Control-Centric Living Laboratory for Management of Distributed Energy Resources
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The author has identified the following significant results. Visual examination of RB-57F color infrared imagery of range sites within Test Site 313 indicates that early season imagery will show significant differences in appearance of sub-irrigated sites as compared to dry valley sites. Differences appear to be significant also when comparing the previous two sites to sands sites. Comparison of existing soil map soils delineations with vegetative growth patterns shows reasonably good agreement between the two patterns over rather broad areas. Visual examination of ERTS-1 imagery has also shown that rangeland burned by prairie fire within the last six months can be distinguished. Three confirmed fire areas have been shown on the imagery. Since only broad estimates of burned acres are available, more accurate acreage measurements will be attempted. Known acreage of burned areas will be of value to those agencies responsible for deferred grazing payments to land owners. The relative speed with which this acreage information would become available to these agencies through ERTS-1 imagery would be of much benefit.
The author has identified the following significant results. There appears to be a direct relationship between densitometry values obtained with MSS band 5 imagery and forage density for those range sites measured on the imagery, provided site category identification is indicated by other forms of imagery or ground truth. Overlap of density values for different site categories with differing forage condition classes does not allow assigning a given forage density value for a given densitometer value unless the range site category is known.
The author has identified the following significant results. Collection of ground truth data provided ground cover percent and the components of ground cover makeup. Percent bare soil appears to have greatest influence on imagery density of sites studied. Forage density estimates can be made on band 5 of MSS, provided site category identification is known. Additional data are provided concerning forage density and vegetation-soil relationship by color composites of MSS imagery. Reflectance differences shown on MSS bands 6 and 7 by Sand Hills lakes are related to water quality and possibly more specifically to total dissolved ions present in the water. Winter imagery with snow cover and low sun angle shows a marked enhancement of topography are associated with differences in forage density. High altitude color infrared photography appears to be a usable tool for recognition, measurement, and evaluation of go-back land.
The author has identified the following significant results. Interpretations of imagery from the Earth Resources Technology Satellite (ERTS-1) indicate that soil associations and attendant range sites can be identified on the basis of vegetation and topography using multitemporal imagery. Optical density measurements of imagery from the visible red band of the multispectral scanner(MSS band 5) obtained during the growing season were related to field measurements of vegetative biomass, a factor that closely parallels range condition class on specific range sites. ERTS-1 imagery also permitted inventory and assessment of center-pivot irrigation systems in the Sand Hills region in relation to soil and topographic conditions and energy requirements. Four resource maps of the Upper Loup Natural Resource District located entirely within the Sand Hills region were prepared from ERTS-1 imagery.
The author has identified the following significant results. Increase in radiance values is directly related to decrease in vegetative biomass, though not in a linear manner. Should the relationship hold true over an entire growing season, this would allow an extremely rapid evaluation of range condition. Computer access by remote terminal would allow production of this type of range condition evaluation in near real time, which is essential if grazing practice decisions are to be made based on satellite imagery acquisition. Negating the manipulation of photographic products appears to be the logical way to provide satellite imagery data to the user in near real time. There appears to be a direct linear relationship between radiance values of bands 4 and 5 and increase in total inorganic ions (6 ions) of lakes in the Sand hills region. Consistent ion concentration of lakes during the year could allow their radiance values to serve as a means of equating radiance values from image to image.
Interpretations of imagery from the Earth Resources Technology Satellite (ERTS-1) indicate that soil associations and attendant range sites can be identified on the basis of vegetation and topography using multi-temporal imagery. Optical density measurements of imagery from the visible red band of the multispectral scanner (MSS band 5) obtained during the growing season were related to field measurements of vegetative biomass, a factor that closely parallels range condition class on specific range sites. ERTS-1 imagery also permitted inventory and assessment of center-pivot irrigation systems in the Sand Hills region in relation to soil and topographic conditions and energy requirements.
There are no author-identified significant results in this report.
The author has identified the following significant results. Evaluation of ERTS-1 imagery for the Sand Hills region of Nebraska has shown that the data can be used to effectively measure several parameters of inventory needs. (1) Vegetative biomass can be estimated with a high degree of confidence using computer compatable tape data. (2) Soils can be mapped to the subgroup level with high altitude aircraft color infrared photography and to the association level with multitemporal ERTS-1 imagery. (3) Water quality in Sand Hills lakes can be estimated utilizing computer compatable tape data. (4) Center pivot irrigation can be inventoried from satellite data and can be monitored regarding site selection and relative success of establishment from high altitude aircraft color infrared photography. (5) ERTS-1 data is of exceptional value in wide-area inventory of natural resource data in the Sand Hills region of Nebraska.
