scholarly journals Development of a Derivative Design Process Considering Uncertainties from Low Fidelity Analysis Tools

2011 ◽  
Author(s):  
Hyeong-Uk Park ◽  
Kamran Behdinan ◽  
Jae-Woo Lee ◽  
Joon Chung
Keyword(s):  
Design Optimization ◽  
Design Process ◽  
Design Parameters ◽  
Engineering Product ◽  
Reliability Based Design ◽  
Analysis Tools ◽  
Design Variables ◽  
Business Jet ◽  
Design Requirements ◽  
Important Design

A sensitivity analysis and an expert system have been applied to find the important design parameters for designing derivative aircraft subject to new design requirements. Additionally, the Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods are used to consider uncertainties on low fidelity analysis tools. This design process can used to reduce the time and cost for derivative design of engineering product by reducing the number of design variables. In this study, the process is applied to a conceptual design of light business jet aircraft.

scholarly journals Integrated uncertainty techniques in aircraft derivative design optimization.

2021 ◽  
Author(s):  
Hyeong-Uk Park
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Design Process ◽  
Aircraft Design ◽  
Collaborative Optimization ◽  
Aircraft Manufacturing ◽  
Analysis Tools ◽  
Design Variables ◽  
The Cost ◽  
Aircraft Conceptual Design

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet the new market demands while keeping the development time and the cost to a minimum. Many researchers have studied the derivative design process, but these research considered the baseline and the derivatives together, while using the whole set of design variables. Therefore, an efficient process that can reduce the cost and the time for the aircraft derivative design is needed. In this dissertation, Aircraft Derivative Design Optimization process (ADDOPT) was developed which obtains the global changes from the local changes in the aircraft design to develop the aircraft derivatives efficiently. The sensitivity analysis was implemented to ignore design variables that have low impact on the objective function. This avoids wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, the classification of uncertainty from its characteristics and sources of uncertainty involved in the aircraft design process were suggested to consider with design optimization. Uncertainty from the fidelity of analysis tools was applied in design optimization to increase the probability of optimization results. To handle uncertainty in low fidelity analysis tools on aircraft conceptual design optimization, Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were performed. In this research, Extended Fourier Amplitude Sensitivity Test (eFAST) method was implemented in ADDOPT for Global Sensitivity Analysis (GSA) method and Collaborative Optimization (CO) based framework with RBDO and PBDO were also used. These methods were evaluated using numerical examples. ADDOPT was carried through on the civil jet aircraft derivative design. The objective of the optimization problem was to increase cruise range while satisfying the requirement such as the number of passengers. The proposed process reduced computation effort by reducing the number of design variables and achieved the target probability of failure when considering uncertainty from low fidelity analysis tools.

scholarly journals Integrated uncertainty techniques in aircraft derivative design optimization.

2021 ◽  
Author(s):  
Hyeong-Uk Park
Keyword(s):  
Sensitivity Analysis ◽  
Design Optimization ◽  
Design Process ◽  
Aircraft Design ◽  
Collaborative Optimization ◽  
Aircraft Manufacturing ◽  
Analysis Tools ◽  
Design Variables ◽  
The Cost ◽  
Aircraft Conceptual Design

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet the new market demands while keeping the development time and the cost to a minimum. Many researchers have studied the derivative design process, but these research considered the baseline and the derivatives together, while using the whole set of design variables. Therefore, an efficient process that can reduce the cost and the time for the aircraft derivative design is needed. In this dissertation, Aircraft Derivative Design Optimization process (ADDOPT) was developed which obtains the global changes from the local changes in the aircraft design to develop the aircraft derivatives efficiently. The sensitivity analysis was implemented to ignore design variables that have low impact on the objective function. This avoids wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, the classification of uncertainty from its characteristics and sources of uncertainty involved in the aircraft design process were suggested to consider with design optimization. Uncertainty from the fidelity of analysis tools was applied in design optimization to increase the probability of optimization results. To handle uncertainty in low fidelity analysis tools on aircraft conceptual design optimization, Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were performed. In this research, Extended Fourier Amplitude Sensitivity Test (eFAST) method was implemented in ADDOPT for Global Sensitivity Analysis (GSA) method and Collaborative Optimization (CO) based framework with RBDO and PBDO were also used. These methods were evaluated using numerical examples. ADDOPT was carried through on the civil jet aircraft derivative design. The objective of the optimization problem was to increase cruise range while satisfying the requirement such as the number of passengers. The proposed process reduced computation effort by reducing the number of design variables and achieved the target probability of failure when considering uncertainty from low fidelity analysis tools.

scholarly journals Enhance Derivative Design Considering Global Sensitivity of Design Parameters

