 Results 1 to 1 of 1. Popular topic for study. These are discrete approximations to the circle. Elements can be separated by disconnecting the nodes, a process called disassembly in the FEM. Upon disassembly. As can. See, e. Table 1. Extrapolated by Wynn-. The relevant element property: length L i j , can be computed in the generic element independently of the others, a property called local support in the FEM. Finally, the desired property: the polygon perimeter, is obtained by reconnecting n elements and adding up their length; the corresponding steps in the FEM being assembly and solution , respectively.

But comparison with the modern FEM, as covered in Chapters 2—3, shows this to be a stretch. The example does not illustrate the concept of degrees of freedom, conjugate quantities and local-global coordinates. This is at the root of the simulation process described in the next section. A model-based simulation process using FEM involves doing a sequence of steps.

This sequence. These are reviewed next to introduce terminology. The mathematical model top is the source of the simulation process. Discrete model and solution follow from it. The ideal physical system should one go to the trouble of exhibiting it is inessential. The process steps are illustrated in Figure 1. The process centerpiece, from which everything emanates, is the mathematical model. This is often an ordinary or partial differential equation in space and time.

The FEM equations are processed by an equation solver, which delivers a discrete solution or solutions. On the left Figure 1. This may be presented as a realization of the mathematical model; conversely, the mathematical model is said to be an idealization of this system. This step is inessential and may be left out. Indeed FEM discretizations may be constructed without any reference to physics.

The solution error is the amount by which the discrete solution fails to satisfy the discrete equations. This error is relatively unimportant when using computers, and in particular direct linear equation solvers, for the solution step.

More relevant is the discretization error , which is the amount by which the discrete solution fails to satisfy the mathematical model. In the present course such forms will be stated as recipes. The physical system left is the source of the simulation process.

The ideal mathematical model should one go to the trouble of constructing it is inessential. The second way of using FEM is the process illustrated in Figure 1. The centerpiece is now the physical system to be modeled. Accordingly, this sequence is called the Physical FEM. The processes of idealization and discretization are carried out concurrently to produce the discrete model. The solution is computed as before. Just like Figure 1. For others, such as complex engineering systems, it makes no sense.

Indeed FEM discretizations may be constructed and adjusted without reference to mathematical models, simply from experimental measurements. As noted above this error is not generally important. Substitution in the ideal mathematical model in principle provides the discretization error. This is rarely useful in complex engineering systems, however, because there is no reason to expect that the mathematical model exists, and if it does, that it is more physically relevant than the discrete model.

Validation tries to compare the discrete solution against observation by computing the simulation error , which combines modeling and solution errors. One way to adjust the discrete model so that it represents the physics better is called model updating. The discrete model is given free parameters. These are determined by comparing the discrete solution against experiments, as illustrated in Figure 1.

Inasmuch as the minimization conditions are generally nonlinear even if the model is linear the updating process is inherently iterative. Model updating process in the Physical FEM. The foregoing physical and mathematical sequences are not exclusive but complementary. This synergy 8 is one of the reasons behind the power and acceptance of the method.

The Mathematical FEM came later and, among other things, provided the necessary theoretical underpinnings to extend FEM beyond structural analysis. A glance at the schematics of a commercial jet aircraft makes obvious the reasons behind the. There is no differential equation that captures, at a continuum mechanics level, 9 the. There is no reason for despair, however. The time honored divide and conquer strategy, coupled with abstraction , comes to the rescue.

First, separate the structure and view the rest as masses and forces, most of which are time-varying and nondeterministic. Second, consider the aircraft. Take each substructure, and continue to decompose it into components : rings, ribs, spars, cover plates, actuators, etc, continuing through as many levels as necessary.

At that point, stop. The component level discrete equations are obtained from a FEM library based on the mathematical model. The system model is obtained by going through the reverse process: from component equations to substructure equations, and from those. Advance Mathematics Vedic Mathematics Sutra. Lee Willis and Randall R….

Fundamentals of Electrical Circuits by Alexander and Sadiku. Electric Power Distribution Reliability by H. Lee Willis.

To solve the problem, it subdivides a large system into smaller, simpler parts that are called finite elements. The simple equations that model these finite elements are then assembled into a larger system of equations that models the entire problem. FEM then uses variational methods from the calculus of variations to approximate a solution by minimizing an associated error function.

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