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Noah Andersen

Publications and source records attributed to Noah Andersen.

Predicting Operational Performance of xEMU Boot at Lunar South Pole Temperatures using Thermal Desktop ®

The spacesuit boots that will be used on Artemis lunar south pole surface missions will be exposed to extremely cold temperatures (down to ~50 K). To assess the performance of the government’s Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these permanently shadowed regions, testing was performed at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU CITADEL TVAC test. Expected thermal conductances within the boot and between the boot and environment were calculated from test data, which was then used as an initial guess for conductances within a Thermal Desktop (TD) model. Correlation of the TD model using the internal SOLVER feature was performed across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. Operational performance at the lunar south pole was then predicted using results from the correlated model. While the predictions provide evidence for acceptable performance of the boots at the 100K environment test point, there is still substantial uncertainty in performance, especially at the 48K test point. This uncertainty is due in part to testing limitations such as contacting the foot to a hard metal plate rather than granular regolith, and model limitations such as the lack of a realistic foot model. These limitations and their impacts are addressed in detail in this paper. The results of this test series and model correlation underscore the importance of additional improved testing and modeling for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

Spacesuit↗

Parametric-Based Heat Rejection Trade Study for Lunar and Martian Surface Operations

Establishing and maintaining a sustained presence on the lunar and/or Martian surfaces will require a diverse portfolio of surface elements (e.g., habitation, mobility, power generation, etc.). Many of these systems generate excess heat that must be rejected across a wide range of magnitudes, temperatures, and duty cycles and under variable environmental conditions. To identify the most promising heat rejection approaches for this diverse portfolio, a heat rejection trade study was conducted to evaluate the performance of different technology approaches across a spectrum of surface environments and heat-load requirements. The trade study consisted of three stages: (1) development of a parametric-based modeling framework, (2) creation of a database of heat rejection technologies, surface elements, and environmental conditions for the Moon and Mars, and (3) execution of a quantitative analysis of various heat rejection technologies across different operating conditions and surface elements. The modeling framework is developed in Python and Excel to prioritize small model size and hence low computational cost to enable large parametric sweeps while avoiding the reliance on proprietary software. Individual heat rejection processes are represented as simple Excel models, and a centralized Python script interfaces with the models to coordinate the parametric study. These simple sizing models were developed to take heat load requirements and environmental parameters as inputs and compute mass, power, and volume as outputs. Rather than assess each heat rejection technology separately for each surface element, a unified parametric space was developed to evaluate all technologies across all elements. This parametric space includes factors related to heat load (e.g., magnitude or temperature) and environment (e.g., surface temperature, sky temperature, solar flux). This effort generated a database containing information on over 60 heat rejection technologies and 30 surface elements. For each surface element, the expected heat rejection requirements were documented and analyzed to determine the most common needs shared across all elements. Environmental conditions at various lunar and Martian latitudes were also established for worst-case hot and worst-case cold scenarios. High-fidelity heat rejection models are currently under development. Preliminary trades between heat rejection technologies including radiators, venting technologies, convective coolers, and more have been conducted to identify promising options. This presentation will summarize the preliminary trade results and provide an overview and discussion of the expected heat loads and thermal environments for sustained surface operations on the Moon and Mars.

Heat Rejection↗

xEMU Spacesuit Boot Lunar South Pole Thermal Vacuum Testing

The Exploration Extravehicular Mobility Unit (xEMU) spacesuit lunar boot was evaluated in the Jet Propulsion Lab (JPL) CITADEL thermal vacuum chamber at lunar South Pole conditions. The JPL CITADEL chamber provides a radiation environment and contact plate temperature of 48K, simulating the temperature of a lunar Permanently Shadowed Region (PSR) at the South Pole of the Moon. The main objectives of the test series are: to evaluate the risk lunar PSRs pose to advanced spacesuit boots, validate the xEMU lunar boot thermal model, and to develop a test methodology to evaluate lunar spacesuit boots. To simulate the thermal effects of a crewmember’s foot inside the boot, a thermal manikin foot was developed to inject heat into the spacesuit boot. Thermal data was collected through a variety of sensors including thermocouples, thermistors, heat flux sensors, and infrared cameras. A test matrix was developed to investigate the variables of foot contact force, simulated skin temperature, external contact plate temperature, and ventilation flowrate. The JPL CITADEL chamber includes a loadlock (airlock) that afforded the ability to simulate the transition of the boot from a thermally neutral IVA condition to a cold EVA condition within seconds. This paper will document the test design, test objectives, success criteria, test support equipment, spacesuit boot to chamber interfaces, and configuration of the test article. Additionally, this paper will document the high-level results of the testing. More detailed test results will be presented in a different paper.

