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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Density-functional errors in ionization potential with increasing system size

This work investigates the effects of molecular size on the accuracy of density-functional ionization potentials for a set of 28 hydrocarbons, including series of alkanes, alkenes, and oligoacenes. As the system size increases, delocalization error introduces a systematic underestimation of the ionization potential, which is rationalized by considering the fractional-charge behavior of the electronic energies. The computation of the ionization potential with many density-functional approximations is not size-extensive due to excessive delocalization of the incipient positive charge. While inclusion of exact exchange reduces the observed errors, system-specific tuning of long-range corrected functionals does not generally improve accuracy. These results emphasize that good performance of a functional for small molecules is not necessarily transferable to larger systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2010

THE LINEARITY OF THE COSMIC EXPANSION FIELD FROM 300 TO 30,000 km s{sup -1} AND THE BULK MOTION OF THE LOCAL SUPERCLUSTER WITH RESPECT TO THE COSMIC MICROWAVE BACKGROUND

The meaning of 'linear expansion' is explained. Particularly accurate relative distances are compiled and homogenized for (1) 246 Type Ia supernovae and 35 clusters with v < 30, 000 km s{sup -1}, and (2) relatively nearby galaxies with 176 tip of the red-giant branch and 30 Cepheid distances. The 487 objects define a tight Hubble diagram from 300-30, 000 km s{sup -1} implying individual distance errors of {approx_lt}7.5%. Here the velocities are corrected for Virgocentric steaming (locally 220 km s{sup -1}) and-if v{sub 220} > 3500 km s{sup -1}-for a 495 km s{sup -1} motion of the Local Supercluster toward the warm cosmic microwave background (CMB) pole at l = 275, b = 12; local peculiar motions are averaged out by large numbers. A test for linear expansion shows that the corrected velocities increase with distance as predicted by a standard model with q{sub 0} = -0.55 (corresponding to ({Omega}{sub M}, {Omega}{sub {Lambda}} = (0.3, 0.7)), but the same holds-due to the distance limitation of the present sample-for a range of models with q{sub 0} between {approx}0.00 and -1.00. For these models H{sub 0} does not vary systematically by more than {+-}2.3% over the entire range. Local, distance-dependent variations are equally limited to 2.3% on average. In particular, the proposed Hubble Bubble of Zehavi et al. and Jha et al. is rejected at the 4{sigma} level. Velocity residuals in function of the angle from the CMB pole yield a satisfactory apex velocity of 448 {+-} 73 km s{sup -1} and a coherence radius of the Local Supercluster of {approx}3500 km s{sup -1} ({approx}56 Mpc), beyond which galaxies are seen on average at rest in comoving coordinates with respect to the CMB. Since no obvious single accelerator of the Local Supercluster exists in the direction of the CMB dipole, its motion must be due to the integral gravitational force of all surrounding structures. Most of the gravitational dipole probably come from within 5000 km s{sup -1}.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

The galactic halo in mixed dark matter cosmologies

A possible solution to the small scale problems of the cold dark matter (CDM) scenario is that the dark matter consists of two components, a cold and a warm one. We perform a set of high resolution simulations of the Milky Way halo varying the mass of the WDM particle (m{sub WDM}) and the cosmic dark matter mass fraction in the WDM component ( f-bar {sub W}). The scaling ansatz introduced in combined analysis of LHC and astroparticle searches postulates that the relative contribution of each dark matter component is the same locally as on average in the Universe (e.g. f{sub W,s}un = f-bar {sub W}). Here we find however, that the normalised local WDM fraction (f{sub W,s}un / f-bar {sub W}) depends strongly on m{sub WDM} for m{sub WDM} < 1 keV. Using the scaling ansatz can therefore introduce significant errors into the interpretation of dark matter searches. To correct this issue a simple formula that fits the local dark matter densities of each component is provided.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Quantum computing for heavy quarkonium spectroscopy

