Molten salt reactors(MSRs)are a promising candidate for Generation IV reactor technologies,and the small modular molten salt reactor(SM-MSR),which utilizes low-enriched uranium and thorium fuels,is regarded as a wise ...Molten salt reactors(MSRs)are a promising candidate for Generation IV reactor technologies,and the small modular molten salt reactor(SM-MSR),which utilizes low-enriched uranium and thorium fuels,is regarded as a wise development path to accelerate deployment time.Uncertainty and sensitivity analyses of accidents guide nuclear reactor design and safety analyses.Uncertainty analysis can ascertain the safety margin,and sensitivity analysis can reveal the correlation between accident consequences and input parameters.Loss of forced cooling(LOFC)represents an accident scenario of the SM-MSR,and the study of LOFC could offer useful information to improve physical thermohydraulic and structural designs.Therefore,this study investigates the uncertainty of LOFC consequences and the sensitivity of related parameters.The uncertainty of the LOFC consequences was analyzed using the Monte Carlo method,and multiple linear regression was employed to analyze the sensitivity of the input parameters.The uncertainty and sensitivity analyses showed that the maximum reactor outlet fuel salt temperature was 725.5℃,which is lower than the acceptable criterion,and five important parameters influencing LOFC consequences were identified.展开更多
Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NP...Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.展开更多
This study investigates how the uncertainty surrounding cryptocurrency affects cryptocurrency returns(CR)by employing various wavelet techniques.We concentrate on the recently published cryptocurrency uncertainty inde...This study investigates how the uncertainty surrounding cryptocurrency affects cryptocurrency returns(CR)by employing various wavelet techniques.We concentrate on the recently published cryptocurrency uncertainty index(UCRY)and the top eight cryptocurrencies by market capitalization from December 30,2013,to June 30,2023.Our results showed that the UCRY index strongly predicted CR.In particular,the UCRY index has a leading position at all frequencies for all cryptocurrencies in our sample.Additionally,when the impacts of economic policy uncertainty and the volatility index are eliminated,the significant comovement of UCRY-CR remains unchanged for the short-,medium-,and long-term investment horizons.Therefore,we conclude that the UCRY-CR relationship is both persistent and pervasive.Our study contributes toward the literature on the relationships between cryptocurrencies and market uncertainties,as well as toward investors who use uncertainty indices to design investment strategies for their portfolios.展开更多
Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal ene...Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.展开更多
Damage to electrical equipment in an earthquake can lead to power outage of power systems.Seismic fragility analysis is a common method to assess the seismic reliability of electrical equipment.To further guarantee th...Damage to electrical equipment in an earthquake can lead to power outage of power systems.Seismic fragility analysis is a common method to assess the seismic reliability of electrical equipment.To further guarantee the efficiency of analysis,multi-source uncertainties including the structure itself and seismic excitation need to be considered.A method for seismic fragility analysis that reflects structural and seismic parameter uncertainty was developed in this study.The proposed method used a random sampling method based on Latin hypercube sampling(LHS)to account for the structure parameter uncertainty and the group structure characteristics of electrical equipment.Then,logistic Lasso regression(LLR)was used to find the seismic fragility surface based on double ground motion intensity measures(IM).The seismic fragility based on the finite element model of an±1000 kV main transformer(UHVMT)was analyzed using the proposed method.The results show that the seismic fragility function obtained by this method can be used to construct the relationship between the uncertainty parameters and the failure probability.The seismic fragility surface did not only provide the probabilities of seismic damage states under different IMs,but also had better stability than the fragility curve.Furthermore,the sensitivity analysis of the structural parameters revealed that the elastic module of the bushing and the height of the high-voltage bushing may have a greater influence.展开更多
To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate ...To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate with all four edges clamped(CCCC)are derived based on Navier's method and Galerkin's method.The novelty of the current work is that the number of unknowns in the displacement field model of a CCCC plate with free midsurface(CCCC-2 plate)is only three compared with four or five in cases of other exposed methods.The present analytical method is proved to be accurate and reliable by comparing linear natural frequencies and nonlinear natural frequencies with other models available in the open literature.Furthermore,a novel method for analyzing effects of mean values and tolerance zones of uncertain structural parameters on random frequencies is proposed based on a self-developed Multiscale Feature Extraction and Fusion Network(MFEFN)system.Compared with a direct Monte Carlo Simulation(MCS),the MFEFNbased procedure significantly reduces the calculation burden with a guarantee of accuracy.Our research provides a method to calculate nonlinear natural frequencies under two boundary conditions and presentes a surrogate model to predict frequencies for accuracy analysis and optimization design.展开更多
To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA）...To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA） is proposed to analyze vibro-acoustics responses with uncertainties at middle frequencies. The mid-frequency dynamic response of the framework-plate structure with uncertainties is studied based on the hybrid FE-SEA method and the Monte Carlo（MC）simulation is performed so as to provide a benchmark comparison with the hybrid method. The energy response of the framework-plate structure matches well with the MC simulation results, which validates the effectiveness of the hybrid FE-SEA method considering both the complexity of the vibro-acoustic structure and the uncertainties in mid-frequency vibro-acousitc analysis. Based on the hybrid method, a vibroacoustic model of a construction machinery cab with random properties is established, and the excitations of the model are measured by experiments. The responses of the sound pressure level of the cab and the vibration power spectrum density of the front windscreen are calculated and compared with those of the experiment. At middle frequencies, the results have a good consistency with the tests and the prediction error is less than 3. 5dB.展开更多
