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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Glauber-Theory Calculations of High-Energy Nuclear Scattering Observables Using Variational Monte Carlo Wave Functions

Experiments using intermediate- to high-energy radioactive nuclear beams present numerous findings. Extracting important properties of physical observables relies on a firm theoretical analysis. Though Glauber theory is believed to work well, no convincing calculation has so far been done. Here, we perform ab initio Glauber theory calculations of both elastic differential cross sections and total reaction cross sections for p+ 12 C, 12 C+ 12 C, and 6 He+ 12 C systems. The wave functions of both 6 He and 12 C are generated by variational Monte Carlo calculations with spatial and spin-isospin correlations induced by realistic two- and three-nucleon potentials. Glauber’s phase-shift function is computed by Monte Carlo integration up to all orders of nucleon-nucleon multiple scatterings. We show an excellent performance of the Glauber description to the selected data on the above systems. We also find that the cumulant expansion of the phase-shift function converges rapidly up to the second order for the above systems. This finding will open up interesting applications for the analysis of high-energy nuclear experiments.

Horiuchi, W. [Osaka Metropolitan University (Japan↗
NASA NTRS1979

False lock performance of quadriphase receivers

Quadriphase receivers, like biphase receivers, have the ability to false lock on a sideband on the data modulation. The theory associated with this phenomenon for receivers of binary phase-shift-keying (BPSK), using Costas loop demodulation, has recently been documented in the literature. This paper considers the corresponding theory for receivers of balanced quadriphase-shift-keying (QPSK) employing a quadriphase Costas loop (or equivalent fourth-power loop) for demodulation. Specific closed form expressions for false lock performance are developed and numerically evaluated for the particular case of single pole arm filters and an NRZ data format for each of the two statistically independent quadrature modulations.

Simon, M. K.↗
DOE OSTI2023

Wildland Fires in the Subtropical Hill Forests of Southeastern Bangladesh

The first ever comprehensive study on wildland fires in Bangladesh is carried out to develop a fire prevention and prediction method. The major causes of huge wildland fires (88%) in the subtropical Chittagong Hill forest (43% of total) of southern Bangladesh are reported as shifting cultivation, grazing and unauthorized settlement. We used satellite hotspot (HS) data from 2003 to 2021 (a total of 54,669 HSs) to clarify the spatio-temporal structure of wildland fires. Fire weather conditions were analyzed using various weather data and synoptic-scale weather maps at different air levels. Fires concentrated from March through April or a transitional period from the dry season, caused by the Asian winter monsoon, to the wet season, due to the Asian summer monsoon. Fire occurrence depended on dry conditions and pre-monsoon showers and their timing. The difference in 925 hPa heights of high and low pressure systems may be attributed to the different types of the Asian winter and summer monsoons. The average maximum air temperature and incident shortwave solar energy in April were the highest and strongest, contributing fire-prone weather conditions. Based on the analysis, a fire prevention and prediction method will be developed, and this report may also facilitate the establishment of future CO 2 reduction measures for Bangladesh.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Glauber’s Salt Composites for HVAC Applications: A Study on the Use of the T-History Method with a Modified Data Evaluation Methodology

Phase change materials (PCMs) can be utilized in buildings for peak load shifting in air conditioning systems, and the use of salt hydrate-based PCMs can reduce the cost of thermal energy storage devices. Glauber’s salt is an economical salt hydrate PCM with a melting point of around 32 °C. However, the desired melting range typically falls between 18 and 22 °C for building air conditioning applications. Although many researchers have characterized Glauber’s salt and its composites with modified melting points, enthalpy–temperature curves for composites of Glauber’s salt and NaCl are unavailable. In this study, we report the melting and solidification enthalpy–temperature curves for two different composites of Glauber’s salt and NaCl with a melting point of 21 °C obtained by the T-history method. Both composites contain NaCl to suppress the melting point, borax to reduce supercooling, and sodium polyacrylate as a thickener to enhance cyclic stability. The first composite with 12 wt.% NaCl demonstrated 139 kJ·kg−1 of latent heat of fusion, and the second composite with 9 wt.% NaCl demonstrated 171 kJ·kg−1. Both the composites have high volumetric energy densities compared to their organic counterparts with similar melting points.

Chemistry↗
NASA NTRS1975

System for generating timing and control signals

A system capable of generating every possible data frame subperiod and delayed subperiod of a data frame of length of M clock pulse intervals (CPIs) comprised of parallel modulo-m sub i counters is presented. Each m sub i is a prime power divisor of M and a cascade of alpha sub i identical modulo-p sub i counters. The modulo-p sub i counters are feedback shift registers which cycle through p sub i distinct states. Every possible nontrivial data frame subperiod and delayed subperiod is derived and a specific CPI in the data frame is detected. The number of clock pulses required to bring every modulo-p sub i counter to a respective designated state or count is determined by the Chinese remainder theorem. This corresponds to the solution of simultaneous congruences over relatively prime moduli.

