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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

The DESI instrument control systems: status and early testing

The Dark Energy Spectroscopic Instrument (DESI) is a new instrument currently under construction for the Mayall 4-m telescope at Kitt Peak National Observatory. It will consist of a wide-field optical corrector with a 3.2 degree diameter field of view, a focal plane with 5,000 robotically controlled fiber positioners and 10 fiber-fed broad-band spectrographs. The DESI Instrument Control System (ICS) coordinates fiber positioner operations, interfaces to the Mayall telescope control system, monitors operating conditions, reads out the 30 spectrograph CCDs and provides observer support and data quality monitoring. In this paper, we summarize the ICS design, review the current status of the project and present results from a multi-stage test plan that was developed to ensure the system is fully operational by the time the instrument arrives at the observatory in 2019.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Automatic Calibration and Health Monitoring of Infrastructure Sensors

Smart transportation infrastructure relies on networks of heterogeneous sensors - cameras, radars, and lidars - continuously monitoring traffic conditions. However, executing the initial spatial calibration of multiple sensors and the subsequent health monitoring presents significant operational challenges. Environmental factors, mechanical vibrations, and gradual drift cause spatial misalignment, degrading fusion performance and tracking accuracy. Traditional calibration approaches require manual intervention with specialized targets or survey equipment, resulting in service interruptions and high maintenance costs. This work presents an automated framework for initial calibration and continuous health monitoring without human intervention or service disruption. Our approach addresses two critical problems: (1) detecting when sensors become miscalibrated during operation, and (2) automatically re-establishing spatial alignment using only operational traffic data. The health monitoring component analyzes measurement innovations - differences between sensor observations and predicted object states - to detect systematic biases indicative of calibration drift. By computing bias magnitude, directional consistency, and rejection rates, the system identifies miscalibrations as small as 0.5 meters. Unlike traditional methods requiring known calibration targets, our diagnostic operates continuously on live traffic observations, enabling early detection before fusion quality degrades. The automatic recalibration algorithm leverages overlapping sensor fields-of-view and temporal correlation of vehicle observations. Using graph-based optimization, the system automatically discovers which sensor pairs observe common regions, estimates pairwise spatial transformations using RANSAC-based robust estimation, and jointly optimizes all sensor poses through bundle adjustment. The framework handles practical deployment challenges, including different sensor sampling rates (1-10 Hz), varying installation positions, unknown orientations, and limited overlap regions (>10%). When approximate sensor positions are available from installation surveys (+/-1m accuracy), the algorithm additionally estimates sensor orientations, refining both position and rotation to sub-meter and sub-degree accuracy. We validate the framework on multi-hour traffic datasets from six heterogeneous sensors with sampling rates ranging from 1 Hz to 10 Hz. Results demonstrate successful calibration even with sparse overlap (<20%) and automatic detection of miscalibrations exceeding 0.8 meters. This work enables a "deploy-and-forget" sensor infrastructure that maintains calibration autonomously, reducing maintenance costs while improving tracking accuracy. The techniques generalize beyond transportation to any multi-sensor monitoring application requiring robust spatial alignment, including smart cities, industrial monitoring, and surveillance systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Utilizing rare earth elements as tracers in high TDS reservoir brines in CCS applications

