Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing...Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.展开更多
As the hydrocarbon generation and storage mechanisms of high quality shales of Upper Ordovician Wufeng Formation– Lower Silurian Longmaxi Formation remain unclear, based on geological conditions and experimental mode...As the hydrocarbon generation and storage mechanisms of high quality shales of Upper Ordovician Wufeng Formation– Lower Silurian Longmaxi Formation remain unclear, based on geological conditions and experimental modelling of shale gas formation, the shale gas generation and accumulation mechanisms as well as their coupling relationships of deep-water shelf shales in Wufeng–Longmaxi Formation of Sichuan Basin were analyzed from petrology, mineralogy, and geochemistry. The high quality shales of Wufeng–Longmaxi Formation in Sichuan Basin are characterized by high thermal evolution, high hydrocarbon generation intensity, good material base, and good roof and floor conditions;the high quality deep-water shelf shale not only has high biogenic silicon content and organic carbon content, but also high porosity coupling. It is concluded that:(1) The shales had good preservation conditions and high retainment of crude oil in the early times, and the shale gas was mainly from cracking of crude oil.(2) The biogenic silicon(opal A) turned into crystal quartz in early times of burial diagenesis, lots of micro-size intergranular pores were produced in the same time;moreover, the biogenic silicon frame had high resistance to compaction, thus it provided the conditions not only for oil charge in the early stage, but also for formation and preservation of nanometer cellular-like pores, and was the key factor enabling the preservation of organic pores.(3) The high quality shale of Wufeng–Longmaxi Formation had high brittleness, strong homogeneity, siliceous intergranular micro-pores and nanometer organic pores, which were conducive to the formation of complicated fissure network connecting the siliceous intergranular nano-pores, and thus high and stable production of shale gas.展开更多
Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.You...Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.展开更多
Hydraulic stimulation technology is widely employed to enhance the permeability of geothermal reservoirs.Nevertheless,accurately predicting hydraulic fracture propagation in complex geological conditions remains chall...Hydraulic stimulation technology is widely employed to enhance the permeability of geothermal reservoirs.Nevertheless,accurately predicting hydraulic fracture propagation in complex geological conditions remains challenging,thereby hindering the effective utilization of existing natural fractures.In this study,a phase field model was developed utilizing the finite element method to examine the influence of fluid presence,stress conditions,and natural fractures on the initiation and propagation of hydraulic fractures.The model employs Biot's poroelasticity theory to establish the coupling between the displacement field and the fluid field,while the phase field theory is applied to simulate fracture behavior.The results show that whenσ_(x0)/σ_(y0)<3 or qf<20 kg/(m^(3)·s),the presence of natural fractures can alter the original propagation direction of hydraulic fractures.Conversely,in the absence of these conditions,the propagation path of natural fractures is predominantly influenced by the initial stress field.Furthermore,based on the analysis of breakdown pressure and damage area,the optimal intersection angle between natural fractures and hydraulic fractures is determined to range from 45°to 60°.Finally,once a dominant channel forms,initiating and propagating hydraulic fractures in other directions becomes increasingly difficult,even in highly fractured areas.This method tackles the challenges of initiating and propagating hydraulic fractures in complex geological conditions,providing a theoretical basis for optimizing Enhanced Geothermal System(EGS)projects.展开更多
The kinetic parameters of hydrocarbon generation are determined through experimental simulation and mathematical calculation using four typical samples selected from the Cretaceous Nenjiang Formation in the northwest ...The kinetic parameters of hydrocarbon generation are determined through experimental simulation and mathematical calculation using four typical samples selected from the Cretaceous Nenjiang Formation in the northwest of Songliao Basin,Chang 7 Member of Triassic Yanchang Formation in the southwest of Ordos Basin,Paleogene in the southwest of Qaidam Basin,and Lucaogou Formation of Jimusar Sag in the east of Junggar Basin.The results show that activation energy of hydrocarbon generation of organic matter is closely related to maturity and mainly ranges between 197 kJ/mol and 227 kJ/mol.On this basis,the temperature required for organic matter in shale to convert into oil was calculated.The ideal heating temperature is between 270℃and 300℃,and the conversation rate can reach 90%after 50-300 days of heating at constant temperature.When the temperature rises at a constant rate,the temperature corresponding to the major hydrocarbon generation period ranges from 225 to 350℃at the temperature rise rate of 1-150℃/month.In order to obtain higher economic benefits,it is suggested to adopt higher temperature rise rate(60-150℃/month).The more reliable kinetic parameters obtained can provide a basis for designing more reasonable scheme of in-situ heating conversion.展开更多
