Hybrid model for BOF oxygen blowing time prediction based on oxygen balance mechanism and deep neural network

The amount of oxygen blown into the converter is one of the key parameters for the control of the converter blowing process,which directly affects the tap-to-tap time of converter. In this study, a hybrid model based on oxygen balance mechanism (OBM) and deep neural network (DNN) was established for predicting oxygen blowing time in converter. A three-step method was utilized in the hybrid model. First, the oxygen consumption volume was predicted by the OBM model and DNN model, respectively. Second, a more accurate oxygen consumption volume was obtained by integrating the OBM model and DNN model. Finally, the converter oxygen blowing time was calculated according to the oxygen consumption volume and the oxygen supply intensity of each heat. The proposed hybrid model was verified using the actual data collected from an integrated steel plant in China, and compared with multiple linear regression model, OBM model, and neural network model including extreme learning machine, back propagation neural network, and DNN. The test results indicate that the hybrid model with a network structure of 3 hidden layer layers, 32-16-8 neurons per hidden layer, and 0.1 learning rate has the best prediction accuracy and stronger generalization ability compared with other models. The predicted hit ratio of oxygen consumption volume within the error±300 m^(3)is 96.67%;determination coefficient (R^(2)) and root mean square error (RMSE) are0.6984 and 150.03 m^(3), respectively. The oxygen blow time prediction hit ratio within the error±0.6 min is 89.50%;R2and RMSE are0.9486 and 0.3592 min, respectively. As a result, the proposed model can effectively predict the oxygen consumption volume and oxygen blowing time in the converter.

HybridGAD: Identification of AI-Generated Radiology Abstracts Based on a Novel Hybrid Model with Attention Mechanism

Class Title:Radiological imaging method a comprehensive overview purpose.This GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent advances in the field.Materials and Methods:This paper provides an overview of conventional radiography digital radiography panoramic radiography computed tomography and cone-beam computed tomography.Additionally recent advances in radiological imaging are discussed such as imaging diagnosis and modern computer-aided diagnosis systems.Results:This paper details the differences between the imaging techniques the benefits of each and the current advances in the field to aid in the diagnosis of medical conditions.Conclusion:Radiological imaging is an extremely important tool in modern medicine to assist in medical diagnosis.This work provides an overview of the types of imaging techniques used the recent advances made and their potential applications.

Microstructure homogeneity and mechanical properties of laser-arc hybrid welded AZ31B magnesium alloy

Laser-arc hybrid welding of AZ31B magnesium alloy was carried out,the effects of welding parameters on weld formation,microstructure homogeneity and mechanical properties were investigated.The results showed that laser-arc hybrid welding was beneficial to improve the weld formation of magnesium alloy by inhibiting the defect of undercut and pores.The weld microstructure was mainly columnar grains neighboring the fusion line and equiaxed grains at the weld center.It was interesting that the grain size at the upper arc zone was smaller than that at the lower laser zone,with the difference mainly affected by laser power rather than welding current and welding speed.The welding parameters were optimized as laser power of 3.5 kW,welding current of 100 A and welding speed of 1.5 m/min.In this case,the weld was free of undercut and pores,and the tensile strength and elongation rate reached 252 MPa and 11.2%,respectively.Finally,the microstructure homogeneity was illustrated according to the heat distribution,and the evolution law of tensile properties was discussed basing on the weld formation and microstructure characteristics.

Effect of Heat Treatment on Microstructure and Mechanical Properties of Multiscale SiC_p Hybrid Reinforced 6061 Aluminum Matrix Composites

The performance of solid solution aging treatment on aluminum matrix composites prepared by powder metallurgy and reinforced with 6061 aluminum alloy powder as matrix;meanwhile, nano silicon carbide particles(nm Si Cp), submicron silicon carbide particles(1 μm Si Cp) and Ti particles were studied. The Al/Si Cp composite powder was prepared by high-energy ball milling, and then cold-pressed, sintered, hotextruded, and then heat-treated with different solution temperatures and aging times for the extruded composites. Optical microscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy(EDS), X-ray diffractometer(XRD) and extrusion testing were used to analyze and test the microstructure and mechanical properties of aluminum matrix composites. The results show that after the multi-stage solid solution at 530 ℃×2 h+535 ℃×2 h+540 ℃×2 h, the particles are mainly equiaxed grains and uniformly distributed. There is no reinforcement agglomeration, and the surface is dense and the insoluble phase is basically dissolved. In the matrix, the strengthening effect is good, and the hardness and compressive strength are 179.43 HV and 680.42 MPa, respectively. Under this solution process, when the aluminum matrix composites are aged at 170 ℃ for 10 h, the hardness and compressive strength can reach their peaks and increase to 195.82 HV and 721.48 MPa, respectively.

