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At least 577 records · Page 32

SMC: SCENIC Model Control

NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in Computer Science, two in Computer Engineering, one in Electrical Engineering, and one studying Space Systems Engineering.

Simulation↗

Computer networks for remote laboratories in physics and engineering

This paper addresses a relatively new approach to scientific research, telescience, which is the conduct of scientific operations in locations remote from the site of central experimental activity. A testbed based on the concepts of telescience is being developed to ultimately enable scientific researchers on earth to conduct experiments onboard the Space Station. This system along with background materials are discussed.

Starks, Scott↗

PrismTech Data Distribution Service Java API Evaluation

My internship duties with Launch Control Systems required me to start performance testing of an Object Management Group's (OMG) Data Distribution Service (DDS) specification implementation by PrismTech Limited through the Java programming language application programming interface (API). DDS is a networking middleware for Real-Time Data Distribution. The performance testing involves latency, redundant publishers, extended duration, redundant failover, and read performance. Time constraints allowed only for a data throughput test. I have designed the testing applications to perform all performance tests when time is allowed. Performance evaluation data such as megabits per second and central processing unit (CPU) time consumption were not easily attainable through the Java programming language; they required new methods and classes created in the test applications. Evaluation of this product showed the rate that data can be sent across the network. Performance rates are better on Linux platforms than AIX and Sun platforms. Compared to previous C++ programming language API, the performance evaluation also shows the language differences for the implementation. The Java API of the DDS has a lower throughput performance than the C++ API.

Riggs, Cortney↗

Cybersecurity Enhancement in Digital Substations: Hidden Markov Model-Based Smart Cyber Switching and Threat Response

The rising incidence of cyber-attacks on critical infrastructure and power grids poses significant threats to the stability and reliability of electrical substations, with potentially devastating consequences such as extended blackouts. This paper introduces an advanced cybersecurity framework aimed at safeguarding IEC 61850-based substations through the integration of software-defined networking (SDN) and digital twin (DT) technologies. The proposed DT-based framework employs smart cyber switching (SCS) for proactive threat mitigation and concurrent intelligent electronic device (CIED) for swift system restoration, thereby maintaining continuous operational integrity and robust cybersecurity defenses. Central to this framework is the adaptive port controller (APC), which enables dynamic port management to adapt to evolving threats, and an intrusion detection system (IDS) designed to detect and neutralize malicious attacks on IEC 61850-based sampled value (SV) and generic object-oriented substation event (GOOSE) messages within the substation’s communication network. Further, novel predictive intrusion detection and response (PIDR) algorithm is implemented on a digital substation (DS) to predict the best route to be taken by the attacker. The efficacy of these comprehensive cybersecurity frameworks is validated through rigorous simulations and a hardware-in-the-loop (HIL) testbed, showcasing the system’s ability to sustain substation operations amidst cyber-attacks.

Digital substation↗

Prospects of federated machine learning in fluid dynamics

Physics-based models have been mainstream in fluid dynamics for developing predictive models. In recent years, machine learning has offered a renaissance to the fluid community due to the rapid developments in data science, processing units, neural network based technologies, and sensor adaptations. So far in many applications in fluid dynamics, machine learning approaches have been mostly focused on a standard process that requires centralizing the training data on a designated machine or in a data center. In this article, we present a federated machine learning approach that enables localized clients to collaboratively learn an aggregated and shared predictive model while keeping all the training data on each edge device. We demonstrate the feasibility and prospects of such a decentralized learning approach with an effort to forge a deep learning surrogate model for reconstructing spatiotemporal fields. Our results indicate that federated machine learning might be a viable tool for designing highly accurate predictive decentralized digital twins relevant to fluid dynamics.

