Modeling of workpiece temperature suppression in high-speed dry milling of UD-CF/PEEK considering heat partition and jet heat transfer

doi:10.1007/s11465-024-0801-7

2024, Vol. 19

Issue (5) : 30 https://doi.org/10.1007/s11465-024-0801-7

Modeling of workpiece temperature suppression in high-speed dry milling of UD-CF/PEEK considering heat partition and jet heat transfer

Lei LIU^1,², Da QU³, Jin ZHANG^1,², Huajun CAO^1,²(

), Guibao TAO^1,², Chenjie DENG^1,²

¹. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
². State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China
³. College of Mechanical Engineering, Chongqing University of Technology, Chongqing 400054, China

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Abstract

High-performance carbon fiber-reinforced polyether-ether-ketone (CF/PEEK) has been gradually applied in aerospace and automobile applications because of its high strength-to-weight ratio and impact resistance. The dry-machining requirement tends to cause the cutting temperature to surpass the glass transition temperature (T_g), leading to poor surface quality, which is the bottleneck for dry milling of CF/PEEK. Temperature suppression has become an important breakthrough in the feasibility of high-speed dry (HSD) milling of CF/PEEK. However, heat partitioning and jet heat transfer mechanisms pose strong challenges for temperature suppression analytical modeling. To address this gap, an innovative temperature suppression analytical model based on heat partitioning and jet heat transfer mechanisms is first developed for suppressing workpiece temperature via the first-time implementation of an air jet cooling process in the HSD milling of UD-CF/PEEK. Then, verification experiments of the HSD milling of UD-CF/PEEK with four fiber orientations are performed for dry and air jet cooling conditions. The chip morphologies are characterized to reveal the formation mechanism and heat-carrying capacity of the chip. The milling force model can obtain the force coefficients and the total cutting heat. The workpiece temperature increase model is validated to elucidate the machined surface temperature evolution and heat partition characteristics. On this basis, an analytical model is verified to predict the workpiece temperature of air jet cooling HSD milled with UD-CF/PEEK with a prediction accuracy greater than 90%. Compared with those under dry conditions, the machined surface temperatures for the four fiber orientations decreased by 30%–50% and were suppressed within the T_g range under air jet cooling conditions, resulting in better surface quality. This work describes a feasible process for the HSD milling of CF/PEEK.

Keywords thermoplastic CF/PEEK high-speed dry milling chip formation heat partition jet heat transfer temperature suppression

Corresponding Author(s): Huajun CAO

Issue Date: 29 October 2024

Cite this article:

Lei LIU,Da QU,Jin ZHANG, et al. Modeling of workpiece temperature suppression in high-speed dry milling of UD-CF/PEEK considering heat partition and jet heat transfer[J]. Front. Mech. Eng., 2024, 19(5): 30.

URL:

https://academic.hep.com.cn/fme/EN/10.1007/s11465-024-0801-7
https://academic.hep.com.cn/fme/EN/Y2024/V19/I5/30

Fig.1 Analysis of chips and heat partition during UD-CF/PEEK HSD milling: (a) formed chips and (b) heat partitions under dry and air jet cooling conditions. PCD: polycrystalline diamond.

Fig.2 Cutting force analysis for UD-CF/PEEK HSD milling. PCD: polycrystalline diamond.

Fig.3 Heat source analysis for UD-CF/PEEK HSD milling: (a) tool-workpiece position relationship and (b) superposition of the workpiece heat source.

Fig.4 Calculation flow of the temperature suppression model in the HSD milling of CF/PEEK via air jet cooling.

Tab.1 Milling conditions for UD-CF/PEEK dry milling

Tab.2 Air parameters for air jet cooling conditions

Tab.3 Performance parameters of the UD-CF/PEEK workpiece [31]

Fig.5 Experimental methods for HSD milling of UD-CF/PEEK under dry and air jet cooling conditions: (a) experimental site, (b) cutting zone setup, (c) thermocouple measurement method, and (d) air jet method. PCD: polycrystalline diamond.

Fig.6 Chip macromorphology for the dry milling of UD-CF/PEEK by using different cutting parameters: (a1–a4) v_c = 250 m/min and f_z = 0.07 mm/z, (b1–b4) v_c = 1500 m/min and f_z = 0.07 mm/z, and (c1–c4) v_c = 250 m/min and f_z = 0.07 mm/z.

Fig.7 Chip morphological characteristics for different fiber orientations (v_c = 1500 m/min, f_z = 0.07 mm/z): (a) 0° fiber orientation, (b) 45° fiber orientation, (c) 90° fiber orientation, and (d) 135° fiber orientation.

Fig.8 Chip micromorphology for different fiber orientations in the HSD milling of UD-CF/PEEK (v_c = 1500 m/min, f_z = 0.07 mm/z): (a) 0° fiber orientation, (b) 45° fiber orientation, (c) 90° fiber orientation, and (d) 135° fiber orientation.

Fig.9 Measured and predicted forces for the effective cutting cycle (θ = 135°, v_c = 1500 m/min, f_z = 0.12 mm/z): (a) x-axis cutting force F_x and (b) y-axis cutting force F_y.

Fig.10 Force coefficients of UD-CF/PEEK HSD milling: (a) tangential force coefficient K_tc and (b) radial tangential force coefficient K_rc.

