Variation Of Design Variables Research Articles

Multi-objective optimization of concentrated solar power plants from an energy-water-environment nexus perspective under distinct climatic conditions – Part B: Environ-economic analysis

The objective of this study is to include environmental impact in optimization of concentrated solar power plants previously limited to techno-economic analysis only. Performance of solar towers and parabolic trough collectors equipped with dry and wet cooling is numerically investigated at 10 min interval for three climatic zones. Based on electricity generation profiles pertinent to variation of design variables of solar multiple and thermal energy storage, the water usage is quantified techno-economically, considering water scarcity levels. Besides, five different potential impacts over lifecycle of concentrated solar and natural gas-based power plants are compared after unifying them into metric of net environmental impact avoided. Additionally, utilizing techno-economic solutions and eco-friendly solutions, multi-objective ‘balanced’ solution is proposed. It is found that levelized cost of water increases five-fold for areas with extreme water scarcity and is higher for trough than solar tower. Net environmental impact of troughs is higher and lower electricity generation causes the avoided impact to be higher than solar towers, when compared with natural gas-fired power plants. For eco-friendly solutions, solar multiple varies from 3.5 to 4 with thermal energy storage of 24 h. Dry-cooled solar towers with optimal solar multiple in range of 3–3.2 and thermal energy storage of 18.8–19.9 h are evaluated for pareto-optimality based ‘balanced’ solutions for all zones. These solutions offer minimum net levelized cost of electricity, alongside maximized electricity generation, huge return on invested capital and energy, and reducing environmental impact by over 94%. Lastly, semi-arid climates are found suitable for concentrated solar power plant installation.

Robust design of ball bearings for an improved performance using genetic algorithm

The design of rolling bearings must be optimized to get an improved fatigue life. As the fatigue life is directly affected by the dynamic capacity, therefore the later is considered as an objective function, which is to be maximized using a robust design optimization. Such design procedures enhance the qualities and reliability of products by ensuring that they are insensitive to the source of variabilities or uncertainties present in them, without eliminating these sources and at the same time maintaining the design feasibility with probabilistic constraints. In the present work, deep groove ball bearings (DGBBs) are designed in such a way that it will have minimum variation in the objective function due to the variation in design variables. A nonlinear constrained optimization problem is formulated with one objective function, ten design variables and a set of total thirty-five constraints. The real-coded genetic algorithm (GA) is used as the optimization tool. The result obtained shows the optimized bearings have improved fatigue life. A convergence study is performed to ensure global optima in the design space and further a sensitivity analysis is performed. The analysis shows that the dynamic capacity is the most sensitive to the variation in the inner groove curvature radius and least sensitive to the bearing pitch diameter. This paper allows the designers to design the rolling bearings by optimizing the fatigue life along with the minimization of their variations, which are due to variations or having tolerances in input design variables during its manufacturing. Moreover, the proposed design methodology is not limited to the bearings only, but can also be enforced in the design of any machine components (like clutches, gears, cams, levers, springs, etc.) having substantial uncertainties in their geometry or material, such as the residual strain, modulus, thickness, density, etc.

Optimal two-stage parachute and retro motor sizing for launch vehicle stage recovery

A deceleration system consisting of staged parachute clusters and retro thrusters is optimized for the recovery of the first stage of a launch vehicle on sea. Optimal mass as well as reduction in speed by each parachute cluster and the retro thrusters is essential to minimize the inherent payload loss due to inclusion of additional systems. Three disciplines are involved in the study, namely parachute design, grain design and Three Degrees of Freedom (3-DOF) trajectory simulations. Parachute components are sized and their masses are estimated using a parachute design code. It computes the number of parachutes in the cluster, their sizes and opening loads for multiple reefing stages. Solid motor grain design is carried out, using high burn rate propellant, to provide high thrust to decelerate the launch vehicle stage to a near-zero descent rate at touchdown. A Multiobjective Multidisciplinary Design Optimization ( $$\text{M}^{2}$$ DO) problem has been formulated to minimize the mass of the deceleration system and minimize the touchdown speed of the recovered stage, subject to constraints on Maximum Expected Operating Pressure (MEOP), feasibility, etc. The optimization is carried out and the Pareto optimal front is obtained using an in-house multi-objective optimization algorithm, Attractor Anchored Multi-objective Evolutionary Algorithm (A $$^2$$ -MOEA). A total of twenty-five design variables are considered including initial conditions for each deceleration stage, size of parachute cluster components for both drogue and main parachutes, and the size and shape of the solid motor grain for retro rockets. It is seen that the two objectives are conflicting. The Pareto optimal designs are discussed and the variation of design variables is presented.

