Investigation on mechanochemical synthesis of Al2O3/BN nanocomposite by aluminothermic reaction

Alpha-alumina–boron nitride (α-Al₂O₃–BN) nanocomposite was synthesized using mixtures of aluminum nitride, boron oxide and pure aluminum as raw materials via mechanochemical process under a low pressure of nitrogen gas (0.5 MPa). The phase transformation and structural evaluation during mechanochemical process were investigated by X-ray diffractometry (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and differential thermal analysis (DTA) techniques. The results indicated that high exothermic reaction of Al–B₂O₃ systems under the nitrogen pressure produced alumina, aluminum nitride (AlN), and aluminum oxynitride (Al₅O₆N) depending on the Al value and milling time, but no trace of boron nitride (BN) phases could be identified. On the other hand, AlN addition as a solid nitrogen source was effective in fabricating in-situ BN phase after 4 h milling process. In Al–B₂O₃–AlN system, the aluminothermic reaction provided sufficient heat for activating reaction between B₂O₃ and AlN to form BN compound. DTA analysis results showed that by increasing the activation time to 3 h, the temperature of both thermite and synthesis reactions significantly decreased and occurred as a one-step reaction. SEM and TEM observations confirmed that the range of particle size was within 100 nm.     

Thermal performance and efficiency of convective–radiative T-shaped fins with temperature dependent thermal conductivity,heat transfer coefficient and surface emissivity

This paper analytically investigates the thermal performance of convective–radiative T-shape fin with simultaneous variation of thermal conductivity, heat transfer coefficient and surface emissivity with temperature. Unlike some other fin studies, the sink temperatures for convection and radiation are assumed to be non-zero. This model is a more realistic representation of fins in actual engineering practice. The collection of graphs provided should facilitate design and performance evaluation of T-shaped fins.     

Novel application of a new metamaterial complementary electric LC resonator for the design of miniaturized sharp band‐pass filters

In this article, we introduce a new metamaterial complementary electric LC resonator (CELC) and investigate its operational mechanism, characteristics, and potentialities for application in microwave components and devices, such as filters. We consider the excitation of CELC by the electric and magnetic fields of microstrip lines and its resonance characteristics by the diagrams of effective permittivity (ε_eff) and permeability (μ_eff). A circuit model is obtained by the consideration of its coupling with the loaded microstrip line. We then realize a novel left‐handed (LH) cell by the combination of the CELC resonator and a short circuited stub. It is designed by the least mean square method. We finally use the cascade connection of such LH cells for the design of a miniaturized narrow‐band band‐pass filter with high out of band rejection. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Rolling-horizon and fix-and-relax heuristics for the multi-product multi-level capacitated lotsizing problem with sequence-dependent setups

This paper discusses the multi-product multi-level capacitated lotsizing and scheduling problem with sequence-dependent setups. An exact formulation of the problem is provided as a mixed-integer program which is impractical to solve in reasonable computing time for non-small instances. To solve non-small instances of the problem, MIP-based heuristics are provided. To test the accuracy of heuristics, two lower bounds are developed and compared against the optimal solution. The trade-offs between schedule quality and computational time of heuristics are also provided.     

An iterative integrated framework for thermal–visible image registration,sensor fusion,and people tracking for video surveillance applications

In this work, we propose a new integrated framework that addresses the problems of thermal–visible video registration, sensor fusion, and people tracking for far-range videos. The video registration is based on a RANSAC trajectory-to-trajectory matching, which estimates an affine transformation matrix that maximizes the overlapping of thermal and visible foreground pixels. Sensor fusion uses the aligned images to compute sum-rule silhouettes, and then constructs thermal–visible object models. Finally, multiple object tracking uses blobs constructed in sensor fusion to output the trajectories. Results demonstrate the advantage of our proposed framework in obtaining better results for both image registration and tracking than separate image registration and tracking methods.     

