Fire

This study investigates the effect of the flame tube convergent segment wall configuration on the performance of a High-Temperature-Rise (HTR) triple-swirler main combustor. Three configurations were evaluated: the Vitosinski principle (Scheme A), the equal velocity gradient criterion (Scheme B), and a novel convex-arc flow-facing method (Scheme C). Three-dimensional numerical simulations were conducted using validated RANS equations with the Realizable k-ε turbulence model and a non-premixed PDF combustion model. The results demonstrate that the proposed Scheme C, characterized by an inflection-free convex contour, successfully avoids the localized high-velocity region and achieves a more uniform flow field. A systematic comparison reveals that Scheme C achieves the highest outlet temperature distribution quality (lowest OTDF and RTDF), the highest combustion efficiency, and the lowest total pressure loss (TPL) in the convergent segment among the three designs. In conclusion, the comprehensive analysis confirms that the convex-arc design (Scheme C), by eliminating the geometric discontinuity of an inflection point, provides the best overall performance for the HTR combustor under takeoff conditions.

Wildfires are a recurring dry-season hazard in northern Thailand, contributing to severe air pollution and trans-boundary haze. However, the region lacks the ground-based measurements necessary for monitoring Live Fuel Moisture Content (LFMC), a key variable influencing vegetation flammability. This study presents a preliminary framework for near-real-time (NRT) LFMC estimation using Sentinel-2 multispectral imagery. The system integrates normalized vegetation and moisture-related indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Infrared Index (NDII), and the Moisture Stress Index (MSI) with an NDVI-derived evapotranspiration fraction (ETf) within a heuristic modeling approach. The workflow includes cloud and shadow masking, weekly to biweekly compositing, and pixel-wise normalization to address the persistent cloud cover and heterogeneous land surfaces. Although currently unvalidated, the LFMC estimates capture the relative spatial and temporal variations in vegetation moisture across northern Thailand during the 2024 dry season (January–April). Evergreen forests maintained higher moisture levels, whereas deciduous forests and agricultural landscapes exhibited pronounced drying from January to March. Short-lag responses to rainfall suggest modest moisture recovery following precipitation, although the relationship is influenced by additional climatic and ecological factors not represented in the heuristic model. LFMC-derived moisture classes reflect broad seasonal dryness patterns but should not be interpreted as direct fire danger indicators. This study demonstrates the feasibility of generating regional LFMC indicators in a data-scarce tropical environment and outlines a clear pathway for future calibration and validation, including field sampling, statistical optimization, and benchmarking against global LFMC products. Until validated, the proposed NRT LFMC estimation product should be used to assess relative vegetation dryness and to support the refinement and development of future operational fire management tools, including early warnings, burn-permit regulation, and resource allocation.

Lightning-ignited wildfires represent a dominant natural disturbance agent in the Greater Khingan Mountains of northeastern China; however, the relationship between their occurrence and lightning characteristics remains insufficiently quantified. This study analyzed cloud-to-ground (CG) lightning data (2019–2024) and 417 lightning-ignited wildfires (2019–2024) using a full-waveform lightning detection network and spatial matching based on the Minimum Distance Method. Lightning activity shows pronounced spatiotemporal clustering, with more than 93% of flashes occurring in summer and a diurnal peak at 15:00. About 74.6% of wildfires ignited within 1 km of a lightning strike, and the holdover time exhibited clear seasonality, peaking in August (≈317 h). Negative CG (−CG) flashes dominated ignition events (56.5% multiple-stroke, average multiplicity = 2.60), and igniting flashes were concentrated within the −10 to −30 kA peak-current range, suggesting a key threshold for ignition. Vegetation type strongly influenced ignition efficiency: cold temperate and temperate coniferous forests recorded the highest lightning and fire counts, while alpine grasslands and sedge meadows showed the highest lightning ignition efficiency (LIE). These findings clarify how lightning electrical properties and vegetation conditions jointly determine ignition probability and provide a scientific basis for improving lightning-ignited wildfire risk monitoring and early-warning systems in boreal forest regions.