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At least 127 records · Page 7

Exploring topography-based methods for downscaling subgrid precipitation for use in Earth System Models

Topography exerts major control on land surface processes. To improve representation of topographic impacts on land surface processes, a new topography-based subgrid structure has been introduced to the Energy Exascale Earth System Model to represent the subgrid heterogeneity of surface elevation. To take advantage of the new subgrid structure for improving land surface modeling, this study explores four variations of topography-based methods for downscaling grid precipitation to the corresponding subgrids. In the first three methods, the deviation of the subgrid precipitation from the grid’s is equal to the grid precipitation multiplied by the ratio of the elevation difference between the subgrid and grid mean to a specified elevation equals to the grid elevation, the difference between the maximum and minimum subgrid elevation, and the maximum subgrid elevation, respectively. The second method limits the ratio to 0.5 to avoid extreme values on mountains and the third method accounts for the slope effect. The fourth method is similar to the third method except that the Froude Number is used to limit the numerator in a blocking regime of the ambient flow. The downscaled precipitation is evaluated using the PRISM precipitation data over the U.S. using statistical metrics. Results show that by accounting for topographic slope besides elevation, the third and fourth methods show clear advantages over the first and second methods. Furthermore, introducing the Froude Number in the fourth method improves downscaling skill and shows consistent advantages over the third method in areas with larger subgrid heterogeneity across different grids sizes.

Tesfa, Teklu K.↗

Extending a land-surface model with <i>Sphagnum</i> moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO<sub>2</sub>

Abstract. Mosses need to be incorporated into Earth system models to better simulate peatland functional dynamics under the changing environment. Sphagnum mosses are strong determinants of nutrient, carbon, and water cycling in peatland ecosystems. However, most land-surface models do not include Sphagnum or other mosses as represented plant functional types (PFTs), thereby limiting predictive assessment of peatland responses to environmental change. In this study, we introduce a moss PFT into the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. The model was parameterized and independently evaluated against observations from an ombrotrophic forested bog as part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) project. The inclusion of a Sphagnum PFT with some Sphagnum-specific processes in ELM allows it to capture the observed seasonal dynamics of Sphagnum gross primary production (GPP) albeit with an underestimate of peak GPP. The model simulated a reasonable annual net primary production (NPP) for moss but with less interannual variation than observed, and it reproduced aboveground biomass for tree PFTs and stem biomass for shrubs. Different species showed highly variable warming responses under both ambient and elevated atmospheric CO2 concentrations, and elevated CO2 altered the warming response direction for the peatland ecosystem. Microtopography is critical: Sphagnum mosses on hummocks and hollows were simulated to show opposite warming responses (NPP decreasing with warming on hummocks but increasing in hollows), and hummock Sphagnum was modeled to have a strong dependence on water table height. The inclusion of this new moss PFT in global ELM simulations may provide a useful foundation for the investigation of northern peatland carbon exchange, enhancing the predictive capacity of carbon dynamics across the regional and global scales.

54 ENVIRONMENTAL SCIENCES↗

Enabling fast charging of lithium-ion batteries through secondary-/dual- pore network: Part II - numerical model

To increase the market share of electric vehicles, it is desirable to reduce the battery charge times, which are significantly limited by poor electrolyte transport. A high rate charging is achievable by using expensive and low energy density cells with thin electrodes. For higher energy density cells, new electrolytes with improved conductivity and diffusivity and/or electrodes with advanced architecture are required to boost the electrolyte transport, leading to a more uniform utilization of active materials. In our previous work, an analytical model was developed to investigate the effect of secondary pore network (SPN) on electrolyte transport and the configuration of SPN was optimized by enforcing equal characteristic diffusion times in through-plane and in-plane directions. Here, to evaluate the effect of SPN on the fast-charging capability of lithium-ion batteries, a 2D physics-based electrochemical model is developed with SPN in either one or both electrodes. Additionally, the effect of SPN on cell energy density and lithium plating is investigated for cells with different loadings and electrode porosities. Combining SPN with elevated charging temperatures, the model predicts that the volumetric discharge energy density of a 3 mA h/cm2 cell can reach 270 Wh/L after a 6C constant-current charging.

