scholarly journals Structural Identification of Masonry Residential Buildings Considering Wall Openings

2020 ◽  
Author(s):  
Burak Toydemir ◽  
Ali Koçak
Keyword(s):  
Numerical Models ◽  
Residential Buildings ◽  
Ambient Vibration ◽  
Response Analysis ◽  
Structural Parameter ◽  
Model Parameters ◽  
Masonry Structures ◽  
Total Strength ◽  
Wall Openings

Although one-story residential masonry structures are thought not to be vulnerable to seismic actions, many heavily damaged and/or collapsed instances of these types of structures have been observed in the past strong earthquake events. Hence, the evaluation of their safety requires much attention in terms of more precise numerical models. In-situ vibration tests together with laboratory tests on masonry specimens provide valuable information for structural parameter identification that can be used to develop accurate numerical models. These numerical models then can be used for evaluation of the response and seismic safety. While many specific methods and parameters can be adopted in numerical modeling, linear material properties of a structure are expedient in response analysis. Hence, an equation to be used to determine the homogenized linear model parameters for masonry walls with openings is proposed in this study. The equation has been developed based on the percentage of the openings on the wall. The effect of wall openings on the stiffness and the total strength of one-story masonry structures have been evaluated by using the experimental data and the calibrated finite element models. In-situ ambient vibration and material tests have been conducted on three masonry buildings with identical materials and the results from these experiments were used to verify the accuracy of the formulation.

Coupled Thermo-Hydro-Geochemical Models of Engineered Barrier Systems: The Febex Project

2000 ◽  
Vol 663 ◽  
Author(s):  
J. Samper ◽  
R. Juncosa ◽  
V. Navarro ◽  
J. Delgado ◽  
L. Montenegro ◽  
...  
Keyword(s):  
Large Scale ◽  
Reference Model ◽  
Numerical Models ◽  
Full Scale ◽  
Small Scale ◽  
Model Parameters ◽  
In Situ Test ◽  
Wide Range ◽  
Engineered Barrier

ABSTRACTFEBEX (Full-scale Engineered Barrier EXperiment) is a demonstration and research project dealing with the bentonite engineered barrier designed for sealing and containment of waste in a high level radioactive waste repository (HLWR). It includes two main experiments: an situ full-scale test performed at Grimsel (GTS) and a mock-up test operating since February 1997 at CIEMAT facilities in Madrid (Spain) [1,2,3]. One of the objectives of FEBEX is the development and testing of conceptual and numerical models for the thermal, hydrodynamic, and geochemical (THG) processes expected to take place in engineered clay barriers. A significant improvement in coupled THG modeling of the clay barrier has been achieved both in terms of a better understanding of THG processes and more sophisticated THG computer codes. The ability of these models to reproduce the observed THG patterns in a wide range of THG conditions enhances the confidence in their prediction capabilities. Numerical THG models of heating and hydration experiments performed on small-scale lab cells provide excellent results for temperatures, water inflow and final water content in the cells [3]. Calculated concentrations at the end of the experiments reproduce most of the patterns of measured data. In general, the fit of concentrations of dissolved species is better than that of exchanged cations. These models were later used to simulate the evolution of the large-scale experiments (in situ and mock-up). Some thermo-hydrodynamic hypotheses and bentonite parameters were slightly revised during TH calibration of the mock-up test. The results of the reference model reproduce simultaneously the observed water inflows and bentonite temperatures and relative humidities. Although the model is highly sensitive to one-at-a-time variations in model parameters, the possibility of parameter combinations leading to similar fits cannot be precluded. The TH model of the “in situ” test is based on the same bentonite TH parameters and assumptions as for the “mock-up” test. Granite parameters were slightly modified during the calibration process in order to reproduce the observed thermal and hydrodynamic evolution. The reference model captures properly relative humidities and temperatures in the bentonite [3]. It also reproduces the observed spatial distribution of water pressures and temperatures in the granite. Once calibrated the TH aspects of the model, predictions of the THG evolution of both tests were performed. Data from the dismantling of the in situ test, which is planned for the summer of 2001, will provide a unique opportunity to test and validate current THG models of the EBS.

scholarly journals Nonlinear modelling of the seismic response of masonry structures: Calibration strategies

