Mathematical Problems in Engineering The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line Thu, 08 Dec 2016 10:19:02 +0000 The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system. Xiaobing Ding, Xuechen Yang, Hua Hu, Zhigang Liu, and Hanchuan Pan Copyright © 2016 Xiaobing Ding et al. All rights reserved. Adaptive Chaos Synchronization Control of Nonlinear PMSM System Using Extended State Observer Thu, 08 Dec 2016 08:45:38 +0000 This paper proposes an adaptive chaos synchronization control scheme for nonlinear permanent magnet synchronous motor (PMSM) systems by using extended state observer (ESO). Frist of all, a chaotic PMSM system is built through an affine transformation and a time scale transformation of the mathematical PMSM model. Then, an adaptive sliding mode controller is developed based on the extended state observer to achieve the synchronization performance of two chaotic PMSM systems. Moreover, an adaptive parameter law of the control gain is designed to reduce the chattering problem existing in the traditional sliding mode control. Finally, the effectiveness of the proposed method is verified by simulation results. Zijing Cheng, Guangyue Xue, Chong Wang, and Qiang Chen Copyright © 2016 Zijing Cheng et al. All rights reserved. Moments of Distance from a Vertex to a Uniformly Distributed Random Point within Arbitrary Triangles Thu, 08 Dec 2016 08:00:43 +0000 We study the cumulative distribution function (CDF), probability density function (PDF), and moments of distance between a given vertex and a uniformly distributed random point within a triangle in this work. Based on a computational technique that helps us provide unified formulae of the CDF and PDF for this random distance then we compute its moments of arbitrary orders, based on which the variance and standard deviation can be easily derived. We conduct Monte Carlo simulations under various conditions to check the validity of our theoretical derivations. Our method can be adapted to study the random distances sampled from arbitrary polygons by decomposing them into triangles. Hongjun Li and Xing Qiu Copyright © 2016 Hongjun Li and Xing Qiu. All rights reserved. Compound Control Strategy for MDF Continuous Hot Pressing Electrohydraulic Servo System with Uncertainties and Input Saturation Thu, 08 Dec 2016 07:34:27 +0000 A compound control strategy is investigated for Medium Density Fiberboard (MDF) continuous hot pressing electrohydraulic servo system (EHSS) with uncertainties and input saturation. Firstly, a hyperbolic tangent function is applied to approximate saturation nonlinearity in the system. And thus the mathematical model is continuous and differentiable. Subsequently, the slab thickness tracking controller is constructed by using a dynamic surface control (DSC) method, which introduces first-order low-pass filters to calculate derivatives of virtual control input in each step. Compared with the conventional backstepping controller, complexity of the design procedure is alleviated obviously. Moreover, a composite disturbance of uncertainties and input saturation is estimated by a nonlinear disturbance observer for compensation of the control law. Finally, an appropriate Lyapunov function is chosen to prove that all signals of the closed-loop system are semiglobally uniformly ultimately bounded and the tracking error converges to zero asymptotically. Numerical simulation results are also exhibited to authenticate and validate the benefits of the proposed control scheme. Zhu Liang-kuan, Wang Zi-bo, and Liu Ya-qiu Copyright © 2016 Zhu Liang-kuan et al. All rights reserved. Study on Transition of Primary Energy Structure and Carbon Emission Reduction Targets in China Based on Markov Chain Model and GM (1, 1) Wed, 07 Dec 2016 13:17:17 +0000 The improvement of the primary energy structure has been considered as one of the important measures to achieve the carbon emissions reduction targets in China. This current paper constructed a Markov chain model, which was used to forecast the transition of primary energy structure. GM (1, 1) model and a linear regression model were used to predict the total energy consumption in 2020 and 2030. Then, the CO2 emissions intensity was calculated, and the realization of carbon emissions reduction targets in China was analyzed. The findings indicated that (1) China’s nonfossil energy share in primary energy cannot be achieved naturally. (2) Part of the carbon emissions intensity in China’s commitments