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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

DNN-based Signal Processing for Liquid Argon Time Projection Chambers

We investigate a deep learning-based signal processing for liquid argon time projection chambers (LArTPCs), a leading detector technology in neutrino physics. Identifying regions of interest (ROIs) in LArTPCs is challenging due to signal cancellation from bipolar responses and various detector effects observed in real data. We approach ROI identification as an image segmentation task, and employ a U-ResNet architecture. The network is trained on samples that incorporate detector geometry information and include a range of detector variations. Our approach significantly outperforms traditional methods while maintaining robustness across diverse detector conditions. This method has been adopted for signal processing in the Short-Baseline Neutrino program and provides a valuable foundation for future experiments such as the Deep Underground Neutrino Experiment.

Bhat, Avinay [Chicago U.]↗
NASA NTRS1987

Analytical approach to peel stresses in bonded composite stiffened panels

A closed-form solution was obtained for the stresses and displacements of two bonded beams. A system of two fourth-order and two second-order differential equations with the associated boundary equations was determined using a variational work approach. A FORTRAN computer program was devised to solve for the eigenvalues and eigenvectors of this system and to calculate the coefficients from the boundary conditions. The results were then compared with NASTRAN finite-element solutions and shown to agree closely.

Barkey, Derek A.↗
DOE OSTI2024

Role of momentum in the generator-coordinate method applied to barrier penetration

Nuclear fission at barrier-top energies is conventionally modeled by a one-dimensional Schrödinger equation applied to internal fission channels, but that treatment is hard to justify in the configuration-interaction approach to nuclear Hamiltonians. Here we show that inclusion of states of finite momentum by the generator coordinate method (GCM) considerably extends the range of energies at which GCM-based Hamiltonians could reproduce the Schrödinger treatment. Furthermore, the transmission probabilities for crossing the barrier are calculated by a discrete version of Kohn's variational method, which may also be useful for other systems of interacting fermions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Counterdiabatic Driving with Performance Guarantees

Counterdiabatic (CD) driving has the potential to speed up adiabatic quantum state preparation by suppressing unwanted excitations. However, existing approaches either require intractable classical computations or are based on approximations that do not have performance guarantees. We propose and analyze a nonvariational, system-agnostic CD expansion method and analytically show that it converges exponentially quickly in the expansion order. In finite systems, the required resources scale inversely with the spectral gap, which we argue is asymptotically optimal. To extend our method to the thermodynamic limit and suppress errors stemming from high-frequency transitions, we leverage finite-time adiabatic protocols. In particular, we show that a time determined by the quantum speed limit is sufficient to prepare the desired ground state, without the need to optimize the adiabatic trajectory. Numerical tests of our method on the quantum Ising chain show that our method can outperform state-of-the-art variational CD approaches.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Evaluating switch lifetime in soft-switched single-stage differential-mode SST

The reliability of semiconductor switches in single-stage differential-mode solid-state transformers (DM-SSTs) has not been systematically evaluated under soft-switching operation and realistic grid conditions. This paper presents a switch-level reliability analysis for soft-switched and hard-switched DM-SST configurations by integrating converter-specific power loss modeling with empirical lifetime prediction. Analytical derivation of device current profiles specific to the DM-SST is used to characterize electrothermal stress, which is then mapped to lifetime using degradation models obtained from power cycling tests (PCTs). Applied to realistic SST load profiles and grid voltage variations, this approach provides a probabilistic prediction of switch lifetime for the DM-SST. Lifetime estimates for both SiC MOSFETs and Si IGBTs are presented, offering insight into device degradation under converter operating conditions. The results quantify the reliability benefits of soft switching in single-stage SSTs, highlighting how switching dynamics influence long-term switch degradation.

