Ignition Phase Research Articles

A transformer-based neural network for ignition location prediction from the final wildfire perimeter

Ignition location prediction is crucial for wildfire incident investigation and events reconstruction. However, existing models mainly focus on simulating the wildfire forward and rarely trace the ignition backward. In this paper, a novel transformer-based neural network named ILNet was proposed to predict the ignition location backward from the final wildfire perimeter. The ILNet first concatenated all wildfire-driven data as a composite image and divided it into several regular patches. Then, the self-attention mechanism was adopted to extract global spatial features with a variable scale among these patches. These features were further decoded to output semantic masks of growth phase and ignition phase. The geometric center of ignition phase was defined as the ignition location. Finally, a real wildfire was chosen as the study case. The results show the competitive performance of ILNet model (MIoU: 88.45%, IDE_N: 1.99%, computation time: 0.57s), enabling to improve the traditional field work for government agencies.

Spectroscopic investigation of diesel-piloted ammonia spray combustion

This work investigates the flame emissions of diesel-piloted ammonia spray combustion under conditions relevant to internal combustion engines. Due to ammonia’s carbon-free structure, its flame emissions differ significantly from carbon-containing fuels. This work provides new insights into the combustion process by distinguishing pilot and main fuel combustion by analyzing spectrally resolved flame emission footprints between 275nm and 750nm in a rapid compression expansion machine (RCEM). Additional results based on Shadowgraphy (SG), OH*-chemiluminescence (CL), visible natural flame luminosity (NL) imaging, and heat release rate (HRR) analysis describe the combustion process in detail. OH*, NH*, NH2*, as well as broadband CL from NH2*, NO2*, and H2O* contribute to ammonia flame luminosity. The results show that the combustion process encompasses a pilot ignition phase, a flame transition phase, and an ammonia combustion phase, during which only ammonia-related flame emissions occur and the main share of heat is released. Background corrected OH*, NH*, and NH2* intensities reveal the evolution of individual contributions to the flame emissions. NH2*-CL is the main contributor to visible ammonia flame emissions under the conditions investigated. Therefore, visible flame emissions are a suitable indicator for the flame front during the ammonia combustion phase.

Effects of water direct injection on a combustion phase and performance of six-stroke gasoline homogeneous charge compression ignition engine

An experimental study was conducted to examine how direct water injection (WI) can optimize the combustion phases of a six-stroke gasoline homogenous charge compression ignition (HCCI) engine. With six-stroke HCCI combustion, the limitations of four-stroke HCCI combustion under high loads and the stability of combustion under low loads can be resolved by adding additional compression and expansion stroke. Previous six-stroke HCCI combustion research suggested that the time loss could be reduced by delaying the combustion phase to the top dead center (TDC) with additional cooling. Thus, in this study, the effects of WI on the overall pressure curve, as well as the first and second combustion phases, were studied from a thermal and chemical kinetics perspective. The performance, thermal efficiency, and pressure rise rate were also examined. It was found that WI retarded the first and second combustion. The first and second combustion phases were located after and before TDC, respectively, resulting in a decrease in the first gross mean effective pressure (GMEP) (180–540 CA) and an increase in the second GMEP (540–900 CA). Because the increase of second GMEP was dominant, the indicated thermal efficiency also monotonically increased (2.7–3.5%p). In addition, the maximum pressure rise rate decreased by 23.1% to 65.2%. Thus, the WI can be used to control the combustion characteristics of six-stroke gasoline HCCI engine.

Combustion of Al Nanoparticles Coated with Nitrocellulose/Ethanol/Ether Molecules by Equilibrium Molecular Dynamics Simulations.

