Granular Properties Research Articles

Cemented sand under hollow cylinder multiaxial loading

Improvement of granular soils’ mechanical properties can be achieved by the addition of bonding agents. In this research, low amount of Portland cement was added to a sand, and its beneficial shear strengthening effects were evaluated under a range of multiaxial stress paths. The influence of the orientation of the principal axes of stress and strain on the stress–strain response and failure of cemented sand has only been scarcely investigated. Therefore, this experimental investigation reports the results of a series of consolidated drained hollow cylinder torsional tests with constant principal stress path direction, ασ, varying from 0° to 90°. Results were compared with the shear behaviour of the uncemented sand tested under similar loading conditions. Results show that the addition of cement to the sand matrix increases the soil strength for all multiaxial stress path directions. The suitability of two multiaxial strength criteria for reproducing the shape of the failure envelope as a function of the orientation of principal stress axis ασ has also been analysed.

On the Relation between the Viscoelastic Properties of Granular Hydrogels and Their Performance as Support Materials in Embedded Bioprinting.

Granular hydrogels, formed by jamming microgels suspension, are promising materials for three-dimensional bioprinting applications. Despite their extensive use as support materials for embedded bioprinting, the influence of the particle's physical properties on the macroscale viscoelasticity on one hand and on the printing performance on the other hand remains unclear. Herein, we investigate the linear and nonlinear rheology of κ-carrageenan granular hydrogel through small- and large-amplitude oscillatory shear measurements. We tuned the granular hydrogel's properties by changing the stiffness (soft, medium, stiff) and the packing density of the individual microgels. Characterizations in the linear viscoelasticity regime revealed that the storage modulus of granular hydrogels is not a simple function of microgel stiffness and depends on the microgel packing density. At larger strains, increasing the microgel stiffness reduced the energy dissipation of the granular beds and increased the solid-fluid transition point. To understand how the different rheological properties of granular support materials influence embedded bioprinting, we examined the printing fidelity and cellular filament shrinkage within the granular beds. We found that microgels with low packing density diminished the printing quality, while stiff microgels promoted filament roughness. In addition, we found that highly packed stiff microgels significantly reduced the postprinting contraction of cellular filaments. Overall, this work provides a comprehensive knowledge of the rheology of granular hydrogels that can be used to rationally design support beds for bioprinting applications with specific characteristics.

Physical Model of Landslide‐Generated Impulse Waves: Experimental Investigation of the Wave‐Granular Flow Coupling

AbstractLarge amplitude and unexpected waves are a regular source of natural disasters. Among them, impulse waves generated by landslides can represent a significant threat. Therefore, predicting and measuring the generation of such waves is essential. In this study, the phenomenon is modeled by a 2D‐experimental setup using a steady non‐uniform granular flow along a slope as a forcing wave generator. The present device provides a continuous supply of grains to avoid finite volume effects, as the part of the landslide actually involved in the wave generation strongly depends on the configuration and is not necessarily available in geophysical events. This system consists of an energy transfer between the granular flow and the wave generation which is characterized by a Froude number. It is found that the latter cannot be defined only based on the dry flow properties to characterize the wave. In particular, the dynamics underwater influence wave generation during a finite time. Accordingly, the present study shows that the wave maximum amplitude is governed by a newly defined Froude number, based on both dry and underwater granular flow properties. Moreover, it is shown that the granular deposit, specifically its runout, can be thought as a proxy of the immersed granular dynamics as long as the impact properties are still considered.

Effect of deposition parameters on structural and mechanical properties of Novel h-BN doped TiCrNbN coatings

In this paper, the novel h-BN doped TiCrNbN thin films was deposited on the DIN 1.2714 steel using closed field unbalanced magnetron sputtering (CFUBMS) technique with variable working pressure, bias voltage, and LaB6 target voltage. The main goal is to determine the contribution of degrees of these parameters on structural and mechanical properties using Analysis of Variance (ANOVA). The deposition parameters were leveled based on L9 (33) orthogonal Taguchi design method. Microstructural and thickness of coatings were investigated using SEM. The coatings had granular and flawless surface properties. The thickness of the coatings was determined in the range of 874 nm and 1.69 μm. The deposition parameter that has the highest contribution to coating thickness is working pressure. Hardness and adhesion strength of coatings were determined employing nanohardness and scratch tester, respectively. The highest hardness among the coatings was 24.67 GPa, obtained with the 3x10-3 Torr working pressure, 100 V bias voltage and 600 V LaB6 target voltage parameters. The deposition parameter that has the highest contribution to hardness is working pressure. The coating conditions with the highest hardness exhibited the highest adhesion strength. The superiority of the contribution of working pressure on the adhesion strength was prominent compared to other parameters.

