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Low-Earth-Orbiter resource allocation and capacity planning for the DSN using LEO4CAST

The Deep Space Network provides tracking and communication services for a number of U.S. and international low-Earth-orbiting (LEO) and near-Earth missions. This service is supplied by the 26-m subnet (located at each of the DSN complexes), the 9-m and the 34-m Antenna Research System antennas at Goldstone, and the 11-m antennas (following the orbital VLBI mission). An increasing number of LEO missions are planned for DSN support, which will result in increasingly complex ground resource allocation and mission support trades. To support TDA decision making on mission support and cost-effective ground system evolution for this 26-m subnet, LEO4CAST has been developed. LEO4CAST is a tool that uses statistical approaches to provide useful information for long-term ground system capacity planning and near-term resource allocation (prior to detailed time-of-day scheduling). LEO4CAST is currently beta-test software and is being exercised by both the Office of Telecommunications and Data Acquisition (TDA) and the JPL Systems Division.

Fox, G.↗

NASA Tech Briefs, April 2004

Topics covered include: Analysis of SSEM Sensor Data Using BEAM; Hairlike Percutaneous Photochemical Sensors; Video Guidance Sensors Using Remotely Activated Targets; Simulating Remote Sensing Systems; EHW Approach to Temperature Compensation of Electronics; Polymorphic Electronic Circuits; Micro-Tubular Fuel Cells; Whispering-Gallery-Mode Tunable Narrow-Band-Pass Filter; PVM Wrapper; Simulation of Hyperspectral Images; Algorithm for Controlling a Centrifugal Compressor; Hybrid Inflatable Pressure Vessel; Double-Acting, Locking Carabiners; Position Sensor Integral with a Linear Actuator; Improved Electromagnetic Brake; Flow Straightener for a Rotating-Drum Liquid Separator; Sensory-Feedback Exoskeletal Arm Controller; Active Suppression of Instabilities in Engine Combustors; Fabrication of Robust, Flat, Thinned, UV-Imaging CCDs; Chemical Thinning Process for Fabricating UV-Imaging CCDs; Pseudoslit Spectrometer; Waste-Heat-Driven Cooling Using Complex Compound Sorbents; Improved Refractometer for Measuring Temperatures of Drops; Semiconductor Lasers Containing Quantum Wells in Junctions; Phytoplankton-Fluorescence-Lifetime Vertical Profiler; Hexagonal Pixels and Indexing Scheme for Binary Images; Finding Minimum-Power Broadcast Trees for Wireless Networks; and Automation of Design Engineering Processes.

Source record↗

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗

Grand challenge scientific questions in coupled modeling

Most convective field experiments in the past (e.g., SESAME, CCOPE, CINDE) have attempted to resolve only the immediate scales of moist convection using network arrays that spanned two or three atmospheric scales at most. Furthermore, these scales have been defined more on practical considerations (cost, manpower, etc.) than on a clear understanding of their theoretical significance. Unfortunately, this has precluded a description of the entire life cycle of MCS's and their interaction with larger scale systems, the land surface, and trace species. Fortunately, the following factors now make it possible to attempt to simulate scale contraction processes from the synoptic scale down to the cloud scale, as well as interactions between complex meteorological, land surface, precipitation, chemical, and hydrologic processes with coupled, multiscale models: the availability of new technology to sample meteorological fields at high temporal and spatial resolution over a broad region made possible by the weather observing modernization program; increased computer power and improved numerical approaches to run limited area models with nonhydrostatic precipitation physics so as to explicitly resolve MCS (Mesoscale Convective System) processes; and four dimensional assimilation of non-conventional data to provide dynamically consistent datasets for diagnostic analysis of nonlinear scale-interactive dynamics. Several examples of scale-interactive processes which present grand challenges for coupled, multiscale modeling were presented.

