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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Comparison of Simulation of Dual-Active Bridge in Different Simulators and Using Different Simulation Methods

The accuracy of states measured from simulation of a dual-active bridge (DAB) converter with an open-loop controller has been used for comparing simulation software and algorithms. The accuracy of the measured states is sensitive to simulation settings and parameters chosen. In this paper, the simulation of the DAB converter with open-loop control is run in the MATLAB/Simscape Electrical, PLECS, and PSCAD software environments, with various simulation settings. The simulation results are also compared with a new simulation algorithm proposed for DAB simulations. Different simulation settings are evaluated, including different solver types, operating conditions, and the on-state resistance values of the MOSFET switches. The simulation results are compared with the theoretical calculations. It is shown that unexpected divergence and DC offset may occur in some cases. This paper provides guidelines to simulate the DAB converter with open-loop control.

Yin, Shiyuan↗
DOE OSTI2024

Software Quality Assurance Plan ANSYS LSDYNA Version 2023R1

ANSYS Inc. develops and markets engineering simulation software and services used in the aerospace, automotive, manufacturing, electronics, biomedical, energy, defense, and many other industries. ANSYS is dedicated to engineering simulation and is the world’s leading software provider. ANSYS was founded in 1970 and is headquartered in Canonsburg, Pennsylvania. ANSYS provides an engineering analysis tool combining structural, thermal, computational fluid dynamics, acoustic and electromagnetic simulation capabilities. ANSYS LS-DYNA is the most used explicit simulation program capable of simulating the response of materials to short periods of severe loading. Its many elements, contact formulations, material models, and other controls can be used to simulate complex models with control over all the details of the problem. ANSYS LS-DYNA has a vast array of capabilities to simulate extreme deformation problems using its explicit solver. Engineers can tackle simulations involving material failure and look at how the failure progresses through a part or through a system. Models with large amounts of parts or surfaces interacting with each other are also easily handled, and the interactions and load passing between complex behaviors are modeled accurately. Using computers with higher numbers of CPU cores can drastically reduce solution times. In addition, many consulting firms and hundreds of universities use ANSYS for analysis, research, and educational purposes. ANSYS is recognized worldwide as one of the most widely used and capable programs of its type. ANSYS has successfully passed over 100 customer quality system audits against American Society of Mechanical Engineers (ASME) NQA-1 and 10 CFR Part 50, Appendix B, since the company was founded, over 60 of which have been since 1997. ANSYS has successfully passed over 100 International Organization for Standardization (ISO) 9001 assessments. ANSYS design analysis software is the first created within a quality system with ISO 9001 certification, which is the internationally accepted quality standard. Product development, testing, maintenance, and support processes also meet the US Nuclear Regulatory Commission’s (NRC’s) quality requirements, as they have for nearly four decades. ANSYS staff perform more than 60,000 software verification tests before releasing each new product. ASME NQA-1-2012 (Subpart 2.7 is specific to software) is the industry- and NRC-accepted approach (consensus standard) for meeting 10 CFR Part 50, Appendix B, requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Hybrid Solid Oxide Fuel Cell/Gas Turbine Model Development for Electric Aviation

A thermodynamic model was developed and validated to analyze a high-performance solid oxide fuel cell and gas turbine (SOFC-GT) hybrid power system for electric aviation. This study used a process simulation software package (ProMax) to study the role of SOFC design and operation on the feasibility and performance of the hybrid system. Standard modules, including compressor, turbine, heat exchanger, reforming reactor, and combustor were used from the ProMax tool suite while a custom module was created to simulate the SOFC stack. The model used an SOFC test data set as an input. Additional SOFC stack performance effects, such as pressure, temperature, and utilization of air and fuel, were added from open source data. System performance predictors were SOFC specific power, fuel-to-electricity conversion efficiency, and hybrid system efficiency. Using these input data and predictors, a static thermodynamic performance model was created that can be modified for different system configurations and operating conditions. Prior to creating the final aircraft performance model, initial demonstration models were developed to validate output results. We used the NASA SOFC model as a benchmark, which was created with their Numerical Propulsion System Simulator (NPSS) software framework. Our output results matched within 1% of both the NASA model and open source SOFC performance data. With confidence gained in the accuracy of this model, a 1-MW SOFC-GT hybrid power system was constructed for an aircraft propulsion concept. Overall hybrid system efficiencies of > 75% FTE were observed during standard 36,000 feet cruise flight conditions.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Simulation-Based Assessment of Energy Consumption of Alternative Powertrains in Agricultural Tractors

