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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Power Quality and Stability in a Cluster of Microgrids with Coordinated Power and Energy Management

Distributed Energy Resources (DER) such as photovoltaic (PV) systems and battery energy storage systems (BESS) can be operated collectively as microgrids. Microgrids can be effective in meeting local load requirements as well as in improving the power quality and stability in a modern power distribution system. Multiple microgrids can also be operated in a coordinated manner as a cluster, to improve the resiliency of the power distribution system. In the event of an outage caused by a transmission system failure, the microgrids in a cluster can use their distributed generation capacity and energy storage resources to recover and extend power availability to the critical loads in the system. In this paper, an illustrative cluster of two microgrids based on the IEEE 13-bus model with DERs has been used, to demonstrate the operation of the concept using real-time simulations. Using real-time simulations, capabilities such as switching reconfiguration following faults, identification of optimal DER placement for effective power quality management, and power electronic controller validation have been demonstrated. For the two-microgrid cluster, this paper also presents improvements in load voltage quality and

Chowdhury, Prithwiraj Roy↗
DOE OSTI2023

A comparison of Eulerian and semi-Lagrangian approaches for modeling stream water quality

This paper describes and compares some of the advantages and limitations of Eulerian and Lagrangian approaches to water quality modeling and introduces a mixed Eulerian-Lagrangian (or semi-Lagrangian) methodology that captures the strengths of both approaches. The semi-Lagrangian modeling approach is applied to advection-dominated rivers, and flexibly ensures unconditional stability for all time step durations and grid segmentations. The semi-Lagrangian modeling approach is demonstrated by applying it to estimate the dissolved oxygen concentrations in the Sava River in Slovenia, focusing on aspects of the methodology and findings that would be of broad interest to managers of water quality in fluvial water bodies. Results of comparisons of the semi-Lagrangian model with the Eulerian-based QUAL2K model in steady and non-steady scenarios demonstrate that while both models are fully capable of producing satisfactory results when optimally configured, the semi-Lagrangian approach offers accuracy and stability without sensitivity to the interaction of time step size and computational grid segmentation scheme.

Sava River↗
DOE OSTI2020

Groundwater Monitoring Report, U.S. Department of Energy Y-12 National Security Complex, Oak Ridge, Tennessee

This report contains the groundwater and surface water monitoring data obtained during calendar year (CY) 2019 at the U.S. Department of Energy (DOE) Y-12 National Security Complex (Y-12) on the DOE Oak Ridge Reservation (ORR) in Oak Ridge, Tennessee. The monitoring data were obtained from wells, springs, and surface water sampling locations in three hydrogeologic regimes at Y-12. The Bear Creek Hydrogeologic Regime (Bear Creek Regime) encompasses a section of Bear Creek Valley (BCV) between the west end of Y-12 and the west end of the Bear Creek Watershed (directions are in reference to the Y-12 grid system, shown as Plant North. The Upper East Fork Poplar Creek Hydrogeologic Regime (East Fork Regime) encompasses the Y-12 industrial facilities and support structures in BCV. The Chestnut Ridge Hydrogeologic Regime (Chestnut Ridge Regime) encompasses a section of Chestnut Ridge directly south of Y-12. Background information in Section 2 of this report outlines the hydrogeologic framework for groundwater and surface water quality monitoring at Y-12 and includes an overview of the groundwater contamination in each hydrogeologic regime. Section 3 provides details regarding the groundwater and surface water sampling and analysis activities implemented under the Y-12 GWPP, including sampling locations and frequency, sample collection and handling, field measurements and laboratory analytes, quality assurance (QA)/quality control (QC) sampling, data management, and data quality assessment (DQA). However, the equivalent QA/QC or DQA information for the groundwater and surface water data associated with the monitoring programs implemented by UCOR are not included in this report and instead are deferred to referenced programmatic plans and reports issued by OREM and UCOR. Section 4 of this report presents a summary evaluation of the CY 2019 monitoring data with regard to the respective objectives of surveillance monitoring and exit pathway/perimeter monitoring. The evaluation is based primarily on the analytical results for the following principal groundwater contaminants at Y-12: nitrate, uranium, gross alpha activity, gross beta activity, and volatile organic compounds (VOCs). Section 5 summarizes the most significant findings with respect to the principal contaminants along with recommendations for any proposed changes to the ongoing groundwater and surface water quality monitoring performed under the Y-12 GWPP. Technical reports and plans cited in the narrative sections of the report are listed in Section 6. Narrative sections of this report reference several appendices. Figures (maps and diagrams) and data tables (excluding data summary tables incorporated in the narrative sections) are in Appendix A and Appendix B, respectively. Appendix C contains construction details for each well sampled during CY 2019 by either the Y-12 GWPP or UCOR, along with schematic diagrams for wells equipped with Westbay™ multiport sampling equipment or Barcad® pump systems. Appendix D supports the background summary discussion in Section 2 and provides more detailed information about the hydrogeologic framework for groundwater and surface water monitoring at Y-12, including the primary sources of groundwater contamination in each hydrogeologic regime. Results for all field measurements and laboratory analyses obtained by the Y-12 GWPP and UCOR are presented in Appendix E, which also includes the sample numbers for the QA/QC samples associated with groundwater and surface water monitoring performed by the Y-12 GWPP.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2018

