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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31

Scheduling Mission Reconfiguration for an Interferometry Synthetic Aperture Radar Using Deep Reinforcement Learning

This paper presents a method to intelligently adapt the baseline of a synthetic aperture radar based on Deep Rein- forcement Learning to help create plans for missions that use formation flight for Earth observation purposes. The main contribution of this paper is the initial results we have found from applying the tool to a toy mission: measuring the ver- tical structure of forests by using a synthetic aperture radar mounted on a formation of 7 satellites orbiting the Earth in a Sun Synchronous Orbit. We have found that with a reward function based on expected science return over time and fuel usage, the Deep Reinforcement Learning planner is able to create plans with positive scientific returns while minimizing fuel usage. We also find that fuel usage and collision avoid- ance planning is better done with traditional methods, as Deep Reinforcement Learning does not converge to optimal solutions.

Viros-i-Martin, Antoni↗

Energy optimization system

A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Profiling Real-Time Electricity Consumption Data for Process Monitoring and Control

Today, smart meters serve as key assets to utilities and their customers because they are capable of recording and communicating real-time energy usage data; thus, enabling better understanding of energy usage patterns. Other potential benefits of smart meters data include the ability to improve customer experience, grid reliability, outage management, and operational efficiency. Despite these tangible benefits, many utilities are inundated by data and remain uncertain about how to extract additional value from these deployed assets outside of billing operations. One way to overcome this challenge is the development of new metrics for classifying utility customers. Traditionally, utilities classified their customers based on their business nature (residential, commercial, and industrial) and/or their total annual consumption. While this classification is useful for some operational functions, it is too limited for designing effective monitoring and control strategies. In this paper, a data mining methodology is proposed for clustering and profiling smart meters data in order to form unique classes of customers exhibiting similar usage patterns. The developed clusters could help utilities in identifying opportunities for achieving some of the benefits of smart meters data.

consumer engagement↗

EVALUATION OF THE EFFECTIVENESS OF TRUCK EFFICIENCY TECHNOLOGIES IN CLASS 8 TRACTOR-TRAILERS BASED ON A TRACTIVE ENERGY ANALYSIS USING MEASURED DRIVE CYCLE DATA

Quantifying the fuel savings that can be achieved from different truck fuel efficiency technologies for a fleet s specific usage allows the fleet to select the combination of technologies that will yield the greatest operational efficiency and profitability. This paper presents an analysis of vehicle usage in a commercial vehicle fleet and an assessment of advanced efficiency technologies using an analysis of measured drive cycle data for a class 8 regional commercial shipping fleet. Drive cycle measurements during a period of a full year from six tractor-trailers in normal operations in a less-than-truckload (LTL) carrier were analyzed to develop a characteristic drive cycle that is highly representative of the fleet s usage. The vehicle mass was also estimated to account for the variation of loads that the fleet experienced. The drive cycle and mass data were analyzed using a tractive energy analysis to quantify the fuel efficiency and CO2 emissions benefits that can be achieved on class 8 tractor-trailers when using advanced efficiency technologies, either individually or in combination. Although differences exist among class 8 tractor-trailer fleets, this study provides valuable insight into the energy and emissions reduction potential that various technologies can bring in this important trucking application.

LaClair, Tim J↗

Systems and methods for controlling energy use in a building management system using energy budgets

Systems and methods for limiting power consumption by a heating, ventilation, and air conditioning (HVAC) subsystem of a building are shown and described. A mathematical linear operator is found that transforms the unused or deferred cooling power usage of the HVAC system based on pre-determined temperature settings to a target cooling power usage. The mathematical operator is applied to the temperature settings to create a temperature setpoint trajectory expected to provide the target cooling power usage.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Modeling the Impacts of Solar Distributed Generation on U.S. Water Resources

Distributed electric power generation technologies typically use little or no water per unit of electrical energy produced; in particular, renewable energy sources such as solar PV systems do not require cooling systems and present an opportunity to reduce water usage for power generation. Within the US, the fuel mix used for power generation varies regionally, and certain areas use more water for power generation than others. The need to reduce water usage for power generation is even more urgent in view of climate change uncertainties. In this paper, we present an example case within the state of Tennessee, one of the top four states in water consumption for power generation and one of the states with little or no potential for developing centralized renewable energy generations. The potential for developing PV generation within Knox County, Tennessee, is studied, along with the potential for reducing water withdrawal and consumption within the Tennessee Valley stream region. Electric power generation plants in the region are quantified for their electricity production and expected water withdrawal and consumption over one year, where electrical generation data is provided over one year and water usage is modeled based on the cooling system(s) in use. Potential solar PV electrical production is modeled based on LiDAR data and weather data for the same year. Our proposed methodology can be summarized as follows: First, the potential solar generation is compared against the local grid demand. Next, electrical generation reductions are specified that would result in a given reduction in water withdrawal and a given reduction in water consumption, and compared with the current water withdrawal and consumption rates for the existing fuel mix. The increase in solar PV development that would produce an equivalent amount of power, is determined. In this way, we consider how targeted local actions may affect the larger stream region through thoughtful energy development. This model can be applied to other regions, other types of distributed generation, and used as a framework for modeling alternative growth scenarios in power production capacity in addition to modeling adjustments to existing capacity.