36 MATERIALS SCIENCE↗

Thermal Conductivity Studies of Sedimentary Materials from Central Australia and the Implications for Mars

In the search for life on Mars, investigating fluvial deposits will be a high priority for future landers. Although there is abundant evidence that fluvial processes worked with great intensity in the past (e.g., outflow channels, valley networks, and modified impact craters), aeolian processes dominate under the current environmental conditions. In fact there is evidence that extensive aeolian deposits may have filled in valley networks [1] and even shallow depressions where water may have ponded [2]. Thus, quite often there may be a disparity between the geology identified by orbital data and the geology accessible to a lander. Determining where fluvial deposits occur on the surface is important for addressing NASA's goal to "follow the water." In order to do that, however, existing remote sensing data must be evaluated and a set of diagnostic criteria for recognizing fluvial deposits must be established. To that end, we are conducting a first order analysis of the thermal characteristics of fluvial and aeolian materials collected from central Australia.

Craddock, Robert A.↗

The Effects of Long Duration Bed Rest as a Spaceflight Analogue on Resting State Sensorimotor Network Functional Connectivity and Neurocognitive Performance

Long duration spaceflight has been associated with detrimental alterations in human sensorimotor systems and neurocognitive performance. Prolonged exposure to a head-down tilt position during long duration bed rest can resemble several effects of the microgravity environment such as reduced sensory inputs, body unloading and increased cephalic fluid distribution. The question of whether microgravity affects other central nervous system functions such as brain functional connectivity and its relationship with neurocognitive performance is largely unknown, but of potential importance to the health and performance of astronauts both during and post-flight. The aims of the present study are 1) to identify changes in sensorimotor resting state functional connectivity that occur with extended bed rest exposure, and to characterize their recovery time course; 2) to evaluate how these neural changes correlate with neurocognitive performance. Resting-state functional magnetic resonance imaging (rsfMRI) data were collected from 17 male participants. The data were acquired through the NASA bed rest facility, located at the University of Texas Medical Branch (Galveston, TX). Participants remained in bed with their heads tilted down six degrees below their feet for 70 consecutive days. RsfMRI data were obtained at seven time points: 7 and 12 days before bed rest; 7, 50, and 65 days during bed rest; and 7 and 12 days after bed rest. Functional connectivity magnetic resonance imaging (fcMRI) analysis was performed to measure the connectivity of sensorimotor networks in the brain before, during, and post-bed rest. We found a decrease in left putamen connectivity with the pre- and post-central gyri from pre bed rest to the last day in bed rest. In addition, vestibular cortex connectivity with the posterior cingulate cortex decreased from pre to post bed rest. Furthermore, connectivity between cerebellar right superior posterior fissure and other cerebellar regions decreased from pre bed rest to the last day in bed rest. In contrast, connectivity within the default mode network remained stable over the course of bed rest. We also utilized a battery of behavioral measures including spatial working memory tasks and measures of functional mobility and balance. These behavioral measurements were collected before, during, and after bed rest. We will report the preliminary findings of correlations observed between brain functional connectivity and behavioral performance changes. Our results suggest that sensorimotor brain networks exhibit decoupling with extended periods of reduced usage. The findings from this study could aid in the understanding and future design of targeted countermeasures to alleviate the detrimental health and neurocognitive effects of long-duration spaceflight.

Cassady, K.↗

Cost analysis of distributed storage in AC and DC microgrids

Building and microgrid designs with highly-distributed electrical storage have potential advantages over today's conventional topologies with centralized storage. Herein this paper studies the capital cost benefits of several residential behind-the-meter distributed-storage topologies, including AC and DC versions of systems with load-packaged batteries and resilient sub-networks. The study begins by defining the block configuration of each topology. This work then develops a model for the cost of the power electronics necessary to interface with the storage elements. Finally, the analysis develops a model for the total cost of each storage topology, incorporating the installation and soft costs. The results suggest that while the cost of power electronics is lower in centralized topologies, the total cost is lower for distributed storage due to the avoided costs of installation and permitting. This paper also explores the benefits of load-packaged batteries for savings in electrical infrastructure.

