Velocity Modulus Research Articles

Resistance- and endurance-trained young men display comparable carotid artery strain parameters that are superior to untrained men.

Central arterial stiffness, a predictor of cardiovascular risk, attenuates with endurance-exercise in ageing populations. However, in young individuals, this effect is inconsistent and emerging evidence suggests resistance-exercise may increase arterial stiffness. Two-dimensional (2D)-Strain imaging of the common carotid artery (CCA) is more sensitive at detecting endurance-training induced alterations in CCA stiffness than conventional methods, but has not been used to examine CCA stiffness in young resistance-trained individuals. Therefore, we compared CCA 2D-Strain parameters at rest, during acute exercise and recovery between resistance-trained, endurance-trained, and untrained young men. Short-axis CCA ultrasound images were obtained from 12 endurance-trained [27yrs (95%CI; 24-29)], 14 resistance-trained [24yrs (23-26)] and 12 untrained [23yrs (22-24] men at rest, during isometric handgrip (IHG) exercise and recovery. 2D-Strain analysis quantified CCA peak circumferential strain (PCS) and systolic (S-SR) and diastolic (D-SR) strain rates. Conventional stiffness indices included aortic pulse-wave velocity, CCA β-stiffness (β1) and Petersons elastic modulus (Ep). Resting conventional stiffness indices were not different between groups (P > 0.05). Resting PCS and S-SR were comparable between resistance- [11.6% (10.6-12.5) and 1.46s-1 (1.37-1.55), respectively] and endurance-trained [11.4% (10.7-12.2) and 1.5s-1 (1.38-1.62)] men and superior to untrained men [9.5% (9.19-9.9); P < 0.004 and 1.24s-1 (1.17-1.31); P < 0.018)]. Both trained groups displayed comparable reductions in PCS and S-SR during IHG, which returned to resting values during recovery (P < 0.001), whereas these parameters remained unchanged in untrained men. D-SR decreased during IHG in all groups (P < 0.001), but to a lesser extent in endurance-trained men (P < 0.023), whereas β1 and Ep increased to a similar magnitude in all groups and returned to resting values during recovery (P < 0.001). Resistance- and endurance-trained men display comparable CCA 2D-Strain parameters that are superior to untrained men, which contends previous reports that resistance-training increases CCA stiffness.

Response Patterns of Acoustic Wave Characteristics to Reservoir Petrophysical Parameters in Different Bedding Directions: A Case Study of Low- and Middle-Rank Coals in Xinjiang, China.

The physical properties of coal reservoirs, important parameters for evaluating the production potential of coalbed methane (CBM) resources, can be assessed nondestructively and in real-time using acoustic wave technology. In this study, we collected 48 low- and middle-rank coal samples oriented in different bedding directions from seven typical coal mines, encompassing the Zhunan, Tuha, and Kuqa-Bay coalfields in Xinjiang, China. We clarified the characteristics of the physical parameters (apparent density, fracture, porosity, and permeability) and acoustic wave of coal variations through acoustic wave, porosity, and permeability experiments, revealing the response law of acoustic wave characteristics to the physical parameters of coal. The results indicated that the acoustic wave velocity and dynamic elastic modulus (E d) of coal samples oriented in the perpendicular bedding direction are larger than those oriented in the parallel bedding direction; however, the dynamic Poisson's ratio (μd) of coal samples oriented in different bedding directions does not significantly differ. The existence of fractures significantly reduces the acoustic wave velocity and E d of the coal. The greater the apparent density of coal, the tighter its structure, resulting in a faster acoustic wave velocity. The larger the porosity of coal, the greater its internal voids, leading to a more pronounced attenuation of acoustic energy and a slower acoustic wave velocity. The more developed and interconnected the bedding fractures of coal bodies oriented in the parallel bedding direction, the higher their permeability, resulting in a smaller decrease in acoustic wave velocity. Conversely, the more developed the bedding fractures of coal bodies oriented in the perpendicular bedding direction, the more pronounced their attenuation of acoustic wave velocity. Finally, the regression equations for E d with the square of P-wave velocity (V P 2) and μd with the square ratio of V P to S-wave velocity (V P 2/V S 2) were established for coal. The study findings can help evaluate and predict the reservoir quality of coal seams, assess CBM, and improve the safety and efficiency of its extraction.

