Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Programming models”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Coupled Neutronics - Thermal-Hydraulics - Thermomechanics modeling of Molten Chloride Reactor

Molten Salt Reactors (MSRs) are innovative Generation-IV nuclear reactors known for their enhanced safety features, fuel economy, and fuel cycle advancements. However, designing and studying these reactors present unique safety and modeling challenges. The Department of Energy (DOE)'s Nuclear Energy Advanced Modeling and Simulation program addresses these challenges through the development of flexible multi-fidelity, multiphysics simulation tools. This study exemplifies NEAMS tools' capabilities by modeling a chloride-based micro-MSR: Griffin for neutronics simulations, Pronghorn for thermal-hydraulics simulations, and BISON for thermomechanics simulations. These tools are integrated into a comprehensive 3D multiphysics model, successfully capturing steady-state and transient reactor operations. A loss of flow accident is examined as an illustrative example of transient behavior. Additionally, this paper contributes to demonstrating the theoretical feasibility of micro-MSR concepts, which have received less attention compared to other designs. The subsequent sections provide a brief description of the MSR concept studied, an overview of the computational tools used, and present results for both steady-state operation and a loss of flow accident.

42 - ENGINEERING↗
DOE OSTI2012

Detection of homologous horizontal gene transfer in SNP data

We study the detection of mutations, sequencing errors, and homologous horizontal gene transfers (HGT) in a set of closely related microbial genomes. We base the model on single nucleotide polymorphisms (SNP's) and break the genomes into blocks to handle the rearrangement problem. Then we apply a synamic programming algorithm to model whether changes within each block are likely a result of mutations, sequencing errors, or HGT.

Wang, W-B.↗
DOE OSTI2018

Charging Decision Making for Automated Electric Vehicles

Abstract: Overview/Significance With the emerging of autonomous driving and its application in electric vehicles, the charging decision making should be taken over by the vehicles. Autonomous electric vehicles will require the capability to make charging decisions according to the battery energy state, the travel demand and also the available charging infrastructure. The introduction of autonomous driving technology would remove the challenge of co-locating charging infrastructure with driver destinations and presents a driver-free method for EVs to reach nearby charging stations. This will significantly change the charging behavior of electric vehicles. EV driver will no longer need to be present at charging stations for charging actions. Automated EVs can drive to nearby charging stations to perform charging actions by themselves when necessary. Meanwhile, connected vehicles technology makes electric vehicles have the capability to sense and obtain pertinent information from nearby charging station networks and then calculate the corresponding costs and availability for charging. All these promising capabilities bring new opportunities to construct an automatic charging decision making system and improve energy efficiency of charging actions for automatic electric vehicles. Abstract: Methodology This research introduces optimization tools and case studies on charging decision making for automated electric vehicles under personal usage scenario. The designed optimization tools aim to provide charging strategies, i.e. the optimal choice of charging station outside home and the amount of charged energy, by considering constraints from personal daily itineraries and existing charging infrastructure. Abundant real world EV data is utilized to construct stochastic energy consumption prediction model under realistic driving conditions. Advanced dynamic programming technology is utilized to model and solve the potential multi-stage decision making process by considering realistic uncertainties of EV energy cost and dynamics of itinerary information. Large-scale simulation studies using Chicago itinerary data are demonstrated to illustrate energy benefits from automatic charging decision making for future autonomous EVs. Abstract: Results/Conclusions Optimal automatic charging decision making and its energy benefits have been studied for personal automated electric vehicles. A data-driven method based on large amount of real-world data and the corresponding real-time update algorithm have been proposed to construct multi-channel stochastic energy consumption prediction model. Based on the energy cost prediction, dynamic multi-stage charging decision-making models are established for optimal strategies during a daily itinerary. Derived charging strategies can minimize the monetary and energy cost of charging actions for autonomous vehicles. Simulations and case studies show the potential ability of autonomous electric vehicles to reduce the range anxiety and charging infrastructure dependency. Automatic charging decision making can mitigate the pain from electric vehicle charging necessity outside home. In conclusion, automated electric vehicles equipped with an appropriate automatic charging decision making system will help EV driver to relieve from heavy time cost of recharging, reduce the energy cost of performing charging actions and improve the energy efficiency in future electrified transportation system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2011

Strategic Plan for Nuclear Energy -- Knowledge Base for Advanced Modeling and Simulation (NE-KAMS)

