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Thermal fractures initiated under cooling at the surfaces of a 2-D or 3-D structure propagate, arrest and coalesce, leading to its structural failure and material-property changes, while the same processes can happen in the rock mass between parallel hydraulic fractures filled with cold fluid, leading to enhanced fracture connectivity and permeability.

This study used a 2-D plane strain fracture model for mixed-mode thermal fractures from two parallel cooling surfaces. Fracture propagation was governed by the theory of linear elastic fracture mechanics, while the displacement and temperature fields were discretized using the adaptive finite element method. This model was validated using two numerical benchmarks with strong fracture curvature and then used to simulate the propagation and coalescence of thermal fractures in a long rock mass.

Modeling results show two regimes: (1) thermal fractures from a cooling surface propagate and arrest by following the theoretical solutions of half-plane fractures before the unfractured portion decreases to 20% rock-mass width and (2) some pairs of fractures from the opposite cooling surfaces tend to eventually coalesce. The fracture coalescence time is in a power law with rock-mass width.

These findings are relevant to both subsurface engineering and material engineering: structure failure is a key concern in the latter, while fracture coalescence can enhance the connectivity of thermal and hydraulic fractures and thus reservoir permeability in the former.

Accurate presentation of the rock microstructure is critical to the grain-scale analysis of rock deformation and failure in numerical modelling. 3D granite microstructure modelling has only been used in limited studies with the mineral pattern often remaining poorly constructed. In this study, the authors developed a new approach for generating 2D and 3D granite microstructure models from a 2D image by combining a heterogeneous material reconstruction method (simulated annealing method) with Voronoi tessellation.

More specifically, the stochastic information in the 2D image is first extracted using the two-point correlation function (TPCF). Then an initial 2D or 3D Voronoi diagram with a random distribution of the minerals is generated and optimised using a simulated annealing method until the corresponding TPCF is consistent with that in the 2D image. The generated microstructure model accurately inherits the stochastic information (e.g. volume fraction and mineral pattern) from the 2D image. Lastly, the authors compared the topological characteristics and mechanical properties of the 2D and 3D reconstructed microstructure models with the model obtained by direct mapping from the 2D image of a real rock sample.

The good agreements between the mapped and reconstructed models indicate the accuracy of the reconstructed microstructure models on topological characteristics and mechanical properties.

The newly developed reconstruction method successfully transfers the mineral pattern from a granite sample into the 2D and 3D Voronoi-based microstructure models ready for use in grain-scale modelling.

The purpose of this paper is to study the insulation structure optimization method of multiwinding high-frequency transformer (HFT).

This paper takes 100 kW, 10 kHz multiwinding HFT as the research object. First, the distribution of electric field strength within the core window of multiwinding HFT with different winding configurations is simulated by the electrostatic field finite element method. The symmetrical hybrid winding structure with minimum electric field strength is selected as the insulation design. To reduce the electric field strength at the end region of the winding, the electrostatic ring and angle ring are designed based on the response surface method.

The optimal results show that the maximum electric field strength can be reduced by 15.4%, and the low voltage stress can be achieved.

The above research provides guidance and basis for the optimal design of insulation structure of multiwinding HFT.

This study aims to study the distribution characteristics of antibiotic resistance in direct-eating food and analysis of Citrobacter freundii genome and pathogenicity. Residual antibiotics and antibiotic resistance genes (ARGs) in the environment severely threaten human health and the ecological environment. The diseases caused by foodborne pathogenic bacteria are increasing daily, and the enhancement of antibiotic resistance of pathogenic bacteria poses many difficulties in the treatment of disease.

In this study, six fresh fruits and vegetable samples were selected for isolation and identification of culturable bacteria and analysis of antibiotic resistance. The whole genome of Citrobacter freundii isolated from cucumber was sequenced and analyzed by Oxford Nanopore sequencing.

