In this work, we introduce a flexible stereolithography (STL)-based approach for uniform triangularization of particle surfaces and integrate it into our in-house lattice Boltzmann interpolated bounce-back (LBM-IBB) code. In this lattice Boltzmann interpolated bounce-back Stereolithography (LB-IBB-STL) approach, the solid particle is constructed externally using third-party software and then integrated into the Lattice Boltzmann (LB) framework where it is treated as object boundary in the particle-fluid system as in traditional LBM method. Our approach offers three key advantages over conventional particle-fluid numerical schemes: (i) it separates object geometry definition from the simulation code, (ii) with minimal modifications, it enables us to study several different particle shapes such as spherical, planar (or flake-like), and polyhedron particles, and (iii) simplified facet representations of Platonic polyhedrons markedly decrease the computational expense of simulations compared with the spheres. To validate our LB-IBB-STL approach, we conducted several numerical experiments, including the settling of spherical particles and polyhedron particles in a viscous fluid. The results show good agreement with the published data, with good accuracy. Grid independence tests confirm the reliability of the LB-IBB-STL approach.

This study employs interface-resolved direct numerical simulations to investigate the settling characteristics of non-spherical particles in homogeneous isotropic turbulence, focusing on the effect of particle shape on settling dynamics. Three particle shapes are considered and compared: spherical particles, ellipsoidal particles with aspect ratio X = 2, and cylindrical particles with aspect ratio X = 1 and X = 2. In addition, the effect of the Galileo number (Ga) is considered. We released multiple particles at a low volume fraction (0.1%) to gather robust statistics while minimizing interactions, in order to mimic the settling of an isolated particle. Results show that the particle shape plays a critical role in the orientation dynamics: ellipsoidal particles exhibit a pronounced preferential orientation with the major axis perpendicular to the direction of gravity that intensifies with increasing Ga, while cylindrical particles (X = 1) remain randomly oriented. Notably, a bifurcation is observed for cylindrical particles (X = 2) as Ga increases: they maintain random orientations at low Ga but transition to a preferential orientation with the major axis perpendicular to the direction of gravity at high Ga, revealing a nonlinear coupling between gravitational forcing and particle elongation. The mean settling velocity reveals a clear ordering: spherical particles settle the fastest, followed by ellipsoidal particles, while cylindrical particles settle the slowest. We find that this reduction in settling velocity for non-spherical particles arises from an increased pressure drag and the greater viscous dissipation associated with the unsteady rotational motion. Furthermore, the ordering of settling velocities in the turbulent flow is found to differ from that observed in a quiescent fluid. These findings further elucidate the influence of particle shape on turbulence-particle interactions and subsequently the settling velocity of non-spherical particles in turbulent flows.

Acoustic agglomeration is a promising treatment technology for small particles and droplets, due to its non-intrusive operation, rapid response, high-temperature compatibility, and pollution-free operation. The agglomeration process under coupled actions of acoustic wave and gravity is complex, involving multiple physical mechanisms, including natural gravitational coalescence, sound wave-induced orthokinetic interaction and acoustic wake effect, etc. A rigorous theoretical description of the agglomeration kernel when these mechanisms act together is not yet available. In this work, we derive an agglomeration kernel, based on the Stokes-flow assumption, that couples rigorously the gravitational coalescence and time-dependent orthokinetic interaction. The resulting kernel is capable of describing the influence of the angle (θ) between the direction of acoustic wave and gravity. It is shown that the agglomeration kernel increases with θ, with the coupling effect expressed in terms of the ratio of the gravitational to the orthokinetic relative velocity. Further analysis reveals that, when θ=0 (i.e., the parallel case), a threshold for sound pressure level (SPL) exists, below which the orthokinetic interaction does not contribute to the overall collision kernel. Numerical simulations based on the super-droplet method further verify that the newly derived kernel can better reproduce experimental data and capture the threshold behavior, with its prediction accuracy surpassing that of the existing empirical kernels.

