Updated Numerical Model Research Articles

Structural modal identification and MCMC-based model updating by a Bayesian approach

Finite element analysis is one of the important methods to study the structural performance. Due to the simplification, discretization and error of structural parameters, numerical model errors always exist. Besides, structural characteristics may also change because of material aging, structural damage, etc., making the initial finite element model cannot simulate the operational response of the structure accurately. Based on Bayesian methods, the initial model can be updated to obtain a more accurate numerical model. This paper presents the work on the field test, modal identification and model updating of a Chinese reinforced concrete pagoda. Based on the ambient vibration test, the acceleration response of the structure under operational environment was collected. The first six translational modes of the structure were identified by the enhanced frequency domain decomposition method. The initial finite element model of the pagoda was established, and the elastic modulus of columns, beams and slabs were selected as model parameters to be updated. Assuming the error between the measured mode and the calculated one follows a Gaussian distribution, the posterior probability density function (PDF) of the parameter to be updated is obtained and the uncertainty is quantitatively evaluated based on the Bayesian statistical theory and the Metropolis-Hastings algorithm, and then the optimal values of model parameters can be obtained. The results show that the difference between the calculated frequency of the finite element model and the measured one is reduced, and the modal correlation of the mode shape is improved. The updated numerical model can be used to evaluate the safety of the structure as a benchmark model for structural health monitoring (SHM).

Remaining capacity estimation for buildings after an explosion using the adaptive alternate path analysis

After an explosion, determining the remaining capacity of a structure to resist a progressive collapse can provide valuable information for emergency operations and decision makers. Condition assessments after a blast are commonly performed with a visual inspection. However, visual inspections can be time-consuming and involve putting additional personnel into harm’s way. Analytical blast analyses can estimate a structures post-blast condition, but to achieve a high level of accuracy these analyses can be time-consuming and require information regarding the blast event which may not be available at the time. This presents a need for a threat independent post-blast analysis method, which can assess for the post-blast structural condition without requiring personnel to enter the structure. The alternate path method has been used to design buildings to resist a progressive collapse; however, it does not incorporate damage outside of element failure making it unsuitable for post-blast condition assessments. Model updating using modal properties from vibration measurements has been used in structural health monitoring to estimate damage on structures, but it has not been applied to post-blast structures. In this article, a method to estimate the remaining elemental structural capacity of a post-blast structure, called the adaptive alternate path analysis, is presented. This method involves using the alternate path method to assess an updated numerical model, which incorporates the buildings’ structural damage. To demonstrate the impact of incorporating additional damage beyond elemental failure on a structure’s capacity, a simulated study is presented using simulated stiffness reductions. A blast simulation is then used to show the capacity of the updated numerical model to represent the post-blast structure and the improvements gained over using the original model. The presented methodology can be used to assess a structures potential for progressive collapse after a blast, leading to safer emergency operations.

An adaptive ensemble Kalman filter for assimilation of multi-sensor, multi-modal water temperature observations into hydrodynamic model of shallow rivers

There is lack of knowledge in assimilation of multi-sensor, multi-modal water temperature observations into hydrodynamic models of shallow rivers, specifically, (a) how does accuracy of shallow river model improve after assimilation of in-situ and remotely sensed temperature observations, and (b) how can data from disparate sensors and sources be assimilated into the prediction model without significant increase in computational burden. Multi-sensor, multi-modal observations used in this study are obtained from in-situ monitoring devices in the river with limited spatial coverage but dense temporal resolution, and from Landsat-7 satellite that has better spatial coverage but limited temporal coverage. Use of remotely-sensed observations from satellites poses the challenge that the physical region represented by satellite data does not directly correspond with the physical domain of the river simulated in hydrodynamic models. Satellites detects the skin water temperature, whereas numerical models estimate the bulk temperature in the surface layer that may be multiple meters in thickness. Furthermore, for rivers narrower than the resolution of satellite data, the temperature of each cell represents the weighted average temperature of land and water. These factors introduce biases into the updated numerical model, thereby impeding appropriate management of temperature, water quality, and aquatic ecology. We implemented an efficient ensemble Kalman filter method using Latin-hypercube sampling to assimilate multi-sensor water temperature observations into the hydrodynamic model of the Lower Klamath River located in northern California. Assimilation of remote sensing data from Landsat-7 improved the model prediction for the entire river. The average spatial error was reduced from 2.59 °C to 0.66 °C (i.e., 75% improvement). In-situ data assimilation reduced the error at the observation location, however, error in the water temperature predicted by the updated model reverted in less than two days to the same level as that of an un-updated model. On the other hand, it is not computationally efficient to assimilate all of the available data into the model as they become available. In order to overcome these challenges, in-situ data were adaptively assimilated into the model whenever the error exceeded a maximum allowable error. Adaptive assimilation of in-situ data for the Lower Klamath river application occurred one to three times per day, and reduced the average daily error up to 58% compared to assimilation of in-situ data only once each day.

