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The exterior application of fire-retardant (FR) timber necessitates it to have high durability because of the possibility to be exposed to rainfall. In this study, water-leaching resistance of FR wood has been imparted by grafting phosphate and carbamate groups of the water-soluble FR additives ammonium dihydrogen phosphate (ADP)/urea onto the hydroxyl groups of wood polymers via vacuum-pressure impregnation, followed by drying/heating in hot air. A darker and more reddish wood surface was observed after the modification. Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, solid-state 13C cross-polarization magic-angle-spinning nuclear magnetic resonance (13C CP-MAS NMR), and direct-excitation 31P MAS NMR suggested the formation of C–O–P covalent bonds and urethane chemical bridges. Scanning electron microscopy/energy-dispersive X-ray spectrometry suggested the diffusion of ADP/urea into the cell wall. The gas evolution analyzed by thermogravimetric analysis coupled with quadrupole mass spectrometry revealed a potential grafting reaction mechanism starting with the thermal decomposition of urea. Thermal behavior showed that the FR-modified wood lowered the main decomposition temperature and promoted the formation of char residues at elevated temperatures. The FR activity was preserved even after an extensive water-leaching test, confirmed by the limiting oxygen index (LOI) and cone calorimetry. The reduction of fire hazards was achieved through the increase of the LOI to above 80%, reduction of 30% of the peak heat release rate (pHRR2), reduction of smoke production, and a longer ignition time. The modulus of elasticity of FR-modified wood increased by 40% without significantly decreasing the modulus of rupture. Validerad;2023;Nivå 2;2023-04-21 (joosat);Funder: OP RDE (Grant no.CZ.02.1.01/0.0/0.0/16_019/0000803); CT WOOD, Luleå University of TechnologyLicens fulltext: CC BY License

The reasons behind the occurrence of a second/end peak heat release rate (PHRR) during wood combustion under radiative heating were determined. Effects of the type of rear material, wood thickness, char progression, and its microstructure, as well as moisture content/transport in spruce wood, were studied. Rear materials used were insulating Kaowool, conducting steel, and the same wood but physically separated from test specimen by aluminium foil. The intensity of the second/end PHRR with Kaowool was almost 50% more than that of the sample with steel. Thus, the second/end peak is governed by the boundary condition defined by the rear material, which determines the heat losses at the rear side of the specimen and consequently the temperature of the specimen. Higher specimen temperature enhances the pyrolysis rate, thereby causing the second/end PHRR. The appearance times and values of the second/end PHRR for 30, 20, and 10 mm wood were 1740 s/78 kWm−2, 685 s/134 kWm−2, and 450 s/160 kWm−2, respectively. Char progressed to the rear of the samples even with a thin (8 mm) conductive steel substrate. Cracks in char grew almost three times wider during the second/end PHRR compared to the sample with no second/end peak. Char cracking had no significance on the time of occurrence of the second/end PHRR but affected the overall heat release. High moisture content reduced the charring rate and delayed the time of occurrence of the second/end PHRR as more water was needed to undergo a phase change, requiring a higher amount of energy. Validerad;2023;Nivå 2;2023-06-29 (sofila)

The microscale combustion calorimeter (MCC) is considered to be the most commonly used small-scale fire experiment in material research. It was developed by Richard E. Lyon and Richard Walters from the Federal Aviation Administration and has existed for over two decades. During this period, the apparatus has been used to obtain combustion properties for a wide range of materials as well as screening flame retardants for the production of fire-resistant materials. MCC separately simulates the pyrolysis and combustion stages of a burning process in a non-flaming test and uniquely measures the heat release capacity. Since its development, several significant modifications have been made in the apparatus to rectify some of the sources of error. This research reviews the literature on microscale combustion calorimetry. It covers the principles of operation applications and limitations, prediction methods and mathematical models for estimation as well as the modifications made in the design. Furthermore, the relationship between MCC parameters and measurement from other fire experiments are outlined. Lastly, the experimental methods designed on the basis of microscale combustion calorimetry have been briefly described.

This study seeks to discover the change of cloud's expansion rate with self-designed shock wave dispersion system. Transmission, diffraction and reflection could be observed intuitively when shock waves passed through solid particle layers. Results show that the longitudinal motion of particle group greatly influenced cloud's volume growth, thus, the maximum rate of longitudinal expansion of clouds was almost twice that of lateral expansion. The cloud growth rate and volume acceleration increased with smaller particle size, thicker particle layer and stronger shock wave intensity. Also, the expansion rate initially had a drastic decrease, small particles made clouds volume acceleration unstable and experienced a subsequent swift rise. Shock wave intensity influenced diffraction and reflection formation waves as well as the cloud's shape and expansion rate. This study therefore proposed a controlling model for cloud's expansion rate, which could illustrate differences between acceleration stage of dynamic action and deceleration stage of resistance action.

