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At least 559 records · Page 31

State involvement in and use of LANDSAT technology

The background of state involvement in LANDSAT systems planning and the status of state LANDSAT use are reviewed. Major recommendations on data continuity; frequency and pattern of observation; state representation in program management; pointable sensors for a fully operational system; data processing systems; data pricing; data copyright; data archival; and technology transfer are highlighted. Plans of the government regarding the LANDSAT system are reflected in the FY-1982 budget process are examined.

Tessar, P. A.↗

Optimal control to handle variations in moisture content and reactor in-feed rate

The variations in feedstock characteristics, such as moisture and particle size distribution, lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass pre-processing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by up to 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. Additionally, HPC reduces the cost of processing biomass by 0.36%–2.22%, and reduces processing time by 0.35%-2.24%. Furthermore, a biorefinery can adapt HPC to achieve its design capacity.

09 BIOMASS FUELS↗

Integrating NASA's Land Analysis System (LAS) image processing software with an appropriate Geographic Information System (GIS): A review of candidates in the public domain

A user requirements analysis (URA) was undertaken to determine and appropriate public domain Geographic Information System (GIS) software package for potential integration with NASA's LAS (Land Analysis System) 5.0 image processing system. The necessity for a public domain system was underscored due to the perceived need for source code access and flexibility in tailoring the GIS system to the needs of a heterogenous group of end-users, and to specific constraints imposed by LAS and its user interface, Transportable Applications Executive (TAE). Subsequently, a review was conducted of a variety of public domain GIS candidates, including GRASS 3.0, MOSS, IEMIS, and two university-based packages, IDRISI and KBGIS. The review method was a modified version of the GIS evaluation process, development by the Federal Interagency Coordinating Committee on Digital Cartography. One IEMIS-derivative product, the ALBE (AirLand Battlefield Environment) GIS, emerged as the most promising candidate for integration with LAS. IEMIS (Integrated Emergency Management Information System) was developed by the Federal Emergency Management Agency (FEMA). ALBE GIS is currently under development at the Pacific Northwest Laboratory under contract with the U.S. Army Corps of Engineers' Engineering Topographic Laboratory (ETL). Accordingly, recommendations are offered with respect to a potential LAS/ALBE GIS linkage and with respect to further system enhancements, including coordination with the development of the Spatial Analysis and Modeling System (SAMS) GIS in Goddard's IDM (Intelligent Data Management) developments in Goddard's National Space Science Data Center.

Rochon, Gilbert L.↗

Making tomorrow's mistakes today: Evolutionary prototyping for risk reduction and shorter development time

In the early days of JPL's solar system exploration, each spacecraft mission required its own dedicated data system with all software applications written in the mainframe's native assembly language. Although these early telemetry processing systems were a triumph of engineering in their day, since that time the computer industry has advanced to the point where it is now advantageous to replace these systems with more modern technology. The Space Flight Operations Center (SFOC) Prototype group was established in 1985 as a workstation and software laboratory. The charter of the lab was to determine if it was possible to construct a multimission telemetry processing system using commercial, off-the-shelf computers that communicated via networks. The staff of the lab mirrored that of a typical skunk works operation -- a small, multi-disciplinary team with a great deal of autonomy that could get complex tasks done quickly. In an effort to determine which approaches would be useful, the prototype group experimented with all types of operating systems, inter-process communication mechanisms, network protocols, packet size parameters. Out of that pioneering work came the confidence that a multi-mission telemetry processing system could be built using high-level languages running in a heterogeneous, networked workstation environment. Experience revealed that the operating systems on all nodes should be similar (i.e., all VMS or all PC-DOS or all UNIX), and that a unique Data Transport Subsystem tool needed to be built to address the incompatibilities of network standards, byte ordering, and socket buffering. The advantages of building a telemetry processing system based on emerging industry standards were numerous: by employing these standards, we would no longer be locked into a single vendor. When new technology came to market which offered ten times the performance at one eighth the cost, it would be possible to attach the new machine to the network, re-compile the application code, and run. In addition, we would no longer be plagued with lack of manufacturer support when we encountered obscure bugs. And maybe, hopefully, the eternal elusive goal of software portability across different vendors' platforms would finally be available. Some highlights of our prototyping efforts are described.

