Multi-Objective Design Exploration of a Canine Ventriculoperitoneal Shunt for Hydrocephalus

2020 ◽  
Author(s):  
Ryan Yingling ◽  
Anand Balu Nellippallil ◽  
Matthew Register ◽  
Travis Hannan ◽  
Jack Simmons ◽  
...  
Keyword(s):  
Ventriculoperitoneal Shunt ◽  
Medical Procedure ◽  
Design Exploration ◽  
Multi Objective ◽  
Design Variables ◽  
Inner Diameter ◽  
Decision Based Design ◽  
Associated Design ◽  
The Brain ◽  
Systematic Framework

Abstract Hydrocephalus is a condition that affects humans and animals in which excess cerebrospinal fluid (CSF) builds up within the ventricles of the brain, causing an increase in intracranial pressure. The CSF can be released using a ventriculoperitoneal shunt, which effectively removes the fluid from the ventricles of the brain to the peritoneal cavity. In canines, hydrocephalus is sometimes a fatal condition complicated by shunt failure due to obstructions. The medical procedure is also expensive and has a high failure rate over the long term. In this paper, we present a systematic framework to carry out the multi-objective design exploration of canine shunts for managing hydrocephalus. We demonstrate the efficacy of the framework by designing a shunt prototype to meet specific goals of meeting the CSF flow rate target, minimizing shear stress on the shunt, and minimizing shunt weight. The shunt design variables considered for the problem include the inner diameter, inlet hole diameter, and the distance from the inlet holes to the outlet. A multi-objective design problem is formulated using the systematic framework to explore the combination of shunt design variables that best satisfy the conflicting goals defined. The framework and associated design constructs are generic and support the formulation and decision-based design of similar biomedical devices for different health conditions.

Multi-Objective Design Exploration of a Canine Ventriculoperitoneal Shunt for Hydrocephalus

2021 ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Ryan Yingling ◽  
Matthew Register ◽  
Travis Hannan ◽  
Jack Simmons ◽  
...  
Keyword(s):  
Ventriculoperitoneal Shunt ◽  
Design Exploration ◽  
Multi Objective

Multi-Objective Robust Design Exploration of a Canine Ventricular Shunt for Managing Hydrocephalus

2021 ◽  
Author(s):  
Gehendra Sharma ◽  
Anand Balu Nellippallil ◽  
Ryan Yingling ◽  
Na Yeon Lee ◽  
Andy Shores ◽  
...  
Keyword(s):  
Robust Design ◽  
Pressure Difference ◽  
Biomedical Devices ◽  
Csf Flow ◽  
Robust Performance ◽  
Design Exploration ◽  
Multi Objective ◽  
Abnormal Accumulation ◽  
Design Solutions ◽  
The Brain

Abstract Hydrocephalus is characterized by the abnormal accumulation of cerebrospinal fluid (CSF) within the ventricles of the brain, resulting in an increase of intracranial pressure (ICP). Ventriculoperitoneal shunts (VPS) are designed to prevent buildup of pressure in the brain by allowing excess CSF flow from the intracranial ventricles to the peritoneal cavity through a shunting mechanism. The shunt design presented in this paper is an inexpensive alternative to VPS, that is, a non-valve ventricular shunt design that directly routes CSF into the subarachnoid space. We recognize that consideration of multiple design criteria and uncertainty management are critical for designing biomedical devices to ensure robust performance. Hence, our objective in this paper is to present a multi-objective robust design exploration of canine shunts for managing hydrocephalus. Our approach in robust design focuses on managing uncertainties to deliver design solutions that are relatively insensitive to uncertainties. Hence, a multi-objective robust design problem is formulated using the compromise Decision Support Problem (cDSP) construct to explore shunt designs that best satisfy the conflicting goals dealing with the pressure difference and the stress, and a robust design goal dealing with the variations in pressure difference. We compare the results against optimal solutions to build confidence in the proposed method to identify design solutions that are relatively insensitive to uncertainties. The method presented is generic and can be applied to the multi-objective robust design of similar biomedical devices.

Multi-Objective Design Problem of Tire Wear and Visualization of Its Pareto Solutions2

2006 ◽  
Vol 34 (3) ◽  
pp. 170-194 ◽  
Author(s):  
M. Koishi ◽  
Z. Shida
Keyword(s):  
Inverse Problems ◽  
Conceptual Design ◽  
Dimensional Space ◽  
Design Stage ◽  
Objective Functions ◽  
Pareto Solutions ◽  
Design Problems ◽  
Multi Objective ◽  
Design Engineers ◽  
Design Variables

