Design Of Industrial Applications Research Articles

Assessing the internationalization dynamics of emerging markets: a comprehensive analysis utilizing SWARA-WASPAS techniques

Purpose This paper aims to evaluate the internationalization of countries represented in the MSCI Emerging Markets Index. The evaluation considers high-technology product imports, foreign direct investments, research and development expenditures, patent and industrial design applications, exports and gross domestic product (GDP) data, representing production. Design/methodology/approach This paper uses the Step-Wise Weight Assessment Ratio Analysis (SWARA) method to assess and rank the criteria for evaluating emerging markets. Four academics who are authorities in the field of foreign trade were consulted to weigh the criteria. The Weighted Aggregated Sum Product Assessment (WASPAS) method, considered one of the most reliable and robust MCDM techniques, was then used to evaluate and rank the countries. Findings The findings obtained during the research process reveal the internationalization dynamics of these countries based on the indicators they possess. As a result, it is observed which countries achieve higher performance in the internationalization process based on relevant criteria. Originality/value This study is theoretically unique and valuable as it simultaneously offers the potential for development to macro-level international trade theories, such as the technologic deficit hypothesis, and meso-level internationalization theories, such as the Uppsala model. Additionally, integrated multiple criteria decision-making (MCDM) methods, which are not frequently used in cross-country studies, have been used, and the performance of emerging markets has been ranked. The findings obtained from this application distinguish the research from the existing literature by transforming it into a performance ranking rather than focusing on the antecedents or consequences of internationalization and their interactions.

Lightweight mask R-CNN for instance segmentation and particle physical property analysis in multiphase flow

A lightweight Mask R-CNN instance segmentation model was developed here to analyze particle size and shape accurately and quickly. Firstly, a hybrid Depthwise Dilated Convolutional Network (DDNet) is proposed, and the feature pyramid layers and the shared convolutional layers of the region proposal network are simplified, reducing the model complexity while ensuring robust feature extraction capabilities. Then, segmentation accuracy is significantly improved without sacrificing computational speed and performance by introducing the Dice loss function and clustering algorithm. Experimental results show that the model parameters are significantly reduced by 49.46%, and the segmentation speed increases from 2.15 FPS (frames per second) to 5.88 FPS. Meanwhile, the segmentation accuracy (AP50) increased from 90.56% to 91.21%. In addition, it was proven that the particle size distribution and shape could be analyzed accurately and rapidly with the proposed model, providing essential information for multiphase flow process optimization and equipment design in industrial applications.

Optimization of building thermal environment and VR industrial heritage landscape design enhanced by computer vision algorithms

With the acceleration of urbanization, the optimization of thermal environment of buildings has become an important topic to improve energy efficiency and environmental sustainability. This paper aims to enhance the optimization of building thermal environment through computer vision algorithm, and explore its application in VR industrial heritage landscape design, so as to achieve the dual goals of building energy conservation and cultural inheritance. In this study, advanced computer vision technology is used to monitor and analyze the thermal performance of buildings in real time. Through the construction of thermal environment model, combined with deep learning algorithm to extract building thermal energy data, and use VR technology for visual display, so as to provide scientific basis for design decisions. The research objects include several representative industrial heritage buildings, and analyze their thermal energy consumption characteristics and optimization potential. The results show that the application of the computer vision algorithm reduces the heat loss of the building and significantly improves the energy efficiency. At the same time, the VR visual model intuitively shows the design effect after thermal optimization, enhancing the communication and understanding between designers and stakeholders. Therefore, the combination of computer vision and VR technology can effectively improve the optimization ability of building thermal environment and promote the sustainable design and operation of traditional industrial heritage.

