Design Of Engineering Components Research Articles

Optimal design of structural engineering components using artificial neural network-assisted crayfish algorithm

Abstract Optimization techniques play a pivotal role in enhancing the performance of engineering components across various real-world applications. Traditional optimization methods are often augmented with exploitation-boosting techniques due to their inherent limitations. Recently, nature-inspired algorithms, known as metaheuristics (MHs), have emerged as efficient tools for solving complex optimization problems. However, these algorithms face challenges such as imbalance between exploration and exploitation phases, slow convergence, and local optima. Modifications incorporating oppositional techniques, hybridization, chaotic maps, and levy flights have been introduced to address these issues. This article explores the application of the recently developed crayfish optimization algorithm (COA), assisted by artificial neural networks (ANN), for engineering design optimization. The COA, inspired by crayfish foraging and migration behaviors, incorporates temperature-dependent strategies to balance exploration and exploitation phases. Additionally, ANN augmentation enhances the algorithm’s performance and accuracy. The COA method optimizes various engineering components, including cantilever beams, hydrostatic thrust bearings, three-bar trusses, diaphragm springs, and vehicle suspension systems. Results demonstrate the effectiveness of the COA in achieving superior optimization solutions compared to other algorithms, emphasizing its potential for diverse engineering applications.

Computational Mechanics for Turbofan Engine Blade Containment Testing: Fan Case Design and Blade Impact Dynamics by Finite Element Simulations

The harsh environment during airplane take-off and flights with complex operating conditions require a high dynamic and impact resistance capability of airplane engines. The design, development, and performance evaluation of new turbofan engines are generally performed through numerical simulations before a full-scale model or prototype experiment for certification. Simulations of fan blade containment tests can reduce trial–error testing and are currently the most convenient and inexpensive alternative for design; however, certification failure is always a risk if the calibration of material models is not correctly applied. This work presents a three-dimensional computational model of a turbofan for designing new engines that meet the certification requirements under the blade containment test. Two calibrated Johnson–Cook plasticity and damage laws for Ti64 are assessed in a simulation of a turbofan blade containment test, demonstrating the ability of the models to be used in the safe design of aircraft engine components subjected to dynamic impact loads with large deformations and adequate damage tolerance.

Notch structural stress theory: Part II predicting total fatigue lives of notched structures

Notch fatigue problems are among the most common topics for the reliability analysis and structural design of mechanical engineering components. In previous work, we proposed the Notch Structural Stress (NSS) method based on fracture mechanics for reflecting the notch effect on fatigue crack propagation lives. However, like other regular fatigue assessing procedures, NSS also cannot accurately predict the fatigue life of notched structures with slower stress gradients due to the inconsistent slope of their S-N curves. This paper presents the Theory of Notch Structural Stress (TNSS) for predicting total fatigue lives of notched structures, which overcomes the life prediction limitations caused by slope differences in S-N curves and constructs a life-predicting frame suitable for different notch types even including plain and sharp notches. Compared with the often-used stress-concentration-assessing procedures, TNSS provides a more effective consolidation of the S-N data from different notch types, mostly since it takes both Initiation and Propagation state resistance into account at the same time.

Analysis of geometric uncertainties in 3D thermo-fluid problems solved by RBF-FD meshless method

The tolerances of production processes can lead to uncertainties in the behaviour and in the features of the manufactured products. From the point of view of the design of engineering components it is therefore of valuable practical interest to be able to quantify such uncertainties as well as the expected, i.e., averaged, performances. Such uncertainty quantification is carried out in this work by means of the Non-Intrusive Polynomial Chaos (PC) method in order to estimate the propagation of geometrical uncertainties of the boundaries, i.e., when the boundaries are described by stochastic variables. Existing deterministic solvers can be used with the PC method because of its non-intrusive formulation, allowing an accurate and practical prediction of the random response through a simple set of deterministic response simulations. The Radial Basis Function Finite Differences (RBF-FD) method is employed as a black box solver for the computation of the required set of responses defined over deterministic boundaries. The RBF-FD method belongs to the class of meshless methods which do not require a computational mesh/grid, therefore its main capability is to easily deal with practical problems defined over complex-shaped domains. The geometrical flexibility of the RBF-FD method is even more advantageous when coupled to the Non-Intrusive PC method for uncertainty quantification since different deterministic solutions over different geometries are required. The applicability of the proposed approach to practical problems is presented through the prediction of geometric uncertainty effects for a steady-state forced convection problem in a 3D complex-shaped domain.