The Discrete Unified Gas Kinetic Scheme (DUGKS) coupled with the Phase-Field Method (PFM) using a specific model (here the Cahn-Hilliard (CH) equation is adopted) offers a robust and accurate framework for simulating two-fluid flows. These simulations require resolving both small-scale flow structures and dynamic interfaces, resulting in high computational costs, especially for droplet-laden turbulent channel flow. Graphics Processing Units (GPUs), with thousands of parallel cores, are well-suited for accelerating grid-based numerical methods, offering the potential for substantial runtime reduction. In this work, we develop a multi-GPU-accelerated framework of an existing CPU-based DUGKS-PFM-CH solver. Memory optimization strategies are employed to improve data access efficiency and reduce GPU memory usage. The accuracy and stability of the multi-GPU solver are validated through a series of benchmark tests, including a stationary droplet, three-dimensional Rayleigh-Taylor instability, and a droplet-laden turbulent channel flow. It is shown that a single P100 GPU provides performance equivalent to at least 100 Intel Xeon 6148 CPU cores. Furthermore, the implementation achieves near-ideal strong scaling, highlighting the favorable parallel efficiency of the DUGKS framework.

Accurately preserving the volume of dispersed droplets remains a significant challenge in phase-field simulations of droplet-laden turbulence, particularly under conditions involving strong interfacial deformation and breakup. This issue was systematically documented in our recent comparative study (Li et al., 2026), which showed that droplet-volume loss becomes increasingly severe as the Weber number increases. However, an effective remedy to this problem is still lacking. In the present work, we first assess the performance of several existing volume-correction strategies in direct numerical simulations of droplet-laden homogeneous isotropic turbulence. The results demonstrate that, at sufficiently high Weber numbers, none of the existing models can satisfactorily preserve droplet volume. To overcome this limitation, we propose a simple yet effective modification of the conservative Allen-Cahn equation through the introduction of a curvature-dependent counter-diffusion correction. The performance of the proposed model is subsequently evaluated using the same turbulent droplet-laden flow configuration over a range of Weber numbers. The results show that the proposed approach preserves droplet volume in a statistical sense while avoiding common adverse effects, such as numerical instability, violation of global mass conservation, increased computational cost, artificial coarsening, and enhanced spurious velocities.

Recently, flow-reversal mechanisms in Rayleigh-B & eacute;nard (RB) convection and controlling strategies via modifying local temperature boundaries have received increasing attention due to the impact on heat-transfer efficiency and extreme eruption events. We consider an alternative possibility of altering fluid density: an added scalar field that induces double-diffusive convection, implemented by imposing local iso-concentration bands on the horizontal plates. In addition to the Rayleigh number ( ${\textit{Ra}}$ ) and Prandtl number ( ${\textit{Pr}}$ ), the system is governed by the Lewis number ( $Le$ ), buoyancy ratio ( $Br$ ), normalised bandwidth ( $\delta$ ) and normalised band-centre-to-midline distance ( $c$ ). We examine the influence of $\delta$ and $c$ on flow reversal at ${\textit{Ra}}=5\times 10<^>7$ , ${\textit{Pr}}=2$ , $Le =1$ and ${\textit{Br}}=1.5$ . Paired bands effectively reduce reversal frequency, with stronger suppression for larger $\delta$ ; the optimal band position is $c=0.2$ . Fourier mode analysis reveals a previously underappreciated role of the $3\times 3$ roll structure in reversal suppression, whose mean energy correlates positively with the single-roll structure. In standard RB convection, turbulence destabilises the symmetric $2\times 2$ roll configuration, causing frequent reversals owing to competition with asymmetric (1, 1) and (3, 3) modes. The concentration bands enhance the (1, 1) and (3, 3) modal energies, especially at the optimal band position, producing a steady mean flow structure comprising a large-scale circulation and four corner rolls. Despite the local boundary modification, scaling laws for the response parameters (Nusselt number ( ${\textit{Nu}}$ ) and Reynolds number ( ${\textit{Re}}$ )) remain close to standard RB convection: ${\textit{Nu}}\sim Ra<^>{1/3}$ and ${\textit{Re}}\sim Ra<^>{4/9}Pr<^>{-2/3}$ . These findings demonstrate an effective approach to suppress flow reversal and alter heat transfer efficiency.

