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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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Poster describing the planned startup process of a solid oxide gas turbine hybrid power system to be constructed at a 20 kW scale. The work is part of the ARPA-E project award to NETL under the INTEGRATE program.
Interest in the utility of seaweed farms to mitigate coastal eutrophication, or nutrient loading, has grown commensurate with the recent rise of the farmed seaweed industry in the U.S. But economic valuation of this ecosystem service remains elusive in part because of challenges in quantifying this spatiotemporally variable biological process with reproducible and comparable metrics. Regulatory bodies that permit wastewater discharge or lease area for aquaculture farms require water quality testing and reporting of dissolved total nitrogen (N) in nearshore marine environments. These metrics must meet EPA standards for testing and reporting (e.g., Total Kjeldahl Nitrogen - TKN). However, these metrics are inherently highly variable over space and time in dynamic nearshore systems, and expensive to evaluate with sufficient breadth to constrain this variance, creating a critical bottleneck to direct quantification of farmed seaweed net uptake rates in situ.
The Cryogenic Division at Fermilab develops large-scale cryogenic systems for particle accelerators and superconducting test facilities. To support design and diagnostics, a Python-based code was created to calculate pressure drops in components such as valves and pipes. This paper presents recent enhancements to the code, including new heat transfer functions that improve the accuracy of thermal and hydraulic predictions. The first application models pressure and temperature changes in PIP-II relief pipes, aiding pipe sizing and protecting relief valves. The second example analyzes heat load evolution in a pipe carrying sub-atmospheric helium, helping interpret temperature sensor data and understand gas return behavior to cold compressors. These improvements significantly expand the tool’s capabilities, offering a practical resource for designing and troubleshooting cryogenic systems under dynamic thermal and flow conditions.
W. L. Gore & Associates assembled a world class team (De Nora Tech, LLC; New York University; and thyssenkrupp nucera) to develop durable, ultra-low resistance diaphragms that dramatically improve system efficiency, dynamic response, and operational flexibility. To enable the use of ultra-thin diaphragms, an optimized electrode package was chosen as part of an electrode down select study. Ultra-thin diaphragms based on microporous polymer scaffolds imbibed with zirconia nanoparticles were developed and tested. Performance and durability on par with incumbent materials was demonstrated. A transparent electrolyzer to directly observe in-situ diaphragm-bubble interactions was designed and built, and simultaneous optical and electrochemical performance tests were performed. A Pressurized Alkaline Water Electrolysis (PAWE) single cell test station was designed to support advanced R&D in high-pressure electrolysis, particularly for evaluating novel electrode and separator configurations under elevated temperature and pressure operating conditions. Due to early project termination, the original scope could not be fully achieved.
SuperLab 2.0 (a five-lab demonstration) is a collaborative, national-scale experiment showcasing the coordination of geographically distributed energy assets in real time. The demonstration integrates 25 physical and digital assets, spanning wind, photovoltaics, batteries, electrolyzers, DC fast chargers, microgrid controllers, building automation systems, small modular reactors, control centers, and gas turbines, across five U.S. Department of Energy (DOE) national laboratories: National Laboratory of the Rockies (NLR), Idaho National Laboratory, National Energy Technology Laboratory, Lawrence Berkeley National Laboratory, and Sandia National Laboratories. These assets are unified using Energy Sciences Network (ESnet), a low-latency, high-performance DOE network, and are controlled via a centralized energy controller hosted at NLR's Advanced Research on Integrated Energy Systems facility. The demonstration validates the ability to stress-test hybrid energy systems under dynamic scenarios to de-risk advanced control strategies for greater resilience and flexibility.
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We revisit the theory of first-order quasilinear systems with diagonalizable principal part and only real eigenvalues, what is commonly referred to as strongly hyperbolic systems. We provide a self-contained and simple proof of local well-posedness, in the Hadamard sense, of the Cauchy problem. Our regularity assumptions are very minimal. As an application, we apply our results to systems of ideal and viscous relativistic fluids, where the theory of strongly hyperbolic equations has been systematically used to study several systems of physical interest.