The results show that 270 strains of bacteria were identified in 6 samples. From 12 samples of direct food, 2 kinds of probiotics and 10 kinds of opportunistic pathogens were screened. The proportion of Citrobacter freundii screened from cucumber was significantly higher than that from other samples, and it showed resistance to a variety of antibiotics. Whole genome sequencing showed that Citrobacter freundii was composed of a circular chromosome containing signal peptides, transmembrane proteins and transporters that could induce antibiotic efflux, indicating that Citrobacter freundii had strong adaptability to the environment. The detection of genes encoding carbohydrate active enzymes is more beneficial to the growth and reproduction of Citrobacter freundii in crops. A total of 29 kinds of ARGs were detected in Citrobacter freundii, mainly conferring resistance to fluoroquinolones, aminoglycosides, carbapenem, cephalosporins and macrolides. The main mechanisms are the change in antibiotic targets and efflux pumps, the change in cell permeability and the inactivation of antibiotics and the detection of virulence factors and ARGs, further indicating the serious risk to human health.

The detection of genomic islands and prophages increases the risk of horizontal transfer of virulence factors and ARGs, which spreads the drug resistance of bacteria and pathogenic bacteria more widely.

The purpose of this paper is to study the multi-objective optimization design method of high-power high-frequency magnetic-resonance air-core transformer (ACT).

First, this paper studies the interleaved winding technology, the process of modeling and simulation, the calculation method of high-frequency loss of Litz wire and the design of magnetic shielding in detail. Second, the multi-objective optimization design process of high-frequency magnetic-resonance ACT is established by parametric scanning method and orthogonal experiment method.

An ACT model of 2 kV/100 kW/81.34 kHz was designed. The efficiency, weight power density and volume power density are 99.61%, 21.6 kW/kg and 5.1 kW/kg, respectively. Finally, the multi-physical field coupling simulation method is used to calculate the port excitation voltages and currents and temperature field of ACT. The maximum temperature of the ACT is 95.5 °C, which meets the design requirements.

The above research provides guidance and basis for the optimization design of high-power high-frequency magnetic-resonance ACT.

Because the nanocrystalline core is widely used in power electronic equipment, and the excitation waveform of its working mode is complex, the vibration at medium and high frequencies cannot be ignored. Therefore, this study aims to study the vibration mechanism of nanocrystalline strip and the vibration characteristics of nanocrystalline magnetic ring under different excitation waveforms.

First, the electromagnetic vibration mechanism between nanocrystalline strips is analyzed by finite element analysis, and the force of the magnetic ring with and without air gap is compared and analyzed. Then, the vibration of nanocrystalline magnetic ring under different excitation waveforms such as sine wave, triangular wave, symmetric rectangular wave and asymmetric rectangular wave is analyzed by experimental method. The acceleration time domain waveform measured by the experiment is analyzed by fast Fourier transform, and the vibration is analyzed according to the spectrum.

Because of the increase of magnetic flux leakage, the volume force density and the Maxwell force on the surface of the nanocrystalline magnetic ring will increase after the air gap is opened, resulting in the intensification of vibration. Under symmetric/asymmetric rectangular wave excitation, the vibration acceleration varies with the duty cycle. Due to the influence of harmonic excitation, the relationship between the main frequency of vibration and the excitation frequency is not two times, and its multiple decreases with the increase of excitation frequency.

The research and analysis of this paper can promote the application of new magnetic materials in electrical equipment in small and medium-sized and medium- to high-frequency fields.

The purpose of this paper is to simulate the tension process of tension-type anchor cable and to explore the mechanical characteristics and tension-torsion coupling effect of anchor cable subjected to tension.

ABAQUS numerical software is applied to construct the numerical models of tension-type anchor cables with different diameters. Through explicit contact, the characteristics of contact between grouting body-anchor cable and grouting body-rock mass are determined. Confining pressure is applied to the model through surface pressure, and drawing force is applied to the model by displacement loading so as to simulate the tension process of the anchor cable.

The results show that the stress is transmitted in both axial and radial directions in the anchorage section and distributed in a cone. The shear stress in the grouting body is unevenly distributed, and its peak value increases with the rise in confining pressure and anchor cable diameter. The stress characteristics of torque and axial force are basically consistent and evenly distributed in the free section; they gradually decrease in the anchorage section. Due to the tension-torsion coupling effect, the internal stress characteristics of the anchor cable structure vary. On average, the anchorage performance of each anchor cable model is improved by 6.19%.

