Refuse landfill plays an important role in daily life,but also brings serious pollution.By investigating environment pollution of Beichen Shuangkou Refuse Landfill in Tianjin City,this paper put forward major problems...Refuse landfill plays an important role in daily life,but also brings serious pollution.By investigating environment pollution of Beichen Shuangkou Refuse Landfill in Tianjin City,this paper put forward major problems of this refuse landfill,and suggestions for turning it into a landscape system with regeneration and renewing capacity,so as to provide references for ecological restoration and landscaping of similar damaged land resources.展开更多
Due to the lack of restrictions on the exploitation and use of coal mine resources in early China,many wetland lakes were formed because of the changes in geological structure and groundwater overflows,which seriously...Due to the lack of restrictions on the exploitation and use of coal mine resources in early China,many wetland lakes were formed because of the changes in geological structure and groundwater overflows,which seriously damaged the land for production and construction.At present,the research on the key technologies and landscape design of water ecosystems and wetland repair in subsidence areas is still insufficient.By analyzing the current situation of thePan'an Lake Wetland,this paper focuses on the strategies of wetland repair and landscape design in this resource-exhausted area.Further,it discusses the enlightenment of these strategies for transforming and planning similar areas in China.展开更多
In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may manifest.This necessitates the restoration of the imag...In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may manifest.This necessitates the restoration of the image to its original quality.The challenge lies in regenerating significantly compressed images into a state in which these become identifiable.Therefore,this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks(GAN).The generator in this network is based on theU-Net architecture.It features a newhourglass structure that preserves the characteristics of the deep layers.In addition,the network incorporates two loss functions to generate natural and high-quality images:Low Frequency(LF)loss and High Frequency(HF)loss.HF loss uses a pretrained VGG-16 network and is configured using a specific layer that best represents features.This can enhance the performance in the high-frequency region.In contrast,LF loss is used to handle the low-frequency region.The two loss functions facilitate the generation of images by the generator,which can mislead the discriminator while accurately generating high-and low-frequency regions.Consequently,by removing the blocking effects frommaximum lossy compressed images,images inwhich identities could be recognized are generated.This study represents a significant improvement over previous research in terms of the image resolution performance.展开更多
Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas...Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.展开更多
Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as ...Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.展开更多
The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep ...The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.展开更多
The Aral Sea was the fourth largest lake in the world but it has shrunk dramatically as a result of irrational human activities, triggering the "Aral Sea ecological crisis". The ecological problems of the Ar...The Aral Sea was the fourth largest lake in the world but it has shrunk dramatically as a result of irrational human activities, triggering the "Aral Sea ecological crisis". The ecological problems of the Aral Sea have attracted widespread attention, and the alleviation of the Aral Sea ecological crisis has reached a consensus among the five Central Asian countries(Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan, and Turkmenistan). In the past decades, many ecological management measures have been implemented for the ecological restoration of the Aral Sea. However, due to the lack of regional planning and zoning, the results are not ideal. In this study, we mapped the ecological zoning of the Aral Sea from the perspective of ecological restoration based on soil type, soil salinity, surface water, groundwater table, Normalized Difference Vegetation Index(NDVI), land cover, and aerosol optical depth(AOD) data. Soil salinization and salt dust are the most prominent ecological problems in the Aral Sea. We divided the Aral Sea into 7 first-level ecological restoration subregions(North Aral Sea catchment area in the downstream of the Syr Darya River(Subregion Ⅰ);artificial flood overflow area in the downstream of the Aral Sea(Subregion Ⅱ);physical/chemical remediation area of the salt dust source area in the eastern part of the South Aral Sea(Subregion Ⅲ);physical/chemical remediation area of severe salinization in the central part of the South Aral Sea(Subregion Ⅳ);existing water surface and potential restoration area of the South Aral Sea(Subregion Ⅴ);Aral Sea vegetation natural recovery area(Subregion Ⅵ);and vegetation planting area with slight salinization in the South Aral Sea(Subregion Ⅶ)) and 14 second-level ecological restoration subregions according to the ecological zoning principles. Implementable measures are proposed for each ecological restoration subregion. For Subregion Ⅰ and Subregion Ⅱ with lower elevations, artificial flooding should be carried out to restore the surface of the Aral Sea. Subregion Ⅲ and Subregion Ⅳ have severe salinization, making it difficult for vegetation to grow. In these subregions, it is recommended to cover and pave the areas with green biomatrix coverings and environmentally sustainable bonding materials. In Subregion Ⅴ located in the central and western parts of the South Aral Sea, surface water recharge should be increased to ensure that this subregion can maintain normal water levels. In Subregion Ⅵ and Subregion Ⅶ where natural conditions are suitable for vegetation growth, measures such as afforestation and buffer zones should be implemented to protect vegetation. This study could provide a reference basis for future comprehensive ecological management and restoration of the Aral Sea.展开更多
Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research an...Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.展开更多
Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum a...Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete problems.This paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected graphs.To expedite the search process,a quantum algorithm employing Grover’s search is proposed.However,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search impossible.Thus,a swap test method is introduced to ascertain the number of iterations required.The oracle,diffusion operators,and swap test are designed with achievable quantum gates.The query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.展开更多
Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing ...Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.展开更多
Bone screws are devices used to fix implants or bones to bones.However,conventional screws are mechanically fixed with thread and often face long-term failure due to poor osseointegration.To improve osseointegration,s...Bone screws are devices used to fix implants or bones to bones.However,conventional screws are mechanically fixed with thread and often face long-term failure due to poor osseointegration.To improve osseointegration,screws are evolving from solid and smooth to porous and rough.Additive manufacturing(AM)offers a high degree of manufacturing freedom,enabling the preparation of predesigned screws that are porous and rough.This paper provides an overview of the problems currently faced by bone screws:long-term loosening and screw breakage.Next,advances in osseointegrated screws are summarized hierarchically(sub-micro,micro,and macro).At the sub-microscale level,we describe surface-modification techniques for enhancing osseointegration.At the micro level,we summarize the micro-design parameters that affect the mechanical and biological properties of porous osseointegrated screws,including porosity,pore size,and pore shape.In addition,we highlight three promising pore shapes:triply periodic minimal surface,auxetic structure with negative Poisson ratio,and the Voronoi structure.At the macro level,we outline the strategies of graded design,gradient design,and topology optimization design to improve the mechanical strength of porous osseointegrated screws.Simultaneously,this paper outlines advances in AM technology for enhancing the mechanical properties of porous osseointegrated screws.AM osseointegrated screws with hierarchical design are expected to provide excellent long-term fixation and the required mechanical strength.展开更多
Since the discovery of enzyme-like activity of Fe3O4 nanoparticles in 2007,nanozymes are becoming the promising substitutes for natural enzymes due to their advantages of high catalytic activity,low cost,mild reaction...Since the discovery of enzyme-like activity of Fe3O4 nanoparticles in 2007,nanozymes are becoming the promising substitutes for natural enzymes due to their advantages of high catalytic activity,low cost,mild reaction conditions,good stability,and suitable for large-scale production.Recently,with the cross fusion of nanomedicine and nanocatalysis,nanozyme-based theranostic strategies attract great attention,since the enzymatic reactions can be triggered in the tumor microenvironment to achieve good curative effect with substrate specificity and low side effects.Thus,various nanozymes have been developed and used for tumor therapy.In this review,more than 270 research articles are discussed systematically to present progress in the past five years.First,the discovery and development of nanozymes are summarized.Second,classification and catalytic mechanism of nanozymes are discussed.Third,activity prediction and rational design of nanozymes are focused by highlighting the methods of density functional theory,machine learning,biomimetic and chemical design.Then,synergistic theranostic strategy of nanozymes are introduced.Finally,current challenges and future prospects of nanozymes used for tumor theranostic are outlined,including selectivity,biosafety,repeatability and stability,in-depth catalytic mechanism,predicting and evaluating activities.展开更多
With the full growth of energy needs in the world, several studies are now focused on finding renewable sources. The aim of this work is to optimise biofuel formulation from a mixture design by studying physical prope...With the full growth of energy needs in the world, several studies are now focused on finding renewable sources. The aim of this work is to optimise biofuel formulation from a mixture design by studying physical properties, such as specific gravity and kinematic viscosity of various formulated mixtures. Optimization from the mixture plan revealed that in the chosen experimental domain, the optimal conditions are: 40% for used frying oil (UFO), 50% for bioethanol and 10% for diesel. These experimental conditions lead to a biofuel with a density of 0.84 and a kinematic viscosity of 2.97 cSt. These parameters are compliant with the diesel quality certificate in tropical areas. These density and viscosity values were determined according to respective desirability values of 0.68 and 0.75.展开更多
