陈连军1，2， 高亢1，3， 孙振姣1， 马辉4，5， 蔡光晖1
1.山东科技大学 安全与环境工程学院， 山东 青岛 266590； 2.青岛理工大学 土木工程学院， 山东 青岛 266520； 3.School of Civil and Environmental Engineering， Nanyang Technological University， Singapore 639798， Singapore； 4.中国矿业大学 安全工程学院， 江苏 徐州 221116； 5.Department of Mechanical Engineering， National University of Singapore， Singapore 117575， Singapore
引用格式：
陈连军， 高亢， 孙振姣， 等. 新拌混凝土流动数值模拟研究进展［J］. 中国粉体技术， 2027， 33（3）： 1-18.
Chen Lianjun， Gao Kang， Sun Zhenjiao， et al. Research progress on numerical simulation of fresh concrete flow［J］. China Powder Science and Technology， 2027， 33（3）： 1-18.
DOI：10.13732/j.issn.1008-5548.2027.03.009
收稿日期： 2026-05-16， 修回日期： 2026-07-23， 上线日期： 2026-10-21。
基金项目： 国家自然科学基金项目， 编号： 52574253； 山东省博士后创新项目， 编号： SDCX-ZG-202502047； 国家留学基金项目，编号：202508370048。
第一作者： 陈连军（1981—），男，教授，博士，研究方向为地下工程高性能混凝土喷射支护技术。E-mail：skyskjxz@163.com。
通信作者： 孙振姣（1996—），男，讲师，博士（后），研究方向为喷射混凝土、粉体颗粒输送及CFD-DEM耦合模拟。E-mail：sunzhenjiao@foxmail.com。
摘要： 【目的】 梳理新拌混凝土流动数值模拟的模型体系、应用场景与发展趋势，明确离散元法（discrete element method，DEM）及其与计算流体动力学（computational fluid dynamics， CFD）、光滑粒子流体动力学（smoothed particle hydrodynamics，SPH）、有限元法（finite element method，FEM）等方法耦合在粉体颗粒力学、浆体流变表征和施工过程预测中的研究价值。【研究现状】 从粉体颗粒学视角综述颗粒接触定律、液桥或浆体桥接模型、硬核-软壳模型、揉捏接触模型、离散新拌混凝土模型（DFC）及多尺度耦合框架，比较其数学形式、参数来源、验证路径和适用边界，并归纳其在搅拌均匀性、自密实混凝土流动与堵塞、泵送管流、喷射输送和混凝土3D打印中的应用规律。【结论与展望】认为新拌混凝土数值模拟已由经验参数拟合逐步转向物理约束、流变关联和多源数据校正的预测型建模，但颗粒尺度放大、参数非唯一性、时变水化-触变耦合、边界条件表征和工程尺度计算效率仍是限制因素。未来应建立可测参数驱动的统一标定体系，发展DEM与连续介质方法、机器学习反演和现场监测数据融合的虚拟混凝土实验室。
关键词： 新拌混凝土； 数值模拟； 离散元法； 流变； 混凝土3D打印； 泵送
Abstract
Significance Fresh concrete is a highly concentrated multiphase granular suspension composed of aggregates， cement paste， admixtures， and entrapped air. Its flow behavior directly affects mixing uniformity， formwork filling， passing ability， pumping stability， shotcrete transport， extrusion quality， and the buildability of three-dimensional concrete printing. Conventional workability and rheological tests provide useful macroscopic indicators， but they cannot fully reveal particle migration， force chain formation， paste film lubrication， aggregate bridging， fiber orientation， or time-dependent structural build-up. Therefore， numerical simulation offers an important approach for linking material composition， mesoscopic particle interaction， and engineering-scale flow performance. Among existing methods， discrete element method （DEM） is particularly valuable because it explicitly tracks particle motion， collision， friction， cohesion， and rearrangement. With advances in contact mechanics， computing power， and multiphysics coupling， DEM has gradually evolved from a qualitative tool for reproducing simple workability tests into a physically interpretable framework for predicting complex fresh concrete construction processes. This review summarizes the model system， physical assumptions， calibration logic， application boundaries， and future development trends of DEM-based simulation of fresh concrete flow.