In this paper we report the result of research associated with the testing of a procedures necessary for utilizing natural occurring trace elements, specifically the Rare Earth Elements (REE) as geochemical tracers in Carbon Capture and Storage (CCS) applications. Trace elements, particularly REE may be well suited to serve as in situ tracers for monitoring geochemical conditions and the migration of CO₂-charged waters within CCS storage systems. We have been conducting studies to determine the efficacy of using REE as a tracer and characterization tool in the laboratory, at a CCS analogue site in Soda Springs, Idaho, and at a proposed CCS reservoir at the Rock Springs Uplift, Wyoming. Results from field and laboratory studies have been encouraging and show that REE may be an effective tracer in CCS systems and overlying aquifers. In recent years, a series of studies using REE as a natural groundwater tracer have been conducted successfully at various locations around the globe. Additionally, REE and other trace elements have been successfully used as in situ tracers to describe the evolution of deep sedimentary Basins. Our goal has been to establish naturally occurring REE as a useful monitoring measuring and verification (MMV) tool in CCS research because formation brine chemistry will be particularly sensitive to changes in local equilibrium caused by the addition of large volumes of CO₂. Because brine within CCS target formations will have been in chemical equilibrium with the host rocks for millions of years, the addition of large volumes of CO₂ will cause reactions in the formation that will drive changes to the brine chemistry due to the pH change caused by the formation of carbonic acid. This CO₂ driven change in formation fluid chemistry will have a major impact on water rock reaction equilibrium in the formation, which will impart a change in the REE fingerprint of the brine that can measured and be used to monitor in situ reservoir conditions. Our research has shown that the REE signature imparted to the formation fluid by the introduction of CO₂ to the formation, can be measured and tracked as part of an MMV program. Additionally, this REE fingerprint may serve as an ideal tracer for fluid migration, both within the CCS target formation, and should formation fluids migrate into overlying aquifers. However application of REE and other trace elements to CCS system is complicated by the high salt content of the brines contained within the target formations. In the United States by regulation, in order for a geologic reservoir to be considered suitable for carbon storage, it must contain formation brine with total dissolved solids (TDS) > 10,000 ppm, and in most cases formation brines have TDS well in excess of that threshold. The high salinity of these brines creates analytical problems for elemental analysis, including element interference with trace metals in Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) (i.e. element mass overlap due to oxide or plasma phenomenon). Additionally, instruments like the ICP-MS that are sensitive enough to measure trace elements down to the parts per trillion level are quickly oversaturated when water TDS exceeds much more than 1,000 ppm. Normally this problem is dealt with through dilution of the sample, bringing the water chemistry into the instruments working range. However, dilution is not an option when analyzing these formation brines for trace metals, because trace elements, specifically the REE, which occur in aqueous solutions at the parts per trillion levels. Any dilution of the sample would make REE detection impossible. Therefore, the ability to use trace metals as in situ natural tracers in high TDS brines environments requires the development of methods for pre-concentrating trace elements, while reducing the salinity and associated elemental interference such that the brines can be routinely analyzed by standard ICP-MS methods. As part of the Big Sky Carbon Sequestration Project the INL-CAES has developed a rapid, easy to use process that pre-concentrates trace metals, including REE, up to 100x while eliminating interfering ions (e.g. Ba, Cl). The process is straightforward, inexpensive, and requires little infrastructure, using only a single chromatography column with inexpensive, reusable, commercially available resins and wash chemicals. The procedure has been tested with synthetic brines (215,000 ppm or less TDS) and field water samples (up to 5,000 ppm TDS). Testing has produced data of high quality with REE capture efficiency exceeding 95%, while reducing interfering elements by > 99%.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Launch Complex 34, SWMU CCO542022 DNAPL Source Zone Operations, Maintenance, and Monitoring, Site-Wide Long-Term Monitoring, and Hot Spot 6 Air Sparge System Annual Performance Monitoring Report Cape Canaveral Space Force Station, Florida

