The NHS is right now confronting huge pressures relating to demand and capacity in radiology. The purpose of this research has been to provide information about MRI usage, details of operational aspects of MRI service...The NHS is right now confronting huge pressures relating to demand and capacity in radiology. The purpose of this research has been to provide information about MRI usage, details of operational aspects of MRI services, and to ascertain the planning intentions of NHS radiology services to keep up and create MRI capacity. The report expands on using Discrete Event Simulation (DES) to inspect and plan the utilisation of NHS hospital resources for the radiology department to help a 24 hr service that is available to outpatients which will help with diminishing patient waiting time, better resource usage, understanding the capacity and demand. Consequently, this research examines to adjust staff and resources with the demand of the MRI. The research was investigated using DES in various scenarios to find which resources are inactive;patients are treated slowly. DES helped in discovering resource utilisation and outpatient throughout the system. It additionally helped in distinguishing the bottlenecks in patient flow. The DES simulation results demonstrated that time for the outpatient in the system is less and more outpatients have been treated too. There is a higher level of outpatient patients leaving the system under 120 minutes. The report uncovered an MRI report interpretation time. Reception room time and MRI waiting room time are decreased significantly. It additionally exhibited with an expanded outflow of outpatients, resources, for example, MRI capacity and radiographer utilisation expanded.展开更多
To determinate the expressway capacity near a bus bay stop with an access, capacity models on the expressway near a bus stop with an access were developed on the basis of gap acceptance theory and queuing theory. Depe...To determinate the expressway capacity near a bus bay stop with an access, capacity models on the expressway near a bus stop with an access were developed on the basis of gap acceptance theory and queuing theory. Depending on a bus stop position to an entrance or an exit ramp, the capacity models were developed for four cases. Bus bay stops with overflow and bus bay stops without overflow were considered. A comparison of simulation experiment and model calculation was carried out. Results show that the suggested models have high accuracy and reliability, at bus arrival rate below 60 vehicles per hour(veh/h) or vehicle volumes at the entrance and the exit below 200 passenger cars units per hour(pcu/h), and there are no significant difference in the capacities for four cases. When bus arrival rate is above 240 veh/h, the capacities of all four cases will decline rapidly. With berth number increasing, the increasing of the capacities is no obvious for four cases. As the bus arrival rate and vehicle volumes at the entrance and the exit increase, bus stops located downstream of an entrance and upstream of an exit have a remarkably effect on the capacities. The latter case is much heavier than the former. Those results can be used to traffic design and optimization on urban expressway near a bus stop with an access.展开更多
This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process s...This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process simulation in semi-arid regions, a spatially varying storage capacity (VSC) model was developed based on the spatial distribution of water storage capacity and the vertical hybrid runoff mechanism. To verify the applicability of the VSC model, both the VSC model and a hybrid runoff model were used to simulate daily runoff processes in the catchment upstream of the Dianzi hydrological station from 1973 to 1979. The results showed that the annual average Nash-Sutcliffe coefficient was 0.80 for the VSC model, and only 0.67 for the hybrid runoff model. The higher annual average Nash-Sutcliffe coefficient of the VSC model means that this hydrological model can better simulate daily runoff processes in semi-arid regions. Furthermore, as a distributed hydrological model, the VSC model can be applied in regional water resource management.展开更多
In the existing power system with a large-scale hydrogen storage system,there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage system.In order...In the existing power system with a large-scale hydrogen storage system,there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage system.In order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation,and speed up the process of electric-hydrogen-electricity conversion.This article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit,and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen storage unit.These models are of great significance for studying and optimizing gas storage technology.Through these models,the performance of gas storage units can be better understood and improved.These studies are very helpful for improving energy storage efficiency and sustainable development.The factors affecting the charge-discharge efficiency of hydrogen storage units are analyzed.By integrating the models of each unit and considering the capacity degradation of the hydrogen storage system,we can construct an efficiency model for a large hydrogen storage system and power conversion system.In addition,the simulation models of the hydrogen production system and hydrogen consumption system were established in MATLAB/Simulink.The