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At least 1,495 records · Page 83

Unified Communications for Space Inventory Management

To help assure mission success for long-duration exploration activities, NASA is actively pursuing wireless technologies that promote situational awareness and autonomy. Wireless technologies are typically extensible, offer freedom from wire tethers, readily support redundancy, offer potential for decreased wire weight, and can represent dissimilar implementation for increased reliability. In addition, wireless technologies can enable additional situational awareness that otherwise would be infeasible. For example, addition of wired sensors, the need for which might not have been apparent at the outset of a program, night be extremely costly due in part to the necessary routing of cables through the vehicle. RFID, or radio frequency identification, is a wireless technology with the potential for significant savings and increased reliability and safety in space operations. Perhaps the most obvious savings relate to the application of inventory management. A fully automated inventory management system is highly desirable for long-term sustaining operations in space environments. This assertion is evidenced by inventory activities on the International Space Station, which represents the most extensive inventory tracking experience base in the history of space operations. In the short tern, handheld RFID readers offer substantial savings owing to reduced crew time for inventory audits. Over the long term, a combination of improved RFID technology and operational concepts modified to fully utilize the technology should result in space based inventory management that is highly reliable and requires very little crew time. In addition to inventory management, RFID is likely to find space applications in real-time location and tracking systems. These could vary from coarse-resolution RFID portals to the high resolution afforded by ultra-wideband (UWB) RFID. Longer range RFID technologies that leverage passive surface acoustic wave (SAW) devices are being investigated to track assets on a lunar or planetary surface.

Gifford, Kevin K.↗

Evaluating multistation phase picking algorithm phase neural operator (PhaseNO) on local seismic networks

Reliable automatic phase picking is important for many seismic applications. With the development of machine learning approaches, many algorithms are proposed, evaluated and applied to different areas. Many of these algorithms are single station based, while recent proposed methods start to combine surrounding stations into consideration in the problem of phase picking. Among these algorithms, the phase neural operator (PhaseNO) shows promising results on regional data sets comparing to existing algorithms. But there are many use cases for the local seismic networks in our community, therefore in this paper we evaluate the performance of PhaseNO on four different local data sets and compare the results to PhaseNet and EQTransformer. We used both individual phase picking metrics as well as association metrics to illustrate the performance of PhaseNO. By manually reviewing the newly detected events, we find that the PhaseNO model outperforms the single station-based approaches in the local-scale use cases due to its consideration of coherent signals from multiple stations. We also explored PhaseNO’s behaviours when only using one station, as well as gradually increasing the number of stations in the seismic network to better understand its behaviour. Overall, using the off-the-shelf machine learning based phase pickers, PhaseNO demonstrated its good performance on local-scale seismic networks.

58 GEOSCIENCES↗

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↗

Enhanced Component Performance Study: Motor-Operated Valves 1998-2024

This report presents an enhanced performance evaluation of motor-operated valves (MOVs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2024 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trend was identified for MOVs for the most recent 10-year period: • Low-demand MOV frequency of FTOC demands (demands per reactor year). The following decreasing trends were identified for MOVs for the most recent 10-year period: • Low-demand MOV FTOC failure probability • High-demand MOV SO failure rate • Low-demand MOV frequency of FTOC events (failures per reactor year) • High-demand MOV frequency of SO events (failures per reactor year).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Wavelet and Deep-Learning-Based Approach for Generation System Problematic Parameters Identification and Calibration

Accurate models of generation systems are critical for maintaining reliable and secure grid operations. In this paper, a novel and systematic approach is proposed to identify and calibrate the generation system problematic parameters using continuous wavelet transform (CWT) and advanced deep-learning technology. The phasor measurement unit (PMU) data are used through “event playback” to check whether the parameter calibration is required, and if yes, a group of suspicious parameters will be identified as the primary problematic parameter candidates (PPCs). These primary PPCs are randomly perturbed to generate the event playback simulation data, which are used by the CWT and convolutional neural networks (CNNs) to further narrow down the primary PPCs into a smaller set of candidates. Then, the identified candidates are perturbed again to generate massive event playback simulation data for training a parameter calibration neural network. Here, we designed a multi-output neural network structure to find the mappings between the perturbed parameters and the simulation data using both CNN and long short-term memory (LSTM) models. Finally, the well-trained and tested CNN-LSTM model is used to estimate the accurate value of the suspicious parameters with actual PMU measurements. The proposed CNN-LSTM network can accurately and reliably estimate the generation-system problematic parameters, and has better performance when compared to other machine-learning methods, such as the multilayer perceptron network and the conditional variational autoencoder method. The accuracy and effectiveness of the proposed approach have been validated through simulation and real-world data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗

