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NASA NTRS1992

Manned testing in a simulated space environment

A view of the facility and operational requirements involved in performing a manned thermal vacuum test is presented. The requirements fall into two major categories. The first category deals with placing the suited crewmen in a hazardous environment and assuring their safety. The second category deals with the constraints and special requirements involved with a suited crewman operating flight hardware in a 1-G environment. Design areas that deal with man rating a chamber, including fire suppression, emergency repress, emergency power, backups, reliable instrumentation and data systems, communications, television monitoring, biomedical monitoring, material compatibilities, and equipment supporting the Extravehicular Mobility Unit (EMU) are discussed. The operational issues that are peculiar to manned testing such as test rules, test procedures, test protocol, emergency drills, availability of hyperbaric facilities, test team training and certification engineering concerns for a safe mechanical and instrumentation buildup, hazard analysis, and Failure Modes and Effects Analysis are discussed. The constraints and special requirements involved with a suited crewman operating flight hardware in a 1-G environment are addressed.

Fender, Donna L.↗

NASA NTRS2010

JANNAF Lessons Learned Panel Discussion

The difference between the AS-510 observed and predicted separation distance is attributed to a greater F-1 engine "tail off" impulse than that used in the separation distance prediction. . The F-1 thrust decay was normal and not appreciably different from previous (AS-505 through 509) flights. . Analysis indicates that with an S-IC stage having only four retro motors, failure of one retro motor to ignite would result in marginal separation distances and, in the 3-sigma case, re-contact of the two stages. . S-IC-11 and subsequent flight stages were equipped with eight retro motors rather than the planned four.

Richards, Steve↗

DOE OSTI2024

Understanding GPU Memory Corruption at Extreme Scale: The Summit Case Study

GPU memory corruption and in particular double-bit errors (DBEs) remain one of the least understood aspects of HPC system reliability. Albeit rare, their occurrences always lead to job termination and can potentially cost thousands of node-hours, either from wasted computations or as the overhead from regular checkpointing needed to minimize the losses. As supercomputers and their components simultaneously grow in scale, density, failure rates, and environmental footprint, the efficiency of HPC operations becomes both an imperative and a challenge. We examine DBEs using system telemetry data and logs collected from the Summit supercomputer, equipped with 27,648 Tesla V100 GPUs with 2nd-generation high-bandwidth memory (HBM2). Using exploratory data analysis and statistical learning, we extract several insights about memory reliability in such GPUs. We find that GPUs with prior DBE occurrences are prone to experience them again due to otherwise harmless factors, correlate this phenomenon with GPU placement, and suggest manufacturing variability as a factor. On the general population of GPUs, we link DBEs to short- and long-term high power consumption modes while finding no significant correlation with higher temperatures. We also show that the workload type can be a factor in memory’s propensity to corruption.

Oles, Vlad↗

DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2005

Materials Science Laboratory

The NASA Materials Science Laboratory (MSL) provides science and engineering services to NASA and Contractor customers at KSC, including those working for the Space Shuttle. International Space Station. and Launch Services Programs. These services include: (1) Independent/unbiased failure analysis (2) Support to Accident/Mishap Investigation Boards (3) Materials testing and evaluation (4) Materials and Processes (M&P) engineering consultation (5) Metrology (6) Chemical analysis (including ID of unknown materials) (7) Mechanical design and fabrication We provide unique solutions to unusual and urgent problems associated with aerospace flight hardware, ground support equipment and related facilities.

Jackson, Dionne↗

DOE OSTI2023

Methods for Analysis and Quantification of Power System Resilience

This paper summarizes the report prepared by an IEEE PES Task Force. Resilience is a fairly new technical concept for power systems, and it is important to precisely delineate this concept for actual applications. As a critical infrastructure, power systems have to be prepared to survive rare but extreme incidents (natural catastrophes, extreme weather events, physical/cyber-attacks, equipment failure cascades, etc.) to guarantee power supply to the electricity-dependent economy and society. Thus, resilience needs to be integrated into planning and operational assessment to design and operate adequately resilient power systems. Quantification of resilience as a key performance indicator is important, together with costs and reliability. Quantification can analyze existing power systems and identify resilience improvements in future power systems. Given that a 100% resilient system is not economic (or even technically achievable), the degree of resilience should be transparent and comprehensible. Several gaps are identified to indicate further needs for research and development.

