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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Risk Reduction for the System Design of an Enhanced MMRTG

Engineering of an enhanced Multi-Mission Radioisotope Thermoelectric Generator (eMMRTG) began 3 years ago with agreement between the U.S. National Aeronautics and Space Administration (NASA) and the U.S. Department of Energy (DOE). The Jet Propulsion Laboratory is leading the transfer of skutterudite thermoelectric couple technology to industry and leading the systems engineering of the proposed eMMRTG. Should NASA fund the flight development of an eMMRTG, the DOE would lead the flight system development. The analytical models and design of the MMRTG have been enhanced to use skutterudite couples developed at Jet Propulsion Laboratory over the last two decades. This required a thorough evaluation of the MMRTG design, and concurrent engineering of an enhanced MMRTG to shed light on potential design issues or risks. At the end of the U.S. fiscal year (FY) 2015, a complete catalog of risks was produced. Tests, hardware development, and analyses have now been put in place to mitigate those risks to acceptable levels. Few risks can ever be truly eliminated unless a design is modified to eliminate specific risks and not introduce more severe risks. The design imperative for the eMMRTG is to change only a few MMRTG features; therefore, risks can largely only be mitigated, not eliminated, through design changes. However, many risks can be effectively - though not totally - eliminated without design changes. This paper briefly describes some of the documented risks and mitigations or reduction approaches to be applied in the coming 3 years, on the way to completing the eMMRTG concept.

eMMRTG↗
DOE OSTI2025

Data Centers and Digital Assurance Workshop 3 – Mitigations for Digital Assurance Risks

The third session of the TADA (Technical Assistance for Digital Assurance) Data Centers Cohort, held on November 18, 2025, focused on developing mitigation strategies for digital assurance risks identified in previous workshops. Hosted by Idaho National Laboratory (INL) and ScottMadden, the session emphasized the application of Cyber-Informed Engineering (CIE) to data center infrastructure, particularly at the utility–data center interface. Participants revisited and ranked key digital assurance risks, including architecture and interface weaknesses, governance gaps, and AI-enabled threats. The workshop introduced the 12 principles of CIE, advocating for consequence-focused design, engineered controls, and secure information architecture to proactively reduce cyber-physical vulnerabilities. These principles were applied to critical data center systems such as power distribution, UPS, cooling, SCADA/BMS, and grid-forming batteries. The session also addressed governance challenges at the interconnection boundary, highlighting the need for clear roles in telemetry sharing, firmware management, and trip settings. Special attention was given to emerging risks from behind-the-meter (BTM) generation, including reverse-power flow and the integration of small modular reactors (SMRs), which shift data centers from large loads to complex generation nodes. Participants explored how interconnection agreements can serve as enforceable instruments for digital assurance, and reviewed gaps in current standards such as NERC CIP, IEC 62443, and IEEE 1547. The workshop concluded with pathways to standardization, including model agreement language, state-level programs, and expanded NERC guidance. INL also presented tools and frameworks for secure procurement and supplier risk management, reinforcing the need for integrated engineering and policy solutions to secure the evolving data center–grid ecosystem. Session 3 of 3.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2004

