Explore the vast range of titles available.

Hydraulic fracturing is a powerful technology, especially in stimulating fluid production from reservoirs. However, the problem of the intersection between hydraulic fractures and natural fractures is inevitable in engineering practice due to naturally fractured formations. This paper presents a new criterion for a toughness-dominated hydraulic fracture crossing a natural frictional interface through coupling the fluid flow and elastic deformation of the hydraulic fracture prior to intersecting with the natural frictional interface. The critical condition for the hydraulic fracture crossing the natural frictional interface is that the total superimposed stress does not satisfy the failure condition of the Mohr–Coulomb criterion. Simultaneously, the new criterion considers nonorthogonal intersection angles and six independent parameters relating to fluid flow (hydraulic fracture half-length, approaching distance and injection rate), rock mechanic properties (rock fracture toughness and Young’s modulus) and in situ stress. The prediction outcomes show good agreement with laboratory experiments as well as sufficient advantages compared with the analytical criteria of Blanton, extended Renshaw-Pollard and Llanos. Parameter sensitivity analysis is conducted using the control variable method. The parametric analysis results reveal that the influence sphere of different parameters is limited to a certain extent by the variations in the intersection angle except for Young’s modulus and the injection rate, which show slight effects on the intersection behaviors.

Untargeted liquid chromatographic-high-resolution mass spectrometric (LC-HRMS) metabolomics for potential exposure marker (PEM) discovery in nutrikinetic studies generates complex outputs. The correct selection of statistically significant PEMs is a crucial analytical step for understanding nutrition-health interactions. Hence, in this paper, different chemometric selection workflows for PEM discovery, using multivariate or univariate parametric or non-parametric data analyses, were comparatively tested and evaluated. The PEM selection protocols were applied to a small-sample-size untargeted LC-HRMS study of a longitudinal set of serum samples from 20 volunteers after a single intake of (poly)phenolic-rich Vaccinium myrtillus and Vaccinium corymbosum supplements. The non-parametric Games-Howell test identified a restricted group of significant features, thus minimizing the risk of false-positive retention. Among the forty-seven PEMs exhibiting a statistically significant postprandial kinetics, twelve were successfully annotated as purine pathway metabolites, benzoic and benzodiol metabolites, indole alkaloids, and organic and fatty acids, and five (i.e. octahydro-methyl-β-carboline-dicarboxylic acid, tetrahydro-methyl-β-carboline-dicarboxylic acid, citric acid, caprylic acid, and azelaic acid) were associated to Vaccinium berry consumption for the first time. The analysis of the area under the curve of the longitudinal dataset highlighted thirteen statistically significant PEMs discriminating the two interventions, including four intra-intervention relevant metabolites (i.e. abscisic acid glucuronide, catechol sulphate, methyl-catechol sulphate, and α-hydroxy-hippuric acid). Principal component analysis and sample classification through linear discriminant analysis performed on PEM maximum intensity confirmed the discriminating role of these PEMs.

Article focuses on the improvement of the technologies used to improve the durability of friction pair components. The authors use the piston compressor to study cellular microrelief surfaces of cylindrical components. The cells are shaped as elliptic paraboloid with uneven positive parameters. The use of cellular microrelief surfaces is highly preferred as they reduce the attrition wear of the friction pairs through assuring the hydrodynamic load capacity of the lubrication layer with the shape of the microrelief. The research goals included the parametric analysis of the lubrication layer behavior in the gap between the microrelief cells. To do this, the authors developed an analytical model based on the theory of hydrodynamic lubrication and constructed a CFD model using the ANSYS Fluent software. To contain the transfer equations, the authors used the turbulence model SST k–ω. Both models showed that the maximum hydrodynamic load capacity coincided with the 75%-length of the major axis of the elliptic cell, which also corresponds to 0.128 mm in cell depth. The maximum lifting hydrodynamic pressure on one microrelief cell amounted to 3 kPa. Based on the results of the parametric analysis, the authors claim that the cellular microrelief can be efficiently used to assure the service properties of friction pairs in process units.

The degradation of biopolymers such as polylactic acid (PLA) has been studied for several years; however, the results regarding the mechanism of degradation are not completely understood yet. PLA is easily processed by traditional techniques including injection molding, blow molding, extrusion, and thermoforming; in this research, the extrusion and injection molding processes were used to produce PLA samples for accelerated destructive testing. The methodology employed consisted of carrying out material testing under the guidelines of several ASTM standards; this research hypothesized that the effects of UV light, humidity, and temperature exposure have a statistical difference in the PLA degradation rate. The multivariate analysis of non-parametric data is presented as an alternative to multivariate analysis, in which the data do not satisfy the essential assumptions of a regular MANOVA, such as multivariate normality. A package in the R software that allows the user to perform a non-parametric multivariate analysis when necessary was used. This paper presents a study to determine if there is a significant difference in the degradation rate after 2000 h of accelerated degradation of a biopolymer using the multivariate and non-parametric analyses of variance. The combination of the statistical techniques, multivariate analysis of variance and repeated measures, provided information for a better understanding of the degradation path of the biopolymer.