Progress This study reviews fresh concrete DEM from the perspective of powder and granular mechanics. Basic contact laws， including linear spring-dashpot， Hertz-Mindlin， cohesive damping， and JKR adhesion models are first discussed in relation to macroscopic rheological parameters. These models can describe collision， damping， frictional sliding， and equivalent cohesion， and are efficient for slump， flow spread， L-box， and small-scale filling simulations. However， since fresh concrete contains paste-coated aggregates rather than dry particles， direct use of dry granular contact laws may underestimate adhesion， yield resistance， and lubrication effects. Therefore， paste bridge and liquid bridge models introduce finite tensile strength， rupture distance， viscous dissipation， and paste film thickness between adjacent aggregates. Hard-core soft-shell models further regard aggregates as rigid cores wrapped by deformable mortar shells， thereby representing mortar film lubrication， blocking， and passing behavior. Kneading contact models introduce moisture or paste distribution as internal variables and are suitable for simulating water addition， liquid migration， mixing， and homogenization. Discrete fresh concrete models embed mortar constitutive behavior into the contact zone between aggregates， allowing contact forces to be calculated from the strain， strain rate， and time-dependent response of the equivalent mortar region. These developments show that DEM modeling is shifting from empirical fitting of contact parameters toward measurable， rheology-related， and history-dependent interaction laws. This study also discusses the effects of particle morphology， fiber orientation， and thixotropy. Real aggregates are angular， elongated， or flaky， and their interlocking can increase dilatancy， shear resistance， and local blocking probability. Multi-sphere clumps， random polyhedra， CT-reconstructed particles， and shape-factor corrections provide different compromises between geometric fidelity and computational efficiency. For fiber-reinforced mixtures， DEM can track fiber orientation and alignment during pumping， spraying， and printing， while flexible fiber models are required when bending deformation is significant. Time-dependent hydration， flocculation， and structural build-up further require evolving contact parameters or constitutive models， especially for printable concrete and shotcrete. In terms of application， DEM and its coupled methods have been used to analyze mixing uniformity， self-compacting concrete flow， reinforcement passing， local blockage， pumping pipe flow， pneumatic conveying， shotcrete transport， and concrete 3D printing. In mixing simulations， DEM can quantify particle trajectories， collision frequency， mixing index， and torque evolution. In self-compacting concrete， DEM reveals that blockage is controlled not only by average fluidity， but also by local aggregate concentration， arching， force chains， and insufficient paste lubrication near constrained openings. For pumping and shotcrete conveying， pure DEM is insufficient to resolve the continuous paste or air pressure field， so coupled computational fluid dynamics （CFD）-DEM is important for predicting pressure loss， particle migration， lubrication layer formation， wall collision， and bend wear. Coupled smoothed particle hydrodynamics （SPH）-DEM is more suitable for free surface flow， nozzle extrusion， interlayer deposition， and large deformation. Coupled DEM-finite element method （FEM） is useful when particle-scale deposition or rearrangement must be transferred to early-age structural deformation， formwork pressure， or printed layer stability. These methods are complementary， and their selection should depend on the dominant physical field， boundary condition， target output， and available validation data.
