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NASA NTRS2021

Population Viability Analysis (PVA) as a Platform for Predicting Outcomes of Management Options for the Florida Scrub-Jay in Brevard County

The Florida scrub-jay (FSJ) is a species in decline because of extinction debt caused by habitat fragmentation and degradation. Understanding and managing the species and its habitats is challenging due to the complex interactions among the social system, a dynamic mosaic of scrub habitat, and active management. To provide insights into the possible fates of the FSJ populations of mainland, cape, and island sections of Brevard County, we modeled the population dynamics using the Vortex population viability analysis (PVA) software. Vortex is an individual-based simulation that allowed us to include such factors as demographic rates dependent on habitat state, impact of helpers on breeding success, and helper to breeder transition probabilities responding to availability of nearby vacant optimal habitat and vacancies due to the death of breeders. Detailed modeling of the FSJ was possible only because a lot of data about the species and its habitats have been gathered over decades of intensive research. We followed a phased approach to constructing population models that incorporated the best available science and data to address a variety of conservation actions. The first phase focused on constructing a model that incorporates sociobiology and source-sink habitat dynamics. This model allowed us to address some of the most important questions about population size and habitat quality. Once the model framework was in place, we considered the real landscapes and actual local populations, rather than just generic representations of typical FSJ dynamics. After examining the viability of the metapopulations under current conditions, we explored the likely consequences of various management actions that might slow or reverse population declines.

Population Viability Analysis↗
NASA NTRS2017

GEOS Atmospheric Model: Challenges at Exascale

The Goddard Earth Observing System (GEOS) model at NASA's Global Modeling and Assimilation Office (GMAO) is used to simulate the multi-scale variability of the Earth's weather and climate, and is used primarily to assimilate conventional and satellite-based observations for weather forecasting and reanalysis. In addition, assimilations coupled to an ocean model are used for longer-term forecasting (e.g., El Nino) on seasonal to interannual times-scales. The GMAO's research activities, including system development, focus on numerous time and space scales, as detailed on the GMAO website, where they are tabbed under five major themes: Weather Analysis and Prediction; Seasonal-Decadal Analysis and Prediction; Reanalysis; Global Mesoscale Modeling, and Observing System Science. A brief description of the GEOS systems can also be found at the GMAO website. GEOS executes as a collection of earth system components connected through the Earth System Modeling Framework (ESMF). The ESMF layer is supplemented with the MAPL (Modeling, Analysis, and Prediction Layer) software toolkit developed at the GMAO, which facilitates the organization of the computational components into a hierarchical architecture. GEOS systems run in parallel using a horizontal decomposition of the Earth's sphere into processing elements (PEs). Communication between PEs is primarily through a message passing framework, using the message passing interface (MPI), and through explicit use of node-level shared memory access via the SHMEM (Symmetric Hierarchical Memory access) protocol. Production GEOS weather prediction systems currently run at 12.5-kilometer horizontal resolution with 72 vertical levels decomposed into PEs associated with 5,400 MPI processes. Research GEOS systems run at resolutions as fine as 1.5 kilometers globally using as many as 30,000 MPI processes. Looking forward, these systems can be expected to see a 2 times increase in horizontal resolution every two to three years, as well as less frequent increases in vertical resolution. Coupling these resolution changes with increases in complexity, the computational demands on the GEOS production and research systems should easily increase 100-fold over the next five years. Currently, our 12.5 kilometer weather prediction system narrowly meets the time-to-solution demands of a near-real-time production system. Work is now in progress to take advantage of a hybrid MPI-OpenMP parallelism strategy, in an attempt to achieve a modest two-fold speed-up to accommodate an immediate demand due to increased scientific complexity and an increase in vertical resolution. Pursuing demands that require a 10- to 100-fold increases or more, however, would require a detailed exploration of the computational profile of GEOS, as well as targeted solutions using more advanced high-performance computing technologies. Increased computing demands of 100-fold will be required within five years based on anticipated changes in the GEOS production systems, increases of 1000-fold can be anticipated over the next ten years.

