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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 OSTI2026

Volatile Organic Compounds in Bankhead National Forest (AMF3). August to September, 2025

The formation of atmospheric aerosols through the transformation of volatile organic compounds (VOCs) is a fundamental process in aerosol-climate interactions, as these particles serve as cloud condensation nuclei and ultimately influence Earth’s radiative balance. However, there remains a critical need to quantify the effects of multiple coexisting VOC precursors on aerosol formation beyond the limitations of laboratory-scale studies. This research aims to advance the mechanistic understanding of secondary organic aerosol formation in the southeastern United States by investigating interactions among coexisting VOC precursors observed at the third ARM Mobile Facility located in the Bankhead National Forest. The dataset was generated from the deployment of Oak Ridge National Laboratory’s PTR-TOF 6000 X2 Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS) for the real-time, continuous monitoring of VOCs from August 21 to September 15, 2025. To minimize sampling artifacts and compound losses, the PTR-ToF-MS inlet was connected to the cabin flow line by replacing the existing Tygon tubing with 1/2-inch outer diameter perfluoroalkoxy (PFA) tubing. The instrument operated on an hourly measurement cycle consisting of 8 minutes of zero-air measurements followed by 52 minutes of ambient air sampling, with a temporal resolution of 10 seconds. The dataset includes concentrations, reported in ppb, of methanol, acetone, acetonitrile, isoprene, methyl vinyl ketone and methacrolein (MVK + MACR), monoterpenes, benzene, toluene, and catechol.

Atmospheric concentration of volatile organic comp↗
DOE OSTI2023

IM3 GO WEST Parameter Search Dataset

GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.

Economics↗
DOE OSTI2023

Modeling the U.S. Western Electric Interconnection to Understand the Consequences of Hydrometeorological Extremes and Options for Risk Mitigation

Electricity grid operators around the world face a dual challenge; withstanding increasingly severe weather and the longer term impacts of climate change, while simultaneously decarbonizing. Extreme weather events such as heat waves and droughts are rising in both severity and frequency, which is threatening the reliability of electricity grids through increased demand, generation capacity losses, and equipment failures. Consequently, incorporating hydrometeorological stressors into computational power systems analysis is becoming an even more critical tool in long term planning and short term operations. However, there is a general lack of open-source customizable grid simulation software capable of exhaustively stress testing the grid under hydrometeorological uncertainty, and/or examining potential risk mitigation pathways. A related, persistent challenge for power system modelers is striking an appropriate balance between model fidelity (e.g. spatial scale and time resolution) and computational tractability (wall clock run-time). In this study, we are proposing a solution to this problem with open-source software that allows users to seamlessly customize the scale and track the accuracy of grid operations models. Our approach allows users to search over numerous model parameters (network topology, mathematical formulation, economic hurdle rates, and transmission line scaling) to identify model instantiations that accommodate experimental design. Further, we use this approach to demonstrate the importance of including extreme weather events in model validation and model selection. Focusing on the occurrence of heatwaves and droughts in the U.S. Western Interconnection, we examine role of extreme events in balancing tradeoffs between model fidelity and run-time at the model design stage.

Economics↗
DOE OSTI2026

The anaerobic fungus Caecomyces churrovis produces H 2 via a non-bifurcating NADH-dependent enzyme complex

ABSTRACT Hydrogenosomes are mitochondria-derived organelles that produce ATP and H 2 to support energy metabolism in anaerobic eukaryotes. H 2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H 2 production in anaerobic eukaryotes remains incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P) + and link electron transfer to H 2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H 2 production in the AF strain Caecomyces churrovis . Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H 2 :NAD + oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H 2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis , and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H 2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H 2 production and altering fungal metabolism. IMPORTANCE H 2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H 2 production from AF was first reported, the molecular mechanism for hydrogenosomal H 2 production and redox balance remains unclear. We demonstrate that AF produce H 2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H 2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H 2 -producing systems.