14 SOLAR ENERGY↗
DOE OSTI2025

Sensitivity of the Shallow‐To‐Deep Convective Transition to Moisture and Wind Shear in the Amazon

Deep convection is the primary influence on weather and climate in tropical regions. However, understanding and simulating the shallow‐to‐deep (STD) convective transition has long been challenging. Here, we conduct high‐resolution numerical simulations to assess the environmental controls on the evolution of isolated convection in the Amazon during the wet season. The large‐scale forcing derived through a constrained variational analysis approach for the GoAmazon2014/5 Experiment is used in the simulations. Through sensitivity experiments, we examine the relative importance of moisture and wind shear in controlling the shallow‐to‐deep convective transition for isolated convective events. Convection exhibits the greatest sensitivity to humidity within the lowest 1.5 km, where a 4 mm reduction in column water vapor nearly suppresses ice water formation on deep convective days. In contrast, a reduction in column water vapor in the free troposphere by a factor of two or more is necessary to produce a comparable impact on convection. Increasing low‐level wind speed from 6 to 9 m s -1 enhances afternoon deep convection, raising the cloud ice mixing ratio by approximately 25%. Conversely, upper‐level wind shear reveals the weakest correlation with daytime convection in our simulations. Our results help characterize the role of moisture and wind shear on the STD transition and our understanding of the underlying mechanisms.

environmental controls↗
DOE OSTI2024

Wavelength modulation laser-induced fluorescence for plasma characterization

Laser-Induced Fluorescence (LIF) spectroscopy is an essential tool for probing ion and atom velocity distribution functions (VDFs) in complex plasmas. VDFs carry information about the kinetic properties of species that is critical for plasma characterization. Accurate interpretation of these functions is challenging due to factors such as multicomponent distributions, broadening effects, and background emissions. Our research investigates the use of Wavelength Modulation (WM) LIF to enhance the sensitivity of VDF measurements. Unlike standard Amplitude Modulation (AM) methods, WM–LIF measures the derivative of the LIF signal. This approach makes variations in VDF shape more pronounced. VDF measurements with WM–LIF were investigated with both numerical modeling and experimental measurements. The developed model enables the generation of both WM and AM signals, facilitating comparative analysis of fitting outcomes. Experiments were conducted in a weakly collisional argon plasma with magnetized electrons and non-magnetized ions. Measurements of the argon ion VDFs employed a narrow-band tunable diode laser, which scanned the 4p 4 D 7/2 –3d 4 F 9/2 transition centered at 664.553 nm in vacuum. A lock-in amplifier detected the second harmonic WM signal, which was generated by modulating the laser wavelength with an externally controlled piezo-driven mirror of the diode laser. Finally, our findings indicate that the WM–LIF signal is more sensitive to fitting parameters, allowing for better identification of VDF parameters such as the number of distribution components, their temperatures, and velocities. In addition, WM–LIF can serve as an independent method to verify AM measurements and is particularly beneficial in environments with substantial light noise or background emissions, such as those involving thermionic cathodes and reflective surfaces.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

State preparation of lattice field theories using quantum optimal control

Here, we explore the application of quantum optimal control (QOC) techniques to state preparation of lattice field theories on quantum computers. As a first example, we focus on the Schwinger model, quantum electrodynamics in 1+1 dimensions. We demonstrate that QOC can significantly speed up the ground state preparation compared to gate-based methods, even for models with long-range interactions. Using classical simulations, we explore the dependence on the interqubit coupling strength and the device connectivity, and we study the optimization in the presence of noise. While our simulations indicate potential speedups, the results strongly depend on the device specifications. In addition, we perform exploratory studies on the preparation of thermal states. Our results motivate further studies of QOC techniques in the context of quantum simulations for fundamental physics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Neuralized fermionic tensor networks for quantum many-body systems

In this work, we describe a class of neuralized fermionic tensor network states (NN-fTNSs) that introduce nonlinearity into fermionic tensor networks through configuration-dependent neural network transformations of the local tensors. The construction uses the fTNS algebra to implement a natural fermionic sign structure and is compatible with standard tensor network algorithms but gains enhanced expressivity through the neural network parametrization. Using the 1D and 2D Fermi-Hubbard models as benchmarks, we demonstrate that NN-fTNSs achieve order of magnitude improvements in the ground-state energy compared to pure fTNSs with the same bond dimension and can be systematically improved through both the tensor network bond dimension and the neural network parametrization. Compared to existing fermionic neural quantum states based on Slater determinants and Pfaffians, NN-fTNSs offer a physically motivated alternative fermionic structure. Furthermore, compared to such states, NN-fTNSs naturally exhibit improved computational scaling and we demonstrate a construction that achieves linear scaling with the lattice size.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Enhancing Short-Range Weather Forecasts through Temporal Variation Encoding: A Multiperiod Embedding Approach

