Changes In Design Variables Research Articles

Optimization and Comparative Analysis of Quarter-Circular Slotted Microstrip Patch Antenna Using Particle Swarm and Fruit Fly Algorithms

This paper proposes a parametric study of modified rectangular microstrip antenna in the frequency range between 1.4-2.65 GHz for wireless communication applications, incorporating with optimization methods Particle Swarm Optimization (PSO) and Fruit Fly Optimization (FOA). To design an antenna using optimization methods a fitness function of required parameters is needed. The resonance frequency of Microstrip Patch Antennas (MPAs) depends on various parameters and a standard frequency function does not exist for MPAs. In this study, a rectangular patch antenna is designed for the required resonance frequency and modified with circular quarter slots. The frequency-shift with the change of design variables, which are the substrate thickness and the radius of the slots, is observed. The resonance frequency is obtained as a function of the design variables and it is used in the optimization process to minimize the difference between the target frequency and the calculated one. The original algorithms FOA and PSO have been adapted for its application to a modified rectangular patch antenna design problem: resonance frequency and design of antenna. The design parameter values obtained via optimization and the performances of the optimization methods are presented. The results showed that both PSO and FOA find the dimensions correctly. It is also observed that the sensitivity of the FOA increases with the fruit fly population and the convergence gets faster. The outcomes of this paper show that the PSO algorithm gives better results when compared to the FOA for the proposed antenna.

Advanced Analysis of Collision-Induced Blast Fragmentation in V-Type Firing Pattern

The firing pattern of blastholes influences the geometric aspects of a blast design in terms of change in blasting burden and spacing. This in turn changes the effective stiffness of a blasthole and confinement of the explosive and aids in better fragmentation. However, during the blasting, the fragments tend to collide and further fragment the rock. In comparison with other patterns, the V-type firing pattern increases the chances of collision between the fragments during flight. The process is scantly documented and accordingly field experiments were conducted using three firing patterns, viz., line, diagonal, and V-type, in a mine with minor variation in rock factor and minor to moderate changes in blast design variables. Sixteen blast design variables such as burden, spacing, charge per hole, in-hole charge density, etc. along with firing pattern were considered for the analysis and fragmentation modeled with the help of surface response analysis and artificial neural networks. The analysis revealed that there is a significant influence of firing patterns on fragmentation. The V-type pattern showed significant reduction in fragment sizes that can be ascribed to in-flight collision processes. A surface response model was developed using advanced ANOVA and resulted in an adjusted R2 and RMSE of 0.89, 0.025, respectively. Further, modeling with ANN was attempted that showed better results than ANOVA with R2 and RMSE of 0.96 and 0.040 in training, and 0.884 and 0.049 in validation tests. Since, diagonal and V-type patterns have similar design parameters, the reduction in fragment size in the former pattern can be ascribed to the collision of rock fragments during their flight in blasting.

Virtual product development process for reducing noise, vibration, and harshness of vehicle based on substructuring and artificial neural network

In this study, virtual product development method for reducing vibration and noise is proposed for designing at the concept development stage of a vehicle. To this end, the vibration characteristics of the system are predicted through the Lagrange-multiplier frequency-based substructuring technique. The concepts of contact, blocked and transmitted force, and force transmissibility were used for determining the improvement subsystem or combination of subsystems when using the modular platform. Moreover, after the subsystems to be improved were determined, Artificial Neural Network was used as a method of predicting vibration characteristics according to the change of design variables. To verify this, the prediction of the blocked force was performed by changing the young’s modulus of the simplified substructure. Finally, the reduction in response was confirmed by applying the blocked force of the simplified subframe to the simplified structure, and a vehicle development process using a database at the concept setting stage is proposed.

Propeller effects on energy, exergy and sustainability parameters of a small turboprop engine

Turboprop engines have been commonly adopted for several applications such as unmanned aerial vehicle and commuter aircraft. In this study, the effects of propeller efficiency (PEF) with various compressor pressure ratio (CPR) are examined for energetic, exergetic, environmental and sustainability indicators of a small turboprop engine (S-TPE) at sea level. For this aim, PEF of the S-TPE has the range varying between 0.7 and 0.95 whereas its CPR has boundary changing between 10 and 12.5. According to performance results, thrust of the S-TPE changes from 5.11 kN to 6.88 kN due to rising PEF and from diminishes from 5.9 kN to 5.68 kN due to rising CPR whereas overall efficiency of the S-TPE alters from 22.1% to 29.7% owing to the PEF effect and from 24.7% to 25.5% owing to the CPR effect. On the other hand, exergetic parameters of the components of the engine remain constant with the PEF effect whereas both effects (PEF and CPR) are observed on exergetic metrics of the whole engine. In this context, exergy efficiency of the combustor increases from 84.83% to 86.7% due to only the CPR effect. Moreover, exergy efficiency of the S-TPE experiences the increase from 21.39% to 28.77% due to rising PEF while it raises from 23.99% to 24.71% due to rising CPR. Finally, specific wasted exergy of the S-TPE decreases from 0.7566 MW/kN to 0.5624 MW/kN with the effect of PEF whereas it drops from 0.6751 MW/kN to 0.6540 MW/kN with the effect of CPR. These findings show that a small change in design variables reflects on energetic and exergetic performance of the engine at different degrees.

