Seismic Study of Soil Structure Interaction Modelling Approaches

In this paper we study certain modelling techniques by which the concept of soil structure interaction can be simulated in engineering problems and become fruitful for modern construction methods. For practical examination, a baseline model is prepared and put in comparison with an isolated base model which conforms to a rigid bathtub model with spring arrangement. Soil flexibility is taken into consideration during modeling. These modelling techniques are analysed using response spectrum analysis to get the maximum response of seismic parameters like storey forces and spectral acceleration. The study showed that the isolated base model had a superior seismic response and may be used in a variety of engineering applications, such as the design of new infrastructure, such as structures for storing water or other types of sediment, geotechnical modelling. Keywords: Baseline Model, Storey Forces, Spectral Acceleration, Soil Flexibility Rigid Bathtub Model

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of free and open-source models to estimate the sea-level impact can contribute to improve coastal management. This study aims to develop and validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE)—a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the sea-level rise impact module of TerrSet—Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses the Bruun rule formula implemented in GEE and can determine the coastline retreat of a profile by creatting a simple vector line from topo-bathymetric data. The model shows a very high correlation (0.97) with a classical Bruun rule study performed in the Aveiro coast (NW Portugal). Therefore, the achieved results disclose that the GEE platform is suitable to perform these analysis. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific community.

Development of Tools for Coastal Management in Google Earth Engine: Uncertainty Bathtub Model and Bruun Rule

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal man-agement. This study aims to develop and to validate two different models to predict the sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for planetary-scale environmental data analysis. The first model is a Bathtub Model based on the uncertainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and Modeling System software. The validation process performed in the Rio Grande do Sul coastal plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule formula implemented in GEE and is capable to determine the coastline retreat of a profile through the creation of a simple vector line from topo-bathymetric data. The model shows a very high cor-relation (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE platform seems to be an important tool for coastal management. The models developed have been openly shared, enabling the continuous improvement of the code by the scientific commu-nity.

Development of Tools for Coastal Management in Google Earth 2 Engine: Uncertainty Bathtub Model and Bruun Rule

Sea-level rise is a problem increasingly affecting coastal areas worldwide. The existence 15 of Free and Open-Source Models to estimate the sea-level impact can contribute to better coastal 16 management. This study aims to develop and to validate two different models to predict the 17 sea-level rise impact supported by Google Earth Engine (GEE) – a cloud-based platform for plan-18 etary-scale environmental data analysis. The first model is a Bathtub Model based on the uncer-19 tainty of projections of the Sea-level Rise Impact Module of TerrSet - Geospatial Monitoring and 20 Modeling System software. The validation process performed in the Rio Grande do Sul coastal 21 plain (S Brazil) resulted in correlations from 0.75 to 1.00. The second model uses Bruun Rule for-22 mula implemented in GEE and is capable to determine the coastline retreat of a profile through the 23 creation of a simple vector line from topo-bathymetric data. The model shows a very high correla-24 tion (0.97) with a classical Bruun Rule study performed in Aveiro coast (NW Portugal). The GEE 25 platform seems to be an important tool for coastal management. The models developed have been 26 openly shared, enabling the continuous improvement of the code by the scientific community.

COVID-19 Tracking, Visualizing and Predicting the Life Expectancy of Virus

An outbreak of the corona virus is hitting around the world. Since many research had stated the prediction of the corona virus based on the active stage. But somehow the results are not reliable or very close enough to get any results. This research main focus is on understanding the life expectancy behavior of the corona virus. This research also develops the COVID-19 tracking dashboard to visualize the trend of cases recorded, cases recovered, and the number of cases died. A Bathtub model is used to understand the survival behavior of the corona virus and based on the life expectancy, a prediction along with visualization will be carried out.