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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Phase-space sensitivity (weight functions) of 3 MeV proton diagnostics

Abstract The weight function W ( X ) is a diagnostic sensitivity to phase-space variables X that relates the measured signal C to the distribution function F ( X ) through the equation C = ∫ W ( X ) F ( X ) d X . In the present work, an algorithm to calculate W for a diagnostic that measures 3 MeV protons produced in d(d,p)t fusion reactions between a fast ion and a thermal deuteron is developed. The emitted protons escape the tokamak on curved orbits and are detected. These curved orbits constitute effective diagnostic ‘sightlines’. The presented algorithm accounts for the complications associated with these curved sightlines. An initial calculation of time-reversed proton orbits computes effective solid angles and sightlines for the relevant range of incident proton velocity vectors. These precomputed orbits are then used within the framework of FIDASIM (2020 Plasma Phys. Cont. Fusion 62 105008) to calculate the reactivity averaged over the thermal distribution of the ‘target’ deuterons and the probability that a fast ion of specified energy and pitch has a gyroangle that is consistent with the kinematic equations along each of the sightlines. Comparisons with analytic formulas and with independent calculations for the Mega Amp Spherical Tokamak 3 MeV proton diagnostic verify the algorithm.

Physics↗
DOE OSTI2022

Weight function procedure for reduced order fracture analysis of arbitrary flaws in cylindrical pressure vessels

Fracture mechanics calculations using the finite element method can be computationally expensive, which makes them challenging to use in engineering evaluations of flaws in pressure vessels. The weight function (WF) technique is a reduced order fracture modeling method that is widely used to greatly reduce these computational costs. Its computational efficiency is essential for use in probabilistic fracture mechanics evaluations of embrittled nuclear reactor pressure vessels (RPVs), due to the large number of sampled flaws that must be evaluated. Although the WF technique is general, it is typically used only for axis-aligned flaws. Recent discoveries of off-axis flaws in operating nuclear reactors have necessitated detailed simulations of such flaws and the interactions between neighboring flaws. This paper presents a generalized WF approach applicable for analyzing arbitrary flaw geometries in thick-walled cylindrical vessels, including surface-breaking and subsurface flaws, which can either axis-aligned or off-axis, and can account for interactions with other flaws. Herein, this approach is demonstrated on representative simulations of multiple flaw geometries in a RPV subjected to transient loading conditions. In all cases, the WF technique gives good comparison with benchmark results from direct simulation with greatly reduced computational effort.

42 ENGINEERING↗
DOE OSTI2025

Optimal Control Strategy With Efficiency and Reliability Improvement for Offshore DC Microgrids

Offshore microgrids, due to their remote location and lack of external energy support, face significant challenges in wide-range load operation and maintenance. Consequently, efficiency and reliability are critical concerns for converters in offshore dc microgrids. This article presents an optimal control strategy aimed at enhancing both efficiency and reliability. A normalized nonlinear relationship between power loss and thermal stress of a paralleled converter is first established. Based on this, a dual-objective optimization function with an active weight function as well as a system overall performance index is established. The active weight function dynamically adjusts the control priority based on converter efficiency and switching device thermal stress. Then, the optimal power-sharing strategy is derived by the Lagrange multiplier method with the proposed optimal function. Additionally, to accommodate a wide load range, an optimal selection strategy for operating converter combinations is proposed, requiring only low-bandwidth communication. Experiment verification is given to validate the effectiveness of the proposed control strategy. The experiment results demonstrate that the proposed control strategy can improve the overall performance of offshore microgrids by optimizing efficiency and reliability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Orbit tomography of energetic particle distribution functions

Both fast ions and runaway electrons are described by distribution functions, the understanding of which are of critical importance for the success of future fusion devices such as ITER. Typically, energetic particle diagnostics are only sensitive to a limited subsection of the energetic particle phase-space which is often insufficient for model validation. However, previous publications show that multiple measurements of a single spatially localized volume can be used to reconstruct a distribution function of the energetic particle velocity-space by using the diagnostics' velocity-space weight functions, i.e. velocity-space Tomography. In this work we use the recently formulated orbit weight functions to remove the restriction of spatially localized measurements and present orbit tomography, which is used to reconstruct the 3D phase-space distribution of all energetic particle orbits in the plasma. Through a transformation of the orbit distribution, the full energetic particle distribution function can be determined in the standard {energy, pitch, r, z}-space. We benchmark the technique by reconstructing the fast-ion distribution function of an MHD-quiescent DIII-D discharge using synthetic and experimental FIDA measurements. We also use the method to study the redistribution of fast ions during a sawtooth crash at ASDEX upgrade using FIDA measurements. Lastly, a comparison between the orbit tomography and velocity-space tomography is shown.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A Decision-Making Machine Learning Approach in Hermite Spectral Approximations of Partial Differential Equations

