L
Lars Bittrich
Researcher at Leibniz Institute for Neurobiology
Publications - 20
Citations - 393
Lars Bittrich is an academic researcher from Leibniz Institute for Neurobiology. The author has contributed to research in topics: Tailored fiber placement & Fiber. The author has an hindex of 9, co-authored 18 publications receiving 241 citations.
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Journal ArticleDOI
Uncertain natural frequency analysis of composite plates including effect of noise – A polynomial neural network approach
Sudip Dey,S. Naskar,Tanmoy Mukhopadhyay,Uwe Gohs,Axel Spickenheuer,Lars Bittrich,Srinivas Sriramula,Sondipon Adhikari,Gert Heinrich,Gert Heinrich +9 more
TL;DR: The effect of noise on a PNN based uncertainty quantification algorithm is explored and the convergence of the proposed algorithm for stochastic natural frequency analysis of composite plates is verified and validated with original finite element method (FEM).
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Improving the open-hole tension characteristics with variable-axial composite laminates: Optimization, progressive damage modeling and experimental observations
TL;DR: In this article, a numerical and experimental investigation on unnotched and open-hole tensile characteristics of fiber-steered variable-axial composite laminates was conducted, where the fiber path was obtained from an optimization framework considering manufacturing characteristics of the Tailored Fiber Placement (TFP) process.
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Buckling optimization of composite cylinders for axial compression: A design methodology considering a variable-axial fiber layout
TL;DR: The current work on optimization of the linear buckling behavior of variable-axial (VA) shells shows both the potential of using VA-configurations to exploit their tailoring ability and the capabilities of the current optimization framework to improve and optimize the behavior of VA structures.
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Cross-section optimization of topologically-optimized variable-axial anisotropic composite structures
TL;DR: In this paper, a methodology to optimize an anisotropic composite structure, comprising in performing cross-section optimization of a topologically optimized structure through an evolutionary optimization using a GA, is presented.
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High-throughput analyses of microplastic samples using fourier transform infrared and raman spectrometry
Josef Brandt,Lars Bittrich,Franziska Fischer,Elisavet Kanaki,Alexander S. Tagg,Robin Lenz,Matthias Labrenz,Elke Brandes,Dieter Fischer,Klaus-Jochen Eichhorn +9 more
TL;DR: The software GEPARD (Gepard Enabled PARticle Detection) allows for acquiring an optical image, then detects particles and uses this information to steer the spectroscopic measurement, which ultimately results in a multitude of possibilities for efficiently reviewing, correcting, and reporting all obtained results.