was not binding actually. (3) The realization of the carbon emissions peak and the reduction target of carbon emissions intensity in 2030 would need the policy intervention. In the last part of this paper, policy recommendations on carbon emissions reduction in China were provided. Feng Ren and Lihong Gu Copyright © 2016 Feng Ren and Lihong Gu. All rights reserved. Rolling Element Bearing Fault Diagnosis Using Integrated Nonlocal Means Denoising with Modified Morphology Filter Operators Wed, 07 Dec 2016 11:59:50 +0000 The impulses in vibration signals are used to identify faults in the bearings of rotating machinery. However, vibration signals are usually contaminated by noise that makes the process of extracting impulse characteristic of localized defect very challenging. In order to effectively diagnose bearing with noise masking vibration signal, a new methodology is proposed using integrated (i) nonlocal means- (NLM-) based denoising and (ii) improved morphological filter operators. NLM based denoising is first employed to eliminate or reduce the background noise with minimal signal distortion. This denoised signal is then analysed by a proposed modified morphological analysis (MMA). The MMA analysis introduces a new morphological operator which is based on Modified-Different (DIF) filter to include only fault relevant impulsive characteristics of the vibration signal. To improve further performance of the methodology the length of the structure element (SE) used in MMA is optimized using a particle swarm optimization- (PSO-) based kurtosis criterion. The results of simulated and real vibration signal show that the integrated NLM with MMA method as well as the MMA method alone yields superior performance in extracting impulsive characteristics of vibrations signals, especially for signal with high level of noise or presence of other sources masking the fault. Mien Van, Pasquale Franciosa, and Dariusz Ceglarek Copyright © 2016 Mien Van et al. All rights reserved. Sensor Placement via Optimal Experiment Design in EMI Sensing of Metallic Objects Wed, 07 Dec 2016 10:09:56 +0000 This work, under the optimal experimental design framework, investigates the sensor placement problem that aims to guide electromagnetic induction (EMI) sensing of multiple objects. We use the linearized model covariance matrix as a measure of estimation error to present a sequential experimental design (SED) technique. The technique recursively minimizes data misfit to update model parameters and maximizes an information gain function for a future survey relative to previous surveys. The fundamental process of the SED seeks to increase weighted sensitivities to targets when placing sensors. The synthetic and field experiments demonstrate that SED can be used to guide the sensing process for an effective interrogation. It also can serve as a theoretic basis to improve empirical survey operation. We further study the sensitivity of the SED to the number of objects within the sensing range. The tests suggest that an appropriately overrepresented model about expected anomalies might be a feasible choice. Lin-Ping Song, Leonard R. Pasion, Nicolas Lhomme, and Douglas W. Oldenburg Copyright © 2016 Lin-Ping Song et al. All rights reserved. Influence of Climate Change in Reliability Analysis of High Rise Building Wed, 07 Dec 2016 06:55:10 +0000 The safety of designed urban structures is highly depending on the respond of structures to different types and magnitude of environmental loads. The safety assessment of an existing building needs to have a full consideration of all the environmental factors. Therefore, the engineers must realize the importance of the environment and take care of all the assumptions and uncertainties. One of the hot topics that researchers nowadays are interested is the influence of climate change to the engineering designs. There is a remarkable consensus in the scientific community telling us a fact that our climate is changing and engineering design failures are increasing. In this paper, we are going to have an investigation of the effect of the climate change to the safety of high rise building. The climate effects are briefly discussed at the first beginning of this paper. Then a detailed study is performed on the modeling of climate effects for the wind load. This is later utilized in a structural reliability analysis for a high rise building. The influence of climate effects to the overall safety of a building is