Flow-state backfill material and matching ratio design method and system thereof based on coupling simulation

Abstract

The invention discloses a flow-state backfill material and a matching ratio design method and system thereof based on coupling simulation. The method comprises the following steps: S1, initial parameter setting and material characterization; s2, CFD simulation and primary optimization of macroscopic workability; s3, DEM simulation and secondary optimization of microstructure stability are carried out; and S4, coupling iteration and final mix proportion determination. The invention relates to the technical field of crossing of civil engineering material design and computer simulation, and can solve the problems of long design period, high cost and unclear mechanism of the mix proportion of a flow-state backfill material in the prior art.

Description

Technical Field

[0001] This invention relates to the interdisciplinary field of civil engineering material design and computer simulation, and in particular to a fluid backfill material and its mix design method and system based on coupled simulation. Background Technology

[0002] Fluidized backfill materials have become a key technology for solving the backfilling challenges of deep, large, and narrow spatial structures. Currently, mix design heavily relies on researchers' experience and complex trial-and-error experiments, resulting in problems such as long cycles, high costs, and unclear mechanisms. When materials utilize large quantities of solid waste with complex compositions and fluctuating performance (such as high-mud-content stone powder and tailings), the limitations of traditional mix design methods become even more pronounced.

[0003] Existing simulation technologies are mostly limited to a single scale or used only for post-event mechanism analysis, failing to form a closed-loop workflow to guide the early design of fluidized backfill materials. Therefore, there is a need to provide a fluidized backfill material and its mix design method and system based on coupled simulation, which can solve the problems of long design cycles, high costs, and unclear mechanisms in the existing fluidized backfill material mix design. Summary of the Invention

[0004] The purpose of this invention is to provide a fluidized backfill material and its mix design method and system based on coupled simulation, which can solve the problems of long design cycle, high cost and unclear mechanism of fluidized backfill material mix design in the prior art.

[0005] This invention is implemented as follows: A mix design method for fluidized backfill materials based on coupled simulation, comprising the following steps: S1: Initial parameter setting and material characterization: Determine the initial components and their mass percentage range of the target fluid backfill material, and determine the physical properties of the solid waste fine powder and the initial rheological parameters of the mixture in the fluid backfill material through physical experiments; S2: CFD simulation and initial optimization of macroscopic workability: A three-dimensional CFD model of the transportation pipeline is established based on the actual engineering pump pipe. The water-cement ratio and sand ratio are used as the first-level optimization variables for parametric scanning simulation. Based on the preset macroscopic workability evaluation index, the first set of optimized mix proportions Ω1 that meets the requirements is selected. S3: DEM simulation and secondary optimization of microstructure stability; a three-dimensional particle DEM model is established, and the content of fine powder of solid waste is used as the second-level optimization variable to simulate and analyze the mix proportions in the first optimized mix proportion set Ω1. Based on the preset microstructure stability evaluation index, the second optimized mix proportion set Ω2 with the best microstructure is selected. S4: Coupled iteration and final mix proportion determination; Select a mix proportion from the second optimized mix proportion set Ω2 for experimental verification. If the deviation between the measured performance of the selected fluid backfill material and the CFD simulation prediction exceeds a preset threshold, then correct the three-dimensional transport pipeline CFD model and repeat S2-S3 for iterative optimization until the deviation between the measured performance of the selected fluid backfill material and the simulation prediction does not exceed the preset threshold, and output the final engineering mix proportion that meets the engineering requirements.

[0006] In S1, the fluid backfill material includes cement, aggregate, fine solid waste powder, water and additives. The fine solid waste powder includes one of stone powder, tailings and slag, wherein the mud content of the stone powder is 30%-60%.

[0007] In S1, the initial rheological parameters of the mixture are obtained by fitting the rheometer test, which simplifies the fluid backfill material to Bingham fluid or Herschel-Bulkley fluid.