The objectives of this research were to develop simulation models for agricultural tractors with different powertrain technologies and evaluate the energy consumption in typical agricultural operations. Simulation models were developed for conventional, parallel hybrid electric, series hybrid electric, fuel cell hybrid, and battery electric powertrains. Autonomie vehicle simulation software (version 2022) was used for the simulations and the tractor models were simulated in two tilling cycles and in a road transport cycle with a trailer. The alternative powertrains were configured to have at least the same tractive performance as the conventional, diesel engine-powered tractor model. The simulation results showed that the potential of the parallel and series hybrid powertrains to improve energy efficiency depends heavily on the tractor size and the operating cycle conditions. The fuel cell hybrid and battery electric powertrains have a higher potential to reduce energy consumption and emissions but still have inherent technical challenges for practical operation. The battery-powered electric tractor would require improvements in the storage energy density to have a comparable operational performance in comparison to other powertrains. The fuel cell hybrid tractor already provided an adequate operating performance but the availability of hydrogen and refueling infrastructure could be challenging to resolve in the farming context.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

N-S3 Cellular Vehicle-to-Everything (C-V2X) Cosimulation Framework [SWR-24-54]

This is a vehicular networking simulator designed to enable synchronized network simulation with vehicle traffic simulation software. The communications model is based on the 3GPP LTE-V2X Mode 4 protocol, but includes several other wireless network protocol models as well. This simulator includes both a V2X network simulation implemented in ns-3 as well as an interface to automatically configure, run, and interact with a set of ns-3 instances based on network size and available hardware. This software has been tested with Aimsun NEXT 2.0 simulator (with V2X SDK), but uses a generic interface for compatibility with any comparable vehicle traffic simulator across the HELICS co-simulation framework. This software is intended as a generalized extension to vehicle traffic simulation, and does not model any vehicle traffic on its own.

Wang, Qichao↗
DOE OSTI2021

Evaluation of the Barracuda Software Package for Simulating Bubble Motion in Vibrating Liquid-Filled Containers

The commercial software package Barracuda, developed by CPFD Software for simulating particle-laden fluid flows, is evaluated as a means to simulate the motion of bubbles in vibrating liquid-filled containers. Demonstration simulations of bubbles rising due to buoyancy forces in a cylinder filled with silicone oil and angled at 0, 30, 45, and 60 degrees from the vertical were performed by CPFD Software. The results of these simulations are discussed, and the capabilities of Barracuda for simulating bubble motion are assessed. It was determined that at present Barracuda does not meet the needs of the desired application. Further developments that would enable its use for this application are highlighted.

42 ENGINEERING↗
DOE OSTI2025

hybridlane (fka CV-DV Quantum Circuit API)

This software package will abstract building a CV-DV quantum circuit for simulation and running on hardware. Existing simulation software each has their own API. This software intends to define a common API to be executed on several simulation and physical hardware backends.

Stavenger, Tim [Pacific Northwest National Laborat↗
DOE OSTI2024

Spinbox: tools for many-body quantum systems in a Monte Carlo context

Spinbox is a piece of software that facilitates quantum mechanical calculations relevant to Monte Carlo simulation of atomic nuclei. At the front lines of research on the nuclear many-body problem are a large number of supercomputer-scale simulation codes. These codes produce valuable results but can be hard to understand, especially for those without intimate knowledge of the relevant theoretical methods. Thus, tools that fill pedagogical roles are extremely valuable. Spinbox makes it easy for one to replicate and analyze the computational processes relevant to a Quantum Monte Carlo (QMC) simulation that may be difficult to understand/debug/analyze due to the scale of the corresponding simulation software. Spinbox is written in Python using other state-of-the-art Python modules for numerical calculations. While a number of Python libraries exist that are suited to general quantum many-body calculations, the motivation of Spinbox is quite particular. In Diffusion Monte Carlo methods (DMC, GFMC, AFDMC), the central calculation is the imaginary-time propagation of individual samples of the many-body wavefunction. Although quantum wavefunctions generally must be described by a probability distribution over a basis, DMC imbues particles (within one sample) with classical spatial coordinates. This method is unusual, so other Python packages are typically not set up to do this easily. Furthermore, the software has built-in options for nuclear systems assuming isospin symmetry, which can be set up with other libraries but is a nontrivial process to do so. Features: - numerical representation of samples of the many-body wavefunctions, including tensor-product states (used in AFDMC) - numerical representation of many-body operators, including tensor-product operators: general, spin, imaginary-time propagation, etc. - the correct associated arithmetic and algebra, implemented as class methods - classes for representing realistic nuclear two- and three-body Hamiltonians (e.g. Argonne V18, Illinois NNN) - large-scale parallel integration over random variables, crucial for the AFDMC method My goal is to make this package open source so that anyone may use it and contribute to it, particularly other researchers doing AFDMC calculations