BACKGROUND Advances in implant material and design have allowed for improvements in total knee arthroplasty(TKA)outcomes.A cruciate retaining(CR)TKA provides the least constraint of TKA designs by preserving the nativ...BACKGROUND Advances in implant material and design have allowed for improvements in total knee arthroplasty(TKA)outcomes.A cruciate retaining(CR)TKA provides the least constraint of TKA designs by preserving the native posterior cruciate ligament.Limited research exists that has examined clinical outcomes or patient reported outcome measures(PROMs)of a large cohort of patients undergoing a CR TKA utilizing a kinematically designed implant.It was hypothesized that the studied CR Knee System would demonstrate favorable outcomes and a clinically significant improvement in pain and functional scores.AIM To assess both short-term and mid-term clinical outcomes and PROMs of a novel CR TKA design.METHODS A retrospective,multi-surgeon study identified 255 knees undergoing a TKA utilizing a kinematically designed CR Knee System(JOURNEY™II CR;Smith and Nephew,Inc.,Memphis,TN)at an urban,academic medical institution between March 2015 and July 2021 with a minimum of two-years of clinical follow-up with an orthopedic surgeon.Patient demographics,surgical information,clinical outcomes,and PROMs data were collected via query of electronic medical records.The PROMs collected in the present study included the Knee Injury and Osteoarthritis Outcome Score for Joint Replacement(KOOS JR)and Patient-Reported Outcomes Measurement Information System(PROMIS■)scores.The significance of improvements in mean PROM scores from preoperative scores to scores collected at six months and two-years postoperatively was analyzed using Independent Samples t-tests.RESULTS Of the 255 patients,65.5%were female,43.8%were White,and patients had an average age of 60.6 years.Primary osteoarthritis(96.9%)was the most common primary diagnosis.The mean surgical time was 105.3 minutes and mean length of stay was 2.1 d with most patients discharged home(92.5%).There were 18 emergency department(ED)visits within 90 d of surgery resulting in a 90 d ED visit rate of 7.1%,including a 2.4%orthopedic-related ED visit rate and a 4.7%non-orthopedic-related ED visit rate.There were three(1.2%)hospital readmissions within 90 d postoperatively.With a mean time to latest follow-up of 3.3 years,four patients(1.6%)required revision,two for arthrofibrosis,one for aseptic femoral loosening,and one for peri-prosthetic joint infection.There were significant improvements in KOOS JR,PROMIS Pain Intensity,PROMIS Pain Interference,PROMIS Mobility,and PROMIS Physical Health from preoperative scores to six month and two-year postoperative scores.CONCLUSION The evaluated implant is an effective,novel design offering excellent outcomes and low complication rates.At a mean follow up of 3.3 years,four patients required revisions,three aseptic and one septic,resulting in an overall implant survival rate of 98.4%and an aseptic survival rate of 98.8%.The results of our study demonstrate the utility of this kinematically designed implant in the setting of primary TKA.展开更多
Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements ...Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements in electrolyte chemistry need to be coupled with optimized electrode materials and tailored electrolyte/electrode interphases.Herein,this review critically outlines electrolytes’limiting factors,including reduced ionic conductivity,large de-solvation energy,sluggish charge transfer,and slow Li-ion transportation across the electrolyte/electrode interphases,which affect the low-temperature performance of Li-metal batteries.Detailed theoretical derivations that explain the explicit influence of temperature on battery performance are presented to deepen understanding.Emerging improvement strategies from the aspects of electrolyte design and electrolyte/electrode interphase engineering are summarized and rigorously compared.Perspectives on future research are proposed to guide the ongoing exploration for better low-temperature Li-metal batteries.展开更多
Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to ...Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy.In this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is developed.Regarding the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is validated.The reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing efficiency.The current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures.展开更多
Mechanical properties of semi-solid casting are dependent on multiple processing parameters,and improper processing parameters will not only reduce mean data but also increase variations.The present study investigated...Mechanical properties of semi-solid casting are dependent on multiple processing parameters,and improper processing parameters will not only reduce mean data but also increase variations.The present study investigated the impact of parameters in slurry preparation and heat treatment on the yield strength and ductility of T6 heat-treated A356 Al-Si alloy using rapid slurry forming(RSF)semi-solid casting.The focus was primarily on the robustness of mechanical properties based on Taguchi design method.By analyzing signal-to-noise ratio and minimum value calculated from-3S,the optimum slurry preparation parameters and heat treatment parameters were determined to be no quench,enthalpy exchange material(EEM)temperature of 140℃,EEM-to-melt ratio of 6mass%,stirring time of 18 s,solution heat treated at 520℃ for 2 h,and ageing heat treated at 190℃ for 6 h.In a small batch validation,the-3S yield strength and-3S elongation reach 256.1 MPa and 5.03% respectively,showing a satisfactory robustness.The hardness and microstructure of heat-treated samples with the best and worst properties were characterized to gain insight into the underlying mechanisms affecting the mean value and variations of mechanical properties.展开更多
