Special collection of 12 issues of "Journal of Shanghai Jiaotong University" in 2021
Nowadays, the third energy revolution has taken place. Many developed countries have formulated clean energy development strategies and announced the time for phasing out thermal and nuclear power to reduce carbon emissions. Meanwhile, China has made a commitment to the world that the carbon emissions of China will peak before 2030, and the carbon neutrality will be achieved before 2060. Therefore, it is of great significance to study the development pathway of clean electricity of China. The reserves and characteristics of clean energy such as hydro, wind, and solar in China are analyzed. The medium and long-term power demand of China is projected, and the power system structure in 2030 and 2050 are respectively estimated based on the electric power and energy balance equations. In addition, the trend of carbon emissions is also analyzed. Some suggestions are proposed to guide the development of China’s clean electricity. The results indicate that the “carbon peaking” of China’s power system would arrive in 2027, and the clean electricity of China is projected to exceed 50% of the total energy production in 2030. Thermal and nuclear power can be replaced by clean electricity such as hydro, wind, and solar energy in 2050, the power industry will achieve “zero CO2 emission”, and the transformation of the green power system will be achieved in response to carbon peaking and carbon neutrality goals.
To improve the accuracy of photovoltaic (PV) power prediction, this paper proposes a novel weather classification method. First, it distinguishs the clear days and cloudy days according to the total cloud cover. Then, it further classifies the cloudy days into three subtypes to investigate whether the sun is obscured by clouds. This method can effectively identify the characteristics of key meteorological environmental factors that affect PV output and form a new classification index sky condition factor (SCF) by weighted summation. This method has clear physical meanings, good discrimination, and easy quantification. The reasonable classification of weather types can eliminate the coupling relationship between many meteorological environmental factors and reduce the dimension of input variables, which makes it easy for statistical modeling. Based on the theoretical and the statistical approachs respectively, the modeling and verification are conducted and the results show that the method can effectively improve the accuracy of PV power prediction.
To respond to the demand of achieving carbon peaking and carbon neutrality goals, and to construct a complete “source-grid-load-storage” new energy power system, a distributed photovoltaic net load forecasting model based on Hamiltonian Monte Carlo inference for deep Gaussian processes (HMCDGP) is proposed. First, direct and indirect forecasting methods are used to examine the accuracy of the proposed model and to obtain spot forecasting results. Then, the proposed model is used to perform probability forecasting experiments and produce interval prediction results. Finally, the superiority of the proposed model is verified through the comparative experiments based on the net load data of 300 households recorded by Australia Grid. After obtaining the exact net load probabilistic forecasting results, the photovoltaic production can be fully utilized via power dispatch, which can reduce the use of fossil energy and further reduce the carbon emission.
Due to the difference in load characteristics and influencing factors in large-scale distribution transformer load forecasting, if all the distribution transformers share a unified model, the prediction accuracy is low, and if the model is built for each distribution transformer, the computational resources will be excessively consumed. An Attention-LSTM short-term forecasting method of distribution load based on multi-dimensional clustering is proposed. The non-parametric kernel method is used to perform probability fitting on the daily load characteristics to form a typical daily load sequence. Improved two-level clustering is applied for load clustering, taking the Euclidean warping distance and influence factors as the similarity evaluation criteria. AP clustering is utilized for obtaining similar time-series, and training sets are formed to train the Attention-LSTM model. Different Attention-LSTM models are obtained by training for different distribution load types and time-series. The effectiveness and practicability of the method proposed are verified by the load data and meteorological data of a municipal distribution network. The accuracy rate is increased by 2.75% and the efficiency is increased by 616.8%.
At present, new elements such as distributed new energy and electric vehicles have emerged in the distribution network, which changes the composition of loads, enriches the connotation of loads, and poses severe challenges to load forecasting. In fact, loads are aggregated in a bottom-up manner in multiple voltage levels of the distribution network, but such hierarchical characteristics are rarely considered in current load forecasting researches. Therefore, a multi-level load collaborative forecasting method based on the distributed optimization algorithm is proposed aimed at ensuring the bottom-up aggregation consistency of loads and jointly improving the performance of load forecasting at all levels. First, the distributed optimization concept based on the alternating direction method of multipliers is adopted to construct a multi-level load collaborative forecasting framework which adapts to the hierarchical characteristics of distribution network and has less data interaction. Then, a specific forecasting method based on the long short term-memory neural network and federated learning is proposed. By aggregating the bottom load forecasting results step by step, the bottom-up integrated load forecasting of distribution network can be realized. The results of calculation examples show that the proposed method has a high accuracy and a great application prospect.
