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At least 667 records · Page 37

HTML 5 Displays for On-Board Flight Systems

During my Internship at NASA in the summer of 2016, I was assigned to a project which dealt with developing a web-server that would display telemetry and other system data using HTML 5, JavaScript, and CSS. By doing this, it would be possible to view the data across a variety of screen sizes, and establish a standard that could be used to simplify communication and software development between NASA and other countries. Utilizing a web- approach allowed us to add in more functionality, as well as make the displays more aesthetically pleasing for the users. When I was assigned to this project my main task was to first establish communication with the current display server. This display server would output data from the on-board systems in XML format. Once communication was established I was then asked to create a dynamic telemetry table web page that would update its header and change as new information came in. After this was completed, certain minor functionalities were added to the table such as a hide column and filter by system option. This was more for the purpose of making the table more useful for the users, as they can now filter and view relevant data. Finally my last task was to create a graphical system display for all the systems on the space craft. This was by far the most challenging part of my internship as finding a JavaScript library that was both free and contained useful functions to assist me in my task was difficult. In the end I was able to use the JointJs library and accomplish the task. With the help of my mentor and the HIVE lab team, we were able to establish stable communication with the display server. We also succeeded in creating a fully dynamic telemetry table and in developing a graphical system display for the advanced modular power system. Working in JSC for this internship has taught me a lot about coding in JavaScript and HTML 5. I was also introduced to the concept of developing software as a team, and exposed to the different types of programs that are used to simplify team coding such as GitLab. While in JSC, I took full advantage of and attended the lectures that were held here on site. I learned a lot about what it is NASA does and about the interesting projects that are conducted here. One of the lectures I attended was about the selection process and the criteria that is used to select future astronauts for flight missions. This truly had an impact on my future plans as it showed me that this path was a viable option for me. After this internship I plan on completing my undergraduate course work and plan to move on for a masters degree. However, during the time in which I will be completing my masters course work, I would like to apply for the NASA pathways graduate program and, if I am accepted, eventually move on to being a full time civil servant. Working in NASA has not only been enjoyable, but full of information and great experiences that have motivated me to seek a full time employment here in the near future.

Silva, Chandika↗

NASA Tech Briefs, August 2003

Topics covered include: Stable, Thermally Conductive Fillers for Bolted Joints; Connecting to Thermocouples with Fewer Lead Wires; Zipper Connectors for Flexible Electronic Circuits; Safety Interlock for Angularly Misdirected Power Tool; Modular, Parallel Pulse-Shaping Filter Architectures; High-Fidelity Piezoelectric Audio Device; Photovoltaic Power Station with Ultracapacitors for Storage; Time Analyzer for Time Synchronization and Monitor of the Deep Space Network; Program for Computing Albedo; Integrated Software for Analyzing Designs of Launch Vehicles; Abstract-Reasoning Software for Coordinating Multiple Agents; Software Searches for Better Spacecraft-Navigation Models; Software for Partly Automated Recognition of Targets; Antistatic Polycarbonate/Copper Oxide Composite; Better VPS Fabrication of Crucibles and Furnace Cartridges; Burn-Resistant, Strong Metal-Matrix Composites; Self-Deployable Spring-Strip Booms; Explosion Welding for Hermetic Containerization; Improved Process for Fabricating Carbon Nanotube Probes; Automated Serial Sectioning for 3D Reconstruction; and Parallel Subconvolution Filtering Architectures.

Source record↗

CARBO - The Carbon Observatory Instrument Suite - The Next Generation of Earth Observing Instruments for Global Monitoring of Carbon Gases

