Mass timber construction has been emerging in architecture because of exceptional durability, sustainability, and versatility. This work applies the 3-point bending test to a reduced-scale wooden stick with a supporting span of 16.5 cm, under loads up to 560 times its self-weight under raised environmental temperatures up to 300 °C in the oven. The experiments quantify the deformation, critical shear stress of rupture, and degradation mass losses of the heated wood before ignition and combustion, while the numerical model further analyses the detailed thermomechanical responses. Results show that with increasing temperature, the deflection of loaded wooden sticks increases, driven by drying, thermal creep deformation, and thermal degradation. Moreover, the critical shear stress and temperature for wooden sticks rupture decrease, primarily caused by the thermal degradation of wood. The effects of fire-scene temperature on bending strength and modulus of elasticity on the loss of load-bearing capacity for wooden sticks are further quantified with numerical simulation. This work reveals the pre-ignition thermomechanical behaviours of wood under fire scenes, which supports early warnings for ignition and collapse, fire resilience design, and structural-fire stability assessment for wooden structures.

Cross-Laminated Timber (CLT) walls are crucial components of modern buildings, consisting of multiple layers of timber bonded together. However, as combustible construction materials, their potential fire risk remains a significant concern. The behaviour of CLT components during a fire is complex and requires careful consideration of both (a) the temperature-dependent behaviour of the timber layers and (b) potential chemical reactions (e.g., pyrolysis) within the wood. For (a), the Eurocode EN 1995-1-2 provides guidelines for assessing the fire resistance of timber structures. For (b), this paper applies a pyrolysis model within a Heat Transfer (HT) analysis framework to predict the CLT structural response under fire conditions. This paper introduces and demonstrates a One-Way Coupled (OWC) fire-structure simulation, which combines Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) domains. Inspired by the standard fire test for CLT walls (Osborne et al. 2012), here, CFD is used to reproduce the ISO-834 standard fire as a preliminary demonstration case. Using the thermal data obtained from the CFD model as the boundary condition, a subsequent heat transfer analysis using Abaqus is able to predict pyrolysis and heat transfer behaviour, but it fails to represent the initial temperature distribution (which because of water evaporation is not considered) and capture post-failure behaviour. Additionally, a Structure Response (SR) analysis of the CLT wall under various mechanical loads indicated failures at different times during the fire. However, due to the lack specific information about experimental set-up in the literature, such as mechanical loads and material properties, future studies are planned to verify the model against experimental data.

Human pose estimation (HPE) is a crucial task in computer vision with extensive applications in healthcare, surveillance, and human–computer interaction. Traditional HPE research primarily utilizes RGB cameras, which may suffer from poor performance under varying lighting conditions and raise privacy concerns. Recently, millimeter-wave (mmWave) radar technology has emerged as a promising alternative, providing a non-invasive and privacy-preserving solution for HPE. However, the progress in mmWave-based HPE is hindered by the limited availability of high-quality datasets that encompass a diverse range of poses and provide accurate data annotations. Current mmWave-based datasets for HPE often feature only basic poses or rely on imprecise annotations, typically derived from pre-trained image-based HPE models using synchronized RGB images, which can limit the potential of derived models. This study introduces a pioneering approach to HPE by synergizing wearable motion capture sensors with mmWave radar technology to create a comprehensive and precise dataset tailored for enhancing HPE with mmWave radar. Leveraging this dataset, we develop an innovative deep learning framework specifically designed to explore the unique properties of radar signals for HPE. The performance of our proposed model is evaluated and compared with several well-known deep learning models. Extensive experimental results affirm the robustness of the dataset, establishing it as a rigorous benchmark for mmWave radar-based HPE. The proposed methodology demonstrates exceptional accuracy in estimating human poses from radar data, setting the stage for its application in environments where privacy and complexity are critical concerns.

