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Structures Group seminars

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The Engineering Department (CUED) hosts a series of Structures seminars for post-graduates, undergraduates and staff. Non-CUED university people are also welcome to attend. The seminars will be at the Seminar room, Civil Engineering building in West Cambridge at 3pm, unless otherwise stated.
URL: http://talks.cam.ac.uk/show/index/7107
Updated: 1 hour 15 sec ago

Fri 23 May 14:30: Recent advances in critical infrastructures forecasting via Physics-Enhanced Machine Learning 

Fri, 16/05/2025 - 22:58
Recent advances in critical infrastructures forecasting via Physics-Enhanced Machine Learning 

This talk will introduce the concept of Physics-Enhanced Machine Learning (PEML) which combines data, physics and expert and domain knowledge to enhance modelling and forecasting capabilities of critical infrastructures such as bridges, ferry quays and wind turbines. PEML approaches developed to address challenges such as parameter identification and virtual sensing will be described. An overview of recent developments on model updates in the presence of sparse information, equation discovery in the presence of non-smooth nonlinearity, and measurements disentanglement will be provided. Finally open challenges are going to be summarised.

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Fri 16 May 15:00: Structural Response and Reuse Potential of Steel-timber Shear Connections

Wed, 14/05/2025 - 09:56
Structural Response and Reuse Potential of Steel-timber Shear Connections

This presentation examines the structural response, disassembly, and reuse potential of steel-timber shear connections. It includes results from experiments and numerical simulations under various loading conditions. A detailed account of the complete deformation response and the main mechanical parameters of the tested shear connections for conventional and slim steel-timber floors is presented. Non-linear finite element simulations were carried out to validate the main numerical parameters for steel, timber, and interaction characteristics, and then used for parametric investigations. Based on the results and observations, code-modified expressions for evaluating stiffness and load resistance were proposed within the ranges considered and validated against a collated database. A constitutive model was developed to predict the full load-slip response of shear connections, which can be adopted for discrete non-linear modelling of connectors. A reuse potential testing protocol was developed to evaluate performance after cyclic loading and reassembly, and a modified separation damage index was introduced to quantify the circularity of these systems. A sensitivity study for the tested shear connections and other practical configurations for steel-timber floors was also carried out for evaluating the circularity of such systems.

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Fri 02 May 15:00: Toward Mechanically Adaptive and Multi-functional Structures

Mon, 28/04/2025 - 10:42
Toward Mechanically Adaptive and Multi-functional Structures

Most natural organisms show fascinating mechanical adaptability when interacting with their environments. Stiffness tuning in nature is used as a powerful tool to combine the load carrying functionality of rigid structures with compliance and adaptability. Human-made structures, however, do not possess this mechanical adaptability and are often designed to meet a specific load carrying requirement. This causes limitations in performance, efficiency and safety. Often to add other functionalities, additional components are needed, which increases the total weight and cost of the structures.

In this talk, I will present the latest research in our group on a variety of structures including multi-material cellular and multi-layered structures that employed active stiffness tuning based on thermoplastic softening. We use a combined experimental and numerical approach to investigate the electro-thermo-mechanical response of these structures. Understanding the main physical obstacles that limit the response time and the fundamental parameters controlling the stability and the failure under harsh electro-thermal loading will help us to better engineer the structures to meet the fast response and low power requirements. This new understanding will accelerate the technology readiness level of active structural control technology to be used in future multi-functional and smart structures. This technology has a wide range of application in robotics, morphing and deployable structures, active damping and active impact protection.

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Fri 17 Oct 15:00: Title to be confirmed

Wed, 02/04/2025 - 15:49
Title to be confirmed

Abstract not available

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Fri 09 May 15:00: Title to be confirmed

Wed, 02/04/2025 - 15:48
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Fri 02 May 15:00: Title to be confirmed

Wed, 02/04/2025 - 15:47
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Fri 30 May 15:00: Title to be confirmed

Tue, 11/03/2025 - 15:54
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Fri 16 May 15:00: Title to be confirmed

Tue, 11/03/2025 - 15:53
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Fri 23 May 14:30: Title to be confirmed

Fri, 28/02/2025 - 14:12
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Fri 10 Oct 15:00: Title to be confirmed

Thu, 27/02/2025 - 15:35
Title to be confirmed

Abstract not available

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Fri 28 Feb 15:00: Shape Optimisation of Concrete Structural Elements Reinforced with WFRP (Wounded-Fibre-Reinforced-Polymer) Bars

Wed, 19/02/2025 - 14:20
Shape Optimisation of Concrete Structural Elements Reinforced with WFRP (Wounded-Fibre-Reinforced-Polymer) Bars

In 2022, building operations and construction accounted for 37% of total global energy and process related CO2 emissions (UNEP, 2023). Reducing these emissions is urgent. It is therefore worth rethinking the most used building material – concrete.

