Showing papers in "Smart Structures and Systems in 2018"

Application of support vector machine with firefly algorithm for investigation of the factors affecting the shear strength of angle shear connectors

Abstract: The factors affecting the shear strength of the angle shear connectors in the steel-concrete composite beams can play an important role to estimate the efficacy of a composite beam. Therefore, the current study has aimed to verify the output of shear capacity of angle shear connector according to the input provided by Support Vector Machine (SVM) coupled with Firefly Algorithm (FFA). SVM parameters have been optimized through the use of FFA, while genetic programming (GP) and artificial neural networks (ANN) have been applied to estimate and predict the SVM-FFA models\' results. Following these results, GP and ANN have been applied to develop the prediction accuracy and generalization capability of SVM-FFA. Therefore, SVM-FFA could be performed as a novel model with predictive strategy in the shear capacity estimation of angle shear connectors. According to the results, the Firefly algorithm has produced a generalized performance and be learnt faster than the conventional learning algorithms.

A review on pavement porous concrete using recycled waste materials

Abstract: Pavements porous concrete is a noble structure design in the urban management development generally enabling water to be permeated within its structure. It has also capable in the same time tocater dynamic loading. During the technology development, the quality and quantity of waste materials have led to a waste disposal crisis. Using recycled materials (secondary) instead of virgin ones (primary) have reduced landfill pressure and extraction demanding. This study has reviewedthe waste materials (Recycled crushed glass (RCG), Steel slag, Steel fiber, Tires, Plastics, Recycled asphalt) used in the pavement porous concretes and report their respective mechanical, durability and permeability functions. Waste material usagein the partial cement replacement will cause the concrete production cost to be reduced; also, the concretes' mechanical features have slightly affected to eliminate the disposal waste materials defects and to use cement in Portland cement (PC) production. While the cement has been replaced by different industrial wastes, the compressive strength, flexural strength, split tensile strength and different PC permeability mixes have depended on the waste materials' type applied in PC production.

A novel shear deformation theory for buckling analysis of single layer graphene sheet based on nonlocal elasticity theory

Abstract: In this paper, a novel simple shear deformation theory for buckling analysis of single layer graphene sheet is formulated using the nonlocal differential constitutive relations of Eringen. The present theory involves only three unknown and three governing equation as in the classical plate theory, but it is capable of accurately capturing shear deformation effects, instead of five as in the well-known first shear deformation theory (FSDT) and higher-order shear deformation theory (HSDT). A shear correction factor is, therefore, not required. Nonlocal elasticity theory is employed to investigate effects of small scale on buckling of the rectangular nano-plate. The equations of motion of the nonlocal theories are derived and solved via Navier\'s procedure for all edges simply supported boundary conditions. The results are verified with the known results in the literature. The influences played by Effects of nonlocal parameter, length, thickness of the graphene sheets and shear deformation effect on the critical buckling load are studied. Verification studies show that the proposed theory is not only accurate and simple in solving the buckling nanoplates, but also comparable with the other higher-order shear deformation theories which contain more number of unknowns.

Application of ANFIS technique on performance of C and L shaped angle shear connectors

Abstract: The behavior of concrete slabs in composite beam with C and L shaped angle shear connectors has been studied in this paper. These two types of angle shear connectors\' instalment have been commonly utilized. In this study, the finite element (FE) analysis and soft computing method have been used both to present the shear connectors\' push out tests and providing data results used later in soft computing method. The current study has been performed to present the aforementioned shear connectors\' behavior based on the variable factors aiming the study of diverse factors\' effects on C and L shaped angle in shear connectors. ANFIS (Adaptive Neuro Fuzzy Inference System), has been manipulated in providing the effective parameters in shear strength forecasting by providing input-data comprising: height, length, thickness of shear connectors together with concrete strength and the respective slip of shear connectors. ANFIS has been also used to identify the predominant parameters influencing the shear strength forecast in C and L formed angle shear connectors.

