CityGML Integration Into the ArcGIS PlatformSafe Software
This document discusses integrating CityGML 3D city model data into ArcGIS systems using FME. It provides an overview of CityGML and Indexed 3D Scene Layers standards, challenges in converting between the formats like preserving semantics and representations, and workflows for importing CityGML into ArcGIS Pro geodatabases and scene layer packages using FME tools. It also describes the ArcGIS CityGML toolbox for standardizing CityGML import into ArcGIS and a future vision of more integrated BIM and GIS data workflows.
A- LES CONCEPTS
Comprehension du bim.
Travailler dans différentes vues.
Classement et hierarchie des éléments dans Revit.
B-L'ENVIRONNEMENT DE TRAVAIL
Page des fichiers rescents et grand R.
Le ruban.
Fenêtre des propriétés.
Explorateur du projet.
Navigation dans un modèle.(zoom, rotation et panoramique).
Selection des objets, et verouillage.
C-DEMARRAGE D'UN PROJET.
Les gabarits.
Travail collaboratif.
Configuration d'un nouveau projet.
Manipulation des niveaux.
Manipulation des files de projet.
Utilisation des cotes temporaires.
C- MODELISATION PAR OBJETS:
Ajout des murs.
Propriété et type de murs.
Utilisation des accroches.
Ajouts de poteaux et poutres.
Ajout de portes et fenêtres.
Ajout d'élements de plomberie et d'électricité.
Utilisation de la jonction entre murs.
Utilisation des contraintes.
D- LIENS, IMPORTS ET GROUPES:
Lier fichiers DWG/DXF/SKP
Création de topogrpahie d'un site à partir d'un fichier.
Création et gestion des groupes.
Création et gestion des liens Revit.
Utilisation du partage d'emplacement.
E- MODELISATION PAR ESQUISSE:
Sols., toits et plafonds.
Toit par extrusion.
Ouvertures.
F-ESCALIERS.
Edition avancée d'escalier.
Edition avancée de gardes corps.
G- EDITION AVANCEE DES MURS:
Création d'un nouveau type de murs..
Création et gestion des murs empilés.
Création et gestion des murs rideaux.
.
H- GESTION DES GRAPHISMES:
Gestion du style des objets.
Gestion du remplacement de la visibilité et du graphisme des éléments.
Création et application des gabarits de vue.
Cacher et isoler les éléments.
Cadrage de la vue.
Plage de vue et entendues.
Vue isométrique d'une selection.
Option d'affichage des graphismes.
I- PIECES:
Création et gestion des pièces.
J- NOMENCLATURE ET ETIQUETTES:
Gestion des étiquettes.
Création et gestion des nomenclatures.
Modification des nomenclatures.
Enrichissement des VCCTP par les nomenclatures.
K-ANNOTATIONS.
Textes.
Dimensions
Symboles.
Légendes.
Détails.
Définir ses annotations.
L- PARAMETRIQUE ET FAMILLES
Utilisation des paramètres en mode projet.
Concept de famille.
Création d'une famille.
Utilisation des contraintes.
Utilisation des formes solides.
M- FEUILLE, IMPRESSION, PUBLICATION:
Création d'une feuille d'impression.
Export CAO.
Publication.
Impression PDF.
N- TRUCS ET ASTUCES.
A découvrir en formation.
http://structalis.fr
Tao Feng gave a presentation on Airflow at Lyft. Some key points:
1) Lyft uses Apache Airflow for ETL workflows with over 600 DAGs and 800 DAG runs daily across three AWS Auto Scaling Groups of worker nodes.
2) Lyft has customized Airflow with additional UI links, DAG dependency graphs, and integration with internal tools.
3) Lyft is working to improve the backfill experience, support DAG-level access controls, and explore running Airflow with Kubernetes executors.
4) Tao discussed challenges like daylight saving time issues and long-running tasks occupying slots, and thanked other Lyft engineers contributing to Airflow.
This document discusses relational and non-relational databases. It begins by introducing NoSQL databases and some of their key characteristics like not requiring a fixed schema and avoiding joins. It then discusses why NoSQL databases became popular for companies dealing with huge data volumes due to limitations of scaling relational databases. The document covers different types of NoSQL databases like key-value, column-oriented, graph and document-oriented databases. It also discusses concepts like eventual consistency, ACID properties, and the CAP theorem in relation to NoSQL databases.
Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data. In this session we will learn how to create data integration solutions using the Data Factory service and ingest data from various data stores, transform/process the data, and publish the result data to the data stores.
This document discusses improving the developer experience through GitOps and ArgoCD. It recommends building developer self-service tools for cloud resources and Kubernetes to reduce frustration. Example GitLab CI/CD pipelines are shown that handle releases, deployments to ECR, and patching apps in an ArgoCD repository to sync changes. The goal is to create faster feedback loops through Git operations and automation to motivate developers.
CityGML Integration Into the ArcGIS PlatformSafe Software
This document discusses integrating CityGML 3D city model data into ArcGIS systems using FME. It provides an overview of CityGML and Indexed 3D Scene Layers standards, challenges in converting between the formats like preserving semantics and representations, and workflows for importing CityGML into ArcGIS Pro geodatabases and scene layer packages using FME tools. It also describes the ArcGIS CityGML toolbox for standardizing CityGML import into ArcGIS and a future vision of more integrated BIM and GIS data workflows.
A- LES CONCEPTS
Comprehension du bim.
Travailler dans différentes vues.
Classement et hierarchie des éléments dans Revit.
B-L'ENVIRONNEMENT DE TRAVAIL
Page des fichiers rescents et grand R.
Le ruban.
Fenêtre des propriétés.
Explorateur du projet.
Navigation dans un modèle.(zoom, rotation et panoramique).
Selection des objets, et verouillage.
C-DEMARRAGE D'UN PROJET.
Les gabarits.
Travail collaboratif.
Configuration d'un nouveau projet.
Manipulation des niveaux.
Manipulation des files de projet.
Utilisation des cotes temporaires.
C- MODELISATION PAR OBJETS:
Ajout des murs.
Propriété et type de murs.
Utilisation des accroches.
Ajouts de poteaux et poutres.
Ajout de portes et fenêtres.
Ajout d'élements de plomberie et d'électricité.
Utilisation de la jonction entre murs.
Utilisation des contraintes.
D- LIENS, IMPORTS ET GROUPES:
Lier fichiers DWG/DXF/SKP
Création de topogrpahie d'un site à partir d'un fichier.
Création et gestion des groupes.
Création et gestion des liens Revit.
Utilisation du partage d'emplacement.
E- MODELISATION PAR ESQUISSE:
Sols., toits et plafonds.
Toit par extrusion.
Ouvertures.
F-ESCALIERS.
Edition avancée d'escalier.
Edition avancée de gardes corps.
G- EDITION AVANCEE DES MURS:
Création d'un nouveau type de murs..
Création et gestion des murs empilés.
Création et gestion des murs rideaux.
.
H- GESTION DES GRAPHISMES:
Gestion du style des objets.
Gestion du remplacement de la visibilité et du graphisme des éléments.
Création et application des gabarits de vue.
Cacher et isoler les éléments.
Cadrage de la vue.
Plage de vue et entendues.
Vue isométrique d'une selection.
Option d'affichage des graphismes.
I- PIECES:
Création et gestion des pièces.
J- NOMENCLATURE ET ETIQUETTES:
Gestion des étiquettes.
Création et gestion des nomenclatures.
Modification des nomenclatures.
Enrichissement des VCCTP par les nomenclatures.
K-ANNOTATIONS.
Textes.
Dimensions
Symboles.
Légendes.
Détails.
Définir ses annotations.
L- PARAMETRIQUE ET FAMILLES
Utilisation des paramètres en mode projet.
Concept de famille.
Création d'une famille.
Utilisation des contraintes.
Utilisation des formes solides.
M- FEUILLE, IMPRESSION, PUBLICATION:
Création d'une feuille d'impression.
Export CAO.
Publication.
Impression PDF.
N- TRUCS ET ASTUCES.
A découvrir en formation.
http://structalis.fr
Tao Feng gave a presentation on Airflow at Lyft. Some key points:
1) Lyft uses Apache Airflow for ETL workflows with over 600 DAGs and 800 DAG runs daily across three AWS Auto Scaling Groups of worker nodes.
2) Lyft has customized Airflow with additional UI links, DAG dependency graphs, and integration with internal tools.
