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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.

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At least 1,171 records · Page 65

All sources NASA NTRS DOE OSTI

NASA NTRS1987

Central Processor Acts as High-Speed DMA Controller

Computer-system architecture enables system host central processor (CP) to make high-speed, direct-memory-access (DMA) data transfers without cost and complexity of adding dedicated DMA controller. New system, CCP used as DMA controller, obviating need for dedicated DMA controller; yet maximum transfer rates equivalent to those obtained with dedicated DMA controller. Useful wherever dedicated DMA controller desired because of required data-transfer rates.

Blaha, Matthew S.↗

NASA NTRS1991

Fuzzy logic applications to expert systems and control

A considerable amount of work on the development of fuzzy logic algorithms and application to space related control problems has been done at the Johnson Space Center (JSC) over the past few years. Particularly, guidance control systems for space vehicles during proximity operations, learning systems utilizing neural networks, control of data processing during rendezvous navigation, collision avoidance algorithms, camera tracking controllers, and tether controllers have been developed utilizing fuzzy logic technology. Several other areas in which fuzzy sets and related concepts are being considered at JSC are diagnostic systems, control of robot arms, pattern recognition, and image processing. It has become evident, based on the commercial applications of fuzzy technology in Japan and China during the last few years, that this technology should be exploited by the government as well as private industry for energy savings.

Lea, Robert N.↗

NASA NTRS1984

Total energy-rate feedback for automatic glide-slope tracking during wind-shear penetration

Low-altitude wind shear is recognized as an infrequent but significant hazard to all aircraft during the take-off and landing phases of flight. A total energy-rate sensor was developed for measuring the specific total energy rate of an airplane with respect to the air mass. Control-system designs, both with and without energy-rate feedback, for the approach to landing of a transport airplane through a severe-wind-shear and gust environment are presented in order to evaluate this application of the sensor. A system model incorporates wind-shear-dynamics equations with the airplane equations of motion to permit analysis of the control systems under various wind-shear conditions. The control systems are designed using optimal-output feedback and are analyzed using frequency-domain control-theory techniques. Control-system performance is evaluated using a complete nonlinear simulation of the airplane combined with a severe-wind-shear and gust data package. This evaluation is concerned with control system stability and regulation capability only.

Belcastro, C. M.↗

NASA NTRS1975

Research study on stabilization and control. Modern sampled-data control theory: Stability analysis of the low cost large space telescope system

The pointing stability of the low-cost large space telescope (LST) system was investigated. The low-cost LST is characterized by the use of reaction wheels for the generation of control torques. Because of the critical requirement on the pointing accuracy of the LST, the nonlinear frictional characteristics of the bearings of the reaction wheels were studied which can cause limit cycles in a closed-loop system. Another possible source of pointing error in the LST is due to the effect of quantization and sensor noise. Since the LST is a digital system, digital to analog and analog to digital converters and sensors for positional and rate feedbacks were used. Sensor noise and amplitude quantization causes pointing error in the LST and, in addition, quantization is a nonlinear phenomenon which can cause self-sustained oscillations in the closed-loop system. The dynamic modeling of the single-axis LST is described, and several methods of evaluating the attitude error of the digital LST due to quantization and noise inputs are given.

Kuo, B. C.↗

NASA NTRS2017

Dynamic Control System Mode Performance of the Space Technology-7 Disturbance Reduction System

The Space Technology-7 (ST-7) Disturbance Reduction System (DRS) is an experiment package aboard the European Space Agency (ESA) LISA Pathfinder spacecraft, launched on December 3, 2015. DRS consists of three primary components: Colloidal MicroNewton Thrusters (CMNTs), an Integrated Avionics Unit (IAU), and flight-software implementing the Command and Data Handling (C&DH) and Dynamic Control System (DCS) algorithms. The CMNTs were designed to provide thrust from 5 to 30 micro Newton, with thrust controllability and resolution of 0.1 micro Newton and thrust noise of 0.1 micro Newton/(square root of (Hz)) in the measurement band from 1-30 mHz. The IAU hosts the C&DH and DCS flight software, as well as interfaces with both the CMNT electronics and the LISA Pathfinder spacecraft. When in control, the DCS uses star tracker attitude data and capacitive or optically-measured position and attitude information from LISA Pathfinder and the LISA Technology Package (LTP) to control the attitude and position of the spacecraft and the two test masses inside the LTP. After completion of the nominal ESA LISA Pathfinder mission, the DRS experiment was commissioned followed by its nominal mission. DRS operations extended over the next five months, interspersed with station keeping, anomaly resolution, and periods where control was handed back to LISA Pathfinder for them to conduct further experiments. The primary DRS mission ended on December 6, 2016, with the experiment meeting all of its Level 1 requirements. The DCS, developed at the NASA Goddard Space Flight Center, consists of five spacecraft control modes and six test mass control modes, combined into six 'DRS Mission Modes'. Attitude Control and Zero-G were primarily used to control the spacecraft during initial handover and during many of the CMNT characterization experiments. The other Mission Modes, Drag Free Low Force, 18-DOF Transitional, and 18-DOF, were used to provide drag-free control of the spacecraft about the test masses. This paper will discuss the performance of these DCS spacecraft and test mass control modes. Flight data will be shown from each mode throughout the mission, both from nominal operations and during various flight experiments. The DCS team also made some changes to controller, filter, and limit parameters during operations; the motivation and results of these changes will be shown and discussed.

