Presentation Transcript

1. Ventilation, Heat, Moisture and Gas Flow Modeling with MULTIFLUX

   Presenters: George Danko, Professor PedramRostami, PhD Graduate Research Assistant Jon Fox, PhD Graduate Research Assistant Contributors: Davood Bahrami, Assistant Research Professor Ray Grymko, MS student William Asante, MS student Date: June 21st, 2012 Location: Salt Lake City, UT
2. Progress Summary Task 1.2. User interface design for MULTIFLUX (Task 1.2c. ) Progress: Continued the Graphical User Interface (GUI) development Plan for next quarter: Continue the user interface implementation Task 1.4. Gas liberation/storage/application model-element (Task 1.4c. ) Progress: Studied and conceptually designed the gas contaminant adsorption model-elements in MULTIFLUX. Plan for next quarter: Continue the study, apply it in numerical examples; design experimental comparison with data from mines. 3) Task 2.1 Development-end Ventilation application(Task 2.1c. ) Progress: Further studied characterization of the development-end module and presented the results to SME Annual Meeting. Also studied the effect of local cooling at Banshee drift at Barrick’sGoldStrike mine as an industrial application. Plan for next quarter: Continue with testing of the development-end template with the GUI. 4) Task 2.2 Ventilation with combined compressed air power application(Task 2.2a. ) Progress: This task is complete Plan for next quarter: No activity is planned
3. Progress Summary 5) Task 4.1MULTIFLUX model results comparison with monitored data(Task 4.1c. ) Progress: Designed, coded and tested the gas contaminant model elements in MULTIFLUX. Plan for next quarter: Continue modeling and comparison with data from mines. 6) Task 5.1A self-calibrating, time-dependent ventilation model concept(Task 5.1a. ) Progress: Studied the effects of time-dependent intake temperature variations. Plan for next quarter: Continue the modeling work; expand the solution to humidity variations. 7) Task 6.1. MULTIFLUX model application to DPM prediction(Task 6.1a. ) Progress: Studied the effects of time-dependent variations of concentrations in underground drifts. Plan for next quarter: Continue modeling work 8) Task 7. MULTIFLUX model application in education Progress: (Offered a graduate course using MULTIFLUX, Mine 701 ) Plan for next quarter: The education program continues Task 8. Publications and reporting Progress: Presented one SME paper at the SME annual meeting. Submitted the 2nd progress report in Phase 3. Worked on completing and submitting four papers to the 14th North American Mine Ventilation Symposium (NAMVS) in Utah. Plan for next quarter: Continue with publications and reporting
4. Mackay Team Overview Industry contributions and publications Goals, research approach & findings this year Equivalent and hydraulic diameters Transient temperature variations Contaminant spread and transient, modeling approach Complex Ventilation and Contaminant Simulation with MULTIFLUX VOD simulation with MULTIFLUX MULTIFLUX GUI development Side-by-side comparison of MULTIFLUX Development end MULTIFLUX sub-model template
5. Project Participants PI George Danko, PhD, University of Nevada, Reno 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4284; Fax: (775)784-1833; E-Mail: danko@unr.edu Co-PI DavoodBahrami, Ph.D., University of Nevada, Reno 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4210; Fax: (775)784-1833; E-Mail: dbahrami@unr.edu Co-PI Pierre Mousset-Jones, Ph.D., University of Nevada, Reno 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-6959; Fax: (775)784-1833; E-Mail: mousset@unr.edu GRA PedramRostami, PhD student 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4209; Fax: (775)784-1833; E-Mail: prostami@unr.edu GRA Jon Fox, PhD student 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4185; Fax: (775)784-1833; E-Mail: jefox@unr.edu GRA Raymond Grymko, MS student 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4209; Fax: (775)784-1833; E-Mail: rgrymko@unr.edu GRA Rajeev Gunda, MS student 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4209; Fax: (775)784-1833; E-Mail: rajeev.gunda@amec.com GRA William Asante, MS student 1664 N. Virginia St., Mailstop 173, Reno, NV 89557 Phone: (775)784-4210; Fax: (775)784-1833; E-Mail: eponition@yahoo.com Industrial Partner BarrickGoldstrike Mining Co.
6. Industry Professional Contributions Rajeev Gunda(MS Mining, August ’11) – Employed at AMEC, Phoenix, AZ – Ventilation Engineer, starting November 2011. Raymond Grymko(MS Mining, August ’12) – Employed at Vale Inco, Sudbury, Ontario, Canada – Ventilation Engineer, starting June 2012.
