7 resultados para refrigeration prices

em Indian Institute of Science - Bangalore - Índia


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A thermodynamic analysis is presented for the two stage thermal compression process for an adsorption refrigeration cycle with HFC-134a as the working fluid and activated carbon as the adsorbent. Three specimens of varying achievable packing densities were evaluated. The influence of evaporating, condensing/adsorption and desorption temperatures was assessed through three performance indicators, namely,the uptake efficiency, the coefficient of performance and the exergetic efficiency. Conditions under which a two stage thermal compression process performs better than the single stage unit are identified. It is concluded that two stage thermal compression will be a viable proposition when the heat source temperature is low or when adsorption characteristics are weak or when adequate packing densities are difficult to realize. (C) 2008 Elsevier Ltd. All rights reserved.

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This paper presents the results of an investigation on the efficacy of hybrid compression process for refrigerant HFC 134a in cooling applications. The conventional mechanical compression is supplemented by thermal compression using a string of adsorption compressors. Activated carbon is the adsorbent for the thermal compression segment. The alternatives of bottoming either mechanical or thermal compression stages are investigated. It is shown that almost 40% energy saving is realizable by carrying out a part of the compression in a thermal compressor compared to the case when the entire compression is carried out in a single-stage mechanical compressor. The hybrid compression is feasible even when low grade heat is available. Some performance indictors are defined and evaluated for various configurations.

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In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.

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The use of binary fluid systems in thermally driven vapour absorption and mechanically driven vapour compression refrigeration and heatpump cycles has provided an impetus for obtaining experimental date on caloric properties of such fluid mixtures. However, direct measurements of these properties are somewhat scarce in spite of the calorimetric techniques described in the literature being quite adequate. Most of the design data are derived through calculations using theoretical models and vapour-liquid equilibrium data. This article addresses the choice of working fluids and the current status on the data availability vis-a-vis engineering applications. Particular emphasis is on organic working fluid pairs.

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A comparative study has been carried out of R-12, 22, 125, 134a, 152a, 218, 245, 500, 502, 507 and 717 as working fluids in a vapour-compression refrigeration system. Two performance parameters were defined, which are expressed in reduced quantities for a corresponding-states comparison of these refrigerants in the temperature range -20 to 50-degrees-C. One is based on the product of temperature drop to pressure penalty ratio and the available volumetric heat of vaporisation at the evaporator; the other considers the effect of isentropic compression in the ideal gas state. It was shown that R-125, 507 and 218 could be better alternatives to R-12 than R-134a. Among these, R-218 has a lower maximum cycle pressure.

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The authors describe the constructional features of a controller for operating an autonomous refrigeration unit powered by a field of photovoltaic panels and backed up by a generator set. The controller enables three voltage levels of operation of an inverter to meet the start, run and off cycle conditions of the refrigerator compressor. The algorithm considers several input and output parameters and status signals from each subsystem of the unit to deduce a control strategy. Such units find application for storage of vaccines and life-saving medicines requiring uninterrupted refrigeration, in medical shops, rural health centres, veterinary laboratories etc.

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The purpose of this paper is to present exergy charts for carbon dioxide (CO2) based on the new fundamental equation of state and the results of a thermodynamic analysis of conventional and trans-critical vapour compression refrigeration cycles using the data thereof. The calculation scheme is anchored on the Mathematica platform. There exist upper and lower bounds for the high cycle pressure for a given set of evaporating and pre-throttling temperatures. The maximum possible exergetic efficiency for each case was determined. Empirical correlations for exergetic efficiency and COP, valid in the range of temperatures studied here, are obtained. The exergy losses have been quantified. (C) 2003 Elsevier Ltd. All rights reserved.