Koch, Steven↗

Space-based Science Operations Grid Prototype

Grid technology is the up and coming technology that is enabling widely disparate services to be offered to users that is very economical, easy to use and not available on a wide basis. Under the Grid concept disparate organizations generally defined as "virtual organizations" can share services i.e. sharing discipline specific computer applications, required to accomplish the specific scientific and engineering organizational goals and objectives. Grids are emerging as the new technology of the future. Grid technology has been enabled by the evolution of increasingly high speed networking. Without the evolution of high speed networking Grid technology would not have emerged. NASA/Marshall Space Flight Center's (MSFC) Flight Projects Directorate, Ground Systems Department is developing a Space-based Science Operations Grid prototype to provide to scientists and engineers the tools necessary to operate space-based science payloads/experiments and for scientists to conduct public and educational outreach. In addition Grid technology can provide new services not currently available to users. These services include mission voice and video, application sharing, telemetry management and display, payload and experiment commanding, data mining, high order data processing, discipline specific application sharing and data storage, all from a single grid portal. The Prototype will provide most of these services in a first step demonstration of integrated Grid and space-based science operations technologies. It will initially be based on the International Space Station science operational services located at the Payload Operations Integration Center at MSFC, but can be applied to many NASA projects including free flying satellites and future projects. The Prototype will use the Internet2 Abilene Research and Education Network that is currently a 10 Gb backbone network to reach the University of Alabama at Huntsville and several other, as yet unidentified, Space Station based science experimenters. There is an international aspect to the Grid involving the America's Pathway (AMPath) network, the Chilean REUNA Research and Education Network and the University of Chile in Santiago that will further demonstrate how extensive these services can be used. From the user's perspective, the Prototype will provide a single interface and logon to these varied services without the complexity of knowing the where's and how's of each service. There is a separate and deliberate emphasis on security. Security will be addressed by specifically outlining the different approaches and tools used. Grid technology, unlike the Internet, is being designed with security in mind. In addition we will show the locations, configurations and network paths associated with each service and virtual organization. We will discuss the separate virtual organizations that we define for the varied user communities. These will include certain, as yet undetermined, space-based science functions and/or processes and will include specific virtual organizations required for public and educational outreach and science and engineering collaboration. We will also discuss the Grid Prototype performance and the potential for further Grid applications both space-based and ground based projects and processes. In this paper and presentation we will detail each service and how they are integrated using Grid

Bradford, Robert N.↗

Generalized Fluid System Simulation Program, Version 5.0-Educational. Supplemental Information for NASA/TM-2011-216470

The Generalized Fluid System Simulation Program (GFSSP) is a finite-volume based general-purpose computer program for analyzing steady state and time-dependent flow rates, pressures, temperatures, and concentrations in a complex flow network. The program is capable of modeling real fluids with phase changes, compressibility, mixture thermodynamics, conjugate heat transfer between solid and fluid, fluid transients, pumps, compressors and external body forces such as gravity and centrifugal. The thermofluid system to be analyzed is discretized into nodes, branches, and conductors. The scalar properties such as pressure, temperature, and concentrations are calculated at nodes. Mass flow rates and heat transfer rates are computed in branches and conductors. The graphical user interface allows users to build their models using the point, drag and click method; the users can also run their models and post-process the results in the same environment. The integrated fluid library supplies thermodynamic and thermo-physical properties of 36 fluids and 21 different resistance/source options are provided for modeling momentum sources or sinks in the branches. This Technical Memorandum illustrates the application and verification of the code through 12 demonstrated example problems. This supplement gives the input and output data files for the examples.

Majumdar, A. K.↗

The VLBA correlator: Real-time in the distributed era

The correlator is the signal processing engine of the Very Long Baseline Array (VLBA). Radio signals are recorded on special wideband (128 Mb/s) digital recorders at the 10 telescopes, with sampling times controlled by hydrogen maser clocks. The magnetic tapes are shipped to the Array Operations Center in Socorro, New Mexico, where they are played back simultaneously into the correlator. Real-time software and firmware controls the playback drives to achieve synchronization, compute models of the wavefront delay, control the numerous modules of the correlator, and record FITS files of the fringe visibilities at the back-end of the correlator. In addition to the more than 3000 custom VLSI chips which handle the massive data flow of the signal processing, the correlator contains a total of more than 100 programmable computers, 8-, 16- and 32-bit CPUs. Code is downloaded into front-end CPU's dependent on operating mode. Low-level code is assembly language, high-level code is C running under a RT OS. We use VxWorks on Motorola MVME147 CPU's. Code development is on a complex of SPARC workstations connected to the RT CPU's by Ethernet. The overall management of the correlation process is dependent on a database management system. We use Ingres running on a Sparcstation-2. We transfer logging information from the database of the VLBA Monitor and Control System to our database using Ingres/NET. Job scripts are computed and are transferred to the real-time computers using NFS, and correlation job execution logs and status flow back by the route. Operator status and control displays use windows on workstations, interfaced to the real-time processes by network protocols. The extensive network protocol support provided by VxWorks is invaluable. The VLBA Correlator's dependence on network protocols is an example of the radical transformation of the real-time world over the past five years. Real-time is becoming more like conventional computing. Paradoxically, 'conventional' computing is also adopting practices from the real-time world: semaphores, shared memory, light-weight threads, and concurrency. This appears to be a convergence of thinking.