2021 ◽  
Author(s):  
Antonio Maria D’Altri ◽  
Francesco Cannizzaro ◽  
Massimo Petracca ◽  
Diego Alejandro Talledo
Keyword(s):  
Mechanical Properties ◽  
Numerical Models ◽  
Shear Stiffness ◽  
Model Material ◽  
National Standards ◽  
National Standard ◽  
Masonry Structures ◽  
Nonlinear Modelling ◽  
Various Boundary Conditions ◽  
Panel Stiffness

AbstractIn this paper, a simple and practitioners-friendly calibration strategy to consistently link target panel-scale mechanical properties (that can be found in national standards) to model material-scale mechanical properties is presented. Simple masonry panel geometries, with various boundary conditions, are utilized to test numerical models and calibrate their mechanical properties. The calibration is successfully conducted through five different numerical models (most of them available in commercial software packages) suitable for nonlinear modelling of masonry structures, using nonlinear static analyses. Firstly, the panel stiffness calibration is performed, focusing the attention to the shear stiffness. Secondly, the panel strength calibration is conducted for several axial load ratios by attempts using as reference the target panel strength deduced by well-known analytical strength criteria. The results in terms of panel strength for the five different models show that this calibration strategy appears effective in obtaining model properties coherent with Italian National Standard and Eurocode. Open issues remain for the calibration of the post-peak response of masonry panels, which still appears highly conventional in the standards.

scholarly journals In-Situ Measurement of Power Loss for Crystalline Silicon Modules Undergoing Thermal Cycling and Mechanical Loading Stress Testing

Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 72
Author(s):  
Sergiu Spataru ◽  
Peter Hacke ◽  
Dezso Sera
Keyword(s):  
Thermal Cycling ◽  
Power Loss ◽  
Stress Testing ◽  
Series Resistance ◽  
Short Circuit ◽  
In Situ Measurement ◽  
Mechanical Degradation ◽  
Model Parameters ◽  
The Impact

An in-situ method is proposed for monitoring and estimating the power degradation of mc-Si photovoltaic (PV) modules undergoing thermo-mechanical degradation tests that primarily manifest through cell cracking, such as mechanical load tests, thermal cycling and humidity freeze tests. The method is based on in-situ measurement of the module’s dark current-voltage (I-V) characteristic curve during the stress test, as well as initial and final module flash testing on a Sun simulator. The method uses superposition of the dark I-V curve with final flash test module short-circuit current to account for shunt and junction recombination losses, as well as series resistance estimation from the in-situ measured dark I-Vs and final flash test measurements. The method is developed based on mc-Si standard modules undergoing several stages of thermo-mechanical stress testing and degradation, for which we investigate the impact of the degradation on the modules light I-V curve parameters, and equivalent solar cell model parameters. Experimental validation of the method on the modules tested shows good agreement between the in-situ estimated power degradation and the flash test measured power loss of the modules, of up to 4.31 % error (RMSE), as the modules experience primarily junction defect recombination and increased series resistance losses. However, the application of the method will be limited for modules experiencing extensive photo-current degradation or delamination, which are not well reflected in the dark I-V characteristic of the PV module.

scholarly journals Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1865
Author(s):  
Gabriel Calassou ◽  
Pierre-Yves Foucher ◽  
Jean-François Léon
Keyword(s):  
Matched Filter ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Parameters ◽  
Surface Reflectance ◽  
Sequential Method ◽  
Modal Radius ◽  
Sentinel 2

Stack emissions from the industrial sector are a subject of concern for air quality. However, the characterization of the stack emission plume properties from in situ observations remains a challenging task. This paper focuses on the characterization of the aerosol properties of a steel plant stack plume through the use of hyperspectral (HS) airborne remote sensing imagery. We propose a new method, based on the combination of HS airborne acquisition and surface reflectance imagery derived from the Sentinel-2 Multi-Spectral Instrument (MSI). The proposed method detects the plume footprint and estimates the surface reflectance under the plume, the aerosol optical thickness (AOT), and the modal radius of the plume. Hyperspectral surface reflectances are estimated using the coupled non-negative matrix factorization (CNMF) method combining HS and MSI data. The CNMF reduces the error associated with estimating the surface reflectance below the plume, particularly for heterogeneous classes. The AOT and modal radius are retrieved using an optimal estimation method (OEM), based on the forward model and allowing for uncertainties in the observations and in the model parameters. The a priori state vector is provided by a sequential method using the root mean square error (RMSE) metric, which outperforms the previously used cluster tuned matched filter (CTMF). The OEM degrees of freedom are then analysed, in order to refine the mask plume and to enhance the quality of the retrieval. The retrieved mean radii of aerosol particles in the plume is 0.125 μμm, with an uncertainty of 0.05 μμm. These results are close to the ultra-fine mode (modal radius around 0.1 μμm) observed from in situ measurements within metallurgical plant plumes from previous studies. The retrieved AOT values vary between 0.07 (near the source point) and 0.01, with uncertainties of 0.005 for the darkest surfaces and above 0.010 for the brightest surfaces.

