This article proposes an optimization control model of the systemic condition of satellite prototype based on the hybrid system. A dynamic programming algorithm is also proposed because the problem is NPhard. An empir...This article proposes an optimization control model of the systemic condition of satellite prototype based on the hybrid system. A dynamic programming algorithm is also proposed because the problem is NPhard. An empirical study validates the model and the algorithm,and proves that the pointed important management resources can be recognized and allocated optimally and correctly.展开更多
The objective of this investigation is to examine the correctness and efficiency of the choice of boundary conditions when using assumed mode approach to simulate flexible multi-body systems. The displacement field du...The objective of this investigation is to examine the correctness and efficiency of the choice of boundary conditions when using assumed mode approach to simulate flexible multi-body systems. The displacement field due to deformation is approximated by the Rayleigh-Ritz assumed modes in floating frame of reference （FFR） formulation. The deformations obtained by the absolute nodal coordinate （ANC） formulation which are transformed by two sets of reference coordinates are introduced as a criterion to verify the accuracy of the simulation results by using the FFR formulation. The relationship between the deformations obtained from different boundary conditions is revealed. Nu- merical simulation examples demonstrate that the assumed modes with cantilevered-free, simply-supported and free- free boundary conditions without inclusion of rigid body modes are suitable for simulation of flexible multi-body system with large over all motion, and the same physical deformation can be obtained using those mode functions, differ only by a coordinate transformation. It is also shown that when using mode shapes with statically indeterminate boundary conditions, significant error may occur. Furthermore, the slider crank mechanism with rigid crank is accurate enough for investigating boundary condition problem of flexible multi-body system, which cost significant less simulating time.展开更多
Let Ω be a bounded domain with smooth boundary Ω in R~n. We consider the following eigenvalue problem for systems of elliptic equations under the natural growth conditions
In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges whe...In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges when datasets lack the comprehensive information necessary for addressing complex scenarios,which hampers adaptability.Thus,enhancing data completeness is essential.Knowledge-guided virtual sample generation transforms domain knowledge into extensive virtual datasets,thereby reducing dependence on limited real samples and enabling zero-sample fault diagnosis.This study used building air conditioning systems as a case study.We innovatively used the large language model(LLM)to acquire domain knowledge for sample generation,significantly lowering knowledge acquisition costs and establishing a generalized framework for knowledge acquisition in engineering applications.This acquired knowledge guided the design of diffusion boundaries in mega-trend diffusion(MTD),while the Monte Carlo method was used to sample within the diffusion function to create information-rich virtual samples.Additionally,a noise-adding technique was introduced to enhance the information entropy of these samples,thereby improving the robustness of neural networks trained with them.Experimental results showed that training the diagnostic model exclusively with virtual samples achieved an accuracy of 72.80%,significantly surpassing traditional small-sample supervised learning in terms of generalization.This underscores the quality and completeness of the generated virtual samples.展开更多
Debris flow susceptibility mapping(DFSM)has been reported in many studies,however,the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved.In this paper,a r...Debris flow susceptibility mapping(DFSM)has been reported in many studies,however,the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved.In this paper,a region-partitioning method that is based on the topographic characteristics of watershed units was developed with the objective of establishing multiple conditioning factor systems for regional-scale DFSM.First,watershed units were selected as the mapping units and created throughout the entire research area.Four topographical factors,namely,elevation,slope,aspect and relative height difference,were selected as the basis for clustering watershed units.The k-means clustering analysis was used to cluster the watershed units according to their topographic characteristics to partition the study area into several parts.Then,the information gain ratio method was used to filter out superfluous factors to establish conditioning factor systems in each region for the subsequent debris flow susceptibility modeling.Last,a debris flow susceptibility map of the whole study area was acquired by merging the maps from all parts.DFSM of Yongji County in Jilin Province,China was selected as a case study,and the analytical hierarchy process method was used to conduct a comparative analysis to evaluate the performance of the region-partitioning method.The area under curve(AUC)values showed that the partitioning of the study area into two parts improved the prediction rate from 0.812 to 0.916.The results demonstrate that the region-partitioning method on the basis of topographic characteristics of watershed units can realize more reasonable regional-scale DFSM.Hence,the developed region-partitioning method can be used as a guide for regional-scale DFSM to mitigate the imminent debris flow risk.展开更多
