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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Optimization techniques in self-similar compressible flow

We investigate the one-dimensional (1D) inviscid compressible flow equations for an ideal gas through the lens of optimization techniques. It is the case that, to our knowledge, optimization analysis applied to the so-called “linear velocity” solutions of the Euler compressible flow equations has not been previously conducted. Through both gradient-based and variational techniques, new variants of well-studied flow scenarios, i.e., self-similar, 1D, linear velocity solution class to idealized inviscid compressible flow equations, are determined, as encoded in both the kinematic and thermodynamic properties of this self-similar solution class. With the kinematics of the said solutions being driven by a self-similar “scale radius” and the thermodynamics being driven separately through the appearance of an arbitrary function, a myriad of new solution classes is possible. Acting as a guide to more realistic physical circumstances as well as discovery, it is the hope that the presented cases serve as the framework for future investigations into the intersection of self-similarity and optimization techniques. Fields of study that may find this work to be of interest include aerodynamic design, flow control, inertial confinement fusion, physics-informed neural networks, and other related areas of interest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Investigation of compression of indirect-drive targets under conditions of the NIF facility using one-dimensional modelling

The indirect compression dynamics of targets containing capsules with ablators of a plastic, high-density carbon and beryllium is simulated in the framework of a one-dimensional model based on the 1D RADIAN code. Experiments with such targets are performed on the NIF facility in the Livermore Laboratory (USA) in 2014 – 2018. The 1D simulation data are consistent with the results of experiments and calculations made at this Laboratory. The effect of the hard part of hohlraum radiation on capsule compression parameters is confirmed. We demonstrate the feasibility of eliminating this influence not only by selecting the hohlraum material but also by introducing admixtures into the capsule that absorb this radiation. It is shown how varying the amount of admixture in the capsule ablator varies the spectrum of the radiation that heats the DT fuel. (interaction of laser radiation with matter. laser plasma)

36 MATERIALS SCIENCE↗
DOE OSTI2022

Simulation of the High Temperature Test Facility (HTTF) Core Using the 2D Ring Model with SAM

A two-dimensional ring model is developed with SAM to model the core of the High Temperature Test Facility (HTTF) at the system level. The ring model simplifies the complex structure of the HTTF core by converting the hexagonal rows of heaters and flow channels into layers of concentric annular rings. The ring model is first compared against a 3D-1D model where the solid structures are fully resolved in three dimensions while the fluid structures are modeled as one-dimensional flows. Comparison between the 3D-1D and the ring models shows that the latter can predict major parameters reasonably well under steady-state normal operating condition, but the heater temperatures are underpredicted. Adjustment is made to the effective thermal conductivity of the ceramic core of the ring model to improve the heater temperature predictions. Furthermore, the ring model is also used to simulate a transient Pressurized Conduction Cooldown (PCC) condition and is benchmarked with the experimental data from the HTTF Test PG-27. Good agreement is obtained between the experimental data and the predictions by the ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Inferring safety critical events from vehicle kinematics in naturalistic driving environment: Application of deep learning Algorithms

Advances in sensing technology has enabled the collection of countless terabytes of second-by-second kinematics data. Such data provides opportunities for real-time monitoring of driving behavior and identification of safety critical events (SCEs) including crashes and near crashes. The concept of volatility is relevant in this context, which identifies instability and erratic variations in driving behavior prior to involvement in SCEs. This study utilized vehicle kinematics from a large-scale naturalistic driving data to develop a deep learning approach based on 1D convolutional neural networks (CNN) for inferring SCEs. The data are unique in the sense that such accurate pre-crash data at high fidelity are not available in traditional crash repositories. This study contributes to the literature by providing a first attempt at predicting responses to SCEs by developing deep learning-based CNN architectures using novel driving volatility based kinematic thresholds for a sample of 9553 events. The key contribution lies in developing a volatility-based CNN input layout that is acceptable to CNN schemes and represents the motion kinematics such as speed, acceleration and volatility measures. Several 1D-CNN architectures were developed using layers, numbers of convolutions, layer patterns, and kernels. Shallow and deep architectures were tested, revealing higher accuracy of shallow architectures in detecting SCEs. The optimal number of epochs were identified using an early stopping method while the CNN performance was improved by increasing the number of epochs. The ensemble CNN had the highest predictive accuracy of 95.6% for detection of crashes and near crashes, which was 2.5% higher than the optimal CNN using 20% hold out test data. The ensemble CNN also outperformed classical machine learning models and model performance reported in past studies on detection of SCEs. Finally, these results have implications for identification of safety hotspots and providing real-time alerts and warnings in connected and highly automated vehicle environment including society of automotive engineers levels 3–5.

