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System Study: High-Pressure Safety Injection 1998-2020

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 69 U.S. commercial nuclear reactors. Demand, run hours, and failure data from calendar years 1998–2020 for selected components were obtained from the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS), formerly the INPO Consolidated Events Database (ICES). The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPSI results.

99 GENERAL AND MISCELLANEOUS↗

System Study: High-Pressure Safety Injection 1998-2024

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 62 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from calendar years 1998 to 2024 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period and yearly estimates for system unreliability are provided for the entire active period. Statistically significant decreasing trends were identified in both the HPSI system start-only unreliability and 24-hour mission unreliability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

System Study: High-Pressure Safety Injection 1998-2022

This report presents an unreliability evaluation of the high-pressure safety injection system (HPSI) at 62 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hours, and failure data from calendar years 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. Highly statistically significant increasing trends were identified in both the HPSI system start-only unreliability and 8-hour mission unreliability.

99 GENERAL AND MISCELLANEOUS↗

Safety Benefits Assessment for Accident Tolerant Fuels in Consideration of Steam Generator Tube Degradation Using Dynamic Event Tree Analysis

Accident tolerant fuel (ATF) is expected to delay or prevent core damage by providing additional coping time under accidents involving loss of core cooling. The effect of extended coping time may vary depending on the plant response to accidents. Age-related component degradation that deteriorates plant performance over time could have an impact on the actual advantages of ATF. The potential safety benefits of two near-term ATF candidates, including Cr-coated Zr cladding and FeCrAl cladding, are assessed for a 2-in. loss-of-coolant accident with failed high-pressure safety injection using the dynamic event tree (DET) approach considering possible stress corrosion cracking of steam generator (SG) tubing under aging. The DET approach allows likelihood quantification of accident sequences leading to core damage, including stochastic variation of system response and human actions during accident mitigation. The safety benefits of the selected ATF claddings in terms of additional coping time and the core damage frequency reduction rate under specified accident situations were quantitatively estimated. The results show that the deployment of the two selected ATF claddings is expected to lead to longer coping times and lower core damage frequency due to the wider safety margin to peak cladding temperature they provide. The safety advantages would be greater as SG tube degradation proceeds. Thus, the two ATF candidates would lead to less severe consequences in terms of likelihood of core damage and susceptibility to the SG tube degradation than UO 2 -Zr fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Chemochromic Hydrogen Leak Detectors

At NASA, hydrogen safety is a key concern for space shuttle processing. Leaks of any level must be quickly recognized and addressed due to hydrogen s lower explosion limit. Chemo - chromic devices have been developed to detect hydrogen gas in several embodiments. Because hydrogen is odorless and colorless and poses an explosion hazard, there is an emerging need for sensors to quickly and accurately detect low levels of leaking hydrogen in fuel cells and other advanced energy- generating systems in which hydrogen is used as fuel. The device incorporates a chemo - chromic pigment into a base polymer. The article can reversibly or irreversibly change color upon exposure to hydrogen. The irreversible pigment changes color from a light beige to a dark gray. The sensitivity of the pigment can be tailored to its application by altering its exposure to gas through the incorporation of one or more additives or polymer matrix. Furthermore, through the incorporation of insulating additives, the chemochromic sensor can operate at cryogenic temperatures as low as 78 K. A chemochromic detector of this type can be manufactured into any feasible polymer part including injection molded plastic parts, fiber-spun textiles, or extruded tapes. The detectors are simple, inexpensive, portable, and do not require an external power source. The chemochromic detectors were installed and removed easily at the KSC launch pad without need for special expertise. These detectors may require an external monitor such as the human eye, camera, or electronic detector; however, they could be left in place, unmonitored, and examined later for color change to determine whether there had been exposure to hydrogen. In one type of envisioned application, chemochromic detectors would be fabricated as outer layers (e.g., casings or coatings) on high-pressure hydrogen storage tanks and other components of hydrogen-handling systems to provide visible indications of hydrogen leaks caused by fatigue failures or other failures in those systems. In another type of envisioned application, chemochromic detectors of this type could be optoelectronically instrumented for monitoring to provide measured digital indications of color changes indicative of the presence of hydrogen.

Roberson, Luke↗

Modeling injection-induced fault slip using long short-term memory networks

Stress changes due to changes in fluid pressure and temperature in a faulted formation may lead to the opening/shearing of the fault. This can be due to subsurface (geo)engineering activities such as fluid injections and geologic disposal of nuclear waste. Such activities are expected to rise in the future making it necessary to assess their short- and long-term safety. Here, a new machine learning (ML) approach to model pore pressure and fault displacements in response to high-pressure fluid injection cycles is developed. The focus is on fault behavior near the injection borehole. To capture the temporal dependencies in the data, long short-term memory (LSTM) networks are utilized. To prevent error accumulation within the forecast window, four critical measures to train a robust LSTM model for predicting fault response are highlighted: (i) setting an appropriate value of LSTM lag, (ii) calibrating the LSTM cell dimension, (iii) learning rate reduction during weight optimization, and (iv) not adopting an independent injection cycle as a validation set. Several numerical experiments were conducted, which demonstrated that the ML model can capture peaks in pressure and associated fault displacement that accompany an increase in fluid injection. The model also captured the decay in pressure and displacement during the injection shut-in period. Further, the ability of an ML model to highlight key changes in fault hydromechanical activation processes was investigated, which shows that ML can be used to monitor risk of fault activation and leakage during high pressure fluid injections.

58 GEOSCIENCES↗

Ground Test Stand Development for One-step Electrochemical Production of High-Pressure Oxygen

NASA designed a test rig, High-Pressure Oxygen Generation Assembly (HPOGA) to test a novel method of electrolysis as an alternative technology to the state-of-the-art Oxygen Generation Assembly (OGA) currently on the International Space Station (ISS). This approach involves utilizing a specialized electrolysis cell stack designed to both generate and compress high-pressure oxygen up to 3600 PSIG. The design eliminates the need for an external compressor and hydrogen separator, streamlining the oxygen generation process. HPOGA tests the viability of an electrolysis cell stack for extended life usage. Within the system, there are several key subsystems: nitrogen, high/low pressure oxygen, hydrogen, water recirculation, and water injection. The water injection subsystem supplies deionized (DI) water to a centralized reservoir for consumption. Subsequently, a water recirculation loop transfers the DI water across the cathode side of the electrolysis cell stack with constant flow rate. The result is a supply of hydrogen in the water loop and oxygen accumulation on the anode side of the cell stack. Hydrogen is evaporated out as part of the hydrogen sub-system which also measures hydrogen/oxygen concentration for safety. The oxygen subsystem is responsible for managing high pressure oxygen, O2 exhaust, and conducting hydrogen/oxygen concentration measurements. The nitrogen subsystem serves dual functions, purging the hydrogen/oxygen subsystems, and regulating pressure in both high/low-pressure O2 sections via pneumatic back pressure regulators. Various sensors monitor pressure, temperature, humidity, gas concentration and flow rate in each subsystem. This paper presents the design and testing of a comprehensive test stand, which serves to operate and functionally verify the performance of the electrolysis cell while offering valuable lessons learned.

electrolysis↗