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At least 91 records · Page 5

High Magnetic Anisotropy and Magnetocaloric Effects in Single-Crystal Cr 2 Te 3

Here, we report a systematic investigation of anisotropic magnetocaloric effects in single-crystal Cr 2 Te 3 . Single-crystal samples are synthesized by chemical vapor transport and characterized by X-ray and Laue diffraction methods. The maximum magnetic entropy change –ΔS M max is 4.50 J kg –1 K –1 for the easy c-axis (3.36 J kg –1 K –1 for the hard axis along ab-plane), and the relative cooling power (RCP) is 296.7 J kg –1 for the easy c-axis (183.84 J kg –1 for the hard axis along ab-plane) for a magnetic field change of 9 T near the Curie temperature. The magneto-crystalline anisotropy constant K u is estimated to be 580.12 kJ m –3 at 140 K, decreasing to 148.60 kJ m –3 at 168 K. Meanwhile, the maximum of the rotational magnetic entropy change –ΔS M R (T, H) between the c-axis and the ab-plane is about 1.14 J kg –1 K –1 for magnetic-field change of 9 T. The critical exponents are estimated by analyzing magnetocaloric effects, which indicate a 2D-Ising type magnetic system. The accuracy of estimated critical exponents is verified by scaling analysis. The maximum magnetic entropy change –ΔS M max ≈ 5.25 J kg –1 K –1 (along the c-axis) and the corresponding adiabatic temperature change ΔT ad ≈ 3.31 K (along the c-axis) are estimated by analyzing heat capacity measurements with a magnetic field up to 9 T.

36 MATERIALS SCIENCE↗

Long-Range Metal–Sorbent Interactions Determine CO 2 Capture and Conversion in Dual-Function Materials

Carbon capture and utilization involve multiple energy- and cost-intensive steps. Dual-function materials (DFMs) can reduce these demands by coupling CO 2 adsorption and conversion into a single material with two functionalities: a sorbent phase and a metal for catalytic CO 2 conversion. The role of metal catalysts in the conversion process seems salient from previous work, but the underlying mechanisms remain elusive and deserve deeper investigation to achieve maximum utilization of the two phases. Here, for this work, preformed colloidal Ru nanoparticles were deposited onto a “NaOx”/Al 2 O 3 sorbent to prepare prototypical DFMs with controlled phases for CO 2 capture and hydrogenation to CH 4 . Ru addition was found to double the high-temperature CO 2 adsorption capacity by activating the “NaOx”/Al 2 O 3 sorbent phase during a reductive pretreatment step. Most importantly, low Ru loadings were sufficient to ensure maximum CO 2 adsorption and conversion. This was attributed to the key role of the metal–sorbent interactions, wherein Ru was required to hydrogenate strongly bound CO 2 on the “NaO x ”/Al 2 O 3 sorbent to CH 4 via the H 2 activated on Ru. This interaction facilitated rate-determining carbonate migration and subsequent hydrogenation at the metal–sorbent interface. Overall, Ru controlled the CO 2 hydrogenation reaction rate, while the “NaO x ”/Al 2 O 3 sorbent dictated the CO 2 uptake capacity. By controlling metal–sorbent interactions at the molecular level, we demonstrate the critical role of the two phases and their synergy, facilitating the design of DFMs with maximum CO 2 capture and conversion efficiency.

carbon capture↗

The Role of Wind Speed in Prolonging Large Fire Durations in the Western US

Abstract The duration of large wildfires in the western US has increased significantly from 1992 to 2020 in the two fire seasons, by 0.76 days yr −1 in summer and 0.55 days yr −1 in fall. The factors driving the trend and variability were analyzed using multiple linear regression models. Our analysis identified the maximum daily wind speed during large fires, which has also increased during the study period, as the primary predictor for the large fire duration. Despite the observed rise in maximum wind speed specifically during large fires, there are no corresponding trends in the average daily mean wind speed throughout the fire seasons. The mechanisms underlying the increase in maximum wind speed during large fires remain unclear and warrant further investigation, as they may pose growing challenges for fire control.

