The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition...The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.展开更多
This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balanc...This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.展开更多
Shaped charge has been widely used for penetrating concrete.However,due to the obvious difference between the propagation of shock waves and explosion products in water and air,the theory governing the formation of sh...Shaped charge has been widely used for penetrating concrete.However,due to the obvious difference between the propagation of shock waves and explosion products in water and air,the theory governing the formation of shaped charge jets in water as well as the underwater penetration effect of concrete need to be studied.In this paper,we introduced a modified forming theory of an underwater hemispherical shaped charge,and investigated the behavior of jet formation and concrete penetration in both air and water experimentally and numerically.The results show that the modified jet forming theory predicts the jet velocity of the hemispherical liner with an error of less than 10%.The underwater jets exhibit at least 3%faster and 11%longer than those in air.Concrete shows different failure modes after penetration in air and water.The depth of penetration deepens at least 18.75%after underwater penetration,accompanied by deeper crater with 65%smaller radius.Moreover,cracks throughout the entire target are formed,whereas cracks exist only near the penetration hole in air.This comprehensive study provides guidance for optimizing the structure of shaped charge and improves the understanding of the permeability effect of concrete in water.展开更多
This article presents a detailed theoretical hybrid analysis of the magnetism and the thermal radiative heat transfer in the presence of heat generation affecting the behavior of the dispersed gold nanoparticles(AuNPs...This article presents a detailed theoretical hybrid analysis of the magnetism and the thermal radiative heat transfer in the presence of heat generation affecting the behavior of the dispersed gold nanoparticles(AuNPs)through the blood vessels of the human body.The rheology of gold-blood nanofluid is treated as magnetohydrodynamic(MHD)flow with ferromagnetic properties.The AuNPs take different shapes as bricks,cylinders,and platelets which are considered in changing the nanofluid flow behavior.Physiologically,the blood is circulated under the kinetics of the peristaltic action.The mixed properties of the slip flow,the gravity,the space porosity,the transverse ferromagnetic field,the thermal radiation,the nanoparticles shape factors,the peristaltic amplitude ratio,and the concentration of the AuNPs are interacted and analyzed for the gold-blood circulation in the inclined tube.The appropriate model for the thermal conductivity of the nanofluid is chosen to be the effective Hamilton-Crosser model.The undertaken nanofluid can be treated as incompressible non-Newtonian ferromagnetic fluid.The solutions of the partial differential governing equations of the MHD nanofluid flow are executed by the strategy of perturbation approach under the assumption of long wavelength and low Reynolds number.Graphs for the streamwise velocity distributions,temperature distributions,pressure gradients,pressure drops,and streamlines are presented under the influences of the pertinent properties.The practical implementation of this research finds application in treating cancer through a technique known as photothermal therapy(PTT).The results indicate the control role of the magnetism,the heat generation,the shape factors of the AuNPs,and its concentration on the enhancement of the thermal properties and the streamwise velocity of the nanofluid.The results reveal a marked enhancement in the temperature profiles of the nanofluid,prominently influenced by both the intensified heat source and the heightened volume fractions of the nanoparticles.Furthermore,the platelet shape is regarded as most advantageous for heat conduction owing to its highest effective thermal conductivity.AuNPs proved strong efficiency in delivering and targeting the drug to reach the affected area with tumors.These results offer valuable insights into evaluating the effectiveness of PTT in addressing diverse cancer conditions and regulating their progression.展开更多
In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimizatio...In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.展开更多
The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram phenomena.The dynamic expansion of the cavity induces liquid pressure ...The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram phenomena.The dynamic expansion of the cavity induces liquid pressure variations,potentially causing catastrophic damage to the container.Current studies mainly focus on non-deforming projectiles,such as fragments,with limited exploration of shaped charge jets.In this paper,a uniquely experimental system was designed to record cavity profiles in behind-armor liquid-filled containers subjected to shaped charge jet impacts.The impact process was then numerically reproduced using the explicit simulation program ANSYS LS-DYNA with the Structured Arbitrary Lagrangian-Eulerian(S-ALE)solver.The formation mechanism,along with the dimensional and shape evolution of the cavity was investigated.Additionally,the influence of the impact kinetic energy of the jet on the cavity characteristics was analyzed.The findings reveal that the cavity profile exhibits a conical shape,primarily driven by direct jet impact and inertial effects.The expansion rates of both cavity length and maximum radius increase with jet impact kinetic energy.When the impact kinetic energy is reduced to 28.2 kJ or below,the length-to-diameter ratio of the cavity ultimately stabilizes at approximately 7.展开更多
(TiZrHf)_(50)Ni_(30)Cu_(20-x)Co_(x)(x=2,4,6,at%)high-entropy high-temperature shape memory alloys were fabricated by watercooled copper crucible in a magnetic levitation vacuum melting furnace,and the effects of Co co...(TiZrHf)_(50)Ni_(30)Cu_(20-x)Co_(x)(x=2,4,6,at%)high-entropy high-temperature shape memory alloys were fabricated by watercooled copper crucible in a magnetic levitation vacuum melting furnace,and the effects of Co content on microstructure and mechanical properties were investigated.The results indicate that the grain size of the alloy decreases with increasing the Co content.In the as-cast state,the alloy consists primarily of the B19′phase,with a trace of B2 phase.The fracture morphology is predominantly composed of the B19′phase,whereas the B2 phase is nearly absent.Increasing the Co content or reducing the sample dimensions(d)markedly enhance the compressive strength and ductility of the alloy.When d=2 mm,the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy demonstrates the optimal mechanical properties,achieving a compressive strength of 2142.39±1.8 MPa and a plasticity of 17.31±0.3%.The compressive cyclic test shows that with increasing the compressive strain,the residual strain of the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy increases while the recovery ability declines.The superelastic recovery capability of the alloy is continuously enhanced.The superelastic recovery rate increases from 1.36%to 2.12%,the residual strain rate rises from 1.79%to 5.52%,the elastic recovery rate ascends from 3.86%to 7.36%,while the total recovery rate declines from 74.48%to 63.20%.展开更多
