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For a specific load, the displacements of a real cable-strut tensile structure can be approximately expressed by only a few contribution modes. The displacements can thus be quickly expanded based on finite sensor locations by the traditional contribution-mode based method (TCMM). However, the TCMM has two shortcomings. First, mode truncation errors occur by neglecting non-contribution modes. Second, too many sensors are needed when a load case has too many contribution modes. In this paper, two strategies named mode compensation strategy (MCS) and mode optimization strategy (MOS) are suggested, respectively. The MCS aims to compensate mode truncation errors observed in the TCMM, with all non-contribution modes treated as one integral compensation mode. The MOS attempts to reduce the quantity of contribution modes by finding the best virtual mass distribution. An improved contribution-mode based method (ICMM) using both the MCS and the MOS is thus proposed. An annular tensile cable-truss canopy structure with a span of 200 m is numerically analyzed. For the load case with 26 loading points and 16 contribution modes, the MOS can significantly reduce the number of contribution modes to 4. Besides, the ICMM presents high expansion accuracy with far less sensor locations than the TCMM and the Guyan method.

It is crucial to predict the worst surface accuracy of deployable mesh reflectors considering uncertainties at the design stage. The traditional method is computationally expensive because a form-finding process which needs many iterations is required in each Monte Carlo simulation. A quick method is adopted to rapidly compute the worst surface accuracy of deployable mesh reflectors. The sensitivity relationships between nodal coordinate deviations, cable force deviations and cable length errors are primarily derived. Instead of the time-consuming form-finding process, the derived sensitivity relationships are utilized to carry out the Monte Carlo simulations in the quick method. Ultimately, both the symmetric and asymmetric AstroMesh reflectors are numerically analyzed. The results show that the derived sensitivity relationships are effective, and the quick method can predict the worst surface accuracy as precise as the traditional method but with far less time consumption.

Relative displacements are introduced between steel bridges and continuously welded rail (CWR) tracks as the bridge girders expand and contract due to thermal effects. Depending on the fastening profile between the CWRs and steel bridge girders, additional forces are transmitted between the two, and when rail compression forces are introduced at the transition zones of the bridge, the risk of track buckling increases. The aim of this paper is to study CWR track buckling in the transition zones of open-deck steel bridges. In order to do so, a finite element model of a bridge is developed and calibrated based on the available literature. The model is then used to study the effects of a number of fastening profiles between the CWRs and steel bridge girders on track buckling in transition zone of the bridge. It is shown that girder temperature and location of lateral misalignment are the primary factors affecting the buckling temperature in the transition zone. Increasing the girder temperature by 45 °C can cause a drop of 11.5 °C in the track buckling temperature, a reduction of almost 19% compared to that of the open track. Furthermore, using zero toe load fasteners can reduce the risk of track buckling in the transition zone, yet there is little to resist the increasing gap size in case of a broken rail in winter.

PurposeThis paper presents a conceptual design process for developing a maintenance-focused heritage conservation model. Currently, there are several intervention approaches that can be applied in conservation from reconstruction, restoration and repairs to a “do-nothing” approach. This paper examines whether a maintenance solution is more than just an option or a necessity. The aim of the paper is to study the challenges and opportunities when putting more emphasis on the maintenance approach in conservation.Design/methodology/approachThis research was conducted in an Australian context, where many major buildings were constructed from the 19th and 20th centuries and are now categorised as “modern heritage”. three case studies were undertaken to inform this paper and others. In addition, 17 global heritage conservation experts were interviewed, and their responses were analysed. Also, comparative field observations and archival records were examined and used to develop the initial framework model. Finally, using focus group discussions amongst 7 experts, the framework was reviewed and formally validated in order to ensure the development of a useful model for use in devising an effective maintenance management plan and monitoring conditions in heritage buildings.FindingsThis paper supports others in a series that have already been accepted by this journal, focussing the research on heritage building conservation being conducted in Australia, the homeland of the Burra Charter. The other papers are entitled (1) model for the maintenance-focused heritage building conservation and (2) engineering in heritage conservation.Originality/valueThe paper examines contemporary issues in heritage building maintenance and conservation in Australia and focusses specifically on the lack of focus on maintenance as a conservation intervention for heritage buildings.

PurposeThis paper aims to set out the role of engineers in heritage conservation and investigates and evaluates the proposed available tools, technology and innovations that are currently available in the civil engineering sector that can be applied in heritage conservation.Design/methodology/approachAs society has become more aware of the grandeur of heritage spaces and structures, there is increasing pressure to preserve historic buildings. But, it is the economic cost of maintaining this important heritage legacy that has become the prime consideration of every state in Australia. Dedicated intelligent monitoring systems supplementing the traditional building inspections will enable the involved and interested stakeholders to carry out not only timely reactive response, but also to plan the maintenance of such buildings in a more vigilant and systematic manner. This will, in future, help to prevent further degradation of heritage buildings, which is very costly, often difficult and sometimes impossible to address if neglected. Savings in time and resources can be achieved, but only if a building's pathological monitoring and inspection results are on hand for use to guide major decisions to be made on how to best prevent further decay, or to save an important historical structure or building fabric.FindingsThe emergence of technological tools will enable the realization of a maintenance-focused conservation model. However, aside from the cost, these tools are still experimental in nature. These technologies are yet to be applied within the conservation industry with hopes of creating an easier and economically effective systematic method of heritage conservation.Originality/valueThe paper discusses the emerging tools and technologies in easing the monitoring aspect of a maintenance-focused conservation model.

PurposeThis paper presents and illustrates the model of a maintenance-focussed conservation plan developed in the thesis. It proposes a framework which puts more emphasis on maintenance in conservation than reconstruction, restorations, repairs or even a “do-nothing” approach.Design/methodology/approachThe research was conducted in an Australian context, where many major buildings are categorised as being “modern heritage”. However, the main problem with modern heritage is that although it has become more celebrated within the architectural historical sector, maintenance is still only in the background of most facility management (FM) operations, and its critical importance has yet to become accepted as a potential solution to greatly facilitate the proper preservation of the nation's architectural legacy. Challenges and barriers to this approach were evaluated, whilst opportunities were identified to improve a failing current situation that has resulted in the loss of many existing heritage structures. The paper makes a strong case in order to highlight the necessity of embedding a maintenance approach in preserving the historical fabric of buildings in the heritage conservation sector.FindingsThis research examines the key strategies for a maintenance-focussed conservation system.Originality/valueThe paper tackles experiences and issues in Australia about a lack of focus on maintenance as a conservation intervention.