Multi-Objective Robust Optimization of Deep Groove Ball Bearings Considering Manufacturing Tolerances Based on Fatigue and Wear Considerations

Abstract In designing any machine element, we need to optimize the design to attain its maximum utilization. Herein, deep-groove ball bearings have been chosen for optimization. Optimization has been done in such a way that the design is robust so that manufacturing tolerances can be considered in the design. Robust design ensures that changes in design variables due to manufacturing tolerances have a minimum effect on the objective function, i.e., its performance. Robustness is achieved by maximizing the mean value of the objective function and minimizing its deviation. For rolling element bearings, its life is one of the most crucial considerations. The rolling bearing rating life depends on dynamic capacity, lubrication conditions, contamination, mounting, manufacturing accuracy, and material quality, and thus, the dynamic capacity and elasto-hydrodynamic minimum film thickness have been taken as objective functions for the current problem. Rolling element bearings have standard boundary dimensions, which include the outer diameter, inner diameter, and bearing width for the case of deep-groove ball bearings. So the performance can be improved by changing internal dimensions, which are the bearing pitch diameter, ball diameter, the inner and outer raceway groove curvature coefficients, and the number of rolling elements. These five internal geometrical parameters are taken as design variables; moreover, five design constraint factors are also included. Thirty-six constraint equations are considered, which are mainly based on geometry and strength considerations. In the present work, the objective functions are optimized individually (i.e., the single-objective optimization) and then simultaneously (i.e., the multi-objective optimization). Nondominated sorting genetic algorithm (NSGA-II) has been used as the optimization tool. Pareto-optimal fronts are obtained for one of the bearings. Of many points on the Pareto-front, only the knee solutions have been presented . This paper shows that geometrically feasible bearings can be designed by optimizing multiple-objective functions simultaneously and by also incorporating the variations in dimensions, which occur due to manufacturing tolerance.

Large deflection model for rub-impact analysis in high-speed rotor-bearing system with mass unbalance

This research article investigated the rotor-casing contact phenomena of a high-speed rotor-bearing system under mass unbalance situation. Here, large deflection rotor-bearing model with a flexible shaft, a rigid disk loaded with an unbalance mass and contact phenomenon between a disk and casing of the rotating system has been used. A nonlinear mathematical model of a rotating system has been developed to study the steady-state stability by elucidating the state of bifurcation and route to chaos phenomena. The steady-state bifurcations and plausible route to chaos phenomena have been explored by numerically solving the governing motion upon gradually varying the design parameters i.e., flexible co-efficient, friction, shaft speed and unbalance mass. The rub-impact onto this large deflection model along with mass unbalance advocates the changes in dynamic state and ill-fated instability where the system losses its structural stability due to the presence of critical bifurcation and sensitivity toward chaotic responses. The present system enables a complex dynamic evolving with periodic, multi-period periodic solutions, sequences of period-doubling to chaotic motion on a gradual change in design variables. The results obtained will contribute to predict and identify the parametric conditions at which the system is safe from any contact between casing and rotor–disk.

Program development on cleaning pattern and performance evaluation for low pressure waterjet

Waterjet is a device that cuts or crushes materials using water pressure injected through the nozzle. Especially, Low pressure waterjet is used in stripping and cleaning work. The cleaning patterns of the low pressure waterjet is determined by various design variables, such as the number of nozzles, an angle of nozzles, gear ratio and so on. In order to optimize the cleaning pattern, the optimum waterjet design is required depending on the shape of the target structure. To do this, a large number of waterjet analysis models should be used. This study reduced design time by automating the creation of the desired analysis model with simple changes in design variables, and conducted evaluation of the cleaning patterns using numerical method for the most frequently used cylindrical structures. In addition, it analyzed the effects of changes in design variables and suggested improvements. Moreover, the idea of a module type waterjet was proposed to reduce the cost of waterjet replacement due to usage changes. This study can be used to design the waterjet, which suits a particular purpose.

