Purpose-This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.Design/methodology/approach-First,taking the Liuyuan Tunnel of Huangg...Purpose-This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.Design/methodology/approach-First,taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion,the critical buried depth of the large section tunnel was determined.Then,the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios,and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality(BQ)index of the rock for different rock classes.Finally,the influences of thickness-span ratio,groundwater,initial stress of rock and structural attitude factors were considered to obtain the corrected BQ,based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed.This evaluation method was then applied to Liuyuan Tunnel and Cimushan No.2 Tunnel of Chongqing Urban Expressway for verification.Findings-This study shows that under different rock classes,the tunnel safety factor is a strict power function of the thickness-span ratio,while a linear function of the BQ to some extent.It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.Originality/value-The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability.The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.展开更多
To study the mechanical responses of large cross-section tunnel reinforced by pretensioned rock bolts and anchor cables, an analytical model is proposed. Considering the interaction between rock mass and bolt-cable su...To study the mechanical responses of large cross-section tunnel reinforced by pretensioned rock bolts and anchor cables, an analytical model is proposed. Considering the interaction between rock mass and bolt-cable support, the strain softening characteristic of rock mass, the elastic-plastic characteristic of bolt-cable support, and the delay effect of installation are considered in the model. To solve the different mechanical cases of tunneling reinforced by bolt-cable support, an analytical approach has been put forward to get the solutions of stress and displacement associated with tunneling. The proposed analytical model is verified by numerical simulation. Moreover, parametric analysis is performed to study the effects of pretension force,cross-section area, length, and supporting density of bolt-cable support on tunnel reinforcement, which can provide references for determining these parameters in tunnel design. Based on the analytical model, a new Ground Response Curve(GRC)considering the reinforcement of bolt-cable support is obtained, which shows the pretension forces and the timely installation are important in bolt-cable support. In addition, the proposed model is applied to the analysis of the Great Wall Station Tunnel, a high-speed railway tunnel with a super large cross-section, which shows that the analytical model of bolt-cable support was a useful tool for preliminary design of large cross-section tunnel.展开更多
Over the past decades, low-energy electron accelerators have been used worldwide for surface curing and sterilization. The beam nonuniformity is an important parameter of the low-energy electron beam with large cross-...Over the past decades, low-energy electron accelerators have been used worldwide for surface curing and sterilization. The beam nonuniformity is an important parameter of the low-energy electron beam with large cross-sections. A simple and accurate measurement system of nonuniformity for the low-energy electron beam with large cross-sections was developed. The main concept consists in the measurement of nonuniformity, which is realized by using a linear actuator to drive two scanning wires through the beam's cross-sections at a fixed speed. The beam distribution can be obtained by sending/collecting the current signals to/from the Data Acquisition (DAQ) software on a laptop by a USB DAQ card. This device is very convenient for the performance testing of a new accelerator at the manufacturer's site. The distribution of the homemade low voltage electron accelerator EBS-300-50 was measured and evaluated.展开更多
In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random vari...In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
Objective:To assess prenatal Bisphenol A(BPA)exposure levels and explore their preliminary associations with maternal and fetal characteristics in a population from Northeastern Yunnan.Methods:A cross-sectional analys...Objective:To assess prenatal Bisphenol A(BPA)exposure levels and explore their preliminary associations with maternal and fetal characteristics in a population from Northeastern Yunnan.Methods:A cross-sectional analysis was performed using data and urine samples from 70 pregnant women in their third trimester recruited at Qujing Central Hospital.Urinary BPA was measured by HPLC-MS/MS.Participants were stratified into high and low BPA exposure groups based on the median concentration.Results:BPA was detected in all samples(100%)with a median concentration of 2.41μg/L(IQR:0.68-4.96).The high BPA exposure group(≥2.41μg/L)had a significantly higher proportion of gestational diabetes mellitus(GDM)(42.9%vs.17.1%,p=0.021)and a lower median fetal birth weight(3250 g vs.3450 g,p=0.048)compared to the low exposure group.Conclusion:This pilot study reveals ubiquitous BPA exposure in pregnant women from Northeastern Yunnan.The observed preliminary associations with GDM and reduced fetal birth weight warrant further investigation in larger,longitudinal studies.展开更多
Objective This study aimed to determine the temporal trends in sleep duration among Chinese adults.Methods In this series of repeated nationally representative cross-sectional surveys(China Chronic Disease and Risk Fa...Objective This study aimed to determine the temporal trends in sleep duration among Chinese adults.Methods In this series of repeated nationally representative cross-sectional surveys(China Chronic Disease and Risk Factors Surveillance)conducted between 2010 and 2018,a total of 645,420 adult participants(97,741 in 2010;175,749 in 2013;187,777 in 2015;and 184,153 in 2018)were included in the trend analysis.Linear and logistic regression models were utilized to assess trends in sleep duration.Results In 2018,the estimated overall mean sleep duration among the Chinese adult population was7.58(SD,1.45)hours per day,with no significant trend from 2010.A significant increase in short sleep duration(≤6 hours)was observed in the total population,from 15.3%(95%CI:14.1%–16.5%)in 2010 to18.5%(95%CI:17.7%–19.3%)in 2018(P<0.001).Similarly,the trend in long sleep duration(>9 hours)was also significant,increasing in weighted prevalence from 7.2%(95%CI:6.3%–8.1%)in 2010 to 9.0%(95%CI:8.2%–9.9%)in 2018(P<0.001).Conclusion The prevalence of both short and long sleep durations significantly increased among Chinese adults from 2010 to 2018,highlighting the urgency of health initiatives to promote optimal sleep duration in China.展开更多
Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentrat...Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentration,and forming defects are prone to occur during their extrusion.This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U,multi-cavity thin-walled structure.Firstly,hot compression experiments were conducted at temperatures of 350○C,400○C,and 450○C,with strain rates of 0.01 and 1.0 s^(−1),to investigate the plastic deformation behavior of the material.Subsequently,a 3D coupled thermo-mechanical extrusion simulation model was established using Deform-3D to systematically analyze the influence of die structure and process parameters on metal flow velocity,effective stress/strain,and temperature distribution.The simulation revealed significant velocity differences,stress concentration,and uneven temperature distribution.Key parameters,including mesh density,extrusion ratio,die fillet,and bearing length,were optimized through full-factorial experiments.This optimization,combined with a stepped flow-guiding die design,effectively improved the metal flow pattern during extrusion.Trial production based on both the initial and optimized parameters were carried out.A comparative analysis demonstrates that the optimized scheme results in a final profile whose cross-section matches the target design closely,with complete filling of complex features and no obvious forming defects.This research provides a valuable reference for the extrusion process optimization and die design of complex-section profiles made from ultra-high-strength aluminum alloys.展开更多
Polyfluoroalkyl substances(PFAS)have emerged as persistent environmental contaminants because of their chemical stability,degradation-resistance and bioaccumulation potential.However,current studies mainly focus on th...Polyfluoroalkyl substances(PFAS)have emerged as persistent environmental contaminants because of their chemical stability,degradation-resistance and bioaccumulation potential.However,current studies mainly focus on the toxicity of single PFAS such as perfluorooctanoic acid(PFOA)and perfluorobutanoic acid(PFBA),the knowledge of their combined effects is relatively limited.In this study,we explored the immune response of the gut in large yellow croaker(Larimichthys crocea)under the combined stress of PFOA and PFBA.Histologicalanalyses revealed that the combined effect induced intestinal vacuolization and decreased the length of intestinal villi.And it significantly activated pro-inflammatory pathways with marked upregulation of tnfα,il1β,il6 and myd88 expressions,particularly after 14 days of exposure.Gut microbiota analysis revealed substantial dysbiosis,including 1)reduced alpha diversity,2)increased abundance of potential pathogenic taxa(Proteobacteria and Spirochaetota),and 3)depletion of beneficial Firmicutes.PICRUSt-based functional prediction indicated temporal metabolic shifts,with upregulation of DNA repair pathways at day 3 and enhanced bacterial motility protein activity at days 7 and 14 of post-exposure.The Pearson correlation analysis further indicated that these immune genes had significant positive correlations with Vibrio and Brevinema,and negative correlations with Streptococcus.Our present study will provide novel insights into the microbiome-mediated immunomodulation in the larger yellow croaker exposed to combined PFAS,which will be helpful for healthy farming of economically important marine species.展开更多
This study presents an implicit multiphysics coupling method integrating Computational Fluid Dynamics(CFD),the Multiphase Particle-in-Cell(MPPIC)model,and the Finite Element Method(FEM),implemented with OpenFOAM,Calcu...This study presents an implicit multiphysics coupling method integrating Computational Fluid Dynamics(CFD),the Multiphase Particle-in-Cell(MPPIC)model,and the Finite Element Method(FEM),implemented with OpenFOAM,CalculiX,and preCICE to simulate fluid-particle-structure interactions with large deformations.Mesh motion in the fluid field is handled using the radial basis function(RBF)method.The particle phase is modeled by MPPIC,where fluid-particle interaction is described through momentum exchange,and inter-particle collisions are characterized by collision stress.The structural field is solved by nonlinear FEM to capture large deformations induced by geometric nonlinearity.Coupling among fields is realized through a partitioned,parallel,and non-intrusive iterative strategy,ensuring stable transfer and convergence of interface forces and displacements.Notably,the influence of particles on the structure is not direct but mediated by the fluid,while structural motion directly affects particle dynamics.The results demonstrate that the proposed approach effectively captures multiphysics interaction processes and provides a valuable reference for numerical modeling of coupled fluid-particle-structure systems.展开更多
This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to use...This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.展开更多
