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DOE OSTI2024

Direct Air Capture Recovery of Energy for CCUS Partnership (DAC RECO 2 UP) Final Technical Report

The “Direct Air Capture Recovery of Energy for CCUS Partnership (DAC RECO 2 UP)” project employs a team approach and supports the U.S. Department of Energy Office of Fossil Energy and Carbon Management’s (DOE-FECM) goal to decrease the cost of capture through the testing of existing direct air capture (DAC) materials in integrated field units that produce a concentrated carbon dioxide (CO 2 ) stream of at least 95% purity. Solid-amine CO 2 adsorption-desorption contactor technology, proven in the laboratory, is undergoing high-fidelity design/validation. Recoverable energy is readily available from a large number of commercial locations where DAC can be deployed; therefore, advancing the fidelity of energy recovery to directly reduce the cost of DAC is a key project objective. In addition, many commercial facilities have low-concentration CO 2 vents that are uneconomical to treat alone but could provide more efficient mass and thermal transport to DAC systems with integrated energy recovery and flexible CO 2 treatment capabilities. Technology scale-up leverages past research and occurs in a commercially relevant environment at the National Carbon Capture Center. Prescreening techno-economic analysis, risk assessments, and life cycle analysis are being performed by experienced team members. Results of the project will address critical technical barriers that, when solved, will improve the capital and operating costs of DAC while validating commercial relevance of cost and product quality/need.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Commercial Off-The-Shelf (COTS) Program: Issues and Results of Upscreening COTS Parts for NASA Flight Hardware

This paper presents The Commercial Off-The-Shelf Program (COTS). The topics of discussion are: 1) Introduction of COTS; 2) MARS01 Program/Requirements; 3) MARS01 COTS Screening Flow; 4) Test Results-Electrical, C-Sam, Burn-In; 5) Value Added Analysis (Risk Reduction); 6) Value Added Analysis (Cost); 7) Impact of COTS ++ Screening; and 8) Summary. This paper is presented in viewgraph form.

Sandor, Mike↗

NASA NTRS1999

Electronic Packaging for Space Applications Workshop 1999

This paper presents viewgraphs on the Commercial Off-The-Shelf (COTS) Program. The topics include: 1) Advocacy for COTS; 2) MARS01 Program/Requirements; 3) MARS01 COTS Screening Flow; 4) Test Results-Electrical, C-Sam, Burn-In; 5) Value Added Analysis (Risk Reduction); 6) Value Added Analysis (Cost); 7) Impact of COTS ++ Screening and 8) Summary.

Sandor, Mike↗

NASA NTRSDate not supplied

HydroSAR: A Cloud-based SAR Data Analysis Service to Monitor Hydrological Disasters and their Impact on Population and Agriculture

Weather-related hazards are ubiquitous around the world including: 1) hurricane storm surges, 2) rapid snowmelt and heavy rainfall, 3) severe weather leading to flash floods, and 4) seasonal freeze and thaw of rivers that may lead to ice jams. Each of these hazards affects human settlements and has the potential to impact agricultural productivity. In each setting, end-users in disaster management need access to data processing tools helpful in mapping past and current disasters. Analysis of past events supports risk mitigation by understanding what has already occurred and how to alleviate those impacts in the future. Having capabilities to generate the same products in a response setting means that lessons learned from risk analysis will carry forward to event response. Synthetic aperture radar (SAR) data are particularly useful for these activities due to their all-weather 24/7 monitoring capabilities. In this effort we present HydroSAR, a cloud-based SAR data analysis service for the mapping of meteorological and hydrological disasters as well as their impact on population and agriculture. As part of this project we have developed a series of SAR-based value added products for the monitoring of surface hydrology (image time series, change detection, flood extent, flood depth) and the assessment of impacts on population (flood depth) and agriculture (active agriculture, inundated agriculture, flood duration). We also developed a cloud-based platform for generating these products over affected areas and are working with end-users to integrate derived product into decision-making workflows The paper will briefly introduce the SAR-based products that were developed for this effort. We describe the cloud-based production pipeline that was built to automatically generate these products in near-real time over extended regions. The integration of SAR-based information into hazard preparation and response activities is described for a number of recent disasters including the 2019 forest fires in Alaska, 2019 flooding in the U.S. Midwest, the 2020 U.S. severe weather easter outbreak, 2020 tropical storm Christobal, 2020 cyclone Amphan, 2020, Alaska Spring breakup flooding, and the 2020 flood season in Eastern India, Bangladesh, and Nepal.

