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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Initial Recognition of a Cellodextrin Chain in the Cellulose-Binding Tunnel May Affect Cellobiohydrolase Directional Specificity

Cellobiohydrolases processively hydrolyze glycosidic linkages in individual polymer chains of cellulose microfibrils, and typically exhibit specificity for either the reducing or nonreducing end of cellulose. Here in this article, we conduct molecular dynamics simulations and free energy calculations to examine the initial binding of a cellulose chain into the catalytic tunnel of the reducing-end-specific Family 7 cellobiohydrolase (Cel7A) from Hypocrea jecorina. In unrestrained simulations, the cellulose diffuses into the tunnel from the -7 to the -5 positions, and the associated free energy profiles exhibit no barriers for initial processivity. The comparison of the free energy profiles for different cellulose chain orientations show a thermodynamic preference for the reducing end, suggesting that the preferential initial binding may affect the directional specificity of the enzyme by impeding nonproductive (nonreducing end) binding. Finally, the Trp-40 at the tunnel entrance is shown with free energy calculations to have a significant effect on initial chain complexation in Cel7A.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

OBJECT KINETIC MONTE CARLO SIMULATIONS OF RADIATION DAMAGE IN TUNGSTEN

We used our recently developed lattice-based object kinetic Monte Carlo code; KSOME [1] to carryout simulations of radiation damage in bulk tungsten at temperatures of 300, and 2050 K for various dose rates. Displacement cascades generated from molecular dynamics (MD) simulations for PKA energies at 60, 75 and 100 keV provided residual point defect distributions. It was found that the number density of vacancies in the simulation box does not change with dose rate while the number density of vacancy clusters slightly decreases with dose rate indicating that bigger clusters are formed at larger dose rates. At 300 K, although the average vacancy cluster size increases slightly, the vast majority of vacancies exist as mono-vacancies. At 2050 K no accumulation of defects was observed during irradiation over a wide range of dose rates for all PKA energies studied in this work.

Nandipati, Giridhar↗
DOE OSTI2015

Effects of Home Energy Management Systems on Distribution Utilities and Feeders Under Various Market Structure; NREL (National Renewable Energy Laboratory)

The combination of distributed energy resources (DER) and retail tariff structures to provide benefits to both utility consumers and the utilities is not well understood. To improve understanding, an Integrated Energy System Model (IESM) is being developed to simulate the physical and economic aspects of DER technologies, the buildings where they reside, and feeders servicing them. The IESM was used to simulate 20 houses with home energy management systems on a single feeder under a time-of-use (TOU) tariff to estimate economic and physical impacts on both the households and the distribution utilities. Home energy management systems (HEMS) reduce consumers’ electric bills by precooling houses in the hours before peak electricity pricing. Utilization of HEMS reduce peak loads during high price hours but shifts it to hours with off-peak and shoulder prices, resulting in a higher peak load. used to simulate 20 houses with home energy management systems on a single feeder under a time-of-use (TOU) tariff to estimate economic and physical impacts on both the households and the distribution utilities. Home energy management systems (HEMS) reduce consumers’ electric bills by precooling houses in the hours before peak electricity pricing. Utilization of HEMS reduce peak loads during high price hours but shifts it to hours with off-peak and shoulder prices, resulting in a higher peak load.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Mass and energy transfer across the Earth's magnetopause caused by vortex-induced reconnection: Mass and energy transfer by K-H vortex

When the interplanetary magnetic field (IMF) is strongly northward, a boundary layer that contains a considerable amount of plasma of magnetosheath origin is often observed along and earthward of the low-latitude magnetopause. Such a pre-existing boundary layer, with a higher density than observed in the adjacent magnetosphere, reduces the local Alfvén speed and allows the Kelvin-Helmholtz instability (KHI) to grow more strongly. We employ a three-dimensional fully kinetic simulation to model an event observed by the Magnetospheric Multiscale (MMS) mission in which the spacecraft detected substantial KH waves between a pre-existing boundary layer and the magnetosheath during strong northward IMF. Initial results of this simulation [Nakamura et al., 2017] have successfully demonstrated ion-scale signatures of magnetic reconnection induced by the non-linearly developed KH vortex, which are quantitatively consistent with MMS observations. Furthermore, we quantify the simulated mass and energy transfer processes driven by this vortex-induced reconnection (VIR) and show that during this particular MMS event (i) mass enters a new mixing layer formed by the VIR more efficiently from the pre-existing boundary layer side than from the magnetosheath side, (ii) mixed plasmas within the new mixing layer convect tailward along the magnetopause at more than half the magnetosheath flow speed, and (iii) energy dissipation in localized VIR dissipation regions results in a strong parallel electron heating within the mixing layer. Finally, the quantitative agreements between the simulation and MMS observations allow new predictions that elucidate how the mass and energy transfer processes occur near the magnetopause during strong northward IMF.