No.	v_c/(m?min⁻¹)	f_z/(mm?z⁻¹)	θ/(° )	d_m/mm	$T max m$ /°C	$T max p$ /°C	E_RMS/°C	E_p/%
1	250	0.07	0	0.175	117	113	1.93	1.98
2	250	0.07	45	0.191	172	176	7.88	5.18
3	250	0.07	90	0.202	134	133	6.57	5.75
4	250	0.07	135	0.184	105	108	4.29	5.04
5	1000	0.07	0	0.180	138	128	2.74	2.33
6	1000	0.07	45	0.216	214	224	3.63	1.87
7	1000	0.07	90	0.214	187	179	4.25	2.56
8	1000	0.07	135	0.192	142	135	2.17	1.79
9	1500	0.07	0	0.243	89	83	1.60	2.32
10	1500	0.07	45	0.247	168	165	3.93	2.66
11	1500	0.07	90	0.172	142	133	1.83	1.51
12	1500	0.07	135	0.211	95	97	2.02	2.69
13	1500	0.12	0	0.195	64	61	1.01	2.32
14	1500	0.12	45	0.242	118	119	2.12	2.15
15	1500	0.12	90	0.281	106	112	1.71	1.98
16	1500	0.12	135	0.157	94	92	1.39	1.88

Tab.4 Measured and predicted temperatures under dry conditions

Fig.11 Workpiece temperature for UD-CF/PEEK dry milling: (a) temperature increase curves for different d_m values (in the No. 10 experiment) and (b) maximum machined surface temperature

T max surf

at d_m = 0 mm.

Fig.12 Heat partition analysis for UD-CF/PEEK HSD milling: (a) total cutting heat Q_total, (b) workpiece carrying heat Q_CF/PEEK, (c) chips carrying heat Q_chip, and (d) heat partition ratio.

No.	v_c/(m?min⁻¹)	f_z/(mm?z⁻¹)	θ/(° )	d_m/mm	$T max m$ /°C	$T max p$ /°C	E_RMS/°C	E_p/%	$T max surf$ /°C
17	1500	0.07	0	0.186	49	48	1.77	6.140	66
18	1500	0.07	45	0.182	108	111	2.06	2.350	133
19	1500	0.07	90	0.249	91	93	3.51	4.950	110
20	1500	0.07	135	0.295	57	54	1.74	4.756	67

Tab.5 Measured and predicted temperatures under air jet cooling conditions

Fig.13 Workpiece temperature analysis for air jet cooling HSD milling: (a) heat partition ratio on the workpiece and (b) machined surface temperatures

T max surf

(in experiments Nos. 9–12 and Nos. 17–20).

Fig.14 Machined surface topography and roughness for different fiber orientations: (a1–a4) dry condition, (b1–b4) air jet cooling condition, and (c) three-dimensional surface roughness S_a (v_c = 1500 m/min, f_z = 0.07 mm/z).

Abbreviations
CF	Carbon fiber-reinforced
CFRP	Carbon fiber-reinforced polymer composite
CFRTP	Carbon fiber-reinforced thermoplastic
HSD	High-speed dry
PEEK	Polyether-ether-ketone
PEKK	Polyether-ketone-ketone
UD	Uni-directional
Variables
a₃	Thermal diffusivity for the Z-axis
a_e	Cutting width
a_p	Cutting depth
C^K	Fletcher-Reeves conjugate coefficient
c	Specific heat capacity of the CF/PEEK
$c ¯$	Average specific heat capacity
c_air	Air specific heat at constant pressure
d^K	Conjugate gradient descent
d_m	Temperature measurement width
E_RMS	Root mean square error
E_p	Percentage error
F_r, F_t, F_x, F_y	Cutting force
f (q_max)	Objective function of the parameter q_max
f_z	Feed per tooth
$∇ f (q max K)$	Gradient direction
g(ϕ_j)	Discrimination coefficient of the jth cutter
h(ϕ)	Uncut chip thickness
h	Average cutting thickness
h_air	Jet-air convective coefficient
I	Total amount of measured temperatures
j	Serial number of tool cutter
K	Total amount of iterations
K_tc, K_rc, K_te, K_re	Cutting force coefficients
k₁, k₂, k₃	Dominant thermal conductivities corresponding to the X-axis, Y-axis, and Z-axis of workpiece coordinate system OXYZ
k_air	Air thermal conductivity
k_v, k_p	Thermal conductivity coefficients vertical and parallel to fiber orientation
l	heat transfer width of cutting zone
l_c	Arc length in workpiece heat source
Nu	Nusslt number
Pr	Prandtl number
Q_chip, Q_CF/PEEK, Q_tool	Heats transmitted to the chip, workpiece and cutting tool
$Q CF/PEEK res$ , Q_air	Carrying heats of the workpiece and air in air jet cooling
Q_total	Total cutting heat
q(ϕ)	Heat flux
q_avg	Average heat flux
q_max	Maximum heat flux
W	Total mechanical work
R	Tool radius
$R CF/PEEK res,t$	Ratio of workpiece carrying heat to total cutting heat in air jet cooling
R_tool, R_CF/PEEK, R_chip	Heat partitions of the cutting tool, workpiece and chip
Re	Reynolds number
S^K	Search step
T_a	Environmental temperature
T_g	Glass transition temperature
$T i m$	ith temperature in measured temperature sequence
$T max m$	Maximum measured temperature
$T max p$	Maximum predicted temperature
$T max surf$	Maximum temperature of machined surface
$Δ T i e$	Estimated temperature rise
t	Observation time for the temperature rise
t_f	Single-tooth cutting duration
Δt	Effective cutting duration
v_air	Air velocity
v_c	Cutting speed
v_f	Feed rate
τ	Time to start releasing heat
α	Coordinate rotation angle
ρ	Mass density of the CF/PEEK
ρ_air	Air density
μ_air	Air dynamic viscosity
θ	Fiber orientation
ϕ	Instantaneous contact angle
ϕ_c	Maximum contact angle

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