Multi-instance image generation remains a challenging task in the field of computer vision.While existing diffusionmodels demonstrate impressive fidelity in image generation,they often struggle with precisely controll...Multi-instance image generation remains a challenging task in the field of computer vision.While existing diffusionmodels demonstrate impressive fidelity in image generation,they often struggle with precisely controlling each object’s shape,pose,and size.Methods like layout-to-image and mask-to-image provide spatial guidance but frequently suffer from object shape distortion,overlaps,and poor consistency,particularly in complex scenes with multiple objects.To address these issues,we introduce PolyDiffusion,a contour-based diffusion framework that encodes each object’s contour as a boundary-coordinate sequence,decoupling object shapes and positions.This approach allows for better control over object geometry and spatial positioning,which is critical for achieving high-quality multiinstance generation.We formulate the training process as a multi-objective optimization problem,balancing three key objectives:a denoising diffusion loss to maintain overall image fidelity,a cross-attention contour alignment loss to ensure precise shape adherence,and a reward-guided denoising objective that minimizes the Fréchet distance to real images.In addition,the Object Space-Aware Attention module fuses contour tokens with visual features,while a prior-guided fusion mechanism utilizes inter-object spatial relationships and class semantics to enhance consistency across multiple objects.Experimental results on benchmark datasets such as COCO-Stuff and VOC-2012 demonstrate that PolyDiffusion significantly outperforms existing layout-to-image and mask-to-image methods,achieving notable improvements in both image quality and instance-level segmentation accuracy.The implementation of Poly Diffusion is available at https://github.com/YYYYYJS/PolyDiffusion(accessed on 06 August 2025).展开更多
A Shape Memory Polymer Composite(SMPC)is developed by reinforcing an epoxy-based polymer with randomly oriented short glass fibers.Diverging from previous research,which primarily focused on the hot programming of sho...A Shape Memory Polymer Composite(SMPC)is developed by reinforcing an epoxy-based polymer with randomly oriented short glass fibers.Diverging from previous research,which primarily focused on the hot programming of short glass fiber-based SMPCs,this work explores the potential for programming below the glass transition temperature(Tg)for epoxy-based SMPCs.To mitigate the inherent brittleness of the SMPC during deformation,a linear polymer is incorporated,and a temperature between room temperature and Tg is chosen as the deformation temperature to study the shape memory properties.The findings demonstrate an enhancement in shape fixity and recovery stress,alongside a reduction in shape recovery,with the incorporation of short glass fibers.In addition to tensile properties,thermal properties such as thermal conductivity,specific heat capacity,and glass transition temperature are investigated for their dependence on fiber content.Microscopic properties,such as fiber-matrix adhesion and the dispersion of glass fibers,are examined through Scanning Electron Microscope imaging.The fiber length distribution and mean fiber lengths are also measured for different fiber fractions.展开更多
In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave pow...In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.展开更多
This study explores the phenomenon of shape coexistence in nuclei around^(172)Hg,with a focus on the isotopes^(170)Pt,^(172)Hg,and^(174)Pb,as well as the^(170)Pt to^(180)Pt isotopic chain.Utilizing a macro-microscopic...This study explores the phenomenon of shape coexistence in nuclei around^(172)Hg,with a focus on the isotopes^(170)Pt,^(172)Hg,and^(174)Pb,as well as the^(170)Pt to^(180)Pt isotopic chain.Utilizing a macro-microscopic approach that incorporates the Lublin-Strasbourg Drop model combined with a Yukawa-Folded potential and pairing corrections,we analyze the potential energy surfaces(PESs)to understand the impact of pairing interaction.For^(170)Pt,the PES exhibited a prolate ground state,with additional triaxial and oblate-shaped isomers.In^(172)Hg,the ground-state deformation transitions from triaxial to oblate with increasing pairing interaction,demonstrating its nearlyγ-unstable nature.Three shape isomers(prolate,triaxial,and oblate)were observed,with increased pairing strength leading to the disappearance of the triaxial isomer.^(174)Pb exhibited a prolate ground state that became increasingly spherical with stronger pairing.While shape isomers were present at lower pairing strengths,robust shape coexistence was not observed.For realistic pairing interaction,the ground-state shapes transitioned from prolate in^(170)Pt to a coexistence ofγ-unstable and oblate shapes in^(172)Hg,ultimately approaching spherical symmetry in^(174)Pb.A comparison between Exact and Bardeen-Cooper-Schrieffer(BCS)pairing demonstrated that BCS pairing tends to smooth out shape coexistence and reduce the depth of the shape isomer,leading to less pronounced deformation features.The PESs for even-even^(170)-180 Pt isotopes revealed significant shape evolution.^(170)Pt showed a prolate ground state,whereas^(172)Pt exhibited both triaxial and prolate shape coexistence.In^(174)Pt,the ground state was triaxial,coexisted with a prolate minimum.For^(176)Pt,aγ-unstable ground state coexists with a prolate minimum.By 178 Pt and 180Pt,a dominant prolate minimum emerged.These results highlight the role of shape coexistence andγ-instability in the evolution of nuclear structure,especially in the mid-shell region.These findings highlight the importance of pairing interactions in nuclear deformation and shape coexistence,providing insights into the structural evolution of mid-shell nuclei.展开更多