The dynamic influence of joints in aero-engine rotor systems is investigated in this paper.Firstly,the tangential stiffness and loss factor are obtained from an isolated lap joint setup with dynamic excitation experim...The dynamic influence of joints in aero-engine rotor systems is investigated in this paper.Firstly,the tangential stiffness and loss factor are obtained from an isolated lap joint setup with dynamic excitation experiments.Also,the influence of the normal contact pressure and the excitation level are examined,which revel the uncertainty in joints.Then,the updated Thin Layer Elements(TLEs)method with fitted parameters based on the experiments is established to simulate the dynamic properties of joints on the interface.The response of the rotor subjected to unbalance excitation is calculated,and the results illustrate the effectiveness of the proposed method.Meanwhile,using the Chebyshev inclusion function and a direct iteration algorithm,a nonlinear interval analysis method is established to consider the uncertainty of parameters in joints.The accuracy is proved by comparison with results obtained using the Monte-Carlo method.Combined with the updated TLEs,the nonlinear Chebyshev method is successfully applied on a finite model of a rotor.The study shows that substantial attention should be paid to the dynamical design for the joint in rotor systems,the dynamic properties of joints under complex loading and the corresponding interval analysis method need to be intensively studied.展开更多
One of the main difficulties in the geotechnical design process lies in dealing with uncertainty. Uncertainty is associated with natural variation of properties, and the imprecision and unpredictability caused by insu...One of the main difficulties in the geotechnical design process lies in dealing with uncertainty. Uncertainty is associated with natural variation of properties, and the imprecision and unpredictability caused by insufficient information on parameters or models. Probabilistic methods are normally used to quantify uncertainty. However, the frequentist approach commonly used for this purpose has some drawbacks.First, it lacks a formal framework for incorporating knowledge not represented by data. Second, it has limitations in providing a proper measure of the confidence of parameters inferred from data. The Bayesian approach offers a better framework for treating uncertainty in geotechnical design. The advantages of the Bayesian approach for uncertainty quantification are highlighted in this paper with the Bayesian regression analysis of laboratory test data to infer the intact rock strength parameters σand mused in the Hoek-Brown strength criterion. Two case examples are used to illustrate different aspects of the Bayesian methodology and to contrast the approach with a frequentist approach represented by the nonlinear least squares(NLLS) method. The paper discusses the use of a Student’s t-distribution versus a normal distribution to handle outliers, the consideration of absolute versus relative residuals, and the comparison of quality of fitting results based on standard errors and Bayes factors. Uncertainty quantification with confidence and prediction intervals of the frequentist approach is compared with that based on scatter plots and bands of fitted envelopes of the Bayesian approach. Finally, the Bayesian method is extended to consider two improvements of the fitting analysis. The first is the case in which the Hoek-Brown parameter, a, is treated as a variable to improve the fitting in the triaxial region. The second is the incorporation of the uncertainty in the estimation of the direct tensile strength from Brazilian test results within the overall evaluation of the intact rock strength.展开更多
The venturi meter has an advantage in its use,because it can measure flow without being much affected by the type of the measured fluid or flow conditions.Hence,it has excellent versatility and is being widely applied...The venturi meter has an advantage in its use,because it can measure flow without being much affected by the type of the measured fluid or flow conditions.Hence,it has excellent versatility and is being widely applied in many industries.The flow of a liquid containing air is a representative example of a multiphase flow and exhibits complex flow characteristics.In particular,the greater the gas volume fraction（GVF）,the more inhomogeneous the flow becomes.As a result,using a venturi meter to measure the rate of a flow that has a high GVF generates an error.In this study,the cause of the error occurred in measuring the flow rate for the multiphase flow when using the venturi meter for analysis by CFD.To ensure the reliability of this study,the accuracy of the multiphase flow models for numerical analysis was verified through comparison between the calculated results of numerical analysis and the experimental data.As a result,the Grace model,which is a multiphase flow model established by an experiment with water and air,was confirmed to have the highest reliability.Finally,the characteristics of the internal flow Held about the multiphase flow analysis result generated by applying the Grace model were analyzed to find the cause of the uncertainty occurring when measuring the flow rate of the multiphase flow using the venturi meter.A phase separation phenomenon occurred due to a density difference of water and air inside the venturi,and flow inhomogeneity happened according to the flow velocity difference of each phase.It was confirmed that this flow inhomogeneity increased as the GVF increased due to the uncertainty of the flow measurement.展开更多
The uncertainty analysis is an effective sensitivity analysis method for system model analysis and optimization. However,the existing single-factor uncertainty analysis methods are not well used in the logistic suppor...The uncertainty analysis is an effective sensitivity analysis method for system model analysis and optimization. However,the existing single-factor uncertainty analysis methods are not well used in the logistic support systems with multiple decision-making factors. The multiple transfer parameters graphical evaluation and review technique（MTP-GERT） is used to model the logistic support process in consideration of two important factors, support activity time and support activity resources, which are two primary causes for the logistic support process uncertainty. On this basis,a global sensitivity analysis（GSA） method based on covariance is designed to analyze the logistic support process uncertainty. The aircraft support process is selected as a case application which illustrates the validity of the proposed method to analyze the support process uncertainty, and some feasible recommendations are proposed for aircraft support decision making on carrier.展开更多
