1991 NASA Life Support Systems Analysis workshop

The 1991 Life Support Systems Analysis Workshop was sponsored by NASA Headquarters' Office of Aeronautics and Space Technology (OAST) to foster communication among NASA, industrial, and academic specialists, and to integrate their inputs and disseminate information to them. The overall objective of systems analysis within the Life Support Technology Program of OAST is to identify, guide the development of, and verify designs which will increase the performance of the life support systems on component, subsystem, and system levels for future human space missions. The specific goals of this workshop were to report on the status of systems analysis capabilities, to integrate the chemical processing industry technologies, and to integrate recommendations for future technology developments related to systems analysis for life support systems. The workshop included technical presentations, discussions, and interactive planning, with time allocated for discussion of both technology status and time-phased technology development recommendations. Key personnel from NASA, industry, and academia delivered inputs and presentations on the status and priorities of current and future systems analysis methods and requirements

Performance Models for Split-execution Computing Systems

Split-execution computing leverages the capabilities of multiple computational models to solve problems, but splitting program execution across different computational models incurs costs associated with the translation between domains. We analyze the performance of a split-execution computing system developed from conventional and quantum processing units (QPUs) by using behavioral models that track resource usage. We focus on asymmetric processing models built using conventional CPUs and a family of special-purpose QPUs that employ quantum computing principles. Our performance models account for the translation of a classical optimization problem into the physical representation required by the quantum processor while also accounting for hardware limitations and conventional processor speed and memory. We conclude that the bottleneck in this split-execution computing system lies at the quantum-classical interface and that the primary time cost is independent of quantum processor behavior.Comment: Presented at 18th Workshop on Advances in Parallel and Distributed Computational Models [APDCM2016] on 23 May 2016; 10 page

1992 NASA Life Support Systems Analysis workshop

The 1992 Life Support Systems Analysis Workshop was sponsored by NASA's Office of Aeronautics and Space Technology (OAST) to integrate the inputs from, disseminate information to, and foster communication among NASA, industry, and academic specialists. The workshop continued discussion and definition of key issues identified in the 1991 workshop, including: (1) modeling and experimental validation; (2) definition of systems analysis evaluation criteria; (3) integration of modeling at multiple levels; and (4) assessment of process control modeling approaches. Through both the 1991 and 1992 workshops, NASA has continued to seek input from industry and university chemical process modeling and analysis experts, and to introduce and apply new systems analysis approaches to life support systems. The workshop included technical presentations, discussions, and interactive planning, with sufficient time allocated for discussion of both technology status and technology development recommendations. Key personnel currently involved with life support technology developments from NASA, industry, and academia provided input to the status and priorities of current and future systems analysis methods and requirements

Virtual Astronomy, Information Technology, and the New Scientific Methodology

All sciences, including astronomy, are now entering the era of information abundance. The exponentially increasing volume and complexity of modern data sets promises to transform the scientific practice, but also poses a number of common technological challenges. The Virtual Observatory concept is the astronomical community's response to these challenges: it aims to harness the progress in information technology in the service of astronomy, and at the same time provide a valuable testbed for information technology and applied computer science. Challenges broadly fall into two categories: data handling (or "data farming"), including issues such as archives, intelligent storage, databases, interoperability, fast networks, etc., and data mining, data understanding, and knowledge discovery, which include issues such as automated clustering and classification, multivariate correlation searches, pattern recognition, visualization in highly hyperdimensional parameter spaces, etc., as well as various applications of machine learning in these contexts. Such techniques are forming a methodological foundation for science with massive and complex data sets in general, and are likely to have a much broather impact on the modern society, commerce, information economy, security, etc. There is a powerful emerging synergy between the computationally enabled science and the science-driven computing, which will drive the progress in science, scholarship, and many other venues in the 21st century

Peer-to-Peer Planning for Space Mission Control

Planning and scheduling for space operations entails the development of applications that embed intimate domain knowledge of distinct areas of mission control, while allowing for significant collaboration among them. The separation is useful because of differences in the planning problem, solution methods, and frequencies of replanning that arise in the different disciplines. For example, planning the activities of human spaceflight crews requires some reasoning about all spacecraft resources at timescales of minutes or seconds, and is subject to considerable volatility. Detailed power planning requires managing the complex interplay of power consumption and production, involves very different classes of constraints and preferences, but once plans are generated they are relatively stable

Synthesis of separation processes with reinforcement learning

This paper shows the implementation of reinforcement learning (RL) in commercial flowsheet simulator software (Aspen Plus V12) for designing and optimising a distillation sequence. The aim of the SAC agent was to separate a hydrocarbon mixture in its individual components by utilising distillation. While doing so it tries to maximise the profit produced by the distillation sequence. All actions of the agent were set by the SAC agent in Python and communicated in Aspen Plus via an API. Here the distillation column was simulated by use of the build-in RADFRAC column. With this a connection was established for data transfer between Python and Aspen and the agent succeeded to show learning behaviour, while increasing profit. Although results were generated, the use of Aspen was slow (190 hours) and Aspen was found unsuitable for parallelisation. This makes that Aspen is incompatible for solving RL problems. Code and thesis are available at https://github.com/lollcat/Aspen-R