The energy loss of the power grid is one of the key factors affecting the economic operation of power systems. How to calculate the electric energy consumption accurately will have a great influence on the planning, o...The energy loss of the power grid is one of the key factors affecting the economic operation of power systems. How to calculate the electric energy consumption accurately will have a great influence on the planning, operation and management of the power grid. Currently there is a mountain of theoretical methods to calculate the line loss of the power system. However, these methods have some limitation, such as less considering the volatility of wind power resources. This paper presents an improved method to calculate the energy loss of wind power generation, considering the fluctuations of wind power generation. First, data are collected to obtain the curve of the typical daily expected output of wind farms for one month. Second, the curve of the typical daily expected output are corrected by the average electricity and the shape factor to obtain the curve of the typical daily equivalent output of wind farms for one month. Finally, the power flow is calculated by using typical daily equivalent output curve to describe the energy loss for one month. The results in the 110 kV main network show that the method is feasible.展开更多
The rapid spreading of the Photovoltaic (PV) Systems as Distributed Generation (DG) in medium and low voltage networks created many effects and changes on the existing power system networks. In this work, two methods ...The rapid spreading of the Photovoltaic (PV) Systems as Distributed Generation (DG) in medium and low voltage networks created many effects and changes on the existing power system networks. In this work, two methods have been used and applied to determine the optimal allocation and sizing of the PV to be installed as DGs (ranging from 250 kW up to 3 MW). The first one is to determine the location according to the maximal power losses reduction over the feeder. The second one is by using the Harmony Search Algorithm which is claimed to be a powerful technique for optimal allocation of PV systems. The results of the two techniques were compared and found to be nearly closed. Furthermore, investigation on the effects on the feeder in terms of voltage levels, power factor readings, and short circuit current levels has been done. All calculations and simulations are conducted by using the MATLAB Simulation Program. Some field calculations and observations have been expended in order to substantiate the research findings and validation.展开更多
In this paper, a significant enhancement in current efficiency of the green tandem organic light-emitting diodes(TOLEDs) is demonstrated, which is based on a buffer-modified charge generation layer(CGL) of fullerene c...In this paper, a significant enhancement in current efficiency of the green tandem organic light-emitting diodes(TOLEDs) is demonstrated, which is based on a buffer-modified charge generation layer(CGL) of fullerene carbon(C60)/zinc-phthalocyanine(ZnPc). Al and MoO3 were used as the buffer-modified layers on both sides of the bilayer C60/ZnPc, respectively. Experimental results show that the inserted Al and MoO3 layers can effectively increase the electron extraction of the CGL for obtaining the device performance enhancement. Compared with that of the green TOLEDs without buffer-modified layers in CGL(37.3 cd·A-1), the current efficiency of the green TOLEDs is increased to 54.1 cd·A-1. Further study results find that the performance can also be improved by optimizing the thickness of Al in the CGL. The maximum current efficiency and maximum luminance of the green TOLEDs achieve 63.5 cd·A-1 and 17 873 cd·m-2, respectively, when the multilayer structure of the CGL is Al(3 nm)/C60(5 nm)/ZnPc(5 nm)/MoO3(3 nm).展开更多
The integration of interfacial photothermal conversion and hydrovoltaic effect into bifunctional evaporators has emerged as a hopeful approach to address water and energy scarcities.However,developing low-cost bifunct...The integration of interfacial photothermal conversion and hydrovoltaic effect into bifunctional evaporators has emerged as a hopeful approach to address water and energy scarcities.However,developing low-cost bifunctional evaporators and elucidating the freshwater-electricity co-generation mechanism remain challenging.In this work,we prepare porous carbon from waste polyester through a metalorganic framework(MOF)-assisted carbonization strategy and subsequently fabricate a bifunctional evaporator for freshwater-hydroelectricity co-generation.The porous carbon contains rich oxygen-containing groups and shows hierarchical micro-and mesopores with a high specific surface area of 904 m^(2)g^(-1).The porous carbon-based evaporator shows broadband and high light absorption,localized thermal management,good hydrophilicity,and high flexibility.Benefiting from these merits,it achieves high-performance freshwater and hydroelectricity co-generation,with the opencircuit voltage of 250 mV,the short-circuit current of 14μA,and the evaporation rate of 2.34 kg m^(-2)h^(-1).Hence,it is ranked among the most efficient freshwater-hydroelectricity co-generator.Additionally,the weakened hydrogen-bonding network reduces water evaporation enthalpy to 1.7 kJ g^(-1).Mechanistic investigations reveal that selective Na+interaction induces differential ion migration rate to generate streaming potential,as evidenced by molecular dynamics simulations.Meanwhile,the photothermal effect enhances voltage output by promoting interfacial ion concentration gradients.During the outdoor freshwater-electricity co-generation,it shows the voltage output of 250 mV and freshwater production of 2.34 kg m-2.This work not only puts forward a new platform to fabricate advanced evaporators from low-cost waste plastics but also unravels the freshwater-electricity co-generation mechanism,offering scalable strategies to tackle freshwater and energy crises.展开更多
