Estimation of Standard Operation Time of Flight Legs Based on Clustering and Probability Analysis

A clustering algorithm and a probability statistics method were applied to different phases of a flight to analyze operation time during aircraft ground taxiing and airborne flight.And the clustering pattern,distribution characteristics and dynamically changing rules of the two phases were identified.Further,an estimate method was established to measure operation time of flight legs,with creative steps of calculating individual segment separately and then integrating them accordingly.The method can both objectively and dynamically measure operation time,and accurately reflect real situation.It helps to better utilize airport slot resources and provides a strong support for air traffic flow management when scheduling flight plan in strategic and pre-tactic phases.

Crack simulation and probability analysis using irregular truss structure modeling equivalent to a continuum structure

The problems related to agricultural structure engineering for crack simulation and reliability analysis are complicated because its variables contain wide ranges of mean and standard deviation.This paper describes an integrated model to perform crack simulation and reliability analysis of a continuum structure.The structure is assumed to be under a two-dimensional plane stress and the deformation is infinitesimal.A truss structure model that has the same behaviour as a continuum structure was developed using irregular triangle truss components where each element consists of two hinges with an axial degree of freedom at both of their ends.A Monte-Carlo simulation(MCS)was adopted for the reliability analysis.If the length of one side of the irregular triangle mesh is shorter than the thickness of the structure,the slenderness associated with compressive failure needs to be examined only for the short column.For that reason,the failure criterion suitable for the equivalent truss structure model was established by checking only axial stresses acting on truss members.Since nodes of the equivalent truss structure model for the structural analysis in this study consist of hinges,development of plastic hinges that occurred during crack propagation were not considered in this model.To simulate the development of crack,truss members over allowable stresses of tension or compression among truss members with the largest amount of stress at each completed structural analysis time step were sequentially removed.Since irregular triangle meshes have an uncertainty in themselves to compare with regular meshes,the equivalent truss structure model could describe crack propagation more realistically.The failure probabilities of structures under various loads and boundary conditions had good agreement with the analytical solutions directly solved from the limit state equations expressed in the form of moments.

Kernel Generalization of Multi-Rate Probabilistic Principal Component Analysis for Fault Detection in Nonlinear Process

In practical process industries,a variety of online and offline sensors and measuring instruments have been used for process control and monitoring purposes,which indicates that the measurements coming from different sources are collected at different sampling rates.To build a complete process monitoring strategy,all these multi-rate measurements should be considered for data-based modeling and monitoring.In this paper,a novel kernel multi-rate probabilistic principal component analysis(K-MPPCA)model is proposed to extract the nonlinear correlations among different sampling rates.In the proposed model,the model parameters are calibrated using the kernel trick and the expectation-maximum(EM)algorithm.Also,the corresponding fault detection methods based on the nonlinear features are developed.Finally,a simulated nonlinear case and an actual pre-decarburization unit in the ammonia synthesis process are tested to demonstrate the efficiency of the proposed method.

Determination and stability analysis of ultimate open-pit slope under geomechanical uncertainty

In open-pit mines,pit slope as one of the important parameters affects the mine economy and total minable reserve,and it is also affected by different uncertainties which arising from many sources.One of the most critical sources of uncertainty effects on the pit slope design is rock mass geomechanical properties.By comparing the probability of failure resulted from deterministic procedure and probabilistic one,this paper investigated the effects of aforesaid uncertainties on open-pit slope stability in metal mines.In this way,to reduce the effect of variance,it implemented Latin Hypercube Sampling(LHS)technique.Furthermore,a hypothesis test was exerted to compare the effects on two cases in Middle East.Subsequently,the investigation approved high influence of geomechanical uncertainties on overall pit steepness and stability in both iron and copper mines,though on the first case the effects were just over.

Wave Energy Estimation by Using A Statistical Analysis and Wave Buoy Data near the Southern Caspian Sea

Statistical analysis was done on simultaneous wave and wind using data recorded by discus-shape wave buoy. The area is located in the southern Caspian Sea near the Anzali Port. Recorded wave data were obtained through directional spectrum wave analysis. Recorded wind direction and wind speed were obtained through the related time series as well. For 12-month measurements（May 25 2007-2008）, statistical calculations were done to specify the value of nonlinear auto-correlation of wave and wind using the probability distribution function of wave characteristics and statistical analysis in various time periods. The paper also presents and analyzes the amount of wave energy for the area mentioned on the basis of available database. Analyses showed a suitable comparison between the amounts of wave energy in different seasons. As a result, the best period for the largest amount of wave energy was known. Results showed that in the research period, the mean wave and wind auto correlation were about three hours. Among the probability distribution functions, i.e Weibull, Normal, Lognormal and Rayleigh, ＂Weibull＂ had the best consistency with experimental distribution function shown in different diagrams for each season. Results also showed that the mean wave energy in the research period was about 49.88 k W/m and the maximum density of wave energy was found in February and March, 2010.