A novel nonlocal refined plate theory for stability response of orthotropic single-layer graphene sheet resting on elastic medium

Abstract: This work presents the buckling investigation of embedded orthotropic nanoplates such as graphene by employing a new refined plate theory and nonlocal small-scale effects. The elastic foundation is modeled as two-parameter Pasternak foundation. The proposed two-variable refined plate theory takes account of transverse shear influences and parabolic variation of the transverse shear strains within the thickness of the plate by introducing undetermined integral terms, hence it is unnecessary to use shear correction factors. Nonlocal governing equations for the single layered graphene sheet are obtained from the principle of virtual displacements. The proposed theory is compared with other plate theories. Analytical solutions for buckling loads are obtained for single-layered graphene sheets with isotropic and orthotropic properties. The results presented in this study may provide useful guidance for design of orthotropic graphene based nanodevices that make use of the buckling properties of orthotropic nanoplates.

Portland cement structure and its major oxides and fineness

Abstract: Predicting the compressive strength of concrete has been considered as the initial phase across the cement production processing. The current study has focused on the integration of the concrete compressive strength in 28 days with the mix of the major oxides and fine aggregates as an experimental formula through the use of two types of Portland cement resulting the compressive strength of the concrete highly dependent on time.

Dynamic analysis of nanoscale beams including surface stress effects

Abstract: In this article, an analytic non-classical model for the free vibrations of nanobeams accounting for surface stress effects is developed The classical continuum mechanics fails to capture the surface energy effects and hence is not directly applicable at nanoscale A general beam model based on Gurtin-Murdoch continuum surface elasticity theory is developed for the analysis of thin and thick beams Thus, surface energy has a significant effect on the response of nanoscale structures, and is associated with their size-dependent behavior To check the validity of the present analytic solution, the numerical results are compared with those obtained in the scientific literature The influences of beam thickness, surface density, surface residual stress and surface elastic constants on the natural frequencies of nanobeams are also investigated It is indicated that the effect of surface stress on the vibrational response of a nanobeam is dependent on its aspect ratio and thickness

PCA-based filtering of temperature effect on impedance monitoring in prestressed tendon anchorage

Abstract: For the long-term structural health monitoring of civil structures, the effect of ambient temperature variation has been regarded as one of the critical issues. In this study, a principal component analysis (PCA)-based algorithm is proposed to filter out temperature effects on electromechanical impedance (EMI) monitoring of prestressed tendon anchorages. Firstly, the EMI monitoring via a piezoelectric interface device is described for prestress-loss detection in the tendon anchorage system. Secondly, the PCA-based temperature filtering algorithm tailored to the EMI monitoring of the prestressed tendon anchorage is outlined. The proposed algorithm utilizes the damage-sensitive features obtained from sub-ranges of the EMI data to establish the PCA-based filter model. Finally, the feasibility of the PCA-based algorithm is experimentally evaluated by distinguishing temperature changes from prestress-loss events in a prestressed concrete girder. The accuracy of the prestress-loss detection results is discussed with respect to the EMI features before and after the temperature filtering.

A review on sensors and systems in structural health monitoring: current issues and challenges

Abstract: Sensors and systems in Civionics technology play an important role for continuously facilitating real-time structure monitoring systems by detecting and locating damage to or degradation of structures. An advanced materials, design processes, long-term sensing ability of sensors, electromagnetic interference, sensor placement techniques, data acquisition and computation, temperature, harsh environments, and energy consumption are important issues related to sensors for structural health monitoring (SHM). This paper provides a comprehensive survey of various sensor technologies, sensor classes and sensor networks in Civionics research for existing SHM systems. The detailed classification of sensor categories, applications, networking features, ranges, sizes and energy consumptions are investigated, summarized, and tabulated along with corresponding key references. The current challenges facing typical sensors in Civionics research are illustrated with a brief discussion on the progress of SHM in future applications. The purpose of this review is to discuss all the types of sensors and systems used in SHM research to provide a sufficient background on the challenges and problems in optimizing design techniques and understanding infrastructure performance, behavior and current condition. It is observed that the most important factors determining the quality of sensors and systems and their reliability are the long-term sensing ability, data rate, types of processors, size, power consumption, operation frequency, etc. This review will hopefully lead to increased efforts toward the development of low-powered, highly efficient, high data rate, reliable sensors and systems for SHM.