This Annual Performance Monitoring Report (PMR) for the Dense Non-Aqueous Phase Liquid (DNAPL) Source Zone (DSZ), Site-Wide Long-Term Monitoring (LTM), and Hot Spot (HS) 6 Air Sparge (AS) System presents the results of Year 13 operation of the hydraulic containment (HC) Interim Measure (IM), the results of performance monitoring direct-push technology (DPT) sampling and monitoring well sampling conducted in the DSZ, results of the biennial site-wide LTM event, and the results of operations and performance sampling of the HS 6 AS IM at Launch Complex 34 (LC34), located at Cape Canaveral Space Force Station (CCSFS), Florida. This site has been designated Solid Waste Management Unit (SWMU) CC054 under the Kennedy Space Center (KSC) Resource Conservation and Recovery Act (RCRA) Corrective Action Program. For the site-wide biennial LTM event, a total of 55 monitoring wells were sampled for volatile organic compounds (VOCs) in February 2023 and one well was sampled for polychlorinated biphenyls (PCBs) in December 2022. One well planned for VOC sampling was found to be destroyed and could not be sampled (CW0002). The LTM wells are screened in two lithologic zones: Layer 1 (0 to 25 feet below land surface [bls]) and Layer 2 (25 to 30 ft bls), and are located in the outlying areas of LC34 to monitor groundwater conditions within the Low-Concentration Plume (LCP), defined as concentrations exceeding Groundwater Cleanup Target Levels (GCTLs), and the High-Concentration Plume (HCP), defined as concentrations exceeding Natural Attenuation Default Concentrations (NADCs). Results from the biennial sampling event indicated overall plume stability and delineation for the plume, which extends over 300 acres. The operational period for Year 13 of the HCS was from April 1, 2022 to March 31, 2023. Operational runtime for the system was 90 percent during Year 13, with downtime events attributed to planned maintenance, system repairs, and power outages. As of March 31, 2023, a total of 313,673,241 cumulative gallons of groundwater containing 88,337 pounds of VOCs have been removed by the HCS. Influent concentrations of trichloroethene (TCE) have decreased since startup from approximately 280,000 μg/L (January 2010) to 12,000 μg/L (March 2023). During the reporting period, all effluent concentrations from the HCS (aqueous and vapor) were below regulatory reporting limits, indicating the system continues to operate as intended. Performance monitoring was conducted in December 2022 within the DSZ to evaluate TCE contamination. Groundwater samples were collected via DPT at nine locations, consistent with previous events between 2017 and 2021. Full vertical profile sampling was completed at each DPT from 8 to 98 feet bls, at 5-foot intervals. The DPT performance monitoring results are summarized in this PMR. The results revealed TCE remains at concentrations greater than 11,000 μg/L in the DSZ (1-percent solubility, indicative of DNAPL) at eight of the nine DPT locations and at depths ranging from 8 to 98 feet bls. In addition to DPT sampling, groundwater samples were collected from deep monitoring wells in the DSZ area (Layers 7 and 8) in December 2022 to verify vertical delineation. Layer 7/8 monitoring well results were non-detect in December 2022, with exception of three wells (IW0162, IW043D2, and IW044D2), where TCE, cis-1,2-dichloroethene (cDCE), and/or vinyl chloride (VC) were detected above GCTLs. These wells are screened 105 to 115 feet bls, which is below the existing recovery well capture zone. TCE was first detected in IW0162 in December 2021 and has since been sampled at least monthly to monitor TCE concentrations. The maximum TCE concentration during this operational period was 15,000 μg/L at IW0162 in March 2023. Because of the increased TCE concentrations in this well, a new recovery well (RW21D), screened 86 to 106 feet bls, was installed in January 2023 and incorporated into existing HCS operations. The HS 6 AS IM was initiated in 2018 with 160 AS wells, and expanded in 2019 with an additional 140 AS wells. Quarterly performance monitoring was reduced to semi-annual in 2020. The HS 6 AS system remained operational during the reporting period covered under this report. The results of the HS 6 system operation and semi-annual performance monitoring are summarized in this report. Semi-annual monitoring results collected in April and October 2022 show concentrations of contaminants of concern (cDCE, trans-1,2-dichloroethene, and vinyl chloride) are generally decreasing and not impacting the surface water drainage canal, indicating the HS 6 IM is meeting objectives. A Phase Two Expansion of the HS 6 AS IM was recently completed. As of the date of this report, the expansion became operational in August 2023 and the first quarter of monitoring was conducted in November 2023. Details of the construction, start-up, and performance monitoring will be included in a future Annual PMR. Overall, the tasks associated with Year 13 operation of the HC IM, operation of the HS 6 AS IM, and biennial site-wide sampling were performed in accordance with recommendations included in the previous 2021 LC34 (Year 12) annual report. Evaluation of results from the HC IM and HS 6 IM show that these systems are operating as designed and meeting performance objectives. Results from the site-wide biennial LTM program also show that the overall network of monitoring wells is adequate to continue monitoring plume-wide conditions.

