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In this work, the structural battery composite (SBC) full-cells based on carbon fiber (CFs) were fabricated using a three-step hot pressing method. LiFePO4 (LFP) was loaded onto CF fabrics considering the influences of hot pressing parameters including the pressure and the temperature. The SBC full-cells were subsequently fabricated using the LFP loaded CF cathode, the CF anode, the glass fiber (GF) separator via a structural electrolyte (SE) filming process, followed by the second hot pressing. The multifunctional efficiencies were assessed for SBCs with SE containing different components. To reduce the capacity loss, the SBC was eventually encapsulated with the GF/Vinyl Ester prepreg and thermally cured in the third hot pressing. The capacity retention of the SBC was significantly improved after encapsulation. This work could be seen as a further step forward the engineering fabrication of the SBC full-cells based on both CF anodes and cathodes.

The Benxi Formation in the eastern Ordos Basin harbors abundant natural gas resources and shows promising exploration and development potential. However, the reservoir characteristics are complex, and the primary controlling factors are unclear, presenting significant challenges for reservoir characterization. In response to these challenges, we conducted a systematic study on the characteristics of tight sandstone reservoirs in the Benxi Formation by integrating thin section analysis, scanning electron microscopy, high-pressure mercury injection, and conventional petrophysical analysis alongside well log data analysis. By applying empirical calculation formulas of a porosity evolution quantitative model, we elucidated the primary controlling factors of reservoir heterogeneity. Our research identified that the reservoirs in the eastern Ordos Basin, Benxi Formation, are predominantly composed of quartz sandstone and lithic quartz sandstone, with pore-filling cementation as the dominant cement type and the main storage spaces being intergranular pores and dissolved pores. The homogenization temperatures of fluid inclusions in authigenic quartz range from 92.8 to 185.7°C, indicating that the target layer is in the mesodiagenesis phase B. The main reasons for the differences in reservoir quality in the Benxi Formation are attributed to both sedimentation and diagenesis. In terms of sedimentation, two distinct sedimentary microfacies control the distribution of reservoir quality differences based on variations in quartz content and soluble components. Regarding diagenesis, the Benxi Formation underwent compaction, cementation, and dissolution, with compaction being the fundamental cause of widespread reservoir compaction.

With the rapid development of electronic information technology, higher requirements have been put forward for the dielectric properties and load-bearing capacity of materials. In continuous glass fiber-reinforced thermoplastic composites, polypropylene matrix is a non-polar polymer with a very low dielectric constant and dielectric loss, but polypropylene is extremely flammable which greatly limits its application. Aiming at the better application of flame retardant-modified continuous glass fiber-reinforced polypropylene composites (FR/GF/PP) in the field of electronic communication, the effects of four different kinds of flame retardants (Decabromodiphenyl ethane (DBDPE), halogen-free one-component flame retardant (MONO), halogen-free compound flame retardant (MULTI), and intumescent flame retardant (IFR)) on the properties of FR/GF/PP were compared, including the mechanical properties, dielectric properties and flame-retardant properties. The results showed that among the FR/GF/PP, IFR has the highest performance in mechanical properties, MULTI has better performance in LOI, DBDPE and IFR have better performance in flame retardant rating, and DBDPE and IFR have lower dielectric properties. Finally, gray relational analysis is applied to propose an approach for selecting the optimal combination (flame retardant type and flame-retardant content) of comprehensive performance. In the application exemplified in this paper, the performance of IFR-3-modified GF/PP is optimized.

The application of continuous glass fiber-reinforced polypropylene thermoplastic composites (GF/PP) is limited due to the inadequate flame retardancy of the polypropylene (PP) matrix. Apart from altering the composition of the flame retardants, the distribution modes of flame retardants also impact material performance. In this study, an alternative approach involving non-uniform distribution is proposed, namely, dispersed distribution, in which non-flame-retardant-content layers (NFRLs) and/or low-flame-retardant-content layers (LFRLs) are dispersed among high-flame-retardant-content layers (HFRLs). The mechanical, flame retardant and dielectric properties of GF/PP with intumescent flame retardant (IFR/GF/PP) are investigated comparatively under uniform, gradient, and dispersed distributions of the flame retardants. The results demonstrate that non-uniform distribution exhibits superior flame retardant performance compared to uniform distribution. Dispersed distribution enables IFR/GF/PP to attain enhanced mechanical properties and reduced dielectric constants while maintaining excellent flame-retardant properties.

