scholarly journals A Mix-resolution Bone-related Statistical Deformable Model (mBr-SDM) for Soft Tissue Prediction in Orthognathic Surgery Planning

2008 ◽  
Author(s):  
He Qizhen ◽  
Ip Horace ◽  
James Xia
Keyword(s):  
Finite Element ◽  
High Resolution ◽  
Orthognathic Surgery ◽  
Computational Cost ◽  
Element Model ◽  
Regions Of Interest ◽  
Deformable Model ◽  
Deformation Region ◽  
Low Computational Cost ◽  
Main Deformation

In this paper, we propose a Mix-resolution Bone-related Statistical Deformable Model (mBr-SDM) to improve the predicting accuracy of orthognathic surgery, particularly for the main deformation region. Mix-resolution Br-SDM consists of two separate Br-SDM of different resolutions: a high-resolution Br-SDM which is trained with more samples to capture the detail deforming variations in the main deforming regions of interest, together with a low-resolution Br-SDM which is trained with a smaller number of samples to capture the major variations of the remaining facial points. The experiments have shown that the mix-resolution Br-SDM is able to significantly reduce the predicting error compared with the corresponding Finite Element Model, while giving a low computational cost which is characteristic of the SDM approach.

scholarly journals Modeling and Stochastic Model Updating of Bolt-Jointed Structure

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Ming Zhan ◽  
Qintao Guo ◽  
Lin Yue ◽  
Baoqiang Zhang
Keyword(s):  
Finite Element ◽  
High Resolution ◽  
Material Properties ◽  
Model Updating ◽  
Computational Cost ◽  
Three Dimensional ◽  
Element Model ◽  
Joint Interface ◽  
Unknown Parameters ◽  
Updating Procedure

Bolt-jointed structure is widely used in engineering fields. The dynamic characteristics of bolt-jointed structure are complex, and there is a variety of uncertainties in the jointed structure. In this study, modeling and updating of a typical bolt-jointed structure are investigated. In modeling terms, three-dimensional brick elements are used to represent the substructures, and thin-layer elements with virtual material properties are employed to represent the joint interface. Modal tests and experimental modal analysis of substructures and built-up structure are performed. A hierarchical model updating strategy based on Bayesian inference is applied to identify the unknown parameters in the substructures model and those in the overall model. Radial basis function (RBF) models are used as surrogates of time-consuming finite element model with high resolution to avoid the enormous computational cost. The results indicate that the updated model can reproduce modal frequencies used in updating and can predict those not used in the updating procedure.

scholarly journals Model Updating Method Based on Kriging Model for Structural Dynamics

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Hong Yin ◽  
Jingjing Ma ◽  
Kangli Dong ◽  
Zhenrui Peng ◽  
Pan Cui ◽  
...  
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Frequency Response ◽  
Structural Dynamics ◽  
Model Updating ◽  
Computational Cost ◽  
Element Model ◽  
Kriging Model ◽  
Surface Model ◽  
Sample Points

Model updating in structural dynamics has attracted much attention in recent decades. And high computational cost is frequently encountered during model updating. Surrogate model has attracted considerable attention for saving computational cost in finite element model updating (FEMU). In this study, a model updating method using frequency response function (FRF) based on Kriging model is proposed. The optimal excitation point is selected by using modal participation criterion. Initial sample points are chosen via design of experiment (DOE), and Kriging model is built using the corresponding acceleration frequency response functions. Then, Kriging model is improved via new sample points using mean square error (MSE) criterion and is used to replace the finite element model to participate in optimization. Cuckoo algorithm is used to obtain the updating parameters, where the objective function with the minimum frequency response deviation is constructed. And the proposed method is applied to a plane truss model FEMU, and the results are compared with those by the second-order response surface model (RSM) and the radial basis function model (RBF). The analysis results showed that the proposed method has good accuracy and high computational efficiency; errors of updating parameters are less than 0.2%; damage identification is with high precision. After updating, the curves of real and imaginary parts of acceleration FRF are in good agreement with the real ones.

