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NASA Talks: Space Shuttle Columbia - Lessons Learned: Columbia Reconstruction, Investigation, Causes and Key Takeaways

On February 25, 2026, this NASA Talk was held regarding the Space Shuttle Columbia (Columbia Launch & Recovery, Columbia Reconstruction, Investigation, Causes & Key Takeaways). Crew & Thermal System Division (EC) partnered with Kennedy Space Center (KSC) and Engineering Directorate (EA) to bring these talks to Johnson Space Center (JSC) centering on what led up to and transpired after the Space Shuttle Columbia accident. Some recovered debris was on exhibit during the talks. NASA Mishap Program Specialist David Erickson presented this talk. Mr. Erickson supports NASA mishap investigations and assists with the development of NASA's new Columbia Learning Center at KSC. This talk was timely and a solemn reminder of the critical importance of diligence, safety, and excellence in our work. EA Director Julie Kramer White welcomed the 400+ center-wide in-person audience, and EC Division Chief Rubik Sheth introduced the speakers. This event was held in the JSC Teague Auditorium, recorded, and executed by the EC in-house STAR Productions team. This record includes an mp4 video with a run time of 32 min. 31 sec.; in color; with sound.

NASA Talks

NASA Talks: Space Shuttle Columbia - Lessons Learned: Columbia Launch and Recovery

On February 25, 2026, this NASA Talk was held regarding the Space Shuttle Columbia (Columbia Launch & Recovery). Crew & Thermal System Division (EC) partnered with Kennedy Space Center (KSC) and Engineering Directorate (EA) to bring this talk to Johnson Space Center (JSC) centering on what led up to and transpired after the Space Shuttle Columbia accident. Some recovered debris was on exhibit during the talk. Retired NASA Columbia Vehicle Manager Scott Thurston presented this talk. Mr. Thurston brings a wealth of knowledge from his mission experience. This talk was timely and a solemn reminder of the critical importance of diligence, safety, and excellence in our work. EA Director Julie Kramer White welcomed the 400+ center-wide in-person audience, and EC Division Chief Rubik Sheth introduced the speakers. This event was held in the JSC Teague Auditorium, recorded, and executed by the EC in-house STAR Productions team. This record includes an mp4 video presentation with a run time of 36 min. 20 sec.; in color; with sound.

NASA Talks

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona

Hidden in Plain Sight: A New Main Belt Population of Aqueously Altered and Thermally Metamorphosed Asteroids

C-complex low albedo asteroids are understood to be related to aqueously altered carbonaceous chondrite meteorites. However, in recent years, a new subgroup of aqueously altered meteorites that have experienced significant heating after their initial interactions with water has been extensively studied. It remains unclear where the aqueously altered and heated parent bodies are located in the asteroid belt. To address this question, we reanalyzed the original dataset that defined the Bus-DeMeo spectral taxonomy of asteroids (DeMeo et al., 2009) using a machine learning approach trained with near-infrared archival meteorite spectra. Results show that ~50% of the C-complex asteroids first identified in the Bus-DeMeo asteroid spectral taxonomy are aqueously altered and heated. Though Ryugu has been shown to also have experienced both of these processes, this is the first evidence of a population of aqueously altered and thermally metamorphosed asteroids in the Main Asteroid Belt. Based on the expected velocity and frequency of impacts in the main belt population, we conclude that impacts are the most likely heat source driving thermal metamorphism we identify. Moreover, these aqueously altered and thermally metamorphosed asteroids may represent a primordial population of low-albedo material that formed in situ in the inner solar system. If these asteroids formed in place, rather than being brought in from the outer solar system during giant planet migration, they would have experienced more frequent and higher velocity impacts, resulting in their distinct mineralogy.

