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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

The Use of the Integrated Medical Model for Forecasting and Mitigating Medical Risks for a Near-Earth Asteroid Mission

Introduction The Integrated Medical Model (IMM) is a decision support tool that is useful to space flight mission managers and medical system designers in assessing risks and optimizing medical systems. The IMM employs an evidence-based, probabilistic risk assessment (PRA) approach within the operational constraints of space flight. Methods Stochastic computational methods are used to forecast probability distributions of medical events, crew health metrics, medical resource utilization, and probability estimates of medical evacuation and loss of crew life. The IMM can also optimize medical kits within the constraints of mass and volume for specified missions. The IMM was used to forecast medical evacuation and loss of crew life probabilities, as well as crew health metrics for a near-earth asteroid (NEA) mission. An optimized medical kit for this mission was proposed based on the IMM simulation. Discussion The IMM can provide information to the space program regarding medical risks, including crew medical impairment, medical evacuation and loss of crew life. This information is valuable to mission managers and the space medicine community in assessing risk and developing mitigation strategies. Exploration missions such as NEA missions will have significant mass and volume constraints applied to the medical system. Appropriate allocation of medical resources will be critical to mission success. The IMM capability of optimizing medical systems based on specific crew and mission profiles will be advantageous to medical system designers. Conclusion The IMM is a decision support tool that can provide estimates of the impact of medical events on human space flight missions, such as crew impairment, evacuation, and loss of crew life. It can be used to support the development of mitigation strategies and to propose optimized medical systems for specified space flight missions. Learning Objectives The audience will learn how an evidence-based decision support tool can be used to help assess risk, develop mitigation strategies, and optimize medical systems for exploration space flight missions.

Kerstman, Eric↗
DOE OSTI2022

1.3.3.402 - Cybersecurity Value-at-Risk Framework

The Cybersecurity Value-at-Risk Framework tool will guide users through an assessment and detailed analysis of a hydropower plant's operations. The tool will then provide results and data to inform effective cybersecurity investment decision-making and planning. The results will help managers understand the risk probability of cyberattacks on their facilities and how best to use resources to mitigate those risks.

cybersecurity↗
NASA NTRSDate not supplied

Future Improvements to Impact for Long Duration Exploration Spaceflight

BACKGROUND: While NASA currently uses the Integrated Medical Model (IMM) to model spaceflight medical risk for Low Earth Orbit missions, IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) was created to improve the fidelity of medical risk analysis for exploration missions involving the Lunar surface and beyond. OVERVIEW: While completion work continues on the initial version of the IMPACT tool, work has already begun to investigate ways to further enhance the fidelity of the model and its utility to stakeholders. DISCUSSION: Future additions leveraging the more robust and flexible IMPACT architecture include analyzing mission segments to account for segment-specific environments (ie. Lunar surface or microgravity), clinically tracible outcomes based on partial treatment of conditions, the ability to model mission outcomes based on provider Knowledge, Skills, and Abilities (KSAs), and the ability to affect the incidence of conditions based on the occurrence of related conditions (e.g. UTI progressing to sepsis). IMPACT also enables the addition of new conditions to its database as required to meet future risk assessment needs. Ultimately, the desire is to broaden IMPACT from a tool that models/trades medical risk to one that does so for all crew health and performance relevant systems (e.g., food, exercise, etc.).

E Stratton↗
NASA NTRS2019

New York City Panel on Climate Change 2019 Report Chapter 1: Introduction

While urban areas like New York City and its surrounding metropolitan region are key drivers of climate change through emissions of greenhouse gases, cities are also significantly impacted by climate shifts, both chronic changes and extreme events. These are already affecting the New York metropolitan region, including the five boroughs of New York City through higher temperatures, more intense precipitation, and higher sea levels, and will increasingly do so in the coming decades. The City of New York has embarked on a flexible adaptation pathway (i.e., strategies that can evolve through time as climate risk assessment, evaluation of adaptation strategies, and monitoring continues) to respond to climate change challenges. This entails significant programs to develop resilience in communities and critical infrastructure to observed and projected changes in temperature, precipitation, and sea level. The first NPCC Report laid out the risk management framing for the city and region via flexible adaptation pathways. The second New York City Panel on Climate Change Report (NPCC2) developed the “climate projections of record” that are currently being used by the City of New York in its resilience programs . The NPCC3 2019 Report co-generates new tools and methods for the next generation of climate risk assessments and implementation of region-wide resilience. Co-generation is an interactive process by which stakeholders and scientists work together to produce climate change information that is targeted to decision-making needs. These tools and methods can be used to observe, project, and map climate extremes; monitor risks and responses; and engage with communities to develop effective programs. They are especially important at “transformation points” in the adaptation process when large changes in the structure and function of physical, ecological, and social systems of the city and region are undertaken.

