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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

A multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Calculation of spin–orbit couplings using RASCI spinless one-particle density matrices: Theory and applications

Here we present the formalism and implementation for calculations of spin–orbit couplings (SOCs) using the Breit–Pauli Hamiltonian and non-relativistic wave functions described by the restricted active space configuration interaction (RASCI) method with general excitation operators of spin-conserving spin-flipping, ionizing, and electron-attaching types. The implementation is based on the application of the Wigner–Eckart theorem within the spin space, which enables the calculation of the entire SOC matrix based on the explicit calculation of just one transition between the two spin multiplets. Numeric results for a diverse set of atoms and molecules highlight the importance of a balanced treatment of correlation and adequate basis sets and illustrate the overall robust performance of RASCI SOCs. The new implementation is a useful addition to the methodological toolkit for studying spin-forbidden processes and molecular magnetism.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Reliable extrapolation of deep neural operators informed by physics or sparse observations

Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equations (PDEs) for real-time prediction, deep neural operators such as deep operator networks (DeepONets) provide a new simulation paradigm in science and engineering. Pure data-driven neural operators and deep learning models, in general, are usually limited to interpolation scenarios, where new predictions utilize inputs within the support of the training set. However, in the inference stage of real-world applications, the input may lie outside the support, i.e., extrapolation is required, which may result to large errors and unavoidable failure of deep learning models. Here, we address this challenge of extrapolation for deep neural operators. First, we systematically investigate the extrapolation behavior of DeepONets by quantifying the extrapolation complexity, via the 2-Wasserstein distance between two function spaces and propose a new strategy of bias–variance trade-off for extrapolation with respect to model capacity. Subsequently, we develop a complete workflow, including extrapolation determination, and we propose five reliable learning methods that guarantee a safe prediction under extrapolation by requiring additional information—the governing PDEs of the system or sparse new observations. The proposed methods are based on either fine-tuning a pre-trained DeepONet or multifidelity learning. We demonstrate the effectiveness of the proposed framework for various types of parametric PDEs. Furthermore, our systematic comparisons provide practical guidelines for selecting a proper extrapolation method depending on the available information, desired accuracy, and required inference speed.

42 ENGINEERING↗
DOE OSTI2025

Experimental study of a tri-functional propane hydronic heat pump

This study investigates the performance of a propane hydronic heat pump system for space cooling, heating, and water heating applications, focusing on various operational conditions, with a total refrigerant charge below 1200 g. Cooling performance was evaluated at different outdoor temperatures, compressor stages (capacity levels), and water flow rates. The results showed that the coefficient of performance (COP) for cooling was higher at lower outdoor temperatures, with peak values exceeding 5.0 under low-stage operation and lower water flow rate. The cooling capacity increased with higher flow rates and compressor stages, reaching 12 kW. Space heating performance, evaluated at ambient temperatures ranging from −8.3 °C to 16.7 °C, revealed a decrease in COP with lower temperatures. However, high-stage operation maintained higher heating capacities even at low temperatures. The system demonstrated high Heating Seasonal Performance Factors (HSPF), exceeding 10.0. For water heating, the COP decreased with lower ambient temperatures and higher supply water temperatures. The system efficiently heated an 189-L water tank, outperforming conventional water heaters, with process COPs exceeding 4.0 under cooling-season conditions. Despite some efficiency loss due to defrosting at low temperatures, the propane heat pump consistently delivered strong performance. Seasonal energy efficiency ratios (SEER) and seasonal heating COP values indicated significant overall efficiency. The study concludes that propane is a promising refrigerant for heat pump systems, with future research needed to future reduce total system charge and optimize system performance through advanced controls and heat exchanger designs.

Hu, Yifeng [ORNL] (ORCID:0000000242875185)↗
DOE OSTI2024

Towards dynamical low-rank approximation for neutrino kinetic equations. Part I: Analysis of an idealized relaxation model

