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Showing 1 to 20 of 20 for “"Surrogate-based"”.

  1. Surrogate-based optimization of a BioMEMs microfluidic weir

    … design optimization computationally tractable a surrogate is derived; that is, a model that provides an accurate approximation to the input/output map of the simulation but that is much cheaper computationally to evaluate.

    mit Repository record for Surrogate-based optimization of a BioMEMs microfluidic weir (opens in a new tab)

  2. Surrogate-based optimization using multifidelity models with variable parameterization

    … such optimization computationally intractable. Surrogate-based optimization (SBO) - optimization using a lower-fidelity model most of the time, with occasional recourse to the high-fidelity model - is a proven method for reducing the cost of optimization. One branch of SBO uses lower-fidelity …

    mit Repository record for Surrogate-based optimization using multifidelity models with variable parameterization (opens in a new tab)

  3. Surrogate-based global optimization of composite material parts under dynamic loading

    … This work presents an optimization approach based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel enhancement drive the design process towards a global optimum. Kriging metamodel is used in the optimization algorithm. This metamodel …

    iupui Repository record for Surrogate-based global optimization of composite material parts under dynamic loading (opens in a new tab)

  4. Data Driven Surrogate Based Optimization in the Problem Solving Environment WBCSim

    … as possible. This paper presents a data driven, surrogate based optimization algorithm that uses a trust region based sequential approximate optimization (SAO) framework and a statistical sampling approach based on design of experiment (DOE) arrays. The algorithm is implemented using techniques …

    vt Repository record for Data Driven Surrogate Based Optimization in the Problem Solving Environment WBCSim (opens in a new tab)

  5. Optimisation of electrical machines using data-driven dynamic thermal models and surrogate-based multi-objective evolutionary algorithms.

    … reducing model complexity by removing features based on the magnitude of their corresponding regression coefficients. Results show that between 30% and 50% of model features can be eliminated without significantly affecting accuracy, enabling more efficient and scalable thermal modelling for …

    rgu Repository record for Optimisation of electrical machines using data-driven dynamic thermal models and surrogate-based multi-objective evolutionary algorithms. (opens in a new tab)

  6. Fusion of correlated information in multifidelity aircraft design optimization

    … the design space. In this thesis, we present a surrogate-based multifidelity framework that simultaneously accounts for model correlation and accommodates non-hierarchical fidelity specifications. The development of our multifidelity framework can be classified into three stages. The first stage …

    mit Repository record for Fusion of correlated information in multifidelity aircraft design optimization (opens in a new tab)

  7. Uncertainty-Integrated Surrogate Modeling for Complex System Optimization

    <p>Approximation models such as surrogate models provide a tractable substitute to expensive physical simulations and an effective solution to the potential lack of quantitative models of system behavior. These capabilities not only enable the efficient design of complex systems, but is also …

    syracuse-diss Repository record for Uncertainty-Integrated Surrogate Modeling for Complex System Optimization (opens in a new tab)

  8. Hydrodynamic Design of Highly Loaded Torque-neutral Ducted Propulsor for Autonomous Underwater Vehicles

    … is applied to Virginia Tech Dragon AUV. It is based on the parametric geometry definition for the propulsor, use of high-fidelity CFD RANSE solver with the transition model, construction of the surrogate model, and multi-objective genetic optimization algorithm. The CFD model is validated using …

    vt Repository record for Hydrodynamic Design of Highly Loaded Torque-neutral Ducted Propulsor for Autonomous Underwater Vehicles (opens in a new tab)

  9. Robust and Data-Driven Uncertainty Quantification Methods as Real-Time Decision Support in Data-Driven Models

    … (UQ) methods are broadly categorized into surrogate-based models, which approximate simulators for speed and efficiency, and probabilistic approaches, such as Bayesian models and Gaussian processes, that inherently capture uncertainty into predictions. For real-time UQ, leveraging recent …

    vt Repository record for Robust and Data-Driven Uncertainty Quantification Methods as Real-Time Decision Support in Data-Driven Models (opens in a new tab)

  10. Surrogate optimization with algebraic notes and applications within the electromagnetics context

    This thesis deals with surrogate optimization for applications within the electromagnetics context. Regarding the electromagnetics context, in particular, the magnetoquasistatic model of Maxwell’s theory is discussed. Moreover, relevant points regarding the magnetoquasistatic model’s numerical …

    tu-berlin Repository record for Surrogate optimization with algebraic notes and applications within the electromagnetics context (opens in a new tab)

