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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Irradiation Testing of Additively Manufactured Materials for LWR Applications: Alloy 718 and 316L Stainless Steel

The objective of this NSUF Project is to assess the changes in irradiated additively manufactured (AM) material properties as compared to non-irradiated material. Type 316L stainless steel and Alloy 718 samples were produced using Direct Metal Laser Melting (DMLM) fabrication. Materials produced from this fabrication method have several potential applications within the nuclear industry as reactor internal repair parts, fuel debris resistant filters, or fuel spacers within existing light water reactors (LWRs). AM materials have been shown to achieve equivalent mechanical behavior in simulated reactor environments as compared to wrought materials, but have significantly more flexibility when it comes to unique design features. The increased component design flexibility makes these AM materials an attractive choice for both current LWR applications as well as for small modular reactor (SMR) designs. Prior to use of these materials in reactor fleet operation, the industry as a whole must evaluate the effects of irradiation on their material properties. Standard 0.4 inch thick Compact Tension specimens and SSJ3 type tensile bars were neutron irradiated at the Advanced Test Reactor to ~1 dpa for the purpose of performing a variety of mechanical tests in a range of simulated environments applicable to LWRs. For the ductile austenitic Type 316L stainless steel, the irradiated data will be used to confirm that the AM process produces materials with properties that are equivalent to wrought materials under testing conditions applicable to LWR operation. Transmission electron microscopy analysis was also performed in order to understand microstructural and microchemical changes induced in each material in response to neutron irradiation. If possible, data collected from these AM 316L samples will be used to remove fluence limits from specifications of ASME code cases for this alloy, which will give vendors much more flexibility in building future components.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

Assessing the Impact of Cybersecurity Attacks on Energy Systems

This paper investigates the cyber resiliency of future power systems with high penetration of distributed energy resources using advanced distributed and (or) hierarchical control architectures. Specifically, we simulate cyberattacks on three prototypical use cases, and we identify attack scenarios that are the most damaging to the overall system performance. We show that these attacks can have a significant impact on grid operation. Results provide additional insights into the robustness of the system to the most common cyberattacks.

buildings↗
DOE OSTI2024

Model predictive control for optimal dispatch of chillers and thermal energy storage tank in airports

Cost of energy consumption is one of the biggest operational cost for airports, and it is increasing from time to time as airports expand to support growing number of passengers. Various factors affect the energy consumption including efficiency of airport Heating Ventilation and Air conditioning (HVAC) systems, which in turn depends on the efficiency of individual subsystems. Here, in this paper, we present an optimal scheduling method for the central plant system at Dallas Fort Worth airport, involving chillers, pumps, and a thermal energy storage (TES) system. A model predictive control (MPC) problem is formulated to minimize both energy and demand charge costs while satisfying the cooling needs of the airport. The proposed Mixed-Integer Nonlinear Programming (MINLP) formulation includes performance curve based models for chillers and pumps and a simplified state of charge model for TES. The formulation also includes predictions of cooling load and chilled water return temperature. Simulation results for a month in summer show savings around 10% compared to the baseline. Initial recommendations based on insights from simulation results to the manual operation procedures resulted in significant savings. Field test results show a 7% chiller efficiency improvement.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Geothermal-integrated thermally anisotropic building envelope for energy and peak-demand reduction

Buildings consume large amounts of energy for heating and cooling, while peak electricity demand places significant stress on the power grid. This paper presents a reduced-order co-simulation framework and load-oriented supervisory control strategy for a geothermal-integrated thermally anisotropic building envelope with a ground loop (TABE+GL). In TABE+GL, a hydronic loop embedded in the building envelope is directly coupled with a geothermal ground loop, allowing for bidirectional heat exchange between the envelope, the ground, and the indoor environment. A hybrid co-simulation framework was established by coupling a reduced-order resistor–capacitor (RC) thermal network model with EnergyPlus augmented with GHEDesigner modules. The RC model generated feasible heat flux options under three operating modes, and EnergyPlus predicted sensible loads, energy use, and pump energy demand. At each simulation step, a supervisory control algorithm selected the optimal loop configuration and duty factor that maximizes useful TABE geothermal utilization without exceeding the predicted sensible load, thereby avoiding overheating or cooling. Case studies were conducted for Los Angeles, California, Charleston, South Carolina, and Denver, Colorado. Results showed that the proposed framework reduced HVAC electricity consumption by 43%–67%, natural gas use for space heating by 11%–38%, and peak electricity demand by 43%–88%. These results highlight the potential of combining reduced-order envelope modeling, direct geothermal coupling, and load-oriented supervisory control to improve whole building energy performance and reduce peak demand across diverse weather conditions.