War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient an...War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient and inflexible,with particularly pronounced limitations in command and decision-making.The overwhelming volume of information and high decision complexity hinder the realization of autonomous and agile command and control.To address this challenge,an intelligent warfare simulation framework named Command-Agent is proposed,which deeply integrates large language models(LLMs)with digital twin battlefields.By constructing a highly realistic battlefield environment through real-time simulation and multi-source data fusion,the natural language interaction capabilities of LLMs are leveraged to lower the command threshold and to enable autonomous command through the Observe-Orient-Decide-Act(OODA)feedback loop.Within the Command-Agent framework,a multimodel collaborative architecture is further adopted to decouple the decision-generation and command-execution functions of LLMs.By combining specialized models such as Deep Seek-R1 and MCTool,the limitations of single-model capabilities are overcome.MCTool is a lightweight execution model fine-tuned for military Function Calling tasks.The framework also introduces a Vector Knowledge Base to mitigate hallucinations commonly exhibited by LLMs.Experimental results demonstrate that Command-Agent not only enables natural language-driven simulation and control but also deeply understands commander intent.Leveraging the multi-model collaborative architecture,during red-blue UAV confrontations involving 2 to 8 UAVs,the integrated score is improved by an average of 41.8%compared to the single-agent system(MCTool),accompanied by a 161.8%optimization in the battle loss ratio.Furthermore,when compared with multi-agent systems lacking the knowledge base,the inclusion of the Vector Knowledge Base further improves overall performance by 16.8%.In comparison with the general model(Qwen2.5-7B),the fine-tuned MCTool leads by 5%in execution efficiency.Therefore,the proposed Command-Agent introduces a novel perspective to the military command system and offers a feasible solution for intelligent battlefield decision-making.展开更多
Large language models(LLMs)have revolutionized AI applications across diverse domains.However,their widespread deployment has introduced critical security vulnerabilities,particularly prompt injection attacks that man...Large language models(LLMs)have revolutionized AI applications across diverse domains.However,their widespread deployment has introduced critical security vulnerabilities,particularly prompt injection attacks that manipulate model behavior through malicious instructions.Following Kitchenham’s guidelines,this systematic review synthesizes 128 peer-reviewed studies from 2022 to 2025 to provide a unified understanding of this rapidly evolving threat landscape.Our findings reveal a swift progression from simple direct injections to sophisticated multimodal attacks,achieving over 90%success rates against unprotected systems.In response,defense mechanisms show varying effectiveness:input preprocessing achieves 60%–80%detection rates and advanced architectural defenses demonstrate up to 95%protection against known patterns,though significant gaps persist against novel attack vectors.We identified 37 distinct defense approaches across three categories,but standardized evaluation frameworks remain limited.Our analysis attributes these vulnerabilities to fundamental LLM architectural limitations,such as the inability to distinguish instructions from data and attention mechanism vulnerabilities.This highlights critical research directions such as formal verification methods,standardized evaluation protocols,and architectural innovations for inherently secure LLM designs.展开更多
The giant impact hypothesis for the Moon's origin has had difficulty explaining the nearly identical isotopic compositions of Moon rocks and rocks from Earth's silicate mantle and crust.These similarities are ...The giant impact hypothesis for the Moon's origin has had difficulty explaining the nearly identical isotopic compositions of Moon rocks and rocks from Earth's silicate mantle and crust.These similarities are instead more compatible with the Darwin-Wise hypothesis that the Moon arose by fission of a rapidly spinning Earth.To overcome problems with the fission model concerning structural stability and angular momentum conservation,some authors suggested that lunar fission was feasible on a more slowly rotating Earth if assisted by a nuclear explosion near the core-mantle boundary.In this light we consider the possible roles of the large low-velocity provinces(LLVPs).These long-lived structures have been implicated in diverse geophysical processes ranging from deep mantle plumes to continental breakup and mass extinction events.While the LLVPs have been seen as possible remnants of the giant imp actor,we propose that one of them was the site of lunar ejection.Internal heating of the liquid core is suggested to have given rise to an equatorial belt just under the core-mantle boundary analogous to the one recently detected by Ma and Tkalcic[Sci Adv 10(35):eadn5562,2024].Upwellings of heat and volatiles from this belt then generated two antipodal,equatorial bulges:the precursors of the Pacific and African LLVPs.Prior to the emergence of plate tectonics,core heat was mainly dissipated by networks of deep mantle plumes extending above the proto-LLVPs.These plume networks represent conduits of weakened mantle through which proto-lunar materials could later rise in a focused ejection.Continuing heat buildup in the core eventually triggered a cataclysmic explosion in the Pacific proto-LLVP,possibly analogous to a planetary-scale kimberlite eruption.This explosion launched LLVP and overlying mantle material into a low Earth orbit,where it coalesced to form the Moon.Some possible sources of additional energy to power the explosion are considered,including nuclear fission,bolide impacts and a hypothetical gravitational decay process culminating in a'A event'.展开更多
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In...We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In two complementary experiments,the use of photographs to estimate cross-sectional areas was first validated,then the use of a caliper and diameter tape was computer-simulated.The results indicated that the photographic method offers high precision,with mean relative errors below 0.1%,minimal deviation,and no significant bias,and the traditional methods led to substantial and systematic errors,with deviations from circularity and convexity significantly increasing the errors in area estimation.展开更多