We perform numerical simulations of forced homogeneous isotropic turbulence over a range of bulk viscosities, Reynolds numbers and Mach numbers to investigate the scaling of key flow statistics. Using the Helmholtz decomposition, we analyse the scalings of Favre-averaged turbulent kinetic energy (TKE), root-mean-square (r.m.s.) pressure, pressure dilatation, dilatational dissipation and higher-order velocity-gradient moments. Additionally, new models are proposed for the pressure-dilatation term and the bulk-viscosity dependence of dilatational dissipation. Although the solenoidal and dilatational components of the Favre-averaged TKE are not strictly orthogonal, our numerical results demonstrate that their ratio is well approximated by the squared ratio of the corresponding r.m.s. velocities. The r.m.s. pressure approaches the pseudo-sound scaling as bulk viscosity increases. Within the Donzis r.m.s. pressure model (Donzis & John 2020 Phys. Rev. Fluids 5(8), 084609), we find that the solenoidal contribution becomes dominant for large bulk viscosity. Pressure dilatation is found to depart systematically from pseudo-sound predictions: without bulk viscosity it favours transfer from kinetic to internal energy, while finite bulk viscosity can reverse this transfer at high Mach numbers. The scaling exponent of dilatational dissipation is shown to vary with bulk viscosity, enabling a corrected model for its exponent and prefactor. Velocity-gradient skewness and flatness reveal that the onset of shocklet-induced divergence is delayed with increasing bulk viscosity and may be suppressed entirely. The results extend recent velocity-ratio-based scaling frameworks and provide modelling insights into compressible turbulence.

In this paper, a discrete unified gas kinetic scheme (DUGKS) is developed based on low-Mach-number (LMN) Navier-Stokes-Fourier (NSF) equations for closed systems. The proposed scheme takes advantage of the mesoscopic numerical framework, in which a double distribution function model is adopted to recover the macroscopic continuity, momentum, and energy equations under the LMN approximation. Based on a decoupled formulation of the LMN equations, thermal pressure is separated from momentum evolution. This framework enables the introduction of a numerical Mach number for the discrete velocity set so that the timestep size for the flow simulation is not constrained by the physical speed of sound. Furthermore, the Hermite expansion orders of the equilibrium distribution functions can be reduced for computational efficiency. Two optimized sets of discrete particle velocity models are used, namely, the D2V7A5 velocity set is employed for the g distribution function to simulate dynamic pressure and momentum, and the D2V4A3 set for the h distribution function to recover temperature. These reduced velocity sets are sufficient since higher-order Mach number terms are neglected under the LMN approximation. The separation of dynamic pressure from the thermodynamic pressure and the use of reduced Hermite quadrature orders have significantly improved the computational efficiency. To validate the proposed scheme, we consider several canonical benchmark cases characterized by strong thermal variation and buoyancy-driven flows. The numerical results are compared with the solutions from the fully compressible scheme (FCS) and reference data from the literature. The total speed-up of our proposed scheme is about 557.27 and 8.89, when compared to FCS, with the normalized temperature variation epsilon at 0.01 and 0.6, respectively. In the above speed-up, the use of numerical Mach numbers contributes to a factor of 152.87 and 2.66, respectively.

Quantitative prediction of the intensity of rainfall events (light or heavy) has remained a challenge in Numerical Weather Prediction (NWP) models. For the first time, the mean coefficient of diffusional growth rate ( c_m ) is calculated using a Eulerian-Lagrangian particle-based model on in situ airborne measurement data from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) during monsoon over the Indian sub-continent. The results show that c_m varies in the range of ∼ 0.25× 10^-3 - 1.5× 10^-3 (cm s^-1 ). The generic problem of overestimation of light rain in NWP models might be related to the choice of c_m in the model. It is also shown from a direct numerical simulation (DNS) experiment using small-scale model that relative dispersion ( ϵ ) is constrained with average values in the range of ∼ 0.2 - 0.37 ( ∼ 0.1 - 0.26) in less humid (more humid) conditions. This is in agreement with in situ airborne observation ( ϵ ∼ 0.36) and previous studies over the Indian sub-continent. The linear relationship between relative dispersion ( ϵ ) and cloud droplet number concentration (NC) is obtained using CAIPEEX. The present study compares different exciting parameterizations for the cloud-to-rain “autoconversion” and effective radius using a sophisticated parcel-DNS model guided by CAIPEEX observation. The dispersion-based ‘autoconversion’ and effective radius parameterization schemes for the Indian region must be useful for the calculation of Indian summer monsoon precipitation in the general circulation model. The present study also provides valuable guidance for parameterizing the effective radius, which is important for the radiation scheme.