Here, we report a first demonstration for the application of quantum computing to heavy quarkonium spectroscopy study. Based on a Cornell-potential model for the heavy quark and antiquark system, we show how this Hamiltonian problem can be formulated and solved with the variational quantum eigensolver (VQE) approach on the IBM cloud quantum computing platform. Errors due to a global depolarizing noise channel are corrected with a zero-noise extrapolation method, resulting in good agreement with the expected value. We also generalize the VQE method for solving excited states by orthogonalization with respect to the ground state. This new approach is demonstrated to be successful for the quarkonium system on a noiseless quantum simulator and can easily be adapted for solving similar excited state problems in many other physical systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

SU-C-16A-01: In Vivo Source Position Verification in High Dose Rate (HDR) Prostate Brachytherapy Using a Flat Panel Imager: Initial Clinical Experience

Purpose: We report our initial clinical experience with a novel position-sensitive source-tracking system based on a flat panel imager. The system has been trialled with 4 prostate HDR brachytherapy patients (8 treatment fractions) in this initial study. Methods: The flat panel imaging system was mounted under a customised carbon fibre couch top assembly (Figure 1). Three gold fiducial markers were implanted into the prostate of each patient at the time of catheter placement. X-ray dwell position markers were inserted into three catheters and a radiograph acquired to locate the implant relative to the imaging device. During treatment, as the HDR source dwells were delivered, images were acquired and processed to determine the position of the source in the patient. Source positions measured by the imaging device were compared to the treatment plan for verification of treatment delivery. Results: Measured dwell positions provided verification of relative dwell spacing within and between catheters, in the coronal plane. Measurements were typically within 2.0mm (0.2mm – 3.3mm, s.d. 0.8mm) of the planned positions over 60 dwells (Figure 2). Discrimination between larger dwell intervals and catheter differentiation were clear. This confirms important delivery attributes such as correct transfer tube connection, source step size, relative catheter positions and therefore overall correct plan selection and delivery. The fiducial markers, visible on the radiograph, provided verification of treatment delivery to the correct anatomical location. The absolute position of the dwells was determined by comparing the measured dwell positions with the x-ray markers from the radiograph, validating the programmed treatment indexer length. The total impact on procedure time was less than 5 minutes. Conclusion: The novel, noninvasive HDR brachytherapy treatment verification system was used clinically with minor impact on workflow. The system allows verification of correct treatment delivery, free of most potential human related errors identified in ICRP 97. This research is supported by funding from the Australian Government Department of Health through Cancer Australia grant no. 616614.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Fast Multigrid Reduction-in-Time for Advection via Modified Semi-Lagrangian Coarse-Grid Operators

Many iterative parallel-in-time algorithms have been shown to be highly efficient for diffusion-dominated partial differential equations (PDEs) but are inefficient or even divergent when applied to advection-dominated PDEs. We consider the application of the multigrid reduction-in-time (MGRIT) algorithm to linear advection PDEs. Here, the key to efficient time integration with this method is using a coarse-grid operator that provides a sufficiently accurate approximation to the so-called ideal coarse-grid operator. For certain classes of semi-Lagrangian discretizations, we present a novel semi-Lagrangian-based coarse-grid operator that leads to fast and scalable multilevel time integration of linear advection PDEs. The coarse-grid operator is composed of a semi-Lagrangian discretization followed by a correction term, with the correction designed so that the leading-order truncation error of the composite operator is approximately equal to that of the ideal coarse-grid operator. Parallel results show substantial speed-ups over sequential time integration for variable-wave-speed advection problems in one and two spatial dimensions, and using high-order discretizations up to order five. The proposed approach establishes the first practical method that provides small and scalable MGRIT iteration counts for advection problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Finite-element analysis of the deformation of thin Mylar films due to measurement forces

Significant deformation of thin films occurs when measuring thickness by mechanical means. This source of measurement error can lead to underestimating film thickness if proper corrections are not made. Analytical solutions exist for Hertzian contact deformation, but these solutions assume relatively large geometries. If the film being measured is thin, the analytical Hertzian assumptions are not appropriate. ANSYS is used to model the contact deformation of a 48 gauge Mylar film under bearing load, supported by a stiffer material. Simulation results are presented and compared to other correction estimates. Ideal, semi-infinite, and constrained properties of the film and the measurement tools are considered.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Criticality Control Overpack Fire Testing (Phase III)

