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DOE OSTI2026

Multi-modal dynamic radiography using short-pulse laser-generated probe beams

Radiography is an important tool for the interrogation of dynamic experiments in the fields of dynamic properties of materials, and in condensed matter, high explosive, and high-energy-density physics. Multi-modal radiography advances the hypothesis that combining the information delivered by multiple radiographic modalities can lead to more constrained (improved) “reconstruction” of the scene than can be obtained from a single probe. We identify four modalities: multi-probe, time sequence, multi-view, and multi-messenger. Multi-probe radiography is a promising candidate for a next-generation dynamic radiographic facility. High-energy X-rays are the most frequently used probe for dynamic radiography, although recent developments show the utility of proton (pRad), electron (eRad), and neutron probe beams. Because each probing species interacts with material in the radiographic scene through quantitatively different mechanisms, each returns independent information about the scene, which can add extra constraints to the reconstruction process. How to conduct detailed, quantitative “co-analysis” of multiple data streams remains an area of active research. Multi-beam, short-pulse, laser-generated probes offer sufficient dose, an appropriate spectrum, and appropriate spatio-temporal resolution to produce high-quality dynamic radiographs. This paper reports on technology development to advance the state of the art of multi-modal/multi-probe radiography and the pursuit of both deterministic and inferential (AI/ML assisted) co-analysis methodologies to produce more constrained reconstructions from multi-modal data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1991

GaAs solar cell photoresponse modeling using PC-1D V2.1

Photoresponse data of high efficiency GaAs solar cells were analyzed using PC-1D V2.1. The approach required to use PC-1D for photoresponse data analysis, and the physical insights gained from performing the analysis are discussed. In particular, the effect of Al(x)Ga(1-x)As heteroface quality was modeled. Photoresponse or spectral quantum efficiency is an important tool in characterizing material quality and predicting cell performance. The strength of the photoresponse measurement lies in the ability to precisely fit the experimental data with a physical model. PC-1D provides a flexible platform for calculations based on these physical models.

Huber, D. A.↗

NASA NTRS1982

Analysis of geologic terrain models for determination of optimum SAR sensor configuration and optimum information extraction for exploration of global non-renewable resources. Pilot study: Arkansas Remote Sensing Laboratory, part 1, part 2, and part 3

Computer-generated radar simulations and mathematical geologic terrain models were used to establish the optimum radar sensor operating parameters for geologic research. An initial set of mathematical geologic terrain models was created for three basic landforms and families of simulated radar images were prepared from these models for numerous interacting sensor, platform, and terrain variables. The tradeoffs between the various sensor parameters and the quantity and quality of the extractable geologic data were investigated as well as the development of automated techniques of digital SAR image analysis. Initial work on a texture analysis of SEASAT SAR imagery is reported. Computer-generated radar simulations are shown for combinations of two geologic models and three SAR angles of incidence.

Kaupp, V. H.↗

NASA NTRS2018

Long-Term Ozone Variability and Trends from Reanalyses

Stratospheric ozone has a profound impact on radiation and chemistry over various spatial and temporal scales. The evolution of stratospheric ozone over the 21st century, however, is not well understood, especially in the lower stratosphere. Highly vertically resolved ozone data from satellite-borne limb sounders have proved to be invaluable for studying ozone in the middle and upper stratosphere but it was not until recently that these measurements were successfully incorporated in atmospheric reanalyses. Validation and comparison studies have demonstrated that the addition of observations from the Microwave Limb Sounder (MLS) on EOS (Earth Observing System) Aura greatly improved the quality of ozone fields in MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) making these assimilated data sets more useful for scientific research. In this presentation we demonstrate that multidecadal lower-stratospheric ozone variability and trends can be derived from NASA's MERRA-2 reanalysis ozone. In particular, the reanalysis ozone bias-corrected using a chemistry model simulation as a transfer function agrees very well with recently reprocessed long ozonesonde records. Ozone trends in the lower stratosphere will be discussed in the context of recent findings (Ball et al., 2018) and interpreted in connection with long-term circulation changes in the lower stratosphere. Next, we show that the use of ozone data retrieved from the next generation OMPS (Ozone Mapping Profiler Suite) instruments, including the OMPS Limb Profiler, can successfully extend the reanalyses into the future allowing comprehensive monitoring of global ozone and interpretation of its evolution during the critical period of expected ozone recovery and climate change from increasing concentration of greenhouse gases.

ozone↗

DOE OSTI2025

The ICARUS light detection system (Fermilab Italian summer student program 2023)