In this paper, an immersed boundary-discrete unified gas-kinetic scheme (IB-DUGKS) is developed for nonOberbeck-Boussinesq (NOB) natural convection with curved surfaces. A double distribution function model with the Bhatnagar-Gross-Krook (BGK) collision model is employed with the first distribution function representing the density and velocity fields, and the second distribution function determining the total energy. To incorporate the IB force and the heat source/sink, the external forcing term and an extra source term are introduced to the kinetic model. The IB forcing term only contributes to the leading order of the momentum and energy equation. By proper design, the source term plays a dual role, it includes the IB source/sink in the energy equation, and it allows an arbitrary Prandtl number by adjusting the heat flux term, demonstrating a great flexibility of mesoscopic methods particularly in treating thermal coupling. This IB-DUGKS enables the simulation of NOB natural convection flows, governed by the fully compressible Navier-Stokes-Fourier system. Simulations of natural convection between the outer square cavity and inner hot cylinders are performed to investigate the NOB effect. Both OB and NOB flows can be considered with the current scheme by selecting different relative temperature differences. The numerical results are in excellent agreement with the literature results, indicating that the current IB-DUGKS is accurate and robust for NOB thermal flow simulations. Finally, the NOB effects are demonstrated using the temperature field, velocity field, and overall heat transfer by contrasting the NOB solutions with the corresponding OB solutions.

In this work, a viscoelastic lattice Boltzmann flux solver (VLBFS) with log-conformation representation is proposed for simulating the incompressible flows of a viscoelastic fluid at high Weissenberg number conditions. Compared with the original lattice Boltzmann flux solver (LBFS), the present method has two main new features. First, the method solves the polymer constitutive equations with log-conformation representation. Second, an upwind-biased scheme is incorporated in the interpolation when performing flux reconstructions at the cell interface. With the aid of these two treatments, the numerical stability of VLBFS is significantly improved, making it capable of solving high Weissenberg number problems (HWNP). Compared with using the lattice Boltzmann method (LBM) to solve the viscoelastic fluid flow, VLBFS inherits the advantages of LBFS, such as flexible mesh generation, decoupling of the grid spacing and time interval, and low memory requirement. VLBFS can also precisely recover the macroscopic constitutive equation. The present method has been critically validated using three benchmark cases, namely, the plane Poiseuille flow, lid-driven cavity flow, and 4:1 abrupt planar contraction flow. The numerical results fully demonstrate the solver’s powerful ability in simulating HWNP.

The demand for separating and analysing rare target cells is increasing dramatically for vital applications such as cancer treatment and cell-based therapies. However, there remains a grand challenge for high-throughput and label-free segregation of lesion cells with similar sizes. Cancer cells with different invasiveness usually manifest distinct deformability. In this work, we employ a hydrogel microparticle system with similar sizes but varied stiffness to mimic cancer cells and examine in situ their deformation and focusing under microfluidic flow. We first demonstrate the similar focusing behaviour of hydrogel microparticles and cancer cells in confined flow that is dominated by deformability-induced lateral migration. The deformation, orientation and focusing position of hydrogel microparticles in microfluidic flow under different Reynolds numbers are then systematically observed and measured using a high-speed camera. Linear correlations of the Taylor deformation and tilt angle of hydrogel microparticles with the capillary number are revealed, consistent with theoretical predictions. Detailed analysis of the dependence of particle focusing on the flow rate and particle stiffness enables us to identify a linear scaling between the equilibrium focusing position and the major axis of the deformed microparticles, which is uniquely determined by the capillary number. Our findings provide insights into the focusing and dynamics of soft beads, such as cells and hydrogel microparticles, under confined flow, and pave the way for applications including the separation and identification of circulating tumour cells, drug delivery and controlled drug release.