42 ENGINEERING↗
DOE OSTI2021

Impact of soil model complexity on the long-term thermal performance prediction of a new shallow bore ground heat exchanger

Shallow bore ground heat exchangers have been investigated in recent years because they have the potential to reduce the initial cost of the ground source heat pump system. Correctly modeling the transient heat transfer between the ground heat exchanger and the surrounding soil is essential for predicting a ground heat exchanger's performance. Simplification of the soil model could increase computation speed but sacrifice accuracy. This study investigates the impact of the soil model complexity on the annual performance prediction of a new shallow bore ground heat exchanger, the underground thermal battery (UTB). A simple 1D soil model and a more detailed 2D soil model were implemented, and they were validated against a 3D soil model. Overall, the resulting predictions of the UTB’s response from the 1D and 2D models to a given thermal load in different climates were compared. The results show that the root mean square differences between the hourly temperatures of the UTB during a year predicted using the two soil models range from 1.17°C to 3.39°C. As a result, the difference in the annual power consumption of the heat pump was between 0.7% and 3.4%. Furthermore, the dimensions of the UTB affected its performance, and a longer UTB was less sensitive to the soil models.

42 ENGINEERING↗
DOE OSTI2023

Inertial and anisotropic pressure effects on cross-field electron transport in low-temperature magnetized plasmas

In this paper, a one-dimensional (1D) particle-in-cell Monte Carlo collision (PIC-MCC) model is developed to investigate the effects of anisotropic pressure and inertial terms due to non-Maxwellian velocity distribution functions on cross-field electron transport. The conservation of momentum is evaluated by taking the moments of the first-principles gas-kinetic equation. A steady-state discharge is obtained without any low-frequency ionization oscillations by considering an anomalous electron scattering profile. Further, the results obtained from the 1D PIC-MCC model are compared with fluid models, including the quasi-neutral drift-diffusion (DD), non-neutral DD, and full fluid moment models. The discharge current obtained from the PIC-MCC model is in good agreement with the fluid models. The cross-field electron transport due to the inertial terms, i.e. the gradient of axial and azimuthal drift, is evaluated. Moreover, PIC-MCC simulation results show non-zero, anisotropic, off-diagonal pressure tensor terms due to asymmetric non-Maxwellian electron velocity distribution function, potentially contributing to cross-field electron transport.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Validation of high-fidelity ion cyclotron range of frequencies antenna coupling simulations in full 3D geometry against experiments in the ASDEX Upgrade tokamak

We address the validation of finite elements ion cyclotron range of frequencies (ICRF) antenna coupling simulation against experiments performed in the ASDEX Upgrade tokamak. Measurements of the loading resistance in ICRF-heated, magnetically-perturbed 3D plasma discharges are compared against numerical predictions of the RAPLICASOL code. To this end, the 3D induction field and the 3D density profile are modeled by concatenating the PARVMEC, BMW and EMC3-EIRENE codes. The 3D density is input to RAPLICASOL, where full-wave simulations are performed on a finite element mesh retaining full 3D geometry in the ICRF antenna model and the plasma description. The results are further compared with RAPLICASOL simulations using a 1D density profile as measured at the outboard midplane in the same experiments. We find that simulations using a 1D density profile overestimate the change in loading resistance by a factor of ~197 -248%, while simulations using the full 3D density profile are in agreement with experiments within a factor ~16%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Strong surface magnetic field generation in relativistic short pulse laser–plasma interaction with an applied seed magnetic field

Abstract While plasma often behaves diamagnetically, we demonstrate that the laser irradiation of a thin opaque target with an embedded target-transverse seed magnetic field B seed can trigger the generation of an order-of-magnitude stronger magnetic field with opposite sign at the target surface. Strong surface field generation occurs when the laser pulse is relativistically intense and results from the currents associated with the cyclotron rotation of laser-heated electrons transiting through the target and the compensating current of cold electrons. We derive a predictive scaling for this surface field generation, B gen ∼ −2 πB seed Δ x / λ 0 (in the large spot size limit), where Δ x is the target thickness and λ 0 is the laser wavelength, and conduct 1D and 2D particle-in-cell simulations to confirm its applicability over a wide range of conditions. We additionally demonstrate that both the seed and surface-generated magnetic fields can have a strong impact on application-relevant plasma dynamics, for example substantially altering the overall expansion and ion acceleration from a μ m-thick laser-irradiated target with a kilotesla-level seed magnetic field.