Thermophysical-mechanical behaviors of hot dry granite subjected to thermal shock cycles and dynamic loadings

Exploring dynamic mechanical responses and failure behaviors of hot dry rock (HDR) is significant for geothermal exploitation and stability assessment. In this study, via the split Hopkinson pressure bar (SHPB) system, a series of dynamic compression tests were conducted on granite treated by cyclic thermal shocks at different temperatures. We analyzed the effects of cyclic thermal shock on the thermal-related physical and dynamic mechanical behaviors of granite. Specifically, the P-wave velocity, dynamic strength, and elastic modulus of the tested granite decrease with increasing temperature and cycle number, while porosity and peak strain increase. The degradation law of dynamic mechanical properties could be described by a cubic polynomial. Cyclic thermal shock promotes shear cracks propagation, causing dynamic failure mode of granite to transition from splitting to tensile-shear composite failure, accompanied by surface spalling and debris splashing. Moreover, the thermal shock damage evolution and coupled failure mechanism of tested granite are discussed. The evolution of thermal shock damage with thermal shock cycle numbers shows an obvious S-shaped surface, featured by an exponential correlation with dynamic mechanical parameters. In addition, with increasing thermal shock temperature and cycles, granite mineral species barely change, but the length and width of thermal cracks increase significantly. The non-uniform expansion of minerals, thermal shock-induced cracking, and water-rock interaction are primary factors for deteriorating dynamic mechanical properties of granite under cyclic thermal shock.

Experimental study on the impact of sulfate attack on the performance of shaft lining concrete under sustained compressive load

To investigate the impact of sulfate corrosion on the performance of shaft lining concrete under sustained compressive loads, this study immersed samples in a 10 % sodium sulfate solution after subjecting to sustained compressive loads of 0.2fcand 0.4fc. The variation in compressive strength, ultrasonic velocity, and dynamic elasticity modulus with corrosion age were examined. The corrosion mechanisms were analyzed using field emission scanning electron microscope and energy dispersive spectrometer. The impact tendency of concrete was also evaluated. The results indicated that under sustained compressive loads of 0.2fcand 0.4fc, the compressive strength, ultrasonic velocity, and dynamic elasticity modulus are all increased with age, in the order of 0.2fc> 0.4fc>no-load. When exposed to a 10 % sodium sulfate solution under sustained compressive loads, these properties initially increased and then decreased, peaking at 90 days of corrosion age, and the order was 0.2fc> no-load > 0.4fc when the corrosion age was longer than 240 days.The shaft lining concrete exhibited weak impact tendency, with the brittleness index increasing as the corrosion age progressed. The outcome of this work might provide a reference for the further research on the design of shaft lining concrete materials.

CARACTERÍSTICAS ACÚSTICAS DA MADEIRA DE ROXINHO (&lt;i&gt;PELTOGYNE SP.&lt;/i&gt;) TRATADA TERMICAMENTE

The present research aimed to develop products for the musical instruments market using wood modified through heat treatments. Initially, a survey of wood traditionally used in musical instruments, or their parts was carried out. Subsequently, bibliographic research about the wood modification treatments was produced to know the technical limits and their characteristics and to identify which of these can be applied in Brazilian woods, being then chosen as the technique of heat treatment with the application of temperatures of 160ºC and 200ºC carried out in laboratory ovens. From this, the musical instrument xylophone was chosen as a test product to evaluate the use of the chosen technique of modification for the roxinho wood (Peltogyne sp.). Thus, the musical instrument was designed and produced with untreated wood and treated with the mentioned temperatures and evaluated the mass loss, specific gravity, resonance frequency, sound propagation velocity and dynamic modulus of elasticity (MOEd). The results indicated that the treatment with the temperatures used increased the sound propagation velocity and the MOEd, even with the decrease in the apparent density. The production of the product also showed a significant gain in relation to the final timbre when compared to untreated wood. Thus, the use of temperature at 160ºC is indicated as a technological product that can increase the final quality of the musical instrument.

