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At least 289 records · Page 16

Development of human epithelial cell systems for radiation risk assessment

The most important health effect of space radiation for astronauts is cancer induction. For radiation risk assessment, an understanding of carcinogenic effect of heavy ions in human cells is most essential. In our laboratory, we have successfully developed a human mammary epithelial cell system for studying the neoplastic transformation in vitro. Growth variants were obtained from heavy ion irradiated immortal mammary cell line. These cloned growth variants can grow in regular tissue culture media and maintain anchorage dependent growth and density inhibition property. Upon further irradiation with high-Linear Energy Transfer (LET) radiation, transformed foci were found. Experimental results from these studies suggest that multiexposure of radiation is required to induce neoplastic tranformation of human epithelial cells. This multihits requirement may be due to high genomic stability of human cells. These growth variants can be useful model systems for space flight experiments to determine the carcinogenic effect of space radiation in human epithelial cells.

Yang, C. H.↗

Method and system for dynamic probabilistic risk assessment

The DEFT methodology, system and computer readable medium extends the applicability of the PRA (Probabilistic Risk Assessment) methodology to computer-based systems, by allowing DFT (Dynamic Fault Tree) nodes as pivot nodes in the Event Tree (ET) model. DEFT includes a mathematical model and solution algorithm, supports all common PRA analysis functions and cutsets. Additional capabilities enabled by the DFT include modularization, phased mission analysis, sequence dependencies, and imperfect coverage.

Dugan, Joanne Bechta↗

Extravehicular Activity Micrometeoroid and Orbital Debris Risk Assessment Methodology

A well-known hazard associated with exposure to the space environment is the risk of vehicle failure due to an impact from a micrometeoroid and orbital debris (MMOD) particle. Among the vehicles of importance to NASA is the extravehicular mobility unit (EMU) “spacesuit” used while performing a US extravehicular activity (EVA). An EMU impact is of great concern as a large leak could prevent an astronaut from safely reaching the airlock in time resulting in a loss of life. For this reason, a risk assessment is provided to the EVA office at the Johnson Space Center (JSC) prior to certification of readiness for each US EVA.

Hoffman, Kevin D.↗

Comparative Analysis of Static and Dynamic Probabilistic Risk Assessment

This study examines three different methodologies for producing loss-of-mission (LOM) and loss-of-crew (LOC) risks estimates for probabilistic risk assessments (PRA) of crewed spacecraft. The three bottom-up, component-based PRA approaches examined are a traditional static fault tree, a dynamic Monte Carlo simulation, and a fault tree hybrid that incorporates some dynamic elements. These approaches were used to model the reaction control system thruster pod of a generic crewed spacecraft and mission, and a comparative analysis of the methods is presented. The methodologies are assessed in terms of the process of modeling a system, the actionable information produced for the design team, and the overall fidelity of the quantitative risk evaluation generated. The system modeling process is compared in terms of the effort required to generate the initial model, update the model in response to design changes, and support mass-versus-risk trade studies. The results are compared by examining the top-level LOM/LOC estimates and the relative risk driver rankings at the failure mode level. The fidelity of each modeling methodology is discussed in terms of its capability to handle real-world system dynamics such as cold-sparing, changes in mission operations due to loss of redundancy, and common cause failure modes. The paper also discusses the applicability of each methodology to different phases of system development and shows that a single methodology may not be suitable for all of the many purposes of a spacecraft PRA. The fault tree hybrid approach is shown to be best suited to the needs of early assessments during conceptual design phases. As the design begins to mature, the level of detail represented in the risk model must go beyond redundancy and nominal mission operations to include dynamic, time- and state-dependent system responses as well as diverse system capabilities. This is best accomplished using the dynamic simulation approach, since these phenomena are not easily captured by static methods. Ultimately, once the design has been finalized and the goal of the PRA is to provide design validation and requirement verification, more traditional, static fault tree approaches may become as appropriate as the simulation method.

