An isogeometrical approach to structural topology optimization by optimality criteria

The Isogeometric Analysis (IA) method is applied for structural topology optimization instead of finite elements. For this purpose, a control point based Solid Isotropic Material with Penalization (SIMP) method is employed and the material density is considered as a continuous function throughout the design domain and approximated by the Non-Uniform Rational B-Spline (NURBS) basis functions. To prevent the formation of layouts with porous media, a penalization technique similar to the SIMP method is used. For optimization an optimality criteria is derived and implemented. A few examples are presented to demonstrate the performance of the method. It is shown that, dissimilar to the element based SIMP topology optimization, the resulted layouts by this method are independent of the number of the discretizing control points and checkerboard free.     

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Theoretical and experimental analyses of rheological,compatibility and mechanical properties of PVMQ/XNBR-g GMA/XNBR/GO ternary hybrid nanocomposites

Iranian Polymer Journal - Effects of graphene oxide (GO) on various properties of rubber hybrid nanocomposites based on PVMQ/XNBR-g-GMA/XNBR (phenyl-vinyl-methyl-polysiloxane/carboxylated nitrile...     

Toward A Mechanistic Understanding of Re-Infiltration in Naturally Fractured Reservoirs with Surfactant-Aided Gravity Drainage Process

Surfactant-aided gravity drainage is an improved oil recovery technique for water-invaded zone in fractured carbonate reservoirs, which are mostly oil-wet or mixed-wet rocks. The re-infiltration mechanism in water-invaded zone has a considerable effect on oil vertical movement in gravity drainage processes. In this work, a mechanistic understanding of re-infiltration in surfactant-aided gravity drainage, in comparison to oil–water gravity drainage is presented using an experimentally and numerically validated model. A column model is constructed from three matrix blocks. These blocks are separated from each other by horizontal fractures. A storage tank is considered on top of the model to store depleted oil from matrix blocks. The stacked-blocks model for re-infiltration is validated and verified to simulate water and chemical flooding using a mesh independency study and experimental flooding data in a composite core experiment. Using this model, several analyses are performed to investigate effects of rock and fluid properties, rock saturation functions, wettability alteration, surfactant adsorption, and capillary continuity on re-infiltration.     

Noncertainty equivalent adaptive control of robot manipulators without velocity measurements

This paper presents a noncertainty equivalent adaptive motion control scheme for robot manipulators in the absence of link velocity measurements. A new output feedback adaptation algorithm, based on the attractive manifold design approach, is developed. A proportional-integral adaptation is selected for the adaptive parameter estimator to strengthen the passivity of the system. In order to relieve velocity measurements, an observer is designed to estimate the velocities. The controller guarantees semiglobal asymptotic motion tracking and velocity estimation, as well as L_∞ and L₂ bounded parameter estimation error. The effectiveness of the proposed controller is verified by simulations for a two-link robot manipulator and a four-bar linkage. The results are further compared with the earlier certainty-equivalent adaptive partial and full state feedback controller to highlight potential closed-loop performance improvements.     

Precautious-RM: a predictable non-preemptive scheduling algorithm for harmonic tasks

A major requirement of many real-time embedded systems is to have time-predictable interaction with the environment. More specifically, they need fixed or small sampling and I/O delays, and they cannot cope with large delay jitters. Non-preemptive execution is a known method to reduce the latter delay; however, the corresponding scheduling problem is NP-Hard for periodic tasks. In this paper, we present Precautious-RM as a predictable linear-time online non-preemptive scheduling algorithm for harmonic tasks which can also deal with the former delay, namely sampling delay. We derive conditions of optimality of Precautious-RM and show that satisfying those conditions, tight bounds for best- and worst-case response times of the tasks can be calculated in polynomial-time. More importantly, response time jitter of the tasks is analyzed and it is proven that under specific conditions, each task has either one or two values for response time, which leads to improving the predictability of the system interaction with the environment. Simulation results demonstrate efficiency of Precautious-RM in increasing accuracy of control applications.     

