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At least 523 records · Page 29

Blockchain Application Within a Multi-Sensor Satellite Architecture

With the thrust towards multi-sensor satellite architectures for earth and space exploration, such as constellations and swarms, new technologies are required to enable the transition to this future capability. One of the areas of interest is establishing secure, efficient and prioritized data and command communication pathways among ground and space-based sources for such systems. This paper presents early research results on the potential role, capabilities and value of blockchain usage within constellation and swarm satellite architectures. It demonstrates the use of blockchain's smart contract and distributed ledger capabilities for secure and prioritized multi-sensor satellite collaborative data exchanges, as well as the logging and tracking of command and control events. Adapting and utilizing this emerging technology will aid in addressing technology gaps expected from future constellation flight architectures, such as managing collective computational operations (correlation), dynamic and autonomous observation planning, time-critical events, and provenance tied to ground and space-based autonomous operations and control recordkeeping. In this scenario blockchain is applied in encrypted command transmittal to multiple, yet specific, entities enabling acknowledgement transmittals, performance scalability, and automatic event-based triggering.

Mital, Rohit↗

Dynamic Cloud-Based Data Collection System

A schema-less cloud-based distributed data collection system with dynamic validation and comprehensive system status and alerting provided a reconfigurable data collection system to solve evolving incoming data schemas. Successful adaptation of the dynamic validation was useful in conforming to the evolution of incoming data.

dynamic data collection↗

Elliptic-Cylindrical Analytical Flux Rope Model for Magnetic Clouds

In this paper, we present the elliptic-cylindrical analytical flux rope model, which constitutes the first level of complexity above that of a circular-cylindrical geometry. The framework of this series of models was established by Nieves-Chinchilla et al. with the circular-cylindrical analytical flux rope model. The model describes the magnetic flux rope topology with distorted cross section as a possible consequence of the flux rope interaction with the solar wind. In this model, for the first time, a flux rope is completely described by a nonorthogonal geometry. The Maxwell equations can be consistently solved using tensorial analysis, and relevant physical quantities can be derived, such as magnetic fluxes, number of turns, or Lorentz force distribution. The model is generalized in termsof the radial dependence of the poloidal and axial current density components. The circular-cylindrical reconstruction technique has been adapted to the new geometry for a specific case of the model and tested againstan interplanetary coronal mass ejection observed by the Wind spacecraft on 2005 June 12. In this specific case,from the comparative analysis between the circular-cylindrical and elliptic-cylindrical models, the inclusion ofthe cross-section distortion in the 3D reconstruction results in significant changes in the derived axis orientation,size, central magnetic field, magnetic fluxes, and force-freeness. The case studied in this paper exemplifies the useof the model and reconstruction technique developed. Furthermore, the novel mathematical formulation to modelflux ropes in heliophysics paves the way to the inclusion of more complex magnetic field configurations.

CMEs↗

Transitioning a Flexible and Scalable Satellite Ground Station Observation Network (GSON) Framework to an Operational Environment

Obtaining accurate and timely satellite observations is of paramount importance in fields like disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing. Stored mission data (SMD), from low Earth orbiting (LEO) satellite sensors, provides important observations for these fields and applications, however data access to SMD can be delayed from one and half hours to three hours from the time the observations were made. This data latency poses a significant impact on data product optimal use. We developed a Ground Station Observation Network (GSON) that utilizes commercial ground station as a service (GSaaS) providers to acquire low latency direct broadcast (DB) data from AQUA, SNPP, and JPSS-1 satellites using antennas located in strategic locations around the world. We will discuss techniques to improve the deployment efficiency and code reliability and quality of the GSON framework. Topics include right-sizing and containerization of the code to facilitate integration and adaptation with continuous delivery (CD) pipeline, locating non-code assets in referenceable repositories separated from code, adaptation of pipelines as code and simplification of CD, intersecting with code quality tests and checks as part of the pipeline execution and deployment, and establishing distributed repositories, registries, and system identities in a way that mitigates compromise to the CD pipeline. These techniques enable deployment of processing systems that are both highly specific but also dynamically modifiable. This new class of system allows for a flexible and scalable deployment while avoiding the “black box” issues that can plague large system deployments.