Intensity Measures (IMs) provide the relationship between Engineering Demand Parameters (EDPs) and seismic hazard characteristics for different structures and hence, their role in performance-based bridge design is significant. A few studies have investigated the optimal IMs for bridges under horizontal ground motions, however, detailed studies to explore the optimal IMs for isolated-bridges under the coupled vertical and horizontal records are very rare. This paper presents a procedure for the selection of optimal IMs for seismic-isolated bridges under the combined strong Horizontal Component (HC) and Vertical Component (VC) seismic excitations. Soil-Structure-Interaction (SSI) effects, the high level of uncertainties for soil properties, uncertainties for structural and geotechnical issues and advanced plasticity model for non-liquefied soil are included to explore the optimal vector-valued IMs. Four individual situations are considered to investigate the geometry effects on the selected optimal IMs. Optimal IMs criteria including efficiency, practicality, proficiency and sufficiency are investigated and developed to achieve a set of optimal vector-valued IMs for critical EDPs: drift ratio, pile-cap displacement and bearing displacement, which are affected by both HC and VC in isolated Soil-Pile-Bridge (SPB) systems. The results show that velocity-related IMs: peak ground velocity (PGVH), Housner spectrum intensity (HIH) and root mean square of velocity (VRMSH) are optimal IMs as representative of HCs. In addition, structure-dependent spectral IMs: vertical spectral acceleration at T = 0.2 s ( $${\text{S}}_{\text{a}0.2}^{\text{V}}$$ ) and square-root-of-the-sum-of-square of vertical spectral acceleration at the first and second vertical periods ( $${\text{S}}_{\text{a}}^{\text{V}}\left({\text{T}}_{\text{s}}\right)$$ ) are the appropriate optimal IMs as representative of VCs. However, the displacement-related IM, peak ground displacement of HCs (PGDH), may be treated as optimal IMs for SPB system supported by inclined pile foundations to investigate pile-cap displacement. In addition, the sufficiency term is investigated extensively with respect to seismological parameters.

Steel modular constructions involve the manufacture of fully equipped three-dimensional prefabricated modules in factory-controlled settings which are then transported to construction sites and assembled to form a complete structure. Adjacent modules are attached to each other only at their corners at inter-modular connections. Typical inter-modular connections are incapable of providing resistance against lateral dynamics loads. Current research shows that under lateral dynamic loads, steel modular buildings with rigid unyielding connectors are vulnerable to failure of the columns which result in either partial or complete collapse of the structure. Modular systems would therefore require additional in-situ lateral load resisting systems, such as shear cores, which would devalue the benefits of purely modular construction as they would need to be built in-situ. To address this shortcoming, this research proposes a novel steel inter-modular connection, with two variations, to achieve safe, reliable and ductile dynamic performance of a modular building under seismic actions. An extensive experimental program was undertaken to study the feasibility of the strength hierarchy and expected ductile failure patterns of the newly proposed inter-modular connections under monotonic and cyclic lateral loads. The experimental study revealed that the proposed inter-modular connections display superior dynamic behaviour with respect to response parameters such as moment-carrying capacity, energy dissipation and ductility. Ductile failure patterns within the connection region and away from the columns, which are critical members, were observed. This information will contribute to the design of safe and efficient inter-modular connections and enable enhanced lateral performance of steel modular buildings under dynamic loads. A comprehensive numerical model of the connection was also developed and validated for use in future parametric studies.

Compression index Cc is an essential parameter in geotechnical design for which the effectiveness of correlation is still a challenge. This paper suggests a novel modelling approach using machine learning (ML) technique. The performance of five commonly used machine learning (ML) algorithms, i.e. back-propagation neural network (BPNN), extreme learning machine (ELM), support vector machine (SVM), random forest (RF) and evolutionary polynomial regression (EPR) in predicting Cc is comprehensively investigated. A database with a total number of 311 datasets including three input variables, i.e. initial void ratio e0, liquid limit water content wL, plasticity index Ip, and one output variable Cc is first established. Genetic algorithm (GA) is used to optimize the hyper-parameters in five ML algorithms, and the average prediction error for the 10-fold cross-validation (CV) sets is set as the fitness function in the GA for enhancing the robustness of ML models. The results indicate that ML models outperform empirical prediction formulations with lower prediction error. RF yields the lowest error followed by BPNN, ELM, EPR and SVM. If the ranges of input variables in the database are large enough, BPNN and RF models are recommended to predict Cc. Furthermore, if the distribution of input variables is continuous, RF model is the best one. Otherwise, EPR model is recommended if the ranges of input variables are small. The predicted correlations between input and output variables using five ML models show great agreement with the physical explanation.

The studies on inverse problems exist extensively in aerospace, mechanical, identification, detection, scanning imaging and other fields. Its ill-posed characteristics often lead to large oscillations in the solution of the inverse problem. In this study, the truncated generalized singular value decomposition (TGSVD) method is introduced to identify two kinds of moving forces, single and multi-axial forces. The truncating point is the most influential regularization parameter of TGSVD, which is initially selected by two classic regularization parameter selection criteria, namely, the L-curve criterion and the generalized cross-validation (GCV) criterion. Due to numerical non-uniqueness and noise disturbance in moving force identification (MFI), numerical simulation results show that neither of the two criteria can effectively help select the optimal truncating point of TGSVD. Hence, a relative percentage error (RPE) criterion is proposed for selecting the truncating point of TGSVD. Comparative studies show that the RPE criterion can be used to select the optimal truncating point of TGSVD more accurately against the GCV criterion and L-curve criterion. Moreover, the RPE criterion can be used to reflect the connections between certain properties and the ill-posedness problem existing in MFI, which should be adopted priority for the optimal truncating point selection of TGSVD.

Track buckling potential can be higher in the transition zones of steel bridges due to the combination of contact loads and large compressive forces present in this region because of rail a...

This paper develops and applies a procedure for detecting damage in a composite slab-on-girder bridge structure comprising of a reinforced concrete slab and three steel I beams, using vibration cha...

This paper presents the development and application of comprehensive numerical modelling techniques to simulate the blast response of cable supported facades (CSFs) and compares the responses of cable truss and cable net facades which are two popular types. The results of the comparative analysis are used to evaluate the influence of the facade type on the key response parameters and hence their effective performance under blast loads. Modelling approaches, material models and constraint types used are presented along with the validation of the procedure. Results from numerical models created in LS DYNA are compared with existing numerical and experimental results from literature to validate the modelling techniques. Behaviour of cable net and cable truss facades under a credible blast event are then compared by analysing the effects of cable and panel configurations. The findings of the comparative analysis, show that cable truss facades (in general) have reduced deflections and higher energy absorption capacities, but with larger cable forces. This information can be used in the design of either facade type to obtain the desired blast response. The numerical modelling techniques developed in this paper deliver important information on the blast response and failure assessment of cable supported facades and the comparative analysis will provide guidance in future research and investigation to enable safer designs.

