Fatigue Life Prediction of Horizontal Press Frame Based on Statistical Probability and Its Redesign

Horizontal press as an important part of hydro-forming machine is used to output the horizontal force to keep the high internal pressure during tube hydro-forming. However,the horizontal press frame is usually mounted on the press bed and not pre-stressed. Meanwhile it will be subjected to the reaction force caused by liquid pressure. Stresses are concentrated severely on the assemble region due to deformation,and total fatigue life will decrease. In order to predict the total fatigue life of the frame,the simulations are used firstly to determine to stress concentration region,and then strain gauge measurements are carried out under different loads. Next,the methods of statistical probability are conducted to calculate the fatigue life based on long-term load history. Finally a structure with the considerable longer fatigue life is redesigned.

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.

The Grade-Tonnage Model for China's Molybdenum Deposits

The authors have studied the statistical characteristics of China＇s molybdenum deposits to establish the grade-tonnage model based on the data updated to the end of 2010. The results showed that each type of China＇s molybdenum deposits complied with Lasky＇s law approximately and the characteristics of grade-tonnage model obey the lognormal distribution. However, there are poor correlations between grade and tonnage respectively. Ultimately, we aimed to fit the grade-tonnage model through the known distribution function, draw the cumulative probability curves, and evaluated undiscovered mineral resources of China＇s molybdenum deposits by means of Monte Carlo simulation integrated in MRAS.

Theoretical Study on Stochastic Modeling of Combined Gravity-Magnetic-Electric-Seismic Inversion and Its Application

As gravity field, magnetic field, electric field and seismic wave field are all physical fields, their object function, reverse function and compound function are certainly infinite continuously differentiable functions which can be expanded into Taylor (Fourier) series within domain of definition and be further reduced into solving stochastic distribution function of series and statistic inference of optimal approximation. This is the basis of combined gravity-magnetic-electric-seismic inversion of stochastic modeling. It is an uncertainty modeling technology of combining gravity-magnetic-electric-seismic inversion built on the basis of separation of field and source gravity-magnetic difference-value (D-value) trend surface, taking distribution-independent fault system as its unit, depths of seismic and electric interfaces of interests as its corresponding bivariate compound reverse function of gravity-magnetic anomalies and using high order polynomial (high order trigonometric function) approximating to its series distribution. The difference from current dominant inversion techniques is that, first, it does not respectively create gravity-seismic, magnetic-seismic deterministic inversion model from theoretical model, but combines gravity-magnetic-electric-seismic stochastic inversion model from stochastic model; second, after the concept of equivalent geological body being introduced, using feature of independent variable of gravity-magnetic field functions, taking density and susceptibility related to gravity-magnetic function as default parameters of model, the deterministic model is established owing to better solution to the contradiction of difficulty in identifying strata and less test analytical data for density and susceptibility in newly explored area; third, under assumption of independent parent distribution, a real modeling by strata, the problem of difficult plane closure arising in profile modeling is avoided. This technology has richer and more detailed fault and strata information than sparse pattern seismic data in newly explored area, successfully inverses and plots structural map of Indosinian discontinuity in Hefei basin with combined gravity-magnetic-electric-seismic inversion. With development of high precision gravity-magnetic and overall geophysical technology, it is certain for introducing new methods of stochastic modeling and computational intelligence and promoting the development of combined gravity-magnetic-electric-seismic inversion to open a new substantial path.

ON DESIGN METHOD OF THE PRECISION CAM PROFILE WITH RANDOM PROCESSING ERRORS

Based on probability and statistic, a design method of precision cam profileconcerning the influence of random processing errors is advanced. Combining the design with theprocess, which can be used to predict that cam profiles will be successfully processed or not in thedesign stage, design of the cam can be done by balancing the economization and reliability. Inaddition, an fuzzy deduction method based on Bayers formula is advanced to estimate processingreasonable of the designed precision cam profile, and it take few samples.

