Bolt and nut contact analsyis(axisymmetric)Vishnu R
This document summarizes an analysis project that models the static structural behavior of a bolted connection between a bolt and nut. It includes the axisymmetric model geometry, mesh, materials defined as structural steel, boundary conditions of forces applied to the bolt and nut, and the static structural analysis solved over time with results such as total deformation, equivalent stress, and stress components displayed.
Experimental Investigation and Parametric Analysis of Surface Roughness in C...IJMER
The manufacturing industries are very much concerned about the quality of their products.
They are focused on producing high quality products in time at minimum cost. Surface finish is one of the
crucial performance parameters that have to be controlled within suitable limits for a particular process.
Surface roughness of machined components has received serious attention of Researchers for many years.
It has been an important design feature and quality measure in machining process. There are a large
number of parameters which affect the surface roughness. These include cutting tool variables, work
piece material variables, cutting conditions etc. Therefore, prediction or monitoring of the surface
roughness of machined components has been challenging and unexplored area of research
The present work is therefore in a direction to integrate effect of various parameters which effect the
surface roughness. Experiments were carried out with the help of factorial method of design of
experiment (DOE) approach to study the impact of turning parameters on the roughness of turned
surfaces. A mathematical model was formulated to predict the effect of machining parameters on surface
roughness of a machined work piece. Model was validated with the experimental data and the reported
data of other researchers. Further parametric investigations were carried out to predict the effect of
various parameters on the surface research
Digital Image Correlation (DIC) is a non-contact method for measuring deformation and strain on surfaces using digital cameras. It can be used for construction applications ranging from individual building materials to large structures. DIC provides full-field surface measurements which capture more data points compared to traditional point-based sensors. This allows detailed analysis of failure mechanisms in materials like concrete, masonry, and roofing under various types of testing such as compression, wind loading, and structural analysis of bridges.
3D beam truss subjected to a certain amount of force over its base. Using beam tools , the axial force , bending moments and shear force diagrams are drawn/calculated.
The document discusses surface metrology and measurement. It covers topics such as why surface finish needs to be measured, various measurement methods including contact and non-contact instruments, parameters like roughness and waviness, filters used to separate out different surface components, and calibration methods. Form measurement is also covered, including measurement of parameters like straightness, least squares arcs and radii.
Artificial Neural Network Modeling and Analysis of EN24 &EN36 Using CNC Milli...ijiert bestjournal
Metal cutting is one of the most significant manufa cturing processes in the area of material removal. It is Block it is defined metal cutting as the removal of metal chips from a work piece in order to obtain a finished product with de sired attributes of size,shape,and surface roughness.The imperative objective of the science o f metal cutting is the solution of practical problems associated with the efficient and precise removal of metal from work piece. It has been recognized that the reliable quantitative pred ictions of the various technological performance measures,preferably in the form of equ ations,are essential to develop optimization strategies for selecting cutting condi tions in process planning. In this thesis experiments has to be conducted to improve the surf ace finish quality of a work piece by using carbide tips. The type is bull nose tip. A se ries of experiments have to be done by varying the milling parameters spindle speed,feed rate and depth of cut and modeling is done by ANN. and Analysis is done by ANSYS.
Machinability Study Of 3D printed Ti-6Al-4VSajjadAhmad214
The objective of the research is to study the machinability of 3D printed materials and provide fundamental insight into the material removal mechanism. Specifically, this study aims to investigate how the porosity in 3D printed materials can affect its machinability in terms of cutting force, surface quality, and tool wear. It is believed that machining response during the subtractive cycle of the process could be used to provide feedback on printing quality for the upcoming addictive cycle to improve the quality of the parts. This could be achieved by the machinability studies of 3D printed parts with varying degrees of defects such as porosity to obtain a one-to-one correlation between the machining response, e.g., cutting forces and vibrations, and the defect concentration e,g, porosity.
The present study is limited to the most extensively used Titanium alloy-6Al-4V which is 3D printed by the Selective Laser Sintering process. Micro-end milling is used as the machining process to conduct the machining experiments.
Analysis and optimization of machining process parametersAlexander Decker
This document analyzes machining process parameters like feed, cutting speed, and depth of cut to optimize surface roughness and metal removal rate when turning aluminum alloy and resin workpieces. Experiments were conducted using a response surface methodology. Mathematical models were developed relating the output responses to the input parameters. The models were found to accurately predict the surface roughness and metal removal rate. Optimization found the minimum surface roughness was 1.18 μm for aluminum alloy and 2.295 μm for resin, while the maximum metal removal rate was achieved at higher speeds, feeds, and depths of cut.
Bolt and nut contact analsyis(axisymmetric)Vishnu R
This document summarizes an analysis project that models the static structural behavior of a bolted connection between a bolt and nut. It includes the axisymmetric model geometry, mesh, materials defined as structural steel, boundary conditions of forces applied to the bolt and nut, and the static structural analysis solved over time with results such as total deformation, equivalent stress, and stress components displayed.
Experimental Investigation and Parametric Analysis of Surface Roughness in C...IJMER
The manufacturing industries are very much concerned about the quality of their products.
They are focused on producing high quality products in time at minimum cost. Surface finish is one of the
crucial performance parameters that have to be controlled within suitable limits for a particular process.
Surface roughness of machined components has received serious attention of Researchers for many years.
It has been an important design feature and quality measure in machining process. There are a large
number of parameters which affect the surface roughness. These include cutting tool variables, work
piece material variables, cutting conditions etc. Therefore, prediction or monitoring of the surface
roughness of machined components has been challenging and unexplored area of research
The present work is therefore in a direction to integrate effect of various parameters which effect the
surface roughness. Experiments were carried out with the help of factorial method of design of
experiment (DOE) approach to study the impact of turning parameters on the roughness of turned
surfaces. A mathematical model was formulated to predict the effect of machining parameters on surface
roughness of a machined work piece. Model was validated with the experimental data and the reported
data of other researchers. Further parametric investigations were carried out to predict the effect of
various parameters on the surface research
Digital Image Correlation (DIC) is a non-contact method for measuring deformation and strain on surfaces using digital cameras. It can be used for construction applications ranging from individual building materials to large structures. DIC provides full-field surface measurements which capture more data points compared to traditional point-based sensors. This allows detailed analysis of failure mechanisms in materials like concrete, masonry, and roofing under various types of testing such as compression, wind loading, and structural analysis of bridges.
3D beam truss subjected to a certain amount of force over its base. Using beam tools , the axial force , bending moments and shear force diagrams are drawn/calculated.
The document discusses surface metrology and measurement. It covers topics such as why surface finish needs to be measured, various measurement methods including contact and non-contact instruments, parameters like roughness and waviness, filters used to separate out different surface components, and calibration methods. Form measurement is also covered, including measurement of parameters like straightness, least squares arcs and radii.
