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All sources NASA NTRS DOE OSTI

DOE OSTI2022

Advanced Power-Hardware-in-the-Loop Evaluation of Inverter-Based Resources (IBRs)

Power-hardware-in-the-loop evaluation of IBRs has become more and more important as it provides reliable testing results to investigate the real responses of inverters with interconnected systems. A successful laboratory PHIL testing gives confidence of the hardware system to be deployed and de-risk technology integration prior to field deployment. So far, there are two important applications for PHIL evaluation: (1) test stability and functionality of large utility inverters into the system when it interconnects to the distribution systems/microgrids; and (2) test the collective grid service that inverters can provide to the grid. For the first application, the PHIL evaluation has high requirements for the stability and accuracy of the PHIL interface as the close-loop in digital real time simulator (DRTS) should replicate the actual current and voltage dynamics in the inverter. This is challenging because of the delays, sensing errors, nonlinearities of inverters, and hardware bandwidth limitations of the elements in the HIL loop. For the second application, multiple inverters will be tested resulting in multiple PCCs, which naturally causes competing dynamics and oscillations among hardware inverters if traditional PHIL interface is used. Therefore, new PHIL interface should be developed to compromise between stability and accuracy and represent the dispatched grid services for the hardware inverters. In this presentation, we will share our latest work in developing PHIL interface in these two applications to address the two key challenges.

DERMS↗

NASA NTRS1954

An Experimental Investigation of Hollow Turbine Blades for Expandable Jet Engines

An experimental investigation was made to determine the feasibility of using hollow turbine blades in engines designed for short service life. Airfoils were fabricated from sheet material and techniques of welding and brazing attachment were investigated. The airfoils were not intended to be cooled. A principal objective was the reduction of strategic material requirements primarily as a function of direct weight reduction. The materials considered were in the density range of 0.28 to 0.31 pound per cubic inch. Three materials were used for airfoils: N-155, Inconel-X and L-605. These were attached to J47 turbine blade bases and operated to destruction at maximum service conditions of turbine speed and temperature. It was found that L-605 airfoils brazed to suitable bases satisfied the requirements for expendable engines. Service life varied from 11 to 40 hours.

Morgan, W C↗

DOE OSTI2023

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Application of Cable Condition Monitoring Technologies to Assess Age-Related Degradation of Industrial Cables Installed in Harsh Environments

The aging of electrical cables has been the subject of substantial research and development (R&D) projects performed by national and international laboratories, universities, and private organizations for many years. This R&D was conducted to develop guidance, equipment, and techniques to support aging management of in-service cables in industrial facilities such as nuclear power plants, research reactors, waste facilities, and fuel fabrication plants. Through these research efforts, condition monitoring technologies have been developed that can determine the severity of age-related degradation that occurs in industrial cables and insulation polymers during service. This paper summarizes the results of aging assessments that were performed for cables installed in two U.S. nuclear power plants, one a pressurized water reactor and one a boiling water reactor. These cables had been in service for over 40 years and during plant operation were exposed to harsh environmental conditions including elevated temperatures and radiation. For these assessments, a comprehensive series of measurements was performed to assess the aged condition of the cables. These cables came from different manufacturers, were manufactured in different years, and were constructed with a variety of jacket and insulation polymers including chloro-sulfonated polyethylene (CSPE), cross-linked polyethylene (XLPE)/cross-linked polyolefin (XLPO), neoprene, and ethylene propylene rubber (EPR). The goal of these assessments was to determine the current aged condition of the cable polymers and provide an estimate of how long the cable insulation materials could remain exposed to their in-service environmental conditions before reaching their end-of-life condition. Both nuclear power plants have received license renewals to extend their operation from 40 to 60 years, and the utilities need objective evidence to show that critical components such as cables will be able to function safely and reliably during the extended operating period. Furthermore, the results of these assessments showed that the cables exhibited different aged conditions depending on the type of polymers they were constructed with and the environment they were exposed to during service. Some of the cables and insulation polymers showed signs of significant age-related degradation and were estimated to have approximately 5 years of remaining service life. Other cables exhibited no signs of significant age-related degradation and were estimated to have 50 years or more of remaining service life. Using the results of these cable aging assessments, plant personnel were able to (1) determine the overall aged condition of cables and insulation polymers using objective test results, (2) identify aged or degraded cables before they caused operability issues, and (3) avoid unnecessary and costly replacement of cables that can continue to operate safely and reliably.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Importance of Contrast-to-Noise Ratio Sensitivity Function in Nondestructive Evaluation

