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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Qualification Testing Versus Quantitative Reliability Testing of PV - Gaining Confidence in a Rapidly Changing Technology: Preprint

Continued growth of PV system deployment would be enhanced by quantitative, low-uncertainty predictions of the degradation and failure rates of PV modules and systems. The intended product lifetime (decades) far exceeds the product development cycle (months), limiting our ability to reduce the uncertainty of the predictions for this rapidly changing technology. Yet, business decisions (setting insurance rates, analyzing return on investment, etc.) require quantitative risk assessment. Moving toward more quantitative assessments requires consideration of many factors, including the intended application, consequence of a possible failure, variability in the manufacturing, installation, and operation, as well as uncertainty in the measured acceleration factors, which provide the basis for predictions based on accelerated tests. As the industry matures, it is useful to periodically assess the overall strategy for standards development and prioritization of research to provide a technical basis both for the standards and the analysis related to the application of those. To this end, this paper suggests a tiered approach to creating risk assessments. Recent and planned potential improvements in international standards are also summarized.

14 SOLAR ENERGY↗
DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size: Preprint

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear- and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute timescale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

REFSafE: A RAG-Enabled Framework for Predictive Risk Analysis and Automated Safety Report Generation in Mission-Critical Environments

Operational safety in mission-critical environments requires AI systems that are accurate, interpretable, and resistant to hallucination. We present an agentic Retrieval-Augmented Generation (RAG) framework, REFSafe, for grounded hazard analysis and automated safety report generation. The system integrates Large Language Models (LLMs) with structured operational data, historical incident repositories, policy documents, and external authoritative sources. Through iterative agentic reasoning, the framework retrieves, verifies, and synthesizes evidence prior to generation, enforcing citation-backed outputs with explicit source attribution (documents, links, and prior events) to ensure traceability and trust. To mitigate hallucinations and unsupported claims, all risk assessments and forecasts are constrained to retrieved evidence, with confidence signals derived from retrieval relevance and source consistency. A transparent pipeline enables subject matter experts (SMEs) to validate predictions, and provide structured feedback, forming a continuous performance calibration loop. Preliminary deployment demonstrates improved reliability in hazard detection and safety/vulnerability report generation. This work advances trustworthy, evidence-grounded AI for predictive safety intelligence in mission-critical operations.

Das, Sanjay [ORNL] (ORCID:0009000542591915)↗
NASA NTRS2017

Orbital Space Solar Power Option for a Lunar Village

One of the most significant challenges to the implementation of a continuously manned lunar base is power. During the lunar day (14 Earth days), it is conceptually simple to deploy solar arrays to generate the estimated 35 kilowatts of continuous power required. However, generating this level of power during the lunar night (also 14 Earth days) has been an extremely difficult problem to solve. Conventional solutions range from the requirement that the base be located at the lunar south pole so as to take advantage of the continuous sunshine available there to developing a space-qualified nuclear reactor and power plant to generate the needed energy. There is a third option: Use the soon-to-be-available Space Launch System to place a space based solar power station in lunar orbit that would beam the needed energy to the lunar base. Several detailed studies have been performed by NASA, universities and others looking at the lunar south pole for locating the base. The results are encouraging: by taking advantage of the moon's orbital tilt, large solar arrays can be deployed there to track the sun continuously and generate the power needed to sustain the base. The problem with this approach is inherent to its design: it will only work at the lunar south pole. There is no other site on the Moon with geometry favorable to generating continuous solar power. NASA has also considered the development of a compact fission reactor and power plant to generate the needed power, allowing the base to be sited anywhere on the Moon. The problem with this approach is that there are no space fission reactors available, none are being planned and the cost of developing one is prohibitively expensive. Using an orbiting space based solar power station to generate electrical power and beam it to a base sited anywhere on the moon should therefore be considered. The technology to collect sunlight, generate greater than the estimated 35 kilowatts of power, and beam it to the surface using microwaves is available today. The problem with this concept in the past would have been the mass and packaging volume (for launch) required to put such a system in place in lunar orbit. This problem is potentially solved with the advent of the Space Launch System (SLS). The SLS, with its 70 mT launch capacity, it more than capable of placing such a system into lunar orbit in a single launch. This paper will examine the potential use of an SLS-launched, space solar power system in lunar orbit as the primary power source for a first-generation, continuously-occupied lunar base and compare it with the other power generation and storage options previously considered.

