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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 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Application of Quantum Machine Learning to High Energy Physics Analysis at LHC Using Quantum Computer Simulators and Quantum Computer Hardware

Machine learning enjoys widespread success in High Energy Physics (HEP) analyses at LHC. However the ambitious HL-LHC program will require much more computing resources in the next two decades. Quantum computing may offer speed-up for HEP physics analyses at HL-LHC, and can be a new computational paradigm for big data analyses in High Energy Physics.We have successfully employed three methods (1) Variational Quantum Classifier (VQC) method, (2) Quantum Support Vector Machine Kernel (QSVM-kernel) method and (3) Quantum Neural Network (QNN) method for two LHC flagship analyses: ttH (Higgs production in association with two top quarks) and H->mumu (Higgs decay to two muons, the second generation fermions). We shall address the progressive improvements in performance from method (1) to method (3).We will present our experiences and results of a study on LHC High Energy Physics data analyses with IBM Quantum Simulator and Quantum Hardware (using IBM Qiskit framework), Google Quantum Simulator (using Google Cirq framework), and Amazon Quantum Simulator (using Amazon Braket cloud service). The work is in the context of a Qubit platform (a gate-model quantum computer). Taking into account the present limitation of hardware access, different quantum machine learning methods are studied on simulators and the results are compared with classical machine learning methods (BDT, classical Support Vector Machine and classical Neural Network). Furthermore, we do apply quantum machine learning on IBM quantum hardware to compare performance between quantum simulator and quantum hardware. The work is performed by an international and interdisciplinary collaboration with the Department of Physics and Department of Computer Sciences of University of Wisconsin, CERN Quantum Technology Initiative, IBM Research Zurich, IBM T.J. Watson Research Center, Fermilab Quantum Institute, BNL Computational Science Initiative, State University of New York at Stony Brook, and Quantum Computing and AI Research of Amazon Web Services. This work pioneers a close collaboration of academic institutions with industrial corporations in the High Energy Physics analyses effort. Though the size of event samples in future HL-LHC physics and the limited number of qubits pose some challenges to the Quantum Machine learning studies for High Energy Physics, more advanced quantum computers with larger number of qubits, reduced noise and improved running time (as envisioned by IBM and Google) may outperform classical machine learning in both classification power and in speed.Although the era of efficient quantum computing may still be years away, we have made promising progress and obtained preliminary results in applying quantum machine learning to High Energy Physics. A PROOF OF PRINCIPLE.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1986

Comparative energetics diagnosis of the observed and simulated blockings in the Northern Hemisphere

The blocking phenomena, in particular winter blocking, are stuided using energetic diagnostics. Sequences of blockings during the FGGE winter and summer in observed and simulated circulations, and energy transformations associated with blockings are examined. It is observed that the simulation of the Northern Hemisphere circulation correlates better with the observed circulation during summer than during winter. It is noted that the observed winter blockings are maintained by the supply of kinetic energy to the ultralong waves from the shorter cyclone scales through nonlinear wave-wave interaction; in the simulated winter blocking, the energy converted at the cyclone scale cascades down to the shorter wave range; and the summer blockings are supported by the baroclinic conversion of long waves in both the observed and simulated circulations.

Kung, Ernest C.↗
DOE OSTI2021

A Flow Rate Dependent 1D Model for Thermally Stratified Hot-Water Energy Storage

Stratified tank models are used to simulate thermal storage in applications such as residential or commercial hot-water storage tanks, chilled-water storage tanks, and solar thermal systems. The energy efficiency of these applications relates to the system components and the level of stratification maintained during various flow events in the tank. One-dimensional (1D) models are used in building energy simulations because of the short computation time but often do not include flow-rate dependent mixing. The accuracy of 1D models for plug flow, plug flow with axial conduction, and two convection eddy-diffusivity models were compared with experimental data sets for discharging a 50-gal residential tank and recharging the tank with hot water from an external hot-water source. A minimum and maximum relationship for the eddy diffusivity factor were found at Re <2100 and >10,000 for recirculation of hot water to the top of the tank and vertical tubes inletting cold water at the bottom. The root mean square error decreased from >4 °C to near 2 °C when considering flow-based mixing models during heating, while the exponential decay of the eddy diffusion results in a root mean square error reduction of 1 °C for cone-shaped diffusers that begin to relaminarize flow at the inlet.