With the objective of carbon neutrality, renewable energy resources gradually become the main power supply, whose variability poses great challenges to the operation and optimization of the system, especially to the power distribution network. In order to solve the problem of reactive power caused by high penetration of renewable energy sources, a centralized optimization model is proposed, which takes reactive power optimization and “generation-network-load-storage” multi-energy integration into account. The model aims at optimizing the operating cost and minimizing network losses and carbon emissions of the system. Reactive power compensation, regulation of energy storage, and energy conversion are considered to achieve safe and low-carbon economic dispatch of the power and gas systems. An improved second-order cone relaxation method is used for the convex relaxation of non-linear equality constraints concerned with the distribution network. The switching capacity produced by discrete reactive power compensators can be exactly linearized by the application of the big M approach. The simulation results demonstrate that the proposed method could effectively compensate the reactive power required by the grid-connection point of wind turbine, coordinate the energy interaction between the power and gas, thus improving the stability and elasticity of the distribution network after integration of large-scale renewable energy sources, which helps promote the consumption of renewable energy.
In order to simulate the impacts of carbon peaking and carbon neutrality goals on power system supply side transformation from, the system dynamics method is used to analyze the main influencing factors for carbon emissions in the process of power structure transformation and their correlations under four different development scenarios. The evolution of power generation structure and power carbon emission in four development paths are studied. The results show that the power system supply side transformation would be affected by many factors. Under the premise of policy support, the development of market absorption mechanism and absorption technology would contribute to the transformation of the power generation structure, which is of great significance to the realization of the dual carbon targets.
An integrated port energy system planning model is established considering the flexibility of shore power load to finely model the shore power load. Next, the proposed model is decoupled into shore power load elasticity and integrated energy system planning. Then, the shore power load curve of the port-ship master-slave game model is calculated. Finally, the optimal response method is used to iteratively solve the optimal integrated energy system planning method considering the shore power load elasticity. The simulation results show that the model can help rationally allocate resources in the port area, effectively improve the energy efficiency of the port area, increase the revenue of port area, and help the port area to save energy and reduce emissions.
To improve the utilization rate of clean energy, reduce carbon emissions, and alleviate the global energy crisis and greenhouse effect, a low-carbon economic dispatch model of multi-energy park considering high proportion of new energy consumption is proposed. First, after introducing the gas storage and heat storage equipment to the park, the potential of energy coupled devices is further tapped, and the impact of electric vehicle charging mode is explored. Then, based on the stepwise price curve, a price-based integrated thermo-electric demand response model is established. Moreover, considering the low-carbon operation of the integrated energy system, a carbon capture and storage equipment model is built. Furthermore, a mixed integer linear programming model for low-carbon economic dispatch before the day of the multi-energy park is proposed. The example analysis shows that the proposed model can improve the energy utilization rate and the scheduling flexibility of the park, effectively reduce the carbon emissions of the park, increase the income of the park, and promote the consumption of high proportion of new energy.
In order to improve the competitiveness of wind power in participating in the power market, promote low-carbon operation of the power system, and meet the new requirements for the completeness and flexibility of the production simulation model due to the uncertainty of wind power output,this paper analyzes the electricity cost composition from the perspective of low-carbon economy, and applies the stochastic programming theory to propose a short-term production simulation model of power system containing wind power. Considering the participation of the carbon trading market, this model aims to minimize the expected cost of electricity production in a short-term time scale, and coordinately optimize the day-ahead power output, real-time power regulation, power reserve capacity, wind curtailment, and load shedding. Taking the modified IEEE 39-bus system as an example, this paper quantitatively evaluates the impact of carbon trading mechanism, carbon trading price, and wind power installed capacity on electricity costs and their contributions to carbon emission reduction. The simulation results show that the proposed model can effectively analyze the short-term electricity cost, carbon emissions, and operational risks of the power system containing wind power under the carbon trading environment, thus has a promise application prospect.