accuracy and effectiveness of the simulation model were proved by comparing the output voltage variation curve of the simulation with the polarization curve of the typical hydrogen production system and hydrogen consumption system.The results show that the charge-discharge efficiency of the hydrogen storage unit increases with the increase of operating temperature,and H2 and O2 partial voltage have little influence on the charge-discharge efficiency.In the process of power conversion system converter rectification operation,its efficiency decreases with the increase of temperature,while in the process of inverter operation,power conversion system efficiency increases with the increase of temperature.Combined with the efficiency of each hydrogen storage unit and power conversion system converter,the upper limit of the capacity loss of different hydrogen storage units was set.The optimal charge-discharge efficiency of the hydrogen storage system was obtained by using the Cplex solver at 36.46%and 66.34%.展开更多
Tan's contact C is an important quantity measuring the two-body correlations at short distances in a dilute system.Here we make use of the technique of exactly solved models to study the thermal-contact capacity K...Tan's contact C is an important quantity measuring the two-body correlations at short distances in a dilute system.Here we make use of the technique of exactly solved models to study the thermal-contact capacity K_(T),i.e.,the derivative of C with respect to temperature in the attractive Gaudin-Yang model.It is found that K_(T) is useful in identifying the low temperature phase diagram,and using the obtained analytical expression of K_(T),we study its critical behavior and the scaling law.Especially,we show K_(T) versus temperature and thus the non-monotonic tendency of C in a tiny interval,for both spin-balanced and imbalanced phases.Such a phenomenon is merely observed in multi-component systems such as SU(2)Fermi gases and spinor bosons,indicating the crossover from the Tomonaga-Luttinger liquid to the spin-coherent liquid.展开更多
The concept of the carbon cycle in the old goaf of a coal mine based on CO_(2)utilization and storage was put forward adhering to the principle of low-carbon development,utilization of space resources in old goafs,and...The concept of the carbon cycle in the old goaf of a coal mine based on CO_(2)utilization and storage was put forward adhering to the principle of low-carbon development,utilization of space resources in old goafs,and associated gas resources development.Firstly,the evolution characteristics of overburden fissures in the goaf of the case was studied using a two-dimensional physical similarity simulation test,the sealing performance of the caprocks after stabilization was analyzed,and the fissures were counted and classi-fied.Then,the process of gaseous CO_(2)injection in the connected fissure was simulated by Ansys Fluent software,and the migration law and distribution characteristics of CO_(2)under the condition of gaseous CO_(2)injection were analyzed.Finally,the estimation models of free CO_(2)storage capacity in the old goaf were constructed considering the proportion of connected fissure and the effectiveness of CO_(2)injection.The CO_(2)storage capacity in the old goaf of the case coal mine was estimated.The results showed that a caprock group of“hard-thickness low-permeability hard-thickness”was formed after the caprock-fissures system in the goaf of the case tended to be stable vertically.The connected fissure,occlude cracks,and micro-fractures in the goaf accounted for 85.5%,8.5%,and 6%of the total fissures,respectively.Gaseous CO_(2)first migrated to the bottom of the connected fissure after CO_(2)was injected into the goaf,then spread horizontally along the bottom of the connected fissure after reaching the bottom,and finally spread longitudinally after filling the bottom of the entire connected fissure.The theoretical and effective storage capacities of free CO_(2)at normal temperature and pressure in the old goaf of the case were 9757 and 7477 t,respectively.The effective storage capacity of free CO_(2)at normal temperature and pressure in the old goaf after all minefield mined was 193404 t.The research can provide some reference for the coal mining industry to help the goal of“carbon peaking and carbon neutrality”.展开更多
The transmission capacity of gas pipeline networks should be calculated and allocated to deal with the capacity booking with shippers. Technical capacities, which depend on the gas flow distribution at routes or inter...The transmission capacity of gas pipeline networks should be calculated and allocated to deal with the capacity booking with shippers. Technical capacities, which depend on the gas flow distribution at routes or interchange points, are calculated with a multiobjective optimization model and form a Pareto solution set in the entry/exit or point-to-point regime. Then, the commercial capacities, which can be directly applied in capacity booking, are calculated with single-objective optimization models that are transformed from the above multiobjective model based on three allocation rules and the demand of shippers.Next, peak-shaving capacities, which are daily oversupply or overdelivery amounts at inlets or deliveries,are calculated with two-stage transient optimization models. Considering the hydraulic process of a pipeline network and operating schemes of compressor stations, all the above models are mixed-integer nonlinear programming problems. Finally, a case study is made to demonstrate the ability of the models.展开更多