Shape memory alloys(SMAs)and shape memory ceramics(SMCs)exhibit high recovery ability due to the martensitic transformation,which complicates the fracture mechanism of SMAs and SMCs.The phase field method,as a powerfu...Shape memory alloys(SMAs)and shape memory ceramics(SMCs)exhibit high recovery ability due to the martensitic transformation,which complicates the fracture mechanism of SMAs and SMCs.The phase field method,as a powerful numerical simulation tool,can efficiently resolve the microstructural evolution,multi-field coupling effects,and fracture behavior of SMAs and SMCs.This review begins by presenting the fundamental theoretical framework of the fracture phase field method as applied to SMAs and SMCs,covering key aspects such as the phase field modeling of martensitic transformation and brittle fracture.Subsequently,it systematically examines the phase field simulations of fracture behaviors in SMAs and SMCs,with particular emphasis on how crystallographic orientation,grain size,and grain boundary properties influence the crack propagation.Additionally,the interplay between martensite transformation and fracture mechanisms is analyzed to provide deeper insights into the material responses under mechanical loading.Finally,the review explores future prospects and emerging trends in phase field simulations of SMA and SMC fracture behavior,along with potential advancements in the fracture phase field method itself,including multi-physics coupling and enhanced computational efficiency for large-scale simulations.展开更多
Impinging jet arrays are extensively used in numerous industrial operations,including the cooling of electronics,turbine blades,and other high-heat flux systems because of their superior heat transfer capabilities.Opt...Impinging jet arrays are extensively used in numerous industrial operations,including the cooling of electronics,turbine blades,and other high-heat flux systems because of their superior heat transfer capabilities.Optimizing the design and operating parameters of such systems is essential to enhance cooling efficiency and achieve uniform pressure distribution,which can lead to improved system performance and energy savings.This paper presents two multi-objective optimization methodologies for a turbulent air jet impingement cooling system.The governing equations are resolved employing the commercial computational fluid dynamics(CFD)software ANSYS Fluent v17.The study focuses on four controlling parameters:Reynolds number(Re),swirl number(S),jet-to-jet separation distance(Z/D),and impingement height(H/D).The effects of these parameters on heat transfer and impingement pressure distribution are investigated.Non-dominated Sorting Genetic Algorithm(NSGA-II)and Weighted Sum Method(WSM)are employed to optimize the controlling parameters for maximum cooling performance.The aim is to identify optimal design parameters and system configurations that enhance heat transfer efficiency while achieving a uniform impingement pressure distribution.These findings have practical implications for applications requiring efficient cooling.The optimized design achieved a 12.28%increase in convective heat transfer efficiency with a local Nusselt number of 113.05 compared to 100.69 in the reference design.Enhanced convective cooling and heat flux were observed in the optimized configuration,particularly in areas of direct jet impingement.Additionally,the optimized design maintained lower wall temperatures,demonstrating more effective thermal dissipation.展开更多
Metamaterials,owing to their exceptional physical characteristics that are absent in natural materials,have emerged as a crucial constituent of intelligent devices and systems.However,there are still significant chall...Metamaterials,owing to their exceptional physical characteristics that are absent in natural materials,have emerged as a crucial constituent of intelligent devices and systems.However,there are still significant challenges that necessitate immediate attention,as they have considerably constrained the applicability of metamaterials,including fixed mechanical properties post-fabrication and restricted design freedom.Here,thermo-responsive,photo-responsive,electro-responsive,and magneto-responsive shape memory polymer nano-composites were developed,and shape memory gradient metamaterials were fabricated using multi-material 4D printing technology.The correlation mechanism between the design parameters and the mechanical properties of multi-responsive gradient metamaterials was systematically analyzed,and the highly designable and programmable configuration and mechanical properties of the gradient metamaterials were realized.More importantly,4D printed multi-responsive shape memory polymer gradient metamaterials can be programmed in situ without additional infrastructure for multi-functional mechanical functions,paving the way for the realization of multiple functions of a single structure.Based on the multi-responsive gradient metamaterials,4D printed digital pixel metamaterial intelligent information carriers were fabricated,featuring customizable encryption and decryption protocols,exceptional scalability,and reusability.Additionally,4D printed gradient metamaterial logic gate electronic devices were developed,which were anticipated to contribute to the development of smart,adaptable robotic systems that combine sensing,actuation,and decision-making capabilities.展开更多
With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm impro...With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.展开更多
This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic(FRP)fishing vessels to address critical limitations of conventional designs,including excessive weight,mate...This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic(FRP)fishing vessels to address critical limitations of conventional designs,including excessive weight,material inefficiency,and performance redundancy.By integrating surrogate modeling techniques with a multi-objective genetic algorithm(MOGA),we have developed a systematic approach that encompasses parametric modeling,finite element analysis under extreme operational conditions,and multi-fidelity performance evaluation.Through a 10-t electric winch case study,the methodology’s effectiveness is demonstrated via parametric characterization of structural integrity,stiffness behavior,and mass distribution.The comparative analysis identified optimal surrogate models for predicting key performance metrics,which enabled the construction of a robust multi-objective optimization model.The MOGA-derived Pareto solutions produced a design configuration achieving 7.86%mass reduction,2.01%safety factor improvement,and 23.97%deformation mitigation.Verification analysis confirmed the optimization scheme’s reliability in balancing conflicting design requirements.This research establishes a generalized framework for marine deck machinery modernization,particularly addressing the structural compatibility challenges in FRP vessel retrofitting.The proposed methodology demonstrates significant potential for facilitating sustainable upgrades of fishing vessel equipment through systematic performance optimization.展开更多