Weichman, K. (ORCID:0000000234877922)↗
DOE OSTI2022

Driven superconducting vortex dynamics in systems with twofold anisotropy in the presence of pinning

Abstract We examine the dynamics of superconducting vortices with twofold anisotropic interaction potentials driven over random pinning, and compare the behavior under drives applied along the hard and the soft anisotropy directions. As the driving force increases, the number of topological defects reaches a maximum near the depinning threshold, and then decreases as the vortices form one-dimensional (1D) chains. This coincides with a transition from a pinned nematic to a moving smectic aligned with the soft anisotropy direction. The system is generally more ordered when the drive is applied along the soft direction of the anisotropy. For driving along the hard direction, there is a critical value of the twofold anisotropy above which the system remains aligned with the soft direction. Hysteretic behavior appears upon cycling the driving force, with 1D vortex chains persisting during the decreasing leg below the threshold for chain formation for increasing drive. More anisotropic systems have a greater amount of structural disorder in the moving state. For lower anisotropy, the system forms a moving smectic-A state, while at higher anisotropy, a moving nematic state appears instead.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Non-linearities in the Lyman-α forest and in its cross-correlation with dark matter halos

Here three-dimensional correlations of the Lyman-α (Lyα) forest and cross correlations between the Lyα forest and quasars have been measured on large scales, allowing a precise measurement of the baryon acoustic oscillation (BAO) feature at redshifts z > 2. These 3D correlations are often modelled using linear perturbation theory, but full-shape analyses to extract cosmological information beyond BAO will require more realistic models capable of describing non-linearities present at smaller scales. We present a measurement of the Lyα forest flux power spectrum from large hydrodynamic simulations — the Sherwood simulations — and compare it to different models describing the small-scale deviations from linear theory. We confirm that the model presented in Arinyo-i-Prats et al. (2015) fits the measured 3D power up to k = 10 h Mpc -1 with an accuracy better than 5%, and show that the same model can also describe the 1D correlations with similar precision. We also present, for the first time, an equivalent study for the cross-power spectrum of halos with the Lyα forest, and we discuss different challenges we face when modelling the cross-power spectrum beyond linear scales. We make all our measured power spectra public in https://github.com/andreufont/sherwoo_p3d. This study is a step towards joint analyses of 1D and 3D flux correlations, and towards using the quasar-Lyα cross-correlation beyond BAO analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Measurement of the small-scale 3D Lyman- α forest power spectrum

Small-scale correlations measured in the Lyman-α (Lyα) forest encode information about the intergalactic medium and the primordial matter power spectrum. In this article, we present and implement a simple method to measure the 3-dimensional power spectrum, P 3D , of the Lyα forest at wavenumbers k corresponding to small, ~ Mpc scales. In order to estimate P 3D from sparsely and unevenly distributed data samples, we rely on averaging 1-dimensional Fourier Transforms, as previously carried out to estimate the 1-dimensional power spectrum of the Lyα forest, P 1D . Further, this methodology exhibits a very low computational cost. We confirm the validity of this approach through its application to Nyx cosmological hydrodynamical simulations. Subsequently, we apply our method to the eBOSS DR16 Lyα forest sample, providing as a proof of principle, a first P 3D measurement averaged over two redshift bins z = 2.2 and z = 2.4. This work highlights the potential for forthcoming P 3D measurements, from upcoming large spectroscopic surveys, to untangle degeneracies in the cosmological interpretation of P 1D .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

MHD simulation on magnetic compression of field reversed configurations with NIMROD

Abstract Magnetic compression has long been proposed a promising method for plasma heating in a field reversed configuration (FRC). However, it remains a challenge to fully understand the physical mechanisms underlying the compression process, due to its highly dynamic nature beyond the one-dimensional (1D) adiabatic theory model (Spencer et al 1983 Phys. Fluids 26 1564). In this work, magnetohydrodynamics simulations on the magnetic compression of FRCs using the NIMROD code (Sovinec et al 2004 J. Comput. Phys. 195 355) and their comparisons with the 1D theory have been performed. The effects of the assumptions of the theory on the compression process have been explored, and the detailed profiles of the FRC during compression have been investigated. The pressure evolution agrees with the theoretical prediction under various initial conditions. The axial contraction of the FRC can be affected by the initial density profile and the ramping rate of the compression magnetic field, but the theoretical predictions on the FRC’s length in general and the relation r s = 2 r o in particular hold approximately well during the whole compression process, where r s is the major radius of FRC separatrix and r o is that of the magnetic axis. The evolutions of the density and temperature can be affected significantly by the initial equilibrium profile and the ramping rate of the compression magnetic field. During the compression, the major radius of the FRC is another parameter that is susceptible to the ramping rate of the compression field. Basically, for the same magnetic compression ratio, the peak density is higher and the FRC’s radius r s is smaller than the theoretical predictions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Invariant regimes of Spencer scaling law for magnetic compression of rotating FRC plasma