As a basic natural resource and strategic economic resource,the development and utilization of water resources is an important issue related to the national economy and people's livelihood.How to scientifically ev...As a basic natural resource and strategic economic resource,the development and utilization of water resources is an important issue related to the national economy and people's livelihood.How to scientifically evaluate the water resources carrying capacity is the premise to improve the regional water resources carrying capacity and ensure the regional water security.The Gansu section of the Yellow River basin is an important water conservation and recharge area.Whether the water resources in this area can ensure the normal operation of the ecosystem and whether it can carry the sustainable development of social economy is the key to realize the high-quality development of the Yellow River basin.In this study,from the three dimensions of water consumption per capita,water consumption of 10000 yuan GDP and ecological water use rate,by constructing the evaluation index system and index grading standard of water resources carrying capacity,the fuzzy comprehensive evaluation model was used to evaluate the water resources carrying capacity of Gansu section of the Yellow River Basin,in order to provide theoretical decision-making basis for the comprehensive development,utilization and planning management of water resources in Gansu section of the Yellow River basin and even the whole basin,and help the high-quality development of the Yellow River basin.展开更多
Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind−Magnetosphere−Ionosphere Link Explorer(SMILE)will observe magnetosheath and its boundary motion in soft X-rays for understanding magnetopause reconnectio...Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind−Magnetosphere−Ionosphere Link Explorer(SMILE)will observe magnetosheath and its boundary motion in soft X-rays for understanding magnetopause reconnection modes under various solar wind conditions after their respective launches in 2024 and 2025.Magnetosheath conditions,namely,plasma density,velocity,and temperature,are key parameters for predicting and analyzing soft X-ray images from the LEXI and SMILE missions.We developed a userfriendly model of magnetosheath that parameterizes number density,velocity,temperature,and magnetic field by utilizing the global Magnetohydrodynamics(MHD)model as well as the pre-existing gas-dynamic and analytic models.Using this parameterized magnetosheath model,scientists can easily reconstruct expected soft X-ray images and utilize them for analysis of observed images of LEXI and SMILE without simulating the complicated global magnetosphere models.First,we created an MHD-based magnetosheath model by running a total of 14 OpenGGCM global MHD simulations under 7 solar wind densities(1,5,10,15,20,25,and 30 cm)and 2 interplanetary magnetic field Bz components(±4 nT),and then parameterizing the results in new magnetosheath conditions.We compared the magnetosheath model result with THEMIS statistical data and it showed good agreement with a weighted Pearson correlation coefficient greater than 0.77,especially for plasma density and plasma velocity.Second,we compiled a suite of magnetosheath models incorporating previous magnetosheath models(gas-dynamic,analytic),and did two case studies to test the performance.The MHD-based model was comparable to or better than the previous models while providing self-consistency among the magnetosheath parameters.Third,we constructed a tool to calculate a soft X-ray image from any given vantage point,which can support the planning and data analysis of the aforementioned LEXI and SMILE missions.A release of the code has been uploaded to a Github repository.展开更多
Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the curr...Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.展开更多
To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based o...To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed.Particle Swarm Optimization and BP neural network are used to establish the forecasting model,the Markov chain model is used to correct the forecasting error of the model,and the weighted fitting method is used to forecast the annual load curve,to complete the optimal allocation of complementary generating capacity of photovoltaic power stations.The experimental results show that thismethod reduces the average loss of photovoltaic output prediction,improves the prediction accuracy and recall rate of photovoltaic output prediction,and ensures the effective operation of the power system.展开更多
In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was ...In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design.展开更多
Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.Ho...Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the“mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.展开更多
Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is presen...Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is present.In order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional concrete.Since concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched properties.As a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes challenging.Meanwhile,the effort required for laboratory trial batches to determine the TSC is reduced.To achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(MLR),and M5P-tree model(M5P),are investigated and employed to predict the TSCof ECCmixtures containing fly ash.Data from115 mixtures are gathered and analyzed to develop a new model.The input variables include mixture proportions,fiber length and diameter,and the time required for curing the various mixtures.The model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(MAE),scatter index(SI),root mean squared error(RMSE),and objective function(OBJ)value.Consequently,the ANN model outperforms the others in predicting the TSC of the ECC,with RMSE,MAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.展开更多
Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but...Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by sunlight.Nightglow emissions and scattered sunlight can contribute to the background signal.To fully utilize such images in space science,background contamination must be removed to isolate the auroral signal.Here we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical harmonics.The approach is robust,flexible,and iteratively deselects outliers,such as auroral emissions.The final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the dayglow.We demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)mission.The method can be applied to historical missions and is relevant for upcoming missions,such as the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.展开更多
Only simplified two-dimensional model and a single failure mode are adopted to calculate the ultimate pullout capacity(UPC)of anchor cables in most previous research.This study focuses on a more comprehensive combinat...Only simplified two-dimensional model and a single failure mode are adopted to calculate the ultimate pullout capacity(UPC)of anchor cables in most previous research.This study focuses on a more comprehensive combination failure mode that consists of bond failure of an anchorage body and failure of an anchored rock mass.The three-dimensional ultimate pullout capacity of the anchor cables is calculated based on the Hoek-Brown failure criterion and variation analysis method.The numerical solution for the curvilinear function in fracture plane is obtained based on the finite difference theory,which more accurately reflects the failure state of the anchor cable,as opposed to that being assumed in advance.The results reveal that relying solely on a single failure mode for UPC calculations has limitations,as changes in parameter values not only directly impact the UPC value but also can alter the failure model and thus the calculation method.展开更多
BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are p...BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.展开更多
文摘The NHS is right now confronting huge pressures relating to demand and capacity in radiology. The purpose of this research has been to provide information about MRI usage, details of operational aspects of MRI services, and to ascertain the planning intentions of NHS radiology services to keep up and create MRI capacity. The report expands on using Discrete Event Simulation (DES) to inspect and plan the utilisation of NHS hospital resources for the radiology department to help a 24 hr service that is available to outpatients which will help with diminishing patient waiting time, better resource usage, understanding the capacity and demand. Consequently, this research examines to adjust staff and resources with the demand of the MRI. The research was investigated using DES in various scenarios to find which resources are inactive;patients are treated slowly. DES helped in discovering resource utilisation and outpatient throughout the system. It additionally helped in distinguishing the bottlenecks in patient flow. The DES simulation results demonstrated that time for the outpatient in the system is less and more outpatients have been treated too. There is a higher level of outpatient patients leaving the system under 120 minutes. The report uncovered an MRI report interpretation time. Reception room time and MRI waiting room time are decreased significantly. It additionally exhibited with an expanded outflow of outpatients, resources, for example, MRI capacity and radiographer utilisation expanded.
基金Project(2012CB723303)supported by National Basic Research Program of China
文摘To determinate the expressway capacity near a bus bay stop with an access, capacity models on the expressway near a bus stop with an access were developed on the basis of gap acceptance theory and queuing theory. Depending on a bus stop position to an entrance or an exit ramp, the capacity models were developed for four cases. Bus bay stops with overflow and bus bay stops without overflow were considered. A comparison of simulation experiment and model calculation was carried out. Results show that the suggested models have high accuracy and reliability, at bus arrival rate below 60 vehicles per hour(veh/h) or vehicle volumes at the entrance and the exit below 200 passenger cars units per hour(pcu/h), and there are no significant difference in the capacities for four cases. When bus arrival rate is above 240 veh/h, the capacities of all four cases will decline rapidly. With berth number increasing, the increasing of the capacities is no obvious for four cases. As the bus arrival rate and vehicle volumes at the entrance and the exit increase, bus stops located downstream of an entrance and upstream of an exit have a remarkably effect on the capacities. The latter case is much heavier than the former. Those results can be used to traffic design and optimization on urban expressway near a bus stop with an access.
