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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Simulation and Analysis of Technology and Operational Procedures to Reduce the Combined Effects of Emissions and Contrails

The development and evaluation of concepts and technology to support future air traffic management systems require a hierarchy of models ranging from real-time simulations to extensive field evaluations. Air traffic simulation models such as Airspace Concept Evaluation System, Center Tracon Automation System, Future Air traffic management Concept Evaluation Tool and others are used to design air traffic systems balancing the conflicting objectives of maximizing safety, meeting future demands for airports and airspace and increase efficiency of traffic flows in the presence of uncertain weather. The impact of aviation emissions and contrails on climate imposes another constraint on the design of aircraft and aviation operations. The understanding of the complex interaction between physical climate system, the carbon and other greenhouse gas emissions and aviation activity can be improved by the development of integrated assessment models that include emission and climate models together with air traffic simulations. The modeling of aircraft emissions and their interaction with each other to change the concentration levels of different gasses in the atmosphere and the resulting impact of the radiative forcing on the equilibrium of the Earth's atmosphere is complex and requires the use of coupled atmosphere-ocean general circulation models together with three-dimensional models of carbon cycle and chemistry of other non-CO2 greenhouse gases. These models are computationally intensive and unsuitable for studies involving the generation of multiple scenarios. Simple emission and climate models, based on the input-output relations of linear systems, capture the fundamental emission to climate impact behavior by careful selection of key variables and their dynamics. The impact of various greenhouse gases depends on the total concentration, effect per unit change in atmospheric concentration and the spatial distribution of the gas. All these quantities are influenced by the lifetime of the gas. The impact of a greenhouse gas depends on the interval of assessment, which may vary from a few decades to a few centuries. Climate metrics are aimed at providing a common scale to compare different greenhouse gases. If the metrics are to be used as a tool in developing and evaluating aviation operations, they should be transparent and easy to apply. Global Warming Potential and Aggregate Global Temperature Potential are some of the commonly used metrics. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability brings together metrics, which are useful in aviation operations together with metrics used in climate studies. The capability can be used to make trade-offs between extra fuel cost and reduction in climate impact. There is considerable uncertainty in our understanding of the radiative forcing associated with emissions and contrails. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails. It can also be used to evaluate the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA's Aviation Environmental Portfolio Management Tool for Impacts.

impact of aviation on the environment↗
DOE OSTI2021

Radiation Transport Simulation of the Sulfur Counting System in the Radiation Metrology Laboratory (RML)

At the request of staff members from the Radiation Metrology Laboratory (RML), a series of Monte Carlo radiation transport calculations were performed using two different models of the detector geometry of the RMLs sulfur counting system. The fraction of electrons from each β-decay of 32 P in the sulfur pellet that enter the window of the sulfur counting system was calculated with both MCNP and ITS. In addition, the differential energy distributions of the electrons entering the counting system window were computed. There was significant agreement between the integral and differential quantities calculated by the two transport codes. Summary tables are for the integral efficiency values are found in the body of the report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1989

Application of optical distributed sensing and computation to control of a large flexible spacecraft

Advances in real-time holography make possible the development of new distributed optical sensors and processors that may have application to the control of flexible structures. This paper presents the analytic evaluation of control system concepts utilizing this new technology on realistic spacecraft. The design of a distributed estimator based on this new optical sensing technique is targeted to vibration control of a complex spacecraft with multiple optical sensors, each of which views a portion of the spacecraft. A simulation of a complex truss structure that was flown in the Solar Array Flight Experiment is utilized to evaluate the performance of the estimator. It is shown that good performance can be obtained from a distributed estimator even in the presence of significant sensor noise.

Montgomery, R. C.↗
NASA NTRS1992

Memory Network For Distributed Data Processors

Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

Bolen, David↗
NASA NTRS1996

Site Partitioning for Redundant Arrays of Distributed Disks

Redundant arrays of distributed disks (RADD) can be used in a distributed computing system or database system to provide recovery in the presence of disk crashes and temporary and permanent failures of single sites. In this paper, we look at the problem of partitioning the sites of a distributed storage system into redundant arrays in such a way that the communication costs for maintaining the parity information are minimized. We show that the partitioning problem is NP-hard. We then propose and evaluate several heuristic algorithms for finding approximate solutions. Simulation results show that significant reduction in remote parity update costs can be achieved by optimizing the site partitioning scheme.

