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Probabilistic-based combined high and low cycle fatigue assessment for turbine blades using a substructure-based kriging surrogate model

, 2020
Fatigue assessment for gas turbine blades under combined high and low fatigue cyclic loading is very difficult. In this paper, we propose a probabilistic approach based on a substructure-based kriging surrogate model (SKM) that embeds substructure ...
Haifeng Gao   +4 more
semanticscholar   +1 more source

Optimization of porous media flow field for proton exchange membrane fuel cell using a data-driven surrogate model

, 2020
Flow field design plays a key role in proton exchange membrane (PEM) fuel cells due to its decisive influence on reactant gas transfer, liquid water discharge, electron conductance, and heat transfer. Porous media flow field (e.g.
Guobin Zhang   +6 more
semanticscholar   +1 more source

Dynamic Surrogate Model Based Optimization for MPPT of Centralized Thermoelectric Generation Systems Under Heterogeneous Temperature Difference

IEEE transactions on energy conversion, 2020
A novel dynamic surrogate model based optimization (DSMO) for centralized thermoelectric generation (TEG) system affected by heterogeneous temperature difference (HeTD) is designed to achieve maximum power point tracking (MPPT) in this article.
Xiao Shun Zhang   +3 more
semanticscholar   +1 more source

Introduction to Surrogate Modeling and Surrogate-Based Optimization

2016
Surrogate-based optimization (SBO) is the main focus of this book. We provide a brief introduction to the subject in this chapter. In particular, we recall the SBO concept and the optimization flow, discuss the principles of surrogate modeling and typical approaches to construct surrogate models.
Slawomir Koziel, Leifur Leifsson
openaire   +1 more source

The Generalized Penalty-Function/Surrogate Model

Operations Research, 1973
This paper combines the monotonic-penalty-function and surrogate models into a general model called the penalty-function/surrogate model. It unifies and generalizes the central theorems of earlier papers, and provides some new theorems that can be specialized to the Lagrangian penalty-function model (GLM) or to linear surrogates.
openaire   +2 more sources

A comparative study on surrogate models for SAEAs

Optimization Letters, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mônica A. C. Valadão, Lucas S. Batista
openaire   +2 more sources

Aerodynamic shape optimization of gas turbines: a deep learning surrogate model approach

Structural And Multidisciplinary Optimization, 2023
Vahid Esfahanian   +5 more
semanticscholar   +1 more source

Surrogate Model-Based Space Mapping in Postfabrication Bandpass Filters’ Tuning

IEEE transactions on microwave theory and techniques, 2020
A procedure for diagnosis and tuning of fabricated bandpass filters is presented. A surrogate model consisting of a mapped coarse model at a basis point and a mapping of measured response with respect to the change of tuning elements from the basis point
Song Li   +3 more
semanticscholar   +1 more source

Surrogate Models for Antimalarials

1984
In recent years studies concerned with the mode of action of antimalarial drugs such as chloroquine have shifted from those concerned primarily with the effects on a particular enzyme or enzyme system to studies concerned with the consequences of the ability of chloroquine to act as a lysosomotropic agent.
S.-C. Chou   +3 more
openaire   +1 more source

Optimization of an explosive waste incinerator via an artificial neural network surrogate model

, 2020
In this study, the operating conditions for a novel method of explosive waste disposal have been optimized to minimize the formation of NOx emissions. Previous methods of disposal include rotary kilns but have disadvantages, especially associated with ...
Sunghyun Cho   +3 more
semanticscholar   +1 more source

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