Search NASA⌕ Search

SEARCH · Search NASA

Results for “Emerging hardware”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhanced Control, Optimization, and Integration of Distributed Energy Applications (ECO-IDEA)

With support from the U.S. Department of Energy Solar Energy Technologies Office, the National Renewable Energy Laboratory (NREL) partnered with Xcel Energy, Schneider Electric, Varentec, and Electric Power Research Institute (EPRI) to meet the goals of the Enabling Extreme Real-Time Grid Integration of Solar Energy (ENERGISE) program. This project developed and validated an innovative data-enhanced hierarchical control architecture that enables the efficient, reliable, resilient, and secure operation of future distribution systems with a high penetration of distributed energy resources like solar energy. The architecture enables a hybrid control approach where a centralized control layer is complemented by distributed control algorithms for solar inverters and autonomous control of grid edge devices. It is fully interoperable and includes all the cybersecurity aspects necessary for reliable and secure system operation. The hybrid approach can seamlessly integrate multiple voltage-regulation technologies, both at central and grid-edge levels, which enables reliable and efficient system operation in the face of unpredictable conditions. The overarching goal of the Eco-Idea project is to develop, validate, and deploy a unique and innovative Data-Enhanced Hierarchical Control (DEHC) architecture that comprehensively addresses the formidable challenges associated with proliferation of high penetration of distributed PV such as reverse power flows, transients from variability of PV systems, feeder load balancing, and voltage stability. These issues are exposing the weaknesses of existing grid operations and controls - including, but not limited to, lack of grid situational awareness, heuristic and slow-acting control actions, latency of control for emergency situations, and points of failure in communications. The proposed architecture will comprehensively resolve the deficiencies of current operational settings - where monitoring and control solutions proposed across industry and academia may not be interoperable and may not coexist in the same system - and will enable an efficient, reliable, resilient, and secure operation of future distribution systems with penetration of solar energy well beyond current limits. The DEHC architecture was developed and validated rigorously through hardware-in-loop simulations in the laboratory environment and deployed on the field.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1996

Neural Networks for Flight Control

Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.

Jorgensen, Charles C.↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
DOE OSTI2023

Design principles for lifelong learning AI accelerators

Lifelong learning-an agent's ability to learn throughout its lifetime-is a hallmark of biological learning systems and a central challenge for artificial intelligence (AI). The development of lifelong learning algorithms could lead to a range of novel AI applications, but this will also require the development of appropriate hardware accelerators, particularly if the models are to be deployed on edge platforms, which have strict size, weight and power constraints. Here we explore the design of lifelong learning AI accelerators that are intended for deployment in untethered environments. We identify key desirable capabilities for lifelong learning accelerators and highlight metrics to evaluate such accelerators. We then discuss current edge AI accelerators and explore the future design of lifelong learning accelerators, considering the role that different emerging technologies could play. The Perspective explores the future design of lifelong learning artificial intelligence (AI) accelerators that are intended for deployment in untethered environments, identifying key desirable capabilities for such edge AI accelerators and guidance on metrics to evaluate them.

42 ENGINEERING↗
NASA NTRS1994

Large angle magnetic suspension test fixture

Over the past few decades, research has proven the feasibility of the concept of noncontacting magnetic bearing systems which operate with no wear or vibration. As a result, magnetic bearing systems are beginning to emerge as integral parts of modern industrial and aerospace systems. Further applications research is still required. NASA has loaned an existing magnetic bearing device, the Annular Suspension and Pointing System (ASPS), to ODU to permit student design teams the opportunity to pursue some of these studies. The ASPS is a protoype for a high-accuracy space payload pointing and vibration isolation system. The project objectives are to carry out modifications and improvements to the ASPS hardware to permit recommissioning in a 1-g (ground-based) environment. Following recommissioning, new applications will be studied and demonstrated, including a rotary joint for solar panels. The first teams designed and manufactured pole shims to reduce the air-gaps and raise the vertical force capability as well as on control system studies. The most recent team concentrated on the operation of a single bearing station, which was successfully accomplished with a PC-based digital controller. The paper will review the history and technical background of the ASPS hardware, followed by presentation of the progress made and the current status of the project.

