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NASA NTRS2020

Electromagnetic Compatibility Test and Analysis Campaign of NASA's Mars 2020 Rover

NASA's Mars 2020 Rover—with a launch window opening July 2020, and landing expected February 2021—has mission objectives to look for evidence of habitability, seek biosignatures of past life, collect and cache samples for possible future return to Earth, and prepare for future human missions. The Rover platform is similar to the previous Mars Science Laboratory (MSL) “Curiosity” rover that landed in 2012 but contains a new suite of scientific instruments and upgrades to existing functionality. The scientific payload includes a trio of chemical analysis tools (PIXL, SHERLOC, SuperCam), a ground penetrating radar (RIMFAX), an upgraded weather station (MEDA), upgraded high resolution camera (MastCam-Z), and an oxygen-producing experiment (MOXIE). These changes—along with new efficiency goals to operate more Rover subsystems concurrently and thus collect more science—presented new electromagnetic compatibility (EMC) challenges. In this paper, we will describe the campaign to ensure Mars 2020 mission success from an electromagnetic environment perspective: 1) confirming existing MSL heritage subsystems and EMC requirements were compatible with the new Mars 2020 mission objectives, 2) engaging with engineers and scientists early in the project to identify and evaluate risks before hardware assembly and performing ambitious risk reduction tests, 3) undertaking a comprehensive subsystem qualification test program based on tailored MIL-STD-461F requirements, occasionally leading to redesign, 4) synthesizing the data collected to perform detailed analyses toward the goal of making risk-informed decisions at a system level. The spacecraft has successfully completed all three planned system level tests, demonstrating self-compatibility with minimal impact to operations from electromagnetic interference in all mission phases.

Gonzales, Edward C↗
NASA NTRSDate not supplied

What Has ExMC Systems Engineering Been Up To Since Last IWS?

Long duration Lunar and Martian missions will change the way NASA currently practices medicine. The missions will require more autonomous capability compared to current low Earth orbit operations. For the medical system, lack of consumable resupply, evacuation opportunities, and real-time ground support are key drivers toward greater autonomy. Recognition of the limited mission and vehicle resources available to carry out exploration missions motivates the Exploration Medical Capability (ExMC) Element’s approach to enabling the necessary autonomy. This element promotes human health and performance in space by advancing medical systems design and risk-informed decision-making for long-duration deep-space exploration missions (LDEMs). ExMC is using system engineering processes and Model-Based System Engineering (MBSE) tools to identify the user needs and requirements of LDEM medical systems. The MBSE approach to medical system design offers a paradigm shift toward greater integration between the vehicle and the medical system, and directly supports the transition of Earth-reliant International Space Station operations to the Earth-independent operations envisioned for LDEMs. This talk will provide a high-level overview of what the ExMC SE team has accomplished since the last IWS, an introduction to upcoming SE talks, and the ongoing systems engineering work.

K. McGuire↗
NASA NTRSDate not supplied

Exploration Atmosphere Demonstration of A Multi-Functional Integrated Medical Device (Tempus Pro)

