NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM最新文献_第2页

Test Range For UAV-Based Geophysical Sensors 基于无人机的地球物理传感器测试范围

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120094

A. Dobrovolskiy, K. Linkevičs

引用次数: 0

Optimized joint interpretation of many different datasets using BIM methodology combining CoClass and GeoBIM 使用结合CoClass和GeoBIM的BIM方法优化了许多不同数据集的联合解释

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120081

M. Svensson, O. Friberg

{"title":"Optimized joint interpretation of many different datasets using BIM methodology combining CoClass and GeoBIM","authors":"M. Svensson, O. Friberg","doi":"10.3997/2214-4609.202120081","DOIUrl":"https://doi.org/10.3997/2214-4609.202120081","url":null,"abstract":"Summary In any project careful data management is one of the core issues, certainly in long on-going projects. In projects trying to understand the contamination situation the number of different datasets is often large and of many different data types. On a former gasworks facility in a railway yard, in Bracke in Sweden, many different methods were used, aiming at understanding the spread of primarily tar and PAH contaminants. Some of the methods were geotechnical sounding and sampling, chemical laboratory tests and DCIP. From the start a BIM methodology was chosen to ensure good order of the data also in the longer perspective. The GeoBIM tool was used for data management and for visualization of both data and geomodels using only a web browser, allowing all involved stakeholders to get access to the same information. For allowing not only visual joint interpretation but also automated and advanced comparisons and analyses of the whole data set all data was classified in the CoClass system. CoClass is a hierarchical system allowing computers to sort and analyze data according to a standardized system. The BIM approach applying CoClass on the data managed by the GeoBIM concept clearly improved the ability of analyzing the data.","PeriodicalId":418930,"journal":{"name":"NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126425451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Geophysical investigation of failure on a railway cutting 铁路路堑破坏的地球物理研究

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120085

A. Verweerd, W. Andrews, J. Eason

引用次数: 0

GPR and NDT Surveys on a Proposed UK Spaceport Runway 拟建英国太空港跑道的探地雷达及无损检测测量

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120012

J. Eason, A. Verweerd, W. Andrews

引用次数: 0

Geophysical Remote Condition Monitoring of Transportation Infrastructure Slopes 交通基础设施边坡的地球物理远程监测

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120077

J. Chambers, P. Meldrum, P. Wilkinson, D. Gunn, A. Watlet, B. Dashwood, J. Whiteley, H. Harrison, R. Swift, C. Inauen, O. Kuras, G. Jessamy, S. Glendinning, P. Clarkson, C. Minto, A. Godfrey, R. Crickmore

引用次数: 2

Sharing Geophysical Data for Seismic Characterization of the Matera (Southern Italy) Urban Area 共享地球物理数据用于马泰拉(意大利南部)城区地震表征

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120102

N. Tragni, G. Calamita, L. Lastilla, V. Belloni, R. Ravanelli, M. Lupo, V. Salvia, M. Gallipoli

{"title":"Sharing Geophysical Data for Seismic Characterization of the Matera (Southern Italy) Urban Area","authors":"N. Tragni, G. Calamita, L. Lastilla, V. Belloni, R. Ravanelli, M. Lupo, V. Salvia, M. Gallipoli","doi":"10.3997/2214-4609.202120102","DOIUrl":"https://doi.org/10.3997/2214-4609.202120102","url":null,"abstract":"Summary In the Smart Cities perspective, the digital archiving of all geological, geotechnical, geophysical and engineering data of cities should become a useful tool to plan strategies for seismic risk mitigation in terms of urban planning, seismic retrofitting, and management of post-earthquake crises. The CLARA WebGIS geodatabase, developed and released in the framework of CLARA project (CLoud plAtform and smart underground imaging for natural Risk Assessment) move toward this way; it contains 488 georeferenced and downloadable surveys (such as Downholes, Mechanical Surveys, Salcarenite Sampling Stations, MASW, HVNSR, Seismic Refraction Surveys), the geological and geomorphological maps and map of homogeneous microzones from a seismic response perspective and 215 new single-station seismic ambient noise measurements carried out on urban soils and buildings. CLARA WebGIS is the first publicly available database reporting for the whole urban area the spatial distribution of the soil resonance frequencies and the vibrational frequency of the overlying 4043 buildings, along with the probability of soil-building resonance occurrence. All data are accessible, visualizing, querying and downloadable at this link: https://smartcities-matera-clara.imaa.cnr.it/","PeriodicalId":418930,"journal":{"name":"NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132950561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-resolution assessment of road basement using ground-penetrating radar (GPR) 基于探地雷达(GPR)的道路地基高分辨率评估