2013 ◽  
Author(s):  
Hyeong-UK Park ◽  
Kamran Behdinan ◽  
Joon Chung ◽  
Jae-Woo Lee
Keyword(s):  
Sensitivity Analysis ◽  
Design Process ◽  
Life Cycle Cost ◽  
Global Sensitivity Analysis ◽  
Collaborative Optimization ◽  
Design Parameters ◽  
Fast Method ◽  
Engineering Product ◽  
Global Sensitivity ◽  
Design Variables

An engineering product design considers derivatives to reduce the life cycle cost and to increase the efficiency on operation when it has new demands. The proposed design process in this study obtains derivative designs based on sensitivity of design variable. The efficiency and accuracy of the derivative design process can be enhanced by implementing global sensitivity analysis. Sensitivity analysis sensors the design variables accordingly and variables with low sensitivity for objective function can be neglected, since computational effort and time is not necessary for a design with less priority. In this research, e-FAST method code for global sensitivity analysis module was developed and implemented on Multidisciplinary Design Optimization (MDO) problem. The wing design was considered for MDO problem that used aerodynamics and structural disciplines. The global sensitivity analysis method was applied to reduce the number of design variables and Collaborative Optimization (CO) was used as MDO method. This research shows the efficiency of reduction of dimensionality of complex MDO problem by using global sensitivity analysis. In addition, this result shows important design variables for design requirement to student when they solving design problem.

Barrier Function Method in Reliability Based Design Optimization

2005 ◽  
Vol 297-300 ◽  
pp. 1882-1887
Author(s):  
Tae Hee Lee ◽  
Jung Hun Yoo
Keyword(s):  
Design Optimization ◽  
Barrier Function ◽  
Reliability Index ◽  
Feasible Solution ◽  
Reliability Based Design Optimization ◽  
User Requirement ◽  
Mean Values ◽  
Reliability Based Design ◽  
Design Variables ◽  
Reliability Method

In practical design applications, most design variables such as thickness, diameter and material properties are not deterministic but stochastic numbers that can be represented by their mean values with variances because of various uncertainties. When the uncertainties related with design variables and manufacturing process are considered in engineering design, the specified reliability of the design can be achieved by using the so-called reliability based design optimization. Reliability based design optimization takes into account the uncertainties in the design in order to meet the user requirement of the specified reliability while seeking optimal solution. Reliability based design optimization of a real system becomes now an emerging technique to achieve reliability, robustness and safety of the design. It is, however, well known that reliability based design optimization can often have so multiple local optima that it cannot converge into the specified reliability. To overcome this difficulty, barrier function approach in reliability based design optimization is proposed in this research and feasible solution with specified reliability index is always provided if a feasible solution is available. To illustrate the proposed formulation, reliability based design optimization of a bracket design is performed. Advanced mean value method and first order reliability method are employed for reliability analysis and their optimization results are compared with reliability index approach based on the accuracy and efficiency.

Reliability-based design optimization of electromagnetic shielding structure using neural networks and real-coded genetic algorithm

2014 ◽  
Vol 228 (18) ◽  
pp. 3471-3481 ◽  
Author(s):  
Heeralal Gargama ◽  
Sanjay K Chaturvedi ◽  
Awalendra K Thakur
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Design Optimization ◽  
Electromagnetic Shielding ◽  
Optimization Approach ◽  
Reliability Based Design Optimization ◽  
Reliability Based Design ◽  
Design Variables ◽  
Real Coded Genetic Algorithm

The conventional approaches for electromagnetic shielding structures’ design, lack the incorporation of uncertainty in the design variables/parameters. In this paper, a reliability-based design optimization approach for designing electromagnetic shielding structure is proposed. The uncertainties/variability in the design variables/parameters are dealt with using the probabilistic sufficiency factor, which is a factor of safety relative to a target probability of failure. Estimation of probabilistic sufficiency factor requires performance function evaluation at every design point, which is extremely computationally intensive. The computational burden is reduced greatly by evaluating design responses only at the selected design points from the whole design space and employing artificial neural networks to approximate probabilistic sufficiency factor as a function of design variables. Subsequently, the trained artificial neural networks are used for the probabilistic sufficiency factor evaluation in the reliability-based design optimization, where optimization part is processed with the real-coded genetic algorithm. The proposed reliability-based design optimization approach is applied to design a three-layered shielding structure for a shielding effectiveness requirement of ∼40 dB, used in many industrial/commercial applications, and for ∼80 dB used in the military applications.