58 GEOSCIENCES↗
DOE OSTI2016

On the stability of the fragments and associated properties at the peak center-of-mass energy of light fragments

We simulate semi-central symmetric system reactions, for center-of-mass energies at which maximal number of light fragments (2 ≤ A ≤ 4) occurs and at a fixed E{sub c.m.} = 60 AMeV. The study was carried out with soft EOS using isospin-dependent quantum molecular dynamics (IQMD) model. We studied various properties of fragments at peak E{sub c.m.} and also at constant energy (E{sub c.m.} = 60 AMeV) to find out the relative difference between the properties at both energies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Blow-off momentum from melt and vapor in nuclear deflection scenarios

For Earth-impacting objects that are large in size or have short warning times nuclear explosives are an effective threat mitigation response. Nuclear-based deflection works by means of conservation of momentum: as material is heated by incoming photons and neutrons it is ejected from the body which imparts momentum to the remaining mass of the asteroid. Predicting the complete response of a particular object is difficult, since the ejecta size and velocity distributions rely heavily on the unknown, complicated internal structure of the body. However, lower bounds on the blow-off momentum can be estimated using the melted and vaporized surface material. In this paper, we model the response of a one-dimensional SiO2 surface to monoenergetic soft X-ray, hard X-ray and neutron sources using Arbitrary Lagrangian–Eulerian radiation/hydrodynamic simulations. Errors in the blow-off momentum due to our hydrodynamic mesh resolution are quantified and inform zone sizing that balances numerical discretization error with computational efficiency. We explore deposited energy densities ranging from 1.1 to 200 times the melt energy density for SiO2, and develop an approximate relation that gives the mesh resolution needed for a desired percent error in the blow-off momentum as a function of deposited energy density and melt depth. Using these mesh constraints, the response of our one-dimensional SiO2 surface to the energy sources is simulated, and lower bounds are placed on the melt/vapor blow-off momentum as a function of deposited energy density and source energy type.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Extension and Demonstration of NEAMS Multiphysics Tools to Lead-Cooled, Sodium-Cooled, and Molten Salt Fast Reactor Applications

The SHARP toolkit is a high-fidelity reactor simulation tool developed under the U.S. Department of Energy, Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. SHARP toolkit is comprised of the neutronics module PROTEUS thermal hydraulics module Nek5000, and structural mechanics module Diablo. During FY17 and FY18, the PROTEUS and Nek5000 components of SHARP were applied to solve challenging sodium-cooled fast reactor (SFR) problems. In particular, selected hot channel factors (HCF) for a prototype metal-fueled SFR design (the AFR-100) were analyzed in high fidelity, and the “SHARP zooming capability” for SFRs was developed and demonstrated to reduce computational expense for full core problems in cases where detailed data is needed in selected fuel assemblies. After the previous success applying SHARP to challenging SFR problems, the focus in FY19 expanded to additional fast reactor applications: lead cooled fast reactors (LFR), sodium cooled fast reactors (SFR), and fast molten salt reactors (MSR). The specific technical tasks were (1) assessment of hot channel factors for LFR, for which no data currently exists, (2) implementation of a gamma transport capability in the PROTEUS solvers to extend the zooming capability to non-fueled assemblies, (3) demonstration of zooming capability in assemblies of the Versatile Test Reactor (VTR), and (4) development of a new coupled capability for simulating fast MSRs, specifically modeling precursor transport inside and outside the core. The progress on tasks (1) and (3) are discussed primarily in this document. Tasks (2) and (4) are briefly mentioned in this document, and the interested reader is referred to separate reports for detailed information. First-of-a-kind hot channel factor (HCF) estimation for LFR with high fidelity codes (PROTEUS/Nek5000) was successfully demonstrated in this study. Selected HCF were computed and compared with SFR data (AFR-100, EBR-II). The findings confirm that different reactor types, design parameters and uncertainties lead to different HCFs. Careful estimation of HCF for a specific design is necessary to obtain appropriate HCFs. In addition to improvement in HCF accuracy, high fidelity tools generate data to help the designer better understand the mechanism of the impact from these uncertainties. For example, the impact of cladding thickness manufacturing tolerance resulted in non-intuitive effects in the corner pins of the LFR assembly. This procedure of computing HCF using high fidelity models shows promise and flexibility for being repeated for any arbitrary reactor of choice, since these tools are targeted to solve many reactor types and geometries. Progress was made towards extending the previously demonstrated SHARP zooming capability to non-fueled SFR assemblies. In particular, a gamma transport capability was implemented in both high fidelity PROTEUS solvers in order to accurately account for heat deposition caused by gamma particles, which accounts for ~10% of total core power. Neutronics verification cases were carried out for a candidate Versatile Test Reactor (VTR) design using the new gamma transport capability in PROTEUS. Comparisons were made with continuous energy MCNP calculations and shown to agree well. The models for the full core design with heterogeneous control and fuel assemblies is in progress and will be completed in FY20. In the fast molten salt reactor (MSR) domain, a new capability was developed to model the flow of neutron precursors both inside and outside of the core, which impacts the effective delayed neutron fraction of the system. The PROTEUS-SN and PROTEUS-NODAL solvers were coupled to Nek5000 in order to simulate precursor flow. The workflows were demonstrated on test problems. The fast MSR modeling capability was supported under two other work packages, and comprehensive details are included in a separate report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Simulation of a High-Confinement Tidal Energy Array (Abstract)

