Fire Behavior Research Articles

The Impact of Initial Fuel Depth on the Combustion Efficiency of Pool Fire in an Enclosed Compartment: A Study Based on Zone Model Theory

In this paper, the effect of initial fuel depth on the combustion efficiency of pool fires in an enclosed compartment was experimentally studied. Three different sizes of pool fires were conducted in the experiments. Several combustion parameters including burning rate, smoke temperature distribution, and oxygen concentration of pool fires under the different initial fuel depths in closed compartments were obtained. Results showed that the pool fire with the different initial fuel depths would appear in two typical extinction modes: fuel burning out and self-extinction due to lack of oxygen. The whole burning process of the pool fire in the enclosed compartment can be divided into the following five stages: rapid rise stage, transition stage, stable combustion stage, boiling combustion stage, and extinguishing decay stage. The maximum and average values of the burning rate presented the power function of the initial fuel depth. The consumption of oxygen concentration in the compartment was mainly affected by the initial fuel depth, the pool size, and the compartment volume. Dimensionless characterization of the oxygen concentration was adopted to characterize the fire extinction behavior in the enclosed compartment. In addition, based on the combustion process and the extinction behavior, a global combustion efficiency of pool fire was proposed to predict the combustion characteristic while considering the initial fuel depth in the enclosed compartment.

Recent Advances in Fire Safety of Carbon Fiber-Reinforced Epoxy Composites for High-Pressure Hydrogen Storage Tanks

The increasing use of hydrogen as a clean energy carrier has underscored the necessity for advanced materials that can provide safe storage under extreme conditions. Carbon fiber-reinforced epoxy (CFRP) composites are increasingly utilized in various high-performance applications, including automotive, aerospace, and particularly hydrogen storage tanks, due to their exceptional strength-to-weight ratio, durability, excellent corrosion resistance, and low thermal conductivity. However, the inherent flammability of epoxy matrices poses significant safety concerns, particularly in hydrogen storage, where safety is paramount. This review paper provides a comprehensive overview of the recent progress in enhancing the fire safety of CFRP. The focus is on innovative strategies such as developing novel flame-retardant (FR) additives, intumescent coatings, and nanomaterial reinforcements. It analyzes the effectiveness of these strategies in improving the fire performance of CFRP composites, including their flame retardancy, smoke suppression, and heat release rate reduction. The review paper also explores the application of fire modeling tools to predict the fire behavior of CFRP composite hydrogen storage tanks under various fire scenarios. Additionally, the review discusses the implications of these advancements on the performance and safety of hydrogen storage tanks, highlighting both the progress made and the challenges that remain.

Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data

Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent socioeconomic losses and environmental damage, but challenging because of the complexity of fire behavior. Existing physics-based models are limited in predicting large or long-duration wildfire events. Here, we develop a deep-learning-based predictive model, Fire-Image-DenseNet (FIDN), that uses spatial features derived from both near real-time and reanalysis data on the environmental and meteorological drivers of wildfire. We trained and tested this model using more than 300 individual wildfires that occurred between 2012 and 2019 in the western US. In contrast to existing models, the performance of FIDN does not degrade with fire size or duration. Furthermore, it predicts final burnt area accurately even in very heterogeneous landscapes in terms of fuel density and flammability. The FIDN model showed higher accuracy, with a mean squared error (MSE) about 82% and 67% lower than those of the predictive models based on cellular automata (CA) and the minimum travel time (MTT) approaches, respectively. Its structural similarity index measure (SSIM) averages 97%, outperforming the CA and FlamMap MTT models by 6% and 2%, respectively. Additionally, FIDN is approximately three orders of magnitude faster than both CA and MTT models. The enhanced computational efficiency and accuracy advancements offer vital insights for strategic planning and resource allocation for firefighting operations.