Artificial Neural Network Modeling and Analysis of EN24 &EN36 Using CNC Milli...ijiert bestjournal
Metal cutting is one of the most significant manufa cturing processes in the area of material removal. It is Block it is defined metal cutting as the removal of metal chips from a work piece in order to obtain a finished product with de sired attributes of size,shape,and surface roughness.The imperative objective of the science o f metal cutting is the solution of practical problems associated with the efficient and precise removal of metal from work piece. It has been recognized that the reliable quantitative pred ictions of the various technological performance measures,preferably in the form of equ ations,are essential to develop optimization strategies for selecting cutting condi tions in process planning. In this thesis experiments has to be conducted to improve the surf ace finish quality of a work piece by using carbide tips. The type is bull nose tip. A se ries of experiments have to be done by varying the milling parameters spindle speed,feed rate and depth of cut and modeling is done by ANN. and Analysis is done by ANSYS.
Machinability Study Of 3D printed Ti-6Al-4VSajjadAhmad214
The objective of the research is to study the machinability of 3D printed materials and provide fundamental insight into the material removal mechanism. Specifically, this study aims to investigate how the porosity in 3D printed materials can affect its machinability in terms of cutting force, surface quality, and tool wear. It is believed that machining response during the subtractive cycle of the process could be used to provide feedback on printing quality for the upcoming addictive cycle to improve the quality of the parts. This could be achieved by the machinability studies of 3D printed parts with varying degrees of defects such as porosity to obtain a one-to-one correlation between the machining response, e.g., cutting forces and vibrations, and the defect concentration e,g, porosity.
The present study is limited to the most extensively used Titanium alloy-6Al-4V which is 3D printed by the Selective Laser Sintering process. Micro-end milling is used as the machining process to conduct the machining experiments.
Analysis and optimization of machining process parametersAlexander Decker
This document analyzes machining process parameters like feed, cutting speed, and depth of cut to optimize surface roughness and metal removal rate when turning aluminum alloy and resin workpieces. Experiments were conducted using a response surface methodology. Mathematical models were developed relating the output responses to the input parameters. The models were found to accurately predict the surface roughness and metal removal rate. Optimization found the minimum surface roughness was 1.18 μm for aluminum alloy and 2.295 μm for resin, while the maximum metal removal rate was achieved at higher speeds, feeds, and depths of cut.
This document summarizes a study that used finite element modeling (FEM) to simulate and analyze milling processes. It describes the steps taken: pre-processing to set up the model, simulation, and post-processing of results. Cutting forces predicted by FEM were validated through experimental milling tests. Both FEM and experimental results showed good agreement between predicted and measured cutting forces. The study concluded that FEM is useful for analyzing milling processes but that further model improvements and experiments are needed.
This study examines the optimization of process parameters in robotic abrasive finishing to achieve the best surface roughness. Design of experiments was used to analyze the effect of spindle speed, feed rate, tool type, and workpiece geometry on the surface roughness (Ra and Rz). Experiments were conducted using two types of abrasive tools on concave and convex workpieces at different speeds and feed rates. Statistical analysis showed that workpiece geometry and interactions between feed rate and other factors most influenced Ra, while feed rate alone influenced Rz. Models were developed to optimize the parameters for minimum roughness, identifying low feed rate and certain tool/workpiece combinations. The results provide optimized parameters for robotic abrasive finishing to achieve the best surface quality.
This document proposes a CAD system to reduce or eliminate supports in additive manufacturing using process parameter optimization and model modification. It involves:
1) Constructing an ontology knowledge base representing AM processes
2) Building a process parameter control map from parametric studies
3) Automatically modifying models and assigning parameters to improve surface quality without supports
Study of roller burnishing process on aluminum work pieces using design of ex...IAEME Publication
This document discusses a study on the roller burnishing process for aluminum workpieces using design of experiments. Roller burnishing is a cold working process that improves the surface finish and hardness of a softer workpiece material through plastic deformation. The study aims to determine the optimum spindle speed, tool feed rate, and number of passes to minimize the surface roughness of aluminum workpieces. Design of experiments techniques are used to understand the individual and interactive effects of the process parameters on surface roughness. The results of this study can be applied to finish aluminum components for applications in various industries such as aerospace where low weight is important.
A study of the effects of machining parameters on surface roughness using res...IAEME Publication
This document discusses a study on the effects of machining parameters on surface roughness in end milling of EN11 alloy steel. Experiments were conducted using an L18 orthogonal array to test combinations of four factors (depth of cut, feed rate, spindle speed, coolant type) at three levels each. Surface roughness was measured after each trial. Statistical analysis using ANOVA and response surface methodology was performed on the experimental data to develop a model relating the factors to surface roughness. The goal was to determine the optimal factor levels that minimize surface roughness.
Michigan Metrology provides 3D surface metrology services including measurement, analysis, and inspection of microtextures and wear to solve problems related to friction, sealing, appearance, and other issues. The company uses non-contact 3D optical profilers and has expertise in analyzing surface topography parameters to characterize functional properties such as fluid retention, load distribution, and wear rates. Services include quantitative 3D analysis of components from various industries such as automotive, manufacturing, biomedical, and more.
Algorithmic Techniques for Parametric Model RecoveryCurvSurf
A complete description of algorithmic techniques for automatic feature extraction from point cloud. The orthogonal distance fitting, an art of maximum liklihood estimation, plays the main role. Differential geometry determines the type of object surface.
This document presents a method for statically calibrating the boresight angles of mobile LiDAR systems. It involves collecting scan lines from different positions on a planar surface and estimating the boresight angles through least squares adjustment to minimize misalignment. The method was tested on a commercial MLS, producing repeatable results comparable to more complex dynamic calibration methods. It has advantages of simplicity and not requiring precise metrological equipment. Validation with a surveying instrument showed improved alignment when using the estimated angles over the manufacturer's values.
The document discusses the design and testing of a 3D printer for additive manufacturing of solid rocket propellant. It describes the project objectives of printing solid propellant and comparing its mechanical properties to traditionally cast propellant. It then outlines the printer design which uses a laser to sinter layers of sucrose and potassium nitrate powder in a powder bed. Test results show the printer can achieve layer thicknesses within specifications but that printed propellant is less dense and more brittle than cast propellant. A thermal model is developed to predict sintering behavior and set safe laser operation settings.
The document presents a methodology for establishing stable process parameters in machining operations using dynamic force signal analysis. Key aspects of the methodology include:
1. Conducting experiments using a fractional factorial design and measuring in-process cutting forces with a dynamometer.
2. Analyzing the cutting force signals using frame statistics to calculate trends in mean, standard deviation, skewness, and kurtosis over time.
3. Understanding the effect of process parameters on force signal characteristics using cause-effect graphs and selecting optimal parameters based on scatter plots of mean versus standard deviation.
