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Analyze, Visualize, and Evaluate structure and behavior using static and dynamic information, individual systems as well as systems of systems. Next steps: Refine software tool support; Apply to other systems; and Apply earlier in system life cycle.
A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Center
Human exploration missions beyond low earth orbit will be long duration with abort scenarios of days to months. This necessitates provisioning the crew with all the things they will need to sustain themselves while carrying out mission objectives. Systems engineering and integration is critical to the point where extensive integrated testing of life support systems on the ground is required to identify and mitigate risks. Ground test facilities (human-rated altitude chamber) at the Johnson Space Center are being readied to integrate all the systems for a mission along with a human test crew. The relevant environment will include deep space habitat human accommodations, sealed atmosphere of 8 psi total pressure and 32% oxygen concentration, life support systems (food, air, water), communications, crew accommodations, medical, EVA, tools, etc. Testing periods will approximate those of the expected missions (such as a near Earth asteroid, Earth-Moon L2 or L1, the moon). This type of integrated testing is needed for research and technology development as well as later during the mission design, development, test, and evaluation (DDT&E) phases of an approved program. Testing will evolve to be carried out at the mission level fly the mission on the ground . Mission testing will also serve to inform the public and provide the opportunity for active participation by international partners.
Human exploration missions beyond low earth orbit will be long duration with abort scenarios of days to months. Providing crews with the essentials of life such as clean air and potable water means recycling human metabolic wastes back to useful products. Individual technologies are under development for such things as CO2 scrubbing, recovery of O2 from CO2, turning waste water into potable water, and so on. But in order to fully evaluate and mature technologies fully they must be tested in a relevant, high-functionality environment; a systems environment where technologies are challenged with real human metabolic wastes. It is for this purpose that an integrated systems ground testing capability at the Johnson Space Center is being readied for testing. The relevant environment will include deep space habitat human accommodations, sealed atmosphere of 8 psi total pressure and 32% oxygen concentration, life support systems (food, air, water), communications, crew accommodations, medical, EVA, tools, etc. Testing periods will approximate those of the expected missions (such as a near Earth asteroid, Earth ]Moon L2 or L1, the moon, and Mars). This type of integrated testing is needed not only for research and technology development but later during the mission design, development, test, and evaluation phases of preparing for the mission.
Structural health monitoring (SHM) is one of the most important tools available for the maintenance, safety, and integrity of aerospace structural systems. Lightweight, electromagnetic-interference- immune, fiber-optic sensor-based SHM will play an increasing role in more secure air transportation systems. Manufacturers and maintenance personnel have pressing needs for significantly improving safety and reliability while providing for lower inspection and maintenance costs. Undetected or untreated damage may grow and lead to catastrophic structural failure. Damage can originate from the strain/stress history of the material, imperfections of domain boundaries in metals, delamination in multi-layer materials, or the impact of machine tools in the manufacturing process. Damage can likewise develop during service life from wear and tear, or under extraordinary circumstances such as with unusual forces, temperature cycling, or impact of flying objects. Monitoring and early detection are key to preventing a catastrophic failure of structures, especially when these are expected to perform near their limit conditions.
Dr. Nick Siegler of the NASA Jet Propulsion Laboratory (JPL) began his talk by stating that the main goal of the Exoplanet Exploration Program technology effort is to enable future space missions to observe a planetary spectrum of a rocky planet in the habitable zone of its star and understand it in the context of potential life. He went on to say that the main exoplanet discovery tools, the radial velocity and transit techniques, which have discovered more than 95% of the more than 3,400 exoplanets, will not be the techniques to directly image exoplanets, which is needed to get a reflected light spectrum. Spectroscopy will be hard though because there simply aren’t many photons available to use, but it will not be the biggest problem. The biggest problem will be suppressing the light from the stars which can be 10 billion times brighter than a rocky planet in the habitable zone of a Sun analog. Starlight suppression could be done in one of three ways: internal occulters (i.e., coronagraphs), external occulters (i.e., starshades), and nulling interferometers. The latter option is the least technologically mature of the options and one that NASA is not currently pursuing.