Conclusions and prospects DEM-based simulation of fresh concrete has gradually shifted from empirical reproduction of single tests to predictive modeling constrained by particle mechanics， paste rheology， and multisource data. Its major value lies in connecting microscale interaction mechanisms with engineering indicators such as workability， passing ability， pumping pressure， blockage risk， wear intensity， extrudability， and buildability. However， several challenges remain to be addressed. Contact parameters are often back-calculated from macroscopic tests， causing nonuniqueness and limited transferability. Particle scaling may change the Stokes number， Froude number， contact network， and cohesion scale. Spherical particles may underestimate angular interlocking. Implicit paste treatment may lose local pressure fields and lubrication layer details. Hydration， thixotropy， temperature， admixture effects， wall roughness， and experimental variability also introduce uncertainty， while engineering-scale simulation remains computationally demanding. Future research should establish a measurable parameter-driven calibration framework combining rheometry， paste bridge tests， particle-paste shear tests， standard workability tests， and process-scale validation. Coarse graining， GPU acceleration， realistic particle morphology， flexible fibers， time-dependent contact laws， machine learning inversion， and field monitoring data should be integrated to build a virtual concrete laboratory for material design， process optimization， and intelligent construction control.
Keywords： fresh concrete； numerical simulation； discrete element method； rheology； three-dimensional concrete printing； pumping
参考文献（References）
［1］Wallevik O H， Wallevik J E. Rheology as a tool in concrete science： the use of rheographs and workability boxes［J］. Cement and Concrete Research， 2011， 41（12）： 1279-1288.
［2］Jiao Dengwu， Shi Caijun， Yuan Qiang， et al. Effect of constituents on rheological properties of fresh concrete： a review［J］. Cement and Concrete Composites， 2017， 83： 146-159.
［3］De Larrard F， Ferraris C， Sedran T. Fresh concrete： a Herschel-Bulkley material［J］. Materials and Structures， 1998， 31（7）： 494-498.
［4］Roussel N， Geiker M R， Dufour F， et al. Computational modeling of concrete flow： general overview［J］. Cement and Concrete Research， 2007， 37（9）： 1298-1307.
［5］Mechtcherine V， Gram A， Krenzer K， et al. Simulation of fresh concrete flow using discrete element method （DEM）： theory and applications［J］. Materials and Structures， 2014， 47（4）： 615-630.
［6］Li Yue， Hao Ji， Jin Caiyun， et al. Simulation of the flowability of fresh concrete by discrete element method［J］. Frontiers in Materials， 2021， 7： 603154.
［7］Chu Hongwei， Machida A， Suzuki N. Experiment investigation and DEM simulation of filling capacity of fresh concrete［J］. Concrete Engineering Annual Proceedings， 1996， 18（1）： 471-476.
［8］Zhan Yijian， Gong Jian， Huang Yulin， et al. Numerical study on concrete pumping behavior via local flow simulation with discrete element method［J］. Materials， 2019， 12（9）： 1415.
［9］Ramyar E， Cusatis G. Discrete fresh concrete model for simulation of ordinary， self-consolidating， and printable concrete flow［J］. Journal of Engineering Mechanics， 2022， 148（2）： 04021142.
［10］Krenzer K， Palzer U， Müller S， et al. Simulation of 3D concrete printing using discrete element method［C］//RILEM International Conference on Concrete and Digital Fabrication. Cham： Springer， 2022： 161-166.
［11］Deng Rong， Lu Xiaowei， Ye Tong. The effect of JKR surface energy on the flowing property of fresh concrete in DEM simulation［J］. Particulate Science and Technology， 2024， 42（5）： 789-803.
［12］Roussel N， Gram A. Simulation of fresh concrete flow： state-of-the-art report of RILEM Technical Committee 222-SCF［M］. Dordrecht： Springer， 2014.
［13］Cao Guodong， Zhang Hao， Tan Yuanqiang， et al. Study on the effect of coarse aggregate volume fraction on the flow behavior of fresh concrete via DEM［J］. Procedia Engineering， 2015， 102： 1820-1826.
［14］Cui Wei， Ji Tianzhu， Li Ming， et al. Simulating the workability of fresh self-compacting concrete with random polyhedron aggregate based on DEM［J］. Materials and Structures， 2017， 50（1）： 92.
［15］Cui Wei， Yan Weishuo， Song Huifang， et al. Blocking analysis of fresh self-compacting concrete based on the DEM［J］. Construction and Building Materials， 2018， 168： 412-421.