Abstract Since tires carry out many functions and many of them have tradeoffs, it is important to find the combination of design variables that satisfy well-balanced performance in conceptual design stage. To find a good design of tires is to solve the multi-objective design problems, i.e., inverse problems. However, due to the lack of suitable solution techniques, such problems are converted into a single-objective optimization problem before being solved. Therefore, it is difficult to find the Pareto solutions of multi-objective design problems of tires. Recently, multi-objective evolutionary algorithms have become popular in many fields to find the Pareto solutions. In this paper, we propose a design procedure to solve multi-objective design problems as the comprehensive solver of inverse problems. At first, a multi-objective genetic algorithm (MOGA) is employed to find the Pareto solutions of tire performance, which are in multi-dimensional space of objective functions. Response surface method is also used to evaluate objective functions in the optimization process and can reduce CPU time dramatically. In addition, a self-organizing map (SOM) proposed by Kohonen is used to map Pareto solutions from high-dimensional objective space onto two-dimensional space. Using SOM, design engineers see easily the Pareto solutions of tire performance and can find suitable design plans. The SOM can be considered as an inverse function that defines the relation between Pareto solutions and design variables. To demonstrate the procedure, tire tread design is conducted. The objective of design is to improve uneven wear and wear life for both the front tire and the rear tire of a passenger car. Wear performance is evaluated by finite element analysis (FEA). Response surface is obtained by the design of experiments and FEA. Using both MOGA and SOM, we obtain a map of Pareto solutions. We can find suitable design plans that satisfy well-balanced performance on the map called “multi-performance map.” It helps tire design engineers to make their decision in conceptual design stage.

scholarly journals Multi-Objective Design Exploration and Its Application to Regional-Jet Wing Design

2007 ◽  
Vol 50 (167) ◽  
pp. 1-8 ◽  
Author(s):  
Shigeru OBAYASHI ◽  
Shinkyu JEONG ◽  
Kazuhisa CHIBA ◽  
Hiroyuki MORINO
Keyword(s):  
Wing Design ◽  
Design Exploration ◽  
Multi Objective

The Finite Element Analysis and the Multi-Objective Optimization Design of Spindle Systems of CNC Gantry Machine Tools

2016 ◽  
Vol 693 ◽  
pp. 243-250
Author(s):  
Zhi Zhong Guo ◽  
Yun Shun Zhang ◽  
Shi Hao Liu
Keyword(s):  
Machine Tools ◽  
Optimization Design ◽  
Multi Objective Optimization ◽  
Element Analysis ◽  
Multi Objective ◽  
Vibration Resistance ◽  
Design Variables ◽  
Force Coupling ◽  
The Finite Element Analysis ◽  
Spindle Structure

It is discovered that the vibration resistance of spindle systems needs to be improved based on the statics analysis, modal analysis and heating-force coupling analysis of spindle systems of CNC gantry machine tools. The design variables of optimization are set according to sensitivity analysis, multi-objective and dynamic optimization design is realized and its designing scheme is gained for spindle structure. The research results show that vibration resistance can be improved without change of the quality and static property of spindle systems of CNC gantry machine tools.

A Goal-Oriented, Inverse Decision-Based Design Method to Achieve the Vertical and Horizontal Integration of Models in a Hot Rod Rolling Process Chain

2017 ◽  
Author(s):  
Anand Balu Nellippallil ◽  
Vignesh Rangaraj ◽  
B. P. Gautham ◽  
Amarendra Kumar Singh ◽  
Janet K. Allen ◽  
...  
Keyword(s):  
Manufacturing Process ◽  
Design Method ◽  
Manufacturing Processes ◽  
Process Chain ◽  
Structure Property ◽  
Horizontal Integration ◽  
Design Exploration ◽  
Unit Operations ◽  
Manufacturing Process Chain ◽  
Decision Based Design

Reducing the manufacturing and marketing time of products by means of integrated simulation-based design and development of the material, product, and the associated manufacturing processes is the need of the hour for industry. This requires the design of materials to targeted performance goals through bottom-up and top-down modeling and simulation practices that enables handshakes between modelers and designers along the entire product realization process. Manufacturing a product involves a host of unit operations and the final properties of the manufactured product depends on the processing steps carried out at each of these unit operations. In order to effectively couple the material processing-structure-property-performance spaces, there needs to be an interplay of the systems-based design of materials with enhancement of models of various unit operations through multiscale modeling methodologies and integration of these models at different length scales (vertical integration). This ensures the flow of information from one unit operation to another thereby establishing the integration of manufacturing processes (horizontal integration). Together these types of integration will support the decision-based design of the manufacturing process chain so as to realize the end product. In this paper, we present a goal-oriented, inverse decision-based design method to achieve the vertical and horizontal integration of models for the hot rolling and cooling stages of the steel manufacturing process chain for the production of a rod with defined properties. The primary mathematical construct used for the method presented is the compromise Decision Support Problem (cDSP) supported by the proposed Concept Exploration Framework (CEF) to generate satisficing solutions under uncertainty. The efficacy of the method is illustrated by exploring the design space for the microstructure after cooling that satisfies the requirements identified by the end mechanical properties of the product. The design decisions made are then communicated in an inverse manner to carry out the design exploration of the cooling stage to identify the design set points for cooling that satisfies the new target microstructure requirements identified. Specific requirements such as managing the banded microstructure to minimize distortion in forged gear blanks are considered in the problem. The proposed method is generic and we plan to extend the work by carrying out the integrated decision-based design exploration of rolling and reheating stages that precede to realize the end product.