Thicker or Shorter Bark Fragments of Eucalypt Tree Species Make More Densely Packed Fuel Beds, Which Slow Down Fire Spread

Many eucalypt trees shed their bark annually. This bark becomes a component of the litter layer, which acts as fuel, especially during surface fires. The amount and quality of shed bark vary greatly among species, which might have important effects on forest surface fire behavior. In this study, we aimed to compare the bark fuel bed flammability of eight eucalypt tree species and tried to link their bark litter traits via the surface fuel bed structure to bark flammability. In controlled laboratory burns, three flammability parameters, the fire spread rate, total burning time, and maximum temperature, were measured. The bark litter traits included length, curliness, thickness, dry matter content, tissue density, carbon content, nitrogen content, and terpene content, while the litter bed packing ratio and packing density were also measured. We found significant differences in bark traits and flammability among species. Thicker bark fragments of the eucalypt tree species had higher packing densities in fuel beds, a slower fire spread, and a longer burning time. This relationship was strongly driven by the thick bark fragments of Eucalyptus punctata DC. Still, also within the other seven species, bark thickness was the strongest predictor of bark fuel bed flammability, with some additional explanatory power for bark length. For the first time, our study demonstrates that bark traits, particularly litter fragment thickness and length, drive bark litter flammability of eucalypt tree species through their effects on bark fuel bed structure. These findings contribute to our understanding and predictive power of wildfire behavior in forest stands dominated by different eucalypt species.

Cheatgrass alters flammability of native perennial grasses in laboratory combustion experiments

Abstract Background The invasive annual grass cheatgrass (Bromus tectorum) increases fuel continuity, alters patterns of fire spread, and changes plant communities in sagebrush shrublands of the Great Basin (USA) and adjacent sagebrush steppe, but no studies have contrasted its flammability to native perennial grasses. Understanding cheatgrass flammability is crucial for predicting fire behavior, informing management decisions, and assessing fire risk in invaded areas. This study aimed to determine the flammability of cheatgrass compared to two native perennial grasses (Columbia needlegrass [Achnatherum nelsonii] and bluebunch wheatgrass [Pseudoroegneria spicata]) across a range of fuel moistures. Results All three grass species had decreased flammability with increasing fuel moisture. Columbia needlegrass averaged 11% lower mass consumption than cheatgrass, and bluebunch wheatgrass had longer flaming duration and higher maximum temperatures than cheatgrass and Columbia needlegrass. The addition of cheatgrass to each perennial grass increased combined mass consumption, flaming duration, and flame heights. For these three attributes, the impact differed by the amount of cheatgrass in the mixture. Maximum and mean temperatures during perennial grass combustion were similar with and without cheatgrass addition. Some attributes of Columbia needlegrass flammability when burned with cheatgrass were higher than expected based on the flammability of each species, suggesting that Columbia needlegrass may be susceptible to pre-heating from combustion of cheatgrass. Conversely, the flammability of bluebunch wheatgrass and cheatgrass together had both positive and negative interactive effects, suggesting the impact on joint flammability from cheatgrass differs by perennial grass species. Conclusions This study provides experimental evidence supporting previous qualitative observations of cheatgrass flammability. Cheatgrass increased perennial grass sustainability and consumption, suggesting that cheatgrass poses a significant fire threat to native grasses regardless of moisture content. The study provides species-specific insights into flammability, which could be used to inform efforts to prevent or mitigate cheatgrass-induced wildfires.

Fire behavior of composite steel truss bridge girders: numerical investigation and design strategies