Zhang, Bo [Department of Chemical Engineering, Uni↗
DOE OSTI2026

Catalytic Bias of NADH-Dependent Reduced Ferredoxin: NADP+ Oxidoreductase (Nfn) and its Relevance to Ethanol Production in Thermoanaerobacterium Saccharolyticum

NADH-dependent reduced ferredoxin: NADP+ oxidoreductase (Nfn) enzyme catalyzes an energy-conserving flavin-based electron bifurcation (FBEB) reaction. In microbial metabolism, Nfn links redox pools of three electron carriers - ferredoxin (Fd), NAD(H), and NADP(H) - through the following FBEB reaction: 2 NADPH + NAD+ + 2 Fdox 2 NADP+ + NADH + 2 Fdred + H+ The forward reaction is termed electron bifurcation, and the reverse reaction is electron confurcation. Catalytic bias describes an enzyme's tendency to favor one direction of a reversible reaction over the other and is expressed as the ratio of activities in the two directions. Thermoanaerobacterium saccharolyticum (Tsac) is a thermophilic, ethanologenic bacterium that ferments hemicellulose to ethanol at yields above 90%. Its Nfn enzyme is known to support ethanol production, presumably by operating in the confurcating direction to balance cellular cofactors, but this has not previously been demonstrated. To investigate the Tsac Nfn further, we heterologously expressed, purified, and reconstituted the proteins NfnS (NfnA), NfnL (NfnB), and the putative partner Fd with iron-sulfur cluster and/or FAD cofactors. Activity assays monitoring the oxidation or reduction of Fd showed that, across pH 5-10, Tsac Nfn is catalytically biased towards the confurcating direction, favoring NADPH generation over NADPH oxidation by at least fivefold. Using protein electrochemistry, we also determined the reduction potentials of the cofactors in NfnL and Fd. These results indicate that the energetic landscape of FBEB in Tsac Nfn is similar to that in an ortholog. However, Tsac Fd has redox properties distinct from previously assayed Fds, suggesting that the identity and redox properties of Fd may help determine the catalytic bias of Nfn. Additionally, we confirmed the standalone ferredoxin: NADP+ oxidoreductase (FNOR) activity of NfnL but found it to be low and likely insignificant for in vivo redox conversion. We also show how the catalytic bias of Nfn integrates with the hydrogen cycling mechanism proposed in Tsac to better explain cofactor balancing for ethanol production. Our work advances the understanding of electron transfer processes within metabolic networks for the generation of valuable bioproducts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Meeting the Challenges of Modern Transit through the Integration of Traditional Transit, On-Demand Micro-Transit Services and Vehicle Automation - A Case Study in Chandler, Arizona

Current technology trends of vehicle automation, electrification and on-demand transit are providing new tools to develop effective public mobility services, yet need to be balanced with traditional modes to serve the spectrum of demand effectively and efficiently. Automated vehicle transportation network company (TNC) services, better known as 'Robotaxis' are beginning to proliferate and scale across the US, with Waymo as the lead commercial entity. Chandler, AZ was the first fully automated deployment of Waymo technology. Chandler was also one of the first municipalities in Arizona to roll out micro-transit service to its citizens in 2022. At present the Chandler Flex micro-transit program is beginning to partner with Waymo to augment micro-transit services during peak demands, another first in the nation. However, the mix of services in Chandler relies not only on new technology, but also on traditional modes including fixed route transit and para-transit services. These are blended and balanced such that both old and new modes are applied within the context in which each excel. This presentation will provide background on the Chandler, AZ public mobility services, and the performance metrics that govern their use and selection within the spectrum of development and population density as well as socio-demographics within Chandler. Additionally, the behavioral response of the use of unmanned, automated vehicles employed to augment micro-transit is novel, the first in the nation - and initial feedback from public transit constituents in Chandler will be shared.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production by conducting a statistical analysis of historical wind data over a five-year period (2020-2025) from a single 1.5MW turbine manufactured by General Electric (GE) located at NLR’s Flatirons Campus, to generate an experimental test profile that was deployed on a 1.25-MW proton exchange membrane type MC250 electrolyzer system manufactured by Nel Hydrogen . [1] While the electrolyzer balance-of-plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. The historical wind data provided several metrics, however, the analysis particularly focused on the measured power output by the wind turbine. The power output time series of data for each day was categorized by total energy generation and standard deviation, and the day that represented the highest combination of these two metrics was chosen – December 25th, 2022. This process was then repeated for a moving four-hour window within this day to identify the most statistically variable period. Finally, this four-hour period was scaled by 65% to match the 1.25 MW electrolyzer. The electrolysis system controls hydrogen production by varying DC current applied to the stack, from a maximum of 3000 A to a minimum safe operation of 300 A, or 10%. Because the current – voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical wind profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1 Hz frequency. For more details on the statistical analysis process, see the presentation labeled “ Public Reference Data for Megawatt-Scale Hydrogen Electrolysis” provided with each data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}_{scaling factor}-{electrolyzer ramp rate in amperes/second} For instance, “wind-GE1.5MW_0.65-400.zip” represents the hour-long experiment using historical data from the wind-GE1.5MW turbine, scaled to 65%, with the electrolyzer power supply set to a maximum ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and wind power input. A PDF file detailing the historical wind data statistical analysis used to generate the wind profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_historical_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis [1] nelhydrogen.com/product/mc-series-electrolyser .

