PVC compounding with renewable materials is reviewed, including raw materials production technology, market dynamics and technical aspects of the finished products compared with current solutions. PVC resins produced from renewable ethylene and plasticisers obtained from vegetable oils are described and evaluated. An overview of the market changes that have enabled the competitiveness of biobased materials is also considered, outlining the agricultural technology and challenges and the state of the art of chemical processes to obtain renewable components for PVC formulating. Options to formulate with renewable components are discussed on the basis of a review of the literature. It is concluded that a PVC compound formulated with renewable resin and plasticiser is not only viable, but represents a natural evolution towards a more sustainable PVC supply chain. As a sample calculation, 1 ton of a clear flexible vinyl formulation with 100 phr resin and 60 phr plasticiser would remove 2?3 tons of CO 2 from the atmosphere.
Effectiveness of active control of micro jets has been examined by conducting experiments through an abruptly expanded axi-symmetric duct in a view to control base pressure. For this purpose, 1mm orifice diameter micro jets have been deployed at an interval of 90 0 along the exit diameter of the nozzle. The experiments have been conducted by considering three flow parameters at three levels. Mach number (M), length to diameter (L/D) ratio and area ratio (AR) are the three parameters used to conduct and analyze the flow experiments. Base pressure is considered to be the response variable. The experimentation has been carried out for two cases, i) without active control; ii) with active control. An L9 orthogonal array has been implemented to plan the experiments. It is observed that the control becomes effective for lower area ratios when compared to the higher ones. In addition to this, at high area ratios suction at the base decreases and hence base pressure continuous to diminish with increasing L/D until it reaches a value of L/D=6. The obtained experimental results are subjected to multiple linear regression analysis and Analysis of variance (ANOVA). The performances of the two linear regression models were tested for their prediction accuracy with the help of 15 random test cases. It is observed that, both linear regression models for base pressure without and with control are statistically adequate and capable of making accurate predictions. Furthermore, this work also concludes that, Mach number is the most significant factor affecting base pressure followed by area ratio and L/D ratio for both cases of experimentation. The obtained experimental results are further validated by CFD analysis and are found to be in good concurrence with each other.
Sudden expansion of flow in supersonic flow regime has gained relevance in the recent pasts for a wide run of applications. A number of kinematic as well as geometric parameters have been significantly found to impact the base pressure created within the suddenly expanded stream. The current research intends to create a predictive model for base pressure that is established in the abruptly extended stream. The artificial neural network (ANN) approach is being utilized for this purpose. The database utilized for training the network was assembled utilizing computational fluid dynamics (CFD). This was done by the design of experiments based L27 Orthogonal array. The three input parameters were Mach number (M), nozzle pressure ratio (NPR) and area ratio (AR) and base pressure was the output parameter. The CFD numerical demonstrate was approved by an experimental test rig that developed results for base pressure, and used a nozzle and sudden extended axissymmetric duct to do so. The ANN architecture comprised of three layers with eight neurons in the hidden layer. The algorithm for optimization was Levenberg-Marquardt. The ANN was able to successfully predict the base pressure with a regression coefficient R 2 of less than 0.99 and RMSE=0.0032. The importance of input parameters influencing base pressure was estimated by using the ANN weight coefficients. Mach number obtained a relative importance of 47.16% claiming to be the most dominating factor.
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