Papers

Papers archive

All papers

Every publication and white paper, newest first and grouped by year.

16 papers · 2007 to 2018

2018

Sep Complex Hole Recognition from CAD Mesh ModelsThis paper reports an algorithm to recognize complex intersecting holes from CAD mesh models based on hybrid mesh segmentation. The algorithm involves three steps viz. preprocessing, hybrid mesh segmentation and hole recognition. In the preprocessing step, we build a topology of the imported CAD mesh model. In the Hybrid Mesh Segmentation step, we cluster facets into groups based on mesh attributes. The facets in the clusters are then subjected to several conformal tests, to identify the type of analytical surface it might be representing, such as a plane, cylinder, cone, torus or sphere. In this research, a rule-based approach is used for compound hole detection along with hole chains. This algorithm has been implemented in VC++ and has been extensively tested on models taken from NIST repository for complex intersecting holes. The innovation lies in complex intersecting hole detection and parameterization. The proposed approach outperforms the existing techniques favorably and is found to be robust and consistent. This extracted feature information can be utilized during all stages of the design-to-manufacturing cycle. Publication · International Journal of Management, Technology And Engineering; 2nd International Conference on Emerging Trends in Science, Engineering & Technology, Pune, IndiaBy Vaibhav J Hase, Yogesh J Bhalerao, Saurabh Verma, Sandip Jadhav, G J Vikhe Patil
Sep Intelligent Threshold Prediction in Hybrid Mesh Segmentation using Machine Learning ClassifiersThe optimal threshold is the decisive factor in CAD mesh segmentation. It is difficult for a layman to set the optimal threshold for hybrid mesh segmentation. In this research work, a generalized technique is developed to predict optimal threshold (Area Deviation Factor) for CAD mesh model which makes hybrid mesh segmentation automatic by using a nonparametric, supervised learning classifier, i.e., K Nearest Neighbor (KNN). The proposed approach classify a CAD mesh model based on mesh attributes and predict the threshold. We demonstrate and validate the algorithm's ability to predict threshold using extensive testing on test models taken from various benchmarks, and it is found to be robust and consistent. We use percentage coverage and the number of primitives as a measure to test the efficacy of the algorithm. The experimentation shows that the optimal value of the threshold for segmentation results in better coverage. The KNN classifier predicts the threshold correctly with coverage of more than 95%. The novelty of the proposed method lies in threshold prediction based on mesh quality. The predicted threshold can be linked to a downstream application like automatic feature recognition from CAD mesh model. Publication · International Journal of Management, Technology And Engineering; 2nd International Conference on Emerging Trends in Science, Engineering & Technology, Pune, IndiaBy Vaibhav J Hase, Yogesh J Bhalerao, Saurabh Verma, Vishnu D Wakshaure, G J Vikhe Patil
Jul Large Scale Modeling of Wind Comfort and Safety Using Pedestrian Comfort Analysis AppAssessing the impact of building induced aerodynamics effects, on pedestrian comfort and safety, at a large scale is of great interest to local governments, architects, urban planners, designers, and developers. A common method of assessing pedestrian comfort is to perform a series of CFD simulations for different wind directions, combining the results with historical wind data obtained from the weather station near the site location and checking compliance with a suitable wind comfort criterion. The existing simulation tools and methodology demand CFD expertise and in-house high-performance computing facility. With the advent of powerful cloud computing, a new Pedestrian Comfort Analysis application has been developed by simulationHub, that performs the CFD simulations on cloud and provides comfort and safety plots for large-scale models within hours. Through introduction and case study, this paper illustrates the 'Pedestrian Comfort Analysis' app to assess the pedestrian wind comfort and safety, across urban building design. White paper · Architecture Engineering & Construction, Wind Pedestrian Comfort & SafetyBy Sandip Jadhav, Vijay Mali, Praveen Kumar Ramachandran, Chaitanya Rane

2017

2012

Jan Geometric forms recognition: Approaches to find shapes from NURBSRecognizing the construction methods of (piecewise) polynomial or rational curves and surfaces are of great importance, e.g., for geometrical data exchange between two different modeling systems. Project aims to find conditions that would determine geometric shape of object from set of input curves and surfaces. These conditions should be able to detect: (1) whether a curve segment is a line, a circle, a circular arc or a planar curve; (2) whether a surface patch is a plane, a cylinder or a cone; and (3) whether a surface is constructed as a surface of revolution, a extrusion, a ruled/developed surface or a generalized cylinder. The detected geometric features could be added to CAD systems using their native CAD APIs. This would be achieved by choosing appropriate model parameters and creation method. In this way, we can reconstruct the geometry as it was in original. Input is received in the form of IGES files through comprehensive IGES Reader programs developed to process input geometric model. Publication · LAP LAMBERT Academic PublishingBy Swapnil D. Thepade, D.S.S. Sudhakar, Sandip N. Jadhav

2010

2009

Jul Determination of the valve sizing coefficient of globe valve using CFDIn this paper the flow past a 2 inch sized globe valve is numerically simulated and the valve sizing coefficient (CV>) is calculated using CFD. A theoretical study using elementary techniques is exercised to understand the significance of the flow coefficient (CV>) in predicting the mass flow rate through the valve. This exercise gives way to a clear understanding of the inherent simplicity of the function of a valve. A commercial grid generation tool ICEM-FLUENT is used for mesh generation. Commercial fluid dynamics code, ANSYS FLUENT is used for the flow modeling. For the static analysis, fully opened valve position is used and 1 atm through 7 atm of pressure difference (delta P) is applied across the valve numerically. The numerical data obtained from the simulations is then used to calculate the flow coefficient (CV) computationally. From the results obtained it is found that the flow coefficient was indeed a constant for the same set of pressure differential and mass flow rate. The flow coefficient value is thus proved to be a function of the valve structure. By comparing between numerical and experimental results it is concluded that flow coefficient (CV) can be predicted with agreeable accuracy using computational techniques. White paper · Control Valve, Computational Fluid DynamicsBy K Yogesh, Kaivalya Bakshi

2008

Jan Development of algorithms for recognition of geometric formsRecognizing the construction methods of (piecewise) polynomial or rational curves and surfaces are of great importance, e.g., for geometrical data exchange between two different modeling systems. Paper aims to find conditions that would determine geometric shape of object from set of input curves and surfaces. These conditions should be able to detect: (1) whether a curve segment is a line, a circle, a circular arc, a ellipse, a elliptic arc or a planar curve; (2) whether a surface patch is a plane, a sphere, a cylinder or a cone; and (3) whether a surface is constructed as a surface of revolution, a extrusion, a ruled/developed surface or a generalized cylinder. The detected geometric features could be added to CAD system using their native CAD API. This would be achieved by choosing appropriate model parameters and creation method. Input is received in form of IGES files through comprehensive IGES Reader programs developed to process input geometric model. Publication · Advances in Computer Vision and Information TechnologyBy Swapnil D. Thepade, D.S.S. Sudhakar, Sandip N. Jadhav

2007