Calibration Of Numerical Model Research Articles

In-plane behaviour of masonry infill walls with openings strengthened using textile reinforced mortar

A numerical study was carried out to simulate the in-plane behaviour of a 1:2.5 scaled one-storey one-bay masonry-infilled reinforced concrete (RC) frame retrofitted with textile-reinforced mortar (TRM). The study used ABAQUS finite element analysis (FEA) software and a three-dimensional (3-D) finite element method. Using a ductile design and details, the TRM-reinforced structure encountered in-plane displacement-control cyclic loads during the test. This study assesses how accurately a representative numerical model can replicate the results of an experimental test. Parametric research was conducted following the numerical model's calibration. To develop a suitable numerical model, suitable constitutive models based on the concrete damage plasticity (CDP) approach were used to characterize the nonlinear response of TRM, masonry infill, and concrete. The experimental findings, which aggrandize the response simulation, served as the basis for calibrating the models. Using a finite element framework and the simplified micro model technique, the masonry structure is simulated at the infill component level. The numerical model demonstrated accurately the ability to simulate the in-plane behaviour of the modified RC frame with infill walls, including its initial stiffness, deterioration, deformation-resisting ability, and failure patterns. Furthermore, a parametric study was conducted to determine the significance of the full-bond scenario between the RC frame infilled with masonry and the TRM considering: (1) the location of the strengthening material on the specimen and (2) the number of layers of the strengthening material. All retrofitted wall specimens showed a considerable improvement in in-plane performance; some features of the wall's behaviour were found to be strongly influenced by the parameters under examination. It can be observed that the specimen with two layers of TRM on both sides of the infill wall exhibit the maximum lateral load carrying capacity and maximum deflection resisting characteristics while the other retrofitted specimens controlled the deflection to some extent and significantly enhancing the load carrying capacities of the masonry system.

Artificial Intelligence-Centric Low-Enthalpy Geothermal Field Development Planning

Low-enthalpy geothermal energy can make a major contribution towards reducing CO2 emissions. However, the development of geothermal reservoirs is costly and time intensive. In particular, high capital expenditures, data acquisition costs, and long periods of time from identifying a geothermal resource to geothermal heat extraction make geothermal field developments challenging. Conventional geothermal field development planning follows a linear approach starting with numerical model calibrations of the existing subsurface data, simulations of forecasts for geothermal heat production, and cost estimations. Next, data acquisition actions are evaluated and performed, and then the models are changed by integrating the new data before being finally used for forecasting and economics. There are several challenges when using this approach and the duration of model rebuilding with the availability of new data is time consuming. Furthermore, the approach does not address sequential decision making under uncertainty as it focuses on individual data acquisition actions. An artificial intelligence (AI)-centric approach to field development planning substantially improves cycle times and the expected rewards from geothermal projects. The reason for this is that various methods such as machine learning in data conditioning and distance-based generalized sensitivity analysis assess the uncertainty and quantify its potential impact on the final value. The use of AI for sequential decision making under uncertainty results in an optimized data acquisition strategy, a recommendation of a specific development scenario, or advice against further investment. This approach is illustrated by applying AI-centric geothermal field development planning to an Austrian low-enthalpy geothermal case. The results show an increase in the expected value of over 27% and a reduction in data acquisition costs by more than 35% when compared with conventional field development planning strategies. Furthermore, the results are used in systematic trade-off assessments of various key performance indicators.

Non-Destructive Testing and Synergistic Investigation of a Historic Tower

This paper focuses on the reliability of a synergistic procedure, involving dynamic tests complemented by documentary and architectural research, for the structural assessment of heritage towers. The reliability of the presented method is exemplified in a relevant case study, the Zuccaro’s Tower in Mantua. As is known, historic buildings require addressed procedures in order to consider past building transformation and eventual damage/decay, which can affect the masonry properties and, more generally, the structural behavior. The proposed investigation procedure is based on multidisciplinary information (i.e., merging data) from historical and document studies, direct inspections, surveys of geometry and front surfaces, and dynamic tests in operational conditions. The processed information allowed the development and the calibration of a simplified numerical model, useful in driving the seismic/structural assessment of the tower. The results of past investigations, found during the archival research, contributed to the structural evaluation. This paper describes the main research outcomes and the model tuning with a special focus on the key role of the synergy between the applied methods for the assessment of a historic building.