Application of electric field to aluminum/copper/aluminum trilayer nanocomposites and determination of mechanical properties: A molecular dynamics approach

Most studies considered metal matrix nanocomposites (NCs) because of their excellent mechanical and electrical properties. In recent years, external electric fields (EEFs) in the aforementioned NCs were identified as a crucial role in modulating mechanical behavior. The EEF may affect strength, hardness, ductility, and fracture toughness. The explanation for these changes is the interaction of EEF with the nanoparticles in the metal matrix. In the present study, the effects of various EEF values on the mechanical properties of Al/Cu/Al three-layer NCs (TLNCs) were assessed using the molecular dynamics (MD) modeling method and LAMMPS software. MD findings predicted that the EEF reduced the physical stability and mechanical strength of modeled samples. Physically, this performance resulted from a decrease in attraction force among distinct particles inside the computing box in the presence of EEF. The proposed samples' ultimate tensile strength (UTS) and Young's modulus (YM) decreased to 2.587 GPa and 20.19 GPa, respectively, when the EEF value increased to 0.05 V/Å. Finally, it was determined that EEF is a crucial parameter in the mechanical development of MMNC structures and should be used in mechanical bacterial design in industrial applications.

Integration of extended reality and CAE in the context of industry 4.0

ABSTRACT Simulation plays a major role in the development of new products and is considered one of the nine technological pillars of Industry 4.0. By encapsulating a plethora of digital tools, simulation has transitioned towards what is known as Computer Aided Engineering (CAE), which further enables engineers to validate the design and ensure product performance. The development of cutting-edge digital technologies, such as Extended Reality (XR), has also gained attention aiming at the facilitation of human-machine interface (HMI) and the creation of communication channels for improved remote collaboration. The contribution of this study lies in the design and development of a cloud-based framework for the integration of CAE tools with Mixed Reality (MR), specifically, Computational Fluid Dynamics (CFD), focusing on industrial refrigeration systems design and editing applications. Furthermore, the developed solution provides augmented 3D visualizations overlaid on the existing installations. The proposed framework supports the virtual co-existence of engineers during the design phase, thus enabling collaboration and mentoring between experienced and young engineers. Additionally, it can be realized as a Cloud platform, which supports the distribution of several services such as storage of CAD files, simulation results, and the XR application for the setup and visualization of simulation results.

Historical evolution of structural optimization techniques for steel skeletal structures including industrial design applications

This study covers the review of algorithms developed for the optimum design of steel skeletal structures from the first article published in 1960 until to date. The paper initially describes the mathematical formulation of a simple truss structural design problem. The early optimum design algorithms that were based on mathematical programming techniques where the design variables are assumed to be continuous are reviewed. The optimum design of steel framed structures necessitates the selection of steel profiles from the standard list of discrete steel sections and requires the satisfaction of design code provisions. Both mathematical programming and optimality criteria techniques need more capability to produce solution to this type of optimum design problems. Soft computing techniques emerged recently provide solution directly without needing any approximation. These techniques are classified and reviewed and their use in obtaining the optimum solution of actual industrial steel design applications is given.

Natural deep eutectic solvents as green and homogeneous catalysts for the glycerolysis of stearic acid: Catalytic activity and kinetic studies

Emulsifier as the mixture of monoglycerides (MG) and diglycerides (DG) is widely used in the food industry such as bakery products, margarines, dairy products, and confectionary. This emulsifier can be produced by glycerolysis of fatty acids using acid catalyst. In this work, natural deep eutectic solvent (NADES) was chosen as a catalyst in the glycerolysis of stearic acid due to greener and sustainable catalyst with advantages such as low vapor pressure, non-toxic, biodegradable, and easy to reuse. The catalytic activity of the NADES, kinetic constants and activation energies for the reaction were investigated. The reaction was carried out at agitation speed (300 rpm), catalyst concentration (5 wt%), reaction temperatures (120 °C, 150 °C and 180 °C) and reactant mole ratios (1:2, 1:4 and 1:6). Choline chloride-sorbitol NADES has highest catalytic activity on the glycerolysis of stearic acid. The kinetic calculation results using choline chloride-sorbitol NADES as a catalyst validated that the reaction was pseudo second order with an activation energy of 64.04 kJ∙mol−1, and a collision factor of 196,696 L∙mol−1∙min−1. This kinetics data will be useful for reactor design in industrial applications.

