Selection Of Design Parameters Research Articles

Multi-objective crashworthiness optimization of square aluminum tubes with functionally graded BCC lattice structure filler

The objective of this study is to find the optimum design configurations for the crashworthiness of functionally graded lattice structure filled aluminum tubes under multiple impact loading conditions. Base strut diameter, draft angle and aspect ratio are considered as filler material design parameters, and the optimal design configurations are sought for maximizing the specific energy absorption and minimizing the peak crush force. The finite element simulations are performed to establish the sample design space; linear and non-linear least square regression meta-models are developed to estimate the objective function values; the weighted superposition attraction-repulsion algorithm is employed to create design alternatives and seek their optimum combinations. The compromise programming technique is also adapted for combining multiple objectives and generating different optimum design options. The results revealed that the proper selection of design parameters can effectively enhance the crashworthiness performance of hybrid structures under multiple impact loading conditions. In particular, the results showed that the specific energy absorption value of square tubes can be improved up to 76% with the selection of appropriate lattice filler parameters. The present study provides a guideline for the optimum design of functionally graded lattice structure filled thin-walled structures under multiple impact loading conditions.

Bifurcation Control for a Ship Maneuvering Model with Nonsmooth Nonlinearities

We consider a widely used form of models for ship maneuvering, whose nonlinearities entail continuous but nonsmooth second-order modulus terms. For such models bifurcations of straight motion are not amenable to standard center manifold reduction and normal forms. Based on a recently developed analytical approach, we nevertheless determine the character of local bifurcations when stabilizing the straight motion course with standard proportional control. For a specific model class we perform a detailed analysis of the linearization to determine the location of these bifurcations in the control parameter space and its dependence on selected design parameters. By computing the analytically derived characteristic parameters, we find that “safe” supercritical Andronov–Hopf bifurcations are typical. Through numerical continuation we provide a more global bifurcation analysis, which identifies the arrangement and relative location of stable and unstable equilibria and periodic orbits.

Design method of asphalt mixture with balanced noise reduction and mechanical properties

A design method of asphalt mixture is proposed for reducing the tyre/road noise while having good mechanical properties. Firstly, by comparing the simulated sound absorption coefficient curve with noise-frequency curve from practical road surface, the target air voids contents are obtained. Then, models which can predict the texture level and sound absorption coefficient from the given mixture properties, such as porosity, gradation, particle size, asphalt content, etc. as inputs parameters, are used for preliminarily selecting the design parameters of mixture. Test samples are made according to these selected design parameters in the lab. Test vales of the texture level, sound absorption coefficient and the skid resistance of the mixtures are obtained from laboratory measurements. These measurement values are used for predicting the attenuation of the tyre/road levels by means of statistical models. Mixtures with superior predicted noise reduction properties are selected for mechanical performance validation. Mixture design which shows the promising noise reduction properties as well as satisfying the mechanical performance requirement are considered as the optimal one, and it is suggested to be used as the road surface. Road surface designed from this method can both meet the needs of traffic load and noise reduction function.

Material Properties and Electric–Thermal–Stress Multiple Fields Coupling Simulation of Power Distribution Cable Accessories

In engineering applications, the material properties of the cable accessories are affected by electrical, thermal, and mechanical stress. In this work, the comprehensive properties of the insulation material and the semi-conductive material for the cable accessory are studied. Furthermore, the multiphysics field coupling simulation model is established to study the distribution and variation in electric, thermal, and stress fields. The experimental results show that the relative permittivity of silicone rubber (SiR) and cross-linked polyethylene (XLPE) gradually decreases with the increasing temperature, with values of 2.29 and 3.39 at room temperature, respectively. The thermal conductivity of the semi-conductive material is higher than that of SiR and XLPE, with values of 0.39, 0.21, and 0.30 W/( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{m}\cdot \text{K}$ </tex-math></inline-formula> ) at room temperature. In contrast, the semi-conductive material has a relatively low thermal expansion coefficient. The elasticity modulus of XLPE at room temperature is approximately 97.62 MPa. Moreover, the mechanical properties of the three materials are relatively good. The simulation results show that the electric field distortion caused by the temperature change is slight. The maximum electric field distortion point locates at the stress cone root, with a value of 2.22 kV/mm. The highest temperature of the cable accessory is approximately 50.31 °C, and the temperature difference between the inside and outside reaches 5.84 °C, which will cause a significant interface stress change. Besides, the internal temperature and temperature difference in the cable accessory vary widely with ambient temperatures and current loadings. The research will be guiding significance for material selection, structural design, and interfacial stress parameter selection of the cable accessories.

