JensenOpenMDAOconnect.py 文件源码

def conferenceWakeOverlap_tune(X, Y, R, boundAngle):

    n = np.size(X)
    boundAngle = boundAngle*np.pi/180.0
    # theta = np.zeros((n, n), dtype=np.float)      # angle of wake from fulcrum
    f_theta = np.zeros((n, n), dtype=np.float)      # smoothing values for smoothing
    q = np.pi/boundAngle                            # factor inside the cos term of the smooth Jensen (see Jensen1983 eq.(3))
    # print 'boundAngle = %s' %boundAngle, 'q = %s' %q
    for i in range(0, n):
        for j in range(0, n):
            if X[i] < X[j]:
                # z = R/tan(0.34906585)
                z = R/np.tan(boundAngle)               # distance from fulcrum to wake producing turbine
                # print z
                theta = np.arctan((Y[j] - Y[i]) / (X[j] - X[i] + z))
                # print 'theta =', theta

                if -boundAngle < theta < boundAngle:

                    f_theta[i][j] = (1. + np.cos(q*theta))/2.
                    # print f_theta

    # print z
    # print f_theta
    return f_theta