Friedman, Gary↗

Dynamic voltage and frequency scaling based on memory channel slack

A processing system scales power to memory and memory channels based on identifying causes of stalls of threads of a wavefront. If the cause is other than an outstanding memory request, the processing system throttles power to the memory to save power. If the stall is due to memory stalls for a subset of the memory channels servicing memory access requests for threads of a wavefront, the processing system adjusts power of the memory channels servicing memory access request for the wavefront based on the subset. By boosting power to the subset of channels, the processing system enables the wavefront to complete processing more quickly, resulting in increased processing speed. Conversely, by throttling power to the remainder of channels, the processing system saves power without affecting processing speed.

Das, Shomit N.↗

Parallel Signal Processing and System Simulation using aCe

Recently, networked and cluster computation have become very popular for both signal processing and system simulation. A new language is ideally suited for parallel signal processing applications and system simulation since it allows the programmer to explicitly express the computations that can be performed concurrently. In addition, the new C based parallel language (ace C) for architecture-adaptive programming allows programmers to implement algorithms and system simulation applications on parallel architectures by providing them with the assurance that future parallel architectures will be able to run their applications with a minimum of modification. In this paper, we will focus on some fundamental features of ace C and present a signal processing application (FFT).

Dorband, John E.↗

Low-cost data analysis systems for processing multispectral scanner data

A research-oriented data analysis system was developed which is used for evaluating complex remote sensor systems and for development of techniques for application of remotely sensed data. Some modular hardware components were developed which may be added to one's existing facilities to establish a low-cost data analysis system for processing multispectral scanner data. Software modules which are compatible with small general purpose digital computers process and analyze remote sensor data, and convert it to information needed by users. The software modules are written in FORTRAN IV language for ease of transfer to other computer systems. The basic hardware and software system requirements are defined for some low-cost data analysis systems consisting of an image display system, a small general purpose digital computer, and an output recording device. The hardware modules consist of: a LANDSAT MSS data reformatting program; a series of spectral pattern recognition programs required to generate surface classification maps and tabular information; programs to convert computer generated maps from image space to a geographically referenced base; programs to extract data and irregularly shaped areas and to produce thematic maps of the designated areas; and programs to tabulate acreages of selected classification categories. Some off-the-shelf, inexpensive digital image display systems are described.

Whitley, S. L.↗

Combustion Performance and Emissions Optimization Through Integration of a Miniaturized High-Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗

Combustion Performance and Emissions Optimization through Integration of Miniaturized High Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗

Combustion Performance and Emissions Optimization Through Integration of a Miniaturized High-Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗

Combustion Performance and Emissions Optimization Through Integration of a Miniaturized High-Temperature Multi Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution of wall conditions in utility boilers. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of a coal-fired utility boiler in this project but can be applied to many other industries and applications as well. The new sensor design, leveraging the existing electrochemical noise-based monitoring system, is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data can be transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, five mMPMS were installed at a full-scale pulverized coal-fired plant, Basin Electric Power Cooperative’s Leland Olds Unit 1. The systems were demonstrated over a 6-week period during typical operation. Sensor measurements of deposit thickness were validated during the demonstration and subsequently leveraged to determine sensor-based boiler cleaning strategies. These strategies have the benefit of reduced thermal stresses on boiler tubes from over-cleaning and improved boiler water management. At the end of the project, continued development of the sensor technology was carried out at PacifiCorp’s Hunter Station. REI leveraged the permanent installation of the mMPMS in Unit 3 made possible by DOE funding on a separate program. The work at Hunter Plant focused on application of machine learning and artificial intelligence-based models for integration of sensor signals into control and optimization of Hunter Unit 3 processes.

42 ENGINEERING↗

Development of Miniaturized High-Temperature Multi-Process Monitoring System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings.

20 FOSSIL-FUELED POWER PLANTS↗

Intelligent Work Process Engineering System

Optimizing performance on work activities and processes requires metrics of performance for management to monitor and analyze in order to support further improvements in efficiency, effectiveness, safety, reliability and cost. Information systems are therefore required to assist management in making timely, informed decisions regarding these work processes and activities. Currently information systems regarding Space Shuttle maintenance and servicing do not exist to make such timely decisions. The work to be presented details a system which incorporates various automated and intelligent processes and analysis tools to capture organize and analyze work process related data, to make the necessary decisions to meet KSC organizational goals. The advantages and disadvantages of design alternatives to the development of such a system will be discussed including technologies, which would need to bedesigned, prototyped and evaluated.