Mechanical and absorption properties of carbon-basalt and glass fiber reinforced composites: A comprehensive study with implications for advanced manufacturing technology

In this research, a combination of hybrid and non-hybrid composite materials were tested for their mechanical properties and water absorption rates. The study focused on composites produced through hand-layup techniques, examining their void percentage, morphology, and elemental composition. Specifically, three different stacking sequences of hybrid composites were compared with three non-hybrid composites of equal thickness. Combining carbon and glass allows the composites to balance flexural (367 MPa, 23 GPa) and tensile (440 MPa, 5.7 GPa) strength and modulus, all while remaining cost-effective and easily accessible. The glass fiber-based composites exhibited exceptional impact (27 J/cm2) strength due to their interfacial solid bonding. Additionally, the study found that basalt and carbon-basalt composites had varying degrees of water absorption when exposed to seawater and river water. SEM and EDS Mapping analyses were conducted to understand better fibrous and granular composites' mechanical properties and water absorption behaviors. These analyses provided valuable insights and a comprehensive knowledge of composite properties. Ultimately, the study recommends using hybrid composite materials for specific applications based on desired flexural tensile strength, impact strength, or water absorption characteristics.

A systematic evaluation of DEM input parameters measurement and calibration

Rotary drums are widely used in industry, however, determining granular dynamics within them is still a complex task, thus remaining a focal point of research over the years. In this context, experimental techniques require numerical support to obtain data that is not easily acquired experimentally. One well-established numerical technique for studying particulate systems is the Lagrangian approach embed with Discrete Element Method (DEM). Although, DEM has limitations related to the definition of input parameters. It is crucial that DEM input parameters be measured and/or calibrated to reliably represent the granular behavior. These parameters are related to particle properties such as density, Young’s modulus, Poisson’s ratio, among others, and particle interactions, such as coefficients of restitution, static friction, and rolling friction. This study explores the experimental determination of interaction parameters preceding the acquisition of DEM input parameters in a rotary drum. Statistical analysis highlights the importance of each parameter and their combined interactions with the static angle of repose. The granular materials used were: soybeans, glass beads, polyacetal, 6 mm steel, and 4 mm steel. The coefficient of restitution was determined via free-fall methodology using equipment that verifies particle trajectory, static friction coefficient through equilibrium between weight and resistance forces, rolling friction coefficient using a launching device on surfaces of different roughness, and static angle of repose in a rectangular box with sections where particles rested. After removing the partition, angles were measured at both top and bottom sections. Regression techniques using a neural network created in Python were employed for both measurements. Experimental investigations and numerical simulations using DEM indicated that the coefficient of restitution depends on the thickness and type of material of the flat surfaces, showing an asymptotic behavior with increasing surface thickness. The static friction coefficient increased on rougher surfaces and in particles with greater imperfections. Rolling friction coefficient also increased on rough surfaces. Analysis of the angle of repose revealed that granular properties influence the response, such as static and rolling friction coefficients, whereas the coefficient of restitution had no significant influence. Neural network correlation coefficients exceeded 0.95, indicating a strong association between the variables. Our findings revealed that mathematical models can be used in conjunction with static repose angle experiments to calibrate DEM parameters for more robust and complex simulations. This research also quantifies and provides insights into the interactions between DEM parameters in direct measurement experiments, promoting more efficient calibration for future research.

