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This chapter proposes a conceptualization of joyful leadership as a unique leadership style and identifies a future research agenda to further explore the concept. While the concept of joyful leadership appears repeatedly in the nonacademic literature, including in blogs, vlogs, and podcasts, there is limited reference to joyful leadership in the academic literature highlighting a lack of academic rigor around the concept. Joyful leadership is proposed as a unique leadership style with specific patterns of behavior demonstrated by the leader. This research draws on understandings of emotion, positive affect, and leadership in the academic literature to develop a conceptualization of joyful leadership.

The proposed conceptualization is based on an extensive literature review drawing from both the leadership field and the study of emotions including various theoretical perspectives from these diverse fields.

Based on discrete emotion theory a conceptualization of joyful leadership as a unique leadership style is presented, identifying key patterns of behavior associated with joyful leadership including discrete autonomic patterns, actions, nonverbal signals, and identified feelings.

This research outlines a conceptual model to provide an understanding of the concept of joyful leadership as a unique leadership style. It draws on the current study of emotion, positive affect, and leadership and more specifically examines the concept of joyful leadership aligned to discrete emotion theory. This particular theory of emotion, when examined in relation to leadership, provides a basis for the concept of joyful leadership as a leadership style and the basis for its proposed characteristics and outcomes.

This paper aims to present nonlinear numerical simulations using the versatile finite element (FE) analysis tool ANSYS and theoretical analysis based on code provisions to assess the load-carrying capacity of reinforced concrete (RC) beams under two-point monotonic static loadings.

Four quarter-size FE models with load and geometry symmetry conditions were constructed, the load-bearing capacity and associated mid-span deflections at critical points are verified against the full-scale experimental RC beams available in the literature. These developed FE models incorporated the tension stiffening effects and bond–slip behaviour. Theoretical analyses based on Indian standard code IS: 456–2000 and ACI 318–19 were also carried to verify the experimental and numerical predicted moments at critical loading points.

The load-deflection curves predicted through FE models exhibit closer corroboration with the experimental curves throughout the loading history. The contour plots for deflections, concrete principal stresses, reinforcement yield stresses are satisfactorily predicted by the FE models, which reveal the complete information of nonlinear behaviour of RC beams. The developed model well captured the initial and progressive crack patterns at each load increments.

The FE modelling is an efficient, valid and economical tool that is an alternative to the expensive experimental program and can be used to explore, analyse and fully understand the nonlinear response of RC beams under static loadings.

The ultimate moment capacity evaluated based on ACI 318–19 code provision show a better correlation with the experimental data as compared to the IS: 456–2000 code provision. The ultimate loads and associated centre-span deflections predicted by RN-2, RN-3, RB-12 and RB-16 FE model show a discrepancy of 1.66 and –0.49%, –4.68 and –0.60%, –9.38 and –14.53% and –4.37 and 4.21%, respectively, against the experimental results, which reveals that the developed ANSYS FE models predict consistent results and achieved a reasonable agreement with the experimental data.

This paper aims to employ a multivariate nonlinear regression analysis to establish a predictive model for the final fracture area, while accounting for the impact of individual parameters.

This analysis is based on the numerical simulation data obtained, using the hybrid finite element–discrete element (FE–DE) method. The forecasting model was compared with the numerical results and the accuracy of the model was evaluated by the root mean square (RMS) and the RMS error, the mean absolute error and the mean absolute percentage error.

The multivariate nonlinear regression model can accurately predict the nonlinear relationships between injection rate, leakoff coefficient, elastic modulus, permeability, Poisson’s ratio, pore pressure and final fracture area. The regression equations obtained from the Newton iteration of the least squares method are strong in terms of the fit to the six sensitive parameters, and the model follow essentially the same trend with the numerical simulation data, with no systematic divergence detected. Least absolutely deviation has a significantly weaker performance than the least squares method. The percentage contribution of sensitive parameters to the final fracture area is available from the simulation results and forecast model. Injection rate, leakoff coefficient, permeability, elastic modulus, pore pressure and Poisson’s ratio contribute 43.4%, −19.4%, 24.8%, −19.2%, −21.3% and 10.1% to the final fracture area, respectively, as they increased gradually. In summary, (1) the fluid injection rate has the greatest influence on the final fracture area. (2)The multivariate nonlinear regression equation was optimally obtained after 59 iterations of the least squares-based Newton method and 27 derivative evaluations, with a decidability coefficient R2 = 0.711 representing the model reliability and the regression equations fit the four parameters of leakoff coefficient, permeability, elastic modulus and pore pressure very satisfactorily. The models follow essentially the identical trend with the numerical simulation data and there is no systematic divergence. The least absolute deviation has a significantly weaker fit than the least squares method. (3)The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

The nonlinear forecasting model of physical parameters of hydraulic fracturing established in this paper can be applied as a standard for optimizing the fracturing strategy and predicting the fracturing efficiency in situ field and numerical simulation. Its effectiveness can be trained and optimized by experimental and simulation data, and taking into account more basic data and establishing regression equations, containing more fracturing parameters will be the further research interests.

