Evaluating atomic mobility and interdiffusivity based on two-dimensional diffusion simulations and diffusion triple experiments

Yang

Mathematical Problems in Engineering

et al. 2022

In order to effectively control the ground deformation and ground subsidence during subway construction, three-dimensional numerical simulation of soil deformation during shield tunnel construction is proposed. Based on a subway tunnel project, this essay firstly divides the shield construction process into several stages and analyzes the vertical displacement of soil in each stage. FLAC 3D was used for three-dimensional finite difference numerical simulation. By comparing the numerical simulation results with the field measured data, the soil settlement caused by shield tunnel excavation is studied deeply. The simulation results show that the maximum settlement value of the monitoring data is 0.59 mm, and the maximum settlement value of the numerical simulation is 0.82 mm, with a difference of 0.23 mm. The maximum value of uplift on both sides of the tunnel is 0.41 mm in monitoring data and 0.29 in numerical simulation, with a difference of 0.12 mm. The maximum settlement value of monitoring data is 2.59 mm, and the maximum settlement value of numerical simulation is 3.05 mm, with a difference of 0.46 mm. The maximum value of uplift on both sides of the tunnel is 0.32 mm in monitoring data and 1.89 mm in numerical simulation, with a difference of 1.57 mm. The settlement value of numerical simulation is slightly larger than that of monitoring data. Conclusion. The simulation can well simulate the state of soil uplift on both sides, and the width of settlement groove is in good agreement with the monitoring data.

Section: Discussionmentioning

confidence: 61%

Section: Literature Reviewmentioning

confidence: 99%

Three-Dimensional Numerical Simulation of Soil Deformation during Shield Tunnel Construction

Yang

Mathematical Problems in Engineering

et al. 2022

Materials Genome Engineering Advances

“…High‐throughput experimental techniques, such as diffusion multiples and combinatorial materials chip, have been developed to efficiently explore materials properties, benefiting from their concentration and diffusional flux distributions in at least two directions or dimensions (2D) and therefore providing much more information than the 1D property distribution. To face this fact, a 2D diffusion simulation code has been developed based on thermodynamic modeling and full diffusivity matrix descriptions of multi‐component alloys, [31,32] taking advantages of one more dimension.…”

Section: Methodsmentioning

confidence: 99%

Design of advanced steels by integrated computational materials engineering

Lu,

He,

Zheng

2024

The integrated computational materials engineering (ICME) has achieved great success in accelerating the rational design and deployment of new materials. It is a new route of designing new materials and processes and highlighted by Materials Genome Initiative/Engineering that stresses the high‐throughput computation in addition to high‐throughput experimentation and materials informatics. This article presents a brief review on the basic theories and multi‐scale computational tools of ICME to design advanced steel grades, including the first‐principles calculations, the CALPHAD method (i.e., computational thermodynamics) fueled by dedicated databases, diffusion and phase‐field simulations, as well as finite analysis methods and machine learning. In the ICME scheme to deal with steels, the CALPHAD method is considered as the core to readily consider multi‐component systems and integrated to link the microscopic simulations (such as diffusion and phase field method to predict microstructure evolutions in response to external conditions) and macroscopic finite analysis method to deal with mechanical properties. Two applications are also presented to address the new routes to carry out materials design, especially for advanced steels.

J. Phase Equilib. Diffus.

“…However, estimation of diffusion parameters becomes exponentially more complicated with an increasing number of elements for a given system. An adapted methodology has been proposed to extract the interdiffusion coefficients for high order systems [29,30] . However, it requires careful preparation and choice of diffusion multiples.…”

Section: Inter-diffusion In Heasmentioning

confidence: 99%

“…Finally, repeating ternary junctions can be useful to deduce (inter-)diffusion coefficients. [28][29][30] Beside thermodynamic stability, the adjustment of the constitutive phases also plays an important role on the resulting mechanical behaviour. BCC phase is generally a stronger but less ductile phase while FCC phase is generally softer but more ductile.…”

Section: Introductionmentioning

confidence: 99%

Diffusion Multiples as a Tool to Efficiently Explore the Composition Space of High Entropy Alloys

Hilhorst

Jacques

2021

The concept of high entropy alloys (HEAs) has already provided specific alloys presenting improved structural and functional properties. However, the discovery and development of new HEAs still represent a big challenge due to their chemical complexity. Diffusion multiples can be used as an experimental approach to screen large composition ranges. The method consists in heat-treating intimately bonded metallic blocks to activate diffusion, thus creating gradients of compositions. Local chemical and physical properties can be directly probed using advanced characterization techniques. The measured characteristics and properties can be further analysed to estimate diffusion properties or mechanical properties. In the present study, four different diffusion multiples related to the Cantor alloy system, Cr-Fe-Mn-Co-Ni, were investigated. Resulting microstructures were investigated after several heat treatments to assess the claimed entropy-based stabilization of a single phase. Crystallographic characterization by EBSD coupled to EDX mapping were compared to Calphad predictions. Local nano-indentation mapping was carried out and compared to the prediction of the yield strength model proposed by Walbru ¨hl et al.