The goal of “carbon peaking and carbon neutrality” puts forward higher requirements for low-carbon operation of power system considering security and stability. The large-scale access of new energy easily leads to problems such as uneven distribution of power flow and electromechanical oscillation. As the representative device of the third-generation flexible AC transmission system (FACTS), interline power flow controller (IPFC) is greatly capable of power flow control, damping control and transient stability control, but the main objectives of IPFC vary considerably under different working conditions, and there is contradiction between the goals. First, based on the improved relative gain matrix (MRGA) theory, the system state equation with IPFC was linearized, the interaction between targets was quantitatively analyzed, the superposition position of the additional controller was selected, and the interaction between steady-state control and dynamic control was weakened. Then, for the transient process, combined with fuzzy logic theory, the IPFC multi-objective coordinated controller was designed. Finally, the controller parameters were optimized using the particle swarm algorithm. While improving the transient stability and small disturbance stability, the controller reduced the power flow overshoot during the transient process and enhanced the coordinated control ability of IPFC under different system operating conditions. It was helpful to solve the problems of energy transmission and consumption, safety and stability control caused by the large load, low inertia, and random fluctuations of the power system under the “dual carbon” background.
Line hardening and energy storage configuration are important parts of the pre-disaster planning defense strategy, which can effectively improve the disaster prevention and emergency response capabilities of the hybrid AC-DC distribution system (HDS). Under the background of frequent extreme events, a method to improve the resilience of hybrid AC-DC distribution system considering line hardening and energy storage resource allocation is proposed, and a two-stage robust optimization model is constructed. Essentially, the model is a tri-level mixed integer nonlinear programming problem. The outer level evaluates the active behavior of HDS to determine the line hardening and energy storage system configuration strategies, the middle level determines the worst line failure set after the extreme event occurs, which is the passive behavior of HDS, and the inner level evaluates the active behavior of HDS to determine the emergency response and the operation strategies. Based on the nested column and constraint generation algorithm (nested column and constraint generation, NC&CG), the 3-level mixed integer linear programming model is solved. Finally, a simulation analysis is conducted with a 9-node DC distribution network and an improved IEEE-33 node hybrid AC-DC distribution system coupled with a ring AC distribution network as an example. The results show that the proposed method can effectively improve the resilience of the distribution network and ensure its safe and reliable operation in extreme events.
It is urgent to vigorously develop renewable energy to achieve the goal of “carbon peaking and carbon neutrality”. Unlike traditional thermal units, the marginal cost of renewable energy units is zero. With the reform of the electricity spot market, renewable energy is bound to have a huge impact on the market-clearing results and the operation of the power system. Considering the actual spot market operating rules, an electricity spot market simulation framework is established based on the security-constrained unit commitment and economic dispatch models for the operation simulation of the electricity spot market. Taking the actual data of a provincial power grid as an example, a quantitative analysis of the impact of renewable energy on the market-clearing results in the spot market environment is conducted. The simulation results show that, in the spot market environment, the participation of renewable energy will reduce the average electricity price, the system operating costs, and the renewable energy accommodation. At the same time, the profit space of the market units will be compressed.
In order to further enhance the active power regulation capacity of East China power grid, this paper analyzes the necessity of constructing an operation reserve system of East China power grid under the new power systems construction from the aspects of receiving end characteristics, new energy development, net load fluctuation, and the demand of power market reform. Furthermore, it proposes an operating reserve proposal system of East China power grid under the new situation based on the status of typical power systems at home and abroad. The suggested operating reserve system reorganizes and revises the principles of reserve classification, response time, and minimum reserve configuration. The results verify the effectiveness of the proposed operating reserve system through the measurement and analysis of the actual operation data of the East China power grid.
A day-ahead optimal decision-making model is established for an integrated electricity-heat energy system to participate in both the electric energy market and the spinning reserve market, and the step-by-step carbon trading is introduced into the proposed model. The conditional value at risk method is used to manage the uncertainty risk of renewable energy and electrical load. With the objective to minimize the operation scheme cost and carbon emission cost, an operation plan is developed and the reserve resources are arranged for the integrated electricity-heat energy system. The results of a case study show that the proposed model improves the reliability, economy, and low-carbon level by taking the complementary advantages of the integrated energy system and reasonably arranging reserve resources to deal with the risks caused by uncertain factors.
In order to accurately quantify the carbon emissions of coal-fired units with different capacities and serve the goal of “carbon peaking and carbon neutrality” in China better, a novel CO2 emission characteristic model for environment-economic dispatch of power systems is established. First, the changes in the capacity and coal consumption of coal-fired units in China in recent years are summarized and analyzed. Then, the relationship between the load rate and CO2 emission intensity is analyzed using the K-Medoide cluster method, and the carbon emission characteristic model of new coal-fired units restricted to basic equations is established. Finally, combined with theoretical analysis and actual data, a simulation is conducted to verify the validity of the model.
