General Report - Session 3

This General Report summarizes the 84 papers accepted for the Session 3 focused on: - 3a. Case Histories on Failure and Remediation of Slopes, Dams, Embankments and Landfills (53 papers), - 3b. Case Histories on Failure and Remediation of Retaining Structures, Slurry Walls, and Deep Excavations, Dewatering, Stability (27 papers), - 3c. Improving the Stability and Maintenance of Monuments (4 papers). The papers originate from 26 countries (11 European countries, 3 American countries, 11 Asian countries and 1 African country). The papers cover a number of relevant topics divided into three different sub - sessions. As for the two papers included in Session 3c, only one deals with maintenance and retrofit of historical monuments. Indeed paper 3.03c is more pertinent to session 3b. On the other hand some papers included in Session 3a could also be considered in Session 3b and vice versa

Vulnerability Assessment of Buildings due to Land Subsidence using InSAR Data in the Ancient Historical City of Pistoia (Italy)

The launch of the medium resolution Synthetic Aperture Radar (SAR) Sentinel-1 constellation in 2014 has allowed public and private organizations to introduce SAR interferometry (InSAR) products as a valuable option in their monitoring systems. The massive stacks of displacement data resulting from the processing of large C-B and radar images can be used to highlight temporal and spatial deformation anomalies, and their detailed analysis and postprocessing to generate operative products for final users. In this work, the wide-area mapping capability of Sentinel-1 was used in synergy with the COSMO-SkyMed high resolution SAR data to characterize ground subsidence affecting the urban fabric of the city of Pistoia (Tuscany Region, central Italy). Line of sight velocities were decomposed on vertical and E–W components, observing slight horizontal movements towards the center of the subsidence area. Vertical displacements and damage field surveys allowed for the calculation of the probability of damage depending on the displacement velocity by means of fragility curves. Finally, these data were translated to damage probability and potential loss maps. These products are useful for urban planning and geohazard management, focusing on the identification of the most hazardous areas on which to concentrate efforts and resources.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI) and European Funds for Regional Development (FEDER) under projects AQUARISK (ESP2013-47780-C2-2-R) and TEMUSA (TEC2017-85244-C2-1-P) and STAR-EO (TIN2014-55413-C2-2-P). The first author shows gratitude for the PhD student contract BES-2014-069076. The work was conceived during the research stay of P. Ezquerro and R. Tomás in the Università degli Studi di Firenze and the research stay of G. Herrera in the IGOT Lisbon University, supported by the Spanish Ministry of Education, Culture and Sport under fellowships EEBB-I-18-13014, PRX17/00439 and PRX19/00065, respectively. The S-1 monitoring activity is funded and supported by the Tuscany Region under the agreement “Monitoring ground deformation in the Tuscany Region with satellite radar data.” The authors also gratefully acknowledge TRE ALTAMIRA for having processed the S-1 data. The project was carried out using CSK® Products, © ASI (Italian Space Agency), delivered under the ASI Project Id Science 678 - “High resolution Subsidence investigation in the urban area of Pistoia (Tuscany Region, central Italy). The work is under the framework of the e-shape project, which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement 820852. This paper is also supported by the PRIMA programme under grant agreement No 1924, project RESERVOIR. The PRIMA programme is supported by the European Union

Flood Risk and Resilience

Flooding is widely recognized as a global threat, due to the extent and magnitude of damage it causes around the world each year. Reducing flood risk and improving flood resilience are two closely related aspects of flood management. This book presents the latest advances in flood risk and resilience management on the following themes: hazard and risk analysis, flood behaviour analysis, assessment frameworks and metrics and intervention strategies. It can help the reader to understand the current challenges in flood management and the development of sustainable flood management interventions to reduce the social, economic and environmental consequences from flooding

Acquiring vulnerability indicators to geo-hydrological hazards: An example of mobile phone-based data collection

Abstract Geo-hydrological risk reduction is a key issue for local governments in Italy. In this context, a collaboration was undertaken between multiple actors in the La Spezia municipality aimed at: (i) monitoring building characteristics, using specific and valuable indicators, and (ii) increasing the knowledge of geo-hydrological hazards across residents and local land planners (iii) implementing local emergency civil protection plan. An extensive mobile data collection was carried out through apps specifically developed for Android and IOS mobile devices. The digital forms were differentiated on the basis of the potential hazard: one of 46 fields and one of 125 fields designed for buildings respectively located in flood prone areas and in medium to very high landslide susceptibility areas. The digital version of the forms was designed using the Open Data Kit (ODK) and GISCloud client-server approach. All the collected data, including geospatial locations and images, were automatically sent to a central server, stored and organized in a database. Geospatial data-analysis and maps resulted useful in evaluating possible impacts to exposed buildings to potential geo-hydrological processes. The proposed public participation method for data-gathering increased the knowledge across residents providing a better understanding of the urban systems, of the buildings condition and their relation respect to the geo-hydrological risk. The method can be considered as part of the decision support systems for civil protection purposes to better planning geo-hydrological mitigation measures. The application of mobile technology for data collection can be effectively used when local government resources are limited

Development and implementation of air quality data mart for Ontario, Canada : a case study of air quality in Ontario using OLAP tool