Globally Adaptive Neural Network Tracking for Uncertain Output-Feedback Systems.

This article investigates the problem of global neural network (NN) tracking control for uncertain nonlinear systems in output feedback form under disturbances with unknown bounds. Compared with the existing NN control method, the differences of the proposed scheme are as follows. The designed actual controller consists of an NN controller working in the approximate domain and a robust controller working outside the approximate domain, in addition, a new smooth switching function is designed to achieve the smooth switching between the two controllers, in order to ensure the globally uniformly ultimately bounded of all closed-loop signals. The Lyapunov analysis method is used to strictly prove the global stability under the combined action of unmeasured states and system uncertainties, and the output tracking error is guaranteed to converge to an arbitrarily small neighborhood through a reasonable selection of design parameters. A numerical example and a practical example were put forward to verify the effectiveness of the control strategy.

Complibot: A compliant external pipe climbing robot

The article presents the design of Complibot, a robot with a novel gripper for pipe climbing. The mechanism of the gripper involves the use of a bistable buckled beam, which is a type of bistable compliant mechanism. The bistable buckled beam in the gripper is alternately actuated between its gripped and ungripped states using a camshaft and lever mechanism, which is powered by a single DC motor. The design parameters associated with the gripper are obtained both experimentally and numerically. A proper selection of design parameters helps in the efficient functioning of the gripper. After the design of the gripper, two such grippers are fabricated and attached to each other by two stepper motor-driven lead screws to make a pipe climbing robot with inchworm locomotion. The mobility of the robot is controlled by an Arduino Uno microcontroller after the electronic components have been integrated. Finally, Complibot is subjected to a series of tests to establish its maximum load-carrying capacity when climbing a polyvinyl chloride (PVC) pipe. Complibot is found to perform satisfactorily without slipping while climbing a PVC pipe with a diameter of 105–115 mm, a velocity of 0.2 m/min, a power consumption of 18.58 W, a maximum load-carrying capacity of 114.64 N, and a payload to weight ratio of 0.52.

Thermal regulation mechanism of air-drying shelter to indoor environment of earth buildings located in Turpan basin with extremely dry and hot climate conditions

This study investigates the thermal regulation mechanism of air-drying shelter of earth buildings located in Turpan basin to indoor thermal environment under the extremely dry and hot climate condition. Firstly, a field measurement lasting for three days was performed to investigate the thermal effect of air-drying shelter on indoor thermal condition. The measured results indicated that air-drying shelter provides the shaded space and natural ventilation to reduce the internal surface temperature of the roof and further improve the indoor thermal comfort in the hot summer. Then, a series of numerical studies on the effects of design parameters of air-drying shelter on indoor environment of earth building in Turpan basin were performed. The selected design parameters of air-drying shelter included air-drying shelter to room height ratio, thickness of carved walls, thickness of air-drying shelter's roof and hole to wall area ratio. The simulated results demonstrated that hole to wall area ratio of the carved walls is considered as an important design parameter of air-drying shelter, and increasing hole to wall area ratio of carved walls could increase solar radiation heat gain of roof, leading to increasing internal surface temperature of roof and indoor air temperature.

Application of mechanical product design parameter optimization based on machine learning in identification

The selection of mechanical product design parameters is a key factor in determining product quality. The defects caused by unreasonable product parameter design are one of the main reasons for the extension of the product development cycle and the impact on product market competitiveness. A slurry blade is one of the most common mechanical structures, which is widely used in wind power, ship, hydropower, and other fields. To identify the parameter defects of mechanical product design in the early stage of the design stage, this paper proposes the parameter design optimization identification model based on Stacking integrated learning and studies the parameter selection and results in the analysis of the slurry blade model. Space Claim software in Ansys software establishes three-dimensional slurry blade models with different scales. Combined with the NSGA II optimization algorithm, the multi-objective optimization design of the aerofoil structure is carried out. The CFD software is used to simulate and verify the slurry blade model after parameter design optimization. The results show that the optimization identification model for the design of slurry blade parameters based on the Stacking integrated learning algorithm can realize the influence of the unexpected change of design parameters on the design results. The prediction accuracy of cavitation proportion is high under different working conditions, and the absolute error is <0.02. The simulation of the optimized blade shows that the cavitation proportion e reaches a minimum of 0.005. The purpose of guiding the selection of design parameters, machining parameters, and assembly accuracy parameters is achieved, the structural defects of the slurry blade are reduced, and the working efficiency of the edge is improved.