distributed energy generation↗

Sequence Polishing Library (SPL) v10.0

The Sequence Polishing Library (SPL) is a suite of software tools in order to automate "Design for Synthesis and Assembly" workflows. Specifically: The SPL "Converter" tool converts files among the following sequence data exchange formats: CSV, FASTA, GenBank, and Synthetic Biology Open Language (SBOL); The SPL "Juggler" tool optimizes the codon usages of DNA coding sequences according to an optimization strategy, a user-specific codon usage table and genetic code. In addition, the SPL "Juggler" can translate amino acid sequences into DNA sequences.:The SPL "Polisher" verifies NA sequences against DNA synthesis constraints, such as GC content, repeating k-mers, and restriction sites. In case of violations, the "Polisher" reports the violations in a comprehensive manner. The "Polisher" tool can also modify the violating regions according to an optimization strategy, a user-specific codon usage table and genetic code;The SPL "Partitioner" decomposes large DNA sequences into smaller building blocks with partial overlaps that enable an efficient assembly. The "Partitioner" enables the user to configure the characteristics of the overlaps, which are mostly determined by the utilized assembly protocol, such as length, GC content, or melting temperature.

Oberortner, Ernst↗

Blended service schedule for a power generator

A power generation system includes a power generator operatively connected to a plurality of sensors and a processor. The processor is configured to observe usage-based or event-based data regarding one or more components and consumables of the power generator. A usage-based service schedule is observed for the one or more event-based components and consumables. Operation-based data is received from the plurality of sensors regarding the functioning of the power generation system and one or more operation-based components and consumables of the power generator. An operation-based service schedule is determined for the one or more operation-based components and consumables based on the operation-based data. A blended service schedule is generated, the blended service schedule including the usage-based service schedule and the operation-based service schedule. The blended service schedule is then provided to at least one of a local monitor or a remote monitor.

Keene, Kevin↗

Systems and methods for data analytics for virtual energy audits and value capture assessment of buildings

A system may provide virtual energy audits of one or more target buildings. The system may retrieve weather data and energy usage data specific to a given target building from a weather server and a utility server, respectively. The system may store predefined building characteristics corresponding to the given target building in local memory. Based on the weather data, energy usage data, and/or predefined building characteristics, the system may generate one or more building markers that characterize the energy usage and efficiency of the given target building. Building efficiency diagnostics and energy conservation prognostics may be generated based on the building markers and may be sent by the system to be displayed via a user interface of a client device. The energy conservation prognostics may include one or more energy conservation measure recommendations and corresponding predicted cost/energy savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Thermal storage system with coupled tanks

Methods and apparatus are disclosed for high-efficiency thermal storage with a fluid-filled “battery” tank positioned within a fluid-filled “reservoir” tank. Fluid loops couple the tanks to a heat pump and a building. The heat pump can charge the battery tank or deliver thermal energy (cold or heat) to a building, using the reservoir tank or ambient air as a thermal energy source. The battery tank can discharge energy to the building jointly with the heat pump or, at periods of peak electricity usage, with the heat pump switched off. Operating modes allow significant savings in electricity usage and mitigate the “duck curve.” Low duty cycle usage of the reservoir enables efficient underground thermal storage with less digging than conventional geothermal technologies. Additional efficiency is achieved with phase change materials installed inside a tank or in a tank wall, providing temperature regulation. Control methods are disclosed.

15 GEOTHERMAL ENERGY↗

Energy Data from Heat Pumps Installed in Juneau, AK

Heat pumps offer a great low carbon emission method to heat homes. Thermalize Juneau 2021 was a clean energy campaign that helped homeowners in Juneau, Alaska install heat pumps into their homes. Juneau is located near the climactic limit of many heat pumps, and we were interested in how well the heat pumps can function in cold climates. This was done by using Sense meters to remotely monitor the energy usage of 10 homes with heat pumps. The Sense meters are small devices that connect to the electrical panel and monitor the energy use of multiple appliances through machine learning. First, we recorded the energy usage of a heat pump in the lab using both the Sense meter and the existing lab datalogger. Both recorded very similar energy usage data which confirmed that the Sense meter can accurately measure the fluctuations in the heat pump energy use. Next, we looked at the energy data from the Sense meters in the homes with heat pumps and paired it with local weather data to see how well the heat pumps functioned in the cold weather.