Multiscale modeling of solid starch-based foods digestion in the intestinal tract for dietary property-based glycemic prediction

The digestion of starch-based foods in the intestinal tract is important for human health. Modeling the details enhances fundamental understanding and glycemic prediction accuracy. It is, however, a challenge to take granular properties into account. A multiscale digestion model has been proposed to characterize mass transfer and hydrolysis reaction at both the intestine and particle scales, seamlessly integrating inter-scale mass exchange. A specific grid scheme was formulated for the shrinkage and transport of the particle computational domain. By incorporating additional glycemic-related processes, e.g., intestinal absorption, a dietary property-based glycemic prediction system has been developed. Its effectiveness was validated based on a human tolerance experiment of cooked rice particles. The model-based investigation comprehensively reveals the impact of initial size on digestion behavior, specifically in terms of enzyme distribution and particle evolution. This work also demonstrates the significance of modeling both particle-scale diffusion and intestine-scale transport, a combination not previously explored. The results indicate that ignoring the former mechanism leads to an overestimation of the glycemic peak by at least 50.8%, while ignoring the latter results in an underestimation of 16.3%.

Assessment of adsorption efficiency of Kaoline-Chitosan composite beads for removal of Ca and As from aqueous solution in lab-scale

Abstract In this study, Kaoline (CK) and Chitosan (CTS) including water-soluble CTS (WCTS) and acid-soluble CTS (ACTS), were synthesized from commercial materials to produce composite beads which were then employed as adsorbents to investigate the removal of Ca and As from aqueous solutions. Results showed that the adhesion and granular properties of CK-WCTS and CK-ACTS were different, which affected the adsorption efficiency. Specifically, when 0.3 g of adsorbent (i.e., CK-WCTS and CK-ACTS) was used to test with 30 ml aqueous solution containing 380 ± 50 mg/L Ca(II) during 2 hours, the CK-ACTS showed more effective (i.e., Ca(II) removal of 34.73%) as compared to CK-WCTS (i.e., only 2.08%). In the case of As(III) removal, 0.5 g of adsorbent (i.e., pure ACTS and CK-ACTS composite) was applied to test with 50 ml artificial aqueous As (III) solution of 500 ± 50 μg/L during 90 mins of operation. The CK-ACTS composite also showed better performance since the highest removal As efficiency of 72% could be obtained after a contacting time of 45 mins, as compared to that produced by pure ACTS (i.e. As removal of 42.42%). The SEM analysis was also conducted to compare the difference in morphology of pure ACTS and CK-ACTS composite.

Modeling heat and mass transfer in granular flows between vertical parallel plates

Gravity-driven granular flows between vertical parallel plates at elevated temperatures are integral in the development of the next generation of particle-based heat exchangers for concentrated solar power. Efficient modeling methodologies that accurately captures the heat transfer mechanisms of temperature-dependent granular flows are essential to effectively design and evaluate these heat exchangers. Transient, pseudo-one-dimensional heat and mass transfer models were developed for inlet flow temperatures between 473 and 1073 K. The mass transfer models for the granular flows were resolved using discrete element method simulation, providing detailed temporal and spatial distributions of flow parameters in good agreement with experimental measurements. The heat transfer model employed a one-dimensional, two-phase, continuum approach, and a system of non-linear differential equations was solved via finite difference method. The particle-to-wall contact heat transfer was determined with an effective thermal conductance model. Radiative heat transfer between particles and walls was also considered. The predicted particle and wall temperatures for two different channel widths of 6.4 and 2 mm were well-correlated to previously obtained experimental measurements with Pearson’s correlation coefficients greater than 0.91. A significant disparity in particle temperature of up to 72 K was observed when radiative heat transfer was omitted, and a maximum temperature difference of 11 K was observed when temperature-dependent granular flow properties were not considered. The model revealed that radiative heat transfer potentially contributed to > 30 % of heat losses in wider channels at high inlet temperatures, and conduction was the dominated heat transfer mechanisms in narrower channels (∼70 %) due to increased particle-to-wall contact. This accurate model, leveraging discrete element method in a streamlined approach, advances the understanding and modeling of heat transfer in granular flows at elevated temperatures, enabling more efficient and reliable solar thermal energy storage and transport.