Perlman, M.↗
DOE OSTI2021

Reconstruction of the Room D, B, G, and Q Closure Histories at the Waste Isolation Pilot Plant

Experimental measurements of room closure in salt repositories are valuable for understanding the evolution of the underground and for validating geomechanical models. Room closure was measured during a number of experiments at the Waste Isolation Pilot Plant (WIPP) during the 1980's and 1990's. Most rooms were excavated using a multi-pass mining sequence, where each pass necessarily destroyed some of the mining sequence closure measurement points. These destroyed points were promptly reinstalled to capture the closure after the mining pass. After the room was complete, the mining sequence closure measurement stations were supplemented with remotely read closure measurement stations. Although many aspects of these experiments were thoroughly documented, the digital copies of the closure data were inadvertently destroyed, the non-trivial process of zeroing and shifting the raw closure measurements after each mining pass was not precisely described, the various closure measurements within a given room were not directly compared on the same plot, and the measurements were collected for several years longer than previously reported. Consequently, the hand-written mining sequence closure measurements for Rooms D, B, G, and Q were located in the WIPP archives, digitized, and reanalyzed for this report. The process of reconstructing the mining sequence closure histories was documented in detail and the raw data can be found in the appendices. Within the mid-section of a given room, the reconstructed closure histories were largely consistent with other mining sequence and remotely read closure histories, which builds confidence in the experiments and suggests that plane strain is an appropriate modeling assumption. The reconstructed closure histories were also reasonably consistent with previously published results, except in one notable case: the reconstructed Room Q closure histories 30 days after excavation were about 45 % less than the corresponding closures reported in Munson's 1997 capstone paper.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Data and scripts associated with a manuscript analyzing ELM-FATES parameter sensitivity under pre-fire and postfire scenarios using machine learning

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “Fire Severity-Dependent Shifts in Vegetation Parameter Sensitivity: A Pre- and Post-Fire Analysis Using ELM-FATES and Explainable AI” submitted to Journal of Advances in Modeling Earth Systems (Zahura et al. 2026). The study examines vegetation physiological parameters controlling pre-fire and post-fire vegetation dynamics. To support this analysis, 73 vegetation parameters in Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (Fisher et al., 2018) , which is coupled with E3SM (Energy Exascale Earth System Model) land model (ELM, ELM-FATES), were perturbed using a Sobol sequence to generate 1,024 ensemble members for two plant functional types: needleleaf evergreen extratropical trees (NEET) and C3 grass. Simulations were conducted for the pre-fire period (2016) and post-fire period (2018–2023). Burn severity was represented by modifying the Nesterov index in FATES to 75,000, 150,000, and 300,000 for low, moderate, and high severity, respectively. A no-fire scenario was also included. Simulations were performed for 16 grid cells in the American River Watershed across different burn severities and plant functional types. XGBoost (eXtreme Gradient Boosting) models were trained using the parameter ensembles and ELM-FATES-simulated outputs, including leaf area index (LAI), gross primary productivity (GPP), aboveground biomass, vegetation evaporation, transpiration, and soil evaporation. Models were trained separately for each year and burn severity, followed by SHAP (SHapley Additive exPlanations) analysis to identify changes in dominant parameters after fire disturbance. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. The data package contains the ELM-FATES simulation data. The scripts and data related to the analysis will be added later. The inputs and outputs from ELM-FATES are inside the “FATES” folder. “FATES_domain_surface” contains the domain and surface netcdfs that were used to run ELM-FATES in the study area. “FATES_parameters” contains the 1024 ensembles that were generated using Sobol sequence. “FATES_outputs” folder contains ELM-FATES simulated variables. All files are .csv and .nc (NetCDF).

