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Statistical energy analysis (SEA) is a modeling procedure which uses energy flow relationships for the theoretical estimation of the sound transmission through structures in resonant motion.
In particular, an approach to achieve topological entity correspondence across collaborative sites during modeling procedure, which is critical to guarantee the correctness and consistency of collaborative modeling result, is proposed.
The specimens are also simulated numerically using a modeling procedure which can include a semi-elliptical surface crack located at any position and any length along its brace-chord intersection within the joint finite element model.
This paper proposes a systematic modeling procedure, which enables the description of the most important experimental settings and biological effects in terms of stoichiometry, kinetics and metabolic regulation.
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We used these methods because they produce interpretable models, as opposed to most other nonlinear modeling procedures, which give us models that are hard to interpret (so-called black box models).
Our main emphasis is on presenting a practical LPV design procedure which covers plant modeling, controller synthesis and actual implementation for an electromechanical positioning device, an advanced wafer-scanner.
A combination of Pseudo Rigid Body Model (PRBM) and Finite Element Analysis (FEA) technique has proven to improve the design efficiency by providing the essential guideline to expedite the prototyping procedure which effectively reduces the cost and modeling time.
This modeling approach determines model parameters that describe a specific electrode structure through an optimization procedure which utilizes data from carefully planned experimental studies.
Similar to the CODEm models, the modeling procedure for LRI and diarrhea etiology models used hierarchal spatial effects by which country models were informed by data from the country, region, and super-region only.
The modeling procedure for the ARIMA models, which is based on the Box Jenkins methodology, comprises three iterative steps: model identification, parameter estimation, and diagnostic checking.
In this paper, a high-fidelity flexible AHSV dynamic modeling procedure is proposed at first, which consists of three main parts: i) panel method based aerodynamic modeling; ii) scramjet modeling; iii) finite-element-method (FEM) based aeroelastic modeling.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com