An 8-Node Plane Hybrid Element for StructuralMechanics Problems Based on the Hellinger-Reissner Variational Principle

The finite element method (FEM) plays a valuable role in computer modeling and is beneficial to the mechanicaldesign of various structural parts. However, the elements produced by conventional FEM are easily inaccurate andunstable when applied. Therefore, developing new elements within the framework of the generalized variationalprinciple is of great significance. In this paper, an 8-node plane hybrid finite element with 15 parameters (PHQ8-15β) is developed for structural mechanics problems based on the Hellinger-Reissner variational principle.According to the design principle of Pian, 15 unknown parameters are adopted in the selection of stress modes toavoid the zero energy modes.Meanwhile, the stress functions within each element satisfy both the equilibrium andthe compatibility relations of plane stress problems. Subsequently, numerical examples are presented to illustrate theeffectiveness and robustness of the proposed finite element. Numerical results show that various common lockingbehaviors of plane elements can be overcome. The PH-Q8-15β element has excellent performance in all benchmarkproblems, especially for structures with varying cross sections. Furthermore, in bending problems, the reasonablemesh shape of the new element for curved edge structures is analyzed in detail, which can be a useful means toimprove numerical accuracy.

Short-Term Household Load Forecasting Based on Attention Mechanism and CNN-ICPSO-LSTM

Accurate load forecasting forms a crucial foundation for implementing household demand response plans andoptimizing load scheduling. When dealing with short-term load data characterized by substantial fluctuations,a single prediction model is hard to capture temporal features effectively, resulting in diminished predictionaccuracy. In this study, a hybrid deep learning framework that integrates attention mechanism, convolution neuralnetwork (CNN), improved chaotic particle swarm optimization (ICPSO), and long short-term memory (LSTM), isproposed for short-term household load forecasting. Firstly, the CNN model is employed to extract features fromthe original data, enhancing the quality of data features. Subsequently, the moving average method is used for datapreprocessing, followed by the application of the LSTM network to predict the processed data. Moreover, the ICPSOalgorithm is introduced to optimize the parameters of LSTM, aimed at boosting the model’s running speed andaccuracy. Finally, the attention mechanism is employed to optimize the output value of LSTM, effectively addressinginformation loss in LSTM induced by lengthy sequences and further elevating prediction accuracy. According tothe numerical analysis, the accuracy and effectiveness of the proposed hybrid model have been verified. It canexplore data features adeptly, achieving superior prediction accuracy compared to other forecasting methods forthe household load exhibiting significant fluctuations across different seasons.

Hybrid artificial bee colony algorithm with variable neighborhood search and memory mechanism

Artificial bee colony(ABC) is one of the most popular swarm intelligence optimization algorithms which have been widely used in numerical optimization and engineering applications. However, there are still deficiencies in ABC regarding its local search ability and global search efficiency. Aiming at these deficiencies,an ABC variant named hybrid ABC(HABC) algorithm is proposed.Firstly, the variable neighborhood search factor is added to the solution search equation, which can enhance the local search ability and increase the population diversity. Secondly, inspired by the neuroscience investigation of real honeybees, the memory mechanism is put forward, which assumes the artificial bees can remember their past successful experiences and further guide the subsequent foraging behavior. The proposed memory mechanism is used to improve the global search efficiency. Finally, the results of comparison on a set of ten benchmark functions demonstrate the superiority of HABC.

An insight into failure mechanism of NASICON-structured Na3V2（PO4）3 in hybrid aqueous rechargeable battery

NASICON (Na-super-ionic-conductors)-structured materials have attracted extensive research interest due to their great application potential in secondary batteries. However, the mechanism of capacity fading for NASICON-structured electrode materials has been rarely studied. In this paper, we synthesized the NASICON-structured Na3V2(PO4)3/C composite by simple sol-gel and high-temperature solid-phase method and investigated its electrochemical performance in Na-Zn hybrid aqueous rechargeable batteries. After characterizing the structure, morphology and composition variations as well as the interfacial resistance changes of Na3V2(PO4)3/C cathode during cycling, we propose a mechanical and interfacial degradation mechanism for capacity fading of NASICON-structured Na3V2(PO4)3/C in Na-Zn hybrid aqueous rechargeable batteries. This work will shed light on enhancing the mechanical and in terfacial stability of NASICON-structured Na3V2(PO4)3/C in Na-Zn hybrid aqueous rechargeable batteries.

