Fire Behavior Research Articles

Hakea decurrens invasion increases fire hazard at the landscape scale

Hakea decurrens subsp. physocarpa is an invasive fire-adapted shrub of Australian origin that is quickly expanding in Portugal with potential impacts on fire behavior and fire regime. In this study we examined the effects of H. decurrens on fire hazard by assessing fire behavior indicators at the landscape scale, using a modeling and simulation approach. Six fuel models for H. decurrens were developed through fuel characterization and experimental fires. The fuel models correspond to combinations of developmental stages of H. decurrens populations (Early, Intermediate and Mature) and management (Standing and Slashed fuels). These combinations were used with three levels of H. decurrens invasion, corresponding to 25%, 50% and 75% of cover of the landscape, applied to five real landscapes in northern Portugal (replicates) under three fuel moisture conditions (Low, Medium and High), used as surrogates of weather severity. Fire behavior simulations were conducted with FlamMap software. The relationships between fire behavior indicators (flame length, rate of spread and burn probability) at the landscape level and the four factors tested were analyzed using Generalized Linear Mixed Models. Standing fuels were found to be more hazardous than slashed fuels. Fire-hazard increased with H. decurrens stand maturity and slash, regardless of moisture conditions. The results of this study indicate that H. decurrens expansion might negatively affect the fire regime in the north of Portugal. Our findings add to other known negative impacts of the species on native ecosystems, calling for the need to reinforce its control.

A robust optimisation approach for the placement of forest fire suppression resources

AbstractThis research develops an initial attack plan for combating forest fires in any wildland areas susceptible to fire outbreaks. To be eligible for such a plan, the landscape must have been previously mapped and modelled concerning spatial and topographic data and fuel levels. Thus, when ignition occurs, one can predict the expected fire behaviour in terms of spread direction and rate of spread. With such information, decisions can be taken on where and when to position the suppression resources. This paper extends a recent contribution to this subject, generalising each node's resource requirement, allowing a more precise modelling of non‐homogeneous landscapes. Moreover, we treat the cases where the estimated number of resources may not be sufficient to deal with the fire intensity, which becomes revealed only at the fire scene. In such cases, additional resources may be needed to contain the fire effectively. This worst‐case approach is modelled with the support of the robust optimisation paradigm. We propose a deterministic mathematical programming model, a robust optimisation counterpart, and a robust tabu search (RoTS) algorithm. We adapt instances from the literature, which are optimally solved by a commercial solver and used for assessing the quality of the RoTS. The proposed algorithm could optimally solve 94 of 96 instances. Finally, we conducted a Monte Carlo simulation as part of a risk analysis assessment of the generated solutions.

Memristive Hodgkin–Huxley Neurons with Diverse Firing Patterns for High‐Order Neuromorphic Computing

The rich firing behaviors of biological neurons enable the nervous system to execute complex computations, emulating which in hardware is advantageous for constructing advanced intelligent machines. Hodgkin–Huxley (H–H) neurons based on memristors feature great merits of high bio‐plausibility and low hardware cost. However, a universal design rule of memristive H–H neurons is still lacking, hindering its development and applications. Herein, a universal H–H neuron circuit structure is proposed and its feasibility based on NbOx memristors is demonstrated. The constructed neuron achieves 23 types of firing behaviors observed in biological neurons, simplifying the communication between neurons. To better understand the correlation between circuit parameters and firing patterns, the firing patterns into three classes according to the switching cycle ratio of two memristors are categorized. The circuit design rules of each category of firing patterns are deeply elucidated and universal regularities for tuning circuit parameters to implement the switch between different firing behaviors are presented. Finally, the potential applications of different firing behaviors in neuromorphic intelligence systems are discussed. This work provides theoretical guidance for engineering memristive H–H neuron circuits, assisting in building high‐order neuromorphic systems based on firing patterns.