Wells, D. C.↗

Hybrid VLSI/QCA Architecture for Computing FFTs

A data-processor architecture that would incorporate elements of both conventional very-large-scale integrated (VLSI) circuitry and quantum-dot cellular automata (QCA) has been proposed to enable the highly parallel and systolic computation of fast Fourier transforms (FFTs). The proposed circuit would complement the QCA-based circuits described in several prior NASA Tech Briefs articles, namely Implementing Permutation Matrices by Use of Quantum Dots (NPO-20801), Vol. 25, No. 10 (October 2001), page 42; Compact Interconnection Networks Based on Quantum Dots (NPO-20855) Vol. 27, No. 1 (January 2003), page 32; and Bit-Serial Adder Based on Quantum Dots (NPO-20869), Vol. 27, No. 1 (January 2003), page 35. The cited prior articles described the limitations of very-large-scale integrated (VLSI) circuitry and the major potential advantage afforded by QCA. To recapitulate: In a VLSI circuit, signal paths that are required not to interact with each other must not cross in the same plane. In contrast, for reasons too complex to describe in the limited space available for this article, suitably designed and operated QCAbased signal paths that are required not to interact with each other can nevertheless be allowed to cross each other in the same plane without adverse effect. In principle, this characteristic could be exploited to design compact, coplanar, simple (relative to VLSI) QCA-based networks to implement complex, advanced interconnection schemes.

Fijany, Amir↗

ExMC Digital Engineering

Future missions beyond Artemis II will become increasingly complex as multiple vehicles (e.g., Gateway, Human Landing System (HLS), and Extravehicular Activity and Human Surface Mobility Program (EHP)), each having their own Program requirements and other associated documentation, which will need to be integrated into a single mission. Currently, the Human Health and Performance Directorate (HHPD)Program Support Teams mostly use documents to manage, perform, and archive their analyses. Identifying an opportunity for efficiency, ExMC demonstrated the ability to utilize MagicDraw, a Model-Based Systems Engineering (MBSE) tool, as a requirements database with traceability, dependencies, and relationships in one place. Rather than existing in documents, emails, and historical knowledge, ExMC pursued a Digital Engineering (DE) effort in coordination with HHPD by combining MBSE tools with other digital platforms to manage and develop user-defined databases and interfaces. This DE approach is aimed to simplify processes and reduce risk through the unification of requirements into a centralized digital network, improving collaboration, decision-making, and transparency compared to isolated documents and knowledge. However, manipulating data views and content in MagicDraw requires a steep learning curve not needed by all users and even the user-friendly web view comes with downsides due to the static views. To provide a more dynamic user interface, ExMC investigated the use of Microsoft Power Platform which does not require as steep of a learning curve to become proficient. This introduces analytics to the DE infrastructure, offering customizable and dynamic data dashboards. ExMC continues developing these dashboards and tailoring the DE infrastructure in alignment with HHPD workforce needs.

M Krihak↗

Multiwavelength study of the magnetically active T Tauri star HD 283447

We observed the luminous T Tauri star HD 283447 = V773 Tauri simultaneously at X-ray, ultraviolet, optical photometric and spectroscopic, and radio wavelengths for several hours on UT 1992 September 11. ROSAT, IUE, Very Large Array (VLA) and an intercontinental Very Long Baseline Interferometry (VLBI) network, and three optical observatories participated in the campaign. The star is known for its unusually high and variable nonthermal radio continuum emission. High levels of soft X-ray and Mg II line emission are discovered, with luminosity L(sub x) = 5.5 x 10(exp 30) ergs/s (0.2 - 2 keV) and L(sub Mg II) = 1 x 10(exp 29) ergs/s, respectively. Optically, the spectrum exhibits rather weak characteristics of `classical' T Tauri stars. A faint, broad emission line component, probably due to a collimated wind or infall, is present. During the campaign, the radio luminosity decreased by a factor of 4, while optical/UV lines and X-ray emission remained strong but constant. The large gyrosynchrotron-emitting regions are therefore decoupled from the chromospheric and coronal emission. Five models for the magnetic geometry around the star are discussed; solar-type activity, dipole magnetosphere, star-disk magnetic coupling, disk magnetic fields, and close binary interaction. The data suggest that two magnetic geometries are simultaneously present: complex multipolar fields like those on the Sun, and a large-scale field possibly associated with the circumstellar disk.

