Braking performance and noise in excessive worn brake discs coated with HVOF thermal spray process

In this paper, two excessive worn brake discs of a light commercial vehicle were coated with High velocity oxygen fuel (HVOF) thermal spray process for reuse. The coated discs were compared with uncoated Original equipment manufacturer (OEM) D1 disc in terms of braking performance and noise. The D2 disc was coated with tungsten-carbide-cobalt (88 %WC-12 %Co) powder and NiCr (80/20) binder, and 500 Gm thick coating was obtained. The D3 disc was coated with Colmonoy-88 (Ni-W-Cr-B-Si) powder and NiCr (80/20) binder and 600 Gm thick coating was obtained. Several test procedures (e.g. bedding, vibration, and structural-strength tests) was applied to three discs using inertia brake dynamometer. Results showed that coated D2 disc with tungsten carbide cobalt provided lower brake noise and higher brake performance compared with OEM disc. Considering the coefficient of friction and temperature, coated D3 disc has approximately equal braking performance with OEM D1 disc despite the high braking noise value.     

A direct and neural controller performance study with beam wandering mitigation control in free space optical link

The beam wander on the detector plane is one of the main causes for major power loss which severely degrades the performance of Free Space Optical (FSO) link. Designing a suitable controller to correct the beam motion at a faster rate to increase the beam stability becomes significant. This paper presents an investigation on the performance of two types of controller designed for aiming a laser beam to be at a particular point under dynamic disturbances. The first design is based on the Taguchi’s method (direct controller) while the second is the Artificial Neural Network (ANN) method (neural-controller). These controllers process the beam location information and generate the necessary outputs to mitigate the beam wandering. The pipelined-parallel architecture for both controllers are developed in a Field Programmable Gate Array (FPGA) and installed at the receiver station. Evidence of the suitability and the effectiveness of the proposed controller in terms of prediction exactness, prediction error, reduction of focal point wander, response to impulse and scintillation are provided through experimental results from the FSO link established for the horizontal range of 0.5 km at an altitude of 15.25 m.     

Monthly flow forecast for Mississippi River basin using artificial neural networks

Long-term monthly flow forecasts are essential for decision making in a river basin system. Many studies have already been reported on monthly as well as seasonal forecast using artificial neural networks (ANNs). This study demonstrates that monthly forecasts can be significantly improved if the input variables in ANN models are chosen with due consideration, even if number of training patterns are less. Monthly forecast models up to 12-month lead-time have been developed for Mississippi River in USA. It is seen that direct forecast with only antecedent flows as inputs does not improve the result. It is better to develop individual models for each month separately with information from previous years for the same month. Further, the forecast is found to significantly improve if the difference in predicted and actual flows is also included as one of the input variables (i.e. error updating), particularly where there is a clearly observed pattern in the historical information.     

A misdirected route avoidance using random waypoint mobility model in wireless sensor network

Wireless Networks - In this paper, a novel method is proposed to reduce the number of route misdirection to increase network throughput. This method increases the network throughput by accurately...     

Effective Scheduling Policies to Optimize Radio Resources between NR-gNodeB and Device to Device Systems in 5G

Wireless Personal Communications - Technology behind every communication systems, especially commercial applications requires periodic modifications to satisfy the subscriber’s desires. A...     

HYDROGEN RESOURCES : CONVERSION OF BLACK LIQUOR TO HYDROGEN RICH GASEOUS PRODUCTS

Abstract

Two precipitates were obtained from original black liquor by using hydrochloric acid and carbon dioxide. The precipitates were liqufied and gasificated by non-catalytic and catalytic runs at gradually elevated temperatures. The amount of gaseous products increased with increasing temperature and percent of catalyst. The percent of hydrogen in the obtained gas mixture was the highest in potassium carbonate catalytic runs (37 %).     

Stable modeling based control methods using a new RBF network

This paper presents a novel model with radial basis functions (RBFs), which is applied successively for online stable identification and control of nonlinear discrete-time systems. First, the proposed model is utilized for direct inverse modeling of the plant to generate the control input where it is assumed that inverse plant dynamics exist. Second, it is employed for system identification to generate a sliding-mode control input. Finally, the network is employed to tune PID (proportional + integrative + derivative) controller parameters automatically. The adaptive learning rate (ALR), which is employed in the gradient descent (GD) method, provides the global convergence of the modeling errors. Using the Lyapunov stability approach, the boundedness of the tracking errors and the system parameters are shown both theoretically and in real time. To show the superiority of the new model with RBFs, its tracking results are compared with the results of a conventional sigmoidal multi-layer perceptron (MLP) neural network and the new model with sigmoid activation functions. To see the real-time capability of the new model, the proposed network is employed for online identification and control of a cascaded parallel two-tank liquid-level system. Even though there exist large disturbances, the proposed model with RBFs generates a suitable control input to track the reference signal better than other methods in both simulations and real time.