Reflection and refraction of light at saturating active boundaries

Abstract

This study deals with the topic of reflection and refraction of light from the boundary of a high-gain saturating laser amplifier. Expressions for the electric field and intensity reflection and transmission coefficients are obtained for the case of a wave in a uniform dielectric that is incident normally on a nonlinear saturating active medium. Bistability effects are predicted even for the simplest case of zero frequency detuning from the line centre of the saturating transition.     

A new layered manufacturing machine with cutting force analysis in tapered end milling

We introduce a new layered manufacturing machine with its associated geometric cutting force model. This machine is designed to build metal parts and is a modified type of commercial layered object manufacturing (LOM) machine. This apparatus uses tapered end mills with different angles instead of laser to cut the layer edges. The proposed machine needs higher stiffness, because cutting action would regularly create more inaccuracy. Consequently, a new force model is considered that takes into account cutting conditions, cutter geometry and combination of tool-workpiece materials. Then, by force and stress analysis cutting-force induced inaccuracy has been evaluated for different components of the machine. Finally, the effectiveness of the machine and its capability to build functional metal parts with different geometries is clearly shown.     

Dynamic performance assessment of the efficiency of fuel cell-powered bicycle: An experimental approach

Zero-emission fuel cell driven systems are regarded as promising technological advances in the future of the transportation industry that have the potential to replace internal combustion engines. The design, performance, and efficiency properties of a vehicle are often stated to be some of the key challenges in its commercialization. This paper highlights a polymer electrolyte membrane fuel cell (PEMFC)-powered system of an electric bicycle. The system consists of a 250-W fuel cell, ECU, battery pack, DC/DC converter, electric motor, and other supporting equipment. After introducing the different parts of the bicycle, its overall efficiency will be discussed in great detail. The efficiency of fuel cells is not specific; it is a subordinate to the power density where the system operates. Experimental work has been conducted to measure the values of the efficiency and energy flow. The results indicated a maximum fuel cell efficiency of 63% and an overall system efficiency of 35.4%. The latter value is expressed with regards to the Lower Heating Value (LHV) of hydrogen. All measurements were taken for the cruising conditions of the vehicle and its corresponding to power consumption. The results are superior to those of a standard internal ignition engine. The fuel cell performance is least efficient when functioning under maximum output power conditions.     

Short vs. long column behavior of pultruded glass-fiber reinforced polymer composites

Analytical and experimental studies were conducted for the purpose of establishing a distinguishing criterion between short and long FRP composite column behaviors. The results of investigating 24 full-scale GFRP composite columns are presented. The experimental studies utilized specimens with commonly used ‘Universal’ and ‘Box’ cross-sections which were manufactured by the pultrusion process using E-glass fibers in various forms as reinforcement and polyester and vinylester as binding matrices. The effective slenderness ratios (L/r) of the investigated columns were 3.79, 32.7, 47.9, 63.1 and 75.4 for the ‘Universal’ section and 9.38, 53.9 and 78.9 for the ‘Box’ section. The specimen lengths were 18 inches (0.46 m), 8 foot (2.44 m), 12 foot (3.66 m), 16 foot (4.88 m) and 19.25 foot (5.87 m). All columns were tested in a vertical position and under compressive axial static loading and the fundamental pinned–pinned end-conditions. The columns’ compressive strains, buckling and crippling loads, lateral displacements, initial curvatures, and modes of failure were documented during the course of this investigation. Orthotropic mechanical properties of the composites were experimentally obtained utilizing 44 coupons cut from the column specimens. Analytically, Euler's formula was employed to obtain critical loads for the slender columns. For short columns, the classical plate theory was used to predict columns’ buckling loads. Based on experimental evaluations and analytical results, a slenderness ratio based criterion was established for distinguishing between short and long composite column behaviors. Further conclusions and design recommendations were made.     

Preparation, Characterization and Photocatalytic Properties of Ba-Cd-Sr-Ti Doped Fe3O4 Nanohollow Spheres on Removal of Congo Red Under Visible-Light Irradiation

In this study, Ba-Cd-Sr-Ti doped Fe₃O₄ nanohollow spheres were successfully prepared via a simple solvothermal method. The crystal size, structure, morphology and elemental analysis of the as-prepared sample were investigated in detail by X-ray diffraction (XRD), FT-IR, scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy, respectively. Magnetic hysteresis measurement was carried out on a vibrant sample magnetometer (VSM) showing the soft ferromagnetic property at room temperature. The synthesized nanohollow spheres were employed as a photocatalyst to study the photocatalytic degradation of dye contaminations. The UV-Vis results showed that the specimen could well catalyze the decolorizing of congo red (CR) solution and a removal efficiency of 99.5 % was obtained at pH 6. The optical characteristic of the products was studied by estimating the band-gap energy based on diffuse-reflectance spectroscopy (DRS) which represented the doped magnetite with semiconductor metals to be more prone in the visible region as compared to UV region. Some factors such as initial dye concentration, pH, and contact time influencing the decomposition of CR were evaluated.     