Conversational recommender systems(CRSs)focus on refining preferences and providing personalized recommendations through natural language interactions and dialogue history.Large language models(LLMs)have shown outstan...Conversational recommender systems(CRSs)focus on refining preferences and providing personalized recommendations through natural language interactions and dialogue history.Large language models(LLMs)have shown outstanding performance across various domains,thereby prompting researchers to investigate their applicability in recommendation systems.However,due to the lack of task-specific knowledge and an inefficient feature extraction process,LLMs still have suboptimal performance in recommendation tasks.Therefore,external knowledge sources,such as knowledge graphs(KGs)and knowledge bases(KBs),are often introduced to address the issue of data sparsity.Compared to KGs,KBs possess higher retrieval efficiency,making them more suitable for scenarios where LLMs serve as recommenders.To this end,we introduce a novel framework integrating LLMs with KBs for enhanced retrieval generation,namely LLMKB.LLMKB initially leverages structured knowledge to create mapping dictionaries,extracting entity-relation information from heterogeneous knowledge to construct KBs.Then,LLMKB achieves the embedding calibration between user information representations and documents in KBs through retrieval model fine-tuning.Finally,LLMKB employs retrievalaugmented generation to produce recommendations based on fused text inputs,followed by post-processing.Experiment results on two public CRS datasets demonstrate the effectiveness of our framework.Our code is publicly available at the link:https://anonymous.4open.science/r/LLMKB-6FD0.展开更多
Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises.While large language models(LLMs)enable automated report generation,this specific domain lack...Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises.While large language models(LLMs)enable automated report generation,this specific domain lacks formal task definitions and corresponding benchmarks.To bridge this gap,we define the Automated Online Public Opinion Report Generation(OPOR-Gen)task and construct OPOR-Bench,an event-centric dataset with 463 crisis events across 108 countries(comprising 8.8 K news articles and 185 K tweets).To evaluate report quality,we propose OPOR-Eval,a novel agent-based framework that simulates human expert evaluation.Validation experiments show OPOR-Eval achieves a high Spearman’s correlation(ρ=0.70)with human judgments,though challenges in temporal reasoning persist.This work establishes an initial foundation for advancing automated public opinion reporting research.展开更多
The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechan...The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechanism of large earthquakes.This study uses rock magnetic,microstructural,and geochemical analyses of representative samples exposed in FZ1681 within the Wenchuan Earthquake Fault Scientific Drilling borehole 2(WFSD-2)cores.Fault gouge and fault breccia have higher magnetic susceptibility values than wall rocks,and they contain abundant paramagnetic minerals and small quantities of magnetite and monoclinic pyrrhotite.The magnetite and monoclinic pyrrhotite in the fault gouge were mainly formed by coseismic frictional heating,indicating that large earthquakes with frictional heating temperatures of~500-900℃once occurred in the YBFZ.The seismogenic and coseismic environment was reducing with a relatively high sulfur content.The monoclinic pyrrhotite in the fault breccia was formed mainly by low-temperature hydrothermal fluid.This indicates that the fault zone experienced reducing and low-temperature(<400℃)hydrothermal fluid with a relatively high sulfur content after the earthquake.The YBFZ,which experiences frequent large earthquakes,is weakly oxidizing environment at different depths,but the effect of the low-temperature hydrothermal fluid is weaker at depth.展开更多
One of the main issues in designing optimum tapered cascades for uranium enrichment for annual fuel production in a power reactor is whether to employ large(fat)or small(thin)cascades.What will be the permissible and ...One of the main issues in designing optimum tapered cascades for uranium enrichment for annual fuel production in a power reactor is whether to employ large(fat)or small(thin)cascades.What will be the permissible and optimal ranges of the number of machines that can be used in a cascade?For the first time,the permissible and optimal ranges of the number of gas centrifuges that can be utilized in a cascade were investigated using two types of centrifuges,and the performance of small and large tapered cascades was discussed.The particle swarm optimization algorithm(PSO)has been used to optimize tapered cascades.The results show:(1)For the first centrifuge,41 cascades(91≤n≤4897)and for the second centrifuge,49 cascades(18≤n≤3839)with small and large sizes can be used in enrichment facilities,and the best cascade for them has 530(with 23 stages)and 39(with 7 stages)centrifuges,respectively.(2)For both centrifuges,when 600≤n(number of centrifuges=n),the large cascade performance changes are relatively insignificant.(3)For both types of gas centrifuges,the annual los s of separation power in enrichment facilities is approximately 1.25%-4.82%of the total separation work required.展开更多
基金supported by the NSFC HSR Fundamental Research Joint Fund (Grant No.U1934213)。
文摘Purpose-This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.Design/methodology/approach-First,taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion,the critical buried depth of the large section tunnel was determined.Then,the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios,and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality(BQ)index of the rock for different rock classes.Finally,the influences of thickness-span ratio,groundwater,initial stress of rock and structural attitude factors were considered to obtain the corrected BQ,based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed.This evaluation method was then applied to Liuyuan Tunnel and Cimushan No.2 Tunnel of Chongqing Urban Expressway for verification.Findings-This study shows that under different rock classes,the tunnel safety factor is a strict power function of the thickness-span ratio,while a linear function of the BQ to some extent.It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.Originality/value-The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability.The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.
