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In this study, a non-local approach is developed for the fatigue life prediction of notched specimens, considering stress/strain gradient and elastic-plastic fatigue damage. The damage coupled constitutive models are presented to model the mechanical behavior of material. The critical plane method and triaxiality factor are employed to determine the location of the couple point. The gradient values of mechanical quantities are then computed, and the modified coefficients in damage models are acquired. The numerical simulations are implemented to compute the damage evolution process and predict fatigue life. Meanwhile, the coupling effects between stress field and damage field are considered. The predicted results are verified by experimental data, and also compared with the local method. Finally, the influence of stress concentration factor, shape of notch, and cyclic variation of stress/strain gradient are further investigated.

Epicentres are the focus of COVID‐19 research, whereas emerging regions with mainly imported cases due to population movement are often neglected. Classical compartmental models are useful, however, likely oversimplify the complexity when studying epidemics. This study aimed to develop a multi‐regional, hierarchical‐tier mathematical model for better understanding the complexity and heterogeneity of COVID‐19 spread and control. By incorporating the epidemiological and population flow data, we have successfully constructed a multi‐regional, hierarchical‐tier SLIHR model. With this model, we revealed insight into how COVID‐19 was spread from the epicentre Wuhan to other regions in Mainland China based on the large population flow network data. By comprehensive analysis of the effects of different control measures, we identified that Level 1 emergency response, community prevention and application of big data tools significantly correlate with the effectiveness of local epidemic containment across different provinces of China outside the epicentre. In conclusion, our multi‐regional, hierarchical‐tier SLIHR model revealed insight into how COVID‐19 spread from the epicentre Wuhan to other regions of China, and the subsequent control of local epidemics. These findings bear important implications for many other countries and regions to better understand and respond to their local epidemics associated with the ongoing COVID‐19 pandemic.

This study investigates the first section of the Shahejie Formation in the Suning area. Based on three-dimensional seismic, logging, drilling core and other data, and on the principle of seismic sedimentology, the difficulty in accurately characterizing thin sand bodies is resolved. Moreover, the study area is clearly defined as sediment from the western provenance, along with the identification of the nearshore terminal fan facies. This study aims to determine the seismic characteristics of sand body based on 90° phase optimization processing and frequency division interpretation processing to judge the relative isochronous seismic event, and a 45-Hz seismic data body is selected for stratum slice to realize the fine characterization of channel sand body. Finally, a high-precision sedimentological interpretation of stratigraphic slices reveals the seismic response characteristics and evolution rules of the nearshore terminal fan deposits.

For daily airport operations, the insufficient number and the improper scheduling of ground support vehicles are the main causes of flight delays. In this paper, a novel network model is proposed to complement the optimal scheduling of ferry vehicles for the flight ground support service. In the process of model construction, we first innovatively construct a ferry vehicle capacity network by having the introduced virtual flights and the ferry vehicle depot as nodes, in which the directed edges indicate that the two nodes associated may be consecutively served by the same ferry vehicle. Based on the capacity network, a mixed integer programming model is constructed to minimize the number of ferry vehicles needed. In addition, this paper shows that the mixed integer programming is equivalent to a linear programming when the service start time of each flight is fixed, which makes the solving process more efficient, and the linear programming model can be applied to solve the minimum node-disjoint path cover of directed acyclic graphs. The efficiency and accuracy of the method are validated by the actual flight data obtained from Beijing Capital International Airport. This study will provide a methodological reference for the optimal scheduling of airport ferry vehicles.

Virtual community (VC) arises rapidly and influences many aspects of human life styles in real world. Differentiated from traditional way to advertise products/services, VC also enables consumers to participate in interaction activities related to products via threads, learn greater insight about products in deep level while improve consumer loyalty. Most of the extant research did not emphasize or lack of effective methods on how to gain deep learning of product and explain the uniformity of users’ importance in VC. In this paper, based on knowledge in complex network, generalised variance of degree in directed network is proposed to ascertain uniformity of directed network, which is an innovative methodology. Research conclusions can guide enterprises more in-depth understanding of the complex network theory and its application to social network analysis (SNA) with big data streams.