Simplified dolphin echolocation algorithm for optimum design of frame

Abstract: implified Dolphin Echolocation (SDE) algorithm is a recently developed meta-heuristic algorithm. This algorithm is an improved and simplified version of the Dolphin Echolocation Optimization (DEO) method, based on the baiting behavior of the dolphins. The main advantage of the SDE algorithm is that it needs no empirical parameter. In this paper, the SDE algorithm is applied for optimization of three well-studied frame structures. The designs are then compared with those of other meta-heuristic methods from the literature. Numerical results show the efficiency of the SDE algorithm and its competitive ability with other well-established meta-heuristics methods.

Seismic performance of a resilient low-damage base isolation system under combined vertical and horizontal excitations

Abstract: Traditional base isolation systems focus on isolating the seismic response of a structure in the horizontal direction. However, in regions where the vertical earthquake excitation is significant (such as near-fault region), a traditional base-isolated building exhibits a significant vertical vibration. To eliminate this shortcoming, a rocking-isolated system named Telescopic Column (TC) is proposed in this paper. Detailed rocking and isolation mechanism of the TC system is presented. The seismic performance of the TC is compared with the traditional elastomeric bearing (EB) and friction pendulum (FP) base-isolated systems. A 4-storey reinforced concrete moment-resisting frame (RC-MRF) is selected as the reference superstructure. The seismic response of the reference superstructure in terms of column axial forces, base shears, floor accelerations, inter-storey drift ratios (IDR) and collapse margin ratios (CMRs) are evaluated using OpenSees. The results of the nonlinear dynamic analysis subjected to multi-directional earthquake excitations show that the superstructure equipped with the newly proposed TC is more resilient and exhibits a superior response with higher margin of safety against collapse when compared with the same superstructure with the traditional base-isolation (BI) system.

Wheel tread defect detection for high-speed trains using FBG-based online monitoring techniques

Abstract: The problem of wheel tread defects has become a major challenge for the health management of high-speed rail as a wheel defect with small radius deviation may suffice to give rise to severe damage on both the train bogie components and the track structure when a train runs at high speeds. It is thus highly desirable to detect the defects soon after their occurrences and then conduct wheel turning for the defective wheelsets. Online wheel condition monitoring using wheel impact load detector (WILD) can be an effective solution, since it can assess the wheel condition and detect potential defects during train passage. This study aims to develop an FBG-based track-side wheel condition monitoring method for the detection of wheel tread defects. The track-side sensing system uses two FBG strain gauge arrays mounted on the rail foot, measuring the dynamic strains of the paired rails excited by passing wheelsets. Each FBG array has a length of about 3 m, slightly longer than the wheel circumference to ensure a full coverage for the detection of any potential defect on the tread. A defect detection algorithm is developed for using the online-monitored rail responses to identify the potential wheel tread defects. This algorithm consists of three steps: 1) strain data pre-processing by using a data smoothing technique to remove the trends; 2) diagnosis of novel responses by outlier analysis for the normalized data; and 3) local defect identification by a refined analysis on the novel responses extracted in Step 2. To verify the proposed method, a field test was conducted using a test train incorporating defective wheels. The train ran at different speeds on an instrumented track with the purpose of wheel condition monitoring. By using the proposed method to process the monitoring data, all the defects were identified and the results agreed well with those from the static inspection of the wheelsets in the depot. A comparison is also drawn for the detection accuracy under different running speeds of the test train, and the results show that the proposed method can achieve a satisfactory accuracy in wheel defect detection when the train runs at a speed higher than 30 kph. Some minor defects with a depth of 0.05 mm~0.06 mm are also successfully detected.

The effect of micro parameters of PFC software on the model calibration

Abstract: One of the methods for investigation of mechanical behavior of materials is numerical simulation. For simulation, its need to model behavior is close to real condition. PFC is one of the rock mechanics software that needs calibration for models simulation. The calibration was performed based on simulation of unconfined compression test and Brazilian test. Indeed the micro parameter of models change so that the UCS and Brazilian test results in numerical simulation be close to experimental one. In this paper, the effect of four micro parameters has been investigated on the uniaxial compression test and Brazilian test. These micro parameters are friction angle, Accumulation factor, expansion coefficient and disc distance. The results show that these micro parameters affect the failure pattern in UCS and Brazilian test. Also compressive strength and tensile strength are controlled by failure pattern.