1D flow model↗
DOE OSTI2014

SU-E-T-242: Monte Carlo Simulations Used to Test the Perturbation of a Reference Ion Chamber Prototype Used for Small Fields

Purpose: To study the perturbation due to the use of a novel Reference Ion Chamber designed to measure small field dosimetry (KermaX Plus C by IBA). Methods: Using the Phase-space files for TrueBeam photon beams available by Varian in IAEA-compliant format for 6 and 15 MV. Monte Carlo simulations were performed using BEAMnrc and DOSXYZnrc to investigate the perturbation introduced by a reference chamber into the PDDs and profiles measured in water tank. Field sizes ranging from 1×1, 2×2,3×3, 5×5 cm2 were simulated for both energies with and without a 0.5 mm foil of Aluminum which is equivalent to the attenuation equivalent of the reference chamber specifications in a water phantom of 30×30×30 cm3 and a pixel resolution of 2 mm. The PDDs, profiles, and gamma analysis of the simulations were performed as well as a energy spectrum analysis of the phase-space files generated during the simulation. Results: Examination of the energy spectrum analysis performed shown a very small increment of the energy spectrum at the build-up region but no difference is appreciated after dmax. The PDD, profiles and gamma analysis had shown a very good agreement among the simulations with and without the Al foil, with a gamma analysis with a criterion of 2% and 2mm resulting in 99.9% of the points passing this criterion. Conclusion: This work indicates the potential benefits of using the KermaX Plus C as reference chamber in the measurement of PDD and Profiles for small fields since the perturbation due to in the presence of the chamber the perturbation is minimal and the chamber can be considered transparent to the photon beam.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Airside HVAC BESTEST: HVAC Air-Distribution System Model Test Cases for ASHRAE Standard 140

This paper summarizes recent work to develop new airside HVAC equipment model analytical verification test cases for ANSI/ASHRAE Standard 140, Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. The analytical verification test method allows comparison of simulation results from a wide variety of building energy simulation programs with quasi-analytical solutions, further described below. Standard 140 is widely cited for evaluating software for use with performance-path energy efficiency analysis, in conjunction with well-known energy-efficiency standards including ASHRAE Standard 90.1, the International Energy Conservation Code, and other international standards. Airside HVAC Equipment is a common area of modelling not previously explicitly tested by Standard 140. Integration of the completed test suite into Standard 140 is in progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A general solution strategy of modified power method for higher mode solutions

A general solution strategy of the modified power iteration method for calculating higher eigenmodes has been developed and applied in continuous energy Monte Carlo simulation. The new approach adopts four features: 1) the eigen decomposition of transfer matrix, 2) weight cancellation for higher modes, 3) population control with higher mode weights, and 4) stabilization technique of statistical fluctuations using multi-cycle accumulations. The numerical tests of neutron transport eigenvalue problems successfully demonstrate that the new strategy can significantly accelerate the fission source convergence with stable convergence behavior while obtaining multiple higher eigenmodes at the same time. The advantages of the new strategy can be summarized as 1) the replacement of the cumbersome solution step of high order polynomial equations required by Booth's original method with the simple matrix eigen decomposition, 2) faster fission source convergence in inactive cycles, 3) more stable behaviors in both inactive and active cycles, and 4) smaller variances in active cycles. Advantages 3 and 4 can be attributed to the lower sensitivity of the new strategy to statistical fluctuations due to the multi-cycle accumulations. The application of the modified power method to continuous energy Monte Carlo simulation and the higher eigenmodes up to 4th order are reported for the first time in this paper. -- Graphical abstract: -- Highlights: •Modified power method is applied to continuous energy Monte Carlo simulation. •Transfer matrix is introduced to generalize the modified power method. •All mode based population control is applied to get the higher eigenmodes. •Statistic fluctuation can be greatly reduced using accumulated tally results. •Fission source convergence is accelerated with higher mode solutions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Techno-Economic Simulation Approach in Preparation of Employing Renewable Energies for Process Industry