42 ENGINEERING↗

DOE OSTI2020

An Applied Strategy for Using Empirical and Hybrid Models in Online Monitoring

The monitoring of plant equipment for failure prediction is one of the key contributors to operation and maintenance (O&M) costs for a nuclear power plant (NPP) because O&M monitoring depends on labor-intensive activities that are required to meet high equipment reliability standards. These activities rely primarily on humans for information gathering, condition diagnosis, and predictive analysis. Online monitoring aims to automate these activities by relying on sensors to replace human information gathering and machine learning to replace human analysis and decision making. To facilitate automated monitoring, a systematic strategy for anomaly detection is needed to optimally use the available sensor data, empirical models, and physics-supported models. This strategy is essential to provide credible reasoning on why and when an empirical (i.e., purely data-driven) versus hybrid (i.e., physics-supported) approach should be used and to determine the ideal mix of these two approaches for a defined anomaly detection scope. The extant methods usually adopt an ad hoc trial-and-error approach that, in addition to being time-consuming and costly, is also highly subjective; it is impacted by the background and the skill set of the personnel making the decisions. Thus, such an approach cannot guarantee an optimum outcome. This represents the motivation of the current research effort, which is focused on devising a scientifically supported strategy for the optimum selection of anomaly detection methods. This report presents a detailed assessment of the main anomaly detection techniques within the empirical or hybrid method streams. Empirical methods include pattern, statistical, and causal inference. Hybrid methods include the use of physics models to train and test data methods, reduce data dimensionality, reduce data-model complexity, augment data, and reduce empirical uncertainty; hybrid methods also include the use of data to tune physics models. The listed techniques within these two streams represent the vast majority of techniques performed for anomaly detection. Using the techniques as outcomes, a strategy was developed to enable a systematic decision-making process to lead to one of these techniques. The strategy is driven by key decision points related to data relevance, simple modeling feasibility, data inference, physics-modeling value, data dimensionality, physics knowledge, method of validation, performance, data availability and suitability for training and testing, cause-effect, entropy inference, and model fitting. Each of these decision points in the strategy is explained in detail in this report with examples, along with the scientific basis behind the decisions and outcomes in common and simplified terminology. The strategy is developed for use by any NPP staff with basic engineering or science knowledge. A user-friendly graphical state flow diagram was also developed as a visual presentation of the strategy. The strategy was tested and demonstrated through two pilot projects for the application of anomaly detection at an NPP. Each pilot had two use cases: an initial case in which certain decisions were made that resulted in one or more empirical techniques and a revised use case where one or more key decisions were modified resulting in using a set of hybrid methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Digital Engineering and Cybersecurity Decision Analysis in Early Phases of SMR-Driven IES Projects

Considerable efforts are underway to ensure cybersecurity is integrated into the systems engineering lifecycle. Cyber-informed engineering and security-by-design frameworks are intended to identify and engineer out cybersecurity risks throughout the lifecycle. While these approaches are valuable for promoting the need to include cybersecurity considerations in early design phases to create more secure systems, they may not consider the entirety of digital risks. Digital risks in a digital instrumentation and control system include adversarial and unintentional risks from internal and external factors, such as human performance errors, design flaws, environmental conditions, and equipment degradation or failure. This report provides a detailed discussion on digital risk prior to describing the background and concept of operations for a small modular reactor-driven integrated energy system connected to industrial applications. The challenges of competing objectives and competing stakeholder requirements are discussed and the impacts on digital engineering, security considerations, and interdependencies are evaluated for mission-level, facility-level, and system-level decisions.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2024