The Carbon Observatory Instrument Suite, or CARBO, consists of four carbon observing instruments sharing a common instrument bus, yet targeted for a particular wavelength band each with a unique science observation. They are: a) Instrument 1, wavelength centered at 756 nm for oxygen and solar-induced chlorophyll fluorescence (SIF) observations, b) Instrument 2, centered at 1629 nm, for carbon dioxide (CO2) and methane (CH4) observation, c) Instrument 3, centered at 2062 nm for carbon dioxide and d) Instrument 4, centered at 2328 for carbon monoxide (CO) and methane. From low-Earth orbit, these instruments have a field-of-view of 10 to 15 degrees, and a spatial resolution of 2 km square. These instruments have a spectral resolving power ranging from ten to twenty thousand, and can monitor columnaverage dry air mole fraction of carbon dioxide (XCO2) at 1.5 ppm, and methane (XCH4) at 7 ppb. These new instruments will advance the use of immersion grating technology in spectrometer instruments in order to reduce the size of the instrument, while improving performance. These compact, capable instruments are envisioned to be compatible with small satellites, yet modular to be configured to address the particular science questions at hand. Here we report on the current status of the instrument design and fabrication, focusing primarily on Instruments 1 and 2. We will describe the key science and engineering requirements and the instrument performance error budget. We will discuss the optical design with particular emphasis on the immersion grating, and the advantages this new technology affords compared to previous instruments. We will also discuss the status of the focal plane array and the detector electronics and housing. Finally, we report on a new approach – developed during this instrument design process - which enables simultaneous measurement of both orthogonal polarization states (S and P) over the field-of-view and optical bandpass. We believe this polarization sensing capability will enable science observations which were previously limited by instrumental and observational degeneracies. In particular: improved sensitivity to all species, better sensitivity to surface polarization effects, better constraints on aerosol scattering parameters, and superior discrimination of the vertical distribution of gases and aerosols.

Bernas, Michael↗

Semi-Automated Diagnosis, Repair, and Rework of Spacecraft Electronics

NASA's Constellation Program for Exploration of the Moon and Mars places human crews in extreme isolation in resource scarce environments. Near Earth, the discontinuation of Space Shuttle flights after 2010 will alter the up- and down-mass capacity for the International Space Station (ISS). NASA is considering new options for logistics support strategies for future missions. Aerospace systems are often composed of replaceable modular blocks that minimize the need for complex service operations in the field. Such a strategy however, implies a robust and responsive logistics infrastructure with relatively low transportation costs. The modular Orbital Replacement Units (ORU) used for ISS requires relatively large blocks of replacement hardware even though the actual failed component may really be three orders of magnitude smaller. The ability to perform in-situ repair of electronics circuits at the component level can dramatically reduce the scale of spares and related logistics cost. This ability also reduces mission risk, increases crew independence and improves the overall supportability of the program. The Component-Level Electronics Assembly Repair (CLEAR) task under the NASA Supportability program was established to demonstrate the practicality of repair by first investigating widely used soldering materials and processes (M&P) performed by modest manual means. The work will result in program guidelines for performing manual repairs along with design guidance for circuit reparability. The next phase of CLEAR recognizes that manual repair has its limitations and some highly integrated devices are extremely difficult to handle and demand semi-automated equipment. Further, electronics repairs require a broad range of diagnostic capability to isolate the faulty components. Finally repairs must pass functional tests to determine that the repairs are successful and the circuit can be returned to service. To prevent equipment demands from exceeding spacecraft volume capacity and skill demands from exceeding crew time and training limits, the CLEAR project is examining options provided by non-real time tele-operations, robotics, and a new generation of diagnostic equipment. This paper outlines a strategy to create an effective repair environment where, with the support of ground based engineers, crewmembers can diagnose, repair and test flight electronics in-situ. This paper also discusses the implications of successful tele-robotic repairs when expanded to rework and reconfiguration of used flight assets for building Constellation infrastructure elements.

