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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

A Magnetic Solid-State Storage Technology: Vertical Bloch Line Storage

No storage technology is known to exist today which simultaneously offers high-storage density, nonvolatility, and a solid-state form factor. For example, common random access memories are solid-state, but are volatile and typically offer modest density. Alternatively, mainstream magnetic disk and magnetic tape systems offer high storage density and nonvolatility, but are fundamentally not solid-state. A number of applications exist which would be suited well with high performance solid- state technology. NASA, for example, is beginning baseline solid-state recorders for upcoming space missions, such as the Cassini mission to Saturn.

Katti, R. R.↗
NASA NTRS2015

Fast Response, Open-Celled Porous, Shape Memory Effect Actuators with Integrated Attachments

This invention relates to the exploitation of porous foam articles exhibiting the Shape Memory Effect as actuators. Each foam article is composed of a plurality of geometric shapes, such that some geometric shapes can fit snugly into or around rigid mating connectors that attach the Shape Memory foam article intimately into the load path between a static structure and a moveable structure. The foam is open-celled, composed of a plurality of interconnected struts whose mean diameter can vary from approximately 50 to 500 microns. Gases and fluids flowing through the foam transfer heat rapidly with the struts, providing rapid Shape Memory Effect transformations. Embodiments of porous foam articles as torsional actuators and approximately planar structures are disposed. Simple, integral connection systems exploiting the ability to supply large loads to a structure, and that can also supply hot and cold gases and fluids to effect rapid actuation are also disposed.

Jardine, Andrew Peter↗
NASA NTRS2016

An Inviscid Decoupled Method for the Roe FDS Scheme in the Reacting Gas Path of FUN3D

An approach is described to decouple the species continuity equations from the mixture continuity, momentum, and total energy equations for the Roe flux difference splitting scheme. This decoupling simplifies the implicit system, so that the flow solver can be made significantly more efficient, with very little penalty on overall scheme robustness. Most importantly, the computational cost of the point implicit relaxation is shown to scale linearly with the number of species for the decoupled system, whereas the fully coupled approach scales quadratically. Also, the decoupled method significantly reduces the cost in wall time and memory in comparison to the fully coupled approach. This work lays the foundation for development of an efficient adjoint solution procedure for high speed reacting flow.

Thompson, Kyle B.↗
NASA NTRS2017

Shape Morphing Adaptive Radiator Technology (SMART) Updates to Techport Entry

The Shape-Morphing Adaptive Radiator Technology (SMART) project builds off the FY16 research effort that developed a flexible composite radiator panel and demonstrated its ability to actuate from SMA's attached to it. The proposed FY17 Shape-Morphing Adaptive Radiator Technology (SMART) project's goal is to 1) develop a practical radiator design with shape memory alloys (SMAs) bonded to the radiator's panel, and 2) build a multi-panel radiator prototype for subsequent system level thermal vacuum tests. The morphing radiator employs SMA materials to passively change its shape to adapt its rate of heat rejection to vehicle requirements. Conceptually, the radiator panel has a naturally closed position (like a cylinder) in a cold environment. Whenever the radiator's temperature gradually rises, SMA's affixed to the face sheet will pull the face sheet open a commensurate amount - increasing the radiators view to space and causing it to reject more heat. In a vehicle, the radiator's variable heat rejection capabilities would reduce the number of additional heat rejection devices in a vehicle's thermal control system. This technology aims to help achieve the required maximum to minimum heat rejection ratio required for manned space vehicles to adopt a lighter, simpler, single loop thermal control architecture (ATCS). Single loop architectures are viewed as an attractive means to reduce mass and complexity over traditional dual-loop solutions. However, fluids generally considered safe enough to flow within crewed cabins (e.g. propylene glycol-water mixtures) have much higher freezing points and viscosities than those used in the external sides of dual loop ATCSs (e.g. Ammonia and HFE7000).