Development activities in a city often generate ground vibration that can cause discomfort to the occupants in nearby buildings, disturbances to the activities undertaken in the buildings and possible damage to nearby structures. This ground vibration is caused by construction activities such as pile driving, ground compaction etc., and road and rail traffic. The use of trenches has been an effective way to mitigate the adverse effects of such ground vibration. The effectiveness of the trench depends on many parameters including the properties of the vibration source, soil medium and trench in-fill material, trench dimensions and the requirements of the receiver. The process of selecting an effective trench for vibration mitigation can therefore become complex due to the influence of a number of parameters and their wide range of values. This paper investigates the use of artificial neural network (ANN) as a smart and efficient tool to predict the effectiveness of geofoam-filled trenches to mitigate ground vibration. Towards this end, a database is developed from an extensive study on the effects of the controlling parameters through numerical simulations with a validated finite element (FE) model. At a certain distance from the vibration source, a geofoam-filled trench is introduced to evaluate the efficiency of vibration mitigation with changes in key parameters such as excitation frequency, amplitude of load, trench configuration (i.e. depth and width), soil shear wave velocity, soil density and damping ratio. These were selected as the input parameters for the ANN while amplitude reduction ratio and peak particle velocity (PPV) were considered as outputs. A multilayer feed forward network was used and trained with the Levenberg-Marquardt algorithm. Neural networks with different configurations were evaluated by comparing coefficient of determination (R 2) and mean square error (MSE). The optimum architecture was then used to predict previous results, which revealed the accuracy and the effectiveness of the ANN approach. The findings of this study will provide useful information for vibration mitigation using geofoam-filed trenches.

This paper develops a novel method for moving force identification (MFI) called preconditioned least square QR-factorization (PLSQR) method. The algorithm seeks to reduce the impact of identification errors caused by unknown noise. The biaxial moving forces travel on a simply supported bridge at three different speeds is used to generate numerical simulations to assess the effectiveness and applicability of the algorithm. Results indicate that the method is more robust towards ill-posed problem and has higher identification precision than the conventional time domain method (TDM). In addition, the robustness and ill-posed immunity of PLSQR are directly affected by two kinds of regularization parameters, namely, number of iterations j and regularization matrix L. Compared with the standard form of least square QR-factorization (LSQR), i.e., the regularization matrix L being the identity matrix In, the PLSQR with the optimal number of iterations j and regularization matrix L has many advantages on MFI and it is more suitable for field trials due to better adaptability with type of sensors and number of sensors.

Machinery at construction sites, pile driving, road and rail traffic and blasting are some of the main sources of ground vibration. Most of these actions are unavoidable and solutions should be found to mitigate their detrimental effects on the buildings in the vicinity and the activities conducted in them. Isolation of this vibration has become an important issue, especially in highly populated urban areas and around buildings with sensitive equipment and/or sensitive activities. Even though base isolation of the target structure is well accepted, its implementation cost is high due to the technology, materials and equipment required for effective isolation. Base isolation techniques are therefore constrained to buildings in areas with high seismic activities. On the contrary, the use of other isolation methods such as the use of ground barriers and ground improvements are cost effective and some experimental and numerical studies have been conducted on using trenches as ground barriers. It has been proven that trenches can be effectively used for ground vibration screening. However, since the problem involves a large number of parameters and the studies are case specific, conclusions made become difficult to correlate. The use of a single trench has been studied previously and at times it requires unrealistic depths to achieve the required vibration mitigation. To address this issue, this paper develops and presents a method for evaluating the effectiveness of mitigating ground vibration with dual or two trenches using artificial neural network (ANN). Towards this end, a finite element (FE) model was first developed and the modelling techniques were validated using results in the literature. It was then used to carry out a parametric study to provide information on the effects of controlling parameters on vibration mitigation. This information was used to develop an ANN to predict vibration mitigation with dual in-filled trenches under different conditions and constraints. The present method can be further extended to a wider range with more numerical simulations which will allow the development of a generic prediction model.

This study investigates the influence of vertical components (VCs) of seismic excitations on the response of short and tall (slender) superstructures, and compares them with the system response under only horizontal components (HCs). The first part of the study examines the capability of the bounding multi-surface plasticity model to identify dynamic soil properties and soil–pile–superstructure system response to the HCs of a strong ground motion using existing results from dynamic centrifuge tests. The influence of VCs on short and tall superstructures is then investigated, and compared with system response under only HCs. A procedure is proposed to select strong vertical ground motion to complete a nonlinear time-history analysis with a three-dimensional finite element model. Step-by-step modelling techniques are described with a direct-method framework to simulate complex soil–pile–superstructure systems. This study emphasises the role of VCs in the general response of the system in regard to selected damage parameters for pile foundations. The results indicate that VCs may have increasing effects on axial loads and maximum pile-cap displacements for short superstructures. In addition, contrary to the vertical vibration period of the superstructure, the variation of the superstructure’s horizontal vibration period with the peak ground acceleration ratio (V/H) may be significant.

This article introduces and evaluates the piecewise polynomial truncated singular value decomposition algorithm toward an effective use for moving force identification. Suffering from numerical non-uniqueness and noise disturbance, the moving force identification is known to be associated with ill-posedness. An important method for solving this problem is the truncated singular value decomposition algorithm, but the truncated small singular values removed by truncated singular value decomposition may contain some useful information. The piecewise polynomial truncated singular value decomposition algorithm extracts the useful responses from truncated small singular values and superposes it into the solution of truncated singular value decomposition, which can be useful in moving force identification. In this article, a comprehensive numerical simulation is set up to evaluate piecewise polynomial truncated singular value decomposition, and compare this technique against truncated singular value decomposition and singular value decomposition. Numerically simulated data are processed to validate the novel method, which show that regularization matrix [Formula: see text] and truncating point [Formula: see text] are the two most important governing factors affecting identification accuracy and ill-posedness immunity of piecewise polynomial truncated singular value decomposition.

Open deck steel bridges are characterized by the direct connection of transoms to the bridge girders. The expansion of steel girders due to thermal loads is transmitted by the fastening sys...

