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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Techno-economic and life cycle analysis of bio-hydrogen production using bio-based waste streams through the integration of dark fermentation and microbial electrolysis

Hydrogen derived from bio-based sources, or biohydrogen (bioH 2 ), has the potential to reduce GHG emissions from industrial and transportation sectors, owing to the low carbon footprint and myriad applications like refinery operation, ammonia production, steel production, fuel cell, etc. To evaluate the commercialization potential of bioH 2 production, we modeled bioH 2 production and conducted techno-economic analysis (TEA) and life cycle analysis (LCA) of two facilities producing 50 metric tonnes of bioH 2 per day from cheese whey (CW) and solid food waste (SFW) through the integration of dark fermentation (DF) and microbial electrolysis cell (MEC) technologies. LCA results showed that CW and SFW can produce carbon-negative bioH 2 , with emissions of −8.6 and −8.0 kg GHG kg −1 bioH 2 with carbon sequestration and renewable electricity resources, respectively, making bioH 2 potentially eligible for a tax credit of $\$3$ kg −1 H 2 based on provision 45 V of the U.S. Inflation Reduction Act (IRA). In this study, bioH 2 production treats waste streams to generate fresh water, thus, potentially can receive waste water treatment fee that varies with regions. The MEC capital cost dominates the bioH 2 cost, which is mainly determined by current density. With a current density of 20 A m −2 , the production cost for CW input varied between $\$17$ and $\$24$ kg −1 bioH 2 , while that for SFW input ranged from $\$29$ to $\$30$ kg −1 bioH 2 under different operating conditions, considering the 45 V tax credit, waste water treatment fee and production revenue. If the current density increases to 100 A m −2 , the bioH 2 cost decreases to a range of $\$4.0$–$\$6.9$ for CW and $\$5$–$\$6$ for SFW scenarios. This study also shows that low-cost bioH 2 can be produced using CW waste stream as feedstock.

Ganguly, Arna [Argonne National Laboratory (ANL), ↗
DOE OSTI2020

IEA Wind TCP Task 37: Definition of the IEA 15-Megawatt Offshore Reference Wind Turbine

This report describes a 15-megawatt offshore wind turbine with a fixed-bottom monopile support structure. This reference wind turbine is a Class IB direct-drive machine, with a rotor diameter of 240 meters and a hub height of 150 meters. An overview of the design is presented in Figure ES-1 and Table ES-1. The design reflects a joint effort between the National Renewable Energy Laboratory, sponsored by the U.S. Department of Energy, and the Technical University of Denmark, sponsored by the European Union's H2020 Program, through the second work package of International Energy Agency Wind Task 37 on Wind Energy Systems Engineering: Integrated RD&D. A forthcoming report will detail a semisubmersible floating support structure developed by the University of Maine.

15 MW↗
DOE OSTI2020

A Time Series Sustainability Assessment of a Partial Energy Portfolio Transition

Energy portfolios are overwhelmingly dependent on fossil fuel resources that perpetuate the consequences associated with climate change. Therefore, it is imperative to transition to more renewable alternatives to limit further harm to the environment. This study presents a univariate time series prediction model that evaluates sustainability outcomes of partial energy transitions. Future electricity generation at the state-level is predicted using exponential smoothing and autoregressive integrated moving average (ARIMA). The best prediction results are then used as an input for a sustainability assessment of a proposed transition by calculating carbon, water, land, and cost footprints. Missouri, USA was selected as a model testbed due to its dependence on coal. Of the time series methods, ARIMA exhibited the best performance and was used to predict annual electricity generation over a 10-year period. The proposed transition consisted of a one-percent annual decrease of coal’s portfolio share to be replaced with an equal share of solar and wind supply. The sustainability outcomes of the transition demonstrate decreases in carbon and water footprints but increases in land and cost footprints. Decision makers can use the results presented here to better inform strategic provisioning of critical resources in the context of proposed energy transitions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1989

