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Article
Publication date: 7 November 2023

Matheus Francisco, João Pereira, Lucas Oliveira, Sebastião Simões Cunha and G.F. Gomes

The present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how…

26

Abstract

Purpose

The present paper aims at the multi-objective optimization of a reentrant hexagonal cell auxetic structure. In addition, a parametric analysis will be carried out to verify how each of the design factors impact each of the responses.

Design/methodology/approach

The multi-objective optimization of five different responses of an auxetic model was considered: mass, critical buckling load under compression effort, natural frequency, Poisson's ratio and failure load. The response surface methodology was applied, and a new meta-heuristic of optimization called the multi-objective Lichtenberg algorithm was applied to find the optimized configuration of the model. It was possible to increase the failure load by 26.75% in compression performance optimization. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively. This paper addresses something new in the scientific world to date when evaluating in a multi-objective optimization problem, the compression and modal performance of an auxetic reentrant model.

Findings

It was possible to find multi-objective optimized structures. It was possible to increase the critical buckling load by 42.82%, and the failure load in compression performance by 26.75%. Furthermore, in the optimization of modal performance, it was possible to increase the natural frequency by 37.43%, and decrease the mass by 15.97%. Finally, all 5 responses analyzed simultaneously were optimized. In this case, it was possible to increase the critical buckling load by 42.55%, increase the failure load by 28.70% and reduce the mass and Poisson's ratio by 15.97 and 11%, respectively.

Originality/value

There is no work in the literature to date that performed the optimization of 5 responses simultaneously of a reentrant hexagonal cell auxetic structure. This paper also presents an unprecedented statistical analysis in the literature that verifies how the design factors impact each of the responses.

Details

Engineering Computations, vol. 40 no. 9/10
Type: Research Article
ISSN: 0264-4401

Keywords

Open Access
Article
Publication date: 28 July 2020

Julián Monsalve-Pulido, Jose Aguilar, Edwin Montoya and Camilo Salazar

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently…

1792

Abstract

This article proposes an architecture of an intelligent and autonomous recommendation system to be applied to any virtual learning environment, with the objective of efficiently recommending digital resources. The paper presents the architectural details of the intelligent and autonomous dimensions of the recommendation system. The paper describes a hybrid recommendation model that orchestrates and manages the available information and the specific recommendation needs, in order to determine the recommendation algorithms to be used. The hybrid model allows the integration of the approaches based on collaborative filter, content or knowledge. In the architecture, information is extracted from four sources: the context, the students, the course and the digital resources, identifying variables, such as individual learning styles, socioeconomic information, connection characteristics, location, etc. Tests were carried out for the creation of an academic course, in order to analyse the intelligent and autonomous capabilities of the architecture.

Details

Applied Computing and Informatics, vol. 20 no. 1/2
Type: Research Article
ISSN: 2634-1964

Keywords

Article
Publication date: 28 August 2023

Anett Kenderes, Szabolcs Gyimóthy and Péter Tamás Benkő

Global sensitivity analysis (SA) by means of Sobol’ indices enhanced with different surrogate modeling techniques is performed in this work. The purpose is to investigate the…

Abstract

Purpose

Global sensitivity analysis (SA) by means of Sobol’ indices enhanced with different surrogate modeling techniques is performed in this work. The purpose is to investigate the influence of measurement uncertainties and the environment characteristics themselves on the desired field uniformity in reverberation chambers (RCs). This yields an efficient apparatus for the stirring and chamber design process.

Design/methodology/approach

The technique of Sobol’ indices, as a candidate of global SA methods, is suitable for high fluctuations due to its robustness, which can be addressed to the stochastic nature of the RC environment. The aim of using surrogate modeling techniques is to compute the indices efficiently with a moderate number of required simulations. The powerfulness of this approach is introduced in a simple numerical example in which the physical phenomena can be identified more straightforwardly.

Findings

This method can provide useful knowledge in the lower frequency range, where the ideal properties of the electromagnetic field in RCs cannot be established, and the importance of the setup parameters can vary from configuration to configuration. In addition, it can serve as a basis for setup adaptation during parallelized electromagnetic compatibility tests, which would result in a more time- and cost-saving option in industrial applications in the future.

Originality/value

Despite the previous attempts, a profound investigation of multiple setup parameters is still a hot topic. The main contribution of this work is the extension of the application area of the method of Sobol’ indices to RCs, which has not been done so far.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 42 no. 5
Type: Research Article
ISSN: 0332-1649

Keywords

Article
Publication date: 1 August 2022

Rustanto Nanang, Connie Susilawati and Martin Skitmore

Governments in developing countries manage their considerable state assets for public service delivery directly. In Indonesia, the Directorate of State Asset Management…

Abstract

Purpose

Governments in developing countries manage their considerable state assets for public service delivery directly. In Indonesia, the Directorate of State Asset Management responsible for developing the national strategy for state asset optimization requires the determination of key elements and prioritization tools. The purpose of this paper is to show that a simple calculation using the combination of the balanced scorecard (BCS) and analytical hierarchy process (AHP) will help in the prioritization of strategy development.

