SEARCH · Search NASA
Results for “network systems”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Intelligent Wireless Sensor Networks for System Health Monitoring
Wireless sensor networks (WSN) based on the IEEE 802.15.4 Personal Area Network (PAN) standard are finding increasing use in the home automation and emerging smart energy markets. The network and application layers, based on the ZigBee 2007 Standard, provide a convenient framework for component-based software that supports customer solutions from multiple vendors. WSNs provide the inherent fault tolerance required for aerospace applications. The Discovery and Systems Health Group at NASA Ames Research Center has been developing WSN technology for use aboard aircraft and spacecraft for System Health Monitoring of structures and life support systems using funding from the NASA Engineering and Safety Center and Exploration Technology Development and Demonstration Program. This technology provides key advantages for low-power, low-cost ancillary sensing systems particularly across pressure interfaces and in areas where it is difficult to run wires. Intelligence for sensor networks could be defined as the capability of forming dynamic sensor networks, allowing high-level application software to identify and address any sensor that joined the network without the use of any centralized database defining the sensors characteristics. The IEEE 1451 Standard defines methods for the management of intelligent sensor systems and the IEEE 1451.4 section defines Transducer Electronic Datasheets (TEDS), which contain key information regarding the sensor characteristics such as name, description, serial number, calibration information and user information such as location within a vehicle. By locating the TEDS information on the wireless sensor itself and enabling access to this information base from the application software, the application can identify the sensor unambiguously and interpret and present the sensor data stream without reference to any other information. The application software is able to read the status of each sensor module, responding in real-time to changes of PAN configuration, providing the appropriate response for maintaining overall sensor system function, even when sensor modules fail or the WSN is reconfigured. The session will present the architecture and technical feasibility of creating fault-tolerant WSNs for aerospace applications based on our application of the technology to a Structural Health Monitoring testbed. The interim results of WSN development and testing including our software architecture for intelligent sensor management will be discussed in the context of the specific tradeoffs required for effective use. Initial certification measurement techniques and test results gauging WSN susceptibility to Radio Frequency interference are introduced as key challenges for technology adoption. A candidate Developmental and Flight Instrumentation implementation using intelligent sensor networks for wind tunnel and flight tests is developed as a guide to understanding key aspects of the aerospace vehicle design, test and operations life cycle.
IEEE 342 Node Low Voltage Networked Test System
The IEEE Distribution Test Feeders provide a benchmark for new algorithms to the distribution analyses community. The low voltage network test feeder represents a moderate size urban system that is unbalanced and highly networked. This is the first distribution test feeder developed by the IEEE that contains unbalanced networked components. The 342 node Low Voltage Networked Test System includes many elements that may be found in a networked system: multiple 13.2kV primary feeders, network protectors, a 120/208V grid network, and multiple 277/480V spot networks. This paper presents a brief review of the history of low voltage networks and how they evolved into the modern systems. This paper will then present a description of the 342 Node IEEE Low Voltage Network Test System and power flow results.
Ripple-type control of networked physical systems
Techniques for ripple-type control of networked physical systems such as power systems, water systems, and others are provided. As one example, a device includes at least one processor configured to determine, for a first controllable device in a system, based on a measurement of an output parameter and a minimum output parameter value, an output violation value for the first device. The processor is further configured to determine, based on a present input value for the first device, the output violation value, and an assistance requisition value corresponding to a second device, a target input value for the first device. The processor is further configured to cause the first controllable device to modify operation based on the target input value and a maximum input value for the first controllable device.
The Network Information Management System (NIMS) in the Deep Space Network
In an effort to better manage enormous amounts of administrative, engineering, and management data that is distributed worldwide, a study was conducted which identified the need for a network support system. The Network Information Management System (NIMS) will provide the Deep Space Network with the tools to provide an easily accessible source of valid information to support management activities and provide a more cost-effective method of acquiring, maintaining, and retrieval data.
