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Results for “Simulation optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Optimization of electrical treatment strategy for surface roughness reduction in conducting thin films

The surface roughness of deposited conducting thin films is responsible for various materials reliability problems in nanoelectronics and nanofabrication technologies. In this work, we report a modeling and simulation study that aims at optimizing the electrical surface treatment of deposited conducting thin films as a physical processing strategy for their surface roughness reduction. Our research is based on a continuum model of film surface morphological evolution that accounts for the residual stress in the deposited conducting thin film, the film’s wetting of the substrate layer that it is deposited on, film texture and surface diffusional anisotropy, and surface electromigration. Through systematic linear stability analysis and dynamical simulation protocols, we examine in detail the effects of film surface crystallographic orientation and applied electric field direction toward minimizing the electric field strength required for film surface smoothening. We believe that the critical electric field strength requirement for surface roughness reduction on {110}, {100}, and {111} surfaces of face-centered cubic crystalline conducting thin films exhibits a very strong dependence on the applied electric field direction, expressed as the electric field misalignment with respect to the principal residual stress directions in the film and the fast surface diffusion directions. Due to these findings, we optimize the electrical treatment strategy for surface roughness reduction of conducting thin films with respect to all relevant processing and material parameters.

42 ENGINEERING↗
DOE OSTI2017

Distributed Workflows for Modeling Experimental Data

Modeling helps explain the fundamental physics hidden behind experimental data. In the case of material modeling, running one simulation rarely results in output that reproduces the experimental data. Often one or more of the force field parameters are not precisely known and must be optimized for the output to match that of the experiment. Since the simulations require high performance computing (HPC) resources and there are usually many simulations to run, a workflow is very useful to prevent errors and assure that the simulations are identical except for the parameters that need to be varied. These workflows are usually distributed because the simulations require HPC, but the optimization and steps to compare the simulation results and experimental data are done on a local workstation. We will present results from force field refinement of data collected at the Spallation Neutron Source using Kepler, Pegasus, and Beam workflows and discuss what we have learned from using these workflows.

Lynch, Vickie E.↗
DOE OSTI2023

Design, fabrication, and testing of a water-cooled tungsten-foam high-heat flux plasma-facing module

Here, we present a comprehensive study detailing the design, fabrication and testing a new modular “finger” component, featuring a hexagonal tungsten foam armor tile bonded to the top surface of the water-cooled finger unit. The mechanical, thermal, and particle transport properties of the tungsten foam armor were determined for a wide range of porosity and cell size, and then combined in an equivalent solid material with “effective” properties suitable for large-scale simulations. A series of 3-D multiphysics simulations for coupled thermal and mechanical behavior of the “finger” module are used to optimize the design before fabrication. The simulation results show that, for the expected experimental conditions, a safe range of heat flux and foam porosity is possible for both water-cooling and helium-cooling. Based on these multiphysics simulations, an optimum finger cooling module has been fabricated at Ultramet, Inc. A series of experiments were designed to study the thermomechanical performance of the “finger” unit under steady-state and transient thermal loading at surface heat flux up to 16 MW/m 2 in the High Energy Flux Test facility (HEFTY) at UCLA. Testing conditions included low-power, steady-state plasma exposure at 6 MW/m 2 , followed by severe high heat flux cycles at 16 MW/m 2 . Results of these tests are explained through comparisons with multiphysics simulations. To eliminate the effects of thermomechanical damage carried out on a module on its thermo-mechanical response on a subsequent test, three different yet identically designed and fabricated finger modules were tested. The results show that the current design is capable of cooling the walls of fusion devices at surface heat flux up to 6 MW/m 2 without failure, and that the failure heat flux limit is below 16 MW/m 2 .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Useability and Optimization Improvements in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed or will be deployed in the coming months. The capabilities were implemented in the same order as they are covered in this report: increased support of face variables, arbitrary spatial and temporal evaluation of material properties, and the addition of a triangular meshing library in libMesh.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Usability and Optimization Improvements in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE’s broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities were implemented in the same order as they are covered in this report: multiple nonlinear systems in the same input file, implementation of generic field transfers and other transfer system enhancements, support for stateful material property redistribution for adaptivity and distributed meshes, and dynamic linking and loading of individually compiled applications. These four additions are fundamental capabilities that will be leveraged by many NEAMS applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Roadrunner

