Design Parameters Research Articles

Investigating post-earthquake progressive collapse resistance of irregular steel structures

Removal of load-bearing elements such as columns, can rapidly lead to structural failures and the compromise of building stability. These failures can be initiated by minor damage but can ultimately culminate in catastrophic events. In the line of progressive collapse resistance of conventional urban buildings, extensive studies have so far been performed; though relatively little attention has been paid to the impact of earthquakes on structural resilience under such failures, this is particularly the case in irregular structures as these structures have hardly received much attention. In this research, considering the presence of setback irregularities in many structures, the impact of the column removal scenario after different earthquake intensities of low, medium, and high on over 60 steel moment frame structures with 5 and 10 stories is investigated. The structures are first categorized into four vulnerability groups, from maximum to minimum resistance against progressive collapse, based on the damage percentage. After applying 12 earthquake records at the MCE level, the cases studied are assessed under column removal scenarios at different spans and stories. The results reveal that earthquakes, elevate the risk of progressive collapse. Moreover, increasing setback irregularity up to 13.33 % improves structural performance against progressive collapse, reducing responses by 21 % on average compared to regular structures. However, at higher setback irregularity percentages, responses increase by 82 % on average, diminishing structural resistance. Setting upper limits for this type of irregularity and imposing constraints on design parameters, while modifying minimum base shear and maximum period limit, can significantly reduce progressive collapse potential.

A Review on Design and Mechanical Properties of Additively Manufactured NiTi Implants for Orthopedic Applications.

NiTi alloy has a wide range of applications as a biomaterial due to its high ductility, low corrosion rate, and favorable biocompatibility. Although Young’s modulus of NiTi is relatively low, it still needs to be reduced; one of the promising ways is by introducing porous structure. Traditional manufacturing processes, such as casting, can hardly produce complex porous structures. Additive manufacturing (AM) is one of the most advanced manufacturing technologies that can solve impurity issues, and selective laser melting (SLM) is one of the well-known methods. This paper reviews the developments of AM-NiTi with a particular focus on SLM-NiTi utilization in biomedical applications. Correspondingly, this paper aims to describe the three key factors, including powder preparation, processing parameters, and gas atmosphere during the overall process of porous NiTi. The porous structure design is of vital importance, so the unit cell and pore parameters are discussed. The mechanical properties of SLM-NiTi, such as hardness, compressive strength, tensile strength, fatigue behavior, and damping properties and their relationship with design parameters are summarized. In the end, it points out the current challenges. Considering the increasing application of NiTi implants, this review paper may open new frontiers for advanced and modern designs.

A novel microgroove-based absorber for sorption heat transformation systems: Analytical modeling and experimental investigation

This study proposes a novel sorber bed design, a stationary thin film microgroove-based absorber, that can address the low specific power and oversized sorber bed issues in existing oscillatory solid sorption heat transformation systems. An analytical heat and mass transfer model is developed for the proposed stationary thin film microgroove-based absorber. A highly-wettable microgrooved aluminum substrate is fabricated by the deposition of a hybrid Al2O3/TiO2 layer, and experimental water uptake measurements are obtained using a custom-built gravimetric large pressure jump setup to validate the analytical model. The model examines how key design parameters affect specific cooling power, cooling power density, and energy storage density. Findings indicate that cycle time and groove depth significantly impact system performance. Also, it is found that there is an optimum groove depth, or film thickness, to achieve maximum power. Trapezoidal grooves achieve higher specific cooling power and cooling power density, while rectangular grooves yield a higher maximum energy storage density. It is experimentally shown that a specific cooling power enhancement of up to 600 % can be obtained compared to the experimental data available for oscillatory sorber beds. Also, the absorption rate of the present sorber bed is up to three times higher than that of falling film absorbers.

