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At least 235 records · Page 13

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator (Third Quarter 2021)

The U.S. Department of Energy's Alternative Fueling Station Locator contains information on public and private nonresidential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the third calendar quarter of 2021 (Q3). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape for EV charging. This is the seventh report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: Fourth Quarter 2021

The U.S. Department of Energy's Alternative Fueling Station Locator contains information on public and private nonresidential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the fourth calendar quarter of 2021 (Q4). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape for EV charging. This is the eighth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator: First Q2022

The U.S. Department of Energy's Alternative Fueling Station Locator contains information on public and private nonresidential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the first calendar quarter of 2022 (Q1). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the ninth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator (Second Quarter 2022)

The U.S. Department of Energy's Alternative Fueling Station Locator contains information on public and private nonresidential alternative fueling stations in the United States and Canada and currently tracks ethanol (E85), biodiesel, compressed natural gas, electric vehicle (EV) charging, hydrogen, liquefied natural gas, and propane stations. Of these fuels, EV charging continues to experience rapidly changing technology and growing infrastructure. This report provides a snapshot of the state of EV charging infrastructure in the United States in the second calendar quarter of 2022 (Q2). Using data from the Station Locator, this report breaks down the growth of public and private charging infrastructure by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared with two different 2030 infrastructure requirement scenarios. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the tenth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and National Renewable Energy Laboratory (NREL) publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗

Marco… Polo, Collecting location data 78 times in 28 days

We report the results of a survey test conducted in advance of a series of community response tests (CRTs) to evaluate response to noise from NASA’s X-59 aircraft. The CRTs will require a substantial number of observations to generate a dose response curve for noise exposure and related annoyance levels and the timeframe is limited due to resource and scheduling constraints with an experimental aircraft. Respondents will be asked to fill out the surveys either on the web or as part of an application they are able to download onto their mobile phones. Respondents will be asked to fill out a survey each time the plane flies over the targeted area. The sample will be drawn targeting households within a specific ‘fly-over’ area. However, respondents may travel during the day, sometimes outside the targeted area. For the observations to be useful respondents need to be within a target area during flights. To collect the location data, respondents will be asked to identify where they were at the time of the flyover. The survey test followed the proposed methodology of the CRTs. We will describe how location data was collected using Google Maps API and evaluate reported rates of location at home, work or other places and whether these were inside or outside the target area. We will also compare how these rates varied across web and app respondents. We will use the results of this work to confirm or improve the design of the CRTs, ensuring the collection of data needed by NASA to evaluate the impact of this innovative technology.

Google Maps↗

EVI-LOCATE: One Stop Solution for Estimating Cost of Installing EV Charging Stations

EVI-LOCATE (Electric Vehicle Infrastructure-Locally Optimized Cost Assessment Tool and Estimator) is a site assessment tool to estimate costs to install EV charging stations. EVI-LOCATE enables users to generate site-specific, user-specific, and location-specific EV charging station installation designs and cost estimates. The tool integrates National Electrical Code, deep-learning pixel classification algorithm, and component-level costs to estimate the costs.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Deep Learning Accelerated Determination of Hydride Locations in Metal Nanoclusters

Abstract Although the coordinates of the metal atoms can be accurately determined by X‐ray crystallography, locations of hydrides in metal nanoclusters are challenging to determine. In principle, neutron crystallography can be employed to pinpoint the hydride positions, but it requires a large crystal and a neutron source, which prevents its routine use. Here, we present a deep‐learning approach that can accelerate determination of hydride locations in single‐crystal X‐ray structure of metal nanoclusters of different sizes. We demonstrate the efficiency of our method in predicting the most probable hydride sites and their combinations to determine the total structure for two recently reported copper nanoclusters, [Cu 25 H 10 (SPhCl 2 ) 18 ] 3− and [Cu 61 (S t Bu) 26 S 6 Cl 6 H 14 ] + whose hydride locations have not been determined by neutron diffraction. Our method can be generalized and applied to other metal systems, thereby eliminating a bottleneck in atomically precise metal hydride nanochemistry.

Wang, Song↗

Deep Learning Accelerated Determination of Hydride Locations in Metal Nanoclusters

Although the coordinates of the metal atoms can be accurately determined by X-ray crystallography, locations of hydrides in metal nanoclusters are challenging to determine. In principle, neutron crystallography can be employed to pinpoint the hydride positions, but it requires a large crystal and a neutron source, which prevents its routine use. Here, we present a deep-learning approach that can accelerate determination of hydride locations in single-crystal X-ray structure of metal nanoclusters of different sizes. We demonstrate the efficiency of our method in predicting the most probable hydride sites and their combinations to determine the total structure for two recently reported copper nanoclusters, [Cu 25 H 10 (SPhCl 2 ) 18 ] 3- and [Cu 61 (S t Bu) 26 S 6 Cl 6 H 14 ] + whose hydride locations have not been determined by neutron diffraction. Our method can be generalized and applied to other metal systems, thereby eliminating a bottleneck in atomically precise metal hydride nanochemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A phased workflow to define permit‐ready locations for large volume CO 2 injection and storage