［16］Guo Zhanqi， Yuan Quan， Stroeven P， et al. Discrete element method simulating workability of fresh concrete［C］//AIP Conference Proceedings. Melville： American Institute of Physics， 2010， 1233： 430-435.
［17］Mechtcherine V， Shyshko S. Simulating the behaviour of fresh concrete with the distinct element method： deriving model parameters related to the yield stress［J］. Cement and Concrete Composites， 2015， 55： 81-90.
［18］Dufour F， Pijaudier-Cabot G. Numerical modelling of concrete flow： homogeneous approach［J］. International Journal for Numerical and Analytical Methods in Geomechanics， 2005， 29（4）： 395-416.
［19］Hoornahad H， Koenders E A B， Van Breugel K. Towards a model for fresh granular-paste systems based on discrete element method［J］. Key Engineering Materials， 2010， 452/453： 569-572.
［20］Hoornahad H， Koenders E A B. Simulating macroscopic behavior of self-compacting mixtures with DEM［J］. Cement and Concrete Composites， 2014， 54： 80-88.
［21］Rémond S， Pizette P. A DEM hard-core soft-shell model for the simulation of concrete flow［J］. Cement and Concrete Rese-arch， 2014， 58： 169-178.
［22］Krenzer K， Mechtcherine V， Palzer U. Simulating mixing processes of fresh concrete using the discrete element method （DEM） under consideration of water addition and changes in moisture distribution［J］. Cement and Concrete Research， 2019， 115： 274-282.
［23］Wu Zhengyang， Li Hongwen， He Jin， et al. Calibration of the Kneading contact model by a simplified infiltration test for modeling rotary-tillage mixes of liquid amendments and soils［J］. Computers and Electronics in Agriculture， 2024， 222： 109079.
［24］Sun Zhenjiao， Chen Lianjun， Ma Guanguo， et al. Calibrating the kneading contact model for simulating fresh concrete： incorporating water addition［J］. Powder Technology， 2025： 121188.
［25］Dahlenburg M， Tan Yuan， Li Mengxue， et al. A flexible and efficient calibration method for discrete element simulations of additive manufacturing in construction［J］. Journal of Building Engineering， 2024， 96： 110398.
［26］Quintana-Ruiz O D， Campello E M.DEM modeling of advanced manufacturing technologies： from SLS to 3D concrete printing［J］. Archive of Applied Mechanics， 2024， 94（9）： 2451-2469.
［27］Nguyen-Van V， Li Shuai， Liu Junli， et al. Modelling of 3D concrete printing process： a perspective on material and structural simulations［J］. Additive Manufacturing， 2023， 61： 103333.
［28］Pieralisi R， Cavalaro S， Aguado A. Discrete element modelling of the fresh state behavior of pervious concrete［J］. Cement and Concrete Research， 2016， 90： 6-18.
［29］Gudžulić V， Dang T S， Meschke G. Computational modeling of fiber flow during casting of fresh concrete［J］. Computational Mechanics， 2019， 63（6）： 1111-1129.
［30］Roussel N， Ovarlez G， Garrault S， et al. The origins of thixotropy of fresh cement pastes［J］. Cement and Concrete Research， 2012， 42（1）： 148-157.
［31］Tan Yuanqiang， Cao Guodong， Zhang Hao， et al. Study on the thixotropy of the fresh concrete using DEM［J］. Procedia Engineering， 2015， 102： 1944-1950.
［32］Qian Ye， Kawashima S. Distinguishing dynamic and static yield stress of fresh cement mortars through thixotropy［J］. Cement and Concrete Composites， 2018， 86： 288-296.
［33］Li Zhuguo， Cao Guodong， Guo Kun. Numerical method for thixotropic behavior of fresh concrete［J］. Construction and Building Materials， 2018， 187： 931-941.
［34］Hoornahad H， Koenders E A B. Tracking the rheological behavior change of a fresh granular-cement paste material to a granular material based on DEM［J］. Advanced Materials Research， 2012， 446/447/448/449： 3803-3809.