Feigelson, Eric D.↗

User-Friendly Interface Developed for a Web-Based Service for SpaceCAL Emulations

A team at the NASA Glenn Research Center is developing a Space Communications Architecture Laboratory (SpaceCAL) for protocol development activities for coordinated satellite missions. SpaceCAL will provide a multiuser, distributed system to emulate space-based Internet architectures, backbone networks, formation clusters, and constellations. As part of a new effort in 2003, building blocks are being defined for an open distributed system to make the satellite emulation test bed accessible through an Internet connection. The first step in creating a Web-based service to control the emulation remotely is providing a user-friendly interface for encoding the data into a well-formed and complete Extensible Markup Language (XML) document. XML provides coding that allows data to be transferred between dissimilar systems. Scenario specifications include control parameters, network routes, interface bandwidths, delay, and bit error rate. Specifications for all satellite, instruments, and ground stations in a given scenario are also included in the XML document. For the SpaceCAL emulation, the XML document can be created using XForms, a Webbased forms language for data collection. Contrary to older forms technology, the interactive user interface makes the science prevalent, not the data representation. Required versus optional input fields, default values, automatic calculations, data validation, and reuse will help researchers quickly and accurately define missions. XForms can apply any XML schema defined for the test mission to validate data before forwarding it to the emulation facility. New instrument definitions, facilities, and mission types can be added to the existing schema. The first prototype user interface incorporates components for interactive input and form processing. Internet address, data rate, and the location of the facility are implemented with basic form controls with default values provided for convenience and efficiency using basic XForms operations. Because different emulation scenarios will vary widely in their component structure, more complex operations are used to add and delete facilities.

Liszka, Kathy J.↗

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗

Session on High Speed Civil Transport Design Capability Using MDO and High Performance Computing

Since the inception of CAS in 1992, NASA Langley has been conducting research into applying multidisciplinary optimization (MDO) and high performance computing toward reducing aircraft design cycle time. The focus of this research has been the development of a series of computational frameworks and associated applications that increased in capability, complexity, and performance over time. The culmination of this effort is an automated high-fidelity analysis capability for a high speed civil transport (HSCT) vehicle installed on a network of heterogeneous computers with a computational framework built using Common Object Request Broker Architecture (CORBA) and Java. The main focus of the research in the early years was the development of the Framework for Interdisciplinary Design Optimization (FIDO) and associated HSCT applications. While the FIDO effort was eventually halted, work continued on HSCT applications of ever increasing complexity. The current application, HSCT4.0, employs high fidelity CFD and FEM analysis codes. For each analysis cycle, the vehicle geometry and computational grids are updated using new values for design variables. Processes for aeroelastic trim, loads convergence, displacement transfer, stress and buckling, and performance have been developed. In all, a total of 70 processes are integrated in the analysis framework. Many of the key processes include automatic differentiation capabilities to provide sensitivity information that can be used in optimization. A software engineering process was developed to manage this large project. Defining the interactions among 70 processes turned out to be an enormous, but essential, task. A formal requirements document was prepared that defined data flow among processes and subprocesses. A design document was then developed that translated the requirements into actual software design. A validation program was defined and implemented to ensure that codes integrated into the framework produced the same results as their standalone counterparts. Finally, a Commercial Off the Shelf (COTS) configuration management system was used to organize the software development. A computational environment, CJOPT, based on the Common Object Request Broker Architecture, CORBA, and the Java programming language has been developed as a framework for multidisciplinary analysis and Optimization. The environment exploits the parallelisms inherent in the application and distributes the constituent disciplines on machines best suited to their needs. In CJOpt, a discipline code is "wrapped" as an object. An interface to the object identifies the functionality (services) provided by the discipline, defined in Interface Definition Language (IDL) and implemented using Java. The results of using the HSCT4.0 capability are described. A summary of lessons learned is also presented. The use of some of the processes, codes, and techniques by industry are highlighted. The application of the methodology developed in this research to other aircraft are described. Finally, we show how the experience gained is being applied to entirely new vehicles, such as the Reusable Space Transportation System. Additional information is contained in the original.