Mattenberger, Christopher J.↗

Heterogeneous Multi-Domain Dataset Synthesis to Facilitate Privacy and Risk Assessments in Smart City IoT

The emergence of the Smart Cities paradigm and the rapid expansion and integration of Internet of Things (IoT) technologies within this context have created unprecedented opportunities for high-resolution behavioral analytics, urban optimization, and context-aware services. However, this same proliferation intensifies privacy risks, particularly those arising from cross-modal data linkage across heterogeneous sensing platforms. To address these challenges, this paper introduces a comprehensive, statistically grounded framework for generating synthetic, multimodal IoT datasets tailored to Smart City research. The framework produces behaviorally plausible synthetic data suitable for preliminary privacy risk assessment and as a benchmark for future re-identification studies, as well as for evaluating algorithms in mobility modeling, urban informatics, and privacy-enhancing technologies. As part of our approach, we formalize probabilistic methods for synthesizing three heterogeneous and operationally relevant data streams—cellular mobility traces, payment terminal transaction logs, and Smart Retail nutrition records—capturing the behaviors of a large number of synthetically generated urban residents over a 12-week period. The framework integrates spatially explicit merchant selection using K-Dimensional (KD)-tree nearest-neighbor algorithms, temporally correlated anchor-based mobility simulation reflective of daily urban rhythms, and dietary-constraint filtering to preserve ecological validity in consumption patterns. In total, the system generates approximately 116 million mobility pings, 5.4 million transactions, and 1.9 million itemized purchases, yielding a reproducible benchmark for evaluating multimodal analytics, privacy-preserving computation, and secure IoT data-sharing protocols. To show the validity of this dataset, the underlying distributions of these residents were successfully validated against reported distributions in published research. We present preliminary uniqueness and cross-modal linkage indicators; comprehensive re-identification benchmarking against specific attack algorithms is planned as future work. This framework can be easily adapted to various scenarios of interest in Smart Cities and other IoT applications. By aligning methodological rigor with the operational needs of Smart City ecosystems, this work fills critical gaps in synthetic data generation for privacy-sensitive domains, including intelligent transportation systems, urban health informatics, and next-generation digital commerce infrastructures.

IoT↗

Large-Scale Hydrogen Storage Cyber Risk Assessment

Hydrogen storage systems may become more widely deployed throughout the country, and so it is possible that individual and interconnected systems will be exposed to cyber-attacks. These events can cause physical and financial harm to employees, people in the vicinity of the facility, and the company that owns the facility. The two main ways bad actors may access information or control from a hydrogen storage facility are through information technology and operations technology devices, the former of which refers to data and information from networked devices and the latter of which refers to onsite controls for the physical system. Both types of entryways into the system should be considered when companies conduct cyber risk assessments and when regulators develop or revise relevant codes and standards. This report analyzes cybersecurity risks associated with a generic hydrogen storage system by outlining the system's purpose and the importance of its cybersecurity. The hydrogen storage system architecture and communication protocols are provided to understand potential cyber vulnerabilities. Later, an event tree analysis is performed on hydrogen operation to identify system weaknesses by outlining potential attack scenarios. This report also identifies critical cyber assets related to different hydrogen operations followed by an examination of potential threats, and the impact of cyber assets on those operational assets.

08 HYDROGEN↗

Expectation vs. Reality: The Sunrise Problem Applied to Probabilistic Risk Assessment

The Sunrise Problem is succinctly stated as a question: “what is the probability that the sun will rise tomorrow?” Attempts to answer this seemingly simple question reveal unexpected incongruities between statistical/probabilistic estimates and “real-world” expectations. Rather than being a purely philosophical problem, similar incongruities can be found in reliability and probabilistic risk assessment (PRA) analyses. These differences between statistical predictions and demonstrated reliability can result in analysis shortcomings that should be addressed and resolved. This presentation will begin by discussing the nature of the Sunrise Problem and how it applies to PRA and reliability. Examples of the Sunrise Problem in a PRA estimate will also be included, along with tips to identify and resolve the shortcomings that result from these anomalous situations.

