Full-scale Fire Tests Research Articles

Full-scale experimental study on fire characteristics induced by double fire sources in a two-lane road tunnel

The vehicle collisions, intense heat radiation and convection from flame and high-temperature smoke can easily cause double-source fire disasters in tunnels. In this paper, four full-scale fire experiments were performed in Jiangpu road tunnel to investigate the characteristics of double fire sources. The whole process of the ventilation velocity, heat release rate, longitudinal ceiling temperature, vertical temperature, carbon monoxide and flame deflection angle are analyzed. The results indicate that the interaction between the double fire sources affects the heat release rate and flame deflection angle and other parameters of each fire source. The ventilation and the fire source spacing can change the coupling state of thermal feedback mechanism and the shielding and entrainment effect of double fire sources. The fire source spacing affects the interaction mechanism and the smoke flow state between the ceiling jets of the double fire sources, which leads to the difference in the longitudinal ceiling temperature distribution between the double fire sources. According to the characteristics of smoke movement between double fire sources, the schematic diagrams of ceiling jets between double fire sources are established. The longitudinal ceiling temperature rise of double fire sources is analyzed from the perspective of steady state and unsteady state. The longitudinal ceiling temperature data of full-scale fire tests is compared with the prediction models proposed by other researchers. The “barrier effect” phenomenon was also observed in the double-source fire tests, especially in the vertical smoke temperature. The findings contribute to deepening the understanding of the fire characteristics of the double-source fire disasters.

Validating hybrid fire testing with full-physical twin experiments

Real fire incidents show that structural systems have specific fire-induced redundancies that make them perform better than classical structural fire analysis predicts. Properly validated hybrid fire testing has the potential to tap into such redundancies for designs. In this study, we conceived and implemented a comprehensive and novel physics-based validation strategy for hybrid fire testing. We developed a laboratory-scale thermo-mechanical proof-of-concept problem that is representative for structural systems exposed to compartment fires. We solved the proof-of-concept problem using our novel thermo-mechanical hybrid solution procedure (Schulthesset al.2020Comput. Struct.238, 106301 (doi:10.1016/j.compstruc.2020.106301)) and compared the resulting hybrid model response against the results from a full-physical laboratory set-up of the same proof-of-concept problem, which we call a full-physical twin experiment. Full-physical twin experiments constitute the top layer of a suite of benchmark tests any specific hybrid fire testing procedure must pass to qualify not only as theoretically accurate and correctly functioning but also (and more importantly) as physically sound and able to yield realistic simulation results. This paper delivers such a first-of-its-kind physics-based validation, and in doing so, the first comprehensively validated method for hybrid fire testing—a method that now allows fire test facilities to conduct meaningful full-scale hybrid fire tests of entire structural systems.

Modeling evaluation for fire resistance design of rail car floor assembly

This paper is prepared to report the engineering practice by a Chinese railcar manufacture in a railcar design process for a Metro system in U.S. The fire resistance of rail car floor systems is considered as one of the important fire protection features on the railcars operated in U.S., which provides fire separation between the equipment installed under the floor and the passengers insider railcar. In this study, a pragmatic approach was developed to numerically evaluate the fire resistance of rail car floor assemblies and provide insights for necessary design modifications. Finite element analysis (FEA) was applied to assess the fire resistance performance of a rail car floor assembly designed for a metro railway system in the U.S. An optimization algorithm was applied to obtain the thermal properties of intumescent coating. FEA analysis results were applied to assist the design modifications so that the floor assembly successfully satisfies the current requirement and passes the ASTM E119 fire resistance test. The FEA modeling details and heat transfer analysis results are presented. It is also shown that the model predictions agree conservatively well with the full-scale fire resistance test data.