We are sorry for the mistakes of Affiliation,"a State Key Laboratory of Advanced Fiber Materials,Center for Advanced Low-Dimension Materials,Donghua University,Shanghai 201620,China"should be replaced by&quo...We are sorry for the mistakes of Affiliation,"a State Key Laboratory of Advanced Fiber Materials,Center for Advanced Low-Dimension Materials,Donghua University,Shanghai 201620,China"should be replaced by"a State Key Laboratory of Advanced Fiber Materials,Center for Advanced Low-Dimension Materials,College of Materials Science and Engineering,Donghua University,Shanghai 201620,China".We apologized for the inconvenience caused by this error.展开更多
In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we devel...In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we develop a multimodal framework that integrates symbolic task reasoning with continuous trajectory generation.The approach employs transformer models and adversarial training to map high-level intent to robotic motion.Information from multiple data sources,such as voice traits,hand and body keypoints,visual observations,and recorded paths,is integrated simultaneously.These signals are mapped into a shared representation that supports interpretable reasoning while enabling smooth and realistic motion generation.Based on this design,two different learning strategies are investigated.In the first step,grammar-constrained Linear Temporal Logic(LTL)expressions are created from multimodal human inputs.These expressions are subsequently decoded into robot trajectories.The second method generates trajectories directly from symbolic intent and linguistic data,bypassing an intermediate logical representation.Transformer encoders combine multiple types of information,and autoregressive transformer decoders generate motion sequences.Adding smoothness and speed limits during training increases the likelihood of physical feasibility.To improve the realism and stability of the generated trajectories during training,an adversarial discriminator is also included to guide them toward the distribution of actual robot motion.Tests on the NATSGLD dataset indicate that the complete system exhibits stable training behaviour and performance.In normalised coordinates,the logic-based pipeline has an Average Displacement Error(ADE)of 0.040 and a Final Displacement Error(FDE)of 0.036.The adversarial generator makes substantially more progress,reducing ADE to 0.021 and FDE to 0.018.Visual examination confirms that the generated trajectories closely align with observed motion patterns while preserving smooth temporal dynamics.展开更多
The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A roll...The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.展开更多
A controllable strategy for eliciting nuclear fusion is presented through ultra-intenselaser derived positron generation by a conceptual first physics perspective. The capability to generate positrons on demand in a c...A controllable strategy for eliciting nuclear fusion is presented through ultra-intenselaser derived positron generation by a conceptual first physics perspective. The capability to generate positrons on demand in a controlled manner through an ultra-intense laser incident on a high atomic number target, such as gold, is the intrinsic core to the foundation of controllable nuclear fusion. Positron antimatter generated from the periphery of the fusion fuel pellet provides the basis for initiating the fusion reaction, which is regulated by controlling the operation of the ultra-intense laser. A dual pulsed Fast Ignition mechanism is selected to achieve the fusion reaction. Based on first physics performance analysis the controllable strategy for eliciting nuclear fusion through ultra-intenselaser derived positron generation offers a realizable means for achieving regulated nuclear fusion. A future perspective of the controllable fusion strategy addresses the opportunities and concerns of a pathway toward regulated nuclear fusion.展开更多
This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following th...This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following three points: 1) This method determines the profit and loss and payback period in order to evaluate the installation of photovoltaic power generation, taking into account the price of equipment, solar battery module conversion efficiency, subsidy, electricity purchase price, service life and rate for selling electricity. 2) The proposed evaluation method was applied to Kanagawa Prefecture in Japan, providing plural scenarios. Using a solar battery module conversion efficiency of more than 15%, it is possible to make the payback period shorter than the 20-year service life and anticipate a profit in almost the whole area. 3) The areas suitable for photovoltaic power generation are Kawasaki City and Ninomiya-machi. It is necessary to adopt measures to increase the subsidy and install photovoltaic power generating systems in specific places in areas where subsidies are not provided in enough amounts.展开更多
