3 Search Results for "Klein, Christoph"

Document
DOI: 10.4230/OASIcs.iPMVM.2020.16
Physical Modeling of Process Forces in Grinding

Authors: Praveen Sridhar, Daniel Mannherz, Raphael Bilz, Kristin M. de Payrebrune, Mahesh R.G. Prasad, and Juan Manuel Rodríguez Prieto

Published in: OASIcs, Volume 89, 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)

Abstract
This paper deals with material removal mechanisms in grinding by considering single grit-workpiece interactions. Individual investigations were performed both experimentally and using finite element simulations. Firstly, a comparison between the Johnson-Cooke material model and a Crystal Plasticity finite element method was performed with the help of micro-indentation experiments. Here the research question was answered if an anisotropic material model better describe the grinding process and process forces compared to an isotropic material model. Secondly, four discretization approaches were employed: pure Lagrangian (LAG), Arbitrary Lagrange Eulerian (ALE), Particle Finite Element Method (PFEM), and Smooth Particle Hydrodynamics (SPH), to simulate a micro-cutting operation of A2024 T351 aluminium. This study aims to compare the conventional approaches (LAG and ALE) to newer approaches (PFEM and SPH). The orthogonal cutting models were benchmarked against a micro-cutting experiment presented in literature, by comparing the obtained cutting and passive forces. The study was then extended to negative rake angles to study the effect on the discretization approaches for grinding. Thirdly, scratch experiments were investigated for a brittle material sodalime glass and A2024 T351 aluminium. Effects of the linear speed of the device, depth of cut, and conical tool angle were analyzed and tendencies are built. Finally, a realistic simulation of the manufacturing process of a grinding wheel was developed, starting with the raw material, compression, sintering, and dressing until the final grinding surface. As a result of the simulations, virtual grinding wheel topographies can be visualized and analyzed with regard to the output variables from grinding wheels such as bonding strength and static grain count. The individual research studies help in understanding the material removal mechanisms in a single grit scratch process as well as in the understanding of the overall grinding wheel topography. This in turn helps in the developing an overall physical force model for scratching/grinding to predict mechanical output parameters and hence reduce the need for experimentation.
Cite as

Praveen Sridhar, Daniel Mannherz, Raphael Bilz, Kristin M. de Payrebrune, Mahesh R.G. Prasad, and Juan Manuel Rodríguez Prieto. Physical Modeling of Process Forces in Grinding. In 2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020). Open Access Series in Informatics (OASIcs), Volume 89, pp. 16:1-16:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{sridhar_et_al:OASIcs.iPMVM.2020.16,
  author =	{Sridhar, Praveen and Mannherz, Daniel and Bilz, Raphael and de Payrebrune, Kristin M. and Prasad, Mahesh R.G. and Prieto, Juan Manuel Rodr{\'\i}guez},
  title =	{{Physical Modeling of Process Forces in Grinding}},
  booktitle =	{2nd International Conference of the DFG International Research Training Group 2057 – Physical Modeling for Virtual Manufacturing (iPMVM 2020)},
  pages =	{16:1--16:20},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-183-2},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{89},
  editor =	{Garth, Christoph and Aurich, Jan C. and Linke, Barbara and M\"{u}ller, Ralf and Ravani, Bahram and Weber, Gunther H. and Kirsch, Benjamin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.iPMVM.2020.16},
  URN =		{urn:nbn:de:0030-drops-137651},
  doi =		{10.4230/OASIcs.iPMVM.2020.16},
  annote =	{Keywords: grinding, single grit approach, finite element method, smooth particle hydrodynamics, particle finite element method, scratch experiments, virtual grinding wheel model}
}
Document
DOI: 10.4230/LIPIcs.ICALP.2018.49
Faster Algorithms for Integer Programs with Block Structure

Authors: Friedrich Eisenbrand, Christoph Hunkenschröder, and Kim-Manuel Klein

Published in: LIPIcs, Volume 107, 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)

Abstract
We consider integer programming problems max {c^Tx : A x = b, l <= x <= u, x in Z^{nt}} where A has a (recursive) block-structure generalizing n-fold integer programs which recently received considerable attention in the literature. An n-fold IP is an integer program where A consists of n repetitions of submatrices A in Z^{r × t} on the top horizontal part and n repetitions of a matrix B in Z^{s × t} on the diagonal below the top part. Instead of allowing only two types of block matrices, one for the horizontal line and one for the diagonal, we generalize the n-fold setting to allow for arbitrary matrices in every block. We show that such an integer program can be solved in time n^2t^2 phi x (r s delta)^{O(rs^2+ sr^2)} (ignoring logarithmic factors). Here delta is an upper bound on the largest absolute value of an entry of A and phi is the largest binary encoding length of a coefficient of c. This improves upon the previously best algorithm of Hemmecke, Onn and Romanchuk that runs in time n^3t^3 phi x delta^{O(st(r+t))}. In particular, our algorithm is not exponential in the number t of columns of A and B. Our algorithm is based on a new upper bound on the l_1-norm of an element of the Graver basis of an integer matrix and on a proximity bound between the LP and IP optimal solutions tailored for IPs with block structure. These new bounds rely on the Steinitz Lemma. Furthermore, we extend our techniques to the recently introduced tree-fold IPs, where we again present a more efficient algorithm in a generalized setting.
Cite as