The spoke as a key component has a significant impact on the performance of the non-pneumatic tire(NPT).The current research has focused on adjusting spoke structures to improve the single performance of NPT.Few studi...The spoke as a key component has a significant impact on the performance of the non-pneumatic tire(NPT).The current research has focused on adjusting spoke structures to improve the single performance of NPT.Few studies have been conducted to synergistically improve multi-performance by optimizing the spoke structure.Inspired by the concept of functionally gradient structures,this paper introduces a functionally gradient honeycomb NPT and its optimization method.Firstly,this paper completes the parameterization of the honeycomb spoke structure and establishes the numerical models of honeycomb NPTs with seven different gradients.Subsequently,the accuracy of the numerical models is verified using experimental methods.Then,the static and dynamic characteristics of these gradient honeycomb NPTs are thoroughly examined by using the finite element method.The findings highlight that the gradient structure of NPT-3 has superior performance.Building upon this,the study investigates the effects of key parameters,such as honeycomb spoke thickness and length,on load-carrying capacity,honeycomb spoke stress and mass.Finally,a multi-objective optimization method is proposed that uses a response surface model(RSM)and the Nondominated Sorting Genetic Algorithm-II(NSGA-II)to further optimize the functional gradient honeycomb NPTs.The optimized NPT-OP shows a 23.48%reduction in radial stiffness,8.95%reduction in maximum spoke stress and 16.86%reduction in spoke mass compared to the initial NPT-1.The damping characteristics of the NPT-OP have also been improved.The results offer a theoretical foundation and technical methodology for the structural design and optimization of gradient honeycomb NPTs.展开更多
Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help...Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield,or to increase product yield while reducing energy consumption.This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm,which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm.The reactor model used in this article is simulated based on a twenty-five lumped kinetic model.Through model and test function verification,the proposed optimization scheme exhibits significant advantages in the multiobjective optimization process of hydrocracking.展开更多
基金supported by National Natural Science Foundations of China(nos.12271326,62102304,61806120,61502290,61672334,61673251)China Postdoctoral Science Foundation(no.2015M582606)+2 种基金Industrial Research Project of Science and Technology in Shaanxi Province(nos.2015GY016,2017JQ6063)Fundamental Research Fund for the Central Universities(no.GK202003071)Natural Science Basic Research Plan in Shaanxi Province of China(no.2022JM-354).
文摘The multi-objective particle swarm optimization algorithm(MOPSO)is widely used to solve multi-objective optimization problems.In the article,amulti-objective particle swarm optimization algorithmbased on decomposition and multi-selection strategy is proposed to improve the search efficiency.First,two update strategies based on decomposition are used to update the evolving population and external archive,respectively.Second,a multiselection strategy is designed.The first strategy is for the subspace without a non-dominated solution.Among the neighbor particles,the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle far away fromthe search particle and the global optimal solution is selected as the personal optimal solution to enhance global search.The second strategy is for the subspace with a non-dominated solution.In the neighbor particles,two particles are randomly selected,one as the global optimal solution and the other as the personal optimal solution,to enhance local search.The third strategy is for Pareto optimal front(PF)discontinuity,which is identified by the cumulative number of iterations of the subspace without non-dominated solutions.In the subsequent iteration,a new probability distribution is used to select from the remaining subspaces to search.Third,an adaptive inertia weight update strategy based on the dominated degree is designed to further improve the search efficiency.Finally,the proposed algorithmis compared with fivemulti-objective particle swarm optimization algorithms and five multi-objective evolutionary algorithms on 22 test problems.The results show that the proposed algorithm has better performance.
基金supported by the National Natural Science Foundation of China(Project No.5217232152102391)+2 种基金Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.
基金supported by the National Science Foundation of China(Grant Nos.12372361,12102427,12372335 and 12102202)the Fundamental Research Funds for the Central Universities(Grant No.30923010908)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX23_0520).
文摘Shaped charge has been widely used for penetrating concrete.However,due to the obvious difference between the propagation of shock waves and explosion products in water and air,the theory governing the formation of shaped charge jets in water as well as the underwater penetration effect of concrete need to be studied.In this paper,we introduced a modified forming theory of an underwater hemispherical shaped charge,and investigated the behavior of jet formation and concrete penetration in both air and water experimentally and numerically.The results show that the modified jet forming theory predicts the jet velocity of the hemispherical liner with an error of less than 10%.The underwater jets exhibit at least 3%faster and 11%longer than those in air.Concrete shows different failure modes after penetration in air and water.The depth of penetration deepens at least 18.75%after underwater penetration,accompanied by deeper crater with 65%smaller radius.Moreover,cracks throughout the entire target are formed,whereas cracks exist only near the penetration hole in air.This comprehensive study provides guidance for optimizing the structure of shaped charge and improves the understanding of the permeability effect of concrete in water.