The study is influenced by the significant progress made in the field of hydrodynamics and heat transfer enhancement of Taylor flow in vertical and horizontal pipelines. It maps the hydrodynamics and thermal properties of Taylor flow using 752 scientific articles published in refereed journals, extracted from the Web of Science Core Collection (WoSCC), using bibliometric analysis. The study identifies clusters that constitute the intellectual structure of the study domain, and investigates their linkages, by incorporating all citations from the Science Citation Index (SCI) from 2000–2021. The study highlights the most active, impactful, and influential parameters surrounding Taylor flow research. This analysis is critical for expanding our understanding of the intellectual network and identifying new research directions.

Guanyl-urea phosphate (GUP) was introduced into furfurylated wood in order to improve fire retardancy. Modified wood was produced via vacuum-pressure impregnation of the GUP–furfuryl alcohol (FA) aqueous solution, which was then polymerized at elevated temperature. The water leaching resistance of the treated wood was tested according to European standard EN 84, while the leached water was analyzed using ultra-performance liquid chromatography (UPLC) and inductively coupled plasma–sector field mass spectrometry (ICP-SFMS). This new type of furfurylated wood was further characterized in the laboratory by evaluating its morphology and elemental composition using optical microscopy and electron microscopy coupled with energy-dispersive X-ray spectrometry (SEM-EDX). The chemical functionality was detected using infrared spectroscopy (FTIR), and the fire resistance was tested using cone calorimetry. The dimensional stability was evaluated in wet–dry soaking cycle tests, along with the mechanical properties, such as the Brinell hardness and bending strength. The fire retardancy of the modified furfurylated wood indicated that the flammability of wood can be depressed to some extent by introducing GUP. This was reflected in an observed reduction in heat release rate (HRR2) from 454.8 to 264.9 kW/m2, without a reduction in the material properties. In addition, this leaching-resistant furfurylated wood exhibited higher fire retardancy compared to conventional furfurylated wood. A potential method for producing fire-retardant treated furfurylated wood stable to water exposure has been suggested.

Guanyl-urea phosphate (GUP) was introduced into furfurylated wood in order to improve fire retardancy. Modified wood was produced via vacuum-pressure impregnation of the GUP-furfuryl alcohol (FA) aqueous solution, which was then polymerized at elevated temperature. The water leaching resistance of the treated wood was tested according to European standard EN 84, while the leached water was analyzed using ultra-performance liquid chromatography (UPLC) and inductively coupled plasma-sector field mass spectrometry (ICP-SFMS). This new type of furfurylated wood was further characterized in the laboratory by evaluating its morphology and elemental composition using optical microscopy and electron microscopy coupled with energy-dispersive X-ray spectrometry (SEM-EDX). The chemical functionality was detected using infrared spectroscopy (FTIR), and the fire resistance was tested using cone calorimetry. The dimensional stability was evaluated in wet-dry soaking cycle tests, along with the mechanical properties, such as the Brinell hardness and bending strength. The fire retardancy of the modified furfurylated wood indicated that the flammability of wood can be depressed to some extent by introducing GUP. This was reflected in an observed reduction in heat release rate (HRR

Wood-based composites such as wood plastic composites (WPC) are emerging as a sustainable and excellent performance materials consisting of wood reinforced with polymer matrix with a variety of applications in construction industries. In this context, wood-based composite materials used in construction industries have witnessed a vigorous growth, leading to a great production activity. However, the main setbacks are their high flammability during fires. To address this issue, flame retardants are utilized to improve the performance of fire properties as well as the flame retardancy of WPC material. In this review, flame retardants employed during manufacturing process with their mechanical properties designed to achieve an enhanced flame retardancy were examined. The addition of flame retardants and manufacturing techniques applied were found to be an optimum condition to improve fire resistance and mechanical properties. The review focuses on the manufacturing techniques, applications, mechanical properties and flammability studies of wood fiber/flour polymer/plastics composites materials. Various flame retardant of WPCs and summary of future prospects were also highlighted.

