Multi-physics Framework Research Articles

MultiRegionFoam: A Unified Multiphysics Framework for Multi-Region Coupled Continuum-Physical Problems

Abstract This paper presents a unified framework, called multiRegionFoam, for solving multiphysics problems of the multi-region coupling type within OpenFOAM (FOAM-extend). It is intended to supersede the existing solver with the same name. The design of the new framework is modular, allowing users to assemble a multiphysics problem region-by-region and coupling conditions interface-by-interface. The present approach allows users to choose between deploying either monolithic or partitioned interface coupling for each individual transport equation. The formulation of boundary conditions is generalised in the sense that their implementation is based on the mathematical jump/transmission conditions in the most general form for tensors of any rank. The present contribution focuses on the underlying mathematical model for interface coupled multiphysics problems, as well as on the software design and resulting code structure that enable a flexible and modular approach. Finally, deployment for different multi-region coupling cases is demonstrated, including conjugate heat, multiphase flows and fuel-cells. Source code: multiRegionFoam v1.1 [1], repository https://bitbucket.org/hmarschall/multiregionfoam/. Article highlights A novel multiphysics framework, called multiRegionFoam, has been developed for solving multi-region coupled problems in OpenFOAM. The design of the framework allows for a modular multiphysics setup with freedom of choice on the coupling strategy (partitioned vs. monolithic). Extension of the general transport equation by interface conditions enables a unified coupling approach.

Monte Carlo Workflow Unification for Nuclear Reactor Analysis with Metamodel-Driven Modeling

Monte Carlo (MC) transport codes are a cornerstone of nuclear reactor analysis frameworks, providing reference solutions and multigroup cross sections, and even as core components in multiphysics couplings. These applications can be seen in toolkits from the Nuclear Energy Advanced Modeling and Simulation program and the U.S. Nuclear Regulatory Commission’s BlueCRAB (Comprehensive Reactor Analysis Bundle). Contrary to their ubiquitousness in reactor physics modeling and simulation, popular MC codes, such as MCNP, Serpent, and KENO, are still reliant on antiquated textual input formats. These input languages use a plethora of keywords with terse syntax to specify all facets of a model, including its geometry, materials, physics settings, and tally options. This poses a steep learning curve and a poor user experience. Being tied to unique text-based input formats also significantly complicates programmatic input generation or modification that may be desired and/or required within a multiphysics framework. This work demonstrates how the development of programmatic interfaces for MC codes can support model unification and translation activities. Building on the Python application program interface (API) development of MCNPy, similar capabilities are being implemented for Serpent that are able to support model translation. In future work, the Serpent API capabilities will be made more robust and the work will be further expanded to include translations with KENO.

Multiphysics framework for cost-effective, long-term monitoring of carbon storage in a carbonate reservoir

We evaluate an effective and cost-efficient multiphysics approach for long-term monitoring of carbon storage in carbonate reservoirs. A key focus of our study is to advocate for a cost-effective, long-term monitoring strategy for carbon storage projects through the integration of surface and borehole multiphysics measurements. By leveraging technologies related to electromagnetic (EM) and gravity methods, we present a framework that addresses the monitoring of the dynamic behavior of injected CO2 over an extended period. The modeling setup integrates realistic static reservoir models with simulated dynamic saturation models to provide results as close as possible to real experimental conditions. Results demonstrate the high sensitivity of EM fields to changes in reservoir CO2 saturation, especially when surface-to-reservoir acquisition configurations are adopted. Additionally, gravity simulations, employing three-axis vector surface gravity measurements and borehole vector gravity, effectively capture density variations over time. Our proposed framework highlights the sequential use of seismic imaging for preinjection site characterization and the transition to EM and gravity surveys for continuous monitoring during and after the injection phases. The multiphysics simulation results performed on realistic carbon storage conditions contribute to the evolving landscape of effective geophysical CO2 monitoring technology for reliable long-term reservoir management.