3) Lyft is working to improve the backfill experience, support DAG-level access controls, and explore running Airflow with Kubernetes executors.
4) Tao discussed challenges like daylight saving time issues and long-running tasks occupying slots, and thanked other Lyft engineers contributing to Airflow.
This document discusses relational and non-relational databases. It begins by introducing NoSQL databases and some of their key characteristics like not requiring a fixed schema and avoiding joins. It then discusses why NoSQL databases became popular for companies dealing with huge data volumes due to limitations of scaling relational databases. The document covers different types of NoSQL databases like key-value, column-oriented, graph and document-oriented databases. It also discusses concepts like eventual consistency, ACID properties, and the CAP theorem in relation to NoSQL databases.
Azure Data Factory is a cloud-based data integration service that orchestrates and automates the movement and transformation of data. In this session we will learn how to create data integration solutions using the Data Factory service and ingest data from various data stores, transform/process the data, and publish the result data to the data stores.
This document discusses improving the developer experience through GitOps and ArgoCD. It recommends building developer self-service tools for cloud resources and Kubernetes to reduce frustration. Example GitLab CI/CD pipelines are shown that handle releases, deployments to ECR, and patching apps in an ArgoCD repository to sync changes. The goal is to create faster feedback loops through Git operations and automation to motivate developers.
“DevOps no es una cosa. No es un producto, estándar, especificación, marco o título de puesto. DevOps tiene que ver con experiencias y cultura. Tiene que ver con comunicación y colaboración estrecha entre operaciones de TI y desarrollo, y en cómo ellos pueden mejorar los productos y servicios que producen mediante pensar diferente acerca de cómo trabajar juntos.
SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications. The SSIS architecture includes packages, tasks, containers, variables, connections and event handlers. Packages contain control flow elements, like tasks and containers, that prepare data. Data flow elements in packages extract, transform and load data. The control flow engine manages task execution while the data flow engine moves data between sources and destinations.
Bitbucket is a hosting site for Git and Mercurial repositories that allows for effective collaboration without requiring a centralized server. While Git does not require a central server, it is good to have Bitbucket to host code repositories. Git uses a distributed version control system that allows developers to directly exchange changes and work independently of network access. Benefits of using Git with Bitbucket include free hosting for academic users, the ability to work offline or on planes, and fast branching and merging of code.
Case Study: Migration to GitLab (from Bitbucket) at AppsFlyerNoa Harel
AppsFlyer migrated from BitBucket to GitLab for their 150 users and 680 repositories. They wanted to leave the hosted BitBucket solution due to API call limits and latency. The migration process involved converting repositories from Mercurial to Git, setting up the GitLab architecture on Amazon Web Services with an EFS file system, educating teams, and creating custom tooling like a Python script to notify Slack. Lessons learned included issues restoring backups and increasing Unicorn workers. The full technical details are available at the provided URL.
How to Create GIS and BIM InteroperabilitySafe Software
Discover how to solve the most common problems with BIM and GIS integration. See how to easily move data between IFC, Autodesk Revit, SketchUp 2015, Esri ArcGIS, AutoCAD, and more. You'll also learn how to use automated techniques to get simplified BIM geometries into GIS, combine attribute or tabular data with existing models, perform space extraction, QC data, and much more.
Designing and Building Next Generation Data Pipelines at Scale with Structure...Databricks
This document discusses the evolution of data pipelines at Databricks over time from 2014 to present day. Early pipelines involved copying data from S3 hourly, which did not scale. Later pipelines used Amazon Kinesis but led to performance issues with many small files. The document then introduces structured streaming and Delta Lake as better solutions. Structured streaming provides correctness while Delta Lake improves performance, scalability, and makes data management and GDPR compliance easier through features like ACID transactions, automatic schema management, and built-in deletion/update support.
Gitops: a new paradigm for software defined operationsMariano Cunietti
The document discusses GitOps and a new paradigm called cloud native applications. It promotes GitOps as an approach where the entire system, including code, config, monitoring rules and policies are described in a Git repository. This allows the entire system to be destroyed and re-built with no human intervention. It then describes Automium, a solution the author's company built based on GitOps fundamentals to help with cloud transformations.
