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Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

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Published on: November 24, 2021

Bringing simulation to engineers in the field: a Web 2.0 approach.

Robert Haines1, Kashif Khan, John Brooke

  • 1Research Computing Services, Devonshire House, Kilburn Building, University of Manchester, Manchester M13 9PL, UK. rhaines@manchester.ac.uk

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|June 3, 2009
PubMed
Summary

Field engineers can now optimize water distribution networks using new mobile decision support tools (DSTs). These tools provide real-time hydraulic and water quality predictions, improving operational efficiency.

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Area of Science:

  • Engineering
  • Environmental Science
  • Computer Science

Background:

  • Water distribution systems require complex operational decisions impacting hydraulics and water quality.
  • Interconnected pipe networks mean local decisions have widespread effects.
  • Field engineers need effective tools for optimizing network management.

Purpose of the Study:

  • To develop predictive decision support tools (DSTs) for field engineers.
  • To enable DSTs to run on lightweight mobile devices.
  • To integrate real-time data and simulation results for enhanced decision-making.

Main Methods:

  • Utilized Software as a Service (SaaS) architecture for mobile deployment.
  • Implemented a Representational State Transfer (REST) architectural style.
  • Integrated static GIS data with dynamic network information and simulation predictions.

Main Results:

  • Successfully created DSTs deployable on mobile devices.
  • The system displays both static geographical data and dynamic network states.
  • Predictions of network conditions are available by invoking remote simulations.

Conclusions:

  • Mobile DSTs enhance field engineers' ability to optimize water distribution networks.
  • SaaS and RESTful architecture facilitate efficient deployment and data integration.
  • Predictive capabilities improve operational decision-making for hydraulic and water quality management.