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At least 325 records · Page 18

Failure risk assessment by analysis and testing

The sources of information on which to base an evaluation of reliability or failure risk of an aerospace flight system are (1) experience from tests and flights and (2) engineering analysis. It is rarely feasible to establish high reliability at high confidence by testing aerospace systems or components. Moreover, failure prediction by conventional, deterministic methods of engineering analysis can become arbitrary and subject to serious misinterpretation when uncertain or approximate information is used to establish analysis parameter values and to calibrate the accuracy of engineering models. The limitations of testing to evaluate failure risk are discussed, and a statistical approach which incorporates both engineering analysis and testing is presented.

Moore, N.↗

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗

Active Swarm Resiliency in the HelioSwarm Mission

Designed to observe plasma turbulence dynamics in solar wind over a distributed volume of space, the HelioSwarm mission comprises a primary chief spacecraft and eight smaller deputy satellites in uniquely assigned “loops” of periodic relative motion in a P/2 lunar resonant orbit. If one or more deputies fail, this multi-satellite architecture facilitates resiliency for science goals through repositioning of satellites to contingency loops. This strategy of Active Swarm Resiliency mitigates risk by modeling quantitative results ahead of time for mission operators to make informed decisions. Responsive actions meet minimum science objectives based on past and predicted system performance, an approach with applications to future missions with similar architecture and requirements.

Fault Management↗

Active Swarm Resiliency in the HelioSwarm Mission

Designed to observe plasma turbulence dynamics in solar wind over a distributed volume of space, the HelioSwarm mission comprises a primary chief spacecraft and eight smaller deputy satellites in uniquely assigned “loops” of periodic relative motion in a P/2 lunar resonant orbit. If one or more deputies fail, this multi-satellite architecture facilitates resiliency for science goals through repositioning of satellites to contingency loops. This strategy of Active Swarm Resiliency mitigates risk by modeling quantitative results ahead of time for mission operators to make informed decisions. Responsive actions meet minimum science objectives based on past and predicted system performance, an approach with applications to future missions with similar architecture and requirements.

Fault Management↗

A risk-based approach to robotic mission requirements

A NASA Risk Team has developed a method for the application of risk management to the definition of robotic mission requirements for the Space Exploration Initiative. These requirements encompass environmental information, infrastructural emplacement in advance, and either technology testing or system/subsystems demonstration. Attention is presently given to a method for step-by-step consideration and analysis of the risk component inherent in mission architecture, followed by a calculation of the subjective risk level. Mitigation strategies are then applied with the same rules, and a comparison is made.

Dias, William C.↗

Considering Risk and Resilience in Decision-Making

This paper examines the concepts of decision-making, risk analysis, uncertainty and resilience analysis. The relation between risk, vulnerability, and resilience is analyzed. The paper describes how complexity, uncertainty, and ambiguity are the most critical factors in the definition of the approach and criteria for decision-making. Uncertainty in its various forms is what limits our ability to offer definitive answers to questions about the outcomes of alternatives in a decision-making process. It is shown that, although resilience-informed decision-making would seem fundamentally different from risk-informed decision-making, this is not the case as resilience-analysis can be easily incorporated within existing analytic-deliberative decision-making frameworks.

Torres-Pomales, Wilfredo↗

Recent evolution of risk analyses in atomic bomb survivor studies: new methods and applications

Abstract Several decades ago a dramatic leap forward occurred in the development and application of statistical methods for modeling radiation risk at the Radiation Effects Research Foundation (RERF). Poisson regression analysis for grouped person-year cohort data and the linear excess relative risk model were introduced, and subsequently a devoted software system, Epicure® (https://www.hirosoft.com), was developed by researchers at RERF and at the U.S. National Cancer Institute. Numerous advancements in understanding radiation effects on humans were made possible with these methods, which are still the state-of-the-art for risk assessment at RERF and have remained part of the standard toolbox for radiation—and other environmental—epidemiological studies worldwide. Nevertheless, as our understanding of radiation risk has increased, so have the breadth and depth of questions that require answers based on emerging data that are not amenable to these conventional methods. This overview briefly recounts the conventional methods and then describes our recent diversification into the use or development of new statistical approaches to meet the challenges of burgeoning biological data and emerging mechanistic information. We briefly discuss the development and application of new methods, current and planned, that are part of the RERF Statistics Department’s role in supporting institution-wide research, especially in our collaborations involving the Life Span Study, Adult Health Study, and First-generation Offspring Clinical Study. Some approaches to modeling and assessing radiation risk with newer methods mentioned herein have already been published, while some are still in development or are only beginning at the proposal stage.

