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Abstract An asymmetric semantic multi‐level segmentation method based on depth learning is proposed in order to improve the precision and effect of semantic segmentation. A ‘content tree’ structure and an adjacency matrix are constructed to represent the parent‐child relationship between each image sub region in a complete image. Through multiple combinations of spatial attention mechanism and channel attention mechanism, the similarity semantic features of the target object can be selectively aggregated, so as to enhance its feature expression and avoid the impact of significant objects. The asymmetric semantic segmentation model asymmetric pyramid feature convolutional network (APFCN) is constructed, and the path feature extraction and parameter adjustment are realised through APFCN. On the basis of APFCN network, a full convolution network is introduced for end‐to‐end image semantic segmentation. Combining the advantages of convolution network in extracting image features and the advantages of short‐term and short‐term memory network in solving long‐term dependence, an end‐to‐end hybrid depth network is constructed for image semantic multi‐level segmentation. The experimental results show that the mean intersection over Union value and mean pixel accuracy value are higher than that of the literature method, both of which are increased by more than 3%, and the segmentation effect is good.

When multiple CCHP microgrids are integrated into an active distribution network (ADN), the microgrids and the distribution network serve as distinct stakeholders, making the economic optimal dispatch of the system more complex. This paper proposes a distributed dispatch model of ADN with CCHP multi-microgrid, and refines the objective functions of each region. The analytical target cascading approach (ATC) is employed to model the power transaction as virtual sources/loads, and solve the optimal dispatch in parallel. Case studies demonstrate the proposed distributed model is capable of achieving economic optimization for both stakeholders.

Hot torsion tests for AZ80 magnesium alloy were carried out in the temperature range of 380 °C-260 °C, with a constant decreasing temperature rate of 10 °C/s in order to weaken the basal texture and refine the grains. The results indicated that the average grain sizes were refined forming gradient structure with increasing specimen radial position from center (12.2–5.4 μm), and that the initial basal texture intensity of the extruded magnesium alloy was weakened from 46.2 to 8.3. Furthermore, the extension twins (ETs) could be disintegrated from the twins forming separated twins with smaller sizes. Interestingly, ETs with the same twin variant intersecting with each other could be coalesced forming grains with similar orientation, while ETs with different twin variants were separated by twins boundaries contributing to grain refinement. Moreover, in addition to the conventional continuous dynamic recrystallized (CDRX) grains with 30˚ orientation rotated around C-axis of the parent grains, CDRXed grains with 30˚ rotation around a-axis and random rotation axis were also discerned. Besides, the CDRX evolution induced twins were also elaborated, exhibiting the complex competition between CDRX and twining. Hot torsion deformation with constant decreasing temperatures rate is an effective way of grain refinement and texture modification.

The extruded AZ80+0.4% Ce magnesium alloy was twisted in the temperature range of 300 - 380 °C by using a Gleeble 3500 thermal simulation test machine with a torsion unit. The deformed cylindrical specimens were cooled at a cooling rate of 10 °C/s or 0.1 °C/s, respectively, and aged at 170 °C. The microstructure analysis results showed that the grain size decreased with increasing specimen radial position from center (SRPC), and that the strong initial basal texture of the extruded magnesium alloy was weakened. Both continuous and discontinuous dynamic recrystallization mechanisms were involved in contributing to the grain refinement for all specimens investigated. And a novel extension twinning induced dynamic recrystallization mechanism was proposed for specimen deformed at 300 °C. For the specimens deformed at 300 °C and 340 °C followed by a slow cooling rate (0.1 °C/s), precipitates of various shapes (β-Mg17Al12), with the dominant precipitates being on the grains boundaries, appeared on the surface section. For specimen deformed at 380 °C, lamellar precipitates (LPS) in the interiors of the grains were predominant. After aging, the LPS still dominated for specimens twisted at 380 °C; however, the LPS gradually decreased with decreasing deformation temperatures from 380 °C to 300 °C. Dynamically precipitated β, especially those decorating the grain boundaries, changed the competition pictures for the LPS and precipitates of other shapes after aging. Interestingly, LPS dominated the areas for the center section of the specimens after aging regardless of deformation temperatures. Low temperature deformation with high SRPC followed by rapid cooling rate increased the micro hardness of the alloy after aging due to refined grain, reduced precipitates size, decreased lamellar spacing as well as strain hardening.