Wurster fluidised-bed coating: Coarse-graining technique within CFD-DEM in conjunction with heat and mass transfer

In this study, we use a combined CFD-Discrete Element Method to assess predictive capabilities and numerical implications of a coarse-graining technique in Wurster fluidised-bed coaters. We investigated both hydrodynamics and heat and mass transfer and conducted simulations of a full three-phase system for the original and three coarse-grained systems, analysing velocity distributions, macroscopic solid stresses, moisture content and phase temperatures. We achieved a logarithmic simulation speed-up by aggregating up to 64 original particles into each coarse grain. This was accomplished while maintaining fidelity to the original CFD-DEM system in terms of reproducing with high accuracy macroscopic granular flow properties in different regions of a coater (drying, tube and bed regions). By integrating a liquid spray and humid air, we demonstrated that the phase temperatures were accurately predicted within the coarse-grained system, with a high capability of delivering liquid spray distributions with the same uniformity and drying. We also give arguments for choosing a certain degree of coarse-graining as a compromise between a desired reduction of computational costs and a trustworthy reproduction of granular-flow physics encountered in different regions of a Wurster bed. Our findings pave the way to using CFD-DEM to industrially-scaled Wurster-bed systems, which is currently unfeasible due to prohibitive computational costs.

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

Structure evolution analysis of asphalt mixtures during compaction based on particle tracking and granular properties

Pavement compaction is a process of structure evolution of materials accompanied by energy dissipation, which is closely related to the inherent granular properties of asphalt mixture. This research achieved dynamic characterization of particle migration energy and contact force development through particle tracking technique and discrete element simulation. Analytical theories for multi-stage structure evolution and compaction mechanisms were proposed based on granular properties. Results indicate that kinetic, dissipative, and potential energies dynamically represent stages of structure evolution, determined by particle collisions, self-organization into arches, and interlocking reinforcement. The initial density state is established after interparticle collisions, while self-organization occurs as particles adaptively rearrange spatially by rotation in response to unbalanced forces, accompanied by a cyclical strengthening trend of arch formation and collapse. Arches facilitate stress redistribution toward isotropy, with strong contact forces exhibiting a top-down and side-center trend, progressively supported by particles larger than 4.75 mm. Theoretical measures for compaction control were proposed, including pre-calculation of IC, selection of compaction temperature corresponding to the optimum energy efficiency, and control of principal stress deflection within the friction cone. This research aims to provide insight into granular properties and compaction dynamics, thereby contributing to intelligent compaction.

A continuous-discontinuous deformation analysis method for research on the mechanical properties of coarse granular materials

The mechanical properties of coarse granular materials play a crucial role in the safety of rockfill dams. From a mesoscopic viewpoint, the macroscopic mechanical properties of these materials are a result of the interactions between particles and the progression of particle breakage. Traditional continuum-based numerical methods struggle to accurately analyze the mechanical properties of coarse granular materials. Discontinuous deformation analysis (DDA) is a more suitable algorithm for studying these properties due to its significant benefits in block displacement mode and open-close iteration for contact handling. In this paper, a continuous-discontinuous deformation analysis method (CDDA) based on the conventional DDA is developed for the numerical investigation of coarse granular materials' mechanical properties. This method incorporates critical kinetic damping, multi-stageloading, stricter displacement convergence criteria and particle breakage simulation. It can provide a comprehensive representation of deformation, particle breakage, force chain, shear zone, and stress–strain curve evolutions. The CDDA results are found to be consistent with indoor test results and can more effectively disclose the deformation and failure mechanism of coarse granular materials. Furthermore, CDDA is employed to examine the impacts of particle size and end friction, leading to valuable insights regarding these effects.

Demonstrating resonant ultrasound spectroscopy as a viable technique to characterize thermally conditioned high explosive materials

We present results of resonant ultrasound spectroscopy (RUS) measurements applied to granular high explosive materials at different bulk pressing densities and degree of thermal conditioning. The material chosen in this study is a ubiquitously used explosive material known as pentaerythritol tetranitrate (PETN), which is used commercially in civil and defense applications both as a binderized plastic bonded explosive material and an unbinderized neat material. However, changes in granular PETN bulk elastic properties due to thermal conditioning, which could have implications for better understanding environmental aging-related effects, have not been well studied even though it is believed that elasticity may play an important role in explosive material initiation mechanisms. Furthermore, monitoring elastic property changes in granular explosive pressings has not yet been demonstrated using RUS, which is an appealing non-destructive characterization tool that requires only dry point contact with the explosive material. To this end, we report the first study using RUS to quantify the elastic properties of binderized and neat PETN pressings as well as to quantify changes in elastic properties as a function of both thermal conditioning and bulk pressing density. Elastic stiffness coefficients, sometimes more commonly referred to as elastic constants, calculated from the RUS measurements on the different PETN-based materials show a significant increase for the post-conditioned samples compared to the pre-conditioned samples. This trend of increasing elastic properties with thermal conditioning was consistent for different density pressings, different thermal exposure conditions, and even different neat PETN pressings of differing average crystal sizes and/or specific surface areas.

