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| 1 | Influence of rock property correlation on reliability analysis of rock slope stability: From property characterization to reliability analysis显示文摘Cohesion(c) and friction angle(φ) of rock are important parameters required for reliability analysis of rock slope stability. There is correlation between c and φ which affects results of reliability analysis of rock slope stability. However, the characterization of joint probability distribution of c and φ through which their correlation can be estimated requires a large amount of rock property data, which are often not available for most rock engineering projects. As a result, the correlation between c and φ is often ignored or simply assumed during reliability studies, which may lead to bias estimation of failure probability. In probabilistic rock slope stability analysis, the influence of ignoring or simply assuming the correlation of the rock strength parameters(i.e., c and φ) on the reliability of rock slopes has not been fully investigated. In this study, a Bayesian approach is developed to characterize the correlation between c and φ, and an expanded reliability-based design(RBD) approach is developed to assess the influence of correlation between c and φ on reliability of a rock slope. The Bayesian approach characterizes the sitespecific joint probability distribution of c and φ, and quantifies the correlation between c and φ using available limited data pairs of c and φ from a rock project. The expanded RBD approach uses the joint probability distribution of c and φ obtained through the Bayesian approach as inputs, to determine the reliability of a rock slope. The approach gives insight into the propagation of the correlation between c and φ through their joint probability into the reliability analysis, and their influence on the calculated reliability of the rock slope. The approaches may be applied in practice with little additional effort from a conventional analysis. The proposed approaches are illustrated using real c and φ data pairs obtained from laboratory tests of fractured rock at Forsmark, Sweden. | Adeyemi Emman Aladejare Yu Wang | 2018 | Geoscience Frontiers2018，9，6： | 5 |
| 2 | Evaluation of empirical estimation of uniaxial compressive strength of rock using measurements from index and physical tests显示文摘The uniaxial compressive strength(UCS) of rock is an important parameter required for design and analysis of rock structures,and rock mass classification.Uniaxial compression test is the direct method to obtain the UCS values.However,these tests are generally tedious,time-consuming,expensive,and sometimes impossible to perform due to difficult rock conditions.Therefore,several empirical equations have been developed to estimate the UCS from results of index and physical tests of rock.Nevertheless,numerous empirical models available in the literature often make it difficult for mining engineers to decide which empirical equation provides the most reliable estimate of UCS.This study evaluates estimation of UCS of rocks from several empirical equations.The study uses data of point load strength(Is(50)),Schmidt rebound hardness(SRH),block punch index(BPI),effective porosity(n) and density(ρ)as inputs to empirically estimate the UCS.The estimated UCS values from empirical equations are compared with experimentally obtained or measured UCS values,using statistical analyses.It shows that the reliability of UCS estimated from empirical equations depends on the quality of data used to develop the equations,type of input data used in the equations,and the quality of input data from index or physical tests.The results show that the point load strength(Is(50)) is the most reliable index for estimating UCS among the five types of tests evaluated.Because of type-specific nature of rock,restricting the use of empirical equations to the similar rock types for which they are developed is one of the measures to ensure satisfactory prediction performance of empirical equations. | Adeyemi Emman Aladejare | 2020 | Journal of Rock Mechanics and Geotechnical Engineering2020，12，2： | 4 |
| 3 | 基于贝叶斯方法的模型选择以及岩石性质概率表征显示文摘岩土工程勘察中,工程师通常从已知岩土性质间接估计岩土的其他性质.例如,工程师会根据岩样的标准点荷载指标(Is(50))间接估计岩石的单轴抗压强度(uniaxial compressive strength,UCS).间接估计时会应用Is(50)和UCS之间的回归模型,然而,现存文献中这种回归模型众多,使得工程师在具体工程应用中难以选择.基于此,阐述了如何通过贝叶斯方法结合Is(50)数据和现场先验信息选择模型,以及选定模型后如何对UCS进行概率表征.所述方法通过工程实例进行了说明.结果显示,所述方法可以单独依据Is(50)数据以及现场先验信息选出合适的模型.且依据所选模型进行UCS的概率表征结果和工程现场情况相吻合. | 赵腾远 ALADEJARE Adeyemi Emman 王宇 | 2016 | 武汉大学学报(工学版)2016，49，5： | 3 |
| 4 | A model for pre- dicting feed intake of growing animals during exposure to pathogens 显示文摘 | SANDBERG F B EMMANS G KYRIAZAKIS I | 2006 | J Anim Sci2006，84，6： | 1 |