Different bilayer structures of HfO_(x)/Ti(TiO_(x)) are designed for hafnium-based memory to investigate the switching characteristics. The chemical states in the films and near the interface are characterized by x-ra...Different bilayer structures of HfO_(x)/Ti(TiO_(x)) are designed for hafnium-based memory to investigate the switching characteristics. The chemical states in the films and near the interface are characterized by x-ray photoelectron spectroscopy,and the oxygen vacancies are analyzed. Highly improved on/off ratio(~104) and much uniform switching parameters are observed for bilayer structures compared to single layer HfO_(x) sample, which can be attributed to the modulation of oxygen vacancies at the interface and better control of the growth of filaments. Furthermore, the reliability of the prepared samples is investigated. The carrier conduction behaviors of HfO_(x)-based samples can be attributed to the trapping and de-trapping process of oxygen vacancies and a filamentary model is proposed. In addition, the rupture of filaments during the reset process for the bilayer structures occur at the weak points near the interface by the recovery of oxygen vacancies accompanied by the variation of barrier height. The re-formation of fixed filaments due to the residual filaments as lightning rods results in the better switching performance of the bilayer structure.展开更多
文摘Refuse landfill plays an important role in daily life,but also brings serious pollution.By investigating environment pollution of Beichen Shuangkou Refuse Landfill in Tianjin City,this paper put forward major problems of this refuse landfill,and suggestions for turning it into a landscape system with regeneration and renewing capacity,so as to provide references for ecological restoration and landscaping of similar damaged land resources.
文摘Due to the lack of restrictions on the exploitation and use of coal mine resources in early China,many wetland lakes were formed because of the changes in geological structure and groundwater overflows,which seriously damaged the land for production and construction.At present,the research on the key technologies and landscape design of water ecosystems and wetland repair in subsidence areas is still insufficient.By analyzing the current situation of thePan'an Lake Wetland,this paper focuses on the strategies of wetland repair and landscape design in this resource-exhausted area.Further,it discusses the enlightenment of these strategies for transforming and planning similar areas in China.
基金supported by the Technology Development Program(S3344882)funded by the Ministry of SMEs and Startups(MSS,Korea).
文摘In the context of high compression rates applied to Joint Photographic Experts Group(JPEG)images through lossy compression techniques,image-blocking artifacts may manifest.This necessitates the restoration of the image to its original quality.The challenge lies in regenerating significantly compressed images into a state in which these become identifiable.Therefore,this study focuses on the restoration of JPEG images subjected to substantial degradation caused by maximum lossy compression using Generative Adversarial Networks(GAN).The generator in this network is based on theU-Net architecture.It features a newhourglass structure that preserves the characteristics of the deep layers.In addition,the network incorporates two loss functions to generate natural and high-quality images:Low Frequency(LF)loss and High Frequency(HF)loss.HF loss uses a pretrained VGG-16 network and is configured using a specific layer that best represents features.This can enhance the performance in the high-frequency region.In contrast,LF loss is used to handle the low-frequency region.The two loss functions facilitate the generation of images by the generator,which can mislead the discriminator while accurately generating high-and low-frequency regions.Consequently,by removing the blocking effects frommaximum lossy compressed images,images inwhich identities could be recognized are generated.This study represents a significant improvement over previous research in terms of the image resolution performance.
基金the National Natural Science Foundation of China and the Natural Science Foundation of Jiangsu Province.It was also supported in part by Young Elite Scientists Sponsorship Program by CAST.
文摘Large cavity structures are widely employed in aerospace engineering, such as thin-walled cylinders, blades andwings. Enhancing performance of aerial vehicles while reducing manufacturing costs and fuel consumptionhas become a focal point for contemporary researchers. Therefore, this paper aims to investigate the topologyoptimization of large cavity structures as a means to enhance their performance, safety, and efficiency. By usingthe variable density method, lightweight design is achieved without compromising structural strength. Theoptimization model considers both concentrated and distributed loads, and utilizes techniques like sensitivityfiltering and projection to obtain a robust optimized configuration. The mechanical properties are checked bycomparing the stress distribution and displacement of the unoptimized and optimized structures under the sameload. The results confirm that the optimized structures exhibit improved mechanical properties, thus offering keyinsights for engineering lightweight, high-strength large cavity structures.