54 ENVIRONMENTAL SCIENCES↗

Representing Soil Microbial Dynamics and Organo‐Mineral Interactions in the E3SM Land Model (ELM‐ReSOM)

Explicit representation of soil microbial processes and interactions with biotic and abiotic processes in Earth System Models (ESMs) remains limited, despite their importance in biogeochemical cycles. To address this gap, which hinders prediction of global biogeochemial cycling and responses to atmospheric conditions, we integrated a microbe- and mineral-surface-explicit model, the Reaction-network-based model of soil organic matter and Microbes (ReSOM), into the Energy Exascale ESM (E3SM) land model (ELM). Here, we describe ELM-ReSOM and show a case study at a conifer forest in California. ELM-ReSOM accurately simulated surface CO 2 fluxes and SOM stocks, demonstrating improved representations of microbial and mineral interactions compared to the default ELM. We examined ELM-ReSOM sensitivity to microbial traits, enzyme properties, and organo-mineral interactions. Microbial traits such as the maximum mortality rate, transporter-density scaling factor, and maximum monomer assimilation rate were strong controllers of heterotrophic respiration, while these microbial traits and enzyme-related properties collectively influenced SOM stocks. Mineral surfaces primarily affected SOM stocks by adsorbing enzymes, thereby limiting depolymerization. Synergies among processes led to stronger impacts of parameters when evaluated together versus separately (i.e., most parameters had greater indirect than direct effects). For example, due to interactions of microbial necromass with mineral surface adsorption, the indirect effect of the maximum microbial mortality rate was 33% larger than its direct effect on SOM stock. Thus, microbial and enzyme dynamics and their interactions with mineral surfaces play critical roles in SOM cycling. Tackling the challenges of microbe-explicit models will advance understanding and modeling of SOM dynamics.

Tao, Jing [Lawrence Berkeley National Laboratory (↗

Modeling strain and quantum confinement in GaAs/Ga x In 1−x P superlattices for spin-polarized electron sources

In this study, we systematically design and simulate a series of GaAs-based superlattice configurations aimed at enhancing heavy-hole–light-hole band splitting while simultaneously optimizing band alignment to reduce the conduction band barrier, thereby facilitating efficient electron transport. These combined effects are crucial for achieving high electron spin polarization and high quantum efficiency, the two key performance metrics of next-generation spin-polarized electron sources. We investigated three types of superlattice architectures: (1) compressively strained GaAs wells on GaInP barriers, yielding a maximum band splitting of 140 meV, (2) lattice-matched GaAs/GaInP structures, resulting in the maximum band splitting of 75 meV, and (3) tensile strained GaAs wells on GaInP barriers, with a maximum band splitting of 40 meV. The results demonstrate the tunability of heavy-hole–light-hole band splitting and establish a design framework for high-performance spin-polarized photocathodes based on a combination of strain engineering, quantum confinement, and optimized heterostructure design.

Electron sources↗

Estimating an executive summary of a time series: the tendency

In this paper, we revisit the problem of decomposing a signal into a tendency and a residual. The tendency describes an executive summary of a signal that encapsulates its notable characteristics while disregarding seemingly random, less interesting aspects. Building upon the Intrinsic Time Decomposition (ITD) and information-theoretical analysis, we introduce two alternative procedures for selecting the tendency from the ITD baselines. The first is based on the maximum extrema prominence, namely the maximum difference between extrema within each baseline. Specifically this method selects the tendency as the baseline from which an ITD step would produce the largest decline of the maximum prominence. The second method uses the rotations from the ITD and selects the tendency as the last baseline for which the associated rotation is statistically stationary. We delve into a comparative analysis of the information content and interpretability of the tendencies obtained by our proposed methods and those obtained through conventional low-pass filtering schemes, particularly the Hodrik–Prescott (HP) filter. Our findings underscore a fundamental distinction in the nature and interpretability of these tendencies, highlighting their context-dependent utility with emphasis in multi-scale signals. Through a series of real-world applications, we demonstrate the computational robustness and practical utility of our proposed tendencies, emphasizing their adaptability and relevance in diverse time series contexts.

