The classical Gauss-Jordan method for matrix inversion involves augmenting the matrix with a unit matrix and requires a workspace twice as large as the original matrix as well as computational operations to be perform...The classical Gauss-Jordan method for matrix inversion involves augmenting the matrix with a unit matrix and requires a workspace twice as large as the original matrix as well as computational operations to be performed on both the original and the unit matrix. A modified version of the method for performing the inversion without explicitly generating the unit matrix by replicating its functionality within the original matrix space for more efficient utilization of computational resources is presented in this article. Although the algorithm described here picks the pivots solely from the diagonal which, therefore, may not contain a zero, it did not pose any problem for the author because he used it to invert structural stiffness matrices which met this requirement. Techniques such as row/column swapping to handle off-diagonal pivots are also applicable to this method but are beyond the scope of this article.展开更多
Starting from an index mapping for one to multi-dimensions, a general in-placeand in-order prime factor FFT algorithm is proposed in this paper. In comparing with existingprime factor FFT algorithms, this algorithm sa...Starting from an index mapping for one to multi-dimensions, a general in-placeand in-order prime factor FFT algorithm is proposed in this paper. In comparing with existingprime factor FFT algorithms, this algorithm saves about half of the required storage capacityand possesses a higher efficiency. In addition, this algorithm can easily implement the DFT andIDFT in a single subroutine,展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
We study the split common solution problem with multiple output sets for monotone operator equations in Hilbert spaces.To solve this problem,we propose two new parallel algorithms.We establish a weak convergence theor...We study the split common solution problem with multiple output sets for monotone operator equations in Hilbert spaces.To solve this problem,we propose two new parallel algorithms.We establish a weak convergence theorem for the first and a strong convergence theorem for the second.展开更多
This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in ...This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.展开更多
This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the compl...This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.展开更多
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious an...Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.展开更多
In order to solve for temperature fields in microwave heating for recycling asphalt mixtures, a two-dimensional heat transfer model for the asphalt mixtures within the heating range is built based on the theory of uns...In order to solve for temperature fields in microwave heating for recycling asphalt mixtures, a two-dimensional heat transfer model for the asphalt mixtures within the heating range is built based on the theory of unsteady heat conduction. Four onedimensional heat transfer models are established for the asphalt mixtures outside the heating range, which are simplified into four half-infinite solids. The intensity of the radiation electric field is calculated through experiment by using heating water loads. It is suggested that the mathematical model of boundary conditions can be established in two ways, which are theoretical deduction and experimental reverse. The actual temperature field is achieved by fitting temperatures of different positions collected in the heating experiment. The simulant temperature field, which is solved with the Matlab PDE toolbox, is in good agreement with the actual temperature field. The results indicate that the proposed models have high precision and can be directly used to calculate the temperature distribution of asphalt pavements.展开更多
Asphalt mixture pavement reheating is one of the important steps in hot in-place recycling(HIR).To improve the heating speed of asphalt pavement in HIR,based on the numerical analysis model of asphalt mixture heating ...Asphalt mixture pavement reheating is one of the important steps in hot in-place recycling(HIR).To improve the heating speed of asphalt pavement in HIR,based on the numerical analysis model of asphalt mixture heating process,a new multi-layer low-temperature heating method(MLHM)was proposed.Considering input heat flux,the thermal capacity and thermal resistance of asphalt mixture,the heat transfer model was established based on energy conservation law.By heating the asphalt mixture in layers,it changes the situation that the heat energy can only be input from the upper surface of the asphalt mixture pavement.Through the simulation of the heating method of asphalt mixture in the existing technology,the result shows that the existing heating methods lead to serious aging or charring of the asphalt mixture.By MLHM,the upper and the bottom of the asphalt mixture are heated at the same time,and the heating temperature is lower than other heat methods,which not only reduces the heating thickness and increases the heating area of the asphalt mixture pavement,but also improves the heating speed,saves the energy resource and ensures the heating quality.Especially,by MLHM,the heating uniformity is better and speed is faster.展开更多