Struk, Peter M.↗

Quantum-Well Infrared Photodetector (QWIP) Focal Plane Assembly

A paper describes the Thermal Infrared Sensor (TIRS), a QWIP-based instrument intended to supplement the Operational Land Imager (OLI) for the Landsat Data Continuity Mission (LDCM). The TIRS instrument is a far-infrared imager operating in the pushbroom mode with two IR channels: 10.8 and 12 microns. The focal plane will contain three 640x512 QWIP arrays mounted on a silicon substrate. The silicon substrate is a custom-fabricated carrier board with a single layer of aluminum interconnects. The general fabrication process starts with a 4-in. (approx.10-cm) diameter silicon wafer. The wafer is oxidized, a single substrate contact is etched, and aluminum is deposited, patterned, and alloyed. This technology development is aimed at incorporating three large-format infrared detecting arrays based on GaAs QWIP technology onto a common focal plane with precision alignment of all three arrays. This focal plane must survive the rigors of flight qualification and operate at a temperature of 43 K (-230 C) for five years while orbiting the Earth. The challenges presented include ensuring thermal compatibility among all the components, designing and building a compact, somewhat modular system and ensuring alignment to very tight levels. The multi-array focal plane integrated onto a single silicon substrate is a new application of both QWIP array development and silicon wafer scale integration. The Invar-based assembly has been tested to ensure thermal reliability.

Jhabvala, Murzy↗

EMASS (trademark): An expandable solution for NASA space data storage needs

The data acquisition, distribution, processing, and archiving requirements of NASA and other U.S. Government data centers present significant data management challenges that must be met in the 1990's. The Earth Observing System (EOS) project alone is expected to generate daily data volumes greater than 2 Terabytes (2 x 10(exp 12) Bytes). As the scientific community makes use of this data, their work will result in larger, increasingly complex data sets to be further exploited and managed. The challenge for data storage systems is to satisfy the initial data management requirements with cost effective solutions that provide for planned growth. The expendable architecture of the E-Systems Modular Automated Storage System (EMASS(TM)), a mass storage system which is designed to support NASA's data capture, storage, distribution, and management requirements into the 21st century is described.

Peterson, Anthony L.↗

Gear optimization

The use of formal numerical optimization methods for the design of gears is investigated. To achieve this, computer codes were developed for the analysis of spur gears and spiral bevel gears. These codes calculate the life, dynamic load, bending strength, surface durability, gear weight and size, and various geometric parameters. It is necessary to calculate all such important responses because they all represent competing requirements in the design process. The codes developed here were written in subroutine form and coupled to the COPES/ADS general purpose optimization program. This code allows the user to define the optimization problem at the time of program execution. Typical design variables include face width, number of teeth and diametral pitch. The user is free to choose any calculated response as the design objective to minimize or maximize and may impose lower and upper bounds on any calculated responses. Typical examples include life maximization with limits on dynamic load, stress, weight, etc. or minimization of weight subject to limits on life, dynamic load, etc. The research codes were written in modular form for easy expansion and so that they could be combined to create a multiple reduction optimization capability in future.

Vanderplaats, G. N.↗

Tool for Sizing Analysis of the Advanced Life Support System

Advanced Life Support Sizing Analysis Tool (ALSSAT) is a computer model for sizing and analyzing designs of environmental-control and life support systems (ECLSS) for spacecraft and surface habitats involved in the exploration of Mars and Moon. It performs conceptual designs of advanced life support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water, and process wastes in order to reduce the need of resource resupply. By assuming steady-state operations, ALSSAT is a means of investigating combinations of such subsystems technologies and thereby assisting in determining the most cost-effective technology combination available. In fact, ALSSAT can perform sizing analysis of the ALS subsystems that are operated dynamically or steady in nature. Using the Microsoft Excel spreadsheet software with Visual Basic programming language, ALSSAT has been developed to perform multiple-case trade studies based on the calculated ECLSS mass, volume, power, and Equivalent System Mass, as well as parametric studies by varying the input parameters. ALSSAT s modular format is specifically designed for the ease of future maintenance and upgrades.