Ultrasonic guided wave approach incorporating SAFE for detecting wire breakage in bridge cable

Abstract: Ultrasonic guided waves have attracted increasing attention for non-destructive testing (NDT) and structural health monitoring (SHM) of bridge cables. They offer advantages like single measurement, wide coverage of acoustical field, and long-range propagation capability. To design defect detection systems, it is essential to understand how guided waves propagate in cables and how to select the optimal excitation frequency and mode. However, certain cable characteristics such as multiple wires, anchorage, and polyethylene (PE) sheath increase the complexity in analyzing the guided wave propagation. In this study, guided wave modes for multi-wire bridge cables are identified by using a semi-analytical finite element (SAFE) technique to obtain relevant dispersion curves. Numerical results indicated that the number of guided wave modes increases, the length of the flat region with a low frequency of L(0,1) mode becomes shorter, and the cutoff frequency for high order longitudinal wave modes becomes lower, as the number of steel wires in a cable increases. These findings were used in design of transducers for defect detection and selection of the optimal wave mode and frequency for subsequent experiments. A magnetostrictive transducer system was used to excite and detect the guided waves. The applicability of the proposed approach for detecting and locating wire breakages was demonstrated for a cable with 37 wires. The present ultrasonic guided wave method has been found to be very responsive to the number of broken wires and is thus capable of detecting defects with varying sizes.

Energy Harvesting Techniques for Health Monitoring and Indicators for Control of a Damaged Pipe Structure

Abstract: Applications of energy harvesting from mechanical vibrations is becoming popular but the full potential of such applications is yet to be explored. This paper addresses this issue by considering an application of energy harvesting for the dual objective of serving as an indicator of structural health monitoring (SHM) and extent of control. Variation of harvested energy from an undamaged baseline is employed for this purpose and the concept is illustrated by implementing it for active vibrations of a pipe structure. Theoretical and experimental analyses are carried out to determine the energy harvesting potential from undamaged and damaged conditions. The use of energy harvesting as indicator for control is subsequently investigated, considering the effect of the introduction of a tuned mass damper (TMD). It is found that energy harvesting can be used for the detection and monitoring of the location and magnitude of damage occurring within a pipe structure. Additionally, the harvested energy acts as an indicator of the extent of reduction of vibration of pipes when a TMD is attached. This paper extends the range of applications of energy harvesting devices for the monitoring of built infrastructure and illustrates the vast potential of energy harvesters as smart sensors.

Size-dependent free vibration and dynamic analyses of a sandwich microbeam based on higher-order sinusoidal shear deformation theory and strain gradient theory

Abstract: The governing equations of motion are derived for analysis of a sandwich microbeam in this paper. The sandwich microbeam is including an elastic micro-core and two piezoelectric micro-face-sheets. The microbeam is subjected to transverse loads and two-dimensional electric potential. Higher-order sinusoidal shear deformation beam theory is used for description of displacement field. To account size dependency in governing equations of motion, strain gradient theory is used to mention higher-order stress and strains. An analytical approach for simply-supported sandwich microbeam with short-circuited electric potential is proposed. The numerical results indicate that various types of parameters such as foundation and material length scales have significant effects on the free vibration responses and dynamic results. Investigation on the influence of material length scales indicates that increase of both dimensionless material length scale parameters leads to significant changes of vibration and dynamic responses of microbeam.

Prediction of the remaining service life of existing concrete bridges in infrastructural networks based on carbonation and chloride ingress

Abstract: The authors would like to show their gratitude for the support received through the project "Life Cycle Assessment for Railway Structures", funded by the OBBInfrastruktur Bau AG, Vienna. Moreover, the authors would like to thank Mr. Roland Aschinger for his immense help and contribution to the research published in this article. Additionally, the authors would like to extend their appreciation to their colleagues at the Institute of Structural Engineering, Department of Civil Engineering and Natural Hazards at University of Natural Resources and Life Sciences in Vienna, Austria.

Improved thermal exchange optimization algorithm for optimal design of skeletal structures

Abstract: Thermal Exchange Optimization (TEO) is a newly developed algorithm which mimics the thermal exchange between a solid object and its surrounding fluid. In this paper, an improved version of the TEO is developed to fix the shortcomings of the standard version. To demonstrate the viability of the new algorithm, the CEC 2016\'s single objective problems are considered along with the discrete size optimization of benchmark skeletal structures. Problem specific constraints are handled using a fly-back mechanism. The results show the validity of the improved TEO method compared to its standard version and a number of well-known algorithms.

