Modulus Coefficient Research Articles

Tensile and compressive properties of bamboo scrimber under different temperature conditions

AbstractBamboo scrimber demonstrates vulnerability to environmental temperature fluctuations, such as exposure to cold or fire, when deployed in structural applications. Consequently, its mechanical properties can substantially diverge from the intended design values under varying thermal conditions. This study aims to study the tensile and compressive properties of bamboo scrimber under different temperatures to provide data support for studying bamboo scrimber under low and high temperatures. The compressive properties of bamboo scrimber under temperatures ranging from −30°C to 250°C and the tensile properties under −20°C to 250°C were determined by a series of tests with a total of 125 specimens. The results show that the mass loss of bamboo scrimber increases gradually with the increase in temperature, and the increasing trend intensifies after 120°C. With the increase of temperature, the failure mode of the specimens under compression changes from the bottom compression cracking damage to the local destabilization of longitudinal fibers, while the tensile damage modes aren't influenced by temperature, and both “straight‐line” and “folded‐line” types of damage modes occur at different temperatures. The tensile and compressive strengths and elastic modulus of the specimens decreased with the increase in temperature, and the strength was more susceptible to the temperature than the elastic modulus: a rise in temperature from 20°C to 250°C resulted in a reduction of compressive strength and tensile strength by 80.80% and 84.11%, respectively, the compressive modulus and tensile modulus experienced decreases of 49.51% and 53.28%. Furthermore, equations of temperature influence coefficients of strength and elastic modulus were established based on the test results.Highlights Bamboo scrimber's mechanical properties under different temperatures are studied. Tendency and explanation of temperature influence coefficients are analyzed. Temperature coefficient equations for strength and elastic modulus are proposed.

3D novel zero Poisson’s ratio metamaterials with programmable thermal expansion and Young's modulus

The shape stability of the structure plays a very important role in deep space exploration engineering. This paper presents 3D novel zero Poisson’s ratio metamaterial (ZPRM) with programmable thermal expansion and Young's modulus through the combination of bi-material triangles and re-entrant hexagonal structures. The coefficient of thermal expansion (CTE) and Young's modulus of the ZPRM-1 are predicted by establishing theoretical analysis models based on the classical beam theory. The mechanical response behavior of the ZPRM −1 under small deformation is simulated by finite element analysis (FEA). 3D printing is adopted to design and prepare experimental specimens, and compression experiments are carried out to certify the accuracy of the theories and FEA of Young's modulus. The results of parameter analysis show that the ZPRM-1 can tune the CTE and Young's modulus in a wide range when the geometric parameters and material combination are changed. In addition, the mechanical properties of the ZPRM-1 under the combined field of temperature and mechanical loads are investigated to achieve the tunable Young's modulus from positive to negative. This study provides a feasible reference for temperature and mechanical sensitivity instruments.

ANN based fire resistance prediction of FRP-strengthened RC slabs with fireproof panel including air layer

In this study, an Artificial Neural Network (ANN) model to predict the fire resistance of Fiber Reinforced Plastic (FRP) strengthened Reinforced Concrete (RC) slabs with fireproof panel including air layer exposed to fire is developed. FRP-strengthened RC slabs with fireproof panel including air layer has a structure that improves structural performance and fire resistance by placing FRP and a fireproof panel including air at the bottom of the RC slab. First, fire test is performed using the air layer as a variable, and the validity of the software ABAQUS heat transfer analysis is verified by comparing it with the fire test results. Through this heat transfer analysis, the temperature distribution of the slab is determined, and 1521 data sets are obtained by calculating the strength reduction coefficient and elastic coefficient reduction coefficient of each material. The data consist of eight input parameters: the type of fire curve, fire exposure time, insulation thickness, air layer thickness, concrete covering thickness, and FRP thickness. The output parameter is the value of the strength and elastic modulus reduction coefficient for each material. The average values of MSE, RMSE, R, and SSE for all output parameters, which are performance indicators of the ANN model, are 0.00202, 0.03978, 0.98235, and 1.10445, respectively, and the developed ANN model has high computational accuracy and high generalization ability. Therefore, the ANN model developed here can determine the mechanical properties of each material in FRP-strengthened RC slabs with fireproof panel including air layer exposed to fire and evaluate the fire resistant without complex calculations. Through contribution and sensitivity analysis, the effect of input data on output data is confirmed.