7. Publications Bahrami D., Danko G., Fox J., Robertson K., 2012 “Development-End Cooling Study.” 14th US/North American Mine Ventilation Symposium, Salt Lake City, Utah. Danko G., and Bahrami D., 2012. “Convective, Diffusive and Dispersive Transport of Gaseous Constituencies by Ventilation.” 14th US/North American Mine Ventilation Symposium, Salt Lake City, Utah. Danko G., Bahrami D., and Mousset-Jones P., 2011 “Ventilation and climate simulation with the MULTIFLUX code.” The 2nd International Conference on mining, Mine Safety and Mine Environment Protection, Xi'an, Shaanxi, China. Danko G., and Bahrami D., 2011 “Ventilation, Heat, Moisture and Gas Flow Modeling with MULTIFLUX.” Third Outreach Seminar, BarrickGoldstrike Mine, Nevada. Danko G., and Bahrami D., Asante W. K., Rostami P., and Grymko R., 2012 “Temperature variations in underground tunnels.” 14th US/North American Mine Ventilation Symposium, Salt Lake City, Utah. Fox J., Danko G., and Bahrami D., 2012 “Development End Characterization Through Response Curves.” SME Annual Meeting, Seattle, Washington.
8. Project Goals To apply the MULTIFLUX air flow, heat, moisture, and gas transport simulation model to ventilation tasks in deep, hot underground mines and demonstrating its capabilities in accurate predictions. To use MULTIFLUX in selected cases by demonstrating improvement in safety and costs. To make MULTIFLUX easy to use as a new mine ventilation and contaminant transport model. To educate students and technical professionals how to use it.
9. Description of the research approach Add new, necessary components to the MULTIFLUX software and model originally developed and qualified for nuclear waste repository ventilation, heat and moisture simulations. Provide the ventilation engineer with an easy–to–use graphical interface for model definition and input data entry. Interpret and animate the results graphically. Apply the MULTIFLUX model to industrial mine ventilation tasks including applications with BarrickGoldstrike, our research partner. Work with a total of six students as research assistants.
10. Project Findings MULTIFLUX is used in predicting the performance of a spot cooler at the BarrickGoldStrikemine. An advanced modeling approach was used to predict the cooling effect of an air chiller if it is installed outby from the working face. The net results show that the spot cooler with 11oC of chilling capacity is cooling the air at the working face by about 6oC. An artificial numerical dispersion error in the simulation results and systematic solution error in the travel time of concentration front , both depending on the discretization scheme and the refinement of the grid were found. But a solution used in MULTIFLUX can be made free of both errors even if relatively large grid sizes are used. The test cases and benchmarking applications reviewed show that MULTIFLUX captures the relevant heat and moisture transport processes excellently than methods which use the simple Gibson age function. MULTIFLUX outperforms Ventsim, which provides only an approximate, but not an exact solution for the transient model. Therefore, we believe that MULTIFLUX is a correct transient model for the contaminant spread in a mine airway. With no temperature history effect in MULTIFLUX, its results are in very good agreement with the other models, namely, with perfect, near-perfect, and very good agreement with Vuma, Climsim, and Ventsim, respectively, but when MULTIFLUX is modeled with temperature history effect very significant disagreements are obtained with the other models. Pre-modeling the development end allows for fine mesh evaluation throughout the mine-wide ventilation model. Results of modeling yields response functions for primary air mass parameters, which respond to intake air mass variations.
11. Transport Model Elements For Conservative Scalar Transport processes The transport of a chemically non-reactive, single-component substance Scalar substance may be: Bulk Mass Water vapor Concentration Contaminant Concentration Heat Six transport modes which are of interest in mine ventilation: Advection Diffusion Dispersion Convection Accumulation or discharge ( Source or Sink)
12. Numerical Applications Two mine ventilation examples are presented to demonstrate the performance of the numerical solution method used in MULTIFLUX for simulating traveling of contaminant concentration with the ventilating air; A simple air flow network with a diagonal airway A single drift
13. Network Example 1 : Contaminant travel in MULTIFLUX with D=0.05 m2/s and Ventsim with default configuration (A) (B) (C) (D) (E) (F)
14. Network Example 2 : Contaminant travel in MULTIFLUX with D=0.0 m2/s and Ventsim with default configuration B C E A D Locations: A: x=10 m B: x=250 m C: x=500 m D: x=750 m E: x=1000 m
15. Network Example 1 : Contaminant travel in MULTIFLUX with D=0.05 m2/s and Ventsim with default configuration A B C D E Locations: A: x=10 m B: x=250 m C: x=500 m D: x=750 m E: x=1000 m
16. Conclusions An artificial, numerical dispersion may occur in the simulation results of fast-traveling concentration transients transported by advection. Numerical dispersion is an error in the simulation, depending on the discretization scheme and the refinement of the grid. In addition to the numerical dispersion, another, systematic solution error may appear in the travel time of the concentration front. This error also depends on the discretization scheme and the refinement of the grid. A solution used in MULTIFLUX, a new mine ventilation, heat, moisture, and contaminant transport model and code, was presented which can be made free of both numerical dispersion and the systematic error in concentration travel time even if relatively large grid size is used.