[0008] In S2, the macroscopic performance evaluation indicators include: the average flow velocity V_avg in the core area of ​​the three-dimensional transport pipeline, the maximum dynamic pressure P_max at the bend of the three-dimensional transport pipeline, and the total pressure drop ΔP_total throughout the entire pipeline.

[0009] In S2, the simulation of the three-dimensional transport pipeline CFD model adopts a parametric scanning method, which systematically traverses the preset combinations of water-cement ratio and sand ratio.

[0010] In S3, the three-dimensional particle DEM model includes spherical particles for simulating coarse aggregates, clustered particles for simulating irregular aggregates, and fine particles for simulating fine components; the three-dimensional particle DEM model adopts a combination of Hertz-Mundelllin contact model and parallel bonding model.

[0011] In S3, the microscopic stability evaluation index may include: the average coordination number Z of the system, the uniformity index H of the force chain network, and the simulated unconfined compressive strength σ obtained through simulated loading.

[0012] In S4, the iterative optimization specifically involves comparing the simulation parameters of the three-dimensional transport pipeline CFD model of the backfill material corresponding to the selected mix proportion from the second optimized mix proportion set Ω2 with its measured rheological parameters. If the deviation exceeds a preset threshold, the three-dimensional transport pipeline CFD model is updated using the measured rheological parameters, and S2 and S3 are re-executed until the deviation between the measured rheological parameters of the selected mix proportion and the predicted parameters used in the simulation of the three-dimensional transport pipeline CFD model does not exceed the preset threshold, thus forming a closed-loop iteration.

[0013] A mix design system employing a coupled simulation-based mix design method for fluidized backfill materials, comprising: The parameter input module is used to set initial parameters; The CFD simulation optimization module is used to perform macroscopic workability simulation of the three-dimensional transportation pipeline CFD model and initial optimization based on preset macroscopic workability evaluation indicators. The data coupling and iteration control module is used to manage the data transfer and control iteration process between the 3D transport pipeline CFD model and the 3D particle DEM model. The results output and visualization module is used to output the final engineering mix proportions.

[0014] A fluidized backfill material designed using a coupled simulation-based mix design method, wherein the proportions of its components are determined using the coupled simulation-based mix design method, and the mass percentage of fine solid waste powder in the fluidized backfill material is 60%-75%. The components of fluid backfill material include cement, fly ash, stone powder, crushed stone, manufactured sand, water and admixtures. Among them, the mud content of stone powder is 40%-50%, the 28-day compressive strength of fluid backfill material is 3-5 MPa, and the slump is 180±20 mm.

[0015] Compared with the prior art, the present invention has the following advantages: 1. This invention reveals the intrinsic formation mechanism of the properties of fluid backfill materials from two dimensions: macroscopic rheology and microscopic mechanics, transforming the design process from "experience-driven" to "model and data-driven", thus possessing high scientific rigor.

[0016] 2. This invention significantly reduces the number of trials and fittings by using a "simulation optimization screening and experimental correction" model, which can shorten the design and development cycle from several weeks to several days, significantly reducing the design and development cost and demonstrating high efficiency and economy.

[0017] 3. This invention ensures the pumpability of the designed fluid backfill material under actual working conditions through CFD simulation, and guarantees the final structural stability of the fluid backfill material from the source through DEM simulation, resulting in high reliability and accuracy of the final output mix ratio.

[0018] 4. This invention provides key technologies and scientific basis for the high-value-added resource utilization of fine powders of complex solid wastes (especially stone powder with high mud content) that are difficult to utilize in the prior art, resulting in significant environmental and economic benefits. Attached Figure Description

[0019] Figure 1 This is a flowchart of the flow state backfill material mix design method based on coupled simulation of the present invention; Figure 2 This is a flow velocity cloud map inside the pump tube displayed by CFD simulation in Embodiment 1 of the present invention. Detailed Implementation

[0020] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0021] Please see the appendix Figure 1 A method for designing the mix proportion of fluidized backfill materials based on coupled simulation is proposed. Through dual screening and iterative calibration of macroscopic and microscopic simulations, the mix proportion of fluidized backfill materials is scientifically optimized, realizing the scientific, efficient and accurate design of liquid backfill materials. It is particularly suitable for scenarios involving the large-scale utilization of fine powders of complex solid waste.