Flexible Polyurethane Adhesives: Predictive Numerical Model Calibration through Experimental Testing at Elevated Temperature

The thermo-mechanical behavior of polyurethane adhesive joints in wood structures is a crucial aspect that needs to be understood to ensure the durability and safety of timber structures, especially in seismic regions. As mass timber, particularly cross-laminated timber, continues to gain popularity as a building material, it is important to pay special attention to the behavior of connections between the timber elements. The use of flexible polyurethane adhesives presents a promising alternative to conventional mechanical connections in seismic-resistant timber structures. This research highlights the potential of polyurethane-based joints at elevated service temperature, offers a promising alternative to traditional wood joints, and suggests viability for post-fire restoration of wood structures. The response at the interface between wood and polyurethane under flexural stresses is also evaluated, underscoring the broader application possibilities of flexible adhesives in wood construction for mechanical and physical improvements.

Large-scale baseline model exploration from structural monitoring based on a novel information entropy-probability learning function

In this paper, an active learning framework for structural baseline model exploration is proposed based on the Kriging method. The framework is built to solve the problem that when the traditional Kriging approach needs to calibrate more structural parameters, the performance of Kriging predictors hinges very much upon the number of samples obtained from the finite element analysis. A novel information entropy-probability learning function is derived based on Bayesian inference and information entropy. To give a full picture, the uncertainties of different responses should also be quantified during the updating process. Then the effects of uncertainties are considered in both the learning function and objective function constructed from the posterior probabilities. The proposed algorithm is first verified experimentally by a two-span continuous beam considering different types of responses. The framework is then further improved for updating the baseline model of a cable-stayed bridge using field data. The active learning approach, as compared to the ordinary Kriging method, can achieve good performance without undue computational cost and the need for imposing weights on different responses. The proposed baseline model exploration method can be extensively applied to bridge engineering because it facilitates the calibration of numerical models using field measurements and response simulation of extreme loading with significant improvement in computational efficiency and performance of Kriging predictors.

Coupling numerical models of deltaic wetlands with AirSWOT, UAVSAR, and AVIRIS-NG remote sensing data

Abstract. Coastal marsh survival relies on the ability to increase elevation and offset sea level rise. It is therefore important to realistically model sediment fluxes between marshes, tidal channels, and bays as sediment availability controls accretion. Traditionally, numerical models have been calibrated and validated using in situ measurements at a few locations within the domain of interest. These datasets typically provide temporal information but lack spatial variability. This paper explores the potential of coupling numerical models with high-resolution remote sensing imagery. Products from three sensors from the NASA Delta-X airborne mission are used. Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) provides vertical water level change on the marshland and was used to adjust the bathymetry and calibrate water fluxes over the marsh. AirSWOT yields water surface elevation within bays, lakes, and channels, and was used to calibrate the Chezy bottom friction coefficient. Finally, imagery from AVIRIS-NG provides maps of total suspended solids (TSS) concentration that were used to calibrate sediment parameters of settling velocity and critical shear stress for erosion. Three numerical models were developed at different locations along coastal Louisiana using Delft3D. The coupling enabled a spatial evaluation of model performance that was not possible using simple point measurements. Overall, the study shows that calibration of numerical models and their general performance will greatly benefit from remote sensing.

