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This presentation will be presented at the NNSS FY 2020 SDRD Annual (Webex) Meeting scheduled for September 23–24, 2020. Phenomenology and Node-Level Processing of MASINT Sensor Data across Distributed Sensor Networks STL-016-19, Year 2
Presentation to be presented during the Site-Directed Research and Development (SDRD) program FY 2021 review meeting (Webex), September 22–23, 2021.
Not Available
This is a report for the FY2021 annual program overview.
High-density airspace operations with multiple aircraft type and potentially noncooperative aircraft require distributed sensor detection and tracking systems to monitor airspace for safe, autonomous flight operations for advanced air mobility, urban air mobility, and high density small uncrewed air systems (SUAS) flight concepts. This work collected data using a distributed radar and camera sensor framework during the NASA Advanced Air Mobility High Density Vertiplex project SUAS flight operation. Node locations include on an onboard SUAS, affixed to the Landing and Impact Research Facility with approximate 200ft elevation, on a tripod on first-floor roof with an approximate elevation of 20 ft, and on a tripod on a concrete pad that is approximately 4 ft above sea level. Each node includes camera, radar, and GPS.
The objective of this work is to design and develop Low-Power RF SOI-CMOS Technology for Distributed Sensor Networks. We briefly report on the accomplishments in this work. We also list the impact of this work on graduate student research training/involvement.
In this paper, we describe the architecture of both the PATS and SAP systems and how these two systems interoperate with each other forming a unified capability for deploying intelligence in hostile environments with the objective of providing actionable situational awareness of individuals. The SAP system works in concert with the UICDS information sharing middleware to provide data fusion from multiple sources. UICDS can then publish the sensor data using the OGC's Web Mapping Service, Web Feature Service, and Sensor Observation Service standards. The system described in the paper is able to integrate a spatially distributed sensor system, operating without the benefit of the Web infrastructure, with a remote monitoring and control system that is equipped to take advantage of SWE.
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This project developed distributed fiber sensors for plastics gasification reactor for clean hydrogen production. These sensors can be directly inserted into gasification reactors to perform real-time, in-situ hydrogen and temperature profile measurements with 5-cm spatial resolution across the entire reactor chamber. Our research team will use this new sensor capability to study how feedstock mixtures, feedstock preparations, and air/steam flows impact feedstock consumption, hydrogen production, and harmful chemical production emissions.
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The aim of the project was to explore, define, and assess the possibilities of optical distributed sensing for feedback control. This type of sensor, which may have some impacts in the dynamic control of deformable structures and the monitoring of small displacements, can be divided into data acquisition, data processing, and control design. Analogue optical techniques, because they are noninvasive and afford massive parallelism may play a significant role in the acquisition and the preprocessing of the data for such a sensor. Assessing these possibilities was the aim of the first stage of this project. The scope of the proposed research was limited to: (1) the characterization of photorefractive resonators and the assessment of their possible use as a distributed optical processing element; and (2) the design of a control system utilizing signals from distributed sensors. The results include a numerical and experimental study of the resonator below threshold, an experimental study of the effect of the resonator's transverse confinement on its dynamics above threshold, a numerical study of the resonator above threshold using a modal expansion approach, and the experimental test of this model. A detailed account of each investigation, including methodology and analysis of the results are also included along with reprints of published and submitted papers.
A recent potential of distributed image processing is discussed. Applications in the control of flexible spacecraft are emphasized. Devices are currently being developed at NASA and in universities and industries that allow the real-time processing of holographic images. Within 5 years, it is expected that, in real-time, one may add or subtract holographic images at optical accuracy. Images are stored and processed in crystal mediums. The accuracy of their storage and processing is dictated by the grating level of laser holograms. It is far greater than that achievable using current analog-to-digital, pixel oriented, image digitizing and computing techniques. Processors using image processing algebra can conceptually be designed to mechanize Fourier transforms, least square lattice filters, and other complex control system operations. Thus, actuator command inputs derived from complex control laws involving distributed holographic images can be generated by such an image processor. Plans are revealed for the development of a Conjugate Optics Processor for control of a flexible object.