Oncology↗

NASA's Human Mission to a Near-Earth Asteroid: Landing on a Moving Target

This paper describes a Bayesian approach for comparing the productivity and cost-risk tradeoffs of sending versus not sending one or more robotic surveyor missions prior to a human mission to land on an asteroid. The expected value of sample information based on productivity combined with parametric variations in the prior probability an asteroid might be found suitable for landing were used to assess the optimal number of spacecraft and asteroids to survey. The analysis supports the value of surveyor missions to asteroids and indicates one launch with two spacecraft going simultaneously to two independent asteroids appears optimal.

precursor decision making↗

CA Risk Assessment Approaches

Current single-Pc approach work well when subtended by appropriate hypothesis-testing framework. Reframing construct in terms of miss distance distribution would confer certain advantages such as reducing to same import as Pc, but still convey some additional information. Methods to incorporate known uncertainties in covariances and HBR should be pursued that can also be framed in terms of miss distance distribution. We present Plausibilistic II and Possibilistic constructs, to determine their adequacy and viable recommendation.

Conjunction↗

How open data and interdisciplinary collaboration improve our understanding of space weather: A risk and resiliency perspective

Space weather refers to conditions around a star, like our Sun, and its interplanetary space that may affect space- and ground-based assets as well as human life. Space weather can manifest as many different phenomena, often simultaneously, and can create complex and sometimes dangerous conditions. The study of space weather is inherently trans-disciplinary, including subfields of solar, magnetospheric, ionospheric, and atmospheric research communities, but benefiting from collaborations with policymakers, industry, astrophysics, software engineering, and many more. Effective communication is required between scientists, the end-user community, and government organizations to ensure that we are prepared for any adverse space weather effects. With the rapid growth of the field in recent years, the upcoming Solar Cycle 25 maximum, and the evolution of research-ready technologies, we believe that space weather deserves a reexamination in terms of a “risk and resiliency” framework. By utilizing open data science, cross-disciplinary collaborations, information systems, and citizen science, we can forge stronger partnerships between science and industry and improve our readiness as a society to mitigate space weather impacts. The objective of this manuscript is to raise awareness of these concepts as we approach a solar maximum that coincides with an increasingly technology-dependent society, and introduce a unique way of approaching space weather through the lens of a risk and resiliency framework that can be used to further assess areas of improvement in the field.

79 ASTRONOMY AND ASTROPHYSICS↗

Chemical changes in thirdhand smoke associated with remediation using an ozone generator

Ozonation is a common remediation approach to eliminate odors from mold, tobacco and fire damage in buildings. Little information exists to: 1) assess its effectiveness; 2) provide guidance on operation conditions; and 3) identify potential risks associated with the presence of indoor ozone and ozonation byproducts. The goal of this study is to evaluate chemical changes in thirdhand smoke (THS) aerosols induced by high levels of ozone, in comparison with THS aerosols aged under similar conditions in the absence of ozone. Samples representing different stages of smoke aging in the absence of ozone, including freshly emitted secondhand smoke (SHS) and THS, were collected inside an 18-m 3 room-sized chamber over a period of 42 h after six cigarettes were consumed. The experiments involved collection and analysis of gas phase species including volatile organic compounds (VOCs), volatile carbonyls, semivolatile organic compounds (SVOCs), and particulate matter. VOC analysis was carried out by gas chromatography/mass spectrometry with a thermal desorption inlet (TD-GC/MS), and volatile carbonyls were analyzed by on-line derivatization with dinitrophenylhydrazine (DNPH), followed by liquid chromatography with UV/VIS detection. SVOCs were extracted from XAD-coated denuders and Teflon-coated fiberglass filters in the absence of ozone. In those extracts, tobacco-specific nitrosamines (TSNAs) and other SVOCs were analyzed by gas chromatography with positive chemical ionization-triple quadrupole mass spectrometric detection (GC/PCI-QQQ-MS), and polycyclic aromatic hydrocarbons (PAHs) were quantified by gas chromatography with ion trap mass spectrometric detection (GC/IT-MS) in selected ion monitoring mode. Particulate matter concentration was determined gravimetrically. In a second experiment, a 300 mg h -1 commercial ozone generator was operated during 1 h, one day after smoke was generated, to evaluate the remediation of THS by ozonation. VOCs and volatile carbonyls were analyzed before and after ozonation. Extracts from fabrics that were exposed in the chamber before and after ozonation as surrogates for indoor furnishings were analyzed by GC/IT-MS, and aerosol size distribution was studied with a scanning mobility particle sizer. Ozone concentration was measured with a photometric detector. An estimated 175 mg ozone reacted with THS after 1 h of treatment, corresponding to 58% of the total O 3 released during that period. Fabric-bound nicotine was depleted after ozonation, and the surface concentration of PAHs adsorbed to fabric specimens decreased by an order of magnitude due to reaction with ozone, reaching pre-smoking levels. These results suggest that ozonation has the potential to remove harmful THS chemicals from indoor surfaces. However, gas phase concentrations of volatile carbonyls, including formaldehyde, acetaldehyde and acetone were higher immediately after ozonation. Ultrafine particles (UFP, in most cases with size <60 nm) were a major ozonation byproduct. UFP number concentrations peaked shortly after ozonation ended, and remained at higher-than background levels for several hours. Based on these results, minimum re-entry times after ozone treatment were predicted for different indoor scenarios. Clearly defining re-entry times can serve as a practical measure to prevent acute exposures to ozone and harmful ozonation byproducts after treatment. This study evaluated potential benefits and risks associated with THS remediation using ozone, providing insights into this technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Assessing the Consistency of Estimated Ground Cover Fractions between the BLM AIM Method and Optical Remote Sensing Method