Establishment of Dynamic Properties for Malaysian Peat Soil Using Multichannel Analysis of Surface Waves

A poor understanding of peat behavior has introduced several engineering problems including differential settlements or slides which greatly impact society. Problematic characteristics of peat including a high moisture content and the presence of fresh fibers, cause a significant challenge in obtaining high-quality samples for laboratory-based investigation. Therefore, the application of in-situ geophysical methods is sought to mitigate these problems. The dynamic properties of a peat deposit in West Malaysia are described in this study. The Multichannel Analysis of Surface Waves (MASW) was conducted at six different locations. These peat soils had considerably different characteristics due to the different natures of decomposed materials. The samples obtained from the five locations had organic contents of 66.5 to 97.1%, water contents of 447 to 964%, and fiber content between 22.1 and 75.2%. Based on Von Post classification, the peat type ranged from H3 (fibrous) to H8 (amorphous). Shear wave velocity (Vs) and maximum shear modulus (Gmax) are presented, and their dependence on variables such as moisture content, organic content, fiber content, specific gravity and bulk density are illustrated. The general trend shows an increase in Vs and Gmaxwith decreasing moisture, organic and fiber content of peat soil. The difference in the degree of humification did not result in significant differences in Vs and Gmax obtained. The results showed that the value of Vs and Gmax ranged from 24.0 to 67.1m/s and 0.40 to 7.06 MPa respectively. Correlation between the index and dynamic properties peat shows that the Vs and Gmax increase as the moisture, organic and fiber content decreases. Successful determination of in-situ Vs and Gmax on peat soil minimized the potential of underestimation due to sample disturbance and provide a sustainable, rapid and economic method.

Mechanical properties of cement-based composites incorporating eco-friendly aggregate of waste rubber

The purpose of this study is to evaluate the waste tires that harm the environment as aggregate in concrete and to examine the effect on the mechanical properties of concrete. Three different classes (powder, crumb and chips) of waste rubber with seven different ratios (0%, 4%, 8%, 12%, 16%, 20% and 24%) and two different water to cement ratio (0.4 and 0.5) were used in concrete production. In this regard, this study conducted various experiments consisting of 28 and 90 days of the curing process to determine the properties of unit weight, compressive, flexural, and splitting tensile strength, along with ultrasonic pulse velocity (UPV) and dynamic modulus of elasticity. The waste rubber concrete with the highest compressive strength at the end of 90 days is the concrete that includes 4% waste rubber (0.4WR4) with 58.81 MPa. Concrete containing 8% waste rubber has the highest UPV of 5660 m/s after 90 days. The increase in the water/cement ratio from 0.4 to 0.5 and the waste rubber ratio cause deterioration in the mechanical properties of concrete. Although the use of waste rubbers does not bring an increase in strength, it is feasible to produce high strength concretes with 4% and 8% waste rubber substitution ratios. The water/cement ratio and curing time were highly effective on the mechanical properties of rubberized concrete.

A novel semi-flexible coaxial nozzle based on fluid dynamics effects and its self-centering performance study

