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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Cyber Halo Innovation Research Program (CHIRP) Student Research Report: Program Analysis

The Cybersecurity and Space Systems Research Program (CHIRP) conducted multi-year, mission-focused research addressing emerging cybersecurity challenges affecting space and ground systems. Students from California State University San Bernardino (CSUSB), University of Texas El Paso (UTEP), and California State University Dominguez Hills (CSUDH) conducted structured research, developed proof-of-concept demonstrations, participated in applied cybersecurity training, and collaborated with Space Systems Command (SSC), academic, and industry partners. This report documents the research questions, methodologies, findings, demonstrations, and student contributions associated with each cohort. It also summarizes the program’s workforce-development outcomes, including applied cybersecurity training, professional certifications, technical credentials, and partnerships with organizations such as CT Cubed, Inc. and ISC2. Collectively, CHIRP strengthened the space-cybersecurity workforce pipeline and produced research and prototype efforts that may inform future cybersecurity assessments, test and evaluation activities, cyber-range development, acquisition planning, operational training, and mission-assurance initiatives.

McKenzie, Penny L.↗
DOE OSTI2019

Estimation of the Fuel Efficiency Potential of Six Gasoline Blendstocks Identified by the U.S. Department of Energy’s Co-Optimization of Fuels and Engines Program

Six blendstocks identified by the Co-Optimization of Fuels & Engines Program were used to prepare fuel blends using a fixed blendstock for oxygenate blending and a target RON of 97. The blendstocks included ethanol, n-propanol, isopropanol, isobutanol, diisobutylene, and a bioreformate surrogate. The blends were analyzed and used to establish interaction factors for a non-linear molar blending model that was used to predict RON and MON of volumetric blends of the blendstocks up to 35 vol%. Projections of efficiency increase, volumetric fuel economy increase, and tailpipe CO2 emissions decrease were produced using two different estimation techniques to evaluate the potential benefits of the blendstocks. Ethanol was projected to provide the greatest benefits in efficiency and tailpipe CO2 emissions, but at intermediate levels of volumetric fuel economy increase over a smaller range of blends than other blendstocks. A bioreformate surrogate blendstock was projected to provide the greatest increase in volumetric fuel economy and the lowest increase in efficiency. Tailpipe CO2 emissions for blends of the bioreformate surrogate were higher at all blend levels compared to the baseline E10 fuel.

02 PETROLEUM↗
DOE OSTI2024

Implementing Ordinary Differential Equation Solvers in Rust Programming Language for Modeling Vehicle Powertrain Systems: Preprint

Efficient and accurate ordinary differential equation (ODE) solvers are necessary for powertrain and vehicle dynamics modeling. However, current commercial ODE solvers can be financially prohibitive, leading to a need for accessible, effective, open-source ODE solvers designed for powertrain modeling. Rust is a compiled programming language that has the potential to be used for fast and easy-to-use powertrain models, given its exceptional computational performance, robust package ecosystem, and short time required for modelers to become proficient. However, of the three commonly used (>3,000 downloads) packages in Rust with ODE solver capabilities, only one has more than four numerical methods implemented, and none are designed specifically for modeling physical systems. Therefore, the goal of the Differential Equation System Solver (DESS) was to implement accurate ODE solvers in Rust designed for the component-based problems often seen in powertrain modeling. DESS is a text-based software package that provides a flexible framework for building and solving systems of ODEs. This allows DESS to be included as a dependency for automotive powertrain models that require a variety of solvers and solver configurations. Seven explicit ODE solver methods have been implemented in DESS: Euler’s, Heun’s, midpoint, Ralston’s, classic Runge-Kutta, Bogacki-Shampine, and Cash-Karp. These represent five fixed-step methods and two adaptive-step methods. This paper shows that the solver implementations increase accuracy and computational efficiency compared to Euler's method when modeling a system of three thermal masses in Rust. DESS also includes features designed for modeling component-based physical systems. Users can define relationships between nodes in their system, which the package then translates into a system of equations, leading to simpler and more intuitive code. In the case of a three-thermal-mass system, the user can specify node thermal properties (e.g., thermal capacitance), how nodes are interconnected, and thermal conductance between nodes rather than providing a system of equations. The core contribution from this work is an open-source, text-based Rust package with ODE solvers for automotive powertrain modeling to support cost-free, fast, and accurate simulation.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Weatherization Assistance Program and Low Income Home Energy Assistance Program for Solar Survey Responses and Plan