文摘Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve.Such design problems are widely experienced in many engineering fields,such as industry,automotive,construction,machinery,and interdisciplinary research.However,there are established optimization techniques that have shown effectiveness in addressing these types of issues.This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues.The algorithms used in the study are listed as:transient search optimization(TSO),equilibrium optimizer(EO),grey wolf optimizer(GWO),moth-flame optimization(MFO),whale optimization algorithm(WOA),slimemould algorithm(SMA),harris hawks optimization(HHO),chimp optimization algorithm(COA),coot optimization algorithm(COOT),multi-verse optimization(MVO),arithmetic optimization algorithm(AOA),aquila optimizer(AO),sine cosine algorithm(SCA),smell agent optimization(SAO),and seagull optimization algorithm(SOA),pelican optimization algorithm(POA),and coati optimization algorithm(CA).As far as we know,there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems.Hence,a remarkable research guideline is presented in the study for researchersworking in the fields of engineering and artificial intelligence,especiallywhen applying the optimization methods that have emerged recently.Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.
基金This research is supported by the Chinese Special Projects of the National Key Research and Development Plan(2019YFB1405702).
文摘The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product design.This study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge graph.Specifically,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product design.Moreover,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction module.Experimental comparison verified the effectiveness and accuracy of the proposed knowledge extraction model.The case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.
基金supported by the Key R&D Program of Xinjiang Uygur Autonomous Region,China(2022B03021)the Strategic Priority Research Program of Chinese Academy of Sciences(XDA20030101)the Tianshan Talent Training Program of Xinjiang Uygur Autonomous Region,China(2022TSYCLJ0011).
文摘The Aral Sea was the fourth largest lake in the world but it has shrunk dramatically as a result of irrational human activities, triggering the "Aral Sea ecological crisis". The ecological problems of the Aral Sea have attracted widespread attention, and the alleviation of the Aral Sea ecological crisis has reached a consensus among the five Central Asian countries(Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan, and Turkmenistan). In the past decades, many ecological management measures have been implemented for the ecological restoration of the Aral Sea. However, due to the lack of regional planning and zoning, the results are not ideal. In this study, we mapped the ecological zoning of the Aral Sea from the perspective of ecological restoration based on soil type, soil salinity, surface water, groundwater table, Normalized Difference Vegetation Index(NDVI), land cover, and aerosol optical depth(AOD) data. Soil salinization and salt dust are the most prominent ecological problems in the Aral Sea. We divided the Aral Sea into 7 first-level ecological restoration subregions(North Aral Sea catchment area in the downstream of the Syr Darya River(Subregion Ⅰ);artificial flood overflow area in the downstream of the Aral Sea(Subregion Ⅱ);physical/chemical remediation area of the salt dust source area in the eastern part of the South Aral Sea(Subregion Ⅲ);physical/chemical remediation area of severe salinization in the central part of the South Aral Sea(Subregion Ⅳ);existing water surface and potential restoration area of the South Aral Sea(Subregion Ⅴ);Aral Sea vegetation natural recovery area(Subregion Ⅵ);and vegetation planting area with slight salinization in the South Aral Sea(Subregion Ⅶ)) and 14 second-level ecological restoration subregions according to the ecological zoning principles. Implementable measures are proposed for each ecological restoration subregion. For Subregion Ⅰ and Subregion Ⅱ with lower elevations, artificial flooding should be carried out to restore the surface of the Aral Sea. Subregion Ⅲ and Subregion Ⅳ have severe salinization, making it difficult for vegetation to grow. In these subregions, it is recommended to cover and pave the areas with green biomatrix coverings and environmentally sustainable bonding materials. In Subregion Ⅴ located in the central and western parts of the South Aral Sea, surface water recharge should be increased to ensure that this subregion can maintain normal water levels. In Subregion Ⅵ and Subregion Ⅶ where natural conditions are suitable for vegetation growth, measures such as afforestation and buffer zones should be implemented to protect vegetation. This study could provide a reference basis for future comprehensive ecological management and restoration of the Aral Sea.
基金This work is supported by the National Key R&D Program of China(No.2022ZD0117501)the Singapore RIE2020 Advanced Manufacturing and Engineering Programmatic Grant by the Agency for Science,Technology and Research(A*STAR)under grant no.A1898b0043Tsinghua University Initiative Scientific Research Program and Low Carbon En-ergy Research Funding Initiative by A*STAR under grant number A-8000182-00-00.