ESMF↗
NASA NTRSDate not supplied

Initial Development of A Digital Twin Model for an Electrified Aircraft Propulsion Emulation Rig

In support of aviation fuel burn and emission reduction goals, NASA is pursing high-payoff research investments that promise to transform aviation. This includes investments in Electrified Aircraft Propulsion (EAP), which relies on the generation, storage, transmission, and use of electrical power for producing thrust and optimizing propulsion system efficiency. Multiple technology challenges must be addressed to unlock the full potential of EAP. This includes advances in propulsion controls, which will be vital for ensuring coordinated efficient operation of the complex integrated subsystems that comprise EAP architectures. To support EAP controls research, the NASA Glenn Research Center has developed the Hybrid Propulsion Emulation Rig (HyPER). The HyPER laboratory hardware includes shaft-mounted electric machines, power converters, power supplies, power distribution cables, and an energy storage device that can be reconfigured to represent a variety of EAP architectures. It also includes an integrated real-time computer system that hosts developed EAP control software and turbomachinery simulations. This enables the electrical system and rotating shafts of EAP designs to be implemented in actual hardware and integrated with turbomachinery simulations and system-level EAP control logic implemented in software. In this form, the HyPER laboratory provides a partially simulated, partially hardware-in-the-loop test environment enabling the initial development and evaluation of EAP control technology. A prerequisite for the development of EAP control designs is the availability of a system model that accurately reflects the operation of the electrical system hardware. To support this need, a digital twin model of the HyPER electrical system hardware is under development. This model is being coded in the MATLAB Simulink environment and uses the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) to construct a digital twin framework. EMTAT contains generic electrical component building blocks that are simulated at turbomachinery timescales. Associated inputs and outputs allow the blocks to be combined to model complete electrical systems. The EMTAT blocks also contain adjustable internal maps and parameters that can be set to reflect the operation of a specific electrical component. For the HyPER digital twin, the settings of these EMTAT block internal maps and parameters is determined through machine learning approaches applied to characterization run data collected from the laboratory. During characterization runs the laboratory electrical system hardware is subjected to a full range of torque, speed, and power settings. Acquired data is then used to estimate EMTAT block parameters using a variety of machine learning techniques. The resulting digital twin model is found to match the operation of actual HyPER hardware with an accuracy suitable for control development purposes. It also holds promise for other applications including modeling the performance of HyPER laboratory reconfigurations and model-based anomaly detection. Planned follow-on work to automate post-processing of acquired laboratory data to update the HyPER digital twin model will also be presented and discussed.

Electrified Aircraft Propulsion↗
NASA NTRS2003

Overview of the SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division Activities and Technical Projects

The SAE G-11 RMSL (Reliability, Maintainability, Supportability, and Logistics) Division activities include identification and fulfillment of joint industry, government, and academia needs for development and implementation of RMSL technologies. Four Projects in the Probabilistic Methods area and two in the area of RMSL have been identified. These are: (1) Evaluation of Probabilistic Technology - progress has been made toward the selection of probabilistic application cases. Future effort will focus on assessment of multiple probabilistic softwares in solving selected engineering problems using probabilistic methods. Relevance to Industry & Government - Case studies of typical problems encountering uncertainties, results of solutions to these problems run by different codes, and recommendations on which code is applicable for what problems; (2) Probabilistic Input Preparation - progress has been made in identifying problem cases such as those with no data, little data and sufficient data. Future effort will focus on developing guidelines for preparing input for probabilistic analysis, especially with no or little data. Relevance to Industry & Government - Too often, we get bogged down thinking we need a lot of data before we can quantify uncertainties. Not True. There are ways to do credible probabilistic analysis with little data; (3) Probabilistic Reliability - probabilistic reliability literature search has been completed along with what differentiates it from statistical reliability. Work on computation of reliability based on quantification of uncertainties in primitive variables is in progress. Relevance to Industry & Government - Correct reliability computations both at the component and system level are needed so one can design an item based on its expected usage and life span; (4) Real World Applications of Probabilistic Methods (PM) - A draft of volume 1 comprising aerospace applications has been released. Volume 2, a compilation of real world applications of probabilistic methods with essential information demonstrating application type and timehost savings by the use of probabilistic methods for generic applications is in progress. Relevance to Industry & Government - Too often, we say, 'The Proof is in the Pudding'. With help from many contributors, we hope to produce such a document. Problem is - not too many people are coming forward due to proprietary nature. So, we are asking to document only minimum information including problem description, what method used, did it result in any savings, and how much?; (5) Software Reliability - software reliability concept, program, implementation, guidelines, and standards are being documented. Relevance to Industry & Government - software reliability is a complex issue that must be understood & addressed in all facets of business in industry, government, and other institutions. We address issues, concepts, ways to implement solutions, and guidelines for maximizing software reliability; (6) Maintainability Standards - maintainability/serviceability industry standard/guidelines and industry best practices and methodologies used in performing maintainability/ serviceability tasks are being documented. Relevance to Industry & Government - Any industry or government process, project, and/or tool must be maintained and serviced to realize the life and performance it was designed for. We address issues and develop guidelines for optimum performance & life.

