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DOE OSTI2024

Trade can buffer climate-induced risks and volatilities in crop supply

Climate change is intensifying the frequency and severity of extreme events, posing challenges to food security. Corn, a staple crop for billions, is particularly vulnerable to heat stress, a primary driver of yield variability. While many studies have examined climate impact on average corn yields, little attention has been given to the climate impact on production volatility. This study investigates the future volatility and risks associated with global corn supply under climate change, evaluating the potential benefits of two key adaptation strategies: irrigation and market integration. A statistical model is employed to estimate corn yield response to heat stress and utilize NEX-GDDP-CMIP6 climate data to project future production volatility and risks of substantial yield losses. Three metrics are introduced to quantify these risks: Sigma (σ), the standard deviation of year-on-year yield change, which reflects overall yield volatility; Rho (ρ), the risk of substantial loss, defined as the probability of yield falling below a critical threshold; and Beta (β), a relative risk coefficient that captures the volatility of a region's corn production compared to the globally integrated market. The analysis reveals a concerning trend of increasing year-on-year yield volatility (σ) across most regions and climate models. This volatility increase is significant for key corn-producing regions like Brazil and the United States. While irrigated corn production exhibits a smaller rise in volatility, suggesting irrigation as a potential buffer against climate change impacts, it is not a sustainable option as it can cause groundwater depletion. On the other hand, global market integration reduces overall volatility and market risks significantly with less sustainability concerns. Furthermore, these findings highlight the importance of a multidimensional approach to adaptation in the food sector. While irrigation can benefit individual farmers, promoting global market integration offers a broader solution for fostering resilience and sustainability across the entire food system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Trends in spatial correlations, two-phase coexistence, and criticality in a class of type-2 Schloegl models for autocatalysis

A class of type-2 Schloegl models is considered for particles on a square lattice with variable-range cooperativity. These models involve: (i) spontaneous particle annihilation at rate p; (ii) autocatalytic particle creation at unoccupied sites (i, j) with n ⩾ 2 particles within a specified neighborhood, Ω 𝑁 (i, j), of sites at rate $k_n$ = $\frac{^{(^n_2)}}{_{(^N_2)}}$ = $\frac{n{(n-1)}}{_{N(N-1)}}$; and (iii) possible spontaneous particle creation at unoccupied sites at “small” rate ɛ ⩾ 0. In some cases, Ω 𝑁 just includes all symmetry-equivalent sites at a single specific distance 𝑑 (in units of lattice constants) from the unoccupied site, e.g., 𝑑 = 1 (nearest-neighbor sites) where 𝑁 = 4, or 𝑑 = √5 (or √13 or…) where 𝑁 = 8. In other cases, Ω 𝑁 includes sites multiple distances from the unoccupied site, e.g., 𝑑 = {1,√2}, where 𝑁 = 8. Kinetic Monte Carlo (KMC) simulation reveals that these models exhibit a nonequilibrium discontinuous phase transition between high- and low-density states below a critical point, ɛ < ɛ c , with generic two-phase coexistence (2PC) at least for smaller 𝑁. With some exceptions, there is an approach toward mean-field behavior with increasing 𝑁 (so the regime of generic 2PC shrinks, and ɛ c approaches the mean-field value of 1/27). Additional insight into trends is provided by analysis of the exact master equations for the models via hierarchical truncation. These truncations utilize suitably tailored pair approximations which reflect the dominant nonequilibrium spatial correlations. These correlations in turn are shown to reflect the details of the autocatalytic particle creation process. For spatially heterogeneous states, the truncations produce coupled sets of lattice differential equations (LDE) which can describe orientation-dependent propagation of an interface between high- and low-density steady states for ɛ < ɛ c . Pair approximation values of 𝑝 = 𝑝 eq where the interface is stationary, and its orientation-dependence, are in semiquantitative agreement with KMC results. In conclusion, this comparison accounts for propagation failure in the LDE which complicates interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2026

Survey of Deep Learning and Physics-Based Approaches in Computational Wave Imaging

Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse that volume. Applications include seismic exploration of the Earth’s subsurface, acoustic imaging and nondestructive testing (NDT) in material science, and ultrasound computed tomography (USCT) in medicine. Current approaches for solving CWI problems can be divided into two categories: those rooted in traditional physics and those based on deep learning. Physics-based methods stand out for their ability to provide high-resolution and quantitatively accurate estimates of acoustic properties within the medium. However, they can be computationally intensive and are susceptible to ill-posedness and nonconvexity typical of CWI problems. Machine learning (ML)-based computational methods have recently emerged, offering a different perspective to address these challenges. Diverse scientific communities have independently pursued the integration of deep learning in CWI. This review discusses how contemporary scientific ML techniques, and deep neural networks in particular, have been developed to enhance and integrate with traditional physics-based methods for solving CWI problems. We present a structured framework that consolidates existing research spanning multiple domains, including computational imaging, wave physics, and data science. This study concludes with important lessons learned from existing ML-based methods and identifies technical hurdles and emerging trends through a systematic analysis of the extensive literature on this topic.