Al nanoparticles (ANPs) have high reactivity, but they are easily inactivated by external oxidants. To improve their surface properties, we coat ANPs with a nitrocellulose (NC)/ethanol/ether solution. Comparative discussions are raised from the coating to the combustion process. Our results show that NC/ethanol/ether forms a dense coating layer on the surface of annealed ANPs and passivates ANPs through physical and chemical adsorption. The coating layer can block the contact between the active Al atoms and O2 molecules at low temperatures. In the ignition phase, the NC/ethanol/ether coating layer can increase the density of the O2 molecules around the ANPs and the surface temperature of ANPs. At the end of the ignition phase, the number of O atoms adsorbed on the surface of NC/ethanol/ether coating-passivated ANPs (csANPs) and NC/ethanol/ether coating-annealed ANPs (cANPs) increased by about 60 and 50%, respectively, compared with passivated ANPs (sANPs). Since the desorption and diffusion of the coating layer will expose more reaction sites, ANPs have a shorter ignition delay and a lower ignition temperature. According to the change in atomic displacement, the combustion stage can be divided into three stages: surface oxidation/core melting diffusion, combustion inward propagation, and uniform combustion. The decomposition of NC molecules can increase the combustion speed, combustion time, and efficiency of ANPs. Such improvement will enable ANPs to obtain better storage and combustion performance and play a stronger role in the field of energetic materials.

DISCHARGE DUTY CYCLES EFFECTS OF 20 KHZ AIR ATMOSPHERIC PRESSURE PLASMA JET ON METHYLENE BLUE SOLUTION DEGRADATION

The degradation of methylene blue (MB) using air atmospheric pressure plasma jet (air APPJ) in contact with liquid was proposed. In this study, an AC-driven air APPJ using three discharge duty cycles (30%, 50%, and 80%) of a neon transformer was investigated. In each discharge duty cycle, the ignition and extinguishment phases were characterized. The constituent particles of the air APPJ in the gas phase were observed by an optical emission spectrophotometer (OES). The OES results of all discharge duty cycles found the NO (A-X) bands, •OH radical, N2 second positive system, N2 first negative system, N+, N, and O. The emission spectra produced by the discharge duty cycle of 80% were the highest relative intensity. The effects of the different discharge duty cycles on the acidity and conductivity of water with and without MB were also determined. The complete dye degradation within 30 min was obtained in the discharge duty cycle 80%, which played an essential role in carrying reactive species from the gas phase to the liquid phase, thus promoting the degradation of MB. The best reaction kinetic rate k is 0.1692 min-1, which is six times compared to discharge duty cycle 50%.

The effect and mechanism of the flow deflector on ignition performance of the centrally staged combustor

Lean premixed prevaporized combustors with a centrally staged scheme are capable to reduce NOx emissions. Ignition is one of the key performances of the centrally staged combustor. The present study proposes a novel method to improve ignition performance by using a flow deflector. The effects of various flow deflector lengths and pressure drops on ignition performance and flame kernel propagation are investigated in this work. It is found that ignition performance is significantly improved by the flow deflector. The ignition process is obtained using a high-speed camera under different operating conditions. The timescale of the successful ignition process is analyzed using a statistical method, revealing the effects of the flow deflector length and pressure drop on the timescale of each phase of ignition. The flame kernel propagation trajectory is extracted and analyzed by combining the flow and spray fields. The mechanism of the flow deflector is analyzed by numerical simulation. It is found that with the flow deflector, the local fuel/air ratio and droplet diameter are both improved, which benefits ignition performance. This work proves that the flow deflector is a potential method to improve ignition.

Development and Validation of a CFD Combustion Model for Natural Gas Engines Operating with Different Piston Bowls

Nowadays, an accurate and precise description of the combustion phase is essential in spark-ignition (SI) engines to drastically reduce pollutant and greenhouse gas (GHG) emissions and increase thermal efficiency. To this end, computational fluid dynamics (CFD) can be used to study the different phenomena involved, such as the ignition of the charge, combustion development, and pollutant formation. In this work, a validation of a CFD methodology based on the flame area model (FAM) was carried out to model the combustion process in light-duty SI engines fueled with natural gas. A simplified spherical kernel approach was used to model the ignition phase, whereas turbulent flame propagation was described through two variables. A zero-dimensional evolution of the flame kernel radius was used in combination with the Herweg and Maly formulation to take the laminar-to-turbulent flame transition into account. To estimate the chemical composition of burnt gas, two different approaches were considered—one was based on tabulated kinetics, and the other was based on chemical equilibrium. Assessment of the combustion model was first performed by using different operating points of a light-duty SI engine fueled with natural gas and by using the original piston. The results were validated by using experimental data on the in-cylinder pressure, apparent heat release rate, and pollutant emissions. Afterward, two other different piston bowl geometries were investigated to study the main differences between one solution and the others. The results showed that no important improvements in terms of combustion efficiency were obtained by using the new piston bowl shapes, which was mainly due to the very low (+4%) or null increase in turbulent kinetic energy during the compression stroke and due to the higher heat losses (+20%) associated with the increased surface area of the new piston geometries.