This article presents the application of an integrated method that estimates the dispersion of polycyclic aromatic hydrocarbons （PAHs） in air, and assesses the human health risk associated with PAHs inhalation. An u...This article presents the application of an integrated method that estimates the dispersion of polycyclic aromatic hydrocarbons （PAHs） in air, and assesses the human health risk associated with PAHs inhalation. An uncertainty analysis method consisting of three components were applied in this study, where the three components include a bootstrapping method for analyzing the whole process associated uncertainty, an inhalation rate （IR） representation for evaluating the total PAH inhalation risk for human health, and a normally distributed absorption fraction （AF） ranging from 0% to 100% to represent the absorption capability of PAHs in human body. Using this method, an integrated process was employed to assess the health risk of the residents in Beijing, China, from inhaling PAHs in the air. The results indicate that the ambient air PAHs in Beijing is an important contributor to human health impairment, although over 68% of residents seem to be safe from daily PAH carcinogenic inhalation. In general, the accumulated daily inhalation amount is relatively higher for male and children at 10 years old of age than for female and children at 6 years old. In 1997, about 1.73% cancer sufferers in Beijing were more or less related to ambient air PAHs inhalation. At 95% confidence interval, approximately 272-309 individual cancer incidences can be attributed to PAHs pollution in the air. The probability of greater than 500 cancer occurrence is 15.3%. While the inhalation of ambient air PAHs was shown to be an important factor responsible for higher cancer occurrence in Beijing, while the contribution might not be the most significant one.展开更多
Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system ...Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization （DDO） and uncertainty-based design optimization （UDO） are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation （KMCS） and Kriging-based Taylor series approximation （KTSA）, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods： DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.展开更多
Inevitable geometric variations significantly affect the performance of turbines or even that of entire engines;thus,it is necessary to determine their actual characteristics and accurately estimate their impact on pe...Inevitable geometric variations significantly affect the performance of turbines or even that of entire engines;thus,it is necessary to determine their actual characteristics and accurately estimate their impact on performance.In this study,based on 1781 measured profiles of a typical turbine blade,the statistical characteristics of the geometric variations and the uncertainty impact are analyzed,and some commonly used uncertainty modelling methods based on Principal-Component Analysis(PCA)are verified.The geometric variations are found to be evident,asymmetric,and non-uniform,and the non-normality of the random distributions is non-negligible.The performance is notably affected,which is manifested as an overall offset,a notable scattering,and significant deterioration in several extreme cases.Additionally,it is demonstrated that the PCA reconstruction model is effective in characterizing major uncertainty characteristics of the geometric variations and their impact on the performance with almost the first 10 PCA modes.Based on a reasonable profile error and mean geometric deviation,the Gaussian assumption and stochasticprocess-based model are also found to be effective in predicting the mean values and standard deviations of the performance variations.However,they fail to predict the probability of some extreme cases with high loss.Finally,a Chi-square-based correction model is proposed to compensate for this deficiency.The present work can provide a useful reference for uncertainty analysis of the impact of geometric variations,and the corresponding uncertainty design of turbine blades.展开更多
The crashworthiness is an important design factor of civil aircraft related with the safety of occupant during impact accident. It is a highly nonlinear transient dynamic problem and may be greatly influenced by the u...The crashworthiness is an important design factor of civil aircraft related with the safety of occupant during impact accident. It is a highly nonlinear transient dynamic problem and may be greatly influenced by the uncertainty factors. Crashworthiness uncertainty analysis is conducted to investigate the effects of initial conditions, structural dimensions and material properties. Simplified finite element model is built based on the geometrical model and basic physics phenomenon. Box-Behnken sampling and response surface methods are adopted to obtain gradient information. Results show that the proposed methods are effective for crashworthiness uncertainty analysis. Yield stress, frame thickness, impact velocity and angle have great influence on the failure behavior, and yield stress and frame thickness dominate the uncertainty of internal energy. Failure strain and tangent modulus have the smallest influence on the initial peak acceleration, and gradients of mean acceleration increase because the appearance of material plastic deformation and element failure.展开更多