In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to co...In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to control the DOC using conventional controllers because of the poorly understood and constantly changing dynamics of the bioprocess. A generalized predictive controller (GPC) based on a nonlinear autoregressive integrated moving average exogenous (NARIMAX) model is presented to stabilize the DOC by manipulation of air flow rate. The NARIMAX model is built by an improved recursive least-squares support vector machine, which is trained by an in-place computation scheme and avoids the computation of the inverse of a large matrix and memory reallocation. The proposed nonlinear GPC algorithm requires little preliminary knowledge of the fermentation process, and directly obtains the nonlinear model in matrix form by using iterative multiple modeling instead of linearization at each sampling period. By application of an on-line bioreactor control, experimental results demonstrate the robustness, effectiveness and advantages of the new controller.展开更多
For lack of laboratory and field performance data on stabilization of reclaimed asphalt pavement （RAP） aggregate and stabilized soil （S） for road bases and subbases construction, the influences of RAP/S ratio, cem...For lack of laboratory and field performance data on stabilization of reclaimed asphalt pavement （RAP） aggregate and stabilized soil （S） for road bases and subbases construction, the influences of RAP/S ratio, cement and fly ash content, modifying agent （MA） on the compact, unconfined compressive strength, indirect tensile strength and water stability of the CIR mixtures were investigated. The experimental results showed that the maximum dry density and the optimum moisture content of the mixture changed significantly with the RAP/S ratio and cement-fly ash content. Unconfined compressive strength, indirect tensile strength and water stability were improved significantly by the addition of MA, and the water stability was improved by nearly 20% on average. Scanning electron microscopy（SEM） images indicated that MA accelerated the hydration of cement-fly ash system. Needle-like AFt and fibrous C-S-H gel were observed in the mixtures, which resulted in the cementation effect among the CIR mixture particles and a more compact microstructure. All these could be the cause of high strength of the CIR mixtures with MA.展开更多
This paper presents some insights on the state-of-the-art practice that has been utilized recently in the inplace structural strength and fatigue analysis for topsides on deepwater floating platforms such as tension l...This paper presents some insights on the state-of-the-art practice that has been utilized recently in the inplace structural strength and fatigue analysis for topsides on deepwater floating platforms such as tension leg plat-form (TLP) and semi-submersibles. Emphases are put on analysis software,geometric and mass modeling,hydro-dynamic loading and its mapping,and analysis procedures. In addition,for the in-place analysis using structure analysis computer system (SACS),the procedure of Visual Basic for Application (VBA) is developed to map AQWA-LINE hydrodynamic loading to the SACS integrated hull/topsides model;for the in-place analysis using structure engineering system analysis model (SESAM),many computer aided applications are made to aid the post-processing. These applications have been used in structural analyses for a few TLP and semi-submersible plat-form topsides,and are briefly introduced in this paper.展开更多
A new research method was proposed（A/S method） to study the components and properties of reclained asphalt mixture（RAP）. The RAP was divided into two main parts, one was marked with A that included all the reclaim...A new research method was proposed（A/S method） to study the components and properties of reclained asphalt mixture（RAP）. The RAP was divided into two main parts, one was marked with A that included all the reclaimed old asphalt materials（including some parts of particle materials covered by asphalt）, the other was marked with S which mainly included works soil in the road structure. The actual working conditions were simulated by this kind of new method, and the adaption between the RAP properties, A/S, and the content of cementitious materials were studied. The research indicated that the real working condition could be simulated effectively by means of A/S method. It was also showed that high content of cement could improve the overall performance of RAP significantly, but it would have a negative effect on the properties of RAP if the types and sizes of aggregate particles in RAP mixture were too single. The optimum water content and maximum dry density could not be regarded as the primary basis to evaluate the overall performance of RAP, when S=0 in the experiments, although the maximum density of samples was bigger than that with A/S=1/1, the samples were not strong enough and they were easy to collapse, which indicated that component design of RAP played a great role in improving the overall properties of RAP and the comprehensive tests should be considered to evaluate the stability of RAP. Low frequency load in high temperature environment had the negative effect on the overall stability of RAP, and factors such as the loading state of the materials, the hydration degree of cementitious materials, and the aggregate gradation in the mixture were the determining factors for improving the overall performance of RAP.展开更多