Machine learning (ML) techniques have emerged as promising approaches to improve regional weather forecast accuracy and reliability through data-driven methods. We propose a novel ML-based weather forecasting model, the Multiperiod Embed Net (MPENet). A key distinguishing feature of MPENet is its explicit utilization of the inherent cyclic nature in weather dynamics, unlike the autoregressive strategies commonly used in other ML weather forecasting approaches. Critical cyclic structures are identified via Fourier analyses of dynamic time series. Cyclicity in the convolutional representation is achieved by transforming one-dimensional time series of meteorological variables into two-dimensional tensors based on identified periods. This approach enables the model to leverage intrinsic weather patterns, enhancing regional forecast performance. To demonstrate the effectiveness of MPENet, we conduct a comparative analysis with Nvidia’s FourCastNet. Both models are trained on High-Resolution Rapid Refresh (HRRR) data from 2015 to 2022, over a 192 km × 192 km region in Tennessee. The comparisons are performed locally at two specific locations known to have different weather dynamics due to orographic effects: Crossville, on the relatively flat Cumberland Plateau with fewer topographic airflow disruptions, and Oak Ridge, in the ridge-and-valley region, where airflow is heavily influenced by surrounding valleys and mountains. Our results indicate that FourCastNet achieves strong accuracy at very short lead times, while MPENet maintains competitive skill and shows advantages in capturing temporal evolution over longer periods. Cross-correlation analyses of MPENet and FourCastNet predictions with the HRRR data suggest that encoding critical cyclicity into the network architecture leads to improvements in the forecasting skill.

Artificial intelligence↗
NASA NTRS1972

Jet noise

The main conclusions reached are: (1) At low subsonic jet exhaust velocities, jet noise varies as the velocity to the eighth power; (2) at high subsonic exhaust velocities, jet noise approaches a variation with velocity to the third power; (3) use of the jet density squared overcorrects density effects on jet noise; (4) subsonic and supersonic jet noise levels can be predicted; and (6) use of multielement nozzles and acoustically lined ejectors significantly suppress jet noise at intermediate jet exhaust velocities.

Vonglahn, U. H.↗
NASA NTRS1978

Analysis of squaring circuit mechanizations in Costas and squaring loops

The paper discusses implementations of the carrier recovery loop for suppressed carrier binary phase shift keyed signals. The tracking performance of a practical squaring loop where the times-two multiplier is mechanized as a limiter/multiplier combination is developed. This produces the absolute value of the arriving signal which is practical in terms of low signal-to-noise ratios, a wide dynamic range of signal level, and temperature variations. The approach is compared to the usual squaring loop whose squaring circuit is the times-two multiplier exhibiting a square law characteristic.

Lindsey, W. C.↗
NASA NTRS1981

On the multiple scattering of VHF/UHF waves in the equatorial ionosphere

Using amplitude data of radio beacons at 40, 140, and 360 MHz from ATS 6 (phase II), an attempt has been made to study scattering of these waves in the equatorial ionosphere. A comparison of observed scintillation index S sub 4 with the theoretical results of the multiple scattering approach and variation of autocorrelation time with frequency indicates that this theory explains the results to a large extent. A comparison of power spectra of amplitude records with the ionograms of a nearby equatorial station has led to the following conclusions: the change from a weak scattering regime to a strong scattering regime is gradual and occurs because of the gradual decrease in the scale size of the irregularities (i.e., broadening of the spectra) and the gradual increase in the thickness of the irregular region.