Using fiber-reinforced polymer composite to replace metal in window frames has become a trend in aircraft manufacturing to achieve structural weight reduction. This study proposes an innovative winding compression molding process for continuous production of aircraft window frames using continuous carbon fiber-reinforced polyamide 6 thermoplastic composite filaments (CF/PA6). Through process parameter optimization, the production cycle of CF/PA6 composite window frames was controlled within 5 min, with an ultra-low porosity of 0.69%, meeting aviation application standards. Combining mechanical property experimental tests and finite element analysis, the mechanical performance of window frames made from three different materials was compared and evaluated. In the hoop direction, the mechanical performance of the continuous CF/PA6 thermoplastic window frames were significantly higher than that of chopped CF/epoxy compression molding window frames and aluminum alloy window frames. In the radial direction, the maximum strain occurred at the corner with the highest curvature of the frame due to the absence of fiber reinforcement, resulting in weak pure interlayer shear. Nevertheless, the thermoplastic CF/PA6 winding compression molded window frame still exhibited a high resistance to crack propagation and damage, as evidenced by the absence of any detectable sound of microdamage during testing with a 9000 N load. It is believed that achieving a further-balanced design of hoop–radial performance by appropriately introducing radial ply reinforcement can lead to a significant weight reduction goal in the window frame. The findings in this study provide an innovative process reference that can be universally applicable to high-speed and near-net-shape manufacturing without material waste of continuous fiber-reinforced thermoplastic composite products.

In this study, in order to expand the engineering application range of thermoplastic corrugated sheets, flame-retardant thermoplastic corrugated sheets were prepared by the thermoplastic molding method. Based on our previous research results, we prepared flame-retardant prepreg tapes with the flame retardant addition accounting for 15%, 20%, and 25% of the resin matrix. Then, we prepared flame-retardant thermoplastic corrugated sandwich panels with corresponding flame retardant addition amounts. The limiting oxygen index test, vertical combustion test, cone calorimetry test, and mechanical property test were carried out on each group of samples and control group samples. The results showed that when the flame retardant was added at 25%, the flame retardant level could reach the V0 level. Compared with the control group, the flexural strength and flexural modulus decreased by 2.6%, 14.1%, and 19.9% and 7.3%, 16.1%, and 21.9%, respectively. When the amount of flame retardant was 15%, 20%, and 25%, respectively, the total heat release decreased by 16.3%, 23.5%, and 34.1%, and the maximum heat release rate decreased by 12.5%, 32.4%, and 37.4%, respectively.

The corrosion of rebars will change the mechanical properties of the reinforced concrete structure, leading to the decline in the structural strength, which seriously threatens the safety and stability of buildings and power equipment foundations. Hence, it is of great significance to detect the internal corrosion of reinforced concrete structures. In this paper, a nondestructive detection method for detecting the corrosion in reinforced concrete structures based on microwave was proposed, and the corrosion state of rebar can be evaluated by the change of microwave information. Compared with other detection methods, microwave nondestructive detection has the advantages of low energy consumption, strong penetration, no contact, and small equipment volume and weight. In order to verify the effectiveness of the method, a microwave nondestructive detection simulation test platform was built and reinforced concrete test models with different corrosion lengths and depths were made. The influences of concrete parameters, the microwave frequency, and the lifting distance of the waveguide were analyzed. The frequency sweeping and moving scanning detection methods of the waveguide were carried out for the test models with different corrosion defects, and the changes of microwave S-parameters under different corrosion defects were obtained. The results show that when the waveguide is placed horizontally by the frequency sweeping detection method, the corrosion length detection effect of rebar is better. When the waveguide is placed vertically by the frequency sweeping detection method, the corrosion depth can be identified and the amplitude of transmission coefficient increases with the increase in the corrosion depth. The corrosion length of rebars can be identified quantitatively by the moving scanning detection method of the waveguide.

This paper deals with the effects of different freeze-thaw cycling environments on the mechanical properties, dimensional stability, and water absorption behaviors of continuous carbon fiber reinforced polyamide 6 composites (CF/PA6). In a nominally dry state, freeze-thaw (FT) exposure can slightly increase the mechanical properties due to the elimination of residual stress. However, FT exposure in a water immersion environment causes a linear decrease in transverse tensile properties and flexural properties and an exponential decrease exposure in water immersion environment. This difference in degradation rate can be attributed to the varying water content, and the relationship between retention rate of mechanical properties and FT cycles was further developed to predict its long-term aging performance. In addition, water absorption behaviors, dimensional measurement, and micro-characterization were also applied to analyze the mechanism of mechanical properties degradation.

