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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 163 records · Page 9

Mechanistic Investigation of Redox Processes in Zn-MnO2 battery in Mild Aqueous Electrolytes

Zinc-MnO2 based batteries have acquired attention for grid-level applications, due to impressive theoretical performance, cost effectiveness and intrinsic safety. However, there are still many challenges that remain elusive due to the complex and controversial mechanisms of operation that hinders commercialization. In this work, the detailed redox processes that occur at the cathode during Zn-MnO2 battery operation are elucidated. Using a blend of structural and electrochemical techniques, the redox pairs that occur during operation are mechanistically studied while also showcasing the true impact of the electrolyte additive (0.1 M MnSO4) in a 1 M ZnSO4 electrolyte. An electrochemical quartz-crystal microbalance (EQCM) has been leveraged to reveal the effect of zinc hydroxy sulfate salt (Zn4SO4(OH)6·nH2O) and zinc manganese oxide (ZnxMnyOz) dissolution/deposition, which are believed to be major components during discharge and charge conditions. . These results provide insight not currently available, allowing a holistic view of the electrochemical reaction mechanisms during battery operation.

Rodriguez Perez, Ismael A.↗

Production and testing of the powerboard for ATLAS ITk Strip barrel modules

The upgrade of the ATLAS ITk strips detector for HL-LHC will employ a custom PCB (powerboard) for on-module DC-DC conversion, HV switching, and monitoring. Production of about 14100 of such PCBs with high reliability is a big challenge. In this paper we will present the production procedure and quality control (QC) testing system for the powerboards to be installed on ITk Strip barrel modules. During production, about 150 powerboards will be produced every week. Each powerboard will need to pass QC tests before they are assembled to module. The QC tests include thermal cycling between -35 °C and 40 °C, soak test (continuous running of DC-DC converter at high load at 20 °C), and basic functionality and characterization electrical tests of the low voltage (LV), high voltage (HV), and monitoring functions of the powerboard. A custom QC test system is described, which is based on a reusable PCB (active board) with all testing circuits, a one-time powerboard carrier card, and a Z-turn SoC board which hosts and runs the testing program. The production procedure and QC test system has been tested with 400 powerboards during pre-production, and the system has been proven ready for production with the desired testing program, speed, safety, and cost. Performance and typical failures of powerboards observed during the QC test of pre-production powerboards is also presented.

47 OTHER INSTRUMENTATION↗

Efficient Sampling of Complex Interdependent and Multiplex Networks

Efficient sampling of interdependent and multiplex infrastructure networks is critical for effectively applying failure and recovery algorithms in real-world settings, as well as to generate property-preserving reduced-order graph-based ensembles that address topological uncertainties. In this paper, we first explore the performance, i.e. the success in preserving graph properties, of graph sampling algorithms for interdependent and multiplex networks with synthetic and real-world graphs. We simulate sampling algorithms under different parameter settings. These settings include probabilistic graph generators, coupling patterns, and various performance metrics. Our results show that while Random Node and Random Walk sampling algorithms perform best for interdependent networks, Random Edge and Forest Fire sampling algorithms perform best for multiplex networks. Second, we propose and implement a novel similarity-based sampling algorithm for multiplex networks that samples only log(N) number of layers of an N-layer multiplex network while yielding computational savings with performance guarantees. Experimental results show that similarity sampling outperforms complete sampling of all layers while decreasing performance costs from a linear scale to a logarithmic one. Our results also indicate that similarity-based sampling outperforms complete sampling and random selection in nearly all scenarios when tested with real-world data.

Subasi, Omer↗

RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows

While in-situ workflow formulations have addressed some of the data-related challenges associated with extreme-scale scientific workflows, these workflows involve complex interactions and different modes of data exchange. In the context of increasing system complexity, such workflows present significant resource management challenges, requiring complex cost-performance tradeoffs. This paper presents RISE, an intelligent staging-based data management middleware, which builds on the DataSpaces framework and performs intelligent scheduling of data management operations to reduce I/O contention. In RISE, data are always written immediately to local buffers to reduce the effect of the transfer impact upon application performance. RISE identifies applications’ data access patterns and moves data towards data consumers only when the network is expected to be idle, reducing the impact of asynchronous background data movement upon critical data read/write requests. Here, we experimentally demonstrate that RISE can take advantage of staging nodes to offload data during writes without degrading application data movement performance.

