Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening pa...Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
This study systematically investigates the hot deformation behavior and microstructural evolution of CoNiV medium-entropy alloy(MEA)in the temperature range of 950-1100℃ and strain rates of 0.001-1 s^(-1).The Arrheni...This study systematically investigates the hot deformation behavior and microstructural evolution of CoNiV medium-entropy alloy(MEA)in the temperature range of 950-1100℃ and strain rates of 0.001-1 s^(-1).The Arrhenius model and machine learning model were developed to forecast flow stresses at various conditions.The predictive capability of both models was assessed using the coefficients of determination(R^(2)),average absolute relative error(AARE),and root mean square error(RMSE).The findings show that the osprey optimization algorithm convolutional neural network(OOA-CNN)model outperforms the Arrhenius model,achieving a high R^(2) value of 0.99959 and lower AARE and RMSE values.The flow stress that the OOA-CNN model predicted was used to generate power dissipation maps and instability maps under different strains.Finally,combining the processing map and microstructure characterization,the ideal processing domain was identified as 1100℃ at strain rates of 0.01-0.1 s^(-1).This study provided key insights into optimizing the hot working process of CoNiV MEA.展开更多
[Objective] The research aimed to study the yield prediction model of processing tomato based on the grey system theory.[Method] The variation trend of processing tomato yield was studied by using the grey system theo...[Objective] The research aimed to study the yield prediction model of processing tomato based on the grey system theory.[Method] The variation trend of processing tomato yield was studied by using the grey system theory,and GM（1,1）grey model of processing tomato yield prediction was established.The processing tomato yield in Xinjiang during 2001-2009 was as the example to carry out the instance analysis.[Result] The model had the high forecast accuracy and strong generalization ability,and was reliable for the prediction of recent processing tomato yield.[Conclusion] The research provided the reference for the macro-control of tomato industry,the processing and storage of tomato in Xinjiang.展开更多
The development of techniques to control and use materials, especially metallic materials continues to play a key role in the technological advancement of modem day society. A variety of materials processes have been ...The development of techniques to control and use materials, especially metallic materials continues to play a key role in the technological advancement of modem day society. A variety of materials processes have been developed overtime, and are applied to design and fabricate products. Heat treatment of metallic materials has been the method of choice applied to improve mechanical properties such as strength, hardness, and toughness, as well as to improve the homogeneity of properties in materials such as corrosion resistance. The molt significant success stories in the application of materials processes involve the heat-treatment of steel. The reasons for this largely lie in the ease with which steel microstructures can be altered by controlled heating and cooling. The objective of computer modeling of materials processes is to maximize on the beneficial factors while keeping to a minimum the negating effects such as components distortion and residual stresses. Computer modeling is a powerful tool in achieving this objective in the sense that with it, the effect of parameters associated with materials processes can be analyzed systematically in order to optimize them before actual production begins.展开更多
With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process...With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.展开更多
Peanut protein is easily digested and absorbed by the human body,and peanut tofu does not contain flatulence factors and beany flour.However,at present,there is no industrial preparation process of peanut tofu,whereas...Peanut protein is easily digested and absorbed by the human body,and peanut tofu does not contain flatulence factors and beany flour.However,at present,there is no industrial preparation process of peanut tofu,whereas the quality of tofu prepared by different peanut varieties is quite different.This study established an industrial feasible production process of peanut tofu and optimized the key process that regulates its quality.Compared with the existing method,the production time is reduced by 53.80%,therefore the daily production output is increased by 183.33%.The chemical properties of 26 peanut varieties and the quality characteristics of tofu prepared from these 26 varieties were determined.The peanut varieties were classified based on the quality characteristics of tofu using the hierarchical cluster analysis(HCA)method,out of which 7 varieties were screened out which were suitable for preparing peanut tofu.An evaluation standard was founded based on peanut tofu qualities.Six chemical trait indexes were correlated with peanut tofu qualities(P<0.05).A logistic regressive model was developed to predict suitable peanut varieties and this prediction model was verified.This study may help broaden the peanut protein utilization,and provide guidance for breeding experts to select certain varieties for product specific cultivation of peanut.展开更多
