Disk motors are characterized by the axial direction of main magnetic flux and the variable length of the magnetic flux path along varying stator/rotor radii. This is why it is generally accepted that reliable electromagnetic calculations for such machines should be carried out using the FEM for 3D models. The 3D approach makes it possible to take into account an entire spectrum of different effects. Such computational analysis is very time-consuming, this is in particular true for machines with one magnetic axis only. An alternate computational method based on a 2D FEM model of a cylindrical motor is proposed in the paper. The obtained calculation results have been verified by means of lab test results for a physical model. The proposed method leads to a significant decrease of computational time, i.e. the decrease of iterative search for the most advantageous design.
The work presented in the paper concerns a very important problem of searching for string alignments. The authors show that the problem of a genome pattern alignment could be interpreted and defined as a measuring task, where the distance between two (or more) patterns is investigated. The problem originates from modern computation biology. Hardware-based implementations have been driving out software solutions in the field recently. The complex programmable devices have become very commonly applied. The paper introduces a new, optimized approach based on the Smith-Waterman dynamic programming algorithm. The original algorithm is modified in order to simplify data-path processing and take advantage of the properties offered by FPGA devices. The results obtained with the proposed methodology allow to reduce the size of the functional block and radically speed up the processing time. This approach is very competitive compared with other related works.
Short-circuit analysis is conducted based on the nodal impedance matrix, which is the inversion of the nodal admittance matrix. If analysis is conducted for sliding faults, then for each fault location four elements of the nodal admittance matrix are subject to changes and the calculation of the admittance matrix inversion needs to be repeated many times. For large-scale networks such an approach is time consuming and unsatisfactory. This paper proves that for each new fault location a new impedance matrix can be found without recalculation of the matrix inversion. It can be found by a simple extension of the initial nodal impedance matrix calculated once for the input model of the network. This paper derives formulas suitable for such an extension and presents a flowchart of the computational method. Numerical tests performed for a test power system confirm the validity and usefulness of the proposed method.