Package: pybimstab
pyBIMstabpybimstabis an application software inPython 3to evaluate the factor
of safety against sliding of slopes made of Blocks-In-Matrix (BIM) materials.The assessment is donde by using the limit equilibrium method through the
General Limit Equilibrium (GLE) method ofFredlund & Krahn (1977).The slip surface has a tortuous geometry and is optimally found by using the
A-star algorithm proposed byHart, Nilsson & Raphael (1968).The following plots are the final outcome of two different analysis:Homogeneus slopeSlope made of BIM materialFeaturesDocumentationPyPIGitHubOpen source and free software:BSD-2-Clause.RequirementsThe code was written in Python 3. The packagesnumpy,scipy,matplotlibandshapelyare
required for usingpybimstab. All of them are
downloadable from the PyPI repository by opening a terminal and typing the
following code lines:pip install numpy
pip install scipy
pip install matplotlib
pip install shapelyInstallationTo installpybimstabopen a terminal and type:pip install pybimstabExampleTo produce the plot shown above execute the following scriptfrom numpy import array
from pybimstab.slope import NaturalSlope
from pybimstab.watertable import WaterTable
from pybimstab.bim import BlocksInMatrix
from pybimstab.slipsurface import CircularSurface, TortuousSurface
from pybimstab.slices import MaterialParameters, Slices
from pybimstab.slopestabl import SlopeStabl
terrainCoords = array(
    [[-2.49, 0.1, 1.7, 3.89, 5.9, 8.12, 9.87, 13.29, 20.29,
      21.43, 22.28, 23.48, 24.65, 25.17],
     [18.16, 17.88, 17.28, 15.73, 14.31, 13.58, 13, 3.61, 3.61,
      3.32, 2.71, 2.23, 1.21, 0.25]])
slope = NaturalSlope(terrainCoords)
bim = BlocksInMatrix(slopeCoords=slope.coords, blockProp=0.25,
                     tileSize=0.4, seed=12345)
watertabDepths = array([[0, 5, 10, 15],
                        [8, 7, 3, 0]])
watertable = WaterTable(slopeCoords=slope.coords,
                        watertabDepths=watertabDepths,
                        smoothFactor=3)
preferredPath = CircularSurface(
    slopeCoords=slope.coords, dist1=5, dist2=15.78, radius=20)
surface = TortuousSurface(
    bim, dist1=4, dist2=15.78, heuristic='euclidean',
    reverseLeft=False, reverseUp=False, smoothFactor=2,
    preferredPath=preferredPath.coords, prefPathFact=2)
material = MaterialParameters(
    cohesion=15, frictAngle=23, unitWeight=17,
    blocksUnitWeight=21, wtUnitWeight=9.8)
slices = Slices(
    material=material, slipSurfCoords=surface.coords,
    slopeCoords=slope.coords, numSlices=15,
    watertabCoords=watertable.coords, bim=bim)
stabAnalysis = SlopeStabl(slices, seedFS=1, Kh=0, maxLambda=1)
fig = stabAnalysis.plot()ReferencesD. G. Fredlund and J. Krahn. Comparison of slope stability methods of analysis.
Canadian Geotechnical Journal, 14(3)(3):429–439, 1977.P. Hart, N. Nilsson, and B. Raphael. A formal basis for the heuristic
determination of minimum cost path. IEEE Transactions of Systems Science and
Cybernetics, ssc-4(2):100–107, 1968.History0.1.0 (2018-07-15)First release on PyPI.0.1.1 (2018-07-22)Solving some issues related to the definition of the slices structure.0.1.2 (2018-08-04)Adjusting the interpolations in the convergence plot and appending a parameter to control the number of lambda values.0.1.3 (2018-10-06)Addition of Bishop and Fellenius methods for LEM.Fixing some issues with convergences.Fixing minor issues.0.1.4 (2019-10-13)Fixing minor issues.0.1.5 (2019-10-15)Editing __init__.py file to import modules by means of an alias.