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At least 289 records · Page 16

All sources NASA NTRS DOE OSTI

DOE OSTI2014

Secure Interoperable Open Smart Grid Demonstration Project

The Consolidated Edison, Inc., of New York (Con Edison) Secure Interoperable Open Smart Grid Demonstration Project (SGDP), sponsored by the United States (US) Department of Energy (DOE), demonstrated that the reliability, efficiency, and flexibility of the grid can be improved through a combination of enhanced monitoring and control capabilities using systems and resources that interoperate within a secure services framework. The project demonstrated the capability to shift, balance, and reduce load where and when needed in response to system contingencies or emergencies by leveraging controllable field assets. The range of field assets includes curtailable customer loads, distributed generation (DG), battery storage, electric vehicle (EV) charging stations, building management systems (BMS), home area networks (HANs), high-voltage monitoring, and advanced metering infrastructure (AMI). The SGDP enables the seamless integration and control of these field assets through a common, cyber-secure, interoperable control platform, which integrates a number of existing legacy control and data systems, as well as new smart grid (SG) systems and applications. By integrating advanced technologies for monitoring and control, the SGDP helps target and reduce peak load growth, improves the reliability and efficiency of Con Edison’s grid, and increases the ability to accommodate the growing use of distributed resources. Con Edison is dedicated to lowering costs, improving reliability and customer service, and reducing its impact on the environment for its customers. These objectives also align with the policy objectives of New York State as a whole. To help meet these objectives, Con Edison’s long-term vision for the distribution grid relies on the successful integration and control of a growing penetration of distributed resources, including demand response (DR) resources, battery storage units, and DG. For example, Con Edison is expecting significant long-term growth of DG. The SGDP enables the efficient, flexible integration of these disparate resources and lays the architectural foundations for future scalability. Con Edison assembled an SGDP team of more than 16 different project partners, including technology vendors, and participating organizations, and the Con Edison team provided overall guidance and project management. Project team members are listed in Table 1-1.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS2006

A Multi-mission Event-Driven Component-Based System for Support of Flight Software Development, ATLO, and Operations first used by the Mars Science Laboratory (MSL) Project

This paper details an architectural description of the Mission Data Processing and Control System (MPCS), an event-driven, multi-mission ground data processing components providing uplink, downlink, and data management capabilities which will support the Mars Science Laboratory (MSL) project as its first target mission. MPCS is developed based on a set of small reusable components, implemented in Java, each designed with a specific function and well-defined interfaces. An industry standard messaging bus is used to transfer information among system components. Components generate standard messages which are used to capture system information, as well as triggers to support the event-driven architecture of the system. Event-driven systems are highly desirable for processing high-rate telemetry (science and engineering) data, and for supporting automation for many mission operations processes.

Mission Data Processing and Control System (MPCS)↗

NASA NTRS2017

Modular Biometric Monitoring System

A modular system for acquiring biometric data includes a plurality of data acquisition modules configured to sample biometric data from at least one respective input channel at a data acquisition rate. A representation of the sampled biometric data is stored in memory of each of the plurality of data acquisition modules. A central control system is in communication with each of the plurality of data acquisition modules through a bus. The central control system is configured to control communication of data, via the bus, with each of the plurality of data acquisition modules.

Chmiel, Alan J.↗

DOE OSTI2015

Multiple Flow Loop SCADA System Implemented on the Production Prototype Loop

The following report covers FY 15 activities to develop supervisory control and data acquisition (SCADA) system for the Northstar Moly99 production prototype gas flow loop. The goal of this effort is to expand the existing system to include a second flow loop with a larger production-sized blower. Besides testing the larger blower, this system will demonstrate the scalability of our solution to multiple flow loops.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2022

Data-driven Resilience Characterization of Control Dynamical Systems

In this paper, we define and quantify resiliency of a power network and propose data-driven algorithms for computing the same for the power grid. To do this, we use the Koopman operator framework to lift the controlled dynamical system to an abstract (possibly higher) dimensional space, where the evolution is linear. The linear system representation allows us to relate small time local controllability and observability of a general nonlinear control system to the controllability and observability of the lifted linear system. Finally, we define the resiliency of the underlying power grid in terms of the controllability and observability gramians of the lifted linear system. We illustrate the proposed approach to compute the resiliency metrics on time-series data obtained from a microgrid.

