Managing Risk: how can process models help - Evangelia Belia, Primodal US Inc. Michael Lunn, Primodal US Inc.
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Managing Risk: how can
process models help
Evangelia Belia, Primodal US Inc.
Michael Lunn, Primodal US Inc.
WWAdCon 2021
Outline
• What is risk?
• How does our industry currently manage risk?
• How do other industries manage risk?
• Can our industry implement the same methods?
WWAdCon 2021
What is risk?
Risk = expectation of losses associated with a harmful event
Example: = Risk of failure (exceeding effluent permit)
Risk = [Probability of event happening] * [Cost]
Example: = [likelihood of exceeding effluent permit] * [cost]
Cost Examples (monetary + non-monetary):
WWAdCon 2021
Non-compliance;
Loss of reputation;
Financial loss;
Not winning a contract or contract annulment;
Loss of operating license;
….
Sources of risk
Originating from the environment:
• Weather/climate effects
• Collection system characteristics
• Wastewater characteristics (flows, loads, temp, pH, fractions, …)
• Growth or loss within collection area (growth rate, changes in I/I, changes in industry)
• Discharge permits/Regulations
Originating from the WRRF:
WWAdCon 2021
• Biological: bacterial kinetics, floc structure
• Physical: non-ideal process behavior (e.g. non-ideal mixing)
• Chemical-physical: e.g. precipitation stoichiometry and kinetics
• Unexpected control system behaviour
• Mechanical failures
• Operational problems
How does our industry currently
manage risk?
• Design guidelines
• Design criteria
• Safety factors
• Redundancy standards
• Scenario analysis
WWAdCon 2021
• Modelling
• Contract documents / contract delivery method
Example of safety factors and
redundancy requirements
SRT safety factor 1.4 to 1.8 takes into account (ATV-DVWK-A 131 guidelines):
a) potential variations of the maximum growth rate caused by certain substances in the
wastewater, short-term variations and/or pH shifts, and
b) the variations of ammonium load
Unit Process EPA, 1974 10 State Standards, 2014
WWAdCon 2021
Primary Must be able to process 50% of Requires multiple units capable of
sedimentation plant flow with 1 (largest) unit independent operation for plants
basins out of service with flows higher than 0.1 MGD,
Redundancy but no redundant unit required
requirements
Secondary Must have 75% of rated capacity Requires multiple units capable of
sedimentation with 1(largest) unit of service independent operation for plants
basins with flows higher than 0.1 MGD,
but no redundant unit required
How does our industry currently
manage risk?
Steady State
Design
Influent constituents
Process-based
equations
Conventional Effluent standards
steady state design Design parameters
Empirical
equations
WWTP’s
WWAdCon 2021
dimensions
Operational targets Experience-
based rules
Safety factors
Mansour Talebizadeh (2015) Probabilistic design of wastewater treatment plants. PhD. Thesis. modelEAU-Université
Laval, Québec, QC, CanadaCompounding of safety factors
300 90
80
250
70
Daily average BOD (mg/L)
Daily average flow (MGD)
200 60
50
150
40
100 30
20
50
Design load Target effluent
10
0
Mar-07 Jul-07 Oct-07 Jan-08 May-08 Aug-08 Nov-08 Feb-09 Jun-09 Sep-09 Dec-09
0 Safety factors Redundancy
Date
WWAdCon 2021
4 4
3 3
Safety factor
Safety factor
2 2
1 1
0 0
Influent load Unit process
Influent load Redundancy
Unit process Risk registers
Redundancy Effluent criteria
Risk registers Effluent criteria
selection safety factors
selection safety factors and compliance and compliance
testing testingDrawbacks of current design
approach
• Steady-state:
• ignores plant dynamics and plant evolution
• a single value does not provide quantifiable information about the reliability of a process
design.
• Lumping risk in a few parameters:
• missing relative importance of individual sources of risk
• inflexible designs
WWAdCon 2021
• Often assumes a combination of worst case conditions that may never happen
• No information on likelihood or frequency of any particular load reaching the
plant within the selected design horizon
• No information on the likelihood or frequency of non-compliance
• Does not address newly developed processesHow do other industries handle
risk?
WWAdCon 2021Can our industry implement the
same methods? Why now?
• Safety factors have not changed for decades
• Increased use of simulators for design and optimization
• Strict effluent guidelines & increased energy efficiency
• Awareness among practitioners
• Scientific approach to balance risk/benefits
WWAdCon 2021
However:
• Simulators lack reliability evaluation
• Need to couple with statistical methodsRisk and Uncertainty
• Risk = expectation of losses associated with a harmful event
Example: = Risk of failure (exceeding effluent permit)
Risk = [Probability of failure] * [Cost of failure]
• Probability: is it "likely" or "unlikely“ that the event will happen?
