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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Transportation Hub Infrastructure Expansion: Decision Support Under Uncertainty

The Athena project (www.athena-mobility.org) has worked to investigate the relationship between the Dallas-Fort Worth Airport (DFW) and the greater Dallas area in order to better understand and therefore better inform future decision-making regarding the critical infrastructure that influence mobility between the airport and the city. Through this work, infrastructure related to curbside pickup and drop-off, parking, public transit, and the road network congestion were identified as critical to the operation of the DFW transportation hub. The infrastructure analysis and expansion aspect of the Athena project is focused on the restructuring of the CTA curb as a hierarchical curb and the building or repurposing of parking infrastructure as the interplay between these two areas. Many sources of uncertainty exist that may impact future airport and transportation hub operations, such as passenger volume growth, population demographic changes over time, electric vehicle (EV) adoption rates, and autonomous vehicle (AV) adoption rates. Due to these sources of uncertainty, we have selected for our research a modeling framework that can capture various types of uncertainty and hedge against those uncertainties in the optimization process. We analyze road network and curb congestion, the rise of transportation networking companies, trends in parking usage, existing policies around this infrastructure, airport revenue streams, and other contributing factors to enable infrastructure decision making with less uncertainty. To accomplish this wholistic analysis, we have developed a novel multi-stage, multi-period stochastic optimization model which considers the airport's decisions from 2025-2045 under different possible future macro trajectories and day-to-day variations in operational conditions captured as "annual representation of operations" scenarios with respective probabilities. This model has also been designed to leverage the outputs of various efforts under the Athena project to create a combined decision framework for infrastructure decisions. These various efforts include the route optimization model, the ASPIRES simulation, the mode choice model, and the SUMO traffic simulation. Our computational experiments of this system at scale have resulted in a working version of our infrastructure model which enables the explicit representation and consideration of various sources of uncertainty in the decision process to enable robust, flexible decision-making. This model has been effectively run on NREL's HPC system, Eagle, with large numbers of stochastic scenarios and shows promise as a scalable tool for robust consideration of uncertainties in airport planning. We have tested our model using 30,240 operational circumstances in total, resulting in a problem with more 200 million variables. This model was solved in several different configurations, and a workflow to simulate the performance of the infrastructure model results was developed and deployed. In general, our results indicate that a combination of remote parking, remote curb infrastructure, and dynamic pricing can generate revenue, reduce emissions, accommodate emerging technologies such as AVs and EVs, and manage airport passenger growth over time. We note the success of the proposed strategy depends on the data collection and forecasting abilities of DFW. We have also seen that the AV adoption by TNCs might necessitate larger amounts of remote curb. The results of this work inform strategies for airport infrastructure decision making, as well as demonstrate the value of an adaptable model, but also indicate that there are avenues remaining where further research would be of value.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Understanding long-term groundwater flow at Pahute Mesa and vicinity, Nevada National Security Site, USA, from naturally occurring geochemical and isotopic tracers

Abstract Recently collected naturally occurring geochemical and isotopic groundwater tracers were combined with historic data from the Pahute Mesa area of the Nevada National Security Site (NNSS), Nevada, USA, to provide insights into long-term regional groundwater flow patterns, mixing and recharge. Pahute Mesa was the site of 85 nuclear detonations between 1965 and 1992, many of them deeply buried devices that introduced radionuclides directly into groundwater. The dataset examined included major ions and field measurements, stable isotopes of hydrogen (δ 2 H), oxygen (δ 18 O), carbon (δ 13 C) and sulfur (δ 34 S), and radioisotopes of carbon ( 14 C) and chloride ( 36 Cl). Analysis of the patterns of groundwater 14 C data and the δ 2 H and δ 18 O signatures indicates that groundwater recharge is predominantly of Pleistocene age, except for a few localized areas near major ephemeral drainages. Steep gradients in sulfate (SO 4 ) and chloride (Cl) define a region near the western edge of the NNSS where high-concentration groundwater flowing south from north of the NNSS merges with dilute groundwater flowing west from eastern Pahute Mesa in a mixing zone that coincides with a groundwater trough associated with major faults. The 36 Cl/Cl and δ 34 S data suggest that the source of the high Cl and SO 4 in the groundwater was a now-dry, pluvial-age playa lake north of the NNSS. Patterns of groundwater flow indicated by the combined data sets show that groundwater is flowing around the northwest margin of the now extinct Timber Mountain Caldera Complex toward regional discharge areas in Oasis Valley.

