This paper reports a study of the initiation of the first failure event in unidirectional composites subjected to transverse tension. Two energy based point failure criteria – critical dilatational ...energy density and critical distortional energy density – are considered. The manufacturing induced disorder in the fiber distribution in the composite cross section is described in terms of the degree of nonuniformity, which is quantified and for which an algorithm is developed. The nonuniformity is captured in a representative volume element (RVE) whose minimum size is determined based on statistics of nearest fiber distance distribution. Several realizations of the RVE for three fiber volume fractions and three degrees of nonuniformity are analyzed using a finite element model. A parametric study of the effect of matrix/fiber stiffness ratio on the damage initiation is also conducted. Significant effects of the fiber distribution nonuniformity on the strain to onset of damage are found.
Composite materials fail generally by reaching a critical state, which culminates from a sequence of prior failure events. This paper is concerned with two specific early events, namely, the onset of ...matrix yielding and of fiber/matrix debonding. Continuing with an earlier work 1 (Elnekhaily and Talreja, 2018) that considered these failure events in a unidirectional polymer matrix composite with nonuniform fiber distribution subjected to transverse tension, the current work treats the case of combined axial shear and transverse tension. Using the same energy based criteria as before, the failure events are analyzed under different combinations of the two loading modes. While in the earlier work a two-dimensional representative area element was used based on a plane strain assumption, the current work uses a three-dimensional representative volume element. The results show the effects of the ratio of the axial shear to transverse tension on the two failure events. The variations of these effects with the fiber volume fraction and the degree of nonuniformity of fiber distribution are also illustrated.
A study of the early stage of crack formation in unidirectional composites subjected to transverse tension in the presence of micro voids in the matrix is conducted by computational simulation. The ...focus of the study is brittle cavitation leading to fiber/matrix debonding followed by debond crack growth and kink-out into the matrix. These failure events are studied considering a nonuniform fiber distribution and a uniform hexagonal fiber pattern in the cross section of a unidirectional composite with voids in the vicinity of the initiated cracks. A dilatational energy density criterion is used for initiation of debonding while the debond crack growth and kink-out into the matrix are studied by the energy release rate, which is calculated by the virtual crack closure technique (VCCT). Results show that while the debond initiation site is not affected significantly, the debond growth and kink-out are affected by circular voids in the close vicinity and when the diameter of these voids is a significant fraction of the fiber diameter. The effect of fiber distribution nonuniformity is manifested in the inter-fiber distances that governs the critical conditions for the debonding and kink-out processes.
This work is concerned with extracting characteristic features of transverse crack formation in cross ply laminates under axial tension considering nonuniform distribution of fibers in the ply cross ...section. The fiber-matrix debond crack initiation sites are determined first by the dilatation induced cavitation criterion for an epoxy matrix. The growth of the debond cracks is analyzed by calculating the energy release rates using the virtual crack closure technique. The kink-out of the debond cracks into the matrix is determined in short incremental steps by the maximum energy release rate criterion. Different scenarios are considered for the linking up of the kinked-out cracks to form continuous transverse cracks. By studying two different degrees of fiber distribution nonuniformity, the interactive effects due to the fiber distribution on the transverse crack formation are clarified.
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In the aircraft industry, the high-strength aluminum alloys AA7075 and AA2024 are extensively used for the manufacture of structural parts like stringers and skins, respectively. Additive ...manufacturing (AM) of the AA7075-T6 aluminum alloy via friction stir deposition to build continuously multilayered parts on a substrate of AA2024-T4 aluminum has not been attempted so far. Accordingly, the present work aimed to explore the applicability of building multilayers of AA7075-T6 alloy on a substrate sheet of AA2024-T4 alloy via the additive friction stir deposition (AFSD) technique and to optimize the deposition process parameters. The experiments were conducted over a wide range of feed rates (1–5 mm/min) and rotation speeds (200–1000 rpm). The axial deposition force and the thermal cycle were recorded. The heat input to achieve the AFSD was calculated. The AA7075 AFSD products were evaluated visually on the macroscale. The microstructures were also investigated utilizing an optical microscope and scanning electron microscope (SEM) equipped with an advanced EDS technique. As well as the presence phases, the mechanical performance of the deposited materials in terms of hardness and compressive strength was also examined. The results showed that the efficiency of the deposition process was closely related to the amount of heat generated, which was governed by the feeding rate, the rotational speed, and the downward force. AA7075 defect-free continuously multilayered parts were produced without any discontinuity defects at the interface with the substrate at deposition conditions of 1, 2, 3, and 4 mm/min and a constant 400 rpm consumable rod rotation speed (CRRS). The additively deposited AA7075-T6 layers exhibited a refined grain structure and uniformly distributed fragment precipitates compared to the base material (BM). The gain size decreased from 25 µm ± 4 for the AA7075-T6 BM to 1.75 µm ± 0.41 and 3.75 µm ± 0.78 for the AFSD materials fabricated at 1 and 4 mm/min deposition feeding rates, respectively, at 400 rpm/min. Among the feeding rates used, the 3 mm/min and 400 rpm rod rotation speed produced an AA7075 deposited part possessing the highest average hardness of 165 HV ± 5 and a compressive strength of 1320 MPa.