investigated and discussed based on the analyzed results. It was found the influence of climate effect can be very significant in the design of high rise buildings. Yi Zhang, Keqin Yan, Tao Cheng, Quan Zhou, Liping Qin, and Shan Wang Copyright © 2016 Yi Zhang et al. All rights reserved. Prediction Model of Coating Growth Rate for Varied Dip-Angle Spraying Based on Gaussian Sum Model Tue, 06 Dec 2016 11:58:59 +0000 In automatic spraying of spray painting robot, in order to solve the problems of coating growth rate modeling for varied dip-angle spraying technology, a prediction mode of coating growth rate using the Gaussian sum model is proposed. Based on the Gaussian sum model, a theoretical model for coating growth rate with varied dip-angle spraying is established by using the theory of differential geometry. The coating thickness of the sample points in the distribution range of the coating was obtained by making the experiment of varied dip-angle spraying. Based on the theoretical model, the nonlinear least square method is used to fit the coating thickness of the sample points and the parameter values of the theoretical model are calculated. By analyzing the variation law of the parameters with the spray dip-angle, the prediction model of coating growth rate for varied dip-angle spraying is established. Experiments have shown that the prediction model has good fitting precision; it can satisfy the real-time requirement with varied dip-angle spraying trajectory planning in the offline programming system. Yong Zeng, Yakun Zhang, Junxue He, Hai Zhou, Chunwei Zhang, and Lei Zheng Copyright © 2016 Yong Zeng et al. All rights reserved. Analytical Modeling of a Ball Screw Feed Drive for Vibration Prediction of Feeding Carriage of a Spindle Tue, 06 Dec 2016 11:26:46 +0000 An analytical modeling approach for ball screw feed drives is proposed to predict the dynamic behavior of the feeding carriage of a spindle. Mainly considering the rigidity of linear guide modules, a ball-screw-feeding spindle is modeled by a mass-spring system. The contact stiffness of rolling interfaces in linear guide modules is accurately calculated according to the Hertzian theory. Next, a mathematical model is derived using the Lagrange method. The presented model is verified by conducting modal experiments. It is found that the simulated results correspond closely with the experimental data. In order to show the applicability of the proposed mathematical model, parameter-dependent dynamics of the feeding carriage of the spindle is investigated. The work will contribute to the vibration prediction of spindles. Lei Zhang, Taiyong Wang, Songling Tian, and Yong Wang Copyright © 2016 Lei Zhang et al. All rights reserved. A New Approach for Chaotic Time Series Prediction Using Recurrent Neural Network Tue, 06 Dec 2016 09:42:42 +0000 A self-constructing fuzzy neural network (SCFNN) has been successfully used for chaotic time series prediction in the literature. In this paper, we propose the strategy of adding a recurrent path in each node of the hidden layer of SCFNN, resulting in a self-constructing recurrent fuzzy neural network (SCRFNN). This novel network does not increase complexity in fuzzy inference or learning process. Specifically, the structure learning is based on partition of the input space, and the parameter learning is based on the supervised gradient descent method using a delta adaptation law. This novel network can also be applied for chaotic time series prediction including Logistic and Henon time series. More significantly, it features rapider convergence and higher prediction accuracy. Qinghai Li and Rui-Chang Lin Copyright © 2016 Qinghai Li and Rui-Chang Lin. All rights reserved. Assessment of Groundwater Potential Based on Multicriteria Decision Making Model and Decision Tree Algorithms Tue, 06 Dec 2016 08:55:44 +0000 Groundwater plays an important role in global climate change and satisfying human needs. In the study, RS (remote sensing) and GIS (geographic information system) were utilized to generate five thematic layers, lithology, lineament density, topology, slope, and river density considered as factors influencing the groundwater potential. Then, the multicriteria decision model (MCDM) was integrated with C5.0 and CART, respectively, to generate the decision tree with 80 surveyed tube wells divided into four classes on the basis of the yield. To test the precision of the decision tree algorithms, the 10-fold cross validation and