Franz Josef Meyer↗

NASA NTRSDate not supplied

A Historical Overview of International Space Station Extravehicular Activity Meteoroid and Orbital Debris Risk

Nearly 300 spacewalks have been conducted over the last 25 years to help build and maintain the International Space Station (ISS). During the nearly 2,000 hours of extra-vehicular activity (EVA), crew members wear extra-vehicular mobility unit (EMU) “spacesuits” to mitigate hazards of the space environment including impacts from meteoroid and orbital debris (MMOD) particles. NASA includes detailed EMU MMOD risk analyses as part of the ISS EVA review and approval process. This paper provides a general historical overview of the ISS EVA MMOD risks and the associated risk assessment process. The NASA Johnson Space Center (JSC) Hypervelocity Impact Technology (HVIT) Team produces the ISS EVA MMOD risk analyses using the Bumper3 MMOD risk analysis code in conjunction with detailed information about the EVA including crew-member EVA work sites, crew translation paths, suit orientation, and duration. Detailed physical models of the EMU spacesuits and the ISS are included and tailored for each EVA analysis. Two types of MMOD risk are included: (1) Penetration, and (2) Catastrophic. Penetration risk is for any size leak in the EMU suit. Catastrophic risk is a subset of Penetration Risk and only includes penetrations that cause a 4mm diameter hole (or larger) in the inner “bladder” layer of the EMU suit. This size hole will exceed the ability of the EMU suit to compensate. The MMOD risk analyses also utilize the latest orbital debris environment and meteoroid environment models including additional transient factors to account for recent satellite break-ups and annual meteor storms. These additional factors and the associated increase in EVA MMOD risk are considered when scheduling an EVA to reduce EMU MMOD risk.

Dana M. Lear↗

NASA NTRSDate not supplied

A Review of International Space Station Extravehicular Activity Micrometeoroid and Orbital Debris Risk

Nearly 300 spacewalks have been conducted over the last 25 years to support the construction and maintenance of the International Space Station (ISS). During the nearly 2,000 hours of extra-vehicular activity (EVA), crew wore extra-vehicular mobility unit (EMU) “spacesuits” to help mitigate hazards of the space environment including impacts from micrometeoroid and orbital debris (MMOD) particles. The National Aeronautics and Space Administration (NASA) conducts detailed EMU MMOD risk analyses as part of the ISS EVA review and approval process. This paper provides a general historical overview of the ISS EVA MMOD risks and the associated risk assessment process. The NASA Johnson Space Center (JSC) Hypervelocity Impact Technology (HVIT) Team produces the ISS EVA MMOD risk analyses using the Bumper MMOD risk analysis code in conjunction with detailed information about the EVA including crew member EVA work sites, crew translation paths, suit orientation, and durations. Detailed physical models of the EMU spacesuit and the ISS are included and tailored for each EVA analysis. Two types of MMOD risk are included: (1) Penetration, and (2) Catastrophic. Penetration risk is for any size leak in the EMU suit. Catastrophic risk is a subset of Penetration Risk and only includes penetrations that cause a 4mm diameter hole (or larger) in the pressure-maintaining “bladder” layer of the EMU suit. This size hole will exceed the ability of the EMU suit to compensate. The MMOD risk analyses also utilize the latest orbital debris environment and meteoroid environment models including additional transient factors to account for recent satellite break-ups and annual meteor storms. These additional factors and the associated increase in EVA MMOD risk are considered when scheduling EVAs to reduce EMU MMOD risk.

