988 resultados para cost sharing


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Abstract: The potential variance in feedstock costs can have signifi cant implications for the cost of a biofuel and the fi nancial viability of a biofuel facility. This paper employs the Grange Feed Costing Model to assess the cost of on-farm biomethane production using grass silages produced under a range of management scenarios. These costs were compared with the cost of wheat grain and sugarbeet roots for ethanol production at an industrial scale. Of the three feedstocks examined, grass silage represents the cheapest feedstock per GJ of biofuel produced. At a production cost of €27/tonne (t) feedstock (or €150/t volatile solids (VS)), the feedstock production cost of grass silage per gigajoule (GJ) of biofuel (€12.27) is lower than that of sugarbeet (€16.82) and wheat grain (€18.61). Grass biomethane is also the cheapest biofuel when grass silage is costed at the bottom quartile purchase price of silage of €19/t (€93/t VS). However, when considering the production costs (full-costing) of the three feedstocks, the total cost of grass biomethane (€32.37/GJ of biofuel; intensive 2-cut system) from a small on-farm facility ranks between that of sugarbeet (€29.62) and wheat grain ethanol (€34.31) produced in large industrial facilities. The feedstock costs for the above three biofuels represent 0.38, 0.57, and 0.54 of the total biofuel cost. The importance of feedstock cost on biofuel cost is further highlighted by the 0.43 increase in the cost of biomethane when grass silage is priced at the top quartile (€46/t or €232/t VS) compared to the bottom quartile purchase price.

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Hunter-gatherers are often ascribed a “monistic” worldview at odds with the nature-society dichotomy. The centerpiece of this claim is that they view hunting as similar to sharing within the band and prey animals as part of a common sphere of sociality. This article challenges this thesis. An examination of the work of its main proponents shows that it conflates two different senses of “animal”—the flesh-and-blood animals of the hunt and the animal Spirit that is said to control the animals. The sharing motif in hunting makes sense with respect to the anthropomorphic Spirit but not to the animals hunted. The conditions of the hunt as a spatiotemporal event provide further grounds for skepticism toward the idea of hunting-as-sharing. Drawing on biologist Robert Hinde’s model of relationships, I argue that hunting represents an anonymous one-off interaction that cannot develop into a personal relationship, in stark contrast to the durable forms of personalized sociality associated with the hunter-gatherer band. This is not to deny the possibility of human-animal cosociality in the form of personal relationships but rather to redirect the search away from the hunt to the interface with domesticated animals.

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We study the scaling behaviors of a time-dependent fiber-bundle model with local load sharing. Upon approaching the complete failure of the bundle, the breaking rate of fibers diverges according to r(t)proportional to(T-f-t)(-xi) where T-f is the lifetime of the bundle and xi approximate to 1.0 is a universal scaling exponent. The average lifetime of the bundle [T-f] scales with the system size as N-delta, where delta depends on the distribution of individual fiber as well as the breakdown rule. [S1063-651X(99)13902-3].

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We develop a recursion-relation approach for calculating the failure probabilities of a fiber bundle with local load sharing. This recursion relation is exact, so it provides a way to test the validity of the various approximate methods. Applying the exact calculation to uniform and Weibull threshold distributions, we find that the most probable failure load coincides with the average strength as the size of the system N --> infinity.

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A critical load x(c) is introduced into the fiber-bundle model with local load-sharing. The critical load is defined as the average load per fiber that causes the final complete failure. It is shown that x(c) --> 0 when the size of the system N --> infinity. A power law for the burst-size distribution, D(DELTA) is-proportional-to DELTA(-xi) is approximately correct. The exponent xi is not universal, since it depends on the strength distribution as well as the size of the system.