Projection-based reduced order modeling of multi-species mixing and combustion

High-fidelity simulations of mixing and combustion processes are computationally demanding and time-consuming, hindering their wide application in industrial design and optimization. This study proposes projection-based reduced order models (ROMs) to predict spatial distributions of physical fields for multi-species mixing and combustion problems in a fast and accurate manner. The developed ROMs explore the suitability of various regression methods, including kriging, multivariate polynomial regression (MPR), k-nearest neighbors (KNN), deep neural network (DNN), and support vector regression (SVR), for the functional mapping between input parameters and reduced model coefficients of mixing and combustion problems. The ROMs are systematically examined using two distinct configurations: steam-diluted hydrogen-enriched oxy-combustion from a triple-coaxial nozzle and fuel-flexible combustion in a practical gas-turbine combustor. The projected low-dimensional manifolds are capable of capturing important combustion physics, and the response surfaces of reduced model coefficients present pronounced nonlinear characteristics of the flowfields with varying input parameters. The ROMs with kriging present a superior performance of establishing the input–output mapping to predict almost all physical fields, such as temperature, velocity magnitude, and combustion products for both test problems. The accuracy of DNN is less encouraging owing to the stringent requirement on the size of training database. KNN performs well in the region near the design points but its effectiveness diminishes when the test points are distant from the sampling points, whereas SVR and MPR exhibit large prediction errors. For the spatial prediction at unseen design points, the ROMs achieve a prediction time of up to eight orders of magnitude faster than conventional numerical simulations, rendering an efficient tool for the fast prediction of mixing and combustion fields and potentially an alternative of a full-order numerical solver.

Improved marine predators algorithm for engineering design optimization problems

The Marine Predator Algorithm (MPA) has unique advantages as an important branch of population-based algorithms. However, it emerges more disadvantages gradually, such as traps to local optima, insufficient diversity, and premature convergence, when dealing with complex problems in practical industrial engineering design applications. In response to these limitations, this paper proposes a novel Improved Marine Predator Algorithm (IMPA). By introducing an adaptive weight adjustment strategy and a dynamic social learning mechanism, this study significantly improves the encounter frequency and efficiency between predators and preys in marine ecosystems. The performance of the IMPA was evaluated through benchmark functions, CEC2021 suite problems, and engineering design problems, including welded beam design, tension/compression spring design, pressure vessel design, and three-bar design. The results indicate that the IMPA has achieved significant success in the optimization process over other methods, exhibiting excellent performance in both solving optimal parameter solutions and optimizing objective function values. The IMPA performs well in terms of accuracy and robustness, which also proves its efficiency in successfully solving complex industrial engineering design problems.

Regeneration of industrial heritage: a study on the feasibility of expanding into campus space

With the rapid pace of urbanization, campuses are confronted with the challenge of increasingly limited land resources. Traditional campus planning has proven inadequate in meeting the growing educational demands. In this context, exploring the feasibility of repurposing industrial heritage sites for campus space has emerged as a crucial research topic, offering valuable opportunities to expand campus facilities. This paper takes the regeneration design of industrial heritage along the Jiangsu Canal as an illustrative example and analyzes its potential value, modes of reuse, and design strategies. It further investigates how these sites can be transformed into educational spaces within a campus setting. Through practical applications in industrial heritage regeneration design, this paper explores three dimensions: adaptive integration with external spatial environments, functional replacement within internal structures, adaptive reconstruction of space layouts, and renewal of architectural forms. Ultimately, feasible strategies for regenerating and expanding industrial heritage into campus spaces are summarized herein, providing novel ideas and methodologies for future campus expansion endeavors. Concurrently, we hope to raise awareness among all sectors of society regarding the protection and reuse of industrial heritage while collectively promoting sustainable development in this field.