Fox, Jordan↗
DOE OSTI2026

MixPI: Mixed-time slicing path integral software for quantized molecular dynamics simulations

We introduce the MixPI software to implement path integral molecular dynamics (PIMD) simulations for the study of condensed phase systems where nuclear quantum effects (NQEs) are important. In contrast to existing PIMD simulation software, MixPI enables the implementation of mixed quantum–classical path integral simulations where only a subset of system degrees of freedom (dofs) are treated quantum mechanically in an extended phase space while the remaining dofs are described classically. We expect this software to be particularly useful for simulations of electron and proton transfer in condensed phase systems, as well as for the study of biological and material systems where only a handful of dofs contribute significantly to the observed NQEs. We demonstrate the use of MixPI in two different systems. The first is a simple water model where we implement a set of mixed quantum–classical simulations to compute average energy and radial distribution functions. We use these simulations to benchmark the effectiveness of MixPI and to demonstrate how it enables systematic investigation into the origin of observed NQEs. We then compute radial distribution functions for a system where MixPI is essential: a solvated metal (M 2+ ) cation described using an explicit quantized electron localized on an M 3+ ion in water.

chemical physics↗
DOE OSTI2023

FLORIS v3.5 Wake Modeling and Wind Farm Controls Software [SWR-17-43 and SWR-14-20]

FLORIS is a controls-focused wind farm simulation software incorporating steady-state engineering wake models into a performance-focused Python framework. It has been in active development at NREL since 2013 and the latest release is FLORIS v3.5.Online documentation is available at https://nrel.github.io/floris. The software is in active development and engagement with the development team is highly encouraged. If you are interested in using FLORIS to conduct studies of a wind farm or extending FLORIS to include your own wake model, please join the conversation in GitHub Discussions! https://www.nrel.gov/wind/floris.html

Fleming, Paul↗
DOE OSTI2022

Denoising Convolutional Networks to Accelerate Detector Simulation

The high accuracy of detector simulation is crucial for modern particle physics experiments. However, this accuracy comes with a high computational cost, which will be exacerbated by the large datasets and complex detector upgrades associated with next-generation facilities such as the High Luminosity LHC. We explore the viability of regression-based machine learning (ML) approaches using convolutional neural networks (CNNs) to "denoise" faster, lower-quality detector simulations, augmenting them to produce a higher-quality final result with a reduced computational burden. The denoising CNN works in concert with classical detector simulation software rather than replacing it entirely, increasing its reliability compared to other ML approaches to simulation. We obtain promising results from a prototype based on photon showers in the CMS electromagnetic calorimeter. Future directions are also discussed.

Banerjee, Sunanda↗
DOE OSTI2021

Denoising Convolutional Networks to Accelerate Detector Simulation [Poster]

The high accuracy of detector simulation is crucial for modern particle physics experiments. However, this accuracy comes with a high computational cost, which will be exacerbated by the large datasets and complex detector upgrades associated with next-generation facilities such as the High Luminosity LHC. We explore the viability of regression-based machine learning (ML) approaches using convolutional neural networks (CNN) to ``denoise'' faster, lower-quality detector simulations, augmenting them to produce a higher-quality final result with a reduced computational burden. The denoising CNN works in concert with classical detector simulation software rather than replacing it entirely, increasing its reliability compared to other ML approaches to simulation. We obtain promising results from a prototype based on photon showers in the CMS electromagnetic calorimeter. Future directions are also discussed.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

A simulation‐based integrated virtual testbed for dynamic optimization in smart manufacturing systems

