Faculty Publications
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Item Stability and dynamic behaviour of bi-directional functionally graded beam subjected to variable axial load(Elsevier Ltd, 2022) Somi Naidu, S.N.; Jeyaraj, J.The current study emphasizes static stability and dynamic characteristics of bi-directional functionally graded beams subjected to variable axial loads using the Ritz method and Reddy's beam theory. The material property is varied as a function of the gradation pattern along with the length and thickness directions. The solutions procedures are tested against the results in the literature to show the accuracy of the present method. The influence of uniform, linear, and parabolic axial loads along the length of the beam on buckling and vibration responses are investigated. There is a remarkable variation observed in both the responses, by changing the material properties from isotropic to bi-direction functionally graded. Furthermore, the study reveals that higher stiffness is achieved by the material gradation index increment along the thickness direction compared to the lengthwise gradation index increment. Even the variations in the aspect ratios and end conditions are depicting significant variations in the buckling and vibration responses. Buckling and free vibration modes are also highly sensitive to the nature of variable axial loads and gradation index. © 2022 Elsevier LtdItem Solar Irradiation Prediction Hybrid Framework Using Regularized Convolutional BiLSTM-Based Autoencoder Approach(Institute of Electrical and Electronics Engineers Inc., 2023) Chiranjeevi, M.; Karlamangal, S.; Moger, T.; Jena, D.Solar irradiance prediction is an essential subject in renewable energy generation. Prediction enhances the planning and management of solar installations and provides several economic benefits to energy companies. Solar irradiation, being highly volatile and unpredictable makes the forecasting task complex and difficult. To address the shortcomings of the traditional approaches, this research developed a hybrid resilient architecture for an enhanced solar irradiation forecast by employing a long short-term memory (LSTM) autoencoder, convolutional neural network (CNN), and the Bi-directional Long Short Term Memory (BiLSTM) model with grid search optimization. The suggested hybrid technique is comprised of two parts: feature encoding and dimensionality reduction using an LSTM autoencoder, followed by a regularized convolutional BiLSTM. The encoder is tasked with extracting the key features in order to deduce the input into a compact latent representation. The decoder network then predicts solar irradiance by analyzing the encoded representation's attributes. The experiments are conducted on three publicly available data sets collected from Desert Knowledge Australia Solar Centre (DKASC), National Solar Radiation Database (NSRDB), and Hawaii Space Exploration Analog and Simulation (HI-SEAS) Habitat. The analysis of univariate and multivariate-multi step ahead forecasting performed independently and it is compared with the conventional approaches. Several benchmark forecasting models and three performance metrics are utilized to validate the hybrid approach's prediction performance. The results show that the proposed architecture outperforms benchmark models in accuracy. © 2013 IEEE.Item Influence of hybrid smart damping system on bi-directionally tapered functionally graded plate using 1-3 PZC resting on winkler-pasternak flexible support(SAGE Publications Inc., 2025) Shada, S.K.; Kattimani, S.; Ramesh, M.R.This article presents a numerical investigation of free vibrational features of bi-directionally tapered functionally graded (BTFG) plate unified with active constrained layer damping (ACLD) on a two-parameter Winkler-Pasternak flexible support. In conjunction with the virtual work principle, the first-order shear theory for deformation is employed. The plate’s damping is actively controlled using a velocity feedback control system with 1-3 piezoelectric patches consisting of piezoelectric and viscoelastic layers. Effects of foundation/support parameters (Kw and Ks), taper ratios, ACLD patch placement, and boundary conditions are systematically analysed through frequency response studies. Results demonstrate that incorporating ACLD patches significantly enhances damping features. Revealing with edge patch placement yields superior vibration suppression on the substrate plate. The study highlights the synergistic impact of ACLD patches, flexible supports, and active control, presenting a robust solution for precision vibration control in advanced structural applications. © The Author(s) 2025Item AN ONTOLOGY-DRIVEN BI-DIRECTIONAL WORKFLOW FOR INTEGRATING PROJECT MANAGEMENT DATA INTO THE IFC STANDARD(International Council for Research and Innovation in Building and Construction, 2025) Kone, V.; Mahesh, G.The evolution of Building Information Modelling (BIM) towards a data-centric paradigm is often hindered by challenges in semantic interoperability, particularly when integrating project management data with the Industry Foundation Classes (IFC) standard. While IFC enables syntactic data exchange, a persistent gap exists dynamically linking building geometry with the complex, relational information of project schedules, resources, and costs in a semantically consistent, interoperable manner. This paper presents a novel, bi-directional methodology that leverages Semantic Web technologies (RDF, OWL, SPARQL) to address this challenge. The core of the methodology is an ontology-driven workflow that uses two purpose-built ontologies: BIMOnto, a lightweight representation of the building asset derived from if cOWL, and IproK (Integrated Project Knowledge Ontology), which formally structures project management information across schedule, resource, and cost domains. The workflow enables both directions: (1) transforming IFC models into queryable knowledge graphs, and (2) programmatically generating new, enriched IFC models from unified knowledge graphs. This reverse transformation creates native, standards-compliant IFC entities for tasks (IfcTask), resources (IfcResource), costs (IfcCostItem), and their standard relationships (IfcRelAssignsToProduct, etc.), moving beyond custom property sets. The feasibility and effectiveness of this approach are validated through a case study using a multi-story residential building model, demonstrating the successful generation of a verifiable, integrated BIM artifact. The findings show that this ontology-driven framework significantly enhances data integration, creating truly interoperable models where process data becomes a first-class citizen within the BIM environment, advancing the potential for more intelligent, data-centric BIM practices throughout the project lifecycle. © © 2025 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.