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We report on a practical application of information technology techniques to aid system engineers effectively explore large design spaces. We make use of heuristic search, visualization and data mining, the combination of which we have implemented wtihin a risk management tool in use at JPL and NASA.
Introduction: In 2009 the Augustine Commission identified near-Earth asteroids (NEAs) as high profile destinations for human exploration missions beyond the Earth-Moon system as part of the Flexible Path. More recently the U.S. presidential administration directed NASA to include NEAs as destinations for future human exploration with the goal of sending astronauts to a NEA in the mid to late 2020s. This directive became part of the official National Space Policy of the United States of America as of June 28, 2010. NEA Space-Based Survey and Robotic Precursor Missions: The most suitable targets for human missions are NEAs in Earth-like orbits with long synodic periods. However, these mission candidates are often not observable from Earth until the timeframe of their most favorable human mission opportunities, which does not provide an appropriate amount of time for mission development. A space-based survey telescope could more efficiently find these targets in a timely, affordable manner. Such a system is not only able to discover new objects, but also track and characterize objects of interest for human space flight consideration. Those objects with characteristic signatures representative of volatile-rich or metallic materials will be considered as top candidates for further investigation due to their potential for resource utilization and scientific discovery. Once suitable candidates have been identified, precursor spacecraft are required to perform basic reconnaissance of a few NEAs under consideration for the human-led mission. Robotic spacecraft will assess targets for potential hazards that may pose a risk to the deep space transportation vehicle, its deployable assets, and the crew. Additionally, the information obtained about the NEA's basic physical characteristics will be crucial for planning operational activities, designing in-depth scientific/engineering investigations, and identifying sites on the NEA for sample collection. Human Exploration Considerations: These missions would be the first human expeditions to interplanetary bodies beyond the Earth-Moon system and would prove useful for testing technologies required for human missions to Mars, Phobos and Deimos, and other Solar System destinations. Current analyses of operational concepts suggest that stay times of 15 to 30 days may be possible at a NEA with total mission duration limits of 180 days or less. Hence, these missions would undoubtedly provide a great deal of technical and engineering data on spacecraft operations for future human space exploration while simultaneously conducting detailed investigations of these primitive objects with instruments and equipment that exceed the mass and power capabilities delivered by robotic spacecraft. All of these activities will be vital for refinement of resource characterization/identification and development of extraction/utilization technologies to be used on airless bodies under low- or micro-gravity conditions. In addition, gaining enhanced understanding of a NEA s geotechnical properties and its gross internal structure will assist the development of hazard mitigation techniques for planetary defense. Conclusions: The scientific, resource utilization, and hazard mitigation benefits, along with the programmatic and operational benefits of a human venture beyond the Earth-Moon system, make a piloted sample return mission to a NEA using NASA s proposed human exploration systems a compelling endeavor.
The U.S. nuclear industry is facing a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light-water reactor nuclear power plant operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed in the Risk-Informed Systems Analysis Pathway under the U.S. Department of Energy Light Water Reactor Sustainability Program. The Light Water Reactor Sustainability Program promotes a wide range of research and development activities to maximize both the safety and economic efficiency of nuclear power plants through improved scientific understanding, especially given that many plants are now considering second license renewals. The Risk-Informed Systems Analysis Pathway has two main goals: Deploy methodologies and technologies that better represent safety margins and cost and safety factors; Develop advanced applications that enable cost-effective plant operations. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses and uses artificial intelligence to support the optimization of core design solutions. This report summarizes genetic-algorithm-based multi-objective fuel reload optimization activities, specifically: Developing the non-dominated sorting genetic algorithm II optimizer in the Risk Analysis and Virtual ENviroment (RAVEN); Demonstrating and validating the developed non-dominated sorting genetic algorithm II optimizer using benchmark optimization problems.