Erickson, Lisa↗
NASA NTRSDate not supplied

Sparse Linear Algebra Toolkit for Computational Aerodynamics

Finding solutions to sparse linear systems of equations is an essential step in Computational Engineering applications of interest to NASA. Linear systems of equations are composed and solved in almost every computational engineering application. The characteristics of linear systems vary greatly from one application to another. Accordingly, there are a wide variety of methods for the solution of linear systems of equations. The operations and methods prepared by the authors are focused on linear systems of interest to NASA, primarily those associated with Computational Fluid Dynamics (CFD), Aeroelasticity, and Aeroacoustics. The Sparse Linear Algebra Toolkit (SLAT) is a coordinated collection of software featuring operations, methods, and data structures that are useful when solving sparse linear systems of equations on modern computer architectures. The implemented operations and methods are designed and tuned for parallelism in shared memory, in distributed memory, and across the hybrid combination of distributed-shared memory. The toolkit includes novel methods and implementations for modern architectures and facilitates development of new approaches for meeting NASA’s evolving computational engineering challenges using evolving computer architectures that are not available in vendor libraries. In this paper, significant features and interfaces within SLAT are presented and verified for simulations performed with NASA’s CFD solver, FUN3D. The runtime and scaling performance of the Generalized Minimum Residual (GMRES) method implemented in SLAT is analyzed for the linear subproblems within the solution of turbulent Navier-Stokes equations employed in the simulation of high-lift configurations. Prior to this work, the SPARSKIT GMRES implementation was the only Krylov subspace method available within FUN3D. A strong scaling study shows the SLAT GMRES implementation facilitates accurate Reynolds-averaged Navier-Stokes CFD solutions between 15% and 56% faster than the SPARSKIT GMRES implementation.

Stephen L Wood↗
DOE OSTI2023

IP Protection in TinyML

Tiny machine learning (TinyML) is an essential component of emerging smart microcontrollers (MCUs). How- ever, the protection of the intellectual property (IP) of the model is an increasing concern due to the lack of desktop/server-grade resources on these power-constrained devices. In this paper, we propose STML, a system and algorithm co-design to Secure IP of TinyML on MCUs with ARM TrustZone. Our design jointly optimizes memory utilization and latency while ensuring the security and accuracy of emerging models. We implemented a prototype and benchmarked with 7 models, demonstrating STML reduces 40% of model protection runtime overhead on average.

42 ENGINEERING↗
DOE OSTI2022

High Performance Adaptive Physics Refinement to Enable Large-Scale Tracking of Cancer Cell Trajectory

The ability to track simulated cancer cells through the circulatory system, important for developing a mechanistic understanding of metastatic spread, pushes the limits of today's supercomputers by requiring the simulation of large fluid volumes at cellular-scale resolution. To overcome this challenge, we introduce a new adaptive physics refinement (APR) method that captures cellular-scale interaction across large domains and leverages a hybrid CPU-GPU approach to maximize performance. Through algorithmic advances that integrate multi-physics and multi-resolution models, we establish a finely resolved window with explicitly modeled cells coupled to a coarsely resolved bulk fluid domain. In this work we present multiple validations of the APR framework by comparing against fully resolved fluid-structure interaction methods and employ techniques, such as latency hiding and maximizing memory bandwidth, to effectively utilize heterogeneous node architectures. Collectively, these computational developments and performance optimizations provide a robust and scalable framework to enable system-level simulations of cancer cell transport.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1984

Research in the design of high-performance reconfigurable systems

An initial design for the Bit Processor (BP) referred to in prior reports as the Processing Element or PE has been completed. Eight BP's, together with their supporting random-access memory, a 64 k x 9 ROM to perform addition, routing logic, and some additional logic, constitute the components of a single stage. An initial stage design is given. Stages may be combined to perform high-speed fixed or floating point arithmetic. Stages can be configured into a range of arithmetic modules that includes bit-serial one or two-dimensional arrays; one or two dimensional arrays fixed or floating point processors; and specialized uniprocessors, such as long-word arithmetic units. One to eight BP's represent a likely initial chip level. The Stage would then correspond to a first-level pluggable module. As both this project and VLSI CAD/CAM progress, however, it is expected that the chip level would migrate upward to the stage and, perhaps, ultimately the box level. The BP RAM, consisting of two banks, holds only operands and indices. Programs are at the box (high-level function) and system level. At the system level initial effort has been concentrated on specifying the tools needed to evaluate design alternatives.

Slotnick, D. L.↗
DOE OSTI2026

Unitary Qubit Lattice Algorithms for Plasma Physics

This final technical report summarizes research conducted under DOE Award DE-SC0021653 to develop unitary Quantum Lattice Algorithms for modeling electromagnetic wave propagation and scattering in complex media, including plasmas. The project developed and validated quantum-inspired formulations of Maxwell's equations that preserve unitary evolution and can be evaluated on classical high-performance computing systems while providing a foundation for future quantum-computing implementations. Major accomplishments include the development of two- and three-dimensional algorithms for electromagnetic scattering; scalable, distributed-memory implementations demonstrated on the Perlmutter supercomputer; formulations for nonlinear lossless fluid dynamics and cold, lossless, inhomogeneous magnetized plasmas; and an explicit quantum algorithm for a time-discretized Lorenz model. Simulations reproduced a range of characteristic wave phenomena, including transient effects that are not readily apparent in conventional frequency-domain studies, demonstrating the effectiveness of the proposed approach for modeling complex electromagnetic and plasma systems. The work establishes a unified theoretical and computational framework for quantum and quantum-inspired simulation and provides a foundation for future implementation on fault-tolerant quantum systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A Hybrid Optimization and Deep Learning Algorithm for Cyber-Resilient DER Control

