Rheological characteristics of modified calcium grease with graphene nanosheets

The effect of graphene nanosheets (GNS) on the rheological characteristics and thermal conductivity of calcium grease used in marine applications, and water pumps for lower demanding applications, has been experimentally evaluated in this paper. Various volume fractions of GNS (0.5, 1, 2, 3, and 4% wt.) have been immersed in the grease aiming at finding the better percentages that improve the properties of nanogrease. The rheological characteristics and thermal conductivity were evaluated with a Brookfield Rheometer DV-III ULTRA and KD2 thermal analyzer, respectively. The results of the modified calcium grease indicated that the best concentration of GNS is 3% wt. The rheological characteristics of the grease with a different volume fraction of GNS indicated a non-Newtonian behavior. Thermal conductivity of nanogreas also increases with an increase of GNS volume fraction. Moreover, the apparent viscosity, shear stress and dropping point increase by 59%, 52%, and 65%, respectively, with increasing GNS volume fraction.     

An Improved Hybrid Indoor Positioning Algorithm via QPSO and MLP Signal Weighting

Accurate location or positioning of people and self-driven devices in large indoor environments has become an important necessity The application of increasingly automated self-operating moving transportation units, in large indoor spaces demands a precise knowledge of their positions. Technologies like WiFi and Bluetooth, despite their low-cost and availability, are sensitive to signal noise and fading effects. For these reasons, a hybrid approach, which uses two different signal sources, has proven to be more resilient and accurate for the positioning determination in indoor environments. Hence, this paper proposes an improved hybrid technique to implement a fingerprinting based indoor positioning, using Received Signal Strength information from available Wireless Local Area Network access points, together with the Wireless Sensor Networks technology. Six signals were recorded on a regular grid of anchor points, covering the research space. An optimization was performed by relative signal weighting, to minimize the average positioning error over the research space. The optimization process was conducted using a standard Quantum Particle Swarm Optimization, while the position error estimate for all given sets of weighted signals was performed using a Multilayer Perceptron (MLP) neural network. Compared to our previous research works, the MLP architecture was improved to three hidden layers and its learning parameters were finely tuned. These experimental results led to the 20% reduction of the positioning error when a suitable set of signal weights was calculated in the optimization process. Our final achieved value of 0.725 m of the location incertitude shows a sensible improvement compared to our previous results.     

Group decision making process for supplier selection with VIKOR under fuzzy environment

During recent years, how to determine suitable suppliers in the supply chain has become a key strategic consideration. However, the nature of supplier selection is a complex multi-criteria problem including both quantitative and qualitative factors which may be in conflict and may also be uncertain. The VIKOR method was developed to solve multiple criteria decision making (MCDM) problems with conflicting and non-commensurable (different units) criteria, assuming that compromising is acceptable for conflict resolution, the decision maker wants a solution that is the closest to the ideal, and the alternatives are evaluated according to all established criteria. In this paper, linguistic values are used to assess the ratings and weights for these factors. These linguistic ratings can be expressed in trapezoidal or triangular fuzzy numbers. Then, a hierarchy MCDM model based on fuzzy sets theory and VIKOR method is proposed to deal with the supplier selection problems in the supply chain system. A numerical example is proposed to illustrate an application of the proposed model.     

Guidance and nonlinear control system for autonomous flight of minirotorcraft unmanned aerial vehicles

Small unmanned aerial vehicles (UAVs) are becoming popular among researchers and vital platforms for several autonomous mission systems. In this paper, we present the design and development of a miniature autonomous rotorcraft weighing less than 700 g and capable of waypoint navigation, trajectory tracking, visual navigation, precise hovering, and automatic takeoff and landing. In an effort to make advanced autonomous behaviors available to mini‐ and microrotorcraft, an embedded and inexpensive autopilot was developed. To compensate for the weaknesses of the low‐cost equipment, we put our efforts into designing a reliable model‐based nonlinear controller that uses an inner‐loop outer‐loop control scheme. The developed flight controller considers the system's nonlinearities, guarantees the stability of the closed‐loop system, and results in a practical controller that is easy to implement and to tune. In addition to controller design and stability analysis, the paper provides information about the overall control architecture and the UAV system integration, including guidance laws, navigation algorithms, control system implementation, and autopilot hardware. The guidance, navigation, and control (GN&C) algorithms were implemented on a miniature quadrotor UAV that has undergone an extensive program of flight tests, resulting in various flight behaviors under autonomous control from takeoff to landing. Experimental results that demonstrate the operation of the GN&C algorithms and the capabilities of our autonomous micro air vehicle are presented. © 2009 Wiley Periodicals, Inc.     