[0022] This design method specifically includes the following steps: S1: Initial parameter setting and material characterization.

[0023] Specifically, the initial components and their mass percentage range of the target fluid backfill material are determined, i.e., the initial parameters, and the physical properties of the solid waste fine powder in the fluid backfill material and the initial rheological parameters of the mixture are determined through physical experiments.

[0024] In S1, the fluid backfill material includes cement, aggregate, fine solid waste powder, water and additives. The fine solid waste powder includes one of stone powder, tailings and slag, wherein the mud content of the stone powder is 30%-60%.

[0025] In S1, the initial rheological parameters of the mixture are obtained by fitting the rheometer test, which simplifies the fluid backfill material to Bingham fluid or Herschel-Bulkley fluid.

[0026] Preferably, the particle size distribution and density of the fine powder of solid waste can be determined by experiment, and the yield stress and plastic viscosity of the mixture under the preliminary mix ratio can be obtained by rheometer, which are defined as Bingham fluid.

[0027] Bingham fluid, proposed by Eugene Bingham, is a viscoelastic non-Newtonian fluid belonging to the category of plastic fluids with yield stress. Its characteristics include exhibiting a rigid state when the applied shear stress is below a critical value τ0, and then showing a linear relationship between shear stress and shear rate above this value. It is commonly found in colloidal systems containing suspended particles, such as toothpaste, mud, and paint.

[0028] Herschel-Bulkley fluid is a typical non-Newtonian fluid, exhibiting shear-thinning or shear-thickening characteristics and possessing yield stress (i.e., the minimum shear stress required for the fluid to begin flowing).

[0029] S2: CFD simulation and initial optimization of macroscopic working performance.

[0030] Specifically, a three-dimensional CFD model of the transportation pipeline is established based on the actual engineering pump pipe. The water-cement ratio and sand ratio are used as the first-level optimization variables for parametric scanning simulation. Based on the preset macroscopic workability evaluation index, the first set of optimal mix proportions Ω1 that meet the requirements (e.g., excellent fluidity and low risk of pipe blockage) is selected.

[0031] In S2, the macroscopic workability evaluation indicators may include: the average flow velocity V_avg in the core area of ​​the three-dimensional transport pipeline, the maximum dynamic pressure P_max at the bend of the three-dimensional transport pipeline, and the total pressure drop ΔP_total throughout the entire pipeline.

[0032] In S2, the simulation of the three-dimensional transport pipeline CFD model adopts a parametric scanning method, which systematically traverses the preset combinations of water-cement ratio and sand ratio.

[0033] S3: DEM simulation and secondary optimization of microstructure stability.

[0034] Specifically, a three-dimensional particle DEM model is established, and the content of fine powder of solid waste is used as the second-level optimization variable. The mixing ratio in the first optimized mixing ratio set Ω1 is simulated and analyzed. Based on the preset microscopic stability evaluation index, the second optimized mixing ratio set Ω2 with the best microstructure (e.g., the most stable microstructure) is selected.

[0035] The three-dimensional particle DEM model is a three-dimensional discrete element model used to reflect the true shape of the particles. The Hertz-Mundell-Fleming contact model and the parallel bonding model are used to simulate the interaction between particles.

[0036] In S3, the three-dimensional particle DEM model includes spherical particles for simulating coarse aggregates, clustered particles for simulating irregular aggregates, and fine particles for simulating fine components; the three-dimensional particle DEM model adopts a combination of Hertz-Mundelllin contact model and parallel bonding model.

[0037] In S3, the microscopic stability evaluation index may include: the average coordination number Z of the system, the uniformity index H of the force chain network, and the simulated unconfined compressive strength σ obtained through simulated loading.

[0038] S4: Coupling iteration and final mix ratio determination.

