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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 73 records · Page 4

High-Speed Visualization of Spray Breakup in a Rotating Detonation Combustor Using Laser Induced Fluorescence

Rotating detonation engines (RDEs) represent a novel propulsion technology where incoming reactants are consumed by a self-sustaining detonation wave that travels azimuthally around an annular combustion chamber. In theory, the operating mode of these devices approximates a constant-volume combustion Humphry cycle. This represents a 5-15% increase in thermal efficiency over current rockets and air breathing systems operating on constant-pressure combustion Brayton cycles. The use of liquid fuels in RDEs represent unique challenges in terms of performance and operability. However, the fundamental physics involved in spray breakup, evaporation, and combustion are not well understood inside these devices. This research seeks to provide direct insight into these processes by adding a single liquid fuel injector into an otherwise hydrogen-air RDE to evaluate the breakup and refill dynamics. Visualization is performed by 200-1000 kHz laser induced fluorescence of liquid phase diesel (355 nm) and or kerosene (266 nm).

Detonation↗

The Amazon Water Cycle: Perspectives from Water Budget Closure and Ocean Salinity

Global and regional water cycle includes precipitation, water vapor divergence, and change of column water vapor in the atmosphere, and land surface evapotranspiration, terrestrial water storage change, and river discharge, which is linked to ocean salinity near the river mouth. The water cycle is a crucial component of the Earth system, and numerous studies have addressed its individual components (e.g., precipitation). Here we assess, for the first time, if remote sensing and reanalysis datasets can accurately and self-consistently portray the Amazon water cycle. This is further assisted with satellite ocean salinity measurements near the mouth of the Amazon River. The widely used practice of taking the mean of an ensemble of datasets to represent water cycle components (e.g., precipitation) can produce large biases in water cycle closure. Additionally, closure is achieved with only a small subset of data combinations (e.g., ERA5 precipitation and evapotranspiration plus GRACE satellite terrestrial water storage), which rules out the lower precipitation and higher evapotranspiration estimates, providing valuable constraints on assessments of precipitation, evapotranspiration, and their ratio. The common approach of using the Óbidos stream gauge (located hundreds of kilometers from the river mouth) multiplied by a constant (1.25) to represent the entire Amazon discharge is found to misrepresent the seasonal cycle, and this can affect the apparent influence of Amazon discharge on tropical Atlantic salinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Powertrain Performance and Total Cost of Ownership Analysis for Class 8 Yard Tractors and Refuse Trucks

Advanced powertrain technologies, specifically fuel cell electric powertrains, have gained attention as viable alternatives for medium- and heavy-duty (M/HD) vehicles. However, it is unclear how these alternative powertrain vehicles stack up against their diesel counterparts in terms of performance and total cost of ownership (TCO). Furthermore, there are vehicle segments within the M/HD sector that have remained unstudied for fuel cell electric applications. This analysis aims to provide a comparative scoping-level TCO and performance analysis for two heavy-duty vocation vehicles (Class 8 U.S. port-side yard tractor and Class 8 U.S.-based refuse truck) for both conventional diesel and heavy-duty fuel cell electric (HDFC) powertrains. The refuse truck analysis also considered compressed natural gas powertrains (CNG) for comparison. The analysis includes seven timeframes (2020, 2025, 2030, 2035, 2040, 2045, and 2050) for comparison. This simplified TCO analysis includes only direct costs (fuel price, glider purchase price, and operating & maintenance costs) and excludes any associated indirect cost (e.g., dwell time costs and other opportunity based costs). Representative drive cycles for each vehicle were based on on-board GPS logged data and chosen by the analysis team to represent average, non-extreme driving conditions. At the time the analysis was performed, the Inflation Reduction Act was not in effect and therefore any potential subsidies and future cost reductions enacted under the Inflation Reduction Act were not included. Based on the operational setpoints used in this analysis, HDFC powertrains for both yard tractors and refuse trucks have the potential to achieve TCO advantages over conventional diesel powertrains (and CNG for refuse truck applications) in the near- to mid-term future while meeting the necessary duty cycle performance requirements. Yard tractors and refuse trucks spend a significant amount of time operating at low speeds, with long durations of idling, and experience numerous start/stop occurrences. These operational characteristics favor fuel cell performance as fuel cells operate with higher efficiencies at lower percentages of total power output. Conversely, conventional diesel and CNG engines are most efficient at higher percentages of total power output. This helps HDFC powered yard tractors and refuse trucks realize improved fuel economy when compared to their diesel counterparts, which helps reduce total fuel costs and therefore, total TCO. The analysis demonstrates that fuel prices play a significant role in determining TCO for each vehicle and should remain an R&D focus area. Overall, under the analysis' specified conditions, HDFC yard tractors have the potential to achieve cost parity with diesel yard tractors as early as 2025. For refuse trucks, HDFC refuse trucks have the potential to achieve cost parity with diesel and CNG refuse trucks in 2030 and 2040, respectively.