In this paper, an optimal sizing and placement model for distributed generation (DG) is established, which includes active power losses, voltage profile, pollution emission, DG costs, and meteorological conditions. Since optimizing placement and sizing are discrete and continuous variables respectively, the model established is a highly nonlinear complex one with discrete optimization variables. Therefore, the adaptive manta ray foraging optimization (AMRFO) algorithm is applied to obtain the optimal Pareto front, which has a rich and diverse search mechanism, individual updating mechanism, and advanced Pareto solution selection mechanism. For this model, a better solution of high quality can be obtained. In order to avoid the influence of subjective setting of weight coefficient, the ideal point method based on Mahalanobis distance is used to make Pareto front decision. Finally, the simulation based on the IEEE 33, 69-bus distribution network and the IEEE 33, 69-bus distribution network in isolated network operation are implemented. The results show that compared with the traditional multi-objective intelligent optimization algorithm, AMRFO algorithm can obtain a more widely distributed and uniform Pareto front. While considering the economy, the optimized distribution network voltage profile and active power losses can be significantly improved.
Aimed at the problems of wide area distribution, resource dispersion, and inefficient aggregation of distributed energy storage, this paper proposes an aggregation model and evaluation method of distributed energy storage based on the adaptive equalization technology. First, this paper establishes an adaptive equalization function model based on dynamic characteristic parameters such as energy storage capacity, power, and state of charge. Then, based on the adaptive equalization function model, it establishes the aggregation model and evaluation method of distributed energy storage, which takes the power regulation rate, adaptive equalization rate, and capacity contribution rate as the dynamic parameters of aggregation degree. The example simulation verifies that the model can realize the fact that each energy storage unit can complete the aggregation from energy storage unit to energy storage aggregate with a smaller internal difference and a higher external aggregation rate. It can be applied to a large number of distributed energy storage aggregation participating in grid auxiliary services, and realize the efficient utilization of energy storage resources.
A method for constructing a novel offshore platform was proposed. Based on the cooperative control of multiple unmanned vessels, a self-assembling platform was realized, which could be reconfigured into different shapes according to requirements. A docking controller was designed to realize the docking of two modules. A connecting rod and electromagnetic forces were adopted to complete the docking and reduce the difficulty. Besides, a test site was constructed using the conditions of pool, and a model test was performed to verify the functions of the proposed self-assembling platform. The results show that the design can realize the docking of any unmanned vessel. Compared with the single platform, this self-assembling platform can perform more complex tasks, whose decentralized design makes it more flexible and reliable.
Traditional process monitoring methods ignore the time-series correlation between variables, and do not distinguish the dynamic relationship and static relationship between variables, resulting in poor monitoring effect. To solve these problems, a dynamic-static joint indicator monitoring method of batch process based on global slow feature analysis(GSFA)-global neighborhood preserving embedding (GNPE) is proposed in this paper, which can effectively extract dynamic global features and static global features. First, the dynamic and static characteristics of the process variables are evaluated. Variables with weak autocorrelation and cross-correlation are regarded as static variables, and the remaining variables are regarded as dynamic ones. Next, the GSFA and GNPE models are constructed for dynamic and static subspaces, respectively. Finally, the statistical information from each subspace is combined by using Bayesian inference to obtain the joint indicator of the mixed model to realize process monitoring. Finally, the proposed algorithm is applied to a numerical example and the penicillin fermentation simulation process for simulation verification. The results show that the proposed GSFA-GNPE algorithm has better fault detection effects than other algorithms.
To solve the fresh water scarce problem in dry regions, a desiccant wheel-assisted atmospheric water harvesting system is designed. Using water production rate as the index, studies are conducted to find the optimized air handling process under typical ambient conditions, considering influencing factors such as air flow rate ratio, stage numbers, and regeneration temperature. Based on a three-stage-desiccant wheel air humidification system, power consumptions are calculated for ideal and actual thermodynamic processes. Besides, using water production efficiency as the index, at the same water production rate, this system is compared with the traditional air-cooling method. The results show that this system has higher performances than the traditional air-cooling method. Under the discussed working conditions, the water production rate of the proposed system is in the range of 15.8—30.9 kg/h and the water production efficiency is in the range of 1.3—2.1 kg/(kW·h). The water production efficiency can be enhanced to 3.3—4.4 kg/(kW·h)when solar heater is used to replace heat pump systems. The proposed method can effectively enrich fresh water sources in dry regions.
