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Computer Modeling and Simulation Projects

The National Institutes of Health often utilzes computer modeling and simulation to inform the design, creation, and evaluation of new projects and inititives. Examples of past uses can be found below. 

 


Past Computer Modeling and Simulation Projects:​

Campus Evacuation

Background
Security and Emergency Response (SER) staff develop plans that provide direction should an event occur that requires the evacuation of a building, a section of the campus, or the entire NIH campus. This on-going computer simulation study provides a greater understanding of the total evacuation flow from buildings to garages, to gates and to the perimeter roads around the campus. Through analysis of the data and discussions with subject matter experts, this study allows for the identification of opportunities to reduce evacuation time, improve readiness, provides for continuity of operations in shelter in place situations, and plans for assisting personnel with special mobility needs. 

A phased approach was utilized beginning with a baseline study as a proof of concept to get stakeholder buy-in, and then incrementally improved analytical rigor and added complexity in subsequent phases. The study also provides data and statistics regarding the expected time required to evacuate the NIH campus in different scenarios. 

Some of the measurable metrics resulting from the model outputs include:

  • Total time to evacuate the NIH Campus
  • Time required for each person to leave the campus by zone (and possibly by building and parking location)  (average, half-width, min, max)
  • Utilization of various routes & exit gates
  • Queuing statistics at garages and pedestrian gates
  • Time required to clear garages/lots

NIH Shuttle Bus

Background
A tool to better understand, analyze, and improve processes with limited data was needed. Although computer simulation was a promising tool, it had to be tested for viability and sustainability. An evaluation of the utilization capacity of the different shuttles throughout the network of routes and stops was used to test computer simulation.  

This project also provided ridership data to the program and acquisition staff that was used along with an innovative approach to performance-based acquisition. This approach was also utilized to obtain offers that reflected a better match between ridership capacity and demand. Obtaining a better understanding of the ridership distribution along the shuttle network throughout the week helped contribute to offers that reduce the cost of providing shuttle transportation.

Goals and Objectives 

  • Proof of concept for the computer simulation capability
  • Provide passenger count data to offerors per shuttle, route, between stops, day of the week, and time of the day
  • Minimize cost of the NIH shuttle bus operation by better matching capacity to demand
  • Provide information to offerors during contract competition so they could offer better alternatives to current system

Active Shooter Scenarios

Background
Recent events across the nation involving shootings within the work place have contributed to an enhanced interest in understanding how such an event might be handled at a Bethesda campus facility. This study helps develop a greater understanding of how the hypothetical active shooter incident could play out and how such an incident could be resolved with minimal impact.  The information obtained through this study is used to evaluate the effectiveness of current planned response efforts and aid improving those response plans to minimize the number of casualties, loss of property, and research productivity were an active shooter situation occurred.

Some of the measurable metrics resulting from the model outputs include:

  • Number of casualties and survivors by shooter at the end of each scenario
  • Number of casualties / wounded by zone
  • Time to contact/neutralize each of the active shooters
  • Number of zones covered by each shooter prior to apprehension or escape
  • Time to secure potential escape routes.
  • Time to search the building or buildings to ensure the absence of other threats

Key Outcomes
Although the initial Active Shooter model was developed for an NIH building, the simulation models were developed in such a way that they could be easily scaled to fit any emergency planning initiative. Developing a generic model that utilizes the building’s floors and divides them into wings and then zones within the wings helped to define occupancy levels and mimic shooter and police response movement throughout the building. Successful models were developed for two additional buildings using the base logic created in the original building model. 

Visitor Inspection

Background
The OQM team partnered with the NIH security team to analyze and assess NIH Gateway Center for vehicle and pedestrian visitor entry into NIH Campus. Through the use of computer simulation modeling, this project delivered recommendations on proper staffing and equipment levels required to meet visitor demand at a reduced cost.

Mass Immunization

Background
The goal of the mass prophylaxis simulation model is to develop an operational concept for providing logistical support for inoculating staff on the NIH campus in the event a local, regional or national crisis requiring urgent immunization as directed by Federal authority. 

The simulation model will guide NIH in development of a resource management strategy, identification of resource requirements subject to varying campus populations (e.g., number of NIH personnel, number of medical staff, etc.), determination of an optimal strategy for routing people to inoculation centers, and a better understanding of the time required to inoculate the NIH Bethesda campus.

Key Outcomes

  • Develop a resource management strategy
  • Identify resource requirements subject to varying campus populations, e.g., number of NIH personnel, number of medical staff
  • Determine an optimal strategy for routing people to inoculation centers
  • Discover the amount of time required to inoculate the NIH Bethesda campus

South Drive Gate Closure

Purpose
To understand the impact of closing entrance to NIH at Old Georgetown Road and South Drive for the Porter construction project, a simulation tool was used to model the traffic flow from Old Georgetown Road (both Northbound and Southbound) into 3 NIH entrances (Center Drive, South Drive, and Lincoln Drive)

Simulation Model Approach

  • Scenario based approach was used to understand the present conditions and evaluate the impact the closure will have on the other 2 entrances
  • Baseline scenario developed using data from May 2010 trip generation study performed by Gorove/Slade
  • Trip generation study provided an enumeration of the overall traffic entering NIH, irrespective of originating direction.  Estimated that 90% of traffic travels southbound and turns left into NIH; 10% travels northbound and turns right.
  • Volume enumerated in 15 minute intervals throughout the peak AM period (6:00 am – 10:00 am)
  • Same volume of traffic considered under all scenarios
  • South Drive traffic is distributed accordingly among other 2 entrances
  • Key model output was the queue length at each entrance within the turn lanes and associated spillover into through lanes on Old Georgetown Road.

Scenarios Analyzed

  • Scenario 1 - Baseline  (Present conditions)
  • Scenario 2 - South Drive Closed - 50% remaining traffic to Center, 50% to Lincoln
  • Scenario 3 - South Drive Closed - 75% remaining traffic to Center, 25% to Lincoln
  • Scenario 4 - South Drive Closed - 25% remaining traffic to Center, 75% to Lincoln
  • Scenario 5 - South Drive Closed - 60% remaining traffic to Center, 40% to Lincoln 

OLAO Simplified Acquisitions

Background
The purpose of the Simplified Acquisitions (SA) project was to identify opportunities to reduce complexity, waste, and lead time during the acquisition process. Steps were taken to obtain and analyze data from the process, (e.g., Deployment Flow Charts, Simplified Acquisitions Shared Spreadsheet, weekly reports sent to ICs, Simplified Acquisitions Spreadsheet Analysis). The challenge was to use the data to model the environment to informing SA management and staff of staffing requirements, devise a strategy for reducing process lead time, and ensure OLAO compliance with the Service Level Agreement with customers.

Goals and Objectives

  • Minimize the number of Requisitions in Queue
  • Enable OLAO to operate within SLA requirements
  • Identify process and staffing adjustments that maximize productivity and customer satisfaction

Scenarios Analyzed

  • End of the Fiscal Year
  • Increased Throughput

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