Overall aerodynamic performance of the airfoils with different amplitudes via a fuzzy decision making based Taguchi methodology

In this study, the overall aerodynamic performance of the airfoils with variable amplitude geometric structure for lift-type vertical axis wind turbine has been analyzed and optimized using Fuzzy Analytic Hierarchy Process (AHP)-Fuzzy COmbinative Distance-based Assessment (CODAS) based on Taguchi Method. In the design of the experiment, leading edge (LE) tubercle airfoil models, Reynolds number, and angle of attack are utilized as the control factors. Drag, lift, and lift to drag ratio performances by comparing the airfoils according to the baseline model are calculated and the combination of these performances is considered as the overall aerodynamic performance response. The experiments are carried out according to the orthogonal matrix L18. Since the importance of each response is different on lift-type vertical axis wind turbines, the importance weights of these responses were obtained by Fuzzy AHP according to the evaluation of the decision maker. Multiple responses are converted into a single response (the overall aerodynamic performance) via Fuzzy CODAS which enables to model uncertainty in order to overcome the physical effects that may arise in experiments. Thereby, a multi objective Taguchi methodology was applied for the overall aerodynamic performance with a novel Fuzzy logic based multi criteria decision analysis approach. As a result, Model-4, having tubercle design parameters of amplitude of 0.025c and 0.0125c and wavelength of 0.5c and 0.125c, was found to have the best performance with the novel Taguchi approach, which saves time and cost. In addition, it has been determined that the airfoils, Reynolds number and angle of attack are significant and what level of contribution to the overall aerodynamic performance. At this point, the most important control factor has emerged as the angle of attack.

Schematic construction of carbon fiber tow microstructure models and their effect on tensile strength of carbon fiber tow/epoxy composites: Quantification of carbon fiber distribution, misalignment, and interlacing

Carbon fiber reinforced polymers (CFRPs) are increasingly being used in cutting-edge technologies, thus rendering accurate material characterization essential. However, the unexpected microstructures of carbon fiber (CF) tows, such as random fiber distribution, misalignment, and interlacing, degrade the mechanical properties of CFRPs and render them unpredictable. Hence, the microstructures of CF tows and their effect on the performance of CFRPs must be investigated.Herein, we propose a framework for quantifying the microstructural parameters of three types of T700 grade CF tows and investigate their effects on the tensile strengths of CF tows and CF tow-reinforced composites. CF cross sections are analyzed via microscopy to measure the fiber distribution and misalignment with respect to the location. A two-roll mill experiment is designed to evaluate fiber interlacing by compressing the CF tow in the thickness direction. The tensile strengths of CFs, CF tows, and CF tow-reinforced composites are measured, whereas their interfacial shear strengths are obtained via a micro-droplet test.Two CF tow microstructure models are proposed: the uniform distribution model with a low degree of fiber misalignment resulted in a higher tensile strength ratio of CF tow compared to the core-shell model, as well as a higher tensile strength of CF tow/epoxy composites. Results indicate that the microstructure of the CF tow significantly affects the properties of the composite materials. Therefore, utilizing the framework proposed herein as a tow design parameter is expected to fulfill the varying requirements of important properties in composite material design based on the application field.

Characterization of damage to steel bridge girders subjected to over-height vehicle collision

Bridge structures that span roads and highways are often at the risk of over-height vehicle collision. Such collisions can cause structural damage to bridge girders, adversely affecting the bridge's safety and functionality, while posing an immediate hazard to traveling motorists. To ensure the structural integrity of the bridge girders, it is imperative to evaluate them in response to the loading demand induced by over-height collisions. However, current specifications and codes do not have the details necessary to predict the impact forces that steel bridge girders can experience during such collisions. To address this gap, a comprehensive investigation was conducted in this study to (i) determine impact force characteristics, (ii) evaluate various impact-induced structural response measures, and (iii) identify design parameters in need of attention to minimize the extent of impact-induced damage to steel girders. For this purpose, nonlinear finite-element models were developed and validated with experimental tests and field surveys. The structural performance of the steel bridge girders was then investigated, in terms of damage patterns, girder displacements and rotations, shear forces and bending moments, and impact forces, during a range of over-height collision scenarios. Based on the obtained results, predictive equations were developed to estimate the mean impact force. This was to facilitate the impact-resistant design of steel girders commonly used in bridge structures.