To improve the vibration isolation performance of suspensions,various new structural forms of suspensions have been proposed.However,there is uncertainty in these new structure suspensions,so the deterministic researc...To improve the vibration isolation performance of suspensions,various new structural forms of suspensions have been proposed.However,there is uncertainty in these new structure suspensions,so the deterministic research cannot refect the performance of the suspension under actual operating conditions.In this paper,a quasi-zero stifness isolator is used in automotive suspensions to form a new suspension−quasi-zero stifness air suspension(QZSAS).Due to the strong nonlinearity and structural complexity of quasi-zero stifness suspensions,changes in structural parameters may cause dramatic changes in suspension performance,so it is of practical importance to study the efect of structural parameter uncertainty on the suspension performance.In order to solve this problem,three suspension structural parameters d_(0),L_(0) and Pc_(0) are selected as random variables,and the polynomial chaos expansion(PCE)theory is used to solve the suspension performance parameters.The sensitivity of the performance parameters to diferent structural parameters was discussed and analyzed in the frequency domain.Furthermore,a multi-objective optimization of the structural parameters d_(0),L_(0) and Pc_(0) of QZSAS was performed with the mean and variance of the root-mean-square(RMS)acceleration values as the optimization objectives.The optimization results show that there is an improvement of about 8%−1_(0)%in the mean value and about 4_(0)%−55%in the standard deviation of acceleration(RMS)values.This paper verifes the feasibility of the PCE method for solving the uncertainty problem of complex nonlinear systems,which provide a reference for the future structural design and optimization of such suspension systems.展开更多
For structural systems with both epistemic and aleatory uncertainties, research on quantifying the contribution of the epistemic and aleatory uncertainties to the failure probability of the systems is conducted. Based...For structural systems with both epistemic and aleatory uncertainties, research on quantifying the contribution of the epistemic and aleatory uncertainties to the failure probability of the systems is conducted. Based on the method of separating epistemic and aleatory uncertainties in a variable, the core idea of the research is firstly to establish a novel deterministic transition model for auxiliary variables, distribution parameters, random variables, failure probability, then to propose the improved importance sampling （IS） to solve the transition model. Furthermore, the distribution parameters and auxiliary variables are sampled simultaneously and independently;therefore, the inefficient sampling procedure with an＇＇inner-loop＇＇ for epistemic uncertainty and an＇＇outer-loop＇＇ for aleatory uncertainty in traditional methods is avoided. Since the proposed method combines the fast convergence of the proper estimates and searches failure samples in the interesting regions with high efficiency, the proposed method is more efficient than traditional methods for the variance-based failure probability sensitivity measures in the presence of epistemic and aleatory uncertainties. Two numerical examples and one engineering example are introduced for demonstrating the efficiency and precision of the proposed method for structural systems with both epistemic and aleatory uncertainties.展开更多
Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent r...Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.展开更多
The reliability estimation of mechanical seals is of crucial importance due to their wide applications in pumps in various mechanical systems.Failure of mechanical seals might cause leakage,and might lead to system fa...The reliability estimation of mechanical seals is of crucial importance due to their wide applications in pumps in various mechanical systems.Failure of mechanical seals might cause leakage,and might lead to system failure and other relevant consequences.In this study,the reliability estimation for mechanical seals based on bivariate dependence analysis and considering model uncertainty is proposed.The friction torque and leakage rate are two degradation performance indicators of mechanical seals that can be described by the Wiener process,Gamma process,and inverse Gaussian process.The dependence between the two indicators can be described by different copula functions.Then the model uncertainty is considered in the reliability estimation using the Bayesian Model Average(BMA)method,while the unknown parameters in the model are estimated by Bayesian Markov Chain Monte Carlo(MCMC)method.A numerical simulation study and fatigue crack study are conducted to demonstrate the effectiveness of the BMA method to capture model uncertainty.A degradation test of mechanical seals is conducted to verify the proposed model.The optimal stochastic process models for two performance indicators and copula function are determined based on the degradation data.The results show the necessity of using the BMA method in degradation modeling.展开更多
The measurement uncertainty provides complete information about an analytical result. This is very important because several decisions of compliance or non-compliance are based on analytical results in pharmaceutical ...The measurement uncertainty provides complete information about an analytical result. This is very important because several decisions of compliance or non-compliance are based on analytical results in pharmaceutical industries. The aim of this work was to evaluate and discuss the estimation of uncertainty in pharmaceutical analysis. The uncertainty is a useful tool in the assessment of compliance or non-compliance of in-process and final pharmaceutical products as well as in the assessment of pharmaceutical equivalence and stability study of drug products.展开更多
基金supported by the Youth Innovation Promotion Association(YIPA)(No.E329290101)of the Chinese Academy of Sciences。
文摘Molten salt reactors(MSRs)are a promising candidate for Generation IV reactor technologies,and the small modular molten salt reactor(SM-MSR),which utilizes low-enriched uranium and thorium fuels,is regarded as a wise development path to accelerate deployment time.Uncertainty and sensitivity analyses of accidents guide nuclear reactor design and safety analyses.Uncertainty analysis can ascertain the safety margin,and sensitivity analysis can reveal the correlation between accident consequences and input parameters.Loss of forced cooling(LOFC)represents an accident scenario of the SM-MSR,and the study of LOFC could offer useful information to improve physical thermohydraulic and structural designs.Therefore,this study investigates the uncertainty of LOFC consequences and the sensitivity of related parameters.The uncertainty of the LOFC consequences was analyzed using the Monte Carlo method,and multiple linear regression was employed to analyze the sensitivity of the input parameters.The uncertainty and sensitivity analyses showed that the maximum reactor outlet fuel salt temperature was 725.5℃,which is lower than the acceptable criterion,and five important parameters influencing LOFC consequences were identified.