Mourad, Antoine N.↗
DOE OSTI2020

Local Phasor-Based Control of DER Inverters for Voltage Regulation on Distribution Feeders

We introduce a new control paradigm termed Phasor-Based Control (PBC) to coordinate Distributed Energy Resources (DER) for improved voltage regulation and other objectives. PBC is a multi-layer control framework where the state of the distribution grid is represented by voltage phasors, and Phasor Measurement Units (PMUs) measure the state at critical points in the distribution grid. In the PBC paradigm, a supervisory controller (S-PBC) sets phasor targets which local controllers track. In this paper, we propose a Proportional Integral (PI) implementation for the local control layer (LPBC), to regulate real and reactive power output of distributed inverters to track a voltage phasor target computed by the supervisory layer. We tune the PI controller gains offline with a genetic algorithm that yields better performance than the Ziegler-Nichols method. We benchmark the proposed L-PBC controller against droop volt-var control (DVVC) and observe improved voltage regulation in simulation on the IEEE 13 node unbalanced test feeder (IEEE 13NF). Furthermore, by means of numerical simulation we observe the response of the L-PBC controllers to small and large grid disturbances. Simulations on larger feeders, IEEE 123-node and 647-node, demonstrate challenges with tuning controllers in setups with different amounts of power-voltage coupling.

42 ENGINEERING↗
DOE OSTI2026

A Framework for Parametric and Predictive Uncertainty Quantification in the E3SM Land Model: Assessing Site and Observable Generalizability

Quantifying parametric uncertainty using observations from individual sites provides a critical foundation for Earth system modeling, serving as a necessary first step before scaling up to regional or global applications. This study introduces a novel computational framework designed to enhance model predictability by reducing parametric uncertainty and assessing site and observable generalizability using various observational constraints. The framework integrates five components: Model Simulation, Statistical Emulation, Global Sensitivity Analysis (GSA), Model Calibration, and Model Prediction. Using the E3SM land model, we simulated site-level land-atmosphere carbon and energy fluxes from 2003 to 2007 across five evergreen needleleaf FLUXNET sites, perturbing 26 vegetation-related model parameters. Gaussian process emulators were employed to expedite GSA and model calibration. Four critical parameters that strongly influence selected land-atmosphere fluxes were identified by GSA. Bayesian approaches were used to infer parameter probability distributions leveraging synthetic data and FLUXNET observations. The results reveal that posterior parameter distributions vary significantly across different sites and observables within the same plant functional type. Probabilistic predictions indicate that parameters calibrated at one site can enhance predictive accuracy at other sites, although site heterogeneity may sometimes outweigh parametric uncertainty. Additionally, the probabilistic predictions demonstrate that calibration for one variable can also improve predictability for other variables, thereby maximizing predictive capabilities with limited observations. This framework provides a powerful approach for reducing parametric uncertainty in Earth system models and deepening our understanding of carbon dynamics and energy cycles. Its adaptability makes it a valuable tool for broader applications in Earth system modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Computational Experiment Design for Operations Model Simulation

Computer simulations that demonstrate the value of novel approaches are crucial to developing more flexible and robust power systems operations with high penetrations of renewable energy at multiple geographic and temporal scales. However, optimization-based simulations that depend on forecast data often face challenges in evaluating performance, reproducing results, and testing under realistic simulation scenarios. In this paper, we develop scientific computing best-practices for the validation and reproduction of power systems operational models. We then employ two case studies to demonstrate the proposed validation and reproduction framework.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗
DOE OSTI2025

Tropical Cyclone Super Resolution using conditional diffusion denoising probabilistic model from mesoscale simulation to LES

