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At least 91 records · Page 5

Integration of Simulated and Real Distributed Acoustic Sensor Measurements to Develop AI Enhanced Intelligent Sensing Operations

Distributed acoustic sensors (DAS) have shown remarkable success in monitoring critical civil, energy and transportation assets over long distances and under harsh environmental conditions. Integration of artificial intelligence (AI) technologies with DAS can extend their operational capabilities from conventional tasks (e.g., vibration frequency detection) to more advanced intelligent tasks like anomaly detection. However, these AI technologies often require large labeled/ annotated DAS measurements datasets of the assets in both normal and anomalous operating conditions. This data acquisition task can be both time consuming and costly. This work develops a generative adversarial network based unsupervised domain adaptation framework to build intelligent DAS operational capabilities.

Venketeswaran, Abhishek↗

Anomalous behavior detection by an artificial intelligence-enabled system with multiple correlated sensors

Multi-metric artificial intelligence (AI)/machine learning (ML) models for detection of anomalous behavior of a machine/system are disclosed. The multi-metric AI/ML models are configured to detect anomalous behavior of systems having multiple sensors that measure correlated sensor metrics such as coolant distribution units (CDUs). The multi-metric AI/ML models perform the anomalous system behavior detection in a manner that enables both a reduction in the amount of sensor instrumentation needed to monitor the system's operational behavior as well as a corresponding reduction in the complexity of the firmware that controls the sensor instrumentation. As such, AI-enabled systems and corresponding methods for anomalous behavior detection disclosed herein offer a technical solution to the technical problem of increased failure rates of existing multi-sensor systems, which is caused by the presence of redundant sensor instrumentation that necessitates complex firmware for controlling the sensor instrumentation.

Serebryakov, Sergey↗

Extended Logic Intelligent Processing System for a Sensor Fusion Processor Hardware

The paper presents the hardware implementation and initial tests from a low-power, highspeed reconfigurable sensor fusion processor. The Extended Logic Intelligent Processing System (ELIPS) is described, which combines rule-based systems, fuzzy logic, and neural networks to achieve parallel fusion of sensor signals in compact low power VLSI. The development of the ELIPS concept is being done to demonstrate the interceptor functionality which particularly underlines the high speed and low power requirements. The hardware programmability allows the processor to reconfigure into different machines, taking the most efficient hardware implementation during each phase of information processing. Processing speeds of microseconds have been demonstrated using our test hardware.

Stoica, Adrian↗

Optical fiber sensors and signal processing for intelligent structure monitoring

The analytic and experimental performance of optical fiber sensors for the control of vibration of large aerospace and other structures are investigated. In particular, model domain optical fiber sensor systems, are being studied due to their apparent potential as distributed, low mass sensors of vibration over appropriate ranges of both low frequency and low amplitude displacements. Progress during the past three months is outlined. Progress since September is divided into work in the areas of experimental hardware development, analytical analysis, control design and sensor development. During the next six months, tests of a prototype closed-loop control system for a beam are planned which will demonstrate the solution of several optical fiber instrumentation device problems, the performance of the control system theory which incorporates the model of the modal domain sensor, and the potential for distributed control which this sensor approach offers.

Rogowski, Robert↗

Kensor: Coordinated Intelligence from Co-Located Sensors

Internet of Things (IoT) is becoming more pervasive in many installations, including homes, manufacturing plants, and industrial facilities of all kinds. The data that IoT produces is a reflection of usual behavior such as daily routines and scheduled tasks, but also from unexpected behavior due to unintentional or undesirable abnormalities. Here, we focus on achieving coordinated intelligence about normal and abnormal phenomena from multiple sensors that are geographically colocated in close proximity, monitoring and controlling a set of co-located devices. Given a set of co-located sensors, we seek an intelligent approach that would automatically determine the “normal” patterns of behaviors among the correlated sensors. After normal behavior is extracted, later monitoring should detect any deviant variations over time. An example application is an entry monitoring and alert system for facilities such as nuclear reactors, where badge readers, door locks, lights, weight trackers and other co-located sensors at the entry point are collectively tracked. To address this problem, we identify the possible solution approach that can be used to solve its different variants. The implemented model is developed as a combination of rules and Markov Chain methods.