Yeh, Hue-Hsie Jannivine↗

Compact Augmented Spark Igniters for Liquid Rocket Engines

The objective of this dissertation is to characterize augmented spark impinging (torch) igniters. Torch igniters inject propellants into a small prechamber where a spark igniter imparts the activation energy to initiate combustion. The flame stabilizes within the prechamber and exits into the main combustion chamber where it ignites the main flow directly or by mixing with a coaxial flow to create a secondary flame. The underlying phenomena that promote reliable ignition are multifaceted and required a broad scope of investigations. Initial efforts focused on spark discharges across an annular geometry. Gaseous propellent projects the electrical arc toward the prechamber, where the arc and the thermal energy is imparted to the surrounding fluid then meets with a combustible mixture. Discharges are parametrically examined against pressure, spark-gap size, and exciter types to emulate transient engine startup. The energy imparted to the flow, approximate velocity, and distance traveled by the exhaust plume are determined. Spark quenching (no energy deposition) and its effects on perceived versus actual measurements are shown. Results outline the prechamber target zone where a combustible mixture is necessary for ignition. Next, three-dimensional, time-accurate, and nonreacting computational fluid dynamics simulations assess effects of geometric and mass flow differences on the size, location, and composition of a combustible mixture. Fluid dynamic phenomena are elucidated. Correlations between nondimensional variables are found. Results are coupled with a conservation-law analysis to produce novel objective functions. Lastly, a full-scale, modular torch igniter is tested. Injector sizes, mixture ratios, and injector momentum ratios are systematically varied to map ignition probability and ignition delay. Results show the importance of local mixture ratios, provide injector momentum ratios guidelines, and demonstrate reliable ignition of core mixture ratios typically outside flammability limits. The deliverable of this project is not a torch igniter or derivative thereof. Instead, this dissertation produces novel objective-functions for igniter design. These equations are functions of variables that may be constrained by engine-level requirements, physics, and experimental results from this work. They provide a foundation for future igniter design and will minimize iterative processes from the design cycle for next-generation ignition hardware.

Torch Igniter↗

An adaptable product for material processing and life science missions

The Experiment Control System II (ECS-II) is designed to make available to the microgravity research community the same tools and mode of automated experimentation that their ground-based counterparts have enjoyed for the last two decades. The design goal was accomplished by combining commercial automation tools familiar to the experimenter community with system control components that interface with the on-orbit platform in a distributed architecture. The architecture insulates the tools necessary for managing a payload. By using commercial software and hardware components whenever possible, development costs were greatly reduced when compared to traditional space development projects. Using commercial-off-the-shelf (COTS) components also improved the usability documentation, and reducing the need for training of the system by providing familiar user interfaces, providing a wealth of readily available documentation, and reducing the need for training on system-specific details. The modularity of the distributed architecture makes it very amenable for modification to different on-orbit experiments requiring robotics-based automation.

Wassick, Gregory↗

Locomotion training of legged robots using hybrid machine learning techniques

In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible patent by NASA, Johnson Space Center. An alternative modular approach is also developed which uses separate controllers for each stage of the running stride. A self-organizing fuzzy-neural controller controls the height, distance and angular momentum of the stride. A CMAC-based controller controls the movement of the leg from the time the foot leaves the ground to the time of landing. Because the leg joints are controlled at each time step during flight, movement is smooth and obstacles can be avoided. Initial results indicate that this approach can yield fast, accurate results.

Simon, William E.↗

Interface shape in Czochralski grown crystals - Effect of conduction and radiation

A sequential modular computational scheme has been proposed for the calculation of temperature profiles in the melt and crystal including the melt-crystal interface shape and the crystal pulling rate for a fixed crystal radius. The heat transfer in the melt is assumed to occur by conduction only. The shape of melt-gas meniscus, described by Laplace-Young equation, is incorporated in the model and its effects on interface shape and pulling rate are examined. Further, the model incorporates the detailed radiation interaction among the various surfaces in the puller using the Gebhart enclosure theory which accounts for both direct and reflected radiation. The effects of various process parameters on the interface shape and the pulling rate have been investigated. The results of this study indicate that the shape of the melt-gas meniscus has a significant effect on the pulling rate and the interface shape in conformity with earlier studies. Further, it is shown that a simple radiation model (Stefan's model) is inadequate to model the radiation heat exchange in the Czochralski puller apparatus and the detailed Gebhart analysis is necessary for accurate calculation of both the temperature profile in the crystal as well as the interface shape.