Full-field finite element model updating using Zernike moment descriptors for structures exhibiting localized mode shapes

The Modal Assurance Criterion (MAC) is a simple and powerful indicator to correlate experimental and analytical mode shapes. However, the MAC is not optimal for use in model updating of structures with localized mode shape features, since it is a global single index. Consequently, an alternative to the MAC is needed to optimally update numerical models of such structures for improved representation of structural dynamic behaviour. Developed from techniques in image processing and pattern recognition, Zernike moment descriptors (ZMDs) have been proposed as alternative correlation indicator in this study. They are highly sensitive to image features and so offer good promise to correlate mode shapes of relevant structures. This paper presents a framework for the use of ZMDs in model updating of structures exhibiting localized mode shapes. A particular example of such structures increasingly being used in civil engineering are glass fibre-reinforced polymer (GFRP) structures, such as buildings and footbridges. The proposed approach is applied to a full-scale pultruded GFRP footbridge with localized features to produce a more faithful numerical model. The effectiveness of both MAC and ZMD are considered. It is found that the use of ZMDs as the target response metrics improves mode shape correlation, giving improved FE representation of the GFRP footbridge. This paper informs on the applicability of ZMDs in FE model updating of structures with localized mode shapes and has recommendations for their use in practice.

Fatigue Assessment of a Slender Footbridge Based on an Updated Finite Element Model

Finite element model updating is a well-known technique to better characterize the real behaviour of civil engineering structures. The updated numerical model can be used to perform a more accurate structural assessment. Herein, its effectiveness is validated through the fatigue assessment of a lively footbridge considering two different numerical models: (i) a preliminary finite element (FE) model and (ii) an updated version of the preliminary model based on the modal parameters of the footbridge identified experimentally. For this purpose, the Malecon footbridge (Murcia, Spain) has been considered. This footbridge, a cable-stayed structure, is prone to vibrate in vertical direction under continuous walking pedestrian flows so fatigue damage might be expected on its supporting cables. A detailed FE model of the footbridge has been performed and subsequently updated based on the experimental modal parameters of the structure. The behaviour of the pedestrian flows was characterized by field observations. Finally, a comparison is performed between the fatigue damage of some cables of the footbridge considering the two mentioned FE models. The safe life method was used to assess such damage. As result, a maximum relative difference around 52 % was obtained between the two numerical models.

Wavelet-based identification of rotor blades in passage-through-resonance tests

Abstract Turbine blades are critical components in turbo engines and their design process usually includes experimental tests in order to validate and/or update numerical models. These tests are generally carried out on full-scale rotors having some blades instrumented with strain gauges and usually involve a run-up or a run-down phase. The quantification of damping in these conditions is rather challenging for several reasons. In this work, we show through numerical simulations that the usual identification procedures lead to a systematic overestimation of damping due both to the finite sweep velocity, as well as to the variation of the blade natural frequencies with the rotation speed. To overcome these problems, an identification procedure based on the continuous wavelet transform is proposed and validated through numerical simulation.

Seismic safety assessment of historical structures using updated numerical models: The case of Mallorca cathedral in Spain

The paper presents an integrated approach aimed at assessing the seismic safety of Mallorca cathedral. This cathedral is an extraordinary historical construction dating back to the middle-ages. The experimental modal parameters of the cathedral were identified using Ambient Vibration Testing (AVT). The cathedral numerical model was updated using the identified modal parameters. This updated model was then used to study the seismic response of the cathedral using non-linear static (pushover) analysis. A sensitively analysis was carried out to reveal the dependency of the seismic capacity on the input materials properties. To assess the seismic performance and the safety of the cathedral, the N2 method was employed. It was found that the cathedral is safe when subjected to the earthquakes expected in Mallorca Island.