A combined rate-shaping-splitting injection strategy for regulating stratification characteristics of fuel sprays

Producing a desired level of fuel stratification has recently aroused much interest to improve performance of combustion systems. In the present work, an injection strategy is proposed by combining the rate-shaping (IRS) and split-injection approaches for regulating the level and quality of stratification. An Eulerian-Lagrangian numerical model is detailed and calibrated against available experiments to study the effect of the uniform and combined IRS-splitting strategy parameters on spray characteristics. The results are analyzed carefully to identify the connection between the liquid and vapor penetration lengths (LL and VL) and the stratification parameters. We also try to reveal the physics underlying the variation of these parameters by the change of common design variables, like the ambient temperature and pressure, as well as by the variables specific to the IRS-splitting strategy. It is proven that the stratification parameter is a better measure of mixture inhomogeneity than VL. For instance, the proposed combined strategy is able to achieve a 50% increase in stratification while keeping the VL variation limited to 3%. Finally, our results demonstrate that the stratification can be effectively controlled by the combined strategy by adjusting the number of split injections and flow-rate coefficients of the main and pilot injections.

Bond graph modeling of a typical flapping wing micro-air-vehicle with the elastic articulated wings

In the present research, a new comprehensive model of a flexible articulated flapping wing robot using the bond graph approach is presented. The flapping kinematics of a two-section wing is introduced via the bond graph based approach on a hybrid mechanism providing amplitude and phase characteristics. The aerodynamic quasi-steady approach equipped with stall correlation is utilized according to the reduced flapping frequency and the angle of attack ranges. The local flow velocity and the wing position are calculated in both wing and body coordinates taking into account rotation and translation of the wing different parts. Estimation of the effective angle of attack is performed by calculating the instantaneous torque distribution on both wing sections. Aeroelastic modeling is employed in which the wing structure is assumed as an elastic Euler–Bernoulli beam at the leading edge with three linear torsional modes. In this novel integrated bond graph model, computation of the performance indices including the average lift and thrust, consumed and produced powers by flapping and mechanical efficiency are presented. Due to existence of the numerous geometric and kinematic parameters in articulated flexible flapping wing, such a model is essential for design and optimization. Consequently, an example of a typical parametric study and the results validation are carried out. It is indicated that the sensitivity of the bird performance to relative change in design variables would increase for out of phase flapping, second part stiffness, flapping amplitude, frequency and velocity respectively. It is interesting that by employing the reverse-phase flapping which is possible only via articulated wings, the maximum efficiency could be achieved. In addition, it is shown that adjusting the wing torsional stiffness is a crucial item in design of passive flapping robots. The key advantage of the two-section flapping wing is depicted as the controlling capability of the angle of attack in the outer part of the wing. Finally, the improved version of the bird is being addressed by approximately 15% progress in propulsive efficiency.

Automatic Strain Gauge Balance Design Optimization Approach and Implementation Based on Integration of Software

Abstract The traditional wind tunnel strain balance design cycle is a manual iterative process. With the experience and intuition of the designer, one solution that meets the design requirements can be selected among a small number of design solutions. This paper introduces a novel software integration-based automatic balance design optimization system (ABDOS) and its implementation by integrating professional design knowledge and experience, stepwise optimization strategy, CAD-CAE software, self-developed scripts and tools. The proposed two-step optimization strategy includes the analytical design process (ADP) and the finite element method design process (FEDP). The built-in optimization algorithm drives the design variables change and searches for the optimal structure combination meeting the design objectives. The client-server based network architecture enables local lightweight design input, task management, and result output. The high-performance server combines all design resources to perform all the solution calculations. The development of more than 10 balances that have been completed and a case study show that this method and platform significantly reduce the time for design evaluation and design-analysis-redesign cycles, assisting designers to comprehensively evaluate and improve the performance of the balance.

