scholarly journals Analysis of Composite Structures in Curing Process for Shape Deformations and Shear Stress: Basis for Advanced Optimization

2021 ◽  
Vol 5 (2) ◽  
pp. 63
Author(s):  
Niraj Kumbhare ◽  
Reza Moheimani ◽  
Hamid Dalir
Keyword(s):  
Composite Structures ◽  
Latin Hypercube Sampling ◽  
Vital Role ◽  
Optimization Techniques ◽  
Design Parameters ◽  
Curing Process ◽  
Input Variables ◽  
Transient Thermal ◽  
Prototype Design ◽  
Shape Deformations

Identifying residual stresses and the distortions in composite structures during the curing process plays a vital role in coming up with necessary compensations in the dimensions of mold or prototypes and having precise and optimized parts for the manufacturing and assembly of composite structures. This paper presents an investigation into process-induced shape deformations in composite parts and structures, as well as a comparison of the analysis results to finalize design parameters with a minimum of deformation. A Latin hypercube sampling (LHS) method was used to generate the required random points of the input variables. These variables were then executed with the Ansys Composite Cure Simulation (ACCS) tool, which is an advanced tool used to find stress and distortion values using a three-step analysis, including Ansys Composite PrepPost, transient thermal analysis, and static structural analysis. The deformation results were further utilized to find an optimum design to manufacture a complex composite structure with the compensated dimensions. The simulation results of the ACCS tool are expected to be used by common optimization techniques to finalize a prototype design so that it can reduce common manufacturing errors like warpage, spring-in, and distortion.

scholarly journals Sensitivity analysis of timber-concrete composite structures

2018 ◽  
Vol 16 (1) ◽  
pp. 125-134
Author(s):  
Nikola Velimirovic ◽  
Dragoslav Stojic
Keyword(s):  
Sensitivity Analysis ◽  
Composite Structures ◽  
Rank Order ◽  
Equivalent Stress ◽  
Latin Hypercube Sampling ◽  
Simulation Method ◽  
Design Parameters ◽  
Model Parameters ◽  
Design And Optimization ◽  
Stochastic Sensitivity Analysis

The sensitivity analysis could be defined as a study of how the variability of the output parameter of the considered model can be distributed to its sources, actually, on the variability of the various input model parameters. It helps to identify the most important design parameters of a particular structure and to focus on them during the design and optimization process. This paper is focused on the application of stochastic sensitivity analysis of maximum equivalent stress and maximum mid-span deflection of timber-concrete composite beam. All input parameters were considered to be random variables. Latin Hypercube Sampling numerical simulation method was employed. The estimation of the sensitivity was derived from Spearman rank-order correlation coefficient.

Optimization in Polymer Composite Piping Design

2013 ◽  
Author(s):  
Pierre Mertiny ◽  
Horst Baier
Keyword(s):  
Polymer Composite ◽  
Polymer Matrix ◽  
Composite Structures ◽  
Mechanical Performance ◽  
Fiber Reinforcement ◽  
Optimization Techniques ◽  
Design Parameters ◽  
Fiber Architecture ◽  
Corrosion Properties ◽  
Additional Function

Polymer composite piping that is composed of a fiber reinforcement phase embedded in a continuous polymer matrix is associated with high specific strength and excellent corrosion properties. The fiber reinforcement is often considered to dominate the mechanical performance of composite structures. Consequently, principal design parameters for composite piping are usually associated with the fiber architecture, which in many practical applications has been limited to simple angle-ply configurations. Nevertheless, the function of the polymer phase is not limited to merely providing rigidity to the otherwise pliable fiber architecture. In fact, the often quoted high strength of composites is sustained by a load-sharing mechanism that the matrix enables between filaments. In this manner, the effect of localized flaws and filament damage is mitigated, and only the accumulation of numerous micro damage events leads to component failure. An additional function of the polymer matrix is to prevent ingress of fluid into the composite and possible leakage in pressure-bearing components. The design of composite piping therefore needs to consider a matrix-sensitive damage criterion. In view of variable loading conditions and multi-angle fiber architectures this study investigates design optimization techniques intended to yield better performance in terms of strength and especially fluid permeation resistance.

scholarly journals Research on the Manufacturing Quality of Co-Cured Hat-Stiffened Composite Structure