文摘This article presents a detailed theoretical hybrid analysis of the magnetism and the thermal radiative heat transfer in the presence of heat generation affecting the behavior of the dispersed gold nanoparticles(AuNPs)through the blood vessels of the human body.The rheology of gold-blood nanofluid is treated as magnetohydrodynamic(MHD)flow with ferromagnetic properties.The AuNPs take different shapes as bricks,cylinders,and platelets which are considered in changing the nanofluid flow behavior.Physiologically,the blood is circulated under the kinetics of the peristaltic action.The mixed properties of the slip flow,the gravity,the space porosity,the transverse ferromagnetic field,the thermal radiation,the nanoparticles shape factors,the peristaltic amplitude ratio,and the concentration of the AuNPs are interacted and analyzed for the gold-blood circulation in the inclined tube.The appropriate model for the thermal conductivity of the nanofluid is chosen to be the effective Hamilton-Crosser model.The undertaken nanofluid can be treated as incompressible non-Newtonian ferromagnetic fluid.The solutions of the partial differential governing equations of the MHD nanofluid flow are executed by the strategy of perturbation approach under the assumption of long wavelength and low Reynolds number.Graphs for the streamwise velocity distributions,temperature distributions,pressure gradients,pressure drops,and streamlines are presented under the influences of the pertinent properties.The practical implementation of this research finds application in treating cancer through a technique known as photothermal therapy(PTT).The results indicate the control role of the magnetism,the heat generation,the shape factors of the AuNPs,and its concentration on the enhancement of the thermal properties and the streamwise velocity of the nanofluid.The results reveal a marked enhancement in the temperature profiles of the nanofluid,prominently influenced by both the intensified heat source and the heightened volume fractions of the nanoparticles.Furthermore,the platelet shape is regarded as most advantageous for heat conduction owing to its highest effective thermal conductivity.AuNPs proved strong efficiency in delivering and targeting the drug to reach the affected area with tumors.These results offer valuable insights into evaluating the effectiveness of PTT in addressing diverse cancer conditions and regulating their progression.
基金sponsored by R&D Program of Beijing Municipal Education Commission(KM202410009013).
文摘In the independent electro-hydrogen system(IEHS)with hybrid energy storage(HESS),achieving optimal scheduling is crucial.Still,it presents a challenge due to the significant deviations in values ofmultiple optimization objective functions caused by their physical dimensions.These deviations seriously affect the scheduling process.A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values.The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods.The proposed method better balances all optimization objective functions and reduces the impact of their dimensionality.When the cost of BESS decreases by approximately 30%,its participation deepens by about 1 time.Moreover,if the price of the electrolyzer is less than 15¥/kWh or if the cost of the fuel cell drops below 4¥/kWh,their participation will increase substantially.This study aims to provide a more reasonable approach to solving multi-objective optimization problems.
基金financial support from the National Natural Science Foundation of China(Grant No.11572159).
文摘The cavity characteristics in liquid-filled containers caused by high-velocity impacts represent an important area of research in hydrodynamic ram phenomena.The dynamic expansion of the cavity induces liquid pressure variations,potentially causing catastrophic damage to the container.Current studies mainly focus on non-deforming projectiles,such as fragments,with limited exploration of shaped charge jets.In this paper,a uniquely experimental system was designed to record cavity profiles in behind-armor liquid-filled containers subjected to shaped charge jet impacts.The impact process was then numerically reproduced using the explicit simulation program ANSYS LS-DYNA with the Structured Arbitrary Lagrangian-Eulerian(S-ALE)solver.The formation mechanism,along with the dimensional and shape evolution of the cavity was investigated.Additionally,the influence of the impact kinetic energy of the jet on the cavity characteristics was analyzed.The findings reveal that the cavity profile exhibits a conical shape,primarily driven by direct jet impact and inertial effects.The expansion rates of both cavity length and maximum radius increase with jet impact kinetic energy.When the impact kinetic energy is reduced to 28.2 kJ or below,the length-to-diameter ratio of the cavity ultimately stabilizes at approximately 7.
基金National Natural Science Foundation of China(12404230,52061027)Science and Technology Program Project of Gansu Province(22YF7GA155)+1 种基金Lanzhou Youth Science and Technology Talent Innovation Project(2023-QN-91)Zhejiang Provincial Natural Science Foundation of China(LY23E010002)。
文摘(TiZrHf)_(50)Ni_(30)Cu_(20-x)Co_(x)(x=2,4,6,at%)high-entropy high-temperature shape memory alloys were fabricated by watercooled copper crucible in a magnetic levitation vacuum melting furnace,and the effects of Co content on microstructure and mechanical properties were investigated.The results indicate that the grain size of the alloy decreases with increasing the Co content.In the as-cast state,the alloy consists primarily of the B19′phase,with a trace of B2 phase.The fracture morphology is predominantly composed of the B19′phase,whereas the B2 phase is nearly absent.Increasing the Co content or reducing the sample dimensions(d)markedly enhance the compressive strength and ductility of the alloy.When d=2 mm,the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy demonstrates the optimal mechanical properties,achieving a compressive strength of 2142.39±1.8 MPa and a plasticity of 17.31±0.3%.The compressive cyclic test shows that with increasing the compressive strain,the residual strain of the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy increases while the recovery ability declines.The superelastic recovery capability of the alloy is continuously enhanced.The superelastic recovery rate increases from 1.36%to 2.12%,the residual strain rate rises from 1.79%to 5.52%,the elastic recovery rate ascends from 3.86%to 7.36%,while the total recovery rate declines from 74.48%to 63.20%.
