Updated Numerical Model Research Articles

Fatigue damage assessment of a large rail-cum-road steel truss-arch bridge using structural health monitoring dynamic data

Structural health monitoring (SHM) system provides valuable information for the fatigue assessment of existing rail-cum-road bridges. This paper aims to develop an effective fatigue assessment approach for the rail-cum-road bridge, Jiujiang Yangtze River Bridge, by utilising the SHM data, focusing on dynamic modal analysis, finite element model updating and fatigue assessment. First, the traffic load spectrum and modal characteristics of the bridge are investigated from the SHM data. A three-dimensional finite element model is constructed and then updated by using the measured modal data through the proposed regularised model updating method. Then, the updated numerical model is verified with the measured dynamic response data, which can be utilised for calculating stress response at critical structural components of the rail-cum-road bridge. Finally, an improved Corten-Dolan’s model is proposed to analyse the fatigue damage and structural reliability of the critical structural components of the bridge, taking into account the combined effects of train and highway vehicle loads. The results demonstrate that the proposed fatigue assessment method provides more reliable results for the rail-cum-road bridge by considering the combined effect of multi-level traffic loads and the non-linear fatigue damage accumulation. It is concluded that the short H-shaped suspender is identified as the most vulnerable structural member of the rail-cum-road bridge, and the remaining fatigue service life of the typical components of the bridge should meet the design requirement.

Damage detection of a cable-stayed footbridge using multiple damage modelling and neural networks

This paper presents a routine for damage detection based on multiple damage modelling and artificial neural networks. The routine aims to identify the existence, location, and the most damaged elements. The first step is to define "critical" regions based on stresses and deformations of the updated numerical model of the structure, as well as the probable order of occurrence in the case of multiple damage by simulating different scenarios. The second step is to train a neural network using the natural frequencies of the intact and damaged numerical models as input data and vectors that indicate the position and magnitude of the damage as expected output. The feed-forward backpropagation neural network was adopted. The approach was used to evaluate a cable-stayed footbridge. A new dynamic test was performed and a vector composed of the identified frequencies was input into the network, which indicated the existence of possible damage. The provided damage scenario was applied to the updated model, along with the prestressing forces of the stays obtained experimentally. The maximum difference between the frequencies of the updated and damaged numerical model with the damage vector provided by the network and the frequencies experimentally identified in the new test was 1.80%.

Element-wise parallel deep learning for structural distributed damage diagnosis by leveraging physical properties of long-gauge static strain transmissibility under moving loads

The Transmissibility Function (TF) has gained considerable interest in structural damage detection because of its relatively high sensitivity to damage and robustness to excitation. This study proposed a distributed damage diagnosis method for beam-like structures based on a long-gauge static strain TF defined as the ratio of the Fourier transform of static strain response under moving loads from a target long-gauge sensor to that from the reference sensor. It has been discovered that each long-gauge static strain TF is independent of moving loads, making it an ideal damage indicator. It exhibits direct proportionality to the ratio of bending stiffness between the two measured zones covered by the target and reference long-gauge strain sensors while being unaffected by the stiffness of any other zones not covered by these two sensors. Moreover, the TF at zero frequency was proved to be equivalent to the ratio of static strain time history areas, relying solely on the stiffness of the covered zones. Leveraged by the physical properties of long-gauge static strain TF, an element-wise parallel deep neural network architecture was developed to decompose damage diagnosis into independent sub-tasks on the element level, utilizing a variational autoencoder (VAE) in the Bayesian inference framework for extracting features from the long-gauge strain TF and a regressor for mapping the features to elemental stiffness reduction. The divide-and-conquer strategy and element-wise parallel learning architecture allow for a significant reduction in the number of labeled training samples generated based on the updated numerical baseline model as it only requires simulated scenarios involving a single damage element. The efficiency and robustness of the proposed method were demonstrated through a numerical simply supported beam and a laboratory experiment on a two-span bridge.