Materials ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 2747
Author(s):  
Xiangwen Ju ◽  
Jun Xiao ◽  
Dongli Wang ◽  
Cong Zhao ◽  
Xianfeng Wang
Keyword(s):  
Composite Structures ◽  
Sound Pressure ◽  
Integration Method ◽  
Complex Geometry ◽  
Sound Field ◽  
Thickness Measurement ◽  
Curing Process ◽  
The Finite Element Method ◽  
Manufacturing Quality

The stringer-stiffened structure is widely used due to its excellent mechanical properties. Improving the manufacturing quality of stringer-stiffened structure which have complex geometry is important to ensure the bearing capacity of aviation components. Herein, composite hat-stiffened composite structures were manufactured by different filling forms and bladders with various properties, the deformation of silicone rubber bladder in co-curing process was studied by using the finite element method. The thickness measurement at different positions of the hat-stiffened structure was performed to determine the best filling form and bladder property. Moreover, in view of the detection difficulties in R-zone of stringer, numerical simulation was performed to get the sound pressure and impulse response of at the R-zone of stringer by Rayleigh integration method, and an effective equipment which could stably detect the manufacturing quality of R-zone was designed to verify the correctness of sound field simulation and realize the detection of stringer. With the optimum filling form and bladder properties, hat-stiffened composites can be manufactured integrally with improved surface quality and geometric accuracy, based on co-curing process.

scholarly journals Comparison of Factorial and Latin Hypercube Sampling Designs for Meta-Models of Building Heating and Cooling Loads

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 512
Author(s):  
Younhee Choi ◽  
Doosam Song ◽  
Sungmin Yoon ◽  
Junemo Koo
Keyword(s):  
Latin Hypercube Sampling ◽  
Building Design ◽  
Gain Coefficient ◽  
Design Parameters ◽  
Latin Hypercube ◽  
Heating And Cooling ◽  
Factor Design ◽  
Heating Loads ◽  
Cooling Loads ◽  
Interest In Research

Interest in research analyzing and predicting energy loads and consumption in the early stages of building design using meta-models has constantly increased in recent years. Generally, it requires many simulated or measured results to build meta-models, which significantly affects their accuracy. In this study, Latin Hypercube Sampling (LHS) is proposed as an alternative to Fractional Factor Design (FFD), since it can improve the accuracy while including the nonlinear effect of design parameters with a smaller size of data. Building energy loads of an office floor with ten design parameters were selected as the meta-models’ objectives, and were developed using the two sampling methods. The accuracy of predicting the heating/cooling loads of the meta-models for alternative floor designs was compared. For the considered ranges of design parameters, window insulation (WDI) and Solar Heat Gain Coefficient (SHGC) were found to have nonlinear characteristics on cooling and heating loads. LHS showed better prediction accuracy compared to FFD, since LHS considers the nonlinear impacts for a given number of treatments. It is always a good idea to use LHS over FFD for a given number of treatments, since the existence of nonlinearity in the relation is not pre-existing information.

A Systematic Function Recommendation Process for Data-Driven Product and Service Design

2017 ◽  
Vol 139 (11) ◽  
Author(s):  
Zhinan Zhang ◽  
Ling Liu ◽  
Wei Wei ◽  
Fei Tao ◽  
Tianmeng Li ◽  
...  
Keyword(s):  
Subjective Experience ◽  
Vital Role ◽  
Data Driven ◽  
Design Parameters ◽  
Sound Design ◽  
New Paradigm ◽  
Senior Managers ◽  
Product Service ◽  
Target User

This paper presents a systematic function recommendation process (FRP) to recommend new functions to an existing product and service. Function plays a vital role in mapping user needs to design parameters (DPs) under constraints. It is imperative for manufacturers to continuously equip an existing product/service with exciting new functions. Traditionally, functions are mostly formulated by experienced designers and senior managers based on their subjective experience, knowledge, creativity, and even heuristics. Nevertheless, against the sweeping trend of information explosion, it is increasingly inefficient and unproductive for designers to manually formulate functions. In e-commerce, recommendation systems (RS) are ubiquitously used to recommend new products to users. In this study, the practically viable recommendation approaches are integrated with the theoretically sound design methodologies to serve a new paradigm of recommending new functions to an existing product/service. The aim is to address the problem of how to estimate an unknown rating that a target user would give to a candidate function that is not carried by the target product/service yet. A systematic function → product recommendation process is prescribed, followed by a detailed case study. It is indicated that practically meaningful functional recommendations (FRs) can indeed by generated through the proposed FRP.