Main Belt asteroids

The NASA Turbulent Heat Flux (THX) Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds-averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS

The NASA Turbulent Heat Flux Experiments: Summary and Lessons Learned

The Turbulent Heat Flux (THX) experiments were conducted at NASA Glenn Research Center (GRC) in order to collect measurements of velocities and temperatures for computational fluid dynamics (CFD) validation of heated flows, with a focus on propulsion system components. The experiments spanned 5 phases; four of which were conducted in the GRC AeroAcoustic Propulsion Laboratory (AAPL) using the Small Hot Jet Flow Rig (SHJAR). In addition to making velocity measurements with Particle Image Velocimetry (PIV), the THX experiments introduced a new Raman-scattering based capability to measure temperatures. Computational studies were also conducted for each of the experimental configurations, in order to provide a baseline of expected CFD results and conduct an assessment of the capability of various CFD approaches for calculating flows where the turbulent transport of heat was important. Two of the collected sets of data were used for American Institute of Aeronautics and Astronautics (AIAA) Propulsion Aerodynamic Workshops (PAWs). The data set from the 5th phase, collected for heated supersonic jets, was also used to construct new validation cases for the NASA Turbulence Model Resource (TMR). This paper provides an overview of the experiments and associated computations for each of the 5 test phases. Key experimental findings are presented. Lessons learned are provided concerning the effect of computational modeling choice on accuracy of predicting turbulent flows where thermal transport is important. Emphasis is placed on comparing Reynolds- averaged Navier-Stokes approaches with large-eddy simulation approaches. The benefits of utilizing a conjugate heat transfer method in conjunction with CFD solver for film cooling is demonstrated.

RANS

PERSIANN-Unet: A Global Deep Learning Framework for Near-Real-Time Precipitation Estimation Using Infrared Data

Access to high-quality, high-resolution, near-real-time precipitation data is essential for hydrological and meteorological research and disaster mitigation. Traditional tools such as rain gauges and radar networks, though effective, have limitations, including sparse coverage in remote areas and high operational costs. Satellite data, with its global coverage and high spatial and temporal resolutions, mitigates limitations in coverage. Satellite precipitation products like Hydro Estimator (HE), Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) utilize both geosynchronous thermal infrared (IR) and passive microwave (PMW) data in their operation. PMW sensors offer detailed atmospheric profiles but suffer from higher latency, whereas IR sensors provide lower latency but only capture cloud-top information. Despite this constraint, IR data remains attractive for low-latency precipitation estimation. Recent advances in deep learning, particularly convolutional neural networks (CNNs), have further improved satellite precipitation retrievals. This study introduces PERSIANN-Unet (PUnet or PERSIANN V3), a quasi-global algorithm covering 60°N–60°S that combines IR data, monthly climatology, and the UNet architecture to produce half-hourly precipitation estimates at 0.04° resolution. The product is evaluated against HE, IMERG, and PDIR-Now for 2022–2023. Results show that PUnet closely matches its training target, IMERG V07 Final, at the global scale, and performance is further evaluated against Stage IV as a reference over CONUS. Training PUnet on IMERG (2016–2021) leverages a high-quality, integrated PMW IR-gauge precipitation product while developing an IR-based framework not reliant on PMW availability. By operating on a single global image, PUnet avoids tile partitioning and blending steps, reducing edge discontinuities, and produces more spatially consistent precipitation fields across hemispheres.

Phu Nguyen

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi

Center for High-Efficiency Electrical Technologies for Aircraft: Phase I Final Report

Under the University Leadership Initiative (ULI), the Center for High-Efficiency for Electrical Technologies (CHEETA) was established to develop and mature early-stage technologies pertaining to hydrogen-electric power and energy systems for aircraft. In particular, integration of these technologies on an aircraft system is envisioned to leverage the high specific energy content of liquid hydrogen (LH2) with fuel cell energy conversion and an electrically driven ducted fan system to provide an ultra-efficient propulsion drivetrain. For this concept, the LH2 system is not just used as an energy storage mechanism, but also as a cryogen to enable highly efficient superconducting electric systems. The end result of this concept is an integrated aircraft system with a quiet, efficient propulsion architecture that produces zero CO2, NOx, SOx, and particulate matter emissions at the vehicle level.

Hydrogen

An Investigation of State-Space Model Fidelity for SSME Data

In previous studies, a variety of unsupervised anomaly detection techniques for anomaly detection were applied to SSME (Space Shuttle Main Engine) data. The observed results indicated that the identification of certain anomalies were specific to the algorithmic method under consideration. This is the reason why one of the follow-on goals of these previous investigations was to build an architecture to support the best capabilities of all algorithms. We appeal to that goal here by investigating a cascade, serial architecture for the best performing and most suitable candidates from previous studies. As a precursor to a formal ROC (Receiver Operating Characteristic) curve analysis for validation of resulting anomaly detection algorithms, our primary focus here is to investigate the model fidelity as measured by variants of the AIC (Akaike Information Criterion) for state-space based models. We show that placing constraints on a state-space model during or after the training of the model introduces a modest level of suboptimality. Furthermore, we compare the fidelity of all candidate models including those embodying the cascade, serial architecture. We make recommendations on the most suitable candidates for application to subsequent anomaly detection studies as measured by AIC-based criteria.