Effects and mechanism of pilot diesel injection strategies on combustion and emissions of natural gas engine

The research objectives of pilot diesel injection (PDI) ignition natural gas technology include high efficiency, clean combustion, and low pilot diesel mass. This study is based on a single-cylinder thermodynamic engine, combined with the CONVERGE simulation model and CHEMKIN chemical reaction kinetics model. The effects and mechanisms of various PDI strategies on the mixture equivalent ratio, temperature, and characteristics of combustion and emissions were investigated. The experimental results showed that the best PDI mass was 8 mg/cycle. The thermal atmosphere and activity in the cylinder were improved with an increase in PDI mass from 2 to 8 mg/cycle, which stabilized the mixture combustion. Further, the effects of different pilot injection timing (PIT) on combustion and emissions were investigated via experiments and simulation by controlling the operating conditions and maintaining a constant PDI total mass. The results show that the diesel had a single low-temperature reaction path when the PIT was close to the top dead center, whereas the PIT at the early stage of the compression stroke (CS) changed the chemical reaction path and accelerated the transformation of CH3 to CH2O, accumulating numerous active groups and accelerating the combustion rate, which is difficult to control the ignition phase. The reaction path of the double PDI strategy was similar to that of the PIT at the early CS stage, and its combustion is closed to premixed combustion; however, the accumulation of active groups was relatively small, and the combustion rate was relatively slow because the ignition phase was controlled by the second PDI, making the combustion phase easy to control. Finally, with the double PDI strategy that had the advantages of efficient combustion and avoidance of knock, the gross indicated thermal efficiency reached 49.3% that involved a −60°crank angle (CA) after top dead center (ATDC) first injection and −4°CA ATDC second injection.

Numerical study on the effects of spark strategies on knocking combustion in a downsized gasoline rotary engine

The application of dual-spark plug in rotary engines (REs) could be regarded as an effective way to improve combustion performance but there is lack of researches about influence of spark strategies on RE knocking. For this reason, the effects of varying dual-spark plug locations and asynchronous ignition phases on local auto-ignition and knocking characteristics of a downsized gasoline RE were studied numerically in this paper. Results showed that asynchronous ignition strategies formed by delaying the trailing-spark ignition timing significantly reduced the knocking intensity (KI) and delayed timing of auto-ignition onset. The appropriate asynchronous ignition phase could induce multiple auto-ignition hot-spots, and the KI caused by multiple hot-spots formed in sequence was higher than that caused by a single hot spot. The arrangement of the dual-spark plug determined the space for flame development, and it was favorable in reducing the KI for the trailing-spark plug to stand an offset from the minor axis of the engine. It should be noted that the KI of the RE was reduced by 87% when the offset distance between the trailing-spark plug location and the minor axis was double that between the leading-spark plug location and the minor axis.

An 18.9 min blue large-amplitude pulsator crossing the ‘Hertzsprung gap’ of hot subdwarfs