Technologies and Methods Used at the Laboratory for Atmospheric and Space Physics (LASP) to Serve Solar Irradiance Data

The Laboratory for Atmospheric and Space Physics (LASP) at the University of Colorado in Boulder, USA operates the Solar Radiation and Climate Experiment (SORCE) NASA mission, as well as several other NASA spacecraft and instruments. Dozens of Solar Irradiance data sets are produced, managed, and disseminated to the science community. Data are made freely available to the scientific immediately after they are produced using a variety of data access interfaces, including the LASP Interactive Solar Irradiance Datacenter (LISIRD), which provides centralized access to a variety of solar irradiance data sets using both interactive and scriptable/programmatic methods. This poster highlights the key technological elements used for the NASA SORCE mission ground system to produce, manage, and disseminate data to the scientific community and facilitate long-term data stewardship. The poster presentation will convey designs, technological elements, practices and procedures, and software management processes used for SORCE and their relationship to data quality and data management standards, interoperability, NASA data policy, and community expectations.

Pankratz, Chris↗
DOE OSTI2023

Quality appraisal of clinical practice guidelines for the management of Dysphagia after acute stroke

Objectives Dysphagia is a common complication in stroke patients, widely affecting recovery and quality of life after stroke. The objective of this systematic review is to identify the gaps that between evidence and practice by critically assessing the quality of clinical practice guidelines (CPGs) for management of dysphagia in stroke. Methods We systematically searched academic databases and guideline repositories between January 1, 2014, and August 1, 2023. The Appraisal of Guidelines for Research and Evaluation (AGREE II) instrument was used by two authors to independently assess CPG quality. Results In a total of 14 CPGs included, we identified that three CPGs obtained a final evaluation of “high quality,” nine CPGs achieved “moderate quality” and two CPGs received “low quality.” The domain of “scope and purpose” achieved the highest mean score (91.1%) and the highest median (IQR) of 91.7% (86.1, 94.4%), while the domain of “applicability” received the lowest mean score (55.8%) and the lowest median (IQR) of 55.4% (43.2, 75.5%). Conclusion The CPG development group should pay more attention to improving the methodological quality according to the AGREE II instrument, especially in the domain of “applicability” and “stakeholder involvement;” and each item should be refined as much as possible.