β-Polymorph enhancement in poly(vinylidene fluoride) by blending with polyamide 6 and barium titanate nanoparticles

Polyamide 6 (PA6) as a cost-effective polar polymer and barium titanate (BT) as piezoelectric ceramic nanofiller were melt compounded with poly(vinylidene fluoride) (PVDF) matrix to enhance the β electroactive phase. A series of samples with two blending ratios of PVDF/PA6 (90/10 and 70/30 [wt%/wt%]) each containing 1, 3, and 5 wt% of BT were prepared. The SEM results revealed that the addition of BT to the neat blends refined the biphasic morphology which is mainly due to selective localization of BTs in PA6 dispersed phase as confirmed by TEM observation and wetting parameter predictions. The EDX analysis demonstrated a uniform distribution of BT nanoparticles in the filled systems. FTIR and XRD results showed that β content increased as a result of blending while the α phase was suppressed. The BT nanoparticles inclusion to the blends showed a synergistic effect on the β-polymorph content. These results in combination with the data derived from DSC (indicating reduction of the total crystallinity) complement the idea of β enhancement by the addition of BT nanoparticles and PA6 into PVDF.     

Quantitative Risk Assessment for Process Design Modification and Maintenance Optimization in Refineries and Petrochemical Plants

Quantitative risk assessment is methodology based on calculating probabilities and frequencies of sequential events using Boolean algebra, and it is normally used to perform safety assessments for complex interacting systems. Although quantitative risk assessment has been commonly used in aerospace and nuclear industries, it can also be used for quantifying economic risk and for estimating possibilities of potential production losses in a petrochemical or a manufacturing plant. In developing quantitative risk assessment models for petrochemical plants, component failures as well as human (operator) errors are taken into consideration in developing the plant's fault‐tree logic, in which is used to predict probabilities of future plant upsets. This paper shows how the quantitative risk assessment can be used to rank the economic importance of the production units in a refinery for prioritizing maintenance activities. In addition, two case studies are compared to demonstrate how a quantitative risk assessment model can be used as an invaluable tool in process design optimization. The quantitative risk assessment methodology developed in this work relates production losses to the performance of the major components and the process design. This application of the quantitative risk assessment provides a basis for the risk‐informed decision‐making and optimizing allocation of plant resources in support of plant operation and maintenance activities.     

A novel approach toward integration of rules into business processes using an agent-oriented framework

Every action a business process performs must be explicitly anticipated, designed for, and implemented by business professionals. The business process is dependent upon business rules (BRs) to achieve its objectives, which also involve pre- and post-conditions in the business process (BP). Most of the current techniques implement these rules directly into BPs. This will result in the BP becoming even more complicated and harder to customize. Most BRs (and laws) are buried in data warehouses as raw data. Incorporating the BRs into any BP is very complex, in terms of customization, reuse, and system integration. To overcome this problem, we propose and implement an agent-oriented framework. Using this framework, we can make the process of incorporating BR into BP less complex. The agent creates a bridge between components of the business structure, the BRs, and the BP. The BP consists of activities and sub-activities. The agent is able to communicate with BP and BRs to execute a BP. The agent can also communicate with other agents and have control over their own internal states and behavior. In this paper, we propose and implement a simple case study to execute a BP dependent upon BRs. The case study shows how the agent will synchronize, integrate, and deploy the BP.     

An innovative computational algorithm for simulation of lead-acid batteries

Predicting transient behavior of lead-acid batteries during charge and discharge processes is an important factor in many applications including hybrid electric vehicles (HEVs). The conventional mathematical models, which are used to predict the battery dynamics, are either inaccurate or time-consuming. In this study, an improved and efficient mathematical model for simulation of flooded lead-acid batteries based on Computational Fluid Dynamics (CFD) and Equivalent Circuit Model (ECM) has been introduced which inherits the accuracy of CFD model and the physical understanding of ECM. This approach makes the numerical procedure very efficient and easy to implement. Moreover, because of simplification of boundary conditions (BC's), it is very fast which makes it quite suitable for real-time simulations. The present approach is verified by previous CFD models and experimental data.