Design on antibacterial and cytocompatible TiO2-CuxO/Ag coating through regulation of ions release

Developing antibacterial and biocompatible coatings remains a challenge. A promising new thought is addressed to control the ion release behaviors through the design of the phases, structures, and morphologies of the products. In this study, TiO2-CuxO/Ag coatings were prepared via co-sputtering combined with annealing, the changes brought by different annealing temperatures were characterized, the physical, electrochemical, and antibacterial properties were concerned, and the relationship between biological performance and ions-releasing behavior was investigated. Results showed that the TiO2-CuxO/Ag coatings performed the morphologies of larger Ag particles seeded like islands on the dense CuO, such features improved the hydrophilicity and corrosion resistance of the Ti substrate. Rising the annealing temperature further enhanced the surface roughness, hydrophilicity, Young's modulus, hardness, and dynamic coefficient of friction of the coatings. Within the initial 3 h of soaking, both metal ions contributed to playing the antibacterial roles and produced a synergistic enhancement effect to satisfy the reduction of Staphylococcus aureus to 99.9%. In the next 3–120 h soaking, Ag releasing was suppressed and Cu releasing maintained its slow and stable trend, which made sure that the MC3T3-E1 cells could proliferate and adhere on the negatively charged coating surface, and copper oxide nanoparticles were phagocytized by cells. Among all TiO2-CuxO/Ag coatings, the M500 sample displayed superior performances on the surface roughness, contact angle, mechanical Young's modulus, and surface hardness, also realized the aim of killing pathogenic bacteria first and then activating cell survival, which enabled it to be potentially applied in clinical treatment.

Tectonic fractures induced by strike-slip faulting in intracratonic ultradeep carbonate rocks: Insights from the finite element method and self-adaptive constraints computational model for boundary conditions

Numerical simulations of the paleostress field during a period of tectonic fracture formation and rock failure criteria are used to quantitatively predict the development and occurrence of tectonic fractures induced by the formation of the SB18 fault zone in the Middle Ordovician Yijianfang Formation of the Shunnan area, Tarim Basin, China. The results of acoustic emission experiments, mechanical property measurements, and tectonic fracture occurrence observations obtained from core descriptions and fullbore formation microimager logs are combined with the Andersonian model of faulting and the finite element method, which is widely used for the numerical simulation of stress fields, to investigate the paleotectonic and in situ stress fields via numerical simulation. The quantitative prediction of the opening pressure and opening sequence of tectonic fractures is based on the occurrence of tectonic fracture, numerical simulation of in situ stresses, and coordinate system conversion. The results show that the width of the fracture zone induced by strike-slip faulting is ∼310 m. The degree of fracture development is significantly increased when the Young’s modulus, paleostress difference, and paleostress difference coefficient of the rock are elevated. The current horizontal principal stress is positively correlated with the distance from the fault, and the elevated areal density of the secondary faults causes a clockwise deflection of the horizontal stress direction. SSE-striking shear fractures with orientations ranging from 140° to 150° and two sets of tensional fractures with orientations ranging from −40° to −35° and 55° to 60° are preferentially opened in the water injection development stage of the reservoir. As the horizontal stress difference, horizontal stress difference coefficient, and angle between the maximum horizontal principal stress and a fracture decrease, the fracture opening pressure decreases. At the structural highs (burial depths <6225 m) and lows (burial depths >6225 m), the fracture burial depth is positively and negatively correlated with the opening pressure, respectively. Quantitative prediction of tectonic fracture developmental characteristics, opening pressure, and the opening sequence and investigation of the main factors that control their development can help to identify and support opportunities for hydrocarbon exploration and development of fractured carbonate reservoirs.

Erratum to: “Coefficients of multiple Fourier-Haar series and variational modulus of continuity” [Bulletin of the Karaganda University. Mathematics series, No. 4(112), 2023, pp. 21–29

Prof. Tuncay Aktosun requests retraction of his co-authorship for the following reason. Prof. Tuncay Aktosun has not been involved in the publication process and has not participated in any discussions, therefore, he cannot hold responsibility for any results in the published paper.