Aboveground biomass↗
DOE OSTI2020

Phase-shift speckle-shearing interferometry

We have numerically simulated the process of measuring stress – strain states by the method of speckle-shearing interferometry using the phase-shift technique. A computer model with the possibility of setting its strain and roughness is developed, which includes a model of a diffusely reflecting test object corresponding to the characteristics of a real membrane, as well as a speckle interferometer model that allows speckle interferograms to be obtained for different speckle sizes and angles between interfering beams. The process of reconstructing the object surface topogram from model speckle interferograms by the phase-shift technique is implemented. Using the developed models, a two-dimensional shearogram are obtained, which is a derivative of the strain field of a circular membrane. Comparison of the results of numerical simulation with experimental data shows that the differences (rms deviations) do not exceed 0.02 μm. It is also shown that the error of interferogram reconstruction by the phase-shift technique increases significantly when the test object strains exceed 12 μm. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

$Z$-Pinch Interferometry Analysis With the Fourier-Based TNT Code

Here, we present the analysis of interferometry diagnostics with the user-friendly Talbot Numerical Tool (TNT), a Fourier-based postprocessing code that enables real-time assessment of plasma systems. TNT performance was explored with visible and infrared interferometry in pulsed-power-driven Z -pinch configurations to expand its capabilities beyond Talbot X-ray interferometry in the high-intensity laser environment. TNT enabled accurate electron density characterization of magnetically driven plasma flows and shocks through phase-retrieval methods that did not require data modification or masking. TNT demonstrated enhanced resolution, detecting below 4 % fringe shift, which corresponds to 8.7 × 10 15 cm –2 within 28 μ m, approaching the laser probing system limit. TNT was tested against a well-known interferometry analysis software, delivering an average resolving power nearly ten times better (~28 μ m versus ~ 210 μ m) when resolving plasma ablation features. TNT demonstrated higher sensitivity when probing sharp electron density gradients in supersonic shocks. A maximum electron areal density of 4.1 × 10 17 cm –2 was measured in the shocked plasma region, and a minimum electron density detection of ~ 1.0 × 10 15 cm –2 was achieved. When probing colliding plasma flows, the calculations of the effective adiabatic index and the associated errors were improved from γ* = 2.6 ± 1.6 – 1.4 ± 0.2 with TNT postprocessing, contributing valuable data for the interpretation of radiative transport. Additional applications of TNT in the characterization of pulsed-power plasmas and beyond are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Deciphering the Solvation Structure of Aqueous ZnCl 2 Solutions from X-ray Absorption Spectra Using the Interpretable Graph Neural Network

Machine learning (ML) provides powerful pathways for predicting spectroscopic observables from atomic structures, but its broader impact depends on making model predictions interpretable in terms of physical and chemical principles. Here, we introduce a physics-guided graph neural network (GNN) model that predicts Zn K-edge X-ray spectroscopy (XAS) spectra of aqueous ZnCl 2 solutions. Training data are generated from ab initio XAS calculations on molecular dynamics snapshots obtained using a machine learning interatomic potential. The GNN reproduces experimental spectra across concentrations from dilute (<0.1 m) to highly concentrated (30 m, “water-in-salt”) regimes and scales efficiently to large, disordered liquid systems beyond the reach of conventional ab initio approaches. Gradient-based attribution analysis reveals that the model learns physically meaningful structure-spectrum relationships. Ligand-specific attributions reflect orbital hybridization patterns and the origin of the excitations derived from the density functional theory. Bond-length attributions recover spectral shifts consistent with multiple-scattering theory. Finally, this work bridges data-driven prediction with electronic-structure theory, establishing a general paradigm for interpretable ML that links atomic structure, electronic structure, and spectroscopic observables.

25 ENERGY STORAGE↗
DOE OSTI2022

Deep transfer operator learning for partial differential equations under conditional shift

Transfer learning enables the transfer of knowledge gained while learning to perform one task (source) to a related but different task (target), hence addressing the expense of data acquisition and labelling, potential computational power limitations and dataset distribution mismatches. Here, we propose a new transfer learning framework for task-specific learning (functional regression in partial differential equations) under conditional shift based on the deep operator network (DeepONet). Task-specific operator learning is accomplished by fine-tuning task-specific layers of the target DeepONet using a hybrid loss function that allows for the matching of individual target samples while also preserving the global properties of the conditional distribution of the target data. Inspired by conditional embedding operator theory, we minimize the statistical distance between labelled target data and the surrogate prediction on unlabelled target data by embedding conditional distributions onto a reproducing kernel Hilbert space. We demonstrate the advantages of our approach for various transfer learning scenarios involving nonlinear partial differential equations under diverse conditions due to shifts in the geometric domain and model dynamics. Our transfer learning framework enables fast and efficient learning of heterogeneous tasks despite considerable differences between the source and target domains.