Numerical Study of a Miniaturized, 1–3 Piezoelectric Composite Focused Ultrasound Transducer

This study aimed to develop an optimal methodology for the design of a miniaturized, 1–3 piezoelectric composite focused ultrasound transducer. Miniaturized focused ultrasound (FUS) devices, generally guided through catheters, have received considerable attention in the biomedical and ultrasound fields as they can overcome the technical restrictions of typical FUS transducers. However, miniaturized transducers cannot readily generate a high acoustic intensity because of their small aperture sizes and the vibration mode coupling. As such, 1–3 composite transducers, having a high electromechanical coupling and efficient vibration directivity, break through the current technical restrictions. However, the systematic methodology for designing miniaturized FUS transducers has not been thoroughly discussed so far. Therefore, in this study, we designed 1–3 piezoelectric composite transducers using analytical and numerical methods. Specifically, extensive parametric studies were performed through finite element analysis under the coupled field with piezoelectricity, structural vibration, and acoustic pressure. The simulation results confirmed that the optimal design of the 1–3 composite type transducer produces much higher (&gt;160%) acoustic pressure output at the focal point than the single-phase device. Furthermore, the array type of the interstitial transducer was predicted to produce an unprecedented acoustic intensity of approximately 188 W/cm2 under a short duty cycle (1%). This study will provide valuable technical methodology for the development of interstitial, 1–3 composite FUS transducers and the selection of optimal design parameters.

Statistical evaluation on hydrologic performance of bioretention design parameters under different rainfall conditions

Effectiveness of a bioretention cell (BC) in mitigating stormwater peak flow load to an urban drainage system is highly dependent on the design configuration and retrofitting scale. The selection of appropriate BC design parameters has always been critical to achieving its maximum benefits. The BC modeling in the stormwater management model (SWMM) relies on numerous design parameters (in total of 18) with wide selection ranges, making parameter selection challenging. This study investigated the effect of hydrologic dynamics of BC design parameters under different rainfall conditions (i.e., intensity, duration, time-to-peak) on surface infiltration, surface outflow, and storage. Firstly, the seven influential BC design parameters (i.e., conductivity, berm height, vegetation volume, suction head, porosity, wilting point, and soil thickness) were selected based on one-factor-at-a-time (OAT) method, and 1000 random samples of each parameter were generated across the factor space by following respective uniform distributions. The simulations were performed with a python wrapper of SWMM (PySWMM) that used random samples for one parameter while leaving the others constant each time. In general, the statistical results of each parameter represent a significant variation in the volume distribution under various design rainfall conditions. Comparatively, the parameters of conductivity, berm height, and vegetation volume are categorized as the most influential compared to other BC design parameters for surface infiltration, storage, and surface outflow, respectively.

Designing Bayesian Two-Sided Group Chain Sampling Plan for Gamma Prior Distribution

Acceptance sampling is used to decide either the whole lot will be accepted or rejected, based on inspection of randomly sampled items from the same lot. As an alternative to traditional sampling plans, it is possible to use Bayesian approaches using previous knowledge on process variation. This study presents a Bayesian two-sided group chain sampling plan (BTSGChSP) by using various combinations of design parameters. In BTSGChSP, inspection is based on preceding as well as succeeding lots. Poisson function is used to derive the probability of lot acceptance based on defective and non-defective products. Gamma distribution is considered as a suitable prior for Poisson distribution. Four quality regions are found, namely: (i) quality decision region (QDR), (ii) probabilistic quality region (PQR), (iii) limiting quality region (LQR) and (iv) indifference quality region (IQR). Producer’s risk and consumer’s risk are considered to estimate the quality regions, where acceptable quality level (AQL) is associated with producer’s risk and limiting quality level (LQL) is associated with consumer’s risk. Moreover, AQL and LQL are used in the selection of design parameters for BTSGChSP. The values based on all possible combinations of design parameters for BTSGChSP are presented and inflection points’ values are found. The finding exposes that BTSGChSP is a better substitute for the existing plan for industrial practitioners.

Selection of design parameters of the system for changing the supply of power supplies for hydraulic systems of aircraft

The article develops a mathematical model of the variable flow pump of the aircraft power supply, designed to simulate the operation of the power supply depending on the speed of the sustainer engine, oil temperature, pressure and supply (removable power). In addition, a control algorithm has been developed that provides the required quality of the transient process, which is achieved by installing additional hydraulic resistances between the servo piston cavity, the drain hydraulic line and the control spool, which change the flow characteristic of the pump and contribute to the fastest attenuation of the transient process and reduce its oscillation.