33 ADVANCED PROPULSION SYSTEMS↗

OPALCO - Decatur Island Solar and Energy Storage Project: An Assessment of Battery Technical Performance

Orcas Power & Light Cooperative (OPALCO) is a member-owned, nonprofit cooperative utility that provides energy services to approximately 11,200 customers across 20 islands in San Juan County, Washington. OPALCO’s mostly hydroelectric power is generated by Bonneville Power Administration and delivered to the islands by submarine cables. In 2016, as part of the second round of funding from the Washington state Clean Energy Fund, OPALCO received a $1 million matching grant to support a project that deployed a 504-kW LG community photovoltaic (PV) system in combination with a 1 MW/2 MWh lithium-iron-phosphate battery energy storage system (BESS) on Decatur Island, Washington. The Decatur Island Substation is essential to ensuring reliable energy for the residents of the San Juan Islands as it is the point of interconnection with the mainland transmission system. The BESS, in combination with the community solar array, will deliver an innovative method to both defer the costly upgrade of the transmission system and allow for other high-value applications intended to benefit the utility and its customers. In 2018, Pacific Northwest National Laboratory (PNNL) completed a preliminary economic assessment for several identified use cases in collaboration with OPALCO. Between August 2021 and May 2022, extensive testing was conducted, and the results were used to assess the technical performance of the BESS subjected to actual field operations. Both reference performance and use case tests were performed: (a) Reference performance tests assess the general technical capabilities of the BESS, such as energy capacity, round-trip efficiency (RTE), ramp rate, and signal tracking capability. These are the first tests performed (baseline) and are repeated after use case tests (post cycle). A standardized U.S. Department of Energy (DOE) energy storage performance protocol was used to characterize the BESS, including representative duty cycle profiles, test procedure guidance, and calculation guidance for determining key characteristics. (b) Use case tests examine the performance of the BESS for specific use cases using duty cycles developed by PNNL in collaboration with OPALCO. Four use cases were selected for testing: 1) demand charge reduction, 2) load shaping, 3) outage mitigation, and 4) transmission deferral. The use case duty cycles were developed based on utility and site-specific characteristics in addition to the technical characteristics and physical capabilities of the BESS. Use case tests were performed between the baseline and post cycle tests. This report describes the BESS and its components, presents testing and performance analysis results, and shares key insights and lessons learned from this project. Outcomes of the tests and analyses will help OPALCO understand the performance of the Decatur Island BESS in its current state and design appropriate operational strategies for this and other BESSs over the long term.

14 SOLAR ENERGY↗

HFAST - A harmonic analysis program for Stirling cycles

HFAST is a general-purpose third-order harmonic analysis and design program for predicting the cyclic-steady state thermodynamic performance of Stirling cycles. It represents the state-of-the-art results of years of research efforts at Mechanical Technology Inc. (MTI) in the development of Stirling cycle machines. The code has been extensively used at MTI to support the development of both free-piston and kinematic Stirling cycle machines. Lately, HFAST has undergone many major improvements, both in the analysis method and in the user's interface. This paper presents a brief description of the current analysis method used in HFAST.

Huang, S. C.↗

Methanol decomposition bottoming cycle for IC engines

This paper presents the concept of methanol decomposition using engine exhaust heat, and examines its potential for use in the operation of passenger cars, diesel trucks, and diesel-electric locomotives. Energy economy improvements of 10-20% are calculated over the representative driving cycles without a net loss in power. Some reductions in exhaust emissions are also projected.

