematics 2022-01-03 Mina Karimi , Mehrdad Massoudi , Noel Walkington , Matteo Pozzi , Kaushik Dayal

Multiscale and multiphysics problems need novel numerical methods in order for them to be solved correctly and predictively. To that end, we develop a wavelet based technique to solve a coupled system of nonlinear partial differential…

Numerical Analysis · Mathematics 2023-03-22 Cale Harnish , Luke Dalessandro , Karel Matous , Daniel Livescu

This study discusses acoustic dissipation, which contributes to inaccuracies in impedance tube measurements. To improve the accuracy of these measurements, this paper introduces a transfer function model that integrates diverse dissipation…

Classical Physics · Physics 2024-03-27 Ziqi Chen , Ning Xiang

Despite its critical role in the study of earthquake processes, numerical simulation of the entire stages of fault rupture remains a formidable task. The main challenges in simulating a fault rupture process include complex evolution of…

Geophysics · Physics 2023-08-22 Fan Fei , Md Shumon Mia , Ahmed E. Elbanna , Jinhyun Choo

Accurate prediction of fragmentation cross sections is essential for rare-isotope beam production, planning new-isotope searches, and designing experiments to study the most exotic regions of the nuclear chart. However, existing reaction…

Nuclear Experiment · Physics 2026-03-12 O. B. Tarasov

We investigate dynamic crack propagation and fragmentation with the phase-field fracture approach. The method was chosen for its ability to yield crack paths that are independent of the underlying mesh, thanks to the damage regularization…

Computational Physics · Physics 2025-12-23 Shad Durussel , Gergely Molnár , Jean-François Molinari

Due to its computational robustness and versatility, the phase field fracture model has become the preferred tool for predicting a wide range of cracking phenomena. However, in its conventional form, its intrinsic tension-compression…

Materials Science · Physics 2022-08-23 Y. Navidtehrani , C. Betegón , E. Martínez-Pañeda

In the phase-field modeling of brittle fracture, anisotropic constitutive assumptions for the degradation of stored elastic energy due to fracture are crucial to preventing cracking in compression and obtaining physically sound numerical…

Numerical Analysis · Mathematics 2018-05-22 Fei Zhang , Weizhang Huang , Xianping Li , Shicheng Zhang

Data driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning…

Machine Learning · Computer Science 2025-10-01 Erfan Hamdi , Emma Lejeune
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