Flow Conditions Research Articles

A Convolutional Neural Network-Based Method for Distinguishing the Flow Patterns of Gas-Liquid Two-Phase Flow in the Annulus

In order to improve the accuracy and efficiency of flow pattern recognition and to solve the problem of the real-time monitoring of flow patterns, which is difficult to achieve with traditional visual recognition methods, this study introduced a flow pattern recognition method based on a convolutional neural network (CNN), which can recognize the flow pattern under different pressure and flow conditions. Firstly, the complex gas–liquid distribution and its velocity field in the annulus were investigated using a computational fluid dynamics (CFDs) simulation, and the gas–liquid distribution and velocity vectors in the annulus were obtained to clarify the complexity of the flow patterns in the annulus. Subsequently, a sequence model containing three convolutional layers and two fully connected layers was developed, which employed a CNN architecture, and the model was compiled using the Adam optimizer and the sparse classification cross entropy as a loss function. A total of 450 images of different flow patterns were utilized for training, and the trained model recognized slug and annular flows with probabilities of 0.93 and 0.99, respectively, confirming the high accuracy of the model in recognizing annulus flow patterns, and providing an effective method for flow pattern recognition.

Creation of aortic regurgitation model on isolated porcine heart and aortic valve-sparing root replacement using a new device for aortic valve cusps positioning

Valve-sparing surgery in ascending aortic and root aneurysms combined with aortic regurgitation (AR) is a relevant and actively developing trend. The ways to improve these operations are the development of new devices to simplify and standardize valve-sparing procedures using animal models and testing in experiment. Objective. To review experimental methods of aortic root aneurysm and AR modeling, as well as devices simplifying aortic valve-sparing root replacement, including a new device for positioning of aortic valve (AV) cusps during valve-sparing root replacement with AV reimplantation (David procedure), which we have developed. Materials and methods. The components of the developed device were manufactured by three-dimensional printing with preliminary modeling in the parametric environment of computer-aided design with the open source code FreeCAD 0.20.1. The possibility of David procedure on the isolated swine aortic root in the experiment using the new device was evaluated. Results. During the experiments we performed aortic root replacement with AV reimplantation on the isolated porcine aortic root. We noted that the developed device provides good exposure of the surgical correction zone and reduces the probability of damage to the aortic root structures, especially to the AV cusps, in the process of reimplantation. The device eliminates the necessity to use assistants during the main stage of intervention, which reduces the probability of operator-associated complications. Conclusion. Standardization and simplification of reimplantation of AV cusps into the vascular graft during aortic root replacement with the help of the device developed by us is achieved by performing trial positioning of AV cusps and hydraulic tests at different positions of the cusps, which simplifies the search for the optimal point of coaptation and allows to keep the found best position of the cusps until their anchoring inside the graft. The directions of further research are improvement of the design of the developed device, experimental studies with evaluation of the result of valve-sparing surgery under conditions of pulsating fluid flow, testing of the technology on large laboratory animals.

Boiling heat transfer enhancement on heterogeneous copper foams in the presence of transverse flow

Open cell copper foams are widely employed to enhance boiling heat transfer, but homogeneous foams face a trade-off between promotion in wetted area and reduction in resistance to bubble departure. In this work, heterogeneous copper foams with horizontal gradient are proposed to assure both enlarged wetted area and facilitated bubble departure. Boiling of HFE-7100 on the heterogeneous foams consisting of 30 pore per inch (PPI) square core and 60 PPI frame with different projection area fractions and thicknesses is conducted under the conditions of forced transverse flow. A peak heat transfer coefficient (HTC) of 5.4 W cm−2 K−1 and a critical heat flux (CHF) of 91.4 W cm−2 are obtained on the heterogeneous foam having a core thickness of 5 mm and a frame thickness of 2 mm. The difference in thickness delays the formation of vapor blanket on the foam to promote CHF and the difference in pore density favors balanced surface wetting and vapor venting to enhance HTC. Vapor bubbles on the copper foams are visually observed and a semi-empirical model correlating CHF with heterogenous geometric parameters of the foam is proposed. This work offers an optional strategy to further enhance boiling heat transfer on porous mediums.