Inorganic-organic hybrid photocatalysts:Syntheses,mechanisms,and applications

Inorganic-organic hybrid materials are promising for application in the field of photocatalysis because of their excellent properties.Therefore,their syntheses,mechanisms,and applications are reviewed in this paper.First,we introduce the role of inorganic-organic photocatalysts,their advantages and disadvantages,and their design principles.Second,we present the top-down and bottom-up synthesis methods of the hybrid materials.The interaction between inorganic and organic components in hybrid materials is discussed,followed by how to improve inorganic-organic photocatalysts.Third,the applications of hybrid materials in the field of photocatalysis,such as realizing hydrogen evolution,organic pollutant degradation,heavy metals and CO_(2) reduction,sterilization,and nitrogen fixation,are examined.Finally,the application prospects and development directions of inorganic-organic hybrid materials are explored and the unsolved problems are described.

Development and strengthening mechanisms of a hybrid CNTs@SiCp/Mg-6Zn composite fabricated by a novel method

The hybrid addition of CNTs was used to improve both the strengths and ductility of SiCp reinforced Mg matrix composites.A novel method was developed to simultaneously disperse SiCp and CNTs in Mg melt.Firstly,new CNTs@SiCp hybrid reinforcements were synthesized by CVD.Thus,CNTs were well pre-dispersed on the SiCp surfaces before they were added to Mg melt.Therefore,the following semisolid stirring and ultrasonic vibration dispersed the new hybrid reinforcements well in Mg-6Zn melt.The hybrid composite exhibits some unique features in microstructures.Although the distribution of SiCp was very uniform in the Mg-6Zn matrix,most CNTs distributed along the strips in the state of micro-clusters,in which CNTs were bonded very well with Mg matrix.Most of the CNTs kept their structure integrity during fabrication process.All these factors ensure that the hybrid composite have much higher strength and elongation than the mono SiC/Mg-6Zn composites.The dominant strengthening mechanism is the load transfer effect of CNTs.Apart from grain refinement,the CNTs toughen the composites by impeding the microcrack propagation inside the material.Thus,the hybrid CNTs@SiCp successfully realizes the reinforcing advantage of“1+1>2”.

Structural Synthesis of a Class of 2R2T Hybrid Mechanisms

Conventional overconstrained parallel manipulators have been widely studied both in industry and academia,however the structural synthesis of hybrid mechanisms with additional constraints is seldom studied,especially for the four degrees of freedom（DOF） hybrid mechanisms.In order to develop a manipulator with additional constraints,a class of important spatial mechanisms with coupling chains（CCs） whose motion type is two rotations and two translations（2R2T） is presented.Based on screw theory,the combination of different types of limbs which are used to construct parallel mechanisms and coupling chains is proposed.The basic types of the general parallel mechanisms and geometric conditions of the kinematic chains are given using constraint synthesis method.Moreover,the 2R2T motion pattern hybrid mechanisms which are derived by adding coupling chains between different serial kinematic chains（SKCs） of the corresponding parallel mechanisms are presented.According to the constraint analysis of the mechanisms,the movement relationship of the moving platform and the kinematic chains is derived by disassembling the coupling chains.At last,fourteen novel hybrid mechanisms with two or three serial kinematic chains are presented.The proposed novel hybrid mechanisms and construction method enrich the family of the spatial mechanisms and provide an instruction to design more complex hybrid mechanisms.

A new hybrid energy absorption mechanism subjected to axial loading

This study aims to introduce a novel hybrid design with a combination of two more common mechanisms for improving the capacity of systems in absorbing the kinetic energy of moving vehicles or devices. This new model consists of two individual mechanisms, i.e., expansion of a circular tube accompanied by crushing of an inner tube, which dissipate the energy through friction, plastic deformations and failures of inner tube. This study comprises 24 case studies surveyed under two different design controls, constant mass and constant volume, for comparing purposes. Finite element simulations are utilized so as to investigate models’ deformations and to extract some crashworthiness parameters in aid of representing the efficiency of the mechanism as well as conducting a parametric study between three different profiles of inner tube. This study shows that models with inner circular and hexagonal tube profile absorb higher amount of energy due to experiencing three different modes of energy dissipation systems, including folding, shear and ductile damages.