Abstract To‐date, only two UIC Class VI permits have been issued by the US Environmental Protection Agency. We illustrate a four‐phase workflow to first identify regional storage resources and then down‐select sites to yield permit‐ready locations that can accept and store large volumes of CO 2 . Specific permit requirements should guide objectives and define deliverables of respective workflow phases. In the first phase we used available regional data and screened structure and injection zones to locate resources that match CO 2 volumes planned to be captured. Available data were also used to assess presence and depth of usable groundwater, the key resource being protected via permitting. We then used advanced, closed‐form, analytical solutions (EASiTool) to estimate CO 2 injectivity into each hydrologically connected injection compartment. In the second phase we acquired and conditioned additional wireline logs and leased available seismic datasets. We interpreted the depositional systems from wireline well‐log character and mapped sandbody geometry to interpolate injection and confining‐zone distribution. Using available data, we mapped faults and locations of freshwater and overpressure (or other capacity‐limiting geologic parameters) in more detail. In the third phase, we used the augmented geologic data to develop a static model for the selected area, extracted the areas of highest interest, and generated and ran dynamic (flow) models. In a fourth phase, we reduced major uncertainties identified in earlier phases. Our case study indicates that to complete preparation of a permit application requires (1) improved lithologic characterization information (thicknesses and horizontal and vertical connectivity) and (2) better definition of poorly defined local faults. © 2023 The Authors. Greenhouse Gases: Science and Technology published by Society of Chemical Industry and John Wiley & Sons Ltd.

58 GEOSCIENCES↗

Effects of stereoisomeric structure and bond location on the ignition and reaction pathways of hexenes

The current work presents new experimental autoignition and speciation data on the two cis-hexene isomers: cis-2-hexene and cis-3-hexene. The new data provide insights on the effects of carbon-carbon double bond location and stereoisomeric structures on ignition delay times and reaction pathways for linear hexene isomers. Experiments were performed using the University of Michigan rapid compression facility to determine ignition delay times from pressure-time histories. Stoichiometric (Φ = 1.0) mixtures at dilution levels of inert gas to O 2 = 7.5:1 (mole basis) were investigated at an average pressure of 11 atm and temperatures from 809 to 1052 K. Speciation experiments were conducted at T = 900 K for the two cis-hexene isomers, where fast-gas sampling and gas chromatography were used to identify and quantify the two cis-hexene isomers and stable intermediate species. The ignition delay time data showed negligible sensitivity to the location of the carbon-carbon double bond and the stereoisomeric structure (cis-trans), and the species data showed no correlation with the stereoisomeric structure, but there was a strong correlation of some of the measured species with the location of the double bond in the hexene isomer. In particular, 2-hexene showed strong selectivity to propene, acetaldehyde, and 1,3-butadiene, and 3-hexene showed selectivity to propanal. Model predictions of ignition delay times were in excellent agreement with the experimental data. Furthermore, there was generally good agreement for the model predictions of the species data for 2-hexene; however, the mechanism overpredicted some of the small aldehyde (C 2 -C 4 ) species for 3-hexene. Reaction pathway analysis indicates the hexenes are almost exclusively consumed by H-atom abstraction reactions at the conditions studied (P = 11 atm, T > 900 K), and not by C 3 -C 4 scission as observed in high-temperature (>1300 K) hexene ignition studies. Improved estimates for 3-hexene + OH reactions may improve model predictions for the species measured in this work.

42 ENGINEERING↗

Long-term impact of electrification and retrofits of the U.S residential building in diverse locations

The U.S. buildings sector contributes 30% of operational carbon emissions, with residential buildings accounting for 56%. Reducing residential carbon emissions is crucial for achieving net-zero carbon goal. While many studies examine energy efficiency retrofit (EER) and electrification, few explore their long-term impacts across diverse climates and dynamic grid clean energy penetrations, as well as their economic effects on households. Here, this study proposes a method to assess how EER and electrification affect long-term decarbonization and economics across different climates, focusing on carbon emissions, energy burden (the percentage of household income spent on energy), and payback period in four locations: Tampa, San Diego, Denver, and Great Falls. The study also introduces the concept of implicit energy burden by considering investment costs. Results show that while electrification can reduce long-term emissions with increased clean energy penetration, it may not always achieve decarbonization due to mismatches between clean energy availability and demand. In cooling-dominant locations, electrification lowers energy burden and peak demand, but in heating-dominant locations, it increases energy burden to 8.24%, raises peak demand by 632.78%, and shifts it from summer to winter. After integrating investment costs, the implicit energy burden can reach 8.35% in cold climates. For already highly electrified buildings in Denver and Great Falls, the payback period of EER measures can be shortened by up to 48.98%. The study highlights a tradeoff between decarbonization and energy burden alleviation, showing that while EER measures can reduce the energy burden, they only achieve one-quarter of the carbon emission reduction of electrification.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Optimization of the number and locations of the calibration stations needed to monitor soil moisture using distributed temperature sensing systems: A proof-of-concept study