基金supported by the National Key Research and Development Program of China (Grant No. 2017YFC0805401)the National Natural Science Foundation of China (Grant No. 51738002)+1 种基金the China Railway Corporation Research and Development Program of Science and Technology (Grant No. 2014004-C)the Fundamental Research Funds for the Central Universities (Grant No. C17JB00030)。
文摘To study the mechanical responses of large cross-section tunnel reinforced by pretensioned rock bolts and anchor cables, an analytical model is proposed. Considering the interaction between rock mass and bolt-cable support, the strain softening characteristic of rock mass, the elastic-plastic characteristic of bolt-cable support, and the delay effect of installation are considered in the model. To solve the different mechanical cases of tunneling reinforced by bolt-cable support, an analytical approach has been put forward to get the solutions of stress and displacement associated with tunneling. The proposed analytical model is verified by numerical simulation. Moreover, parametric analysis is performed to study the effects of pretension force,cross-section area, length, and supporting density of bolt-cable support on tunnel reinforcement, which can provide references for determining these parameters in tunnel design. Based on the analytical model, a new Ground Response Curve(GRC)considering the reinforcement of bolt-cable support is obtained, which shows the pretension forces and the timely installation are important in bolt-cable support. In addition, the proposed model is applied to the analysis of the Great Wall Station Tunnel, a high-speed railway tunnel with a super large cross-section, which shows that the analytical model of bolt-cable support was a useful tool for preliminary design of large cross-section tunnel.
文摘Over the past decades, low-energy electron accelerators have been used worldwide for surface curing and sterilization. The beam nonuniformity is an important parameter of the low-energy electron beam with large cross-sections. A simple and accurate measurement system of nonuniformity for the low-energy electron beam with large cross-sections was developed. The main concept consists in the measurement of nonuniformity, which is realized by using a linear actuator to drive two scanning wires through the beam's cross-sections at a fixed speed. The beam distribution can be obtained by sending/collecting the current signals to/from the Data Acquisition (DAQ) software on a laptop by a USB DAQ card. This device is very convenient for the performance testing of a new accelerator at the manufacturer's site. The distribution of the homemade low voltage electron accelerator EBS-300-50 was measured and evaluated.
文摘In this paper,we establish some strong laws of large numbers,which are for nonindependent random variables under the framework of sublinear expectations.One of our main results is for blockwise m-dependent random variables,and another is for sub-orthogonal random variables.Both extend the strong law of large numbers for independent random variables under sublinear expectations to the non-independent case.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
文摘Objective:To assess prenatal Bisphenol A(BPA)exposure levels and explore their preliminary associations with maternal and fetal characteristics in a population from Northeastern Yunnan.Methods:A cross-sectional analysis was performed using data and urine samples from 70 pregnant women in their third trimester recruited at Qujing Central Hospital.Urinary BPA was measured by HPLC-MS/MS.Participants were stratified into high and low BPA exposure groups based on the median concentration.Results:BPA was detected in all samples(100%)with a median concentration of 2.41μg/L(IQR:0.68-4.96).The high BPA exposure group(≥2.41μg/L)had a significantly higher proportion of gestational diabetes mellitus(GDM)(42.9%vs.17.1%,p=0.021)and a lower median fetal birth weight(3250 g vs.3450 g,p=0.048)compared to the low exposure group.Conclusion:This pilot study reveals ubiquitous BPA exposure in pregnant women from Northeastern Yunnan.The observed preliminary associations with GDM and reduced fetal birth weight warrant further investigation in larger,longitudinal studies.
基金supported by the National Natural Science Foundation of China(82341245,82371491)the Chinese Central Government(Key Project of Public Health Program)the National Key Research and Development Program of China(2018YFC1311706,2018YFC1311702)。
文摘Objective This study aimed to determine the temporal trends in sleep duration among Chinese adults.Methods In this series of repeated nationally representative cross-sectional surveys(China Chronic Disease and Risk Factors Surveillance)conducted between 2010 and 2018,a total of 645,420 adult participants(97,741 in 2010;175,749 in 2013;187,777 in 2015;and 184,153 in 2018)were included in the trend analysis.Linear and logistic regression models were utilized to assess trends in sleep duration.Results In 2018,the estimated overall mean sleep duration among the Chinese adult population was7.58(SD,1.45)hours per day,with no significant trend from 2010.A significant increase in short sleep duration(≤6 hours)was observed in the total population,from 15.3%(95%CI:14.1%–16.5%)in 2010 to18.5%(95%CI:17.7%–19.3%)in 2018(P<0.001).Similarly,the trend in long sleep duration(>9 hours)was also significant,increasing in weighted prevalence from 7.2%(95%CI:6.3%–8.1%)in 2010 to 9.0%(95%CI:8.2%–9.9%)in 2018(P<0.001).Conclusion The prevalence of both short and long sleep durations significantly increased among Chinese adults from 2010 to 2018,highlighting the urgency of health initiatives to promote optimal sleep duration in China.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFB3710805).