Dissection of Genetic Mechanism of Abnormal Heading in Hybrid Rice

Abnormal heading in hybrid rice production has caused great economic loss in recent years, but the genetic basis of this phenomenon remains elusive. In this study, we developed four testcross populations using 38 introgression lines （ILs） from Shuhui 527 （SH527）/Fuhui 838 （FH838）//SH527 population as male parents and four male sterile lines （MSLs; namely 11-32A, Xieqingzao A, Gang 46A and Jin 23A） as female parents. Progeny testing allowed us to identify 55 abnormal heading combinations in Hefei, but had late heading date in Hangzhou and Guangzhou of China. By one- and two-way analysis of variance, a total of 21 QTLs and 31 pairs of epistatic QTLs associated with photosensitivity were identified in the four populations, respectively. Genotypic analysis showed that the IL parent of most abnormal heading combinations showed some introgressions at markers RM331 and RM3395 on chromosome 8 （strongly associated with the known genes OsHAP3H/DTH8/Ghd8/LHD1） of donor FH838 alleles, and these two markers were also identified as affecting photosensitivity. The observation that the recipient parent （SH527）, donor parent （FH838）, their testcross combinations with four MSLs, and the IL parents of abnormal heading combinations had normal heading date in Hefei suggested that OsHAP3H/DTH8/Ghd8/LHD1 showed no independent regulation on abnormal heading in the abnormal heading combinations. It is noteworthy that complex epistasis among RM331 or RM3395 with other loci, including dominant x additive, additive x dominant, and dominant x dominant epistases, were identified only in the four testcross populations of the current study, but not in the SH527/FH838//SH527 population suggesting the cause of abnormal heading in abnormal heading combinations in Hefei and delayed heading in Hangzhou and Guangzhou.

EEG Emotion Recognition Using an Attention Mechanism Based on an Optimized Hybrid Model

Emotions serve various functions.The traditional emotion recognition methods are based primarily on readily accessible facial expressions,gestures,and voice signals.However,it is often challenging to ensure that these non-physical signals are valid and reliable in practical applications.Electroencephalogram(EEG)signals are more successful than other signal recognition methods in recognizing these characteristics in real-time since they are difficult to camouflage.Although EEG signals are commonly used in current emotional recognition research,the accuracy is low when using traditional methods.Therefore,this study presented an optimized hybrid pattern with an attention mechanism(FFT_CLA)for EEG emotional recognition.First,the EEG signal was processed via the fast fourier transform(FFT),after which the convolutional neural network(CNN),long short-term memory(LSTM),and CNN-LSTM-attention(CLA)methods were used to extract and classify the EEG features.Finally,the experiments compared and analyzed the recognition results obtained via three DEAP dataset models,namely FFT_CNN,FFT_LSTM,and FFT_CLA.The final experimental results indicated that the recognition rates of the FFT_CNN,FFT_LSTM,and FFT_CLA models within the DEAP dataset were 87.39%,88.30%,and 92.38%,respectively.The FFT_CLA model improved the accuracy of EEG emotion recognition and used the attention mechanism to address the often-ignored importance of different channels and samples when extracting EEG features.

Generalized Kinematics Analysis of Hybrid Mechanisms Based on Screw Theory and Lie Groups Lie Algebras

Advanced mathematical tools are used to conduct research on the kinematics analysis of hybrid mechanisms,and the generalized analysis method and concise kinematics transfer matrix are obtained.In this study,first,according to the kinematics analysis of serial mechanisms,the basic principles of Lie groups and Lie algebras are briefly explained in dealing with the spatial switching and differential operations of screw vectors.Then,based on the standard ideas of Lie operations,the method for kinematics analysis of parallel mechanisms is derived,and Jacobian matrix and Hessian matrix are formulated recursively and in a closed form.Then,according to the mapping relationship between the parallel joints and corresponding equivalent series joints,a forward kinematics analysis method and two inverse kinematics analysis methods of hybrid mechanisms are examined.A case study is performed to verify the calculated matrices wherein a humanoid hybrid robotic arm with a parallel-series-parallel configuration is considered as an example.The results of a simulation experiment indicate that the obtained formulas are exact and the proposed method for kinematics analysis of hybrid mechanisms is practically feasible.

Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control

This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance.