基金supported by the National Key Basic Research Program of China (Grant No. 2006CB400502)the Special Basic Research Fund for Methodology in Hydrology (Grant No. 2007FY140900)the 111 Project (Grant No. B08048)
文摘This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process simulation in semi-arid regions, a spatially varying storage capacity (VSC) model was developed based on the spatial distribution of water storage capacity and the vertical hybrid runoff mechanism. To verify the applicability of the VSC model, both the VSC model and a hybrid runoff model were used to simulate daily runoff processes in the catchment upstream of the Dianzi hydrological station from 1973 to 1979. The results showed that the annual average Nash-Sutcliffe coefficient was 0.80 for the VSC model, and only 0.67 for the hybrid runoff model. The higher annual average Nash-Sutcliffe coefficient of the VSC model means that this hydrological model can better simulate daily runoff processes in semi-arid regions. Furthermore, as a distributed hydrological model, the VSC model can be applied in regional water resource management.
基金supported by the Jilin Province Higher Education TeachingReform Research Project Funding(Contract No.2020285O73B005E).
文摘In the existing power system with a large-scale hydrogen storage system,there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage system.In order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation,and speed up the process of electric-hydrogen-electricity conversion.This article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit,and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen storage unit.These models are of great significance for studying and optimizing gas storage technology.Through these models,the performance of gas storage units can be better understood and improved.These studies are very helpful for improving energy storage efficiency and sustainable development.The factors affecting the charge-discharge efficiency of hydrogen storage units are analyzed.By integrating the models of each unit and considering the capacity degradation of the hydrogen storage system,we can construct an efficiency model for a large hydrogen storage system and power conversion system.In addition,the simulation models of the hydrogen production system and hydrogen consumption system were established in MATLAB/Simulink.The accuracy and effectiveness of the simulation model were proved by comparing the output voltage variation curve of the simulation with the polarization curve of the typical hydrogen production system and hydrogen consumption system.The results show that the charge-discharge efficiency of the hydrogen storage unit increases with the increase of operating temperature,and H2 and O2 partial voltage have little influence on the charge-discharge efficiency.In the process of power conversion system converter rectification operation,its efficiency decreases with the increase of temperature,while in the process of inverter operation,power conversion system efficiency increases with the increase of temperature.Combined with the efficiency of each hydrogen storage unit and power conversion system converter,the upper limit of the capacity loss of different hydrogen storage units was set.The optimal charge-discharge efficiency of the hydrogen storage system was obtained by using the Cplex solver at 36.46%and 66.34%.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.12104372,12047511,and 12247103)the Youth Innovation Team of Shaanxi Universities。
文摘Tan's contact C is an important quantity measuring the two-body correlations at short distances in a dilute system.Here we make use of the technique of exactly solved models to study the thermal-contact capacity K_(T),i.e.,the derivative of C with respect to temperature in the attractive Gaudin-Yang model.It is found that K_(T) is useful in identifying the low temperature phase diagram,and using the obtained analytical expression of K_(T),we study its critical behavior and the scaling law.Especially,we show K_(T) versus temperature and thus the non-monotonic tendency of C in a tiny interval,for both spin-balanced and imbalanced phases.Such a phenomenon is merely observed in multi-component systems such as SU(2)Fermi gases and spinor bosons,indicating the crossover from the Tomonaga-Luttinger liquid to the spin-coherent liquid.
基金the financial support from the National Natural Science Foundation of China(No.52074217)the Natural Science Basic Research Program of Shaanxi Province(No.2021JLM-26).