The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data st...Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data structure to create virtual samples,which can be used to augment the original dataset.The ALVSG process consists of two steps.First,an average-linkage clustering technique is applied to the dataset to create a dendrogram.The dendrogram represents the hierarchical structure of the dataset,with each merging operation regarded as a linkage.Next,the linkages are combined into an average-based dataset,which serves as a new representation of the dataset.The second step in the ALVSG process involves generating virtual samples using the average-based dataset.The research project generates a set of 100 virtual samples by uniformly distributing them within the provided boundary.These virtual samples are then added to the original dataset,creating a more extensive dataset with improved generalization performance.The efficacy of the ALVSG approach is validated through resampling experiments and t-tests conducted on two small real-world datasets.The experiments are conducted on three forecasting models:the support vector machine for regression(SVR),the deep learning model(DL),and XGBoost.The results show that the ALVSG approach outperforms the baseline methods in terms of mean square error(MSE),root mean square error(RMSE),and mean absolute error(MAE).展开更多
It remains difficult to automate the creation and validation of Unified Modeling Language(UML)dia-grams due to unstructured requirements,limited automated pipelines,and the lack of reliable evaluation methods.This stu...It remains difficult to automate the creation and validation of Unified Modeling Language(UML)dia-grams due to unstructured requirements,limited automated pipelines,and the lack of reliable evaluation methods.This study introduces a cohesive architecture that amalgamates requirement development,UML synthesis,and multimodal validation.First,LLaMA-3.2-1B-Instruct was utilized to generate user-focused requirements.Then,DeepSeek-R1-Distill-Qwen-32B applies its reasoning skills to transform these requirements into PlantUML code.Using this dual-LLM pipeline,we constructed a synthetic dataset of 11,997 UML diagrams spanning six major diagram families.Rendering analysis showed that 89.5%of the generated diagrams compile correctly,while invalid cases were detected automatically.To assess quality,we employed a multimodal scoring method that combines Qwen2.5-VL-3B,LLaMA-3.2-11B-Vision-Instruct and Aya-Vision-8B,with weights based on MMMU performance.A study with 94 experts revealed strong alignment between automatic and manual evaluations,yielding a Pearson correlation of r=0.82 and a Fleiss’Kappa of 0.78.This indicates a high degree of concordance between automated metrics and human judgment.Overall,the results demonstrated that our scoring system is effective and that the proposed generation pipeline produces UML diagrams that are both syntactically correct and semantically coherent.More broadly,the system provides a scalable and reproducible foundation for future work in AI-driven software modeling and multimodal verification.展开更多
Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined ...Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.展开更多
Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural ...Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.展开更多
文摘Present day power scenarios demand a high quality uninterrupted power supply and needs environmental issues to be addressed. Both concerns can be dealt with by the introduction of the renewable sources to the existing power system. Thus, automatic generation control(AGC) with diverse renewable sources and a modified-cascaded controller are presented in the paper.Also, a new hybrid scheme of the improved teaching learning based optimization-differential evolution(hITLBO-DE) algorithm is applied for providing optimization of controller parameters. A study of the system with a technique such as TLBO applied to a proportional integral derivative(PID), integral double derivative(IDD) and PIDD is compared to hITLBO-DE tuned cascaded controller with dynamic load change.The suggested methodology has been extensively applied to a 2-area system with a diverse source power system with various operation time non-linearities such as dead-band of, generation rate constraint and reheat thermal units. The multi-area system with reheat thermal plants, hydel plants and a unit of a wind-diesel combination is tested with the cascaded controller scheme with a different controller setting for each area. The variation of the load is taken within 1% to 5% of the connected load and robustness analysis is shown by modifying essential factors simultaneously by± 30%. Finally, the proposed scheme of controller and optimization technique is also tested with a 5-equal area thermal system with non-linearities. The simulation results demonstrate the superiority of the proposed controller and algorithm under a dynamically changing load.
基金Supported by the China National Science and Technology Major Project(2017ZX05036,2017ZX05036001).