A Novel Elliptical Ring Microstrip Patch Antenna for Ultra-Wideband Applications

This paper proposes a new ultra-wideband (UWB) antenna. The proposed antenna is designed for operation from 3 to 15 GHz. It consists of a Sierpinski fractal based ellipse etched onto the radiating patch and a rectangular defected ground structure in the ground plane. Details of the proposed antenna as well as with variations in design variables are presented and the results discussed.

Whirl Flutter Investigation of Hingeless Proprotors

Hingeless proprotor whirl flutter in cruise flight is investigated using comprehensive rotorcraft analysis codes CAMRAD II and RCAS. Generic hingeless proprotor designs include conventional soft-in-plane and stiff-in-plane rotors operating at cruise tip speeds typical of existing tiltrotor systems and a rotor that exhibits higher frequencies and operates at much lower cruise tip speed than existing rotor designs. The effects of the blade elasticity, wing/pylon model, density, speed of sound, unsteady aerodynamics, and realistic airfoil tables on whirl flutter speed are examined. CAMRAD II and RCAS show consistently excellent agreement with each other for wide variations of design variables and operating conditions.

Truncated hierarchical B-spline–based topology optimization

This work presents a truncated hierarchical B-spline–based topology optimization (THB-TO) to address topology optimization (TO) for both minimum compliance and compliant mechanism. The sensitivity and density filters with a lower bound are adaptively consistent with the hierarchical levels of active elements to remove the checkboard pattern and reduce the gray transition area. By means of the maximum variation of design variables on two consecutive iterative steps and the density differences of adjacent active elements, a mark strategy is established, which triggers the hierarchical local refinement and identifies the elements to be refined during the course of THB-TO. Besides, a locally refined design space is constructed in terms of the parent–child relationship of the cells on consecutive hierarchical levels. Numerical examples are used to verify the effectiveness of the proposed THB-TO, where the resolution around the boundary of the optimized designs can be effectively improved by THB-TO. Compared with global refinement, the number of degree of freedoms (DOFs) and design variables are largely decreased for 2D and 3D cases by THB-TO, which demonstrates that the proposed THB-TO is a promising approach to solving 2D and 3D TO problems.

Robust Optimization of Planar Constrained Mechanical System with Varying Joint Clearance Size Based on Sensitivity Analysis

This paper is devoted to a general methodological study on sensitivity analysis and robust optimization for a planar crank-slider mechanism in presence of joint clearances and random parameters and investigate the effects of parameter uncertainty on optimization results when joint clearance sizes are constantly changing due to wear. The first-order sensitivity analysis based on the response surface proxy model is performed. Then, a multiobjective robust optimization algorithm based on sensitivity analysis is carried out to reduce the undesirable effects of joint clearances and random parameters. In the algorithm, a multiobjective robust optimization model derived from the mean and variance of the objective function is constructed. Here, the objective function is defined based on the consideration of reducing the contact force generated at all clearance joints. Additionally, in order to balance computational accuracy and efficiency in the multiobjective robust optimization process, high-precision Kriging agent models are established. The optimum values of design variables are determined by combining Monte Carlo sampling and multiobjective particle swarm optimization method. By combining the Baumgarte approach with Lankarani–Nikravesh contact force model and Coulomb friction model, the dynamic equations of the planar multibody system with clearance joints are established. The uniform probability distribution is applied for characterizing random parameters. Simulation results show that the influence of design variable variations on the objective function changes in relation to the joint clearance size, but their relative influence degree on the objective function will not vary with the size of joint clearances. Moreover, the optimal solution selected on the Pareto front will affect the average levels and peak fluctuations of the dynamic responses in multibody systems.

Solution to the topology optimization problem using a time‐evolution equation

SummaryThis article describes a numerical solution to the topology optimization problem using a time‐evolution equation. The design variables of the topology optimization problem are defined as a mathematical scalar function in a given design domain. The scalar function is projected to the normalized density function. The adjoint variable method is used to determine the gradient defined as the ratio of the variation of the objective function or constraint function to the variation of the design variable. The variation of design variables is obtained using the solution of the time‐evolution equation in which the source term and Neumann boundary condition are given as a negative gradient. The distribution of design variables yielding an optimal solution is obtained by time integration of the solution of the time‐evolution equation. By solving the topology optimization problem using the proposed method, it is shown that the objective function decreases when the constraints are satisfied. Furthermore, we apply the proposed method to the thermal resistance minimization problem under the total volume constraint and the mean compliance minimization problem under the total volume constraint.

Robust Design Optimization and Improvement by Metamodel

The robust design optimization (RDO) is an effective method to improve product performance with uncertainty factors. The robust optimal solution should be not only satisfied the probabilistic constraints but also less sensitive to the variation of design variables. There are some important issues in RDO, such as how to judge robustness, deal with multi-objective problem and black-box situation. In this paper, two criteria are proposed to judge the deterministic optimal solution whether satisfies robustness requirment. The robustness measure based on maximum entropy is proposed. Weighted sum method is improved to deal with the objective function, and the basic framework of metamodel assisted robust optimization is also provided for improving the efficiency. Finally, several engineering examples are used to verify the advantages.

