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Influence of simple terrain on the spatial variability of a low-level jet and wind farm performance in the AWAKEN field campaign
In wind energy research, scientific challenges are often associated with complex terrain sites, where orography, vegetation, and buildings disrupt flow uniformity. However, even sites characterized as simple terrain can exhibit significant spatial variability in wind speed, particularly during stable boundary layers (SBLs) and low-level jets (LLJs). This study investigates these terrain interactions using both simulations and observations from the American WAKe ExperimeNt (AWAKEN). We employ a multiscale Weather Research and Forecasting (WRF) model simulation, integrating mesoscale forcing in the coarse domains and representing three rows of turbines from the King Plains wind farm as generalized actuator disks (GAD) in the large-eddy simulation (LES) domains. During a nocturnal LLJ event on 3 April 2023, the downstream, wake-affected turbine rows outperformed the upstream, unwaked row by 25 %–51 %. This counterintuitive result arises from terrain-induced streamwise variations in hub-height wind speed of approximately 4 m s −1 over 5 km – equivalent to ∼50 % of the upstream reference speed. This enhancement outweighs the wake-induced reduction in mean wind speed (∼12 %) and global blockage effects reported in the literature (∼1 %–3.4 %). The multiscale simulations capture the intra-farm spatial variability in power performance observed in SCADA data. Terrain-induced vertical displacement of the LLJ, coupled with large wind shear below the jet maximum, drives the substantial streamwise acceleration within the wind farm. These findings underscore the importance of accounting for spatial variability related to terrain, even in simple landscapes, particularly during LLJ conditions. Incorporating such effects into reduced-order modeling frameworks for wind farm design and control could significantly enhance their effectiveness.
Characterizing the Mechanisms of Ca and Mg Carbonate Ion-Pair Formation with Multi-Level Molecular Dynamics/Quantum Mechanics Simulations
The carbonate minerals of Ca and Mg are abundant throughout the lithosphere and have recently garnered significant research interest as possible long-term carbon sinks in the sequestration of atmospheric carbon dioxide. Nonetheless, an understanding of the atomic-level processes comprising their mineralization remains limited. Furthermore, we characterize and contrast the mechanisms of contact ion-pair formation in aqueous Ca and Mg carbonate systems, which represents the most fundamental step leading to the formation of their mineral solids. Utilizing multilevel embedded correlated wavefunction-based ab initio molecular dynamics/quantum mechanics simulations, we characterize not only the dynamics of these processes but also factors arising from the electronic structure of the involved species, revealing further details of the fundamentally different mechanisms for the interconversion between the contact ion-pairs and solvent-shared ion-pairs of Ca versus Mg carbonate.
Realization of the orbital-selective Mott state at the molecular level in Ba3LaRu2O9
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Aerosol Observing System (AOS) Purge: initiated flow reversal for aerosol stack dependent on CO level (b0-level)
Aerosol Observing System (AOS) Purge: initiated flow reversal for aerosol stack dependent on CO level
Lunar Spectral Deconvolution Algorithm (SDA) Retrieval Version 4.1 Level 2.0 (Quality checked and filtered ) (a1-level)
Lunar Spectral Deconvolution Algorithm (SDA) Retrieval Version 4.1 Level 2.0 (Quality checked and filtered )
Cimel Sunphotometer (CSPHOT): lunar aerosol optical depth, filtered and quality-controlled with pre-field and post-field calibration applied, Level 2.0, version 3 data (a1-level)
Cimel Sunphotometer (CSPHOT): lunar aerosol optical depth, filtered and quality-controlled with pre-field and post-field calibration applied, Level 2.0, version 3 data
Level-conversion circuits utilizing level-dependent inverter supply voltages
Voltage level conversion circuits include PMOS pull-down devices or NMOS pull-up devices, and inverters with outputs that determine gate voltages of these devices. The inverters are powered by moving supply voltages, for example complementary supply voltages generated from a pair of cross-coupled inverters. The cross-coupled inverters may implement a data storage latch with the moving supply voltages generated from the internal data storage nodes of the latch.