As large amounts of distributed renewable energy generation (DREG) replace conventional generating units on the grid, the tension between the supply lack of flexible resources and the increased demand for flexible resources on the grid intensifies. To address this issue, this paper focuses on distributed renewable energy generation aggregation (DREGA) applications based on energy storage systems (ESS). Considering the interconnection and supply–demand coupling between generation and consumption in the grid, ESS is used to flexibly regulate the flow of electrical energy between producers and consumers in DREGA. A pricing methodology that takes into account aggregation differences and real-time changes based on supply and demand is developed. This method mobilizes resources within the aggregator to help the network operator balance supply and demand through price incentives. Electricity is shared directly between producers and consumers within the aggregation, in addition to indirectly shared through ESS. It improves the self-consumption of renewable energy and the self-supply rate of users from the perspective of aggregators. The validity of the proposed method is proven by case study results.

Shared energy storage offers substantial savings on construction costs and improves energy efficiency for users, yet its business model as an independent economic entity remains unclear. An optimal scheduling method for cooperative operation of shared energy storage among multiple user types is proposed in this paper, which relied on asymmetric Nash bargaining to define operational schedules and pricing strategies effectively. Initially, a cost-benefit model for shared energy storage operators, along with power generation users, demand-side consumers, and microgrid prosumers is developed. Then, a cooperative game framework is established using asymmetric Nash bargaining principles which decomposes the problem into two parts: minimizing social total cost through cooperative operation scheduling and determining service fee pricing for equitable benefit distribution. For benefit distribution, the bargaining power of users is adjusted based on their alliance contribution, ensuring revenue distribution is aligned with individual contributions and improving fairness in pricing. Subsequently, the adaptive penalty factor alternating direction multiplier method (ADMM) algorithm is employed for distributed equilibrium solving, enhancing the convergence speed and safeguarding user privacy. Finally, the economics and feasibility of the proposed cooperation framework for shared energy storage are validated through a numerical example.

Integrated power-gas systems (IPGS) have developed critical infrastructure in integrated energy systems. Moreover, various extreme weather events with low probability and high risk have seriously affected the stable operation of IPGSs. Due to close interconnectedness through coupling elements between the power system (PS) and natural gas system (NGS) when a disturbance happens in one system, a series of complicated sequences of dependent events may follow in another system. Especially under extreme conditions, this coupling can lead to a dramatic degradation of system performance, resulting in catastrophic failures. Therefore, there is an urgent need to model and evaluate resilience of IPGSs under extreme weather. Following this development trend, an integrated model for resilience evaluation of IPGS is proposed under extreme weather events focusing on windstorms. First, a framework of IPGS is proposed to describe states of the system at different stages under disaster conditions. Furthermore, an evaluation model considering cascading effects is used to quantify the impact of windstorms on NGS and PS. Meanwhile, a Monte Carlo simulation (MCS) technique is utilized to characterize chaotic fault of components. Moreover, time-dependent nodal and system resilience indices for IPGS are proposed to display impacts of windstorms. Numerical results on the IPGS test system demonstrate the proposed methods.