A reliable nondestructive evaluation (NDE) technique provides minimum 90% probability of detection (POD) with 95% confidence for detection of cracklike flaws of a specific size. This requirement comes from fracture control. Fracture control is a risk assessment and control approach for preventing structural failure of fracture critical hardware during its service life. One of the approaches of fracture control is damage tolerance safe life analysis, which assumes that NDE reliably detectable size flaw may exist in the hardware post nondestructive evaluation. Analysis and/or testing are performed to verify that the hardware will not fail during its service life despite existence of such a flaw. NDE methods are conventionally qualified by probability of detection (POD) demonstration testing to ensure reliable flaw detection. Here, a novel and alternative to POD flaw detection reliability approach that uses contrast-to-noise ratio (CNR) is given. The approach uses CNR sensitivity function (SF) and CNR. CNR SF is the minimum CNR needed for reliable flaw detection as a function of certain flaw indication characteristics. Primary difference between POD approaches and CNR flaw detection reliability approach is resolution of flaw detection system. POD approach does not account for the resolution of the system, while CNR approach accounts for the flaw detection resolution. Resolution is determined from the modulation transfer function (MTF) of the flaw detection system. CNR flaw detection reliability approach emphasizes quantitative assessment of “how well each flaw indication is detected”. Therefore, CNR approach is helpful in reducing number of flaws in the sample used in NDE procedure qualification, resulting in cost and time savings. CNR approach is also a case of multi-hit flaw detection analysis which has better flaw detectability size than conventional single-hit flaw detectability. Thus, CNR approach, where applicable, may be superior to conventional POD approach. The paper is an overview of development of CNR modeling, CNR SF modeling and measurement by the author. The paper gives key references to currently used NDE procedure POD qualification approaches including those specific to CNR and CNR SF development in multi-hit flaw detection in NDE. The paper covers core topics in nondestructive evaluation engineering.

Contrast-to-noise ratio↗

DOE OSTI2020

Predicting System Response at Unmeasured Locations

Traditional techniques to derive dynamic specification for components have a great deal of uncertainty. One of the major sources of uncertainty is that the number of response measurements in the operational system environment is insufficient to determine the component motion. This inadequacy is due to logistical limitations for data recording in field testing and space limitations for accelerometers, strain gages and associated wiring. Available measurements are often some distance from the component and therefore do not represent component motion. Typical straight-line envelopes of these unrepresentative measurements guarantee an increase in the uncertainty. In this paper multiple methods are attempted to expand a sparse set of field test measurements on a system to responses of interest that cannot be measured in the field due to the limitations. Proof of concept is demonstrated on the Modal Analysis Test Vehicle (MATV). The responses of interest, known as “truth responses”, are measured in a system vibration environment along with an optimized sparse set of 30 field responses. Methods to expand the field responses to the truth responses are demonstrated by comparing the acceleration spectral density of the expanded response to the measured response. Two methods utilize a validated finite element model of the MATV. One is developed from purely experiment based frequency response functions of a laboratory pre-test. Finally, these approaches are designed to drastically reduce the uncertainty of the component in-service motion as a basis for developing specifications that are guaranteed to be conservative with a known (instead of unknown) conservatism.

42 ENGINEERING↗

DOE OSTI2022

Introducing the Bacterial and Viral Bioinformatics Resource Center (BV-BRC): a resource combining PATRIC, IRD and ViPR

The National Institute of Allergy and Infectious Diseases (NIAID) established the Bioinformatics Resource Center (BRC) program to assist researchers with analyzing the growing body of genome sequence and other omics-related data. In this report, we describe the merger of the PAThosystems Resource Integration Center (PATRIC), the Influenza Research Database (IRD) and the Virus Pathogen Database and Analysis Resource (ViPR) BRCs to form the Bacterial and Viral Bioinformatics Resource Center (BV-BRC) https://www.bv-brc.org/. The combined BV-BRC leverages the functionality of the bacterial and viral resources to provide a unified data model, enhanced web-based visualization and analysis tools, bioinformatics services, and a powerful suite of command line tools that benefit the bacterial and viral research communities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Insurance in the Operation of Photovoltaic Plants

This paper provides an overview of property and casualty insurance industry functions, insurance terminology descriptions, and special insurance coverage considerations for photovoltaic (PV) system owners, asset managers, operators, PV operation-and-maintenance service providers, utilities, and other parties. The paper includes the results of an analysis of 6 years of property and casualty insurance claims for PV equipment and discusses considerations for purchasing property and casualty insurance for owners and operators of PV systems. PV is a relatively new asset type, and insurance companies are revisiting rates and offerings as actuarial data become available. This paper seeks to inform decisions that optimize the balance of the cost of insurance with enabling benefits to finance, permitting, utility connections, and the operation of PV plants.