Activity Planning for a Lunar Orbital Mission

This paper describes a challenging, real-world planning problem within the context of a NASA mission called LADEE (Lunar Atmospheric Dust Environment Explorer). LADEEs science phase was performed in an equatorial, retrograde orbit around the Moon. The science observations were constrained with respect to key points in the spacecrafts orbit. We present the approach taken to reduce the complexity of the activity planning task in order to effectively perform it within the time pressures imposed by the mission requirements. One key aspect of this approach is the design of the activity planning process based on principles of problem decomposition and planning abstraction levels. The second key aspect is the mixed-initiative system developed for this task, called LASS (LADEE Activity Scheduling System). The primary challenge for LASS was representing and managing the orbit-based science constraints, given their dynamic nature due to the continually updated orbit determination solution

Index to NASA news releases and speeches, 1988

This issue of the Index to NASA News Releases and Speeches contains a listing of news releases distributed by the Office of Public Affairs, NASA Headquarters, and a selected listing of speeches presented by members of the Headquarters staff during 1988. The index is arranged in six sections: Subject Index, Personal Names Index, News Release Number Index, Accession Number Index, and Speeches and News Releases

Engineering Resilient Space Systems

Several distinct trends will influence space exploration missions in the next decade. Destinations are becoming more remote and mysterious, science questions more sophisticated, and, as mission experience accumulates, the most accessible targets are visited, advancing the knowledge frontier to more difficult, harsh, and inaccessible environments. This leads to new challenges including: hazardous conditions that limit mission lifetime, such as high radiation levels surrounding interesting destinations like Europa or toxic atmospheres of planetary bodies like Venus; unconstrained environments with navigation hazards, such as free-floating active small bodies; multielement missions required to answer more sophisticated questions, such as Mars Sample Return (MSR); and long-range missions, such as Kuiper belt exploration, that must survive equipment failures over the span of decades. These missions will need to be successful without a priori knowledge of the most efficient data collection techniques for optimum science return. Science objectives will have to be revised ‘on the fly’, with new data collection and navigation decisions on short timescales. Yet, even as science objectives are becoming more ambitious, several critical resources remain unchanged. Since physics imposes insurmountable light-time delays, anticipated improvements to the Deep Space Network (DSN) will only marginally improve the bandwidth and communications cadence to remote spacecraft. Fiscal resources are increasingly limited, resulting in fewer flagship missions, smaller spacecraft, and less subsystem redundancy. As missions visit more distant and formidable locations, the job of the operations team becomes more challenging, seemingly inconsistent with the trend of shrinking mission budgets for operations support. How can we continue to explore challenging new locations without increasing risk or system complexity? These challenges are present, to some degree, for the entire Decadal Survey mission portfolio, as documented in Vision and Voyages for Planetary Science in the Decade 2013–2022 (National Research Council, 2011), but are especially acute for the following mission examples, identified in our recently completed KISS Engineering Resilient Space Systems (ERSS) study: 1. A Venus lander, designed to sample the atmosphere and surface of Venus, would have to perform science operations as components and subsystems degrade and fail; 2. A Trojan asteroid tour spacecraft would spend significant time cruising to its ultimate destination (essentially hibernating to save on operations costs), then upon arrival, would have to act as its own surveyor, finding new objects and targets of opportunity as it approaches each asteroid, requiring response on short notice; and 3. A MSR campaign would not only be required to perform fast reconnaissance over long distances on the surface of Mars, interact with an unknown physical surface, and handle degradations and faults, but would also contain multiple components (launch vehicle, cruise stage, entry and landing vehicle, surface rover, ascent vehicle, orbiting cache, and Earth return vehicle) that dramatically increase the need for resilience to failure across the complex system. The concept of resilience and its relevance and application in various domains was a focus during the study, with several definitions of resilience proposed and discussed. While there was substantial variation in the specifics, there was a common conceptual core that emerged—adaptation in the presence of changing circumstances. These changes were couched in various ways—anomalies, disruptions, discoveries—but they all ultimately had to do with changes in underlying assumptions. Invalid assumptions, whether due to unexpected changes in the environment, or an inadequate understanding of interactions within the system, may cause unexpected or unintended system behavior. A system is resilient if it continues to perform the intended functions in the presence of invalid assumptions. Our study focused on areas of resilience that we felt needed additional exploration and integration, namely system and software architectures and capabilities, and autonomy technologies. (While also an important consideration, resilience in hardware is being addressed in multiple other venues, including 2 other KISS studies.) The study consisted of two workshops, separated by a seven-month focused study period. The first workshop (Workshop #1) explored the ‘problem space’ as an organizing theme, and the second workshop (Workshop #2) explored the ‘solution space’. In each workshop, focused discussions and exercises were interspersed with presentations from participants and invited speakers. The study period between the two workshops was organized as part of the synthesis activity during the first workshop. The study participants, after spending the initial days of the first workshop discussing the nature of resilience and its impact on future science missions, decided to split into three focus groups, each with a particular thrust, to explore specific ideas further and develop material needed for the second workshop. The three focus groups and areas of exploration were: 1. Reference missions: address/refine