Simulations – a Guide to Terminology

Following on to our introduction to the benefits of Simulations in our earlier blog, we’re following it up with a guide to the terminology around the subject.

If you come from a technical and engineering background, the words used around the software are probably second nature, but if you’re not; we hope this helps you understand what we do and how it helps airports realise their capacity.

The background

Our simulations model real-life or hypothetical situations in an attempt to understand how they work, and how they work once a specific change or action has been applied.

For example, we often model the activities around airports and terminals to study the flow of traffic, passengers, airlines and more. We can then use this model when suggesting changes that can affect capacity such as seasonal changes. The resulting simulation then informs the client of the effects of any changes, before any investment has occurred. This could be prior to a design or to prove a design.

This is of great benefit to our clients, especially when some of them are complex airport hubs, responsible for millions of passengers, complex stakeholder negotiations and worldwide flight networks.

Big Data

This is the term applied to very large and complex data sets, that are difficult or impossible to manage in traditional or commonly used software.

Gartner  defines it as… “high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.” Wiki 2013. These data sets are almost incomprehensible sizes – petabytes and exabytes – that would be impossible to work with, unless you have specific software and a huge amount of servers to process it on, such as AiQ’s own bespoke 2D simulation tool, Transvision AiR.


2D/3D Visuals

We believe one of Transvision AiR’s key benefits is its 2D approach. Whereas many of our competitors concentrate on 3D as a way of helping the client visualize their processes, we believe that the ease of use and functionality of 2D can not be beaten.

Although 3D simulations make look more polished and offer a three dimensional overview, the 2D visual demonstrates plans and live operations with much more clarity. It is also a cheaper and less time consuming way of working, allowing us to offer much quicker and cost effective work. There is a lesser possibility of mistakes and less software to keep constantly updated.


Stochastic model

We have created Stochastic models for many of our clients, including Heathrow Airport, as it is a technique of presenting data that takes into account unpredictability, or randomness. When it is hard for the aviation industry to predict fluctuations in terminal traffic, passenger numbers or outside factors such as the weather, our models can help them judge the likely outcomes throughout each season.

Whether they need these models to justify any the impact of any changes in their processes, layout, etc, or to get a handle on possible risks of any situations that might impact on passenger experience, this simulation technique allows us to lay out the possibilities clearly and effectively.


Monte Carlo Method

AiQ uses Monte Carlo methods in our simulations to obtain a true realization of risk for our clients. Monte Carlo methods use repeated random sampling to create results. We run simulations many times over to calculate and define the possibilities of increased passenger flow, or traffic congestion, or more.

Although our inputs don’t have to be ‘truly’ random, although this isn’t an unusual thing in the aviation industry, we ensure that the situations we input into our simulations are random enough to capture the data we and our clients require.

Are there any terms you’d like us to explore further? Do you want to know anything else about Simulations? Let us know