In this study, a dynamic modeling method for foil-like underwater vehicles is introduced and experimentally verified in different sea tests of the Hadal ARV. The dumping force of a foil-like underwater vehicle is sens...In this study, a dynamic modeling method for foil-like underwater vehicles is introduced and experimentally verified in different sea tests of the Hadal ARV. The dumping force of a foil-like underwater vehicle is sensitive to swing motion. Some foil-like underwater vehicles swing periodically when performing a free-fall dive task in experiments. Models using conventional modeling methods yield solutions with asymptotic stability, which cannot simulate the self-sustained swing motion. By improving the ridge regression optimization algorithm, a grey-box modeling method based on 378 viscous drag coefficients using the Taylor series expansion is proposed in this study. The method is optimized for over-fitting and convergence problems caused by large parameter matrices. Instead of the PMM test data, the unsteady computational fluid dynamics calculation results are used in modeling. The obtained model can better simulate the swing motion of the underwater vehicle. Simulation and experimental results show a good consistency in free-fall tests during sea trials, as well as a prediction of the dive speed in the swing state.展开更多
In order to solve the problem of difficult modeling and identification caused by time-variable parameters,multiple inputs and outputs and unstable open loop,a subsystem model-based close-loop grey-box identification m...In order to solve the problem of difficult modeling and identification caused by time-variable parameters,multiple inputs and outputs and unstable open loop,a subsystem model-based close-loop grey-box identification method was put forward when consider the main coupling effects of hydraulic Stewart platform.Firstly,the whole system is divided into three TITO(Two Input Two Output) subsystems according to the characteristics of the pseudo-mass matrix,hence transfer function matrix model of the subsystem can also be found.Secondly,since the Stewart platform is unstable,the close-loop transfer model of the subsystem is derived under the proportional controllers.The inverse M serial is adopted as the identification signal to get the experimental data.All parameters of the subsystem are determined in close-loop indirect identification by PEM(Prediction Error Method).Finally,a case study validates the correctness and effectiveness of the subsystem model-based close-loop grey-box identification method for hydraulic Stewart platform.展开更多
Soft grippers are favored for handling delicate objects due to their compliance but often have lower load capacities compared to rigid ones.Variable Stiffness Module(VSM)offer a solution,balancing flexibility and load...Soft grippers are favored for handling delicate objects due to their compliance but often have lower load capacities compared to rigid ones.Variable Stiffness Module(VSM)offer a solution,balancing flexibility and load capacity,for which particle jamming is an effective technology for stiffness-tunable robots requiring safe interaction and load capacity.Specific applica-tions,such as rescue scenarios,require quantitative analysis to optimize VSM design parameters,which previous analytical models cannot effectively handle.To address this,a Grey-box model is proposed to analyze the mechanical response of the particle-jamming-based VSM by combining a White-box approach based on the virtual work principle with a Black-box approach that uses a shallow neural network method.The Grey-box model demonstrates a high level of accuracy in predict-ing the VSM force-height mechanical response curves,with errors below 15%in almost 90%of the cases and a maximum error of less than 25%.The model is used to optimize VSM design parameters,particularly those unexplored combinations.Our results from the load capacity and force distribution comparison tests indicate that the VSM,optimized through our methods,quantitatively meets the practical engineering requirements.展开更多
In this paper, the test suite construction for GUI (Graphical User Interface) software may be executed centered on grey-box approach with the prior test design of window access controls for unit testing, including fro...In this paper, the test suite construction for GUI (Graphical User Interface) software may be executed centered on grey-box approach with the prior test design of window access controls for unit testing, including front-end method of white box and follow-up black box method for integration testing. Moreover, two key opinions are proposed for the test suite construction for GUI software, the first one is that the “Triple-step method” should be used for unit testing with the prior disposing of data boundary value testing of input controls, and another one is that the “Grey-box approach” should be applied in integration testing for GUI software with necessary testing preparation in the precondition. At the same time, the testing of baseline version and the incremental testing should be considered for the test case construction to coordinate with the whole evolution of software product today. Additionally, all our opinion and thought are verified and tested with a typical case of GUI software—PQMS (Product Quality Monitoring Software/System), and results indicate that these methods and specific disposing are practical and effective.展开更多