The methodology is applied and tested for process parameter selection in turning, drilling, and face milling operations. Results are compared to the Tag
Shear Field Size Effect on Determining the Shear Modulus of Glulam beam - Cri...CrimsonPublishersRDMS
Six glue laminated timber beams were tested to investigate the effect of the size of the constructing square used in the shear field test method for determining the shear modulus. Stereovision was used to capture the displacement of target points in grids on the beams. Analysis of variance found that the size of the square had a significant influence on the measured shear modulus values. The shear modulus increased with larger square sizes for most beams tested. It is recommended that the square size be at least half the beam depth to obtain appropriate results. Further research is needed to fully understand the impact of square size.
Topology Optimization for Additive Manufacturing as an Enabler for Robotic Ar...piyushsingh376
The current research is intended to minimize the mass of T shaped joint by using lattice structure and topological optimization tool.
The stresses, deformation, safety factor of generic and optimized design is evaluated on the basis of these mentioned parameters. The findings have shown that topological optimization method is best as compared to lattice structure method for weight minimization.
Trends in the Backend for Semiconductor Wafer InspectionRajiv Roy
The document discusses trends in back-end semiconductor inspection for the automotive industry in 2008. It covers increasing use of inspection for zero defects programs, tool matching and correlation, tall particle detection to prevent probe card damage, inspection of CMOS sensors and TSVs, and microbump and copper pillar bump inspection. Key points emphasized are the need for inspection tools designed for tool matching, implementing golden standards, and combining 2D and 3D inspection.
The document discusses block modeling in Surpac software. It begins by defining block modeling and describing Surpac as mine planning software with various modules. It then outlines the objectives of block modeling in Surpac as familiarizing with its block modeling module, learning to fill a block model from drill hole data, apply constraints, and report volume, tonnage and grade. The document proceeds to explain the basic steps involved in block modeling and key concepts like model space, blocks and attributes, constraints, and estimation methods. It includes pictures demonstrating block models, borehole data display, and the Surpac interface. It concludes by providing an example workflow for creating a block model in Surpac.
Optimization of sealing casting by identifying solidification defect and impr...IRJET Journal
1. The document discusses optimization of sealing castings through casting simulation. It aims to identify solidification defects in sealing castings and minimize them by optimizing the casting design using simulation software.
2. The current sealing casting design is analyzed using casting simulation software to identify solidification defects like shrinkage and misruns. Modifications are then made to the design using simulation to improve strength.
3. The methodology involves 3D modeling the casting, meshing it, applying material properties and boundary conditions in simulation software, and analyzing the results to identify defects and optimize the design.
Optimization of sealing casting by identifying solidification defect and impr...IRJET Journal
1. The document discusses optimization of sealing castings through casting simulation. It aims to identify solidification defects in sealing castings and minimize them by optimizing the casting design using simulation software.
2. The current sealing casting design is analyzed using casting simulation software to identify solidification defects like shrinkage and misruns. Modifications are then made to the design using simulation to improve strength.
3. The methodology involves 3D modeling the casting, meshing it, applying material properties and boundary conditions in simulation software, and analyzing the results to identify defects and optimize the design.
This document outlines a master's project that aims to apply 2-Dimensional Digital Image Correlation (2D-DIC) to map bond strain and stress distribution in concrete pull-out specimens. Eleven concrete specimens with varying bar diameters and fiber contents were tested. 2D-DIC analysis was used to find displacement fields from images taken during testing, which were then used to calculate strain and stress distributions. Results showed good agreement between 2D-DIC displacements and measurements from LVDT sensors. Strain contours were mapped for two selected specimens.
This paper applies inverse transform sampling to sample training points for surrogate models. Inverse transform sampling uniformly generates a sequence of real numbers ranging from 0 to 1 as the probabilities at sample points. The coordinates of the sample points are evaluated using the inverse functions of Cumulative Distribution Functions (CDF). The inputs to surrogate models are assumed to be independent random variables. The sample points obtained by inverse transform sampling can effectively represent the frequency of occurrence of the inputs. The distributions of inputs to the surrogate models are fitted to their observed data. These distributions are used for inverse transform sampling. The sample points have larger densities in the regions where the Probability Density Functions (PDF) are higher. This sampling approach ensures that the regions with higher densities of sample points are more prevalent in the observations of the random variables. Inverse transform sampling is applied to the development of surrogate models for window performance evaluation. The distributions of the following three climatic conditions are fitted: (i) the outside temperature, (ii) the wind speed, and (iii) the solar radiation. The sample climatic conditions obtained by the inverse transform sampling are used as training points to evaluate the heat transfer through a generic triple pane window. Using the simulation results at the sample points, surrogate models are developed to represent the heat transfer through the window as a function of the climatic conditions. It is observed that surrogate models developed using the inverse transform sampling can provide higher accuracy than that developed using the Sobol sequence directly for the window performance evaluation.
This document summarizes an application of inverse analysis to the material point method (MPM) for modeling geotechnical problems. The key points are:
- Inverse analysis can be used to calibrate constitutive model parameters in MPM simulations by comparing results to field or laboratory observations.
- Two examples are provided where inverse analysis is used to estimate Mohr-Coulomb parameters from CPT data and calibrate friction parameters to match a granular flow experiment.
- The main case study involves calibrating a constitutive model to simulate liquefaction and slope failure observed in a laboratory experiment using Northwich Park Coal. Parameters are fitted to triaxial test data and the slope failure stages are modeled.
This document discusses profilometers, which are devices used to measure surface roughness. It describes the two main types - contact and non-contact profilometers. Non-contact profilometers use optical techniques like interferometry to measure surfaces without touching them, while contact profilometers use a physical stylus. The document outlines various measurement techniques, performance parameters, surface topography concepts, and examples of profilometers available at IISc. It provides an overview of profilometry for measuring and analyzing surface roughness.
This document summarizes a study that used finite element modeling (FEM) to simulate and analyze milling processes. It describes the steps taken: pre-processing to set up the model, simulation, and post-processing of results. Cutting forces predicted by FEM were validated through experimental milling tests. Both FEM and experimental results showed good agreement between predicted and measured cutting forces. The study concluded that FEM is useful for analyzing milling processes but that further model improvements and experiments are needed.
This study examines the optimization of process parameters in robotic abrasive finishing to achieve the best surface roughness. Design of experiments was used to analyze the effect of spindle speed, feed rate, tool type, and workpiece geometry on the surface roughness (Ra and Rz). Experiments were conducted using two types of abrasive tools on concave and convex workpieces at different speeds and feed rates. Statistical analysis showed that workpiece geometry and interactions between feed rate and other factors most influenced Ra, while feed rate alone influenced Rz. Models were developed to optimize the parameters for minimum roughness, identifying low feed rate and certain tool/workpiece combinations. The results provide optimized parameters for robotic abrasive finishing to achieve the best surface quality.