One approach to lowering the embodied carbon of concrete structures is shape optimisation – using material only where it is needed and taking advantage of the fluidity of concrete to create non-prismatic structural elements (Orr 2012; Orr et al. 2014). Another approach is replacing traditional steel reinforcement by alternative reinforcement, such as WFRP (Wounded-Fibre-Reinforced-Polymer) Bars which show the potential to reduce the embodied carbon compared to their steel-reinforced counterparts (Pavlović et al. 2022; Garg and Shrivastava 2019; Inman et al. 2017).

However, non-prismatic beams and slabs might be more prone to excessive deflection than their prismatic counterparts due to reduced flexural stiffness (Tayfur 2016). Additionally, WFRP -reinforced elements often exhibit greater deflection than steel-reinforced ones, because FRP bars (except carbon FRP ) typically have a lower elastic modulus than steel.

To address this issue, it is necessary to optimise the shape of WFRP - reinforced structural elements for Serviceability Limit State (SLS), ensuring they achieve lower embodied carbon than steel-reinforced ones whilst meeting design requirements for SLS . To achieve this, a theoretical method of shape optimisation for SLS is proposed, demonstrating higher efficiency than the existing method (Tayfur 2016). In addition, a flexural test on three BFRP (basalt FRP ) reinforced concrete slabs was conducted in the NFRIS (National Research Facility for Infrastructure Sensing) laboratory in 2024.

This presentation will cover this experimental study on the deflection of non-prismatic slabs in flexure as well as the theoretical method of shape optimisation for SLS .

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Fri 21 Feb 15:30: Low carbon construction, a return to stone, a new vernacular for the UK

Mon, 17/02/2025 - 10:25
Low carbon construction, a return to stone, a new vernacular for the UK

Steve founded Webb Yates Engineers with Andy Yates in 2005. Since founding the company, he has led a number of prestigious, multi award-winning projects, including the Stirling Prize shortlisted 15 Clerkenwell Close, The Kantor Centre of Excellence for the Anna Freud Centre, and the Hoover Building.

While thriving to make building structures intrinsic to architecture, Steve has pioneered the practice’s approach to innovation and sustainability. He is a strong advocate for the use of non-conventional materials to design low carbon structures, from cast iron to cork, and from inflatables to stone and timber.

Steve has written extensively for industry publications, including the Architect’s Journal, Architectural Review, Architecture Today, and the RIBA Journal. In 2020, he was awarded the Milne Medal, for continuously challenging and redefining what is considered possible in structural design.

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Fri 21 Feb 15:30: Title to be confirmed

Wed, 05/02/2025 - 15:30
Title to be confirmed

Abstract not available

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Fri 07 Feb 15:00: Population-Based Inference in Mechanics

Wed, 05/02/2025 - 14:44
Population-Based Inference in Mechanics

Inferring model parameters from observational data of a physical system is the setup for many inverse problems. Solving these kinds of problems can give key insight into the state of a system for quantities that are not directly observable, such as material properties. In this talk, we discuss a population-based perspective on solving inverse problems where the data available comes from a collection of physical systems and we are interested in characterising the (indirectly observable) properties of these systems at a distributional level. We call this: calibrating priors from indirect data. Furthermore, we show how this can be accomplished while concurrently learning ML-based surrogates which capture the behaviour of the physical systems of interest.

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Fri 14 Feb 15:00: Dematerialisation in Construction

Tue, 04/02/2025 - 16:09
Dematerialisation in Construction

Only in the last three decades, cement and plastic production has grown 2.5-fold, glass 2 and steel 1.5-fold (Cullen J.M., Drewniok M.P. et al. 2020). In 2022, the global building sector accounted for 34% of energy demand and 37% of total energy related CO2 emissions, reaching nearly 10 Gt CO2 (Hamilton, Kennard et al. 2024). More than a quarter were related to production of cement, steel, aluminium, bricks and glass (embodied carbon). It is predicted that global building stock should almost double by 2050 to meet population growth needs (GABC and IEA 2017 ). In the UK context, the built environment already accounts for nearly 30% of the UK’s total territorial GHG emissions (Green, Jonca et al. 2021), with the main materials used in construction accounting for up to 6% (Drewniok, Azevedo et al. 2023). As demand for construction is expected to increase (residential, commercial, non-emitting carbon infrastructure), we expect the use of materials to increase.