The Nuclear Energy Computational Fluid Dynamics Advanced Modeling and Simulation (NE-CAMS) system is being developed at the Idaho National Laboratory (INL) in collaboration with Bettis Laboratory, Sandia National Laboratory (SNL), Argonne National Laboratory (ANL), Utah State University (USU), and other interested parties with the objective of developing and implementing a comprehensive and readily accessible data and information management system for computational fluid dynamics (CFD) verification and validation (V&V) in support of nuclear energy systems design and safety analysis. The two key objectives of the NE-CAMS effort are to identify, collect, assess, store and maintain high resolution and high quality experimental data and related expert knowledge (metadata) for use in CFD V&V assessments specific to the nuclear energy field and to establish a working relationship with the U.S. Nuclear Regulatory Commission (NRC) to develop a CFD V&V database, including benchmark cases, that addresses and supports the associated NRC regulations and policies on the use of CFD analysis. In particular, the NE-CAMS system will support the Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, which aims to develop and deploy advanced modeling and simulation methods and computational tools for reliable numerical simulation of nuclear reactor systems for design and safety analysis. Primary NE-CAMS Elements There are four primary elements of the NE-CAMS knowledge base designed to support computer modeling and simulation in the nuclear energy arena as listed below. Element 1. The database will contain experimental data that can be used for CFD validation that is relevant to nuclear reactor and plant processes, particularly those important to the nuclear industry and the NRC. Element 2. Qualification standards for data evaluation and classification will be incorporated and applied such that validation data sets will result in well-defined, well-characterized data. Element 3. Standards will be established for the design and operation of experiments for the generation of new validation data sets that are to be submitted to NE-CAMS that addresses the completeness and characterization of the dataset. Element 4. Standards will be developed for performing verification and validation (V&V) to establish confidence levels in CFD analyses of nuclear reactor processes; such processes will be acceptable and recognized by both CFD experts and the NRC.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

CASL Institutional Computing Report, Calendar Year 2012

CASL, the Consortium for Advanced Simulation of Light water reactors (or LWRs) is a multi-institutional, $22-25M per year, 5-year project lead by Oak Ridge National Laboratory. This project is one of DOE’s Energy Innovation Hubs and started late in the last quarter of FY10. As part of this joint work with 10 different institutions, senior LANL management agreed to provide 10% of all Institutional Computing resources at Los Alamos to the project for the life of the project. This is part of an in-kind institutional contribution LANL is making to the CASL effort. Similar contributions have been made by all national laboratory partners in CASL (ORNL, LANL, INL, and SNL)1. CASL is a highly visible and extremely valuable project for Los Alamos, with line of sight visibility and attention from the Secretary of Energy and high-impact results delivered to the nuclear energy industry. It is considered to be a model for such large programs with multiple partners, as well as a model for future simulation hubs defined by DOE. At the time of this writing, LANL leads three areas in the project. Thermal Hydraulics Methods (THM, Mark Christon, CCS-2), Materials Optimization and Performance (MPO, Chris Stanek, MST-8), and Validation and Uncertainty Quantification (VUQ, Brian Williams, CCS-6). This report summarizes the use of Institutional Computing (IC) resources by the CASL project, for calendar year 2013.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM development aims for advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability for reactor transient analyses. To facilitate the code development, SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SAM focuses on modeling advanced reactor concepts such as SFRs (sodium fast reactors), LFRs (lead-cooled fast reactors), and FHRs (fluoride-salt-cooled high temperature reactors) or MSRs (molten salt reactors). These advanced concepts are distinguished from light-water reactors in their use of single-phase, low-pressure, high-temperature, and low Prandtl number (sodium and lead) coolants. As a new code development, the initial effort has been focused on modeling and simulation capabilities of heat transfer and single-phase fluid dynamics responses in Sodium-cooled Fast Reactor (SFR) systems. The system-level simulation capabilities of fluid flow and heat transfer in general engineering systems and typical SFRs have been verified and validated. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As the code is still under ongoing development, this SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