Time series analysis↗

16 O + 16 O fusion at sub-coulomb energies

A simple optical model (OPM) method using non-monotonic (NM) potentials characterized by a repulsive core from the microscopic theory of the Pauli-led energy-density functional (EDF) has been developed to investigate the 16 O + 16 O fusion at sub-Coulomb energies relevant to the oxygen burning. Here, the study involves the analysis of the experimental fusion cross-section (FCS) data in energy range 6.92 ≤ E cm ≤ 13.83 MeV, which includes the Coulomb barrier region E cm = 10.0–11.92 MeV. Apart from an excellent description of the existing FCS data in the studied energy range, the associated hindrance, characterized by the S-factor reaching a maximum and then gradually falling off at lower energies, so far suggested empirically for the system, is reproduced down to 4 MeV for the first time in the simple OPM. An S-factor maximum of S 0 = 3.15 × 10 25 MeV.b at E 0 = 7.14 MeV is observed with T ≃ 2.6 GK, which conforms to the values reported for quiescent and explosive burning. Our reaction rate, deduced from the NM potential, compares well with the Caughlan and Fowler data. Dominant partial waves implicit in the observed maximum S-factor in the studied Gamow range are also explored. Our present findings, with the success of NM potentials, suggest that the nucleus–nucleus potential is non-monotonic.

16O+16O↗

SN 2021foa: the bridge between SN IIn and Ibn

ABSTRACT We present the long-term photometric and spectroscopic analysis of a transitioning SN IIn/Ibn from –10.8 d to 150.7 d post V-band maximum. SN 2021foa shows prominent He i lines comparable in strength to the H $\alpha$ line around peak, placing SN 2021foa between the SN IIn and SN Ibn populations. The spectral comparison shows that it resembles the SN IIn population at pre-maximum, becomes intermediate between SNe IIn/Ibn, and at post-maximum matches with SN IIn 1996al. The photometric evolution shows a precursor at –50 d and a light curve shoulder around 17 d. The peak luminosity and colour evolution of SN 2021foa are consistent with most SNe IIn and Ibn in our comparison sample. SN 2021foa shows the unique case of an SN IIn where the narrow P-Cygni in H $\alpha$ becomes prominent at 7.2 d. The H $\alpha$ profile consists of a narrow (500–1200 km s$^{-1}$) component, intermediate width (3000–8000 km s$^{-1}$) and broad component in absorption. Temporal evolution of the H $\alpha$ profile favours a disc-like CSM geometry. Hydrodynamical modelling of the light curve well reproduces a two-component CSM structure with different densities ($\rho \propto$ r$^{-2}$–$\rho \propto$ r$^{-5}$), mass-loss rates (10$^{-3}$–10$^{-1}$ M$_{\odot }$ yr$^{-1}$) assuming a wind velocity of 1000 km s$^{-1}$ and having a CSM mass of 0.18 M$_{\odot }$. The overall evolution indicates that SN 2021foa most likely originated from an LBV star transitioning to a WR star with the mass-loss rate increasing in the period from 5 to 0.5 yr before the explosion or it could be due to a binary interaction.