Currently,there are two types of defect detection systems used to monitor the health of freight railcar bearings in service:wayside hot-box detection systems and trackside acoustic detection systems.These systems have...Currently,there are two types of defect detection systems used to monitor the health of freight railcar bearings in service:wayside hot-box detection systems and trackside acoustic detection systems.These systems have proven to be inefficient in accurately determining bearing health,especially in the early stages of defect development.To that end,a prototype onboard bearing condition monitoring system has been developed and validated through extensive laboratory testing and a designated field test in 2015 at the Transportation Technology Center,Inc.in Pueblo,CO.The devised system can accurately and reliably characterize the health of bearings based on developed vibration thresholds and can identify defective taperedroller bearing components with defect areas smaller than 12.9 cm2 while in service.展开更多
The importance and necessity of energy saving in the world have been discussed for many years,but achieving a logical and transparent solution is still one of the main challenges and problems of the world’s eco...The importance and necessity of energy saving in the world have been discussed for many years,but achieving a logical and transparent solution is still one of the main challenges and problems of the world’s economy.The rapid growth of energy consumption in the last two decades has caused the security of the domestic energy supply of buildings to face serious problems.In this research,first by entering parameters such as the type of materials,doors and windows,and the type of soil on the floor connected to the ground,etc.in the heat and cold load calculation software(HAP Carrier)as the design calculations and then in the second step entering the specifications inferred from the Iran’s national building code as a reference for energy saving calculations,calculations are performed and compared as the first criterion,and finally these two outputs are compared.The actual energy consumption and determination of the building energy consumption index are determined as another criterion,as well as the degree of deviation from the actual consumption.The results showed that the theoretical method and the thermal and refrigeration load calculations of the Zanjan Gas Company building have 6%difference in cooling load but the heating load is about 34%different,which means for cooling loads,the theoretical model can be used with high accuracy but for heating loads,the national building code needs fundamental changes.展开更多
Unbalanced operating condition in a power system can cause partial overloading of the generators in the network,a condition where one or two of the three phases of the generator become overloaded even if the total 3-p...Unbalanced operating condition in a power system can cause partial overloading of the generators in the network,a condition where one or two of the three phases of the generator become overloaded even if the total 3-phase power output of the generator is within its specified limit.Partial overloading of generators beyond certain limits is undesirable and must be avoided.Distribution systems are often subjected to highly unbalanced operating conditions.Introduction of distributed generations(DGs),therefore,has rendered today’s distribution systems quite susceptible to this problem.Mitigation of this problem requires the issue to be addressed properly during analysis,operation and planning of such systems.Analysis,operation and planning of power networks under unbalanced operating condition require 3-phase load flow study.The existing methods of 3-phase load flow are not equipped to take into account any limit on the loadings of the individual phases of the generators.In the present work,a methodology based on NewtonRaphson(N-R)3-phase load flow with necessary modifications is proposed.The proposed methodology is able to determine the safe loading limits of the generators,and,can be adopted for operation and planning of power networks under unbalanced operating conditions to overcome the above difficulties.Test results on IEEE-37 bus feeder network are presented to demonstrate the effectiveness of the proposed method.展开更多