［35］Secrieru E， Khodor J， Schröfl C， et al. Formation of lubricating layer and flow type during pumping of cement-based materials［J］. Construction and Building Materials， 2018， 178： 507-517.
［36］Shyshko S， Mechtcherine V. Simulating the workability of fresh concrete［C］//Schlangen E， De Schutter G. International RILEM Symposium on Concrete Modelling： CONMOD'08. Bagneux： RILEM Publications SARL， 2008， pro058： 173-181.
［37］Zhang Xuan， Zhang Zhihua， Li Zhida， et al. Filling capacity analysis of self-compacting concrete in rock-filled concrete based on DEM［J］. Construction and Building Materials， 2020， 233： 117321.
［38］Wilkinson S， Turnbull S， Yan Z， et al. A parametric evaluation of powder flowability using a Freeman rheometer through statistical and sensitivity analysis： a discrete element method （DEM） study［J］. Computers & Chemical Engineering， 2017，97： 161-174.
［39］Choi M S， Kim Y J， Jang K P， et al. Effect of the coarse aggregate size on pipe flow of pumped concrete［J］. Construction and Building Materials， 2014， 66： 723-730.
［40］Zafar U， Hare C， Hassanpour A， et al. Drop test： a new method to measure the particle adhesion force［J］. Powder Technology， 2014， 264： 236-241.
［41］Li Xiaotian， Xie Guangnian， Gao Zhurui， et al. A hard-core soft-shell model for vibration condition of fresh concrete based on low water-cement ratio concrete［J］. Science and Engineering of Composite Materials， 2021， 28（1）： 689-701.
［42］Xu Wenxiang， Duan Qinglin， Ma Huaifa， et al. Interfacial effect on physical properties of composite media： interfacial volume fraction with non-spherical hard-core-soft-shell-structured particles［J］. Scientific Reports， 2015， 5（1）： 16003.
［43］Lin Jianjun， Zhao Qingxin， Chen Huisu， et al. Insight into the diffusivity of particulate composites considering percolation of soft interphases around hard fillers： from spherical to polyhedral particles［J］. Powder Technology， 2021， 392： 459-472.
［44］Liu Jiajie， Fang Huaiying， Yang Jianhong， et al. Simulation and experimental study on kneading and crushing of waste concrete for recycled aggregate production［J］. Construction and Building Materials， 2025， 500： 144201.
［45］Lombois-Burger H， Colombet P， Halary J L， et al. Kneading and extrusion of dense polymer-cement pastes［J］. Cement and Concrete Research， 2006， 36（11）： 2086-2097.
［46］Fernandes V， Silva L， Ferreira V， et al. Influence of the kneading water content in the behaviour of single-coat mortars［J］. Cement and Concrete Research， 2005， 35（10）： 1900-1908.
［47］Huang Qinghua， Jiang Zhilu， Gu Xianglin， et al. Numerical simulation of moisture transport in concrete based on a pore size distribution model［J］. Cement and Concrete Research， 2015， 67： 31-43.
［48］Avancini V H M， Quintana-Ruiz O D， Campello E M B. Assessing 3D-printed concrete process parameters through discrete element modeling［C］//Ibero-Latin American Congress on Computational Methods in Engineering. 2024：7.
［49］Zhang Xiao， Tao Muxuan， Ding Ran， et al. Simulation of reinforced concrete beam-column joint pouring process based on three-dimensional particle flow method［J］. Buildings， 2025， 15（20）： 3795.
［50］Buswell R A， Da Silva W L， Bos F P， et al. A process classification framework for defining and describing digital fabrication with concrete［J］. Cement and Concrete Research， 2020， 134： 106068.
［51］Hass L， Nefs K， Bos F， et al. Application potential of combining strain hardening cementitious composites and helical reinforcement for 3D concrete printed structures： case study of a spiral staircase［J］. Journal of Building Engineering， 2023， 80： 107926.