[0039] Specifically, mix proportions are selected from the second optimized mix proportion set Ω2 for experimental verification. If the deviation between the measured performance of the selected fluid backfill material and the CFD simulation prediction exceeds a preset threshold, the three-dimensional transport pipeline CFD model is corrected, and S2-S3 are repeated for iterative optimization until the deviation between the measured performance of the selected fluid backfill material and the simulation prediction does not exceed the preset threshold, and the final engineering mix proportion that meets the engineering requirements is output.

[0040] In S4, the iterative optimization specifically involves comparing the simulation parameters of the three-dimensional transport pipeline CFD model of the backfill material corresponding to the selected mix proportion from the second optimized mix proportion set Ω2 with its measured rheological parameters (i.e., the actual measured performance in the laboratory). If the deviation exceeds a preset threshold, the three-dimensional transport pipeline CFD model is updated using the measured rheological parameters, and S2 and S3 are re-executed until the deviation between the measured rheological parameters of the selected mix proportion and the predicted parameters used in the simulation of the three-dimensional transport pipeline CFD model does not exceed the preset threshold, thus forming a closed-loop iteration.

[0041] Taking a specific mix proportion from the second optimized mix proportion set Ω2 as an example, let the simulation parameter of its three-dimensional transport pipeline CFD model be A. The measured rheological parameter B is obtained through laboratory experiments using the simulation parameter A. The simulation parameter A is then compared with the measured rheological parameter B. A preset threshold of 15% is used (this threshold can be adjusted adaptively according to actual design requirements). If the deviation between the simulation parameter A and the measured rheological parameter B exceeds 15%, the three-dimensional transport pipeline CFD model is updated using the measured rheological parameter, and steps S2 and S3 are re-executed until the deviation between the measured rheological parameter of the selected mix proportion and the predicted parameter used in the simulation of the three-dimensional transport pipeline CFD model does not exceed 15%.

[0042] A mix design system for fluidized backfill materials based on coupled simulation, comprising: The parameter input module is used to set the initial parameters.

[0043] The CFD simulation optimization module is used to perform macroscopic workability simulation of the three-dimensional transportation pipeline CFD model and initial optimization based on preset macroscopic workability evaluation indicators.

[0044] The data coupling and iteration control module is used to manage the data transfer and control iteration process between the 3D transport pipeline CFD model and the 3D particle DEM model.

[0045] The results output and visualization module is used to output the final engineering mix proportions.

[0046] The mixture design system for fluidized backfill materials based on coupled simulation of the present invention integrates functions such as parameter input, CFD simulation optimization, DEM simulation optimization, iterative control and result visualization through modular design, thereby realizing the automation and intelligence of the mixture design process for fluidized backfill materials.

[0047] A fluidized backfill material, wherein the proportion of its components is determined by the above-mentioned proportion design method based on coupled simulation for fluidized backfill material, and the mass proportion of fine powder of solid waste in the fluidized backfill material is 60%-75%.

[0048] The fluid backfill material comprises cement, fly ash, stone powder, crushed stone, manufactured sand, water, and admixtures. The stone powder has a mud content of 40%-50%, the 28-day compressive strength of the fluid backfill material is 3-5 MPa, and the slump is 180±20 mm.

[0049] The fluidized backfill material obtained by the coupled simulation-based mix design method and system design of the present invention makes extensive use of fine powder of solid waste (60%-75% by mass), especially stone powder with a mud content of 40%-50%, and can achieve excellent engineering performance of 3-5 MPa strength and slump of 180±20 mm in 28 days.

[0050] Example 1: The design of the fluidized backfill material (C3) for the deep-sea partition compartment of Kunming Changshui International Airport Terminal 2 is used as an example.

[0051] Please see the appendix Figure 1 S1: Initial parameter setting and material characterization. Objective: To prepare a fluid backfill material with a 28-day strength ≥ 3.5 MPa and a slump of 180 ± 20 mm, and to make extensive use of in-situ high mud content (approximately 45%) stone powder.

