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(Geospatial) computing in civil engineering

(Geospatial) computing in civil engineering. Ari Jolma 12.4.2007. Materials. Miles & Ho 1999: Applications and Issues of GIS as Tool for Civil Engineering Modeling. J.Comp.Civ.Eng. Volume 13, Issue 3, pp. 144-152

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(Geospatial) computing in civil engineering

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  1. (Geospatial) computing in civil engineering Ari Jolma 12.4.2007

  2. Materials • Miles & Ho 1999: Applications and Issues of GIS as Tool for Civil Engineering Modeling. J.Comp.Civ.Eng. Volume 13, Issue 3, pp. 144-152 • Venigalla & Casey 2006: Innovations in Geographic Information Systems Applications for Civil Engineering. J.Comp.Civ.Eng.Volume 20, Issue 6, pp. 375-376 • Wikipedia pages: GIS, CAD, Building Information Modeling, ... • Peachavanish et al 2006: An ontological engineering approach for integrating CAD and GISin support of infrastructure management. Advanced Engineering Informatics 20 (2006) 71–88

  3. Civil engineering • a broad field of engineering dealing with the planning, construction, and maintenance of fixed structures, or public works, as they are related to earth, water, or civilization and their processes • Fundamentally, we as civil engineers—regardless of emphasis— share one characteristic in that we are all problem solvers.

  4. Problem solving cycle • Definition • Structuring • Defining possible solutions • Evaluation of solutions • Decision making • Implementation Modeling Design Simulation, optimization

  5. What are problems? • G Polya: How to solve it (from M Jackson: Software requirements and specifications) • ideas for solving mathematical problems • from ancient Greeks • the first people in Western world to think systematically about how to solve problems • (1) problems to prove, (2) problems to find • Each problem has principal parts and a solution task • (1): parts are hypothesis and conclusion • (2): parts are unknown, the data, and the condition • Fitting a problem into a particular frame is a primary activity in understanding any problem

  6. Domain characteristics • The characteristics of the (CE) context of the problem • Characteristics of the data and information that the CE professional has to manage computationally • Tangible vs intangible • Dynamic vs static • Spatial vs aspatial • ...

  7. Design cycle • Conceive (innovate) • Design • Develop • Build / manufacture • Operate / maintain Model Drawings

  8. A design is a solution • A CE design may be • a structure • a plan • which may include also structures • a management procedure • an operational procedure

  9. Computing • Manage acquired data and information • that is from outside sources • that is made within the project / organization • Produce required/useful data and information products • to match generic methods • to match specific needs of people

  10. GIS • Geospatial software • Varying origins/foci • Cartography • One or more methods • Resource management • Management of geospatial data

  11. Brief history of GIS 1 • 60’s • Tomlinson: CGIS • land-use management, resource monitoring • Laboratory for Computer Graphics and Spatial Analysis at the Harvard Graduate School of Design • 70’s • Commercial mapping applications sold by vendors • 80’s • Personal computer: interaction, new application areas

  12. Brief history of GIS 2 • 90’s • Tomlin: cartographic modeling • GIS and hydrological modeling • Increasing commercialization • 2000 • Web, spatial data infrastructures

  13. GIS and CE 1 • Benefits • Capture, store, and manage geospatially referenced data in common formats • Visualization capabilities for information and verification • Common methods to compute information from Digital Elevation Models (DEM)

  14. GIS and CE 2 • Problem areas • The mismatch between CE specifics and generic GIS capabilities • The common GIS data model is generic and simple -> difficulties in applying CE specific data models • Linking of CE (simulation) models with GIS that lack the concept of temporal data

  15. The GIS data model • Thematic layers • Features sharing a similar set of attributes • feature = spatial object + record of attributes • Common spatial representations • points, polylines, polygons, rasters • Topological relationships • it is common to not to specify these explicitly

  16. A CE data model (an example: water management plan) • Hydro system description and operation • objectives: flood control, storage, ecology, ... • Monitoring system and operation • Loads and associated permits and requirements etc. • Other actions and measures

  17. CAD • A computer-based design tool • Commonly used, e.g., in Architecture, Engineering, and Construction • for creating plans and drawings • 2D drafting / 3D solid modeling