This document proposes a CAD system to reduce or eliminate supports in additive manufacturing using process parameter optimization and model modification. It involves:
1) Constructing an ontology knowledge base representing AM processes
2) Building a process parameter control map from parametric studies
3) Automatically modifying models and assigning parameters to improve surface quality without supports
Study of roller burnishing process on aluminum work pieces using design of ex...IAEME Publication
This document discusses a study on the roller burnishing process for aluminum workpieces using design of experiments. Roller burnishing is a cold working process that improves the surface finish and hardness of a softer workpiece material through plastic deformation. The study aims to determine the optimum spindle speed, tool feed rate, and number of passes to minimize the surface roughness of aluminum workpieces. Design of experiments techniques are used to understand the individual and interactive effects of the process parameters on surface roughness. The results of this study can be applied to finish aluminum components for applications in various industries such as aerospace where low weight is important.
A study of the effects of machining parameters on surface roughness using res...IAEME Publication
This document discusses a study on the effects of machining parameters on surface roughness in end milling of EN11 alloy steel. Experiments were conducted using an L18 orthogonal array to test combinations of four factors (depth of cut, feed rate, spindle speed, coolant type) at three levels each. Surface roughness was measured after each trial. Statistical analysis using ANOVA and response surface methodology was performed on the experimental data to develop a model relating the factors to surface roughness. The goal was to determine the optimal factor levels that minimize surface roughness.
Michigan Metrology provides 3D surface metrology services including measurement, analysis, and inspection of microtextures and wear to solve problems related to friction, sealing, appearance, and other issues. The company uses non-contact 3D optical profilers and has expertise in analyzing surface topography parameters to characterize functional properties such as fluid retention, load distribution, and wear rates. Services include quantitative 3D analysis of components from various industries such as automotive, manufacturing, biomedical, and more.
Algorithmic Techniques for Parametric Model RecoveryCurvSurf
A complete description of algorithmic techniques for automatic feature extraction from point cloud. The orthogonal distance fitting, an art of maximum liklihood estimation, plays the main role. Differential geometry determines the type of object surface.
This document presents a method for statically calibrating the boresight angles of mobile LiDAR systems. It involves collecting scan lines from different positions on a planar surface and estimating the boresight angles through least squares adjustment to minimize misalignment. The method was tested on a commercial MLS, producing repeatable results comparable to more complex dynamic calibration methods. It has advantages of simplicity and not requiring precise metrological equipment. Validation with a surveying instrument showed improved alignment when using the estimated angles over the manufacturer's values.
The document discusses the design and testing of a 3D printer for additive manufacturing of solid rocket propellant. It describes the project objectives of printing solid propellant and comparing its mechanical properties to traditionally cast propellant. It then outlines the printer design which uses a laser to sinter layers of sucrose and potassium nitrate powder in a powder bed. Test results show the printer can achieve layer thicknesses within specifications but that printed propellant is less dense and more brittle than cast propellant. A thermal model is developed to predict sintering behavior and set safe laser operation settings.
The document presents a methodology for establishing stable process parameters in machining operations using dynamic force signal analysis. Key aspects of the methodology include:
1. Conducting experiments using a fractional factorial design and measuring in-process cutting forces with a dynamometer.
2. Analyzing the cutting force signals using frame statistics to calculate trends in mean, standard deviation, skewness, and kurtosis over time.
3. Understanding the effect of process parameters on force signal characteristics using cause-effect graphs and selecting optimal parameters based on scatter plots of mean versus standard deviation.
The methodology is applied and tested for process parameter selection in turning, drilling, and face milling operations. Results are compared to the Tag
Shear Field Size Effect on Determining the Shear Modulus of Glulam beam - Cri...CrimsonPublishersRDMS
Six glue laminated timber beams were tested to investigate the effect of the size of the constructing square used in the shear field test method for determining the shear modulus. Stereovision was used to capture the displacement of target points in grids on the beams. Analysis of variance found that the size of the square had a significant influence on the measured shear modulus values. The shear modulus increased with larger square sizes for most beams tested. It is recommended that the square size be at least half the beam depth to obtain appropriate results. Further research is needed to fully understand the impact of square size.
Topology Optimization for Additive Manufacturing as an Enabler for Robotic Ar...piyushsingh376
The current research is intended to minimize the mass of T shaped joint by using lattice structure and topological optimization tool.
The stresses, deformation, safety factor of generic and optimized design is evaluated on the basis of these mentioned parameters. The findings have shown that topological optimization method is best as compared to lattice structure method for weight minimization.
Trends in the Backend for Semiconductor Wafer InspectionRajiv Roy
The document discusses trends in back-end semiconductor inspection for the automotive industry in 2008. It covers increasing use of inspection for zero defects programs, tool matching and correlation, tall particle detection to prevent probe card damage, inspection of CMOS sensors and TSVs, and microbump and copper pillar bump inspection. Key points emphasized are the need for inspection tools designed for tool matching, implementing golden standards, and combining 2D and 3D inspection.
The document discusses block modeling in Surpac software. It begins by defining block modeling and describing Surpac as mine planning software with various modules. It then outlines the objectives of block modeling in Surpac as familiarizing with its block modeling module, learning to fill a block model from drill hole data, apply constraints, and report volume, tonnage and grade. The document proceeds to explain the basic steps involved in block modeling and key concepts like model space, blocks and attributes, constraints, and estimation methods. It includes pictures demonstrating block models, borehole data display, and the Surpac interface. It concludes by providing an example workflow for creating a block model in Surpac.
Optimization of sealing casting by identifying solidification defect and impr...IRJET Journal
1. The document discusses optimization of sealing castings through casting simulation. It aims to identify solidification defects in sealing castings and minimize them by optimizing the casting design using simulation software.
2. The current sealing casting design is analyzed using casting simulation software to identify solidification defects like shrinkage and misruns. Modifications are then made to the design using simulation to improve strength.
3. The methodology involves 3D modeling the casting, meshing it, applying material properties and boundary conditions in simulation software, and analyzing the results to identify defects and optimize the design.
Optimization of sealing casting by identifying solidification defect and impr...IRJET Journal
1. The document discusses optimization of sealing castings through casting simulation. It aims to identify solidification defects in sealing castings and minimize them by optimizing the casting design using simulation software.
2. The current sealing casting design is analyzed using casting simulation software to identify solidification defects like shrinkage and misruns. Modifications are then made to the design using simulation to improve strength.
3. The methodology involves 3D modeling the casting, meshing it, applying material properties and boundary conditions in simulation software, and analyzing the results to identify defects and optimize the design.
This document outlines a master's project that aims to apply 2-Dimensional Digital Image Correlation (2D-DIC) to map bond strain and stress distribution in concrete pull-out specimens. Eleven concrete specimens with varying bar diameters and fiber contents were tested. 2D-DIC analysis was used to find displacement fields from images taken during testing, which were then used to calculate strain and stress distributions. Results showed good agreement between 2D-DIC displacements and measurements from LVDT sensors. Strain contours were mapped for two selected specimens.
