Modeling Implications in Simulation-Based Design of Stents

2006 ◽  
Author(s):  
Tiefu Shao ◽  
Sundar Krishnamurty
Keyword(s):  
Detailed Comparison ◽  
Surrogate Models ◽  
Process Efficiency ◽  
Element Analysis ◽  
Sampling Schemes ◽  
Simulation Based Design ◽  
Simulation Based ◽  
The Cost ◽  
Design Preferences ◽  
Analysis Models

Variations associated with stenting systems, artery properties, and doctor skills necessitate a better understanding of coronary artery stents so as to facilitate the design of stents that are customized to individual patients. This paper presents the development of an integrated computer simulation-based design approach using engineering finite element analysis (FEA) models for capturing stent knowledge, utility theory-based decision models for representing the design preferences, and statistics-based surrogate models for improving process efficiency. Two focuses of the paper are: 1) understanding the significance of engineering analysis and surrogate models in the simulation-based design of medical devices; 2) investigating the modeling implications in the context of stent design. The study reveals that the advanced nonlinear FEA software with analysis capacities on large deformation and contact interaction has offered a platform to execute high fidelity simulations, yet the selection of appropriate analysis models is still subject to the tradeoff between cost of analysis and accuracy of solution; the cost-prohibitive simulations necessitate the employment of surrogate models in subsequent multi-objective design optimization. A detailed comparison between regression models and Kriging models suggests the importance of sampling schemes in successfully implementing Kriging methods.

Miniaturization of injection abrasive water jet machining process

2006 ◽  
Vol 220 (11) ◽  
pp. 1697-1705 ◽  
Author(s):  
H Orbanic ◽  
B Jurisevic ◽  
D Kramar ◽  
M Grah ◽  
M Junkar
Keyword(s):  
Water Jet ◽  
Heat Sinks ◽  
Machining Process ◽  
Process Efficiency ◽  
Abrasive Water Jet ◽  
Element Analysis ◽  
Abrasive Particles ◽  
Cutting Head ◽  
Simulation Based ◽  
Awj Cutting

This contribution presents the possibilities of applying abrasive water jet (AWJ) technology for multi-material micromanufacture. The working principles of injection and suspension AWJ systems are presented. Characteristics of this technology, such as the ability to machine virtually any kind of material and the absence of a relevant heat-affected zone, are given, especially those from which the production of microcomponents can benefit. A few attempts to miniaturize the AWJ machining process are described in the state-of-the-art preview. In order to develop and improve the AWJ as a microtool, a numerical simulation based on the finite element analysis is introduced to evaluate the effect of the size abrasive particles and the process efficiency of microsized AWJ. An ongoing project in which an improved mini AWJ cutting head is being developed, is presented. Finally, the possible fields of application are given, including a case study on the machining of miniaturized heat sinks.

A Maximum Confidence Enhancement Based Sequential Sampling Scheme for Simulation-Based Design

2013 ◽  
Author(s):  
Zequn Wang ◽  
Pingfeng Wang
Keyword(s):  
Confidence Level ◽  
Sequential Sampling ◽  
Surrogate Models ◽  
Design Sensitivity ◽  
Reliability Estimation ◽  
Sampling Scheme ◽  
Design Variables ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Maximum Improvement

This paper presents a maximum confidence enhancement based sequential sampling approach for simulation-based design under uncertainty. In the proposed approach, the ordinary Kriging method is adopted to construct surrogate models for all constraints and thus Monte Carlo simulation (MCS) is able to be used to estimate reliability and its sensitivity with respect to design variables. A cumulative confidence level is defined to quantify the accuracy of reliability estimation using MCS based on the Kriging models. To improve the efficiency of proposed approach, a maximum confidence enhancement based sequential sampling scheme is developed to update the Kriging models based on the maximum improvement of the defined cumulative confidence level, in which a sample that produces the largest improvement of the cumulative confidence level is selected to update the surrogate models. Moreover, a new design sensitivity estimation approach based upon constructed Kriging models is developed to estimate the reliability sensitivity information with respect to design variables without incurring any extra function evaluations. This enables to compute smooth sensitivity values and thus greatly enhances the efficiency and robustness of the design optimization process. Two case studies are used to demonstrate the proposed methodology.

