Please note! Course description is confirmed for two academic years, 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: 20.04.2022 - 01.06.2022

Teacher in charge (valid for whole curriculum period):

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

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

anna.mikola@aalto.fi

CEFR level (valid for whole curriculum period):

Language of instruction and studies (applies in this implementation):

Teaching language: English. Languages of study attainment: English

CONTENT, ASSESSMENT AND WORKLOAD

Content
  • valid for whole curriculum period:

    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 for whole curriculum period:

    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 for whole curriculum period:

    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

Substitutes for Courses
Prerequisites
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

Further Information
  • valid for whole curriculum period:

    Teaching Language : English

    Teaching Period : 2022-2023 Spring V
    2023-2024 Spring V

    Enrollment :

    Registration for courses will take place on Sisu (sisu.aalto.fi). A limited number of students will be accepted to the course, with preference given to our own Master's Programme students. Other students may be selected based on Motivation Letter and/or other criteria. The course may not be organized if fewer than 5 students register to the course.

  • applies in this implementation

    The course will be organized on site. Some recordings from last year's lectures will be made available.

Details on the schedule
  • applies in this implementation

    The first lecture of the course will be Friday April 22nd at 8:30 (note no lecture yet April 20th!)

    No lecture on Friday May 27th.

    One additional teaching session Monday May 30th at 13