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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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At least 271 records · Page 15
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DOE OSTI2024

Frequency Response Improvement in a Standalone Small Hydropower Plant Using Battery Storage

This paper proposes a control architecture for frequency, current, and voltage control that facilitates using battery storage to improve the response of standalone small hydropower plants. The frequency controller uses rate-of-change of frequency and frequency-Watt-based generations to produce active power commands. The distinctive feature of the controller design is that it nicely integrates response to frequency change with constraints on frequency and state of battery to enable power injections. The current and voltage control scheme allows incorporating the frequency controller. The distinctive feature of this controller is that it incorporates a bounded integral control strategy that guarantees stability. Results on the stability of the hydropower plant with proposed scheme are presented and robust ways to choose the controller gains are investigated via root locus analysis. In conclusion, simulations performed show that: the hydropower plant response is significantly improved with battery storage using the proposed scheme; the load carrying capability of the hydropower plant is significantly improved with battery storage; the proposed scheme has the capability to recharge the battery; and the proposed control scheme gives improved performance.

13 HYDRO ENERGY↗
DOE OSTI2024

Market Implications of Alternative Operating Reserve Modeling in Wholesale Electricity Markets

Pricing and settlement mechanisms are crucial for efficient resource allocation, investment incentives, market competition, and regulatory oversight. In the United States, Regional Transmission Operators (RTOs) adopts a uniform pricing scheme that hinges on the marginal costs of supplying additional electricity. This study investigates the pricing and settlement impacts of alternative reserve constraint modeling, highlighting how even slight variations in the modeling of constraints can drastically alter market clearing prices, reserve quantities, and revenue outcomes. Focusing on the diverse market designs and assumptions in ancillary services by U.S. RTOs, particularly in relation to capacity sharing and reserve substitutions, the research examines four distinct models that combine these elements based on a large-scale synthetic power system test data. Our study provides a critical insight into the economic implications and the underlying factors of these alternative reserve constraints through market simulations and data analysis.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

The critical importance of software for HEP

Particle physics has an ambitious and broad global experimental programme for the coming decades. Large investments in building new facilities are already underway or under consideration. Scaling the present processing power and data storage needs by the foreseen increase in data rates in the next decade for HL-LHC is not sustainable within the current budgets. As a result, a more efficient usage of computing resources is required in order to realise the physics potential of future experiments. Software and computing are an integral part of experimental design, trigger and data acquisition, simulation, reconstruction, and analysis, as well as related theoretical predictions. A significant investment in computing and software is therefore critical. Advances in software and computing, including artificial intelligence (AI) and machine learning (ML), will be key for solving these challenges. Making better use of new processing hardware such as graphical processing units (GPUs) or ARM chips is a growing trend. This forms part of a computing solution that makes efficient use of facilities and contributes to the reduction of the environmental footprint of HEP computing. The HEP community already provided a roadmap for software and computing for the last EPPSU, and this paper updates that, with a focus on the most resource critical parts of our data processing chain.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Foundations of automatic feature extraction at LHC–point clouds and graphs

Abstract Deep learning algorithms will play a key role in the upcoming runs of the Large Hadron Collider (LHC), helping bolster various fronts ranging from fast and accurate detector simulations to physics analysis probing possible deviations from the Standard Model. The game-changing feature of these new algorithms is the ability to extract relevant information from high-dimensional input spaces, often regarded as “replacing the expert” in designing physics-intuitive variables. While this may seem true at first glance, it is far from reality. Existing research shows that physics-inspired feature extractors have many advantages beyond improving the qualitative understanding of the extracted features. In this review, we systematically explore automatic feature extraction from a phenomenological viewpoint and the motivation for physics-inspired architectures. We also discuss how prior knowledge from physics results in the naturalness of the point cloud representation and discuss graph-based applications to LHC phenomenology.

