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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 1,045 records · Page 58

DOE Energy Frontier Research Centers Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio)

New capabilities to predict, design and control the chemistries of carbon could answer a global imperative to transition from fossil-based to sustainable transportation fuels. While the use of inexpensive hydrocarbons has been an unparalleled achievement and enabler of economic prosperity for many nations, singular dependence upon crude oil has given rise to systemic vulnerabilities in climate, energy, economic, and national security. Lignocellulosic biomass, a renewable and carbon-neutral resource, has the potential to displace an estimated annual equivalent of three billion barrels of oil in the U.S. alone (National Research Council 2009, U. S. Department of Energy, 2011). However, biomass has only one-third the energy density of crude oil (Agrawal and Singh 2009, Richard 2010) and lacks petroleum’s versatility as a feedstock for fuels and chemicals. These limitations keep biomass conversion below the efficiency level needed for strategic impact while the scientific challenge of routing carbon from one molecular context to another remains unmet. In 2009, the Center for Direct Catalytic Conversion of Biomass to Biofuels (C3Bio) recognized the potential of chemical catalysis and fast pyrolysis to overcome such limitations by transforming the main components of biomass (cellulose, xylan, and lignin) from grasses and trees directly to liquid hydrocarbons and aromatic co-products. Enabled by the EFRC high-risk, high-reward approach to grand challenge science, C3Bio researchers have been key national players in disrupting the conventional paradigm of the cellulosic biorefinery into a new future of “no carbon left behind”—the full utilization of carbon from plant cell walls in energy-dense fuels (Fig. 1). We identified catalytic and fast-pyrolytic pathways that utilize cellulose, xylan and, most significantly, lignin. We developed catalytic processes that deoxygenate and transform monomers and isolated polymers into useful products and tested their use with intact biomass. We gained control of lignin synthesis within plants and initiated tailoring biomass to its end-use through the tools of plant molecular biology and genetic engineering. C3Bio breakthroughs have increased the energy density of biomass-derived substrates via catalytic and pyrolytic conversions into products such as benzoquinones, furfural and hydroxymethylfurfural, levoglucosan and levulinic acid, methoxypropylphenols and propylbenzene. Such advances in biomass conversion would not have been possible without simultaneous advances in analytical instrumentation and methodologies, and imaging technologies and applications. The legacy science developed by C3Bio enables design and control strategies for achieving a targeted product portfolio of fuel and chemical feedstocks from a diverse range of native and tailored biomass. Our research provides the knowledge base required for a bio-economy with product streams as diverse in functionality as those of the petrochemical industry. Coupling targeted computational modeling with experimentation, we achieved: (1) fundamental understanding of biopolymers and cell wall architecture assembly, (2) discovery of new chemistries that allow the development of highly selective pathways to fuels and desirable chemicals, and (3) an integrated systems-level understanding to control catalytic and pyrolytic pathways.

09 BIOMASS FUELS↗

Assessment of Potential Future Demands for Hydrogen in the United States

H2@Scale is a U.S. Department of Energy (DOE) initiative that brings together stakeholders to advance the affordable production, transport, storage, and utilization of hydrogen (H2) as an energy carrier to increase revenue opportunities in multiple energy sectors. The focus of the current work is to characterize the growth potential of diverse hydrogen industries in the United States, given research and development (R&D) advancements in hydrogen technologies. Current and emerging hydrogen production technologies utilize diverse energy sources, including natural gas (NG) reforming, as well as renewable and nuclear power for low-temperature and high-temperature water splitting. The produced hydrogen also enables emerging domestic industries that value conventional and renewable hydrogen as an energy carrier for intermediate and end use. The success of H2@Scale (Figure ES.1) depends not only on hydrogen demand from growing existing markets such as petroleum refining and ammonia (NH 3 ) production, but also on the development of new markets such as metals refining, synthetic fuel (synfuel) and chemical production, biofuels, light-duty (LD) and heavy-duty (HD) hydrogen fuel cell (FC) electric vehicles (FCEVs), and injection into NG pipelines, all of which can significantly increase hydrogen demand relative to current levels of approximately10 million metric tons [MMT] annually. This study focused primarily on five demand sectors — synfuels, upgrading of oil/biomass, NH 3 /fertilizer, metals refining, and hydrogen vehicles (transportation) — along with gas infrastructure. For each sector, a hydrogen demand potential was quantified, along with a “threshold price.” The hydrogen demand potential reflects a practical amount of hydrogen that could be used in that sector, barring economic considerations. The threshold price reflects the price at which the consumer would utilize hydrogen in lieu of an alternative that could supply the same performance.