The waterfall model is a linear software development process consisting of requirements gathering, analysis, design, implementation, testing, deployment, and maintenance stages. It has advantages like being easy to plan, emphasizing documentation, and allowing for better project control. However, it is also rigid and inflexible, has limited customer involvement and testing late in the process, and is not well-suited for changing requirements. The waterfall model works best for projects with well-defined requirements and scope.
2019년 8월 7일 COEX에서 개최된 '새로운 위치기준 포럼 2019'에서 발표한 자료입니다.
요약: 본 발표에서는 CAD/BIM/GIS의 통합과 관련한 최근 동향을 살펴보고 실제 사례 중심으로 현장에서 겪은 경험들을 공유한다. CAD/BIM/GIS의 통합시도는 OGC, buildingSmart 같은 관련 국제 표준화기구, AutoDesk, ESRI, Bentley 등과 같은 산업계, 그리고 오픈소스 진영의 참여 속에 활발하게 진행되고 있다. CAD/BIM/GIS 통합은 태생적, 기술적, 문화적 차이로 인해 쉽지 않은 과정이다. 성공적인 CAD/BIM/GIS 통합을 위해서는 기술적 통합 자체보다는 통합을 통해 얻고자 하는 혜택과 가치에 집중해야 한다. 구체적 통합 방향으로 목적에 맞는 데이터 활용, 상호운용성을 위한 표준 준수, 데이터 생애주기에 대한 이해, 타 2D/3D/4D 데이터 및 시스템과의 융복합, 분석 및 시뮬레이션 구현 등을 제시한다.
At wetter.com we build analytical B2B data products and heavily use Spark and AWS technologies for data processing and analytics. I explain why we moved from AWS EMR to Databricks and Delta and share our experiences from different angles like architecture, application logic and user experience. We will look how security, cluster configuration, resource consumption and workflow changed by using Databricks clusters as well as how using Delta tables simplified our application logic and data operations.
This document provides a history of Google's Developer Relations program from 2006 to 2011. It discusses how DevRel was originally founded in the US in 2006 and has since expanded globally. Key events discussed include the launches of Android, Google Maps API, and Google I/O conference. The document outlines DevRel's mission to make Google platforms the ecosystem of choice for developers and describes the roles of Developer Advocates, Engineers, and Program Managers. It also summarizes some of the programs DevRel runs like IO, Developer Days, GTUGs, and Developer Labs.
Spiral Model - Software Development Life Cycle (SDLC)ACM-KU
This presentation is about Spiral Model in Software Development models. It includes all of it a bit of it's antiquity, its phases and all the important features.
ROI & Business Value of CI, CD, DevOps, DevSecOps, & MicroservicesDavid Rico
Comprehensive overview of CI, CD, DevOps, DevSecOps, and Microservices, along with costs, benefits, facts, figures, statistics, models, tools, DevOps ecosystems and pipelines, case studies, and edge cases ...
DevOps Transformation: Learnings and Best PracticesQBurst
The presentation delves into the best practices and approach for DevOps adoption. Understand key aspects of DevOps and how it brings about speed and efficiency in the software development lifecycle
We are more than thrilled to announce the second meetup on 10 December 2022 where we discuss GitOps, ArgoCD and their fundamentals. Inviting SREs, DevOps engineers, developers & platform engineers from all around the world.
Agenda:-
1. GitOps Overview
2. Why and What is GitOps
3. Opensource GitOps tools
4. What is ArgoCD, Architecture
5. Let's Get our hands dirty on ArgoCD
6. Q&A
Staffing in Software Projects In software development environment, when proje...ssuserb7c8b8
Staffing in software projects involves four main concerns: staff selection, development, motivation, and well-being. The document discusses these concerns and how they impact all stages of project planning and execution. It also covers topics like team formation, decision making, and organizational structures. Effective staffing requires selecting the right people, providing training and feedback, job design, and addressing issues like stress and safety. Collaboration, communication, and developing a collective mindset are important for high performing teams.
Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure. Designed in collaboration with the founders of Apache Spark, Azure Databricks combines the best of Databricks and Azure to help customers accelerate innovation with one-click set up, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts. As an Azure service, customers automatically benefit from the native integration with other Azure services such as Power BI, SQL Data Warehouse, and Cosmos DB, as well as from enterprise-grade Azure security, including Active Directory integration, compliance, and enterprise-grade SLAs.