Experimental Assessment of Hydrodynamic Behavior in a Gravitational Vortex Turbine with Different Inlet Channel and Discharge Basin Configurations

Gravitational vortex turbines can provide a sustainable and efficient solution for generating renewable energy from small watercourses, minimizing environmental impact, and contributing to the decentralization of energy production. Their design allows for high energy efficiency even under low flow conditions, thus benefiting rural communities and reducing their dependence on fossil fuels. This paper presents an experimental assessment of the hydrodynamic behavior of gravitational vortex turbines by examining various geometric configurations. The combinations of two types of inlet channels (spiral and tangential) and two types of discharge basins (conical and cylindrical) were investigated. Additionally, different geometries and placements of the runners were evaluated to determine their influence on the efficiency and performance of the turbine. The results indicate that the highest efficiency of 60.85% was achieved with a configuration that included a spiral inlet channel, cylindrical discharge, and a runner placement of 50%.

Hydrometric data discretization into environmental flow components: a new, practical approach to explore concentration-discharge relationships

The intricate dynamics of streamflow and water quality are often explored through the lens of concentration-discharge (C-Q) relationships. Interpreting C-Q relationships and using mathematical models to explain them can, however, be challenging due to hysteresis effects, low-frequency data, or noisy data. To address these challenges, this study introduces a noise-filtering approach by aggregating discrete data collected over several years into bins corresponding to distinct environmental flow components (EFCs). Covering a spectrum from extreme low flows to small and large floods, this method simplifies C-Q analysis by focusing on watershed hydrochemical responses to varying flow conditions. The objectives of the study were to explore the variability of stream water quality across a gradient of EFCs, categorize watersheds based on their median dominant export behaviour type (e.g. dilution, mobilization, chemostatic), and evaluate the predictability of export behaviour type from watershed characteristics. The study relied on 30 watersheds located in Québec, Canada, ranging in size from 11 to 2610 km2, with daily streamflow data and at least monthly water quality data spanning at least two years over the 1989-2020 period. EFC-specific summary statistics for dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) concentrations were computed and used to assess C-Q relationships and classify the general tendencies of watershed export behaviour. Results reveal nuances in watershed export behaviour depending on the specific water quality parameter and flow components assessed. Some differences in watershed hydrobiogeochemical behaviours could be explained by differences in watershed physiographic characteristics. The EFC-based approach to C-Q analysis provides watershed scientists and managers with a simple and comprehensive tool to utilize existing data, enabling a deeper understanding of watershed nutrient export dynamics.

Two-Dimensional Prediction of Transient Cavitating Flow Around Hydrofoils Using a DeepCFD Model

Cavitation is a common phenomenon in naval and ocean engineering, typically occurring in the wakes of high-speed rotating propellers and on the surfaces of fast-moving underwater vehicles. To investigate cavitation phenomena, computational fluid dynamics (CFD) simulations are indispensable. Nevertheless, the inherently complex nature of cavitation, which involves phase transitions, heat transfer, and significant pressure fluctuations, often results in high computational costs for these simulations. To address the computational challenges associated with cavitation simulations, a DeepCFD model, which leverages convolutional neural networks (CNNs), was employed to accurately predict cavitation around hydrofoils. Through specific modifications, the DeepCFD model was trained on 400 hydrofoil configurations, learned from CFD simulations. The numerical methods were validated against a modified NACA66 hydrofoil. It was found that the model could accurately predict cavitation shapes under various flow conditions, although it showed some discrepancies in velocity predictions, especially for detached cavitating flows. The significance of this study lies in its potential to simply predict cavitating flows and expedite marine vehicle design through the application of CNNs in cavitation prediction, offering a novel and impactful approach to computational fluid dynamics in the field.