Documentation for the token ring network simulation system
A manual is presented which describes the language features of the Token Ring Network Simulation System. The simulation system is a powerful simulation tool for token ring networks which allows the specification of various Medium Access Control (MAC) layer protocols as well as the specification of various features of upper layer ISO protocols. In addition to these features, it also allows the user to specify message and station classes virtually to any degree of detail desired. The choice of a language instead of an interactive system to specify network parameters was dictated by both flexibility and time considerations. The language was developed specifically for the simulation system, and is very simple. It is also user friendly in that language elements which do not apply to the case at hand are ignored rather than treated as errors.
Data-driven Vulnerability Analysis of Networked Pipeline System
This paper introduces an attack generation framework for evaluating the vulnerability of nonlinear networked pipeline systems. The vulnerability analysis is formulated as determining the presence of feasible attack sets, defined by boundary functions representing the effectiveness and stealthiness of attack signals with respect to the objective and attack detection module. The framework utilizes three data-driven models, including two discriminative models that learn the boundary functions and a generative model that produces elements of the feasible attack set. A new loss function ensures successful attack generation with high probability.
Field operations with cesium clocks in HF navigation systems
Networks of HF phase comparison marine navigation stations employing cesium clocks are discussed. The largest permanent network is in the Gulf of Mexico where some fourteen base stations are continuously active and others are activated as needed. These HF phase comparison systems, which operate on a single transmission path, require a clock on the mobile unit as well. Inventory consists of upwards of 70 clocks from two different manufacturers. The maintenance of this network as an operating system requires a coordinated effort involving clock preparation, clock environment control, station performance monitoring and field service.
Online Primal-Dual Methods With Measurement Feedback for Time-Varying Convex Optimization
This paper addresses the design and analysis of feedback-based online algorithms to control systems or networked systems based on performance objectives and engineering constraints that may evolve over time. The emerging timevarying convex optimization formalism is leveraged to model optimal operational trajectories of the systems, as well as explicit local and network-level operational constraints. Departing from existing batch and feed-forward optimization approaches, the design of the algorithms capitalizes on an online implementation of primal-dual projected-gradient methods; the gradient steps are, however, suitably modified to accommodate feedback from the system in the form of measurements - hence, the term 'online optimization with feedback.' By virtue of this approach, the resultant algorithms can cope with model mismatches in the algebraic representation of the system states and outputs, they avoid pervasive measurements of exogenous inputs, and they naturally lend themselves to a distributed implementation. Under suitable assumptions, analytical convergence claims are established in terms of dynamic regret. Furthermore, when the synthesis of the feedback-based online algorithms is based on a regularized Lagrangian function, Q-linear convergence to solutions of the time-varying optimization problem is shown.
Dissipative rendering and neural network control system design
Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.
The network queueing system
Described is the implementation of a networked, UNIX based queueing system developed on contract for NASA. The system discussed supports both batch and device requests, and provides the facilities of remote queueing, request routing, remote status, queue access controls, batch request resource quota limits, and remote output return.
Effective restoration strategies of interdependent power system and communication network
The power system is continuously evolving towards a smarter grid by adding intelligent electrical devices that leverage communication technologies to provide visualisation, control and automation. The integration of power system and communication network has brought challenges into the resilience of interdependent networks. Following an outage or blackout, system operators cannot only restore one network while simply ignoring the interconnection with the other network. Effective restoration strategies that involve co‐ordination between power system and communication network have become critical in enhancing the resilience. An optimisation‐based restoration strategy is developed to coordinate the restoration actions between two networks. The problem is modelled as a mixed integer linear programming problem, with the objective of activating every node in both networks with the minimum number of activation/energisation of branches. The developed strategies are tested on the modified IEEE 14‐bus system incorporating communication network. Simulation results demonstrate that the coordinated restoration strategies are effective and critical in the successful recovery of interdependent networks. The developed model could also provide insights in network design and planning to enhance the resilience of interdependent power system and communication network.
The Deep Space Network Tracking System, Mark 4-A, 1986
The Deep Space Network (DSN) Tracking System provides highly precise measurements of spacecraft Doppler and range. It was recently extensively modified as part of the Mark 4-A implementation. The DSN Tracking System as currently implemented, its performance in support of Voyager 2, and plans for new implementation are described.