Prediction of Rheological Parameters of Polymers by Machine Learning Methods

Introduction. All polymer materials and composites based on them are characterized by pronounced rheological properties, the prediction of which is one of the most critical tasks of polymer mechanics. Machine learning methods open up great opportunities in predicting the rheological parameters of polymers. Previously, studies were conducted on the construction of predictive models using artificial neural networks and the CatBoost algorithm. Along with these methods, due to the capability to process data with highly nonlinear dependences between features, machine learning methods such as the k-nearest neighbor method, and the support vector machine (SVM) method, are widely used in related areas. However, these methods have not been applied to the problem discussed in this article before. The objective of the research was to develop a predictive model for evaluating the rheological parameters of polymers using artificial intelligence methods by the example of polyvinyl chloride.Materials and Methods. This paper used k-nearest neighbor method and the support vector machine to determine the rheological parameters of polymers based on stress relaxation curves. The models were trained on synthetic data generated from theoretical relaxation curves constructed using the nonlinear Maxwell-Gurevich equation. The input parameters of the models were the amount of deformation at which the experiment was performed, the initial stress, the stress at the end of the relaxation process, the relaxation time, and the conditional end time of the process. The output parameters included velocity modulus and initial relaxation viscosity coefficient. The models were developed in the Jupyter Notebook environment in Python.Results. New predictive models were built to determine the rheological parameters of polymers based on artificial intelligence methods. The proposed models provided high quality prediction. The model quality metrics in the SVR algorithm were: MAE – 1.67 and 0.72; MSE – 5.75 and 1.21; RMSE – 1.67 and 1.1; MAPE – 8.92 and 7.3 for the parameters of the initial relaxation viscosity and velocity modulus, respectively, with the coefficient of determination R2 – 0.98. The developed models showed an average absolute percentage error in the range of 5.9 – 8.9%. In addition to synthetic data, the developed models were also tested on real experimental data for polyvinyl chloride in the temperature range from 20° to 60°C.Discussion and Conclusion. The approbation of the developed models on real experimental curves showed a high quality of their approximation, comparable to other methods. Thus, the k-nearest neighbor algorithm and SVM can be used to predict the rheological parameters of polymers as an alternative to artificial neural networks and the CatBoost algorithm, requiring less effort to preset adjustment. At the same time, in this research, the SVM method turned out to be the most preferred method of machine learning, since it is more effective in processing a large number of features

Wavelet-based photoacoustic viscoelastographic microscopy using photoacoustic damped oscillation effect

Viscoelastic characterization of biological tissue has significant biomedical value. In this study, we propose a wavelet-based photoacoustic viscoelastographic microscopy to characterize the viscoelasticity of tissues beneath the optical scattering depth from photoacoustic oscillation signals. Irradiated by laser pulses, biological tissue absorbs energy, expands, continues oscillating, and emits damped transient ultrasonic waves, i.e., photoacoustic oscillation signals, for a short time. A damped oscillation wavelet is applied to map photoacoustic oscillation signals into a representation of time, frequency, and decay rate. We can evaluate the frequency and decay rate of the photoacoustic oscillation signals. By considering the interrelationships among frequency, decay rate, shear modulus, and shear viscosity coefficient, we can generate images that depict the shear modulus image and shear viscosity coefficient image within the tissue. These images of the shear modulus and shear viscosity coefficient collectively form the viscoelastogram of the tissue, offering a comprehensive portrayal of its viscoelastic properties. Our study has potential biomedical value and may improve the accurate diagnosis of diseases and achieve more effective early interventions.

Damage Monitoring of Regularly Arrayed Short-Fiber-Reinforced Composite Laminates under Tensile Load Based on Acoustic Emission Technology.

Carbon-fiber-reinforced polymer (CFRP) composites are widely used in lightweight structures because of their high specific strength, specific modulus, and low coefficient of thermal expansion. Additionally, the unidirectionally arrayed chopped strand (UACS) laminates have excellent mechanical properties and flowability, making them suitable for fabricating structures with complex geometry. In this paper, the damage process of UACS quasi-isotropic laminates under tensile load was tested using acoustic emission detection technology. The mechanical properties and damage failure mechanism of UACS laminates were studied combined with finite element calculation. By comparing and analyzing the characteristic parameters of acoustic emission signals such as amplitude, relative energy, and impact event, it is found that acoustic emission behavior can accurately describe the damage evolution of specimens during loading. The results show that the high-amplitude signals representing fiber fracture in continuous fiber laminates are concentrated in the last 41%, while in UACS laminates they are concentrated in the last 30%. In UACS laminates, more of the damage is caused by matrix cracks and delamination with medium- and low-amplitude signals, which indicates that UACS laminates have a good suppression effect on damage propagation. The stress-strain curves obtained from finite element analysis agree well with the experiment results, showing the same damage sequence, which confirms that the model described in this research is reliable.