Fuzz testing is crucial for identifying software vulnerabilities,with coverage-guided grey-box fuzzers like AFL and Angora excelling in broad detection.However,as the need for targeted detection grows,directed grey-bo...Fuzz testing is crucial for identifying software vulnerabilities,with coverage-guided grey-box fuzzers like AFL and Angora excelling in broad detection.However,as the need for targeted detection grows,directed grey-box fuzzing(DGF)has become essential,focusing on specific vulnerabilities.The initial seed corpus,which consists of carefully selected input samples that the fuzzer uses as a starting point,is fundamental in determining the paths that the fuzzer explores.A well-designed seed corpus can guide the fuzzer more effectively towards critical areas of the code,improving the efficiency and success of the fuzzing process.Even with its importance,much work concentrates on refining guidance mechanisms while paying less attention to optimizing the initial seed corpus.In this paper,we introduce ISC4DGF,a novel approach to generating optimized initial seed corpus for DGF using large language models(LLMs).By leveraging LLMs’deep understanding of software and refined user inputs,ISC4DGF creates a precise seed corpus that efficiently triggers specific vulnerabilities through a multi-round validation process.Implemented on AFL and tested against state-of-the-art fuzzers such as Titan,BEACON,AFLGo,FairFuzz,and Entropic using the Magma benchmark,ISC4DGF achieves a 25.03x speedup with fewer target reaches.Moreover,ISC4DGF improves target vulnerabilities detection accuracy while narrowing the detection scope and reducing code coverage.展开更多
Commercial buildings,in particular grocery stores(due mainly to their large refrigeration load),provide opportunities for energy cost reductions.Grocery stores could offer substantial load flexibility to the power gri...Commercial buildings,in particular grocery stores(due mainly to their large refrigeration load),provide opportunities for energy cost reductions.Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity.This load flexibility could come from modifying the control of heating,ventilation,and air conditioning(HVAC)systems,refrigeration systems,or both.Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature,estimating load flexibility of refrigeration systems is nascent and has been a challenge,in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases.The existing refrigerated case model within EnergyPlus,a whole building energy simulation program,assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case.In addition,it does not encompass modeling of temperatures of the product inside the refrigerated case.This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential.In this paper,we present a grey-box model for modeling refrigerated cases in grocery stores,which include medium temperature and low temperature.Four cases are modeled;two are low-temperature closed cases and two are medium-temperature cases with one closed and one open.Data from an experimental facility are used to train and test the models.Results demonstrate the efficacy of the grey-box models in predicting the temperatures.This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment(case credits).These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost,develop and test unique algorithms that could affect refrigeration interactions with HVAC,and refine store design for any commercial building with refrigeration.展开更多
Integrated continuous stirred-tank reactors and distillation columns with recycle(CSTR-DC-recycle)are essential components in chemical processes.This paper proposes a method to establish a normal operating zone(NOZ)mo...Integrated continuous stirred-tank reactors and distillation columns with recycle(CSTR-DC-recycle)are essential components in chemical processes.This paper proposes a method to establish a normal operating zone(NOZ)model to represent allowable variations of the CSTR-DC-recycle chemical processes.The NOZ is a geometric space containing all safe operating points of the CSTR-DC-recycle chemical processes,so that it is an effective model for process monitoring.The novelty of the proposed method is to establish the NOZ model based on boundary points.The boundary points make it possible to capture the actual geometric space irrespective of the space shape.In contrast,existing methods represent the NOZ of processes by fixed mathematical models such as ellipsoidal and convex-hull models;they are not suitable for the CSTR-DC-recycle chemical processes whose NOZs cannot be exactly defined by fixed mathematical structures.Simulated case studies based on Aspen Hysys software are given to illustrate the proposed method.展开更多