Design-airworthiness integration method for general aviation aircraft during early development stage

2019 ◽  
Vol 91 (7) ◽  
pp. 1067-1076
Author(s):  
Maxim Tyan ◽  
Jungwon Yoon ◽  
Nhu Van Nguyen ◽  
Jae-Woo Lee ◽  
Sangho Kim
Keyword(s):  
Design Optimization ◽  
Design Stage ◽  
Design Parameters ◽  
Design Framework ◽  
Efficient Design ◽  
Content Type ◽  
Early Design ◽  
Early Design Stage ◽  
Optimization Framework ◽  
Design Requirements

Purpose Major changes of an aircraft configuration are conducted during the early design stage. It is important to include the airworthiness regulations at this stage while there is extensive freedom for designing. The purpose of this paper is to introduce an efficient design framework that integrates airworthiness guidelines and documentation at the early design stage. Design/methodology/approach A new design and optimization process is proposed that logically includes the airworthiness regulations as design parameters and constraints by constructing a certification database. The design framework comprises requirements analysis, preliminary sizing, conceptual design synthesis and loads analysis. A design certification relation table (DCRT) describes the legal regulations in terms of parameters and values suitable for use in design optimization. Findings The developed framework has been validated and demonstrated for the design of a Federal Aviation Regulations (FAR) 23 four-seater small aircraft. The validation results show an acceptable level of accuracy to be applied during the early design stage. The total mass minimization problem has been successfully solved while satisfying all the design requirements and certification constraints specified in the DCRT. Moreover, successful compliance with FAR 23 subpart C is demonstrated. The proposed method is a useful tool for design optimization and compliance verifications during the early stages of aircraft development. Practical implications The new certification database proposed in this research makes it simpler for engineers to access a large amount of legal documentation related to airworthiness regulations and provides a link between the regulation text and actual design parameters and their bounds. Originality/value The proposed design optimization framework integrates the certification database that is built of several types of legal documents such as regulations, advisory circulars and standards. The Engineering Requirements and Guide summarizes all the documents and design requirements into a single document. The DCRT is created as a summary table that indicates the design parameters affected by a given regulation(s), the design stage at which the parameter can be evaluated and its value bounds. The introduction of the certification database into the design optimization framework significantly reduces the engineer’s load related for airworthiness regulations.

Design Optimization of Folding Solar Powered Autonomous Underwater Vehicles Using Origami Architecture

2017 ◽  
Author(s):  
Doe Young Hur ◽  
Edwin Peraza Hernandez ◽  
Edgar Galvan ◽  
Darren Hartl ◽  
Richard Malak
Keyword(s):  
Design Optimization ◽  
Design Process ◽  
Autonomous Underwater Vehicles ◽  
Electrical Power ◽  
Active Material ◽  
Pareto Frontier ◽  
Underwater Vehicles ◽  
Hydrodynamic Performance ◽  
Design Parameters ◽  
Solar Panels

Recently, the importance of design process with unknown parameter increased. On the other hand, the design of Autonomous Underwater Vehicles (AUVs) is a difficult challenge since it requires the consideration of various aspects such as mission range, controllability, energy source, and carrying capacity. A design process for novel type of AUV constructed using an origami-based structure that includes active material actuators and solar panels is proposed in this paper. To increase the efficiency in the three-dimensional shape modeling of the AUV, the shape of the outer surface is parameterized by a finite set of variables using shape functions. Here, the AUV should operate underwater via electrical power with the batteries being charged periodically using solar panels. The ability of the AUV to transport cargo such as instrumentation is also addressed. The design parameters include the total height and width of the AUV. As these dimensions of the AUV might vary in a non-preferential manner based on particular mission goals, these dimensions are considered as design parameters in a multi-objective optimization setting. The Predictive Parameterized Pareto Genetic Algorithm (P3GA) is selected as the optimization method to determine a Pareto frontier of design options with desired characteristics for a variety of missions for the AUV. The evaluation of each AUV design entails quantitative assessment of the origami fold pattern determined using a method developed by the authors and Computational Fluid Dynamics (CFD) analysis. The development of a design process that addresses the design optimization of the AUV considering its hydrodynamic performance and origami aspects is the main topic of this paper.

A Modified Reliability Index Approach for Reliability-Based Design Optimization

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Po Ting Lin ◽  
Hae Chang Gea ◽  
Yogesh Jaluria
Keyword(s):  
Design Optimization ◽  
Reliability Index ◽  
Reliability Based Design Optimization ◽  
Second Moment ◽  
Reliability Indices ◽  
Reliability Based Design ◽  
Design Variables ◽  
Index Approach ◽  
Definition Of ◽  
Code Format

Reliability-based design optimization (RBDO) problems have been intensively studied for many decades. Since Hasofer and Lind [1974, “Exact and Invariant Second-Moment Code Format,” J. Engrg. Mech. Div., 100(EM1), pp. 111–121] defined a measure of the second-moment reliability index, many RBDO methods utilizing the concept of reliability index have been introduced as the reliability index approach (RIA). In the RIA, reliability analysis problems are formulated to find the reliability indices for each performance constraint and the solutions are used to evaluate the failure probability. However, the traditional RIA suffers from inefficiency and convergence problems. In this paper, we revisited the definition of the reliability index and revealed the convergence problem in the traditional RIA. Furthermore, a new definition of the reliability index is proposed to correct this problem and a modified reliability index approach is developed based on this definition. The strategies to solve RBDO problems with non-normally distributed design variables by the modified RIA are also investigated. Numerical examples using both the traditional and modified RIAs are compared and discussed.

