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1Temperature Reduction as Operando Performance Recovery Procedure for Polymer Electrolyte Membrane Fuel Cells
Q. Zhang, M. Schulze, P. Gazdzicki, K. Friedrich, and K. Friedrich. (2024)
3 months ago by @ipappwiedmann
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Cells
Electrolyte
Fuel
Membrane
Operando
Performance
Polymer
Procedure
Recovery
Reduction
Temperature
as
for
CellsElectrolyteFuelMembraneOperandoPerformancePolymerProcedureRecoveryReductionTemperatureasfor
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2DSL4DPiFS – Eine Grafische Notation zur Modellierung von Daten-Pipelines in der Umformtechnik
B. Vogel-Heuser, M. Zhang, M. Krueger, A. Vicaria, M. Gardill, Y. Jiang, A. Trächtler, H. Peters, M. Liewald, A. Schenek and 2 other author(s). at-Automatisierungstechnik, 73 (4): 232-250 (2025)
4 months ago by @roxyfoxy2211
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AS
Daten-Pipeline
Informationsmodell
ML
Maschinelles-Lernen
Modellbasierte-Systementwicklung
PH
Umformtechnik
datengetriebene-Ansaetze
ASDaten-PipelineInformationsmodellMLMaschinelles-LernenModellbasierte-SystementwicklungPHUmformtechnikdatengetriebene-Ansaetze
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2DSL4DPiFS – Eine Grafische Notation zur Modellierung von Daten-Pipelines in der Umformtechnik
B. Vogel-Heuser, M. Zhang, M. Krueger, A. Vicaria, M. Gardill, Y. Jiang, A. Trächtler, H. Peters, M. Liewald, A. Schenek and 2 other author(s). at-Automatisierungstechnik, 73 (4): 232-250 (2025)
4 months ago by @ifu
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datengetriebene-Ansaetze
Daten-Pipeline
Maschinelles-Lernen
AS
Informationsmodell
PH
Umformtechnik
ML
Modellbasierte-Systementwicklung
datengetriebene-AnsaetzeDaten-PipelineMaschinelles-LernenASInformationsmodellPHUmformtechnikMLModellbasierte-Systementwicklung
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2Surrogat-Modelle zur Auslegung und Optimierung einhubiger Scherschneidprozesse
A. Schenek. (2024)
10 months ago by @ifu
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AS
KI
KuenstlicheIntelligenz
Modellierung
Optimierung
Scherschneidprozess
Schnittflaechenkenngroessen
dissertation
ASKIKuenstlicheIntelligenzModellierungOptimierungScherschneidprozessSchnittflaechenkenngroessendissertation
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2Production of Thin Outer Skin Car Body Panels by Using Novel Short Cycle Stretch-Forming (SCS) Technology
M. Liewald, and A. Schenek. Advances in Automotive Production Technology -- Theory and Application, page 286--292. Berlin, Heidelberg, Springer Berlin Heidelberg, (2021)
a year ago by @ifu
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imported
AS
ML
importedASML
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4Identification of process limits for punching with a slant angle
A. Schenek, M. Liewald, and S. Senn. IOP Conference Series: Materials Science and Engineering, 651 (1): 012066 (November 2019)
a year ago by @ifu
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imported
AS
importedAS
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1Numerical and Experimental Investigations to Increase Cutting Surface Quality by an Optimized Punch Design
A. Schenek, S. Senn, and M. Liewald. Production at the Leading Edge of Technology, page 179--188. Cham, Springer International Publishing, (2023)
a year ago by @ifu
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imported
AS
ML
SS
importedASMLSS
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1Lochen mit Blechlagewinkel -- Methodenoptimierung/Punching with a slant angle -- a novel approach in process design
A. Schenek, S. Senn, and M. Liewald. wt Werkstattstechnik online, 110 (10): 689-696 (January 2020)
a year ago by @ifu
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AS
ML
SS
ASMLSS
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1Application of a neural network for predicting the cutting surface quality of punching processes based on tooling parameters
A. Schenek, M. Görz, M. Liewald, and K. Riedmüller. IOP Conference Series: Materials Science and Engineering, 1284 (1): 012014 (June 2023)
a year ago by @ifu
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AS
KR
MG
ML
ASKRMGML
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1Einsatz von ML beim Scheren im offenen Schnitt/Use of ML in shearing with an open cutting line
M. Görz, A. Schenek, M. Liewald, and K. Riedmüller. wt Werkstattstechnik online, 113 (10): 384--388 (January 2023)
a year ago by @ifu
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AS
KR
MG
imported
ASKRMGimported
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1Prediction of Cutting Surface Parameters in Punching Processes Aided by Machine Learning
A. Schenek, M. Görz, M. Liewald, and K. Riedmüller. TMS 2023 152nd Annual Meeting & Exhibition Supplemental Proceedings, page 607--619. Cham, Springer Nature Switzerland, (2023)
a year ago by @ifu
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AS
KR
MG
ML
imported
ASKRMGMLimported
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1Detection of Defective Deep Drawn Sheet Metal Parts by Using Machine Learning Methods for Image Classification
P. Tchasse, A. Schenek, K. Riedmüller, and M. Liewald. Production at the Leading Edge of Technology, page 84--93. Cham, Springer Nature Switzerland, (2024)
a year ago by @ifu
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AS
KR
ML
PT
imported
ASKRMLPTimported
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1Determining the residual formability of shear-cut sheet metal edges by utilizing an ML based prediction model
M. Goerz, A. Schenek, V. Quan, K. Riedmueller, and M. Liewald. Materials Research Proceedings, 41, page 1799-1806. Millersville PA, USA, Materials Research Forum LLC, (May 2024)
a year ago by @ifu
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AS
KR
MG
imported
ASKRMGimported
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5Punching with a slant angle - cutting surface quality
A. Schenek, and M. Liewald. ESAFORM 2021, (April 2021)
a year ago by @ifu
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AS
imported
ASimported
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1Production at the leading edge of technology
T. Bauernhansl, A. Verl, M. Liewald, and H. Möhring (Eds.) Springer International Publishing, Cham, Switzerland, 1 edition, (November 2023)
a year ago by @ifu
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imported
AS
ML
importedASML
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1Data-driven derivation of sheet metal properties gained from punching forces using an artificial neural network
A. Schenek, M. Görz, M. Liewald, and K. Riedmüller. Key Engineering Materials, (July 2022)
a year ago by @ifu
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AS
KR
MG
ML
imported
ASKRMGMLimported
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7Determination of muscle shape deformations of the tibialis anterior during dynamic contractions using 3D ultrasound
A. Sahrmann, L. Vosse, T. Siebert, G. Handsfield, and O. Röhrle. Frontiers in Bioengineering and Biotechnology, (2024)
a year ago by @utilityimsb
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3Dfoot
as
cbm
exc2075
grk
grk2198
myown
or
3Dfootascbmexc2075grkgrk2198myownor
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2Shearing of sheet metal under special attention of compressive stresses
M. Liewald, D. Briesenick, S. Senn, and A. Schenek. 41st SENAFOR Porto Alegre Brasilien, (2022)
a year ago by @ifu
show all tags
AS
DB
ML
SS
imported
ASDBMLSSimported
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23D ultrasound-based determination of skeletal muscle fascicle orientations
A. Sahrmann, L. Vosse, T. Siebert, G. Handsfield, and O. Röhrle. Biomechanics and Modeling in Mechanobiology, (March 2024)
a year ago by @utilityimsb
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EXC2075
as
cbm
grk2198
or
EXC2075ascbmgrk2198or
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2A System for Reproducible 3D Ultrasound Measurements of Skeletal Muscles
A. Sahrmann, G. Handsfield, L. Gizzi, J. Gerlach, A. Verl, T. Besier, and O. Röhrle. IEEE Transactions on Biomedical Engineering, (2024)
2 years ago by @utilityimsb
show all tags
as
cbm
exc2075
grk
grk2198
lg
or
ascbmexc2075grkgrk2198lgor
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PUMA