An optimized dynamic model improved deep discriminative transfer learning network for fault detection in rotation vector reducers

In recent years, recognized fault types using artificial intelligence (AI) models has gradually become one of the mainstream directions in the field of mechanical fault diagnosis. However, it is very difficult to obtain relatively complete fault samples, which limits the application of AI models for complex mechanical systems, such as rotation vector (RV) reducers. To address this issue, physical model-based fault sample generation methods attracted many attentions but still an open problem: the difference in fault samples between numerical simulation and measurement of a physical system needs to be well decreased. Therefore, this article proposes an improved deep discriminative transfer learning network (IDDTLN) for RV reducer fault diagnosis. The presented network is driven by an optimized dynamic model. Firstly, the measurement normal signal and whale optimization algorithm (WOA) are utilized to update the dynamic model parameters of the RV reducer. Secondly, the updated numerical model is employed to calculate simulation fault samples. Finally, simulation samples and unlabeled measurement fault samples are used to train IDDTLN. The trained IDDTLN can accurately identify the unknow measurement fault samples. The data obtained from RV reducer test rigs are utilized to explore the feasibility of the proposed method, and the classification accuracies reach 99.8 %.

Maximizing aged photovoltaic array power: a computer modelling study

Abstract Photovoltaic (PV) modules age with time for various reasons such as corroded joints and terminals and glass coating defects, and their ageing degrades the PV array power. With the help of the PV array numerical model, this paper explores the effects of PV module ageing on the PV array power, and the power gains and costs of rearranging and recabling aged PV modules in a PV array. The numerical PV array model is first revised to account for module ageing, rearrangement and recabling, with the relevant equations presented herein. The updated numerical model is then used to obtain the array powers for seven different PV arrays. The power results are then analysed in view of the attributes of the seven PV array examples. A guiding method to recommend recabling after rearranging aged modules is then proposed, leading to further significant power gains, while eliminating intra-row mismatches. When certain conditions are met, it was shown that recabling PV modules after rearranging them may lead to further significant power gains, reaching 57% and 98% in two considered PV array examples. Higher gains are possible in other arrays. A cost–benefit analysis weighing annual power gains versus estimated recabling costs is also given for the seven considered PV array examples to guide recabling decisions based on technical and economic merits. In the considered examples, recabling costs can be recovered in <4 years. Compared with the powers of the aged arrays, power gains due to our proposed rearranging and recabling the PV arrays ranged between 73% and 131% in the considered examples—well over the gains reported in the literature. Moreover, the cost of our static module rearrangement and recabling method outshines the costs of dynamic reconfiguration methods recently published in the literature.

Towards an active semi-anechoic room: simulations and first measurements

Semi-anechoic rooms are used for the acoustic characterisation of noise sources. They involve heavy infrastructures and thick absorbent lining. The aim of this work is to demonstrate a less expensive alternative by complementing a thin passive coating with an active technology. Previous work has achieved the active reduction of the pressure scattered by the reflective wall of a semi-anechoic room, in the 80–200 Hz frequency band. This work validated an innovative approach allowing to control the scattered pressure throughout the measurement volume, using a setup located over its periphery. This paper extends a previous presentation at Forum Acusticum dealing with the active control of the low-frequency reflections on the walls and ceiling of a semi-anechoic room [Pinhède et al., Forum Acusticum 2023, Torino, Italy, 11–15 September, 2023, https://doi.org/10.61782/fa.2023.0399]. We describe the design principles and the 2D semi-analytical and 3D finite element simulations of the control system that help optimise parameters such as the transducers number and locations. A full-scale demonstrator has been built to validate the control strategy. Acoustics measurements, which have been used to characterise the room acoustics and to update the simulation parameters are also presented and compared to an updated numerical model.

Digital twin framework using agent-based metaheuristic optimization

Despite advances in instrumentation and measurement techniques, it is still necessary to update numerical models to simulate or predict some structural responses, for example. Thus, this work proposes a metaheuristic framework based on hybrid agents, an approach within the Artificial Intelligence (AI) topics for updating Finite Element (FE) numerical models. This framework aims to provide flexible non-deterministic strategies to guide the updating process, ranging from simple local search procedures to complex learning processes. Two case studies are presented: (i) a free–free aluminium beam tested under laboratory conditions and; (ii) a catamaran tested during a sea trial under real operating conditions. The updating process aimed to optimize the stiffness matrix while maintaining the mass matrix unchanged. The objective function seeks to minimize the differences between numerical and experimental modal parameters, namely, natural frequencies and vibration modes. Results from the digital twin framework showed that the difference in natural frequencies significantly decreased, for example, 9% to 1% for the free–free aluminium beam and 15% to 4% for the catamaran’s main deck, when comparing the experimental with the updated FE model. As for the updated FE vibration modes, the Modal Assurance Criteria (MAC) values decreased slightly in both cases but within the acceptable MAC values (above 0.9), thus showing good consistency with the experimental vibration modes. In the end, the proposed framework was able to update the FE model directly using its respective reduced model, circumventing the”black box” of commercial packages.

