Producing high-resolution near-real-time forecasts of fire behavior and smoke impact that are useful for fire and air quality management requires accurate initialization of the fire location. One common representation of the fire progression is through the fire arrival time, which defines the time that the fire arrives at a given location. Estimating the fire arrival time is critical for initializing the fire location within coupled fire-atmosphere models. We present a new method that utilizes machine learning to estimate the fire arrival time from satellite data in the form of burning/not burning/no data rasters. The proposed method, based on a support vector machine (SVM), is tested on the 10 largest California wildfires of the 2020 fire season, and evaluated using independent observed data from airborne infrared (IR) fire perimeters. The SVM method results indicate a good agreement with airborne fire observations in terms of the fire growth and a spatial representation of the fire extent. A 12% burned area absolute percentage error, a 5% total burned area mean percentage error, a 0.21 False Alarm Ratio average, a 0.86 Probability of Detection average, and a 0.82 Sørensen’s coefficient average suggest that this method can be used to monitor wildfires in near-real-time and provide accurate fire arrival times for improving fire modeling even in the absence of IR fire perimeters.

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The objective of this study is to identify, evaluate, and provide recommendations towards the realisation of near-term hypersonic flight hardware through the consideration of carrier vehicle constraints. The current rush of available funds for hypersonic research cannot cause a program to ignore growth potential for future missions. The prior NB-52 carrier vehicles, famous for the X-15 and X-43A missions, are retired. Next generation hypersonic demonstrator requirements will necessitate a substitution of carrier vehicle capability. Flight vehicle configuration, technology requirements, and recommendations are arrived at by constructing and evaluating a hypersonic technology demonstrator design matrix. This multi-disciplinary parametric sizing investigation of hypersonic vehicle demonstrators focuses on the evaluation of the combined carrier platform, booster, and hypersonic cruiser solution space topography. Promising baseline configurations are evaluated against operational requirements by trading fuel type, endurance cruise time, and payload weight. The multi-disciplinary study results are constrained with carrier payload mass and geometry limitations. The multi-disciplinary results provide physical insights into near-term hypersonic demonstrator payload and cruise time requirements that will stretch the capability of existing carrier aircraft. Any growth in hypersonic research aircraft size or capability will require new carrier vehicle investments.

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