[0052] The initial component range is set as follows: cement 3%-5%, fly ash 5%-8%, stone powder 60%-75%, aggregate (crushed stone and manufactured sand) 20%-35%, water and appropriate amount of admixtures.

[0053] Rheological testing showed that the yield stress of the initially formulated mixture was 125 Pa and the plastic viscosity was 0.85 Pa·s.

[0054] S2: CFD simulation and initial optimization of macroscopic workability. A three-dimensional CFD model of the transport pipeline, including two 90° bends, was built using ANSYS Fluent. 25 sets of parametric sweep simulations were performed with water-cement ratios (1.9, 2.0, 2.1, 2.2, 2.3) and sand ratios (55%, 60%, 63%, 65%, 70%) as the first-level optimization variables.

[0055] Set the macroscopic workability evaluation indicators as follows: V_avg>0.8m / s, P_max<0.15MPa, ΔP_total<18MPa.

[0056] Please see the appendix Figure 2 The left image shows the velocity cloud map inside the pump pipe with a water-to-binder ratio of 1.9. There is a large area of ​​low-velocity blue behind the bend, indicating poor flow and a high risk of pipe blockage. The right image shows the velocity cloud map inside the pump pipe with a water-to-binder ratio of 2.1. The colors inside the pipe are mainly red and yellow, which represent high speed, indicating smooth and uniform flow.

[0057] Through CFD simulation of a three-dimensional transportation pipeline, it was found that the optimal performance was achieved when the water-cement ratio was 2.1 and the sand ratio was 63%, thus determining the optimal water-cement ratio range. Furthermore, all combinations with a water-cement ratio ≥ 2.0 and a sand ratio ≤ 65% met the requirements, forming the first optimal mix design set Ω1.

[0058] S3: DEM simulation and secondary optimization of microstructure stability. Using PFC3D software, with a fixed water-cement ratio of 2.1 and a sand ratio of 63%, the content of fine solid waste powder was used as the second-level optimization variable, i.e., varying the volume content of stone powder (35%, 40%, 45%, 50%, 55%).

[0059] DEM simulations showed that when the stone powder content was 45%, the system had the highest coordination number Z (4.8), the lowest force chain uniformity index H (0.22), and the highest simulated strength σ_sim (4.1 MPa). Based on this, the optimal stone powder content range was determined to be 40%-50%, and the corresponding proportions were identified from the first optimized mix proportion set Ω1 to form the second optimized mix proportion set Ω2.

[0060] S4: Coupled Iteration and Final Mix Proportion Determination. The optimal mix proportion (cement:fly ash:stone powder:crushed stone:sand:water = 1:2:68.7:25:43.3:6) in the second optimized mix proportion set Ω2 was selected for trial mixing.

[0061] The measured slump of the trial-mixed fluidized backfill material was 185 mm, and the deviation of the rheological parameters (τ0=118 Pa, μ=0.81 Pa·s) from the predicted parameters input by the CFD simulation was less than 10%, which is within an acceptable range and requires no iteration. The measured compressive strength at 28 days was 3.8 MPa, fully meeting the requirements. The fluidized backfill material with this mix proportion was successfully applied to this project, resulting in uniform backfill quality and a 60% improvement in construction efficiency.