Design/methodology/approach

A questionnaire survey of 131 multistakeholder respondents to identify the most important key elements and the best alternative for asset optimization was done in this study.

Findings

The respondents agree on the most important key elements, and that the best alternative for asset optimization is the efficient maintenance of assets. Competitive human resources comprise the recommended second key element, and that improvements in asset performance and value will improve public service as the second-highest alternative. This study also shows the importance of the integration of asset optimization in existing government strategic instruments supported by a comprehensive data set related to public assets and their performance.

Originality/value

This paper provides a new contribution to integrating asset optimization strategies as the core of the organization’s performance and prioritization strategies. Additional BSC perspectives are suggested, with the inclusion of AHP for prioritization. In addition, this study includes the opinions of all the stakeholders, from external users to the central management. The flexibility of the tools to adapt to the existing strategic framework will allow their application by different agencies and in different countries.

Details

Construction Innovation , vol. 23 no. 5
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 2 August 2023

Shaoyi Liu, Song Xue, Peiyuan Lian, Jianlun Huang, Zhihai Wang, Lihao Ping and Congsi Wang

The conventional design method relies on a priori knowledge, which limits the rapid and efficient development of electronic packaging structures. The purpose of this study is to…

Abstract

Purpose

The conventional design method relies on a priori knowledge, which limits the rapid and efficient development of electronic packaging structures. The purpose of this study is to propose a hybrid method of data-driven inverse design, which couples adaptive surrogate model technology with optimization algorithm to to enable an efficient and accurate inverse design of electronic packaging structures.

Design/methodology/approach

The multisurrogate accumulative local error-based ensemble forward prediction model is proposed to predict the performance properties of the packaging structure. As the forward prediction model is adaptive, it can identify respond to sensitive regions of design space and sample more design points in those regions, getting the trade-off between accuracy and computation resources. In addition, the forward prediction model uses the average ensemble method to mitigate the accuracy degradation caused by poor individual surrogate performance. The Particle Swarm Optimization algorithm is then coupled with the forward prediction model for the inverse design of the electronic packaging structure.

Findings

Benchmark testing demonstrated the superior approximate performance of the proposed ensemble model. Two engineering cases have shown that using the proposed method for inverse design has significant computational savings while ensuring design accuracy. In addition, the proposed method is capable of outputting multiple structure parameters according to the expected performance and can design the packaging structure based on its extreme performance.

Originality/value

Because of its data-driven nature, the inverse design method proposed also has potential applications in other scientific fields related to optimization and inverse design.

Details

Soldering & Surface Mount Technology, vol. 35 no. 5
Type: Research Article
ISSN: 0954-0911

Keywords

Article
Publication date: 30 October 2023

Qiangqiang Zhai, Zhao Liu, Zhouzhou Song and Ping Zhu

Kriging surrogate model has demonstrated a powerful ability to be applied to a variety of engineering challenges by emulating time-consuming simulations. However, when it comes to…

Abstract

Purpose

Kriging surrogate model has demonstrated a powerful ability to be applied to a variety of engineering challenges by emulating time-consuming simulations. However, when it comes to problems with high-dimensional input variables, it may be difficult to obtain a model with high accuracy and efficiency due to the curse of dimensionality. To meet this challenge, an improved high-dimensional Kriging modeling method based on maximal information coefficient (MIC) is developed in this work.

Design/methodology/approach

The hyperparameter domain is first derived and the dataset of hyperparameter and likelihood function is collected by Latin Hypercube Sampling. MIC values are innovatively calculated from the dataset and used as prior knowledge for optimizing hyperparameters. Then, an auxiliary parameter is introduced to establish the relationship between MIC values and hyperparameters. Next, the hyperparameters are obtained by transforming the optimized auxiliary parameter. Finally, to further improve the modeling accuracy, a novel local optimization step is performed to discover more suitable hyperparameters.

Findings

The proposed method is then applied to five representative mathematical functions with dimensions ranging from 20 to 100 and an engineering case with 30 design variables.

Originality/value

The results show that the proposed high-dimensional Kriging modeling method can obtain more accurate results than the other three methods, and it has an acceptable modeling efficiency. Moreover, the proposed method is also suitable for high-dimensional problems with limited sample points.