“DevOps no es una cosa. No es un producto, estándar, especificación, marco o título de puesto. DevOps tiene que ver con experiencias y cultura. Tiene que ver con comunicación y colaboración estrecha entre operaciones de TI y desarrollo, y en cómo ellos pueden mejorar los productos y servicios que producen mediante pensar diferente acerca de cómo trabajar juntos.
SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications. The SSIS architecture includes packages, tasks, containers, variables, connections and event handlers. Packages contain control flow elements, like tasks and containers, that prepare data. Data flow elements in packages extract, transform and load data. The control flow engine manages task execution while the data flow engine moves data between sources and destinations.
Bitbucket is a hosting site for Git and Mercurial repositories that allows for effective collaboration without requiring a centralized server. While Git does not require a central server, it is good to have Bitbucket to host code repositories. Git uses a distributed version control system that allows developers to directly exchange changes and work independently of network access. Benefits of using Git with Bitbucket include free hosting for academic users, the ability to work offline or on planes, and fast branching and merging of code.
Case Study: Migration to GitLab (from Bitbucket) at AppsFlyerNoa Harel
AppsFlyer migrated from BitBucket to GitLab for their 150 users and 680 repositories. They wanted to leave the hosted BitBucket solution due to API call limits and latency. The migration process involved converting repositories from Mercurial to Git, setting up the GitLab architecture on Amazon Web Services with an EFS file system, educating teams, and creating custom tooling like a Python script to notify Slack. Lessons learned included issues restoring backups and increasing Unicorn workers. The full technical details are available at the provided URL.
How to Create GIS and BIM InteroperabilitySafe Software
Discover how to solve the most common problems with BIM and GIS integration. See how to easily move data between IFC, Autodesk Revit, SketchUp 2015, Esri ArcGIS, AutoCAD, and more. You'll also learn how to use automated techniques to get simplified BIM geometries into GIS, combine attribute or tabular data with existing models, perform space extraction, QC data, and much more.
Designing and Building Next Generation Data Pipelines at Scale with Structure...Databricks
This document discusses the evolution of data pipelines at Databricks over time from 2014 to present day. Early pipelines involved copying data from S3 hourly, which did not scale. Later pipelines used Amazon Kinesis but led to performance issues with many small files. The document then introduces structured streaming and Delta Lake as better solutions. Structured streaming provides correctness while Delta Lake improves performance, scalability, and makes data management and GDPR compliance easier through features like ACID transactions, automatic schema management, and built-in deletion/update support.
Gitops: a new paradigm for software defined operationsMariano Cunietti
The document discusses GitOps and a new paradigm called cloud native applications. It promotes GitOps as an approach where the entire system, including code, config, monitoring rules and policies are described in a Git repository. This allows the entire system to be destroyed and re-built with no human intervention. It then describes Automium, a solution the author's company built based on GitOps fundamentals to help with cloud transformations.
The waterfall model is a linear software development process consisting of requirements gathering, analysis, design, implementation, testing, deployment, and maintenance stages. It has advantages like being easy to plan, emphasizing documentation, and allowing for better project control. However, it is also rigid and inflexible, has limited customer involvement and testing late in the process, and is not well-suited for changing requirements. The waterfall model works best for projects with well-defined requirements and scope.
2019년 8월 7일 COEX에서 개최된 '새로운 위치기준 포럼 2019'에서 발표한 자료입니다.
요약: 본 발표에서는 CAD/BIM/GIS의 통합과 관련한 최근 동향을 살펴보고 실제 사례 중심으로 현장에서 겪은 경험들을 공유한다. CAD/BIM/GIS의 통합시도는 OGC, buildingSmart 같은 관련 국제 표준화기구, AutoDesk, ESRI, Bentley 등과 같은 산업계, 그리고 오픈소스 진영의 참여 속에 활발하게 진행되고 있다. CAD/BIM/GIS 통합은 태생적, 기술적, 문화적 차이로 인해 쉽지 않은 과정이다. 성공적인 CAD/BIM/GIS 통합을 위해서는 기술적 통합 자체보다는 통합을 통해 얻고자 하는 혜택과 가치에 집중해야 한다. 구체적 통합 방향으로 목적에 맞는 데이터 활용, 상호운용성을 위한 표준 준수, 데이터 생애주기에 대한 이해, 타 2D/3D/4D 데이터 및 시스템과의 융복합, 분석 및 시뮬레이션 구현 등을 제시한다.