The single-probe heat-pulse (SPHP) technique combined with the Fiber-optic Distributed Temperature Sensing (DTS) technology can offer novel high-resolution measurements of soil moisture (θ) over spatial scales ranging from several centimeters to several kilometers. However, the key limitation of this method is in obtaining the calibration relationship between θ and soil thermal conductivity (λ) across a specific field. In a previous study, a new methodology using a Gaussian processes model was presented to account for the spatial variability in the λ-θ relationship. The model aggregated θ measurements from soil moisture sensors scattered over the SPHP transect with the corresponding DTS λ measurements at their locations. In this study, a novel methodology is tested to optimize the number and locations of soil moisture sensors required to account for the spatial variability of the λ - θ relationship to achieve higher accuracy from the SPHP technique. The proposed methodology utilizes hierarchical clustering to analyze the information contained in the spatial structure of the SPHP measurements as the soil dries from a nearly-saturated condition. The proposed methodology was tested using data from a field in Oklahoma. Monte-Carlo simulation was performed to validate the performance of the proposed methodology. The predictions obtained from the proposed methodology resulted in θ measurements accuracy comparable to those obtained from the 10% best Monte-Carlo iterations of randomly assigned soil moisture locations. Further, this study demonstrates that the proposed methodology is more efficient than the traditional practice of randomly spreading calibration soil moisture sensors along the SPHP transect.

54 ENVIRONMENTAL SCIENCES↗

Aperture size distribution, length, and preferential location of bed-parallel veins in shale

Bed-parallel, calcite-filled veins (BPVs) are common in shale formations, and although they have been widely described in other studies, little is known about their population aperture size distribution. To address this knowledge gap, we analyzed BPV sizes in outcrops and cores from the Vaca Muerta Formation, Neuquén Basin, Argentina; in two cores from the Marcellus Formation, Appalachian Basin, northeast Pennsylvania; and in one core from the Wolfcamp Shale, Delaware Basin, West Texas. Nine out of ten aperture size populations follow a negative exponential distribution, with one following a weak power law. Bed-parallel vein size distribution and intensity vary among formations and within the same shale. We define three groups of distributions: (1) Vaca Muerta outcrops, with the highest BPV intensity and the largest BPVs (cumulative frequency of 4.9 BPVs per meter [BPVs/m] for apertures 0.265 mm to 8.7 cm); (2) Vaca Muerta cores with a similar BPV intensity overall but with no apertures wider than 1.2 cm; and (3) Vaca Muerta, Wolfcamp, and Marcellus cores with the fewest BPVs (cumulative frequency up to 0.63 BPVs/m) and very few wider than 1 cm. Aperture and length in two outcrop data sets are weakly positively correlated and follow power laws with exponents of 0.44 and 0.49. Mechanical interfaces at boundaries between different lithologies exert a strong control on BPV location, with 65–75% of observed interfaces having BPVs along them. Only 25–30% of the BPVs occur at observed material interfaces, however, and unless subtle, unobserved mechanical layering is present, other factors must also control location. BPV intensity and organic richness (TOC) from Vaca Muerta well logs are correlated in some instances but not in others, indicating TOC is not always a good proxy for BPV location or intensity. Furthermore, these findings provide useful information for modeling of hydraulic fracture treatments where BPVs may influence development of the stimulated fracture network, for example by limiting height growth.

58 GEOSCIENCES↗

Estimating Permafrost Distribution Using Co‐Located Temperature and Electrical Resistivity Measurements

Abstract Assessing the lateral and vertical extent of permafrost is critical to understanding the fate of Arctic ecosystems under climate change. Yet, direct measurements of permafrost distribution and temperature are often limited to a small number of borehole locations. Here, we assess the use of co‐located shallow temperature and electrical resistivity tomography (ERT) measurements to estimate at high‐resolution the distribution of permafrost in three watersheds underlain by discontinuous permafrost. Synthetic modeling shows that co‐located temperature and ERT measurements allow for supervised classification schemes that provide 60% higher accuracy compared to unsupervised methods. Linking resistivity and size of the identified permafrost bodies to surface observations, we show that tall vegetation (>0.5 m) and gentle slopes (<15°) are related to warmer and smaller permafrost bodies, and a more frequent occurrence of taliks.

