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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Crew State and Risk Model (CSRM) - Medication Impacts on Physiologic Models for Exploration Class EVA Predictive Modeling and Operations

EVA and Environmental Physiology Laboratory (EEPL) wanted to expand upon the previous CSRM Physiologic Map to visually demonstrate the impact of medications on various modeling inputs that map to the seven physiologic models. It is acknowledged various physiologic states present during EVA could impact drug pharmacokinetics (i.e. pressure changes, core body temperature), which could impact pharmacodynamics. However, that is outside the scope of this document. The medications below represent the authors’ assumption of what medications will be available and able to impact an Artemis EVA and do not include the full ISS formulary, a final Artemis medical kit, or additional personal medications for individual crewmember’s chronic medical conditions.

Emma Ives↗
DOE OSTI2022

Eagle Behavior and Risk Modeling for Wind Energy Webinar

NREL presents recent progress in the development and validation of new eagle behavioral models, highlighting applications for wind-plant siting and operations. This webinar features talks focused on three areas: atmospheric modeling across the spatiotemporal scales of interest, facility-scale behavioral modeling, and turbine-scale data-driven behavioral modeling. A final presentation demonstrates micrositing as an application of our completely open-source analysis framework.

agent-based movement model↗
NASA NTRSDate not supplied

Integration of the Cardiovascular Clinical Risk Prediction Model Astro-CHARM Into the NASA Radiation Risk Model

Space radiation poses an increased risk for cardiovascular diseases (CVD) during and after spaceflight, that should be quantified to plan future space missions such as the flight to Mars. The radiation-induced CVD risk is evaluated using a linear no-threshold dose response excess relative risk (ERR) model, so that the risk is function of the radiation dose and of the background (i.e., non-exposed) incidence rate. The background CVD risk can be evaluated using clinical prediction models (CPMs). The first CPMs developed in the 1960’s have identified CVD risk factors such as blood pressure, diabetes, cholesterol, and smoking. In this work, the steps used to integrate the CVD risk provided by a CPM into the NASA Radiation Risk Model are described. Simulation results calculated using available data for relevant mission scenarios are also shown, and the challenges in CVD risk predictions are discussed.

I Plante↗
NASA NTRS2017

Modelling the Risks Remotely Piloted Aircraft Pose to People on the Ground

Worldwide there is much e ort being directed towards the development of a framework of air- worthiness regulations for remotely piloted aircraft systems (RPAS). It is now broadly accepted that regulations should have a strong foundation in, and traceability to, the management of the safety risks. Existing risk models for RPAS operations do not provide a simple means for incorporating the wide range of technical and operational controls into the risk analysis and evaluation processes. This paper describes a new approach for modelling and evaluating the risks associated with RPAS operations near populous areas based on the barrier bow tie (BBT) model. A BBT model is used to structure the underlying risk management problem. The model focuses risk analysis, evaluation, and decision making activities on the devices, people, and processes that can be employed to reduce risk. The BBT model and a comprehensive set of example risk controls are presented. The general model can be applied to any RPAS operation. The foundations for quantitative and qualitative assessments using a BBT model are also presented. The modelling and evaluation framework is illustrated through its application to a case-study rotary wing RPAS for two operational scenarios. The model can be used as a basis for determining airworthiness certification requirements for RPAS.

Barrier bow tie model↗
DOE OSTI2020

Choosing the Best Modeling Platform for Radiological Risk Assessment Models - 20468