Design of a Damper for a Suspension System via Evolutive Optimization

2013 ◽  
Author(s):  
Carlos A. Duchanoy ◽  
Marco A. Moreno-Armendáriz ◽  
Carlos A. Cruz-Villar
Keyword(s):  
Dynamic Optimization ◽  
Optimization Algorithm ◽  
Physical Characteristics ◽  
Suspension System ◽  
Dynamic Interactions ◽  
Multi Objective ◽  
Damping Coefficients ◽  
Design Variables ◽  
Parameterized Model ◽  
Stiffness And Damping

In this paper a dynamic optimization methodology for designing a passive automotive damper is proposed. The methodology proposes to state the design problem as a dynamic optimization one by considering the nonlinear dynamic interactions between the damper and the other elements of the suspension system, emphasizing geometry, dimensional and movement constraints. In order to obtain realistic simulations of the suspension, a link between a Computer-Aided Engineering Model (CAEM) and a multi-objective dynamic optimization algorithm is developed. As design objectives we consider the vehicle safety and the passenger comfort which are represented by the contact area of the tire and the vibrations of the cockpit respectively. The damper is optimized by stating a set of physical variables that determine the stiffness and damping coefficients as independent variables for the dynamic optimization problem, they include the spring helix diameter, the spring wire diameter, the oil physical characteristics and the bleed orifice diameters among others. The optimization algorithm that we use to solve the problem at hand is a multi-objective evolutive optimization algorithm. For this purpose we developed a parameterized model of the damper which is used to link the CAE tools and the optimization software, thus enabling fitness evaluations during the dynamic optimization process. By selecting the physical characteristics of the damper as design variables instead of the typical stiffness and damping coefficients, it is possible to consider important design constrains as the damper size, movement limitations and anchor points. As result of the proposed methodology a set of blueprints of non dominated Pareto configurations of the damper are provided to the decision maker.

Multi Objective Design Optimization of Two Bar Truss Using NSGA II and TOPSIS

2014 ◽  
Vol 984-985 ◽  
pp. 419-424
Author(s):  
P. Sabarinath ◽  
M.R. Thansekhar ◽  
R. Saravanan
Keyword(s):  
Design Optimization ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Optimal Solutions ◽  
Objective Functions ◽  
Nsga Ii ◽  
Multi Objective ◽  
Total Displacement ◽  
Design Variables ◽  
Conflicting Objectives

Arriving optimal solutions is one of the important tasks in engineering design. Many real-world design optimization problems involve multiple conflicting objectives. The design variables are of continuous or discrete in nature. In general, for solving Multi Objective Optimization methods weight method is preferred. In this method, all the objective functions are converted into a single objective function by assigning suitable weights to each objective functions. The main drawback lies in the selection of proper weights. Recently, evolutionary algorithms are used to find the nondominated optimal solutions called as Pareto optimal front in a single run. In recent years, Non-dominated Sorting Genetic Algorithm II (NSGA-II) finds increasing applications in solving multi objective problems comprising of conflicting objectives because of low computational requirements, elitism and parameter-less sharing approach. In this work, we propose a methodology which integrates NSGA-II and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for solving a two bar truss problem. NSGA-II searches for the Pareto set where two bar truss is evaluated in terms of minimizing the weight of the truss and minimizing the total displacement of the joint under the given load. Subsequently, TOPSIS selects the best compromise solution.

Multi-Objective Design Optimization of a Mixed-Flow Pump

2009 ◽  
Author(s):  
Yumiko Takayama ◽  
Hiroyoshi Watanabe
Keyword(s):  
Performance Characteristic ◽  
Performance Characteristics ◽  
Inverse Design ◽  
Surface Model ◽  
Objective Functions ◽  
Mixed Flow ◽  
Multi Objective ◽  
Design Variables ◽  
Flow Head ◽  
Flow Pump

In most cases of high specific speed mixed-flow pump applications, it is necessary to satisfy more than one performance characteristic such as deign point efficiency, shut-off power/head and non-stall characteristic (no positive slope in flow-head curve). However, it is known that these performance characteristics are in relation of trade-offs. As a result, it is difficult to optimize these performance characteristics by conventional way such as trial and error approach by modifying geometrical parameters. This paper presents the results of the multi-objective optimization strategy of mixed-flow pump design by means of three dimensional inverse design approach, Computational Fluid Dynamics (CFD), Design of Experiments (DoE), response surface model (RSM) and Multi Objective Genetic Algorism (MOGA). The parameters to control blade loading distributions and meridional geometries for impeller and diffuser blades in inverse design were chosen as design variables of the optimization process. Pump efficiency, maximum slope in flow-head curve and shut-off power/head were selected as objective functions. Objective functions of pumps, designed by design variables specified in DoE, were evaluated by using CFD. Then, trade-off relations between objective functions were analyzed by using Pareto fronts obtained by MOGA. Some pumps which have specific performance characteristic (non-stall, low shut-off power, high efficiency etc.) designed along the Pareto front were numerically evaluated.

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