# fsd weighted (vn+sd) correlations [u, v, w, y] c(latex="c") = 1.0 - y wrate (latex="\dot{\omega}") = rxn_rate(c) fsd (latex="\Sigma_f'")= sqrt (sqr(ddx(c)) + sqr(ddy(c)) + sqr(ddz(c))) lapc(latex="\Delta c") = d2dx(c) + d2dy(c) + d2dz(c) sd(latex="S_d") = ($rod * lapc + wrate) / fsd nx(latex="n_x") = - ddx(c) / fsd ny(latex="n_y") = - ddy(c) / fsd nz(latex="n_z") = - ddz(c) / fsd unx = u * nx vny = v * ny wnz = w * nz vn(latex="v_n") = unx + vny + wnz divn(latex="\nabla \cdot \vec{n}") = ddx(nx) + ddy(ny) + ddz(nz) divn2 = sqr(divn) # grad(n) : grad(n) gradn_gradn(latex="\nabla \vec{n} : \nabla \vec{n}") = sqr(ddx(nx)) + sqr(ddy(ny)) + sqr(ddz(nz)) + 2*(ddx(ny)*ddy(nx)) + 2*(ddx(nz)*ddz(nx)) + 2*(ddy(nz)*ddz(ny)) absk = abs(divn) vnsd = vn+sd divn_nx = divn*nx gradn_vnsd (latex="\nabla_{\mathrm{n}}(v_n+S_d)") = ddx(vnsd) * nx + ddy(vnsd) * ny + ddz(vnsd) * nz gradt_vnsd1 (latex="\nabla_{\top,x}(v_n+S_d)")= ddx(vnsd) - nx * gradn_vnsd divn2_dndn = divn2 - gradn_gradn sign_divn(latex="\mathrm{sign}(\nabla \cdot \vec{n})") = $dsign(1.0, divn) sign_divn2_dndn = sign_divn * divn2_dndn vnsd_divn = vnsd * divn vnsd_divn_cor = vnsd' * divn' vnsd_divn_nx_cor = vnsd' * divn_nx' vnsd_divn2_dndn_cor = vnsd' * divn2_dndn' vnsd_sign_divn2_dndn_cor = vnsd' * sign_divn2_dndn' vnsd_divn_nx = vnsd * divn_nx vnsd_divn2_dndn = vnsd * divn2_dndn vnsd_sign_divn2_dndn = vnsd * sign_divn2_dndn vnsd_divn_nxfluc = vnsd * divn * nx' vnsd_divn_divnfluc = vnsd * divn * divn' vnsd_divn_abskfluc = vnsd * divn * absk' vnsd_dndn = vnsd * gradn_gradn sign_vnsd_dndn = sign_divn * vnsd * gradn_gradn avg { c, u, v, w, fsd, lapc, ddx_c, ddy_c, ddz_c, d2dx_c, d2dy_c, d2dz_c } avg fsd { u, v, w, nx, ny, nz, absk, divn, unx, vny, wnz, vn, sd, gradt_vnsd1, vnsd, vnsd_divn, vnsd_divn_cor, divn_nx, vnsd_divn_nx, vnsd_divn_nx_cor, divn2_dndn, vnsd_divn2_dndn, vnsd_divn2_dndn_cor, sign_divn2_dndn, vnsd_sign_divn2_dndn, vnsd_sign_divn2_dndn_cor, vnsd_divn_nxfluc, vnsd_divn_divnfluc, vnsd_divn_abskfluc, vnsd_dndn, sign_vnsd_dndn }