32,618 research outputs found

    Quantifying the Economic Case for Electric Semi-Trucks

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    There has been considerable interest in the electrification of freight transport, particularly heavy-duty trucks to downscale the greenhouse-gas (GHG) emissions from the transportation sector. However, the economic competitiveness of electric semi-trucks is uncertain as there are substantial additional initial costs associated with the large battery packs required. In this work, we analyze the trade-off between the initial investment and the operating cost for realistic usage scenarios to compare a fleet of electric semi-trucks with a range of 500 miles with a fleet of diesel trucks. For the baseline case with 30% of fleet requiring battery pack replacements and a price differential of US\50,000,wefindapaybackperiodofabout3years.Basedonsensitivityanalysis,wefindthatthefractionofthefleetthatrequiresbatterypackreplacementsisamajorfactor.Forthecasewith100thepaybackperiodcouldbeashighas56years.Weidentifythepriceofelectricityasthesecondmostimportantvariable,whereapriceofUS50,000, we find a payback period of about 3 years. Based on sensitivity analysis, we find that the fraction of the fleet that requires battery pack replacements is a major factor. For the case with 100% replacement fraction, the payback period could be as high as 5-6 years. We identify the price of electricity as the second most important variable, where a price of US0.14/kWh, the payback period could go up to 5 years. Electric semi-trucks are expected to lead to savings due to reduced repairs and magnitude of these savings could play a crucial role in the payback period as well. With increased penetration of autonomous vehicles, the annual mileage of semi-trucks could substantially increase and this heavily sways in favor of electric semi-trucks, bringing down the payback period to around 2 years at an annual mileage of 120,000 miles. There is an undeniable economic case for electric semi-trucks and developing battery packs with longer cycle life and higher specific energy would make this case even stronger.Comment: 12 pages, 3 figures, 1 table, 5 pages of S

    Role of anisotropy in determining stability of electrodeposition at solid-solid interfaces

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    We investigate the stability of electrodeposition at solid-solid interfaces for materials exhibiting an anisotropic mechanical response. The stability of electrodeposition or resistance to the formation of dendrites is studied within a linear stability analysis. The deformation and stress equations are solved using the Stroh formalism and faithfully recover the boundary conditions at the interface. The stability parameter is used to quantify the stability of different solid-solid interfaces incorporating the full anisotropy of the elastic tensor of the two materials. Results show a high degree of variability in the stability parameter depending on the crystallographic orientation of the solids in contact, and point to opportunities for exploiting this effect in developing Li metal anodes.Comment: 10 pages, 5 figures, 1 table, v3: corrected typos, modified figures, v2: added references, corrected typo

    Dynamics of Attention in Depth: Evidence from Mutli-Element Tracking

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    The allocation of attention in depth is examined using a multi-element tracking paradigm. Observers are required to track a predefined subset of from two to eight elements in displays containing up to sixteen identical moving elements. We first show that depth cues, such as binocular disparity and occlusion through T-junctions, improve performance in a multi-element tracking task in the case where element boundaries are allowed to intersect in the depiction of motion in a single fronto-parallel plane. We also show that the allocation of attention across two perceptually distinguishable planar surfaces either fronto-parallel or receding at a slanting angle and defined by coplanar elements, is easier than allocation of attention within a single surface. The same result was not found when attention was required to be deployed across items of two color populations rather than of a single color. Our results suggest that, when surface information does not suffice to distinguish between targets and distractors that are embedded in these surfaces, division of attention across two surfaces aids in tracking moving targets.National Science Foundation (IRI-94-01659); Office of Naval Research (N00014-95-1-0409, N00014-95-1-0657

    Attention in Depth: Disparity and Occlusion Cues Facilitate Multi-Element Visual Tracking

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    Human observers can track up to five moving targets in a display with ten identical elements (Pylyshyn and Storm, 1988; Yantis, 1992). Previous experiments manipulated element trajectories to prevent intersections of element boundaries, evidently in the belief that transient overlaps among homogeneous elements make the task too hard. We examine whether depth cues such as occlusion (T-junctions) and disparity affect performance in a tracking task when element boundaries, as projected onto the two-dimensional plane of the monitor screen, are allowed to intersect. Elements move smoothly in depth, as well as in horizontal and vertical position, throughout a 7-second tracking period. A probe is then flashed, and subjects report whether the flash occurred on a target or on a non-target. Overlapping circular objects form T-junctions when shaded to appear like spheres or figure eight regions when rendered as disks. Two factors, disparity and T-junctions, are considered. Results from eight naive observers show that performance improves for displays with depth information (T-junctions or disparity), suggesting that depth cues are useful for multi-element tracking.National Science Foundation (IRI-94-01659); Office of Naval Research (N00014-92-J-1309, N00014-95-1-0657, N00014-94-1-0597, N00014-95-1-0409

    Stochastic Neural Networks with the Weighted Hebb Rule

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    Neural networks with synaptic weights constructed according to the weighted Hebb rule, a variant of the familiar Hebb rule, are studied in the presence of noise(finite temperature), when the number of stored patterns is finite and in the limit that the number of neurons NN\rightarrow \infty. The fact that different patterns enter the synaptic rule with different weights changes the configuration of the free energy surface. For a general choice of weights not all of the patterns are stored as {\sl global} minima of the free energy function. However, as for the case of the usual Hebb rule, there exists a temperature range in which only the stored patterns are minima of the free energy. In particular, in the presence of a single extra pattern stored with an appropriate weight in the synaptic rule, the temperature at which the spurious minima of the free energy are eliminated is significantly lower than for a similar network without this extra pattern. The convergence time of the network, together with the overlaps of the equilibria of the network with the stored patterns, can thereby be improved considerably.Comment: 14 pages, OKHEP 93-00
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