At wetter.com we build analytical B2B data products and heavily use Spark and AWS technologies for data processing and analytics. I explain why we moved from AWS EMR to Databricks and Delta and share our experiences from different angles like architecture, application logic and user experience. We will look how security, cluster configuration, resource consumption and workflow changed by using Databricks clusters as well as how using Delta tables simplified our application logic and data operations.
This document provides a history of Google's Developer Relations program from 2006 to 2011. It discusses how DevRel was originally founded in the US in 2006 and has since expanded globally. Key events discussed include the launches of Android, Google Maps API, and Google I/O conference. The document outlines DevRel's mission to make Google platforms the ecosystem of choice for developers and describes the roles of Developer Advocates, Engineers, and Program Managers. It also summarizes some of the programs DevRel runs like IO, Developer Days, GTUGs, and Developer Labs.
Spiral Model - Software Development Life Cycle (SDLC)ACM-KU
This presentation is about Spiral Model in Software Development models. It includes all of it a bit of it's antiquity, its phases and all the important features.
ROI & Business Value of CI, CD, DevOps, DevSecOps, & MicroservicesDavid Rico
Comprehensive overview of CI, CD, DevOps, DevSecOps, and Microservices, along with costs, benefits, facts, figures, statistics, models, tools, DevOps ecosystems and pipelines, case studies, and edge cases ...
DevOps Transformation: Learnings and Best PracticesQBurst
The presentation delves into the best practices and approach for DevOps adoption. Understand key aspects of DevOps and how it brings about speed and efficiency in the software development lifecycle
We are more than thrilled to announce the second meetup on 10 December 2022 where we discuss GitOps, ArgoCD and their fundamentals. Inviting SREs, DevOps engineers, developers & platform engineers from all around the world.
Agenda:-
1. GitOps Overview
2. Why and What is GitOps
3. Opensource GitOps tools
4. What is ArgoCD, Architecture
5. Let's Get our hands dirty on ArgoCD
6. Q&A
Staffing in Software Projects In software development environment, when proje...ssuserb7c8b8
Staffing in software projects involves four main concerns: staff selection, development, motivation, and well-being. The document discusses these concerns and how they impact all stages of project planning and execution. It also covers topics like team formation, decision making, and organizational structures. Effective staffing requires selecting the right people, providing training and feedback, job design, and addressing issues like stress and safety. Collaboration, communication, and developing a collective mindset are important for high performing teams.
Azure Databricks is a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure. Designed in collaboration with the founders of Apache Spark, Azure Databricks combines the best of Databricks and Azure to help customers accelerate innovation with one-click set up, streamlined workflows, and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts. As an Azure service, customers automatically benefit from the native integration with other Azure services such as Power BI, SQL Data Warehouse, and Cosmos DB, as well as from enterprise-grade Azure security, including Active Directory integration, compliance, and enterprise-grade SLAs.
The document summarizes two experimental studies on improving the durability of concrete bridge decks. Phase I studied different concrete mix designs including ordinary Portland cement and mixes with admixtures like fly ash and blast furnace slag. Phase II focused on three mix designs: ordinary Portland cement and two high-performance concretes with different admixture combinations. Field application of the best performing mix from Phase II on an actual bridge deck is also described. Test results showed that high-performance concretes improved cracking resistance, chloride permeability, scaling resistance and freeze-thaw durability compared to ordinary Portland cement.
Interactive Visual Analysis for In-Depth Bridge ManagementXiaoyu Wang
Bridges deteriorate over their life cycles and require continuous maintenance to ensure their structural integrity, and in turn, the safety of the public. Maintaining bridges is a multi-faceted operation that requires both domain knowledge and analytics techniques over large data sources. Although most existing bridge management systems (BMS) are very efficient at data storage, they are not as effective at providing analytical capabilities or as flexible at supporting different inspection technologies. In this paper, we present a visual analytics system that extends the capability of current BMSs. Based on a nation-wide survey and our interviews with bridge managers, we designed our system to be customizable so that it can provide interactive exploration, information correlation, and domain-oriented data analysis. When tested by bridge managers of the U.S. Department of Transportation, we validated that our system provides bridge managers with the necessary features for performing in-depth analysis of bridges from a variety of perspectives that are in accordance to their typical workflow.