This report will describe the one test conducted during phase III of the Pipe Overpack Container (POC) test campaign, present preliminary results from these tests, and discuss implications for the Criticality Control Overpack (CCO). The goal of this test was to see if aerosol surrogate material inside the Criticality Control Container (CCC) gets released when the drum lid of the CCO comes off during a thirty-minute long, fully-engulfing, fire test. As expected from POC tests conducted in Phase I and II of this test campaign, the CCO drum lid is ejected about one minute after the drum is exposed to fully-engulfing flames. The remaining pressure inside the drum is high enough to eject the top plywood dunnage a considerable distance from the drum. Subsequently, most of the bottom plywood dunnage supporting the CCC burns off during and after the fire. High pressure buildup inside the CCC and inside two primary containers holding the surrogate powder also results in damage to the filter media of the CCC and the filter-house, thread attachment of the primary canisters. No discernable release of surrogate powder material was detected from the two primary containers when pre- and post-test average mass were compared. However, when the average masses are corrected to account for possible uncertainties in mass measurements, error overlap does not preclude the possibility that some surrogate powder mass may have been lost from these primary canisters. Still, post-test conditions of the secondary canisters enclosing these two primary canisters suggest it is very unlikely this mass loss would have escaped into the CCC.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Hadronic vacuum polarization to muon g-2 using twisted-mass fermions

In an era dominated by the LHC, precision experiments will nonetheless play an essential and complementary role in constraining or discovering physics beyond the standard model. The anomalous magnetic moment of the muon is a prominent example of such, especially tantalizing because the disagreement between its measurement and the standard model prediction is currently larger than three standard deviations. At some level of precision, all quantities, even those commonly referred to as electroweak properties, become sensitive to QCD. Again the anomalous magnetic moment of the muon is an example of such, with theory errors due almost exclusively to those of the hadronic corrections. In this talk, I will discuss our efforts to calculate nonperturbatively the leading QCD corrections to all electroweak observables using lattice QCD.

Renner, Dru↗
DOE OSTI2023

Improving Fission Products at CARIBU: Near Field Detection (Q4/FY23 Quarterly Progress Report)

We have addressed another round of referees’ comments and resubmitted our mass measurement of the isomer and ground state of 128 Sb to Phys. Rev. Letters. One of the referees recommended publication so we anticipate this will be the last round with the referees. This paper focuses on the astrophysical implications of our measurement, as we can directly measure the excitation energy of the isomer along with other observables like the isomer to ground state ratio produced in the fission of 252 Cf. With our summer student Asha, we were able to determine that there was an error in our Gas Counter simulations, which has been corrected and is now implemented in our 111 Ag simulations. This report describes the progress on this effort from July until August 2023. We have paused the work on this project in the last 7 Weeks while the PI was on leave. We are resuming the work on this effort in early October.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Hybrid learning techniques for scientific data reduction with performance guarantees

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Final report- UFL - RAPIDS2: A SciDAC Institute for Computer Science, Data, and Artificial Intelligence

The research initiatives supported by the U.S. Department of Energy (DOE) Grant DE-SC0022265 are fundamentally aimed at pioneering advanced machine learning (ML) techniques for scientific data compression within high-performance computing (HPC) environments. This comprehensive body of work addresses the critical challenge posed by the exponential growth of data generated by scientific simulations in domains such as fusion energy, climate modeling, and computational fluid dynamics (CFD). A core objective is to develop compression algorithms that achieve substantial data reduction—often by orders of magnitude—while rigorously ensuring the fidelity of both the primary data (PD) and scientifically crucial derived quantities of interest (QoI). The methodologies deployed under this grant integrate sophisticated deep learning architectures, prominently featuring autoencoders, advanced generative models like conditional diffusion, and hybrid learning techniques. Key innovations include the development of Guaranteed Autoencoders (GAE) and the Guaranteed Conditional Diffusion with Tensor Correction (GCDTC) framework, which provide explicit, instance-level error bounds on reconstructed data. Furthermore, specialized strategies such as nonlinear constraint satisfaction are employed to preserve the integrity of QoI, a vital requirement for the trustworthiness of downstream scientific analyses. This research also focuses on the design and implementation of scalable, GPU-accelerated software pipelines that seamlessly integrate into existing HPC workflows, ensuring both computational efficiency and practical applicability. The CAESAR framework, for example, unifies foundation and generative models to create an adaptive and efficient compression solution for spatio-temporal scientific data. Collectively, these efforts represent a significant advancement in mitigating the scientific data deluge, enabling more effective data management, accelerated scientific discovery, and optimized utilization of HPC resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Second ARM Aerosol Chemical Speciation Monitor Users’ Meeting Report