The ICARUS T600 detector is the largest Liquid Argon Time Projection Chamber ever used on a neutrino beam, and it acts as the far detector of the Short Baseline Neutrino program at Fermilab. Its purpose is the study of the possibility of the existence of a fourth sterile neutrino in the O(eV2) mass range that could take part in the neutrino oscillations. The light detection system of the ICARUS detector plays the role of localising in space and time the neutrino interactions taking place inside the detector, collecting the argon scintillation photons generated when an event occurs. This light detection system also has a crucial role in the trigger system and the rejection of the huge amount of background cosmic events, working together with the trigger request signals sent by the beam complex. In August 2023 part of the cables that are used to carry the signals from the photomultipliers to the electronics were replaced with a new model, because a deterioration of the quality of the signal inside the cables had previously been observed. An analysis of the performance of the new cables was carried out, comparing laser run data collected before and after the change of the cable model, and it was proved that the introduction of the new cables lead to a general improvement of the quality of the signals reaching the electronics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

European residential wood pellet trade and prices dataset

The European market for wood pellets used in small-scale heating systems has been expanding significantly over the past decade. For an analysis of market efficiency in the Journal Energy with the title “The European wood pellets for heating market - price developments, trade and market efficiency“ wood pellet prices have been collected as well as trade flows downloaded for the trade relations between Austria, Germany, Italy and France. Only since January 2012 monthly wood pellet trade data is published by Eurostat. This, now monthly expanding data-set provides new opportunities for analysing the development of this important renewable energy commodity. Furthermore, national wood pellet prices published by national authorities and interest groups are improving in quality in the recent years. The collection and combination of these data-sets are a chance for novel econometric analysis. This paper presents valuable tools and processes to acquire and prepare this data and connects to a data and code repository for downloading the resources described in this and the related Journal Energy publication.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2010

Impact of Asian Dust on Climate and Air Quality

Dust generated from Asian permanent desert and desertification areas can be efficiently transported around the globe, making significant radiative impact through their absorbing and scattering solar radiation and through their deposition on snow and ice to modify the surface albedo. Asian dust is also a major concern of surface air quality not only in the source and immediate downwind regions but also areas thousands of miles away across the Pacific. We present here a global model, GOCART, analysis of data from satellite remote sensing instrument (MODIS, MISR, CALIPSO, OMI) and other observations on Asian dust sources, transport, and deposition, and use the model to assess the Asian dust impact on global climate and air quality.

Chin, Mian↗

DOE OSTI2020

Square Kilometre Array Science Data Challenge 1: analysis and results

ABSTRACT As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality data sets for testing and evaluating new techniques. In this paper, we present a description and results from the first such Science Data Challenge 1 (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560, 1400, and 9200 MHz) at three depths (8, 100, and 1000 h), SDC1 asked participants to apply source detection, characterization, and classification methods to simulated data. The challenge opened in 2018 November, with nine teams submitting results by the deadline of 2019 April. In this work, we analyse the results for eight of those teams, showcasing the variety of approaches that can be successfully used to find, characterize, and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.

Bonaldi, A.↗

NASA NTRS2001

Linking Science Analysis with Observation Planning: A Full Circle Data Lifecycle

A clear goal of the Virtual Observatory (VO) is to enable new science through analysis of integrated astronomical archives. An additional and powerful possibility of the VO is to link and integrate these new analyses with planning of new observations. By providing tools that can be used for observation planning in the VO, the VO will allow the data lifecycle to come full circle: from theory to observations to data and back around to new theories and new observations. The Scientist's Expert Assistant (SEA) Simulation Facility (SSF) is working to combine the ability to access existing archives with the ability to model and visualize new observations. Integrating the two will allow astronomers to better use the integrated archives of the VO to plan and predict the success of potential new observations. The full circle lifecycle enabled by SEA can allow astronomers to make substantial leaps in the quality of data and science returns on new observations. Our paper will examine the exciting potential of integrating archival analysis with new observation planning, such as performing data calibration analysis on archival images and using that analysis to predict the success of new observations, or performing dynamic signal-to-noise analysis combining historical results with modeling of new instruments or targets. We will also describe how the development of the SSF is progressing and what has been its successes and challenges.

Jones, Jeremy↗

DOE OSTI2022

Recent advances and applications of deep learning methods in materials science

Deep learning (DL) is one of the fastest-growing topics in materials data science, with rapidly emerging applications spanning atomistic, image-based, spectral, and textual data modalities. DL allows analysis of unstructured data and automated identification of features. The recent development of large materials databases has fueled the application of DL methods in atomistic prediction in particular. In contrast, advances in image and spectral data have largely leveraged synthetic data enabled by high-quality forward models as well as by generative unsupervised DL methods. In this article, we present a high-level overview of deep learning methods followed by a detailed discussion of recent developments of deep learning in atomistic simulation, materials imaging, spectral analysis, and natural language processing. For each modality we discuss applications involving both theoretical and experimental data, typical modeling approaches with their strengths and limitations, and relevant publicly available software and datasets. We conclude the review with a discussion of recent cross-cutting work related to uncertainty quantification in this field and a brief perspective on limitations, challenges, and potential growth areas for DL methods in materials science.