The element-free Galerkin scaled boundary method (EFG-SBM) based on moving Kriging (MK) interpolation is used to solve steady heat conduction problems with temperature loads on side-faces, in which the circumferential boundary is discretized based on MK interpolation and the element-free Galerkin (EFG) method. As the shape functions constructed from the MK interpolation possess the Kronecker delta interpolation property, the MK shape functions overcome the shortcomings of moving least squares (MLS) approximation which is difficult to impose essential boundary conditions directly and accurately. As a new boundary-type meshless method, EFG-SBM has advantages of the EFG and scaled boundary finite element method (SBFEM). This method inherits the semi-analytical property of SBFEM by introducing the scaled boundary coordinate system, in which the governing differential equations are weakened in the circumferential direction and can be solved analytically in the radial direction. Unlike the traditional SBFEM, the preprocessing and postprocessing processes of EFG-SBM are simplified since only the nodal data structure is required in the circumferential direction. Numerical examples show that the EFG-SBM based on MK interpolation can obtain a higher accuracy than the SBFEM based on Lagrange polynomials. Compared with the finite element method (FEM), this method can better characterize the thermal singularity at the sharp corner and the temperature distribution of the infinite region.
High-resolution simulation of shear layer oscillation induced by ridge ice in post-stall condition is conducted via the improved delayed detached-eddy simulation (IDDES) method. The flow-field evolution characteristics of large scale separation in high Reynolds number condition are described. It is shown that the ridge ice and trailing edge of the lower surface induce the development of shear flow at the same time. The wall is not reattached by the shear layer induced by ridge ice, and the “up-wash” flow from the lower surface is interacted with the shear layer, which lead to the formation of large-scale coherent structures. Combined with the spectral analysis, the pressure pulsation located in the shear layer is characterized by two typical frequencies, which are associated with Kelvin-Helmholtz instability and appear as the vortex pairing and shedding. Based on the proper orthogonal decomposition, the dominant mode of pressure pulsation between shear layers is extracted as large-scale coherent structures. The same peak value is shown in power density spectrum of dominant mode temporal coefficient and lift coefficient, which indicates that the large-scale coherent structure is connected with lift fluctuation.
In order to explore the influencing factors of the effectiveness and stability for stall recovery and its flow mechanism when the antisurge valve is opened quickly, the dynamic stall recovery processes are simulated and the recovery processes at different discharging speeds are emphatically compared. Two numerical simulation methods, i.e., the distributed speed-changeable MG (Moore-Greitzer) model and the RANS (Reynolds Averaged Navier-Stokes) equation are used. The performance curves predicated by the two models agree well. The results of RANS show that the flow field changes are essentially the same when the valve is opened at different speeds. The disturbance, affected by the high-speed air flow generated at the inlet, moves downstream and finally reaches the leading edge of the rotor, whose scale will be further reduced with the impact of axial high-speed flow until completely dissipated. A comparison of different valve opening speeds indicates that the faster the valve is opened, the stronger the high-speed air flow generated at the inlet, shortening the stall recovery time. The greater the disturbance weakening degree, the faster the circumferential propagation speed of the disturbance, and the closer to the rotor speed. In the process of valve opening, the air flow fluctuation is more intense, and more energy is lost.
In view of the issue that surface catalysis has a significant influence on aerodynamic heating of hypersonic vehicle heatshield and is difficult to accurately predict, a four-step surface heterogeneous catalytic model including physisorption, chemisorption, Eley-Rideal (ER) recombination, and Langmuir-Hinshelwood (LH) recombination was established by combining theoretical analysis and numerical simulation. Based on the model, the nonequilibrium flow and the aerodynamic heat around a two-dimensional cylinder were simulated. The influence of the fraction of occupied physisorption and chemisorption sites on the catalysis rate and the aerodynamic heat was analyzed. The results show that the established model can improve the prediction accuracy of the aerodynamic heat. The surface adsorption has a nonlinear influence on the aerodynamic heat due to the competing and promoting between different reaction pathways. Based on the real physicochemical process, the model can reflect the catalytic properties of different materials and further provides theoretical support for the lightweight and low redundancy design of the thermal protection system.