Rosenzweig, Cynthia↗
DOE OSTI2021

Physics-Informed Machine Learning-Aided System Space Discretization

Decision-making is the process of identifying and choosing alternatives based on an agreed-upon set of metrics and preferences established by the decision-maker. There are options to be considered during the decision-making process and each option offers a different trajectory and associated success profile in moving from a given system state to the desired system state. The decision-making process typically involves uncertainties associated with the current component and system states. In this sense, probabilistic risk assessment (PRA) can be an analytical method and tool for accomplishing the probabilistic aspect of the decision-making process. Dynamic PRA is an evolution of conventional PRA methodology in which driving forces on modeled plant elements and the element behaviors are explicitly modeled over time. In the recent past, risk assessment methodologies have evolved to address risk issues in a continuously evolving environment and a novel probabilistic dynamics framework in continuous time and state-space discretization forms has been proposed. While state-space discretization has shown its strength in both consequence and causal reasoning modes, several challenges, including the computational requirement and physically meaningful system state identification, exist. Conventional system space discretization has usually been done by either the equal width discretization method or a data-driven method. Those methods naturally possess challenges coming from the physical understanding of discretized system space (i.e., system state) and the trajectory moving from a given system state to another system state. The purpose of this paper is to present a physics-based and data-driven system state discretization method such that one can justify what the discretized system space implies and understand the state trajectory from the viewpoint of operational actions.

Kim, Junyung↗
DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

New technologies as decision aids for the advancement of ecological risk assessment

Moore's law states that the number of transistors that can be placed on an integrated circuit doubles every two years (Moore, 1975). This has led to a steady increase in the processing power of computers over time, and technology is now enhancing and advancing software and scientific applications, which has enabled computationally intensive methods such as machine learning, data science, modeling, and simulation. The advancement of computers and data-driven algorithms is profoundly impacting people's lives. It is changing the way we work, the way we learn, and the way we interact with the world around us. Here, this editorial will discuss how scientists can benefit from the latest technology advancements and related tools by incorporating them into the ecological risk assessment (ERA) to study ecosystems as a way to create refined assessments and accelerate the turnaround times.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating the Aftershock Duration of Induced Earthquakes

As the carbon sequestration community prepares to scale up the number and size of commercial operations, the need for tools and methods to assess and mitigate risks associated with these operations becomes increasingly important. One outstanding question is whether aftershocks of induced events decay quickly after injection operations cease or if aftershock activity persists for hundreds of years before returning to background levels more akin to tectonic events (Stein and Liu, 2009). Appropriate estimates of the aftershock duration impact several operational management decisions including mitigation strategies and post-injection monitoring for seismic activity. It is hypothesized that induced earthquake rates may diminish more quickly after injection is stopped, owing to higher stressing rates from injected fluids. Alternatively, it is plausible that only the first event in the sequence is induced by increased fluid overpressures, whereas subsequent events (e.g., aftershocks) respond to the stored tectonic stresses and static and dynamic stress changes due to the mainshock (Keranen et al., 2013). Further, if the aftershock duration can be linked to stressing rates due to injection, then it follows that operational strategies to reduce seismic hazard by reducing injection rates or volumes may be successful. However, if aftershocks of induced events are relieving stored tectonic stresses, then altering injection volumes may not alleviate ongoing seismic activity. Furthermore, knowledge of an aftershock duration could aid in the determination of an appropriate post-injection monitoring period for ongoing seismicity, which is a factor in overall operational costs. In this study, we model induced seismicity sequences in Oklahoma with a coupled Coulomb rate–state earthquake rate model (Dieterich, 1994; Kroll et al., 2017) to estimate aftershocks durations. Results for the current study indicate that elevated rates of aftershock activity following induced mainshocks return to background seismicity rates in less than five years, contrary to the tens to hundreds of years observed for tectonic aftershocks.

58 GEOSCIENCES↗
DOE OSTI2023

Hydropower Cybersecurity Value-at-Risk Framework

Hydropower remains one of the strongest forms of renewable energy generation methods. It is crucial to address the increasing risks associated with the rapid digitization. The push towards decarbonization also factors in the need to ensure security and resilience for grid-connected renewable energy resources. This report summarizes the U.S. Department of Energy's Water Power Technologies Office's effort to develop a cybersecurity valuation methodology that assists hydropower stakeholders in assessing risks associated with plan operations and gathers valuation guidance through a web-based application. The Hydropower Cybersecurity Value-at-Risk Framework delivers a platform for industry members to perform self-assessments and make informed decisions on their cybersecurity investments.