Structural and dynamic characteristics of horseshoe vortex systems in front of rigid vegetation inclined upstream under conditions of overland flow

Inclined angle significantly impacts horseshoe vortex (HV) system and subsequent flow events upstream of vegetation stems, which are crucial for understanding of erosion mechanisms and geodynamics. Flume experiments were conducted to investigate dynamic characteristics of horseshoe vortex (HV) system upstream of inclined rigid vegetation stems under shallow overland flow conditions. Five inclination angles (10°, 20°, 30°, 40°, 50°) were tested alongside a vertical column (0°) across four low Reynolds number conditions (ReD = 2995–4639). Using high-precision particle image velocimetry (PIV) system, we measured the flow field in upstream symmetry plane of the cylinder. Then time-averaged primary HV features were analyzed in terms of the location, radius, vorticity, swirling strength, flow direction and vertical velocity. The increasing inclination angle weakens the formation of the HV system. This is evident in the decrease of vorticity and swirling strength, as well as the gradual diffusion and eventual rupture of the HV system. In the horizontal direction, the primary HV gradually moves away from the cylinder, with minimal vertical impact. The radius of the main HV is positively correlated with the tilt angle, while vorticity and rotation intensity are negatively correlated. We also examined the time-resolved characteristics of the velocity components. The probability density functions (PDFs) of streamwise and vertical velocity components show asymmetric double peaks, indicating two high-frequency events: backflow and downwelling. Linear random estimation revealed that the backflow event is driven by a high-momentum counter current passing through the primary HV, which is mainly dominated by a backflow mode, while the downwelling event arises from low-momentum fluid that cannot penetrate the HV, dominated by a zero-flow mode. These two modes exhibited minimum and maximum time percentages within the current time range, highlighting erosion dynamics from the perspectives of flow event frequency and momentum theory.

A general Physics-Informed Neural Network approach for deriving fluid flow fields from temperature distribution

One attractive application of Physics-Informed Neural Network (PINN) is deriving fluid flow information such as velocity and pressure from temperature field. However, this requires developing a suitable loss function for a given flow condition. In this paper we implemented a general loss function in PINN to directly obtain fluid velocity and pressure from temperature information. We first validated this method through cases of natural convection in a square cavity, flow around a cylinder in a square cavity, and two-dimensional channel flow. Additionally, we examined forced convection heat transfer around a cylinder in depth. Results show that different Reynolds numbers (2, 10, 40, and 140) can all be effectively resolved using temperature data. Furthermore, super-resolution predictions of temperature, velocity and pressure are achievable even far outside the training area, suggesting that the proposed PINN method could be used to measure fluid flow within confined spaces via finite visualization windows without tracers.

Phase field-lattice Boltzmann method investigation of particle morphology evolution in slush hydrogen during convective freezing and melting

Freezing-thawing is one of the prevalent and pragmatic approach for the preparation of slush hydrogen. Understanding how production parameters affect the evolution of slush hydrogen particles is crucial for optimizing its efficiency. This study develops a two-dimensional Phase Field-Lattice Boltzmann Method (PF-LBM) to investigate the solidification and melting behavior of individual slush hydrogen particle under dynamic flow conditions. The proposed model integrates the Ginzburg-Landau theoretical phase-field model with a D2Q9 single-relaxation LBM. The variation of the phase and temperature fields of hydrogen particle during the freezing and melting process is investigated, and the role of vortices in shaping the profile of dendrites is found. Differences in dendrite growth at different flow rates and equilibrium temperatures are analyzed, and the variation in solid content is given. This study explores the mesoscopic mechanisms of slush hydrogen particle in a flowing field and provides theoretical guidance for the dynamic preparation of high-quality slush hydrogen.

