Adaptive spacetime discontinuous Galerkin method for hyperbolic advection–diffusion with a non‐negativity constraint

Applications where the diffusive and advective time scales are of similar order give rise to advection–diffusion phenomena that are inconsistent with the predictions of parabolic Fickian diffusion models. Non‐Fickian diffusion relations can capture these phenomena and remedy the paradox of infinite propagation speeds in Fickian models. In this work, we implement a modified, frame‐invariant form of Cattaneo's hyperbolic diffusion relation within a spacetime discontinuous Galerkin advection–diffusion model. An h‐adaptive spacetime meshing procedure supports an asynchronous, patch‐by‐patch solution procedure with linear computational complexity in the number of spacetime elements. This localized solver enables the selective application of optimization algorithms in only those patches that require inequality constraints to ensure a non‐negative concentration solution. In contrast to some previous methods, we do not modify the numerical fluxes to enforce non‐negative concentrations. Thus, the element‐wise conservation properties that are intrinsic to discontinuous Galerkin models are defined with respect to physically meaningful Riemann fluxes on the element boundaries. We present numerical examples that demonstrate the effectiveness of the proposed model, and we explore the distinct features of hyperbolic advection–diffusion response in subcritical and supercritical flows. Copyright © 2015 John Wiley & Sons, Ltd.     

On the Effect of Measurement Error with Linearly Increasing‐Type Variance on Simultaneous Monitoring of Process Mean and Variability

In most quality control applications, the errors generated from measurement system can adversely affect the ability of control charts in detecting out‐of‐control conditions. In this paper, the effect of measurement error with linearly increasing‐type variance on the performance of maximum exponentially weighted moving average and mean‐squared deviation (MAX‐EWMAMS) control chart is studied. For this purpose, different out‐of‐control scenarios including mean shifts, variance shifts, and simultaneous shifts in both are considered, and the detecting performance of the proposed approach is investigated through simulation study. The results of simulation study in terms of three criteria including average run length, standard deviation of run lengths, and the empirical distribution of run lengths prove that the measurement error with linearly increasing‐type variance can adversely affect the performance of MAX‐EWMAMS control. Copyright © 2015 John Wiley & Sons, Ltd.     

An efficient numerical method for analyzing the thermal effects on the vibration of embedded single-walled carbon nanotubes based on the nonlocal shell model

Employing the variational differential quadrature (VDQ) method, the effects of initial thermal loading on the vibrational behavior of embedded single-walled carbon nanotubes (SWCNTs) based on the nonlocal shell model are studied. According to the first-order shear deformation theory and considering Eringen's nonlocal elasticity theory, the energy functionality of the system is presented and discretized using the VDQ method. The effects of thermal loading and elastic foundation are simultaneously taken into account. The use of the numerical discretization technique in the context of variational formulation reduces the order of differentiation in the governing equations and consequently improves the convergence rate. The accuracy of the present model is first checked by comparison with molecular dynamics simulation results and those of other methods. The effects of involved parameters are then investigated on the fundamental frequencies of thermally preloaded embedded SWCNTs. The results imply that the thermal loading has a significant effect on the vibration analysis of embedded SWCNTs.     

Vibration analysis of parabolic shear-deformable piezoelectrically actuated nanoscale beams incorporating thermal effects

Thermoelectric-mechanical vibration behavior of functionally graded piezoelectric (FGP) nanobeams is first investigated in this article, based on the nonlocal theory and third-order parabolic beam theory by presenting a Navier-type solution. Electro-thermo-mechanical properties of a nanobeam are supposed to change continuously throughout the thickness based on the power-law model. To capture the small-size effects, Eringen's nonlocal elasticity theory is adopted. Using Hamilton's principle, the nonlocal governing equations for the third-order, shear deformable, piezoelectric, FG nanobeams are obtained and they are solved applying an analytical solution. By presenting some numerical results, it is demonstrated that the suggested model presents accurate frequency results of FGP nanobeams. The influences of several parameters, including external electric voltage, power-law exponent, nonlocal parameter, and mode number on the natural frequencies of the size-dependent FGP nanobeams are discussed in detail. The results should be relevant to the design and application of the piezoelectric nanodevices.     

The role of thermal residual stress on the yielding behavior of carbon nanotube–aluminum nanocomposites

The initial yield envelopes of aluminum (Al) nanocomposites reinforced with carbon nanotubes (CNTs) subjected to biaxial loading are predicted in the presence of thermal residual stress (TRS) arising from the manufacturing process. Micromechanical model based on the unit cell method is presented to generate the yielding surfaces. The formation of the interphase caused by the interfacial reaction between the CNT and Al matrix is taken into account in the analysis. The effects of several important parameters, i.e. the change of temperature, CNT volume fraction, interphase thickness and Al material properties on the yielding onset of the CNT/Al nanocomposite are explored extensively. The results clearly reveal that the initial yield surfaces of nanocomposite are dependent on the TRS. Also, the interphase has a significant influence on the yielding behavior of Al nanocomposite in the presence of TRS. The results demonstrate that the size of initial yield surfaces become minimum with considering the coupled effects of TRS and interphase. With increasing the temperature variation, interphase thickness, elastic modulus and coefficient of thermal expansion of Al matrix, the size of initial yield surfaces reduces. The present study is consequential for understanding the key role of TRS on the initial damage of CNT/Al nanocomposites.     

