Computer simulations are programs that run various mathematical scenarios to determine the potential scope or impact that a particular scenario could have.
Computer Simulation Definition
A computer simulation uses mathematical equations to model possible real-world scenarios, products or settings and create various responses to them. It works by duplicating the real-life model and its functions, and — once it’s up and running — the simulation creates a record of what is being modeled and its responses, which is translated into data.
For example, simulations help car manufacturers virtually crash-test their new lines of vehicles. Instead of physically crashing dozens of new cars, researchers run simulations to see all possible scenarios that could occur to both the vehicle and passengers in a multitude of accidents. These simulations determine if the car is safe enough to drive.
The idea is that computer simulations allow researchers to replicate possible real-world events — ranging from the spread of infectious diseases to impending hurricanes — so we can save time and money planning for the future.
What Is a Computer Simulation?
Computer simulations are computer programs that model a real-life scenario or product and test many possible outcomes against it.
“Simulation allows you to create data or systems that are conceptual, that people want to build, want to consider or want to change,” Barry Nelson, a professor of engineering at Northwestern University, told Built In. “I sometimes say that simulation is data analytics for systems that don’t yet exist.”
Although computer simulations are typically used to test potential real-world scenarios, they can be more theoretical too. In 2016, scientists at Argonne National Laboratory near Chicago, Illinois concluded that it would take only a couple of months for zombies to overrun the city and wipe out its population.
Fortunately, we now have “the knowledge to develop an actionable program to train the population to both better defend themselves against zombies and also take offensive actions that are the most effective,” Chick Macal, an Argonne senior systems engineer, told Built In.
Pivoting back to reality, Macal and his co-researchers wanted to predict how more plausible infectious diseases might spread and determine the most effective methods for intervention and policy action. Their research relied on what’s called agent-based computer modeling and simulation. This method has allowed researchers in all types of academic disciplines and commercial industries to figure out how things (equipment, viruses, etc.) would function or act in certain environments without having to physically replicate those conditions.
Macal’s colleague, computational scientist Jonathan Ozik, described this part of their work as the “computational discovery of effective interventions,” and it’s especially good at working with a particular population of people. An added benefit, he said, is that “we can do these experiments without worrying about the cost of experiments or even ethical and privacy considerations,” because the populations they study are synthetic representations, not the real thing.
How Do Computer Simulations Work?
Computer simulation is a step-by-step process in which a computer simulation program is modeled after a real-world system — a car, a building or even a tumor. To replicate the system and possible outcomes, the simulation uses mathematical equations to create an algorithm that defines the system’s state, or the combination of different possible variables. If you’re simulating a car crash, for example, the simulation’s algorithm can test what would happen if there was a storm during the crash against what happens when the weather is milder.
The simulation calculates the system’s state at a given time (t), then it moves to t+1 and so on. Once the simulation is complete, the sequence of variables is saved as large datasets, which can then be translated into a visualization.
“We’re not interested in simply extrapolating into the future,” Macal said. “We’re interested in looking at all the uncertainties as well as different parameters that characterize the model, and doing thousands or millions of simulations of all the different possibilities and trying to understand which interventions would be most robust.”
This is where high-performance computing comes in. Thanks to the robust data-crunching powers of supercomputers, simulation is more advanced than ever — and evolving at a rapid pace. The computational resources at their disposal, Ozik said, allow researchers “to fully explore the behaviors that these models can exhibit rather than just applying ad hoc approaches to find certain interesting behaviors that might reflect some aspect of reality.”
Which is to say, the simulations are much broader, and therefore even more realistic — at least from a hypothetical perspective.
Computer Simulations in the Real World
Plenty of simulations are done with far less computing power than Argonne possesses. Alison Bridger, department chair of meteorology and climate science at San Jose State University in California, said on-site cluster computers are strong enough to run the climate simulation models she builds. Cloud computing services like those offered by Amazon (AWS) and Microsoft (Azure) are gradually gaining a foothold in the space as well.
Along with nuclear physics, meteorology was one of the first disciplines to make use of computer simulation after World War II. And climate modeling, Bridger said, “is like a close cousin of weather forecasting. Back in the 1960s, people used early weather forecasting models to predict the climate. Before you can predict the weather, you have to be able to properly reproduce it with your model.”
Bridger’s work employs a widely used “local scale” model called WRF, which stands for Weather, Research and Forecasting and can produce “reasonably good simulations of weather on the scale of, say, Northern Illinois — so Chicago up to Green Bay and down into the central part of the state. It will forecast things like high and low temperatures, rain and so forth. And it’s typically only run to simulate 24, 48 or 72 hours of weather.”
In further explaining her process, Bridger employs the imagery of a cube centered over Chicago that’s roughly a kilometer east-west by a kilometer north-south. The goal is to predict the temperature in the cube’s center and extrapolate that reading to the entire thing. There are also additional cubes surrounding the initial one “stacked up all the way to the top of the atmosphere” whose future temperatures will be predicted in various time increments.