97 MATHEMATICS AND COMPUTING↗

Magnets for a Muon Collider—Needs and Plans

We describe the magnet challenges for a Muon Collider, an exciting option considered for the future of particle physics at the energy frontier. Starting from the comprehensive work performed by the US Muon Accelerator Program, we have reviewed the performance specifications dictated by beam physics and the operating conditions to satisfy the accelerator needs. Among the many magnets that make up a muon collider, we have identified four systems that represent well the envelope of challenges: the target and capture solenoid, the final cooling solenoid, the accelerator dipoles and the collider dipoles. These systems provide focus for the development of novel concepts, largely based on HTS for reasons of performance, cost and sustainability. After giving a consolidated overview of the needs for the magnet systems, we describe here the basic technology options considered, and the plan for design and development activities.

43 PARTICLE ACCELERATORS↗

"PoliMOR: A Policy Engine \"Made-to-Order\" for Automated and Scalable Data Management in Lustre"

Modern supercomputing systems are increasingly reliant on hierarchical, multi-tiered file and storage system architectures due to cost-performance-capacity trade-offs. Within such multi-tiered systems, data management services are required to maintain healthy utilization, performance, and capacity levels. We present PoliMOR, a pragmatic and reliable policy-driven data management framework. PoliMOR is composed of modular, single-purpose agents that gather file system metadata and enforce policies on storage systems. PoliMOR facilitates automated and scalable data management with customizable agents tailored to HPC facility-specific storage systems and policies. Our evaluations demonstrate the scalability and performance of PoliMOR both by its individual agents and as a collective entity. We believe PoliMOR is widely applicable across HPC facilities with large-scale data management challenges and will garner interest from the HPC community, given its flexible and open-source nature.

George, Anjus↗

Synchronization-Based Guaranteed-Performance Formation Design for Swarm Systems

Guaranteed-performance formation control for swarm systems with the second-order dynamics is investigated based on the synchronization control strategy. Firstly, a new formation protocol is presented, where the weights of connected edges are adaptively regulated and the performance constraint is imposed. Then, on the basis of the Riccati inequality, sufficient conditions for synchronization-based guaranteed-performance formation are proposed, and an explicit expression of the guaranteed-performance cost is shown, where it is fully distributed to design gain matrices of the formation protocol in the sense that it is independent of global information of swarm systems. Moreover, the whole motion of a swarm system is determined, which is associated with initial states of all agents and formation control vectors. Finally, two numerical examples are shown to demonstrate theoretical conclusions, where the static whole motion and the dynamic whole motion are considered, respectively.

Dang, Hongtao↗

Component Development for Alkaline URFCS

Performance, cost, and durability of the catalyst materials are the key factors that govern the commercialization of H 2 -based energy devices such as unitized regenerative fuel cells (URFCs). URFCs offer the advantage of high energy density vs. existing battery systems. In addition, with the use of an alkaline URFC system, lower system costs can be achieved through the use of platinum group metalfree (PGM-free) materials. This project seeks to address the major obstacles faced in URFC systems and establish a URFC technical capability through the strategic partnership between USC and SRNL. The research focuses on the development of low-PGM and PGM-free based bifunctional oxygen catalysts and electrodes, as well as the development of a URFC testing capability at SRNL.

36 MATERIALS SCIENCE↗

Next Generation Hydrogen Station Composite Data Products: Retail Stations (Data through Quarter 3 of 2019)

This publication includes 98 composite data products (CDPs) produced for next generation hydrogen stations, with data through the third quarter of 2019. These CDPs include data from retail stations only and represent the following analysis categories: deployment, safety, maintenance and reliability, performance, cost, utilization, hydrogen quality, and component energy.

08 HYDROGEN↗

Peak Demand Savings from Efficiency: Opportunities and Practices [Slides]

Electricity systems are designed to meet peak demand - the maximum load during a specified period, typically in summer - even if that demand occurs only a few hours in a year. Yet most evaluations of electricity efficiency programs focus on reductions in annual energy use. However, these efficiency programs are also delivering peak demand savings at an affordable cost. A new study by the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) explores the program administrator (PA) cost - or the cost to implement an energy efficiency program to a utility or third party administrator - of saving peak demand through efficiency programs for electric utility customers. Berkeley Lab collected data on costs, annual energy savings, and peak demand savings for electricity efficiency programs for 52 utilities and other program administrators in 15 states between 2014 and 2018. The analysis focused on eight program types that represent 68% of the peak demand savings for the utilities and program administrators studied. The findings improve our understanding of which energy efficiency programs produce the most peak demand savings and their cost performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

2021 Thermal Energy Storage Systems for Buildings Workshop: Priorities and Pathways to Widespread Deployment of Thermal Energy Storage in Buildings