Wood is undeniably the most useful and readily available natural raw material. However, the susceptibility of wood products to fire is one of the crucial challenges faced in the wood industry. The fire behaviour of wood is a very complex phenomenon due to the different constituents and their independent reactions to fire. This article presents a thorough overview of the flammability stages of wood. It covers pyrolysis, thermal oxidative decomposition, ignition, combustion and heat release as well as flame extinction mechanisms. In the area of flame retardancy, conventional wood fire retardants, nanocomposites fire retardants and wood modification processes are investigated. Factors such as wood species, moisture content, density, experimental conditions such as external heat flux, heat exposure time, wood permeability and porosity are some of the deterministic parameters characterising the fire behaviour. This paper is a one-stop-shop for researchers analysing wood flammability due to the inclusion of all aspects pertaining to the burning of wood.

Soft-computing techniques for fire safety parameter predictions in flammability studies are essential for describing a material fire behaviour. This study proposed, two novel Artificial Intelligence developed models, Multivariate Adaptive Regression Splines (MARS) and Random Forest (RF) methods, to model and predict peak heat release rate (pHRR) of Polymethyl methacrylate (PMMA) from Microscale Combustion Calorimetry (MCC) experiment. From the statistical analysis, MARS presented the highest coefficient of determination (R2) values of (0.9998) and (0.9996) for training and testing respectively, with low MAD, MAPE and RMSE values. Comparatively, MARS outperformed RF in the predictions of pHRR, through its model algorithms that generated optimized equations for pHRR predictions, covering all non-linearity points of the experimental data. Amongst the input variables (sample mass, THR, HRC, pTemp and pTime), heating rate (β), highly influenced pHRR outcome predictions from MARS and RF models. However, to validate the performance and applicability of the proposed models. Results of MARS and RF were benchmarked with that from Artificial Neural Network (ANN) methods. The MARS and RF models observed the least error deviation when compared with pHRR results for PMMA from the ANN models. This study therefore, recommends the adoption of MARS and RF in the predictions of flammability characteristics of polymeric materials.

Predictions of both combustible material flammability and heat release parameters have been long goals in fire safety research, for its complex heat, mass transfer and chemical reaction process in gas phase. In this study, neural network method is employed to predict materials flammability considering its wide application in predicting key properties of engineering problems. The use of group method of data handling (GMDH) and feed forward back-propagation (FFBP) neural networks in predicting the heat of combustion and heat release capacity (HRC) from microscale combustion calorimetry has been examined. The study presented models with excellent predictability though GMDH out-performed FFBP. The deviation of the predicted and measured HRC data from this study was compared with the results of other predictive modelling techniques used in flammability studies. The GMDH neural network results presented the least mean deviation of 4.01 signifying accurate predictions. Hence, this study proposed the use of GMDH in predicting flammability characteristics of materials.

Composites can be divided into three groups based on their matrix materials, namely polymer, metal and ceramic. Composite materials fail due to micro cracks. Repairing is complex and almost impossible if cracks appear on the surface and interior, which minimizes reliability and material life. In order to save the material from failure and prolong its lifetime without compromising mechanical properties, self-healing is one of the emerging and best techniques. The studies to address the advantages and challenges of self-healing properties of different matrix materials are very limited; however, this review addresses all three different groups of composites. Self-healing composites are fabricated to heal cracks, prevent any obstructed failure, and improve the lifetime of structures. They can self-diagnose their structure after being affected by external forces and repair damages and cracks to a certain degree. This review aims to provide information on the recent developments and prospects of self-healing composites and their applications in various fields such as aerospace, automobiles etc. Fabrication and characterization techniques as well as intrinsic and extrinsic self-healing techniques are discussed based on the latest achievements, including microcapsule embedment, fibers embedment, and vascular networks self-healing. Validerad;2023;Nivå 2;2023-01-19 (sofila);Funder: Navajo Technical University, USA

Surface ablation and in-depth temperature distribution of the charring material are the key properties of the thermal protection system in re-entry vehicles subjected to aerodynamic heating. To investigate the factors affecting the ablation performance of charring materials, the influence of decomposition reaction and surface recession on ablation was added to the heat conduction and surface energy balance equation, to comprehend the phenomenon of surface material removal. The model developed in this study was verified by comparing with results from traditional finite difference method. Furthermore, the effects of external constant heat flux, initial material thickness, and heating time on ablation were determined and discussed on temperature, surface recession, and density distribution. The change trend of the external heat flux significantly affects the change trend of the surface temperature. The material thickness and heating time have great influence on the bottom temperature. This paper contributes to the understanding of the heat transfer and ablation of the charring materials, thereby providing a basis for the selection of the thermal protection material for re-entry vehicles.