scholarly journals Multi-Objective Optimization of Switched Reluctance Machine Design Using Jaya Algorithm (MO-Jaya)

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1107
Author(s):  
Mohamed Afifi ◽  
Hegazy Rezk ◽  
Mohamed Ibrahim ◽  
Mohamed El-Nemr
Keyword(s):  
Optimization Techniques ◽  
Design Parameters ◽  
Jaya Algorithm ◽  
Switched Reluctance Machine ◽  
Nsga Ii ◽  
Switched Reluctance ◽  
Multi Objective ◽  
Reluctance Machine ◽  
Linear Relationships ◽  
Forward Equations

The switched reluctance machine (SRM) design is different from the design of most of other machines. SRM has many design parameters that have non-linear relationships with the performance indices (i.e., average torque, efficiency, and so forth). Hence, it is difficult to design SRM using straight forward equations with iterative methods, which is common for other machines. Optimization techniques are used to overcome this challenge by searching for the best variables values within the search area. In this paper, the optimization of SRM design is achieved using multi-objective Jaya algorithm (MO-Jaya). In the Jaya algorithm, solutions are moved closer to the best solution and away from the worst solution. Hence, a good intensification of the search process is achieved. Moreover, the randomly changed parameters achieve good search diversity. In this paper, it is suggested to also randomly change best and worst solutions. Hence, better diversity is achieved, as indicated from results. The optimization with the MO-Jaya algorithm was made for 8/6 and 6/4 SRM. Objectives used are the average torque, efficiency, and iron weight. The results of MO-Jaya are compared with the results of the non-dominated sorting genetic algorithm (NSGA-II) for the same conditions and constraints. The optimization program is made in Lua programming language and executed by FEMM4.2 software. The results show the success of the approach to achieve better objective values, a broad search, and to introduce a variety of optimal solutions.

COMPLEX METHODOLOGY FOR CALCULATING THE OPTIMAL PARAMETERS OF THE HEAT RECOVERY SYSTEM OF A BOILER PLANT

2017 ◽  
Author(s):  
Nataliia Fialko ◽  
◽  
Alla Stepanova ◽  
Raisa Navrodskaia ◽  
Svetlana Shevchuk ◽  
...  
Keyword(s):  
Heat Recovery ◽  
Optimization Techniques ◽  
Planning Theory ◽  
Design Parameters ◽  
Optimal Parameters ◽  
Multilevel Optimization ◽  
Boiler Plant ◽  
Experimental Planning ◽  
Recovery System ◽  
Heat Recovery System

The results of optimizing the parameters of the heat recovery system of a boiler plant designed to heat return water are presented. The feasibility of using a technique that combines methods of exergy analysis experimental planning theory and multilevel optimization to optimize plant parameters is analyzed. It is emphasized that the efficiency of heat recovery systems optimized using the above technique is 2-3% higher than the efficiency of systems optimized using other optimization techniques. In addition, the specified method allows to take into account a significant part of the technical losses in the heat recovery system and to optimize a large number of parameters. The main stages of a comprehensive methodology are given. At each stage, the above methods are used to develop mathematical models and obtain dependences of exergy efficiency criteria on the parameters of the heat recovery system. The results of calculating the optimum values of operating and design parameters for the considered heat recovery system of the boiler unit are presented.

scholarly journals Variability in Pavement Design

2015 ◽  
Vol 16 (2) ◽  
pp. 50-67 ◽  
Author(s):  
Paola Dalla Valle ◽  
Nick Thom
Keyword(s):  
Pavement Design ◽  
Pavement Performance ◽  
Design Parameters ◽  
Probability Density Distribution ◽  
Analysis And Design ◽  
The Subject ◽  
The Mean ◽  
Subgrade Modulus ◽  
Input Variables ◽  
The Uk