Britcher, Colin P.↗
NASA NTRS2014

Investigation of HZETRN 2010 as a Tool for Single Event Effect Qualification of Avionics Systems

NASA's future missions are focused on long-duration deep space missions for human exploration which offers no options for a quick emergency return to Earth. The combination of long mission duration with no quick emergency return option leads to unprecedented spacecraft system safety and reliability requirements. It is important that spacecraft avionics systems for human deep space missions are not susceptible to Single Event Effect (SEE) failures caused by space radiation (primarily the continuous galactic cosmic ray background and the occasional solar particle event) interactions with electronic components and systems. SEE effects are typically managed during the design, development, and test (DD&T) phase of spacecraft development by using heritage hardware (if possible) and through extensive component level testing, followed by system level failure analysis tasks that are both time consuming and costly. The ultimate product of the SEE DD&T program is a prediction of spacecraft avionics reliability in the flight environment produced using various nuclear reaction and transport codes in combination with the component and subsystem level radiation test data. Previous work by Koontz, et al.1 utilized FLUKA, a Monte Carlo nuclear reaction and transport code, to calculate SEE and single event upset (SEU) rates. This code was then validated against in-flight data for a variety of spacecraft and space flight environments. However, FLUKA has a long run-time (on the order of days). CREME962, an easy to use deterministic code offering short run times, was also compared with FLUKA predictions and in-flight data. CREME96, though fast and easy to use, has not been updated in several years and underestimates secondary particle shower effects in spacecraft structural shielding mass. Thus, this paper will investigate the use of HZETRN 20103, a fast and easy to use deterministic transport code, similar to CREME96, that was developed at NASA Langley Research Center primarily for flight crew ionizing radiation dose assessments. HZETRN 2010 includes updates to address secondary particle shower effects more accurately, and might be used as another tool to verify spacecraft avionics system reliability in space flight SEE environments.

Rojdev, Kristina↗
NASA NTRS2018

The Evolution of Payload Data Capabilities on the Commercial Visiting Vehicles that Service the International Space Station

For over 10 years, NASA has been working with U.S.-based commercial companies to support the design, development, and operations of new commercial space vehicles. The purpose of these vehicles is to provide cargo and crew transportation services to the International Space Station (ISS) and to stimulate the commercial space transportation industry to Low-Earth Orbit (LEO). Along with the ability to provide a couple tons of cargo to the ISS each mission, the commercial visiting vehicles also provide the ability to transfer NASA payloads to and from the ISS in an active, powered state. To take advantage of this capability, NASA requirements for the data services that payloads need while they are integrated into the visiting vehicles have grown with each set of commercial contracts. Today, NASA desires for payload data services encompass a variety of capabilities including payload health and status (H&S) telemetry monitoring, visiting vehicle environment data monitoring, and payload commanding. The intent of these capabilities is to provide payload developers with situational awareness and the ability to quickly diagnose any problems with payload operations prior to vehicle docking or post-landing to support immediate troubleshooting response. As new requirements for payload data services have emerged over the years, the ISS Payload Operations Integration Center (POIC) at the NASA Marshall Space Flight Center (MSFC) has established ground segment interfaces to the visiting vehicle control centers to enable payload developers to use these services. Many technical and programmatic challenges have been faced while establishing these interfaces. The most significant challenge faced has been in finding the right balance amongst providing interfaces to payloads that are compatible with the ISS so that payload hardware or software changes are not necessary to ensure compatibility with the visiting vehicles; keeping POIC ground system development costs low by standardizing implementation approaches across commercial vehicle partners; and fostering commercialization through supporting vendor-unique implementations that are commercially economical. This paper will first detail the data services that will be available to payload users under each commercial visiting vehicle contract. Secondly, this paper will offer discussion of the most significant technical and programmatic challenges faced to-date in offering these new data services to payload developers.

Wiggins, Lindsay M.↗
DOE OSTI2020

OpenCGRA: An Open-Source Unified Framework for Modeling,Testing, and Evaluating CGRAs

Coarse-grained reconfigurable arrays (CGRAs),loosely defined as arrays of functional units (e.g, adder, sub-tractor, multiplier, divider, or larger multi-operation units, butsmaller than a general-purpose core) interconnected through aNetwork-on-Chip, provide higher flexibility than domain-specificASIC accelerators while offering increased hardware efficiencywith respect to fine-grained reconfigurable devices, such as FieldProgrammable Gate Arrays (FPGAs). The fast evolving fieldsof machine learning and edge computing, which are seeing acontinuous flow of novel algorithms and larger models, makeCGRAs ideal target architectures to allow domain specializationwithout loosing too much generality. They also generally offerquicker and more effective reconfigurability than FPGAs, po-tentially allowing adaptation during actual algorithm execution,and implement a dataflow programming paradigm that adaptswell to these emerging workloads. Designing and generating aCGRA, however, still requires to define the type and number ofthe specific functional units, implement their interconnect andthe network topology, and perform its simulation and validation,given a variety of workloads of interest.In this paper, we propose OpenCGRA, a Python-based unifiedframework that integrates generation, modeling, testing and eval-uation for CGRAs. OpenCGRA is the first open-source integratedframework able to support the full top-to-bottom design flow forspecializing and implementing CGRAs: modeling at different ab-straction levels (functional level, cycle level, register-transfer level),generation, simulation, testing at different granularities (unit test-ing, integration testing, property-based testing), and characteriza-tion (area, power, and timing). OpenCGRAs will be made availableon GitHub.