Abstract Natural gas is the main energy source and carbon emission source of integrated energy systems (IES). In existing studies, the price of natural gas is generally fixed, and the impact of price fluctuation which may be brought by future liberalization of the terminal side of the natural gas market on the IES is rarely considered. This paper constructs a natural gas price fluctuation model based on particle swarm optimization (PSO) and Dynamic Bayesian networks (DBN) algorithms. It uses the improved epsilon constraint method and fuzzy multi-weight technology to solve the Pareto frontier set considering the system operation cost and carbon emission. The system operation cost is described using Latin Hypercube Sampling (LHS) to predict the stochastic output of the renewable energy source, and a penalty function based on the Predicted Mean Vote (PMV) model to describe the thermal comfort of the user. This is analyzed using the Grey Wolf Optimization (GWO) algorithm. Carbon emissions are calculated using the carbon accounting method, and a ladder penalty mechanism is introduced to define the carbon trading price. Results of the comparison illustrate that the Pareto optimal solution tends to choose less carbon emission, electricity is more economical, and gas is less carbon-intensive in a small IES for end-users when the price of natural gas fluctuates. The impacts of various extents of natural gas price fluctuation for the same load are also discussed.

Battery charging and swapping station (BCSS) can provide flexibility for the distribution network due to accumulating a large number of batteries. This paper proposes a multi-objective optimization method of distribution network considering BCSS, aiming to minimize the transmission losses, voltage deviation and curtailment of wind and photovoltaic power. Besides, The present study puts forth a novel integrated modeling methodology for batteries, which is founded upon the State of Charge (SOC) interval. This approach includes the total energy constraint, as well as the charging and discharging priorities of the batteries. Finally, numerical tests are carried out to validate the correctness and rationality of the presented method. The outcomes of the study show that 2% reduction in wasted energy is achieved with BCSS.

With the deepening interdependence between the power system and the natural gas system (NGS), the integrated power-gas system (IGPS) has been a vital part of the energy structure. On one hand, interdependence improves energy utilization. On the other hand, the two-way energy flow brings new challenges to the reliable operation of IPGS. Therefore, the integrated planning model of IPGS considering N-1 constraint is proposed. Firstly, a framework of IPGS is developed to describe the N-1 contingency both in the power system and NGS considering cascading effects. Then an integrated planning model is proposed considering N-1 constraint and cascading effects between the power system and NGS. The reduced disjunctive model (RDM) is utilized to obtain the optimal planning scheme and reduce calculation difficulty. Furthermore, to further verify the effectiveness of the proposed methods, the integrated planning model is performed on an integrated gas and power test system.

The investment-return model of power system plays an important part in the business model of power system. In previous studies, the financial pressure brought by the proportion of power project investment was neglected. An investment-return model based on asymmetric Nash bargaining was proposed in this paper, which could better reflect the game process of investment-return in the new power system. Firstly, the stakeholders of cooperative game were analyzed so as to establish the framework of cooperative game model. Secondly, combined with various characteristics of new power system, various influencing factors of the cooperative game was estimated. Thirdly, the expression and solution of Nash bargain were put forward. Finally, the availability of the model was verified by an example. The experiment showed that the investment-return model could reflect the process of investment-return of the new power system more completely.

Abstract Background Stroke has been found to be highly correlated with the triglyceride-glucose (TyG) index. The relation between the TyG index changes and stroke, however, has seldom been reported, and current researches mentioning the TyG index concentrate on individual values. We aimed to investigate whether the level and the change of TyG index was associated with the incidence of stroke. Methods Sociodemographic, medical background, anthropometric and laboratory information were retrospectively collected. Classification was conducted using k-means clustering analysis. Logistic regressions were to determine the relationship between different classes with changes in the TyG index and incidence of stroke, taking the class with the smallest change as a reference. Meanwhile, restricted cubic spline regression was applied to examine the links of cumulative TyG index and stroke. Results 369 (7.8%) of 4710 participants had a stroke during 3 years. Compared to class 1 with the best control of the TyG Index, the OR for class 2 with good control was 1.427 (95% CI, 1.051–1.938), the OR for class 3 with moderate control was 1.714 (95% CI, 1.245–2.359), the OR for class 4 with worse control was 1.814 (95% CI, 1.257–2.617), and the OR for class 5 with consistently high levels was 2.161 (95% CI, 1.446–3.228). However, after adjusting for multiple factors, only class 3 still had an association with stroke (OR 1.430, 95%CI, 1.022-2.000). The relation between the cumulative TyG index and stroke was linear in restricted cubic spline regression. In subgroup analysis, similar results were shown in participants without diabetes or dyslipidemia. There is neither additive nor multiplicative interaction between TyG index class and covariates. Conclusion A constant higher level with worst control in TyG index indicated a higher risk of stroke.

