Please note! Course description is confirmed for two academic years (1.8.2018-31.7.2020), which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.

LEARNING OUTCOMES

Upon completion, the student should be able to:

  • Understand the overall process train and the influence of the selected dimensioning on performance, including the characterization of the influent fractions as well as the identification of the process dynamics and of the main disturbances for the process operation [knowledge]
  • Understand the modelling and control techniques: state-of-the-art models, basic controllers and their practical application to full scale processes [knowledge]
  • Recognise the instrumentation available in the plants: actuators, on-line sensors/analyzers, structure of the automation system and their representation on the piping and instrumentation diagram [knowledge]
  • Optimise plant operation in terms of resources consumption and effluent quality improvement [knowledge/skill]
  • Analyse and understand the on-line and off-line data available at the treatment plants [skill]
  • Design the automation system for the treatment plants by means of simulator software [skill]

Credits: 5

Schedule: 21.04.2021 - 04.06.2021

Teacher in charge (valid 01.08.2020-31.07.2022): Anna Mikola, Anna Mikola

Teacher in charge (applies in this implementation): Anna Mikola, Anna Mikola

Contact information for the course (applies in this implementation):

CEFR level (applies in this implementation):

Language of instruction and studies (valid 01.08.2020-31.07.2022):

Teaching language: English

Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • Valid 01.08.2020-31.07.2022:

    The course is useful for students interested in the operation, design and optimization of municipal and industrial water and wastewater treatment plants. Mathematical models of water and wastewater treatment: first principle models and data-derived models, calibration techniques; Basics of data analysis: data visualization, time series, outliers, missing data, time distribution; On-line sensors/analysers: characteristics, measurement principles; Off-line measurements: main parameters to be measured in the lab and related reference methods; Control algorithms: feedback, feedforward, cascade and predictive control; P&I symbols; Simulation software.

Assessment Methods and Criteria
  • Valid 01.08.2020-31.07.2022:

    Lectures, weekly exercises and individual simulation project. Assessment of the course is based on the exercises, exams and the simulation project. Relative weights between the different components are given in the beginning of the course.

Workload
  • Valid 01.08.2020-31.07.2022:

    Contact hours

    • Lectures 20 h
    • Exercise sessions & workshops 20 h
    • Project presentations 4 h
    • Exams 2 h

    Independent work

    • Weekly exercises 25 h
    • Reading materials 34 h
    • Project assignment 30 h

DETAILS

Study Material
  • Valid 01.08.2020-31.07.2022:

    Study material is announced in the first lecture and in the course home page in MyCourses.

Prerequisites
  • Valid 01.08.2020-31.07.2022:

    WAT-E2120 Physical & chemical treatment of water and waste and CHEM-E0190 Biological treatment of water and waste, or equivalent knowledge.

SDG: Sustainable Development Goals

    6 Clean Water and Sanitation

    7 Affordable and Clean Energy

    9 Industry, Innovation and Infrastructure

    11 Sustainable Cities and Communities

    12 Responsible Production and Consumption

    13 Climate Action

    14 Life Below Water

FURTHER INFORMATION

Description

Registration and further information