From skin to bulk: An adjustment technique for assimilation of satellite-derived temperature observations in numerical models of small inland water bodies

Data Assimilation (DA) has been proposed for multiple water resources studies that require rapid employment of incoming observations to update and improve accuracy of operational prediction models. The usefulness of DA approaches in assimilating water temperature observations from different types of monitoring technologies (e.g., remote sensing and in-situ sensors) into numerical models of in-land water bodies (e.g., lakes and reservoirs) has, however, received limited attention. In contrast to in-situ temperature sensors, remote sensing technologies (e.g., satellites) provide the benefit of collecting measurements with better X-Y spatial coverage. However, assimilating water temperature measurements from satellites can introduce biases in the updated numerical model of water bodies because the physical region represented by these measurements do not directly correspond with the numerical model's representation of the water column. This study proposes a novel approach to address this representation challenge by coupling a skin temperature adjustment technique based on available air and in-situ water temperature observations, with an ensemble Kalman filter based data assimilation technique. Additionally, the proposed approach used in this study for four-dimensional analysis of a reservoir provides reasonably accurate surface layer and water column temperature forecasts, in spite of the use of a fairly small ensemble. Application of the methodology on a test site - Eagle Creek Reservoir - in Central Indiana demonstrated that assimilation of remotely sensed skin temperature data using the proposed approach improved the overall root mean square difference between modeled surface layer temperatures and the adjusted remotely sensed skin temperature observations from 5.6°C to 0.51°C (i.e., 91% improvement). In addition, the overall error in the water column temperature predictions when compared with in-situ observations also decreased from 1.95°C (before assimilation) to 1.42°C (after assimilation), thereby, giving a 27% improvement in errors. In contrast, doing data assimilation without the proposed temperature adjustment would have increased this error to 1.98°C (i.e., 1.5% deterioration).

An innovative framework for probabilistic-based structural assessment with an application to existing reinforced concrete structures

A novel framework for probabilistic-based structural assessment of existing structures, which combines model identification and reliability assessment procedures, considering in an objective way different sources of uncertainty, is presented in this paper. A short description of structural assessment applications, provided in literature, is initially given. Then, the developed model identification procedure, supported in a robust optimization algorithm, is presented. Special attention is given to both experimental and numerical errors, to be considered in this algorithm convergence criterion. An updated numerical model is obtained from this process. The reliability assessment procedure, which considers a probabilistic model for the structure in analysis, is then introduced, incorporating the results of the model identification procedure. The developed model is then updated, as new data is acquired, through a Bayesian inference algorithm, explicitly addressing statistical uncertainty. Finally, the developed framework is validated with a set of reinforced concrete beams, which were loaded up to failure in laboratory.

Numerical model upgrading of a historical masonry palace monitored with a wireless sensor network

Seismic protection and vulnerability reduction are very relevant issues in European regions, such as Italy, characterised by the presence of a large stock of heritage structures. This increased the interest in structural health monitoring as a powerful tool to quantify and reduce uncertainties regarding the structural performance of buildings. Monitoring can be successfully implemented in some cases as an alternative to interventions or to control the medium- and long-term effectiveness of already applied strengthening solutions. Recently, the use of wireless sensor networks (WSN) as a new kind of architecture for structural monitoring systems has been explored. A WSN is usually a flexible solution with minor costs associated, especially if the network is composed by cheap devices. In this framework, this work details the main results obtained in the context of the 'Palazzo Comunale di Castelfidardo' monitoring project with WSN, with the aim to get an accurate numerical model (NM) that simulates the dynamic behaviour of the whole structure. An iterative approach to perform the manual tuning of the NM is proposed, using as calibration parameters not only mechanical entities, but also boundary conditions. Finally, a comparison between the structural responses, obtained with experimental analysis, and the updated NM is provided.

Numerical and experimental comparison between two different blade configurations of a wind generator

This paper presents a comparison between the structural behaviour of a wind generator with straight blades and a composite prototype of a wind generator with helical blades. Numerical structural analyses are performed by means of FEM models by using ANSYS® Mechanical™ software package. Furthermore, laboratory dynamic experimental tests are carried out on real scale specimens of the two wind generator configurations in order to find their modal properties in terms of natural frequencies and modal shapes. The results of the experimental campaign are then used to update the numerical models by minimizing an objective function. Total stresses and deformations of the two wind generator configurations, coming from the updated numerical models, are evaluated and compared to quantitatively point out the improvement of the structural behaviour obtained by the use of composite materials.