The energy system of process industry are faced with a new unprecedented challenge. Renewable energies should be incorporated but single of them cannot meet its energy demand of high degree and a large quantity. This paper investigates a simulation framework to compute the capacity of multiple energy sources including solar, wind power, diesel and batteries. The framework involves actual renewable energy supply and demand profile generation and supply demand matching. Eight configurations of different supply options are evaluated to illustrate the applicability of the proposed framework with some remarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Energy Implications of Retrofitting Retail Sector Rooftop Units With Stepped Speed and Variable-Speed Functionality

Commercial retailers understand that retrofitting constant-speed RTU fan motors with stepped- or variable-speed alternatives could save significant energy in most U.S. climate zones. However, they lack supporting data, both real-world and simulation based, on the cost effectiveness and climate zone-specific energy savings associated with this measure. Thus, building managers and engineers havebeen unable to present a compelling business case for fan motor upgrades to upper management. This study uses whole-building energy simulation to estimate the energy impact of this type of measure so retailers can determine its economic feasibility.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

SU-E-T-78: Comparison of Dose-Averaged Linear Energy Transfer Calculation Methods Used in Monte Carlo Simulations of Clinical Proton Beams

Purpose: To evaluate the differences in dose-averaged linear energy transfer (LETd) maps calculated in water by means of different strategies found in the literature in proton therapy Monte Carlo simulations and to compare their values with dose-mean lineal energy microdosimetry calculations. Methods: The Geant4 toolkit (version 9.6.2) was used. Dose and LETd maps in water were scored for primary protons with cylindrical voxels defined around the beam axis. Three LETd calculation methods were implemented. First, the LETd values were computed by calculating the unrestricted linear energy transfer (LET) associated to each single step weighted by the energy deposition (including delta-rays) along the step. Second, the LETd was obtained for each voxel by computing the LET along all the steps simulated for each proton track within the voxel, weighted by the energy deposition of those steps. Third, the LETd was scored as the quotient between the second momentum of the LET distribution, calculated per proton track, over the first momentum. These calculations were made with various voxel thicknesses (0.2 – 2.0 mm) for a 160 MeV proton beamlet and spread-out Bragg Peaks (SOBP). The dose-mean lineal energy was calculated in a uniformly-irradiated water sphere, 0.005 mm radius. Results: The value of the LETd changed systematically with the voxel thickness due to delta-ray emission and the enlargement of the LET distribution spread, especially at shallow depths. Differences of up to a factor 1.8 were found at the depth of maximum dose, leading to similar differences at the central and distal depths of the SOBPs. The third LETd calculation method gave better agreement with microdosimetry calculations around the Bragg Peak. Conclusion: Significant differences were found between LETd map Monte Carlo calculations due to both the calculation strategy and the voxel thickness used. This could have a significant impact in radiobiologically-optimized proton therapy treatments.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2012

Annealing simulation of cascade damage in -Fe- Damage energy and temperature dependence analyses

In this paper, kinetic Monte Carlo method was applied to investigate the long time evolution of cascade damage prepared by molecular dynamics simulations in -Fe up to recoil energy of more than 200 keV. We conducted thorough investigation on how the surviving defects vary with cascade damage energy and annealing temperature. The results can be used for input parameters of rate equations to simulate microstructural evolution under irradiation. The study also suggested that neighboring sub-cascades evolves almost independently during annealing, and that the temperature dependence of the annealing results can be explained by the temperature dependence of vacancy-migration and vacancy-dissociation probabilities.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