Gangopadhyay, Anjasha (ORCID:0000000238845637)↗

Unified nonparametric equation-of-state inference from the neutron-star crust to perturbative-QCD densities

Perturbative quantum chromodynamics (pQCD), while valid only at densities exceeding those found in the cores of neutron stars, could provide constraints on the dense-matter equation of state (EOS). Here, in this work, we examine the impact of pQCD information on the inference of the EOS using a nonparametric framework based on Gaussian processes (GPs). We examine the application of pQCD constraints through a ``pQCD likelihood,'' and verify the findings of previous works; namely, a softening of the EOS at the central densities of the most massive neutron stars and a reduction in the maximum neutron-star mass. Although the pQCD likelihood can be easily integrated into existing EOS inference frameworks, this approach requires an arbitrary selection of the density at which the constraints are applied. The EOS behavior is also treated differently on either side of the chosen density. To mitigate these issues, we extend the EOS model to higher densities, thereby constructing a ``unified'' description of the EOS from the neutron-star crust to densities relevant for pQCD. In this approach the pQCD constraints effectively become part of the prior. Since the EOS is unconstrained by any calculation or data between the densities applicable to neutron stars and pQCD, we argue for maximum modeling flexibility in that regime. We compare the unified EOS with the traditional pQCD likelihood, and although we confirm the EOS softening, we do not see a reduction in the maximum neutron-star mass or any impact on macroscopic observables. Though residual model dependence cannot be ruled out, we find that pQCD suggests the speed of sound in the densest neutron-star cores has already started decreasing toward the asymptotic limit; we find that the speed of sound squared at the center of the most massive neutron star has an upper bound of $\sim 0.5$ at the 90% level.

equations of state of nuclear matter↗

Tidal–hydrological dynamics of water temperature across freshwater forested wetlands on the northeastern Pacific coast

Abstract Tidal freshwater forests were once extensive across temperate coastlines, but loss and fragmentation have made estimation of their ecosystem functions challenging. We measured water temperature for 2 years in three Sitka spruce tidal forests, a restoration site, and an adjacent emergent marsh on the Columbia River, Washington, United States. We assessed spatial variability of water temperature within sites including the effects of hydrology, differences among bay and tributary tidal forests, and differences between the tidal forests and the mainstem Columbia, the restoration site, and the emergent marsh. The tidal forests nearest to the bay had lower interior water temperatures than their channel confluences by up to 2.5°C (weekly median temperature) and 2.0°C (weekly maximum temperature), with most cooling occurring during the low‐flow months of July–September. Tributary sites had maximum temperatures up to 1.9°C cooler than bay sites and 4.2°C cooler than the mainstem. Temperatures in the two bay sites decreased by −0.16°C/100 m and −0.07°C/100 m, on average. The restoration site had the smallest within‐site temperature gradient. Differences in maximum temperatures were greatest when tidal range was low, while higher tidal ranges were associated with warmer and more variable site interiors relative to their confluences. These results suggest that water temperatures in these tidal forests can provide temperature refugia for cold water biota including salmon.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of Mechanical and Thermomechanical Water Vapor Compression Techniques for Enabling High Temperature Lift Hydration-Based Chemical Heat Pumps

Achieving high temperature lifts (>200 K) via a chemical heat pump based on salt hydration/dehydration reactions requires the transport of water vapor from low to high pressure. Alternative compression approaches require condensing of low-pressure water vapor, pumping of liquid water, and subsequent evaporation when the low-side pressure corresponds to sub-ambient water saturation temperatures. Thus, this study compares four steam compression methods for use within a chemical heat pump system based on a reversible calcium oxide hydration/dehydration reaction with a temperature lift from 350 °C heat to >600 °C. Purely mechanical and thermochemical/mechanical compression technologies are considered. A parametric study of maximum allowable temperature, the isentropic efficiency of mechanical compressors, the effectiveness of heat exchangers, and the assumed allowable heat exchanger pressure drop is conducted to determine the mechanical and thermal energy consumed per kilogram of compressed steam. The system complexity in terms of the number of main system components, maximum pressure ratio, and maximum allowable temperature is estimated. Model results show an absorption-based steam compressor has the highest exergetic efficiency for the required chemical heat pump required conditions. As a result, this system configuration was then experimentally demonstrated to illustrate the impact of system performance on component effectiveness.

