In-flight detection of non-catastrophic equipment failures in a space vehicle guidance- and-navigation system.
Noncatastrophic guidance and navigation equipment failures detected in flight, using two separate statistical tests
ORBITAL RENDEZVOUS↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Equipment Failure Analysis
Tennessee Eastman uses NASTRAN to minimize lost production by pinpointing the causes of equipment failures and preventing recurrences. An example of the program's utility involves a large centrifugal fan which developed cracks during start-ups and shutdowns. This information prompted redesign of the fan. Tennessee Eastman has made extensive use of NASTRAN, both as failure analysis tool and as an aid in redesigning production hardware.
Source record↗
Detecting Process Equipment Failures Using Acoustic Data and Machine Learning
Nuclear power plant (NPP) process equipment such as fans, motors, valves, and pumps generate frequent or continuous noise, and deviations from the normal operational sounds made by this equipment can indicate potential issues. These deviations can be identified via automated acoustic anomaly detection, which involves using acoustic sensors (i.e., microphones) alongside detection algorithms to continuously monitor for changes in acoustic signatures. This task is made challenging by the substantial background noise that exists, such as operators opening and closing doors, manipulating valves, and conversing—in addition to typical plant noises. In collaboration with a nuclear power utility partner, this effort assessed the efficacy of acoustic anomaly detection when using a specific acoustic sensor that compresses data into a fixed set of features that are transferable over a standard Internet of Things communication protocol, thereby improving usability but potentially degrading detection performance. Two methods of performing automated acoustic anomaly detection were evaluated: one-class support vector machine (OC-SVM) and isolation forest (iForest). To enable the use of high-quality acoustic data encompassing both normal and anomalous conditions, the study utilized the publicly available Malfunctioning Industrial Machine Investigation and Inspection dataset, which includes real measured acoustic sensor data for a range of equipment types, model numbers, and signal-to-noise ratios (SNRs), along with a benchmark set of detection results. Using this dataset, the methods were tested and then compared against the benchmark results. The results indicated that although the specific acoustic sensor did not enable as rich a feature set extraction, the proposed methods with the limited feature set performed just as well. This provides solid justification for both the methods and the use of the proposed acoustic sensor.
46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
Determining Mission Effects of Equipment Failures
NASA plans call for long duration deep space missions with human crews. Because of light-time delay and other considerations, increased autonomy is needed. Crews on next-generation missions will likely be small, perhaps with as few as four members. A small crew is not likely to possess the full range of expertise needed to deal with unexpected failures and anomalies. Applied artificial intelligence technologies have developed decision support tools with the potential to fill the gap, but these tools need to be integrated to provide a smooth operational capability. In this paper we describe such an integration involving anomaly detection, diagnosis, system effect propagation, and plan repair.
Morris, Paul↗
EDP outputs of Surveyor failure reporting system - Ground equipment.
Electronic data processing system for Surveyor ground equipment failure reporting system
Daush, A. A., Jr.↗
Powering the Blue Economy Foundational Research & Development Topics Reliability for Marine Energy Power Systems
Ocean observing platforms are deployed across the world’s oceans to collect meteorological and oceanographic data. Current technology makes use of solar panels and battery banks to provide power to these platforms, which can be challenging at high latitudes due to lack of solar insolation and cold temperatures. Marine renewable energy (MRE) generation offers a potential improvement in consistent power generation throughout the year for this use on ocean observation buoys. This report analyzes existing reliability of high latitude coastal weather buoys and tsunami detection buoys to determine performance standards that MRE generation sources must meet to become viable power sources for these remote systems. Using measurements recorded from the U.S. National Data Buoy Center’s coastal weather buoys and tsunami detection buoys, the analysis calculated the historic data availability – or the percentage of time a measurement is recorded – to evaluate the reliability of ocean observation buoys. The results show that coastal weather buoys operate at 74% data availability and the tsunami detection systems operate at an average 72% data availability. The results describe the total reliability of the system, including many different types of failures not associated with the power system such as mooring failures or equipment failures caused by extreme weather. Power system outages may only account for a small portion of the system failures. Reliability is an important design criterion for the power system of ocean observation platforms. Future power systems that would be designed for these buoys, such as an MRE generator, need to have a minimum reliability of 72% and 74% to meet the overall performance of the weather buoys and tsunami buoys, respectively. However, power system reliability likely needs to be much higher than overall system reliability, so that power system outages do not negatively impact the overall performance of the buoy.