54 ENVIRONMENTAL SCIENCES↗

Travelling wave‐based fault detection and location in a real low‐voltage DC microgrid

Abstract This paper discusses a device‐level implementation of a travelling wave (TW) protection device (PD) designed for a real low‐voltage DC microgrid. The TWPD fault detection and location algorithm is executed on a commercial digital signal processor (DSP) board, involving signal sampling at 1 MHz via the DSP board's analog‐to‐digital converter (ADC). The analogue input card measures positive pole, negative pole and pole‐to‐pole voltages at the TWPD location. Upon a successful fault detection using a second‐order high‐pass filter, the voltage data is normalised and multi‐resolution analysis (MRA) is performed on a 128‐sample buffer around the TW arrival time. MRA employs the discrete wavelet transform (DWT) to capture high‐frequency voltage patterns, and then the Parseval's energy theorem quantifies these TW characteristics by computing the energy of reconstructed wavelet coefficients. These energy values per decomposed frequency band are the basis for training a random forest classifier that predicts fault location and type. The TWPD is fully implemented and connected to a real DC microgrid in Albuquerque, NM, USA, for validation, and results are shown for field tests verifying the performance under faults.

Paruthiyil, Sajay Krishnan [Department of Electric↗

A Customizable Metric to Provide a Comprehensive Picture of the Mobility Potential of a Location

Accessibility in a geo-spatial context refers to the ease of reaching a variety of opportunities from a given location. Accessibility theories (and resulting metrics) have traditionally focused on quantifying access to specific opportunities (such as jobs), or focused on specific modes (such as car, bike, etc.). Such approaches often fall short of providing a comprehensive picture of the true accessibility potential of a location as a combination of multiple modes to multiple types of destinations. Addressing this drawback, a novel metric labeled the ‘Mobility Energy Productivity (MEP) Metric’ was developed at the National Renewable Energy Laboratory to quantify the mobility potential of a location to connect people to goods, services, and employment using a variety of modes, while accounting for time, energy, and affordability. The MEP metric has been integrated with advance travel behavior models to compute the changes in mobility potential for various future scenarios, such as introduction of automated vehicles, and/or electric vehicles—but does so at the aggregate, or average-citizen level. The MEP in its initial iteration is not customized to the particular socio-economic contingents, or even to an individual whose modal availability or pattern of trip making may substantially differ from the average. Addressing this gap, this research effort extends the MEP framework from a static state to a more tailored and dynamic state, one in which an individual, or group can customize the metric for their unique characteristics, such as modes, activity patterns, and time-of-day preferences. The extended MEP metric framework can now be integrated to assess the customized mobility energy productivity of an individual.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

Impact of ionization peak location on measured opaqueness in DIII-D H-mode plasmas

This study investigates the relationship between electron pedestal density and the location of the ionization peak on neutral penetration in DIII-D H-mode plasmas, utilizing a database of Lyman-α emission measurements. The high electron density leads to neutrals being ‘screened’ and the ionization front being pushed out into the Scrape-Off Layer (SOL). This is also referred to as the neutral opaqueness, which is heuristically expected to scale with edge plasma density and machine size. However, at lower electron pedestal density, the penetration depth of the neutrals varies, and measured opaqueness deviates from the heuristic scaling. The database reveals that at low density, when the ionization peak is located in SOL region, the linear relationship between the electron density and neutral penetration holds. However, when the peak is located inside the separatrix, the penetration of the neutrals (λ n 0 ) is much wider ~3.0–3.5 cm, breaking the heuristic opaqueness approximation. These findings provide valuable insights into fueling efficiency and plasma behavior, with implications for Fusion Pilot Plants where high pedestal densities are anticipated and where the neutral opaqueness behaves like its heuristic approximation. This analysis offers a framework to refine neutral opaqueness approximations, enhancing the predictive capability for advanced tokamak operations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Locating the QCD critical point through contours of constant entropy density

We propose a new method to investigate the existence and location of the conjectured high-temperature critical point of strongly interacting matter via contours of constant entropy density. By approximating these lines as a power series in the baryon chemical potential 𝜇 𝐵 , one can extrapolate them from first-principle results at zero net-baryon density, and use them to locate the quantum chromodynamics (QCD) critical point, including the associated first-order and spinodal lines. As a proof of principle, we employ currently available continuum-extrapolated lattice data from the Wuppertal-Budapest collaboration to find a critical point at a temperature and a baryon chemical potential of 𝑇 𝑐 = 114.3 ± 6.9 MeV and 𝜇 𝐵,𝑐 = 602.1 ± 62.1 MeV, respectively, at expansion order 𝒪⁡(𝜇$^{2}_{𝐵}$). We advocate for a more precise determination of the required expansion coefficients via lattice QCD simulations as a means of pinpointing the location of the critical endpoint in the phase diagram of strongly interacting matter.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