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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Structural studies of the IFNλ4 receptor complex using cryoEM enabled by protein engineering

Abstract IFNλ4 has posed a conundrum in human immunology since its discovery in 2013, with its expression linked to complications with viral clearance. While genetic and cellular studies revealed the detrimental effects of IFNλ4 expression, extensive structural and functional characterization has been limited by the inability to express and purify the protein, complicating explanations of its paradoxical behavior. In this work, we report a method for robust production of IFNλ4. We then use yeast surface display to affinity-mature IL10Rβ and solve the 72 kilodalton structures of IFNλ4 (3.26 Å) and IFNλ3 (3.00 Å) in complex with their receptors IFNλR1 and IL10Rβ using cryogenic electron microscopy. Comparison of the structures highlights differences in receptor engagement and reveals a distinct 12-degree rotation in overall receptor geometry, providing a potential mechanistic explanation for differences in cell signaling, downstream gene induction, and antiviral activities. Further, we perform a structural analysis using molecular modeling and simulation to identify a unique region of IFNλ4 that, when replaced, enables secretion of the protein from cells. These findings provide a structural and functional understanding of the IFNλ4 protein and enable future comprehensive studies towards correcting IFNλ4 dysfunction in large populations of affected patients.

Science & Technology - Other Topics↗
DOE OSTI2021

Big Data Analysis of Massive PMU Datasets: A Data Platform Perspective

The discovery of `event signatures' and useful insights from very large historical Phasor Measurement Unit (PMU) datasets is predicated on offline Big Data analysis approaches that rely on the generation of predictive features on a massive scale. This paper presents lessons learned from a data platform perspective towards reducing barriers to adoption of Big Data analytics against a real dataset of almost half a trillion data points drawn from over 400 PMUs distributed across the North American power grid. We demonstrate software abstractions and targeted performance optimizations that can lead to significant productivity gains for power systems researchers seeking to perform offline exploratory temporal analysis and modeling tasks, with a focus on feature generation. We describe how our optimized approach goes beyond a naive application of mainstream Big Data technologies, enabling feature generation tasks, that previously took days or even weeks, to now be completed in just a few hours.

Kumar, Vijay S.↗
DOE OSTI2024

Impedance-Aware Graph Convolutional Networks for Voltage Estimation in Active Distribution Networks

Voltage estimation plays a key role in ensuring the effective control and reliability of distribution networks. However, traditional machine learning methods often fail to capture the details of the distribution network’s topology. To overcome this challenge, graph convolutional networks (GCN) have emerged as an alternative. Graph convolutional networks inherently capture the topology of the grid, utilizing correlations to achieve precise voltage estimation. Other machine learning models and conventional GCNs fail to account for the distribution line characteristics found in the real world, limiting their effectiveness. This paper proposes an advanced variant of GCN called the Impedance-Aware Graph Convolutional Network (IA-GCN). The IA-GCN layer incorporates the magnitude of the impedance into the graph convolution mechanism, allowing it to capture topological nuances and provide valuable insights into node interrelationships by considering impedance as an intrinsic dimension. The performance of the IA-GCN layer is then compared with that of GCN and GraphSAGE layers through a surrogate model for voltage estimation. The performance analysis demonstrates that IA-GCN outperforms GCN by reducing the MAE by 87.55% and improving the R-squared value by 98%.

Ravi, Abhijith↗
DOE OSTI2020

As-Run Neutronics Evaluation for the CSM-10584 Experiment in the ATR

This engineering calculations and analysis report (ECAR) documents the results of the Advanced Test Reactor (ATR) detailed Monte Carlo N-Particle (MCNP) code full-core model as-run physics analysis performed to support the Colorado School of Mines (CSM) experiment in the B-5 position.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Simulating Atmospheric Boundary Layer Turbulence with Nek5000/RS