Kotevska, Olivera↗

Intelligent Elements for ISHM

There are a number of architecture models for implementing Integrated Systems Health Management (ISHM) capabilities. For example, approaches based on the OSA-CBM and OSA-EAI models, or specific architectures developed in response to local needs. NASA s John C. Stennis Space Center (SSC) has developed one such version of an extensible architecture in support of rocket engine testing that integrates a palette of functions in order to achieve an ISHM capability. Among the functional capabilities that are supported by the framework are: prognostic models, anomaly detection, a data base of supporting health information, root cause analysis, intelligent elements, and integrated awareness. This paper focuses on the role that intelligent elements can play in ISHM architectures. We define an intelligent element as a smart element with sufficient computing capacity to support anomaly detection or other algorithms in support of ISHM functions. A smart element has the capabilities of supporting networked implementations of IEEE 1451.x smart sensor and actuator protocols. The ISHM group at SSC has been actively developing intelligent elements in conjunction with several partners at other Centers, universities, and companies as part of our ISHM approach for better supporting rocket engine testing. We have developed several implementations. Among the key features for these intelligent sensors is support for IEEE 1451.1 and incorporation of a suite of algorithms for determination of sensor health. Regardless of the potential advantages that can be achieved using intelligent sensors, existing large-scale systems are still based on conventional sensors and data acquisition systems. In order to bring the benefits of intelligent sensors to these environments, we have also developed virtual implementations of intelligent sensors.

Schmalzel, John L.↗

A Brief Overview of NASA Glenn Research Center Sensor and Electronics Activities

Aerospace applications require a range of sensing technologies. There is a range of sensor and sensor system technologies being developed using microfabrication and micromachining technology to form smart sensor systems and intelligent microsystems. Drive system intelligence to the local (sensor) level -- distributed smart sensor systems. Sensor and sensor system development examples: (1) Thin-film physical sensors (2) High temperature electronics and wireless (3) "lick and stick" technology. NASA GRC is a world leader in aerospace sensor technology with a broad range of development and application experience. Core microsystems technology applicable to a range of application environmentS.

Hunter, Gary W.↗

Optical fiber sensors and signal processing for intelligent structure monitoring

Few mode optical fibers have been shown to produce predictable interference patterns when placed under strain. The use is described of a modal domain sensor in a vibration control experiment. An optical fiber is bonded along the length of a flexible beam. Output from the modal domain sensor is used to suppress vibrations induced in the beam. A distributed effect model for the modal domain sensor is developed. This model is combined with the beam and actuator dynamics to produce a system suitable for control design. Computer simulations predict open and closed loop dynamic responses. An experimental apparatus is described and experimental results are presented.

Thomas, Daniel↗

Sensor and Actuator Needs for More Intelligent Gas Turbine Engines

This paper provides an overview of the controls and diagnostics technologies, that are seen as critical for more intelligent gas turbine engines (GTE), with an emphasis on the sensor and actuator technologies that need to be developed for the controls and diagnostics implementation. The objective of the paper is to help the "Customers" of advanced technologies, defense acquisition and aerospace research agencies, understand the state-of-the-art of intelligent GTE technologies, and help the "Researchers" and "Technology Developers" for GTE sensors and actuators identify what technologies need to be developed to enable the "Intelligent GTE" concepts and focus their research efforts on closing the technology gap. To keep the effort manageable, the focus of the paper is on "On-Board Intelligence" to enable safe and efficient operation of the engine over its life time, with an emphasis on gas path performance

Garg, Sanjay↗

Experimental Test-Bed for Intelligent Passive Array Research

This document describes the test-bed designed for the investigation of passive direction finding, recognition, and classification of speech and sound sources using sensor arrays. The test-bed forms the experimental basis of the Intelligent Small-Scale Spatial Direction Finder (ISS-SDF) project, aimed at furthering digital signal processing and intelligent sensor capabilities of sensor array technology in applications such as rocket engine diagnostics, sensor health prognostics, and structural anomaly detection. This form of intelligent sensor technology has potential for significant impact on NASA exploration, earth science and propulsion test capabilities. The test-bed consists of microphone arrays, power and signal distribution modules, web-based data acquisition, wireless Ethernet, modeling, simulation and visualization software tools. The Acoustic Sensor Array Modeler I (ASAM I) is used for studying steering capabilities of acoustic arrays and testing DSP techniques. Spatial sound distribution visualization is modeled using the Acoustic Sphere Analysis and Visualization (ASAV-I) tool.

