Due to the absence of adequate control at different stages of complex manufacturing process, material and geometric properties of composite structures are often uncertain. For a secure and safe design, tracking the impact of these uncertainties on the structural responses is of utmost significance. Composite materials, commonly adopted in various modern aerospace, marine, automobile and civil structures, are often susceptible to low-velocity impact caused by various external agents. Here, along with a critical review, we present machine learning based probabilistic and non-probabilistic (fuzzy) low-velocity impact analyses of composite laminates including a detailed deterministic characterization to systematically investigate the consequences of source-uncertainty. While probabilistic analysis can be performed only when complete statistical description about the input variables are available, the non-probabilistic analysis can be executed even in the presence of incomplete statistical input descriptions with sparse data. In this study, the stochastic effects of stacking sequence, twist angle, oblique impact, plate thickness, velocity of impactor and density of impactor are investigated on the crucial impact response parameters such as contact force, plate displacement, and impactor displacement. For efficient and accurate computation, a hybrid polynomial chaos based Kriging (PC-Kriging) approach is coupled with in-house finite element codes for uncertainty propagation in both the probabilistic and non-probabilistic analyses. The essence of this paper is a critical review on the hybrid machine learning algorithms followed by detailed numerical investigation in the probabilistic and non-probabilistic regimes to access the performance of such hybrid algorithms in comparison to individual algorithms from the viewpoint of accuracy and computational efficiency.
The applications of lightweight planar parallel robotic manipulators are increasing enormously because of its various desirable characteristics such as low weight, lower inertia and higher stiffness. Higher accelerations and accuracies can be achieved in planar parallel manipulators. Also, shape memory alloy restoration technique (SMART)-based linear actuators are replacing huge and bulky linear actuators. This study presents the kinematic design of smart linearly actuated family of U-shape base planar parallel robotic manipulator. With the aid of solid modelling software, different available configurations were modelled and their workspace was analysed. The developed 3-DOF motion stages (18 unique configurations) were fabricated using fused deposition modelling process, and the top three configurations having higher workspace were further experimented. It is interesting to observe that the actual or experimental workspace of a particular manipulator configuration is further minimised from the predicted or feasible workspace. It is due to the presence of passive links, singularities, friction between the parts, heat dissipation, force distribution, stiffness, etc. The present study depicts the experimental workspace of the top three configurations, namely PPR-PRP-PRR, PRP-PPR-PRP and PRP-PPR-PRR. Since none of the experimental workspace observed is equal or higher than the model workspace, an efficiency loss in terms of workspace reduction was calculated to understand the acceptability of the configurations in different domains. Apart from the loss, the result disclosed that the actual workspace of all the manipulators was within the feasible workspace domain of mobile platform. The PPR-PRP-PRR manipulator was found to possess highest experimental workspace than other configurations. Note: P, P, and R refer to active prismatic, passive prismatic and passive revolute joints respectively.
The shape memory alloy (SMA) based actuators are replacing huge and bulky actuators because of its ability to provide high work per unit mass and serves as active prismatic joint to develop precise robotic manipulators. It also helps in developing a light weight manipulators with a simple actuation process. Here, the study presents the relationship between the contraction of Nitinol SMA prings and the input variables such as current and time to effectively interpret the behavioural complexity. In addition, the response of two Shape memory alloy springs in series combination has been discussed. The finite element analysis (FEA) of the SMA wire and spring has also been carried out to predict the fatigue life of SMA wire and spring. The result showed that the contraction rate of SMA spring increases with increase in current and vice-versa. Moreover, the range of current is classified based on its significance. The relationship of current, displacement and time parameters, during the actuation of SMA spring, is a second order polynomial regression model. The applied current and time have positive impact on the contractiong rate of SMA. Several polynomial regression models were developed in order to predict the precise amount of spring actuation. This study also predicts the range of current suitable for its actuation based on its application as actuator. The FEA result shows that the SMA springs can have high endurance stress limit which makes it unique as compared to other commercially available actuators. This study enables to predict the rate of contraction and the deflection trend of SMA based actuators for precise positioning applications.
The applications of light weight planar parallel robotic manipulators are increasing enormously because of their various desirable characteristics such as low weight, lower inertia, higher stiffness, energy efficiency etc. Higher accelerations and accuracies can be achieved using planar parallel manipulators (PPMs). Also, Shape Memory Alloy (SMA) based actuators are replacing huge and bulky actuators as SMA actuators provide higher work per unit mass as compared to other actuators and also undergoes silent actuation by simple actuation process. In the present study, three configurations (3PRP, PPR-2PRP and PRR-2PRP) of 3 degrees of freedom U-shaped base planar parallel robotic manipulator have been presented using SMA based smart actuators. The manipulator constitutes of one fixed base and one moving platform. The SMA spring acts as linear actuators mounted on the base which is connected to the end effector with the help of three limbs. A detailed experimental study was carried out to understand the workspace associated with each configuration. The movement of manipulators was investigated with the various combinations associated with the input SMA translation joints. And the study showed that the various configurations acquire different areas of workspace in the manipulator region. This study also shows the essence of SMA springs in PPMs for precise and accurate positioning of the end-effector and also its tracking ability for the development of future micro-motion stage. Note: P refers to Passive Prismatic Joint, R refers to Passive Revolute Joint and P refers to Active Prismatic Joint.
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