Conjugate heat transfer analysis of an energy conversion device with an updated numerical model obtained through inverse identification

Energy conversion devices undergo thermal loading during their operation as a result of inefficiencies in the energy conversion process. This will eventually lead to degradation and possible failure of the device if the heat generated is not properly managed. The ability to accurately predict the thermal behavior of such a device during the initial developmental stage is an important requirement. However, accurate predictions of critical temperature is challenging due to the variation of heat transfer parameters from one device to another. The ability to determine the model parameters is key to accurately representing the heat transfer in such a device. This paper presents the use of an inverse identification technique to estimate the model parameters of an energy conversion device designed for vehicular applications. To simulate the imperfect contact and the presence of insulating materials in the permanent magnet electric machine, thin material are introduced at the component interface of the numerical model. The proposed inverse identification method is used to estimate the equivalent thermal conductance of the thin material. In addition, the electromagnetic losses generated in the permanent magnet is also derived indirectly from the temperature measurement using the same method. With the thermal properties and input parameters of the numerical model obtained from the inverse identification method, the critical temperature of the device can be predicted more accurately. The deviation between the maximum measured and predicted winding temperature is less than 2.4%.

Refined optimal passive control of buffeting-induced wind loading of a suspension bridge

Modern design of long suspension bridges must satisfy at the same time spanning very long distances and limiting their response against several external loads, even if of high intensity. Structural Control, with the solutions it provides, can offer a reliable contribution to limit internal forces and deformations in structural elements when extreme events occur. This positive aspect is very interesting when the dimensions of the structure are large. Herein, an updated numerical model of an existing suspension bridge is developed in a commercial finite element work frame, starting from original data. This model is used to reevaluate an optimization procedure for a passive control strategy, already proven effective with a simplified model of the buffeting wind forces. Such optimization procedure, previously implemented with a quasi-steady model of the buffeting excitation, is here reevaluated adopting a more refined version of the wind-structure interaction forces in which wind actions are applied on the towers and the cables considering drag forces only. For the deck a more refined formulation, based on the use of indicial functions, is adopted to reflect coupling with the bridge orientation and motion. It is shown that there is no variation of the previously identified optimal passive configuration.

Analysis and Back-Analysis for Temperature Field of Concrete Arch Dam During Construction Period Based on Temperature Data Measured by DTS

Based on the observed temperature information of arch dam, the mathematical and mechanical methods are combined usually with dam engineering theory to capture in real time and evaluate in time the developing status and space-time distribution of arch dam temperature, and implement the back analysis for temperature control measures. It is an important step for dam construction and safe operation. Some methods, namely transient temperature-field simulation, thermodynamic parameters back-calculation, and model correction, are used synthetically to solve the above problem. A method is proposed to back calculate the thermodynamic parameters of arch dam by use of the temperature data obtained by the distributed optical fiber temperature sensor (DTS). A problem is studied to couple the simulated temperature field by finite element method (FEM) and the observed temperature field by the DTS. A method is presented to update dynamically the FEM model on the basis of the observed temperature field. An actual engineering is analyzed by the proposed method. It is shown that the DTS system can implement the real-time observation of concrete arch dam temperature field. According to the observed temperature field by the DTS and the updated numerical simulation model of the temperature field, scientific guidance can be given during the pouring process of the arch dam, and reliable data can be provided to analyze and evaluated arch dam safety.

Finite element model updating of a bowstring-arch railway bridge based on experimental modal parameters

This article describes the calibration of the numerical model of a bowstring-arch railway bridge based on modal parameters. An ambient vibration test allowed the identification of the natural frequencies, mode shapes and damping coefficients of several global and local modes of vibration of the bridge by the application of an output-only technique based on the enhanced frequency domain decomposition method. The calibration was performed using a genetic algorithm that allowed obtaining the optimal values of fifteen parameters of the numerical model. For the mode pairing, a new technique based on the calculation of the modal strain energy was used. The stability of a significant number of parameters, considering different initial populations, proved the robustness of the adopted algorithm in the scope of the optimization of the numerical model. The updated numerical model was validated based on an experimental test for the characterization of the modulus of deformability of the concrete and a dynamic test under railway traffic. The results showed an excellent agreement between numerical and experimental results.