Thermally-induced cracking behaviors of coal reservoirs subjected to cryogenic liquid nitrogen shock

The benefits of using cryogenic liquid nitrogen shock to enhance coal permeability have been confirmed from experimental perspectives. In this paper, we develop a fully coupled thermo-elastic model in combination with the strain-based isotropic damage theory to uncover the cooling-dominated cracking behaviors through three typical cases, i.e. coal reservoirs containing a wellbore, a primary fracture, and a natural fracture network, respectively. The progressive cracking processes, from thermal fracture initiation, propagation or cessation, deflection, bifurcation to multi-fracture interactions, can be well captured by the numerical model. It is observed that two hierarchical levels of thermal fractures are formed, in which the number of shorter thermal fractures consistently exceeds that of the longer ones. The effects of coal properties related to thermal stress levels and thermal diffusivity on the fracture morphology are quantified by the fracture fractal dimension and the statistical fracture number. The induced fracture morphology is most sensitive to changes in the elastic modulus and thermal expansion coefficient, both of which dominate the complexity of the fracture networks. Coal reservoir candidates with preferred thermal-mechanical properties are also recommended for improving the stimulation effect. Further findings are that there exists a critical injection temperature and a critical in-situ stress difference, above which no thermal fractures would be formed. Preexisting natural fractures with higher density and preferred orientations are also essential for the formation of complex fracture networks. The obtained results can provide some theoretical support for cryogenic fracturing design in coal reservoirs.

3D MR elastography-based stiffness as a marker for predicting tumor grade and subtype in cervical cancer

BackgroundIncreasing evidence has indicated that high tissue stiffness (TS) may be a potential biomarker for evaluation of tumor aggressiveness. PurposeTo investigate the value of magnetic resonance elastography (MRE)-based quantitative parameters preoperatively predicting the tumor grade and subtype of cervical cancer (CC). Study typeRetrospective. PopulationTwenty-five histopathology-proven CC patients and 7 healthy participants. Field strength/sequence3.0T, magnetic resonance imaging (MRI) (LAVA-flex) and MRE with a three-dimensional spin-echo echo-planar imaging. AssessmentThe regions of interest (ROIs) were manually drawn by two observers in tumors to measure mean TS, storage modulus (G′), loss modulus (G″) and damping ratio (DR) values. Surgical specimens were evaluated for tumor grades and subtypes. Statistical testsIntraclass correlation coefficient (ICC) was expressed in terms of inter-observer agreements. t-test or Mann-Whitney nonparametric test was used to compare the complex modulus and apparent diffusion coefficient (ADC) values between different tumor groups. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate the diagnostic performance. ResultsThe TS of endocervical adenocarcinoma (ECA) group was significantly higher than that in squamous cell carcinoma (SCC) group (5.27 kPa vs. 3.44 kPa, P = 0.042). The TS also showed significant difference between poorly and well/moderately differentiated CC (5.21 kPa vs. 3.47 kPa, P = 0.038), CC patients and healthy participants (4.18 kPa vs. 1.99 kPa, P < 0.001). The cutoff value of TS to discriminate ECA from SCC was 4.10 kPa (AUC: 0.80), while it was 4.42 kPa to discriminate poorly from well/moderately differentiated CC (AUC: 0.83), and 2.25 kPa to distinguish normal cervix from CC (AUC: 0.88), respectively. There were no significant difference in G″, DR and ADC values between any subgroups except for comparison of healthy participants and CC patients (P = 0.001, P = 0.004, P < 0.001, respectively). Data conclusion3D MRE-assessed TS shows promise as a potential biomarker to preoperatively assess tumor grade and subtype of CC.

Modifying gas transfer membranes with nanoscale zero-valent iron: effects on membrane material properties, treatment performance, and biofilm thickness.