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120032

A. Sendrós, A. Casas, C. Abancó, L. Rivero, R. García‐Artigas, A. Urruela, R. Lovera, M. Himi

{"title":"High-resolution assessment of road basement using ground-penetrating radar (GPR)","authors":"A. Sendrós, A. Casas, C. Abancó, L. Rivero, R. García‐Artigas, A. Urruela, R. Lovera, M. Himi","doi":"10.3997/2214-4609.202120032","DOIUrl":"https://doi.org/10.3997/2214-4609.202120032","url":null,"abstract":"Summary Road networks suffer significant structural damage caused by a variety of reasons amplified if the underlying geology induces cracks or deformations. The most common procedure to obtain information from the interior layers of the infrastructure is drilling holes in the road. However, these diagnostic tools are destructive, expensive and slow. Ground Penetration Radar (GPR) brings considerable advantages for the detection of pathologies in inner layers of the road, such as cracks in the wearing course, buried holes and settlement problems providing high-quality images of the radar signal in the interior of the structures. The objectives of the research were to carry out a study with the GPR technique of degraded road pavements to delineate the lateral and depth extent of the cracks and to identify the most problematic areas of the 1 km studied segment. The use of the GPR methods in Pont de Suert site (Spain) have provided an accurate road conditions assessment and differentiate areas with very clear anomalies, that were not visible from the surface, which can serve as a guide for the road managers to intervene before the collapse due to dissolution of gypsums sediments would occur","PeriodicalId":418930,"journal":{"name":"NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117207879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Geophysical survey in the frame of preservation works for an old silo of planes 在保存工程框架下的地球物理测量对一个旧的飞机筒仓

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120043

G. Apostolopoulos, S. Karizonis, G. Amolochitis, D. Karaiskos

引用次数: 0

Fast Near-Surface Investigation With Surface-Wave Attributes 基于表面波属性的快速近地表调查

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120128

M. Papadopoulou, C. Colombero, M. Staring, J. Singer, R. Eddies, M. Fliedner, F. Janod, V. Socco

引用次数: 0

Numerical modeling using gprMax to identify a subsurface tack coat for SVM classification 利用gprMax进行数值模拟，识别地下粘性涂层，并进行SVM分类

NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM Pub Date : 2021-08-29 DOI: 10.3997/2214-4609.202120040

G. Andreoli, A. Ihamouten, C. Fauchard, R. Jaufer, Shreedhar Savant Todkar, D. Guilbert, V. Buliuk, X. Dérobert

{"title":"Numerical modeling using gprMax to identify a subsurface tack coat for SVM classification","authors":"G. Andreoli, A. Ihamouten, C. Fauchard, R. Jaufer, Shreedhar Savant Todkar, D. Guilbert, V. Buliuk, X. Dérobert","doi":"10.3997/2214-4609.202120040","DOIUrl":"https://doi.org/10.3997/2214-4609.202120040","url":null,"abstract":"Summary Face to an increasing traffic volumes, a poor adhesion between bitumen layers combined with weather conditions can lead to premature deterioration of pavement structures. Therefore, it is essential to resort a tack coat where the wearing course and the binder course connect, so that they work as a monolithic block. The purpose of this study, carried out by using gprMax software, is to identify a thin millimetric subsurface tack coat from a modelled bilayer of bitumen and to differentiate the signals according to the modifications of some parameters like thickness, permittivity and conductivity. The so generated large database of time signals with diverse geometric and dielectric characteristics will enable to classify the datas by a supervised machine learning method namely, Support Vector Machines (SVM). Among existing methods, the algorithm of Two-Class SVM (TCSVM) allows to split the datas in two distinct classes. One data set is described as the “adhered” class, and another as the “non adhered” class. The supervised machine learning is conducted with a resolution by global approach to use the raw data set, without any pre-processing. Finally, the binary classification appears then as a promising method to identify clearly and automatically the presence of a tack coat.","PeriodicalId":418930,"journal":{"name":"NSG2021 2nd Conference on Geophysics for Infrastructure Planning, Monitoring and BIM","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122169675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0