State of the Art Distributed Parallel Computational Techniques in Industrial Finite Element Analysis

Author(s):  
L. Komzsik
2011 ◽  
Author(s):  
David Fornaro

Finite Element Analysis (FEA) is mature technology that has been in use for several decades as a tool to optimize structures for a wide variety of applications. Its application to composite structures is not new, however the technology for modeling and analyzing the behavior of composite structures continues to evolve on several fronts. This paper provides a review of the current state-of-the-art with regard to composites FEA, with a particular emphasis on applications to yacht structures. Topics covered are divided into three categories: Pre-processing; Postprocessing; and Non-linear Solutions. Pre-processing topics include meshing, ply properties, laminate definitions, element orientations, global ply tracking and load case development. Post-processing topics include principal stresses, failure indices and strength ratios. Nonlinear solution topics include progressive ply failure. Examples are included to highlight the application of advanced finite element analysis methodologies to the optimization of composite yacht structures.


2017 ◽  
Vol 24 (3) ◽  
pp. 615-621 ◽  
Author(s):  
Ioana T. Nistea ◽  
Simon G. Alcock ◽  
Paw Kristiansen ◽  
Adam Young

Actively bent X-ray mirrors are important components of many synchrotron and X-ray free-electron laser beamlines. A high-quality optical surface and good bending performance are essential to ensure that the X-ray beam is accurately focused. Two elliptically bent X-ray mirror systems from FMB Oxford were characterized in the optical metrology laboratory at Diamond Light Source. A comparison of Diamond-NOM slope profilometry and finite-element analysis is presented to investigate how the 900 mm-long mirrors sag under gravity, and how this deformation can be adequately compensated using a single, spring-loaded compensator. It is shown that two independent mechanical actuators can accurately bend the trapezoidal substrates to a range of elliptical profiles. State-of-the-art residual slope errors of <200 nrad r.m.s. are achieved over the entire elliptical bending range. High levels of bending repeatability (ΔR/R = 0.085% and 0.156% r.m.s. for the two bending directions) and stability over 24 h (ΔR/R = 0.07% r.m.s.) provide reliable beamline performance.


Author(s):  
Siva C. Chaduvula ◽  
Mikhail J. Atallah ◽  
Jitesh H. Panchal

Designers need a way to overcome information-related risks, including information leakage and misuse by their own collaborators during collaborative product realization. Existing cryptographic techniques aimed at overcoming these information-related risks are computationally expensive and impractical even for moderate problem sizes, and legal approaches such as nondisclosure agreements are not effective. The computational practicality problem is particularly pronounced for computational techniques, such as the finite element analysis (FEA). In this paper, we propose a technique that enables designers to perform simulations, such as FEA computations, without the need for revealing their information to anyone, including their design collaborators. We present a new approach, the secure finite element analysis approach, which enables designers to perform FEA without having to reveal structural/material information to their counterparts even though the computed answer depends on all the collaborators' confidential information. We build secure finite element analysis (sFEA) using computationally efficient protocols implementing a secure codesign (SCD) framework. One of our findings is that the direct implementation of using SCD framework (termed as naïve sFEA) suffers from lack of scalability. To overcome these limitations, we propose hybrid sFEA that implements performance improvement strategies. We document and discuss the experiments we conducted to determine the computational overhead imposed by both naïve and hybrid sFEA. The results indicate that the computational burden imposed by hybrid sFEA makes it challenging for large-scale FEA—our scheme significantly increases the problem sizes that can be handled when compared to implementations using previous algorithms and protocols, but large enough problem sizes will swamp our scheme as well (in some sense this is unavoidable because of the cubic nature of the FEA time complexity).


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