Next, temperature-affecting variables are added to the mix, such as amount of sunshine, cloud cover, natural disasters like wildfires and manmade pollution. It’s then a matter of applying the laws of physics to determine a variety of weather-related events: rising and falling temperatures, amount of wind and rain and so on.
8 Examples of Computer Simulations
Whether scientists want to better understand healthcare responses or even explore black holes, computer simulation allows for important research opportunities:
1. Responding to Pandemics
Along with Ozik and their fellow researcher Nick Collier, Macal also worked on a modeling and simulation project that determined what might happen if the deadly Ebola virus — which initially spread through West Africa in 2013 through 2016, with devastating effects — would impact the United States population. Part of that process involved visiting Chicago hospitals to learn about Ebola-related procedures, and then incorporating those procedures into their models.
2. Improving Cancer Treatment
Other Argonne scientists have used modeling and simulation to improve cancer treatment through predictive medicine, finding out how various patients and tumors respond to different drugs.
A 2019 study found positive results in simulating breast cancer tumors. For the study, researchers built a computer simulation that modeled tumors from four different patients under 12-week therapy treatments. After two of the simulated tumors didn’t respond to treatment, they concluded that more frequent, lower doses of chemotherapy could reduce a low proliferative tumor, while lower doses of antiangiogenic agents helped poorly perfused tumors respond to drug treatment better.
3. Predicting Health Code Violations
In Chicago, the city’s Department of Public Health uses computer modeling and simulation to predict where critical violations might pop up first. Those restaurants are then bumped to the top of a 15,000-establishment list that’s overseen by only three dozen inspectors. One simulation yielded 14 percent more violations, which ideally means earlier inspection and a lower chance of patrons getting sick from poorly refrigerated fish.
4. Understanding Our Relationship With Religion and Crisis
Computer simulation is being used in interesting ways at the University of Boston. Wesley Wildman, a professor of philosophy, theology and ethics, uses computer simulation to study “how religion interacts with complex human minds, including in processes such as managing reactions to terrifying events.”
He and his team designed a world and filled it with computer-controlled characters, or “agents,” that are “programmed to follow rules and tendencies identified in humans through psychological experiments, ethnographic observation and social analysis.”
Then they observed what happened when their agents were tested against real-world examples like a massive earthquake that struck Christchurch, New Zealand, in 2011.
“The better our agents mimic the behavior of real humans in those sorts of circumstances,” Wildman said, “the more closely aligned the model is with reality, and the more comfortable we are saying humans are likely to behave the way the agents did in new and unexplored situations.”
5. Researching Earthquakes
In Germany, a team at the Leibniz Supercomputing Centre performed earthquake simulations using the devastating Indian Ocean earthquake of 2004, which spurred a massive tsunami, as their point of origin.
According to Professor Michael Bader of Germany’s Institut für Informatik, they wanted to “better understand the entire process of why some earthquakes and resulting tsunamis are so much bigger than others. Sometimes we see relatively small tsunamis when earthquakes are large, or surprisingly large tsunamis connected with relatively small earthquakes. Simulation is one of the tools to get insight into these events.”
But it’s far from perfect. New York Times reporter Sheri Fink detailed how a Seattle-based disaster response startup called One Concern developed an earthquake simulation that failed to include many densely populated commercial structures in its test runs because it relied on residential census data. The potential real-world result of this faulty predictive model: Rescuers might not have known the location of many victims in need.
6. Exploring Black Holes
In 2024, researchers in the Netherlands built a black hole simulation by modeling a single-file chain of atoms to create the event horizon of a black hole. This led to the team observing Hawking radiation, the hypothetical theory that particles formed by the edge of a black hole create temperatures that are inversely proportional to a black hole’s mass. Although the research is still in its early stages, this could potentially help scientists understand and resolve the differences between the general theory of relativity and quantum mechanics.
7. Supporting Sustainability Initiatives
Environmentally friendly technologies can be expensive to create and operate, so simulations are being used to prove the feasibility of greentech projects. For instance, a team of researchers at Berkeley Labs used computer simulations to study a property of transistor materials called negative capacitance, which enables them to store more electrical charge while requiring less voltage. By studying this property, scientists aim to build more energy-efficient microelectronics moving forward.
A Swedish company called Novatron also employed simulations to prove the viability of its fusion solution. Running computer simulations, Novatron has been able to confirm that its fusion technology is stable and ready to fuel a fusion reactor. According to the company’s timeline, a Novatron fusion reactor will likely be up and running at a power plant by the 2030s.
8. Predicting Air Quality During Natural Disasters
In the area of public health, computer scientists at the University of California San Diego created detailed computer-generated images of fluid dynamics, such as those seen in volcanic smoke. These highly realistic models enable researchers to understand how smoke disperses during volcanic eruptions. Public health experts could then use these insights to predict air quality levels and direct the public accordingly to prioritize people’s safety.