08 HYDROGEN↗

Artificial Intelligence/Machine Learning Technology in Power System Applications

The primary purpose of this report is to provide an overview of the advancement in artificial intelligence and machine learning (AI/ML) technologies and their applications in power systems. It offers a foundation for understanding the transformative role of AI/ML in power systems and aims to stimulate further research and development in this area. This report begins with a historical perspective of AI/ML technologies, then explores their advancement to today’s prominence. The document highlights key contributors to the success of AI/ML technologies, including increased computational power, greater data availability, innovative algorithms, and advanced tools. It further introduces various AI/ML techniques, including supervised, unsupervised and reinforcement learning, graph neural networks, and generative AI. It also emphasizes the critical importance of ensuring the safety, security, and trustworthiness of these AI/ML techniques within this sector. The report reviews the recent representative advancements in various power system applications enhanced by AI/ML techniques, underscoring key developments and their transformative impact as evidenced by numerous studies. It also explores both the opportunities and challenges associated with the application of AI/ML technologies to improve power system applications. While the report extensively covers AI/ML applications in power systems, focusing primarily on the technical and operational aspects, it may not thoroughly explore the sociopolitical, economic, and broader regulatory implications of AI/ML integration in power systems. AI/ML techniques hold significant potential for enhancing power system applications; however, they are not omnipotent. It is crucial to acknowledge their limitations and understand that they may not be able to address all challenges in the power system domain. Various factors must be considered that influence the implementation, adoption, and effectiveness of AI/ML solutions, including but not limited to safety, security, transparency, and trustworthiness. Additionally, the incorporation of advanced human–machine interfaces is essential, as it enables humans to validate the effectiveness of AI/ML solutions while remaining actively engaged, fostering trust in AI/ML deployment. Finally, the report summarizes AI/ML research activities supported by the Department of Energy (DOE) Office of Electricity (OE) through the Advanced Grid Modeling (AGM) program. The work aligns with the interests and mission of DOE-OE AGM, with the report serving as a resource for identifying existing progress and for pinpointing future applications within AI/ML that need further exploration and support.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Community Sentiment Analysis with Focus on CCS

This research assesses community sentiment towards Carbon Capture and Storage (CCS) as depicted in digital media, focusing on themes such as emissions, transport, and storage. Utilizing the VADER sentiment analysis model, the study analyzed titles and descriptions from online news articles to capture immediate impressions and sentiments. Results indicate a predominantly positive sentiment towards CCS, with significant regional variations. States like Alabama and Texas exhibit high positive sentiment, likely due to economic ties to the energy industry, while states like Delaware and Utah show negative sentiment, potentially driven by environmental concerns. The significance of this study lies in its potential to inform policy and communication strategies for CCS implementation. Understanding public sentiment is crucial for the success of CCS projects as it helps to identify and address community concerns. Media influence plays a significant role in shaping public opinion, and this study highlights the need for effective communication strategies to promote the benefits of CCS while addressing any misconceptions. By providing insights into regional differences in sentiment, this research supports the development of tailored interventions that can enhance public acceptance and support for CCS initiatives, ultimately contributing to the success of efforts to mitigate climate change through reduced greenhouse gas emissions.

White, Casey↗

Improving the Freight Productivity of a Heavy-Duty, Battery Electric Truck by Intelligent Energy Management

This project aimed to enhance the range and reduce the operating costs of battery electric Class 8 trucks traveling over 250 miles daily. This was achieved through the development and implementation of an intelligent-Energy Management System (i-EMS) that leverages vehicle and operations data, physics-aware machine learning algorithms, and vehicle-to-cloud (V2C) connectivity. The project hypothesized that advanced machine learning algorithms and real-time data analytics could significantly improve the energy efficiency and range of these trucks. Key objectives included developing a physics-aware machine learning algorithm, implementing an i-EMS with V2C connectivity and physics-aware spatial data analytics (PSDA), and validating the system’s effectiveness with fleet partners HEB Companies and Murphy Logistics. Extensive data collection from vehicle operations, including vehicle characteristics, road conditions, and payload, was conducted. A machine learning algorithm was developed to predict energy consumption and enable proactive decision-making. The i-EMS was implemented on two Volvo VNR BEVs, with operators receiving charging and routing recommendations. Charging stations were installed at depot locations in Texas and Minnesota, with an additional on-route charger in Minnesota. Significant findings included a 14% range improvement for Murphy Logistics on a highway-driving eco-route and a 22% range improvement for HEB Companies on a city-driving eco-route. The i-EMS utilized rule-based methods and physics-based algorithms to predict and reduce energy consumption, with real-time monitoring and analysis through V2C connectivity enabling proactive decision-making. The project demonstrated the feasibility and economic viability of battery electric Class 8 trucks for long-haul operations, showcasing the potential of physics-aware machine learning in optimizing energy management. The successful implementation of the i-EMS in real-world scenarios validates its practical application and effectiveness, paving the way for the widespread adoption of battery electric vehicles in the freight transportation industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Scaled Implementation of Smart Charge Management for Electric Vehicles