During synchronous fracturing of horizontal well clusters, the induced stresses generated by multiple wells affect the formation of complex fractures. By using linear superposition and vector representation, the productivity model for the horizontal stress field between wells was constructed. The results demonstrated simultaneous fracturing can produce stronger and a wider range of stress interference variable impact on induced stress field, the most influential factor is the row spacing, accounting for 32.09% and the engineering factors with the least impact is fracture conductivity, with weight of 0.08%. The research results were used to YA gas field. After the preliminary implementation in the field, the initial production of a well in the reservoir increased by 20.48%, the decline rate slowed down by 13.16% and the output of well increased by 43.75% in the stable production period. In addition, these results might also provide an acceptable explanation for the high productivity of synchronous fracturing operations in horizontal well clusters. Generally speaking, a clear understanding of changes in induced stress fields in horizontal clusters might provide are liable foundation for the determination of optimal well spacing and a fracturing program for horizontal well clusters to develop unconventional formations.

Compared with conventional reservoirs, shale gas reservoirs usually have no natural productivity or lower productivity, and the production decline is faster in the later stage. The production effect of shale gas can be effectively improved by designing well pattern reasonably or fracturing in the later stage. Therefore, it is critical for shale gas reservoir to study on how to design well pattern and set reasonable fracturing parameters reasonably in order to make it effectively developed. Based on data of block-A shale gas field of Zhejiang region, considering the contribution of rock compression to the production of fluid, the productivity formula of the shale gas horizontal well development mode at different seepage stages is deduced. Data of A shale gas field is verified by orthogonal experiment, including gas reservoir parameters and engineering parameters. The results show that: the order of gas reservoir parameters that affect the development of shale gas is as follows: Langmuir pressure, inter-porosity flow parameter, diffusion coefficient, Langmuir volume; the order of engineering parameters that affect the development of shale gas is as follows: the number of fractures, the horizontal section length, production pressure, fractures length, row spacing and well spacing. The research results have been applied to Zhejiang oilfield. After the preliminary implementation in the field, the decline rate of shale gas has slowed down by 26.08%. The research results have important reference significance for the efficient development of similar gas reservoirs.

Due to growing concerns for environmental problems and food quality, consumers pay more attention to the carbon emission and freshness of fresh food. The booming e-commerce also accelerates the development of the dual-channel supply chain. In the dual-channel supply chain of fresh food, the carbon emission and freshness of fresh food are becoming important factors affecting consumers’ purchase demand. This paper focuses on the optimal decision of carbon emission reduction and pricing, which is investigated by a Stackelberg game-theoretic approach in three dual-channel supply chain sales models (retailer dual channel, producer dual channel, and mixed dual channel). A two-stage fresh food supply chain system composed of a producer and a retailer is explored. The sensitivity analysis and the comparison of three dual-channel models are carried out. The results show the following: (1) the sales price, carbon emission reduction, market demand, producer’s profit, retailer’s profit, and supply chain’s profit of fresh food under the three dual-channel supply chains show the same change on different levels of consumers’ low-carbon preference coefficient and freshness level, respectively, (2) the optimal decision of carbon emission reduction and pricing, demand, and profit of the three dual-channel models need to be determined according to the value of consumers’ purchasing preferences for the retailer’s offline channel. The paper gives some enlightenment to the decision-making members in the fresh dual-channel supply chain.

Under “the Belt and Road” initiative, China promoted cooperation between domestic enterprises and international ports vigorously, which brought back fruitful results, while the rational selection of strategic pivots ports and the optimization of the layout of the port network are important guarantees to a further promotion to the economic development of “the Belt and Road” ports and give full play to the driving and radiation role of strategic pivots ports. On the basis of constructing a network of 155 ports in the world, according to the number of ports crossed by the shortest path and betweenness centrality in the network, this paper uses K-Medoids clustering algorithm to train the strategic importance of ports and verifies the reliability of the analysis results. On this basis, the joint coverage analysis of strategically important ports is carried out, 17 ports are identified as strategic pivots ports of the global port network, and, finally, based on the two attributes of “the Belt and Road” and “Chinese enterprise participation” of strategic pivots ports, the leading role of strategic pivots ports in geographical location, path coverage, development potential, cooperation stability, and control is analyzed, and instructive suggestions are put forward.

Synergetic development is the basis and means for the sustainable development of regional economies. Research on the synergetic economic relationship between cities and the exposure of the internal structure and evolution mechanisms of the Urban Economic Synergetic Development Network (UESDN) in the context of industrial agglomeration promote the construction and sustainable development of such a system. Industrial agglomeration not only affects the spatial distribution of industrial structures and enterprise activities but also causes differences in city positions. Using input−output theory, this study constructed a UESDN for China in 2005, 2010, and 2015, and employed social-network analysis to analyze the spatial and temporal evolution characteristics of China’s synergetic development pattern. The degree centrality, betweenness centrality, and cohesive subgroups of the UESDN were computed using models in complex-network theory. This study found that the synergetic development pattern of Chinese urban economies has gradually developed from the hub-spoke model focused on Eastern provincial capitals to the network model of eastern and central cities over the period of 2005−2015. A few key cities act as intermediaries that carry economic factors with the shortest path in the UESDN. The Yangtze River economic belt, the axis belt of the Eastern coast and that of the Western economic belt were gradually formed. The number and strength of the correlation between cities within the subgroups have also continually increased. In our conclusion, we offer some suggestions for establishing a system of synergetic development between cities to improve urbanization levels.