Successful Use of Geoelectrical Surveys in Area 3 of the Gol-e-Gohar Iron Ore Mine,Iran

Geoelectrical surveys were conducted in Area 3 of the Gol-e-Gohar iron ore mine to provide geological and hydrogeological information. Open pit mining is currently underway in the northern part of the Area, and underground mining operations are planned for the southern section. Groundwater has already been encountered in the open pit mine. Twenty five resistivity soundings were first performed in the mine area; then, induced polarization (IP) measurements were carried out to remove ambiguities between clay and water-bearing layers. To investigate fault zones as water conduits, combined resistivity profiling surveys were also carried out. These measurements provided a detailed structural map of the pit area. Resistivity and IP results have subsequently been confirmed by observations at three monitoring wells and the mine pit wall. Monitoring and piezometric wells will be drilled at locations suggested by the results of the geoelectrical surveys. Drainage galleries may be developed to dewater the open pit mine. However, another option being considered is to start the underground mining with the idea that it will initially simply serve as a dewatering mechanism.     

Predictive control of drying process using an adaptive neuro-fuzzy and partial least squares approach

In this paper, adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN), and partial least squares (PLS) approaches are applied to predictive control of a drying process. In the proposed approaches, the PLS analysis is used to pre-process actual data and to provide the necessary background to apply ANN and ANFIS approaches. A reasonable section of this study is assigned to the modeling with the aim at predicting the granule particle size and executing by ANFIS and ANN. ANN holds the promise of being capable of producing non-linear models, being able to work under noise conditions, and being fault tolerant to the loss of neurons or connections. Also, the ANFIS approach combines the advantages of fuzzy system and artificial neural network to design architecture and is capable of dealing with both limitation and complexity in the data set. The efficiencies of ANFIS and ANN approaches in prediction are compared and the superior approach is selected. Finally, by deploying the preferred approach, several scenarios are presented to be used in predictive control of spray drying as an accurate, fast running, and inexpensive tool. This is the first study that presents a flexible intelligent approach for predictive control of drying process by ANN, ANFIS, and PLS. The approach of this study may be easily applied to other production process.     

A robust decision-making methodology for evaluation and selection of simulation software package

Today, simulation has a broad range of applications from solving service problems to analyzing manufacturing problems such as warehousing and logistic systems. Simulation has become a popular methodology and selecting an appropriate simulation software package is one of the decisions that any industrial engineer may face at work. As a result, numerous types of simulation software packages have been developed for modeling simulation problems. The increasing variety of simulation software packages in the software market makes the selection of an appropriate simulation software package a critical decision. Selecting an inappropriate software package will be followed by many negative consequences. This paper will present a robust decision-making methodology based on Fuzzy Analytical Hierarchy Process (FAHP) for evaluating and selecting the appropriate simulation software package. The robust decision method aggregates the experts’ judgments for the criteria weights and the suitability of simulation software alternatives. The FAHP is used to prioritize and evaluate existing alternatives based on the proposed criteria for choosing the proper simulation software. The proposed methodology is applied to selecting the appropriate simulation software as an experiment and results are provided.     

Performance assessment of decision-making units using an adaptive neural network algorithm: one period case

This study proposes a nonparametric method based on adaptive neural network (ANN) technique for measuring efficiency of decision making units (DMUs) in one period case as a complementary tool for the ANN-based efficiency methods in the previous studies. In previous studies, there are needed to have large volume of data, and so the proposed method in this study is more applicable because it can be used for the cases which have no historical data. In fact, a limitative weakness of the ANN-based efficiency methods about applying them for these cases is removed. So, it can be a competitive method to the other common tools for measuring efficiency. By noting the importance of flexible manufacturing system, this study presents a decision-making model for optimization of operators’ allocation in cellular manufacturing system by computer simulation. The methodology is illustrated through its application on a previously reported dataset. It was found out that ANN provides more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored.     

Empirical evaluation of river basin sustainability affected by inter‐basin water transfer using composite indicators

In this study, a practical approach to evaluate the sustainability of river basins subjected to an inter‐basin water transfer project is developed. Selection of appropriate evaluation indicators is pivotal to such approach. To make use of huge amount of data, composite indicators of sustainability (CIS) should be utilised. The proposed approach relies on 15 sustainability indicators (SI) that cover three major criteria namely (economic, social and environmental), and aggregates them into eight different types of sustainability indices for a more robust outcome. Two scenarios were considered within the source and recipient basins. Furthermore, multivariate principal component analysis (PCA) was applied to determine principal and non‐principal indicators for the two river basins. The ability of CIS and PCA methods were verified via correlation and simple regression methods respectively. The results demonstrated that inter‐basin water transfer may improve sustainability, provided that a proper water resource management is enforced.