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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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Supplemental tables for the paper "Machine learning enables identification of a novel yeast galactose utilization pathway" by Marie-Claire Harrison et al. 2024.
This presentation gives a general overview of the developer, local land use permitting, and utility interconnection partners that might be relevant for agrivoltaic developments.
This paper presents a comprehensive simulation model for advanced membrane-based heat and mass exchanger (HMX) components which account for three separate fluid streams with complex flow patterns. The model was implemented with various liquid desiccants and their properties (including LiCl, CaCl and ionic liquid (IL)). Preliminary model validation is presented using data from a laboratory prototype absorber. The paper also presents implementation of the model into a sorption system modeling platform and analyzes potential benefit analysis of the HMX component in utilizing the sensible and latent heat removed in space cooling to heat water. The developed model and codes are expected to enable detailed optimization studies and identify novel configurations for the three-fluid HMX maximum performance and cost effectiveness.
Process heating is the most energy-intensive manufacturing process for most sectors of industry. To quantify energy savings from various energy conservation measures, the Department of Energy (DOE) sponsored the development of the Process Heating Assessment and Survey Tool (PHAST) and similar tools for other industrial systems in the early 2000s. It has been used extensively in the Save Energy Now Program’s Energy Savings Assessments and the Better Plants Program’s In-Plant Trainings. Since the initial development of the legacy tools, both computer operating systems and software development have evolved significantly. Thus, DOE has invested in the modernization of PHAST and other legacy software tools to create the Manufacturing Energy Assessment Software for Utility Reduction (MEASUR) tool suite. MEASUR offers a collection of software tools that can aid manufacturing facilities in improving the efficiency of energy systems and equipment (specifically pumps, fans, steam, and process heating) and in conducting “Energy Treasure Hunts”. Eventually, the tool will also add compressed air and process cooling systems. The Process Heating Assessment (PHA) module of MEASUR is an upgrade of the PHAST tool. PHA provides the means to model fuel-fired, steam-based, and electric process heating systems, covering process heating for most industrial plants in manufacturing sector. It also includes several key upgrades, including the ability to consider multi-component charge loads and account for several different areas of energy losses. The new tool includes a comprehensive flue gas calculator to quantify available heat and heat loss for various gaseous, liquid, and solid fuels and new heat loss calculators. It generates a report and a dynamic Sankey diagram to show the energy consumption in various areas of energy use. MEASUR has significantly improved the user experience by adopting a modern software design. This paper details the structure and workflow of PHA and presents a real-world case study to demonstrate energy savings quantification and MEASUR’s outstanding reporting capabilities.
Research into explanation of machine learning models, i.e. explainable AI (XAI), has seen a sympathetic exponential growth alongside deep artificial neural networks throughout the past decade. For historical reasons explanation and trust have been intertwined. However this focus on trust is too narrow, and has led the research community astray from tried and true empirical methods that lead to more defensible scientific knowledge about people and explanations. To address this, we contribute a practical path forward for researchers in the XAI field. We recommend researchers focus on the utility and impact of their explanations instead of trust. We outline five broad use cases where explanations are useful and, for each, we describe pseudo-experiments that rely on objective empirical measurements and falsifiable hypotheses. We believe that this experimental rigor is necessary to contribute to scientific knowledge in the field of XAI.
The goal of the ChemCatBio DataHub project is to accelerate the catalyst and process development cycle by developing transformational tools for prediction and collaboration in catalyst R&D. The project is currently focused on the development of the Catalyst Property Database (CPD), a free and public resource released in September 2020. The CPD was designed to advance the state of the art for application of computational data. When computational data, such as computed reaction energetics, is used in catalyst design, it is almost always generated by the researchers seeking to use it, even if similar data has been published previously. One barrier to data reuse that results in this duplication of effort is the difficult process of finding and applying published data, which can be slow, error-prone, and manual. The CPD seeks to overcome these challenges by creating a centralized, searchable database of quality catalyst property data. At present, the CPD contains computed adsorption energies for intermediates along catalytic pathways. During FY21 and FY22, development of the CPD continues with a focus on external users and meeting their requirements. A batch upload capability, training and curation procedures, user interviews, and a demonstration of the CPD's utility in accelerating catalyst research are planned. Overall, the Data Hub project and CPD aim to reduce the time and cost of catalyst research by harnessing the power of data in catalyst discovery.
This presentation provides an overview of peak load management in distribution systems using legacy utility equipment and distributed energy resources.
Breaking It Down: Carbon Capture, Utilization & Storage Technologies
United States building energy use accounted for 40% of total energy use, 74% of peak demand, and $412 billion in 2019. Building energy modeling allows researchers to simulate building physics, gain insights into possible energy/demand saving opportunities, and assess cost-effective resilience amidst climate change. Many building features needed to create building energy models are readily available such as 2D footprints and LiDAR (height). A critical feature that is not generally obtainable is the building type. In partnership with a utility, a years worth of real-world, 15-minute electrical use data has been examined. The smart meter data is compared to 97 different prototype building energy models to assign building type. Real-world considerations including data preparation, quality assurance, and handling of missing values for advanced metering infrastructure data are addressed. Euclidean distance for pattern-matching of energy use, dynamic time warping, and time-window statistics with machine learning are compared for determining building type from measured electricity use.
