Effect of surface roughness on crosswind deflection and hit probability for large caliber direct-fire ballistics

Abstract

The study introduces a new wind profile model that dynamically integrates mean wind stratification, turbulence, and surface roughness effects along the trajectory of large-caliber direct fire ballistics simulator. The new description of wind is compared against the legacy wind model on downrange deflection due to crosswind and first round hit probability. The methodology develops a deterministic Height and Surface Roughness Dependent (HASRD) mean wind stratification model, and combines this with a Von Karman turbulent signal for a novel description of atmospheric wind. Another key aspect of this research is the use of real-world surface roughness data from global land cover datasets to inform the HASRD model, thus enabling greater situational accuracy. The present work reveals that the new HASRD model generates statistically significant differences in downrange deflections compared to the legacy model. The difference in first round hit probabilities calculated using the legacy and HASRD wind model was also statistically significant. The findings indicate that rougher terrains generally cause slower wind speeds and smaller wind speed deviations, thus causing higher hit probabilities when compared to smoother terrains. Extreme surface roughness profiles, such as sudden changes or very smooth/rough terrains, show the most significant differences in hit probability and downrange deflection. This integrated approach provides a deeper understanding of atmospheric conditions affecting weapon system accuracy, emphasizing the crucial role of surface roughness in wind profiles to enhance combat engagement effectiveness in direct fire ballistics.iii TABLE OF CONTENTS NOMENCLATURE vi ACKNOWLEDGMENTS vii ACKNOWLEDGMENTS This work was supported by ARL DEVCOM (W911QX23D0002). All work presented in this thesis is unclassified and based on publicly available data. Any opinions expressed in this thesis are solely of the author and do not represent the viewpoints of the funding agency. The following people contributed their advice and time to improve this report: Ms. Jennifer Forsythe, US Army Futures Command DEVCOM Analysis Center, supplied professional advice on TAM use. Dr. Tomas Bober, US Army Futures Command DEVCOM Armaments Center, generously provided code that enabled the implementation of mean and turbulent wind models. Mr. Vignesh Selvanayagam and Mr. Tony Smoragiewicz converted TAM from Fortran into Matlab and contributed to the improvements of TAM 3.0. Mr. Matthew Tortolani conducted preliminary wind simulations and small caliber tests. Mr. Peter Kefallinos provided expert knowledge of tank use. Dr. Rifat Sipahi led this investigation, reviewed the report and suggested numerous improvements.