kappa coefficient were adopted and the average kappa coefficient for C5.0 and CART was 90.45% and 85.09%, respectively. After applying the decision tree to the whole study area, four classes of groundwater potential zones were demarcated. According to the classification result, the four grades of groundwater potential zones, “very good,” “good,” “moderate,” and “poor,” occupy 4.61%, 8.58%, 26.59%, and 60.23%, respectively, with C5.0 algorithm, while occupying the percentages of 4.68%, 10.09%, 26.10%, and 59.13%, respectively, with CART algorithm. Therefore, we can draw the conclusion that C5.0 algorithm is more appropriate than CART for the groundwater potential zone prediction. Huajie Duan, Zhengdong Deng, Feifan Deng, and Daqing Wang Copyright © 2016 Huajie Duan et al. All rights reserved. An Ultra-Low Frequency Two DOFs’ Vibration Isolator Using Positive and Negative Stiffness in Parallel Tue, 06 Dec 2016 07:25:58 +0000 With the improvement of performance in the ultra-precision manufacturing engineering, the requirements for vibration isolation have become increasingly stringent. In order to get wider effective bandwidth and higher performance of vibration isolation in multiple DOFs system, an ultra-low frequency two DOFs’ vibration isolator with positive and negative stiffness in parallel (PNSP) is proposed. The two DOFs’ isolator which combines a positive stiffness (PS) air spring with a negative stiffness (NS) magnetic spring in parallel and combines a PS flat spring with an NS inverted pendulum in parallel is designed to reduce the natural frequency and broaden the effective bandwidth in horizontal and vertical direction. Based on this structure, stiffness models of different components in different directions are established. Compared with a PS isolator, it possesses the characteristic of high-static-low-dynamic stiffness. The simulation curves also provide strong evidence. Last, a real-time active control system and a spectrum testing and analysis system are used for the contrast experiment between the mentioned PNSP structure and PS only. The experimental results demonstrate that the isolator with PNSP can obviously reduce the natural frequency to 1 Hz and simultaneously maintain the stability of the system and consequently verify the validity and superiority of the mentioned structure. Min Wang, Xuedong Chen, and Xiaoqing Li Copyright © 2016 Min Wang et al. All rights reserved. Efficient Community Detection in Heterogeneous Social Networks Mon, 05 Dec 2016 16:00:47 +0000 Community detection is of great importance which enables us to understand the network structure and promotes many real-world applications such as recommendation systems. The heterogeneous social networks, which contain multiple social relations and various user generated content, make the community detection problem more complicated. Particularly, social relations and user generated content are regarded as link information and content information, respectively. Since the two types of information indicate a common community structure from different perspectives, it is better to mine them jointly to improve the detection accuracy. Some detection algorithms utilizing both link and content information have been developed. However, most works take the private community structure of a single data source as the common one, and some methods take extra time transforming the content data into link data compared with mining directly. In this paper, we propose a framework based on regularized joint nonnegative matrix factorization (RJNMF) to utilize link and content information jointly to enhance the community detection accuracy. In the framework, we develop joint NMF to analyze link and content information simultaneously and introduce regularization to obtain the common community structure directly. Experimental results on real-world datasets show the effectiveness of our method. Zhen Li, Zhisong Pan, Yanyan Zhang, Guopeng Li, and Guyu Hu Copyright © 2016 Zhen Li et al. All rights reserved. Forecasting Water Demand in Residential, Commercial, and Industrial Zones in Bogotá, Colombia, Using Least-Squares Support Vector Machines Mon, 05 Dec 2016 12:40:50 +0000 The Colombian capital, Bogotá, has undergone massive growth in a short period of time. Naturally, this growth has increased the city’s water demand. The prediction of this demand will help understand and analyze consumption behavior, thereby allowing for effective management of the urban water