INTRODUCTION The Exploration Medical Capability (ExMC) element within the Human Research Program and the Exploration Medical Integrated Product Team (XMIPT) within the Mars Campaign Office seek to advance medical system design and risk-informed decision-making for exploration missions. This includes assessment of candidate devices and their compatibility within a variety of increasingly Earth-independent medical scenarios. The Tempus Pro (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) is a commercial-off-the-shelf (COTS), multi-functional integrated medical device capable of vital signs monitoring, with built-in procedure support (iAssist), patient record and telemedicine communication features, and medical imaging (e.g., camera, laryngoscope, ultrasound) that meets multiple exploration medical capability needs. One of several hypobaric atmospheres being considered for exploration vehicles is 8.2 psi with 34% oxygen. To assess the useability of the Tempus Pro in such environments by individuals without formal medical training, the unit was tested in May and June of 2023 at the Johnson Space Center 20-Foot Exploration Atmosphere Chamber in conjunction with the Exploration Atmospheres-2 (EA-2) study. TECHNOLOGY DEMONSTRATION Eight subjects in the EA-2 study were assigned roles as the caregiver or patient – or both in the case of a self-exam – and caregivers were asked to place sensors for 3-Lead ECG, non-invasive blood pressure (NIBP), pulse oximetry (SpO2), and temperature using Tempus Pro’s iAssist. Depending on the procedure, additional tasks included an oropharyngeal exam of the throat with the laryngoscope and capturing ultrasound images of a cardiac subxiphoid view or of the user’s choice from a pre-specified list. Scenarios ranged from remote-guided to fully autonomous operations and surveyed the effectiveness of support, amount of support desired, and importance of support by type (e.g., written crew procedures, iAssist and device guidance, remote console guidance, etc.). Feedback from the subjects and the support personnel was also gathered to inform future designs for training and support and to determine what operations are plausible given different levels of each. An unweighted NASA task load index (TLX) was used to profile the demands of using the device, however the sample size does not support statistics. The research was exploratory in nature and qualitative information was the main goal. Calibration checks on the Tempus Pro were conducted before and after chamber testing to ensure the device was in useable condition. RESULTS All subjects performed their tasks successfully and found the Tempus Pro easy to use with the support provided. The calibration checks outside the chamber showed that the Tempus Pro remained unchanged and measurements inside the chamber were within normal values. Caregivers taking the NASA TLX reported mean scores ≤ 41/100 showing the tasks to be undemanding and less demanding with repeated use (~20/100). Novice users were able to easily connect sensors and take vital signs with the guidance from Tempus Pro’s iAssist feature. For more complex tasks, such as the oropharyngeal exam and ultrasound image acquisition, guidance beyond iAssist was needed, primarily from a supporting physician. Feedback on the importance of support types varied by person and scenario but greater than 50% of the support used by each was non-native to the device. Overall opinions were positive, but the ultrasound users expressed a lack of confidence in their results and 3 out of 4 desired more time, training, or support. Subjects found the sensors to be comfortable and comparable to prior experiences with such devices, except for the blood pressure cuff, which squeezed too tightly for uncomfortably long periods. Many observations provoked discussion, especially regarding ultrasound, that will aide decisions about future demonstrations.

R. S. Miller↗
NASA NTRSDate not supplied

Accounting for Point Estimate Uncertainty in Space Systems Reliability and Risk Analysis

Understanding and accounting for uncertainty in risk analysis is a critical step in the management and communication of risk in engineered systems. The component and system-level analysis to determine the probability of a negative outcome and its consequence is often quantified by a point estimate. Many Program and Enterprise decisions involving technical concerns and issues rely on reliability engineering activities to produce quantified risk analysis to inform the decision making process. At NASA, it is common to use a Probabilistic Risk Analysis (PRA) to inform the overall risk to Loss of Mission or Loss of Crew that involves integration across all spacecraft subsystem fault trees to produce an overall probability of mission failure. The point estimate is an estimate of this overall probability and is an immediate result of a fault tree model. It is the result of a model where the probability of each event is taken to be equal to its mean. The value provides an approximation of the overall mean without running any uncertainty calculations (e.g., no sampling). Using only the point estimate can lead to a false sense of precision and the point estimate may not match the resulting mean when uncertainty is taken into consideration. This paper will explore five conditions that can cause the PRA model mean to diverge from the point estimate and will provide engineers and managers insight into the importance of understanding uncertainty in the elements of PRA models.

Paul J Collier↗
NASA NTRS2015

Using Risk Assessment Methodologies to Meet Management Objectives

Current decision making involves numerous possible combinations of technology elements, safety and health issues, operational aspects and process considerations to satisfy program goals. Identifying potential risk considerations as part of the management decision making process provides additional tools to make more informed management decision. Adapting and using risk assessment methodologies can generate new perspectives on various risk and safety concerns that are not immediately apparent. Safety and operational risks can be identified and final decisions can balance these considerations with cost and schedule risks. Additional assessments can also show likelihood of event occurrence and event consequence to provide a more informed basis for decision making, as well as cost effective mitigation strategies. Methodologies available to perform Risk Assessments range from qualitative identification of risk potential, to detailed assessments where quantitative probabilities are calculated. Methodology used should be based on factors that include: 1) type of industry and industry standards, 2) tasks, tools, and environment 3) type and availability of data and 4) industry views and requirements regarding risk & reliability. Risk Assessments are a tool for decision makers to understand potential consequences and be in a position to reduce, mitigate or eliminate costly mistakes or catastrophic failures.

