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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

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

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 NTRSDate not supplied

Dynamics of A Vibration Isolation System Including Inertia of the Human Body

Using an exercise device in a spacecraft is liable to transmit an unacceptable amount of vibration to that vehicle. This is commonly mitigated by a Vibration Isolation System (VIS), whose dynamics must be analyzed to confirm that the oscillatory forces on the spacecraft remain within allowed range, both from a structural and microgravity perspective (see, e.g., [1]). When modeling a VIS for countermeasures devices, one common approach is to record forces and moments applied on the floor while exercising, and then drive the VIS simulation by applying these recorded loads to the exercise platform part of the VIS mechanical model. This approach misses the fact that when exercising on a moving platform, the force and moment on it will differ from that on the stationary floor due to inertial effects involving the human body. For example, standing up on a platform as it gives under the subject’s feet reduces the foot force on it, and such inertial effects are especially complex for rotational motion. In principle, one could model both the motion of the human body and dynamics of the VIS mechanism in a single combined simulation, e.g., employing a tool such as the commonly used biomechanical simulation OpenSim. Here, the joints of the human body would be driven kinematically along prescribed exercise trajectories while the dynamics engine computed the response of the VIS degrees of freedom. However, mechanism designers and biomechanics experts have their own established tools, making it very desirable to have a way of decoupling the biomechanics from the VIS modeling, simulation, and analyses. We have derived a set of equations that rigorously accomplishes this goal, and have implemented them as an interface function that provides an alternative driving mechanism for an existing force-based VIS analysis simulation. When enabled, the simulated human/VIS system dynamics is now driven by this function, instead of the recorded force methodology described above. The function is designed to accept input from a data file containing the required time-stamped human motion and inertia terms corresponding to the specific exercise in question. This data file is generated by an OpenSim plugin written for that purpose. The existing VIS analytical simulation is developed using NASA’s Trick Simulation Environment [2], as well as its MBDyn multibody dynamics [3] package. The presentation will provide a detailed overview of the mathematical formulation, assumptions, plugin implementation, software interfaces, and results for a sample set of representative exercises. The results from this work aim to better inform VIS design efforts, as well as countermeasure device/protocol designs with respect to exercise type and frequency effects on vehicle structural and microgravity restrictions.

Countermeasures↗

NASA NTRS1991

Classification of posture maintenance data with fuzzy clustering algorithms

Sensory inputs from the visual, vestibular, and proprioreceptive systems are integrated by the central nervous system to maintain postural equilibrium. Sustained exposure to microgravity causes neurosensory adaptation during spaceflight, which results in decreased postural stability until readaptation occurs upon return to the terrestrial environment. Data which simulate sensory inputs under various conditions were collected in conjunction with JSC postural control studies using a Tilt-Translation Device (TTD). The University of West Florida proposed applying the Fuzzy C-Means Clustering (FCM) Algorithms to this data with a view towards identifying various states and stages. Data supplied by NASA/JSC were submitted to the FCM algorithms in an attempt to identify and characterize cluster substructure in a mixed ensemble of pre- and post-adaptational TTD data. Following several unsuccessful trials with FCM using a full 11 dimensional data set, a set of two channels (features) were found to enable FCM to separate pre- from post-adaptational TTD data. The main conclusions are that: (1) FCM seems able to separate pre- from post-TTD subject no. 2 on the one trial that was used, but only in certain subintervals of time; and (2) Channels 2 (right rear transducer force) and 8 (hip sway bar) contain better discrimination information than other supersets and combinations of the data that were tried so far.

Bezdek, James C.↗

NASA NTRS1992

Classification of posture maintenance data with fuzzy clustering algorithms

Bezdek, James C.↗

NASA NTRS2015

Data Recipes: Toward Creating How-To Knowledge Base for Earth Science Data

Both the diversity and volume of Earth science data from satellites and numerical models are growing dramatically, due to an increasing population of measured physical parameters, and also an increasing variety of spatial and temporal resolutions for many data products. To further complicate matters, Earth science data delivered to data archive centers are commonly found in different formats and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and or formats. The data recipe project at Goddard Earth Science Data and Information Services Center (GES DISC) was initiated in late 2012 for enhancing user support. A data recipe is a How-To online explanatory document, with step-by-step instructions and examples of accessing and working with real data (http:disc.sci.gsfc.nasa.govrecipes). The current suite of recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant, even though the data recipe topics are still limited. An Earth Science Data System Working Group (ESDSWG) for data recipes was established in the spring of 2014, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group is working on an inventory and analysis of existing data recipes and tutorials, and will provide guidelines and recommendation for writing and grouping data recipes, and for cross linking recipes to data products. This presentation gives an overview of the data recipe activites at GES DISC and ESDSWG. We are seeking requirements and input from a broader data user community to establish a strong knowledge base for Earth science data research and application implementations.

data recipe↗

NASA NTRS2021

Optimal Input Design for Aircraft Stability and Control Flight Testing

Flight testing to characterize aircraft stability and control is a complex and expensive task that involves restrictive practical constraints. Methods are examined for optimizing the inputs applied to aircraft controls during flight test maneuvers to produce informative flight data. Theory underpinning optimal input design for stability and control flight testing is explained. The merits and limitations of optimal inputs are discussed, along with optimization approaches and practical considerations involved in applying optimal inputs in a real flight test environment. Simulated and flight test case studies of optimal multiple-input design for aircraft stability and control flight testing are presented and discussed.

optimal input design↗

NASA NTRS2000

Improvements To Progressive Wave Tube Performance Through Closed-Loop Control

This report documents recent improvements to the acoustic and thermal control systems of the Thermal Acoustic Fatigue Apparatus (TAFA), a progressive wave tube test facility at the NASA Langley Research Center, Hampton, Virginia. A brief summary of past acoustic performance is given first to serve as a basis for comparison with the new performance data using a multiple-input, closed-loop, narrow-band controller. Performance data in the form of test section acoustic power spectral densities and coherence are presented in three of six facility configurations for a variety of input spectra. Tested spectra include uniform, two cases of pink noise, three cases of narrow-band random, a simulated launch payload bay environment for an expendable launch vehicle, and a simulated external acoustic load for the aft section of a reusable launch vehicle. In addition, a new closed-loop temperature controller and thermocouple data acquisition system are described.