Inland waters are hotspots for biogeochemical activity, but the environmental and biological factors that govern the transformation of organic matter (OM) flowing through them are still poorly constrained. Here we evaluate data from a crowdsourced sampling campaign led by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to investigate broad continental-scale trends in OM composition compared to localized events that influence biogeochemical transformations. Samples from two different OM compartments, sediments and surface water, were collected from 97 streams throughout the Northern Hemisphere and analyzed to identify differences in biogeochemical processes involved in OM transformations. By using dimensional reduction techniques, we identified that putative biogeochemical transformations and microbial respiration rates vary across sediment and surface water along river continua independent of latitude (18°N–68°N). In contrast, we reveal small- and large-scale patterns in OM composition related to local (sediment vs. water column) and reach (stream order, latitude) characteristics. These patterns lay the foundation to modeling the linkage between ecological processes and biogeochemical signals. We further showed how spatial, physical, and biogeochemical factors influence the reactivity of the two OM pools in local reaches yet find emergent broad-scale patterns between OM concentrations and stream order. OM processing will likely change as hydrologic flow regimes shift and vertical mixing occurs on different spatial and temporal scales. As our planet continues to warm and the timing and magnitude of surface and subsurface flows shift, understanding changes in OM cycling across hydrologic systems is critical, given the unknown broad-scale responses and consequences for riverine OM.
Wave energy converters (WECs) harness the untapped power of ocean waves to generate renewable energy, offering a promising solution to sustainable energy. An optimal WEC control strategy is essential to maximize power capture that dynamically adjusts system parameters in response to rapidly changing sea states. This study presents a novel control approach that leverages neural networks to estimate sea states from onboard WEC measurements such as position, velocity, and force. Using a point absorber WEC device as a test platform, our proposed approach estimates sea states in real-time and subsequently adjusts PID controller gains to maximize energy extraction. Simulation results across diverse sea conditions demonstrate that our strategy eliminates the need for external wave monitoring equipment while maintaining power capture efficiency. The results show that our neural network-based control technique can improve power capture by 25.6% while significantly reducing system complexity. This approach offers a practical alternative for WEC deployments where direct wave measurements are either infeasible or cost prohibitive.
River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.
The spatial distribution and properties of submicron organic aerosol (OA) are among the key sources of uncertainty in our understanding of aerosol effects on climate. Uncertainties are particularly large over remote regions of the free troposphere and Southern Ocean, where very few data have been available and where OA predictions from AeroCom Phase II global models span 2 to 3 orders of magnitude, greatly exceeding the model spread over source regions. The (nearly) pole-to-pole vertical distribution of non-refractory aerosols was measured with an aerosol mass spectrometer onboard the NASA DC-8 aircraft as part of the Atmospheric Tomography (ATom) mission during the Northern Hemisphere summer (August 2016) and winter (February 2017). This study presents the first extensive characterization of OA mass concentrations and their level of oxidation in the remote atmosphere. OA and sulfate are the major contributors by mass to submicron aerosols in the remote troposphere, together with sea salt in the marine boundary layer. Sulfate was dominant in the lower stratosphere. OA concentrations have a strong seasonal and zonal variability, with the highest levels measured in the lower troposphere in the summer and over the regions influenced by biomass burning from Africa (up to 10 µg sm -3 ). Lower concentrations (~0.1–0.3 µg sm -3 ) are observed in the northern middle and high latitudes and very low concentrations (<0.1 µg sm -3 ) in the southern middle and high latitudes. The ATom dataset is used to evaluate predictions of eight current global chemistry models that implement a variety of commonly used representations of OA sources and chemistry, as well as of the AeroCom-II ensemble. The current model ensemble captures the average vertical and spatial distribution of measured OA concentrations, and the spread of the individual models remains within a factor of 5. These results are significantly improved over the AeroCom-II model ensemble, which shows large overestimations over these regions. However, some of the improved agreement with observations occurs for the wrong reasons, as models have the tendency to greatly overestimate the primary OA fraction and underestimate the secondary fraction. Measured OA in the remote free troposphere is highly oxygenated, with organic aerosol to organic carbon (OA/OC) ratios of ~2.2–2.8, and is 30 %–60 % more oxygenated than in current models, which can lead to significant errors in OA concentrations. The model–measurement comparisons presented here support the concept of a more dynamic OA system as proposed by Hodzic et al. (2016), with enhanced removal of primary OA and a stronger production of secondary OA in global models needed to provide better agreement with observations.