Post-Earthquake Dynamic Performance of Intact Masonry Building Based on Finite Element Model Updating

The recent seismic activity in Croatia has inflicted significant damage upon numerous buildings, with masonry structures being particularly affected. Consequently, experimental investigations and structural condition assessments’ have garnered increased attention, as they have become integral to the renovation process for such buildings. Additionally, assessing the structural condition prior to seismic events is vital for determining the extent to which earthquakes impact the stiffness of systems, such as masonry structures. This paper presents the results of experimental investigations and numerical analysis conducted on a damaged high school building in Sisak, Croatia. The experimental investigation involved shear testing, flat jack analysis, and operational modal analysis. Utilizing the available drawings and mechanical properties determined experimentally, an initial numerical model was developed. Subsequently, through the iterative process of finite element model updating, the initial numerical model was refined based on the structural dynamic properties. The updated numerical model was then employed to assess the structural condition prior to the earthquake event. This study contributes to the field by providing insights into the post-earthquake estimation of dynamic properties in intact masonry buildings, utilizing a comprehensive approach that combines experimental investigations and finite element model updating. By quantifying the changes in dynamic parameters, such as natural frequencies and mode shapes, the study provides valuable insights into the response characteristics of damaged masonry building. The observed differences in natural frequencies between the damaged and undamaged states are as follows: 9% for the first mode shape, 6% for the second mode shape, and 2% for the third mode shape.

An updated numerical model of fracture fluid loss coupled with wellbore flow in managed pressure drilling

The loss of drilling fluids often occurs during reservoir extraction in fractured formations, and the prediction of natural fracture loss rate is vital for controlling drilling fluids loss. However, the coupling of loss model to wellbore flow has rarely been considered. Based on the non-Newtonian fluid loss dynamics theory, this study considers Herschel–Buckley fluid and develops an updated numerical model to couple the loss of fracture with wellbore flow. The roughness of the fracture is characterized using the continuous random accumulation method. The coupling model is verified by field data, and its simulated results show the average relative and maximum relative errors were 4.76% and 12.8%, respectively. A linear throttle valve is introduced to simulate the effect of regulating wellhead back pressure and pump displacement on drilling fluids loss in managed pressure drilling, and the results indicate that the impact of regulating wellhead back pressure is better than that of pump displacement. This paper studies the pressure fluctuates of the fractured borehole breathing mechanism in detail and has proposed two possible scenarios that may cause borehole breathing. Increasing the wellhead back pressure can convert the overflow into loss, while reducing the wellhead back pressure by too much at once may also turn a loss into an overflow. The orthogonal experiment design is performed to study the influence of eight parameters on the loss rate, and the order of influence is as follows: fracture width, fluidity index, fracture area, consistency factor, yield stress, drilling fluids density, circulating displacement, and fracture dip.

Vision-based model updating and evaluation of miter gates on inland waterways

Miter gates are critical components of inland waterways infrastructure, typically used as both the door for and damming surface of locks. Therefore, knowing the condition of miter gates is especially important to ensure their continued operation. Measured displacements of the gates under load are known to be informative of their condition. Such measurements can also be used to update numerical models of the structure that can serve as part of a digital twin, allowing for more comprehensive management of the infrastructure. However, model updating of large-scale infrastructure requires sufficient displacement data that are often challenging to obtain, due in part to inaccessibility and a lack of a viable reference location for contact-type sensors. Vision-based displacement measurements have been proposed to inform a model-updating scheme of the miter gates; however, several challenges have prevented field implementation of these technologies. First, determining the appropriate location and orientation of cameras is critical to obtaining useful displacement information for model updating. In addition, environmental factors that can negatively affect vision-based structural displacement measurements such as lighting changes and camera motion need to be remediated. Moreover, interpreting displacement from photographic imagery is abstract because 2D images can only capture a projection of displacements of the 3D structure or the 3D numerical models. This research addresses each of the challenges through the use of a graphics-based digital twin (GBDT). Prior to conducting the field survey, optimal camera locations and orientations are explored. Additionally, a robust optical flow method is developed to mitigate the negative influence from environment factors on displacement measurements. Finally, displacement from the photographic survey is interpreted by projecting displacement from the numerical models onto the 2D image plane using the GBDT; the difference between these displacements is used to inform a heuristic-based model updating strategy. The proposed approach is demonstrated on the miter gates at The Dalles Lock and Dam. This initial study focuses on determining degradation parameters to which the displacement measurements of the miter gate are most sensitive, laying the groundwork for future rigorous model updating to provide the necessary information regarding repairs and retrofits that would otherwise be difficult to obtain. The main novelty and contribution of this research lie in how the practical challenges of field implementation of existing technologies regarding vision-based model updating are effectively resolved, thus bridging the gap between theory and application to large-scale civil infrastructure.