koopman operator, resilience, control↗

NASA NTRS1973

TDRSS data handling and management system study. Ground station systems for data handling and relay satellite control

Results of a two-phase study of the (Data Handling and Management System DHMS) are presented. An original baseline DHMS is described. Its estimated costs are presented in detail. The DHMS automates the Tracking and Data Relay Satellite System (TDRSS) ground station's functions and handles both the forward and return link user and relay satellite data passing through the station. Direction of the DHMS is effected via a TDRSS Operations Control Central (OCC) that is remotely located. A composite ground station system, a modified DHMS (MDHMS), was conceptually developed. The MDHMS performs both the DHMS and OCC functions. Configurations and costs are presented for systems using minicomputers and midicomputers. It is concluded that a MDHMS should be configured with a combination of the two computer types. The midicomputers provide the system's organizational direction and computational power, and the minicomputers (or interface processors) perform repetitive data handling functions that relieve the midicomputers of these burdensome tasks.

Source record↗

NASA NTRS1962

NASA Scout ST-1 Flight-Test Results and Analyses, Launch Operations, and Test Vehicle Description

The first of a series of flight tests for the development of the four-stage, solid-propellant Scout vehicle was conducted at the NASA Wallops Station under the direction of the Langley Research Center. Vehicle designation for the test was NASA Scout ST-1. Performance characteristics of the vehicle and components were recorded during a high-altitude probe mission. Flight-simulation studies are presented and show that the accuracy of the guidance system during the flight was within control-system design specifications. The control system functioned normally during the flight with the exception of an overpowering of the reaction-control roll jets near burnout of the third-stage rocket motor. The resulting roll displacement of the vehicle is shown to have caused the monitor tracking radar which had been erroneously tracking a radar beacon in the vehicle on a side lobe to reorient to the major lobe of the receiving antenna. This tracking switch falsely indicated a violent turning maneuver on the monitor plot board and resulted in a hold-fire decision for the fourth-stage rocket motor. Although data for the final thrusting and coast phase of the flight were not obtained, the majority of the test objectives were achieved. In-flight thrust misalignment angles for the second- and third-stage rocket motors derived from control-system error data and for the first-stage motor determined from flight-simulation studies are presented. All rocket-motor thrust misalignment angles were well within the tolerances used for control-system design. Rocket-motor flight performance is presented, and velocity increments attained from the first three stages substantiated the predicted nominal performance. Operation of the rocket motors was satisfactory with the exception of high-level vibrations which were encountered during third-stage motor burning. Rolling moments which overpowered the reaction-control jets are also attributed to the burning characteristics of the third-stage motor. A discussion of the premature loss of the third-stage heat shield is given and shows that the heat-shield latching mechanism failed from pressure loads as the vehicle entered the transonic speed range. Although venting was provided to relieve the high negative pressures known to exist on the heat shield at these speeds, a field modification of the wiring tunnel had the same effect as opening the inside of the heat shield to ambient pressures. Consequently, the latching mechanism failed from pressure loads which were of about the same magnitude as the latching-mechanism yield loads. Skin temperatures were recorded at several locations on the vehicle and were generally in good agreement with theoretical values. Aerodynamic heating presented no problem during the flight since the maximum temperatures recorded during the flight were only about half the design values because of the high-launch-angle trajectory. Environmental vibrations recorded in the vicinity of the guidance package showed that no significant continuous amplitude levels above the general instrumentation noise level were present during first- and second-stage burning. Large vibration amplitudes were recorded during third-stage burning which coincided with the large roll disturbance experienced by the vehicle near burnout of the third-stage motor.