基金National Natural Science Foundation of China under Grant Nos.52208191 and 51908397Shanxi Province Science Foundation for Youths under Grant No.201901D211025China Postdoctoral Science Foundation under Grant No.2020M670695。
文摘Seismic fragility analysis(SFA)is known as an effective probabilistic-based approach used to evaluate seismic fragility.There are various sources of uncertainties associated with this approach.A nuclear power plant(NPP)system is an extremely important infrastructure and contains many structural uncertainties due to construction issues or structural deterioration during service.Simulation of structural uncertainties effects is a costly and time-consuming endeavor.A novel approach to SFA for the NPP considering structural uncertainties based on the damage state is proposed and examined.The results suggest that considering the structural uncertainties is essential in assessing the fragility of the NPP structure,and the impact of structural uncertainties tends to increase with the state of damage.Subsequently,machine learning(ML)is found to be superior in high-precision damage state identification of the NPP for reducing the time of nonlinear time-history analysis(NLTHA)and could be applied in the damage state-based SFA.Also,the impact of various sources of uncertainties is investigated through sensitivity analysis.The Sobol and Shapley additive explanations(SHAP)method can be complementary to each other and able to solve the problem of quantifying seismic and structural uncertainties simultaneously and the interaction effect of each parameter.
文摘This study investigates how the uncertainty surrounding cryptocurrency affects cryptocurrency returns(CR)by employing various wavelet techniques.We concentrate on the recently published cryptocurrency uncertainty index(UCRY)and the top eight cryptocurrencies by market capitalization from December 30,2013,to June 30,2023.Our results showed that the UCRY index strongly predicted CR.In particular,the UCRY index has a leading position at all frequencies for all cryptocurrencies in our sample.Additionally,when the impacts of economic policy uncertainty and the volatility index are eliminated,the significant comovement of UCRY-CR remains unchanged for the short-,medium-,and long-term investment horizons.Therefore,we conclude that the UCRY-CR relationship is both persistent and pervasive.Our study contributes toward the literature on the relationships between cryptocurrencies and market uncertainties,as well as toward investors who use uncertainty indices to design investment strategies for their portfolios.
基金supported by the National Natural Science Foundation of China(12305185)Natural Science Foundation of Hunan Province,China(No.2023JJ50122)+1 种基金International Cooperative Research Project of the Ministry of Education,China(No.HZKY20220355)Scientific Research Foundation of the Education Department of Hunan Province,China(No.22A0307).
文摘Compared to other energy sources,nuclear reactors offer several advantages as a spacecraft power source,including compact size,high power density,and long operating life.These qualities make nuclear power an ideal energy source for future deep space exploration.A whole system model of the space nuclear reactor consisting of the reactor neutron kinetics,reactivity control,reactor heat transfer,heat exchanger,and thermoelectric converter was developed.In addition,an electrical power control system was designed based on the developed dynamic model.The GRS method was used to quantitatively calculate the uncertainty of coupling parameters of the neutronics,thermal-hydraulics,and control system for the space reactor.The Spearman correlation coefficient was applied in the sensitivity analysis of system input parameters to output parameters.The calculation results showed that the uncertainty of the output parameters caused by coupling parameters had the most considerable variation,with a relative standard deviation<2.01%.Effective delayed neutron fraction was most sensitive to electrical power.To obtain optimal control performance,the non-dominated sorting genetic algorithm method was employed to optimize the controller parameters based on the uncertainty quantification calculation.Two typical transient simulations were conducted to test the adaptive ability of the optimized controller in the uncertainty dynamic system,including 100%full power(FP)to 90%FP step load reduction transient and 5%FP/min linear variable load transient.The results showed that,considering the influence of system uncertainty,the optimized controller could improve the response speed and load following accuracy of electrical power control,in which the effectiveness and superiority have been verified.
基金National Key R&D Program of China under Grant Nos.2018YFC1504504 and 2018YFC0809404。
文摘Damage to electrical equipment in an earthquake can lead to power outage of power systems.Seismic fragility analysis is a common method to assess the seismic reliability of electrical equipment.To further guarantee the efficiency of analysis,multi-source uncertainties including the structure itself and seismic excitation need to be considered.A method for seismic fragility analysis that reflects structural and seismic parameter uncertainty was developed in this study.The proposed method used a random sampling method based on Latin hypercube sampling(LHS)to account for the structure parameter uncertainty and the group structure characteristics of electrical equipment.Then,logistic Lasso regression(LLR)was used to find the seismic fragility surface based on double ground motion intensity measures(IM).The seismic fragility based on the finite element model of an±1000 kV main transformer(UHVMT)was analyzed using the proposed method.The results show that the seismic fragility function obtained by this method can be used to construct the relationship between the uncertainty parameters and the failure probability.The seismic fragility surface did not only provide the probabilities of seismic damage states under different IMs,but also had better stability than the fragility curve.Furthermore,the sensitivity analysis of the structural parameters revealed that the elastic module of the bushing and the height of the high-voltage bushing may have a greater influence.