Howard, Daniel [Southern Adventist University]↗
DOE OSTI2025

Mitigating Impact Through Community-Engaged Flood Modeling

Urban pluvial flooding poses a growing threat to the city of Baltimore, driven by heavy rainfall, increased impervious area, and aging infrastructure. Adapting to the risks posed by pluvial flooding is critical for building greater climate resiliency in Baltimore's Inner Harbor Watershed. This study addresses these challenges through community-informed decision analysis, which uses hydrologic modeling and optimization tools to identify robust flooding adaptation pathways. We will collaborate with community partners to identify key concerns and objectives regarding flooding. These concerns have been purposefully built in to a combined surface-subsurface dynamic flow simulation model. Model outputs are used to identify flooding locations within the Inner Harbor, and to test adaptation methods. Machine learning will be used search for solutions which meet diverse environmental, financial, and social goals, and solution performance will be examined under a wide range of potential future climatic conditions and integrated with an adaptive planning approach. This novel set of adaptation pathways will enhance the City's capacity to respond to evolving pluvial flood risk.

climate resilience↗
NASA NTRS2007

SPENVIS Implementation of End-of-Life Solar Cell Calculations Using the Displacement Damage Dose Methodology

This paper presents a method for using the SPENVIS on-line computational suite to implement the displacement damage dose (D(sub d)) methodology for calculating end-of-life (EOL) solar cell performance for a specific space mission. This paper builds on our previous work that has validated the D(sub d) methodology against both measured space data [1,2] and calculations performed using the equivalent fluence methodology developed by NASA JPL [3]. For several years, the space solar community has considered general implementation of the D(sub d) method, but no computer program exists to enable this implementation. In a collaborative effort, NRL, NASA and OAI have produced the Solar Array Verification and Analysis Tool (SAVANT) under NASA funding, but this program has not progressed beyond the beta-stage [4]. The SPENVIS suite with the Multi Layered Shielding Simulation Software (MULASSIS) contains all of the necessary components to implement the Dd methodology in a format complementary to that of SAVANT [5]. NRL is currently working with ESA and BIRA to include the Dd method of solar cell EOL calculations as an integral part of SPENVIS. This paper describes how this can be accomplished.

Walters, Robert↗
DOE OSTI2026

Data for Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process- Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process- based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data- constrained representation of the sterile triploid Miscanthus (IL clone) within the process- based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam- derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field- measured biomass. Building on the calibrated operating state, parameter- response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post- calibration GPP R2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

Carbon↗
DOE OSTI2020

Fossil Energy Workshop on Quantum Information Science & Technology (Summary Report)

This report summarizes findings and discussion from the Fossil Energy Workshop on Quantum Information Science & Technology which took place on November 19-21, 2019. Quantum Information Science (QIS) is expected to profoundly change the practice of science and engineering in the coming decades. It is a rapidly progressing field, fueled by large investments from the private sector and governments. Its importance to the U.S. economy and national security is underscored by the National Quantum Initiative Act passed in December 2018. QIS includes quantum sensing, quantum communications, quantum simulation experiments, and quantum computation. QIS technology exploits quantum phenomena for performing tasks that are impossible to do today, such as finding prime factors of large numbers or elucidating reaction mechanisms in complex chemical systems. The opportunities for applying QIS to problems encountered in fossil energy technology development are not known today. This workshop brought together, for the first time, experts in these fields to exchange information and explore potential research opportunities for QIS to advance fossil energy. The goal of the workshop was to develop a set of priority research opportunities that can inform future research efforts in QIS and build a community of next-generation researchers at the intersection of QIS and fossil energy.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Spatio-Temporal Surrogates for Interaction of a Jet with High Explosives: Part I - Analysis with a Small Sample Size

Computer simulations, especially of complex phenomena, can be expensive, requiring high-performance computing resources. Often, to understand a phenomenon, multiple simulations are run, each with a different set of simulation input parameters. These data are then used to create an interpolant, or surrogate, relating the simulation outputs to the corresponding inputs. When the inputs and outputs are scalars, a simple machine learning model can suffice. However, when the simulation outputs are vector valued, available at locations in two or three spatial dimensions, often with a temporal component, creating a surrogate is more challenging. In this report, we use a two-dimensional problem of a jet interacting with high explosives to understand how we can build high-quality surrogates. The characteristics of our data set are unique - the vector-valued outputs from each simulation are available at over two million spatial locations; each simulation is run for a relatively small number of time steps; the size of the computational domain varies with each simulation; and resource constraints limit the number of simulations we can run. We show how we analyze these extremely large data-sets, set the parameters for the algorithms used in the analysis, and use simple ways to improve the accuracy of the spatio-temporal surrogates without substantially increasing the number of simulations required.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Tough Errors are no Match (TEAM): Optimizing the Quantum Compiler for Noise Resilience