Space Station Freedom Safety Program

The renewed emphasis within NASA on the incorporation of firmly established safety design requirements and evolving new safety analysis techniques, including quantitative safety risk assessment methods, is discussed with particular reference to the Space Station Freedom Safety Program. The program provides for integration of the partial safety analysis performed by numerous NASA Centers and International Partners into a Programmatic Safety Assessment for each of the launch increments and the complete Space Station Freedom on orbit. Communication in the safety program will utilize state-of-the-art software and computers, which will provide broad accessibility to safety information among the NASA and International Partners.

Griggs, John G., III↗
NASA NTRS2004

The Processing of Airspace Concept Evaluations Using FASTE-CNS as a Pre- or Post-Simulation CNS Analysis Tool

As NASA speculates on and explores the future of aviation, the technological and physical aspects of our environment increasing become hurdles that must be overcome for success. Research into methods for overcoming some of these selected hurdles have been purposed by several NASA research partners as concepts. The task of establishing a common evaluation environment was placed on NASA's Virtual Airspace Simulation Technologies (VAST) project (sub-project of VAMS), and they responded with the development of the Airspace Concept Evaluation System (ACES). As one examines the ACES environment from a communication, navigation or surveillance (CNS) perspective, the simulation parameters are built with assumed perfection in the transactions associated with CNS. To truly evaluate these concepts in a realistic sense, the contributions/effects of CNS must be part of the ACES. NASA Glenn Research Center (GRC) has supported the Virtual Airspace Modeling and Simulation (VAMS) project through the continued development of CNS models and analysis capabilities which supports the ACES environment. NASA GRC initiated the development a communications traffic loading analysis tool, called the Future Aeronautical Sub-network Traffic Emulator for Communications, Navigation and Surveillance (FASTE-CNS), as part of this support. This tool allows for forecasting of communications load with the understanding that, there is no single, common source for loading models used to evaluate the existing and planned communications channels; and that, consensus and accuracy in the traffic load models is a very important input to the decisions being made on the acceptability of communication techniques used to fulfill the aeronautical requirements. Leveraging off the existing capabilities of the FASTE-CNS tool, GRC has called for FASTE-CNS to have the functionality to pre- and post-process the simulation runs of ACES to report on instances when traffic density, frequency congestion or aircraft spacing/distance violations have occurred. The integration of these functions require that the CNS models used to characterize these avionic system be of higher fidelity and better consistency then is present in FASTE-CNS system. This presentation will explore the capabilities of FASTE-CNS with renewed emphasis on the enhancements being added to perform these processing functions; the fidelity and reliability of CNS models necessary to make the enhancements work; and the benchmarking of FASTE-CNS results to improve confidence for the results of the new processing capabilities.

Mainger, Steve↗
DOE OSTI2022

Cyber-Resilient Distributed Autonomous Energy Grid

The aim of Cyber-Resilient Distributed Autonomous Grid research initiative is to advance fundamental science and engineering approaches for cyber-resilient design, control, and operation of a distributed, highly interconnected, and autonomous energy grid of the future. From increasing penetration of DERs, smart homes and building with highly controllable loads at the distribution layer, to the interconnection of bulk renewables at the transmission layer the fundamental nature of the energy grid is changing, and these changes are enabled by rapid increase in dependence on the communication infrastructure and independent third parties for control and operation of the grid. NREL's Integrated Energy Pathways critical objective correctly identifies that there are fundamental cyber-resilience challenges inherent in the grid's evolution, and this effort is establishing strong and novel integrated cyber-resilience framework and approaches to address these new and fundamental challenges.

controls↗
DOE OSTI2022

1.4.2.403 - Water Power STEM Workforce Development (Hydro)