Normal Flux Distribution at Step-Lap Joints of Si-Fe Wound Cores

2010 ◽  
Vol 670 ◽  
pp. 284-290 ◽  
Author(s):  
Themistoklis D. Kefalas ◽  
George Loizos ◽  
Antonios G. Kladas
Keyword(s):  
Finite Element ◽  
Flux Distribution ◽  
Computational Cost ◽  
Lap Joints ◽  
Accurate Estimation ◽  
Element Analysis ◽  
Lack Of Information ◽  
Simple Geometry ◽  
Flux Measurements ◽  
Low Computational Cost

Even though, the flux distribution at joints of stacked type transformer cores has been investigated thoroughly many issues remain unclear in the case of wound transformer cores. The paper addresses this lack of information by longitudinal and normal flux measurements at step-lap joints of Si-Fe wound cores. Flux measurements are verified by an original finite element analysis where the necessary excitation is performed by means of a pseudo-source. The advantage of the proposed technique is the accurate estimation of the flux distribution at step-lap joints, with a two dimensional model of simple geometry and low computational cost, by using any commercial finite element code.

Highly Efficient Probabilistic Finite Element Model Updating Using Intelligent Inference With Incomplete Modal Information

2016 ◽  
Vol 138 (5) ◽  
Author(s):  
K. Zhou ◽  
J. Tang
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Model Updating ◽  
Computational Cost ◽  
Sampling Technique ◽  
Element Model ◽  
Measurement Information ◽  
Model Parameters ◽  
Finite Element Model Updating ◽  
Highly Efficient

A highly efficient probabilistic framework of finite element model updating in the presence of measurement noise/uncertainty using intelligent inference is presented. This framework uses incomplete modal measurement information as input and is built upon the Bayesian inference approach. To alleviate the computational cost, Metropolis–Hastings Markov chain Monte Carlo (MH MCMC) is adopted to reduce the size of samples required for repeated finite element modal analyses. Since adopting such a sampling technique in Bayesian model updating usually yields a sparse posterior probability density function (PDF) over the reduced parametric space, Gaussian process (GP) is then incorporated in order to enrich analysis results that can lead to a comprehensive posterior PDF. The PDF obtained with densely distributed data points allows us to find the most optimal model parameters with high fidelity. To facilitate the entire model updating process with automation, the algorithm is implemented under ansys Parametric Design Language (apdl) in ansys environment. The effectiveness of the new framework is demonstrated via systematic case studies.

Efficient Uncertainty Quantification in Structural Dynamic Analysis Using Two-Level Gaussian Processes

2015 ◽  
Author(s):  
Kai Zhou ◽  
Pei Cao ◽  
Jiong Tang
Keyword(s):  
Finite Element ◽  
Dynamic Analysis ◽  
Uncertainty Quantification ◽  
Large Scale ◽  
Computational Cost ◽  
Response Prediction ◽  
Element Model ◽  
High Fidelity ◽  
Structural Dynamic ◽  
Rapid Sampling

Uncertainty quantification is an important aspect in structural dynamic analysis. Since practical structures are complex and oftentimes need to be characterized by large-scale finite element models, component mode synthesis (CMS) method is widely adopted for order-reduced modeling. Even with the model order-reduction, the computational cost for uncertainty quantification can still be prohibitive. In this research, we utilize a two-level Gaussian process emulation to achieve rapid sampling and response prediction under uncertainty, in which the low- and high-fidelity data extracted from CMS and full-scale finite element model are incorporated in an integral manner. The possible bias of low-fidelity data is then corrected through high-fidelity data. For the purpose of reducing the emulation runs, we further employ Bayesian inference approach to calibrate the order-reduced model in a probabilistic manner conditioned on multiple predicted response distributions of concern. Case studies are carried out to validate the effectiveness of proposed methodology.