UNI-axial dynamic tests on a stone masonry subassembly before and after interventions

The present study deals with the seismic response of three-leaf stone masonry subassemblies before and after the application of intervention techniques. In detail, shaking table tests are performed on a scaled substructure in the Laboratory for Earthquake Engineering, at the National Technical University of Athens (NTUA). The substructure consists of two parallel walls. One wall is of rectangular section, whereas the other is provided with a portion of transverse wall at its mid-length. A flexible timber floor rests on the top of the walls. Sine-sweep and dynamic tests are performed perpendicular to the two walls, before and after interventions. The aim of this work is to experimentally study the response of three leaf masonry walls against in-plane and out-of-plane seismic actions, to investigate the effect of the transverse wall to the out-of-plane behavior of walls (and vice versa) and to assess the effect of a selected set of interventions on the behavior of the substructure. The results of this study confirm the vulnerability of three leaf masonry structures, evidenced by the premature detachment of masonry leaves. They prove the significant role of the transverse wall, in reducing the width of the separation cracks observed in the walls subjected to out-of-plane actions followed by an increase of its in-plane damage, as well as the positive effect (in terms of load and deformation capacity) of grouting the walls and enhancing the diaphragm action of the floor. Additionally, the experimental results of this study can serve as a validation tool for the calibration of numerical models and as input for further analytical research. In this paper, the calibration of a smeared crack model that is based on macro-modeling approach is presented, along with a comparison between experimental and numerical results for the specimen before interventions, based on the performed calibration.

Evaluation of dissimilar TIG welded joints of novel high strength low alloy steel for automotive applications: Experiment and numerical comparative approach

Modern automotive, aerospace, and manufacturing sectors use tungsten inert gas (TIG) welding widely as a critical procedure due to the weld's quality and joint efficiency. In this study, mechanical characterization of TIG-welded joints of high strength low alloy (HSLA) steel with two different grades (S1 and S2) was performed experimentally and mechanical properties were calculated in terms of hardness profile along the weldment and load-displacement curves. True stress-strain curves of base metal, heat-affected zone, and melted zones were used for calibration of the 8-node solid numerical model. The highest hardness value of 386 HV was obtained in the melted zone whereas a softening zone was observed in the heat-affected zone (HAZ) of S2 where the Vicker's microhardness value was 270 HV. During the comparison of simulation results with experimental data, it was found that the overall error was less than 5% which reflects a good accuracy of material models used for numerical modeling. A higher ultimate tensile strength was found in similar S1-S1 steel joints as compared to similar S2-S2 and dissimilar S1-S2 steel joints. Furthermore, the results of simulations revealed that the maximum von Mises stress (1050 MPa) concentrations were found in the HAZ of a similar S1-S1 welded joint, whereas the minimum von Mises stresses (880 MPa) in S2-S2 welded joint, and intermediate von Mises stresses (1010 MPa) on the side of S1 HAZ in S1-S2 dissimilar welded joint. The results of simulations and experimental study of TIG welding joints show good agreement with reasonable accuracy.

3D digital image correlation analysis of medium velocity soft impacts on laminated composite

In aerospace acamedic and industrial world, soft impacts are commonly used to replace bird strike tests for the validation of materials and structures as well as the calibration of numerical models. However in general, the analysis reported show only a few part of the experimental information available. In this paper, three laminate composites made of epoxy resin reinforced by glass or carbon fibres are tested under gelatin impact at several velocities up to complete failure. A detailed analysis based on 3D Digital Image Correlation (3D DIC) and visual inspection of the three laminates is provided for a total of 21 tests with impact velocities in the range 60–112 m/s. DIC extraction provides accurate quantitative displacement fields of the rear face in both time and space. Moreover, specific failure scenarios are identified for each laminate. The results obtained provide a suitable database for the development of numerical models. In addition, all experimental data from DIC extractions are opened to the readers on the Recherche Data Gouv website for comparisons with their own tests or numerical models.

