Begell House Inc.
Composites: Mechanics, Computations, Applications: An International Journal
CMCA
2152-2057
9
1
2018
INFLUENCE OF RANDOM AGGREGATES ON DIFFUSION BEHAVIOR OF CHLORIDE IONS IN CONCRETE BASED ON COMSOL SIMULATION
1-16
10.1615/CompMechComputApplIntJ.v9.i1.10
Shuangxi
Zhou
School of Civil Engineering and Architecture, East China Jiaotong University,
Nanchang 330013, China
Zhen
Han
School of Civil Engineering and Architecture, East China Jiaotong University,
Nanchang 330013, China
Lehua
Yu
School of Civil Engineering and Architecture, East China Jiaotong University,
Nanchang 330013, China
Xing
Wei
School of Civil Engineer and Architecture, East China Jiaotong University,
Changbei Open and Developing District, Nanchang, 330013, China
Yongqi
Wei
College of Civil Engineering, Tongji University, Shanghai 200092, China
aggregate content
ITZ
diffusion of chloride ions
numerical simulation
In the previous paper, concrete was considered as a three-phase composite material consisting of aggregates, interfacial area, and mortar, and the random delivery model of aggregates in concrete was established by MATLAB software. In the paper, the model is introduced into COMSOL, and the effect of different aggregate contents and volume fractions of the interface on the diffusion of chloride ions is discussed. By means of design of experiment, the repeatability of the proposed model is verified and simulation precision is confirmed. The effectiveness of the model is tested by a comparative analysis of experimental data and simulated results. The simulation results show that
the diffusion performance of chloride ions is restrained by the increase in the content of aggregates, which is manifested by a zigzag effect of the aggregate; the performance of the diffusion of chloride ions is accelerated with increase in the interfacial area, which is assumed as interfacial effect. From the simulated profiles, it can be seen that the acceleration becomes more obvious with increase of the content of aggregates.
FRICTIONAL BEHAVIOR OF THE AA7050/B4Cp ALUMINUM COMPOSITES
17-25
10.1615/CompMechComputApplIntJ.v9.i1.20
R.
Ranjith
Department of Mechanical Engineering, SNS College of Technology, Coimbatore Tamil Nadu — 641035, India
P. K.
Giridharan
Department of Mechanical Engineering, Kumaraguru College of Technology, Coimbatore — 641049, Tamil Nadu, India
J.
Devaraj
Department of Mechanical Engineering, Axis College of Engineering
and Technology, East Kodaly, Kerela — 680699, India
S.
Balamurugan
Department of Mechanical Engineering, Sri Krishna College of Engineering
and Technology, Kuniamuthur, Coimbatore, Tamil Nadu — 641 008, India
coefficient of friction
ANOVA
mathematical modeling
stir casting
K2TiF6
In this work, the AA7050 aluminum alloy reinforced with B4Cp was fabricated by the liquid stir
casting technique. The influence of the percentage reinforcement, sliding speed, applied load, and of
the sliding distance on the friction coefficient was investigated using pin-on-disc equipment with tests based on design of experiments. The results revealed that the sliding speed, load, and distance exert their impact on the coefficient of friction but the percentage reinforcement has no significant effect on it. A mathematical model for the friction coefficient has been developed using the response
surface methodology, and the combined effect of the process parameters was thoroughly analyzed.
RESIDUAL STRESS PREDICTION IN POROUS CFRP USING ARTIFICIAL NEURAL NETWORKS
27-40
10.1615/CompMechComputApplIntJ.v9.i1.30
Guilherme Ferreira
Gomes
Mechanical Engineering Institute, Federal University of Itajubá (UNIFEI),
Av. BPS, 1303, Itajubá, Brazil
Antonio Carlos
Ancelotti, Jr.
Mechanical Engineering Institute, Federal University of Itajubá (UNIFEI),
Av. BPS, 1303, Itajubá, Brazil
Sebastião Simões
da Cunha, Jr.