Coaxial nozzles are widely used to produce fibers with core–shell structures. However, conventional coaxial nozzles cannot adjust the coaxiality of the inner and outer needles in real-time during the fiber production process, resulting in uneven fiber wall thickness and poor quality. Therefore, we proposed an innovative semi-flexible coaxial nozzle with a dynamic self-centering function. This new design addresses the challenge of ensuring the coaxiality of the inner and outer needles of the coaxial nozzle. First, based on the principles of fluid dynamics and fluid–structure interaction, a self-centering model for a coaxial nozzle is established. Second, the influence of external fluid velocity and inner needle elastic modulus on the centering time and coaxiality error is analyzed by finite element simulation. Finally, the self-centering performance of the coaxial nozzle is verified by observing the coaxial extrusion process online and measuring the wall thickness of the formed hollow fiber. The results showed that the coaxiality error increased with the increase of Young’s modulus E and decreased with the increase of flow velocity. The centering time required for the inner needle to achieve force balance decreases with the increase of Young's modulus (E\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$E$$\\end{document}) and fluid velocity (vf\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${v}_{f}$$\\end{document}). The nozzle exhibits significant self-centering performance, dynamically reducing the initial coaxiality error from 380 to 60 μm within 26 s. Additionally, it can mitigate the coaxiality error caused by manufacturing and assembly precision, effectively controlling them within 8 μm. Our research provides valuable references and solutions for addressing issues such as uneven fiber wall thickness caused by coaxiality errors.

Mechanical behaviors and progressive fracture processes of dry basalt after Martian cryogenic freeze-thaw cycles

The steep Martian terrain features numerous notches and alcoves that could potentially be adapted as temporary shelters. By sealing their entrances and modifying the interior space, these alcoves can be transformed into habitable structures. Given their prolonged exposure to Martian temperature fluctuations, it is crucial to understand the mechanical properties of alcove rocks to design appropriate shelter parameters. This study investigates the mechanical behavior of basalt specimens subjected to Martian cryogenic freeze-thaw (F-T) cycles (−143∼35 °C) and subsequent uniaxial cyclic loading tests. The test results indicate that the longitudinal wave velocity, peak stress, and elastic modulus of basalt specimens degrade to varying degrees with an increasing number of F-T cycles. At higher stress levels, the ratio of dissipated energy density to elastic energy density in basalt specimens subjected to different F-T treatments converges to approximately 0.25. During the uniaxial cyclic loading tests, both cumulative acoustic emission (AE) counts and average maximum principal strains of the specimens increase stepwise. For specimens after F-T treatment, the spectral-domain characteristics can be classified into three frequency bands, with the middle and high frequencies predominating. The application of the Gaussian Mixture Model (GMM) clustering algorithm enhances the analysis of AE results, facilitating the identification of tensile and shear cracks. As the number of F-T cycles increases, the percentage of shear cracks in basalt specimens decreases from 76.5% (0 cycle) to 53.5% (7 cycles).

Effect of stress evolution in destressed borehole on gas desorption in deep coal seam

Hydraulic flushing is a crucial technology for enhancing deep coal seam gas extraction, while the gas desorption characteristic is a critical factor impacting efficient gas extraction. This paper first analyzed stress variation around borehole during flushing and subsequently conducted experimental research to explore the effect of stress evolution on gas desorption. The results indicated that stress variation had a relatively insignificant effect on gas desorption during the early stage. When stress variation peaked in coal samples, instability and damage occurred, leading to a surge in the gas desorption rate. The ultrasonic wave velocity and dynamic elastic modulus of coal under different stress paths exhibited significant changes. With an increase in desorption time, the coal dynamic elastic modulus decreased, and the damage coefficient gradually increased. When comparing gas desorption behavior during constant stress and stress relief, Pingdingshan Mine (PDS) and Jiaozishan Mine (JZS) coal samples exhibited desorption amounts 2.85 and 1.41 times higher after stress relief, respectively. Based on the influence of stress relief on gas desorption rate and structure, a theoretical matrix scale change model was deduced. The mechanism controlling the rate of gas desorption by stress relief was illustrated. These research results offer theoretical guidance for implementing stress relief techniques to optimize coal seam gas extraction in practical field applications.