文摘As the hydrocarbon generation and storage mechanisms of high quality shales of Upper Ordovician Wufeng Formation– Lower Silurian Longmaxi Formation remain unclear, based on geological conditions and experimental modelling of shale gas formation, the shale gas generation and accumulation mechanisms as well as their coupling relationships of deep-water shelf shales in Wufeng–Longmaxi Formation of Sichuan Basin were analyzed from petrology, mineralogy, and geochemistry. The high quality shales of Wufeng–Longmaxi Formation in Sichuan Basin are characterized by high thermal evolution, high hydrocarbon generation intensity, good material base, and good roof and floor conditions;the high quality deep-water shelf shale not only has high biogenic silicon content and organic carbon content, but also high porosity coupling. It is concluded that:(1) The shales had good preservation conditions and high retainment of crude oil in the early times, and the shale gas was mainly from cracking of crude oil.(2) The biogenic silicon(opal A) turned into crystal quartz in early times of burial diagenesis, lots of micro-size intergranular pores were produced in the same time;moreover, the biogenic silicon frame had high resistance to compaction, thus it provided the conditions not only for oil charge in the early stage, but also for formation and preservation of nanometer cellular-like pores, and was the key factor enabling the preservation of organic pores.(3) The high quality shale of Wufeng–Longmaxi Formation had high brittleness, strong homogeneity, siliceous intergranular micro-pores and nanometer organic pores, which were conducive to the formation of complicated fissure network connecting the siliceous intergranular nano-pores, and thus high and stable production of shale gas.
文摘Standards are the common language that consolidates global consensus and builds the most solid foundation for international partnerships.They are the cornerstone for global sustainable and high-quality development.Young students,with their active and vibrant minds,represent the future and hope of standardization.
基金supported by the National Key Research and Development Program(2021YFB150740401)National Natural Science Foundation of China(42202336)the CAS Pioneer Hundred Talents Program in China(Y826031C01)。
文摘Hydraulic stimulation technology is widely employed to enhance the permeability of geothermal reservoirs.Nevertheless,accurately predicting hydraulic fracture propagation in complex geological conditions remains challenging,thereby hindering the effective utilization of existing natural fractures.In this study,a phase field model was developed utilizing the finite element method to examine the influence of fluid presence,stress conditions,and natural fractures on the initiation and propagation of hydraulic fractures.The model employs Biot's poroelasticity theory to establish the coupling between the displacement field and the fluid field,while the phase field theory is applied to simulate fracture behavior.The results show that whenσ_(x0)/σ_(y0)<3 or qf<20 kg/(m^(3)·s),the presence of natural fractures can alter the original propagation direction of hydraulic fractures.Conversely,in the absence of these conditions,the propagation path of natural fractures is predominantly influenced by the initial stress field.Furthermore,based on the analysis of breakdown pressure and damage area,the optimal intersection angle between natural fractures and hydraulic fractures is determined to range from 45°to 60°.Finally,once a dominant channel forms,initiating and propagating hydraulic fractures in other directions becomes increasingly difficult,even in highly fractured areas.This method tackles the challenges of initiating and propagating hydraulic fractures in complex geological conditions,providing a theoretical basis for optimizing Enhanced Geothermal System(EGS)projects.
基金Supported by the PetroChina Science and Technology Major Project(2016E-0101).
文摘The kinetic parameters of hydrocarbon generation are determined through experimental simulation and mathematical calculation using four typical samples selected from the Cretaceous Nenjiang Formation in the northwest of Songliao Basin,Chang 7 Member of Triassic Yanchang Formation in the southwest of Ordos Basin,Paleogene in the southwest of Qaidam Basin,and Lucaogou Formation of Jimusar Sag in the east of Junggar Basin.The results show that activation energy of hydrocarbon generation of organic matter is closely related to maturity and mainly ranges between 197 kJ/mol and 227 kJ/mol.On this basis,the temperature required for organic matter in shale to convert into oil was calculated.The ideal heating temperature is between 270℃and 300℃,and the conversation rate can reach 90%after 50-300 days of heating at constant temperature.When the temperature rises at a constant rate,the temperature corresponding to the major hydrocarbon generation period ranges from 225 to 350℃at the temperature rise rate of 1-150℃/month.In order to obtain higher economic benefits,it is suggested to adopt higher temperature rise rate(60-150℃/month).The more reliable kinetic parameters obtained can provide a basis for designing more reasonable scheme of in-situ heating conversion.
文摘The energy loss of the power grid is one of the key factors affecting the economic operation of power systems. How to calculate the electric energy consumption accurately will have a great influence on the planning, operation and management of the power grid. Currently there is a mountain of theoretical methods to calculate the line loss of the power system. However, these methods have some limitation, such as less considering the volatility of wind power resources. This paper presents an improved method to calculate the energy loss of wind power generation, considering the fluctuations of wind power generation. First, data are collected to obtain the curve of the typical daily expected output of wind farms for one month. Second, the curve of the typical daily expected output are corrected by the average electricity and the shape factor to obtain the curve of the typical daily equivalent output of wind farms for one month. Finally, the power flow is calculated by using typical daily equivalent output curve to describe the energy loss for one month. The results in the 110 kV main network show that the method is feasible.