ANALISIS ANTESEDEN YANG MEMPENGARUHI NIAT BELI ON-LINE PADA TOKOPEDIA.COM

This research was conducted to examine the antecedents that affect online purchase intentions. The sample used in this study amounted to 71 respondents. The sampling method using purposive sampling. Data analysis method used is quantitative analysis using validity and reliability tests, F tests, coefficient of determination, t tests and multiple regression analysis. By using the multiple regression method it can be concluded that the web design variable does not have a positive and significant effect on online purchase intention with a significance value (P Value) of 0.324> 0.05. While reliability has a positive and significant effect on online purchase intentions with a significance value (P Value) of 0.018 <0.05. responsiveness has a positive and significant effect on online purchase intentions with a significance value (PValue) of 0.061> 0.05. The guarantee has a positive and significant effect on online purchase intention with a significance value (P Value) of 0.815> 0.05. For ordering a positive and significant effect on online purchase intentions with a significance value (P Value) of 0, 002 <0.05. Simultaneously web design, reliability, responsiveness, guarantee, and ordering have a significant effect on online purchase intention with an F count of 5.960 with a significance value (P Value) of 0.000 <0.05. The resulting determination coefficient is 0.246, which means that 24.6 percent of changes in the online purchase intention variable are explained by changes in web design variables, reliability, responsiveness, guarantees, and bookings together, while the remaining 76.4 percent is explained by other variables which is not included in this study.

Predicting Scattering From Complex Nano-Structures via Deep Learning

Existing numerical electromagnetic (EM) solvers are usually computationally expensive, time consuming, and memory demanding. Recent advances in deep learning (DL) techniques have demonstrated superior efficiency and provide an alternative pathway for speeding up simulations by serving as effective computational tools. In this paper, we propose a DL framework for real-time predictions of the scattering from an isolated nano-structure in the near-field regime. We find that, to achieve precise approximation of the optical response obtained from numerical simulations, the proposed DL framework only requires a small training data set. The fully trained framework can be three orders of magnitude faster than a conventional EM solver based on the finite difference frequency domain method (FDFD). Furthermore, the proposed DL framework has demonstrated robustness to changes in design variables which govern the nano-structure geometry and material selection as well as properties of the incident wave, shedding light on universal scattering predictions at the nano scale via deep learning techniques. This framework increases the viability of the design and analysis of complex nanostructures, offering great potential for applications pertaining to complex light-matter interaction between electromagnetic fields and nanomaterials.

Nonlinear modeling, dynamics, and chaos in a large deflection model of a rotor–disk–bearing system under geometric eccentricity and mass unbalance

The present article treats the nonlinear dynamic analysis of a lightweight flexible rotor–disk–bearing system with geometric eccentricity and mass unbalance. A large deflection model has been derived to represent a nonlinear flexible rotor–bearing system to study the bifurcation, stability, and route to chaos. This mathematical model includes a bidirectional flexible shaft characterized by nonlinear curvature and gyroscopic effect, geometric eccentricity, a rigid disk crooked with unbalance mass, and nonlinear flexible bearings. A perturbation technique has been used to obtain a set of nonlinear algebraic equations that govern the overall dynamics of the system. The system stability has been studied by investigating the bifurcation and route to chaos upon changing the design parameters such as geometric eccentricity, mass unbalance, and disk parameters under the resonance conditions. The present system exhibits a complex behavior traveling with periodic, quasi-periodic, period doubling and chaotic behavior on a gradual change in design variables. The system loses its stability due to S–N bifurcation, which leads to a sudden jump in the response amplitude. These complex behaviors have been studied in detail with the illustration of time history, phase trajectories, bifurcation diagrams, and Poincare’s map for each category. Qualitative assessment of bifurcation diagrams has been studied to explore the boundaries of the stable and unstable behaviors and essential dynamics of the systems. Special attention to predict its rich dynamics to highlight the route to chaos as a future diagnostic tool has been explored. The presented results offer significant understanding of the dynamic performances and its critical operating conditions of a rotor system subjected to geometric eccentricity and mass imbalance.

독립회전 방식 철도차량의 설계변수 변화에 대한 주행특성 해석

독립회전 방식 철도차량의 설계변수 변화에 대한 주행특성 해석

Coarse- and Fine-Mesh Space Mapping for EM Optimization Incorporating Mesh Deformation

Space mapping (SM) is a recognized method for speeding up electromagnetic (EM) optimization. The SM technique often requires an equivalent circuit as the coarse model. In practical cases, equivalent circuit coarse models are not always available. This letter addresses this situation and proposes a new coarse- and fine-mesh SM technique for EM optimization incorporating mesh deformation. By incorporating mesh deformation into coarse-mesh EM optimization, the coarse-mesh EM responses change continuously as the values of the geometrical design variables change. The incorporation of mesh deformation also improves the consistency between the coarse-mesh EM sensitivities and the changes in the coarse-mesh EM responses. This results in the speedup of the coarse-mesh EM optimization and potentially less SM iterations, therefore accelerating the overall SM optimization. This technique is illustrated by two microwave examples.