Singhal, Surendra N.↗
NASA NTRS2004

Monitoring the Performance of a Neuro-Adaptive Controller

Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

Schumann, Johann↗
NASA NTRS1998

Mechanical Characterization of Thermomechanical Matrix Residual Stresses Incurred During MMC Processing

In recent years, much effort has been spent examining the residual stress-strain states of advanced composites. Such examinations are motivated by a number of significant concerns that affect composite development, processing, and analysis. The room-temperature residual stress states incurred in many advanced composite systems are often quite large and can introduce damage even prior to the first external mechanical loading of the material. These stresses, which are induced during the cooldown following high-temperature consolidation, result from the coefficient of thermal expansion mismatch between the fiber and matrix. Experimental techniques commonly used to evaluate composite internal residual stress states are non-mechanical in nature and generally include forms of x-ray and neutron diffraction. Such approaches are usually complex, involving a number of assumptions and limitations associated with a wide range of issues, including the depth of penetration, the volume of material being assessed, and erroneous effects associated with oriented grains. Furthermore, and more important to the present research, these techniques can assess only "single time" stress in the composite. That is, little, if any, information is obtained that addresses the time-dependent point at which internal stresses begin to accumulate, the manner in which the accumulation occurs, and the presiding relationships between thermoelastic, thermoplastic, and thermoviscous behaviors. To address these critical issues, researchers at the NASA Lewis Research Center developed and implemented an innovative mechanical test technique to examine in real time, the time-dependent thermomechanical stress behavior of a matrix alloy as it went through a consolidation cycle.

Castelli, Michael G.↗
NASA NTRS2019

Utilization of Unsupervised Anomalies Detector as a Tool for Managing the TDRS Constellation at GSFC

NASA’s Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The mission of the TDRS constellation is to provide relay communications from low-earth orbiting spacecraft to the primary ground station at the White Sands Complex in Las Cruces, New Mexico. Major customers include the International Space Station and Hubble Space Telescope. The NASA Space Network project office at GSFC manages the constellation of spacecraft. The constellation is over 30 years old, and a wide range of technologies and manufacturing techniques are represented on-orbit. Since 1983, the TDRS constellation has recorded thousands of gigabytes of telemetry data. Spacecraft telemetry data has changed throughout the three generations of TDRS spacecraft, however each spacecraft has the same basic functions with some generational enhancements. The constellation includes several spacecraft that have significantly outlived the manufacturer's projected lifetime. This has provided NASA with a significant benefit in terms of return on investment, however it places a burden on efficient management of the assets for maximum life without permitting a TDRS spacecraft to become stranded in its geosynchronous orbital slot. Consequently, the highest level of attention is paid to systems whose failure could strand a TDRS spacecraft in orbit. In this paper, we proposed two stages of analyzing spacecraft anomalies using data mining (DM) to enhance on-going predictions of spacecraft life, subsystem performance, and analysis of subsystem anomalies. The first stage conducts the unsupervised anomaly detector to detect potential anomalies in real-time telemetry data. The second stage introduced telemetry weight (TW) to each telemetry parameter to determine which parameter caused the strongest anomaly. We will present case studies of some of these analyses and how the data can impact decisions on the management of the constellation.

Ma, Kenneth Y.↗
NASA NTRS2000

A Probabilistic Framework for the Validation and Certification of Computer Simulations

