Effect of Microalloying Additions on the Microstructure and Mechanical Properties of Low Carbon Steel

Low carbon steels are characterized by good weldability,formability and fracture toughness properties.However,the low strength levels of these steel grades limit their wide applications.On the other hand,increasing the strength by increasing the carbon content and alloying elements deteriorates the other properties.In this study,the microalloying technique was used to examine the possibility of attaining low carbon steels with good combination of strength,ductility and impact properties.A low carbon steel microalloyed with single addition of vanadium and another one microalloyed with combined addition of vanadium and titanium were used in this investigation and their properties were compared with non-microalloyed low carbon steel having the same base composition.Furthermore,other two nonmicroalloyed and V-microalloyed steels with higher carbon,silicon and manganese contents were also investigated to reveal the effect of base composition.Tensile,hardness,room and zero temperature Charpy V-notch impact tests were conducted to evaluate the variations in the mechanical properties of low carbon hot forged steel containing vanadium and combinations of vanadium and titanium.In addition,the microstructures of the different investigated steels were observed using both optical microscope and scanning electron microscope.Furthermore,the hardness of the ferrite phase was also determined using micro-hardness technique.The results showed improvement of the mechanical properties of the investigated steels by both single V-and combined V + Ti-microadditions.Tensile,hardness and impact tests results indicated that good combinations of strength,ductility and impact properties can be achieved by V-microalloying addition.Steel with combination of V and Ti microaddition has much higher hardness,yield strength,ultimate tensile strength and impact energy at both room and zero temperatures compared with non-microalloyed and single Vmicroalloyed steels.Higher C,Si and Mn contents result in increasing the strength accompanied with decrea     

Numerical Characterization of Advective Gas Flow through GM/GCL Composite Liners Having a Circular Defect in the Geomembrane

Numerical experiments were conducted to understand the effect of geometric and transport characteristics of a geomembrane-geosynthetic clay liner (GM/GCL) composite liner on gas leakage rate through a circular defect in the geomembrane (GM). The originality of the approach proposed in this paper rests on the use of a new conceptual two-layered system for modeling of GM/GCL composite liners where the interface zone between the GM and geosynthetic clay liner (GCL) has been merged with the GCL cover geotextile and handled as one layer; the GCL bentonite layer was considered the second layer. The role of the carrier geotextile layer was ignored since it can be considered as a no pressure loss layer. Analysis of numerical simulation results shows the existence of a constitutive leakage flow surface which enables evaluation of the leakage flow state for different geometric and transport properties of GM/GCL composite liners. Furthermore, the determined surface was also exploited to evaluate gas leakage rates under the framework of the Forchheimer’s analytical solution. The gas leakage rate predictions were found to be in good agreement with experimental results obtained at different GCL moisture content.     

Detecting nonlinear interrelation patterns among process variables using genetic programming

Detecting non-linear interaction patterns among process variables is an important task for fault detection and propagation analysis. There are many statistical and evolutionary techniques being developed in the literature for prediction of interaction strengths but their accuracy is generally unsatisfactory. This study demonstrates an evolutionary programming approach to uncover non-linear relations among process variables. In this study, we make an attempt to use genetic programming (GP) based approach for this purpose. GP overcomes many shortcomings faced by other statistical or evolutionary techniques in this context. The effectiveness, feasibility, and robustness of the proposed method are demonstrated on simulated data emanating from a well-known Tennessee Eastman process. The proposed method has successfully achieved reasonable detection and prediction of non-linear interaction patterns among process variables.     

Mu-based trajectory tracking control for a quad-rotor UAV

In this paper, the design and application of a robust mu-synthesis-based controller for quad-rotor trajectory tracking are presented. The proposed design approach guarantees robust performance over a weakly nonlinear range of operation of the quad-rotor, which is a practical range that suits various applications. The controller considers different structured and unstructured uncertainties, such as unmodeled dynamics and perturbation in the parameters. The controller also provides robustness against external disturbances such as wind gusts and wind turbulence. The proposed controller is fixed and linear; therefore, it has a very low computational cost. Moreover, the controller meets all design specifications without tuning. To validate this control strategy, the proposed approach is compared to a linear quadratic regulator (LQR) controller using a high- fidelity quad-rotor simulation environment. In addition, the experimental results presented show the validity of the proposed control strategy.     

