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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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NASA NTRS2020

Simultaneous Retrieval of Surface Roughness Parameters for Bare Soils From Combined Active–Passive Microwave SMAP Observations

An active–passive microwave retrieval algorithm for simultaneous determination of soil surface roughness parameters [vertical root-mean-square (RMS) height ( s ) and horizontal correlation length ( l )] is presented for bare soils. The algorithm is based on active–passive microwave covariation, including the improved Integral Equation Method (I(exp 2) EM), and is tested with global soil moisture active passive (SMAP) observations. The estimated retrieval results for s and l are overall consistent with values in the literature, indicating the validity of the proposed algorithm. Sensitivity analyses showed that the developed roughness retrieval algorithm is independent of permittivity for E(sub s) > 10 [-]. Furthermore, the physical model basis of this approach (I(exp 2) EM) allows the application of different autocorrelation functions (ACF), such as Gaussian and exponential ACFs. Global roughness retrieval results confirm bare areas in deserts such as Sahara or Gobi. However, the type of ACF used within roughness parameter estimation is important. Retrieval results for the Gaussian ACF describe a rougher surface than retrieval results for the exponential ACF. No correlations were found between roughness results and the amount of precipitation or the soil texture, which could be due to the coarse spatial resolution of the SMAP data. The extension of this approach to vegetated soils is planned as an add-on study.

Correlation length↗

NASA NTRS1981

Functional methods for waves in random media

Some basic ideas in functional methods for waves in random media are illustrated through a simple random differential equation. These methods are then generalized to solve certain random parabolic equations via an exponential representation given by the Feynman-Kac formula. It is shown that these functional methods are applicable to a number of problems in random wave propagation. They include the forward-scattering approximation in Gaussian white-noise media; the solution of the optical beam propagation problem by a phase-integral method; the high-frequency scattering by bounded random media, and a derivation of approximate moment equations from the functional integral representation.

Chow, P. L.↗

NASA NTRS1981

Functional methods for waves in random media

Some basic ideas in functional methods for waves in random media are illustrated through a simple random differential equation. These methods are then generalized to solve certain random parabolic equations via an exponential representation given by the Feynman-Kac formula. It is shown that these functional methods are applicable to a number of problems in random wave propagation. They include the forward-scattering approximation in Gaussian white-noise media; the solution of the optical beam propagation problem by a phase-integral method; the high-frequency scattering by bounded random media; and a derivation of approximate moment equations from the functional integral representation.

Chow, P. L.↗

DOE OSTI2026

From Rules to Reasoning: A Survey of Large Language Model-Based Approaches to Scientific Hypothesis and Idea Generation

Scientific hypothesis generation represents a fundamental challenge in contemporary research due to exponentially expanding literature volumes and increasing disciplinary specialization. Large language models (LLMs) have emerged as transformative tools for automated scientific discovery, moving beyond traditional rule-based and literature-mining approaches. Four paradigmatic approaches define current LLM-driven hypothesis generation: direct prompting and fine-tuning methods, knowledge-enhanced frameworks integrating retrieval-augmented generation (RAG), multi-agent collaborative systems simulating research teams, and reasoning-focused approaches implementing cognitive architectures. Domain-specific applications demonstrate statistical equivalence to human expert performance in social psychology, experimental validation in biomedical research, and near-expert quality in astronomy. Evaluation methodologies encompass human expert assessment, LLM-as-judge frameworks, and comprehensive benchmarking systems. Technical challenges include hallucination management, knowledge integration limitations, and balancing novelty with feasibility. Future directions emphasize hybrid neural-symbolic architectures and sophisticated human-AI collaboration models for responsible scientific discovery acceleration.

AI-driven discovery↗

NASA NTRS1986

SMM observation of a cosmic gamma-ray burst from 20 keV to 100 MeV

The Solar Maximum Mission gamma-ray spectrometer has detected an intense gamma-ray burst that occurred on August 5, 1984. The burst originated from a source in the constellation Hydra and lasted about 45 s. Its integral fluence at 20 keV was 0.003 erg/sq cm. Spectral evolution similar to other bursts detected by SMM was observed. The overall shape of the spectrum from 20 keV to 100 MeV, on timescales as short as 2 s, is relatively constant. This shape can be fitted by the sum of an exponential-type function and a power law. There is no evidence for narrow or broadened emission lines.

Share, G. H.↗

NASA NTRS1990

Evidence for fast dynamo action in a chaotic web

The evolution of a magnetic field in a chaotic web is studied. The model flow possessing the web is closely related to the nearly integrable ABC flow with A = B and C much less than 1. The magnetic diffusivity is taken to be zero and the field is followed using the Cauchy solution. It is found that the flow folds the magnetic field constructively, in the sense that the average magnetic field in a chaotic region grows exponentially in time. This is suggestive of fast dynamo action, although the effect of diffusion of the strong streamwise magnetic field remains to be assessed.