The Influence of Intellectual Property Rights (IPR) on Asean+5’s International Trade (IT)

In accordance with the ASEAN IPR Action Plan 2016-2025, this study explores the connections and causality of Intellectual Property Rights (IPR) on international trade (IT) of ASEAN+5 countries represented by Malaysia, Thailand, the Philippines, Singapore, and Indonesia. According to this, international trade is measured in terms of trade (as a percentage of GDP). IPR is measured by patent applications filed by residents, patent applications filed by non-residents, industrial design applications filed by residents, and industrial design applications filed by non-residents. Along with IPR, the effect of government effectiveness (GE) on IT is also investigated. Foreign direct investment (FDI) and inflation are also utilized as control variables. This study adopts new growth theory as to further explain the variables involved. All ASEAN+5 data for the individual variables were derived from the World Bank Development database, and the panel dataset was investigated using the PFGLS estimator and Dumitrescu-Hurlin test for over 21-years period (2000-2020). The findings of this study revealed a strong effect between IPR and IT as well as a unidirectional relationship between IPR (except industrial design application, filed by residents) and IT for the ASEAN+5 region. The limitation of this study is that it only focused on five ASEAN countries, and the selection of IPR indicators was limited. Nevertheless, this study provides some important insights for policymakers and local merchants to focus and invest more on IPR in order to promote ASEAN's international trade in accordance with global norms.

Utilization of 3D printing technology in hepatopancreatobiliary surgery.

The technology of three-dimensional (3D) printing emerged in the late 1970s and has since undergone considerable development to find numerous applications in mechanical engineering, industrial design, and biomedicine. In biomedical science, several studies have initially found that 3D printing technology can play an important role in the treatment of diseases in hepatopancreatobiliary surgery. For example, 3D printing technology has been applied to create detailed anatomical models of disease organs for preoperative personalized surgical strategies, surgical simulation, intraoperative navigation, medical training, and patient education. Moreover, cancer models have been created using 3D printing technology for the research and selection of chemotherapy drugs. With the aim to clarify the development and application of 3D printing technology in hepatopancreatobiliary surgery, we introduce seven common types of 3D printing technology and review the status of research and application of 3D printing technology in the field of hepatopancreatobiliary surgery.

Do intellectual property rights promote foreign direct investment inflows and technological exports in developing and developed countries?

PurposeThis study aims to analyse the intellectual property rights (INPR), foreign direct investment (FDI) inflows and technological exports of 32 developing and developed countries for the period of 2006–2020.Design/methodology/approachDiagnostic tests were used to confirm the panel least squares, fixed effect, random effect, feasible general least squares, dynamic ordinary least squares and fully modified ordinary least squares estimator results as well as to increase the robustness.FindingsAccording to the findings for the developing countries, trademark, patent and industrial design applications, each had a significant positive long-run effect on FDI inflows. In addition, there was a significant positive long-run relationship between patent applications and medium- and high-technology exports. Meanwhile, trademark and industrial design applications had a significant negative long-term effect on medium- and high-technology exports. In developed countries, patent and industrial design applications each have a significant negative long-term on medium- and high-technology exports. Furthermore, patent and trademark applications each had a significant negative long-run effect on FDI inflows.Originality/valueThis study contributes significantly to the focus that host countries evaluate the technology gaps between domestic and foreign investors at different industry levels to select the best INPR rules and innovation process by increasing international cooperation. Furthermore, the host countries should follow the structure–conduct–performance paradigm based on analysis of the market structure, strategic firms and industrial dynamics systems.

Hydrodynamics and particle array optical characterizations of a high-performance Langmuir–Blodgett process

This paper describes the scientific features of an innovative technique to mass-produce monolayers of hexagonal close-packed structures (HCP) of particles (280–1100 nm). Our technique differs from a continuous roll-to-roll Langmuir–Blodgett (LB) process. It consists of a thin liquid film flowing down an inclined plane channel, the ramp, and entraining deposited particles floating on its surface to form a compact monolayer. Vertical sidewalls limit the entire flow. The main benefits of this technique in comparison with a standard LB process are a gentler push on the floating particles during the assembly and the prospect of better flexibility and scalability in the design of industrial applications. Our disruptive approach presents new control parameters and surprising but challenging hydraulic phenomena due to the flowing liquid. This paper investigates the hydrodynamics of this new LB-type design theoretically and experimentally. We propose an original theoretical prediction of the thickness of the liquid film flowing down the ramp without or with particles on its surface, including within the hydraulic jump region separating the liquid film whose surface is free of particles and the liquid film whose surface is particle-loaded. The experimental determinations of the film thickness obtained by a confocal chromatic technique and moiré topography agree well with our model. In addition, Bragg diffraction topography and false colour topography allow the HCP structure of the compact monolayer of particles to be quantified.

