Thermal effects on fracture of biaxial-oriented poly(ethylene terephthalate) (BOPET) film

The effect of temperature on the fracture behaviour of biaxial-oriented poly(ethylene terephthalate) (BOPET) film was studied using the Essential Work of Fracture (EWF) approach. Fracture tests were performed over the temperature range +25 to +160 °C at the speed of 5 mm/min using double edge notched tension (DENT) specimens. The length of the specimens was either along the machine direction (MD) (0°), transverse direction (TD) (90°) or at 45° to either MD or TD. Ductile tearing of the ligament region was noted over the entire temperature range in all three directions. A linear relationship was found between the specific total work of fracture and the ligament length at all test temperatures. Values of the specific essential work of fracture (w _e) in the MD and TD were similar and smaller than in the 45° direction. Within temperature range 25–140 °C, w _e showed little variation if any with respect to temperature. As expected, the Specific Non-Essential Work of Fracture (βw _p) was temperature dependent. This parameter increased with increasing temperature and reached a maximum around the glass transition temperature of BOPET (T _g ≈ 80 °C). The values of the maxima are respectively 16.15, 20.38 and 17.8 MJm⁻³ for the 0°, 45° and 90°.     

Prediction of forming limit diagrams using the modified M-K method in hydroforming of aluminum tubes

The purpose of this study is to predict forming limit diagrams (FLDs) for AA6063 and AA6065 aluminum seamless extruded tubes. The Modified Marciniak and Kuczynski (M-K) method is used with Barlat’s 1989 anisotropic yield function and Voce equation. Furthermore, a new calibration method for FLD determination based on the modified M-K method is also applied. The predicted forming limits correlate well with experimental data. It is shown that in comparison to other methods, this method is able to predict necking in tube hydroforming with more accuracy. Therefore, this method can be used to predict bursting in a wide range of practical tube hydroforming of aluminum alloys.     

Classroom furniture and anthropometric characteristics of Iranian high school students: Proposed dimensions based on anthropometric data

The study evaluated the potential mismatch between classroom furniture dimensions and anthropometric characteristics of 978 Iranian high school students (498 girls, 480 boys), aged 15-18 years. Nine anthropometric measurements (stature, sitting height, sitting shoulder height, popliteal height, hip breadth, elbow-seat height, buttock-popliteal length, buttock-knee length and thigh clearance) and five dimensions from the existing classroom furniture were measured and then compared together (using match criterion equations) to identify any potential mismatch between them. The results indicated a considerable mismatch between body dimensions of the students and the existing classroom furniture, with seat height (60.9%), seat width (54.7%) and desktop height (51.7%) being the furniture dimensions with a higher level of mismatch. The levels of mismatch varied between the high-school grade levels and between genders, indicating their special requirements and possible problems. The proposed dimensions of the classroom furniture more appropriate for the students were given. This additional information on students' anthropometry can be used by local furniture industries as a starting point for designing more appropriate furniture for school children, or used by schools to aid in furniture selection.     

Gain-scheduled controller synthesis for a nonlinear PDE

Linear parameter-varying (LPV) modelling and control of a nonlinear partial differential equation (PDE) is considered in this article. The one-dimensional viscous Burgers' equation is discretised using a finite difference scheme; the boundary conditions are taken as control inputs and the velocities at two grid points are assumed to be measurable. A nonlinear high-order state space model is generated and proper orthogonal decomposition is used for model order reduction. After assessing the accuracy of the reduced model, a low-order functional observer is designed to estimate the reduced states which are linear combinations of the velocities at all grid points. A discrete-time quasi-LPV model that is affine in scheduling parameters is derived based on the reduced model. A polytopic LPV controller is synthesised based on a generalised plant containing the LPV model and the functional observer. More generally, the proposed method can be used to design an LPV controller for a quasi-LPV system with non-measurable scheduling parameters. Simulation results demonstrate the high tracking performance and disturbance and measurement noise rejection capabilities of the designed LPV controller compared with a linear quadratic Gaussian (LQG) controller based on a linearised model.     