文摘Ultra-high-strength aluminumalloy profile is an ideal choice for aerospace structuralmaterials due to its excellent specific strength and corrosion resistance.However,issues such as uneven metal flow,stress concentration,and forming defects are prone to occur during their extrusion.This study focuses on an Al-Zn-Mg-Cu ultra-high-strength aluminum alloy profile with a double-U,multi-cavity thin-walled structure.Firstly,hot compression experiments were conducted at temperatures of 350○C,400○C,and 450○C,with strain rates of 0.01 and 1.0 s^(−1),to investigate the plastic deformation behavior of the material.Subsequently,a 3D coupled thermo-mechanical extrusion simulation model was established using Deform-3D to systematically analyze the influence of die structure and process parameters on metal flow velocity,effective stress/strain,and temperature distribution.The simulation revealed significant velocity differences,stress concentration,and uneven temperature distribution.Key parameters,including mesh density,extrusion ratio,die fillet,and bearing length,were optimized through full-factorial experiments.This optimization,combined with a stepped flow-guiding die design,effectively improved the metal flow pattern during extrusion.Trial production based on both the initial and optimized parameters were carried out.A comparative analysis demonstrates that the optimized scheme results in a final profile whose cross-section matches the target design closely,with complete filling of complex features and no obvious forming defects.This research provides a valuable reference for the extrusion process optimization and die design of complex-section profiles made from ultra-high-strength aluminum alloys.
基金supported by the Ningbo Natural Science Foundation(Youth Foundation,No.2024J449)the Scientific Research Foundation for Introduced Talents of Ningbo University(Nos.ZX2022000602 and ZX2024000043)。
文摘Polyfluoroalkyl substances(PFAS)have emerged as persistent environmental contaminants because of their chemical stability,degradation-resistance and bioaccumulation potential.However,current studies mainly focus on the toxicity of single PFAS such as perfluorooctanoic acid(PFOA)and perfluorobutanoic acid(PFBA),the knowledge of their combined effects is relatively limited.In this study,we explored the immune response of the gut in large yellow croaker(Larimichthys crocea)under the combined stress of PFOA and PFBA.Histologicalanalyses revealed that the combined effect induced intestinal vacuolization and decreased the length of intestinal villi.And it significantly activated pro-inflammatory pathways with marked upregulation of tnfα,il1β,il6 and myd88 expressions,particularly after 14 days of exposure.Gut microbiota analysis revealed substantial dysbiosis,including 1)reduced alpha diversity,2)increased abundance of potential pathogenic taxa(Proteobacteria and Spirochaetota),and 3)depletion of beneficial Firmicutes.PICRUSt-based functional prediction indicated temporal metabolic shifts,with upregulation of DNA repair pathways at day 3 and enhanced bacterial motility protein activity at days 7 and 14 of post-exposure.The Pearson correlation analysis further indicated that these immune genes had significant positive correlations with Vibrio and Brevinema,and negative correlations with Streptococcus.Our present study will provide novel insights into the microbiome-mediated immunomodulation in the larger yellow croaker exposed to combined PFAS,which will be helpful for healthy farming of economically important marine species.
基金supported in part by the Mining Hydraulic Technology and Equipment Engineering Research Center,Liaoning Technical University,Fuxin,China(Grant No.MHTE23-R04)the Fundamental Research Funds for the Central Universities(ID N25BSS068).
文摘This study presents an implicit multiphysics coupling method integrating Computational Fluid Dynamics(CFD),the Multiphase Particle-in-Cell(MPPIC)model,and the Finite Element Method(FEM),implemented with OpenFOAM,CalculiX,and preCICE to simulate fluid-particle-structure interactions with large deformations.Mesh motion in the fluid field is handled using the radial basis function(RBF)method.The particle phase is modeled by MPPIC,where fluid-particle interaction is described through momentum exchange,and inter-particle collisions are characterized by collision stress.The structural field is solved by nonlinear FEM to capture large deformations induced by geometric nonlinearity.Coupling among fields is realized through a partitioned,parallel,and non-intrusive iterative strategy,ensuring stable transfer and convergence of interface forces and displacements.Notably,the influence of particles on the structure is not direct but mediated by the fluid,while structural motion directly affects particle dynamics.The results demonstrate that the proposed approach effectively captures multiphysics interaction processes and provides a valuable reference for numerical modeling of coupled fluid-particle-structure systems.
基金funded by the Office of the Vice-President for Research and Development of Cebu Technological University.
文摘This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.