cluster↗

Role of Vibration-Induced Streaming in Float-Zone Crystal Growth

This presentation will examine in detail the role of vibration-induced streaming flow in the context of float-zone crystal growth. It is very well known that during float-zone materials processing, the naturally occurring temperature gradients along the zone surface impose a thermocapillary flow in the zone. Under certain processing conditions, the thermocapillary flow can also become nonsteady (oscillatory). The presence of thermocapillary flow is detrimental to crystal quality, for it can promote non-uniform dopant distribution and crystal striations. To null this effect we have imposed a counter streaming flow in the zone, via end-wall vibration. This technique has been adapted to float-zone processing of Sodium Nitrate-Barium Nitrate eutectic alloys, under both steady and nonsteady thermocapillary flow conditions. The beneficial effects of counter streaming flow have been clearly brought out through the before and after comparisons of the crystal microstructure. In addition, we are also examining the theoretical underpinnings of the balancing of thermocapillary flows with vibration-driven counter flows in float-zones.

Anilkumar, A. V.↗

Role of Vibration-Induced Streaming in Float-Zone Crystal Growth

This presentation will examine in detail the role of vibration-induced streaming flow in the context of float-zone crystal growth. It is very well known that during float-zone materials processing, the naturally occurring temperature gradients along the zone surface impose a thermocapillary flow in the zone. Under certain processing conditions, the thermocapillary flow can also become nonsteady (oscillatory). The presence of thermocapillary flow is detrimental to crystal quality, for it can promote non-uniform dopant distribution and crystal striations. To null this effect we have imposed a counter streaming flow in the zone, via end-wall vibration. This technique has been adapted to float-zone processing of Sodium Nitrate-Barium Nitrate eutectic alloys, under both steady and nonsteady thermocapillary flow conditions. The beneficial effects of counter streaming flow have been clearly brought out through the before and after comparisons of the crystal microstructure. In addition, we are also examining the theoretical underpinnings of the balancing of thermocapillary flows with vibration-driven counter flows in float-zones.

Anikumar, A. V.↗

New challenges for Life Sciences flight project management

Scientists have conducted studies involving human spaceflight crews for over three decades. These studies have progressed from simple observations before and after each flight to sophisticated experiments during flights of several weeks up to several months. The findings from these experiments are available in the scientific literature. Management of these flight experiments has grown into a system fashioned from the Apollo Program style, focusing on budgeting, scheduling and allocation of human and material resources. While these areas remain important to the future, the International Space Station (ISS) requires that the Life Sciences spaceflight experiments expand the existing project management methodology. The use of telescience with state-the-art information technology and the multi-national crews and investigators challenges the former management processes. Actually conducting experiments on board the ISS will be an enormous undertaking and International Agreements and Working Groups will be essential in giving guidance to the flight project management Teams forged in this matrix environment must be competent to make decisions and qualified to work with the array of engineers, scientists, and the spaceflight crews. In order to undertake this complex task, data systems not previously used for these purposes must be adapted so that the investigators and the project management personnel can all share in important information as soon as it is available. The utilization of telescience and distributed experiment operations will allow the investigator to remain involved in their experiment as well as to understand the numerous issues faced by other elements of the program The complexity in formation and management of project teams will be a new kind of challenge for international science programs. Meeting that challenge is essential to assure success of the International Space Station as a laboratory in space.

NASA Discipline General Space Life Sciences↗

Risk of Performance and Behavioral Health Decrements Due to Inadequate Cooperation, Coordination, Communication, and Psychosocial Adaptation within a Team