The paper presents a methodology for quantifying, propagating, and managing the uncertainty in the data required to initialize computer simulations of complex phenomena. The purpose of the methodology is to permit the quantitative assessment of a certification level to be associated with the predictions from the simulations, as well as the design of a data acquisition strategy to achieve a target level of certification. The value of a methodology that can address the above issues is obvious, specially in light of the trend in the availability of computational resources, as well as the trend in sensor technology. These two trends make it possible to probe physical phenomena both with physical sensors, as well as with complex models, at previously inconceivable levels. With these new abilities arises the need to develop the knowledge to integrate the information from sensors and computer simulations. This is achieved in the present work by tracing both activities back to a level of abstraction that highlights their commonalities, thus allowing them to be manipulated in a mathematically consistent fashion. In particular, the mathematical theory underlying computer simulations has long been associated with partial differential equations and functional analysis concepts such as Hilbert spares and orthogonal projections. By relying on a probabilistic framework for the modeling of data, a Hilbert space framework emerges that permits the modeling of coefficients in the governing equations as random variables, or equivalently, as elements in a Hilbert space. This permits the development of an approximation theory for probabilistic problems that parallels that of deterministic approximation theory. According to this formalism, the solution of the problem is identified by its projection on a basis in the Hilbert space of random variables, as opposed to more traditional techniques where the solution is approximated by its first or second-order statistics. The present representation, in addition to capturing significantly more information than the traditional approach, facilitates the linkage between different interacting stochastic systems as is typically observed in real-life situations.

Ghanem, Roger↗
NASA NTRS2013

Development Status of the WetLab-2 Project: New Tools for On-orbit Real-time Quantitative Gene Expression.

The primary objective of NASA Ames Research Centers WetLab-2 Project is to place on the ISS a research platform to facilitate gene expression analysis via quantitative real-time PCR (qRT-PCR) of biological specimens grown or cultured on orbit. The WetLab-2 equipment will be capable of processing multiple sample types ranging from microbial cultures to animal tissues dissected on-orbit. In addition to the logistical benefits of in-situ sample processing and analysis, conducting qRT-PCR on-orbit eliminates the confounding effects on gene expression of reentry stresses and shock acting on live cells and organisms. The system can also validate terrestrial analyses of samples returned from ISS by providing quantitative on-orbit gene expression benchmarking prior to sample return. The ability to get on orbit data will provide investigators with the opportunity to adjust experimental parameters for subsequent trials based on the real-time data analysis without need for sample return and re-flight. Finally, WetLab-2 can be used for analysis of air, surface, water, and clinical samples to monitor environmental contaminants and crew health. The verification flight of the instrument is scheduled to launch on SpaceX-5 in Aug. 2014.Progress to date: The WetLab-2 project completed a thorough study of commercially available qRT-PCR systems and performed a downselect based on both scientific and engineering requirements. The selected instrument, the Cepheid SmartCycler, has advantages including modular design (16 independent PCR modules), low power consumption, and rapid ramp times. The SmartCycler has multiplex capabilities, assaying up to four genes of interest in each of the 16 modules. The WetLab-2 team is currently working with Cepheid to modify the unit for housing within an EXPRESS rack locker on the ISS. This will enable the downlink of data to the ground and provide uplink capabilities for programming, commanding, monitoring, and instrument maintenance. The project is currently designing a module that will lyse the cells and extract RNA of sufficient quality for use in qRT-PCR reactions while using a housekeeping gene to normalize RNA concentration and integrity. Current testing focuses on two promising commercial products and chemistries that allow for RNA extraction with minimal complexity and crew time.

quantitative PCR↗
NASA NTRS2016

Towards Autonomous Aviation Operations: What Can We Learn from Other Areas of Automation?

Rapid advances in automation has disrupted and transformed several industries in the past 25 years. Automation has evolved from regulation and control of simple systems like controlling the temperature in a room to the autonomous control of complex systems involving network of systems. The reason for automation varies from industry to industry depending on the complexity and benefits resulting from increased levels of automation. Automation may be needed to either reduce costs or deal with hazardous environment or make real-time decisions without the availability of humans. Space autonomy, Internet, robotic vehicles, intelligent systems, wireless networks and power systems provide successful examples of various levels of automation. NASA is conducting research in autonomy and developing plans to increase the levels of automation in aviation operations. This paper provides a brief review of levels of automation, previous efforts to increase levels of automation in aviation operations and current level of automation in the various tasks involved in aviation operations. It develops a methodology to assess the research and development in modeling, sensing and actuation needed to advance the level of automation and the benefits associated with higher levels of automation. Section II describes provides an overview of automation and previous attempts at automation in aviation. Section III provides the role of automation and lessons learned in Space Autonomy. Section IV describes the success of automation in Intelligent Transportation Systems. Section V provides a comparison between the development of automation in other areas and the needs of aviation. Section VI provides an approach to achieve increased automation in aviation operations based on the progress in other areas. The final paper will provide a detailed analysis of the benefits of increased automation for the Traffic Flow Management (TFM) function in aviation operations.

