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The Advancement of Simulator ModelsHow the Evolution of Simulator Technology has
Impacted its Application
Michael M. Petersen Xcel Energy
The Age of Simulation
• Simulation is the imitation of the operation of a real-‐world process or system over time. • Simulation has been around since before written and oral history. • Medical simulation was documented thousands of years ago.
Simulation as Simulation
• The Antoinette Learning Barrel • Allowed pilots to be trained to fly their Antoinette VII monoplane
Integrated Simulation
• The Link Trainer • A former organ and nickelodeon builder, Link used his knowledge of pumps, valves and bellows to create a flight simulator that responded to the pilot's controls and gave an accurate reading on the included instruments.
Electronic Simulation
• Cathode Ray Tube Amusement Device -‐ Artillery
Computer Simulation
• Atari -‐ SCRAM
The Power of Computers
• Gould Concept 32/97 • 4.67 MIPS • 16M of main memory • $5M • Original hardware for numerous simulators
Nuclear Power Plant Simulators
• Monticello • Rehosted to a PC with Intel Pentium II processor • 2,054 MIPS
The Power of Computers
• Intel Core i7 6950X • 317,900 MIPS • Roughly a 7,000,000% increase in speed from Gould 32/97 • 64G of main memory • $5k
Simulator Models
• Because of limited processing power, simplifications to models was common. • As hardware performance has improved simulator models have not only become more complex but have also added additional functionality. • More complex physical models • More detailed control system modelling • Data gathering and recording • Glass panel simulators • Severe accident models
Traditional Simulator Uses
• Things that it is certified to do: • Training • Experience requirements • Examination
• ANSI/ANS-‐3.5 and the associated testing program ensure qualification for these tasks. • The Nuclear Regulatory Commission verifies that our programs actually do what they are intended (Regulatory Guide 1.149).
Simulator Testing
• More sophisticated models allow for more precise and accurate tuning. • Transient testing can be pursued to a level far more aggressive than previously performed. • As a result (for Xcel simulators) several plant issues have been revealed by running transients on the simulator; • Unknown loop seal in an instrument sensing line. • Unknown core design “feature”. • Unknown feedwater system transient response.
Perspective
• A subtle but continuous shift in perspective on simulator “quality” has occurred over time due to various factors; • More sophisticated simulator models. • Expanded modelling of plant systems. • More detailed modelling of plant systems. • Better plant performance, so operators have less “real” transient experience and more “simulated” plant experience.
Extended Simulator Tasks
• Plant modification beta testing; • Proposed plant modifications are installed in the simulator to evaluate the design and provide “real world” operation and feedback.
• Evaluation of plant response; • Plant transient events are run on the simulator to see if the plant responded as expected.
• Evaluation of “What If” scenarios based on degraded plant conditions • Small steam leak that cannot be isolated – what is plant response if it gets bigger?
Unintended Consequences
• Other site personnel have a mental model of simulator capability and accuracy that is not based on reality • How fast does the room fill up with water?
• An engineer contacted the simulator group to ask us to run a specific simulation to justify a plant operability.
• We needed to break a specific pipe in a very specific location and trend how fast the turbine building basement filled with water, taking into account the volume of the equipment in the area.
• The output they needed was simple; • Exact pressure and flow from the leak • A graph over time of the water level in the room and an explanation of any knees in the rate of change of level
• A timeline of when each piece of equipment in the room failed and the mechanism by which it failed
Unintended Consequences
• The operator’s mental model is based more on simulator response than plant response (because plants rarely experience significant power transients). • This places a higher risk on simulator training to cause negative training because the operators “trust” the simulator and don’t as often engage in berating the fidelity of the simulator. • Incremental shifts in simulator response go unnoticed by operators that have never seen events in the “actual” plant.
Perception vs. Reality
What is wrong with being overrated?
• Unrealistically high expectations for simulator performance result in poor performance appraisals for simulator personnel. • There are no qualification or testing requirements for performing these extended simulator tasks. • Simulator staffing is based on traditional simulator uses and any tasks beyond that must be performed without additional resources. This problem is compounded by external personnel believing that the simulator already automatically performs the task you must do manually, with much effort.
Real or Imagined?
• Run the simulator in real time 60 minutes ahead of plant evolutions (including executing all procedure steps) to validate that those planned evolutions will go as expected (this is NOT JITT). • Use automatic IC creation routines to duplicate plant conditions in real time so the consequences of various potential recovery actions can be compared after a transient. • Use simulator transient response to justify plant system operability. • Use simulator response to justify continued operation beyond historical plant limits.
Engineering Calculations
• The simulator is not just a front end on an engineering calculation. • During power ascension for Extended Power Uprate the feedwater minimum flow valves experienced cavitation. • The engineering calculation did not predict this nor did anyone associated with the project have any idea that it might happen. • Senior Management personnel wanted to know why the simulator did not expose this condition when the power ascension was performed in the simulator. • Because of this, the simulator group spent much effort justifying why the simulator did not have a significant fidelity issue.
Learnings
• There is no good way to try and convince senior management that though you have an excellent simulator there is no way they should try to use it to see what the plant is going to do. • Most managers are not capable of understanding what intense surprise looks like on my face; when the simulator doesn’t halt when it is driven outside the scope of testing. • The current standards are not adequate to address testing the simulator to “qualify” it to perform the new tasks.
Learnings
• The expectation for simulator performance for “engineering” questions is that it EXACTLY replicate plant response as the plant is THIS VERY MINUTE even though the best engineering calculations available are just close approximations. • The resources to perform these new tasks are minimal in comparison to the resources needed to validate the performance of the simulator to justify performing these new tasks. • The simulator models are least accurate and most likely to give incorrect results exactly where the station expects the highest degree of fidelity.
Learnings
• Non-‐simulator personnel have no understanding of the approximations that are made in the models. • Non-‐simulator personnel do not understand the “tuning” process and thus do not understand that tuning is only affective for a range of operating parameters and when you get outside of that range the tuning is no longer affective. • Non-‐simulator personnel play too many FPS games and believe that the contrived reality they are exposed to on weekends is similar in some way to the simulator models of the reference unit.
Questions???