Two B400B-R and B500B grade rebars were industrially produced through a Tempcore process. The standard chemical composition of B500B grade was additionally alloyed with 0.067 wt.% V to enhance its ...mechanical properties. A set of optimized processing parameters were applied to manufacture two different diameters D20 (Ø 20 mm) and D32 (Ø 32 mm). The microstructure -mechanical properties relationships were evaluated using optical and scanning electron microscopes, hardness, and tensile testing. In addition, a thermal model was developed to define the thermal cycle evolution during cooling in the quenching & tempering box (QTB) to simulate the kinetics of V(C,N) precipitation. The microstructure observations showed a typical graded microstructure consisting of ferrite-pearlite core and outer tempered martensite ring for both grades of both diameters. The optimized processing parameters for B400B-R of D32 (compared with D20) resulted in softening of the core (from 160 to 135 HV10) and tempered martensite surface (from 220 to 200 HV10) as well as in decreasing the yield strength (from 455 to 413 MPa) and tensile strength (from 580 to 559 MPa). On the contrary, an increase in hardness of the core (from 165 to 175 HV10) and the outer tempered martensite (from 240 to 270 HV10), in addition to an increase in yield strength (from 510 to 537 MPa) at almost the same level of tensile strength of 624–626 MPa are observed for B500B grade D32 compared with D20. The modeling and simulation calculations suggest that the manufacturing D32 rebars of B500B grade involves longer quenching time in the QTB which allow deeper tempered martensite surface along with a relatively higher core temperature that renders faster kinetics and larger volume fraction of V(C,N) precipitates. The current study demonstrates that the full potential of V-alloying can be exploited when a sufficient quenching time at the equalization temperature is achieved, which is valid for D32 rebars.
Mud filtrate invasion is a vital parameter that should be optimized during drilling for oil and gas to reduce formation damage. Nanoparticles (NPs) have shown promising filtrate loss mitigation when ...used as drilling fluid (mud) additives in numerous recent studies. Modeling the influence of NPs can fasten the process of selecting their optimum type, size, concentration, etc. to meet the drilling conditions. In this study, a model was developed, using artificial neural network (ANN), to predict the filtrate invasion of nano-based mud under wide range of pressures and temperatures up to 500 psi and 350 °F, respectively. A total of 2,863 data points were used in the development of the model (806 data points were collected form conducted experiments and the rest were collected form the literature). Seven different types of NPs with size and concentration ranges from 15 to 50 nm and 0 to 2.5 wt%, respectively, had been included in the model to ensure universality. The dataset was divided into 70 % for training and 30 % for validation. A total of 6,750 different combinations for the model’s hyperparameters were evaluated to determine the optimum combination. The N-encoded method was used to convert the categorical data into numerical values. The model was evaluated through calculating the statistical parameters. The developed ANN-model proofed to be efficient in predicting the filtrate invasion at different pressures and temperatures with an average absolute relative error (AARE) of less than 0.5 % and a coefficient of determination (R2) of more than 0.99 for the overall data. The ANN-model covers wide range of pressures, temperatures as well as various NPs’ types, concentrations, and sizes, which confirms its useability and coverability.
HIGHLIGHTS
Artificial neural network (ANN)-model was developed to predict the volume of filtrate of water-based mud (WBM) modified with nanoparticles (NPs)
A total of 2,863 data points were collected to build the ANN-model from both experimental work and literature considering 3 types of WBM modified with 7 types of NPs (SiO2, TiO2, Al2O3, CuO, MgO, ZnO, Fe2O3) with size and concentration ranges from 15 to 50 nm and 0 to 2.5 wt%, respectively, under wide range of pressures and temperatures up to 500 psi and 350 °F
A total of 6,750 different combinations for the model’s hyperparameters were evaluated to determine the optimum combination and the N-encoded method was used to convert the categorical data into numerical values
The ANN-model proofed to be efficient with an average absolute relative error (AARE) of less than 0.5 % and a coefficient of determination (R2) of more than 0.99 for the overall data
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