scholarly journals Simulation Based Design and Evaluation of a Transcatheter Mitral Heart Valve Frame

2012 ◽  
Vol 6 (3) ◽  
Author(s):  
Melissa Young ◽  
Ahmet Erdemir ◽  
Samantha Stucke ◽  
Ryan Klatte ◽  
Brian Davis ◽  
...  
Keyword(s):  
Mitral Valve ◽  
Heart Surgery ◽  
Large Diameter ◽  
Open Heart Surgery ◽  
Element Analysis ◽  
Mechanical Fracture ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Desirable Feature ◽  
Computational Modeling And Simulation

In certain populations, open heart surgery to replace a diseased mitral valve is not an option, leaving percutaneous delivery a viable alternative. However, a surgical transcatheter based delivery of a metallic support frame incorporating a tissue derived valve puts considerable constraints on device specifications. Expansion to a large diameter from the catheter diameter without mechanical fracture involves advanced device design and appropriate material processing and selection. In this study, a new frame concept is presented with a desirable feature that incorporates wings that protrude during expansion to establish adequate fixation. Expansion characteristics of the design in relation to annulus fixation were quantified through finite element analysis predictions of the frame wing span and angles. Computational modeling and simulation was used to identify many favorable design features for the transcatheter mitral valve frame and obtain desired expansion diameters (35–45 mm), acceptable radial stiffness (2.7 N/mm), and ensure limited risk of failure based on predicted plastic deformations.

scholarly journals Analysis of a Lightweight Aluminum Vehicle Chassis in a Simulation-Based Design Approach

2020 ◽  
pp. 1-10
Author(s):  
Mohsen Alardhi ◽  
Fahad Almaskari ◽  
Melad Fahed ◽  
Jasem Alrajhi
Keyword(s):  
Safety Factor ◽  
Side Impact ◽  
Design Approach ◽  
Element Analysis ◽  
Trade Offs ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Impact Side ◽  
Von Mises ◽  
Vehicle Chassis

This study investigates different chassis designs through a simulation-based design approach. The inherent aluminum ductility and softness could make chassis a daunting modification if not analyzed properly. Structural finite element analysis is comprehensively performed on a vehicle chassis for static loading cases up to 1G in equivalent acceleration. The analysis of the vehicle chassis of both A36 steel and 6061 aluminum for the scenarios of bump, front impact, side impact and a rollover. The von Mises stresses and displacement results showed that the steel chassis possessed higher safety factor in all load cases. The safety factors for an aluminum clone of the steel chassis in some load cases are below 1.0, hence indicating that the failure criterion has been triggered and failure would occur under the 1G load. The original aluminum chassis deformation is far more severe than steel reaching as high as 9.88 mm for the bump loading. A modified aluminum chassis is proposed, by optimizing the wall thickness of the rectangular bars. The slight increase in weight resulted in overcoming the deficiency of aluminum in load carrying capacity. An evaluation matrix procedure is implemented to analyze the trade offs between cost, weight and safety factor for the three chassis materials.

SIMULATION-BASED DESIGN METHOD FOR ROOM AIR CONDITIONER WITH SMALLER DIAMETER COPPER TUBES

2012 ◽  
Vol 20 (03) ◽  
pp. 1250012 ◽  
Author(s):  
GUOLIANG DING ◽  
TAO REN ◽  
YONGXIN ZHENG ◽  
YIFENG GAO ◽  
JI SONG
Keyword(s):  
Heat Exchanger ◽  
Design Method ◽  
Copper Tube ◽  
Air Conditioner ◽  
Air Conditioners ◽  
Knowledge Based ◽  
Simulation Based Design ◽  
Simulation Based ◽  
The Cost

