Strength of Materials
The study of strength of materials often refers to various methods of calculating the stresses and strains in structural members such as beams, columns, and shafts. The methods employed to predict the response of a structure under loading and its susceptibility to various failure modes takes into account the properties of the materials such as its yield strength, ultimate strength, Young's modulus, and Poisson's ratio in addition the mechanical element's macroscopic properties (geometric properties), such as its length, width, thickness, boundary constraints and abrupt changes in geometry such as holes are considered.
Related Conferences: Engineering Conferences | Structural Engineering Conferences | Construction Engineering Conferences | Civil Engineering Conferences
5th International Conference on Steel and Concrete Structures August 29-30, 2018 4th World Congress and Exhibition on Construction & Steel Structure October 16-18, 2017 Atlanta Georgia, USA 4th International Conference on Advanced Steel Structures November 09-10, 2017 Singapore 3rd Euro Congress on Iron, Steel and Construction Engineering November 16-17, 2017 London, UK 2nd World Conference and Exhibition on Construction and Steel Structure, September 22-24, 2016 Las Vegas,USA World Congress and Exhibition on Construction & Steel Structure November 16-18, 2015 Dubai, UAE Metallurgy for the Non-Metallurgists 2017, May 22-23, 2017 Ottawa, Canada 19th International Conference on Structural Analysis and Structural stability May 14-15,2017 Amsterdam, The Netherlands.
Related Societies and Associations: World Steel Association (world steel), American Institute of Steel Construction (AISC), ASM International Society (American Society for Metals), China Iron & Steel Association, Minerals, Metals & Materials Society.
- Types of loading
- Stress & Strain terms
- General state of stress
- Stress-Strain relations
- Failure Theories
- Loading of beams
- Axial deformation of bars
Related Conference of Strength of Materials
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3rd World Summit on Big Data, Machine Learning and Artificial Intelligence
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