58 GEOSCIENCES↗
DOE OSTI2022

NCSU Industrial Assessment Center

Renewable energy technologies are becoming more attractive and gaining more attention as the world becomes increasingly aware of the negative impacts of global warming and greenhouse gas (GHG) emissions. Two such emerging technologies are geothermal heat pumps (GHP) and solar thermal heating which can be used for heating and cooling of buildings. GHP systems are a well-studied technology that have been proven to be more efficient than traditional air-source heat pumps for space conditioning of buildings. Solar thermal heating has become more common as a way to heat domestic hot water (DHW) in homes, but the two technologies are not often combined. This study presents the findings of combining an open-loop GHP with 100 ft2 of flat plate solar thermal panels and a 5,655-gallon sensible water storage tank for space heating and DHW heating needs of a residential home in Bozeman, MT, USA. The goal of this system was to use energy from the solar panels and storage tank first to decrease pumping energy from the GHP well. The open loop system was designed to be a backup system to the solar thermal panels and sensible storage tank. An actual home was modeled to determine potential energy and cost savings of such a system compared to a traditional propane boiler. Then, a case study was performed on the installed system from January to June 2021. Results obtained from April 2nd to June 5th, 2021 indicated that the combination system supplied all necessary heat, and that heat was supplied from the thermal storage tank 55% of the time. This represents a savings of 330 kWh of energy and $36 compared to operating just the open loop geothermal system. From April 2nd to June 5th the combination system consumed a total of 2,510 kWh of energy and cost $274 to operate. Based on data obtained, there is significant potential for energy savings compared to a propane boiler, however only small potential for cost savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Strontium Effects on the Formation of Iron-Intermetallic Phases in Secondary Al–9Si–0.6Fe Alloys

The presence and morphology of Fe-containing intermetallic phases affect the mechanical properties of aluminum alloys, especially in secondary Al–Si-based cast alloys. Although strontium (Sr) addition of 50 to 500 ppm is known to refine the needle-type eutectic silicon structure, the influence of Sr on the formation of Fe-intermetallic phases remains unclear. The present work investigates the combined additions of Sr and Mn to Al–9Si–0.6Fe–0.35Mg (All compositions are in wt pct except otherwise stated.) alloys on the formation of Fe-intermetallic phases at different solidification rates from ~ 1.5 to ~ 60 °C/s. Long and branched-type AlFeSi phase with size ranging from 50 to 120 µm are more common when solidified at the rate of 1.5 °C/s regardless of Sr and Mn additions. However, at the fast solidification rate of 60 °C/s, a 60 ppm Sr addition significantly reduced the average length of needle-shaped AlFeSi phase to less than 3 to 5 µm. Thermodynamic simulations have been performed using CALculation of PHAse Diagrams (CALPHAD) models to predict the formation of various phases and their possible interactions during solidification. The results indicated that the combination of a high solidification rate and about 60 ppm of Sr is beneficial to refining the δ-Al 3 FeSi 2 phase in Al–Si–Mg alloys containing 0.6 pctFe. As a result, this unexpected finding of Fe-intermetallic refinement by low Sr addition (~60 ppm) provides an important guide in designing secondary alloys for sustainable casting applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

The hyperplane of early-type galaxies: using stellar population properties to increase the precision and accuracy of the fundamental plane as a distance indicator