Fire pose more severe threat to steel truss bridge girders as compared to common steel plate and box bridge girders. To deeply clarify failure mechanism of fire exposed steel truss bridge girders, this paper presents an investigation on fire performance of composite steel truss bridge girders simultaneously subjected to structural loadings and hydrocarbon fires. A numerical model, developed using the computer program ANSYS, is validated dependent on fire test to trace fire behavior of a typical through-type composite steel truss bridge girders under different hydrocarbon fire exposure conditions. The analysis is applied to evaluate influence of potential fire exposure scenarios occurred in bridge structures, including fire exposure lanes on bridge deck and fire exposure length beneath bridge, on temperature and structural response in steel truss bridge girders. The results shows that fire exposure lanes on bridge decks and fire exposure length beneath bridge has a significant influence on fire performance of steel truss bridge girders. Fire exposure on all lanes and side lanes can cut down fire resistance highly as compared to fire exposure on mid-lanes. The composite steel truss bridge girders exhibit special multi-hinge failure modes when fire exposure under bridge. Further, the composite steel truss bridge girders exposed to side-lane fire exhibit significant transverse torsional deformation. The established failure criteria dependent on structural deflection limit states, chord deformation and strength can be applied to evaluate fire resistance of actual composite steel truss bridge girders under realistic fire exposure scenarios. Limiting the minimum clearance of passage on bridge deck and increasing fire protection measures in upper portion of trusses can effectively improve fire resistance of through-type composite steel truss bridge girders. Some predominant design strategies closely related to oil tanker trucks traversing composite steel truss bridge girders are proposed to minimize probability of fire incidents on bridge and keep integrity of structure in the case of fire to the maximum extent possible.

A review of optimization and decision models of prescribed burning for wildfire management.

Prescribed burning is an essential forest management tool that requires strategic planning to effectively address its multidimensional impacts, particularly given the influence of global climate change on fire behavior. Despite the inherent complexity in planning prescribed burns, limited efforts have been made to comprehensively identify the critical elements necessary for formulating effective models. In this work, we present a systematic review of the literature on optimization and decision models for prescribed burning, analyzing 471 academic papers published in the last 25 years. Our study identifies four main types of models: spatial-allocation, spatial-extent, temporal-only, and spatial-temporal. We observe a growing number of studies on modeling prescribed burning, primarily due to the expansion in spatial-allocation and spatial-temporal models. There is also an increase in complexity as the models consider more elements affecting prescribed burning effectiveness. We identify the essential components for optimization models, including stakeholders, decision variables, objectives, and influential factors, to enhance model practicality. The review also examines solution techniques, such as integer programming in spatial allocation, stochastic dynamic programming in probabilistic models, and multiobjective programming in balancing trade-offs. These techniques' strengths and limitations are discussed to help researchers adapt methods to specific challenges in prescribed burning optimization. In addition, we investigate general assumptions in the models and challenges in relaxation to enhance practicality. Lastly, we propose future research to develop more comprehensive models incorporating dynamic fire behaviors, stakeholder preferences, and long-term impacts. Enhancing these models' accuracy and applicability will enable decision-makers to better manage wildfire treatmentoutcomes.

Estimating forest litter fuel load by integrating remotely sensed foliage phenology and modeled litter decomposition

Litter on the forest floor, or from a fire perspective the litter fuel load (LFL), is a key driver of the occurrence and spread of surface fires and an important regulator of forest fire behavior. High-quality spatiotemporal LFL data are essential for modeling fire behavior and assessing fire risk in forest ecosystems. Traditionally, LFL is estimated from ground-based measurements, but they are difficult to implement on large spatial scales. While remote sensing techniques have the advantage of large-scale observation, they encounter challenges in retrieving LFL because forest canopies generally block signals from the forest floor. Here we present a new method based on modeled litter accumulation to estimate LFL dynamics, integrating litterfall influx from the forest canopy and decomposition outflux through a mass balance approach. Annual litterfall was estimated based on seasonal changes in foliage fuel load which are retrieved from Landsat imagery and a radiative transfer model, while the decomposition rate was derived from meteorological data. Litterfall and decomposition were quantified over the past 20 years with the difference between the two being LFL accumulating over time. We validated the estimated LFL using 105 ground-based measurements in Liangshan Yi Autonomous Prefecture, China, and this validation demonstrated a reasonably strong performance for estimating LFL (R2 = 0.67, root mean squared error (RMSE) = 2.56 Mg ha−1, relative RMSE = 31.61 %). Our method integrates remote sensing-based foliage phenology with the ecological process of LFL accumulation, enabling large-scale LFL monitoring for forest fire risk assessments.