36 MATERIALS SCIENCE↗

NASA NTRS2000

A Decision Support Information System for Urban Landscape Management Using Thermal Infrared Data

In this paper, we describe efforts to use remote sensing data within the purview of an information support system, to assess urban thermal landscape characteristics as a means for developing more robust models of the Urban Heat Island (UHI) effect. We also present a rationale on how we have successfully translated the results from the study of urban thermal heating and cooling regimes as identified from remote sensing data, to decision-makers, planners, government officials, and the public at large in several US cities to facilitate better understanding of how the UHI affects air quality. Additionally, through the assessment of the spatial distribution of urban thermal landscape characteristics using remote sensing data, it is possible to develop strategies to mitigate the UHI that hopefully will in turn, drive down ozone levels and improve overall urban air quality. Four US cities have been the foci for intensive analysis as part of our studies: Atlanta, GA, Baton Rouge, LA, Salt Lake City, UT, and Sacramento, CA. The remote sensing data for each of these cities has been used to generate a number of products for use by "stakeholder" working groups to convey information on what the effects are of the UHI and what measures can be taken to mitigate it. In turn, these data products are used to both educate and inform policy-makers, planners, and the general public about what kinds of UHI mitigation strategies are available.

Quattrochi, Dale A.↗

DOE OSTI2025

Wide‐Field Bond Quality Evaluation Using Frequency Domain Thermoreflectance with Deep Neural Network Feature Reconstruction

Heterogeneous integration of microelectronic components provides a pathway to improve circuit/component performance; however, this comes with assembly challenges, in particular due to complex interfaces via subsurface bump bonds. The ability of these bonds to transmit electrical signals and conduct heat to the carrier substrate limits component performance. In this work, hyperspectral frequency‐domain thermoreflectance (FDTR) imaging is demonstrated as a robust technique for evaluating the quality of subsurface indium bump bonds in a surrogate microelectronic sample. By performing microscale FDTR imaging with coarse motion image stitching, thermal phase maps that cover a 4 mm by 4 mm field‐of‐view with subsurface feature sensitivity at depths greater than 50 µm are obtained. The resulting FDTR hyperspectral data contains more than three million pixels and reveal the quality of subsurface microbump arrays. Wide‐field analysis of bonded versus gap regions is enabled by deep neural network feature reconstruction, that after training, rapidly provides an interpretable representation of bond quality. Utility of noisy higher frequency FDTR phase maps, i.e., near the computationally predicted sensing depth limit, results in an average prediction error of 11%. Taken together, FDTR with neural network‐based analysis demonstrates subsurface bond monitoring at length scales relevant for heterogeneously integrated microelectronics.

FDTR↗

DOE OSTI2026

A Comprehensive Comparison of Building Height Products at a Global Level

The built environment continues to expand due to increasing human populations with some projections indicating additional growth of 2.5 billion persons by 2050. Buildings are a key component of the built environment and information on building height and urban morphology in general can help to better understand and address a host of development and urban planning issues including energy consumption, urbanization, population dynamics, urban heat islands, environmental degradation, and others. To date, several approaches have been developed to address the need for mapping building height at scale. These approaches can be grouped into two main categories: 1) directly measure height from remote sensing products or 2) indirectly estimate height from footprint morphology features at the building-by-building level. Due to a number of these global height datasets now being available for consumption and use across domains, there is a critical need to understand the differences displayed between these products and how the use of these may influence the outcome when applied. In this analysis, we compare and evaluate 5 global building height datasets: Global Human Settlement, World Settlement Footprint 3D, Global Building Morphology dataset, three-dimensional Global Building Footprints, and an approach developed at Oak Ridge National Laboratory (ORNL). Our analysis shows that, across 5 cities at a global scale with high-quality building height reference data, the approach developed by ORNL of inferring height at the building-by-building level is more accurate and consistent. This was evidenced by the ORNL product improving upon the baseline in all 5 cities, the only product to do so. These findings will aid researchers in choosing a global building height product that best meets their needs and provides global availability, consistency, and accuracy.

