Results 51 to 60 of about 7,268 (236)

Performance Evaluation of Generalized Polynomial Chaos [PDF]

, 2003
In this paper we review some applications of generalized polynomial chaos expansion for uncertainty quantification. The mathematical framework is presented and the convergence of the method is demonstrated for model problems. In particular, we solve the first-order and second-order ordinary differential equations with random parameters, and examine the
Dongbin Xiu, Didier Lucor, Chau-Hsing Su, George E. Karniadakis   +3 more
openaire   +1 more source

CFD modeling and sensitivity‐guided design of silicon filament CVD reactors

AIChE Journal, EarlyView.
Abstract Filament‐based chemical vapor deposition (CVD) for silicon (Si) coatings is often treated as an adaptation of planar deposition. But this overlooks fundamental shifts in transport phenomena and reaction kinetics. In filament CVD, the filament acts as a substrate, heat source, and flow disruptor simultaneously. In this work, we ask: What really
G. P. Gakis, G. Loachamín‐Suntaxi, I. G. Aviziotis, E. D. Koronaki, P. P. Filippatos, G. Chatzigiannakis, S. P. A. Bordas, D. Davazoglou, A. G. Boudouvis   +8 more
wiley   +1 more source

A Posteriori Validation of Generalized Polynomial Chaos Expansions

SIAM Journal on Applied Dynamical Systems, 2023
Generalized polynomial chaos expansions are a powerful tool to study differential equations with random coefficients, allowing in particular to efficiently approximate random invariant sets associated to such equations. In this work, we use ideas from validated numerics in order to obtain rigorous a posteriori error estimates together with existence ...
openaire   +3 more sources

A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws

Advanced Intelligent Discovery, EarlyView.
The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows, G. Zhang, S. Anand, Z. Chen, J. Lin, A. Desai, S. Martiniani, F. Caravelli   +7 more
wiley   +1 more source

Comparison of two approaches to compute magnetic field in problems with random domains [PDF]

, 2012
This paper is a postprint of a paper submitted to and accepted for publication in Science, Measurement & Technology, IET and is subject to Institution of Engineering and Technology Copyright.
MAC, Duy Hung, CLENET, Stephane, MIPO, Jean-Claude   +2 more
core   +1 more source

Small Sample-Based Fatigue Reliability Analysis Using Non-Intrusive Polynomial Chaos

IEEE Access, 2020
Based on small sample of fatigue test data, a new method to obtain p-S-N curve for fatigue reliability analysis using non-intrusive polynomial chaos (NIPC) is proposed to lower test cost.
Xiaoran Liu, Qin Sun
doaj   +1 more source

Uncertainty Propagation and Global Sensitivity Analysis of a Surface Acoustic Wave Gas Sensor Using Finite Elements and Sparse Polynomial Chaos Expansions

Vibration, 2023
The aim of this work is to perform an uncertainty propagation and global sensitivity analysis of a surface acoustic wave (SAW) gas sensor using finite elements and sparse polynomial chaos.
Mohamed Hamdaoui
doaj   +1 more source

Stable Neural Signal Recording Processed by Memristor‐Based Reservoir Computing System

Advanced Intelligent Systems, EarlyView.
This work introduces a memristor‐based reservoir computing (RC) system for real‐time, energy‐efficient processing of neural signals in brain‐machine interface (BMI). Combined with flexible mesh neural probes with tissue‐like flexibility and subcellular‐scale features that enable consistent, long‐term tracking of single‐cell neural activities, the ...
Soohyeon Kim, Yuting Wu, Finn Moore, Mingtao Hu, Xiaoyu Zhang, Sangmin Yoo, Eric Yeu‐Jer Lee, Hao Shen, Yichun He, Jia Liu, Wei D. Lu   +10 more
wiley   +1 more source

Best Practices in Developing a Workflow for Uncertainty Quantification for Modeling the Biodegradation of Mg‐Based Implants

Advanced Science
Computational models of electrochemical biodegradation of magnesium (Mg)‐based implants are uncertain. To quantify the model uncertainty, iterative evaluations are needed.
Tamadur AlBaraghtheh, Regine Willumeit‐Römer, Berit Zeller‐Plumhoff   +2 more
doaj   +1 more source

Time‐Delayed Spiking Reservoir Computing Enables Efficient Time Series Prediction

Advanced Intelligent Systems, EarlyView.
This study proposes time‐delayed spiking reservoir computing (TDSRC) for efficient time series prediction. By concatenating time‐lagged states, TDSRC constructs an expanded readout feature vector without altering internal reservoir dynamics. This approach enables highly accurate forecasting with significantly fewer neurons, providing a resource ...
Pin Jin, Ren Cao, Zhongxue Gan, Siyang Leng   +3 more
wiley   +1 more source