Aimed at the problem of weak coordination and low balance of distributed resources under multiple parallel deicing tasks, a cooperative control method of aircraft ground deicing resources based on multi-agent negotiation was proposed, which combined airport deicing resource allocation and space-time distribution. A framework for collaborative operation of multi-agent deicing resources was established, and a resource optimization method for the bidding mechanism of a global collaborative consortium was designed to improve the overall task balance. Based on the operating plan, an autonomous multi-agent resource collaborative optimization model was constructed. The model predictive control method was applied to generate a collaborative control strategy, and the feasibility was verified in actual scenarios. The results demonstrate that the resource coordination and anti-interference ability of the proposed method are significantly enhanced while meeting the real-time requirements. Compared with the results obtained by other methods, the average takeoff tolerance is 4.89 min, increased by 1.015 min, and the average utilization rate is increased by 15.28%, which can ensure the safety and synergy of deicing resources.
A novel test method for analyzing the influence of stress path and roughness of structure on the strength characteristics of saturated sand-structure interface by using triaxial apparatus is presented. By making a triaxial specimen with a slope structure with a certain inclination angle, the soil slides along the preset failure surface during the shearing process, and the slope surface roughness of the structure can be controlled and adjusted. A triaxial instrument is used to control the changes in axial pressure,confining pressure to achieve loading in different stress paths. The soil slides along the structure surface with a certain angle during shearing when preformed failure surface exists. The roughness of the structure can be controlled and adjusted. The triaxial apparatus is used to control the confining pressure change of the sample to realize loading under different drainage conditions and stress paths. To verify the effectiveness of the method, direct shear test and triaxial shear tests are carried out on the specimen composed of Fujian sand and steel structures with different roughness and different stress paths. The results show that at the beginning of sliding, the friction angle of the interface in the interfacial constant normal stress path is smaller than that in the conventional shear path. Under smooth conditions, the interface friction angle obtained by direct shear test is 30% to 40% lower than that obtained by triaxial test. Under rough conditions, the interface friction angle obtained by direct shear test is slightly smaller than that obtained by triaxial test, and closer to the friction angle in normal stress shear paths.
Integral steel platform formwork is widely used in the construction of super high-rise buildings, which brings a high degree of risk uncertainty to construction personnel. Therefore, it is crucial and necessary to establish a risk-based evacuation model for steel platform formwork in skyscraper construction. First, the spatial distribution of hazards sources on the steel platform is considered, hazardous areas are defined, and expert data are collected through survey questionnaires to assess the joint risk probability. Next, the joint risk probability of hazardous areas is coupled into the evacuation process based on the cellular automaton floor field model, and the evacuation process of construction personnel on the steel platform is simulated. Finally, the proposed risk-based evacuation simulation model is applied to an actual construction project. The results show that the influence of the top and lower hazardous areas on the evacuation process is significantly affected by the size of the exit. The model provides a new paradigm for experience-oriented construction safety management, with a theoretical and application value for the maintenance of the integral steel platform formwork system.
Bottom pivot bearing acts as the supporting and rotating component of the important water conservancy structure. The wear in the turning and closing operation is directly related to the normal operation and reliability of the gate. To directly monitor the wear of the bearing under severe deep water working conditions, a novel thin film resistive wear sensor was designed and constructed by using the micro-electro-mechanical-system (MEMS) micro-manufacturing technology. The wear measurement and characterization experiments were conducted. Besides, a wear test was simulated by computer simulation modeling. The relationship between the measured resistance and the wear parameters under different working conditions was specifically analyzed. The results show that the production and installation process of the sensor is feasible, and the experimental results are basically consistent with the simulation results. In the allowable range of working conditions, as the resistance increases, the accuracy of wear measurement increases. The sensor is expected to be applied in the intelligent monitoring of the herringbone gate of Dateng Gorge, and realize the Internet of things (IoT) and intelligent monitoring of the water conservancy projects in the 21st century.
In order to improve the life prediction effect of elevator brake in the real working environment, an unsupervised deep transfer learning (UDTL) method based on long short-term memory encoder-decoder (LSTM-ED) was proposed. The simulation data were used to analyze the health status of brake when it was working. First, the LSTM-ED and the fully connected network were initially trained through the source domain data. Then, the LSTM-ED was used as a feature extractor to map the simulated and actual data to the feature space, and the maximum mean discrepancy was adopted to achieve data alignment. Finally, the target domain data in the feature space was regressed through the fully connected network to predict the remaining useful life (RUL) of the real brake. In the training phase, a step-by-step training method was used to ensure the accuracy of a single module. The validity was verified by comparing the experimental simulation data with the real working data in the elevator tower. The results show that by introducing the transfer learning and step-by-step training methods, the proposed method can reduce the mean square error of RUL prediction to 0.0016, and can achieve accurate RUL prediction of elevator brakes in real working environment.
