Brittle fracture assessment of engineering components in the presence of notches: a review

Brittle fracture of notched components has been widely investigated in recent decades both experimentally and theoretically. This is because of designers' concern about catastrophic failure in notched engineering components made of brittle or quasi‐brittle materials. Up to now, extensive studies have been performed on brittle fracture analysis of engineering components weakened by notches of various features under mode I, mode II, mode III and mixed mode loading conditions. In the present paper, the attempt is made to review the research articles published in the open literature on brittle fracture assessment of notched components by means of notch fracture mechanics concepts. The main focus of this paper is on the stress‐based fracture criteria, which are the basis of authors' experience in recent years.     

Frequency response of thin film heads with longitudinal andtransverse anisotropy

A transmission surface model (TSM) that analyzes the conduction of flux by rotation and wall motion is reported. It has been used to quantitatively compare the predicted performance of thin-film heads with longitudinal and transverse magnetic anisotropy. The TSM analysis predicts that a transversely oriented type of thin-film head can be operated at much higher frequencies than a longitudinally oriented head. In addition, its group delay dispersion is much less. Finally, its susceptibility to wall pinning is an order of magnitude less. Therefore, it is concluded that the traditional aversion of head designers to the longitudinal orientation is justified for frequencies above several megahertz     

Optimization of peroxidase-catalyzed oxidative coupling process for phenol removal from wastewater using response surface methodology

Hydroxylated aromatic compounds (HACs) are considered to be primary pollutants in a wide variety of industrial wastewaters. Horseradish peroxidase (HRP) is suitable for the removal of these toxic substances. However, development of a mathematical model and optimization of the HRP-based treatment considering the economical issues by novel methods is a necessity. In the present study, optimization of phenol removal from wastewater by horseradish peroxidase (HRP) was carried out using response surface methodology (RSM) and central composite design (CCD). As the initial experimental design, 2(4-1) half-fraction factorial design (H-FFD) is accomplished in triplicate at two levels to select the most significant factors and interactions in the phenol removal procedure. Temperature (degrees C), pH, concentration of enzyme (unit mL(-1)), and H202 (mM) were determined as the most effective independent variables. Finally, a fourfactor-five coded level CCD, 30 runs, was performed in order to fit a second-order polynomial function to the results and calculate the economically optimum conditions of the reaction. The goodness of the model was checked by different criteria including the coefficient of determination (R2 = 0.93), the corresponding analysis of variance ((Pmodel > F) < 0.0001) and parity plot (r = 0.96). These analyses indicated that the fitted model is appropriate for this enzymatic system. With the assumption that the minimum enzyme concentration was 0.26 unit mL(-1), the analysis of the response surface contour and surface plots defined the optimum conditions as follows: pH = 7.12, hydrogen peroxide concentration 1.72 mM, and 10 degrees C. This work improves phenol removal operation economically by applying minimum enzyme concentration and highest removal in comparison with previous studies.     

Fracture assessment of graphite V‐notched and U‐notched specimens by using the cohesive crack model

This article explores the capability of the Cohesive Zone Model in predicting the critical load of blunt notched specimens made of coarse‐grained polycrystalline graphite, a brittle material that has gained the attention of researchers because of its favourable properties for protection against thermal loads. To that aim, 39 different tests on U‐notched and V‐notched specimens made of this material, with loading modes raging from mode I to mixed mode I/II, have been modelled by using the Cohesive Zone Model. The model has been implemented through the embedded crack approach, avoiding thus the necessity of defining the crack trajectory prior to the simulation because it is automatically generated once the maximum principal stress overcomes the tensile strength of the material. The numerical predictions obtained show good agreement with the experimental results.     

Mechanism of the reversibility of asphaltene precipitation in crude oil

Asphaltene precipitation and deposition occur in petroleum reservoirs as a change in pressure, temperature and liquid phase composition and reduce the oil recovery considerably. In addition to these, asphaltene precipitates may deposit in the pore spaces of reservoir rock and form plugging, which is referred to as a type of formation damage, i.e. permeability reduction. In all cases above, it is of great importance to know under which conditions the asphaltenes precipitate and to what extent precipitated asphaltenes can be re-dissolved. In other words, to what extent the process of asphaltene precipitation is reversible with respect to change in thermodynamic conditions. In present work, a series of experiments was designed and carried out to quantitatively distinguish the reversibility of asphaltene precipitation upon the change in pressure, temperature and liquid composition. Experiments were conducted in non-porous media. Generally it was observed that the asphaltene precipitation is a partial reversible process for oil under study upon temperature change with hysteresis. However, the precipitation of asphaltene as a function of mixture composition and pressure is nearly reversible with a little hysteresis.     