Abstract Introduction Adverse reactions are relatively common during peanut oral immunotherapy. To reduce the risk to the patient, some researchers have proposed modifying the allergen to reduce IgE reactivity, creating a putative hypoallergen. Analysis of recently cloned human IgG from patients treated with peanut immunotherapy suggested that there are three common conformational epitopes for the major peanut allergen Ara h 2. We sought to test if structural information on these epitopes could indicate mutagenesis targets for designing a hypoallergen and evaluated the reduction in IgE binding via immunochemistry and a mouse model of passive cutaneous anaphylaxis (PCA). Methods X‐ray crystallography characterized the conformational epitopes in detail, followed by mutational analysis of key residues to modify monoclonal antibody (mAb) and serum IgE binding, assessed by ELISA and biolayer interferometry. A designed Ara h 2 hypoallergen was tested for reduced vascularization in mouse PCA experiments using pooled peanut allergic patient serum. Results A ternary crystal structure of Ara h 2 in complex with patient antibodies 13T1 and 13T5 was determined. Site‐specific mutants were designed that reduced 13T1, 13T5, and 22S1 mAbs binding by orders of magnitude. By combining designed mutations from the three major conformational bins, a hexamutant (Ara h 2 E46R, E89R, E97R, E114R, Q146A, R147E) was created that reduced IgE binding in serum from allergic patients. Further, in the PCA model where mice were primed with peanut allergic patient serum, reactivity upon allergen challenge was significantly decreased using the hexamutant. Conclusion These studies demonstrate that prior knowledge of common conformational epitopes can be used to engineer reduced IgE reactivity, an important first step in hypoallergen design.
The United States (U.S.) nuclear industry faces a challenge in maintaining required levels of safety while ensuring economic competitiveness to stay in business. Safety remains a key parameter for all aspects of light water reactor (LWR) nuclear power plant (NPP) operations. Safety can become more economical by using a risk-informed ecosystem, such as the one being developed by the Risk-Informed Systems Analysis (RISA) Pathway under the U.S. Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program. The LWRS Program promotes a wide range of research and development activities with the goal of maximizing both the safety and economic efficiency of NPPs through improved scientific understanding, especially given many plants are now considering second license renewals. The RISA Pathway has two main goals: (1) deploy methodologies and technologies that better represent safety margins and cost and safety factors and (2) develop advanced applications that enable cost-effective plant operation. The Plant Reload Optimization Platform development project aims to build a reactor core design tool that includes reactor safety and fuel performance analyses, and also uses artificial intelligence to support optimization of core design solutions. This report summarizes Fiscal Year 2022 (FY-22) activity in platform capability developments in RAVEN. This platform performs simulations using industry codes for core design (i.e., PARCS) and fuel performance (i.e., TRANSURANUS) which will allow expansion of the capabilities to include advanced fuel designs such as accident-tolerant fuel (ATF)s with high burnup.
The production of renewable fuels is a critical component of global strategies to reduce greenhouse gas (GHG) emissions. Moreover, the collection of raw materials for its production can provide added benefits such as reduction of wildfire risk, additional income for farmers, and decreased disposal costs. Although there is substantial literature on design and modeling of supply chains, the authors were unable to find a single reference with the information needed for the selection and cost estimation of each type of equipment involved in the supply chain. Therefore, the goal of this research is to gather information necessary for the construction and utilization of models that might drive the identification of a feasible supply chain to produce renewable fuels at a commercial scale. The primary objectives are to 1) understand the supply chain of critical feedstocks for renewable fuels production; 2) identify the equipment commercially available for collection and adequation of feedstock; and 3) consolidate information regarding equipment cost, energy consumption, and efficiency, as well as feedstock storage and transportation systems. This paper provides a compilation for five feedstock types studied for sustainable aviation fuel production: 1) agricultural residues and grasses, 2) forest residues, 3) urban wood waste, 4) oilseeds, 5) fats, oils & greases. All the technologies involved from the field to the gate of the preprocessing or conversion unit were reviewed. The information on fats, oils & greases supply chains and equipment purposely designed for forest thinning and pruning was very limited.