An Investigation on Utilizing Large Language Model for Industrial Computer-Aided Design Automation

Text-to-image or 3D content generation has attracted attention in academia and industry because of its impressive performance in high-fidelity content generation with natural language commands. However, its widespread application in industrial computation-aided design (CAD) is not yet found. The main issue lies in the end-to-end generation through implicit probabilistic learning from datasets. This presents difficulties in precise, controllable, and transparent creations. Also, it is time-consuming and labor-intensive for designers to verify and customize the generated result to fit their demands. Furthermore, popular generative models offer limited support for early-stage engineering computations, leaving tedious and massive calculations to human engineers. To overcome these challenges, this paper proposes a method to apply large language model (LLM) to assist standard CAD design workflow on both engineering computation and precise 3D geometry generation. During the designing process, LLM can support the computation process with human guidance and generate accurate 3D shapes with the capability of sequential code representation and transformation. To verify the feasibility of the proposed method, a use case for a one-stage reduction gear system consisting of two gears will be given as a proof-of-concept demonstration. The result shows that the LLM can carry out the computation and get the result as expected with only a few lines of human guidance and feedback. Then, it can create CAD models with accurate parameters aligned to the computational results. It can cope with various requirements given by users and allow users to further modify the generation using the same CAD environment without much effort. Authors believe that this piece of work can shed light on utilizing the capability of LLMs for a certain part of task automation based on human beings’ intentions. With the rise of LLMs and relevant technologies, conventional CAD may shift to a more user-friendly AI-aided design (AIAD) diagram.

Facial Analysis of the Igbo Ethnic Group of Nigeria for the Evaluation of Sexual Dimorphism

Background: Facial analysis defines the measurement of soft tissue in the face used in forensics, anthropology, artistic design, and facial reconstruction. The study aims to evaluate the sexual differences in facial parameters among the Igbo ethnic group of Nigeria.
 Methods: 400 (200 males and 200 females) subjects of Igbo origin volunteered for the study. Each subject's frontal view photographs were taken in the Natural Head Position (NHP) and analyzed using Pro-Image Facial Software Version 2 to evaluate the nasal width, nasal height, mouth width, facial width, facial height, inner canthal distance, and outer canthal distance. Data obtained were analyzed with IBM SPSS (version 23) and independent T-test as an inferential statistic.
 Results: The result showed that NW was (M=5.16±0.65, F=5.34±0.53, t=-2.91, p=0.00), NH was (M=5.61±0.62, F=5.26±0.57, t=5.92, p=0.00), MW was (M=6.64±0.7, F=6.54±0.71, t=1.46, p=0.14), FW was (M=16.17±1.31, F=15.07±2.04, t=6.39, p=0.00), FH was (M=16.63±1.11, F=16.08±1.31, t=4.36, p=0.00), En was (M=4.62±0.46, F=4.31±0.47, t=6.75, p=0.00) and Ex was (M=12.23±0.86, F=12.16±1.01, t=0.82, p=0.41).
 Conclusion: The nasal width and Height, facial width and height, and inner canthal distance show gender differences among the Igbo ethnic group of Nigeria. This study will have a practical application in Forensics, Anthropology, Artistic and Industrial design, and to medical professionals involved in facial reconstruction.

Underwater electrical explosion of metallic wire and tube: A comparison study

With an initial energy storage of approximately 53.5 kJ, experiments on underwater electrical explosions of metallic wire and thin-wall tube were conducted. Two sets of controlled experiments were designed, and the wire and tube for each set were of the same length, cross-sectional area, and material. Load voltage, circuit current, and shock wave pressure were measured and analyzed, and electric power, energy deposition, and energy deposition rate were also calculated and investigated. Experimental results indicated that the underwater electrical tube explosion (UETE) always has higher and earlier local resistance peak, voltage peak, and electric power peak, as well as faster phase transition and ionization process than the underwater electrical wire explosion (UEWE). In addition, the energy deposition rate from the beginning of discharge or the decrease in current to the voltage peak is significantly increased when replacing a wire with a tube. For the shock-wave characteristics, the peak pressure, energy density, and impulse of the shock wave generated by UETE are greater than that generated by UEWE. The peak pressure at ∼33 cm increased from 21.1 to 24.5 MPa in the first set and from 18.1 to 21.7 MPa in the second when a tube was used instead of a wire. These experimental results help us understand the physical process of UETE and provide an alternative methodology for load design in industrial applications.