Dana M. Lear↗

NASA NTRSDate not supplied

A Review of International Space Station Extravehicular Activity Micrometeoroid and Orbital Debris Risk

Dana M. Lear↗

NASA NTRS2007

Risk Management: A Practical Design Tool For Space Systems and Technology Development

Over the past two decades, risk management and risk analysis have emerged throughout the business community in the United States (US) as prominent planning and development strategies used to mitigate risk of failure and ensure a high return on investment (ROI) for business endeavors (financial and otherwise). They are generic tools that can be applied to any business regardless of the sector (i.e., government, university, private) and have been used by the Federal government in the form of institutional practices aimed at maximizing the probability of success in business activities. One US Federal agency that incorporates risk management and analysis techniques into business and/or engineering activities is the National Aeronautics and Space Administration (NASA). The present work is a discussion on mission, spacecraft and instrument design (as well as technology development) and the role of risk management, analysis and mitigation as a fundamental tool in the design process.

Silk, Eric A.↗

NASA NTRS1986

Risk and value analysis of SETI

The risks, values, and costs of the SETI project are evaluated and compared with those of the Viking project. Examination of the scientific values, side benefits, and costs of the two projects reveal that both projects provide equal benefits at equal costs. The probability of scientific and technical success is analyzed.

Billingham, J.↗

NASA NTRS2017

Time Dependence of Collision Probabilities During Satellite Conjunctions

The NASA Conjunction Assessment Risk Analysis (CARA) team has recently implemented updated software to calculate the probability of collision (P (sub c)) for Earth-orbiting satellites. The algorithm can employ complex dynamical models for orbital motion, and account for the effects of non-linear trajectories as well as both position and velocity uncertainties. This “3D P (sub c)” method entails computing a 3-dimensional numerical integral for each estimated probability. Our analysis indicates that the 3D method provides several new insights over the traditional “2D P (sub c)” method, even when approximating the orbital motion using the relatively simple Keplerian two-body dynamical model. First, the formulation provides the means to estimate variations in the time derivative of the collision probability, or the probability rate, R (sub c). For close-proximity satellites, such as those orbiting in formations or clusters, R (sub c) variations can show multiple peaks that repeat or blend with one another, providing insight into the ongoing temporal distribution of risk. For single, isolated conjunctions, R (sub c) analysis provides the means to identify and bound the times of peak collision risk. Additionally, analysis of multiple actual archived conjunctions demonstrates that the commonly used “2D P (sub c)” approximation can occasionally provide inaccurate estimates. These include cases in which the 2D method yields negligibly small probabilities (e.g., P (sub c)) is greater than 10 (sup -10)), but the 3D estimates are sufficiently large to prompt increased monitoring or collision mitigation (e.g., P (sub c) is greater than or equal to 10 (sup -5)). Finally, the archive analysis indicates that a relatively efficient calculation can be used to identify which conjunctions will have negligibly small probabilities. This small-P (sub c) screening test can significantly speed the overall risk analysis computation for large numbers of conjunctions.

Hall, Doyle T.↗

NASA NTRSDate not supplied

Development of A Crew Health and Performance System Probabilistic Risk Assessment Tool: Proof-of-Concept Approach

The crew health and performance (CHP) system represents the span of technological interventions and tested processes and procedures that in combination address the human risk to space flight. The Human Research Program (HRP) mental model of the CHP system breaks the capabilities needed to meet NASA human flight systems standards into specific categories (i.e., countermeasures, behavioral health, medical intervention). These categories are further broken down into specific sub-groups generally associated with the human system risks that these capabilities seek to mitigate. Like the approach used to develop the Integrated Medical Model (IMM) and the Medical Extensible Dynamic Probabilistic Risk Analysis Tool (MEDPRAT), HRP tasked NASA GRC’s Cross-Cutting Computational Modeling Project with developing a CHP probabilistic risk assessment tool, the CHP-PRA. The CHP-PRA model seeks to quantify and relatively assess the human risk state within the crew health and performance domain, using a combination of knowledge about human system risks and technology and practices likely to be applied during space flight missions. This modeling system will incorporate customer and stakeholder feedback and be flexible enough to address multiple different questions about important low-level mission-specific parameters. This presentation will introduce the initial concept and development timeline for this tool and demonstrate proof-of-concept through an application addressing a specific human risk question posed within the Artemis program.