Smart charge management (SCM) has become a critical strategy for mitigating potential grid impacts and reducing electricity costs for all customers. This study will evaluate the economics of implementing light-duty EV SCM at scale across the United States. This work will enhance distribution system analysis by estimating SCM implementation costs, exploring viable business cases, and developing a framework for national-level applications. The primary methodology involves leveraging detailed grid modeling from a specific service territory and using spatial extrapolation techniques to generalize findings to other regions. The analysis will develop key metrics to quantify the costs and benefits of SCM, including implementation costs relative to strategy and scale, the cost of distribution system upgrades with and without SCM, and the percentage of peak-load reduction. The objective is to produce a comprehensive report and a parameterized framework that enables utilities to self-assess the value of SCM in their own service territories. This will support the development of cost-effective charging strategies, accelerate the energization of new EV chargers, and facilitate the seamless integration of EVs into the nation's power grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Economic study of future aircraft fuels (1970-2000)

Future aircraft fuels are evaluated in terms of fuel resource availability and pricing, processing methods, and economic projections over the period 1970-2000. Liquefied hydrogen, methane and propane are examined as potential turbine engine aircraft fuels relative to current JP fuel.

Alexander, A. D., III↗

The National Geothermal Energy Research Program

The continuous demand for energy and the concern for shortages of conventional energy resources have spurred the nation to consider alternate energy resources, such as geothermal. Although significant growth in the one natural steam field located in the United States has occurred, a major effort is now needed if geothermal energy, in its several forms, is to contribute to the nation's energy supplies. From the early informal efforts of an Interagency Panel for Geothermal Energy Research, a 5-year Federal program has evolved whose objective is the rapid development of a commercial industry for the utilization of geothermal resources for electric power production and other products. The Federal program seeks to evaluate the realistic potential of geothermal energy, to support the necessary research and technology needed to demonstrate the economic and environmental feasibility of the several types of geothermal resources, and to address the legal and institutional problems concerned in the stimulation and regulation of this new industry.

Green, R. J.↗

Space manufacturing III; Proceedings of the Fourth Conference, Princeton University, Princeton, N.J., May 14-17, 1979

Papers are presented on the various technological, political, economic, environmental and social aspects of large manufacturing facilities in space. Specific topics include the potential global market for satellite solar power stations in 2025, the electrostatic separation of lunar soil, methods for extraterrestrial materials processing, the socio-political status of efforts toward the development of space manufacturing facilities, the financing of space industrialization, the optimization of space manufacturing systems, the design and project status of Mass Driver Two, and the use of laser-boosted lighter-than-air-vehicles as heavy-lift launch vehicles. Attention is also given to systems integration in the development of controlled ecological life support systems, the design of a space manufacturing facility to use lunar materials, high performance solar sails, the environmental effects of the satellite power system reference design, the guidance, trajectory and capture of lunar materials ejected from the moon by mass driver, the relative design merits of zero-gravity and one-gravity space environments, consciousness alteration in space and the prospecting and retrieval of asteroids.

Grey, J.↗

Pathways of Understanding: the Interactions of Humanity and Global Environmental Change

How humans, interacting within social systems, affect and are affected by global change is explored. Recognizing the impact human activities have on the environment and responding to the need to document the interactions among human activities, the Consortium for International Earth Science Information Network (CIESIN) commissioned a group of 12 scientists to develop a framework illustrating the key human systems that contribute to global change. This framework, called the Social Process Diagram, will help natural and social scientists, educators, resource managers and policy makers envision and analyze how human systems interact among themselves and with the natural system. The Social Process Diagram consists of the following blocks that constitute the Diagram's structural framework: (1) fund of knowledge and experience; (2) preferences and expectations; (3) factors of production and technology; (4) population and social structure; (5) economic systems; (6) political systems and institutions; and (7) global scale environmental processes. To demonstrate potential ways the Diagram can be used, this document includes 3 hypothetical scenarios of global change issues: global warming and sea level rise; the environmental impact of human population migration; and energy and the environment. These scenarios demonstrate the Diagram's usefulness for visualizing specific processes that might be studied to evaluate a particular global change issues. The scenario also shows that interesting and unanticipated questions may emerge as links are explored between categories on the Diagram.

