Finite Element Analysis (FEA) is a great tool for biologists, palaeontologists, doctors, veterinarians, and other biosciences specialities in which researchers face questions about biomechanics of living and extinct organisms. Elements... more
Finite Element Analysis (FEA) is a great tool for biologists, palaeontologists, doctors, veterinarians, and other biosciences specialities in which researchers face questions about biomechanics of living and extinct organisms. Elements like bone, arthropod exoskeleton, mollusc shells, or the stems and leaves of plants can be analysed using this technique. FEA is a non-invasive modelling technique, based on the principle of dividing a system into a finite number of discrete elements where the equations are applied. Although static and dynamic analysis can be solved using FEA, in this course only static analysis will be covered.
In this course, there will be an introduction to the Finite Element in order to model biological structures and understand how they worked. It will cover all the steps involved in FEA (for static analysis) except the creation or reconstruction of the model, which will be covered in the previous course 3D Model Generation in Biosciences. That is how to define the material properties of biological structures, the use of a consistent Mesh Generation Methods, the proper definition of biomechanical boundary conditions and finally, how understand and analyse the results obtained in a computational simulation.
After the theoretical introduction we will build and analyse 2D and 3D finite element models of skeletal elements and deepen on the methods and software’s required to perform FEA. Key questions as mesh size, boundary conditions, applied forces, scaling and numerical singularities will be thoroughly addressed. The last day attendees will have opportunity for trying to analyse by themselves their own data or other examples with the help of both instructors.
In this course, there will be an introduction to the Finite Element in order to model biological structures and understand how they worked. It will cover all the steps involved in FEA (for static analysis) except the creation or reconstruction of the model, which will be covered in the previous course 3D Model Generation in Biosciences. That is how to define the material properties of biological structures, the use of a consistent Mesh Generation Methods, the proper definition of biomechanical boundary conditions and finally, how understand and analyse the results obtained in a computational simulation.
After the theoretical introduction we will build and analyse 2D and 3D finite element models of skeletal elements and deepen on the methods and software’s required to perform FEA. Key questions as mesh size, boundary conditions, applied forces, scaling and numerical singularities will be thoroughly addressed. The last day attendees will have opportunity for trying to analyse by themselves their own data or other examples with the help of both instructors.
Research Interests:
This course is addressed to bioscience researchers and technicians who routinely work with complex biological structures and need to analyze them in three dimensions, and who digitise their samples for any reason, such as digital... more
This course is addressed to bioscience researchers and technicians who routinely work with complex biological structures and need to analyze them in three dimensions, and who digitise their samples for any reason, such as digital preservation or retrospective analysis of a previously scanned sample. You may arrive at this course from a diversity of different backgrounds (laser, photogrammetry, CT, etc.) and use it as a basis to move on to further analyses.
The course is designed to enable participants to arrive at a three-dimensional image solution by concentrating on not just one methodology or technology but by considering the range that is available. This range is now quite extensive, including such things as 3D imaging, 3D printing, image processing, image filtering, laser imaging, photogrammetry, computed tomography (CT), and more. Images resulting from one methodology or technology should not be the end of the road but a starting point from which you can gain much more by performing other analyses, applying other methodologies or using different technologies, even with existing data. It is easy to become satisfied by one methodology that you know well, yet there may be much more you can achieve. And there are other advantages. Not only will your final result be more precise and accurate, you also have the potential of finding a more efficient approach than the one originally chosen, even though a multi-solution approach might seem inefficient at the outset.
The goal of this course is to explain how you can work with a range of technologies with the aim of obtaining a 3D model from different sources. By the end of the course participants should be able to work in an autonomous way to develop high quality digitalizations of samples with the most commonly used techniques and also be able to edit and manipulate the digital models that are produced.
The course is designed to enable participants to arrive at a three-dimensional image solution by concentrating on not just one methodology or technology but by considering the range that is available. This range is now quite extensive, including such things as 3D imaging, 3D printing, image processing, image filtering, laser imaging, photogrammetry, computed tomography (CT), and more. Images resulting from one methodology or technology should not be the end of the road but a starting point from which you can gain much more by performing other analyses, applying other methodologies or using different technologies, even with existing data. It is easy to become satisfied by one methodology that you know well, yet there may be much more you can achieve. And there are other advantages. Not only will your final result be more precise and accurate, you also have the potential of finding a more efficient approach than the one originally chosen, even though a multi-solution approach might seem inefficient at the outset.
The goal of this course is to explain how you can work with a range of technologies with the aim of obtaining a 3D model from different sources. By the end of the course participants should be able to work in an autonomous way to develop high quality digitalizations of samples with the most commonly used techniques and also be able to edit and manipulate the digital models that are produced.