The NASA Continuous Risk Management Process

As an intern this summer in the GRC Risk Management Office, I have become familiar with the NASA Continuous Risk Management Process. In this process, risk is considered in terms of the probability that an undesired event will occur and the impact of the event, should it occur (ref., NASA-NPG: 7120.5). Risk management belongs in every part of every project and should be ongoing from start to finish. Another key point is that a risk is not a problem until it has happened. With that in mind, there is a six step cycle for continuous risk management that prevents risks from becoming problems. The steps are: identify, analyze, plan, track, control, and communicate & document. Incorporated in the first step are several methods to identify risks such as brainstorming and using lessons learned. Once a risk is identified, a risk statement is made on a risk information sheet consisting of a single condition and one or more consequences. There can also be a context section where the risk is explained in more detail. Additionally there are three main goals of analyzing a risk, which are evaluate, classify, and prioritize. Here is where a value is given to the attributes of a risk &e., probability, impact, and timeframe) based on a multi-level classification system (e.g., low, medium, high). It is important to keep in mind that the definitions of these levels are probably different for each project. Furthermore the risks can be combined into groups. Then, the risks are prioritized to see what risk is necessary to mitigate first. After the risks are analyzed, a plan is made to mitigate as many risks as feasible. Each risk should be assigned to someone in the project with knowledge in the area of the risk. Then the possible approaches to choose from are: research, accept, watch, or mitigate. Next, all risks, mitigated or not, are tracked either individually or in groups. As the plan is executed, risks are re-evaluated, and the attribute values are adjusted as necessary. Metrics are established and monitored as tools for risk tracking. Also a trigger or threshold should be set on the metric data that indicates when an action is needed. Results of this tracking are usually evaluated and reported in a relevant format at weekly or monthly meetings. Choosing controls is the subsequent step, which involves the effects of the tracking. The three basic controls are: close, continue tracking, and re- plan. Finally communicate & document is the last step, but occurs throughout the process. It is vital that main risks, plans, changes, and progress are known by everyone in the project. A good way to keep everyone updated and inform other projects of common issues is by thoroughly documenting project risks. NASA sees value in risk management and believes that projects have greater probability or success by using the NASA Continuous Risk Management Process.

Pokorny, Frank M.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-31853-DND

Risk that Orion arrives later than Space Launch System (SLS). MSO mitigates this risk by using a mass simulator for SLS’ tests. An Orion simulator for the Integrated Modal Test (IMT) and Umbilical Release and Retraction Tests (URRT) mitigates schedule risk by significant timeframe. A clean sheet alternate being pursued - analysis shows matching modal characteristics unnecessary; rigid simulator is acceptable wrt existing SLS accelerometer locations and shaker placement/size. Key Simulator Requirements: Representative mass, CG, rigid modal characteristics, high fidelity interface at MSA. Pre-test analyses show that MSO vertical CG could be up to 40” low without affecting IMT.

Steve Cutright↗
NASA NTRS2015

Identification and Evaluation of Integration and Cross Cutting Issues Across HRP Risks

The HRP Integrated Research Plan contains the research plans for the 32 risks requiring research to characterize and mitigate. These risks to human health and performance in spaceflight are identified by evidence and each one focuses on a single aspect of human physiology or performance. They are further categorized by aspects of the spaceflight environment, such as altered gravity or space radiation, that that play a major role in their likelihood and consequence. From its inception the "integrate" in the Research Plan has denoted the integrated nature of risks to human health and performance, the connectedness of physiological systems within the human body regardless of the spaceflight environment, and the integrated response of the human body to the spaceflight environment. Common characteristics of the spaceflight environment include altered gravity, atmospheres and light/dark cycles, space radiation, isolation, noise, and periods of high or low workload. Long term exposure to this unique environment produces a suite of physiological effects such as stress; vision, neurocognitive and anthropometric changes; circadian misalignment; fluid shifts, deconditioning; immune dysregulation; and altered nutritional requirements. Matrix diagraming was used to systematically identify, analyze and rate the many-to-many relationships between environmental characteristics and the suite of physiological effects. It was also to identify patterns in the relationships of common physiological effects to each other. Analyses of patterns or relationships in these diagrams help to identify issues that cut across multiple risks. Cross cutting issues benefit from a multidisciplinary approach that synthesizes concepts or data from two or more disciplines to identify and characterize risk factors or develop countermeasures relevant to multiple risks. They also help to illuminate possible problem areas that may arise when a countermeasure impacts risks other than those which it was developed to mitigate, or identify groupings of physiological changes that are likely to occur that may impact the overall risk posture.