This study aimed to investigate moisture absorption behaviors, dimensional stability, and mechanical performance evolution of continuous carbon fibers reinforced with polyamide 6 composites (CF/PA6) under a hygrothermal environment. 3D Fickian model determined the principal three-dimensional (3D) diffusion coefficients by using an optimization algorithm. Three-dimensional changes of samples were measured to quantify the relationship between swelling coefficient and water content. After hygrothermal aging, the tensile properties of PA6 resin and CF/PA6 composites in the transverse direction decreased significantly, but the longitudinal tensile properties of CF/PA6 composites were insensitive to hygrothermal aging. DMA (Dynamic Mechanical Analysis), SEM (Scanning Electron Microscopy) and FTIR (Fourier Transform Infrared) tests were also applied to analyze the mechanism of mechanical properties degradation.

In this work, Fe–decorated nitrogen–doped carbon nanospheres are prepared for electrochemical monitoring of acetaminophen. Via a direct pyrolysis of the melamine–formaldehyde resin spheres, the well–distributed Fe–NC spheres were obtained. The as–prepared Fe–NC possesses enhanced catalysis towards the redox of acetaminophen for abundant active sites and high–speed charge transfer. The effect of loading Fe species on the electrochemical sensing of acetaminophen is investigated in detail. The synergistic effect of nitrogen doping along with the above–mentioned properties is taken advantage of in the fabrication of electrochemical sensors for the acetaminophen determination. Based on the calibration plot, the limits of detection (LOD) were calculated to be 0.026 μM with a linear range from 0–100 μM. Additionally satisfactory repeatability, stability, and selectivity are obtained.

This paper describes a strategy for preparing free-standing reduced graphene oxide@Si nanoparticles (rGO@Si NPs) composite membranes. Graphene oxide (GO) was reduced and self-assembled synchronously with nanoparticles of silicon (Si NPs) on a metal surface and the composite film was subsequently used in a lithium-ion battery (LIB). This work describes several important novel aspects of the reported technology. Firstly, the composite membrane has a flexible self-supporting structure, allowing it to function as an anode material without requiring binders and current collectors. Secondly, the successful assembly of Si NPs and reduced Graphene oxide (rGO) sheets has enabled the production of the rGO@Si NPs composite film with high controllability and orderliness. Thirdly, the conductive nature of graphene has significantly decreased the resistivity while enhancing the electron transport capacity of the battery anode. Lastly, the robust and flexible structure of the graphene sheet has greatly mitigated the large volume variation in Si NPs during charging or discharging, resulting in the rGO@Si NPs composite film exhibiting excellent energy density and high-power density.

Abstract Power systems depend on discrete devices, such as shunt capacitors/reactors and on-load tap changers, for their long-term reliability. In transmission systems that contain large wind farms, we must take into account the uncertainties in wind power generation when deciding when to operate these devices. In this paper, we describe a method to schedule the operation of these devices over the course of the following day. These schedules are designed to minimize wind-power generation curtailment, bus voltage violations, and dynamic reactive-power deviations, even under the worst possible conditions. Daily voltage-control decisions are initiated every 15 min using a dynamic optimization algorithm that predicts the state of the system over the next 4-hour period. For this, forecasts updated in real-time are employed, because they are more precise than forecasts for the day ahead. Day-ahead schedules are calculated using a two-stage robust mixed-integer optimization algorithm. The proposed control strategies were tested on a Chinese power network with wind power sources; the control performance was also validated numerically.

Aramid fibre-reinforced epoxy composites (AF/EP) are promising materials in the aerospace, transportation, and civil fields owing to their high strength, high modulus, and light weight. Thick composite laminates are gradually being applied to large composite structures such as wind turbine blades. During curing, temperature overheating is a common problem in thick composites, which leads to matrix degradation, thermal residual stresses, and uneven curing. This paper proposes a signal-to-noise ratio (SNR) method to optimise the curing cycle of thick AF/EP laminates and reduce the overheating temperature. During curing, the temperature and strain evolution in a thick AF/EP laminate were monitored using fibre Bragg grating sensors. The effects of the curing factors on the overheating temperature of the thick AF/EP laminate were evaluated using the Taguchi method and predicted via the SNR method and analysis of variance. The results indicate that the dwelling temperature is the main factor affecting the overheating temperature. The optimal curing cycle involves an overheating temperature of 192.72 °C, which constitutes an error of 2.58% compared to the SNR method predictions. Additionally, in comparison to the initial curing cycle, the overshoot temperature in the optimised curing cycle was reduced by 58.48 °C, representing a reduction ratio of 23.28%.