基金supported in part by the Scientific Research Fund of National Natural Science Foundation of China(Grant No.62372168)the Hunan Provincial Natural Science Foundation of China(Grant No.2023JJ30266)+2 种基金the Research Project on teaching reform in Hunan province(No.HNJG-2022-0791)the Hunan University of Science and Technology(No.2022-44-8)the National Social Science Funds of China(19BZX044).
文摘Multi-instance image generation remains a challenging task in the field of computer vision.While existing diffusionmodels demonstrate impressive fidelity in image generation,they often struggle with precisely controlling each object’s shape,pose,and size.Methods like layout-to-image and mask-to-image provide spatial guidance but frequently suffer from object shape distortion,overlaps,and poor consistency,particularly in complex scenes with multiple objects.To address these issues,we introduce PolyDiffusion,a contour-based diffusion framework that encodes each object’s contour as a boundary-coordinate sequence,decoupling object shapes and positions.This approach allows for better control over object geometry and spatial positioning,which is critical for achieving high-quality multiinstance generation.We formulate the training process as a multi-objective optimization problem,balancing three key objectives:a denoising diffusion loss to maintain overall image fidelity,a cross-attention contour alignment loss to ensure precise shape adherence,and a reward-guided denoising objective that minimizes the Fréchet distance to real images.In addition,the Object Space-Aware Attention module fuses contour tokens with visual features,while a prior-guided fusion mechanism utilizes inter-object spatial relationships and class semantics to enhance consistency across multiple objects.Experimental results on benchmark datasets such as COCO-Stuff and VOC-2012 demonstrate that PolyDiffusion significantly outperforms existing layout-to-image and mask-to-image methods,achieving notable improvements in both image quality and instance-level segmentation accuracy.The implementation of Poly Diffusion is available at https://github.com/YYYYYJS/PolyDiffusion(accessed on 06 August 2025).
文摘A Shape Memory Polymer Composite(SMPC)is developed by reinforcing an epoxy-based polymer with randomly oriented short glass fibers.Diverging from previous research,which primarily focused on the hot programming of short glass fiber-based SMPCs,this work explores the potential for programming below the glass transition temperature(Tg)for epoxy-based SMPCs.To mitigate the inherent brittleness of the SMPC during deformation,a linear polymer is incorporated,and a temperature between room temperature and Tg is chosen as the deformation temperature to study the shape memory properties.The findings demonstrate an enhancement in shape fixity and recovery stress,alongside a reduction in shape recovery,with the incorporation of short glass fibers.In addition to tensile properties,thermal properties such as thermal conductivity,specific heat capacity,and glass transition temperature are investigated for their dependence on fiber content.Microscopic properties,such as fiber-matrix adhesion and the dispersion of glass fibers,are examined through Scanning Electron Microscope imaging.The fiber length distribution and mean fiber lengths are also measured for different fiber fractions.
文摘In the last decade,space solar power satellites(SSPSs)have been conceived to support net-zero carbon emissions and have attracted considerable attention.Electric energy is transmitted to the ground via a microwave power beam,a technology known as microwave power transmission(MPT).Due to the vast transmission distance of tens of thousands of kilometers,the power transmitting antenna array must span up to 1 kilometer in diameter.At the same time,the size of the rectifying array on the ground should extend over a few kilometers.This makes the MPT system of SSPSs significantly larger than the existing aerospace engineering system.To design and operate a rational MPT system,comprehensive optimization is required.Taking the space MPT system engineering into consideration,a novel multi-objective optimization function is proposed and further analyzed.The multi-objective optimization problem is modeled mathematically.Beam collection efficiency(BCE)is the primary factor,followed by the thermal management capability.Some tapers,designed to solve the conflict between BCE and the thermal problem,are reviewed.In addition to these two factors,rectenna design complexity is included as a functional factor in the optimization objective.Weight coefficients are assigned to these factors to prioritize them.Radiating planar arrays with different aperture illumination fields are studied,and their performances are compared using the multi-objective optimization function.Transmitting array size,rectifying array size,transmission distance,and transmitted power remaine constant in various cases,ensuring fair comparisons.The analysis results show that the proposed optimization function is effective in optimizing and selecting the MPT system architecture.It is also noted that the multi-objective optimization function can be expanded to include other factors in the future.
基金supported by the National Natural Science Foundation of China(Nos.12275115 and 12175097)the National Science Centre of Poland(No.2023/49/B/ST2/01294).