08 HYDROGEN↗
DOE OSTI2026

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Solar PV

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) research platform. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence data centers and other variable loads. This dataset entry describes the behavior of a 1.25-MW proton exchange membrane MC250 electrolyzer system, manufactured by Nel Hydrogen , [1] when fed historical data generated by the 430-kW, fixed-axis solar photovoltaic (PV) array located at NLR’s Flatirons Campus. (While the electrolyzer balance of plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.) Solar PV power output data for the 2020 calendar year were categorized on a daily basis by total energy generation and standard deviation. Each day was then ranked by these metrics, and the 25th, 50th, and 100th percentiles were selected. The 75th percentile day did not exhibit sufficient variability to make for a valuable experiment. A similar process was used for the related historical wind dataset . [2] The historical days in 2020 that represented these percentiles are Dec. 19, March 29, and May 4, respectively. The entire solar day’s power profile was then fed through the MC250 electrolyzer. Due to its length, the 100th percentile day experiment was split into two parts, and the final 3 hours of the solar day were not captured. These final 3 hours contained no spikes or dips of interest and simply represented a slow decay of input solar power. Also, a single timestamp (13:13:47 on Jan. 14, 2026) was lost in the hydrogen system supervisory control and data acquisition. Finally, during the 25th percentile experiment (solar day Dec. 19, 2020) data recording was lost from 11:00:13 to 11:14:45. The roughly 15 minutes of the solar profile were rerun at the end of the experiment and spliced into this time slot during post-processing. The electrolysis system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operation of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical solar profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. For more details on the statistical analysis process, see the slide deck “Public Reference Data for Megawatt-Scale Hydrogen Electrolysis: NLR Historical Solar PV Analysis and Profile Generation” accessible with this data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single solar PV electrolysis experiment and is formatted as: {technology}_{percentile}_{scaling factor} For instance, “solarPV-430kW_25_2x.zip” reports the experiment using the 25th percentile solar data from the historical 2020 solar PV dataset, scaled to 200%. Scaling factors were applied to the generated solar PV power output files to more closely match the 1.25-MW capacity of the electrolyzer. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and solar power input. A PDF file detailing the historical solar data statistical analysis used to generate the solar profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all experiments combined into one dataset labeled "combined_solarPV_experiments.csv". [1] nelhydrogen.com/product/mc-series-electrolyser . [2] data.nlr.gov/submissions/316 .

08 HYDROGEN↗
DOE OSTI2021

Dynamic Phase Alignment in Inertial Alfven Turbulence

In weakly-collisional plasma environments with sufficiently low electron beta, Alfvenic turbulence transforms into inertial Alfvenic turbulence at scales below the electron skin-depth. We argue that, in inertial Alfvenic turbulence, both energy and generalized kinetic helicity exhibit direct cascades. We demonstrate that the two cascades are compatible due to the existence of a strong scale-dependence of the phase alignment angle between velocity and magnetic field fluctuations, with the phase alignment angle scaling as proportional to the perpendicular wavenumber to the power of -1. The kinetic and magnetic energy spectra scale as the perpendicular wavenumber to the power of -5/3 and -11/3, respectively. As a result of the dual direct cascade, the generalized-helicity spectrum scales as the perpendicular wavenumber to the power of -5/3, implying progressive balancing of the turbulence as the cascade proceeds to smaller scales in the sub-electron-skin-depth range. Turbulent eddies exhibit a phase-space anisotropy, with the parallel wavenumber scaling as the perpendicular wavenumber to the power of 5/3, consistent with critically-balanced inertial Alfven fluctuations. Our results may be applicable to a variety of geophysical, space, and astrophysical environments, including the Earth's magnetosheath and ionosphere, solar corona, non-relativistic pair plasmas, as well as to strongly rotating non-ionized fluids.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