O'Donnell, James R., Jr.↗

NASA NTRS2014

On-Orbit Engineering and Vehicle Integration Poster Presentation

One of the duties of the MER Managers is getting the consoles to review and sign Electronic Flight Notes (EFN) and Mission Action Requests (Chit) before they are due. Chits and EFNs and are accessible through the Mission Control Center - Houston (MCC-H) Gateway. Chits are the official means of documenting questions and answers, technical direction, real-time changes to Flight Rules (FR) and procedures, request for analysis, etc. between various consoles concerning on-orbit operations. EFNs are documents used by the Flight Control Team (FCT) to communicate precise details between console positions and manage real time changes to FR and Systems Operation Data File (SODF) procedures. On GMT 2013/345 the External Active Thermal Control System (EATCS) on the Columbus (COL) Moderate Temperature Loop (MTL) Interface Heat Exchanger (IFHX) shut down due to low temperatures. Over the next couple of days, the core temperature of COL MT IFHX dropped due to the failure of the Flow Control Valve (FCV). After the temperature drop was discovered, heaters were turned on to bring the temperatures back to nominal. After the incident occurred, a possible freeze threat was discovered that could have ruptured the heat exchanger. The COL MT IFHX rupturing would be considered a catastrophic failure and potentially result in a loss of the vehicle and/or the lives of the International Space Station (ISS) crew members

Heimerdinger, Madison↗

DOE OSTI2021

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1990

Reduced-order filtering for flexible space structures

There is a need for feedback control of the large flexible space structures which are going to be increasingly important in the future of the space program. These structures are very lightly damped, and vibrations may persist for a long time when the system is disturbed unless an active feedback control strategy is used to damp out the vibrations. The system is best described by a partial differential equation description, but the more common approach is to use a large set of second order differential equations, where a large number of modes must be retained if the mathematics is to provide an adequate description of the dynamical process. Sensors, such as accelerometers and rate gyros, may provide data to the feedback controller so that it may respond appropriately to control the system. The data from the sensors is not perfect, but is subject to noise, called measurement noise, and the dynamical process itself is subject to disturbances referred to as process noise. Filtering the sensor signals to remove the measurement noise, and using the resulting state estimates to control the system are investigated.

Sims, Craig S.↗

NASA NTRS1993

Optimization of actuator arrays for aircraft interior noise control

A numerical procedure for grouping actuators in order to reduce the number of degrees of freedom in an active noise control system is evaluated using experimental data. Piezoceramic actuators for reducing aircraft interior noise are arranged into groups using a nonlinear optimization routine and clustering algorithm. An actuator group is created when two or more actuators are driven with the same control input. This procedure is suitable for active control applications where actuators are already mounted on a structure. The feasibility of this technique is demonstrated using measured data from the aft cabin of a Douglas DC-9 fuselage. The measured data include transfer functions between 34 piezoceramic actuators and 29 interior microphones and microphone responses due to the primary noise produced by external speakers. Control inputs for the grouped actuators were calculated so that a cost function, defined as a quadratic pressure term and a penalty term, was a minimum. The measured transfer functions and microphone responses are checked by comparing calculated noise reductions with measured noise reductions for four frequencies. The grouping procedure is then used to determine actuator groups that improve overall interior noise reductions by 5.3 to 15 dB, compared to the baseline experimental configuration.

