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NASA NTRS2023

Quantitative Gas Property Measurements By Filtered Rayleigh Scattering: A Review

Filtered Rayleigh scattering (FRS) is a laser-based diagnostic technique used to nonintrusively quantify various thermodynamic properties of a light-scattering gas. The backbone of FRS is the molecular filtering of Rayleigh scattered light. This concept was initially introduced by the atmospheric LIDAR community before being adopted within the aerospace research field in the early 1990s. Since then, FRS has matured into a versatile quantitative diagnostic tool and has found use in a variety of flow regimes ranging from sub- to supersonic speeds in both reacting and nonreacting environments. This adoption can be attributed to the wealth of information that can be obtained via FRS, including the gas density, pressure, temperature, velocity, species composition, or, in some cases, several of these properties at once. This article reviews the current state of FRS methodology in recovering such gas properties. As knowledge of the fundamentals of Rayleigh scattering and spectral light filtering is crucial to the design of an FRS experiment, we begin by briefly reviewing these areas. Subsequently, we conduct a survey of experimental design strategies, assumptions, and data reduction methods used to measure different gas properties using FRS. We conclude the review with a short discussion on quantification of experimental uncertainty and future trends in FRS.

filtered Rayleigh scattering↗

NASA NTRS2023

Elastic Modulus Testing for TriTruss Struts

The TriTruss is a novel structural module developed by researchers at NASA Langley Research Center (LaRC) that can be used in space to assemble large backing structures for a variety of applications. One such application is the metering truss and primary mirror backbone support structure of an in-space assembled telescope(iSAT). For the iSAT application, the TriTruss will be supporting mirror segments, payloads, and instruments, all of which require the TriTruss to have robust structural integrity. An accurate elastic modulus value is crucial to the finite element analysis(FEA) of the structure. Initial testing indicated that the equivalent elastic modulus provided by the manufacturer and used in the analyses did not accurately predict the behavior of the structure. In this paper, the in-house testing method developed at LaRC to accurately measure the equivalent elastic modulus of the composite struts for use in the analyses is described. A tensile and compressive equivalent elastic modulus was computed from the data obtained in this test. The testing resulted in a tensile equivalent elastic modulus of 24.6 Msi (standard deviation of 0.888 Msi) or 169 GPa (standard deviation of 6.20 GPa) and a compressive equivalent elastic modulus of 22.8 Msi (standard deviation of 0.780 Msi) or 157 GPa(standard deviation of 5.38 GPa) for the single wall thickness struts. For double wall thickness struts, the testing resulted in a tensile equivalent elastic modulus of32.1 Msi (standard deviation of 1.003 Msi) or 221 GPa (standard deviation of 6.91GPa) and a compressive equivalent elastic modulus of 31.9 Msi (standard deviation of 1.123) or 220 GPa (standard deviation of 7.74 GPa).1

TriTruss↗

NASA NTRSDate not supplied

Interactive Framework to Support Open Model-Data Validation Efforts at the CCMC

Validation of models using observation data has been a central activity at the Community Coordinated Modeling Center (CCMC) over more than a decade. The Comprehensive Assessment of Models and Events using Library Tools (CAMEL) framework is a database-driven implementation of the interactive analysis of model-data comparisons that simultaneously provides a view across a multitude of locations and time periods. CAMEL thus extends the single-location or single-trajectory timeseries data comparison capabilities provided by the CCMC online visualization that formed the backbone of initial validation efforts. We demonstrate CAMEL capabilities for an example application to study Neutral Density in the upper atmosphere among comparisons in the heliosphere, the Earth’s radiation belt, magnetosphere, and ionosphere-thermosphere-mesosphere domains.

Lutz Rastaetter↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

Operational Guidance

Procedures and checklists form the backbone of all operations. But a given procedure does not exist in a vacuum. It is part of a large system, and it must fit well within it. For all procedures to fit well, we must take a comprehensive approach to their design. We present such an approach and the results we got when we applied it.