“Travelling fires” discriminate a fire plume at the near-field and a hot smoke layer preheating the ceiling at the far-field, with the intent of ensuring the robustness of structural design for large compartments under realistic fires. Once the fire is “travelling”, the near-field has a leading edge representing the fire spread, and a trailing edge representing the burnout of the fuel. Despite the recognised effects of travelling fires, the mainstream of efforts into their effect on structural response has been limited to 2D models using the finite element method (FEM). This paper aims to identify the importance of slab inclusion with a 3D FEM structural model for steel-composite structures under travelling fires, assessed against the corresponding simplified 2D structural frame models (i.e., with and without effective slab in the 2D steel frame model). The first step is a comparative structural analysis of a prototype composite structure under various design fire scenarios, including standard fire, parametric fires and travelling fires. The role of the fire protection scheme for the simplified 2D models against the 3D model for the numerical predictions is also explored. It is found that the structural load path, and the potential structural failure mechanisms, could be fundamentally different between the 3D model and the simplified 2D models. Although the 2D frame model tends to predict larger deflections (i.e., more conservative) than the 3D model, it could also significantly underestimate the large internal forces from the beams, so that the connections' failure under travelling fires might be overlooked. Further, due to the simplification of the 2D models in omitting the significant stiffness contribution from the slab and the adjacent structural components, the effect of the fire protection is likely to be amplified. This may give misleading information on the performance-based structural fire design under different travelling fire scenarios. Hence, the 3D model can be considered as feasible but also necessary for structural fire analysis for travelling fires as a complement to the simplified 2D model approach.

Fire accidents in buildings are occurring and claiming thousands of lives each year. Due to various architectural designs, fire hazards would be unique to each building layout. This paper discusses how fire hazard varies with the arrangement of the fuel inside buildings. To comprehensively present the effect of fuel distribution on fire behaviour, results from large-scale experiments, bench-scale experiments, empirical correlations, and numerical studies are provided. In large-scale fire tests, two different cases of wood cribs were tested to demonstrate the effects of porosity on heat generation and fire spread behaviour. Due to the limitations of experimental conditions, the variation in heat release rate attributable to differences in fuel porosity and surface area has been also qualitatively investigated using a cone calorimeter test. To bring the gap between experimental observations and real-word scenarios, a numerical study is also performed. This study further explores the effects of fuel distribution (considering porosity and surface area of fuel throughout the compartment) and ventilation on fire spread beyond the fire compartment. The computational fluid dynamics (CFD) simulations show how the distribution of fuel in different ways can lead fire to spread beyond its origin, as observed in many fire accidents. The paper suggests that designers should consider such critical fire scenarios in performance-based design.

Designing and constructing a building is a complex process with many stakeholders, constraints, and requirements. Generally, a property development firm would hire an architect to produce a concept design that is meant to achieve the client objectives. After a few iterations, and if the development firm and client succeeded in obtaining initial funding for the project, they move on to hire design, construction, and possibly project management firms. The structural engineering designer is one of the various engineering teams involved in the project and is responsible for ensuring that the structure is designed with sufficient capacity to be safe under all expected loading conditions [1].

Typically, the structural engineer operates under the supervision of the architect and the project manager and liaises with the contractor and other engineering disciplines such as those dealing with fire, ventilation, plumbing, and electrical systems. Naturally, each of these engineering disciplines have their own objectives for their part of the project, and thus conflicts often arise and are resolved by interdisciplinary compromise and cooperation. Structural fire engineering is unique in its nature as it is, by definition, a cross-disciplinary enterprise that is concerned with both fire and structural behaviour. Unfortunately, current practice is that structural fire design is performed as a “check” rather than a part of a holistic design approach. This means that the structural fire engineer is often given the constraints of a mostly finished structural design that they need to ensure remains safe under any potential fire scenarios. The time given for such a critical undertaking is usually in the range of one to three weeks. This chapter will cover how automation of the most repetitive and time-consuming parts of structural fire engineering may enable the engineer to perform a thorough structural fire analysis within the tight limitations of realistic project timelines.