Uses of Computer Simulation in Different Industries
In the past 75 years, computer modeling and simulation has evolved from a primarily scientific tool to something industry has embraced for the purposes of optimization and profitability.
“Industry is embracing simulation at a faster rate than ever before and connecting it to what I would call data analytics for things like scheduling and supply chain management,” Macal said. “Industry is trying to simulate everything they do because they realize it’s cheaper and quicker than actually building a prototype system.”
When Northwestern’s Nelson spoke with Built In, he had recently returned from the annual Applied Probability Conference. There, the simulation applications discussed included but weren’t limited to the following: aviation modeling, cybersecurity, environmental sustainability and risk, financial risk management, healthcare, logistics, supply chain and transportation, semiconductor manufacturing, military applications, networking communications, project management and construction.
“Frequently, companies that use simulation want to optimize system performance in some sense,” Nelson said, using a car company that wants to build a new assembly plant or decide what vehicles to bring to market as an example.
Industries Must Apply Computer Simulations With Caution
While simulations promise to enhance various systems, organizations would be mistaken not to exercise caution with this approach. Simulations are built on data, so any errors in the data, incorrect assumptions and other minor missteps can snowball into major issues.
“When people build mathematical and computer models, even though the model may have been built from data, they treat it as if the model is correct and therefore the solution that [results] is optimal,” Nelson said. “What we try to do is continue to incorporate in the model the uncertainty that was created when we built it.”
The financial crisis of 2008, Nelson said, is one instance where model risk was detrimentally downplayed.
“The financial industry uses a tremendous number of very sophisticated mathematical computer modeling [methods],” he said. “And it’s quite clear that the correlations among various financial instruments and securities and so on were kind of ignored, so we got cascading failures.”
Such cautionary tales, however, don’t mean that those who create the mathematical and computer models on which simulations are based must strive for perfection — no model is perfect, and models drive progress. Demanding perfection, Nelson said, “would paralyze us. But as we start to make more life-critical decisions based on models, then it does become more important to account for risks.”
The Future of Computer Simulations
Computer simulations will continue to play an integral role across a range of contexts.
Accelerating Cancer Discoveries
Imagine someone you know has been diagnosed with a cancerous tumor. But instead of immediately bombarding them with radiation and highly toxic chemotherapy drugs and hoping for the best, doctors instead perform tests from which they create a mathematical, virtual twin of that person’s malignant growth. The digital replica is then subjected to computational interventions in the form of millions or even billions of simulations that quickly determine the most effective form of treatment.
This vision is becoming a reality, thanks to a partnership between the National Cancer Institute and the Department of Energy. Through the use of simulations and digital twins, these partners can better understand cancer behavior and outcomes to develop more effective treatments.
Enhancing Molecular Research
As Los Alamos National Laboratory physicist Justin Smith told Science Daily, “we can now model materials and molecular dynamics billions of times faster compared to conventional quantum methods, while retaining the same level of accuracy.”
That’s good news for drug developers, whose researchers study molecular movement to see what’s suitable for use in pharmaceutical manufacturing, as well as patients who are all too often caught up in a detrimental guessing game when it comes to treatment.
Anticipating the Diseases of Tomorrow
Computer simulations are also paving the way for researchers to prepare for the next wave of diseases. For example, scientists at the University of Surrey designed a simulation to model how the brain grows neurons. By understanding the development of neurons, researchers hope they can apply this knowledge to tailor solutions to neurodegenerative diseases and eventually learn how to regenerate brain tissue as part of stem cell research.
Meanwhile, researchers at the University of Oxford’s Pandemic Sciences Institute are using computer simulations to model disease outbreaks and understand how to best conduct vaccine trials. With insights gleaned from these scenarios, researchers can prepare an appropriate response for the next pandemic.
Improving Weather Forecasting
Penn State researchers working in tandem with colleagues at the University of Almeria in Spain developed “a computer model that can help forecasters recognize potential severe storms more quickly and accurately.” As Steve Wistar, a senior forensic meteorologist at AccuWeather, explained, the tool could lead to better forecasts because he and his fellow forecasters will have “a snapshot of the most complete look of the atmosphere.”
Frequently Asked Questions
What is meant by computer simulation?
A computer simulation is a computer program that builds mathematical models to accurately represent and predict the behavior of a real-life system. In this case, a system can be something as small as a tumor or as vast as a galaxy.
Which is an example of computer simulation?
Real-life examples of computer simulations span many industries, with more common examples being car crash simulations, predictive disease models and weather forecasting models.
Is it possible that we are living in a computer simulation?
Simulation theory — the idea that our reality is a computer simulation — has influenced actual experiments and led some scientists to conclude that we really are living in a simulation. While there is a possibility that this is true, the theory remains up for debate.