L-H transition trigger physics in ITER-similar plasmas with applied n = 3 magnetic perturbations

The L–H transition power threshold PLH is observed to increase with applied n = 3 resonant magnetic perturbations (RMP) in ITER-similar-shape plasmas with balanced neutral beam torque injection in DIII-D. The increase is most pronounced with added electron–cyclotron heating: PLH increases with decreasing edge plasma collisionality as PLH/PLH-08 ~ (ν*)−0.5, where PLH-08 is the 2008 ITPA multi-machine power threshold scaling. This result raises concerns for H-mode access at low edge collisionality in ITER, where RMP may have to be applied before the L–H transition to safely suppress the first edge-localized mode. Non-axisymmetric modifications with RMP include a simultaneous reduction of the radial electric field (Er) well depth and E × B shear. This can be attributed to increasing edge toroidal co-current rotation, and is consistent with substantially increased local long-wavelength turbulence (measured via beam emission spectroscopy). At high RMP perturbation strength the edge electric field Er reverses sign locally (becomes positive), with changes in dominant turbulence modes. Edge magnetic stochasticity provides an attractive explanation of the observed modifications, and the observed changes in toroidal rotation and Er are consistent with a simple fluid model describing radial electron current flow along stochastic fieldlines. The observed collisionality dependence of the L-mode edge electric field with applied RMP is also qualitatively consistent with this model. Reflectometry data indicate a significant reduction of the normalized L-mode radial density gradient a/Ln at high RMP field with simultaneous increase in radial particle flux and electron thermal flux from power balance analysis. We conjecture that the increase of PLH with RMP results from the combined effects of reduced E × B flow shear (increasing turbulent transport levels) and toroidal/poloidal flow modulation due to edge stochasticity. Initial experiments indicate that non-resonant n = 3 magnetic perturbations lead only to relatively small changes in Er, E × B shear and fluctuation characteristics, and have less impact on the L–H transition power threshold. This motivates further exploration of the RMP spectrum dependence of PLH for possible mitigation of the observed threshold increase.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

National direct-drive program on OMEGA and the National Ignition Facility

A major advantage of the laser direct-drive (DD) approach to ignition is the increased fraction of laser drive energy coupled to the hot spot and relaxed hot-spot requirements for the peak pressure and convergence ratios relative to the indirect-drive approach at equivalent laser energy. With the goal of a successful ignition demonstration using DD, the recently established national strategy has several elements and involves multiple national and international institutions. These elements include the experimental demonstration on OMEGA cryogenic implosions of hot-spot conditions relevant for ignition at MJ-scale energies available at the National Ignition Facility (NIF) and developing an understanding of laser-plasma interactions and laser coupling using DD experiments on the NIF. DD designs require reaching central stagnation pressures in excess of 100 Gbar. The current experiments on OMEGA have achieved inferred peak pressures of 56 Gbar (Regan et al 2016 Phys. Rev. Lett. 117 025001). Extensive analysis of the cryogenic target experiments and two- and three-dimensional simulations suggest that power balance, target offset, and target quality are the main limiting factors in target performance. In addition, cross-beam energy transfer (CBET) has been identified as the main mechanism reducing laser coupling. Reaching the goal of demonstrating hydrodynamic equivalence on OMEGA includes improving laser power balance, target position, and target quality at shot time. CBET must also be significantly reduced and several strategies have been identified to address this issue. (2016-01-01)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Quantum random number generators

Random number generators include a thermal optical source and detector configured to produce random numbers based on quantum-optical intensity fluctuations. An optical flux is detected, and signals proportional to optical intensity and a delayed optical intensity are combined. The combined signals can be electrical signals or optical signals, and the optical source is selected so as to have low coherence over a predetermined range of delay times. Balanced optical detectors can be used to reduce common mode noise, and in some examples, the optical flux is directed to only one of a pair of balanced detectors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Future of Zero Energy Buildings: Produce, Respond, Regenerate: Preprint