Periodontal diseases are prevalent among the general population and are associated with several systemic conditions,such as chronic kidney disease and type 2 diabetes mellitus.Chronic liver disease and cirrhosis have ...Periodontal diseases are prevalent among the general population and are associated with several systemic conditions,such as chronic kidney disease and type 2 diabetes mellitus.Chronic liver disease and cirrhosis have also been linked with periodontal disease,an association with complex underlying mechanisms,and with potential prognostic implications.Multiple factors can explain this relevant association,including nutritional factors,alcohol consumption,disruption of the oral-gut-liver axis and associated dysbiosis.Additionally,patients with liver disease have been observed to exhibit poorer oral hygiene practices compared with the general population,potentially predisposing them to the development of periodontal disease.Therefore,it is recommended that all patients with liver disease undergo screening and subsequent treatment for periodontal disease.Treatment of periodontal disease in patients with cirrhosis may help reduce liver-derived inflammatory damage,with recent research indicating a potential benefit in terms of reduced mortality.However,further studies on periodontal disease treatment in patients with liver disease are still warranted to determine optimal management strategies.This narrative review describes current concepts on the association between periodontal disease and chronic liver disease.展开更多
Digital twin is regarded as the next-generation technology for the effective operation of heating,ventilation and air conditioning(HVAC)systems.It is essential to calibrate the digital twin models to match them closel...Digital twin is regarded as the next-generation technology for the effective operation of heating,ventilation and air conditioning(HVAC)systems.It is essential to calibrate the digital twin models to match them closely with real physical systems.Conventional real-time calibration methods cannot satisfy such requirements since the computation loads are beyond acceptable tolerances.To address this challenge,this study proposes a clustering compression-based method to enhance the computation efficiency of digital twin model calibration for HVAC systems.This method utilizes clustering algorithms to remove redundant data for achieving data compression.Moreover,a hierarchical multi-stage heuristic model calibration strategy is developed to accelerate the calibration of similar component models.Its basic idea is that once a component model is calibrated by heuristic methods,its optimal solution is utilized to narrow the ranges of parameter probability distributions of similar components.By doing so,the calibration process can be guided,so that fewer iterations would be used.The performance of the proposed method is evaluated using the operational data from an HVAC system in an industrial building.Results show that the proposed clustering compression-based method can reduce computation loads by 97%,compared to the conventional calibration method.And the proposed hierarchical heuristic model calibration strategy is capable of accelerating the calibration process after clustering and saves 14.6%of the time costs.展开更多
文摘This article proposes an optimization control model of the systemic condition of satellite prototype based on the hybrid system. A dynamic programming algorithm is also proposed because the problem is NPhard. An empirical study validates the model and the algorithm,and proves that the pointed important management resources can be recognized and allocated optimally and correctly.
基金supported by the National Natural Science Foundation of China (10872126)the Research Fund of the Doctoral Program of Higher Education of China (20100073110007)
文摘The objective of this investigation is to examine the correctness and efficiency of the choice of boundary conditions when using assumed mode approach to simulate flexible multi-body systems. The displacement field due to deformation is approximated by the Rayleigh-Ritz assumed modes in floating frame of reference （FFR） formulation. The deformations obtained by the absolute nodal coordinate （ANC） formulation which are transformed by two sets of reference coordinates are introduced as a criterion to verify the accuracy of the simulation results by using the FFR formulation. The relationship between the deformations obtained from different boundary conditions is revealed. Nu- merical simulation examples demonstrate that the assumed modes with cantilevered-free, simply-supported and free- free boundary conditions without inclusion of rigid body modes are suitable for simulation of flexible multi-body system with large over all motion, and the same physical deformation can be obtained using those mode functions, differ only by a coordinate transformation. It is also shown that when using mode shapes with statically indeterminate boundary conditions, significant error may occur. Furthermore, the slider crank mechanism with rigid crank is accurate enough for investigating boundary condition problem of flexible multi-body system, which cost significant less simulating time.
文摘Let Ω be a bounded domain with smooth boundary Ω in R~n. We consider the following eigenvalue problem for systems of elliptic equations under the natural growth conditions
基金supported by the National Natural Science Foundation of China(No.62306281)the Natural Science Foundation of Zhejiang Province(Nos.LQ23E060006 and LTGG24E050005)the Key Research Plan of Jiaxing City(No.2024BZ20016).