An engineering-oriented Shallow-water Hydro-Sediment-Morphodynamic model using the GPU-acceleration and the hybrid LTS/GMaTS method

Engineering applications of finite volume Shallow-water Hydro-Sediment-Morphodynamic models (SHSM) have faced limitations due to their high computational demands arising from either extremely large amounts of computational cells or extremely small time steps at some regions and simultaneously the adoption of the globally minimum time step. To this end, we present an engineering-oriented modeling framework by (1) using the GPU-acceleration that overcomes the challenge of extremely large amounts of computational cells and (2) using a hybrid local-time-stepping/global maximum time step (LTS/GMaTS) strategy that mitigates the extremely small local time steps necessitated by locally-refined meshes or non-uniformity of flow conditions. The GPU parallel algorithm is tailored to fully leverage the computational power of GPU, optimizing numerical structure, kernel functions and memory usage, all in conjunction with the hybrid LTS/GMaTS implementation. We demonstrate its computational efficiency by simulating one experimental dam-break flow and a field-scale case in the Xinjiu waterway, Middle Yangtze River. The results show that the scheme performs well in terms of accuracy, efficiency, and robustness in reproducing real-world hydro-sediment-morphological evolution.

Enhancement of Heat Transfer rate using Axially Interrupted Rectangular Fins in Double Pipe Heat Exchanger

The current investigates the thermo-fluid behavior of a double pipe heat exchanger (DPHE) featuring axially interrupted rectangular fins (AIRF) on the annulus part. The inner tube under this study with AIRF represents an interruption of straight longitudinal fins. This modification introduces periodic breaks along the tube's surface, effectively disrupting the boundary layer of the fluid flow. Consequently, it enables a non-continuous fluid passage along the length of the tube, potentially enhancing heat transfer. The experimentation employs standard liquid water, for investigations conducted under varying cold water mass flow rate 0.136 Kg/s to with 0.374 Kg/s keeping hot water at constant flow rate of 0.34 Kg/s with a fin split interval of four different lengths 7mm,27mm,55mm,100mm. A comprehensive investigation of the AIRF arrangements is carried out in contrast to the plain pipe arrangement, concentrating on fluid flow parameters such as Nusselt number (Nu), friction factor, heat transfer rate, and overall performance factor. The findings reveal that heat transfer rates in an annulus equipped with 7mm AIRF exceed those of a plain pipe by 59.31% under similar fluid flow conditions. The Nusselt number shows 1.5 times increase in the 0.007 m AIRF arrangement compared to the plain pipe. Thermal performance factor for 7mm interrupted length of AIRF outperforms other models.

PIV experimental study on dynamic and static interference flow field of multi-operating centrifugal pump under the influence of impeller wake

In order to study the influence law of the impeller wake on dynamic and static interference flow field of the centrifugal pump, this paper obtains the dynamic and static interference flow field of the centrifugal pump under different flow conditions (15 m3/h, 50 m3/h, 70 m3/h) based on PIV technology, and analyzes the influence mechanism of the impeller wake change on dynamic and static interference flow field. The results show that rotating stall occurs in the centrifugal pump under low flow condition, but it has little effect on the head loss in the centrifugal pump. In the dynamic and static interference flow field, under the condition of the low flow rate, the impeller wake collides with the baffle tongue, resulting in serious velocity fluctuation, and then there will be the secondary collision with the volute wall, which will eventually cause the wake to dissipate, and the change process of the wake shows the periodic characteristic. In the design condition and the large flow condition, the spacer tongue will have the cutting effect on the wake, and the high-speed accumulation phenomenon will occur in the volute flow path near the spacer tongue. In the side flow path of the volute, under the condition of the low flow, the impeller wake is mainly located at the exit of the impeller, and the end of the impeller wake is easy to fall off and gradually break up under the impact of the main stream. Under the design condition, the flow stability is good, and the wake vortex is close to the trailing edge of the blade, and there is no obvious shedding phenomenon. Under the condition of the large flow rate, the velocity fluctuates sharply, and many large-scale vortex structures appear on the cross section of the flow channel due to the cutting of the wake near the diaphragm tongue. In the impeller passage, the movement and distribution of the wake are significantly affected by changes in flow conditions. The research results provide a basis for optimizing volute channel.