Numerical Investigations on the Influencing Factors of Rapid Fire Spread of Flammable Cladding in a High-Rise Building

This paper investigates aluminium composite panels (ACPs) to understand the fire behaviour of combustible cladding systems under different fire scenarios. A fire dynamics simulator (FDS) is used to develop the numerical model of full-scale fire tests of combustible cladding systems using the procedures of the British BS 8414.1 standards. The results obtained from the FDS models are verified with test data. Seven test scenarios are investigated with four distinct parameters, i.e., cavity barrier, air-cavity gap, panel mounting (with and without joining gaps between the panels), and material combustibility qualities. A critical air-cavity gap (50–100 mm) is established at which maximum fire spread is noticed. Furthermore, variations in the cavity barrier, panel mounting, and material combustibility significantly impact the rapid fire spread of ACP cladding systems and the internal failure criterion. The results from the present study can serve as a basis for future research on the full-scale fire-test development of combustible ACPs.

Structural behaviour of a novel modular cellular steel beam system at elevated temperatures based on large-scale experimental testing and numerical modelling

This paper presents experimental and numerical results of a modular structural steel system, encompassing non-composite cellular beams, that was tested using a 1-h standard fire scenario while loaded. The modular system consists of a 5.66 m × 3.8 m rectangular steel frame, with a sandwich decking (SD) system attached, which comprises of a) profiled steel decking, b) fibre cement, and c) calcium silicate boards. The SD system is hung from the underside of the horizontal structural members to provide inherent fire protection to the steel beams from the bottom and is the load-bearing component of the flooring. The aim of the experiment was to determine the structural systems fire resistance because its unusual geometry renders existing full-scale fire test data inapplicable. Novel temperature and deflection data for the system are obtained from the large-scale experiment conducted, which are used to validate numerical finite element analysis models on a single element and global model basis. The numerical and experimental data are compared and show suitable correlation, and highlight some unusual behaviour regarding vertical deformations. From the numerical models and experimental data, it is shown that (a) the structural steel system typically behaves well due to the limited temperature rise as a consequence of the attached SD system, (b) limited plasticity occurred in the system, (c) small axial forces are induced due to the flexibility of the structure, and (d) the system is heavily reliant upon the integrity of the sandwich decking system it supports. Failure of the SD would lead to loss of compartmentation, and potentially structural failure.

Smart real-time forecast of transient tunnel fires by a dual-agent deep learning model

Disastrous fire accidents occurred in the tunnel is fatal and destructive, which may pose great threats to the trapped person and firefighters. However, fire in a confined tunnel can develop rapidly and spread between vehicles, so it is difficult to forecast the fire development and possible catastrophic incidents. This work develops an intelligent model to predict the fire information, temperature distribution and critical events in real-time based on artificial intelligence algorithms. The numerical model is first validated by the full-scale tunnel fire test, and then a numerical database of 300 transient tunnel-fire scenarios is established under various initial fire locations, fire sizes, fire growth and spread rates, and ventilation conditions. The proposed dual-agent deep-learning model combining the Long Short-term Memory (LSTM) model and Transpose Convolution Neural Network (TCNN) is trained with the database. With the input data of on-site temperature sensors, the dual-agent model can forecast transient fire scenarios with changing location and size 30 s in advance. This study demonstrates the feasibility of the AI model in identifying and forecasting the rapid-changing fire scenarios inside a tunnel in smart firefighting practices.

Numerical modelling and fire testing of gypsum plasterboard sheathed cold-formed steel walls

Gypsum plasterboards are used in Light-gauged Steel Framed (LSF) walls as the primary fire-resistant material. In addition to thermal protection, they provide restraints to the cold-formed steel studs at the screw locations and improve the load-bearing capacity. In this study, three full-scale standard fire tests were conducted first to investigate the thermal and structural behaviour of LSF walls in fire. Close examination of the plasterboard joint opening up and plasterboard fall-off phenomena showed that most of the plasterboard joint compound fell-off after 17 min of fire exposure and the joint gap gradually widened afterwards. A multi-step heat transfer finite element (FE) model was developed incorporating the physical changes observed during the fire tests and validated using the test results. The important time–temperature profiles obtained from this study and past literature were compared, and idealised time–temperature profiles of wall studs were developed for use in structural FE models. Past studies involving elevated temperature structural FE models considered mainly the in-plane restraints provided by plasterboard sheathing. Hence the effects of their out-of-plane restraints were investigated using structural FE models and fire tests, and suitable out-of-plane restraint values were proposed for numerical analysis. This study has shown that out-of-plane restraints significantly reduced the lateral deflections of LSF walls and improved their fire resistance levels (FRL) when double layers of plasterboards were used. However, excessive out-of-plane restraints could adversely affect the FRL. Overall, this research has used the fire test results to enhance the understanding of the thermal and structural behaviour of LSF walls and provided useful data and recommendations for more accurate thermal and structural modelling of LSF walls.

