Design parameters Thermal performance

Effect of Uncertainties in Thermal Design Parameters. The parameters that are used ia the basic siting calculations of a heat exchanger iaclude heat-transfer coefficients tube dimensions, eg, tube diameter and wall thickness and physical properties, eg, thermal conductivity, density, viscosity, and specific heat. Nominal or mean values of these parameters are used ia the basic siting calculations. In reaUty, there are uncertainties ia these nominal values. For example, heat-transfer correlations from which one computes convective heat-transfer coefficients have data spreads around the mean values. Because heat-transfer tubes caimot be produced ia precise dimensions, tube wall thickness varies over a range of the mean value. In addition, the thermal conductivity of tube wall material cannot be measured exactiy, a dding to the uncertainty ia the design and performance calculations. 

If a heat exchanger is sized usiag the mean values of the design parameters, then the probabiUty, or the confidence level, of the exchanger to meet its design thermal duty is only 50%. Therefore, in order to increase the confidence level of the design, a proper uncertainty analysis must be performed for all principal design parameters. 

Recently, the fluidized bed membrane reactor (FBMR) has also been examined from the scale-up and practical points of view. Key factors affecting the performance of a commercial FBMR were analysed and compared to corresponding factors in the PBMR. Challenges to the commercial viability of the FBMR were identified. A very important design parameter was determined to be the distribution of membrane area between the dense bed and the dilute phase. Key areas for commercial viability were mechanical stability of reactor internals, the durability of the membrane material, and the effect of gas withdrawal on fluidization. Thermal uniformity was identified as an advantageous property of the FBMR. 

Numerical methods such as the Runge-Kutta-Gill fourth-order correct integration algorithm are required to simulate the performance of a nonisothermal tubular reactor. In the following sections, the effects of key design parameters on temperature and conversion profiles illustrate important strategies to prevent thermal runaway. 

Properties of the reactive fluid within the inner tube are identified by the subscript Rx, and represents the kinetic rate law that converts reactant A to products. Only one independent variable is required to simulate reactor performance because axial coordinate z and average residence time for the reactive fluid trx are related by the average velocity of the reactive fluid j)rx. In comparison with the single-pipe reactor discussed earlier, the double-pipe reactor contains two additional design parameters that can be manipulated to control thermal runaway radius ratio k and average velocity ratio x/f, defined as follows ... 

The reactor performance can be improved by changing design parameters. The effects of changing the pump coastdown half-time and the thermal centres elevation difference on maximum cladding temperature are shown in Figures XXV-16 and XXV-17, respectively. 

To design the optimal diffusion layer for a specific fuel cell system, it is important to be able to measure and understand all the parameters and characteristics that have a direct influence on the performance of the diffusion layers. This section will discuss in detail some of the most important properties that affect the diffusion layers, such as thickness, hydrophobicity and hydrophilicity, porosity and permeability (for both gas and liquids), electrical and thermal conductivity, mechanical properties, durability, and flow... 

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