When the projected area of a current turbine array occupies a substantial fraction of a tidal or river channel cross-sectional area, the confinement associated with the channel boundaries substantially increases turbine efficiency. This effect can be exploited to substantially reduce the levelized cost of energy for current turbine arrays. However, the presence of such an array will affect inflow velocity, water depth, and circulation in the surrounding area. This has implications for array performance and environmental impacts. This project combines existing numerical modeling capability from PNNL with an understanding of confined array performance from UW. The work will 1) Simulate tidal currents and water surface elevation in a regional circulation model that includes the Knik Arm site at appropriate resolution; 2) Incorporate a varying thrust coefficient into this model that reflects the outcomes of tidal hydrodynamic simulations of confined turbine arrays; 3) Use the model to determine the effects of array operation on water levels and inflow conditions as a function of different blockage ratios and control strategies; and 4) Identify the “far field” environmental implications of operating an array of this type. UW will use the outputs from this model to evaluate the implications of “feedback effects” and variable inflow conditions on levelized cost of energy estimates for a confinement exploiting array of cross-flow turbines.

16 TIDAL AND WAVE POWER↗
DOE OSTI2025

A new way to unravel the $^{12}$C($\alpha $,$\gamma $)$^{16}$O cross section components using neural networks

The $^{12}$C($\alpha $,$\gamma $)$^{16}$O reaction rate is crucial in determining the carbon-to-oxygen abundance ratio in stellar nucleosynthesis. Measuring this reaction’s cross section at stellar energies is challenging due to its extremely small value, approximately 10 -17 barn at E c.m. = 300 keV. To address this, R-matrix calculations are employed to extrapolate data to lower energies, requiring a comprehensive understanding of each contribution to the cross section. The dominant contributions to the cross section at stellar energies arise from electric dipole (E1) and electric quadrupole (E2) transitions to the ground state of 16 O, along with a significant cascade contribution. Traditionally, these contributions have been separated using the γ-ray angular distribution. In this work, we propose a novel technique using the energy distribution of the 16 O recoils at the focal plane. This method involves a neural network trained on detailed Monte Carlo simulations of the energy distribution of recoils transported through the recoil mass separator ERNA. This approach enables the simultaneous determination of all three contributions with errors around 10% in the energy range E c.m. = 1.0–2.2 MeV. In conclusion, by employing this new technique, we aim to significantly improve the accuracy of determining the cross section of the $^{12}$C($\alpha $,$\gamma $)$^{16}$O reaction at astrophysical energies.

Astrochemistry↗
DOE OSTI2020

Creating a Detector Response Matrix for the Micro-Calorimeter

To better understand the results from the micro calorimeter, a detector response matrix (DRM) was generated. This will allow to predict source responses, which in turn will improve the confidence in the instrument. To generate a DRM, the simulation package Rapid Adaptable Multi-threaded Particle and Radiation Transport Simulation (RAMPART) that utilizes underlying Geant4 libraries for particle transport was used to generate the simulation. A flat energy input spectrum ranging from 0 keV to 3000 keV was used to generate the response. 37 x 10 9 particles were simulated. In this report, the details and findings are presented.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Python Library for Monte Carlo Simulations with Ab Initio and Machine-Learned Interatomic Potentials