Advanced reactors↗

Phoenix Dust Storm (PHX-DUST) Scale: A Cooperatively Developed Dust Storm Scale for Phoenix, Arizona

Using extensive localized meteorological and air quality data for central Arizona from 2010 to 2023, we create a postevent dust storm scale for use by the primary stakeholders in central Arizona for the Phoenix metropolitan area called the Phoenix Dust Storm (PHX-DUST) scale. To ensure usability across a wide spectrum of users, a core concept was to “keep it simple.” The PHX-DUST scale is based on (i) maximum dust concentration for particulate matter (PM10) across the network in micrograms per cubic meter which determines category, e.g., “category 5 (the highest observed category)” and category 4; (ii) the number of network monitors achieving dust concentrations above a threshold of 500 μg m−3 (categorized as “widespread” or “isolated,” as measures of spatial extent); (iii) a duration parameter (which determines “long duration” or “short duration”); and (iv) a measure of wind speed over the affected area (maximum wind gust recorded over the network, which may not be the maximum wind of the storm). Using this index for the 189 dust storms impacting the Phoenix metropolitan area for the period 2010–23, the most severe dust storm occurred on 5 July 2011 and is classified as a “Category 5, Widespread, Long-Duration High-Gust” event. This initial attempt at defining the PHX-DUST scale holds valuable applications for research, education, and applied analyses. It demonstrates that a consortium of interested groups can effectively work to create products benefiting the weather community and general public. Here, the PHX-DUST scale can also serve as a foundational framework for application in other regions where dust storms pose a threat to the well-being of populations, infrastructure, and ecosystems.

Atmosphere↗

Lake-Effect Snowstorm Events and Associated Snowfall Totals Integrated from NOAA Storm Reports, ERA5, and HRRR for the Laurentian Great Lakes (1997–2024)

Lake-effect snowstorms are localized, impactful winter weather phenomena that can generate substantial snowfall totals and pose significant challenges for forecasting, transportation, and regional infrastructure. To support the analysis and modeling of these events, this dataset compiles observational reports of lake-effect snowstorms alongside corresponding snowfall estimates derived from gridded atmospheric datasets. The observational component of the data originates from the National Weather Service (NWS) winter storm report, subset to lake-effect snow event type, covering 1997–2024. For each lake-effect snow event, this data provides the impacted county, event start and end datetimes at an hourly resolution, as well as relevant storm narratives. The complementary reanalysis-derived data is sourced from European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA5) and High-Resolution Rapid Refresh (HRRR) gridded data. For both gridded datasets, the maximum total snowfall (in units mm) was extracted, constrained by the county and datetimes specified by the observational report. ERA5 data covers the entire observational period (1997–2024), whereas HRRR data is only available from November 2016 – December 2024. Three CSV files are provided here: (1) the observational lake-effect snow event report, (2) ERA5 maximum snowfall detections for each event, and (3) HRRR maximum snowfall detections for each event. Relevant data from the observational files, such as impacted state and county, event datetimes, and event IDs, were included for convenience. Users can inspect and visualize the data using tools such as Microsoft Excel and Python pandas/matplotlib packages. This dataset may support a variety of applications, including climatological analyses of lake-effect snowfall, evaluation of snowfall representation in atmospheric datasets and numerical weather prediction models, and the development of machine learning approaches for detecting or predicting lake-effect snowfall events.