Refereed/Peer-reviewed Hollow block masonry buildings constructed alongside busy roads are vulnerable to vehicular impacts resulting in damage to property and harm to the building and vehicle occupants. This paper presents a method for the design and insertion of various forms of geometrically modified auxetic foam structures inside the hollow cores of block masonry walls for mitigating the adverse effects of such impacts. Due to the low tensile strength of masonry, the insertion material should possess high energy absorption characteristics and high strength for impact damage mitigation which can be achieved through auxetic foams with negative Poisson's ratio. To this end, finite element models of geometrically modified auxetic foams (GMAFs) are developed by inserting thin polyester sheets and hollow acrylonitrile butadiene styrene (ABS) tubes of various geometries into conventional polyurethane foams. The proposed geometrical configurations of inserted tubes and sheets result in auxetic behaviour of the conventional foam with a maximum negative Poisson's ratio of about-12. These foam models are validated analytically and then employed to model masonry walls with auxetic foam insertions in the hollow cores of blocks. These masonry wall models are then analysed under high-velocity lateral impacts. Results show the beneficial change in the failure mechanism of the masonry walls which altered from severe damage of wall face to the rebound of the impactor without penetration by reducing the displacement by four times, due to the presence of the auxetic foam insertions. This phenomenon occurred due to the significant energy dissipation caused by the combined effects of the re-entrant shaped hollow tubes and thin polyester sheet arrangements in the GMAF. Outcomes of this study will contribute towards safer masonry buildings along busy road fronts.

Vehicular crashes into buildings seem to be an on-going problem with severe consequences. When the building is of masonry, the damage at the impact zone is more severe with possible intrusion of the vehicle into the building, depending on the velocity of impact. In all these cases, vibration is propagated from the impact zone to the wall edges and then to adjoining walls in the building and can result in their damage. While the damage at the impact zone has been studied, the vibration propagation to the edges of the impacted wall and the adjoining walls and their potential for damage have not been treated. Dynamic response and damage of masonry walls due to vibration caused by vehicular impacts is important for the global safety assessment of the masonry structures. With this in mind, this paper presents a numerical study on the vibration-induced damage characteristics of the masonry structures subjected to vehicular impacts. A homogenised masonry material model incorporating strain rate effects suitable for impact applications using layered shell elements is adopted in this research with improved computational efficiency. The vibration induced damage at the edges of masonry walls is studied through numerical models of various types of wall structures. A validated vehicle model with deformable characteristics is employed to predict the HIC (Head Injury Criteria) to evaluate the head injury risk of the occupants of the vehicle when it crashes into the masonry structure. The outcomes of this study demonstrated that the vibration-induced damage in unreinforced masonry structures due to vehicular collision is more severe at low velocities compared that at high-velocity impacts. Moreover, the HIC value calculated for impacting vehicle velocity of 100 km/hr is 23.5, which is considerably lower than the HIC tolerance limit of 1000. This is a desirable safety feature for the occupants of the impacting vehicle, and it is due to the significant amount of energy absorbed at the impact zone and through the vibration transmission across the masonry wall Refereed/Peer-reviewed

This paper presents a new method that can locate and quantify damage in Euler-Bernoulli beams from changes in static deflection. Using the principle of Virtual Work, for the first time, the deflection change (DC) parameter is formulated as a function of both the damage location and damage severity. Through this, the study shows that the changes in static deflection follow certain patterns that clearly reveal the damage location. Therefore, by observing a plot of the measured DC, the damage locations can be identified conveniently. Once the damage is located, its severity is estimated directly from the measured relative deflection change through a new concept named damage severity consistency (DSC) function. A constant or nearly constant DSC function indicates a high precision of the damage detection results and reflects a good quality of the measurement data. Numerical and laboratory investigations demonstrate that the method accurately locates and quantifies the damage under various scenarios in statically determinate beams. The proposed damage detection method has a clear theoretical base, does not rely on an optimization algorithm, and can be extended to other beam-type structures including statically indeterminate beams.

Vibration characteristics of a structure can be used as an indication of its state of structural health as they vary if the structural health is affected by damage. This is the broad principle used in structural health monitoring for vibration-based damage detection of structures. Although most structures are built to have a long life span, they can incur damage due to many reasons. Early damage detection and appropriate retrofitting will enable the continued safe and efficient functioning of structures. This study develops and applies a dual-criteria method based on vibration characteristics to detect and locate damage in arch bridges. Steel arch bridges are one of the most aesthetically pleasing bridge types, which are reasonably popular in Australia and elsewhere. They exhibit three-dimensional and somewhat complex vibration characteristics that may not be suitable for traditional vibration-based damage detection methods. There have been relatively fewer studies on damage detection in these bridge types, and in particular the arch rib and struts, which are important structural components, have received little attention for damage detection. This study will address this research gap and treat the damage detection in the arch bridge structural components using the dual-criteria method to give unambiguous results. The proposed method is first validated by experimental data obtained from testing of a laboratory arch bridge model. The experimental results are also used to validate the modelling techniques and this is followed by damage detection studies on this bridge model as well as on a full-scale long-span arch bridge. Results demonstrate that the proposed dual-criteria method based on the two damage indices can detect and locate damage in the arch rib and vertical columns of deck-type arch bridges with considerable accuracy under a range of damage scenarios using only a few of the early modes of vibration.

For assessment of existing bridges, load rating is usually performed to assess the capacity against vehicular loading. Codified load rating can be conservative if the rating is not coupled with the field data or if simplifications are incorporated into assessment. Recent changes made to the Australian Bridge assessment code (AS 5100.7) distinguish the difference between design and assessment requirements, and include addition of structural health monitoring for bridge assessment. However, very limited guidelines are provided regarding higher order assessment levels, where more refined approaches are required to optimize the accuracy of the assessment procedure. This article proposes a multi-tier assessment procedure for capacity estimation of existing bridges using a combination of structural health monitoring techniques, advanced nonlinear analysis, and probabilistic approaches to effectively address the safety issues on aging bridges. Assessment of a Box Girder bridge was carried out according to the proposed multi-tier assessment, using data obtained from modal and destructive testing. Results of analysis at different assessment tiers showed that both load-carrying capacity and safety index of the bridge vary significantly if current bridge information is used instead of as-designed bridge information. Findings emerged from this study demonstrated that accuracy of bridge assessment is significantly improved when structural health monitoring techniques along with reliability approaches and nonlinear finite element analysis are incorporated, which will have important implications that are relevant to both practitioners and asset managers.