We present large-eddy-simulation (LES) modeling approaches for the simulation of atmospheric boundary layer turbulence that are of direct relevance to wind energy production. In this report, we study a GABLS benchmark problem using high-order spectral element code Nek5000/RS, which is supported under the DOE’s Exascale Computing Project (ECP) Center for Efficient Exascale Discretizations (CEED) project, targeting application simulations on various acceleration-device based exascale computing platforms [1, 2]. We demonstrate our newly developed subgrid-scale (SGS) models based on high-pass filter (HPF), mean-field eddy viscosity (MFEV), and Smagorinsky (SMG) with no-slip and traction boundary conditions, provided with low-order statistics, convergence and turbulent structure analysis. The model fidelity and scaling performance of Nek5000/RS on DOE’s leadership computing platforms in comparison to those of AMR-Wind, a block-structured second-order finite-volume code with adaptive-mesh-refinement capabilities, are discussed in [3].

17 WIND ENERGY↗
DOE OSTI2023

Advanced Research Directions on AI for Science, Energy, and Security: Report on Summer 2022 Workshops

Over the past decade, fundamental changes in artificial intelligence (AI)—from foundational to applied—have delivered dramatic insights across a wide breadth of U.S. Department of Energy (DOE) mission space. AI is helping to augment and improve scientific and engineering workflows (e.g., for control, design, and dramatic performance gains through surrogate models) in national security, the Office of Science, and DOE’s applied energy programs. The progress and potential for AI in DOE science was captured in the 2020 “AI for Science” report from the DOE laboratory community in collaboration with academia and industry. Specific scientific areas ready to further leverage the power of AI ranged from the scale and performance of computational models to data analysis to creating new classes of observations using computer vision. Since that report, the scale and scope of scientific AI have accelerated, revealing new, emergent properties that yield insights that go beyond enabling opportunities to being potentially transformative in the way that scientific problems are posed and solved. Thus, under the guidance of both the Office of Science (SC) and the National Nuclear Security Administration (NNSA), the DOE national laboratories organized a series of workshops in 2022 to gather input on new and rapidly emerging opportunities and challenges of scientific AI. This 2023 report is a synthesis of those workshops. The scientific community believes AI can have a foundational impact on a broad range of DOE missions, including science, energy, and national security. Further, DOE has unique capabilities that enable the community to drive progress in scientific use of AI, building on long-standing DOE strengths and investments in computation, data, and communications infrastructure, spanning the Energy Sciences Network (ESnet), the Exascale Computing Project (ECP), and integrative programs such as the NNSA Office of Defense Programs Advanced Simulation and Computing (ASC) and the SC Scientific Discovery through Advanced Computing (SciDAC) programs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Motor with Advanced Concepts for High power density and INtegrated cooling for Efficiency (MACHINE)

Raytheon Technologies Research Center (RTRC) is the central research and development (R&D) organization for RTX, and has extensive expertise in the design, modeling and analysis of high-performance electrical machines and thermal management for all its business units. The proposing team consists of researchers from RTRC and John Deere (JD), will be referred as “Team”. Each organization a has long track record of successful R&D of materials, manufacturing, components, and systems for energy efficiency applications. Motor power density and efficiency are limited by fundamental physical trade-offs between electromagnetics, thermal management, and structural design considerations. The team is proposing to utilize novel technologies and multi-physics design methods to develop a Motor with Advanced Concepts for High power density and INtegrated cooling for Efficiency (MACHINE), demonstrating an 8X improvement in power density.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Commercialization of a Non-Intrusive Optical (NIO) Technology to Measure Heliostat Optical Errors in Utility-Scale Concentrating Solar Power Plants: Final TCF Report

The drone-based Non-Intrusive Optical (NIO) Technology has been developed at NREL to allow for efficient and automated optical characterization of heliostats in Concentrating Solar Power (CSP) plants. For this project, the technology will be developed into a commercial tool package, including software and user-interface (UI), operations manual, and training and support services. The project team will partner with Tietronix to perform market assessment and stakeholder engagement, develop the tool package and business model, and perform data collection and analysis to demonstrate and refine the capabilities for use at a commercial plant. The team will collaborate with a commercial plant to conduct the data collection operations and provide optical error deliverables. The goal of the project is to advance the commercialization of the technology to a stage where a beta version can be demonstrated at additional commercial plants and developed into a licensable product.