The aerosol chemical speciation monitor (ACSM) was developed to adapt the technology of the aerosol mass spectrometer (AMS) to routine, long-term, standalone monitoring. The calculation of particulate mass concentration from ACSM data requires the measurement of the response of the instrument to aerosol of specific size and composition as well as assumptions about the instrument response based on laboratory measurements and field experience acquired over more than two decades of operation of AMS and a decade of operation of the ACSM. Three parameters in the concentration calculations that are particularly important are the NO3 response factor (RFNO3), relative ionization efficiency (RIE), and the collection efficiency (CE). The values of RFNO3 and RIEs are determined from calibration, however the jump calibration method previously used in calibration can result in errors in the RIE for sulfate. This has been corrected by implementing a continuous calibration method. The default collection efficiency is 0.5. This has been shown to result in mass loadings that do not agree with mass determinations from other instruments because of effects of composition on the vaporization of the particles. The previous work of investigators addressing this issue is discussed. After preliminary work on ACSM and scanning mobility particle sizer (SMPS) data from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) observatory collected in late 2016 and 2017 produced a parameterization of composition dependent collection efficiency very different from the results of previous studies, SMPS data were examined and we determined that there was significant mass that the instrument did not capture because the particles with diameters larger than 465 nm are not counted by this instrument. Data for the ultra-high-sensitivity aerosol spectrometer (UHSAS), SMPS, and ACSM are available for nearly all of 2019. The data from UHSAS and SMPS collected in 2019 were compared. We found that the UHSAS data has particle counts and total volumes significantly less than measured by the condensation particle counter (CPC) and SMPS. The SMPS data were extended by fitting the average volume distribution with a log normal curve and using this relationship to estimate a mass value for the SMPS over extended diameter range. The extended SMPS mass values result in a CDCE parameterization that is in better agreement with the results of other investigators, but is still different from other formulations. The working group recommends that the ACSM data be processed with a collective efficiency (CE)=1, that this be documented clearly in the metadata, and the use of the default CE of 0.5 or a formulation of composition-dependent collection efficiencies (CDCE) chosen by the user should be implemented based on the ammonium nitrate mass fraction. This is clearly necessary for the wintertime SGP ACSM data because of the high nitrate concentrations.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Satellite Embedding-Based Population Imputation for Areas with Missing Building Footprint Data: A Computer Vision-Based Approach

High-resolution population modeling is important for supporting effective decision-making across diverse sectors. LandScan Mosaic generates population estimates at the level of individual buildings and aggregates them to 3 arc-second grids, and this approach performs well in regions where building footprint data are comprehensive and reliable. However, large portions of the globe still suffer from incomplete, sparse, or entirely missing building stock datasets, creating a structural limitation for strictly building-based population models. To address this research gap, this study proposes a computer vision-based framework that employs Google Earth Engine satellite embeddings and UNet, which allows us to directly impute grid-level population estimates in building-data-deficient areas. Applied to Taiwan as a case study, the framework achieved strong predictive performance with R$^{2}$ of 0.89, RMSE of 18.70, and MAE of 8.41, outperforming traditional machine learning approaches. Notably, the proposed framework effectively addressed building false-positive errors inherent in Global Human Settlement Layer (GHSL) data, correctly identifying uninhabited areas that were erroneously classified as populated. The framework also offers significant advantages for global population mapping, particularly in terms of scalability and temporal consistency, thereby extending the coverage and accuracy of high-resolution population products in data-scarce regions worldwide. Urban planners, decision makers, and related stakeholders can obtain granular population distributions to support more accurate and targeted infrastructure investment, service delivery, resource allocation, and risk assessment decisions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2010