Deep transfer learning for efficient and accurate prediction of composite pressure vessel behaviors

Composite pressure vessels are manufactured by winding carbon fiber-reinforced plastic, while its performance is determined by fabrication conditions. To properly design composite pressure vessels, it is essential to analyze their behavior according to the design parameters. However, analytical or numerical methods have limitations in terms of accuracy or cost-effectiveness. In this study, a method is proposed to accurately and efficiently predict the behavior of composite pressure vessels through deep transfer learning. A prediction model is built by pre-training on a sufficient amount of analytical data, and then fine-tuning on a limited amount of numerical data. The performance of the deep transfer learning-based prediction model was evaluated through various error assessments. Its computational cost was also compared with that of finite element analysis. Furthermore, the deep transfer learning-based prediction model was used to analyze the impact of design parameters on the behavior of composite pressure vessels and for design optimization.

Investigation of plastic hinge length in high-ductility reinforced concrete shear walls

In this study, the plastic hinge lengths of reinforced concrete (R/C) cantilever shear walls were analytically determined considering various design parameters. Nonlinear static (Pushover) analyses were conducted on R/C shear wall models and their nonlinear behavior was examined using ABAQUS software. In the study, 72 shear wall models with different parameters were analyzed under the influence of vertical and horizontal loads. Parameters whose effects on plastic hinge length were investigated height/length ratio (Hw/Lw), axial load ratio (N/No), and horizontal web reinforcement ratio (ρsh). The load-displacement graphs of the modelled shear walls were obtained. The plastic hinge height of shear walls was determined according to the heights of the deformations in the concrete and longitudinal steel reinforcement in the section when the shear walls lateral load decreased by 15%. The analytical plastic hinge lengths (Lpz) were determined with respect to the location of the yield occurred at the longitudinal steel reinforcement of the shear wall. The observed plastic hinge lengths (Lp) were determined based on the height of observed the crush as of the foundation top level in the concrete shear wall model. The relationship between the findings of this study and empirical formulas in the literature was determined. It was determined that there is greater closeness between the values obtained from empirical formulas in the literature and the observed plastic hinge length values. It was observed that the plastic hinge length generally increases as the shear span increases. It was observed that the change in ρsh was not a very effective parameter in plastic hinge formation. As the N/No decreases, the plastic hinge length values ​​ generally increase. The Lp/Lpz ratio varied within the range of 0.15-0.50. In addition to ductility (μ) values were determined by using the displacements determined according to both the crushing occurred in the shear wall concrete and the yield observed in the steel reinforcement. The observed that the ductility value depends more on Hw/Lw ratio as N/No ratio decreases.

Nature-inspired 3D printing-based double-graded aerospace negative Poisson’s ratio metastructure: Design, Fabrication, Investigation, optimization

The advanced metamaterials concept has been widely explored and utilized in many industries, ranging from automotive applications to medicine, and has great potential in the aerospace field. Novel nature-inspired 3D printed double-graded aluminum foam-filled negative Poisson’s ratio metamaterials (DGAT) were designed, fabricated, and investigated. Their mechanical properties were examined by the finite element method and experiments. The geometrical parameters and combination types show different effects on the mechanical properties of DGAT metastructures. Under axial compressive loading, the DGAT structure has a lower peak force and higher specific energy absorption. Then, parametric analysis shows that several design parameters (e.g. m, T, θ, tmin, tmax) have a very strong effects on the mechanical performance. Finally, multi-objective optimization is performed to maximize specific energy absorption while reducing maximum impact force. Optimization results show that the novel graded metamaterials have stronger energy absorption capacity than the ordinary counterparts. Especially, the specific energy absorption can be increased to 80% with 15% peak loading force rising. Due to their unique structural design and excellent mechanical properties, the DGAT metastructures have great potential applications in the fields of transportation protection, military protection engineering, manned spacecraft cushioning and energy-absorbing boxes.