文摘War rehearsals have become increasingly important in national security due to the growing complexity of international affairs.However,traditional rehearsal methods,such as military chess simulations,are inefficient and inflexible,with particularly pronounced limitations in command and decision-making.The overwhelming volume of information and high decision complexity hinder the realization of autonomous and agile command and control.To address this challenge,an intelligent warfare simulation framework named Command-Agent is proposed,which deeply integrates large language models(LLMs)with digital twin battlefields.By constructing a highly realistic battlefield environment through real-time simulation and multi-source data fusion,the natural language interaction capabilities of LLMs are leveraged to lower the command threshold and to enable autonomous command through the Observe-Orient-Decide-Act(OODA)feedback loop.Within the Command-Agent framework,a multimodel collaborative architecture is further adopted to decouple the decision-generation and command-execution functions of LLMs.By combining specialized models such as Deep Seek-R1 and MCTool,the limitations of single-model capabilities are overcome.MCTool is a lightweight execution model fine-tuned for military Function Calling tasks.The framework also introduces a Vector Knowledge Base to mitigate hallucinations commonly exhibited by LLMs.Experimental results demonstrate that Command-Agent not only enables natural language-driven simulation and control but also deeply understands commander intent.Leveraging the multi-model collaborative architecture,during red-blue UAV confrontations involving 2 to 8 UAVs,the integrated score is improved by an average of 41.8%compared to the single-agent system(MCTool),accompanied by a 161.8%optimization in the battle loss ratio.Furthermore,when compared with multi-agent systems lacking the knowledge base,the inclusion of the Vector Knowledge Base further improves overall performance by 16.8%.In comparison with the general model(Qwen2.5-7B),the fine-tuned MCTool leads by 5%in execution efficiency.Therefore,the proposed Command-Agent introduces a novel perspective to the military command system and offers a feasible solution for intelligent battlefield decision-making.
基金supported by 2023 Higher Education Scientific Research Planning Project of China Society of Higher Education(No.23PG0408)2023 Philosophy and Social Science Research Programs in Jiangsu Province(No.2023SJSZ0993)+2 种基金Nantong Science and Technology Project(No.JC2023070)Key Project of Jiangsu Province Education Science 14th Five-Year Plan(Grant No.B-b/2024/02/41)the Open Fund of Advanced Cryptography and System Security Key Laboratory of Sichuan Province(Grant No.SKLACSS-202407).
文摘Large language models(LLMs)have revolutionized AI applications across diverse domains.However,their widespread deployment has introduced critical security vulnerabilities,particularly prompt injection attacks that manipulate model behavior through malicious instructions.Following Kitchenham’s guidelines,this systematic review synthesizes 128 peer-reviewed studies from 2022 to 2025 to provide a unified understanding of this rapidly evolving threat landscape.Our findings reveal a swift progression from simple direct injections to sophisticated multimodal attacks,achieving over 90%success rates against unprotected systems.In response,defense mechanisms show varying effectiveness:input preprocessing achieves 60%–80%detection rates and advanced architectural defenses demonstrate up to 95%protection against known patterns,though significant gaps persist against novel attack vectors.We identified 37 distinct defense approaches across three categories,but standardized evaluation frameworks remain limited.Our analysis attributes these vulnerabilities to fundamental LLM architectural limitations,such as the inability to distinguish instructions from data and attention mechanism vulnerabilities.This highlights critical research directions such as formal verification methods,standardized evaluation protocols,and architectural innovations for inherently secure LLM designs.
文摘The giant impact hypothesis for the Moon's origin has had difficulty explaining the nearly identical isotopic compositions of Moon rocks and rocks from Earth's silicate mantle and crust.These similarities are instead more compatible with the Darwin-Wise hypothesis that the Moon arose by fission of a rapidly spinning Earth.To overcome problems with the fission model concerning structural stability and angular momentum conservation,some authors suggested that lunar fission was feasible on a more slowly rotating Earth if assisted by a nuclear explosion near the core-mantle boundary.In this light we consider the possible roles of the large low-velocity provinces(LLVPs).These long-lived structures have been implicated in diverse geophysical processes ranging from deep mantle plumes to continental breakup and mass extinction events.While the LLVPs have been seen as possible remnants of the giant imp actor,we propose that one of them was the site of lunar ejection.Internal heating of the liquid core is suggested to have given rise to an equatorial belt just under the core-mantle boundary analogous to the one recently detected by Ma and Tkalcic[Sci Adv 10(35):eadn5562,2024].Upwellings of heat and volatiles from this belt then generated two antipodal,equatorial bulges:the precursors of the Pacific and African LLVPs.Prior to the emergence of plate tectonics,core heat was mainly dissipated by networks of deep mantle plumes extending above the proto-LLVPs.These plume networks represent conduits of weakened mantle through which proto-lunar materials could later rise in a focused ejection.Continuing heat buildup in the core eventually triggered a cataclysmic explosion in the Pacific proto-LLVP,possibly analogous to a planetary-scale kimberlite eruption.This explosion launched LLVP and overlying mantle material into a low Earth orbit,where it coalesced to form the Moon.Some possible sources of additional energy to power the explosion are considered,including nuclear fission,bolide impacts and a hypothetical gravitational decay process culminating in a'A event'.