As interest in renewable energy grows, water power technologies will continue to play a robust and growing role. However, the industry needs new talent to spur innovation and to support industry needs. With one-quarter of the domestic hydropower workforce retiring in the coming decade, the need to fill the workforce pipeline has never been more critical. The lack of new hydropower development has limited the number of educational programs focused on this sector at all levels of education. NREL has a long track record of working to address educational needs across the renewable energy spectrum. Leveraging this track record, this project brought the Hydropower STEM Portal to water power stakeholders fueled by information from a multitude of sectors, our partnership with the Hydropower Foundation, NEED, and others. The team has also sought to integrate activities with the Bonneville Environmental Foundation, to increase dissemination opportunities and interfaces. The purpose of the portal is to be a one-stop shop to information geared at inspiring the next-generation water power professional. NREL also leverages experience in engaging with stakeholders to understand barriers to technology adoption to identify issues and drivers, provide feedback to the R&D community, work to clarify misperceptions, and inform decisions to facilitate market adoption. The outcome of this work is a more successful and diverse water power industry based on a motivated and better-trained workforce.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗
DOE OSTI2025

Integrating Energy-Efficient Computing with Computational Research to Accelerate Energy Technology

NREL's computational sciences center hosts the largest high performance computing (HPC) capabilities dedicated to energy research while functioning as a living laboratory for energy-efficient computing. NREL's HPC capabilities support the research needs of the Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). In ten years of operation, HPC use in EERE-sponsored research has grown by a factor of 30, including work in electricity generation, energy efficiency, transportation, and energy system modeling. This paper analyzes this research portfolio, providing examples of individual use cases. The paper documents NREL's history of operating one of the world's most energy-efficient data centers while examining pathways to reduce economic and environmental impact beyond reduction of Power Usage Efficiency (PUE). This paper concludes by examining the unique opportunities created for accelerating improvements in data center efficiency created by combining an HPC system dedicated to energy research and a research program in energy-efficient computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Integrating plant physiology into simulation of fire behavior and effects

Summary Wildfires are a global crisis, but current fire models fail to capture vegetation response to changing climate. With drought and elevated temperature increasing the importance of vegetation dynamics to fire behavior, and the advent of next generation models capable of capturing increasingly complex physical processes, we provide a renewed focus on representation of woody vegetation in fire models. Currently, the most advanced representations of fire behavior and biophysical fire effects are found in distinct classes of fine‐scale models and do not capture variation in live fuel (i.e. living plant) properties. We demonstrate that plant water and carbon dynamics, which influence combustion and heat transfer into the plant and often dictate plant survival, provide the mechanistic linkage between fire behavior and effects. Our conceptual framework linking remotely sensed estimates of plant water and carbon to fine‐scale models of fire behavior and effects could be a critical first step toward improving the fidelity of the coarse scale models that are now relied upon for global fire forecasting. This process‐based approach will be essential to capturing the influence of physiological responses to drought and warming on live fuel conditions, strengthening the science needed to guide fire managers in an uncertain future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Comparative life-cycle assessments and techno-economic analysis of renewable natural gas production pathways from biogas

Renewable natural gas (RNG) offers a promising pathway for decarbonizing hard-to-abate sectors. This study shows that, relative to conventional upgrading technologies (i.e., membrane separation and pressure swing adsorption), the catalytic methanation reaction (CMR) at water resource recovery facilities doubles RNG output. When consuming lowcarbon hydrogen, the CMR reduces operational energy use and global warming potential. Techno-economic analysis indicates that the CMR is not yet competitive but will become viable if hydrogen reaches $1/kg. Heat integration and hydrogen cost are key drivers of overall performance.