14 SOLAR ENERGY↗
DOE OSTI2026

MONet/1000 Soils metagenome pathway modelling narrative w/ auto batch import

This narrative performs metabolic modeling and flux balance analysis (FBA) using metagenome-assembled genomes (MAGs) from the 1000 Soils samples, as described by Song et al. (2026, accepted). The set of MAGs (in FASTA format) is converted into a set of assembly objects compatible with functional annotation via RASTtk, yielding a set of genome objects that undergo metabolic modeling via OMEGGA. These genome objects are then used to conduct FBA, generating tables of metabolite uptake rates across the MAGs under investigation.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1972

Technical, analytical and computer support

The development of a rigorous mathematical model for the design and performance analysis of cylindrical silicon-germanium thermoelectric generators is reported that consists of two parts, a steady-state (static) and a transient (dynamic) part. The material study task involves the definition and implementation of a material study that aims to experimentally characterize the long term behavior of the thermoelectric properties of silicon-germanium alloys as a function of temperature. Analytical and experimental efforts are aimed at the determination of the sublimation characteristics of silicon germanium alloys and the study of sublimation effects on RTG performance. Studies are also performed on a variety of specific topics on thermoelectric energy conversion.

Source record↗
NASA NTRS1973

Transient analysis using conical shell elements

The use of the NASTRAN conical shell element in static, eigenvalue, and direct transient analyses is demonstrated. The results of a NASTRAN static solution of an externally pressurized ring-stiffened cylinder agree well with a theoretical discontinuity analysis. Good agreement is also obtained between the NASTRAN direct transient response of a uniform cylinder to a dynamic end load and one-dimensional solutions obtained using a method of characteristics stress wave code and a standing wave solution. Finally, a NASTRAN eigenvalue analysis is performed on a hydroballistic model idealized with conical shell elements.

Yang, J. C. S.↗
NASA NTRS1976

Orbit Modelling for Satellites Using the NASA Prediction Bulletins

For some satellites the NASA Prediction Bulletins are the only means available to the general user for obtaining orbital information. A computational interface between the information given in the NASA Prediction Bulletins and standard orbit determination programs is provided. Such an interface is necessary to obtain accurate orbit predictions. The theoretical considerations and their computational verification in this interface modelling are presented. This analysis was performed in conjunction with satellite aided search and rescue position location experiments where accurate orbits of the Amateur Satellite Corporation (AMSAT) OSCAR-6 and OSCAR-7 spacecraft are a prerequisite.

Bonavito, N. L.↗
NASA NTRS1977

Simplified and refined structural modeling for economical flutter analysis and design

A coordinated use of two finite-element models of different levels of refinement is presented to reduce the computer cost of the repetitive flutter analysis commonly encountered in structural resizing to meet flutter requirements. One model, termed a refined model (RM), represents a high degree of detail needed for strength-sizing and flutter analysis of an airframe. The other model, called a simplified model (SM), has a relatively much smaller number of elements and degrees-of-freedom. A systematic method of deriving an SM from a given RM is described. The method consists of judgmental and numerical operations to make the stiffness and mass of the SM elements equivalent to the corresponding substructures of RM. The structural data are automatically transferred between the two models. The bulk of analysis is performed on the SM with periodical verifications carried out by analysis of the RM. In a numerical example of a supersonic cruise aircraft with an arrow wing, this approach permitted substantial savings in computer costs and acceleration of the job turn-around.

