Browsing by Author "Ivey, Daniela"
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Item Design, Build, Test of a CO2 Removal Testbed and Twin Robotically Manipulable Testbed: Sensing Degradation and Performing Maintenance with Robot/Human Teaming(2023 International Conference on Environmental Systems, 2023-07-16) Ivey, Daniela; Barkouki, Tammer; Torralba, Monica; Ulusoy, Ulubilge; Eshima, Samuel; Mohanty, Ayush; Lindbeck, Christopher; Balakirsky, Stephen; Robinson, StephenThe NASA-sponsored “Habitats Optimized for Missions of Exploration” (HOME) Space Technology Research Institute is creating a foundation for smart deep-space habitats that can both sustain human residents and sustain themselves without human residents. A vital element of any human-rated mission is the Environmental Control and Life Support System (ECLSS), composed of multiple subsystems, including an Air Revitalization subsystem that maintains a breathable atmosphere. Tracking performance, identifying performance degradation, predicting remaining useful life of components, and performing maintenance on such a critical system are paramount to creating a safe, habitable environment and are thus key research areas within HOME. This paper outlines the design, build, and test of two new testbeds at UC Davis. The first, ZeoDe (Zeolite Capacity Degradation), is a chemically functional CO2 removal testbed that generates degradation data for prognostics through the introduction of humidity into the system. The introduction of humidity can occur in a space habitat due to leaks or other faults. Humidity build-up within the system leads to CO2 removal capacity degradation of the sorbent. Thus, the study of sorbent degradation is of paramount importance to any zeolite-based CO2 removal system deployed on future spacecraft. The maintenance of such a system is equally important. The second UC Davis testbed, RobInZeN (Robotically Interactive ZeoDe twiN), is a non-functional ECLSS testbed designed for the physical manipulation by robots and humans of its components for task execution. It is modeled after ZeoDe, with additional design changes to allow maintenance practices for both humans and onboard robotic agents. These two testbeds will allow HOME to investigate sensor criticality, degradation physics, detection sequences, and maintenance plans for a degraded ECLSS CO2 removal unit in both autonomous robotic tasks and integrated robot/human teaming scenarios.Item ECLSS Air Revitalization Technology Review 2022: Review of Current Published Units and their Fault Modes(51st International Conference on Environmental Systems, 7/10/2022) Ivey, Daniela; Torralba, Monica; Robinson, StephenNASA, the commercial industry, and international partners are expanding humanity's reach into space, with milestones set for the Lunar Gateway, Artemis, and eventual crewed Mars missions. A key element of any long-term human spaceflight mission is the Environmental Control and Life Support System (ECLSS), composed of multiple subsystems, including an Air Revitalization subsystem that maintains a breathable atmosphere. To match programmatic milestones for deep-space exploration, there is a global push toward developing a next-generation ECLSS. As a result, there are many recent breakthroughs in the research and development of individual ECLSS units. This paper reviews both heritage and recent technologies in Air Revitalization, including US, Japanese, and European technologies for carbon dioxide (CO2) capture and oxygen (O2) generation in spacecraft habitats. Published fault modes are mentioned to facilitate discussions on the repairability and maintainability of potential future life support systems.Item Generating Anomalous Regenerable CO2 Removal System Data for Environmental Control and Life Support System Self-Awareness(51st International Conference on Environmental Systems, 7/10/2022) Eshima, Samuel; Nabity, James; Torralba, Monica; Ivey, Daniela; Robinson, StephenHuman spaceflight beyond Earth orbit will require autonomous deep space habitats that can keep the crew alive when present and keep the habitat "alive" when not. To achieve this goal, the autonomous agent must be both self-aware and self-sufficient. A self-aware Environmental Control and Life Support System (ECLSS) that can perform diagnostics and failure prognostics will be especially crucial towards enabling autonomy. A machine learning-based autonomous agent requires time-dependent data to train, test, and evolve the algorithm. Unfortunately, such data are not available during nominal or anomalous ECLSS operations. The Simulation Testbed for Exploration Vehicle ECLSS (STEVE), a 13X zeolite sorbent bed with CO2-laden simulated cabin atmosphere flow, was developed along with a Simulink and Aspen Adsorption-based computational model of STEVE to produce data of a regenerable CO2 removal system. Experiments and simulations can be conducted at nominal operating conditions and with faults to rapidly generate a diverse set of data. This paper describes the design and development of STEVE and the corresponding computational models. We recommend guidelines for generating data to develop machine learning algorithms for ECLSS self-awareness.