Power Electronics Materials and Bonded Interfaces - Reliability and Lifetime

Advanced packaging technologies are currently being designed and developed by the power electronics industry however, the maximum operating temperature is still limited to 175 degrees Celsius for the silicon carbide devices. Bonded materials such as sintered copper and polymeric materials are potential candidates for high temperature operation, but it is critical to characterize and evaluate its reliability under harsh operating conditions. In this project, we discuss the results of the accelerated experiments conducted on sintered copper and polymeric materials. Additionally, a novel framework to develop the lifetime prediction model of bonded interfaces through employing statistical and machine learning models are described. In this task, scanning acoustic microscope images of bonded interfaces obtained under thermal cycling experiments are used as the data.

ENGINEERING↗

Enhanced Component Performance Study: Air-Operated Valves 1998–2020

This report presents an enhanced performance evaluation of air-operated valves (AOVs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The AOV failure modes considered are failure-to-open/close (FTOC), failure to operate or control (FTOP), and spurious operation (SO). The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following trends were identified for the most recent 10-year period: o Extremely statistically significant increasing trend for the frequency of FTOC demands (demands per reactor year) for low-demand (= 20 demands per year) AOVs o Extremely statistically significant increasing trend for the frequency of FTOC demands for high-demand (> 20 demands per year) AOVs o Highly statistically significant decreasing trend for the failure rate of FTOP for low-demand AOVs o Highly statistically significant decreasing trend for the frequency of FTOP events (failures per reactor year) for low-demand AOVs o Statistically significant decreasing trend for the failure rate of SO for low-demand AOVs o Statistically significant decreasing trend for the frequency of SO events (failures per reactor year) for low-demand AOVs.

99 GENERAL AND MISCELLANEOUS↗

Advanced Solar and Load Forecasting Incorporating HD Sky Imaging (Phase III)

Due to rapidly changing sky conditions, the available solar irradiance for energy generation is subject to wide swings in amplitude. As the market penetration of solar energy continues to increase rapidly, these variations in solar power generation are beginning to have an impact on grid stability and increased wear on power switches. Solar power forecasting plays a critical role in operations for Independent System Operators (ISOs) and utilities. Accurate forecasts help maintain grid reliability, optimize generation from renewables, and reduce operating costs. Of particular interest to the ISOs and utilities are sudden changes in solar irradiance, termed “ramp events,” due to the movement of clouds. One significant impact of ramp events on the grid is additional ancillary service requirements necessary to manage such variability. Ramp events can also cause voltage fluctuations in the distribution grids and trigger actions of automated line equipment (e.g., tap changers), leading to additional maintenance costs. In high penetration solar regions, forecasts must be made for both transmission-connected and distribution-connected resources – either behind the meter or in front of it. Particularly for distributed solar energy resources, forecasting can be a challenge due to the lack of visibility of the energy resource. Brookhaven National Laboratory (BNL) has been working towards nowcasting Global Horizontal Irradiance (GHI) using low-cost technologies for several years now. The Solar NowCasting technology being developed by BNL is a 0 – 30 min solar “nowcasting” technology applicable to a scale covering both large generating facilities and residential, distributed solar installations that relies on a network of ground-based high-definition (HD) cameras and surface pyranometers. GHI forecasts are being produced for both regions using 8 ground-based HD cameras and at least 2 surface pyranometers. When stitched together, the camera images can be used to forecast the impact of clouds on available solar irradiance over a domain of ~50 km 2 . Phase I of the project was the engineering scale up conceptual design stage. Phase II was the initial field test and demonstration, in which the technology was scaled up by a factor of 20 times and successfully demonstrated in eastern Long Island. In Phase III, an additional forecasting network was added in upstate NY and both networks are currently being operated until at least a full year of data is gathered by the Albany network to allow for the collection of sufficient data to evaluate performance against the persistence and smart persistence models using the Solar Arbiter.

14 SOLAR ENERGY↗

BETO 2021 Peer Review - FCIC Task 5 - Preprocessing

In the study of feedstock variability, this presentation specifically looks at preprocessing processes that will created well-defined and homogenous feedstock from variable biomass resources, in the quest to produce homogeneous intermediates that will be converted into market-ready products. The objective of this stage of the project is to develop science-based design and operation principles informed by TEA/LCA that result in predictable, reliable, and scalable performance of preprocessing unit operations (comminution, fractionation, deconstruction, and real-time imaging).

biomass↗

Science Operations on the Lunar Surface - Understanding the Past, Testing in the Present, Considering the Future

The scientific success of any future human lunar exploration mission will be strongly dependent on design of both the systems and operations practices that underpin crew operations on the lunar surface. Inept surface mission preparation and design will either ensure poor science return, or will make achieving quality science operation unacceptably difficult for the crew and the mission operations and science teams. In particular, ensuring a robust system for managing real-time science information flow during surface operations, and ensuring the crews receive extensive field training in geological sciences, are as critical to mission success as reliable spacecraft and a competent operations team.