Achieving an 80% Renewable Portfolio in Alaska's Railbelt: Cost Analysis

This study examines the system-level costs and benefits of increased renewable energy deployment in the Railbelt grid, in the context of a proposed 80% renewable portfolio standard (RPS). This work studies the period from 2024 to 2040 and uses a model that simulates the planning, evolution, and operation of the power system to identify the mix of resources that maintains system reliability at the lowest electricity system cost over the period of analysis. The model tracks several reliability metrics, including the ability to serve demand during all hours of the year, even when normal power system failures occur. The model includes several measures (and associated costs) to address the variable output of renewable resources, including additional operating reserves, fuel storage, cycling of fossil plants, and additional equipment needed to maintain system stability. The Reference (least-cost) scenario results in substantial deployment of renewable energy and cost savings, reaching about 76% of Railbelt generation derived from renewables in 2040. Annual savings average about $105 M/year from 2030 to 2040. About 50% of this generation is from wind by 2040. Enforcing an 80% RPS results in about a 2% cumulative reduction in net savings. Demand is met in all scenarios, relying heavily on use of existing hydropower and fossil-fueled generators during periods of low renewable output. Meeting the increase in variability will require substantial changes in how the system is operated, with inverter-based resources providing nearly 100% of electricity during some periods.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

NASA NTRS2003

Satellite GN and C Anomaly Trends

On-orbit anomaly records for satellites launched from 1990 through 2001 are reviewed to determine recent trends of un-manned space mission critical failures. Anomalies categorized by subsystems show that Guidance, Navigation and Control (GN&C) subsystems have a high number of anomalies that result in a mission critical failure when compared to other subsystems. A mission critical failure is defined as a premature loss of a satellite or loss of its ability to perform its primary mission during its design life. The majority of anomalies are shown to occur early in the mission, usually within one year from launch. GN&C anomalies are categorized by cause and equipment type involved. A statistical analysis of the data is presented for all anomalies compared with the GN&C anomalies for various mission types, orbits and time periods. Conclusions and recommendations are presented for improving mission success and reliability.

Robertson, Brent↗

NASA NTRS1990

The Hubble Space Telescope optical systems failure report

The findings of the Hubble Space Telescope Optical Systems Board of Investigation are reported. The Board was formed to determine the cause of the flaw in the telescope, how it occurred, and why it was not detected before launch. The Board conducted its investigation to include interviews with personnel involved in the fabrication and test of the telescope, review of documentation, and analysis and test of the equipment used in the fabrication of the telescope's mirrors. The investigation proved that the primary mirror was made in the wrong shape (a 0.4-wave rms wavefront error at 632.8 nm). The primary mirror was manufactured by the Perkin-Elmer Corporation (Hughes Danbury Optical Systems, Inc.). The critical optics used as a template in shaping the mirror, the reflective null corrector (RNC), consisted of two small mirrors and a lens. This unit had been preserved by the manufacturer exactly as it was during the manufacture of the mirror. When the Board measured the RNC, the lens was incorrectly spaced from the mirrors. Calculations of the effect of such displacement on the primary mirror show that the measured amount, 1.3 mm, accounts in detail for the amount and character of the observed image blurring. No verification of the reflective null corrector's dimensions was carried out by Perkin-Elmer after the original assembly. There were, however, clear indications of the problem from auxiliary optical tests made at the time. A special optical unit called an inverse null corrector, designed to mimic the reflection from a perfect primary mirror, was built and used to align the apparatus; when so used, it clearly showed the error in the reflective null corrector. A second null corrector was used to measure the vertex radius of the finished primary mirror. It, too, clearly showed the error in the primary mirror. Both indicators of error were discounted at the time as being themselves flawed. The Perkin-Elmer plan for fabricating the primary mirror placed complete reliance on the reflective null corrector as the only test to be used in both manufacturing and verifying the mirror's surface with the required precision. This methodology should have alerted NASA management to the fragility of the process and the possibility of gross error. Such errors had been seen in other telescope programs, yet no independent tests were planned, although some simple tests to protect against major error were considered and rejected. During the critical time period, there was great concern about cost and schedule, which further inhibited consideration of independent tests.