Srivastava, R. K.↗

EMASS (tm): An expandable solution for NASA space data storage needs

The data acquisition, distribution, processing, and archiving requirements of NASA and other U.S. Government data centers present significant data management challenges that must be met in the 1990's. The Earth Observing System (EOS) project alone is expected to generate daily data volumes greater than 2 Terabytes (2(10)(exp 12) Bytes). As the scientific community makes use of this data their work product will result in larger, increasingly complex data sets to be further exploited and managed. The challenge for data storage systems is to satisfy the initial data management requirements with cost effective solutions that provide for planned growth. This paper describes the expandable architecture of the E-Systems Modular Automated Storage System (EMASS (TM)), a mass storage system which is designed to support NASA's data capture, storage, distribution, and management requirements into the 21st century.

Peterson, Anthony L.↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface. In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha-Ray↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC for Lunar Exploration: Differential Dynamic Microscopy to Spectroscopy to Computer Vision

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

Recent Advances in Soft Matter Characterization Capabilities Developed at NASA GRC

In 1991, famous French scientist Pierre-Gilles de Genes was awarded Nobel prize for his impactful research in soft matter, more specifically polymers. He is defined as the founding father of soft matter. In his Nobel lecture (https://www.nobelprize.org/uploads/2018/06/gennes-lecture.pdf ) he described soft matter aka complex fluids as materials with two primary features – (a) complexity and (b) flexibility. The sub-categories of soft matter (e.g.- granular materials, polymers, foams, colloids etc.) are defined on the basis of Pierre-Gilles de Gennes’ definition. At NASA GRC, we are pushing the boundaries for fundamental study of soft matter on Lunar Surface. With regard to Lunar surface science, we are focusing on developing capabilities pertaining to granular materials and bio-soft/active matter to facilitate future efforts in ISRU and bio-ISRU capabilities. In order to achieve fundamental goals of soft matter research within the limitations of Lunar environment, the scientific capabilities need to be small, flexible, modular, off the shelf and the focus needs to be more on developing an interdisciplinary capability that leverages the recent growth in AI/ML and Computer Vision to augment our understanding of fundamental science. This strategy would allow us to reduce our resource requirement during launch, installation, and occupied real estate footprint on Lunar surface In this talk, we will go over 3 different capabilities that we have developed in house and in close collaboration – (a) Differential Dynamic Microscopy (DDM), (b) Portable In-situ Chemical Spectroscopy (PICS) and (c) Computer Vision Enabled Observation. At very high level, Differential Dynamic Microscopy (DDM) allows us to study the structure-property-process relation (microrheology) of bio-soft/active matter using optical microscope and improved image analysis capabilities. PICS uses AI/ML-based advanced signal deconvolution and analysis technique that can work with existing portable spectroscopy tools to perform materials analysis (e.g.- granular materials and bio-soft/active matter) inspection on the go. Finally, computer vision enabled analysis allows us to use simple camera images for 3D reconstruction of experimental process and tracking of objects of interest in an experiment. We expect that this detailed process will allow us reach a thorough understanding of soft matter in Lunar environment. The capabilities developed by us will help to validate and establish fundamental understanding in Lunar environment. This will, in turn, allow us to guide future space exploration missions and expand the knowledge base of the scientific and engineering communities.

Suman Sinha Ray↗

Some considerations in low-cost image processing on a university main frame: The Penn State (ORSER) experience

The ORSER System as implemented on the Penn State University Computation Center's IBM main frame is an exceptionally useful mechanism for instructing the present and future remote sensing community in the theory and practice of automated analysis of digitized data. From its beginning, the system was used as the hands-on back-bone of a graduate level "Multispectral Remote Sensing" one-term course taught annually in the School of Forest Resources. It was also used at the end of a senior-level undergraduate "Introduction to Remote Sensing" course, and in teaching a variety of short courses, ranging in length from a few days for small groups of remote sensing consultants with specific application interests, to a 2-week course oganized by NASA for regional and urban planners who had little or no previous exposure to remote sensing. Because of its modular construction, the ORSER is suitable for all classes of remote sensing users. Although in a beginning course only 6 to 10 of the programs are generally used, the researcher has a set of about 35 programs available for his analyses.

Turner, B. J.↗