Fomite disinfection using spray systems: A computational multi-physics framework

Disinfecting inanimate objects or materials carrying infectious agents, i.e., fomites, using spray systems reduces healthcare-associated infections in medical settings and community-acquired infections in non-medical environments. However, an accurate prediction of such systems is challenging as these systems embrace multi-physics phenomena depending on several parameters. Therefore, this paper presents a computational modeling-based multi-physics framework to evaluate the performance and effectiveness of spray systems employed in disinfecting fomites with non-porous hydrophilic surfaces. The framework includes four key phases: (i) atomizing the liquid disinfectant jet into the disinfectant droplets; (ii) interactions between disinfectant droplets and the surrounding air; (iii) impingements created by the disinfectant droplets on the fomite surface; (iv) interactions between the disinfectant depositions and pathogens causing fomite disinfection. The accuracy of the framework is evaluated using two sets of experimental data on the reduction of viable Bacillus atrophaeus spores over an 1800-second period. The results show that the framework can predict fomite disinfection via spray systems, with the deviations from the measured data being 2.73% and 2.38%. By presenting a detailed perception of the dynamics involved in fomite disinfection, this framework has the potential to improve public health practices and lead to the development of more effective and targeted disinfection strategies in diverse settings.

Investigation of the fission gas release and grain boundary percolation in oxide fuels: A COMSOL multiphysics-based study

In this study, we explore fission gas release (FGR) behaviour in oxide fuels using the COMSOL Multiphysics framework. Building upon the conventional Booth model, our model incorporates the influence of grain boundary network percolation on FGR. The microstructure of the fuel pellet is represented by a 2D axi-symmetric geometry. We investigate various factors affecting FGR, mainly includes bubble contact angle, resolution rate, radial position. This study aims to capture the physical phenomena observed in FGR experiments and assess the sensitivity of FGR to these parameters at both microscopic and macroscopic scales. Moreover, our model accounts for long-range percolation on the networked grain boundaries, a factor overlooked by the Booth model. The gas resolution of grain boundaries is also considered. Finally, we compare and analyze the results obtained from our model with those from the Booth model and other relevant models, aiming at enhancing our understanding of FGR behavior in oxide fuels.

Mechanics of polymers obtained by layered photopolymerization

The photopolymerization process is a high-precision and efficient technology to obtain solid polymers starting from a photosensible liquid resin made of monomer units. This technology is widely used in Additive Manufacturing (AM) to produce objects whose size can fall within the range 10−5−100 m. The outstanding potentialities of this technology can be harnessed to tailor the structure of a polymeric material by controlling how the light-induced polymerization process is performed, typically by operating on subsequent layers forming the final object. The present research illustrates the chemical-physics phenomena involved in the photopolymerization and presents a multi-physics framework and the related governing equations. Its implementation within a computational framework is developed and several simulations demonstrating the influence of the AM printing setup on the final microstructure of the obtained polymer are presented. It is shown that photopolymerization-based AM technology allows us to finely tune the mechanical properties distribution within the material domain, enabling the material's architecture to be tailored to the application of interest.

A powder-scale multiphysics framework for powder bed fusion of fiber-reinforced polymer composites

Additive manufacturing of fiber-reinforced polymer composites has garnered great interest due to its potential in fabricating functional products with lightweight characteristics and unique material properties. However, the major concern in polymer composites remains the presence of pore defects, as a thorough understanding of pore formation is insufficient. In this study, a powder-scale multiphysics framework has been developed to simulate the printing process of fiber-reinforced polymer composites in powder bed fusion additive manufacturing. This numerical framework involves various multiphysics phenomena such as particle flow dynamics of fiber-reinforced polymer composite powder, infrared laser–particle interaction, heat transfer, and multiphase fluid flow dynamics. The melt depths of one-layer glass fiber–reinforced polyamide 12 composite parts fabricated by selective laser sintering are measured to validate modelling predictions. The numerical framework is employed to conduct an in-depth investigation of pore formation mechanisms within printed composites. Our simulation results suggest that an increasing fiber weight fraction would lead to a lower densification rate, larger porosity, and lower pore sphericity in the composites.

Designing piezoelectric stretcher through multiphysics topology for enhanced photodynamic therapy in cancer treatment