Bhardwaj, Akanksha↗
DOE OSTI2025

MiniMOD

SAND2025-03854O MiniMod is a user-friendly software tool designed to assess the performance of high-performance computing (HPC) systems. Researchers can use the program to test communication methods and computational tasks to understand how different setups can affect application efficiency. This software is particularly useful for optimizing network performance in scientific research, simulations, and data analysis. MiniMod‘s flexible design allows users to make informed decisions about their computing environments, which can enhance productivity and results in real-world applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Dosanjh, Matthew [Sandia National Lab. (SNL-CA), L↗
DOE OSTI2025

Subtropical Jet Regulates Arabian Winter Precipitation: A Viable Mechanism

The present study explores the mechanism governing wintertime (November–April) precipitation over the Arabian Peninsula (AP) using a 17-yr-long (2002–18) high-resolution WRF simulation. The composite analysis of strong precipitation events suggests that the equatorward extension of the upper-level jet together with the embedded upper-level trough creates a positive (cyclonic) midlevel vorticity and subsequently generates an anomalous lower-level convergence through Ekman pumping. This leads to the development of an anomalous surface low, which is further enhanced in the presence of the existing Red Sea trough over the AP. This surface low weakens the persistent anticyclone over the AP, shifting it further eastward to the Arabian Sea. The eastward shift in the lower-level anticyclone contributes to the transport of warm, moist air from the Arabian Sea and the Red Sea toward the AP. This warm, moist air converges with the cold and dry air advected by the midlatitude jet and creates a moisture convergence zone, leading to the initiation of convection. We test the proposed mechanism through numerical experiments with modified upper-level wind and demonstrate that a strong, southward intrusion of the jet can indeed lead to precipitation over the AP. The above mechanism also explains the interannual variability of precipitation over the AP. During wet years, we notice approximately 3 m s -1 stronger jet core magnitude and about a 2° equatorward shift of the jet compared to dry years. While the equatorward extension of the jet explains about 21% of the interannual variability, the jet magnitude explains around 7% of the variability during wet years.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Environmental Conditions Affecting Global Mesoscale Convective System Occurrence

Abstract The ERA5 environments of mesoscale convective systems (MCSs), tracked from satellite observations, are assessed over a 20-yr period. The use of a large set of MCS tracks allows us to robustly test the sensitivity of the results to factors such as region, latitude, and diurnal cycle. We aim to provide novel information on environments of observed MCSs for assessments of global atmospheric models and to improve their ability to simulate MCSs. Statistical analysis of all tracked MCSs is performed in two complementary ways. First, we investigate the environments when an MCS has occurred at different spatial scales before and after MCS formation. Several environmental variables are found to show marked changes before MCS initiation, particularly over land. The vertically integrated moisture flux convergence shows a robust signal across different regions and when considering MCS initiation diurnal cycle. We also found spatial scale dependence of the environments between 200 and 500 km, providing new evidence of a natural length scale for use with MCS parameterization. In the second analysis, the likelihood of MCS occurrence for given environmental conditions is evaluated, by considering all environments and determining the probability of being in an MCS core or shield region. These are compared to analogous non-MCS environments, allowing discrimination between conditions suitable for MCS and non-MCS occurrence. Three environmental variables are found to be useful predictors of MCS occurrence: total column water vapor, midlevel relative humidity, and total column moisture flux convergence. Such relations could be used as trigger conditions for the parameterization of MCSs, thereby strengthening the dependence of the MCS scheme on the environment. Significance Statement Large storm systems called mesoscale convective systems form across Earth. These are collections of thunderstorms, with associated high-level clouds that produce substantial, lighter rainfall and modulate Earth’s energy balance. They produce hazardous weather conditions, such as floods and high winds, and are responsible for a high percentage of rainfall in many regions globally. We investigate the environmental conditions under which they form, so that we can understand the spatial extent of the environment which is important for their formation, and also where and when the effects of these storms might be felt. The novel information generated here should help improve the representation of these storms in weather and climate models, improving the prediction of rainfall, thunderclouds, and high-level clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Universality of Collective Density Fluctuations in Liquids at and away from Equilibrium – An Integrated Neutron Scattering, Theoretical, and Computational Study (Final Technical Report)