Numerical Simulation of Flow and Flame Dynamics of a Pool Fire Under Combined Effects of Wind and Slope

Wind has a significant effect on pool fire behavior, which is relevant to many fire conditions, such as wildfires, building fires, and oil transportation fires. Although fire behavior and morphology changes have received considerable attention and been widely researched, there are few works concerning the flow and flam dynamics of pool fire. A large eddy simulation model is adopted to investigate the flow and flame dynamics of a rectangular pool fire considering the combined effects of wind and slope. The results show that, with a wind speed of 0.5 m/s, a flame develops immediately downstream of the fire source and sustains two flanks of plume. Further downstream, the plume starts to rise due to buoyant force. Temperature, velocity, and vorticity distributions show significantly different shapes at different streamwise locations. Near the fire source, the flame is confined to a small region around the fire source. The air circulation downstream shows a cylindrical spiring pattern. When the wind speed increases, the temperature and velocity become more parallel to the surface and their maximum values increase. On the contrary, the temperature fluctuations and turbulent kinetic energy decrease with the wind speed, and they are more frequent near the flame tails.

Pixels to pyrometrics: UAS-derived infrared imagery to evaluate and monitor prescribed fire behaviour and effects

Background Prescribed fire is vital for fuel reduction and ecological restoration, but the effectiveness and fine-scale interactions are poorly understood. Aims We developed methods for processing uncrewed aircraft systems (UAS) imagery into spatially explicit pyrometrics, including measurements of fuel consumption, rate of spread, and residence time to quantitatively measure three prescribed fires. Methods We collected infrared (IR) imagery continuously (0.2 Hz) over prescribed burns and one experimental calibration burn, capturing fire progression and combustion for multiple hours. Key results Pyrometrics were successfully extracted from UAS-IR imagery with sufficient spatiotemporal resolution to effectively measure and differentiate between fires. UAS-IR fuel consumption correlated with weight-based measurements of 10 1-m2 experimental burn plots, validating our approach to estimating consumption with a cost-effective UAS-IR sensor (R2 = 0.99; RMSE = 0.38 kg m−2). Conclusions Our findings demonstrate UAS-IR pyrometrics are an accurate approach to monitoring fire behaviour and effects, such as measurements of consumption. Prescribed fire is a fine-scale process; a ground sampling distance of <2.3 m2 is recommended. Additional research is needed to validate other derived measurements. Implications Refined fire monitoring coupled with refined objectives will be pivotal in informing fire management of best practices, justifying the use of prescribed fire and providing quantitative feedback in an uncertain environment.

Numerical Analysis of Fire Resistance in Cross-Laminated Timber (CLT) Constructions Using CFD: Implications for Structural Integrity and Fire Protection

Fire represents a serious challenge to the safety and integrity of buildings, especially timber structures exposed to high temperatures and intense heat radiation. The combustibility of timber is one of the main reasons why regulations strictly limit timber as a building material, especially in multi-storey structures. This investigation seeks to assess the fire behaviour of cross-laminated timber (CLT) edifices and examine the ramifications for structural integrity and fire protection. Utilising computational fluid dynamics (CFD) simulations, critical variables including charring rate, heat emission, and smoke generation were analysed across two scenarios: one featuring exposed CLT and another incorporating protected CLT. The outcomes indicated that protective layers markedly diminish charring rates and heat emission, thereby augmenting fire resistance and constraining smoke dissemination. These revelations imply that CFD-based methodologies can proficiently inform fire protection design paradigms for CLT structures, presenting potential cost efficiencies by optimising material utilisation and minimising structural impairment.

