Dr. Suib is a Board of Trustees Distinguished Professor of Chemistry and received the CT Medal of Science for his work in catalysis, semiconductors and ceramic composites. He received a B. S. degree in chemistry and geology at the State University College of New York at Fredonia. His graduate and postdoctoral training was completed at the University of Illinois at Champaign Urbana. In 1980, Steve joined UConn’s faculty in the Department of Chemistry and served as the head of the department for 10 years. He is a Fellow of the American Chemical Society and the American Institute of Chemists.

Materials by Design

The magnetorheological fluids are classified as smart materials with controllable rheological properties. The fast growing application of magnetorheological fluids in recent years has increased the...

A review on the simulation and modeling of magnetorheological fluids

Joining of carbon fibre reinforced polymer (CFRP) composites and aluminium alloys – A review Part A Applied science and manufacturing

In this paper, we describe an automatic detection system to recognise welding defects in radiographic images. In a first stage, image processing techniques, including noise reduction, contrast enhancement, thresholding and labelling, were implemented to help in the recognition of weld regions and the detection of weld defects. In a second stage, a set of geometrical features which characterise the defect shape and orientation was proposed and extracted between defect candidates. In a third stage, an artificial neural network (ANN) for weld defect classification was used. With the aim of obtaining the best performance of ANN three different methods for improving network generalisation was used. The results was compared with a method without generalisation. For the input layer, the principal component analysis technique was used in order to reduce the number of feature variables; and, for the hidden layer, a different number of neurons was used.

An automatic system of classification of weld defects in radiographic images

Emergence of Controlled Environment Agriculture (CEA) ranging from computer controlled water irrigation system to lightning and ventilation has changed the conventional scenario of farming. This paper proposes and demonstrate an economical and easy to use arduino based controlled irrigation system. The designed system deals with various environmental factors such as moisture, temperature and amount of water required by the crops using sensors like water flow sensor, temperature sensor and soil moisture sensor. Datas are collected and received by arduino which can be linked to an interactive website which show the real time values along with the standard values of different factor required by a crop. This allows user to control irrigation pumps and sprinklers from far distance through a website and to meet the standard values which would help the farmer to yield maximum and quality crops. Studies conducted on laboratory prototype suggested the designed system to be applicable which can be implemented.

Arduino-based smart irrigation using water flow sensor, soil moisture sensor, temperature sensor and ESP8266 WiFi module

This article reports on the design and development work on a modular pole climbing robot. Modularity was achieved by ensuring similar repeated structures can be coupled and controlled in almost similar fashion. The design considers the rudimentary aspect of climbing and adopts grasp-push-grasp motion arrangement. The resulting design consists of two grippers for grasping and two central arms for climbing and lowering, all of which employs pneumatic cylinders. The whole climbing motion was achieved in six steps and the climbing speed is determined from the rate of filling the pneumatic cylinders involved. Parallel four-bar linkages arrangement was used to ensure the horizontal orientation of the grippers to prevent locking. The structure of the robot are made from aluminum with pin joints throughout to allow for easy assembly. PLC was used at this stage for the motion control. The developed robot can climb a 150 mm diameter pole at a speed of 0.6 m/min.

Development of a low-cost modular pole climbing robot

Magneto-rheological (MR) valve is one of the devices generally used to control the speed of Hydraulic actuator of MR fluid. The performance of valve depends on the magnetic circuit design. Present study deals with a new design of MR valve. A mathematical model for the MR valve is developed and the simulation is carried out to evaluate the newly developed MR valve. The design of the magnetic circuit is accomplished by magnetic finite element software such as Finite Element Method Magnetic (FEMMR). The model dimensions of MR valve, material properties are taken into account. The results of analysis are presented in terms of magnetic strength H and magnetic flux density B. The simulation results based on the proposed model indicate that the efficiency of the proposed MR valve is superior to two other types of MR valves, under the same magnetic flux density. As a conclusion, the new valve design has improved the efficiency of MR valve significantly.

Finite element modeling and simulation of proposed design magneto-rheological valve

The Effect of Feed Rate and Cutting Speed to Surface Roughness

Machine vision has been widely deployed in many industrial applications. However, for solder joint inspection, it has yet to reach the desired maturity level. This paper presents a new inspection methodology using images from both orthogonal and oblique viewing directions to the solder joint. The oblique view was made possible through a mirror pyramid. Image capturing and selection of the soldered region were done manually, but could be automated if the positional coordinates were known. Combined orthogonal and oblique gray-level images at the pixel level were directly input to an artificial neural network (ANN) for processing, eliminating the need to determine heuristic features. Learning vector quantization architecture was used as the classifier. This study was focused on geometry-related joint defects, namely, excess and insufficient. Comparisons show that the oblique view provides more useful information compared to the orthogonal view. The experimental results indicate that the proposed system has an improved recognition rate and good resilience to noise.

Solder joint inspection with multi-angle imaging and an artificial neural network

Cooperative AUV performance and efficiency is directly related to its power efficiency. The power consumption for this type of underwater vehicle is influenced by its motion needed because most of the power is spent for thruster to produce thrust. Drag force is known as main contribution to resist the body motion. In this paper, the behavior of this force is study by using Computational fluid dynamic approach (CFD). Two position arrangement of cooperative AUV was chosen to study the drag variation. First, the distance effect between two AUV was studied to represent the basic position arrangement of cooperative AUV. second position arrangement is studied to look at the effect of different position arrangement. The comparison between distance and position arrangement was discuss in detail in this paper. The study show that the distance behind the leading AUV does not give much effect to drag force, but the position arrangement show significant important to drag force.

/pdf/cfd-simulation-of-cooperative-auv-motion-4x06jk55j6.pdf

Zahurin Samad

Papers

Development of a low-cost modular pole climbing robot

Finite element modeling and simulation of proposed design magneto-rheological valve

The Effect of Feed Rate and Cutting Speed to Surface Roughness

Solder joint inspection with multi-angle imaging and an artificial neural network

CFD simulation of cooperative AUV motion