Purpose Bowel habits may affect the prognosis in the chronic kidney disease (CKD) patients. This study aimed to explore the association of bowel habits with cardiovascular and all-cause mortality in CKD.Methods 2460 CKD patients in the National Health and Nutrition Examination Survey (NHANES) from 2005 through 2010 without missing data for bowel habits and mortality were enrolled. Bowel habits including bowel movements (BMs) per week and stools consistency were obtained by standard interview. Mortality status and cause of death were determined by NHANES-linked National Death Index records through 31 December 2015. Cox proportional hazard models and Kaplan-Meier analysis were used to evaluate the association of bowel habits with cardiovascular and all-cause mortality.Results A total of 2460 CKD patients with an average age of 60.80 ± 0.57 years were enrolled. During an average follow-up of 87.47 ± 0.98 months, 144 cardiovascular and 669 all-cause deaths were documented. Reporting 3 or fewer BMs per week was associated with cardiovascular (HR = 1.83, 95% CI: 1.06, 3.17) and all-cause mortality (HR = 1.71, 95% CI: 1.20, 2.43). More than 10 BMs per week also increased the risk of all-cause mortality (HR = 1.21, 95% CI: 1.01, 1.45). Hard stools consistency increased the risk of all-cause mortality (HR= 2.00, 95% CI: 1.48, 2.70) compared with those reporting normal stools.Conclusion Low stool frequency and hard stool consistency were associated with an increased risk of mortality in patients with CKD.

Improving the resilience of the distribution grid to extreme rainstorms can effectively reduce the resulting outage losses. Based on the massive number of electric vehicles (EV) with objective capacity in the distribution network environment, it is essential to study the discharge of EVs to make up for the shortage load in the distribution network’s post-disaster recovery. In this paper, we first establish a coupling network integrating the distribution grid and road network, simultaneously coupling information from different levels. Then establish a model describing the characteristics of EV travel behavior based on the travel chain and probability distribution function to portray the spatial distribution of EVs in the time dimension. Then establish a model of EVs in this area and cross-area EV participating in discharge response based on the area after EV clustering. Also, establish the extreme storm weather affected EV discharge willingness model to describe the uncertainties of EVs. Finally, two faults set in the IEEE33 node are simulated and verified, and the model description and analysis of the influencing factors of EV participation in discharge are given.

With the deepening of the coupling between the power system and natural gas system (NGS), the integrated gas and power systems (IGPSs) have been an important infrastructure in the energy systems. On the one hand, the IGPSs improve the energy efficiency. On the other hand, the coupling structure makes the safe and reliable operation of the power system more threatened, especially under extreme events. As an important infrastructure, the IGPS often has large-scale power outage in meteorological disaster events, such as windstorm. Therefore, it is necessary to evaluate the resilience of the IGPS. A resilience assessment model is proposed to evaluate the resilience of IGPSs considering the cascading effects between the two systems under windstorms with low probability and high risk. Firstly, the failure model of components utilizing the fragility curve is represented. Then, an optimal power flow model is proposed to evaluate the resilience of the power system. Based on this, resilience indicators are proposed to quantify the damage caused by windstorms. The proposed methods have been proved to be effective in evaluating the resilience of the IPGS. Simulation results show that IPGS is less resilient than independent power systems due to cascading effects. The decrease of resilience intensifies with the increase of wind speeds, and the performance level of IGPS is 58% lower than that of IPS when the wind speed is 36 m/s.