Finite-time stability and stabilisation for a class of nonlinear systems with time-varying delay

This paper is concerned with the problems of finite-time stability (FTS) and finite-time stabilisation for a class of nonlinear systems with time-varying delay, which can be represented by Takagi–Sugeno fuzzy system. Some new delay-dependent FTS conditions are provided and applied to the design problem of finite-time fuzzy controllers. First, based on an integral inequality and a fuzzy Lyapunov–Krasovskii functional, a delay-dependent FTS criterion is proposed for open-loop fuzzy system by introducing some free fuzzy weighting matrices, which are less conservative than other existing ones. Then, the parallel distributed compensation controller is designed to ensure FTS of the time-delay fuzzy system. Finally, an example is given to illustrate the effectiveness of the proposed design approach.     

Multi-objective approach for robot motion planning in search tasks

This work addresses the problem of single robot coverage and exploration in an environment with the goal of finding a specific object previously known to the robot. As limited time is a constraint of interest we cannot search from an infinite number of points. Thus, we propose a multi-objective approach for such search tasks in which we first search for a good set of positions to place the robot sensors in order to acquire information from the environment and to locate the desired object. Given the interesting properties of the Generalized Voronoi Diagram, we restrict the candidate search points along this roadmap. We redefine the problem of finding these search points as a multi-objective optimization one. NSGA-II is used as the search engine and ELECTRE I is applied as a decision making tool to decide among the trade-off alternatives. We also solve a Chinese Postman Problem to optimize the path followed by the robot in order to visit the computed search points. Simulation results show a comparison between the solution found by our method and solutions defined by other known approaches. Finally, a real robot experiment indicates the applicability of our method in practical scenarios.     

Scalable graph-based OLAP analytics over process execution data

In today’s knowledge-, service-, and cloud-based economy, businesses accumulate massive amounts of data from a variety of sources. In order to understand businesses one may need to perform considerable analytics over large hybrid collections of heterogeneous and partially unstructured data that is captured related to the process execution. This data, usually modeled as graphs, increasingly come to show all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics. We use the term big process graph to refer to such large hybrid collections of heterogeneous and partially unstructured process related execution data. Online analytical processing (OLAP) of big process graph is challenging as the extension of existing OLAP techniques to analysis of graphs is not straightforward. Moreover, process data analysis methods should be capable of processing and querying large amount of data effectively and efficiently, and therefore have to be able to scale well with the infrastructure’s scale. While traditional analytics solutions (relational DBs, data warehouses and OLAP), do a great job in collecting data and providing answers on known questions, key business insights remain hidden in the interactions among objects: it will be hard to discover concept hierarchies for entities based on both data objects and their interactions in process graphs. In this paper, we introduce a framework and a set of methods to support scalable graph-based OLAP analytics over process execution data. The goal is to facilitate the analytics over big process graph through summarizing the process graph and providing multiple views at different granularity. To achieve this goal, we present a model for process OLAP (P-OLAP) and define OLAP specific abstractions in process context such as process cubes, dimensions, and cells. We present a MapReduce-based graph processing engine, to support big data analytics over process graphs. We have implemented the P-OLAP framework and integrated it into our existing process data analytics platform, ProcessAtlas, which introduces a scalable architecture for querying, exploration and analysis of large process data. We report on experiments performed on both synthetic and real-world datasets that show the viability and efficiency of the approach.     

Semi fractal three leaf clover‐shaped CPW antenna for triple band operation

This article presents a unique and compact coplanar waveguide (CPW) antenna that exhibits triband operation with circular polarization. The single antenna was designed to operate simultaneously in the following bands: WiMAX (3.3–3.6 GHz), wireless local area network (WLAN) (5.15–5.825 GHz), ITS (5.795–6.400 GHz), and ITU‐R (7.725–8.5 GHz). The realization of the triband antenna was achieved by using two semi fractal ring patches resembling the shape of a three leaf clover, and by introducing a pair of symmetrical L‐shaped slits in its ground plane. The antenna's physical parameters were investigated to fully understand their affect on the antenna's performance. The salient parameters obtained from this analysis enabled the optimization of the antenna's overall characteristics. The design concept was confirmed by fabricating the antenna prototype and measuring its characteristics. The proposed antenna has dimensions of 20 × 20 × 1 mm³. Measured results show the antenna exhibits circular polarization in WiMAX and ITU‐R bands, and linear polarization in the WLAN band. The antenna radiates omnidirectionally in the H‐plane, and approximately bidirectionally in the E‐plane. In addition, the antenna presents stable gain over the triband. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:413–418, 2015.     

Quantized Filtering for Continuous‐Time Markovian Jump Systems with Deficient Mode Information

This paper investigates the problem of quantized filtering for a class of continuous‐time Markovian jump linear systems with deficient mode information. The measurement output of the plant is quantized by a mode‐dependent logarithmic quantizer, and the deficient mode information in the Markov stochastic process simultaneously considers the exactly known, partially unknown, and uncertain transition rates. By fully exploiting the properties of transition rate matrices, together with the convexification of uncertain domains, a new sufficient condition for quantized performance analysis is first derived, and then two approaches, namely, the convex linearization approach and iterative approach, to the filter synthesis are developed. It is shown that both the full‐order and reduced‐order filters can be obtained by solving a set of linear matrix inequalities (LMIs) or bilinear matrix inequalities (BMIs). Finally, two illustrative examples are given to show the effectiveness and less conservatism of the proposed design methods.