(U) Ristra Next Generation Code Report

LANL’s Weapons Physics management (ADX) and ASC program office have defined a strategy for exascale-class application codes that follows two supportive, and mutually risk-mitigating paths: evolution for established codes (with a strong pedigree within the user community) based upon existing programming paradigms (MPI+X); and Ristra (formerly known as NGC), a high-risk/high-reward push for a next-generation multi-physics, multi-scale simulation toolkit based on emerging advanced programming systems (with an initial focus on data-flow task-based models exemplified by Legion [5]). Development along these paths is supported by the ATDM, IC, and CSSE elements of the ASC program, with the resulting codes forming a common ecosystem, and with algorithm and code exchange between them anticipated. Furthermore, solution of some of the more challenging problems of the future will require a federation of codes working together, using established-pedigree codes in partnership with new capabilities as they come on line. The role of Ristra as the high-risk/high-reward path for LANL’s codes is fully consistent with its role in the Advanced Technology Development and Mitigation (ATDM) sub-program of ASC (see Appendix C), in particular its emphasis on evolving ASC capabilities through novel programming models and data management technologies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Quasielastic lepton-nucleus scattering and the correlated Fermi gas model

The neutrino research program in the coming decades will require improved precision. A major source of uncertainty is the interaction of neutrinos with nuclei that serve as targets for such experiments. Broadly speaking, this interaction often depends, e.g., for charge-current quasielastic scattering, on the combination of “nucleon physics,” expressed by form factors, and “nuclear physics,” expressed by a nuclear model. It is important to get a good handle on both. We present a fully analytic implementation of the correlated Fermi gas model for electron-nucleus and charge-current quasielastic neutrino-nucleus scattering. The implementation is used to compare separately form factors and nuclear model effects for both electron-carbon and neutrino-carbon scattering data. Published by the American Physical Society 2025

Bhattacharya, Bhubanjyoti (ORCID:000000032238321X)↗
DOE OSTI2012

BWR ex-vessel steam explosion analysis with MC3D code

A steam explosion may occur, during a severe reactor accident, when the molten core comes into contact with the coolant water. A strong enough steam explosion in a nuclear power plant could jeopardize the containment integrity and so lead to a direct release of radioactive material to the environment. To resolve the open issues in steam explosion understanding and modeling, the OECD program SERENA phase 2 was launched at the end of year 2007, focusing on reactor applications. To verify the progress made in the understanding and modeling of fuel coolant interaction key phenomena for reactor applications a reactor exercise has been performed. In this paper the BWR ex-vessel steam explosion study, which was carried out with the MC3D code in conditions of the SERENA reactor exercise for the BWR case, is presented and discussed. The premixing simulations were performed with two different jet breakup modeling approaches and the explosion was triggered also at the expected most challenging time. For the most challenging case, at the cavity wall the highest calculated pressure was {approx}20 MPa and the highest pressure impulse was {approx}90 kPa.s. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Sockeye Heat Pipe Analysis Code Verification and Validation

Some of the most promising microreactor designs currently under development utilize heat pipe technology to transfer heat from the reactor core to the secondary side heat exchanger, due to the technology’s compactness, efficiency, passivity, and reliability. Sockeye is an engineering-scale heat pipe tool developed under the Nuclear Energy Advanced Modeling and Simulation Program to be used for the design and safety analysis of microreactors. Sockeye’s core capability lies in a 1D, two-phase, compressible flow model, used to simulate the working fluid inside the heat pipe. Sockeye is built on the Multiphysics Object-Oriented Simulation Environment framework, which allows for seamless multiphysics coupling with other Nuclear Energy Advanced Modeling and Simulation tools and can thus be used in a full-scale simulation of a microreactor assembly, which can include hundreds of heat pipes. This paper presents some initial verification and validation assessments performed for Sockeye. We demonstrate good agreement between Sockeye’s numerical results and steady-state analytic solutions for velocity and pressure drop, with differences attributable to the underlying assumptions made by the analytic solutions. We also show that Sockeye reproduces analytic predictions of key operational limits, such as the capillary limit and the sonic limit. Finally, we compare Sockeye results to experimental data for the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

BEPAM Model Code and CABBI Simulation Results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land"

This dataset contains BEPAM model code and input data to the replicate the results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land." The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output_0213-2020_Complete_daycent-agversion-[rental payment level]%_[biomass price].gms. (BEPAM-CRP model-Sep2020.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.

biomass price↗
DOE OSTI2023

Estimating the Drivers of the Cost of Saved Electricity in Utility Customer-Funded Energy Efficiency Programs