Damage identification for complex structures is a challenging task due to the large amount of structural elements, limited number of measured modes and uncertainties in referenced numerical models. This article presents a study on enhancing the effectiveness of modal characteristics correlation methods for damage identification of complex structures. First, a correlation method using change in the ratio of modal strain energy to eigenvalue is introduced. Damage information is determined via a forward approach by optimizing the correlation level between the patterns of the analytical and measured changes in the ratio of modal strain energy to eigenvalue. Different from traditional optimization-based forward methods that require accurate numerical models, damage sensitivity coefficients of the ratio of modal strain energy to eigenvalue are directly estimated from the experimental modal information. To enhance the damage identification capability, both the elemental modal strain energy–eigenvalue ratio and the total modal strain energy–eigenvalue ratio components are examined in the correlation function. Second, a sensitivity-weighted search space scheme incorporated with genetic algorithm is developed to overcome the ill-posed problem that causes false detection errors. Finally, the correlation method and the enhanced technique are experimentally tested on a complex truss model with nearly 100 elements. To deal with the huge number of degrees of freedom in this structure, a multi-layout roving test with the adoption of redundant channels is designed, and a three-criterion strategy is used for the selection of modes. Results demonstrate the effectiveness of the proposed damage assessment framework to locate and estimate damage in complex truss structures.

In recent years, it has become increasingly important to develop methodologies for reliable deterioration assessment of civil structures over their life cycle to facilitate maintenance and/or rehabilitation planning processes. Several approaches have been established to address this issue mainly using Bayesian probabilistic model updating techniques with some capability to incorporate uncertainties in the updating process. However, Bayesian model updating techniques are often found to be complex and computationally inefficient as opposed to their deterministic counterparts such as conventional or hybrid techniques of sensitivity-based model updating. Nevertheless, the deterministic model updating techniques have not been well developed for sophisticated assessment applications such as deterioration evaluation. To address these issues, this article presents a novel methodology for deterioration assessment of building structures under serviceability loading conditions, based upon an improved hybrid model updating approach incorporating the use of long-term monitoring data. This is first realized by a simple but effective scheme to simulate the deterioration mechanism in serviceability loading conditions before enhanced with innovative solutions to classify structural elements as well as to handle measurement and updating uncertainties in a meaningful way. The effectiveness of the established methodology is illustrated through a benchmark 10-story reinforced concrete building which is equipped with a long-term structural health monitoring system.

This paper develops a modified preconditioned conjugate gradient (M-PCG) method for moving force identification (MFI) by improving the conjugate gradient (CG) and preconditioned conjugate gradient (PCG) methods with a modified Gram-Schmidt algorithm. The method aims to obtain more accurate and more efficient identification results from the responses of bridge deck caused by vehicles passing by, which are known to be sensitive to ill-posed problems that exist in the inverse problem. A simply supported beam model with biaxial time-varying forces is used to generate numerical simulations with various analysis scenarios to assess the effectiveness of the method. Evaluation results show that regularization matrix L and number of iterations j are very important influence factors to identification accuracy and noise immunity of M-PCG. Compared with the conventional counterpart SVD embedded in the time domain method (TDM) and the standard form of CG, the M-PCG with proper regularization matrix has many advantages such as better adaptability and more robust to ill-posed problems. More importantly, it is shown that the average optimal numbers of iterations of M-PCG can be reduced by more than 70% compared with PCG and this apparently makes M-PCG a preferred choice for field MFI applications.

Load assessment of existing bridges in Australia is evaluated mainly using beam line model and the grillage analogy to examine the structural integrity of bridge components due to live loadings. With the majority of existing bridge networks designed for superseded design vehicular loading, the necessity to utilise more rigorous analysis methods to assess the load effects of bridges is indispensable. In this paper, various vehicular loading cases on a grillage model of a box girder bridge and its equivalent finite element model (FE) are considered, and their applicability for bridge assessment using structural health monitoring (SHM) as defined in the new revision of AS 5100.7 is studied. Based on numerical analyses, it was observed that component-level load effects in the two models have notable differences, irrespective of vehicle speed, position and loading. However, when global-level load responses are compared, the discrepancy in analysis outputs drops dramatically. The modelling ratios developed in this paper are practical and will be applicable with any modelling techniques for bridge assessment under vehicular loading on both a global and component-response basis. It was also observed that FE is more efficient in terms of model updating and damage simulation, and hence more appropriate for implementation of SHM techniques. The proposed flowchart suggested for heavy load assessment incorporates detailed and simple modelling approaches aligned with experimental data obtained by SHM techniques, which can be used for periodic and long-term monitoring of bridges. It can enhance the proper determination of bridge condition states, as any conservative estimation of bridge capacity may result in unnecessary load limitations.

Aesthetics and functionality requirements have caused most buildings to be asymmetric in recent times. Such buildings exhibit complex vibration characteristics under dynamic loads as there is coupling between the lateral and torsional components of vibration, and are referred to as torsionally coupled buildings. These buildings require three dimensional modelling and analysis. In spite of much recent research and some successful applications of vibration based damage detection methods to civil structures in recent years, the applications to asymmetric buildings has been a challenging task for structural engineers. There has been relatively little research on detecting and locating damage specific to torsionally coupled asymmetric buildings. This paper aims to compare the difference in vibration behaviour between symmetric and asymmetric buildings and then use the vibration characteristics for predicting damage in them. The need for developing a special method to detect damage in asymmetric buildings thus becomes evident. Towards this end, this paper modifies the traditional modal strain energy based damage index by decomposing the mode shapes into their lateral and vertical components and to form component specific damage indices. The improved approach is then developed by combining the modified strain energy based damage indices with the modal flexibility method which was modified to suit three dimensional structures to form a new damage indicator. The procedure is illustrated through numerical studies conducted on three dimensional five-story symmetric and asymmetric frame structures with the same layout, after validating the modelling techniques through experimental testing of a laboratory scale asymmetric building model. Vibration parameters obtained from finite element analysis of the intact and damaged building models are then applied into the proposed algorithms for detecting and locating the single and multiple damages in these buildings. The results obtained from a number of different damage scenarios confirm the feasibility of the proposed vibration based damage detection method for three dimensional asymmetric buildings.

