By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite d...By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite different from each other, resuling in different seismic porosity inversion equations, potentially leading to difficulties in correctly applying them and evaluating their results. In response to this, a uniform relation with two adjusting parameters suitable for all rock skeleton models is established from an analysis and comparison of various conventional rock skeleton models and their expressions including the Eshelby-Walsh, Pride, Geertsma, Nur, Keys-Xu, and Krief models. By giving the two adjusting parameters specific values, different rock skeleton models with specific physical characteristics can be generated. This allows us to select the most appropriate rock skeleton model based on geological and geophysical conditions, and to develop more wise seismic porosity inversion. As an example of using this method for hydrocarbon prediction and fluid identification, we apply this improved porosity inversion, associated with rock physical data and well log data, to the ZJ basin. Research shows that the existence of an abundant hydrocarbon reservoir is dependent on a moderate porosity range, which means we can use the results of seismic porosity inversion to identify oil reservoirs and dry or water-saturated reservoirs. The seismic inversion results are closely correspond to well log porosity curves in the ZJ area, indicating that the uniform relations and inversion methods proposed in this paper are reliable and effective.展开更多
Open pit mining operations utilize large scale and expensive equipment. For the mines implementing shovel and truck operation system, trucks constitute a large portion of these equipment and are used for hauling the m...Open pit mining operations utilize large scale and expensive equipment. For the mines implementing shovel and truck operation system, trucks constitute a large portion of these equipment and are used for hauling the mined materials. In order to have sustainable and viable operation, these equipment need to be utilized efficiently with minimum operating cost. Maintenance cost is a significant proportion of the overall operating costs. The maintenance cost of a truck changes non-linearly depending on the type, age and truck types. A new approach based on stochastic integer programming （SIP） techniques is used for annually scheduling a fixed fleet of mining trucks in a given operation, over the life of mine （multi-year time horizon） to minimize maintenance cost. The maintenance cost data in mining usually has uncertainty caused from the variability of the operational conditions at mines. To estimate the cost, usually historic data from different operations for new mines, and/or the historic data at the operating mines are used. However, maintenance cost varies depending on road conditions, age of equipment and many other local conditions at an operation. Traditional models aim to estimate the maintenance cost as a deterministic single value and financial evaluations are based on the estimated value. However, it does not provide a confidence on the estimate. The proposed model in this study assumes the truck maintenance cost is a stochastic parameter due to the significant level of uncertainty in the data and schedules the available fleet to meet the annual production targets. The scheduling has been performed by applying both the proposed stochastic and deterministic approaches. The approach provides a distribution for the maintenance cost of the optimized equipment schedule minimizing the cost.展开更多
Physiological parameters of people and enact assessment standard of indoor thermal environment that are appropriate to our national conditions were explored from the perspective of physiology. From December 2005 to Ja...Physiological parameters of people and enact assessment standard of indoor thermal environment that are appropriate to our national conditions were explored from the perspective of physiology. From December 2005 to January 2006, nerve conduction velocities and skin temperatures of 20 healthy students were tested with questionnaire investigation. The results show that the nerve conduction velocities as well as skin temperatures present an obvious decline trend in a continuous draught, and that the nerve conduction velocities and skin temperatures have a definite linear relationship. Draught velocity is an important factor in winter that affects body comfort, and the subjects are sensitive to air velocity.展开更多
Quantitatively determining the sources of dune sand is one of the problems necessarily and urgently to be solved in aeolian landforms and desertification research. Based on the granulometric data of sand materials fro...Quantitatively determining the sources of dune sand is one of the problems necessarily and urgently to be solved in aeolian landforms and desertification research. Based on the granulometric data of sand materials from the Hulun Buir Sandy Land, the paper employs the stepwise discriminant analysis technique (SDA) for two groups to select the principal factors determining the differences between surface loose sediments. The extent of similarity between two statistical populations can be described quantitatively by three factors such as the number of principal variables, Mahalanobis distance D 2 and confidence level 琢for F-test. Results reveal that: 1) Aeolian dune sand in the region mainly derives from Hailar Formation (Q 3 ), while fluvial sand and palaeosol also supply partially source sand for dunes; and 2) in the vicinity of Cuogang Town and west of the broad valley of the lower reaches of Hailar River, fluvial sand can naturally become principal supplier for dune sand.展开更多
The mechanical behavior of plastic concrete used in the cut-off walls of earth dams has been studied. Triaxial compression tests on the specimens in various ages and mix designs under different confining pressures hav...The mechanical behavior of plastic concrete used in the cut-off walls of earth dams has been studied. Triaxial compression tests on the specimens in various ages and mix designs under different confining pressures have been done and the stress-strain behavior of such materials and their strength parameter changes have been experimentally investigated. It has been observed that increasing the confining pressures applied on the specimens causes the material behavior to be alike the more ductile materials and the compressive strength increases considerably as well. Moreover, a parametric study has been carded out to investigate the influence of essential parameters on the shear strength parameters of these materials. According to the research, increasing the coarse to fine aggregates ratio leads to the increase of compressive strength of the specimens as well as the increase of the cohesion and internal friction angle of the materials. Furthermore, the bentonite content decrease and the cement factor increase result in an increase of the cohesion parameter of plastic concretes and decrease of the internal friction angle of such materials.展开更多