This project builds toward a comprehensive error-mitigating toolkit that makes quantum programming more robust and adaptive to the noisy, resource-limited nature of today’s quantum hardware. To that end, it integrates established error-mitigation methods — such as zero-noise extrapolation and dynamical decoupling — directly into compiler infrastructures. These techniques will be packaged as modules that can automatically adjust and combine based on performance analysis, enabling compilers to explore large design spaces and produce optimized, low-noise quantum programs with minimal manual intervention. In parallel, this project also explores new approaches to analog quantum programming or quantum simulation, and has developed the programming language SimuQ which treats quantum Hamiltonian evolution as the central object.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1983

Experimental and theoretical study of combustion jet ignition

A combustion jet ignition system was developed to generate turbulent jets of combustion products containing free radicals and to discharge them as ignition sources into a combustible medium. In order to understand the ignition and the inflammation processes caused by combustion jets, the studies of the fluid mechanical properties of turbulent jets with and without combustion were conducted theoretically and experimentally. Experiments using a specially designed igniter, with a prechamber to build up and control the stagnation pressure upstream of the orifice, were conducted to investigate the formation processes of turbulent jets of combustion products. The penetration speed of combustion jets has been found to be constant initially and then decreases monotonically as turbulent jets of combustion products travel closer to the wall. This initial penetration speed to combustion jets is proportional to the initial stagnation pressure upstream of the orifice for the same stoichiometric mixture. Computer simulations by Chorin's Random Vortex Method implemented with the flame propagation algorithm for the theoretical model of turbulent jets with and without combustion were performed to study the turbulent jet flow field. In the formation processes of the turbulent jets, the large-scale eddy structure of turbulence, the so-called coherent structure, dominates the entrainment and mixing processes. The large-scale eddy structure of turbulent jets in this study is constructed by a series of vortex pairs, which are organized in the form of a staggered array of vortex clouds generating local recirculation flow patterns.

Chen, D. Y.↗
NASA NTRSDate not supplied

Simplified Vehicle Control Concept for a Lift Plus Cruise eVTOL Vehicle

Electric Vertical Takeoff and Landing (eVTOL) vehicles have the potential to enable cost effective Urban Air Mobility (UAM) applications. These concepts may also pose several challenging handling and control problems, which must be addressed prior to safe and reliable urban operations. This paper investigates a simplified vehicle control concept that is designed to address some of these challenges for a conceptual Lift Plus Cruise vehicle designed by NASA’s Revolutionary Vertical Lift Technology (RVLT) project. The command and control architecture for this concept is presented along with preliminary findings. Initial results explore the vehicle performance in an approach to hover transition scenario, designed to explore the challenge of dissipating energy across all flight regimes. Operational concepts with varying aggressiveness are evaluated through changing glideslope and deceleration rates. Preliminary results show that the simplified control concept is effective over these operational conditions, with control strategies and envelope protection limits able to maintain control though aggressive operations despite saturation at steeper slopes with higher deceleration rates. Final results will show piloted simulation evaluations in the the Aerospace Cognitive Engineering Lab – Rapid Automation Test Environment (ACEL-RATE) laboratory at NASA Ames Research Center. The planned tests will build on these operations with additional test cases exploring variations in wind conditions as well as transition-to-hover automation strategies and display information.

simplified vehicle control↗
NASA NTRS2024

Scalability in SLA lattice through lattice orientation and hybrid frame and plate architectures

Lightweighting has been a key goal for engineers and designers, with lattice structures widely explored as the building blocks for structural components. Cellular structure-inspired lattice truss frame designs made of struts, have been extensively studied. All plate-based lattice designs have superior mechanical performance. Limits in scalability occur from formation of closed pockets limiting uv curing in processes like stereolithography (SLA). We examine hybrid frame and plate body-centered cubic-simply cubic (BCC-SC) lattices under compression. Unit cells and scaled up lattice exhibit an increase in yield stress and modulus with the addition of plates. The loading direction on the hybrid frame and plate unit cells affected the magnitude of improvement. Simulations and measurements indicated that the optimal lightweight lattice was determined to be when two plates were placed opposite each other with plates buttressing the struts, inhibiting buckling of the struts aligned with the loading direction. This lattice resulted in 63% improvement in specific modulus, a 137% improvement in specific yield point, and a 360% improvement in specific energy absorption (SEA) and the scaled up 4 × 4 × 4 scaled-up structures, showed a 107%, 148%, and 297% in specific modulus, specific yield point, and SEA, respectively A combined stretching-bending behavior was identified in optimal orientations reflecting the delayed buckling mechanism paired to a rising stress-strain curve past the elastic yield indicating bending resistance. The mass moment of inertia was found to be a key parameter correlating optimum orientation for the same number of plates added to the BCC-SC frame.