ANALYSIS OF THIN-WALLED COMPONENTS WITH INTERNAL MICROSTRUCTURE DESIGN MANUFACTURED BY LPBF

Additive Manufacturing techniques represent a revolution for the design of certain engineering components traditionally subject to a design highly influenced by the manufacturing process linked to the manufacture of the component. Additive Manufacturing techniques therefore allow components with different internal and external structures to be manufactured. Thus, components formed by an internal microstructure are of special interest due to their high strength-to-weight and high stiffness-to-weight properties. This work investigates the hybrid fabrication of curved thin-walled Inconel 718 with internal microstructural supports fabricated by laser powder bed fusion (LPBF). The outer walls are made up of solid surfaces with a fixed curvature and thickness, while the internal structure of the pieces is made up of internal microstructures that vary at different angles of inclination. Finally, the outer surfaces of the piece have been milled. Eventually, the dimensional quality of the components and their internal microstructure has been analysed.

Scaling Overall Effectiveness in Low-Temperature Experiments

Abstract The design of film-cooled engine components requires an understanding of the expected temperature distributions while in service, thus requiring accurate predictions through low-temperature testing. Overall effectiveness, ϕ, is the integrated indicator of overall cooling performance. An experiment to measure ϕ at low temperature requires appropriate scaling through careful selection of not only the coolant and freestream gases but also the model material itself. Matching ϕ requires that the experiment has matched values of the adiabatic effectiveness, Biot number, coolant warming factor, and ratio of external to internal heat transfer coefficient. Previous research has shown the requirements to match each of those four parameters individually. However, matching all those parameters simultaneously presents an overconstrained problem, and no comprehensive recommendations exist for the practical experimentalist who wishes to conduct an appropriately scaled, low-temperature experiment truly suitable for determining ϕ. Four fluidic parameters are identified, which in an experiment must be as close as possible to their values at engine conditions. A normalized root-mean-square difference (NRMSD) of the residuals of those parameters is proposed to quantify how well a proposed wind tunnel experiment is likely to yield engine-relevant ϕ values. We show that this process may be used by any experimentalist to identify the appropriate fluids, conditions, and materials for a matched ϕ experiment. Several case studies were performed using computational fluid dynamics (CFD) to show the utility of this process. Of the common experimental techniques examined here, a matched Biot number experiment with 500 K freestream air and 250 K coolant appears to be particularly adept at simulating engine conditions, even better than experiments that make use of CO2 coolant.

A Modified Constitutive Model for Isotropic Hyperelastic Polymeric Materials and Its Parameter Identification.

Given the importance of hyperelastic constitutive models in the design of engineering components, researchers have been developing the improved and new constitutive models in search of a more accurate and even universal performance. Here, a modified hyperelastic constitutive model based on the Yeoh model is proposed to improve its prediction performance for multiaxial deformation of hyperelastic polymeric materials while retaining the advantages of the original Yeoh model. The modified constitutive model has one more correction term than the original model. The specific form of the correction term is a composite function based on a power function represented by the principal stretches, which is derived from the corresponding residual strain energy when the Yeoh model predicts the equibiaxial mode of deformation. In addition, a parameter identification method based on the cyclic genetic-pattern search algorithm is introduced to accurately obtain the parameters of the constitutive model. By applying the modified model to the experimental datasets of various rubber or rubber-like materials (including natural unfilled or filled rubber, silicone rubber, extremely soft hydrogel and human brain cortex tissue), it is confirmed that the modified model not only possesses a significantly improved ability to predict multiaxial deformation, but also has a wider range of material applicability. Meanwhile, the advantages of the modified model over most existing models in the literatures are also demonstrated. For example, when characterizing human brain tissue, which is difficult for most existing models in the literature, the modified model has comparable predictive accuracy with the third-order Ogden model, while maintaining convexity in the corresponding deformation domain. Moreover, the effective prediction ability of the modified model for untested equi-biaxial deformation of different materials has also been confirmed using only the data of uniaxial tension and pure shear from various datasets. The effective prediction for the untested equibiaxial deformation makes it more suitable for the practice situation where the equibiaxial deformation of certain polymeric materials is unavailable. Finally, compared with other parameter identification methods, the introduced parameter identification method significantly improves the predicted accuracy of the constitutive models; meanwhile, the uniform convergence of introduced parameter identification method is also better.