For a long time, both in theory and in practice, safety and reliability have not been clearly differentiated, which leads to confusion, inefficiency, and sometime counter-productive practices in executing each of these two disciplines. It is imperative to address the uniqueness and the unison of these two disciplines to help both disciplines become more effective and to promote a better integration of the two for enhancing safety and reliability in our products as an overall objective. There are two purposes of this paper. First, it will investigate the uniqueness and unison of each discipline and discuss the interrelationship between the two for awareness and clarification. Second, after clearly understanding the unique roles and interrelationship between the two in a product design and development life cycle, we offer suggestions to enhance the disciplines with distinguished and focused roles, to better integrate the two, and to improve unique sets of skills and tools of reliability and safety processes. From the uniqueness aspect, the paper identifies and discusses the respective uniqueness of reliability and safety from their roles, accountability, nature of requirements, technical scopes, detailed technical approaches, and analysis boundaries. It is misleading to equate unreliable to unsafe, since a safety hazard may or may not be related to the component, sub-system, or system functions, which are primarily what reliability addresses. Similarly, failing-to-function may or may not lead to hazard events. Examples will be given in the paper from aerospace, defense, and consumer products to illustrate the uniqueness and differences between reliability and safety. From the unison aspect, the paper discusses what the commonalities between reliability and safety are, and how these two disciplines are linked, integrated, and supplemented with each other to accomplish the customer requirements and product goals. In addition to understanding the uniqueness in reliability and safety, a better understanding of unison and commonalities will further help in understanding the interaction between reliability and safety. This paper discusses the unison and uniqueness of reliability and safety. It presents some suggestions for better integration of the two disciplines in terms of technical approaches, tools, techniques, and skills to enhance the role of reliability and safety in supporting a product design and development life cycle. The paper also discusses eliminating the redundant effort and minimizing the overlap of reliability and safety analyses for an efficient implementation of the two disciplines.
Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.
This book gives a popular account of the forces that have shaped human beings into their present form and created the power of human intelligence, and considers the prospects for intelligent life on other planets in the solar system and elsewhere in the universe. The chain of events leading from the big bang to the origin of life on earth is reviewed together with the observations that established the expansion of the universe. Philosophical difficulties with the concept of a universe that has both a beginning and an end are pondered, steady-state cosmology is briefly explained, and the discovery of the relict microwave background is discussed. The formation of the solar system is recounted along with the scientific view of the origin of terrestrial life. Attention is given to the origin of cells and the evolution of oxygen-breathing life, multicelled creatures, armored animals, fishes, amphibians, early reptiles, dinosaurs, and mammals. The development of mammalian intelligence is traced from the early tree dwellers through monkeys, apes, ape men, humanoid tool makers, and primitive members of the genus Homo, to Homo sapiens. Possible evidence for the existence of life on Mars is evaluated together with prospects for communication or other contact with extraterrestrial intelligence.
This talk began by presenting the Space Station Freedom Program (SSFP) definitions of software commonality and software reuse. Software commonality is the use of identical, interchangeable, functionally compatible, or similar software items to satisfy different sets of functionally similar requirements. The Software Support Environment (SSE) and the Data Management System (DMS) of onboard computing facilities are examples of SSFP common software. Software reuse is the use of identical, compatible, or similar software items in either modified or unmodified form to satisfy development activities at any point in the software life cycle; in other words, taking an existing item and applying it to another development activity. Software commonality has been mandated in several critical areas (such as the SSE and DMS) and a policy directive is under review. A software reuse study group was established in May 1988 to gather background information (see Level 2 Software Reuse Study that follows by Scott Herman). The SSFP Program Definition and Requirements Document contains requirements for SSE support in the area of software reuse. The SSE is a collection of tools and rules, and provides the common environment to be used for the life cycle management of all SSFP operational software.
The reentry demise of fiber-reinforced polymer (FRP) composites is an increasing concern for modern spacecraft at end of life. Unlike traditional materials such as metals, shredding of the material by aerodynamic forces appears to be a major component of the reentry demise mechanism. This paper will describe a new mechanical, strength-based, material demise model for the Object Reentry Survival Analysis Tool (ORSAT) Version 7.1. The model is based on laboratory in-situ and residual strength tests of several FRP materials performed during the NASA Orbital Debris Program Office’s Phase II Composite Material Demise test campaign. To test the residual strength of partially charred FRP materials, the authors tested 107 rectangular shaped samples of different thicknesses that were previously exposed to high-enthalpy flow at the University of Texas at Austin’s Inductively Coupled Plasma Torch facility. Tests were performed under normal atmospheric conditions at NASA Johnson Space Center’s Experimental Impact Laboratory using a Chatillon TCD1000 tensile test machine configured with a three-point bending jig. Mean fracture load, residual strength, delamination, and flexural modulus were measured for each test. An engineering model of aeromechanical demise for each material was developed by correlating the measured residual strength of the samples with the duration and magnitude of the applied heat flux and the mass loss and char progression. This model has been implemented in ORSAT 7.1 for the built-in, charring carbon fiber/epoxy and charring glass fiber/epoxy material models. The new model was verified by calculating the demise of hundreds of FRP composite fragments of various shapes and sizes and checking the calculations for consistency, with specific focus on material characterization in one-dimension. Further tests are planned in hypersonic flow facilities to validate the assumptions used in the model.