Emissions reduction techniques during manufacture (e.g. using alternative fuels, increase resource efficiency in production) can only slightly reduce rather than entirely eliminate the emissions related to construction materials. Moving to the most materially and carbon efficient technology options for buildings can bring further savings (Drewniok, Azevedo et al. 2023) with the largest savings occurring in structural efficiency (Dunant, Drewniok et al. 2021). Nevertheless, this will not allow to reach net-zero carbon by 2050. It is therefore crucial to minimise the overall flow of materials in the UK construction – dematerialisation (Drewniok, Azevedo et al. 2023).

In the presentation we will try to analyse the extent to which dematerialisation should be implemented in the UK construction industry to minimise the emissions from UK construction.

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Fri 07 Feb 15:00: Population-Based Inference in Mechanics This talk has been canceled/deleted

Mon, 03/02/2025 - 09:36
Population-Based Inference in Mechanics

Inferring model parameters from observational data of a physical system is the setup for many inverse problems. Solving these kinds of problems can give key insight into the state of a system for quantities that are not directly observable, such as material properties. In this talk, we discuss a population-based perspective on solving inverse problems where the data available comes from a collection of physical systems and we are interested in characterising the (indirectly observable) properties of these systems at a distributional level. We call this: calibrating priors from indirect data. Furthermore, we show how this can be accomplished while concurrently learning ML-based surrogates which capture the behaviour of the physical systems of interest.

This talk has been canceled/deleted

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Fri 07 Feb 15:00: Population-Based Inference in Mechanics

Mon, 03/02/2025 - 09:29
Population-Based Inference in Mechanics

Inferring model parameters from observational data of a physical system is the setup for many inverse problems. Solving these kinds of problems can give key insight into the state of a system for quantities that are not directly observable, such as material properties. In this talk, we discuss a population-based perspective on solving inverse problems where the data available comes from a collection of physical systems and we are interested in characterising the (indirectly observable) properties of these systems at a distributional level. We call this: calibrating priors from indirect data. Furthermore, we show how this can be accomplished while concurrently learning ML-based surrogates which capture the behaviour of the physical systems of interest.

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Fri 07 Feb 15:00: Population-Based Inference in Mechanics

Mon, 03/02/2025 - 09:29
Population-Based Inference in Mechanics

Inferring model parameters from observational data of a physical system is the setup for many inverse problems. Solving these kinds of problems can give key insight into the state of a system for quantities that are not directly observable, such as material properties. In this talk, we discuss a population-based perspective on solving inverse problems where the data available comes from a collection of physical systems and we are interested in characterising the (indirectly observable) properties of these systems at a distributional level. We call this: calibrating priors from indirect data. Furthermore, we show how this can be accomplished while concurrently learning ML-based surrogates which capture the behaviour of the physical systems of interest.

Add to your calendar or Include in your list

Fri 07 Feb 15:00: Population-Based Inference in Mechanics

Mon, 03/02/2025 - 09:29
Population-Based Inference in Mechanics

Inferring model parameters from observational data of a physical system is the setup for many inverse problems. Solving these kinds of problems can give key insight into the state of a system for quantities that are not directly observable, such as material properties. In this talk, we discuss a population-based perspective on solving inverse problems where the data available comes from a collection of physical systems and we are interested in characterising the (indirectly observable) properties of these systems at a distributional level. We call this: calibrating priors from indirect data. Furthermore, we show how this can be accomplished while concurrently learning ML-based surrogates which capture the behaviour of the physical systems of interest.

Add to your calendar or Include in your list

Fri 07 Feb 15:00: Population-Based Inference in Mechanics

Mon, 03/02/2025 - 09:29
Population-Based Inference in Mechanics

Inferring model parameters from observational data of a physical system is the setup for many inverse problems. Solving these kinds of problems can give key insight into the state of a system for quantities that are not directly observable, such as material properties. In this talk, we discuss a population-based perspective on solving inverse problems where the data available comes from a collection of physical systems and we are interested in characterising the (indirectly observable) properties of these systems at a distributional level. We call this: calibrating priors from indirect data. Furthermore, we show how this can be accomplished while concurrently learning ML-based surrogates which capture the behaviour of the physical systems of interest.

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Civil Engineering Division

National Research Facility for Infrastructure Sensing

Department of Engineering

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