ABSTRACT We use deep spectroscopy from the SAMI (Sydney-AAO Multi-object Integral) Galaxy Survey to explore the precision of the fundamental plane (FP) of early-type galaxies as a distance indicator for future single-fibre spectroscopy surveys. We study the optimal trade-off between sample size and signal-to-noise ratio (SNR), and investigate which additional observables can be used to construct hyperplanes with smaller intrinsic scatter than the FP. We add increasing levels of random noise (parametrized as effective exposure time) to the SAMI spectra to study the effect of increasing measurement uncertainties on the FP- and hyperplane-inferred distances. We find that, using direct-fit methods, the values of the FP and hyperplane best-fitting coefficients depend on the spectral SNR, and reach asymptotic values for a mean $\langle \mathrm{ SNR} \rangle =40\, \mathrm{\mathring{\rm A}}^{-1}$. As additional variables for the FP we consider three stellar-population observables: light-weighted age, stellar mass-to-light ratio, and a novel combination of Lick indices ($I_\mathrm{age}$). For an $\langle \mathrm{ SNR} \rangle =45~\mathrm{\mathring{\rm A}}^{-1}$ (equivalent to 1-h exposure on a 4-m telescope), all three hyperplanes outperform the FP as distance indicators. Being an empirical spectral index, $I_\mathrm{age}$ avoids the model-dependent uncertainties and bias underlying age and mass-to-light ratio measurements, yet yields a 10 per cent reduction of the median distance uncertainty compared to the FP. We also find that, as a by-product, the $I_\mathrm{age}$ hyperplane removes most of the reported environment bias of the FP. After accounting for the different SNR, these conclusions also apply to a 50 times larger sample from SDSS-III (Sloan Digital Sky Survey). However, in this case, only $\mathrm{ age}$ removes the environment bias.

D’Eugenio, Francesco (ORCID:0000000323888172)↗
DOE OSTI2021

Tower-Based Remote Sensing Reveals Mechanisms Behind a Two-phased Spring Transition in a Mixed-Species Boreal Forest

The boreal forest is a major contributor to the global climate system, therefore, reducing uncertainties in how the forest will respond to a changing climate is critical. One source of uncertainty is the timing and drivers of the spring transition. Remote sensing can provide important information on this transition, but persistent foliage greenness, seasonal snow cover, and a high prevalence of mixed forest stands (both deciduous and evergreen species) complicate interpretation of these signals. We collected tower-based remotely sensed data (reflectance-based vegetation indices and Solar-Induced Chlorophyll Fluorescence [SIF]), stem radius measurements, gross primary productivity, and environmental conditions in a boreal mixed forest stand. Evaluation of this data set shows a two-phased spring transition. The first phase is the reactivation of photosynthesis and transpiration in evergreens, marked by an increase in relative SIF, and is triggered by thawed stems, warm air temperatures, and increased available soil moisture. The second phase is a reduction in bulk photoprotective pigments in evergreens, marked by an increase in the Chlorophyll-Carotenoid Index. Deciduous leaf-out occurs during this phase, marked by an increase in all remotely sensed metrics. The second phase is controlled by soil thaw. Our results demonstrate that remote sensing metrics can be used to detect specific physiological changes in boreal tree species during the spring transition. The two-phased transition explains inconsistencies in remote sensing estimates of the timing and drivers of spring recovery. Our results imply that satellite-based observations will improve by using a combination of vegetation indices and SIF, along with species distribution information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Enzymatic depolymerization of polyester: Foaming as a pretreatment to increase specific surface area

Abstract Poly(ethylene terephthalate) (PET) is widely used for its high strength‐to‐weight ratio, gas barrier properties, and chemical resistance. The growing PET use highlights the demand for a better recycling system. Enzymatic recycling, alongside mechanical and chemical methods, is eco‐friendly and yields properties similar to virgin PET. Substrate properties ( T g , crystallinity, and specific surface area [SSA]) and enzyme stability significantly impact conversion efficiency. Higher SSA and lower crystallinity tend to yield improved depolymerization when employing leaf compost‐cutinase (LCC‐ICCG) enzymes. This study explored melt extrusion and foaming as pretreatment techniques to modify PET structural properties, using a low‐cost chemical foaming agent (CFA). The monomer conversion rate and efficiency during depolymerization were measured and related to the processing, extrudate micro‐ and meso‐structure, and polyester type. Pretreated PET substrates showed reduced T g , crystallinity, density, and enhanced SSA, resulting in a 90% mass loss for foamed RPET and VPET substrates within 2 days. In contrast, PET with ~30% of cyclohexanedimethanol comonomer exhibited a nearly 50% lower depolymerization rate, with zero BHET production. It indicates that the combination of low crystallinity, low T g , and high SSA leads to improved monomer conversion. These findings emphasize the significance of amorphization and foaming in enhancing PET enzymatic depolymerization.