A modified version of the Gauss-Jordan algorithm for performing In-Place matrix inversion without using an augmenting unit matrix was described in a previous article by the author. He had also developed several Struct...A modified version of the Gauss-Jordan algorithm for performing In-Place matrix inversion without using an augmenting unit matrix was described in a previous article by the author. He had also developed several Structural Engineering softwares during his career using that method as their analysis engine. He chose matrix inversion because it was suitable for in-core solution of large numbers of vectors for the same set of equations as encountered in structural analysis of moving, dynamic and seismic loadings. The purpose of this article is to provide its readers with its theoretical background and detailed computations of an In-Place matrix inversion task as well as a Visual Basic routine of the algorithm for direct incorporation into Visual Basic 6TM softwares and Visual Basic for ApplicationsTM macros in MS-ExcelTM spreadsheets to save them time and effort of software development.展开更多
Pavement rehabilitation and reconstruction methods with CIR （cold in-place recycling） are alternatives that can effectively reduce the high stresses and waste produced by conventional pavement strategies. An attempt...Pavement rehabilitation and reconstruction methods with CIR （cold in-place recycling） are alternatives that can effectively reduce the high stresses and waste produced by conventional pavement strategies. An attempt was made to predict the performance, particularly low-temperature cracking resistance characteristics of CIR mixtures. These were prepared with the mix design procedure developed at the URI （University of Rhode Island） for the FHWA （Federal Highway Administration） to reduce wide variations in the application of CIR mixtures production. This standard was applied to RAP （reclaimed asphalt pavement） to produce CIR mixtures with CSS-Ih asphalt emulsion as the additive. By adjusting the number of gyrations of the SGC （Superpave gyratory compactor） for compaction, the field density of 130 pcf was represented accurately. To secure a base line, HMA （hot mix asphalt） samples were produced according to the Superpave volumetric mix design procedure. The specimens were tested using the IDT （indirect tensile） tester according to the procedure of AASHTO T 322 procedure at temperatures of-20, -10 and 0 ℃ （-4, 14, and 32°F, respectively）. The obtained results for the creep compliance and tensile strength were used as input data for the MEPDG （mechanistic empirical pavement design guide）. The analysis results indicated that no thermal or low-temperature cracking is expected over the entire analysis period of 20 years for both HMA and CIR mixtures. Thus, it appears that CIR is a sustainable rehabilitation technique which is also suitable for colder climates, and it is recommended to conduct further investigation of load-related distresses such as rutting and fatigue cracking.展开更多
Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently...Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.展开更多
Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,th...Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.展开更多
文摘The classical Gauss-Jordan method for matrix inversion involves augmenting the matrix with a unit matrix and requires a workspace twice as large as the original matrix as well as computational operations to be performed on both the original and the unit matrix. A modified version of the method for performing the inversion without explicitly generating the unit matrix by replicating its functionality within the original matrix space for more efficient utilization of computational resources is presented in this article. Although the algorithm described here picks the pivots solely from the diagonal which, therefore, may not contain a zero, it did not pose any problem for the author because he used it to invert structural stiffness matrices which met this requirement. Techniques such as row/column swapping to handle off-diagonal pivots are also applicable to this method but are beyond the scope of this article.
基金Supported by the National Natural Science Foundation of China
文摘Starting from an index mapping for one to multi-dimensions, a general in-placeand in-order prime factor FFT algorithm is proposed in this paper. In comparing with existingprime factor FFT algorithms, this algorithm saves about half of the required storage capacityand possesses a higher efficiency. In addition, this algorithm can easily implement the DFT andIDFT in a single subroutine,
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金supported by the Science and Technology Fund of TNU-Thai Nguyen University of Science.
文摘We study the split common solution problem with multiple output sets for monotone operator equations in Hilbert spaces.To solve this problem,we propose two new parallel algorithms.We establish a weak convergence theorem for the first and a strong convergence theorem for the second.
基金supported by the P.G.Senapathy Center for Computing Resources at IIT Madrasfunding provided by the Ministry of Education,Government of Indiasupported by the National Natural Science Foundation of China(Grant Nos.12388101,12472224 and 92252104).