Scout Launch Vehicle↗

DOE OSTI2016

New generation of data acquisition and data storage systems of the IBR-2 reactor spectrometers complex

The paper presents an overview of works on the creation of data acquisition and data storage systems, which have been carried out in the Department of the IBR-2 spectrometers complex (DCS) of the Frank Laboratory of Neutron Physics (FLNP) over the past 15 years (before, during, and after the modernization of the IBR-2 reactor). These systems represent a unified set of identical (from the viewpoint of hardware) modules limited in type but functionally complete, wherein distinctions in parameters, functional capabilities, encoding, correction and preliminary data processing procedures specific to each spectrometer are realized on the level of microprograms, electronic tables, and integrated software control system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1978

The data system dynamic simulation /DSDS/

The paper describes the development by NASA of the data system dynamic simulation (DSDS) which provides a data system simulation capability for a broad range of programs, with the capability to model and simulate all or any portion of an end-to-end data system to multiple levels of fidelity. Versatility is achieved by specifying parameters which define the performance characteristics of data system components, and by specifying control and data paths in a data system. DSDS helps reduce overall simulation cost and the time required for obtaining a data systems analysis, and helps provide both early realistic representations of data systems and the flexibility to study design changes and operating strategies.

Hooper, J. W.↗

NASA NTRS2011

Framework for Integrating Science Data Processing Algorithms Into Process Control Systems

A software framework called PCS Task Wrapper is responsible for standardizing the setup, process initiation, execution, and file management tasks surrounding the execution of science data algorithms, which are referred to by NASA as Product Generation Executives (PGEs). PGEs codify a scientific algorithm, some step in the overall scientific process involved in a mission science workflow. The PCS Task Wrapper provides a stable operating environment to the underlying PGE during its execution lifecycle. If the PGE requires a file, or metadata regarding the file, the PCS Task Wrapper is responsible for delivering that information to the PGE in a manner that meets its requirements. If the PGE requires knowledge of upstream or downstream PGEs in a sequence of executions, that information is also made available. Finally, if information regarding disk space, or node information such as CPU availability, etc., is required, the PCS Task Wrapper provides this information to the underlying PGE. After this information is collected, the PGE is executed, and its output Product file and Metadata generation is managed via the PCS Task Wrapper framework. The innovation is responsible for marshalling output Products and Metadata back to a PCS File Management component for use in downstream data processing and pedigree. In support of this, the PCS Task Wrapper leverages the PCS Crawler Framework to ingest (during pipeline processing) the output Product files and Metadata produced by the PGE. The architectural components of the PCS Task Wrapper framework include PGE Task Instance, PGE Config File Builder, Config File Property Adder, Science PGE Config File Writer, and PCS Met file Writer. This innovative framework is really the unifying bridge between the execution of a step in the overall processing pipeline, and the available PCS component services as well as the information that they collectively manage.

Mattmann, Chris A.↗

DOE OSTI2016

Pre-commercial Demonstration of Direct Non-iterative State Estimator for Operational Use of Synchrophasor Management Systems