DeMott, D. L.↗
NASA NTRS2013

PRA and Conceptual Design

Once a project obtains approval, decision makers have to consider a variety of alternative paths for completing the project and meeting the project objectives. How decisions are made involves a variety of elements including: cost, experience, current technology, ideologies, politics, future needs and desires, capabilities, manpower, timing, available information, and for many ventures management needs to assess the elements of risk versus reward. The use of high level Probabilistic Risk Assessment (PRA) Models during conceptual design phases provides management with additional information during the decision making process regarding the risk potential for proposed operations and design prototypes. The methodology can be used as a tool to: 1) allow trade studies to compare alternatives based on risk, 2) determine which elements (equipment, process or operational parameters) drives the risk, and 3) provide information to mitigate or eliminate risks early in the conceptual design to lower costs. Creating system models using conceptual design proposals and generic key systems based on what is known today can provide an understanding of the magnitudes of proposed systems and operational risks and facilitates trade study comparisons early in the decision making process. Identifying the "best" way to achieve the desired results is difficult, and generally occurs based on limited information. PRA provides a tool for decision makers to explore how some decisions will affect risk before the project is committed to that path, which can ultimately save time and money.

DeMott, Diana↗
NASA NTRS2005

An Overview of Power Capability Requirements for Exploration Missions

Advanced power is one of the key capabilities that will be needed to achieve NASA's missions of exploration and scientific advancement. Significant gaps exist in advanced power capabilities that are on the critical path to enabling human exploration beyond Earth orbit and advanced robotic exploration of the solar system. Focused studies and investment are needed to answer key development issues for all candidate technologies before down-selection. The viability of candidate power technology alternatives will be a major factor in determining what exploration mission architectures are possible. Achieving the capabilities needed to enable the CEV, Moon, and Mars missions is dependent on adequate funding. Focused investment in advanced power technologies for human and robotic exploration missions is imperative now to reduce risk and to make informed decisions on potential exploration mission decisions beginning in 2008. This investment would begin the long lead-time needed to develop capabilities for human exploration missions in the 2015 to 2030 timeframe. This paper identifies some of the key technologies that will be needed to fill these power capability gaps. Recommendations are offered to address capability gaps in advanced power for Crew Exploration Vehicle (CEV) power, surface nuclear power systems, surface mobile power systems, high efficiency power systems, and space transportation power systems. These capabilities fill gaps that are on the critical path to enabling robotic and human exploration missions. The recommendations address the following critical technology areas: Energy Conversion, Energy Storage, and Power Management and Distribution.

Davis, Jose M.↗
NASA NTRS2022

Reliability-Aware Requirements Development for Autonomy Software

Autonomy is the ability of a system to make decisions and take actions in the presence of uncertainty. Validating autonomy, therefore, is a matter of validating that the system makes intelligent decisions even when there might be discrepancies between the observed and the expected state of the world as well as when the possible outcome of each of the possible courses of action is uncertain. During the requirements engineering phase, the functions, including those that are required to be autonomous and their expected behavior are specified. However, in the case of autonomous software system, it is challenging to specify all possible scenarios that the software may encounter. Additionally, since autonomous behaviors cannot always be fully predetermined, it is difficult to reason about their completeness and correctness. While these challenges are also faced with non-autonomous system, they are more prevalent for autonomous system due to their complexity and emergent behavior. Our efforts have been three-fold. On one hand, we have developed a goal-based method for requirements decomposition. We have embedded this approach into a higher-level systems engineering framework and then developed methods for decision and reliability analysis within this framework. And finally, we use simulation analysis to validate the more theoretical methods and provide a feedback mechanism. The decision analysis approach (DA) helps in identifying and mitigating the run-time risks, by bringing to the forefront the uncertainties, decisions, interactions, and other factors that may cause autonomous software to make erroneous decisions. The DA framework is used to quantify, for each decision that the software can make, failure risk due to uncertainties. The information about the key decisions and circumstances that can cause autonomous system to make incorrect decisions are used to generate test scenarios to be run in a simulator to ensure that the system can handle error-prone circumstances. The results or outcomes from decisions, based on the simulated scenarios, can then be leveraged to further gain insight of the assured system. We combine a goal-based approach with simulation analysis to facilitate requirements development for autonomous systems and further provide a method for run-time systems level reliability considerations during the autonomous software development process. The DA and the reliability analysis methods provide a formalism for the consideration of uncertainty in the run time decision-making process for autonomous software. This formalism considers the uncertainty involved in the outcome of different courses of action, in terms of performance and cost, as well as a method to consider the system level reliability implications. System level reliability considerations for autonomous software decision making contribute to the satisfaction of the system level goals over the lifecycle of a given mission. We demonstrate our approach using a hypothetical rover path planning example. The requirements for our rover simulator are based on existing literature about Mars rovers and lessons learned from real world observations at JPL. The specifics of the autonomy design for the Mars rovers, that have not been previously cleared for external release, are not used for our demonstrations.