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > SOLID↗

Uncertainty in Synthetic Tropical Cyclone Hazard and Risk Estimates: Insights from RAFT, CHAZ, MIT, STORM, and CLIMADA

We synthesize five complementary tropical cyclone (TC) hazard frameworks—RAFT (physics-based machine learning), CHAZ and MIT (statistical–dynamical), STORM (fully statistical), and CLIMADA (observation-driven resampling)—to characterize uncertainty in wind-related TC metrics relevant to energy applications. All datasets and the IBTrACS observational record are harmonized to a common 6-hourly, 2.5° grid. We compare basin-wide and coastal properties using consistent definitions for TC frequency, mean and maximum intensity, 24-hour intensification, and 6-hour translation speed, and quantify agreement with Pearson r, RMSE, and Kling–Gupta efficiency (KGE) alongside resampling-based confidence intervals. CLIMADA is included for basin context but excluded from coastal skill scoring because it resamples historical IBTrACS; if supplied with projected future tracks from an external hazard model, CLIMADA can be used to simulate future TC scenarios. Results show robust, cross-model signals: (i) a corridor of activity from the tropical Atlantic through the Caribbean into the Bahamas and western subtropical Atlantic; (ii) a meridional dipole in 24-hour intensification (low-latitude strengthening, subtropical weakening); and (iii) a transition from slower tropical motion to faster midlatitude translation. Coastal winds (mean and maximum) consistently cluster from the eastern Gulf into the Bahamas–western Atlantic transition. The largest structural spread occurs in the amplitude and footprint of lifetime maximum intensity and, secondarily, in translation speed; intensification exhibits similar central behavior across frameworks with variability in extremes. Translation speed shows the most uniform coastal agreement. These findings provide a decision envelope for wind-focused risk screening and clarify where uncertainty should be carried forward; wind-only results represent a lower bound on total hazard, motivating integration of surge and rainfall modules and a companion, asset-level damage analysis.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Initial Characterization of the NREL Large-Amplitude Motion Platform

The Large Amplitude Motion Platform (LAMP) at NREL represents a significant advancement in the controlled testing of Wave Energy Converters (WECs) under laboratory conditions. Originally designed by E2M as a six-degree-of-freedom (DOF) Stewart platform for flight simulation, LAMP has been adapted by NREL to facilitate the mounting and evaluation of WECs. This adaptation enables dry testing of WECs using motion profiles similar to the ocean, facilitating the iterative design, testing, and validation of WEC performance prior to ocean deployments. This report presents the initial work completed to characterize LAMP, with particular emphasis on its stability and operational capabilities across various single and multi-degree-of-freedom (DOF) motion profiles. The report includes planned comparisons at three distinct mass payloads, aimed at assessing the platform's positional accuracy, frequency response, and endurance over extended runtime periods. These experimental tests are critical for establishing the platform's limitations and ensuring that the data generated during WEC validation is both accurate and reproducible. The outcomes of this study not only contribute to a deeper understanding of LAMP's capabilities but also lay the groundwork for future advancements in WEC testing methodologies. By providing robust and reliable performance data within a controlled laboratory setting, the findings are expected to significantly enhance the development and commercialization of marine energy technologies. This report presents the initial findings of the LAMP Characterization work and proposed steps to further understand and characterize LAMP. Data collected during this work can be found on MHKDR at: https://mhkdr.openei.org/submissions/602 Note that this report shares the measured/found instantaneous maximum operating range of LAMP. For most applications the maximum operating range cannot be used for system health and longevity. The operating range and capabilities of LAMP will be evaluated on a case-by-case basis, single-DOF position, velocity, and acceleration values presented in Table 4a-c, and Table 5 should be taken as instantaneous absolute maximum values. Future use of LAMP will likely be limited to smaller values.

16 TIDAL AND WAVE POWER↗

Correlations between the Neutron Star Mass–Radius Relation and the Equation of State of Dense Matter

We develop an analytic method of inverting the Tolman–Oppenheimer–Volkoff relations to high accuracy. In principle, a specified energy density–pressure relation gives a unique mass–radius (M–R) relation and vice versa. Our method is developed from the strong correlations that are shown to exist between the neutron star mass–radius curve and the equation of state (EOS) or pressure–energy density relation. Selecting points that have masses equal to fixed fractions of the maximum mass, we find a semi-universal power-law relation between the central energy densities, pressures, sound speeds, chemical potentials, and number densities of those stars, with the maximum mass and the radii of one or more fractional maximum mass points. Rms fitting accuracies, for EOSs without large first-order phase transitions, are typically 0.5% for all quantities at all mass points. The method also works well, although less accurately, in reconstructing the EOS of hybrid stars with first-order phase transitions. These results permit, in effect, an analytic method of inverting an arbitrary M–R curve to yield its underlying EOS. We discuss applications of this inversion technique to the inference of the dense matter EOS from measurements of neutron star masses and radii as a possible alternative to traditional Bayesian approaches.