High traffic flow in a confined tunnel makes fire safety a critical issue. This paper proposed a digital twin framework for tunnel fire safety management in real-time, driven by dynamic sensor data and AIoT technologies. A deep learning model trained by the Transformer network and simulation dataset is used to predict real-time fire location and size. Then, the AI model is integrated into a 3D digital twin platform developed by the game engine Unity 3D. The performance of the proposed digital twin framework is demonstrated using numerical experiments and large-scale tunnel fire tests. Results show that the established AI model achieved promising accuracy in predicting fire location and power for both numerical and experimental data. The digital twin platform can also visualize the 3D fire scene that supports evacuation, firefighting, and emergency rescue. This research demonstrates the feasibility of using a 3D environment and digital twin in real-time fire safety management.

The diagrid structural system has seen significant uptake in medium to high rise buildings because of the architectural and resource advantages that it provides. These arise mainly as a result of flexibility in the topology that this particular structural solution provides. However, as a result of the way in which diagrids carry both horizontal and vertical loading, the diagrid structure itself may be susceptible to fire in ways which are not immediately obvious on the basis of our understanding of more traditional rectilinear construction forms. This study addresses this to improve our understanding of diagrid structures' response to fire. A comprehensive structural analysis on 45 fire load cases is conducted, considering different fire locations and sizes, using parametric design tools and finite element analysis software. The results provide valuable insights into the load redistribution and collapse mechanisms of diagrid structures in fire conditions.

The ‘travelling fire’ models have been used to describe the localised and travelling burning of uniform fuel bed in large open-plan building space. However, fuel is typically distributed non-uniformly in the built environment, leading to complex fire spread behaviours. This paper investigates the effect of non-uniform fuel load distribution on fire development in a sufficiently-ventilated space. A series of fire tests up to 3.5 MW with different wood crib layouts are categorised into two types, i.e., non-uniform and continuous, and non-uniform and discontinuous. The leading and trailing edges of the flame, height of flame, and fire spread rates are estimated using visual evidence. The non-uniform fuel load distribution fundamentally changes the spreading behaviour of fire. On a continuous wood crib, the fire spread rate and fire size are generally proportional to the fuel load density when the arrangement of the wood crib is similar. However, when wood cribs are discontinuous, the fire dynamics depend more on the localised burning size and gaps between fuels. Furthermore, very distinct fire behaviours were observed for fuel loads with different porosity. This work reveals the possible under-estimation of fire hazards of assuming evenly distributed fuel load and suggests considering design fire scenarios of non-uniform fuel load distribution in the performance-based fire safety design.

This study analyses the structural response of an aluminium reticulated roof structure that is constructed at Sichuan Fire Research Institute (Sichuan, China), and to be tested in fire. The structural fire behaviour under 960 localised fire scenarios is considered first, and then used to construct a database for training a modular artificial intelligence (AI) system for real-time forecasting. The system consists of several AI models, each of which predicts the displacement at a specific monitoring point. These individual predictions are then combined to generate a comprehensive forecast of the global structural-fire behaviour. The individual AI model utilized is a Long Short-Term Memory Recurrent Neural Network (LSTM RNN). The modular design allows different models to be modified or added as needed, making the system flexible and adaptable, and improving the accuracy and reliability of the predictions. The results demonstrate the effectiveness of the modular AI approach in accurately forecasting fire-induced structural collapses as indicated by the sensitivity the local models can have. The key objective of this research is to help to make informed decisions and prioritize efforts to minimize the risk of structural collapse in fire.