Massive composite components manufactured by autoclave curing in large framed molds are extensively used in the aerospace industry. The high temperature performance of the large framed mold is the key to achieving the desired composite part quality. This paper explores and summarizes the important thermal properties of metal and heat transfer fluid materials influencing the heating performance of large framed molds, with the aim of improving the mold temperature distribution. Considering the fluid–thermal–solid interaction inside the autoclave, a reliable computational fluid dynamics (CFD) simulation model was developed and verified by a temperature monitoring experiment to achieve the prediction of the temperature distribution of the large framed mold. Then, numerical simulations were designed on the basis of the CFD model, and the single-variable method was used to study the effects of the material thermal properties on the temperature performance of large framed molds. Our simulation predicts that when copper is used as the mold material, the temperature difference decreases by 30.63% relative to that for steel, and the heating rate increases by 3.45%. Further, when helium is used as the heat transfer medium, the temperature difference decreases by 68.27% relative to that for air, and the heating rate increases by 32.76%. This paper provides a reference for improvement of large framed mold manufacturing and autoclave process in terms of heating rate and temperature uniformity.

Thermoplastic composites (TPCs) are promising materials for aerospace, transportation, shipbuilding, and civil use owing to their lightweight, rapid prototyping, reprocessing, and environmental recycling advantages. The connection assemblies of TPCs components are crucial to their application; compared with traditional mechanical joints and adhesive connections, fusion connections are more promising, particularly resistance welding. This study aims to investigate the effects of process control parameters, including welding current, time, and pressure, for optimization of resistance welding based on glass fiber-reinforced polypropylene (GF/PP) TPCs and a stainless-steel mesh heating element. A self-designed resistance-welding equipment suitable for the resistance welding process of GF/PP TPCs was manufactured. GF/PP laminates are fabricated using a hot press, and their mechanical properties were evaluated. The resistance distribution of the heating elements was assessed to conform with a normal distribution. Tensile shear experiments were designed and conducted using the Taguchi method to evaluate and predict process factor effects on the lap shear strength (LSS) of GF/PP based on signal-to-noise ratio (S/N) and analysis of variance. The results show that current is the main factor affecting resistance welding quality. The optimal process parameters are a current of 12.5 A, pressure of 2.5 MPa, and time of 540 s. The experimental LSS under the optimized parameters is 12.186 MPa, which has a 6.76% error compared with the result predicted based on the S/N.

Traditional outage model for the power equipment usually focus on the behavior of the equipment under random factors, and the availability of the power equipment in system analysis is usually confined to the steady value. However, this model may be inaccurate in the short term analysis, where the transient process of availability has not ended yet. Furthermore, the power equipment in the short term analysis might be influenced by both random factors and deterministic factors, yet the impact of deterministic factors cannot be completely reflected in the traditional outage model. Based on the above issues, a Markov-based transient outage model is proposed in this paper, which describes the deterioration and repair process of an equipment. Both the corrective maintenance and preventive maintenance are concerned in the model. The preventive maintenance in the model is considered as deterministic event, in which the start time and duration are both scheduled. Meanwhile the corrective maintenance and the unexpected failure are modeled as random events. The transient state probability and availability of equipment under preventive maintenance is derived. The effect of deterministic events on the availability of equipment is analyzed on numerical tests. The proposed model can be used in the short-term reliability assessment and maintenance scheduling in actual systems.

“Tube beams” are common lightweight structures, which have domestic and industry applications, and are often subjected to complex multidirectional loads. Therefore, metals with mature manufacturing methods and isotropic properties are commonly used in the fabrication of these structures, which are preferred to be lighter in weight. Although polymer matrix composites are generally used for weight reduction, their conventional manufacturing methods, such as pultrusion and filament-winding, cannot meet the isotropic requirements. Moreover, research on bent tube beams (elbows) is rare. Therefore, a self-made glass fiber/epoxy polyvinyl ester fabric prepreg and a self-designed mold were used in this study to prepare an isotropic composite double-bent elbow by a silicone rubber airbag-assisted process. The load capacity of the elbow was tested and validated by the finite element method. A strength and deformation of up to 3448 N and 2.84 mm respectively, were achieved. The simulation and experimental results were consistent: the error for the load capacity and deformation was only 4.15% and 7.75% respectively, under the max stress criterion.

