Multi-3D-Models Registration-Based Augmented Reality (AR) Instructions for Assembly

This paper introduces a novel, markerless, step-by-step, in-situ 3D Augmented Reality (AR) instruction method and its application - BRICKxAR (Multi 3D Models/M3D) - for small parts assembly. BRICKxAR (M3D) realistically visualizes rendered 3D assembly parts at the assembly location of the physical assembly model (Figure 1). The user controls the assembly process through a user interface. BRICKxAR (M3D) utilizes deep learning-trained 3D model-based registration. Object recognition and tracking become challenging as the assembly model updates at each step. Additionally, not every part in a 3D assembly may be visible to the camera during the assembly. BRICKxAR (M3D) combines multiple assembly phases with a step count to address these challenges. Thus, using fewer phases simplifies the complex assembly process while step count facilitates accurate object recognition and precise visualization of each step. A testing and heuristic evaluation of the BRICKxAR (M3D) prototype and qualitative analysis were conducted with users and experts in visualization and human-computer interaction. Providing robust 3D AR instructions and allowing the handling of the assembly model, BRICKxAR (M3D) has the potential to be used at different scales ranging from manufacturing assembly to construction

Determination of thermal conductivity of eutectic Al-Cu compounds utilizing experiments, molecular dynamics simulations and machine learning

In this study, the thermal conductivity ( κ ) of Al-Cu eutectics were investigated by experimental and computational methods to shed light on the role of these compounds in thermal properties of Al-Cu connections in compound casting. Specifically, the nonequilibrium molecular dynamics (MD) method was utilized to simulate the lattice thermal conductivity ( κ l ) of six compositions of Al-Cu with 5-30 at.% Cu. To extend the results of the MD simulations to bulk materials, instead of using conventional linear extrapolation methods, a machine learning approach was developed for the dataset acquired from the MD simulations. The bootstrapping approach was utilized to find the most suitable method among the support vector machine (SVM) with polynomial and radial basis function (RBF) kernels and the random forest method. The results showed that the SVM model with RBF kernel performed the best, and thus was used to predict the bulk κ l . Subsequently, the chosen compositions were produced by induction casting and their electrical conductivities were measured via eddy current method for calculating the electronic contribution of κ using the Wiedemann-Franz law. Finally, the actual κ of the alloys were measured using the xenon flash method and the results were compared with the computational values. It was shown that the MD method is capable of successfully simulating the thermal conductivity of this system. In addition, the experimental results demonstrated that the κ of Al-Cu eutectics decreases almost linearly with formation of the Al2Cu phase due to increase in the Cu content. Overall, the current findings can be used to enhance the κ of cooling devices made via Al-Cu compound casting

A Detailed Investigation of the Strain Hardening Response of Aluminum Alloyed Hadfield Steel

147 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.The success of the model was tested by its application to different crystallographic orientations, and finally the polycrystals of the aluminum alloyed Hadfield steel. Meanwhile, the capability of the model to predict texture was also observed through the rotation of the loading axis in single crystals. The ability of the model to capture the polycrystalline deformation response provides a venue for its utilization in other alloys that exhibit dislocation sheet structures.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

A Detailed Investigation of the Strain Hardening Response of Aluminum Alloyed Hadfield Steel

147 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2005.The success of the model was tested by its application to different crystallographic orientations, and finally the polycrystals of the aluminum alloyed Hadfield steel. Meanwhile, the capability of the model to predict texture was also observed through the rotation of the loading axis in single crystals. The ability of the model to capture the polycrystalline deformation response provides a venue for its utilization in other alloys that exhibit dislocation sheet structures.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD

Web-Based Parametric Modeling for Architectural Design and Optimization: Case Studies

This thesis presents a new framework for Web-based parametric modeling for design collaboration, towards allowing multiple users to work on the shared Web-based model in the process of drafting, design, simulation, and optimization. The framework consists of a WebGL-based model Viewer (Autodesk Forge Viewer), two visual programming tools, Grasshopper and Dynamo, and two software prototypes developed for this thesis. The prototypes, one for Grasshopper, the other for Dynamo, provide the communication between the Viewer and the visual programming tools. The Web-based 3D model and design data can be viewed in the Viewer. The Web-based model is controlled and modified through the visual programming tools using the prototypes. The embodiment of the Web-based information technology, WebGL and networking, makes it possible for users to view the Web-based model, collaborate, and participate in modeling through Web browsers. The full-fledged visual programming environments, Grasshopper and Dynamo, enable users to interact with the parametric Web-based model; the plugins of the visual programming tools allow users to implement building energy performance (BEP) simulation and optimization while the Web-based model enables collaborative design exploration. Two case studies with three tests each were conducted on a simplified residential building model. In Case Study 1, two simulated users (actions done by the author) tested the parametric capabilities of the shared Web-based model using Grasshopper and Dynamo. The basic geometric transformations including scale, translate, and rotate were tested in Tests 1.1, 1.2, and 1.3 respectively. In the Case Study 2, the collaboration of two Grasshopper users on the shared Web-based model in the process of optimization for different building performance objectives -in terms of daylight, energy use, and roof coverage- was tested. Case Study 2 was conducted through three tests of optimization. (i) In Test 2.1, the objectives were maximum preferred daylight and minimum roof shape with shading. (ii) In Test 2.2, the objectives were minimum energy and minimum roof shape with shading. (iii) In Test 2.3, minimum energy use was the first objective, maximum preferred daylight and minimum roof shape with shading was the second objective. The findings demonstrate that the framework successfully provides interoperable Web-based architectural models which could be controlled parametrically through different visual programming tools. The framework also constitutes an environment of collaboration between Grasshopper users during daylight, energy, and integrated daylight and energy optimization along with the optimization of the roof shape. In both collaboration cases, the users retrieve data from the Web-based model to update their visual programming files. Major technical limitations of the framework are also found and discussed. Future work includes automation of the data flow through Web to the local visual programming files and contributing to the interoperability solutions by incorporating other tools