［52］Asprone D， Menna C， Bos F， et al. Structural design and testing of digitally manufactured concrete structures［M］//Roussel N， Lowke D. Digital Fabrication with Cement-Based Materials： State-of-the-Art Report of the RILEM TC 276-DFC. Cham： Springer， 2022： 187-222.
［53］Mata-Falcón J， Bischof P， Huber T， et al. Digitally fabricated ribbed concrete floor slabs： a sustainable solution for construction［J］. RILEM Technical Letters， 2022， 7： 68-78.
［54］Schwabe J H， Kuch H. Development and control of concrete mix processing procedures［C］//Proceedings of the 18th BIBM International Congress and Exhibition. Amsterdam， 2005： 108-109.
［55］Kuch H， Palzer S， Schwabe J. Anwendung der Simulation bei der Verarbeitung von Gemengen［C］//Finger-Institut für Baustoffkunde， FA. Tagungsbericht. Weimar， 2006， 16： 20-23.
［56］Mechtcherine V， Shyshko S. Virtual concrete laboratory： continuous numerical modelling of concrete from fresh to the hardened state［M］//Advances in Construction Materials 2007. Berlin： Springer， 2007： 479-488.
［57］Vasilić K. A numerical model for self-compacting concrete flow through reinforced sections： a porous medium analogy［D］.Dresden： Technische Universität Dresden， 2015.
［58］Zhang Xuan， Li Zhida， Zhang Zhihua. Blocking mechanism study of self-compacting concrete based on discrete element method［C］//IOP Conference Series： Materials Science and Engineering. 2017， 269： 012090.
［59］Zheng Jingwei， An Xuehui， Huang Miansong. GPU-based parallel algorithm for particle contact detection and its application in self-compacting concrete flow simulations［J］. Computers & Structures， 2012， 112/113： 193-204.
［60］Noor M A， Uomoto T. Numerical simulation of fresh concrete （2）： verification of three dimensional discrete element model for fresh concrete［J］. Seisan Kenkyu， 1999， 51（11）： 793-796. DOI： 10.11188/seisankenkyu.51.793.
［61］Shyshko S， Mechtcherine V. Developing a discrete element model for simulating fresh concrete： experimental investigation and modelling of interactions between discrete aggregate particles with fine mortar between them［J］. Construction and Building Materials， 2013， 47： 601-615.
［62］Mu Jinlei， Li Yue， Hao Ji， et al. Research on discrete element simulation of slump test for fresh self-compacting concrete［J］. Journal of Building Engineering， 2023， 70： 106464.
［63］Gram A， Silfwerbrand J. Numerical simulation of fresh SCC flow： applications［J］. Materials and Structures， 2011， 44（4）：805-813.
［64］Cui Wei， Yan Weishuo， Song Huifang， et al. DEM simulation of SCC flow in L-Box set-up： influence of coarse aggregate shape on SCC flowability［J］. Cement and Concrete Composites， 2020， 109： 103558.
［65］Zhou Xiang， Xie Youjun， Long Guangcheng， et al. Simulating passing ability of self-compacting concrete in the J-ring test using cohesive particle liquid bridge model［J］. Powder Technology， 2023， 416： 118218.
［66］Jiang Shengqiang， Chen Xiaodong， Cao Guodong， et al. Optimization of fresh concrete pumping pressure loss with CFD-DEM approach［J］. Construction and Building Materials， 2021， 276： 122204.
［67］Cao Guodong， Bai Yalong， Shi Yihao， et al. Investigation of vibration on rheological behavior of fresh concrete using CFD-DEM coupling method［J］. Construction and Building Materials， 2024， 425： 135908.
［68］Jiang Shengqiang， Zhang Wei， Chen Xiaodong， et al. CFD-DEM simulation research on optimization of spatial attitude of concrete pumping boom based on evaluation of minimum pressure loss［J］. Powder Technology， 2022， 403： 117365.
