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Simultaneous hydrofracturing of multiple perforation clusters in vertical wells has been applied in the stimulation of hydrocarbon resources reservoirs. This technology is significantly impeded due to the challenges in its application to the multilayered reservoirs that comprise multiple interlayers. One of the challenges is the accurate understanding and characterization of propagation and deflection of the multiple hydraulic fractures between reservoirs and embedded interlayers.

Numerical models of the tight multilayered reservoirs containing multiple interlayers were established to study hydrofracturing of multiple perforation clusters and its influencing factors on unstable propagation and deflection of hydraulic fractures. Brittle and plastic multilayered reservoirs fully considering the influences of different in situ stress ratio and physical attributes for reservoir and interlayer strata on propagations of hydraulic fractures were investigated. The combined finite element–discrete element method and mesh refinement strategy were adopted to guarantee the accuracy of stress solutions and reliability of fracture path in computation.

Results show that the shear stress fields between adjacent multiple hydraulic fractures are superposed to cause fractures deflection. Stress shadows induce the shielding effects of hydraulic fractures and inhibit fractures growth to emerge unstable propagation behaviors, and a main single fracture and several minor fractures develop. As the in situ stress ratio increases, hydraulic fractures more easily deflect toward the direction of maximum in situ stress, and stress shadow and mutual interaction effects between them are intensified. Compared to brittle reservoir, plastic-enhanced reservoir may limit fracture growth and cannot form long fracture length; nevertheless, plastic properties of reservoir are prone to induce more microseismic events with larger magnitude.

The obtained fracturing behaviors and mechanisms based on engineering-scale multilayered reservoir may provide effective schemes for controlling and estimating the unstable propagation of multiple hydraulic fractures.

This study aims to analyse the deep resource mining that causes high in situ stress, and the disturbance of tunnelling and mining which may induce large stress concentration, plastic deformation and rock strata compression deformation. The depth of deep resources, excavation rate and multilayered heterogeneity are critical factors of excavation disturbance in deep rock. However, at present, there are few engineering practices used in deep resource mining, and it is difficult to analyse the high in situ stress and dynamic three-dimensional (3D) excavation process in laboratory experiments. As a result, an understanding of the behaviours and mechanisms of the dynamic evolution of the stress field and plastic zone in deep tunnelling and mining surrounding rock is still lacking.

This study introduced a 3D engineering-scale finite element model and analysed the scheme involved the elastoplastic constitutive and element deletion techniques, while considering the influence of the deep rock mass of the roadway excavation, coal seam mining-induced stress, plastic zone in the process of mining disturbance of the in situ stress state, excavation rate and layered rock mass properties at the depths of 500 m, 1,500 m and 2,500 m of several typical coal seams, and the tunnelling and excavation rates of 0.5 m/step, 1 m/step and 2 m/step. An engineering-scale numerical model of the layered rock and soil body in an actual mining area were also established.

The simulation results of the surrounding rock stress field, dynamic evolution and maximum value change of the plastic zone, large deformation and settlement of the layered rock mass are obtained. The numerical results indicate that the process of mining can be accelerated with the increase in the tunnelling and excavation rate, but the vertical concentrated stress induced by the surrounding rock intensifies with the increase in the excavation rate, which becomes a crucial factor affecting the instability of the surrounding rock. The deep rock mass is in the high in situ stress state, and the stress and plastic strain maxima of the surrounding rock induced by the tunnelling and mining processes increase sharply with the excavation depth. In ultra-deep conditions (depth of 2,500 m), the maximum vertical stress is quickly reached by the conventional tunnelling and mining process. Compared with the deep homogeneous rock mass model, the multilayered heterogeneous rock mass produces higher mining-induced stress and plastic strain in each layer during the entire process of tunnelling and mining, and each layer presents a squeeze and dislocation deformation.