The reentry demise of fiber-reinforced polymer (FRP) composites is an increasing concern for modern spacecraft at end of life. Unlike traditional materials such as metals, shredding of the material by aerodynamic forces appears to be a major component of the reentry demise mechanism. This paper will describe a new mechanical, strength-based, material demise model for the Object Reentry Survival Analysis Tool (ORSAT) Version 7.1. The model is based on laboratory in-situ and residual strength tests of several FRP materials performed during the NASA Orbital Debris Program Office’s Phase II Composite Material Demise test campaign. To test the residual strength of partially charred FRP materials, the authors tested 107 rectangular shaped samples of different thicknesses that were previously exposed to high-enthalpy flow at the University of Texas at Austin’s Inductively Coupled Plasma Torch facility. Tests were performed under normal atmospheric conditions at NASA Johnson Space Center’s Experimental Impact Laboratory using a Chatillon TCD1000 tensile test machine configured with a three-point bending jig. Mean fracture load, residual strength, delamination, and flexural modulus were measured for each test. An engineering model of aeromechanical demise for each material was developed by correlating the measured residual strength of the samples with the duration and magnitude of the applied heat flux and the mass loss and char progression. This model has been implemented in ORSAT 7.1 for the built-in, charring carbon fiber/epoxy and charring glass fiber/epoxy material models. The new model was verified by calculating the demise of hundreds of FRP composite fragments of various shapes and sizes and checking the calculations for consistency, with specific focus on material characterization in one-dimension. Further tests are planned in hypersonic flow facilities to validate the assumptions used in the model.
This report was compiled to provide recommendations on the availability of public background data from the U.S. Federal life cycle assessment (LCA) Data Commons to be conformant with the Association for Life Cycle Assessment (ACLCA) 2022 Product Category Rule (PCR) Open Standard to build technical tools that can assist industry in creating more comparable Type II Environmental Product Declarations (EPDs) for Federal Buy Clean and sustainability initiatives. The Federal LCA Commons is not only a public data source but also a consistently structured, self-referencing mega-repository for data developed by federal agency experts (in agency repositories) and by academia, nonprofit organizations, and industry (via the US Life Cycle Inventory Database). The Federal LCA Commons Technical Working Group is continuously improving the standardization of data documentation, formatting, and nomenclature to ensure lossless data loading and accurate data representation. This report and appendixes include the following: 1) An introduction to data-driven Buy Clean and decarbonization initiatives at the federal level; 2) The current status and associated challenges with LCA data and EPD standards and comparability; 3) Opportunities for the Federal LCA Commons to support conformance with the ACLCA 2022 PCR Open Standard and provide resources to implement the Federal Sustainability Plan, Buy Clean Program, and Inflation Reduction Act (IRA) sustainability goals and objectives. To date, the Federal LCA Commons is the result of coordinated work by National Renewable Energy Laboratory (NREL), the U.S. Department of Agriculture (USDA), the Environmental Protection Agency (EPA), the National Energy Technology Laboratory (NETL), the Argonne National Laboratory (ANL), the U.S. Army Corps of Engineers (USACE), the Federal Highway Administration (FHWA), the U.S. Forest Service (USFS), the Federal Aviation Administration (FAA), the Department of Defense (DoD) and the National Institute of Standards and Technologies (NIST). The Federal LCA Commons will continue to combine databases from the collaborating agencies while remaining a public resource. There are several initiatives among the collaborating agencies to expand the Federal LCA Commons and dedicated federal funding and resources could accelerate and strengthen these initiatives.
NASA currently has a program called the Space Synthetic Biology Project. Synthetic Biology or SynBio is the design and construction of new biological functions and systems not found in nature. Four NASA field centers, along with experts from industry and academia, have been partnering on the Space Synthetic Biology Project and are working on new breakthroughs in this increasingly useful pursuit, which is part a science discipline and part engineering. Led by researchers at NASA s Ames Research Center, the team is studying how this powerful new tool can help NASA now and in the future. The project was created to harness biology in reliable, robust, engineered systems to support the agency s exploration and science missions, to improve life on Earth and to help shape NASA's future. The program also is intended to contribute foundational tools to the synthetic biology research community.
BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.
The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.
The new DOE Order 436.1A approved on April 25 th provides instructions to incorporate principles of sustainability early in the project planning and design process. Integral to the principles of sustainability is life cycle cost effectiveness Life Cycle Cost (LCC) Analysis is vital to the sustainable energy efficient design and construction of the Electron Ion Collider (EIC). Reducing energy consumption has a direct impact on reducing life cycle operating costs with benefits to the environment. The early stages of the project are the most influential where design decisions and so life-cycle considerations during this stage can result in significant impacts to the energy footprint of the design. For example, when comparing between various options, it is necessary to compare the energy savings in $\frac{US$}{kWh}$ to the capital cost in US$. And although uncertain by nature, it is important to factor in the expected inflation and discount of future spendings to compare with the cost of immediate capital investment. This tech note presents a tool that engineers can readily use to analyze energy operating costs using an incremental life cycle cost method when comparing different design alternative.
Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.