Example: Probability of a design to meet effluent standards
Probability is the expected likelihood of occurrence of an event
WWAdCon 2021
• Uncertainty assessment and propagation are:
Quantification of probabilities
Quantify risk = assess uncertainty = quantify probabilityLevels of uncertainty
Donald Rumsfeld
WWAdCon 2021
As we know, there are known knowns.
There are things we know we know.
We also know there are known unknowns.
That is to say :
We know there are some things we do not know.
But there are also unknown unknowns,
the ones we don't know we don't know.Steady-state probabilistic design
Sources if uncertainty
Steady State
“Safety Factor” Influent constituents
redistributed Effluent standards
Design guidelines
+
daylighting the Design parameters
Models
WWTP’s Effluent
+
WWAdCon 2021
dimensions performance
specific risks Operational targets Statistical and risk
methods
Safety factors
Mansour Talebizadeh (2015) Probabilistic design of wastewater treatment plants. PhD. Thesis. modelEAU-Université
Laval, Québec, QC, CanadaDynamic probabilistic design with
Monte Carlo PDF: Probability
density function
CDF: Cumulative
distribution
function
WWAdCon 2021
Unit
sizesVariability and Uncertainty – model
output
0.8
0.7
in blue: temporal variability
95%ile - MC
due to influent variability
0.6
0.5
in red: output uncertainty
NH4 [mg/L]
single
WWAdCon 2021
0.4 simulation
band due to parameter
0.3 uncertainty
0.2
0.1
5%ile - MC
0
1 2 3 4 5
time [d]Uncertainty analysis of results
100
90
Frequency + confidence (variability + uncertainty)
• 5% sure NH4 < 3 mg/l 96% of the time
80
70
• 95% sure NH4 < 3 mg/l 78% of the time
25
60 Alt1 Mixed Alt1
80
Nominal
Duration [%]
50 Worst case
20 70
40 60
WWAdCon 2021
PONC for NH4 (%)
PONC for TN (%)
Alt2
15 50
30 Alt2
Alt3
40
20
10
Alt3 30
10
20
5
0
0 1 2 3 4 5 6 7 8
Concentration [mg/l]
Alt4
Alt5
10
Alt4
Cumulative curves for NH4 concentration at the effluent: 0
6 6.2 6.4 6.6
0
6 6.2
Total Cost (Million Dollar) Total Cost (Mi
daily composite samples 50th, 5th and 95th %iles Mansour Talebizadeh (2015) Probabilistic design of
wastewater treatment plants. PhD. Thesis. modelEAU-
Université Laval, Québec, QC, CanadaProposed design procedure
Define project Preliminary
objectives evaluation of selected Compile list of sources
Identify
alternatives of uncertainty for the
Prioritise Effluent standards and
Reduce frequency of compliance Use design guidelines for design objective
preliminary sizing and
Design horizon approximate costing
Characterize sources Run dynamic
of uncertainty with simulations using
Model Monte Carlo
PDFs
WWAdCon 2021
Propagate
Compile effluent CDFs
Define scenarios
Calculate output
Analyse metrics Multi-criteria decision
Synthesize Quantify the probability of and selection of best
Communicate (non)compliance alternative
Estimate detailed total cost
Talebizadeh, M. (2015). Probabilistic design of wastewater treatment plants. PhD. Thesis. Département de génie civil et de génie des
eaux, Université Laval, Québec, QC, Canada. https://corpus.ulaval.ca/jspui/handle/20.500.11794/26196Lag in implementation of explicit
risk analysis
• Considered high costs and time-consuming - computers reduce considerably
costs and time
• Lack of data - the more uncertain the input data, the more helpful accounting
for uncertainty and evaluating the associated risk
• Decision makers reluctant to accept these techniques (not confident they will
WWAdCon 2021
help them make better decisions) - may stem in part from lack of
understanding of the techniques, requires multidisciplinary teams
1988 NIST: “A Comprehensive examination of the different approaches to
treating uncertainty and risk in project evaluation would show how the
application of risk analysis techniques to uncertain data can improve
management decision making.”Opportunities of explicit risk analysis
• Risk is made explicit
• Daylights conservatisms buried in the various design assumptions
• Allows plants to be right-sized
• Allows to design a system with a desired level of risk
• Transparency
• Decision making process
• Quantitative evaluation of statistical likelihood of achieving a particular effluent/performance criteria
WWAdCon 2021
• Approach can be steady-state (applying Monte Carlo to basic design equations) or dynamic
(probabilistic design with dynamic Monte Carlo simulator runs)
• Benefit-cost-risk analysis
• Showing how benefits, costs and risks are spread among stakeholders
• Integration of socio-economic & statistical sciences
• Fore-sighting methods, life cycle analysis, environmental economics, ...Scientific and Technical Report
(STR)
WWAdCon 2021
(Publication in 2021)Presenter contact information
Evangelina Belia
Ph.D., P. Eng.
Primodal Inc.
WWAdCon 2021
US & Canada
belia@primodal.com
www.primodal.comYou can also read