Energy efficiency programs funded by utility customers provide an electricity resource in most U.S. states, but their scale and cost of saving electricity varies significantly by state. In this paper, we explore the drivers of the cost of saved electricity in these programs with an econometric model and nearly a decade of data reported by efficiency program administrators. We found strong evidence for economies of scale and weak evidence for diseconomies of scale, which suggests that states with low levels of efficiency savings relative to retail sales can increase the size of their efficiency programs without large increases to the cost of saved electricity. We discuss examples of energy efficiency forecasting and potential modeling in light our econometric analysis and identify methodological improvements relevant to utilities and grid operators. This paper provides insights into the economics of customer-funded efficiency programs that will support regulators, utilities, and policymakers to utilize energy efficiency as a resource.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Measurements of Decay and Snapback in Nb₃Sn Accelerator Magnets at Fermilab

In recent years, Fermilab has been executing an inten-sive R&D program on Nb₃Sn accelerator magnets. This program has included dipole and quadrupole models and demonstrators for various programs and projects, including the HL-LHC accelerator upgrade project. A systematic study of the field decay and snapback during the injection portion of a simulated accelerator cycle was executed at the Fermilab Magnet Test Facility. This paper summarizes the recent measurements of the MQXFS1 short quadrupole model and discusses the results of some previously measured Nb₃Sn magnets at CERN

43 PARTICLE ACCELERATORS↗
DOE OSTI2012

REopt® [SWR-12-19]

The REopt® techno-economic decision support platform is used by NREL researchers to optimize energy systems for buildings, campuses, communities, microgrids, and more. REopt recommends the optimal mix of renewable energy, conventional generation, and energy storage technologies to meet cost savings, resilience, emissions reductions, and energy performance goals. The REopt® model provides concurrent, multiple technology integration and optimization capabilities to help organizations meet their cost savings and energy performance goals. Formulated as a mixed integer linear program, the REopt model recommends an optimally sized mix of renewable energy, conventional generation, and energy storage technologies; estimates the net present value of implementing those technologies; and provides a dispatch strategy for operating the technology mix at maximum economic efficiency. The REopt model was initially created to identify and prioritize cost-effective renewable energy projects across a portfolio of sites. The model is now also used to optimize the size and operating strategy of microgrids, storage, and energy/water systems.

Walker, Andy↗
DOE OSTI2022

Refining perovskite structures to pair distribution function data using collective Glazer modes as a basis

Structural modelling of octahedral tilts in perovskites is typically carried out using the symmetry constraints of the resulting space group. In most cases, this introduces more degrees of freedom than those strictly necessary to describe only the octahedral tilts. It can therefore be a challenge to disentangle the octahedral tilts from other structural distortions such as cation displacements and octahedral distortions. This paper reports the development of constraints for modelling pure octahedral tilts and implementation of the constraints in diffpy-CMI, a powerful package to analyse pair distribution function (PDF) data. The model in the program allows features in the PDF that come from rigid tilts to be separated from non-rigid relaxations, providing an intuitive picture of the tilting. The model has many fewer refinable variables than the unconstrained space group fits and provides robust and stable refinements of the tilt components. It further demonstrates the use of the model on the canonical tilted perovskite CaTiO 3 which has the known Glazer tilt system α + β – β – . The Glazer model fits comparably to the corresponding space-group model Pnma below r = 14 Å and becomes progressively worse than the space-group model at higher r due to non-rigid distortions in the real material.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulations of the High Temperature Test Facility using SAM

Under the support from the U.S. Department of Energy Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an effort is being pursued to support the modeling and simulation needs of high-temperature gas-cooled reactor (HTGR) technology development. There is a particular need for advanced modeling and simulation methods and tools to predict thermal-fluid behavior in the nuclear reactor primary system during safety-related transients. This report focuses on one such activity related to HTGR: developing a model of the High Temperature Test Facility (HTTF) at Oregon State University using the system-level code SAM, and using the model to understand thermal response behavior in the facility. Note this activity is coordinated with the DOE-NE’s Advanced Reactor Technology Gas-Cooled Reactor Program

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Compare Mechanistic Predictions for Doped UO 2 Mechanical Response and Other Properties with Empirical Models and Experimental Measurements

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program develops predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity, high resolution fuel performance tool at the engineering scale. As part of its development, additional modeling capabilities and improvements have been developed for relevant fuel forms. In this work, a fuel creep deformation model for Cr-doped fuel has been implemented into BISON, along with improvements to the empirical UO 2 fuel creep model based on experimental data and improvements to the radial power factor calculation for doped fuels. This work allows for more accurate simulation analyses for both UO 2 and doped-UO 2 fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