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The purpose of this study is to investigate the effects of the cementite morphology on the hydrogen trapping behavior in low-alloy pipeline steel.

In this study, the hydrogen trapping behavior in low-alloy pipeline steel was quantitatively studied by a combination of microstructural observations, electrochemical hydrogen permeation experiments and thermal desorption spectroscopy (TDS) analyses.

P-1 and P-2 steels are two samples with different microstructures. The morphology of cementite precipitates in the P-1 and P-2 steels was different. Lamellar cementite is present in P-2 steel and only granular cementite in P-1 steel, which led to a better irreversible hydrogen trapping ability of P-2 steel, which was confirmed by subsequent hydrogen permeation and TDS experiments.

The study of these deep hydrogen trap sites is helpful in improving the hydrogen embrittlement resistance of low-alloy pipeline steels.

The purpose of this study is to develop a model extending Oriani’s formula by introducing a normalised concentration to simulate hydrogen diffusion in a multi-material system such as coated steels, under the presence of traps.

Implemented through the finite element method based on the analogy between mass diffusion and heat transfer, the governing equation was applied to investigate the combined effects of hydrogen traps and surface oxide films on hydrogen permeation in ferritic steels.

This study shows that the effective diffusivity varies over several orders of magnitude depending on the traps and films. This explains the divergence of measured hydrogen diffusivities in steels. It is revealed that hydrogen permeation in steels with Pd or Ni film is a trapping-dominant transport process, while hydrogen permeation in steel with oxide film is a process controlled by both trapping effect and retarding effect of oxide film. The oxide film enhances total hydrogen concentration within the steel substrate and is therefore detrimental. The Pd or Ni film has a little influence on total hydrogen concentration distribution depending on trapping energy.

Hydrogen flux curves and transient hydrogen concentration distributions can be directly obtained through the developed model. The proposed approach can also be extended to investigate other interstitial (i.e. carbon, oxygen and nitrogen) diffusion with traps revisited in complex systems.

The purpose of this paper is to discuss a linear vibratory part feeder for handling brake liners, typical sector-shaped components. Part feeders have been used in the industries for a long time to present the parts in a desired orientation. Berretty et al. (1999) discussed a class of mechanical filters that are capable of removing polygonal sections from the track of the feeder which are referred to as traps. The traps eliminate or reorient the parts until they reach the final desired orientation. A part feeder was developed using traps, to reorient the sector-shaped part to desired orientation. The desired orientation was the most probable natural resting orientation. The trap was mounted on a linear vibratory feeder. The adaptive part feeder developed was capable of identifying the size of the incoming part and adjust the trap to accommodate that. This set-up eliminates the use of different traps for different-sized sector-shaped parts and wastage of productive time in changing the traps for different sizes. A regression model was developed to predict the conveying velocity of part on the feeder.

A part feeder was developed using traps, to reorient the sector-shaped part to desired orientation. Acrylic material was found to be suitable for trap compared to aluminium. The adaptive part feeder developed was capable of identifying the size of the incoming part using proximity sensors. Depending on the size of the incoming part, the track width was adjusted dynamically with the help of a stepper motor, rack and pinion arrangement. A regression model was developed to predict the conveying velocity.

Typical brake liners in the size range of 40-60 mm (radius) were considered for developing the adaptive part feeder. Based on performance studies, the acrylic trap was found better than aluminium traps. The appropriate frequency and amplitude of vibration for maximum conveying velocity of the adaptive part feeder were found experimentally. Regression equation was developed to determine the conveying velocity based on input frequency and amplitude. The regression results were found to be in close agreement with the experimental results.

The developed part feeder is suitable for handling sector-shaped parts only.

This paper demonstrates an inexpensive adaptive part feeding device for handling sector-shaped parts which can be extended for handling other asymmetric parts also.

The purpose of this paper is to focus on the local minima issue encountered in motion planning by the artificial potential field (APF) method, investigate the currently existing approaches and analyze four types of previous methods. Based on the conclusions of analysis, this paper presents an improved wall‐following approach for real‐time application in mobile robots.