With the growth of online commerce, companies have created virtual communities (VCs) where users can create posts and reply to posts about the company’s products. VCs can be represented as networks, with users as nodes and relationships between users as edges. Information propagates through edges. In VC studies, it is important to know how the number of topics concerning the product grows over time and what network features make a user more influential than others in the information-spreading process. The existing literature has not provided a quantitative method with which to determine key points during the topic emergence process. Also, few researchers have considered the link between multilayer physical features and the nodes’ spreading influence. In this paper, we present two new ideas to enrich network theory as applied to VCs: a novel application of an adjusted coefficient of determination to topic growth and an adjustment to the Jaccard coefficient to measure the connection between two users. A two-layer network model was first used to study the spread of topics through a VC. A random forest method was then applied to rank various factors that might determine an individual user’s importance in topic spreading through a VC. Our research provides insightful ways for enterprises to mine information from VCs.

The Chinese stock 300 index (CSI 300) is widely accepted as an overall reflection of the general movements and trends of the Chinese A-share markets. Among the methodologies used in stock market research, the complex network as the extension of graph theory presents an edged tool for analyzing internal structure and dynamic involutions. So, the stock data of the CSI 300 were chosen and divided into two time series, prepared for analysis via network theory. After stationary test and coefficients calculated for daily amplitudes of stock, two “year-round” complex networks were constructed, respectively. Furthermore, the network indexes, including out degree centrality, in degree centrality, and betweenness centrality, were analyzed by taking negative correlations among stocks into account. The first 20 stocks in the market networks, termed “major players,” “gatekeeper,” and “vulnerable players,” were explored. On this basis, temporal networks were constructed and the algorithm to test robustness was designed. In addition, quantitative indexes of robustness and evaluation standards of network robustness were introduced and the systematic risks of the stock market were analyzed. This paper enriches the theory on temporal network robustness and provides an effective tool to prevent systematic stock market risks.

Substantial changes took place in the role of consumers in the supply chain with the development of practices. They became creators from consumers of product values. More and more consumers express their consumption experiences by posting in network community. Consumer community network is an important place for feedback of product experiences and facilitating product innovation in future. Manufacturers can promote improvement and innovation of products by exploring effective information on the consumer community network, thus improving the experience level of consumers. Therefore, how to explore information in topics (posts) and their relationships becomes very important. Is it possible to describe the structure of consumer community network by complex network and explore information about products and consumers? There is important and positive significance to study the collaborative innovation in the supply chain in which consumers participate. In this paper, the consumer community network was constructed by Boolean retrieve programming and discussed in the methodology and empirical way based on the community data of Huawei P10/P10 Plus. In methodology, interaction difference and uniformity within consumer community were explored by the density of isolated nodes and generalized variance of degree of network. In empirical studies, community network users were divided into ordinary user group, intermediary user group, and enterprise user group according to empirical data, and corresponding interaction networks were constructed. A contrastive analysis on the interaction of these three groups was carried out by combining the existing properties and innovative properties. Topics in each network were put in the order according to significance. Research conclusions have important significance to enrich the network analysis methods, explore the effective information in consumer community network, facilitate product improvement and innovations, and improve the experience level of consumers.

A continuum damage mechanics-based method is adopted to predict the fatigue life of notched specimens subjected to constant amplitude cyclic loading while containing single or multiple overloads. The residual stress and plastic damage induced by an overload are considered to be the main factors affecting the fatigue life of a specimen. The residual stress and plastic strain fields of a notched specimen are calculated using the elastic–plastic finite element method. The mean stress of the following cyclic loading is then varied by superimposing the residual stress. Meanwhile, the plastic damage is calculated based on the ductile damage model and accumulated into the total damage of the material. The quantitative effects of an overload on the damage evolution and the fatigue life are evaluated. Furthermore, the effects of the damage–overload ratio on the variation of the residual stress induced by an overload are investigated, and the effects of the occurrence time for a single overload and the occurrence frequency for multiple overloads are studied.