Lindvall, Mikael↗
NASA NTRS1995

Earth Sciences Data and Information System (ESDIS) program planning and evaluation methodology development

An Earth Sciences Data and Information System (ESDIS) Project Management Plan (PMP) is prepared. An ESDIS Project Systems Engineering Management Plan (SEMP) consistent with the developed PMP is also prepared. ESDIS and related EOS program requirements developments, management and analysis processes are evaluated. Opportunities to improve the effectiveness of these processes and program/project responsiveness to requirements are identified. Overall ESDIS cost estimation processes are evaluated, and recommendations to improve cost estimating and modeling techniques are developed. ESDIS schedules and scheduling tools are evaluated. Risk assessment, risk mitigation strategies and approaches, and use of risk information in management decision-making are addressed.

Dickinson, William B.↗
NASA NTRSDate not supplied

Early Information Parameter-Set Analysis for Satellite Close Approaches using Machine Learning

Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc

Brianna I. Robertson↗
NASA NTRS2013

HRA Aerospace Challenges

Compared to equipment designed to perform the same function over and over, humans are just not as reliable. Computers and machines perform the same action in the same way repeatedly getting the same result, unless equipment fails or a human interferes. Humans who are supposed to perform the same actions repeatedly often perform them incorrectly due to a variety of issues including: stress, fatigue, illness, lack of training, distraction, acting at the wrong time, not acting when they should, not following procedures, misinterpreting information or inattention to detail. Why not use robots and automatic controls exclusively if human error is so common? In an emergency or off normal situation that the computer, robotic element, or automatic control system is not designed to respond to, the result is failure unless a human can intervene. The human in the loop may be more likely to cause an error, but is also more likely to catch the error and correct it. When it comes to unexpected situations, or performing multiple tasks outside the defined mission parameters, humans are the only viable alternative. Human Reliability Assessments (HRA) identifies ways to improve human performance and reliability and can lead to improvements in systems designed to interact with humans. Understanding the context of the situation that can lead to human errors, which include taking the wrong action, no action or making bad decisions provides additional information to mitigate risks. With improved human reliability comes reduced risk for the overall operation or project.

DeMott, Diana↗
NASA NTRS1995

A Systematic Approach to Hardware Qualification

A systematic approach for the development of a hardware qualification approach is described. This approach stems from the need to break the "Catch-22" of not being able to fly new technology because it hasn't flown. A physics of failure approach is used to identify failure modes and the impact and likelihood of these failures on the mission requirements is plotted in a Requirements Matrix. These same failure modes are plotted against the effectiveness of the available Preventions, Analyses, Control and Tests (PACTs) at screening for, or eliminating, these failure modes in a Test Effectiveness Matrix. Matrix multiplication results in a ranked set of PACTs which can be sorted according to cost and redundancy with other PACTs. This, and other information which results from the process, will allow project managers to make more informed decisions regarding the cost and risk tradeoffs inherent in any qualification program.