The objective of this project was to demonstrate functionality and performance of a Direct Non-iterative State Estimator (DNSE) integrated with NYPA’s Energy Management System (EMS) and with enhanced Real Time Dynamics Monitoring System (RTDMS) synchrophasor platform from Electric Power Group (EPG). DNSE is designed to overcome a major obstacle to operational use of Synchro-Phasor Management Systems (SPMS) by providing to synchrophasor management systems (SPMS) applications a consistent and a complete synchrophasor data foundation in the same way that a traditional EMS State Estimator (SE) provides to EMS applications. Specifically, DNSE is designed to use synchrophasor measurements collected by a central PDC, Supervisory Control and Data Acquisition (SCADA) measurements, and Energy Management System (EMS) network model, to obtain the complete state of the utility’s operating model at rates that are close to the synchrophasor data rates. In this way, the system is comprehensive in that it does not only cover the part of the network that is “visible” via synchrophasors, but also the part that is only “visible” through the SCADA measurements. Visualization needs associated with the use of DNSE results are fulfilled through suitably enhanced Real Time Dynamics Monitoring System (RTDMS), with the enhancements implemented by EPG. This project had the following goals in mind: To advance the deployment of commercial grade DNSE software application that relies on synchrophasor and SCADA data ; Apply DNSE at other utilities, to address a generic and fundamental need for “clean” operational data for synchrophasor applications; Provide means for “live” estimated data access by control system operators; Enhance potential for situational awareness through full system operational model coverage; Sub-second execution rate of the Direct Non-iterative State Estimator, eventually at a near-phasor data rate execution speed, i.e. < 0.1 sec. Anticipated benefits from this projects are: Enhanced reliability and improvements in the economic efficiency of bulk power system planning and operations; Providing “clean” data to other synchrophasor applications; Enhancement of situational awareness by providing the full operational model updated at near synchrophasor rate; A production-grade software tool that incorporate synchrophasor and SCADA data; Provides a basis for development of next generation monitoring and control applications, based on both SCADA and PMU data. Quanta Technology (QT) team worked in collaboration with Electric Power Group (EPG) whose team has enhanced its commercial Real Time Dynamics Monitoring System (RTDMS) to accommodate the requirements posed by DNSE application. EPG also provided its ePDC and Model-less Data Conditioning (PDVC) software for integration with DNSE+. QT developed the system requirements for DNSE; developed system architecture and defined interfaces between internal DNSE components. The core DNSE algorithm with all surrounding interfaces was named DNSE+. Since the DNSE development was done in a simulated system environment, QT used its PMU simulator that was enhanced during this project for development and factory acceptance testing (FAT). SCADA data in this stage was simulated by commercial PSS/e software. The output of DNSE are estimates of System states in C37.118-2 format, sent to RTDMS for further processing and display. As the number of these states is large, it was necessary to expand the C37.111-2 standard to accommodate large data sets. This enhancement was implemented in RTDMS. The demonstration of pre-production DNSE technology was done at NYPA using streaming field data from NYPA PMUs and from its RTUs through their SCADA system. NYPA provided ICCP interface as well as Common Information Model (CIM). The relevance of the DNSE+ application is that it provides state estimation of the power system based on hybrid set of data, consisting of both available PMU data and SCADA measurements. As this is a direct, non-iterative method of calculation of the system states, if does not suffer from convergence issues which is potential problem for conventional state estimators. Also, it can take any available PMU measurements, so it does not need to have a high percentage of PMU coverage needed in the case of Linear State Estimator. As the DNSE calculates synchrophasors of the system states (both phase and absolute value) as sub-second rate, this application can provide a basis for development of next generation of applications based both on SCADA and PMU data.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1966

Mariner Mars science Data Automation System.

RT Data Automation System automatically controls and synchronizes data-gathering sequence of cruise instruments of Mariner IV spacecraft

MARINER IV SPACE PROBE↗

DOE OSTI2022

System and method for measuring sun-induced chlorophyll fluorescence

A chlorophyll fluorescence measuring system having at least one spectrometer coupled to a data logger. The data logger provides direct control of the spectrometer and includes on-board memory for storage of target and reference spectrum data obtained by the spectrometer. The data logger may be coupled to an external computer that receives and analyzes target and reference spectrum data to determine SIF using a spectral fitting algorithm. The system may include a spectrometer aiming system coupled to and controlled by the data logger. The system may also include one or more environmental sensors configured to measure environment variables. The environmental sensors may be coupled to the data logger for control and data storage. The environmental data may be communicated to the external computer for use in the spectral fitting algorithm. The data logger may be connected to a network for remote monitoring and control.

Gu, Lianhong↗

NASA NTRS2006

NASA Stennis Space Center Integrated System Health Management Test Bed and Development Capabilities