Sunrise Problem↗

Plan for Development and Application of Risk Assessment Approach for Transportation Package Approval of an MNPP for Domestic Highway Shipment

For nuclear reactors, Probabilistic Risk Assessment (PRA) has been conducted since the 1970s [e.g., see WASH-1400 (NRC 1975), NUREG-1150 (NRC 1990), and NUREG-1935 (Chang et al. 2012)]. PRA has also been used to assess a dry cask storage system at a nuclear power plant [see NUREG-1864 (NRC 2007)]. PRA techniques have also been applied to the transportation of spent nuclear fuel, most notably in NUREG/CR-4829 (Fischer et al. 1987), NUREG/CR-6672 (Sprung et al. 2000), and NUREG-2125 (NRC 2014). Additional guidance is provided in International Atomic Energy Agency (IAEA) IAEA-TECDOC-1346 (2003). Transportation PRA was also used in the evaluations of transportation impacts in reports such as the Repository Final Environmental Impact Statement (DOE 2002) and the Repository Final Supplemental Environmental Impact Statement (DOE 2008).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advanced risk assessment of the effects of graphite fibers on electronic and electric equipment

An assessment of the risk associated with accidents involving aircraft with carbon fiber composite structural components is examined. The individual fiber segments cause electrical and electronic equipment to fail under certain operating conditions. A Monte Carlo simulation model was used to computer the risk. Aircraft accidents with fire, release of carbon fiber material, entrainment of carbon fibers in a smoke plume transport of fibers downwind, transfer of some fibers/into the the interior of buildings, failures of electrical and electronic equipment, and economic impact of failures are discussed. Risk profiles were prepared for individual airports and the Nation. The vulnerability of electrical transmission equipment to carbon fiber incursion and aircraft accident total costs is investigated.

Pocinki, L.↗

Probability of failure and risk assessment of propulsion structural components

Because of the increasing need to account for the uncertainties in material properties, loading conditions, geometry, etc., a methodology was developed to determine structural reliability and to assess the associated risk. The methodology consists of a probabilistic structural analysis by a probabilistic finite element computer code, numerical evaluation of stochastic structures under stress (NESSUS), and a generic probabilistic material property model. The methodology is versatile and is equally applicable to structures operating at high and cryogenic temperature environments. Results obtained demonstrate that the issues of structural reliability and risk can be formally evaluated by using the methodology developed which is inclusive of the uncertainties in material properties, structural parameters, and loading conditions. The methodology is described in some detail with illustrative examples.

Shiao, Michael C.↗

Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors: Probabilistic Risk Assessment Approach

This report, “Modernization of Technical Requirements for Licensing of Advanced Non-Light Water Reactors: Probabilistic Risk Assessment Approach,” represents a key element in the development of a methodology for the efficient licensing of advanced non-light water reactors (non-LWRs). It is the result of a Licensing Modernization Project (LMP) led by Southern Company and cost-shared by the U.S. Department of Energy (DOE). The LMP has developed detailed proposals for establishing licensing technical requirements to facilitate risk-informed and performance-based design and licensing of advanced non-LWRs. Such a methodology acknowledges enhancements in safety achievable with advanced designs and reflects more recent states of knowledge regarding safety and design innovation, creating an opportunity for reduced regulatory complexity with increased levels of safety. The project builds on best practices, as well as previous activities through DOE and industry-sponsored advanced reactor licensing initiatives.

42 ENGINEERING↗

SOSAT: Geohazard Risk Assessment in Carbon Sequestration Operations

Like all operations in which fluids are injected into the subsurface, geologic carbon storage (GCS) presents inherit risks that must be assessed and mitigated to successfully deploy such technology in the field. For example, alterations to pore pressure and the stress state due to fluid injection may trigger certain geohazards, such as potential fault activation and induced seismicity or unintentional hydraulic fracturing. Here we present capabilities for assessing these potential risks using the State of Stress Analysis Tool (SOSAT): a Python library and web-based application capable of probabilistically estimating the subsurface state of stress informed by various field observations. Using posterior distributions of principal stress components, SOSAT can assess the risk of fault activation within the injection formation for either a critically oriented fault or a fault with a user-prescribed orientation. Additionally, SOSAT can estimate the probability of unintentional hydraulic fracturing of the intact reservoir rock. Here, we demonstrate these SOSAT capabilities using a hypothetical GCS site. This type of risk assessment can assist with the effective deployment of GCS technology in the field by informing safe design and management practices.

