Browsing by Author "Eshima, Samuel"
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Item A Diagnostics Model for Detecting Leak Severity in a Regenerable CO2 Removal System(51st International Conference on Environmental Systems, 7/10/2022) Eshima, Samuel; Nabity, James; Mohany, Ayush; Rozas, Heraldo; Gebraeel, NagiHuman spaceflight beyond Earth orbit will experience high latency in communication and data transmission requiring 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 system able to perform advanced diagnostics and prognostics of possible failures will be crucial towards enabling autonomy. Keeping the crew alive will demand a robust Environmental Control and Life Support System (ECLSS), the health of which can be sensed in real-time (self-aware) and appropriate corrective action taken when something's wrong (self-sufficient). To investigate the feasibility for autonomous control of ECLSS, a case study utilized a machine learning-based diagnostics model for a leaky regenerable CO2 removal system. A zeolite 13X sorbent bed processed simulated cabin atmosphere flows laden with elevated levels of CO2. Experiments were conducted at nominal operating conditions as well as with faults to generate a diverse set of data for training the model. For this paper, a leak was introduced into the CO2 removal bed. We present the experimental data, describe model development for diagnostics, and then discuss its validation and performance. This paper will further pose a design framework for self-aware ECLSS that utilizes machine learning-based algorithms.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 Effects of E-Textile Circuit Components on Signal Quality for Wearable Sensing Applications(51st International Conference on Environmental Systems, 7/10/2022) Golgouneh, Alireza; Holschuh, Brad; Dunne, Lucy; Eshima, SamuelWearable sensors are an emerging area of interest for next-generation spacesuits. Wearable sensors can be used to measure things like physiological signals or forces experienced by the body to obtain information about crew members� wellness, mobility, and body position. Obtaining this information within rigid, constrained environments such as spacesuits can be challenging and labor-intensive. Requirements of comfort and conformability are often at odds with both functional and durability requirements involved with wearing a sensing layer underneath a stiff suit. Using E-textile components such as conductive threads and rubbers instead of typical electrical components can help manage the comfort/durability requirements of a sensing baselayer for space suit applications. However, flexible e-textile components may influence circuit integrity and sensor signal quality, and lead to inaccurate measurement. This study seeks to quantify the effects of various approaches to integrating soft textile-based electrical connections (such as threads and rubbers) on the responses of soft strain sensors. Changes in Signal to Noise Ratio (SNR) for textile-based piezoresistive and capacitive strain sensors were measured under wearability conditions including three e-textile lead configurations, a body curvature condition, and a skin proximity condition. Effects were most significant for the capacitive sensor. All lead types maintained strong SNR for the piezoresistive sensor, and body curvature did not induce significant changes. Skin proximity (and particularly motion artifacts) affected the capacitive sensor response, but effects were smallest when using conductive rubber leads.Item Estimation of System States for Non-Measured Parameters and Integration with a Digital Twin framework to Boost Spacecraft Autonomy and Awareness(51st International Conference on Environmental Systems, 7/10/2022) Torralba, Monica; George, Cory; Robinson, Stephen; Eshima, Samuel; Nabity, JamesAs technologies for human exploration develop to meet the challenges of Lunar and Mars transit and habitation, there is increasing need for technologies that boost vehicle autonomy and awareness with or without human presence. This need for autonomy is driven largely by distance, with two-way communications and resupply lead times exceeding practical limits for a more traditional ground-supported habitat such as the International Space Station. Vehicle autonomy depends on awareness, which relies on sufficient data to inform and predict the state of health of critical systems. This paper will describe a use case for the estimation of states of a carbon dioxide removal system which will mimic the operation of the Simulation Testbed for Exploration Vehicle ECLSS (STEVE), a physical testbed built and operated at the University of Colorado Boulder. Specifically, this paper uses state estimation and physics first principles to estimate the state of parameters inside the testbed�s sorbent bed. Parameters within the bed must be estimated because sensors cannot be introduced internally to the sorbent bed without affecting performance. In addition to generating data about system state of health, vehicle awareness also relies on the availability of sensor data for use by autonomous agents or intelligent modules aboard a spacecraft. This paper proposes a Digital Twin architecture that acts as the framework for storage, transport, and the exchange of data in an autonomous and self-aware vehicle.Item Failure Mode and Effects Analysis for Environmental Control and Life Support System Self-Awareness(2020 International Conference on Environmental Systems, 2020-07-31) Eshima, Samuel; Nabity, JamesAn Environmental Control and Life Support System (ECLSS) meets the environmental and metabolic needs of the crew. However, regenerable ECLSS subsystems have required continuous monitoring and frequent maintenance and repair. For the International Space Station (ISS), ground control monitors these subsystems and directs maintenance and repair operations using replacement components and assemblies sent from Earth via resupply. While this has been sustainable for the ISS, habitats for crewed Moon and Mars missions will need to be less dependent on Earth, requiring the ECLSS to be more self-sustaining. For “self-awareness”, the ECLSS will be expected to detect and diagnose component and system health in real time. To do so, the possible failure modes of each ECLSS subsystem and their effects on operability and performance, habitability and crew health must be known. This then informs the data that must be collected via instruments and sensors, and then synthesized for meaningful projections of ECLSS health. This paper summarizes the findings of a Failure Mode and Effects Analysis (FMEA) conducted for ECLSS subsystems. We use these results to define a framework for implementing self-awareness into the ECLSS architecture.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.Item Simulation Study of Environmental Control and Life Support System Design for Deep Space Exploration(49th International Conference on Environmental Systems, 2019-07-07) Moroshima, Reiji; Moriyama, Eriko; Terao, Takuma; Taguchi, Ayako; Hirosaki, Tomofumi; Eshima, Samuel; Miyajima, HiroyukiWith Japan participating in the Lunar Orbital Platform-Gateway (LOP-G) program, expectations to use the LOP-G as an advanced base to open the door to deep space will increase and further destinations for human spaceflight will likely to be planned. This derives the need to design an environmental control and life support system (ECLSS) that can withstand a long duration mission without resupplies. In particular, an atmosphere revitalization (AR) subsystem and a water recovery and management (WRM) subsystem require highly reliable architectures with higher regeneration rates than ones currently operating in the International Space Station (ISS), as well as an environmental monitoring and control subsystem demands advanced technologies with great efficiency. We have worked for years to develop SICLE (SImulator for Closed Life and Ecology), a software to design and simulate ECLSS models, based on the knowledge of ECLSS simulations at the Closed Ecology Experiment Facilities (CEEF) in Japan. In addition, our recent research and development of ECLSS assemblies including carbon dioxide removal, oxygen generator and water recovery and management with JAXA has contributed largely to the development of SICLE. This paper discusses the results of the ECLSS simulation analyses using SICLE especially on water/air revitalization, temperature, humidity, and CO2 concentration control of the space habitat currently designed for deep space exploration.