On a numerical methodology to assess the fatigue life of connecting rods

Although simulation-based fatigue analysis is a standard tool adopted in every sector including automotive industry, the design of engine components in automotive and motorsport applications mostly relies on simplified design approaches supported by time-consuming testing programs. This manuscript proposes a new methodology based on individual engine speed damage estimation and engine speed time history combined with Palmgren-Miner linear damage rule to predict the fatigue state of the connecting rod. The track data, engine multibody simulation (AVL ExciteTM) and engine combustion simulation (AVL BoostTM) are used to generate the initial variable trace that is processed to obtain the block programs. Stress amplitude estimated with finite element analysis (Abaqus) are used to estimate the damage from S-N curve and the cumulative damage is estimated with Palmgren-Miner cumulative damage model. The method proposed is demonstrated using a connecting rod case study and the duty cycle from the race on Sebring international raceway. This work shows the suitability of the approach and the benefit in terms of accuracy in the prediction of the fatigue life.

On the Use of Surface Roughness Parameters

In most practical applications, surface roughness is characterized by just one or two parameters (numbers). I show that the standard maximum surface height parameters fluctuate strongly between different surface realizations (or measurements), and should not be used in the design of engineering components. I show how some roughness parameters depend on the size of the roll-off region in the surface roughness power spectra, and introduce a new height parameter which is very reproducible. The numerical results presented agree well with experimental observations.Graphical

Structural Efficiency Analysis of a Piston for Aviation Engines

The high-performance piston has a great impact on the performance parameters of the engine. The rapid design of a high-performance piston can shorten the research and development cycle and lower the experimental cost. At present, the piston design is mostly considered from a single factor, but it has not been comprehensively designed from multiple factors. Starting from the concept of structural efficiency, this paper defines the restrictive factors affecting engine performance parameters in piston design, puts forward an evaluation method of quantifying the benefit of piston design on engine performance parameters, and deduces the calculation model. The piston is designed and iterated many times to obtain the best two schemes. The two schemes are quantitatively compared through the above calculation model and verified by experiments. The results show that the structural efficiency of the piston in scheme 2 is 4.6% higher than that in scheme 1. The calculation method is applicable to the design of key engine components, which can shorten the research and development cycle, save the test costs, and greatly improve the R&D efficiency.

Data‐driven approach to design fatigue‐resistant notched structures

AbstractFatigue is the most common failure mode for engineering materials in various industrial applications. Generally, designing new products and components based on typical deterministic fatigue design approaches is slow and expensive. Although numerous investigations have been carried on this topic over decades, there still lacks a robust and efficient method to design a super‐fatigue‐resistant and testless structure. In this investigation, a novel data‐driven approach based on the deep learning algorithm is applied on designing a fatigue‐resistant notched structure under different loading via numerical simulations and deep learning. The notches with various shapes are designed by employing the same material. Then finite element (FE) simulations are performed to obtain the mechanical behaviors of notched structures under different loading conditions. The deep learning algorithm is applied to predict mechanical behaviors of unknown notched structures based on input training set of simple notched geometries and relative lower computational cost. It is demonstrated that deep learning on the fatigue‐resistant structure is a promising approach of fatigue design. This work offers an alternative design strategy of fatigue‐resistant structure and cost‐effective solution to accelerate the design of engineering components under different loading conditions.