Predicting roadheader performance by using artificial neural network

With growing use of roadheaders in the world and its significant role in the successful accomplishment of a tunneling project, it is a necessity to accurately predict performance of this machine in different ground conditions. On the other hand, the existence of some shortcomings in the prediction models has made it necessary to perform more research on the development of the new models. This paper makes an attempt to model the rate of roadheader performance based on the geotechnical and geological site conditions. For achieving the aim, an artificial neural network (ANN), a powerful tool for modeling and recognizing the sophisticated structures involved in data, is employed to model the relationship between the roadheader performance and the parameters influencing the tunneling operations with a high correlation. The database used in modeling is compiled from laboratory studies conducted at Azad University at Science and Research Branch, Tehran, Iran. A model with architecture 4-10-1 trained by back-propagation algorithm is found to be optimum. A multiple variable regression (MVR) analysis is also applied to compare performance of the neural network. The results demonstrate that predictive capability of the ANN model is better than that of the MVR model. It is concluded that roadheader performance could be accurately predicted as a function of unconfined compressive strength, Brazilian tensile strength, rock quality designation, and alpha angle R ² = 0.987. Sensitivity analysis reveals that the most effective parameter on roadheader performance is the unconfined compressive strength.     

Mechanical properties of composites from sawdust and recycled plastics

Mechanical properties of wood plastic composites (WPCs) manufactured from sawdust and virgin and/or recycled plastics, namely high density polyethylene (HDPE) and polypropylene (PP), were studied. Sawdust was prepared from beech industrial sawdust by screening to the desired particle size and was mixed with different virgin or recycled plastics at 50% by weight fiber loading. The mixed materials were then compression molded into panels. Flexural and tensile properties and impact strength of the manufactured WPCs were determined according to the relevant standard specifications. Although composites containing PP (virgin and recycled) exhibited higher stiffness and strength than those made from HDPE (virgin and recycled), they had lower unnotched impact strengths. Mechanical properties of specimens containing recycled plastics (HDPE and PP) were statistically similar and comparable to those of composites made from virgin plastics. This was considered as a possibility to expand the use of recycled plastics in the manufacture of WPCs. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 3641–3645, 2006     

Static and dynamic mechanical properties of a kenaf fiber–wood flour/polypropylene hybrid composite

A natural fiber hybrid composite containing equal proportions of kenaf fibers (KFs) and wood flour (WF) as the reinforcements and polypropylene (PP) as the polymer matrix was prepared, and its static and dynamic mechanical properties were compared with KF/PP and WF/PP composites. Static tensile and flexural tests and dynamic mechanical analysis (DMA) were carried out. The hybrid composite exhibited tensile and flexural moduli and strength values closer to those of the KF composite, which indicated a higher reinforcing efficiency of KFs compared with WF. DMA revealed that although the glass‐transition temperature remained unchanged by the replacement of half of the WF by KFs, the α‐transition temperature of the hybrid composite was identical to that of WF composite. The magnitudes of both the α and β (glass) transitions of the hybrid composite were comparable to that of the WF/PP composite. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 98: 665–672, 2005     

Biclustering meets triadic concept analysis

Biclustering numerical data became a popular data-mining task at the beginning of 2000’s, especially for gene expression data analysis and recommender systems. A bicluster reflects a strong association between a subset of objects and a subset of attributes in a numerical object/attribute data-table. So-called biclusters of similar values can be thought as maximal sub-tables with close values. Only few methods address a complete, correct and non-redundant enumeration of such patterns, a well-known intractable problem, while no formal framework exists. We introduce important links between biclustering and Formal Concept Analysis (FCA). Indeed, FCA is known to be, among others, a methodology for biclustering binary data. Handling numerical data is not direct, and we argue that Triadic Concept Analysis (TCA), the extension of FCA to ternary relations, provides a powerful mathematical and algorithmic framework for biclustering numerical data. We discuss hence both theoretical and computational aspects on biclustering numerical data with triadic concept analysis. These results also scale to n-dimensional numerical datasets.