CGRA, synthesis↗
NASA NTRS2014

Deep Space Habitat Wireless Smart Plug

NASA has been interested in technology development for deep space exploration, and one avenue of developing these technologies is via the eXploration Habitat (X-Hab) Academic Innovation Challenge. In 2013, NASA's Deep Space Habitat (DSH) project was in need of sensors that could monitor the power consumption of various devices in the habitat with added capability to control the power to these devices for load shedding in emergency situations. Texas A&M University's Electronic Systems Engineering Technology Program (ESET) in conjunction with their Mobile Integrated Solutions Laboratory (MISL) accepted this challenge, and over the course of 2013, several undergraduate students in a Capstone design course developed five wireless DC Smart Plugs for NASA. The wireless DC Smart Plugs developed by Texas A&M in conjunction with NASA's Deep Space Habitat team is a first step in developing wireless instrumentation for future flight hardware. This paper will further discuss the X-Hab challenge and requirements set out by NASA, the detailed design and testing performed by Texas A&M, challenges faced by the team and lessons learned, and potential future work on this design.

Morgan, Joseph A.↗
NASA NTRS1974

The prologue - A look at Apollo and Apollo/Soyuz

The importance of man to the success of the Apollo missions is considered, giving attention to man's capabilities to provide rapid response to emergencies, the ability to carry out self-contained operations in the absence of communication with the ground, and the ability for rapid sensing, reaction, and vehicle control. In the upcoming Shuttle era the capabilities possessed by man are to be further utilized. The concern for the safety of men in space is one of the major reasons for the flight of the Apollo/Soyuz test project. Details regarding this project are discussed, taking into account the mission profile, hardware, program organization, mission communication modes, tracking, the participating astronauts and cosmonauts, and scientific studies.

Lee, C. M.↗
NASA NTRS1991

Geostationary Operational Environmental Statellite(GEOS-N report)

The Advanced Missions Analysis Office (AMAO) of GSFC has completed a study of the Geostationary Operational Environmental Satellites (GOES-N) series. The feasibility, risks, schedules, and associated costs of advanced space and ground system concepts responsive to National Oceanic and Atmospheric Administration (NOAA) requirements were evaluated. The study is the first step in a multi-phased procurement effort that is expected to result in launch ready hardware in the post 2000 time frame. This represents the latest activity of GSFC in translating meteorological requirements of NOAA into viable space systems in geosynchronous earth orbits (GEO). GOES-N represents application of the latest spacecraft, sensor, and instrument technologies to enhance NOAA meteorological capabilities via remote and in-situ sensing from GEO. The GOES-N series, if successfully developed, could become another significant step in NOAA weather forecasting space systems, meeting increasingly complex emerging national needs for that agency's services.

Source record↗
DOE OSTI2026

Benchmark for two-dimensional large scale coherent structures in partially magnetized E × B plasmas—community collaboration & lessons learned

Low-temperature plasmas (LTPs) are essential to both fundamental scientific research and critical industrial applications. As in many areas of science, numerical simulations have become a vital tool for uncovering new physical phenomena and guiding technological development. Code benchmarking remains crucial for verifying implementations and evaluating performance. This work continues the Landmark benchmark initiative, a series specifically designed to support the verification of LTP codes. In this study, seventeen simulation codes from a collaborative community of nineteen international institutions modeled a partially magnetized E × B Penning discharge. The emergence of large scale coherent structures, or rotating plasma spokes, endows this configuration with an enormous range of time scales, making it particularly challenging to simulate. The codes showed excellent agreement on the rotation frequency of the spoke as well as key plasma properties, including time-averaged ion density, plasma potential, and electron temperature profiles. Achieving this level of agreement came with challenges, and we share lessons learned on how to conduct future benchmarking campaigns. Comparing code implementations, computational hardware, and simulation runtimes also revealed interesting trends, which are summarized with the aim of guiding future plasma simulation software development.

benchmarking↗
DOE OSTI2024

Phasor-Domain Modeling of Inverter Based Resources Considering Unbalanced Grid Faults