Micromechanism and mathematical model of stress sensitivity in tight reservoirs of binary granular medium

Research on reservoir rock stress sensitivity has traditionally focused on unary granular structures, neglecting the binary nature of real reservoirs, especially tight reservoirs. Understanding the stress-sensitive behavior and mathematical characterization of binary granular media remains a challenging task. In this study, we conducted online-NMR experiments to investigate the permeability and porosity evolution as well as stress-sensitive control mechanisms in tight sandy conglomerate samples. The results revealed stress sensitivity coefficients between 0.042 and 0.098 and permeability damage rates ranging from 65.6% to 90.9%, with an average pore compression coefficient of 0.0168–0.0208 MPa−1. Pore-scale compression occurred in three stages: filling, compression, and compaction, with matrix pores playing a dominant role in pore compression. The stress sensitivity of binary granular media was found to be influenced by the support structure and particle properties. High stress sensitivity was associated with small fine particle size, high fines content, high uniformity coefficient of particle size, high plastic deformation, and low Young's modulus. Matrix-supported samples exhibited a high irreversible permeability damage rate (average = 74.2%) and stress sensitivity coefficients (average = 0.089), with pore spaces more slit-like. In contrast, grain-supported samples showed low stress sensitivity coefficients (average = 0.021) at high stress stages. Based on the experiments, we developed a mathematical model for stress sensitivity in binary granular media, considering binary granular properties and nested interactions using Hertz contact deformation and Poiseuille theory. By describing the change in activity content of fines under stress, we characterized the non-stationary state of compressive deformation in the binary granular structure and classified the reservoir into three categories. The model was applied for production prediction using actual data from the Mahu reservoir in China, showing that the energy retention rates of support-dominated, fill-dominated, and matrix-controlled reservoirs should be higher than 70.1%, 88%, and 90.2%, respectively.

A starch digestion model considering intrinsic granular properties

Starch particle digestion is an important topic in food digestion research. This study has developed a diffusion-reaction model to characterize hindered enzyme diffusion and substrate hydrolysis on the surface and in the interior of porous starch particles. A moving boundary numerical method is applied to account for particle shrinkage caused by surface reaction. This model has been proven to predict the digestion rate of various starch particles of different sizes. The parameter estimation procedure quantifies the properties that are hard to measure by experimental techniques, i.e., diameter, reactive area, and proportion of pores accessible for enzyme as well as susceptibility of starch to enzyme. This work formulates a quantitative procedure for identifying the particle digestion pattern (i.e., outside-in or inside-out) by resorting to the developed model. Computational experiments indicate that in addition to internal architecture, particle size has a significant effect on the digestion pattern.

Nitrospira dominant pin-point flocs with granule-like settleability in stirred tank reactors with oxic/hypoxic/oxic zones.

The characteristics of biomass and microbial community dynamics, in relation to autotrophic nitrification, were studied in two 20 L stirred tank reactors (STR) with oxic/hypoxic/oxic zones. The bioreactors were fed with synthetic wastewater with stepwise increasing ammonia concentrations (50-200 N mg/L) without organic substrate in the first phase (autotrophic phase) for 35 days (R1) and 15 days (R2), followed by a heterotrophic phase (with supplementation of organic substrate). The settling properties of the biomass, represented by pin-point flocs, gradually improved in both reactors during the autotrophic phase. The pin-point flocs of R1 exhibited granule-like settling properties. The SVI30 in RI gradually improved to 29 mL/g MLSS, and the corresponding SVI30/ SVI10 gradually improved to 0.88 during the autotrophic phase. The settling properties of the biomass deteriorated in both bioreactors during the heterotrophic phase. The protein to polysaccharide ratio (PN:PS ratio) gradually increased in the extracted EPS (in both, loosely bound (LB) and tightly bound (TB) EPS) during the autotrophic phase, in both bioreactors. The TB:LB EPS ratio was higher when the pin-point flocs of R1 showed granule-like settling properties, followed by a decline in TB:LB EPS ratio during the heterotrophic phase. A combination of molecular approaches (droplet digital-PCR (dd-PCR) and 16S rRNA gene sequencing) revealed that Nitrospira were the predominant nitrifying bacteria in the pin-point flocs that show granular sludge-like settling properties during autotrophic phase in R1. Comammox Nitrospira was the dominant ammonia oxidizer in seed biomass and at low ammonia concentrations in both bioreactors. The relative abundance of canonical ammonia-oxidizing bacteria increased with an increase in influent-ammonia concentrations.