42 ENGINEERING↗
DOE OSTI2022

Modelica-based modeling and simulation of district cooling systems: A case study

While equation-based object-oriented modeling language Modelica can evaluate practical energy improvements for district cooling systems, few have adopted Modelica for this type of large-scale thermo-fluid system. Further, to our best knowledge, district cooling modeling studies have yet to include hydraulics in piping networks alongside plant models featuring realistic mechanical systems and controls. These are critical details to include when looking to make energy and control improvements in many physical system installations. To fill these gaps, this study released new open-source district cooling models at the Modelica Buildings Library and leveraged these models for a real-world case study at the University of Colorado Boulder. Here, the site includes six buildings connected to a central chiller plant featuring a waterside economizer. Several energy saving strategies are pursued based on the validated model, including control setpoint optimization, equipment modification, and pump setpoint adjustments. Results indicate that a combination of the studied measures can save the campus annually 84.6 MWh of energy, 8.9% of electricity costs, 58.0 metric tons of carbon dioxide emissions, while the waterside economizer cuts down chillers’ run times by 201 days/year, reducing maintenance costs and extending chiller life.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

On the viability of stimulated hydrogen generation from iron-rich formations

Hydrogen-based technologies present a promising solution for the global energy transition. In addition to electrolytic production, subsurface geological formations provide a potential natural source of hydrogen. Iron-rich ultramafic rocks, in particular, are favorable for hydrogen generation through natural processes such as serpentinization. Naturally occurring reactions and migration can be enhanced through various types of stimulation, including thermal, hydraulic, and chemical treatment. Through numerical simulations, we analyzed the complex interplay of factors influencing the production and migration within the subsurface, emphasizing the importance of different stimulation techniques, catalysts, and conditions. Our findings indicate that key parameters, such as damage zone permeability and width, significantly impact producible hydrogen mass. Our results indicate that a combination of large damage zone widths, high permeability, and a stimulated reaction rate of 1 × 10 -9 can yield economically viable production rates of up to 1 kg s -1 at the wellhead. Moreover, the availability of ferrous iron, rather than the serpentinization rate itself, has been identified as the primary limiting factor in achieving economically sustainable hydrogen production. In conclusion, while an unstimulated rock volume of 0.165 km 3 yields only 45t of hydrogen in two years, various stimulation techniques can increase production to 18500t.

08 - HYDROGEN↗
DOE OSTI2025

Development and application of two-step uncertainty propagation and sensitivity analysis methodology for fast reactor safety analysis

Uncertainty quantification (UQ) in nuclear reactors for transients is directly linked with safety assessment through the cross-sections uncertainties, provided as a covariance matrix, which are propagated through the reactor system to output of interest pertaining to reactor safety, such as peak temperatures in fuel/clad/coolant. Using a two-step approach, uncertainties are first quantified and propagated from basic input variables (such as reaction cross-sections) to intermediate quantities (such as reactivity feedback coefficients) through lattice level calculations. Uncertainties of intermediate quantities (from the first step) are then propagated through the system transient calculations, in the second step, to obtain uncertainties on reactor safety output parameters of interest. The scope of this work consists of Uncertainty Quantification & Propagation of nuclear data uncertainties that are highly correlated through unprotected transient overpower and unprotected loss of flow to assess their impact on core safety parameters. This two-step approach in the presence of covariance renders the sensitivity analysis very challenging. In fact, usually the sensitivity analysis is restricted to each step, which limits its application since the sensitivities between the system output quantities and the basic input variables are difficult to obtain. Here, in this work, we address this issue by proposing a simple, general methodology to combine the sensitivity indices obtained in each step by assuming the model behavior being linear. For the first step Generalized Perturbation theory based indices are used while in the second step the recently studied Johnson indices. The uncertainty quantification and sensitivity methodologies discussed here are demonstrated on a generic LFR design which is based on the 500 MWth demonstration Lead-cooled fast reactor (DLFR) using oxide fuel, developed by Westinghouse Electric Company (WEC).