This data contains the results of surveys given to Low Income Home Energy Assistance Program (LIHEAP)/Weatherization Assistance Program (WAP) administrators in 2022, 2023, and 2024, as well as spreadsheets coding states' annual LIHEAP and WAP plans from 2021, 2022, and 2023 for mentions of solar energy. This data is the second version of the original dataset which has been updated to include the most recent years of LIHEAP and WAP plans. The original version of the dataset is also part of this record but has been deprecated.

14 SOLAR ENERGY↗
DOE OSTI2013

Evaluation of the flow-based programming (FBP) paradigm as an alternative to standard programming practices in physics data processing applications

The majority of developed physics data processing applications (PDP) are single, sequential processes that start at a point in time, and advance one step at a time until they are finished. In the current era of cloud computing and multi-core hardware architectures this approach has noticeable limitations. In this paper we present a detailed evaluation of the FBP-based Clas12 event reconstruction program that was deployed and operated both in cloud and in batch processing environments. We demonstrate the programming methodology and discuss some of the issues and optimizations affecting performance. We will also discuss our choice of using the Petri-Net process modeling formalism for the representation of the Clas12 PDP application building blocks which exhibit concurrency, parallelism, and synchronization.

Abbott, David↗
DOE OSTI2022

Plasma-Catalyst Reactivity Control of Surface Nitrogen Species through Plasma-Temperature-Programmed Hydrogenation to Ammonia

Nonthermal plasma activation of N 2 can facilitate nitrogen adsorption on metal catalysts at low bulk temperatures and atmospheric pressure. Here, we apply a plasma-assisted temperature-programmed reaction (plasma-TPRxn) for ammonia (NH 3 ) synthesis using sequential exposure of a silica-supported metal catalyst to N 2 plasma followed by thermal hydrogen treatment while ramping the temperature to decouple the plasma activation of N 2 from surface catalyzed hydrogenation steps. This approach eliminates the effects from bulk plasma phase reactions, thereby allowing for direct interrogation of plasma activated nitrogen on the active metal surfaces. We confirm previously reported spectroscopic observations that show plasma-generated surface nitrogen can be converted to NH 3 through surface catalyzed pathways. Further, we demonstrate that the ammonia desorption peak temperature is sensitive to metal, with Pt desorbing NH 3 at the lowest temperature. Unsteady state microkinetic models of desorption kinetics as a function of initial N coverage and metal recover observed trends in NH 3 desorption temperatures and confirm that observed results reflect hydrogenation of plasma-induced N accommodation at each surface. In total, we show that the hydrogenation ability of the catalyst after plasma activation of N 2 is responsible for the reactivity trends observed in plasma-assisted NH 3 synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Optimizing the self-assembly of conjugated polymers and small molecules through structurally programmed non-covalent control

Organic conjugated polymers and oligomers are key electronic materials for applications such as transistors, photovoltaics, and light emitting devices due to their potential for solution processability, mechanical flexibility, and precise structure-based tuning compared to inorganic materials. In dilute environments, the optoelectronic properties of conjugated polymers are largely governed by their constitutional structure and, to a lesser degree, their solution-state intramolecular configuration. In the solid state, intramolecular conformation and intermolecular electronic coupling impact these properties substantially, especially in relation to device performance. Therefore, an increasingly important area of research concerning conjugated materials is developing design strategies aimed at optimizing the solid-state packing for electronic applications. Programming solid-state packing arrangements through discrete non-covalent interactions is an emerging strategy within the context of conjugated polymers. This review focuses on the use of the two most prevalent discrete and directional interactions used to dictate the self-assembly of conjugated polymers and oligomers—hydrogen bonds and chalcogen bonds. Further, we also discuss how these design motifs can imbue conjugated materials with appealing physical properties while simultaneously retaining or improving electronic capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bridging the Void: Halogen Bonding and Aromatic Interactions to Program Luminescence and Electronic Properties of π -Conjugated Materials in the Solid State

