A Simplified Chamber Pressure Model for EPB TBM Tunneling in Granular Soil. Hongjie Yu Mike Mooney Adam Bezuijen
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1 A Simplified Chamber Pressure Model for EPB TBM Tunneling in Granular Soil Hongjie Yu Mike Mooney Adam Bezuijen 1
2 Excavation chamber is like the Heart Beat of the TBM During advancement, TBM operation varies Material flow Thrust& Torque Cutterhead & screw conveyor #5 #6 #4 #1 #3 #2 2
3 Model Overview Simulated region: chamber with a fixed size Tool gap: where formation soil is mixed Operation input Advance rate, v Cutterhead rotation speed, ω Screw conveyor speed, ω s Injections, Q air, Q sol, Q adt Pressure output Pressure gauge readings, p x is neglected, but not for y and z z is caused by muck unit weight Q formation Q foam Q Adt Simulated region Tool gap Pressure gauge Q out 3
4 Model Physics Three physical processes are considered important and modeled Compressible material flow Fluid seepage Rotation induced muck surface 1. Compressible material flow Formation soil inflow as TBM advances at v Q = Av Formation Foam, additives are injected to the chamber QAir + QSol + QAdt Muck discharged via screw conveyor, regulated by its speed ω s Q =ηahω Outflow s s 4
5 Model Physics 1. Compressible material flow Horizontally-oriented pressure gauges σ x = K σ + u ' z Lateral EP coefficient Effective stress K =1, assumed for mixed muck e > e max σ ' x = σ ' z 0 e < e max Assume soil behaves as NC with C c Pore pressure For granular soils, matric suction is neglected Gas is modeled as ideal gas u V = n RT g g g u = u = u g l 5
6 Model Physics 2. Fluid seepage The chamber is connected to ground via openings, and fluid can seep away to the ground under the hydraulic gradient Assumption Muck permeability is lower than the ground Only liquid can seep from the chamber - NOT the air bubbles Laminar, quasi-static flow Velocity of liquid escaping the chamber at cutterhead face (Bezuijen,2002) ku ( chamber ugeo ) vseepage = φrγ w u u gap u chamber Seepage reduce the liquid volume V l, the gas volume V g expand to compensate u geo Formation soil (b) Chamber 6
7 Model Physics 3. Rotation induced unlevel muck surface Pressure gauge As cutterhead rotates, pressure on the upflow side is observed to be greater than the downflow side Pedestal One hypothesis Muck level on the upflow side is higher due to pedestal rotation θ Assuming Estimating muck tilting angle using a linear relationship with cutterhead rotation speed ω The pressure difference are #6 #5 #4 y z #1 #2 #3 Upflow Downflow 7
8 Model Implementation Model is organized in a state machine architecture Model outputs t Yt ( ) = p, p,... p State variables { } t { Vg Vl ng} St () =,, Operation inputs t Xt () = { v, ωω, s, Qair, Qsol, Qadt} Model parameters Permeability: k Buried depth, water head: H, H w Formation soil properties: G s, ϕ, e max GDR Surface tilting coefficient: β Initial state variable {V g,v l,n g } Screw conveyor efficiency coefficient: η Fitted Y(t-Δt) Y(t) Y(t+Δt) S(t-Δt) S(t) S(t+Δt) X(t-Δt) X(t) X(t+Δt) Time step Δt is set small enough to ensure numerical stability 8
9 Model Implementation Demonstration using data of N125 project, Seattle 3.5 miles twin tunnel bored using a 6.5 m, EPB TBM Three rings are chosen Ring H(m) Hw (m) Ring #1310 Ring #1201 Ring #1125 Geology Cohesionless sand & gravel Dense, compacted kh m/s, kv m/s Porosity ϕ = 0.3 Water content, w=16% Unit weight, γ= 20.4 kn/m3 Friction angle, θ=39 9
10 Model implementation Demonstration using data of N125 project, Seattle The recorded operations are used as model inputs The model output is then compared to the recorded pressure Ring
11 Model implementation Demonstration using data of N125 project, Seattle Ring
12 Model implementation Demonstration using data of N125 project, Seattle Ring
13 Model implementation Demonstration using data of N125 project, Seattle Since {V g,v l,n g } are modeled, some extra information is available (Ring 1125) Muck volumes During excavation: phase volume stays fairly constant In standstill, liquid volume V l decreases due to seepage, V g increases for compensation Degree of saturation S r, void ratio e Muck becomes dryer over standstill period Void ratio only changes during excavation 13
14 Conclusions The model captures the chamber fluctuation reasonably well Responds correctly with material flow Can reproduce pressure dissipation during standstill Physics-based: interpretable and scalable Can run in real-time: Making some applications possible, e.g., TBM simulator, expert system Limited to granular soil; does not function well in clayey ground Operational delay is currently not considered (influence of x direction) Certain operations take time to act (e.g. Soil conditioning) 14
15 Acknowledgement We would like to express our gratitude towards Jay Dee Contractors, Inc. for sharing project data and knowledge from people on the project Thank You.
Copyright by Lisa Mori All Rights Reserved
ADVANCING UNDERSTANDING OF THE RELATIONSHIP BETWEEN SOIL CONDITIONING AND EARTH PRESSURE BALANCE TUNNEL BORING MACHINE CHAMBER AND SHIELD ANNULUS BEHAVIOR by Lisa Mori Copyright by Lisa Mori 2016 All Rights
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