ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2023, Vol. 44 ›› Issue (1): 627518-627518.doi: 10.7527/S1000-6893.2022.27518
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Qilei GUO1,2, Weimin SANG1,3(), Junjie NIU1, Ye YUAN4
Received:
2022-05-25
Revised:
2022-06-15
Accepted:
2022-09-09
Online:
2023-01-15
Published:
2022-09-13
Contact:
Weimin SANG
E-mail:aeroicing@sina.cn
Supported by:
CLC Number:
Qilei GUO, Weimin SANG, Junjie NIU, Ye YUAN. UAV flight strategy considering icing risk under complex meteorological conditions[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023, 44(1): 627518-627518.
Table 1
Characteristics of four microphysics schemes
微物理过程 | 方案特征 |
---|---|
WSM6方案 | 考虑了雨、水汽、云水、雪、云冰、霰等6种水成物的处理,允许混合相变过程和过冷水的存在,分开处理冰与水的饱和调整过程,适合格距在云尺度和中尺度间的格点研究。 |
Purdue-Lin方案 | 一维云模型,可对水汽、云水、雨、云冰、雪、霰等6种水成物处理,考虑了夹带、云微物理、压力扰动、横向涡流扩散和垂直涡流扩散的影响,适合理论研究及高分辨率的实测数据研究。 |
Thompson方案 | 可预测云水、云冰、雨、雪和霰等5种水凝物质量浓度及云冰和雨的数量浓度。该方案最初针对航空结冰问题而改进设定,采用了相对更为复杂的混合相过程公式,尤其是对雪类转换机制的定义使其对云中LWC预测表现出色。 |
Morrison方案 | 基于完整的二矩(即质量混合比和数量浓度)方案,可预测与Thompson方案相同的5种水凝物的质量浓度,还可获得云冰、雪、雨和霰的数量浓度。对上述4种水凝物的质量混合比和数量浓度的预测可以更可靠地描述其尺寸分布。 |
Algorithm 1 Ice tolerance route planning based on PSO
结冰容限航迹规划算法 |
---|
1. 设置必要算法参数,并随机产生一个初始种群 2. 计算每个粒子在初始时刻总的违反约束度TD m,超过容限则重新生成粒子 3. 迭代计算初始时刻种群的全局最优位置 4. while k ≤ kmax do 5. for i=1:K do 6. 更新PSO算法中的粒子i的速度 7. 根据 8. if 9. 粒子i视为暂时可行粒子 10. else 11. 粒子i视为暂时不可行粒子 12. end if 13. 如 14. 利用解的可行性原则更新粒子i的个体最优位置 15. end for 16. 更新种群的全局最优位置 17. for i=1:K do 18. 更新PSO算法中粒子的控制参数:w、c1、c2 19. end for 20. 迭代次数自加,即k = k + 1 21. end while 22. 输出种群的全局最优位置 |
Table 4
Verification condition
工况 | T/K | H/m | MVD/μm | LWC/ (g·m-³) | V/ (m∙s-1) |
---|---|---|---|---|---|
Case 01 | 258 | 3 000 | 15 | 0.445 5 | 50 |
Case 02 | 268 | 1 200 | 15 | 0.697 0 | 55 |
Case 03 | 243.15 | 6 700 | 15 | 0.200 0 | 60 |
Case 04 | 268.15 | 1 200 | 25 | 0.402 7 | 65 |
Case 05 | 258 | 3 000 | 25 | 0.227 7 | 70 |
Case 06 | 243.15 | 6 700 | 25 | 0.099 5 | 75 |
Case 07 | 268 | 1 200 | 35 | 0.206 7 | 80 |
Case 08 | 258 | 3 000 | 35 | 0.117 3 | 85 |
Case 09 | 243.15 | 6 700 | 35 | 0.049 8 | 90 |
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