procedures↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

Enhancing Air Traffic Control Planning with Automatic Speech Recognition

The decisions made during the Federal Aviation Administration Air Traffic Control System Command Center's planning teleconferences hold significant sway over the National Airspace System. Held every two hours, these teleconferences convene air traffic managers and stakeholders from across the nation to discuss airspace conditions, weather, and constraints, leading to the formulation and adjustment of traffic management initiatives. Given the critical nature of these decisions, the need for accurate and efficient record-keeping is paramount. In recent years, the application of automatic speech recognition has gained popularity across diverse industries, including aviation. While traditional applications focus on transcribing air traffic control communication, this paper explores a unique application of automatic speech recognition by converting the audio from planning teleconferences into text transcriptions. This innovative approach addresses key challenges in the field, presenting potential benefits for quality assurance, real-time participation, and downstream natural language processing tasks. A notable breakthrough in the machine learning community, namely the transformer neural network architecture, forms the backbone of the proposed solution in this paper. The transformer architecture's role in this research represents a paradigm shift in the efficiency of automatic speech recognition models. By reducing the amount of in-domain training data required, this architecture allows for the fine-tuning of such models like Whisper, originally pretrained on vast English speech datasets. The adaptability of the transformer architecture proves invaluable in capturing the nuances of aviation terminology and specific language used in planning teleconferences. Leveraging the Whisper model as a baseline, our research details the fine-tuning and validation using a dataset comprising 20 hours of meticulously transcribed planning teleconferences. Notably, the baseline pretrained Whisper model exhibited a word error rate of 18.77%. Through the fine-tuning process, the model achieved a substantial improvement, demonstrating an impressive performance with a reduced word error rate of 6.82%. This substantial decrease in WER not only highlights the effectiveness of the transformer architecture but also emphasizes the practical advancements achieved through the application of automatic speech recognition in this specific domain. The utilization of automatic speech recognition in planning teleconferences in this work introduces several novelties. Firstly, the creation of text transcriptions offers a valuable tool for quality assurance and facilitates the efficient review of teleconferences. This is an important aspect of the proposed solution, given the time-sensitive and high-stakes nature of decisions made during these meetings. Furthermore, text-searchable transcriptions provide a streamlined approach for locating and validating critical information, potentially saving hours of manual effort in searching through audio recordings. Moreover, our research identifies a key use case for external facilities and stakeholders. In situations where attendance at the planning teleconference is not feasible, having access to text transcriptions in real-time or shortly after the teleconference ends, proves to be a time-saving and informative resource. This feature enhances collaboration and ensures that stakeholders can stay abreast of important discussions and decisions even in their absence. Despite the efficiency gains facilitated by the transformer architecture in automatic speech recognition technology, it is essential to acknowledge the human factors in data creation. Subject matter experts play a crucial role in accurately transcribing planning teleconferences due to the specificity and complexity of the information discussed. The research dataset, consisting of 20 hours of transcribed planning teleconferences, forms the foundation for fine-tuning and validating the Whisper model. The achieved word error rate of 6.82% demonstrates promising advancements, particularly in recognizing essential aviation terminology within the teleconferences. In conclusion, this paper presents a comprehensive exploration of the application of automatic speech recognition in Air Traffic Control System Command Center planning teleconferences, leveraging the transformer architecture for enhanced efficiency. The novel contributions lie in the improved accessibility of decision-making records, real-time participation opportunities for external stakeholders, and the potential for downstream natural language processing advancements. As the aviation industry continues to evolve, the integration of automatic speech recognition technologies holds the promise of revolutionizing decision-making processes and contributing to the overall safety and efficiency of air traffic management.

ATM↗

NASA NTRS2024

Structural Characterization of a TriTruss Module

The TriTruss is a novel structural module developed by researchers at NASA Langley Research Center (LaRC) that can be used in space to assemble large support structures for a variety of applications. One such application is the metering truss or primary mirror backbone support structure of an In-Space Assembled Telescope (iSAT). For the iSAT application, the TriTruss will be supporting mirror segments, payloads, and instruments, all of which require the TriTruss to have a high stiffness. Structural characterization from testing and analysis is needed to ensure the integrity of the struts that make up a TriTruss module is maintained when subjected to loads representative of the application. The test setup and loads applied to the TriTruss module as well as the analytical methods used to predict the response of the structure under conditions representative of those implemented during testing will be discussed. Also, the results obtained from testing and analysis will be summarized. The goal for the characterization study was to achieve a correlation within 10% between the test data and the analysis. Overall, the correlation varied for the struts with a few struts still having a larger error margin after further studies were conducted to improve the correlation through additional analysis.