文摘The rapid spreading of the Photovoltaic (PV) Systems as Distributed Generation (DG) in medium and low voltage networks created many effects and changes on the existing power system networks. In this work, two methods have been used and applied to determine the optimal allocation and sizing of the PV to be installed as DGs (ranging from 250 kW up to 3 MW). The first one is to determine the location according to the maximal power losses reduction over the feeder. The second one is by using the Harmony Search Algorithm which is claimed to be a powerful technique for optimal allocation of PV systems. The results of the two techniques were compared and found to be nearly closed. Furthermore, investigation on the effects on the feeder in terms of voltage levels, power factor readings, and short circuit current levels has been done. All calculations and simulations are conducted by using the MATLAB Simulation Program. Some field calculations and observations have been expended in order to substantiate the research findings and validation.
基金supported by the Scientific and Technological Research Foundation of Chongqing Municipal Education Commission(No.KJ1600439)the Basic and Advanced Technology Research Project of Chongqing Municipality(No.cstc2018jcyjAX0462)the Scientific and Technological Research Foundation of Chongqing Municipal Education Commission(No.KJ1500404)
文摘In this paper, a significant enhancement in current efficiency of the green tandem organic light-emitting diodes(TOLEDs) is demonstrated, which is based on a buffer-modified charge generation layer(CGL) of fullerene carbon(C60)/zinc-phthalocyanine(ZnPc). Al and MoO3 were used as the buffer-modified layers on both sides of the bilayer C60/ZnPc, respectively. Experimental results show that the inserted Al and MoO3 layers can effectively increase the electron extraction of the CGL for obtaining the device performance enhancement. Compared with that of the green TOLEDs without buffer-modified layers in CGL(37.3 cd·A-1), the current efficiency of the green TOLEDs is increased to 54.1 cd·A-1. Further study results find that the performance can also be improved by optimizing the thickness of Al in the CGL. The maximum current efficiency and maximum luminance of the green TOLEDs achieve 63.5 cd·A-1 and 17 873 cd·m-2, respectively, when the multilayer structure of the CGL is Al(3 nm)/C60(5 nm)/ZnPc(5 nm)/MoO3(3 nm).
基金supported by the National Natural Science Foundation of China(52373099)Interdisciplinary Research Program of Huazhong University of Science and Technology(5003013161)+1 种基金Innovation and Talent Recruitment Base of New Energy Chemistry and Device(B21003)Hubei Integrative Technology and Innovation Center for Advanced Fiberous Materials(XC202502)。
文摘The integration of interfacial photothermal conversion and hydrovoltaic effect into bifunctional evaporators has emerged as a hopeful approach to address water and energy scarcities.However,developing low-cost bifunctional evaporators and elucidating the freshwater-electricity co-generation mechanism remain challenging.In this work,we prepare porous carbon from waste polyester through a metalorganic framework(MOF)-assisted carbonization strategy and subsequently fabricate a bifunctional evaporator for freshwater-hydroelectricity co-generation.The porous carbon contains rich oxygen-containing groups and shows hierarchical micro-and mesopores with a high specific surface area of 904 m^(2)g^(-1).The porous carbon-based evaporator shows broadband and high light absorption,localized thermal management,good hydrophilicity,and high flexibility.Benefiting from these merits,it achieves high-performance freshwater and hydroelectricity co-generation,with the opencircuit voltage of 250 mV,the short-circuit current of 14μA,and the evaporation rate of 2.34 kg m^(-2)h^(-1).Hence,it is ranked among the most efficient freshwater-hydroelectricity co-generator.Additionally,the weakened hydrogen-bonding network reduces water evaporation enthalpy to 1.7 kJ g^(-1).Mechanistic investigations reveal that selective Na+interaction induces differential ion migration rate to generate streaming potential,as evidenced by molecular dynamics simulations.Meanwhile,the photothermal effect enhances voltage output by promoting interfacial ion concentration gradients.During the outdoor freshwater-electricity co-generation,it shows the voltage output of 250 mV and freshwater production of 2.34 kg m-2.This work not only puts forward a new platform to fabricate advanced evaporators from low-cost waste plastics but also unravels the freshwater-electricity co-generation mechanism,offering scalable strategies to tackle freshwater and energy crises.
