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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Off-shell single-top-quark production in the Standard Model Effective Field Theory

We present a fully differential and spin-dependent t-channel single-top-quark calculation at next-to-leading order (NLO) in QCD including off-shell effects by using the complex mass scheme in the Standard Model (SM) and in the Standard Model Effective Field Theory (SMEFT). We include all relevant SMEFT operators at 1/Λ$^{2}$ that contribute at NLO in QCD for a fully consistent comparison to the SM at NLO. In addition, we include chirality flipping operators that do not interfere with the SM amplitude and contribute only at 1/Λ$^{4}$ with a massless b-quark. Such higher order effects are usually captured by considering anomalous right-handed Wtb and left-handed Wtb tensor couplings. Despite their formal suppression in the SMEFT, they describe an important class of models for new physics. Our calculation and analysis framework is publicly available in MCFM.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Updates to the Regional Seismic Travel Time (RSTT) Model: 1. Tomography

Abstract A function of global monitoring of nuclear explosions is the development of Earth models for predicting seismic travel times for more accurate calculation of event locations. Most monitoring agencies rely on fast, distance-dependent one-dimensional (1D) Earth models to calculate seismic event locations quickly and in near real-time. RSTT (Regional Seismic Travel Time) is a seismic velocity model and computer software package that captures the major effects of three-dimensional crust and upper mantle structure on regional seismic travel times, while still allowing for fast prediction speed (milliseconds). We describe updates to the RSTT model using a refined data set of regional phases (i.e., Pn, Pg, Sn, Lg) using the Bayesloc relative relocation algorithm. The tomographic inversion shown here acts to refine the previous RSTT public model ( rstt201404um ) and displays significant features related to areas of global tectonic complexity as well as further reduction in arrival residual values. Validation of the updated RSTT model demonstrates significant reduction in median epicenter mislocation (15.3 km) using all regional phases compared to the iasp91 1D model (22.1 km) as well as to the current station correction approach used at the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (18.9 km).

58 GEOSCIENCES↗
DOE OSTI2025

Integration of a grey-box refrigerated case model in EnergyPlus via Python plugin

Commercial buildings, in particular grocery stores (due mainly to their large refrigeration load), provide opportunities for energy cost reductions. Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity. This load flexibility could come from modifying the control of heating, ventilation, and air conditioning (HVAC) systems, refrigeration systems, or both. Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature, estimating load flexibility of refrigeration systems is nascent and has been a challenge, in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases. The existing refrigerated case model within EnergyPlus, a whole building energy simulation program, assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case. In addition, it does not encompass modeling of temperatures of the product inside the refrigerated case. This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential. In this paper, we present a grey-box model for modeling refrigerated cases in grocery stores, which include medium temperature and low temperature. Four cases are modeled; two are low-temperature closed cases and two are medium-temperature cases with one closed and one open. Data from an experimental facility are used to train and test the models. Results demonstrate the efficacy of the grey-box models in predicting the temperatures. This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment (case credits). These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost, develop and test unique algorithms that could affect refrigeration interactions with HVAC, and refine store design for any commercial building with refrigeration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Low-order multiphysics coupling techniques for nuclear reactor applications

The accurate modeling and simulation of nuclear reactor designs depends greatly on the ability to couple differing sets of physics together. Current coupling techniques most often use a fixed-point, or Picard, iteration scheme in which each set of physics is solved separately, and the resulting solutions are passed between each solver. In the work presented here, two different coupling techniques are investigated: a Jacobian-Free Newton-Krylov (JFNK) approach and a new methodology called Coarse Mesh Finite Difference Coupling (CMFD-Coupling). In this work, both techniques were applied to the low-order CMFD system of equations. This allows for the multiphysics feedback effects to be captured on the low-order system without having to perform a neutron transport solve. The JFNK and CMFD-Coupling approaches were implemented in the MPACT neutron transport code, which is being developed for the Consortium for Advanced Simulation of Light Water Reactors (CASL). These methods were tested on a wide range of practical reactor physics problems, from a single 3D fuel pin to a massively parallel 3D full core problem. When coupled neutronics-thermal hydraulics problems were investigated with both JFNK and CMFD-Coupling, it was concluded that CMFD-Coupling outperformed JFNK in terms of both accuracy and runtime for every problem. When applied to large full core problems with multiple sources of strong feedback enabled, CMFD-Coupling reduced the overall number of transport sweeps required for convergence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