Sensitivity analysis of free torsional vibration frequencies of thin-walled laminated beams under axial load

The paper addresses sensitivity analysis of free torsional vibration frequencies of thin-walled beams of bisymmetric open cross section made of unidirectional fibre-reinforced laminate. The warping effect and the axial end load are taken into account. The consideration is based upon the classical theory of thin-walled beams of non-deformable cross section. The first-order sensitivity variation of the frequencies is derived with respect to the design variable variations. The beam cross-sectional dimensions and the material properties are assumed the design variables undergoing variations. The paper includes a numerical example related to simply supported I-beams and the distributions of sensitivity functions of frequencies along the beam axis. Accuracy is discussed of the first-order sensitivity analysis in the assessment of frequency changes due to the fibre volume fraction variable variations, and the effect of axial loads is discussed too.

Design for service life of underground space based on water seepage criterion

Ever increased urbanisation in the world has made the underground space a viable alternative to the expanding city space. Underground space usually operates under the water level whereby the water ingress is one of the most detrimental factors affecting its service life and sustainability. But little or no research has been conducted on design for service life of underground space based on the criterion of water seepage. This paper proposes a rational and practical methodology for design of service life of underground space as represented by its lining structures against water seepage. A stochastic model of water seepage depth in concrete lining is developed. The proposed methodology is verified with numerical method for prediction of the probability of failure due to water seepage. The merit of the proposed methodology is that it allows for the randomness and time variation of design variables and also directly relates to the real time in service of underground space. It is found in the paper that the correlation of water seepage depth between two points in time and the concrete constituent materials can significantly affect the probability of water seepage failure. The significance of the proposed methodology is that it can be used as a design guide for service life of underground space based on various design criteria.

Kinematic Design Optimization of an Eight Degree-of-Freedom Upper-Limb Exoskeleton

SummaryThis paper studies the problem of optimizing the kinematic structure of an eight degree-of-freedom upper-limb rehabilitation exoskeleton. The objective of optimization is achieving minimum volume and maximum dexterity in the workspace of daily activities specified by a set of upper-arm configurations. To formulate the problem, a new index is proposed for effective characterization of kinematic dexterity for wearable robots. Additionally, a set of constraints are defined to ensure that the optimal design can cover the desired workspace of the exoskeleton, while singular configurations and physical interferences are avoided. The formulated multi-objective optimization problem is solved using an evolutionary algorithm (Non-dominated Sorting Genetic Algorithm II) and the weighted sum approach. Among the resulted optimal points, the point with least sensitivity with respect to the variations of design variables is chosen as the final design.

A new multidisciplinary robust design optimization framework for an autonomous underwater vehicle in system and tactic design

The design process of an autonomous underwater vehicle requires mathematical model of subsystems or disciplines such as guidance and control, payload, hydrodynamic, propulsion, structure, trajectory and performance and their interactions. In early phases of design, an autonomous underwater vehicle is often encountered with a high degree of uncertainty in the design variables and parameters of system. These uncertainties present challenges to the design process and have a direct effect on the autonomous underwater vehicle performance. Multidisciplinary design optimization is an approach to find both optimum and feasible design, and robust design is an approach to make the system performance insensitive to variations of design variables and parameters. It is significant to integrate the robust design and the multidisciplinary design optimization for designing complex engineering systems in optimal, feasible and robust senses. In this article, we present an improved multidisciplinary design optimization methodology for conceptual design of an autonomous underwater vehicle in both engineering and tactic aspects under uncertainty. In this methodology, uncertain multidisciplinary feasible is introduced as uncertain multidisciplinary design optimization framework. The results of this research illustrate that the new proposed robust multidisciplinary design optimization framework can carefully set a robust design for an autonomous underwater vehicle with coupled uncertain disciplines.

Dynamics analysis in the design of turbomachinery using sensitivity coefficients

Solving the optimization problems based on numerical models is an important step in the design of machinery and equipment. Special attention is given to the calculation gradient of the target and limitation functions behavior with the variation of design variables (known as sensitivity). Using the sensitivity function and varying the design variables the designer gets the opportunity to analyze various basic design variants quickly and efficiently without timeconsuming calculations for each of them. This allows speeding up greatly the design process and reducing its time input. In this regard the numerical models development using algorithms of sensitivity calculation for the strength and vibration analysis of structures is an urgent task.