Ben Swartout↗

Model Correlation and Thermal Analysis of xEMU Boot at Lunar South Pole Temperatures

The National Aeronautics and Space Administration (NASA) Artemis program plans to send astronauts to the lunar south pole, a region of the moon that is colder than previous lunar missions and low earth orbit operations. The spacesuit boots that will be used on these missions will be directly impacted by these extremely cold temperatures (down to ~50 K). To assess the performance of the Exploration Extravehicular Mobility Unit (xEMU) lunar boot in these extreme temperatures, the boot was tested at the Jet Propulsion Lab (JPL) in the Cryogenic Ice Transfer, Acquisition Development, and Excavation Laboratory (CITADEL) thermal vacuum (TVAC) chamber. This data was used to correlate thermal models to predict operational performance of the boots on the lunar south pole. This paper documents the data analysis, thermal boot model correlation, and operational predictions conducted using data from the xEMU TVAC test. Data from the test series was used to determine expected thermal conductances within the boot and between the boot and environment. These conductances were used to correlate a Thermal Desktop model of the xEMU boot across 10 different test points which varied external temperature, internal boot ventilation flowrate, and contact pressure. The correlated model was then used to predict operational performance in the lunar south pole. While the predictions indicate promising evidence for performance of the boots at the 100K test point, there is still substantial uncertainty in performance, particularly at the 48K test point. The results of this test series and model correlation stress the importance of improved testing for characterizing the expected thermal resistance between the outside of the boot and the lunar surface.

xEMU↗

xEMU Spacesuit Boot Lunar South Pole Thermal Vacuum Testing

The Exploration Extravehicular Mobility Unit (xEMU) spacesuit lunar boot was evaluated in the Jet Propulsion Lab (JPL) CITADEL thermal vacuum chamber at lunar South Pole conditions. The JPL CITADEL chamber provides a radiation environment and contact plate temperature of 48K, simulating the temperature of a lunar Permanently Shadowed Region (PSR) at the South Pole of the Moon. The main objectives of the test series were: to evaluate the risk lunar PSRs pose to advanced spacesuit boots, validate the xEMU lunar boot thermal model, and develop a test methodology to evaluate lunar spacesuit boots. To simulate the thermal effects of a crewmember’s foot inside the boot, a thermal manikin foot was developed to inject heat into the spacesuit boot. Thermal data was collected through a variety of sensors including thermocouples, thermistors, heat flux sensors, and infrared cameras. A test matrix was developed to investigate the variables of foot contact force, simulated skin temperature, external contact plate temperature, and ventilation flowrate. The JPL CITADEL chamber includes a loadlock (airlock) that afforded the ability to simulate the transition of the boot from a thermally neutral IVA condition to a cold EVA condition within seconds. This paper will document the test design, test objectives, success criteria, test support equipment, spacesuit boot to chamber interfaces, and configuration of the test article. Additionally, this paper will document the high-level results of the testing. More detailed test results will be presented in a different paper.

