The five values of B and the corresponding best-fit values of A used to compute the
Mode-5 distributions shown in Figure 9 through Figure 13 are tabulated in Table 20. It
is apparent that the value of A is dependent on both qcx. and B. In general, if a larger
value of B is selected, a larger value of A is required to effect a fit with the random-
attitude-tum data. On the other hand, if the breakup qcx. is increased, the required
value of A must be decreased. Only qcx. is critical since, as shown later, any value of B,
together with its corresponding value of A, can be used in the launch-area risk
computations if significant targets do not lie within ±80° of the flight line.

                      Table 20. Shaping Constants for Atlas IIAS
                        Breakup qcx.
                        (deg-lb/ft2)       B             A
                           none           1,000        1.90
                        20,000                         2.75
                         14,000 *                     3.00*
                        10,000                        3.20
                          5,000                       3.45
                          none           50,000       3.15
                        20,000                        4.10
                        10,000                        4.50
                          5,000                       4.75
                          none          100,000       3.40
                        20,000                        4.30
                        10,000                        4.75
                          5,000                       5.00
                          none          500,000       4.00
                        20,000                        4.85
                        10,000                        5.30
                          5,000                       5.55
                          none        5,000,000       4.75
                        20,000                        5.65
                        10,000                        6.10
                          5,000                       6.30
                      *interpolated




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