Dynamical low-rank approximation (DLRA) is an emerging tool for reducing computational costs and provides memory savings when solving high-dimensional problems. Here, in this work, we propose and analyze a semi-implicit dynamical low-rank discontinuous Galerkin (DLR-DG) method for the space homogeneous kinetic equation with a relaxation operator, modeling the emission and absorption of particles by a background medium. Both DLRA and the discontinuous Galerkin (DG) scheme can be formulated as Galerkin equations. To ensure their consistency, a weighted DLRA is introduced so that the resulting DLR-DG solution is a solution to the fully discrete DG scheme in a subspace of the standard DG solution space. Similar to the standard DG method, we show that the proposed DLR-DG method is well-posed. We also identify conditions such that the DLR-DG solution converges to the equilibrium. Numerical results are presented to demonstrate the theoretical findings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Acceleration of heavy ions in inverse free electron laser

In conventional linear accelerators, the beam is accelerated with a synchronous harmonic of the radio frequency field where the electric field component is collinear with the beam direction. This approach requires the design of complex accelerating structures, especially for low-energy heavy ions. If the beam motion were sustainably coupled to transverse electromagnetic fields, this could significantly simplify the accelerating structure design, and even allow acceleration with free-space waves. However, despite the long history of the proposed concept for accelerating low-velocity ion beams, it has not found practical application, partially because of the complexity of the technical design. In this paper, we present a practical design approach for this undulator-based accelerator for low-energy heavy-ions, reminiscent of the inverse free electron laser operating principle, but in a different parameter space.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Radiation effects induced by the energetic protons in 8x8x32 mm3 CdZnTe detectors

We report CdZnTe (CZT) detectors have been used in the past and are being actively considered for future gamma-ray space telescopes. One of the challenges of operating CZT detectors in low Earth orbit is radiation damage caused by energetic protons. Previous studies concluded that fluences of 10 8 -10 9 p/cm 2 are sufficient to cause shifting of peak positions and degradations of energy resolution. Degradation of detectors after proton irradiation has been extensively investigated to determine their radiation resistance limits and performance recovering procedures for their applications in space and nuclear nonproliferation. Here we present the study of radiation effects induced by 100 MeV protons in 3-cm long CdZnTe detectors that we recently proposed for the gamma-ray telescope GECCO. The goal this study is to evaluate the feasibility of using such long CZT detectors in future space missions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Renormalizing two-fermion operators in the SMEFT via supergeometry

We extend the geometric framework of field-space covariance for loop computations, thereby unifying the treatment of scalars, fermions, and gauge bosons in effective field theories. This allows us to derive a manifestly covariant formula for one-loop UV divergences that includes contributions from mixed boson-fermion graphs. The result is expressed in terms of geometric invariants of the field-space supermanifold. As a demonstration of this formula, we compute the renormalization group equations for two-fermion operators at the dimension-eight level in the Standard Model Effective Field Theory.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Improved honeycomb and hyperhoneycomb lattice Hamiltonians for quantum simulations of non-Abelian gauge theories

Improved Kogut-Susskind Hamiltonians for quantum simulations of non-Abelian Yang-Mills gauge theories are developed for honeycomb (2+1⁢D) and hyperhoneycomb (3+1⁢D) spatial tessellations. This is motivated by the desire to identify lattices for quantum simulations that involve only 3-link vertices among the gauge field group spaces in order to reduce the complexity in applications of the plaquette operator. For the honeycomb lattice, we derive a classically 𝒪⁡(𝑏 2 )-improved Hamiltonian, with 𝑏 being the lattice spacing. Tadpole improvement via the mean-field value of the plaquette operator is used to provide the corresponding quantum improvements. We have identified the (nonchiral) hyperhoneycomb as a candidate spatial tessellation for 3+1⁢D quantum simulations of gauge theories, and determined the associated 𝒪⁡(𝑏)-improved Hamiltonian.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Energy window stochastic density functional theory

We report that linear scaling density functional theory is important for understanding electronic structure properties of nanometer scale systems. Recently developed stochastic density functional theory can achieve linear or even sublinear scaling for various electronic properties without relying on the sparsity of the density matrix. The basic idea relies on projecting stochastic orbitals onto the occupied space by expanding the Fermi-Dirac operator and repeating this for N χ stochastic orbitals. Often, a large number of stochastic orbitals are required to reduce the statistical fluctuations (which scale as N$-1/2\atop{χ}$) below a tolerable threshold. In this work, we introduce a new stochastic density functional theory that can efficiently reduce the statistical fluctuations for certain observable and can also be integrated with an embedded fragmentation scheme. The approach is based on dividing the occupied space into energy windows and projecting the stochastic orbitals with a single expansion onto all windows simultaneously. This allows for a significant reduction of the noise as illustrated for bulk silicon with a large supercell. Finally, we also provide theoretical analysis to rationalize why the noise can be reduced only for a certain class of ground state properties, such as the forces and electron density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Metal oxide barrier layers for terrestrial and space perovskite photovoltaics