This study presents an advancement in Photodynamic Therapy (PDT) by introducing piezoelectric stretchers designed to enhance tissue surface characteristics. With a focus on mitigating the impact of irregular tissue surfaces on light distribution, we propose a structural topology optimization method to design a stretcher that utilizes the piezoelectric effect for precise tissue stretching. The aim is to achieve uniform laser irradiance across treated tissue, thereby maximizing therapy efficiency. Our approach involves the formulation of finite element models that consider the piezoelectric effect and the elastic response in a multiphysics framework. Mesh convergence tests were conducted to strike a balance between accuracy and computational efficiency in evaluating the designed piezoelectric stretcher. The investigation into the application of piezoelectric stretchers for enhancing laser irradiance on non-uniform tissue reveals significant improvements in surface uniformity with increasing electric potential. Notably, the disparity between regions of high laser focusing and defocusing decreases as the stretcher expands, achieved through the application of higher voltages. The observed enhancement from no expansion to full expansion is quantified at 31 %. The implementation of electrically driven piezoelectric tissue expansion results in a more uniform tissue surface, leading to an augmentation of laser irradiance. In the absence of expansion, distinct areas of laser focus and near-zero irradiance are noted. Conversely, an increased potential yields a predominantly even surface, with 100 % extension achieving commendable laser irradiance uniformity.

Modeling the mechanical response of microelectromechanical system (MEMS)-based sensors to volatile alcohol vapors: A finite element analysis

The development of microelectromechanical system-based sensors, such as microcantilever sensors, has garnered considerable interest across various fields. Notably, there is a significant focus on the detection of volatile alcohol vapors, which holds promise in mitigating breath-related illnesses. This study employed finite element analysis to simulate the deflection of a silica-based microcantilever coated with polymethyl methacrylate in response to different volatile alcohol vapors (VAVs), such as methanol, ethanol, and isopropanol. A Multiphysics framework was used to analyze the time-dependent response of a microcantilever to different concentrations of VAVs incorporating fluid–structure interaction. This complex model integrated the aspects of laminar flow, solid mechanics, and transport of dilute species. Significant agreement has been achieved between finite element analysis-simulated results and the experimental findings that we had previously documented. This alignment revealed consistent trends, with methanol exhibiting higher levels than ethanol, followed by isopropanol, further validating the robustness and reliability of the sensor system in VAV detection.

Ultra-short pulse laser ablation of metals: A comprehensive 3D simulation perspective enlightening novel process insights

Intricate dynamics in ultra-short pulse laser ablation of metals necessitate deeper process understanding. This work presents an auspicious contribution in this direction, incorporating a sophisticated three-dimensional finite-volume simulation tool, building upon our previously validated models in continuous-wave laser material processing. Atop the existing multiphysics framework, a two-temperature and a Drude absorption model has been integrated. Focused on laser ablation of copper, preliminary results unveil novel perspectives on the dynamic interaction between thermal effects and material response. Surpassing limitations inherent in one- and two-dimensional descriptions, this model distinctively captures the complex interplay of electron heating, energy transfer to the lattice, and ensuing rapid phase transitions. Crucially, it complements existing insights into ablation mechanism by illustrating the influence of elusive temperature-dependent material properties, such as density and the bulk modulus for superheated liquid metal, on the process. While still in development, these advancements mark a promising stride towards a deeper process comprehension.

A self-powered strain sensor utilizing hydrogel-nanosheet composites, Zn foil, and silver-coated nylon

Self-powered strain sensing, using a combination of nanosheets and hydrogel, shows tremendous potential in the context of wearable electronic applications. However, achieving the desired multifunctionality of conductive nanosheets within the hydrogel material remains a significant challenge. Further research is needed to better understand the underlying physics mechanisms of the ionically conductive polymer battery and the various factors that influence its voltage output. In this study, we introduce a self-powered strain sensor that utilizes a combination of hydrogel, Zn foil, and silver-coated Nylon to create a Zinc-air battery. The hydrogel, composed of PAAm-PVA-GO, exhibits remarkable properties such as high elasticity(∼1000 %), adhesion(∼15kPa), and improved sensitivity to strains(0.58, 2.44). The hydrogel’s strong bonding behavior is due to the abundant hydroxyl groups generated by the redox activity. The strain-induced voltage output, as determined through experimental evaluation, demonstrates excellent repeatability(1000 cycles of 100 %). Additionally, we examine the impact of temperature and usage time on the output voltage. To gain further insight into the sensor’s electrical potential, we develop a simulation model based on the multiphysics framework, which aligns closely with the experimental findings. To demonstrate its practical application, we successfully apply this self-powered strain sensor for monitoring joint bending and throat movement.