文摘This study explores the phenomenon of shape coexistence in nuclei around^(172)Hg,with a focus on the isotopes^(170)Pt,^(172)Hg,and^(174)Pb,as well as the^(170)Pt to^(180)Pt isotopic chain.Utilizing a macro-microscopic approach that incorporates the Lublin-Strasbourg Drop model combined with a Yukawa-Folded potential and pairing corrections,we analyze the potential energy surfaces(PESs)to understand the impact of pairing interaction.For^(170)Pt,the PES exhibited a prolate ground state,with additional triaxial and oblate-shaped isomers.In^(172)Hg,the ground-state deformation transitions from triaxial to oblate with increasing pairing interaction,demonstrating its nearlyγ-unstable nature.Three shape isomers(prolate,triaxial,and oblate)were observed,with increased pairing strength leading to the disappearance of the triaxial isomer.^(174)Pb exhibited a prolate ground state that became increasingly spherical with stronger pairing.While shape isomers were present at lower pairing strengths,robust shape coexistence was not observed.For realistic pairing interaction,the ground-state shapes transitioned from prolate in^(170)Pt to a coexistence ofγ-unstable and oblate shapes in^(172)Hg,ultimately approaching spherical symmetry in^(174)Pb.A comparison between Exact and Bardeen-Cooper-Schrieffer(BCS)pairing demonstrated that BCS pairing tends to smooth out shape coexistence and reduce the depth of the shape isomer,leading to less pronounced deformation features.The PESs for even-even^(170)-180 Pt isotopes revealed significant shape evolution.^(170)Pt showed a prolate ground state,whereas^(172)Pt exhibited both triaxial and prolate shape coexistence.In^(174)Pt,the ground state was triaxial,coexisted with a prolate minimum.For^(176)Pt,aγ-unstable ground state coexists with a prolate minimum.By 178 Pt and 180Pt,a dominant prolate minimum emerged.These results highlight the role of shape coexistence andγ-instability in the evolution of nuclear structure,especially in the mid-shell region.These findings highlight the importance of pairing interactions in nuclear deformation and shape coexistence,providing insights into the structural evolution of mid-shell nuclei.
基金supported by the National Natural Science Foundation of China(12202294)the Sichuan Science and Technology Program(2024NSFSC1346).
文摘Shape memory alloys(SMAs)and shape memory ceramics(SMCs)exhibit high recovery ability due to the martensitic transformation,which complicates the fracture mechanism of SMAs and SMCs.The phase field method,as a powerful numerical simulation tool,can efficiently resolve the microstructural evolution,multi-field coupling effects,and fracture behavior of SMAs and SMCs.This review begins by presenting the fundamental theoretical framework of the fracture phase field method as applied to SMAs and SMCs,covering key aspects such as the phase field modeling of martensitic transformation and brittle fracture.Subsequently,it systematically examines the phase field simulations of fracture behaviors in SMAs and SMCs,with particular emphasis on how crystallographic orientation,grain size,and grain boundary properties influence the crack propagation.Additionally,the interplay between martensite transformation and fracture mechanisms is analyzed to provide deeper insights into the material responses under mechanical loading.Finally,the review explores future prospects and emerging trends in phase field simulations of SMA and SMC fracture behavior,along with potential advancements in the fracture phase field method itself,including multi-physics coupling and enhanced computational efficiency for large-scale simulations.
文摘Impinging jet arrays are extensively used in numerous industrial operations,including the cooling of electronics,turbine blades,and other high-heat flux systems because of their superior heat transfer capabilities.Optimizing the design and operating parameters of such systems is essential to enhance cooling efficiency and achieve uniform pressure distribution,which can lead to improved system performance and energy savings.This paper presents two multi-objective optimization methodologies for a turbulent air jet impingement cooling system.The governing equations are resolved employing the commercial computational fluid dynamics(CFD)software ANSYS Fluent v17.The study focuses on four controlling parameters:Reynolds number(Re),swirl number(S),jet-to-jet separation distance(Z/D),and impingement height(H/D).The effects of these parameters on heat transfer and impingement pressure distribution are investigated.Non-dominated Sorting Genetic Algorithm(NSGA-II)and Weighted Sum Method(WSM)are employed to optimize the controlling parameters for maximum cooling performance.The aim is to identify optimal design parameters and system configurations that enhance heat transfer efficiency while achieving a uniform impingement pressure distribution.These findings have practical implications for applications requiring efficient cooling.The optimized design achieved a 12.28%increase in convective heat transfer efficiency with a local Nusselt number of 113.05 compared to 100.69 in the reference design.Enhanced convective cooling and heat flux were observed in the optimized configuration,particularly in areas of direct jet impingement.Additionally,the optimized design maintained lower wall temperatures,demonstrating more effective thermal dissipation.
基金supported by the National Key R&D Program of China(2022YFB3805700)the National Natural Science Foundation of China(Grant No.12302198)+2 种基金China Postdoctoral Science Foundation(2022M720042)Heilongjiang Postdoctoral Science Foundation(LBH-Z22016)Key Project of Heilongjiang Provincial Department of Science and Technology(2022ZX02C25).
文摘Metamaterials,owing to their exceptional physical characteristics that are absent in natural materials,have emerged as a crucial constituent of intelligent devices and systems.However,there are still significant challenges that necessitate immediate attention,as they have considerably constrained the applicability of metamaterials,including fixed mechanical properties post-fabrication and restricted design freedom.Here,thermo-responsive,photo-responsive,electro-responsive,and magneto-responsive shape memory polymer nano-composites were developed,and shape memory gradient metamaterials were fabricated using multi-material 4D printing technology.The correlation mechanism between the design parameters and the mechanical properties of multi-responsive gradient metamaterials was systematically analyzed,and the highly designable and programmable configuration and mechanical properties of the gradient metamaterials were realized.More importantly,4D printed multi-responsive shape memory polymer gradient metamaterials can be programmed in situ without additional infrastructure for multi-functional mechanical functions,paving the way for the realization of multiple functions of a single structure.Based on the multi-responsive gradient metamaterials,4D printed digital pixel metamaterial intelligent information carriers were fabricated,featuring customizable encryption and decryption protocols,exceptional scalability,and reusability.Additionally,4D printed gradient metamaterial logic gate electronic devices were developed,which were anticipated to contribute to the development of smart,adaptable robotic systems that combine sensing,actuation,and decision-making capabilities.
