A python library to compute exact view factors between planar faces (Documentation).
This code computes the radiation view factor between polygons using the double contour integral method described in (Mazumder and Ravishankar 2012) and (Schmid 2016).
It uses the handy Pyvista package to deal with geometrical aspects of such problems.
- Use pyvista to import your geometry (*.stl, *.vtk, *.obj, ...) or alternately draw it with the same package.
- Optionally check that the faces can "see" each other with
get_visibility(face1, face2) - Optionally check that no obstruction lies between them
get_visibility_obstruction(face1, face2, obstacle) - Compute the view factor from
face2toface1withcompute_view_factor(face1, face2): Done!
Suppose we want to compute the radiation view factor between a triangle and a rectangle.
You are now 18 lines of code away from your first view factor computation:
import pyvista as pv
import pyviewfactor as pvf
# first define a rectangle...
pointa = [1, 0, 0]
pointb = [1, 1, 0]
pointc = [0, 1, 0]
pointd = [0, 0, 0]
rectangle = pv.Rectangle([pointa, pointb, pointc, pointd])
# ... then a triangle
pointa = [1, 0, 1]
pointb = [1, 1, 1]
pointc = [0, 1, 1]
liste_pts = [pointa, pointb, pointc]
liste_pts.reverse() # let us put the normal the other way around (facing the rectangle)
triangle = pv.Triangle(liste_pts) # ... done with geometry.
# preliminary check for visibility
if pvf.get_visibility(rectangle , triangle):
F = pvf.compute_viewfactor(rectangle, triangle)
print("View factor from triangle to rectangle = ", F)
else:
print("Not facing each other")You usually get your geometry from a different format? (*.idf, *.dat, ...)
Check pyvista's documentation on how to generate a PolyData facet from points.
We will now compute the view factors within a more complex geometry: a closed sphere (clipped in half below), with inwards facing normals, so the faces can "see" each other. Note that the face-to-face visibility is unobstructed (for obstructed geometries, see next section).
The field of view factors from one facet to all others will be computed and stored in a VTK file, which you can explore with the open source Paraview software.
Following snippet can be reused as a kick-start for your own purposes:
import pyvista as pv
import numpy as np
from pyviewfactor import compute_viewfactor, fc_unstruc2poly # viewfactor + a useful conversion function
from tqdm import tqdm # for a fancy progress bar
# create a raw sphere with pyvista
sphere = pv.Sphere(radius=50, center=(0, 0, 0), direction=(0, 0, 1),
theta_resolution=9, phi_resolution=9)
# and put the normals inwards please
sphere.flip_normals()
# let us chose a cell to compute view factors from
chosen_face = sphere.extract_cells(10)
# convert the face from UnstructuredGrid to PolyData
chosen_face = fc_unstruc2poly(chosen_face)
# "one array to contain them all" -> the results will be stored there
F = np.zeros(sphere.n_cells)
# now let us compute the view factor to all other faces
# (with a fancy progress bar, iterating over the mesh's faces)
for i in tqdm(range(sphere.n_cells), total=sphere.n_cells):
face = sphere.extract_cells(i) # other facet
face = fc_unstruc2poly(face) # convert to PolyData
F[i] = compute_viewfactor(face, chosen_face) # compute VF
print("Complementarity check: \n (e.g. is \sum_{i=0}^n F_i =? 1)", np.sum(F))
# put the scalar values in the geometry
sphere.cell_data["F"] = F
sphere.save("./sphere.vtk") # ... and save.The results look as per following images showing the view factor from the chosen cell to all others.
For building simulation purposes, it may prove to be useful to compute the ground and sky view factors of a given wall, or the view factor of the wall to other walls in the built environment. In following example (available in the "examples" folder), we compute the view factors of the environment of the purple wall depicted below.
import numpy as np
import pyvista as pv
from tqdm import tqdm
import pyviewfactor as pvf
# read the geometry
mesh = pv.read("./built_envmt.vtk")
meshpoly = pvf.fc_unstruc2poly(mesh) # convert to polydata for obstruction check
# identify who is who
i_wall = np.where(mesh["wall_names"]=='wall')[0]
i_sky = np.where(mesh["wall_names"]=='sky')[0]
i_building1 = np.where(mesh["wall_names"]=='building1')[0]
i_building2 = np.where(mesh["wall_names"]=='building2')[0]
# get the different elements
wall = mesh.extract_cells(i_wall)
sky = mesh.extract_cells(i_sky)
building1 = mesh.extract_cells(i_building1)
building2 = mesh.extract_cells(i_building2)
# convert to polydata
wall = pvf.fc_unstruc2poly(wall)
Fsky = 0
# for all cells constituting the ensemble
for patch in tqdm(i_sky):
sky = mesh.extract_cells(patch) # extract one cell
sky = pvf.fc_unstruc2poly(sky) # convert to polydata
if pvf.get_visibility(sky, wall): # if the can see each other...