文摘The concept of the carbon cycle in the old goaf of a coal mine based on CO_(2)utilization and storage was put forward adhering to the principle of low-carbon development,utilization of space resources in old goafs,and associated gas resources development.Firstly,the evolution characteristics of overburden fissures in the goaf of the case was studied using a two-dimensional physical similarity simulation test,the sealing performance of the caprocks after stabilization was analyzed,and the fissures were counted and classi-fied.Then,the process of gaseous CO_(2)injection in the connected fissure was simulated by Ansys Fluent software,and the migration law and distribution characteristics of CO_(2)under the condition of gaseous CO_(2)injection were analyzed.Finally,the estimation models of free CO_(2)storage capacity in the old goaf were constructed considering the proportion of connected fissure and the effectiveness of CO_(2)injection.The CO_(2)storage capacity in the old goaf of the case coal mine was estimated.The results showed that a caprock group of“hard-thickness low-permeability hard-thickness”was formed after the caprock-fissures system in the goaf of the case tended to be stable vertically.The connected fissure,occlude cracks,and micro-fractures in the goaf accounted for 85.5%,8.5%,and 6%of the total fissures,respectively.Gaseous CO_(2)first migrated to the bottom of the connected fissure after CO_(2)was injected into the goaf,then spread horizontally along the bottom of the connected fissure after reaching the bottom,and finally spread longitudinally after filling the bottom of the entire connected fissure.The theoretical and effective storage capacities of free CO_(2)at normal temperature and pressure in the old goaf of the case were 9757 and 7477 t,respectively.The effective storage capacity of free CO_(2)at normal temperature and pressure in the old goaf after all minefield mined was 193404 t.The research can provide some reference for the coal mining industry to help the goal of“carbon peaking and carbon neutrality”.
文摘The transmission capacity of gas pipeline networks should be calculated and allocated to deal with the capacity booking with shippers. Technical capacities, which depend on the gas flow distribution at routes or interchange points, are calculated with a multiobjective optimization model and form a Pareto solution set in the entry/exit or point-to-point regime. Then, the commercial capacities, which can be directly applied in capacity booking, are calculated with single-objective optimization models that are transformed from the above multiobjective model based on three allocation rules and the demand of shippers.Next, peak-shaving capacities, which are daily oversupply or overdelivery amounts at inlets or deliveries,are calculated with two-stage transient optimization models. Considering the hydraulic process of a pipeline network and operating schemes of compressor stations, all the above models are mixed-integer nonlinear programming problems. Finally, a case study is made to demonstrate the ability of the models.
基金Supported by Gansu Province 2023 Education Science and Technology Innovation Project(2023B-431).
文摘As a basic natural resource and strategic economic resource,the development and utilization of water resources is an important issue related to the national economy and people's livelihood.How to scientifically evaluate the water resources carrying capacity is the premise to improve the regional water resources carrying capacity and ensure the regional water security.The Gansu section of the Yellow River basin is an important water conservation and recharge area.Whether the water resources in this area can ensure the normal operation of the ecosystem and whether it can carry the sustainable development of social economy is the key to realize the high-quality development of the Yellow River basin.In this study,from the three dimensions of water consumption per capita,water consumption of 10000 yuan GDP and ecological water use rate,by constructing the evaluation index system and index grading standard of water resources carrying capacity,the fuzzy comprehensive evaluation model was used to evaluate the water resources carrying capacity of Gansu section of the Yellow River Basin,in order to provide theoretical decision-making basis for the comprehensive development,utilization and planning management of water resources in Gansu section of the Yellow River basin and even the whole basin,and help the high-quality development of the Yellow River basin.
