Results 61 to 70 of about 767,107 (236)

Density estimation for time-dependent PDE with random input by a Legendre-based multi-element probabilistic collocation method

AIP Advances
This paper proposed a Legendre-based multi-element probabilistic collocation method for time-dependent stochastic differential equations, used for density estimation of unknown functions.
Hongling Xie
doaj   +1 more source

A Hybrid Fractional Chebyshev–Legendre Spectral Collocation Method for Hamilton–Jacobi–Bellman Equations

IEEE Access
Stochastic optimal control problems are commonly formulated as optimization problems constrained by stochastic dynamical systems, whose value functions satisfy Hamilton–Jacobi–Bellman (HJB) equations.
Alvian Alif Hidayatullah, Subchan Subchan, Sena Safarina, Tahiyatul Asfihani, R. Mohamad Atok, Irma Fitria, Andriyansah, Kasno Pamungkas   +7 more
doaj   +1 more source

Respiratory Organ‐on‐a‐Chip for Disease Modeling: From Architecture to Functional Integration

Advanced Healthcare Materials, EarlyView.
Respiratory organ‐on‐a‐chip (ROC) models capture key mechanical and cellular cues of the human respiratory system, enabling quantitative dissection of disease mechanisms. This review links ROC architectures to disease modeling, functional integration, and commercialization, and proposes a decision framework that aligns model complexity with mechanistic
Jinzhuo Hu, Yongjie Tang, Sidi Liu, Tao Xu, Qian Liu   +4 more
wiley   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Sensitivity analysis to compute advanced stochastic problems in uncertain and complex electromagnetic environments

Advanced Electromagnetics, 2012
This paper deals with the advanced integration of uncertainties in electromagnetic interferences (EMI) and electromagnetic compatibility (EMC) problems.
S. Lalléchère, B. Jannet, P. Bonnet, F. Paladian   +3 more
doaj   +1 more source

Topology‐Enriched Toughness Enhancement in Quasi‐Periodic Metastructures Featuring Tailorable Strong‐Weak Network

Advanced Science, EarlyView.
A quasi‐periodic Dart‐Kite (QDK) metastructure with a golden‐ratio‐constrained strong–weak bond network simultaneously enhances strength, toughness, and damage tolerance. Its distributed topology enables predictable, tailorable crack paths for precise fracture control and stable mechanics, demonstrating a high‐performance, controllable architecture ...
Tianyu Gao, Genda Wang, Jiabao Bai, Kai Liu   +3 more
wiley   +1 more source

A test of backward stochastic differential equations solver for solving semilinear parabolic differential equations in 1D and 2D

Partial Differential Equations in Applied Mathematics, 2022
Backward stochastic differential equation solver was first introduced by Han et al in 2017. A semilinear parabolic partial differential equation is converted into a stochastic differential equation, and then solved by the backward stochastic differential
Evan Davis, Guangming Yao, Elizabeth Javor, Kalani Rubasinghe, Luis Antonio Topete Galván   +4 more
doaj   +1 more source

Valuation of boundary-linked assets [PDF]

, 2004
This article studies the valuation of boundary-linked assets and their derivatives in continuous-time markets. Valuing boundary-linked assets requires the solution of a stochastic differential equation with boundary conditions, which, often, is not ...
Esteban-Bravo, Mercedes, Vidal-Sanz, Jose M.   +1 more
core   +1 more source

Boltzmann-type models with uncertain binary interactions

, 2017
In this paper we study binary interaction schemes with uncertain parameters for a general class of Boltzmann-type equations with applications in classical gas and aggregation dynamics.
Tosin, Andrea, Zanella, Mattia
core   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source