paramsNom_O.errtol1 = 0 paramsNom_O.errtol2 = 0 paramsNom_O.dtGdn = 1 # s paramsNom_O.hmin = 3 paramsNom_O.hmax = paramsNom_O.p.halt + 1e-7 paramsNom_O.tf = 6000 # copy generic params for probe and ballistic probe paramsNom_P = copy.deepcopy(paramsNom_O) # ============================================================================= # Orbiter Setup # ============================================================================= # vehicle paramsNom_O.BC = 130 paramsNom_O.A = paramsNom_O.m / (paramsNom_O.BC * paramsNom_O.CD) paramsNom_O.CL = paramsNom_O.CD * paramsNom_O.LD paramsNom_O.Rn = np.sqrt(paramsNom_O.A / np.pi) / 2 # search brackets for Brent's Method paramsNom_O.sig1 = 0 paramsNom_O.sig2 = 180 paramsNom_O.ts1 = 1 paramsNom_O.ts2 = 300 # target state paramsNom_O.raStar = (250 + paramsNom_O.p.rad) * 1e3 paramsNom_O.rpStar = (250 + paramsNom_O.p.rad) * 1e3 # nominal simulation values t0 = 0
paramsNom.p = constants.MARS
paramsNom.returnTimeVectors = True
### INPUT ATM TABLE - GET ATM TABLE FROM GRAM DATA FILE
paramsNom.dMode = 'table'
filename = '../data/dens_Mars_nom.txt'
atmdata = np.genfromtxt(filename, names=True)
paramsNom.atmdat = np.array([atmdata['Var_X'], atmdata['DENSAV']])
### VEHICLE PARAMS
paramsNom.m = 2920 # kg, roughly MSL mass
paramsNom.CD = 1.6 # roughly MSL CD
paramsNom.LD = 0.25
paramsNom.BC = 130
paramsNom.A = paramsNom.m / (paramsNom.BC * paramsNom.CD)
paramsNom.CL = paramsNom.CD * paramsNom.LD
paramsNom.Rn = np.sqrt(paramsNom.A / np.pi) / 2
### WIND-RELATIVE INITIAL STATE
paramsNom.lat = 18.38
paramsNom.lon = -77.58
paramsNom.alt = paramsNom.p.halt
paramsNom.efpaWR = -12
paramsNom.hdaWR = 0
paramsNom.vmagWR = 6
### GET OTHER STATE TYPES (and assume t0 = 0)
paramsNom.x0, paramsNom.vInfvec_N = LLAEHV2RV(paramsNom.lat, paramsNom.lon,
paramsNom.alt, paramsNom.efpaWR,
paramsNom.hdaWR,
# generate input realizations
params.efpa_Y = norm.rvs(size = 1).item(0)
params.efpaWR = efpamean + efpastd * params.efpa_Y
params.vmag_Y = norm.rvs(size = 1).item(0)
params.vmagWR = vmagmean + vmagstd * params.vmag_Y
params.CD_Y = norm.rvs(size = 1).item(0)
params.CD = CDmean + CDstd * params.CD_Y
params.m_Y = norm.rvs(size = 1).item(0)
params.m = mmean + mstd * params.m_Y
params.BC = params.m / (params.CD * Anom)
params.A = Anom
# run sim
print('\nTrial {}'.format(i_trial+1))
outs = Outs()
outsList.append(mainAD(params, tspan, events, outs))
paramsList.append(getQoIParams(params))
m_YList.append(params.m_Y)
CD_YList.append(params.CD_Y)
efpa_YList.append(params.efpa_Y)
vmag_YList.append(params.vmag_Y)
atm_YsList.append(params.atm_Ys)
# every 50 trials, save all results to a file