Risk analysis↗

NASA NTRS2001

A Probabilistic Approach to Model Update

Finite element models are often developed for load validation, structural certification, response predictions, and to study alternate design concepts. In rare occasions, models developed with a nominal set of parameters agree with experimental data without the need to update parameter values. Today, model updating is generally heuristic and often performed by a skilled analyst with in-depth understanding of the model assumptions. Parameter uncertainties play a key role in understanding the model update problem and therefore probabilistic analysis tools, developed for reliability and risk analysis, may be used to incorporate uncertainty in the analysis. In this work, probability analysis (PA) tools are used to aid the parameter update task using experimental data and some basic knowledge of potential error sources. Discussed here is the first application of PA tools to update parameters of a finite element model for a composite wing structure. Static deflection data at six locations are used to update five parameters. It is shown that while prediction of individual response values may not be matched identically, the system response is significantly improved with moderate changes in parameter values.

Horta, Lucas G.↗

NASA NTRS2009

Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis

This document, Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis, is intended to provide guidelines for the collection and evaluation of risk and reliability-related data. It is aimed at scientists and engineers familiar with risk and reliability methods and provides a hands-on approach to the investigation and application of a variety of risk and reliability data assessment methods, tools, and techniques. This document provides both: A broad perspective on data analysis collection and evaluation issues. A narrow focus on the methods to implement a comprehensive information repository. The topics addressed herein cover the fundamentals of how data and information are to be used in risk and reliability analysis models and their potential role in decision making. Understanding these topics is essential to attaining a risk informed decision making environment that is being sought by NASA requirements and procedures such as 8000.4 (Agency Risk Management Procedural Requirements), NPR 8705.05 (Probabilistic Risk Assessment Procedures for NASA Programs and Projects), and the System Safety requirements of NPR 8715.3 (NASA General Safety Program Requirements).

Dezfuli, Homayoon↗

NASA NTRS2014

Simulation for Prediction of Entry Article Demise (SPEAD): An Analysis Tool for Spacecraft Safety Analysis and Ascent/Reentry Risk Assessment

For the purpose of performing safety analysis and risk assessment for a potential off-nominal atmospheric reentry resulting in vehicle breakup, a synthesis of trajectory propagation coupled with thermal analysis and the evaluation of node failure is required to predict the sequence of events, the timeline, and the progressive demise of spacecraft components. To provide this capability, the Simulation for Prediction of Entry Article Demise (SPEAD) analysis tool was developed. The software and methodology have been validated against actual flights, telemetry data, and validated software, and safety/risk analyses were performed for various programs using SPEAD. This report discusses the capabilities, modeling, validation, and application of the SPEAD analysis tool.