As the penetration of renewables increases, air conditioners (ACs), whose electricity consumptions account for a large share, present tremendous potential in providing load regulating service to maintain the power supply–demand balance. In this paper, an analytical model for the dynamic aggregated power and schedulable capacity of ACs is presented, where the safe protocol (SP) is utilized to eliminate the power oscillations caused by temperature setpoint shifting. Based on this, the response potential of ACs is quantified by the evaluation indexes in the dimensions of capacity and time. Besides, an optimal dispatch strategy is proposed to implement the coordination of air conditioning resources in the response stage and recovery stage, by which not only the reliable load regulation service can be provided, but also the influences on users can be minimized. Simulation studies demonstrate the effectiveness of the proposed method.

In this study, 7075 Al alloy was prepared by solution treatment + natural aging. The anisotropic behavior of 7075 Al alloy in extrusion direction (ED), 45° direction (45°) and radial direction (RD) was studied by quasi-static tensile test and strain controlled low cycle fatigue (LCF) test. The specimens of ED, 45° and RD were 0°, 45° and 90° to the extrusion direction of the bar, respectively. The mechanical properties of the specimens in three directions showed strong anisotropy. The yield strength (YS) and ultimate tensile strength (UTS) of ED specimens were better than 45° and RD specimens, but 45° specimens had better plasticity. With the extension of aging time, the YS and UTS increase significantly. In the quasi-static tensile process, the specimens would have dynamic strain aging (DSA), and obvious serrated flow behavior could be observed on the curve. For the fatigue performance of specimens in three directions, when the strain amplitude was low, the fatigue life of ED and 45° specimens was high. When the strain amplitude was high, the fatigue life of RD specimens was high. The experimental results showed that after cyclic loading, the second phase size of solution treatment + cyclic loading specimens was larger than T6 (480 °C × 3 h + 130 °C × 24 h). Therefore, the fatigue fracture mode was multi-source fracture at low strain amplitude.

Focused on life, consumption, and leisure, communities have been regarded as the basic unit of energy use in a city owing to rapid urbanization, whose energy use density continues to increase. Moreover, community integrated energy systems (CIESs) in the rapid development stage have become em-bedded, small, and self-sufficient energy ecosystems within cities because of their environmental and economic benefits. CIESs face a competitive energy trading environment that comprises numerous entities and complicated relationships. This paper presents an extensive review of various issues related to CIES trading. First, the concepts, types, and resources of CIESs are described. Second, the trading patterns and strategies of CIESs are reviewed from the four perspectives of the trading objects: community-to-peer (C2P), peer-to-peer (P2P), community-to-community (C2C), and community-to-grid (C2G). Third, a tri-layer trading framework and the features of CIESs that participate in combined multienergy markets are proposed. Last, the key issues in CIES trading are summarized.

A free-induction-decay (FID) type optically-pumped rubidium atomic magnetometer driven by a radio-frequency (RF) magnetic field is presented in this paper. Influences of parameters, such as the temperature of rubidium vapor cell, the power of pump beam, and the strength of RF magnetic field and static magnetic field on the amplitude and the full width at half maximum (FWHM) of the FID signal, have been investigated in the time domain and frequency domain. At the same time, the sensitivities of the magnetometer for the single-pass and the triple-pass probe beam cases have been compared by changing the optical path of the interaction between probe beam and atomic ensemble. Compared with the sensitivity of ∼21.2 pT/Hz1/2 in the case of the single-pass probe beam, the amplitude of FID signal in the case of the triple-pass probe beam has been significantly enhanced, and the sensitivity has been improved to ∼13.4 pT/Hz1/2. The research in this paper provids a reference for the subsequent study of influence of different buffer gas pressure on the FWHM and also a foundation for further improving the sensitivity of FID rubidium atomic magnetometer by employing a polarization-squeezed light as probe beam, to achieve a sensitivity beyond the photo-shot-noise level.