Abstract The scaling laws for the magnetic compression of a toroidally rotating field reversed configuration (FRC) have been investigated in this work. The magnetohydrodynamics (MHD) simulations of the magnetic compression on rotating FRCs employing the NIMROD code (Sovinec et al 2004 J. Comput. Phys. 195 355), are compared with the Spencer’s one-dimensional (1D) theory (Spencer et al 1983 Phys. Fluids 26 1564) for a wide range of initial flow speeds and profiles. The toroidal flow can influence the scalings directly through the alteration of the compressional work as also evidenced in the 1D adiabatic model, and indirectly by reshaping the initial equilibrium. However, in comparison to the static initial FRC equilibrium cases, the pressure and the radius scalings remain invariant for the magnetic compression ratio B w 2 / B w 1 up to 6 in presence of the initial equilibrium flow, suggesting a broader applicable regime of the Spencer scaling law for FRC magnetic compression. The invariant scaling has been proven a natural consequence of the conservation of angular momentum of both fluid and magnetic field during the dynamic compression process.

Ma, Yiming↗
DOE OSTI2025

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Optically induced changes in the band structure of the Weyl charge-density-wave compound (TaSe 4 ) 2 I

Collective modes are responsible for the emergence of novel quantum phases in topological materials. In the quasi-one dimensional (1D) Weyl semimetal (TaSe 4 ) 2 I , a charge density wave (CDW) opens band gaps at the Weyl points, thus turning the system into an axionic insulator. Melting the CDW would restore the Weyl phase, but 1D fluctuations extend the gapped regime far above the 3D transition temperature (T CDW = 263 K), thus preventing the investigation of this topological phase transition with conventional spectroscopic methods. Here we use a non-equilibrium approach: we perturb the CDW phase by photoexcitation, and we monitor the dynamical evolution of the band structure by time- and angle-resolved photoelectron spectroscopy. We find that, upon optical excitation, electrons populate the linearly dispersing states at the Fermi level (E F ), and fill the CDW gap. The dynamics of both the charge carrier population and the band gap renormalization (BGR) show a fast component with a characteristic time scale of a few hundreds femtoseconds. However, the BGR also exhibits a second slow component on the µs time scale. The combination of an ultrafast response and of persistent changes in the spectral weight at E$_\mathrm{F}$, and the resulting sensitivity of the linearly dispersing states to optical excitations, may explain the high performances of (TaSe 4 ) 2 I as a material for broadband infrared photodetectors.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Applications of physics informed neural operators

Abstract We present a critical analysis of physics-informed neural operators (PINOs) to solve partial differential equations (PDEs) that are ubiquitous in the study and modeling of physics phenomena using carefully curated datasets. Further, we provide a benchmarking suite which can be used to evaluate PINOs in solving such problems. We first demonstrate that our methods reproduce the accuracy and performance of other neural operators published elsewhere in the literature to learn the 1D wave equation and the 1D Burgers equation. Thereafter, we apply our PINOs to learn new types of equations, including the 2D Burgers equation in the scalar, inviscid and vector types. Finally, we show that our approach is also applicable to learn the physics of the 2D linear and nonlinear shallow water equations, which involve three coupled PDEs. We release our artificial intelligence surrogates and scientific software to produce initial data and boundary conditions to study a broad range of physically motivated scenarios. We provide the source code , an interactive website to visualize the predictions of our PINOs, and a tutorial for their use at the Data and Learning Hub for Science .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Machine-learning Kohn–Sham potential from dynamics in time-dependent Kohn–Sham systems

Abstract The construction of a better exchange-correlation potential in time-dependent density functional theory (TDDFT) can improve the accuracy of TDDFT calculations and provide more accurate predictions of the properties of many-electron systems. Here, we propose a machine learning method to develop the energy functional and the Kohn–Sham potential of a time-dependent Kohn–Sham (TDKS) system is proposed. The method is based on the dynamics of the Kohn–Sham system and does not require any data on the exact Kohn–Sham potential for training the model. We demonstrate the results of our method with a 1D harmonic oscillator example and a 1D two-electron example. We show that the machine-learned Kohn–Sham potential matches the exact Kohn–Sham potential in the absence of memory effect. Our method can still capture the dynamics of the Kohn–Sham system in the presence of memory effects. The machine learning method developed in this article provides insight into making better approximations of the energy functional and the Kohn–Sham potential in the TDKS system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

RCSB Protein Data Bank 1D3D module: displaying positional features on macromolecular assemblies

Mapping positional features from one-dimensional (1D) sequences onto three-dimensional (3D) structures of biological macromolecules is a powerful tool to show geometric patterns of biochemical annotations and provide a better understanding of the mechanisms underpinning protein and nucleic acid function at the atomic level. We present a new library designed to display fully customizable interactive views between 1D positional features of protein and/or nucleic acid sequences and their 3D structures as isolated chains or components of macromolecular assemblies.

59 BASIC BIOLOGICAL SCIENCES↗