A High Performance Computing Network and System Simulator for the Power Grid: NGNS^2
Designing and planing next generation power grid sys- tems composed of large power distribution networks, monitoring and control networks, autonomous generators and consumers of power requires advanced simulation infrastructures. The objective is to predict and analyze in time the behavior of networks of systems for unexpected events such as loss of connectivity, malicious attacks and power loss scenarios. This ultimately allows one to answer questions such as: “What could happen to the power grid if ...”. We want to be able to answer as many questions as possible in the shortest possible time for the largest possible systems. In this paper we present a new High Performance Computing (HPC) oriented simulation infrastructure named Next Generation Network and System Simulator (NGNS2 ). NGNS2 allows for the distribution of a single simulation among multiple computing elements by using MPI and OpenMP threads. NGNS2 provides extensive configuration, fault tolerant and load balancing capabilities needed to simulate large and dynamic systems for long periods of time. We show the preliminary results of the simulator running approximately two million simulated entities both on a 64-node commodity Infiniband cluster and a 48-core SMP workstation.
NMESys: An expert system for network fault detection
The problem of network management is becoming an increasingly difficult and challenging task. It is very common today to find heterogeneous networks consisting of many different types of computers, operating systems, and protocols. The complexity of implementing a network with this many components is difficult enough, while the maintenance of such a network is an even larger problem. A prototype network management expert system, NMESys, implemented in the C Language Integrated Production System (CLIPS). NMESys concentrates on solving some of the critical problems encountered in managing a large network. The major goal of NMESys is to provide a network operator with an expert system tool to quickly and accurately detect hard failures, potential failures, and to minimize or eliminate user down time in a large network.
Stochastic approximation methods-Powerful tools for simulation and optimization: A survey of some recent work on multi-agent systems and cyber-physical systems
Stochastic approximation methods have found extensive and diversified applications. Recent emergence of networked systems and cyber-physical systems has generated renewed interest in advancing stochastic approximation into a general framework to support algorithm development for information processing and decisions in such systems. This paper presents a survey on some recent developments in stochastic approximation methods and their applications. Using connected vehicles in platoon formation and coordination as a platform, we highlight some traditional and new methodologies of stochastic approximation algorithms and explain how they can be used to capture essential features in networked systems. Distinct features of networked systems with randomly switching topologies, dynamically evolving parameters, and unknown delays are presented, and control strategies are provided.
Design-to-Deployment Continuum Platform for Microscopes and Computing Ecosystems
Science ecosystems with networked computing systems and physical instruments are increasingly being deployed with a goal to achieve the productivity promised by AI-supported remote automation. In support of these efforts, the virtual infrastructure twins (VITs) have been successfully utilized to develop the orchestration codes for these ecosystems without requiring physical access to expensive instruments, such as electron microscopes. Currently, the utility of such a VIT is severely limited by the computing capacity and capability of the computing system used as its host. Furthermore, codes developed on the VIT typically need to be transferred and refactored for production use, particularly, on high-performance systems with accelerators. In response, we develop a design-to-deployment continuum platform wherein a VIT runs natively on the ecosystem's own computing system, and thereby facilitates the continual in-situ testing and transition of codes for production use. Here, we describe the development and testing of software for remote microscope steering and GPU-based image reconstruction using this platform on a multi-GPU computing system networked to Nion microscopes. We demonstrate a continual transition of steering and reconstruction codes developed under VIT platform to production ecosystem deployment.
Study of optical techniques for the Ames unitary wind tunnel: Digital image processing, part 6
A survey of digital image processing techniques and processing systems for aerodynamic images has been conducted. These images covered many types of flows and were generated by many types of flow diagnostics. These include laser vapor screens, infrared cameras, laser holographic interferometry, Schlieren, and luminescent paints. Some general digital image processing systems, imaging networks, optical sensors, and image computing chips were briefly reviewed. Possible digital imaging network systems for the Ames Unitary Wind Tunnel were explored.