EPS Example Notebook
This notebook shows an example replicating previous the simple electric power system implemented in IBFM in the eps example directory, with some basic fault propagation and visualization.
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The “"Fault Model Design tools - fmdtools version 2"” software is licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.
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[1]:
from examples.eps.eps import EPS
import fmdtools.sim.propagate as propagate
This script provides some example I/O for using static models, using the EPS system implemented in eps.py as an example.
A graphical representaiton of this system is shown below:
[2]:
mdl= EPS()
mg = mdl.as_modelgraph()
fig, ax = mg.draw()
As with dynamic models, in static models we use fp.run_one_fault to see the effects of single faults. All setup is performed in the Model class definition
[3]:
result, mdlhist = propagate.one_fault(mdl, 'ee_to_me', 'toohigh_torque', desired_result="graph")
In this case, however, the output in mdlhists will be a single-dimensional dictionary (not something we can plot very well)
[4]:
fig, ax = mdlhist.plot_line(*mdlhist.nominal.keys())
C:\Users\dhulse\Documents\GitHub\fmdtools\fmdtools\analyze\history.py:776: UserWarning: Attempting to set identical low and high xlims makes transformation singular; automatically expanding.
ax.set_xlim(min_ind, max_ind)
As a result, it’s better to look at the results graph for a visualization of what went wrong. In this case resgraph better represents the fault propagation of the system than in a dynamic model, since there is only one time-step to represent (rather than a set)
[5]:
result.graph.set_edge_labels(title='')
fig, ax = result.graph.draw(figsize=(14,10))
We can run the set of single-fault scenarios on this model using fmdtools.sim.propagate.single_faults. For single-fault scenarios, one does not need to use a SampleApproach, since all faults are injected at a single time-step.
[6]:
endclasses, mdlhists = propagate.single_faults(mdl, staged=True)
SCENARIOS COMPLETE: 100%|██████████| 35/35 [00:00<00:00, 57.22it/s]
Using analyze.tabulate.result_summary_fmea, one can see the degradation effects of this fault on the flows:
[7]:
from fmdtools.analyze.tabulate import result_summary_fmea
[8]:
tab = result_summary_fmea(endclasses, mdlhists, *mdl.fxns, *mdl.flows)
tab
[8]:
| degraded | faulty | rate | cost | expected_cost | |
|---|---|---|---|---|---|
| import_ee_low_v_t0p0 | [] | [] | 0.00001 | 700.0 | 306.6 |
| import_ee_high_v_t0p0 | ['me', 'oe', 'he'] | [] | 0.000005 | 2100.0 | 459.9 |
| import_ee_no_v_t0p0 | [] | [] | 0.00001 | 1550.0 | 678.9 |
| supply_ee_adverse_resist_t0p0 | [] | [] | 0.000002 | 1650.0 | 144.54 |
| supply_ee_minor_overload_t0p0 | [] | [] | 0.00001 | 5150.0 | 2255.7 |
| supply_ee_major_overload_t0p0 | ['me', 'oe', 'he'] | [] | 0.000003 | 2400.0 | 315.36 |
| supply_ee_short_t0p0 | [] | [] | 0.0 | 5150.0 | 22.557 |
| supply_ee_open_circuit_t0p0 | [] | [] | 0.0 | 1450.0 | 3.1755 |
| store_ee_low_storage_t0p0 | ['me', 'oe', 'he'] | [] | 0.000005 | 2000.0 | 438.0 |
| store_ee_no_storage_t0p0 | [] | [] | 0.000005 | 3250.0 | 711.75 |
| import_signal_partial_signal_t0p0 | [] | [] | 0.00001 | 2000.0 | 876.0 |
| import_signal_no_signal_t0p0 | [] | [] | 0.000001 | 2000.0 | 87.6 |
| distribute_ee_adverse_resist_t0p0 | [] | [] | 0.00001 | 2750.0 | 1204.5 |
| distribute_ee_poor_alloc_t0p0 | [] | [] | 0.00002 | 1750.0 | 1533.0 |
| distribute_ee_short_t0p0 | [] | [] | 0.00002 | 4750.0 | 4161.0 |
| distribute_ee_open_circuit_t0p0 | [] | [] | 0.00003 | 2750.0 | 3613.5 |
| ee_to_me_high_torque_t0p0 | ['oe', 'he'] | [] | 0.0001 | 450.0 | 1971.0 |
| ee_to_me_low_torque_t0p0 | [] | [] | 0.0001 | 4950.0 | 21681.0 |
| ee_to_me_toohigh_torque_t0p0 | [] | [] | 0.00005 | 5050.0 | 11059.5 |
| ee_to_me_open_circuit_t0p0 | ['oe', 'he'] | [] | 0.00005 | 650.0 | 1423.5 |
| ee_to_me_short_t0p0 | [] | [] | 0.00005 | 4950.0 | 10840.5 |
| ee_to_oe_optical_resist_t0p0 | ['me', 'he'] | [] | 0.0 | 520.0 | 11.388 |
| ee_to_oe_burnt_out_t0p0 | ['me', 'he'] | [] | 0.000002 | 550.0 | 48.18 |
| ee_to_he_low_heat_t0p0 | ['me', 'oe'] | [] | 0.000002 | 550.0 | 48.18 |
| ee_to_he_high_heat_t0p0 | ['me', 'oe'] | [] | 0.0 | 2500.0 | 10.95 |
| ee_to_he_toohigh_heat_t0p0 | [] | [] | 0.0 | 5100.0 | 111.69 |
| ee_to_he_open_circuit_t0p0 | ['me', 'oe'] | [] | 0.0 | 550.0 | 2.409 |
| export_he_hot_sink_t0p0 | ['me', 'oe'] | [] | 0.00001 | 600.0 | 262.8 |
| export_he_ineffective_sink_t0p0 | ['me', 'oe'] | [] | 0.000005 | 1500.0 | 328.5 |
| export_waste_h1_hot_sink_t0p0 | ['me', 'oe', 'he'] | [] | 0.00001 | 500.0 | 219.0 |
| export_waste_h1_ineffective_sink_t0p0 | ['me', 'oe', 'he'] | [] | 0.000005 | 1000.0 | 219.0 |
| export_waste_ho_hot_sink_t0p0 | ['me', 'oe', 'he'] | [] | 0.00001 | 500.0 | 219.0 |
| export_waste_ho_ineffective_sink_t0p0 | ['me', 'oe', 'he'] | [] | 0.000005 | 1000.0 | 219.0 |
| export_waste_hm_hot_sink_t0p0 | ['me', 'oe', 'he'] | [] | 0.00001 | 500.0 | 219.0 |
| export_waste_hm_ineffective_sink_t0p0 | ['me', 'oe', 'he'] | [] | 0.000005 | 1000.0 | 219.0 |
| nominal | ['me', 'oe', 'he'] | [] | 1.0 | 0.0 | 0.0 |