Relationship between static and dynamic balance in 4-to-5-year-old preschoolers: a cross-sectional study

BackgroundBalance is crucial for physical development in preschool children. Exploring the relationship between different types of balance can help understand early physical development in children. Currently, research is mostly focused on the relationship between different types of balance in the adult population and lacks exploration of the preschool population. The aim of this study explored the relationship between static and dynamic balance in preschool children aged 4 to 5 years.MethodsA total of 128 preschool children between the ages of 4 to 5 years were selected. The following tests were conducted as they wore inertial sensors detecting their centers of mass (COM): T1, standing with eyes open; T2, standing with eyes closed; T3, standing with eyes open on foam; T4, standing with eyes closed on foam; and T5, walking on the balance beam. Static balance was measured by the angular velocity modulus (ω−T1–ω−T4) of the shaking COM, as well as the pitch angle (θ−T1–θ−T4) and roll angle (φ−T1–φ−T4) indicators in T1–T4 testing. Dynamic balance was measured by the time (t) and angular velocity modulus (ω−T5), as well as the pitch angle (θ−T5) and roll angle (φ−T5) indicators in the T5 test. The Pearson product-moment correlation coefficient was used to test the correlation between static and dynamic balance indicators.ResultsThere is no correlation between ω−T1–ω−T4 and t (P > 0.05), while ω−T1–ω−T4 and ω−T5 (r = 0.19–0.27, P < 0.05) and ω−T1–ω−T4 and θ−T5, φ−T5 (r = 0.18–0.33, P < 0.05) were weakly correlated. There is no correlation between θ−T1–θ−T4, φ−T1–φ−T4 and t (P > 0.05), while θ−T1–θ−T4, φ−T1–φ−T4, and θ−T5, φ−T5 were weakly correlated (r = 0.01–0.28, P < 0.05).ConclusionsThe relationship between static and dynamic balance in preschool children aged 4–5 years is weak. Static and dynamic balance in children needs to be intervened separately for the development of children.

Investigation of damping coefficients for elastic collision particles utilizing the acoustic frequency sampling method

The damping coefficient serves to quantify the energy dissipation in particle collisions and constitutes a crucial parameter in discrete element simulations. Nevertheless, the factors influencing the damping coefficient remain unclear, and the damping coefficients of the majority of materials have not been precisely determined. In this investigation, the damping coefficients of eight representative particles were studied using the acoustic frequency sampling method, and the correlations between these coefficients and collision velocity, material density, and elastic modulus were analyzed. The findings indicate that damping coefficients exhibit insensitivity to velocity in strongly elastic and moderately elastic material particles. Conversely, for weakly elastic material particles, damping coefficients demonstrate an increase with rising velocity. The damping coefficient of metallic particles exhibits a linear relationship with material density and elastic modulus.

Deceleration of fast ion rarefied beam due to Cherenkov interaction with ion-acoustic waves.

The deceleration of a low-density beam of ions in plasma with developed ion-acoustic turbulence arising in strong electric field is described. The time and length of beam deceleration along and across the anisotropy axis of the wave number distribution of ion-acoustic waves are found. It is shown to what extent an increase in the strength of the electric field that generates turbulence is accompanied by a decrease in the time and length of braking. As the beam propagates along the anisotropy axis, its velocity decreases to approximately the velocity of ion sound, and the direction of propagation does not change. When the beam is decelerated with an initial velocity across the anisotropy axis, a velocity component appears along the anisotropy axis during deceleration, which results in the beam deflection from the initial direction. In this case, the modulus of the beam velocity at the end of deceleration is close to the ion sound velocity.

Determining the Rheological Parameters of Polymers Using Machine Learning Techniques