PyFly: A fast, portable aerodynamics simulator

Here, we present a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM), namely PyFly. UVLM computes the aerodynamic loads applied on lifting surfaces while capturing the unsteady effects such as the added mass forces, the growth of bound circulation, and the wake while assuming that the flow separation location is known a priori. This method is based on discretizing the body surface into a lattice of vortex rings and relies on the Biot–Savart law to construct the velocity field at every point in the simulated domain. We introduce the pointwise approximation approach to simulate the interactions of the far-field vortices to overcome the computational burden associated with the classical implementation of UVLM. The computational framework uses the Python programming language to provide an easy to handle user interface while the computational kernels are written in Fortran. The mixed language approach enables high performance regarding solution time and great flexibility concerning easiness of code adaptation to different system configurations and applications. The computational tool predicts the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges) subject to incoming air. The aerodynamic simulator can also deal with enclosure effects, multi-body interactions, and B-spline representation of body shapes. Finally, we simulate different aerodynamic problems to illustrate the usefulness and effectiveness of PyFly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Cost-constrained adaptive simulations of transient spray combustion in a gas turbine combustor

Predictive high-fidelity simulations of turbulent spray combustion must capture the combined effects of complex chemistry, multiphase evaporating flow and spray-flame interactions to achieve physical accuracy. Finite-rate chemistry (FRC) combined with a realistic chemical mechanism is a combustion model well-suited for this purpose, but has a high computational cost due to the large number and stiffness of transported chemical species. In contrast, flamelet-based models achieve lower cost by transporting a small number of quantities of reduced stiffness, but assumptions regarding local flame topology, boundary conditions and inter-phase coupling limit their physical accuracy. Recently, the Pareto-efficient combustion (PEC) framework was developed to dynamically assign combustion models based on local cost and accuracy metrics in gas-phase reacting flows. In this work, we extend this PEC framework to spray combustion through the rigorous analysis of the multiphase coupling terms in the governing equations. The derivation shows that spray evaporation causes errors in the prediction of species mass fractions for flamelet-based models due to the sensitivity of the local thermo-chemical state to changes in composition caused by fuel vaporization across combustion regimes present in practical spray combustion devices. Sub-model assignment is formulated as a multiple-choice knapsack problem, where computational cost is directly controlled through the fraction of the domain assigned to the FRC sub-model. The extended PEC formulation is applied to the simulation of a realistic rich-quench-lean gas turbine combustor at steady-state conditions, as well as transient operation resulting in lean blow-out (LBO). Analysis of transient simulations during LBO demonstrates the extended PEC formulation’s capacity to dynamically adapt to changing conditions within the combustor. Transient combustor dynamics are shown to approach convergence with limited increases in computational cost, while retaining substantial computational cost reduction compared to monolithic FRC simulations. Through PEC simulations with increasing fractions of the domain assigned to FRC, monolithic flamelet simulations are shown to over-predict flame stability during LBO. Finally, the extended PEC formulation is thus shown to overcome deficiencies of monolithic models by controlling modeling error for multiphase combustion modeling.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Prototype energy models for data centers

Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Building Models. Here we present the development of two new data center prototype models and their implementation in OpenStudio and EnergyPlus. The small-size data center model represents a computer room in a building served by computer room air conditioners (CRACs); while the large-sized model represents stand-alone data centers served by computer room air handlers (CRAHs) with a central chiller plant. For each data center model, two levels of IT equipment (ITE) load density were considered, to cover the wide range of IT power density of data centers: 40 and 100 W/ft 2 (430 and 1076 W/m 2 ) for the computer room, and 100 and 500 W/ft 2 (1076 and 5382 W/m 2 ) for the stand-alone data center. All other assumptions, such as building envelope, lighting, HVAC efficiencies and schedules, were based on the minimal requirements of ASHRAE Standard 90.1 at various vintages. We introduced a novel concept of supply and return air approach temperatures to capture the essential effects of non-uniform airflow and temperature distribution in data centers. The approach temperatures were pre-computed by computational fluid dynamics (CFD) simulations for various configurations of ITE loads and airflow containment management in data centers. A new feature was developed in EnergyPlus to implement the approach temperature method. A case study was conducted to demonstrate the use of the data center models. The two data center models cover all U.S. climate zones and can be used to evaluate energy saving measures for data centers, as well as to support development of data center energy efficiency codes and standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Experimental apparatus and methodology to test and quantify thermal performance of micro and macro-encapsulated phase change materials in building envelope applications