Report on Modifications to the BX12 and BX13 BC1 Dipoles

Emittance growth seen during the last commissioning run in the bunch compressor optics section, BC1, was blamed on inadequate dipole field quality. The significant linear and nonlinear field non-uniformities generated large horizontal dispersion errors beyond BC1. The linear dispersion after BC1 was corrected using two small 'corrector' quadrupoles placed in BC1 for this purpose, but the remaining nonlinear field caused growth of the normalized horizontal emittance of 40% or more. At best {gamma}{epsilon}{sub x} went from 1.2 {micro}m before BC1 up to 1.7 {micro}m after BC1. The problem was magnified by the larger-than-design energy spread in BC1 due to a long initial bunch length. To improve the field quality we decided to modify the two 'inner dipoles', BX12 and BX13, of the four magnet chicane during the four month down time in the Fall of 2007. Only the two inner dipoles were chosen because of the limited time available and the fact that the beam is particularly sensitive to field quality of the inner dipoles due to its very large transverse size when going through them. The modifications were completed in November and included new poles and a new pinning scheme. The outer dipoles were left unchanged.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Developing A Custom-Built Metal Aerosol Processing Chamber: Analysis of Aerosol Coagulation at Low Humidities

We have developed an intermediate size (906 L) aerosol processing chamber, and this work reports on the design and initial characterization of dry aerosol experiments. Specifically, we are determining wall-loss and coagulation correction factors using the observed size distribution measurements for surrogates of common aerosol classes: sodium chloride, sucrose, and biomass burning aerosol smoke. Results show that, on average, sodium chloride, sucrose, and smoke wall-loss rates converge to similar values on relatively short time scales (< 1 h). The fitted coagulation correction factor, W C -1 , for smoke particles (1.23 ± 0.312), indicates that on average they adhere to each other more than sodium chloride (0.969 ± 0.524) and sucrose (1.16 ± 1.38). The relative uncertainty is high for the coagulation correction, but it is consistent with our Monte Carlo error analysis. This study lays the foundation for future experiments at elevated humidity and supersaturation conditions to characterize the influence of particle shape on coagulation and cloud parameters.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data and code from: Multivariate bayesian regression model for predicting disposed ash composition at U.S. coal fired power stations

This dataset contains the code and data files needed for implementation of a Multivariate Bayesian Regression model, described in Jin et al. (2025), for the historical prediction of the chemical composition of disposed coal ash at U.S. coal fired power plants as a function of annualized coal purchase data. The integrated coal supply data file (CoalSupplyDataset.csv) represents a compilation of monthly fuel purchase records for the period 1973-2022 at major U.S. power stations. These records were obtained from the U.S. Energy Information Administration. The CSV file also contains, for each coal purchase record, the coal region of the mine as defined by the U.S. Geological Survey. Data entry errors and data gaps in the EIA records were corrected as described in Jin et al. This CSV file represents the integrated coal supply data after corrections were made. The model structure and fitting parameters are encoded in pickle file format (Bayesian.pkl). The model was developed with the coal supply data and coal ash composition data, apportioned according to the Stratified Shuffle Split for training and testing subsets. The model was built using Python and the PyMC library. Reference Publication: Jin, Z.; Huang, J.; Hower, J.C.; Hsu-Kim, H.(2025). Predictive Assessment of the Chemical Composition of Coal Ash in Reserve at U.S. Disposal Sites. Environmental Science & Technology.

Coal ash composition↗
DOE OSTI2010

Optimal Countrates for Deadtime Corrections

The high x-ray flux available at synchrotron radiation sources can cause nonlinearities in photon-counting detectors unless deadtime corrections are employed. We compute the uncertainties associated with several common deadtime-correction formulas. At lower countrates, statistical noise dominates the error in the measured countrates; at higher countrates, the dominating factors are saturation of the response and uncertainty in the value of the deadtime parameter. In between, a range of countrates exists in which the signal-to-noise ratio can be optimized for photon-counting experiments.

43 PARTICLE ACCELERATORS↗