文摘We are sorry for the mistakes of Affiliation,"a State Key Laboratory of Advanced Fiber Materials,Center for Advanced Low-Dimension Materials,Donghua University,Shanghai 201620,China"should be replaced by"a State Key Laboratory of Advanced Fiber Materials,Center for Advanced Low-Dimension Materials,College of Materials Science and Engineering,Donghua University,Shanghai 201620,China".We apologized for the inconvenience caused by this error.
基金The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through the project number(PSAU/2024/01/32082).
文摘In Human–Robot Interaction(HRI),generating robot trajectories that accurately reflect user intentions while ensuring physical realism remains challenging,especially in unstructured environments.In this study,we develop a multimodal framework that integrates symbolic task reasoning with continuous trajectory generation.The approach employs transformer models and adversarial training to map high-level intent to robotic motion.Information from multiple data sources,such as voice traits,hand and body keypoints,visual observations,and recorded paths,is integrated simultaneously.These signals are mapped into a shared representation that supports interpretable reasoning while enabling smooth and realistic motion generation.Based on this design,two different learning strategies are investigated.In the first step,grammar-constrained Linear Temporal Logic(LTL)expressions are created from multimodal human inputs.These expressions are subsequently decoded into robot trajectories.The second method generates trajectories directly from symbolic intent and linguistic data,bypassing an intermediate logical representation.Transformer encoders combine multiple types of information,and autoregressive transformer decoders generate motion sequences.Adding smoothness and speed limits during training increases the likelihood of physical feasibility.To improve the realism and stability of the generated trajectories during training,an adversarial discriminator is also included to guide them toward the distribution of actual robot motion.Tests on the NATSGLD dataset indicate that the complete system exhibits stable training behaviour and performance.In normalised coordinates,the logic-based pipeline has an Average Displacement Error(ADE)of 0.040 and a Final Displacement Error(FDE)of 0.036.The adversarial generator makes substantially more progress,reducing ADE to 0.021 and FDE to 0.018.Visual examination confirms that the generated trajectories closely align with observed motion patterns while preserving smooth temporal dynamics.
文摘The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.
文摘A controllable strategy for eliciting nuclear fusion is presented through ultra-intenselaser derived positron generation by a conceptual first physics perspective. The capability to generate positrons on demand in a controlled manner through an ultra-intense laser incident on a high atomic number target, such as gold, is the intrinsic core to the foundation of controllable nuclear fusion. Positron antimatter generated from the periphery of the fusion fuel pellet provides the basis for initiating the fusion reaction, which is regulated by controlling the operation of the ultra-intense laser. A dual pulsed Fast Ignition mechanism is selected to achieve the fusion reaction. Based on first physics performance analysis the controllable strategy for eliciting nuclear fusion through ultra-intenselaser derived positron generation offers a realizable means for achieving regulated nuclear fusion. A future perspective of the controllable fusion strategy addresses the opportunities and concerns of a pathway toward regulated nuclear fusion.
文摘This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following three points: 1) This method determines the profit and loss and payback period in order to evaluate the installation of photovoltaic power generation, taking into account the price of equipment, solar battery module conversion efficiency, subsidy, electricity purchase price, service life and rate for selling electricity. 2) The proposed evaluation method was applied to Kanagawa Prefecture in Japan, providing plural scenarios. Using a solar battery module conversion efficiency of more than 15%, it is possible to make the payback period shorter than the 20-year service life and anticipate a profit in almost the whole area. 3) The areas suitable for photovoltaic power generation are Kawasaki City and Ninomiya-machi. It is necessary to adopt measures to increase the subsidy and install photovoltaic power generating systems in specific places in areas where subsidies are not provided in enough amounts.
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
基金funding support from the National Science and Technology Council(NSTC),under Grant No.114-2410-H-011-026-MY3.
文摘Small datasets are often challenging due to their limited sample size.This research introduces a novel solution to these problems:average linkage virtual sample generation(ALVSG).ALVSG leverages the underlying data structure to create virtual samples,which can be used to augment the original dataset.The ALVSG process consists of two steps.First,an average-linkage clustering technique is applied to the dataset to create a dendrogram.The dendrogram represents the hierarchical structure of the dataset,with each merging operation regarded as a linkage.Next,the linkages are combined into an average-based dataset,which serves as a new representation of the dataset.The second step in the ALVSG process involves generating virtual samples using the average-based dataset.The research project generates a set of 100 virtual samples by uniformly distributing them within the provided boundary.These virtual samples are then added to the original dataset,creating a more extensive dataset with improved generalization performance.The efficacy of the ALVSG approach is validated through resampling experiments and t-tests conducted on two small real-world datasets.The experiments are conducted on three forecasting models:the support vector machine for regression(SVR),the deep learning model(DL),and XGBoost.The results show that the ALVSG approach outperforms the baseline methods in terms of mean square error(MSE),root mean square error(RMSE),and mean absolute error(MAE).