17. PedramRostami Equivalent and hydraulic diameters Transient temperature variations Contaminant spread and transient, modeling approach Complex Ventilation and Contaminant Simulation with MULTIFLUX
18. Equivalent and hydraulic diameters Equivalent diameter of a rectangular opening is defined as the diameter of a circular opening having the same pressure loss. The hydraulic diameter, dh, is used to determine the dimensionless Reynolds number to see if a flow is turbulent or laminar. dh = 4*A/P Since equivalent diameter results in simplified calculations, current ventilation programs use this instead of the actual geometry of the drifts.
19. Results and concluding remarks Shape and size analysis various shapes and sizes of mine airways were studied Infinitely long wall (flat model), original size rectangular-shaped model double-size rectangular model were studied and analyzed. Study results show the rectangular (including square) models have a heat flux percentage difference of about 5% with the equivalent diameter size cylindrical models. There is no need to consider the actual drift geometry. Equivalent diameter is sufficiently accurate for airflow calculations.
20. Transient temperature variations Flywheel effect in underground mining The thermal flywheel is effectively storage and release of heat from the intake air into the intake airways as a function of the diurnal and seasonal change in surface temperatures It can be considered as a damping effect. Heat stored by hot intake air into intake airway walls is released in the cooler time periods (mostly evenings) This lowers the predicted underground temperatures during the day (compared to theoretical values) but increases the underground temperatures (when wall temperatures are now hotter than intake air temperatures) during the night (effectively a phase shift) Currently used mine ventilation and climate models, apply the Gibson function for wall heat flux without superposition. a step-change model element that erases the true temperature history Refer to ”Temperature variations in underground tunnels” by G. Danko, D. Bahrami, P. Rostami, W. K. Asante, and R. Grymko
21. Comparison between History and No History Effects on Simulation Results 1km & 5m3/s 3km & 50m3/s 5km & 100m3/s
22. Comparison between Temperature Mesh With and Without Temperature History With History at 50m3/s airflow rate. Without History at 50m3/s airflow rate.
23. Contaminant spread and transient modeling BarrickGoldstrike, modeling approach is described in the following. Type of contaminants: SO2 and CO are selected as the two problematic gases. Sources of contaminants: Strata Operating machinery Blasting operations Ventilation recirculation
24. Mine Overview North Rodeo, Level 4040 Meikle, Level 1075
25. Rodeo North Working Zones CO2 Monitoring Station SO2 Monitoring Station Active Face CO Monitoring Station Junction
26. Meikle Working Zones North Active Face Junction
27. Heat and Water Distribution ** Electrical power consumption is not considered in the heat simulation. The electricity is assumed to be used mainly by, hoisting, pumps and lighting of the mine.
28. Complex Ventilation and Contaminant Simulation with MULTIFLUX Background Dispersion of contaminant gas can happen due: Along the length of the airway through natural dispersion. From low velocity flow to high velocity in the center of the airway. In the Cross-sectional area of the airflow depending on the concentration zone. And finally the convective dispersion from the forced air. Current codes use a simple algorithm which distributes Contaminants in a linear velocity fashion, and assumes perfect mixing at intersections. This method is fine for studies through broad mine areas, but is not recommended for analysis of contaminant diffusion on a small scale level
29. Spatial Issue Due to the location of a source and ventilation system spatial inhomogeneity arises. In addition to this spatial variability there is also temporal variability processes coming on and going off line and ventilation rates changing with time. While the worker is moving in this complex environment the concentration level of air he is breathing may be different from the average. What is a safe zone! Exposure is limited or not harmful! Where is the safe zone?