Rizzi, Stephen A.↗

NASA NTRS1990

Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.

Steffen, K.↗

NASA NTRS2002

Software for Preprocessing Data From Rocket-Engine Tests

Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC "E" test-stand complex and utilize the SSC file format. The programs are the following: 1) Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel; 2) QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot (a free graphing program written by Rick Paris); and 3) EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PVWAVE based plotting software.

Cheng, Chiu-Fu↗

NASA NTRS2004

Software for Preprocessing Data from Rocket-Engine Tests

Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot (a free graphing program written by Rick Paris). EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PV-WAVE based plotting software.

Cheng, Chiu-Fu↗

NASA NTRS2006

Process evaluation distributed system

The distributed system includes a database server, an administration module, a process evaluation module, and a data display module. The administration module is in communication with the database server for providing observation criteria information to the database server. The process evaluation module is in communication with the database server for obtaining the observation criteria information from the database server and collecting process data based on the observation criteria information. The process evaluation module utilizes a personal digital assistant (PDA). A data display module in communication with the database server, including a website for viewing collected process data in a desired metrics form, the data display module also for providing desired editing and modification of the collected process data. The connectivity established by the database server to the administration module, the process evaluation module, and the data display module, minimizes the requirement for manual input of the collected process data.

Moffatt, Christopher L.↗

NASA NTRS2003

Software for Preprocessing Data From Rocket-Engine Tests

Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: (1) Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. (2) QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot. (3) EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PVWAVE based plotting software.

Cheng, Chiu-Fu↗

NASA NTRS2016

Graphical Visualization of Human Exploration Capabilities

NASA's pioneering space strategy will require advanced capabilities to expand the boundaries of human exploration on the Journey to Mars (J2M). The Evolvable Mars Campaign (EMC) architecture serves as a framework to identify critical capabilities that need to be developed and tested in order to enable a range of human exploration destinations and missions. Agency-wide System Maturation Teams (SMT) are responsible for the maturation of these critical exploration capabilities and help formulate, guide and resolve performance gaps associated with the EMC-identified capabilities. Systems Capability Organization Reporting Engine boards (SCOREboards) were developed to integrate the SMT data sets into cohesive human exploration capability stories that can be used to promote dialog and communicate NASA's exploration investments. Each SCOREboard provides a graphical visualization of SMT capability development needs that enable exploration missions, and presents a comprehensive overview of data that outlines a roadmap of system maturation needs critical for the J2M. SCOREboards are generated by a computer program that extracts data from a main repository, sorts the data based on a tiered data reduction structure, and then plots the data according to specified user inputs. The ability to sort and plot varying data categories provides the flexibility to present specific SCOREboard capability roadmaps based on customer requests. This paper presents the development of the SCOREboard computer program and shows multiple complementary, yet different datasets through a unified format designed to facilitate comparison between datasets. Example SCOREboard capability roadmaps are presented followed by a discussion of how the roadmaps are used to: 1) communicate capability developments and readiness of systems for future missions, and 2) influence the definition of NASA's human exploration investment portfolio through capability-driven processes. The paper concludes with a description of planned future work to modify the computer program to include additional data and of alternate capability roadmap formats currently under consideration.

Rodgers, Erica M.↗

NASA NTRS2001

Closed-Loop Control for Sonic Fatigue Testing Systems

This article documents recent improvements to the acoustic control system of the Thermal Acoustic Fatigue Apparatus (TAFA), a progressive wave tube test facility at the NASA Langley Research Center, Hampton, VA. A brief summary of past acoustic performance is first given to serve as a basis of comparison with the new performance data using a multiple-input, closed-loop, narrow-band controller. Performance data in the form of test section acoustic power spectral densities and coherence are presented for a variety of input spectra including uniform, band-limited random and an expendable launch vehicle payload bay environment.

Rizzi, Stephen A.↗

NASA NTRS2002

Monitoring Global Precipitation Using Satellite Observations: Status and Future

The current status of monitoring global precipitation amounts and patterns is described using data sets from the Global Precipitation Climatology Project (GPCP) of the World Climate Research Program (WCRP) and from recent research satellites, especially the Tropical Rainfall Measuring Mission (TRMM). The GPCP monthly (and pentad) data set is a 23-year, globally complete precipitation analysis that is used to explore global and regional variations and trends. The data set is a blend of data mainly from low-orbit microwave satellites and geosynchronous infrared satellites, with additional input from satellite sounder data, Outgoing Longwave Radiation (OLR) data and raingauges. The monthly GPCP data set shows no significant global trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 23-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 23-year period. This apparent trend may be a short-term variation, but also might be related to the increase with time of extreme precipitation events reported elsewhere. Patterns of precipitation variation related to ENSO and other phenomena are shown with clear signals extending from the Tropics into middle and high latitudes of both hemispheres. Also shown, as an example of higher time resolution data is the GPCP daily analysis, which is available for the last six years. A second focus of the talk is on TRMM precipitation data and how these newer data sets incorporating information from the first space-borne meteorological radar compare with the established GPCP data sets.

Adler, Robert F.↗

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