Thermal energy storage (TES) is used as a viable technology to shift peak electricity demand caused by the space cooling requirements in buildings. Passive TES is implemented in building envelope via micro and macroencapsulation methods. This study describes the use of a state-of-the-art laboratory to test different PCM inclusions in simplified building walls. A microencapsulated PCM and two macroencapsulated PCMs are tested in a controlled environment to gather data for validation purposes of PCM modelling algorithms in building energy modelling programs. Data indicates that the chamber environment and the heating and cooling system can conduct full-cycle tests of wall panels with PCM inclusions. This study also generates data from parallel tests on 4 wall panels which can be used in building energy modelling programs to validate the PCM modelling algorithms. The cyclic tests also capture the thermal effects of PCMs and complex PCM behaviors like sub-cooling in PCM hydrate-salts.

25 ENERGY STORAGE↗
DOE OSTI2013

Particle-scale CO2 adsorption kinetics modeling considering three reaction mechanisms

In the presence of water (H2O), dry and wet adsorptions of carbon dioxide (CO2) and physical adsorption of H2O happen concurrently in a sorbent particle. The three reactions depend on each other and have a complicated, but important, effect on CO2 capturing via a solid sorbent. In this study, transport phenomena in the sorbent were modeled, including the tree reactions, and a numerical solving procedure for the model also was explained. The reaction variable distribution in the sorbent and their average values were calculated, and simulation results were compared with experimental data to validate the proposed model. Some differences, caused by thermodynamic parameters, were observed between them. However, the developed model reasonably simulated the adsorption behaviors of a sorbent. The weight gained by each adsorbed species, CO2 and H2O, is difficult to determine experimentally. It is known that more CO2 can be captured in the presence of water. Still, it is not yet known quantitatively how much more CO2 the sorbent can capture, nor is it known how much dry and wet adsorptions separately account for CO2 capture. This study addresses those questions by modeling CO2 adsorption in a particle and simulating the adsorption process using the model. As adsorption temperature changed into several values, the adsorbed amount of each species was calculated. The captured CO2 in the sorbent particle was compared quantitatively between dry and wet conditions. As the adsorption temperature decreased, wet adsorption increased. However, dry adsorption was reduced.

CO2 capture, Mathematical modeling, Sorbent partic↗
DOE OSTI2014

Annealing dynamics of WO{sub 3} by in situ XRD

Highlights: • Flame-made WO{sub 3} nanoparticles with closely controlled crystal and grain size. • Dynamic phase transition of annealing of pure and Si-doped WO{sub 3} by in situ XRD. • Irreversible evolution of WO{sub 3} crystallinity by heating/cooling during its annealing. • Si-doping alters the WO{sub 3} crystallinity dynamics and stabilizes nanosized WO{sub 3}. • Flame-made nano-WO{sub 3} can sense NO at the ppb level. - Abstract: Tungsten trioxide is a semiconductor with distinct applications in gas sensors, catalysis, batteries and pigments. As such the transition between its different crystal structures during its annealing are of interest, especially for sensor applications. Here, WO{sub 3} nanoparticles with closely controlled crystal and grain size (9–15 nm) and phase composition are made by flame spray pyrolysis and the formation of different WO{sub 3} phases during annealing is investigated. Most notably, the dynamic phase transition and crystal size evolution of WO{sub 3} during heating and cooling is monitored by in situ X-ray diffraction revealing how metastable WO{sub 3} phases can be captured stably. The effect of Si-doping is studied since it is used in practise to control crystal growth and phase transition during metal oxide synthesis and processing. Finally the influence of annealing on the WO{sub 3} sensing performance of NO, a lung inflammation tracer in the human breath, is explored at the ppb-level.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Performance of large-scale 6 Li-doped pulse-shape discriminating plastic scintillators