Space Shuttles

Multidisciplinary Design Optimization and Analysis of an Open Rotor Stage: Part 1

Successful design of open rotor propulsors requires effective analysis across multiple disciplines, including aerodynamics, acoustics, and structures. A viable design must not only be efficient but must also produce an acceptable level of noise and meet all static and dynamic structural requirements. For design and optimization, this is especially challenging because running high fidelity analyses is resource-intensive, and optimizing a design may require many thousands of cases to be analyzed. For this reason, the NASA team has applied design methodology that utilizes low-cost aerodynamic methods, machine learning models, and high-fidelity analyses when necessary. This includes standard two-dimensional methods such as throughflow analysis and quasi-3D blade-to-blade CFD, as well as some newly developed methods. Optimization using 3D CFD is necessary to maximize performance, and this is considered as well. All optimizations are carried out subject to structural constraints evaluated using finite element analysis. Doing this accurately requires a robust trunnion design, capable of pitching the blade between cruise and takeoff conditions while maintaining acceptable factor of safety. Hot to cold analysis must also be applied in order to correctly determine the as-manufactured shape. For acoustics, the unsteady pressures on the blade surfaces must be predicted, and this can be done either through full-annulus unsteady CFD or through a nonlinear harmonic method (NLH). NLH can run much faster, allowing some acoustic considerations to be made earlier in the design process. The design process is ongoing, and this presentation will review the current status and planned next steps. This part of the talk will focus on aerodynamic performance and be followed by a talk on structures and acoustics.

Design

Manufacturing Process Development of a Carbon Fiber Reinforced Polymer Composite Shaft for Electric Motors

Electric aircraft applications require electric motors with increased specific power and efficiency. Composite structural components in motors are a potential solution for reducing motor mass, reducing magnetic losses, and limiting undesired conduction paths for fault, electromagnetic interference, or common-mode currents. In this report, manufacturing trials for a high-speed carbon fiber reinforced polymer composite motor shaft are presented. Four prototype shafts were produced using a hybrid biaxial/triaxial fabric that was circumferentially wrapped onto an additively manufactured high-temperature washout mandrel. An additional traditional overbraid approach was also evaluated and shows promise for high-rate, high-performance parts using automated manufacturing. This paper discusses the shaft design, manufacturing methods explored, material selection, the manufacturing trials, and the lessons learned. The results of this manufacturing investigation show feasibility for manufacturing composite shafts for electric motors.

Electric moto shaft

Structural Mechanics and Dynamics Branch 2002 Annual Report

The 2002 annual report of the Structural Mechanics and Dynamics Branch reflects the majority of the work performed by the branch staff during the 2002 calendar year. Its purpose is to give a brief review of the branch s technical accomplishments. The Structural Mechanics and Dynamics Branch develops innovative computational tools, benchmark experimental data, and solutions to long-term barrier problems in the areas of propulsion aeroelasticity, active and passive damping, engine vibration control, rotor dynamics, magnetic suspension, structural mechanics, probabilistics, smart structures, engine system dynamics, and engine containment. Furthermore, the branch is developing a compact, nonpolluting, bearingless electric machine with electric power supplied by fuel cells for future "more electric" aircraft. An ultra-high-power-density machine that can generate projected power densities of 50 hp/lb or more, in comparison to conventional electric machines, which generate usually 0.2 hp/lb, is under development for application to electric drives for propulsive fans or propellers. In the future, propulsion and power systems will need to be lighter, to operate at higher temperatures, and to be more reliable in order to achieve higher performance and economic viability. The Structural Mechanics and Dynamics Branch is working to achieve these complex, challenging goals.