The Role of Nanocrystallization for the Enhancement of Structural, Electrical, and Transport Properties of BaTiO3-V2O5-PbO Glasses

Glass-ceramic nanocrystals (GCNs) were created via annealing at crystallization temperature Tc for the parent BaTiO3-V2O5-PbO glasses prepared by the melt quenching technique. The amorphous character of the existing quenched glasses was confirmed by scanning electron microscopy. Furthermore, the general characteristics of x-ray diffraction support the amorphous nature of the glasses. In the related heat-treated samples, the typical nanostructure size is less than 60 nm. It was discovered that an increase in the density of the GCNs occurred with an increase in the BaTiO3 percentage. Also, with increasing BaTiO3 content, a slight increase was observed in the crystallization and glass transition temperature from 335°C to 365°C and 265°C to 320°C, respectively. It was revealed that suitable nanocrystallization at temperatures around the onset of Tc for 1 h was able to significantly increase the electronic conductivity of the initial glasses. The accumulation of V4+–V5+ pairs at the interlayer zones created between nanocrystallites and the glassy phase were accountable for electron hopping in the current approach, which was significantly higher than in the glass phase. The experimental findings were investigated in a model based on the “core–shell” idea. Appropriate values for the different small polaron hopping (SPH) variables were found from the best fits. Non-adiabatic hopping of small polarons was responsible for the conduction. As a result of the alteration of the nanostructure, conductivity was enhanced. Compared to the original glasses, the final materials have significantly better electrical conductivity. Such characteristics can be utilized in the design for industrial applications.

Enumeration and Identification of Unique 3D Spatial Topologies of Interconnected Engineering Systems Using Spatial Graphs

Abstract Systematic enumeration and identification of unique 3D spatial topologies (STs) of complex engineering systems (such as automotive cooling systems, electric power trains, satellites, and aero-engines) are essential to navigation of these expansive design spaces with the goal of identifying new spatial configurations that can satisfy challenging system requirements. However, efficient navigation through discrete 3D ST options is a very challenging problem due to its combinatorial nature and can quickly exceed human cognitive abilities at even moderate complexity levels. This article presents a new, efficient, and scalable design framework that leverages mathematical spatial graph theory to represent, enumerate, and identify distinctive 3D topological classes for a generic 3D engineering system, given its system architecture (SA)—its components and their interconnections. First, spatial graph diagrams (SGDs) are generated for a given SA from zero to a specified maximum number of interconnect crossings. Then, corresponding Yamada polynomials for all the planar SGDs are generated. SGDs are categorized into topological classes, each of which shares a unique Yamada polynomial. Finally, within each topological class, 3D geometric models are generated using the SGDs having different numbers of interconnect crossings. Selected case studies are presented to illustrate the different features of our proposed framework, including an industrial engineering design application: ST enumeration of a 3D automotive fuel cell cooling system (AFCS). Design guidelines are also provided for practicing engineers to aid the application of this framework to different types of real-world problems such as configuration design and spatial packaging optimization.

Research on the Application of Computer-Aided Industrial Design and 3D Printing Technology: A Comprehensive Perspective Analysis

With the continuous development and popularization of computer-aided industrial design technology and 3D printing technology, the integration of the two is also receiving more and more attention. Starting from the basic principles and development history of computer-aided industrial design technology and 3D printing technology, this paper introduces the advantages and current situation of the integration of the two, and focuses on exploring the integration of computer-aided industrial design and 3D printing technology in product design, process analysis, and manufacturing process optimization. Finally, the development trend and future prospects of integration application are summarized.