An integrated structural health monitoring system for the Xijiang high-speed railway arch bridge

Abstract: Compared with the highway bridges, the relatively higher requirement on the safety and comfort of vehicle makes the high-speed railway (HSR) bridges need to present enhanced dynamic performance. To this end, installing a health monitor system (HMS) on selected key HSR bridges has been widely applied. Typically, the HSR takes fully enclosed operation model and its skylight time is very short, which means that it is not easy to operate the acquisition devices and download data on site. However, current HMS usually involves manual operations, which makes it inconvenient to be used for the HSR. Hence, a HMS named DASP-MTS (Data Acquisition and Signal Processing - Monitoring Test System) that integrates the internet, cloud computing (CC) and virtual instrument (VI) techniques, is developed in this study. DASP-MTS can realize data acquisition and transmission automatically. Furthermore, the acquired data can be timely shared with experts from various locations to deal with the unexpected events. The system works in a Browser/Server frame so that users at any places can obtain real-time data and assess the health situation without installing any software. The developed integrated HMS has been applied to the Xijiang high-speed railway arch bridge. Preliminary analysis results are presented to demonstrate the efficacy of the DASP-MTS as applied to the HSR bridges. This study will provide a reference to design the HMS for other similar bridges.

Axial load detection in compressed steel beams using FBG-DSM sensors

Abstract: Nondestructive testing methods are required to assess the condition of civil structures and formulate their maintenance programs. Axial force identification is required for several structural members of truss bridges, pipe racks, and space roof trusses. An accurate evaluation of in situ axial forces supports the safety assessment of the entire truss. A considerable redistribution of internal forces may indicate structural damage. In this paper, a novel compressive force identification method for prismatic members implemented using static deflections is applied to steel beams. The procedure uses the Euler–Bernoulli beam model and estimates the compressive load by using the measured displacement along the beam\'s length. Knowledge of flexural rigidity of the member under investigation is required. In this study, the deflected shape of a compressed steel beam is subjected to an additional vertical load that was short-term measured in several laboratory tests by using fiber Bragg grating–differential settlement measurement (FBG–DSM) sensors at specific cross sections along the beam\'s length. The accuracy of midspan deflections offered by the FBG–DSM sensors provided excellent force estimations. Compressive load detection accuracy can be improved if substantial second-order effects are induced in the tests. In conclusion, the proposed method can be successfully applied to steel beams with low slenderness under real conditions.

Long-term health monitoring for deteriorated bridge structures based on Copula theory

Abstract: Maintenance of deteriorated bridge structures has always been one of the challenging issues in developing countries as it is directly related to daily life of people including trade and economy. An effective maintenance strategy is highly dependent on timely inspections on the bridge health condition. This study is intended to investigate an approach for detecting bridge damage for the long-term health monitoring by use of copula theory. Long-term measured data for the seven-span plate-Gerber bridge is investigated. Autoregressive time series models constructed for the observed accelerations taken from the bridge are utilized for the computation of damage indicator for the bridge. The copula model is used to analyze the statistical changes associated with the modal parameters. The changes in the modal parameters with the time are identified by the copula statistical properties. Applicability of the proposed method is also discussed based on a comparison study among other approaches.

Real-time condition assessment of railway tunnel deformation using an FBG-based monitoring system

Abstract: A tunnel deformation monitoring system is developed with the use of fiber Bragg grating (FBG) sensing technique, aiming at providing continuous monitoring of railway tunnel deformation in the long term, and early warning for the rail service maintainers and authorities to avoid catastrophic consequences when significant deformation occurs. Specifically, a set of FBG bending gauges with the ability of angle measurement and temperature compensation is designed and manufactured for the purpose of online monitoring of tunnel deformation. An overall profile of lateral tunnel displacement along the longitudinal direction can be obtained by implementing an array of the FBG bending gauges interconnected by rigid rods, in conjunction with a proper algorithm. The devised system is verified in laboratory experiments with a test setup enabling to imitate various patterns of tunnel deformation before the implementation of this system in an in-service high-speed railway (HSR) tunnel.