Assessing four decades of fire behavior dynamics in the Cerrado biome (1985 to 2022)

BackgroundFire significantly transforms ecology and landscapes worldwide, impacting carbon cycling, species interactions, and ecosystem functions. In the Brazilian Cerrado, a fire-dependent savanna, the interaction between fire, society, and the environment is evident. Given that wildfires significantly contribute to greenhouse gas emissions, our study aimed to analyze four decades of burned area data to understand changes in fire dynamics, using Collection 2 of annual MapBiomas Fire maps (1985 to 2022). Our study examined spatiotemporal patterns, fire recurrence, fire distribution across land uses, temporal changes in fire scar size, burned area variations across ecoregions, and their correlation with farming areas.ResultsFrom 1985 to 2022, fire impacted 40% (792,204 km2) of the Cerrado biome, with 63% burning more than once. Natural vegetation was the most affected, primarily due to human-driven ignition during the dry season. A noticeable trend of later peaks in fire activity, concentrated towards the end of the dry season, along with an increase in patch size over time, characterized a clear shift in the Cerrado fire regime. Recently, the MATOPIBA region and the northern biome exhibited significant fire clusters, with burned areas rising alongside farming expansion. The ecoregion-based analysis identified fire hotspots, with the "Bananal" ecoregion, the largest wetland area in the biome, exhibiting increased fire recurrence and larger patch size over time.ConclusionsOur four-decade analysis of fire dynamics in the Cerrado revealed human-induced changes in the fire regime, originally shifting from July to September to a new fire season from August to October. This shift poses several environmental threats given their overlap with the driest months of the year. This study improved our understanding of changes in fire patterns and their impacts on each ecoregion and land use. Wetlands experienced the highest relative burned area, highlighting their ecological importance and increased vulnerability. In the southern Cerrado, where farming is established and natural vegetation more fragmented, fire events tend to decrease; while in the north, with recent farming expansion, fire susceptibility rises. Conservation-oriented strategies, like the Brazilian Integrated Fire Management (MIF), are crucial for mitigating impacts while enhancing the Cerrado’s resilience to climate change.

Effect of the wood species on the fire behavior in vertical orientation

The objective of this study was to investigate the parameters controlling auto-ignition, degradation and auto-extinction of wood. For this purpose an extensive set of experiments was conducted varying extrinsic parameters such as external heat-flux but also the type of wood. Varying the wood species allowed to explore the role of thermal properties and wood composition. Seven wood samples were tested, some light and some heavy, both hardwood and softwood. The experimental setup was based on a double-cone calorimeter, which allowed to accurately change the imposed heat flux at a predefined moment. More than 600 tests were carried out in a vertical orientation, allowing a statistical analysis. For each test, mass loss, surface temperature and in-depth temperature of the samples were measured using a precision scale, an infrared camera and thin wire thermocouples embedded using a special machining, respectively. The auto-ignition study showed that the time to auto-ignition increases linearly with density. Despite a wide range of these times to ignition, the surface temperatures at ignition were in the same order of magnitude for all species considered: between 450 and 700 °C for auto-ignition before 2 min and between 700 and 800 °C for auto-ignition after 2 min. The onset of char oxidation was observed at low heat fluxes. It occurs at different times depending on the wood species, but at similar surface temperatures, between 380 and 400 °C. The sliding double heating cone made it possible to identify the criteria for auto-extinction: the heat flux for auto-extinction can vary from 40 to 55 kW.m−2 depending on the wood species, and a linear correlation was found between the mass loss rate at extinction and the initial density of each sample studied. The study highlights the dominant role of density for auto-ignition and auto-extinction.

Development of New Lignin-Based Coatings with Ultraviolet Resistance for Biobased Composite Materials.

Nowadays, there is a challenge in searching for more sustainable alternatives to decrease the environmental impact of composite materials. In this work, we fabricate new composites based on a biobased-content epoxy system, lignin, and flax fiber; considering these materials could be promising due to their high renewable content of around 40%. In addition, another key requirement for composites, besides being sustainable, is that they present improved properties such as UV resistance. Therefore, throughout this work, priority was given to improving UV resistance in addition to taking into account sustainability. In order to carry out a complete characterization of the materials developed, the mechanical properties, brightness, and thermal, rheological, and fire behavior of these kinds of materials were analyzed by using vacuum-assisted resin infusion processes. By way of conclusion, it should be noted that the manufactured composite with the optimized formulation showed improved UV resistance using lignin and that it could be applied on internal and external walls according to the railway fire regulations.