Study on the flame behavior of ethanol spill fire on base plate with different width in longitudinal ventilation environment

The intricate flame behavior of spill fire in a ventilated tunnel significantly aggravates the severity of accident consequences. Flame height, flame tilt angle, and combustion area were measured by conducting ethanol spill fire experiments in model tunnel with different wind speeds in base plates of different width. Furthermore, critical transition wind speed, dimensionless analysis of burning rate and heat transfer analysis were performed. The findings reveal that, in windy conditions, wind speed linearly lowers flame height, while baseplate width’s impact is irregular. Longitudinal ventilation notably causes flame inclination, base plate width and wind speed jointly affect inclination at low wind speed, however, in high wind speeds, the inclination is mainly determined by the wind speed. With the increase of wind speed, the burning rate firstly increases and then decreases, resulting in an initial decline followed by an increase in the combustion area. The increase in base plate width not only leads to a continuous increase in the combustion area, but also results in a decrease of the critical transition wind speed at which the burning rate changes. An equation for the dimensionless burning rate in upwind environments has been developed, revealing that burning rate is significantly higher in longitudinal wind conditions compared to still air. Furthermore, the difference becomes more pronounced as the baseplate width decreases. By taking into account the asymmetric air entrainment of the spill fire flame, a revised model for flame height and inclination has been introduced, utilizing a dimensionless array (2n+1/n). This model effectively predicts the morphological changes of spill fire flames under windy conditions, and the dimensionless flame height of spill fires is approximately 0.18 to 0.36 times that of pool fires.

Assessing fire dynamics and suppression techniques in electric vehicles at different states of charge: Implications for maritime safety

The maritime transportation of electric vehicles (EVs) poses significant fire risks due to the potential for thermal runaway in lithium-ion batteries, particularly when the state of charge (SOC) varies. This study uniquely examines the effects of SOC on fire behavior and suppression efficacy, going beyond previous research by focusing on the maritime environment. Experiments were conducted on EV battery packs at SOC levels of 70 %, 50 %, and 30 %, and on a full-scale EV at 50 % SOC, to evaluate fire dynamics and the effectiveness of suppression methods, including seawater injection and fire blankets. Results showed that higher SOC levels are associated with significantly increased heat release rates and extended fire durations, while lower SOC levels (30 %) reduce fire intensity yet necessitate continuous monitoring for re-ignition risks. Moreover, the combination of seawater injection and fire blankets showed promise in cases where rapid cooling and containment of fire spread were priorities, illustrating a potential strategy for managing EV battery fires during maritime transport. These findings underscore the need for strategic SOC management, recommending lower SOC thresholds to minimize fire severity, and the use of combined suppression techniques to enhance EV fire safety during maritime transport.

Assessing the Role of Forest Grazing in Reducing Fire Severity: A Mitigation Strategy

This study investigates the role of prescribed grazing as a sustainable fire prevention strategy in Mediterranean ecosystems, with a focus on Sardinia, an area highly susceptible to wildfires. Using FlamMap simulation software, we modeled fire behavior across various grazing and environmental conditions to assess the impact of grazing on fire severity indicators such as flame length, rate of spread, and fireline intensity. Results demonstrate that grazing can reduce fire severity by decreasing combustible biomass, achieving reductions of 25.9% in fire extent in wet years, 60.9% in median years, and 45.8% in dry years. Grazed areas exhibited significantly lower fire intensity, particularly under high canopy cover. These findings support the integration of grazing into fire management policies, highlighting its efficacy as a nature-based solution. However, the study’s scope is limited to small biomass fuels (1-h fuels); future research should extend to larger fuel classes to enhance the generalizability of prescribed grazing as a fire mitigation tool.