Excessive membrane biofilm growth on membrane fibers depends on various factors, with membrane properties playing a pivotal role in influencing microbial affinity for the membrane. To investigate the antibacterial impact of nano-sized zero-valent iron (nZVI) on membrane biofilm structure, pristine (polyvinylidene fluoride (PVDF)) only: HF-0 (PVDF:20/nZVI:0 w/w) and four gas transfer membranes (PVDF:nZVI at different concentrations: HF-1 (PVDF:20/nZVI:0.25 w/w), HF-2 (PVDF:20/nZVI:0.50 w/w), HF-3 (PVDF:20/nZVI:0.75 w/w), HF-4 (PVDF:20/nZVI:1.0 w/w)) were produced. These membranes were assessed for surface morphology, porosity, gas permeability, and biofilm thickness, which ultimately affect biochemical reaction rates in membrane biofilm reactors (MBfRs). Various MBfRs utilizing these gas transfer membranes were operated at different hydraulic retention times (HRTs) and oxygen pressures to assess chemical oxygen demand (COD) removal efficiency and nitrification performance. Incorporating nZVI into the PVDF polymer solution increased surface hydrophilicity and porosity but reduced Young's Modulus and oxygen diffusion coefficients. Confocal laser scanning microscopy (CLSM) analysis revealed an average biofilm thickness of 700 μm in HF-0, HF-1, and HF-3, with a 100 μm decrease in HF-2, even though Escherichia coli growth was observed in HF-3 fibers. Regardless of nZVI dosage, a significant decline in COD removal and nitrification rates occurred at low HRTs and gas pressures.

Under Sulfate Dry–Wet Cycling: Exploring the Symmetry of the Mechanical Performance Trend and Grey Prediction of Lightweight Aggregate Concrete with Silica Powder Content

In order to improve the mechanical properties and durability of lightweight aggregate concrete in extreme environments, this study utilized Inner Mongolia pumice as the coarse aggregate to formulate pumice lightweight aggregate concrete (P-LWAC) with a silica powder content of 0%, 2%, 4%, 6%, 8%, and 10%. Under sulfate dry–wet cycling conditions, this study mainly conducted a mass loss rate test, compressive strength test, NMR test, and SEM test to investigate the improvement effect of silica powder content on the corrosion resistance performance of P-LWAC. In addition, using grey prediction theory, the relationship between pore characteristic parameters and compressive strength was elucidated, and a grey prediction model GM (1,3) was established to predict the compressive strength of P-LWAC after cycling. Research indicates that under sulfate corrosion conditions, as the cycle times and silica powder content increased, the corrosion resistance of P-LWAC showed a trend of first increasing and then decreasing. At 60 cycles, P-LWAC with a content of 6% exhibited the lowest mass loss rate and the highest relative dynamic elastic modulus, compressive strength, and corrosion resistance coefficient. From the perspective of data distribution, various durability indicators showed a clear mirror symmetry towards both sides with a silica powder content of 6% as the symmetrical center. The addition of silica fume reduced the porosity and permeability of P-LWAC, enhanced the saturation degree of bound fluid, and facilitated internal structural development from harmful pores towards less harmful and harmless pores, a feature most prominent at the 6% silica fume mixing ratio. In addition, a bound fluid saturation and pore size of 0.02~0.05 μm/% exerted the most significant influence on the compressive strength of P-LWAC subjected to 90 dry–wet cycles. Based on these two factors, grey prediction model GM (1,3) was established. This model can accurately evaluate the durability of P-LWAC, improving the efficiency of curing decision-making and construction of concrete materials.

Numerical modeling and statistical analysis of the effect of thermomechanical properties on residual stresses in feldspar‐based ceramic materials after thermal tempering

AbstractThis study focuses on the investigation of the impact of the thermomechanical properties of ceramic materials on residual stresses generated after the thermal tempering process. A sodium feldspar matrix was chosen for numerical simulations, with variations in its thermomechanical properties of up to ± 20%, to encompass a range of properties exhibited by other ceramic materials. The simulations demonstrated that the viscosity of the material had the most significant influence on residual stress generation, while the coefficient of thermal expansion, modulus of elasticity, and effective diffusivity also contributed to residual stress formation. A statistical analysis based on a 24 factorial design revealed that increasing residual compressive stress on the surface was achievable by increasing the coefficient of thermal expansion and modulus of elasticity, as well as the viscosity, while reducing the effective thermal diffusivity. Finally, a mathematical model was proposed to relate the thermomechanical properties of the ceramic material to the residual stresses observed on the surface following thermal tempering.