Liquids, ubiquitous on earth, are prototypical disordered condensed matter. As the mediate phase between non-structured gases and ordered solids, liquids p ossess intriguing complexities that are absent on either extreme counter phase, especially when they are driven away from equilibrium. Despite decades of studies, the physics of liquids still keeps surprising us and challenges our understanding of condensed matter, emergent phenomena, and complex systems. Among the many interesting properties, the nature of collective dynamics in liquids remains elusive because of both the presence of strong interactions and the absence of translational invariance. This project studied the universal features of collective density fluctuations (or collective modes), which include both phonon-like excitations and collective relaxations, in the Q-dependent generalized hydrodynamic regime in liquids and liquid-like matter both at and away from equilibrium. We performed systematic studies of the fast collective dynamics (including both phonon-like excitations and collective relaxations) of four classes of liquids characterized by different fragilities and interactions using synergistically integrated coherent neutron scattering experiments (Inelastic Neutron Scattering (INS), Quasi-Elastic Neutron Scattering (QENS), and Neutron Spin Echo (NSE)), a ViscoElastic Hydrodynamics theory we have been developing, andMolecular Dynamics (MD) simulations and our analysis package LiquidLib. The transformative knowledge of the collective dynamics in liquids is important to understand and ultimately control the transport of mass, energy, and charge in liquids, both at and away from thermal equilibrium, which may will likely impact a wide range of disciplines.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Analyzing Multifaceted Scientific Data with Topological Analytics (Final Technical Report)

This final technical report describes the activities undertaken through Department of Energy, Office of Science, Advanced Scientific Computing Research Early Career award DE-SC-0019039, “Analyzing Multifaceted Scientific Data with Topological Analytics." This report summarizes contributions made toward the research of visualization, machine learning, and topological data analysis of complex simulation data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Final DOE-ASR Report for the Project “Using LASSO to bridge the gap between model and observations and to learn about atmospheric convection”

Atmospheric convection spans a wide range of spatial and temporal scales and involves complex interactions with the surrounding dynamic and thermodynamic environment, particularly over tropical continental regions. These processes remain a major source of uncertainty in weather and climate models, including persistent biases in the diurnal cycle of convective precipitation that directly affect estimates of climate sensitivity. Addressing these challenges requires the combined use of high-resolution observations and cloud-resolving modeling frameworks. In this context, the DOE Atmospheric Radiation Measurement (ARM) program’s Large-Eddy Simulation ARM Symbiotic Simulation and Observation (LASSO) activity provides a powerful platform that pairs comprehensive observations with numerical simulations to enable process-level understanding of atmospheric convection. Within this context, this Research and Development Partnership Pilot (RDPP) project was designed to initiate and expand DOE ARM/ASR research capacity at minority-serving institutions, while advancing scientific understanding of convective processes over the Amazon rainforest. Consistent with the RDPP mission, the project emphasized partnership development, training, and workforce capacity building alongside exploratory research activities. On the scientific side, the project produced two peer-reviewed journal articles, and one manuscript currently under review (see list in section 3.1). Together, these studies combine long-term ARM observations and cloud-resolving and convection-permitting modeling to investigate the environmental controls on the shallow-to-deep convective transition during the Amazon wet season. The results demonstrate the central role of early-day moisture preconditioning and large-scale dynamical forcing in regulating isolated deep convection, provide mechanistic insight into convective evolution, and establish physically informed modeling frameworks for future sensitivity experiments. These scientific outcomes are described in sections 2.1 to 2.3 and were disseminated in 8 conference presentations (see section 3.2) and 5 invited talks (see section 3.3), reflecting broad engagement with our community. Equally important, the project achieved its RDPP capacity-building objectives (see section 2.4). A sustained research partnership was established among the University of Maryland, Baltimore County (UMBC), Morgan State University (MSU), and Howard University (HU), and extended to include collaboration with Pacific Northwest National Laboratory (PNNL). The project organized multiple multi-day training events focused on ARM data, LASSO simulations, and quantitative analysis methods, directly engaging students, postdoctoral researchers, and faculty across institutions. These activities broadened participation in ASR research and led to independent adoption of LASSO workflows by students beyond the immediate project team. Finally, the project successfully positioned the participating institutions to pursue future DOE research. Preliminary scientific results, coupled with strengthened partnerships and technical capacity, enabled the submission of follow-on proposals to DOE ASR funding opportunities. In this way, the project fulfilled the RDPP goal of seeding durable research capacity and laying the foundation for larger-scale, sustained engagement with DOE ARM and ASR programs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

