• Semi-Bayesian active learning quadrature for estimating extremely low failure probabilities 

  Dang, Chao; Beer, Michael (London [u.a.] : Elsevier Science, 2024)

  The Bayesian failure probability inference (BFPI) framework provides a sound basis for developing new Bayesian active learning reliability analysis methods. However, it is still computationally challenging to make use of ...
• Microplastic retention in marine vegetation canopies under breaking irregular waves 

  Kerpen, Nils B.; Larsen, Bjarke Eltard; Schlurmann, Torsten; Paul, Maike; Guler, Hasan Gokhan; Goral, Koray Deniz; Carstensen, Stefan; Christensen, Erik Damgaard; Fuhrman, David R. (Amsterdam [u.a.] : Elsevier Science, 2023)

  The present study provides indications and underlying drivers of wave-induced transport and retention potential of microplastic particles (MP) in marine vegetation canopies having different densities. The anthropogenic ...
• Directionally Resolved Environmental Contours 

  Kaliske, Malte; Schmidt, Boso (Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2024)

  Statistical analysis and probabilistic modelling of metocean conditions play a crucial role in the design of offshore wind turbines (OWT) and other marine structures. Typically, environmental contours are created to ...
• Building detection from aerial imagery using inception ResNet UNet and UNet architectures 

  Aghayari, S.; Hadavand, A.; Mohamadnezhad Niazi, S.; Omidalizarandi, M. (Red Hook, NY : Curran, 2023)

  Buildings are one of the key components in change detection, urban planning, and monitoring. The automatic extraction of the building from high-resolution aerial imagery is still challenging due to the variations in their ...
• Intelligent 3D crack reconstruction using close range photogrammetry imagery 

  Majidi, S.; Omidalizarandi, M.; Sharifi, M.A. (Red Hook, NY : Curran, 2023)

  Civil infrastructure Structural Health Monitoring (SHM) and its preservation from deterioration is a crucial task. In general, natural disasters like severe earthquakes, extreme landslides, subsidence or intensive floods ...
• Automatic extraction of control points from 3D Lidar mobile mapping and UAV imagery for aerial triangulation 

  Naimaee, R.; Saadatseresht, M.; Omidalizarandi, M. (Red Hook, NY : Curran, 2023)

  Installing targets and measuring them as ground control points (GCPs) are time consuming and cost inefficient tasks in a UAV photogrammetry project. This research aims to automatically extract GCPs from 3D LiDAR mobile ...
• Numerical and laboratory investigations of thermally induced fractures in rock salt 

  Körner, Feline; Baumgärtel, Lukas; Leuger, Bastian (London [u.a.] : Institute of Physics, 2023)

  In order to widen the basis for the dimensioning of storage caverns in rock salt, some special attention must be paid to the temperature developments within the cavity during its operation. Passed numerical investigations ...
• Hydrodynamic coefficients of mussel dropper lines derived from large-scale experiments and structural dynamics 

  Landmann, Jannis; Flack, Christian; Kowalsky, Ursula; Wüchner, Roland; Hildebrandt, Arndt; Goseberg, Nils (Berlin [u.a.] : Springer, 2023)

  The expansion of marine aquaculture production is driven by a high market demand for marine proteins and a stagnation of wild catch of fish. Bivalve farming, i.e., the cultivation of oysters, mussels and scallops, is an ...
• 3D-ResNet-BiLSTM Model: A Deep Learning Model for County-Level Soybean Yield Prediction with Time-Series Sentinel-1, Sentinel-2 Imagery, and Daymet Data 

  Fathi, Mahdiyeh; Shah-Hosseini, Reza; Moghimi, Armin (Basel : MDPI, 2023)

  Ensuring food security in precision agriculture requires early prediction of soybean yield at various scales within the United States (U.S.), ranging from international to local levels. Accurate yield estimation is essential ...
• Complete fatigue crack arrest in metallic structures using bonded prestressed iron-based shape memory alloy repairs 

  Wang, Wandong; Zhou, Wei; Ma, Yu’e; Motavalli, Masoud; Ghafoori, Elyas (Oxford : Elsevier, 2023)

  Vast aging metallic structures are suffering from fatigue cracking, jeopardizing structural integrity and personnel safety. Therefore it is of great benefit to develop strengthening solutions to achieve complete fatigue ...
• Mode I fracture analysis of Fe-SMA bonded double cantilever beam considering nonlinear behavior of the adherends 