Accurate modeling of tropical cyclone wind fields is essential for the design, risk assessment, and operational planning of offshore energy infrastructure. While mesoscale simulations are widely used thanks to their computational efficiency, they lack the necessary resolution to capture key features such as wind shear and veer profiles as well as the distribution turbulent kinetic energy (TKE). High-fidelity large-eddy simulation (LES) models on the other hand, can resolve turbulent structures and provide a more accurate representation of the complex wind field, albeit at a higher computational cost. To address this modeling gap, we introduce a two-part generative framework to enhance the resolution and physics-capturing ability of mesoscale simulations. First, a reduced-order model based on Karhunen–Loève (KL) decomposition is used to extract dominant spatial modes from one-dimensional mean wind profiles. A multilayer perceptron (MLP) is trained to map mesoscale mode weights to their LES counterparts, enabling accurate reconstruction of vertical velocity profiles. Second, a conditional Diffusion Denoising Probabilistic Model (DDPM) is developed to super-resolve coarse and low-fidelity mesoscale velocity fields, recovering fine-scale turbulence structures and stress distributions. The framework is evaluated across different tropical cyclone intensity categories defined by the Saffir–Simpson scale and demonstrates strong performance in both interpolation and extrapolation tasks. The generated fields accurately reproduce spatial coherence, stress distributions, and spectral energy characteristics observed in LES data. By bridging the fidelity gap between mesoscale and LES outputs, this approach offers a scalable, data-driven solution for enhancing the representation of tropical cyclone wind fields, enabling more robust offshore energy infrastructure systems design in tropical-cyclone-prone areas.

17 WIND ENERGY↗
DOE OSTI2019

Spatial dependence of the growth of polycyclic aromatic compounds in an ethylene counterflow flame

The complex environments that characterize combustion systems can influence the distribution of gas-phase species, the relative importance of various growth mechanisms and the chemical and physical characteristics of the soot precursors generated. In order to provide molecular insights on the effect of combustion environments on the formation of gas-phase species, in this paper, we study the temporal and spatial dependence of soot precursors growth mechanisms in an ethylene/oxygen/argon counterflow diffusion flame. As computational tools of investigation, we included fluid dynamics simulations and stochastic discrete modeling. Results show the relative importance of various reaction pathways in flame, with the hydrogen-abstraction-acetylene-addition mechanism contributing to the formation of pure hydrocarbons near the stagnation plane, and oxygen chemistry prevailing near the maximum temperature region, where the concentration of atomic oxygen reaches its peak and phenols, ethers and furan-embedded species are formed. The computational results show excellent agreement with measurements obtained using aerosol mass spectrometry coupled with vacuum-ultraviolet photoionization. Knowledge acquired in this study can be used to predict the type of compounds formed in various locations of the flame and eventually provide insights on the environmental parameters that influence the growth of soot precursors. In addition, the results reported in this paper highlight the importance of modeling counterflow flames in two or three dimensions to capture the spatial dependence of growth mechanisms of soot precursors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1985

NAS - Supercomputing master tool for aeronautics

Features, performance objectives and applications planned for the NASA National Aerodynamics Simulator (NAS) are outlined. NAS was conceived in the 1970s as a means to performing numerical aerodynamic simulations beyond the scope of wind tunnel testing for high-speed flight. Present supercomputers cannot deal with problems exhibiting strongly coupled viscous effects, which are being increasingly more accurately represented by approximations to the full Navier-Stokes equations. Located at the NASA-Ames Center, the NAS will by 1990 comprise a distributed computer network capable of a 4 Gflop computing rate and have a memory capacity of 1 billion 64-bit words. Remote access to the system through UNIX-based microcomputers will be available through land lines and satellite links. New supercomputers will be tested on the system without disturbing ongoing work. The core machine will be a Cray-2 with a 2 Gflop rate.

