Structural Optimizations of Different Load-Carrying Members Based on Low Structural Performance Through Computational Structural Analysis

2022 ◽  
pp. 262-286
Author(s):  
Vijayanandh Raja ◽  
Balaji S. ◽  
Raj Kumar Gnanasekaran ◽  
Naveen Kumar Kulandaiyappan ◽  
Jagadeeshwaran Ponmariappan ◽  
...  
Keyword(s):  
Cross Section ◽  
Structural Engineering ◽  
Comparative Investigation ◽  
Sandwich Composite ◽  
Lightweight Materials ◽  
Load Carrying ◽  
Honeycomb Sandwich ◽  
Composite Models ◽  
Honeycomb Sandwich Composite ◽  
The Given

Load withstanding characteristics are one of the major considerations involved in structural engineering because the lifetime factor is directly proportional to load withstanding behavior. Thus, this work computationally analyzes the load withstanding behavior of various sandwich lightweight composite materials under the given flexural load. In this work, four major materials are imposed under flexural loads for two different cum prime core structures such as hexagonal cross-section and twisted cum integrated pentagonal cross-section. The major materials implemented for this comparative investigation are Aluminium Alloy, CFRP, GFRP, and KFRP. All the computational composite models are constructed through the advanced computational tool (i.e., ANSYS Workbench). Finally, the best structures with respect to their lightweight materials are shortlisted to withstand a high amount of flexural loads. According to this comprehensive study, the CFRP-based honeycomb sandwich composite performed better than all other lightweight materials.

Prediction of Elastic Properties of Honeycomb Core Materials and Analysis of Interlaminar Stress of Honeycomb Sandwich Composite Plate

2006 ◽  
Vol 306-308 ◽  
pp. 763-768
Author(s):  
Hyoung Gu Kim ◽  
Hoong Soo Yoon ◽  
Nak Sam Choi
Keyword(s):  
Poisson’S Ratio ◽  
Poisson's Ratio ◽  
Sandwich Composite ◽  
Plate Model ◽  
Honeycomb Core ◽  
Interlaminar Stresses ◽  
Honeycomb Sandwich ◽  
Honeycomb Sandwich Composite ◽  
Theoretical Results ◽  
Core Materials

Theoretical formulas for effective elastic modulus and Poisson's ratio of honeycomb core materials were proposed considering the bending, axial and shear deformations of cell walls. Theoretical results obtained by the formulas showed orthotropic elasticity and large Poisson’s ratio, which were comparable to results by finite element analysis(FEA). Tensile test of honeycomb sandwich composite(HSC) plates was performed for analysis of their deformation behaviors and interlaminar stresses. Equivalent plate model using the theoretical results of honeycomb core layer show that interlaminar shear stress occurring due to large difference of Poisson’s ratio between skin and honeycomb core layers led to the delamination in HSC plate under tensile loading. Load-displacement behavior of HSC specimen simulated by equivalent plate model coincided fairly with that of detailed FEA model similar to experimental results.

scholarly journals NDE Detection Techniques and Characterization of Aluminum Wires Embedded in Honeycomb Sandwich Composite Panels Using Terahertz Waves

Materials ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1264 ◽  
Author(s):  
Kwang-Hee Im ◽  
Sun-Kyu Kim ◽  
Jong-An Jung ◽  
Young-Tae Cho ◽  
Yong-Deuck Woo ◽  
...  
Keyword(s):  
Carbon Fibers ◽  
Sandwich Panels ◽  
Sandwich Composite ◽  
Composite Panels ◽  
Fiber Reinforced ◽  
Terahertz Waves ◽  
Fiber Reinforced Plastic ◽  
Reinforced Plastic ◽  
Honeycomb Sandwich ◽  
Honeycomb Sandwich Composite