An approach to the selection of design parameters based on conflict with constraints

The Axiomatic Design (AD) supports decision-making based on the axioms of independence and information. In the engineering design activity, the designer must make early decisions that impact the success of the project. These decisions are of paramount importance in the design of one-off products. In these products, one must make decisions in the early design phases, with scarce data about the product that will undeniably affect the solution. Applying the information axiom requires data from the alternative solutions under consideration that for one-off products are most often non-existent in the conceptual phase of the design.Additionally, the design process is highly conditioned by existing constraints, which significantly influence the outcome. This work suggests selecting design parameters (DP) for one-off products from different sets of proposals that comply with the independence of functional requirements (FR). AD design follows a hierarchical decomposition process from a conceptual to a detailed design. The proposed method allows selecting the DPs among the set of alternatives by quantifying the degree of conflict each solution presents to the constraints. It shows the first step to define the DPs, at each level of decomposition of the AD process. It is the first step to establish a zig in AD or, otherwise, a way to find a solution in the conceptual phase. It applies to one-off products – any product with one chance to be right. The paper applies this method to the DP selection of a manipulation device.

An integrated approach for selecting design parameters in smart product-service system conceptual design

Nowadays, with the rapid development of cyber physical systems, IoT, and artificial intelligence, more and more attention has been paid to adapting the combination of smart, connected products and their generated services. Among these, smart product-service system (SPSS) with the unique features of smartness, connection, value co-creation, and data-driven has been widely concerned. Therefore, based on axiomatic design theory, the mapping from function domain to physical domain is a critical process in SPSS's conceptual design and the selecting of design parameters in physical domain has great impact on meeting multi-stakeholders’ benefits. Nevertheless, despite a few works on requirement conversion, it is not clear about the mapping mechanism under the target of value co-creation. Aiming to fill this gap, an integrated SPSS conceptual design method is proposed to solve the cross-domain mapping problem. It decomposes and reorganizes SPSS's function requirements with requirement development laws in TRIZ and divides the physical domain into product-related domain and service-related domain. Design parameters would be selected and evaluated by domain experts based on fuzzy comprehensive evaluation from different dimensions, which could represent the benefit of multi-stakeholders. Next, a binary integer programming (BIP) model with restrictions from different stakeholders would be constructed, which could be regarded as a multi-objective optimization problem. To solve the BIP model, the genetic algorithm is used and the optimal design parameters combination could be generated as the output of this process. Finally, a case study is carried out to demonstrate the feasibility and advantages of the integrated approach for cross-domain mapping in SPSS conceptual design.

Selected design parameters of a thermal management system for a lithium-ion phosphate battery

Selected design parameters of a thermal management system for a lithium-ion phosphate battery

Influence of yarn geometry on electrical properties of silver-coated nylon filaments for e-textiles: a fundamental study

Conductive fibrous assemblies and yarns play a crucial role in wearable electronic textiles (e-textiles), through their use in flexible sensors and interconnects. This study investigated the influence of yarn twist and geometrical parameters on the electrical properties of silver-coated nylon multifilament yarns, ranging from 1-ply to 4-ply, with twist levels of 30 twists per meter (TPM) and up to 600 TPM. Increase in twist level resulted in decreasing yarn linear resistance, with a plateau at 300 TPM, along with limiting values for yarn specific volume (1.6-1.9 cc/g), and fibre orientation angle (12-18°). The increase in yarn conductivity with higher twist was explained by greater contact between the fibrous assembly, that bridges electrically conductive pathways in the yarn structure. Twisted yarns (2-ply) were fabricated into electrode structures via embroidery, and a progressive increase in contact impedance was observed, followed by a stabilization and plateau within the range of measured impedance from 210 to 300 TPM. This observation was attributed to the decrease in the yarn specific volume, and subsequently the longitudinal diameter with increasing twist level, which decreased the contact area between the skin and electrode interface. The electrodes fabricated from varying yarn twist levels were used for electrocardiogram (ECG) measurement, and demonstrated comparable signal quality to standard gel electrodes. This experimental and theoretical work forms the basis in defining relationships between established yarn twist mechanics and geometrical properties with electrical properties. This can guide materials and design parameter selection of suitable conductive yarns for e-textiles used in biopotential monitoring applications.