| 5 | Growth,body composition and feed intake显示文摘 | Emmans G C | 1986 | World''s Poultry Science Journal1986，43，： | 1 |
| 6 | Describing and predicting potential growth in the pig显示文摘 | Wellock I J Emmans G C Kyriazakis I | 2004 | Animal Science2004，78，： | 1 |
| 7 | The grateful disposition: A conceptual and empirical topography 显示文摘 | McCu//ough ME Emmans RA Tsang J | 2002 | Journal of Personality and Social Psychology2002，82，： | 1 |
| 8 | Problems in modeling the growth of poultry显示文摘 | Emmans G C | 1995 | World''s Poultry Science Journal1995，51，： | 1 |
| 9 | The evaluation of the growth parameters of six strains of commercial broiler chickens 显示文摘 | HANCOCK C E BRADFORD G D EMMANS G C | 1995 | British Poultry Science1995，36，： | 1 |
| 10 | The effect ofbreed on the relationship between food composition and the efficiency of protein utilization in pigs显示文摘 | Kyriazakis I Dotas K Emmans G C | 1994 | British Journal of Nutrition1994，71，： | 1 |
| 11 | A general method for predicting the weight of water in the empty bodies of pigs显示文摘 | Emmans G C Kyriazakis I | 1995 | Animal Science1995，61，： | 1 |
| 12 | A comparative study of geometric and geostatistical methods for qualitative reserve estimation of limestone deposit显示文摘Mining projects especially relating to limestone deposits require an accurate knowledge of tonnage and grade,for both short and long-term planning.This is often difficult to establish as detailed exploration operations,which are required to get the accurate description of the deposit,are costly and time consuming.Geologists and mining engineers usually make use of geometric and geostatistical methods,for estimating the tonnage and grade of ore reserves.However,explicit assessments into the differences between these methods have not been reported in literature.To bridge this research gap,a comparative study is carried out to compare the qualitative reserve of Oyo-Iwa limestone deposit located in Nigeria,using geometric and geostatistical methods.The geometric method computes the reserve of the limestone deposit as 74,536,820 t(mean calcite,CaO grade=52.15)and 99,674,793 t(mean calcite,CaO grade=52.32),for the Northern and Southern zones of the deposit,respectively.On the other hand,the geostatistical method calculates the reserve as 81,626,729.65 t(mean calcite,CaO grade=53.36)and 100,098,697.46 t(mean calcite,CaO grade=52.96),for the two zones,respectively.The small relative difference in tonnage estimation between the two methods(i.e.,9.51%and 0.43%),proves that the geometric method is effective for tonnage estimation.In contrast,the relative difference in grade estimation between the two methods(i.e.,2.32%and 1.26%)is not negligible,and could be crucial in maintaining the profitability of the project.The geostatistical method is,therefore,more suitable,reliable and preferable for grade estimation,since it involves the use of spatial modelling and cross-validated interpolation.In addition,the geostatistical method is used to produce quality maps and three-dimensional(3-D)perspective view of the limestone deposit.The quality maps and 3-D view of the limestone deposit reveal the variability of the limestone grade within the deposit,and it is useful for operational management of the limestone raw materials.The qualitative mapping of the limestone deposit is key to effective production scheduling and accurate projection of raw materials for cement production. | Thomas Busuyi Afeni Victor Oluwatosin Akeju Adeyemi Emman Aladejare | 2021 | Geoscience Frontiers2021，12，1： | 1 |
| 13 | Models of pig growth:problems and proposed solutions显示文摘 | Emmans G C Kyriazakis I | 1997 | Livestock Production Science1997，51，： | 1 |
| 14 | Problems in modelling the growth of poultry显示文摘 | Emmans G C | 1995 | World''s Poult Sci1995，51，： | 1 |
| 15 | The evaluation of the growth parameters of six strains of commercial broiler chickens 显示文摘 | HANCOCK C E BRADFORD G D EMMANS G C | 1995 | British Poultry Science1995，36，2： | 1 |
| 16 | Protein growth in pigs 显示文摘 | Tullis J B Emmans G C | 1988 | Anim Prod1988，46，： | 1 |
| 17 | Models of pig growth: problems and proposed solutions 显示文摘 | Emmans G C Kyriazkis I | 1997 | Livestock Production Science1997，51，： | 1 |
| 18 | Diet selection in pigs:Choices made by growing pigs given foods of different protein concentrations显示文摘 | Kyriazakis I Emmans G C Whittemore C T | 1990 | Anim Prod1990，51，： | 1 |
| 19 | Factors affecting the hatchability of eggs from broiler breeders显示文摘 | Kirk S Emmans G C Mc Donald R | 1987 | British Poult Sci1987，21，： | 1 |
| 20 | Protein growth in pigs 显示文摘 | Whittemore C T Tullis J B Emmans G C | 1988 | Anim Prod1988，46，： | 1 |
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