The purpose of this study is to investigate the unstable propagation of parallel hydraulic fractures induced by interferences of adjacent perforation clusters and thermal diffusion. Fracture propagation in the process of multistage fracturing of a rock mass is deflected owing to various factors. Hydrofracturing of rock masses in deep tight reservoirs involves thermal diffusion, fluid flow and deformation of rock between the rock matrix and fluid in pores and fractures.

To study the unstable propagation behaviours of three-dimensional (3D) parallel hydraulic fractures induced by the interferences of adjacent perforation clusters and thermal diffusion, a 3D engineering-scale numerical model is established under different fracturing scenarios (sequential, simultaneous and alternate fracturing) and different perforation cluster spacings while considering the thermal-hydro-mechanical coupling effect. Stress disturbance region caused by fracture propagation in a deep tight rock mass is superimposed and overlaid with multiple fractures, resulting in a stress shadow effect and fracture deflection.

The results show that the size of the stress shadow areas and the interaction between fractures increase with decreasing multiple perforation cluster spacing in horizontal wells. Alternate fracturing can produce more fracture areas and improve the fracturing effect compared with those of sequential and simultaneous fracturing. The larger the temperature gradient between the fracturing fluid and rock matrix, the stronger the thermal diffusion effect, and the effect of thermal diffusion on the fracture propagation is significant.

This study focuses on the behaviours of the unstable dynamic propagation of 3D parallel hydraulic fractures induced by the interferences of adjacent perforation clusters and thermal diffusion. Further, the temperature field affects the fracture deflection requires could be investigated from the mechanisms; this paper is to study the unstable propagation of fractures in single horizontal well, which can provide a basis for fracture propagation and stress field disturbance in multiple horizontal wells.

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.

Multi-well hydrofracturing is an important technology to create new fractures and expand existing fractures to increase reservoir permeability. The propagation morphology of the fracture network is affected by the disturbance between the fractures initiation sequences and spacings between adjacent wells. However, it remains unclear how well spacing and initiation sequences lead to fracture propagation, deflection and connection.

In this study, the thermal-hydro-mechanical coupling effect in the hydrofracturing process was considered, to establish a finite element-discrete element model of multistage hydrofracturing in a horizontal well. Using typical cases, the unstable propagation of hydraulic fractures in multiple horizontal wells was investigated under varying well spacing and initiation sequences. Combined with the shear stress shadow caused by in situ stress disturbed by fracture tip propagation, the quantitative indexes of fracture propagation such as length, volume, displacement vector, deflection and unstable propagation behavior of the hydrofracturing fracture network were analyzed.

The results show that the shear stress disturbance caused by multiple hydraulic fractures is a significant factor in multi-well hydrofracturing. Reducing the spacing between multiple wells increases the stress shadow area and aggravates the mutual disturbance and deflection between the fractures. The quantitative analysis results show that a decrease of well spacing reduces the total length of hydraulic fractures but increases the total volume of the fracture; compared with sequential and simultaneous fracturing, alternate fracturing can effectively reduce stress shadow area, alleviate fracture disturbance and generate larger fracture propagation length and volume.

The numerical models and results of the unstable propagation and stress evolution of the hydraulic fracture network under thermal-hydro-mechanical coupling obtained in this study can provide useful guidance for the evaluation and design of rock mass fracture networks in deep unconventional oil and gas reservoirs.

Multi-well hydrofracturing is a key technology in engineering, and the evaluation, control and optimization of the fracturing network determine the recovery rate of unconventional oil and gas production. In engineering terms, altering well spacing and perforation initiation sequences changes fracture propagation behavior. Fracture propagation can result in fracture-to-fracture and well-to-well interactions. This may be attributed to the interference between fractures caused by squeezing of the reservoir strata. Meanwhile, the stratal movement caused by the propagation of the fractures may lead to either the secondary fracturing of wells with primary fractures or perforation to begin fracturing. Besides, the stratal compression and squeeze of multi-well hydrofracturing will cause earthquakes; the fracture size is different owing to the different fracturing scenarios, and the occurrence of induced microseismic events is still unknown; microseismic events also affect fracture orientation and deflection. If the mechanism of the above mechanical behavior cannot be clarified, optimizing the fracture network and reduce the induced microseismic disaster becomes difficult.