Seismic Soil-Structure Interaction Analyses of a Deeply Embedded Model Reactor – SASSI Analyses

This report summarizes the SASSI analyses of a deeply embedded reactor model performed by BNL and CJC and Associates, as part of the seismic soil-structure interaction (SSI) simulation capability project for the NEAMS (Nuclear Energy Advanced Modeling and Simulation) Program of the Department of Energy. The SASSI analyses included three cases: 0.2 g, 0.5 g, and 0.9g, all of which refer to nominal peak accelerations at the top of the bedrock. The analyses utilized the modified subtraction method (MSM) for performing the seismic SSI evaluations. Each case consisted of two analyses: input motion in one horizontal direction (X) and input motion in the vertical direction (Z), both of which utilized the same in-column input motion. Besides providing SASSI results for use in comparison with the time domain SSI results obtained using the DIABLO computer code, this study also leads to the recognition that the frequency-domain method should be modernized so that it can better serve its mission-critical role for analysis and design of nuclear power plants.

42 ENGINEERING↗
DOE OSTI2025

Geographically Distributed Co-Simulation for the Interplay of Integrated Energy Systems and Power Grid

The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).

Co-simulation↗
DOE OSTI2023

A machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)

Tropical forest dynamics play a crucial role in the global carbon, water, and energy cycles. However, realistically simulating the dynamics of competition and coexistence between different plant functional types (PFTs) in tropical forests remains a significant challenge. This study aims to improve the modeling of PFT coexistence in the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a vegetation demography model implemented in the Energy Exascale Earth System Model (E3SM) land model (ELM), ELM-FATES. Specifically, we explore (1) whether plant trait relationships established from field measurements can constrain ELM-FATES simulations and (2) whether machine learning (ML)-based surrogate models can emulate the complex ELM-FATES model and optimize parameter selections to improve PFT coexistence modeling. We conducted three ensembles of ELM-FATES experiments at a tropical forest site near Manaus, Brazil. By comparing the ensemble experiments without (Exp-CTR) and with (Exp-OBS) consideration of observed trait relationships, we found that accounting for these relationships slightly improves the simulations of water, energy, and carbon variables when compared to observations but degrades the simulation of PFT coexistence. Using ML-based surrogate models trained on Exp-CTR, we optimized the trait parameters in ELM-FATES and conducted another ensemble of experiments (Exp-ML) with these optimized parameters. The proportion of PFT coexistence experiments significantly increased from 21 % in Exp-CTR to 73 % in Exp-ML. After filtering the experiments that allow for PFT coexistence to agree with observations (within 15 % tolerance), 33 % of the Exp-ML experiments were retained, which is a significant improvement compared to the 1.4 % in Exp-CTR. Exp-ML also accurately reproduces the annual means and seasonal variations in water, energy, and carbon fluxes and the field inventory of aboveground biomass. This study represents a reproducible method that utilizes machine learning to identify parameter values that improve model fidelity against observations and PFT coexistence in vegetation demography models for diverse ecosystems. Our study also suggests the need for new mechanisms to enhance the robust simulation of coexisting plants in ELM-FATES and has significant implications for modeling the response and feedbacks of ecosystem dynamics to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Simulation of the dissipated and stored energy under deformation and failure of metallic materials

This work is devoted to the development of the statistical model of the structural defect evolution which was developed at the Institute of continuous media mechanics UB RAS. This model takes into account stochastic properties of the defect evolution process, nonlinear interaction of defects, and connection between microplasticity and damage accumulation. The obtained constitutive equations allow us to propose a model of the energy storage and dissipation in the process of plastic deformation and failure of metallic materials. The obtained relations were adapted for standard finite-element package. Applicability of this model was demonstrated in three-dimensional simulation of the strain localization and crack propagation in metals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Probabilistic Resilience of DER Systems - A Simulation Assisted Optimization Approach

Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-tlie-meter distributed energy resource system to sustain a site's critical loads during a pre-defined outage period. With the fixed system design, we then propose an outage simulation approach to estimate the resilience potential of the DER system to sustain loads beyond the fixed outage period - a yearlong resilience performance analysis. We apply statistical analysis to assess the system's resilience performance over a broader parametric problem space on an hourly, monthly, and yearly basis. We demonstrate the impact of the pre-defined outage period on the resilience performance through a case study. Results show that the probability of surviving a random outage of a given duration changes from 20% to 95% when the outage is modeled for a weekday instead of a weekend for the given load-profile.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2025

Investigating the relationship between simulation parameters and flow variables in simulating atmospheric gravity waves for wind energy applications

Wind farms, particularly offshore clusters, are becoming larger than ever before. Besides influencing the surface wind flow and the inflow for downstream wind farms, large wind farms can trigger atmospheric gravity waves in the inversion layer and the free atmosphere aloft. Wind-farm-induced gravity waves can cause adverse pressure gradients upstream of the wind farm, which contribute to the global blockage effect, and can induce favorable pressure gradients above and downstream of the wind farm that enhance wake recovery. Numerical modeling is a powerful means of studying these wind-farm-induced atmospheric gravity waves, but it comes with the challenge of handling spurious reflections of these waves from domain boundaries. Typically, approaches which employ radiation boundary conditions and forcing zones are used to avoid these reflections. However, the simulation setup of these approaches relies heavily on ad hoc processes. For instance, the widely used Rayleigh damping method requires ad hoc tuning to produce a setup that may only produce satisfactory results for a particular case. To provide more systematic guidance on setting up realistic simulations of atmospheric gravity waves, we conduct a large-eddy simulation (LES) study of flow over a 2D hill and through a wind farm canopy that explores the optimum domain size and damping layer setup depending on the fundamental parameters which determine the flow characteristics. In this work, we only consider linearly stratified conditions (i.e., no inversion layer), thereby focusing on internal gravity waves in the free atmosphere and their reflections from the domain boundaries. This type of flow is governed by a single Froude number, which dictates most of the internal wave properties, such as wavelength, amplitude, and direction. This, in turn, will dictate the optimum domain size and Rayleigh damping layer setup. We find the effective horizontal and vertical wavelengths (the representative wavelengths of the entire wave spectrum) to be the appropriate length scales to size the domain and damping layer thickness, and the optimal Rayleigh damping coefficient scales with the Brunt–Väisälä frequency. Considering Froude numbers seen in wind farm applications, we propose recommendations to limit the reflections to less than 10 % of the total upward-propagating wave energy. Typically, damping is done at the top boundary, but given the non-periodic lateral boundary conditions of practical wind farm simulation domains, we find that damping the inflow–outflow boundaries is of equal importance to damping the top boundary. The Brunt–Väisälä frequency-normalized damping coefficient should be between 1 and 10. The damping layer thickness should be at least one effective vertical wavelength; damping layers exceeding 1.5 times the vertical wavelength are found to be unnecessary. The domain length and height should accommodate at least one effective horizontal and vertical wavelength, respectively. Moreover, Rayleigh damping does not damp the waves completely, and the non-damped energy might accumulate over the simulation time.