Development schedules and a highly dynamic supply chain are a challenge to developers of complex systems produced at low volume. Flaws in designs, parts and materials availability problems, poor manufacturability, and a lack of knowledge about critical items and key process attributes can be realized well before traditional second-party quality assurance activities begin. Supplier audits and product inspections may have little mitigating effect once these foundational problems have been realized. Their impacts can be significant lifecycle disruption, cost overruns, inability to deliver to plan, and even project cancellation. AS9145, Requirements for Advanced Product Quality Planning and Production Part Approval Process, can be used to drive quality engineering practices into early development lifecycles to significantly reduce this late-cycle risk and to reduce the cost of quality overall. Since its initial publication in 2016, it has had very limited adoption by the DoD, no adoption by NASA, and sparse adoption in the aerospace and defense supply chain. A task group within the Aerospace Industries Association's (AIA) Joint Strategic Quality Council (JSQC) identified that both acquirers and suppliers see as AS9145 as a cost-adder and are hesitant to use it as an alternative to late-stage-heavy quality assurance approaches. A lack of prior use creates large capability gaps in request-for-proposal (RFP) teams, proposal teams, suppliers’ quality management systems (QMS), and in experienced personnel executing the early lifecycle approach. To create a more realizable on-ramp for using AS9145 in the space and defense sectors, the AIA JSQC task team created five deliverable requirements descriptions (DRDs) that can be used in a contract to begin to engage both parties in early lifecycle quality engineering and quality assurance activities, that reduce exposure to late-stage cost and schedule collapse due to unidentified risks in design, supply chain, and manufacturability. These DRDs drive the parties to engage in planning and analysis discussions early on to understand what production risks can be known and how they will focus resources based on safety criticality and the key elements of design and construction. The suppliers and acquirers who will produce the data and information required by the DRD will be able to incrementally evolve their QMS and the acquirer will incrementally be able to track and understand the benefits of cost shifting from late to early development phases. A white paper describing this approach and the five recommended DRDs will be published by the AIA in late 2024 or early 2025.
System-Theoretic Process Analysis (STPA) is a systems-based hazard analysis method that identifies unsafe interactions and control deficiencies in complex systems but has been rarely used for NASA programs in favor of more well-established hazard analyses. To evaluate its applicability, a NASA Safety and Mission Assurance (SMA) team applied the STPA method to an early-stage hybrid electrified aircraft concept, focusing on the energy storage system and electric powertrain. Objectives include assessing STPA’s value relative to traditional methods and its suitability for early design phases. Activities include team training, system review, detailed STPA execution, and comparison with traditional analyses. Findings show STPA provides a structured, comprehensive hazard evaluation and can identify additional risks by expanding analysis boundaries. However, traditional methods can yield similar results when applied rigorously, though they typically require more mature designs. Overall, STPA is a valuable addition, particularly for early development, informing safety requirements and supporting preliminary hazard analyses. Further pilot applications are recommended.
Over the course of long-duration spaceflight, spacecraft develop a microbial ecology that directly interacts with the crew of the vehicle. While most microorganisms are harmless or beneficial to the inhabitants of the vehicle, the presence of medically significant organisms appearing in this semi-closed environment could adversely affect crew health and performance. The risk of exposure of the crew to medically significant organisms during a mission is estimated using information gathered during nominal and contingency environmental monitoring. Analysis of the air and surface microbiota in the habitable compartments of the International Space Station (ISS) over the last four years indicate a high presence of Staphylococcus species reflecting the human inhabitants of the vehicle. Generally, air and surface microbial concentrations are below system design specifications, suggesting a lower risk of contact infection or biodegradation. An evaluation of sample frequency indicates a decrease in the identification of new species, suggesting a lower potential for unknown microorganisms to be identified. However, the opportunistic pathogen, Staphylococcus aureus, has been identified in 3 of the last 5 air samples and 5 of the last 9 surface samples. In addition, 47% of the coagulase negative Staphylococcus species that were isolated from the crew, ISS, and its hardware were found to be methicillin resistance. In combination, these observations suggest the potential of methicillin resistant infectious agents over time.
With the ending of the Space Shuttle Program, it is critical that we not forget the Human Factors lessons we have learned over the years. At every phase of the life cycle, from manufacturing, processing and integrating vehicle and payload, to launch, flight operations, mission control and landing, hundreds of teams have worked together to achieve mission success in one of the most complex, high-risk socio-technical enterprises ever designed. Just as there was great diversity in the types of operations performed at every stage, there was a myriad of human factors that could further complicate these human systems. A single mishap or close call could point to issues at the individual level (perceptual or workload limitations, training, fatigue, human error susceptibilities), the task level (design of tools, procedures and aspects of the workplace), as well as the organizational level (appropriate resources, safety policies, information access and communication channels). While we have often had to learn through human mistakes and technological failures, we have also begun to understand how to design human systems in which individuals can excel, where tasks and procedures are not only safe but efficient, and how organizations can foster a proactive approach to managing risk and supporting human enterprises. Panelists will talk about their experiences as they relate human factors to a particular phase of the shuttle life cycle. They will conclude with a framework for tying together human factors lessons-learned into system-level risk management strategies.
