Biography
Professor Sinan Acikgoz studied at the Middle East Technical University, before gaining his PhD in Engineering from Trinity College, Univeristy of Cambridge, in 2014.
Sinan was a Postdoctoral Research Associate at Cambridge's Centre for Smart Infrastructure and Construction, before receiving an 1851 Brunel Research Fellowship at Clare Hall College.
He is now an Associate Professor of Engineering Science, based at the Information Engineering Building at the University of Oxford.
Most Recent Publications
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
Research Interests
Sinan's interests include:
- Masonry structures
- Structural health monitoring
- Structural dynamics
- Soil-structure interaction
Research Groups
Current Projects
Influence of underground construction on nearby structures
Underground construction is becoming the preferred method to deliver infrastructure to urban areas. However, ground movements during construction can damage existing structures. Inspired by comprehensive field data, our research develops new analytical assessment techniques which consider salient building features and soil-structure interaction in a simple and effective manner. These models aim to provide a clearer appreciation of risk to existing structures in order to minimise expensive mitigation methods.
Structural response of ageing masonry arch bridges
Masonry arch bridges form an integral part of the European transportation network. These enduring structures are facing new challenges due to modern use and increased flood risks, yet their serviceability response is poorly understood. Our research investigates the fundamental behaviour of masonry bridges with detailed field data and computational modelling. The objective of this research is to devise new assessment tools which can better describe the serviceability response of damaged masonry bridges and predict their complex degradation processes.
Vision-based remote and distributed sensing techniques
Vision based remote and distributed sensing technologies provide the ability to remotely quantify the damage condition of the asset and precisely measure displacements and strains in different parts of the structure. Our research interests in this area include the use of photogrammetry, digital image correlation and laser scanning to describe structural geometry, load, performance and damage, to inform structural assessments.
Dynamics of rocking structures
During earthquakes, masonry structures exhibit rocking behaviour in different forms. In addition, new generation of earthquake resilient design systems use rocking mechanisms to mitigate damage in structures. Therefore, understanding the dynamics of rocking systems is of fundamental importance for the protection of old and new structures from earthquakes. Our work in this area focuses on the complex interactions between the soil, the rocking mechanisms and the structural vibrations.
Most Recent Publications
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
Journal Publications
An up to date publication list can be found on my personal website or Google Scholar profile.
Most Recent Publications
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
DPhil Opportunities
I am looking for graduate engineering students with a strong academic background and an enthusiasm for interdisciplinary structural engineering research. Please get in touch.
Most Recent Publications
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
A lightweight Transformer‐based neural network for large‐scale masonry arch bridge point cloud segmentation
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Determining the Young’s Modulus of Lime Mortar Using the Virtual Fields Method
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Strengthening Historic Masonry Walls Using Sprayed Glass-Fibre-Reinforced Gypsum (GFRG) Against Settlement-Induced Damage
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster
Preliminary Experimental Investigation on Mechanical Properties of Historical Fibrous Plaster