Gilbert, A. D.↗

DOE OSTI2024

Modeling stimulated Brillouin backscatter from outer-cone quads across multiple inertial confinement fusion hohlraum designs

Stimulated Brillouin scattering (SBS) is a potential risk for laser damage in the experiments carried out at the National Ignition Facility (NIF), and by altering the energy deposition pattern in hohlraums, it affects the symmetry of indirect-drive inertial confinement fusion implosions. We have surveyed backward SBS on outer-cone quads across NIF integrated hohlraums of various platforms numerically, using three-dimensional (3D) simulations with the backscatter code pF3D [Berger et al. Phys. Plasmas 5, 4337 (1998)] and ray-based gain calculations. Simulated reflected powers and energies, as well as the spectrum of reflected light all compare favorably with measurements. Ray-based calculations of exponential SBS amplification (“gain”), which assume a strongly damped plasma wave and steady-state response, are performed using a novel method that includes the 3D speckled field of the laser that drives SBS. This approach is useful for understanding qualitative differences between hohlraum designs and identifying regions susceptible to SBS within hohlraums. Quantitatively, gains are not found to correlate with SBS reflectivities in 3D, necessitating fully wave-based calculations that naturally include diffraction and various temporal dependencies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Eigenstate thermalization and disappearance of quantum many-body scar states in weakly interacting fermion systems

The recent discovery of quantum many-body scar states has revealed the possibility of having states with low entanglement that violate the eigenstate thermalization hypothesis in nonintegrable systems. Eigenstates with low entanglement entropy are rare but naturally exist in the integrable system of free fermions. Here, we demonstrate analytically that these atypical states would be always eliminated when an arbitrary weak interaction is introduced between the fermions. In particular, we show that the probability of having a many-body scar state with entanglement entropy satisfying a sub-volume scaling law decreases double exponentially as the system size. Furthermore, our results provide a quantitative argument for the disappearance of scar states in interacting fermion systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Efficient and flexible multirate temporal adaptivity

In this work we present two new families of multirate time step adaptivity controllers, that are designed to work with embedded multirate infinitesimal (MRI) time integration methods for adapting time steps when solving problems with multiple time scales. We compare these controllers against competing approaches on two benchmark problems, showing that the proposed methods offer dramatically improved performance and flexibility. The combination of embedded MRI methods and the proposed controllers enable adaptive simulations of problems with a potentially arbitrary number of time scales, achieving high accuracy while maintaining low computational cost. Additionally, we introduce a new set of embeddings for the family of explicit multirate exponential Runge–Kutta (MERK) methods of orders 2 through 5, resulting in the first-ever fifth-order embedded MRI method. Finally, we compare the performance of a wide range of embedded MRI methods on our benchmark problems to provide guidance on how to select an appropriate MRI method and multirate controller.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Pyrolysis of high-density polyethylene: Degradation behaviors, kinetics, and product characteristics

Pyrolysis is a promising technology for converting plastic waste into valuable raw materials while offering a potential solution to the global plastic pollution crisis. In this study, the thermal pyrolysis of high-density polyethylene (HDPE) is investigated in a drop tube reactor under nearly isothermal conditions. The impact of reaction temperature and gas/volatile residence time on carbon conversion and product distribution is examined across a range of 500–900°C and 3.6–32.2s, respectively. Non-condensable gas products detected by online mass spectrometry are H 2 , CH 4 , C 2 H 4 , C 2 H 6 , C 3 H 6 , and C 3 H 8 . At elevated temperatures and prolonged residence time, H 2 yield reaches as high as 8.6 wt% of the initial HDPE mass due to intensified cracking reactions of C 2 –C 3 hydrocarbons and long-chain aliphatic compounds. Consequently, pyrolysis tars consist mainly of polycyclic aromatic hydrocarbons (PAHs) with 5–7 rings, accompanied by visible coke deposition within the reactor. HDPE decomposition to volatiles is an endothermic process and it is complete at a temperature between 492°C and 525°C, depending on the heating rate employed, from non-isothermal thermogravimetric analysis and differential scanning calorimetry (TGA-DSC) measurements. The thermal degradation of HDPE pellets follows the two-dimensional nucleation growth model for conversion levels up to 0.8 with an apparent activation energy of 259–270 kJ/mol and a pre-exponential factor of 4.83 × 10 17 –1.37 × 10 19 min -1 , determined from various isoconversional methods such as Flynn-Wall-Ozawa (FWO), Kissinger-Akahira-Sunose (KAS), and Starink, along with Criado's master plots. Further, these findings provide valuable insights into optimizing process parameters and refining reactor design for pyrolysis, which can be integrated with gasification and reforming processes to enhance hydrogen production on a larger scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗

NASA NTRS1973

Bayesian estimation of life parameters in the Weibull distribution.