An updated numerical model of the Larderello–Travale geothermal system, Italy

Larderello–Travale is one of the few geothermal systems in the world that is characterized by a reservoir pressure much lower than hydrostatic. This is a consequence of its natural evolution from an initial liquid-dominated to the current steam-dominated system. Beneath a nearly impermeable cover, the geothermal reservoir consists of carbonate-anhydrite formations and, at greater depth, by metamorphic rocks. The shallow reservoir has temperatures in the range of 220–250 °C, and pressures of about 20 bar at a depth of 1000 m, while the deep metamorphic reservoir has temperatures of 300–350 °C, and pressures of about 70 bar at a depth of 3000 m. The 3D numerical code “TOUGH2” has been used to conduct a regional modeling study to investigate the production mechanism of superheated steam, the interactions between the geothermal field and the surrounding deep aquifers, and the field sustainability. All the available geoscientific data collected in about one century of exploration and exploitation have been used to provide the necessary input parameters for the model, which covers an area (4900 km 2) about 10 times wider than the Larderello–Travale geothermal field (400 km 2). The numerical model explains the origin of the steam extracted in about one century of exploitation and shows that, at the current level, the production is sustainable at least for the next 100 years.

A Hybrid Accelerated Random Search-Centrifugal Force Algorithm for Dynamic Finite Element Model Updating

An effective algorithm, which combined an adaptive centrifugal force algorithm with accelerated random search method, is proposed to update numerical models for dynamics problems. The objective is to minimize the difference between measured and simulated vibration data. The related problem is formulated as an optimization problem by considering multi-objective function defined in modal domain. A simulated beam structure is examined to test the applicability of the new approach for FE model updating applying multi-objective criteria. A real beam-like structure model is updated, making use of experimental modal data. The application of the centrifugal force algorithm enables us to obtain results well correlated with experiments in reduced time.

Dynamic Field Test, System Identification, and Modal Validation of an RC Minaret: Preprocessing and Postprocessing the Wind-Induced Ambient Vibration Data

The investigation of dynamic response for civil engineering structures largely depends on a detailed understanding of their dynamic characteristics, such as the natural frequencies, mode shapes, and modal damping ratios. Dynamic characteristics of structures may be obtained numerically and experimentally. The finite-element method is widely used to model structural systems numerically. However, there are some uncertainties in numerical models. Material properties and boundary conditions may not be modeled correctly. There may be some microcracks in the structures, and these cracks may directly affect the modeling parameters. Modal testing gives correct uncertain modeling parameters that lead to better predictions of the dynamic behavior of a target structure. Therefore, dynamic behavior of special structures, such as minarets, should be determined with ambient vibration tests. The vibration test results may be used to update numerical models and to detect microcracks distributed along the structure. The o...

FE Model Updating for Damage Detection – Application to a Welded Structure

Finite Element (FE) model updating is initially developed to update numerical models of structures to match their experimentally measured modal properties (i.e., natural frequencies and modes). In FE model updating, uncertain physical parameters of a structure are modified so that the discrepancies between the numerically estimated and experimentally measured modal properties are minimized. The process of updating is employed not only in parameter identification; it can also be developed for structural damage identification. In this work, a welded structure that is intended to represent a common configuration used in automotive body construction is investigated. It is known that presence of any damage in the welds of such a structure could affect its dynamic behavior. So, in theory modal test data can allow damage to be assessed accurately. As a typical automotive body contains thousands of welds, the effects of damage in the welds could be influential. The FE model updating process using experimental data is presented. It is carried out using NASTRAN optimization code. The procedure aims to adjust the uncertain properties of the FE model (from the weld joints) by minimizing the differences between the measured modal properties and the corresponding numerical predictions. The initial parameter values used in the numerical model are the nominal values. The procedure brings the numerical results of the structure as close as possible to the experimental ones, according to an objective function, therefore altering some of the FE model parameters of the structure. It may be concluded that when the identified values of certain parameters deviates from the nominal values to certain extent, there is a fault or damage at that particular joint.

Simulation of Axial Combustion Instability Development and Suppression in Solid Rocket Motors

In the design of solid-propellant rocket motors, the ability to understand and predict the expected behaviour of a given motor under unsteady conditions is important. Research towards predicting, quantifying, and ultimately suppressing undesirable strong transient axial combustion instability symptoms necessitates a comprehensive numerical model for internal ballistic simulation under dynamic flow and combustion conditions. An updated numerical model incorporating recent developments in predicting negative and positive erosive burning, and transient, frequency-dependent combustion response, in conjunction with pressure-dependent and acceleration-dependent burning, is applied to the investigation of instability-related behaviour in a small cylindrical-grain motor. Pertinent key factors, like the initial pressure disturbance magnitude and the propellant's net surface heat release, are evaluated with respect to their influence on the production of instability symptoms. Two traditional suppression techniques, axial transitions in grain geometry and inert particle loading, are in turn evaluated with respect to suppressing these axial instability symptoms.