A factorial analysis of input parameters using finite element techniques

1991 ◽  
Vol 9 (4) ◽  
pp. 221-231 ◽  
Author(s):  
Daniel F. Carbaugh ◽  
John L. Frater
Keyword(s):  
Finite Element ◽  
Factorial Analysis ◽  
Input Parameters

Development of a Stochastic Approach for Vehicle FE Models

2003 ◽  
Author(s):  
David Riha ◽  
Joseph Hassan ◽  
Marlon Forrest ◽  
Ke Ding
Keyword(s):  
Finite Element ◽  
Reliability Analysis ◽  
System Reliability ◽  
Model Parameters ◽  
Fe Model ◽  
Original Design ◽  
Acceptance Criteria ◽  
Model Input ◽  
Input Parameters ◽  
Occupant Injury

This paper describes the development of a mathematical model capable of providing realistic simulations of vehicle crashes by accounting for uncertainty in the model input parameters. The approach taken was to couple advanced and efficient probabilistic and reliability analysis methods with well-established, high fidelity finite element and occupant modeling software. Southwest Research Institute has developed probabilistic analysis software called NESSUS. This code was used as the framework for a stochastic crashworthiness FE model. The LS-DYNA finite element model of vehicle frontal offset impact and the MADYMO model of a 50th percentile male Hybrid III dummy were integrated with NESSUS to comprise the crashworthiness characteristics. The system reliability of the vehicle is computed by defining ten acceptance criteria performance functions; four occupant injury criteria and six compartment intrusion criteria. The reliability for each acceptance criteria was computed using NESSUS to identify the dominant acceptance criteria of the original design. The femur axial load acceptance criteria event has the lowest reliability (46%) followed by the HIC event (58%) and the door aperture closure event (73%). One approach to improve the reliability is to change vehicle parameters to improve the reliability for the dominant criteria. However, a parameter change such as vehicle strength/stiffness may have a beneficial effect on certain acceptance criteria but be detrimental to others. A system reliability analysis was used to include the contribution of all acceptance criteria to correctly quantify the vehicle reliability and identify important parameters. A redesign analysis was performed using the computed probabilistic sensitivity factors. These sensitivities were used to identify the most effective changes in model parameters to improve the reliability. A redesign using 11 design modifications was performed that increased the original reliability from 23% to 86%. Several of the design changes include increasing the rail material yield strength and reducing its variation, reducing the variation of the bumper and rail installation tolerances, and increasing the rail weld stiffness and reducing its variation. The results show that major reliability improvements for occupant injury and compartment intrusion can be realized by certain specific modifications to the model input parameters. A traditional (deterministic) method of analysis would not have suggested these modifications.

Study of the Effect of Process Induced Uncertainties on the Performance of a Micro-Comb Resonator

2009 ◽  
Vol 147-149 ◽  
pp. 716-725 ◽  
Author(s):  
Irina Codreanu ◽  
Adam Martowicz ◽  
A. Gallina ◽  
Łukasz Pieczonka ◽  
Tadeusz Uhl
Keyword(s):  
Sensitivity Analysis ◽  
Monte Carlo Simulation ◽  
Finite Element ◽  
Monte Carlo ◽  
Mode Shapes ◽  
Computational Techniques ◽  
Simulation Methods ◽  
Input Parameters ◽  
Mobile Mass ◽  
Study Case

This paper presents a modeling technique based on the integration in the classic deterministic simulation methods of probabilistic computational techniques such as uncertainty analysis and sensitivity analysis. As study case, it is presented a micro-comb resonator that is actuated electrostatically to vibrate in the plane parallel to the substrate. A deterministic Finite Element coupled electromechanical analysis is performed to evaluate the mode shapes and the corresponding eigenfrequencies of the mobile mass and afterwards a Monte Carlo simulation is used to determine the dispersion of the eigenfrequency of the mode shape of interest in function of the variations of the input parameters. The scatter of the results is analyzed and then it is presented a sensitivity analysis for establishing which of the input parameters have more influence on the variability of the microresonators performance.

Sensitivity of finite element analysis of forging to input parameters

1998 ◽  
Vol 82 (1-3) ◽  
pp. 21-26 ◽  
Author(s):  
R.G. Snape ◽  
S.E. Clift ◽  
A.N. Bramley
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Element Analysis ◽  
Input Parameters

scholarly journals Improving the biomechanical performance of screws fixation in a customized mandibular reconstruction prosthesis based on reliability measure

2021 ◽  
Author(s):  
Sahand Kargarnejad ◽  
Farzan Ghalichi ◽  
Mohammad Pourgol Mohammad ◽  
Ata Garajei
Keyword(s):  
Finite Element ◽  
Cortical Bone ◽  
Maximum Stress ◽  
Screw Fixation ◽  
Poor Performance ◽  
Fixation Strength ◽  
Stress And Strain ◽  
Plate Interface ◽  
Input Parameters ◽  
Von Mises

Background: The customized prosthesis is a new method for the reconstruction of large mandibular defects. The ability of dental rehabilitation to improve masticatory functions while maintaining the aesthetics of the main anatomy of the patient's jaw. But the most important problem with all custom prosthesis is the poor performance of screw fixation strength the connections at the bone-plate interface. Materials and Methods: This study was performed to investigate the effect of the number and layout of screws to improve the strength of the bone–prosthesis interface. Due to the inherent variability of input parameters, Analysis of the biomechanical performance of screw fixation strength, a probabilistic finite element method approach has been used. Random input parameters include mechanical properties of the cortical bone, cancellous bone, titanium alloy (Ti6Al4V), and bite force. The layout of the screws was designed in 6 models. Criteria for evaluating the biomechanical performance of screw fixation strength include maximum stress and strain of von Mises cortical bone around the screws. The Monte-Carlo method was used for finite element simulation. Results: The most critical screw in all models is screw No.1, which by increasing the number of screws and correcting the layout shape, the values of maximum stress and strain in the bone around screw No.1 has decreased by 26.7% and 46.3%, respectively, and increased the reliability of the screw connection performance by 25% and 28%, respectively. Conclusion: Finally, in the reconstruction of a large lateral mandibular defect by the customized prosthesis, the strength of the prosthesis to connect to the remaining mandible bone can be improved by increasing the number and modifying the layout of the screws.

Sign in / Sign up

Export Citation Format

Share Document