[0062] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the invention. Therefore, any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A mix design method for fluidized backfill materials based on coupled simulation, characterized by: Includes the following steps: S1: Initial parameter setting and material characterization: Determine the initial components and their mass percentage range of the target fluid backfill material, and determine the physical properties of the solid waste fine powder and the initial rheological parameters of the mixture in the fluid backfill material through physical experiments; S2: CFD simulation and initial optimization of macroscopic workability: A three-dimensional CFD model of the transportation pipeline is established based on the actual engineering pump pipe. The water-cement ratio and sand ratio are used as the first-level optimization variables for parametric scanning simulation. Based on the preset macroscopic workability evaluation index, the first set of optimized mix proportions Ω1 that meets the requirements is selected. S3: DEM simulation and secondary optimization of microstructure stability; a three-dimensional particle DEM model is established, and the content of fine powder of solid waste is used as the second-level optimization variable to simulate and analyze the mix proportions in the first optimized mix proportion set Ω1. Based on the preset microstructure stability evaluation index, the second optimized mix proportion set Ω2 with the best microstructure is selected. S4: Coupled iteration and final mix proportion determination; Select a mix proportion from the second optimized mix proportion set Ω2 for experimental verification. If the deviation between the measured performance of the selected fluid backfill material and the CFD simulation prediction exceeds a preset threshold, then correct the three-dimensional transport pipeline CFD model and repeat S2-S3 for iterative optimization until the deviation between the measured performance of the selected fluid backfill material and the simulation prediction does not exceed the preset threshold, and output the final engineering mix proportion that meets the engineering requirements.

2. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S1, the fluid backfill material includes cement, aggregate, fine solid waste powder, water and additives. The fine solid waste powder includes one of stone powder, tailings and slag, wherein the mud content of the stone powder is 30%-60%.

3. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S1, the initial rheological parameters of the mixture are obtained by fitting the rheometer test, which simplifies the fluid backfill material to Bingham fluid or Herschel-Bulkley fluid.

4. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S2, the macroscopic performance evaluation indicators include: the average flow velocity V_avg in the core area of ​​the three-dimensional transport pipeline, the maximum dynamic pressure P_max at the bend of the three-dimensional transport pipeline, and the total pressure drop ΔP_total throughout the entire pipeline.

5. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S2, the simulation of the three-dimensional transport pipeline CFD model adopts a parametric scanning method, which systematically traverses the preset combinations of water-cement ratio and sand ratio.

6. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S3, the three-dimensional particle DEM model includes spherical particles for simulating coarse aggregates, clustered particles for simulating irregular aggregates, and fine particles for simulating fine components; the three-dimensional particle DEM model adopts a combination of Hertz-Mundelllin contact model and parallel bonding model.

7. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S3, the microscopic stability evaluation index may include: the average coordination number Z of the system, the uniformity index H of the force chain network, and the simulated unconfined compressive strength σ obtained through simulated loading.

8. The mix design method for fluidized backfill materials based on coupled simulation according to claim 1, characterized in that: In S4, the iterative optimization specifically involves comparing the simulation parameters of the three-dimensional transport pipeline CFD model of the backfill material corresponding to the selected mix proportion from the second optimized mix proportion set Ω2 with its measured rheological parameters. If the deviation exceeds a preset threshold, the three-dimensional transport pipeline CFD model is updated using the measured rheological parameters, and S2 and S3 are re-executed until the deviation between the measured rheological parameters of the selected mix proportion and the predicted parameters used in the simulation of the three-dimensional transport pipeline CFD model does not exceed the preset threshold, thus forming a closed-loop iteration.

9. A mix design system employing the coupled simulation-based mix design method for the fluidized backfill material as described in claim 1, characterized in that: include: The parameter input module is used to set initial parameters; The CFD simulation optimization module is used to perform macroscopic workability simulation of the three-dimensional transportation pipeline CFD model and initial optimization based on preset macroscopic workability evaluation indicators. The data coupling and iteration control module is used to manage the data transfer and control iteration process between the 3D transport pipeline CFD model and the 3D particle DEM model. The results output and visualization module is used to output the final engineering mix proportions.

10. A fluidized backfill material designed using the mix design method based on coupled simulation as described in claim 1, characterized in that: The proportions of its components are designed and determined using the coupled simulation-based proportioning design method for fluidized backfill materials, and the mass percentage of fine solid waste powder in the fluidized backfill material is 60%-75%. The components of fluid backfill material include cement, fly ash, stone powder, crushed stone, manufactured sand, water and admixtures. Among them, the mud content of stone powder is 40%-50%, the 28-day compressive strength of fluid backfill material is 3-5 MPa, and the slump is 180±20 mm.

Images