基金supported by the NSF grant AGS-1928883the NASA grants,80NSSC20K1670 and 80MSFC20C0019+2 种基金support from NASA GSFC IRADHIFISFM funds。
文摘Lunar Environment heliospheric X-ray Imager(LEXI)and Solar wind−Magnetosphere−Ionosphere Link Explorer(SMILE)will observe magnetosheath and its boundary motion in soft X-rays for understanding magnetopause reconnection modes under various solar wind conditions after their respective launches in 2024 and 2025.Magnetosheath conditions,namely,plasma density,velocity,and temperature,are key parameters for predicting and analyzing soft X-ray images from the LEXI and SMILE missions.We developed a userfriendly model of magnetosheath that parameterizes number density,velocity,temperature,and magnetic field by utilizing the global Magnetohydrodynamics(MHD)model as well as the pre-existing gas-dynamic and analytic models.Using this parameterized magnetosheath model,scientists can easily reconstruct expected soft X-ray images and utilize them for analysis of observed images of LEXI and SMILE without simulating the complicated global magnetosphere models.First,we created an MHD-based magnetosheath model by running a total of 14 OpenGGCM global MHD simulations under 7 solar wind densities(1,5,10,15,20,25,and 30 cm)and 2 interplanetary magnetic field Bz components(±4 nT),and then parameterizing the results in new magnetosheath conditions.We compared the magnetosheath model result with THEMIS statistical data and it showed good agreement with a weighted Pearson correlation coefficient greater than 0.77,especially for plasma density and plasma velocity.Second,we compiled a suite of magnetosheath models incorporating previous magnetosheath models(gas-dynamic,analytic),and did two case studies to test the performance.The MHD-based model was comparable to or better than the previous models while providing self-consistency among the magnetosheath parameters.Third,we constructed a tool to calculate a soft X-ray image from any given vantage point,which can support the planning and data analysis of the aforementioned LEXI and SMILE missions.A release of the code has been uploaded to a Github repository.
基金supported by Ministry of Science and Technology of China (Grant No. 2018YFA0606501)National Natural Science Foundation of China (Grant No. 42075037)+1 种基金Key Laboratory Open Research Program of Xinjiang Science and Technology Department (Grant No. 2022D04009)the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility” (EarthLab)。
文摘Both the attribution of historical change and future projections of droughts rely heavily on climate modeling. However,reasonable drought simulations have remained a challenge, and the related performances of the current state-of-the-art Coupled Model Intercomparison Project phase 6(CMIP6) models remain unknown. Here, both the strengths and weaknesses of CMIP6 models in simulating droughts and corresponding hydrothermal conditions in drylands are assessed.While the general patterns of simulated meteorological elements in drylands resemble the observations, the annual precipitation is overestimated by ~33%(with a model spread of 2.3%–77.2%), along with an underestimation of potential evapotranspiration(PET) by ~32%(17.5%–47.2%). The water deficit condition, measured by the difference between precipitation and PET, is 50%(29.1%–71.7%) weaker than observations. The CMIP6 models show weaknesses in capturing the climate mean drought characteristics in drylands, particularly with the occurrence and duration largely underestimated in the hyperarid Afro-Asian areas. Nonetheless, the drought-associated meteorological anomalies, including reduced precipitation, warmer temperatures, higher evaporative demand, and increased water deficit conditions, are reasonably reproduced. The simulated magnitude of precipitation(water deficit) associated with dryland droughts is overestimated by 28%(24%) compared to observations. The observed increasing trends in drought fractional area,occurrence, and corresponding meteorological anomalies during 1980–2014 are reasonably reproduced. Still, the increase in drought characteristics, associated precipitation and water deficit are obviously underestimated after the late 1990s,especially for mild and moderate droughts, indicative of a weaker response of dryland drought changes to global warming in CMIP6 models. Our results suggest that it is imperative to employ bias correction approaches in drought-related studies over drylands by using CMIP6 outputs.
文摘To improve the operation efficiency of the photovoltaic power station complementary power generation system,an optimal allocation model of the photovoltaic power station complementary power generation capacity based on PSO-BP is proposed.Particle Swarm Optimization and BP neural network are used to establish the forecasting model,the Markov chain model is used to correct the forecasting error of the model,and the weighted fitting method is used to forecast the annual load curve,to complete the optimal allocation of complementary generating capacity of photovoltaic power stations.The experimental results show that thismethod reduces the average loss of photovoltaic output prediction,improves the prediction accuracy and recall rate of photovoltaic output prediction,and ensures the effective operation of the power system.
基金supported by the Key R&D Project of Jiangsu Province(Modern Agriculture)under Grant BE2022322 the"Pilot Plan"Internet of Things special project(China Institute of Io T(wuxi)and Wuxi Internet of Things Innovation Promotion Center)under Grant 2022SP-T16-Bin part by the 111 Project under Grant B12018+2 种基金in part by the Six talent peaks project in Jiangsu Provincein part by the open foundation of Key Laboratory of Wireless Sensor Network and Communication,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences under Grant 20190917in part by the open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications,Ministry of Education)。
文摘In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design.