The role of “travelling fires” is to ensure the robustness of structural design with large compartments under realistic fires, having a fire plume at the near-field, and a hot smoke layer preheating the ceiling at the far-field. Once the fire travels, the near-field has a leading edge representing the fire spread, and a trailing edge representing the burnout of the fuel. Though well understood by its definition, the mainstream of efforts on travelling fires for structural response is limited to 2D finite element modelling (FEM). This paper aims to identify the importance of slab inclusion with a 3D FEM structural model for steel-composite structures under travelling fires, with a special emphasis on the significance of ignoring the slab structural capacity contribution from a 2D simplified structural model. The role of fire protection scheme for 2D model against the 3D model on numerical predictions was also explored. It was found that the structural load path, and the potential structural failure mechanisms could be fundamentally different between the 3D model and the 2D model, i.e., with or without slabs. Although the 2D model tends to predict larger deflections (i.e. more conservative) than the 3D model, it could also significantly underestimate the large internal forces from the beams, which might overlook the connections failure under travelling fires. Further, due to the simplification of the 2D model omitting the significant stiffness contribution from the slab, the effect of the fire protection is likely to be amplified. It may be misleading for the performance-based structural fire design under different travelling fire scenarios. Hence, the 3D model is likely to be considered as necessary and feasible for structural fire analysis for travelling fires as a complement to the 2D model approach.

Fire safety of modern buildings is crucial and the fire safety design of these buildings has been a challenging task. Large open-plan compartments are commonly designed in modern urbanisation and the fire behaviour in such compartments is different from the traditional knowledge built upon small compartment fire research. Various experimental studies have been performed to represent such fires to evaluate the structural fire resistance, which were accompanied by a series of travelling fire models to describe the non-uniform fire impact in large compartments. However, the localised fire models adopted in the latest travelling fire methodology were derived from localised fire tests of unconfined ceiling boundaries. The effects of smoke generation due to fire during various stages of the fire development are not included explicitly. This paper characterises the thermal impact on structural members from the localised fire tests and extends the simulation models and analysis approaches to localised fires in large compartments. Comparing the cases with soffits and without soffits, temperature differences of up to 150 °C are observed and the convective coefficient adopted as 35 W/m2K is too high. The work recommends to modify the current localised fire models to consider realistic fire sizes and smoke layer with the recognition of semi-confined conditions in large compartment fire scenarios. By including these aspects, it is possible to establish more universal design fire models to overcome the current limitations and to address the fire impact in compartments of various sizes and ventilation conditions.

First respondents to fires in structures face severe risks as both the fire and structural behaviour are unpredictable. While structural collapse may manifest some warning signs, these signs are not always easily identified which has led to the death of many fire fighters over the years. Both fire and structural fire simulation have come a long way and are now capable of assessing the thermomechanical behaviour of structures to a good degree of accuracy. However, such simulations take hundreds or thousands of engineering and computation hours. This paper explores performing these analyses a priori and using the generated database to train a recurrent neural network for real time prediction of potential failure. The analysis is performed on an aluminium reticulated roof structure that is constructed in Sichuan Fire Research Institute (Sichuan, China) and is expected to be tested to failure in fire in 2023. One hundred localised fire scenarios were used to cover the potential fire that will be used to induce the failure of the test roof. Heat transfer analyses for each section were then performed in OpenSEES followed by thermomechanical analysis in the same software. The generated results database was then cleaned and the data at several key locations were extracted and used to train a long short term memory recurrent neural network. The results of the predictions show that the artificial intelligence model can infer results with increasing accuracy the closer the structure is to failure. The real test of the accuracy of the model, however, will be during the fire experiment on the real structure. This would be the first time an artificial intelligence model for rapid forecasting of structural response in fire is built a priori and tested against a real fire.