42 ENGINEERING↗

DOE OSTI2025

Deep Design Data Portal (D3P) v0.01

The Deep Design Data Portal (D3P) tool was developed to demonstrate how readily accessible data sources, such as building energy model reports for design and baseline energy performance data for projects, can provide the data required for reporting to an industry initiative (AIA 2030 commitment), as well as more detailed data that makes the industry dataset more valuable to all stakeholders, enabling project level analysis and analysis of BEM industry trends. D3P provides an easier and less time-consuming way for firms to auto-extract data from this data source, compared to the current reporting workflows of the firms. The BEM reports are the first of several data sources that D3P could integrate. D3P also provides the ability for firms to review, compare, and evaluate the performance of their projects to not only their portfolio, but also to the larger anonymized industry dataset created each time a project is added to D3P. The intent of D3P is to become part of a data-sharing ecosystem to assist creating large anonymized industry datasets that are accessible to industry.

Regnier, Cynthia [Lawrence Berkeley National Labor↗

DOE OSTI2026

Annual Supply Chain for Photovoltaics (ASC-PV) in the United States: 2024 in Review

This report analyzes U.S. PV and BESS supply chains and costs in 2024, for PV module and battery technologies, structural and electrical balance of system (BOS) components, as well as PV recycling. The report concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.

14 SOLAR ENERGY↗

DOE OSTI2026

Genesis Mission-Enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE)

Argonne National Laboratory is supporting the U.S. Department of Transportation’s (USDOT’s) Bureau of Transportation Statistics (BTS) with collaborative research on development and application of privacy preserving AI frameworks that leverage unmatched AI expertise and secure computing resources made available through the U.S. Genesis Mission1 . This research advances U.S. energy security goals by supporting a safe offshore energy industry with secure, domain-specific AI tools to analyze confidential industry datasets collected by BTS to rapidly improve identification of hazards, precursors, and systemic safety risks in high-risk operational environments. The staged, security-first approach begins with development and testing of Argonne’s Genesis Mission-enabled Secure AI to Fortify Energy Process Safety (Genesis-SAFE) framework within Argonne’s accredited secure computing enclave (ABLE) leveraging Argonne’s AI scientific assistant substrate (AISAC). Methods to build synthetic datasets were developed together with BTS for use in preparing synthetic datasets that can be used to validate data containment, governance, and security controls in the ABLE environment. Future research directions would focus on applying the Genesis-SAFE framework to CIPSEA-protected datasets entirely within ABLE to support confidentiality-preserving analysis of safety risks, trends, and contributing factors.

Kim, Hyekyung [Argonne National Laboratory (ANL), ↗

DOE OSTI2026

U.S. Hydropower Development Pipeline Data, 2026

The U.S. Hydropower Development Pipeline dataset provides a comprehensive, regularly updated view of proposed and potential hydropower projects across the United States. This resource compiles information from federal agencies and other public sources to track non-powered dams considered for electrification, proposed hydropower facilities at stream reaches with no existing dams, conduit exemptions, and emerging pumped storage hydropower proposals. The dataset includes project characteristics such as location, development status, technology type, ownership category, and other attributes that support analysis of future hydropower trends. It is designed to help researchers, planners, policymakers, and stakeholders assess national‑scale development patterns, understand the evolving hydropower landscape, and explore opportunities and challenges associated with new hydropower deployment. The dataset is updated annually to reflect changes in project status, new proposals entering the pipeline, and projects that are cancelled, completed, or otherwise removed from active consideration. Note: Capacity additions to existing hydropower plants are not included in this database due to reliance on a proprietary data source.