TVAC↗

System Engineering & Integration (SE&I) In-Situ Resource Utilization (ISRU) Modeling and Analysis (SIMA)

NASA developed a flexible system modeling framework of integrated ISRU and ISRU related subsystem models: MAIT (Mission Analysis & Integration Tool) that enables point solutions, optimization, and/or parametric studies at the system level to predict mission architecture mass, power, and volume and provides accessible consolidated database that categorizes specific ISRU and ISRU related subsystem variables common between NASA & industry. Directly and indirectly addresses multiple STMD shortfalls: - ISRU-581 - ‘ISRU System Modeling’: Establish a modular end-to-end ISRU system modeling & analysis capability by leveraging and evolving prior, on-going, and future investments - More than an ISRU system modeling tool, MAIT integrates power, excavation, Environmental Control & Life Support System (ECLSS), Cryogenic Fluid Management (CFM) liquification, & compares surface ops & environments, to assist in the closure of other related ISRU shortfalls Adheres to governing NASA procedures for Models & Simulations (NASA-HDBK-7009) & AIAA standards for Mass Properties Control for Space Systems.

Modeling↗

Comparative Analysis for EMU Fleet Latent Loading Characterization in Support of US EVA 80 Failure

During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. One of the primary mechanisms that can cause water in the helmet of an EMU is integrated performance induced sublimator carryover. The sublimator is a heat exchanger that removes heat and humidity from the ventilation loop. Water vapor is condensed from the gas and removed by slurper holes in the sublimator. Sublimator carryover is caused by the inability of the EMU sublimator to remove all of the condensed water vapor, resulting in liquid water entering the helmet. To determine if sublimator carryover was a likely cause of the US EVA 80 failure, a comparative analysis of numerous historical EVAs was conducted to calculate the total latent load (total water vapor generated by the crewmember) for numerous historical EVAs and ground tests using the Systems Improved Numerical Differencing Analyzer EMU (SINDA EMU) model. The analysis showed that US EVA 80 was associated with a comparatively high latent load when compared to other EVAs that did not present water in the helmet. Further, this analysis showed that other historical EVAs which had visible water in the helmet were also associated with higher latent loads. This analysis provides evidence that the likely cause of the US EVA 80 water in the helmet event was not the failure of an individual component, but rather sublimator carryover caused by excessive production of water vapor by the crewmember. The evidence from this analysis agrees with results from the Test, Teardown, and Evaluation (TT&E) of the EMU which did not show any failure of individual components of the EMU that would lead to water in the helmet.

Noah Andersen↗

Extravehicular Mobility Unit System-Level Model (SINDA EMU) Usage for Operational Mitigations in Support of US EVA 80

During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. Through a comparative analysis and Test, Teardown, and Evaluation (TT&E) of this EMU, the most likely cause of the US EVA 80 water failure was determined to be sublimator carryover caused by a comparatively high latent load (water vapor production by the crewmember). High latent load can be reduced by the crewmember adjusting the thermal control valve (TCV) setting on the EMU to prevent the onset of significant sweating. To reduce the risk of high latent load leading to water in the helmet, a potential warning system was developed using the Systems Improved Numerical Differencing Analyzer EMU model (SINDA EMU). The goal of this warning system is to alert the crewmember when they are producing a high latent load and recommend adjustment of the TCV to increase cooling. This warning system was designed to ensure high risk conditions are avoided while simultaneously preventing a system that warns the crewmember too frequently. Theoretical tests of the warning system through modeling calculated that if the warning system were used during US EVA 80, the total latent load could have been reduced by up to 33% which would have significantly reduced the risk of water in the helmet. This analysis also investigated the effectiveness of the warning system on EVAs that occurred after US EVA 80.

Noah Andersen↗

Integrated Computational Fluid Dynamics and Thermal Desktop Thermal Modeling for Assessment of the EMU in Support of ISS EVA 80

Following the reports of water accumulation in the Extravehicular Mobility Unit (EMU) helmet during the ISS US EVA-80, various efforts for mitigation and further understanding of this phenomenon have been undertaken with the goal of prevention and to ensure crew safety in future EVAs. In support of this goal, a combination of Thermal Desktop thermal modeling and Computational Fluid Dynamics (CFD) has been performed in order to characterize the performance of the EMU components, specifically those within the ventilation/cooling water loops. This modeling effort evaluates the dry/wet gas pressure drop and flow distribution through gas and liquid flow paths using CFD, as well as a two-phase flow assessment of condensation production and water separation/removal performance using an integrated Thermal Desktop model of important EMU ventilation loop components. The models assess this overall thermal-fluid performance in comparison with previous existing models, design points, and historical EVA data using their inputs.