Gao, Shi-Lin↗
NASA NTRS2020

Searching for Hyperspectral Optical Proxies to Aid Chesapeake Bay Resource Managers in the Detection of Poor Water Quality

Shellfish aquaculture is a growing industry in the Chesapeake Bay. As population grows near the coast, extreme weather events cause a greater volume of pollutant runoff from impervious surfaces and agricultural lands. Resource managers who monitor shellfish beds need reliable information on a variety of water quality indicators at higher frequency than is possible through field monitoring programs and at a higher level of detail than current satellite products can provide. Although many factors causing degraded water quality that can impact human health are not currently discernable by traditional multispectral techniques, hyperspectral imagery offers a new opportunity to detect phytoplankton communities associated with harmful algal blooms and biotoxin production. Together with resource managers in their routine monitoring of sites around the bay from small boats, we have been exploring remotely sensed optical proxies for the detection of harmful algal blooms and sewage. Early warning by remote sensing could guide sampling and improve the efficiency of shellfish bed closures, ultimately improving health outcomes for humans and animals. An extensive network of routine sampling by Chesapeake Bay Program managers makes this is an ideal location to develop and test future satellite data products to support management decisions. Next generation hyperspectral measurements from the future Plankton Aerosol Cloud ocean Ecosystem (PACE) mission at nearly daily frequency, combined with the potential of higher spatial resolution from the Surface Biology and Geology (SBG) observing system recommended in the recent Decadal Survey, along with high frequency observations from the newly selected Geostationary Littoral Imaging and Monitoring Radiometer (GLIMR) Earth Venture Instrument make this a critical time for defining the needs of the aquaculture and resource management community to save lives, time, and money.

Schollaert Uz, Stephanie↗
NASA NTRS1994

Continual improvement: A bibliography with indexes, 1992-1993

This bibliography lists 606 references to reports and journal articles entered into the NASA Scientific and Technical Information Database during 1992 to 1993. Topics cover the philosophy and history of Continual Improvement (CI), basic approaches and strategies for implementation, and lessons learned from public and private sector models. Entries are arranged according to the following categories: Leadership for Quality, Information and Analysis, Strategic Planning for CI, Human Resources Utilization, Management of Process Quality, Supplier Quality, Assessing Results, Customer Focus and Satisfaction, TQM Tools and Philosophies, and Applications. Indexes include subject, personal author, corporate source, contract number, report number, and accession number.

Source record↗
DOE OSTI2022

Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

Abstract The global decline of water quality in rivers and streams has resulted in a pressing need to design new watershed management strategies. Water quality can be affected by multiple stressors including population growth, land use change, global warming, and extreme events, with repercussions on human and ecosystem health. A scientific understanding of factors affecting riverine water quality and predictions at local to regional scales, and at sub‐daily to decadal timescales are needed for optimal management of watersheds and river basins. Here, we discuss how machine learning (ML) can enable development of more accurate, computationally tractable, and scalable models for analysis and predictions of river water quality. We review relevant state‐of‐the art applications of ML for water quality models and discuss opportunities to improve the use of ML with emerging computational and mathematical methods for model selection, hyperparameter optimization, incorporating process knowledge into ML models, improving explainablity, uncertainty quantification, and model‐data integration. We then present considerations for using ML to address water quality problems given their scale and complexity, available data and computational resources, and stakeholder needs. When combined with decades of process understanding, interdisciplinary advances in knowledge‐guided ML, information theory, data integration, and analytics can help address fundamental science questions and enable decision‐relevant predictions of riverine water quality.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

Telescience Resource Kit Software Lifecycle

The challenge of a global operations capability led to the Telescience Resource Kit (TReK) project, an in-house software development project of the Mission Operations Laboratory (MOL) at NASA's Marshall Space Flight Center (MSFC). The TReK system is being developed as an inexpensive comprehensive personal computer- (PC-) based ground support system that can be used by payload users from their home sites to interact with their payloads on board the International Space Station (ISS). The TReK project is currently using a combination of the spiral lifecycle model and the incremental lifecycle model. As with any software development project, there are four activities that can be very time consuming: Software design and development, project documentation, testing, and umbrella activities, such as quality assurance and configuration management. In order to produce a quality product, it is critical that each of these activities receive the appropriate amount of attention. For TReK, the challenge was to lay out a lifecycle and project plan that provides full support for these activities, is flexible, provides a way to deal with changing risks, can accommodate unknowns, and can respond to changes in the environment quickly. This paper will provide an overview of the TReK lifecycle, a description of the project's environment, and a general overview of project activities.