13 HYDRO ENERGY↗
NASA NTRS2001

Advanced Finite Element Modeling of Low Cycle Fatigue Crack Growth

This document (a viewgraph presentation) assumes a crack-like defect of a size which may be missed in inspection will exist in most critical location of any critical structure or component. Flaw existence assumption is usually, but not always, conservative based on past experiences in NASA and knowledge of manufacturing processes. Cyclic, environmental, and sustained loads used to generate stresses on models. Fracture Mechanics analysis used to predict crack growth and residual strength. Must show that defective structure will still provide four times required mission lifetime. Special exemptions cover redundant structures, low risk parts, etc. Assessments require specialized software tools, experienced analysts, and reliable material crack growth rate test database.

Gregg, Wayne↗
NASA NTRS2005

Enhancing the Design Process for Complex Space Systems through Early Integration of Risk and Variable-Fidelity Modeling

An important enabler of the new national Vision for Space Exploration is the ability to rapidly and efficiently develop optimized concepts for the manifold future space missions that this effort calls for. The design of such complex systems requires a tight integration of all the engineering disciplines involved, in an environment that fosters interaction and collaboration. The research performed under this grant explored areas where the space systems design process can be enhanced: by integrating risk models into the early stages of the design process, and by including rapid-turnaround variable-fidelity tools for key disciplines. Enabling early assessment of mission risk will allow designers to perform trades between risk and design performance during the initial design space exploration. Entry into planetary atmospheres will require an increased emphasis of the critical disciplines of aero- and thermodynamics. This necessitates the pulling forward of EDL disciplinary expertise into the early stage of the design process. Radiation can have a large potential impact on overall mission designs, in particular for the planned nuclear-powered robotic missions under Project Prometheus and for long-duration manned missions to the Moon, Mars and beyond under Project Constellation. This requires that radiation and associated risk and hazards be assessed and mitigated at the earliest stages of the design process. Hence, RPS is another discipline needed to enhance the engineering competencies of conceptual design teams. Researchers collaborated closely with NASA experts in those disciplines, and in overall space systems design, at Langley Research Center and at the Jet Propulsion Laboratory. This report documents the results of this initial effort.

Mavris, Dimitri↗
NASA NTRS2010

The Multispectral Microscopic Imager: Integrating Microimaging with Spectroscopy for the In-Situ Exploration of the Moon

To maximize the scientific return, future robotic and human missions to the Moon will need to have in-situ capabilities to enable the selection of the highest value samples for returning to Earth, or a lunar base for analysis. In order to accomplish this task efficiently, samples will need to be characterized using a suite of robotic instruments that can provide crucial information about elemental composition, mineralogy, volatiles and ices. Such spatially-correlated data sets, which place mineralogy into a microtextural context, are considered crucial for correct petrogenetic interpretations. . Combining microscopic imaging with visible= nearinfrared reflectance spectroscopy, provides a powerful in-situ approach for obtaining mineralogy within a microtextural context. The approach is non-destructive and requires minimal mechanical sample preparation. This approach provides data sets that are comparable to what geologists routinely acquire in the field, using a hand lens and in the lab using thin section petrography, and provide essential information for interpreting the primary formational processes in rocks and soils as well as the effects of secondary (diagenetic) alteration processes. Such observations lay a foundation for inferring geologic histories and provide "ground truth" for similar instruments on orbiting satellites; they support astronaut EVA activities and provide basic information about the physical properties of soils required for assessing associated health risks, and are basic tools in the exploration for in-situ resources to support human exploration of the Moon.

Nunez, J. I.↗
NASA NTRS2013

NASA Human Research Program Space Radiation Program Element

The goal of the NASA Human Research Program's Space Radiation Program Element is to ensure that crews can safely live and work in the space radiation environment. Current work is focused on developing the knowledge base and tools required for accurate assessment of health risks resulting from space radiation exposure including cancer and circulatory and central nervous system diseases, as well as acute risks from solar particle events. Division of Space Life Sciences (DSLS) Space Radiation Team scientists work at multiple levels to advance this goal, with major projects in biological risk research; epidemiology; and physical, biophysical, and biological modeling.