Machine-learned atomic cluster expansion potentials for fast and quantum-accurate thermal simulations of wurtzite AlN

Thermal transport in wurtzite aluminum nitride (w-AlN) significantly affects the performance and reliability of corresponding electronic devices, particularly when lattice strains inevitably impact the thermal properties of w-AlN in practical applications. To accurately model the thermal properties of w-AlN with high efficiency, we develop a machine learning interatomic potential based on the atomic cluster expansion (ACE) framework. The predictive power of the ACE potential against density functional theory (DFT) is demonstrated across a broad range of properties of w-AlN, including ground-state lattice parameters, specific heat capacity, coefficients of thermal expansion, bulk modulus, and harmonic phonon dispersions. Validation of lattice thermal conductivity is further carried out by comparing the ACE-predicted values to the DFT calculations and experiments, exhibiting the overall capability of our ACE potential in sufficiently describing anharmonic phonon interactions. As a practical application, we perform a lattice dynamics analysis using the potential to unravel the effects of biaxial strains on thermal conductivity and phonon properties of w-AlN, which is identified as a significant tuning factor for near-junction thermal design of w-AlN-based electronics.

Simultaneous Improvement of the Strength and Plasticity for Ti‐Reinforced Fine‐Grained Magnesium Matrix Composites Prepared by Powder Metallurgy

Ti‐reinforced AZ61 magnesium matrix composites, demonstrating enhanced strength and plasticity, are synthesized via powder metallurgy method, including mechanical milling and spark plasma sintering. This study investigates the evolution of microstructure and compressive mechanical properties of Ti/AZ61 composites across various Ti weight percentages: 0%, 5%, 10%, 15%, and 20%. The composites at 5, 10, 15, and 20 wt% Ti concentrations are effectively compacted, achieving relative densities of 99.1%, 99.4%, 98.7%, and 98.6%, respectively. The integration of Ti particles facilitates a refinement of the Mg grain size. The average Mg grain size in the AZ61 alloy is refined from 8.7 ± 3.6 to 7.2 ± 4.5 μm and 4.4 ± 2.2 μm upon the addition of 5 and 10 wt% Ti particles. Conversely, incremental Ti concentrations of 15 and 20 wt% result in minor increases in the average Mg grain size to 5.3 ± 2.6 and 5.7 ± 3.2 μm, respectively. Interfacial compounds, notably Al3Ti, are identified. Compressive mechanical properties, including compressive yield stress (CYS), ultimate compressive stress (UCS), and compressive failure strain (CFS), are synergistically enhanced with Ti particle incorporation. Optimal mechanical properties, specifically CYS at 250 MPa, UCS at 502 MPa, and CFS at 13%, are observed in the 10 wt% Ti/AZ61 composite. The enhanced compressive behavior is attributed to strong interfacial bonding between deformable Ti and Mg, effective load transfer, and grain refinement. Additional contributing factors include variations in the elastic modulus and thermal expansion coefficients between Ti and Mg. The fracture mechanisms observed in the Ti/AZ61 composites involve both ductile and brittle modes of failure.

Thermal effect on the modal characteristics of the rotor of a typical cryogenic turbine for helium refrigerator

The helium turbine is a critical component of the cryogenic system for nuclear fusion devices. To ensure the turbine's steady functioning and avoid resonance, it is essential to understand and clarify the influence of key factors on its modal characteristics. This paper investigates the influence of thermal effect, fluid-structure interaction and rotational effects on the intrinsic frequency of a helium turbine used in the Comprehensive Research Facility for Fusion Technology (CRAFT) cryogenic system. The effects of coefficient of thermal expansion, thermal conductivity and Young's modulus on the intrinsic frequency of the rotor are explored, considering these thermal factors that vary with temperature. The results indicate that thermal effect has the greatest influence on the intrinsic frequency of the rotor over rotational effectand fluid-structure interaction. Lower-order modes are more sensitive to changes in thermal conductivity, while higher-order modes are more sensitive to changes in Young's modulus at low temperatures. The intrinsic frequency of the rotor is more sensitive to changes in the thermal factors of the shaft rather than the thermal factors of the impellers.

