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Some variation in the topological distribution of fibers inside the matrix phase of fiber reinforced polymers (FRP) is inevitable. Such irregularities can accelerate moisture diffusion and adversely affect the life of FRP. This paper presents a hierarchical technique for characterization of clustered microstructures and their transient moisture diffusion response. The clustering descriptors are derived for different fiber volume fractions (dilute to dense) for the quantitative definition of a given fiber matrix architecture. The metrics are normalized to remove dependence on volume fraction. The microstructures are analyzed for Fickian moisture diffusion. Suggested descriptors show a good correlation with transient diffusion response in relation to saturation time. The results can be used to predict the time-dependent moisture diffusion response of FRPs for any given fiber volume fraction.

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper deals with the fault detection, isolation (FDI) and reconfiguration of the locomotion of a bipedal-legged robot. Initially, the planar model of the legged robot in the vertical plane is developed using a bond graph (BG) approach. Then, the planar BG model of the legged robot is extended to the three-dimensional legged robot. Two individual motors are used to actuate the prismatic leg of the robot for locomotion. The BG simulation provides results for straight walking based on an oscillating cylinder mechanism and the turning motion of the legged robot are discussed. The prototype model of the legged robot is also developed and experimentation is done for straight and inclined plane applications. Finally, an FDI technique for the three-dimensional model of a legged robot is developed for the generation of fault indicators (i.e., analytical redundancy relations; ARRs) in the presence of system failure. The ARRs are derived from the BG model of the legged robot during the occurrences of the fault. The experimental results are validated with the simulation results for FDI and reconfiguration when the robot manoeuvres in a U-shaped path. The real-time fault diagnosis and reconfiguration for locomotion of the legged robot is possible with this FDI approach. [ABSTRACT FROM AUTHOR]

This work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using 'S-function' directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases. [ABSTRACT FROM AUTHOR]

This work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using 'S-function' directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases. [ABSTRACT FROM AUTHOR]

Gas metal arc welding (GMAW) is extensively used for joining of different graded steels as well as aluminium and other nonferrous materials. GMAW offers clean welding with low defects without using flux and suitable for different positional welding. In the present work, a fabricated automatic movement setup is used for GMAW to study the influences of four different process parameters during joining of austenitic stainless steel AISI 316 using AISI 304 (ER304) filler wire. With this setup, welding is carried out maintaining a constant contact tube-to-workpiece (CTW) distance and uniform heat input. Experimental results and subsequent analysis show that the toughness is most significantly influenced by voltage followed by welding speed, gas flow rate, and current. Toughness reduces with the increase in shielding gas flow rate and welding speed as austenite and traces of retained delta ferrite may be present due to high solidification rate. Metallurgical observations by X-ray diffraction (XRD) and scanning electron microscopy indicate that solidification mode is mainly characterized by formation of fully austenite or austenite and ferrite at cell and dendritic boundaries. XRD results revealed that higher toughness is observed due to minimum formation of carbides. [ABSTRACT FROM AUTHOR]

In the present work, a simple arrangement is made to provide double layer shielding gas supply in addition to primary shielding during gas metal arc welding (GMAW) of two dissimilar stainless steels, i.e., AISI 316 and duplex 2205. Influences of double layer shielding in addition to five more process parameters like welding current, voltage, material of the electrode wire, the type of primary shielding gas, and flow rate on joint tensile strength and fusion zone microhardness are studied. An experimental design technique is used to design the experimental conditions and the results are analyzed to observe the influences of each process parameter and their interactions. The tensile strength is more influenced by the electrode material and the type of shielding, whereas current, interaction between current × voltage and current × flow rate significantly influence microhardness. Welding voltage influences both tensile strength and microhardness. Double layer shielding with CO2as an outer shielding layer helps in controlling the cooling rate which improves the tensile strength and microhardness. Microstructural observations by scanning electron microscopy reveal that moderate to low heat input with a single layer of shielding results in poor joint strength and severe damage or lack of fusion, and the duplex 2205 filler gives the maximum joint strength due to the presence of a ferrite structure. [ABSTRACT FROM AUTHOR]