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Designs
Special Issues
Design Sensitivity Analysis and Engineering Optimization
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Design Sensitivity Analysis and Engineering Optimization

A special issue of Designs (ISSN 2411-9660). This special issue belongs to the section "Mechanical Engineering Design".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 13620

Special Issue Editors

Prof. Dr. Duc Thai Nguyen

E-Mail Website
Guest Editor
Department of Civil & Environmental Engineering, Old Dominion University, Norfolk, VA, USA
Interests: computational mechanics; finite element analysis (FEA); structural dynamics; engineering design sensitivity analysis & optimization; parallel computing for FEA; efficient sparse/dense linear solvers; non-linear solvers; eigen-solvers; branch & bound mixed real-integer linear programming problems; etc.
Prof. Dr. Gene Hou

E-Mail Website
Guest Editor
Department of Mechanical & Aerospace Engineering, Old Dominion University, Norfolk, VA, USA
Interests: computational mechanics; multibody dynamics and design under uncertainty; emphasizing on multidisciplinary applications

Special Issue Information

Dear Colleagues,

The Special Issue "Design Sensitivity Analysis and Engineering Optimization" is a peer-reviewed journal issue covering different aspects related to simulation and multi-disciplinary design optimization. It is devoted to publishing original work related to advanced design methodologies, theoretical/heuristic approaches, high-performance computers, and their applications in different engineering and science fields such as engineering software/hardware developments, aerospace/automobile/mechanical/chemical/structural engineering, manufacturing processes, advanced optimization algorithms, and the industrial applications of optimization methods. The journal publishes original research papers, critical reviews, and short communications. The scope of this Special Issue includes, but is not limited to original research contributions on the following topics:

  • Optimization algorithms/methodologies (optimization methods that involve heuristic or mathematical/rigorous algorithms, stochastic programming, multi-objective optimization, discrete and dynamic programming, response surface methods, or operational research).
  • Design sensitivity analysis and gradient-based optimization, such as efficient methods for gradient (derivative) computation, efficient linear/nonlinear constraint optimization algorithms, serial and/or parallel sub-structuring (or domain partitioning) algorithms for finite element-based analysis and optimization, size/shape/topology optimization, and the application of MATLAB/FMINCON built-in function for optimization.
  • Non-gradient-based optimization algorithms (such as genetic algorithm, etc.).
  • Applications in dynamics, vibration, fluid-structure interaction, and other modeling and simulation.
  • Industrial applications.

Prof. Dr. Duc Thai Nguyen
Prof. Dr. Gene Hou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Designs is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • optimization algorithms/methodologies
  • design sensitivity analysis and gradient-based optimization
  • optimization, application of MATLAB/FMINCON built-in function for optimization
  • non-gradient-based optimization algorithms
  • applications in dynamics, vibration, fluid-structure interaction, and other modeling and simulation
  • industrial applications

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Published Papers (7 papers)