Johnson, Les↗
NASA NTRSDate not supplied

A Deployable 40 kWe Lunar Fission Surface Power Concept

Continuous power at the kilowatt level will be imperative for future lunar users including crew infrastructure, future science, and in-situ resource utilization (ISRU). The Compass Team explored both 10 kWe and 40 kWe concepts, assuming planned lander and rover capabilities. Both concepts found that a crew pressurized rover chassis, repurposed for deploying reactor power components, could place a fission surface power system (FSPS) at least one km from users. While the 10 kWe fission power system (FPS) could be deployed as a single unit, the 40 kWe system was too large and had to be deployed in multiple trips with the same rover. Key technologies and design approaches included a high-assay low-enriched uranium (HALEU), yttrium hydride (YH) moderated heat pipe reactor, Stirling convertors, deployable radiators based on International Space Station (ISS) designs, and power conversion/transmission at ±2800 VDC for a one km remote distance.

Fission Power↗
DOE OSTI2023

Task 2.3: Continuous Counter-Current Chromatography

This task in the Separations Consortium focuses on the development of counter-current chromatography (CCC), which is an advanced liquid-liquid chromatography method. Today, CCC is primarily practiced in batch mode operation, but continuous operation will be required for at-scale deployment in a biorefinery setting. In this task, we are developing a continuous CCC process in collaboration with a company that builds CCC units. This work will be demonstrated on the biorefining challenge of lignin valorization. Specifically, we demonstrate use of continuous CCC for both monomer-monomer and monomer-oligomer separations in multiple lignin streams of relevance to the biorefining industry. Breakthroughs in this area would be useful for BETO goals in both sustainable aviation fuel and biochemicals production, including directly contributing to BETO's 2030 lignin valorization goal. Our approach includes developing new computational modeling approaches to optimize both batch and continuous CCC processes, experimental work to determine optimal solvent systems for multiple lignin streams sourced from BETO-funded projects and industrial collaborators, and techno-economic analysis and life cycle assessment to identify the most impactful areas to ultimately enable this approach in the biorefinery. This task overall will enable high-resolution, multi-component, continuous separations at scale, demonstrated on a grand challenge biorefining problem.

BIOMASS FUELS↗
DOE OSTI2025

Fusing Edge Computing with Transport Security by Leveraging the Controller Area Network Transport Security Tracking and Reporting (C-STAR) Unit

Rapid advances in embedded system complexity and capability provides exciting opportunities for transportation security deployment. Manufacturers and developers of these embedded systems continue to provide lower cost and more powerful solutions that can be leveraged by researchers and engineers. Furthermore, deploying these devices at the “edge” of the Internet-of-Things (IoT) infrastructure provides opportunities for highly capable applications in transport security. In an edge computation architecture, the device is co-located at the source of the data in the larger IoT structure – this provides computational capability at the location directly where the data is collected. For shipment transport security, this provides a direct compute node for digestion of data and mitigation actions in real-time. In our application, the vehicle provides a significant amount of this data that can be processed in real-time via the Controller Area Network Transport Security Tracking and Reporting (C-STAR) edge device. Utilization of a computational node located on the vehicle, such as the C-STAR, capitalizes on previously discussed opportunities of edge architectures. In this paper, we will discuss this security solution’s usability, current deployments, and scalability to further applications in transport security. First, we will cover the supported vehicle platforms that can leverage the C-STAR technology. This will be particularly relevant to medium- and heavy-duty vehicles transporting high-risk shipments. Second, we will speak to current deployments of the C-STAR that are ongoing. Finally, we will discuss additional areas for expansion such as maturing the onboard algorithms through continuing collaborations.