Consecutive hybrid mechanism boosting Na+storage performance of dual-confined SnSe2 in N,Se-doping double-walled hollow carbon spheres

Rationally designed hierarchical structures and heteroatomic doping of carbon are effective strategies to enhance the stability and electrical conductivity of materials.Herein,SnSe_(2)flakes were generated in the double-walled hollow carbon spheres(DWHCSs),in which N and Se atoms were doped in the carbon walls,to construct SnSe_(2)@N,Se-DWHCSs by confined growth and in-situ derivatization.The N and Sedoped DWHCSs can effectively limit the size increase of SnSe_(2),promote ion diffusion kinetics,and buffer volume expansion,which can be proved by electron microscope observation and density functional theory calculation.Consequently,the SnSe_(2)@N,Se-DWHCSs as an anode material for sodium ion batteries(SIBs)demonstrated a distinguished reversible capacity of 322.8 mAh g^(-1)at 5 A g^(-1)after 1000 cycles and a superior rate ability of 235.3 m Ah g^(-1)at an ultrahigh rate of 15 A g^(-1).Furthermore,the structure evolution and electrochemical reaction processes of SnSe2@N,Se-DWHCSs in SIBs were analyzed by exsitu methods,which confirmed the consecutive hybrid mechanism and the phase transition process.

Recent progress of hybrid cathode interface layer for organic solar cells

Organic solar cells(OSCs)have gained conspicuous progress during the past few decades due to the development of materials and upgrading of the device structure.The power conversion efficiency(PCE)of the single-junction device had surpassed 19%.The cathode interface layer(CIL),by optimizing the connection between the active layer and the cathode electrode,has become a momentous part to strengthen the performances of the OSCs.Simultaneously,CIL is also indispensable to illustrating the working mechanism of OSCs and enhancing the stability of the OSCs.In this essay,hybrid CILs in OSCs have been summarized.Firstly,the advancement and operating mechanism of OSCs,and the effects and relevant design rules of CIL are briefly concluded;secondly,the significant influence of CIL on enhancing the stability and PCE of OSCs is presented;thirdly,the characteristics of organic hybrid CIL and organic-inorganic hybrid CIL are introduced.Finally,the conclusion and outlook of CIL are summarized.

Beam oscillating parameters on pore inhibition,recrystallization and grain boundary characteristics of laser-arc hybrid welded AZ31 magnesium alloy

Oscillating laser-arc hybrid welding of AZ31B magnesium alloy was carried out,the effects of beam oscillation parameters on pore inhibition,microstructure,grain boundary characteristics and tensile properties were investigated.The results showed that the pore formation can be inhibited with oscillating frequency higher than 75 Hz and radius smaller than 0.5 mm.The columnar grains neighboring the fusion line can be broken by the beam oscillation behavior,while the grain growth was promoted with the increase of frequency or radius.It should be noted that the coincidence site lattice(CSL)boundaries were mainlyΣ13b andΣ29 boundaries,which were contributed by{10■2}tensile twins and{11■2}compression twins,respectively.The total fraction of CSL boundaries reached maximum at radius of 0.25 mm and frequency of 75 Hz,which was also confirmed as the optimized parameters.In this case,the elongation rate increased up to 13.2%,12.8%higher than that of the weld without beam oscillation.Finally,the pore formation and inhibition mechanisms were illustrated according to the state of melt flow and keyhole formation,the abnormal growth was discussed basing on secondary recrystallization,and the relationship among the pore formation,grain size,boundary characteristics and weld toughness were finally established.

Dual-ion carrier storage through Mg^(2+) addition for high-energy and long-life zinc-ion hybrid capacitor

Cation additives can efficiently enhance the total electrochemical capabilities of zinc-ion hybrid capacitors (ZHCs).However their energy storage mechanisms in zinc-based systems are still under debate.Herein,we modulate the electrolyte and achieve dual-ion storage by adding magnesium ions.And we assemble several Zn//activated carbon devices with different electrolyte concentrations and investigate their electrochemical reaction dynamic behaviors.The zinc-ion capacitor with Mg^(2+)mixed solution delivers 82 mAh·g^(-1)capacity at 1 A·g^(-1) and maintains 91%of the original capacitance after 10000 cycling.It is superior to the other assembled zinc-ion devices in single-component electrolytes.The finding demonstrates that the double-ion storage mechanism enables the superior rate performance and long cycle lifetime of ZHCs.