Structural stiffness of a real tension structure may degrade due to many factors, so the stiffness monitoring is very important. If the displacements under the dominant design loads are obtained, the stiffness state of the real structure can be intuitively assessed by a deformation checking process. However, exerting design loads on a real structure is neither efficient nor economical, because they usually have too many loading points. A method is hence proposed to indirectly measure the displacements under the design loads by merely exerting several simple testing loads. By utilizing the linear combination of several contributing eigenvectors to express the displacements, the problem of measuring displacements is transformed to that of measuring combinational coefficients of these contributing eigenvectors. The relationship between the combinational coefficients of the mutual contributing eigenvector of the design load and the testing load is set up firstly, with two basic conditions established. To satisfy the basic conditions, a strategy to decompose the design load and an algorithm to find proper testing loads are suggested. The numerical example of a cable net with two typical design loads is finally analyzed. Results illustrate that the proposed indirect method is effective, with three simple testing loads (no more than 3 loading points) found to replace the two design loads (181 loading points) in the on-site static testing. Besides, the proposed indirect method is more robust to resist the influence of measurement noise than the traditional direct method. The reason why the proposed indirect method has better robustness is also discussed.

Hyperbolic cooling towers are large thin shell reinforced concrete structures that are used to remove the heat from wastewater and transfer it to the atmosphere using the process of evaporation. During its long service life, a cooling tower can experience damage due to the large temperature variations, environmental degradation, or random actions such as impacts or earthquakes. Such a damage can develop over time and result in the sudden collapse of the cooling tower. To ensure that a cooling tower operates safely and efficiently at all times, it is important to monitor its structural health. In this context, structural health monitoring based on the vibration characteristics of the structure, has emerged as a useful method to detect and locate damage in structures. Hyperbolic cooling towers, due to their particular shape, exhibit rather complex vibration characteristics that do not suit the traditional vibration-based damage detection techniques. This paper develops and applies a damage assessment method using the absolute changes in mode shape curvature (ACMSC) in conjunction with Artificial Neural Networks (ANNs) to detect, locate, and quantify damage in hyperbolic cooling towers. ANN is a machine learning technique that can predict behavioural patterns using a set of data samples and finds use in the damage quantification process. The proposed method for detecting and locating damage is experimentally validated and demonstrated its capability to accurately detect and locate damage. A feed-forward network having one hidden layer with Bayesian algorithm is used to train the artificial neural network. Damage indices calculated from noise polluted mode shape data are used to train the network. The trained network is then used to successfully assess the unknown damage severities in the cooling tower. The outcomes of this paper will enable early warning of damages in the cooling towers and will help towards their safe operation.

Structural Identification (St-Id) is the process of constructing and calibrating a physics-based model based on the measured static and/or dynamic response of the structure. Over the last two decades, although the St-Id methods have become increasingly popular amongst civil–structural engineering communities, most complete and successful applications are often found with flexible structures such as long-span bridges and towers. Very few comprehensive studies were reported on building structures, especially those with medium-rise characteristics which are often associated with complicated analytical modelling and different degrees of parameter uncertainties. To address this need, this paper presents an in-depth study on St-Id of a benchmark medium-rise building firstly demonstrating the importance of developing appropriate initial analytical models that can be used for the automated model calibration techniques. Then, a novel parametric study-based sensitivity analysis approach is introduced to identify tuning parameters as well as their appropriate ranges to maximise the correlation of the calibrated model whilst preserving the physical relevance of the calibrated model. Modal data of the first few modes measured under ambient vibration conditions are used in this study. Further application of the St-Id process developed herein for structural health monitoring (SHM) of buildings is also discussed.

Structural failure can be prevented if the damage in the structure is detected at its onset and appropriate retrofitting carried out. Towards this end, this paper presents a vibration-based technique, using only the first vibration mode, for predicting damage and its location and severity in steel beams that are important structural components in buildings and bridges. For single damage scenarios, the modal strain energy based damage index β was capable of detecting, locating and quantifying damage. For multiple damage scenarios, Artificial Neural Network incorporating β as the input layer was used. This research used computer simulations supported by limited experiments. Damage intensity was specified as a percentage reduction in stiffness compared to that at first yield. The procedure is illustrated through several numerical examples and the results confirm the feasibility of the method and its application in preventing structural failure. Keywords: Damage prediction, Failure prevention, Vibration based technique, Modal strain energy, Artificial Neural Network, Damage location, Damage severity, Damage index, Damage scenarios.

This paper proposes a new methodology for moving force identification (MFI) from the responses of bridge deck. Based on the existing time domain method (TDM), the MFI problem eventually becomes solving the linear algebraic equation in the form Ax = b . The vector b is usually contaminated by an unknown error e generating from measurement error, which often called the vector e as ‘‘noise’’. With the ill-posed problems that exist in the inverse problem, the identification force would be sensitive to the noise e . The proposed truncated generalized singular value decomposition method (TGSVD) aims at obtaining an acceptable solution and making the noise to be less sensitive to perturbations with the ill-posed problems. The illustrated results show that the TGSVD has many advantages such as higher precision, better adaptability and noise immunity compared with TDM. In addition, choosing a proper regularization matrix L and a truncation parameter k are very useful to improve the identification accuracy and to solve ill-posed problems when it is used to identify the moving force on bridge.

Use of concrete filled steel tube columns is becoming increasingly popular in high rise buildings due to their composite action, superior strength, seismic and fire resistance capacities and construction simplicity. These composite columns and the reinforced concrete (RC) lift core in the framing systems of high rise buildings are commonly coupled with reinforced concrete outrigger and belt systems to facilitate lateral load resistance. Axial shortening (AS) of the vertical structural components due to time dependent phenomena of basic creep, shrinkage and elastic deformation, is a common problem in concrete high rise construction. The creep and shrinkage of these composite columns develop more rapidly, but are comparatively lower in magnitude than for RC columns due to the concrete core having no direct exposure to the external environment. There is a need for a comprehensive understanding of the differential axial shortening (DAS) in concrete filled tube (CFT) buildings which will be different from that in a RC building. An appraisal of the DAS and accurate quantification of all the adverse effects that can occur in a building due to DAS, are required to facilitate a safe and efficient design. This paper develops and applies a comprehensive technique to evaluate the DAS in a high rise building with composite CFTs. This technique incorporates the effects of (i) construction sequence and concrete levelling (ii) stress relaxation of concrete due to the presence of the steel tube (iii) time dependent material properties and (iv) effects of belt and outrigger systems. The technique has been validated using experimental data and is then illustrated through its application to a 60 storey building with CFT columns. The DAS between the vertical members are evaluated and its effects on the structural components are studied. Finally, the technique is applied to a similar building with RC columns and the results compared with those from the CFT building. The technique developed in this paper and the new information on DAS generated will facilitate safer designs of buildings with composite CFT columns.