Purohit, G.↗

Multivariate prognosis of battery advanced state of health via transformers

De-risking energy storage investments necessary to meet CO 2 reduction targets requires a deep understanding of the connections between battery health, design, and use. The historical definition of the battery state of health (SOH) as the percentage of current versus initial capacity is inadequate for this purpose, motivating an expanded SOH consisting of an interrelated set of descriptors including capacity, energy, ionic and electronic impedances, open-circuit voltages, and microstructure metrics. In this work, we introduce deep transformer networks for the simultaneous prognosis of 28 battery SOH descriptors using two cycling datasets representing six lithium-ion cathode chemistries, multiple electrolyte/anode compositions, and different charge-discharge scenarios. The accuracy of these predictions for battery life (with an unprecedented mean absolute error of 19 cycles in predicting end of life for a lithium-iron-phosphate fast-charging dataset) illustrates the promise of deep learning toward providing enhanced understanding and control of battery health.

25 ENERGY STORAGE↗

Thermal Dynamics and Lithium Plating Detection in High‐Power Li‐Ion Batteries for eVTOL Applications

The rapid electrification of aerial transportation is driving the need for high‐performance Li‐ion batteries that can operate reliably under stringent thermal and safety constraints. The unique mission profile of electric Vertical Take‐off and Landing (eVTOL) aircraft necessitates a focused investigation into the thermal behavior and safety characteristics of these batteries. Here, in this study, operando isothermal microcalorimetry is employed to examine the thermal evolution of Li‐ion batteries under cycling conditions representative of eVTOL operations. These findings reveal that high‐power discharge events—such as those during take‐off and landing—shift the thermal response toward exothermic behavior, in contrast to the typically endothermic response expected under near‐equilibrium cycling conditions. Additionally, the results suggest that advanced electrolyte formulations may help suppress excess heat generation, thereby improving battery safety. Notably, the calorimetric results exhibit a distinct thermal signature associated with lithium plating, offering a potential diagnostic for detecting Li plating during eVTOL operation. Overall, this study demonstrates the utility of isothermal microcalorimetry as a valuable tool for assessing thermal risks in Li‐ion batteries for eVTOL applications, and highlights the importance of targeted design strategies to mitigate safety hazards during high‐power demand scenarios.

Li plating↗

A Binomial Stochastic Framework for Efficiently Modeling Discrete Statistics of Convective Populations

Abstract Understanding the coupling between convective clouds and the general circulation, as well as addressing the gray zone problem in convective parameterization, requires insight into the genesis and maintenance of spatial patterns in cumulus cloud populations. In this study, a simple toy model for recreating populations of interacting convective objects as distributed over a two‐dimensional Eulerian grid is formulated to this purpose. Key elements at the foundation of the model include i) a fully discrete formulation for capturing discrete behavior in convective properties at small population sample sizes, ii) object age‐dependence for representing life‐cycle effects, and iii) a prognostic number budget allowing for object interactions and co‐existence of multiple species. A primary goal is to optimize the computational efficiency of this system. To this purpose the object birth rate is represented stochastically through a spatially aware Bernoulli process. The same binomial stochastic operator is applied to horizontal advection of objects, conserving discreteness in object number. The applicability to atmospheric convection as well as behavior implied by the formulation is assessed. Various simple applications of the BiOMi model (Binomial Objects on Microgrids) are explored, suggesting that important convective behavior can be captured at low computational cost. This includes i) subsampling effects and associated powerlaw scaling in the convective gray zone, ii) stochastic predator‐prey behavior, iii) the downscale turbulent energy cascade, and iv) simple forms of spatial organization and convective memory. Consequences and opportunities for convective parameterization in next‐generation weather and climate models are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Life cycle assessment of the wood pallet repair and remanufacturing sector in the United States

Wood pallets are ubiquitous products that can be recovered and reused to enhance their service life and environmental performance. Repair/remanufacturing has an important role in extending the service life of the wood pallet. To quantify environmental performances of wood pallet reuse, this study developed representative life cycle inventory data for pallet repair/remanufacturing in the United States based on comprehensive industry-wide production data for 2018. A gate-to-gate life cycle assessment covering raw material supply, raw material transportation and pallet repair/remanufacturing showed that repair/remanufacturing often had the highest impacts, including primary energy consumption at 5.09 MJ and global warming impact at 0.355 kg CO 2 eq per repaired/remanufactured pallet. Electricity consumed onsite followed by nail input and the fuel used by forklifts during the manufacturing drove much of the impacts on the environment. Finally, the results of this study provide valuable information on the repair/remanufacturing impacts, allowing quantification and evaluation of the recovery stage on the overall environmental performance of wood pallets.