文摘Membrane technologies are becoming increasingly versatile and helpful today for sustainable development.Machine Learning(ML),an essential branch of artificial intelligence(AI),has substantially impacted the research and development norm of new materials for energy and environment.This review provides an overview and perspectives on ML methodologies and their applications in membrane design and dis-covery.A brief overview of membrane technologies isfirst provided with the current bottlenecks and potential solutions.Through an appli-cations-based perspective of AI-aided membrane design and discovery,we further show how ML strategies are applied to the membrane discovery cycle(including membrane material design,membrane application,membrane process design,and knowledge extraction),in various membrane systems,ranging from gas,liquid,and fuel cell separation membranes.Furthermore,the best practices of integrating ML methods and specific application targets in membrane design and discovery are presented with an ideal paradigm proposed.The challenges to be addressed and prospects of AI applications in membrane discovery are also highlighted in the end.
基金Project supported by the National Natural Science Foundation of China(Grant No.62101600)the Science Foundation of China University of Petroleum,Beijing(Grant No.2462021YJRC008)the State Key Laboratory of Cryptology(Grant No.MMKFKT202109).
文摘Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete problems.This paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected graphs.To expedite the search process,a quantum algorithm employing Grover’s search is proposed.However,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search impossible.Thus,a swap test method is introduced to ascertain the number of iterations required.The oracle,diffusion operators,and swap test are designed with achievable quantum gates.The query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.
基金supported by the National Natural the Science Foundation of China(51971042,51901028)the Chongqing Academician Special Fund(cstc2020yszxjcyj X0001)+1 种基金the China Scholarship Council(CSC)Norwegian University of Science and Technology(NTNU)for their financial and technical support。
文摘Magnesium(Mg),being the lightest structural metal,holds immense potential for widespread applications in various fields.The development of high-performance and cost-effective Mg alloys is crucial to further advancing their commercial utilization.With the rapid advancement of machine learning(ML)technology in recent years,the“data-driven''approach for alloy design has provided new perspectives and opportunities for enhancing the performance of Mg alloys.This paper introduces a novel regression-based Bayesian optimization active learning model(RBOALM)for the development of high-performance Mg-Mn-based wrought alloys.RBOALM employs active learning to automatically explore optimal alloy compositions and process parameters within predefined ranges,facilitating the discovery of superior alloy combinations.This model further integrates pre-established regression models as surrogate functions in Bayesian optimization,significantly enhancing the precision of the design process.Leveraging RBOALM,several new high-performance alloys have been successfully designed and prepared.Notably,after mechanical property testing of the designed alloys,the Mg-2.1Zn-2.0Mn-0.5Sn-0.1Ca alloy demonstrates exceptional mechanical properties,including an ultimate tensile strength of 406 MPa,a yield strength of 287 MPa,and a 23%fracture elongation.Furthermore,the Mg-2.7Mn-0.5Al-0.1Ca alloy exhibits an ultimate tensile strength of 211 MPa,coupled with a remarkable 41%fracture elongation.
基金supported by the National Natural Science Foundation of China(Nos.82272504 and 82072456)the National Key R&D Program of China(No.2018YFB1105100)+4 种基金the Department of Science and Technology of Jilin Province,China(Nos.20200404202YY,20200403086SF,20210101321JC,20210204104YY,20200201453JC,20220204119YY,202201ZYTS131,202201ZYTS129,20220401084YY,202201ZYTS505,and YDZJ202301ZYTS076)the Department of Finance of Jilin Province,China(No.2020SCZT037)the Jilin Provincial Development and Reform Commission,China(Nos.2018C010 and 2022C043-5)the Interdisciplinary Integration and Cultivation Project of Jilin University(No.JLUXKJC2020307)the Central University Basic Scientific Research Fund(No.2023-JCXK-04).
文摘Bone screws are devices used to fix implants or bones to bones.However,conventional screws are mechanically fixed with thread and often face long-term failure due to poor osseointegration.To improve osseointegration,screws are evolving from solid and smooth to porous and rough.Additive manufacturing(AM)offers a high degree of manufacturing freedom,enabling the preparation of predesigned screws that are porous and rough.This paper provides an overview of the problems currently faced by bone screws:long-term loosening and screw breakage.Next,advances in osseointegrated screws are summarized hierarchically(sub-micro,micro,and macro).At the sub-microscale level,we describe surface-modification techniques for enhancing osseointegration.At the micro level,we summarize the micro-design parameters that affect the mechanical and biological properties of porous osseointegrated screws,including porosity,pore size,and pore shape.In addition,we highlight three promising pore shapes:triply periodic minimal surface,auxetic structure with negative Poisson ratio,and the Voronoi structure.At the macro level,we outline the strategies of graded design,gradient design,and topology optimization design to improve the mechanical strength of porous osseointegrated screws.Simultaneously,this paper outlines advances in AM technology for enhancing the mechanical properties of porous osseointegrated screws.AM osseointegrated screws with hierarchical design are expected to provide excellent long-term fixation and the required mechanical strength.