42 - ENGINEERING↗
DOE OSTI2020

Molecular Orientation for Vapor-Deposited Organic Glasses Follows Rate-Temperature Superposition: The Case of Posaconazole

The anisotropic properties of organic glasses produced by physical vapor deposition (PVD) depend upon substrate temperature and deposition rate. In recent work, it was shown for a liquid crystalline system that the anisotropic structure of the glass was controlled by a single combined variable as indicated by the observation of deposition rate-substrate temperature superposition (RTS). Here we test the utility of RTS for posaconazole, a molecule that does not form liquid crystals. We prepare glasses of posaconazole utilizing a range of deposition rates covering 2 orders of magnitude and an 18 K range in substrate temperature. We characterize the glasses using ellipsometry and X-ray scattering. Consistent with RTS, we find that decreasing the deposition rate has the same effect upon molecular orientation as increasing the substrate temperature during deposition. Thus, RTS can be used to predict and control the structure of glasses prepared at a wide range of deposition conditions. We use RTS to infer a characteristic time for molecular reorientation at the surface of posaconazole.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Medium Energy Electron Flux in Earth's Outer Radiation Belt (MERLIN): A Machine Learning Model

The radiation belts of the Earth, filled with energetic electrons, comprise complex and dynamic systems that pose a significant threat to satellite operation. While various models of electron flux both for low and relativistic energies have been developed, the behavior of medium energy (120–600 keV) electrons, especially in the MEO region, remains poorly quantified. At these energies, electrons are driven by both convective and diffusive transport, and their prediction usually requires sophisticated 4D modeling codes. In this paper, we present an alternative approach using the Light Gradient Boosting (LightGBM) machine learning algorithm. The Medium Energy electRon fLux In Earth's outer radiatioN belt (MERLIN) model takes as input the satellite position, a combination of geomagnetic indices and solar wind parameters including the time history of velocity, and does not use persistence. MERLIN is trained on >15 years of the GPS electron flux data and tested on more than 1.5 years of measurements. Tenfold cross validation yields that the model predicts the MEO radiation environment well, both in terms of dynamics and amplitudes o f flux. Evaluation on the test set shows high correlation between the predicted and observed electron flux (0.8) and low values of absolute error. The MERLIN model can have wide space weather applications, providing information for the scientific community in the form of radiation belts reconstructions, as well as industry for satellite mission design, nowcast of the MEO environment, and surface charging analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Observational Constraints on the Spatial Effect of Greenness and Canopy Cover on Urban Heat in a Major Midlatitude City

Abstract Urban heat stress is a critical issue, particularly in cities where dense infrastructure and limited green space exacerbate temperature extremes. This study investigates the impact of greenery (EVI2), canopy cover (CC), impervious cover (IC), and water bodies on heat index in Chicago using high‐resolution data from the Heat Watch campaign. We find that EVI2, CC and proximity to water body significantly reduce heat while IC increases heat, particularly in the afternoon when solar radiation is intense. Additionally, the effective radius that land cover impacts heat is smaller in the afternoon. The combined effect analysis indicates that enhancing total greenness, not just canopy cover, is the most effective strategy to reduce heat. This study underscores the importance of strategic vegetation management, highlighting the critical role of integrated approaches in reducing urban heat.

Lee, Jangho↗
DOE OSTI2023

Spin–vibronic coherence drives singlet–triplet conversion

Design-specific control over the transitions between excited electronic states with different spin multiplicities is of the utmost importance in molecular and materials chemistry. Previous studies have indicated that the combination of spin-orbit and vibronic effects, collectively termed the spin-vibronic effect, can accelerate quantum-mechanically forbidden transitions at non-adiabatic crossings. However, it has been difficult to identify precise experimental manifestations of the spin-vibronic mechanism. Here we present coherence spectroscopy experiments that reveal the interplay between the spin, electronic and vibrational degrees of freedom that drive efficient singlet-triplet conversion in four structurally related dinuclear Pt(II) metal-metal-to-ligand charge-transfer (MMLCT) complexes. Photoexcitation activates the formation of a Pt-Pt bond, launching a stretching vibrational wavepacket. The molecular-structure-dependent decoherence and recoherence dynamics of this wavepacket resolve the spin-vibronic mechanism. Further, we find that vectorial motion along the Pt-Pt stretching coordinates tunes the singlet and intermediate-state energy gap irreversibly towards the conical intersection and subsequently drives formation of the lowest stable triplet state in a ratcheting fashion. This work demonstrates the viability of using vibronic coherences as probes to clarify the interplay among spin, electronic and nuclear dynamics in spin-conversion processes, and this could inspire new modular designs to tailor the properties of excited states.