EVA 80↗

Integrated In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) connects individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. MATLAB was favorable to use as the main software integration tool due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of technologies, including but not limited to, the water processing Lunar Auger Dryer for ISRU (LADI) system and an oxygen extraction carbothermal reduction process. With individual models consolidated, the MAIT tool generated over 60,000 cases during its parametric sweeps; these system iterations produced valuable insight into the optimal LADI geometry for minimizing heater energy demands, estimating carbothermal reactor and radiator mass relationships, and calculated the power dynamics of the electrolysis unit. Efforts to update the MAIT tool are ongoing to accommodate and scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy, and increase the MAIT software capability to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 60,000 cases during its parametric sweeps; these system iterations produced valuable insight into the optimal LADI geometry for minimizing energy demands, estimating carbothermal reactor and radiator mass relationships, and calculated the power dynamics of the electrolysis unit. Advanced efforts with advanced models will include examining multiple production targets to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy, and increase the MAIT software capability to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis mission, the development of an exploration portable life support system (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the design, verification, and testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the exploration pressure garment system (xPGS) and simulating five extravehicular activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. This data was compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was updated and became the capital program in the Systems Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) project. Prior work was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 5,000 cases during its first round of parametric sweeps on the water processing architecture at multiple production targets; the system analysis produced valuable insight into the optimal LADI geometry that minimized energy demands, estimated effects to cold trap size and radiator requirements, and calculated the power dynamics of the electrolysis unit and liquid oxygen storage volume. Additional efforts are being made to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy and increase the MAIT software capability. Work is ongoing to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

Comparison of Exploration Portable Life Support Subsystem (xPLSS) Thermal Modeling to Thermal Vacuum Testing

To support NASA’s goal to return to the Moon through the Artemis Mission, the development of an Exploration Portable Life Support Subsystem (xPLSS) has been conducted at Johnson Space Center (JSC). As part of this development process, a large system level thermal/fluid model of the xPLSS was developed using Thermal Desktop and an in-house human model (METMAN). The xPLSS model was used throughout the design process to predict the performance and temperature of nearly all components within the xPLSS. In the fall of 2023, the Design, Verification, and Testing (DVT) unit of the xPLSS was tested in a thermal vacuum (TVAC) chamber at JSC. This testing consisted of combining the xPLSS with an upper torso of the Exploration Pressure Garment System (xPGS) and simulating five Extravehicular Activities (EVAs) in extreme thermal conditions (two cold EVAs and three hot EVAs). The data generated in this test series provided system level data of the xPLSS operating in vacuum and at flight-like environmental temperatures for the first time. These data were compared to results output by the xPLSS system model to assess the accuracy of previous analyses and improve the fidelity and accuracy of the xPLSS system model. The comparison between model and test hardware provides valuable insight that will help improve the design and fidelity of next generation space suits. In general, comparison between test data and model data generally showed slightly un-conservative values (model predicting colder temperatures than test in hot environments, and hotter temperatures than test in cold environments). Model assumptions and test assumptions were assessed to understand potential causes of some of these sources in error. Recommendations to improve the fidelity of the xPLSS model were also made based on the results presented in this paper.