Quantifying Likelihood in Digital Forensic Investigations

While the conventional forensic scientists routinely validate and express the results of their investigations quantitatively using statistical measures from probability theory,digital forensics examiners rarely if ever do so.In this paper,we review some of the quantitative tools and techniques which are available for use in digital forensic investigations,including Bayesian networks,complexity theory,information theory and probability theory,and indicate how they may be used to obtain likelihood ratios or odds ratios for the relative plausibility of alternative explanations for the creation of the recovered digital evidence.The potential benefits of such quantitative measures for modern digital forensics are also outlined.

Applications of probability and statistics in cancer genomics

Background:The past decade has witnessed a rapid progress in our understanding of the genetics of cancer and its progression.Probabilistic and statistical modeling played a pivotal role in the discovery of general patterns from cancer genomics datasets and continue to be of central importance for personalized medicine.Results:In this review we introduce cancer genomics from a probabilistic and statistical perspective.We start from(1)functional classification of genes into oncogenes and tumor suppressor genes,then(2)demonstrate the importance of comprehensive analysis of different mutation types for individual cancer genomes,followed by(3)tumor purity analysis,which in turn leads to(4)the concept of ploidy and clonality,that is next connected to(5)tumor evolution under treatment pressure,which yields insights into cancer drug resistance.We also discuss future challenges including the non-coding genomic regions,integrative analysis of genomics and epigenomics,as well as early cancer detection.Conclusion:We believe probabilistic and statistical modeling will continue to play important roles for novel discoveries in the field o f cancer genomics and personalized medicine.

Robust and Efficient Reliability Estimation for Exponential Distribution

In modeling reliability data,the exponential distribution is commonly used due to its simplicity.For estimating the parameter of the exponential distribution,classical estimators including maximum likelihood estimator represent the most commonly used method and are well known to be efficient.However,the maximum likelihood estimator is highly sensitive in the presence of contamination or outliers.In this study,a robust and efficient estimator of the exponential distribution parameter was proposed based on the probability integral transform statistic.To examine the robustness of this new estimator,asymptotic variance,breakdown point,and gross error sensitivity were derived.This new estimator offers reasonable protection against outliers besides being simple to compute.Furthermore,a simulation study was conducted to compare the performance of this new estimator with the maximum likelihood estimator,weighted likelihood estimator,and M-scale estimator in the presence of outliers.Finally,a statistical analysis of three reliability data sets was conducted to demonstrate the performance of the proposed estimator.

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.

Methods for Controlling the Authenticity of Textual Information Transfer on the Basis of Statistical and Structural Redundancy

In this paper,the problem of increasing information transfer authenticity is formulated.And to reach a decision,the control methods and algorithms based on the use of statistical and structural information redundancy are presented.It is assumed that the controllable information is submitted as the text element images and it contains redundancy,caused by statistical relations and non-uniformity probability distribution of the transmitted data.The use of statistical redundancy allows to develop the adaptive rules of the authenticity control which take into account non-stationarity properties of image data while transferring the information.The structural redundancy peculiar to the container of image in a data transfer package is used for developing new rules to control the information authenticity on the basis of pattern recognition mechanisms.The techniques offered in this work are used to estimate the authenticity in structure of data transfer packages.The results of comparative analysis for developed methods and algorithms show that their parameters of efficiency are increased by criterion of probability of undetected mistakes,labour input and cost of realization.

Vertical temperature gradients of concrete box girder caused by solar radiation in Sichuan-Tibet railway

Spatial and temporal temperature variations are critical for concrete box girders,and non-uniform temperature distributions induced by solar radiation depend on the structural shapes and shadows cast on them.There have been many studies of temperature distributions and temperature gradients of concrete box girders,but few have considered a high altitude plateau climatic environment.In this study,the nonlinear temperature distributions of concrete box girders in the Sichuan-Tibet railway caused by solar radiation were investigated based on experimental analysis,real-time shadow-selection algorithm,and finite element method.Furthermore,a vertical temperature gradient model of the concrete box girders was obtained.The vertical temperature gradient values first rise,then decrease,and finally rise again from Chengdu to Lhasa,with samples forming a normal distribution.The recommended vertical temperature gradient value was 25℃with a confidence interval of 95%.This provides a reference for the design and maintenance of concrete box girders on the Sichuan-Tibet railway.