Optimal design of computer experiments for surrogate models with dimensionless variables
Sign Up to like & getrecommendations! Published in 2017 at "Structural and Multidisciplinary Optimization"
DOI: 10.1007/s00158-017-1683-7
Abstract: This paper presents a method for constructing optimal design of experiments (DoE) intended for building surrogate models using dimensionless (or non-dimensional) variables. In order to increase the fidelity of the model obtained by regression, the… read more here.
Keywords: dimensionless; space; doe; optimal design ... See more keywords
Scalable Gaussian process-based transfer surrogates for hyperparameter optimization
Sign Up to like & getrecommendations! Published in 2017 at "Machine Learning"
DOI: 10.1007/s10994-017-5684-y
Abstract: Algorithm selection as well as hyperparameter optimization are tedious task that have to be dealt with when applying machine learning to real-world problems. Sequential model-based optimization (SMBO), based on so-called “surrogate models”, has been employed… read more here.
Keywords: surrogate; model; optimization; transfer ... See more keywords
Development and Implementation of Support Vector Machine Regression Surrogate Models for Predicting Groundwater Pumping-Induced Saltwater Intrusion into Coastal Aquifers
Sign Up to like & getrecommendations! Published in 2018 at "Water Resources Management"
DOI: 10.1007/s11269-018-1936-2
Abstract: Predicting the extent of saltwater intrusion (SWI) into coastal aquifers in response to changing pumping patterns is a prerequisite of any groundwater management framework. This study investigates the feasibility of using support vector machine regression… read more here.
Keywords: machine; support vector; coastal aquifers; saltwater intrusion ... See more keywords
Wing stiffness parameterisation for surrogate models
Sign Up to like & getrecommendations! Published in 2020 at "CEAS Aeronautical Journal"
DOI: 10.1007/s13272-020-00439-w
Abstract: Surrogate models are key enablers for robust, multidisciplinary design in aerospace. However, a critical question for their efficient use remains in terms of how the aircraft should be parameterised into design variables. This study investigates… read more here.
Keywords: aircraft; stiffness; stiffness parameters; wing stiffness ... See more keywords
Predicting trace organic compound attenuation by ozone oxidation: Development of indicator and surrogate models.
Sign Up to like & getrecommendations! Published in 2017 at "Water research"
DOI: 10.1016/j.watres.2017.04.024
Abstract: Ozone oxidation has been demonstrated to be an effective treatment process for the attenuation of trace organic compounds (TOrCs); however, predicting TOrC attenuation by ozone processes is challenging in wastewaters. Since ozone is rapidly consumed,… read more here.
Keywords: ozone oxidation; indicator; attenuation; surrogate models ... See more keywords
C4+ Surrogate Models for Thermophysical Properties of Aviation Kerosene RP-3 at Supercritical Pressures
Sign Up to like & getrecommendations! Published in 2021 at "Energy & Fuels"
DOI: 10.1021/acs.energyfuels.1c00326
Abstract: Due to the complexity of the chemical compositions in aviation kerosene, simplified surrogate models have gained significant attention to effectively reproduce the thermophysical properties of avia... read more here.
Keywords: properties aviation; aviation kerosene; kerosene supercritical; surrogate models ... See more keywords
Comparison of RP-3 Pyrolysis Reactions between Surrogates and 45-Component Model by ReaxFF Molecular Dynamics Simulations
Sign Up to like & getrecommendations! Published in 2019 at "Energy & Fuels"
DOI: 10.1021/acs.energyfuels.9b01321
Abstract: This work compares pyrolysis reactions of 3- and 4-component surrogate models of RP-3 aviation fuel by a ReaxFF molecular dynamics (MD) simulation method. To evaluate the reactivity of the two RP-3 surrogate models, a multi-component… read more here.
Keywords: pyrolysis reactions; surrogate models; model; reaxff molecular ... See more keywords
Application of Surrogate Models as an Alternative to Process Simulation for Implementation of the Self-Optimizing Control Procedure on Large-Scale Process Plants—A Natural Gas-to-Liquids (GTL) Case Study
Sign Up to like & getrecommendations! Published in 2021 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.0c05715
Abstract: High computational loads, time-consuming convergence, and simulation crashes are common when using process simulators for flowsheet optimization. In this paper, by replacing the large-scale physica... read more here.
Keywords: application surrogate; alternative process; surrogate models; large scale ... See more keywords
Multiple-Surrogate Models for Probabilistic Performance Assessment of Wind-Excited Tall Buildings under Uncertainties
Sign Up to like & getrecommendations! Published in 2020 at "ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering"
DOI: 10.1061/ajrua6.0001091
Abstract: AbstractPerformance-based design (PBD) is becoming a benchmark approach for design and performance assessment of civil structures because it facilitates communication between stakeholders and desig... read more here.
Keywords: models probabilistic; performance assessment; multiple surrogate; performance ... See more keywords
Flow imaging as an alternative to non-intrusive measurements and surrogate models through vision transformers and convolutional neural networks
Sign Up to like & getrecommendations! Published in 2023 at "Physics of Fluids"
DOI: 10.1063/5.0144700
Abstract: A numerical framework is proposed whereby flow imaging data are leveraged to extract relevant information from flowfield visualizations. To this end, a vision transformer (ViT) model is developed to predict quantities of interest from images… read more here.
Keywords: surrogate models; convolutional neural; imaging alternative; flow imaging ... See more keywords
Radiation Source Localization Using Surrogate Models Constructed from 3-D Monte Carlo Transport Physics Simulations
Sign Up to like & getrecommendations! Published in 2020 at "Nuclear Technology"
DOI: 10.1080/00295450.2020.1738796
Abstract: Abstract Recent research has focused on the development of surrogate models for radiation source localization in a simulated urban domain. We employ the Monte Carlo N-Particle (MCNP) code to provide high-fidelity simulations of radiation transport… read more here.
Keywords: source localization; source; monte carlo; physics ... See more keywords