  Pichler, Niels; Wang, Wandong; Motavalli, Masoud; Taras, Andreas; Ghafoori, Elyas (Kidlington : Elsevier Science, 2023)

  In the scope of developing a bonded iron-based shape memory alloy (Fe-SMA) strengthening solution, nonlinear deformation in the adherends upon joint failure due to phase transformation and high adhesive toughness is ...
• Bedoi: Benchmarks For Determining Overlapping Images With Photogrammetric Information 

  Zhan, H.; Yu, Y.F.; Xu, Y.W.; Hou, Q.B.; Xia, R.; Wang, X.; Feng, Y.; Zhan, Z.Q.; Li, M.L.; Gruber, M.; Hänsch, R.; Heipke, C. (Katlenburg-Lindau : Copernicus Publications, 2023)

  For conventional SfM pipeline, image matching is enduring limitation when considering the time efficiency. In the last few years, to speed up image matching procedure, many image retrieval works were proposed to fast find ...
• Integrating Motion Priors For End-To-End Attention-Based Multi-Object Tracking 

  Ali, R.; Mehltretter, M.; Heipke, C. (Katlenburg-Lindau : Copernicus Publications, 2023)

  Recent advancements in multi-object tracking (MOT) have heavily relied on object detection models, with attention-based models like DEtection TRansformer (DETR) demonstrating state-of-the-art capabilities. However, the ...
• Oil spill monitoring using satellite imagery in the Sharm El-Maya Bay of Sharm El-Sheikh, Egypt 

  Morsy, M. (Katlenburg-Lindau : Copernicus Publications, 2023)

  Sharm el-Sheikh, in Egypt, is a prominent tourist destination. The city attracts millions of visitors annually due to its exceptional location and pleasant climate. Owing to its natural ecosystem and marine diversity, Sharm ...
• Enhancing The Quality Of CNN-Based Burned Area Detection In Satellite Imagery Through Data Augmentation 

  Hnatushenko, V.; Hnatushenko, V.; Soldatenko, D.; Heipke, C. (Katlenburg-Lindau : Copernicus Publications, 2023)

  This study aims to enhance the quality of detecting burned areas in satellite imagery using deep learning by optimizing the training dataset volume through the application of various augmentation methods. The study analyzes ...
• Preface: Workshop “Semantics3D - Semantic Scene Analysis and 3D Reconstruction from Images and Image Sequences” 

  Rottensteiner, F.; Haala, N.; Ying Yang, M. (Katlenburg-Lindau : Copernicus Publications, 2023)

  [no abstract available]
• Network log-ARCH models for forecasting stock market volatility 

  Mattera, Raffaele; Otto, Philipp (Amsterdam [u.a.] : Elsevier Science, 2024)

  This paper presents a dynamic network autoregressive conditional heteroscedasticity (ARCH) model suitable for high-dimensional cases where multivariate ARCH models are typically no longer applicable. We adopt the theoretical ...
• Estimation of capacity decrease due to accumulated excess pore pressures around cyclically loaded offshore foundations in sand 

  Saathoff, Jann-Eike; Achmus, Martin (Amsterdam [u.a.] : Elsevier Science, 2024)

  In particular during storm events, a build-up of excess pore pressures may occur in the soil around cyclically loaded offshore foundations. Such accumulated excess pore pressure reduces the effective stresses in the soil ...
• Spatio-temporal analysis of scour around complex offshore foundations under clear water and live bed conditions 

  Welzel, Mario; Schendel, Alexander; Satari, Ramish; Neuweiler, Insa; Schlurmann, Torsten (Amsterdam [u.a.] : Elsevier Science, 2024)

  This study investigates scour around offshore wind foundations, focusing on two complex structures with varying degrees of flow blockage: a novel hybrid gravity-based jacket (structure “A") and a conventional four-legged ...
• Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities 

  Dang, Chao; Faes, Matthias G.R.; Valdebenito, Marcos A.; Wei, Pengfei; Beer, Michael (Amsterdam [u.a.] : Elsevier Science, 2024)

  The Bayesian failure probability inference (BFPI) framework provides a well-established Bayesian approach to quantifying our epistemic uncertainty about the failure probability resulting from a limited number of performance ...

View more