SAND2026-17073O Roadrunner software provides a comprehensive platform for simulating the mechanical behavior of crystalline materials under various loading conditions, allowing users to investigate the effects of dislocation slip hardening and damage evolution. Developed as a fork of the Multiphysics Object Oriented Simulation Environment (MOOSE) software from Idaho National Laboratory, Roadrunner is optimized for high-performance computing and can simulate large-scale problems, enabling researchers to explore complex scenarios. Its applications include material design and optimization in aerospace and automotive industries, investigation of failure mechanisms in structural materials, and development of predictive models for crystalline materials under various loading conditions. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Lim, Hojun [Sandia National Lab. (SNL-CA), Livermo↗
DOE OSTI2019

Simulation of double buffer layer on CIGS solar cell with SCAPS software

In a CIGS thin film solar cell, the buffer layer is interposed between the absorber layer and the window layer, which plays an important role in interface electricity. CdS is often used as a buffer layer in CIGS cells. Beside the toxicity of Cd, the main drawback of CdS is its relatively narrow band gap (2.4 eV), which can lead to the current loss due to parasitic absorption. In order to reduce the use of CdS, we try other buffer layers instead of CdS and optimize buffer layer structure. Numerical simulation has been used to explore the effect of different buffer layer materials (CdS and ZnSe) on the performance of CuInGaSe{sub 2} solar cells with SCAPS-1D software. The main photovoltaic parameters of the analog device: open circuit voltage, short circuit current density, fill factor and conversion efficiency (η) were compared and analyzed. The results show that different buffer materials and thickness have great influence on the performance of the cell. In this simulation, CdS buffer layer was replaced by ZnSe material, which has a wider band gap. However, the efficiency of this kind of cell is lower than that of CIGS device with CdS buffer layer because of the bad energy band alignment. In order to improve the short-wave absorption and the efficiency of CIGS cell, we simulated a novel CdS/ZnSe double buffer layer structure. The efficiency of the optimized cell with double buffer layer increases from 18.47% (conventional cell with the same CdS buffer layer thickness) to 19.01%.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Co-Simulation of Electric Power Distribution Systems and Buildings including Ultra-Fast HVAC Models and Optimal DER Control

Smart homes and virtual power plant (VPP) controls are growing fields of research with potential for improved electric power grid operation. A novel testbed for the co-simulation of electric power distribution systems and distributed energy resources (DERs) is employed to evaluate VPP scenarios and propose an optimization procedure. DERs of specific interest include behind-the-meter (BTM) solar photovoltaic (PV) systems as well as heating, ventilation, and air-conditioning (HVAC) systems. The simulation of HVAC systems is enabled by a machine learning procedure that produces ultra-fast models for electric power and indoor temperature of associated buildings that are up to 133 times faster than typical white-box implementations. Hundreds of these models, each with different properties, are randomly populated into a modified IEEE 123-bus test system to represent a typical U.S. community. Advanced VPP controls are developed based on the Consumer Technology Association (CTA) 2045 standard to leverage HVAC systems as generalized energy storage (GES) such that BTM solar PV is better utilized locally and occurrences of distribution system power peaks are reduced, while also maintaining occupant thermal comfort. An optimization is performed to determine the best control settings for targeted peak power and total daily energy increase minimization with example peak load reductions of 25+%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Inertial Confinement Fusion Design Search Using Bayesian Optimization