Dynamic characteristic modeling and simulation of an aerospike-shaped pintle nozzle for variable thrust of a solid rocket motor

To utilize propulsion energy effectively, it is necessary to develop technology that can enable variable thrust by altering the area of the nozzle throat in a solid rocket motor in real time. In this study, an aerospike-shaped pintle nozzle, an altitude compensation nozzle technology, was designed to improve the performance compared to that of the existing pintle nozzles. Pressure fluctuations caused by the movement of the pintle led to the hysteresis of the combustion chamber pressure, which sharply increased the pintle load. Depending on the design conditions of the actuator, a load that was approximately 2.5 times larger than that in the normal state could be applied to the actuator. Additionally, cold flow tests were conducted under static conditions to verify the reliability of the design code for the actuator load prediction results. Moreover, firing tests were performed to verify the reliability of the internal ballistic simulation code. Finally, factors related to the thermal expansion of the pintle and the deformation of the nozzle throat, which caused changes in the nozzle throat area during combustion, were identified and mathematically modeled. Additional firing tests were conducted to validate the updated numerical model. Before the model was updated, a pressure difference occurred at most three times or more between the performance prediction model and the firing test results, but the performance prediction error was reduced when the modified numerical analysis was used. If the present results are applied to a guided missile system, the high-altitude operation performance will improve and precision thrust control will become possible, enabling flexible guided missile system operation.

Influence of Analog and Digital Crease Lines on Mechanical Parameters of Corrugated Board and Packaging.

When producing packaging from corrugated board, material weakening often occurs both during the die-cutting process and during printing. While the analog lamination and/or printing processes that degrade material can be easily replaced with a digital approach, the die-cutting process remains overwhelmingly analog. Recently, new innovative technologies have emerged that have begun to replace or at least supplement old techniques. This paper presents the results of laboratory tests on corrugated board and packaging made using both analog and digital technologies. Cardboard samples with digital and analog creases are subject to various mechanical tests, which allows for an assessment of the impact of creases on the mechanical properties of the cardboard itself, as well as on the behavior of the packaging. It is proven that digital technology is not only more repeatable, but also weakens the structure of corrugated board to a much lesser extent than analog. An updated numerical model of boxes in compression tests is also discussed. The effect of the crushing of the material in the vicinity of the crease lines in the packaging arising during the analog and digital finishing processes is taken into account. The obtained enhanced computer simulation results closely reflect the experimental observations, which prove that the correct numerical analysis of corrugated cardboard packaging should be performed with the model taking into account the crushing.

Dynamic Stability Assessment of High-Speed Railway Bridges Using Numerical Model Updating

Numerical model updating using the data measured from the actual structure is required in order to minimize the error between the initial numerical model and the actual structure. Field load tests, which are conducted in order to assess the condition and safety of high-speed railway bridges, are generally expensive and restricted by railway control and weather conditions. Therefore, a method for evaluating the performance of high-speed railway bridges using updated numerical models without conducting field load tests is required. In this study, numerical model updating was performed by using the data measured from the ambient vibration test in order to assess the dynamic stability of high-speed railway bridges. In the ambient vibration test, the measurement point roaming method was applied in order to accurately measure high-speed railway bridges using a limited number of sensors. For numerical model updating, the univariate search method was used, and several measured parameters were updated and converted into the properties of the target bridges in the numerical models. The vertical and torsional modes of the updated numerical models differed by less than 5% from those estimated using the data measured from the target bridges. The responses of the updated numerical models were found to be similar to those measured from the high-speed railway bridges in operation. It was also shown that the updated numerical models could be used to assess the dynamic stability of the bridges.