Observe, inspect, modify: Three conditions for generative AI governance

In a world increasingly shaped by generative AI systems like ChatGPT, the absence of benchmarks to examine the efficacy of oversight mechanisms is a problem for research and policy. What are the structural conditions for governing generative AI systems? To answer this question, it is crucial to situate generative AI systems as regulatory objects: material items that can be governed. On this conceptual basis, we introduce three high-level conditions to structure research and policy agendas on generative AI governance: industrial observability, public inspectability, and technical modifiability. Empirically, we explicate those conditions with a focus on the EU’s AI Act, grounding the analysis of oversight mechanisms for generative AI systems in their granular material properties as observable, inspectable, and modifiable objects. Those three conditions represent an action plan to help us perceive generative AI systems as negotiable objects, rather than seeing them as mysterious forces that pose existential risks for humanity.

Effect of non-starch components on the structural properties, physicochemical properties and in vitro digestibility of waxy highland barley starch

Highland barley (HB) endosperm with an amylose content of 0–10 % is called waxy HB (WHB). WHB is a naturally slow-digesting grain, and the interaction between its endogenous non-starch composition and the WHB starch (WHBS) has an important effect on starch digestion. This paper focuses on the mechanisms by which the components of β-glucan, proteins and lipids affect the molecular, granular, crystalline structure and digestive properties of WHBS. After eliminating the main nutrients except for starch, the estimated glycemic index (eGI) of the samples rose from 62.56 % to 92.93 %, and the rapidly digested starch content increased from 60.81 % to 98.56 %, respectively. The resistant starch (RS) content, in contrast, dropped from 38.61 % to 0.13 %. Comparatively to lipids, β-glucan and protein contributed more to the rise in eGI and decline in RS content. The crystalline characteristics of starch were enhanced in the decomposed samples. The samples' gelatinization properties improved, as did the order of the starch molecules. Protein and β-glucan form a dense matrix on the surface of WHBS particles to inhibit WHBS digestion. In summary, this study revealed the mechanism influencing the digestibility of WHBS from the perspective of endogenous non-starch composition and provided a theoretical basis to develop slow-digesting foods.

Effects of salinity and betaine addition on anaerobic granular sludge properties and microbial community succession patterns in organic saline wastewater

In this study, the effects of different salinity gradients and addition of compatible solutes on anaerobic treated effluent water qualities, sludge characteristics and microbial communities were investigated. The increase in salinity resulted in a decrease in particle size of the granular sludge, which was concentrated in the range of 0.5-1.0 mm. The content of EPS (extracellular polymeric substances) in the granular sludge gradually increased with increasing salinity and the addition of betaine (a typical compatible solute). Meanwhile, the microbial community structure was significantly affected by salinity, with high salinity reducing the diversity of bacteria. At higher salinity, Patescibacteria and Proteobacteria gradually became the dominant phylum, with relative abundance increasing to 13.53% and 12.16% at 20 g/L salinity. Desulfobacterota and its subordinate Desulfovibrio, which secrete EPS in large quantities, dominated significantly after betaine addition.Their relative abundance reached 13.65% and 7.86% at phylum level and genus level. The effect of these changes on the treated effluent was shown as the average chemical oxygen demand (COD) removal rate decreased from 82.10% to 79.71%, 78.01%, 68.51% and 64.55% when the salinity gradually increased from 2 g/L to 6, 10, 16 and 20 g/L. At the salinity of 20 g/L, average COD removal increased to 71.65% by the addition of 2 mmol/L betaine. The gradient elevated salinity and the exogenous addition of betaine played an important role in achieving stability of the anaerobic system in a highly saline environment, which provided a feasible strategy for anaerobic treatment of organic saline wastewater.