For many years, scientists have been aware of the importance of terahertz waves (T-rays), which have now emerged as an NDE (nondestructive evaluation) technique for certain ranges of the electronic spectrum. The present study deals with T-ray scanning techniques of honeycomb sandwich composite panels with a carbon-fiber-reinforced plastic (CFRP) skin as well as the refractive index (n), and the electrical conductivity (α) of glass fiber-reinforced plastic (GFRP) composites. For this experiment, the degree of penetration to FRP composites is investigated for the THz transmitted power based on the angle in the electric field (E-field) direction vs. the direction of the unidirectional carbon fibers. Also, when CFRP skin honeycomb sandwich panels are manufactured for use in aerospace applications, aluminum wires are twisted together into the one-sided surface of the honeycomb sandwich panels to protect against thunderstorms. The aluminum wires are partly visible because they are embedded in the CFRP skin on the honeycomb sandwich panels. After finishing work with a paintjob, the wires become invisible. Thus, detecting the aluminum wires is a key issue for product monitoring. Based on a simple resistor model, an optimal scanning method is proposed to determine the preferred scan orientation on the baseline of the E-field in the direction of fibers to evaluate the level of transmission of T-rays according to the frequency bandwidth. Thus, the combination of angles required to detect the aluminum wires embedded with carbon fibers on the surface of the composite panels can be determined.

Study on Ballistic Energy Absorption of Laminated and Sandwich Composites

2006 ◽  
Vol 306-308 ◽  
pp. 739-744 ◽  
Author(s):  
Xiao Dong Cui ◽  
Tao Zeng ◽  
Dai Ning Fang
Keyword(s):  
Energy Absorption ◽  
Impact Response ◽  
Sandwich Composite ◽  
Sandwich Composites ◽  
Ballistic Resistance ◽  
Honeycomb Sandwich ◽  
Honeycomb Sandwich Composite ◽  
Improved Model ◽  
Energy Absorbing ◽  
The Impact

The impact response and energy absorbing characteristics of laminated, foam sandwich and honeycomb sandwich composites under ballistic impact have been studied in this investigation. An improved model is proposed in this paper to predict the ballistic property of the laminated composites. In this model, the material structures related to fiber lamination angles are designed in terms of their anti-impacting energy absorption capability. The ballistic limit speed and energy absorption per unit thickness of the three composites under different conditions are calculated. It is shown that honeycomb sandwich composite has the best ballistic resistance capability and energy absorption property among the three composites.

scholarly journals Artificial Neural Network–Particle Swarm Optimization (ANN-PSO) Approach for Behaviour Prediction and Structural Optimization of Lightweight Sandwich Composite Heliostats

2021 ◽  
Author(s):  
Sulaiman O. Fadlallah ◽  
Timothy N. Anderson ◽  
Roy J. Nates
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Particle Swarm Optimization ◽  
Structural Optimization ◽  
Particle Swarm ◽  
Sandwich Composite ◽  
Swarm Optimization ◽  
Honeycomb Sandwich ◽  
Artificial Neural ◽  
Honeycomb Sandwich Composite

AbstractThe necessity to diminish the heliostats’ cost so that central tower concentrating solar power (CSP) systems can stride to the forefront to become the technology of choice for generating renewable electricity is obliging the industry to consider innovative designs, leading to new materials being implemented into the development of heliostats. Honeycomb sandwich composites offer a lightweight but stiff structure that appear to be an ideal substitute for existing heliostat mirrors and their steel supporting trusses, avoiding large drive units and reducing energy consumption. However, realizing a honeycomb sandwich composite as a heliostat, among a multitude of possible combinations can be tailored from, that delivers the best trade-off between the panel’s weight reduction (broadly equates to cost) and structural integrity is cumbersome and challenging due to the complex nonlinear material behaviour, along with the large number of design variables and performance constraints. We herein offer a simulation–optimization model for behaviour prediction and structural optimization of lightweight honeycomb sandwich composite heliostats utilizing artificial neural network (ANN) technique and particle swarm optimization (PSO) algorithm. Considering various honeycomb core configurations and several loading conditions, a thorough investigation was carried out to optimally choose the training algorithm, number of neurons in the hidden layer, activation function in a network and the suitable swarm size that delivers the best performance for convergence and processing time. Carried out for three case scenarios, each with different design requirements, the results showed that the proposed integrated ANN-PSO approach provides a useful, flexible and time-efficient tool for heliostat designers to predict and optimize the structural performance of honeycomb sandwich composite-based heliostats as per desired requirements. Knowing that heliostats in the field are not all subjected to the same wind conditions, this method offers flexibility to tailor heliostats independently, allowing them to be made lighter depending on the local wind speed in the field. This could lead to reductions in the size of drive units used to track the heliostat, and the foundations required to support these structures. Such reductions would deliver real cost savings, which are currently an impediment to the wider spread use of CSP systems.

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