25 ENERGY STORAGE↗

Privacy-preserving federated learning: Application to behind-the-meter solar photovoltaic generation forecasting

Here, the growing usage of decentralized renewable energy sources has made accurate estimation of their aggregated generation crucial for maintaining grid flexibility and reliability. However, the majority of distributed photovoltaic (PV) systems are behind-the-meter (BTM) and invisible to utilities, leading to three challenges in obtaining an accurate forecast of their aggregated output. Firstly, traditional centralized prediction algorithms used in previous studies may not be appropriate due to privacy concerns. There is therefore a need for decentralized forecasting methods, such as federated learning (FL), to protect privacy. Secondly, there has been no comparison between localized, centralized, and decentralized forecasting methods for BTM PV production, and the trade-off between prediction accuracy and privacy has not been explored. Lastly, the computational time of data-driven prediction algorithms has not been examined. This article presents a FL power forecasting method for PVs, which uses federated learning as a decentralized collaborative modeling approach to train a single model on data from multiple BTM sites. The machine learning network used to design this FL-based BTM PV forecasting model is a multi-layered perceptron, which ensures privacy and security of the data. Comparing the suggested FL forecasting model to non-private centralized and entirely private localized models revealed that it has a high level of accuracy, with an RMSE that is 18.17% lower than localized models and 9.9% higher than centralized models.

14 SOLAR ENERGY↗

Extreme Decentralized Water Treatment: Exploring the Future of Premise-Scale Water Treatment and Reuse

Access to an adequate quantity of piped water and management of wastewater produced in homes and businesses is an expectation of city dwellers in wealthy countries, and an aspiration for many people living in rapidly developing cities in low- and middle-income countries. It is also crucial to public health and protection of the environment. For well over a century, municipal drinking water provision and wastewater management have been made possible by large investments in centralized systems in which fresh water passes through a small number of drinking water treatment plants before being distributed through a vast underground pipe network to buildings throughout the city (Sedlak 2014). After it is used, wastewater is collected in underground sewers that route it to treatment plants prior to its discharge to the environment. In some water-stressed cities, a fraction of the treated wastewater undergoes additional treatment prior to reuse. This recycled water often is returned to users through another dedicated water distribution system, which is designated in many places with purple pipes (non-potable water reuse). Alternatively, treated wastewater may be subjected to advanced treatment (e.g., reverse osmosis followed by advanced oxidation) prior to being returned to the drinking water supply (potable water reuse).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Realizable feed-element patterns and optimum aperture efficiency in multibeam antenna systems

The results of an earlier paper by Rahmat-Samii et al. (1981), regarding realizable patterns from feed elements that are part of an array that feeds a reflector antenna, are extended. The earlier paper used a cos exp q theta model for the element radiation pattern, whereas here a parametric study is performed, using a model that assumes a central beam of cos exp q theta shape, with a constant sidelobe level outside the central beam. Realizable q-values are constrained by the maximum directivity based on feed element area. The optimum aperture efficiency (excluding array feed network losses) in an array-reflector system is evaluated as a function of element spacing using this model as well as the model of the earlier paper. Experimental data for tapered slot antenna (TSA) arrays are in agreement with the conclusions based on the model.

Yngvesson, K. S.↗

Geodetic measurement of deformation in the Ventura basin region, southern California

We have measured the deformation in the Ventura basin region, southern California, with Global Positioning System (GPS) measurements carried out over 4.6 years between 1987 and 1992. The deformation within our network is spatically variable on scales of tens of kilometers, with strain rates reaching 0.6 +/- 1 micro-rad/yr in the east-central basin. Blocklike rotations are observed south and northwest of the basin where the maximum shear strain rates are an order of magnitude lower (0.06 +/- 1 micro-rad/yr to the south). We also observed clockwise rotations of 1 deg - 7 deg/m.y. Shear strain rates determined by comparing angle changes from historical triangulation spanning several decades and GPS measurements give consistent, though less precise, results. The geodetic rates of shortening across the basin and Western Transverse Ranges are lower than those estimated from geological observations, but the patterns of deformation from the two methods agree qualitatively.