文摘In the era of big data,data-driven technologies are increasingly leveraged by industry to facilitate autonomous learning and intelligent decision-making.However,the challenge of“small samples in big data”emerges when datasets lack the comprehensive information necessary for addressing complex scenarios,which hampers adaptability.Thus,enhancing data completeness is essential.Knowledge-guided virtual sample generation transforms domain knowledge into extensive virtual datasets,thereby reducing dependence on limited real samples and enabling zero-sample fault diagnosis.This study used building air conditioning systems as a case study.We innovatively used the large language model(LLM)to acquire domain knowledge for sample generation,significantly lowering knowledge acquisition costs and establishing a generalized framework for knowledge acquisition in engineering applications.This acquired knowledge guided the design of diffusion boundaries in mega-trend diffusion(MTD),while the Monte Carlo method was used to sample within the diffusion function to create information-rich virtual samples.Additionally,a noise-adding technique was introduced to enhance the information entropy of these samples,thereby improving the robustness of neural networks trained with them.Experimental results showed that training the diagnostic model exclusively with virtual samples achieved an accuracy of 72.80%,significantly surpassing traditional small-sample supervised learning in terms of generalization.This underscores the quality and completeness of the generated virtual samples.
基金funded by the National Natural Science Foundation of China(Grant Nos.41977221 and 41202197)Jilin Provincial Science and Technology Department(No.20190303103SF,No.20170101001JC)。
文摘Debris flow susceptibility mapping(DFSM)has been reported in many studies,however,the irrational use of the same conditioning factor system for DFSM in regional-scale has not been thoroughly resolved.In this paper,a region-partitioning method that is based on the topographic characteristics of watershed units was developed with the objective of establishing multiple conditioning factor systems for regional-scale DFSM.First,watershed units were selected as the mapping units and created throughout the entire research area.Four topographical factors,namely,elevation,slope,aspect and relative height difference,were selected as the basis for clustering watershed units.The k-means clustering analysis was used to cluster the watershed units according to their topographic characteristics to partition the study area into several parts.Then,the information gain ratio method was used to filter out superfluous factors to establish conditioning factor systems in each region for the subsequent debris flow susceptibility modeling.Last,a debris flow susceptibility map of the whole study area was acquired by merging the maps from all parts.DFSM of Yongji County in Jilin Province,China was selected as a case study,and the analytical hierarchy process method was used to conduct a comparative analysis to evaluate the performance of the region-partitioning method.The area under curve(AUC)values showed that the partitioning of the study area into two parts improved the prediction rate from 0.812 to 0.916.The results demonstrate that the region-partitioning method on the basis of topographic characteristics of watershed units can realize more reasonable regional-scale DFSM.Hence,the developed region-partitioning method can be used as a guide for regional-scale DFSM to mitigate the imminent debris flow risk.
基金This study was made possible by funding provided by The University Transportation Center for Railway Safety(UTCRS),through a USDOT Grant No.DTRT 13-G-UTC59.
文摘Currently,there are two types of defect detection systems used to monitor the health of freight railcar bearings in service:wayside hot-box detection systems and trackside acoustic detection systems.These systems have proven to be inefficient in accurately determining bearing health,especially in the early stages of defect development.To that end,a prototype onboard bearing condition monitoring system has been developed and validated through extensive laboratory testing and a designated field test in 2015 at the Transportation Technology Center,Inc.in Pueblo,CO.The devised system can accurately and reliably characterize the health of bearings based on developed vibration thresholds and can identify defective taperedroller bearing components with defect areas smaller than 12.9 cm2 while in service.
