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Investigation of wear resistance performance for asphalt pavement coarse aggregates based on morphological characteristics and mineral composition
No full textThis study investigates the wear resistance mechanism of coarse aggregates in asphalt pavements from a fine-scale perspective, focusing on their morphological characteristics and mechanical properties. Firstly, the Los Angeles abrasion test was conducted to assess the microstructural wear of the aggregates. Scanning electron microscopy (SEM) and ImageJ software were used to analyze the morphological evolution of the aggregates at different abrasion stages. Subsequently, micromechanical parameters of aggregate mineral grains were calculated via X-ray diffraction (XRD) and nanoindentation testing at the microscale. Considering that the mechanical properties of individual mineral components do not fully reflect the macroscopic behavior of the coarse aggregates, the nano-hardness of the aggregates was scaled up using a modified equivalent Mohs hardness (HM) formula. Based on this, a cross-scale study of the elastic modulus was conducted using homogenization theory. Finally, a predictive model for the Los Angeles abrasion loss rate of coarse aggregates was developed, incorporating both morphological characteristics and mechanical properties. The results indicate that the fractal dimension is an effective indicator of morphological changes in coarse aggregates at different stages of abrasion. Moreover, a smaller change in fractal dimension correlates with a lower abrasion loss rate. Additionally, both the hardness and modulus of the coarse aggregates significantly influence their wear resistance. The ratio of the abrasion loss rate to the fractal dimension change (kD) showed a strong negative correlation with both hardness and modulus, suggesting that the prediction of abrasion loss rate based on fractal dimension and mechanical properties is highly reliable
Plant Community Shifts as Early Indicators of Abrupt Permafrost Thaw and Associated Carbon Release in an Interior Alaskan Peatland
No full textWidespread changes to near-surface permafrost in northern ecosystems are occurring through gradual top-down thaw and more abrupt localized thermokarst development. Both thaw types are associated with a loss of ecosystem services, including soil hydrothermal and mechanical stability and long-term carbon storage. Here, we analyzed relationships between the vascular understory, basal moss layer, active layer thickness (ALT), and greenhouse gas fluxes along a thaw gradient from permafrost peat plateau to thaw bog in Interior Alaska. We used ALT to define four distinct stages of thaw: Stable, Early, Intermediate, and Advanced, and we identified key plant taxa that serve as reliable indicators of each stage. Advanced thaw, with a thicker active layer and more developed thermokarst features, was associated with increased abundance of graminoids and Sphagnum mosses but decreased plant species richness and ericoid abundance, as well as a substantial increase in methane emissions. Early thaw, characterized by active layer thickening without thermokarst development, coincided with decreased ericoid cover and plant species richness and an increase in CH4 emissions. Our findings suggest that early stages of thaw, prior to the formation of thermokarst features, are associated with distinct vegetation and soil moisture changes that lead to abrupt increases in methane emissions, which then are perpetuated through ground surface subsidence and collapse scar bog formation. Current modeling of permafrost peatlands will underestimate carbon emissions from thawing permafrost unless these linkages between plant community, nonlinear active layer dynamics, and carbon fluxes of emerging thaw features are integrated into modeling frameworks
Hourly Simulated Power Production Data with Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Fixed-Tilt Systems in the U.S. Eastern Interconnection for Weather Year 2013
No full textUsing 2013 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be 30-degree, fixed tilt systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with No Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Fixed-Tilt Systems in the U.S. Eastern Interconnection for Weather Year 2015
No full textUsing 2015 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be 30-degree, fixed tilt systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Aggregate-Superpose-Project: A Cognitive Model for Quantum Problem Solving
No full textThis work proposes a novel cognitive model, called Aggregate-Superpose-Project (ASP), to facilitate problem solving and the analysis of algorithms in Quantum Computing (QC). Our model contains three simple abstractions that help students use classic computing concepts towards specifying quantum states and transformations. Simplicity is a major advantage of ASP along with reinforcing the use of classical concepts in learning QC abstractions. Preliminary evaluations indicate that ASP can provide students with the means to describe quantum algorithms at appropriate levels of abstraction
Hourly Simulated Power Production Data with Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Single-Axis Tracking Systems in the U.S. Eastern Interconnection for Weather Year 2017
No full textUsing 2017 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory’s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be single-axis tracking systems. Sites’ latitudes and longitudes were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with No Snow Loss Model at Queued Utility-Scale PV Sites Simulated as Single-Axis Tracking Systems in the U.S. Eastern Interconnection for Weather Year 2021
No full textUsing 2021 weather data, we ran PySAM power production simulations for utility-scale PV sites in the U.S. Eastern Interconnection queue. Site IDs, capacities, and locations (counties) were extracted from Lawrence Berkeley National Laboratory\u27s Queued Up: 2024 Edition dataset. No panel mount information was provided, so all sites were assumed to be the centers of the installation counties. See queued_site_metadata.csv file for individual site metadat
Hourly Simulated Power Production Data with Snow Loss Model at Existing Utility-Scale PV Sites (\u3e5 MW) in the U.S. Eastern Interconnection in 2015
No full textProject Summary: We ran PySAM power production simulations for utility-scale (\u3e5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2015. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory\u27s Utility-Scale Solar 2024 Edition dataset. See 2015_PV_existing_site_metadata.csv file for individual site metadata
Hourly Simulated Power Production Data with Snow Loss Model at Existing Utility-Scale PV Sites (\u3e5 MW) in the U.S. Eastern Interconnection in 2017
No full textProject Summary: We ran PySAM power production simulations for utility-scale (\u3e5 MW) PV sites located in the U.S. Eastern Interconnection in the year 2017. Site panel mounts (fixed-tilt or single-axis tracking), capacities, and locations (latitudes and longitudes) were extracted from Lawrence Berkeley National Laboratory\u27s Utility-Scale Solar 2024 Edition dataset. See 2017_PV_existing_site_metadata.csv file for individual site metadata