In this paper, by means of effective testing practices, main strategies of integration testing for GUI software, including differentiating strategy for distinguished system, strategy of personnel organization, increme...In this paper, by means of effective testing practices, main strategies of integration testing for GUI software, including differentiating strategy for distinguished system, strategy of personnel organization, incremental testing strategy based on baseline version, testing strategy of circulating loop through the whole life, and the strategy of test suite construction, were briefly investigated. Moreover, for the code analysis, the FTA (Fault Tree analysis) is proposed to deal with the software change in regression testing. For test suite constructing, the constructing methods for baseline version and the incremental change are deeply discussed, in which main points focus on the testing strategy based on “Sheet/Form”, the “Grey-box approach” for integration testing process, and the application of the improved STD (State Transform Diagram) in state testing. At the same time, the suite construction of integration testing for two types, including small scale program and large scale software, is analyzed and discussed in detail. For testing execution, the specific method based on “Cross-testing” is investigated. Concurrently, by a lot of examples, all results of testing activity indicate that these strategies and methods are useful and fitted to integration testing for GUI software.展开更多
Thermally activated building system(TABS)embeds heat exchanging tubes inside the building structure.The high thermal inertia possesses significant energy flexibility potential but also results in challenges for effect...Thermally activated building system(TABS)embeds heat exchanging tubes inside the building structure.The high thermal inertia possesses significant energy flexibility potential but also results in challenges for effective control,especially for the situations with unmeasurable stochastic thermal disturbances.This study presents an innovative hybrid model predictive control(MPC)framework that synergistically combines grey-box modeling with neural network-based disturbance prediction,specifically designed to overcome the control challenges of high-thermal-inertia TABS subject to unmeasurable stochastic disturbances.The framework is validated by experimental tests and supports both single and multiple disturbance scenarios.Concerning occupancy and outdoor solar global irradiance as the key stochastic disturbances,different control strategies including the rule-based control(RBC),conventional MPC without disturbance prediction,MPC with single disturbance prediction,MPC with multiple disturbances prediction,are established and systematically compared.Performance metrics including the temperature regulation accuracy,energy consumption,operation cost,and energy flexibility are quantitatively investigated.The results demonstrate that all MPC strategies outperform RBC.Compared to conventional MPC,the disturbance-prediction-coupled MPC reduces temperature constraint violations by 20%–42%,achieves 6%cost savings,and improves energy flexibility by 3.1%–8.6%.The multi-disturbanceprediction MPC shows optimal performance in temperature control,cost savings and energy flexibility enhancement.The proposed framework improves the accuracy of building load forecasting and the control performance of high thermal inertia systems,providing a pathway for optimizing building energy consumption and the coordinated operation efficiency of renewable energy in practical engineering applications.展开更多
基金financially supported by the National Key R&D Program of China(Grant No.2016YFC0300802)the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB06050200)
文摘In this study, a dynamic modeling method for foil-like underwater vehicles is introduced and experimentally verified in different sea tests of the Hadal ARV. The dumping force of a foil-like underwater vehicle is sensitive to swing motion. Some foil-like underwater vehicles swing periodically when performing a free-fall dive task in experiments. Models using conventional modeling methods yield solutions with asymptotic stability, which cannot simulate the self-sustained swing motion. By improving the ridge regression optimization algorithm, a grey-box modeling method based on 378 viscous drag coefficients using the Taylor series expansion is proposed in this study. The method is optimized for over-fitting and convergence problems caused by large parameter matrices. Instead of the PMM test data, the unsteady computational fluid dynamics calculation results are used in modeling. The obtained model can better simulate the swing motion of the underwater vehicle. Simulation and experimental results show a good consistency in free-fall tests during sea trials, as well as a prediction of the dive speed in the swing state.
文摘In order to solve the problem of difficult modeling and identification caused by time-variable parameters,multiple inputs and outputs and unstable open loop,a subsystem model-based close-loop grey-box identification method was put forward when consider the main coupling effects of hydraulic Stewart platform.Firstly,the whole system is divided into three TITO(Two Input Two Output) subsystems according to the characteristics of the pseudo-mass matrix,hence transfer function matrix model of the subsystem can also be found.Secondly,since the Stewart platform is unstable,the close-loop transfer model of the subsystem is derived under the proportional controllers.The inverse M serial is adopted as the identification signal to get the experimental data.All parameters of the subsystem are determined in close-loop indirect identification by PEM(Prediction Error Method).Finally,a case study validates the correctness and effectiveness of the subsystem model-based close-loop grey-box identification method for hydraulic Stewart platform.
基金supported by the National Key R&D Program of China(Grant No.2019YFB1311200).