Online condition assessment of high-speed trains based on Bayesian forecasting approach and time series analysis

Abstract: High-speed rail (HSR) has been in operation and development in many countries worldwide. The explosive growth of HSR has posed great challenges for operation safety and ride comfort. Among various technological demands on high-speed trains, vibration is an inevitable problem caused by rail/wheel imperfections, vehicle dynamics, and aerodynamic instability. Ride comfort is a key factor in evaluating the operational performance of high-speed trains. In this study, online monitoring data have been acquired from an in-service high-speed train for condition assessment. The measured dynamic response signals at the floor level of a train cabin are processed by the Sperling operator, in which the ride comfort index sequence is used to identify the train\'s operation condition. In addition, a novel technique that incorporates salient features of Bayesian inference and time series analysis is proposed for outlier detection and change detection. The Bayesian forecasting approach enables the prediction of conditional probabilities. By integrating the Bayesian forecasting approach with time series analysis, one-step forecasting probability density functions (PDFs) can be obtained before proceeding to the next observation. The change detection is conducted by comparing the current model and the alternative model (whose mean value is shifted by a prescribed offset) to determine which one can well fit the actual observation. When the comparison results indicate that the alternative model performs better, then a potential change is detected. If the current observation is a potential outlier or change, Bayes factor and cumulative Bayes factor are derived for further identification. A significant change, if identified, implies that there is a great alteration in the train operation performance due to defects. In this study, two illustrative cases are provided to demonstrate the performance of the proposed method for condition assessment of high-speed trains.

Nonlocal elasticity approach for free longitudinal vibration of circular truncated nanocones and method of determining the range of nonlocal small scale

Abstract: The free longitudinal vibration of a circular truncated nanocone is investigated based on the nonlocal elasticity theory. Exact analytical formulations for tapered nanostructures are derived and the nonlinear differential governing equation of motion is developed. The nonlocal small scale effect unavailable in classical continuum theory is addressed to reveal the long-range interaction of atoms implicated in nonlocal constitutive relation. Unlike most previous studies applying the truncation method to the infinite higher-order differential equation, this paper aims to consider all higher-order terms to show the overall nonlocality. The explicit solution of nonlocal stress for longitudinal deformation is determined and it is an infinite series incorporating the classical stress derived in classical mechanics of materials and the infinite higher-order derivative of longitudinal displacement. Subsequently, the first three modes natural frequencies are calculated numerically and the significant effects of nonlocal small scale and vertex angle on natural frequencies are examined. The coupling phenomenon of natural frequency is observed and it is induced by the combined effects of nonlocal small scale and vertex angle. The critical value of nonlocal small scale is defined, and after that a new proposal for determining the range of nonlocal small scale is put forward since the principle of choosing the nonlocal small scale is still unclear at present. Additionally, two different types of nonlocal effects, namely the nonlocal stiffness weakening and strengthening, reversed phenomena existing in nanostructures are observed and verified. Hence the opposite nonlocal effects are resolved again clearly. The nano-engineers dealing with a circular truncated nanocone-based sensors and oscillators may benefit from the present work.

Free vibration and static analysis of functionally graded skew magneto-electro-elastic plate

Abstract: This article presents a finite element (FE) model to assess the free vibration and static response of a functionally graded skew magneto-electro-elastic (FGSMEE) plate. Through the thickness material grading of FGSMEE plate is achieved using power law distribution. The coupled constitutive equations along with the total potential energy approach are used to develop the FE model of FGSMEE plate. The transformation matrix is utilized in bringing out the element matrix corresponding to the global axis to a local axis along the skew edges to specify proper boundary conditions. The effect of skew angle on the natural frequency of an FGSMEE plate is analysed. Further, the study includes the evaluation of the static behavior of FGSMEE plate for various skew angles. The influence of skew angle on the primary quantities such as displacements, electric potential, and magnetic potential, and secondary quantities such as stresses, electric displacement and magnetic induction is studied in detail. In addition, the effect of power-law gradient, thickness ratio, boundary conditions and aspect ratio on the free vibration and static response characteristics of FGSMEE plate has been investigated.