Isothermal compression experiments were conducted to study the hot deformation behaviors of a Sr-modified Al-Si-Mg alloy in the temperature range of 300-420°C and strain rate range of 0.01-10 s-1.A physically-bas...Isothermal compression experiments were conducted to study the hot deformation behaviors of a Sr-modified Al-Si-Mg alloy in the temperature range of 300-420°C and strain rate range of 0.01-10 s-1.A physically-based model was developed to accurately predict the flow stress.Meanwhile,processing maps were established to optimize hot working parameters.It is found that decreasing the strain rate or increasing the deformation temperature reduces the flow stress.The high activation energy is closely related to the pinning of dislocations from Si-containing dispersoids.Moreover,the deformed grains and the Si-containing dispersoids in the matrix are elongated perpendicular to the compression direction,and incomplete dynamic recrystallization(DRX)is discovered on the elongated boundaries in domain with peak efficiency.The flow instability is mainly attributed to the flow localization,brittle fracture of eutectic Si phase,and formation of adiabatic shear band.The optimum hot working window is 380-420°C and 0.03-0.28 s-1.展开更多
Titanium has been widely used as the implant materials of joint prostheses. This paper simulates the microstructures of the hot forged titanium knee joint component by physical modeling. Ti-6Al-4V ELI were deformed b...Titanium has been widely used as the implant materials of joint prostheses. This paper simulates the microstructures of the hot forged titanium knee joint component by physical modeling. Ti-6Al-4V ELI were deformed by GLEEBLE 2000 hot deforma- tion simulator in compression mode to determine the hot workability, in the range of 900 to 1100℃, with the strain rates between 0.05 to 5 s^(-1). Test results derived from specimens processed by on-cooling test and on-heating test were compared, thereby estimating the effect due to thermal history. The forging process of Ti-6Al-4V ELI tibial base plate of knee joint prostheses was design based on the workability data obtained.展开更多
The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so t...The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.展开更多
General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has ...General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.展开更多
The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented...The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented. Two image algorithms are developed: template-based automatic target recognition and zone labeling. One is estimating for motion direction in the infrared image background, another is line picking-up algorithm based on image zone labeling and phase grouping technique. It is a kind of 'hardware' function that can be called by the DSP in high-level algorithm. It is also a kind of hardware algorithm of the DSP. The results of experiments show the reconfigurable computing technology based on RMP is an ideal accelerating means to deal with the high-speed image processing tasks. High real time performance is obtained in our two applications on RMP.展开更多
A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary ...A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary micro-variables evolution at different temperatures and their interaction.The dislocation density was incorporated into the model to capture the effect of creep deformation on precipitation.Quantitative transmission electron microscopy and experimental data obtained from a previous study were used to calibrate the model.Subsequently,the developed constitutive model was implemented in the finite element(FE)software ABAQUS via the user subroutines for TSCA process simulation and the springback prediction of an integral panel.A TSCA test was performed.The result shows that the maximum radius deviation between the formed plate and the simulation results is less than 0.4 mm,thus validating the effectiveness of the developed constitutive model and FE model.展开更多
The isothermal compression test for Ti-6Al-7Nb alloy was conducted by using Gleeble-3800 thermal simulator.The hot deformation behavior of Ti-6Al-7Nb alloy was investigated in the deformation temperature ranges of 940...The isothermal compression test for Ti-6Al-7Nb alloy was conducted by using Gleeble-3800 thermal simulator.The hot deformation behavior of Ti-6Al-7Nb alloy was investigated in the deformation temperature ranges of 940-1030℃and the strain rate ranges of 0.001-10 s^(-1).Meanwhile,the activation energy of thermal deformation was computed.The results show that the flow stress of Ti-6Al-7Nb alloy increases with increasing the strain rate and decreasing the deformation temperature.The activation energy of thermal deformation for Ti-6Al-7Nb alloy is much greater than that for self-diffusion ofα-Ti andβ-Ti.Considering the influence of strain on flow stress,the strain-compensated Arrhenius constitutive model of Ti-6Al-7Nb alloy was established.The error analysis shows that the model has higher accuracy,and the correlation coefficient r and average absolute relative error are 0.9879 and 4.11%,respectively.The processing map(PM)of Ti-6Al-7Nb alloy was constructed by the dynamic materials model and Prasad instability criterion.According to PM and microstructural observation,it is found that the main form of instability zone is local flow,and the deformation mechanisms of the stable zone are mainly superplasticity and dynamic recrystallization.The optimal processing parameters of Ti-6Al-7Nb alloy are determined as follows:960-995℃/0.01-0.18 s^(-1)and 1000-1030℃/0.001-0.01 s^(-1).展开更多