Cook, Adian [ORNL] (ORCID:0000000160825395)↗
NASA NTRS2006

Large Deployable Reflectarray Antenna

A report discusses a 7-meter-diameter reflectarray antenna that has been conceived in a continuing effort to develop large reflectarray antennas to be deployed in outer space. Major underlying concepts were reported in three prior NASA Tech Briefs articles: "Inflatable Reflectarray Antennas" (NPO-20433), Vol. 23, No. 10 (October 1999), page 50; "Tape-Spring Reinforcements for Inflatable Structural Tubes" (NPO-20615), Vol. 24, No. 7 (July 2000), page 58; and "Self-Inflatable/Self-Rigidizable Reflectarray Antenna" (NPO-30662), Vol. 28, No. 1 (January 2004), page 61. Like previous antennas in the series, the antenna now proposed would include a reflectarray membrane stretched flat on a frame of multiple inflatable booms. The membrane and booms would be rolled up and folded for compact stowage during transport. Deployment in outer space would be effected by inflating the booms to unroll and then to unfold the membrane, thereby stretching the membrane out flat to its full size. The membrane would achieve the flatness for a Ka-band application. The report gives considerable emphasis to designing the booms to rigidify themselves upon deployment: for this purpose, the booms could be made as spring-tape-reinforced aluminum laminate tubes like those described in two of the cited prior articles.

Fang, Houfei↗
DOE OSTI2018

Y-12 Lean Six Sigma Marketing Plan 2018

The Lean Six Sigma (LSS) organization at Y-12 sponsors the deployment of Performance Enterprise System (PES) and provides continuous improvement facilitation and training for the Y-12 site. The Lean Six Sigma organization is comprised of Subject Matter Experts (SME) who are passionate about continuous improvement and helping organizations improve their processes. The LSS group includes Support Leads, who perform various PES deployment activities, and Black Belts who use Lean, Six Sigma, and other leadership and project management tools to scope, analyze, and expertly facilitate teams on multifaceted improvement projects to meet safety, security, quality, timeliness, and/or cost savings goals. LSS is a group of change agents who help initiate continuous improvement throughout the Y-12 site. The ultimate goal of this marketing plan is to build a consistent, positive, and influential brand throughout Y-12. This brand will provide employees with information about the Lean Six Sigma organization, generate desire for employees to take the Performance Enterprise System training course, and to improve continuously.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

On the Path to SunShot. Advancing Concentrating Solar Power Technology, Performance, and Dispatchability

This report examines the remaining challenges to achieving the competitive concentrating solar power (CSP) costs and large-scale deployment envisioned under the U.S. Department of Energy's SunShot Initiative. Although CSP costs continue to decline toward SunShot targets, CSP acceptance and deployment have been hindered by inexpensive photovoltaics (PV). However, a recent analysis found that thermal energy storage (TES) could increase CSP's value--based on combined operational and capacity benefits--by up to 6 cents/kWh compared to variable-generation PV, under a 40% renewable portfolio standard in California. Thus, the high grid value of CSP-TES must be considered when evaluating renewable energy options. An assessment of net system cost accounts for the difference between the costs of adding new generation and the avoided cost from displacing other resources providing the same level of energy and reliability. The net system costs of several CSP configurations are compared with the net system costs of conventional natural-gas-fired combustion-turbine (CT) and combined-cycle plants. At today's low natural gas prices and carbon emission costs, the economics suggest a peaking configuration for CSP. However, with high natural gas prices and emission costs, each of the CSP configurations compares favorably against the conventional alternatives, and systems with intermediate to high capacity factors become the preferred alternatives. Another analysis compares net system costs for three configurations of CSP versus PV with batteries and PV with CTs. Under current technology costs, the least-expensive option is a combination of PV and CTs. However, under future cost assumptions, the optimal configuration of CSP becomes the most cost-effective option.