Practical use of computational building information modeling in repairing and maintenance of hospital building- case study

Abstract: Computational Building Information Modeling (BIM) is an intelligent 3D model-based process that provides architecture, engineering, and construction professionals the insight to plan, design, construct, and manage buildings and infrastructure more efficiently. This paper aims at using BIM in Hospitals configurations protection. Infrastructure projects are classified as huge structural projects taking advantage of many resources such as finance, materials, human labor, facilities and time. Immense expenses in infrastructure programs should be allocated to estimating the expected results of these arrangements in domestic economy. Hence, the significance of feasibility studies is inevitable in project construction, in this way the necessity in promoting the strategies and using global contemporary technologies in the process of construction maintenance cannot be neglected. This paper aims at using the building information modeling in covering Imam Khomeini Hospital\' s equipment. First, the relationship between hospital constructions maintenance and repairing, using the building information modeling, is demonstrated. Then, using library studies, the effective factors of constructions\' repairing and maintenance were collected. Finally, the possibilities of adding these factors in Revit software, as one of the most applicable software within BIM is investigated and have been identified in some items, where either this software can enter or the software for supporting the repairing and maintenance phase lacks them. The results clearly indicated that the required graphical factors in construction information modeling can be identified and applied successfully.

Vibration suppression in high-speed trains with negative stiffness dampers

Abstract: This work proposes and investigates re-centering negative stiffness dampers (NSDs) for vibration suppression in high-speed trains. The merit of the negative stiffness feature is demonstrated by active controllers on a high-speed train. This merit inspires the replacement of active controllers with re-centering NSDs, which are more reliable and robust than active controllers. The proposed damper design consists of a passive magnetic negative stiffness spring and a semi-active positioning shaft for re-centering function. The former produces negative stiffness control forces, and the latter prevents the amplification of quasi-static spring deflection. Numerical investigations verify that the proposed re-centering NSD can improve ride comfort significantly without amplifying spring deflection.

Influence of track irregularities in high-speed Maglev transportation systems

Abstract: Track irregularities of high-speed Maglev lines have significant influence on ride comfort. Their adjustment is of key importance in the daily maintenance of these lines. In this study, an adjustment method is proposed and track irregularities analysis is performed. This study considers two modules: an inspection module and a vehicle-guideway coupling vibration analysis module. In the inspection module, an inertial reference method is employed for field-measurements of the Shanghai high-speed Maglev demonstration line. Then, a partial filtering, integration method, resampling method, and designed elliptic filter are employed to analyze the detection data, which reveals the required track irregularities. In the analysis module, a vehicle-guideway interaction model and an electromagnetic interaction model were developed. The influence of the measured line irregularities is considered for the calculations of the electromagnetic force. Numerical integration method was employed for the calculations. Based on the actual field detection results and analysis using the numerical model, a threshold analysis method is developed. Several irregularities modalities with different girder end\'s deviations were considered in the simulations. The inspection results indicated that long-wavelength irregularities with larger girder end\'s deviations were the dominant irregularities. In addition, the threshold analysis of the girder end\' s deviations were considered in the simulations. The inspection results indicated that long-wavelength irregularities with larger girder end\'s deviation shows that irregularities that have a deviation amplitude larger than 6 mm and certain modalities (e.g., M- and N-shape) are unfavorable. These types of irregularities should be adjusted during the daily maintenance.

Blast vibration of a large-span high-speed railway tunnel based on microseismic monitoring

Abstract: Ground vibration is one of the most undesirable effects induced by blast operation in mountain tunnels, which could cause negative impacts on the residents living nearby and adjacent structures. The ground vibration effects can be well represented by peak particle velocity (PPV) and corner frequency (fc) on the ground. In this research, the PPV and the corner frequency of the mountain surface above the large-span tunnel of the new Badaling tunnel are observed by using the microseismic monitoring technique. A total of 53 sets of monitoring results caused by the blast inside tunnel are recorded. It is found that the measured values of PPV are lower than the allowable value. The measured values of corner frequency are greater than the natural frequencies of the Great Wall, which will not produce resonant vibration of the Great Wall. The vibration effects of associated parameters on the PPV and corner frequency which include blast charge, rock mass condition, and distance from the blast point to mountain surface, are studied by regression analysis. Empirical formulas are proposed to predict the PPV and the corner frequency of the Great Wall and surface structures due to blast, which can be used to determine the suitable blast charge inside the tunnel.

SHM-based probabilistic representation of wind properties: statistical analysis and bivariate modeling

Abstract: The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, R2. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.