  11. An Approach to Incorporate Additive Manufacturing and Rapid Prototype Testing for Aircraft Conceptual Design to Improve MDO Effectiveness

    … using WT data was adapted from traditional surrogate-based optimization (SBO), which uses computational fluid dynamics (CFD) for data generation. Split-plot experimental designs were developed for analysis of the WT SBO strategy using historical data and for WT testing of the NACA 0012. …

    vt Repository record for An Approach to Incorporate Additive Manufacturing and Rapid Prototype Testing for Aircraft Conceptual Design to Improve MDO Effectiveness (opens in a new tab)

  12. Nature-based algorithms for deep learning based systems and applications.

    Deep Learning Based Systems (DLBS), characterized by their layered processing, in-model feature transformation, and high complexity, have revolutionized problem-solving across numerous domains. However, the manual design of optimal DLBS architectures is prohibitively time-consuming and …

    rgu Repository record for Nature-based algorithms for deep learning based systems and applications. (opens in a new tab)

  13. A Fuel Surrogate Approach to Model Combustion Chemistry in Specialty Jet Fuels

    … speciation data were first modeled using a surrogate-based mechanism from the CRECK Modelling Group and chemical-functional group based optimized surrogates (CFGO), showing less than satisfactory agreement. Adjusting the aromatic content of the surrogates led to overall improvements in the …

    uic

  14. Seismic experimental analyses and surrogate models of multi-component systems in special-risk industrial facilities

    … and environmental impact. Besides, based on both observations of damage following recent major/moderate seismic events and numerical/experimental studies, it clearly emerges that critical non-structural components (NSCs) that are ubiquitous to most industrial facilities are …

    trento Repository record for Seismic experimental analyses and surrogate models of multi-component systems in special-risk industrial facilities (opens in a new tab)

  15. Design optimization and analysis of a fluoride salt cooled high temperature test reactor for accelerated fuels and materials testing and nonproliferation and safeguards evaluations

    … the Efficient Global Optimization (EGO) surrogate-based optimization framework, which has been successfully applied to aerospace and automotive engineering optimization problems in the past. OpenFRO extends the EGO framework to full-core reactor optimization in the presence of …

    mit Repository record for Design optimization and analysis of a fluoride salt cooled high temperature test reactor for accelerated fuels and materials testing and nonproliferation and safeguards evaluations (opens in a new tab)

  16. Optimization Boosts Decarbonization: Accelerating Net Zero from the Perspective of Carbon Capture and Utilization

    … effective way to decarbonize the fossil fuel-based energy sector. Carbon capture consists of two major fields: carbon capture and storage (CCS) as well as carbon capture and utilization (CCU). While CCS is more relevant to electricity production, CCU is compatible with the existing downstream …

    cambridge Repository record for Optimization Boosts Decarbonization: Accelerating Net Zero from the Perspective of Carbon Capture and Utilization (opens in a new tab)

  17. Optimization Under Uncertainty and Total Predictive Uncertainty for a Tractor-Trailer Base-Drag Reduction Device

    … (EA) and dividing rectangles (DIRECT), twelve surrogate models, six sampling methods, and surrogate-based global optimization (SBGO) methods. The DAKOTA optimization and uncertainty quantification framework is used to interface the RANS flow solver, grid generator, and optimization algorithm. …

    vt Repository record for Optimization Under Uncertainty and Total Predictive Uncertainty for a Tractor-Trailer Base-Drag Reduction Device (opens in a new tab)

  18. Methods for the integrated design of viscoelastic materials and structural geometry

    … constraint generation methods for multiobjective surrogate-based optimization for challenging problems (Chapter 4). The chapters in Part II present integrated design studies and methodologies that apply to the design problems of viscoelastic material systems. Studies in this part present numerical …

    uiuc Repository record for Methods for the integrated design of viscoelastic materials and structural geometry (opens in a new tab)

  19. A physiological basis to crop improvement and agronomic development

    … genotypes with the optimal heights. Approaches based on physiological understanding of yield are necessary for developing genotypes combining high yielding potential and agronomic traits of superior adaptation, and for understanding yield limiting factors. Yet, direct measurement of …

    cambridge Repository record for A physiological basis to crop improvement and agronomic development (opens in a new tab)