Topological design of structures under dynamic periodic loads

Most of forces acted on real structures are dynamic and topology optimization of dynamic structures has aroused wide attention over the past years. Due to the complexity of dynamic behavior, achieving clear 0/1 optimal topology of dynamic structures is still challenging. This paper aims to develop a topology optimization algorithm of dynamic structures under periodic loads based on the bi-directional evolutionary structural optimization (BESO) method. To minimize the dynamic compliance under the single or multiple excitation frequencies, four typical topology optimization problems are proposed for different scenarios. To solve the defined topology optimization problems, sensitivity analysis with regard to the variation of design variables is conducted for iteratively updating the structural topology. Since BESO uses discrete design variables, the resulting solid-void solutions show unambiguous topologies of dynamic structures. Various 2D and 3D numerical examples are given to demonstrate the capability of the proposed method for obtaining optimal designs of dynamic structures under periodic loads.

Influence of Envelope Design in the Optimization of the Operational Energy Costs of a Multi-family Building

The international efforts for improving energy efficiency in buildings and reducing their environmental impact also constitute a challenge for working against the risk of energy poverty. The work aims to test a methodology for optimizing the operational costs of the different flats of a multi-family building for social housing. The method combines the use of TRNSYS building energy simulation program with GenOpt Generic Optimization program in a so-called simulation-based optimization method.A typical floor of a real case study building was modeled and the energy costs for heating and cooling due to the variation of design variables related to the building envelope was studied. The optimization led to reduce the total operational costs of the flats by the range 17%-23%. The different share of heating, cooling, ventilation and DHW in the total operational costs was studied and resulted differences in energy rating and costs between flats were analyzed.

A generalized heat-transfer model for shielded-fire household cookstoves

This paper presents an experimentally validated steady-state heat transfer model of a shielded-fire, natural-draft biomass cookstove suitable for conceptual design of the small household cookstoves used in developing countries. The input variables for the model included 10 geometrical design variables, 2 material design variables, and 3 operating conditions. This model was validated using data from three previously published studies including 63 distinct combinations of the 15 design variables. The model results for thermal efficiency are within ±5% for 59 of the 63 designs and have an L2 norm error of 3.0%. Parametric variations of design variables can assist in the conceptual phase of design. In addition, the temperature and velocity profiles, location and magnitude of losses, and heat transfer contributions through various modes and regions of the pot provide sufficient detail to improve the understanding of a cookstove system and support detailed design.

Concurrent topology optimization of macrostructures and material microstructures for natural frequency

Based on the bi-direction evolutionary structural optimization (BESO) method, a concurrent two-scale topology optimization algorithm is proposed for maximizing natural frequency of structures. The macro-scale structure is assumed to be constructed with a composite material, whose microstructure is represented by periodic unit cells (PUC). This optimization scheme aims to obtain the optimal topologies of the structure at the macro-scale level and microstructure of its material at the micro scale simultaneously, so that the resulting structure with a given weight has maximum natural frequency. The effective properties of a composite material with representative PUC are homogenized and integrated into the frequency analysis of the macrostructure. To implement topology optimization at both scales, the design variables are assigned for both the macrostructure and microstructure of its material. The sensitivity analysis with regard to the variation of design variables is conducted for iteratively updating the topologies at both scales synchronously. Numerical 2D and 3D examples are presented to demonstrate the validity of the proposed concurrent optimization algorithm for frequency optimization problems.

An enhanced fraction polynomial microwave filter modeling method exploiting space mapping

ABSTRACTA method for bandpass filter modeling taking advantage of the space mapping (SM) is presented in this letter. The coarse model is constructed by the fraction polynomial approximating the data from high‐fidelity simulations, and the approach of obtaining the coefficients is specifically designed to avoid rapidly increasing complexity as the data adds. The surrogate model, which the accuracy is further enhanced, is established utilizing SM. In this work, the SM process allows a flexible tradeoff between accuracy and computational cost. The proposed model can be operated with a relatively wide variation of design variables and is practical for arbitrary bandwidth filter. Couple line filters and an ultrawideband (UWB) radial‐stub‐loaded filter are modeled using the proposed modeling method to validate its merits and the result shows a good performance. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:1159–1163, 2016

Parametric analysis of space nuclear power plants in thermodynamic design variables

The purpose of the study is to analyze the influence of efficiency factor and medium-entropy temperatures on the specific mass of a space power plant and the specific area of the radiator cooler with regard for heat losses and mass coefficients of subsystems. Functions of the specific performance sensitivity to variations of design variables are used as the parametric analysis tool. It has been shown that sensitivity functions represent criteria relations that define the optimality and similarity range for space nuclear power plants (SNPP) of different types. To specify the permissible intervals for the variation of design variables, a form has been proposed for recording the specific characteristics with explicit interrelationships between target functions and design variables. The obtained results demonstrate a single-extremum dependence of the considered specific characteristics on generalized design variables. This makes it reasonable to define the optimization problem based on the said criteria of the SNPP technical level.