14 SOLAR ENERGY↗
DOE OSTI2025

Integrating vehicle trajectory planning and arterial traffic management to facilitate eco-approach and departure deployment

Eco-approach and departure (EAD) enable continuous vehicle motion in urban signalized corridors. Since such a motion can extend to the EAD vehicles’ followers, it makes EAD a promising technology to benefit the traffic flow where automated vehicles and conventional vehicles coexist. Most existing EAD studies envision an ideal setting that neglects real-world operational conditions such as lane changes, multi-movement intersection configuration, partially automated fleet, and/or limited traffic state awareness. This study aims to fill the gap by designing an EAD algorithm considering real-world traffic operation constraints. The proposed algorithm uses a model predictive controller to minimize vehicle speed reduction and variation based on the real-time traffic signal control plan and measured queues at the intersection. The required inputs are readily available at many modern intersections. We observed that the proposed controller’s performance might degrade because of lane-changing maneuvers and lead-left turn traffic signals. These observations motivated our development of a lane change management strategy and a signal control implementation strategy to facilitate the EAD implementation. The lane change management strategies separate the EAD operations and lane-changing maneuvers in time and space. The signal control implementation strategy applies lag-left turn signals to enable EAD operation for both the through and left-turn vehicles. Compared to the non-EAD case, our EAD approach produces 2.5% to 7.8% energy savings while keeping similar intersection mobility. Notably, this approach brings about 2.5% to 3.6% energy savings in a 2% CAV case. This result demonstrates the feasibility of deploying EAD at low connected automated vehicle penetration rates.

Arterial corridor management↗
NASA NTRS2008

Launch Pad 39 Hail Monitor Array System

Weather conditions at Kennedy Space Center are extremely dynamic, and they greatly affect the safety of the Space Shuttles sitting on the launch pads. For example, on May 13, 1999, the foam on the External Tank (ET) of STS-96 was significantly damaged by hail at the launch pad, requiring rollback to the Vehicle Assembly Building. The loss of ET foam on STS-114 in 2005 intensified interest in monitoring and measuring damage to ET foam, especially from hail. But hail can be difficult to detect and monitor because it is often localized and obscured by heavy rain. Furthermore, the hot Florida climate usually melts the hail even before the rainfall subsides. In response, the hail monitor array (HMA) system, a joint effort of the Applied Physics Laboratory operated by NASA and ASRC Aerospace at KSC, was deployed for operational testing in the fall of 2006. Volunteers from the Community Collaborative Rain, Hail, and Snow (CoCoRaHS) network, in conjunction with Colorado State University, continue to test duplicate hail monitor systems deployed in the high plains of Colorado.

Source record↗
DOE OSTI2018

Summertime Aerosol across the North Slope of Alaska Field Campaign Report

The Summertime Aerosol across the North Slope of Alaska U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility field campaign, a collaborative effort between the University of Michigan and Baylor University, was focused on chemically characterizing sources of summertime aerosol impacting the Utqiagvik (Barrow, NSA) and the Oliktok Point (AMF3) ARM sites. This campaign was co-funded by a grant from the National Oceanic and Atmospheric Administration (NOAA, PI: Kerri Pratt, Co-I: Rebecca Sheesley) titled “Assessment of Atmospheric Aerosols Resulting from Oil and Gas Extraction Activities near the North Slope of Alaska”. The ARM field campaign took place on the North Slope of Alaska (NSA) from August 21 to September 30, 2015 and August 12 to September 20, 2016, with filter sampling occurring both years at both the NSA Barrow and AMF3 Oliktok Point sites. Online intensive measurements occurred at Barrow in 2015 and at Oliktok Point in 2016, coordinated with the arrival of the ARM Aerosol Observing System (AOS) in August 2016 at Oliktok Point. During 2015, the University of Michigan deployed the newly constructed aerosol time-of-flight mass spectrometer (ATOFMS), as well as a microanalysis particle sampler (MPS) to collect particles for offline analysis by computer-controlled scanning electron microscopy with energy-dispersive x-ray spectroscopy (CCSEM-EDX). Unfortunately, an issue with the time-of-flight mass spectrometer on the ATOFMS limited the number of particles that produced mass spectra during the 2015 study. This issue was subsequently fixed for the 2016 deployment. During 2016, the ATOFMS was deployed to the AMF3 at the Oliktok Point field site, in addition to a micro-orifice uniform deposition impactor (MOUDI) to collect particles for offline analysis by CCSEM-EDX. Notably, these measurements, to our knowledge, represent the first real-time, single-particle chemical characterization (aerosol mixing state) measurements at Utqiagvik and Oliktok Point. Online aerosol measurements also included: PM2.5 (particulate matter <2.5 μm) black carbon mass concentrations (aethalometer; Baylor) and size-resolved (0.013-20 μm) number concentrations (scanning mobility particle sizer, SMPS, and aerodynamic particle sizer, APS; Michigan). Baylor conducted filter sampling at both the Utqiagvik and Oliktok Point locations during both intensive operational periods (IOPs). Baylor deployed a total suspended particulate matter (TSP) sampler to Oliktok Point, and continuous one-week samples were collected in 2015 for a total of seven samples; during 2016, continuous 3-7 day samples were collected, for a total of 13 filters. Baylor deployed a TSP sampler and a PM1.0 sampler at Utqiagvik, Alaska; continuous 4-7 day filter samples were collected in 2015 for a total of eight samples. To supplement this campaign, PI Sheesley had a simultaneous DOE ARM field campaign at Utqiagvik and Oliktok Point (https://www.arm.gov/research/ campaigns/amf2016bbc), the goal of which was to collected continuous one-week TSP samples at both sites from June 2016 to September 2017. These results provide better context in terms of annual trends and for year-to-year variability and a final report with data was already submitted by PI Sheesley for that project. Analysis by Baylor focuses on TSP samples because of the extremely low PM loading on the PM1.0 sampler. Michigan deployed a three-stage impactor (0.07-5 μm PM collection) at Utqiagvik and a 10-stage impactor (0.056-10 μm PM collection) at Oliktok Point, during the 2015 and 2016 campaigns, respectively.