A team is defined as: "two or more individuals who interact socially and adaptively, have shared or common goals, and hold meaningful task interdependences; it is hierarchically structured and has a limited life span; in it expertise and roles are distributed; and it is embedded within an organization/environmental context that influences and is influenced by ongoing processes and performance outcomes" (Salas, Stagl, Burke, & Goodwin, 2007, p. 189). From the NASA perspective, a team is commonly understood to be a collection of individuals that is assigned to support and achieve a particular mission. Thus, depending on context, this definition can encompass both the spaceflight crew and the individuals and teams in the larger multi-team system who are assigned to support that crew during a mission. The Team Risk outcomes of interest are predominantly performance related, with a secondary emphasis on long-term health; this is somewhat unique in the NASA HRP in that most Risk areas are medically related and primarily focused on long-term health consequences. In many operational environments (e.g., aviation), performance is assessed as the avoidance of errors. However, the research on performance errors is ambiguous. It implies that actions may be dichotomized into "correct" or "incorrect" responses, where incorrect responses or errors are always undesirable. Researchers have argued that this dichotomy is a harmful oversimplification, and it would be more productive to focus on the variability of human performance and how organizations can manage that variability (Hollnagel, Woods, & Leveson, 2006) (Category III1). Two problems occur when focusing on performance errors: 1) the errors are infrequent and, therefore, difficult to observe and record; and 2) the errors do not directly correspond to failure. Research reveals that humans are fairly adept at correcting or compensating for performance errors before such errors result in recognizable or recordable failures. Astronauts are notably adept high performers. Most failures are recorded only when multiple, small errors occur and humans are unable to recognize and correct or compensate for these errors in time to prevent a failure (Dismukes, Berman, Loukopoulos, 2007) (Category III). More commonly, observers record variability in levels of performance. Some teams commit no observable errors but fail to achieve performance objectives or perform only adequately, while other teams commit some errors but perform spectacularly. Successful performance, therefore, cannot be viewed as simply the absence of errors or the avoidance of failure Johnson Space Center (JSC) Joint Leadership Team, 2008). While failure is commonly attributed to making a major error, focusing solely on the elimination of error(s) does not significantly reduce the risk of failure. Failure may also occur when performance is simply insufficient or an effort is incapable of adjusting sufficiently to a contextual change (e.g., changing levels of autonomy).

Landon, Lauren Blackwell↗

Accelerated Simulation of Air Pollution Using NVIDIA RAPIDS

Atmospheric chemistry models are a central tool to study and forecast the impact of air pollution on the environment, vegetation, and human health. However, the numerical simulation of chemical kinetics is computationally expensive due to the stiffness of the system of ordinary differential equations that describes atmospheric chemistry. Here we present an alternative approach to the computation of atmospheric chemistry based on machine learning. Our training data set is produced using the NASA Goddard Earth Observing System (GEOS) model with GEOS-Chem chemistry, run on the NASA Center for Climate Simulation (NCCS) Discover supercomputing cluster on 384 Intel Xeon Haswell cores. This model spends more than 50% of total run time on solving atmospheric chemistry. The data set contains as input features the air pollution concentrations before solving the differential equations, together with some key physical parameters such as temperature and sun intensity. As target variables we define the air pollution concentrations after solving the differential equations. Using Dask-cuDF and Dask-XGBoost on the NVIDIA RAPIDS platform on 8 Tesla V100 GPUs, we generate from this training set gradient boosted decision tree models that can reproduce the simulation of chemical kinetics. We do this on the NCCS Advanced Data Analytics Platform (ADAPT) science cloud environment. Our application takes full advantage of recent advances in Dask-XGBoost, such as multi-node and multi-GPU scaling for distributed training with large data sets. The increase in training data size enabled by this is critical to capture the full range of chemical environments encountered across the globe and all annual seasons.The boosted tree models offer good predictability and show many of the features of the full chemistry reference simulation. Further improvements can be achieved through mass balance considerations and by accounting for error correlations. We incorporate the boosted tree models into the GEOS reference model using XGBoost's C API. This enables a seamless integration of the GPU trained models into GEOS-Chem, which is written in Fortran and optimized for use in a massively parallel CPU environment. We show the benefits of this approach and discuss the potential speedup of this machine learning accelerated atmospheric chemistry model.

Keller, Christoph A.↗

Surveillance system and method having an adaptive sequential probability fault detection test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Herzog, James P.↗

Surveillance system and method having an adaptive sequential probability fault detection test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Bickford, Randall L.↗

Surveillance System and Method having an Adaptive Sequential Probability Fault Detection Test

System and method providing surveillance of an asset such as a process and/or apparatus by providing training and surveillance procedures that numerically fit a probability density function to an observed residual error signal distribution that is correlative to normal asset operation and then utilizes the fitted probability density function in a dynamic statistical hypothesis test for providing improved asset surveillance.

Bickford, Randall L.↗

Far-field radiation pattern of tunable diode lasers

Technique rapidly determines far-field spatial energy distribution. Method takes about 3 minutes. It is optically simple and is economical, using standard laboratory parts and equipment. It records automatically without operator control and is easily adaptable to computer control of input instructions and computer treatment of output data. Degree of data resolution is limted only by width of recorder pen, and data are repeatable.

