Numerical analysis of a fin-tube plate heat exchanger with winglets

In this presented work, numerical analysis of heat transfer and flow characteristic using longitudinal vortex generators (LVGS) in fin and flat tube heat exchanger has been presented. Conjugate heat transfer 3D numerical model has been developed and successfully carried out. Rectangular winglets were set in pairs, with downstream orientation. The effects of impact angles of (20⁰ , 30⁰, and 40⁰ ) as well as tubes and winglets were placed in one row lined arrangement and air flow by forward arrangement and backward arrangement. Reynolds number is ranged from 500 to 5000. The numerical results showed that in the range of the present study, the variation of these parameters can result in the increase of heat transfer. The study focuses on the Influence of the different parameters of VGs on heat transfer and fluid flow characteristics of one row lined circular-tube banks. The characteristics of average Nu number and skin friction coefficient are studied numerically by the aid of the computational fluid dynamics (CFD) commercial code of FLUENT ANSYS 14. The results showed increasing in the heat transfer and skin friction coefficient with the increasing of Re number. It has been observed that the overall Nuav number of one circular tubes increases by 23-31% ,by 23-43% and by 23-47% with angles of (20⁰, 30°, and 40⁰) respectively, in forward arrangement and the overall Nuav number of one circular tubes increases by 23-42%, by 23-46% and 23-52%with angles of (20⁰, 30°, and 40⁰) respectively, in backward arrangement, with increasing in the overall average of skin friction coefficient. Also the results showed that the rectangular winglet pairs (RWPs) can significantly improve the heat transfer performance of the fin and-tube heat exchangers with a moderate pressure loss penalty

Distributed learning of CNNs on heterogeneous CPU/GPU architectures

Convolutional Neural Networks (CNNs) have shown to be powerful classification tools in tasks that range from check reading to medical diagnosis, reaching close to human perception, and in some cases surpassing it. However, the problems to solve are becoming larger and more complex, which translates to larger CNNs, leading to longer training times that not even the adoption of Graphics Processing Units (GPUs) could keep up to. This problem is partially solved by using more processing units and distributed training methods that are offered by several frameworks dedicated to neural network training. However, these techniques do not take full advantage of the possible parallelization offered by CNNs and the cooperative use of heterogeneous devices with different processing capabilities, clock speeds, memory size, among others. This paper presents a new method for the parallel training of CNNs that can be considered as a particular instantiation of model parallelism, where only the convolutional layer is distributed. In fact, the convolutions processed during training (forward and backward propagation included) represent from $60$-$90$\% of global processing time. The paper analyzes the influence of network size, bandwidth, batch size, number of devices, including their processing capabilities, and other parameters. Results show that this technique is capable of diminishing the training time without affecting the classification performance for both CPUs and GPUs. For the CIFAR-10 dataset, using a CNN with two convolutional layers, and $500$ and $1500$ kernels, respectively, best speedups achieve $3.28\times$ using four CPUs and $2.45\times$ with three GPUs. Modern imaging datasets, larger and more complex than CIFAR-10 will certainly require more than $60$-$90$\% of processing time calculating convolutions, and speedups will tend to increase accordingly

Development of PAN (personal area network) for Mobile Robot Using Bluetooth Transceiver

In recent years, wireless applications using radio frequency (RF) have been rapidly evolving in personal computing and communications devices. Bluetooth technology was created to replace the cables used on mobile devices. Bluetooth is an open specification and encompasses a simple low-cost, low power solution for integration into devices. This research work aim was to provide a PAN (personal area network) for computer based mobile robot that supports real-time control of four mobile robots from a host mobile robot. With ad hoc topology, mobile robots may request and establish a connection when it is within the range or terminated the connection when it leaves the area. A system that contains both hardware and software is designed to enable the robots to participate in multi-agent robotics system (MARS). Computer based mobile robot provide operating system that enabled development of wireless connection via IP address

Real Time Airborne Monitoring for Disaster and Traffic Applications

Remote sensing applications like disaster or mass event monitoring need the acquired data and extracted information within a very short time span. Airborne sensors can acquire the data quickly and on-board processing combined with data downlink is the fastest possibility to achieve this requirement. For this purpose, a new low-cost airborne frame camera system has been developed at the German Aerospace Center (DLR) named 3K-camera. The pixel size and swath width range between 15 cm to 50 cm and 2.5 km to 8 km respectively. Within two minutes an area of approximately 10 km x 8 km can be monitored. Image data are processed onboard on five computers using data from a real time GPS/IMU system including direct georeferencing. Due to high frequency image acquisition (3 images/second) the monitoring of moving objects like vehicles and people is performed allowing wide area detailed traffic monitoring