42 ENGINEERING↗
Underground Coal Mining
Computer program models coal-mining production, equipment failure and equipment repair. Underground mine is represented as collection of work stations requiring service by production and repair crews alternately. Model projects equipment availability and productivity, and indicates proper balance of labor and equipment. Program is in FORTRAN IV for batch execution; it has been implemented on UNIVAC 1108.
Hill, G. M.↗
Substation Secondary Asset Health Monitoring and Management System (SSHM)
Electric Power Group, LLC (EPG) was awarded DOE OE0000850 to design, develop, and demonstrate a real-time software application for substation secondary equipment health monitoring and management at host utility American Electric Power (AEP), a cost share partner. This project addresses the need for monitoring substation equipment health and providing operators with tools to identify and take pre-emptive action to avoid catastrophic equipment failure. By monitoring synchrophasor data in real time, data anomalies that indicate potential asset failure can be detected and alerts can be sent to operators in time to take corrective actions. EPG developed two data driven algorithms to identify abnormal equipment signature patterns as well as a method using substation linear state estimation (SLSE). The software has been deployed on hardened PC’s and tested and validated for cost share partner AEP’s substations - 138kV and 765 kV. The SSHM software has been accepted by AEP and final demonstration of DOE - OE0000850 for AEP and DOE was successfully completed on March 17th, 2020. EPG developed the Substation Secondary Asset Health Monitoring (SSHM) Platform to analyze equipment failure signatures in PMU data and alert substation personnel when pre-emptive inspection, repairs and other actions are warranted to prevent potential catastrophic failures. This is the first system that automatically monitors the health of substation secondary assets and alerts users to emerging failures using synchrophasor measurements. SSHM uses high resolution PMU data from PTs, CTs, and CCVTs to analyze equipment signatures and identify anomalies that are precursor indicators of potential equipment failure. When an anomaly is detected, there is a likelihood of potential failure of monitored equipment, the system alerts the user with visual alarms including alarm trend charts and indicator lights on a oneline diagram of the substation.
24 POWER TRANSMISSION AND DISTRIBUTION↗
The Corrective Maintenance Paradigm Shift at Hanford's Tank Farms - 20077
Hanford's Tank Farms facilities have been used to safely store waste for over 70 years, with the first single-shell tanks being constructed in 1943. Tank Farm facilities consist of 149 single-shell tanks, 28 double-shell tanks, an evaporator facility, and wastewater treatment facilities. Tank Farm facilities are aging, with a tremendous corrective maintenance burden on the Tank Farm contractor. The mission of Tank Farm facilities is soon changing from waste storage to waste staging for the Hanford Waste Treatment and Immobilization Plant (WTP). WTP operations will demand a significant increase in Tank Farm facility operations, in which corrective maintenance outage windows will shrink drastically. This realization has forced the Tank Farm contractor to consider a paradigm shift in Tank Farm facilities Maintenance planning, and the use of reliability Engineering tools. The Tank Farm Production Operations Engineering Cognizant System Engineering (CSE) organization has led the way in motivating this paradigm shift. This shift has been realized through the use of: 1) technical exchange with other Department of Energy (DOE) contractors to develop improvements in the CSE program, 2) a shift from the use of lagging to leading system health indicators, and 3) a Plant Health Committee to unite Engineering, Operations, and Maintenance personnel toward a productive maintenance strategy. The CSE organization has held several technical exchanges with other DOE contractors to discuss CSE concepts, and how to better maintain aging infrastructure. The technical exchange with other contractors has greatly reduced the time required to make improvements in the Tank Farm CSE program. Other DOE contractors have already faced issues surrounding aging infrastructure, and have vast experience in improving the reliability and usable life of structures and components in nuclear facilities. The past CSE program used lagging health indicators to determine the health of systems. The key lagging indicator used to determine system health was availability, which is the percentage of time that a facility was ready for operation compared to the time the facility was demanded for operation. Availability was a good indicator of health in the waste storage mission of Tank Farms, where safe storage was the most important function of the facility, and where maintenance outage windows were typically long-duration. In current and future operations, outage windows are reducing, resulting in the need for much more reliable systems. Systems that have had high availability may suddenly become inoperable due to a failed component or sub-system. In several instances, the use of availability as an indicator of system health failed to predict system/equipment failure before its occurrence. In discussions with other DOE contractors, a set of reliability tools, including leading indicators of health, has been implemented in the CSE program. This primarily