Mechanical Engineering Institute, Federal University of Itajubá (UNIFEI),
Av. BPS, 1303, Itajubá, Brazil
artificial neural networks
porous carbon fiber
fatigue test
residual stress
The use of composite materials, especially the ones made of carbon fiber/epoxy, has considerably increased for structural applications in the aerospace industry. One of the most common defects related to composite processing refers to void formation or porosity. In general, porosity causes reduction of the mechanical properties of composites and therefore it is important to evaluate the behavior of this material in the presence of this type of defect. The porosity level was taken as the input of the network. Four fatigue test data groups were used in this work, three for the training state and one set of data for validation. The ultimate strength prediction was performed with an artificial neural network backpropagation algorithm. The neural network results showed that the application of the Levenberg–Marquardt learning algorithm leads to a high predictive ultimate strength quality.
DETERMINATION OF STRESS INTENSITY FACTORS OF JUTE FIBER-REINFORCED HYBRID POLYMER-MATRIX COMPOSITES
41-50
10.1615/CompMechComputApplIntJ.v9.i1.40
P. Prabaharan
Graceraj
School of Mechanical and Building Sciences, VIT University, Vellore, India
Venkatachalam
Gopalan
Centre for Innovation and Product Development, VIT, Chennai, 600127, India
Anshul S.
Garg
School of Mechanical and Building Sciences, VIT University, Vellore, India
M. Akhil
Afsan
School of Mechanical and Building Sciences, VIT University, Vellore, India
biocomposites
fracture toughness
stress intensity factor
hybrid
As the environmental concerns are rapidly increasing in all aspects of industrial utilities, research in this regard is directed to develop a new environmentally friendly material as an alternate to the conventional materials. Biocomposite materials are highly heterogeneous in composition and
isotropic in material properties. The study of the tensile strength of a newly developed biocomposite material will not give complete details regarding the fracture or failure initiation as the study will not consider cracks in specimens. Hence, it is required to study the fracture toughness of the material to evaluate the suitability of material for engineering applications. In this paper, investigations are carried out to determine the stress intensity factors of the jute fiber-reinforced hybrid polymer-matrix composite.
REVIEW OF MODELING AND SIMULATION OF VOID FORMATION IN LIQUID COMPOSITE MOLDING
51-93
10.1615/CompMechComputApplIntJ.v9.i1.50
A.
Saad
Laboratory of Electrical Engineering and Energetic Systems, Faculty of Sciences, BOP: 133, Ibn Tofail University, Kenitra, Morocco
A.
Echchelh
Laboratory of Electrical Engineering and Energetic Systems, Faculty of Sciences, BOP: 133, Ibn Tofail University, Kenitra, Morocco
Mohamed
Hattabi
Applied Research Team on Polymers, Department of Mechanical Engineering, ENSEM, Hassan II University, Ain Chok, PB 8118, Oasis, Casablanca, Morocco
M. El.
Ganaoui
University of Lorraine, LERMAB/IUT Longwy, Institut Carnot, Nancy,
France
void
liquid composite molding
composite material
dual scale
capillary number
Liquid composite molding (LCM) processes are being used in manufacturing near-net-shape, geometrically complex composite parts. One of the current obstacles to a larger scale application of these processes is the formation of defects such as voids during resin injection. To reach
aeronautic requirements or short injection cycles in the automotive industry, entrapped air in the final part before curing has to remain as low as possible. Air entrapment will depend on the fibrous structure and on the injection parameters, or more precisely on the fluid pressure
and the flow front orientation with respect to the fibrous direction. A key parameter for production of structural composite parts is air entrapment, since high void content could lead to mechanical softening, early failure, or part rejection. The quantitative simulation of the void
formation is important for proper design and selection of material and processing parameters to minimize such voids in the composite materials. Despite several advancements in voidage predictions via modeling and simulations, the void formation mechanisms in RTM and similar processes are still not fully understood. In this study, a review of current approaches to modeling and simulation of void formation and unsaturated flow in the liquid composite molding
process is presented. We examine modeling efforts considering all the mechanisms involved such as void formation and transport, bubble compression, and gas dissolution. In particular, the capillary number is identified as a key parameter for void formation and transport. The influence of voids on the global resin flow is also investigated and a state-of-the-art is presented.