Results 121 to 130 of about 4,853,850 (241)

Regional Variance‐Based Sensitivity Analysis and a Study of Regional Equifinality

Risk Analysis, Volume 46, Issue 10, October 2026.
ABSTRACT Models in risk analysis frequently exhibit nonlinear behavior, thresholds, and regime shifts, which challenge conventional global sensitivity analysis (GSA) paradigms. Classical variance‐based methods quantify input importance over the entire output space, which can mask how these sensitivities vary across regions that are most relevant for ...
Justus Helo, Mariia Kozlova, Pamphile Roy, Julian Scott Yeomans   +3 more
wiley   +1 more source

Deciphering the Link Between Modeling Errors and the North Atlantic Surface Warming Pattern Projected by CMIP5 and CMIP6 Models

Geophysical Research Letters, Volume 53, Issue 18, 28 September 2026.
Abstract The North Atlantic Subpolar Gyre (NASG) has warmed much less than the global ocean over recent decades, thereby suggesting a human‐caused slowdown of the Atlantic Meridional Overturning Circulation (AMOC). This North Atlantic “warming hole” is also found in climate projections, yet with a model‐dependent timing, location and intensity. Here we
Hervé Douville, George Whittle, Pascal Terray   +2 more
wiley   +1 more source

Constrained optimization in simulation: a novel approach. [PDF]

This paper presents a novel heuristic for constrained optimization of random computer simulation models, in which one of the simulation outputs is selected as the objective to be minimized while the other outputs need to satisfy prespeci¯ed target values.
Van Nieuwenhuyse, Inneke, van Beers, W., Kleijnen, J.P.C.   +2 more
core   +2 more sources

A Review of Advances in Composite Materials, Structural Optimization, and Machine Learning for Wind Turbine Blades: Challenges and Future Perspectives

Polymer Composites, Volume 47, Issue 18, Page 16125-16154, 20 September 2026.
Overview of the holistic engineering lifecycle and core research pillars for wind turbine blades. ABSTRACT This paper reviews recent advancements across the lifecycle of wind turbine blades, focusing on three interconnected areas: advanced composites, structural optimization, and machine learning (ML) diagnostics. In materials, we highlight progress in
Kemal Hasirci, Denizhan Yavas, Alaeddin Burak Irez   +2 more
wiley   +1 more source

Enhancing Structural Reliability of Composite Adhesive Joints: An Integrated Experimental‐Numerical‐Machine Learning Framework for Material‐Geometric Co‐Optimization

Polymer Composites, Volume 47, Issue 18, Page 17023-17048, 20 September 2026.
An integrated experimental, numerical, and explainable machine learning framework for the material‐geometric co‐optimization and multi‐objective Pareto design of robust composite adhesive joints. ABSTRACT The reliability of composite adhesive joints is compromised by non‐linear dependencies between material properties and manufacturing uncertainties ...
Sajjad Karimi
wiley   +1 more source

Fixed Rank co-Kriging: a model for multivariate spatial prediction

This work develops a multivariate extension of the Fixed Rank Kriging (FRK) framework for spatial prediction in settings where multiple spatial processes may provide complementary information. The goal is to preserve the computational efficiency, the ability to operate without assuming stationarity over the domain, and the spatial support flexibility ...
Caringi, Gaia, Secchi, Piercesare
openaire   +2 more sources

Scalarizing cost-effective multi-objective optimization algorithms made possible with kriging

, 2008
Purpose – The purpose of this paper is threefold: to make explicitly clear the range of efficient multi-objective optimization algorithms which are available with kriging; to demonstrate a previously uninvestigated algorithm on an electromagnetic design ...
Hawe, G., Sykulski, J.K.
core  

Maximum‐Entropy‐Based Meshless Modeling of Surface‐Tension‐Driven Large Deformation

International Journal for Numerical Methods in Engineering, Volume 127, Issue 17, 15 September 2026.
ABSTRACT Soft material modeling is challenging due, among others, to the substantial structural changes these materials undergo. In this context, meshless methods offer a promising alternative to overcome the limitations of established mesh‐based approximations such as finite elements. However, they introduce new challenges.
Rodrigo Castillo‐Acuna, Nicholas Gianotti, Dennis M. Kochmann   +2 more
wiley   +1 more source

A singularity regression kriging for spatial prediction

GIScience & Remote Sensing
Accurate spatial prediction remains challenging in heterogeneous environments where environmental variables exhibit nonlinear, multiscale, and non-Gaussian characteristics.
Kai Ren, Yongze Song, Min Chen, Qiang Yu
doaj   +1 more source

Quantity and Quality Modeling of Groundwater by Conjugation of ANN and Co-Kriging Approaches

, 2012
Today, groundwater is a major source of supply for domestic and agricultural purposes; especially in arid and semi arid regions. More water is being consumed to meet of a society whose population increases steadily. Worldwide, irrigated land has increased from 50 million ha in 1900 to 267 million ha in 2000 (Cay and Uyan, 2009).
Vahid Nourani, Reza Goli
openaire   +2 more sources