基金supported by the Open Fund of Guangxi Key Laboratory of Building New Energy and Energy Conservation(Project Number:Guike Energy 17-J-21-3).
文摘With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through algorithm improvement.To reduce the operational costs of micro-grid systems and the energy abandonment rate of renewable energy,while simultaneously enhancing user satisfaction on the demand side,this paper introduces an improvedmultiobjective Grey Wolf Optimizer based on Cauchy variation.The proposed approach incorporates a Cauchy variation strategy during the optimizer’s search phase to expand its exploration range and minimize the likelihood of becoming trapped in local optima.At the same time,adoptingmultiple energy storage methods to improve the consumption rate of renewable energy.Subsequently,under different energy balance orders,themulti-objective particle swarmalgorithm,multi-objective grey wolf optimizer,and Cauchy’s variant of the improvedmulti-objective grey wolf optimizer are used for example simulation,solving the Pareto solution set of the model and comparing.The analysis of the results reveals that,compared to the original optimizer,the improved optimizer decreases the daily cost by approximately 100 yuan,and reduces the energy abandonment rate to zero.Meanwhile,it enhances user satisfaction and ensures the stable operation of the micro-grid.
基金supported by the Basic Public Welfare Research Program of Zhejiang Province(No.LGN22E050005).
文摘This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic(FRP)fishing vessels to address critical limitations of conventional designs,including excessive weight,material inefficiency,and performance redundancy.By integrating surrogate modeling techniques with a multi-objective genetic algorithm(MOGA),we have developed a systematic approach that encompasses parametric modeling,finite element analysis under extreme operational conditions,and multi-fidelity performance evaluation.Through a 10-t electric winch case study,the methodology’s effectiveness is demonstrated via parametric characterization of structural integrity,stiffness behavior,and mass distribution.The comparative analysis identified optimal surrogate models for predicting key performance metrics,which enabled the construction of a robust multi-objective optimization model.The MOGA-derived Pareto solutions produced a design configuration achieving 7.86%mass reduction,2.01%safety factor improvement,and 23.97%deformation mitigation.Verification analysis confirmed the optimization scheme’s reliability in balancing conflicting design requirements.This research establishes a generalized framework for marine deck machinery modernization,particularly addressing the structural compatibility challenges in FRP vessel retrofitting.The proposed methodology demonstrates significant potential for facilitating sustainable upgrades of fishing vessel equipment through systematic performance optimization.
基金Supported by National Natural Science Foundation of China(Grant Nos.52072156,52272366)Postdoctoral Foundation of China(Grant No.2020M682269).
文摘The spoke as a key component has a significant impact on the performance of the non-pneumatic tire(NPT).The current research has focused on adjusting spoke structures to improve the single performance of NPT.Few studies have been conducted to synergistically improve multi-performance by optimizing the spoke structure.Inspired by the concept of functionally gradient structures,this paper introduces a functionally gradient honeycomb NPT and its optimization method.Firstly,this paper completes the parameterization of the honeycomb spoke structure and establishes the numerical models of honeycomb NPTs with seven different gradients.Subsequently,the accuracy of the numerical models is verified using experimental methods.Then,the static and dynamic characteristics of these gradient honeycomb NPTs are thoroughly examined by using the finite element method.The findings highlight that the gradient structure of NPT-3 has superior performance.Building upon this,the study investigates the effects of key parameters,such as honeycomb spoke thickness and length,on load-carrying capacity,honeycomb spoke stress and mass.Finally,a multi-objective optimization method is proposed that uses a response surface model(RSM)and the Nondominated Sorting Genetic Algorithm-II(NSGA-II)to further optimize the functional gradient honeycomb NPTs.The optimized NPT-OP shows a 23.48%reduction in radial stiffness,8.95%reduction in maximum spoke stress and 16.86%reduction in spoke mass compared to the initial NPT-1.The damping characteristics of the NPT-OP have also been improved.The results offer a theoretical foundation and technical methodology for the structural design and optimization of gradient honeycomb NPTs.
基金supported by National Key Research and Development Program of China (2023YFB3307800)National Natural Science Foundation of China (Key Program: 62136003, 62373155)+1 种基金Major Science and Technology Project of Xinjiang (No. 2022A01006-4)the Fundamental Research Funds for the Central Universities。
文摘Hydrocracking is one of the most important petroleum refining processes that converts heavy oils into gases,naphtha,diesel,and other products through cracking reactions.Multi-objective optimization algorithms can help refining enterprises determine the optimal operating parameters to maximize product quality while ensuring product yield,or to increase product yield while reducing energy consumption.This paper presents a multi-objective optimization scheme for hydrocracking based on an improved SPEA2-PE algorithm,which combines path evolution operator and adaptive step strategy to accelerate the convergence speed and improve the computational accuracy of the algorithm.The reactor model used in this article is simulated based on a twenty-five lumped kinetic model.Through model and test function verification,the proposed optimization scheme exhibits significant advantages in the multiobjective optimization process of hydrocracking.