A significant increase in inverter-based distributed energy resources (DERs) is expected in distribution systems of the near future. The latest phasor modeling approach of DERs with emerging control technologies can capture relevant dynamics in large-scale three-phase distribution systems with unbalanced construction. However, there is a lack of appropriate phasor models to deal with unbalanced fault scenarios. As such, this paper describes per-phase phasor modeling approach appropriate for unbalanced grid disturbance studies in distribution systems with high penetration of DERs. The overall modeling performance of representative DERs is simulated in phasor domain GridLAB-D environment and validated against controller hardware-in-the loop (CHIL) testing or electromagnetic transient (EMT) based switching model simulation in PSCAD with test cases including different unbalanced grid faults. The high accuracy retained from the simulation verifies the effectiveness of the proposed phasor modeling approach considering interactions between positive and negative sequence signals.

Chen, Zhe↗
NASA NTRS1989

Computerized structural mechanics for 1990's: Advanced aircraft needs

The needs for computerized structural mechanics (CSM) as seen from the standpoint of the aircraft industry are discussed. These needs are projected into the 1990's with special focus on the new advanced materials. Preliminary design/analysis, research, and detail design/analysis are identified as major areas. The role of local/global analyses in these different areas is discussed. The lessons learned in the past are used as a basis for the design of a CSM framework that could modify and consolidate existing technology and include future developments in a rational and useful way. A philosophy is stated, and a set of analyses needs driven by the emerging advanced composites is enumerated. The roles of NASA, the universities, and the industry are identified. Finally, a set of rational research targets is recommended based on both the new types of computers and the increased complexity the industry faces. Computerized structural mechanics should be more than new methods in structural mechanics and numerical analyses. It should be a set of engineering applications software products that combines innovations in structural mechanics, numerical analysis, data processing, search and display features, and recent hardware advances and is organized in a framework that directly supports the design process.

Viswanathan, A. V.↗
DOE OSTI2023

Quantum Computing and Visualization: A Disruptive Technological Change Ahead

The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore’s Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. Importantly, while present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Non-intrusive speed sensor

In Phase I of the Non-Intrusive Speed Sensor program, a computerized literature search was performed to identify candidate technologies for remote, non-intrusive speed sensing applications in Space Shuttle Main Engine (SSME) turbopumps. The three most promising technologies were subjected to experimental evaluation to quantify their performance characteristics under the harsh environmental requirements within the turbopumps. Although the infrared and microwave approaches demonstrated excellent cavitation immunity in laboratory tests, the variable-source magnetic speed sensor emerged as the most viable approach. Preliminary design of this speed sensor encountered no technical obstacles and resulted in viable and feasible speed nut, sensor housing, and sensor coil designs. Phase II of this program developed the variable-source magnetic speed sensor through the detailed design task and guided the design into breadboard fabrication. The speed sensor and its integral speed nut were evaluated at both unit and system level testing. The final room-temperature and cryogenic spin testing of the hardware demonstrated that the sensor was capable of generating sufficient output signal to enable remote speed sensing from 1500 to 40000 rpm over a speed nut/sensor separation of 3.5 inches.

Wyett, L.↗
NASA NTRS2014

A Modular Aerospike Engine Design Using Additive Manufacturing

A modular aerospike engine concept has been developed with the objective of demonstrating the viability of the aerospike design using additive manufacturing techniques. The aerospike system is a self-compensating design that allows for optimal performance over the entire flight regime and allows for the lowest possible mass vehicle designs. At low altitudes, improvements in Isp can be traded against chamber pressure, staging, and payload. In upper stage applications, expansion ratio and engine envelope can be traded against nozzle efficiency. These features provide flexibility to the System Designer optimizing a complete vehicle stage. The aerospike concept is a good example of a component that has demonstrated improved performance capability, but traditionally has manufacturing requirements that are too expensive and complex to use in a production vehicle. In recent years, additive manufacturing has emerged as a potential method for improving the speed and cost of building geometrically complex components in rocket engines. It offers a reduction in tooling overhead and significant improvements in the integration of the designer and manufacturing method. In addition, the modularity of the engine design provides the ability to perform full scale testing on the combustion devices outside of the full engine configuration. The proposed design uses a hydrocarbon based gas-generator cycle, with plans to take advantage of existing powerhead hardware while focusing DDT&E resources on manufacturing and sub-system testing of the combustion devices. The major risks for the modular aerospike concept lie in the performance of the propellant feed system, the structural integrity of the additive manufactured components, and the aerodynamic efficiency of the exhaust flow.

Peugeot, John↗