We present a method for computed tomography(CT)image processing and modeling for tibia microstructure,achieved by using computer graphics and fractal theory.Given the large-scale image data of tibia species with DICOM...We present a method for computed tomography(CT)image processing and modeling for tibia microstructure,achieved by using computer graphics and fractal theory.Given the large-scale image data of tibia species with DICOM standard for clinical applications,we take advantage of algorithms such as image binarization,hot pixel removing and close operation to obtain visually clear image for tibia microstructure.All of these images are based on 20 CT scanning images with 30μm slice thickness and 30μm interval and continuous changes in pores.For each pore,we determine its profile by using an improved algorithm for edge detection.Then,to calculate its three-dimensional fractal dimension,we measure the circumference perimeter and area of the pores of bone microstructure using a line fitting method based on the least squares.Subsequently,we put forward an algorithm for the pore profiles through ellipse fitting.The results show that the pores have significant fractal characteristics because of the good linear correlation between the perimeter and the area parameters in log–log scale coordinates system,and the ratio of the elliptical short axis to the long axis through ellipse fitting tends to 0.6501.Based on support vector machine and structural risk minimization principle,we put forward a mapping database theory of structure parameters among the pores of CT images and fractal dimension,Poisson’s ratios,porosity and equivalent aperture.On this basis,we put forward a new concept for 3D modeling called precision-measuring digital expressing to reconstruct tibia microstructure for human hard tissue.展开更多
Ultra-wideband （UWB） microwave imaging is a promising method for breast cancer detection based on the large contrast of electric parameters between the malignant tumor and its surrounded normal breast organisms. In ...Ultra-wideband （UWB） microwave imaging is a promising method for breast cancer detection based on the large contrast of electric parameters between the malignant tumor and its surrounded normal breast organisms. In the case of multiple tumors being present, the conventional imaging approaches may be ineffective to detect all the tumors clearly. In this paper, a progressive processing method is proposed for detecting more than one tumor. The method is divided into three stages： primary detection, refocusing and image optimization. To test the feasibility of the approach, a numerical breast model is developed based on the realistic magnetic resonance image （MRI）. Two tumors are assumed embedded in different positions. Successful detection of a 3.6 mm-diameter tumor at a depth of 42 mm is achieved. The correct information of both tumors is shown in the reconstructed image, suggesting that the progressive processing method is promising for multi-tumor detection.展开更多
The aim of this study is to develop processing maps based on two models and compare them with conventional processing maps.The hyperbolic sinus constitutive equation and artificial neural network(ANN)approaches were u...The aim of this study is to develop processing maps based on two models and compare them with conventional processing maps.The hyperbolic sinus constitutive equation and artificial neural network(ANN)approaches were used in this investigation to predict flow stress and to develop processing maps in various conditions.The hot compression tests of InX-750 superalloy were carried out above the gamma prime phase temperature and within the temperature range of 1000-1150℃and strain rate of 0.001-1.000 s^(-1).The processing maps were conducted based upon dynamic material model(DMM)for data by experimental,constitutive equation and ANN approaches.The processing maps drawn by either of the prediction methods show that the method developed by ANN data does not significantly differ from the experimental processing map.The ANN approach is thus a suitable way to predict the flow stress as well as hot working processing map of engineering metals and materials.展开更多
The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same ...The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same period, workflow management has experienced significant development, but has become more focused on the industry. However, it seems to us that document workflows have not had the same interest for the scientific community. But nowadays, the emergence and supremacy of the Internet in electronic exchanges are leading to a massive dematerialization of documents;which requires a conceptual reconsideration of the organizational framework for the processing of said documents in both public and private administrations. This problem seems open to us and deserves the interest of the scientific community. Indeed, EDM has mainly focused on the storage (referencing) and circulation of documents (traceability). It paid little attention to the overall behavior of the system in processing documents. The purpose of our researches is to model document processing systems. In the previous works, we proposed a general model and its specialization in the case of small documents (any document processed by a single person at a time during its processing life cycle), which represent 70% of documents processed by administrations, according to our study. In this contribution, we extend the model for processing small documents to the case where they are managed in a system comprising document classes organized in subclasses;which is the case for most administrations. We have thus observed that this model is a Markovian <i>M<sup>L×K</sup>/M<sup>L×K</sup>/</i>1 queues network. We have analyzed the constraints of this model and deduced certain characteristics and metrics. <span style="white-space:normal;"><i></i></span><i>In fine<span style="white-space:normal;"></span></i>, the ultimate objective of our work is to design a document workflow management system, integrating a component of global behavior prediction.展开更多
Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely used...Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely usedin model copyright protection, but there are two challenges: (1) designinguniversal trigger sample watermarking for different network models is stilla challenge;(2) existing methods of copyright protection based on trigger swatermarking are difficult to resist forgery attacks. In this work, we propose adual model watermarking framework for copyright protection in image processingnetworks. The trigger sample watermark is embedded in the trainingprocess of the model, which can effectively verify the model copyright. And wedesign a common method for generating trigger sample watermarks based ongenerative adversarial networks, adaptively generating trigger sample watermarksaccording to different models. The spatial watermark is embedded intothe model output. When an attacker steals model copyright using a forgedtrigger sample watermark, which can be correctly extracted to distinguishbetween the piratical and the protected model. The experiments show that theproposed framework has good performance in different image segmentationnetworks of UNET, UNET++, and FCN (fully convolutional network), andeffectively resists forgery attacks.展开更多
Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective...Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective Coriolis condition,the velocity component parallel to the rotational axis exerts no influence on the magnitude of Coriolis acceleration.This circumstance implies a potential mitigation of the Coriolis force's deflective impact.Regrettably,extant investigations predominantly emphasize the dilative and compressive Coriolis effects,largely neglecting the pragmatic import of the deflective Coriolis condition.In pursuit of this gap,a series of discrete element method(DEM)simulations have been conducted to scrutinize the feasibility of centrifugal modelling for dry granular run-out processes under deflective Coriolis conditions.The findings concerning the deflective Coriolis effect reveal a consistent rise in the run-out distance by 2%–16%,a modest increase in bulk flow velocity of under 4%,and a slight elevation in average flow depth by no more than 25%.These alterations display smaller dependence on the specific testing conditions due to the granular flow undergoing dual deflections in opposing directions.This underscores the significance and utility of the deflective Coriolis condition.Notably,the anticipated reduction in error in predicting the final run-out distance is substantial,potentially reaching a 150%improvement compared to predictions made under the dilative and compressive Coriolis conditions.Therefore,the deflective Coriolis condition is advised when the final run-out distance of the granular flow is the main concern.To mitigate the impact of Coriolis acceleration,a greater initial height of the granular column is recommended,with a height/width ratio exceeding 1,as the basal friction of the granular material plays a crucial role in mitigating the deflective Coriolis effect.For more transverse-uniform flow properties,the width of the granular column should be as large as possible.展开更多
基金financial support of the National Natural Science Foundation of China(No.52371103)the Fundamental Research Funds for the Central Universities,China(No.2242023K40028)+1 种基金the Open Research Fund of Jiangsu Key Laboratory for Advanced Metallic Materials,China(No.AMM2023B01).financial support of the Research Fund of Shihezi Key Laboratory of AluminumBased Advanced Materials,China(No.2023PT02)financial support of Guangdong Province Science and Technology Major Project,China(No.2021B0301030005)。
文摘Oxide dispersion strengthened(ODS)alloys are extensively used owing to high thermostability and creep strength contributed from uniformly dispersed fine oxides particles.However,the existence of these strengthening particles also deteriorates the processability and it is of great importance to establish accurate processing maps to guide the thermomechanical processes to enhance the formability.In this study,we performed particle swarm optimization-based back propagation artificial neural network model to predict the high temperature flow behavior of 0.25wt%Al2O3 particle-reinforced Cu alloys,and compared the accuracy with that of derived by Arrhenius-type constitutive model and back propagation artificial neural network model.To train these models,we obtained the raw data by fabricating ODS Cu alloys using the internal oxidation and reduction method,and conducting systematic hot compression tests between 400 and800℃with strain rates of 10^(-2)-10 S^(-1).At last,processing maps for ODS Cu alloys were proposed by combining processing parameters,mechanical behavior,microstructure characterization,and the modeling results achieved a coefficient of determination higher than>99%.
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
基金supported by the National Natural Science Foundation of China(NSFC)(Grant No.51901078)the Central Guidance for Local Scientific and Technological Development Funding Project(Grant No.236Z1003G)+3 种基金the Science and Technology Plan Project of Tangshan City(Grant No.24130207C)the Natural Science Foundation of Hebei Province(Grant No.E2022209070)the High-level Talent Project of Hebei(Grant No.E2019100007)the Open Project Program of Key Laboratory of Ministry of Education for Modern Metallurgy Technology(Grant No.2024YJKF02).
