Abstract
The present experimental investigation focuses on finding optimal parametric data-set of laser microdrilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxybased composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm2) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm2) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.
Key Words
accelerated particle swarm optimization; CNT/Epoxy based PMC; heat-affected zone; laser micro-drilling; RSM; taper
Address
Lipsamayee Mishra, Trupti Ranjan Mahapatra and Debadutta Mishra: Department of Production Engineering, Veer Surendra University of Technology, Burla, 768018, India
Akshaya Kumar Rout: School of Mechanical Engineering, KIIT Deemed to be University, Bhubaneswar, 751024, India
Abstract
Presented Article evaluates the effect of nanoclay on permeability, compressive strength, and plasticity behavior of fine-grained soil related to the Tabriz landfill site. In this regard, comprehensive experimental study was performed on taken soil samples (42 specimens) with aim of design high-performance liners for Tabriz landfill. The samples was mixed by 0% (control) 3%, 6% and 9% nanoclay and prepared in 1, 7, 14 and 28 days before testing stage. Index tests like particle-size, permeability, atterberg limits, and uniaxial compressive strength (UCS) was conducted on samples. The results show that studied soil is classified as CL in USCS classification and atterberg limits measured as LL is 37, PL is 20.67, and PI is 16.33 which increase into 75, 45, and 30. The assessment presented the LL was increased about 20.27% based on increasing in nanoclay from 0% to 9%. These variations for PL and PI were 21.77% and 18.37%, respectively. Also, the and soil's compressive strength is increase from 120 kPa to 188 kPa and permeability is estimated as 4.25*10-6 m/s which reduced into the 6.34*10-9 m/s with respect the naboclay content increases form 0% to 9%.
Key Words
fine-grained Soils; landfill liners; leachate control; nanoclay; permeability
Address
Mahdi Nikbakht, Fariba Behrooz Sarand and Rouzbeh Dabiri: Department of Civil Engineering, Islamic Azad University, Tabriz Branch, Tabriz, Iran
Masoud Hajialilue Bonab: Department of Civil Engineering, University of Tabriz, Tabriz, Iran
Abstract
This paper presents a careful theoretical investigation into interfacial stresses in RC beams strengthened with externally bonded imperfect FGM plate. In this study, an original model is presented to predict and to determine the stresses concentration at the imperfect FGM end, with the new theory analysis approach. Stress distributions, depending on an inhomogeneity constant, were calculated and presented in forms. It is shown that both the shear and normal stresses at the interface are influenced by the material and geometry parameters of the composite beam, and it is shown that the inhomogeneities play an important role in the distribution of interfacial stresses. The theoretical predictions are compared with other existing solutions. The numerical resolution was finalized by taking into account the physical and geometric properties of materials that may play an important role in reducing the stress values. This research is helpful for the understanding on mechanical behaviour of the interface and design of the PFGM-RC hybrid structures.
Address
Benferhat Rabia, Hassaine Daouadji Tahar and Rabahi Abderezak: 1) Civil Engineering Department, University of Tiaret, Algeria, 2) Laboratory of Geomatics and Sustainable Development, University of Tiaret, Algeria
Abstract
Cu-based sulfides have recently emerged as promising thermoelectric (TE) materials due to their low cost, non-toxicity, and abundance. In this research, point defect structure of Cu2-xZnSnS4 (x=0.1, 0.2, 0.3) samples were synthesized by the mechanical alloying method. Mixed powders of Cu, Zn, Sn and S were milled using high energy ball milling at a rotation speed of 300 rpm in Ar atmosphere. The milled Cu2-xZnSnS4 powders were heat-treated at 723 K for 24 h, and subsequently consolidated using spark plasma sintering (SPS) under an applied pressure of 60 MPa for 15 min. The thermal conductivity of the sintered Cu2-xZnSnS4 samples was evaluated. A well-defined Cu2-xZnSnS4 powders were successfully formed after milling for 16 h, with the particle sizes mostly distributed in the range of 60-100 nm. The lattice constants of a and c decreased with increasing composition value x. The thermal conductivity of sintered x=0.1 sample exhibited the lowest value and attained 0.93 W/m K at 673 K.
Key Words
Cu2ZnSnS4; mechanical alloying and thermal conductivity; thermoelectric materials
Address
School of Materials Science and Engineering, Hanoi University of Science and Technology, No.1 Dai Co Viet, Hai Ba Trung, Hanoi, Vietnam
Abstract
Asphalt concrete (AC), is a mixture of bitumen and aggregates, which is very sensitive in the design of flexible pavement. In this study, the Marshall stability of the glass and carbon fiber bituminous concrete was predicted by using Artificial Neural Network (ANN), Support Vector Machine (SVM), Random Forest (RF), and M5P Tree machine learning algorithms. To predict the Marshall stability, nine inputs parameters i.e., Bitumen, Glass and Carbon fibers mixed in 100:0, 75:25, 50:50, 25:75, 0:100 percentage (designated as 100GF:0CF, 75GF:25CF, 50GF:50 CF, 25GF:75CF, 0GF:100CF), Bitumen grade (VG), Fiber length (FL), and Fiber diameter (FD) were utilized from the experimental and literary data. Seven statistical indices i.e., coefficient of correlation (CC), mean absolute error (MAE), root mean squared error (RMSE), relative absolute error (RAE), root relative squared error (RRSE), Scattering index (SI), and BIAS were applied to assess the effectiveness of the developed models. According to the performance evaluation results, Artificial neural network (ANN) was outperforming among other models with CC values as 0.9147 and 0.8648, MAE values as 1.3757 and 1.978, RMSE values as 1.843 and 2.6951, RAE values as 39.88 and 49.31, RRSE values as 40.62 and 50.50, SI values as 0.1379 and 0.2027 and BIAS value as -0.1 290 and -0.2357 in training and testing stage respectively. The Taylor diagram (testing stage) also confirmed that the ANN-based model outperforms the other models. Results of sensitivity analysis showed that the fiber length is the most influential in all nine input parameters whereas the fiber combination of 25GF:75CF was the most effective among all the fiber mixes in Marshall stability.
Key Words
artificial neural network; carbon fiber; glass fiber; M5P Tree-based model; Marshall stability; random forest; support vector machine
Address
Ankita Upadhya, M. S. Thakur, Nitisha Sharma and Fadi H. Almohammed: Department of Civil Engineering, Shoolini University, Solan, Himachal Pradesh, 173229, India
Parveen Sihag: Department of Civil Engineering, Chandigarh University, Chandigarh, 140413, India