cycle. This paper uses the Least-Squares Support Vector Machines (LS-SVM) model for forecasting residential, industrial, and commercial water demand in the city of Bogotá. The parameters involved in this study include the following: monthly water demand, number of users, and total water consumption bills (price) for the three studied uses. Results provide evidence of the model’s accuracy, producing between 0.8 and 0.98, with an error percentage under 12%. Carlos Peña-Guzmán, Joaquín Melgarejo, and Daniel Prats Copyright © 2016 Carlos Peña-Guzmán et al. All rights reserved. Fractional Calculus-Based Modeling of Electromagnetic Field Propagation in Arbitrary Biological Tissue Mon, 05 Dec 2016 12:38:18 +0000 The interaction of electromagnetic fields and biological tissues has become a topic of increasing interest for new research activities in bioelectrics, a new interdisciplinary field combining knowledge of electromagnetic theory, modeling, and simulations, physics, material science, cell biology, and medicine. In particular, the feasibility of pulsed electromagnetic fields in RF and mm-wave frequency range has been investigated with the objective to discover new noninvasive techniques in healthcare. The aim of this contribution is to illustrate a novel Finite-Difference Time-Domain (FDTD) scheme for simulating electromagnetic pulse propagation in arbitrary dispersive biological media. The proposed method is based on the fractional calculus theory and a general series expansion of the permittivity function. The spatial dispersion effects are taken into account, too. The resulting formulation is explicit, it has a second-order accuracy, and the need for additional storage variables is minimal. The comparison between simulation results and those evaluated by using an analytical method based on the Fourier transformation demonstrates the accuracy and effectiveness of the developed FDTD model. Five numerical examples showing the plane wave propagation in a variety of dispersive media are examined. Pietro Bia, Luciano Mescia, and Diego Caratelli Copyright © 2016 Pietro Bia et al. All rights reserved. Modified Fire Simulation Curve of Cabin Temperatures in Postcrash Fires for Fire Safety Engineering Mon, 05 Dec 2016 10:31:22 +0000 The fire simulation curve this paper presents is based on a curve which is proposed by Barnett in 2002. The curve is used to study the temperature change in a fire scenario in the interior of a rectangular compartment. However, it is not applicable to use in some long, limited spaces with arc boundaries, such as aircraft cabins. Some improvements and simplifications are made to the curve to solve this problem. A numerical simulation is conducted via the modified curve in a B737 fuselage during a postcrash fire. The result is compared with a fire dynamics simulator (FDS) simulation and a full-scale test undertaken by the National Aeronautics and Space Administration (NASA). The practicability and accuracy of the modified curve is proved through the relevant analysis and the main relative error analysis. The time to flashover is also predicted by the curve and the FDS simulation, respectively. Several parameters are chosen as influence factors to study their effect on the time to flashover in order to delay the occurrence of the flashover. This study may provide a technical support for the cabin fire safety design, safety management, and fire safety engineering. Qingsong Zhang, Naiwen Jiang, Hanpeng Qi, and Xingna Luo Copyright © 2016 Qingsong Zhang et al. All rights reserved. A Mixture of Two Burr Type III Distributions: Identifiability and Estimation under Type II Censoring Mon, 05 Dec 2016 08:47:54 +0000 The mixture of two Burr Type III distributions (MTBIIID) is investigated. First, the identifiability property of the MTBIIID is proved. Then, two different methods of estimation are used. Next, the estimates of the unknown five parameters and reliability function of the MTBIIID under Type II censoring are obtained. To study the performance of the estimation technique in the paper, a Monte Carlo simulation is presented. In addition, the numerical illustration requires solving nonlinear equations; therefore, the software international mathematical statistical library (IMSL) is used to assess these effects numerically. Finally, a real data set is applied to illustrate the methods proposed here. A. S. Al-Moisheer Copyright © 2016 A. S. Al-Moisheer. All rights reserved. On the Polynomial Basis of Having a