A Semi-Active Vibration Isolator For 3D Printing On Shipboard

In the recent years, additive manufacturing (AM) (aka 3D printing)-has become a viable alternative to traditional manufacturing due to its unique advantages, such as enabling the fabrication of complex geometries at reduced weight and costs as well as allowing on-site fabrication for maintenance and repair. One specific application area of the AM is the navy vessels. During extended voyages, the navy vessels likely require the convenience of on-site fabrication of the malfunctioned parts. However, the shipboard equipment suffers from a broad range of external excitations arising not only from the waves but also from the vessel’s engines, which poses a concern for the quality of the 3D printed parts. Thus, efficient vibration isolation systems are needed for quality production. To this end, in this study, a novel semi-active vibration isolation system called Magnetorheological-based Semi-Active Vibration Isolator (MR-SAVI for short) was proposed. A comprehensive design methodology for the MR-SAVI, including both analytical and simulation modeling, was presented. A sophisticated optimization program was created to find the optimal values of the significant design parameters. The results were discussed, and future recommendations were made for the fabrication and characterization of the device

FPGA implementation of stair matrix based massive MIMO detection

Abstract Approximate matrix inversion based methods is widely used for linear massive multiple-input multiple-output (MIMO) received symbol vector detection. Such detectors typically utilize the diagonally dominant channel matrix of a massive MIMO system. Instead of diagonal matrix, a stair matrix can be utilized to improve the error-rate performance of a massive MIMO detector. In this paper, we present very large-scale integration (VLSI) architecture and field programmable gate array (FPGA) implementation of a stair matrix based iterative detection algorithm. The architecture supports a base station with 128 antennas, 8 users with single antenna, and 256 quadrature amplitude modulation (QAM). The stair matrix based detector can deliver a 142.34 Mbps data rate and reach a clock frequency of 258 MHz in a Xilinx Virtex -7FPGA. The detector provides superior error-rate performance and higher scaled throughput than most contemporary massive MIMO detectors