Introduction. The paper investigates the methodology for determining the rheological parameters of materials based on the nonlinear Maxwell-Gurevich rheological model using the stress relaxation curves. The review of the main directions of the metaheuristic approaches (local search, evolutionary algorithms) to solving the combinatorial optimization problems is presented. The metaheuristic algorithms for solving some important combinatorial optimization problems with the special emphasis on building decision trees are described. The comparative analysis of the algorithms for solving the regression problem in CatBoost Regressor is carried out. The aim of the work is to determine the rheological properties of polymers using machine learning techniques.Materials and Methods. The objects of the study are the generated data sets obtained on the basis of the theoretical stress relaxation curves. The source data tables for model training across all samples are presented, and the statistical analysis of the source data sets characteristics is carried out. The total number of numerical experiments across all samples amounted to 346020 variations. To develop the models, the CatBoost artificial intelligence techniques were used; the regularization techniques (Weight Decay, Decoupled Weight Decay Regulation, Augmentation) were used to increase the model accuracy; and Z–Score technique was used for data normalization.Results. As a result of the research, the intelligent models for determining the rheological parameters of polymers (initial relaxation viscosity, velocity modulus) have been developed based on the generated data sets on the example of the epoxy binder EDT-10. Based on the testing results of the models with the best parameters, the quality assessments were carried out: for the parameter 𝜂∗0 the range of values MAPE 0.46 — 2.72, MSE 0.15 — 1.09, RMSE 0.19 — 0.44, MAPE 0.46 — 1.27; for the parameter 𝑚∗ — MAPE 0.07 — 0.32, MSE 0.01 — 0.13, RMSE 0.10 — 0.41, MAPE 0.58 — 2.72. The resulting metric values are permissible. The training graphs demonstrate the stability of the process.Discussion and Conclusion. The developed intelligent models are scalable and cross-platform, have practical applied significance that ensures their implementation in a wide range of the scientific and engineering apps.

Data science integrated with computational fluid dynamics for particle collision modeling in fluidized bed

Fluidized beds are critical in numerous industrial applications, including chemical processing and energy production. Accurate modeling of solid particles and fluids within these beds is essential for process optimization and improved efficiency. In this study, we developed a machine learning model to predict the coefficient of restitution (COR) of solid particles in fluidized beds. Four variables—collision velocity, effective temperature, effective mass, and effective elastic modulus—were used in the model. Our dataset comprised 2446 data points from previous literature. We employed self-organizing map (SOM) and artificial neural network (ANN) approaches for data analysis. The initial ANN model, which did not incorporate data clustering, exhibited an impressive coefficient of determination (R-squared) of 0.989, indicating its high accuracy. To enhance the model further, we clustered the data into four groups using SOM and developed separate ANN models for each group. All four models achieved R-squared greater than 0.99, illustrating the effectiveness of data clustering. The resulting model can be integrated into simulation software, such as MFIX, to provide a more precise representation of fluidized bed behavior across various industrial settings. The findings emphasize the potential of machine learning models to enhance fluidized bed simulations, leading to increased efficiency and cost-effectiveness in industrial processes. Future studies should explore the inclusion of additional variables and extend the model's application to different industrial processes. Additionally, incorporating recommendations for optimizing fluidized bed behavior based on the model's predictions would provide valuable insights for process engineers.

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

Experimental investigation on mechanical properties of sustainable roller compacted concrete pavement (RCCP) containing waste rubbers as alternative aggregates

Different types of solid waste are generated every year due to global industrialization. With the rapid growth of the automobile industry, the disposal of billions of waste rubbers (WR), which pollute the environment and cannot be disposed of properly, is emerging as an urgent matter of concern. Recycling waste rubbers by using them on pavements will contribute to the elimination of ecological and economic problems. In this study, the effects of waste rubbers on the mechanical properties of roller-compacted concrete pavement (RCCP) were investigated by obtaining sustainable RCCP mixtures using different types of waste rubbers as coarse and fine aggregate substitutes. In this context, waste rubbers with three different sizes (powder, crumb and shredded) were substituted for aggregate by volume at seven levels (0%, 2.5%, 5%, 7.5%, 10%, 20% and 30%) with a maximum of 30% in RCC mixtures. Unit weight, mechanical properties, modulus of elasticity and ultrasonic pulse velocity (UPV) were evaluated and compared according to the waste rubber content in the RCC mixtures. In addition, microstructural analysis of the mixtures was performed through scanning electron microscopy (SEM). The experimental results revealed that the compressive, flexural and splitting tensile strength and modulus of elasticity decreased with increasing waste rubber content in RCC. The utilization of waste rubber increased the ductility of RCC and decreased the density to produce lighter concrete. RCC with a compressive strength of about 30 MPa could be obtained by substituting 10% of waste rubber for aggregate. Thus, the utilization of high waste rubber content in pavements was feasible. This study can contribute to a more sustainable RCCP production by replacing natural aggregates with waste rubbers.