Most high-order computational fluid dynamics methods for compressible flows are based on the Riemann solver for the flux evaluation and high-order interpolation or reconstruction such as the Weighted Essential Non-Oscillatory (WENO) scheme for spatial accuracy. The advantage of this kind of combination is the easy implementation and the ability to achieve the required spatial accuracy. However, despite the extensive research on high-order spatial reconstruction in the past, solvers coupling high-order space and time schemes have not been systematically evaluated. In this paper, based on the same fifth-order finite volume method (FVM), comparisons of the performance of the same flux solver with different reconstructions and the same reconstruction but different flux solvers are carried out on a structured mesh. For reconstruction, the TENO scheme and classic WENO-Z reconstruction have been chosen as representative methods. Meanwhile, for the flux solver, Lax-Friedrichs (LF) Riemann solver, HLLC solver, and GKS are considered. Through a serious of simulated comparison cases, the unique characteristics of GKS and TENO have been demonstrated. Overall, the comparisons suggest that proper spatial and temporal coupling is important for accurate shock and vortex capturing.

The coagulational growth of particles, governed by the population balance equation (PBE), is essential for powder production. The discrete bin methods for solving the PBE consider bin-based pair-interactions, where the effects of coagulation events between two given bins on the particle size distribution are evaluated in sequence to cover all independent bin pairs. In this paper, we show that an analytical solution can be obtained when coagulation events between a specific pair of bins are considered. This analytical solution allows us to propose a set of improved methods, such as bin integral methods with analytical solutions based on constant (BIMAS) or extended-linear (BIMAS-L) bin-wise distributions. The unique features of the proposed methods include the assurance of positive-definite bin number density or mass density (i.e., physical realizability condition), unconditional numerical stability, and low numerical dissipation. A quantitative metric is introduced to thoroughly analyze the convergence and accuracy characteristics of BIMAS and BIMAS-L for both the hydrodynamic and Golovin kernels. With the Golovin kernel, it is shown that, at large time step sizes, BIMAS and BIMAS-L perform better than the upstream flux method, linear flux method and linear discrete method. With the hydrodynamic (Long) and the Brownian kernel, the numerical results also demonstrate the advantages of the new methods in terms of numerical stability and accuracy, especially when using large time step size. It should be emphasized that the new methods guarantee unconditional numerical stability in all cases, whereas the other methods may require a limiter at large time step sizes to ensure physical realizability.

In this paper, a viscoelastic lattice Boltzmann flux solver (VLBFS) is developed to simulate incompressible flows of viscoelastic fluids with linear and non-linear constitutive models. In this method, the macroscopic equations are solved by the finite volume method, where the fluxes at the cell interface are evaluated by local reconstruction of the solutions of lattice Boltzmann equations (LBE). Two sets of distribution functions are introduced to reconstruct the cell-interface fluxes, one used for mass and momentum fluxes and the other for the conformation tensor flux in the polymer constitutive equation. The elastic-viscous stress splitting (EVSS) and the solvent-polymer stress splitting (SPSS) techniques are incorporated into the present LBFS to improve the numerical stability. The standard lattice Boltzmann method (LBM) for solving the polymer constitutive equation contains redundant diffusion terms, but this problem is resolved in the current LBFS by setting the relaxation time corresponding to the true diffusion-free limit thus the correct polymer constitutive equation can be recovered. Furthermore, VLBFS eliminates other disadvantages of the standard LBM, such as the LBM on-grid advection coupling the time interval with grid spacing, complicated treatment of the mesoscopic boundary conditions, dependence on uniform grids, and the larger memory requirement due to solving the phase-space discrete distributions. Several flows of a viscoelastic fluid, namely, the two-dimensional plane Poiseuille flow, two-dimensional simplified four-roll mill flows, and three-dimensional Taylor-Green vortex flows, are considered to investigate the accuracy and stability of the present method. The results are found to be in good agreement with the analytical solutions and the previous numerical results. Numerical error analyses show that the present method owns a second-order accuracy in space. The developed VLBFS extends the application domain of LBFS and serves as a basis for simulating viscoelastic flows at high Weissenberg numbers.