There is a growing need in the simulation community for software that provides a transparent, reproducible, usable, and extensible (TRUE) Monte Carlo (MC) simulation framework employing energies from ab initio methods and machine-learning interatomic potentials (MLIPs). We introduce a Python library (ASE-MC) that adds Monte Carlo functionality to the Atomic Simulation Environment (ASE) package. Now, we can combine the powerful tools used to build systems and perform ab initio and MLIP in ASE with MC simulation algorithms to sample the configurational space with a concise Python script. After presenting the design philosophy, we demonstrate the flexibility of our approach using selected examples. These example simulations include liquid water described with a message-passing MLIP in the canonical and isothermal–isobaric ensembles, sampling the characteristic dihedral angle of biphenyl and comparing an MLIP to first-principles calculations, and a grand canonical Monte Carlo simulation of ammonia adsorption on Pt(111). These examples showcase the main features of the software, which include flexibility in the choice of ab initio or MLIP engine, ab initio or MLIP grand canonical MC with cavity bias insertions and deletions, the ability to add custom MC moves to the move set, and how users can condense complex MC workflows into a single Python script. Finally, this library serves as a framework for reproducible Monte Carlo simulations, facilitating easy reproduction of the work and application to new systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Internal wave energy radiated from a turbulent mixed layer

We examine mixed-layer deepening and the generation of internal waves in stratified fluid resulting from turbulence that develops in response to an applied surface stress. In laboratory experiments the stress is applied over the breadth of a finite-length tank by a moving roughened conveyor belt. The turbulence in the shear layer is characterized using particle image velocimetry to measure the kinetic energy density. The internal waves are measured using synthetic schlieren to determine their amplitudes, frequencies, and energy density. We also perform fully nonlinear numerical simulations restricted to two dimensions but in a horizontally periodic domain. These clearly demonstrate that internal waves are generated by transient eddies at the integral length scale of turbulence and which translate with the background shear along the base of the mixed layer. In both experiments and simulations we find that the energy density of the generated waves is 1%–3% of the turbulent kinetic energy density of the turbulent layer.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

BISON Fuel Fragmentation Relocation and Dispersal (FFRD) Assessment Database for Eventual Use in Bayesian Calibration

Existing light-water reactor (LWR) fuel vendors have been interested in seeking increased discharge burnups of nuclear fuel rods for improved economics for quite a few years. With increased burnups come additional challenges that must be addressed. It has been experimentally observed that average burnups higher than the current regulatory limit of 62 MWd/kgU may undergo fuel fragmentation, relocation, and dispersal (FFRD) during a loss-of-coolant accident (LOCA). Industry must demonstrate approaches to mitigate FFRD. In an effort to support industry, the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program within the U.S. Department of Energy (DOE) has for several years invested in developing multiscale models and creating a validation/assessment database for these models to study the mechanisms driving FFRD. This report provides an update on changes made to the assessment database and new models added to BISON to support the study of fuel rod behavior during FFRD. An effort has been initiated this year to begin adding dedicated inputs to the publicly available Virtual Test Bed (VTB) repository for industry use. A section of this report details the efforts made in this area. NEAMS has recently developed new capabilities in the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework’s stochastic tools module for calibration using Bayesian inference. The goal in the future is to use these capabilities to calibrate and identify weaknesses in the existing BISON models for FFRD. The report concludes with a discussion on the models most likely to benefit the most from such calibration.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Parallel derivative-free optimization for simulation-based design of behind-the-meter energy systems

In this work, the integrated design and dispatch of behind-the-meter or distributed resources (e.g. stationary battery storage and solar PV generation) is considered. A simulation-based framework is employed, generating high-fidelity results with closed-loop predictive control at a fine resolution, at the expense of high computational cost (several minutes to a few hours per design point). To address this challenge, parallel derivative-free design methods are considered. Four methods are compared, including state-of-the-art surrogate-based methods (Radial-Basis Functions and Gaussian processes) and sampling strategies, an evolutionary-based method, and a simple sequential grid refinement method. As a case study, two types of design problem with increasing complexity are considered, namely, the design of behind-the-meter resources (three design variables) and the inclusion of grid capacity (four design variables). The second yields a constrained design problem for which violations can only be determined after solving the computationally expensive simulation. For the three-dimensional case, all methods present a good performance, achieving a solution within 1% of the optimum after the first iteration, with the sequential grid refinement exhibiting the fastest convergence and achieving the best final objective value. This indicates that the parallel evaluation of multiple sampling points may be more important than the choice of method for small decision spaces. For the four-dimensional constrained case, the Genetic Algorithm presents the best tradeoff between performance and computational effort, while the rough objective function terrain generated by constraint violation penalties reduces the performance of surrogate-based methods. Contour plots with flat regions indicate flexibility in the optimal design and highlight the importance of characterizing the solution space.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Performance and Energy Usage of Workloads on KNL and Haswell Architectures. In: High Performance Computing Systems. Performance Modeling, Benchmarking, and Simulation