Development of a Bayesian analysis of the scale and shape parameters in the Weibull distribution and the corresponding reliability function with respect to the usual life-testing procedures. For the scale parameter theta, Bayesian estimates of theta and reliability are obtained for the uniform, exponential, and inverted gamma prior probability densities. Bhattacharya's results (1967) for the one-parameter exponential life-testing distribution are reduced to a special case of these results. A fully Bayesian analysis of both the scale and shape parameters is developed by assuming independent prior distributions; since in the latter case, analytical tractability is not possible, Bayesian estimates are obtained through a conjunction of Monte Carlo simulation and numerical-integration techniques. In both cases, a computer simulation is carried out, and a comparison is made between the Bayesian and the corresponding minimum-variance unbiased, or maximum likelihood, estimates. As expected, the Bayesian estimates are superior.

Canavos, G. C.↗

DOE OSTI2024

Hadamard products and BPS networks

We study examples of fourth-order Picard-Fuchs operators that are Hadamard products of two second-order Picard-Fuchs operators. Each second-order Picard-Fuchs operator is associated with a family of elliptic curves, and the Hadamard product computes period integrals on the fibred product of the two elliptic surfaces. We construct 3-cycles on this geometry as the union of 2-cycles in the fibre over contours on the base. We then use the special Lagrangian condition to constrain the contours on the base. This leads to a construction that is reminiscent of spectral networks and exponential networks that have previously appeared in string theory literature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1977

Control logic to track the outputs of a command generator or randomly forced target

A procedure is presented for synthesizing time-invariant control logic to cause the outputs of a linear plant to track the outputs of an unforced (or randomly forced) linear dynamic system. The control logic uses feed-forward of the reference system state variables and feedback of the plant state variables. The feed-forward gains are obtained from the solution of a linear algebraic matrix equation of the Liapunov type. The feedback gains are the usual regulator gains, determined to stabilize (or augment the stability of) the plant, possibly including integral control. The method is applied here to the design of control logic for a second-order servomechanism to follow a linearly increasing (ramp) signal, an unstable third-order system with two controls to track two separate ramp signals, and a sixth-order system with two controls to track a constant signal and an exponentially decreasing signal (aircraft landing-flare or glide-slope-capture with constant velocity).

Trankle, T. L.↗

NASA NTRS1983

Variation in light intensity with height and time from subsequent lightning return strokes

Photographic measurements of relative light intensity as a function of height and time have been conducted for seven return strokes in two lightning flashes at 7.8 and 8.7 km ranges, using film which possesses an approximately constant spectral response in the 300-670 nm range. The amplitude of the initial light peak is noted to decrease exponentially with height, with a decay constant of 0.6-0.8 km. The logarithm of the peak light intensity near the ground is found to be approximately proportional to the initial peak electric field intensity, implying that the current decrease with height may be much slower than the light decrease. Absolute light intensity is presently estimated through the integration of the photographic signals from individual channel segments, in order to simulate the calibrated, all-sky photoelectric data of Guo and Krider (1982).

Jordan, D. M.↗

NASA NTRS1999

A Diagnostic Analysis of the Kennedy Space Center LDAR Network: Data Characteristics - 1

An analytical framework is developed in which to analyze climatological VHF (66 MHz) radiation measurements taken by the Kennedy Space Center Lightning Detection and Ranging (LDAR) network. A 19-month noise-filtered sample of LDAR observations is examined using this framework. It is found that the climatological VHF source density as observed by LDAR falls off approximately 10 dB every 71 km of ground range away from the network centroid (a 31 km e-folding scale). From this framework it is inferred that the underlying source distribution is likely inverse exponential in amplitude, with a log-slope of 126-147 mW(sup -1/2). The underlying vertical distribution of VHF sources is approximately normally distributed with a mean altitude of 9 km and a standard deviation of 2.7 km; this implies that the loss of below-horizon sources has a negligible effect on column-integrated source densities within 200 km ground range. At medium to far ranges, location errors are primarily radial and have a slightly asymmetric distribution whose first moment increases as range squared. Error moments estimated from observed lightning are significantly higher than those from aircraft-based signal generator or analytic solution estimates, suggesting that timing errors arising from poor signal identification and discrimination may dominate over timing errors arising from nominal sensor resolution. The VHF source properties of individual LDAR-observed flashes are computed and an analytic expression for flash detection efficiency vs. range is derived. This reveals nearly constant flash detection efficiency to 80-94 km range from the network centroid.

Boccippio, D. J.↗

NASA NTRS2009

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗

NASA NTRS2009

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Molthan, Andrew L.↗