involves the use of failure modes and effects analysis and the study of equipment failure to develop system monitoring plans that focus on trending data to detect oncoming equipment failure ahead of time. In addition, the use of a Plant Health Committee has added significantly to the paradigm shift from a corrective maintenance philosophy to the use of predictive and preventive maintenance. The Plant Health Committee is a chartered team consisting of Engineering, Operations, and Maintenance personnel. CSEs use this forum to present the results of their performance monitoring, including the presentation of health via leading health indicators. The most positive aspect of this committee is the communication that it creates within these critical organizations. The Operations and Maintenance organization benefit from focusing maintenance on the reliability-centered focus provided by Engineering. Engineering benefits from the operational experience of the Operations organization and from the failure data that can be provided by Maintenance personnel. The continued use of the Plant Health Committee is expected to further decrease maintenance outage times, in better support of oncoming 24/7 operations. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Surface and Airborne Monitoring Technology for Detecting Geologic Leakage in a CO 2 -Enhanced Oil Recovery Pilot, Anadarko Basin, Texas
Surface and airborne gas monitoring programs are becoming an important part of environmental protection in areas favorable for subsurface storage of carbon dioxide. Understanding structural architecture and its effects on the flux of fluids, specifically CO 2 and CH 4 , in the shallow subsurface and atmosphere is helping design and implement next generation monitoring technologies, including unmanned aerial vehicles (UAVs). An important aspect of this research is using subsurface fracture data to inform the design of flight pathways for UAVs in the Farnsworth Oil Unit of the Anadarko Basin. The target zone for CO 2 storage and enhanced oil recovery in the Farnsworth Oil Unit is in the upper Morrow sandstone at subsurface depths greater than 2,000 m. Field study reveals that sandstone and chert in the High Plains Aquifer contain numerous joints that provide crucial insight into aquifer architecture and subsurface flow pathways. Properties of more than 1,700 joints were measured in the field and in high-resolution satellite images. Two distinctive joint systems interpreted as a conjugate pair were identified in the study area. Joint spacing follows a log-normal statistical scaling rule. These fractures appear to be the product of an E-NE regional compressive stress and may have a significant effect on flow in the High Plains Aquifer system. Based on the results of this research, design of UAV flight paths should be oblique to fractures in a way that maximizes the likelihood of CO 2 and CH 4 flux from of systematic joints and cross joints. Detection of leaks either from subsurface seal failures or surface equipment problems is important to insure that stored CO 2 is not being lost to the atmosphere. In the case of surface leaks, costs go up and injection efficiency goes down. Surface leaks are often short term caused by seal leaks, pop off valves, or other equipment failure modes. In either case, CO 2 is released to the atmosphere. This projects primary goal was to explore the use of low cost sensors coupled with the appropriate hardware and software to produce a low cost system capable of detecting both long and short term leaks. In addition, an aerial system was designed to measure the CO 2 and CH 4 distributions above the surface. Both the ground and UAV based systems were designed, tested and deployed in the Farnsworth field.
02 PETROLEUM↗
Hanford Direct Feed Low Activity Waste Program Throughput Optimization Through Modeling - 18587
The Direct Feed Low Activity Waste (DFLAW) program at Hanford allows for the early treatment of tank wastes years earlier than previously planned. Operational Research (OR) modeling is being used to provide invaluable insight into how complex and integrated processes will operate. The DFLAW OR models are used to help optimize the design and operation of the integrated system. The DFLAW OR models include the processes and real-life complexities involved in the day-to-day operation of the systems and equipment, and can predict key performance characteristics including throughput, mission timescale, equipment and labor utilization, lag storage and capacity requirements. The DFLAW OR models also have the in-built capability to simulate random events such as equipment failures. Adding random variability to models introduces a real-life element to model results. For example, OR modeling breakdown analysis of equipment failure and restoration times may inform specific improvements to a design and plant operation, including areas where the provision of spare (duty/standby) equipment would prove beneficial; the optimum number and capacity of lag storage tanks (for waste intermediate storage, reagents, etc.); operational issues, including scheduling constraints, labor resource constraints, effect of shift schedules (e.g. days only, extended shifts, 24/7),, maintenance strategies, including planned maintenance, equipment upgrades, on-hand spare part stockholding, etc. At Hanford, standalone OR models to date, have been used to help identify key operational issues and improve the design and operation of individual systems within the Tank Farms, Low Activity