xPLSS↗

In-Situ Resource Utilization Modeling of a Lunar Water Processing System

A key element of achieving a sustained surface presence, such as defined in NASA’s Artemis plan, is In-Situ Resource Utilization (ISRU). ISRU is the practice of using local resources to provide mission consumables that reduce system launch mass requirements, and regenerate resources (chiefly, water and oxygen) for propulsion and life support supporting both Lunar and Martian missions. ISRU systems require multiple complex processes, such as excavation, chemical reactors, and electrolysis subsystems that must operate in harmony to optimize the overall system process from beginning to end. The Mission Analysis and Integration Tool (MAIT) was previously developed with MATLAB in FY22 to connect individual subsystem models into a customized, flexible framework for the purpose of technology downselect, optimization, and end-to-end process planning. Beginning in FY24, MAIT was updated and became the capital program in the Systems Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) project. Prior work was leveraged and evolved using MATLAB/Simulink due to its ability to communicate with a vast number of other programming languages and makes up the backbone of data flow between inputs and outputs to the subsystem models. MAIT initially evaluated a suite of ISRU-related technologies, including the water processing Lunar Auger Dryer for ISRU (LADI) system with integrated upstream excavation and downstream electrolysis subsystems. With individual models consolidated, the MAIT tool generated over 5,000 cases during its first round of parametric sweeps on the water processing architecture at multiple production targets; the system analysis produced valuable insight into the optimal LADI geometry that minimized energy demands, estimated effects to cold trap size and radiator requirements, and calculated the power dynamics of the electrolysis unit and liquid oxygen storage volume. Additional efforts are being made to demonstrate the ability to scale ISRU technologies supporting the Space Technology Mission Directorate’s (STMD) commercialization strategy and increase the MAIT software capability. Work is ongoing to handle a wide array of ISRU system models beyond the Lunar environment, e.g. production of propellant for a Martian lander.

Avery Carlson↗

Evaluating Lunar Water Processing System Model Configurations for Small Scale Oxygen and Hydrogen Production Within JAXA'S ISRU Technology

Introduction: In-Situ Resource Utilization (ISRU) refers to novel methods of extracting and processing local resources for use in life support and propulsion systems, reducing or eliminating the required consumables to be transferred from Earth. Current estimates of water-ice availability embedded in regolith within the Moon’s permanently shadowed regions (PSR’s) range between 1-5% by weight. However, the composition and characteristics of the “wet” regolith is unknown. Alternate ISRU excavation techniques and Concept of Operations (ConOps) must be explored to optimize surface system operations based on these factors. To assess the feasibility of different ISRU subsystem technologies and compare system architecture configurations, an interchangeable system model was generated to incorporate technologies spanning excavation of raw materials to storage of products and determine optimal arrangement of total system processing needs. Total Mass, Volume, and Power (M/V/P) requirements were computed for 168 design iterations of this water processing plant. System Model: In FY24, the System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team developed a lunar water processing system model using the Mission Analysis and Integration Tool (MAIT) to estimate the M/V/P for ISRU subsystems operating under a wide range of Hydrogen (H2) and Oxygen (O2) production targets for the Space Technology Mission Directorate (STMD) [1]. Based on Japan Aerospace Exploration Agency’s (JAXA) surface operational requirements, this system architecture was modified to include the ability to excavate consolidated icy regolith (versus granular ice excavation using Kennedy Space Center’s (KSC) ISRU Pilot Excavator, IPEx) and explore the feasibility of processing the lunar water both inside and outside of the PSR. For the consolidated icy regolith case study, excavation was performed via a mobility transport chassis outfitted with The Regolith Ice Drill for Exploring New Terrain (TRIDENT) for drilling [2] and the Cold Operable Lunar Deployable Arm (COLDArm) [3] for regolith transfer. The system model determines the required rover and payload. M/V/P to handle the required regolith processing rates. The regolith is then sorted and heated to sublimate the ice (via an auger dryer). The exiting high temperature, low pressure vapor is cleaned of volatiles (via cold trap) and electrolyzed to produce H2 and O2. These products are then dried, liquified with 20 K and 90 K cryocoolers (for H2 and O2, respectively), and stored in cylindrical tanks. Study Goals: Due to the different ConOps options of regolith transport to the ridge for processing versus processing it directly inside the PSR, as well as the unknown regolith/water-ice composition, new excavation techniques and their power configurations are being evaluated within a ISRU system architecture for production targets less than NASA’s pilot plant (1 mT). This analysis investigates the feasibility of numerous excavation techniques, power architectures, and logistical operations and determines an optimal system configuration with regards to M/V/P. It aims to investigate which parameters, both locally and globally, have the greatest effect on each subsystem within the plant. This can be used to identify the most critical components of the plant, and guide future decisions on allocating funding for research and development. The results from this study may provide subsystem developers with appropriate interfaces with excavation subsystems and downstream processes, and assessing the overall feasibility of each excavation technique, power architecture, and logistical timeframe. References: [1] Carlson, A. et. al. (2024) ICES. [2] Zacny, K., et. al. (2024) “ASCE Earth and Space”. [3] McCormick, R., et. Al. (2024) IEEE Xplore.

