Simulator fidelity

Hays, R. T. (1980), Simulator Fidelity A Concept Paper, Tech. Rep. No. 490, Army Research Institute, Alexandria, VA. 

Hays, R. T., and Singer, M. J. (1989), Simulation Fidelity in Training System Design, Springer, New York. 

For years, simulator data collection has been seen and proposed as rich and good additional data source helping in HRA quantitative part. Although simulator exercises observation can help significantly in qualitative analysis of some factors influenciDg failure potential (team work), the idea of grounding HEP quantification just on simulator data is fairly naive, because the statistics is clearly insufficient to produce direct estimates and because of common simulator fidelity problems. 

Once the process simulation is developed, it is desirable to verify the simulation fidelity using different process conditions. The predicted product rates and purity and compositions as well as key operating parameters such as reflux rate and reboiling/condensing duties can then be compared with measurement. In some cases, performance tests are required to gather key data to compare with simulation for the accuracy and reliability of the simulation. To do this, performance tests must be conducted under steady and smooth conditions to mimic steady state operations. 

If the simulation fidelity is proven to be sufficient enough, it is ready to move to the next task, which is evaluation of the tower performance, because the purpose of reproducing the original design data is to understand the tower hydraulic and thermal performances of the base case and use the well defined base case to conduct what if analysis in order to identify improvements. 

Simulation fidelity is matched to training requirements. Simulation fidelity is a key factor in the success of simulation-based training system however, the much-used adage that more is better is not always true in this case. It has been suggested by many in the field that the physical fidelity of the simulation is less important than the psychological fidelity of the scenarios used. The level of simulation fidelity used is a function of the cognitive and behavioral requirements of the task and training involved. 

A third challenge is simulation fidelity, in particular whether there are faults in the system that the simulation cannot reveal because they depend on details that are not modelled. In this paper, we explore this issue in a simple way - we run simulations with both infallible sensors and sensors subject to random noise, and look at how the results of the latter simulations are richer (in terms of the range of hazardous situations found). 

Arandes et al. [37] and Han et al. [38] summarize the key submodels required for a unit-level model that can provide necessary simulation fidelity for this work. We briefly summarize these submodels in Table 4.3, and refer readers to these two papers for detailed equations and additional references. 

The withheld information technique is used to explore the manner in which operators select and use information in process abnormalities. A particular abnormal process event is represented in a control panel "mock-up" or a "low-fidelity" simulator, and information is withheld from the worker until it is requested. This technique has been developed by Marshall et al. (1981) and has been used to elicit the diagnostic plans used by experienced workers during various process transients in a crude distillation imit. There are three main applications of this technique ... 

One-dimensional turbulence A new approach to high-fidelity subgrid closure of turbulent flow simulations. Computer Physics Communications 148, 1-16. 

Fig. 8.3. A Acquired high SNR data and simulated noisy spectra (peak-to-peak noise = 0.001, 0.01, 0.1, and 0.4 a.u.), showing the degradation in data quality. Spectra are offset for clarity. B Spectra after noise reduction demonstrate the dramatic gains possible by chemometric methods. C Noise reduction was implemented to classify breast tissue and application of noise rejection allowed the same quality of classification (accuracy) to be recovered at higher noise levels. D In another example, image fidelity (here the nitrile stretching vibrational mode at 2227 cm-1) is much enhanced as a result of spectral noise rejection A and C are reproduced from Reddy and Bhargava, Submitted [165], D is reproduced from [43]...

Since the advent of efficient and robust simulation and optimization solution engines" and flowsheeting software packages that allow for relatively easy configuration of complex models, numerous integrated, high fidelity, and multiscale process model applications have been deployed in industrial plants to monitor performance and to determine and capture improvements in operating profit. 

When the simulation is complete, check the fidelity of the final trajectory file using the gmxcheck program and, if desired, convert to the less memoryconsuming. xtc format. Subset group trajectories based on groups listed in the index file can also be written. 

As with the standard simulation, check the fidelity of the final trajectory file using gmxcheck and convert to. xtc format if desired. 

Instabilities are present in the physical problem studied but they are also present in the numerical methods used to simulate these mechanisms. Most high-fidelity numerical schemes required for Computational Fluid D5mamics exhibit low dissipation and therefore multiple non-physical instabilities (wiggles) arise which can require significant efforts to be kept under control [374 362 340]. 

Numerical Waves in High-Fidelity Simulations of Reacting Flows... 

A less pleasant implication of Table 8.2 is that, as soon as high-fidelity methods such as DNS or LES are developed, they have to avoid large values of turbulent and artificial viscosities. This requires small mesh sizes, high-order schemes, small time steps [268 362 340]. But even after all these improvements, these methods will remain sensitive to numerical waves [363]. In DNS or LES, numerical waves are intrinsic elements of the simulation and must be controlled by something other than viscosity. This usually means significant improvements of initial and boundary conditions and a careful... 

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