Abstract In a manufacturing system, production control‐related decision‐making activities occur at different levels. At the process level, one of the main control activities is to tune the parameters of individual manufacturing equipment. At the system level, the main activity is to coordinate production resources and to route parts to appropriate workstations based on their processing requirement, priority indices, and control policy. At the factory level, the goal is to plan and schedule the processing of parts at different operations for the entire system in order to optimize certain objectives. Note that the results of such activities at different levels are closely coupled and affect the overall performance of the manufacturing system as a whole. Therefore, it is important to systematically integrate these control and optimization activities into one unified platform to ensure the goal of each individual activity is aligned with the overall performance of the system. In this paper, we develop a simulation‐based virtual testbed that implements dynamic optimization, automatic information exchange, and decision‐making from the process‐level, system‐level, and factory‐level of a manufacturing system into an integrated computation environment. This is demonstrated by connecting a Python‐based numerical computation program, discrete‐event simulation software (Simul8), and an optimization solver (CPLEX) via a third‐party master program. The application of this simulation‐based virtual testbed is illustrated by a case study in a machining shop.

Sun, Yuting↗
DOE OSTI2022

Evaluating the Effects of Nitrogen Doping and Oxygen Doping on SRF Cavity Performance

Superconducting radiofrequency (SRF) cavities are resonators with extremely low surface resistance that enable accelerating cavities to have extremely high quality factors (Q₀). High Q₀ decreases the capital required to keep the accelerators cold by reducing power loss. The performance of SRF cavities is largely governed by the surface composition of the first §I{100}{nm} of the cavity surface. Impurities such as oxygen and nitrogen have been observed to yield high Q₀, but their precise roles are still being studied. Here, we compare the performance of cavities doped with nitrogen and oxygen in terms of surface composition and heating behavior with field. A simulation of the diffusion of oxygen into the bulk of the cavity was built using COMSOL Multiphysics software. Simulated results were compared to the actual surface composition of the cavities as determined from secondary ion mass spectrometry analysis. Understanding how these impurities affects performance allows us to have further insight into the underlying mechanisms that enable these surface treatments to yield high Q₀.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

The HUNTER Dynamic Human Reliability Analysis Tool: Coupling an External Plant Code

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a framework to support dynamic human reliability analysis (HRA) with the aim to develop standalone software to perform the dynamic HRA calculations. Within the HRA, human actions in nuclear power plants (NPPs) are predicated by plant states, and human actions influence the plant. In other words, plant operations are necessarily recursive, and it becomes challenging to model complex human-plant interactions. Consequently, we have linked two software simulations that complement those shortcomings. RELAP5-3D—the Reactor Excursion and Leak Analysis Program (RELAP; Aumiller, Tomlinson, and Bauer 2001) is the foundational thermal-hydraulic software used to model nuclear systems. Using RELAP5-3D, we have simulated the plant operations proceeding according to procedures developed to address emergent situations in NPPs. Plant operations include various actions such as the operator checking plant parameters, as well as actions that are continuously performed over time until a specific parameter reaches certain criteria. That means that HUNTER and RELAP5-3D exchange information with each other and should be carried out simultaneously over time. To simulate plant operations, which represent the actual operator checks of plant parameters and corresponding manual control actions, changes in plant status are identified through simulation and performed according to the criteria and order of the procedure. Thus, the goal of coupling HUNTER with RELAP5-3D is to facilitate synchronous coupling, where human and plant models provide iterative feedback loops that drive the course of actions. The advantage of coupling with RELAP5-3D to serve as the external environment module in HUNTER is the ability to customize the plant model and streamline for particular model applications. In this paper, we will address the key features of the coupling and the coupling structure built to perform the feedback loops.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2025

Using the ATLAS experiment software on heterogeneous resources

With the large dataset expected from 2030 onwards by the HL-LHC at CERN, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM CPU architecture is becoming a competitive and energy efficient alternative. Accelerators like GPUs are available in any recent HPC. In the past years ATLAS has successfully ported its full data processing and simulation software framework Athena to ARM and has invested significant effort in porting parts of the reconstruction and simulation algorithms to GPUs. We report on the successful usage of the ATLAS experiment offline and online software framework Athena on ARM and GPUs through the PanDA workflow management system at various WLCG sites. Furthermore we report on performance optimizations of the builds for ARM CPUs and the GPU integration efforts. We will discuss performance comparisons of different ARM and x86_64 architectures on WLCG resources and Cloud compute providers like GCP and AWS using ATLAS productions workflows as used in the Hep-Score23 benchmark suite.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