The cyclic contact stresses in cylindrical roller bearings are evaluated through the explicit finite element analysis with rolling the roller instead of moving a constant contact pressure in the computational domain. A new damage evolution equation in terms of the amplitude of octahedral shear stress is proposed, which considers the non-proportional variation of stress, and the material parameters in which are easily obtained from torsion fatigue testing data. Numerical simulations of crack initiation, crack propagation, and spalling are performed. The simulation results are consistent with the previous experimental results. Furthermore, the coupling effect between the contact stresses and fatigue damage is investigated, and the effects of contact loading on the fatigue life are studied.

A novel inter-fiber failure criterion of composites based on micro-scale failure mechanism is proposed in this paper. The composites failure is determined by the failure of constituents near interface, where the micro-scale stress is “risk”. A cross-scale stress calculation formula is derived according to inclusion theory, and proved precise by comparing with the micro-scale simulation results. The accuracy of the failure criterion is verified through the experimental results and simulation results of micro-scale model under biaxial stress . The failure criterion considers the micro-scale stress distribution, fiber volume fraction and elastic properties of constituents, and can give precise predictions on the strength and failure angle of fiber reinforced polymer composite .

In this paper, a standardization modelling method of composites micro-scale simulation is proposed, in which the random distribution of fiber, hydrostatic pressure sensitivity yield behavior of polymer matrix and friction effect in fiber/matrix interface are considered. After the detailed introduction of the constitutive models of polymer matrix and interface, the methods to determine the input data of polymer, fiber and interface are provided. Then the stress-strain curves of composites under uniaxial loads were simulated and compared with experiment, which proving the accuracy of the micro-scale model. Besides, the comparison of failure envelopes under transverse stress and longitudinal shear stress of simulation and experiment further verified the validity of the model. Finally, the influence of the geometry, friction coefficient and interface properties on the mechanical properties of composites were discussed. The proposed modelling method provides a standardization means to establish micro-scale model, thus easy to be reproduced by other researchers.

Considering uncertainties in emergency demand quantity and occurrence time, allowance cooperation strategy and prosocial sale strategy are designed to mitigate expiration wastages for emergency perishable inventory system. Distribution-free newsboy models are developed for relief supply chain. For computational tractability, we derive upper bound of the expected total cost, then determine the applicable conditions of proposed strategies with pessimistic criterion. We offer a proof that the controversial sale strategy may be effective in both expiration mitigation and cost reduction, and elaborate an application framework and managerial insights of proposed strategies based on the type of emergency supplies and type of disasters.

Additive manufacturing (AM) technology has been widely employed in the fabrication of titanium alloy parts for aerospace engineering applications. In this paper, a damage mechanics based machine learning framework is presented for the data-driven fatigue life prediction of AM titanium alloy. At first, a theoretical framework including the damage mechanics based fatigue models and random forest model is presented for the fatigue damage analysis and life prediction of the AM titanium alloys under cyclic loadings. Second, a computational methodology is demonstrated in detail from two aspects, that is, the numerical implementation of the damage mechanics based fatigue models and the construction process of the random forest model. After that, fatigue life predictions are carried out for the AM titanium alloy smooth and notched specimens under different stress levels and stress ratios. The predicted results are compared with the experimental data to verify the proposed method. Finally, parametric studies are investigated on the prediction performance and fatigue lives for the AM titanium alloys.

In this paper, a new method is proposed to calculate the fatigue life and defect tolerance for a 30CrMnSiA steel specimen with foreign object impact damage and scratch damage. First, the processes of foreign object impact and scratch are simulated. Then, the Lemaitre’s plasticity damage model is adopted to calculate the initial damage field arising from the impact process and scratch process. Second, the Chaudonneret’s damage model is applied to calculate the fatigue damage for the specimen with a defect under multiaxial fatigue loading. Then, the FE implementation of the damage mechanics model is presented in the platform of ANSYS, in which the coupling effect between the stress and damage fields is considered. Finally, this proposed method is applied to fatigue life and defect tolerance calculation for the 30CrMnSiA steel specimen with an impact defect and a scratch defect. The experiments were conducted to evaluate the approach mentioned above.