Abstract. Biochemical transformations of organic matter (OM) are a primary driver of river corridor biogeochemistry, thereby modulating ecosystem processes at local to global scales. OM transformations are driven by diverse biotic and abiotic processes, but we lack knowledge of how the diversity of those processes varies across river corridors and across surface and subsurface components of river corridors. To fill this gap we quantified the number of putative biotic and abiotic transformations of organic molecules across diverse river corridors using ultra-high-resolution mass spectrometry. The number of unique transformations is used here as a proxy for the diversity of biochemical processes underlying observed profiles of organic molecules. For this, we use public data spanning the contiguous United States (ConUS) from the Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems (WHONDRS) consortium. Our results show that surface water OM had more biotic and abiotic transformations than OM from shallow hyporheic zone sediments (1–3 cm depth). We observed substantially more biotic than abiotic transformations, and the numbers of biotic and abiotic transformations were highly correlated with each other. We found no relationship between the number of transformations in surface water and sediments and no meaningful relationships with latitude, longitude, or climate. We also found that the composition of transformations in sediments was not linked with transformation composition in adjacent surface waters. We infer that OM transformations represented in surface water are an integrated signal of diverse processes occurring throughout the upstream catchment. In contrast, OM transformations in sediments likely reflect a narrower range of processes within the sampled volume. This indicates decoupling between the processes influencing surface water and sediment OM, despite the potential for hydrologic exchange to homogenize OM. We infer that the processes influencing OM transformations and the scales at which they operate diverge between surface water and sediments.
Abstract not provided.
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A power system's inter-area electromechanical modes of oscillation determine if the system is small-signal stable. Mode meters are tools that estimate the modes based on ambient synchrophasor measurements, allowing continuous monitoring of the system's stability margin. This paper reports on the application of mode meter algorithms to 21 months of synchrophasor measurements from the United States Eastern Interconnection (EI). Estimates for three modes were updated every minute, providing a much more comprehensive set of results than previous studies based on disturbance recordings. The detailed signal designs and mode meter configurations provided in this paper can be used to accelerate mode meter deployments in the EI. Analysis of the mode estimates reveal for the first time how seasonal load changes and system reconfiguration impact the EI system's dynamics.
In the preliminary design stage of a wave energy converter (WEC), fast and reliable simulation tools are required. High-fidelity numerical models are usually employed to study the wave-structure interaction, yet the computational cost is demanding. Instead, mid-fidelity models provide simulations in the order of real time. In this study, Uppsala University WEC operates in a relatively mild sea state and is modeled using WEC-Sim. The model is verified based on OpenFOAM simulations. To analyze the ability of mid-fidelity model to capture the WEC dynamics, the system is investigated separately in 1, 2 and 3 DoF. The contribution of viscous phenomena is examined. Moreover, linear and weakly non-linear solutions provided by WEC-Sim are studied. The results obtained indicate that the viscous effects in heave and surge motion can be neglected but not for the pitch. The weakly non-linear WEC-Sim solution successfully agrees with the CFD, whereas the linear solution could drive to misleading results.
In the preliminary design stage of a wave energy converter (WEC), fast and reliable simulation tools are required. High-fidelity numerical models are usually employed to study the wave-structure interaction, yet the computational cost is demanding. Instead, mid-fidelity models provide simulations in the order of real time. In this study, Uppsala University WEC operates in a relatively mild sea state and is modeled using WEC-Sim. The model is verified based on OpenFOAM simulations. To analyze the ability of mid-fidelity model to capture the WEC dynamics, the system is investigated separately in 1, 2 and 3 DoF. The contribution of viscous phenomena is examined. Moreover, linear and weakly non-linear solutions provided by WEC-Sim are studied. The results obtained indicate that the viscous effects in heave and surge motion can be neglected but not for the pitch. The weakly non-linear WEC-Sim solution successfully agrees with the CFD, whereas the linear solution could drive to misleading results.
Abstract not provided.