Jacobson, Harold K.↗

Power systems for future missions

A comprehensive scenario of future missions was developed and applicability of different power technologies to these missions was assessed. Detailed technology development roadmaps for selected power technologies were generated. A simple methodology to evaluate economic benefits of current and future power system technologies by comparing Life Cycle Costs of potential missions was developed. The methodology was demonstrated by comparing Life Cycle Costs for different implementation strategies of DIPS/CBC technology to a selected set of missions.

Gill, S. P.↗

Cyber Technology for Materials and Structures in Aeronautics and Aerospace

The evolution of composites applications in aeronautics from 1970 to the present is discussed. The barriers and challenges to economic application and to certification are presented and recommendations for accelerated development are outlined. The potential benefits of emerging technologies to aeronautics and their foundation in composite materials are described and the resulting benefits in vehicle take off gross weight are quantified. Finally, a 21st century vision for aeronautics in which human mobility is increased by an order of magnitude is articulated.

Pipes, R. Byron↗

Performance of Gas Turbine Engines Using Wave Rotors Modeled

A wave rotor is a device that can boost the pressure and temperature of an airflow. When used as part of the core of a gas turbine engine, a wave rotor can significantly improve the thrust or shaft horsepower by boosting the flow pressure without raising the turbine inlet temperature. The NASA Lewis Research Center's Aeropropulsion Analysis Office, which is identifying technologies and research opportunities that will enhance the technical and economic competitiveness of the U.S. aeronautics industry, is evaluating the wave rotor to quantify the potential benefits of this device. Preliminary studies such as these are critical to identifying technologies that have high payoffs.

Source record↗

Soy expansion in Brazil's Cerrado

The Cerrado biome is Brazil's breadbasket and a major provider of ecosystem services, though these dual roles are increasingly at odds, in part because there are few mechanisms to protect remaining vegetation from large‐scale agricultural expansion. We assessed Cerrado conversion to soy using over 580,000 property boundaries, covering 77% of the biome that is eligible for commercial land use, and using microwatersheds, to cover 100% of eligible areas. Soy expansion accounted for 22% of conversion during 2003–14. Only 15% of clearing exceeded restrictions on private properties under the Forest Code (FC). However, 51% of soy farms have violated the FC, five times the rate of other farms. As a leading cause of both Cerrado conversion and FC violations, the soy sector has environmental and economic incentives to shift production to already cleared land. We used suitability maps to identify potential pathways for soy expansion across both old and new cropland frontiers.

Brazil↗

Bioeconomy Scenario Analysis

The Bioeconomy Scenario Analysis project has shed light on system interactions within the biomass-to-biofuel supply chain for the past 15 years. This presentation highlights recent analyses on investment and policy scenarios for sustainable aviation fuel, the economic and policy considerations for the historical buildout of the starch ethanol industry, and the potential impact of U.S. Department of Energy investment in bioenergy R&D.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗

Performance and Cost Potential for Direct-Fired Supercritical CO2 Natural Gas Power Plants

Direct-fired supercritical CO2 (sCO2) power cycles are being explored as an attractive alternative to natural gas combined cycle (NGCC) plants with carbon capture and storage (CCS). Therefore, understanding their performance and cost potential is important for the commercialization of the technology. This study presents the techno-economic optimization results of natural gas-fired, utility-scale power plants based on the direct sCO2 power cycle, which are lacking in public literature. To identify the optimum plant configuration, the study considered multiple cases with varying levels of thermal integration with the plant air separation unit (ASU). Several design variables for each power cycle configuration were identified and optimized to minimize the levelized cost of electricity (LCOE) for each case. The optimization design variables include the sCO2 cooler outlet temperatures, recuperator approach temperatures, and pressure drops. High fidelity models for recuperators, coolers, and turbines were developed and used to capture the impact of design variables on plant efficiency and capital costs. The optimization was conducted using a combination of manual sensitivity analyses and automated derivative-free optimization algorithms available under NETL’s Framework for Optimization and Quantification of Uncertainty and Sensitivity platform. The optimized direct sCO2 power plants offered similar or slightly higher plant efficiencies than the reference NGCC plants based on the F-class gas turbine with CCS. The LCOE of the optimized direct sCO2 plants is 13 to 17% higher than the reference NGCC plants with CCS due to high capital costs associated with the ASU and sCO2 power block, though there is significant room for improvement due to the high uncertainty in component capital costs for these new plants. Recuperators make up over 50% of the sCO2 power block costs. Consequently, any research and development efforts to reduce the recuperator capital costs will benefit the technology’s commercialization. The study also presents preliminary results showing the impact of co-firing landfill gas and natural gas on plant efficiency, LCOE, and CO2 emissions.

Pidaparti, Sandeep↗