Johnson, Megan [ORNL] (ORCID:0000000290141741)↗

NASA NTRS1975

Utilization of Skylab EREP system for appraising changes in continental migratory bird habitat

The author has identified the following significant results. Surface water statistics using data obtained by supporting aircraft were generated. Signature extraction and refinement preliminary to wetland and associated upland vegetation recognition were accomplished, using a selected portion of the aircraft data. Final classification mapping and analysis of surface water trends will be accomplished.

Gilmer, D. S.↗

NASA NTRS1975

Preferential concentration of certain elements in smaller aerosols emitted from aircraft engines

Aerosols from aircraft engines were collected with an eight-stage cascade sampler for a period of 24 h. The aerosol samples from each stage were analyzed for their elemental composition using the proton-induced X-ray emission (PIXE) technique. Seventeen elements (Si, P, S, Cl, K, Ca, Ti, V, Fe, Ni, Cu, Zn, Br, Sr, Nb, Sn, and Pb) were positively identified and quantitated at each stage. Six elements (S, Ca, Fe, Zn, Sn, and Pb) showed a fractional concentration increase with decreasing aerosol size. Similar, but less well-defined, trends were also observed for V and Ni. Silicon and chlorine, on the other hand, showed an opposite trend. Neutron-activation analysis of bulk aerosol samples collected every 2 h over the same period showed a correlation between concentration of Si, Ca, V, Ti, Zn, Br, and Sn and the density of air traffic at the airport. Analysis of the aviation-fuel samples by PIXE indicates that major fractions of Pb, Sn, Br, Zn, Ni, Fe, V, Ca, and S observed in these aerosol studies come from the aircraft engine exhaust.

Jolly, R. K.↗

NASA NTRS1979

Mean velocity and decay characteristics of the guidevane and stator blade wake of an axial flow compressor

Pure tone noise, blade row vibrations, and aerodynamic losses are phenomena which are influenced by stator and IGV (inlet guide vane) blade wake production, decay, and interaction in an axial-flow compressor. The objective of this investigation is to develop a better understanding of the nature of stator and IGV blade wakes that are influenced by the presence of centrifugal forces due to flow curvature. A single sensor hot wire probe was employed to determine the three mean velocity components of stator and IGV wakes of a single stage compressor. These wake profiles indicated a varying decay rate of the tangential and axial wake velocity components and a wake profile similarity. An analysis, which predicts this trend, has been developed. The radial velocities are found to be appreciable in both IGV and the stator wakes.

Lakshminarayana, B.↗

NASA NTRS1981

Landsat in the search for Appalachian hydrocarbons

A study has been conducted to determine the applicability of enhanced Landsat imagery for oil and gas exploration in Appalachia. Attention was given to the feasibility to employ lineaments identified on Landsat imagery as a tool in petroleum exploration. Lineaments, as defined in this connection, are linear or sublinear traces seen on Landsat imagery. They frequently reflect subsurface geological structures. The investigation was conducted in two stages. The first was designed to identify the specific Landsat imagery enhancement best suited for displaying lineaments. The second stage consisted of plotting lineaments and conducting an analysis of the lineament trends with regard to both local geological structure and regional tectonics. A close relationship was observed between lineaments identified on Landsat imagery and known oil and gas reservoirs. This result suggests that lineaments can be related to the structural control of oil and gas reservoirs throughout Appalachia.

Blodget, H. W.↗

NASA NTRS1982

Coupled rotor/airframe vibration analysis

A coupled rotor/airframe vibration analysis developed as a design tool for predicting helicopter vibrations and a research tool to quantify the effects of structural properties, aerodynamic interactions, and vibration reduction devices on vehicle vibration levels is described. The analysis consists of a base program utilizing an impedance matching technique to represent the coupled rotor/airframe dynamics of the system supported by inputs from several external programs supplying sophisticated rotor and airframe aerodynamic and structural dynamic representation. The theoretical background, computer program capabilities and limited correlation results are presented in this report. Correlation results using scale model wind tunnel results show that the analysis can adequately predict trends of vibration variations with airspeed and higher harmonic control effects. Predictions of absolute values of vibration levels were found to be very sensitive to modal characteristics and results were not representative of measured values.