This document provides a comparison of several food waste utilization options: landfill gas capture, anaerobic digestion, and composting, across various metrics. These options are the most prevalent pathways for energy and resource recovery. Other options, not considered here, include food donation, animal feed, incineration, and gasification. The table below describes the differences or similarities between these processes and provides information about products, the number of current projects in the United States, capital and operation and maintenance (O&M) costs, job development potential, emissions, and incentives associated with each pathway, as well as other parameters, such as level of complexity, land requirement, and revenue type. Sources for the data in the table are listed in the references at the end of the document.
The present disclosure is directed to methods that provide a secure communication protocol by utilizing one step process of authenticating and encrypting data without having to exchange symmetric keys or needing to renew or re-issue digital identities fundamental to asymmetric encryption methodology.
Disclosed herein are compositions of non-naturally occurring enzymes to enable microbial syringol utilization with GcoAB.
The presentation, delivered at the 2022 Carbon Management Project Review Meeting held in Pittsburgh, PA (August 15 – 19, 2022), provides a detailed perspective on CO2 utilization and storage as a deep decarbonization pathway as it relates to states that make up the Intermountain West (I-WEST) region of the U.S. Content within shows findings from evaluation of the opportunity and potential value delivery that exists for CCUS to deploy at significant scale in the I-WEST region considering the region’s prominent enabling factors. This work is part of a larger initiative involving the development of a regional, stakeholder-informed technology “roadmap” for a sustainable and equitable transition to carbon neutral in the I-WEST.
An electrochemical heat transfer device for a hot water tank utilizes an electrochemical hydrogen compressor to pump hydrogen into and out of a tank having a metal hydride forming alloy therein. The absorption of hydrogen by the metal hydride forming alloy is exothermic, produces heat, and the desorption of the hydrogen from the metal hydride forming alloy is endothermic and draws heat in. An electrochemical hydrogen compressor may be configured between to tanks and pump hydrogen back and forth to form a heat transfer device, such as a hot water heater. A heat transfer device may be coupled with the tank or may comprise the outer surface of the tank to transfer heat to an object or to the surroundings. A closed loop may be configured having two tanks and one or two electrochemical hydrogen compressors to pump the hydrogen in a loop around the system.
Heat transfer/storage fluids that are resistant to oxidation in air at elevated temperatures, and systems that utilize such heat transfer/storage fluids, for example, as part of a concentrating solar power (CSP) system or other electricity-generating systems. The heat transfer/storage fluid is a molten chloride solution comprising two or more chlorides selected from the group consisting of CaCl 2 , SrCl 2 , BaCl 2 , NaCl, and KCl.
An electrochemical heat transfer device utilizes an electrochemical hydrogen compressor to pump hydrogen into and out of a reservoir having a metal hydride forming alloy therein. The absorption of hydrogen by the metal hydride forming alloy is exothermic, produces heat, and the desorption of the hydrogen from the metal hydride forming alloy is endothermic and draws heat in. An electrochemical hydrogen compressor may be configured between to reservoirs and pump hydrogen back and forth to form a heat transfer device. A heat exchange device may be coupled with the reservoir or may comprise the outer surface of the reservoir to transfer heat to an object or to the surroundings. A closed loop may be configured having two reservoirs and one or two electrochemical hydrogen compressors to pump the hydrogen in a loop around the system.
A water purification system utilizes an ionomer membrane and mild vacuum to draw water from source water through the membrane. A water source may be salt water or a contaminated water source. The water drawn through the membrane passes across the condenser chamber to a condenser surface where it is condensed into purified water. The condenser surface may be metal or any other suitable surface and may be flat or pleated. In addition, the condenser surface may be maintained at a lower temperature than the water on the water source side of the membrane. The ionomer membrane may be configured in a cartridge, a pleated or flat plate configuration. A latent heat loop may be configured to carry the latent heat of vaporization from the condenser back to the water source side of the ionomer membrane. The source water may be heated by a solar water heater.
The proliferation of distributed energy resources (DERs) presents opportunities and challenges to distribution grid operators. The National Renewable Energy Laboratory (NREL) and Survalent are collaborating to demonstrate advanced distribution management system (ADMS) and DER coordinated capability to assist utilities to increase resilience and reliability. ADMS and Distributed Energy Resource Management System (DERMS) Coordination for Peak Load Management (PLM). Fault Location, Isolation, and Service Restoration (FLISR) in the Presence of DERs. Grid-Edge Intelligent Distribution Automation System for Self-Healing Distribution Grids. These laboratory demonstrations use NREL's ADMS Test Bed.