Ganesh Tamadapu

Bio: Ganesh Tamadapu is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Hyperelastic material & Isotropy. The author has an hindex of 7, co-authored 13 publications receiving 151 citations. Previous affiliations of Ganesh Tamadapu include Royal Institute of Technology & Indian Institute of Technology Kharagpur.

Finite inflation analysis of a hyperelastic toroidal membrane of initially circular cross-section

Abstract: In this work, we have studied the finite inflation of a hyperelastic toroidal membrane with an initially circular cross-section under internal pressure. The membrane material is assumed to be a Mooney–Rivlin solid. The inflation problem is formulated as a variational problem for the total potential energy comprising the membrane strain energy and internal energy of the gas. The problem is then discretized and solved up to a high degree of accuracy through a sequence of approximations based on the Ritz expansion of the field variables combined with a potential energy density perturbation and Newton–Raphson method. The effects of the inflation pressure and material properties on the state of stretch and geometry of the inflated torus have been studied, and some interesting results have been obtained. The stability of the inflated configurations in terms of impending wrinkling of the membrane has been investigated on the principal stretch parameter plane for both isotropic and anisotropic (transversely isotropic) material cases. Certain shape factors quantifying the geometry of the membrane have been defined and calculated which characterize the cross-sectional shape and size of the torus during inflation.

Effect of curvature and anisotropy on the finite inflation of a hyperelastic toroidal membrane

Abstract: The problem of finite inflation of a hyperelastic toroidal membrane under uniform internal pressure is considered in this paper. The work consists of the following two aspects of the inflation problem. Firstly, a formulation for solving the inflation problem efficiently by directly integrating the differential equations of equilibrium without discretization is proposed. The results obtained are compared with those obtained using a discretization method proposed earlier. Secondly, the effects of the geometric and material parameters of the membrane and the internal pressure on the inflation and its stability are studied. The roles of the curvature (specifically, the eigenvalues of the shape operator) of the toroidal geometry and the membrane material parameter on the distortion of the cross-section and occurrence of wrinkling instability are clearly brought out. Based on the Cauchy stress resultants, the limits on the inflation to avoid wrinkling are determined. It is observed that the limit point pressure of the membrane is inversely proportional to the geometric parameter of the torus. The proportionality constant involved is found to vary linearly with the material parameter of the membrane, and involves two universal constants for the toroidal geometry.

Geometrical feature of the scaling behavior of the limit-point pressure of inflated hyperelastic membranes.

Abstract: The occurrence of the limit-point instability is an intriguing phenomenon observed during stretching of hyperelastic membranes. In toy rubber balloons, this phenomenon may be experienced in the sudden reduction in the level of difficulty of blowing the balloon accompanied by its rapid inflation. The present paper brings out a link between the geometry and strain-hardening parameter of the membrane, and the occurrence of the limit-point instability. Inflation of membranes with different geometries and boundary conditions is considered, and the corresponding limit-point pressures are obtained for different strain-hardening parameter values. Interestingly, it is observed that the limit-point pressure for the different geometries is inversely proportional to a geometric parameter of the uninflated membrane. This dependence is shown analytically, which can be extended to a general membrane geometry. More surprisingly, the proportionality constant has a power-law dependence on the nondimensional material strain-hardening parameter. The constants involved in the power-law relation are universal constants for a particular membrane geometry.

Detection of Alzheimer's disease by displacement field and machine learning.