This paper applies inverse transform sampling to sample training points for surrogate models. Inverse transform sampling uniformly generates a sequence of real numbers ranging from 0 to 1 as the probabilities at sample points. The coordinates of the sample points are evaluated using the inverse functions of Cumulative Distribution Functions (CDF). The inputs to surrogate models are assumed to be independent random variables. The sample points obtained by inverse transform sampling can effectively represent the frequency of occurrence of the inputs. The distributions of inputs to the surrogate models are fitted to their observed data. These distributions are used for inverse transform sampling. The sample points have larger densities in the regions where the Probability Density Functions (PDF) are higher. This sampling approach ensures that the regions with higher densities of sample points are more prevalent in the observations of the random variables. Inverse transform sampling is applied to the development of surrogate models for window performance evaluation. The distributions of the following three climatic conditions are fitted: (i) the outside temperature, (ii) the wind speed, and (iii) the solar radiation. The sample climatic conditions obtained by the inverse transform sampling are used as training points to evaluate the heat transfer through a generic triple pane window. Using the simulation results at the sample points, surrogate models are developed to represent the heat transfer through the window as a function of the climatic conditions. It is observed that surrogate models developed using the inverse transform sampling can provide higher accuracy than that developed using the Sobol sequence directly for the window performance evaluation.
This document summarizes an application of inverse analysis to the material point method (MPM) for modeling geotechnical problems. The key points are:
- Inverse analysis can be used to calibrate constitutive model parameters in MPM simulations by comparing results to field or laboratory observations.
- Two examples are provided where inverse analysis is used to estimate Mohr-Coulomb parameters from CPT data and calibrate friction parameters to match a granular flow experiment.
- The main case study involves calibrating a constitutive model to simulate liquefaction and slope failure observed in a laboratory experiment using Northwich Park Coal. Parameters are fitted to triaxial test data and the slope failure stages are modeled.
This document discusses profilometers, which are devices used to measure surface roughness. It describes the two main types - contact and non-contact profilometers. Non-contact profilometers use optical techniques like interferometry to measure surfaces without touching them, while contact profilometers use a physical stylus. The document outlines various measurement techniques, performance parameters, surface topography concepts, and examples of profilometers available at IISc. It provides an overview of profilometry for measuring and analyzing surface roughness.
The document discusses current and continuing issues in computational fluid dynamics (CFD). It identifies the main issues as accuracy, CAD geometry, users, application areas, computational resources, and new challenges. For each issue, it provides more details on specific challenges. For example, for accuracy it discusses validation, turbulence modeling, convergence, and mesh quality. It also provides examples to illustrate some of the challenges and notes activities by NAFEMS to address these issues.
This thesis document summarizes the development of numerical models to analyze composite grid structures under compressive loads. The student developed a numerical model at the coupon level (Test Case A) and then a more complex model (Test Case B) to determine the mechanical properties. Experimental testing was conducted and compared to numerical results. The best numerical model used solid elements, enhanced reduced integration, and applied realistic boundary conditions. Summary comparisons showed the numerical models accurately captured the structural response in the experimental tests.
1) Andrew Littlejohn implemented new laser scan programs for cylinder blocks and heads using a CMM laser scanner to reduce costs and improve efficiency of die confirmation.
2) Previously, die confirmation took over 3 hours and involved scrapped parts. The new method scans over 80% of surfaces in under an hour and eliminates scrapped parts, reducing scrap costs by $37,250 annually.
3) Through fixtures designed in Catia and custom scan and inspection macros, the process is now automated, improving capabilities from 47% to 100% for new model die confirmation.
Similar to Utilisation de la méthode des éléments finis dans le cadre de l’inspection automatique de pièces flexibles (20)
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
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Utilisation de la méthode des éléments finis dans le cadre de l’inspection automatique de pièces flexibles
1. Par: Sasan Sattarpanah Karganroudi
Professeurs:
Jean-Christophe Cuillière
Vincent François
Souheil-Antoine Tahan
Mai. 04. 2016
Utilisation de la méthode des éléments finis dans le cadre
de l’inspection automatique de pièces flexibles
1
7ème colloque québécois sur le développement numérique de produits
2. layout
2
1. Introduction
• Inspection of non-rigid parts
• Fixtureless computer aided inspection
• Non-rigid registration methods
2. Sample point filtration method
• Corresponding sample points generation
• Principal curvature and von Mises stress filtration criteria
• Robustness validation of the method
3. Virtual assembly of non-rigid parts (Preliminary results)
• Estimation of necessary assembly load
4. Conclusion and future researches
3. Non-rigid (flexible) parts
3
Reference: ASCIONE, R. & POLINI, W. 2010. Measurement of nonrigid freeform surfaces by coordinate measuring machine. The
International Journal of Advanced Manufacturing Technology, 51, 1055-1067.
• Such as thin-walled sheet metals
• In aerospace and automotive industries
• Deform to an extent in a free-state which
exceeds the designed tolerance of model
4. Inspection of Non-rigid parts _ inspection fixture Vs. free-state
4
Reference: G. N. Abenhaim, S. A. Tahan, A. Desrochers, and J.-F. Lalonde, "Aerospace Panels Fixtureless Inspection Methods
with Restraining Force Requirements; A Technology Review," SAE Technical Paper 2013.
• Conventional inspection methods
• To retrieve the functional shape of
part
Elastic deformation of non-rigid parts:
• Weight
• Residual stress
• Spring back effect
• …
In a free-state Constrained in inspection fixture
5. Inspection fixtures Vs. Fixtureless CAI
5
Reference: ASCIONE, R. & POLINI, W. 2010. Measurement of nonrigid freeform surfaces by coordinate measuring machine. The
International Journal of Advanced Manufacturing Technology, 51, 1055-1067.
• Sophisticated
• Time consuming
• Expensive
Fixtureless computer aided inspection (CAI) methods
6. Fixtureless computer aided inspection
6
Measured data:
• Scan model in a free-state
• Obtain point-cloud
• In measured coordinate sys.
Designed model:
• CAD model
• In design coordinate sys.
