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At least 649 records · Page 36

Design of an expert system for estimating the cost of new knowledge in high energy astrophysics

The High Energy Astrophysics Costing Tool (HEACT) is a combined Expert System/Numerical Simulation to evaluate sensors and experiments proposed for space platforms in order to determine their expected performance and to assess the amount and quality of scientific information likely to be gathered by such experiments. The end product of this tool will be both a cost estimate for the experiment package as deployed and also an estimate of the amount of new scientific knowledge (both new data and reductions in the uncertainties of previous measurements) which would result from the actual deployment and operation of that experiment package. The numerical simulation part of HEACT will contain components to: (1) calculate the high energy signatures of both actual and proposed classes of astrophysical objects, and (2) model the response and resolution of the candidate sensors for observing those objects. The rule based part of the HEACT will be based on knowledge in the areas of experiment design, instrument selection, and system integration developed from experience with existing high energy astrophysics observatories, both orbiting and lofted by rockets or balloons. This paper presents mainly results from the design of the rule-based part of HEACT. It focuses on the structure of the rules and the structures used to represent the knowledge related to the design and integration of such experiments. Methods for integrating the results from numerical simulations into the expert system will also be discussed.

Bosworth, Edward L., Jr.↗

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2018

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group. This package includes data from 34 flights flown over the NGEE-Arctic Council Mile Maker 72 (MM72), Kougarok MM64, Kougarok MM80, and Teller MM27 sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provide the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of the L0 data, and file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Data Processing Package for Cyclic Integrated Reversible Bending Fatigue Testing

A data processing software package has been introduced. The package was developed using MATLAB with the aid of the Curve Fitting Toolbox. The package is made up of four modules: pre-processing, data processing for static testing, data processing for monitoring, and data processing for measurements. CIRFT data are structured with multiple levels of architecture involving group, specimen, session, and scan/block. The degree of complexity of the data structure depends on whether a test is static or cyclic.The test results are presented in figures, scatter plots, and tables. For static testing, the output in tables provides bending mechanical properties and characteristic points of moment–curvature relation: flexural rigidities in linear segments of loading and unloading stages, intersection points between characteristic segments of the curve, and equivalent stress and strain quantities. For cyclic testing, the table output lists control and fatigue life and responsive/dependent quantities including moment, curvature, flexural rigidity, flexural hysteresis, rigidity phase angle, and equivalent stresses and strains. In addition, derivatives such as half-gage length and sensor spacing correction are included. The output also provides standard deviations of the reported quantities when they are applicable or available. The data processing package can serve as a fundamental characterization tool in mechanical study of materials. The package is intended primarily for data processing for the CIRFT process and can also be used in applications for which similar testing requirements exist.

36 MATERIALS SCIENCE↗

Development of a MEMS dual-axis differential capacitance floating element shear stress sensor

A single-axis MEMS wall shear stress sensor with differential capacitive transduction method is produced. Using a synchronous modulation and demodulation interface circuit, the system is capable of making real time measurements of both mean and fluctuating wall shear stress. A sensitivity of 3.44 mV/Pa is achieved, with linearity in response demonstrated up to testing limit of 2 Pa. Minimum detectable signals of 340 μPa at 100 Hz and 120 μPa at 1 kHz are indicated, with a resonance of 3.5 kHz. Multiple full scale wind tunnel tests are performed, producing spectral measurements of turbulent boundary layers in wind speeds ranging up to 0.5 Ma (18 Pa of mean wall shear stress). The compact packaging allows for minimally invasive installation, and has proven relatively robust over multiple testing events. Temperature sensitivity, likely due to poor CTE matching of packaged materials, is an ongoing concern being addressed. These successes are being directly leveraged into a development plan for a dual-axis wall shear stress sensor, capable of producing true vector estimates at the wall.

47 OTHER INSTRUMENTATION↗

Sap Velocity Data for Urban Trees in Chicago, Illinois (2024-2025)

This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.