Inertial confinement fusion (ICF) experiments rely on complex multi-physics simulation codes such as the Lawrence Livermore National Laboratory-developed HYDRA to guide design work. However, these simulations have several dozen tunable parameters and can be computationally expensive. This makes searching the parameter space challenging and time-consuming. Recently developed automated tools utilize Bayesian optimization to search these high-dimensional parameter spaces for optimal designs. The optimization tools run 2D integrated simulations in HYDRA to converge on a design that produces specified scalar or vector outputs. In this paper, we apply the Bayesian optimization tools to two common tuning scenarios. First, we tune simulation inputs to match measurements of a well-characterized experiment at the National Ignition Facility. This type of tuning is commonly performed to compensate for the use of simplified simulation settings (e.g. reduced resolution) or to account for missing physics in the simulations. Second, we search for an ICF simulation design that has a particular radiation drive profile. These optimizations replicate the kinds of tuning researchers routinely perform, but do so with significantly reduced manual effort. This approach demonstrates a powerful and efficient pathway toward autonomous, high-fidelity design optimization for future ICF experiments.

Bayesian optimization↗
DOE OSTI2024

Critical mineral substitutions in IN617: A combined computational and experimental approach to performance evaluation and feasibility

Addressing the escalating demand for critical minerals (CMs) driven by global climate change initiatives, this study explores compositional modifications to Inconel 617 (IN617) by substituting cobalt (Co) with manganese (Mn) across various atomic percentages. Here, we conducted a computational feasibility study employing Molecular Dynamics (MD) simulations to provide strategic guidance for experimental validation. The simulations analyzed tensile strength and corrosion resistance for five modified compositions (M1 to M5) to identify optimal properties. Tensile tests on cubic simulation cells were performed to generate stress-strain curves, revealing the impact of Co replacement with Mn on tensile strength—a metric correlated with hardness. Oxygen penetration simulations were conducted to evaluate corrosion resistance, indicating that reduced oxygen penetration depth corresponds to enhanced resistance. Promising compositions underwent phase diagram calculations for assessing phase stability. The optimal composition (M1), characterized by high tensile strength and minimal oxygen penetration, was chosen for experimental validation using induction melting and friction stir consolidation techniques. The materials were further characterized using SEM-EDS, XRD, and Vickers hardness testing. Our findings suggest that Mn substitution in IN617 can yield mechanical performance at par with high-Co alloys in energy-critical applications.

36 MATERIALS SCIENCE↗
NASA NTRS1980

Closed loop models for analyzing engineering requirements for simulators

A closed loop analytic model, incorporating a model for the human pilot, (namely, the optimal control model) that would allow certain simulation design tradeoffs to be evaluated quantitatively was developed. This model was applied to a realistic flight control problem. The resulting model is used to analyze both overall simulation effects and the effects of individual elements. The results show that, as compared to an ideal continuous simulation, the discrete simulation can result in significant performance and/or workload penalties.

Baron, S.↗
NASA NTRS1984

Model for optimal parallax in stereo radar imagery

Simulated stereo radar imagery is used to investigate parameters for a spaceborne imaging radar. Incidence angles ranging from small to intermediate to large are used with three digital terrain model areas which are representative of relatively flat, moderately rough, and mountaneous terrain. The simulated radar imagery was evaluated by interpreters for ease of stereo perception and information content, and rank ordered within each class of terrain. The interpreter's results are analyzed for trends between the height of a feature and either parallax or vertical exaggeration for a stereo pair. A model is developed which predicts the amount of parallax (or vertical exaggeration) an interpreter would desire for best stereo perception of a feature of a specific height. Results indicate the selection of angle of incidence and stereo intersection angle depend upon the relief of the terrain. Examples of the simulated stereo imagery are presented for a candidate spaceborne imaging radar having four selectable angles of incidence.

Pisaruck, M. A.↗
NASA NTRS1996

NASA battery testbed: A designed experiment for the optimization of LEO battery operational parameters

Simulation of spacecraft battery operation is implemented. Robust design experiment to obtain optimum battery operational parameters is performed. It is found that short term tests using robust design of experiments can provide guidelines for optimum battery operation. It is decided to use robust design approach to provide guidelines for battery operation on current spacecraft in orbit as batteries age (GRO, UARS, EUVE, TOPEX).