［69］Deng Rong， Ye Zhiwei， Li Sizhong. CFD-DEM study on the effect of coarse aggregate characteristics on pipe blockage in concrete pumping［J］. Powder Technology， 2025， 457： 120920.
［70］Tavangar T， Hosseinpoor M， Marshall J S， et al. Four-way CFD-DEM coupling to simulate concrete pipe flow： mechanism of formation of lubrication layer［J］. Cement and Concrete Research， 2024， 179： 107479.
［71］Cao Guodong， Su Hongwei， Xie Sheng， et al. Numerical investigation on pumping behavior of fresh concrete by CFD-DEM， considering uneven distribution of aggregate［J］. Construction and Building Materials， 2025， 465： 140130.
［72］Liao Yuankun， Cheng Kai， Sun Wuhe， et al. Study on pumping wear characteristics of concrete pipeline based on CFD-DEM coupling［J］. Scientific Reports， 2023， 13（1）： 16119.
［73］Sun Zhenjiao， Chen Lianjun， Ma Guanguo， et al. Flow characteristics of moist-mixed materials for shotcrete： from experiment to CFD-DEM simulation［J］. Powder Technology， 2023， 428： 118821.
［74］Ma Hui， Ma Guanguo， Sun Zhenjiao， et al. Study on flow characteristics of pneumatic conveying of stiff shotcrete materials by CFD-DEM［J］. Results in Engineering， 2025： 105129.
［75］Sun Zhenjiao， Chen Lianjun， Ma Hui， et al. Study on the influence of elbow on the pneumatic conveying characteristics of stiff shotcrete materials by CFD-DEM［J］. Powder Technology， 2024， 443： 119937.
［76］Sun Zhenjiao， Chen Lianjun， Ma Hui， et al. Study on flow characteristics of vertical pneumatic conveying of stiff shotcrete materials based on CFD-DEM［J］. Powder Technology， 2024， 439： 119716.
［77］Ma Guanguo， Cai Guanghui， Sun Zhenjiao， et al. Effects of material properties on pneumatic conveying flow characteristics of stiff shotcrete materials［J］. Powder Technology， 2025，468： 121647.
［78］Sun Zhenjiao， Chen Lianjun， Gao Kang， et al. Additional pressure loss coefficient of pneumatic conveying of moist-mixed materials for shotcrete based on CFD-DEM method［J］. Journal of Building Engineering， 2023， 76： 107242.
［79］Chen Lianjun， Sun Zhenjiao， Ma Hui， et al. Energy loss caused by the elbow of stiff shotcrete pneumatic conveying based on response surface method and CFD-DEM［J］. Powder Technology， 2022， 408： 117726.
［80］Chen Lianjun， Sun Zhenjiao， Ma Hui， et al. Flow characteristics of pneumatic conveying of stiff shotcrete based on CFD-DEM method［J］. Powder Technology， 2022， 397： 117109.
［81］Cao Guodong， Li Zhuguo. Numerical flow simulation of fresh concrete with viscous granular material model and smoothed particle hydrodynamics［J］. Cement and Concrete Research， 2017， 100： 263-274.
［82］Xu Zhisong， Li Zhuguo， Jiang Fei. The applicability of SPH and MPS methods to numerical flow simulation of fresh cemen-titious materials［J］. Construction and Building Materials， 2021， 274： 121736.
［83］Wu Wanrong， Chen Wang， Lu Guoyi， et al. Research on rheological behavior of fresh concrete single-cylinder pumping based on SPH-DEM［J］. Scientific Reports， 2023， 13（1）： 20828.
［84］Chen Wang， Wu Wanrong， Lu Guoyi， et al. Simulation analysis of concrete pumping based on smooth particle hydrodynamics and discrete elements method coupling［J］. Materials， 2022， 15（12）： 4294.
［85］Peng Chong， Zhan Ling， Wu Wei， et al. A fully resolved SPH-DEM method for heterogeneous suspensions with arbitrary particle shape［J］. Powder Technology， 2021， 387： 509-526.