Stefko, George

Ultrasonic Washer–Dryer System for Space Habitats: Design Upgrades and Parabolic Flight Readiness

Clothing makes up nearly 25% of all non-food supplies sent to the International Space Station (ISS). To support sustainable human missions in deep space, NASA’s Life Support and Habitation Systems Focus Area looks to advance technologies to support and improve logistics. Our team is creating a compact ultrasonic clothing washer/dryer system that bypasses traditional limitations and is suitable for space. Thermal drying uses a lot of energy to evaporate water, while our ultrasonic drying method offers a quicker, more efficient alternative. It uses piezoelectric transducers to vibrate textiles at the micron scale, mechanically removing water as cold mist rather than evaporating it. This speeds up drying and reduces energy use, no matter the fabric makeup. This paper details recent upgrades to a full-scale ultrasonic washer–dryer system, readying it for parabolic flight testing. Improvements include an enhanced human–machine interface, better packaging, and optimized performance and control. We also present extensive pre-flight ground tests conducted to ensure reliability and identify potential risks. Collaborating with P&G, we report preliminary cleaning tests using various detergents. These results lay a crucial foundation for the laundry system designed specifically for space. By cutting clothing-related payload and waste by over 97%, this technology supports long-term human exploration missions on the ISS, the Moon, Mars, and beyond.

Laundry

Motor Configuration Selection for A New Technical Challenge to Develop A 5 MW Cryogenic Motor and Drive

Due to aviation’s appreciable and growing share of humanity’s impact on our environment and estimates that CO2emissions only account for 34% of aviation’s total effective radiative forcing [1], there is a need to reach beyond climate goals that focus only on CO2emissions, such as the US Aviation Climate Action Plan’s [3] goal to reach net-zero carbon emissions by 2050.There is motivation to develop technology that pushes toward future large transport aircraft with net zero climate impact that are highly electrified (i.e., have higher power electrical propulsion system components). This paper describes a new, 6-year technical challenge to address this need by developing a 5 MW superconducting motor and cryogenic drive. Section 1 will detail the motivation for this work. Section 2 will describe the technical challenge and the selected specifications for the motor. Section 3 will present the results of a motor configuration trade study and the down selection of one configuration to develop a detailed design for. The technical challenge focuses on the design of a5 MW superconducting motor and cryogenic drive and demonstration of it at a 2+ MW scale to achieve TRL 3. Both fully superconducting (superconducting stator and rotor) and fully cryogenic (superconducting rotor and cryogenic stator) machine configurations will be explored. An emphasis will be placed on addressing the key tall poles for high power superconducting machines. Further details will be included in the full paper. The requirements and goals of the motor will be detailed. The rated speed (2,000 to 3,000 rpm) is defined to be appropriate for directly driving multi-MW fans or propellers. A range of rated speed is permitted because the motor is not designed for a specific aircraft and to provide design flexibility if AC losses in the stator winding are found to be a significant constraint (i.e., a lower speed can be selected to reduce electrical frequency). Relatively conservative requirements for efficiency (99%) and specific power (20 kW/kg) are defined, because TRL advancement and pushing toward flight readiness is emphasized over performance optimization. However, more aggressive efficiency and specific power goals are specified (99.9% and 40 kW/kg). The 3rd section will present the results of a motor configuration trade study. The study started with a qualitative assessment of sixteen motor configurations based on geometric, mechanical, thermal, and electromagnetic criteria. This assessment has been completed with three evaluators scoring all nine criteria. A configuration down select was made by prioritizing the sixteen configurations into four tiers based on each configuration’s total score and consideration of manufacturability, complexity, and support hardware (e.g., rotary vacuum seals, bearings). Configurations in priority A and B will be further evaluated through quantitative assessments, whereas those in priority C will only be further evaluated if time permits and priority D will not be further evaluated. Eight of the sixteen configurations were down selected for quantitative assessment, which will include analytical calculations and low-to moderate-fidelity finite element analysis to produce a preliminary Pareto front of efficiency versus specific power for each configuration. This assessment emphasizes the calculation of AC losses in the stator winding and an exploration of thermal management approaches to remove that heat and maintain cryogenic temperature. The final paper will include a description of each motor configuration that was considered. The quantitative assessments are underway, and an assessment of one configuration is complete for multiple stator conductor options. The remaining assessments are scheduled to be completed by late March so that the final down select to one configuration can be included in this paper.