Jet-assisted membrane filtration and design application: A model for fouling removal area estimation

Membrane fouling remains a significant challenge in desalination and other membrane-based filtration processes. This study presents a novel force-balance model to accurately estimate the de-fouling area in jet-assisted filtration for in-situ fouling control. The model includes various design parameters, such as initial jet velocity, nozzle diameter, impinging angle, membrane pore size, membrane resistance, and permeate flux. The validation showed a strong correlation between theoretical predictions and experimental observations, with an R2 value of 0.97, indicating high predictive accuracy. Additionally, an empirical formula and design automation tools were developed to facilitate the configuration of jet filtration modules, enabling practical application of the findings. As a demonstration, the arrangement of multiple jets in a hollow fiber membrane module was optimized using the model, significantly improving microalgae filtration performance. The optimized jet configuration enhanced permeate flux by 236 % and reduced the specific energy consumption by 67 % compared to conventional setups. This research offers a framework for extending the application of jet-based fouling mitigation and cleaning in various membrane filtration systems, providing substantial improvements in efficiency and operational sustainability.

Optimization design and simulation of chip-level micro-gas columnar preconcentrator structure based on ANSYS

Abstract To achieve the efficient preconcentration of measured sample gas in microfluidic chips, this paper proposes a design and simulation scheme for the chip-level micro-gas columnar pre-concentrated structure based on ANSYS software. Firstly, four kinds of chip-level micro-gas columnar preconcentrators with circular, semi-circular, triangular, and rhombic shapes were designed, and the simulation analysis of gas-phase micro-fluidic dynamics was performed on the chip-level micro-gas columnar preconcentrator by ANSYS software. The influence of different design parameters on the pre-concentrated effect of level chips micro-gas columnar preconcentrator was discussed. The simulation results show that the arrangement is a triangle arranged in reverse parallel, and the preconcentration effect of the chip-level micro gas column preconcentrator is better.

An analytical method for out-of-plane stability assessment of network arch bridges

Network arch bridges typically feature inclined cables with a net configuration to support the bridge deck, therefore, improving the bridge's stiffness and reducing bending moments along the arch elements. Given their relatively slender cross-sections and large compression stresses, properly evaluating stability safety is crucial to the integrity of network arch bridges. However, because of the unique design of cable configuration, current design specifications mostly do not provide specific methods for such stability assessments. To address this gap, the study proposes a new analytical methodology that elucidates the mechanical relationship between basic design parameters and the stability performance of network arch bridges. A numerical example is conducted using finite element analysis to validate the performance of the proposed method. In addition, the influence of several design parameters on the stability factor and buckling length factor is investigated. This research further proposes a practical expression for the buckling length factor of arch ribs with nonlinear regression analysis. The results exhibit that the proposed method can efficiently and accurately evaluate the buckling stability performance of network arch bridges, and the established practical expression can facilitate designers in easily estimating the critical buckling load during the design process.

One of the Core Leverages to Ensure the Applicability of Design Research: Design Parameters and Paths for Adjusting Design Parameters Through Research

One of the Core Leverages to Ensure the Applicability of Design Research: Design Parameters and Paths for Adjusting Design Parameters Through Research

A Prototype Design of a Vertical Axis Wind Turbine as One of the Renewable Energy Sources in Brunei

Background: According to the Asia Wind Energy Association, Brunei can harness the power of wind energy to meet its future demands for a reliable energy source that is both renewable and non-polluting. Objective: A preliminary study to design and manufacture wind turbines needs to be initiated earlier especially in the Brunei with has potential wind energy. Methods: This preliminary study compares several Vertical Axis Wind Turbine (VAWT) types and examines the optimal design in terms of mechanical parts for wind speed characteristics in Brunei. The project focuses on the engineering design stages to obtain a selected design that differs from other available designs. Results: The preliminary study successfully generated a small amount of electricity from the mechanical rotation of the VAWT. Conclusion: Although the preliminary study can generate a small amount of electricity, several design parameters need to be improved in further study. Proper manufacturing technologies are also needed to fabricate a better VAWT.