Arctic processes, North Slope of Alaska, Barrow, O↗
DOE OSTI2026

Expedited desalination permitting enables adaptive planning and water system cost reduction

Seawater desalination is a drought-proof water supply for coastal cities, but widespread development of desalination plants in the U.S. has been limited by both cost and the complexity of permitting processes designed to minimize environmental impact . This work estimates the value of accelerating the permitting timeline without changing environmental or social standards. On average, faster permitting reduces the frequency of desalination plant construction and operation, the overall costs of robust water system operation, the environmental impacts of drought-tolerant water supplies due to shorter duration of plant operation. Expedited permitting allows fundamental changes in how water infrastructure is deployed, facilitating a transition from anticipatory construction and continuous operation of seawater desalination capacity as a redundant drought buffer to just-in-time (i.e. adaptive) deployment of seawater desalination capacity when critical drought thresholds are crossed. We demonstrate the value of expedited desalination permitting in enabling adaptive planning and reducing water system costs using a simple case study in Santa Barbara, CA. We discuss additional forms of adaptive water infrastructure planning as enabled by faster permitting and address their challenges and opportunities. Lastly, we identify synergies between innovation in adaptive planning, innovation in expedited permitting practices, and innovation in water technology.

adaptive planning↗
DOE OSTI2023

A National Infrastructure for Artificial Intelligence on the Grid (NI4AI) (Final Scientific/Technical Report)