25 ENERGY STORAGE↗

Assessment of WRF (v 4.2.1) dynamically downscaled precipitation on subdaily and daily timescales over CONUS

Abstract. This study analyzes the quality of simulated historical precipitation across the contiguous United States (CONUS) in a 12 km Weather Research and Forecasting model version 4.2.1 (WRF v 4.2.1)-based dynamical downscaling of the fifth-generation ECMWF atmospheric reanalysis (ERA5). This work addresses the following questions. First, how well are the 3 and 24 h precipitation characteristics (diurnal and annual cycles, precipitation frequency, annual and seasonal mean and maximum precipitation, and distribution of seasonal maximum precipitation) represented in the downscaled simulation, compared to ERA5? And second, how does the performance of the simulated WRF precipitation vary across seasons, regions, and timescales? Performance is measured against the National Centers for Environmental Prediction/Environmental Modeling Center (NCEP/EMC) 4 km Stage IV and Oregon State University Parameter-Elevation Regressions on Independent Slopes Model (PRISM) data on 3 and 24 h timescales, respectively. Our analysis suggests that the 12 km WRF exhibits biases typically found in other WRF simulations, including those at convection-permitting scales. In particular, WRF simulates both the timing and magnitude of the summer diurnal precipitation peak as well as ERA5 over most of the CONUS, except for a delayed diurnal peak over the Great Plains. As compared to ERA5, both the month and the magnitude of the precipitation peak annual cycle are remarkably improved in the downscaled WRF simulation. WRF slightly overestimates 3 and 24 h precipitation maximum over the CONUS, in contrast to ERA5, which generally underestimates these quantities mainly over the eastern half of the CONUS. Notably, WRF better captures the probability density distribution (PDF) of 3 and 24 h annual and seasonal maximum precipitation. WRF exhibits seasonally dependent precipitation biases across the CONUS, while ERA5's biases are relatively consistent year round over most of the CONUS. These results suggest that dynamical downscaling to a higher resolution improves upon some precipitation metrics but is susceptible to common regional climate model biases. Consequently, if used as input data for domain-specific models, we suggest moderate bias correction be applied to the dynamically downscaled product.

54 ENVIRONMENTAL SCIENCES↗

Long-term single-column model intercomparison of diurnal cycle of precipitation over midlatitude and tropical land

General Circulation Models (GCMs) have for decades exhibited difficulties in modelling the diurnal cycle of precipitation (DCP). This issue can be related to inappropriate representation of the processes controlling sub-diurnal phenomena like convection. In this study, 11 single-column versions of GCMs are used to investigate the interactions between convection and environmental conditions, processes that control nocturnal convections, and the transition from shallow to deep convection on a diurnal time-scale. Long-term simulations are performed over two continental land sites: the Southern Great Plains (SGP) in the USA for 12 summer months from 2004 to 2015 and the Manacapuru site at the central Amazon (MAO) in Brazil for two full years from 2014 to 2015. The analysis is done on two regimes: afternoon convective regime and nocturnal precipitation regime. Most models produce afternoon precipitation too early, likely due to the missing transition of shallow-to-deep convection in these models. At SGP, the unified convection schemes better simulate the onset time of precipitation. At MAO, models produce the heating peak in a much lower level compared with observation, indicating too shallow convection in the models. For nocturnal precipitation, models that produce most of nocturnal precipitation all allow convection to be triggered above the boundary layer. This indicates the importance of model capability to detect elevated convection for simulating nocturnal precipitation. Sensitivity studies indicate that (a) nudging environmental variables towards observations has a minor impact on DCP, (b) unified treatment of shallow and deep convection and the capability to capture mid-level convection can help models better capture DCP, and (c) the interactions of the atmosphere with other components in the climate system (e.g. land) are also important for DCP simulations in coupled models. Finally, these results provide long-term statistical insights on which physical processes are essential in climate models to simulate DCP.