Bailey, F. R.↗
NASA NTRS2013

Flow Simulation of N3-X Hybrid Wing-Body Configuration

System studies show that a N3-X hybrid wing-body aircraft with a turboelectric distributed propulsion system using a mail-slot inlet/nozzle nacelle can meet the environmental and performance goals for N+3 generation transports (three generations beyond the current air transport technology level) set by NASA s Subsonic Fixed Wing Project. In this study, a Navier-Stokes flow simulation of N3-X on hybrid unstructured meshes was conducted, including the mail-slot propulsor. The geometry of the mail-slot propulsor was generated by a CAD (Computer-Aided Design)-free shape parameterization. A body force approach was used for a more realistic and efficient simulation of the turning and loss effects of the fan blades and the inlet-fan interactions. Flow simulation results of the N3-X demonstrates the validity of the present approach.

Kim, Hyoungjin↗
NASA NTRS2013

Optimal Shape Design of Mail-Slot Nacelle on N3-X Hybrid Wing-Body Configuration

System studies show that a N3-X hybrid wing-body aircraft with a turboelectric distributed propulsion system using a mail-slot inlet/nozzle nacelle can meet the environmental and performance goals for N+3 generation transports (three generations beyond the current air transport technology level) set by NASA's Subsonic Fixed Wing Project. In this study, a Navier-Stokes flow simulation of N3-X on hybrid unstructured meshes was conducted, including the mail-slot propulsor. The geometry of the mail-slot propulsor was generated by a CAD (Computer-Aided Design)-free shape parameterization. A novel body force model generation approach was suggested for a more realistic and efficient simulation of the flow turning, pressure rise and loss effects of the fan blades and the inlet-fan interactions. Flow simulation results of the N3-X demonstrates the validity of the present approach. An optimal Shape design of the mail-slot nacelle surface was conducted to reduce strength of shock waves and flow separations on the cowl surface.

Kim, Hyoungjin↗
DOE OSTI2024

Real-time hybrid controls of energy storage and load shedding for integrated power and energy systems of ships

This paper presents an original energy management methodology to enhance the resilience of ship power systems. The integration of various energy storage systems (ESS), including battery energy storage systems (BESS) and super-capacitor energy storage systems (SCESS), in modern ship power systems poses challenges in designing an efficient energy management system (EMS). The EMS proposed in this paper aims to achieve multiple objectives. The primary objective is to minimize shed loads, while the secondary objective is to effectively manage different types of ESS. Considering the diverse ramp-rate characteristics of generators, SCESS, and BESS, the proposed EMS exploits these differences to determine an optimal long-term schedule for minimizing shed loads. Furthermore, the proposed EMS balances the state-of-charge (SoC) of ESS and prioritizes the SCESS’s SoC levels to ensure the efficient operation of BESS and SCESS. For better computational efficiency, we introduce the receding horizon optimization method, enabling real-time EMS implementation. Further, a comparison with the fixed horizon optimization (FHO) validates its effectiveness. Simulation studies and results demonstrate that the proposed EMS efficiently manages generators, BESS, and SCESS, ensuring system resilience under generation shortages. Additionally, the proposed methodology significantly reduces the computational burden compared to the FHO technique while maintaining acceptable resilience performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗
NASA NTRS1973

Space shuttle solid rocket booster recovery system definition. Volume 2: SRB water impact Monte Carlo computer program, user's manual

The HD 220 program was created as part of the space shuttle solid rocket booster recovery system definition. The model was generated to investigate the damage to SRB components under water impact loads. The random nature of environmental parameters, such as ocean waves and wind conditions, necessitates estimation of the relative frequency of occurrence for these parameters. The nondeterministic nature of component strengths also lends itself to probabilistic simulation. The Monte Carlo technique allows the simultaneous perturbation of multiple independent parameters and provides outputs describing the probability distribution functions of the dependent parameters. This allows the user to determine the required statistics for each output parameter.

Source record↗
NASA NTRS2002

Simulation of Etching in Chlorine Discharges Using an Integrated Feature Evolution-Plasma Model

To better utilize its vast collection of heterogeneous resources that are geographically distributed across the United States, NASA is constructing a computational grid called the Information Power Grid (IPG). This paper describes various tools and techniques that we are developing to measure and improve the performance of a broad class of NASA applications when run on the IPG. In particular, we are investigating the areas of grid benchmarking, grid monitoring, user-level application scheduling, and decentralized system-level scheduling.

Hwang, Helen H.↗