Implementing a Vision to Create and Deploy
the Airport Risk Assessment Model
(ARAM)PNNL’s Community Science &
Technology Seminar Series
Nick BetzsoldData Scientist, ARAM Co-PI
10 November 2020
PNNL-SA-157568
Airport Risk Assessment Modelo Developed by Pacific Northwest National Laboratory – first model
to dynamically quantify risk from terrorist threats at airports
o Automatically optimizes recommended assignment locations of deployable security countermeasures
o Demonstrated to DHS S&T, TSA, Port of Seattle Security/Police Department, and Delta Airline Security
o Operationally deployed at Sea-Tac starting inSeptember 2019; additional airports to follow
o Sponsored by DHS S&T – APEX Program
4
Definitions and Risk Analysis Introduction
Risk: Potential for an unwanted outcome resulting from an incident, event, or occurrence, as determined by its likelihood and the associated consequences
Risk Score: Numerical result of a semi-quantitative risk assessment methodology Gauges the combination of threat, vulnerability, and consequence at a
specific moment and location Basic risk equation: R = f (T, V, C )
ARAM Risk Engineo Math Program Formulation:
• Objective function: Minimize Daily Risk
• Decision variables: where and whento place assets
• Constraints: asset availability andother imposedrequirements
Baseline maximum risk as assessed for threats and areas
Risk with no security assets as airport volume ebbs and flow
Risk with routine security asset assignments
Risk with optimized security asset assignments
ARAM Typical Results – Risk Comparison
1. Stakeholders input availability of deployable countermeasures
2. Hit the “easy button” to obtain schedule of optimal assignments
3. Patrol assigned areas per defined stakeholder CONOPS
4. View risk buydown and heat maps to evaluate benefits in terms of countermeasure contributions to overall risk reduction
ARAM CONOPS
Typical ARAM Operational Flow Process
A R A M S C H E D U L E S C R E E N :A D D S H I F T S
“ E A S Y B U T T O N ”
N O T I O N A L O N LY
A R A M E N D I N G D A S H B O A R D
13 countermeasures
74 hours deployed
Risk buydown = 41%
59% risk remaining
N O T I O N A L O N LY
A R A M H E AT M A P R I S K B Y A R E A + C O U N T E R -M E A S U R E S AT 1 5 0 0
N O T I O N A L O N LY
A LT. A R A M H E AT M A PP O P U L AT I O NB Y A R E A + C O U N T E R -M E A S U R E SAT 1 5 0 0
N O T I O N A L O N LY
A LT. A R A M H E AT M A PC O U N T E R -M E A S U R E SB Y A R E AAT 1 6 0 0
N O T I O N A L O N LY
ARAM Summaryo Risk-based approach to decide on best use of discretionary
resources
o Accounts for multiple threats
o Unity of effort across stakeholder organizations / reduces duplication of effort
o Tracks risk and risk reduction trends over time
o Easy to use
For more information, contact:
Dr. Robert T. Brigantic, ARAM PIChief Operations Research ScientistNATIONAL SECURITY DIRECTORATE
Pacific Northwest National LaboratoryRichland, WA 99352 USATel: (509) [email protected]
Nick Betzsold, ARAM Co-PIData ScientistNATIONAL SECURITY DIRECTORATE
Pacific Northwest National LaboratoryRichland, WA 99352 USATel: (509) [email protected]
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