09 BIOMASS FUELS↗

Engine design considerations for 2nd generation supersonic transports

The environmental and economic goals projected for advanced supersonic transports will require revolutionary improvements in propulsion systems. Variable cycle engine concepts that incorporate unique components and advanced technologies show promise in meeting these goals. Pratt & Whitney Aircraft is conducting conceptual design studies of variable cycle engine concepts under NASA sponsorship. This paper reviews some of the design considerations for these engine concepts. Emphasis is placed on jet noise abatement, reduction of emissions, performance improvements, installation considerations, hot-section characteristics and control system requirements. Two representative variable cycle engine concepts that incorporate these basic design considerations are described.

Howlett, R. A.↗

Sparse chronology strategy for integrating seasonal energy storage in capacity expansion models

Here, this study develops the sparse chronology method to enhance the representative period framework in capacity expansion models, enabling the effective integration of long-duration energy storage modeling. Traditional representative period methods cannot capture the state of charge of seasonal energy storage systems because they do not establish effective inter-day linkages to connect the state of charge between periods. The sparse chronology approach addresses this limitation by establishing inter-day linkages that allow state of charge to shift inter-seasonally. At the same time, it groups identical representative days into partitions, applying constraints sparsely and implicitly to reduce computational load further. Validation results demonstrate that this method successfully simulates long-duration energy storage patterns, achieving close alignment with a continuous yearly benchmark model, with seasonal trends and state of charge cycles clearly represented. The computational load analysis reveals that the sparse chronology method efficiently applies constraints on maximum and minimum state of charge limits within the representative day framework, eliminating the need for detailed constraints on each individual day. By partitioning representative days and constraining only the start and end of each partition, the method significantly decreases computational requirements. Simulation results show that sparse chronology closely approximates the continuous yearly method's accuracy, even with as few as 20 representative days, achieving correlation values with the benchmark of nearly 0.9 in state of charge plots. Furthermore, it maintains computational efficiency, requiring only 4 % of the solver time compared to the continuous yearly method with 20 representative days. This approach allows capacity expansion models to incorporate long-duration energy storage with high temporal, spatial, and technological resolution, enabling more detailed modeling for large-scale power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Representative Modules for Accelerated Thermal Cycling and Static Load Testing

In this work, we explore the influence of module size on the rate of interconnect solder bond thermomechanical fatigue (TMF) damage and the probability of cell fracture. For the solder bond TMF damage evaluation, structural mechanics models of crystalline silicon PV models are created to solve with the Finite Element Method. For the probability of cell fracture evaluation, Weibull analysis and weakest link theory are employed to resolve the probability of crystalline silicon PV cell fracture when measured as bare cells and when stressed in reduced- and full-sized modules. Results conclusively demonstrate that the rate of solder bond TMF damage is independent of module size, interconnect location across the cell and cell location across the module and that smaller, representative, modules must be loaded to a much higher level than their parent full-sized modules to achieve an equivalent driving force for cell fracture.

accelerated testing↗

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗

Remote Sensing of Dissolved Organic Carbon (DOC) Stocks, Fluxes and Transformations Along the Land-Ocean Aquatic Continuum: Advances, Challenges, and Opportunities

From stream headwaters to the deep ocean, dissolved organic carbon (DOC) is ubiquitous across the world’s aquatic systems, where it fulfills important biogeochemical and ecological functions. Importantly, DOC is a dynamic component of the carbon cycle and represents a global reservoir (mass of carbon) equivalent in size to the atmospheric CO 2 pool. The mobilization, transport, and transformations of DOC along the land-ocean aquatic continuum biogeochemically connect terrestrial landscapes, freshwater and marine ecosystems, and the atmosphere. As a result, DOC budgets are vulnerable to climate- and human-driven changes. Having the ability to quantify DOC stocks, fluxes, and transformations consistently and accurately in aquatic systems is therefore critical to our understanding of DOC’s functions in the environment and of their susceptibility to change. In recent years, optical techniques and synoptic earth observations have opened new doors to achieve this objective on a global scale. In this review, we explore how in situ measurements, earth observations, and the models they inform have facilitated the large-scale quantification of DOC stocks, fluxes, and transformations along the land-ocean aquatic continuum and how they have helped shape our current understanding of the global DOC cycle. The review also explores the limitations and challenges we still face today, and discusses how upcoming and future sensors are expected to provide new insights into our understanding of the global DOC cycle.