Steinberg, S. L.↗
NASA NTRS2014

The Impact of Apollo-Era Microbiology on Human Space Flight

The microbiota of crewmembers and the spacecraft environment contributes significant risk to crew health during space flight missions. NASA reduces microbial risk with various mitigation methods that originated during the Apollo Program and continued to evolve through subsequent programs: Skylab, Shuttle, and International Space Station (ISS). A quarantine of the crew and lunar surface samples, within the Lunar Receiving Laboratory following return from the Moon, was used to prevent contamination with unknown extraterrestrial organisms. The quarantine durations for the crew and lunar samples were 21 days and 50 days, respectively. A series of infections among Apollo crewmembers resulted in a quarantine before launch to limit exposure to infectious organisms. This Health Stabilization Program isolated the crew for 21 days before flight and was effective in reducing crew illness. After the program developed water recovery hardware for Apollo spacecraft, the 1967 National Academy of Science Space Science Board recommended the monitoring of potable water. NASA implemented acceptability limits of 10 colony forming units (CFU) per mL and the absence of viable E. coli, anaerobes, yeasts, and molds in three separate 150 mL aliquots. Microbiological investigations of the crew and spacecraft environment were conducted during the Apollo program, including the Apollo-Soyuz Test Project and Skylab. Subsequent space programs implemented microbial screening of the crew for pathogens and acceptability limits on spacecraft surfaces and air. Microbiology risk mitigation methods have evolved since the Apollo program. NASA cancelled the quarantine of the crew after return from the lunar surface, reduced the duration of the Health Stabilization Program; and implemented acceptability limits for spacecraft surfaces and air. While microbial risks were not a main focus of the early Mercury and Gemini programs, the extended duration of Apollo flights resulted in the increased scrutiny of impact of the space flight environment on crew health. The lessons learned during that era of space flight continue to impact microbiology risk mitigation in space programs today.

Elliott, T. F↗
NASA NTRS2007

NASA Strategy to Safely Live and Work in the Space Radiation Environment

In space, astronauts are constantly bombarded with energetic particles. The goal of the National Aeronautics and Space Agency and the NASA Space Radiation Project is to ensure that astronauts can safely live and work in the space radiation environment. The space radiation environment poses both acute and chronic risks to crew health and safety, but unlike some other aspects of space travel, space radiation exposure has clinically relevant implications for the lifetime of the crew. Among the identified radiation risks are cancer, acute and late CNS damage, chronic and degenerative tissue decease, and acute radiation syndrome. The term "safely" means that risks are sufficiently understood such that acceptable limits on mission, post-mission and multi-mission consequences can be defined. The NASA Space Radiation Project strategy has several elements. The first element is to use a peer-reviewed research program to increase our mechanistic knowledge and genetic capabilities to develop tools for individual risk projection, thereby reducing our dependency on epidemiological data and population-based risk assessment. The second element is to use the NASA Space Radiation Laboratory to provide a ground-based facility to study the health effects/mechanisms of damage from space radiation exposure and the development and validation of biological models of risk, as well as methods for extrapolation to human risk. The third element is a risk modeling effort that integrates the results from research efforts into models of human risk to reduce uncertainties in predicting the identified radiation risks. To understand the biological basis for risk, we must also understand the physical aspects of the crew environment. Thus, the fourth element develops computer algorithms to predict radiation transport properties, evaluate integrated shielding technologies and provide design optimization recommendations for the design of human space systems. Understanding the risks and determining methods to mitigate the risks are keys to a successful radiation protection strategy.

Cucinotta, Francis A.↗
NASA NTRS2006

A Strategy to Safely Live and Work in the Space Radiation Environment

The goal of the National Aeronautics and Space Agency and the Space Radiation Project is to ensure that astronauts can safely live and work in the space radiation environment. The space radiation environment poses both acute and chronic risks to crew health and safety, but unlike some other aspects of space travel, space radiation exposure has clinically relevant implications for the lifetime of the crew. The term safely means that risks are sufficiently understood such that acceptable limits on mission, post-mission and multi-mission consequences (for example, excess lifetime fatal cancer risk) can be defined. The Space Radiation Project strategy has several elements. The first element is to use a peer-reviewed research program to increase our mechanistic knowledge and genetic capabilities to develop tools for individual risk projection, thereby reducing our dependency on epidemiological data and population-based risk assessment. The second element is to use the NASA Space Radiation Laboratory to provide a ground-based facility to study the understanding of health effects/mechanisms of damage from space radiation exposure and the development and validation of biological models of risk, as well as methods for extrapolation to human risk. The third element is a risk modeling effort that integrates the results from research efforts into models of human risk to reduce uncertainties in predicting risk of carcinogenesis, central nervous system damage, degenerative tissue disease, and acute radiation effects. To understand the biological basis for risk, we must also understand the physical aspects of the crew environment. Thus the fourth element develops computer codes to predict radiation transport properties, evaluate integrated shielding technologies and provide design optimization recommendations for the design of human space systems. Understanding the risks and determining methods to mitigate the risks are keys to a successful radiation protection strategy.