Characterization↗

NASA NTRSDate not supplied

Lessons Learned from NASA Goddard Space Flight Center’s Product Development Lead Training Schedule and Cost Development Workshop: Continuous Improvement

This presentation provides a status of the Goddard Space Flight Center (GSFC) effort to increase foundational knowledge of Product Development Leads (PDLs) in schedule and cost management including earned value management (EVM). In 2012, GSFC’s Engineering and Technology Directorate (ETD) implemented an in-house training program to prepare PDLs for managing the technical, cost, schedule, and risk aspects of spaceflight systems to meet their subsystem commitments. Developed in-house, the PDL training program provides an integrated approach to requirements development, risk, schedule and cost management, EVM, performance tracking, and other areas. The program has been held twice yearly since its inception with 531 participating and 451 completing the curriculum. In 2017, the program won the Robert H. Goddard award for Quality and Process Improvement. Program development and evolution were presented in the 2018 NASA Schedule and Cost Symposium. The presentation was so well received that this year we focus on one workshop within the program: Schedule and Cost Development, including EVM. We examine the on-going logic modeling process and how participant and stakeholder data influence workshop content and design, and how the disciplines of schedule and cost contribute to mission success. In this presentation we refresh you on how the approach integrates lecture, small group discussion, estimating, case study exercises, and problem solving. We update you on the data collected from participants and stakeholders, and we discuss how we use these data to measure training effectiveness. Specific topics include: • How the logic model is used as the backbone for continuous program improvement, • How feedback influences implementation and curriculum updates, • How data collection and analysis inform workshop content and development, including participant discoveries of EVM data, • How including the resource analyst and planner in the product development team supports project success.

Lessons Learned↗

NASA NTRS2024

Experimentally Modeling the Emergence of Prebiotically Plausible Phospholipid Vesicles

The prebiotic emergence of protocells is an important part of any origins of life scenario. Although fatty-acid-based vesicles are well studied, how they transitioned to phospholipid vesicles is uncertain. Herein, we show that cyclic-phospholipids formed from fatty acids and glycerol could have played a role by generating a heterogeneous library of vesicles with diverse morphologies and tolerance to a range of metal ions, temperature, and pH. The cyclic phosphate moiety facilitates the natural emergence of vesicles composed of diacyl-phospholipids to become part of the chemical evolutionary process. Competing emergent properties of the various systems (facilitated by additives) could have led to an early preference of the sn-1,2-acyl-substitution on the glycerol backbone coincidental with extant biology. Thus, cyclic-phospholipids could have played a significant role not only in early prebiotic protocellular chemistry but also in facilitating the chemical evolution of protocells from the structurally simple to the functionally more complex.

Sunil Pulletikurti↗

NASA NTRSDate not supplied

Thinking About Procedures

procedures↗

NASA NTRSDate not supplied

Clifford Neural Operators on Atmospheric Data Influenced Partial Differential Equations

Mathematical representations of the atmosphere are key to forecasting and research tasks across Earth science. Numerically solving the underlying partial differential equations(PDEs) of the atmosphere, however, can be difficult and computationally expensive with numerous trade-offs between computing efficiency and accuracy. Utilizing neural net-works to learn approximations of the PDE solutions from the data can help us model complex phenomena more efficiently than traditional numerical schemes. Here, we have applied Clifford algebra-based neural operators for predicting atmospheric variables. Clifford Fourier neural operators are used with two different backbone architectures, ResNet and UNet, on custom data of U10, V10 and surface pressure as well as U500, V500 and Z500. Clifford Fourier neural operators, coupled with ResNet and UNet architectures, are applied to a key reanalysis dataset. Model performance is initially strong, but we observe increasing errors, resulting in the model becoming highly unstable.

Sujit Roy↗

NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

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↗

NASA NTRS2024

Synthesis of Flexible Polyamide Aerogels Cross-Linked with a Tri-Isocyanate

A new series of flexible polyamide (PA) aerogels was synthesized using terephthaloyl chloride (TPC), 2,2′-dimethylbenzidine (DMBZ) and cross-linked with an inexpensive, commercially available tri-isocyanate (Desmodur N3300A) at polymer concentrations of 6–8 wt.% total solids and repeating units, n, from 30 to 60. The cross-linked DMBZ-based polyamide aerogels obtained, after supercritically drying using liquid CO 2 , had shrinkages of 19–27% with densities ranging from 0.12 g/cm 3 to 0.22 g/cm 3 , porosity and surface areas up to 91% and 309 m 2 /g, respectively, and modulus values ranging from 20.6 to 109 MPa. Evidence suggests that a higher flexibility could be achieved using DMBZ in the polyamide backbone with N3300A as a cross-linker, when compared to previously reported TPC-mPDA-BTC PA aerogels, N3300A-polyimide aerogels, and N3300-reinforced silica aerogels.