Ling, Lisa↗

DOE OSTI2024

Considerations for Introducing Artificial Intelligence into Nuclear Power Plants

Advanced computational tools and techniques such as artificial intelligence and machine learning (AI/ML) can transform the nuclear power industry. This is necessary given that the economic viability of the existing fleet is in jeopardy and its labor-centric approach to operations and maintenance. Currently, AI/ML research is being undertaken for reactor system design and analysis including fault and accident prognosis, nuclear risk analysis such as plant safety and security evaluation, and plant operations and maintenance including predictive maintenance. Applications include both existing and advanced reactor technologies with the aim of improving operational and business efficiencies. Most every aspect of the organization can benefit, from instrumentation and control, to work planning, to human-machine interactions and business management. AI/ML in nuclear can simplify complex problems and produce more effective decision-making. Nonetheless, careful consideration must be given to the implementation of an AI/ML initiative. The aims of this research are to 1) review barriers to AI/ML adoption within the nuclear power industry, and 2) suggest potential solutions. These barriers are organized along five distinct categories (Figure 1) that are interconnected. The first are historical barriers that track the industry’s development over the decades including worldwide nuclear events that shaped public perceptions. The resulting federal scrutiny and intense safety culture that emerged are discussed. Technical barriers to AI/ML adoption are considerable, and include data privacy concerns, data governance, and the current lack of AI/ML expert knowledge at the plants. The main business case barrier remains cost, but an absence of an industry-wide vision and wide-scale adoption also produces reluctance. Stakeholder readiness is reviewed with special attention given to regulatory readiness. The 5-year strategic plan for AI readiness recently published by the U.S. Nuclear Regulatory Commission is highlighted. Last, adoption barriers at the user level are addressed including the importance of user experience and explainable AI. The AI adoption barriers described here are inter-related and ideally should be addressed in a holistic fashion.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRSDate not supplied

In-Time Safety Assessment & Risk Prediction for Unmanned Aerial Systems

One of the critical challenges in emerging autonomous systems is timely mitigation of hazards encountered during operation which may not be known or accounted for at the time of design. Efficient execution of unmanned systems therefore demands a paradigm shift from scheduled periodic maintenance to predictive risk analysis that includes condition-based-monitoring, real-time reliability assessment and hazard mitigation. Particularly, the state-of-health parameters needs to be computed at the component level, unit level as well as the integrated system level. While in the former two levels, the physics of health propagation may be based on underlying electro-mechanical properties, system level prognostics often relies on data-driven models. Further, uncertainty from model, measurements and input sources should be accurately quantified to generate meaningful prediction results that can be fed into reliable decision making processes. Finally, the expected risk and time to failure has to be computed based on the current state-of-health of the overall system. This talk presents a conceptual design of such an in-time safety assurance approach for unmanned aerial vehicles (UAV) operating at low altitudes near and over populated areas. Typical in-flight hazard incidents include unplanned detour, proximity to obstacles, mid-flight component faults, limited battery life and poor quality of GPS measurements. Safety assessment therefore comprises trajectory generation and re-plan, battery RUL computation, distributed fault diagnostics and uncertainty management of predicted trajectory based on GPS measurement noise. The entire monitoring framework will be demonstrated on simulated as well as real UAV flight experiments conducted at the NASA Langley Research Center. This tutorial will therefore guide the audience through a step-by-step tracking of an autonomous system with focus on in-time risk prediction in the presence of unforeseen hazards and uncertain environment.

diagnostics↗

DOE OSTI2025

Consequence Based Framework for Deployment of Cloud Solutions in the Digital Energy Transition

This study proposes a framework for evaluating cloud computing deployment in the electric sector, focusing on the digital transition of energy systems. It assesses the implications of cloud technology adoption, particularly in terms of security, operational resilience, and efficiency. The paper introduces a method for consequence-driven risk analysis, enabling utilities to prioritize and mitigate potential threats effectively. It also discusses the shared responsibility model in cloud computing, highlighting the need for collaborative security efforts. The research aims to provide utilities with a strategic assessment tool for cloud adoption, emphasizing the importance of security culture in enhancing cloud computing's role in critical infrastructure.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Consequence Based Framework for Deployment of Cloud Solutions in the Digital Energy Transition

This study proposes a framework for evaluating cloud computing deployment in the electric sector, focusing on the digital transition of energy systems. It assesses the implications of cloud technology adoption, particularly in terms of security, operational resilience, and efficiency. The paper introduces a framework for consequence-driven applied risk analysis, enabling utilities to prioritize and mitigate potential threats effectively, and responsibly deploy cloud applications. It also discusses the shared responsibility model in cloud computing, highlighting the need for collaborative security efforts. The research aims to provide utilities with a strategic assessment tool for cloud adoption, emphasizing the importance of security culture in enhancing cloud computing's role in critical infrastructure.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