Corbin, Barbara J.↗
NASA NTRSDate not supplied

Root Cause Analysis of the Data Refinement Process – Medical Conditions Capability Resource Tables

The medical system for spaceflight thus far has been designed to support missions in low earth orbit (LEO). Crew capabilities are limited and heavily dependent on the team of medical support staff at Mission Control Center (MCC) to guide diagnosis and management. However, missions to the Moon and Mars will suffer from several constraints that will make this ground support focused approach to care ineffective. In order to update and modify medical system design, NASA has relied on Probabilistic Risk Assessment (PRA) modeling to mitigate medical risk through trade space analysis. Specifically, capability resource tables (CRT’s) were developed to create a dataset of resources required to manage a list of accepted medical conditions significant in exploration spaceflight. With 120 conditions, this dataset contained hundreds of capabilities and thousands of resources with tens of thousands of cells of data. Initially these tables were built in excel for high throughput during development, but ultimately had to be transferred, managed, and modified into the Evidence Library database for modeling purposes. The process of collating and reviewing the Evidence Library revealed numerous errors in the dataset that had to be corrected through iterative changes. Several error types emerged during this process and can be broken into specific classifications defined as “input”, “transcription”, “structural”, “branching”, and “information”. In reviewing these error types through the root cause analysis (RCA) approach, we were able to identify the contributors to these errors which included single data review points, changing product end goals, limited software selection, time constraints and several others. By reviewing and evaluating the underlying causes we can provide possible system improvements that can be implemented for current and future data management in PRA model inputs.

A. Anderson↗
DOE OSTI2022

Prototype HB650 Transportation Validation For The PIP-II Project

The PIP-II Project at Fermilab is centered around a superconducting 800 MeV proton linac to upgrade and modernize the Fermilab accelerator complex, allowing increased beam current to intensity frontier experiments such as LBNF-DUNE. PIP-II includes strong international collaborations, including the delivery of 12 cryomodules from European labs to FNAL (3 from STFC-UKRI in the UK and 9 from CEA in France). The transatlantic shipment of these completed modules is identifed as a serious risk for the project. To mitigate this risk, a rigorous and systematic process has been developed to design and validate a transport system, including specifcation, procedures, logistics, and realistic testing. This paper will detail the engineering process used to manage this effort across the collaboration and the results of the first major validation testing of the integrated shipping system prior to use with a cryomodule.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

Heritage and Advanced Technology Systems Engineering Lessons Learned from NASA Space Missions

Use of heritage and new technology is necessary/enabling to implementing small, low cost missions, yet overruns decrease the ability to sustain future mission flight rates The majority of the cost growth drivers seen in the D&NF study were embedded early during formulation phase and later realized during the development and I&T phases Cost drivers can be avoided or significantly decreased by project management and SE emphasis on early identification of risks and realistic analyses SE processes that emphasize an assessment of technology within the mission system to identify technical issues in the design or operational use of the technology. Realistic assessment of new and heritage spacecraft technology assumptions , identification of risks and mitigation strategies. Realistic estimates of effort required to inherit existing or qualify new technology, identification of risks to estimates and develop mitigation strategies. Allocation of project reserves for risk-based mitigation strategies of each individual area of heritage or new technology. Careful tailoring of inheritance processes to ensure due diligence.

