Fast Structural Analysis for Deforming Objects sing Machine Learning .850 Project, Spring 2014
نویسنده
چکیده
The motivation of this work is customizing 3D models for fabrication. It is desirable to update the visualization of the model’s problematic areas in real time during editing, but often these analysis algorithms are very time consuming. We investigate creating a fast update algorithm for per-vertex model fragility using machine learning. We propose and analyze a new feature vector formulation and present preliminary classification results.
منابع مشابه
TBM Tunneling Construction Time with Respect to Learning Phase Period and Normal Phase Period
In every tunnel boring machine (TBM) tunneling project, there is an initial low production phase so-called the Learning Phase Period (LPP), in which low utilization is experienced and the operational parameters are adjusted to match the working conditions. LPP can be crucial in scheduling and evaluating the final project time and cost, especially for short tunnels for which it may constitute a ...
متن کاملLarge Amplitude Vibration Analysis of Graphene Sheets as Resonant Mass Sensors Using Mixed Pseudo-Spectral and Integral Quadrature Methods
The present paper investigates the potential application of graphene sheets with attached nanoparticles as resonant sensors by introducing a nonlocal shear deformation plate model. To take into account an elastic connection between the nanoplate and the attached nanoparticle, the nanoparticle is considered as a mass-spring system. Then, a combination of pseudo-spectral and integral quadrature m...
متن کاملFault diagnosis in a distillation column using a support vector machine based classifier
Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...
متن کاملStructure Health Monitoring in Extreme Events from Machine Learning Perspective
Structure health monitoring utilizes the statistical signal information gathered from sensors implemented on structures to detect the building behavior. This information is more accurate and easier to analyze than traditional structural analysis method, which detects the building damage using dynamic properties directly. In this project, acceleration time history records of a Benchmark structur...
متن کاملA METAHEURISTIC-BASED ARTIFICIAL NEURAL NETWORK FOR PLASTIC LIMIT ANALYSIS OF FRAMES
Despite the advantages of the plastic limit analysis of structures, this robust method suffers from some drawbacks such as intense computational cost. Through two recent decades, metaheuristic algorithms have improved the performance of plastic limit analysis, especially in structural problems. Additionally, graph theoretical algorithms have decreased the computational time of the process impre...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2014