Fire resistance behaviour of non-load bearing LSF walls with restrained thermal elongation

In this research study, based on suitable and rational thermal and sequentially coupled structural FE (finite element) analyses, the fire resistance behaviour and FRLs (fire resistance levels) of non-load bearing LSF (light gauge steel framed) walls with restrained thermal elongation were deeply analysed. The FE analysis results confirmed that CFS (cold-formed steel) channel studs of the mentioned walls collapsed prematurely due to additional compression loads caused by the effects of fire and the thermal elongation restraints at stud ends, which led to the reduced FRLs of these walls. Besides, the wall height and the clearance between the stud ends and rigid floors were shown as having significant effects on the FRLs of non-load bearing LSF walls with restrained thermal elongation. In contrast, the effects of the thickness and depth of CFS channel studs and cavity insulation were inconsiderable. Finally, a simplified and reliable design equation and some recommendations were proposed for some types of non-load bearing fire-rated LSF walls commonly used in Australia. This paper presents details of this study, including its analyses, outcomes, and proposals.

Fire parameters of recycled plastic pellets

AbstractDuring the recycling process, waste plastic undergoes various processes that change its geometry. The thermal properties and fire behaviour of plastic in different geometries has not been widely studied. This paper aims to determine critical thermal properties of plastic pellets made of recycled plastic. For this paper, cone calorimeter tests of various volumes of recycled plastic pellets of low‐ and high‐density polyethylene and polypropylene were conducted. During these tests, the heat release rate (HRR), mass loss rate and time‐to‐ignition were measured, thereafter the heat of combustion (HOC) was calculated. A calibration of suitable time‐to‐ignition equations is carried out. The average HRR is between 353 and 581 kW/m2 with an external heat flux of 50 kW/m2. The measured time‐to‐ignition values ranged between 27 s at 50 kW/m2 and just more than 90 s at 25 kW/m2. Values obtained analytically from the thermally thin time‐to‐ignition equations for these materials describe ignition well, which appears to be due to the particulate nature of the samples. The HOC (40–41 MJ/kg) shows good agreement with the HOC for virgin plastic found in literature. These properties can be used as a basis for material characterisation, and further testing will be done before using this as simulation inputs to determine how bulk stored plastic pellets will behave in the event of a fire.

The Global Forest Fire Emissions Prediction System version 1.0

Abstract. The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that estimates biomass burning in near-real time for global air quality forecasting. The model uses a bottom-up approach, based on remotely sensed hotspot locations, and global databases linking burned area per hotspot to ecosystem-type classification at a 1 km resolution. Unlike other global fire emissions models, GFFEPS provides dynamic estimates of fuel consumption, fire behaviour and fire growth based on the Canadian Forest Fire Danger Rating System, plant phenology as calculated from daily global weather and burned-area estimates using near-real-time Visible Infrared Imaging Radiometer Suite (VIIRS) satellite-detected hotspots and historical burned-area statistics. Combining forecasts of daily fire weather and hourly meteorological conditions with a global land classification, GFFEPS produces fuel consumption and emission predictions in 3 h time steps (in contrast to non-dynamic models that use fixed consumption rates and require a collection of burned area to make post-burn estimates of emissions). GFFEPS has been designed for use in operational forecasting applications as well as historical simulations for which data are available. A study was conducted showing GFFEPS predictions through a 6-year period (2015–2020). Regional annual total smoke emissions, burned area and total fuel consumption per unit area as predicted by GFFEPS were generated to assess model performance over multiple years and regions. The model's fuel consumption per unit area results clearly distinguished regions dominated by grassland (Africa) from those dominated by forests (boreal regions) and showed high variability in regions affected by El Niño and deforestation. GFFEPS carbon emissions and burned area were then compared to other global wildfire emissions models, including the Global Fire Assimilation System (GFAS), the Global Fire Emissions Database (GFED4.1s) and the Fire INventory from NCAR (FINN 1.5 and 2.5). GFFEPS estimated values lower than GFAS and GFED (80 % and 74 %) and had values similar to FINN 1.5 (97 %). This was largely due to the impact of fuel moisture on consumption rates as captured by the dynamic weather modelling. Model evaluation efforts to date are described – an ongoing effort is underway to further validate the model, with further developments and improvements expected in the future.