Finite Element Models of One Dimensional Flows With Node-Dependent Accuracy

2018 ◽  
Author(s):  
Daniele Guarnera ◽  
Enrico Zappino ◽  
Alfonso Pagani ◽  
Erasmo Carrera
Keyword(s):  
Finite Element ◽  
Stokes Problem ◽  
Computational Cost ◽  
Circulatory System ◽  
Element Model ◽  
Laminar Flows ◽  
Sudden Expansion ◽  
Fe Modelling ◽  
Weak Formulation ◽  
One Dimensional

The formulation of simplified models in the description of flow fields can be highly interesting in many complex network such as the circulatory system. This work presents a refined one-dimensional finite element model with node-dependent kinematics applied to incompressible and laminar flows. In the framework of 1D-FE modelling, this methodology is a new development of the Carrera Unified Formulation (CUF), which is largely employed in structural mechanics. According to the CUF, the weak formulation of the Stokes problem is expressed in terms of fundamental nuclei and, in this novel implementation, the kinematics can be defined node by node, realizing different levels of refinements within the main direction of the pipe. Such feature allows to increase the accuracy of the model only in the areas of the domain where it is required, i.e. particular boundary condition, barriers or sudden expansion. Some typical CFD examples are proposed to validate this novel technique, including Stokes flows in uniform and non-uniform domains. For each numerical example, different combinations of 1D models have been considered to account for different kinematic approximations of flows, and in particular, models based on Taylor and Lagrange expansion have been used. The results, compared with ones obtained from uniform kinematics 1D models and with those come from available tools, highlight the capability of the proposed model in handling non-conventional boundary conditions with ease and in preserving the computational cost without any accuracy loss.

scholarly journals An Efficient Image Enlargement Method for Image Sensors of Mobile in Embedded Systems

2016 ◽  
Vol 2016 ◽  
pp. 1-12
Author(s):  
Hua Hua ◽  
Xiaomin Yang ◽  
Binyu Yan ◽  
Kai Zhou ◽  
Wei Lu
Keyword(s):  
High Resolution ◽  
Embedded Systems ◽  
Embedded System ◽  
Computational Cost ◽  
Image Sensors ◽  
Memory Usage ◽  
Least Squares Regression ◽  
Efficient Manner ◽  
Image Enlargement ◽  
Low Computational Cost

Main challenges for image enlargement methods in embedded systems come from the requirements of good performance, low computational cost, and low memory usage. This paper proposes an efficient image enlargement method which can meet these requirements in embedded system. Firstly, to improve the performance of enlargement methods, this method extracts different kind of features for different morphologies with different approaches. Then, various dictionaries based on different kind of features are learned, which represent the image in a more efficient manner. Secondly, to accelerate the enlargement speed and reduce the memory usage, this method divides the atoms of each dictionary into several clusters. For each cluster, separate projection matrix is calculated. This method reformulates the problem as a least squares regression. The high-resolution (HR) images can be reconstructed based on a few projection matrixes. Numerous experiment results show that this method has advantages such as being efficient and real-time and having less memory cost. These advantages make this method easy to implement in mobile embedded system.

Effects of Grain Orientations on Nanoindentation Behavior in Hexagonal Zirconium

2011 ◽  
Vol 702-703 ◽  
pp. 311-314 ◽  
Author(s):  
Arijit Lodh ◽  
Indradev Samajdar ◽  
Raghvendra Tewari ◽  
Dinesh Srivastava ◽  
Gautam Kumar Dey ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Finite Element ◽  
High Resolution ◽  
Electron Diffraction ◽  
Crystal Orientation ◽  
Element Model ◽  
Orientation Dependence ◽  
Strain Hardening Exponent ◽  
Resolution Electron ◽  
Grain Orientations

The present study deals with nanoindentation behavior of commercial Zircaloy 2 and high purity (5N purity) crystal bar Zirconium. The effect of crystal orientation was studied through high resolution electron diffraction, while a finite element model was developed to extract yield strength and strain hardening exponent from nanoindentation data. The study brings in clear signatures of orientation dependence of mechanical properties in hexagonal Zirconium.

Finite element model-based tumor registration of microPET and high-resolution MR images for photodynamic therapy in mice

2006 ◽  
Author(s):  
Baowei Fei ◽  
Hesheng Wang ◽  
Raymond F. Muzic, Jr. ◽  
Chris A. Flask ◽  
Denise Feyes ◽  
...  
Keyword(s):  
Finite Element ◽  
Photodynamic Therapy ◽  
High Resolution ◽  
Finite Element Model ◽  
Element Model ◽  
Mr Images ◽  
Model Based
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