Bayesian statistics↗

Effects of Critical Compression Ratio on Rating Gasoline Knock Propensity

It is common practice in the automotive industry to explore the knock limits of fuels on an engine by a comparison of the knock limited spark advance (KLSA) at threshold knock intensity. However, the knock propensity of gasolines can be rated by changing one of three metrics on a variable compression ratio Cooperative Fuels Research (CFR) octane rating engine while holding the other two variables constant: knock intensity, spark timing, and critical compression ratio. The operational differences between the standard research octane number (RON) rating and modern engine operation have been explored in three parts. The first part focused on the effects of lambda and knock characterization. The second part studied the effects of spark timing. This third part explores the knock ratings of several gasolines by comparing the critical compression ratios at constant combustion phasing and knock intensity. The threshold knock intensity was based on the standard octane rating D1 pickup or by maximum amplitude of pressure oscillations (MAPO) measured by a piezoelectric cylinder pressure transducer. Several Fuels for Advanced Combustion Engines (FACE) gasolines, primary reference fuels (PRFs), and toluene standardization fuels (TSFs) were tested on a CFR octane rating engine with advanced data acquisition equipment and a piezoelectric cylinder pressure transducer. These tests deviated from the ASTM D2699 standard octane rating procedure. For each test fuel, the CFR engine was operated at stoichiometry at a constant combustion phasing (CA50) and the compression ratio was modified until a threshold knock intensity was realized. It was found that the chemical composition of the fuels affected the relationship of critical compression ratios between the D1 knockmeter and piezoelectric pressure transducer knock intensity thresholds, as well as the measured combustion maximum pressure rise rate and spark timing setting for constant CA50. For highly aromatic fuels tested at a constant MAPO knock intensity threshold, it was found that the maximum pressure rise rate was two to three times higher than that of highly paraffinic fuels with similar RON and the spark advance was several crank angle degrees less for constant combustion phasing.