42 ENGINEERING↗

NASA NTRS1995

Turbulence measurements in hypersonic boundary layers using constant-temperature anemometry and Reynolds stress measurements in hypersonic boundary layers

The primary objective in the two research investigations performed under NASA Langley sponsorship (Turbulence measurements in hypersonic boundary layers using constant temperature anemometry and Reynolds stress measurements in hypersonic boundary layers) has been to increase the understanding of the physics of hypersonic turbulent boundary layers. The study began with an extension of constant-temperature thermal anemometry techniques to a Mach 11 helium flow, including careful examinations of hot-wire construction techniques, system response, and system calibration. This was followed by the application of these techniques to the exploration of a Mach 11 helium turbulent boundary layer (To approximately 290 K). The data that was acquired over the course of more than two years consists of instantaneous streamwise mass flux measurements at a frequency response of about 500 kHz. The data are of exceptional quality in both the time and frequency domain and possess a high degree of repeatability. The data analysis that has been performed to date has added significantly to the body of knowledge on hypersonic turbulence, and the data reduction is continuing. An attempt was then made to extend these thermal anemometry techniques to higher enthalpy flows, starting with a Mach 6 air flow with a stagnation temperature just above that needed to prevent liquefaction (To approximately 475 F). Conventional hot-wire anemometry proved to be inadequate for the selected high-temperature, high dynamic pressure flow, with frequent wire breakage and poor system frequency response. The use of hot-film anemometry has since been investigated for these higher-enthalpy, severe environment flows. The difficulty with using hot-film probes for dynamic (turbulence) measurements is associated with construction limitations and conduction of heat into the film substrate. Work continues under a NASA GSRP grant on the development of a hot film probe that overcomes these shortcomings for hypersonic flows. Each of the research tasks performed during the NASA Langley research grants is discussed separately below.

Spina, Eric F.↗

NASA NTRS1998

The Effect of Solution Parameters on Lysozyme Nucleation Rates and Crystal Quality

In the pursuit of strongly diffracting high quality macromolecule crystals of suitable volume, this study investigates how the formation of macromolecules in solution and their growth characteristics effect crystal volume and diffracting quality. We systematically investigated the effect of solution conditions on lysozyme nucleation rates and the volume of crystals produced. Batch crystallization plates were used in combination with a video microscope system to measure nucleation rates and crystal volume. As expected from classical nucleation theory, crystal numbers were found to increase with increases in temperature and supersaturation. Small changes in solution pH, at constant supersaturation values were found, however, to dramatically effect the number of crystals nucleated in the wells varying from 1000s to 10s in the pH range 4.0 to 5.2. Having optimized the conditions required to produce an appropriate number of crystals of a suitable volume for X-ray analysis, a large number of uniform crystals were produced under exactly the same conditions. In the X-ray analysis of more than 50 such crystals there was found a wide variation in crystal lattice parameters and data quality. The variation in X-ray quality crystal samples is thought to be related to the growth rate variation caused by growth rate dispersion seen in lysozyme crystal growth experiments.

Judge, R. A.↗

NASA NTRS2008

Overview of the LaNCETS Flight Experiment and the CFD Analysis

LaCETS baseline flight study include: 29 high-quality nearfield shock structure probings at three Mach numbers; Shocks in exhaust plume measured; ! CFD study of simplified nozzle shows similar plume structures as flight data; ! Phase II flights scheduled for October 2008; and ! US Industry and Academia invited to participate in analysis, review, and assessment of LaNCETS data.

Cliatt, Larry J., II↗

NASA NTRS1989

Application of the p-version of the finite-element method to global-local problems

A brief survey is given of some recent developments in finite-element analysis technology which bear upon the three main research areas under consideration in this workshop: (1) analysis methods; (2) software testing and quality assurance; and (3) parallel processing. The variational principle incorporated in a finite-element computer program, together with a particular set of input data, determines the exact solution corresponding to that input data. Most finite-element analysis computer programs are based on the principle of virtual work. In the following, researchers consider only programs based on the principle of virtual work and denote the exact displacement vector field corresponding to some specific set of input data by vector u(EX). The exact solution vector u(EX) is independent of the design of the mesh or the choice of elements. Except for very simple problems, or specially constructed test problems, vector u(EX) is not known. Researchers perform a finite-element analysis (or any other numerical analysis) because they wish to make conclusions concerning the response of a physical system to certain imposed conditions, as if vector u(EX) were known.

Szabo, Barna A.↗

NASA NTRS1979

Remote sensing analysis of water quality in the San Francisco Bay-delta

Water quality parameters in the San Francisco Bay-delta area using remotely sensed data combined with in situ data are investigated. The parameters included suspended solids, chlorophyll, turbidity, and electrical conductivity; the ocean color scanner (OCS) data were acquired from a NASA U-2 aircraft, and water quality samples were obtained from boats. It was concluded that areas with high biological activity were clearly discernible on enhanced imagery from OCS data, and it was impossible to locate such areas on aerial photography taken with conventional or infrared sensitive color films.

Khorram, S.↗