The accuracy and effectiveness of Hermite spectral methods for the numerical discretization of partial differential equations on unbounded domains are strongly affected by the amplitude of the Gaussian weight function employed to describe the approximation space. This is particularly true if the problem is under-resolved, i.e., there are no enough degrees of freedom. The issue becomes even more crucial when the equation under study is time-dependent, forcing in this way the choice of Hermite functions where the corresponding weight depends on time. In order to adapt dynamically the approximation space, it is here proposed an automatic decision-making process that relies on machine learning techniques, such as deep neural networks and support vector machines. The algorithm is numerically tested with success on a simple 1D problem, but the main goal is its exportability in the context of more serious applications. Here we also show at the end an application in the framework of plasma physics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A quasi-meshfree method for constructing boundary-aware reproducing bases on geometrically complex domains using manifold geodesics

In many applications, physical domains are geometrically complex making it challenging to perform coarse-scale approximation. A defeaturing process is often used to simplify the domain in preparation for approximation and analysis at the coarse scale. In this paper, a methodology is presented for constructing a coarse-scale reproducing basis on geometrically complex domains given an initial fine-scale mesh of the fully featured domain. The initial fine-scale mesh can be of poor quality and extremely refined. The construction of the basis functions begins with a coarse-scale covering of the domain and generation of weighting functions with local support. Manifold geodesics are used to define distances within the local support for general applicability to non-convex domains. Conventional moving least squares is used to construct the coarse-scale reproducing basis. Applications in quasi-interpolation and linear elasticity are presented.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Machine learning bridges local static structure with multiple properties in metallic glasses

A long-standing challenge in the metallic glass (MG) community has been how to quantitatively gauge the influence of the intricate local packing environment on the response (such as the propensity for atomic rearrangement) of the atomic configuration to external stimuli. Here we establish this structure–property relation by representing the complex amorphous structure using a single, flexibility-orientated structural quantity. This structural flexibility (SF) couples to a bona fide structural representation, the pair distribution function (PDF) of individual atoms, through a weighting function that reflects what matters in the static atomic configuration to dynamic responses. Machine learning is used, employing microscopic flexibility volume as the supervisory signal, to establish via direct regression an optimized weighting vector, which is proven robust for all quenching rates, deformation conditions, and different compositions in a given (e.g., Cu x Zr 100-x ) alloy system. Additionally, the SF is evaluated solely from the particle positions (PDF), for any structure variation, from the atomic scale up to sample average. Strong correlations are demonstrated between SF and a broad range of properties, including vibrational, diffusional, as well as elastic and plastic relaxation responses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Influence of the complete basis set approximation, tight weighted-core, and diffuse functions on the DLPNO-CCSD(T1) atomization energies of neutral H,C,O-compounds

The impact of complete basis set extrapolation schemes (CBS), diffuse functions, and tight weighted core functions on enthalpies of formation predicted via the DLPNO-CCSD(T1) reduced Feller Peterson-Dixon approach has been examined for neutral H,C,O-compounds. All tested three-point (TZ/QZ/5Z) extrapolation schemes result in mean unsigned deviation (MUD) below 2 kJ mol -1 relative to the experiment. Here, the two-point QZ/5Z and TZ/QZ CBS 1/$l^3_{max}$ extrapolation schemes are inferior to their inverse power counterpart (1/($l_{max}$ + 1/2) 4 ) by 1.3 and 4.3 kJ mol -1 . The CBS extrapolated frozen core atomization energies are insensitive (within 1 kJ mol -1 ) to augmentation of the basis set with tight weighted core functions. The core-valence correlation effects converge already at triple-ζ, although double- ζ/triple- ζ CBS extrapolation performs better and is recommended. The effect of diffuse function augmentation converges slowly, and cannot be reproduced with double- ζ or triple- ζ calculations as these are plagued with basis set superposition and incompleteness errors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

M/P Ratios—A Call for Consistency

This is an article for the Illuminating Engineering Society's LD+A magazine. It addresses Melanopic/Photopic ratios, a metric that roughly calculates the portion of the visible spectrum from a light source that contributes to the ipRGC response, relative to the traditional photopic response. The paper explains weighting functions, and that there are four ways to calculate M/P ratios. These four methods produce different values, so it is incumbent on recommendations for M/P ratios (usually for health-related design) to list the method to use. Better still, the lighting and medical communities should standardize on one approach.