Since 2012, Argonne National Laboratory (Argonne) has supported the Bureau of Land Management (BLM) in developing remote sensing methodologies for long-term environmental monitoring of Palo Verde Mesa in eastern Riverside County, California, including methods for: detailed mapping of ephemeral streams, estimating fractional cover of desert-land surface components (e.g., trees, shrubs, litters, and bare ground), evaluating erosion risk or land stability, and characterizing vegetation alliances using spatial structure and geostatistical approaches. These studies showed the promise of remote sensing for monitoring changes in desert landscapes by providing information that would be difficult to obtain through field surveys. During this time the BLM has also worked to establish long-term monitoring protocols and compiled field-observation data collected using standardized protocols from the Assessment, Inventory, and Monitoring (AIM) strategy. The AIM data can be compared to data derived from remote sensing methods to evaluate their relative operational utility in monitoring landscape change. If ground cover estimated using remotely sensed imagery is comparable to AIM ground cover estimates, then remote sensing can be used to monitor whether any land cover change in desert landscapes may be related to solar energy development. Therefore, the goal of this study was to determine the consistency in ground cover estimates between AIM data and those derived from publicly- available remotely sensed imagery, such as that available through the U.S. Department of Agriculture, National Agricultural Imagery Program (NAIP), to examine feasibility of a remote sensing method for complementing AIM monitoring. Based on the image analysis in this study, we also provide recommendations for how small unmanned aerial system (sUAS) data may be used to complement BLM’s AIM data and NAIP imagery for future vegetation monitoring. The ground cover types we originally planned to investigate were trees, shrubs, and bare ground. However, the small sample size and a limited range of cover fraction of trees and shrubs in the AIM dataset (e.g., 33 samples with a maximum shrub cover of 18%, 14 samples with a maximum tree cover of 17%) did not allow for performing a meaningful evaluation for the remote sensing approach. Therefore, we conducted the study focusing on bare ground, foliar, and rock cover, all of which are indicators reported in the AIM remote sensing dataset.

47 OTHER INSTRUMENTATION↗

Optimal Sensor Selection for Health Monitoring Systems

Sensor data are the basis for performance and health assessment of most complex systems. Careful selection and implementation of sensors is critical to enable high fidelity system health assessment. A model-based procedure that systematically selects an optimal sensor suite for overall health assessment of a designated host system is described. This procedure, termed the Systematic Sensor Selection Strategy (S4), was developed at NASA John H. Glenn Research Center in order to enhance design phase planning and preparations for in-space propulsion health management systems (HMS). Information and capabilities required to utilize the S4 approach in support of design phase development of robust health diagnostics are outlined. A merit metric that quantifies diagnostic performance and overall risk reduction potential of individual sensor suites is introduced. The conceptual foundation for this merit metric is presented and the algorithmic organization of the S4 optimization process is described. Representative results from S4 analyses of a boost stage rocket engine previously under development as part of NASA's Next Generation Launch Technology (NGLT) program are presented.