Alaska↗

Dry coupled magnetostrictive transducers for robotic inspection of dry storage casks - 15304

The lack of a national repository for used nuclear fuel has lead to the usage of dry storage casks as the de facto long term storage solution, the usage of which is prevalent throughout the United States. Furthermore, as shown in figure 3, the usage of dry storage is only expected to increase over time. Because these casks were originally intended as only an interim measure, there is an urgent need to develop methods to monitor their structural health over the long-term. Additionally, when concerns about the susceptibility of these casks to cracking is considered, the need for inspection becomes even more apparent. The use of robotic devices to inspect the interior of these casks for signs of damage has been proposed, but in order for this to be realized, advances in sensing technology must occur. We develop a novel type of transducer for non-destructive evaluation to aid in these efforts. We construct a prototype sensor, demonstrate simple defect detection with it, and present a design for an inspection robot equipping these transducers. Ultrasonic inspection is a well known method of non-destructive evaluation which works by measuring the response of ultrasonic waves propagating through a material. In through-transmission inspection, a transmitter and receiver are used to generate and detect waves in the material to be inspected. The presence of a crack or defect in the material will scatter some of the transmitted wave's energy, reducing the strength of the response at the receiver. Magnetostrictive transducers are often used to generate and detect guided waves. These transducers depend on the magnetostrictive effect, where certain materials will deform in the presence of a magnetic field. The typical construction of one of these transducers is shown in figure 5, consisting of a magnetostrictive foil, meandering coil, and a biasing magnet. Materials typically used for the foil include Fe-Co and Terfenol-D. For wave generation, a high-frequency alternating current is supplied to the coil of the transducer, which generates an oscillating magnetic field that causes the foil to deform. For reception, the inverse occurs: deformation of the foil results in a current in the coil that can be detected. The deformation of the foil is usually coupled to the material to be inspected with an adhesive, and waves are transmitted through this bond. Obviously, an inspection robot cannot have its sensors bound to the surface of the cask. A robot is being designed for inspection, and it must deal with many challenges inside the cask, including tight confines, right-angle transitions, high temperatures, and radiation. For our initial design, we consider only the geometrical constraints, and present a design for a prototype that can be assembled from COTS components. The robot needs to be articulated to navigate the bends in the cask, so each wheel is individually actuated. The robot is controlled via a tether, which also supplies electrical power and compressed air. For localization, ultrasonic range-finders and a camera are equipped. Using the basic transducer, we experimented with various configurations of materials and geometry. In order to gather relevant data, we used force sensitive resistors to measure applied force, and a Matec computer system to generate and measure ultrasonic waves. A testing rig was constructed to simulate the geometrical constraints of the interior of the cask, and we experimented using deadweights, a pneumatic cylinder, and an air bladder to apply the force. It was discovered early in the testing process that the performance of the transducer was very sensitive to the alignment of the components, and the method by which the foil was attached. To maximize performance, we designed an enclosure that would hold the components in alignment while still allowing the foil to float. To test the effectiveness of our new transducer, we cut circular holes of varying diameter in 2 mm aluminum plate, and measured the response across them. It can be seen that there is a clear relationship between the strength of the received signal and the force applied, and to a lesser extent, the size of the defect. This design performs adequately as a proof of concept, and a more precisely fabricated enclosure should further increase the accuracy of its measurements.

42 ENGINEERING↗

Development of the 3 m{sup 3} Low Level Radioactive Waste Container in Taiwan - 20037

Chinshan Nuclear Power Plant stopped its business operation in July, 2019, and Kuosheng Nuclear Power Plant will also be permanently shut down in 2023. Nuclear Reactor Facilities Regulation Act requires a nuclear facility must be dismantled in 25 years after being permanently ceased operation. According to the approved decommissioning plan of Chinshan Nuclear Power Plant and the proposed one of Kuosheng Nuclear Power Plant, the 3 m{sup 3} low level radioactive waste container is planned to store the low level radioactive wastes with higher radiation produced during the decommissioning. However, 3 m{sup 3} low level radioactive waste containers are not used or developed in Taiwan before. To meet such need, Institute of Nuclear Energy Research develops a new type of 3 m{sup 3} low level radioactive waste container and performs the corresponding analyses and tests based on Guidelines of Applying the Usage License of Low Level Radioactive Waste Containers and Regulations for the Safe Transport of Radioactive Material. In this article, it provides the information of the low level radioactive waste containers that have been approved or is under reviewing in Taiwan, and so do the design specifications of the developed 3 m{sup 3} waste container. Besides, the numerical evaluation and test results of the developed 3 m{sup 3} waste container are also included in this article. Based on the evaluation and test results, the developed 3 m{sup 3} waste container satisfies the requirements of the storage container and industrial package type 2. Institute of Nuclear Energy Research will submit the usage license applications to the authority this year, and the usage licenses would be granted in 2021, expectedly. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