Integrated System Health Management (ISHM) is a capability that focuses on determining the condition (health) of every element in a complex System (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK)-not just data-to control systems for safe and effective operation. This capability is currently done by large teams of people, primarily from ground, but needs to be embedded on-board systems to a higher degree to enable NASA's new Exploration Mission (long term travel and stay in space), while increasing safety and decreasing life cycle costs of spacecraft (vehicles; platforms; bases or outposts; and ground test, launch, and processing operations). The topics related to this capability include: 1) ISHM Related News Articles; 2) ISHM Vision For Exploration; 3) Layers Representing How ISHM is Currently Performed; 4) ISHM Testbeds & Prototypes at NASA SSC; 5) ISHM Functional Capability Level (FCL); 6) ISHM Functional Capability Level (FCL) and Technology Readiness Level (TRL); 7) Core Elements: Capabilities Needed; 8) Core Elements; 9) Open Systems Architecture for Condition-Based Maintenance (OSA-CBM); 10) Core Elements: Architecture, taxonomy, and ontology (ATO) for DIaK management; 11) Core Elements: ATO for DIaK Management; 12) ISHM Architecture Physical Implementation; 13) Core Elements: Standards; 14) Systematic Implementation; 15) Sketch of Work Phasing; 16) Interrelationship Between Traditional Avionics Systems, Time Critical ISHM and Advanced ISHM; 17) Testbeds and On-Board ISHM; 18) Testbed Requirements: RETS AND ISS; 19) Sustainable Development and Validation Process; 20) Development of on-board ISHM; 21) Taxonomy/Ontology of Object Oriented Implementation; 22) ISHM Capability on the E1 Test Stand Hydraulic System; 23) Define Relationships to Embed Intelligence; 24) Intelligent Elements Physical and Virtual; 25) ISHM Testbeds and Prototypes at SSC Current Implementations; 26) Trailer-Mounted RETS; 27) Modeling and Simulation; 28) Summary ISHM Testbed Environments; 29) Data Mining - ARC; 30) Transitioning ISHM to Support NASA Missions; 31) Feature Detection Routines; 32) Sample Features Detected in SSC Test Stand Data; and 33) Health Assessment Database (DIaK Repository).

Figueroa, Fernando↗

NASA NTRS1971

Apollo 11 Mission Report, Supplement 5: Performance of Lunar Module Reaction Control Systems

Spacecraft velocity data and crew reports indicated that RCS engine performance was nominal. It is estimated that the RCS engines accumulated a total of 1060 seconds on-time and 12,000 firings during the mission. The quad temperatures ranged from 132 to 232 F during the period when the heaters were active, within predicated ranges. The total propellant consumption from the RCS tanks was about 319 pounds, compared to a predicted value of 253 pounds. An additional 69 pounds of propellant were used from the ascent propulsion system tanks during interconnect feed operations associated with APS lift-off, following periods of rapid propellant usage. The only problems noted were two thrust chamber pressure switch failures on the quad one down-firing engine and on the quad 2 aft-firing engine. Engine performance was nominal on both engines, and the switch failures had no effect on the mission.

Blevins, D. R.↗

NASA NTRS2006

ISHM Implementation for Constellation Systems

Figueroa, Fernando↗

NASA NTRS2013

System Administrator for LCS Development Sets

The Spaceport Command and Control System Project is creating a Checkout and Control System that will eventually launch the next generation of vehicles from Kennedy Space Center. KSC has a large set of Development and Operational equipment already deployed in several facilities, including the Launch Control Center, which requires support. The position of System Administrator will complete tasks across multiple platforms (Linux/Windows), many of them virtual. The Hardware Branch of the Control and Data Systems Division at the Kennedy Space Center uses system administrators for a variety of tasks. The position of system administrator comes with many responsibilities which include maintaining computer systems, repair or set up hardware, install software, create backups and recover drive images are a sample of jobs which one must complete. Other duties may include working with clients in person or over the phone and resolving their computer system needs. Training is a major part of learning how an organization functions and operates. Taking that into consideration, NASA is no exception. Training on how to better protect the NASA computer infrastructure will be a topic to learn, followed by NASA work polices. Attending meetings and discussing progress will be expected. A system administrator will have an account with root access. Root access gives a user full access to a computer system and or network. System admins can remove critical system files and recover files using a tape backup. Problem solving will be an important skill to develop in order to complete the many tasks.

Virtualizing in Linux↗

NASA NTRS1987

A knowledge-based system for monitoring the electrical power system of the Hubble Space Telescope

The design and the prototype for the expert system for the Hubble Space Telescope's electrical power system are discussed. This prototype demonstrated the capability to use real time data from a 32k telemetry stream and to perform operational health and safety status monitoring, detect trends such as battery degradation, and detect anomalies such as solar array failures. This prototype, along with the pointing control system and data management system expert systems, forms the initial Telemetry Analysis for Lockheed Operated Spacecraft (TALOS) capability.

Eddy, Pat↗