Sridhar, Banavar↗
NASA NTRS2012

SE-FIT

The mathematical theory of capillary surfaces has developed steadily over the centuries, but it was not until the last few decades that new technologies have put a more urgent demand on a substantially more qualitative and quantitative understanding of phenomena relating to capillarity in general. So far, the new theory development successfully predicts the behavior of capillary surfaces for special cases. However, an efficient quantitative mathematical prediction of capillary phenomena related to the shape and stability of geometrically complex equilibrium capillary surfaces remains a significant challenge. As one of many numerical tools, the open-source Surface Evolver (SE) algorithm has played an important role over the last two decades. The current effort was undertaken to provide a front-end to enhance the accessibility of SE for the purposes of design and analysis. Like SE, the new code is open-source and will remain under development for the foreseeable future. The ultimate goal of the current Surface Evolver Fluid Interface Tool (SEFIT) development is to build a fully integrated front-end with a set of graphical user interface (GUI) elements. Such a front-end enables the access to functionalities that are developed along with the GUIs to deal with pre-processing, convergence computation operation, and post-processing. In other words, SE-FIT is not just a GUI front-end, but an integrated environment that can perform sophisticated computational tasks, e.g. importing industry standard file formats and employing parameter sweep functions, which are both lacking in SE, and require minimal interaction by the user. These functions are created using a mixture of Visual Basic and the SE script language. These form the foundation for a high-performance front-end that substantially simplifies use without sacrificing the proven capabilities of SE. The real power of SE-FIT lies in its automated pre-processing, pre-defined geometries, convergence computation operation, computational diagnostic tools, and crash-handling capabilities to sustain extensive computations. SE-FIT performance is enabled by its so-called file-layer mechanism. During the early stages of SE-FIT development, it became necessary to modify the original SE code to enable capabilities required for an enhanced and synchronized communication. To this end, a file-layer was created that serves as a command buffer to ensure a continuous and sequential execution of commands sent from the front-end to SE. It also establishes a proper means for handling crashes. The file layer logs input commands and SE output; it also supports user interruption requests, back and forward operation (i.e. undo and redo), and others. It especially enables the batch mode computation of a series of equilibrium surfaces and the searching of critical parameter values in studying the stability of capillary surfaces. In this way, the modified SE significantly extends the capabilities of the original SE.

Chen, Yongkang↗
NASA NTRS2006

Noninvasive Diagnosis of Coronary Artery Disease Using 12-Lead High-Frequency Electrocardiograms

A noninvasive, sensitive method of diagnosing certain pathological conditions of the human heart involves computational processing of digitized electrocardiographic (ECG) signals acquired from a patient at all 12 conventional ECG electrode positions. In the processing, attention is focused on low-amplitude, high-frequency components of those portions of the ECG signals known in the art as QRS complexes. The unique contribution of this method lies in the utilization of signal features and combinations of signal features from various combinations of electrode positions, not reported previously, that have been found to be helpful in diagnosing coronary artery disease and such related pathological conditions as myocardial ischemia, myocardial infarction, and congestive heart failure. The electronic hardware and software used to acquire the QRS complexes and perform some preliminary analyses of their high-frequency components were summarized in Real-Time, High-Frequency QRS Electrocardiograph (MSC- 23154), NASA Tech Briefs, Vol. 27, No. 7 (July 2003), pp. 26-28. To recapitulate, signals from standard electrocardiograph electrodes are preamplified, then digitized at a sampling rate of 1,000 Hz, then analyzed by the software that detects R waves and QRS complexes and analyzes them from several perspectives. The software includes provisions for averaging signals over multiple beats and for special-purpose nonrecursive digital filters with specific low- and high-frequency cutoffs. These filters, applied to the averaged signal, effect a band-pass operation in the frequency range from 150 to 250 Hz. The output of the bandpass filter is the desired high-frequency QRS signal. Further processing is then performed in real time to obtain the beat-to-beat root mean square (RMS) voltage amplitude of the filtered signal, certain variations of the RMS voltage, and such standard measures as the heart rate and R-R interval at any given time. A key signal feature analyzed in the present method is the presence versus the absence of reduced-amplitude zones (RAZs). In terms that must be simplified for the sake of brevity, an RAZ comprises several cycles of a high-frequency QRS signal during which the amplitude of the high-frequency oscillation in a portion of the signal is abnormally low (see figure). A given signal sample exhibiting an interval of reduced amplitude may or may not be classified as an RAZ, depending on quantitative criteria regarding peaks and troughs within the reduced-amplitude portion of the high-frequency QRS signal. This analysis is performed in all 12 leads in real time.