In the proposed method, new switching conditions among various behaviors are reasonably designed in order to guarantee the reliability and the generality of the method. In addition, path memory is incorporated in this method to enhance the robot's cognition capability to the environment. Therefore, the new method greatly weakens the blindness of decision making of robot and it is very helpful to select appropriate behaviors facing to the changeable situation. Comparing with the previous methods which are normally considering specific obstacles, the effectiveness of this proposed method for the environment with convex polygon‐shaped obstacles has been theoretically proved. The simulation and experimental results further demonstrate that the proposed method is adaptable for the environment with convex polygon‐shaped obstacles or non‐convex polygon‐shaped obstacles. It has more widely generality and adaptiveness than other existed methods in complicated unknown environment.

The proposed method can effectively realize real time motion planning with high reliability and generality. The cognition capability of mobile robot to the environment can be improved in order to adapt to the changeable situation. The proposed method can be suitable to more complex unknown environment. It is more applicable for actual environment comparing with other traditional APF methods.

This paper has widely investigated the currently existed approaches and analyzes deeply on four types of traditional APF methods adopted for real time motion planning in unknown environment with simulation works. Based on the conclusions of analysis, this paper presents an improved wall‐following approach. The proposed method can realize real time motion planning considering more complex environment with high reliability and generality. The simulation and experimental results further demonstrate that the proposed method is adaptable for the environment with convex polygon‐shaped obstacles or non‐convex polygon‐shaped obstacles. It has more widely generality and adaptiveness than other existed methods in complicated unknown environment.

The present experiments are intended to help characterize defects in very thin MOS oxide and at its Si/SiO₂ interface using a temperature‐dependent electrical characterization method, high low temperature capacitance voltage method and, especially, to investigate high temperature range. Oxide‐fixed traps are differentiated from slow‐state traps and from fast‐state traps by evaluating their electrical behaviour at different temperatures. The analysis points out the excess current after Fowler Nordheim electron injection based on hole generation, trapping, and hopping transport at high temperatures. The defect relaxation property versus temperature is investigated and defect relaxation activation energies are calculated. Creation mechanisms of interface states are especially identified by injection at different temperatures and these are compared with the other two kinds of defects. Fast‐state traps and all defect cross‐sections are calculated along and their creation activation energies are determined from Arrhenius plots.

The purpose of this paper is to optimize and improve a bipolar charge transport (BCT) model used to simulate charge dynamics in insulating polymer materials, specifically low-density polyethylene (LDPE).

An optimization algorithm is applied to optimize the BCT model by comparing the model outputs with experimental data obtained using two kinds of measurements: space charge distribution using the pulsed electroacoustic (PEA) method and current measurements in nonstationary conditions.

The study provides an optimal set of parameters that offers a good correlation between model outputs and several experiments conducted under varying applied fields. The study evaluates the quantity of charges remaining inside the dielectric even after 24 h of short circuit. Moreover, the effects of increasing the electric field on charge trapping and detrapping rates are addressed.

This study only examined experiments with different applied electric fields, and thus the obtained parameters may not suit the experimental outputs if the experimental temperature varies. Further improvement may be achieved by introducing additional experiments or another source of measurements.

This work provides a unique set of optimal parameters that best match both current and charge density measurements for a BCT model in LDPE and demonstrates the use of trust region reflective algorithm for parameter optimization. The study also attempts to evaluate the equations used to describe charge trapping and detrapping phenomena, providing a deeper understanding of the physics behind the model.

Currently, China’s economy is in the critical phase of transforming economic development patterns and replacing old growth drivers with new ones. Whether it can successfully overcome the “middle-income trap” has become a significant issue attracting wide attention.

Driven by underlying digital technologies such as artificial intelligence, blockchain, cloud computing and big data, the fourth industrial revolution featuring the booming digital economy has provided significant opportunities for China’s economy to “overtake” and overcome the “middle-income trap”. The transformation of economic development pattern, the optimization of industrial structure, and the change of growth drivers, brought by the deep integration of digital and real economies are the keys to leaping over the “middle-income trap”.

From the supply side, the digital economy can improve the quality and efficiency of the supply side and promote the supply-side structural reform and economic growth from the following three aspects: First, promote the quality, efficiency and diversification of the supply system; second, promote networking, opening-up and synergy in the innovation system and third, promote the socialization, modularization and flexibility of production pattern. From the demand side, the digital economy can boost the new drivers of the “troika” of economic growth consisting of consumption, exports and investment by changing the market investment direction, promoting consumption upgrade and fostering export strengths. However, once these two attributes interact with each other, especially when data is combined with capital, the most adhesive factor in the market economy, a series of new social relations will then be produced based on the technical attribute, resulting in significant adjustments in social relations, involving both positive and negative externalities.

