MABY4400 Structural Analysis and Design Course description

The course gives the students the necessary fundamental understanding of the principles used in the design of large complex structures. An important goal is to give knowledge and experience of how to use the finite element method (FEM) correctly in design calculations, with emphasis on non-linearities in structural engineering. In particular, the students will gain a deeper understanding of the non-linear behaviour of structural materials, and achieve both theoretical and practical insight. The course covers theories of elastic and elasto-plastic materials, introduces solution methods in non-linear finite element analysis, and contains the following topics: Classification of nonlinearities (geometrical, material and boundary conditions). Introduction of continuum mechanics/Theory of elasticity: Stresses and equilibrium, strains and compatibility, material law. Strain- and stress measures. Plasticity theory (yield criteria, flow law, hardening, effects of strain rate and temperature). Mathematical models for elastic and elastoplastic materials. Solution methods in nonlinear FEA. Constraints and contact. Geometric nonlinear FEA. 

The teaching will consist of a combination of:

• Lectures & discussions
• Independent studies including video recordings and online exercises
• Coursework assignment
• Short laboratory exercises
• Practical use of tools and software

Admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge:

The student:

• has advanced knowledge about the simulation and analysis of concrete and metal structures.
• has knowledge about basic theory of elasticity and plasticity.
• has knowledge about material models used in FEA.
• has in-depth knowledge of the non-linear behaviour of structural materials.
• understands how to quantify uncertainties in load and material descriptions.

Skills:

The student is capable of:

• modelling and simulating components and structures with non-linear behaviour, and evaluating the results.
• selecting appropriate analysis and material models, and carrying out structural analyses for determining internal forces and moments, stresses, strains, and displacements with a satisfactory degree of accuracy.
• choosing appropriate material models and material properties to solve the problem in question.
• determining the parameters of mathematical models for materials from laboratory experiments or from the literature.
• describing the difference between linear and non-linear structural analysis.
• explaining the theoretical basis for linear and non-linear geometry and material behaviour.

General competence:

The student is capable of:

• using FEM software in practical structural analyses.
• assessing approaches to and limitations in linear and non-linear analyses.
• using scholarly reports and articles to gain an overview of the latest developments in research in the field of non-linear analysis of structures.

The teaching consists of lectures, exercises (written assignments or computer-based assignments) and project work. The exercises are linked to the topics taught. The project assignment is to be carried out in groups of 1-3 students and concerns FE-analysis of a structure. The report forms part of the assessment for the grade awarded for the course. Detailed guidelines for the project assignment will be published in Canvas.

Four individual assignments, three of which must be approved before the student can take the exam. Students who fail to meet the coursework requirements can be given up to one re-submission opportunity before the exam.

Type of assessment:  

1) Individual written exam under supervision (three hours), weighted 60 %.

2) Project report prepared in groups of 1-3 students, approx. 20-30 pages, weighted 40 %.

The exam can be appealed.

All assessment parts must be awarded a pass grade (E or better) in order for the student to pass the course. In the event of a resit or rescheduled exam, oral examination may be used instead. If oral exams are used for resit and rescheduled exams, the result cannot be appealed.

Assessment parts:

1) Written Exam: All printed and written aids and a calculator that cannot be used to communicate with others.

2) Project Report: All aids are permitted.

Grade scale A-F. 

This course will provide an advanced understanding of bioprocesses by which water pollutants can be removed. The course will additionally convey an overview and a deeper understanding of urban water resource recovery in the context of circular economy. It will provide comprehensive knowledge about the behavior of contaminants and the processes for their conversion/removal in engineered water systems. The main focus will be on systems analysis and process engineering, as well as on classification and risk assessment of pollutants and water-borne resources. 

The students will make use of software such as Matlab, Python, West, Sumo or similar tools.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence.

Knowledge

The student has

• good understanding of the water pollutant and resource classifications in water resource systems;
• advanced knowledge of biological, chemical and physical-chemical reactor operations to remove water pollutants;
• advanced comprehension of bioprocess reactor operations in water resource recovery facilities;
• advanced knowledge of design, optimization and control of water process systems;
• good understanding of data analysis in water process systems.

Skills:

The student

• can use pollutants classifications, describe their impact and fate in the water environment;
• can conceptualize complex bioprocesses to separate and recover urban water resources;
• is capable to apply systems analysis methods to water resource recovery processes;
• is capable to apply process knowledge to build advanced computer simulation models to critically evaluate and select from alternative technologies;
• has hands-on computational experience to deal with novel scenarios, solve problems and make engineering decisions in the face of incomplete or uncertain information;
• has hands-on expertise to appraise solutions for eliminating water environmental problems.

General competence:  

The student

• has deep insight into smart water process engineering with links to global sustainable development;
• is able to infer mathematical description of advanced unit operations and to create advanced computer simulation models of whole smart water resource engineered systems;
• Is able to solve advanced smart water process design and optimization problems using information processing tools.