Size effect in fatigue modelling of defective materials: Application of the calibrated weakest-link theory

Fatigue life prediction is critical for the design of engineering components made from defective materials. Not only do these imperfections show a detrimental effect on the fatigue performances, but they also contribute to a considerable scatter of fatigue properties. In this work, a probabilistic fatigue life prediction model under size effect was proposed based on the calibrated weakest-link theory (WLT) considering the defect location and the size sensitivity. Specifically, a surface factor was defined to consider the superiority of the surface-defect. In addition, a size sensitivity factor was developed to capture the sensitivity of fatigue strength to the volume/size change. Model validation and comparison using two types of metallic materials indicated that the developed surface factor and size sensitivity factor improve the predictive ability of the traditional WLT.

Manta ray foraging optimization algorithm and hybrid Taguchi salp swarm-Nelder–Mead algorithm for the structural design of engineering components

Abstract The adaptability of metaheuristics is proliferating rapidly for optimizing engineering designs and structures. The imperative need for the fuel-efficient design of vehicles with lightweight structures is also a soaring demand raised by the different industries. This research contributes to both areas by using both the hybrid Taguchi salp swarm algorithm-Nelder–Mead (HTSSA-NM) and the manta ray foraging optimization (MRFO) algorithm to optimize the structure and shape of the automobile brake pedal. The results of HTSSA-NM and MRFO are compared with some well-established metaheuristics such as horse herd optimization algorithm, black widow optimization algorithm, squirrel search algorithm, and Harris Hawks optimization algorithm to verify its performance. It is observed that HTSSA-NM is robust and superior in terms of optimizing shape with the least mass of the engineering structures. Also, HTSSA-NM realize the best value for the present problem compared to the rest of the optimizer.

Machining-induced characteristics of microstructure-supported LPBF-IN718 curved thin walls

The microstructure-supported design of engineering components is recently gaining attention due to their high strength-to-weight and high stiffness-to-weight properties. The present study investigates the hybrid manufacturing of Inconel 718 curved thin walls with internal microstructural supports fabricated by laser powder bed fusion (LPBF). Printed walls contain a fixed curvature and thickness, whereas the internal microstructures were varied at different inclination angles. In this research, a finish milling operation has been performed at different milling parameters. Machining-induced damages on the internal microstructures have been studied and correlated with geometrical deviation and surface integrity features on the outer thin wall surfaces.

A phenomenological constitutive model for predicting both the moderate and large deformation behavior of elastomeric materials

Constitutive models that describe nonlinear elastic mechanical behavior are indispensable in the design of engineering components fabricated of elastomeric materials. The main drawbacks of the existing models include complexities in calibrating the model to experimental data and erroneous descriptions of multi-axial response. These challenges motivate researchers to continually formulate new or improved models with better predictive capabilities. In this work, we propose a new polynomial-type phenomenological model with linear and logarithmic dependence on the first and the second invariants respectively. Model parameters were obtained by utilizing the Levenberg-Marquardt algorithm to fit the model expression to the strain energy density data calculated from the experimental data of uniaxial tension loading. The predictive performance of our proposed model in comparison to that of three popular existing models was determined by utilizing three sets of classical experimental data from the literature with varying deformation ranges. Quantities used to relate the predicted and the experimental data include the coefficient of determination, relative errors, and average relative error (for overall behavior). The computations demonstrated that the proposed model exhibits superior predictive capabilities for the entire deformation range whilst requiring minimum efforts in obtaining its parameters, thus, exhibits the desirable features of a phenomenological hyperelastic model.