Small Number of Trace-One Elements Mon, 05 Dec 2016 07:35:54 +0000 In the Galois fields , a polynomial basis with a small number of trace-one elements is desirable for its convenience in computing. To find new irreducible polynomials over with this property, we research into the auxiliary polynomial with roots , such that the symmetric polynomials are relative to the symmetric polynomials of . We introduce a new class of polynomials with the number “1” occupying most of the values in its . This indicates that the number “0” occupies most of the values of the traces of the elements . This new class of polynomial gives us an indirect way to find irreducible polynomials having a small number of trace-one elements in their polynomial bases. Jiantao Wang, Dong Zheng, and Zheng Huang Copyright © 2016 Jiantao Wang et al. All rights reserved. Finite-Time Composite Position Control for a Disturbed Pneumatic Servo System Mon, 05 Dec 2016 07:04:00 +0000 This paper investigates the finite-time position tracking control problem of pneumatic servo systems subject to hard nonlinearities and various disturbances. A finite-time disturbance observer is firstly designed, which guarantees that the disturbances can be accurately estimated in a finite time. Then, by combining disturbances compensation and state feedback controller together, a nonsmooth composite controller is developed based on sliding mode control approach and homogeneous theory. It is proved that the tracking errors under the proposed composite control approach can be stabilized to zero in finite time. Moreover, compared with pure state feedback control, the proposed composite control scheme offers a faster convergence rate and a better disturbance rejection property. Finally, numerical simulations illustrate the effectiveness of the proposed control scheme. Xiaojun Wang, Jiankun Sun, and Guipu Li Copyright © 2016 Xiaojun Wang et al. All rights reserved. Design of Sail-Assisted Unmanned Surface Vehicle Intelligent Control System Mon, 05 Dec 2016 05:58:10 +0000 To achieve the wind sail-assisted function of the unmanned surface vehicle (USV), this work focuses on the design problems of the sail-assisted USV intelligent control systems (SUICS) and illustrates the implementation process of the SUICS. The SUICS consists of the communication system, the sensor system, the PC platform, and the lower machine platform. To make full use of the wind energy, in the SUICS, we propose the sail angle of attack automatic adjustment (Sail_4A) algorithm and present the realization flow for each subsystem of the SUICS. By using the test boat, the design and implementation of the SUICS are fulfilled systematically. Experiments verify the performance and effectiveness of our SUICS. The SUICS enhances the intelligent utility of sustainable wind energy for the sail-assisted USV significantly and plays a vital role in shipping energy-saving emission reduction requirements issued by International Maritime Organization (IMO). Yong Ma, Yujiao Zhao, Jiantao Diao, Langxiong Gan, Huaxiong Bi, and Jingming Zhao Copyright © 2016 Yong Ma et al. All rights reserved. Robust K-Median and K-Means Clustering Algorithms for Incomplete Data Sun, 04 Dec 2016 11:47:19 +0000 Incomplete data with missing feature values are prevalent in clustering problems. Traditional clustering methods first estimate the missing values by imputation and then apply the classical clustering algorithms for complete data, such as K-median and K-means. However, in practice, it is often hard to obtain accurate estimation of the missing values, which deteriorates the performance of clustering. To enhance the robustness of clustering algorithms, this paper represents the missing values by interval data and introduces the concept of robust cluster objective function. A minimax robust optimization (RO) formulation is presented to provide clustering results, which are insensitive to estimation errors. To solve the proposed RO problem, we propose robust K-median and K-means clustering algorithms with low time and space complexity. Comparisons and analysis of experimental results on both artificially generated and real-world incomplete data sets validate the robustness and effectiveness of the proposed algorithms. Jinhua Li, Shiji Song, Yuli Zhang, and Zhen Zhou Copyright © 2016 Jinhua Li et al. All rights reserved. Multistep Wind Speed Forecasting Using a Novel Model Hybridizing Singular Spectrum Analysis, Modified Intelligent Optimization, and