Chicago↗

Sapflow raw and translated data, 2015 - 2017, BR-Ma2: Manaus

Raw sapflow data from K34 tower site on a plateau near Manaus, Brazil. These are mostly raw data from the data loggers, except in the case of the ICT sensors where the datalogger output was translated using ICT software. One heat ratio sap flow sensor (SFM1, ICT international) was installed per tree. Tree biophysical characteristics for each tree were used with Sap Flow Tool version 1.4.1 (ICT International/Phyto-IT) to calculate sap velocities from raw data downloaded from the SFM1 sap flow sensors in the field. Attached data files include data, sensor manuals, and detailed methods. Related metadata is contained in referenced dataset. This dataset replaces the sapflow data of two retired packages, http://dx.doi.org/10.15486/ngt/1507764 and http://dx.doi.org/10.15486/ngt/1507767

54 ENVIRONMENTAL SCIENCES↗

New accelerometers under development

The commercial viability of the Space Station requires that it provide a micro-g, or submicro-g environment to users. This represents significant improvement over existing systems. Attainment of the lowest micro-g levels requires isolation systems. Passive and active systems have been evaluated. Best performance is achieved using active approaches where accelerometer sensors close feedback loops. Two emerging accelerometer technologies are presented that have promise for meeting performance goals while achieving reductions of package size, weight, and power. The technologies addressed are Honeywell's design concept for an optical cavity locking accelerometer and the recent development of an integrated silicon accelerometer for government applications.

Wald, Jerry↗

Microsensors and Microinstruments for Space Science and Exploration

Most future NASA spacecraft will be small, low cost, highly integrated vehicles using advanced technology. This will also be true of planetary rovers. In order to maintain a high scientific value to these missions, the instruments, sensors and subsystems must be dramatically miniaturized without compromising their measurement capabilities. A rover must be designed to deliver its science package. In fact, the rover should be considered as the arms, legs and/or wheels that are needed to enable a mobile integrated scientific payload.

Kukkonen, C. A.↗

MEMS Applications in Aerodynamic Measurement Technology

Microelectromechanical systems (MEMS) embodies the integration of sensors, actuators, and electronics on a single substrate using integrated circuit fabrication techniques and compatible bulk and surface micromachining processes. Silicon and its derivatives form the material base for the MEMS technology. MEMS devices, including microsensors and microactuators, are attractive because they can be made small (characteristic dimension about 100 microns), be produced in large numbers with uniform performance, include electronics for high performance and sophisticated functionality, and be inexpensive. For aerodynamic measurements, it is preferred that sensors be small so as to approximate measurement at a point, and in fact, MEMS pressure sensors, wall shear-stress sensors, heat flux sensors and micromachined hot wires are nearing application. For the envisioned application to wind tunnel models, MEMS sensors can be placed on the surface or in very shallow grooves. MEMS devices have often been fabricated on stiff, flat silicon substrates, about 0.5 mm thick, and therefore were not easily mounted on curved surfaces. However, flexible substrates are now available and heat-flux sensor arrays have been wrapped around a curved turbine blade. Electrical leads can also be built into the flexible substrate. Thus MEMS instrumented wind tunnel models do not require deep spanwise grooves for tubes and leads that compromise the strength of conventionally instrumented models. With MEMS, even the electrical leads can potentially be eliminated if telemetry of the signals to an appropriate receiver can be implemented. While semiconductor silicon is well known for its electronic properties, it is also an excellent mechanical material for MEMS applications. However, silicon electronics are limited to operations below about 200 C, and silicon's mechanical properties start to diminish above 400 C. In recent years, silicon carbide (SiC) has emerged as the leading material candidate for applications in high temperature environments and can be used for high-temperature MEMS applications. With SiC, diodes and more complex electronics have been shown to operate to about 600 C, while the mechanical properties of SiC are maintained to much higher temperatures. Even when MEMS devices show benefits in the laboratory, there are many packaging challenges for any aeronautics application. Incorporating MEMS into these applications requires new approaches to packaging that goes beyond traditional integrated circuit (IC) packaging technologies. MEMS must interact mechanically, as well as electrically with their environment, making most traditional chip packaging and mounting techniques inadequate. Wind tunnels operate over wide temperature ranges in an environment that is far from being a 'clean-room.' In flight, aircraft are exposed to natural elements (e.g. rain, sun, ice, insects and dirt) and operational interferences(e.g. cleaning and deicing fluids, and maintenance crews). In propulsion systems applications, MEMS devices will have to operate in environments containing gases with very high temperatures, abrasive particles and combustion products. Hence deployment and packaging that maintains the integrity of the MEMS system is crucial. This paper presents an overview of MEMS fabrication and materials, descriptions of available sensors with more details on those being developed in our laboratories, and a discussion of sensor deployment options for wind tunnel and flight applications.