Prediction model of grinding roughness for worm with complicated space tooth surface

Optimum grinding parameters are crucial for achieving high-quality grinding of helical tooth surfaces for worm drives. The complex coupling motion relationship and formation mechanism between the worm blank and the grinding head make it difficult to predict the effect of grinding parameters on tooth surface roughness. Therefore, we developed a prediction model for the worm tooth surface roughness under conjugate grinding and applied it to the Roller Enveloping Worm Reducer (REWR). The forming process of the theoretical worm tooth surface during the grinding process was modeled by using the conjugate meshing principle. Considering the plowing and cutting effects of grinding particles on the tooth surface at different design parameters, feed speeds, and rotational speeds of the grinding head, the roughness prediction equation was established based on the theory of the maximum depth of valley bottom. Through the coupling analysis of the theoretical tooth surface model and the roughness prediction model, the prediction of the worm tooth surface roughness is realized. Based on the validated model, the influences of grinding parameters on the worm tooth surface roughness of REWR were quantitatively discussed. This study is of great significance for optimizing process parameters in the grinding of complex spatial surface transmissions.

Integrated photon pairs source in silicon carbide based on micro-ring resonators for quantum storage at telecom wavelengths

We present the design of an on-chip integrated photon pair source based on Spontaneous Four Wave Mixing (SFWM), implemented on a ring resonator in the 4H Silicon Carbide On Insulator (4H-SiCOI) platform, compatible with a solid state quantum memory in the telecommunications band. Through careful engineering of the waveguide dispersion and micro-ring resonator dimensions, we found solutions where the signal photons are emitted at 1536.48 nm with a bandwidth of ∼150\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 150$$\\end{document} MHz, enabling the interaction with the hyperfine structure of Er3+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{3+}$$\\end{document} ions. Simultaneously, the idler photons are generated at 1563.86 nm, matching the central wavelength of a specific channel in a commercial dense wavelength division multiplexing system. The proposed device fulfill all the spectral requirements in a simple ring-bus coupled waveguide configuration with design parameters within the range of reported values for similar resonators, making feasible its manufacturing with current fabrication capabilities.

Investigating on thermal insulation in concrete partition wall with insulation-material-infilled Voronoi sections: Feature impact analysis and efficient assessment approach

Reducing energy consumption in building operations, occupying 27 % of total carbon emissions, is crucial for decarbonization. Concrete partition walls with insulation-filled hollow sections, offer high thermal resistance, reducing air conditioning needs. Voronoi pattern represent a space being subdivided into polygonal regions and can be incorporated as the cavity pattern of the hollow section. However, the existing studies on Voronoi sections focus on porosity and pore quantity, with limited research on other feature metrics. This research addresses this gap by quantifying additional feature metrics of Voronoi sections using Bayesian inference, determining their collective influence on insulation. Findings reveal that feature metrics like cavity distribution and standard deviation of cavity areas affect insulation. Additionally, to improve time-consuming simulations, we proposed a model using Graph Neural Networks (GNNs) for accurate and rapid thermal assessments of complex Voronoi sections. Our GNN model, which uses graph-structured data rather than design parameters as training inputs, outperforms another four widely used models, achieving over 85 % prediction accuracy. In this research, two novel approaches are introduced: a Bayesian-based statistical model to understand the relationship between multiple feature metrics and insulation, pinpointing the most promising search space affiliated with certain values ranges of various feature metrics, and a rapid and accurate GNN-based model that uses graph representations of Voronoi sections in building components, preserving detailed geometric information for insulation prediction. Both approaches collectively improve the design process for building components with material-filled Voronoi sections by narrowing the search space and enhancing evaluation efficiency, respectively.