Unraveling microforging principle during in situ shot-peening-assisted cold spray additive manufacturing aluminum alloy through a multi-physics framework

Cold spray (CS) is a highly potential solid-state additive manufacturing (AM) technique. In situ shot-peening-assisted CSAM was proposed to additively manufacture fully dense deposits using cost-effective and renewable nitrogen gas. The role of in situ shot-peening particles is critical but remains unclear. Here, the process was quantitatively modeled to visualize the dynamic deformation, energy conversion, as well as cell/sub-grain size and microhardness evolutions, compared to those during the conventional CSAM process, identifying the key role of in situ shot-peening particles in the AA6061 extreme deformation and microstructure characteristics during in situ shot-peening-assisted CSAM. High-fidelity modeling was verified fully by comparing the experimental and model-reproduced deformation profiles, cell/sub-grain size distributions, and increases in microhardness. The results show that the kinetic energy of in situ shot-peening particles was 470 times higher and dissipated mainly through AA6061 plastic deformation (86.36% of total energy), leading to significant enhancement of microhardness and tensile strength. Moreover, the mixing ratio of large-size SS410 particles required to create a fully dense deposit was evaluated from an energy perspective, in good agreement with the experiment. This study elucidates the microforging principle during in situ shot-peening-assisted CSAM, providing scientific guidelines for high-quality and low-cost CSAM of high-strength aluminum alloys.

Numerical simulation of the impact of different cushion gases on underground hydrogen storage in aquifers based on an experimentally-benchmarked equation-of-state

Underground hydrogen storage (UHS) in geological formations is a promising technology for large-scale hydrogen energy storage. In this study we focus on UHS in saline aquifers. Although lessons were learned from similar studies, including geological carbon sequestration and underground gas storage, the unique thermodynamic and physical properties of hydrogen distinguish UHS from the other subsurface storage projects. We developed a two-phase, three-component reservoir simulator, which incorporated essential physics based on the fully coupled multi-physics framework of the Delft Advanced Reservoir Simulation (DARSim). Properties of fluid mixtures were computed using the GERG-2008 equation of state (EoS), in which the parameters were determined by fitting laboratory data. The simulation results demonstrated the impact of different cushion gases (CO2, CH4, and N2) on UHS. Most hydrogen stayed in the gaseous phase at the top of the aquifer when CH4 and N2 were used as the cushion gas. Conversely, hydrogen-rich fingers were observed in the aqueous phase when CO2 was used as the cushion gas, because dissolved CO2 increased brine density, leading to density-driven downward convection which was favorable for hydrogen dissolution into the aqueous phase. The highest purity of produced hydrogen was observed when CO2 was used as the cushion gas, whereas using CH4 and N2 as the cushion gas was favorable for the hydrogen production rate and mobility. This work is the first study that utilizes an EoS-based reservoir simulator to investigate hydrogen's flow patterns and interactions with cushion gases in an underground storage system. Specifically, the productivity and retrievability of hydrogen in a two-phase, three-component UHS system were analyzed in detail. The developed reservoir simulation tool and research findings from this study will be valuable to support decision making in practical UHS projects.

Modular Framework for the Solution of Boundary-coupled Multiphysics Problems

This paper presents a modular multiphysics framework developed for OpenFOAM. The framework is built around an iterative implicit coupling scheme based on a multi-region partitioned approach. This scheme allows the implementation of formal implicit time-marching schemes, which improves the stability of strongly interacting coupled problems. This methodology allows physical interactions to be handled through specifically designed interface boundary conditions. It also allows region-specific solvers to be implemented as modular class solvers. The coupling methodology is handled with a main program that manages solver-specific actions. The aim of this framework is to facilitate the implementation and testing of new multiphysics coupling problems in an integrated code structure. To show the capabilities of the framework to integrate new physics, solvers and boundary conditions requirements are discussed. Also, three validated examples involving fluid-structure interactions, conjugate heat transfer, and fluid-structure-thermal interactions are presented. Although all these problems are boundary-coupled multiphysics problems, the framework is conceptually not limited to this kind of problems. The benefit of this work to the OpenFOAM community is a general and modular framework that facilitates the setup and solution of diversified multiphysics problems, and that illustrates the implementation of modular interface boundary conditions between physics regions.