文摘Soft grippers are favored for handling delicate objects due to their compliance but often have lower load capacities compared to rigid ones.Variable Stiffness Module(VSM)offer a solution,balancing flexibility and load capacity,for which particle jamming is an effective technology for stiffness-tunable robots requiring safe interaction and load capacity.Specific applica-tions,such as rescue scenarios,require quantitative analysis to optimize VSM design parameters,which previous analytical models cannot effectively handle.To address this,a Grey-box model is proposed to analyze the mechanical response of the particle-jamming-based VSM by combining a White-box approach based on the virtual work principle with a Black-box approach that uses a shallow neural network method.The Grey-box model demonstrates a high level of accuracy in predict-ing the VSM force-height mechanical response curves,with errors below 15%in almost 90%of the cases and a maximum error of less than 25%.The model is used to optimize VSM design parameters,particularly those unexplored combinations.Our results from the load capacity and force distribution comparison tests indicate that the VSM,optimized through our methods,quantitatively meets the practical engineering requirements.
文摘In this paper, the test suite construction for GUI (Graphical User Interface) software may be executed centered on grey-box approach with the prior test design of window access controls for unit testing, including front-end method of white box and follow-up black box method for integration testing. Moreover, two key opinions are proposed for the test suite construction for GUI software, the first one is that the “Triple-step method” should be used for unit testing with the prior disposing of data boundary value testing of input controls, and another one is that the “Grey-box approach” should be applied in integration testing for GUI software with necessary testing preparation in the precondition. At the same time, the testing of baseline version and the incremental testing should be considered for the test case construction to coordinate with the whole evolution of software product today. Additionally, all our opinion and thought are verified and tested with a typical case of GUI software—PQMS (Product Quality Monitoring Software/System), and results indicate that these methods and specific disposing are practical and effective.
基金supported by the National Key Research and Development Program of China under Grant No.2021YFB3101802.
文摘Fuzz testing is crucial for identifying software vulnerabilities,with coverage-guided grey-box fuzzers like AFL and Angora excelling in broad detection.However,as the need for targeted detection grows,directed grey-box fuzzing(DGF)has become essential,focusing on specific vulnerabilities.The initial seed corpus,which consists of carefully selected input samples that the fuzzer uses as a starting point,is fundamental in determining the paths that the fuzzer explores.A well-designed seed corpus can guide the fuzzer more effectively towards critical areas of the code,improving the efficiency and success of the fuzzing process.Even with its importance,much work concentrates on refining guidance mechanisms while paying less attention to optimizing the initial seed corpus.In this paper,we introduce ISC4DGF,a novel approach to generating optimized initial seed corpus for DGF using large language models(LLMs).By leveraging LLMs’deep understanding of software and refined user inputs,ISC4DGF creates a precise seed corpus that efficiently triggers specific vulnerabilities through a multi-round validation process.Implemented on AFL and tested against state-of-the-art fuzzers such as Titan,BEACON,AFLGo,FairFuzz,and Entropic using the Magma benchmark,ISC4DGF achieves a 25.03x speedup with fewer target reaches.Moreover,ISC4DGF improves target vulnerabilities detection accuracy while narrowing the detection scope and reducing code coverage.
基金the National Renewable Energy Laboratory for the U.S.Department of Energy(DOE)under contract no.DE-AC36-08GO28308Department of Energy Office of Energy Efficiency and Renewable Energy Building Technologies Office and in part by Copeland through contract CRD-19-16224.
文摘Commercial buildings,in particular grocery stores(due mainly to their large refrigeration load),provide opportunities for energy cost reductions.Grocery stores could offer substantial load flexibility to the power grid through participation in demand response programs because of their usage patterns and relatively high energy intensity.This load flexibility could come from modifying the control of heating,ventilation,and air conditioning(HVAC)systems,refrigeration systems,or both.Although estimation of the HVAC system’s load flexibility potential is relatively targeted in the literature,estimating load flexibility of refrigeration systems is nascent and has been a challenge,in part because of the lack of proper simulation tools that capture the dynamics in the refrigeration cases.The existing refrigerated case model within EnergyPlus,a whole building energy simulation program,assumes a constant case temperature throughout the simulation period and does not explicitly model the cycling of the compressor serving the refrigerated case.In addition,it does not encompass modeling of temperatures of the product inside the refrigerated case.This difference between modeled and actual operation can be a barrier to the development of demand control algorithm and accurate analysis of load flexibility potential.In this paper,we present a grey-box model for modeling refrigerated cases in grocery stores,which include medium temperature and low temperature.Four cases are modeled;two are low-temperature closed cases and two are medium-temperature cases with one closed and one open.Data from an experimental facility are used to train and test the models.Results demonstrate the efficacy of the grey-box models in predicting the temperatures.This model is integrated into EnergyPlus to capture the dynamic effects of case temperature on the environment and enhance the calculation of sensible and latent heat exchange with the environment(case credits).These enhancements can be leveraged more broadly to model advanced refrigeration controls such as defrost,develop and test unique algorithms that could affect refrigeration interactions with HVAC,and refine store design for any commercial building with refrigeration.