The In-Time Aviation Safety Management System (IASMS) Concept of Operations (ConOps) envisions new capabilities to monitor, assess, and mitigate flight safety risks. Systems will be tailored to mission type, vehicle/equipage type, operational environment, and safety risk tolerance. Within an IASMS framework, several capabilities may be implemented spanning three operational phases (pre-flight, in-flight, and post-flight/off-line); and consisting of lower level functions and information services which may reside onboard the aircraft, on third-party server(s), and/or on ground/operator station(s). Each capability will be designed to produce and disseminate safety-relevant information; perform detection, diagnosis, and prediction of unsafe situations; and/or execute mitigation actions when hazardous events warrant such changes. This paper focuses on recent testing of airborne capabilities that demonstrate inflight aspects of the overarching concept for autonomous unmanned aircraft systems (UAS) operations in urban environments. A flight test architecture is described that applies run-time assurance principles (e.g., executes independent of the unassured autopilot), real-time risk assessment, and a technique to execute contingencies if necessary either automatically or via pilot intervention. Several tests using small UAS were conducted to verify the assured in-flight risk mitigation capability. The paper draws significantly from a larger NASA technical report and recent prior conference papers, providing additional details. Data is analyzed for two representative flights to illustrate the performance for various sequential and simultaneous hazards used during testing. During each automated flight, several hazards are encountered at various points along the flight path. At each point, the hazard is mitigated by the system, with the vehicle then continuing to subsequent points. The paper concludes with lessons-learned regarding relevant aspects of the overarching IASMS concept and how it may be updated and further advanced in the future.
Frontline has prioritized personnel safety, equipment preservation, and environmental protection throughout the design process of the autothermal pyrolysis unit. To facilitate a safe design, Frontline completed an informal hazards and operability (HAZOP) study and a formal HAZOP study, and employ management of change procedures. The result of these safety procedures is a plant that will function in a safe manner with a limited and acceptable amount of risk. Frontline took an approach it used in previous projects to execute a preliminary, internally facilitated hazards and operability (HAZOP) study. While this HAZOP study was performed without any subsequent change tracking, it enables a group of well-trained engineers to consider the safety implications of each part of the plant in a thorough and methodical manner. Frontline chose to bring in a pyrolysis consultant (Daren Daugaard of Burning Oak Energy) to participate in the review. Following the preliminary HAZOP and once the detailed design work was nearing completion, Frontline performed a formal HAZOP with a third-party facilitator, Jason Stittleburg of Novetus Engineering. Although the plant is not subject to process safety management (PSM) requirements, this formal HAZOP was performed in accordance with OSHA regulations deemed reasonable for PSM. Finally, after the formal HAZOP was conducted, Frontline maintained a safe system by implementing and following management of change procedures on each substantial change to the process. Frontline has kept a record of each subsequent change made to the formal HAZOP P&IDs. The process hazard assessment process allowed Frontline to find and correct several unacceptable configurations within the plant.
In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.
The issue of technology advancement and future space transportation vehicles is addressed. The challenge is to develop systems which can be evolved and improved in small incremental steps where each increment reduces present cost, improves, reliability, or does neither but sets the stage for a second incremental upgrade that does. Future requirements are interface standards for commercial off the shelf products to aid in the development of integrated facilities; enhanced automated code generation system slightly coupled to specification and design documentation; modeling tools that support data flow analysis; and shared project data bases consisting of technical characteristics cast information, measurement parameters, and reusable software programs. Topics addressed include: advanced avionics development strategy; risk analysis and management; tool quality management; low cost avionics; cost estimation and benefits; computer aided software engineering; computer systems and software safety; system testability; and advanced avionics laboratories - and rapid prototyping. This presentation is represented by viewgraphs only.