scholarly journals Sub-Level Stoping in an Underground Limestone Quarry: An Analysis of the State of Stress in an Evolutionary Scenario

2016 ◽  
Vol 61 (1) ◽  
pp. 199-216 ◽  
Author(s):  
Marilena Cardu ◽  
Sergio Dipietromaria ◽  
Pierpaolo Oreste
Keyword(s):  
Numerical Models ◽  
The State ◽  
In Situ Tests ◽  
Future Scenario ◽  
Limestone Quarry ◽  
Geomechanical Properties ◽  
State Of Stress ◽  
Upper Level ◽  
Pillar Structure

Abstract The aim of this study was to evaluate the state of stress of a „voids-pillar“ structure excavated by means of the sub-level stoping method in an underground limestone quarry near Bergamo (Italy). Both the current structure of the quarry (i.e. the rooms exploited till now) and a possible future scenario were analysed using the (FDM) FLAC 2D code. The quarry has been in operation since 1927; at present, exploitation is carried out underground via the sub-level stoping method. Exploitation involves two levels, with 5 rooms on the upper level and 9 rooms on the lower level. After analysing data obtained from laboratory and in situ tests carried out on rock samples and natural discontinuities, the geomechanical properties of the medium, knowledge of which is essential in order to establish the parameters that must be included in the numerical model, were evaluated. The implementation of three numerical models made it possible to study both the present conditions of quarry exploitation and the evolution of the exploited rooms, as well as a possible expansion involving a third level of rooms. Using the results obtained regarding the stress-strain present in the pillars, a potential change in room geometry was proposed aimed at reducing the stress state inside the pillars, decreasing plasticity and increasing overall quarry safety.

Analysis of TBM Tunnel Behavior in Jointed Rock Mass

2011 ◽  
Vol 90-93 ◽  
pp. 2033-2036 ◽  
Author(s):  
Jin Shan Sun ◽  
Hong Jun Guo ◽  
Wen Bo Lu ◽  
Qing Hui Jiang
Keyword(s):  
Rock Mass ◽  
Numerical Models ◽  
Jointed Rock ◽  
In Situ Stress ◽  
Jointed Rock Mass ◽  
Joint Orientation ◽  
Joint Spacing ◽  
Factors Affecting ◽  
Dip Angle

The factors affecting the TBM tunnel behavior in jointed rock mass is investigated. In the numerical models the concrete segment lining of TBM tunnel is concerned, which is simulated as a tube neglecting the segment joint. And the TBM tunnel construction process is simulate considering the excavation and installing of the segment linings. Some cases are analyzed with different joint orientation, joint spacing, joint strength and tunnel depth. The results show that the shape and areas of loosing zones of the tunnel are influenced by the parameters of joint sets and in-situ stress significantly, such as dip angle, spacing, strength, and the in-situ stress statement. And the stress and deformation of the tunnel lining are influenced by the parameters of joint sets and in-situ stress, too.

Ice-Phase Precipitation

2017 ◽  
Vol 58 ◽  
pp. 6.1-6.36 ◽  
Author(s):  
I. Gultepe ◽  
A. J. Heymsfield ◽  
P. R. Field ◽  
D. Axisa
Keyword(s):  
Collection Efficiency ◽  
Numerical Models ◽  
Mass Density ◽  
Three Dimensional ◽  
Phase Precipitation ◽  
Microphysical Parameters ◽  
Mass Size ◽  
Ice Water ◽  
Ice Phase