A pump-free microfluidic co-culture system for investigating NK cell-tumor spheroid interactions in flow conditions

Natural killer (NK) cells are pivotal in immunotherapy due to their potent tumor-targeting capabilities. However, accessible in vitro 3D dynamic models for evaluating Tumor Infiltrating Natural Killer Cells (TINKs) remain scarce. This study addresses this gap by developing a novel pump-free microfluidic chip to investigate the interactions between NK-92 cells and prostate DU 145 tumor spheroids. The platform facilitates the separation of free NKs and TINKs for subtype characterization. The design integrates multiple planes with a multi-layer paper scaffold to accommodate tumor spheroids, allowing NK-92 cells to traverse Matrigel-coated barriers that mimic the extracellular matrix. The dual-channel pump-free device enables unidirectional circulation of NK-92 cells, allowing analysis of tumor spheroid movement and NK-92 cell interactions under flow conditions. Results demonstrate continuous fluid circulation in the dual-channel device by rocking the platform at tilt angles of 21° and 15°. Tumor spheroids show- enhanced migration under flow conditions compared to static culture. Although spheroids recruit slightly more NK-92 cells under flow conditions, CD56 and CD16 receptor expression on IL-2-activated free NK-92 cells and tumor-infiltrating NK-92 cells matches in vivo patterns in dynamic cultures. These findings suggest that tumor cells and fluid dynamics significantly influence NK cell subtypes. This pump-free microfluidic platform is a functional tool for simulating and studying immune cell-tumor interactions, providing valuable insights into NK cell dynamics with tumor spheroids in physiologically relevant environments.

Experimental evaluation of solitary slugs in a horizontal pipe

In this work the existence of a bi-stable flow regime in a horizontal gas-liquid two-phase flow was experimentally confirmed. In this regime, both stratified and slug flows were found to be stable, and the occurrence of either regime depended on the inlet conditions imposed on the flow. When operating in the bi-stable flow condition, two types of slugs can occur. The first type was obtained by forcing a regular slug flow at the inlet of the horizontal pipe using an uphill section before the inlet. In this case, slugs in the uphill and horizontal sections have similar frequencies. The second type was obtained by forcing a stratified flow at the inlet, and then introducing a short pulse in the liquid flow rate. This triggered a solitary slug in the pipe, which grew linearly with the distance from the inlet. The behavior of the solitary slugs observed experimentally confirms the explanation and the model provided by Belt et al., 2024. The existence of such slugs can represent a threat in operations, since in long flowlines they can become extremely large and flood the downstream process installations. For instance, the experiments showed solitary slugs more than 200 pipe diameters long at a distance of 460 pipe diameters from the inlet. In order to evaluate the conditions under which the solitary slug phenomenon might occur, the extent of the bi-stable flow regime was experimentally determined. Its lower and upper boundaries match reasonably well with the stability conditions for slug flow and stratified flow, respectively, which were calculated within a 1D modeling framework.

Application of Imaging Algorithms for Gas-Water Two-Phase Array Fiber Holdup Meters in Horizontal Wells.

The flow dynamics of low-yield horizontal wells demonstrate considerable complexity and unpredictability, chiefly attributable to the structural attributes of the wellbore and the interplay of gas-water two-phase flow. In horizontal wellbores, precisely predicting flow patterns using conventional approaches is often problematic. Consequently, accurate monitoring and analysis of water holdup in gas-water two-phase flows are essential. This study performs a gas-water two-phase flow simulation experiment under diverse total flow and water cut conditions, utilizing air and tap water to represent downhole gas and formation water, respectively. The experiment relies on the measurement principles of an array fiber holdup meter (GAT) and the response characteristics of the sensors. In the experiment, GAT was utilized for real-time water holdup measurement, and the acquired sensor data were analyzed using three interpolation algorithms: simple linear interpolation, inverse distance weighted interpolation, and Gaussian radial basis function interpolation. The results were subsequently post-processed and visualized with 2020 version MATLAB software, generating two-dimensional representations of water holdup in the wellbore. The study findings demonstrate that, at total flow of 300 m3/d and 500 m3/d, the simple linear interpolation approach yields superior accuracy in water holdup calculations, with imaging outcomes closely aligning with the actual gas-water flow patterns and the authentic gas-water distribution. As total flow and water cut increase, the gas-water two-phase flow progressively shifts from stratified smooth flow to stratified wavy flow. In this paper, the Gaussian radial basis function and inverse distance weighted interpolation algorithms exhibit superior accuracy in water holdup calculations, effectively representing the fluctuating features of the gas-water interface and yielding imaging outcomes that align more closely with experimentally observed gas-water flow patterns.