M/P ratios, melanopic/photopic ratios, spectral we↗
DOE OSTI2021

3D Printing of Transparent Silicone Elastomers

Here in this paper, inks for transparent elastomers that are formulated by matching the refractive index of silica and polysiloxanes are described. The transparent inks transmit up to ≈90% of 700 nm light through 1 cm and remain transparent when solidified. The inks and solidified materials exhibit a thermochromic effect. This thermochromic effect can be controlled by the refractive index mismatch. Transparency may increase or decrease as temperature increases, depending on the refractive index mismatch of the base polysiloxane and silica. It is found that the rheological properties of the ink depend on the distribution of silica particles, which is dictated by silica functionality, weight content, and processing. Siloxane precursors that vary in chemical functionality are introduced to tailor the mechanical properties of the printed elastomers, which obtain stretchability >65% along with a tensile modulus of 1.9 MPa. After optimizing siloxane chemistry and ink processing, the authors are able to print transparent elastomers. Potential applications are demonstrated for printed structures by printing encapsulation structures for light-emitting diodes, semitransparent dye-filled structures, a microfluidic mixing device, and a multimaterial structure that exhibits temperature-dependent camouflage.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Weighted nodal domain averages of eigenstates for quantum Monte Carlo and beyond

In this report we study the nodal properties of many-body eigenstates of stationary Schrödinger equation that affect the accuracy of real-space quantum Monte Carlo calculations. In particular, we introduce weighted nodal domain averages that provide a new probe of nodal surfaces beyond the usual expectations. Particular choices for the weight function reveal, for example, that the difference between two arbitrary fermionic eigenvalues is given by the nodal hypersurface integrals normalized by overlaps with the bosonic ground state of the given Hamiltonian. Noninteracting and fully interacting Be atom with corresponding almost exact and approximate wave functions are used to illustrate several aspects of these concepts. Variational formulations that employ different weights are proposed for prospective improvement of nodes in variational and fixed-node diffusion Monte Carlo calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Deconvolving the components of the sign problem

Auxiliary field quantum Monte Carlo simulations of interacting fermions require sampling over a Hubbard-Stratonovich field h introduced to decouple the interactions. The weight for a given configuration involves the products of the determinant of matrices $M_σ(h)$ where σ labels the species, and hence is typically not positive definite. Indeed, the average sign $\langle \mathscr {L} \rangle$ of the determinants goes to zero exponentially with increasing spatial size and decreasing temperature for most Hamiltonians of interest. This statement, however, does not explicitly separate two possible origins for the vanishing of $\langle \mathscr {L} \rangle$. Does $\langle \mathscr {L} \rangle$ → 0 because randomly chosen field configurations have det[M(h)] < 0, or does the sign problem arise because the specific subset of configurations chosen by the weighting function have a greater preponderance of negative values? In the latter case, the process of weighting the configurations with |det[M(h)]| might steer the simulation to a region of configuration space of h where positive and negative determinants are equally likely, even though randomly chosen h would preferentially have determinants with a single dominant sign. Here in this paper, we address the relative importance of these two mechanisms for the vanishing of $\langle \mathscr {L} \rangle$ in quantum simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Light-front holography model of the EMC effect

A new two-component model of the EMC effect based on Light-Front Holographic QCD (LFHQCD) is presented. The model suggests the EMC effect is the result of the nuclear potential breaking SU(6) symmetry. The model separates the $F_{2}^{A}$ nuclear structure function into two parts: a free contribution, involving the addition of proton and neutron structure functions weighted by the number of protons and neutrons respectively, and a nuclear/medium modified contribution that involves a universal function for all nuceli. Further, the model displays a connection with the correlation between the size of the EMC effect and the SRC pair density, a 2 - extracted from kinematic plateaus at around x > 1 in inclusive quasi-elastic (QE) scattering.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Multifidelity multiobjective optimization for wake-steering strategies