Abstract: Aim. Alzheimer's disease (AD) is a chronic neurodegenerative disease. Recently, computer scientists have developed various methods for early detection based on computer vision and machine learning techniques. Method. In this study, we proposed a novel AD detection method by displacement field (DF) estimation between a normal brain and an AD brain. The DF was treated as the AD-related features, reduced by principal component analysis (PCA), and finally fed into three classifiers: support vector machine (SVM), generalized eigenvalue proximal SVM (GEPSVM), and twin SVM (TSVM). The 10-fold cross validation repeated 50 times. Results. The results showed the "DF + PCA + TSVM" achieved the accuracy of 92.75 ± 1.77, sensitivity of 90.56 ± 1.15, specificity of 93.37 ± 2.05, and precision of 79.61 ± 2.21. This result is better than or comparable with not only the other proposed two methods, but also ten state-of-the-art methods. Besides, our method discovers the AD is related to following brain regions disclosed in recent publications: Angular Gyrus, Anterior Cingulate, Cingulate Gyrus, Culmen, Cuneus, Fusiform Gyrus, Inferior Frontal Gyrus, Inferior Occipital Gyrus, Inferior Parietal Lobule, Inferior Semi-Lunar Lobule, Inferior Temporal Gyrus, Insula, Lateral Ventricle, Lingual Gyrus, Medial Frontal Gyrus, Middle Frontal Gyrus, Middle Occipital Gyrus, Middle Temporal Gyrus, Paracentral Lobule, Parahippocampal Gyrus, Postcentral Gyrus, Posterior Cingulate, Precentral Gyrus, Precuneus, Sub-Gyral, Superior Parietal Lobule, Superior Temporal Gyrus, Supramarginal Gyrus, and Uncus. Conclusion. The displacement filed is effective in detection of AD and related brain-regions.

Detection of Alzheimer’s Disease by Three-Dimensional Displacement Field Estimation in Structural Magnetic Resonance Imaging

Abstract: Background Within the past decade, computer scientists have developed many methods using computer vision and machine learning techniques to detect Alzheimer's disease (AD) in its early stages. Objective However, some of these methods are unable to achieve excellent detection accuracy, and several other methods are unable to locate AD-related regions. Hence, our goal was to develop a novel AD brain detection method. Methods In this study, our method was based on the three-dimensional (3D) displacement-field (DF) estimation between subjects in the healthy elder control group and AD group. The 3D-DF was treated with AD-related features. The three feature selection measures were used in the Bhattacharyya distance, Student's t-test, and Welch's t-test (WTT). Two non-parallel support vector machines, i.e., generalized eigenvalue proximal support vector machine and twin support vector machine (TSVM), were then used for classification. A 50 × 10-fold cross validation was implemented for statistical analysis. Results The results showed that "3D-DF+WTT+TSVM" achieved the best performance, with an accuracy of 93.05 ± 2.18, a sensitivity of 92.57 ± 3.80, a specificity of 93.18 ± 3.35, and a precision of 79.51 ± 2.86. This method also exceled in 13 state-of-the-art approaches. Additionally, we were able to detect 17 regions related to AD by using the pure computer-vision technique. These regions include sub-gyral, inferior parietal lobule, precuneus, angular gyrus, lingual gyrus, supramarginal gyrus, postcentral gyrus, third ventricle, superior parietal lobule, thalamus, middle temporal gyrus, precentral gyrus, superior temporal gyrus, superior occipital gyrus, cingulate gyrus, culmen, and insula. These regions were reported in recent publications. Conclusions The 3D-DF is effective in AD subject and related region detection.

Finite inflation of an initially stretched hyperelastic circular membrane

Abstract: In this paper, finite axisymmetric inflation of an initially stretched flat circular hyperelastic membrane has been analyzed. The membrane material has been assumed to be a homogeneous and isotropic Mooney–Rivlin solid. The inflation problem has been reduced to a set of three first order ordinary differential equations using a set of appropriately defined variables. An interesting method based on the invariance of these equations to scaling has been used to solve the two point boundary value problem without much effort. This method does not require any special technique for negotiating the limit points in the pressure–stretch relations of the membrane. Several inflation results of an initially unstretched and pre-stretched circular membrane for various material parameters are obtained. The roles of pre-stretch and internal pressure on the inflation mechanics are clearly delineated. The initial stretch is observed to have some interesting counter-intuitive effects on the inflation of the membrane.