Waste Pretreatment System (LAWPS), Low Activity Waste (LAW) Vitrification and Effluent Management Facility (EMF) and Integrated Disposal Facility (IDF), logistics and infrastructure, 222-S laboratory [References 1 and 2] including: - Identification of critical spares including transfer pumps; - Underpin size and number of lag storage tanks to maintain continuous LAW feed to the LAW melters; - Underpin sample turnaround times at the 222-S Laboratory (e.g. feed prequalification and evaporator campaign samples) and determine how targets can be achieved without impacting waste feed delivery to LAWPS and the LAW Vitrification Facility; - Determine operational strategy required at IDF including shift schedules and sizes and the number of ILAW transporters that can support DFLAW throughput; - Identification of lag storage management strategies for glass formers, reagents, other consumables due to delivery distance and delays due to bad weather; and - Truck delivery badging needs to support 24/7 operation and management of shift in/out times required to reduce congestion. An Integrated DFLAW OR model has been developed and combines the standalone OR models such that integrated throughput and availability can be assessed from a program perspective. The Integrated OR model will provide a more detailed understanding of the interactions between Tank Farms, LAWPS, LAW VIT and IDF such that key bottleneck areas can be identified and ensure improvements are focused. Examples of future improvements that may be considered include identification of critical spare parts, required on-site maintenance capabilities, shift scheduling, and craft and labor availability. The methods, results and insights derived by DFLAW OR modeling efforts are expected to provide useful applications to other projects that involve combinations of mechanical handling, chemical processing, waste treatment/packaging or environmental remediation operations. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Development of the IPRO-zone for fire PSA and its applications
A PSA analyst has been manually determining fire-induced component failure modes and modeling them into the PSA logics. These can be difficult and time-consuming tasks as they need much information and many events are to be modeled. KAERI has been developing the IPRO-ZONE (interface program for constructing zone effect table) to facilitate fire PSA works for identifying and modeling fire-induced component failure modes, and to construct a one top fire event PSA model. With the output of the IPRO-ZONE, the AIMS-PSA, and internal event one top PSA model, one top fire events PSA model is automatically constructed. The outputs of the IPRO-ZONE include information on fire zones/fire scenarios, fire propagation areas, equipment failure modes affected by a fire, internal PSA basic events corresponding to fire-induced equipment failure modes, and fire events to be modeled. This paper introduces the IPRO-ZONE, and its application results to fire PSA of Ulchin Unit 3 and SMART(System-integrated Modular Advanced Reactor). (authors)
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Binary Power Plant CO2 Life Cycle Emissions Including Isobutane Fugitive Emission
Geothermal energy production has one of the lowest life cycle CO2 emission factors (~ 15 g-CO2/kWh) for plants producing electricity (Hondo, 2005). This life cycle factor includes indirect emissions from plant construction as well as ongoing operations such as additional well drilling and equipment replacement. Not included in this calculation are direct emissions from geothermal power production. Geothermal flash plants emit CO2 at rates related to the reservoir concentration. Binary plants report “near zero” emissions of high global warming potential gases because of their closed loop system design. Binary plants use working fluids to drive the turbine generators and leakage of these working fluids have not yet been quantified. To assess the working fluid emissions from geothermal power production using an Organic Rankine Cycle, reported isobutane emissions were accessed for 3 California binary plants from the Great Basin Unified and Imperial County Air Pollution Control Districts as well as the California Air Resource Board. Each binary plant used in this study has been operating for more than 25 years. From the data, two types of isobutane emissions were accounted for over a 15 month period: ‘normal’ equipment leakage and equipment breakdown emissions. This preliminary analysis of working fluid emissions from these plants suggest that if a binary plant has equipment failures, the majority of the isobutane releases can be due to these events. The results indicate that a well maintained binary plant releases approximately 0.13 g-Isobutane/kWh where as a plant with equipment failures releases approximately 6 g-Isobutane/kWh. Assuming a greenhouse warming potential of 3 for isobutane, these emission values become 0.4 and 18 g-CO2e/kWh (where CO2e is the CO2 equivalent effect). The direct operation isobutane leakage for a well maintained binary plant does not significant increase the life cycle CO2 emission factor whereas a plant with significant equipment issues can effectively double the life cycle CO2 emissions. This limited data set suggests that when direct CO2e fugitive emission are add to the indirect CO2 emissions, the total CO2 emissions from binary power plants are equivalent or less than nuclear, as well as other renewables power production such as wind and solar.