03 NATURAL GAS↗
DOE OSTI2022

Advancing Platooning with ADAS (Advanced Driver-Assistance Systems) Control Integration and Assessment

Application of Cooperative Adaptive Cruise Control (CACC) to heavy duty trucks known as truck platooning has shown fuel economy improvements on the test track under ideal driving conditions. However, limited test data is available to assess the truck platooning under real-world driving conditions. Under this Cummins-led project that was funded by the U.S. Department of Energy, truck platooning with CACC has been tested on a real-world interstate highway and the results of the project are reviewed in this report. At first, the real-world driving conditions were characterized using National Renewable Energy Laboratory (NREL) Fleet DNA database to define test factors, including route, terrain, and highway traffic. Afterward, both test track and on-highway testing guided by SAE J1321 procedures were conducted to assess truck platooning under controlled and real-world driving conditions. On-highway testing was done on a highway route in Indiana, consisting of low, medium, and high road grade segments. The highway test results of 2-truck and 3-truck platooning showed considerably reduced fuel savings compared to the controlled test track data, which mainly stems from the traffic or high-grade portions of the route. However, integration of Cummins powertrain and vehicle eco-driving features such as predictive cruise control and neutral coasting called ADEPT™ on the lead truck showed an improvement of fuel saving for the trucks in CACC operation. Furthermore, the importance of tire connectivity in efficient and safe operation of the trucks in platooning is characterized.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Synchro-Waveform-Based Event Identification Using Multi-Task Time-Frequency Transform Networks

Influenced by the transient dynamics and reduced inertia characteristics of high-penetration renewable energy systems, power system events frequently exhibit distinct characteristics such as high-frequency components including wide-band oscillations and hyper-harmonics. This makes standard systems face challenges including significant latency and reduced accuracy due to limited data resolution. However, current methods face significant limitations, including insufficient pattern capture ability, low noise immunity, limited feature learning, and restricted localization capabilities, thereby hindering real-time performance. To tackle this issue, this paper proposed a novel synchro-waveform-based event identification approach via a Multi-task Time-frequency Transform Network (MTTNet). Initially, a Time-frequency Transform Block (TTB) is developed to extract both local and global information. The TTB leverages both Fourier and S-transforms to derive comprehensive time-frequency information from synchro-waveforms. Subsequently, a multi-task learning strategy is employed to identify the type and distinguish localization of events. Integrating the TTB and multi-task learning, the MTTNet is designed for synchro-waveform-based event identification, incorporating an adaptive weighting strategy and simplified computation for the S-transform. Two different datasets, comprising simulated and actual synchro-waveforms, are collected from the IEEE 123 bus system and a real-world high-penetration renewable energy system using a universal grid analyzer. Extensive experiments on various conditions are carried out. In conclusion, results demonstrated that the MTTNet consistently surpasses both basic and advanced baselines, with maximum improvements of 13.24% and 9.86%, respectively, while reducing the calculation burden by 15-19 times to achieve real-time event identification.

Event identification↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Integrating air quality and health considerations into power sector decarbonization strategies

Climate change and public health are two interconnected societal challenges. Curbing fossil-based electricity generation reduces the emissions of both CO 2 and air pollutants, which brings tangible health benefits from improved air quality. The potential health benefits from decarbonizing the grid are enormous, immediate, and widespread. From renewable portfolio standards to carbon market, the health co-benefits from clean electricity policies often outweigh their policy costs. As climate action goes local, framing decarbonization around health benefits also makes it more personally relevant and economically attractive. Yet, to date, the health impacts have largely been viewed as ancillary benefits from decarbonization, rather than as a core consideration when energy strategies are formed, assessed and implemented. When strategic choices are made about retiring old infrastructure and building new ones, bringing public health to the center of the discussion can generate greater health benefits with more equitable distribution. Here we identify concrete ways to incorporate air quality and health considerations into power sector decarbonization strategies. We draw insights mainly from empirical and modeling evidence for the United States. These insights are generally applicable and could guide health-oriented decarbonization efforts in other countries as well.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Pathways of bio-jet adoption in the US aviation industry with implications for the overall transportation and energy sectors: an integrated, multi-sectoral analysis of future scenarios