Rehder, Joe↗

Time Analyzer for Time Synchronization and Monitor of the Deep Space Network

A software package has been developed to measure, monitor, and archive the performance of timing signals distributed in the NASA Deep Space Network. Timing signals are generated from a central master clock and distributed to over 100 users at distances up to 30 kilometers. The time offset due to internal distribution delays and time jitter with respect to the central master clock are critical for successful spacecraft navigation, radio science, and very long baseline interferometry (VLBI) applications. The instrument controller and operator interface software is written in LabView and runs on the Linux operating system. The software controls a commercial multiplexer to switch 120 separate timing signals to measure offset and jitter with a time-interval counter referenced to the master clock. The offset of each channel is displayed in histogram form, and "out of specification" alarms are sent to a central complex monitor and control system. At any time, the measurement cycle of 120 signals can be interrupted for diagnostic tests on an individual channel. The instrument also routinely monitors and archives the long-term stability of all frequency standards or any other 1-pps source compared against the master clock. All data is stored and made available for

Cole, Steven↗

Exploration Architecture with Quantum Inertial Gravimetry and In-Situ ChipSat Sensors

The Dual Exploration Architecture is a mission concept that combines remote sensing and in-situ observations into a single mission to answer planetary science questions that can only be answered with both types of data. Adoption of dual exploration architectures may short circuit the long, slow cycle of missions to inaccessible bodies by eliminating the need for separate precursor and follow-up missions. Additionally, the dual architecture possesses inherent flexibility that enables the design of adaptive, event-driven missions that are very different from traditional, largely pre-planned missions. Five key observations about the state and trends of planetary science exploration lead us to the dual architecture: increasing complexity of observations; scarcity of future mission opportunities; desire to capture transitory events; continued miniaturization of spacecraft components; and the Mars exploration cycle. Our goal in this study is to explore missions that can only happen using the dual architecture concept and find technology development needs that must be filled for those missions to compete. A survey of historical and current missions finds that opportunities for exploration are becoming less frequent, causing the flexibility and dual-nature elements of each mission to become more common. The dual exploration architecture takes these trends to their far conclusion, attempting to eliminate precursor and follow-up missions while still returning more scientific payoff. A study of the future of planetary science goals through the decadal survey reveals broad applicability of dual missions to solve mysteries that cannot be answered with a traditional mission architecture. These missions fall into three broad classes: choosing a local target from a global survey; dynamic/reactive science; and global in-situ networks. Two example missions of each class are notionally described. A deeper look at these dual architecture classes reveals four technology development needs that must be addressed for wide adoption of dual missions: passive landers; guided atmospheric probes; robust sensing packages; and small, precise orbital instruments. This study pursues a specific focus on two examples of such enabling technologies: the ChipSat and cold atom gravimetry. The ChipSat is a fully functional spacecraft-on-a-chip system that has broad versatility in the dual architecture mission space. Initial studies show that ChipSats could survive as passive impactor landers on bodies up to the size of Europa. Furthermore, COTS (Commercial Off-The-Shelf) components could provide an in-situ sensor suite that readily answers a number of pressing planetary science questions. Cold atom gravimetry uses inertial sensors based on light-pulse atom interferometry in a small form factor to map the gravity field of a body to precision equaling what would normally require two full spacecraft to achieve. The cold atom gravimeter provides an example of how advanced remote sensing capability can enable dual missions by providing greater returns in a significantly smaller package. Using the above two technologies, we study an example dual-architecture mission to both characterize and sample the subsurface oceans at Europa. The greatest scientific return in terms of detecting extraterrestrial life is in those regions where Europa’s ice crust is thin. The identification of regions with thin ice should therefore precede the selection of surface targets and dispatch of probes to those targets. This two-step process, if accomplished by separate flagship-scale missions, might take decades. As a result, a combined mission to both identify thin areas of Europa’s ice and follow up with surface observations at those regions is a good candidate for the dual-exploration architecture. This example mission consists of an orbiter spacecraft carrying a cold atom gravimeter capable of sensing or inferring the ice thickness on regional to local scales, along with a number of ChipSat probes capable of landing on the moon. The small size and weight of the ChipSats allows large numbers of them to be carried, ensuring that enough can be dropped to ensure survival of a minimum number of probes and potentially allowing for the in-situ sampling of multiple locations on the moon. The example missions and Europa case study show that amazing scientific return can obtained from dual-exploration architecture missions with a single launch by breaking the long timescales of planetary exploration and providing the flexibility to capturing transitory events and collect data across the local, regional, and global scales.