基金supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
文摘We investigated the impact of convexity and isoperimetric deficits on the accuracy of sectional area estimates of tree stems using traditional methods(caliper,tape,formulas based on stem diameter and circumference).In two complementary experiments,the use of photographs to estimate cross-sectional areas was first validated,then the use of a caliper and diameter tape was computer-simulated.The results indicated that the photographic method offers high precision,with mean relative errors below 0.1%,minimal deviation,and no significant bias,and the traditional methods led to substantial and systematic errors,with deviations from circularity and convexity significantly increasing the errors in area estimation.
文摘Conversational recommender systems(CRSs)focus on refining preferences and providing personalized recommendations through natural language interactions and dialogue history.Large language models(LLMs)have shown outstanding performance across various domains,thereby prompting researchers to investigate their applicability in recommendation systems.However,due to the lack of task-specific knowledge and an inefficient feature extraction process,LLMs still have suboptimal performance in recommendation tasks.Therefore,external knowledge sources,such as knowledge graphs(KGs)and knowledge bases(KBs),are often introduced to address the issue of data sparsity.Compared to KGs,KBs possess higher retrieval efficiency,making them more suitable for scenarios where LLMs serve as recommenders.To this end,we introduce a novel framework integrating LLMs with KBs for enhanced retrieval generation,namely LLMKB.LLMKB initially leverages structured knowledge to create mapping dictionaries,extracting entity-relation information from heterogeneous knowledge to construct KBs.Then,LLMKB achieves the embedding calibration between user information representations and documents in KBs through retrieval model fine-tuning.Finally,LLMKB employs retrievalaugmented generation to produce recommendations based on fused text inputs,followed by post-processing.Experiment results on two public CRS datasets demonstrate the effectiveness of our framework.Our code is publicly available at the link:https://anonymous.4open.science/r/LLMKB-6FD0.
基金supported by the Fundamental Research Funds for the Central Universities(No.CUC25SG013)the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),Ministry of Education(No.EIN2024C006).
文摘Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises.While large language models(LLMs)enable automated report generation,this specific domain lacks formal task definitions and corresponding benchmarks.To bridge this gap,we define the Automated Online Public Opinion Report Generation(OPOR-Gen)task and construct OPOR-Bench,an event-centric dataset with 463 crisis events across 108 countries(comprising 8.8 K news articles and 185 K tweets).To evaluate report quality,we propose OPOR-Eval,a novel agent-based framework that simulates human expert evaluation.Validation experiments show OPOR-Eval achieves a high Spearman’s correlation(ρ=0.70)with human judgments,though challenges in temporal reasoning persist.This work establishes an initial foundation for advancing automated public opinion reporting research.
基金supported by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project(2024ZD1000500)the National Natural Science Foundation of China(42172262 and 42372266)+1 种基金the China Geological Survey(DD20240041)the Fundamental Research Funds of the Institute of Geomechanics(DZLXJK202516).
文摘The Yingxiu-Beichuan fault zone(YBFZ)has long been active and experienced repeated large earthquakes.The physicochemical properties of the deep fault zone(>1000 m)are the key to understanding the deformation mechanism of large earthquakes.This study uses rock magnetic,microstructural,and geochemical analyses of representative samples exposed in FZ1681 within the Wenchuan Earthquake Fault Scientific Drilling borehole 2(WFSD-2)cores.Fault gouge and fault breccia have higher magnetic susceptibility values than wall rocks,and they contain abundant paramagnetic minerals and small quantities of magnetite and monoclinic pyrrhotite.The magnetite and monoclinic pyrrhotite in the fault gouge were mainly formed by coseismic frictional heating,indicating that large earthquakes with frictional heating temperatures of~500-900℃once occurred in the YBFZ.The seismogenic and coseismic environment was reducing with a relatively high sulfur content.The monoclinic pyrrhotite in the fault breccia was formed mainly by low-temperature hydrothermal fluid.This indicates that the fault zone experienced reducing and low-temperature(<400℃)hydrothermal fluid with a relatively high sulfur content after the earthquake.The YBFZ,which experiences frequent large earthquakes,is weakly oxidizing environment at different depths,but the effect of the low-temperature hydrothermal fluid is weaker at depth.
文摘One of the main issues in designing optimum tapered cascades for uranium enrichment for annual fuel production in a power reactor is whether to employ large(fat)or small(thin)cascades.What will be the permissible and optimal ranges of the number of machines that can be used in a cascade?For the first time,the permissible and optimal ranges of the number of gas centrifuges that can be utilized in a cascade were investigated using two types of centrifuges,and the performance of small and large tapered cascades was discussed.The particle swarm optimization algorithm(PSO)has been used to optimize tapered cascades.The results show:(1)For the first centrifuge,41 cascades(91≤n≤4897)and for the second centrifuge,49 cascades(18≤n≤3839)with small and large sizes can be used in enrichment facilities,and the best cascade for them has 530(with 23 stages)and 39(with 7 stages)centrifuges,respectively.(2)For both centrifuges,when 600≤n(number of centrifuges=n),the large cascade performance changes are relatively insignificant.(3)For both types of gas centrifuges,the annual los s of separation power in enrichment facilities is approximately 1.25%-4.82%of the total separation work required.
