Effect of Hf additions on microstructure and mechanical properties of a Co-9Al-9W-2Ta alloy at room and high-temperatures

AbstractIn The microstructural evolution, room/high-temperature mechanical properties of a Co-9Al-9W-2Ta alloy with 2, 5, 6, 9 at.% Hf additions (referred as to 2Hf, 5Hf, 6Hf and 9Hf alloy hereafter, and content of W+Hf = 9 at.% for all alloys) prepared by arc-melting were investigated. It was found that the as-cast 2Hf∼6Hf alloys showed a microstructure composed of Co-base solid solution γ phase (γ-CoSS) and eutectic of γ+ intermetallic compound Co23Hf6, and the 9Hf alloy was composed of primary Co23Hf6 and (γ+ Co23Hf6) eutectic. While after 1170°C/8h solution and 800°C/100h aging, the cubic γ’ phase with a size of 200nm∼700nm homogeneously and coherently precipitates on the γ matrix for the 2Hf ∼ 6Hf alloys, no γ’ particles were found in the 9Hf alloy. The 2Hf alloy exhibits yield stress anomaly at temperatures above 600°C, and the temperature corresponding to the anomalies stress peak is at about 700°C. However, the other three alloys show no yield stress anomalies

The Improvement of Motor Cooling Through Stator Profile Optimization using CFD Analysis in Hermetic Scroll Compressors

With the increased pressure of cost, hermetic compressor sizing become an important part of the design optimization process, while maintain the same performance level in the same time. Hermetic compressor motor design also face the same challenge. However, reducing motor size for same compressor capacity will increase the motor power density, with the same motor cooling design as before, motor running temperature will be increased and this affect both motor life and reliability as well as passing UL certification requirement for compressors using OLP ( internal overload protector). Hermetic motor cooling improvement using thermal modelling has been investigated before by using thermal network method, with limited accuracy since this do not taken all thermal correlation between motor and compressors. (refer to Purdue paper: thermal modelling ro the motor in semi-hermetic screw refrigeration compressor under part load conditions) However, the real situation in terms of thermal and fluid distribution which affect motor cooling inside the compressor in much more complicated than a pure thermal lumped circuit can represent. With the usage of fluid and thermal coupled simulation method today, we can simulate and understand more accurately the correlation between motor and compressor heat transfer and fluid distribution to optimize motor cooling channel, both in static and dynamic stage, and keep motor temperature under the accepted level while main a good flow for the overall compressor performance. In this paper, different geometry of stator outer diameter profiles are investigated, to balance between the motor efficiency impacts versus the motor temperature increase, compressor and conclude the optimization in terms of stator outer profile for the compressor structure discussed in this paper. Motor efficiency results are calculated and also tested, motor cooling optimization also calculated and tested inside compressor. From the research work done here, we can see that by using CFD tool (ANSYS), compressor motor design engineers can find the optimal stator lamination design, and understand the biggest influence factor to motor cooling, but not important for motor electromagnetic design and performance. In future, if the design concentrated on the important factors, and optimize the motor cooling, compressor design in terms of sizing and cooling correlation would be well balanced between cost and performance

FGO-ILNS: Tightly Coupled Multi-Sensor Integrated Navigation System Based on Factor Graph Optimization for Autonomous Underwater Vehicle

Multi-sensor fusion is an effective way to enhance the positioning performance of autonomous underwater vehicles (AUVs). However, underwater multi-sensor fusion faces challenges such as heterogeneous frequency and dynamic availability of sensors. Traditional filter-based algorithms suffer from low accuracy and robustness when sensors become unavailable. The factor graph optimization (FGO) can enable multi-sensor plug-and-play despite data frequency. Therefore, we present an FGO-based strapdown inertial navigation system (SINS) and long baseline location (LBL) system tightly coupled navigation system (FGO-ILNS). Sensors such as Doppler velocity log (DVL), magnetic compass pilot (MCP), pressure sensor (PS), and global navigation satellite system (GNSS) can be tightly coupled with FGO-ILNS to satisfy different navigation scenarios. In this system, we propose a floating LBL slant range difference factor model tightly coupled with IMU preintegration factor to achieve unification of global position above and below water. Furthermore, to address the issue of sensor measurements not being synchronized with the LBL during fusion, we employ forward-backward IMU preintegration to construct sensor factors such as GNSS and DVL. Moreover, we utilize the marginalization method to reduce the computational load of factor graph optimization. Simulation and public KAIST dataset experiments have verified that, compared to filter-based algorithms like the extended Kalman filter and federal Kalman filter, as well as the state-of-the-art optimization-based algorithm ORB-SLAM3, our proposed FGO-ILNS leads in accuracy and robustness