In this study, the effects of open innovation practices on enterprise value were discussed based on the supply chain perspective. A nonlinear programming mode was constructed considering the uncertainty of open innovation effect. On this basis, the prototype was analyzed using a robust optimization approach with comprehensive considerations to the infeasible probability of constraint and goal accuracy. Findings show that parameter $$\Gamma $$ could convert the nonlinear programming model with uncertainty into a robust model with a strong stability. Furthermore, $$\Gamma $$ could be used to regulate the preference of the manufacturer to profit and the uncertainties in innovative practices. A small $$\Gamma $$ indicates manufacturers can refer to more information, and the manufacturers are more inclined to a mass production, so the profit is larger. Meanwhile, a high $$\Gamma $$ means that manufacturers can refer to less information, so that they pay more attention to making the product output adapt to the uncertainty of innovative effect. Manufacturers could select the appropriate $$\Gamma $$ value and reasonably arrange the production outputs of different goods according to the technological level of open innovation subject and their preference to profit and uncertainty. These conclusions were verified by a case study. In this work, the uncertainty of the open innovation effect was investigated from the supply chain perspective, which is of important significance to the decision making on optimal supply chain output and innovation risk control under an uncertain environment.

Fatigue is a major reason for the failure of components subjected to cyclic loadings, and the fatigue failure of components can be divided into two phases: crack initiation and crack propagation. In this study, continuum damage mechanics (CDM) combined with the extended finite element method (XFEM) is proposed to predict the total fatigue life of components, that is, the crack initiation life and propagation life. First, the damage-coupled elastic-plastic constitutive equations and fatigue damage evolution equations are derived to calculate the fatigue damage and to predict the crack initiation life of a material under cyclic loads. Second, according to the distribution of the damage field and trend of fatigue damage evolution, the criterion to judge the formation of crack initiation is proposed. Third, based on linear elastic fracture mechanics (LEFM) with XFEM, the crack propagation life is predicted. Then, fatigue crack initiation and propagation analysis for a specimen with a preset pit and for a fuselage structure with opening are conducted using the method described above. Finally, fatigue experiments are conducted to verify the proposed method, and the predicted total fatigue life and crack propagation path are in accordance with the experimental results.

In this study, a continuum damage mechanics approach coupled with an improved pit evolution model was proposed to predict the corrosion fatigue life of aluminum alloy. The coupled elasto-plastic damage constitutive equations and elastic–plastic damage evolution models were adopted to evaluate the fatigue damage. Pit growth was modeled with considering the effects of multiaxial stresses and fatigue damage. Numerical simulations were then implemented using the ABAQUS, and the results were compared with the experimental data. In addition, the interaction between corrosion and fatigue damage was presented, and the effects of the stress level and loading frequency were examined.

Both air pollution and greenhouse effect have become important issues with regard to environmental protection both in China and across the world. Consumption of energy derived from coal, oil, and natural gas forms the main source of China&rsquo, s major air pollutants, SO2 and NOX, as well as the major greenhouse gas CO2. The energy structure adjustment approach provides a sensible way, not only to achieve climate change mitigation and air pollutant reduction, but also to reduce abatement costs. In this paper, a multi-objective optimization method was adopted in order to analyze the collaborative optimization of emissions and abatement costs for both air pollutants and greenhouse gases. As a typical industrial city and economic center with fossil fuels as its main energy source, Tianjin of China is used as the research sample to prove that this method can mitigate air pollutants and greenhouse gas emissions and reduce abatement costs. Through demonstration, the results show that the optimization method proposed can reduce SO2, NOX, and CO2 emissions by 27,000 tons, 33,000 tons, and 29,000 tons, respectively, and the abatement costs will be reduced by 620 million yuan by adjusting the energy structure of Tianjin. The proposed method also suggests that China can achieve reductions of abatement cost and greenhouse gas and air pollutant emissions under the proposed energy structure. The results indicate that collaborative optimization would help China and other countries cope with climate change while improving domestic air quality.

Closed-loop supply chain value co-creation research has attracted attention from numerous scholars but is rarely discussed in terms of the electronics industry. As such, the impact of cross-shareholding on value co-creation remains unclear. This paper integrates value co-creation and cross-shareholding into the electronics closed-loop supply chain. Stackelberg Game and bi-level programming are used to build the model of electronics closed-loop supply chain value co-creation considering cross-shareholding between the manufacturer and retailer. The impact of cross-shareholding on value co-creation is revealed through comparative static analysis. The case of consumer electronics is adopted to execute numerical analysis and simulation. It is found that: (1) value co-creation includes not only the concern of the manufacturer for consumer value, but also consumer participation in value creation; (2) increasing cross-shareholding ratios will increase values of the closed-loop supply chain and each party (the manufacturer, retailer, remanufacturer, and consumers) and promote consumer participation in value creation when increasing such ratios is conducive to reducing the manufacturer’s unit production cost of using remanufactured parts, as well as the retailer’s unit environmental cost and the concern extent of the manufacturer for consumer value is controlled appropriately at the same time; (3) optimal cross-shareholding ratios should allow for Pareto improvement of values of the closed-loop supply chain and each party.