In this study, combined finite element-discrete element models were used to simulate the multi-well hydrofracturing. Numerical cases compared the fracture network, dynamic stratal movement and microseismic events at 50, 75 and 100 m well spacings, respectively, and varying initiation sequence of multiple horizontal wells.

From the results, fracture propagation in multi-well hydrofracturing may simulate the propagation and deflection of adjacent fractures and induce fracture-to-fracture and well-to-well interactions. As the well spacing increases, the effect of fracturing-induced stratal movement and squeezing deformation decrease. In alternate fracturing, starting from a well located in the middle can effectively reduce the influence of stratal movement on fracturing, and the fracturing scenario with cross-perforation can minimize the influence of stratal movement. The stratal movement between multiple wells is positively correlated to microseismic events, which behaviors can be effectively weakened by reducing the strata movement.

The fracture network, thermal-hydro-mechanical coupling, fracturing-induced stratal movement and microseismic events were analyzed. This study analyzed the intersection and propagation behavior of fractures in multi-well hydrofracturing, which can be used to evaluate and study the mechanism of hydrofracturing fracture network propagation in multiple horizontal wells and conduct fracture optimization research to form an optimized hydrofracturing scheme by reasonably arranging the spacing between wells and initiation sequences of perforation clusters.

This paper aims to report the study of a fluid buoy system that includes wave effects, with particular emphasis on validating the numerical results with experimental data.

A fluid–solid coupled algorithm is proposed to describe the motion of a rigid buoy under the effects of waves. The Navier–Stokes equations are solved with the open-source finite volume package Code Saturne, in which a free-surface capture technique and equations of motion for the solid are implemented. An ad hoc experiment on a laboratory scale is built. A buoy is placed into a tank partially filled with water; the tank is mounted into a shake table and subjected to controlled motion that promotes waves. The experiment allows for recording the evolution of the free surface at the control points using the ultrasonic sensors and the movement of the buoy by tracking the markers by postprocessing the recorded videos. The numerical results are validated by comparison with the experimental data.

The implemented free-surface technique, developed within the framework of the finite-volume method, is validated. The best-obtained agreement is for small amplitudes compatible with the waves evolving under deep-water conditions. Second, the algorithm proposed to describe rigid-body motion, including wave analysis, is validated. The numerical body motion and wave pattern satisfactorily matched the experimental data. The complete 3D proposed model can realistically describe buoy motions under the effects of stationary waves.

The novel aspects of this study encompass the implementation of a fluid–structure interaction strategy to describe rigid-body motion, including wave effects in a finite-volume context, and the reported free-surface and buoy position measurements from experiments. To the best of the authors’ knowledge, the numerical strategy, the validation of the computed results and the experimental data are all original contributions of this work.

Slope stability analysis is essential for ensuring the safe design of road embankments. While various conventional methods, such as the finite element approach, are used to determine the safety factor of road embankments, there is ongoing interest in exploring the potential of machine learning techniques for this purpose.

Within the study context, the outcomes of the ensemble machine learning models will be compared and benchmarked against the conventional techniques used to predict this parameter.

Generally, the study results have shown that the proposed machine learning models provide rapid and accurate estimates of the safety factor of road embankments and are, therefore, promising alternatives to traditional methods.

Although machine learning algorithms hold promise for rapidly and accurately estimating the safety factor of road embankments, few studies have systematically compared their performance with traditional methods. To address this gap, this study introduces a novel approach using advanced ensemble machine learning techniques for efficient and precise estimation of the road embankment safety factor. Besides, the study comprehensively assesses the performance of these ensemble techniques, in contrast with established methods such as the finite element approach and empirical models, demonstrating their potential as robust and reliable alternatives in the realm of slope stability assessment.

The purpose of this study is to propose and explore a conceptualization of decisional capital that is suitable for early career teachers.

This study uses exploratory factor analysis on a sample of early career teachers to examine a literature-derived conceptualization of decisional capital.

The factors that emerged support the literature-derived conceptualization. A subsequent confirmatory factor analysis on a second sample of early career teachers offers additional evidence for the proposed conceptualization. An exploration of the underlying factor structure comparing results across four competing models (i.e. unidimensional, correlated factors, second order, and bifactor) suggests that a second order factor explains the variance across the three proposed factors well. We conclude that this second order factor is decisional capital.

This is the first study that examines the discrete elements of decisional capital. Understanding these discrete elements is an avenue for investigation into the development of decisional capital beyond the acknowledgment that it takes time to develop.