Radiological risk assessments, in the form of performance or safety assessments, are often required under regulations or guidance for remediation of contaminated land, decommissioning of contaminated buildings or structures, and radioactive waste disposal. These risk assessments are usually supported by fate and transport models that address decay and ingrowth of radionuclides, as well as their movement through engineered systems and the natural environment. These models are often projected thousands, or more, years into the future, largely because the radioactive species change through decay and ingrowth, and hence the magnitude of the radioactive effect changes with time. There are many computer codes that are available to address this type of modeling. They range from addressing specific pathways or processes such as infiltration of water, groundwater, surface water, air, biota, diffusion and advection of water and gases, to those that try to couple all processes together to evaluate the impact of fate and transport through the entire system to places in space and time to which access is assumed. These different types of codes are sometimes separated with the monikers process-level and systems-level codes, although it is often not clear that this separation does justice to the capabilities of the many codes that are available to evaluate fate and transport of radionuclides. The focus of this paper is the latter group of modeling codes. Several systems level modeling codes exist and are used. There are differences between these codes in terms of utility, flexibility, complexity and cost. The purpose of this paper is to compare a few of these codes in the context of work currently being performed by the International Atomic Energy Agency (IAEA) Modeling and Data for Radiological Impact Assessments (MODARIA) II Working Group 1 (WG1). The MODARIA II WG1's main focus is how stakeholder engaged decision analysis can, or should, be applied to radiological contamination problems so that better, longstanding, sustainable, solutions are reached. However, the WG1 also recognizes the potential impact of the modeling tools that are chosen to address radiological risk, which is often a primary objective of decision making for radiological problems. Other objectives might also be important, such as constraining costs, obtaining financing, minimizing impact on ecosystems, saving cultural resources, saving jobs, farmland, environmental justice, etc., in a full decision analysis for a given radiological contamination problem, but none of these other objectives have the same types of complex modeling needs as minimize radiological dose. Consequently, a further focus of WG1 is to evaluate the potential impacts on decision making of the choice of fate and transport, and risk assessment, modeling codes that are used to support decision making. The WG1 will produce a report at the end of 2020 that will focus on an approach to effective decision making and stakeholder engagement. The report will also consider the role that performance assessment modeling should play in the decision-making process, including the impact of the choice of modeling tools or computer codes on risk-informed decision making. Several sites around the World have been made available by Member States for these model comparisons, and several modeling tools have been considered. However, the focus of this paper is on two of the sites, one in Belgium and one in Ukraine, and on three of the tools: NORMALYSA (NORM And Legacy Site Assessment); GoldSim{sup C}, and AMBER{sup C}. The final report from this working group will also cover other modeling tools, including RESRAD, and PC-Cream{sup R}. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2012

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties 2010 (Cucinotta et al., 2011). The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables cited more formally as Cucinotta et al. (2011). The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. They include, more recently: (1) The "BEIR VII Phase 2" report from the NRC's Committee on Biological Effects of Ionizing Radiation (BEIR) (NRC, 2006); (2) Studies of Radiation and Cancer from the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR, 2006), (3) The 2007 Recommendations of the International Commission on Radiological Protection (ICRP), ICRP Publication 103 (ICRP, 2007); and (4) The Environmental Protection Agency s (EPA s) report EPA Radiogenic Cancer Risk Models and Projections for the U.S. Population (EPA, 2011). The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements (NCRP, 2000, 2006). However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors (Preston et al., 2007), transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Source record↗
NASA NTRS1999

The Use of the Satellite Breakup Risk Assessment Model (SBRAM) to Characterize Collision Risk to Manned Spacecraft

NASA uses environment models such as ORDEM96 to characterize the long-term orbital debris collision hazard for spacecraft in LEO. Occasionally, however, there are breakups of satellites or rocket bodies that create enhanced collision hazard for a period of time. This enhanced collision hazard can pose increased risks to space operations - especially those involving manned missions where the tolerance for risk is very low. NASA has developed SBRAM to simulate the enhanced debris environment in the days and weeks that follow such a breakup. This simulation provides the kind of risk probabilities that can be used by mission planners to consider if changes are warranted for the mission. Announcements of breakups come to NASA from US Space Command as soon as they are identified. The pre-breakup orbit and time of breakup are used to determine the initial conditions of the explosion. SBRAM uses the latest explosion models developed at NASA to simulate a debris cloud for the breakup. The model uses a Monte Carlo technique to create a random debris cloud from the probability distributions in the breakup model. Each piece of debris randomly created in the cloud is propagated in a deterministic manner to include the effects of drag and other orbital perturbations. The detailed geometry of each simulated close approach to the target spacecraft is noted and logged and the collision probability is computed using an estimated probability density in down-range and cross-range positions of both the target spacecraft and debris object. The collision probability is computed from the overlap of these probability densities for each close-approach geometry and summed over all computed conjunctions. Cloud propagation runs over the desired time interval are then repeated until the scale of the collision risk can be estimated to a desired precision. This paper presents an overview of the SBRAM model and a number of examples, both real and hypothetical, to demonstrate its use. In addition, a number of different examples are shown how the data can be used by decision makers on issues such as spacecraft orientation and timing of EVAs.

Matney, Mark J.↗
NASA NTRS2011

Methodology for Developing a Probabilistic Risk Assessment Model of Spacecraft Rendezvous and Dockings