基金supported by the National Outstanding Youth Science Fund Project of National Natural Science Foundation of China[Grant No.52222708]the Natural Science Foundation of Beijing Municipality[Grant No.3212033]。
文摘Battery pack capacity estimation under real-world operating conditions is important for battery performance optimization and health management,contributing to the reliability and longevity of batterypowered systems.However,complex operating conditions,coupling cell-to-cell inconsistency,and limited labeled data pose great challenges to accurate and robust battery pack capacity estimation.To address these issues,this paper proposes a hierarchical data-driven framework aimed at enhancing the training of machine learning models with fewer labeled data.Unlike traditional data-driven methods that lack interpretability,the hierarchical data-driven framework unveils the“mechanism”of the black box inside the data-driven framework by splitting the final estimation target into cell-level and pack-level intermediate targets.A generalized feature matrix is devised without requiring all cell voltages,significantly reducing the computational cost and memory resources.The generated intermediate target labels and the corresponding features are hierarchically employed to enhance the training of two machine learning models,effectively alleviating the difficulty of learning the relationship from all features due to fewer labeled data and addressing the dilemma of requiring extensive labeled data for accurate estimation.Using only 10%of degradation data,the proposed framework outperforms the state-of-the-art battery pack capacity estimation methods,achieving mean absolute percentage errors of 0.608%,0.601%,and 1.128%for three battery packs whose degradation load profiles represent real-world operating conditions.Its high accuracy,adaptability,and robustness indicate the potential in different application scenarios,which is promising for reducing laborious and expensive aging experiments at the pack level and facilitating the development of battery technology.
文摘Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is present.In order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional concrete.Since concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched properties.As a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes challenging.Meanwhile,the effort required for laboratory trial batches to determine the TSC is reduced.To achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(MLR),and M5P-tree model(M5P),are investigated and employed to predict the TSCof ECCmixtures containing fly ash.Data from115 mixtures are gathered and analyzed to develop a new model.The input variables include mixture proportions,fiber length and diameter,and the time required for curing the various mixtures.The model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(MAE),scatter index(SI),root mean squared error(RMSE),and objective function(OBJ)value.Consequently,the ANN model outperforms the others in predicting the TSC of the ECC,with RMSE,MAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.
基金supported by the Research Council of Norway under contracts 223252/F50 and 300844/F50the Trond Mohn Foundation。
文摘Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by sunlight.Nightglow emissions and scattered sunlight can contribute to the background signal.To fully utilize such images in space science,background contamination must be removed to isolate the auroral signal.Here we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical harmonics.The approach is robust,flexible,and iteratively deselects outliers,such as auroral emissions.The final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the dayglow.We demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)mission.The method can be applied to historical missions and is relevant for upcoming missions,such as the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.
基金supported by the Natural Science Foundation of Hunan Province(2023JJ40078)the Scientific Research Project of Hunan Provincial Education Department(No.22C0573)+2 种基金the National Natural Science Foundation of China(51478477,51878668)Guizhou Provincial Department of Transportation Foundation(2017-122058)Foundation of Guizhou Provincial Science and Technology Department([2018]2815).
文摘Only simplified two-dimensional model and a single failure mode are adopted to calculate the ultimate pullout capacity(UPC)of anchor cables in most previous research.This study focuses on a more comprehensive combination failure mode that consists of bond failure of an anchorage body and failure of an anchored rock mass.The three-dimensional ultimate pullout capacity of the anchor cables is calculated based on the Hoek-Brown failure criterion and variation analysis method.The numerical solution for the curvilinear function in fracture plane is obtained based on the finite difference theory,which more accurately reflects the failure state of the anchor cable,as opposed to that being assumed in advance.The results reveal that relying solely on a single failure mode for UPC calculations has limitations,as changes in parameter values not only directly impact the UPC value but also can alter the failure model and thus the calculation method.
文摘BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.