Solid‐State Prealkylation of Electrode Architectures (SPEAR): Direct Control of Prelithiation Levels in Silicon Anodes and Electrochemical Cycling
The Solid-state Prealkylation of Electrode ARchitectures (SPEAR) is different than traditional electrochemical prealkylation processes. Through SPEAR, alkylation is driven by solid-state diffusion without the simultaneous SEI formation concomitant with polarization. Here, we investigate the prelithiation of 80 wt. % Si-based anodes to varying amounts (up to Li 1.38 Si) to understand the trade-off between improved Li capacity and expansion-induced stress. Through dilatometry, we found that solid-state lithiation led to filling of the electrode pores through silicon expansion. This swelling changed the SEI formation process and accessibility of the silicon compared to an electrochemically lithiated electrode. Indeed, optimal prelithiation to Li 0.82 Si increases the initial C/3 cycling capacity post-SEI formation up to 43%, consistent with deeper Si activation through the electrode bulk. Prelithiation and cycling cells prelithiated beyond Li 0.82 Si results in a state of charge (SOC) close to 100% which facilitates parasitic degradation mechanisms and volume expansion of the Si electrode. The results demonstrate a pathway to modify silicon activation/SEI formation to enable high-energy electrodes.
AlphaBuilding ResCommunity: A multi-agent virtual testbed for community-level load coordination
Training and validating algorithms in a simulation testbed can accelerate research and applications of optimal control of residential loads to improve energy flexibility and grid resilience. We developed an open-source simulation environment, AlphaBuilding ResCommunity, that can be used to train and validate algorithms to control a single thermostatically controlled load (TCL) or coordinate a group of TCLs. We used reduced-order models to simulate the thermodynamics of TCLs, and the parameter values were determined from the connected smart thermostat data of real households. The environment was built upon the standardized OpenAI Gym interface. Ancillary functions, such as retrieving the parameters and weather forecasts, are provided to facilitate control strategies that require predictive information. Compared with existing efforts, AlphaBuilding ResCommunity has three advantages: (1) more realistic model settings because the parameter values are identified from actual household operating data, and modelling and measurement uncertainty are considered; (2) passive thermal storage control; and (3) ease of use due to a simple software dependency and standardized interface. We demonstrated the applications of the environment by implementing a Kalman Filter and Model Predictive Control on a single TCL and a Priority-Stack-Based Control and Alternating Direction Method of Multipliers to coordinate multiple TCLs for load tracking.
Atomic-level mechanism of CO2-promoted oxidation of alumina-forming alloys
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International perspectives on glass waste form development for low-level and intermediate-level radioactive waste
Not Available
Exposing Process‐Level Biases in a Global Cloud Permitting Model With ARM Observations
The emergence of global convective‐permitting models (GCPMs) represents a significant advancement in climate modeling, offering improved representation of deep convection and complex precipitation patterns. In this study, we evaluate the performance of the Simple Cloud‐Resolving E3SM Atmosphere Model (SCREAM) using its doubly periodic configuration (DP‐SCREAM) against large eddy simulations and modern observational data sets from the Atmospheric Radiation Measurement program. We introduce several new transitional cloud regime cases, such as the transition from shallow to deep convection and from stratocumulus to cumulus, as well as cold‐air outbreak scenarios. The results reveal both strengths and limitations of SCREAM, particularly in the accurate simulation of cloud transitions and midlevel convection, with varying degrees of sensitivity to horizontal and vertical resolution. Despite improvements at higher resolutions, key biases remain, including the abrupt transition from shallow to deep convection and the lack of congestus clouds. These findings underscore the need for further refinement in turbulence parameterizations and vertical grid resolution in GCPMs.
CDC LOCATe: discrepancies between self-reported level of maternal care and LOCATe-assessed level of maternal care among 463 birth facilities
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