Web-Based Parametric Modeling for Architectural Design and Optimization: Case Studies

This thesis presents a new framework for Web-based parametric modeling for design collaboration, towards allowing multiple users to work on the shared Web-based model in the process of drafting, design, simulation, and optimization. The framework consists of a WebGL-based model Viewer (Autodesk Forge Viewer), two visual programming tools, Grasshopper and Dynamo, and two software prototypes developed for this thesis. The prototypes, one for Grasshopper, the other for Dynamo, provide the communication between the Viewer and the visual programming tools. The Web-based 3D model and design data can be viewed in the Viewer. The Web-based model is controlled and modified through the visual programming tools using the prototypes. The embodiment of the Web-based information technology, WebGL and networking, makes it possible for users to view the Web-based model, collaborate, and participate in modeling through Web browsers. The full-fledged visual programming environments, Grasshopper and Dynamo, enable users to interact with the parametric Web-based model; the plugins of the visual programming tools allow users to implement building energy performance (BEP) simulation and optimization while the Web-based model enables collaborative design exploration. Two case studies with three tests each were conducted on a simplified residential building model. In Case Study 1, two simulated users (actions done by the author) tested the parametric capabilities of the shared Web-based model using Grasshopper and Dynamo. The basic geometric transformations including scale, translate, and rotate were tested in Tests 1.1, 1.2, and 1.3 respectively. In the Case Study 2, the collaboration of two Grasshopper users on the shared Web-based model in the process of optimization for different building performance objectives -in terms of daylight, energy use, and roof coverage- was tested. Case Study 2 was conducted through three tests of optimization. (i) In Test 2.1, the objectives were maximum preferred daylight and minimum roof shape with shading. (ii) In Test 2.2, the objectives were minimum energy and minimum roof shape with shading. (iii) In Test 2.3, minimum energy use was the first objective, maximum preferred daylight and minimum roof shape with shading was the second objective. The findings demonstrate that the framework successfully provides interoperable Web-based architectural models which could be controlled parametrically through different visual programming tools. The framework also constitutes an environment of collaboration between Grasshopper users during daylight, energy, and integrated daylight and energy optimization along with the optimization of the roof shape. In both collaboration cases, the users retrieve data from the Web-based model to update their visual programming files. Major technical limitations of the framework are also found and discussed. Future work includes automation of the data flow through Web to the local visual programming files and contributing to the interoperability solutions by incorporating other tools

A Microstructure-Sensitive Model for Simulating the Impact Response of a High-Manganese Austenitic Steel

Microstructurally informed macroscopic impact response of a high-manganese austenitic steel was modeled through incorporation of the viscoplastic self-consistent (VPSC) crystal plasticity model into the ANSYS LS-DYNA nonlinear explicit finite-element (FE) frame. Voce hardening flow rule, capable of modeling plastic anisotropy in microstructures, was utilized in the VPSC crystal plasticity model to predict the micromechanical response of the material, which was calibrated based on experimentally measured quasi-static uniaxial tensile deformation response and initially measured textures. Specifically, hiring calibrated Voce parameters in VPSC, a modified material response was predicted employing local velocity gradient tensors obtained from the initial FE analyses as a new boundary condition for loading state. The updated micromechanical response of the material was then integrated into the macroscale material model by calibrating the Johnson-Cook (JC) constitutive relationship and the corresponding damage parameters. Consequently, we demonstrate the role of geometrically necessary multi-axial stress state for proper modeling of the impact response of polycrystalline metals and validate the presented approach by experimentally and numerically analyzing the deformation response of the Hadfield steel (HS) under impact loading

Incorporation of Dynamic Strain Aging Into a Viscoplastic Self-Consistent Model for Predicting the Negative Strain Rate Sensitivity of Hadfield Steel

A new multiscale modeling approach is proposed to predict the contributions of dynamic strain aging (DSA) and the resulting negative strain rate sensitivity (NSRS) on the unusual strain-hardening response of Hadfield steel (HS). Mechanical response of HS was obtained from monotonic and strain rate jump experiments under uniaxial tensile loading within the 10 À4 to 10 À1 s À1 strain rate range. Specifically, a unique strain-hardening model was proposed that incorporates the atomic-level local instabilities imposed upon by the pinning of dislocations by diffusing carbon atoms to the classical Voce hardening. The novelty of the current approach is the computation of the shear stress contribution imposed on arrested dislocations leading to DSA at the atomic level, which is then implemented to the overall strain-hardening rule at the microscopic level. The new model not only successfully predicts the role of DSA and the resulting NSRS on the macroscopic deformation response of HS but also opens the venue for accurately predicting the deformation response of rate-sensitive metallic materials under any given loading condition