The zero energy buildings concept is more than 20 years old, and the paradigm shift from buildings as energy consumers to buildings as energy producers is underway. Buildings also consume land and material resources, however, with attendant environmental impacts. Another paradigm is emerging: a built environment that produces energy and is environmentally responsive and regenerative. This paper investigates an updated framework for thinking about zero energy buildings that includes discussions of prioritizing renewables; determining on-site versus off-site generation; exploring how and when buildings should use energy; and balancing renewables, storage, and energy efficiency. Buildings are typically connected to the utility grid and the utility grid develops largely in response to the built environment. If more buildings’ real time electricity use aligned with renewable generation, more renewables would be added to the grid. Ultimately, the goal for zero energy buildings will be to use 100% renewables, 100% of the time, matching loads with energy storage and renewable generation at each discrete timestep over a year. This target is beyond the current zero energy definitions, which focus on an annual balance of renewable supply and energy demand and use the grid to “store” excess production to make up for hours without sufficient on-site renewable generation. This paper expands this upgraded concept and outlines simple metrics to evaluate the alignment of renewable sources and storage with building loads. This process can provide insights on building design considerations, including the use of flexible loads and optimal resource management.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2020

Mechanical Properties of Aged A709

A709 plate is in the process of being developed and qualified through a collaboration by Argonne National Laboratory (ANL), Idaho National Laboratory (INL), and Oak Ridge National Laboratory (ORNL). The goal is to qualify A709 plate in Section III, Division 5 of the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code (BPVC). This would permit the construction of A709 plate for fast-reactor structural applications. A tradeoff between creep and creep-fatigue properties was established in prior work. A processing route was identified as providing the optimal balance between creep-rupture and elevated-temperature cyclic properties for the solution annealed condition. This condition, however, resulted in a shorter than desired creep-rupture life. Aging is probed to evaluate its potential at further improving mechanical properties. Aging statically precipitates the solutes in solution prior to service. The processing routes identified as providing the best creep-rupture properties and best balance in mechanical properties are investigated. This report discloses the results from tensile, creep, and elevated-temperature cyclic testing performed at INL on the aged material. The aged properties are compared to solution annealed properties. A709 offers improvement in performance compared to 316H particularly at high temperatures; 316H is a material qualified in Section III, Division 5 of the ASME BPVC. For certain high-temperature fast-reactor design conditions, 316H cannot be used while A709 can.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Counterweight for Long Reach Robotic Arm

Maintenance for vital systems proves challenging due to their location: tucked up and behind components. Pinpointing the precise location of errors presents difficulty when relying solely on the human eye. The solution to this issue arises in the form of a Long Reach Robotic Arm. An adequately balanced robot with several individually controlled links contains the capability to maneuver around obstructing components to locate the points of failure with accuracy. The design process for such a robot begins with the writing of a program. The program intends to visualize how the Long Reach Robotic Arm will move in 2D space by printing a select number of lines representing each arm link to the screen and controlling each link through the keyboard. This code substantially simplifies the design process for the multi-linked arm. The next step in the Long Reach Robotic Arm design process is the development of the arm and its counterweight system. The clear division of this work allows two interns to work on this project: one assumes responsibility for the arm, and the other for the counterweight. I undertook the design for the counterbalance. My half of the project is essential for maintaining safety as an extended multi-linked robot arm presents the challenge of preserving stability. The best method to supply a balance to the robot, even in extension, is a mobile counterweight with a compact design.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Design Study for Bio-Oil Production from Biomass Using a Dual Fluidized-Bed Reactor