文摘This study systematically investigates the hot deformation behavior and microstructural evolution of CoNiV medium-entropy alloy(MEA)in the temperature range of 950-1100℃ and strain rates of 0.001-1 s^(-1).The Arrhenius model and machine learning model were developed to forecast flow stresses at various conditions.The predictive capability of both models was assessed using the coefficients of determination(R^(2)),average absolute relative error(AARE),and root mean square error(RMSE).The findings show that the osprey optimization algorithm convolutional neural network(OOA-CNN)model outperforms the Arrhenius model,achieving a high R^(2) value of 0.99959 and lower AARE and RMSE values.The flow stress that the OOA-CNN model predicted was used to generate power dissipation maps and instability maps under different strains.Finally,combining the processing map and microstructure characterization,the ideal processing domain was identified as 1100℃ at strain rates of 0.01-0.1 s^(-1).This study provided key insights into optimizing the hot working process of CoNiV MEA.
基金Supported by National Natural Science Fund Item(61064005)~~
文摘[Objective] The research aimed to study the yield prediction model of processing tomato based on the grey system theory.[Method] The variation trend of processing tomato yield was studied by using the grey system theory,and GM（1,1）grey model of processing tomato yield prediction was established.The processing tomato yield in Xinjiang during 2001-2009 was as the example to carry out the instance analysis.[Result] The model had the high forecast accuracy and strong generalization ability,and was reliable for the prediction of recent processing tomato yield.[Conclusion] The research provided the reference for the macro-control of tomato industry,the processing and storage of tomato in Xinjiang.
文摘The development of techniques to control and use materials, especially metallic materials continues to play a key role in the technological advancement of modem day society. A variety of materials processes have been developed overtime, and are applied to design and fabricate products. Heat treatment of metallic materials has been the method of choice applied to improve mechanical properties such as strength, hardness, and toughness, as well as to improve the homogeneity of properties in materials such as corrosion resistance. The molt significant success stories in the application of materials processes involve the heat-treatment of steel. The reasons for this largely lie in the ease with which steel microstructures can be altered by controlled heating and cooling. The objective of computer modeling of materials processes is to maximize on the beneficial factors while keeping to a minimum the negating effects such as components distortion and residual stresses. Computer modeling is a powerful tool in achieving this objective in the sense that with it, the effect of parameters associated with materials processes can be analyzed systematically in order to optimize them before actual production begins.
基金supported by the National Natural Science Foundation of China(62225302,623B2014,and 62173023).
文摘With the emergence of general foundational models,such as Chat Generative Pre-trained Transformer(ChatGPT),researchers have shown considerable interest in the potential applications of foundation models in the process industry.This paper provides a comprehensive overview of the challenges and opportunities presented by the use of foundation models in the process industry,including the frameworks,core applications,and future prospects.First,this paper proposes a framework for foundation models for the process industry.Second,it summarizes the key capabilities of industrial foundation models and their practical applications.Finally,it highlights future research directions and identifies unresolved open issues related to the use of foundation models in the process industry.
基金This study was supported by the earmarked fund for China Agriculture Research System(CARS-13-03A)the Corps Science and Technology Development Special Promotion Achievement Transformation Guidance Plan,Xinjiang,China(2018BCO12)the TaiShan Industrial Experts Programme,China(LJNY201711).
文摘Peanut protein is easily digested and absorbed by the human body,and peanut tofu does not contain flatulence factors and beany flour.However,at present,there is no industrial preparation process of peanut tofu,whereas the quality of tofu prepared by different peanut varieties is quite different.This study established an industrial feasible production process of peanut tofu and optimized the key process that regulates its quality.Compared with the existing method,the production time is reduced by 53.80%,therefore the daily production output is increased by 183.33%.The chemical properties of 26 peanut varieties and the quality characteristics of tofu prepared from these 26 varieties were determined.The peanut varieties were classified based on the quality characteristics of tofu using the hierarchical cluster analysis(HCA)method,out of which 7 varieties were screened out which were suitable for preparing peanut tofu.An evaluation standard was founded based on peanut tofu qualities.Six chemical trait indexes were correlated with peanut tofu qualities(P<0.05).A logistic regressive model was developed to predict suitable peanut varieties and this prediction model was verified.This study may help broaden the peanut protein utilization,and provide guidance for breeding experts to select certain varieties for product specific cultivation of peanut.