A coupled hybrid numerical study of tunnel longitudinal ventilation under fire conditions

This paper presents the validation of a coupled hybrid (1D/3D-CFD) modelling methodology, using FDS version 6.7.5, for the first time, with full-scale fire tests. Real fire conditions of the Runehamar tests with maximum heat release rates of 6 MW, 66 MW, and 119 MW are compared by assessing temperature profiles, centreline velocity, backlayering lengths, and maximum temperatures at different locations both upstream and downstream from the fire source. An expression to evaluate the length of the 3D domain where the fire is located is successfully assessed. Also, a pressure boundary condition at one of the portals is suggested to predict more precisely the inner flow conditions. The temperature profiles are accurately predicted with time-averaged differences lower than 20% beyond 40 m downstream from the fire source in the three tests. Furthermore, with the coupled hybrid approach, the backlayering length is estimated accurately with the fire of 66 MW and underestimated in the 6 MW and 119 MW fires, i.e. a maximum difference lower than 4% of the total tunnel length. The validated proposed methodology allows accurate predictions of temperature for tunnel fires and reduces the computational cost between 27% and 75% with respect to a full-CFD numerical model.

Thermal behavior of composite slabs with closed profiled steel decking and recycled aggregate concrete in fire

This paper presents experimental and numerical investigations on the thermal performance of composite slabs comprised of closed profiled steel decking and recycled aggregate concrete (RAC). Full-scale fire tests were performed on four RAC composite slabs to obtain the temperature distribution exposed to standard fire (ISO 834) for a duration of 90 min. Results indicated that the temperatures within composite slabs generally declined with the increasing coarse recycled aggregate (CRA) content. Due to the shielding effect of the concrete, the temperature of the decking rib was much lower than that at the decking soffit. Finite element (FE) modelling was then conducted and parametric investigation was carried out to analyze the influences of the CRA content, the moisture content and the rib height on the temperature distributions of the composite slabs. Finally, simplified formulas were developed to predict the cross-section temperature in RAC composite slabs, which yielded good agreements with the test and modelling results.

A Quantitative Analysis of the Fire Hazard Generated from Hydrogen Fuel Cell Electric Vehicles

There is a lack of information on (i) the potential fire load of new green-technology vehicles, (ii) flame spread behavior, (iii) thermal impacts on high-pressure hydrogen storage vessels (HSVs) and lithium-ion batteries (LIBs) during fuel cell electric vehicles fires (FCEVs), and (iv) thermal damage to adjacent vehicles and upper structural members during FCEV fires occurring in civil structures, such as underground spaces, multi-story parks, and tunnels. In view of this, a full-scale fire test was conducted in this study to quantitatively assess the fire risk of hydrogen FCEVs. Large-scale cone calorimetry was used to quantify the thermal intensity released from the FCEV fire. The flame spreading behavior through an FCEV with HSVs and LIBs was observed using the thermocouples installed. Changes in the temperature and irradiance around the FCEV fire were also measured using an instrumented test rig. The peak heat release rate, total heat released, and fire growth rate were observed to be 5.99 MW, 11.8 GJ, and 0.0055 kW/s², respectively. The temporal point of hydrogen gas release from the HSVs' thermal pressure relief device (TPRD) was estimated to be 16.2-26.2 min. The initiation of thermal runaway of LIBs was deduced from the temperature-time profiles of the LIB modules and their metal housing approximately 22.2 min after HCEV ignition. Moreover, FCEV fires could thermally impair adjacent upper structural members by 800 ℃ combustion gas for at least 13 min and emit a median heat flux of 27.2 kW/m² (peak heat flux of 76.5 kW/m²) to adjacent vehicles. The measurements and findings obtained from this study can contribute to the evaluation of and further studies on newly emerging fire hazards.