6. 교량 붕괴 원인(미국토목학회 저널, 2003)
관리부실 자연 재해
구분 계
소계 결함 세굴 충돌 화재 기타 소계 홍수 지진
개소 503 296 98 78 59 16 45 207 190 17
(%) 100 56 20 15 12 3 9 41 38 3
7. 고속도로의 변화
인력 점검/진단의 문제점
• 교통차단 불가
• 포장내부 바닥판 상태조사 불가
• 고소교량의 증가
• 특수교량의 증가
• 안전성, 편의성, 신뢰성 결여 서울영업소 교통량 증가
• 체계적인 DB확보 곤란
관리연장증가
교통차단으로인한 지체 포장내부 손상심화 고소교량의 증가 인천대교 등장
8. 구조물 안전관리 정부정책 강화
1995년 : 『시설물의 안전관리에 관한 특별법』제정
1996년 : 1,2종 시설물 정밀안전진단 관리주체 직접 실시 금지
2002년 : 하자만료전 마지막 정밀점검 관리주체 직접 실시 금지
안전진단결과 사후 평가 제도 도입
2003년 : 진단결과 중대결함 조치기간 설정(3년 이내 완료)
2006년 : 정밀안전진단 주기 강화
(최초진단 : 준공 15년→준공11년, 진단주기 : 10년→5년)
※ 정밀안전진단 시행 현황
년 도 2007년 이전 평균 2007 2008 2009 비 고
개 소 9 116 172 96 2007년 이후 진단대상
금액(억) 7 60 72 55 급격히 증가
9. 유지관리 환경
점검 인원 점검 외주화 비용(억원/년)
구분 적정 과부족 과부족
정원 전면
인원 인원 부분
계 322 129 193 473 282
정밀점검(본부) 110 24 86 156 122
정기점검(지사) 212 105 107 317 160
11. 교량 손상
청계고가 바닥판 보수, 철거 병천2교 펀칭파괴 교대변위에 따른 받침손상
[2000년] (준공 1993년, 2008년 보수) (준공 1983년, 2008년 보강)
TV 보도 받침거동 불량으로른 코핑파손
신문 보도
(청계고가) (준공 1970년, 2008년 보수)
(진부교)
12. 콘크리트 교량 바닥판
교량바닥판 내구수명이 설계수명 보다 짧아
경제적 손실 발생
교량 손상 발생 교량 보수 시행
- 241개소(전체의 3.9%) - 년간 200억원 소요 (’07년)
40년 미달
13. 관리 구조물의 급격한 증가 및 노후화
최근 10년간 관리구조물 2.4배 증가
유지관리비용 4.5배 증가
교면재포장, 교면개량이 전체비용의 57% 차지
전면개량
년도 계 점검,진단 보수,보강
암거확장
8
2001년 275 (100%) 159 (58%) 108 (39%)
(3%)
2011년 1,242 (100%) 178 (14%) 147 (12%) 917 (74%)
증가율
비용 : 4.5배 비용 : 8.5배
(10년대비)
21. 교면상태등급
100
2007년 2008년 합계
상태 관리등급 실제등급
등급 관리 실제 관리 실제 관리 실제 80
등급 등급 등급 등급 등급 등급
A 68 0 60 25 128 25
교량비율(%)
60
B 40 27 18 37 58 64
40
C 19 72 0 16 19 88
20
D 0 20 0 0 0 20
0
E 0 8 0 0 0 8
A B C D E
계 127 127 78 78 205 205 교량상태등급
34. 외관조사와 레이더 조사결과 비교(32개소)
E A B
D
6% 0% 19% 40
19%
C 30
56%
손상율(%)
20
교면조사 상태등급
A B 10
0% 12%
E
C 0
47%
28%
D 1차로 2차로 갓길
13% 외관조사결과 비파괴조사결과
내부조사 상태등급
54. 염소이온 침투저항성능
9000
: 무시할만 함(100이하)
8000
: 매우 낮음(100-1000)
7000 : 낮음(1000-2000)
: 중간(2000-4000)
6000 : 높음(4000이상)
Coulombs
5000
4000
3000
2000
1000
0
A B C D E F G H I