30. Average Concentration level
31. Methodology A CFD model needs to be established. This master model will be used to run various scenarios. Results will be compared and analyzed. Considering the geometry source terms, machinery and obstacles in the airway we can: Propose a distance in which the flow is mixed enough and any measurements of contamination would represent the average value.
32. Temporal Issue When and at what concentrations level? Be able to predict arrival time and concentration levels at any given point in the mine network. We need: Calculate a dispersion coefficient that represent all types of diffusions mentioned before in the airway. Use the representing dispersion coefficient for a larger scale contaminant modeling. Model In a non-CFD code.
33. Concentration Arrival time Dilution
34. Methodology CFD model will be established using gathered data from the mine. This master model will be verified and used again in various ventilation scenarios to calculate the dispersion coefficient and compare the findings to the spatial issue. The calculated parameters will be used in future predictions of contaminant arrival and concentrations at a given point using MULTIFLUX code.
35. Data collection and calibration of the model This investigation of contaminant behavior can be achieved by gathering required data from actual mine scenario. This data collection set is one the most crucial steps in modeling and verification of findings. Two sets of database are needed to address the temporal and spatial issues. First Set The first data set includes three stations located 100meters apart from each other in a long airway. We need to take 10 measurements of velocity and contamination concentrations in each station for three different scenarios of, 1) no airflow, 2) laminar and 3) turbulent. Second Set The second set of data base would include measurements of velocity and concentrations before and after the contaminant source. We need to know the airway properties (geometry, obstructions and heat transfer properties), to find a distance from which the measurements would represent the average of the mixture.
36. Jon Fox VOD Simulation with MULTIFLUX MULTIFLUX GUI Development Side-by-side comparison of MULTIFLUX, Ventsim & Vuma vs. VnetPC/Climsim Development end MULTIFLUX sub-model template
37. VOD Simulation with MULTIFLUX Define control architecture. Vary one big underground booster fan. Study mass flow cross effects among affected ventilation districts.
38. Mine-wide ventilation control flow chart
39. Change in Airflow Directions From Variable Fan Modulation Modulate twin Joy M84 booster fans at 1450 level Variable frequency modeled @ 50%
40. Change in Airway VelocitiesDue To Fan Modulation Modulate twin Joy M84 booster fans at 1450 level Variable frequency modeled at 50% pressure Affected airways are shown in red
41. Conclusions Careful model exercises are needed VOD to understand cross-effects on dynamic changes. Variations of VOD control components must be carefully evaluated. Future research findings will drive new developments in ventilation control architecture.
42. MULTIFLUX GUI Development Network definition is made in Google SketchUp Airway branch definition is by: graphical template selection and Interactive user’s data input
43. Side-by-side comparison of MULTIFLUX, Ventsim & Vuma vs. VnetPC/Climsim Base model of Garson nickel mine with aerodynamic simulation in VnetPC and thermodynamic simulation in Climsim. Verification methods have been validated in Matlab. Comparison of dry bulb and wet bulb predictions are the meter of modeling performance.
44. MULTIFLUX model verification methods
45. MULTIFLUX model verification methods
46. MULTIFLUX Graphical User Interface Google SketchUp Workspace
47. Ventsim model
48. Vuma model
49. Conclusions Without a tutor properly versed in each simulation software, the probability of creating an accurate model is spotty at best. Having reliable technical support that can guide the student through the intricacies of the model configuration is paramount when comparative simulations are required. Until extreme resistances, either zero or (practically) infinite, are resolved into realistic resistances even the base case airflow model is suspect.
50. Development end MULTIFLUX sub-model template Cooling capacity prediction and parametric studies are being conducted to support the design or the development of single-entry drifts A new set of data has been obtained from the Barrick Gold strike Mine complex for model verification The goal of the study is to model and apply a development-end template and determine the performance of the proposed chiller in providing workable environment at the face
51. Ventilation configuration for the Banshee development end
52. Geometry, specification & measurement locations for the Banshee development end
53. Drift airflow direction Duct airflow direction duct drift Pressure distribution with three fan locations, p3. Pressure distribution along drift and duct with 2.7kPa back pressure behind the bulkhead.
54. duct drift Drift airflow direction duct airflow direction Dry bulb temperature distribution along drift and duct
55. Conclusions Transient thermal-humidity simulation needs to be configured to predict the true effect of the installed chiller. 14% leakage between duct and drift has been determined. MULTIFLUX is capable of simulating this multiple-aged case with multiple transients. A net temperature decrease of 6 °C can be expected at the face.