Source record↗

NASA NTRSDate not supplied

Passive Dust Mitigation Technologies Being Developed for Demonstration Under Patch Plate Materials Compatibility Analysis Task

With the Artemis program, we are planning longer stays on the surface, with more activities that have the potential to put the astronauts and equipment in contact with greater quantities of lunar dust. The success of these missions will depend on our understanding of material interactions with lunar dust and the development of ways to mitigate dust effects in cases where exposure to dust will lead to failure of components, unacceptable loss of power or thermal control, unacceptable loss of visibility, or health issues. Passive dust mitigation by coating or surface alteration is one method that is being developed and demonstrated under the Space Technology Mission Directorate’s Game Changing Technology, Dust Mitigation Program as part of the Patch Plate Materials Compatibility Assessment Task. The goal of the task is to alter the surfaces of materials in order to passively reduce the adhesion of dust, demonstrate their performance in relevant ground-based tests using lunar simulants, and prepare them for demonstration through experiment on the lunar surface. Optically transparent, sputter deposited, work function matching coatings are being developed to reduce adhesion of dust to windows, lenses and display panels by matching the minimum energy to remove an electron from the surface to that of lunar dust in order to reduce adhesion due to charge transfer. Low surface energy coatings and surfaces for thermal control are also being developed to reduce the bonding of dust with the surface enabling it to be removed more easily. Conductive coatings with the ability to shed dust more easily are being developed for use with the active Electrodynamic Dust Shield technology to help reduce the power needed to remove dust from the surface. Passive dust mitigation surfaces for metals such as aluminum, stainless steel, and titanium are being developed that reduce the area of dust contact with the surfaces through topographical modification using laser ablation patterning to impart hierarchical topographies with nanometer to micrometer length scales in a single step. Topographically modified polymeric materials, both those with extensive space heritage and those with lower technology readiness levels, are also being evaluated. Space suit fabric surfaces that can reduce dust penetration into and through the fabric are also being investigated as well as pristine and topographically modified ceramic materials that exhibit high wear resilience. An overview of the passive dust mitigation surfaces and coatings being developed under this task, ground testing being conducted using lunar simulants, characterization techniques, and materials preparation for flight sample delivery for integration into the Alpha Space Regolith Adherence Characterization experiment going to the lunar surface on a Commercial Lunar Payload Services (CLPS) lander in 2023 will be discussed.

Lunar dust, passive mitigation, lunar simulant, co↗

NASA NTRS1971

Application of system safety to rail transit systems

Management emphasis on system safety in the rapid transit industry includes the granting and use of funds by the Federal Government according to systematic analysis of safety hazards in advance. Likelihood predictions that those hazards will be activated by exposure of the system to a system failure, a human error, external conditions, or combinations of these aspects determine alternatives to the assumption of risk and recommend corrections before the system is operational. Rigorous safety analyses are projected to assure operational safety for prolonged periods under varied maintenance conditions; these analysis encompass station accident possibilities as well as train-person collisions, car equipment and design, traffic control systems, and tunnel design problems.

Thomas DeW. Styles↗

DOE OSTI2023

Metamodels for Rapid Analysis of Large Sets of Building Designs for Robotic Constructability: Technology Demonstration Using the NASA 3D Printed Mars Habitat Challenge

Disruptive robotic construction technologies such as additive deposition of cementitious materials like concrete (or "3D concrete printing") require the synchronous operation of multiple pieces of equipment in the production setup. In such an environment, it is crucial to simulate the robotic motions (for toolpath clashes) and the cementitious material behavior (for toolpath failures) to ensure fail-proof constructability of the envisioned building geometry. However, toolpath clash detection requires 4D simulations of the production setup, which are computationally graphics intensive, whereas toolpath failure detection requires actual 3D printing of test parts from the geometry to identify areas prone to failure while 3D printing, which is physically tedious. Both these processes, being computationally and physically intensive, have largely curtailed designers from simulating and exploring large sets of design options with varying geometries and toolpath configurations. To overcome this and allow designers to explore large sets of design possibilities, this paper proposes two novel computational metamodels capable of performing robotic toolpath clash detection and failure detection with significantly reduced times than the earlier approaches. The developed metamodels were used to rapidly simulate large sets of building design options for robotic constructability in the NASA 3D-Printed Mars Habitat Challenge.