The discrete collocation method for Fredholm–Hammerstein integral equations based on moving least squares method

The purpose of this paper is to investigate the discrete collocation method based on moving least squares (MLS) approximation for Fredholm–Hammerstein integral equations. The scheme utilizes the shape functions of the MLS approximation constructed on scattered points as a basis in the discrete collocation method. The proposed method is meshless, since it does not require any background mesh or domain elements. Error analysis of this method is also investigated. Some numerical examples are provided to illustrate the accuracy and computational efficiency of the method.     

Dynamic Control of Walking Cycle with Initiation Process for Humanoid Robot

This paper focuses on numerical method to solve the dynamic equilibrium of a humanoid robot during the walking cycle with the gait initiation process. It is based on a multi-chain strategy and a dynamic control/command architecture previously developed by Gorce. The strategy is based on correction of the trunk center of mass acceleration and force distribution of the forces exerced by the limbs on the trunk. This latter is performed by mean of a Linear Programming (LP) method. We study the gait initiation process when a subject, initially in quiet erect stance posture, performs a walking cycle. In this paper, we propose to adjust the method for the multiphases (from double support to single support) and multicriteria features of the studied movement. This is done by adapting some specific constraints and criteria in order to ensure the global stability of the humanoid robot along the task execution. For that, we use a Real-Time Criteria and Constraints Adaptation method. Simulation results are presented to demonstrate criteria and constraints influences on the dynamic stability.     

A novel image encryption/decryption scheme based on chaotic neural networks

This paper presents a novel image encryption/decryption algorithm based on chaotic neural network (CNN). The employed CNN is comprised of two 3-neuron layers called chaotic neuron layer (CNL) and permutation neuron layer (PNL). The values of three RGB (Red, Green and Blue) color components of image constitute inputs of the CNN and three encoded streams are the network outputs. CNL is a chaotic layer where, three well-known chaotic systems i.e. Chua, Lorenz and Lü systems participate in generating weights and biases matrices of this layer corresponding to each pixel RGB features. Besides, a chaotic tent map is employed as the activation function of this layer, and makes the relationship between the plain image and cipher image nonlinear. The output of CNL, i.e. the diffused information, is the input of PNL, where three-dimensional permutation is applied to the diffused information. The overall process is repeated several times to make the encryption process more robust and complex. A 160-bit-long authentication code has been used to generate the initial conditions and the parameters of the CNL and PNL. Some security analysis are given to demonstrate that the key space of the new algorithm is large enough to make brute-force attacks infeasible and simulations have been carried out with detailed numerical analysis, demonstrating the high security of the new image encryption scheme.     

Generation of sodium hypochlorite (NaOCl) from sodium chloride solution using C/PbO_2 and Pb/PbO_2 electrodes

Two modified electrodes (Pb/PbO2 and C/PbO2) were prepared by electrodepositing a lead oxide layer on lead and carbon sub-strates. These modified electrodes were used as anodes for the generation of sodium hypochlorite (NaOCl) from sodium chloride solution. Different operating conditions and factors affecting the treatment process of NaOCl generation, including current density, pH values, con-ductive electrolytes, and electrolysis time, were studied and optimized. By comparison the C/PbO2 electrode shows a higher efficiency than the Pb/PbO2 electrode for the generation of NaOCl.     

Implicit algorithm for finite deformation hypoelastic–viscoplasticity in fcc metals

An implicit objective stress update algorithm is proposed for a hypoelastic–viscoplastic model. A thermal/dynamic yield function, which is derived based on the thermal activation analysis and dislocation interaction mechanisms, is used, along with the Consistency approach and the framework of additive viscoplasticity, in deriving the proposed model for fcc metals. The corotational formulation approach is utilized in developing the proposed model in the finite deformation field. For the case of the Newton–Raphson iteration method, a new expression for the consistent (algorithmic) tangent stiffness matrix of rate‐dependent metals is derived by direct linearization of the stress update algorithm. Finite element simulations are performed by implementing the proposed viscoplasticity constitutive models in the commercial finite element program ABAQUS. Numerical implementation for a simple tensile problem is used for validating the material parameters of the OFHC Copper under low and high strain rates and temperatures. The numerical results of the adiabatic true stress–true strain curves compare very well with the experimental data. The effectiveness of the present approach is tested by studying strain localization in a simple plane strain problem. Results indicate excellent performance of the present framework in describing the strain localization problem and in obtaining mesh‐independent results. Copyright © 2006 John Wiley & Sons, Ltd.