요천3교 유촌교 금호대교 화원IC교 정읍천교 정읍철육교 묘현교 성산교 광지원2교
남원 군위 전주 광주 경안
88선 구마선 호남선 중부선
58. 전체시스템
Data Acquisition System Camera Module 2
GPS Receiver Ultra-Sonic
Disto
& Lighting
Camera Module 1
Data Analysis System
Super Structure (Deck)
Control Room Remote Control
Robot
Robot Carrier Boom
Data Process System
Inspection Result Data
Drawing
66. 육안관찰에 의한 도막상태 평가 기준
도막열화도 평가
등급 상태
(상세 평가)
A ․도장 변색, 표면양호
필요 없음
B ․도장탈락 및 녹발생 면적 2% 미만
․도장탈락 및 녹발생 면적 2~10%
C
․누수 취약부에 국부적부식
․도장탈락 및 녹발생 면적 10~20%
D 평가 시행
․배수구, 신축이음 주변에 심한 부식 발생
․도장탈락 및 녹발생 면적 20%이상
E
․부식깊이가 단면의 20%이상 진행
74. 박스형식 교량은 PSC Box 교량 점검의
고속도로 중/장경간 문제점
교량의 대표적 형식
내부 밀폐공간
고속도로 유지관리 대상교량(2008년 기준)
작업 여건 열악
총 6,663개소 / 연장 780km
많은 시간과 인력이 요구
점검결과의 신뢰성 부족
780km 중 50%가 PSC Box 및 Steel Box
유지관리용 DB 구축 미흡
PSC Box : 280개소 132km
Steel Box : 1227개소 258km
Data 획득 시스템
Data 분석 시스템
Box 교량 무인점검시스템
DB 저장 및 활용
Box 교량 무인점검 로봇
영상획득 시스템 Data
화상 및 영상을 이용한 Box 내부 점검
결과처리 시스템
75. PC
영상 Data 및
현재 상태 Camera
초음파 거리 센 레이저 거리 센
서 서
<카메라의 영상획
카메라 제어 S/W
득>
CCD/IR 카메라 Width_
h
화상획득용 디 ② ③
상부
지털 카메라 슬래브
Camera 회
Height ① 전 ④
α
무선 안테나 °
원격제어기 하부
Tilting 장치 예 Width_
(UMPC) 슬래브
영상/데이터 메인 제어기 l
전송장치 모터 드라이
버 <Box교량 내부의 영상획득>
카메라 제어 영상획득 방식
• USB2.0을 이용한 고속 통신(최대 480Mbps) • 로봇 양 측면에 모터구동이 가능한 Tilting장치와 카메라 장
• PC to Camera : 카메라 제어 명령 전송 착
• Camera to PC : 촬영영상 및 현재 카메라 상태 전송 • Box교량 내부의 측정영역 분할
• 1대 PC로 최대 25대의 카메라 제어 가능 • 사다리꼴 형태의 교량을 FOV 고려하여 적절히 분할
• PC상에서 렌즈의 Zoom In · Out 배율 조절 • Tilting 유닛이 분할된 영역을 회전하며 영상 획득
• PC상에서 조명, 노출, ISO등의 촬영조건 설정
78. 기존조사방법과의 비교
• 육안조사방법
■ 최종 결과물
■ 많은 인력과 시간 소요 ■ 수기에 의한 균열 표시
■ 고압선으로 조사자 위험노출 ■ 주관적 판단
■ 장기적 교통 흐름 방해 ■ 작업 기간 30일 ~ 200일이상
• 터널스캐너
■ 전용 SW를 이용한 신속한 균열처리 ■ 3차원 입체 구조를 이용한 데이터 베이스 유지관리
■ 작업시간 - 10km/1hr ■ 0.1mm 이상 검출 및 정확한 위치 및 길이산출 ■ 공사 완료 시점 초기상태, 보수/보강 전후 상태 검증가능
■ 육안조사 대비 약150배 ■ 이미지 데이터 오버랩에 의한 균열 진행성 여부 판단용이 ■ 터널의 생애주기비용(LCC)중에 따른 경제적 효과 기대
79. 터널스캐너 구성
영상촬영.팬틸트 16분할모티터링
레이져 화각교정
줌.레코딩 컨트롤
프레널 라이트 팬.틸트 컨트롤