Effective and secure carbon subsurface storage, involving the deep underground injection of CO 2 into geological formations where it is permanently trapped, is paramount to mitigating CO 2 emissions (Figure I). Ensuring the integrity of these storage sites and detecting potential leakage through the casing annulus necessitates robust monitoring. This work provides the first integrated demonstration of a wireless casing-annulus monitoring architecture that can operate in highly attenuating cement-brine environments relevant to CO 2 storage. This project focused on developing and validating a novel sensor system for integration with autonomous monitoring near the cement reservoir interface. The goal was a fully integrated Technology Readiness Level (TRL) 4/5 field validation of a distributed wireless intelligent sensor system providing real-time, direct subsurface formation measurements to enhance fluid movement monitoring in the cemented casing annulus. Achieving this objective required the development and integration of 1) wireless autonomous microsensor technology by California Institute of Technology (Caltech); 2) sensor packaging and emplacement technology by Research Triangle Institute (RTI); and 3) smart well completions using wireless active casing collars and NOV pipe by the Sandia National Lab (SNL). The collaboration with the Caltech team in this project aimed to develop millimeter-scale radio frequency identification (RFID) sensors capable of detecting CO 2 , pH, and/or methane levels. These sensors are engineered to be impervious to fluids, allowing them to be mixed with cement and installed within the casing annulus. They operate using RFID protocols at frequencies of 902–928 MHz for both power and communication. A Sandia National Laboratories’ team engaged their expertise in the development of a Smart Collar system designed for the wireless data collection from these RFID sensors embedded in the cement annulus and transmission of this information to the ground surface via IntelliPipe/IntelliServ NOV drill pipe. This is accomplished through inductive coupling at the collar, which facilitates data transfer through each segment of the pipe. Because the system cannot transmit a direct current signal to power the Smart Collar, both power and communication were implemented using alternating current and electromagnetic signals at varying frequencies. Furthermore, the developed microsensor technology had to be demonstrated and validated in comparison with reference transducer measurements in a field test site at The University of Texas at Austin (UT-Austin). Although the full sensor suite did not reach field-deployment readiness, the system-level integration achieved in this project establishes a validated pathway for future incorporation of advanced microsensors.
The objective of this research is to develop micro-opto-mechanical system (MOMS)-based sensors for time- and space-resolved measurements of flow properties in aerodynamics applications. The measurement technique we propose uses optical resonances in dielectric micro-spheres that can be excited by radiation tunneling from optical fibers. It exploits the tunneling-induced and morphology-dependent shifts in the resonant frequencies. The shift in the resonant frequency is dependent on the size, shape, and index of refraction of the micro-sphere. A physical change in the environment surrounding a micro-bead can change one or more of these properties of the sphere thereby causing a shift in frequency of resonance. The change of the resonance frequency can be detected with high resolution by scanning a frequency-tunable laser that is coupled into the fiber and observing the transmission spectrum at the output of the fiber. It is expected that, in the future, the measurement concept will lead to a system of distributed micro-sensors providing spatial data resolved in time and space. The present project focuses on the development and demonstration of temperature sensors using the morphology-dependent optical resonances although in the latter part of the work, we will also develop a pressure sensor. During the period covered in this report, the optical and electronic equipment necessary for the experimental work was assembled and the experimental setup was designed for the single sensor temperature measurements. Software was developed for real-time tracking of the optical resonance shifts. Some preliminary experiments were also carried out to detect temperature using a single bead in a water bath.
Abstract In this paper, we computationally investigate the effects of metal coating length and coating coverage on the reflected spectrum of a long period grating (LPG) over a broad bandwidth. Simulation results indicate that coating the tail end of the fiber between the LPG and the end facet of the fiber provides a reflected spectrum that mimics the LPG transmission spectrum shape over a 400 nm bandwidth. Based on single LPG simulation results, we present the design of a distributed LPG structure containing a multiple number ( n ) of LPGs in reflection mode for the first time. Simulation results for n = 1, 2, and 3 are presented here to demonstrate the concept of a distributed reflective LPG design. It is expected that such a sensor will open a new window for distributed sensing using reflective LPGs.
Smart structures which contain dense two- or three-dimensional arrays of attached or embedded sensor elements inherently require signal multiplexing and processing capabilities to permit good spatial data resolution as well as the adequately short calculation times demanded by real time active feedback actuator drive circuitry. This paper reports the implementation of an in-line optical signal processor and its application in a structural sensing system which incorporates multiple discrete optical fiber sensor elements. The signal processor consists of an array of optical fiber couplers having tailored s-parameters and arranged to allow gray code amplitude scaling of sensor inputs. The use of this signal processor in systems designed to indicate the location of distributed strain and damage in composite materials, as well as to quantitatively characterize that damage, is described. Extension of similar signal processing methods to more complicated smart materials and structures applications are discussed.
The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM On-line Visualization and Analysis System precipitation and other satellite data products and services. AIS outputs will be ,integrated into existing operational decision support system for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that ,allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical ,parameters, area of interest, and time period; and the system generates an output ,on screen in a matter of seconds.
Abstract not provided.