The application of differential transformation method to nonlinear equations arising in heat transfer

In this paper two nonlinear heat transfer problems were solved by considering variable specific heat coefficient. The calculations are carried out by using differential transformation method (DTM) which is a semi-numerical-analytical solution technique. By using DTM, the nonlinear constrained governing equations are reduced to recurrence relations and related initial conditions are transformed into a set of algebraic equations. The principle of differential transformation is briefly introduced, and then applied for the aforementioned problems. The solutions are subsequently solved by a process of inverse transformation. The current results are then compared with those derived from the variational iteration method (VIM), homotopy perturbation method (HPM), perturbation method (PM) and the exact solutions in order to verify the accuracy of the proposed method. The findings reveal that the DTM can achieve more suitable results in predicting the solution of such problems.     

Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach

In the design of adaptive cruise control (ACC) system two separate control loops - an outer loop to maintain the safe distance from the vehicle traveling in front and an inner loop to control the brake pedal and throttle opening position - are commonly used. In this paper a different approach is proposed in which a single control loop is utilized. The objective of the distance tracking is incorporated into the single nonlinear model predictive control (NMPC) by extending the original linear time invariant (LTI) models obtained by linearizing the nonlinear dynamic model of the vehicle. This is achieved by introducing the additional states corresponding to the relative distance between leading and following vehicles, and also the velocity of the leading vehicle. Control of the brake and throttle position is implemented by taking the state-dependent approach. The model demonstrates to be more effective in tracking the speed and distance by eliminating the necessity of switching between the two controllers. It also offers smooth variation in brake and throttle controlling signal which subsequently results in a more uniform acceleration of the vehicle. The results of proposed method are compared with other ACC systems using two separate control loops. Furthermore, an ACC simulation results using a stop&go scenario are shown, demonstrating a better fulfillment of the design requirements.     

Thermal buckling analysis of temperature-dependent FG-CNTRC quadrilateral plates

The main objective of the present study is to analyze the thermal buckling of functionally graded carbon nanotube-reinforced composite (FG-CNTRC) quadrilateral plates. Functionally graded patterns are introduced for the distribution of the carbon nanotubes (CNTs) through the thickness direction of the plate. The effective material properties of nanocomposite plate reinforced by CNTs are considered to be temperature-dependent (TD) and estimated using the micromechanical model. By the use of minimum total potential energy principle and based on the first-order shear deformation theory of plates, the stability equations are obtained. In order to use the generalized differential quadrature (GDQ) method and solve the stability equations, the irregular domain of quadrilateral plate is transformed into regular computational domain employing the mapping technique. The efficiency and accuracy of the proposed approach are first validated. Then, a comprehensive parametric study is presented to examine the effects of model parameters on the thermal buckling of FG-CNTRC quadrilateral plates. The results indicate that considering temperature dependency of the material properties plays an important role in the stability of the FG-CNTRC quadrilateral plates subjected to thermal loading.     

A dynamic task scheduling framework based on chicken swarm and improved raven roosting optimization methods in cloud computing

Scheduling means devoting tasks among computational resources, considering specific goals. Cloud computing is facing a dynamic and rapidly evolving situation. Devoting tasks to the computational resources could be done in numerous different ways. As a consequence, scheduling of tasks in cloud computing is considered as a NP-hard problem. Meta-heuristic algorithms are a proper choice for improving scheduling in cloud computing, but they should, of course, be consistent with the dynamic situation in the field of cloud computing. One of the newest bio-inspired meta-heuristic algorithms is the chicken swarm optimization (CSO) algorithm. This algorithm is inspired by the hierarchical behavior of chickens in a swarm for finding food. The diverse movements of the chickens create a balance between the local and the global search for finding the optimal solution. Raven roosting optimization (RRO) algorithm is inspired by the social behavior of raven and the information flow between the members of the population with the goal of finding food. The advantage of this algorithm lies in using the individual perception mechanism in the process of searching the problem space. In the current work, an ICDSF scheduling framework is proposed. It is a hybrid (IRRO-CSO) meta-heuristic approach based on the improved raven roosting optimization algorithm (IRRO) and the CSO algorithm. The CSO algorithm is used for its efficiency in satisfying the balance between the local and the global search, and IRRO algorithm is chosen for solving the problem of premature convergence and its better performance in bigger search spaces. First, the performance of the proposed hybrid IRRO-CSO algorithm is compared with other imitation-based swarm intelligence methods using benchmark functions (CEC 2017). Then, the capabilities of the proposed scheduling hybrid algorithm (IRRO-CSO) are tested using the NASA-iPSC parallel workload and are compared with the other available algorithms. The obtained results from the implementation of the hybrid IRRO-CSO algorithm in MATLAB show an improvement in the average best fitness compared with the following algorithms: IRRO, RRO, CSO, BAT and PSO. Finally, simulation tests performed in cloud computing environment show improvements in terms of reduction of execution time, reduction of response time and the increase in throughput by using the proposed hybrid IRRO-CSO approach for dynamic scheduling.