Engineering design of green hybrid energy production and supply chains

There is a national and international move towards green energy production and supply chains. This requires a systematic engineering design approach that enables government and private energy producers and agents to design and operate the target green hybrid energy production chains in flexible and optimized manner. This research paper presents analytical view and process modeling and engineering design framework to design and evaluate green hybrid energy production / supply chains. Process models are constructed on the basis of process object oriented modeling methodology, or POOM. Performance indicators are evaluated in different hierarchical levels using risk-based life cycle and environmental assessment framework, which is essential to evaluate different energy production chain scenarios based on risk and environmental perspectives. Case study is illustrated to explain the proposed engineering design of energy production chains, which is evaluated using developed computer-aided process engineering environment.     

AutoRWN: automatic construction and training of random weight networks using competitive swarm of agents

Neural Computing and Applications - Random Weight Networks have been extensively used in many applications in the last decade because it has many strong features such as fast learning and good...     

Efficient deployment of wireless sensor networks targeting environment monitoring applications

Maximizing network connectivity while maintaining a useful lifetime period without exceeding cost constraints is a challenging design objective for wireless sensor networks. Satisfying such objective becomes even a more intricate task with 3-D setups and harsh operational conditions found in typical large scale environment monitoring applications. While much work has been performed in environment monitoring, only few have addressed the unique characteristics of such applications. In this paper, we introduce a novel 3-D deployment strategy, called Optimized 3-D deployment with Lifetime Constraint (O3DwLC), for relay nodes in environmental applications. The strategy optimizes network connectivity, while guarantying specific network lifetime and limited cost. Key to our contribution is a very limited search space for the optimization problem, in addition to a revised definition for network lifetime that is more appropriate in environment monitoring. The effectiveness of our strategy is validated through extensive simulations and comparisons, assuming practical considerations of signal propagation and connectivity.     

Effect of humidity on nanoparticle-based chemiresistors: a comparison between synthetic and real-world samples

Chemiresistors based on metal monolayer-capped nanoparticles (MCNPs) are promising candidates for fast, inexpensive, and portable tracing of (bio)chemical species in the gas phase. However, the sensitivity of such sensors to humidity is problematic, limiting their reliable and reproducible application in real-world environmental conditions. In this work, we employed a compensation method to explore the effect of humidity on a single MCNP chemiresistor as well as on an array of MCNP sensors used to analyze either synthetic or real-world samples. We show that an array of MCNP chemiresistors is able to precisely detect and estimate subtle concentrations of (mixtures of) volatile organic compounds (VOCs) under variable backgrounds of 2-83% relative humidity (RH) only after humidity compensation. Humidity effects were also tested in two clinical trials aimed at detecting prostate cancer and breast cancer through exhaled breath analysis. Analysis of the results showed improved cancer detection capabilities as a result of RH compensation, though less substantial than the impact of RH compensation on synthetic samples. This outcome is attributed to one - or a combination - of the following effects: (i) the RH variance was smaller in the breath samples than that in the synthetic samples; (ii) the VOC composition in the breath samples is less controlled than the synthetic samples; and (iii) the responses to small polar VOCs and water are not necessarily additive in breath samples. Ultimately, the results presented here could assist the development of a cost-effective, low-power method for widespread detection of VOCs in real-world applications, such as breath analysis, as well as for environmental, security, and food applications.     

Building identity-based security associations for provider-provisioned virtual private networks

Provider-provisioned virtual private networks are nowadays well-established networking concepts. They are envisaged as an extension of the basic VPN concept to securely network low-capacity nodes in large-scale personal networks, with the help of network providers. This article presents an adaptation of the Internet Key Exchange (IKEv2) protocol to the context of dynamic tunneling in personal networks. It relies on the providers’ infrastructure to build identity-based security associations. Results of a preliminary security analysis are also provided.