ISRU↗

System Modeling of a Lunar Molten Regolith Electrolysis Plant

Introduction: In-Situ Resource Utilization (ISRU) is the process of extracting local resources to produce commodities for propulsion, life support systems, and off-planet construction rather than transporting consumables from Earth. Molten Regolith Electrolysis (MRE) is a novel ISRU method of extracting oxygen gas and metal alloy from lunar regolith. The MRE process involves placing lunar regolith between two electrodes, through which current is passed, to melt the regolith and reduce the metal oxide constituents by direct electrolysis (e.g. FeO, SiO2, MgO, Al2O3) into oxygen gas and metal alloys. The oxygen is liquefied and used as propellant for landers, while the metals (e.g. Ferro-alloys) are further processed and used in structural building materials and parts manufacturing. A system model was developed that accounted for the major processes of an MRE plant (from excavation of raw materials to storage of products) to assess the feasibility of a lunar MRE plant. The System Engineering and Integration (SE&I) ISRU Modeling and Analysis (SIMA) team utilized its previously documented system sizing model, the Mission Analysis and Integration Tool (MAIT) [1] as framework of the system model. MAIT uses MATLAB/Simulink to integrate subsystem models into a complete system model of the MRE plant. Total mass, volume, and power requirements were computed for numerous iterations of a MRE plant. System Model: Figure 1: MRE Plant Block Diagram The regolith excavation model determines the mass and power needed to excavate sufficient regolith. The preheating auger initiates the regolith heating process before regolith enters the MRE re-actor to reduce the energy required to turn the solid into a molten liquid. The MRE reactor is modeled in COMSOL Multiphysics and based on the research by Dominguez, Sibille, and Schreiner [2, 3, 4]. This preliminary reactor model provides an accurate calculation of thermal equilibrium during electrochemical operation of the reactor system to assess the optimal mass and power required to process the inlet flow of regolith. The model also computes the outlet flowrates of oxygen and molten products. For this analysis, the primary components of the metal alloy considered were iron and silicon. The oxygen is then purified using an Yttrium Stabilized Zirconia (YSZ) electrode, followed by liquefaction using a 90K cryocooler to be stored as liquid oxygen in insulated cylindrical tanks. In future iterations of the system model, the molten metal tapped from the MRE reactor will undergo additional processing or refinement. However, downstream handling of metals is currently a technology gap that is missing a high TRL subsystem model. Therefore, for this analysis, the accumulated metal alloy stream terminates after leaving the MRE reactor. Study Goals: This analysis investigates multiple input variables to the system to determine the sensitivity of a (near) complete plant at full-scale. This preliminary investigation ran parametric sweeps on the MRE reactor geometry, electrical current supply, layers of multi-layer insulation (MLI) on the reactor, size of the electrodes in the oxygen purification model, and regolith composition (based on landing site location). Three production targets of oxygen (1,000, 10,000, and 50,000 kg/yr) were investigated for this analysis. The parametric sweeps conducted in this analysis provide valuable insight into the expected impact of the various model inputs on plant size. This information can be used to identify the most critical components of the plant and guide future decisions on allocating funding for research and development, providing subsystem developers with appropriate interfaces with downstream and upstream processes, and assessing the overall feasibility of MRE when compared to other ISRU plants. References: [1] Carlson, A. et al. (2024) ICES, ICES-2024-53. [2] Dominguez, D.A., and Sibille, L. (2011) AIAA, AIAA-2011-700. [3] Schreiner, S.S. (2015) MIT, Dissertation. [4] Schreiner, S.S. et al. (2016) ASR, 57(7), pp.1585-1603.

ISRU↗