Flexible piezoresistive pressure sensors have promising applications in wearable devices, artificial intelligence, and other fields. However, developing low-cost and high-performance pressure sensors still poses a great challenge. Herein, we utilize low-cost carbon black (CB) and multi-walled carbon nanotubes (MWCNTs) mixed in porous polydimethylsiloxane to assemble a flexible piezoresistive pressure sensor combined with interdigitated electrodes. Simultaneously, the COMSOL Multiphysics simulation analysis was performed to predict the sensing behavior of the pressure sensor, which was verified by experiments; the preparation of the pressure sensor was guided according to the prediction. Additionally, we studied the effects of the mixed conductive filler’s weight ratio, the shape of the interdigital electrode, and the line width and spacing of the interdigital electrode on the performance of the sensor. Based on the interaction of the 3D porous structure and the synergistic conductive network of CB/MWCNTs, the prepared pressure sensor exhibits a high sensitivity of 3.57 kPa–1 (∼21 kPa), a wide detection range of 0–275 kPa, fast response time (96 ms), fast recovery time (198 ms), good durability (about 3000 cycles), and good flexibility. Moreover, the fabricated sensor can monitor and recognize human activities (such as finger bending and mouse clicking), indicating that it has great potential in flexible wearable devices and other fields. It is worth noting that the preparation process of the entire pressure sensor was simple, low cost, and environmentally friendly, which provides a certain basis for industrial and commercial applications.
A new dynamic mesh algorithm is developed in this paper to realize the three-dimensional (3D) computational fluid dynamics (CFD) method for studying the small clearance transient flow field of tilting pad journal bearings (TPJBs). It is based on a structured grid, ensuring that the total number and the topology relationship of the grid nodes remain unchanged during the dynamic mesh updating process. The displacements of the grid nodes can be precisely recalculated at every time step. The updated mesh maintains high quality and is suitable for transient calculation of large journal displacement in FLUENT. The calculation results, such as the static equilibrium position and the dynamic characteristic coefficients, are consistent with the two-dimensional (2D) solution of the Reynolds equation. Furthermore, in the process of transient analysis, under conditions in which the journal is away from the static equilibrium position, evident differences appear between linearized and transient oil film forces, indicating that the nonlinear transient calculation is more suitable for studying the rotor-bearing system.
With the development of large-scale hydrologic modeling, computational efficiency is becoming more and more important. Rapid modeling and analysis are needed to deal with emergency environmental disasters. The Soil and Water Assessment Tool (SWAT) is a popular hydrologic model, which is less applied in large-scale watershed simulation because of its sequential characteristics. For improving the computational efficiency of the SWAT model, we present a new parallel processing solution for hydrologic cycle and calibration based on MPI (Message Passing Interface). We partitioned sub-basins during the processes based on a load balancing method. Then the calibration was parallelized using a master-slave scheme, in which different input parameters were allocated to different processes to run the hydrologic cycle and compute the function value. Because of the slow convergence and local optimization of the SCE-UA (Shuffled Complex Evolution-developed by University of Arizona) algorithm in SWAT calibration, a genetic algorithm (GA) is developed to optimize the calibration step. Then by dividing the default communicator into several sub-communicators, all the hydrologic cycles were parallelized in their own sub-communicators to achieve further acceleration. In this paper the results show speedups for the hydrologic cycle calculations, as well as in the optimized calibration step. In the case study, we tested the parallel hydrologic cycle by four processes, and got a speedup of 3.06. In the calibration section, after applying the GA optimization, with 10 cores, we got a speed increase of 8.0 in our GA parallel framework compared with the GA sequential calibration, which is much better than the original SWAT calibration. After the sub-communicators added, this process was speeded up even further. The study demonstrated that the GA parallel framework with multi-sub-communicators is an effective and efficient solution for the hydrologists in large scale hydrology simulations.
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