The Response Surface Single Loop Reliability-Based Design Optimization Method With Reliability Requirement on System Failure

2016 ◽  
Author(s):  
Rami Mansour ◽  
Mårten Olsson
Keyword(s):  
Design Optimization ◽  
Response Surface ◽  
Optimization Problem ◽  
Optimization Method ◽  
Reliability Based Design Optimization ◽  
Single Loop ◽  
Reliability Based Design ◽  
Design Variables ◽  
Reliability Method ◽  
Deterministic Solution

In reliability-based design optimization (RBDO), an optimal design which minimizes an objective function while satisfying a number of probabilistic constraints is found. As opposed to deterministic optimization, statistical uncertainties in design variables and design parameters have to be taken into account in the design process in order to achieve a reliable design. In the most widely used RBDO approaches, the First-Order Reliability Method (FORM) is used in the probability assessment. This involves locating the Most Probable Point (MPP) of failure, or the inverse MPP, either exactly or approximately. If exact methods are used, an optimization problem has to be solved, typically resulting in computationally expensive double loop or decoupled loop RBDO methods. On the other hand, locating the MPP approximately typically results in highly efficient single loop RBDO methods since the optimization problem is not necessary in the probability assessment. However, since all these methods are based on FORM, which in turn is based on a linearization of the deterministic constraints at the MPP, they may suffer inaccuracies associated with neglecting the nonlinearity of deterministic constraints. In a previous paper presented by the authors, the Response Surface Single Loop (RSSL) Reliability-based design optimization method was proposed. The RSSL-method takes into account the non-linearity of the deterministic constraints in the computation of the probability of failure and was therefore shown to have higher accuracy than existing RBDO methods. The RSSL-method was also shown to have high efficiency since it bypasses the concept of an MPP. In RSSL, the deterministic solution is first found by neglecting uncertainties in design variables and parameters. Thereafter quadratic response surface models are fitted to the deterministic constraints around the deterministic solution using a single set of design of experiments. The RBDO problem is thereafter solved in a single loop using a closed-form second order reliability method (SORM) which takes into account all elements of the Hessian of the quadratic constraints. In this paper, the RSSL method is used to solve the more challenging system RBDO problems where all constraints are replaced by one constraint on the system probability of failure. The probabilities of failure for the constraints are assumed independent of each other. In general, system reliability problems may be more challenging to solve since replacing all constraints by one constraint may strongly increase the non-linearity in the optimization problem. The extensively studied reliability-based design for vehicle crash-worthiness, where the provided deterministic constraints are general quadratic models describing the system in the whole region of interest, is used to demonstrate the capabilities of the RSSL method for problems with system reliability constraints.

Reliability-Based Design Optimization of a Cemented Prosthesis in a Femur Undergoing Bone Remodeling

2019 ◽  
Vol 142 (4) ◽  
Author(s):  
Leandro Luis Corso ◽  
Herbert Martins Gomes ◽  
Leandro de Freitas Spinelli ◽  
Crisley Dossin Zanrosso ◽  
Rogério José Marczak ◽  
...  
Keyword(s):  
Design Optimization ◽  
Bone Remodeling ◽  
Three Dimensional ◽  
Young Modulus ◽  
Fe Model ◽  
Reliability Based Design Optimization ◽  
Bone Mass Loss ◽  
Reliability Based Design ◽  
Design Variables ◽  
Three Dimensional Finite Element

Abstract This study proposes a numerical methodology to minimize the bone mass loss in a femur with a total hip arthroplasty procedure, considering uncertainties in the material parameters and using a reliability-based design optimization (RBDO) procedure. A genetic algorithm (GA) is applied for optimization, and a three-dimensional finite element (FE) model associated with the bone remodeling procedure is proposed and described to account for the internal and external femoral bone behavior. An example of a femoral prosthesis design is presented as a basis for discussion of the proposed methodologies, and the corresponding reliability level is evaluated. Constraints on the strength of all materials and target reliability levels are inputs to the optimization model. The main prosthesis dimensions and Young modulus are the design variables. The proposed methodology is compared with a well-known deterministic optimization (DO) procedure and the results show that it is important to consider the uncertainties in this kind of problem since in this case, the a posteriori reliability may be low.

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