Influence of liquid viscosity on surface wave motion in a vertical cylindrical tank

In order to explore the influence of liquid viscosity on surface wave motion in offshore cylindrical oil storage tank, hundreds of sloshing experiments were conducted by using four white oils with different viscosities. The present study demonstrates that the excitation frequency and excitation amplitude as well as liquid viscosity have significant influence on sloshing behavior in the cylindrical tank subjected to harmonic horizontal excitation. For low-viscosity oil, when the excitation frequency is very close to or equal to the natural frequency of first asymmetric mode, swirling wave motion with or without breaking can be observed. In addition, it is interesting to note that the sloshing behavior at the second-mode resonant condition is more complicated than that at the first-mode resonant condition, owing to the adjacent asymmetric modes are excited by various nonlinear effects. With the increase of oil viscosity, the surface wave motion becomes more and more stable with smaller wave amplitude and simpler wave pattern. To the best of the author's knowledge, this is the first case of systematic study of sloshing behavior of liquid with different viscosity in the vertical cylindrical tank. The experiments also provide accurate data for the calibration of theoretical and numerical models.

The Challenge of Interdisciplinarity at the Intersection of Groundwater Management and Visualization Research.

This design study presents an analysis and abstraction of temporal and spatial data, and workflows in the domain of hydrogeology and the design and development of an interactive visualization prototype. Developed in close collaboration with a group of hydrogeological researchers, the interface supports them in data exploration, selection of data for their numerical model calibration, and communication of findings to their industry partners. We highlight both pitfalls and learnings of the iterative design and validation process and explore the role of rapid prototyping. Some of the main lessons were that the ability to see their own data changed the engagement of skeptical users dramatically and that interactive rapid prototyping tools are thus powerful to unlock the advantage of visual analysis for novice users. Further, we observed that the process itself helped the domain scientists understand the potential and challenges of their data more than the final interface prototype.

Monitoring corrosion-induced concrete cracking adjacent to the steel-concrete interface

Substantial research effort has been devoted on linking corrosion-induced cracking of concrete with the internal corrosion damage level. Still, numerical models of the corrosion and cracking process require internal parameters, that cannot be directly evaluated from experimental data. Therefore, this study provides a novel experimental method for monitoring the effects of steel corrosion adjacent to the steel-concrete interface. This non-destructive method is suited for small-scale laboratory-made specimen, and was designed to provide missing information required for subsequent calibration of numerical models. Hollow steel bars were cast into concrete and subjected to accelerated corrosion using the impressed current technique. The deformations of the hollow steel bars were measured using distributed strain sensing in an optical fibre, attached to the inner surface of the hollow steel bars. After the corrosion period, X-ray Computed Tomography scans were performed to evaluate concrete cracking and corrosion level. The results reveal a non-uniform distribution of strain around the perimeter of the steel, indicating a non-uniform radial stress distribution. The non-uniformity correlated very well with the position of the corrosion-induced cracks; with extension hoop strains in the steel at the location of these cracks and contraction hoop strains in between. Further, the corrosion level varied around the perimeter, with higher values near cracks. The combination of non-destructive monitoring techniques used in this study on small-scale laboratory-made specimens show great potential to reveal new insights on how the corrosion pattern, corrosion-induced cracking of the concrete cover and stress (indirectly measured through the strain in the steel) interact throughout the corrosion process.

Analysis and interpretation of observed dynamic behaviour of a large concrete dam aided by soft computing and machine learning techniques

The nowadays-available dynamic monitoring equipment integrating sensitive low-noise sensors creates an opportunity to implement continuously operating dynamic monitoring systems in dams and validate the suitability of these systems to monitor such massive structures with the goal of detecting damage. The continuous characterisation of the dam modal properties during important variations of the water level and temperature is a unique experimental result, which is particularly interesting for the calibration of numerical models that consider water–structure interaction.Using a quite rare database collected in a large concrete dam, the Baixo Sabor dam in this case study, a methodology based on machine learning techniques and soft computing is proposed for the analysis and interpretation of observed dynamic behaviour of concrete dams based on models HST (hydrostatic, seasonal, time). For this model, two methodologies are applied, Multiple Linear Regression and MultilLayer Perceptron Neural Network, to characterise the water level effect and the thermal effect related to the seasonal variation of temperature during one year period. A spectral analysis based on wavelet transform is also presented to characterise the thermal effect of daily temperature variations.The Baixo Sabor dam is a concrete double-curvature arch dam, 123 meters high, located in the northeast of Portugal, which is being monitored by a dynamic monitoring system that comprises 20 uniaxial accelerometers. The results are compared and discussed. The results of this study show that the methodology proposed is suitable for a better understating of the observed dynamic behaviour and opens new opportunities for dam safety control activities.