Rolling Elman Neural Network Sun, 04 Dec 2016 09:26:01 +0000 Wind speed high-accuracy forecasting, an important part of the electrical system monitoring and control, is of the essence to protect the safety of wind power utilization. However, the wind speed signals are always intermittent and intrinsic complexity; therefore, it is difficult to forecast them accurately. Many traditional wind speed forecasting studies have focused on single models, which leads to poor prediction accuracy. In this paper, a new hybrid model is proposed to overcome the shortcoming of single models by combining singular spectrum analysis, modified intelligent optimization, and the rolling Elman neural network. In this model, except for the multiple seasonal patterns used to reduce interferences from the original data, the rolling model is utilized to forecast the multistep wind speed. To verify the forecasting ability of the proposed hybrid model, 10 min and 60 min wind speed data from the province of Shandong, China, were proposed in this paper as the case study. Compared to the other models, the proposed hybrid model forecasts the wind speed with higher accuracy. Zhongshan Yang and Jian Wang Copyright © 2016 Zhongshan Yang and Jian Wang. All rights reserved. Research on a Risk Assessment Method considering Risk Association Sun, 04 Dec 2016 07:14:42 +0000 Regarding risk assessment problems with multiple associated risks, a risk assessment method (RAM) is proposed in this paper. According to the risk-associated assessment information offered by expert panel, a comprehensive associated matrix is constructed to identify the influence relationship among risks so as to determine the hierarchical structure of risks. Then, based on the determined divided or undivided risk hierarchical structure as well as the possibility and loss of risks provided by expert panel, each value at risk (VAR) is calculated through knowledge related to probability theory. Finally, the feasibility and efficiency of the proposed method are demonstrated through a calculating case. Zhan Zhang, Kai Li, and Lei Zhang Copyright © 2016 Zhan Zhang et al. All rights reserved. A Doubly Adaptive Algorithm for Edge Detection in 3D Images Thu, 01 Dec 2016 08:02:12 +0000 This paper proposes a new algorithm (DA3DED) for edge detection in 3D images. DA3DED is doubly adaptive because it is based on the adaptive algorithm EDAS-1 for detecting edges in functions of one variable and a second adaptive procedure based on the concept of projective complexity of a 3D image. DA3DED has been tested on 3D images that modelize real problems (composites and fractures). It has been much faster than the 1D edge detection algorithm for 3D images derived from EDAS-1. Sagrario Lantarón, M. Dolores López, and Javier Rodrigo Copyright © 2016 Sagrario Lantarón et al. All rights reserved. Model Test Research on the End Bearing Behavior of the Large-Diameter Cast-in-Place Concrete Pile for Jointed Rock Mass Wed, 30 Nov 2016 14:31:38 +0000 For large-diameter, cast-in-place concrete piles, the end bearing capacity of a single pile is affected by discontinuous surfaces that exist in natural rock masses when the bearing layer of the pile end is located in the rock layer. In order to study the influence of the jointed dip angle on the bearing characteristics of the pile end, the discrete element models are adopted to simulate the mechanical characteristics of the jointed rock masses, and the model tests of the failure mode of the jointed rock masses were also designed. The results of the numerical calculations and modeling tests show that the joints, which have a filtering effect on the internal stress of the bedrock located at the pile end, change the load transferring paths. And the failure mode of the jointed rock foundation also changes as jointed dip angle changes. The rock located at the pile end generally presents a wedge failure mode. In addition, the curves obtained by model tests show that the ultimate end bearing capacity of a single pile is influenced by the jointed dip angle. The above results provide an important theoretical basis for how to correctly calculate end resistance for a cast-in-place concrete pile. Jingwei Cai, Aiping Tang, Xinsheng Yin, Xiaxin Tao, and Shibo Tao Copyright © 2016 Jingwei Cai et al. All rights reserved. Subspace Identification of Hammerstein Model with Unified Discontinuous Nonlinearity Wed, 30 Nov 2016 13:28:05 +0000 The main aim of this study is to handle the case where