Carbon based fillers have attracted a great deal of interest in polymer composites because of their ability to beneficially alter properties at low filler concentration, good interfacial bonding with polymer, availability in different forms, etc. The property alteration of polymer composites makes them versatile for applications in various fields, such as constructions, microelectronics, biomedical, and so on. Devastations due to building fire stress the importance of flame-retardant polymer composites, since they are directly related to human life conservation and safety. Thus, in this review, the significance of carbon-based flame-retardants for polymers is introduced. The effects of a wide variety of carbon-based material addition (such as fullerene, CNTs, graphene, graphite, and so on) on reaction-to-fire of the polymer composites are reviewed and the focus is dedicated to biochar-based reinforcements for use in flame retardant polymer composites. Additionally, the most widely used flammability measuring techniques for polymeric composites are presented. Finally, the key factors and different methods that are used for property enhancement are concluded and the scope for future work is discussed.

The capability of artificial neural networks in predicting microscale combustion calorimeter (MCC) parameters of polymethyl methacrylate (PMMA) was carried out in this study. Using values of sample mass and corresponding heating rate, feed forward back propagation (FFBP) and generalized regression neural network (GRNN) models were developed to predict MCC parameters. On the whole, GRNN outperformed FFBP in predicting HRC data while FFBP model saw an improvement over GRNN when estimating pTime. It was also discovered that GRNN obtained better THR, pTemp and pHRR predictions during training but generated a relatively poor correlation when estimating the testing data. Sensitivity analysis on the ANN models revealed that heating rate had a more significant effect on the models’ outcome. Also, the ANN models observed the least error deviation when compared with HRC results for PMMA from structure-property models. Hence, ANN presents a reliable method for predicting flammability characteristics of PMMA from MCC test.

Flammability studies are conducted to evaluate the behavior of materials exposed to fire. In this study, microscale combustion calorimetry (MCC) and cone calorimetry methods were applied to acquire the flammability characteristics of red and grey extruded polystyrene (XPS) samples. To understand the effect of changes between parameters, Pearson’s correlation coefficient was used to examine their linear relationships. From the research, moderate and weak correlations were recorded between the total heat release rates from both methods for red and grey XPS, respectively. Plotting peak heat release rate against heat release temperature for MCC and ignition temperature for cone test showed that 25, 35 and 50 kW m−2 incident heat fluxes of the cone test fall within 0.2 K s−1 and 0.5 K s−1 heating rates of MCC. Also, all the MCC parameters except char yield and total heat release presented good correlations with the cone calorimetry flammability characteristics. Hence, MCC could be used in conjunction with cone calorimetry to accurately and reliably assess the flammability of materials.

To study the practicability of a micro combustion calorimeter to analyze the calorimetry kinetics of wood, a micro combustion calorimeter with 13 heating rates from 0.1 to 5.5 K/s was used to perform the analysis of 10 kinds of common hardwood and softwood samples. As a microscale combustion measurement method, MCC (microscale combustion calorimetry) can be used to judge the flammability of materials. However, there are two methods for measuring MCC: Method A and Method B. However, there is no uniform standard for the application of combustible MCC methods. In this study, the two MCC standard measurement Methods A and B were employed to check their practicability. With Method A, the maximum specific heat release rate, heat release temperature, and specific heat release of the samples were obtained at different heating rates, while for Method B, the maximum specific combustion rate, combustion temperature and net calorific values of the samples were obtained at different heating rates. The ignition capacity and heat release capacity were then derived and evaluated for all the common hardwood and softwood samples. The results obtained by the two methods have significant differences in the shape of the specific heat release rate curves and the amplitude of the characteristic parameters, which lead to the differences of the derived parameters. A comparison of the specific heat release and the net calorific heat of combustion with the gross caloric values and heating values obtained by bomb calorimetry was also made. The results show that Method B has the potentiality to evaluate the amount of combustion heat release of materials.

Flammability analysis of extruded polystyrene (XPS) has become crucial due to its utilization as insulation material for energy efficient buildings. Using the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods, the degradation kinetics of two pure XPS from the local market, red and grey ones, were obtained from the results of thermogravity analysis (TG) and microscale combustion calorimetry (MCC) experiments performed under the same heating rates. From the experiments, it was discovered that red XPS released more heat than grey XPS and both materials showed two mass loss stages. Consequently, the kinetic parameters for red XPS were higher than grey XPS. A comparative evaluation of activation energies from MCC and TG showed an insignificant degree of deviation signifying an equivalent apparent activation energy from both methods. However, different activation energy profiles as a result of the different chemical pathways were presented when the dependencies of the activation energies on extent of conversion for TG and MCC were compared.