文摘This paper presents an Eulerian-Lagrangian algorithm for direct numerical simulation(DNS)of particle-laden flows.The algorithm is applicable to perform simulations of dilute suspensions of small inertial particles in turbulent carrier flow.The Eulerian framework numerically resolves turbulent carrier flow using a parallelized,finite-volume DNS solver on a staggered Cartesian grid.Particles are tracked using a point-particle method utilizing a Lagrangian particle tracking(LPT)algorithm.The proposed Eulerian-Lagrangian algorithm is validated using an inertial particle-laden turbulent channel flow for different Stokes number cases.The particle concentration profiles and higher-order statistics of the carrier and dispersed phases agree well with the benchmark results.We investigated the effect of fluid velocity interpolation and numerical integration schemes of particle tracking algorithms on particle dispersion statistics.The suitability of fluid velocity interpolation schemes for predicting the particle dispersion statistics is discussed in the framework of the particle tracking algorithm coupled to the finite-volume solver.In addition,we present parallelization strategies implemented in the algorithm and evaluate their parallel performance.
基金supported by the Research Project of China Southern Power Grid(No.056200KK52222031).
文摘This paper proposes an equivalent modeling method for photovoltaic(PV)power stations via a particle swarm optimization(PSO)K-means clustering(KMC)algorithm with passive filter parameter clustering to address the complexities,simulation time cost and convergence problems of detailed PV power station models.First,the amplitude–frequency curves of different filter parameters are analyzed.Based on the results,a grouping parameter set for characterizing the external filter characteristics is established.These parameters are further defined as clustering parameters.A single PV inverter model is then established as a prerequisite foundation.The proposed equivalent method combines the global search capability of PSO with the rapid convergence of KMC,effectively overcoming the tendency of KMC to become trapped in local optima.This approach enhances both clustering accuracy and numerical stability when determining equivalence for PV inverter units.Using the proposed clustering method,both a detailed PV power station model and an equivalent model are developed and compared.Simulation and hardwarein-loop(HIL)results based on the equivalent model verify that the equivalent method accurately represents the dynamic characteristics of PVpower stations and adapts well to different operating conditions.The proposed equivalent modeling method provides an effective analysis tool for future renewable energy integration research.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金the National Key Research and Development Program of China (Grant No.2022YFF0711400)the National Space Science Data Center Youth Open Project (Grant No. NSSDC2302001)
文摘Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.
基金The Key Project of Science and Technology of Ministryof Education (No.105085)the Specialized Research Fund of Science andTechnology Production Translation of Jiangsu Province (No.BA2006068).
文摘In order to solve for temperature fields in microwave heating for recycling asphalt mixtures, a two-dimensional heat transfer model for the asphalt mixtures within the heating range is built based on the theory of unsteady heat conduction. Four onedimensional heat transfer models are established for the asphalt mixtures outside the heating range, which are simplified into four half-infinite solids. The intensity of the radiation electric field is calculated through experiment by using heating water loads. It is suggested that the mathematical model of boundary conditions can be established in two ways, which are theoretical deduction and experimental reverse. The actual temperature field is achieved by fitting temperatures of different positions collected in the heating experiment. The simulant temperature field, which is solved with the Matlab PDE toolbox, is in good agreement with the actual temperature field. The results indicate that the proposed models have high precision and can be directly used to calculate the temperature distribution of asphalt pavements.
基金Project(2017JM5077)supported by the Natural Science Basic Research Plan in Shaanxi Province,ChinaProjects(300102259109,300102259306)supported by the Fundamental Research Funds for the Central Universities,China。
文摘Asphalt mixture pavement reheating is one of the important steps in hot in-place recycling(HIR).To improve the heating speed of asphalt pavement in HIR,based on the numerical analysis model of asphalt mixture heating process,a new multi-layer low-temperature heating method(MLHM)was proposed.Considering input heat flux,the thermal capacity and thermal resistance of asphalt mixture,the heat transfer model was established based on energy conservation law.By heating the asphalt mixture in layers,it changes the situation that the heat energy can only be input from the upper surface of the asphalt mixture pavement.Through the simulation of the heating method of asphalt mixture in the existing technology,the result shows that the existing heating methods lead to serious aging or charring of the asphalt mixture.By MLHM,the upper and the bottom of the asphalt mixture are heated at the same time,and the heating temperature is lower than other heat methods,which not only reduces the heating thickness and increases the heating area of the asphalt mixture pavement,but also improves the heating speed,saves the energy resource and ensures the heating quality.Especially,by MLHM,the heating uniformity is better and speed is faster.