基金Project(51375502)supported by the National Natural Science Foundation of ChinaProject(2015CX002)supported by the Innovation-driven Plan in Central South University,China+2 种基金Project(2016RS2006)supported by the Science and Technology Leading Talent in Hunan Province,ChinaProject(Q2015140)supported by the Program of Chang Jiang Scholars of Ministry of Education,ChinaProject(2016JJ1017)supported by the Natural Science Foundation for Distinguished Young Scholars of Hunan Province,China
文摘Isothermal compression experiments were conducted to study the hot deformation behaviors of a Sr-modified Al-Si-Mg alloy in the temperature range of 300-420°C and strain rate range of 0.01-10 s-1.A physically-based model was developed to accurately predict the flow stress.Meanwhile,processing maps were established to optimize hot working parameters.It is found that decreasing the strain rate or increasing the deformation temperature reduces the flow stress.The high activation energy is closely related to the pinning of dislocations from Si-containing dispersoids.Moreover,the deformed grains and the Si-containing dispersoids in the matrix are elongated perpendicular to the compression direction,and incomplete dynamic recrystallization(DRX)is discovered on the elongated boundaries in domain with peak efficiency.The flow instability is mainly attributed to the flow localization,brittle fracture of eutectic Si phase,and formation of adiabatic shear band.The optimum hot working window is 380-420°C and 0.03-0.28 s-1.
文摘Titanium has been widely used as the implant materials of joint prostheses. This paper simulates the microstructures of the hot forged titanium knee joint component by physical modeling. Ti-6Al-4V ELI were deformed by GLEEBLE 2000 hot deforma- tion simulator in compression mode to determine the hot workability, in the range of 900 to 1100℃, with the strain rates between 0.05 to 5 s^(-1). Test results derived from specimens processed by on-cooling test and on-heating test were compared, thereby estimating the effect due to thermal history. The forging process of Ti-6Al-4V ELI tibial base plate of knee joint prostheses was design based on the workability data obtained.
基金Project 70533050 supported by the National Natural Science Foundation of China
文摘The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.
基金supported by the National Natural Science Foundation of China (Nos 40974066 and 40821062)National Basic Research Program of China (No 2007CB209602)
文摘General purpose graphic processing unit （GPU） calculation technology is gradually widely used in various fields. Its mode of single instruction, multiple threads is capable of seismic numerical simulation which has a huge quantity of data and calculation steps. In this study, we introduce a GPU-based parallel calculation method of a precise integration method （PIM） for seismic forward modeling. Compared with CPU single-core calculation, GPU parallel calculating perfectly keeps the features of PIM, which has small bandwidth, high accuracy and capability of modeling complex substructures, and GPU calculation brings high computational efficiency, which means that high-performing GPU parallel calculation can make seismic forward modeling closer to real seismic records.
文摘The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented. Two image algorithms are developed: template-based automatic target recognition and zone labeling. One is estimating for motion direction in the infrared image background, another is line picking-up algorithm based on image zone labeling and phase grouping technique. It is a kind of 'hardware' function that can be called by the DSP in high-level algorithm. It is also a kind of hardware algorithm of the DSP. The results of experiments show the reconfigurable computing technology based on RMP is an ideal accelerating means to deal with the high-speed image processing tasks. High real time performance is obtained in our two applications on RMP.
基金supported by the National Key R&D Program of China(No.2021YFB3400900)the National Natural Science Foundation of China(Nos.52175373,52205435)+1 种基金Natural Science Foundation of Hunan Province,China(No.2022JJ40621)the Innovation Fund of National Commercial Aircraft Manufacturing Engineering Technology Center,China(No.COMACSFGS-2022-1875)。
文摘A new unified constitutive model was developed to predict the two-stage creep-aging(TSCA)behavior of Al-Zn-Mg-Cu alloys.The particular bimodal precipitation feature was analyzed and modeled by considering the primary micro-variables evolution at different temperatures and their interaction.The dislocation density was incorporated into the model to capture the effect of creep deformation on precipitation.Quantitative transmission electron microscopy and experimental data obtained from a previous study were used to calibrate the model.Subsequently,the developed constitutive model was implemented in the finite element(FE)software ABAQUS via the user subroutines for TSCA process simulation and the springback prediction of an integral panel.A TSCA test was performed.The result shows that the maximum radius deviation between the formed plate and the simulation results is less than 0.4 mm,thus validating the effectiveness of the developed constitutive model and FE model.
基金the National Natural Science Foundation of China(Grant No.51464035).