Kolodziej, Christopher P↗

CERF: IM3 Projected Western US Power Plant Locations

Overview The Capacity Expansion Regional Feasibility (CERF) model is an open-source geospatial python package that provides new power plant locations at a 1km resolution. The model ingests U.S. state or regional-scale electricity system capacity expansion plans, such as those produced by the Global Change Analysis Model (GCAM-USA), and identifies feasible, site-specific locations for individual new power plants (renewable and non-renewable). CERF combines high-resolution geospatial suitability analyses with an economic algorithm that selects individual plant siting locations based on grid interconnection costs and the locational marginal value of new generation. The model incorporates a wide range of dynamic constraints and opportunities, such as protected lands, population density, existing infrastructure, and water availability. This dataset provides CERF power plant siting results for IM3 Phase 2 simulations across eight different scenarios for the Western US through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 CERF siting results in this dataset correspond to capacity expansion plans in the GCAM-USA IM3 Phase 2 simulation data and are available for each of the above scenarios. Data Details Temporal Range: 2015-2055 in 5-year timesteps. Note that 2015 is the experiment base year and 2020 and beyond represent model simulation years. Spatial Range: Plant locations are provided for the eleven states in the Western US including Arizona, California, Colorado, Idaho, Montana, New Mexico, Nevada, Oregon, Utah, Washington, and Wyoming. Spatial Resolution: 1 km-squared, provided in x and y coordinates Geospatial Projection: Albers Equal Area Conic (ESRI:102003) File Type: csv The dataset contains subdirectories for each of the eight scenarios described in the overview. Each scenario folder contains two subfolders with the following information: 1. Power Plant Data This directory contains a single .csv file of power plant locations for both pre-existing (non-CERF sited plants in operation in 2015) and new (CERF-sited) power plants across the temporal range along with additional CERF model output parameters for CERF-sited plants. Plant with a siting year earlier than 2020 correspond to facilities that are operational leading into the first timestep CERF simulation. For a more detailed description of CERF model output parameters, see the CERF model documentation. Note that the cerf_plant_id parameter is unique within each scenario file but not across scenario files. Parameter Descriptions scenario - Name of scenario cerf_plant_id - Unique siting identifier cerf_sited - If True, indicates that plant was sited by CERF model. If False, indicates pre-existing facility region_name - Name of region (state) tech_id - Technology ID tech_name - Full generation technology name inclusive of cooling type (if applicable) and additional characteristics tech_simple - Simplified generation technology type unit_size_mw - Power plant unit size (MW) xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) index - Index position in the flattend 2D array buffer_in_km - Exclusion buffer around site (km) sited_year - Year of siting retirement_year - Year of retirement lmp_zone - Locational marginal price (LMP) zone ID locational_marginal_price_usd_per_mwh - Locational marginal price ($/MWh) generation_mwh_per_year - Generation output (MWh/yr) operating_cost_usd_per_year - Cost of plant operations ($/yr) net_operational_value - Net operational value based on LMP and and operating costs ($/yr) interconnection_cost - Cost of interconnection for transmission & gas pipeline (if applicable) net_locational_cost -- Difference of interconnection cost and operating value ($/yr) capacity_factor_fraction - Capacity factor (fraction) carbon_capture_rate_fraction - Carbon capture rate (fraction) fuel_co2_content_tons_per_btu - Fuel CO2 content (tons/Btu) fuel_price_usd_per_mmbtu - Fuel price ($/MMBtu) fuel_price_esc_rate_fraction - Fuel price escalation rate (fraction) heat_rate_btu_per_kWh - Heat rate (Btu/kWh) lifetime_yrs - Technology lifetime for annuity (years) operational_life_yrs - Operational lifetime for retirement (years) variable_om_usd_per_mwh - Variable operation and maintenance costs of yearly capacity use ($/MWh) variable_om_esc_rate_fraction - Variable operation and maintenance costs escalation rate (fraction) carbon_tax_usd_per_ton - Carbon tax ($/ton) carbon_tax_esc_rate_fraction - Carbon tax escalation rate (fraction) 2. Storage Data This directory contains information on new and pre-existing energy storage facilities operational in each timestep along with various storage operational parameters. The 2015 timestep provides pre-existing energy storage data and corresponds with facilities that are operational leading into the first model simulation timestep. Note that coordinates in the storage files correspond to the interconnection point on the grid (substation location), not individual energy storage locations. Energy storage is added in a cumulative process at each given interconnection point. That is, each individual file provides the total operational storage capacity interconnected to the specified substation for the given timestep, inclusive of previously installed storage at that location and new storage installed in that timestep at that location. Parameters scenario - Name of scenario timestep - Simulation timestep name - Unique storage identifier s_typ - Type of energy storage technology (battery or pumped storage hydro) s_node - Node ID of interconnecting substation xcoord - X coordinate in the default CRS (meters) ycoord - Y coordinate in the default CRS (meters) charge_rate - Maximum charge rate (power capacity) of storage system (MW) discharge_rate - Maximum discharge rate (power capacity) of storage system (MW) duration - Duration of storage system (hours) max_SoC - Allowed maximum state of charge (energy capacity) of storage system (MWh) min_SoC -Allowed minimum state of charge (energy capacity) of storage system (MWh) charge_eff - Efficiency of charge (fraction between 0 and 1) discharge_eff - Efficiency of discharge (fraction between 0 and 1) Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program.

CERF↗