The results of this study can provide a valuable reference for the dynamic evolution of stress and plastic deformation in roadway tunnelling and coal seam mining to investigate the mechanisms of in situ stress at typical depths, excavation rates, stress concentrations, plastic deformations and compression behaviours of multilayered heterogeneity.

This paper aims to present the implementation of a multi-layer radiation propagation model in simulations of multi-phase flow and heat transfer, for a dissociating methane hydrate reservoir subjected to microwave heating.

To model the induced heterogeneity due to dissociation of hydrates in the reservoir, a multiple homogeneous layer approach, used in food processes modelling, is suggested. The multi-layer model is incorporated in an in-house, multi-phase, multi-component hydrate dissociation simulator based on the finite volume method. The modified simulator is validated with standard experimental results in the literature and subsequently applied to a hydrate reservoir to study the effect of water content and sand dielectric nature on radiation propagation and hydrate dissociation.

The comparison of the multi-layer model with experimental results show a maximum difference in temperature estimation to be less than 2.5 K. For reservoir scale simulations, three homogeneous layers are observed to be sufficient to model the induced heterogeneity. There is a significant contribution of dielectric properties of sediments and water content of the reservoir in microwave radiation attenuation and overall hydrate dissociation. A high saturation reservoir may not always provide high gas recovery by dissociation of hydrates in the case of microwave heating.

The multi-layer approach to model microwave radiation propagation is introduced and tested for the first time in dissociating hydrate reservoirs. The multi-layer model provides better control over reservoir heterogeneity and interface conditions compared to existing homogeneous models.

Wearable electronic devices have emerged which require compact, flexible power storage devices such as batteries and supercapacitors. Recently, energy storage devices have been developed based on supercapacitor threads. However, current supercapacitor energy storage threads which use electrolytes based on aqueous gels have a 1 V potential window. This is much lower than the voltage required by most electronic devices. This current contribution presents an approach for fabricating a multilayer supercapacitor working as a circuit unit, in which series combinations of the multiple layer structures can achieve a higher potential window, which can better meet the needs of wearable electronic devices.

Two-capacitive layer thread supercapacitors were fabricated using a semi-automatic dip coating method by coating two capacitive layers sequentially on a 50 μm stainless steel core wire, each capacitive layer includes ink, aqueous-based gel electrolyte and silver conductive paint layers.

Two capacitive layers of the single thread supercapacitor can work independently, or as combination circuits – parallel and series. Cyclic voltammograms showed that all flexible circuits have high electrochemical stability. For the case of series circuit configuration, with H₃PO-polyvinyl alcohol (PVA) gel electrolyte, a working potential window of 2 V was achieved.

A flexible single thread supercapacitor of multilayer structure, with working voltage above 1 V in H₃PO₄-PVA gel electrolyte, has not been reported before. A semi-automatic dip coating setup used to process the thread supercapacitor has high potential for transfer to an industrial environment for mass production.

This paper seeks to present a novel computational intelligence technique to generate concise neural network models for distributed dynamic systems.

The approach used in this paper is based on artificial neural network architectures that incorporate linear and nonlinear principal component analysis, combined with generalized dimensional analysis.

Neural network principal component analysis coupled with generalized dimensional analysis reduces input variable space by about 90 percent in the modeling of oil reservoirs. Once trained, the computation time is negligible and orders of magnitude faster than any traditional discretisation schemes such as fine‐mesh finite difference.

Finding the minimum number of input independent variables needed to characterize a system helps in extracting general rules about its behavior, and allows for quick setting of design guidelines, and particularly when evaluating changes in the physical properties of systems.

The methodology can be used to simulate dynamical systems characterized by differential equations, in an interactive CAD and optimization providing faster on‐line solutions and speeding up design guidelines.

IMASA Ltd. have introduced a new generic name for their range of gold plating processes which have been developed in their UK laboratories. ORIMA N is the first in this series and was previously known as EUROGOLD N.