Chappell, Lori↗
NASA NTRS2014

Mixed-field GCR Simulations for Radiobiological Research Using Ground Based Accelerators

Space radiation is comprised of a large number of particle types and energies, which have differential ionization power from high energy protons to high charge and energy (HZE) particles and secondary neutrons produced by galactic cosmic rays (GCR). Ground based accelerators such as the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory (BNL) are used to simulate space radiation for radiobiology research and dosimetry, electronics parts, and shielding testing using mono-energetic beams for single ion species. As a tool to support research on new risk assessment models, we have developed a stochastic model of heavy ion beams and space radiation effects, the GCR Event-based Risk Model computer code (GERMcode). For radiobiological research on mixed-field space radiation, a new GCR simulator at NSRL is proposed. The NSRL-GCR simulator, which implements the rapid switching mode and the higher energy beam extraction to 1.5 GeV/u, can integrate multiple ions into a single simulation to create GCR Z-spectrum in major energy bins. After considering the GCR environment and energy limitations of NSRL, a GCR reference field is proposed after extensive simulation studies using the GERMcode. The GCR reference field is shown to reproduce the Z and LET spectra of GCR behind shielding within 20% accuracy compared to simulated full GCR environments behind shielding. A major challenge for space radiobiology research is to consider chronic GCR exposure of up to 3-years in relation to simulations with cell and animal models of human risks. We discuss possible approaches to map important biological time scales in experimental models using ground-based simulation with extended exposure of up to a few weeks and fractionation approaches at a GCR simulator.

Kim, Myung-Hee Y.↗
NASA NTRS2018

The Growth of Mass and Reliability Source Database and Me

Mass and Reliability Source (MaRS) is a database which draws together information from multiple other sources and databases (MADS, VMDB, ISS PART, Bayesian PowerPoint, etc.). Information such as mass, operating hours, and failure data are compiled to create a tool for the building of probabilistic Risk Assessment (PRA) models. MaRS also has great potential for deep space mission planning. Understanding the lowest point of failure within an ORU helps to inform the efficient selection of spare parts necessary for a journey where mass and volume are at a premium and resupply is not possible.

George, Cory A.↗
DOE OSTI2023

Geomechanical Characterization of the Mount Simon Sandstone and Eau Claire Formation of Northern Illinois Basin

The purpose of this paper is to analyze publicly available geomechanical data from two carbon storage sites in the Illinois Basin: the Illinois Basin-Decatur Project (IBDP) in Macon County, IL and the FutureGen2.0 project in Morgan County, IL, cancelled before injection began. This study estimates the magnitudes and directions of the least compressive principal stress gradient using hydraulic fracture-based stress measurement tests, borehole breakouts, and sonic logs in the Eau Claire Formation (primary confining zone) and the Mount Simon Sandstone (targeted reservoir). The range of stresses expected in the underlying Precambrian basement is also investigated. The evaluation of the state of stress is carried out in a probabilistic manner using the State of Stress Analysis Tool (SOSAT) developed under the National Risk Assessment Partnership (NRAP) program. Finally, the paper also provides a discussion on distinctions between fracture initiation pressure, propagation pressure, and fracture closure pressure, given that hydraulic fracture testing results show a significant difference between these three values. The discussion also addresses why the fracture closure pressure should be preferred in injection pressure determinations, a critical point in geological carbon storage projects.

de Toledo Camargo, Julia↗
DOE OSTI2021

Optimization of Mitigating System Performance Index to Improve Nuclear Power Plant Safety and Efficiency

MSPI (Mitigation System Performance Index) is one of the risk-informed, plant-specific performance indicators of NRC’s Reactor Oversight Process. MSPI is used by the regulator and nuclear industry to monitor and assess the performance of plant mitigating systems. In this project, a calculation tool has been developed by incorporating the plant operation data, Probabilistic Risk Assessment (PRA) data, and industry baseline values to automate the calculation process of MSPI and the generation of the report. This is the first stage in an effort to optimize the MSPI through advanced artificial intelligence (AI) and machine learning (ML) techniques to improve nuclear power plant safety and efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

NRAP-Open-IAM Multisegmented Wellbore Reduced-Order Model

Geologic carbon storage is one of the promising strategies to mitigate climate change by reducing the emission of carbon dioxide to the atmosphere. As part of the National Risk Assessment Partnership (NRAP), a systems-level stochastic analysis tool called the open source integrated assessment model, NRAP-Open-IAM, has been developed to estimate and manage the risk of containment loss at a geological carbon sequestration site. NRAP-Open-IAM contains several wellbore leakage model components that estimate the fluid leak rate that may occur through compromised legacy wells due to the increase in pressure resulting from CO 2 injection activities. Coupled to a reservoir component model, these components estimate the leakage of CO 2 and/or brine from a storage reservoir to overlying aquifer layers and the atmosphere through legacy wells. This report presents the theoretical framework and quality testing of the multisegmented wellbore reduced-order model. The model allows for segmenting of the legacy wells passing through the overlying stratigraphy into several intervals to simulate a site’s specific stratigraphic and hydrogeologic properties. For quality assurance, the analytical model is validated against numerical reservoir flow simulations for single and multiple aquifer(s) models. The results indicate that the model accurately predicts the transport of two-phase fluids (brine and injected CO 2 ) through the well over time. A detailed description of the model helps users to understand the model and provides a basis for future improvements.

58 GEOSCIENCES↗