Inverse solution to heat transfer coefficient during heat assembly of aluminum alloy drill pipes

Sun, Youhong; Лиу, Баочанг; Ding, Dali; Meng, Qingnan

doi:10.1177/1687814017714970

Cited by 6 publications

(3 citation statements)

References 21 publications

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“…Some researchers have also reported results on conductivity. For example, Sun et al [11] mentioned the change in specific heat and thermal conductivity between room temperature and 400°C of 7075T6 Al alloy used as a drill pipe. However, further information on the thermal properties of this alloy was not discussed.…”

Section: Introductionmentioning

confidence: 99%

Changes in thermal properties of 7075 aluminium alloy by aging heat treatment

Kim

Kang

et al. 2023

Materials Science and Technology

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This study investigated the effects of aging heat treatment on the change of thermal properties of 7075 Al alloy using differential scanning calorimetry and a laser flash apparatus. The thermal diffusivity showed different trends in the three temperature ranges: In the range from room temperature to 160°C, the thermal diffusivity increased with increasing temperature. Between 160 and 240°C, the thermal diffusivity increased with an increase in the temperature of the specimen. Precipitation was completed at 240°C or higher, and the thermal diffusivity decreased with an increase in the temperature of the specimen. The amount of precipitation of η′ and η phases did not affect the change in thermal diffusivity but only contributed to the improvement of micro-hardness.

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Section: Introductionmentioning

confidence: 99%

Changes in thermal properties of 7075 aluminium alloy by aging heat treatment

Kim

Kang

et al. 2023

Materials Science and Technology

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“…Aluminum alloy drill pipes are popular due to their lightweight, good corrosion resistance, low bending stress, and non-magnetic properties [1][2][3]. However, the low hardness of the aluminum alloy drill pipe and the inevitable spiral bending downhole result in significant wear between the pipe and the wellbore and casing, leading to a reduced lifespan for the aluminum alloy drill pipe [4][5][6]. So, the demand for improving the wear resistance of aluminum alloy drill pipes has become urgent.…”

Section: Introductionmentioning

confidence: 99%

Wear Resistance Study of Bionic Pitted Ni Cladding Layer on 7075 Aluminum Alloy Drill Pipe Surface

Li,

Gao,

Zhao

et al. 2023

Coatings

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To enhance the lifespan of drill pipes and minimize wear, this study introduces a bionic structure model inspired by the pit shape structure found in the dung beetle’s abdomen. The stress distribution and wear of bionic pitted structure and ordinary structure are simulated by finite element software. The findings revealed that the bionic structure significantly improves stress distribution, resulting in an impressive 81.3% increase in lifespan. Subsequently, the surface of the 7075 aluminum drill pipe was coated with Ni powder by a laser cladding system. Wear tests were conducted to analyze the wear and surface damage behavior of the cladding layer. The microstructure, composition, and microhardness of the cladding layer were measured and observed. The results showed that the cladding layer was mainly composed of Al3Ni2 and had high hardness. Additionally, a transition region exists between the cladding layer and the substrate, comprising relatively low hardness Al, thereby enhancing the drill pipe’s ability to withstand alternating loads. Furthermore, the bionic structure possesses the capability to store particles, effectively reducing the occurrence of abrasive wear and increasing the lifespan by 70.0%.

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“…The fatigue strength of the connection was improved by optimizing the thread. Sun, Y [2][3][4] used a finite element program and inverse heat conduction model to identify the heat transfer coefficient during thermal assembly in line with the experimental data and then obtained the correlation curve between cooling water flow and the convective heat transfer coefficient. Belkacem [5] studied the connection between ST 2024 aluminum alloy drill pipe and steel drill pipe in a curved hole trajectory.…”

Section: Introductionmentioning

confidence: 99%

Prediction of the Deformation of Aluminum Alloy Drill Pipes in Thermal Assembly Based on a BP Neural Network

et al. 2022

Self Cite

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The connection between the steel joint and aluminum alloy pipe is the weak part of the aluminum alloy drill pipe. Practically, the interference connection between the aluminum alloy rod and the steel joint is usually realized by thermal assembly. In this paper, the relationship between the cooling water flow rate, initial heating temperature and the thermal deformation of the steel joint in interference thermal assembly was studied and predicted. Firstly, the temperature data of each measuring point of the steel joint were obtained by a thermal assembly experiment. Based on the theory of thermoelasticity, the analytical solution of the thermal deformation of the steel joint was studied. The temperature function was fitted by the least square method, and the calculated value of radial thermal deformation of the section was finally obtained. Based on the BP neural network algorithm, the thermal deformation of steel joint section was predicted. Besides, a prediction model was established, which was about the relationship between cooling water flow rate, initial heating temperature and interference. The magnitude of interference fit of steel joint was predicted. The magnitude of the interference fit of the steel joint was predicted. A polynomial model, exponential model and Gaussian model were adopted to predict the sectional deformation so as to compare and analyze the predictive performance of a BP neural network, among which the polynomial model was used to predict the magnitude of the interference fit. Through a comparative analysis of the fitting residual (RE) and sum of squares of the error (SSE), it can be known that a BP neural network has good prediction accuracy. The predicted results showed that the error of the prediction model increases with the increase of the heating temperature in the prediction model of the steel node interference and related factors. When the cooling water velocity hit 0.038 m/s, the prediction accuracy was the highest. The prediction error increases with the increase or decrease of the velocity. Especially when the velocity increases, the trend of error increasing became more obvious. The analysis shows that this method has better prediction accuracy.

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Inverse solution to heat transfer coefficient during heat assembly of aluminum alloy drill pipes

Cited by 6 publications

References 21 publications

Changes in thermal properties of 7075 aluminium alloy by aging heat treatment

Changes in thermal properties of 7075 aluminium alloy by aging heat treatment

Wear Resistance Study of Bionic Pitted Ni Cladding Layer on 7075 Aluminum Alloy Drill Pipe Surface

Prediction of the Deformation of Aluminum Alloy Drill Pipes in Thermal Assembly Based on a BP Neural Network

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