Perovskite photovoltaics are attractive for both terrestrial and space applications. Although terrestrial conditions require durability against stressors such as moisture and partial shading, space poses different challenges: radiation, atomic oxygen, vacuum and high-temperature operation. Here we demonstrate a silicon oxide layer that hardens perovskite photovoltaics to critical space stressors. A 1-um-thick silicon oxide layer evaporated atop the device contacts blocks 0.05 MeV protons at fluences of 10 15 cm -2 without a loss in power conversion efficiency, which results in a device lifetime increase in low Earth orbit by x20 and in highly elliptical orbit by x30. Silicon-oxide-protected Cs 0.05 (MA 0.17 FA 0.83 ) 0.95 Pb(I 0.83 Br 0.17 ) 3 ) (MA, methylammonium; FA, formamidinium cation) and CsPbI 2 Br cells survive submergence in water and N,N-dimethylformamide. Furthermore, moisture tolerance of Sn-Pb and CsPbI 2 Br devices is boosted. Devices are also found to retain power conversion efficiencies on exposure to alpha irradiation and atomic oxygen. So, this barrier technology is a step towards lightweight packaging designs for both space and terrestrial applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Neural operators for stochastic modeling of nonlinear structural system response to natural hazards

Traditionally, neural networks have been employed to learn the mapping between finite-dimensional Euclidean spaces. However, recent research has opened up new horizons, focusing on the utilization of deep neural networks to learn operators capable of mapping infinite-dimensional function spaces. Here, in this work, we employ two state-of-the-art neural operators, the deep operator network (DeepONet) and the Fourier neural operator (FNO) for the prediction of the nonlinear time history response of structural systems exposed to natural hazards, such as earthquakes and windstorms. Specifically, we propose two architectures, a self-adaptive FNO and a fast Fourier transform-based DeepONet (DeepFNOnet), where we employ a FNO beyond the DeepONet to learn the discrepancy between the ground truth and the solution predicted by the DeepONet. To demonstrate the efficiency and applicability of the architectures, two problems are considered. In the first, we use the proposed model to predict the seismic nonlinear dynamic response of a six-story shear building subject to stochastic ground motions. In the second problem, we employ the operators to predict the wind-induced nonlinear dynamic response of a high-rise building while explicitly accounting for the stochastic nature of the wind excitation. In both cases, the trained metamodels achieve high accuracy while being orders of magnitude faster than their corresponding high-fidelity models.

DeepONet↗
DOE OSTI2021

Optimization of Asynchronous Communication Operations through Eager Notifications

UPC++ is a C++ library implementing the Asynchronous Partitioned Global Address Space (APGAS) model. We propose an enhancement to the completion mechanisms of UPC++ used to synchronize communication operations that is designed to reduce overhead for on-node operations. Our enhancement permits eager delivery of completion notification in cases where the data transfer semantics of an operation happen to complete synchronously, for example due to the use of shared-memory bypass. This semantic relaxation allows removing significant overhead from the critical path of the implementation in such cases. We evaluate our results on three different representative systems using a combination of microbenchmarks and five variations of the the HPCChallenge RandomAccess benchmark implemented in UPC++ and run on a single node to accentuate the impact of locality. We find that in RMA versions of the benchmark written in a straightforward manner (without manually optimizing for locality), the new eager notification mode can provide up to a 25% speedup when synchronizing with promises and up to a 13.5x speedup when synchronizing with conjoined futures. We also evaluate our results using a graph matching application written with UPC++ RMA communication, where we measure overall speedups of as much as 11% in single-node runs of the unmodified application code, due to our transparent enhancements.