To overcome the “middle-income trap”, it is necessary to adapt to the laws of economic evolution and promote a fundamental change in economic growth drivers; boost the high-quality development of the digital economy by strengthening the support role of data in the digital economy; and accelerate digital industrialization and industrial digitalization to realize the integration of digital and real economies.

This paper focuses on social innovation dynamics in extreme contexts where institutional volatility is deeply rooted and enduring. In other words, the authors focus their discussion on the challenges that social innovators are facing in their endeavor of solving wicked social problems within an extreme institutional environment. This research is guided by the following question: How does an extreme institutional environment influence social innovation processes?

This qualitative research builds on the unique case of the Palestinian non-governmental organization (NGO) sector, a rarely studied context in organizational studies. The authors combine archival sources with 24 semi-structured interviews with Palestinian NGOs.

The authors theorize three barriers that hinder social innovation in such contexts: institutional trap, effectiveness trap and sustainability trap. The authors also theorize five mechanisms through which these barriers influence each other dynamically: mingling, surviving, undermining, binding and reinforcing. Taken together, these barriers and mechanisms shed light on social innovation processes taking place within extreme institutional environments.

The main limitation of this study is the methodological design, based on an extreme single case-study which, on a bunch of features, is quite unique in the world. The authors argue that the results are all the same transferable to other relatively similar contexts.

By theorizing the institutional barriers to social innovation in an extreme institutional context, the research thus sheds light on how social innovation could be sustained and stimulated in Palestine and other contexts that face similar institutional challenges.

From an engaged scholarship perspective, studying Palestine cannot be more relevant than today considering the turmoil in which Palestinians are. The research thus provides a deeper understanding of organizational and institutional dynamics with crucial social repercussions.

The social innovation literature has overemphasized success stories to the detriment of the struggles that hinder social innovations in extreme institutional environments. By focusing on the barriers that social innovators experience in these contexts, the authors provide novel empirical insight. Furthermore, this study enriches the understanding of the institutional dynamics of social innovations by proposing a process model that elucidates how an extreme institutional context can influence social innovations.

The purpose of this paper is to describe a rapid and robust axisymmetric hybrid algorithm to create dynamic temporal and spatial charge distributions, or charge map, in the simulation of bipolar charge injection using Schottky emission and Fowler-Nordheim tunneling, field-dependent transport, recombination, and bulk and interfacial trapping/de-trapping for layered polymer films spanning the range from initial injection to near breakdown.

This hybrid algorithm uses a source distribution technique based on an axisymmetric boundary integral equation method (BIEM) to solve the Poisson equation and a fourth-order Runge-Kutta (RK4) method with an upwind scheme for time integration. Iterative stability is assured by satisfying the Courant-Friedrichs-Levy (CFL) stability criterion. Dynamic charge mapping is achieved by allowing conducting and insulating boundaries and material interfaces to be intuitively represented by equivalent free and bound charge distributions that collectively satisfy all local and far-field conditions.

Charge packets cause substantial increase of electric stress and could accelerate the breakdown of polymeric capacitors. Conditions for the creation of charge packets are identified and numerically demonstrated for a combination of impulsive step excitation, high charge injection, and discontinuous interface.

Metallized bi-axially oriented polypropylene (BOPP) dielectric thin film capacitor with self-clearing and enhanced current carrying capability offer an inexpensive and lightweight alternative for efficient power conditioning, energy storage, energy conversion, and pulsed power. The originality is the comprehensive physics and multi-dimensional modeling which span the dynamic range from initial injection to near breakdown. This model has been validated against some empirical data and may be used to identify failure mechanisms such as charge packets, gaseous voids, and electroluminescence. The value lies in the use of this model to develop mitigation strategies, including re-designs and materials matching, to avoid these failure mechanisms.

Ten common “sand‐traps”, selected by two team‐building consultants from their experiences in team building, are discussed along with the interventions that have worked successfully for them and with their clients, both team leaders and team members, in chipping out of the sometimes unavoidable sand‐trap. The sand‐trap metaphor also points to sharpening skills already apparent in the team, and to increasing alternatives for constructive problem solving. A consultant′s checklist is included for managing a successful team‐building effort.