In 2007 NASA was preparing to send two new visiting vehicles carrying logistics and propellant to the International Space Station (ISS). These new vehicles were the European Space Agency s (ESA) Automated Transfer Vehicle (ATV), the Jules Verne, and the Japanese Aerospace and Explorations Agency s (JAXA) H-II Transfer Vehicle (HTV). The ISS Program wanted to quantify the increased risk to the ISS from these visiting vehicles. At the time, only the Shuttle, the Soyuz, and the Progress vehicles rendezvoused and docked to the ISS. The increased risk to the ISS was from an increase in vehicle traffic, thereby, increasing the potential catastrophic collision during the rendezvous and the docking or berthing of the spacecraft to the ISS. A universal method of evaluating the risk of rendezvous and docking or berthing was created by the ISS s Risk Team to accommodate the increasing number of rendezvous and docking or berthing operations due to the increasing number of different spacecraft, as well as the future arrival of commercial spacecraft. Before the first docking attempt of ESA's ATV and JAXA's HTV to the ISS, a probabilistic risk model was developed to quantitatively calculate the risk of collision of each spacecraft with the ISS. The 5 rendezvous and docking risk models (Soyuz, Progress, Shuttle, ATV, and HTV) have been used to build and refine the modeling methodology for rendezvous and docking of spacecrafts. This risk modeling methodology will be NASA s basis for evaluating the addition of future ISS visiting spacecrafts hazards, including SpaceX s Dragon, Orbital Science s Cygnus, and NASA s own Orion spacecraft. This paper will describe the methodology used for developing a visiting vehicle risk model.

Farnham, Steven J., II↗
DOE OSTI2022

Airport Risk Assessment Model (ARAM)

The Airport Risk Assessment Model (ARAM) model automatically determines the optimal allocation of limited security resources to minimize total risk to the airport. At the same time, the model adds an element of randomness to the, reducing the predictability of asset schedules and further increasing countermeasure effectiveness.

Brigantic, Robert↗
DOE OSTI2022

The modeling of risk perception in the use of structural health monitoring information for optimal maintenance decisions

This paper proposes an approach to select a maintenance strategy from a predefined set of choices considering the decision maker’s behavioral risk profile. It is assumed that the damage state is characterized by a continuous state parameter probabilistically inferred from observable sensor data. This work applies an engineering application of consequence-based decision-making incorporating the acceptable risk intensity of the decision-maker, i.e., the decision-maker’s (individual or an organization) valuation of the outcome of a decision, using a risk profile model. The utility of a decision-maker is subjective, and this paper considers the fact that different decision-makers mentally assign a different importance factor (the utility) to the seriousness or urgency to take necessary actions with the increasing intensity of structural damage. The approach herein incorporates a layer of human psychology on selecting appropriate maintenance strategies that not only depend on the posterior distribution of unmeasurable damage state but also consider the behavioral risk profile of the decision-maker. Further, the collective decision-making of an organization consisting of many individuals is also investigated. The approach is exemplified in a case study involving life cycle monitoring of a miter gate, part of a lock system enabling navigation of inland waterways.

42 ENGINEERING↗
NASA NTRS2010

An Accident Precursor Analysis Process Tailored for NASA Space Systems

Accident Precursor Analysis (APA) serves as the bridge between existing risk modeling activities, which are often based on historical or generic failure statistics, and system anomalies, which provide crucial information about the failure mechanisms that are actually operative in the system and which may differ in frequency or type from those in the various models. These discrepancies between the models (perceived risk) and the system (actual risk) provide the leading indication of an underappreciated risk. This paper presents an APA process developed specifically for NASA Earth-to-Orbit space systems. The purpose of the process is to identify and characterize potential sources of system risk as evidenced by anomalous events which, although not necessarily presenting an immediate safety impact, may indicate that an unknown or insufficiently understood risk-significant condition exists in the system. Such anomalous events are considered accident precursors because they signal the potential for severe consequences that may occur in the future, due to causes that are discernible from their occurrence today. Their early identification allows them to be integrated into the overall system risk model used to intbrm decisions relating to safety.

Groen, Frank↗
NASA NTRS2002

A Quantitative Software Risk Assessment Model

This slide presentation reviews a risk assessment model as applied to software development. the presentation uses graphs to demonstrate basic concepts of software reliability. It also discusses the application to the risk model to the software development life cycle.

Lee, Alice↗
NASA NTRS2001

Quantitative risk assessment system (QRAS)

A quantitative risk assessment system (QRAS) builds a risk model of a system for which risk of failure is being assessed, then analyzes the risk of the system corresponding to the risk model. The QRAS performs sensitivity analysis of the risk model by altering fundamental components and quantifications built into the risk model, then re-analyzes the risk of the system using the modifications. More particularly, the risk model is built by building a hierarchy, creating a mission timeline, quantifying failure modes, and building/editing event sequence diagrams. Multiplicities, dependencies, and redundancies of the system are included in the risk model. For analysis runs, a fixed baseline is first constructed and stored. This baseline contains the lowest level scenarios, preserved in event tree structure. The analysis runs, at any level of the hierarchy and below, access this baseline for risk quantitative computation as well as ranking of particular risks. A standalone Tool Box capability exists, allowing the user to store application programs within QRAS.

Weinstock, Robert M↗