To evaluate the re-design and reconfiguration of a dual-fluidized bed (DFB) gasification system into a recirculating pyrolysis reactor, Computation Fluid Dynamic (CFD) simulations of the system were conducted. The Barracuda Virtual Reactor® computational particle fluid dynamic code was used to perform simulations of the pyrolysis process. Modeling of the chemical reaction kinetics for both gas phase and solid particle phase were included. The recirculating pyrolysis reactor shown in Fig. 1a is based on a bubbling-bed biomass pyrolyzer and a riser combustor to convert the remaining char. The operational differences in the re-configuration of the DFB gasification system into a recirculating pyrolysis system for the production of bio-oil are (1) replacement of a low-surface area inert bed material with a high-surface-area bed material that has acidic properties to provide catalytic activity for the production of bio-oil with reduced oxygen content, (2) lower temperature and residence time for bio-oil production from pyrolysis, (3) replacement of the fluidization gas in the bubbling bed pyrolyzer from steam to nitrogen, and (4) the reduction of pyrolyzer freeboard volume. The bed material used for catalytic pyrolysis is Sasol 300 (300-micron dia., bulk density 0.94 kg/l, and surface area 130 m2/g) and is a theta-alumina with mild acidity. This is in comparison with previous standard bed material Carbo HSP (430-micron dia., bulk density 2.01 kg/l, and surface area 0.03 m2/g) used for gasification. For bio-oil production, pyrolysis in the bubbling bed requires temperatures in the range of 550 C in comparison with gasification temperatures near 850 C. To attain this lower temperature requires management of the energy mass balances, with control of the bed material recirculation rate between bubbling bed pyrolyzer and riser combustor, the introduction of a nitrogen purge in the pyrolyzer, and adjusting the pressure balance between the two vessels. To extract bio-oil from the pyrolysis reactor with a snorkel, two different freeboard configurations were evaluated. In Fig. 1 b the existing high freeboard configuration is shown and in Fig. 1 c the reduced freeboard design is presented. The introduction of a nitrogen purge for the high free board configuration provided the highest bio-oil production from the CFD simulations. To decrease the bed-material circulation rate, primary and secondary air on the combustor side were reduced, and the pressure on the combustor was slightly increased. A portion of the biomass and bio-oil was observed to be transported to the combustor, leading to a smaller pyrolysis yield. The control of the pyrolyzer temperature is performed by controlling the circulation rate. Good fluidization of the bubbling bed and cascade PID control are required to keep the temperature from oscillating due to large time delay experienced when changing primary and secondary air. (a) (b) (c) Figure 1. (a) Dual Fluidized Bed pyrolysis system configuration, (b) mole fraction of nonpolar biooil in high freeboard configuration, and (c) mole fraction of nonpolar bio-oil in low freeboard configuration with nitrogen purge introduced in both configurations.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗
DOE OSTI2021

Biodegradable surfactants and related compositions, methods and systems

Biodegradable surfactants are described, in which an amphiphilic heteroatom containing hydrocarbon optionally comprising at least one counterion (Z), and related compositions, methods and systems. Biodegradable surfactant described herein has an aHLB value in accordance with equation (1): aHLB=20*Gh/(Gh−Gt) (1) wherein Gh is the Group Number of a hydrophilic head portion of the biodegradable surfactant optionally comprising the at least one counterion (Z), and Gt is the Group Number of a hydrophobic tail portion of the biodegradable surfactant. A biodegradable surfactant in the sense of the disclosure can be tuned to a set hydrophilic-lipophilic balance (aHLB) by selectively modifying at least one tuning moiety of the biodegradable surfactants to provide tuned biodegradable surfactants having an increase or decrease in their adjusted hydrophilic-lipophilic balance (aHLB).

Lyman, Mathew Gerald↗
DOE OSTI2022

Plasma Science: Enabling Technology, Sustainability, Security, and Exploration

The Plasma2020 decadal report took a forward-looking, interagency perspective on how the different elements that constitute plasma science provide a broad interdisciplinary driver for capitalizing on future opportunities in the scientific community. Goals of the study were to (1) provide a retrospective survey of the field of plasma science; (2) illustrate the vibrant connections that unify the field of plasma science; (3) offer a vision for future developments in plasma science, such as those related to organizational structure, program balance, and funding; (4) provide an assessment of the demographic characteristics and human resource development of the field, such as those related to workforce, educational, and other societal needs; and (5) make recommendations to balance the objectives of the field in a sustainable and healthy manner over the long term. The resulting report was composed in a style accessible to the non-scientist reader. With this approach, a broad audience can understand the importance of plasma science and what researchers in the field want to learn in the coming decades.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