Optimization of the Impeller Geometry for an Automotive Torque Converter Using Response Surface Methodology and Desirability Function

Response surface methodology (RSM) based on desirability function approach (DFA) is applied to obtain an optimal design of the impeller geometry for an automotive torque converter. The relative importance of six design parameters including impeller blade number, blade thickness, bias angle, scroll angle, inlet angle and exit angle is investigated using orthogonal design approach. The impeller inlet angle, exit angle and bias angle are found to exert the greatest influence on the overall performance of a torque converter, with two flow area factors being considered, namely 17% and 20%. Then, RSM together with central composite design (CCD) method is used to in-depth evaluate the interaction effect of the three key parameters on converter performance. The results demonstrate that impeller exit angle has the strongest impact on peak efficiency, with larger angles yielding the most favorable results. The stall torque ratio maximization is attainable with the increase of impeller bias angle and inlet angle together with smaller exit angle. In the end, an optimized design for the impeller geometry is obtained with stall torque ratio and peak efficiency increased by 1.62% and 1.1%, respectively. The new optimization method can be used as a reference for performance enhancement in the design process of impeller geometry for an automotive torque converter.

Effects of electrolysis process parameters on alumina dissolution and their optimization

The Box–Behnken design and desirability approach were used to investigate and optimize the process parameters for aluminum reduction cells related to alumina dissolution. The bath temperature, alumina content, current and alumina temperature were chosen as the design parameters. The content of cumulative dissolved alumina(CCDA) and the relative deviation from the target content(RDTC) were adopted as the responses. The interactive influence results show that increasing the bath temperature and alumina temperature, as well as decreasing the alumina content, can increase CCDA. Increasing the bath temperature and lowering the current are beneficial for obtaining a more uniform alumina distribution. The optimal operating parameters were determined to be as follows: bath temperature of 958.8 ℃, alumina content of 2.679 wt.%, current of 300 kA and alumina temperature of 200 ℃.

Assessment of dead layers thickness of an HPGe detector after an extended operating period using response surface methodology and Box–Behnken design

Purpose This work aims to study the increase in dead layer thickness of an HPGe N-type detector during its operational period from 2012 to 2018.Methods The dead layer was examined along three Ge-crystal surfaces,such as outer frontal,outer lateral,and inner lateral.These parameters were optimized using response surface methodology(RSM)with a Box–Behnken design(BBD).The Monte Carlo calculations using the GAMOS(Geant4-based Architecture for Medicine-Oriented Simulations)code were performed to evaluate the detector’s efficiency at different values of the inactive germanium layer.Results and conclusion The optimal combination of dead layer thickness has been identified using the desirability function approach,which is a useful tool to optimize multi-response problems.To find the variation in dead layer thickness over the operational period,the optimization procedure was reiterated for both experimental efficiencies measured in 2012 and 2018.The obtained results show that dead layers thickness has increased from 0.6141 mm to 0.7447 mm,0.0803 mm to 2.2721 mm,and 1.5012 mm to 1.6091 mm for the outer frontal,outer lateral,and inner lateral surfaces,respectively.