Complex 34↗
NASA NTRS1976

Skylab/EREP application to ecological, geological, and oceanographic investigations of Delaware Bay

The author has identified the following significant results. Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for mapping coastal land use; inventorying wetlands vegetation; monitoring tidal conditions; observing suspended sediment patterns; charting surface currents; locating coastal fronts and water mass boundaries; monitoring industrial and municipal waste dumps in the ocean; and determining the size and flow direction of river, bay, and man-made discharge plumes. Film products were visually analyzed to identify and map ten land use and vegetation categories at a scale of 1:125,000. Thematic maps were compared with CARETS land use maps, resulting in classification accuracies of 50 to 98%. Digital tapes from S192 were used to prepare thematic land use maps. The resolutions of the S190A, S190B, and S192 systems were 20-40m, 10-20m, and 70-100m, respectively.

Klemas, V.↗
DOE OSTI2018

Insight into Thermal Aging of Jacket-bonded Ethylene-propylene Rubber Cable Insulation

Electrical cables are integral to nuclear power plant operation and control during power generation, during planned outages, and during design basis events. Polymeric insulation and jacketing used in cable construction does age over time as a function of environmental stresses including heat, moisture, and radiation. Degradation of polymer mechanical properties can lead to breaks in the insulation and consequent electrical shorting. In this work we consider the thermal aging behavior of one of the two most common insulation polymer classes in nuclear power plants, ethylene-propylene rubber (EPR), both as an independent material and within a cable in which the EPR is bonded to a chlorinated polyethylene (CPE) jacket. Understanding the changes in these two materials with aging, both independently and in concert, will allow the establishment of aging lifetime curves and enable the development of effective non-destructive methods for tracking the condition of installed cables composed of similar material systems. Additional and more effective methods for monitoring the condition of installed cables are needed as a technical basis for continued safe use of aging cables in long term operation and to minimize operating costs for cable aging management through better informed retain/repair/replace decisions.

Light Water Reactors, electrical cables, aging, EP↗
NASA NTRS1981

Environmental charging effects monitors for operational satellites

A set of three instruments has been developed that can provide early detection of potentially dangerous geomagnetic substorm conditions, and monitor the spacecraft response. The set consists of three instruments: (1) a 'surface voltage sensor' that measures the characteristic energy of collected electrons or ions from +100 to -20,000 volts; (2) a 'nanoammeter' or logarithmic current density sensor that measures local electron flux by measuring currents from 10 to the -9th to 10 to the -5th A; and (3) a 'transient events counter' that counts the spurious pulses from electrostatic discharges that are coupled into the spacecraft wiring harness. Performance characteristics, specifications, and application of these instruments are discussed.

Sturman, J. C.↗
DOE OSTI2016

Improving online risk assessment with equipment prognostics and health monitoring

The current approach to evaluating the risk of nuclear power plant (NPP) operation relies on static probabilities of component failure, which are based on industry experience with the existing fleet of nominally similar light water reactors (LWRs). As the nuclear industry looks to advanced reactor designs that feature non-light water coolants (e.g., liquid metal, high temperature gas, molten salt), this operating history is not available. Many advanced reactor designs use advanced components, such as electromagnetic pumps, that have not been used in the US commercial nuclear fleet. Given the lack of rich operating experience, we cannot accurately estimate the evolving probability of failure for basic components to populate the fault trees and event trees that typically comprise probabilistic risk assessment (PRA) models. Online equipment prognostics and health management (PHM) technologies can bridge this gap to estimate the failure probabilities for components under operation. The enhanced risk monitor (ERM) incorporates equipment condition assessment into the existing PRA and risk monitor framework to provide accurate and timely estimates of operational risk.

active and passive components↗
DOE OSTI2019

System for kick detection during a drilling operation

The disclosure provides a kick detection system for use during a drilling operation where wellbore kick warnings are provided based on indications of standoff conditions in a compensated instrument system. The system provides a warning of a potential kick condition by analyzing a current instrument compensation against a time series of past compensations, in order to monitor whether conditions within the standoff region of the wellbore are unexpectedly changing. The system comprises a source, a short-spaced detector, and a long-spaced detector, and a processor receives the short-spaced signal and the long-spaced signal, compensates the long-spaced signal, and generates standoff data reflecting the corrections applied to the long-range signal. The processor determines and maintains the standoff data as a time series and periodically compares a recent data point to a moving average in order to evaluate indications of a potential well kick.

