A dynamic simulator at Texas A&M–Corpus Christi is helping process industries build better-prepared operators, improve abnormal-situation response, and reduce avoidable downtime.
Abnormal situations remain one of the biggest threats to safe and efficient operation across refineries, petrochemical plants, pipelines, and other processing facilities. Most modern facilities already employ control, alarm, and safety systems. The issue is not usually whether those layers exist. It is whether they will perform well enough together once a process moves outside normal operating ranges.
Many protection strategies still depend, at least in part, on operator action. Those actions can only reduce risk if the operator can detect the condition, diagnose the cause, and complete the required response within the available time. When that does not happen, alarms build, conditions change, and a manageable deviation can turn into lost production, downtime, or something more serious.
There is growing interest in addressing that problem before it unfolds in a live facility or across a transportation network. At Texas A&M University–Corpus Christi (TAMU-CC), a digital twin control room simulation effort is being developed with funding from the U.S. Department of Transportation’s Pipeline and Hazardous Materials Safety Administration (PHMSA) and with support from Honeywell. Honeywell is providing an operator training simulator that includes process simulation, control emulation, and an Experion control-system environment.
Dynamic simulation
“One of the biggest blind spots is assuming operator response will succeed without fully testing whether the system gives the operator the clarity, time, and support needed under pressure,” says Angela Summers, president of SIS-TECH Solutions and an expert in process safety and safety instrumented systems.
Summers says many facilities credit operator response as a safeguard without fully verifying how it will hold up as conditions begin to deteriorate. On paper, the required action can look simple. In a real control room, it rarely is.
She points to the kind of scenario that exposes the gap: an inlet valve fails open, the procedure says to close it, and the valve does not respond. The real test is whether the operator can quickly determine the next move, whether that means sending a field operator to check the valve status, isolating upstream, or taking another action before the available time runs out.
“We don’t always verify that the operator can detect the condition, understand what is happening, and take the right action within the time available,” she explains. “Until that is tested under realistic conditions, that layer of protection is still an assumption.”
Honeywell’s Chris Jones says the project will look and feel like a real control-room environment, with the main variable being how closely the simulated process mirrors a specific live operation. That realism is what makes the exercise useful beyond classroom instruction. It allows operators, researchers, and industry partners to study how people and systems respond as a theoretical disturbance unfolds.
What the simulator can reveal
Once that environment is in place, the value of simulation goes beyond rehearsing rare scenarios. A plant may appear acceptable on normal alarm metrics and still bury the operator with alarms during an upset.
Summers notes that once conditions begin to propagate through an integrated process, the operator may be hit with a surge of alarms at exactly the moment clear prioritization becomes critical. In that kind of environment, simulation can be used not only to test operator response, but to evaluate which alarms should be prioritized or suppressed so the initiating problem is easier to diagnose under stress.
The same environment can expose other weaknesses that are difficult to identify in conventional reviews. Alarms may obscure the initiating cause instead of clarifying it. Interface design may slow recognition of what matters most. Procedures may no longer align with what the operator is actually seeing. Control strategy may leave too little time or too little support for recovery once the process begins moving away from normal.
For operating companies, those are important questions, but not always easy ones to study in live operations. Jones says day-to-day production, reliability, and profitability demands rarely leave much room for deep what-if research.
Those kinds of questions are difficult to answer in a live operating environment. That is where the university setting becomes useful.
Dr. Jangwoon Park, who is the Principal Investigator for this PHMSA-funded research at TAMU-CC, says the lab can be used to run controlled human-factor studies and experiments that are often much harder to carry out in industry. That includes studying how interface design, alarm presentation, workload, and other conditions affect operator decision-making under pressure.
Park’s focus is especially relevant in pipeline control rooms, where fatigue, cognitive demand, long shifts, and communication challenges can all shape how operators interpret and respond to developing conditions.
Industry impact
Dr. Stewart Behie, who joined TAMU-CC after more than four decades in major-hazard risk management and process safety, says the goal is to create an environment that feels familiar enough to industry to support meaningful training and practical research. Someone sitting in the lab’s control room, he explains, should see exactly the same type of setup they would encounter in plant operations.
That has implications both for workforce readiness and plant performance. It can shorten the path for new operators entering increasingly complex control environments. It can also help facilities identify weaknesses in alarms, procedures, and interface design before those weaknesses are exposed during a live upset.
“Most operating companies are consumed by production, reliability, and profitability demands, leaving limited room for repeated scenario testing or extended what-if analysis,” explains Jones.
A university lab can take on that research burden, run scenarios multiple times, and generate practices that industry can later apply without having to do all of the raw research itself.
For Behie, that creates value beyond the classroom.
“This creates a place where operators can be exposed to upset conditions, alarm overload, and interface challenges before those issues are staring at them in a live system,” says Behie.
It also opens the possibility of supporting facilities that do not maintain their own simulator but still want access to more realistic operator training.
From assumption to evidence
The larger opportunity is for plants to move beyond assuming operator response will work and begin testing the conditions that make good response possible. That includes alarms that help rather than distract, interfaces that make the initiating problem easier to recognize, and procedures that still work when the process is moving away from normal.
For operators, engineers, and plant managers, the question is not whether simulation exists. It is whether the protection strategies credited on paper will hold up in the control room when alarms start stacking up and time begins to shrink.
If a realistic simulation environment exposes those weaknesses before a live upset does, the payoff goes well beyond training. It can mean faster diagnosis, fewer avoidable trips, stronger abnormal-situation response, and more confidence that the operator layer will perform when it is needed most.