The 2021 U.S. Department of Energy's (DOE) "Thermal Energy Storage Systems for Buildings Workshop: Priorities and Pathways to Widespread Deployment of Thermal Energy Storage in Buildings" was hosted virtually on May 11 and 12, 2021. This report provides an overview of the workshop proceedings. Organized by DOE's Building Technologies Office (BTO), the National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, and Oak Ridge National Laboratory, the workshop convened more than 600 stakeholders from around the world to discuss the need for advancing the deployment of thermal energy storage (TES) in buildings. This workshop was designed to build on BTO's webinar series and 2019 workshop. The goals of this workshop were to promote discussion on TES related to: 1. Market adoption and deployment barriers, 2. Key applications and value drivers, 3. System cost, performance, and market requirements, and 4. End-use specific needs. The workshop took place over two days and consisted of keynote presentations, moderated panels, breakout sessions, and open discussion forums. The keynote presentations introduced opportunities for building TES, barriers to widespread deployment, and future visions. Moderated panel discussions presented diverse perspectives, breakout sessions provided opportunities for more intimate conversations, and open discussions captured feedback from the entire workshop group. Over the course of the two days, attendees exchanged experiences and ideas surrounding multiple aspects of TES in buildings. The first section of this report provides background on the motivations behind advancing TES for residential and commercial buildings and elaborates on the workshop objectives. The second section details the workshop structure and participant demographics. The third section provides key findings of the discussions that took place during the breakout sessions. Finally, this report details recommendations and actions to increase the TES deployment. Several recommendations from workshop attendees are presented in Table ES-1. TES holds significant potential to help increase building efficiency, grid-interactivity, and energy resilience, as well as reduce associated carbon emissions. The outputs generated from this workshop will aid stakeholders in advancing TES in buildings through a deeper understanding of the opportunities and barriers surrounding widespread deployment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Options for Subscale Maturation of Advanced Reactor Technologies Testing for Nuclear Thermal Propulsion

Several options could be implemented to establish an irradiation testing capability suitable for investigation of the performance of multiple nuclear thermal propulsion fuel elements at prototypic conditions. The prototypic conditions of interest are based on the current needs of the National Aeronautics and Space Administration’s Space Nuclear Power Program. The results of such testing are also intended to reduce the risks currently seen for any future subscale or full-scale ground testing of an engine-reactor system. The optimal solution is dependent upon several factors such as performance, cost, availability, schedule, technology readiness level, and plans for future testing in the SNP Program. Three options, based on different combinations of these factors, are considered in this report.

33 ADVANCED PROPULSION SYSTEMS↗

Integrated Heat Pump Thermal Storage and Power Cycle for CSP (Final Technical Report)

Pumped thermal energy storage (PTES) is a storage system that stores electricity in thermal reservoirs. In this project, methods of integrating PTES with concentrating solar power (CSP) systems were investigated and their feasibility evaluated. Hybrid "solar-PTES" devices can provide both flexible renewable power generation as well as a variety of electricity storage services. Techno-economic models of PTES and solar-PTES were developed and used to assess their performance, cost, and commercial viability. Systems were optimized using multi-objective optimization techniques. The value that these storage devices provide to the grid was estimated using production cost modelling. Key advances made in this project include the development of detailed techno-economic models that improve state-of-the-art assessments of these technologies. Off-design models were developed and used in grid-analysis models. This work describes for the first time how PTES and solar-PTES behave over a range of operating points and assesses the value that these systems can provide to the electrical grid. Feedback was obtained from experts in the field, which clarified key technological and economic barriers that must be addressed to improve the feasibility of these devices.

14 SOLAR ENERGY↗

SEIN: Breaking Barriers Resilient Energy System Analysis [Slides]

The Solar Energy Innovation Network (SEIN) is a collaborative research program that supports multi-stakeholder teams in researching and sharing solutions to real-world challenges associated with solar energy adoption. The Breaking Barriers project was selected to participate in the Solar Energy Innovation Network, Round 2, and was led by Groundswell, a D.C.-based clean energy project developer. The Breaking Barriers team included Partnership for Southern Equity, Atlanta University Center campus facility managers and professors, the City of Atlanta's Neighborhood Planning Unit T, and Georgia Power Company. The project aimed to design and construct innovative urban energy resiliency hubs integrating microgrid technology, solar generation, and energy storage in Atlanta colleges and communities. The hubs will help these historically Black colleges and universities (HBCUs) and the energy-burdened broader community in West Atlanta be more resilient, in addition to informing new course curricula at Atlanta University Center campuses. With many possible options for the system's battery size, the Breaking Barriers team needed insight into the relationships between BESS size, economic performance, and resilience at Spelman College's Manley Center. These insights are crucial for entering procurement negotiations with project developers, establishing resilience capabilities that the HBCU campuses can plan around, and guiding the team's fundraising targets. This analysis includes estimates of PV and battery performance, costs, savings, and resilience for multiple battery sizes. In order to provide power during a grid outage, the resilient energy system also needs to be connected to the Manley Center in a safe and island-able manner (electrically isolated from the grid). Analysis of potential electrical configurations and estimated setup costs is key to successfully entering a required interconnection agreement with Georgia Power, as well as informing requests for engineering firms to construct the system. This analysis includes conceptual options and rough order of magnitude cost estimates for electrically interconnecting the resilient energy system to the Manley Center and the grid. The Breaking Barriers team used this analysis to select preferred system characteristics and design for the resilient energy system.