Haagenson, Ryan J.↗

Improving the Fidelity of Capability & Resource Weighting in A Probalistic Risk Assessment Model for Spaceflight

INTRODUCTION NASA’s Informing Mission Planning via Analysis of Complex Tradespaces (IMPACT) tool uses Probabilistic Risk Assessment (PRA) to provide an evidence-based, data-driven estimate of how medical system capabilities affect mission outcomes. IMPACT maps condition incidence to available resources thereby facilitating the calculation of outcome metrics that allow the estimation of mission medical risk. Conditions can be nominally categorized as either treated or untreated depending on the availability of necessary diagnostic and therapeutic capabilities. This categorization enables IMPACT to estimate the effect of various medical system configurations on mission outcomes such as crew mortality, disability, crew member down-time, return to duty/recovery, and need for evacuation. IMPACT currently employs an equal weighting, “partial credit” approach to define treatment in which each of the capabilities associated with a given condition contributes an equal amount to management of the condition. This feature enables IMPACT to report values in between “fully untreated” and “fully treated” based on the proportion of capabilities available within the model. However, as is normal in medical/clinical practice, not all individual capabilities contribute equally to medical care. For example, the ability to provide intramuscular epinephrine during an anaphylactic episode contributes more likelihood of overall management success than does the administration of oral diphenhydramine. We hypothesize that weighting the relative contribution of each capability to each specific condition will improve outcome prediction and therefore will better provide mission planners with more nuanced and accurate options when designing space medical systems. METHODS Using a five-point Fibonacci scaling sequence (1, 2, 3, 5, 8) subject matter experts from NASA’s Exploration Medical Capabilities (ExMC) element assigned relative contribution weighting values to each identified capability within IMPACT. Since the relative importance of each capability varies depending on the specific condition, the resulting “partial” weighting was completed for more than 1,600 individual weighting assignments for 666 capabilities across 121 conditions. Each assignment required three-physician concurrence based on the overall importance of the capability to the diagnosis and management of the condition being considered and the difficulty with which it could be improvised by the crew. Once complete, 100,000 IMPACT simulations were run for a 6-month Lunar mission with a 30-day surface stay to evaluate the effect of this modification of the model. RESULTS Partial weighting significantly decreased predicted task time loss (TTL), evacuation, and loss of crew life without causing significant changes to the recommended medical system design. CONCLUSIONS The paucity of real-world referent data to support long-duration space missions of this type limits the ability to judge one predictive analytics method as superior to another. However, since the proposed method significantly reduces and optimizes outcome risks—without changing the medical system design—incorporating a partial weighting methodology is likely to provide a more accurate and operationally-relevant representation of medical risk without compromising IMPACTs ability to inform overarching medical system requirements.

Steller JG↗

Solutions for Enhanced Legacy Probabilistic Risk Assessment Tools and Methodologies: Improving Efficiency of Model Development and Processing via Innovative Human Reliability Dependency Analysis

Probabilistic risk assessments (PRAs) are integral to nuclear power plant (NPP) operations, having tremendously benefitted the safety of the U.S. reactor fleet for decades. Insights obtained from the models have provided perspectives on a variety of applications, both at the plant and for the regulator. While these models are very useful, they are now being asked to represent and analyze aspects of the plant that were never envisioned by the initial PRA practitioners. Furthermore, heightened demands on the PRA models have led to increased computing power requirements. Additionally, as the complexity of the PRA models increased, the difficulty experienced by non-PRA experts in trying to understand these models, grasp the insights they provide, and effectively use that information has become problematic. The need for research to address key issues regarding PRA tools and methods has never been greater. Although the nuclear power industry has largely been well-served by these tools and methods, the underlying science is dated, remaining mostly unchanged for over two decades. Three areas were identified as most beneficial to address to maintain and improve the usefulness of the current practice legacy PRA tools: improved quantification speed, increased ability to efficiently model multi-hazard models, and improved modeling human action dependency in PRA. This report is focused on the third critical area, improvements in dependency analysis of human actions conducted as part of a typical human reliability assessment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