Eppler, Dean B.↗

High-level fuel fabrication facility designs from discrete-event simulation

Like other industrial processes, the production of metallic nuclear fuels (MNF) requires that fabrication facilities be able to reliably meet production demands, operate efficiently, and adhere to federal and local safety regulations. In turn, the set of design variables employed by such a facility, such as operations policies, infrastructure and machinery purchased, and the type and number of staff hired, directly impact a facility’s ability to satisfy these goals. Therefore, facility designers must carefully determine which set of design variable values optimally satisfies these constraints. In this paper, we explore how values for these high-level design variables, namely hiring requirements, can be determined in the context of nuclear fuel manufacturing through the coupling of physics-based and discrete-event simulation technologies. Using the Versatile Test Reactor (VTR) program as a case study, we demonstrate how SCALE and MCNP nuclear physics model outputs can be integrated into ExtendSim discrete-event simulation (DES) models of the fuel fabrication process to determine the optimal number of staff hired to ensure fuel production goals are met, operations comply with effective dose limit regulations, and overall project costs are reduced.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Neutron irradiation & thermomechanical experiment (NITE) - design

For the reliable long-term operation of fusion power plants, it is crucial to understand and predict the lifetime of materials in use. These materials include all structural and functional materials utilized at the first wall, blanket, magnets, and shielding. The key challenge is, that the harsh environment including high heat fluxes, high thermal stress and stress cycling, neutron irradiation, and sputtering on such materials should not be viewed separately. Currently, the synergistic loads cannot be evaluated experimentally because of the lack of adequate facilities. The purpose of that work is to design a synergetic Neutron Irradiation and Thermomechanical Experiment (NITE) for fusion materials. This design will leverage the existing Advanced-Test-Reactor (ATR), a fission reactor at the Idaho National Laboratory. We also acknowledge that with existing fission reactors the exact fusion condition cannot be created, and the limitations are critically discussed. The combination of neutron irradiation with a high heat flux is the focus. This is realized with an irradiation capsule design that includes a TRISO fueled region inside the capsule to enable a steady-state heat flux on one side of the specimen. In conclusion, the experimental design modeling showed that steady-state heat fluxes of 2.4 MW/m 2 with a thermal gradient of above 250°C can be achieved in a 5 mm thick specimen.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermodynamic parametric analysis of refueling heavy-duty hydrogen fuel-cell electric vehicles

Reliable design and safe operation of heavy-duty hydrogen refueling stations are essential for the successful deployment of heavy-duty fuel cell electric vehicles (FCEVs). Fueling heavy-duty FCEVs is different from light-duty vehicles in terms of the dispensed hydrogen quantities and fueling rates, requiring tailored fueling station design for each vehicle class. In particular, the selection and design of the onboard hydrogen storage tank system and the fueling performance requirements influence the safe design of hydrogen fueling stations. A thermodynamic modeling and analysis are performed to evaluate the impact of various fueling parameters and boundary conditions on the fueling performance of heavy-duty FCEVs. Here, we studied the effect of dispenser pressure ramp rate and precooling temperature, initial tank temperature and pressure, ambient temperature, and onboard storage design parameters, such as onboard storage pipe diameter and length, on the fueling rate and final vehicle state-of-charge, while observing prescribed tank pressure and temperature safety limits. An important finding was the sensitivity of the temporal fueling rate profile and the final tank state of charge to the design factors impacting pressure drop between the dispenser and vehicle tank, including onboard storage pipe diameter selection, and flow coefficients of nozzle, valves, and fittings. The fueling rate profile impacts the design and cost of the hydrogen precooling unit upstream of the dispenser.