Overstory and fuel traits drive moisture dynamics of mesophytic and pyrophytic leaf litter and 10-h woody debris fuels in a mixed longleaf pine-hardwood woodland

BackgroundFollowing decades of fire exclusion, many open pine and oak forests across the central and eastern US are shifting to closed-canopy forests that are increasingly dominated by shade-tolerant, fire-sensitive species (i.e., mesophytes). As mesophytes encroach into historically pyrophytic landscapes, changes in crown traits and understory microclimate may interact with fine fuel traits to influence fuel moisture retention, and ultimately, fire behavior. To better understand potential interactions among overstory trees and underlying fine fuels that occur during mesophyte encroachment, we measured in situ drying rates of leaf litter and 10-h woody debris of three functional groups (pyrophytic pine, pyrophytic oak, and mesophytic oak) in gaps and beneath overstory trees of each functional group within a longleaf pine-mixed oak woodland along with crown (area, volume, cover), leaf litter (curling, thickness, specific leaf area, volume), and woody debris (density) traits of each functional group and understory microclimate (vapor pressure deficit (VPD)).ResultsWe found that leaf litter from pyrophytic and mesophytic oaks had higher initial moisture content than pyrophytic pines, but pyrophytic pine and pyrophytic oak leaf litter dried 1.5 times faster than that of mesophytic oaks, likely due to their greater leaf curl, thickness, and volume. Initial moisture content of mesophytic oak woody fuels was lower than that of pyrophytic pine and pyrophytic oak, potentially because of higher wood density, but there were no differences in fuel drying rates. Regardless of fuel functional type, leaf litter and woody fuels dried 1.5 times faster in gaps and underneath pyrophytic pine compared to mesophytic oaks, likely due to the more open conditions in these areas. Notably overstory functional group and time of the day interacted to influence VPD, with VPD increasing throughout the day for all groups, but more so for gaps and beneath pyrophytic pines than either oak functional group.ConclusionsThus, fuel and crown traits differentially impacted understory microclimate and leaf litter and 10-h woody debris drying rates, leading to slower drying of fuels of encroaching mesophytes compared to pyrophytic pines and oaks, which could lead to reduced forest flammability, and consequently, the continued encroachment of mesophytic species into fire-dependent pine and oak forests.

Unoccupied aerial system (UAS) Structure-from-Motion canopy fuel parameters: Multisite area-based modelling across forests in California, USA

There is a pressing need for well-informed management to reduce wildfire hazard and restore fire's beneficial ecological role in the Mediterranean- and temperate-climate forests of California, USA. These efforts rely upon the accessibility of high spatial and temporal resolution data on biomass and canopy fuel parameters such as canopy base height (CBH), mean canopy height, canopy bulk density (CBD), canopy cover, and leaf area index (LAI). Remote sensing using unoccupied aerial system Structure-from-Motion (UAS-SfM) presents a promising technology for this application due to its accessibility, relatively low cost, and possibility for high temporal cadence. However, to date, this method has not been studied in the complex mosaic of forest types found across California. In this study we examined the capacity of structural and multispectral information obtained from UAS-SfM, in conjunction with machine learning methods, to model aboveground biomass and forest canopy fuel structural parameters using an area-based approach across multiple sites representing a diversity of forest types in California.Based on correlations with field measurements, fuel parameters separated into vertical (biomass, CBH, and mean height) and horizontal (LAI, CBD, canopy cover) groups. UAS-SfM random forest models performed well for modelling the vertical structure canopy fuels parameters (R2 0.69–0.75). These models exhibited strong performance in comparison to ALS, as well as when transferred to a novel site. Vertical structure predictors were prominent in these models, and did not improve with the addition of spectral predictors. UAS-SfM random forest models of horizontal structure parameters mainly used raster-based spectral indices (primarily NDVI) and had relatively low performance (R2 0.49–0.59). In addition, these models underperformed ALS and had poor performance when applied to a novel site. When applied to a region with widespread UAS-SfM coverage, models from both groups successfully produced contiguous maps that could be used for modelling fire behavior or in management decision making and monitoring.These findings indicate that UAS-SfM, without the need for multispectral sensors, is well suited for mapping area-based vertical-structure canopy parameters across diverse landscapes supporting a wide range of forest types. In contrast, the identification of spectral mean variables for modelling horizontal structure canopy fuels suggests the potential of multi- or hyperspectral sensors or high-resolution satellite imagery for meeting management information needs.