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

Identification of a nematic pair density wave state in Bi 2 Sr 2 CaCu 2 O 8+x

Electron-pair density wave (PDW) states are now an intense focus of research in the field of cuprate correlated superconductivity. PDWs exhibit periodically modulating superconductive electron pairing that can be visualized directly using scanned Josephson tunneling microscopy (SJTM). Although from theory, intertwining the d-wave superconducting (DSC) and PDW order parameters allows a plethora of global electron-pair orders to appear, which one actually occurs in the various cuprates is unknown. In this work, we use SJTM to visualize the interplay of PDW and DSC states in Bi 2 Sr 2 CaCu 2 O 8+x at a carrier density where the charge density wave modulations are virtually nonexistent. Simultaneous visualization of their amplitudes reveals that the intertwined PDW and DSC are mutually attractive states. Then, by separately imaging the electron-pair density modulations of the two orthogonal PDWs, we discover a robust nematic PDW state. Its spatial arrangement entails Ising domains of opposite nematicity, each consisting primarily of unidirectional and lattice commensurate electron-pair density modulations. Further, we demonstrate by direct imaging that the scattering resonances identifying Zn impurity atom sites occur predominantly within boundaries between these domains. This implies that the nematic PDW state is pinned by Zn atoms, as was recently proposed [Lozano et al., Phys. Rev. B 103, L020502 (2021)]. Taken in combination, these data indicate that the PDW in Bi 2 Sr 2 CaCu 2 O 8+x is a vestigial nematic pair density wave state [Agterberg et al. Phys. Rev. B 91, 054502 (2015); Wardh and Granath arXiv:2203.08250].

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors

ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.

Zazzera, Stefano (ORCID:0000000158979221)↗
DOE OSTI2023

Zero-point motion of liquid and solid hydrogen

We present an inelastic neutron scattering study of liquid and solid hydrogen carried out using the wide Angular Range Chopper Spectrometer at Oak Ridge National Laboratory. From the observed dynamic structure factor, we obtained empirical estimates of the molecular mean-squared displacement and average translational kinetic energy. Here we find that the former quantity increases with temperature, indicating that a combination of thermal and quantum effects is important near the liquid-solid phase transition, contrary to previous measurements. We also find that the kinetic energy drops dramatically on melting of the crystals, a consequence of the large increase in molar volume together with the Heisenberg indeterminacy principle. Our results are compared with quantum Monte Carlo simulations based on different model potentials. In general, there is good agreement between our findings and theoretical predictions based on the Silvera-Goldman and Buck potentials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

DCFC + Hydrogen Station Design Optimization [Slides]

Both direct current fast charging (DCFC) and Hydrogen stations are working to create successful long-term business models; however, analyses for DCFC and hydrogen fueling infrastructure are almost always performed separately. This work provides a detailed exploration of the benefit of integrating DCFC and hydrogen stations to lower the total system cost from load balancing and equipment cost sharing. To achieve this we have adapted the REopt optimization framework to simultaneously optimize the design and operation of integrated DCFC and H2 fueling station. Results indicate that 1) combining hydrogen fueling and DCFC stations can significantly reduce lifetime costs compared to separated stations. 2) Co-location with additional site load reduces DCFC costs, however, integration of DCFC with hydrogen provides an even greater cost reduction. 3) Adding PV to combined stations further reduces the lifetime station cost. 4) Capital investments in station combination today can help reduce the cost of operating DCFC tomorrow and 5) product diversification acts as a hedge against variability and enables a more dynamic response to market changes.

08 HYDROGEN↗