Granular piles, either ordinary or encased with geosynthetic materials are being extensively used as one of the ground improvement techniques, depending on the strength of the adjoining soil. The optimum granular pile (GP) length is still a matter of research, even though the approach is widely established in the literature. In the present study, a thorough and detailed parametric analysis has been carried out to ascertain the optimum length for ordinary and encased granular piles using a 2D axisymmetric finite element model. The soil behaviour has been modelled with the linearly elastic perfectly plastic Mohr–Coulomb failure criterion constitutive model. The parameters considered in this study are area replacement ratio, encasement stiffness, soil properties, infill material properties, and crust layer thickness. The findings revealed that the parameters with the greatest influence on the optimum length are the area replacement ratio, encasement stiffness, surrounding soil strength properties, and friction angle of the infill material. For encased granular piles, the optimum length was often found to be longer than ordinary granular piles. It was found that the optimum length for ordinary and encased GP ranges between 0.8–2.12 and 1–2.75 times of footing diameter ( D ), respectively. Through this study, an effort has also been made to investigate how the aforementioned parameters affect the radial bulging of the end-bearing GP. The upper section of 0.5–1.5 D showed excessive bulging in each case. Additionally, the optimum encasement length was determined, and it was found that increasing the encasement length beyond 1.5 D results in minimal improvement. Furthermore, a multiple regression analysis was employed to establish the correlation between the optimum length of GP and potential influencing factors.

PurposeThe existence of the regional Kuznets curve, i.e. an inverted U-shaped relationship between regional disparity and economic development is widely debated and discussed. The bell-shaped curve of the spatial growth process where during the initial phase inequality increases and then reduces is theoretically supported by Myrdal (1957), Hirschman (1958), and Williamson (1965). It becomes important to understand regional Kuznets curve globally. Understanding the relationship between regional disparity and economic development becomes essential for public policy for balanced regional growth.Design/methodology/approachRegional Kuznets Curve which is an inverted U-shaped relationship between regional disparity and economic development is not a new phenomenon. Theoretical framework by Myrdal (1957), Hirschman (1958), and Williamson (1965) support the an inverted U-shaped relationship. To understand the relationship between regional disparity and economic development, the authors investigate the regional Kuznets curve by using data for 184 countries and 1765 subnational regions. Using parametric, semi-parametric, and non-parametric, it is found that there exists an inverted U-shaped relationship between regional disparity and economic development. The presence of the regional Kuznets curve is observed. As the theoretical framework suggests, regional inequality increases with income initially and decreases after attaining a certain level of income. This study identifies two stages of divergence-convergence where in the first stage, divergence across regions in a country happens with increasing income and in the later stage, convergence across regions in a country occurs with increasing income.FindingsUsing the parametric approach (panel data analysis), semi-parametric and non-parametric approaches, it is found that there exists a regional Kuznets curve. It is found that there exists an inverted-U relationship between regional inequality and per capita GNI. This suggests that the divergence-convergence passes through two stages. In the first stage, divergence across regions in a country happens with increasing income while in the later stage convergence occurs.Originality/valueThis research work has done three important things which fill the research gap that exists in the literature: (1) constructing the Gini coefficient to measure the regional inequality for 184 countries using 1765 subnational regional data; (2) using a parametric approach (panel data analysis) to understand the regional Kuznets phenomenon and (3) using a semi-parametric approach and non-parametric approach to understand the regional Kuznets phenomenon.

A vector method for recording phase-dynamic radio images is proposed by forming and numerically analyzing the S -parametric scattering matrix of multidisciplinary signatures of material media and objects. The key advantages of aperture capture of signal radio images by the method of a frequency-synthesized power spectral density function of a scattered wave radio profile are determined. On the basis of a vector analyzer of microwave circuits and broadband antennas of the Vivaldi type, an experimental laboratory installation for signal registration of time-scale radio images in the spectral region of 0.03–6.0 GHz has been built. The dependences of the influence of the angular characteristics of the object on the spectral-temporal structure of the formation of phase-dynamic radio images have been experimentally established. As the time-scale postprocessing of radio images, a method of cepstral transformation of S -parametric characteristics with convolution of basic signatures in the radiogenic part of the irradiated object is proposed. A series of cepstral convolutions of phase-dynamic radio images was obtained, establishing a functional relationship between the change of the signature of an object in time with its radio genome.