With the proliferation of distributed energy resources (DERs) in the distribution grid, it is a challenge to effectively control a large number of DERs resilient to the communication and security disruptions, as well as to provide the online grid services, such as voltage regulation and virtual power plant (VPP) dispatch. To this end, a hybrid feedback-based optimization algorithm along with deep learning forecasting technique is proposed to specifically address the cyber-related issues. The online decentralized feedback-based DER optimization control requires timely, accurate voltage measurement from the grid. However, in practice such information may not be received by the control center or even be corrupted. Therefore, the long short-term memory (LSTM) deep learning algorithm is employed to forecast delayed/missed/attacked messages with high accuracy. The IEEE 37-node feeder with high penetration of PV systems is used to validate the efficiency of the proposed hybrid algorithm. The results show that 1) the LSTM-forecasted lost voltage can effectively improve the performance of the DER control algorithm in the practical cyber-physical architecture; and 2) the LSTM forecasting strategy outperforms other strategies of using previous message and skipping dual parameter update.

cyber-resilient algorithm↗
DOE OSTI2021

On the Symmetry of Blast Waves

This paper presents a brief historical review of G. I. Taylor’s solution of the point blast wave problem which was applied to the Trinity test of the first atomic bomb. Lie group symmetry techniques (also referred to throughout this paper as geometric techniques) are used to derive Taylor’s famous two-fifths law that relates the position of a blast wave to the time after the explosion and the total energy released. The theory of exterior differential systems is combined with the method of characteristics to demonstrate that the solution of the blast wave problem is directly related to the basic relationships that exist between the symmetry (or geometry) and the physics of wave propagation through the equations of motion. The point blast wave model is cast in terms of two exterior differential systems, and both systems are shown to be integrable with local solutions for the velocity, pressure, and density along curves in space and time behind the blast wave. This work is dedicated to the memory of Professor Roy Axford, who introduced many of his students to the topic of symmetry analysis of differential equations.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Magnon confinement in epitaxial antiferromagnetic oxide heterostructures.

Magnons, the quanta of spin waves, have been extensively studied in a range of materials for spintronics, particularly for non-volatile logic-in-memory devices. Controlling magnons in conventional antiferromagnets and harnessing them in practical applications, however, remains a challenge. Here, we demonstrate highly efficient magnon transport in a LaFeO3/ BiFeO3/ LaFeO3 all-antiferromagnetic system, which can be controlled electrically, making it highly desirable for energy-efficient computation. Leveraging spin-orbit-driven spin-charge transduction, we demonstrate that this material architecture permits magnon confinement in ultrathin antiferromagnets, enhancing the output voltage generated by magnon transport by several orders of magnitude, which provides a pathway to enable magnetoelectric memory and logic functionalities. Additionally, the non-volatility of output voltage enables ultralowpower logic-in-memory processing, where magnonic devices can be efficiently reconfigured via electrically controlled magnon spin currents within magnetoelectric channels.

Husain, Sajid↗
NASA NTRS1989

Methods and decision making on a Mars rover for identification of fossils

A system for automated fusion and interpretation of image data from multiple sensors, including multispectral data from an imaging spectrometer is being developed. Classical artificial intelligence techniques and artificial neural networks are employed to make real time decision based on current input and known scientific goals. Emphasis is placed on identifying minerals which could indicate past life activity or an environment supportive of life. Multispectral data can be used for geological analysis because different minerals have characteristic spectral reflectance in the visible and near infrared range. Classification of each spectrum into a broad class, based on overall spectral shape and locations of absorption bands is possible in real time using artificial neural networks. The goal of the system is twofold: multisensor and multispectral data must be interpreted in real time so that potentially interesting sites can be flagged and investigated in more detail while the rover is near those sites; and the sensed data must be reduced to the most compact form possible without loss of crucial information. Autonomous decision making will allow a rover to achieve maximum scientific benefit from a mission. Both a classical rule based approach and a decision neural network for making real time choices are being considered. Neural nets may work well for adaptive decision making. A neural net can be trained to work in two steps. First, the actual input state is mapped to the closest of a number of memorized states. After weighing the importance of various input parameters, the net produces an output decision based on the matched memory state. Real time, autonomous image data analysis and decision making capabilities are required for achieving maximum scientific benefit from a rover mission. The system under development will enhance the chances of identifying fossils or environments capable of supporting life on Mars

Eberlein, Susan↗
NASA NTRS1982

Automatic weld torch guidance control system

A highly reliable, fully digital, closed circuit television optical, type automatic weld seam tracking control system was developed. This automatic tracking equipment is used to reduce weld tooling costs and increase overall automatic welding reliability. The system utilizes a charge injection device digital camera which as 60,512 inidividual pixels as the light sensing elements. Through conventional scanning means, each pixel in the focal plane is sequentially scanned, the light level signal digitized, and an 8-bit word transmitted to scratch pad memory. From memory, the microprocessor performs an analysis of the digital signal and computes the tracking error. Lastly, the corrective signal is transmitted to a cross seam actuator digital drive motor controller to complete the closed loop, feedback, tracking system. This weld seam tracking control system is capable of a tracking accuracy of + or - 0.2 mm, or better. As configured, the system is applicable to square butt, V-groove, and lap joint weldments.