Correction: Evaluation of the Fire Behavior of Low-Rise Eccentrically Braced Frame Structures Under Different Fire Scenarios

Correction: Evaluation of the Fire Behavior of Low-Rise Eccentrically Braced Frame Structures Under Different Fire Scenarios

Bio-based boards made of hazelnut shell and A. donax for indoor applications - A solution with good performance in case of fire

The present study investigated the reaction to fire of bio-based boards for indoor applications made of A. donax and hazelnut shells as aggregates. A sodium silicate solution was employed as the adhesive due to its several advantages. Among others, the possibility of moderating some of the main drawbacks of bio-based building composites, such as the resistance to fire. The considered materials were analysed both individually, to test their inherent properties, and when integrated into the composites, ensuring considerations about materials' influence on the final products’ properties. Two different test methods, using a cone calorimeter, were considered and performed. The results showed that the sodium silicate solution avoided flaming and smoking, in case of a constant heat application with and without an igniter (spark), demonstrating the benefit of its use in this type of bio-based composites. Overall, the particleboards demonstrated their ability to comply with fire behaviour consistent with the Class A1 requirements, while the bio-components on themselves were characterized by an intermediate fire risk propensity. Thus, the present study provided an effective solution to avoid one of the main drawbacks of bio-based composites. It demonstrated the feasibility of employing the proposed bio-based boards as indoor coating, with no risk to human life in case of fire.

Synthesis of novel reactive flame retardant to improve fire resistance and mechanical properties in epoxy resin

A novel reactive flame-retardant (FR), phosphorus-modified tetraethylenepentamine (TEPA-m-MVP), was prepared via aza-Michael addition process, using dimethyl vinylphosphonate (MVP). TEPA-m-MVP was successfully covalently introduced into the structure of the epoxy system, into the epoxy resin matrix synthesised from tetraethylenepentamine (TEPA) and diglycidyl ether bisphenol A (DGEBA) reaction, leading to the development of a flame-retardant epoxy resin (FR-EP). The curing behaviour, mechanical properties, thermal stability and flame-retardant behaviour of FR-EP samples were investigated and compared to the behaviour of the neat epoxy resin (EP). FR-EPs showed an increase in glass transition temperature (Tg), from 120 to 147 °C upon integrating TEPA-m-MVP into the epoxy resin structure, while the value of the E modulus remained unaffected. Furthermore, FR-EP-2%P sample with the optimal P content, approximately 2 wt%, displayed excellent flame-retardant properties. In comparison to EP, total heat release (THR) and peak heat release rate (pHRR) for FR-EP-2%P decreased from 22.6 to 15.3 kJ.g−1 and from 1557 to 572 kW.m−2, respectively. In addition, an interesting impact of the crosslinking density of FR-EP samples on the fire behaviour was observed. This work presents a new strategy for the simultaneous modification of the flame retardancy and mechanical properties of epoxy systems.

Empirical study on the influence of initial relative humidity on wood crib fire behavior in compartment under varied natural ventilation conditions

This empirical study investigates the influence of initial relative humidity (RH) variations (35 % and 95 %) on key fire behavior parameters, specifically focusing on the fully developed stage, occurrences of flashover, and the temperature of the upper gas layer. Wooden cribs weighing 10 kg–40 kg are used as fuel in a compartment with three openings to establish different natural ventilation conditions. The experimental findings reveal that increasing the initial RH within the chamber leads to a delay in the onset of the fire growth phase. Furthermore, it induces two noticeable effects on the fully developed fire stage: a reduction in its duration by up to 50 % and a delay in its initiation by at least 30 s. While heightened initial RH does not prevent flashover, it effectively postpones its occurrence by a minimum of 40 s. Experiments with maximum fuel loads demonstrate negligible effects of increased RH on the maximum temperature, even under varying ventilation conditions. Conversely, lower fuel loads exhibit a significant decline in temperature with rising humidity, notably from 626 °C to 474 °C. The quantitative and qualitative insights derived from this study have considerable potential to inform the development of more effective fire suppression strategies in enclosed compartments.