Aimed at the reconstruction problem of foreign large-scale warships, the spacing and minimum plate thickness of some profiles of large-scale warships are obtained by adopting the grey theory method and taking the data in the design code of warships as samples. Based on the advantages of the grey theory in dealing with small data and uncertainties, the grey models of different captains and their corresponding profile parameters are built and compared with the data of foreign large ships. The results show that the method has a high accuracy in calculating structural parameters with a strong correlation with the total longitudinal strength. The reason for the deviation in calculating structural parameters with local strength as the main consideration factor lies in the fact that the captain parameters as the reference for modeling are highly correlated with the total longitudinal strength. The magnitude of the deviation by calculating the grey relational degree between the structural parameters and the captain is described, and the results obtained are of engineering application value.
Aimed at the lack of effective stability evaluation methods for the current steam power system, an operation stability assessment method suitable for single parameter is proposed. This method is a composite method, which first applied the midpoint and regression based empirical mode decomposition (MREMD) and singular value decomposition (SVD) to decompose the time series of operation parameters and extract their hidden trend terms. Then, the components are selected for reconstruction according to the optimal algorithm parameter permutation entropy (OAPPE) of each component. Finally, the auto-regressive integrated moving average (ARIMA ) model commonly used in the non-stationary time series analysis is utilized to predict the trend and the disturbance of parameters, and their distribution characteristics are also extracted in this process, based on which, the probability of instability (PI) of operation parameters at each point on the predicted trend are calculated, and their stabilities are quantitatively evaluated. The actual case proves that this method can effectively assess the operation stability of a single parameter of the steam power system, which has a certain theoretical innovation and engineering application value.
The release of compressive stress and atom diffusion have important influences on the growth of whiskers in 3D electronic packaging, and the compressive stress is also one of the main factors for dynamic recrystallization (DRX). By using the mathematical model of growth mechanism and the behavior of tin whisker based on the finite element method, the process of forming whiskers on silicon substrate by 3D electronic packaging tin layer with a typical physical size and structure was simulated. The qualitative analysis and growth of whiskers were realized. By controlling the key parameters such as gas pressure, thermal cycling temperature, and cycle of Ar in the background of the experiment, the external factors and plating process were constructed. The experimental system of accelerated test of internal pressure stress and whisker growth speed, length, and density in the film was constructed. The growth rate and density of whiskers were observed and detected by SEM. The effectiveness of the mathematical model of stress release, atom diffusion, and DRX in 3D electronic packaging tin whiskers was verified by SEM. The quantitative description of whiskers was realized, providing constructive suggestions for reducing whisker problems in future 3D packaging microstructure graphic design.
The band structure properties of phononic crystal is important to evaluate the vibration and noise reduction of acoustic metamaterials. Taking the 2D hexachiral phononic crystal as an example, the band structure and Dirac cone properties were investigated by numerical analysis, and the four-fold accidental degenerate Dirac point was obtained in the center of Brillouin zone. By adjusting the design parameters of ligament structure, a double Dirac cone was broken and a novel directional band gap was formed. The influence of geometric parameters on the directional band gaps width was investigated, and the band structure inversion problem was further discussed. This research can provide support for the application of hexachiral phononic crystal in elastic wave manipulation and acoustic topological insulator.
Carbon fiber-reinforced epoxy composites are widely used in the primary structure of aircraft, the compressive strength of which after impact is an important part in the evaluation of damage tolerance. At present, it mainly relies on a large number of tests to obtain compressive strength after impact in the engineering project. Therefore, it is necessary to develop a simple mathematical model to describe the compressive strength law after impact. A novel mathematical model for fitting compressive strength data of composite laminate after impact was proposed. Using the mathematical model and the initial model parameters, the compressive strength data after impact at different impact energy could be converted into some equivalent undamaged compressive strength data. Then, these equivalent undamaged compressive strength data were normally fitted using the maximum-likelihood estimate (MLE) method to obtain the standard deviation of normal distribution. The above steps was repeated until the minimum estimator of standard deviation was obtained. Hence, the best estimators of parameters for the mathematical model were determined. In order to further demonstrate the applicability of the mathematical model, post-impact compressive strength tests including different thicknesses, layup proportion, and material types were conducted, and the experimental data were fitted with the model. The results indicate that the mathematical model has a good applicability to the compressive strength test data after impact including different thicknesses, layup proportions, and material types.