Santi, L. Michael↗

Assessment of Medical Risks and Optimization of their Management using Integrated Medical Model

The Integrated Medical Model (IMM) Project is a software-based technique that will identify and quantify the medical needs and health risks of exploration crew members during space flight and evaluate the effectiveness of potential mitigation strategies. The IMM Project employs an evidence-based approach that will quantify probability and consequences of defined in-flight medical risks, mitigation strategies, and tactics to optimize crew member health. Using stochastic techniques, the IMM will ultimately inform decision makers at both programmatic and institutional levels and will enable objective assessment of crew health and optimization of mission success using data from relevant cohort populations and from the astronaut population. The objectives of the project include: 1) identification and documentation of conditions that may occur during exploration missions (Baseline Medical Conditions List [BMCL), 2) assessment of the likelihood of conditions in the BMCL occurring during exploration missions (incidence rate), 3) determination of the risk associated with these conditions and quantify in terms of end states (Loss of Crew, Loss of Mission, Evacuation), 4) optimization of in-flight hardware mass, volume, power, bandwidth and cost for a given level of risk or uncertainty, and .. validation of the methodologies used.

Fitts, Mary A.↗

Risk management and expert system development methodology

A risk-based expert-system development methodology has been developed to provide guidance to managers and technical personnel and to serve as a standard for developing expert systems. Expert-system development differs from conventional software development in that the information needed to prepare system requirements for expert systems is not known at the outset of a project and is obtained by knowledge engineering methods. The paper describes the expert-system life cycle, development methodology, and the approach taken in this methodology to manage and reduce the risks in expert system development. Also examined are the risks of using and of not using a methodology, the studies undertaken to validate the provisions of the expert system development methodology, and the results of these validation studies.

Hull, Larry↗

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Medicine and Pharmacogenomics for Human Deep Space Exploration

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expanding duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be even more essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to further tailor medications included in the spacecraft formulary and increased examination of appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of cutting-edge research and medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique factors and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. One example is the field of pharmacogenomics (PGX),the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on pharmaceutical choice and dosing to avoid adverse drug events and maximize pharmacological efficacy. The goal of this study was to evaluate which drugs in the current space pharmacy could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs onboard the International Space Station (ISS) was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both personal astronaut medications, including supplements and over the counter drugs (n=151) and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in 157 total drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure. Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent adverse events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost or technical and ranked from 1 (very low) to 5 (very high).A comprehensive assessment of commercially available PGX solutions is currently underway to evaluate specimen requirements, cost/benefit analysis (cost vs. number of alleles assessed), utility of variant analysis, relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments(LxC 5x5 table) indicated29medicationswere in the yellow or red zone driven predominantly by drug failure or safety concerns, with the remainder(n=128)of the medications in the green zone where risk is acceptable. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive pre-flight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve targeting drug efficacy and safety, and further open the door to countermeasure research exploring PGX-related allelic variants. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more cost effective and more efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing crew autonomy and providing tailored countermeasures

Alice R W Tang↗

Integrating Cyber-Informed Engineering into Process Automation

As organizations increasingly automate their core missions and essential functions to address business risks and enhance efficiency, process automation becomes pivotal. This shift, involving minimal or no manual intervention, significantly impacts an organization's cyber-risk landscape. While automation drives efficiencies, it also introduces new cyber risks if not properly managed. Cyber-Informed Engineering (CIE) provides a proactive framework for managing these digital risks, enhancing cyber-resilience in process automation. This document supports organizations in applying CIE principles to mitigate the cyber risks associated with automation. The outlined approach can be independently implemented to improve any organization’s cyber-resilience, ensuring that the advantages of automation do not result in unaddressed or unmanaged digital risks. It serves as a starting point, offering considerations for integrating CIE principles and practices into organizational processes. CIE is presented as an iterative process, fostering continuous improvement and reinforcing the engineering and operational cultures to manage digital risks effectively. The document is structured as follows: Section 1 provides background on CIE and process automation, and their integration. Section 2 explores the twelve CIE principles in the context of process automation, highlighting key questions, engineering considerations, and implications for digital risk management. Section 3 synthesizes the findings and offers recommendations to advance resilience by design.

42 - ENGINEERING↗

Multi‐Objective Urban Observational Strategies: A Risk‐Based Framework for Expanding Flood Sensor Networks

In coupled human and natural systems, developing an observation strategy which maximizes insight into both the natural system and the human system is a challenging multi-objective optimization problem. In this article, we describe the expansion of a flood risk observation system in Southeast Texas designed to improve our understanding of both physical and socioeconomic exposure to hydrological hazards at fine spatial scales, in the context of a structured hazard-exposure-vulnerability risk framework. We describe a new approach for assessing the spatial extent through which a flood sensor's observations can be assumed to be relevant, and estimate the population served within each sensor's area of information using downscaled socio-demographic data. As hydrological observations and modeling move to ever finer scale, assessing the information they contain in the context of both social and natural systems becomes increasingly important for developing actionable scientific insights.

54 ENVIRONMENTAL SCIENCES↗