54 ENVIRONMENTAL SCIENCES↗

Development of High-Temperature Emissivity Measurement Capabilities for Molten Salts at PNNL

In this study, an emissivity measurement system for a liquid molten salt was developed on the bases on the Stefan Boltzmann Law. A prototype device operating in ambient atmosphere was constructed an initial result compared well with available literature. The diffuse emissivity of NaCl-KCl system (NaCl, 51mol% NaCl – 49mol% KCl and KCl) was measured from 550 to 850 °C at a wavelength of 1.3 µm. The system appears to be relatively invariant with composition but a clear trend of decreasing emissivity values from ~0.9 at 550 °C to 0.75 at 850 °C was observed. A schematic for an enclosed system for inert atmosphere and actinide salts was drafted. Several of the components for fabrication of this device, improved laser system, furnace, nickel for capsule construction, have been purchased and are ready for assembly. The new laser system will have an improved measurement range of 275-1000 °C. The clam shell furnace has a maximum temperature of 1200 °C and will support the hermetically sealed inert encapsulation vessels. Nickel plate and tubing will create a relatively corrosion resistance capsule for testing that can withstand temperature up to 1000 °C. Emissivity measurements are important for a larger effort to understand radiative heat transfer within molten salts at elevated temperatures (600-1000 °C). Literature review of optical salt properties and radiative heat transfer models indicated that systems within elevated temperature regimes could see upwards of 20% or more of their total heat transferred through photonic mechanisms. Ultimately, future work will measure the total thermal conductivity and break down the molecular and radiative portions. Thermal conductivity, along with other thermal properties of molten salts, both coolant and fuel, are fundamental to modeling and simulations that support MSR design. The results presented here and ongoing work at PNNL will be useful in selecting optimal salt compositions, designing reactor systems, and optimizing heat transfer within a MSR power plant.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Tidal Hydrodynamic Model for Cook Inlet, Alaska, to Support Tidal Energy Resource Characterization

Cook Inlet in Alaska has been identified as a prime site in the U.S. for potential tidal energy development, because of its enormous tidal power potential that accounts for nearly one-third of the national total. As one important step to facilitate tidal energy development, a tidal hydrodynamic model based on the unstructured-grid, finite-volume community ocean model (FVCOM) was developed for Cook Inlet to characterize the tidal stream energy resource. The model has a grid resolution that varies from about 1000 m at the open boundary to 100–300 m inside the Inlet. Extensive model validation was achieved by comparing model predictions with field observations for tidal elevation and velocity at various locations in Cook Inlet. The error statistics confirmed the model performs reasonably well in capturing the tidal dynamics in the system, e.g., R2 > 0.98 for tidal elevation and generally > 0.9 for velocity. Model results suggest that tides in Cook Inlet evolve from progressive waves at the entrance to standing waves at the upper Inlet, and that semi-diurnal tidal constituents are amplified more rapidly than diurnal constituents. The model output was used to identify hotspots that have high energy potential and warrant additional velocity and turbulence measurements such as East Foreland, where averaged power density exceeds 5 kw/m2. Lastly, a tidal energy extraction simulation was conducted for a hypothetical turbine farm configuration at the Forelands cross section to evaluate tidal energy extraction and resulting changes in far-field hydrodynamics.

16 TIDAL AND WAVE POWER↗

Diversifying Isoprenoid Platforms via Atypical Carbon Substrates and Non-model Microorganisms

Isoprenoid compounds are biologically ubiquitous, and their characteristic modularity has afforded products ranging from pharmaceuticals to biofuels. Isoprenoid production has been largely successful in Escherichia coli and Saccharomyces cerevisiae with metabolic engineering of the mevalonate (MVA) and methylerythritol phosphate (MEP) pathways coupled with the expression of heterologous terpene synthases. Yet conventional microbial chassis pose several major obstacles to successful commercialization including the affordability of sugar substrates at scale, precursor flux limitations, and intermediate feedback-inhibition. Now, recent studies have challenged typical isoprenoid paradigms by expanding the boundaries of terpene biosynthesis and using non-model organisms including those capable of metabolizing atypical C1 substrates. Conversely, investigations of non-model organisms have historically informed optimization in conventional microbes by tuning heterologous gene expression. Here, we review advances in isoprenoid biosynthesis with specific focus on the synergy between model and non-model organisms that may elevate the commercial viability of isoprenoid platforms by addressing the dichotomy between high titer production and inexpensive substrates.