42 ENGINEERING↗
DOE OSTI2024

Human–mouse comparison of the multistage nature of radiation carcinogenesis in a mathematical model

Abstract Mouse models are vital for assessing risk from environmental carcinogens, including ionizing radiation, yet the interspecies difference in the dose response precludes direct application of experimental evidence to humans. Herein, we take a mathematical approach to delineate the mechanism underlying the human–mouse difference in radiation‐related cancer risk. We used a multistage carcinogenesis model assuming a mutational action of radiation to analyze previous data on cancer mortality in the Japanese atomic bomb survivors and in lifespan mouse experiments. Theoretically, the model predicted that exposure will chronologically shift the age‐related increase in cancer risk forward by a period corresponding to the time in which the spontaneous mutational process generates the same mutational burden as that the exposure generates. This model appropriately fitted both human and mouse data and suggested a linear dose response for the time shift. The effect per dose decreased with increasing age at exposure similarly between humans and mice on a per‐lifespan basis (0.72‐ and 0.71‐fold, respectively, for every tenth lifetime). The time shift per dose was larger by two orders of magnitude in humans (7.8 and 0.046 years per Gy for humans and mice, respectively, when exposed at ~35% of their lifetime). The difference was mostly explained by the two orders of magnitude difference in spontaneous somatic mutation rates between the species plus the species‐independent radiation‐induced mutation rate. Thus, the findings delineate the mechanism underlying the interspecies difference in radiation‐associated cancer mortality and may lead to the use of experimental evidence for risk prediction in humans.

Oncology↗
DOE OSTI2020

X-ray scattering signatures of early-time accelerations in iodine dissociation

Ultrafast time-resolved x-ray scattering (TRXS) from a photoexcited molecular ensemble measures a distribution $S(Q, τ)$ of the x-ray momentum transfer Q and pump-probe delay τ in which all modes of motion induced by the excitation overlap. Frequency-resolved x-ray scattering (FRXS) based on $\tilde {S}\left(Q,\omega \right)$ separates each oscillation and dissociation channel in the TRXS data, enabling measurements of vibrational frequencies and phases, and dissociation velocities and time shifts. In this work, we extend FRXS analysis to study early-time accelerations as well. We show how these appear as diffuse scattering patterns with characteristic phase evolution in FXRS and we develop a set of transformations that isolate individual channels to measure the early-time accelerated motion. This procedure is used to analyze diatomic iodine x-ray scattering data with multiple dissociations, and the ability of this technique to characterize early-time accelerations of one dissociation channel even in the presence of another dissociation is demonstrated.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1981

Adjacent channel interference degradation with minimum shift keyed modulation

Computer simulation results for degradation in signal-to-noise ratio for various values of bit error probability are given for minimum shift-keyed-type signaling in the presence of adjacent channel interference. A serial modulator structure which utilizes spectral shaping is characterized in terms of envelope deviation and bandwidth efficiency. This serial generation technique is convenient for implementation at high data rates and results in signal spectra with lower sidelobe levels than conventional minimum shift-keyed modulation at the expense of moderate envelope deviation. Because of the lower sidelobe levels, the resulting spectra allow denser channel packing than does ideal MSK.

Ziemer, R. E.↗
NASA NTRS2004

Vibration-Based Data Used to Detect Cracks in Rotating Disks

Rotor health monitoring and online damage detection are increasingly gaining the interest of aircraft engine manufacturers. This is primarily due to the fact that there is a necessity for improved safety during operation as well as a need for lower maintenance costs. Applied techniques for the damage detection and health monitoring of rotors are essential for engine safety, reliability, and life prediction. Recently, the United States set the ambitious goal of reducing the fatal accident rate for commercial aviation by 80 percent within 10 years. In turn, NASA, in collaboration with the Federal Aviation Administration, other Federal agencies, universities, and the airline and aircraft industries, responded by developing the Aviation Safety Program. This program provides research and technology products needed to help the aerospace industry achieve their aviation safety goal. The Nondestructive Evaluation (NDE) Group of the Optical Instrumentation Technology Branch at the NASA Glenn Research Center is currently developing propulsion-system-specific technologies to detect damage prior to catastrophe under the propulsion health management task. Currently, the NDE group is assessing the feasibility of utilizing real-time vibration data to detect cracks in turbine disks. The data are obtained from radial blade-tip clearance and shaft-clearance measurements made using capacitive or eddy-current probes. The concept is based on the fact that disk cracks distort the strain field within the component. This, in turn, causes a small deformation in the disk's geometry as well as a possible change in the system's center of mass. The geometric change and the center of mass shift can be indirectly characterized by monitoring the amplitude and phase of the first harmonic (i.e., the 1 component) of the vibration data. Spin pit experiments and full-scale engine tests have been conducted while monitoring for crack growth with this detection methodology. Even so, published data are extremely limited, and the basic foundation of the methodology has not been fully studied. The NDE group is working on developing this foundation on the basis of theoretical modeling as well as experimental data by using the newly constructed subscale spin system shown in the preceding photograph. This, in turn, involved designing an optimal sub-scale disk that was meant to represent a full-scale turbine disk; conducting finite element analyses of undamaged and damaged disks to define the disk's deformation and the resulting shift in center of mass; and creating a rotordynamic model of the complete disk and shaft assembly to confirm operation beyond the first critical concerning the subscale experimental setup. The finite element analysis data, defining the center of mass shift due to disk damage, are shown. As an example, the change in the center of mass for a disk spinning at 8000 rpm with a 0.963-in. notch was 1.3 x 10(exp -4) in. The actual vibration response of an undamaged disk as well as the theoretical response of a cracked disk is shown. Experiments with cracked disks are continuing, and new approaches for analyzing the captured vibration data are being developed to better detect damage in a rotor. In addition, the subscale spin system is being used to test the durability and sensitivity of new NDE sensors that focus on detecting localized damage. This is designed to supplement the global response of the crack-detection methodology described here.

