You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 airline
【Schema】
# Table: Air Carriers
[
(Code:INTEGER, Primary Key, Examples: [19031, 19032, 19033]),
(Description:TEXT, Examples: [Mackey International Inc.: MAC])
]
# Table: Airports
[
(Code:TEXT, Primary Key, Examples: [01A, 03A, 04A]),
(Description:TEXT, Examples: [Afognak Lake, AK: Afognak Lake Airport])
]
# Table: Airlines
[
(FL_DATE:TEXT, Examples: [2018/8/1, 2018/8/2, 2018/8/3]),
(OP_CARRIER_AIRLINE_ID:INTEGER, Examples: [19805, 20427, 21167]),
(TAIL_NUM:TEXT, Examples: [N956AN, N973AN, N9006]),
(OP_CARRIER_FL_NUM:INTEGER, Examples: [1587, 1588, 1590]),
(ORIGIN_AIRPORT_ID:INTEGER, Examples: [12478, 14107, 11042]),
(ORIGIN_AIRPORT_SEQ_ID:INTEGER, Examples: [1247805, 1410702, 1104205]),
(ORIGIN_CITY_MARKET_ID:INTEGER, Examples: [31703, 30466, 30647]),
(ORIGIN:TEXT, Examples: [JFK, PHX, CLE]),
(DEST_AIRPORT_ID:INTEGER, Examples: [14107, 11618, 11298]),
(DEST_AIRPORT_SEQ_ID:INTEGER, Examples: [1410702, 1161802, 1129806]),
(DEST_CITY_MARKET_ID:INTEGER, Examples: [30466, 31703, 30194]),
(DEST:TEXT, Examples: [PHX, EWR, DFW]),
(CRS_DEP_TIME:INTEGER, Examples: [1640, 1512, 744]),
(DEP_TIME:INTEGER, Examples: [1649, 1541, 741]),
(DEP_DELAY:INTEGER, Examples: [9, 29, -3]),
(DEP_DELAY_NEW:INTEGER, Examples: [9, 29, 0]),
(ARR_TIME:INTEGER, Examples: [2006, 2350, 938]),
(ARR_DELAY:INTEGER, Examples: [44, 53, -2]),
(ARR_DELAY_NEW:INTEGER, Examples: [44, 53, 0]),
(CANCELLED:INTEGER, Examples: [0, 1]),
(CANCELLATION_CODE:TEXT, Examples: [A, B, C]),
(CRS_ELAPSED_TIME:INTEGER, Examples: [342, 285, 176]),
(ACTUAL_ELAPSED_TIME:INTEGER, Examples: [377, 309, 177]),
(CARRIER_DELAY:INTEGER, Examples: [9, 0, 43]),
(WEATHER_DELAY:INTEGER, Examples: [0, 2, 48]),
(NAS_DELAY:INTEGER, Examples: [35, 53, 0]),
(SECURITY_DELAY:INTEGER, Examples: [0, 42, 4]),
(LATE_AIRCRAFT_DELAY:INTEGER, Examples: [0, 6, 73])
]
【Foreign keys】
Airlines.ORIGIN=Airports.Code
Airlines.DEST=Airports.Code
Airlines.OP_CARRIER_AIRLINE_ID=Air Carriers.Code

    【Question】
    On August 2018, which day had the highest number of cancelled flights due to the most serious reasons in Dallas/Fort Worth International? On August 2018 refers to FL_DATE like '2018/8%'; day with the highest number of cancelled flights refers to MAX(COUNT(FL_DATE WHERE CANCELLED = 1)); cancelled due to the most serious reasons refers to CANCELLATION_CODE = 'A'; in Dallas/Fort Worth International refers to Description = 'Dallas/Fort Worth, TX: Dallas/Fort Worth International';

    【Evidence】
    On August 2018 refers to FL_DATE like '2018/8%'; day with the highest number of cancelled flights refers to MAX(COUNT(FL_DATE WHERE CANCELLED = 1)); cancelled due to the most serious reasons refers to CANCELLATION_CODE = 'A'; in Dallas/Fort Worth International refers to Description = 'Dallas/Fort Worth, TX: Dallas/Fort Worth International';

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT T2.FL_DATE FROM Airports AS T1 INNER JOIN Airlines AS T2 ON T1.Code = T2.ORIGIN WHERE T2.FL_DATE LIKE '2018/8%' AND T1.Description = 'Dallas/Fort Worth, TX: Dallas/Fort Worth International' AND T2.ORIGIN = 'DFW' AND T2.CANCELLED = 1 AND T2.CANCELLATION_CODE = 'A' GROUP BY T2.FL_DATE ORDER BY COUNT(T2.FL_DATE) DESC LIMIT 1