Abstract This paper presents the results of a review on variability of key pavement design input variables (asphalt modulus and thickness, subgrade modulus) and assesses effects on pavement performance (fatigue and deformation life). Variability is described by statistical terms such as mean and standard deviation and by its probability density distribution. The subject of reliability in pavement design has pushed many highway organisations around the world to review their design methodologies, mainly empirical, to move towards mechanistic-empirical analysis and design which provide the tools for the designer to evaluate the effect of variations in materials on pavement performance. This research has reinforced this need for understanding how the variability of design parameters affects the pavement performance. This study has only considered flexible pavements. The sites considered for the analysis, all in the UK (including Northern Ireland), were mainly motorways or major trunk roads. Pavement survey data analysed were for Lane 1, the most heavily trafficked lane. Sections 1km long were considered wherever possible. Statistical characterisation of the variation of layer thickness, asphalt stiffness and subgrade stiffness is addressed. A sensitivity analysis is then carried out to assess which parameter(s) have the greater influence on the pavement life. The research shows that, combining the effect of all the parameters considered, the maximum range of 15th and 85th percentiles (as percentages of the mean) was found to be 64% to 558% for the fatigue life and 94% to 808% for the deformation life.

scholarly journals Optimization Aspects of an Ejector Type Hypersonic Thrust Nozzle

1992 ◽  
Author(s):  
G. Trittler ◽  
E. Eckert ◽  
M. Göing
Keyword(s):  
High Performance ◽  
Exhaust System ◽  
Vital Role ◽  
Calculation Model ◽  
Nozzle Geometry ◽  
Design Parameters ◽  
Axial Thrust ◽  
Thrust Coefficient ◽  
Wide Range ◽  
Low Performance

Hypersonic aircraft projects are highly dependant on efficient propulsion systems. High performance and integration within the airframe play a vital role in the overall concept. Particular attention must be paid to the exhaust system that is submitted to a wide range of operational requirements. An optimization of the nozzle geometry for high flight Mach numbers will lead to a low performance at the transonic flight regime. The additional use of secondary ejector air flow at transonic speeds is one option to improve the thrust behaviour of the nozzle. In the presented paper performance data of single expansion ramp ejector type nozzles are predicted using a calculation model based on a method-of-characteristics algorithm. For optimization purposes the effects of various design parameters on axial thrust coefficient and thrust vector angle are discussed. The geometric parameters investigated are the length of the lower nozzle wall and its deflection angle as well as the ejector slot location and its cross-section.

Vibroacoustic design optimization of curved composite shells

2021 ◽  
Vol 29 (9_suppl) ◽  
pp. S1520-S1531
Author(s):  
Rilwan K Apalowo ◽  
Dimitrios Chronopoulos
Keyword(s):  
Optimal Design ◽  
Structural Design ◽  
Composite Structures ◽  
Sensitivity Analyses ◽  
Computational Time ◽  
Design Parameters ◽  
Sandwich Shell ◽  
Acoustic Transmission ◽  
Composite Shells ◽  
Model Composite

The need to simultaneously optimize the structural design properties, and attain a satisfactory vibroacoustic performance for composite structures, has been a challenging task for modern structural engineers. This work is aimed at developing a statistical energy analysis (SEA) based numerical scheme for computing the optimal design parameters of each individual layer of layered curved shells having arbitrary complexities and layering. The main novelty of the work focuses on the computation of SEA properties for curved composite shells and derive the sensitivities of the acoustic transmission coefficient, expressed through the computed SEA properties, with respect to the structural design characteristics to be optimized. A wave finite element approach is employed to calculate the wave propagation constants of the curved shell. The calculated wave constants are then applied to compute the vibroacoustic properties for the curved shell using a SEA approach. Sensitivity analyses are conducted on the vibroacoustic properties to estimate their response to changes in the structural properties. Gradient vector is then formulated and hence the Hessian matrix, which is employed to formulate a Newton-like optimisation algorithm for optimizing the properties of the layered composite shell. The developed scheme is applied to a sandwich shell; optimal design parameters of [Formula: see text] and [Formula: see text] are obtained for the facesheet and the core of the shell whose base parameters are [Formula: see text] and [Formula: see text], respectively. This simultaneously optimizes the structure with maximum stiffness and minimum mass and attains a satisfactory dynamic performance for acoustic transmission through the sandwich shell. The principal advantage of the scheme is the ability to accurately model composite panels of arbitrary curvature at a rational computational time.

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