Manycore architectures are an energy-efficient step towards exascale computing within a constrained power budget. The Intel Knights Landing (KNL) manycore chip is a specific example of this and has seen early adoption by a number of HPC facilities. It is therefore important to understand the performance and energy usage characteristics of KNL. In this paper, we evaluate the performance and energy efficiency of KNL in contrast to the Xeon (Haswell) architecture for applications representative of the workload of users at NERSC. We consider the optimal MPI/OpenMP configuration of each application and use the results to characterize KNL in contrast to Haswell. As well as traditional DDR memory, KNL contains MCDRAM and we also evaluate its efficacy. Our results show that, averaged over our benchmarks, KNL is 1.84 × more energy efficient than Haswell and has 1.27 × greater performance.

Benchmarking↗
NASA NTRS1977

Dynamic modeling and sensitivity analysis of solar thermal energy conversion systems

Since the energy input to solar thermal conversion systems is both time variant and probabilistic, it is unlikely that simple steady-state methods for estimating lifetime performance will provide satisfactory results. The work described here uses dynamic modeling to begin identifying what must be known about input radiation and system dynamic characteristics to estimate performance reliably. Daily operation of two conceptual solar energy systems was simulated under varying operating strategies with time-dependent radiation intensity ranging from smooth input of several magnitudes to input of constant total energy whose intensity oscillated with periods from 1/4 hour to 6 hours. Integrated daily system output and efficiency were functions of both level and dynamic characteristics of insolation. Sensitivity of output to changes in total input was greater than one.

Hamilton, C. L.↗
DOE OSTI2021

DOE WPTO FY2021 Seedling End Report: Coupling Soil-Foundation Models to MHK Device Dynamic Models to Tighten the Design Envelope

The purpose of this Seedling project is to couple a marine renewable energy (MRE) dynamics simulation software with the soil-foundation models in the OC6 Phase II project [Bergua et al., 2021] and evaluate the software’s performance. This is a first step to accurately evaluating soil-foundation impacts on other types of MRE, like wave or current energy converters (WECs, CECs). OC6 Phase II compares offshore wind turbine (OWT) simulations using several different soil-foundation models to identify and fill key gaps in soil-foundation analyses. WEC-Sim was chosen to model the OC6 Phase II offshore wind turbine and various load cases because of its adaptability, accuracy of hydrodynamic loads, and ability to apply an arbitrary wind loading. Of the four methods used in OC6, the apparent fixity soil-foundation method was coupled with WEC-Sim. Technical challenges with flexible hydrodynamic bodies, added mass and external function libraries inhibited the ability to compare the WEC-Sim results to other OC6 participants. These challenges required that the WEC-Sim model of the OC6 OWT use a combination of rigid and flexible bodies to ensure a numerically stable solution. The rigid monopile creates a more stiff system and causes smaller amplitude motion under hydrodynamic loading and higher dominant frequency of motion under wind loading. These discrepancies are expected based on the increased stiffness of the WEC-Sim case.

16 TIDAL AND WAVE POWER↗
DOE OSTI2018

Introducing GEOPHIRES v2.0: Updated Geothermal Techno-Economic Simulation Tool

This paper presents an updated version of the geothermal techno-economic simulation tool GEOPHIRES (GEOthermal energy for Production of Heat and electricity ('IR') Economically Simulated). GEOPHIRES combines engineering models of the reservoir, wellbores, and surface plant facilities of a geothermal plant with an economic model to estimate the capital and operation and maintenance costs, lifetime energy production, and overall levelized cost of energy. The available end-use options are electricity, direct-use heat, and cogeneration. The main updates in the new version include conversion of the source code from FORTRAN to Python, the option to import temperature data (e.g., measured or from stand-alone reservoir simulator), updated cost correlations, and more flexibility in selecting the time step and number of injection and production wells. In this paper, we provide an overview of all the updates and two case studies to illustrate the tool's new capabilities.

15 GEOTHERMAL ENERGY↗

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