14 SOLAR ENERGY↗

Advanced Water-Related Technology Performance Development

This U.S. Department of Energy/National Energy Technology Laboratory techno-economic analysis evaluates those parameters having the greatest performance and cost impact on wet flue gas desulfurization (FGD) effluent wastewater treatment systems, and air cooled condensers for dry cooling systems. Two supercritical pulverized coal power plants are considered: 1) an existing plant (modified for surface water discharge and air emissions consistent with limits for existing plants) retrofitted with wet FGD effluent wastewater treatment and 2) a greenfield plant constructed with an air-cooled condenser (ACC). Sensitivity analyses are completed on various process parameters associated with the wet FGD effluent wastewater treatment system and ACC to determine the impact on the net plant efficiency and levelized cost of electricity (LCOE). Research and development targets are recommended for the parameters shown to have the greatest potential impact on cost or performance.

20 FOSSIL-FUELED POWER PLANTS↗

Artificial Intelligence and Machine Learning for Bioenergy Research: Opportunities and Challenges

The integration of artificial intelligence and machine learning (AI/ML) with automated experimentation, genomics, biosystems design, and bioprocessing technologies is poised to revolutionize scientific investigation and, particularly, bioenergy research. To identify the opportunities and challenges in this emerging research area, the U.S. Department of Energy’s (DOE) Biological and Environmental Research program (BER) and Bioenergy Technologies Office (BETO) held a joint virtual workshop on AI/ML for Bioenergy Research (AMBER) on August 23–25, 2022. These interests have since been amplified in a September 2022 Executive Order, “Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure U.S. Bioeconomy,” to promote a whole-of government approach to biotechnology development (White House 2022). Approximately 50 scientists with various backgrounds and expertise from academia, industry, and DOE national laboratories met to discuss the opportunities and challenges of AI/ML for bioenergy research. Workshop participants were tasked with assessing the potential for AI/ML and laboratory automation to advance biological understanding and engineering in general. They particularly examined how integrating AI/ML tools with laboratory automation could accelerate biosystems design and optimize biomanufacturing. Discussions included the data and computational infrastructure needed to augment biosystems design applications and the expertise and workforce development efforts urgently required to shift integrated systems toward bioenergy research more broadly. Participants discussed many existing and future applications of AI/ML for biosystems design ranging from enzymes to plants and microbes, microbiomes, and bioprocess development. They also identified three key categories of scientific and technical opportunities and challenges: high-quality data, AI/ML algorithms, and laboratory automation. Several main takeaways emerged from the workshop: 1. Numerous AI/ML and automated experimentation applications exist for a variety of DOE mission needs in energy and the environment; 2. Exemplary research grand challenges for which AI/ML could provide solutions include: building microbes and microbial communities to specifications, developing closed-loop autonomous design and control for biosystems design, and advancing scale-up and automation; 3. Lack of sufficient high-quality, annotated data hinders the development of AI/ML applications; 4. New and improved AI/ML tools are needed, particularly those meeting the specific needs of the BER and BETO research communities; 5. Trade-offs in performance, cost, and reliability exist between deploying commercially available versus building custom-developed instrumentation and software for automated or autonomous experimentation; translation of manual to automated or autonomous methods is often a nontrivial endeavor; 6. Training a new generation of young scientists who can develop and apply AI/ML tools is needed to solve long-standing scientific challenges in bioenergy research. The integration of AI/ML tools and automated experimentation represents a new data-driven research paradigm complementary to the traditional hypothesis-driven research paradigm. This paradigm accelerates design and optimization of biological systems and processes for a variety of DOE mission needs in energy and the environment. The AMBER workshop broadly explored the potential of this new paradigm for bioenergy research, of particular interest to BER and BETO, and identified key challenges and opportunities that DOE can address in the coming years by leveraging its unique capabilities and resources.

59 BASIC BIOLOGICAL SCIENCES↗

Distributed Wind Market Report: 2023 Edition

The annual Distributed Wind Market Report provides stakeholders with market statistics and analysis along with insights into market trends and characteristics for wind technologies used as distributed energy resources. This report presents the distributed wind market from 2003 through 2022. Installed capacity, deployment trends, customer types, incentives, policies, installed costs, performance, and the future outlook for the distributed wind market are the key topics included in the report.

17 WIND ENERGY↗