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ObjectivesSubstantial epistemic and aleatory uncertainties coexist in the modeling and simulation (M&S) of ship non-contact underwater explosion (UNDEX). Such uncertainties can lead to large deviations between the numerical results and true experimental data for system response quantity (SRQ), which can deteriorate M&S performance. However, the uncertainty quantification (UQ) of non-contact UNDEX can improve the reliability and credibility of M&S.MethodsFirst, the D−S theory of evidence (DSTE) combined with subject matter expert (SME) opinion is utilized to obtain the basic belief assignment (BBA) function and value interval of the phenomenological parameters, which have no physical meaning and cannot be directly calibrated through physical experiments. In view of the constraints of engineering experience and knowledge structure of SME, the multiple source fusion and periodic fusion methods are used to further improve the objectivity of the epistemic UQ. Furthermore, the Monte Carlo method is applied to study the high-dimensional uncertainty propagation of the non-contact UNDEX of the ship. Finally, the double-loop method is applied in the mixed UQ when the ship non-contact UNDEX is disturbed by both aleatory uncertainty and epistemic uncertainty; to be specific, the phenomenological parameters are solved in the outer loop and the aleatory uncertainty is handled in the inner loop.ResultsThe results show that the range of epistemic uncertainty is shortened and the initial opinion of SME substantially altered. The BBA of epistemic uncertainty computed from altered DSTE becomes more accurate and objective. The credible confidence interval of SRQ and corresponding BBA function in the non-contact UNDEX calculation can be obtained by double loop approach, and the results indicate that it agrees with the common sense.ConclusionThis study can provide guiding references for ship protection design and improve the explosive damage power of underwater weapons.

The flexibility of thermal loads of buildings is a valuable balancing resource for operation of the heat and electricity integrated energy system (HE-IES). Considering the characteristics of large scale and small single load capacity of the themal load, the non-intrusive data-driven method has become an effective means to quantify the flexibility of building thermal load. However, due to the inaccuracy of the model or the lack of data, this method inevitably produces errors and brings epistemic uncertainty to the optimal dispatch of the HE-IES. An optimal dispatch model of the HE-IES that is compatible with the epistemic uncertainty of demand flexibility in the thermal loads of buildings is proposed. First, a data-driven flexible demand assessment method for building thermal load is described. The measurement errors are modeled as epistemic uncertainty and the multiple error sources are combined by using the D-S evidence theory. Then, the representative scenarios are selected to represent the epistemic uncertainty of the demand flexibility based Latin hypercube sampling(LHS) method, and the scenarios are reduced by the fuzzy clustering method. Finally, the representative scenarios are embedded in the coordinated and optimized dispatch of the HE-IES to realize the comprehensive consideration of the thermal load flexibility and related epistemic uncertainty of the building. The results demonstrate that considering the epistemic uncertainties of the thermal load demand is crucial for reducing the wind power curtailments and improving the operational flexibility of HE-IES.

To investigate the impact resistance of steel slag fine aggregate concrete, the concrete specimens were prepared by replacing fine aggregate with equal volume of steel slag at replacement rates of 10%, 20% and 30%, respectively. The impact resistance test was carried out by drop hammer impact device to study the impact life and damage evolution law, and the impact resistance of specimen was compared with ordinary concrete. The results show that the addition of steel slag fine aggregate can improve the impact resistance of concrete, and the impact life is obviously improved when the drop weight is small. There is a certain degree of dispersion in the results of concrete impact resistance test, and the impact life of steel slag concrete conforms to Weibull distribution. Based on the Weibull distribution, the impact life under different failure probabilities is estimated, and the impact damage evolution equation is established to calculate the corresponding impact times when the concrete with different steel slag content reaches a certain damage variable. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem that the aleatory uncertainty is only considered in the wear resistance reliability calculation of ball screw pair, and the epistemic uncertainty is not considered. Aiming at this problem, based on uncertainty theory, a reliability model of wear resistance of ball screw pair was established which considered both random uncertainty of parameters and cognitive uncertainty. Firstly, based on the modified Archard theory, the wear resistance model of the ball screw pair was established. Then, by introducing the uncertainty theory, the wear-resistant reliability model of the ball screw pair was established. In view of the problem that the uncertainty distribution of the wear-resistant reliability in the model could not be obtained, a two-layer parameter uncertainty simulation algorithm was proposed. Finally, the established reliability model and the uncertainty simulation algorithm were analyzed and calculated through an example, and the influence of the uncertainty of each parameter on the wear-resistant reliability of the ball screw was analyzed. The results show that the reliability is 0.656 522 when the aleatory uncertainty is considered, and the reliability is 0.770 07 by Monte Carlo method without aleatory uncertainty. From the calculation results, it is concluded that the uncertainty of the parameters can reduce the reliability of the ball screw. The uncertainty of the guide angle has the greatest influence on the wear resistance reliability, followed by the pitch diameter, wear coefficient, contact angle, axial load and adaptation ratio, and the influence of the ball diameter is the smallest. The research results can provide a reference for the optimal design and reliability improvement of the ball screw pair. [ABSTRACT FROM AUTHOR]