Analytical study on fire resistance performance of precast concrete hollow-core slabs for electric vehicle fire in parking structures

This study evaluated the effects of fires that occur in internal combustion engine vehicles (ICEVs) and battery electric vehicles (BEVs) on the structural safety of hollow-core slabs (HCS) installed in parking structures. A fire simulation of a prototype parking structure was performed using the time–heat release rate curves of ICEVs and BEVs derived from fire experiments, and fire behavior and temperature history were derived according to the fire curve. Additionally, nonlinear finite element analysis was conducted using a general-purpose finite element analysis program, and the fire resistance performance of HCS was evaluated according to the fire curve and slab load ratio. In the case of a fire in ICEVs, the performance criteria of ISO 834–1 were met even at a slab load ratio of 0.7. However, in the case of a fire in BEVs, the standard for insulation was not met as the temperature change of the upper surface of HCS exceeded 180 K, and the load-bearing capacity was also not satisfied as the limiting deflection reached a slab load ratio of 0.7.

Variations in stand structure, composition, and fuelbeds drive prescribed fire behavior during mountain longleaf pine restoration

Across the central and eastern U.S., frequent-fire (∼ 1–5 year interval) dependent savannas, woodlands, and forests have experienced widespread ecological state shifts due to decades of fire exclusion. Without fire, mesophytes (i.e., shade-tolerant, often fire-sensitive and/or opportunistic tree species) are encroaching in the midstory, creating shady, moist understories with low flammability and reduced biodiversity through a process known as “mesophication.” Although prescribed fire is commonly used to reverse mesophication and restore fire-dependent ecosystems, fire behavior during restoration remains difficult to predict because variations in stand structure and composition and associated fuels interact to influence flammability. To better understand the mesophication mechanisms influencing fire behavior and to identify key predictors of fire behavior for the benefit of land managers, we assessed how metrics that describe fire intensity (maximum temperature, rate of spread, and residence time) and severity (fuel consumption) relate to pre-fire stand and leaf litter composition and structure. We focused on the restoration of remnant mountain longleaf pine (Pinus palustris Mill. (LLP)) stands during the dormant prescribed fire season in the Georgia Piedmont region, USA. Using Bayesian path analysis, we compared the effects of either stand or leaf litter composition and structure on fire behavior. Lower stand basal area and higher relative importance of pine and pyrophytic hardwoods (e.g., upland Quercus spp.) and associated leaf litter types were expected to increase fire intensity. Results showed that stand composition and structure significantly influenced fire behavior, but not because of their influence on litter structure (load and bulk density). Rather, leaf litter composition may better explain fire behavior than leaf litter structure. Results also suggest that simple measures of stand composition and structure alone can be used to predict fire behavior, providing a potentially useful tool for assessing restoration potential of fire-dependent ecosystems under threat of mesophication.

A multiaxial thermo-plasticity model for concrete in a transient fire condition

Lateral confinement and high temperature affect the load-carrying capacity of a concrete member significantly. In a fire condition, a concrete member exhibits not only mechanical deformation but also thermal deformation. Therefore, accurately modeling the fire behavior of confined structural concrete is challenging. In this paper, a new three-dimensional thermo-plasticity model for concrete is developed, taking both high temperature and confinement into account. A temperature-dependent yield surface and a non-associate flow rule are formulated. The hardening rules for concrete are proposed as a function of confinement and temperature. The load-induced strain of concrete at elevated temperatures is calculated by using a stress-triaxiality factor to consider the confinement effect. The proposed concrete model is implemented in the user-subroutine (UMAT) of Abaqus, in which Runge-Kutta-England scheme with sub-stepping is used to update stress increment. The accuracy of the proposed model is validated by experiments on concrete specimens, circular concrete-filled steel tubular (CFST) columns, double-skin CFST (DCFST) columns, and concrete-filled double steel tubular (CFDST) columns. It is shown that the developed thermo-plasticity model of concrete accurately captures the behavior of confined concrete at ambient and elevated temperatures and can be incorporated in nonlinear procedures for simulating the fire resistance of composite columns exposed to fire.