Investigation of splat curling up in thermal spray coatings

The curling up of the edges of splats of molten metal deposited on a cold substrate was investigated both experimentally and numerically. An analytical model, based on mismatch of thermal expansion between the splat and substrate, was developed to calculate the deformation of splats after curling up. The curling-up angle was measured from both millimeter-sized splats of aluminum alloy and bismuth and plasma-sprayed nickel particles. The curling-up angles were predicted using both the analytical model and a numerical code and were found to agree reasonably well with experimental measurements. This article was originally published inBuilding on 100 Years of Success, Proceedings of the 2006 International Thermal Spray Conference (Seattle, WA), May 15–18, 2006, B.R. Marple, M.M. Hyland, Y.-Ch. Lau, R.S. Lima, and J.Voyer, Ed., ASM International, Materials Park, OH, 2006.     

Prediction of spindle dynamics in milling by sub-structure coupling

The Stability of machining process depends on the dynamics of the machine tool, among other things. However, the dynamics of the machine tool changes when the tool is changed. To avoid the need for repeating the measurements, sub-structuring analysis may be used to couple the tool and spindle frequency response functions. A major difficulty in this approach is the determination of joint stiffness and damping between the two sub-structures. In particular, the measurement of rotational responses (RDOFs) at joints is a difficult task. In this research, a simple joint model that accounts for RDOFs is proposed. It is shown that this model avoids RDOF measurement while taking into account the bending modes. An optimization method based on genetic algorithm is employed to find parameters of the joint model. Receptance coupling analysis is used to couple the machine tool and tool FRFs obtained from experiment and FE, respectively. The RC based response obtained in this way is compared with experimental FRF which shows good agreement and confirms that the joint model has been successful in predicting the tool bending modes.     

Melt pool temperature control using LabVIEW in Nd:YAG laser blown powder cladding process

Employing automatic gauges is one of the fundamental steps in advanced manufacturing system not only for assuring product quality, but also monitoring process stability. Statistical process control (SPC), therefore, is developed to detect the occurrence of assignable causes so that unnecessary quality costs can be avoided. However, it is necessary to provide a practical way to evaluate the monitoring capability of an automatic gauge for its application. That is, the monitoring capability study should be conducted before applying any automatic gauge on SPC application. The economic SPC chart then can be properly designed. Rather than conventionally considering the relationship between both manufacturing cappability and control limits, gauge capability is further and concurrently considered to analyze the monitoring error of an automatic gauge in this paper. After interpreting the effect of manufacturing capability, gauge capability, and control limits to construct the monitoring error model, furthermore, the engineer can then distinctly evaluate monitoring capability by the expected cost incurred in the SPC process. Also, genetic algorithm is successfully applied to determine the economic design of X-bar control chart with the realistic monitoring error model embedded.     

Joint Clustering Relay Selection and Beamforming in Cooperative Cognitive Radio Networks

This paper proposes a joint clustering relay selection and beamforming method for a more realistic cooperative cognitive radio network, in which a secondary network of multiple secondary links and a relay network coexist with a primary network of one primary link. We aim to improve performance of the system in terms of maximizing the received signal power of the secondary destinations, subject to the constraint of received interference plus noise power of the primary destination using the proposed method. Since different relays cooperate differently towards the signals at the secondary and primary destinations, the proposed method can improve the performance of the system and enables the relay network to simultaneously transmit signals of all secondary links toward the destinations by clustering the relays. Results of simulations confirm validity of the method and improve the system performance compared to the existing cooperative beamforming and Zero-Forcing beamforming, in which no relay selection strategy is used.     

Wear resistance and friction coefficient of nano-SiO<Subscript>2</Subscript> and ash-filled HDPE/lignocellulosic fiber composites

This work comparatively evaluates the effect of nano-SiO₂ (at 2 and 3 wt%), rice husk and bagasse ash (at 5 and 10 wt%) on the wear resistance and friction coefficient of HDPE (high-density polyethylene)/lignocellulosic fiber composites. Rice husk and bagasse fibers at 50% by weight contents were mixed with HDPE and 2% maleic anhydride-grafted polyethylene as compatibilizer. SEM images showed a fairly appropriate connection between the polymer matrix and fillers. We found that the fillers improve the wear resistance, and the effect of nano-SiO₂ is more pronounced. The rice husk ash showed a better performance compared to the bagasse ash, probably due to greater SiO₂ content measured by X-ray fluorescence spectrometry. In contrast to nano-SiO₂, both ashes had a reducing effect on other mechanical strengths (Izod impact resistance, modulus of elasticity and modulus of rupture). All fillers remarkably increased the water absorption and thickness swelling. The water uptake of composites increased after wear.     