基金partially funded by the National Natural Science Foundation of China(62273215)。
文摘Integrated continuous stirred-tank reactors and distillation columns with recycle(CSTR-DC-recycle)are essential components in chemical processes.This paper proposes a method to establish a normal operating zone(NOZ)model to represent allowable variations of the CSTR-DC-recycle chemical processes.The NOZ is a geometric space containing all safe operating points of the CSTR-DC-recycle chemical processes,so that it is an effective model for process monitoring.The novelty of the proposed method is to establish the NOZ model based on boundary points.The boundary points make it possible to capture the actual geometric space irrespective of the space shape.In contrast,existing methods represent the NOZ of processes by fixed mathematical models such as ellipsoidal and convex-hull models;they are not suitable for the CSTR-DC-recycle chemical processes whose NOZs cannot be exactly defined by fixed mathematical structures.Simulated case studies based on Aspen Hysys software are given to illustrate the proposed method.
文摘In this paper, by means of effective testing practices, main strategies of integration testing for GUI software, including differentiating strategy for distinguished system, strategy of personnel organization, incremental testing strategy based on baseline version, testing strategy of circulating loop through the whole life, and the strategy of test suite construction, were briefly investigated. Moreover, for the code analysis, the FTA (Fault Tree analysis) is proposed to deal with the software change in regression testing. For test suite constructing, the constructing methods for baseline version and the incremental change are deeply discussed, in which main points focus on the testing strategy based on “Sheet/Form”, the “Grey-box approach” for integration testing process, and the application of the improved STD (State Transform Diagram) in state testing. At the same time, the suite construction of integration testing for two types, including small scale program and large scale software, is analyzed and discussed in detail. For testing execution, the specific method based on “Cross-testing” is investigated. Concurrently, by a lot of examples, all results of testing activity indicate that these strategies and methods are useful and fitted to integration testing for GUI software.
基金funded by the National Natural Science Foundation of China(Project No.52208120)the Opening Fund of Anhui Province Key Laboratory of Intelligent Building&Building Energy Saving,Anhui Jianzhu University(Project No.IBES2024KF07).
文摘Thermally activated building system(TABS)embeds heat exchanging tubes inside the building structure.The high thermal inertia possesses significant energy flexibility potential but also results in challenges for effective control,especially for the situations with unmeasurable stochastic thermal disturbances.This study presents an innovative hybrid model predictive control(MPC)framework that synergistically combines grey-box modeling with neural network-based disturbance prediction,specifically designed to overcome the control challenges of high-thermal-inertia TABS subject to unmeasurable stochastic disturbances.The framework is validated by experimental tests and supports both single and multiple disturbance scenarios.Concerning occupancy and outdoor solar global irradiance as the key stochastic disturbances,different control strategies including the rule-based control(RBC),conventional MPC without disturbance prediction,MPC with single disturbance prediction,MPC with multiple disturbances prediction,are established and systematically compared.Performance metrics including the temperature regulation accuracy,energy consumption,operation cost,and energy flexibility are quantitatively investigated.The results demonstrate that all MPC strategies outperform RBC.Compared to conventional MPC,the disturbance-prediction-coupled MPC reduces temperature constraint violations by 20%–42%,achieves 6%cost savings,and improves energy flexibility by 3.1%–8.6%.The multi-disturbanceprediction MPC shows optimal performance in temperature control,cost savings and energy flexibility enhancement.The proposed framework improves the accuracy of building load forecasting and the control performance of high thermal inertia systems,providing a pathway for optimizing building energy consumption and the coordinated operation efficiency of renewable energy in practical engineering applications.