Details

Engineering Computations, vol. 40 no. 9/10
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 20 October 2023

Duo Zhang, Yonghua Li, Gaping Wang, Qing Xia and Hang Zhang

This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of…

Abstract

Purpose

This study aims to propose a more precise method for robust design optimization of mechanical structures with black-box problems, while also considering the efficiency of uncertainty analysis.

Design/methodology/approach

The method first introduces a dual adaptive chaotic flower pollination algorithm (DACFPA) to overcome the shortcomings of the original flower pollination algorithm (FPA), such as its susceptibility to poor accuracy and convergence efficiency when dealing with complex optimization problems. Furthermore, a DACFPA-Kriging model is developed by optimizing the relevant parameter of Kriging model via DACFPA. Finally, the dual Kriging model is constructed to improve the efficiency of uncertainty analysis, and a robust design optimization method based on DACFPA-Dual-Kriging is proposed.

Findings

The DACFPA outperforms the FPA, particle swarm optimization and gray wolf optimization algorithms in terms of solution accuracy, convergence speed and capacity to avoid local optimal solutions. Additionally, the DACFPA-Kriging model exhibits superior prediction accuracy and robustness contrasted with the original Kriging and FPA-Kriging. The proposed method for robust design optimization based on DACFPA-Dual-Kriging is applied to the motor hanger of the electric multiple units as an engineering case study, and the results confirm a significant reduction in the fluctuation of the maximum equivalent stress.

Originality/value

This study represents the initial attempt to enhance the prediction accuracy of the Kriging model using the improved FPA and to combine the dual Kriging model for uncertainty analysis, providing an idea for the robust optimization design of mechanical structure with black-box problem.

Details

Multidiscipline Modeling in Materials and Structures, vol. 19 no. 6
Type: Research Article
ISSN: 1573-6105

Keywords

Article
Publication date: 20 March 2024

Ziming Zhou, Fengnian Zhao and David Hung

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine…

Abstract

Purpose

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

Design/methodology/approach

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

Findings

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

Originality/value

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 15 December 2022

Xuesong Wang, Jinju Sun, Ernesto Benini, Peng Song and Youwei He

This study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an…

Abstract

Purpose

This study aims to use computational fluid dynamics (CFD) to understand and quantify the overall blockage within a transonic axial flow compressor (AFC), and to develop an efficient collaborative design optimization method for compressor aerodynamic performance and stability in conjunction with a surrogate-assisted optimization technique.

Design/methodology/approach

A quantification method for the overall blockage is developed to integrate the effect of regional blockages on compressor aerodynamic stability and performance. A well-defined overall blockage factor combined with efficiency drives the optimizer to seek the optimum blade designs with both high efficiency and wide-range stability. An adaptive Kriging-based optimization technique is adopted to efficiently search for Pareto front solutions. Steady and unsteady numerical simulations are used for the performance and flow field analysis of the datum and optimum designs.

Findings

The proposed method not only remarkably improves the compressor efficiency but also significantly enhances the compressor operating stability with fewer CFD calls. These achievements are mainly attributed to the improvement of specific flow behaviors oriented by the objectives, including the attenuation of the shock and weakening of the tip leakage flow/shock interaction intensity.

Originality/value

CFD-based design optimization of AFC is inherently time-consuming, which becomes even trickier when optimizing aerodynamic stability since the stall margin relies on a complete simulation of the performance curve. The proposed method could be a good solution to the collaborative design optimization of aerodynamic performance and stability for transonic AFC.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 33 no. 5
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 19 October 2023

Steffen Schrock, Stefan Junk and Albert Albers

This study aims to investigate a systematic approach to the production and use of additively manufactured injection mould inserts in product development (PD) processes. For this…

Abstract

Purpose

This study aims to investigate a systematic approach to the production and use of additively manufactured injection mould inserts in product development (PD) processes. For this purpose, an evaluation of the additive tooling design method (ATDM) is performed.

Design/methodology/approach

The evaluation of the ATDM is conducted within student workshops, where students develop products and validate them using AT-prototypes. The evaluation process includes the analysis of work results as well as the use of questionnaires and participant observation.

Findings

This study shows that the ATDM can be successfully used to assist in producing and using AT mould inserts to produce valid AT prototypes. As a reference for the implementation of AT in industrial PD, extracts from the work of the student project groups and suitable process parameters for prototype production are presented.

Originality/value

This paper presents the application and evaluation of a method to support AT in PD that has not yet been scientifically evaluated.

Details

Rapid Prototyping Journal, vol. 30 no. 1
Type: Research Article
ISSN: 1355-2546

Keywords

1 – 10 of 36