To solve the problems of alignment for launch container loading in field-artillery rocket, a novel end-effector, i.e., a swing-compliant hook, is proposed, whose structural parameters are optimized. First, the theoretical model describing the performance of the swing-compliant hook is established based on the node displacement method. The static displacement, static stress, and swing curve of the swing-compliant hook are analyzed by MATLAB, which verifies the rationality of the model. Then, the main structure parameters on the performance of the swing-compliant hook are obtained by using the experimental design method. Additionally, a response surface model characterizing the comprehensive performance of the swing-compliant hook is established. The optimization results show that when the length and the installation height of the compliant mechanism are 90 mm and 23 mm, and the end height of the lifting hook is 110 mm, the swing-compliant hook has an excellent performance in docking, lifting, transferring, and locating.
The mechanical behavior of the quenching and partitioning 980 (QP980) steel is affected by martensitic transformation during deformation. The microstructure of QP980 steel before and after deformation is characterized by using the electron backscattered diffraction (EBSD) method. An elastic visco-plastic self-consistent (EVPSC) polycrystalline model considering phase transformation is established based on the phenomenological theory of martensite crystallography (PTMC). The macroscopic flow stress as well as texture evolution of QP980 steel during uniaxial tension process is reproduced by the model. The material consists of ferrite (F), martensite, and retained austenite (RA) with rolling texture in the initial state. After deformation, the content of RA decreases and the <111> fiber of the RA, the <110> fiber of the ferrite and martensite along the tensile direction are enhanced. Phase transformation enhances the strength and work hardening rate but has little effect on the texture evolution. According to the distribution of stress and strain during the calculation of deformation, ferrite and tempered martensite (TM) contribute most to the deformation, and the new martensite (NM) is the most probable nucleation sites of fracture due to its highest average stress.
In order to develop a new lightweight enclosure structure with an excellent fireproof and bearing performance, and to replace the traditional stiffened fire enclosure bulkheads in the superstructure area, a design method of light fireproof enclosure bulkheads for cruise ship based on the topography optimization technology was proposed. The location and numbers of corrugated beads in lightweight wall designed by this method were generated according to the requirements of load bearing capacity and manufacturing process, and this method overcomes the disadvantages that the location and numbers of beads in the design of conventional corrugated wall have to be determined in advance. Aimed at the specified design regions, the lightweight of cruise fireproof enclosure bulkheads (CFEB) structure was taken as the objective function while the stress in the weld zone, the stress in the nonweld zone, and the first-order buckling factor of CFEB were taken as constraints. Then, the topography design models of CFEB were established and solved. Feasible configurations were obtained by topography optimization, and the final configurations of CFEB were formed by secondary design. The mechanical properties of the final configurations were compared with the traditional stiffened fireproof bulkheads. It is concluded that the new CFEB has advantages of lightweight and good strength compared with the traditional stiffened fireproof bulkheads.
This paper analyzes the characteristics and influences of new pulse loads of ships. The surge-suppression power supply system for high power and multi-mode pulse loads, the capacitance and inductance calculation methods for the energy buffer unit are proposed, which can realize the power suppression, energy grouping, harmonic control and support backup, so that the safety of the ship power station and high precision power supply for loads can be ensured. The integrated power system simulation model of a new survey ship with high power radar loads is established in MATLAB/Simulink to verify the effectiveness of the surge-suppression power supply system at different modes. The system can not only reduce the impact of impulse load on the system, but also effectively suppress the system voltage harmonics, thus solving the key technical difficulties in the application of high power pulse loads to the independent power system.
The wireless powered intestinal robot transmits the intestinal images taken by the image acquisition system to the external upper computer for diagnosis. However, the image transmission process will be interfered by the circuit structure and external environment, leading to noise in the collected images. Therefore, an image denoising algorithm based on non-subsampled contourlet transform (NSCT) is proposed to reduce the noise of the images collected by intestinal robots. First, histogram equalization pretreatment is adopted to improve the brightness and contrast of intestinal noise images. Next, NSCT transformation is performed on intestinal noise images and a residual network model is constructed to reduce the noise of frequency domain information after transformation. Finally, the denoised image is reconstructed by NSCT inverse transformation. The results show that the proposed algorithm can effectively reduce the influence of intestinal noise in complex environments, and better maintain the visual effect of the image. Compared with other intelligent algorithm models, both subjective and objective noise reduction effects are improved, with peak signal to noise ratio (PSNR) improved by 1.35 to 3.45 dB and structural similarity index measure (SSIM) improved by 0.0083 to 0.0252.
Special collection of 12 issues of "Journal of Shanghai Jiaotong University" in 2021 