A 249-Year Record of Floods at Appleby in Westmorland, UK

An analysis of nearly 250 years of flood records on the river Eden at Appleby-in-Westmorland has enabled a flood frequency relationship to be established. The most severe floods were in the late 18th and early 19th century. With such a long history of flooding, some remedial measures would have been expected but the local people have, to some extent, adapted to the flood hazard by means of temporary and permanent flood proofing methods such as a cemented board across a doorway and removable flood boards. These measures were overwhelmed during the 2015 flood, as were the flood gates installed by the Environment Agency in 1998. A higher level of protection from floods at Appleby is called for.

Sensitivity Study on Durability Variables of Marine Concrete Structures

In order to study the influence of parameters on durability of marine concrete structures, the parameter＇s sensitivity analysis was studied in this paper. With the Fick＇s 2nd law of diffusion and the deterministic sensitivity analysis method （DSA）, the sensitivity factors of apparent surface chloride content, apparent chloride diffusion coefficient and its time dependent attenuation factor were analyzed. The results of the analysis show that the impact of design variables on concrete durability was different. The values of sensitivity factor of chloride diffusion coefficient and its time dependent attenuation factor were higher than others. Relative less error in chloride diffusion coefficient and its time dependent attenuation coefficient induces a bigger error in concrete durability design and life prediction. According to probability sensitivity analysis （PSA）, the influence of mean value and variance of concrete durability design variables on the durability failure probability was studied. The results of the study provide quantitative measures of the importance of concrete durability design and life prediction variables. It was concluded that the chloride diffusion coefficient and its time dependent attenuation factor have more influence on the reliability of marine concrete structural durability. In durability design and life prediction of marine concrete structures, it was very important to reduce the measure and statistic error of durability design variables.

On the non-Gaussian errors in high-z supernovae type Ia data

The nature of random errors in any data set is Gaussian, which is a well established fact according to the Central Limit Theorem. Supernovae type Ia data have played a crucial role in major discoveries in cosmology. Unlike in laboratory experiments, astronomical measurements cannot be performed in controlled situations. Thus, errors in astronomical data can be more severe in terms of systematics and non-Gaussianity compared to those of laboratory experiments. In this paper, we use the Kolmogorov-Smiruov statistic to test non-Gaussianity in high-z supernovae data. We apply this statistic to four data sets, i.e., Gold data （2004）, Gold data （2007）, the Union2 catalog and the Union2.1 data set for our analysis. Our results show that in all four data sets the errors are consistent with a Gaussian distribution.

Regional moment-independent sensitivity analysis with its applications in engineering

Traditional Global Sensitivity Analysis（GSA） focuses on ranking inputs according to their contributions to the output uncertainty.However,information about how the specific regions inside an input affect the output is beyond the traditional GSA techniques.To fully address this issue,in this work,two regional moment-independent importance measures,Regional Importance Measure based on Probability Density Function（RIMPDF） and Regional Importance Measure based on Cumulative Distribution Function（RIMCDF）,are introduced to find out the contributions of specific regions of an input to the whole output distribution.The two regional importance measures prove to be reasonable supplements of the traditional GSA techniques.The ideas of RIMPDF and RIMCDF are applied in two engineering examples to demonstrate that the regional moment-independent importance analysis can add more information concerning the contributions of model inputs.

Theoretical analysis of non-probabilistic reliability based on interval model

The aim of this paper is to propose a theoretical approach for performing the nonprobabilistic reliability analysis of structure.Due to a great deal of uncertainties and limited measured data in engineering practice,the structural uncertain parameters were described as interval variables.The theoretical analysis model was developed by starting from the 2-D plane and 3-D space.In order to avoid the loss of probable failure points,the 2-D plane and 3-D space were respectively divided into two parts and three parts for further analysis.The study pointed out that the probable failure points only existed among extreme points and root points of the limit state function.Furthermore,the low-dimensional analytical scheme was extended to the high-dimensional case.Using the proposed approach,it is easy to find the most probable failure point and to acquire the reliability index through simple comparison directly.A number of equations used for calculating the extreme points and root points were also evaluated.This result was useful to avoid the loss of probable failure points and meaningful for optimizing searches in the research field.Finally,two kinds of examples were presented and compared with the existing computation.The good agreements show that the proposed theoretical analysis approach in the paper is correct.The efforts were conducted to improve the optimization method,to indicate the search direction and path,and to avoid only searching the local optimal solution which would result in missed probable failure points.