The Workstation Prototype Laboratory is currently working on a number of projects which can have a direct impact on ground operations automation. These projects include: (1) The fuel cell monitoring system (FCMS), which will monitor and detect problems with the fuel cells on the shuttle. FCMS will use a combination of rules (forward/backward) and multithreaded procedures, which run concurrently with the rules, to implement the malfunction algorithms of the EGIL flight controllers. The combination of rule-based reasoning and procedural reasoning allows us to more easily map the malfunction algorithms into a real-time system implementation. (2) A graphical computation language (AGCOMPL) is an experimental prototype to determine the benefits and drawbacks of using a graphical language to design computations (algorithms) to work on shuttle or space station telemetry and trajectory data. (3) The design of a system will allow a model of an electrical system, including telemetry sensors, to be configured on the screen graphically using previously defined electrical icons. This electrical model would then be used to generate rules and procedures for detecting malfunctions in the electrical components of the model. (4) A generic message management (GMM) system is being designed for real-time applications as a message management system which sends advisory messages to a user. The primary purpose of GMM is to reduce the risk of overloading a user with information when multiple failures occur and to assist the developer in the devising an explanation facility. The emphasis of our work is to develop practical tools and techniques, including identification of appropriate software tools to support research, application, and tool building activities, while determining the feasibility of a given approach.
Aerothermodynamics, encompassing aerodynamics, aeroheating, and fluid dynamic and physical processes, is the genesis for the design and development of advanced space transportation vehicles. It provides crucial information to other disciplines involved in the development process such as structures, materials, propulsion, and avionics. Sources of aerothermodynamic information include ground-based facilities, computational fluid dynamic (CFD) and engineering computer codes, and flight experiments. Utilization of this triad is required to provide the optimum requirements while reducing undue design conservatism, risk, and cost. This paper discusses the role of ground-based facilities in the design of future space transportation system concepts. Testing methodology is addressed, including the iterative approach often required for the assessment and optimization of configurations from an aerothermodynamic perspective. The influence of vehicle shape and the transition from parametric studies for optimization to benchmark studies for final design and establishment of the flight data book is discussed. Future aerothermodynamic testing requirements including the need for new facilities are also presented.
The Workstation Prototype Laboratory is currently working on a number of projects which we feel can have a direct impact on ground operations automation. These projects include: The Fuel Cell Monitoring System (FCMS), which will monitor and detect problems with the fuel cells on the Shuttle. FCMS will use a combination of rules (forward/backward) and multi-threaded procedures which run concurrently with the rules, to implement the malfunction algorithms of the EGIL flight controllers. The combination of rule based reasoning and procedural reasoning allows us to more easily map the malfunction algorithms into a real-time system implementation. A graphical computation language (AGCOMPL). AGCOMPL is an experimental prototype to determine the benefits and drawbacks of using a graphical language to design computations (algorithms) to work on Shuttle or Space Station telemetry and trajectory data. The design of a system which will allow a model of an electrical system, including telemetry sensors, to be configured on the screen graphically using previously defined electrical icons. This electrical model would then be used to generate rules and procedures for detecting malfunctions in the electrical components of the model. A generic message management (GMM) system. GMM is being designed as a message management system for real-time applications which send advisory messages to a user. The primary purpose of GMM is to reduce the risk of overloading a user with information when multiple failures occurs and in assisting the developer in devising an explanation facility. The emphasis of our work is to develop practical tools and techniques, while determining the feasibility of a given approach, including identification of appropriate software tools to support research, application and tool building activities.
This paper showcases the unique technical capabilities of the CLVTOPS multi-body flight dynamics toolchain developed by Marshall Space Flight Center (MSFC) for analyzing NASA’s Space Launch System (SLS) liftoff events. The CLVTOPS toolchain integrates high-fidelity simulations, geometric algorithms, advanced data analytics, and post-flight telemetry to demonstrate positive clearance between separating bodies and inform design decisions that enhance mission reliability. Proper liftoff separation is crucial to the success of the launch vehicle’s mission; vehicle impacts with the launch tower and supporting components incur a heightened risk of mission failure. For liftoff analysis, the CLVTOPS toolchain enables the integration of vehicle, launch pad, and environmental input models for the investigation of key clearance effectors. Furthermore, recent enhancements to the CLVTOPS toolchain allow for validation via photogrammetric trajectory reconstruction and plume pressure impingement estimation on the tower. The following sections will walk through the tool-chain, SLS liftoff ground rules and assumptions, key models, standard analysis, recent enhancements, and post-flight validation of the Artemis I mission liftoff event.