14 SOLAR ENERGY↗

DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

Historically, cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation that is designed to operate on live cables up to 1000 volts and with a bandwidth of 48 MHz. Initial evaluation by the Pacific Northwest National Laboratory (PNNL) of the Live Wire system indicated that a broader bandwidth (BW) SSTDR may be better for many kinds of flaws. This led PNNL to develop an SSTDR laboratory instrument suitable for tests up to 500 MHz bandwidth. Testing on energized cables is also desirable for online monitoring systems so an inductive clamshell coupler was developed that allows energized cables to be tested up to at least 5 kV and likely higher voltage levels. Dielectric spectroscopy and tan delta testing plus various laboratory destructive tests were included in this data acquisition campaign directed to feed a machine learning (ML) study. With these kinds of developments, online energized cable tests may be possible with industrial adoption of such hardware advances but it will be completely impractical to have highly skilled data analysts continually examine these complex signals for indications of damage or compromised conditions. If online testing is to be implemented in new test hardware, it must be accompanied by software that can interpret the signals and alert plant operators of changing or degraded conditions. The thermally aged, shielded cable investigated here was separately treated for ML analysis. Visual analysis of electrical data showed generally increasing peaks where the cable entered and exited the oven. These peaks were not exactly aligned with expected locations, but these differences were attributed to velocity of propagation calibration errors. Only supervised ML was applied to the thermally aged data as this data was only available shortly before the committed publication date of this report. The supervised ML was structured to divide the 0 to 70-day responses as ‘normal’ from 0 to 35 days or ‘anomalous’ from 36 to 70 days, based on cable tensile elongation at break (EAB) insulation characterization. Using 80% of the data for training and 20% for testing, the supervised ML predicted normal versus anomalous was 70% accurate. Important conclusions include: • Accuracy to predict the presence of cable damage is improved from the 2023 effort by more training data. Weighted accuracies for comparisons among the instruments ranged from 67 to 89 % for unsupervised ML and 71 to 99% for supervised ML. • Based on the synthetic data tests, the unsupervised models are more generalizable to unseen anomalies. The Multi-Layer Perceptron classifier (MLP) model reported as high as 99.7% accuracy on the test data, but this dropped to 58.3% when tested on the synthetic data. In contrast, the unsupervised Pointwise model only achieved 89.7% accuracy on the experimental data but reported 78.3% accuracy on the synthetic data. • The best anomaly indicators are higher frequency (400 MHz BW) FDR data. Other tests may be interesting but for this study, this was the best predicter.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

SSTDR and FDR Detection of Un-Energized and Energized Cable Anomalies Including Thermal Degradation Using Machine Learning

36 MATERIALS SCIENCE↗

DOE OSTI2023

Spread Spectrum Time Domain Reflectometry (SSTDR) and Frequency Domain Reflectometry (FDR) for Detection of Cable Anomalies Using Machine Learning

Cables are initially qualified for nuclear power plant use for 40 years. As plants extend their operating license to 60 and 80 years, continued use of these cables must shift to a performance-based approach since it is cost prohibitive to completely replace cables that are likely still capable of performing their design function. A variety of cable tests are available and are commonly applied during outages when the cables can be taken out of service. Frequency domain reflectometry (FDR) is one of these test methods that is being more broadly accepted and used because it not only detects anomalies along the cable with a low-voltage signal that does not stress the cable insulation, but the technique also locates the anomalies. This supports follow-up local inspection and local repair or partial replacement of a damaged cable segment. Currently, FDR testing is only applied to cables that are taken out of service since the test instrument would be damaged by operational voltages. A related technology that has found some acceptance in the aircraft and rail industry is spread spectrum time domain reflectometry (SSTDR). This technology has been implemented with a custom commercial instrument by LiveWire Innovation Inc. that is designed to operate on live cables up to 1000 volts. One of the main conclusions of a previous effort was that cable reflectometry plots can be difficult for humans to analyze due to baseline noise, low or noisy anomaly response peaks, or large responses from cable ends. Detection of cable anomalies for many of these frequencies and test conditions was challenging for manual analysis. This presented an ideal opportunity for ML analysis to distinguish undamaged cable indications from anomalous cable indications. This research discusses application of machine learning (ML) to reflectometry cable test methods. The goal was to assess feasibility to distinguish undamaged cable reflectometry responses from damaged or anomalous cable reflectometry responses. The assessment considered the 3 instruments, multiple frequency bandwidths from each instrument, multiple cable anomalies and test conditions, and both supervised and unsupervised ML approaches. Although approaches and analysis methods were not identical or directly comparable, both outputs were encouraging. The unsupervised prediction weighted accuracy was assessed by instrument and by frequency. It performed better at high frequencies with the highest prediction accuracy of 0.84 for the higher frequency FDR, 0.79 for the 48-MHz LiveWire SSTDR, and 0.77 for 300-MHz PNNL SSTDR. The initial weighted accuracy average across all frequencies for using supervised ML was 0.56 to 0.68. The supervised analysis was repeated with noisier training data removed resulting in weighted accuracies of 0.69 to 0.87. These weighted accuracies are not directly comparable due to differences in the supervised and unsupervised analysis details but do indicate an encouraging trend. Even with limited and unbalanced data, strong prediction accuracies seem encouraging for further work including more data under a wider range of conditions.