Mahan Ghosh↗
DOE OSTI2025

Macro-micro multiscale modeling to assist the design of HPDC Al castings microstructure and alloys for EV super-large body structures (Phase 1)

Implementation of High Pressure Die Casting (HPDC) Aluminum (Al) body structures for high volume electrified vehicles (EV) to improve electric efficiency remains a key strategy within many original equipment manufacturer (OEM)s. In addition to high strength for safety requirements, superior Self-Piercing Riveting (SPR) performance is demanded for HPDC Al alloys to be compatible with high volume SPR joining. In this work, it is proposed to extend and validate an existing Contractor finite element multiscale macro-micro modeling approach to quantify the influence of the microstructure of HPDC alloys on the fracture strain/displacement under 3-point bend and clinch testing. The success of this work will allow to replace solution treatment stage with low energy consumption heat treatment (HT) processes, or to design new non heat treatable (NHT) HPDC Al alloys to eliminate HT requirements. Ultimately, this project will facilitate the application of HPDC Al alloys for super-large vehicle structures to significantly reduce vehicle weight, and thus improving energy efficiency. The purpose of this project is to extend and validate an existing finite element code, which is based on the Contractor developed macro-micro multi-scale modeling approach, to numerically simulate the three-point bending and clinch test and study the influences of material microstructural characteristics and phase properties on the rivetability. The macro-micro modeling approach begins with a sample scale model and identify the location, which is mostly prone to failure, the deformation history of the boundaries of that location calculated will be used to drive a microstructure-based sub-models where the material microstructure and microscale properties are considered. Using this approach, the wrap-bending failure for two Al alloys are correctly predicted for the first time. This will start with phase I effort of building a framework of macro-micro three point bending test and clinch test of Al10SiMgMn HPDC alloy in the as-cast and T7 heat treated conditions. Those results will then be validated with experimental test results. The phase II effort will involve the utilization of the knowledge learned in phase I to establish the quantitative correlation between the microstructure characteristics and the riveting performance, which will be further used to guide the optimization of HPDC Al alloy microstructure using heat treatment process to achieve sufficient rivetability to join large thin-wall HPDC alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Optimisation of the Kaplan hydropower system via PID 2 and digital twin

Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.

Hydropower system↗
DOE OSTI2024

Nanoindentation Stress Relaxation to Quantify Dislocation Velocity–Stress Exponent

This work reports a new methodology using indentation stress relaxation to characterize the dislocation velocity–stress exponent. Through the indentation stress relaxation process, the dislocation structure builds up at the rate governed by dislocation velocity, which is a function of the externally applied stress. The relationship between the dislocation velocity and stress can thus be derived from the indentation stress relaxation data of the stress as a function of time. In this study, instrumented nanoindentation stress relaxation experiments were performed on pure aluminum samples, following three different initial displacement rates of 100, 400, and 800 nm/s. Based on the scaling properties of dislocation kinetics, the data were interpreted to derive a dislocation velocity–stress exponent of 2.5 ± 0.5 for room-temperature aluminum. Crystal plasticity finite-element simulations were performed to illustrate the sensitivity of the proposed nanoindentation stress relaxation methodology to the dislocation velocity–stress exponent value.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Implementation of Chemistry in the Athena++ Code

Chemistry plays a key role in many aspects of astrophysical fluids. Atoms and molecules are agents for heating and cooling, determine the ionization fraction, serve as observational tracers, and build the molecular foundation of life. We present the implementation of a chemistry module in the publicly available magnetohydrodynamic code Athena++ . We implement several chemical networks and heating and cooling processes suitable for simulating the interstellar medium (ISM). A general chemical network framework in the KIDA format is also included, allowing users to easily implement their own chemistry. Radiation transfer and cosmic-ray ionization are coupled with chemistry and solved with the simple six-ray approximation. The chemical and thermal processes are evolved as a system of coupled ordinary differential equations with an implicit solver from the CVODE library. We perform and present a series of tests to ensure the numerical accuracy and convergence of the code. Many tests combine chemistry with gas dynamics, including comparisons with analytic solutions, 1D problems of the photodissociation regions and shocks, and realistic 3D simulations of the turbulent ISM. We release the code with the new public version of Athena++ , aiming to provide a robust and flexible code for the astrochemical simulation community.

79 ASTRONOMY AND ASTROPHYSICS↗