Electric utilities have traditionally taken a very pragmatic yet myopic approach with grid sensors and the resulting collected data. Sensors are purchased and deployed to solve a specific, known problem that has risen to sufficient awareness as to justify the effort of deploying sensors and the needed capital investment. This sensor data flows into proprietary software packages with limited functionality intended only to address the initial problem. This approach aligns with the financial incentives of the utility to deploy capital into fixed hardware assets for which the corporations earn a rate of return. This mentality stands in stark contrast to the big data revolution that started nearly 25 years ago with the rise of Google. In this worldview, data is a fundamental business asset; successful organizations collect, store, explore, merge, and exploit as much data as possible to not only solve problems well understood today but also to tackle new problems that will inevitably rise tomorrow. The ARPA-E Open Innovation 2018 project entitled A National Infrastructure for Artificial Intelligence on the Grid or NI4AI for short was designed to demonstrate this alternative paradigm for using data. To do this, the project was composed of three key thrust areas. The first major component deployed a variety of high-frequency grid sensors and captured terabytes of both wide-scale and localized grid measurements, generating high-value datasets for grid research and algorithm development. The second aspect made available PingThings’ PredictiveGridTM, a horizontally scalable, cloud-based data management and AI platform built for time series data to explore and exploit the collected data. Finally, the project fostered a diverse and open research community composed of experts from numerous fields through focused educational content, code sharing, and data science competitions. Shifting away from “single use” sensors and closed data silos within electric utilities is a major benefit to the public at large. This legacy approach to data is incredibly (1) capital intensive (new sensors must be deployed for each new problem and problems tend to arise continuously) and (2) painfully slow (new problems must be identified first and then new sensors must be deployed to collect data to begin to address the issue). The transition to a carbon neutral grid requires a massive transformation of the existing grid infrastructure and will continue to challenge the legacy grid in unforeseen ways. The only way to make the energy transition cost effective is for utilities to abandon this dated data paradigm and adopt more contemporary approaches. NI4AI has shown that it is technically possible and economically feasible to ingest, explore, and exploit grid data collected from even very high frequency sensing, such as continuous point on wave sensors collecting measurements 10,000 times a second. In fact, the PredictiveGrid platform used is commercially available and deployed at several utilities in the United States. Project accomplishments were numerous and included (1) making available a state of the art time series platform to the community, (2) collecting over 520 streams of time series data from grid sensors totaling over 1 trillion grid measurements, and (3) developing and nurturing a community within the industry focused on the use of data to create value for utilities and, ultimately, end consumers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗
NASA NTRS1994

Performance results of cooperating expert systems in a distributed real-time monitoring system

There are numerous definitions for real-time systems, the most stringent of which involve guaranteeing correct system response within a domain-dependent or situationally defined period of time. For applications such as diagnosis, in which the time required to produce a solution can be non-deterministic, this requirement poses a unique set of challenges in dynamic modification of solution strategy that conforms with maximum possible latencies. However, another definition of real time is relevant in the case of monitoring systems where failure to supply a response in the proper (and often infinitesimal) amount of time allowed does not make the solution less useful (or, in the extreme example of a monitoring system responsible for detecting and deflecting enemy missiles, completely irrelevant). This more casual definition involves responding to data at the same rate at which it is produced, and is more appropriate for monitoring applications with softer real-time constraints, such as interplanetary exploration, which results in massive quantities of data transmitted at the speed of light for a number of hours before it even reaches the monitoring system. The latter definition of real time has been applied to the MARVEL system for automated monitoring and diagnosis of spacecraft telemetry. An early version of this system has been in continuous operational use since it was first deployed in 1989 for the Voyager encounter with Neptune. This system remained under incremental development until 1991 and has been under routine maintenance in operations since then, while continuing to serve as an artificial intelligence (AI) testbed in the laboratory. The system architecture has been designed to facilitate concurrent and cooperative processing by multiple diagnostic expert systems in a hierarchical organization. The diagnostic modules adhere to concepts of data-driven reasoning, constrained but complete nonoverlapping domains, metaknowledge of global consequences of anomalous data, hierarchical reporting of problems that extend beyond a single domain, and shared responsibility for problems that overlap domains. The system enables efficient diagnosis of complex system failures in real-time environments with high data volumes and moderate failure rates, as indicated by extensive performance measurements.

Schwuttke, U. M.↗
DOE OSTI2012

CORRTEX Diagnostic Deployment for the SPE-III experiment, 24 July 2012: Fielding Report and Preliminary Data Analysis

The Continuous Reflectometry for Radius vs Time Experiments (CORRTEX) diagnostic system was deployed for the third explosives test in the Source Physics Experiment (SPE) sequence to monitor and verify several conditions of the experiment including the detonation velocity of the explosive package and functioning of explosive initiators. Six distance-marked coaxial cables were installed on the SPE-III explosives canister, and key locations documented through along-cable length measurements and photography. CORRTEX uses electrical-pulse time-domain reflectometry to continuously record the two-way transit time (TWTT) of the cables. As the shock front of the detonation advances, the coaxial cable is shorted or destroyed, and the resulting TWTT also decreases. Interpretation of these changes as a function of TWTT can be converted to positional measurements using known parameters of the cables.

47 OTHER INSTRUMENTATION↗