Assessment of twin tunnelling induced settlement and load transfer mechanism of a single pile in dry sand

This study conducted both three-dimensional physical model tests and numerical back-analyses to examine the performance of a single pile subjected to twin tunnelling beneath the pile toe in dry sand. Moreover, numerical parametric analyses were carried out to assess the impact of working load level and tunnel volume loss on pile behaviour. The findings revealed that the first tunnelling induced a 1.9% dp (pile diameter) settlement in the pile when the pile toe was 0.5 D (tunnel diameter) above the twin tunnels, which had a 1.0% volume loss. The settlement was accompanied by an upward load transfer mechanism. The second tunnelling had a reduced impact and induced only 76% of the settlement caused by the first tunnelling. The study also showed that tunnelling-induced shearing behaviours weakened beneath the pile toe with a decrease in working load, resulting in reduced pile head settlement. Moreover, the computed pile settlement increased by 178% when the tunnel volume loss increased from 0.5% to 2%. The findings of this study offer valuable data for the validation and calibration of numerical models. In addition, the outcome from this study provides useful insights into the prediction of the pile-soil-tunnel interaction when subjected to twin tunnelling.

A comparison of modal parameter identification tests in laboratory conditions

AbstractModal parameter evaluation is widely used for structural health monitoring, damage detection, and numerical model calibration. This study benchmarks two methods for modal identification under controlled laboratory conditions using operational modal analysis to compare dynamic parameters from ambient vibrations and shaker tests. A 2‐storey 3D spatial steel frame equipped with 3‐axial accelerometers is used as a case study. The identified dynamic parameters are benchmarked against a preliminary finite element model by computing Auto‐MAC and MAC matrices. It can be concluded that the preliminary FEM approach performs better in the prediction of modes shapes than natural frequencies. It was found that analysing the structural response to both ambient and artificially induced excitations provide a more complete understanding of a structure's dynamic characteristics. An additional mode shape was identified from the artificially induced excitation that was not previously captured from the ambient excitation.

A real-time calibration method for the numerical pollen forecast model COSMO-ART

Technologies for monitoring pollen concentrations in real-time made substantial advances in the past years and become increasingly available. This opens the possibility to calibrate numerical pollen forecast models in real-time and make a significant step forward regarding the quality of pollen forecasts. We present a method to use real-time pollen measurements in numerical pollen forecast models. The main idea is to calibrate model parameterizations and not to assimilate measurements in a nudging sense. This ensures that the positive effect persists throughout the forecast period and does not vanish after a few forecast hours. We propose to adapt in real-time both the model phenology scheme and the overall tuning factor that are present in any numerical pollen forecast model. To test this approach, we used the numerical pollen forecast model COSMO-ART (COnsortium for Small-scale MOdelling-Aerosols and Reactive Trace gases) on a mesh size of 1.1 km covering the greater Alpine domain. Test runs covered two pollen seasons and included Corylus, Alnus, Betula and Poaceae pollen. Comparison with daily measurements from 13 Swiss pollen stations revealed that the model improvements are large, but fine-tuning of the method remains a challenge. We conclude that the presented approach is a first valuable step towards comprehensive real-time calibration of numerical pollen forecast models.