Optimal Design of Microstrip Antenna for UWB Applications using EBG Structure with the Aid of Pigeon Inspired Optimization Technique

Ultra-wideband (UWB) technology has become influential among academic research and industry because of its vast application in the wireless world. However, several drawbacks have in UWB based antenna. To tackle this, EBG (Electromagnetic Band Gap) structures have proposed. Furthermore, the design of EBG structures is very complex due to the uncertain EBG properties dependence upon unit cell parameters. Therefore, to the optimal design of micro strip antenna for applications of UWB, EBG-PIO (pigeon inspired optimization) on the basis of micro strip patch antenna has been proposed to enhance micro strip antenna’s performance in terms of directivity, gain, bandwidth and efficiency. To select design parameters optimally, the PIO technique is proposed with substrate material of Rogers RT/Duroid 6010 with height h = 1.6 mm. Proposed antenna return loss remains –34.6 dB to cover applications of UWB (3.1–10.6 GHz). Also, results exhibited by both proposed technique and fabricated model-based antenna has outperformed than existing techniques regarding directivity, return loss, bandwidth, gain and radiation efficiency.

Multi-objective optimization of metal hydride hydrogen storage tank with phase change material

• Transient simulation and optimization of a metal hydride storage tank. • Application of a phase change material to the metal hydride tank for heat recovery. • Appropriate selection of design parameters for the optimization purpose. • Consideration of hydrogen to metal ratio and the absorption time as the objective functions. • Finding the design parameters that reasonably satisfies both objective functions. The use of hydrogen as a future energy source to supply world fuel is essential. The storage problem is one of the main challenges facing the use of hydrogen as a fuel. In this study, we model and optimize the transient operation of a 2D metal hydride storage tank. A phase change material (PCM) is attached to a metal hydride tank for heat recovery during hydrogen absorption and heat supply during desorption. Four parameters, porosity and diameter of the metal hydride tank, initial temperature and melting temperature of the PCM, are selected to optimize hydrogen absorption. An advanced optimization algorithm is applied to increase the hydrogen to metal ratio and decrease the absorption reaction time. The hydrogen to metal ratio and the absorption time, when system pressure equals equilibrium pressure, are considered as the two objective functions. The optimization and appropriate selection of design parameters result in a significant increase in the hydrogen to metal ratio. For better understanding, five particular points in the ranges of high, mediocre and low values of hydrogen to metal ratio are selected on the optimized Pareto front. The effects of the different parameters on the objective functions are discussed for the optimal points. A final (global) optimum point is obtained based on the LINMAP method that reasonably satisfies both objective functions and the results in this point are presented and discussed separately.

Multi-objective robust optimization using adaptive surrogate models for problems with mixed continuous-categorical parameters

Explicitly accounting for uncertainties is paramount to the safety of engineering structures. Optimization which is often carried out at the early stage of the structural design offers an ideal framework for this task. When the uncertainties are mainly affecting the objective function, robust design optimization is traditionally considered. This work further assumes the existence of multiple and competing objective functions that need to be dealt with simultaneously. The optimization problem is formulated by considering quantiles of the objective functions which allows for the combination of both optimality and robustness in a single metric. By introducing the concept of common random numbers, the resulting nested optimization problem may be solved using a general-purpose solver, herein the non-dominated sorting genetic algorithm (NSGA-II). The computational cost of such an approach is however a serious hurdle to its application in real-world problems. We therefore propose a surrogate-assisted approach using Kriging as an inexpensive approximation of the associated computational model. The proposed approach consists of sequentially carrying out NSGA-II while using an adaptively built Kriging model to estimate the quantiles. Finally, the methodology is adapted to account for mixed categorical-continuous parameters as the applications involve the selection of qualitative design parameters as well. The methodology is first applied to two analytical examples showing its efficiency. The third application relates to the selection of optimal renovation scenarios of a building considering both its life cycle cost and environmental impact. It shows that when it comes to renovation, the heating system replacement should be the priority.

Adaptive neural network tracking control of an omnidirectional mobile robot

The trajectory tracking control problem of an omnidirectional mobile robot is studied in this article. The omnidirectional mobile robot is adsorbed by suction cups for aircraft skin inspection, which is a typical nonholonomic system. In the control design part, a novel adaptive neural network control scheme is presented in the presence of uncertainty and external disturbance. The adaptive neural network has the characteristics of weights online updating. The neural network is applied to estimate uncertainty online to obtain the desired tracking performance. The weights online updating algorithm contains a correction term, which is an improved algorithm to ensure robustness. On the basis of Lyapunov theory, the closed-loop system can converge to an arbitrarily small domain containing origin. This illustrates that the closed-loop system is globally asymptotically bounded stable. Excellent control performance can be obtained by selecting design parameters reasonably. A simulation example of tracking an eight-shape trajectory is given to verify the effectiveness of the proposed control scheme.