Reshotko, E.↗

Imaging Beyond What Man Can See

Three lightweight, portable hyperspectral sensor systems have been built that capture energy from 200 to 1700 nanometers (ultravio1et to shortwave infrared). The sensors incorporate a line scanning technique that requires no relative movement between the target and the sensor. This unique capability, combined with portability, opens up new uses of hyperspectral imaging for laboratory and field environments. Each system has a GUI-based software package that allows the user to communicate with the imaging device for setting spatial resolution, spectral bands and other parameters. NASA's Space Partnership Development has sponsored these innovative developments and their application to human problems on Earth and in space. Hyperspectral datasets have been captured and analyzed in numerous areas including precision agriculture, food safety, biomedical imaging, and forensics. Discussion on research results will include realtime detection of food contaminants, molds and toxin research on corn, identifying counterfeit documents, non-invasive wound monitoring and aircraft applications. Future research will include development of a thermal infrared hyperspectral sensor that will support natural resource applications on Earth and thermal analyses during long duration space flight. This paper incorporates a variety of disciplines and imaging technologies that have been linked together to allow the expansion of remote sensing across both traditional and non-traditional boundaries.

May, George↗

Monolithic short wave infrared (SWIR) detector array

A monolithic self-scanned linear detector array was developed for remote sensing in the 1.1- 2.4-micron spectral region. A high-density IRCCD test chip was fabricated to verify new design approaches required for the detector array. The driving factors in the Schottky barrier IRCCD (Pdsub2Si) process development are the attainment of detector yield, uniformity, adequate quantum efficiency, and lowest possible dark current consistent with radiometric accuracy. A dual-band module was designed that consists of two linear detector arrays. The sensor architecture places the floating diffusion output structure in the middle of the chip, away from the butt edges. A focal plane package was conceptualized and includes a polycrystalline silicon substrate carrying a two-layer, thick-film interconnecting conductor pattern and five epoxy-mounted modules. A polycrystalline silicon cover encloses the modules and bond wires, and serves as a radiation and EMI shield, thermal conductor, and contamination seal.

Source record↗

The use of aircraft and satellite remote sensing of phytoplankton chlorophyll concentrations in case 2 estuarine waters of the Chesapeake Bay

Two projects using remote sensing of phytoplankton chlorophyll concentrations in the Chesapeake Bay estuary were proposed. The first project used aircraft remote sensing with a compact radiometer system developed at NASA's Goddard Space Flight Center (GSFC), the Ocean Data Acquisition System (ODAS). ODAS includes three radiometers at 460, 490, and 520 nm, an infrared temperature sensor (PRT-5), Loran-C for navigation, and a data acquisition system using a PC and mass storage device. This instrument package can be flown in light aircraft at relatively low expense, permitting regular and frequent flights. Sixteen flights with ODAS were completed using the Virginia Institute of Marine Science's De Havilland 'Beaver'. The goal was to increase spatial and temporal resolution in assaying phytoplankton pigment concentrations in the Chesapeake. At present, analysis is underway of flight data collected between March and July 1989. The second project focused on satellite data gathered with the Nimbus-7 Coastal Zone Color Scanner (CZSC) between late 1978 and mid 1986. The problem in using CZSC data for the Chesapeake Bay is that the optical characteristics of this (and many) coastal and estuarine waters are distinct from those of the open ocean for which algorithms for computing pigment concentrations were developed. The successful use of CZCS data for the estuary requires development of site-specific algorithms and analytical approaches. Of principal importance in developing site-specific procedures is the availability of in-situ data on pigment concentrations. A significant data set was acquired from EPA's Chesapeake Bay Program in Annapolis, Maryland, and clear satellite scenes are being analyzed for which same-day sea truth measurements of pigment were obtained. Both the University of Miami and GSFC Seapak systems are being used in this effort. The main finding to date is an expected one, i.e., the algorithms developed for oceanic waters are inadequate to compute pigment concentrations for the Case 2 waters of the Chesapeake Bay. One reason is the overestimation of aerosol radiances by assuming that water-leaving radiance in Band 4 of CZCS (670 nm) is zero, an assumption that is invalid for the Bay. This prompted any attempts to iterative procedures for estimating the proportion of the Band 4 radiance that is actually attributable to aerosol by estimating the water-leaving component using optical data. A cruise on the Chesapeake the week of 7 August 1989 was conducted to collect additional optical data necessary to this task.