08 HYDROGEN↗

US building energy efficiency and flexibility as an electric grid resource

Buildings consume 75% of U.S. electricity; therefore, improving the efficiency and flexibility of building operations could increase the reliability and resilience of the rapidly-changing electricity system. We estimate the technical potential near- and long-term impacts of best available building efficiency and flexibility measures on annual electricity use and hourly demand across the contiguous U.S. Co-deployment of building efficiency and flexibility avoids up to 742 TWh of annual electricity use and 181 GW of daily net peak load in 2030, rising to 800 TWh and 208 GW by 2050; at least 59 GW and 69 GW of the peak reductions are dispatchable. Implementing efficiency measures alongside flexibility measures reduces the potential for off-peak load increases, underscoring limitations on load shifting in efficient buildings. Overall, however, we find a substantial building-grid resource that could reduce future fossil-fired generation needs while also reducing dependence on energy storage with increasing variable renewable energy penetration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NSLS-II longitudinal impedance budget

From the beginning of the NSLS-II project, the vacuum chamber of the NSLS-II storage ring has been optimized to reduce its impedance. The optimization, performed in close collaboration with the Diagnostic, Vacuum, RF, and Mechanical Engineering groups, has been achieved via calculating the impedance of the vacuum chamber components with the use of both analytical and numerical tools, with the numerical computations carried out with the GdfidL code. Fore reliable NSLS-II operation with the total beam current of 500 mA, each component of the vacuum chamber has been individually optimized to minimize the beam-induced heating and to prevent single-bunch and coupled-bunch instabilities. In this study, the impedance calculation and optimization know-how are summarized for all the chamber components, and the total longitudinal impedance budget is analyzed. As a result of this extensive research and engineering effort, the design beam current of 500 mA has been recently accumulated in NSLS-II without any major problem caused by collective effects.

43 PARTICLE ACCELERATORS↗

Assessment of irradiation embrittlement effect on fatigue life of a pressurized-water reactor pressure vessel using the fracture toughness master curve approach

The reactor pressure vessel (RPV) is a critical structural component in pressurized-water reactors, and it is designed to withstand extreme conditions, such as high pressures, elevated temperatures, and prolonged radiation exposure. Ensuring RPV integrity is essential for the safe and reliable long-term operation of nuclear power plants, especially as aging mechanisms such as fatigue and irradiation embrittlement pose increased risks. Fatigue, caused by cyclic thermal and mechanical loading, can lead to crack initiation in localized high-stress regions. Simultaneously, neutron irradiation, particularly in the beltline region, progressively reduces fracture toughness, increasing susceptibility to brittle fracture. These combined effects of fatigue and irradiation embrittlement potentially impact the RPV structural integrity, necessitating fitness-for-service assessments. This study applies the fracture toughness master curve approach to evaluate the impact of irradiation embrittlement on RPV fatigue life. A coupled thermo-mechanical stress analysis identifies critical stress locations under normal service transients, pinpointing regions most vulnerable to fatigue crack initiation and growth. Stress intensity factors for postulated flaws at these locations are calculated, enabling an assessment of fatigue life under irradiated and unirradiated conditions. The results indicate that neutron irradiation embrittlement accelerates the conditions in which a critical crack can form and lead to failure, particularly at lower temperatures. The failure occurs where reduced fracture toughness limits the material’s resistance to crack growth. Axial cracks at nozzle corners are the most life limiting without irradiation, while circumferential cracks demonstrate longer fatigue lives. The findings highlight the importance of incorporating irradiation effects into fatigue life predictions to ensure the long-term structural integrity of RPVs.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Electro-Optic Modulation Using Metal-Free Perovskites

Electro-optic (EO) modulation is of interest to impart information onto an optical carrier. Inorganic crystals—most notably LiNbO 3 and BaTiO 3 —exhibit EO modulation and good stability, but are difficult to integrate with silicon photonic technology. Solution-processed organic EO materials are readily integrated but suffer from thermal degradation at the temperatures required in operating conditions for accelerated reliability studies. Hybrid organic–inorganic metal halide perovskites have the potential to overcome these limitations; however, these have so far relied on heavy metals such as lead and cadmium. Here, we report linear EO modulation using metal-free perovskites, which maintain the crystalline features of the inorganic EO materials and incorporate the flexible functionality of organic EO chromophores. We find that, by introducing a deficiency of cations, we reduce the symmetry in the perovskite crystal and produce thereby an increased EO response. The best-engineered perovskites reported herein showcase an EO coefficient of 14 pm V –1 at a modulation frequency of 80 kHz, an order of magnitude higher than in the nondefective materials. Furthermore, we observe split peaks in the X-ray diffraction and neutron diffraction patterns of the defective sample, indicating that the crystalline structure has been distorted and the symmetry reduced. Density functional theory (DFT) studies link this decreased symmetry to NH 4 + deficiencies. This demonstration of EO from metal-free perovskites highlights their potential in next-generation optical information transmission.

36 MATERIALS SCIENCE↗