LSST Scheduler & Progress Monitoring

The NSF-DOE Vera C. Rubin Observatory scheduling team is providing a set of tools for monitoring the scheduler and progress on the Legacy Survey of Space and Time (LSST). These slides provide an overview of available pages and assorted figures on them: the night summary provides an overview of a completed night of observing, including maps of exposures and plots of data quality metrics; the pre-night briefing, an analysis of a simulation of an upcoming night; and a handful of figures that provide information on long-term progress toward LSST survey goals.

H.Neilsen, Eric, Jr. [Fermilab] (ORCID:00000002735↗
DOE OSTI2024

Testing the LSST Difference Image Analysis Pipeline Using Synthetic Source Injection Analysis

Abstract We evaluate the performance of the Legacy Survey of Space and Time Science Pipelines Difference Image Analysis (DIA) on simulated images. By adding synthetic sources to galaxies on images, we trace the recovery of injected synthetic sources to evaluate the pipeline on images from the Dark Energy Science Collaboration Data Challenge 2. The pipeline performs well, with efficiency and flux accuracy consistent with the signal-to-noise ratio of the input images. We explore different spatial degrees of freedom for the Alard–Lupton polynomial-Gaussian image subtraction kernel and analyze for trade-offs in efficiency versus artifact rate. Increasing the kernel spatial degrees of freedom reduces the artifact rate without loss of efficiency. The flux measurements with different kernel spatial degrees of freedom are consistent. We also here provide a set of DIA flags that substantially filter out artifacts from the DIA source table. We explore the morphology and possible origins of the observed remaining subtraction artifacts and suggest that given the complexity of these artifact origins, a convolution kernel with a set of flexible bases with spatial variation may be needed to yield further improvements.

Liu, S. (ORCID:0000000244612143)↗
DOE OSTI2026

Constraining the Dynamo Layers in Jupiter and Saturn with Observations and Scaling Laws

The dipole-dominated magnetic fields of Jupiter and Saturn provide evidence for active dynamos operating within their deep interiors, yet the depth of the convecting dynamo layers remains poorly constrained. While magnetic field observations, gravity data, and interior models each provide partial insight, they have not been combined into a single, self-consistent picture of the internal structure. Here, we develop a framework that links observed magnetic field strength with intrinsic heat flux and gravity-constrained interior structure using energy-based dynamo scaling laws. By relating the axial magnetic field strength to the convective power, we infer the radial thickness of the dynamo-generating region for both Jupiter and Saturn. The constants of proportionality in the scaling relations are derived using independent constraints from Earth observations, Jupiter observations, and numerical dynamo simulations. Applied to Jupiter, this framework shows how the inferred dynamo layer thickness is coupled to the outer boundary of the dynamo region. Thinner dynamo layers are predicted when the outer boundary shifts to shallower depths, and no solutions are possible when the outer boundary is less than 73% of Jupiter’s radius. These results constrain plausible geometries for future numerical dynamo simulations. Extending the analysis to Saturn, we find a thick, deep-seated dynamo layer with an outer radius at 42% of the radius to be most plausible. An alternative solution with an inner radius of the dynamo region at 60% of the planetary radius, as suggested by ring seismology models, requires a very thin dynamo layer, occupying only 2%–3% of the total radius.