hardware↗
NASA NTRS2003

Risk-based analysis and decision making in multi-disciplinary environments

A risk-based decision-making process conceived of and developed at JPL and NASA, has been used to help plan and guide novel technology applications for use on spacecraft. These applications exemplify key challenges inherent in multi-disciplinary design of novel technologies deployed in mission-critical settings. 1) Cross-disciplinary concerns are numerous (e.g., spacecraft involve navigation, propulsion, telecommunications). These concems are cross-coupled and interact in multiple ways (e.g., electromagnetic interference, heat transfer). 2) Time and budget pressures constrain development, operational resources constrain the resulting system (e.g., mass, volume, power). 3) Spacecraft are critical systems that must operate correctly the first time in only partially understood environments, with no chance for repair. 4) Past experience provides only a partial guide: New mission concepts are enhanced and enabled by new technologies, for which past experience is lacking. The decision-making process rests on quantitative assessments of the relationships between three classes of information - objectives (the things the system is to accomplish and constraints on its operation and development), risks (whose occurrence detracts from objectives), and mitigations (options for reducing the likelihood and or severity of risks). The process successfully guides experts to pool their knowledge, using custom-built software to support information gathering and decision-making.

technology↗
NASA NTRS2009

Approach for Mitigating Pressure Garment Design Risks in a Mobile Lunar Surface Systems Architecture

The stated goals of the 2004 Vision for Space Exploration focus on establishing a human presence throughout the solar system beginning with the establishment of a permanent human presence on the Moon. However, the precise objectives to be accomplished on the lunar surface and the optimal system architecture to achieve those objectives have been a topic of much debate since the inception of the Constellation Program. There are two basic styles of system architectures being traded at the Programmatic level: a traditional large outpost that would focus on techniques for survival off our home planet and a greater depth of exploration within one area, or a mobile approach- akin to a series of nomadic camps- that would allow greater breadth of exploration opportunities. The traditional outpost philosophy is well within the understood pressure garment design space with respect to developing interfaces and operational life cycle models. The mobile outpost, however, combines many unknowns with respect to pressure garment performance and reliability that could dramatically affect the cost and schedule risks associated with the Constellation space suit system. This paper provides an overview of the concepts being traded for a mobile architecture from the operations and hardware implementation perspective, describes the primary risks to the Constellation pressure garment associated with each of the concepts, and summarizes the approach necessary to quantify the pressure garment design risks to enable the Constellation Program to make informed decisions when deciding on an overall lunar surface systems architecture.

Aitchison, Lindsay↗
NASA NTRS2010

2009 Space Shuttle Probabilistic Risk Assessment Overview

Loss of a Space Shuttle during flight has severe consequences, including loss of a significant national asset; loss of national confidence and pride; and, most importantly, loss of human life. The Shuttle Probabilistic Risk Assessment (SPRA) is used to identify risk contributors and their significance; thus, assisting management in determining how to reduce risk. In 2006, an overview of the SPRA Iteration 2.1 was presented at PSAM 8 [1]. Like all successful PRAs, the SPRA is a living PRA and has undergone revisions since PSAM 8. The latest revision to the SPRA is Iteration 3. 1, and it will not be the last as the Shuttle program progresses and more is learned. This paper discusses the SPRA scope, overall methodology, and results, as well as provides risk insights. The scope, assumptions, uncertainties, and limitations of this assessment provide risk-informed perspective to aid management s decision-making process. In addition, this paper compares the Iteration 3.1 analysis and results to the Iteration 2.1 analysis and results presented at PSAM 8.

Hamlin, Teri L.↗
NASA NTRS2016

Purpose, Principles, and Challenges of the NASA Engineering and Safety Center

NASA formed the NASA Engineering and Safety Center in 2003 following the Space Shuttle Columbia accident. It is an Agency level, program-independent engineering resource supporting NASA's missions, programs, and projects. It functions to identify, resolve, and communicate engineering issues, risks, and, particularly, alternative technical opinions, to NASA senior management. The goal is to help ensure fully informed, risk-based programmatic and operational decision-making processes. To date, the NASA Engineering and Safety Center (NESC) has conducted or is actively working over 600 technical studies and projects, spread across all NASA Mission Directorates, and for various other U.S. Government and non-governmental agencies and organizations. Since inception, NESC human spaceflight related activities, in particular, have transitioned from Shuttle Return-to-Flight and completion of the International Space Station (ISS) to ISS operations and Orion Multi-purpose Crew Vehicle (MPCV), Space Launch System (SLS), and Commercial Crew Program (CCP) vehicle design, integration, test, and certification. This transition has changed the character of NESC studies. For these development programs, the NESC must operate in a broader, system-level design and certification context as compared to the reactive, time-critical, hardware specific nature of flight operations support.

Gilbert, Michael G.↗