Dissolved organic carbon↗

Potential applications of microbial genomics in nuclear non-proliferation

As nuclear technology evolves in response to increased demand for diversification and decarbonization of the energy sector, new and innovative approaches are needed to effectively identify and deter the proliferation of nuclear arms, while ensuring safe development of global nuclear energy resources. Preventing the use of nuclear material and technology for unsanctioned development of nuclear weapons has been a long-standing challenge for the International Atomic Energy Agency and signatories of the Treaty on the Non-Proliferation of Nuclear Weapons. Environmental swipe sampling has proven to be an effective technique for characterizing clandestine proliferation activities within and around known locations of nuclear facilities and sites. However, limited tools and techniques exist for detecting nuclear proliferation in unknown locations beyond the boundaries of declared nuclear fuel cycle facilities, representing a critical gap in non-proliferation safeguards. Microbiomes, defined as “characteristic communities of microorganisms” found in specific habitats with distinct physical and chemical properties, can provide valuable information about the conditions and activities occurring in the surrounding environment. Microorganisms are known to inhabit radionuclide-contaminated sites, spent nuclear fuel storage pools, and cooling systems of water-cooled nuclear reactors, where they can cause radionuclide migration and corrosion of critical structures. Microbial transformation of radionuclides is a well-established process that has been documented in numerous field and laboratory studies. These studies helped to identify key bacterial taxa and microbially-mediated processes that directly and indirectly control the transformation, mobility, and fate of radionuclides in the environment. Expanding on this work, other studies have used microbial genomics integrated with machine learning models to successfully monitor and predict the occurrence of heavy metals, radionuclides, and other process wastes in the environment, indicating the potential role of nuclear activities in shaping microbial community structure and function. Results of this previous body of work suggest fundamental geochemical-microbial interactions occurring at nuclear fuel cycle facilities could give rise to microbiomes that are characteristic of nuclear activities. These microbiomes could provide valuable information for monitoring nuclear fuel cycle facilities, planning environmental sampling campaigns, and developing biosensor technology for the detection of undisclosed fuel cycle activities and proliferation concerns.

59 BASIC BIOLOGICAL SCIENCES↗

A spatial emergent constraint on the sensitivity of soil carbon turnover to global warming

Carbon cycle feedbacks represent large uncertainties in climate change projections, and the response of soil carbon to climate change contributes the greatest uncertainty to this. Future changes in soil carbon depend on changes in litter and root inputs from plants and especially on reductions in the turnover time of soil carbon (τ s ) with warming. An approximation to the latter term for the top one metre of soil (ΔC s,τ ) can be diagnosed from projections made with the CMIP6 and CMIP5 Earth System Models (ESMs), and is found to span a large range even at 2 °C of global warming (-196 ± 117 PgC). Here, we present a constraint on ΔC s,τ , which makes use of current heterotrophic respiration and the spatial variability of τs inferred from observations. This spatial emergent constraint allows us to halve the uncertainty in ΔC s,τ at 2 °C to -232 ± 52 PgC.

54 ENVIRONMENTAL SCIENCES↗

Infrared thermography NDT for in-situ defect detection in sandwich composite panel manufacturing

Composite manufacturing presents numerous challenges, as defects can arise from various sources throughout the process. In sandwich composite structures, the integration of a foam core introduces additional complexity and increases the likelihood of defect formation like delamination. To mitigate these issues and reduce the risk of future structural failures, in-situ monitoring during manufacturing is essential. This study investigates infrared (IR) thermography as a non-destructive technique for detecting manufacturing defects in foam-core sandwich composite panels under thermally excited conditions representative of in-situ processing. A stationary FLIR A8590 IR camera (640 × 512 pixels, 30Hz, 17mm lens, 9 ft stand-off distance) was used to monitor prefabricated panels subjected to controlled external heating simulating compression molding and resin cure exotherm. Interlaminar delamination defects with characteristic sizes ranging from 0.25 × 0.25in² to 5 × 5in² produced measurable surface temperature depressions of approximately 4–10°C during transient cooling, exceeding the effective noise floor of the camera by more than two standard deviations. Thicker laminates exhibited prolonged defect detectability windows due to increased thermal diffusion time. In contrast, embedded Teflon inclusions generated weak thermal contrasts of ≤ 3°C, approaching the measurement noise floor, due to limited thermal property contrast with the surrounding glass fiber composite. These results establish quantitative detectability limits for stationary thermographic inspection of sandwich composite panels under manufacturing-representative thermal cycles.

Barakat, Abdallah [ORNL] (ORCID:0000000296141398)↗