Surface Engineering Development Trends and Impact of Surface Coatings and Textures on Automotive Powertrain Friction and Wear Control

Abstract The global automotive industry is facing higher energy costs, more legislative pressure, and an ever-increasing environmental awareness to achieve fuel efficiency and environmental sustainability. In recent years the automotive industry has undergone a revolution in hardware and materials. Among these approaches, engine friction reduction and wear control by surface engineering are the most effective approaches. In this paper, surface engineering and its impact of surface coatings and texture technologies on powertrain components will be reviewed. Recently the lightweight nonferrous alloy and nanocomposites are being incorporated into the emerging powertrain technologies—including a wide range of surface coating materials such as thermal sprayed aluminum liners, diamond-like carbon-coated valve train components, and hard nitride piston rings or composite coatings toward energy-efficient and wear-resistant systems. The major section of this paper will discuss the future development trends of engine friction reduction and wear control by surface modification such as friction-reducing and wear-resistant coatings or surface textures in powertrain components. The impact of surface coatings or surface textures on tribological characteristics will be reviewed. Specifically, this review paper will address the impact of these emerging technologies on engine material requirements. The connection between surface engineering and the emerging powertrain technologies will be described. In summary, this paper will review the impact of emerging surface engineering technologies on tribological performance and future trends for advanced powertrain components. In addition, the bench and engine wear and scuffing assessments will be reviewed in terms of wear and scuffing resistance for a variety of surface coatings or textures applied to engine components. This paper also addresses the interactions between powertrain components and surface coatings or textures and their effects on friction, wear, and engine durability. The increasing importance of surface coatings and textures in engine component design and tribological performance will be fully illustrated.

Natural frequency and critical velocities of heated inclined pinned PP-R pipe conveying fluid

Purpose: The flow velocity and pressure of fluid flowing through a pipeline can cause the vibration of pipes, and consequently result in the modification in natural frequency via fluid-structure interaction. The value of the natural frequency of a component when approaches the excitation force to a certain degree, a severe resonance failure may occur. Hence, avoiding the resonance failure of a pipe subjected to complex conditions is an essential issue that requires to be solved urgently in the engineering field. This work treats the transverse vibration for flexible inclined heated pipe, made of polypropylene randomcopolymer (PP-R), conveying fluid assuming pinned connections at the ends. The pipe was placed at different support angles and subjected to variant temperatures. Design/methodology/approach: The inclined pipe is modelled as Euler-Bernoulli beam taking into account its self-weight, temperature variation, inclination angle, aspect ratio, and internal fluid velocity. The integral transforms method, which includes the finite Fourier sine and the Laplace transforms, was used to develop an analytic solution to the modified equation of motion and the analytical expressions for dual natural frequencies of the pipefluid interaction system were computed. Findings: The proposed solution technique via finite Fourier sine and Laplace transforms offers a more convenient alternative to calculate the dynamic characteristic of pipes conveying fluid. The obtained results showed that the dynamical behaviour of pipe–fluid system is strongly affected by fluid flow velocity, degree of inclination, temperature variation, and aspect ratio of the pipe in transverse modes. Research limitations/implications: This work focuses on fundamental (first) mode in the most discussions. Practical implications: It was revealed that the thermal effects in the pipe are a very important factor and more significant in comparison with the internal fluid velocity and the inclination angle has a larger impact on vibration characteristics at a higher aspect ratio. The findings can be useful for the design of engineering components. Originality/value: Determining the combining effect of inclination angle, aspect ratio, and thermal loading on vibration characteristic of the pipes conveying fluid by using an improved analytic solution to the modified equation of motion via mixed of finite Fourier sine and Laplace transforms.

Identification of In-Cylinder Aerosol Flow Induced Emissions due to Piston Ring Design in a DISI Single Cylinder LV Engine Using Oxygenated Synthetic Fuels