文摘The isothermal compression test for Ti-6Al-7Nb alloy was conducted by using Gleeble-3800 thermal simulator.The hot deformation behavior of Ti-6Al-7Nb alloy was investigated in the deformation temperature ranges of 940-1030℃and the strain rate ranges of 0.001-10 s^(-1).Meanwhile,the activation energy of thermal deformation was computed.The results show that the flow stress of Ti-6Al-7Nb alloy increases with increasing the strain rate and decreasing the deformation temperature.The activation energy of thermal deformation for Ti-6Al-7Nb alloy is much greater than that for self-diffusion ofα-Ti andβ-Ti.Considering the influence of strain on flow stress,the strain-compensated Arrhenius constitutive model of Ti-6Al-7Nb alloy was established.The error analysis shows that the model has higher accuracy,and the correlation coefficient r and average absolute relative error are 0.9879 and 4.11%,respectively.The processing map(PM)of Ti-6Al-7Nb alloy was constructed by the dynamic materials model and Prasad instability criterion.According to PM and microstructural observation,it is found that the main form of instability zone is local flow,and the deformation mechanisms of the stable zone are mainly superplasticity and dynamic recrystallization.The optimal processing parameters of Ti-6Al-7Nb alloy are determined as follows:960-995℃/0.01-0.18 s^(-1)and 1000-1030℃/0.001-0.01 s^(-1).
基金supported by the National Key Research and Development Program of China(No.2016YFC1100600)the National Nature Science Foundation of China(Nos.61540006,61672363).
文摘We present a method for computed tomography(CT)image processing and modeling for tibia microstructure,achieved by using computer graphics and fractal theory.Given the large-scale image data of tibia species with DICOM standard for clinical applications,we take advantage of algorithms such as image binarization,hot pixel removing and close operation to obtain visually clear image for tibia microstructure.All of these images are based on 20 CT scanning images with 30μm slice thickness and 30μm interval and continuous changes in pores.For each pore,we determine its profile by using an improved algorithm for edge detection.Then,to calculate its three-dimensional fractal dimension,we measure the circumference perimeter and area of the pores of bone microstructure using a line fitting method based on the least squares.Subsequently,we put forward an algorithm for the pore profiles through ellipse fitting.The results show that the pores have significant fractal characteristics because of the good linear correlation between the perimeter and the area parameters in log–log scale coordinates system,and the ratio of the elliptical short axis to the long axis through ellipse fitting tends to 0.6501.Based on support vector machine and structural risk minimization principle,we put forward a mapping database theory of structure parameters among the pores of CT images and fractal dimension,Poisson’s ratios,porosity and equivalent aperture.On this basis,we put forward a new concept for 3D modeling called precision-measuring digital expressing to reconstruct tibia microstructure for human hard tissue.
基金supported by the National Natural Science Foundation of China(Grant No.61271323)the Open Project from State Key Laboratory of MillimeterWaves,China(Grant No.K200913)
文摘Ultra-wideband （UWB） microwave imaging is a promising method for breast cancer detection based on the large contrast of electric parameters between the malignant tumor and its surrounded normal breast organisms. In the case of multiple tumors being present, the conventional imaging approaches may be ineffective to detect all the tumors clearly. In this paper, a progressive processing method is proposed for detecting more than one tumor. The method is divided into three stages： primary detection, refocusing and image optimization. To test the feasibility of the approach, a numerical breast model is developed based on the realistic magnetic resonance image （MRI）. Two tumors are assumed embedded in different positions. Successful detection of a 3.6 mm-diameter tumor at a depth of 42 mm is achieved. The correct information of both tumors is shown in the reconstructed image, suggesting that the progressive processing method is promising for multi-tumor detection.
基金the support by the Faculty of Engineering,Hakim Sabzevari University,Sabzevar,Iran。
文摘The aim of this study is to develop processing maps based on two models and compare them with conventional processing maps.The hyperbolic sinus constitutive equation and artificial neural network(ANN)approaches were used in this investigation to predict flow stress and to develop processing maps in various conditions.The hot compression tests of InX-750 superalloy were carried out above the gamma prime phase temperature and within the temperature range of 1000-1150℃and strain rate of 0.001-1.000 s^(-1).The processing maps were conducted based upon dynamic material model(DMM)for data by experimental,constitutive equation and ANN approaches.The processing maps drawn by either of the prediction methods show that the method developed by ANN data does not significantly differ from the experimental processing map.The ANN approach is thus a suitable way to predict the flow stress as well as hot working processing map of engineering metals and materials.