Quantitative Prediction of the Development and Opening Sequence of Fractures in an Ultradeep Carbonate Reservoir: A Case Study of the Middle Ordovician in the Shunnan Area, Tarim Basin, China

Summary Quantitative prediction of reservoir tectonic fracture development characteristics, opening pressures, and opening sequences is critical in the exploration and development of oil- and gas-bearing reservoirs and thus has received widespread attention. Using numerical simulations of the paleostress field during the formation of tectonic fractures and the rock fracture criterion, we predict the development and occurrence of fractures in the Middle Ordovician Yijianfang Formation in the Shunnan region of the Tarim Basin, China. The local paleostress fields reflected by the mechanical properties and occurrence of tectonic fractures obtained from core descriptions, acoustic emission (AE) experiments, paleomagnetic experiments, sound velocity measurements, and borehole breakouts were used to determine the regional paleostress and in-situ stress. We established a geomechanical model by combining the mechanical parameters of the rocks with the finite element method (FEM), optimizing the boundary conditions with a self-adaptive constraint algorithm, and conducting numerical simulations of the in-situ stresses. Fracture occurrence and numerical simulation results of the in-situ stress field were used to determine the opening pressure (Pk) and opening sequence of the fractures. The level of fracture development decreases away from the strike-slip fault in the study area. Fracture development is positively correlated with the Young’s modulus, paleostress difference, and paleostress difference coefficient of the rock. The direction of the maximum horizontal principal stress is from north-northeast (NNE) to northeast (NE). Initially, shear fractures and tensional fractures oriented NNE 30°–35° and NE 40°–45°, respectively, open during the water injection process. Pk is positively correlated with the horizontal stress difference coefficient and the angle between the fracture strike and the maximum horizontal principal stress. At the structural highs (burial depths shallower than 6450 m) and the structural lows (burial depths deeper than 6450 m), the burial depth correlates negatively and positively with Pk, respectively. This investigation of the development, occurrence, Pk, and opening sequence of tectonic fractures and their principal controlling factors will have a positive impact on the future exploration and production opportunities of similar fractured reservoirs.

산화아연 나노입자 유형이 카라기난 기반 복합 필름의 구조, 기계적 및 항균 특성에 미치는 영향

In this study, zinc oxide nanoparticles (ZnONPs) were synthesized using three distinct zinc salts: zinc acetate, zinc chloride, and zinc nitrate. These ZnONPs were subsequently utilized in the fabrication of carrageenan-ZnONPs (Car-ZnONPs) composite films. The study assessed influence of the various ZnONPs on the morphological, water vapor barrier, color, optical, and antimicrobial properties of the Car-ZnONPs composite films. The surface morphology and UV-blocking attributes of the composite films were affected by the type of ZnONPs used, but their surface color, transparency, and chemical structure remained unaltered. The composite film's thickness and elongation at break (EB) significantly increased, while the tensile strength significantly decreased. In contrast, film’s elastic modulus (EM) and water vapor permeability coefficient (WVP) showed no significant difference. All the composite films with added ZnONPs demonstrated potent antibacterial activity against Escherichia coli O157:H7 and Listeria monocytogenes. Among the carrageenan-based composite films, Car-ZnONPsZC showed the highest antibacterial and UV-blocking properties, and its elongation at break was significantly higher than that of the pure carrageenan films. This suggests that ZnONPs composite films have the potential to be used as an active packaging film, preserve the safety of the packaged food and extend shelf life.

Phase-field cohesive zone modeling of hydro-thermally induced fracture in hot dry rock during liquid nitrogen fracturing

Liquid nitrogen (LN2) fracturing is regarded as a viable alternative for the efficient development of hot dry rock (HDR) resources due to its main advantage in producing complex fracture networks and lowering breakdown pressure. However, the fracturing mechanisms and major factors controlling the LN2 fracturing efficiency are still poorly understood. A thermo-hydro-mechanical-damage (THMD) coupling model is proposed to study the fracture initiation/propagation behavior of LN2 fracturing under various fracturing parameters and reservoir conditions based on a phase-field cohesive zone method (PF-CZM). The characteristic differences between LN2 and water fracturing are compared. Results indicate that the tensile stress of LN2 fracturing is concentrated at the tip of fractures. When the HDR reservoirs are undertaken lower stress level with higher initial rock temperature, the damage ratio can be enhanced. Young's modulus and thermal expansion coefficient are the key petrophysical and mechanical properties affecting the LN2 fracturing performance. The optimal pressurization rate is 0.2 MPa/s. It indicated that a balanced contribution of thermal stress and fluid pressure is crucial to the bifurcation of major fracture and forming complex fracture networks. The major findings of the study are expected to provide theoretical guidance and computational simulation basis for the LN2 fracturing on HDR reservoirs.