Donnellan, Andrea↗

Morphological evidence for local microcircuits in rat vestibular maculae

Previous studies suggested that intramacular, unmyelinated segments of vestibular afferent nerve fibers and their large afferent endings (calyces) on type I hair cells branch. Many of the branches (processes) contain vesicles and are presynaptic to type II hair cells, other processes, intramacular nerve fibers, and calyces. This study used serial section transmission electron microscopy and three-dimensional reconstruction methods to document the origins and distributions of presynaptic processes of afferents in the medial part of the adult rat utricular macula. The ultrastructural research focused on presynaptic processes whose origin and termination could be observed in a single micrograph. Results showed that calyces had 1) vesiculated, spine-like processes that invaginated type I cells and 2) other, elongate processes that ended on type II cells pre- as well as postsynaptically. Intramacular, unmyelinated segments of afferent nerve fibers gave origin to branches that were presynaptic to type II cells, calyces, calyceal processes, and other nerve fibers in the macula. Synapses with type II cells occurred opposite subsynaptic cisternae (C synapses); all other synapses were asymmetric. Vesicles were pleomorphic but were differentially distributed according to process origin. Small, clear-centered vesicles, approximately 40-60 nm in diameter, predominated in processes originating from afferent nerve fibers and basal parts of calyces. Larger vesicles approximately 70-120 nm in diameter having approximately 40-80 nm electron-opaque cores were dominant in processes originating from the necks of calyces. Results are interpreted to indicate the existence of a complex system of intrinsic feedforward (postsynaptic)-feedback (presynaptic) connections in a network of direct and local microcircuits. The morphological findings support the concept that maculae dynamically preprocess linear acceleratory information before its transmission to the central nervous system.

NASA Center ARC↗

Spatial Correlation and Coherence of Boundary Layer Winds Near Cape Canaveral Florida

The spatial correlation and coherence of winds over separation distances from 8.5 to 31 km based on central Florida data from November 1999 through August 2001 are presented. The winds at altitudes from 500 to 3000 m were measured using a network of five radar wind profilers. The goal was to determine the extent to which the profilers may be considered independent data sources. Quality controlled profiles were produced every 15 minutes for up to sixty gates, each representing 101 m in altitude over the range from 130 m to 6089 m. Five levels, each containing three consecutive gates, were selected for analysis. These levels covered the range from 433 to 3059 m. The results show that the profilers are independent for features having time scales of less than one hour in the winter or two hours in the summer. This does not depend significantly on height. Because the size of the network coincides with the "spectral gap" in the boundary layer, the result also does not depend on the spacing of the profilers within the network.

Merceret, Francis J.↗

Characterization Study of TestBed Infrastructure Performance in a Distributed Simulation Environment: Baseline Analysis

Characterization of the performance of Air Traffic Management Exploration (ATM-X) TestBed integration environment has been investigated and documented for one system configuration for progressively increasing traffic. Several statistical parameters were used to assess the performance of the TestBed distributed system such as mean, standard deviation, skewness, and kurtosis of latency, and update rate for aircraft state messages that are transmitted through the simulated system under investigation. It is necessary to assess the performance characteristics of distributed systems in terms of the indicated statistical parameters mentioned above. It is critical to verify the system performance with respect to a researcher’s required system performance. Computer host specifications are documented in terms of Central Processing Unit (CPU) clock speed and core count. Transmission Control Protocol/ Internet Protocol (TCP/IP) message protocol was used for data transmission. The system network topology also contributes to the latency and update rate variations from the one imposed by the data source. The motivation for selecting the TestBed infrastructure as the focus of this study can be attributed to the number of services and capabilities it provides that help simplify the process of preparing and conducting a simulation. These capabilities include an easy to use GUI for simulation configuration, access to TestBed library by the end-user of other simulation software components, a modular adapter paradigm that allows simple connectivity of external software to TestBed, connectivity with other simulation laboratories, and a Software Development Kit (SDK) for quicker development. Two types of traffic generators, Air Traffic Generator (ATG) and Multi Aircraft Control System (MACS) were used to generate messages that were injected into the TestBed distributed environment. Eight different air traffic scenarios with progressively increasing loads were generated for each air traffic simulator. The corresponding air traffic loads between the two simulators had an identical number of aircraft per scenario, but different flight plans. It was observed that the performance of MACS degraded for air traffic scenarios containing more than 200 aircraft (37.5 KB/s nominal throughput). However, ATG performed adequately under all tested air traffic loads up to 1200 aircraft (225. KB/s nominal throughput). The tests show that MACS exhibits better latency performance with smaller aircraft loads when compared to ATG. The tests also show that the TestBed infrastructure successfully transmits 1200 aircraft without significant degradation of its performance. From the latency trends for both MACS and ATG, it is clear that as aircraft load increases, the latency in the system increases as well as its standard deviation. Likewise, the trends for the update data rate for both MACS and ATG show that as the aircraft load increases, so does the standard deviation and mean of the update rates which can be attributed to the performance of MACS and ATG applications. The analysis of the results of this study have proven that the overall system performance is dependent on the individual performance of each system component that is connected to TestBed, which subsequently propagates into the system. All TestBed characterization tests were conducted in SimLabs at NASA Ames Research Center in November 2019. This study addresses the need for a baseline TestBed characterization, and the results will serve as a reference for more complex simulation systems.