文摘The issue of document management has been raised for a long time, especially with the appearance of office automation in the 1980s, which led to dematerialization and Electronic Document Management (EDM). In the same period, workflow management has experienced significant development, but has become more focused on the industry. However, it seems to us that document workflows have not had the same interest for the scientific community. But nowadays, the emergence and supremacy of the Internet in electronic exchanges are leading to a massive dematerialization of documents;which requires a conceptual reconsideration of the organizational framework for the processing of said documents in both public and private administrations. This problem seems open to us and deserves the interest of the scientific community. Indeed, EDM has mainly focused on the storage (referencing) and circulation of documents (traceability). It paid little attention to the overall behavior of the system in processing documents. The purpose of our researches is to model document processing systems. In the previous works, we proposed a general model and its specialization in the case of small documents (any document processed by a single person at a time during its processing life cycle), which represent 70% of documents processed by administrations, according to our study. In this contribution, we extend the model for processing small documents to the case where they are managed in a system comprising document classes organized in subclasses;which is the case for most administrations. We have thus observed that this model is a Markovian <i>M<sup>L×K</sup>/M<sup>L×K</sup>/</i>1 queues network. We have analyzed the constraints of this model and deduced certain characteristics and metrics. <span style="white-space:normal;"><i></i></span><i>In fine<span style="white-space:normal;"></span></i>, the ultimate objective of our work is to design a document workflow management system, integrating a component of global behavior prediction.
基金supported by the National Natural Science Foundation of China under grants U1836208,by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD)fundby the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET)fund,China.
文摘Image processing networks have gained great success in many fields,and thus the issue of copyright protection for image processing networks hasbecome a focus of attention. Model watermarking techniques are widely usedin model copyright protection, but there are two challenges: (1) designinguniversal trigger sample watermarking for different network models is stilla challenge;(2) existing methods of copyright protection based on trigger swatermarking are difficult to resist forgery attacks. In this work, we propose adual model watermarking framework for copyright protection in image processingnetworks. The trigger sample watermark is embedded in the trainingprocess of the model, which can effectively verify the model copyright. And wedesign a common method for generating trigger sample watermarks based ongenerative adversarial networks, adaptively generating trigger sample watermarksaccording to different models. The spatial watermark is embedded intothe model output. When an attacker steals model copyright using a forgedtrigger sample watermark, which can be correctly extracted to distinguishbetween the piratical and the protected model. The experiments show that theproposed framework has good performance in different image segmentationnetworks of UNET, UNET++, and FCN (fully convolutional network), andeffectively resists forgery attacks.
基金supported by the National Natural Science Foundation of China(Grant Nos.42120104008 and 42307214)the Postdoctoral Fellowship Program of CPSF(Grant No.GZB20230620).
文摘Coriolis effects,encompassing the dilative,compressive,and deflective manifestations,constitute pivotal considerations in the centrifugal modelling of high-speed granular run-out processes.Notably,under the deflective Coriolis condition,the velocity component parallel to the rotational axis exerts no influence on the magnitude of Coriolis acceleration.This circumstance implies a potential mitigation of the Coriolis force's deflective impact.Regrettably,extant investigations predominantly emphasize the dilative and compressive Coriolis effects,largely neglecting the pragmatic import of the deflective Coriolis condition.In pursuit of this gap,a series of discrete element method(DEM)simulations have been conducted to scrutinize the feasibility of centrifugal modelling for dry granular run-out processes under deflective Coriolis conditions.The findings concerning the deflective Coriolis effect reveal a consistent rise in the run-out distance by 2%–16%,a modest increase in bulk flow velocity of under 4%,and a slight elevation in average flow depth by no more than 25%.These alterations display smaller dependence on the specific testing conditions due to the granular flow undergoing dual deflections in opposing directions.This underscores the significance and utility of the deflective Coriolis condition.Notably,the anticipated reduction in error in predicting the final run-out distance is substantial,potentially reaching a 150%improvement compared to predictions made under the dilative and compressive Coriolis conditions.Therefore,the deflective Coriolis condition is advised when the final run-out distance of the granular flow is the main concern.To mitigate the impact of Coriolis acceleration,a greater initial height of the granular column is recommended,with a height/width ratio exceeding 1,as the basal friction of the granular material plays a crucial role in mitigating the deflective Coriolis effect.For more transverse-uniform flow properties,the width of the granular column should be as large as possible.