15 GEOTHERMAL ENERGY↗
A Flexible and Generic Functional Mock-up Unit Based Threat Injection Framework for Grid-interactive Efficient Buildings: A Case Study in Modelica
Grid-interactive efficient buildings (GEBs) have been considered as an important asset to support the power grid reliability by utilizing the demand flexibility offered by GEBs. GEBs are enabled by advances in sensors and controls, and the communication between building equipment, whole buildings, and the grid. The integration of different building technologies and network-based communication system makes GEBs vulnerable to passive threats such as equipment failure and active threats such as cyber-attacks. Modeling and simulation is an effective way to evaluate the impact of threats on the system performance. This paper proposes a generic and flexible threat injection framework for commonly-used building energy simulators such as EnergyPlus and Modelica to support threat modeling and evaluation. This framework leverages functional mock-up unit (FMU) to develop a general modeling interface for threat injection and simulation. A numerical case study using Modelica as a building energy simulator is conducted to demonstrate the capability of the framework for supporting single/multiple-order threat modeling and simulation of a GEB. Four threats and their combinations are injected on a Modelica-based threat-free building energy and control system, including operating supply fan at its full speed, remotely cycling the chiller on and off, blocking the chiller from receiving the chilled water supply temperature setpoints, and hijacking the global zone air temperature setpoint. Simulation results show that the cyber-attack that leads to short-term signal blocking has small effects on the system operation due to the "self-healing" feature of the heating, ventilation, and air-conditioning (HVAC) interactive control system. The threat that takes control of resetting the global zone air temperature setpoints has the most adverse impact on the system energy use, peak power demand, thermal comfort and the provision of demand flexibility. The combination of four threats have aggregative effects on the system but the effects are less than the additive effects of the individual threat.
Fu, Yanyang↗
Alternating Direction Decomposition with Strong Bounding and Convexification (ADDSBC) for Solving Security Constrained AC Unit Commitment Problems
This project aims to develop efficient and robust computational methods for solving the security-constrained unit commitment and alternating current optimal power flow problem (SC-UC-ACOPF). The SC-UC-ACOPF problem is at the center of the short-term operation of the U.S. Power Grid. It is solved every week, every day, and every 10 minutes to plan for the optimal action of electricity generation and consumption by minimizing the generation cost and maintaining power system reliability against potential disruptions of equipment failures. In mathematical terms, SC-UC-ACOPF is a challenging large-scale mixed-integer nonlinear optimization model. This means that the decisions involve both discrete variables, e.g. the turning on and off of generators and switching of transmission lines and transformers, and continuous decisions, e.g. the amount of energy generated by each generator and the power flows in the power grid. The physics of the power flow is described by nonlinear equations involving real and reactive power and bus voltages. Another key feature is the large number of contingencies, i.e. the system needs to stay reliable in face of failure of any one equipment, such as transmission lines and generators. The U.S. power grids are extremely complicated and large scale with more than 5,000 generators, 50,000 buses, and 100,000 high-voltage transmission lines, making the SC-UC-ACOPF a very large-scale computation challenge. The research developed in this project aims to solve the SC-UC-ACOPF problems in the three timescales, i.e. weekly, daily, and every 10-min. The proposed computational methods are built on a principled algorithmic approach of decomposition and penalization. More specifically, the algorithm develops spatial and temporal decomposition by exploiting the strong temporal coupling and weak spatial coupling of the UC problem and the complementary feature, i.e. weak temporal coupling and strong spatial coupling of the ACOPF problem. The algorithm also leverages recent progresses in strong convex relaxation of ACOPF. A unique feature of the proposed approach is that it generates a valid, global upper bound on the optimal maximum profit. In this way, a global optimality gap is available to measure the quality of the solution. To further speed up computation, the research team has developed a plethora of effective heuristics to strengthen the iterative penalty-based decomposition framework. For instance, a heuristic is developed to construct inner approximations of the time coupling constraints within the time decoupled problems. Contingencies are pre-screened and low-rank matrix computation is exploited to find the almost unique solution to each contingency. A novel heuristic for line switching is proposed and tested with positive impacts on instances where line switching is beneficial. Taking a systematic approach and carefully handling every detail of the problem pays off. The TIM-GO’s performance throughout the trials and the final event was stellar. TIM-GO garnered the second highest total prize money and is ranked in the top three positions across all categories of comparison.