基金the research project funded by the Fundamental Research Funds for the Central Universities(No.HIT.OCEP.2024038)the National Natural Science Foundation of China(No.52372351)the State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster,China(No.MS02240107)。
文摘To improve design accuracy and reliability of structures,this study solves the uncertain natural frequencies with consideration for geometric nonlinearity and structural uncertainty.Frequencies of the laminated plate with all four edges clamped(CCCC)are derived based on Navier's method and Galerkin's method.The novelty of the current work is that the number of unknowns in the displacement field model of a CCCC plate with free midsurface(CCCC-2 plate)is only three compared with four or five in cases of other exposed methods.The present analytical method is proved to be accurate and reliable by comparing linear natural frequencies and nonlinear natural frequencies with other models available in the open literature.Furthermore,a novel method for analyzing effects of mean values and tolerance zones of uncertain structural parameters on random frequencies is proposed based on a self-developed Multiscale Feature Extraction and Fusion Network(MFEFN)system.Compared with a direct Monte Carlo Simulation(MCS),the MFEFNbased procedure significantly reduces the calculation burden with a guarantee of accuracy.Our research provides a method to calculate nonlinear natural frequencies under two boundary conditions and presentes a surrogate model to predict frequencies for accuracy analysis and optimization design.
基金Science and Technology Support Planning of Jiangsu Province(No.BE2014133)the Open Foundation of Key Laboratory of Underw ater Acoustic Signal Processing(No.UASP1301)the Prospective Joint Research Project of Jiangsu province(No.BY2014127-01)
文摘To take into account the influence of uncetainties on the dynamic response of the vibro-acousitc structure, a hybrid modeling technique combining the finite element method（FE）and the statistic energy analysis（SEA） is proposed to analyze vibro-acoustics responses with uncertainties at middle frequencies. The mid-frequency dynamic response of the framework-plate structure with uncertainties is studied based on the hybrid FE-SEA method and the Monte Carlo（MC）simulation is performed so as to provide a benchmark comparison with the hybrid method. The energy response of the framework-plate structure matches well with the MC simulation results, which validates the effectiveness of the hybrid FE-SEA method considering both the complexity of the vibro-acoustic structure and the uncertainties in mid-frequency vibro-acousitc analysis. Based on the hybrid method, a vibroacoustic model of a construction machinery cab with random properties is established, and the excitations of the model are measured by experiments. The responses of the sound pressure level of the cab and the vibration power spectrum density of the front windscreen are calculated and compared with those of the experiment. At middle frequencies, the results have a good consistency with the tests and the prediction error is less than 3. 5dB.
基金supported by the National Natural Science Foundation of China(Nos.51575022,11772022 and 51475021).
文摘The dynamic influence of joints in aero-engine rotor systems is investigated in this paper.Firstly,the tangential stiffness and loss factor are obtained from an isolated lap joint setup with dynamic excitation experiments.Also,the influence of the normal contact pressure and the excitation level are examined,which revel the uncertainty in joints.Then,the updated Thin Layer Elements(TLEs)method with fitted parameters based on the experiments is established to simulate the dynamic properties of joints on the interface.The response of the rotor subjected to unbalance excitation is calculated,and the results illustrate the effectiveness of the proposed method.Meanwhile,using the Chebyshev inclusion function and a direct iteration algorithm,a nonlinear interval analysis method is established to consider the uncertainty of parameters in joints.The accuracy is proved by comparison with results obtained using the Monte-Carlo method.Combined with the updated TLEs,the nonlinear Chebyshev method is successfully applied on a finite model of a rotor.The study shows that substantial attention should be paid to the dynamical design for the joint in rotor systems,the dynamic properties of joints under complex loading and the corresponding interval analysis method need to be intensively studied.
基金supported by the Large Open PitⅡProject through contract No.019799 with the Geotechnical Research Centre of The University of Queensland and by SRK Consulting South Africa
文摘One of the main difficulties in the geotechnical design process lies in dealing with uncertainty. Uncertainty is associated with natural variation of properties, and the imprecision and unpredictability caused by insufficient information on parameters or models. Probabilistic methods are normally used to quantify uncertainty. However, the frequentist approach commonly used for this purpose has some drawbacks.First, it lacks a formal framework for incorporating knowledge not represented by data. Second, it has limitations in providing a proper measure of the confidence of parameters inferred from data. The Bayesian approach offers a better framework for treating uncertainty in geotechnical design. The advantages of the Bayesian approach for uncertainty quantification are highlighted in this paper with the Bayesian regression analysis of laboratory test data to infer the intact rock strength parameters σand mused in the Hoek-Brown strength criterion. Two case examples are used to illustrate different aspects of the Bayesian methodology and to contrast the approach with a frequentist approach represented by the nonlinear least squares(NLLS) method. The paper discusses the use of a Student’s t-distribution versus a normal distribution to handle outliers, the consideration of absolute versus relative residuals, and the comparison of quality of fitting results based on standard errors and Bayes factors. Uncertainty quantification with confidence and prediction intervals of the frequentist approach is compared with that based on scatter plots and bands of fitted envelopes of the Bayesian approach. Finally, the Bayesian method is extended to consider two improvements of the fitting analysis. The first is the case in which the Hoek-Brown parameter, a, is treated as a variable to improve the fitting in the triaxial region. The second is the incorporation of the uncertainty in the estimation of the direct tensile strength from Brazilian test results within the overall evaluation of the intact rock strength.