An Improved Updatable Backpropagation Neural Network for Temperature Prognosis in Tunnel Fires

Because it is impossible to predict the temperature in advance, specific fire scenes (fire type, fire location, tunnel geometry, etc.) are unknown in traditional tunnel fire research. To address this difficulty, this work developed a novel algorithm to achieve temperature prognosis in tunnel fires that includes an updatable backpropagation (BP) neural network and a smoothing procedure. The data-driven algorithm is not limited to a specific fire scene, which makes it easy to fit real complex tunnel fire disasters. In addition, a full-scale fire test was conducted and utilized to verify the algorithm. Two innovations, including the updatable BP neural network and the smoothing procedure, made the predicted results match well with the experimental results. We can achieve a real-time precise temperature prediction 20 s in advance at a high accuracy of about 85.6%. If there is no sudden external factor intervention, the accuracy is about 99.4%. The algorithm provides an effective numerical tool for early fire warning and firefighting decision making that can address the temperature prognosis of tunnel fires.

Analysis of fire-induced progressive collapse for topside structures of a VLCC-class ship-shaped offshore installation

ABSTRACT This study extends the authors’ previous numerical and experimental studies simulating the progressive collapse of steel stiffened-plate structures in fire events (Paik JK, Ryu MG, He KH, Lee DH, Lee SY, Park DK, Thomas G. 2021a. Full-scale fire testing to collapse of steel stiffened plate structures under lateral patch loading (part 1) – without passive fire protection. Ships Offsh Struct. 16(3):227–242; Paik JK, Ryu MG, He KH, Lee DH, Lee SY, Park DK, Thomas G. 2021b. Full-scale fire testing to collapse of steel stiffened plate structures under lateral patch loading (part 2) – with passive fire protection. Ships Offsh Struct. 16(3):243–254; Ryu MG, He KH, Lee DH, Park SI, Thomas G, Paik JK. 2021. Finite element modeling for the progressive collapse analysis of steel stiffened-plate structures in fires. Thin-Walled Struct. 159:107262). Specifically, this study demonstrates that the computational models developed in the earlier studies can be applied to the analysis of the heat transfer and fire-induced progressive collapse behaviour of the topside structures of a ship-shaped offshore installation. To this end, a hypothetical VLCC-class floating, production, storage and offloading (FPSO) unit hull structure is considered, and transient thermal elastic-plastic large-deformation finite element models are used. The novelty of this study and its contribution to industry are the development of a practical procedure to ensure the fire safety of large-scale steel-plated structures with complex geometries.

Full-scale fire tests in the underwater tunnel section model with sidewall smoke extraction

The Hong Kong–Zhuhai–Macau Bridge (HZMB) is a 55-km bridge-tunnel system, including a 6.7-km undersea tunnel that adopts the sidewall smoke extraction system. To evaluate the potential tunnel fire hazards, a 1:1 full-scale HZMB tunnel section model (16 m × 7.2 m × 150 m) was constructed, and eight full-scale tunnel fire tests were conducted with the sidewall smoke extraction. The temperature distribution and smoke movement under different vent arrangements and fire sizes (1.2–6.6 MW) were quantified. Results indicated that the fire HRR was mainly affected by the size of the liquid-fuel pool but insensitive to the arrangement of ventilation. The correlation between HRR and diesel pool-fire area can be fitted by a linear function of HRR=1.24AF-0.87 MW. The sidewall smoke extraction generated a tilted fire plume and non-uniform temperature distribution at the transverse direction, whereas the temperature decay still followed the exponential decay for the far fire field region. The decay factor increases with the increase of the HRR and increases when distributing the ventilation capability into two vent groups. A relatively slow smoke motion (0.8–1.2 m/s) and good smoke stratification were demonstrated in the tests, indicating a robust condition for safe evacuation. This research deepens the understanding of fire and smoke characteristics in tunnels with the sidewall extraction and highlights the importance of full-scale test data in the development of the smart tunnel-fire protection system.

Fire Performance of FRP-RC Flexural Members: A Numerical Study.