Cabell, R. H.↗

NASA NTRS2007

Smart Sensor Node Development, Testing and Implementation for Rocket Propulsion Systems

Successful design and implementation of an Integrated System Health Management (ISHM) approach for rocket propulsion systems requires the capability improve the reliability of complex systems by detecting and diagnosing problems. One of the critical elements in the ISHM is an intelligent sensor node for data acquisition that meets specific requirements for rocket motor testing including accuracy, sample rate and size/weight. Traditional data acquisition systems are calibrated in a controlled environment and guaranteed to perform bounded by their tested conditions. In a real world ISHM system, the data acquisition and signal conditioning needs to function in an uncontrolled environment. Development and testing of this sensor node focuses on a design with the ability to self check in order to extend calibration times, report internal faults and drifts and notify the overall system when the data acquisition is not performing as it should. All of this will be designed within a system that is flexible, requiring little re-design to be deployed on a wide variety of systems. Progress in this design and initial testing of prototype units will be reported.

Mengers, Timothy R.↗

NASA NTRS2009

Integrated System Health Management Development Toolkit

This software toolkit is designed to model complex systems for the implementation of embedded Integrated System Health Management (ISHM) capability, which focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, and predict future anomalies), and to provide data, information, and knowledge (DIaK) to control systems for safe and effective operation.

Figueroa, Jorge↗

NASA NTRS2010

Monitoring System for Storm Readiness and Recovery of Test Facilities: Integrated System Health Management (ISHM) Approach

Severe weather events are likely occurrences on the Mississippi Gulf Coast. It is important to rapidly diagnose and mitigate the effects of storms on Stennis Space Center's rocket engine test complex to avoid delays to critical test article programs, reduce costs, and maintain safety. An Integrated Systems Health Management (ISHM) approach and technologies are employed to integrate environmental (weather) monitoring, structural modeling, and the suite of available facility instrumentation to provide information for readiness before storms, rapid initial damage assessment to guide mitigation planning, and then support on-going assurance as repairs are effected and finally support recertification. The system is denominated Katrina Storm Monitoring System (KStorMS). Integrated Systems Health Management (ISHM) describes a comprehensive set of capabilities that provide insight into the behavior the health of a system. Knowing the status of a system allows decision makers to effectively plan and execute their mission. For example, early insight into component degradation and impending failures provides more time to develop work around strategies and more effectively plan for maintenance. Failures of system elements generally occur over time. Information extracted from sensor data, combined with system-wide knowledge bases and methods for information extraction and fusion, inference, and decision making, can be used to detect incipient failures. If failures do occur, it is critical to detect and isolate them, and suggest an appropriate course of action. ISHM enables determining the condition (health) of every element in a complex system-of-systems or SoS (detect anomalies, diagnose causes, predict future anomalies), and provide data, information, and knowledge (DIaK) to control systems for safe and effective operation. ISHM capability is achieved by using a wide range of technologies that enable anomaly detection, diagnostics, prognostics, and advise for control: (1) anomaly detection algorithms and strategies, (2) fusion of DIaK for anomaly detection (model-based, numerical, statistical, empirical, expert-based, qualitative, etc.), (3) diagnostics/prognostics strategies and methods, (4) user interface, (5) advanced control strategies, (6) integration architectures/frameworks, (7) embedding of intelligence. Many of these technologies are mature, and they are being used in the KStorMS. The paper will describe the design, implementation, and operation of the KStorMS; and discuss further evolution to support other needs such as condition-based maintenance (CBM).

Figueroa, Fernando↗

NASA NTRS2012

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, spacecraft vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery

Space Propulsion↗

DOE OSTI2020

A Vector Sensor-Based Acoustic Characterization System for Marine Renewable Energy

NoiseSpotter is a passive acoustic monitoring system that characterizes, classifies, and geo-locates anthropogenic and natural sounds in near real time. It was developed with the primary goal of supporting the evaluation of potential acoustic effects of offshore renewable energy projects. The system consists of a compact array of three acoustic vector sensors, which measures acoustic pressure and the three-dimensional particle velocity vector associated with the propagation of an acoustic wave, thereby inherently providing bearing information to an underwater source of sound. By utilizing an array of three vector sensors, the application of beamforming techniques can provide sound source localization, allowing for characterization of the acoustic signature of specific underwater acoustic sources. Here, performance characteristics of the system are presented, using data from controlled acoustic transmissions in a quiet environment and ambient noise measurements in an energetic tidal channel in the presence of non-acoustic flow noise. Data quality is demonstrated by the ability to reduce non-acoustic flow noise contamination, while system utility is shown by the ability to characterize and localize sources of sound in the underwater environment.