Ricketts, R. H.↗
NASA NTRS1981

Control system development for an organic Ranking cycle engine

An organic Rankine cycle engine is used as part of a solar thermal power conversion assembly (PCA). The PCA, including a direct-heated cavity receiver and a shaft-mounted alternator, is mounted at the focal point of a parabolic dish concentrator. The engine controls are required to maintain approximately constant values of turbine inlet temperature and shaft speed, despite variation in the concentrated solar power input to the receiver. The controls design approach, system models, and initial stability and performance analysis results are presented herein.

Bergthold, F. M., Jr.↗
NASA NTRS1986

Development of a prototype automated on-orbit contact heat exchanger

An automated contact heat exchanger is being developed for use aboard the manned Space Station, serving as an interface heat exchanger between the pressurized module internal thermal buses and the central external thermal bus. The concept makes use of an array of flattened, thin-walled, flexible tubes that expand or contract to make or break the thermal connection as the internal pressure changes. Because of its simplicity, it permits on-orbit assembly by the remote manipulator system, thus eliminating the need for expensive EVA to make connections. A design methodology based on stress and thermal analyses has been developed and used to perform trade-offs between performance and cost, and to optimize design parameters. Simple verification tests have been performed to confirm the stress analysis model. Two conceptual variants of the contact heat exchanger are described, each designed for a 25 kW total heat load and a minimum uniform heat flux of 2.15 W/sq cm.

Lee, C. Y.↗
NASA NTRS1986

Flight test report of the NASA icing research airplane: Performance, stability, and control after flight through natural icing conditions

Flight test results are presented documenting the effect of airframe icing on performance and stability and control of a NASA DHC-6 icing research aircraft. Kohlman System Research, Inc., provided the data acquisition system and data analysis under contract to NASA. Performance modeling methods and MMLE techniques were used to determine the effects of natural ice on the aircraft. Results showed that ice had a significant effect on the drag coefficient of the aircraft and a modest effect on the MMLE derived longitudinal stability coefficients (code version MMLE). Data is also presented on asymmetric power sign slip maneuvers showing rudder floating characteristics with and without ice on the vertical stabilizer.

Jordan, J. L.↗
NASA NTRS1989

DYSCO: A software system for modeling general dynamic systems

The DYSCO program has been under development since 1979. It has been funded by Army and Air Force laboratories and by the Kaman Aerospace Corporation. It is presently available at a number of government and nongovernment installations. It has been used to analyze a very broad range of dynamics problems. A principle feature of the software design of DYSCO is the separation of the executive from the technology. The executive, which controls all the operations, is intelligent in the sense that it knows that its function is to assemble differential equations and to prepare them for solution. The technology library contains FORTRAN routines which perform standard functions, such as, computing the equation coefficients of an element (or component) given the local state at any time. The technology library also contains algorithms and procedures for solving the coupled system equations. The system was designed to allow easy additional of technology to the library. Any linear or nonlinear structural entity, control system, or set of ordinary differential equations may be simply coded and added to the library, as well as algorithms for time or frequency domain solution. The program is described with emphasis on its usefulness in easily modeling unusual concepts and configurations, performing analysis of damage, evaluating new algorithms, and simulating dynamic tests.

Berman, Alex↗
NASA NTRS1991

Thermal design of the Cosmic Background Explorer cryogenic optical assembly

The Cosmic Background Explorer (COBE) is a satellite which is designed to study the 3-K cosmic background radiation. Two cryogenic instruments and a common support structure comprise the Cryogenic Optical Assembly (COA). In order to make definitive measurements of the low-energy FIR radiation, the temperature of the COA must be maintained below 3 K. Temperature control of the COA elements is achieved by the use of a superfluid helium dewar. The thermal design also minimizes power dissipation, transient operational effects, and thermal gradients within the COA. This is accomplished by isolating selected components and heat-sinking others to various locations on the cryogen tank. The thermal design was developed primarily through analysis. Analytical models were created to perform parametric design studies. Ground testing was performed to correlate the thermal models and validate the thermal design. Both test and flight data confirmed that all design requirements were either met or exceeded.

Mosier, Carol L.↗