Smaith, H. E.↗
DOE OSTI2026

An Autonomous MCP Bridge to Rucio: Enhancing Data Management Accessibility for High Energy Physics

The Rucio Data Management System [1] is an important tool used by High Energy Physics experiments, including those at Fermi National Accelerator Laboratory, to store and manage exabyte-scale scientific datasets. Despite its central role in coordinating data across globally distributed storage sites, Rucio's command line interface (CLI) presents a steep learning curve, and makes it difficult for scientists to navigate through. To solve this issue, a containerized Model Context Protocol (MCP) [2] server was built that connects Large Language Models directly to Rucio, allowing AI agents to handle data tasks by using simple, natural language rather than memorized terminal commands. The core engineering focus of this project was moving the server away from slow terminal commands that require text parsing and replacing them with a native Python Client API toolset and a planned REST API framework. Moving to the Python API handles data operations directly in memory, which helps clear up formatting errors, provides the AI with clean, structured JSON data and speeds up tool execution. To prove that the system actually works, a benchmarking pipeline was also built with various questions to test the AI across four different model configurations. The questions included finding data scopes, tracking down specific datasets, and checking replication rules. Through benchmarking, early runs showed that with raw terminal text, the model would get confused and stuck, whereas switching to the Python API to feed the AI clean, structured data yielded massive improvement. By creating an intelligent and autonomous bridge to a storage network, this project shows how AI can be implemented in scientific data management, which ultimately helps scientists at Fermilab spend less time sorting through data and more time focusing on their experiments and analysis.

Akella, Kashyap [William Rainey Harper Coll.]↗
NASA NTRS1984

Flight critical system design guidelines and validation methods

Efforts being expended at NASA-Langley to define a validation methodology, techniques for comparing advanced systems concepts, and design guidelines for characterizing fault tolerant digital avionics are described with an emphasis on the capabilities of AIRLAB, an environmentally controlled laboratory. AIRLAB has VAX 11/750 and 11/780 computers with an aggregate of 22 Mb memory and over 650 Mb storage, interconnected at 256 kbaud. An additional computer is programmed to emulate digital devices. Ongoing work is easily accessed at user stations by either chronological or key word indexing. The CARE III program aids in analyzing the capabilities of test systems to recover from faults. An additional code, the semi-Markov unreliability program (SURE) generates upper and lower reliability bounds. The AIRLAB facility is mainly dedicated to research on designs of digital flight-critical systems which must have acceptable reliability before incorporation into aircraft control systems. The digital systems would be too costly to submit to a full battery of flight tests and must be initially examined with the AIRLAB simulation capabilities.

Holt, H. M.↗
DOE OSTI2025

Enabling Multireference Calculations on Multimetallic Systems with Graphic Processing Units

Modeling multimetallic systems efficiently enables faster prediction of desirable chemical properties and the design of new materials. This work describes an initial implementation for performing multireference wave function method localized active-space self-consistent field (LASSCF) calculations through the use of multiple graphics processing units (GPUs) to accelerate time-to-solution. Density fitting is leveraged to reduce memory requirements, and we demonstrate the ability to fully utilize multi-GPU compute nodes. Performance improvements of 5–10x in total application runtime were observed in LASSCF calculations for multimetallic catalyst systems up to 1200 AOs and an active space of (22e,40o) using up to four NVIDIA A100 GPUs. Furthermore, written with performance portability in mind, a comparable performance is also observed in early runs on the Aurora exascale system using Intel Max Series GPUs.

Algorithms↗
DOE OSTI2024

Linear Time-Invariant Models of a Large Cumulus Ensemble

Abstract Methods in system identification are used to obtain linear time-invariant state-space models that describe how horizontal averages of temperature and humidity of a large cumulus ensemble evolve with time under small forcing. The cumulus ensemble studied here is simulated with cloud-system-resolving models in radiative–convective equilibrium. The identified models extend steady-state linear response functions used in past studies and provide accurate descriptions of the transfer function, the noise model, and the behavior of cumulus convection when coupled with two-dimensional gravity waves. A novel procedure is developed to convert the state-space models into an interpretable form, which is used to elucidate and quantify memory in cumulus convection. The linear problem studied here serves as a useful reference point for more general efforts to obtain data-driven and interpretable parameterizations of cumulus convection.

Meteorology & Atmospheric Sciences↗