基金Supported by the National Natural Science Foundation of China (20476007, 20676013)
文摘In this study, Saccharomyces cerevisiae (baker's yeast) was produced in a fed-batch bioreactor at the optimal dissolved oxygen concentration (DOC) and growth medium temperature. However, it is very difficult to control the DOC using conventional controllers because of the poorly understood and constantly changing dynamics of the bioprocess. A generalized predictive controller (GPC) based on a nonlinear autoregressive integrated moving average exogenous (NARIMAX) model is presented to stabilize the DOC by manipulation of air flow rate. The NARIMAX model is built by an improved recursive least-squares support vector machine, which is trained by an in-place computation scheme and avoids the computation of the inverse of a large matrix and memory reallocation. The proposed nonlinear GPC algorithm requires little preliminary knowledge of the fermentation process, and directly obtains the nonlinear model in matrix form by using iterative multiple modeling instead of linearization at each sampling period. By application of an on-line bioreactor control, experimental results demonstrate the robustness, effectiveness and advantages of the new controller.
基金Funded by the High-Tech Research and Development Program (863 National Program) of China(No.2009AA11Z106)
文摘For lack of laboratory and field performance data on stabilization of reclaimed asphalt pavement （RAP） aggregate and stabilized soil （S） for road bases and subbases construction, the influences of RAP/S ratio, cement and fly ash content, modifying agent （MA） on the compact, unconfined compressive strength, indirect tensile strength and water stability of the CIR mixtures were investigated. The experimental results showed that the maximum dry density and the optimum moisture content of the mixture changed significantly with the RAP/S ratio and cement-fly ash content. Unconfined compressive strength, indirect tensile strength and water stability were improved significantly by the addition of MA, and the water stability was improved by nearly 20% on average. Scanning electron microscopy（SEM） images indicated that MA accelerated the hydration of cement-fly ash system. Needle-like AFt and fibrous C-S-H gel were observed in the mixtures, which resulted in the cementation effect among the CIR mixture particles and a more compact microstructure. All these could be the cause of high strength of the CIR mixtures with MA.
文摘This paper presents some insights on the state-of-the-art practice that has been utilized recently in the inplace structural strength and fatigue analysis for topsides on deepwater floating platforms such as tension leg plat-form (TLP) and semi-submersibles. Emphases are put on analysis software,geometric and mass modeling,hydro-dynamic loading and its mapping,and analysis procedures. In addition,for the in-place analysis using structure analysis computer system (SACS),the procedure of Visual Basic for Application (VBA) is developed to map AQWA-LINE hydrodynamic loading to the SACS integrated hull/topsides model;for the in-place analysis using structure engineering system analysis model (SESAM),many computer aided applications are made to aid the post-processing. These applications have been used in structural analyses for a few TLP and semi-submersible plat-form topsides,and are briefly introduced in this paper.
基金Funded by the Natural Science Foundation of Fujian Province(Nos.2016J01241 and 2016H0021)the Science & Technology Pillar Program of Fujian Provincial Education Department(No.Z1425072)
文摘A new research method was proposed（A/S method） to study the components and properties of reclained asphalt mixture（RAP）. The RAP was divided into two main parts, one was marked with A that included all the reclaimed old asphalt materials（including some parts of particle materials covered by asphalt）, the other was marked with S which mainly included works soil in the road structure. The actual working conditions were simulated by this kind of new method, and the adaption between the RAP properties, A/S, and the content of cementitious materials were studied. The research indicated that the real working condition could be simulated effectively by means of A/S method. It was also showed that high content of cement could improve the overall performance of RAP significantly, but it would have a negative effect on the properties of RAP if the types and sizes of aggregate particles in RAP mixture were too single. The optimum water content and maximum dry density could not be regarded as the primary basis to evaluate the overall performance of RAP, when S=0 in the experiments, although the maximum density of samples was bigger than that with A/S=1/1, the samples were not strong enough and they were easy to collapse, which indicated that component design of RAP played a great role in improving the overall properties of RAP and the comprehensive tests should be considered to evaluate the stability of RAP. Low frequency load in high temperature environment had the negative effect on the overall stability of RAP, and factors such as the loading state of the materials, the hydration degree of cementitious materials, and the aggregate gradation in the mixture were the determining factors for improving the overall performance of RAP.
