A5017449289- Infrastructure Maintenance and Monitoring
- earthquake and tectonic studies
- Asphalt Pavement Performance Evaluation
- Geotechnical Engineering and Soil Stabilization
- Structural Analysis and Optimization
- Grouting, Rheology, and Soil Mechanics
- Geotechnical Engineering and Analysis
- 3D Surveying and Cultural Heritage
- Advanced Multi-Objective Optimization Algorithms
- Industrial Vision Systems and Defect Detection
- Tree Root and Stability Studies
- Seismic Performance and Analysis
- Robotic Path Planning Algorithms
- Seismology and Earthquake Studies
- Metaheuristic Optimization Algorithms Research
- Water Systems and Optimization
- Earthquake Detection and Analysis
- Seismic Waves and Analysis
- Structural Health Monitoring Techniques
- Experimental Learning in Engineering
- Topology Optimization in Engineering
- Greenhouse Technology and Climate Control
- Earthquake and Tsunami Effects
- Microbial Applications in Construction Materials
- Biomimetic flight and propulsion mechanisms
Middle East Technical University
2013-2024
University of Illinois Urbana-Champaign
2005
The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of North-eastern Atlantic, Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as three-phase project. first two phases were dedicated to development calculations, following formalized decision-making process based on multiple-expert protocol. third phase documentation dissemination. assessment workflow structured in Steps Levels. There...
Abstract This paper presents a comprehensive overview of the rapid damage assessment and reconnaissance efforts following devastating earthquakes on February 6, 2023, in Türkiye. It specifically focuses implementing SiteEye Disaster Plugin, an additional component software developed by i4 Company engineers Middle East Technical University researchers. tool played critical role managing analyzing massive dataset comprising over 28,000 images videos. The research highlights plugin’s innovative...
Pavement condition assessment is an essential piece of modern pavement management systems as rehabilitation strategies are planned based upon its outcomes. For proper evaluation existing pavements, they must be continuously and effectively monitored using practical means. Conventionally, truck-based monitoring have been in-use in assessing the remaining life in-service pavements. Although such produce accurate results, their use can expensive data processing time consuming, which make them...
The use of biological means for ground improvement have become popular, which generally works through the process called microbially-induced calcium carbonate precipitation (MICP). Many studies indicate successful application MICP based with multiple bacteria and on several soils. Given proven performance MICP, this study aims to examine by comparing ability widely studied bacteria, i.e., Sporosarcina pasteurii relatively under-recognized Bacillus licheniformis outline formation success. For...
Removal of Construction Machinery Occlusion using Image Segmentation and Inpainting for Automated Progress Tracking Ahmet Bahaddin Ersoz, Onur Pekcan Pages 759-767 (2024 Proceedings the 41st ISARC, Lille, France, ISBN 978-0-6458322-1-1, ISSN 2413-5844) Abstract: This study introduces an innovative method enhancing digital modeling accuracy in construction site monitoring by integrating UAV imaging with advanced machine learning computer vision algorithms. It focuses on removing temporary...
Simulation of engineering problems plays a crucial role in understanding them well and solving efficiently. In geotechnical engineering, first need very good the field conditions, which can be modeled by various tools available market such as borehole loggers, geographic information system-based software, etc. Game engines, heavily used development computer games, alternative to visualize problems. this paper, game engine called Unity was create virtual environment defined data from or...
Applying deep learning algorithms in the construction industry holds tremendous potential for enhancing site management, safety, and efficiency. The development of such necessitates a comprehensive diverse image dataset. This study introduces Aerial Image Dataset Construction (AIDCON), novel aerial collection containing 9563 machines across nine categories annotated at pixel level, carrying critical value researchers professionals seeking to develop refine object detection segmentation...