Fiber-reinforced polymer (FRP) bars are increasingly used as a substitute for steel reinforcements in the construction of concrete structures, mainly due to their excellent durability characteristics. When FRP bar-reinforced concrete (referred to as FRP-RC for simplicity) members are used in indoor applications (e.g., in buildings), the fire performance of FRP-RC members needs to be appropriately designed to satisfy safety requirements. The bond behavior between the FRP bar and the surrounding concrete governs the composite action between the two materials and the related structural performance of the FRP-RC flexural member that will be affected when exposed to fire. However, there is a lack of reliable numerical models in the literature to quantify the effect of bond degradations of the FRP bar-to-concrete interface at high temperatures on the fire performance of FRP-RC flexural members. This paper presents a three-dimensional (3D) finite element (FE) model of FRP-RC flexural members exposed to fire and appropriately considers the temperature-dependent bond degradations of the FRP bar-to-concrete interface at high temperatures. In addition, the thermal properties of concrete and FRP bars are considered in the heat transfer analysis to predict the cross-sectional temperatures of the FRP-RC members under fire exposure. In the FE model, the mechanical properties and constitutive laws of concrete and FRP bars at high temperatures in addition to the bond degradations between them have been properly defined, thereby accurately predicting the global and local structural responses of the FRP-RC members under fire exposure. The proposed FE model has been validated by comparing the FE predictions (both temperature and midspan deflection responses during fire exposure) and the full-scale fire test results reported in the literature. The validated FE model is then used to study the effects of bond degradations on the global and local structural responses of the FRP-RC members under fire exposure. It is proved that the temperature-dependent bond degradations need to be considered to achieve accurate predictions of the failure mode and deflection responses.

Study on real-time heat release rate inversion for dynamic reconstruction and visualization of tunnel fire scenarios

This study proposes a framework integrating tunnel fire knowledge with the machine learning approach to provide key fire parameters and reconstruct tunnel fire scenarios. The machine learning approach establishes mapping rules between tunnel ceiling temperatures measured by Fiber Bragg Grating (FBG) system and the real-time heat release rate (HRR) based on the tunnel fire database. The database employed in training and testing algorithms was generated by numerical simulations and full-scale tunnel fire tests, respectively. In addition, the HRR database establishment procedures, hyperparameter selection of machine learning algorithms and test dataset selection are systematically analysed. The real-time HRR inversion performance of four machine learning methods (support vector regression (SVR), random forests (RF), multilayer perceptron (MLP), long short-term memory network (LSTM)) and two tunnel fire knowledge methods (maximum ceiling gas temperature, smoke back-layering length) are evaluated. It is shown that the LSTM method provides the best prediction accuracy on full-scale tunnel fire test datasets, and the RF method is found to be most resilient despite the loss of partial temperature data due to the failure of temperature sensors. The corresponding models have been verified by the full-scale tunnel fire tests, and can provide the scientific decision support for intelligent fire-fighting.

Experimental and Numerical Investigations on Fire-Resistance Performance of Precast Concrete Hollow-Core Slabs

In this study, full-scale fire tests and finite element (FE) analyses are conducted to investigate the fire resistance performance of hollow-core slabs (HCSs) manufactured using the extrusion method. The deflection of the HCS specimens and the temperature distribution in the section according to the fire exposure time are measured and analyzed comprehensively, and the test results are compared with the FE analysis results. In addition, parametric analyses are conducted on 21 cases with the HCS depth, span length, hollow ratio in a section, cover thickness of concrete, and load ratio (i.e., the ratio of the external load to the ultimate load) as variables, based on which the fire resistance performance of the HCS according to each variable is investigated. The analysis results show that the load ratio is a key factor governing the fire resistance behavior of HCSs, whereas the effects of the cover thickness of concrete and the hollow ratio in a section are relatively slight within the range of variables examined in this study.