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While Waste Management budgets are shrinking, DOE required cost and schedule controls are becoming increasingly stringent. At the same time, there is a scarcity of adept, qualified, and competent projects controls staff who both understand nuclear waste management and are capable of addressing today's cost and schedule challenges. In response, we have developed a systematic approach to training and mentoring project controls staff. The approach is based on the observations and lessons learned on projects, both successful and unsuccessful, over the past 20 years. During that time, we evaluated staff development and used that experience to design a program that progresses the maturity, knowledge and experience of the individual. The program is based on the unique needs of cost and schedule specialists while incorporating the best leadership and managerial applications. The system is not limited to developing individual software skills, which is a primary focus of many project controls training programs. Instead, our system develops an individual's soft and hard skill sets. The system develops the user's skill, talent, attitude, and drive to do the best job possible. It focuses on all aspects of becoming a more productive technical team while accepting responsibility for individual growth. It also enhances the project controls team by setting up checks and balances that everyone is aware of and participates in. The system is based on 14 steps of increasing complexity in knowledge and application. The system clarifies roles, responsibilities and expectations. It helps eliminate uncertainty and reduces stress on staff and managers. It contains everyday routine actions and is simple to implement. It allows the development of a consistent rhythm to staff growth and development. Mastering the steps will allow the user to achieve excellence in cost and schedule control. The 14 steps are: 1 - Key Performance Objectives, 2 - Check Lists, 3 - Desktop Guides, 4 - System Description, 5 - Procedures, 6 - Software and On the Job Training (OTJ), 7 - Traceability Checks, 8 - Surveillances, 9 - 32 Criteria, 10 - The Contract, 11 - Customer/Government Guidance, 12 - Training and Mentoring Others, 13 - Master your weekly and daily schedules, 14 - Improving your interpersonal skills. Application and mastery of this system will produce better cost and schedule control results. Your project controls staff will write better reports, analyze data better, make better use of their time, and be more valuable to decision makers. If followed rigorously, our system will produce a great project controls team, which is invaluable to the success of each project. (authors)
The CMS Submission Infrastructure is the primary system for managing computing resources for CMS workflows, including data processing, simulation, and analysis. It integrates geographically distributed resources from Grid, HPC, and cloud providers into federated pools managed by HTCondor and Glidein- WMS, for a total of around 500k CPU cores. This system dynamically manages workloads based on priorities defined by the collaboration. Additionally, CMS scheduling strategies must be flexible to handle multiple concurrent workloads while considering changing processing demands and resource availability from various providers.Efficient utilization of vast amounts of distributed compute resources is a key element for the success of the scientific programs of the LHC experiments. Optimizing the system is essential to maximize resource efficiency and fully utilize the distributed computing power. The CMS Submission Infrastructure team thus systematically investigates sources of inefficiency in workload scheduling to reduce their impact. In addition, a strategy of pilot overloading has been introduced to compensate for other inefficiency sources, thereby optimizing resource utilization and enhancing computational throughput.
Information needs of those concerned with the harvest and management of coastal fishery resources can be satisfied in part through applications of satellite remote sensing. Recently completed and ongoing investigations have demonstrated potentials for defining fish distribution patterns from multispectral data, monitoring fishing distribution and effort with synthetic aperture radar systems, forecasting recruitment of certain estuarine-dependent species, and tracking marine mammals. These investigations, which are reviewed in this paper, have relied on Landsat 1 and 2, Skylab-3, and Nimbus-6 supported sensors and sensors carried by aircraft and mounted on surface platforms to simulate applications from Seasat-A and other future spacecraft systems. None of the systems are operational as all were designed to identify and demonstrate applications and to aid in the specification of requirements for future spaceborne systems.
Landsat data remains a vital tool for the management of resources in Alaska. Utilization of these data by many agencies in Alaska trends toward the solution to operational problems in a wide spectrum of disciplinary applications. Four examples of current applications are reviewed briefly: mapping of coastal sediment plumes, mapping of coastal zone ecosystems, mapping of landform and ground cover for proposed national parks and forests, and evaluation of seismic risks for a proposed hydroelectric project.
Deep learning models are efficient computational tools that can accelerate the inverse design of molecules with desired functional properties by generating predictions at a fraction of the time required by traditional quantum chemical approaches. To ensure that a model maintains accuracy and transferability across broad regions of the chemical space explored during the inverse design, it must be trained on massively large volumes of simulation data. This requires running large-scale ensemble quantum chemical calculations on high-performance computing (HPC) systems for data collection. However, the efficient execution of such large ensemble calculations and the management of large volumes of output data require tools that can judiciously utilize computational resources and manage metadata overhead on the file system. Therefore, we present a high-performance, scalable, ensemble management framework for performing data-intensive quantum chemical electronic structure calculations for organic molecules. This framework provides abstractions to plug different ab initio, first principles, and first principles-based semi-empirical methods and executes them efficiently at large scale on HPC systems. It dynamically distributes tasks to resources and uses tiered storage for managing large collections of files. We employed this framework to process over ten million organic molecules and generate open-source datasets that provide UV-vis absorption spectra by running time-dependent density-functional tight-binding calculations. It is the largest database containing molecular optical spectra that were simulated with quantum chemical methods in a consistent manner.
International administration of ocean resources and US policy toward deep sea bed data management
This presentation provides an overview of the National Renewable Energy Laboratory's advanced distribution management system test bed overview.