Sim‐Net: Simulation Net for Solving Seepage Equation Under Unsteady Boundary

ABSTRACTThe seepage equation plays a crucial role in fields such as groundwater management, petroleum engineering, and civil engineering. Currently, physical‐informed neural networks (PINNs) have become an effective tool for solving seepage equations. However, practical applications often involve variable flow rates, which pose significant challenges for using neural networks to find solutions. Inspired by Deep Operator Network (DeepONet), this paper proposes a new model named Simulation Net (Sim‐net) to deal with unsteady sources or sinks problems. Sim‐net is designed to simulate and solve seepage equations without the need for retraining. This model integrates potential spatial and temporal features based on spatial pressure distribution and well bottom–hole pressure, respectively, which serve as additional signposts to guide neural networks in approximating seepage equations. Sim‐net exhibits transfer learning capabilities, enabling it to handle variable flow rate problems without retraining for new flow conditions. Numerical experiments demonstrate that the trained model can directly solve seepage equations without the need for retraining, indicating its superior applicability compared to existing PINNs‐based methods. Additionally, in comparison to the DeepONet, Sim‐net achieves higher accuracy.

Transition to turbulence in hypersonic flow over a compression ramp due to upstream forcing

Several transition scenarios are present in a hypersonic compression-ramp flow. In our previous work (Cao et al., J. Fluid Mech., vol. 941, 2022, p. A8), a complete transition process induced by the global instability of a compression-ramp flow was revealed. In a globally stable flow, however, the transition to turbulence can be promoted by convective instabilities, which is the focus of this work. The same flow conditions as in our previous work (Mach number 7.7, Reynolds number $8.6\times 10^5$ based on the flat-plate length) are considered here. Owing to a smaller ramp angle, a weakly separated flow forms on the compression ramp, which supports no global instability. Resolvent analysis identifies low-frequency streamwise streaks as the optimal response of base flow to upstream forcing. Local stability analysis reveals Mack's second mode in the boundary layer downstream of reattachment. By introducing random disturbances upstream of separation in direct numerical simulations, we observe breakdown to turbulence downstream of reattachment. Two transition scenarios are revealed, and they are highly dependent on the amplitude of upstream disturbances. For a large amplitude, strong streamwise streaks develop near the reattachment region, which break down to turbulence quickly. However, when the disturbance amplitude is reduced, the second-mode instability dominates the transition to turbulence.

Effects of reduced flow gradient on benthic biofilm communities' ecological network and community assembly.

The intensification of human activities has led to flow reduction and cut-off in most global rivers, seriously affecting riverine organisms and the biogeochemical processes. As key indicators of river ecosystems' structure and function, benthic biofilms play a critical role in driving primary production and material cycling in rivers. This research aimed to investigate the characteristics of microbial communities' complexity and stability during river flow reduction. Benthic biofilms were grown in artificial channels and subjected to eight gradients of flow reduction (represented by flow velocity from 0.4 to 110 cm/s). Biofilms' biodiversity, ecological networks and community assembly of bacteria, fungi and algae were investigated by high-throughput sequencing. Results showed significant differences in community composition and structure under different flow conditions. The eight flow gradients' microbial communities were divided into three groups: low, medium and high flows. The flow reduction led to significant decreases in bacterial and fungal communities' Chao1 index. Low flow conditions enriched the bacterial phyla Oxyphotobacteria, Alphaproteobacteria and Mollicutes, but significantly decreased the fungal phylum Chytridiomycota. Lowering flow reduced the fungal network's number of nodes and increased the algal network's number of edges. Cross-domain interactions network analysis showed a gradual increase in node and edge numbers with decreasing flow, while decreasing average path length. The neutral model predicted stochastic processes primarily drove biofilm community assembly, and that model's explanations decreased as the flow gradient decreased. The null model analysis revealed diffusion limitation as the most common stochastic ecological process for bacterial and algal communities, with reduced flow reducing heterogeneous selection and increasing diffusion-limited processes. This study provides an in-depth analysis of flow reduction's effects on biofilm communities' ecological networks and community assembly.