Vibration based Structural Health Monitoring (SHM) has a seasoned commitment in assessing the performance of structures continuously and detecting damage in an early stage which minimizes chances of structural failures and cost of maintenance. However, SHM is still an emerging branch of engineering and has many challenges yet to be resolved before it can be employed widely in various structures and conditions. This study presents a new Modal Kinetic Energy (MKE) based approach to identify and assess damage in structures. A new damage sensitivity parameter has been developed based on modal kinetic energy change concept. The sensitivity matrix thus developed is applied on damage quantification procedure. Finally, some numerical studies are conducted on a simply supported beam to confirm its robustness under various test conditions. The simulation results revealed that the proposed approach can successfully detect and estimate single and multiple damage even in noise contaminated environment.

Steel modular building structures are being increasingly adopted for a variety of building applications since their method of construction, despite being relatively new, offers many benefits over conventional constructional methods. Even though their behaviour under gravity (dead and live) loads is generally well understood, their response to lateral dynamic loads such as seismic and wind loads, is relatively less known. Due to their unique structural detailing, their structural response and failure patterns under lateral dynamic loading can vary considerably from that exhibited by conventional structures. Limited research has shown that under lateral loadings, modular structures tend to fail at the columns which are critical members whose failure can lead to partial or total collapse of the structure. This paper aims to mitigate this by shifting the failure away from the columns to inter-modular connections which can be allowed to deform in a ductile manner. Towards this end, this paper proposes two innovative inter-modular connections and investigates their performance under monotonic and cyclic lateral loading using comprehensive validated numerical techniques. The proposed connections have an additional steel plate and resilient layers to provide increased ductility and dissipation of seismic energy with desired ductile failure mechanisms. Three-dimensional numerical models of the proposed connections are developed in ABAQUS software considering geometric and material nonlinearities, as well as contact formulations to accurately capture their response to the lateral loads and failure propagations. The numerical model is verified based on experimental results in the literature and used for extensive parametric studies. Seismic reliance of the proposed connections in terms of ductility, failure patterns, and energy absorption are compared with those of a standard inter-modular connection currently used in modular buildings. The outcome of this study demonstrates that the proposed connections have superior dynamic performances compared to the standard inter-modular connections in use today. New information generated through this study will enable to improve life safety and dynamic performance of modular building structures under typical gravity loads as well as under seismic loading., Civil engineering; Construction engineering; Structural analysis; Structural engineering; Structural mechanics; Failure mechanism; Innovative inter-modular connection; Lateral loading; Seismic mitigation; Steel modular structures

Structural health monitoring plays a significant role in providing information regarding the performance of structures throughout their life spans. However, information that is directly extracted from monitored data is usually susceptible to uncertainties and not reliable enough to be used for structural investigations. Finite element model updating is an accredited framework that reliably identifies structural behavior. Recently, the modular Bayesian approach has emerged as a probabilistic technique in calibrating the finite element model of structures and comprehensively addressing uncertainties. However, few studies have investigated its performance on real structures. In this article, modular Bayesian approach is applied to calibrate the finite element model of a lab-scaled concrete box girder bridge. This study is the first to use the modular Bayesian approach to update the initial finite element model of a real structure for two states—undamaged and damaged conditions—in which the damaged state represents changes in structural parameters as a result of aging or overloading. The application of the modular Bayesian approach in the two states provides an opportunity to examine the performance of the approach with observed evidence. A discrepancy function is used to identify the deviation between the outputs of the experimental and numerical models. To alleviate computational burden, the numerical model and the model discrepancy function are replaced by Gaussian processes. Results indicate a significant reduction in the stiffness of concrete in the damaged state, which is identical to cracks observed on the body of the structure. The discrepancy function reaches satisfying ranges in both states, which implies that the properties of the structure are predicted accurately. Consequently, the proposed methodology contributes to a more reliable judgment about structural safety.

Track thermal buckling is one of the primary safety issues of continuously welded rail tracks. The lateral track resistance is the main resisting force against track buckling, which is mainly provided through the interaction of sleepers in the ballast material. In this sense, researchers have focused on determining the lateral resistance of various types of sleepers in ballast material through tie push tests; yet the implications of these results on track buckling temperature have not been fully addressed. The aim of this paper is to fulfill this gap by analyzing the performance of three types of concrete sleepers on track buckling temperature: B70, winged and frictional concrete sleepers. A finite element model of the track is developed and updated based on the results of single tie push tests performed on each type of sleeper. The model is then used to estimate the buckling temperature of tangent and curved sections of tracks. In addition, a sensitivity analysis of the parameters involved in track buckling is presented. It is concluded that for a tight curve of radius 100 m, only frictional concrete sleepers can resist track buckling, if a safe temperature of 40 °C is considered for the track. For the same safe temperature, conventional B70 sleepers can only be used in curves with a radius larger than 1200 m.

Moving force identification (MFI) is a widely concerned inverse problem in structural dynamics and well-known as intrinsically existing ill-posedness. With the help of Arnoldi process and Krylov subspace method, the generalized minimal residual (GMRES) method can be improved to a range restricted generalized minimal residual (RRGMRES) method. Furthermore, by introducing the smoothing-norm preconditioning, a preconditioned range restricted generalized minimal residual (PRRGMRES) method is proposed to provide a stable solution to the ill-posed dynamic force identification problem. Simulations show that the novel method has significant improvement when compared to the classic time domain method and the RRGMRES method. In addition, to show the effectiveness and advantages of the proposed method, the PRRGMRES method is also compared with a newly-proposed regularization method named the preconditioned least square QR-factorization (PLSQR) method. Simulation results show that the PRRGMRES method has much better robustness and higher computational efficiency than the PLSQR method especially in dealing with highly inaccurate measurement cases. Finally, the accuracy and efficiency of the PRRGMRES method is verified by experimental studies. The PRRGMRES method has good performance in both overcoming ill-posed problems and improving computational efficiency, which should be of the highest priority in adoption for MFI.

Visual inspection of a steel truss railway bridge revealed multiple fatigue cracks on the top member of the truss, mainly attributed to the high impact loads of crossing wheels over the jointed tracks on the bridge. The proposal to replace the jointed track with continuously welded rails (CWR) raised a number of issues regarding the thermal interaction of track and bridge, as the bridge experiences extreme temperature variations. Incorporation of high longitudinal restraint between the track and the bridge may increase the risk of track buckling failure at bridge transition zones, since bridge thermal expansion during hot weather can add compressive forces to the rails transferred through the track fastening system. Reducing longitudinal restraining may increase the size of a rail gap resulting from cold weather rail fracture. An optimal longitudinal fastening profile between the bridge and the track therefore is required to mitigate thermal issues both in hot summers and cold winters. To do so, a numerical model of the track and the bridge is developed in Abaqus and calibrated based on the results of tests performed on the bridge and available literature. Three longitudinal fastening profiles between the bridge and the track are introduced in the numerical model and performance of each for mitigating buckling failure and cold weather rail fracture are analyzed. It is concluded that providing 50% resilient fasteners and 50% zero toe load fasteners on each span can be a sound approach to mitigating the thermal issues of CWR tracks on the bridge.