<div class="section abstract"><div class="htmlview paragraph">In the near future, pollutant and GHG emission regulations in the transport sector will become increasingly stringent. For this reason, there are many studies in the field of internal combustion research that investigate alternative fuels, one example being oxygenated fuels. Additionally, the design of engine components needs to be optimized to improve the thresholds of clean combustion and thus reduce particulates. Simulations based on PRiME 3D® for dynamic behaviors inside the piston ring group provide a guideline for experimental investigation. Gas flows into the combustion chamber are controlled by adjusting the piston ring design. A direct comparison of regular and synthetic fuels enables to separate the emissions caused by oil and fuel. This study employed a mixture of dimethyl carbonate (DMC) and methyl formate (MeFo). These two components have no C-C bonds, and the mixture displayed extremely good performance in terms of the particle number (PN) emissions on an ambient level published in previous studies. This fuel property is employed in this study to identify oil induced, engine-out PN-emissions, while the combustion process remains almost identical to that of conventional gasoline. The PN-emissions are measured and subdivided into two ranges: larger than 10 nm and larger than 23 nm.</div><div class="htmlview paragraph">It was demonstrated that merely changing the piston ring design has an impact on raw PN engine emissions and gas flow behavior in the piston assembly. An increase in PN-emissions and lower blow-by level could only be detected by changing the piston ring design. With reduced, predicted fluid flows into the combustion chamber, lower VOC emissions could be observed during motored runs. The adaptations in the tested piston ring design demonstrate that it is possible to improve particulate emissions by modifying the piston ring group.</div></div>

Propagation of geometric uncertainties in heat transfer problems solved by RBF-FD meshless method

The design of engineering components must take into account the manufacturing tolerances of production processes since they lead to uncertainties in the behaviour of the products. It is therefore of valuable practical interest to quantify such uncertainties, with particular reference to problems involving geometrical uncertainties of the boundaries. This task is carried out in the present work by coupling the Non-Intrusive Polynomial Chaos (PC) method, employed for the quantification of uncertainties, with a Radial Basis Function Finite Differences (RBF-FD) meshless method, employed for the numerical simulations. The PC method with the Non-Intrusive formulation allows the use of existing deterministic solvers for the accurate prediction of the sought random response, i.e., the statistic moments of the involved variables. The RBF-FD method is therefore employed as a black box solver for the required set of problems defined over deterministic domains. The main advantage of the RBF-FD meshless method over traditional mesh-based methods is its capability of easily deal with practical problems defined over complex-shaped domains since no traditional mesh is required. The geometrical flexibility of the RBF-FD is even more advantageous in the context of geometric uncertainty quantification with the Non-Intrusive PC method since different solutions over different geometries are required. The applicability of the proposed approach to practical problems is then presented through the prediction of geometric uncertainty effects for a tube heat exchanger under natural convection where a 2D steady incompressible flow is considered.

Design Space Exploration of a Jet Engine Component Using a Combined Object Model for Function and Geometry

The design of aircraft and engine components hinges on the use of computer aided design (CAD) models and the subsequent geometry-based analyses for evaluation of the quality of a concept. However, the generation (and variation) of CAD models to include radical or novel design solutions is a resource intense modelling effort. While approaches to automate the generation and variation of CAD models exist, they neglect the capture and representation of the product’s design rationale—what the product is supposed to do. The design space exploration approach Function and Geometry Exploration (FGE) aims to support the exploration of more functionally and geometrically different product concepts under consideration of not only geometrical, but also teleological aspects. The FGE approach has been presented and verified in a previous presentation. However, in order to contribute to engineering design practice, a design method needs to be validated through application in industrial practice. Hence, this publication reports from a study where the FGE approach has been applied by a design team of a Swedish aerospace manufacturers in a conceptual product development project. Conceptually different alternatives were identified in order to meet the expected functionality of a guide vane (GV). The FGE was introduced and applied in a series of workshops. Data was collected through participatory observation in the design teams by the researchers, as well as interviews and questionnaires. The results reveal the potential of the FGE approach as a design support to: (1) Represent and capture the design rationale and the design space; (2) capture, integrate and model novel solutions; and (3) provide support for the embodiment of novel concepts that would otherwise remain unexplored. In conclusion, the FGE method supports designers to articulate and link the design rationale, including functional requirements and alternative solutions, to geometrical features of the product concepts. The method supports the exploration of alternative solutions as well as functions. However, scalability and robustness of the generated CAD models remain subject to further research.