A 6 Li-doped plastic scintillator with pulse-shape discrimination capabilities, commercially identified as EJ -299-50, has been developed and produced at the kilogram-scale. A total of 44 bars of dimensions 5.5 cm x 5.5 cm x 50 cm of this material have been characterized. Optical properties like light output and effective attenuation length have been found to be comparable to 6 Li-doped liquid scintillators. Further, the scintillator EJ -299-50 shows good neutron detection capabilities with an effective efficiency for capture on 6 Li of approximately 85%. Stability tests performed on two formulation variations showed no intrinsic degradation in the material or optical properties during several months of observations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Failure investigation of nuclear grade POCO graphite target in high energy neutrino physics through numerical simulation

In many high energy physics neutrino beamlines, targets are made up of isotropic POCO graphite grade for production of neutrinos for high energy particle physics research and are bombarded with highly energetic pulsed proton beam. The pulsed proton beam with a small beam size creates thermal stress waves as well as radiation damage such as displacement damage, void formation, swelling, and gas formation amongst others. As a result, after a few years of operation one of the longest operated targets appears to have undergone bulk swelling and fractured along the beam centerline. A complex interaction of dynamic loading due to beam, material degradation due to irradiation are thought to have caused such a failure. Here, we present a numerical simulation to capture the combined effects of swelling and the dynamic effect of thermal stress waves due to beam heating, to explain the failure of target. An empirical formula has been developed to take into account swelling as a function of temperature and proton fluence and has been implemented in a commercial finite element code. Extensive X-ray diffraction (XRD) were performed on graphite samples from the failed target to understand the lattice parameter changes due to irradiation and build a valid empirical model. Simulation results show that swelling plays a major role in elevating the stress state in the material exceeding the failure strength while the pulsed beam heating also introduces fatigue loading that would explain brittle fracture emanating from inside of the material and propagating outward. Such empirical formulations will help in identifying the threshold values of critical parameters to extend the service life of future multi-megawatt neutrino targets and targets in other accelerator environments.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability

Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Machine learning from RANS and LES to inform coarse grid simulations

Nuclear system thermal hydraulic analysis has historically relied on computationally inexpensive 1D codes. However, such tools are unable to capture multiscale multidimensional effects in large nuclear reactor enclosures. On the other hand, simulations with higher fidelity can be too expensive for such purposes. One of the ways to reduce computational cost is to perform simulations on a coarse grid, which, unfortunately, introduces large discretization errors. In this paper, two high-to-low data-driven approaches are investigated: (1) a coarse grid turbulence model to predict eddy viscosity and (2) correction of errors in coarse grid velocity fields. The approaches aim to reduce grid- and turbulence model-induced errors in coarse grid Reynolds-averaged Navier–Stokes (RANS) simulations. Two sources of high-fidelity data, RANS and large eddy simulations (LES), are explored. To extract the eddy viscosity from the LES data, an inverse optimization problem is solved. However, the LES eddy viscosity is shown to be comparable to the RANS eddy viscosity in terms of error reduction. Therefore, the directly available RANS eddy viscosity was used to develop a coarse grid data-driven turbulence model. Additionally, error correction in velocity is used to reduce the remaining uncertainties and bring the results closer to reality. In conclusion, the performance of the frameworks is demonstrated for a scaled upper plenum of a gas-cooled reactor facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Multivariate degradation modeling using generalized cauchy process and application in life prediction of dye-sensitized solar cells

Recently, the Generalized Cauchy (GC) process has been applied to capture a Long Memory (LM) phenomenon in product degradation modeling and life prediction. Compared with the traditional fractional Brownian motion that captures the LM using a single Hurst parameter, the GC process has two free parameters (Hurst and fractal dimension parameters) that flexibly capture both global LM and local irregularity. However, all existing GC-based degradation models are for a single Degradation Characteristic (DC). In this article, motivated by a real degradation problem of dye-sensitized solar cells that jointly exhibits multiple DCs, global LM, local irregularity and DC-wise cross-correlation, we propose a novel GC-based Multivariate Degradation Model (GC-MDM) to simultaneously capture the aforementioned effects. A maximum likelihood estimation approach is developed to estimate parameters of the GC-MDM. Subsequently, product life prediction based on the GC-MDM is developed. The proposed GC-MDM is validated through a simulation study and a physical experiment of dye-sensitized solar cells. Furthermore, results show that the proposed GC-MDM fundamentally improves the life prediction accuracy in comparison with conventional degradation models which significantly misestimate the uncertainty of product life.