Schlegel, Todd T.↗
NASA NTRS2003

Investigation of the Surface Stress in SiC and Diamond Nanocrystals by In-situ High Pressure Powder Diffraction Technique

The real atomic structure of nanocrystals determines key properties of the materials. For such materials the serious experimental problem lies in obtaining sufficiently accurate measurements of the structural parameters of the crystals, since very small crystals constitute rather a two-phase than a uniform crystallographic phase system. As a result, elastic properties of nanograins may be expected to reflect a dual nature of their structure, with a corresponding set of different elastic property parameters. We studied those properties by in-situ high-pressure powder diffraction technique. For nanocrystalline, even one-phase materials such measurements are particularly difficult to make since determination of the lattice parameters of very small crystals presents a challenge due to inherent limitations of standard elaboration of powder diffractograms. In this investigation we used our methodology of the structural analysis, the 'apparent lattice parameter' (alp) concept. The methodology allowed us to avoid the traps (if applied to nanocrystals) of standard powder diffraction evaluation techniques. The experiments were performed for nanocrystalline Sic and GaN powders using synchrotron sources. We applied both hydrostatic and isostatic pressures in the range of up to 40 GPa. Elastic properties of the samples were examined based on the measurements of a change of the lattice parameters with pressure. The results show a dual nature of the mechanical properties (compressibilities) of the materials, indicating a complex, core-shell structure of the grains.

Palosz, B.↗
NASA NTRS2010

SPOT Program

A Spacecraft Position Optimal Tracking (SPOT) program was developed to process Global Positioning System (GPS) data, sent via telemetry from a spacecraft, to generate accurate navigation estimates of the vehicle position and velocity (state vector) using a Kalman filter. This program uses the GPS onboard receiver measurements to sequentially calculate the vehicle state vectors and provide this information to ground flight controllers. It is the first real-time ground-based shuttle navigation application using onboard sensors. The program is compact, portable, self-contained, and can run on a variety of UNIX or Linux computers. The program has a modular objec-toriented design that supports application-specific plugins such as data corruption remediation pre-processing and remote graphics display. The Kalman filter is extensible to additional sensor types or force models. The Kalman filter design is also strong against data dropouts because it uses physical models from state and covariance propagation in the absence of data. The design of this program separates the functionalities of SPOT into six different executable processes. This allows for the individual processes to be connected in an a la carte manner, making the feature set and executable complexity of SPOT adaptable to the needs of the user. Also, these processes need not be executed on the same workstation. This allows for communications between SPOT processes executing on the same Local Area Network (LAN). Thus, SPOT can be executed in a distributed sense with the capability for a team of flight controllers to efficiently share the same trajectory information currently being computed by the program. SPOT is used in the Mission Control Center (MCC) for Space Shuttle Program (SSP) and International Space Station Program (ISSP) operations, and can also be used as a post -flight analysis tool. It is primarily used for situational awareness, and for contingency situations.

