Applications Of The Numerical Methods In Mechanical Engineering Experimental Studies

E. Oanta, A. Raicu, B. Menabil

MODTECH INTERNATIONAL CONFERENCE - MODERN TECHNOLOGIES IN INDUSTRIAL ENGINEERING VIII(2020)

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摘要
Tremendous advances in computer science led to important progresses in science and technology. The significant feature of a computer, to rapidly and accurately perform calculi, was used for several purposes; the most important influence regarded the applied mathematics concepts where it was lifted the constraint concerning the necessary volume of calculi to be minimal when solving a complex problem. Conceptual advances also influenced the experimental mechanics domain, where numerical methods or numerical solving principles were applied to solve specific problems. The paper presents three original applications of the numerical methods in experimental mechanics. Reusability of the experimental projects' results saves time and effort. For relevancy purposes many experimental studies' results are expressed as diagrams. In the first example the approximation theory is used to solve interpolation problems. The output of the data processor consists of the spline function coefficients stored as CSV files or expressed as automatically generated computer codes, ready to be included in upper level applications. The second example is a particular study included in a hybrid model of an internal combustion engine, which outputs the states of strains and stresses in its cylinder block in running conditions. The particular study presents a method to compute the linear thermal expansion coefficient in the points where the temperatures are measured and to compute the temperatures in the inaccessible points, using the values of the previously computed coefficient. The experiment used strain gage rosettes bonded in 10 measurement points. The last original example presents a method to compute the analytical functions of the isostatics using as input data the pattern of isoclinic fringes of a photoelastic model or coating. Deep integration of the analytical, numerical and experimental studies is an important target in hybrid modelling.
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