clash detection↗

DOE OSTI2025

Informing Plant Asset Reliability and Availability Through AI-Driven Analysis of Operator Logs

The availability and reliability of nuclear power plant (NPP) structures, systems, and components (SSCs) are critical parameters for NPP safety. Tracking these parameters is necessary but costly and labor-intensive, requiring the collection and evaluation of SSC event data such as shutdowns, startups, and failures. To show how these events are needed for the parameters an example is given: one measure of reliability is based on the number of equipment failure events and the number of run hours (i.e., the time from a startup event to a shutdown event). Here, this work investigates using artificial intelligence (AI) to mine NPP operator log entry texts for SSC event data. Four AI approaches were explored for identifying these events, including natural language processing (NLP) methods, generative AI, generative AI combined with NLP, and topic modeling. A key challenge addressed with all four approaches is the brevity of operator log entries. Among these four a neural network–based NLP method was shown to be the most promising for this application, achieving F1 scores of 86.0% for shutdowns, 92.2% for startups, and 80.4% for failures on a subject-matter-expert-curated dataset from NPP operator logs, compared to a baseline of 66.6% for a random classifier. This shows that NLP methods can perform better than generative AI. Additionally, the NLP methods combined with generative AI were shown to perform better than generative AI alone. Generative AI was most successful at providing the background information for the NLP methods to use. This work demonstrates the potential to use AI to automate parameter collection from NPP operator log entries and other records.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Transportation analysis and related design optimization of the Fermilab high-beta 650 MHz cryomodule

The Proton Improvement Plan-II (PIP-II) at Fermi National Accelerator Laboratory (FNAL) will create a new and vastly improved accelerator, which will be the source of high-energy particles for the experiments taking place at FNAL. The new linear accelerator (LINAC) contains several types of cryomodules, which are individual particle accelerators. The last cryomodule in the LINAC will be the High-Beta 650 (HB650), which will operate at 650 MHz. Each module is approximately 15 meters in length and 1.5 meters wide, weighs 13 tonnes, and shares many design features with three of the other cryomodules. The HB650 consists of two primary sections, the outer vacuum vessel and the components that reside within it, which will be cooled to cryogenic temperatures – the cold mass. Once assembly is complete at FNAL, it will be transported to one of three places: another location at FNAL, another national laboratory within the continental United States, or to a scientific partner in Europe. Any excitation the module experiences, such as going over rough roads when on a semitrailer, can create high stresses in components and cause failure if severe enough. Additionally, any delicate components with low resonant frequencies that match the excitation spectrum could achieve resonance, potentially causing a fatigue failure by repeated flexing. To ensure the successful transportation of the HB650, a transport analysis utilizing ANSYS simulation software has been performed on major subassemblies, as well as analysis of the subassemblies as a combined system. The optimization of components, design of support structures, and overall increasing of the lowest resonant frequencies have resulted in a cryomodule that will be better equipped to handle transportation and any large impact loads that come with it.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Woody Feedstock 2022 State of Technology Report