This thesis describes the development and implementation of Air Quality Data Mart for Ontario Canada using Online Analytical Processing (OLAP) tool. It is followed by a case study which presents comparisons of air quality between the urban and rural areas, peak and non-peak hours, working days and weekends for various cities in Ontario. The purpose of this study is to develop a user friendly tool for historical air quality data and evaluate the functionality of the tool by extracting the data across several dimensions. The data for air quality is available on the Ontario Ministry of Environment website for 43 monitoring stations across Ontario. This data is in the form of static Hyper Text Markup Language (HTML) pages which cannot be used for analytical purposes. Air quality data mart was developed using open source OLAP. The database was designed using multidimensional modeling approach. OLAP server “Mondrian” was used as the presentation server whereas “Openi” client was used as an end user tool for this study. The different functions available in this data mart are: rollup, drill down and slice and dice the data across several dimensions such as time, location and pollutant. The most important conclusion of this thesis is the successful implementation of an air quality data mart with the possibility to extract accurate historical air quality data. The data in the form of a data mart provides numerous advantages, where it can be analyzed according to the required analytical perspective for a given city/cities. The only drawback of having data in the form of a data mart is that, if the data is drilled down to the finest precision i.e. to the hour (depending on the number of dimensions selected) the resulting chart will be very crowded but the generated report will present a complete overview of the analysis.Popular summary: Air quality data mart built in this study consists of historical air pollutant data for cities across Ontario. This data is available at the Ontario ministry of environment website from 2000-2007 for most of the cities. There is missing data for some of the cities and some pollutants as well. It is because the monitoring of those specific pollutants did not commence in or before 2000. This data mart facilitates the user to extract historical data. The user does not need to know query language skills. With user friendly interface data analysis can be performed using drag and drop feature. The statistical functions implemented in this data mart are AVG, MIN and MAX. The database is designed in a form where it is possible to extract data for a specific time period. This data can be further filtered based on location and a given pollutant. The query output is in the form of a chart and a table. It is also possible to save the analysis which can be accessed again in future for referential purposes. The air quality in Ontario was compared using parameters like weekday – weekend effect, peak hour – off peak hour, urban and rural areas etc. Most of these parameters were used for the cities of Toronto and Ottawa. The results generated by the data mart showed that the pollutant concentration levels in both cities surpassed the recommended guidelines, but there were less exceedance days monitored in Ottawa compared to Toronto. This data mart lacks the component of visual maps. It would be interesting if this data mart had a choropleth map associated with the pollutant measurements. This would enable the user to visually comprehend the air quality data. However, if there are limitations in air quality data mart for Ontario, Canada at this point it is an indicator that spatial maps with spatial statistics can be implemented in future

Finite element analysis based on a parametric model by approximating point clouds

Simplified models are widely applied in finite element computations regarding mechanical and structural problems. However, the simplified model sometimes causes many deviations in the finite element analysis (FEA) of structures, especially in the non-designed structures which have undergone unknowable deformation features. Hence, a novel FEA methodology based on the parametric model by approximating three-dimensional (3D) feature data is proposed to solve this problem in the present manuscript. Many significant anci effective technologies have been developeci to detect 3D feature information accurately, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology. In this manuscript, the parametric FEA model combines 3D point clouds from TLS and the parametric surface approximation method to generate 3D surfaces and models accurately. TLS is a popular measurement method for reliable 3D point clouds acquisition and monitoring deformations of structures with high accuracy and precision. The B-spline method is applied to approximate the measured point clouds data automatically and generate a parametric description of the structure accurately. The final target is to reduce the effects of the model description and deviations of the FEA. Both static and dynamic computations regarding a composite structure are carried out by comparing the parametric and general simplified models. The comparison of the deformation and equivalent stress of future behaviors are reflected by different models. Results indicate that the parametric model based on the TLS data is superior in the finite element computation. Therefore, it is of great significance to apply the parametric model in the FEA to compute and predict the future behavior of the structures with unknowable deformations in engineering accurately

2012 Projects Day Booklet

https://scholarworks.seattleu.edu/projects-day/1027/thumbnail.jp

Landslide Hazard Affecting Historical Buildings: Santa Scolastica Monastery in Subiaco

Every year landslides occur as a consequence of ground conditions, geomorphological, physical or man-made processes, often triggered by heavy rainfalls or earthquakes. They affect buildings and infrastructures, causing economic and life losses. On the Italian territory, more than 14,000 heritage sites interact with potentially unstable slopes. This work investigates the effects of a landslide, occurred on the 26th of November 2018, on the Monastry of Santa Scolastica in Subiaco (Rome), one of the most ancient and well-preserved examples of medieval architecture in Central Italy. The geometry of the slope was reconstructed based on aerial photographic survey and point-cloud processing, obtaining meshed surfaces and extracting relevant sections. The mechanical parameters and the specific hydraulic conditions triggering the failure mechanism were first recognised by traditional limit equilibrium back-analyses and then implemented in a 3D non-linear finite element (FE) model, which included both the slope and the interacting portion of the ancient structure. Elastic-perfectly plastic constitutive assumptions were adopted for the soil, while the structure was modelled by a three-dimensional anisotropic elastic-perfectly plastic constitutive model, specifically conceived for masonry, accounting for block dimensions and staggering joints effects. Finite element approach proves to be very effective in the analysis of such a coupled interaction problem, leading to a realistic representation of the interplay between the soil displacements and their deformative effects within the structure. The numerical results have been interpreted to highlight the structural response in terms of crack pattern and stress distribution as induced by the interaction with the deforming slope, leading to a quantitative evaluation of the landslide-induced damage. Several scenarios were simulated: first, the pre landslide existing crack pattern was reproduced, then the event was modelled as it occurred, evaluating its consequences on the structure