Th.3.A
Visionary Concepts, Deep Learning

Th.3.A.1
  Full Paper

Self-Prestressed Carbon-Reinforced High Performance Concrete Elements

M. Wyrzykowski1, P. Lura1, G. Terrasi1

1: EMPA, Dübendorf, Switzerland

Th.3.A.2
  Full Paper

Automated Infrastructure Inspection based on Digital Twins and Machine Learning.

P. Furtner1, E. Forstner2, A. Karlusch2

1: VCE Vienna Consulting Engineers ZT GmbH, Vienna, Austria
2: Palfinger Structural Inspection GmbH, Vienna, Austria

Th.3.A.3
  Full Paper

Reinforced Masonry Retention Wall Model Using Artificial Neural Networks

E.S. Hernandez1, J.A. Alvarado-Contreras2, A.A. López-Inojosa2, J.J. Myers1

1: Missouri University of Science and Technology, Rolla, USA
2: University of Los Andes, Merida, Venezuela

Th.3.A.4
  Full Paper

Modeling of Bimodulus Materials with Applications to the Analysis of the Brazilian Disk Test

E.S. Hernandez1, J.A. Alvarado-Contreras2, A.A. López-Inojosa2, J.J. Myers1

1: Missouri University of Science and Technology, Rolla, USA
2: University of Los Andes, Mérida, Venezuela

Th.3.A.5
  Full Paper

Artificial intelligence-based estimation of the consumed fatigue-related lifetime for an operating wind turbine support structure

M. Ratkovac1, I. Mueller1, R. Höffer1

1: Ruhr-Universität Bochum, Bochum, Germany

Th.3.A.6
  Full Paper

Deep Learning-based Defect Detection and Assessment for Engineering Structures

Z.Y. Wu1, R. Kalfarisi1

1: Bentley Systems, Incorporated, Watertown, USA

Th.3.A.7
  Full Paper

Moving Beyond the Romans: Deep Learning and Road Maintenance

M. DeSantis1, C. Mertz1

1: RoadBotics, Pittsburgh, USA

Th.3.A.8
  Full Paper

Application of deep learning-based crack assessment technique to civil structures

S. Cho1, B. Kim1, G. Kim1

1: University of Seoul, Seoul, South Korea