Registration
7. Registration methods for a non-rigid part
7
CAD model Scanned model
Defect Elastic deformation
• Rigid registration
X
Y
X
Y
• Non-rigid registration
X
Y
Defect Elastic deformation
9. CAD and scan models of a typical aerospace part
9
CAD mesh Scan mesh
Bump #1
Max. amplitude: 1 mm
Area: 85 mm2
Bump #2
Max. amplitude: 1.5 mm
Area: 98 mm2
Bump #3
Max. amplitude: 1 mm
Area: 60mm2
1 m
0.5 m
Thickness: 1 mm
10. Generalized numerical inspection fixture (GNIF) method
10
• Based on the fact that geodesic distances are preserved during an isometric deformation
• The CAD and scan models are intrinsically the same
• Generates corresponding sample points on CAD and scan models
CAD-sp1
CAD-sp2
Scan-sp1
Scan-sp2
Correspondence
Correspondence
CAD model Scan model
Reference: RADVAR-ESFAHLAN, H. & TAHAN, S. A. 2011. Nonrigid geometric metrology using generalized numerical inspection
fixtures. Precision Engineering-Journal of the International Societies for Precision Engineering and Nanotechnology, 36, 1-9
11. FEAnon-rigid registration on corresponding sample points
11
Corresponding sample points are evenly distributed over the CAD and scanned models
Coordinate of sample
point on CAD model
Coordinate of
corresponding sample
point on scanned model
Displacement vector
FEA non-rigid registration
12. Delaunay incremental point insertion
12
• Corresponding sample points are not on CAD mesh
• Insert points by Delaunay method
Sample points on CAD model CAD mesh
Inserted sample
points into CAD model
13. 1st Finite element non-rigid registration (FENR)
13
[mm]
Displacement boundary condition
FEA
CAD model Deformed CAD model
15. Scanned model
CAD model
Problem definition
15
Defects are underestimated
• Corresponding sample points close to defects may deform the CAD model to take
on the shape of defects.
The position of defects are not known a priori
in manufactured parts !!!
Objective:
• Distinguish between elastic (flexible)
deformation and deviations (defects)
Approach:
• Filtering sample points close to defects
16. Principal curvature differences distribution
16
Principal curvatures on defects are higher than
the general curvature value
Discrete CURV. diff. Kmax [mm-1] Discrete CURV. diff. Kmin [mm-1]
[mm-1] [mm-1]
[mm]
CAD model
Deformed CAD model
Threshold Threshold
Threshold values based on Mean distribution of principal
curvatures difference values
17. Filtering sample points based on curvaturecriterion, applying2nd FENR and
defect evaluation
17
Filtered sample points
18. von Mises stress distribution
18
[Pa] von Mises stress distribution
Deformed CAD model after
using curvature filtering
criterion
Threshold
Threshold values based on Mean distribution of von Mises stress values
19. Filtering more sample points based on curvature and von Mises criteria, applying
3rd FENR and defect evaluation
19
Filtered sample points
20. Various validation cases
20
simulation of
Scanned part
Part A
Bending
Torsion
Flexible deformation
Part B Bending
Torsion
Small (local)
Big (global)
Defects
Small (local)
Big (global)
Small (local)
Big (global)
Small (local)
Big (global)
22. Validation and verification (V&V) method
22
Problematic:
• Computational simulations, containing our sample point filtration method, always include
uncertainty.
Objectives:
• Assessing the level of accuracy and reliability of the method.
• Assessing the robustness by validating the method while adding noises to scan model.
Validation method:
• Based on ASME V&V 10.1 2006
• Statistic hypothesis testing (Kolmogorov-Smirnov (K-S) test)
Actual shape of
defects
23. Validation results by Kolmogorov-Smirnov (K-S) test
23
Kolmogorov-Smirnov (K-S) test:
• Evaluates the difference between the cumulative distribution functions (CDFs) of the
two sample data at a desired significance level.
24. Summary of validation results by Kolmogorov-Smirnov (K-S) test
24
BUMP1
BUMP2
BUMP3
BUMP1
BUMP2
BUMP3
• If an estimated defect shape is sufficiently similar to that of the nominal defect or not.
26. Conventional assembly inspection method
26
• Applying sand bags on the manufactured part with defects constrained in fixture
• Make an inspection to decide if the manufactured part can be assembled
• If deviations are more than dedicated tolerance, the part is rejected.
27. Assembly load estimation for non-rigid parts
27
CAD model + Assembly fixations
Scanned mesh (after rigid registration)
Constrained
mounting hole
Free
mounting hole
Mounting hole position
Permitted load
limitation
Objective Function
(Distance & Orientation mounting holes
between CAD and scan models as
function of loads)
Threshold Objective
Function Value (TOFV)
OFV < TOFV
Yes NO
Optimization method
(Fmincon in Matlab)
FF
F
F
28. Optimized assembly load estimation (pressures on distributed zones)
28
Fixations
Scan model
CAD model
ncad
nscn
CGSCN
CGcad
1
2
7
10
84
3
6
9
5
29. Optimized assembly load estimation (pressures on distributed zones)
29
Objective function (P) := (Distance + wf*Orientation)
Distance = 1000*d(CG_optim,CG_cad)
Orientation = angle between ( noptim and ncad )
Weight factor (wf) = 100
Fixations
Scan model
CAD model
ncad
nscn
1
2
7
10
84
3
6
9
5
Variables:
• Set of pressures
Limitations:
• Applying the least no. of pressures
• Pressures less than the permitted
value
30. Preliminary pressure optimization results
30
Objective function value = 0.33
1
2
7
10
84
3 6
9
5
Pressure
zone
1 2 3 4 5 6 7 8 9 10
Pressure
value [Pa]
21.2 0.0 0.0 0.0 0.0 0.0 0.0 19.8 31.0 0.0
Zone area
[m2]
0.024 0.031 0.035 0.049 0.069 0.061 0.046 0.030 0.040 0.062
Force value
[N]
0.509 0.000 0.000 0.000 0.000 0.000 0.000 1.235 2.338 0.000
Scan model
CAD model
31. Conclusion
31
• Automating the fixtureless inspection of non-rigid parts in a free-state.
• Improving the estimation of defect size in manufactured non-rigid parts.
• Validating the robustness of the improved inspection method.
• Virtually assembling a manufactured non-rigid part and reject faulty parts
before starting the assembly stage.
• Apply virtual assembly method on real cases with defects
• Study the nonlinear FE calculation effect on our simulations.
Future researches
32. Acknowledgement
32
• 7ème colloque québécois sur le développement numérique de produits
• National Sciences and Engineering Research Council of Canada (NSERC)
• Consortium for Aerospace Research and Innovation in Québec (CRIAQ)
• UQTR foundation
35. Simulation of scanned parts
35
simulation of
Scanned part
Part A
Bending
Torsion
Flexible deformation
Part B
Bending
Torsion
Small (local)
Big (global)
Defects
Small (local)
Big (global)
Small (local)
Big (global)
Small (local)
Big (global)
Bending
Torsion
36. Evaluation of defects (A_big defect_bending)
36
Actual: 1.5 mm
Evaluated: 0.09 mm
[mm]All generated sample points
39. References
39
• ASCIONE, R. & POLINI, W. 2010. Measurement of nonrigid freeform surfaces by coordinate
measuring machine. The International Journal of Advanced Manufacturing Technology, 51, 1055-
1067.