基金supported by the Industrial Infrastructure Program through The Korea Institute for Advancement of Technology(KIAT) Grant funded by the Korea government Ministry of Trade,Industry and Energy(Grant N0000502)
文摘The venturi meter has an advantage in its use,because it can measure flow without being much affected by the type of the measured fluid or flow conditions.Hence,it has excellent versatility and is being widely applied in many industries.The flow of a liquid containing air is a representative example of a multiphase flow and exhibits complex flow characteristics.In particular,the greater the gas volume fraction（GVF）,the more inhomogeneous the flow becomes.As a result,using a venturi meter to measure the rate of a flow that has a high GVF generates an error.In this study,the cause of the error occurred in measuring the flow rate for the multiphase flow when using the venturi meter for analysis by CFD.To ensure the reliability of this study,the accuracy of the multiphase flow models for numerical analysis was verified through comparison between the calculated results of numerical analysis and the experimental data.As a result,the Grace model,which is a multiphase flow model established by an experiment with water and air,was confirmed to have the highest reliability.Finally,the characteristics of the internal flow Held about the multiphase flow analysis result generated by applying the Grace model were analyzed to find the cause of the uncertainty occurring when measuring the flow rate of the multiphase flow using the venturi meter.A phase separation phenomenon occurred due to a density difference of water and air inside the venturi,and flow inhomogeneity happened according to the flow velocity difference of each phase.It was confirmed that this flow inhomogeneity increased as the GVF increased due to the uncertainty of the flow measurement.
基金supported by the National Natural Science Foundation of China(71171008)
文摘The uncertainty analysis is an effective sensitivity analysis method for system model analysis and optimization. However,the existing single-factor uncertainty analysis methods are not well used in the logistic support systems with multiple decision-making factors. The multiple transfer parameters graphical evaluation and review technique（MTP-GERT） is used to model the logistic support process in consideration of two important factors, support activity time and support activity resources, which are two primary causes for the logistic support process uncertainty. On this basis,a global sensitivity analysis（GSA） method based on covariance is designed to analyze the logistic support process uncertainty. The aircraft support process is selected as a case application which illustrates the validity of the proposed method to analyze the support process uncertainty, and some feasible recommendations are proposed for aircraft support decision making on carrier.
文摘This article presents the application of an integrated method that estimates the dispersion of polycyclic aromatic hydrocarbons （PAHs） in air, and assesses the human health risk associated with PAHs inhalation. An uncertainty analysis method consisting of three components were applied in this study, where the three components include a bootstrapping method for analyzing the whole process associated uncertainty, an inhalation rate （IR） representation for evaluating the total PAH inhalation risk for human health, and a normally distributed absorption fraction （AF） ranging from 0% to 100% to represent the absorption capability of PAHs in human body. Using this method, an integrated process was employed to assess the health risk of the residents in Beijing, China, from inhaling PAHs in the air. The results indicate that the ambient air PAHs in Beijing is an important contributor to human health impairment, although over 68% of residents seem to be safe from daily PAH carcinogenic inhalation. In general, the accumulated daily inhalation amount is relatively higher for male and children at 10 years old of age than for female and children at 6 years old. In 1997, about 1.73% cancer sufferers in Beijing were more or less related to ambient air PAHs inhalation. At 95% confidence interval, approximately 272-309 individual cancer incidences can be attributed to PAHs pollution in the air. The probability of greater than 500 cancer occurrence is 15.3%. While the inhalation of ambient air PAHs was shown to be an important factor responsible for higher cancer occurrence in Beijing, while the contribution might not be the most significant one.
基金supported by the National Natural Science Foundation of China(No.51305014)China Postdoctoral Science Foundation(No.2013M540842)
文摘Abstract In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor （HRM） powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity anal- ysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization （DDO） and uncertainty-based design optimization （UDO） are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation （KMCS） and Kriging-based Taylor series approximation （KTSA）, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods： DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.
基金supported by the National Science and Technology Major Project, China (No. J2019-II-0012-0032)
文摘Inevitable geometric variations significantly affect the performance of turbines or even that of entire engines;thus,it is necessary to determine their actual characteristics and accurately estimate their impact on performance.In this study,based on 1781 measured profiles of a typical turbine blade,the statistical characteristics of the geometric variations and the uncertainty impact are analyzed,and some commonly used uncertainty modelling methods based on Principal-Component Analysis(PCA)are verified.The geometric variations are found to be evident,asymmetric,and non-uniform,and the non-normality of the random distributions is non-negligible.The performance is notably affected,which is manifested as an overall offset,a notable scattering,and significant deterioration in several extreme cases.Additionally,it is demonstrated that the PCA reconstruction model is effective in characterizing major uncertainty characteristics of the geometric variations and their impact on the performance with almost the first 10 PCA modes.Based on a reasonable profile error and mean geometric deviation,the Gaussian assumption and stochasticprocess-based model are also found to be effective in predicting the mean values and standard deviations of the performance variations.However,they fail to predict the probability of some extreme cases with high loss.Finally,a Chi-square-based correction model is proposed to compensate for this deficiency.The present work can provide a useful reference for uncertainty analysis of the impact of geometric variations,and the corresponding uncertainty design of turbine blades.
