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In this paper, we derive multicontinuum poroelasticity models using the multicontinuum homogenization method. Poroelasticity models are widely used in many areas of science and engineering to describe coupled flow and mechanics processes in…

Numerical Analysis · Mathematics 2025-06-27 Dmitry Ammosov , Mohammed Al-Kobaisi , Yalchin Efendiev

Discovering the underlying relationships among variables from temporal observations has been a longstanding challenge in numerous scientific disciplines, including biology, finance, and climate science. The dynamics of such systems are…

Machine Learning · Computer Science 2024-05-07 Benjie Wang , Joel Jennings , Wenbo Gong

In this paper, we describe the unification and extension of multiple kinematic theories on the advection of colloidal particles through periodic obstacle lattices of arbitrary geometry and infinitesimally small obstacle size. We focus…

Computational Physics · Physics 2020-03-25 Arnaldo Rodriguez-Gonzalez , Jason P. Gleghorn , Brian J. Kirby

Microstructured particles are widely used in industries and state-of-the-art research and development. Diffusion of particles, particularly, controlled diffusion by a remotely applied field, has inspired novel applications ranging from…

Soft Condensed Matter · Physics 2022-09-30 Tianyu Yuan , Liping Liu , Jianxiang Wang

In this paper homogenization of a mathematical model for biomechanics of a plant tissue with randomly distributed cells is considered. Mechanical properties of a plant tissue are modelled by a strongly coupled system of…

Analysis of PDEs · Mathematics 2020-10-28 Andrey Piatnitski , Mariya Ptashnyk

Topology optimization offers optimal material layouts, enabling automation in the design of devices. Given the recent advances in computer technology and additive manufacturing, topology optimization is increasingly being used to design…

Fluid Dynamics · Physics 2021-07-28 T. Phatak , K. B. Nakshatrala

In this article, we extend the idea of stochastic dyadic Cantor set to weighted planar stochastic lattice that leads to a stochastic porous lattice. The process starts with an initiator which we choose to be a square of unit area for…

Statistical Mechanics · Physics 2022-01-25 Tushar Mitra , Md. Kamrul Hassan

Stochastic dual dynamic programming is a cutting plane type algorithm for multi-stage stochastic optimization originated about 30 years ago. In spite of its popularity in practice, there does not exist any analysis on the convergence rates…

Optimization and Control · Mathematics 2023-05-10 Guanghui Lan

Elastic metasurfaces offer precise control over elastic waves for applications such as vibration isolation, sensing, and imaging. However, achieving high-efficiency and scattering-free performance with complex functionalities remains a…

Applied Physics · Physics 2025-12-15 Chun Min Li , Wenjing Ye

Stochastic modeling has become a popular approach to quantify uncertainty in flows through heterogeneous porous media. The uncertainty in heterogeneous structure properties is often parameterized by a high-dimensional random variable. This…

Numerical Analysis · Mathematics 2013-10-22 Lijian Jiang , J. David Moulton , Jia Wei

Stochastic Spatio-Temporal processes are prevalent across domains ranging from modeling of plasma to the turbulence in fluids to the wave function of quantum systems. This letter studies a measure-theoretic description of such systems by…

Optimization and Control · Mathematics 2021-05-25 George I. Boutselis , Ethan N. Evans , Marcus A. Pereira , Evangelos A. Theodorou

A multiphysics data analytic platform is established for imaging poroelastic interfaces of finite permeability (e.g., hydraulic fractures) from elastic waveforms and/or acoustic pore pressure measurements. This is accomplished through…

Numerical Analysis · Mathematics 2022-03-02 Fatemeh Pourahmadian , Kevish Napal

We propose a mathematical methodology to derive a stochastic parameterization of bulk warm cloud micro-physics properties. Unlike previous bulk parameterizations, the stochastic parameterization does not assume any particular droplet size…

Atmospheric and Oceanic Physics · Physics 2016-06-08 David Collins , Boualem Khouider

Physical models of biological systems can become difficult to interpret when they have a large number of parameters. But the models themselves actually depend on (i.e. are sensitive to) only a subset of those parameters. Rigorously…

Biological Physics · Physics 2018-11-27 Chieh-Ting Hsu , Gary J. Brouhard , Paul François

The paper presents a new type of weakly nonlinear two-scale model of inflatable periodic poroelastic structures saturated by Newtonian fluids. The periodic microstructures incorporate fluid inclusions connected to the fluid channels by…

Analysis of PDEs · Mathematics 2025-08-28 Eduard Rohan , Vladimír Lukeš

We propose an efficient probabilistic method to solve a deterministic problem -- we present a randomized optimization approach that drastically reduces the enormous computational cost of optimizing designs under many load cases for both…

Optimization and Control · Mathematics 2017-10-11 Xiaojia Zhang , Eric de Sturler , Glaucio H. Paulino

Superhydrophobic surfaces with multi-scale topographies offer exceptionally high apparent water contact angles and low contact angle hysteresis by virtue of the small liquid{\textendash}solid contact fractions they enable. Natural…

Applied Physics · Physics 2019-12-16 Soochan Chung , Kristyn Kadala , Hayden Taylor

Significant progress has been made for assessing the influence of porosity on the performance metrics for cast components through various modeling techniques. However, a computationally efficient framework to account for porosity with…

Computational Engineering, Finance, and Science · Computer Science 2022-04-05 Shiguang Deng , Carl Soderhjelm , Diran Apelian , Krishnan Suresh

The paper discusses local porosity theory and its relation with other geometric characterization methods for porous media such as correlation functions and contact distributions. Special emphasis is placed on the charcterization of…

Disordered Systems and Neural Networks · Physics 2007-05-23 R. Hilfer

Stochastic approximation is a framework unifying many random iterative algorithms occurring in a diverse range of applications. The stability of the process is often difficult to verify in practical applications and the process may even be…

Probability · Mathematics 2014-03-10 Christophe Andrieu , Matti Vihola