the structures of nonlinear systems are unknown. In the many works, the parametric identification of nonlinear systems represented by Hammerstein model, with discontinuous and asymmetric nonlinearity, considers the structures of the nonlinear and linear blocks are known, especially the nonlinear bloc. To solve this problem, a unified form of nonlinearity representing eight cases of nonlinearities can be used. The parameters of both blocks, linear and nonlinear, are estimated using an iterative subspace approach. More importantly, in an attempt to show the extent to which this method is efficient, we apply it to experimental data obtained from the electropneumatic system. As a result, the numerical and experimental examples confirm a good conditioning and computational efficiency. Borhen Aissaoui, Moêz Soltani, and Abdelkader Chaari Copyright © 2016 Borhen Aissaoui et al. All rights reserved. Analytical Model of Waterflood Sweep Efficiency in Vertical Heterogeneous Reservoirs under Constant Pressure Wed, 30 Nov 2016 09:59:50 +0000 An analytical model has been developed for quantitative evaluation of vertical sweep efficiency based on heterogeneous multilayer reservoirs. By applying the Buckley-Leverett displacement mechanism, a theoretical relationship is deduced to describe dynamic changes of the front of water injection, water saturation of producing well, and swept volume during waterflooding under the condition of constant pressure, which substitutes for the condition of constant rate in the traditional way. Then, this method of calculating sweep efficiency is applied from single layer to multilayers, which can be used to accurately calculate the sweep efficiency of heterogeneous reservoirs and evaluate the degree of waterflooding in multilayer reservoirs. In the case study, the water frontal position, water cut, volumetric sweep efficiency, and oil recovery are compared between commingled injection and zonal injection by applying the derived equations. The results are verified by numerical simulators, respectively. It is shown that zonal injection works better than commingled injection in respect of sweep efficiency and oil recovery and has a longer period of water free production. Lisha Zhao, Li Li, Zhongbao Wu, and Chenshuo Zhang Copyright © 2016 Lisha Zhao et al. All rights reserved. Discontinuous Deformation Analysis Coupling with Discontinuous Galerkin Finite Element Methods for Contact Simulations Wed, 30 Nov 2016 05:51:25 +0000 A novel coupling scheme is presented to combine the discontinuous deformation analysis (DDA) and the interior penalty Galerkin (IPG) method for the modeling of contacts. The simultaneous equilibrium equations are assembled in a mixed strategy, where the entries are derived from both discontinuous Galerkin variational formulations and the strain energies of DDA contact springs. The contact algorithms of the DDA are generalized for element contacts, including contact detection criteria, open-close iteration, and contact submatrices. Three representative numerical examples on contact problems are conducted. Comparative investigations on the results obtained by our coupling scheme, ANSYS, and analytical theories demonstrate the accuracy and effectiveness of the proposed method. Yue Sun, Xiangchu Feng, Jun Xiao, and Ying Wang Copyright © 2016 Yue Sun et al. All rights reserved. Interval 2-Tuple Linguistic Distance Operators and Their Applications to Supplier Evaluation and Selection Tue, 29 Nov 2016 14:18:02 +0000 With respect to multicriteria supplier selection problems with interval 2-tuple linguistic information, a new decision making approach that uses distance measures is proposed. Motivated by the ordered weighted distance (OWD) measures, in this paper, we develop some interval 2-tuple linguistic distance operators such as the interval 2-tuple weighted distance (ITWD), the interval 2-tuple ordered weighted distance (ITOWD), and the interval 2-tuple hybrid weighted distance (ITHWD) operators. These aggregation operators are very useful for the treatment of input data in the form of interval 2-tuple linguistic variables. We study some desirable properties of the ITOWD operator and further generalize it by using the generalized and the quasi-arithmetic means. Finally, the new approach is utilized to complete a supplier selection study for an actual hospital from the healthcare industry. Meng-Meng Shan, Ping Li, and Hu-Chen Liu Copyright © 2016 Meng-Meng Shan et al. All rights reserved.