59 BASIC BIOLOGICAL SCIENCES↗

Ensemble modeling of watershed-scale hydrologic effects of short-rotation woody crop production

Short-rotation woody crop (SRWC) production involves a set of silvicultural practices that aim to produce large volumes of biomass over relatively short time frames. The area over which these practices are employed is likely to increase in the coming decades as the demand for bioenergy increases, but the potential effects of this change in land management, including the hydrologic effects, are largely unknown. Here we outline the results from an ensemble modeling study that was developed to forecast the range of potential hydrological responses to the implementation of SRWC production over areas that are large (>1000 ha) relative to the size of individual clearcuts. The three models, SWAT, MIKE-SHE, and Envision-SRS, a physically based model designed to represent watersheds with dynamic land cover, represent a range of simulation tools that include hydrological response to landcover change. Results suggest that SRWC production will affect the hydrologic balance, primarily through changes in the volume of transpired water associated with the rapidly growing young stands. In particular, average annual actual evapotranspiration (ET) rates tend to decline under SRWC production in response to the less mature vegetation. These reductions in ET are balanced in the hydrological cycle through elevated groundwater recharge, expressed in the model results as elevated annual stream discharge.

09 BIOMASS FUELS↗

Joint Inversion of Surface Electrical Resistivity Tomography and Seismic Refraction Data between the 200 Areas

Geologic stratigraphy on the Hanford Site influences groundwater and contaminant migration through the aquifer system and the vadose zone. The current geologic framework model (GFM) relies heavily on a sparse distribution of borehole data in some locations to map geologic contacts and hydrologic properties in the subsurface. Non-invasive geophysical methods such as electrical resistivity tomography (ERT), transient electromagnetic surveying, and seismic imaging are being used at Hanford to map subsurface structure in areas with limited well observations. This is to develop and mature the capability of geophysical methods to aid in GFM refinement, to identify regions of subsurface complexity, and for optimal well siting. A joint inversion of co-located seismic refraction and ERT data was carried out for data collected on a ~2.3-km profile between the 200 Areas on the Hanford Site. While ERT and seismic refraction images have sensitivity to overlapping physical properties (porosity, moisture content, lithology), the resolution and physics used to acquire each of these datasets are different and therefore information can be different or mutually complementary. Performing a joint inversion provides a reasonable option for a coherent, coupled interpretation for mutually complementary datasets. Between the 200 Areas, there are few boreholes to interpret the geologic framework model, and these data sets were obtained to provide a first line of evidence toward identifying stratigraphic structure. The seismic refraction and ERT data were independently inverted during fiscal year 2022 and broadly showed a two-layer structure with a trough-like feature that is ~1 km wide and upwards of 150 m deep. The depth of the trough feature was greater in the ERT image compared to the seismic image, which indicated a maximum depth of approximately 110 m. The objective of the joint inversion described in this report was to invert the seismic refraction and ERT data together while constraining the ERT image to be structurally similar to the seismic refraction image. The approach was applied using the geophysical inverse modeling program E4D, which has the capability to invert first-arrival times from seismic refraction data and ERT resistances using a “cross-gradient” constraint. The application of cross-gradient constraints with different weights produces ERT models that show a high degree of similarity within the upper 100 m (above ~120 m elevation). None of the ERT models show an improved structural similarity to the seismic result; therefore, it is recommended that further attempts to jointly interpret these models focus on petrophysics and image resolution. Petrophysical measurements of core samples would improve knowledge of what drives the ERT response in this region and, along with downhole geophysical measurements, could be used to “ground truth” the surface-based geophysical results. Image resolution studies would provide insight into which regions of the inverted images are reliable and which regions are poorly constrained.