An Efficient Annual-Performance Model of a Geothermal Network for Improved System Design, Operation, and Control: Preprint

Geothermal district energy systems (DES), and specifically geothermal networks, provide a viable solution for decarbonizing residential and commercial heating and cooling loads. District energy systems of all kinds enable a thermal resource with a relatively high capital cost (such as a geothermal borehole field) to be shared among a large number of users. While district heating and cooling has been studied for many years, geothermal networks, fifth generation DES that utilize water-source heat pumps and an ambient temperature loop to meet heating and cooling loads, have not been implemented extensively and thus require additional technical and economic optimization to obtain maximum benefits. This paper presents a newly developed reduced-order model that captures the flow of energy within the network, including the commercial and residential users' electrical usage, at an hourly rate over a year. The model includes building loads, heat pumps, borehole fields, and auxiliary heat/cool input, all connected with an ambient-temperature thermal loop model. In the model, operational control is possible for the borehole fields, circulation pump, and auxiliary system. For a given system, the model can output the complete state parameters for each component, the thermal loop, and the collective system, such as flow rate over time, average thermal loop temperature over time, and total electricity usage. The model can also be used to optimize the system control for maximizing system efficiency or minimizing system operational cost. For example, one initial assessment of the borehole controller for an example system showed that a controller with on/off operation of the borehole field reduces annual electrical usage by 33%, compared with continuous operation mode. Hence, the model can assist in optimizing a given system's operation to get the most value out of a geothermal network installation. Future work will consider the model's application to a demonstration project, including the model validation against operational data and system operation optimization.

ambient-temperature loop↗

Holistic energy analysis method for thermal management architectures of data centers

Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Validation of a Hot Water Distribution Model Using Laboratory and Field Data

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the ARBI team validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. In addition to completing validation activities, this project looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. Based on these datasets, we conclude that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws. This has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Validation of a Hot Water Distribution Model Using Laboratory and Field Data

Characterizing the performance of hot water distribution systems is a critical step in developing best practice guidelines for the design and installation of high performance hot water systems. Developing and validating simulation models is critical to this effort, as well as collecting accurate input data to drive the models. In this project, the Building America research team ARBI validated the newly developed TRNSYS Type 604 pipe model against both detailed laboratory and field distribution system performance data. Validation efforts indicate that the model performs very well in handling different pipe materials, insulation cases, and varying hot water load conditions. Limitations of the model include the complexity of setting up the input file and long simulation run times. This project also looked at recent field hot water studies to better understand use patterns and potential behavioral changes as homeowners convert from conventional storage water heaters to gas tankless units. The team concluded that the current Energy Factor test procedure overestimates typical use and underestimates the number of hot water draws, which has implications for both equipment and distribution system performance. Gas tankless water heaters were found to impact how people use hot water, but the data does not necessarily suggest an increase in usage. Further study in hot water usage and patterns is needed to better define these characteristics in different climates and home vintages.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Implications of Current Travel and the Adoption of Automated Vehicles

Current travel patterns and energy usage could be dramatically disrupted by new vehicle technologies, specifically in the case of automated vehicle (AV) technology. AV development is rapidly progressing and some experts anticipate it will be widely available to the public within 10 to 30 years (Litman and Litman 2018; Bansal and Kockelman 2017). This transformation in transportation could have a significant impact on the way people travel and potentially on overall energy consumption. AV adoption could have a wide range of potential energy implications, depending on their usage and the efficiency of the AVs. To better understand these implications, a random survey of more than 1,000 adults living in the continental United States was conducted for the National Renewable Energy Laboratory (NREL) using the Opinion Research Corporation (ORC) survey methodology (See A.1). While other survey efforts at the time of the study broadly investigated the barriers to acceptance of AVs, this study uniquely investigated how the technology will affect driving and commuting habits. The results were analyzed to better understand which groups of people will likely adopt AV technology first, how respondents currently travel, and how respondents may change their travel patterns if AVs are widely adopted.

33 ADVANCED PROPULSION SYSTEMS↗