97 MATHEMATICS AND COMPUTING↗
Optimization models for integrated biorefinery operations
Variations of physical and chemical characteristics of biomass lead to an uneven flow of biomass in a biorefinery, which reduces equipment utilization and increases operational costs. Uncertainty of biomass supply and high processing costs increase the risk of investing in the US’s cellulosic biofuel industry. We propose a stochastic programming model to streamline processes within a biorefinery. A chance constraint models system’s reliability requirement that the reactor is operating at a high utilization rate given uncertain biomass moisture content, particle size distribution, and equipment failure. The model identifies operating conditions of equipment and inventory level to maintain a continuous flow of biomass to the reactor. Furthermore, the sample average approximation method approximates the chance constraint and a bisection search-based heuristic solves this approximation. A case study is developed using real-life data collected at Idaho National Laboratory’s biomass processing facility. An extensive computational analysis indicates that sequencing of biomass bales based on moisture level, increasing storage capacity, and managing particle size distribution, increases utilization of the reactor and reduces operational costs.
09 BIOMASS FUELS↗
Plant growth during the Greenhouse II experiment on the Mir orbital station
We carried out three experiments with Super Dwarf wheat in the Bulgarian/Russian growth chamber Svet (0.1 m2 growing area) on the Space Station Mir. This paper mostly describes the first of these NASA-supported trials, began on Aug. 13, 1995. Plants were sampled five times and harvested on Nov. 9 after 90 days. Equipment failures led to low irradiance (3, then 4 of 6 lamp sets failed), instances of high temperatures (ca. 37 degrees C), and sometimes excessive substrate moisture. Although plants grew for the 90 d, no wheat heads were produced. Considering the low light levels, plants were surprisingly green, but of course biomass production was low. Plants were highly disoriented (low light, mirror walls?). Fixed and dried samples and the root module were returned on the U.S. Shuttle Atlantis on Nov. 20, 1995. Samples of the substrate, a nutrient-charged zeolite called Balkanine, were taken from the root module, carefully examined for roots, weighed, dried, and reweighed. The Svet control unit and the light bank were shipped to Moscow. An experiment validation test (EVT) of plant growth and experimental procedures, carried out in Moscow, was highly successful. Equipment built in Utah to measure CO2, H2O vapor, irradiance, air and leaf (IR) temperature, O2, pressure, and substrate moisture worked well in the EVT and in space. After this manuscript was first prepared, plants were grown in Mir with a new light bank and controller for 123 d in late 1996 and 39 days in 1996/1997. Plants grew exceptionally well with higher biomass production than in any previous space experiment, but the ca. 280 wheat heads that were produced in 1996 contained no seeds. Ethylene in the cabin atmosphere was responsible. c2002 Published by Elsevier Science Ltd on behalf of COSPAR.
Mir Project↗
Light Water Reactor Sustainability Program Advanced Seismic Soil Structure Modeling
Risk calculations should focus on providing best estimate results, and associated insights, for evaluation and decision-making. Specifically, seismic probabilistic risk assessments (SPRAs) are intended to provide best estimates of the various combinations of structural and equipment failures that can lead to a seismic induced core damage event. However, in some instances the current SPRA approach has large uncertainties, and potentially masks other important events (for instance, it was not the seismic motions that caused the Fukushima core melt events, but the tsunami ingress into the facility). SPRA’s are performed by convolving the seismic hazard (this is the estimate of all likely damaging earthquakes at the site of interest) with the seismic fragility (the conditional probability of failure of a structure, system, or component given the occurrence of earthquake ground motion). In this calculation, there are three main pieces to seismic risk quantification, 1) seismic hazard and nuclear power plants (NPPs) response to the hazard, 2) fragility or capacity of structures, systems and components (SSC), and 3) systems analysis. Two areas where NLSSI effects may be important in SPRA calculations are, 1) when calculating in-structure response at the area of interest, and 2) calculation of seismic fragilities (current fragility calculations assume a lognormal distribution for probability of failure of components). Some important effects when using NLSSI in the SPRA calculation process include, 1) gapping and sliding, 2) inclined seismic waves coupled with gapping and sliding of foundations atop soil, 3) inclined seismic waves coupled with gapping and sliding of deeply embedded structures, 4) soil dilatancy, 5) soil liquefaction, 6) surface waves, 7) buoyancy, 8) concrete cracking and 9) seismic isolation The focus of the research task presented here-in is on implementation of NLSSI into the SPRA calculation process when calculating in-structure response at the area of interest. The specific nonlinear soil behavior included in the NLSSI calculation presented in this report is gapping and sliding. Other NLSSI effects are not included in the calculation. The results presented in this report document initial model runs in the linear and nonlinear analysis process. Final comparisons between traditional and advanced SPRA will be presented in the September 30th deliverable.
54 ENVIRONMENTAL SCIENCES↗