58 GEOSCIENCES↗

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Elevated temperature mechanical properties of Inconel 617 surface oxide using nanoindentation

Inconel 617 is a principal candidate material for helium gas cooled very-high-temperature reactors with outlet temperatures of 700–950 °C. Recent findings showed that this alloy develops unique surface oxide layers especially at high temperature (HT) helium environment with distinctive wear, friction and contact properties. This study investigates the elevated temperature mechanical properties of Inconel 617 top surface layers aged in HT helium environment. Nanoindentation technique is used to obtain load-displacement graphs of the alloy top surface oxide in temperatures ranging from 25 °C up to 600 °C. In addition, using finite element analysis along with an iterative regression technique, a semi-numerical method is developed to further measure and quantify the material parameters and, in particular, time-independent and creep characteristics of the oxide. Although Young's modulus of the oxide is found to be relatively close to the bulk for the tested temperatures, the yield strength and hardness, in comparison to the bulk material, increase significantly as the material is oxidized after aging. The oxide exhibits significant softening as the temperature increases to 600 °C. Unlike the bulk material, diffusion through the grains is found to be the dominant creep mechanism for the oxide. Considerable difference between the mechanical properties of the oxide and the bulk material shows the need for accurate measurements of near surface mechanical properties, if reliable predictive contact and tribological models are sought at elevated temperatures.

36 MATERIALS SCIENCE↗

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reprocessing Models for the Optical Light Curves of Hypervariable Quasars from the Sloan Digital Sky Survey Reverberation Mapping Project

We explore reprocessing models for a sample of 17 hypervariable quasars, taken from the Sloan Digital Sky Survey Reverberation Mapping project, which all show coordinated optical luminosity hypervariability with amplitudes of factors ≳2 between 2014 and 2020. We develop and apply reprocessing models for quasar light curves in simple geometries that are likely to be representative of quasar inner environments. In addition to the commonly investigated thin-disk model, we include the thick-disk and hemisphere geometries. The thick-disk geometry could, for instance, represent a magnetically elevated disk, whereas the hemisphere model can be interpreted as a first-order approximation for any optically thick out-of-plane material caused by outflows/winds, warped/tilted disks, and so on. Of the 17 quasars in our sample, 11 are best-fitted by a hemisphere geometry, five are classified as thick disks, and both models fail for just one object. We highlight the successes and shortcomings of our thermal reprocessing models in case studies of four quasars that are representative of the sample. While reprocessing is unlikely to explain all of the variability that we observe in quasars, we present our classification scheme as a starting point for revealing the likely geometries of reprocessing for quasars in our sample and hypervariable quasars in general.

79 ASTRONOMY AND ASTROPHYSICS↗

Incorporating Elevation in Traffic-Vehicle CO-Simulation: Issues, Impacts, and Solutions

Traffic-vehicle co-simulation couples microscopic traffic simulation with full-body vehicle dynamics to assess system-level impacts on mobility, energy, and safety with greater realism. Incorporating elevation is critical for accurately modeling vehicle behavior and energy use, especially for gradient-sensitive vehicles such as electric and heavy-duty trucks. However, raw elevation data often contain noise, discontinuities, and inconsistencies. While such issues may be negligible in traditional traffic simulations, they significantly affect traffic-vehicle co-simulations where vehicle dynamics are sensitive to road grade variations. This paper investigates the impact of unprocessed elevation data on vehicle behavior and energy consumption using a 42-mile simulation along Interstate 81. We propose an elevation processing workflow that can mitigate the effects stem from elevation data issues, improving the realism and stability of traffic-vehicle co-simulation. Results show that the method effectively removes noise and abrupt elevation transitions while preserving roadway geometry.