Blue large-amplitude pulsators (BLAPs) represent a new and rare class of hot pulsating stars with unusually large amplitudes and short periods. Up to now, only 24 confirmed BLAPs have been identified from more than one billion monitored stars, including a group with pulsation period longer than $\sim 20$ min (classical BLAPs, hereafter) and the other group with pulsation period below $\sim 8$ min. The evolutionary path that could give rise to such kinds of stellar configurations is unclear. Here we report on a comprehensive study of the peculiar BLAP discovered by the Tsinghua University - Ma Huateng Telescopes for Survey (TMTS), TMTS J035143.63+584504.2 (TMTS-BLAP-1). This new BLAP has an 18.9 min pulsation period and is similar to the BLAPs with a low surface gravity and an extended helium-enriched envelope, suggesting that it is a low-gravity BLAP at the shortest-period end. In particular, the long-term monitoring data reveal that this pulsating star has an unusually large rate of period change, P_dot/P=2.2e-6/yr. Such a significant and positive value challenges its origins from both helium-core pre-white-dwarfs and core helium-burning subdwarfs, but is consistent with that derived from shell helium-burning subdwarfs. The particular pulsation period and unusual rate of period change indicate that TMTS-BLAP-1 is at a short-lived (~10^6 yr) phase of shell-helium ignition before the stable shell-helium burning; in other words, TMTS-BLAP-1 is going through a "Hertzsprung gap" of hot subdwarfs.

Particle temperature and composition measurements in the ignition phase of single coal particles and particle groups under conventional and oxy-fuel atmospheres

The transition from single to group particle combustion is experimentally investigated in a laminar flow reactor. Optical techniques including two-colour pyrometry and a sampling probe provide data on surface temperature and composition of high-volatile bituminous coal particles during ignition, volatile combustion, and char burnout. Adjustable particle number densities (PND) permit studying the transition from single to group particle combustion. An optical imaging pyrometer provides simultaneously acquired data on the soot particles during the volatile combustion and the particle temperature, particle size and position in the 3D particle streak. These parameters are investigated as a function of the PND, which is used to differentiate between single and group particle combustion. Additionally, particle sampling provides particle composition data, which together with the particle temperatures extends a previously published data set from the same reactor. The results show a direct relation between the particle temperature during char burnout and the PND. As particles in group combustion absorb a significant amount of thermal energy from the surrounding atmosphere and reduce the oxygen content in the group, the measurements prove a lower temperature for particles that burn in group compared to single particle. Furthermore, sampling at several residence times indicates a notable difference in the burnout process between single particle (SP) and group particle (GP) combustion. While the effect of different atmospheres impacts the results of SP combustion, GP combustion is significantly less affected. The results of the current study are jointly discussed with previously acquired data of the same burner for a thorough interpretation.

Effects of curvature on triple flame propagation in fuel-oxidizer counterflow

In this study, we analyze the propagation of an expanding triple flame in an axisymmetric counterflow of a fuel against an oxidizer. The problem is formulated as a thermo-diffusive model with one-step global reaction. An asymptotic analysis in the limit of large activation energy and weak strain rate is conducted. The study is supported and complemented by numerical simulations carried out for arbitrary values of the strain rate. In addition to the flame front curvature 1/Rt associated with the variation in the reactants concentrations transverse to the mixing layer, the propagation of the expanding triple flame also depends on the azimuthal curvature 1/Rf where Rf is the front leading edge radial distance. As the triple flame expands to large radial distances, its propagation becomes quasi-steady. Under a quasi-steady state assumption, an explicit expression is derived for the displacement speed of the triple flame, which is found to be linearly proportional to the total curvature 1/Rf+1/Rt. Two-dimensional axisymmetric simulations are conducted to validate in particular the quasi-steady assumption. These include transient simulations of the expanding triple flame which are compared to the numerical solution of the steady eigenvalue problem obtained in a frame attached to the propagating front under a quasi-steady assumption. Following a transient ignition phase, the triple flame is found to propagate in a quasi-steady manner when Rf (measured with the stoichiometric planar flame thickness) exceeds 5, approximately. Although the theoretical analysis is performed in the weak strain limit, the linear dependence of the triple flame speed on the curvature 1/Rfis found to be applicable over a wide range of strain rates. Besides, the analysis is extended for inwardly propagating triple flames (flame holes) and similar expressions describing the relationship between displacement speed of the triple flame and curvatures are obtained.

Integrated assessment of volatile organic compounds from industrial biomass boilers in China: emission characteristics, influencing factors, and ozone formation potential.