Barley, Bryan↗
DOE OSTI2020

Inventory and Probabilistic Function of Natural Hazards in the United States: July 19, 2018 - September 18, 2018

The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) developed a standardized risk assessment process that considers the location-specific vulnerabilities and threats (climate-related as well as human-caused) at a site to generate a ranked list of organizational risks and associated mitigation options for reducing those risks. To support this effort, the Southern Climate Impacts Planning Program (SCIPP), a National Oceanic and Atmospheric (NOAA) Regional Integrated Sciences and Assessments (RISA) team, was selected to provide climate science expertise to develop a comprehensive inventory and probabilistic function of natural hazards (e.g., hurricanes, tornadoes, flooding, and sea level rise) for the entire United States by region. The inventory of climate-related hazards and the associated likelihood scores are incorporated into a companion risk assessment tool enabling standardized comparisons of risk at sites across the country.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Securing The Future: 2026 Manufacturing & Critical Infrastructure Threat Landscape

This report outlines the current state of manufacturing weaknesses introduced by the complexities of modern environments, including cloud services and Internet of Things (IoT) devices, with particular attention paid to the unique vulnerabilities encountered by SMMs. It also highlights CyManII’s strategic initiatives and collaborative solutions to mitigate these risks and strengthen the cybersecurity posture of the manufacturing ecosystem. Utilizing data from 2025 to inform forward-looking mitigation strategies, this report provides manufacturers with a clear understanding of both current and emerging cybersecurity threats, as well as practical opportunities to strengthen their cyber ecosystems. The following sections detail key vulnerabilities and threat vectors, along with actionable mitigation strategies, many of which have been developed or piloted through CyManII-led efforts. A thorough understanding of these risks and mitigation strategies is essential for manufacturers seeking to strengthen the security and resilience of their manufacturing operations.

3D Printing↗
NASA NTRSDate not supplied

Assessing Risk Due to Small Sample Size in Probability of Detection Analysis Using Tolerance Intervals

Small sample size (e.g.6-30) poses risk in results of probability of detection (POD) analysis using tolerance intervals. This method is also called as the limited sample or LS POD. The analysis is performed either during NDE procedure qualification or for assessment of reliability of an NDE procedure. The risk is primarily due to sampling error. Smaller samples are not likely to be random to the population or representative of the population. The small samples are likely to be biased. Biased samples have smaller standard deviation compared to the population. POD analysis with small biased sample can lead to overestimation of POD. Many sampling schemes are available in statistics to mitigate sampling risk. Primary objective of POD analysis is to determine a decision threshold from signal response measurements of a sample such that it is less than or equal to population decision threshold for 90% POD. Sampling error implies that this NDE reliability condition is violated. One of sampling types is called a representative sample. Representative samples reduce variance in POD estimates but also reduce magnitude of the error. Sampling sensitivity analysis for some sampling types is performed here using repetitive random sampling or Monte Carlo method. Six sampling types are considered for comparison. Some of the sampling types are similar to drawing a representative sample. LS POD model assumes random sampling. Therefore, random sampling is used as a basis for comparison with each sampling type. The sampling types used in the analysis are, A. Nominal and worst-case sampling, B. Worst-case sampling, C. Nominal case sampling, D. Random sampling, E. Random target, and sub-target sampling. F. Nominal target and sub-target sampling. Results of Monte Carlo simulation indicate that type F sampling can mitigate sampling risk and is also more practical to implement. Type A sampling may also mitigate the sampling risk, but it may be less practical to implement.

Ajay M Koshti↗
NASA NTRS2017

A Fuzzy Logic Approach for Separation Assurance and Collision Avoidance for Unmanned Aerial Systems

In the coming years, operations in low altitude airspace will vastly increase as the capabilities and applications of small Unmanned Aerial Systems (sUAS) continue to multiply. Therefore, solutions to managing sUAS in highly congested airspace must be explored. In this study, a Fuzzy Logic based approach was used to help mitigate the risk of collisions between aircraft using separation assurance and collision avoidance techniques. The system was evaluated for its effectiveness to mitigate the risk of mid-air collisions between aircraft. This system utilizes only current state information and can resolve potential conflicts without knowledge of intruder intent. The avoidance logic was verified using formal methods and shown to select the correct action in all instances. Additionally, the Fuzzy Logic Controllers were shown to always turn the vehicles in the correct direction. Numerical testing demonstrated that the avoidance system was able to prevent a mid-air collision between two sUAS in all tested cases. Simulations were also performed in a three-dimensional environment with a heterogenous fleet of sUAS performing a variety of realistic missions. Simulations showed that the system was 99.98 effective at preventing mid-air collisions when separation assurance was disabled (unmitigated case) and 100 effective when enabled (mitigated case).