On the MHD boundary layer flow with diffusion and chemical reaction over a porous flat plate with suction/blowing: two reliable methods

Engineering with Computers - In this paper, a Lie-group integrator based on $$GL_4(\mathbb {R})$$ and the reproducing kernel functions has been constructed to investigate the flow characteristics...     

Experimental investigation of tornado-like vortex dynamics with swirl ratio: The mean and turbulent flow fields

An experimental simulation of tornado-like vortices is conducted in a small tornado vortex simulator in order to study the effect of swirl ratio on flow characteristics. Particle Image Velocimetry (PIV) method is employed to quantitatively determine the tornado-vortex velocity field for swirl ratios ranging from 0.08 to 1. The radial and tangential components of velocity as well as the core radius of the tornado increase with increase in swirl ratio. The location of the maximum radial and tangential velocities is adjacent to the ground where the tornado vortex interacts with the surface. The values of normal and shear turbulent stresses indicate the existence of a laminar core for small swirl. As expected the shear stresses increase with swirl ratio as the vortex becomes turbulent. The highest turbulent production corresponds to the critical case of vortex touchdown.     

The logical precedence network planning of projects, considering the finish-to-start (FS) relations, using neural networks

One of the important steps in the process of project planning is the designing of logical precedence network. As the procedure of the logical precedence network planning is case dependent and varies in different projects, it could be considered as an unstructured and complex problem which should be solved by implementing the implicit domain knowledge of the planner. In this paper, we have shown how the artificial neural networks could be implemented to plan the finish-to-start logical precedence network of projects. The implementation results depict that the proposed methodology could result reasonable, accurate, and reliable outcomes, which could be used as a primary solution, which can enrich the acquired knowledge, after the accomplishment of the project and its practical corrections.     

An efficient data dissemination model for wireless sensor networks

Wireless Networks - In a wireless sensor network, one of the most important constraints on sensor nodes is their power source, which is a battery. Sensor nodes carry a limited and generally...     

Synthesis and Characterization of Pure Phase Zn(II) and Cd(II) Oxide Nanoparticles via Thermal Decomposition of Four New Zn(II) and Cd(II) Coordination Polymers

Four new Zn(II) and Cd(II) coordination polymers, [Zn(2-AMP)₂(N₃)₂]_n (1), [Zn(2-AMP)₂(SCN)₂]_n (2), [Cd(2-AMP)(N₃)₂]_n (3) and [Cd(2-AMP)₂(SCN)₂]_n (4) {2-AMP: 2-Aminomethylpyridine}, have been synthesized and characterized by single crystal X-ray diffraction, IR spectroscopy and elemental analyses. The Zinc(II) oxide and Cadmium(II) oxide nano-particles have been synthesized from thermolysis of 1–4 at 600 °C under air atmosphere for 4 h. The ZnO and CdO nanoparticles were characterized by X-ray diffraction and scanning electron microscopy (SEM). SEM images show the average size of produced ZnO and CdO nanoparticles are 60–70 nm in all compounds.     

A graph mining approach for detecting unknown malwares

Nowadays malware is one of the serious problems in the modern societies. Although the signature based malicious code detection is the standard technique in all commercial antivirus softwares, it can only achieve detection once the virus has already caused damage and it is registered. Therefore, it fails to detect new malwares (unknown malwares). Since most of malwares have similar behavior, a behavior based method can detect unknown malwares. The behavior of a program can be represented by a set of called API's (application programming interface). Therefore, a classifier can be employed to construct a learning model with a set of programs' API calls. Finally, an intelligent malware detection system is developed to detect unknown malwares automatically. On the other hand, we have an appealing representation model to visualize the executable files structure which is control flow graph (CFG). This model represents another semantic aspect of programs. This paper presents a robust semantic based method to detect unknown malwares based on combination of a visualize model (CFG) and called API's. The main contribution of this paper is extracting CFG from programs and combining it with extracted API calls to have more information about executable files. This new representation model is called API-CFG. In addition, to have fast learning and classification process, the control flow graphs are converted to a set of feature vectors by a nice trick. Our approach is capable of classifying unseen benign and malicious code with high accuracy. The results show a statistically significant improvement over n-grams based detection method.