Solano, Wanda M.↗

A Framework for Intelligent Rocket Test Facilities with Smart Sensors

A long-term center goal at the John C. Stennis Space Center (SSC) is the formulation and implementation of a framework for an Intelligent Rocket Test Facility (IRTF), which incorporates distributed smart sensor elements. The IRTF is to provide reliable, high-confident measurements. Specific objectives include: 1. Definition of a framework and architecture that supports implementation of highly autonomous methodologies founded on basic physical principles and embedded knowledge. 2. Modeling of autonomous sensors and processes as self-sufficient, evolutionary elements. 3. Development of appropriate communications protocols to enable the complex interactions that must take place to allow timely and high-quality flow of of information among all the autonomous elements of the system. 4. Development of lab-scale prototypes of key system elements. Though our application is next-generation rocket test facilities, applications for the approach are much wider and include monitoring of shuttle launch operations, air and spacecraft operations and health monitoring, and other large-scale industrial system operations such as found in processing and manufacturing plans. Elements of prototype IRTF have been implemented in preparation for advanced development and validation using rocket test stand facilities as SSC. This work has identified issues that are important to further development of complex network and should be of interest to other working with sensor networks.

Figueroa, Fernando↗

The Energy and Operational Impacts of Using 0-10V Control for LED Streetlights

Lighting systems have historically utilized either a proprietary control method, or one of a handful of standardized methods (e.g., 0-10V, DALI, DMX512) aimed at facilitating vendor interoperability. The utility and market success of the standardized methods has been limited for a variety of reasons. Although 0-10V is presently the most commonly available control interface for indoor and outdoor products in North America – even after the emergence of LED products and “connected lighting systems” with more modern network interfaces and luminaire-level sensors and intelligence – the use of 0-10V methods has significant tradeoffs. For instance, it is difficult to predict relative luminaire light output and input power at any particular control voltage, and performance across luminaires is inconsistent. This study characterizes 23 LED streetlights that claimed dimmability via a 0-10V interface, quantifies the performance variation found in market-available LED drivers, and explores the potential impact of the most recent 0-10V voluntary standard (ANSI C137.1-2022). Notably, the tested products were all manufactured prior to the release of this standard, and thus do not make compliance claims. Variation in response to 0-10V control voltages was expected to be more significant across different make/model luminaires than different units of the same make/model; the test population was structured based on this expectation. The 23 tested luminaires comprised 21 unique make/model streetlights from 14 different manufacturers. Three samples of one make/model streetlight were included in the test population to facilitate a limited exploration of unit-to-unit variation. The 21 unique make/model luminaires contained 20 unique make/model LED drivers from eight different driver manufacturers. Luminaire input power and current were measured at 11 control voltages (0.5 V and 1–10 V in 1 V increments).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Energy and Operational Impacts of Using 0-10V Control for LED Streetlights

LED lighting is becoming widely adopted and displacing most traditional lighting technologies. However, the traditional methods used to control light sources have not seen similar displacement. Lighting systems have historically utilized either a proprietary control method, or one of a handful of standardized methods (e.g., 0-10V, DALI, DMX512). The utility and market success of the standardized methods has been limited for a variety of reasons. Analog 0-10V methods have long been popular due to their simplicity and low cost of implementation and are presently the most commonly available control interface for indoor and outdoor LED products in North America. The emergence of “connected lighting systems” with more modern network interfaces and luminaire-level sensors and intelligence was anticipated by many to mark the beginning of the end of analog control. However, 0-10V interfaces continue to be prevalent with these more “digital” systems. The use of 0-10V methods has significant tradeoffs. 0-10V standards have historically not explicitly defined the relationship between the luminaire input control signal and output luminous flux for the full control signal range. As a result, it is difficult to predict relative luminaire light output and input power at any particular control voltage, and in practice the performance across LED drivers and the luminaires power is inconsistent. While this inconsistency has long been acknowledged by experts in the field, it is not accounted for in standard practice deployment, and end-users continue to regularly see unexpected and undesirable performance. It is hoped that the results from this study will help the lighting industry and standards developing organizations better understand and possibly resolve the shortcomings of 0-10V products, and consider what is best for the industry – additional incremental improvements to this fundamentally limited analog technology, or fully moving on to existing digital approaches, such as DALI D4i, that deliver accurate and consistent dimming performance across all luminaires in the system and thus guarantee the delivery of expected light levels, and energy and cost savings. Recommendations consistent with these goals are made to lighting and driver manufacturers, lighting software developers, standard developing organizations, and system designers and specifiers.