Intelligent evaluation of supplier bids using a hybrid technique in distributed supply chains

The main idea of this research is to devise the smart module to pick the best supplier bid(s) automatically. The hybrid model is composed of three useful tools: fuzzy logic, AHP, and QFD. The approach has been carefully implemented and verified via a real-world case study in a medium-to-large industry manufacturing vehicle tires and other rubber products. A collection of 12 assessment criteria classified into two categories have been considered. Eight factors are derived from customer suggestions and the other four are design specifications required to manufacture the product. The main outcomes are: a hybrid autonomous model to evaluate supplier bids without direct human intervention; devising a hybrid three-module method and overcoming complexity of computations in resulting algorithm by means of agents; outlining the best criteria to assess suppliers; evaluating the suppliers based on voice of customer during all stages of the process; and discussing analysis, design, and implementation issues of the evaluation agent. The paper includes implications for development of an integrated total system for supply chain coordination. The most important advantages of this work over earlier researches on supplier selection are: implementation of an autonomous assessment mechanism using intelligent agents for the first time, making the best out of three widely applied methodologies all at once, evaluation process mainly based on features of customer order, coordination of supply job based on a bidding system, and portal-mediated operation and control.     

DART: A DISTRIBUTED ANALYSIS OF REPUTATION AND TRUST FRAMEWORK

Artificial societies—distributed systems of autonomous agents—are becoming increasingly important in open distributed environments, especially in e‐commerce. Agents require trust and reputation concepts to identify communities of agents with which to interact reliably. We have noted in real environments that adversaries tend to focus on exploitation of the trust and reputation model. These vulnerabilities reinforce the need for new evaluation criteria for trust and reputation models called exploitation resistance which reflects the ability of a trust model to be unaffected by agents who try to manipulate the trust model. To examine whether a given trust and reputation model is exploitation‐resistant, the researchers require a flexible, easy‐to‐use, and general framework. This framework should provide the facility to specify heterogeneous agents with different trust models and behaviors. This paper introduces a Distributed Analysis of Reputation and Trust (DART) framework. The environment of DART is decentralized and game‐theoretic. Not only is the proposed environment model compatible with the characteristics of open distributed systems, but it also allows agents to have different types of interactions in this environment model. Besides direct, witness, and introduction interactions, agents in our environment model can have a type of interaction called a reporting interaction, which represents a decentralized reporting mechanism in distributed environments. The proposed environment model provides various metrics at both micro and macro levels for analyzing the implemented trust and reputation models. Using DART, researchers have empirically demonstrated the vulnerability of well‐known trust models against both individual and group attacks.     

A new model-dependent time integration scheme with effective numerical damping for dynamic analysis

This paper presents a new semi-explicit dissipative model-dependent time integration algorithm for solving structural dynamics problems. Motivated by the superior properties of the composite time-stepping scheme, the proposed method is designed, so that it fully inherits the numerical characteristics of its parent algorithm, namely the Bathe method. The algorithm design procedure is carried out by assuming unknown integration parameters for the proposed method. Afterwards, by time discretization of an SDOF model equation, the unknown parameters can be obtained explicitly by solving nonlinear system of equations. Some numerical examples are analyzed by the presented technique and comparisons are also made with two other dissipative model-dependent time integration algorithms as well as the Bathe method. Results demonstrate that the suggested technique can effectively damp out the spurious oscillations of the high-frequency modes, while the other schemes exhibit significant overshoot in the calculated responses. Furthermore, it is also observed that numerical results of the presented method totally coincide with the parent algorithm. While the Bathe method subdivides each time increment into two sub-steps, the proposed algorithm is single-step, non-iterative and does not involve any time-step subdividing.

     

Navigation in the social internet-of-things (SIoT) for discovering the influential service-providers using distributed learning automata

The Journal of Supercomputing - The integration of the social network concepts and IoT has led to the creation of a new concept called Social IoT, wherein objects or things can interact and provide...     

Investigating Chemical Properties and Oxidative Stability of Kernel Oil from Pistacia khinjuk Growing Wild in Iran

In this study in order to introduce a new vegetable oil, oxidative stability and chemical characteristics of Pistacia khinjuk kernel oil (PKKO) as compared with P. atlantica kernel oil (PAKO) and extra virgin olive oil (EVOO) were investigated. Oxidative stability of studied oils was considered based on the conjugated diene value (CDV), carbonyl value (CV) and oil/oxidative stability index (OSI) through an 8‐h thermal process at 170 °C. Also, chemical characteristics [fatty acid composition, unsaponifiable matter (USM), total tocopherols (TT), total phenolics (TP) and total sterols (TS), iodine value, saponification number and waxes] of these oils were analyzed. The ratio of polyunsaturated fatty acids to saturated fatty acids and the oxidizability (Cox) value of PKKO (1.14 and 2.78; respectively) were between those of PAKO (2.37 and 4.23; respectively) and EVOO (1.14 and 2.78; respectively). USM content of the three studied oils was between 1.1 and 1.51 %. TT and TP contents of PKKO (619.4 and 26.6 ppm) were lower than those of PAKO (845.33 and 75.22 ppm) and higher than those of EVOO (365.23 and 19.78 ppm). TS contents of PKKO, PAKO and EVOO were 2,500, 2,150 and 3,800 ppm, respectively. Oxidative stability data indicated that PKKO is the most resilient oil against lipid oxidation, followed by PAKO and EVOO. CDV significantly increased by the lowest speed for PKKO, followed by PAKO and EVOO. Increase of CV and reduction of OSI for PKKO, PAKO and EVOO were 29.2, 128 and 338.7 and 32.8, 67.9 and 79.3 %; respectively.