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Research

18 pages, 8045 KiB  
Article
Designs of Optomechanical Acceleration Sensors with the Natural Frequency from 5 Hz to 50 kHz
by Marina Rezinkina and Claus Braxmaier
Designs 2024, 8(2), 33; https://doi.org/10.3390/designs8020033 - 7 Apr 2024
Cited by 1 | Viewed by 1534
Abstract
In many applications, such as space navigation, metrology, testing, and geodesy, it is necessary to measure accelerations with frequencies ranging from fractions of a hertz to several kilohertz. For this purpose, optomechanical sensors are used. The natural frequency of such sensors should be [...] Read more.
In many applications, such as space navigation, metrology, testing, and geodesy, it is necessary to measure accelerations with frequencies ranging from fractions of a hertz to several kilohertz. For this purpose, optomechanical sensors are used. The natural frequency of such sensors should be approximately ten times greater than the frequency of the measured acceleration. In the case of triaxial acceleration measurements, a planar design with two sensors that measure accelerations in two perpendicular in-plane directions and a third sensor that measures out-of-plane acceleration is effective. The mechanical characteristics of the existing designs of both in-plane and out-of-plane types of sensors were analyzed, and the improved designs were elaborated. Using numerical simulation, the dependencies of the natural frequency level in the range from several hertz to tens of kilohertz on the designs and geometric parameters of opto-mechanical accelerometers were modeled. This allows one to select the accelerometer design and its parameters to measure the acceleration at the assigned frequency. It is shown that the opto-mechanical accelerometers of the proposed designs have reduced dissipation losses and crosstalk. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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24 pages, 6792 KiB  
Article
Investigating the Combined Impact of Water–Diesel Emulsion and Al2O3 Nanoparticles on the Performance and the Emissions from a Diesel Engine via the Design of Experiment
by A. Mostafa, M. Mourad, Ahmad Mustafa and I. Youssef
Designs 2024, 8(1), 3; https://doi.org/10.3390/designs8010003 - 22 Dec 2023
Cited by 2 | Viewed by 1935
Abstract
This study aims to assess the impact of the water ratio and nanoparticle concentration of neat diesel fuel on the performance characteristics of and exhaust gas emissions from diesel engines. The experimental tests were conducted in two stages. In the first stage, the [...] Read more.
This study aims to assess the impact of the water ratio and nanoparticle concentration of neat diesel fuel on the performance characteristics of and exhaust gas emissions from diesel engines. The experimental tests were conducted in two stages. In the first stage, the effects of adding water to neat diesel fuel in ratios of 2.5% and 5% on engine performance and emissions characteristics were examined and compared to those of neat diesel at a constant engine speed of 3000 rpm under three different engine loads. A response surface methodology (RSM) based on a central composite design (CCD) was utilized to simulate the design of the experiment. According to the test results, adding water to neat diesel fuel increased the brake-specific fuel consumption and reduced the brake thermal efficiency compared to neat diesel fuel. In the examination of exhaust emissions, hydrocarbons (HC), carbon monoxide (CO), and nitrogen oxides (NOx) in the tested fuel containing 2.5% of water were decreased in comparison to pure diesel fuel by 16.62%, 21.56%, and 60.18%, respectively, on average, through engine loading. In the second stage, due to the trade-off between emissions and performance, the emulsion fuel containing 2.5% of water is chosen as the best emulsion from the previous stage and mixed with aluminum oxide nanoparticles at two dose levels (50 and 100 ppm). With the same engine conditions, the emulsion fuel mixed with 50 ppm of aluminum oxide nanoparticles exhibited the best performance and the lowest emissions compared to the other evaluated fuels. The outcomes of the investigations showed that a low concentration of 50 ppm with a small amount of 11 nm of aluminum oxide nanoparticles combined with a water diesel emulsion is a successful method for improving diesel engine performance while lowering emissions. Additionally, it was found that the mathematical model could accurately predict engine performance parameters and pollution characteristics. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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19 pages, 33039 KiB  
Article
Comparative Analysis of Various Hyperelastic Models and Element Types for Finite Element Analysis
by Po-Sen Lin, Olivier Le Roux de Bretagne, Marzio Grasso, James Brighton, Chris StLeger-Harris and Owen Carless
Designs 2023, 7(6), 135; https://doi.org/10.3390/designs7060135 - 22 Nov 2023
Cited by 1 | Viewed by 3605
Abstract
This study aims to evaluate the precision of nine distinct hyperelastic models using experimental data sourced from the existing literature. These models rely on parameters obtained through curve-fitting functions. The complexity in finite element models of elastomers arises due to their nonlinear, incompressible [...] Read more.
This study aims to evaluate the precision of nine distinct hyperelastic models using experimental data sourced from the existing literature. These models rely on parameters obtained through curve-fitting functions. The complexity in finite element models of elastomers arises due to their nonlinear, incompressible behaviour. To achieve accurate representations, it is imperative to employ sophisticated hyperelastic models and appropriate element types and formulations. Prior published work has primarily focused on the comparison between the fitting models and the experimental data. Instead, in this study, the results obtained from finite element analysis are compared against the original data to assess the impact of element formulation, strain range, and mesh type on the ability to accurately predict the response of elastomers over a wide range of strain values. This comparison confirms that the element formulation and strain range can significantly influence result accuracy, yielding different responses in various strain ranges also because of the limitation with the curve fitting tools. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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25 pages, 2046 KiB  
Article
A Unit-Load Approach for Reliability-Based Design Optimization of Linear Structures under Random Loads and Boundary Conditions
by Robert James Haupin and Gene Jean-Win Hou
Designs 2023, 7(4), 96; https://doi.org/10.3390/designs7040096 - 2 Aug 2023
Cited by 2 | Viewed by 1466
Abstract
The low order Taylor’s series expansion was employed in this study to estimate the reliability indices of the failure criteria for reliability-based design optimization of a linear static structure subjected to random loads and boundary conditions. By taking the advantage of the linear [...] Read more.