Investigations of the Fire Behavior of Functionally Graded Concrete Slabs with Mineral Hollow Spheres

Investigations of the Fire Behavior of Functionally Graded Concrete Slabs with Mineral Hollow Spheres

Experimental study on the inertization of wood-based biomass with solid inerts

Wood pellets are one of the primary solid substitutes for fossil fuels worldwide. They present both advantages and disadvantages that have been widely studied, where one of the main disadvantages is the risk of self-heating, which may lead to smouldering combustion or explosion. The risk of smouldering increases with decreasing particle size, while the difference in fire behaviour due to particle sizes needs to be studied in more detail. One of the techniques used to avoid, or decrease, the risk of smouldering is inertization. Inertization with gases is ineffective due to the difficulty gas has in accessing all voids in solid materials. An alternative solution is to use inert solids instead of gas.This research empirically studies the fire behaviour of wood pellets and wood dust with particle size of less than 1 mm, and the influence of solid inertization in both materials in two different configurations: mixed and layered. The ignition initiation of both particle sizes is similar, while the cool-down phase is quicker in the case of dust. However, inertization of dust needs a significantly higher amount of inert solids than in the case of pellets, being easier to avoid smouldering when the inerts are disposed in layers rather than mixed with the materials.

Experimental study on nonlinear development process of oil-filled equipment fire under external fire source

Abstract The transformer is the key oil-filled equipment in the power system, and its fire behavior seriously affects the safe operation of the power grid. In this paper, in order to analyze the fire development process and combustion behavior of oil-filled equipment, a mesoscale model of transformer equipment was constructed, and fire simulation experiments of transformer equipment under the action of external ignition sources were conducted. The flame temperature, flame height, heat release rate, oil temperature, and pressure were measured. The experimental results show that the oil-filled equipment fire presents the characteristics of nonlinear development. The fire can be divided into three stages: ignition stage, stable growth stage, and combustion mutation stage. The transformer oil near the wall is pyrolyzed by the external heat source, and the combustible gas and transformer oil form a gas-liquid two-phase flow, which is the main reason for the nonlinear development of oil-filled equipment fire. The experimental results are of great significance for the safe operation and fire control of power system oil-filled equipment.

A Systematic Approach to Map and Evaluate the Wildfire Behavior at a Territorial Scale in the Northwestern Iberian Peninsula

In the current context of extreme wildfires, understanding fire behavior at a territorial level has proven crucial for territory planning. This type of analysis is usually conducted by analyzing past wildfire statistics. In this study, we forego the past information related to wildfires and analyze, instead, the behavior of the entire territory in the face of wildfires. This allows for the distribution of ignition points to be systematized and for typical and atypical weather scenarios to be considered. This analysis relies on the use of wildfire simulation software. Ignition points used for the simulations were distributed using a systematic 1 × 1 km grid throughout the whole study area. Wildfires were simulated for each ignition point using eight different weather scenarios representing both typical and atypical weather conditions. The fire behavior on the territory was analyzed using rate of spread and intensity parameters for each simulated wildfire. It was observed that this territory is extremely prone to large wildfires both in typical and atypical weather conditions and that there is a tendency for extreme behaviors to develop. Some features were identified as prevention issues that ought to be addressed. This study develops a strategy to evaluate, in a systematic manner, the response of the territory to the threat of wildfires.

Metaheuristic algorithms for calibration of two-dimensional wildfire spread prediction model

Wildfires are complex phenomena with harmful consequences, ranging from environmental and property destruction to loss of human lives. In this sense, predicting wildfire behaviour is essential to mitigate its impacts and consequences. The Rothermel model is the most used fire rate of spread prediction model. However, input parameter uncertainty is a significant source of prediction error. In this paper, we propose the calibration of the input parameters of the fire propagation model by metaheuristic algorithms under a two-stage framework. The fire spread model consists on the Rothermel model in a two-dimensional approach for surface fires. The proposed calibration is performed in two stages iteratively repeated over time: (i) the calibration of the fire spread model’s input parameters and (ii) the wildfire spread prediction using the calibrated input parameters. The calibration was performed by the genetic algorithm, differential evolution, and simulated annealing, which calibrates the surface-area-to-volume ratio, fuel bed depth, live fuel moisture and dead fuel moisture. The symmetric difference between the real and predicted fire map shapes was defined as the fitness function of all three metaheuristic algorithms. For validation, simulations were done on two prescribed fires. The results for the real and estimated fire behaviour were then compared and revealed that all the tested metaheuristic algorithms produce a better fit to the real fire’s perimeter when compared to the uncalibrated Rothermel model. From the results, differential evolution provided the majority of best results when compared to genetic algorithm and simulated annealing algorithms in each scenario.