Moving force identification (MFI) from dynamic responses of bridges is a typical inverse problem with ill-posedness. Under the efforts of researchers, some regularization methods have been presented to solve the ill-posed problem, but there still lacks an effective index to reveal the ill-posedness of the vehicle–bridge dynamic system such that it can be utilized as a guidance for the regularization parameter selection. In this paper, an ill-posedness indicator (IPI) defined as the ratio of the Fourier coefficient to the singular value is adopted to reveal the ill-posedness in the MFI problem. Simulation results show that the larger the IPI value is, the more obvious the ill-posedness of the vehicle–bridge system equation, namely, the intrinsic factor of ill-posedness in MFI is attributed to very large IPI value. The maximum IPI value increases with the increasing noise level, which leads directly to the ill-posedness of the vehicle–bridge system equation. In addition, a relative percentage error (RPE) is used to select the optimal regularization parameters, while evaluating the ill-posedness existing in the MFI. Using the proposed IPI value, the influence of ill-posedness on identified results is evaluated in this study, which can assist qualitatively and quantitatively in selecting optimal regularization parameters and proper regularization methods.

Insufficient available dynamic characteristics data of real structures during the service and prior to damage is a concern in Structural Health Monitoring (SHM) employing Vibration Based Damage Detection (VBDD) techniques. The issue becomes more intense with complexity of the structure. One remedy for this problem is to apply new methodologies to the same structure as the benchmark structure having measured data available at different cases. Hence, the reliability of the proposed approach is typically confirmed in reality for that type of structures. This study aims to examine the application of an improved two-stage Modal Strain Energy (MSE) method to a benchmark bridge available, whereas the MSE method has already been numerically and experimentally verified. For this purpose, a steel truss bridge model is numerically simulated. Different damage scenarios, affected by up to five percent noise are considered and the first five vertical mode shapes are used. The results show that the proposed method is proper for health monitoring of complex bridges and accurately identifies the damage in the bridge model under consideration. The findings of this paper can confidently contribute to academic studies and the bridge industry to realize the genuine condition and behaviour of complex bridges during the damage.

Increasing applications of large diameter and long span cables as key structural components in cable supported structures are evident. However these cables accumulate damage over time during their life cycle and such damage needs to be detected to avoid the detrimental influences on the serviceability and ultimate capacity of the structure. In this context, vibration based damage detection (VBDD) methods have been used in some structures. Cable structures however exhibit complex vibration patterns namely with vertical, lateral, torsional and coupled modes which complicate the vibration based damage detection procedure. To address this matter, this paper proposes a new approach for detecting and locating damage in cables using component specific damage indices (DIs) based on the modal flexibility method considering the modal mass participation. Application of this new procedure is illustrated through two case studies: - (i) a suspended cable, and; - (ii) a three dimensional (3D) suspension bridge structure. Results verify that the DIs based on the lateral and vertical components of mode shapes, identified through their modal mass participation factors, are effective for detecting and locating damage in suspended cables and the main cables in a suspension bridge respectively, under a range of damage scenarios. Consequently, the research outcomes of this paper confirm that the modal mass participation factor is an important signature in damage detection of a structure using VBDD techniques.

The durability of carbon fibre reinforced polymer (CFRP) strengthened steel circular hollow section (CHS) member under prolonged cold weather has not been explored sufficiently. Furthermore, various parameters that may affect the durability of such members have not been revealed yet. This paper presents an analytical and experimental study with a finite element (FE) approach to study the effects of prolonged cold weather (+3 °C) exposure on CFRP strengthened CHS member subjected bending. It was found that a prolonged exposure about 12 month cold weather immersion adversely affected the durability of strengthened beams by reducing strength and stiffness. Durability design factor has been recommended. The proposed analytical models and FE models were found in good agreement with the experimental results. The results of parametric studies showed that the durability design factors varied from section to section, CFRP with higher tensile modulus and higher number of CFRP layers performed better in cold weather.

This paper presents the results from a research program to investigate the durability of CFRP strengthened steel circular hollow section (CHS) members with and without embedded glass fibre reinforced polymer (GFRP) at ambient (24 °C ± 4 °C) and 50 °C temperatures under accelerated corrosion environment. The beams were tested to failure under four-point bending. It was found that the accelerated corrosion adversely affected the durability of the strengthened beams at both temperatures and the embedded GFRP enhanced the durability. Durability design factor has also been recommended. The proposed theoretical approach predicts ultimate loads reasonably compared to experimental value of ultimate loads.

Suspension bridges are flexible and vibration sensitive structures that exhibit complex and multi-modal vibration. Due to this, the usual vibration based methods could face a challenge when used for damage detection in these structures. This paper develops and applies a mode shape component specific damage index (DI) to detect and locate damage in a suspension bridge with pre-tensioned cables. This is important as suspension bridges are large structures and damage in them during their long service lives could easily go un-noticed. The capability of the proposed vibration based DI is demonstrated through its application to detect and locate single and multiple damages with varied locations and severity in the cables of the suspension bridge. The outcome of this research will enhance the safety and performance of these bridges which play an important role in the transport network.

In a prestressed concrete bridge, the magnitude of the prestress force (PF) decreases with time. This unexpected loss can cause failure of a bridge which makes prestress force identification (PFI) critical to evaluate bridge safety. However, it has been difficult to identify the PF non-destructively. Although some research has shown the feasibility of vibration based methods in PFI, the requirement of having a determinate exciting force in these methods hinders applications onto in-service bridges. Ideally, it will be efficient if the normal traffic could be treated as an excitation, but the load caused by vehicles is difficult to measure. Hence it prompts the need to investigate whether PF and moving load could be identified together. This paper presents a synergic identification method to determine PF and moving load applied on a simply supported prestressed concrete beam via the dynamic responses caused by this unknown moving load. This method consists of three parts: (i) the PF is transformed into an external pseudo-load localized in each beam element via virtual distortion method (VDM); (ii) then these pseudo-loads are identified simultaneously with the moving load via Duhamel Integral; (iii) the time consuming problem during the inversion of Duhamel Integral is overcome by the load-shape function (LSF). The method is examined against different cases of PFs, vehicle speeds and noise levels by means of simulations. Results show that this method attains a good degree of accuracy and efficiency, as well as robustness to noise.