Rose, Kelly K.↗
DOE OSTI2021

Online Monitoring System for Concrete Structures Affected by Alkali-Silica Reaction

This report presents a comprehensive study of developing ultrasonic wave and acoustic emission (AE) techniques for long-term monitoring of alkali-silica reaction (ASR) development in concrete. Small, medium, and full-scale concrete specimens were cast, conditioned, and monitored for various periods, from at least one year to 2.4 years. The reactive concrete specimens contain coarse or fine reactive aggregates to study the effects of different types of reactive aggregates. Confinements were also designed to simulate the 2-dimensional confinement effects of reinforcement in the shield building of nuclear power plants. The concrete specimens were stored in a environmental chamber with high humidity and high temperature to accelerate the ASR development. The ultrasonic monitoring data shows high sensitivity to ASR development and could detect cracking initiation well before visible surface cracks occurred. However, the linear ultrasonic analysis based on wave velocity is strongly affected by temperature variation. Therefore, a nonlinear ultrasonic method was proposed to measure thermally induced nonlinear acoustic responses of concrete (thermal modulation of ultrasonic wave). The measured nonlinear acoustic parameter shows a high correlation with ASR expansion across specimens with different reactive aggregates and confinement conditions. The same conclusion was obtained from nonlinear resonance tests on small concrete prisms. Compared to the linear acoustic methods, the nonlinear tests show high sensitivities to ASR damage from internal microcracking initiation at the early stage to visible cracks at the late stage of ASR. The attributes of the thermal modulation of nonlinear ultrasonic method include high sensitivity, immunity to temperature effects, and strong correlation with ASR expansion, which demonstrate great potentials of the nonlinear ultrasonic method for diagnosis of ASR damage and prediction of concrete deterioration process. Acoustic emission is a passive sensing technique for damage assessment, and access to only one surface is needed even for thick and heavily reinforced elements such as the walls utilized for nuclear shield building. Additionally, relatively few sensors are required to monitor the progression of the damage process. Results indicate that the AE data can be related to the damage rating index, which is a petrography-based means of assessing damage due to ASR in reinforced concrete. Furthermore, AE is capable of detecting ASR damage long before surface cracking is visually noticeable. Boundary conditions play in important role in the progression of ASR damage and differences in boundary conditions are reflected in the AE data. Entropy based data assessment methods provide a means to assess the damage state, and convolutional neural network based data assessment provided a means to assess the damage state in real-time. Results indicate that artificial neural network models may be used as a means to predict volumetric expansion based on AE data.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2010

Correlate Life Predictions and Condition Indicators in Helicopter Tail Gearbox Bearings

Research to correlate bearing remaining useful life (RUL) predictions with Helicopter Health Usage Monitoring Systems (HUMS) condition indicators (CI) to indicate the damage state of a transmission component has been developed. Condition indicators were monitored and recorded on UH-60M (Black Hawk) tail gearbox output shaft thrust bearings, which had been removed from helicopters and installed in a bearing spall propagation test rig. Condition indicators monitoring the tail gearbox output shaft thrust bearings in UH-60M helicopters were also recorded from an on-board HUMS. The spal-lpropagation data collected in the test rig was used to generate condition indicators for bearing fault detection. A damage progression model was also developed from this data. Determining the RUL of this component in a helicopter requires the CI response to be mapped to the damage state. The data from helicopters and a test rig were analyzed to determine if bearing remaining useful life predictions could be correlated with HUMS condition indicators (CI). Results indicate data fusion analysis techniques can be used to map the CI response to the damage levels.