Sopher, R.↗

NASA NTRS1985

Discrimination of a major stratospheric warming event in February-March 1984 from earlier minor warmings

As part of its responsibility for stratospheric monitoring, the Climate Analysis Center derives time trends of various dynamic parameters from NMC stratospheric analyses. Selected figures from this stratospheric monitoring data base are published in Climate Diagnostics Bulletin in March and October, after each hemispheric winter. During the Northern Hemisphere winter of December 1983-February 1984 several warming events may be seen in the plot of 60 deg. N zonal mean temperatures for 10 mb. Minor warmings may be noted in early December, late December, mid January and early February. A major warming with the 60 deg. N zonal mean temperatures reaching -40C is observed in late February, associated with a circulation reversal. In all of the minor warming episodes, there is a polarward movement of the Aleutian anticyclone; however, at 10 mb the North Pole remains in the cyclonic circulation of the stratospheric vortex which is not displaced far from its usual position. In the case of the later February major warming, the 10 mb circulation pattern over the North Pole is anticyclonic, and the cyclonic circulation has moved to the south and east with a considerable elongation. Cross sections of heat transport and momentum transport are not dramatically different for the minor and major warming episodes.

Johnson, K. W.↗

NASA NTRS1989

Volatile fractionation and tektite source material

The arguments used by Love and Woronow (1988) to assess the role played in the origin of bediasites by extensive volatile fractionation are critically examined. Using the ratios of 'refractory' oxides, CaO, Al2O3, and MgO, to the 'volatile' oxides, Na2O and K2O, these authors concluded that vapor fractionation did not play a significant role. In this paper, experimental evidence is presented that shows that the assumption of volatility for the alkali elements (as least with respect to silica) to be not valid under the conditions under which tektites formed. It is shown that the results of vapor fractionation in experiments on glasses of tektite composition are approximately parallel the trends seen in bediasite analysis.

Walter, Louis S.↗

NASA NTRS1992

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Chao, Luen-Yuan↗

NASA NTRS1992

Intelligent diagnostics systems

Intelligent systems have been applied to today's problems and could also be applied to space operations integrity. One of these systems is the XMAN tool designed for 'troubleshooting' jet engines. XMAN is the eXpert MAiNtenance tool developed to be an expert information analysis tool which stores trending and diagnostic data on Air Force engines. XMAN operates with a 'network topology' which follows a flow chart containing engine management information reports required by the governments technical order procedures. With XMAN technology, the user is able to identify engine problems by presenting the assertions of the fault isolation logic and attempting to satisfy individual assertions by referring to the databases created by an engine monitoring system. The troubleshooting process requires interaction between the technician and the computer to acquire new evidence form auxiliary maintenance tests corroboration of analytical results to accurately diagnose equipment malfunctions. This same technology will be required for systems which are functioning in space either with an onboard crew, or with an unmanned system. The technology and lessons learned developing this technology while suggesting definite applications for its use with developing space systems are addressed.

Mcquiston, Barbara M.↗

NASA NTRS1992

Computational technology for high-temperature aerospace structures

The status and some recent developments of computational technology for high-temperature aerospace structures are summarized. Discussion focuses on a number of aspects including: goals of computational technology for high-temperature structures; computational material modeling; life prediction methodology; computational modeling of high-temperature composites; error estimation and adaptive improvement strategies; strategies for solution of fluid flow/thermal/structural problems; and probabilistic methods and stochastic modeling approaches, integrated analysis and design. Recent trends in high-performance computing environment are described and the research areas which have high potential for meeting future technological needs are identified.

Noor, A. K.↗

NASA NTRS1998

Changes in the Radiometric Sensitivity of SeaWiFS

We report on the lunar and solar measurements used to determine the changes in the radiometric sensitivity of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Radiometric sensitivity is defined as the output from the instrument (or from one of the instrument bands) per unit spectral radiance at the instrument's input aperture. Knowledge of the long-term repeatability of the SeaWiFS measurements is crucial to maintaining the quality of the ocean scenes derived from measurements by the instrument. For SeaWiFS bands 1 through 6 (412 nm through 670 rim), the change in radiometric sensitivity is less than 0.2% for the period from November 1997 through November 1998. For band 7 (765 nm), the change is about 1.5%, and for band 8 (865 nm) about 5%. The rates of change of bands 7 and 8, which were linear with time for the first eight months of lunar measurements, are now slowing. The scatter in the data points about the trend lines in this analysis is less than 0.3% for all eight SeaWiFS bands. These results are based on monthly measurements of the moon. Daily solar measurements using an onboard diffuser show that the radiometric sensitivities of the SeaWiFS bands have changed smoothly during the time intervals between lunar measurements. Since SeaWiFS measurements have continued past November 1998, the results presented here are considered as a snapshot of the instrument performance as of that date.

McClain, Charles R.↗