• BESL, P. J. & MCKAY, N. D. 1992. A Method for Registration of 3-D Shapes. Ieee Transactions on
Pattern Analysis and Machine Intelligence, 14, 239-256.
• SABRI, V., TAHAN, S. A., PHAM, X. T., RADVAR-ESFAHLAN, H., LOUHICHI, B. & TAHVILIAN, A. M.
Fixtureless profile inspection of non-rigid parts. 43rd International Conference on Computers and
Industrial Engineering (CIE43), 2013 The university of Hong Kong. [71].1-[71].11.
• CUILLIÈRE, J.-C., FRANCOIS, V. & DROUET, J.-M. 2013. Automatic 3D mesh generation of multiple
domains for topology optimization methods. Proceedings of the 21st International Meshing
Roundtable. Springer.
• DIJKSTRA, E. W. 1959. A note on two problems in connexion with graphs. Numerische mathematik,
1, 269-271.
• MASUDA, T. & YOKOYA, N. 1995. A Robust Method for Registration and Segmentation of Multiple
Range Images. Computer Vision and Image Understanding, 61, 295-307.
• Gentilini I, Shimada K (2011) Predicting and evaluating the post-assembly shape of thin-walled
components via 3D laser digitization and FEA simulation of the assembly process. Comput Aided
Des 43(3):316–328
• Blaedel K, Swift D, Claudet A, Kasper E, Patterson S (2002) Metrology of non-rigid objects. Tech.
Rep. UCRL-ID- 146957, Lawrence Livermore National Lab
40. References
40
• WECKENMANN, A. & GABBIA, A. 2006. Testing formed sheet metal parts using fringe projection and
evaluation by virtual distortion compensation. Fringe 2005, 539-546.
• WECKENMANN, A., GALL, P. & GABBIA, A. 2005. 3D surface coordinate inspection of formed sheet
material parts using optical measurement systems and virtual distortion compensation. Eighth
International Symposium on Laser Metrology, 5776, 640-647.
• WECKENMANN, A., GALL, P. & HOFFMANN, J. Inspection of holes in sheet metal using optical
measuring systems. Proceedings of VIth International Science Conference Coordinate Measuring
Technique (April 21-24, 2004, Bielsko-Biala, Poland), 2004. 339-346.
• WECKENMANN, A. & WEICKMANN, J. 2006. Optical Inspection of Formed Sheet Metal Parts
Applying Fringe Projection Systems and Virtual Fixation. Metrology and Measurement Systems, 13,
321-330.
• WECKENMANN, A., WEICKMANN, J. & PETROVIC, N. Shortening of inspection processes by
virtual reverse deformation. 4th international conference and exhibition on design and production of
machines and dies/molds, Cesme, Turkey, 2007.
• ABENHAIM, G. N., DESROCHERS, A. & TAHAN, A. 2012. Nonrigid parts' specification and
inspection methods: notions, challenges, and recent advancements. International Journal of
Advanced Manufacturing Technology, 63, 741-752.
• ABENHAIM, G. N., TAHAN, A. S., DESROCHERS, A. & MARANZANA, R. 2011. A Novel Approach
for the Inspection of Flexible Parts Without the Use of Special Fixtures. Journal of Manufacturing
Science and Engineering-Transactions of the Asme, 133.
• AIDIBE, A., TAHAN, A. & ABENHAIM, G. Dimensioning control of non-rigid parts using the iterative
displacement inspection with the maximum normed residual test. International conference on
theoretical and applied mechanics. Corfu Island, Greece, 2011.
• AIDIBE, A., TAHAN, A. S. & ABENHAIM, G. N. 2012. Distinguishing profile deviations from a part's
deformation using the maximum normed residual test. WSEAS Transactions on Applied & Theoretical
Mechanics, 7.
41. References
41
• RADVAR-ESFAHLAN, H. 2010. Geometrical inspection of flexible parts using intrinsic geometry.
École de technologie supérieure.
• RADVAR-ESFAHLAN, H. & TAHAN, S.-A. 2013. Robust generalized numerical inspection fixture for
the metrology of compliant mechanical parts. The International Journal of Advanced Manufacturing
Technology, 1-12.
• RADVAR-ESFAHLAN, H. & TAHAN, S. A. 2011. Nonrigid geometric metrology using generalized
numerical inspection fixtures. Precision Engineering-Journal of the International Societies for
Precision Engineering and Nanotechnology, 36, 1-9.
• RIVARA, M. C. 1997. New longest‐edge algorithms for the refinement and/or improvement of
unstructured triangulations. International journal for numerical methods in Engineering, 40, 3313-
3324.
• RIVARA, M. C. & INOSTROZA, P. 1997. USING LONGEST‐SIDE BISECTION TECHNIQUES FOR
THE AUTOMATIC REFINEMENT OF DELAUNAY TRIANGULATIONS. International journal for
numerical methods in Engineering, 40, 581-597.
• SABRI, V., TAHAN, S. A., PHAM, X. T., RADVAR-ESFAHLAN, H., LOUHICHI, B. & TAHVILIAN, A. M.
Fixtureless profile inspection of non-rigid parts. 43rd International Conference on Computers and
Industrial Engineering (CIE43), 2013 The university of Hong Kong. [71].1-[71].11.
• RIVARA, M. C. 1997. New longest‐edge algorithms for the refinement and/or improvement of
unstructured triangulations. International journal for numerical methods in Engineering, 40, 3313-
3324.
• RIVARA, M. C. & INOSTROZA, P. 1997. USING LONGEST‐SIDE BISECTION TECHNIQUES FOR
THE AUTOMATIC REFINEMENT OF DELAUNAY TRIANGULATIONS. International journal for
numerical methods in Engineering, 40, 581-597.
• SETHIAN, J. A. 1996. A fast marching level set method for monotonically advancing fronts.
Proceedings of the National Academy of Sciences, 93, 1591-1595.
47. 47
FEA non-rigid registration
GNIF method
CAD model Scanned model
Evaluated defects size
Corresponding Sample Points (CSP)
between CAD and scanned model
Deformed CAD using all CSP
Inspection: geometrical comparison
Sample points generating by GNIF method
48. 48
FEA non-rigid registration
Filtering CSP by von Mises stress criterion
GNIF method
CAD model Scanned model
Evaluated defects size
Corresponding Sample Points (CSP)
between CAD and scanned model
Filtered CSP by von Mises stress criterion
Deformed CAD using all CSP
Deformed CAD using filtered CSP
based on von Mises stress criterion
Inspection: geometrical comparison
FEA non-rigid registration
Sample point filtering based on von Mises stress criterion
49. 49
FEA non-rigid registration
Filtering CSP by Curvature criterion
GNIF method
CAD model Scanned model
Evaluated defects size
Corresponding Sample Points (CSP)
between CAD and scanned model
Filtered CSP by Curvature criterion
Deformed CAD using all CSP
Deformed CAD using filtered CSP
based on curvature criterion
Inspection: geometrical comparison
FEA non-rigid registration
Sample point filtering based on curvature criterion
50. Non-rigid (flexible) parts definition
50
Reference: G. N. Abenhaim, A. Desrochers, and A. Tahan, "Nonrigid parts' specification and inspection methods: notions, challenges,
and recent advancements," International Journal of Advanced Manufacturing Technology, vol. 63, pp. 741-752, Nov 2012.