Deligiannis, F.↗
NASA NTRS2017

TRACC_PB SOSS Integrated Traffic Simulation for CLT Ramp Operation

This presentation provides the current task under the NASA-DLR research collaboration for airport surface. It presents the effort done to adapt TRACC and SOSS software components to simulate airport (CLT) ramp area traffic management using TRACC's conflict free taxi trajectory optimization and SOSS's fast time simulation platform.

surface operations↗
DOE OSTI2026

Multi-Fidelity Bayesian Optimization with Gaussian Processes for Double Shell Inertial Confinement Fusion Target Design

Reliable, secure access to energy is a major focus for national security efforts. One potential route to such energy is through fusion reactions in inertial confinement fusion (ICF) experiments. Such experiments are carried out at facilities such as the National Ignition Facility (NIF) in Livermore, California, where high powered lasers are used to compress a DT fuel-containing target to the necessary high temperature, high pressure conditions. These experiments are limited in number, which creates a heavy dependence on high fidelity predictive physics simulations and analysis performed “pre shot,” or before the experiment occurs. Many of these simulations in higher dimensions (2D and 3D) are computationally expensive, so finding optimal simulation-based designs presents its own challenges. In this work, we present our multi-fidelity Bayesian optimization with Gaussian processes (GPs) for ICF double shell targets, where a 1D surrogate model is used to help find a 2D surrogate model, enabling us to find optimal targets in the higher fidelity (2D), while saving computational cost.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1993

Atlas IIAS ascent trajectory design for the SOHO mission

In 1995, an Atlas IIAS launch vehicle will loft the Solar and Heliospheric Observatory (SOHO) as part of the International Solar and Terrestrial Physics program. The operational phase of the SOHO mission will be conducted from a `halo orbit' about the Sun-Earth interior libration point. Depending on the time of the year of launch, the optimal transfer requires a parking orbit of variable duration to satisfy widely varying inertial targets. A simulation capability has been developed that optimizes the launch vehicle ascent and spacecraft transfer phases of flight together, subject to both launch vehicle and spacecraft constraints. It will be shown that this `ground-up' simulation removes the need for an intermediate target vector at Centaur upper stage/spacecraft separation. Although providing only a modest gain in deliverable satellite mass, this capability substantially improves the mission integration process by removing the strict reliance on near-Earth target vectors. Trajectory data from several cases are presented and future applications of this capability are also discussed.

Willen, Robert E.↗
NASA NTRS1994

Evaluation of NASA's end-to-end data systems using DSDS+

The Data Systems Dynamic Simulator (DSDS+) is a software tool being developed by the authors to evaluate candidate architectures for NASA's end-to-end data systems. Via modeling and simulation, we are able to quickly predict the performance characteristics of each architecture, to evaluate 'what-if' scenarios, and to perform sensitivity analyses. As such, we are using modeling and simulation to help NASA select the optimal system configuration, and to quantify the performance characteristics of this system prior to its delivery. This paper is divided into the following six sections: (1) The role of modeling and simulation in the systems engineering process. In this section, we briefly describe the different types of results obtained by modeling each phase of the systems engineering life cycle, from concept definition through operations and maintenance; (2) Recent applications of DSDS+. In this section, we describe ongoing applications of DSDS+ in support of the Earth Observing System (EOS), and we present some of the simulation results generated of candidate system designs. So far, we have modeled individual EOS subsystems (e.g. the Solid State Recorders used onboard the spacecraft), and we have also developed an integrated model of the EOS end-to-end data processing and data communications systems (from the payloads onboard to the principle investigator facilities on the ground); (3) Overview of DSDS+. In this section we define what a discrete-event model is, and how it works. The discussion is presented relative to the DSDS+ simulation tool that we have developed, including it's run-time optimization algorithms that enables DSDS+ to execute substantially faster than comparable discrete-event simulation tools; (4) Summary. In this section, we summarize our findings and 'lessons learned' during the development and application of DSDS+ to model NASA's data systems; (5) Further Information; and (6) Acknowledgements.

Rouff, Christopher↗