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Recap: Principles of Physical Similarity & Dimensional Analysis | Fluid Mechanics for Mechanical Engineering PDF Download

Recap
In this course you have learnt the following

  • Physical similarities are always sought between the problems of same physics. The complete physical similarity requires geometric similarity, kinematic similarity and dynamic similarity to exist simultaneously
     
  • In geometric similarity, the ratios of the corresponding geometrical dimensions between, the systems remain the same. In kinematic similarity, the ratios of corresponding motions and in dynamic similarity, the ratios of corresponding forces between the systems remain the same
     
  • For prediction of the performance characteristics of actual systems in practice from the results of model scale experiments in laboratories, complete physical similarity has to be achieved between the prototype and the model.
     
  • Dimensional homogeneity of physical quantities implies that the number of dimensionless independent variables are smaller as compared to the number of their dimensional counterparts to describe a physical phenomenon. The dimensionless variables represent the criteria of similarity. Buckingham’s π theorem states that if a physical problem is described by m dimensional variables which can be expressed by n fundamental dimensions, then the number of independent dimensionless variables defining the problem will be m-n. These dimensionless variables are known as π terms. The independent π terms of a physical problem are determined either by Buckingham’s π theorem or by Rayleigh’s indicial method.
The document Recap: Principles of Physical Similarity & Dimensional Analysis | Fluid Mechanics for Mechanical Engineering is a part of the Mechanical Engineering Course Fluid Mechanics for Mechanical Engineering.
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FAQs on Recap: Principles of Physical Similarity & Dimensional Analysis - Fluid Mechanics for Mechanical Engineering

1. What is physical similarity and why is it important in engineering?
Physical similarity refers to the resemblance between two systems or phenomena in terms of their physical characteristics and behavior. In engineering, it is important because it allows engineers to study and analyze the behavior of a scaled-down model or prototype, and then apply the findings to the full-scale system. By ensuring physical similarity, engineers can make accurate predictions and assessments, saving time and resources.
2. What is dimensional analysis and how is it used in engineering?
Dimensional analysis is a mathematical technique used in engineering to understand and analyze the relationships between different physical quantities. It involves identifying the relevant variables, determining their dimensions, and then using mathematical equations to establish the relationships between these variables. Dimensional analysis helps engineers simplify complex problems, validate equations, and identify the key parameters that affect the behavior of a system.
3. How does scaling affect physical similarity in engineering experiments?
Scaling plays a crucial role in maintaining physical similarity in engineering experiments. When scaling down a system, it is important to ensure that the ratios of relevant physical quantities, such as size, shape, and velocity, remain the same. This ensures that the scaled-down model accurately represents the behavior of the full-scale system. By preserving these ratios, engineers can make reliable predictions and draw meaningful conclusions from their experiments.
4. Can physical similarity be achieved without dimensional analysis?
No, physical similarity cannot be achieved without dimensional analysis. Dimensional analysis helps engineers identify and quantify the relevant physical quantities that need to be preserved when scaling down a system. Without dimensional analysis, engineers would not have a systematic and mathematical approach to determine the scaling factors and ensure physical similarity. Dimensional analysis is therefore an essential tool in achieving accurate and meaningful results in engineering experiments.
5. What are the limitations of dimensional analysis in engineering?
While dimensional analysis is a powerful tool in engineering, it does have its limitations. One limitation is that it cannot account for complex interactions and phenomena that involve multiple variables. Additionally, dimensional analysis assumes linear relationships between variables, which may not always be accurate in real-world situations. Furthermore, dimensional analysis cannot account for certain non-dimensional parameters, such as surface roughness or material properties. Despite these limitations, dimensional analysis remains a valuable tool for simplifying and understanding complex engineering problems.
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