17 WIND ENERGY↗
DOE OSTI2022

A Comprehensive Simulation Study to Evaluate Future Vehicle Energy and Cost Reduction Potential

Under the umbrella of EERE’s Office of Sustainable Transportation, the U.S. Department of Energy’s (DOE) Vehicle Technologies Office (VTO) and Hydrogen and Fuel Cell Technologies Office (HFTO) seek to develop sustainable, affordable, and efficient technologies for transportation of goods and people. Translating investments in advanced transportation component technologies and powertrains to estimate the potential for vehicle-level fuel savings is critical to understanding DOE’s impact and success in this mission For this study, Argonne National Laboratory (Argonne) simulated technologies funded by VTO and HFTO for light-duty vehicles across the following: Powertrain configurations (conventional, power-split hybrid electric vehicle, extended-range electric vehicle, battery electric drive, and fuel-cell vehicles); Vehicle classes (compact car, mid-size car, small sport utility vehicle [SUV], mid-size SUV, and pickup truck); Fuels (gasoline, diesel, natural gas, hydrogen, and battery electricity). We assessed each technology for five different timeframes: laboratory years 2015 (reference), 2020, 2025, 2030, and 2045. We assumed a delay of 5 years between laboratory year and model year (i.e., the year the technology is introduced into production). Finally, we included uncertainties for both technology performance and cost by considering two cases (note that these cases are not intended as predictions of future performance): Low case , aligned with DOE technology manager estimates of expected original equipment manufacturer (OEM) improvements based on business as usual regulatory and market environments; High case , aligned with aggressive technology advancements based on research and development (R&D) targets developed through support by VTO and HFTO. We estimated the energy and cost impact of different technologies using Autonomie (Argonne undated), a state-of-the-art vehicle system simulation tool developed by Argonne and used to assess the energy consumption, performance, and cost of multiple advanced vehicle technologies. The tool comprises a complete set of vehicle models to assess impacts across a wide range of classes (from light- to heavy-duty), powertrain configurations (from conventional to hybrid electric vehicles [HEVs], fuel cell electric vehicles [FCEVs], plug-in hybrid electric vehicles [PHEVs], and battery electric vehicles [BEVs]), components, and control strategies, including vehicle-level and component-level controls developed and calibrated using dynamometer test data. Autonomie has been used to support a wide range of studies: analyzing various component technologies, sizing powertrain components to meet different vehicle requirements, comparing the benefits of powertrain configurations, optimizing both heuristic and route-based vehicle energy control, and predicting transportation energy use when paired with a traffic modeling tool such as POLARIS. This report documents the assumptions made and the vehicle-level energy consumption benefits and associated technology costs estimated for various types of light-duty vehicles. Details regarding vehicle assumptions and simulation results are available in the spreadsheets accompanying this report.

08 HYDROGEN↗
DOE OSTI2019

Moisture Transfer in Commercial Buildings Due to Air Leakage: A New Feature in the Online Airtightness Savings Calculator

Air leakage through the building envelopes is responsible for a large amount of energy use. The US Department of Energy Windows and Building Envelope Research and Development Roadmap for Emerging Technologies states that, in 2010, air infiltration was responsible for 20% of primary energy consumption attributable to the fenestration and building envelopes of commercial buildings. Despite this fact, improving airtightness is not always recognized by commercial building owners, as they have been slow in acknowledging and diminishing the detrimental effects of air leakage on energy use, comfort, indoor air quality, and building material durability.The design and construction industry would benefit from a credible, easy-to-use tool that estimates potential energy and financial savings in a standardized manner so designers and contractors can give building owners compelling reasons to invest in reducing air leakage. In 2016–2017, Oak Ridge National Laboratory, the National Institute of Standards and Technology, the Air Barrier Association of America, and the US-China Clean Energy Research Center for Building Energy Efficiency collaborated to develop an online calculator. This user-friendly calculator is free to the public and uses the simulation results of the whole building energy simulation tool EnergyPlus and the airflow simulation tool CONTAM. In 2018–2019, the calculator was expanded to add moisture transfer calculations given that air leakage through the building envelope can have a significant impact on moisture transfer and associated impacts. Four more commercial building types were also added to the existing database of three building types as part of this update. This paper describes the procedure used to calculate moisture transfer due to air leakage and provides examples that demonstrate the moisture transfer for each of the seven commercial building types that are currently part of the calculator.

Shrestha, Som↗