Industrial biomass boilers (IBBs) are widely promoted in China as a type of clean energy. However, they emit large amount of volatile organic compounds (VOCs) and the emission characteristics and the underlying factors are largely unknown due to the sampling difficulties. In this study, three wood pellet-fueled and two wood residue-fueled IBBs were selected to investigate the characteristics of VOC emissions and to discover their underlying impacting factors. The emission factor of VOCs varied from 21.6 ± 2.8mg/kg to 286.2 ± 10.8mg/kg for the IBBs. Oxygenated VOCs (OVOCs) were the largest group, contributing to 30.3 - 73.6% of the VOC emissions. Significant differences were revealed in the VOC source profiles between wood pellet-fueled and wood residue-fueled IBBs. Operating load, excess air, furnace temperature, and fuel type were identified as the primary factors influencing VOC emissions. The excess air coefficient should be limited below 3.5, roughly corresponding to the operating load of 62% and furnace temperature of 630°C, to effectively reduce VOC emissions. VOC emissions also showed great differences in different combustion phases, with the ignition phase having much greater VOC emissions than the stable combustion and the ember phases. The ozone formation potential (OFP) ranged from 4.3 to 31.2mg/m3 for the IBBs, and the wood residue-fueled IBBs yielded higher OFP than the wood pellet-fueled ones. This study underscored the importance of OVOCs in IBB emissions, and reducing OVOC emissions should be prioritized in formulating control measures to mitigate their impacts on the atmospheric environment and human health.

Indoor fire detection utilizing computer vision-based strategies

Fires are an ever-increasing risk in the world for both indoor and outdoor environments. Current technologies for detection in indoor environments are smoke and flame detectors. However, these detectors have several limitations during both the ignition phase of a fire and propagation. These systems cannot detect an exact position of the fire nor how the fire is spreading, or its size, all of which is necessary information for fire services when dealing with these incidents. A potential solution is to use artificial intelligence techniques such as computer vision, which has shown the potential to detect and recognize objects and activities in indoor spaces. This study aims to develop a vision-based indoor fire and smoke detection system. Existing models based on the Faster R–CNN Inception V2 and the SSD MobileNet V2 models were explored and adopted in this work. This study utilized small training and testing datasets (for indoor specific fire cases) of varying pixel density images. Initial evaluation of the approach was carried out by testing both models on videos, including a mock-up bedroom and living room and a CCTV video of office space. Both high-density smoke environments and flame density scenarios were recognized. The promising results were achieved from using only 480 training images. Despite the success achieved by the Faster R–CNN Inception V2, the SSD MobileNet V2 model showed low accuracy and missed detection results. Future works can focus on integrating this with our previously developed approach, such as occupancy detection, enhancing training data and models, using more advanced detection models, and integrating the proposed approach with the fire fighting and HVAC control systems.

Outdoor charcoal grilling: Particulate and gas-phase emissions, organic speciation and ecotoxicological assessment

Charbroiling is a major source of air pollution worldwide. In this study, the particulate and gas-phase emissions from the charcoal lighting phase and during the grilling of meat (pork and rump cap) and fish (sardine and salmon) on an outdoor barbecue grill were characterized. Some gaseous compounds (ethane, hexane, NO2, N2O, SO2, NH3, HCl) did not display significant variations between samples and the background level, indicating that they are not emitted during barbecuing. During the charcoal heating phase, levels of total volatile organic compounds (TVOCs) increased 6 times above the background value. Four-to 5-fold increases in TVOC concentrations were observed when grilling sardines and salmon, while rises of 1.3–1.5 were recorded for meat. Emission factors of 32.4 g PM10 kg−1 and 22.7 g TVOCs kg−1 were obtained for the biofuel ignition phase. PM10 emission rates of 472, 531, 1104 and 918 mg kg−1 were estimated for pork, rump cap, sardine and salmon charbroiling, respectively. TVOC emissions ranged from 23.9 mg kg−1 (pork) to 82.6 mg kg−1 (salmon). Organic carbon accounted for 35.0% of the PM10 emitted during the ignition and flaming phases of the biofuel but represented mass fractions of 56–64% of the particulate emissions during food charbroiling. About 235 organic compounds were quantified in the PM10 samples. The ecotoxicity was assessed using the kinetic version of the Vibrio fischeri bioluminescence inhibition bioassay. All samples were classified as very toxic or toxic. Ecotoxicity was statistically correlated with several n-alkanes, PAHs and alkyl-PAHs, anhydrosugars, acids, and phenolic compounds.