Friedrich Eisenbrand, Christoph Hunkenschröder, and Kim-Manuel Klein. Faster Algorithms for Integer Programs with Block Structure. In 45th International Colloquium on Automata, Languages, and Programming (ICALP 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 107, pp. 49:1-49:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{eisenbrand_et_al:LIPIcs.ICALP.2018.49,
  author =	{Eisenbrand, Friedrich and Hunkenschr\"{o}der, Christoph and Klein, Kim-Manuel},
  title =	{{Faster Algorithms for Integer Programs with Block Structure}},
  booktitle =	{45th International Colloquium on Automata, Languages, and Programming (ICALP 2018)},
  pages =	{49:1--49:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-076-7},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{107},
  editor =	{Chatzigiannakis, Ioannis and Kaklamanis, Christos and Marx, D\'{a}niel and Sannella, Donald},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2018.49},
  URN =		{urn:nbn:de:0030-drops-90537},
  doi =		{10.4230/LIPIcs.ICALP.2018.49},
  annote =	{Keywords: n-fold, Tree-fold, Integer Programming}
}
Document
DOI: 10.4230/DagSemProc.05471.6
Evaluation of LC-MS data for the absolute quantitative analysis of marker proteins

Authors: Nathanaël Delmotte, Bettina Mayr, Andreas Leinenbach, Knut Reinert, Oliver Kohlbacher, Christoph Klein, and Christian G. Huber

Published in: Dagstuhl Seminar Proceedings, Volume 5471, Computational Proteomics (2006)

Abstract
The serum complexity makes the absolute quantitative analysis of medium to low-abundant proteins very challenging. Tens of thousands proteins are present in human serum and dispersed over an extremely wide dynamic range. The reliable identification and quantitation of proteins, which are potential biomarkers of disease, in serum or plasma as matrix still represents one of the most difficult analytical challenges. The difficulties arise from the presence of a few, but highly abundant proteins in serum and from the non-availability of isotope-labeled proteins, which serve to calibrate the method and to account for losses during sample preparation. For the absolute quantitation of serum proteins, we have developed an analytical scheme based on first-dimension separation of the intact proteins by anion-exchange high-performance liquid chromatography (HPLC), followed by proteolytic digestion and second-dimension separation of the tryptic peptides by reversed-phase HPLC in combination with electrospray ionization mass spectrometry (ESI-MS). The potential of mass spectrometric peptide identification in complex mixtures by means of peptide mass fingerprinting (PMF) and peptide fragment fingerprinting (PFF) was evaluated and compared utilizing synthetic mixtures of commercially available proteins and electrospray-ion trap- or electrospray time-of-flight mass spectrometers. While identification of peptides by PFF is fully supported by automated spectrum interpretation and database search routines, reliable identification by PMF still requires substantial efforts of manual calibration and careful data evaluation in order to avoid false positives. Quantitation of the identified peptides, however, is preferentially performed utilizing full-scan mass spectral data typical of PMF. Algorithmic solutions for PMF that incorporate both recalibration and automated feature finding on the basis of peak elution profiles and isotopic patterns are therefore highly desirable in order to speed up the process of data evaluation and calculation of quantitative results. Calibration for quantitative analysis of serum proteins was performed upon addition of known amounts of authentic protein to the serum sample. This was essential for the analysis of human serum samples, for which isotope-labeled protein standards are usually not available. We present the application of multidimensional HPLC-ESI-MS to the absolute quantitative analysis of myoglobin in human serum, a very sensitive biomarker for myocardial infarction. It was possible to determine myoglobin concentrations in human serum down to 100-500 ng/mL. Calibration graphs were linear over at least one order of magnitude and the relative standard deviation of the method ranged from 7-15%.
Cite as

Nathanaël Delmotte, Bettina Mayr, Andreas Leinenbach, Knut Reinert, Oliver Kohlbacher, Christoph Klein, and Christian G. Huber. Evaluation of LC-MS data for the absolute quantitative analysis of marker proteins. In Computational Proteomics. Dagstuhl Seminar Proceedings, Volume 5471, pp. 1-5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006)

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@InProceedings{delmotte_et_al:DagSemProc.05471.6,
  author =	{Delmotte, Nathana\"{e}l and Mayr, Bettina and Leinenbach, Andreas and Reinert, Knut and Kohlbacher, Oliver and Klein, Christoph and Huber, Christian G.},
  title =	{{Evaluation of LC-MS data for the absolute quantitative analysis of marker proteins}},
  booktitle =	{Computational Proteomics},
  pages =	{1--5},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2006},
  volume =	{5471},
  editor =	{Christian G. Huber and Oliver Kohlbacher and Knut Reinert},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.05471.6},
  URN =		{urn:nbn:de:0030-drops-5397},
  doi =		{10.4230/DagSemProc.05471.6},
  annote =	{Keywords: RP-HPLC, monolith, Mascot, Myoglobin, Absolute quantitation, Serum}
}
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