Kamil, Amir↗
DOE OSTI2021

Beyond RMS: Understanding the Evolution of Beam Distributions in High Intensity Linacs

Understanding the evolution of beams with space charge is crucial to design and operation of high intensity linacs. While the community holds a broad understanding of the mechanisms leading to emittance growth and halo formation, there is outstanding discrepancy between measurements and beam evolution models that precludes prediction of halo losses. This may be due in part to insufficient information of the initial beam distribution. This talk will describe work at the SNS Beam Test Facility to directly measure the 6D beam distribution. Full-and-direct 6D measurement has revealed hidden but physically significant dependence between the longitudinal distribution and transverse coordinates. This nonlinear correlation is driven by space charge and reproduced by self-consistent simulation of the RFQ. Omission of this interplane correlation, common when bunches are reconstructed from lower-dimensional measurements, degrades downstream predictions. This talk will also describe the novel diagnostics supporting this work. This includes ongoing improvements to efficiency of the 6D phase space measurement as well as recent achievement of six orders of dynamic range in 2D phase space.

Ruisard, Kiersten↗
DOE OSTI2024

Majorana chain and Ising model - (non-invertible) translations, anomalies, and emanant symmetries

We study the symmetries of closed Majorana chains in 1+1d, including the translation, fermion parity, spatial parity, and time-reversal symmetries. The algebra of the symmetry operators is realized projectively on the Hilbert space, signaling anomalies on the lattice, and constraining the long-distance behavior. In the special case of the free Hamiltonian (and small deformations thereof), the continuum limit is the 1+1d free Majorana CFT. Its continuum chiral fermion parity (-1)^{F_L} ( − 1 ) F L emanates from the lattice translation symmetry. We find a lattice precursor of its mod 8 ’t Hooft anomaly. Using a Jordan-Wigner transformation, we sum over the spin structures of the lattice model (a procedure known as the GSO projection), while carefully tracking the global symmetries. In the resulting bosonic model of Ising spins, the Majorana translation operator leads to a non-invertible lattice translation symmetry at the critical point. The non-invertible Kramers-Wannier duality operator of the continuum Ising CFT emanates from this non-invertible lattice translation of the transverse-field Ising model.

Physics↗
DOE OSTI2025

In-flight performance of the XRISM/Resolve detector system

The Resolve instrument was launched on board the XRISM observatory in early September 2023. The Resolve spectrometer is based on a high-sensitivity X-ray calorimeter detector system (DS) that has been successfully deployed in many ground and sub-orbital spectrometers. However, the Resolve instrument is the first long-term implementation in space. The instrument will provide essential diagnostics for nearly every class of X-ray emitting objects, from galactic supernova remnants to the outskirts of galaxy clusters, without degradation for spatially extended objects. The Resolve DS consists of a 36-pixel microcalorimeter array operated at a heat sink temperature of 50 mK. In pre-flight testing, the DS demonstrated a resolving power of better than 1300 at 6 keV with a simultaneous bandpass from below 0.3 keV to above 12 keV and a timing precision better than 100μs. An anti-coincidence detector placed directly behind the microcalorimeter array effectively suppresses background. The detector energy-resolution budget included terms for interference from the Resolve cooling system and the spacecraft. Additional terms for energy-scale stability, on-orbit effects, and use of mid-grade events were also included, predicting an end-of-life, on-orbit performance for high- and mid-resolution grade events that meet the requirement of 7 eV FWHM at 6 keV. Here, we discuss the actual on-orbit performance of the Resolve DS and compare this with the performance in pre-flight testing, on-orbit predictions, and the almost identical Hitomi/SXS instrument. We will also discuss the on-orbit gain stability, an assessment of on-orbit interference, and measurements of the on-orbit background.

Astronomy and AstroPhysics↗
DOE OSTI2024

WFIP3 High Frequency Radar / Processed Data

These data were collected by Kirincich as part of the DOE Wind Forecast Improvement Project, based on support from NOAA-IOOS, WHOI, and DOE. The data consist of estimates of the near-surface horizontal (East and North) ocean currents made via High Frequency (HF) radar-based remote sensing of the Ocean backscatter spectrum. The effective measurement depth of the WHOI HF radars is 0.5 m below the ocean surface. The WHOI HF radar system, as operated during the experiment, consisted of 4 land-based sites spaced at 30-40km intervals along the area spanning from Nantucket,MA to Narragansett,RI that operate at 16 MHz and 25 MHz systems (see Kirincich et al, 2019 and Kirincich et al 2022 for details). Received doppler spectra from each were processed using the advanced methods of Kirincich et al. 2012, and Kirincich et al 2019, and unpublished work Kirincich, 2024) into radial or elliptical velocity estimates every 30 min based on a 30 min averaging window.

17 WIND ENERGY↗