Air Traffic Management simulations↗

The Neuroendocrinology of Thirst and Salt Appetite: Visceral Sensory Signals and Mechanisms of Central Integration

This review examines recent advances in the study of the behavioral responses to deficits of body water and body sodium that in humans are accompanied by the sensations of thirst and salt appetite. Thirst and salt appetite are satisfied by ingesting water and salty substances. These behavioral responses to losses of body fluids, together with reflex endocrine and neural responses, are critical for reestablishing homeostasis. Like their endocrine and neural counterparts, these behaviors are under the control of both excitatory and inhibitory influences arising from changes in osmolality, endocrine factors such as angiotensin and aldosterone, and neural signals from low and high pressure baroreceptors. The excitatory and inhibitory influences reaching the brain require the integrative capacity of a neural network which includes the structures of the lamina terminalis, the amygdala, the perifornical area, and the paraventricular nucleus in the forebrain, and the lateral parabrachial nucleus (LPBN), the nucleus tractus solitarius (NTS), and the area postrema in the hindbrain. These regions are discussed in terms of their roles in receiving afferent sensory input and in processing information related to hydromineral balance. Osmoreceptors controlling thirst are located in systemic Viscera and in central structures that lack the blood-brain barrier. Angiotensin and aldosterone act on and through structures of the lamina terminalis and the amygdala to stimulate thirst and sodium appetite under conditions of hypovolemia. The NTS and LPBN receive neural signals from baroreceptors and are responsible for inhibiting the ingestion of fluids under conditions of increased volume and pressure and for stimulating thirst under conditions of bypovolemia and hypotension. The interplay of multiple facilitory influences within the brain may take the form of interactions between descending angiotensinergic systems originating in the forebrain and ascending adrenergic systems emanating from the hindbrain. Oxytocin and serotonin are additional candidate neuro- chemicals with postulated inhibitory central actions and with essential roles in the overall integration of sensory input within the neural network devoted to maintaining hydromineral balance.

Johnson, Alan Kim↗

Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints

The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution.

25 ENERGY STORAGE↗

Decentralized Schemes with Overlap for Solving Graph-Structured Optimization Problems

We present a new algorithmic paradigm for the decentralized solution of graph-structured optimization problems that arise in the estimation and control of network systems. A key and novel design concept of the proposed approach is that it uses overlapping subdomains to promote and accelerate convergence. We show that the algorithm converges if the size of the overlap is sufficiently large and that the convergence rate improves exponentially with the size of the overlap. The proposed approach provides a bridge between fully decentralized and centralized architectures and is flexible in that it enables the implementation of asynchronous schemes, handling of constraints, and balancing of computing, communication, and data privacy needs. The proposed scheme is tested in an estimation problem for a 9241-node power network and we show that it outperforms the alternating direction method of multipliers.

asynchronous↗