Results 51 to 60 of about 31,846 (223)

Magnetometric resistivity tomography using chaos polynomial expansion [PDF]

Geophysical Journal International, 2020
SUMMARY We present an inversion algorithm to reconstruct the spatial distribution of the electrical conductivity from the analysis of magnetometric resistivity (MMR) data acquired at the ground surface. We first review the theoretical background of MMR connecting the generation of a magnetic field in response to the injection of a low ...
Vu, M, Jardani, Abderrahim, Revil, A, Jessop, M   +3 more
openaire   +3 more sources

Structural reliability analysis by a Bayesian sparse polynomial chaos expansion

, 2021
Accurate computation of failure probability considering uncertain input parameters is very challenging within limited computational cost. An efficient surrogate model, referred to here as sparse variational Bayesian inference based polynomial chaos ...
B. Bhattacharyya
semanticscholar   +1 more source

Robust Design of Suspension System with Polynomial Chaos Expansion and Machine Learning

Наука и техника, 2020
During the early development of a new vehicle project, the uncertainty of parameters should be taken into consideration because the design may be perturbed due to real components’ complexity and manufacturing tolerances. Thus, the numerical validation of
H. Gao, L. Jézéque, E. Cabrol, B. Vitry   +3 more
doaj   +1 more source

On polynomial chaos expansion via gradient-enhanced ℓ1-minimization [PDF]

Journal of Computational Physics, 2016
Gradient-enhanced Uncertainty Quantification (UQ) has received recent attention, in which the derivatives of a Quantity of Interest (QoI) with respect to the uncertain parameters are utilized to improve the surrogate approximation. Polynomial chaos expansions (PCEs) are often employed in UQ, and when the QoI can be represented by a sparse PCE, $\ell_1$-
Peng, Ji, Hampton, Jerrad, Doostan, Alireza   +2 more
openaire   +3 more sources

The Role of Chemistry Across Disciplines From Humanities to Life Sciences in Understanding Complexity and Emergence

Angewandte Chemie International Edition, EarlyView.
This study explores the origins of life by linking prebiotic chemistry, the emergence of information‐carrying molecules such as RNA and proteins, and philosophical questions about consciousness. The study emphasizes the role of molecular evolution in the Central Dogma and provides insights into the chemical origins of biology and the basis of life's ...
Harald Schwalbe, Josef Wachtveitl, Alexander Heckel, Florian Buhr, Sabrina Toews, Thomas M. Schimmer   +5 more
wiley   +1 more source

Impact of Uncertain Parameters on Navier–Stokes Equations With Heat Transfer via Polynomial Chaos Expansion

International Journal for Numerical Methods in Fluids, EarlyView.
This study investigates the impact of uncertain parameters on Navier–Stokes equations coupled with heat transfer using the Intrusive Polynomial Chaos Method (IPCM). Sensitivity equations are formulated for key input parameters, such as viscosity and thermal diffusivity, and solved numerically using the Finite Element‐Volume method.
N. Nouaime, B. Després, M. A. Puscas, C. Fiorini   +3 more
wiley   +1 more source

Embracing Complexity in HRM Research: A Call for System and Process Perspectives

Human Resource Management, EarlyView.
ABSTRACT Human resource management (HRM) is inherently complex. It involves systems of principles, practices, and activities operating at individual, group, organizational, and macro levels, which are interlinked through complex processes. Yet, empirical research has not kept pace with this conceptual richness.
Rebecca Hewett, Madleen Meier‐Barthold
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

Systematic Parameter Selection for Short Fiber Polymer Composite Direct Fiber Simulation

Polymer Composites, EarlyView.
Interactions of individually simulated fibers are systematically calibrated such that their orientation history agrees with the results from analytical orientation models. ABSTRACT The orientation of fibers in short discontinuous fiber reinforced polymer composites is a critical factor in determining final mechanical and thermal properties.
Jason B. Pierce, Douglas E. Smith
wiley   +1 more source

Recursive Feasibility of Nonlinear Stochastic Model Predictive Control With Gaussian Process Dynamics

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf, Andreas Völz, Knut Graichen   +2 more
wiley   +1 more source