Browsing by Author "Harish, A.B."

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    Online structural health monitoring of pretwisted anisotropic beams
    (2007) Harursampath, D.; Harish, A.B.; Kiran, S.
    Delamination is a mode of damage in laminated composites, which might occur either during manufacturing or during service in regions of material and geometric discontinuity. An effective and efficient mathematical model has been developed to assess the degradation in stiffness properties of a pretwisted anisotropic strip due to delamination. The same is implemented using MATLAB to enable Online Structural Health Monitoring. This model captures the non-linear effects in a strip thai arise due to thin & slender geometry in the presence of delamination at generic locations and can be used for static & dynamic applications. The possible direct application of this model is to helicopter flexbeams, and keeping this in view, a strip made of antisymmetric layup composed of symmetric sublaminates with a small pretwist is considered in the formulation. Variational Asymptotic Method (VAM) is used as a mathematical tool to systematically disintegrate the original geometrically nonlinear 3D problem and the sublaminate approach further simplifies the formulation. This is demonstrated by considering a strip made of piezoelectric fibre composites subjected to an axial load, typically caused by a centrifugal force on a helicopter rotor flexbeam. The model developed is not limited in application as the type of delamination and layup considered is generalised and hence offers critical insight. Also considered is the random nature of material properties. This work provides an effective mathematical tool for Online Structural Health Monitoring of pretwisted anisotropic beams due to delamination. Copyright � 2007 by DEStech Publications, Inc. All Rights Reserved.
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    Online structural health monitoring of pretwisted anisotropic beams
    (DEStech Publications, 2007) Harursampath, D.; Harish, A.B.; Kiran, S.
    Delamination is a mode of damage in laminated composites, which might occur either during manufacturing or during service in regions of material and geometric discontinuity. An effective and efficient mathematical model has been developed to assess the degradation in stiffness properties of a pretwisted anisotropic strip due to delamination. The same is implemented using MATLAB to enable Online Structural Health Monitoring. This model captures the non-linear effects in a strip thai arise due to thin & slender geometry in the presence of delamination at generic locations and can be used for static & dynamic applications. The possible direct application of this model is to helicopter flexbeams, and keeping this in view, a strip made of antisymmetric layup composed of symmetric sublaminates with a small pretwist is considered in the formulation. Variational Asymptotic Method (VAM) is used as a mathematical tool to systematically disintegrate the original geometrically nonlinear 3D problem and the sublaminate approach further simplifies the formulation. This is demonstrated by considering a strip made of piezoelectric fibre composites subjected to an axial load, typically caused by a centrifugal force on a helicopter rotor flexbeam. The model developed is not limited in application as the type of delamination and layup considered is generalised and hence offers critical insight. Also considered is the random nature of material properties. This work provides an effective mathematical tool for Online Structural Health Monitoring of pretwisted anisotropic beams due to delamination. © © 2007 by DEStech Publications, Inc. All Rights Reserved.
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    Trimodal Attention Module for Multimodal Sentiment Analysis
    (AAAI press, 2020) Harish, A.B.; Sadat, F.
    In our research, we propose a new multimodal fusion architecture for the task of sentiment analysis. The 3 modalities used in this paper are text, audio and video. Most of the current methods deal with either a feature level or a decision level fusion. In contrast, we propose an attention-based deep neural network and a training approach to facilitate both feature and decision level fusion. Our network effectively leverages information across all three modalities using a 2 stage fusion process. We test our network on the individual utterance based contextual information extracted from the CMUMOSI Dataset. A comparison is drawn between the state-ofthe- A rt and our network. © 2020 The Twenty-Fifth AAAI/SIGAI Doctoral Consortium (AAAI-20). All Rights Reserved.