Harding, Lawrence W., Jr.↗

A Microinstrumentation System for Remote Environmental Monitoring

This paper reports on a hybrid micro-instrumentation system that includes a embedded micro-controller, transducers for monitoring environmental parameters, interface/readout electronics for linking the controller and the transducers, and custom circuitry for system power management. Sensors for measuring temperature, pressure, humidity, and acceleration are included in the initial system, which operates for more than 180 days and dissipates less than 700 microW from a 6V battery supply. The sensor scan rate is adaptive and can be event triggered. The system communicates internally over a 1 MHz, nine-line intramodule sensor bus and outputs data over a hard-wired serial interface or a 315MHz wireless link. The use of folding platform packaging allows an internal system volume as small as 5 cc.

Mason, Andrew↗

Machine Vision Applied to Navigation of Confined Spaces

The reliability of space related assets has been emphasized after the second loss of a Space Shuttle. The intricate nature of the hardware being inspected often requires a complete disassembly to perform a thorough inspection which can be difficult as well as costly. Furthermore, it is imperative that the hardware under inspection not be altered in any other manner than that which is intended. In these cases the use of machine vision can allow for inspection with greater frequency using less intrusive methods. Such systems can provide feedback to guide, not only manually controlled instrumentation, but autonomous robotic platforms as well. This paper serves to detail a method using machine vision to provide such sensing capabilities in a compact package. A single camera is used in conjunction with a projected reference grid to ascertain precise distance measurements. The design of the sensor focuses on the use of conventional components in an unconventional manner with the goal of providing a solution for systems that do not require or cannot accommodate more complex vision systems.

Briscoe, Jeri M.↗

Transparent flexible nanogenerator as self-powered sensor for transportation monitoring

A traffic sensor includes a flexible substrate having a top surface. A piezoelectric structure extends from the first electrode layer. The piezoelectric structure has a top end. An insulating layer is infused into the piezoelectric structure. A first electrode layer is disposed on top of the insulating layer. A second electrode layer is disposed below the flexible substrate. A packaging layer is disposed around the substrate, the first electrode layer, the piezoelectric structure, the insulating layer and the second electrode layer. In a method of sensing a traffic parameter, a piezoelectric nanostructure-based traffic sensor is applied to a roadway. An electrical event generated by the piezoelectric nanostructure-based traffic sensor in response to a vehicle interacting with the piezoelectric nanostructure-based traffic sensor is detected. The electrical event is correlated with the traffic parameter.

36 MATERIALS SCIENCE↗

FTICR-MS, Sensor, and Environmental Data from 5 Streams Impacted by the 2020 Holiday Farm Fire Associated with: "Spatiotemporal controls on the delivery of dissolved organic matter to streams following a wildfire"

This data package is associated with the publication "Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire" submitted to Geophysical Research Letters (Roebuck et al., 2022). The study aims to understand storm induced transport of pyrogenic materials to streams impacted by varying degrees of burn severity. Time series samples (24 samples in 1-hour intervals) were collected at 5 sites within the McKenzie River Watershed (Oregon, USA) whose catchment were each completely engulfed by the 2020 Holiday Farm Fire. The samples were collected in November 2020 during the first major storm pulse following the conclusion of the wildfire. Samples were characterized for dissolved organic carbon, total dissolved nitrogen, and by ultra-high resolution mass spectrometry. In situ turbidity data also collected.This data package contains 4 primary folders that include the following: 1) Metadata, 2) EnvData (Environmental Data), 3) SensorData, and 4) FTICR_SupportingData. The package contains a single file-level metadata (flmd) file. Each primary folder also contains individual data dictionaries (dd) to define and provide descriptors of column/row headers and data flags. The FTICR_SupportingData, folder 4, contains raw, unprocessed FTICR-MS Data files in addition to a csv containing processed FTICR-MS data. This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗

Wireless Data-Acquisition System for Testing Rocket Engines

A prototype wireless data-acquisition system has been developed as a potential replacement for a wired data-acquisition system heretofore used in testing rocket engines. The traditional use of wires to connect sensors, signal-conditioning circuits, and data acquisition circuitry is time-consuming and prone to error, especially when, as is often the case, many sensors are used in a test. The system includes one master and multiple slave nodes. The master node communicates with a computer via an Ethernet connection. The slave nodes are powered by rechargeable batteries and are packaged in weatherproof enclosures. The master unit and each of the slave units are equipped with a time-modulated ultra-wide-band (TMUWB) radio transceiver, which spreads its RF energy over several gigahertz by transmitting extremely low-power and super-narrow pulses. In this prototype system, each slave node can be connected to as many as six sensors: two sensors can be connected directly to analog-to-digital converters (ADCs) in the slave node and four sensors can be connected indirectly to the ADCs via signal conditioners. The maximum sampling rate for streaming data from any given sensor is about 5 kHz. The bandwidth of one channel of the TM-UWB radio communication system is sufficient to accommodate streaming of data from five slave nodes when they are fully loaded with data collected through all possible sensor connections. TM-UWB radios have a much higher spatial capacity than traditional sinusoidal wave-based radios. Hence, this TM-UWB wireless data-acquisition can be scaled to cover denser sensor setups for rocket engine test stands. Another advantage of TM-UWB radios is that it will not interfere with existing wireless transmission. The maximum radio-communication range between the master node and a slave node for this prototype system is about 50 ft (15 m) when the master and slave transceivers are equipped with small dipole antennas. The range can be increased by changing to larger antennas and/or greater transmission power. The battery life of a slave node ranges from about six hours during operation at full capacity to as long as three days when the system is in a "sleep" mode used to conserve battery charge during times between setup and rocket-engine testing. Batteries can be added to prolong operational lifetimes. The radio transceiver dominates the power consumption.

Lin, Chujen↗

Model Based Optimal Sensor Network Design for Condition Monitoring in an IGCC Plant

This report summarizes the achievements and final results of this program. The objective of this program is to develop a general model-based sensor network design methodology and tools to address key issues in the design of an optimal sensor network configuration: the type, location and number of sensors used in a network, for online condition monitoring. In particular, the focus in this work is to develop software tools for optimal sensor placement (OSP) and use these tools to design optimal sensor network configuration for online condition monitoring of gasifier refractory wear and radiant syngas cooler (RSC) fouling. The methodology developed will be applicable to sensing system design for online condition monitoring for broad range of applications. The overall approach consists of (i) defining condition monitoring requirement in terms of OSP and mapping these requirements in mathematical terms for OSP algorithm, (ii) analyzing trade-off of alternate OSP algorithms, down selecting the most relevant ones and developing them for IGCC applications (iii) enhancing the gasifier and RSC models as required by OSP algorithms, (iv) applying the developed OSP algorithm to design the optimal sensor network required for the condition monitoring of an IGCC gasifier refractory and RSC fouling. Two key requirements for OSP for condition monitoring are desired precision for the monitoring variables (e.g. refractory wear) and reliability of the proposed sensor network in the presence of expected sensor failures. The OSP problem is naturally posed within a Kalman filtering approach as an integer programming problem where the key requirements of precision and reliability are imposed as constraints. The optimization is performed over the overall network cost. Based on extensive literature survey two formulations were identified as being relevant to OSP for condition monitoring; one based on LMI formulation and the other being standard INLP formulation. Various algorithms to solve these two formulations were developed and validated. For a given OSP problem the computation efficiency largely depends on the “size” of the problem. Initially a simplified 1-D gasifier model assuming axial and azimuthal symmetry was used to test out various OSP algorithms. Finally these algorithms were used to design the optimal sensor network for condition monitoring of IGCC gasifier refractory wear and RSC fouling. The sensors type and locations obtained as solution to the OSP problem were validated using model based sensing approach. The OSP algorithm has been developed in a modular form and has been packaged as a software tool for OSP design where a designer can explore various OSP design algorithm is a user friendly way. The OSP software tool is implemented in Matlab/Simulink© in-house. The tool also uses few optimization routines that are freely available on World Wide Web. In addition a modular Extended Kalman Filter (EKF) block has also been developed in Matlab/Simulink© which can be utilized for model based sensing of important process variables that are not directly measured through combining the online sensors with model based estimation once the hardware sensor and their locations has been finalized. The OSP algorithm details and the results of applying these algorithms to obtain optimal sensor location for condition monitoring of gasifier refractory wear and RSC fouling profile are summarized in this final report.

20 FOSSIL-FUELED POWER PLANTS↗