A linear programming formulation for eco-driving over road slopes
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Compared to a conventional electrolyte concentration of 1 M HCOOK, the use of a highly concentrated 7.1 M HCOOK electrolyte increases the Faradaic efficiency (FE) ratio of C2H4/CO from 2.2 +- 0.3 to 18.3 +- 4.8 at -1.08 V vs. reversible hydrogen electrode (RHE) on a Cu gas-diffusion electrode. Based on electrochemical analysis and ab initio molecular dynamics (AIMD) simulation, the identity and concentration of the cation and anion play more important roles in controlling the CO2R reaction pathway than the bulk CO2 solubility and the bulk pH of electrolytes. In situ attenuated reflectance surface enhanced infrared absorption spectroscopy (ATR-SEIRAS) suggests that, unlike 1 M HCOOK, the *CO-bridge-binding mode on Cu is dominant in 7.1 M HCOOK electrolyte, which potentially results in less CO release and higher yield of C2H4. This study demonstrates that although we can tailor the electrolyte composition to shift product selectivity, the factors that control the product selectivity are numerous and cannot be distilled down into one correlated property-reactivity relationship.
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With the advent of faster computer processors and especially graphics processing units (GPUs) over the last few decades, the use of data-intensive machine learning (ML) and artificial intelligence (AI) has increased greatly, and the study of crystal nucleation has been one of the beneficiaries. In this study, we outline how ML and AI have been applied to address four outstanding difficulties of crystal nucleation: how to discover better reaction coordinates (RCs) for describing accurately non-classical nucleation situations; the development of more accurate force fields for describing the nucleation of multiple polymorphs or phases for a single system; more robust identification methods for determining crystal phases and structures; and as a method to yield improved course-grained models for studying nucleation.
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Residential consumers are moving to the center of electricity systems and their flexibility is seen as a key resource to integrate renewable energy sources and support the grid. However, residential flexibility capacities are not homogeneous, as they depend on household appliances, comfort patterns, occupancy, and climate conditions. In this work, we calculate the technical flexibility capacities of 45 consumer types in mainland Spain, organised according to income and regional criteria. We show that flexibility gaps exist at both regional and socioeconomic (income) levels with flexibility differences of up to 10 times more capacity between the household groups from the lowest to the highest capacities. These geographical and socioeconomic gaps in flexibility can lead to distortions in national markets and have the potential to exclude citizens from the provision of flexibility services. Our results show in quantitative terms that a consumer-centered approach without considering correcting measures nor these gaps in drafting energy policies may lead to increasing inequality levels in the residential sector. Under an economic competitive paradigm, households with lower income levels or located in regions with lower flexibility potential may be excluded from the provision of flexibility to the detriment of households with larger potential, raising justice concerns in a flexibility-based energy transition.
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Active control of plasma properties may be necessary to achieve stable operation of next-generation tokamaks over large time scales. Such control algorithms can regulate the plasma properties to avoid the onset of magnetohydrodynamic (MHD) instabilities. For instance, the global and local properties of the safety factor profile are linked to the onset of neoclassical tearing modes (NTMs). This work proposes a model-based control approach for deterring/delaying NTMs through active modulation of one of the safety factor properties - the gradient of the safety factor profile at a particular rational safety factor surface. In particular, a novel control-oriented model for the local safety factor gradient is developed. The nonlinear control model is governed by a nonautonomous ordinary differential equation that accounts for a given rational safety factor surface’s spatial variation over time. Further, to improve the controllability of the spatially evolving parameter, the control model treats ECH&CD positions, along with noninductive powers, as controllable variables. A nonlinear control algorithm based on feedback linearization with optimization is synthesized to achieve the objective of regulating the safety factor gradient around a given target. The proposed algorithm allocates optimal ECH&CD positions, in addition to auxiliary powers, at each time instant as the rational safety factor surface drifts to locations with a low control authority. Stability guarantees of the proposed control law are also discussed in this work. The proposed algorithm is tested for a DIII-D tokamak scenario in nonlinear simulations carried out using the Control Oriented Transport SIMulator (COTSIM). Both fixed and moving ECH&CD cases are studied, and their outcomes are compared. Simulation results demonstrate that enthusiastic regulation of the safety factor gradient can be achieved during the ramp-up and flat-top phases of tokamak operation in both fixed and moving ECH&CD cases. However, real-time updates of ECH&CD positions can prevent the saturation of auxiliary powers.
At National Ignition Facility (NIF), yield amplification due to alpha particle heating approached ~3 in the highest performing inertial confinement fusion (ICF) implosions, while yield amplification of ~15-30 is needed for ignition. Hydrodynamic instabilities are a major factor in degradation of implosions while understanding and mitigation of the instabilities are critical to achieving ignition. This article describes recent and planned hydrodynamic instability experiments with several focused platforms that have been developed to directly measure these instabilities in all phases of ICF implosions. Measurements of ripple-shock generation at OMEGA laser have indicated initial seeds for the instabilities in three ablators - plastic (CH), beryllium, and high-density carbon (HDC). Hydrodynamic Growth Radiography (HGR) platform was used to measure instability growth at the ablation front in the acceleration phase of implosions. This platform used pre-imposed 2-D perturbations for growth factor measurements at different perturbation wavelengths and was also used to measure growth of “native roughness” modulations, fill tubes, and capsule support membranes or “tents”. Also, in the acceleration phase several new experimental platforms have been or are being developed to measure instability growth at the ablator-ice interface. In the deceleration phase of implosions, “self-emission” and “self-backlighting” platforms were developed to measure perturbations near peak compression. This article reviews recent progress and results.