Vats, H. O.↗
NASA NTRS1981

On the measurement of precipitation frequencies by passive microwave radiometery

Over most of the microwave spectrum, raindrops both absorb and scatter radiation producing large changes in brightness temperatures relative to clear or cloudy conditions. Since the structure of rain varies substantially for different rain rates and climatological backgrounds, the raindrop size distribution, the rain layer thickness and the ice clouds above the rain layer are all important inputs to the model computations. The subsequent modeling involves applying the Mie theory to derive the absorption and scattering effects and the radiative transfer calculation is based upon a variational iterative approach which takes account of the multiple scattering effect of the rain layer. Results over both ocean and land backgrounds are demonstrated. It is also demonstrated that by using discrimination tests of the radiometric data, the rain/no rain decision can be made and the rainfall rate can be retrieved from a statistical inversion technique.

Kidder, S. Q.↗
NASA NTRS1983

Three dimensional global modeling of atmospheric CO2

A model was developed to study the prospects of extracting information on carbon dioxide sources and sinks from observed CO2 variations. The approach uses a three dimensional global transport model, based on winds from a 3-D general circulation model (GCM), to advect CO2 noninteractively, i.e., as a tracer, with specified sources and sinks of CO2 at the surface. The 3-D model employed is identified and biosphere, ocean and fossil fuel sources and sinks are discussed. Some preliminary model results are presented.

Fung, I.↗
NASA NTRS1984

The nature of the metal-CO interaction and bonding

The adsorption of CO on metal surfaces is represented by molecular orbital cluster models of CO at an on top site and adsorbed normal to the surface carbon end down. Ab initio SCF and MCSCF calculations are performed for several clusters. The new constrained space orbital variation CSOV approach is used to analyze the bonding and to compare CO adsorption on Al, representative of sp metals, with that on Cu, representative of transition metals. There is a large repulsion between the superposed free CO and metal charge distributions which is considerably smaller for Cu than for Al because there are fewer valence sigma electrons for Cu than for Al. The CSOV analysis shows that the metal to CO pi donation is much more important than the CO to metal sigma donation. It is also shown that for Cu, the d pi contribution to the metal pi donation is larger than the valence 4p pi contribution. The d pi donation is compared between Fe, Ni, and Cu and this donation and the metal-CO interaction are found to be different in the order Fe greater than Ni greater than Cu.

Bagus, P. S.↗
NASA NTRS1985

An initialization procedure for assimilating geostationary satellite data into numerical weather prediction models

An attempt was made to offset the limitations of GEO satellites for supplying timely initialization data for numerical weather prediction models (NWP). The NWP considered combined an isentropic representation of the free atmosphere with a sigma-coordinate model for the lower 200 mb. A flux form of the predictive equations described vertical transport interactions at the boundary of the two model domains, thereby accounting for the poor vertical temperature and wind field resolution of GEO satellite data. A variational analysis approach was employed to insert low resolution satellite-sensed temperature data at varying rates. The model vertical resolution was limited to that available from the satellite. Test simulations demonstrated that accuracy increases with the frequency of data updates, e.g., every 0.5-1 hr. The tests also showed that extensive cloud cover negates the capabilities of IR sensors and that microwave sensors will be needed for temperature estimations for 500-1000 mb levels.

Gal-Chen, T.↗
NASA NTRS1989

Nonprincipal plane scattering of flat plates and pattern control of horn antennas

Using the geometrical theory of diffraction, the traditional method of high frequency scattering analysis, the prediction of the radar cross section of a perfectly conducting, flat, rectangular plate is limited to principal planes. Part A of this report predicts the radar cross section in nonprincipal planes using the method of equivalent currents. This technique is based on an asymptotic end-point reduction of the surface radiation integrals for an infinite wedge and enables nonprincipal plane prediction. The predicted radar cross sections for both horizontal and vertical polarizations are compared to moment method results and experimental data from Arizona State University's anechoic chamber. In part B, a variational calculus approach to the pattern control of the horn antenna is outlined. The approach starts with the optimization of the aperture field distribution so that the control of the radiation pattern in a range of directions can be realized. A control functional is thus formulated. Next, a spectral analysis method is introduced to solve for the eigenfunctions from the extremal condition of the formulated functional. Solutions to the optimized aperture field distribution are then obtained.

Balanis, Constantine A.↗