Gyekenyesi, Andrew L.↗
NASA NTRS2004

OVOC (Oxygenated Volatile Organic Chemicals) in the Global Atmosphere: Atmospheric Budgets, Oceanic Concentrations, and Uncertainties

Airborne measurements of oxygenated volatile organic chemicals (OVOC), OH free radicals, and tracers of pollution were performed over the Pacific during Winter/Spring of 2001. Large concentrations of OVOC are present in the global troposphere and are expected to play an important role in atmospheric chemistry. Their total abundance (SIGMAOVOC) was nearly twice that of non-methane hydrocarbons (SIGMAC2-C8 NMHC). Throughout the troposphere, the OH reactivity of OVOC is comparable to that of methane and far exceeds that of NHMC. A comparison of these data with western Pacific observations collected some seven years earlier (Feb.-March, 1994) did not reveal significant differences. Analysis of the relative enhancement of selected OVOC with respect to CH3Cl and CO in twelve plumes originating from fires and sampled in the free troposphere (3-11 km) is used to assess their primary and secondary emissions from biomass combustion. The composition of these plumes also indicates a large shift of reactive nitrogen into the PAN reservoir thereby limiting ozone formation. These data are combined with other observations and interpreted with the help of a global 3-D model to assess OVOC global sources and sinks. We further interpret atmospheric observations with the help of an air-sea exchange model io show that oceans can be both net so~rces and sinks. An extremely large oceanic reservoir of OVOC, that exceeds the atmospheric reservoir by more than an order of magnitude, can be inferred to be present. We conclude that OVOC sources are extremely large (150-500 TgC y-1) but remain poorly quantified. In many cases, measured concentrations are uncertain and incompatible with our present knowledge of atmospheric chemistry. Results based on observations from several field studies and critical gaps will be discussed.

Singh, Hanwant B.↗
DOE OSTI2020

Investigation of the benefits of diabatic microreactors for process intensification of the water-gas shift reaction within the steam reforming process

Presently, the steam reforming process is the largest industrial source of hydrogen. Improving its efficiency can help to reduce associated carbon emissions and hydrogen production costs. Intensifying the water-gas shift reaction using microreactors with integrated cooling is one way of achieving this. In this study, a 2-D computational model of one of these microreactors is developed, validated with experimental data, and then used to demonstrate how microreactors can enhance the conversion of the water-gas shift reaction beyond what can be achieved using conventional packed bed reactors. These results are then generalized into a full system model of the steam reforming process to demonstrate how microreactors can reduce hydrogen production costs. The results suggest that microreactors can significantly reduce the required reactor volume and catalyst loading for the water-gas shift reaction and can similarly reduce the hydrogen production costs associated with the steam reforming process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Enhancing Data Quality Monitoring at CMS with Interactive Visualization Tools and Automated Reference Run Selection

Current data quality monitoring (DQM) tools at CMS offer granularity limited to per-run analysis. Consequently, issues manifesting at the per-lumisection level can go unnoticed or, even if detectable, often lead to the classification of the whole run as bad, resulting in unnecessary data loss. Additionally, shifters have to evaluate a large set of monitoring elements during their long shifts, increasing the probability of human errors or overlooked problems. In this contribution, we present ongoing work on the development of tools that will provide shifters with an accessible, granularity-enhanced view of DQM data through interactive and dynamic visualizations. Furthermore, we introduce a reference run selection tool currently under development, which will automate the selection based on data-taking conditions and will offer a curated set of training data for machine learning models that will be used for the partial automation of the offline data certification process. These endeavors will be integrated into the DIALS website, enabling enhancements in data certification accuracy and improving the accessibility of DQM at CMS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