文摘A modified version of the Gauss-Jordan algorithm for performing In-Place matrix inversion without using an augmenting unit matrix was described in a previous article by the author. He had also developed several Structural Engineering softwares during his career using that method as their analysis engine. He chose matrix inversion because it was suitable for in-core solution of large numbers of vectors for the same set of equations as encountered in structural analysis of moving, dynamic and seismic loadings. The purpose of this article is to provide its readers with its theoretical background and detailed computations of an In-Place matrix inversion task as well as a Visual Basic routine of the algorithm for direct incorporation into Visual Basic 6TM softwares and Visual Basic for ApplicationsTM macros in MS-ExcelTM spreadsheets to save them time and effort of software development.
文摘Pavement rehabilitation and reconstruction methods with CIR （cold in-place recycling） are alternatives that can effectively reduce the high stresses and waste produced by conventional pavement strategies. An attempt was made to predict the performance, particularly low-temperature cracking resistance characteristics of CIR mixtures. These were prepared with the mix design procedure developed at the URI （University of Rhode Island） for the FHWA （Federal Highway Administration） to reduce wide variations in the application of CIR mixtures production. This standard was applied to RAP （reclaimed asphalt pavement） to produce CIR mixtures with CSS-Ih asphalt emulsion as the additive. By adjusting the number of gyrations of the SGC （Superpave gyratory compactor） for compaction, the field density of 130 pcf was represented accurately. To secure a base line, HMA （hot mix asphalt） samples were produced according to the Superpave volumetric mix design procedure. The specimens were tested using the IDT （indirect tensile） tester according to the procedure of AASHTO T 322 procedure at temperatures of-20, -10 and 0 ℃ （-4, 14, and 32°F, respectively）. The obtained results for the creep compliance and tensile strength were used as input data for the MEPDG （mechanistic empirical pavement design guide）. The analysis results indicated that no thermal or low-temperature cracking is expected over the entire analysis period of 20 years for both HMA and CIR mixtures. Thus, it appears that CIR is a sustainable rehabilitation technique which is also suitable for colder climates, and it is recommended to conduct further investigation of load-related distresses such as rutting and fatigue cracking.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
基金National Natural Science Foundation of China(11971211,12171388).
文摘Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.
基金supported by Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443)National Natural Science Foundation of China(62263014,52207105)+1 种基金Yunnan Lancang-Mekong International Electric Power Technology Joint Laboratory(202203AP140001)Major Science and Technology Projects in Yunnan Province(202402AG050006).
文摘Accurate short-term wind power forecast technique plays a crucial role in maintaining the safety and economic efficiency of smart grids.Although numerous studies have employed various methods to forecast wind power,there remains a research gap in leveraging swarm intelligence algorithms to optimize the hyperparameters of the Transformer model for wind power prediction.To improve the accuracy of short-term wind power forecast,this paper proposes a hybrid short-term wind power forecast approach named STL-IAOA-iTransformer,which is based on seasonal and trend decomposition using LOESS(STL)and iTransformer model optimized by improved arithmetic optimization algorithm(IAOA).First,to fully extract the power data features,STL is used to decompose the original data into components with less redundant information.The extracted components as well as the weather data are then input into iTransformer for short-term wind power forecast.The final predicted short-term wind power curve is obtained by combining the predicted components.To improve the model accuracy,IAOA is employed to optimize the hyperparameters of iTransformer.The proposed approach is validated using real-generation data from different seasons and different power stations inNorthwest China,and ablation experiments have been conducted.Furthermore,to validate the superiority of the proposed approach under different wind characteristics,real power generation data fromsouthwestChina are utilized for experiments.Thecomparative results with the other six state-of-the-art prediction models in experiments show that the proposed model well fits the true value of generation series and achieves high prediction accuracy.