  18. The CAD data model • A mathematical model for describing arbitrary (smooth) curves and surfaces • Boundary representation • topology (faces, edges, vertices) + geometry • compare to GIS data model! • NURBS • non uniform rational B-spline

  19. CE and CAD 1 • Benefits • Create engineering drawings and visualizations • Simulation of designs • Output of design data to manufacturing utilities • Maintain libraries of parts and assemblies

  20. CE and CAD 2 • Problem areas • (If there is a) focus on drawings and not in the data model • Interoperability problems, especially caused by proprietary file formats

  21. GML, LandXML, IFC, ... • A shared data model is a key to interoperability that is an important requirement as CE projects are often large and involve many participants • Data and information exchange • between organizations • between planning tools and equipment • Based on • XML (Extensible mark-up language) • Object-orientation • Ontologies

  22. Data in an information system • Organized structure (data model) • Efficient update and querying • also complex updates and queries • standards-based update and querying • employs advanced algorithms! • Remove redundancy • within one data base • within organization • A single shared/forced structure • Management objectives • security, integrity, ... • Support discovery

  23. State-of the art solutions • RDBMS • relational database management systems • data is in tables, tables have columns (fields) and rows (tuples), columns have a field name, field data type, ... • columns between tables may be linked • SQL • structured query language • OODBMS • Object-oriented database management systems • data is stored as objects, objects have a class, a class has attributes and methods, attributes have names and data types • classes may have various types of relationships

  24. Data in messages • Messages are a means of communication • In computing • human<->human (not directly, via a computer system) • human->program • program->human • program<->program • Semantics • Syntax • construction of complex signs from simpler signs • Pragmatics • how signs are interpreted in particular circumstances or context

  25. State-of-the-art computational solutions • Derivatives of SGML • standard generalized markup language • HTML, XML • Typesetting and document formats • LaTeX, .doc, RTF, ... • All other file formats • Shapefile, DGW • All program to program protocols • ODBC (open database connectivity), ... • Everything else • SQL, ...

  26. Digging still deeper... • Descriptions • raw material for databases • raw material for message structures • raw material for problem solving • raw material for program development • The suitability of a description is judged by the purpose • Descriptions are organized thoughts • the level of organization may vary • Descriptions are not specifications

  27. State-of-the-art solutions • Predicate logic • extension of propositional logic • logic with generalized facts • Jackson: designations, definitions, refutable descriptions, rough sketches • Ontologies • a data model that represents a set of concepts within a domain and the relationships between those concepts • UML • a standardized specification language for object modeling • structure, behavior, and interaction diagrams • really a specification language

  28. The basic solution of/for a poor man 1 • There are objects, and they are realisations of classes • An example of a class: ”a wetland” • Classes have attributes and characteristics • For exampe ”average depth” • For example ”a wetland designed primarily for birds”, ”a wetland for designed primarily for water quality improvement” • Classes have relationships • For example ”a wetland is on a property”, ”a wetland has a catchment” • When some description is an attribute and when it is a relationship is a design choice

  29. The basic solution of/for a poor man 2 • There are processes • For example ”a wetland is planned and built and then it is in operation”

  30. Ontologies (knowledge engineering) • Classes (concepts) • a set of objects • compare to an idea of an object • a subset: subsume, inherit, ”is a kind of” • e.g. vehicle -> car • Attributes of classes • name, value • Relationships between classes • inheritance, ”a part of”, ...

  31. Object-orientation (software development) • A program is a collection of cooperating objects • cooperation is ideally based on communication with messages • Classes, attributes, methods • Inheritance, encapsulation, abstraction, polymorphism • The methods constitute the primary interface of an object, its data is encapsulated within the object. Methods may be inherited from superclasses and the behavior they awake may be different, giving raise to polymorphism.

  32. XML (information system design) • A tree-like stucture of nodes • each node has possibly a parent, children, siblings (the siblings form a list) • a node consists of contents that is surrounded by begin and end tags, in the begin tag there may be named attributes with values • <tag attr1=”value”>contents</tag>

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