Novel conventional and modular LSF wall panels with improved fire performance

Fire performance of Light-gauge Steel Frame (LSF) constructions is being extensively investigated recently, due to the critical behaviour of cold-formed steel structures at elevated temperatures. Among the many design parameters involved with LSF constructions, the effect of cavity insulation inside LSF walls at different ratios on the Fire Resistance Level (FRL) has not been addressed yet. Hence, Finite Element Models (FEMs) were developed for the LSF walls to simulate the full-scale fire tests conducted applying the standard fire temperatures, where the Finite Element Analyses (FEA) results were very well agreeing with the experimental results. Thereafter, the validated FEMs were extended to study the fire performance of the conventional and modular LSF wall systems with different cavity insulation ratios, where 0.4 cavity insulation ratio was found to be most efficient when structural FRL is of concern while producing satisfactory energy performance at reduced material costs. To calculate the structural FRLs of conventional and modular, single and double plasterboard layers sheathed LSF walls, 4 empirical models have been proposed where more than 97% accuracy was achieved. Moreover, incorporating back blocking panels and discontinuous insulation options, several novel conventional and modular LSF walls have been proposed with up-to 70% improvement in structural FRL.

Bridge fires in the 21st century: A literature review

Bridge failures due to fires are more common than failures due to extreme weather or earthquakes. Yet, unlike wind and earthquake loading, fire does not receive the same level of attention. Major 21st Century fire incidents involving bridges are listed and discussed. Various methods by which fire could be considered in design are reviewed and discussed. Sources of fire test data, which include only one full scale fire test to-date, are provided. It is hoped that by considering these factors, codes, standards and engineering practice could be updated to include consideration of fire in routine bridge design.

Fire resistance of external LSF walls with corrugated steel cladding

This paper presents the details of full-scale standard fire tests of external light-gauge steel-framed (LSF) walls with corrugated steel cladding exposed to fire on the external side. Corrugated steel cladding of 0.42mm thickness is generally used in roof and wall systems of buildings. In this study, it is used as the wall cladding of external LSF walls and as a lightweight cladding replacement to the combustible aluminium composite panels. A detailed investigation was undertaken to evaluate and understand the fire and energy performance of corrugated steel clad external LSF walls, which included (a) thermal property tests of two different types of Earthwool insulation (glass fibre insulation) used in wall systems, (b) full-scale (3m×3m) load bearing standard fire tests of two external LSF wall systems – first with cavity insulation and the second with external insulation and (c) THERM modelling of the tested walls. Steel cladding prevented direct exposure of fire on plasterboards and hence delayed the temperature rise and increased the failure time. Overlaps along the vertical edges of steel cladding played a critical role as gaps formed during the tests. The two external LSF wall systems achieved fire resistance levels (FRLs) in excess of two hours (122min and 158min) with improvements greater than 40% due to the addition of thin steel cladding. Replacing cavity insulation with external insulation improved the FRL by about 30% and also its effectiveness in terms of energy efficiency.

Sequentially coupled structural modelling of LSF floor-ceiling systems

Fire resistance levels provide a standardised measurement of building elements' fire resistance under structural, integrity and insulation criteria, and are usually obtained from standard full-scale fire tests. However, these tests consume excessive time and money and thus the use of validated advanced numerical models is preferred. This paper presents the details of a sequentially coupled structural modelling study of LSF floor-ceilings made of Lipped Channel beam (LCB) and rivet fastened Rectangular Hollow Flange Channel beam (RHFCB) section joists used in eight different floor-ceiling configurations, and its results. Ambient temperature structural finite element (FE) models of LCB and RHFCB joists were developed first and validated using experimental results. Full scale fire test results of LCB floor system were then used to validate a structural FE model developed and analysed using a sequentially coupled approach utilising the time-temperature profiles from the same fire test. Finally, using the validated sequentially coupled structural FE models, the effects of a range of influential parameters such as joist types and floor-ceiling configurations were investigated. The results of structural fire resistance/failure times versus load ratio showed that the new RHFCB joists gave only minor improvements, however, they provided superior load bearing capacities. Fire resistance improved significantly when more gypsum plasterboard layers were used. The use of thin steel sheathing also improved the failure times, and is recommended as the fire exposed layer due its ability prevent plasterboard fall-off. Finally, suitable critical mid-web temperatures are proposed for predicting the structural fire resistance times of LSF floor-ceiling systems.