The U.S. Department of Energy promotes production of advanced liquid transportation fuels from lignocellulosic biomass by funding fundamental and applied research that advances the state of technology (SOT). As part of its involvement in this mission, Idaho National Laboratory completes an annual SOT report for n th -plant and 1 st -plant woody biomass feedstock logistics. The purpose of the SOT is to provide the status of feedstock supply system technology development for woody biomass to biofuels relative to technical targets and cost goals from specific design cases, based on data and experimental results. Conventional feedstock supply systems need to be modified to meet the demands of conversion pathways, specifically to have the ability to adjust the quality of the raw biomass materials. Advanced systems incorporate innovative methods of material handling, preprocessing and supply chain configuration. In advanced designs, variability of the raw biomass can be reduced to produce feedstocks of a uniform format, moving toward biomass commoditization. Against this backdrop, the 2022 Woody SOT for low-ash woody feedstocks utilizes feedstock fractionation by incorporating technologies that can separate the biomass into its anatomical fractions (wood, bark, needle, and extrinsic ash) to reduce impurities and attempt to maximize the retention of usable fractions that satisfy downstream quality considerations. By using a series of air classification steps, this strategy can reduce the extrinsic ash in forest residues, separate out a majority of the incoming needles (which can be supplied to alternate markets), and maximize the retention of whitewood in the usable fraction. The fractionated forest residues are then mixed with clean-pine chips in a 50-50 blend to prepare the feedstock for the desired conversion pathway. The n th -plant analysis estimated the delivered cost for the feedstock at $\$$69.23/dry ton (2016$\$$) which represents a $\$$6.64/dry ton decrease compared to the cost estimate of the 2021 Woody SOT supply system for low-ash woody feedstocks. The quality requirements in the 2022 Woody SOT were identical to those of the 2021 Woody SOT at = 1.00 wt % ash and = 50.51 wt% carbon. The cost savings derive primarily from reductions in dry matter losses during air classification. The GHG emissions for the n th -plant analysis were estimated at 178.39 kg CO2e/dry ton compared to 178.71 kg CO 2 e/dry ton in the 2021 Woody SOT, a decrease of 0.32 kg CO2e/dry ton. The small change stems from an increase in emissions attributed to preprocessing and slightly larger savings in emissions from transportation. In the 1 st -plant analysis of the 2022 Woody SOT system, the average throughput was estimated to be approximately 2,128 dry tons/day or 96.51% of the name plate capacity. During the simulation the daily throughput ranged from 1,090 dry tons/day to 2,200 dry tons/day, or 49.43% to 99.75% of the daily nameplate capacity. After the year of operation 722,403 tons of processed feedstock were produced in total without regard to quality considerations (99.64% of the annual nameplate capacity). The variability in throughput was primarily caused by equipment failures in the system. Regular failures, downtime caused by routine maintenance per manufacturer guidelines, contributed to a majority 62.50% of failures and 62.60% of downtime. Failures due to wear were the other cause of disruption within the system, impacting the rotary shear and orbital screen and accounting for 37.50% of the failures and 37.40% of the total downtime. Ultimately the system was on stream for 87.84% during the simulation period, which is only 2.16 percentage points below the nth-plant assumption for on-stream time. The production cost of the system averaged $\$$71.66/dry ton. The costs ranged from a minimum of $\$$71.23/dry ton to a maximum of $\$$2,115.30/dry ton. When dry matter losses (disposed low-quality fractions as well as other losses such as in grinders) were considered the costs increased to an average of $\$$75.11/dry ton with a minimum of $\$$74.69/dry ton and a maximum of $\$$2,136.86/dry ton...

09 BIOMASS FUELS↗

NASA NTRS2017

Dynamic Positioning System (DPS) Risk Analysis Using Probabilistic Risk Assessment (PRA)

The National Aeronautics and Space Administration (NASA) Safety & Mission Assurance (S&MA) directorate at the Johnson Space Center (JSC) has applied its knowledge and experience with Probabilistic Risk Assessment (PRA) to projects in industries ranging from spacecraft to nuclear power plants. PRA is a comprehensive and structured process for analyzing risk in complex engineered systems and/or processes. The PRA process enables the user to identify potential risk contributors such as, hardware and software failure, human error, and external events. Recent developments in the oil and gas industry have presented opportunities for NASA to lend their PRA expertise to both ongoing and developmental projects within the industry. This paper provides an overview of the PRA process and demonstrates how this process was applied in estimating the probability that a Mobile Offshore Drilling Unit (MODU) operating in the Gulf of Mexico and equipped with a generically configured Dynamic Positioning System (DPS) loses location and needs to initiate an emergency disconnect. The PRA described in this paper is intended to be generic such that the vessel meets the general requirements of an International Maritime Organization (IMO) Maritime Safety Committee (MSC)/Circ. 645 Class 3 dynamically positioned vessel. The results of this analysis are not intended to be applied to any specific drilling vessel, although provisions were made to allow the analysis to be configured to a specific vessel if required.

Thigpen, Eric B.↗