The proposed method of numerical modelling is effective in addressing the interface contact between the anchor cable and the grouting body and in solving the problem with convergence of calculation. Compared with the indoor test, this method is more suited to collecting the internal mechanical data of the anchor body.

This study aims to develop a building renovation duration prediction model incorporating both scope and non-scope factors.

The study used a questionnaire to obtain basic information relating to identified project scope factors as well as information relating to the impact of the non-scope factors on the duration of building renovation projects. The study retrieved 121 completed questionnaires from construction firms on tertiary education trust fund (TETFund) building renovation projects. Artificial neural network was then used to develop the model using 90% of the data, while mean absolute percentage error was used to validate the model using the remaining 10% of the data.

Two artificial neural network models were developed – a multilayer perceptron (MLP) and a radial basis function (RBF) model. The accuracy of the models was 86% and 80%, respectively. The developed models’ predictions were not statistically different from those of actual duration estimates with less than 20% error margin. Also, the study found that MLP models are more accurate than RBF models.

The developed models are only applicable to projects that suit the characteristics and nature of the data used to develop the models. Hence, models can only predict the duration of building renovation projects.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it.

The developed models are expected to serve as a tool for realistic estimation of the duration of building renovation projects and thus, help construction project managers to effectively plan and manage it; it also helps clients to effectively benchmark projects duration and contractors to accurately estimate duration at tendering stage.

The study presents models that combine both scope and non-scope factors in predicting the duration of building renovation projects so as to ensure more realistic predictions.

This study aims to investigate whether temperature affects the product quality of exporters and whether the effect is non-linear. More specifically, whether the impact of high temperatures differs from the impact of low temperatures, and whether different types of companies or industries are affected differently.

The paper uses detailed data covering all Chinese exporters from 2000 to 2016 to estimate the effects of temperature on the product quality of export firms. To clarify the relationship between them, the authors use a semi-parametric regression method, trying to test whether there is a non-linear relationship between temperature and the export quality of firms.

The increase in the number of high temperature days significantly reduces the quality of exported products, and this negative effect increases as the temperature rises. High temperature has the most significant negative impact on export quality for firms with low technical complexity, private firms and firms with no intermediate imports and located in historical hot cities. Product quality of both labor-intensive and capital-intensive firms will be affected by heat. High temperatures have the greatest negative impact on the export quality of newly entering products, followed by exiting products, with the least negative impact on persisting product.

To the best of the authors’ knowledge, this paper is the first to examine the impact of temperature on the quality of economic development. The findings of this paper again show that the potential economic impacts of global warming are huge. In addition to some potentially devastating impacts in the future, global warming is already causing imperceptible impacts in the present. Public and economic agents need to fully understand the possible adverse impacts of climate change and take corresponding adaptation measures to cope with global warming.

Since there is lack of studies in determine factors that affecting enjoyment sentiment when using online learning system, this study aims to explore the antecedents of perceived online learning enjoyment by using extended technology acceptance model (TAM) and its effect on behavioral intentions (BIN) among higher education institutions students.

The research framework was empirically evaluated using a cross-sectional research design and the data was collected from 715 undergraduate students from public higher education institutions in Malaysia using an online survey method. A structural equation modeling using partial least square method was used to examine the hypothesized model.

The results of partial least squares structural equation modeling indicated that the main predictive variables of TAM along with the extended variables were significantly influence the perceived online learning enjoyment. Meanwhile, the analysis also identified that perceived online learning enjoyment can significantly generate positive BIN for using online learning platforms as well as it also plays as a significant mediator role.

This study has significant implications for higher education institutions that wish to develop online learning environment for their students by providing answers to higher education institutions on how to successfully use the learning management system to assist students' learning performance from the aspect of online learning enjoyment sentiment.

This study is remarkable because it is the first attempt to explore the effect of these five predictors on students' learning enjoyment toward online learning platforms and subsequently on BIN to use this learning platforms, especially in the context of Malaysian higher education system. It is also unique in the way to extend the use of TAM predictive variables with others variables to produce more informative results about the study. Hence, this study also has a new contribution in the literature in the domain of digital learning.