if pvf.get_visibility_raytrace(sky, wall, meshpoly): # ... if no obstruction
Fsky += pvf.compute_viewfactor(sky, wall) # compute and increment view factor : F_i->(j+k) = F_i->j + F_i->k
# same for building 1
Fbuilding1 = 0
for patch in tqdm(i_building1):
bldng1 = mesh.extract_cells(patch)
bldng1 = pvf.fc_unstruc2poly(bldng1)
if pvf.get_visibility(bldng1, wall):
if pvf.get_visibility_raytrace(bldng1, wall, meshpoly):
Fbuilding1 += pvf.compute_viewfactor(bldng1, wall)
# same for building 2
Fbuilding2 = 0
for patch in tqdm(i_building2):
bldng2 = mesh.extract_cells(patch)
bldng2 = pvf.fc_unstruc2poly(bldng2)
if pvf.get_visibility(bldng2, wall):
if pvf.get_visibility_raytrace(bldng2, wall, meshpoly):
Fbuilding2 += pvf.compute_viewfactor(bldng2, wall)
# complementarity implies \sigma F_i = 1 : compute viewfactor to ground
Fground = 1-Fbuilding1-Fbuilding2-Fsky
print('\n----------------------')
print('Wall to environment view factors :')
print('\tSky ', round(Fsky, 4))
print('\tBuilding 1 ', round(Fbuilding1, 4))
print('\tBuilding 2 ', round(Fbuilding2, 4))
print('Ground view factor :')
print('\tGround ', round(Fground, 4))The code yields following view factors :
$$F_{\text{sky}} = 0.345 \\ F_{\text{ground}} = 0.373 \\ F_{\text{building1}} = 0.251 \\ F_{\text{building2}} = 0.031 \\$$In real life problems, obstacles may well hinder the radiation heat transfer between surfaces. We make use here of pyvista's raytrace function to perform obstruction tests, as per following example, much inspired from pyvista's online documentation.
The code snippet below shows how the ray tracing function works and allows to understand its usage in the pyviewfactor get_visibility_raytrace function.
import pyvista as pv
from pyviewfactor import get_visibility_raytrace
# let us first create two rectangles
pointa = [1, 0, 0]
pointb = [1, 1, 0]
pointc = [0, 1, 0]
pointd = [0, 0, 0]
rectangle_down = pv.Rectangle([pointa, pointb, pointc, pointd])
pointa = [1, 0, 1]
pointb = [1, 1, 1]
pointc = [0, 1, 1]
pointd = [0, 0, 1]
rectangle_up = pv.Rectangle([pointa, pointb, pointc, pointd])
# a circle will be the obstruction
z_translation, r = 0.5, 2
obstacle = pv.Circle(radius=r, resolution=10)
# we translate the obstruction right between both rectangles
obstacle.translate([0, 0, z_translation], inplace=True)
# Define line segment
start = rectangle_down.cell_centers().points[0]
stop = rectangle_up.cell_centers().points[0]
# Perform ray trace
points, ind = obstacle.ray_trace(start, stop)
# Create geometry to represent ray trace
ray = pv.Line(start, stop)
intersection = pv.PolyData(points)
# Render the result
p = pv.Plotter(notebook=True)
p.add_mesh(obstacle, show_edges=True, opacity=0.5, color="red", lighting=False, label="obstacle")
p.add_mesh(rectangle_up, color="blue", line_width=5, opacity=0.5, label="rect up")
p.add_mesh(rectangle_down, color="yellow", line_width=5,opacity=0.5, label="rect down")
p.add_mesh(ray, color="green", line_width=5, label="ray trace")
# if any intersection
if intersection.n_cells > 0:
p.add_mesh(intersection, color="green", point_size=25, label="Intersection Points")
p.add_legend()
p.show(cpos="yz")
#now a call to the obstruction check function
print(get_visibility_raytrace(rectangle_up, rectangle_down, obstacle))More complex scenes can then be treated with the function get_visibility_raytrace.
pyViewFactor can be installed from PyPi using pip on Python >= 3.7:
pip install pyviewfactor
You can also visit PyPi or Gitlab to download the sources.
Requirements:
numpy==1.17.4
pandas==1.4.2
pyvista==0.35.2
scipy==1.8.1
numba>=0.55.2
The code will probably work with lower versions of the required packages, however this has not been tested.
Note - If you are alergic to numba, you may pip install pyviewfactor==0.0.10 that works (and give up the x2 speed-up in view factor computation).
Mateusz BOGDAN, Edouard WALTHER, Marc ALECIAN, Mina CHAPON
There is even a conference paper, showing analytical validations :
Mateusz BOGDAN, Edouard WALTHER, Marc ALECIAN and Mina CHAPON. Calcul des facteurs de forme entre polygones - Application à la thermique urbaine et aux études de confort. IBPSA France 2022, Châlons-en-Champagne.
Bibtex entry:
@inproceedings{pyViewFactor22bogdan,
authors = "Mateusz BOGDAN and Edouard WALTHER and Marc ALECIAN and Mina CHAPON",
title = "Calcul des facteurs de forme entre polygones - Application à la thermique urbaine et aux études de confort",
year = "2022",
organization = "IBPSA France",
venue = "Châlons-en-Champagne, France"
note = "IBPSA France 2022",
}MIT License - Copyright (c) AREP 2022