Lash, T. J.↗

Development of computer models for the prediction of large distorted antenna characteristics

A program for calculating the radiation patterns of analytic reflector antennas, using geometric optics and aperture plane integration techniques, was modified and extended to include nonanalytic surfaces. The original program, while capable of predicting patterns for a variety of reflectors, both smooth and multipanelled, was subject to the restriction that the surface had to be expressed analytically, i.e., described by a set of mathematical equations. This restriction was removed by adapting a technique which allows the reflector configuration to be interpolated from a finite set of points measured on the surface. Criteria for choosing both the number and distribution of these measured surface points were developed by comparing the predicted antenna radiation patterns with measured laboratory results. Test cases involved relatively smooth as well as grossly distorted arbitrary surfaces. Finally, surface point accuracies were established by applying random error analysis to the measurement process.

Moskowitz, S. M.↗

3-D components of a biological neural network visualized in computer generated imagery. II - Macular neural network organization

Computer-assisted reconstructions of small parts of the macular neural network show how the nerve terminals and receptive fields are organized in 3-dimensional space. This biological neural network is anatomically organized for parallel distributed processing of information. Processing appears to be more complex than in computer-based neural network, because spatiotemporal factors figure into synaptic weighting. Serial reconstruction data show anatomical arrangements which suggest that (1) assemblies of cells analyze and distribute information with inbuilt redundancy, to improve reliability; (2) feedforward/feedback loops provide the capacity for presynaptic modulation of output during processing; (3) constrained randomness in connectivities contributes to adaptability; and (4) local variations in network complexity permit differing analyses of incoming signals to take place simultaneously. The last inference suggests that there may be segregation of information flow to central stations subserving particular functions.

Ross, Muriel D.↗

Design alternatives for process group membership and multicast

Process groups are a natural tool for distributed programming, and are increasingly important in distributed computing environments. However, there is little agreement on the most appropriate semantics for process group membership and group communication. These issues are of special importance in the Isis system, a toolkit for distributed programming. Isis supports several styles of process group, and a collection of group communication protocols spanning a range of atomicity and ordering properties. This flexibility makes Isis adaptable to a variety of applications, but is also a source of complexity that limits performance. This paper reports on a new architecture that arose from an effort to simplify Isis process group semantics. Our findings include a refined notion of how the clients of a group should be treated, what the properties of a multicast primitive should be when systems contain large numbers of overlapping groups, and a new construct called the casuality domain. As an illustration, we apply the architecture to the problem of converting processes into fault-tolerant process groups in a manner that is 'transparent' to other processes in the system.

Birman, Kenneth P.↗

Performance of a focused cavity aerosol spectrometer for measurements in the stratosphere of particle size in the 0.06-2.0-micrometer-diameter range

A focused cavity aerosol spectrometer aboard a NASA ER-2 high-altitude aircraft provided high-resolution measurements of the size of the stratospheric particles in the 0.06-2.0-micrometer-diameter range in flights following the eruption of Mount Pinatubo in 1991. Effects of anisokinetic sampling and evaporation in the sampling system were accounted for by means adapted and specifically developed for this instrument. Calibrations with monodisperse aerosol particles provided the instrument's response matrix, which upon inversion during data reduction yielded the particle size distributions. The resultant dataset is internally consistent and generally shows agreement to within a factor of 2 with comparable measurements simultaneously obtained by a condensation nuclei counter, a forward-scattering spectrometer probe, and aerosol particle impactors, as well as with nearby extinction profiles obtained by satellite measurements and with lidar measurements of backscatter.

Jonsson, H. H.↗

Research in Parallel Algorithms and Software for Computational Aerosciences

Phase 1 is complete for the development of a computational fluid dynamics CFD) parallel code with automatic grid generation and adaptation for the Euler analysis of flow over complex geometries. SPLITFLOW, an unstructured Cartesian grid code developed at Lockheed Martin Tactical Aircraft Systems, has been modified for a distributed memory/massively parallel computing environment. The parallel code is operational on an SGI network, Cray J90 and C90 vector machines, SGI Power Challenge, and Cray T3D and IBM SP2 massively parallel machines. Parallel Virtual Machine (PVM) is the message passing protocol for portability to various architectures. A domain decomposition technique was developed which enforces dynamic load balancing to improve solution speed and memory requirements. A host/node algorithm distributes the tasks. The solver parallelizes very well, and scales with the number of processors. Partially parallelized and non-parallelized tasks consume most of the wall clock time in a very fine grain environment. Timing comparisons on a Cray C90 demonstrate that Parallel SPLITFLOW runs 2.4 times faster on 8 processors than its non-parallel counterpart autotasked over 8 processors.

Domel, Neal D.↗