Polyethylene (PE) is one the most used plastics worldwide for a wide range of applications due to its good mechanical and chemical resistance, low density, cost efficiency, ease of processability, non-reactivity, low toxicity, good electric insulation, and good functionality. However, its high flammability and rapid flame spread pose dangers for certain applications. Therefore, different flame-retardant (FR) additives are incorporated into PE to increase its flame retardancy. In this review article, research papers from the past 10 years on the flame retardancy of PE systems are comprehensively reviewed and classified based on the additive sources. The FR additives are classified in well-known FR families, including phosphorous, melamine, nitrogen, inorganic hydroxides, boron, and silicon. The mechanism of fire retardance in each family is pinpointed. In addition to the efficiency of each FR in increasing the flame retardancy, its impact on the mechanical properties of the PE system is also discussed. Most of the FRs can decrease the heat release rate (HRR) of the PE products and simultaneously maintains the mechanical properties in appropriate ratios. Based on the literature, inorganic hydroxide seems to be used more in PE systems compared to other families. Finally, the role of nanotechnology for more efficient FR-PE systems is discussed and recommendations are given on implementing strategies that could help incorporate flame retardancy in the circular economy model.

The effect of pyrolysis reactors on the properties of biochars (with a focus on flammability and mechanical characteristics) were investigated by keeping factors such as feedstock, carbonisation temperature, heating rate and residence time constant. The reactors employed were hydrothermal, fixed-bed batch vertical and fixed-bed batch horizontal-tube reactors. The vertical and tube reactors, at the same temperature, produced biochars having comparable elemental carbon content, surface functionalities, thermal degradation pattern and peak heat release rates. The hydrothermal reactor, although, a low-temperature process, produced biochar with high fire resistance because the formed tarry volatiles sealed water inside the pores, which hindered combustion. However, the biochar from hydrothermal reactor had the lowest nanoindentation properties whereas the tube reactor-produced biochar at 300 °C had the highest nanoindentation-hardness (290 Megapascal) and modulus (ca. 4 Gigapascal) amongst the other tested samples. Based on the inherent flammability and mechanical properties of biochars, polymeric composites’ properties can be predicted that can include them as constituents.

Cellulose nitrate, also known as nitrocellulose (NC), is a highly flammable energetic cellulose derivatives formed by exposing cellulose to nitric acid, whose producing procedure has been greatly employed in daily life and military area. In this study, to explore its pyrolysis and combustion kinetics, NC samples were subjected to isothermal and non-isothermal DSC experiments. The isothermal experiments were carried at 150, 155, 160, and 165 °C, while the non-isothermal experiments were taken at 2, 4, 8, and 10 °C min−1 for heating rates. By model fitting methods, several classical reaction models with high fitting degree were obtained. The model corresponding to isothermal conditions was f(α) = 4(1 − α)[−ln(1 − α)]3/4, while for non-isothermal conditions the model was identified as f(α) = (1 − α)3. The variation of activation energy with conversion was calculated by model free methods including FR, KAS, FWO, and advanced Vyazovkin methods. Finally, based on the results of kinetic analysis, the adjustment function was introduced and the accurate reaction mechanism functions of NC were identified for isothermal and non-isothermal conditions, respectively. This study has a high guiding significance for the thermal decomposition and combustion kinetics of NC under isothermal and non-isothermal heating conditions.

The fire behavior of materials is usually modeled on the basis of fire physics and material composition. However, significant strides have been made recently in applying soft computing methods such as artificial intelligence in flammability studies. In this paper, multiple linear regression (MLR) was employed to test the degree of non-linearities in flammability parameter modeling by assessing the linear relationship between sample mass, heating rate, heat release capacity (HRC) and total heat release (THR). Adaptive neuro-fuzzy inference system (ANFIS) was then adopted to predict the HRC and THR of the extruded polystyrene measured from microscale combustion calorimetry experiments. The ANFIS models presented excellent predictions, showing very low mean training and testing errors as well as reasonable agreements between experimental and predicted datasets. Hence, it can be inferred that ANFIS can handle the non-linearities in flammability modeling, making it apt as a modeling technique for accurate and effective flammability assessments.