Residential air conditionings (RACs) can be seen as one of the important flexible demand resources controlled to provide balance services for the power system due to their spatial thermal storage feature. However, such control on RACs will bring out the negative impact on the comfort level of residents inevitably, affecting their proactivity in demand response (DR). So, a novel two-stage control model of large-scale RACs is proposed to participate in DR considering different comfort sensitivity of various residents. The comfort sensitivity index is developed in terms of daily operation time and daily power consumption per area of RACs, classified by K-means clustering. Besides, the DR potential of RACs is established with the adjusted temperature setpoint, where the temperature setpoint is determined by the comfort sensitivity index. Moreover, a two-stage control model of large-scale RACs is proposed comprised of load response and recovery, where the corresponding control strategies at each stage are proposed. Simulations of the proposed method have been performed on residential 20,000 RACs to validate its effectiveness in Changzhou, China. The outcome reveals that the strategies could maximize the DR potential of RACs and ensure the stable recovery of RACs under the premise of meeting the comfort demand of differentiated population.

Roll forming can improve the material utilization rate and production efficiency of cups with a curved rotary profile, but there is no basis for the determination of forming limit. The DEFORM-3D software was used to simulate the roll forming of cups. The influence of the billet wall thickness and bottom thickness, coefficient of friction, radius of roller, and the fillet radius of the punch on the forming limit was studied, and the damage value and velocity vector were analyzed. The results showed that the forming limit of the billet’s wall thickness in roll forming for a cup is about 62%. With the increase of the ratio of the formed cup’s wall thickness to the billet’s bottom thickness, the forming limit of wall thickness will be slightly reduced. A larger radius of roller, fillet radius of punch, and friction coefficient between punch and billet and a smaller friction coefficient between roller and billet are good for decreasing the damage value and improving the roll-forming limit. According to the numerical simulation results, the roll-forming limit diagram of cups is established, and the accuracy of the forming limit diagram is verified by experiments.

This study proposed a rotary back extrusion (RBE) process for an open punch, which is used to produce high-performance 7075 aluminum alloy cup-shaped piece. The RBE experiment was carried out on the Gleeble-3500 testing machine at 400 °C and compared with the conventional back extrusion (CBE). The microstructure was analyzed by optical microscope, scanning electron microscope and DEFORM-3D simulation software. The results shown that compared with CBE, RBE can significantly increase the equivalent strain value and deformation uniformity of 7075 aluminum alloy cup-shape pieces. RBE deformation increases the accumulated strain of the piece, and the rotation of the die causes the piece to produce shear strain, which increases the overall strain of the cup-shape piece. The proportion of dynamic recrystallization increases, and the grain refinement was obvious. The micro-hardness value of the RBE sample is higher than that of the CBE sample, which could be the result of grain refinement strengthening. What is more, RBE and CBE have different metal flow laws.

For an extrusion process of 7075 Al alloy, the extrusion direction of the initial blank is changed to study the mechanical properties of the formed plates and characterize their microstructure. The as-received bar is extruded 7075 Al alloy. The secondary extrusion deformation is along and perpendicular to the initial extrusion direction. The results show that the anisotropy of mechanical properties of the two samples decreases obviously after secondary deformation. The anisotropy of yield strength and ultimate tensile strength of ED90 sample is lower than that of ED0 sample, but the plastic anisotropy is slightly higher than that of ED0 sample. In addition, the recrystallized grain proportion of ED90 sample is high and the texture strength is low, so the Schmid factor in the three directions is similar. The tensile fracture mode of the two samples belongs to ductile fracture, but the morphology of dimple and the size of cleavage plane are slightly different.