Research Trends in Wildland Fire Prediction Amidst Climate Change: A Comprehensive Bibliometric Analysis

Wildfire prediction plays a vital role in the management and conservation of forest ecosystems. By providing detailed risk assessments, it contributes to the reduction of fire frequency and severity, safeguards forest resources, supports ecological stability, and ensures human safety. This study systematically reviews wildfire prediction literature from 2003 to 2023, emphasizing research trends and collaborative trends. Our findings reveal a significant increase in research activity between 2019 and 2023, primarily driven by the United States Forest Service and the Chinese Academy of Sciences. The majority of this research was published in prominent journals such as the International Journal of Wildland Fire, Forest Ecology and Management, Remote Sensing, and Forests. These publications predominantly originate from Europe, the United States, and China. Since 2020, there has been substantial growth in the application of machine learning techniques in predicting forest fires, particularly in estimating fire occurrence probabilities, simulating fire spread, and projecting post-fire environmental impacts. Advanced algorithms, including deep learning and ensemble learning, have shown superior accuracy, suggesting promising directions for future research. Additionally, the integration of machine learning with cellular automata has markedly improved the simulation of fire behavior, enhancing both efficiency and precision. The profound impact of climate change on wildfire prediction also necessitates the inclusion of extensive climate data in predictive models. Beyond conventional studies focusing on fire behavior and occurrence probabilities, forecasting the environmental and ecological consequences of fires has become integral to forest fire management and vital for formulating more effective wildfire strategies. The study concludes that significant regional disparities in knowledge exist, underscoring the need for improved research capabilities in underrepresented areas. Moreover, there is an urgent requirement to enhance the application of artificial intelligence algorithms, such as machine learning, deep learning, and ensemble learning, and to intensify efforts in identifying and leveraging various wildfire drivers to refine prediction accuracy. The insights generated from this field will profoundly augment our understanding of wildfire prediction, assisting policymakers and practitioners in managing forest resources more sustainably and averting future wildfire calamities.

Temperature evolution and flame behavior inside a ceiling-vented compartment with different fire source locations under the effect of wind

This work presents an experimental investigation on ceiling-vented compartment fire behavior and thermal characteristics with different fire source locations under the effect of wind associated by CFD simulations. Experiments were carried out under the ambient wind condition, and the fire source was respectively set at windward side, center and leeward side. Results show that: (1) In no-wind cases, a critical heat release rate is found at which the inside temperature decreases with the increasing of fire heat release rate indicating flame flows outside. The critical HRR for fire source attached to sidewall is slightly larger than that when the fire source is located at compartment center, and it increases as vent dimension increases. (2) In ambient wind condition, there is a travelling process that the flame transfers from windward side to leeward side with the increasing of fire HRR. The critical HRR for the transition increases as vent size increases, and decreases as wind speed increases, and is basically independent of fire source location, which is proved to be related to air inflow rate. A Froude number is proposed to characterize the wind effect based on air inflow analysis, and the critical HRR for transition is represented well by the Froude number.

The Recyclability of Fire-Retarded Biobased Polyamide 11 (PA11) Composites Reinforced with Basalt Fibers (BFs): The Influence of Reprocessing on Structure, Properties, and Fire Behavior.

The growing requirements regarding the safety of using polymers and their composites are related to the emergence of more effective, sustainable, and hazardous-limited fire retardants (FRs). Significant amounts of FRs are usually required to effectively affect a polymer's burning behavior, while the knowledge of their recycling potential is still insufficient. At the same time, concerns are related not only to the reduced effectiveness of flame retardancy but also, above all, to the potential deterioration of mechanical properties caused by the degradation of temperature-affected additives under processing conditions. This study describes the impact of the four-time reprocessing of bio-based polyamide 11 (PA11) modified with an intumescent flame-retardant (IFR) system composed of ammonium polyphosphate (APP), melamine cyanurate (MC), and pentaerythritol (PER) and its composites containing additional short basalt fibers (BFs). Composites manufactured via twin-screw extrusion were subjected to four reprocessing cycles using injection molding. A comprehensive analysis of their structural, mechanical, and fire behavior changes in each cycle was conducted. The obtained results confirmed the safety of using the proposed fire-retarded polyamide and its composites while reprocessing under the recommended process parameters without the risk of significant changes in the structure. The partial increase in flammability of reprocessed PA-based materials caused mainly by polymer degradation has been described.