Verification and validation of the open-source plasma fluid code: Zapdos

Zapdos is an open-source finite element plasma fluid solver based on the MOOSE multiphysics framework. This paper outlines Zapdos verification, benchmarking, and validation efforts for 1D and 2D RF capacitively-coupled plasma discharge models for mid-range pressures (0.1 - 1 Torr). The verification process involved using the method of manufactured solutions to assess Zapdos spatial and temporal error convergence. L2 errors ranged from 10−2 to 10−4, while the convergence's slope were in agreement with the predicted slopes for the tested variable and time integration orders. The benchmarking process involved comparisons to previously results from the validated finite element code, LSODI [1–3]. These works included 1D and 2D simulations for a range of plasma parameters (densities, temperatures, voltage, etc.). For the 1D cases, Zapdos and LSODI results were in very good agreement. In the 2D cases, variable behaviors matched, with slight discrepancies in peak values. The validation process involved comparisons to experimental works including electron density measurements by microwave interferometry [4] and metastable density measurements by planar laser-induced fluorescence imaging [5]. Results shown reasonable agreement at higher pressure, with results starting to diverge at low pressures. Probable causes for this diverges are the limitation of the fluid assumption for plasmas at low pressure, or the need for more robust boundary conditions. Overall, Zapdos shown reasonable results for the verification, benchmarking, and validation efforts, and Zapdos can be downloaded at https://github.com/shannon-lab/zapdos. Program summaryProgram Title: ZapdosCPC Library link to program files:https://doi.org/10.17632/j76jr9m66p.1Developer's repository link:https://github.com/shannon-lab/zapdosLicensing provisions: LGPL-2.1Programming language: C++, PythonSupplementary material:shannon-lab.github.io/zapdosNature of problem: For the plasma computational community, multiphysics packages are needed for the highly couple physics seen in plasma problems (e.g. chemistry, fluid flow, heat transfer, electromagnetic, etc.). One limiting factor for these types of computational research is the high cost to purchase the licenses needed for established multiphysics packages, such as COMSOL. An additional problem that can arise is the limited ability to add new physics to these existing frameworks, in such a way that new physics can be easily coupled to current models. For any new software that wants to tackle these problems, the question of verification and validation for these codes needs to be addressed.Solution method: Zapdos is an open-source finite element plasma fluid solver based on the MOOSE multiphysics framework. MOOSE (Multiphysics Object Oriented Simulation Environment) solves highly nonlinear, tightly coupled sets of partial differential equations (PDEs) and houses multiple physics applications that can be easily coupled together. Zapdos, along with the MOOSE ecosystem, is all free, open-source, and completing customizable with no black box components. Zapdos has gone through verification and validation for applications common in the plasma computational community.Additional comments including restrictions and unusual features: Zapdos, along with MOOSE and other MOOSE applications, require an Unix based operating system.

Exploring the benefits of functionally graded carbon nanotubes (FG-CNTs) as a platform for targeted drug delivery systems

Background and ObjectiveModern therapeutic systems have benefited from the use of functionally graded carbon nanotubes (FG-CNTs) to enhance their efficiency. Various studies have shown that the study of dynamic response and stability of fluid-conveying FG-nanotubes can be improved by considering a Multiphysics framework for the modeling of such a complex biological environment. However, despite noticing important aspects in modeling, the previous studies have drawbacks such as underrepresenting the effect of varying composition of the nanotube on magnetic drug release in drug delivery systems. The present work has the novelty of studying the combined effects of fluid flow, magnetic field, small-scale parameters, and functionally graded material on the performance of FG-CNTs for drug delivery applications. Additionally, the lack of an inclusive parametric study is resolved in the present study by evaluating the significance of different geometrical and physical parameters. As such, the achievements support the development of an efficient drug delivery treatment. MethodsThe Euler–Bernoulli beam theory is implemented to model the nanotube and Hamilton's principle based on Eringen's nonlocal elasticity theory is used to derive the constitutive equations of motion. To add the effect of slip velocity on the CNT's wall, a correction factor is applied to velocity based on the Beskok–Karniadakis model. Resultsdemonstrate that the dimensionless critical flow velocity increases by 227% as the magnetic field intensity increases from 0 to 20 T, and improves the system stability. On the contrary, drug loading on the CNT has the opposite effect, as the critical velocity decreases from 10.1 to 8.38 using a linear function for drug loading, and it decreases to 7.95 using an exponential function. By employing a hybrid load distribution, an optimum material distribution can be achieved. ConclusionsTo benefit from the potential of CNTs in drug delivery systems while minimizing the instability problems, a suitable design for the drug loading is required prior to the clinical implementation of the nanotube.