the resilience needs by exploring a set of reference missions 2. Capability survey: collect, document, and assess current efforts to develop capabilities and technology that could be used to address the documented needs, both inside and outside NASA 3. Architecture: analyze the impact of architecture on system resilience, and provide principles and guidance for architecting greater resilience in our future systems The key product of the second workshop was a set of capability roadmaps pertaining to the three reference missions selected for their representative coverage of the types of space missions envisioned for the future. From these three roadmaps, we have extracted several common capability patterns that would be appropriate targets for near-term technical development: one focused on graceful degradation of system functionality, a second focused on data understanding for science and engineering applications, and a third focused on hazard avoidance and environmental uncertainty. Continuing work is extending these roadmaps to identify candidate enablers of the capabilities from the following three categories: architecture solutions, technology solutions, and process solutions. The KISS study allowed a collection of diverse and engaged engineers, researchers, and scientists to think deeply about the theory, approaches, and technical issues involved in developing and applying resilience capabilities. The conclusions summarize the varied and disparate discussions that occurred during the study, and include new insights about the nature of the challenge and potential solutions: 1. There is a clear and definitive need for more resilient space systems. During our study period, the key scientists/engineers we engaged to understand potential future missions confirmed the scientific and risk reduction value of greater resilience in the systems used to perform these missions. 2. Resilience can be quantified in measurable terms—project cost, mission risk, and quality of science return. In order to consider resilience properly in the set of engineering trades performed during the design, integration, and operation of space systems, the benefits and costs of resilience need to be quantified. We believe, based on the work done during the study, that appropriate metrics to measure resilience must relate to risk, cost, and science quality/opportunity. Additional work is required to explicitly tie design decisions to these first-order concerns. 3. There are many existing basic technologies that can be applied to engineering resilient space systems. Through the discussions during the study, we found many varied approaches and research that address the various facets of resilience, some within NASA, and many more beyond. Examples from civil architecture, Department of Defense (DoD) / Defense Advanced Research Projects Agency (DARPA) initiatives, ‘smart’ power grid control, cyber-physical systems, software architecture, and application of formal verification methods for software were identified and discussed. The variety and scope of related efforts is encouraging and presents many opportunities for collaboration and development, and we expect many collaborative proposals and joint research as a result of the study. 4. Use of principled architectural approaches is key to managing complexity and integrating disparate technologies. The main challenge inherent in considering highly resilient space systems is that the increase in capability can result in an increase in complexity with all of the 3 risks and costs associated with more complex systems. What is needed is a better way of conceiving space systems that enables incorporation of capabilities without increasing complexity. We believe principled architecting approaches provide the needed means to convey a unified understanding of the system to primary stakeholders, thereby controlling complexity in the conception and development of resilient systems, and enabling the integration of disparate approaches and technologies. A representative architectural example is included in Appendix F. 5. Developing trusted resilience capabilities will require a diverse yet strategically directed research program. Despite the interest in, and benefits of, deploying resilience space systems, to date, there has been a notable lack of meaningful demonstrated progress in systems capable of working in hazardous uncertain situations. The roadmaps completed during the study, and documented in this report, provide the basis for a real funded plan that considers the required fundamental work and evolution of needed capabilities. Exploring space is a challenging and difficult endeavor. Future space missions will require more resilience in order to perform the desired science in new environments under constraints of development and operations cost, acceptable risk, and communications delays. Development of space systems with resilient capabilities has the potential to expand the limits of possibility, revolutionizing space science by enabling as yet unforeseen missions and breakthrough science observations. Our KISS study provided an essential venue for the consideration of these challenges and goals. Additional work and future steps are needed to realize the potential of resilient systems—this study provided the necessary catalyst to begin this process

Enabling Astronaut Self-Scheduling using a Robust Advanced Modelling and Scheduling system: an assessment during a Mars analogue mission

Human long duration exploration missions (LDEMs) raise a number of technological challenges. This paper addresses the question of the crew autonomy: as the distances increase, the communication delays and constraints tend to prevent the astronauts from being monitored and supported by a real time ground control. Eventually, future planetary missions will necessarily require a form of astronaut self-scheduling. We study the usage of a computer decision-support tool by a crew of analog astronauts, during a Mars simulation mission conducted at the Mars Desert Research Station (MDRS, Mars Society) in Utah. The proposed tool, called Romie, belongs to the new category of Robust Advanced Modelling and Scheduling (RAMS) systems. It allows the crew members (i) to visually model their scientific objectives and constraints, (ii) to compute near-optimal operational schedules while taking uncertainty into account, (iii) to monitor the execution of past and current activities, and (iv) to modify scientific objectives/constraints w.r.t. unforeseen events and opportunistic science. In this study, we empirically measure how the astronauts, who are novice planners, perform at using such a tool when self-scheduling under the realistic assumptions of a simulated Martian planetary habitat