文摘The importance and necessity of energy saving in the world have been discussed for many years,but achieving a logical and transparent solution is still one of the main challenges and problems of the world’s economy.The rapid growth of energy consumption in the last two decades has caused the security of the domestic energy supply of buildings to face serious problems.In this research,first by entering parameters such as the type of materials,doors and windows,and the type of soil on the floor connected to the ground,etc.in the heat and cold load calculation software(HAP Carrier)as the design calculations and then in the second step entering the specifications inferred from the Iran’s national building code as a reference for energy saving calculations,calculations are performed and compared as the first criterion,and finally these two outputs are compared.The actual energy consumption and determination of the building energy consumption index are determined as another criterion,as well as the degree of deviation from the actual consumption.The results showed that the theoretical method and the thermal and refrigeration load calculations of the Zanjan Gas Company building have 6%difference in cooling load but the heating load is about 34%different,which means for cooling loads,the theoretical model can be used with high accuracy but for heating loads,the national building code needs fundamental changes.
文摘Unbalanced operating condition in a power system can cause partial overloading of the generators in the network,a condition where one or two of the three phases of the generator become overloaded even if the total 3-phase power output of the generator is within its specified limit.Partial overloading of generators beyond certain limits is undesirable and must be avoided.Distribution systems are often subjected to highly unbalanced operating conditions.Introduction of distributed generations(DGs),therefore,has rendered today’s distribution systems quite susceptible to this problem.Mitigation of this problem requires the issue to be addressed properly during analysis,operation and planning of such systems.Analysis,operation and planning of power networks under unbalanced operating condition require 3-phase load flow study.The existing methods of 3-phase load flow are not equipped to take into account any limit on the loadings of the individual phases of the generators.In the present work,a methodology based on NewtonRaphson(N-R)3-phase load flow with necessary modifications is proposed.The proposed methodology is able to determine the safe loading limits of the generators,and,can be adopted for operation and planning of power networks under unbalanced operating conditions to overcome the above difficulties.Test results on IEEE-37 bus feeder network are presented to demonstrate the effectiveness of the proposed method.
基金support from the Chilean government through the Fondo Nacional de Desarrollo Científico y Tecnológico(FONDECYT 1241450).
文摘Periodontal diseases are prevalent among the general population and are associated with several systemic conditions,such as chronic kidney disease and type 2 diabetes mellitus.Chronic liver disease and cirrhosis have also been linked with periodontal disease,an association with complex underlying mechanisms,and with potential prognostic implications.Multiple factors can explain this relevant association,including nutritional factors,alcohol consumption,disruption of the oral-gut-liver axis and associated dysbiosis.Additionally,patients with liver disease have been observed to exhibit poorer oral hygiene practices compared with the general population,potentially predisposing them to the development of periodontal disease.Therefore,it is recommended that all patients with liver disease undergo screening and subsequent treatment for periodontal disease.Treatment of periodontal disease in patients with cirrhosis may help reduce liver-derived inflammatory damage,with recent research indicating a potential benefit in terms of reduced mortality.However,further studies on periodontal disease treatment in patients with liver disease are still warranted to determine optimal management strategies.This narrative review describes current concepts on the association between periodontal disease and chronic liver disease.
基金support of the National Natural Science Foundation of China (No.51978601 and No.52161135202).
文摘Digital twin is regarded as the next-generation technology for the effective operation of heating,ventilation and air conditioning(HVAC)systems.It is essential to calibrate the digital twin models to match them closely with real physical systems.Conventional real-time calibration methods cannot satisfy such requirements since the computation loads are beyond acceptable tolerances.To address this challenge,this study proposes a clustering compression-based method to enhance the computation efficiency of digital twin model calibration for HVAC systems.This method utilizes clustering algorithms to remove redundant data for achieving data compression.Moreover,a hierarchical multi-stage heuristic model calibration strategy is developed to accelerate the calibration of similar component models.Its basic idea is that once a component model is calibrated by heuristic methods,its optimal solution is utilized to narrow the ranges of parameter probability distributions of similar components.By doing so,the calibration process can be guided,so that fewer iterations would be used.The performance of the proposed method is evaluated using the operational data from an HVAC system in an industrial building.Results show that the proposed clustering compression-based method can reduce computation loads by 97%,compared to the conventional calibration method.And the proposed hierarchical heuristic model calibration strategy is capable of accelerating the calibration process after clustering and saves 14.6%of the time costs.