Multiphysics Modeling of Plasmon-Enhanced All-Optical Helicity-Dependent Switching.

In this work, we propose a multiphysics approach to simulate all-optical helicity-dependent switching induced by the local hot spots of plasmonic nanostructures. Due to the plasmonic resonance of an array of gold nanodisks, strong electromagnetic fields are generated within the magnetic recording media underneath the gold nanodisks. We construct a multiphysics framework considering the opto-magnetic and opto-thermal effects, and then model the magnetization switching using the Monte Carlo method. Our approach bridges the gap between plasmonic nanostructure design and magnetization switching modeling, allowing for the simulation of helicity-dependent, nanoscale magnetization switching in the presence of localized surface plasmons.

Hygroscopic phase field fracture modelling of composite materials

This paper investigates the effect of moisture content upon the degradation behaviour of composite materials. A coupled phase field framework considering moisture diffusion, hygroscopic expansion, and fracture behaviour is developed. This multi-physics framework is used to explore the damage evolution of composite materials, spanning the micro-, meso- and macro-scales. The micro-scale unit-cell model shows how the mismatch between the hygroscopic expansion of fibre and matrix leads to interface debonding. From the meso-scale ply-level model, we learn that the distribution of fibres has a minor influence on the material properties, while increasing moisture content facilitates interface debonding. The macro-scale laminate-level model shows that moisture induces a higher degree of damage on the longitudinal ply relative to the transverse ply. This work opens a new avenue to understand and predict environmentally assisted degradation in composite materials.

Multi-physics simulation of 3D in-flight ice-shedding

In-flight ice accretion may possibly jeopardize the safety of fixed- and rotary-wing aircraft. Icing can possibly occur if supercooled water droplets in clouds impinge on the aircraft surfaces and freeze upon impact. It may result in instrument failures and degradation of the aerodynamic performances. A major problem related to ice accretion is the possibility of ice shedding from the main body and impacting other parts of the aircraft or being ingested by the engines. In fixed-wing aircraft, shedding is caused by the action of the aerodynamic forces or the activation of an Ice Protection System. In the present work, a multi-physics framework is presented to simulate ice accretion and shedding from wings and engine nacelles. The aerodynamics is computed using the open-source toolkit SU2 (Economon et al., 2015)[1] . Cloud droplet trajectories are computed using the arbitrary-precision Lagrangian in-house solver PoliDrop. Then, the in-house ice accretion toolkit PoliMIce (Gori et al., 2015) is used to determine the ice layer. An algebraic level-set approach with iterative volume mesh refinement has been developed to extract the ice shape from the iced wing geometry. A FEM structural analysis is performed on the accreted ice shape by means of the open-source code MoFEM (Kaczmarczyk et al., 2014, 2020) [2]. Internal stresses within the ice geometry due to aerodynamic forces are computed. Three-dimensional ice accretion simulations are performed to check the validity of the present approach.

Numerical investigation on the spewing mechanism of earth pressure balance shield in a high‐pressure water‐rich sand stratum

AbstractThe spewing of a screw conveyor easily occurs from the earth pressure balance (called EPB) shield in a water‐rich sand stratum. This may lead to the collapse of the tunnel face and even serious subsidence of the ground surface. To understand the spewing mechanism of the shield screw conveyor and explore the critical hydraulic condition of soil spewing in a shield–soil chamber, a simplified theoretical model for the spewing of the screw conveyor was developed based on the equation of groundwater flow in the screw conveyor under turbulent state. Thus, coupling Darcy's law with Brinkman's equation, this model was implemented within the COMSOL Multiphysics framework. The underground water flow in the shield screw conveyor was simulated so as to obtain its velocity and flow rate. Numerical simulations show that the water pressure distribution is concentrated in the lower part of the soil chamber after the groundwater enters the soil chamber. When the groundwater enters the screw conveyor, its pressure gradually decreases along the direction of the screw conveyor. When the water flow reaches the stratum–shield interface, the flow velocity changes markedly: first increases and concentrates at the entrance of the lower soil chamber, plummets and stabilizes gradually, and increases again at the exit. The soil chamber and screw conveyor are significantly depressurized. It is also found that the soil permeability coefficient can be reduced to k < 2.6 × 10−4 cm/s through appropriate soil improvement, which can effectively prevent the occurrence of spewing disasters.