基金supported by the Postdoctoral Science Foundation of China (Nos. 2012M510306, 2013T60054)
文摘The crashworthiness is an important design factor of civil aircraft related with the safety of occupant during impact accident. It is a highly nonlinear transient dynamic problem and may be greatly influenced by the uncertainty factors. Crashworthiness uncertainty analysis is conducted to investigate the effects of initial conditions, structural dimensions and material properties. Simplified finite element model is built based on the geometrical model and basic physics phenomenon. Box-Behnken sampling and response surface methods are adopted to obtain gradient information. Results show that the proposed methods are effective for crashworthiness uncertainty analysis. Yield stress, frame thickness, impact velocity and angle have great influence on the failure behavior, and yield stress and frame thickness dominate the uncertainty of internal energy. Failure strain and tangent modulus have the smallest influence on the initial peak acceleration, and gradients of mean acceleration increase because the appearance of material plastic deformation and element failure.
基金Supported by National Natural Science Foundation of China(Grant No.51875256)Open Platform Fund of Hunan Institute of Technology of China(Grant No.KFA20009)Hong Kong,Macao and Taiwan Science and Technology Cooperation Project in Jiangsu Province of China(Grant No.BZ2020050)。
文摘To improve the vibration isolation performance of suspensions,various new structural forms of suspensions have been proposed.However,there is uncertainty in these new structure suspensions,so the deterministic research cannot refect the performance of the suspension under actual operating conditions.In this paper,a quasi-zero stifness isolator is used in automotive suspensions to form a new suspension−quasi-zero stifness air suspension(QZSAS).Due to the strong nonlinearity and structural complexity of quasi-zero stifness suspensions,changes in structural parameters may cause dramatic changes in suspension performance,so it is of practical importance to study the efect of structural parameter uncertainty on the suspension performance.In order to solve this problem,three suspension structural parameters d_(0),L_(0) and Pc_(0) are selected as random variables,and the polynomial chaos expansion(PCE)theory is used to solve the suspension performance parameters.The sensitivity of the performance parameters to diferent structural parameters was discussed and analyzed in the frequency domain.Furthermore,a multi-objective optimization of the structural parameters d_(0),L_(0) and Pc_(0) of QZSAS was performed with the mean and variance of the root-mean-square(RMS)acceleration values as the optimization objectives.The optimization results show that there is an improvement of about 8%−1_(0)%in the mean value and about 4_(0)%−55%in the standard deviation of acceleration(RMS)values.This paper verifes the feasibility of the PCE method for solving the uncertainty problem of complex nonlinear systems,which provide a reference for the future structural design and optimization of such suspension systems.
基金supported by the National Natural Science Foundation of China (No. 51175425)the Special Research Fund for the Doctoral Program of Higher Education of China (No. 20116102110003)
文摘For structural systems with both epistemic and aleatory uncertainties, research on quantifying the contribution of the epistemic and aleatory uncertainties to the failure probability of the systems is conducted. Based on the method of separating epistemic and aleatory uncertainties in a variable, the core idea of the research is firstly to establish a novel deterministic transition model for auxiliary variables, distribution parameters, random variables, failure probability, then to propose the improved importance sampling （IS） to solve the transition model. Furthermore, the distribution parameters and auxiliary variables are sampled simultaneously and independently;therefore, the inefficient sampling procedure with an＇＇inner-loop＇＇ for epistemic uncertainty and an＇＇outer-loop＇＇ for aleatory uncertainty in traditional methods is avoided. Since the proposed method combines the fast convergence of the proper estimates and searches failure samples in the interesting regions with high efficiency, the proposed method is more efficient than traditional methods for the variance-based failure probability sensitivity measures in the presence of epistemic and aleatory uncertainties. Two numerical examples and one engineering example are introduced for demonstrating the efficiency and precision of the proposed method for structural systems with both epistemic and aleatory uncertainties.
基金partially supported by the National Natural Science Foundation of China(No.62173272)。
文摘Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.
基金supported by the National Natural Science Foundation of China(Nos.51875015,51620105010)。
文摘The reliability estimation of mechanical seals is of crucial importance due to their wide applications in pumps in various mechanical systems.Failure of mechanical seals might cause leakage,and might lead to system failure and other relevant consequences.In this study,the reliability estimation for mechanical seals based on bivariate dependence analysis and considering model uncertainty is proposed.The friction torque and leakage rate are two degradation performance indicators of mechanical seals that can be described by the Wiener process,Gamma process,and inverse Gaussian process.The dependence between the two indicators can be described by different copula functions.Then the model uncertainty is considered in the reliability estimation using the Bayesian Model Average(BMA)method,while the unknown parameters in the model are estimated by Bayesian Markov Chain Monte Carlo(MCMC)method.A numerical simulation study and fatigue crack study are conducted to demonstrate the effectiveness of the BMA method to capture model uncertainty.A degradation test of mechanical seals is conducted to verify the proposed model.The optimal stochastic process models for two performance indicators and copula function are determined based on the degradation data.The results show the necessity of using the BMA method in degradation modeling.
基金supported by Fundacao de Apoio à Pesquisa do Estado de Sao Paulo(FAPESP)
文摘The measurement uncertainty provides complete information about an analytical result. This is very important because several decisions of compliance or non-compliance are based on analytical results in pharmaceutical industries. The aim of this work was to evaluate and discuss the estimation of uncertainty in pharmaceutical analysis. The uncertainty is a useful tool in the assessment of compliance or non-compliance of in-process and final pharmaceutical products as well as in the assessment of pharmaceutical equivalence and stability study of drug products.