Exploration↗

Monitoring task loading with multivariate EEG measures during complex forms of human-computer interaction

Electroencephalographic (EEG) recordings were made while 16 participants performed versions of a personal-computer-based flight simulation task of low, moderate, or high difficulty. As task difficulty increased, frontal midline theta EEG activity increased and alpha band activity decreased. A participant-specific function that combined multiple EEG features to create a single load index was derived from a sample of each participant's data and then applied to new test data from that participant. Index values were computed for every 4 s of task data. Across participants, mean task load index values increased systematically with increasing task difficulty and differed significantly between the different task versions. Actual or potential applications of this research include the use of multivariate EEG-based methods to monitor task loading during naturalistic computer-based work.

NASA Discipline Space Human Factors↗

Sensor Selection and Data Validation for Reliable Integrated System Health Management

For new access to space systems with challenging mission requirements, effective implementation of integrated system health management (ISHM) must be available early in the program to support the design of systems that are safe, reliable, highly autonomous. Early ISHM availability is also needed to promote design for affordable operations; increased knowledge of functional health provided by ISHM supports construction of more efficient operations infrastructure. Lack of early ISHM inclusion in the system design process could result in retrofitting health management systems to augment and expand operational and safety requirements; thereby increasing program cost and risk due to increased instrumentation and computational complexity. Having the right sensors generating the required data to perform condition assessment, such as fault detection and isolation, with a high degree of confidence is critical to reliable operation of ISHM. Also, the data being generated by the sensors needs to be qualified to ensure that the assessments made by the ISHM is not based on faulty data. NASA Glenn Research Center has been developing technologies for sensor selection and data validation as part of the FDDR (Fault Detection, Diagnosis, and Response) element of the Upper Stage project of the Ares 1 launch vehicle development. This presentation will provide an overview of the GRC approach to sensor selection and data quality validation and will present recent results from applications that are representative of the complexity of propulsion systems for access to space vehicles. A brief overview of the sensor selection and data quality validation approaches is provided below. The NASA GRC developed Systematic Sensor Selection Strategy (S4) is a model-based procedure for systematically and quantitatively selecting an optimal sensor suite to provide overall health assessment of a host system. S4 can be logically partitioned into three major subdivisions: the knowledge base, the down-select iteration, and the final selection analysis. The knowledge base required for productive use of S4 consists of system design information and heritage experience together with a focus on components with health implications. The sensor suite down-selection is an iterative process for identifying a group of sensors that provide good fault detection and isolation for targeted fault scenarios. In the final selection analysis, a statistical evaluation algorithm provides the final robustness test for each down-selected sensor suite. NASA GRC has developed an approach to sensor data qualification that applies empirical relationships, threshold detection techniques, and Bayesian belief theory to a network of sensors related by physics (i.e., analytical redundancy) in order to identify the failure of a given sensor within the network. This data quality validation approach extends the state-of-the-art, from red-lines and reasonableness checks that flag a sensor after it fails, to include analytical redundancy-based methods that can identify a sensor in the process of failing. The focus of this effort is on understanding the proper application of analytical redundancy-based data qualification methods for onboard use in monitoring Upper Stage sensors.

Garg, Sanjay↗

Machine-Learned Committor Functions for Reactive Molecular Dynamics

Reactive molecular dynamics (MD) is a powerful tool for atomistic-scale modeling of a diverse range of chemical processes. However, scaling these simulations to large systems and long times scales remains a challenge because of the complexity of the potential energy function required. The authors previously developed a heuristic approach, called REACTER, that incorporates reactivity in MD simulations in a less general but much more computationally efficient manner. REACTER uses standard, fixed valence force fields as the underlying potentialenergy surface for describing all interatomic interactions but adds a procedure for enforcing user-defined reactions that occur when certain geometric constraints on relative atomic positions are satisfied. Further, these bonding changes can be accepted or rejected with a probability related tothe local thermal energy. This work seeks to generalize this approach by replacing the set of user defined geometric constraints and energetic criteria with a committor function that specifies the probability of a reaction occurring on the basis of the local atomic configuration. The committor function is a useful mathematical tool for modeling rare events but, unfortunately, is very difficult to compute for realistic systems in a general way. This work describes a method for approximating the committor function using a machine learning approach, specifically a deep neural network trained with data from reactive MD and DFT-based dynamics simulations. This network is coupled to the existing REACTER protocol, as implemented in the LAMMPS MD package, and used to make on-the-fly predictions of reaction probabilities without the more extensive user input previously required. The new method is demonstrated using the polymerization of polystyrene as a case study. Although very dependent on the quality and quantity of training data, machine-learned committor functions show promise as a method for incorporating reaction probability from higher level calculations into highly scalable MD simulations.

polymer simulations↗