In performance-based structural fire engineering, “travelling fires” is being gradually accepted as an important fire boundary condition. However, its application is still limited by uncertainties in the selection of different design travelling fire parameters, resulting from the lack of relevant experimental data and corresponding validated structural finite element models which can be used with advanced travelling fire methodologies, e.g. the Extended Travelling Fire Methodology (ETFM) framework. This paper aims to fill this gap through modelling a prototype steel-composite floor structure (representing a “slice” of a large open-plan office), to investigate its true structural response under a wide range of travelling fire scenarios, with an emphasis on considering the effect of concrete slab in a 3D finite element model, using LS-DYNA. To ensure the credibility of this numerical study, the model was first validated against the experimental data of the structural response from the Veselí Travelling Fire Test. In the parametric studies, 32 cases were examined to investigate the thermal and structural response, related to the selection of key design parameters for travelling fires (i.e. fire spread rates, fuel load densities and inverse opening factors (IOF)); fire protection (i.e. different fire protection schemes and required fire resistance rating (FRR)), and the effect of slab specification (i.e. thicknesses and steel reinforcements). It was found that solely satisfying the critical temperature and deflection criteria for the structural members might not guarantee a sufficient structural design for travelling fire scenarios, and it is suggested that the steel stress utilisation should also be examined. Compared with the IOF, it appears that the selection of fire spread rates and fuel load densities are likely to be more critical in identifying the worst travelling fire scenario for the structural response with fire protection. Moreover, the global structural response under travelling fire is also affected by the combination of fire protection (i.e. equivalent FRR in this paper) and fire spread rate. Under a “slow” travelling fire (e.g. 0.5 mm/s) with increasing FRR, the failure of structural elements during the cooling phase was prevented effectively; however, under a relatively “fast” travelling fire (e.g. 2.5 mm/s, 12.5 mm/s), increasing FRR may not always improve the fire performance of the structure. This work also indicates that steel reinforcement ratio has a greater influence on structural response than slab thickness under travelling fires. Furthermore, the 3D finite element model is very important for structural fire analysis, not only due to the more conservative internal force captured by the 3D model (i.e. reduced by over 80 % on the 2D model in our case) thereby reproducing the collapse triggered by the failure of the connection under fire in general, but also the 3D model was able to better represent the deflection and the “internal force reversal” caused by travelling fires.

Large open-plan compartment fires in modern buildings may exhibit a local burning region travelling across the floor plan as a ‘travelling fire’. This phenomenon has been found in the forensic investigations of fire accidents and in the large compartment fire tests. The fire impact in a large compartment is spatially non-uniform and time-variant, which can cause severe local damage to structural components. Advanced from the previous models assuming constant travelling, the natural fire model established in this paper comprises time-variant and test-based travelling behaviour models and localised fire models of various modes. It is demonstrated with the fast-spread Veselí fire test and the slow-spread Malveira fire test. A generic structural model is set up within OpenSees for fire to examine the thermal impact on structural members under various travelling fire scenarios of different travelling parameters, fire travelling directions, and beam sizes. Locally much higher thermal responses are represented after introducing behaviour models while adopting the same design fire load. Based on the work in this paper, a library of design fire models can be potentially enabled to examine the fire safety performance of structures regarding the realistic fire load and fire impact aiming for discovering unknown worse fire scenarios.

In the recent development of the performance-based structural fire design, the “travelling fire” methodology has been gradually accepted as a necessary fire boundary condition. However, its application is still limited by uncertainties in the selection of different design travelling fire parameters, which result from the lack of relevant experimental data and corresponding validated structural finite element models which can be used in advanced travelling fire methodologies, e.g. the extended travelling fire methodology (ETFM) framework. This paper aims to fill this gap through modelling a prototype steel-composite floor structure (regarded as a 'slice' of a large open-plan office), to investigate its true structural response under a wide range of travelling fire scenarios, with an emphasis on considering the effect of concrete slabs in a 3D finite element model, using LS-DYNA. To ensure the credibility of this numerical study, the model was validated against the experimental data from the Veselí Travelling Fire Test, and comparisons made with similar modelling efforts using Vulcan. In the parametric studies, eight cases were examined to investigate the structural response and the failure criteria, related to the selection of different key design parameters for the travelling fire within the ETFM framework, i.e. fire spread rate and inverse opening factor. It was found that solely satisfying the critical temperature (e.g. 550 o C for steel) and deflection criteria (e.g. beam span over 20) for the structural members might not guarantee a safe structural design for travelling fire scenarios, and it is suggested that the steel yielding stress status during the cooling phase in tension should also be examined. Compared to the inverse opening factor, it appears that the selection of fire spread rates is likely to be more critical in identifying the worst travelling fire scenario for the structural response with fire protection.