Reliability analysis based on a novel density estimation method for structures with correlations

Estimating the Probability Density Function（PDF） of the performance function is a direct way for structural reliability analysis,and the failure probability can be easily obtained by integration in the failure domain.However,efficiently estimating the PDF is still an urgent problem to be solved.The existing fractional moment based maximum entropy has provided a very advanced method for the PDF estimation,whereas the main shortcoming is that it limits the application of the reliability analysis method only to structures with independent inputs.While in fact,structures with correlated inputs always exist in engineering,thus this paper improves the maximum entropy method,and applies the Unscented Transformation（UT） technique to compute the fractional moments of the performance function for structures with correlations,which is a very efficient moment estimation method for models with any inputs.The proposed method can precisely estimate the probability distributions of performance functions for structures with correlations.Besides,the number of function evaluations of the proposed method in reliability analysis,which is determined by UT,is really small.Several examples are employed to illustrate the accuracy and advantages of the proposed method.

Cost reduction of a hybrid energy storage system considering correlation between wind and PV power

A hybrid energy storage system(HESS)plays an important role in balancing the cost with the performance in terms of stabilizing the fluctuant power of wind farms and photovoltaic(PV)stations.To further bring down the cost and actually implement the dispatchability of wind/PV plants,there is a need to penetrate into the major factors that contribute to the cost of the any HESS.This paper first discusses hybrid energy storage systems,as well as chemical properties in different medium,deeming the ramp rate as one of the determinants that must be observed in the cost calculation.Then,a mathematical tool,Copula,is explained in details for the purpose of unscrambling the dependences between the power of wind and PV plants.To lower the cost,the basic rule for allocation of buffered power is also put forward,with the minimum energy capacities of the battery ESS(BESS)and the supercapacitor ESS(SC-ESS)simultaneously determined by integration.And the paper introduces the probability method to analyze how power and energy is compensated in certain confidence level.After that,two definitions of coefficients are set up,separately describing energy storage status and wind curtailment level.Finally,the paper gives a numerical example stemmed from real data acquired in wind farms and PV stations in Belgium.The conclusion presents that the cost of a hybrid energy storage system is greatly affected by ramp-rate and dependence between the power of wind farms and photovoltaic stations,in which dependence can easily be determined by Copulas.

PARAMETRIC AND NON-PARAMETRIC COMBINATION MODEL TO ENHANCE OVERALL PERFORMANCE ON DEFAULT PREDICTION

The probability of default(PD) is the key element in the New Basel Capital Accord and the most essential factor to financial institutions' risk management.To obtain good PD estimation,practitioners and academics have put forward numerous default prediction models.However,how to use multiple models to enhance overall performance on default prediction remains untouched.In this paper,a parametric and non-parametric combination model is proposed.Firstly,binary logistic regression model(BLRM),support vector machine(SVM),and decision tree(DT) are used respectively to establish models with relatively stable and high performance.Secondly,in order to make further improvement to the overall performance,a combination model using the method of multiple discriminant analysis(MDA) is constructed.In this way,the coverage rate of the combination model is greatly improved,and the risk of miscarriage is effectively reduced.Lastly,the results of the combination model are analyzed by using the K-means clustering,and the clustering distribution is consistent with a normal distribution.The results show that the combination model based on parametric and non-parametric can effectively enhance the overall performance on default prediction.

Characterization of the genes involved in nitrogen cycling in wastewater treatment plants using DNA microarray and most probable number-PCR

To improve nitrogen removal performance of wastewater treatment plants （WWTPs）, it is essential to understand the behavior of nitrogen cycling communities, which comprise various microorganisms. This study characterized the quantity and diversity of nitrogen cycling genes in various processes of municipal WWTPs by employing two molecular-based methods：most probable number-polymerase chain reaction （MPN-PCR） and DNA microarray. MPN-PCR analysis revealed that gene quantities were not statistically different among processes, suggesting that conventional actwated sludge processes （CAS） are similar to nitrogen removal processes in their ability to retain an adequate population of nitrogen cycling microorganisms. Furthermore, most processes in the WWTPs that were researched shared a pattern：the nitS and the bacterial amoA genes were more abundant than the nirK and archaeal amoA genes, respectivelv. DNA microarray analysis revealed that several kinds of nitrification and denitrification genes were detected in both CAS and anaerobic-oxic processes （AO）, whereas limited genes were detected in nitrogen removal processes. Results of this study suggest that CAS maintains a diverse community of nitrogen cycling microorganisms; moreover, the microbial communities in nitrogen removal processes may be specific.