The low order Taylor’s series expansion was employed in this study to estimate the reliability indices of the failure criteria for reliability-based design optimization of a linear static structure subjected to random loads and boundary conditions. By taking the advantage of the linear superposition principle, only a few analyses of the structure subjected to unit-loads are needed through the entire optimization process to produce acceptable results. Two structural examples are presented in this study to illustrate the effectiveness of the proposed approach for reliability-based design optimization: one deals with a truss structure subjected to random multiple point constraints, and the other conducts shape design optimization of a plane stress problem subjected to random point loads. Both examples were formulated and solved by the finite element method. The first example used the penalty method to reformulate the multiple point constraints as external loads, while the second example introduced an approach to propagate the uncertainty linearly from the nodal displacement vector to the nodal von Mises stress vector. The final designs obtained from the reliability-based design optimization were validated through Monte Carlo simulation. This validation process was completed with only four unit-load analyses for the first example and two for the second example. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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16 pages, 1753 KiB  
Article
Binary Integer Formulations for Task Allocation and Optimal Labor Cost in Small and Medium Apparel Manufacturing
by Vi Nguyen, Quyen Tran, Faisal Altarazi and Thanh Tran
Designs 2023, 7(4), 84; https://doi.org/10.3390/designs7040084 - 30 Jun 2023
Viewed by 1564
Abstract
In small apparel manufacturing, unit price determination is often based on production duration given by customers and design complexity rather than information relating to internal labor resources. However, labor expertise and skills are critical factors that outweigh the machinery and technology in small [...] Read more.
In small apparel manufacturing, unit price determination is often based on production duration given by customers and design complexity rather than information relating to internal labor resources. However, labor expertise and skills are critical factors that outweigh the machinery and technology in small and medium apparel companies. The quality of the product greatly depends on the experience and delicacy of the tailors. Using data on labor skill and wage levels in the planning process will benefit human resource utilization, increasing productivity, and profits effectively. This paper proposes a general mathematical model for task allocation and cost optimization for small and medium apparel companies. The model handles task allocation and cost minimization problems that must ensure processing time requirements and balance workloads for operators. The developed model tests two case studies in a published paper. The results prove that although the proposed model is simple, it has high applicability and efficiency in solving allocation optimization problems. The authors then integrate the formulations into a Standalone desktop app in the MATLAB “App designer” module. With a standalone desktop app, end users can enjoy the application. This app has a user-friendly design. Users unfamiliar with computers or planners with no background in programming can use the app to tackle similar optimization problems. The proposed mathematical model can further expand to include more complex issues in apparel companies and can also be a good reference for other fields. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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20 pages, 8936 KiB  
Article
Optimal Domain-Partitioning Algorithm for Real-Life Transportation Networks and Finite Element Meshes
by Jimesh Bhagatji, Sharanabasaweshwara Asundi, Eric Thompson and Duc T. Nguyen
Designs 2023, 7(4), 82; https://doi.org/10.3390/designs7040082 - 27 Jun 2023
Viewed by 1403
Abstract
For large-scale engineering problems, it has been generally accepted that domain-partitioning algorithms are highly desirable for general-purpose finite element analysis (FEA). This paper presents a heuristic numerical algorithm that can efficiently partition any transportation network (or any finite element mesh) into a specified [...] Read more.
For large-scale engineering problems, it has been generally accepted that domain-partitioning algorithms are highly desirable for general-purpose finite element analysis (FEA). This paper presents a heuristic numerical algorithm that can efficiently partition any transportation network (or any finite element mesh) into a specified number of subdomains (usually depending on the number of parallel processors available on a computer), which will result in “minimising the total number of system BOUNDARY nodes” (as a primary criterion) and achieve “balancing work loads” amongst the subdomains (as a secondary criterion). The proposed seven-step heuristic algorithm (with enhancement features) is based on engineering common sense and observation. This current work has the following novelty features: (i) complicated graph theories that are NOT needed and (ii) unified treatments of transportation networks (using line elements) and finite element (FE) meshes (using triangular, tetrahedral, and brick elements) that can be performed through transforming the original network (or FE mesh) into a pseudo-transportation network which only uses line elements. Several examples, including real-life transportation networks and finite element meshes (using triangular/brick/tetrahedral elements) are used (under MATLAB computer environments) to explain, validate and compare the proposed algorithm’s performance with the popular METIS software. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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19 pages, 742 KiB  
Article
Gradient-Based Trade-Off Design for Engineering Applications
by Lena A. Royster and Gene Hou
Designs 2023, 7(4), 81; https://doi.org/10.3390/designs7040081 - 24 Jun 2023
Cited by 1 | Viewed by 1207
Abstract
The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Quadratic Programming. The method is [...] Read more.
The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Quadratic Programming. The method is computationally efficient as it is gradient-based, which, however, requires the performance functions to be differentiable. A new equation to calculate the scale factor to control the size of the design variables is introduced in this study, which can ensure the new design achieves the targeted performance objective. Three formal approaches are developed in this study for trade-off design to handle various design scenarios, which include one that can handle cases with linearly dependent constraints and with more constraints than the number of design variables. Three engineering design problems are presented as examples to validate and demonstrate the use of these trade-off approaches to find the best way to adjust the design variables to meet the revised performance requirements. Full article
(This article belongs to the Special Issue Design Sensitivity Analysis and Engineering Optimization)
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