Thermal-Induced Microstructure Deterioration of Egyptian Granodiorite and Associated Physico-Mechanical Responses.

Mineral transformations often induce microstructural deteriorations during temperature variations. Hence, it is crucial to understand why and how this microstructure weakens due to mineral alteration with temperature and the correlated physical and mechanical responses. Therefore, in this study, physical, chemical, thermal, petrographic, and mechanical analyses were carried out to comprehend better the thermal behaviors of Egyptian granodiorite exposed to temperatures as high as 800 °C. The experimental results indicate that the examined attributes change in three distinct temperature phases. Strength zone (up to 200 °C): During this phase, the temperature only slightly impacts the granodiorite mass loss and porosity, and the P-wave velocity and E slightly decrease. However, the rock structure was densified, which resulted in a minor increase in strength. After that, the transition zone (200-400 °C) was distinguished by the stability of most studied parameters. For instance, mass and porosity did not significantly alter, and the uniaxial compressive strength steadily increased with an axial failure mode. When the temperature rises, transgranular cracks cause the P-wave velocity and elastic modulus to decrease moderately. The decay zone started after 400 °C and continued to 800 °C. This zone is characterized by complicated factors that worsen the granodiorite properties, lead to color shift, and produce a shear failure mode. The properties of granodiorite became worse because of chemical reactions, structural and crystal water evaporation, rising thermal expansion coefficient variation, and quartz inversion at 575 °C (α to β, according to the differential thermal analysis). Thermal damage greatly affected granodiorite's physical and mechanical properties and microstructure at 800 °C. As a result, UCS measurements were extremely small with a complex failure pattern, making Vp and E unattainable.

The Gaia RVS benchmark stars

Context. The Gaia satellite has already provided the astronomical community with three data releases, and the Radial Velocity Spectrometer (RVS) on board Gaia has provided the radial velocity for 33 million stars. Aims. When deriving the radial velocity from the RVS spectra, several stars are measured to have large values. To verify the credibility of these measurements, we selected some bright stars with the modulus of radial velocity in excess of 500 km s−1 to be observed with SOPHIE at OHP and UVES at VLT. This paper is devoted to investigating the chemical composition of the stars observed with UVES. Methods. We derived atmospheric parameters using Gaia photometry and parallaxes, and we performed a chemical analysis using the MyGIsFOS code. Results. We find that the sample consists of metal-poor stars, although none have extremely low metallicities. The abundance patterns match what has been found in other samples of metal-poor stars selected irrespective of their radial velocities. We highlight the presence of three stars with low Cu and Zn abundances that are likely descendants of pair-instability supernovae. Two stars are apparently younger than 1 Ga, and their masses exceed twice the turn-off mass of metal-poor populations. This makes it unlikely that they are blue stragglers because it would imply they formed from triple or multiple systems. We suggest instead that they are young metal-poor stars accreted from a dwarf galaxy. Finally, we find that the star RVS721 is associated with the Gjoll stream, which itself is associated with the Globular Cluster NGC 3201.

Shrinkage cracking and mechanical properties of cementitious composites produced with multiwall carbon nano tubes and different types of polypropylene fibres

This study was conducted to experimentally demonstrate the control the nano-, micro- and macro-scale cracking in cement-based composites by using nano-, micro- and macro-scale fibres. While micro, macro and hybrid system polypropylene (PP) fibres were used in concrete designs, micro-scale PP and multi-walled carbon nano tubes (MWCNT) were utilized in mortar mixtures. The progression of the cracks was monitored in accordance with a well-known standard and also with a modified method which enabled the investigation of plastic and restrained shrinkage. Fracture energy, flexural strength, compressive strength, modulus of elasticity and ultrasonic pulse velocity of the samples were also determined as the mechanical properties of the composites. Results showed significant improvements in the reduction of cracks, especially with hybrid fibres system.