aerogels↗

NASA NTRSDate not supplied

In-situ Nanoscale Ablation

An understanding of the ablation of carbon-based materials is crucial to modeling the behavior of atmospheric entry spacecrafts equipped with thermal protection systems (TPS).Carbon is the backbone of TPS systems such as PICA (phenolic-impregnated carbon ablator).Therefore in the present work we study ablation of highly oriented pyrolytic graphite (HOPG)in oxygen at temperatures up to 1000°C done within a gas reaction cell housed in a scanning transmission electron microscope (STEM). Observation of the HOPG oxidation on specimens sectioned parallel and normal to the carbon basal planes in the presence of oxygen are reported.Pitting caused by residual oxygen and/or platinum particles from the sectioning process was observed before oxygen gas flow was established at 750°C in the specimen sectioned with the carbon basal planes parallel to the beam direction. Introduction of oxygen flow caused rapid oxidation moving in a uniform front that completely consumed the HOPG in approximately 1.5minutes. The specimen sectioned with the carbon basal planes normal to the beam direction did not show the same pitting phenomenon but exhibited rapid oxidation at 1000°C that proceeded in a uniform front and completed in approximately 1 minute. All specimens tested had a husk resembling the original specimen shape left over after oxidation. It is concluded that this husk is most likely ash impurity from the HOPG or impurities from the sectioning process or E-chip. A residual gas analyszer (RGA) was successfully used to monitor gas flows during the experiments but was yet unsuccessful in monitoring oxidation gas products produced during the experiment.Future studies will optimize the RGA setup in order to maximize the potential for detecting these species. These in-situ studies successfully show how this highly ordered carbon ablates on a nano- and micro-scopic length scale and can be used to provide fundamental understanding of carbon ablation that can be used to design the next-generation of TPS systems.

Nanoscale Ablation↗

NASA NTRS2024

Absolute Intercalibration of Spaceborne Microwave Radiometers

Absolute calibration of spaceborne microwave radiometer observations consists of accurate determination of antenna cold space spillover, cross-polarization contamination, and nonlinearity coefficients of the receivers. We deem the GMI sensor to be the most accurate calibrated spaceborne microwave radiometer due to its unique calibration design features and its carefully planned orbit maneuvers. We demonstrate how to transfer the GMI calibration to other spaceborne radiometers, whose operations have sufficient time overlap with GMI. Specifically, we show results for WindSat and AMSR2. The sensor intercalibration is based on brightness temperature matchups between GMI and the other instruments over both open ocean and rainforest scenes. To assess the calibration accuracy, we compare the intercalibrated brightness temperatures with radiative transfer model calculations. In addition, we provide in situ validation results for wind speed and water vapor retrievals from the intercalibrated sensors. The intercalibration methodology allows for the creation of a multidecadal climate data record from passive microwave satellite observations. Significance Statement Creating a long-term climate data record of satellite observations of ocean winds, water vapor, and other variables requires careful and accurate calibration of the various sensors that are used. In particular, it is important to achieve the best possible consistency between the measurements from all the different instruments. This is a challenging task as the configuration and accuracy of these instruments can differ widely. The purpose of our paper is to demonstrate and validate the basic methodology for performing this intercalibration. The backbone of our method is data observed by a well-calibrated sensor that measures the passive microwave emission from Earth’s surface and atmosphere. We show how to transfer its calibration standard to other sensors.

Katherine Wentz↗

NASA NTRSDate not supplied

Technology Assessment and Modelling of Three Terminal Tandem Solar Cells for In-Space Utilization

NASA seeks a sustained human presence on the lunar surface. High-efficiency and resilient energy systems are critical to supporting habitats, scientific outposts, and lunar surface operations. Photovoltaics have long been the backbone of space power systems, transitioning from silicon solar cells to multi-junction III-V solar cells, which now dominate state-of-the-art (SOA) technology. Multi-junction cells achieve high efficiency by layering semiconductors, each absorbing a specific portion of the solar spectrum. However, efficiency gains are increasingly constrained by device physics and manufacturing complexity. Additionally, higher-order junctions pose challenges for accurate modelling and performance characterization due to difficulties in replicating the AM0 spectrum.

solar cells↗