The quasi-static and low cycle fatigue tests of extruded 7075 Al alloy (Φ200 mm) were investigated in three directions: the extrusion direction (ED), the radial direction (RD), and 45° with ED (45°). Grain morphology analysis, texture measurement, and fatigue fracture characterization were conducted to discuss the relationship between microstructure and mechanical properties. The experimental results showed that the ED specimen had higher ultimate tensile strength (UTS) and low cycle fatigue (LCF) properties, which were mainly attributed to the following three causes. First, the grain boundaries (GBs) had an obvious effect on the crack growth. The number of GBs in the three directions was different due to the shape of the grains elongated along the ED. Second, the sharp texture and the small Schmidt factor along the ED explained the higher ultimate tensile strength (UTS) of the ED specimens. Third, fatigue fracture observation showed that the ED specimen had a narrow fatigue striation spacing, which indicated that the plastic deformation of the ED specimen was the smallest in each cycle. In addition, two fatigue prediction models were established to predict the LCF life of extruded 7075 Al alloy, based on the life response behavior of the three directions under different strains.

Abstract Stochastic noises have a great adverse effect on the prediction accuracy of electric power load. Modeling online and filtering real-time can effectively improve measurement accuracy. Firstly, pretreating and inspecting statistically the electric power load data is essential to characterize the stochastic noise of electric power load. Then, set order for the time series model by Akaike information criterion (AIC) rule and acquire model coefficients to establish ARMA (2,1) model. Next, test the applicability of the established model. Finally, Kalman filter is adopted to process the electric power load data. Simulation results of total variance demonstrate that stochastic noise is obviously decreased after Kalman filtering based on ARMA (2,1) model. Besides, variance is reduced by two orders, and every coefficient of stochastic noise is reduced by one order. The filter method based on time series model does reduce stochastic noise of electric power load, and increase measurement accuracy.

Energy absorption for AZ31 magnesium Alloy was investigated with Split Hopkinson Pressure Bar using single stress wave so as to avoid multiple stress wave loading. The stress wave amplitude, which was in elastic stress range and propagated along the AZ31 magnesium bar, was reduced with increasing propagating distance, and with increasing stress wave amplitude, the stress wave amplitude reduction along the magnesium bar was increased losing more energy as compared with that of the stress wave with lower amplitude. The drastically decreased stress wave amplitude could be explained based on dislocations movements, which was similar to the established theory of damping for the explanation of the energy loss during cyclic loading. However, it was not the case for LY12 aluminum alloy: the stress wave amplitude changed slightly without drastic energy loss regardless of the variation of stress wave amplitude.

A hollow billet Expanding-Reducing Extrusion (ERE) wheel hub forming process was carried out with AZ80 magnesium alloy. The effects of ageing on Low-cycle fatigue (LCF) properties were investigated, and the microstructure was characterized with scanning electronic microscopy (SEM). The LCF testing results exhibited that the stress amplitude increased with increasing ageing time, while the plastic strain decreased with increasing ageing time. Cyclic softening followed by hardening was observed for 0 h and 16 h aged samples; however, there was no obvious cyclic softening or hardening for 36 h aged sample. The tension-compression asymmetry were not obvious due to the low strain, precipitation and the non typical basal texture. Fracture observations indicated that the fatigue cracks were initiated on the surface, and the crack propagation area decreased with increasing ageing time. Thus, it can be concluded that ageing has strong effects on the fatigue life for the studied magnesium alloy.

This paper concentrates on the capacity credit (CC) evaluation of wind energy, where a new method for constructing the joint distribution of wind speed and load is proposed. The method is based on the skew-normal mixture model (SNMM) and D-vine copulas, which is used to model the marginal distribution and the correlation structure, respectively. Then a cross entropy based importance sampling (CE-IS) is improved to enhance the efficiency of the power system reliability assessment, which is a crucial part of the CC evaluation. After that, the proposed methods are adopted to combine with the secant method to develop a complete algorithm to calculate the CC of wind energy. Numerical tests are designed and carried out based on the IEEE-RTS 79 system and wind speed data obtained from four wind farms in Northwest China. In order to show the superiority of SNMM and D-vine copula, the goodness-of-fit is quantified by different statistics. Besides, the improved CE-IS method is validated by comparison with Monte Carlo sampling (MCS) and traditional CE-IS in the efficiency of reliability assessment. Finally, the proved methods are combined with the secant method to calculate the CC of four wind farms, which can provide information for wind farm planning.