14 SOLAR ENERGY↗
DOE OSTI2017

Fast Quasi-Static Time-Series (QSTS) for yearlong PV impact studies using vector quantization

The rapidly growing penetration levels of distributed photovoltaic (PV) systems requires more comprehensive studies to understand their impact on distribution feeders. IEEE P.1547 highlights the need for Quasi-Static Time Series (QSTS) simulation in conducting distribution impact studies for distributed resource interconnection. Unlike conventional scenario-based simulation, the time series simulation can realistically assess time-dependent impacts such as the operation of various controllable elements (e.g. voltage regulating tap changers) or impacts of power fluctuations. However, QSTS simulations are still not widely used in the industry because of the computational burden associated with running yearlong simulations at a 1-s granularity, which is needed to capture device controller effects responding to PV variability. This study presents a novel algorithm that reduces the number of times that the non-linear 3-phase unbalanced AC power flow must be solved by storing and reassigning power flow solutions as it progresses through the simulation. Each unique power flow solution is defined by a set of factors affecting the solution that can easily be queried. We demonstrate a computational time reduction of 98.9% for a yearlong simulation at 1-s resolution with minimal errors for metrics including: number of tap changes, capacitor actions, highest and lowest voltage on the feeder, line losses, and ANSI voltage violations. Finally, the key contribution of this work is the formulation of an algorithm capable of: (i) drastically reducing the computational time of QSTS simulations, (ii) accurately modeling distribution system voltage-control elements with hysteresis, and (iii) efficiently compressing result time series data for post-simulation analysis.

14 SOLAR ENERGY↗
DOE OSTI2025

Curvature Memory in Electrically Stimulated Lipid Membranes

Here, we demonstrate, using non-equilibrium molecular dynamics simulations, that lipid membrane capacitance varies with surface charge accumulation linked to membrane shape and curvature changes. Specifically, we show that lipid membranes exhibit a hysteretic response when exposed to oscillatory electric fields. The electromechanical coupling in these membranes leads to hysteretic buckling, in which the membrane can spontaneously buckle in one of two distinct directions along the electric field, even for the same ionic charge accumulation at the water–membrane interface. In this regard, these binary buckled membrane states suggest potential applications in neuromorphic computing. Their bistable nature, characterized by two distinct and stable configurations, could serve as a foundation for implementing memory storage systems and logic operations. Furthermore, we introduce a circuit model that captures these dynamic effects, offering insights into emergent memory effects in electrically stimulated lipid membranes. Finally, this work presents lipid bilayers as dynamic, adaptable elements and suggests a new platform for exploring energy storage, information processing, and memory encoding at the lipid membrane level.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

X-ray and Neutron Reflectivity Studies of Styrene-Maleic Acid Copolymer Interactions with Galactolipid-Containing Monolayers

Styrene-maleic acid (SMA) copolymers have recently gained attention for their ability to facilitate the detergent-free solubilization of membrane protein complexes and their native boundary lipids into polymer-encapsulated, nanosized lipid particles, referred to as SMALPs. However, the interfacial interactions between SMA and lipids, which dictate the mechanism, efficiency, and selectivity of lipid and membrane protein extraction, are barely understood. Our recent finding has shown that SMA 1440, a chemical derivative of the SMA family with a functionalized butoxyethanol group, was most active in galactolipid-rich membranes, as opposed to phospholipid membranes. In the present work, we have performed X-ray reflectometry (XRR) and neutron reflectometry (NR) on the lipid monolayers at the liquid–air interface followed by the SMA copolymer adsorption. XRR and Langmuir Π–A isotherms captured the fluidifying effect of galactolipids, which allowed SMA copolymers to infiltrate easily into the lipid membranes. NR results revealed the detailed structural arrangement of SMA 1440 copolymers within the membranes and highlighted the partition of butoxyethanol group into the lipid tail region. In conclusion, this work allows us to propose a possible mechanism for the membrane solubilization by SMA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