Abstract. Wake steering is an emerging wind power plant control strategy where upstream turbines are intentionally yawed out of perpendicular alignment with the incoming wind, thereby “steering” wakes away from downstream turbines. However, trade-offs between the gains in power production and fatigue loads induced by this control strategy are the subject of continuing investigation. In this study, we present a multifidelity multiobjective optimization approach for exploring the Pareto front of trade-offs between power and loading during wake steering. A large eddy simulation is used as the high-fidelity model, where an actuator line representation is used to model wind turbine blades and a rainflow-counting algorithm is used to compute damage equivalent loads. A coarser simulation with a simpler loads model is employed as a supplementary low-fidelity model. Multifidelity Bayesian optimization is performed to iteratively learn both a surrogate of the low-fidelity model and an additive discrepancy function, which maps the low-fidelity model to the high-fidelity model. Each optimization uses the expected hypervolume improvement acquisition function, weighted by the total cost of a proposed model evaluation in the multifidelity case. The multifidelity approach is able to capture the logit function shape of the Pareto frontier at a computational cost only 30 % that of the single-fidelity approach. Additionally, we provide physical insights into the vortical structures in the wake that contribute to the Pareto front shape.

17 WIND ENERGY↗
DOE OSTI2021

Data-Driven Forgetting and Discount Factors for Vehicle Speed Forecasting in Ecological Adaptive Cruise Control

Abstract This paper investigates temporal correlations in human driving behavior using real-world driving to improve speed forecasting accuracy. These correlations can point to a measurement weighting function with two parameters: a forgetting factor for past speed measurements that the vehicle itself drove with, and a discount factor for the speeds of vehicles ahead based on information from vehicle-to-vehicle communication. The developed weighting approach is applied to a vehicle speed predictor using polynomial regression, a prediction method well-known in the literature. The performance of the developed approach is then assessed in both real-world and simulated traffic scenarios for accuracy and robustness. The new weighting method is applied to an ecological adaptive cruise control system, and its influence is analyzed on the prediction accuracy and the performance of the ecological adaptive cruise control in an electric vehicle powertrain model. The results show that the new prediction method improves energy saving from the eco-driving by up to 4.7% compared to a baseline least-square-based polynomial regression. This is a 10% improvement over the constant speed/acceleration model, a conventional speed predictor.

Automation & Control Systems↗
DOE OSTI2020

Effects of CELF Pretreatment Severity on Lignin Structure and the Lignin-Based Polyurethane Properties

Conversion of technical lignin into performance biopolymers such as polyurethane offers environmental and economic advantages when combined with production of biofuels from biomass sugars, presenting significant interest toward studying the role of pretreatment on lignin structure and functionality. Co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment, employing acidic aqueous tetrahydrofuran (THF) mixtures, was developed to effectively break down the lignin-carbohydrate matrix and promote extraction of lignin from lignocellulosic biomass with desirable purity and yield. In this study, we report the effects of CELF pretreatment reaction severity on the molecular structure of CELF-extracted lignin and its impact toward the mechanical properties of the resulting lignin-based polyurethanes. Reaction temperature was found to play the most significant role, compared to reaction time and acidity, in manipulating structural features such as molecular weight, functionality and intra-polymer structure. At the severe reaction conditions at 180&#x00B0;C, the order of reactivity for primary lignin interlinkages characterized by semiquantitative HSQC NMR analysis were found to be &#x03B2;-ether &#x003E; phenylcoumaran (&#x03B2;&#x2212;5&#x2032;) &#x003E; resinol (&#x03B2;&#x2212;&#x03B2;&#x2032;) facilitating a high degree of depolymerization and yielding a high frequency of free phenolics and reduced aliphatic hydroxyl groups. All side-chain interlinkages were depleted converting guaiacyl subunits into condensed forms, while still retaining uncondensed syringyl subunits. Under the mild 150&#x00B0;C temperature reaction, CELF lignin had higher molecular weight and retained more &#x03B2;-ether interlinkages. The results from CELF lignin-based polyurethane synthesis indicated that the tensile properties depended on the miscibility of CELF lignin with other components and low molecular weight cuts improved the dispersion of lignin in the polyurethane network. Pre-mixing of CELF with poly(ethylene glycol) (PEG) reduced the brittleness and improved the ductility of the CELF lignin-PEG polyurethanes.

59 BASIC BIOLOGICAL SCIENCES↗