Bio-jet adoption has emerged as an attractive option to complement and supplement the use of refined fossil liquid fuels in the aviation industry in the US. However, there are significant uncertainties surrounding the costs of bio-jet including but not limited to costs of feedstock, transformation costs and the competition with co-products of bio-jet that may be demanded elsewhere in the transportation or energy sectors. This study models alternative trajectories of bio-jet adoption in the US aviation industry by 2050 through the use of a global integrated multi sector dynamics model. Three bio-jet production and consumption pathways are presented- soybean oil to jet, corn ethanol to jet (ETJ) and Fisher–Tropsch-based bio-jet, with each pathway explicitly considering the co-production of renewable diesel and renewable gasoline alongside the bio-jet. Without explicit actions or technology changes to offset the technology cost of bio-jet, scenarios where bio-jet displaces refined liquids result in higher aviation fuel prices (ranging from a 25% increase to 120% increase by mid-century) and lower demand (ranging from −14% to −43%). Corn ethanol will play an important role in the US if large scale amounts of bio-jet are to be produced with smaller effects on demand and prices. While scenarios with high levels of bio-jet availability without the availability of ETJ in the US can significantly reduce emissions in the aviation sector, these reductions are achieved more through the reduction in overall aviation fuel demand rather than technology adoption.

09 BIOMASS FUELS↗
DOE OSTI2024

Fundamentals of Scalable Nanoparticle Assembly in Engineering Polymres

Systematically improving the properties of polymer nanocomposites is contingent on effectively controlling nanoparticle (NP) dispersion; further, it is necessary to attain this at scale if these methods are to impact practical applications. While most past work has focused on amorphous polymers, ≈ 70% of all polymers sold annually are semicrystalline. Inspired by this apparent disconnect, our work in the current DOE funded grant and this renewal proposal employs a novel handle, polymer crystallization, to organize NPs into the various amorphous zones of the lamellar semicrystalline morphology (interlamellar, interfibrillar and interspherulitic domains) of stereoregular polymers. We hypothesize that the isothermal crystallization rate of a polymer host, G, and NP diffusivity, are the two relevant control parameters in this context. In the case where the NPs are miscible in the melt, they remain spatially well-dispersed when the polymer is crystallized at a rate that is fast relative to NP diffusion. In contrast, monolayer-thick NP sheets with intersheet spacing of ~10-100nm form in slowly crystallized samples. This sheet stacking is remarkably similar to that seen in natural materials, e.g., Nacre. There is also ordering of the NPs at the larger interfibrillar scale. Importantly, the relative fraction of engulfed, interlamellar and interfibrillar NPs is determined by G. Further, the modulus of these materials can increase by a factor of 2-3 due to the organization state of the NPs, while leaving fracture toughness unaffected. We have established the broad applicability of this approach in two polymers, polyethylene (PE) and polyethyleneoxide (PEO). To achieve this goal we developed a method for grafting long PE chains from NPs with controlled graft density and molecular weight, giving us the ability to tailor their dispersion in the PE melt prior to crystallization. In this renewal proposal, we will develop the fundamental, quantitative understanding that will allow us to independently tailor polymer crystallization rate, NP diffusivity and NP agglomeration state in semicrystalline polymers so as to facilely control NP ordering and hence properties. A program that tightly integrates experiment and theory is proposed, and a key outcome of this research will be a three-dimensional design map for different regimes of NP organization (and hence properties) that can be achieved by polymer crystallization. A second independent outcome is the role of directional solidification and how it competes with the rates of polymer crystallization and NP mobility to affect the organization of the NP.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Technology Innovation Opportunities for the U.S. Buildings Sector [Slides]

Technology innovation can improve the competitiveness of American companies and the lives of American families. This report identifies promising building technology innovation opportunities to: • Make buildings more affordable, efficient, healthy, and resilient for all Americans. • Increase the international competitiveness of U.S. businesses. • Improve the integration of buildings with the electric grid to reduce consumer and grid system costs.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