Xu, Guanhao [ORNL] (ORCID:0000000214326357)↗

Simulation of a High-Confinement Tidal Energy Array (Abstract)

When the projected area of a current turbine array occupies a substantial fraction of a tidal or river channel cross-sectional area, the confinement associated with the channel boundaries substantially increases turbine efficiency. This effect can be exploited to substantially reduce the levelized cost of energy for current turbine arrays. However, the presence of such an array will affect inflow velocity, water depth, and circulation in the surrounding area. This has implications for array performance and environmental impacts. This project combines existing numerical modeling capability from PNNL with an understanding of confined array performance from UW. The work will 1) Simulate tidal currents and water surface elevation in a regional circulation model that includes the Knik Arm site at appropriate resolution; 2) Incorporate a varying thrust coefficient into this model that reflects the outcomes of tidal hydrodynamic simulations of confined turbine arrays; 3) Use the model to determine the effects of array operation on water levels and inflow conditions as a function of different blockage ratios and control strategies; and 4) Identify the “far field” environmental implications of operating an array of this type. UW will use the outputs from this model to evaluate the implications of “feedback effects” and variable inflow conditions on levelized cost of energy estimates for a confinement exploiting array of cross-flow turbines.

16 TIDAL AND WAVE POWER↗

Real-Time Dynamic Brake Assessment for Heavy Commercial Vehicle Safety

This paper summarizes initial results and findings of a model developed to determine the braking performance of commercial motor vehicles in motion regardless of brake type or gross weight. Real-world data collected by Oak Ridge National Laboratory for a U.S. Department of Energy study was used to validate the model. Expanding on previous proof-of-concept research showing the linear relationship of brake application pressure and deceleration additional parameters such as elevation were added to the model. Outputs from the model consist of coefficients calculated for every constant pressure braking event from a vehicle that can be used to calculate a deceleration and thus compute a stopping distance for a given scenario. Using brake application pressure profiles derived from the dataset, stopping distances for light and heavy loads of the same vehicle were compared for various speed and road grades. For a constant brake application pressure profile (i.e. the pressure is relatively constant throughout the entire stop) it was shown that the lighter vehicle was able to stop in a shorter distance than the heavier vehicle in most scenarios other than large uphill grades. Significant changes in weight can be observed through the fuel efficiency of the vehicle to determine if the model needs to be calibrated with new or additional braking events. The model was initially developed for tracking brake performance to inform routine maintenance and the ordering of vehicles in a platoon but can be expanded to other connected and automated research areas.

Siekmann, Adam↗

The formation and evolution of Ni 2 Cr precipitates in Ni–Cr model alloys as a function of stoichiometry characterized by synchrotron x-ray diffraction

Ni-based alloys containing significant amounts of Cr, may precipitate new phases during long-term service at elevated temperatures. In Ni–Cr model alloys, the formation of Ni 2 Cr has been found to impact the material properties, including the strength and ductility after isothermal aging below the critical temperature of 590°C. In this work, we quantify the formation and evolution of long-range ordering in four Ni–Cr binary model alloys (Ni/Cr = 1.8, 2.0, 2.2, 2.4) after isothermal aging up to 10,000h at temperatures between 373 and 475°C. The alloys were characterized by hardness testing and synchrotron-based x-ray diffraction to quantify the impact of Ni 2 Cr phase fraction and precipitate size on mechanical properties. After 500h of isothermal aging, the formation of Ni 2 Cr was detected in all four alloys at 475°C. In the stochiometric alloy samples (Ni/Cr = 2.0), the formation of Ni 2 Cr was found after 500 and 3000h aging at 418 and 373°C, respectively. We found that the matrix lattice contraction and Ni 2 Cr phase fraction both saturate after early aging times. This is in stark contrast to the hardness and Ni 2 Cr precipitate size that both continue to increase with increasing aging time. Our results highlight that changes in hardness correlate linearly with Ni 2 Cr precipitate size rather than phase fraction. This important structure-property relationship can potentially help define Ni–Cr-based component lifetimes directly through an understanding of how Ni 2 Cr formation impacts strength and ductility. Here, we find that a precipitation hardening model for critical resolved shear stress with weakly coupled dislocations shows good agreement with the material property changes quantified from experimental measurements.

36 MATERIALS SCIENCE↗