This paper focus on the investigation of the behaviour of rubble stone masonry piers, with air lime mortar, loaded in their plane using nonlinear static parametric analysis. This investigation is crucial for the seismic assessment of existing old unreinforced masonry buildings in Lisbon, since there is a clear lack of data for the nonlinear characterization of this kind of masonry. Numerical analyses are performed by adopting the macro-modelling approach implemented in the DIANA software. The adopted procedure for model calibration consists on fitting its behaviour with the results of the performed experimental tests on rubble stone masonry piers with air lime mortar. The parametric analyses are carried out by varying the slenderness and thickness of the piers, as well as the axial load in order to evaluate the influence of such parameters on shear strength, displacement capacity and stiffness. A sensitivity analysis is executed to define the most appropriate size of the elements’ mesh. A good agreement is obtained between the piers tested experimentally and its numerical counterpart models in terms of the force–displacement diagram, damage pattern, failure mode and dissipated energy. In addition, the comparison in what concerns both ductility and energy dissipation is also presented for different cases. The results attained by numerical parametric analyses are presented and discussed along with the main conclusions.

This paper evaluates the time-dependent fragility and post-earthquake residual seismic performance of existing steel frame columns in offshore atmospheric environments. Based on experimental research, the seismic failure mechanism and deterioration laws of the seismic behavior of corroded steel frame columns were revealed. A finite element analysis (FEA) method for steel frame columns, which considers corrosion damage and ductile metal damage criteria, is developed and validated. A parametric analysis in terms of service age and design parameters is conducted. Considering the impact of environmental erosion and aging, a classification criterion for damage states for existing steel frame columns is proposed, and the theoretical characterization of each damage state is provided based on the moment-rotation skeleton curves. Based on the test and numerical analysis results, probability distributions of the fragility function parameters (median and logarithmic standard deviation) are constructed. The evolution laws of the fragility parameters with increasing service age under each damage state are determined, and a time-dependent fragility model for existing steel frame columns in offshore atmospheric environments is presented through regression analysis. At a drift ratio of 4%, the probability of complete damage to columns with 40, 50, 60, and 70-year service ages increased by 18.1%, 45.3%, 79.2%, and 124.5%, respectively, compared with columns within a 30-year service age. Based on the developed FEA models and the damage class of existing columns, the influence of characteristic variables (service age, design parameters, and damage level) on the residual seismic capacity of earthquake-damaged columns, namely the seismic resistance that can be maintained even after suffering earthquake damage, is revealed. Using the particle swarm optimization back-propagation neural network (PSO-BPNN) model, nonlinear mapping relationships between the characteristic variables and residual seismic capacity are constructed, thereby proposing a residual seismic performance evaluation model for existing multi-aged steel frame columns in an offshore atmospheric environment. Combined with the damage probability matrix of the time-dependent fragility, the expected values of the residual seismic capacity of existing multi-aged steel frame columns at a given drift ratio are obtained directly in a probabilistic sense. The results of this study lay the foundation for resistance to sequential earthquakes and post-earthquake functional recovery and reconstruction, and provide theoretical support for the full life-cycle seismic resilience assessment of existing steel structures in earthquake-prone areas.

Climate change has become trending news due to its serious impacts on Earth. Initiatives are being taken to lessen the impact of climate change and mitigate it. Among the different initiatives, researchers are aiming to find suitable alternatives for cement. This study is a humble effort to effectively utilize industrial- and agricultural-waste-based pozzolanic materials in concrete to make it economical and environmentally friendly. For this purpose, a ternary blend of binders (i.e., cement, fly ash, and rice husk ash) was employed in concrete. Different variables such as the quantity of different binders, fine and coarse aggregates, water, superplasticizer, and the age of the samples were considered to study their influence on the compressive strength of the ternary blended concrete using gene expression programming (GEP) and artificial neural networking (ANN). The performance of these two models was evaluated using R2, RMSE, and a comparison of regression slopes. It was observed that the GEP model with 100 chromosomes, a head size of 10, and five genes resulted in an optimum GEP model, as apparent from its high R2 value of 0.80 and 0.70 in the TR and TS phase, respectively. However, the ANN model performed better than the GEP model, as evident from its higher R2 value of 0.94 and 0.88 in the TR and TS phase, respectively. Similarly, lower values of RMSE and MAE were observed for the ANN model in comparison to the GEP model. The regression slope analysis revealed that the predicted values obtained from the ANN model were in good agreement with the experimental values, as shown by its higher R2 value (0.89) compared with that of the GEP model (R2 = 0.80). Subsequently, parametric analysis of the ANN model revealed that the addition of pozzolanic materials enhanced the compressive strength of the ternary blended concrete samples. Additionally, we observed that the compressive strength of the ternary blended concrete samples increased rapidly within the first 28 days of casting.