The lattice Boltzmann method has become a popular tool for simulating complex flows, including incompressible turbulent flows; however, as an artificial compressibility method, it can generate spurious pressure oscillations whose impact on the statistics of incompressible turbulence has not been systematically examined. In this work, we propose a theoretical approach to analyse the origin of compressibility-induced oscillations (CIOs) and explore ways to suppress or remove them. We begin by decomposing the velocity field and pressure field each into the solenoidal component and the compressive component, and then study the evolution of these two components analytically and numerically. The analysis yields an evolution equation of the mean-square pressure fluctuation which reveals several coupling effects of the two components. The evolution equation suggests that increasing the bulk-to-shear viscosity ratio can suppress CIOs, which is confirmed by numerical simulations. Furthermore, based on the derived evolution equation and data from the simulation, a model is developed to predict the long-term behaviours of the mean-square pressure fluctuations. In the case of decaying turbulence in a periodic domain, we show that the Helmholtz–Hodge decomposition can be used to obtain the solenoidal components reflecting the true evolution of incompressible turbulent flow, from the mesoscopic artificial compressibility approach. The study provides general theoretical guidelines to understand, suppress and even remove CIOs in other related pseudo-compressibility methods.

Based on the two-phase macroscopic governing equations in the phase field model, the governing equations and analytical solutions for the steady-state layered Poiseuille flows in the diffuse interface (DI) model are derived and analyzed. Then, based on three dynamic viscosity models commonly used in the literature, the corresponding analytical solutions of the velocity profiles are obtained. Under the condition of high dynamic viscosity ratio, the analytical solution of the DI model may be significantly different from that of the sharp interface (SI) model, and the degree of deviation depends on the dynamic viscosity model and the interfacial thickness. Therefore, the numerical simulation of layered Poiseuille flow with the DI model should be compared with the analytical solution of the DI model with the same dynamic viscosity model. A direct comparison of the numerical solution results with the SI analytical solution could misinterpret the model error with the numerical error. In addition, the direct numerical simulation data and the DI analytical solutions agree well, which validates the theoretical results. Finally, a new set of symmetrical dynamic viscosity models is proposed and recommended for the simulation of two-phase flows in the DI model, which makes both the viscosity profiles and velocity profiles close to the SI model.

This work presents a macroscopic model for the flow of two immiscible and incompressible fluids within inhomogeneous porous media. At the pore scale, the flow is governed by the full Navier-Stokes equations while the phase interface evolution is described by the Cahn-Hilliard equation. Applying the volume averaging method, we rigorously derive upscaled equations that characterize the Darcy-scale behavior of the two-phase system. The derivation yields unclosed terms originating from spatial derivations, which are subsequently closed by modeling them as functions of averaged quantities and specific transport coefficients. These coefficients are evaluated by solving localized closure problems defined on representative elementary volumes (REVs). A key contribution of this study is the formal incorporation of wetting behavior into the averaged chemical potential. We further discuss the theoretical distinctions between the proposed framework and standard empirical two-phase Darcy models. Finally, numerical simulations of the upscaled equations are performed, demonstrating the model's capability to capture essential two-phase flow characteristics in porous media.

The preference for particles to accumulate at specific regions in the near-wall part is a widely observed phenomenon in wall-bounded turbulence. Unlike small particles more frequently found in low-speed streaks, finite-size particles can accumulate in either low-speed or high-speed streaks. However, mechanisms and influencing factors leading to the different preferential concentration locations still need to be clarified. The present study conducts particle-resolved direct numerical simulations of particle-laden turbulent channel flows to provide a better understanding of this seemingly puzzling behaviour of preferential accumulation. These simulations cover different particle-to-fluid density ratios, particle volume fractions, particle sizes and degrees of sedimentation intensity. We find that the large particle size is the crucial factor that results in particles accumulating in high-speed streaks. Large particles not only are difficult to be conveyed by the quasi-streamwise vortices to low-speed streaks but also can escape from the near-wall region before moving spanwisely out from high-speed streaks. The sedimentation effect allows particles to gather closer to the channel wall and stay longer in the near-wall regions, reinforcing the sweeping mechanism of quasi-streamwise vortices that transport particles from high- to low-speed streaks. As a result, sedimenting particles tend to accumulate in the low-speed streaks.