42 ENGINEERING↗

NASA NTRS1971

Adaptive multisatellite systems for aeronautical services.

The use of satellite systems to provide operational communications and ATC services to aircraft flying the oceanic routes has been the subject of considerable interest recently. Since most of the link factors are functions of geometry and the aircraft traffic density varies with time, the satellite power needed to meet the communication demand varies considerably in an oceanic area as a function of both location and time. An adaptive system that tailors the use of system resources to the needs of the user can result in an additional system capacity improvement by a factor of between two and three. Results of studies conducted to date indicate that simple implementation of adaptive techniques in aeronautical satellite systems is feasible. Study is continuing in this area and on the application of satellite multibeam techniques to gain even further increase in capacity.

Bisaga, J. J.↗

NASA NTRS1976

Learning/cost-improvement curves

Review guide is an aid to manager or engineer who must determine production costs for components, systems, or services. Methods are described by which manufacturers may use historical data, task characteristics, and current cost data to estimate unit prices as function of number of units to be produced.

Delionback, L. M.↗

NASA NTRS1984

Commercial space services

An overview of space service opportunities as identified by a Wyle Laboratories' research team is given. Through the use of a baseline space scenario, a variety of space hardware, services, and commercial activities are identified and related on a time-phased basis. A model is presented to relate the potential functions of government and the private sector in a commercialized space environment during the period 1984 to 2004. Barriers, incentives and key issues are likewise identified and addressed to aid in the implementation of private sector activities for spacerelated programs. Broader awareness, legislative actions, incentive development and benefit analyses are considered in the presentation. The time-phased plan provides a useful planning and management tool, allows broader communication, and supports overall space commercialization program assessment.

Christensen, D. L.↗

NASA NTRS1991

SMA applications in an innovative multishot deployment mechanism

An innovative Deployment and Retraction hinge Mechanism (DARM) in the frame of a technological program is examined. The mechanism includes two restraint/release devices, which enable it to be stable in its stowed or deployed position while sustaining all associated loads, and to carry its payload by remote command. The main characteristics of the DARM are as follows: deployment and retraction movements are spring actuated; the available amount of functional sequences is almost unlimited; and no use of electrical motors is made. These features were accomplished by: the application of a special kinematic scheme to the mechanical connection between the spring motor and the swivel head arm; and the use of shape memory alloys (SMA) actuators for both release and spring recharge functions. DARM is thus a mechanism which can find many applications in the general space scenario of in-orbit maintenance and servicing. In such a frame, the DARM typical concept, which has a design close to very simple one-shot deployment mechanisms, has a good chance to replace existing analog machines. Potential items that could be moved by DARM are: booms for satellite instruments; antenna reflector tips; entire antenna reflectors; and solar panels.

Stella, D.↗

NASA NTRS1990

Recent technical advances in general purpose mobile Satcom aviation terminals

A second general aviation amplitude companded single sideband (ACSSB) aeronautical terminal was developed for use with the Ontario Air Ambulance Service (OAAS). This terminal is designed to have automatic call set up and take down and to interface with the Public Service Telephone Network (PSTN) through a ground earth station hub controller. The terminal has integrated RF and microprocessor hardware which allows such functions as beam steering and automatic frequency control to be software controlled. The terminal uses a conformal patch array system to provide almost full azimuthal coverage. Antenna beam steering is executed without relying on aircraft supplied orientation information.

Sydor, John T.↗