Promoting the use of smaller diameter tube in room air conditioner is beneficial to reduce copper consumption and refrigerant charge, but may cause reduction of air conditioner performance, so a design method is needed. This paper presents a simulation-based design method for air conditioner with smaller diameter tube. The new method combines heat exchanger simulator and knowledge-based evolution method optimizer for designing air conditioner heat exchanger with smaller diameter tube. The simulation-based design method is illustrated in detail by an air conditioner of replacing 7 mm tube indoor unit heat exchanger and 9.52 mm tube outdoor unit heat exchanger with 5 mm tube. Case study shows that the cost of the designed air conditioner with 5 mm copper tube is 17.3% lower than that of the original one while the performance deviation between these two air conditioners is less than 0.7%.

Web-Based Self-Paced Virtual Prototyping Tutorials

2003 ◽  
Author(s):  
Rajankumar Bhatt ◽  
Chin Pei Tang ◽  
Leng-Feng Lee ◽  
Venkat Krovi
Keyword(s):  
Engineering Design ◽  
Virtual Environment ◽  
Virtual Prototyping ◽  
Engineering Curriculum ◽  
Engineering Analysis ◽  
Web Based ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Analysis Models ◽  
Crucial Part

By permitting designers to realistically, accurately and quantitatively prototype and test multiple intermediate models within virtual environment, Virtual Prototyping (VP), also known as Simulation-Based Design (SBD), has rapidly gained popularity and become a crucial part of most engineering design processes. While there is a significant demand from industry for students trained in this methodology, currently there is not much room in engineering curriculum to permit widespread adoption in the lecture-based classroom. In this paper, we describe the rationale and the stages in the development of a series of web-based and self-paced VP tutorials targeted at students of a course in machine and mechanism design. These undergraduate seniors are permitted to: (1) interactively explore the process of creating engineering analysis models in integrated VP environment; (2) develop skills for interactive SBD of models; and (3) develop their engineering judgment by interactive exploration of a spectrum of examples. The outcome of a phased introduction of these exercises and our experience based on the first successful course offering are also discussed.

Surrogate Model Updating Using Clustering in a Genetic Algorithm Setup

2006 ◽  
Author(s):  
Tiefu Shao ◽  
Sundar Krishnamurty
Keyword(s):  
Genetic Algorithm ◽  
Surrogate Model ◽  
Model Building ◽  
Model Updating ◽  
Cost Effective ◽  
Critical Issue ◽  
Surrogate Models ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Updating Procedure

This paper addresses the critical issue of fidelity in simulation-based design optimization using preference-based surrogate models. Specifically, it presents an integrated clustering-based updating procedure in a genetic algorithm setup to iteratively improve the efficacy of Kriging models. A potential drawback of using preference-based surrogate models in simulation based design is that the surrogates may misrepresent the true optima if the model building schemes fail to capture the critical points of interest with enough fidelity or clarity. This work addresses this vulnerability and presents an efficient clustering-technique integrated surrogate model updating procedure that can capture the buried, transient, yet inherent data pattern in the evolution progression of design candidates within a genetic algorithm setup, and screen out distinct optimal points for subsequent sequential model validation and updating. The results show that the successful finding of the true optimal design through cost-effective surrogate-based optimization depends not only on the selection of sampling schemes such as sample rate and distribution in the initial surrogate model build-up, but also on an efficient and reliable updating procedure that can prevent suboptimal decisions.