基金supported by the DH2025-TN07-07 project conducted at the Thai Nguyen University of Information and Communication Technology,Thai Nguyen,Vietnam,with additional support from the AI in Software Engineering Lab.
文摘It remains difficult to automate the creation and validation of Unified Modeling Language(UML)dia-grams due to unstructured requirements,limited automated pipelines,and the lack of reliable evaluation methods.This study introduces a cohesive architecture that amalgamates requirement development,UML synthesis,and multimodal validation.First,LLaMA-3.2-1B-Instruct was utilized to generate user-focused requirements.Then,DeepSeek-R1-Distill-Qwen-32B applies its reasoning skills to transform these requirements into PlantUML code.Using this dual-LLM pipeline,we constructed a synthetic dataset of 11,997 UML diagrams spanning six major diagram families.Rendering analysis showed that 89.5%of the generated diagrams compile correctly,while invalid cases were detected automatically.To assess quality,we employed a multimodal scoring method that combines Qwen2.5-VL-3B,LLaMA-3.2-11B-Vision-Instruct and Aya-Vision-8B,with weights based on MMMU performance.A study with 94 experts revealed strong alignment between automatic and manual evaluations,yielding a Pearson correlation of r=0.82 and a Fleiss’Kappa of 0.78.This indicates a high degree of concordance between automated metrics and human judgment.Overall,the results demonstrated that our scoring system is effective and that the proposed generation pipeline produces UML diagrams that are both syntactically correct and semantically coherent.More broadly,the system provides a scalable and reproducible foundation for future work in AI-driven software modeling and multimodal verification.
基金Nguyen Tat Thanh University,Ho Chi Minh City,Vietnam for supporting this study。
文摘Wing design is a critical factor in the aerodynamic performance of flapping-wing(FW)robots.Inspired by the natural wing structures of insects,bats,and birds,we explored how bio-mimetic wing vein morphologies,combined with a bio-inspired double wing clap-and-fling mechanism,affect thrust generation.This study focused on increasing vertical force and payload capacity.Through systematic experimentation with various vein configurations and structural designs,we developed innovative wings optimized for thrust production.Comprehensive tests were conducted to measure aerodynamic forces,power consumption,and wing kinematics across a range of flapping frequencies.Additionally,wings with different aspect ratios,a key factor in wing design,were fabricated and extensively evaluated.The study also examined the role of bio-inspired vein layouts on wing flexibility,a critical component in improving flight efficiency.Our findings demonstrate that the newly developed wing design led to a 20%increase in thrust,achieving up to 30 g-force(gf).This research sheds light on the clap-and-fling effect and establishes a promising framework for bio-inspired wing design,offering significant improvements in both performance and payload capacity for FW robots.
基金supported by the National Key Research and Development Program of China(2023YFF0906502)the Postgraduate Research and Innovation Project of Hunan Province under Grant(CX20240473).
文摘Due to the digital transformation tendency among cultural institutions and the substantial influence of the social media platform,the demands of visual communication keep increasing for promoting traditional cultural artifacts online.As an effective medium,posters serve to attract public attention and facilitate broader engagement with cultural artifacts.However,existing poster generation methods mainly rely on fixed templates and manual design,which limits their scalability and adaptability to the diverse visual and semantic features of the artifacts.Therefore,we propose CAPGen,an automated aesthetic Cultural Artifacts Poster Generation framework built on a Multimodal Large Language Model(MLLM)with integrated iterative optimization.During our research,we collaborated with designers to define principles of graphic design for cultural artifact posters,to guide the MLLM in generating layout parameters.Later,we generated these parameters into posters.Finally,we refined the posters using an MLLM integrated with a multi-round iterative optimization mechanism.Qualitative results show that CAPGen consistently outperforms baseline methods in both visual quality and aesthetic performance.Furthermore,ablation studies indicate that the prompt,iterative optimization mechanism,and design principles significantly enhance the effectiveness of poster generation.