Dempsey, Paula J.↗
NASA NTRS1978

Skylab/EREP application to ecological, geological, and oceanographic investigations of Delaware Bay

Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for; (1) mapping coastal land use; (2) inventorying wetlands vegetation; (3) monitoring tidal conditions; (4) observing suspended sediment patterns; (5) charting surface currents; (6) locating coastal fronts and water mass boundaries; (7) monitoring industrial and municipal waste dumps in the ocean; (8) determining the size and flow direction of river, bay and man-made discharge plumes; and (9) observing ship traffic. Film products were visually analyzed to identify and map ten land-use and vegetation categories at a scale of 1:125,000. Digital tapes from the multispectral scanner were used to prepare thematic maps of land use. Classification accuracies obtained by comparison of derived thematic maps of land-use with USGS-CARETS land-use maps in southern Delaware ranged from 44 percent to 100 percent.

Klemas, V.↗
NASA NTRS2013

Distributed Prognostics and Health Management with a Wireless Network Architecture

A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the prognostics task is over, and after appropriate actions have been taken, all CEs return to their original default configuration. Wireless technology-based implementation would ensure more flexibility in terms of sensor placement. It would also allow more sensors to be deployed because the overhead related to weights of wired systems is not present. Distributed architectures are furthermore generally robust with regard to recovery from node failures.

Goebel, Kai↗
NASA NTRS1973

Flight monitor for jet engine disk cracks and the use of critical length criterion of fracture mechanics

A disk crack detector is discussed which is intended to operate under flight conditions. It monitors the disk rim for surface cracks emanating from the blade root interface. An eddy current type sensor, with a remotely located capacitance/conductance bridge and signal analyzer, can reliably detect a simulated crack 3 mm long. The sensor was tested on a spinning turbine disk at 540 C. Tests indicate that the system is useful at disk rim velocities to 460 m/sec. By using fracture mechanics, it is shown for Inconel 718 th at a crack operating under a rim stress of 34 x ten to the 7th power N/sqm has a critical length of 18 mm.

Barranger, J. P.↗
DOE OSTI2016

Summary Describing Integration of ERM Methodology into Supervisory Control Framework with Software Package Documentation; Advanced Reactor Technology Milestone: M4AT-16PN2301052

This project involved the development of enhanced risk monitors (ERMs) for active components in Advanced Reactor (AdvRx) designs by integrating real-time information about equipment condition with risk monitors. Health monitoring techniques in combination with predictive estimates of component failure based on condition and risk monitors can serve to indicate the risk posed by continued operation in the presence of detected degradation. This combination of predictive health monitoring based on equipment condition assessment and risk monitors can also enable optimization of maintenance scheduling with respect to the economics of plant operation. This report summarizes PNNL’s multi-year project on the development and evaluation of an ERM concept for active components while highlighting FY2016 accomplishments. Specifically, this report provides a status summary of the integration and demonstration of the prototypic ERM framework with the plant supervisory control algorithms being developed at Oak Ridge National Laboratory (ORNL), and describes additional case studies conducted to assess sensitivity of the technology to different quantities. Supporting documentation on the software package to be provided to ONRL is incorporated in this report.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2016

Microgravity Simulation Facility (MSF)

The Microgravity Simulator Facility (MSF) at Kennedy Space Center (KSC) was established to support visiting scientists for short duration studies utilizing a variety of microgravity simulator devices that negate the directional influence of the "g" vector (providing simulated conditions of micro or partial gravity). KSC gravity simulators can be accommodated within controlled environment chambers allowing investigators to customize and monitor environmental conditions such as temperature, humidity, CO2, and light exposure.

Microgravity↗
DOE OSTI2025

Open data sets for assessing photovoltaic system reliability

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types is used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, image inspection and module materials, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driven research. Our aim is to enhance data utilization and publication among researchers and industry professionals, promoting a deeper understanding of the role of data in enhancing the performance and durability of PV systems.

14 SOLAR ENERGY↗