基金S.G.acknowledges the financial support from the National Natural Science Foundation of China(NSFC 52272144,51972076)the Heilongjiang Provincial Natural Science Foundation of China(JQ2022E001)+4 种基金the Natural Science Foundation of Shandong Province(ZR2020ZD42)the Fundamental Research Funds for the Central Universities.H.D.acknowledges the financial support from the National Natural Science Foundation of China(NSFC 22205048)China Postdoctoral Science Foundation(2022M710931 and 2023T160154)Heilongjiang Postdoctoral Science Foundation(LBH-Z22010)G.Y.acknowledges the financial support from the National Science Foundation of Heilongjiang Education Department(324022075).
文摘Since the discovery of enzyme-like activity of Fe3O4 nanoparticles in 2007,nanozymes are becoming the promising substitutes for natural enzymes due to their advantages of high catalytic activity,low cost,mild reaction conditions,good stability,and suitable for large-scale production.Recently,with the cross fusion of nanomedicine and nanocatalysis,nanozyme-based theranostic strategies attract great attention,since the enzymatic reactions can be triggered in the tumor microenvironment to achieve good curative effect with substrate specificity and low side effects.Thus,various nanozymes have been developed and used for tumor therapy.In this review,more than 270 research articles are discussed systematically to present progress in the past five years.First,the discovery and development of nanozymes are summarized.Second,classification and catalytic mechanism of nanozymes are discussed.Third,activity prediction and rational design of nanozymes are focused by highlighting the methods of density functional theory,machine learning,biomimetic and chemical design.Then,synergistic theranostic strategy of nanozymes are introduced.Finally,current challenges and future prospects of nanozymes used for tumor theranostic are outlined,including selectivity,biosafety,repeatability and stability,in-depth catalytic mechanism,predicting and evaluating activities.
文摘With the full growth of energy needs in the world, several studies are now focused on finding renewable sources. The aim of this work is to optimise biofuel formulation from a mixture design by studying physical properties, such as specific gravity and kinematic viscosity of various formulated mixtures. Optimization from the mixture plan revealed that in the chosen experimental domain, the optimal conditions are: 40% for used frying oil (UFO), 50% for bioethanol and 10% for diesel. These experimental conditions lead to a biofuel with a density of 0.84 and a kinematic viscosity of 2.97 cSt. These parameters are compliant with the diesel quality certificate in tropical areas. These density and viscosity values were determined according to respective desirability values of 0.68 and 0.75.
文摘BACKGROUND Advances in implant material and design have allowed for improvements in total knee arthroplasty(TKA)outcomes.A cruciate retaining(CR)TKA provides the least constraint of TKA designs by preserving the native posterior cruciate ligament.Limited research exists that has examined clinical outcomes or patient reported outcome measures(PROMs)of a large cohort of patients undergoing a CR TKA utilizing a kinematically designed implant.It was hypothesized that the studied CR Knee System would demonstrate favorable outcomes and a clinically significant improvement in pain and functional scores.AIM To assess both short-term and mid-term clinical outcomes and PROMs of a novel CR TKA design.METHODS A retrospective,multi-surgeon study identified 255 knees undergoing a TKA utilizing a kinematically designed CR Knee System(JOURNEY™II CR;Smith and Nephew,Inc.,Memphis,TN)at an urban,academic medical institution between March 2015 and July 2021 with a minimum of two-years of clinical follow-up with an orthopedic surgeon.Patient demographics,surgical information,clinical outcomes,and PROMs data were collected via query of electronic medical records.The PROMs collected in the present study included the Knee Injury and Osteoarthritis Outcome Score for Joint Replacement(KOOS JR)and Patient-Reported Outcomes Measurement Information System(PROMIS■)scores.The significance of improvements in mean PROM scores from preoperative scores to scores collected at six months and two-years postoperatively was analyzed using Independent Samples t-tests.RESULTS Of the 255 patients,65.5%were female,43.8%were White,and patients had an average age of 60.6 years.Primary osteoarthritis(96.9%)was the most common primary diagnosis.The mean surgical time was 105.3 minutes and mean length of stay was 2.1 d with most patients discharged home(92.5%).There were 18 emergency department(ED)visits within 90 d of surgery resulting in a 90 d ED visit rate of 7.1%,including a 2.4%orthopedic-related ED visit rate and a 4.7%non-orthopedic-related ED visit rate.There were three(1.2%)hospital readmissions within 90 d postoperatively.With a mean time to latest follow-up of 3.3 years,four patients(1.6%)required revision,two for arthrofibrosis,one for aseptic femoral loosening,and one for peri-prosthetic joint infection.There were significant improvements in KOOS JR,PROMIS Pain Intensity,PROMIS Pain Interference,PROMIS Mobility,and PROMIS Physical Health from preoperative scores to six month and two-year postoperative scores.CONCLUSION The evaluated implant is an effective,novel design offering excellent outcomes and low complication rates.At a mean follow up of 3.3 years,four patients required revisions,three aseptic and one septic,resulting in an overall implant survival rate of 98.4%and an aseptic survival rate of 98.8%.The results of our study demonstrate the utility of this kinematically designed implant in the setting of primary TKA.