The Lagrange multiplier-based method is an effective network parameter error identification method. However, two full matrices with high-dimensions are involved in the calculation procedure; these create huge computational burdens for large-scale power systems. To solve this problem, a fast solution is proposed in this paper, where special treatment techniques for full matrices are used to dramatically improve the calculation efficiency. A practical parameter error identification program has been developed and used in many electric power control centers. In this paper, the results for test systems and on-site applications are given, which show that the proposed approach is very efficient.

When large wind farms are centrally integrated in a power grid, cascading tripping faults induced by voltage issues are becoming a great challenge. This paper therefore proposes a concept of static voltage security region to guarantee that the voltage will remain within operation limits under both base conditions and N-1 contingencies. For large wind farms, significant computational effort is required to calculate the exact boundary of the proposed security region. To reduce this computational burden and facilitate the overall analysis, the characteristics of the security region are first analyzed, and its boundary components are shown to be strictly convex. Approximate security regions are then proposed, which are formed by a set of linear cutting planes based on special operating points known as near points and inner points. The security region encompassed by cutting planes is a good approximation to the actual security region. The proposed procedures are demonstrated on a modified nine-bus system with two wind farms. The simulation confirmed that the cutting plane technique can provide a very good approximation to the actual security region.

The operation of power systems has been complicated by the rapid diversification of loads. Analyzing load characteristics becomes necessary to different utilities in energy management systems to ensure the reliability of power systems. Here, we describe a method of analyzing and quantifying the load characteristics and introduce its application to pilot nodes selection for zone based voltage control. We propose a new index, the Q-fluctuation (QF), to quantify the load characteristic of reactive power based on an analysis of historical data. A second index, the V-fluctuation (VF), which is a combination of the QF and the Q–V sensitivity that reflects structural information for the grid describes the voltage deviation at each node. These indices are used to construct the voltage fluctuation space, which is then used to select the pilot node for each zone. Simulation studies using IEEE 14-bus and 118-bus systems are described, and used to demonstrate the advantages of the proposed method. The method was able to improve the secondary voltage control and enhance the grid reliability in response to structural changes.

In Part I of this work, a static voltage security region was introduced to guarantee the safety of wind farm reactive power outputs under both base conditions and N-1 contingency. In this paper, a mathematical representation of the approximate N-1 security region has further studied to provide better coordination among wind farms and help prevent cascading tripping following a single wind farm trip. Besides, the influence of active power on the security region is studied. The proposed methods are demonstrated for N-1 contingency cases in a nine-bus system. The simulations verify that the N-1 security region is a small subset of the security region under base conditions. They also illustrate the fact that if the system is simply operated below the reactive power limits, without coordination among the wind farms, the static voltage is likely to exceed its limit. A two-step optimal adjustment strategy is introduced to shift insecure operating points into the security region under N-1 contingency. Through extensive numerical studies, the effectiveness of the proposed technique is confirmed.

Spinning reserve allocation is a critical problem for active power dispatch with large-scale wind power penetration. A risk-based reserve allocation method that accounts multiple control sub-area coordination is given in this paper. And a multi-objective optimization model is constructed to schedule the spinning generation reserve for online active power dispatch. A fuzzy optimization method is used to transform the multi-objective optimization problem into a single-objective optimization one. The relationship between loss of load expectation and spinning reserve is also derived. And a particle swarm optimization (PSO) method is employed to provide a numerical solution to the problem. Numerical tests on IEEE RTS system are also given to validate the proposed method.

Electric vehicles (EVs) and the related infrastructure are being developed rapidly. In order to evaluate the impact of factors on the aggregated EV load and to coordinate charging, a model is established to capture the relationship between the charging load and important factors based on data mining. The factors can be categorized as internal and external. The internal factors include the EV battery size, charging rate at different places, penetration of the charging infrastructure, and charging habits. The external factor is the time-of-use pricing (TOU) policy. As a massive input data is necessary for data mining, an algorithm is implemented to generate a massive sample as input data which considers real-world travel patterns based on a historical travel dataset. With the input data, linear regression was used to build a linear model whose inputs were the internal factors. The impact of the internal factors on the EV load can be quantified by analyzing the sign, value, and temporal distribution of the model coefficients. The results showed that when no TOU policy is implemented, the rate of charging at home and range anxiety exerts the greatest influence on EV load. For the external factor, a support vector regression technique was used to build a relationship between the TOU policy and EV load. Then, an optimization model based on the relationship was proposed to devise a TOU policy that levels the load. The results suggest that implementing a TOU policy reduces the difference between the peak and valley loads remarkably.