Bletilla striata, a member of the family Orchidaceae, is a perennial herbaceous plant used in Chinese medicine. It is a commonly cultivated economic crop in the Yangtze River Basin provinces of China, as its roots are used to treat bleeding and inflammation. In Zhejiang province, Bletilla striata has a planting area of 1400 hectares with a total production of approximately 2.6×106 kg. In October 2021, over 40% of B. striata plants showed severe wilt in a traditional Chinese medicine plantation (ca. 10 ha) in Xianju City, Zhejiang Province, China. In July, leaf curling, crinkling, and leaf-edge browning of the diseased plants were first noticed in the field. Then, necrotic streaks gradually spread to the roots. Stems displayed chlorosis and withering and when they were cut vertically, symptoms such as vascular bundle discoloration, appeared. After October, the individual plants slowly wilted and died, their aboveground parts became filamentous, and the epidermis detached from the corm's fibrous roots. Diseased plants were easily removed as the corm root had fractured. White mycelia were clearly seen in the stem. Three symptomatic leaves and three stems were cut, their surfaces disinfected, and plated on potato dextrose agar (PDA). Six strains were subsequently isolated from all samples. Fungal colonies with white to cream-colored mycelia from all tissues appeared after 3 d of incubation at 26 °C. Pure cultures obtained after monospore isolation were examined for their morphological characteristics. The colonies grew rapidly, were fluffy and appressed, and had cottony white to pale cream coloration. Microconidia were hyaline, oval to reniform, with zero or one-septate (4.0-12.0 × 1.0-5.5 µm), and usually formed on elongated monophialidic conidiogenous cells. Macroconidia were wide, fusiform, or slightly curved with one or three septa (23.0-36.0 × 4.5-7.0 μm). Chlamydospores were spherical and were abundant on carrot agar (CA) medium within 2 wk. Fresh mycelia and conidia that grew at 26 ℃ for 7 d were collected from PDA plates. Next, DNA was extracted using the Ezup Column Fungi Genomic DNA Purification kit (Sangon Biotech, Shanghai, China). We amplified a portion of RNA polymerase II second largest subunit gene (RPB2) using primers 5f2/7cr (O'Donnell et al. 2010), the internal transcribed spacer (ITS) region using primers ITS1F/ITS4 (White et al. 1990), and the partial translation elongation factor-1α gene using primers EF1/ EF2 (O'Donnell et al. 1998) from the genomic DNA and sent the PCR amplicons for sequencing at Tsingke Biotechnology Co., Ltd., Wuhan, China. A BLAST search of the obtained sequences (GenBank accessions OP743920, OP913183, and OP913180) showed 99-100% homology with the respective sequences of the Fusarium solani reference isolate NRRL46702 (O'Donnell et al. 2008). Based on the morphological and molecular characteristics and BLAST search, the fungus was identified as F. solani (Leslie and Summerell 2006). Pathogenicity of the purified F. solani isolate was assessed by inoculateing a F. solani spore suspension of 1×106 conidia/mL (20 mL per seedling) on corm wounds made with a toothpick. Four inoculated and three non-inoculated seedlings (sterilized water as a negative control) were grown in a greenhouse at 26 °C under natural sunlight and covered with plastic bags to maintain humidity for 72 h. After 15 d, leaf browning on leaf edges, new leaf bases, and corm epidermis was observed. Symptoms, similar to those detected in the original sample, developed on the inoculated leaves, whereas the controls remained asymptomatic. Fusarium solani was successfully re-isolated from all four inoculated seedlings, and their identity confirmed by generating partial Tef1 and RPB2 sequences, thereby fulfilling the Koch's postulate. To our knowledge, F. solani has not been previously reported as a pathogen of B. striata.