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publications (hide)36
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1Temperature Reduction as Operando Performance Recovery Procedure for Polymer Electrolyte Membrane Fuel Cells

2DSL4DPiFS – Eine Grafische Notation zur Modellierung von Daten-Pipelines in der Umformtechnik

2DSL4DPiFS – Eine Grafische Notation zur Modellierung von Daten-Pipelines in der Umformtechnik

2Surrogat-Modelle zur Auslegung und Optimierung einhubiger Scherschneidprozesse

2Production of Thin Outer Skin Car Body Panels by Using Novel Short Cycle Stretch-Forming (SCS) Technology

4Identification of process limits for punching with a slant angle

1Numerical and Experimental Investigations to Increase Cutting Surface Quality by an Optimized Punch Design

1Lochen mit Blechlagewinkel -- Methodenoptimierung/Punching with a slant angle -- a novel approach in process design

1Application of a neural network for predicting the cutting surface quality of punching processes based on tooling parameters

1Einsatz von ML beim Scheren im offenen Schnitt/Use of ML in shearing with an open cutting line

1Prediction of Cutting Surface Parameters in Punching Processes Aided by Machine Learning

1Detection of Defective Deep Drawn Sheet Metal Parts by Using Machine Learning Methods for Image Classification

1Determining the residual formability of shear-cut sheet metal edges by utilizing an ML based prediction model

5Punching with a slant angle - cutting surface quality

1Production at the leading edge of technology

1Data-driven derivation of sheet metal properties gained from punching forces using an artificial neural network

7Determination of muscle shape deformations of the tibialis anterior during dynamic contractions using 3D ultrasound

2Shearing of sheet metal under special attention of compressive stresses

23D ultrasound-based determination of skeletal muscle fascicle orientations

2A System for Reproducible 3D Ultrasound Measurements of Skeletal Muscles

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