Ignition dynamics of radio frequency discharge in atmospheric pressure cascade glow discharge

A cascade glow discharge in atmospheric helium was excited by a microsecond voltage pulse and a pulse-modulated radio frequency (RF) voltage, in which the discharge ignition dynamics of the RF discharge burst was investigated experimentally. The spatio-temporal evolution of the discharge, the ignition time and optical emission intensities of plasma species of the RF discharge burst were investigated under different time intervals between the pulsed voltage and RF voltage in the experiment. The results show that by increasing the time interval between the pulsed discharge and RF discharge burst from 5 μs to 20 μs, the ignition time of the RF discharge burst is increased from 1.6 μs to 2.0 μs, and the discharge spatial profile of RF discharge in the ignition phase changes from a double-hump shape to a bell-shape. The light emission intensity at 706 nm and 777 nm at different time intervals indicates that the RF discharge burst ignition of the depends on the number of residual plasma species generated in the pulsed discharges.

Effects of humidity on the dynamics and electron recombination of a pin-to-pin discharge in He + H2O at atmospheric pressure

Control of the plasma chemistry is essential for the effectiveness of atmospheric pressure plasmas in many applications. For this, the effects of the humidity of the feed gas on the discharge chemistry need to be considered. Detailed studies are scarce and many of them are dominated by surface interactions, obscuring any volume effects. Here, a negative nanosecond pulsed discharge is generated in a pin–pin 3 mm gap geometry in He + H2O that enables the study of volume kinetics due to minimal surface area. The effect of humidity on the discharge development, electric field and electron density is investigated through experiments and modelling. It is found that the presence of water vapour affects both the electron density at the start of the pulse (remaining from the previous pulse) and the ionisation rates during the ignition phase, leading to a complex dependence of the discharge development speed depending on the water concentration. The electron decay is studied using the 0D global kinetics model GlobalKin. The dominant reactions responsible for the electron decay depending on the concentration of water vapour are determined by comparing experimental and simulated results and these reactions are grouped in simplified kinetic models. It is found that with water concentrations increasing from 0 to 2500 ppm, the complexity of the dominant reactions increases with in particular O2 +, H2O3 + and water clusters becoming important for high water concentrations. This work also provides experimental data for validation of kinetic models of plasmas in controlled environments.

Development and evaluation of a vision-based transfer learning approach for indoor fire and smoke detection

Fire poses a significant risk across industrial and domestic settings, especially to firefighters who must tackle the blaze. Current technology for detection in indoor environments are smoke detectors and flame detectors. However, these detectors have several limitations during the ignition phase of a fire and propagation. These systems cannot detect an exact position of the fire nor how the fire is spreading or its size, all of which is necessary information for fire services when dealing with these incidents. A potential solution is to use artificial intelligence techniques such as computer vision, which has shown the potential to detect and recognise objects and activities in indoor spaces. This study aims to develop a vision-based fire and smoke detection system. A deep learning technique that incorporates convolutional neural networks (CNN) was utilised to develop the real-time detection approach that can potentially provide necessary information for fire services, including identifying the position and size of the fire and how the fire spreads. A transfer learning approach using a pre-trained model was used to train the detector. Based on the detection and recognition tests using indoor fire and smoke videos, results indicated that the fire detection achieved up to 92.37% correct detections while the smoke detection did not perform as well. Hence, further improvement and evaluation of the detection approach will be conducted in future work, focusing on the impact of different parameters such as the detection model, building type, indoor space size and positioning of the detection camera. The present study provides an insight into the capabilities and potential applications of the concept.