π-Conjugated materials are promising candidates for emerging organic optoelectronic devices empowered by molecular design. The unsolved challenges of predicting and controlling their packing as solids, central to their properties and performance, currently limits their practical application. As noncovalent interactions drive packing, control over such interactions are critical to bridging from chemical structure to functional properties. In molecular crystals, halogen bonding and interactions of aromatic rings have emerged as versatile tools for noncovalent control with tailored luminescence and electronic properties. Here, we describe how the interplay of these directional and tunable interactions can engineer properties, including stimuli-responsive behavior. Specifically, halogen bonding can provide robust designs for directing 2D molecular assembly, whereas the intentional interactions of aromatic rings can yield metastable, switchable packing modes, as well as programmed stacking between layers of chromophores. Examples, herein, demonstrate clear relationships between assembly by design and resulting solid-state properties, and strategies presented offer guidance for future designs of π-conjugated molecular materials using specific aromatic interactions and halogen bonding.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The Development of Kinetic and Radiation Hydrodynamics Modeling of Thermonuclear Burn Propagation in Isochoric p - 11 B Through the Support of the INFUSE Program

The report summarizes DOE INFUSE-supported work between HB11 Energy and the University of Rochester’s TriForce Institute to improve computational modeling of advanced fusion fuels, especially proton–boron-11 (p- 11 B). The project extended the TriForce particle-in-cell/Monte Carlo collision code to include physics needed for dense, high-temperature p- 11 B burn studies, including p- 11 B fusion reactions, three-alpha-particle reaction products, relativistic Coulomb collisions, large-angle nuclear scattering, bremsstrahlung radiation, inverse bremsstrahlung absorption, and photon transport. The upgraded models were verified against focused physics tests and against known deuterium–tritium burn behavior. The study then used one-dimensional spherical simulations to estimate the conditions required for thermonuclear burn propagation in isochoric p- 11 B fuel. The calculations found that burn propagation is possible in the model, but only under very extreme hot-spot conditions, such as about 7000 g/cm 3 at 500 keV or 9000 g/cm 3 at 300 keV for a 20-micron hot spot. These conditions are much more demanding than current demonstrated inertial confinement fusion hot spots. The report concludes that the INFUSE collaboration successfully advanced kinetic and radiation modeling capabilities for p- 11 B fusion and provided useful estimates of ignition requirements. However, the simulated fuel gains remain below what would be needed for practical inertial fusion energy, and further work is needed to reconcile differences among kinetic, radiation-hydrodynamic, and analytic models and to identify more achievable target designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

Exascale Programming Approaches for Accelerated Climate Modeling for Energy

The Accelerated Climate Modeling for Energy (ACME) program is a leading-edge climate and Earth system model designed to address the U.S. Department of Energy (DOE) mission needs. The ACME project involves collaboration between seven National Laboratories, the National Center for Atmospheric Research, four academic institutions, and one private-sector company. The ACME project funds ongoing efforts to ensure the model continues to make efficient use of DOE Leadership Computing Facilities (LCFs) in order to best address the three driving grand challenge science questions:Water cycle: How will more realistic portrayals of features important to the water cycle (resolution, clouds, aerosols, snowpack, river routing, land use) affect river flow and associated freshwater supplies at the watershed scale?Cryosphere systems: Could a dynamical instability in the Antarctic ice sheet be triggered within the next 40 years?Biogeochemistry: What are the contributions and feedbacks from natural and managed systems to current greenhouse gas fluxes, and how will those factors and associated fluxes evolve in the future?