Integrated optimal design and scheduling for a bitumen upgrader facility

Partial upgrading of bitumen is advantageous yet energy intensive in itself, needing various resources such as electricity, heat, hydrogen, and steam. Therefore, partially upgrading the bitumen while minimizing energy usage and thus lowering the carbon footprint is desirable. Consequently, optimal design and operation of an upgrader then becomes a challenging two-pronged problem. The key, however, lies in identifying that the design and operation problems are not mutually exclusive, but instead, synergistic, and hence require simultaneous consideration. Consequently, this research highlights the importance of the real-time integrated design and scheduling problem through two formulations; maximizing profit and minimizing energy usage. The results indicate changes in design and scheduling decision variables as per the medium-term forecasts of the volatile commodity and energy pricing markets. Therefore, a design independent of the scheduling constraints or a schedule based on a fixed design may lead to suboptimal results in the design and/or schedule decision space(s).

Adaptive Feature Zero Assisted Surrogate-Based EM Optimization for Microwave Filter Design

Feature-based electromagnetic (EM) optimization techniques can help avoid local minima in microwave design. Zeros of the transfer functions are recently used to help extract the features when the features of filter responses are not explicitly identifiable. This letter proposes a feature zero-adaptation approach to enlarge the surrogate range by overcoming the problem of varying orders of the transfer function w.r.t. the changes in design variables. In this way, the proposed technique allows larger step sizes for optimization, therefore, speeding up the overall EM optimization process. During each optimization iteration, parallel techniques are proposed to be used to generate multiple EM geometrical samples simultaneously for creating the feature-based surrogate model. The proposed technique is demonstrated using two microwave filter examples.

Response sensitivity analysis of laminated composite shells based on higher-order shear deformation theory

Laminated composite shells are widely used as structural components in important aerospace, marine, automobile engineering structures. Thus, appropriate evaluation of sensitivities of responses like deflection, frequency, buckling etc. due to changes in design variables is of great importance for efficient and safe design of such structures. The present paper deals with a comprehensive sensitivity analysis of laminated composite shells using $${C}^{0 }$$ finite element with more accurate theoretical model based on higher-order shear deformation theory (HSDT). The sensitivity analysis of deflection and natural frequency with respect to important design parameters such as material parameters, angle of fiber orientation, radius of curvature, density of materials and external load is presented. Furthermore, sensitivity-based importance factor for each parameter is obtained so that the most important parameters affecting the shell responses can be readily identified. The response sensitivities obtained by the proposed formulation are compared with those obtained by the finite difference procedure. An extensive parametric study has been carried out considering different variables to understand the performance of laminated shell.

A Study of Multi-Objective Aerodynamic Optimization Design for Variable Camber Airfoils and High Lift Devices

Aiming at the synthetical optimization of the aerodynamic performance between the low-speed condition of two-dimensional high lift devices during take-off and landing phase and the high-speed condition of variable camber airfoil during cruise phase, an aerodynamic optimization design method for high lift device based on Kriging based surrogate model and multi-objective genetic algorithm has been developed. With the application of Adaptive Dropped Hinge Flap mechanism, the low-speed take-off and landing performance and high-speed cruise performance of the aircraft is improved by coupling deflection of the flap and spoiler. The position of flap hinge, deflection angle of spoiler and deflection angle of flap are taken as design variables; The Navier-Stokes equations are used to predict the aerodynamic forces of initial samples; The Kriging based surrogate model is employed to establish the algebraic relation between design variables and aerodynamic forces at take off, landing and cruise, obtaining four efficient prediction models for aerodynamic forces; Multi-objective optimization design with multi-objective genetic algorithm is conducted on the basis of surrogate models. The automatic generation of computational grid is achieved by the mesh deformation method based on RBF (Radial Basis Function) when the design variables change. On the basis of efficient global multi-objective optimization design platform, the synthetical optimization of high-speed and low-speed aerodynamic performance is conducted; The multi-objective solution set of the Pareto frontier is verified and analyzed, and the optimal solution with well matched high and low speed performance is selected.

Reanalysis of Modified Structures by Adding or Removing Substructures

This study considers structural reanalysis owing to the modification of structural elements including (1) addition of substructures, (2) removal of substructures, and (3) changes in design variables. Coupling and decoupling reanalysis methods proposed in the study are performed by using the concept of compatibility conditions at interface nodes between the substructures or between the original structure and the substructures. Subsequently, a generalized inverse method to describe constrained responses is modified to obtain the reanalysis responses. In this study, constrained equilibrium equations are modified to consider a reanalysis of a structure with the addition and removal of statically stable or unstable substructures. The proposed reanalysis method is examined by using five examples of handling coupling and decoupling reanalysis of a truss structure.