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Brewing is the property of China Brewing Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Engineering Mechanics / Gongcheng Lixue is the property of Engineering Mechanics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Systems Engineering & Electronics is the property of Journal of Systems Engineering & Electronics Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To compute the sensitivity of the hybrid uncertain system in which both aleatory and epistemic uncertainties are present, a global sensitivity analysis method is proposed on the basis of evidence theory and conditional probability theory. The aleatory uncertain variables are represented by using the evidence theory. For epistemic uncertain variable, two stochastic sampling approaches based on the evidence theory are put forward, which are named one-step and two-step random sampling approach, respectively. With the conditional probability theory and the Sobol, method used, the global sensitivity indexes of the hybrid uncertain system are proposed in the presence of epistemic uncertainties, and the formulas of the first-order and total sensitivity indexes are derived. A single-loop quasi-Monte Carlo simulation is developed and it is used to approximately calculate the sensitivity indexes proposed. The sensitivity analysis program based on Matlab is designed. A typical example is presented and its results show that the proposed method is correct and its computational cost is acceptable. [ABSTRACT FROM AUTHOR]

Copyright of Transactions of Beijing Institute of Technology is the property of Beijing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Vibration Engineering is the property of Nanjing University of Aeronautics & Astronautics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

There is epistemic uncertainty on high-reliability components since it is hard to obtain adequate performance data of the components within a short time. The components′ performance distribution parameter is assumed as a fuzzy number, according to the decomposition theorem of the fuzzy set, a performance distribution model based on β- level cut set is built, and a definition of the components′ performance interval in the fuzzy state and a computational method of the fuzzy state probability are provided. The traditional universal generating function is improved, the α-level cut set universal generating function and its algorithm are defined. An assessment method of fuzzy reliability of multi state system in consideration of epistemic uncertainty is proposed, and verification and illustration are conducted with simulation examples in order to reduce the influence on components′ performance analysis and achieve precise estimation of system reliability. This method overcomes the shortcoming that a state information analysis model cannot be accurately built on account of the deficiency of performance distribution information. It can be widely used and has great engineering application value. [ABSTRACT FROM AUTHOR]

Considering computer model validation under epistemic uncertainty, this paper developed an improved Bayesian model validation method which combined the second order probability method and the interval number rank method. The method first accomplished the model uncertainty quantification by the second order probability method. Then it updated the prior model response computed from uncertainty quantification based on experimental observation using Bayesian theory. Finally it used the method for ranking interval numbers to contrast the posterior probability density of the model response with the prior probability density. The obtained Bayes factor provided a credible result for model validation under epistemic uncertainty. Simulation results show that the presented method is rational. [ABSTRACT FROM AUTHOR]

From the viewpoint of uncertainty propagation, both the seismic fragility function considering aleatory uncertainty and the seismic fragility function considering epistemic uncertainty are derived in analytical forms, and the corresponding parameters are determined. The consistency between the displacement-based function and the earthquake-intensity-based function, which are two categories of commonly used seismic fragility functions considering aleatory uncertainty, is proved. The confidence level of the point estimate function of seismic fragility with consideration of epistemic uncertainty is developed. Based on the equation of seismic risk that is equal to the convolution of seismic fragility and seismic hazard, the derived analytical seismic fragility functions are further extended to the corresponding probabilistic seismic risk functions by adopting a power-law seismic hazard function. Using the derived analytical functions of seismic fragility and seismic risk, the process of seismic fragility and risk evaluations can be simplified, and it is convenient to conduct probabilistic seismic safety assessment for various types of structural systems. [ABSTRACT FROM AUTHOR]