Zones
Displacement by a reasonable force during
inspection (40 N)
Compliance behavior
A < 5 % Of the assigned tolerance Rigid
B > 10 % Of the assigned tolerance Nonrigid (Flexible)
C >> Of the assigned tolerance Extremely Nonrigid
Aerospace & automotive industries
52. Computer aided inspection (CAI)
52
Measured data:
• Scanned point-cloud
• In measured coordinate sys.
Designed model:
• CAD model
• In design coordinate sys.
53. Non-rigid (flexible) parts definition
53
Reference: G. N. Abenhaim, A. Desrochers, and A. Tahan, "Nonrigid parts' specification and inspection methods: notions, challenges,
and recent advancements," International Journal of Advanced Manufacturing Technology, vol. 63, pp. 741-752, Nov 2012.
Aerospace & automotive industries
Rigid Non-rigid Extremely non-rigid
54. Registration for a non-rigid part
54
X
Y
Rigid registration
CAD model Scanned model
Defect
X
Y
X
Y
Y
X
Y
58. Curvature distribution without bump (GNIF error)
58
Discrete CURV. diff. Kmax [mm-1] Discrete CURV. diff. Kmin [mm-1]
[mm-1] [mm-1]
59. Principal curvature differences distribution Gauss-Bonnet scheme
59
Discrete CURV. diff. Kmax [mm-1] Discrete CURV. diff. Kmin [mm-1][mm-1] [mm-1]
𝐾1 𝑝 = 𝐾 𝐻 𝑝 + 𝐾 𝐻
2
𝑝 − 𝐾 𝐺 𝑝
𝐾2(𝑝) = 𝐾 𝐻(𝑝) − 𝐾 𝐻
2
𝑝 − 𝐾 𝐺(𝑝)
KH : the mean curvature
KG : the Gaussian curvature
60. Generalized numerical inspection fixture (GNIF) method
60
• A non-rigid registration method
• Corresponding sample points
• Geodesic distances are preserved during an isometric deformation
• The CAD and scanned models are intrinsically the same
CAD-sp2 Scan-sp2
Correspondence
CAD model Scanned model
61. Corresponding sample points generated by GNIF method
61
Corresponding sample points are evenly distributed over the CAD and scanned models
FEA
63. Defect evaluation summary (A_Big defect_Bending)
63
Actual defect size
[mm]
Evaluated defect
size [mm]
Error [%]
Using all sample points 1.5 0.09 94
Filtering sample points with the
curvature criterion only
1.5 1.59 6
Filtering sample points with the
curvature and von Mises criteria
successively
1.5 1.6 7
64. Defect evaluation summary (A_Small defects_Torsion)
64
Actual defect size
[mm]
Evaluated defect size
[mm]
Error
[%]
Average error
[%]
Using all sample points
1.0 0.14 86
801.5 0.18 88
1.0 0.35 65
Filtering sample points with the
curvature criterion only
1.0 0.73 27
211.5 1.22 19
1.0 0.82 18
Filtering sample points with the
curvature and von Mises
criteria successively
1.0 0.79 21
201.5 1.20 20
1.0 0.81 19
65. Defect evaluation summary (A_Big defect_Torsion)
65
Actual defect size
[mm]
Evaluated defect
size [mm]
Error [%]
Using all sample points 1.5 0.08 95
Filtering sample points with the
curvature criterion only
1.5 1.6 7
Filtering sample points with the
curvature and von Mises criteria
successively
1.5 1.68 12
66. Defect evaluation summary (B_Small defects_Bending)
66
Actual defect size
[mm]
Evaluated defect size
[mm]
Error
[%]
Average error
[%]
Using all sample points
1.0 0.36 64
59
2.0 0.54 73
2.0 1.11 45
1.5 0.71 53
Filtering sample points with the
curvature criterion only
1.0 0.78 22
16
2.0 1.82 9
2.0 1.79 11
1.5 1.18 21
Filtering sample points with the
curvature and von Mises
criteria successively
1.0 0.76 24
16
2.0 1.82 9
2.0 1.75 13
1.5 1.22 19
67. Defect evaluation summary (B_Big defect_Bending)
67
Actual defect size
[mm]
Evaluated defect
size [mm]
Error [%]
Using all sample points 1 0.50 50
Filtering sample points with the
curvature criterion only
1 0.64 36
Filtering sample points with the
curvature and von Mises criteria
successively
1 0.83 17
68. Defect evaluation summary (B_Small defects_Torsion)
68
Actual defect size
[mm]
Evaluated defect size
[mm]
Error
[%]
Average error
[%]
Using all sample points
1.0 0.56 44
59
2.0 0.78 61
2.0 0.65 68
1.5 0.54 64
Filtering sample points with the
curvature criterion only
1.0 0.83 17
29
2.0 1.16 42
2.0 1.77 12
1.5 0.79 47
Filtering sample points with the
curvature and von Mises
criteria successively
1.0 0.90 10
27
2.0 1.32 34
2.0 1.67 17
1.5 0.81 46
69. Defect evaluation summary (B_Big defect_Torsion)
69
Actual defect size
[mm]
Evaluated defect
size [mm]
Error [%]
Using all sample points 1 0.51 49
Filtering sample points with the
curvature criterion only
1 0.79 21
Filtering sample points with the
curvature and von Mises criteria
successively
1 0.90 10
70. Defect evaluation summary
70
Actual defect size
[mm]
Evaluated defect size
[mm]
Error
[%]
Average error
[%]
Using all sample points
1.0 0.14 86
801.5 0.18 88
1.0 0.33 67
Filtering sample points with the
curvature criterion only
1.0 0.72 28
211.5 1.48 1
1.0 0.66 34
Filtering sample points with the
curvature and von Mises
criteria successively
1.0 0.74 26
181.5 1.47 2
1.0 0.73 27
72. Filtering sample points based on curvature criterion and defect evaluation
72
Actual: 1.5 mm
Evaluated: 1.59 mm
[mm]
Comparison between:
• Deformed CAD model filtered sample points
• Scanned model
Filtered sample points
73. Filtering sample points based on von Mises stress criterion
73
[Pa]
von Mises stress distribution
Deformed CAD model using
filtered sample points with
curvature criterion
Threshold
74. Filtering more sample points based on von Mises and defect evaluation
74
Actual: 1.5 mm
Evaluated: 1.6 mm
[mm]
Filtered sample points