Knowledge Composition for Efficient Analysis Problem Formulation: Part 1 — Motivation and Requirements

2007 ◽  
Author(s):  
Manas Bajaj ◽  
Russell S. Peak ◽  
Christiaan J. J. Paredis
Keyword(s):  
Gap Analysis ◽  
Problem Formulation ◽  
Analysis Problem ◽  
Element Analysis ◽  
Design Alternatives ◽  
Simulation Based Design ◽  
Variable Topology ◽  
Commercial Off The Shelf ◽  
Multi Body ◽  
Analysis Models

In simulation-based design a key challenge is to formulate and solve analysis problems efficiently to evaluate a variety of design alternatives. Numerically solving analysis problems has benefited from advancements in commercial off-the-shelf mathematical solvers and computational capabilities. However, the formulation of analysis problems for a given set of design alternatives is still typically a laborious and costly process. In the scope of design alternatives with variable topology multi-body (VTMB) characteristics, these papers (Part 1 and Part 2) present research that addresses the following primary question: How can we improve the efficiency of the analysis problem formulation process for VTMB design alternatives? The objective of this paper (Part 1) is to identify requirements for a methodology that answers this. The methodology is formulates analysis problems for VTMB design alternatives based on decisions taken by analysts and independent of the solution method (such as finite element analysis) and the solver. This paper presents a gap analysis using an example VTMB problem and identifies key inadequacies in existing approaches for analysis problem formulation. Based on the gap analysis and technical background, we present five main requirements relating to (a) key drivers for efficiently creating analysis models; (b) abstracting and formalizing analysis knowledge for composing analysis models; and (c) automatically creating, reconfiguring and verifying analysis models.

High-Fidelity Models and Multiobjective Global Optimization Algorithms in Simulation-Based Design

2005 ◽  
Vol 49 (03) ◽  
pp. 159-175
Author(s):  
Daniele Peri ◽  
Emilio F. Campana
Keyword(s):  
Global Optimization ◽  
Optimization Technique ◽  
Surrogate Models ◽  
Optimization Process ◽  
High Fidelity ◽  
Objective Functions ◽  
Analytical Approximations ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Variable Fidelity

This work presents a simulation-based design environment for the solution of optimum ship design problems based on a global optimization (GO) algorithm that prevents the optimizer from being trapped into local minima. The procedure, illustrated in the framework of multiobjective optimization problems, makes use of high-fidelity, CPU-time-expensive computational models, including a free surface-capturing Reynolds-averaged Navier Stokes equation (RANSE) solver. The optimization process is composed of a global and a local phase. In the global stage of the search, a few computationally expensive simulations are needed for creating analytical approximations(i.e., surrogate models) of the objective functions. Tentative designs, created to explore the design space, are then evaluated with these inexpensive approximations. The more promising designs are then clustered and locally minimized and eventually verified with high-fidelity simulations. New exact values are used to improve the surrogate models, and repeated cycles of the algorithm are performed. A decision maker strategy is finally adopted to select the more interesting solution, and a final local refinement stage is performed by a gradient-based local optimization technique. A key point in the algorithm is the introduction of the surrogate models for the reduction of the overall time needed for the objective functions evaluation and their dynamic evolution and refinement along the optimization process. Moreover, an attractive alternative to adjoint formulations, the approximation management framework (AMF), based on a combined strategy that joins variable fidelity models and trust region techniques, is tested. Numerical examples are given demonstrating both the validity and usefulness of the proposed approach.

scholarly journals Simulation-based design of patient-specific femoral locking plate using topology optimization

2017 ◽  
Author(s):  
◽  
Parag Gholawade
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Topology Optimization ◽  
Orthopedic Implants ◽  
Patient Specific ◽  
Element Analysis ◽  
Simulation Based Design ◽  
Expected Performance ◽  
Simulation Based ◽  
Traditional Approaches

Femoral locking plates are orthopedic implants used in closed reduction of the fractured femur. These orthopedic implants designed using conventional methods apply finite element analysis to evaluate their performance. These traditional approaches result in failure of implants and need for revision surgery. Designing a patient-specific or a customised implant can make a substantial difference to the expected performance response and reduce the failure or breakage of implant. Therefore, a simulation-based design approach is employed which encompasses medical imaging segmentation, finite element analysis, Taguchi design methodology and topology optimization. The intent is to provide a methodology that will help surgeons to make informed decisions backed by engineering analysis.

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