Model performance evaluation of build time using geometric shape complexity and process parameters in material extrusion

Additive Manufacturing (AM) is gaining widespread interest and recognition in both academia and industry due to its numerous advantages over traditional manufacturing processes. The AM process offers two significant benefits: mass customization and the ability to achieve higher shape complexity at no cost. The present study introduces a methodology for quantifying the shape complexity of feature-based parametric models that AM can produce. This method is exclusively a quantitative approach based on the “number of inputs” required to define the feature or integral sketch. Furthermore, an Artificial Neural Network (ANN) based predictive model for estimating the AM build time has been developed and validated. Supervised Machine Learning (ML) is employed to predict printing time by considering significant design and manufacturing parameters that affect the overall process time. A performance evaluation is conducted between the developed ANN model and a statistical Multiple Linear Regression (MLR) model. The validation Computer Aided Design (CAD) samples are chosen to evaluate the ANN and MLR model's performance to predict the build time. It is observed that the ANN model outperforms the MLR model in estimating the build time of complex geometries. Regarding the efficiency of models, the ANN model achieved an R square value of 0.880 and a lower prediction error of 15.543%. However, the MLR model showed some sensitivity to high complexity and large volume parts when predicting printing time, with a R square value of 0.96. In contrast, the ANN model is more precise in forecasting FDM build time for complex geometries and large volume parts.

Design, manufacturing and experimental validation of additive manufacturing cores for bearing seats in carbon fibre reinforced polymer structures

The integration of carbon-fibre reinforced polymers (CFRP) in structural applications offers significant advantages due to their high strength-to-weight ratio. However, these materials exhibit limitations under out-of-plane loads, particularly in bearing applications. This study explores an innovative approach to enhance the performance of CFRP structures in such scenarios by incorporating annular polyamide inserts manufactured via additive manufacturing (AM).To evaluate the mechanical performance of the AM inserts, a novel ring tensile test is designed to emulate the bearing load conditions. This test also enables the analysis of the impact of several design and manufacturing parameters of the AM inserts, including surface geometry, surface treatment, internal structure, and curing process. These are then compared with specimens made of carbon fibre sheet moulding compounds (CF-SMC), commonly used to support bearing loads. The study reveals that AM inserts provide a viable alternative to state-of-the-art CF-SMC, offering a significant enhancement in mechanical properties under specific bearing loading conditions. The test results indicate a 17.7% improvement in the first failure limit and an 8.6% increase in the ultimate strength for AM inserts compared to CF-SMC.Additionally, the study develops a simplified analytical model to predict stress distributions and potential failure mechanisms, validating its efficacy through experimental data with discrepancies of less than 6%. Economic analysis underscores the cost benefits of AM inserts due to reduced labour and higher repeatability. This research demonstrates the potential of AM inserts to improve the stability and strength of CFRP structures, paving the way for their broader application in demanding load-bearing environments.

Optimal environmental sampling conditions for electrostatic aerosol-to-hydrosol collection of airborne viruses

Due to adverse effects of viral outbreaks on human health, accurate detection of airborne pathogens is essential. Among many methods available for bioaerosol sampling, electrostatic precipitation (ESP) has been used to directly collect bioaerosols as hydrosols. The performance of an ESP sampler depends on its design, operational and environmental parameters such as air relative humidity (RH), air temperature, sampling liquid type and liquid temperature. Thus, it is essential to identify and maintain optimal conditions throughout sampling process to operate the sampler at its highest capacity. This study provides crucial insights into parameters that affect the collection efficiency of the aerosol-to-hydrosol ESP sampler and its virus recovery. The results indicate that air temperature does not affect collection efficiency, meanwhile, air RH, sampling liquid temperature, and salt concentration are the main parameters that significantly affect collection efficiency. Likewise, when deionized water is used as sampling liquid, hydrogen peroxide concentration increases proportionally with increasing air RH, resulting in significant decrease of virus viability. Consequently, for ESP samplers similar to our study, the following conditions are recommended: air RH of 55–65%, air and sampling liquid temperature of 37 °C, and a mixture of 10–20 mM ascorbic acid in PBS as sampling liquid.