A physically based numerical model to predict the microstructure evolution and yield strength of high Cu-to-Mg mass ratio Al-Cu-Mg-Ag alloys during the whole ageing process was developed.A thermodynamically-based prec...A physically based numerical model to predict the microstructure evolution and yield strength of high Cu-to-Mg mass ratio Al-Cu-Mg-Ag alloys during the whole ageing process was developed.A thermodynamically-based precipitation model,employing the classical nucleation and growth theories,was adapted to deal with the precipitation kinetics (evolution of radius and volume fraction of precipitates for Ω phase) of aged Al-Cu-Mg-Ag alloys.The model gives an estimation of the precipitation kinetics (evolution of radius and density of precipitates for both θ' and Ω phases) of the alloy.The strengthening model based on Orowan mechanism was deduced.The microstructural development and strength predictions of the model are generally in good agreement with the experimental data.展开更多
Solid solution strengthening(SSS)is one of the main contributions to the desired tensile properties of nickel-based superalloys for turbine blades and disks.The value of SSS can be calculated by using Fleischer’s and...Solid solution strengthening(SSS)is one of the main contributions to the desired tensile properties of nickel-based superalloys for turbine blades and disks.The value of SSS can be calculated by using Fleischer’s and Labusch’s theories,while the model parameters are incorporated without fitting to experimental data of complex alloys.In thiswork,four diffusionmultiples consisting of multicomponent alloys and pure Niare prepared and characterized.The composition and microhardness of singleγphase regions in samples are used to quantify the SSS.Then,Fleischer’s and Labusch’s theories are examined based on high-throughput experiments,respectively.The fitted solid solution coefficients are obtained based on Labusch’s theory and experimental data,indicating higher accuracy.Furthermore,six machine learning algorithms are established,providing a more accurate prediction compared with traditional physical models and fitted physical models.The results show that the coupling of highthroughput experiments and machine learning has great potential in the field of performance prediction and alloy design.展开更多
Determining the width of an induced hydraulic fracture is the first step for applying wellbore strengthening and hydraulic fracturing techniques. However, current 2-D analytical solutions obtained from the plane strai...Determining the width of an induced hydraulic fracture is the first step for applying wellbore strengthening and hydraulic fracturing techniques. However, current 2-D analytical solutions obtained from the plane strain assumption may have large uncertainties when the fracture height is small. To solve this problem, a 3-D finite element method(FEM) is used to model wellbore strengthening and calculate the fracture width. Comparisons show that the 2-D plane strain solution is the asymptote of the 3-D FEM solution. Therefore, the 2-D solution may overestimate the fracture width. This indicates that the2-D solution may not be applicable in 3-D conditions. Based on the FEM modeling, a new 3-D semi-analytical solution for determining the fracture width is proposed, which accounts for the e ects of 3-D fracture dimensions, stress anisotropy and borehole inclination. Compared to the 2-D solution, this new 3-D semi-analytical solution predicts a smaller fracture width.This implies that the 2-D-based old design for wellbore strengthening may overestimate the fracture width, which can be reduced using the proposed 3-D solution. It also allows an easy way to calculate the fracture width in complex geometrical and geological conditions. This solution has been verified against 3-D finite element calculations for field applications.展开更多
基金Project(2005CB623705-04) supported by the National Basic Research Program of ChinaProject(1810-752300020) supported by Central South University and Ministry of Education of China for the Domestic Exchange PhD student
文摘A physically based numerical model to predict the microstructure evolution and yield strength of high Cu-to-Mg mass ratio Al-Cu-Mg-Ag alloys during the whole ageing process was developed.A thermodynamically-based precipitation model,employing the classical nucleation and growth theories,was adapted to deal with the precipitation kinetics (evolution of radius and volume fraction of precipitates for Ω phase) of aged Al-Cu-Mg-Ag alloys.The model gives an estimation of the precipitation kinetics (evolution of radius and density of precipitates for both θ' and Ω phases) of the alloy.The strengthening model based on Orowan mechanism was deduced.The microstructural development and strength predictions of the model are generally in good agreement with the experimental data.
基金supported by National Science and Technology Major Project (J2019-IV-0003-0070)the Natural Science Foundation of China (91860105,52074366)+4 种基金China Postdoctoral Science Foundation (2019M662799)Natural Science Foundation of Hunan Province of China (2021JJ40757)the Science and Technology Innovation Program of Hunan Province (2021RC3131)Changsha Municipal Natural Science Foundation (kq2014126)Project Supported by State Key Laboratory of Powder Metallurgy,Central South University,Changsha,China.
文摘Solid solution strengthening(SSS)is one of the main contributions to the desired tensile properties of nickel-based superalloys for turbine blades and disks.The value of SSS can be calculated by using Fleischer’s and Labusch’s theories,while the model parameters are incorporated without fitting to experimental data of complex alloys.In thiswork,four diffusionmultiples consisting of multicomponent alloys and pure Niare prepared and characterized.The composition and microhardness of singleγphase regions in samples are used to quantify the SSS.Then,Fleischer’s and Labusch’s theories are examined based on high-throughput experiments,respectively.The fitted solid solution coefficients are obtained based on Labusch’s theory and experimental data,indicating higher accuracy.Furthermore,six machine learning algorithms are established,providing a more accurate prediction compared with traditional physical models and fitted physical models.The results show that the coupling of highthroughput experiments and machine learning has great potential in the field of performance prediction and alloy design.
基金the financial support from the Fundamental Research Program of Shanxi Province,China(No.202203021211130)the National Natural Science Foundation of China(Nos.51801132,52075359)。
基金partially supported by National Key R&D Program of China (2017YFC0804108) during the 13th Five-Year Plan PeriodNational Science Foundation of China (51774136)+1 种基金Natural Science Foundation of Hebei Province of China (D2017508099)the Program for Innovative Research Team in the University sponsored by Ministry of Education of China (IRT-17R37)
文摘Determining the width of an induced hydraulic fracture is the first step for applying wellbore strengthening and hydraulic fracturing techniques. However, current 2-D analytical solutions obtained from the plane strain assumption may have large uncertainties when the fracture height is small. To solve this problem, a 3-D finite element method(FEM) is used to model wellbore strengthening and calculate the fracture width. Comparisons show that the 2-D plane strain solution is the asymptote of the 3-D FEM solution. Therefore, the 2-D solution may overestimate the fracture width. This indicates that the2-D solution may not be applicable in 3-D conditions. Based on the FEM modeling, a new 3-D semi-analytical solution for determining the fracture width is proposed, which accounts for the e ects of 3-D fracture dimensions, stress anisotropy and borehole inclination. Compared to the 2-D solution, this new 3-D semi-analytical solution predicts a smaller fracture width.This implies that the 2-D-based old design for wellbore strengthening may overestimate the fracture width, which can be reduced using the proposed 3-D solution. It also allows an easy way to calculate the fracture width in complex geometrical and geological conditions. This solution has been verified against 3-D finite element calculations for field applications.