Net Zero

Ultrasonic Washer–Dryer System for Space Habitats: Design Upgrades and Parabolic Flight Readiness

Clothing makes up nearly 25% of all non-food supplies sent to the International Space Station (ISS). To support sustainable human missions in deep space, NASA’s Life Support and Habitation Systems Focus Area looks to advance technologies to support and improve logistics. Our team is creating a compact ultrasonic clothing washer/dryer system that bypasses traditional limitations and is suitable for space. Thermal drying uses a lot of energy to evaporate water, while our ultrasonic drying method offers a quicker, more efficient alternative. It uses piezoelectric transducers to vibrate textiles at the micron scale, mechanically removing water as cold mist rather than evaporating it. This speeds up drying and reduces energy use, no matter the fabric makeup. This paper details recent upgrades to a full-scale ultrasonic washer–dryer system, readying it for parabolic flight testing. Improvements include an enhanced human–machine interface, better packaging, and optimized performance and control. We also present extensive pre-flight ground tests conducted to ensure reliability and identify potential risks. Collaborating with P&G, we report preliminary cleaning tests using various detergents. These results lay a crucial foundation for the laundry system designed specifically for space. By cutting clothing-related payload and waste by over 97%, this technology supports long-term human exploration missions on the ISS, the Moon, Mars, and beyond.

Ultrasonic

Fatigue Behavior of Laser Powder Bed Fused HAYNES 214: Effects of Different Surface Treatments

In this study, under NASA’s Rapid and Analysis Manufacturing Propulsion Technology (RAMPT) project, effects of different surface post-treatments on surface texture and fatigue behavior of L-PBF Alloy 214 were investigated. Various subtractive SPTs including abrasive flow machining (AFM), machining (M), shot peening (SP), vapormatt (VM), dry electropolishing (DE), chemical milling (CM), chemical-mechanical polishing (CMP), electro chemical (ECP) were applied to study the variations of the surface texture, microstructure and uniaxial fatigue behavior under fully reversed strain-controlled condition at four different strain amplitudes of 0.005, 0.004, 0.003, and 0.0025 mm/mm. The insights gained regarding the relationship between structural and mechanical properties for different SPTs can help establish guidelines for selecting the most effective process to enhance the performance of Laser Powder Bed Fusion (L-PBF) Alloy 214, especially for critical aerospace applications.

Post-Processing

Gateway Element and Payload Materials Outgassing Analyses: HALO, HERMES, and ERSA

Gateway was intended to be humanity’s first space station around the Moon, but its development has been paused as the National Aeronautics and Space Administration (NASA) shifts focus to achieving the United States’ National Space Policy goals. Instead of an orbiting lunar outpost, NASA will now pursue the development of a lunar surface base to support a sustained human presence on the Moon. Before the program’s pause, Gateway’s Induced Environments team worked to ensure payloads and elements (i.e., modules) complied with induced environment requirements. Methods developed and insights gained from this work will have applicability to NASA’s Moon Base and the potential repurposing of Gateway elements and payloads, as well as to induced environments modeling for future space stations. The Gateway program’s induced environment included molecular contamination, electric thruster plume sputter and redeposition, and lunar dust transfer from the Human Landing System (HLS). Primary sources of external molecular contamination included materials outgassing, chemical thruster plume contamination, and vacuum venting. The focus of this paper will be on element- and payload-level materials outgassing analyses performed for Gateway Configuration 1, extending the previously-developed framework for Gateway system-level external molecular contamination modeling. Gateway Configuration 1 consisted of the Power and Propulsion Element (PPE) and the Habitation and Logistics Outpost (HALO). It also included payloads like the European Radiation Sensor Array (ERSA) attached to PPE and the Heliophysics Environmental and Radiation Measurement Experiment Suite (HERMES) attached to HALO. The element- and payload-level analyses to be introduced in this paper for HALO, HERMES, and ERSA enabled high-fidelity descriptions of Gateway’s external molecular contamination environment. Approaches to geometric modeling, meshing, outgassing rate assignment, molecular transport modeling, and analysis methodology will be presented. Element and payload contaminant deposition onto sensitive Gateway receiver surfaces will be summarized and results compared to induced environment requirements. While these results incorporate refinements made over the course of the program, they were not intended to be final. Therefore, modeling assumptions and inputs, potential improvements, and lessons-learned will be documented to inform future work on Moon Base, repurposed elements and payloads, and other space stations.

Gateway