Vibration performance assessment of deteriorating footbridges: A study of Tunja’s public footbridges

This paper presents the results of the assessment of the dynamic characteristics and vibration performance of eight deteriorating footbridges. The bridges examined, part of the public infrastructure of the city of Tunja (Colombia), present an evident state of deterioration, showing excessive vibration under service loadings. A consistent evaluation methodology based on vibration tests and numerical analyses was implemented. After completing a deterioration assessment, an experimental modal characterization was carried out, the results of which were used to update numerical structural models. Uniform vibration tests for different pedestrian loading scenarios were conducted. Then, pedestrian crossing simulations for a typical range of walking and running frequencies were performed using a step-by-step load model with a new proposal of normalised single-footstep force functions. Results showed elevated vibrations in most of the footbridges for temporary and exceptional loading conditions, which are unsafe for some of the structures. Discomfort and deterioration were compared using a vibration discomfort index (VDI) and a deterioration index (DI). High vibration discomfort levels were found to be consistent with the degree of deterioration of the structures evaluated.

Operational Modal Analysis and Non-Linear Dynamic Simulations of a Prototype Low-Rise Masonry Building

This paper focuses on the dynamic behaviour of a low-rise masonry building representing the Italian residential heritage through experimental and numerical analyses. The authors discuss an application of combined Operational Modal Analysis and Finite Element Model updating for indirect estimation of the structural parameters. Two ambient vibration tests were carried out to estimate the structure’s dynamic behaviour in operational conditions. The first experimental setup consisted of accelerometers gathered in a row along the first floor to characterize the local dynamic of the floor. Conversely, the second setup had the accelerometers placed at the building’s corners to characterize the global dynamics. The outcomes of the first setup were used to estimate the mechanical parameters of the floor, while the ones form the second were used to characterize the mechanical parameters of the masonry piers. Therefore, two finite element models were implemented: (i) a single beam with an equivalent section of the floor to grasp the local behaviour of the investigated horizontal structure; (ii) an equivalent frame model of the entire building to characterise the global dynamic behaviour. The model updating process was developed in two phases to seize local and global dynamic responses. The updated numerical model formed the basis for a sensitivity analysis using the modelling parameters. The authors chose to delve into the influence of the floor on the dynamic behaviour of low-rise masonry buildings. With this aim, non-linear dynamic analyses were carried out under different mechanical characteristics of floors, expressing the scatter for ordinary masonry buildings. The displacements’ trends along the height of the building evidenced the notable role of the floor’s stiffness in the non-linear dynamic behaviour of the building. Lastly, the authors derived the fragility curves predicting the seismic performance in failure probability under a highly severe damage state.

Deep learning-based functional assessment of piezoelectric-based smart interface under various degradations

The piezoelectric-based smart interface technique has shown promising prospects for electro-mechanical impedance (EMI)-based damage detection with various successful applications. During the process of EMI monitoring and damage identification, the operational functionality of the smart interface device is a major concern. In this study, common functional degradations that occurred in the smart interface are diagnosed using a deep learning-based method. Firstly, the effect of functional degradations on the EMI responses is analytically discussed. Secondly, a critical structural joint is selected as the test structure from which EM measurement using the smart interface is conducted. Thirdly, a numerical model corresponding to the experimental model is established and updated to reproduce the measured EMI responses. By using the updated numerical model, the EMI responses of the smart interface under the common functional degradations, such as the shear lag effect, the adhesive debonding, the sensor breakage, and the interface detaching, are simulated; then, the functional degradation-induced EMI changes are characterized. Finally, a convolutional neural network (CNN)-based functional assessment method is newly proposed for the smart interface. The CNN can automatically extract and directly learn optimal features from the raw EMI signals without preprocessing. The CNN is trained and tested using the datasets obtained from the updated numerical model. The obtained results show that the proposed method was successful to classify four types of common defects in the smart interface, even under the effect of noises.