Verification & Validation of a Fuzzy Logic Control↗
NASA NTRS2017

Human Mars EDL Pathfinder Study: Assessment of Technology Development Gaps and Mitigations

This paper presents the results of a NASA initiated Agency-wide assessment to better characterize the risks and potential mitigation approaches associated with landing human class Entry, Descent, and Landing (EDL) systems on Mars. Due to the criticality and long-lead nature of advancing EDL techniques, it is necessary to determine an appropriate strategy to improve the capability to land large payloads. A key focus of this study was to understand the key EDL risks and with a focus on determining what "must" be tested at Mars. This process identified the various risks and potential risk mitigation strategies along with the key near term technology development efforts required and in what environment those technology demonstrations were best suited. The study identified key risks along with advantages to each entry technology. In addition, it was identified that provided the EDL concept of operations (con ops) minimized large scale transition events, there was no technology requirement for a Mars pre-cursor demonstration. Instead, NASA should take a direct path to a human-scale lander.

Lillard, Randolph↗
NASA NTRS2003

Reducing the Risk of Human Space Missions with INTEGRITY

The INTEGRITY Program will design and operate a test bed facility to help prepare for future beyond-LEO missions. The purpose of INTEGRITY is to enable future missions by developing, testing, and demonstrating advanced human space systems. INTEGRITY will also implement and validate advanced management techniques including risk analysis and mitigation. One important way INTEGRITY will help enable future missions is by reducing their risk. A risk analysis of human space missions is important in defining the steps that INTEGRITY should take to mitigate risk. This paper describes how a Probabilistic Risk Assessment (PRA) of human space missions will help support the planning and development of INTEGRITY to maximize its benefits to future missions. PRA is a systematic methodology to decompose the system into subsystems and components, to quantify the failure risk as a function of the design elements and their corresponding probability of failure. PRA provides a quantitative estimate of the probability of failure of the system, including an assessment and display of the degree of uncertainty surrounding the probability. PRA provides a basis for understanding the impacts of decisions that affect safety, reliability, performance, and cost. Risks with both high probability and high impact are identified as top priority. The PRA of human missions beyond Earth orbit will help indicate how the risk of future human space missions can be reduced by integrating and testing systems in INTEGRITY.

Jones, Harry W.↗
NASA NTRS2011

Monitoring of Microbial Loads During Long Duration Missions as a Risk Reduction Tool

Humans have been exploring space for more than 40 years. For all those years microorganisms have accompanied, first un-manned spacecraft/cargo and later manned vessels. Microorganisms are everywhere on Earth, could easily adapt to new environments and/or can rapidly mutate to survive in very harsh conditions. Their presence in spacecraft and cargo have caused a few inconveniences over the years of humans spaceflight, ranging from crew health, life support systems challenges and material degradation. The sterilization of spacecraft that will host humans in long duration mission would be a costly operation that will not provide a long-term solution to the microbial colonization of the vessels. As soon as a human is exposed to the spacecraft, during the mission, microorganisms will start to populate the new environment. As the hum an presence in space increases in length, the risk from the microbial load, to hardware and crew will also increase. Mitigation of this risk includes several different strategies that will include minimizing the microbial load (in numbers and diversity) and monitoring. This presentation will provide a list of the risk mitigation strategies that should be implemented during ground processing, and during the mission. It will also discuss the areas that should be discussed before an effective in-flight microbial monitoring regimen is implemented. Microbial monitoring technologies will also be presented.

Roman, Monsi C.↗