This paper aims to explore the micro-political complexities of operating over institutional distance in a modern international enterprise. The focal sector of the study is the pharmaceutical industry, which, in its latest phase of global development, has engaged in “internal sourcing” of research and development (R&D) talent from China. This paper contributes to emergent “socio-political” theorization in international business through revealing complex forms of workplace segmentation and conflictual forms of practice at micro-organizational level.

The author of this paper and a UK-based research associate visited the Shanghai-based R&D facility of a major Western owned pharmaceutical concern to carry out interviews with key managers, expatriates and scientists to “hear their stories”. Access was gained to the research site through insider contacts.

It was discovered that, in the context of an enterprise intent on innovation, motivational logics themselves emanate from the embedded positions of diverse organizational actors, in turn bringing to the fore issues of power, resistance, ethnicity and language.

Generalizations from a single case study may have limited significance. However, the unique case setting provides the scope for a novel contribution to the field of international business by examining contradictory and asymmetrical factors in the social construction of a Global Value Chain extending from West to East to source emergent local talent.

The case offers the possibility for managerial learning in the areas of working across cultures, managing expatriation, dealing with linguistic and etymological differences and formulating international business strategy (integration or differentiation in the MNC). The study highlights the significance of critical realist perspectives in fostering reflexive behaviours of actors in multilayered and complex micro-environments.

The work has significance concerning the devolution of both managerial and medical responsibilities to local agents in China. This is a vital social factor in the emerging economy context. The work also casts light on social and personal issues confronting international managerial and scientific migrants.

To date, the phenomena of Global Value Chains have been approached in a relatively transactional and economistic fashion. The paper shed light on GVCs as humanistic and political phenomena. A relatively new departure of the study is to demonstrate that workplace actors in modern and modularized industrial enterprises located in the emerging economy setting respond to environmental volatility through engaging in variant and conflictual forms of institutional entrepreneurship.

A new model for the power system, covering resistance, self‐inductance, mutual inductance, and capacitive coupling between planes is presented. The model parameters are calculated from the geometry of the actual board. No measurements are necessary to set up a model for a new board. The model has been verified against detailed computer simulations and measured data.

A novel approach using artificial neural networks (ANNs) for predicting temperature profiles evaluated 27 wells in the Gulf of Mexico. Two artificial neural network models were developed that predict the temperature of the flowing fluid at any depth in flowing oil wells. Back propagation was used in training the networks. The networks were tested using measured temperature profiles from the 27 oil wells. Both neural network models successfully mapped the general temperature‐profile trends of naturally flowing oil wells. The highest accuracy was achieved with a mean absolute relative percentage error of 6.0 per cent. The accuracy of the proposed neural network models to predict the temperature profile is compared to that of existing correlations. Many correlations to predict temperature profiles of the wellbore fluid, for single‐phase or multiphase flow, in producing oil wells have been developed using theoretical principles such as energy, mass and momentum balances coupled with regression analysis. The Neural Network 2 model exhibited significantly lower mean absolute relative percentage error than other correlations. Furthermore, in order to test the accuracy of the neural network models to that of Kirkpatrick’s correlation, a mathematical model was developed for Kirkpatrick’s flowing temperature gradient chart.

This study aims to provide a technical insight into sensors fabricated by three-dimensional (3D) printing methods.

Following an introduction to 3D printing, this article first discusses printed sensors for strain and allied variables, based on a diverse range of principles and materials. It then considers ultrasonic and acoustic sensor developments and provides details of a sensor based on 3D printed electronic components for monitoring food quality in real-time. Finally, brief concluding comments are drawn.

Several variants of the 3D printing technique have been used in the fabrication of a range of sensors based on many different operating principles. These exhibit good performance and sometimes unique characteristics. A key benefit is the ability to overcome the limitations of conventional manufacturing techniques by creating complex shapes from a wide range of sensing materials.

3D printing is a new and potentially important sensor fabrication technology, and this article provides details of a range of recently reported developments.