Topology Optimization of an Actively Cooled Electronics Section for Downhole Tools

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Topology Optimization of an Actively Cooled Electronics Section for Downhole Tools S. Soprani*, J. H. K. Haertel, B. S. Lazarov, O. Sigmund, K. Engelbrecht

Table of contents Introduction Method and COMSOL model Analysis of the results Choice of the final design Conclusions 2 2715 November October 2014

Introduction Topology Optimization: mathematical approach that optimizes the material layout within a given design space and boundary conditions. 3 2715 November October 2014

Introduction Downhole Tool: cylindrical robotic tool used to increase or restore the production of oil and gas wells (well cleaning, pipe cutting, installation of valves). I feed Q TEC - Thermoelectric (Peltier) cooler: upgrade the maximum operating temperature from 175 C to 200 C. 4 2715 November October 2014

Problem formulation Metallic housing (o.d. 80mm) Optimizable chassis TEC Heat spreader + soft thermal pad Design Criteria: Use aluminum to enhance Axial thesection cooler s of heat the downhole rejection tool s the implemented well. geometry. Structural chassis (o.d. 60mm) T-sensitive electronics (PCB) Use thermal insulation to protect the cooled electronics. Optimize the distribution of aluminum-thermal insulation within the chassis Minimize the average PCB temperature 5 2715 November October 2014

Governing equations Heat conduction k T = Q source (1) Modified heat conduction JST k T = Q JouleHeating (2) Convective heat flux (T fluid, h) TEC feed current I feed Boundary conditions Thermal insulation Thermal (contact) resistance Heat source (1 W) 6 2715 November October 2014

Topology Optimization Implementation (SIMP method) minimize: f obj T, ρ design = 1 A PCB Ω PCB T dω PCB (3) constraints: 0 ρ design 1 (4) ρ design Density filter f(r) ρ Projection function p(η,β) ρ interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 7 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) p(η,β = 1) p(η,β = 8) I feed = 4 A h = 50 Wm -2 K -1 8 2715 November October 2014

Simulation results T fluid = 200 C h = 25, 50, 100, 500 Wm -2 K -1 I feed = 1, 2, 3, 4 A ρ optimized distribution I feed = 2 A h = 100 Wm -2 K -1 ρ optimized distribution I feed = 4 A h = 50 Wm -2 K -1 Aluminum Insulator Design 1 Design 2 Low I feed / High h High I feed / Low h Aluminum pad length grows with I feed and decreases with h. Aluminum layer thickness grows with I feed and decreases with h. 9 2715 November October 2014

Choice of the final design Axial section of the finally chosen design. h (Wm -2 K -1 ) Opt - 1A T PCB ( C) Design - 1A T PCB ( C) ΔT (K) 25 182.31 181.95 0.10 50 179.32 178.97 0.11 100 177.83 177.47 0.11 500 176.56 176.21 0.11 h (Wm -2 K -1 ) Opt - 2A T PCB ( C) Design - 2A T PCB ( C) ΔT (K) 25 175.63 175.68 0.05 50 168.18 168.23 0.05 100 164.54 164.57 0.04 500 161.46 161.48 0.03 h (Wm -2 K -1 ) Opt - 3A T PCB ( C) Design - 3A T PCB ( C) ΔT (K) 25 188.22 188.93 0.71 50 171.48 171.87 0.39 100 163.68 163.90 0.22 500 157.12 157.35 0.23 h (Wm -2 K -1 ) Opt - 4A T PCB ( C) Design - 4A T PCB ( C) ΔT (K) 25 228.62 233.59 4.97 50 192.79 195.71 2.92 100 177.25 179.29 2.04 500 165.23 166.37 1.14 ΔT = T PCB,design - T PCB,Opt 10 2715 November October 2014

Conclusions The topology optimization (SIMP) approach supported the development of a chassis for actively cooled downhole electronics. Two main design concepts were found and analyzed. A parametric study evaluated the sensitivity of the optimized topologies to the boundary conditions. The final design was defined according to the optimization results and proved to perform very closely to the optimized systems. 11 2715 November October 2014

Thank you for the attention 12 2715 November October 2014

Extra slides 13 2715 November October 2014

COMSOL Multiphysics representation of the longitudinal section of the downhole tool (left side) and particular of the TEC device with the two plates and the semiconducting material layer highlighted in blue (right side). 14 2715 November October 2014

Governing equations Heat conduction k T = Q source (1) Modified heat conduction JST k T = Q JouleHeating (2) Convective heat flux (T fluid, h) TEC feed current I feed Boundary conditions Thermal insulation Thermal (contact) resistance Heat source (1 W) 15 2715 November October 2014

Cross-Check analysis Evaluate the performance of the optimized designs at different boundary conditions The optimization process is negligibly sensitive to the well fluid convection regime, at a given I feed. The TEC feed current influences significantly the optimized design. But we can control it! An optimal feed current I feed,opt was found. I feed,opt varies with h and ranges between 2 and 3 A. 16 2715 November October 2014

R vs. well fluid convective coefficient, for different TEC feed currents. Different symbols refer to the different optimized design concepts. = Design 1, = Design 2. HTS electronics temperature vs. well fluid convective coefficient for four different systems, optimized for I feed = 2 A and h = 25, 50, 100 and 500 Wm -2 K -1. 17 2715 November October 2014

HTS electronics temperature vs. TEC feed current for four different systems, optimized for I feed h = 25 Wm -2 K -1 (left side) and 50 Wm -2 K -1 (right side). = 1, 2, 3 and 4 A, and 18 2715 November October 2014

Characteristic curve of the finally designed electronics unit. The plot reports the performance of the cooling system as HTS electronics temperature vs. Convective coefficient and TEC feed current. The minimum HTS electronics temperatures for each operating condition are highlighted with a red line. 19 2715 November October 2014

J = NI feed A tot = NI feed A tot NA leg = I feed A BiTe = J x NA leg A leg A BiTe tot J S = J S S = S x BiTe k A air A BiTe = k air + k A BiTe = k tot A air (1 x BiTe ) + k BiTe x BiTe tot σ = σ BiTe x BiTe + σ air x air = σ BiTe x BiTe (Gordon 2002) 20 2715 November October 2014

Topology Optimization Implementation (SIMP method) minimize: f obj T, ρ design = 1 A PCB Ω PCB T dω PCB (3) constraints: 0 ρ design 1 (4) r T, ρ design = 0 (5) density filter: r 2 2 ρ + ρ = ρ design (Lazarov 2011) (6) projection function: ρ i = tanh βη +tanh(β( ρ i η) tanh βη +tanh β 1 η (Wang 2011) (7) interpolation function: k SIMP = k ins + k Al k ins ρ p (8) 21 2715 November October 2014

Topology Optimization Implementation (SIMP method) projection function: ρ i = tanh βη +tanh(β( ρ i η) tanh βη +tanh β 1 η (Wang 2011) (7) 22 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 23 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 24 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 25 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 26 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 27 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 28 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 29 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) 30 2715 November October 2014

Simulation results interpolation function: k SIMP = k ins + k Al k ins ρ p (5) p(η,β = 1) p(η,β = 8) 31 2715 November October 2014