Distinct mutations and lineages of SARS-CoV-2 virus in the early phase of COVID-19 pandemic and subsequent 1-year global expansion.

A novel coronavirus, SARS‐CoV‐2, has caused over 274 million cases and over 5.3 million deaths worldwide since it occurred in December 2019 in Wuhan, China. Here we conceptualized the temporospatial evolutionary and expansion dynamics of SARS‐CoV‐2 by taking a series of the cross‐sectional view of viral genomes from early outbreak in January 2020 in Wuhan to the early phase of global ignition in early April, and finally to the subsequent global expansion by late December 2020. Based on the phylogenetic analysis of the early patients in Wuhan, Wuhan/WH04/2020 is supposed to be a more appropriate reference genome of SARS‐CoV‐2, instead of the first sequenced genome Wuhan‐Hu‐1. By scrutinizing the cases from the very early outbreak, we found a viral genotype from the Seafood Market in Wuhan featured with two concurrent mutations (i.e., M type) had become the overwhelmingly dominant genotype (95.3%) of the pandemic 1 year later. By analyzing 4013 SARS‐CoV‐2 genomes from different continents by early April, we were able to interrogate the viral genomic composition dynamics of the initial phase of global ignition over a time span of 14 weeks. Eleven major viral genotypes with unique geographic distributions were also identified. WE1 type, a descendant of M and predominantly witnessed in western Europe, consisted of half of all the cases (50.2%) at the time. The mutations of major genotypes at the same hierarchical level were mutually exclusive, which implies that various genotypes bearing the specific mutations were propagated during human‐to‐human transmission, not by accumulating hot‐spot mutations during the replication of individual viral genomes. As the pandemic was unfolding, we also used the same approach to analyze 261 323 SARS‐CoV‐2 genomes from the world since the outbreak in Wuhan (i.e., including all the publicly available viral genomes) to recapitulate our findings over 1‐year time span. By December 25, 2020, 95.3% of global cases were M type and 93.0% of M‐type cases were WE1. In fact, at present all the five variants of concern (VOC) are the descendants of WE1 type. This study demonstrates that viral genotypes can be utilized as molecular barcodes in combination with epidemiologic data to monitor the spreading routes of the pandemic and evaluate the effectiveness of control measures. Moreover, the dynamics of viral mutational spectrum in the study may help the early identification of new strains in patients to reduce further spread of infection, guide the development of molecular diagnosis and vaccines against COVID‐19, and help assess their accuracy and efficacy in real world at real time.

Phases and Time-Scales of Ignition and Burning of Live Fuels

Wildland fires impact ecosystems and communities worldwide. Many wildfires burn in living or a mixture of living and senescent vegetation. Therefore, it is necessary to understand the burning behavior of living fuels, in contrast to just dead or dried fuels, to more effectively support fire management decisions. In this study, the ignition and burning behaviors of needles placed in convective heat flux were evaluated. The species included longleaf pine (Pinus palustris), Douglas-fir (Pseudotsuga menziesii), western red cedar (Thuja plicata), ponderosa pine (Pinus ponderosa), western larch (Larix occidentalis), pacific yew (Taxus brevifolia), white spruce (Picea glauca), and sagebrush (Artemisia tridentate). The ignition and burning behaviors were related to live fuel moisture content (LFMC), pilot flame temperatures, and convective heat fluxes. The different phases of ignition and burning were captured using high-speed imaging. In general, four burning phases can be observed: droplet ejection and burning, a transition phase, flaming combustion, and smoldering combustion. Ejection and subsequent burning of droplets can occur prior to sustained flaming ignition only in live fuels. For some species (e.g., longleaf pine, ponderosa pine, white spruce) droplet ejection and burning can reduce ignition times relative to dried fuel with lower LFMC. In general, the transition phase tends to take longer than the flaming and droplet phases (when these occur). During the transition phase, the fuels are heated and pyrolysis occurs. Time-scales to ignition and the different phases of ignition and burning vary more among live fuels than dead and dried fuels. This conclusion indicates that other parameters, such as chemical composition and structural morphology of the fuel, can significantly influence the burning of live fuels.