Norman, Matthew↗
DOE OSTI2020

On Mixed-Integer Programming Formulations for the Unit Commitment Problem

We provide a comprehensive overview of mixed-integer programming formulations for the unit commitment (UC) problem. UC formulations have been an especially active area of research over the past 12 years due to their practical importance in power grid operations, and this paper serves as a capstone for this line of work. We additionally provide publicly available reference implementations of all formulations examined. We computationally test existing and novel UC formulations on a suite of instances drawn from both academic and real-world data sources. Driven by our computational experience from this and previous work, we contribute some additional formulations for both generator production upper bounds and piecewise linear production costs. By composing new UC formulations using existing components found in the literature and new components introduced in this paper, we demonstrate that performance can be significantly improved—and in the process, we identify a new state-of-the-art UC formulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Materials Design and Discovery: Catalysis and Energy Storage (Mira Early Science Program Final Technical Report): ALCF-2 Early Science Program Technical Report

The investigation and design of new classes of materials for energy and catalysis requires a multi-facetted approach to simulation. Multiple methods are needed to study materials on the length scale 0.1 nm - 10 nm. For simulations where the atomic (and electronic) degrees of freedom are relevant, the methods of choice in the surface science, condensed matter physics, and material science communities are classical molecular dynamics (CMD), Density Functional Theory (DFT), and quantum Monte Carlo (QMC). The original scope for this Early Science Program (ESP) project was to perform fast-accurate DFT calculations on materials for energy and catalysis using the GPAW code on Blue Gene/Q. The types of calculations included significantly reduced time-to-solution on systems sizes accessible on Blue Gene/P (~10, 0000 valence electrons), but also systems which were were at least a factor of two larger (~20, 000 valence electrons). GPAW is a real-space DFT code using the projector augmented wave (PAW) method. DFT calculations on Blue Gene/P were executed on over >100, 000 cores using GPAW; thus it was consider a success on Mira’s predecessor system, Intrepid. One of the co-PIs (NAR), determined that the work necessary to allow the GPAW code for these aforementioned types of calculations could not be accomplish within the time frame of the ESP. This was not simply due to human time required to implement OpenMP parallelism, but also from intrinsic algorithmic limitations in supporting libraries, most notably ScaLAPACK. Additionally, the return-on-investment on $\mathcal{O}(N^3)$ DFT code has become some what tenable at best. NAR argues that what is really needed in preparation for exascale computing and to enable high-fidelity materials research is robust reduced scaling, $\mathcal{O}$(N) or $\mathcal{O}$(N)log(N), DFT approaches. Thus, in agreement with the other co-PIs, the decision was made to purse QMC as a complimentary method on Mira since it would be valuable for the scientific community and could easily leverage the massive parallelism that would be provided by the Blue Gene/Q. We note that the two other atomic-scale methods mentioned here, CMD and DFT, are being pursued by other ESP projects on Mira. The remainder of this report will focus on our progress on QMC.

Benali, Anouar↗
DOE OSTI2013

Methane Hydrate Field Program. Development of a Scientific Plan for a Methane Hydrate-Focused Marine Drilling, Logging and Coring Program

This topical report represents a pathway toward better understanding of the impact of marine methane hydrates on safety and seafloor stability and future collection of data that can be used by scientists, engineers, managers and planners to study climate change and to assess the feasibility of marine methane hydrate as a potential future energy resource. Our understanding of the occurrence, distribution and characteristics of marine methane hydrates is incomplete; therefore, research must continue to expand if methane hydrates are to be used as a future energy source. Exploring basins with methane hydrates has been occurring for over 30 years, but these efforts have been episodic in nature. To further our understanding, these efforts must be more regular and employ new techniques to capture more data. This plan identifies incomplete areas of methane hydrate research and offers solutions by systematically reviewing known methane hydrate “Science Challenges” and linking them with “Technical Challenges” and potential field program locations.

58 GEOSCIENCES↗
DOE OSTI2021

Light Water Reactor Sustainability Program Materials Research Pathway Technical Program Plan

The objectives of this report are to describe the motivation and organization of the MR Pathway within the LWRS program; provide details on the individual research tasks within the MR Pathway; describe the outcomes and deliverables of the MR Pathway, including recent technical highlights and progress; and describe the requirements for performing this critically important research.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

System, method, and computer program product for bulk synchronous binary program translation and optimization

A system, method, and computer program product are provided for. The method includes the steps of executing a block of translated binary instructions by multiple threads and gathering profiling data during execution of the block of translated binary instructions. The multiple threads are then synchronized at a barrier instruction associated with the block of translated binary instructions and the block of translated binary instructions is replaced with optimized binary instructions, where the optimized binary instructions are produced based on the profiling data.

Diamos, Gregory Frederick↗