16 TIDAL AND WAVE POWER↗

NASA NTRS1999

Microphone Array Phased Processing System (MAPPS): Version 4.0 Manual

A processing system has been developed to meet increasing demands for detailed noise measurement of individual model components. The Microphone Array Phased Processing System (MAPPS) uses graphical user interfaces to control all aspects of data processing and visualization. The system uses networked parallel computers to provide noise maps at selected frequencies in a near real-time testing environment. The system has been successfully used in the NASA Ames 7- by 10-Foot Wind Tunnel.

Watts, Michael E.↗

NASA NTRS1987

An analysis of redundancy management algorithms for asynchronous fault tolerant control systems

Redundancy management algorithms, commonly referred to as voters, are algorithms used in fault-tolerant control systems to vote on incoming redundant data, isolate bad signals, and output a single good value. In a synchronous environment, this algorithm is a straightforward signal-to-signal comparison with relatively low complexity. The technology of asynchronous control systems, recently realized in the Ultrareliable Fault Tolerant Control System research program at NASA Ames Research Center, requires more complex algorithms for fault detection and signal selection. A variety of algorithms used for this process, a means of testing them, and their basic performance under a simulated environment of the ultrareliable fault-tolerant control system are presented.

Davis, Gloria J.↗

DOE OSTI2020

Data-driven Cyberattack Detection for Photovoltaic (PV) Systems through Analyzing Micro-PMU Data

With increasing exposure to software-based sensing and control, Photovoltaic (PV) systems are facing higher risks of cyber attacks. Here, to ensure the system stability and minimize potential economic losses, it is imperative to monitor operating states and detect attacks at the early stage. To meet this demand, Micro-Phasor Measurement Units (μPMU) are increasingly popular in monitoring distribution networks. However, due to the relatively low sampling rate, μPMU has not yet been used to detect and classify cyber-attacks in power electronics enabled smart grid. To our knowledge, this is one of the first attempts to use μPMU to detect cyber attacks that degrade the performance of power electronics systems. We propose to apply data-driven methods on micro-PMU data to implement attack detection. We have evaluated data-driven methods, including decision tree (DT), K-nearest neighbor (KNN), support vector machine (SVM), artificial neural network (ANN), long short-term memory (LSTM) and convolutional neural network (CNN). The proposed CNN model achieves the required performances with the highest 99.23% accuracy and 0.9963 F 1 score.

14 SOLAR ENERGY↗

DOE OSTI2021

Nominal and adversarial synthetic PMU data for standard IEEE test systems

GridSTAGE (Spatio-Temporal Adversarial scenario GEneration) is a framework for the simulation of adversarial scenarios and the generation of multivariate spatio-temporal data in cyber-physical systems. GridSTAGE is developed based on Matlab and leverages Power System Toolbox (PST) where the evolution of the power network is governed by nonlinear differential equations. Using GridSTAGE, one can create several event scenarios that correspond to several operating states of the power network by enabling or disabling any of the following: faults, AGC control, PSS control, exciter control, load changes, generation changes, and different types of cyber-attacks. Standard IEEE bus system data is used to define the power system environment. GridSTAGE emulates the data from PMU and SCADA sensors. The rate of frequency and location of the sensors can be adjusted as well. Detailed instructions on generating data scenarios with different system topologies, attack characteristics, load characteristics, sensor configuration, control parameters are available in the Github repository - https://github.com/pnnl/GridSTAGE. There is no existing adversarial data-generation framework that can incorporate several attack characteristics and yield adversarial PMU data. The GridSTAGE framework currently supports simulation of False Data Injection attacks (such as a ramp, step, random, trapezoidal, multiplicative, replay, freezing) and Denial of Service attacks (such as time-delay, packet-loss) on PMU data. Furthermore, it supports generating spatio-temporal time-series data corresponding to several random load changes across the network or corresponding to several generation changes. A Koopman mode decomposition (KMD) based algorithm to detect and identify the false data attacks in real-time is proposed in https://ieeexplore.ieee.org/document/9303022. Machine learning-based predictive models are developed to capture the dynamics of the underlying power system with a high level of accuracy under various operating conditions for IEEE 68 bus system. The corresponding machine learning models are available at https://github.com/pnnl/grid_prediction.

99 GENERAL AND MISCELLANEOUS↗