基金The work described in this paper was fully supported by a Grant from the City University of Hong Kong(Project No.9610641).
文摘Electrolyte design holds the greatest opportunity for the development of batteries that are capable of sub-zero temperature operation.To get the most energy storage out of the battery at low temperatures,improvements in electrolyte chemistry need to be coupled with optimized electrode materials and tailored electrolyte/electrode interphases.Herein,this review critically outlines electrolytes’limiting factors,including reduced ionic conductivity,large de-solvation energy,sluggish charge transfer,and slow Li-ion transportation across the electrolyte/electrode interphases,which affect the low-temperature performance of Li-metal batteries.Detailed theoretical derivations that explain the explicit influence of temperature on battery performance are presented to deepen understanding.Emerging improvement strategies from the aspects of electrolyte design and electrolyte/electrode interphase engineering are summarized and rigorously compared.Perspectives on future research are proposed to guide the ongoing exploration for better low-temperature Li-metal batteries.
基金supported by the National Natural Science Foundation of China under Grant(Number:52105136)the Hong Kong Scholar program under Grant(Number:XJ2022013)China Postdoctoral Science Foundation under Grant(Number:2021M690290)Academic Excellence Foundation of BUAA under Grant(Number:BY2004103).
文摘Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy.In this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is developed.Regarding the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is validated.The reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing efficiency.The current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures.
文摘Mechanical properties of semi-solid casting are dependent on multiple processing parameters,and improper processing parameters will not only reduce mean data but also increase variations.The present study investigated the impact of parameters in slurry preparation and heat treatment on the yield strength and ductility of T6 heat-treated A356 Al-Si alloy using rapid slurry forming(RSF)semi-solid casting.The focus was primarily on the robustness of mechanical properties based on Taguchi design method.By analyzing signal-to-noise ratio and minimum value calculated from-3S,the optimum slurry preparation parameters and heat treatment parameters were determined to be no quench,enthalpy exchange material(EEM)temperature of 140℃,EEM-to-melt ratio of 6mass%,stirring time of 18 s,solution heat treated at 520℃ for 2 h,and ageing heat treated at 190℃ for 6 h.In a small batch validation,the-3S yield strength and-3S elongation reach 256.1 MPa and 5.03% respectively,showing a satisfactory robustness.The hardness and microstructure of heat-treated samples with the best and worst properties were characterized to gain insight into the underlying mechanisms affecting the mean value and variations of mechanical properties.
基金financially supported by the National Natural Science Foundation of China (Grant No.51802025)the Natural Science Basic Research Plan in Shaanxi Province of China (Grant No.2020JQ-384)。
文摘Different bilayer structures of HfO_(x)/Ti(TiO_(x)) are designed for hafnium-based memory to investigate the switching characteristics. The chemical states in the films and near the interface are characterized by x-ray photoelectron spectroscopy,and the oxygen vacancies are analyzed. Highly improved on/off ratio(~104) and much uniform switching parameters are observed for bilayer structures compared to single layer HfO_(x) sample, which can be attributed to the modulation of oxygen vacancies at the interface and better control of the growth of filaments. Furthermore, the reliability of the prepared samples is investigated. The carrier conduction behaviors of HfO_(x)-based samples can be attributed to the trapping and de-trapping process of oxygen vacancies and a filamentary model is proposed. In addition, the rupture of filaments during the reset process for the bilayer structures occur at the weak points near the interface by the recovery of oxygen vacancies accompanied by the variation of barrier height. The re-formation of fixed filaments due to the residual filaments as lightning rods results in the better switching performance of the bilayer structure.
