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RISK ASSESSMENT
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WHAT DO WE MEAN BY RISK?
• Chambers – “hazard, danger, chance of loss or injury”
• OED - “Exposure to the possibility of loss, injury, or other adverse or unwelcome circumstance”
• Common usage – the probability of suffering an undesired event
• The Risk Analyst’s definition would be the combination of the probability of suffering a loss together with the magnitude of that loss
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A GAME OF CHANCE – TOSS A COIN
• Game 1 - Heads I give you £1, Tails you give me £1 Will you play?
• Game 2 - Heads I give you £100, Tails you give me £100
• Game 3 - Heads I give you £100,000 Tails you give me £100,000
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WHAT’S THE POINT OF RA?
• Not so much to provide a value to the risk of a given activity
Rather
• To provide a comparison between various alternatives
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QUALITATIVE RA
• Levels of loss Probability
• High
• Moderate
• Low
• Improbable
• Levels of loss Magnitude
• Severe
• Large
• Moderate
• Trvial
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THE RISK MATRIX
Probabiity >Magnitude v
High Moderate Low Improbable
Severe
Large
Moderate
Trivial
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ACTION SCALEAvoid at all costs
Avoid if at all possible
Consider but look for ways to improve risk
Accept risk but do not over commit
Go for it
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FINANCIAL RISKComparing Investments
• Case A – High probability of failure but small lossesProbability of failure = 0.4Loss if investment fails = £100Risk 0.4 x 100 = £40/investment
• Case B – Low probability of failure but high lossesProbability of failure = 0.05Loss if investment fails = £1000Risk 0.05 x 1000 = £50/investment
• So Case A gets our vote
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FINANCIAL RISKIncorporat ing gains and losses
• Case A – High probability of failure but small losses or modest gainsProbability of failure = 0.4, Probability of success = 0.6Loss if investment fails = £100, Gain if investment succeeds £100Risk 0.6 x 100 - 0.4 x 100 = £20/investment
• Case B – Low probability of failure but high losses or modest gainsProbability of failure = 0.05, Probability of success = 0.95Loss if investment fails = £1000 , Gain if investment succeeds £100Risk 0.95 x 100 - 0.05 x 1000 = £45/investment
• So now Case B gets our vote!
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RISK OF DEATH OR INJURY
• Average person visits a pub once a month
• Probability of contracting COVID 0.1% (0.001) per visit
• Probability of dying if you contract COVID 4%
Thus risk of COVID infection from pub visits is :
12 x 0.001 x 0.04 = 0.00048 fatalities/person/year (4.8x10-4)
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COMPARISON WITH OTHER RISKS
• Working in agriculture/forestry - 7.73x10-5 fatalities/person/year
• Working in admin/support - 0.23x10-5 fatalities/person/year
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SO IT’S SIMPLE THEN!Unfor tunately there are complicat ions
• Working out the probability of loss events
• Working out the magnitude of loss
• Working out overall risk from multiple loss events each with their own probability and loss magnitude
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DETERMINING FAILURE/LOSS PROBABILITIES
Analytically from 1st principles
e.g. toss of a coin or throw of a dice
Historical DataDecomposition into sub-events
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HISTORICAL DATABEWARE LOW BEAM!
• The King Head has a low beam in the public bar – how do we determine the probability of a customer banging their head
• Employ student to sit in the bar and record the number of head bangs over a given period
• Thus period of record – 6 weeks (42 days) for 8 hours per day
• Number of head bangs recorded 31
• Number of customers in 6 weeks - 240
• Thus frequency of head bangs = 31/240/42/8 = 0.000384 bangs/customer/hour (3.84x10-4)
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HISTORICAL DATAINFREQUENT EVENTS
• What if the event is very rare e.g. number of fatalities at pedestrian crossing at Halesworth Station
• Could use data from a much larger sample size e.g. national records
• But data may not be representative of Halesworth specific circumstances
• Data needs adjustment but can be v. complex
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E V E N T D E C O M P O S I T I O N
Combine this data using Boolean logic to build up a composite
failure probability for the whole system
Break down failure event into a set of simple sub-events for which
data exists
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FAILURE OF A 7 CYLINDER PETROL ENGINE!
• Engine comprises sub-systems : cylinders (including valves & spark plugs), crankshaft, block, fuel injection, ignition etc.
• Take data for each subsystem from a typical 6 cylinder engine
• Combine data for each sub-system plus the failure rate for an additional cylinder
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DECOMPOSITION OF COMPLEX SYSTEMSFAULT TREE ANALYSIS
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DETERMINING LOSS MAGNITUDE
• Financial Loss
• Loss of life
• Loss of good health or injury
• Loss of reputation
• Loss of peace of mind
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EVENTS WITH SINGLE OUTCOMESTHE BEIRUT FERTILISER EXPLOSION
• Known quantity of Ammonium Nitrate (2750 tonnes)
• Know from previous NH4NO3 explosions (Oppau, Texas Bay, Tiajin) fraction of material that will explosively decompose (30-50%) hence can calculate energy release
• Calculate and plot explosion overpressure contours
• Know population density within affected areas
• Fatality fraction in relation to overpressure exposure
• Calculate number of fatalities
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EVENTS WITH MULTIPLE OUTCOMESTHE CORONA VIRUS PANDEMIC
• Different people have different probabilities of contracting COVID19
• Magnitude of hazard differs for an individual
• No observable symptoms
• Headache, Mild fever and short lived cough – no medical intervention required
A more severe cough requiring them remain at home for a few days to recover
Severe symptoms requiring hospitalisation
Very severe symptoms requiring ventilation
Death
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EVENT TREES
• Go to Excel file
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PROBLEMS AND PITFALLS
• Availability of event frequency/probability data
• Data accuracy and spread
• Impact assessment
• Loss acceptability
• Loss equivalency
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FAILURE DATA AVAILABILIT Y
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DATA ACCURACY & SPREAD
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IMPACT ASSESSMENT COMPLEXITIES
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RISK ACCEPTABILIT YCROSSING THE ROAD
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RISK PERCEPTION
• Are lots of little accidents better than one big one?
• 1700 deaths/year from road accidents
• 0 deaths/year from UK nuclear power station accidents (in 60 years of operation)
• Do we have an unfounded belief that we are in control and therefore safe?
• 77% of RTAs caused by driver of vehicle involved
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LOSS ACCEPTABILIT Y
• What value do we put on life
• How much are we prepared to spend to reduce the probability of dying
• How much should other organisations or our government be prepared to spend to save an individual’s life.