Experimental investigation of mixing railway ballast grains with different form using large-scale direct shear box apparatus

This paper investigates the effect of grain form on the mechanical behaviour of a railway ballast aggregate using large-scale shear box tests. The speciality of the research is that – contrarily to most of the experimental studies, where the shape content of the assemblies are not manipulated – here, the grains were carefully sorted and the ballast samples were assembled with the desired size and form content. A new sorting method was developed for laboratory-scale samples to separate compact and non-compact (flat, elongated or bladed) grains. This method utilises the combination of standard bar sieves and shape index calliper. The geometries of the grains in the resultant assemblies were thoroughly investigated using modern 3D imaging-based shape characterisation methods. With the adequate parameter thresholds, good correspondence was found between the standard industrial and the modern imaging-based methods, which allows the virtual reproduction of the introduced laboratory sorting technique. Three types of andesite railway ballast assemblies were tested experimentally: a fully compact, a fully non-compact and a mixed one. The mixed assembly had the highest internal friction angle which proves that it can be beneficial to mix grains with different types form. The amount of broken mass and the failure modes of the grains were also recorded, and it was found that the non-compact assembly had the highest rate of breakage. The results of the study also serve as a good basis for the calibration of numerical models.

Seismic performance of eccentrically braced frames with short-links: IDA approach using chilean earthquakes

In this research the seismic performance of eccentrically braced frames (EBF) with short links using Chilean earthquakes is studied. The study includes nonlinear static and dynamic analyses, calibration of numerical link models with experimental studies, and over 15,000 models analyzed. Results show that higher ductility and deformation are obtained in most archetypes, while models with 8 stories exhibit more stiffness and less ductile behavior. Furthermore, the strength capacity and ductility increase with the increment of the seismic zone and soft type of soil. Moreover, the research provides a table with the seismic design parameters for each archetype group comparing these values with Chilean seismic specifications. Finally, the study concludes that structures designed with more strength and stiffness have a lower collapse probability under extreme events. This research provides valuable information for structural design and includes fragility curves and a discussion of results that can be applied to structural design.

Churches Acoustics as Intangible Cultural Heritage: Experimental and Numerical Characterization of the Temple of San Biagio

ABSTRACT The acoustic properties of churches are, to date, as much a cultural asset as their architectural features. The study, understanding and conservation of acoustic phenomena that characterize liturgical spaces, to date, make use of new technologies and methodologies that facilitate their practice. The study presented here analyzes the acoustic phenomena that characterize the Temple of San Biagio (Montepulciano, Tuscany, Italy). It makes use of experimental acoustic surveying and the aid of the laser scanning surveying technique for the creation of the geometry, subsequently adopted for numerical acoustic modeling of the church in Odeon Acoustics software, used for the study of its acoustic characteristics. The selected methodology allowed us to delve into dynamics often encountered in acoustic simulations, such as the calibration of numerical models and the influence of the mesh number of the generated geometric models, and to understand the acoustic characteristics of the church.

Efficient Calibration of Groundwater Contaminant Transport Models Using Bayesian Optimization.

Numerical modeling is a significant tool to understand the dynamic characteristics of contaminants transport in groundwater. The automatic calibration of highly parametrized and computationally intensive numerical models for the simulation of contaminant transport in the groundwater flow system is a challenging task. While existing methods use general optimization techniques to achieve automatic calibration, the large numbers of numerical model evaluations required in the calibration process lead to high computing overhead and limit the efficiency of model calibration. This paper presents a Bayesian optimization (BO) method for efficient calibration of numerical models of groundwater contaminant transport. A Bayes model is built to fully represent calibration criteria and derive the objective function for model calibration. The efficiency of model calibration is made possible by the probabilistic surrogate model and the expected improvement acquisition function in BO. The probabilistic surrogate model approximates the computationally expensive objective function with a closed-form expression that can be computed efficiently, while the expected improvement acquisition function proposes the most promising model parameters to improve the fitness to the calibration criteria and reduce the uncertainty of the surrogate model. These schemes allow us to find the optimized model parameters effectively by using a small number of numerical model evaluations. Two case studies for the calibration of the Cr(VI) transport model demonstrate that the BO method is effective and efficient in the inversion of hypothetical model parameters, the minimization of the objective function, and the adaptation of different model calibration criteria. Specifically, this promising performance is achieved within 200 numerical model evaluations, which substantially reduces the computing budget for model calibration.