This paper presents a comparative study of two translational parallel manipulators (TPMs) with three Degrees of Freedom (3-DOF) based on the orientation errors due to joint clearances. In fact, the kinematic and static models of the manipulators have been used to determine the analytical model of the orientation errors. Then, the maximum and the sensitivity of the orientation errors have been considered as criteria to compare the precision of the DELTA and the RAF manipulators. The maximum orientation error is determined by solving an optimization problem of the previous analytical model. The sensitivity of the orientation errors is divided into two types: one related to the sensitivity of the orientation errors to the geometric parameters and another one related to the sensitivity of the orientation error to the joint clearances. The results show that the RAF robot precision is more sensitive to the joint clearances than the DELTA one. However, this advantage of the DELTA is limited to a portion of the workspace, which is free from singular configurations.

Effects of geometric parameters of diffuser vanes as well as impeller micro grooves depth on the performance of a vertically suspended centrifugal pump have been studied. Different diffuser vanes height,leading angles, trailing angles, wrapping angles and furthermore, impeller micro grooves depths have been analyzed thoroughly. Numerical results have been verified by comparing experimental data. Results, without considering cavitation, reveal that diffuser vanes height has the profound impact on the vertically suspended centrifugal pump performance followed by vanes wrapping angle. Additionally, it is observed that delivered head and efficiency of micro-grooved impellers reduce more by flow rate enhancing rather than that of the original impeller.

This paper presents a general method to identify the geometric parameters of robots. An algorithm is given to calculate the identifiable geometric parameters. The robot location and the tool location parameters are taken into account. The algorithm is generalized to tree structure robots. The problem of selecting the optimum robot configurations to be used during the identification is discussed and a solution is proposed.

Automated methods for identifying and characterizing regular β-barrels from coordinate data have been developed to analyze and classify various kinds of barrel structures based on geometric parameters such as the barrel strand number (n) and shear number (S). In total, we find 1,316 barrels in the January 1998 release of Protein Data Bank. Of 1,316 barrels, 1,277 barrels had an even shear number, corresponding to 50 nonhomologous families. The (βα)8 triose phosphate isomerase (TIM) barrel (n = 8, S = 8) fold has the largest number of apparently nonhomologous entries, 16, although the trypsin like antiparallel (n = 6, S = 8) barrels (representing only three families) are the most common with 527 barrels. Of all the protein families that exhibit barrel structures, 68% are found to be various kinds of enzymes, the remainder being binding proteins and transport membrane proteins. In addition, the layers of side chains, which form the cores of barrels with S = n and S = 2n, are also analyzed. More sophisticated methods were developed for detecting TIM barrels specifically, including consideration of the amino acid propensities for the side chains that form the layers. We found that the residues on the outside of the eight stranded parallel β-barrel, buried by the α-helices, are much more hydrophobic than the residues inside the barrel.