Williams, Kent E.↗

Knowledge elicitation for an operator assistant system in process control tasks

A knowledge based system (KBS) methodology designed to study human machine interactions and levels of autonomy in allocation of process control tasks is presented. Users are provided with operation manuals to assist them in normal and abnormal situations. Unfortunately, operation manuals usually represent only the functioning logic of the system to be controlled. The user logic is often totally different. A method is focused on which illicits user logic to refine a KBS shell called an Operator Assistant (OA). If the OA is to help the user, it is necessary to know what level of autonomy gives the optimal performance of the overall man-machine system. For example, for diagnoses that must be carried out carefully by both the user and the OA, interactions are frequent, and processing is mostly sequential. Other diagnoses can be automated, in which the case the OA must be able to explain its reasoning in an appropriate level of detail. OA structure was used to design a working KBS called HORSES (Human Orbital Refueling System Expert System). Protocol analysis of pilots interacting with this system reveals that the a-priori analytical knowledge becomes more structured with training and the situation patterns more complex and dynamic. This approach can improve the a-priori understanding of human and automatic reasoning.

Boy, Guy A.↗

Using Systems Theoretic Process Analysis and Causal Analysis to Map and Manage Organizational Information to Enable Digitalization and Information Automation

The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Silicon Micromachined Sensor for Broadband Vibration Analysis

The development of a family of silicon based integrated vibration sensors capable of sensing mechanical resonances over a broad range of frequencies with minimal signal processing requirements is presented. Two basic general embodiments of the concept were designed and fabricated. The first design was structured around an array of cantilever beams and fabricated using the ARPA sponsored multi-user MEMS processing system (MUMPS) process at the Microelectronics Center of North Carolina (MCNC). As part of the design process for this first sensor, a comprehensive finite elements analysis of the resonant modes and stress distribution was performed using PATRAN. The dependence of strain distribution and resonant frequency response as a function of Young's modulus in the Poly-Si structural material was studied. Analytical models were also studied. In-house experimental characterization using optical interferometry techniques were performed under controlled low pressure conditions. A second design, intended to operate in a non-resonant mode and capable of broadband frequency response, was proposed and developed around the concept of a cantilever beam integrated with a feedback control loop to produce a null mode vibration sensor. A proprietary process was used to integrat a metal-oxide semiconductor (MOS) sensing device, with actuators and a cantilever beam, as part of a compatible process. Both devices, once incorporated as part of multifunction data acquisition and telemetry systems will constitute a useful system for NASA launch vibration monitoring operations. Satellite and other space structures can benefit from the sensor for mechanical condition monitoring functions.

Gutierrez, Adolfo↗

New Compressor Added to Glenn's 450- psig Combustion Air System

In September 1999, the Central Process Systems Engineering Branch and the Maintenance and the Central Process Systems Operations Branch, released for service a new high pressure compressor to supplement the 450-psig Combustion Air System at the NASA Glenn Research Center at Lewis Field. The new compressor, designated C-18, is located in Glenn s Central Air Equipment Building and is remotely operated from the Central Control Building. C-18 can provide 40 pounds per second (pps) of airflow at pressure to our research customers. This capability augments our existing system capacity (compressors C 4 at 38 pps and C-5 at 32 pps), which is generated from Glenn's Engine Research Building. The C-18 compressor was originally part of Glenn's 21-Inch Hypersonic Tunnel, which was transferred from the Jet Propulsion Laboratory to Glenn in the mid-1980's. With the investment of construction of facilities funding, the compressor was modified, new mechanical and electrical support equipment were purchased, and the unit was installed in the basement of the Central Air Equipment Building. After several weeks of checkout and troubleshooting, the new compressor was ready for long-term, reliable operations. With a total of 110 pps in airflow now available, Glenn is well positioned to support the high-pressure air test requirements of our research customers.

Swan, Jeffrey A.↗

Compiler-generated memory mapping hints

According to one embodiment, a method of creating compiler-generated memory mapping hints in a computer system includes analyzing code, by a compiler of the computer system, to identify data access patterns in the code. System configuration information defining data processing system characteristics of a target system for the code is accessed. The data processing system characteristics include a plurality of processing resources and memory domain characteristics relative to the processing resources. A preferred allocation of data in memory domains of the target system is determined based on mapping the code to one or more selected processing resources and mapping the data to one or more of the memory domains based on the memory domain characteristics relative to the one or more selected processing resources. The preferred allocation is stored as compiler-generated memory mapping hints in a format accessible by a physical memory mapping resource of the target system.

97 MATHEMATICS AND COMPUTING↗