Smith, Jason T.↗
NASA NTRSDate not supplied

Astrobee Operations on the Iss: Gui’S Impact on the Operators’ Cognitive Load

The Astrobee free-flying robots have completed their fifth successful year of operations housed in the Japanese Experimental Module (JEM) on the International Space Station (ISS). In this paper, we introduce two Graphical User Interfaces (GUI) used to operate and monitor in real-time the Astrobee free-flying robots onboard the ISS and report on the impact these GUIs have in the operator’s cognitive load. A review of the state-of-the-art GUI design for remotely teleoperated scenarios with minimal time delay is presented and the study’s conclusion used to determine the elements and recommendations to create an interface that minimizes its impact on the overall performance of an operator during an activity at the ISS. The Ground Data System (GDS) is one of the two GUIs in the study: it contains several tabs, each of which displays a different set of controls for specific tasks e.g. Overview, Run Plan, Teleoperate, Guest Science; some also display video and a three-dimensional (3D) representation of the ISS and robot based on the Astrobee’s telemetry. Most tabs enable a single operator-robot connection, however some of its tabs are capable to monitor and control up to three Astrobees simultaneously. The GDS Helper is a text-based user interface created to facilitate commanding and monitoring of an Astrobee robot directly from an SSH session. In full interactive mode it displays a maximum of 5 sections: general commanding, feedback/ack, telemetry, guest science commanding, and data, all in one view. In batch mode, it enables complex command scripting while retaining some interactive capabilities. A comparative analysis between these GUIs is carried out at an analogous ISS environment at the NASA Ames Research Center’s Granite Lab and its results presented. While GDS is able to provide an operator with control and situational awareness via its video and 3D displays, its several tabs may introduce an overwhelming amount of information confusing and delaying the operator especially during time-sensitive maneuvers where the operator may need to switch back and forth between them. GDS helper in the other hand does not provide video or 3D displays thus not allowing an operator to attain situational awareness, however it provides the operator with a design displaying commonly used data in a single window, enabling the operator to understand the state of the robot at a glance and control it through a commands entered via keyboard instead of a combination of mouse clicks and keyboard input. The results of the experiments measure the cognitive load across several operators maneuvering Astrobee to accomplish tasks ranging from fully manual to supervised activities. A GUI combining a single window displaying data along video and a 3D display is expected to reduce the operator’s cognitive load.

Astrobee↗
NASA NTRS2000

Use Computer-Aided Tools to Parallelize Large CFD Applications

Porting applications to high performance parallel computers is always a challenging task. It is time consuming and costly. With rapid progressing in hardware architectures and increasing complexity of real applications in recent years, the problem becomes even more sever. Today, scalability and high performance are mostly involving handwritten parallel programs using message-passing libraries (e.g. MPI). However, this process is very difficult and often error-prone. The recent reemergence of shared memory parallel (SMP) architectures, such as the cache coherent Non-Uniform Memory Access (ccNUMA) architecture used in the SGI Origin 2000, show good prospects for scaling beyond hundreds of processors. Programming on an SMP is simplified by working in a globally accessible address space. The user can supply compiler directives, such as OpenMP, to parallelize the code. As an industry standard for portable implementation of parallel programs for SMPs, OpenMP is a set of compiler directives and callable runtime library routines that extend Fortran, C and C++ to express shared memory parallelism. It promises an incremental path for parallel conversion of existing software, as well as scalability and performance for a complete rewrite or an entirely new development. Perhaps the main disadvantage of programming with directives is that inserted directives may not necessarily enhance performance. In the worst cases, it can create erroneous results. While vendors have provided tools to perform error-checking and profiling, automation in directive insertion is very limited and often failed on large programs, primarily due to the lack of a thorough enough data dependence analysis. To overcome the deficiency, we have developed a toolkit, CAPO, to automatically insert OpenMP directives in Fortran programs and apply certain degrees of optimization. CAPO is aimed at taking advantage of detailed inter-procedural dependence analysis provided by CAPTools, developed by the University of Greenwich, to reduce potential errors made by users. Earlier tests on NAS Benchmarks and ARC3D have demonstrated good success of this tool. In this study, we have applied CAPO to parallelize three large applications in the area of computational fluid dynamics (CFD): OVERFLOW, TLNS3D and INS3D. These codes are widely used for solving Navier-Stokes equations with complicated boundary conditions and turbulence model in multiple zones. Each one comprises of from 50K to 1,00k lines of FORTRAN77. As an example, CAPO took 77 hours to complete the data dependence analysis of OVERFLOW on a workstation (SGI, 175MHz, R10K processor). A fair amount of effort was spent on correcting false dependencies due to lack of necessary knowledge during the analysis. Even so, CAPO provides an easy way for user to interact with the parallelization process. The OpenMP version was generated within a day after the analysis was completed. Due to sequential algorithms involved, code sections in TLNS3D and INS3D need to be restructured by hand to produce more efficient parallel codes. An included figure shows preliminary test results of the generated OVERFLOW with several test cases in single zone. The MPI data points for the small test case were taken from a handcoded MPI version. As we can see, CAPO's version has achieved 18 fold speed up on 32 nodes of the SGI O2K. For the small test case, it outperformed the MPI version. These results are very encouraging, but further work is needed. For example, although CAPO attempts to place directives on the outer- most parallel loops in an interprocedural framework, it does not insert directives based on the best manual strategy. In particular, it lacks the support of parallelization at the multi-zone level. Future work will emphasize on the development of methodology to work in a multi-zone level and with a hybrid approach. Development of tools to perform more complicated code transformation is also needed.

Jin, H.↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