Optimization of submersible LNG centrifugal pump blades design based on support vector regression and the non-dominated sorting genetic algorithm Ⅱ

Optimizing the impeller blade design of submersible LNG centrifugal pump significantly enhances mechanical efficiency, reducing energy consumption and carbon emissions during LNG storage and transportation. This study focuses on optimizing blades of the centrifugal pump, combining Bezier blade design, CFD simulations, optimal Latin Hypercube sampling, Support Vector Regression (SVR), and Non-Dominated Sorting Genetic Algorithm II(NSGA-II) multi-objective optimization into a systematic method. During the development of this optimization method, it was found that directly applying sampled CFD simulation data for machine learning led to poor overall predictive performance of the models. To address this, a data augmentation method based on Gaussian noise was proposed. Through Bayesian optimization of the machine learning model's hyperparameters, the R2 of the predictive model was successfully increased from below 0.8 to above 0.99. The optimized design improved the prototype pump's efficiency from 70 % to 77.8 % under rated flow and head conditions. This efficiency gain is due to the significant reduction in flow separation vortices between blades and decreased turbulent kinetic energy between the impeller and diffuser vanes. Additionally, sensitivity and linear relationship analyses using the Sobol method and Pearson correlation provided valuable insights for blade optimization design.

Non-antibiotic disinfectant synchronously interferes methane production and antibiotic resistance genes propagation during sludge anaerobic digestion: Activation of microbial adaptation and reconfiguration of bacteria-archaea synergies

Waste activated sludge (WAS) presents both resource recovery potential and pollution risks, making its efficient treatment challenging. Anaerobic digestion is broadly recognized as a green and sustainable approach to WAS treatment, whose efficiency is easily impacted by the exogeneous pollutants in WAS. However, the impact of polyhexamethylene guanidine (PHMG), as a widely-used non-antibiotic disinfectant, on WAS digestion under semi-continuous flow conditions remains unclear. In this study, CH4 production decreased from 16.1 mL/g volatile suspended solids (VSS) in the control to 13.2 mL/g VSS and 0.3 mL/g VSS under low and high PHMG exposure, respectively, while PHMG increased the number of antibiotic resistance gene (ARG) copies per bacterium by 4.6-12.7 %. Molecular docking analysis revealed that PHMG could spontaneously bind to and disintegrate WAS (binding energy:2.35 and -9.62 kcal/mol), increasing the likelihood of microbial exposure to PHMG. This led to an increase in bacterial abundance and a reduction in archaeal populations, resulting in bacterial dominance in ecological niches. The network topology index in PHMG-treated reactors was consistently lower than in the control, with a higher proportion of negatively correlated links, indicating a more antagonistic relationship between bacteria and archaea. Consequently, PHMG significantly interfered with key genes involved in CH4 biosynthesis (e.g., mch and mtd). Interestingly, methanogenic activity and archaeal chemotaxis (e.g., rfk and cheA) partially recovered under low PHMG exposure due to archaeal adaptation through quorum sensing and two-component systems. However, this adaptation process also contributed to the propagation of ARGs through horizontal gene transfer, facilitated by the enhancement of mobile genetic elements and ARGs hosts. These findings confirm the ecological risks of PHMG and highlight the need for effective WAS disposal strategies.