AbstractIce-phase precipitation occurs at Earth’s surface and may include various types of pristine crystals, rimed crystals, freezing droplets, secondary crystals, aggregates, graupel, hail, or combinations of any of these. Formation of ice-phase precipitation is directly related to environmental and cloud meteorological parameters that include available moisture, temperature, and three-dimensional wind speed and turbulence, as well as processes related to nucleation, cooling rate, and microphysics. Cloud microphysical parameters in the numerical models are resolved based on various processes such as nucleation, mixing, collision and coalescence, accretion, riming, secondary ice particle generation, turbulence, and cooling processes. These processes are usually parameterized based on assumed particle size distributions and ice crystal microphysical parameters such as mass, size, and number and mass density. Microphysical algorithms in the numerical models are developed based on their need for applications. Observations of ice-phase precipitation are performed using in situ and remote sensing platforms, including radars and satellite-based systems. Because of the low density of snow particles with small ice water content, their measurements and predictions at the surface can include large uncertainties. Wind and turbulence affecting collection efficiency of the sensors, calibration issues, and sensitivity of ground-based in situ observations of snow are important challenges to assessing the snow precipitation. This chapter’s goals are to provide an overview for accurately measuring and predicting ice-phase precipitation. The processes within and below cloud that affect falling snow, as well as the known sources of error that affect understanding and prediction of these processes, are discussed.

scholarly journals Advanced experimental approaches to marine water-column biogeochemical processes

2017 ◽  
Vol 75 (1) ◽  
pp. 30-42 ◽  
Author(s):  
Louis Legendre ◽  
Richard B Rivkin ◽  
Nianzhi Jiao
Keyword(s):  
Water Column ◽  
Numerical Models ◽  
Free Water ◽  
Sea Surface ◽  
Biogeochemical Processes ◽  
In Situ Experiments ◽  
Technological Developments ◽  
Approaches To Study ◽  
Experimental Approaches

Abstract This “Food for Thought” article examines the potential uses of several novel scientific and technological developments, which are currently available or being developed, to significantly advance or supplement existing experimental approaches to study water-column biogeochemical processes (WCB-processes). After examining the complementary roles of observation, experiments and numerical models to study WCB-processes, we focus on the main experimental approaches of free-water in situ experiments, and at-sea and on-land meso- and macrocosms. We identify some of the incompletely resolved aspects of marine WCB-processes, and explore advanced experimental approaches that could be used to reduce their uncertainties. We examine three such approaches: free-water experiments of lengthened duration using bioArgo floats and gliders, at-sea mesocosms deployed several 100s m below the sea-surface using new biogeochemical sensors, and 50 m-tall on-land macrocosms. These approaches could lead to significant progress in concepts related to marine WCB-processes.

Conditioning Model Ensembles to Various Observed Data (Field and Regional Level) by Applying Machine-Learning-Augmented Workflows to a Mature Field with 70 Years of Production History

2021 ◽  
pp. 1-18
Author(s):  
Gisela Vanegas ◽  
John Nejedlik ◽  
Pascale Neff ◽  
Torsten Clemens
Keyword(s):  
Machine Learning ◽  
Oil Recovery ◽  
Numerical Models ◽  
Operating Conditions ◽  
Model Parameters ◽  
Large Set ◽  
Model Parameter ◽  
Production History ◽  
Hydrocarbon Fields ◽  
Parameter Distributions

Summary Forecasting production from hydrocarbon fields is challenging because of the large number of uncertain model parameters and the multitude of observed data that are measured. The large number of model parameters leads to uncertainty in the production forecast from hydrocarbon fields. Changing operating conditions [e.g., implementation of improved oil recovery or enhanced oil recovery (EOR)] results in model parameters becoming sensitive in the forecast that were not sensitive during the production history. Hence, simulation approaches need to be able to address uncertainty in model parameters as well as conditioning numerical models to a multitude of different observed data. Sampling from distributions of various geological and dynamic parameters allows for the generation of an ensemble of numerical models that could be falsified using principal-component analysis (PCA) for different observed data. If the numerical models are not falsified, machine-learning (ML) approaches can be used to generate a large set of parameter combinations that can be conditioned to the different observed data. The data conditioning is followed by a final step ensuring that parameter interactions are covered. The methodology was applied to a sandstone oil reservoir with more than 70 years of production history containing dozens of wells. The resulting ensemble of numerical models is conditioned to all observed data. Furthermore, the resulting posterior-model parameter distributions are only modified from the prior-model parameter distributions if the observed data are informative for the model parameters. Hence, changes in operating conditions can be forecast under uncertainty, which is essential if nonsensitive parameters in the history are sensitive in the forecast.

A new ensemble-based statistical methodology to verify changes in weather and climate models

2021 ◽  
Author(s):  
Christian Zeman ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Hypothesis Test ◽  
Model Development ◽  
Atmospheric Model ◽  
Statistical Hypothesis ◽  
Model Parameters ◽  
Rounding Errors ◽  
Weather And Climate

<p>Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.</p><p>Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.</p><p>We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.</p>

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