Griner, Carolyn S.↗
DOE OSTI2021

Quality of service for input/output memory management unit

A data processing system includes a memory, a group of input/output (I/O) devices, an input/output memory management unit (IOMMU). The IOMMU is connected to the memory and adapted to allocate a hardware resource from among a group of hardware resources to receive an address translation request for a memory access from an I/O device. The IOMMU detects address translation requests from the plurality of I/O devices. The IOMMU reorders the address translation requests such that an order of dispatching an address translation request is based on a policy associated with the I/O device that is requesting the memory access. The IOMMU selectively allocates a hardware resource to the input/output device, based on the policy that is associated with the I/O device in response to the reordering.

Basu, Arkaprava↗
NASA NTRS1988

Modernization of software quality assurance

The customers satisfaction depends not only on functional performance, it also depends on the quality characteristics of the software products. An examination of this quality aspect of software products will provide a clear, well defined framework for quality assurance functions, which improve the life-cycle activities of software development. Software developers must be aware of the following aspects which have been expressed by many quality experts: quality cannot be added on; the level of quality built into a program is a function of the quality attributes employed during the development process; and finally, quality must be managed. These concepts have guided our development of the following definition for a Software Quality Assurance function: Software Quality Assurance is a formal, planned approach of actions designed to evaluate the degree of an identifiable set of quality attributes present in all software systems and their products. This paper is an explanation of how this definition was developed and how it is used.

Bhaumik, Gokul↗
NASA NTRSDate not supplied

More than RBE: Exploring Two Decades of Space Radiation Quality and Carcinogenesis Research and How NASA Manages Cancer Risk

NASA’s Space Radiation Element (SRE), both as a stand-alone entity and as part of the Human Research Program, has invested heavily into investigating how the different qualities of radiation and low dose rates relevant to the space environment and how these factors effect long term carcinogenesis risk. NASA’s current model to assess astronaut excess cancer risk due to radiation exposure utilizes data generated from both in vitro and in vivo models to inform quality factor and dose-rate functions that scales risk estimates originally established from human cohorts exposed to terrestrial radiation, most notably the Lifespan Study of atomic bomb survivors (LSS). As part of an effort to update these quality function, the SRE hosted a workshop in on radiation quality in September 2021 and a workshop on dose-rate at NASA HRP’s Investigators’ Workshop in February 2022 where current and former grantees presented data that could potentially be incorporated into assessing carcinogenic risk. This presentation is intended to both inform the broader research community of the outcome of those workshops and generate a discussion as to what biological data should be generated to better inform NASA’s risk estimates. Additionally, NASA’s current risk disposition for cancer assessment will be discussed and clarified. We look forward to hearing feedback from the Radiation Research Society community!

Brock J Sishc↗
DOE OSTI2022

Developing a Decision Support System for Regional Agricultural Nonpoint Salinity Pollution Management: Application to the San Joaquin River, California

Environmental problems and production losses associated with irrigated agriculture, such as salinity, degradation of receiving waters, such as rivers, and deep percolation of saline water to aquifers, highlight water-quality concerns that require a paradigm shift in resource-management policy. New tools are needed to assist environmental managers in developing sustainable solutions to these problems, given the nonpoint source nature of salt loads to surface water and groundwater from irrigated agriculture. Equity issues arise in distributing responsibility and costs to the generators of this source of pollution. This paper describes an alternative approach to salt regulation and control using the concept of “Real-Time Water Quality management”. The approach relies on a continually updateable WARMF (Watershed Analysis Risk Management Framework) forecasting model to provide daily estimates of salt load assimilative capacity in the San Joaquin River and assessments of compliance with salinity concentration objectives at key monitoring sites on the river. The results of the study showed that the policy combination of well-crafted river salinity objectives by the regulator and the application of an easy-to use and maintain decision support tool by stakeholders have succeeded in minimizing water quality (salinity) exceedances over a 20-year study period.

real-time management economics↗
NASA NTRS2001

Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

Vermillion, Stephanie C.↗
DOE OSTI2021

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program’s (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States’ largest estuary. The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework’s current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

54 ENVIRONMENTAL SCIENCES↗