0-10V↗

UHT-CAMANCHE: Ultra-High Temperature Ceramic Additively Manufactured Compact Heat Exchangers

The conceptual basis for this project is the convergence of advanced ultra-high temperature ceramic materials and additive manufacturing technologies to produce compact ceramic heat exchangers with complex internal flow path geometries. Task areas were broadly divided into materials and manufacturing development, heat exchanger design, component testing, and techno-economic analysis. Technical challenges included the design and commissioning of new test facilities, improving feature resolution and deposition rate of ceramic additive manufacturing techniques, establishing process-structure-property relationships in additively manufactured ultra-high temperature ceramics, and assessing high temperature materials compatibility in CO 2 environments. The primary candidate material evaluated in this work is a composite comprising zirconium diboride (ZrB2) with 30 vol. % silicon carbide (SiC) which was selected based on its desirable combination of high temperature mechanical properties, high thermal and electrical conductivities, and oxidation resistance. High solids loaded ZrB2-SiC pastes suitable for extrusion-based additive manufacturing were developed for the first time as part of this work. Materials compatibility studies indicate this material oxidizes in CO 2 to form a protective borosilicate scale which transforms to pure silica above 1000°C. Parts made by additive manufacturing displayed enlarged grain sizes produced by pressureless sintering as compared to hot-press sintering. Increases in microstructural coarseness have outsized effect on oxidation performance up to 1400°C due to incomplete oxidation of coarse large diameter SiC particles resulting in lower amounts of silica that apparently inhibit protective scale formation. Additive manufacturing as a forming technique did not appear to significantly affect thermal conductivity, hardness, or elastic modulus, though flexural strength was reduced by half or more as compared to traditionally hot-pressed materials. This effect was attributed to the presence of strength-limiting flaws (ca. 40 microns in size) originating from extrudate inhomogeneities that could potentially be eliminated with further process improvements. Attempts to attain economies of scale for production of multi-kilowatt scale heat exchangers by ceramic additive manufacturing proved difficult. Lack of automation and a modest extrusion rate while retaining fine feature resolution made the overall process labor intensive and limited experimental throughput. A number of full-scale components were taken through post-process heat treatments including drying, binder burnout, and sintering; however, none survived without significant flaws or cracks. Therefore, no operational data from a newly installed heat exchanger test loop were able to be obtained during the performance period. Continued research and development is recommended to improve economic feasibility of ceramic additive manufacturing by standardizing the use of advanced sensors, artificial intelligence, and automation tools to reduce associated labor costs and accelerate production rates. The materials and manufacturing techniques demonstrated in this work are likely to find applications in defense and energy applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Numerical Investigation of Butterfly Valve Performance in Variable Valve Sizes, Positions and Flow Regimes

Reliability and efficiency of valves are necessary for precise control and sufficient heat-flow to heat application plants for the integrated energy systems of nuclear power plants (NPPs). Strategic Management Analysis Requirement and Technology (SMART) valves’ ability to control flow and assess environmental parameters stands out for these requirements. Their ability to sustain the downstream flow rate, prevent reverse flow, and maintain pressure in the heat transport loop is much more efficient with the integration of sensors and intelligent algorithms. For assessing valve performance and monitoring, mechanical design and operating conditions are two important parameters. In this study, the butterfly valves of three different sizes are simulated with water and steam using STAR-CCM+ in various flow regimes and positions to analyze performance parameters to strategize an automated control system for efficiently balancing the heat–transport network. Also, flow behavior is studied using velocity and pressure fields for valve–body geometry optimization. It can be observed, through performance parameters, that the valves are suitable for operation between 30° and 90° positions with significantly low loss coefficients and high flow coefficients, and the performance parameters follow a certain pattern in both water and steam flow in each scenario.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