Updated Numerical Model of Mataloko Geothermal Field

Data collection and further geoscience studies have been carried out in the Mataloko area at the end of 2019. In general, the results of the study showed significant differences compared to previous studies. Therefore, it is necessary to update the Mataloko geothermal field’s numerical model following the latest studies’ data and analysis. In this research, numerical modeling will be performed using a TOUGH2 V.2 simulator and graphical interface software. The model will be built and validated at the natural state phase. It is expected that the model can complement existing geoscience studies and can be used by developers in planning field development.

Progressive numerical model validation of a bowstring-arch railway bridge based on a structural health monitoring system

This paper presents a progressive numerical model validation of a bowstring-arch railway bridge based on the analysis of experimental data from different structural response measurements, namely, static deformations under environmental actions, modal vibrations, and transient dynamic responses under traffic loads. This work also addresses an integrated approach that uses structural health monitoring (SHM) measurements in combination with FE modelling to understand the structural behaviour of a long-span complex bridge. A progressively phased in situ SHM system has provided a diverse set of data streams ranging from static and dynamic responses to the measurement of environmental and operational traffic loads. The first phase consists of defining a detailed baseline finite-element (FE) model of the bridge, envisaging the initial condition of the structure immediately after construction, and its validation using modal parameters (natural frequencies and mode shapes) derived from an ambient vibration test. Since overall in-service deflections in general do not exercise the non-linear regime of the bridge response, the second phase focuses on the analysis of static response data and temperature measurements to validate the non-linear behaviour of the structural system, particularly at the bearing devices, under slow actions. The third and final phase addresses the dynamic analysis under traffic actions, which provides greater sensitivity in the detection of non-linear behaviour due to the effects of high-amplitude actions induced by regular train loading profiles. To guarantee the accuracy of the baseline numerical model, particularly under temperature and traffic actions, it was necessary to use contact restrictions in some specific bearing devices. This improvement is in line with the structural changes detected in some bearing devices through visual inspections. As a result, an updated numerical model capable of reproducing the modal, static, and dynamic structural responses was achieved, showing a very good agreement between experimental and numerical data. In future applications, this updated numerical model will be useful for assessing the condition of the bridge under traffic loads, namely to identify damages and support the adoption of life cycle maintenance strategies based on the integration of SHM systems with (stochastic) load and failure models.

Uncertainty analysis of an offshore jacket-type platform using a developed numerical model updating technique

To investigate the dynamic behavior of a complex system, an accurate updated finite element (FE) model is essentially required. Numerical model updating, which is performed based on valid experimental data, is imprecise without taking the related uncertainties into account. In this study, both structural and parametric uncertainties are considered within model updating of an offshore jacket platform through time history analysis for the first time. The experimental test is implemented employing a shake table and a scaled hydro-elastic model of the case study. For updating the FE model, a three-step updating procedure is implemented through eight distinct scenarios. In the first step, three unknown structural parameters are calibrated over ten distinct groups of elements in the FE model by using particle swarm optimization algorithm (PSO). In the second step, the damping matrix coefficients are also updated through the optimization process. In the third step, the model form error is considered utilizing four mathematical functions to decrease the parametric uncertainty and improve the FE model accuracy. Based on the results, by employing the proposed methodology, approximately 98 percent fitness is observed between the experimental and updated numerical model. According to the results, not only reducing both structural and parametric uncertainties is essential, but also calibrating the damping matrix for updating a numerical model and improving the FE model accuracy is of great importance. The developed methodology, which is applied to a sophisticated structural system, is strongly recommended for updating the systems that existence of an accurate updated numerical model is vital.

Anisotropy Effect of Masonry on the Behaviour and Bearing Capacity of Masonry Walls

Firstly, an updated numerical model for the numerical analysis of planar unreinforced and confined masonry walls is presented. The model can simulate the main nonlinear material effects of masonry and reinforced concrete. A simplified anisotropic constitutive model for masonry is developed and presented. The criteria for the limit bearing capacity and collapse of masonry are separately defined for normal stresses only and for normal and shear stresses. The presented numerical model is verified and used to analyse the anisotropy effect of masonry on the behaviour of unreinforced and confined two‐story anisotropic masonry walls with different coefficients of anisotropy, wall lengths, and quality of masonry under horizontal static forces. The influence of the anisotropy coefficient of the masonry on the response of the walls is discussed in detail, and the main conclusions are given.