Geosciences↗
DOE OSTI2026

Time-resolved X-ray imaging of the current filamentation instability in solid-density plasmas

The streaming of energetic charged particles can magnetize astrophysical and laboratory plasmas via the current filamentation instability. Despite its importance, the experimental characterization of this instability has remained a challenge. Here, we report an experiment combining a high-intensity optical laser with a high-brightness X-ray free electron laser that successfully images the instability in solid-density plasmas with 200nm spatial and 50fs temporal resolution. We characterize the development of µm-scale filamentary structures and their evolution over tens of picoseconds through a non-linear merging process. The measured plasma density modulations and long merging time reveal the critical importance of space-charge effects and ion motion on this electron-driven instability. Supporting theoretical analysis and kinetic simulations help distinguish the relative role of space-charge and resistive effects. Our findings indicate that magnetic fields on the order of 10megagauss are produced, with important implications for transport and radiation emission of energetic particles in plasmas.

Schoenwaelder, Christopher↗
DOE OSTI2025

Quantum Enhanced Dark-Matter Search with Entangled Fock States in High-Quality Cavities

We present a quantum-enhanced protocol for detecting wave-like dark matter using an array of $N$ entangled superconducting cavities initialized in an $m$-photon Fock state. By distributing and recollecting the quantum state with an entanglement-distribution operation, the scan rate scales as $N^2(m+1)$ while thermal excitation is the dominant background, significantly outperforming classical single-cavity methods under matched conditions. We evaluate the robustness of our scheme against additional noise sources, including decoherence and beamsplitter infidelity, through theoretical analysis and numerical simulations. In practice, the key requirements, namely high-Q superconducting radio-frequency cavities that support long integration times, high-fidelity microwave beamsplitters, and universal cavity control, are already available on current experimental platforms, making the protocol experimentally feasible.

Freiman, Benjamin [Fermilab]↗
DOE OSTI2026

Conservation laws and effective hadronization models

Hadronization models based on local string-breaking dynamics are typically Markovian by construction, yet the physical ensemble of final states is shaped by global constraints that couple the entire fragmentation trajectory. Recasting hadronization as a conditioned stochastic diffusion process provides a precise mathematical resolution to this tension. In particular, this language reveals explicitly that constraints stemming from conservation laws induce non-Markovian correlations between otherwise independent fragmentation steps, and that these correlations can be absorbed exactly into a renormalization of the local dynamics through a Doob $h$-transform. We develop this formalism for a $q\bar{q}$ string in the chiral limit, where the longitudinal-transverse factorization of the Lund kernel becomes exact, enabling systematic power counting and clean ultraviolet (UV)/infrared (IR) separation. The dynamics organize naturally into a tower of effective theories distinguished by the remaining string mass, spanning a UV fixed point with scale-invariant transport coefficients, an intermediate regime where transverse phase space induces controlled running, and an IR boundary layer where non-local effects enter at leading order. The tower exhibits genuine Wilsonian structure, including $β$-functions, anomalous dimensions, and systematic matching conditions. The resulting framework achieves a clean factorization of universal microscopic fragmentation dynamics from infrared constraint effects, and opens new directions for both the theoretical analysis and practical simulation of hadronization.

Menzo, Tony [Alabama U.; Fermilab] (ORCID:00000002↗
DOE OSTI2024

Infrastructure improvements in the National Reactor Innovation Center Virtual Test Bed

The National Reactor Innovation Center’s (NRIC) mission is to support deployment of novel reactor concepts. This is achieved by providing physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed (VTB) represents the virtual counterpart to the physical test bed. The VTB is being developed in collaboration with the Department of Energy’s (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The mission of the VTB is to accelerate the deployment and licensing of advanced reactors by leveraging state-of-the-art modeling and simulation (M&S) tools developed by the DOE NEAMS program. This is accomplished via three primary means: (1) openly hosting simulations that showcase analysis capabilities, (2) continuously testing the models hosted against code updates to avoid deprecation, and (3) filling key M&S gaps that are relevant for the physical NRIC test beds. The VTB repository consists of two sub-entities: • A documentation website detailing the models: https://mooseframework.inl.gov/virtual_test_bed • A GitHub repository that hosts the corresponding files: https://github.com/idaholab/virtual_test_bed. This paper presents the infrastructure added to the VTB in the last two fiscal years. Additional information about the VTB can be found in various publications [1, 2, 3, 4, 5, 6, 7, 8].

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