When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is l...When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is low.To address the problem,an integrated strategy is proposed.It organically combines the fundamental theories of the three mainstream methods(read-pair approaches,split-read technologies and read-depth analysis) with modern machine learning algorithms,using the recipe of feature extraction as a bridge.Compared with the state-of-art split-read methods for deletion detection in both low and high sequence coverage,the machine-learning-aided strategy shows great ability in intelligently balancing sensitivity and false discovery rate and getting a both more sensitive and more precise call set at single-base-pair resolution.Thus,users do not need to rely on former experience to make an unnecessary trade-off beforehand and adjust parameters over and over again any more.It should be noted that modern machine learning models can play an important role in the field of structural variation prediction.展开更多
基金supported by the National Nature Science Foundation of China(Grant No.41174114)Important National Science and Technology Specific Projects(Grant No.2011ZX05025-005-010)
文摘By substituting rock skeleton modulus expressions into Gassmann approximate fluid equation, we obtain a seismic porosity inversion equation. However, conventional rock skeleton models and their expressions are quite different from each other, resuling in different seismic porosity inversion equations, potentially leading to difficulties in correctly applying them and evaluating their results. In response to this, a uniform relation with two adjusting parameters suitable for all rock skeleton models is established from an analysis and comparison of various conventional rock skeleton models and their expressions including the Eshelby-Walsh, Pride, Geertsma, Nur, Keys-Xu, and Krief models. By giving the two adjusting parameters specific values, different rock skeleton models with specific physical characteristics can be generated. This allows us to select the most appropriate rock skeleton model based on geological and geophysical conditions, and to develop more wise seismic porosity inversion. As an example of using this method for hydrocarbon prediction and fluid identification, we apply this improved porosity inversion, associated with rock physical data and well log data, to the ZJ basin. Research shows that the existence of an abundant hydrocarbon reservoir is dependent on a moderate porosity range, which means we can use the results of seismic porosity inversion to identify oil reservoirs and dry or water-saturated reservoirs. The seismic inversion results are closely correspond to well log porosity curves in the ZJ area, indicating that the uniform relations and inversion methods proposed in this paper are reliable and effective.
文摘Open pit mining operations utilize large scale and expensive equipment. For the mines implementing shovel and truck operation system, trucks constitute a large portion of these equipment and are used for hauling the mined materials. In order to have sustainable and viable operation, these equipment need to be utilized efficiently with minimum operating cost. Maintenance cost is a significant proportion of the overall operating costs. The maintenance cost of a truck changes non-linearly depending on the type, age and truck types. A new approach based on stochastic integer programming （SIP） techniques is used for annually scheduling a fixed fleet of mining trucks in a given operation, over the life of mine （multi-year time horizon） to minimize maintenance cost. The maintenance cost data in mining usually has uncertainty caused from the variability of the operational conditions at mines. To estimate the cost, usually historic data from different operations for new mines, and/or the historic data at the operating mines are used. However, maintenance cost varies depending on road conditions, age of equipment and many other local conditions at an operation. Traditional models aim to estimate the maintenance cost as a deterministic single value and financial evaluations are based on the estimated value. However, it does not provide a confidence on the estimate. The proposed model in this study assumes the truck maintenance cost is a stochastic parameter due to the significant level of uncertainty in the data and schedules the available fleet to meet the annual production targets. The scheduling has been performed by applying both the proposed stochastic and deterministic approaches. The approach provides a distribution for the maintenance cost of the optimized equipment schedule minimizing the cost.
基金Project(CSTC 2004AA7008) supported by the State I mportant Project of the Science and Technology
文摘Physiological parameters of people and enact assessment standard of indoor thermal environment that are appropriate to our national conditions were explored from the perspective of physiology. From December 2005 to January 2006, nerve conduction velocities and skin temperatures of 20 healthy students were tested with questionnaire investigation. The results show that the nerve conduction velocities as well as skin temperatures present an obvious decline trend in a continuous draught, and that the nerve conduction velocities and skin temperatures have a definite linear relationship. Draught velocity is an important factor in winter that affects body comfort, and the subjects are sensitive to air velocity.
文摘Quantitatively determining the sources of dune sand is one of the problems necessarily and urgently to be solved in aeolian landforms and desertification research. Based on the granulometric data of sand materials from the Hulun Buir Sandy Land, the paper employs the stepwise discriminant analysis technique (SDA) for two groups to select the principal factors determining the differences between surface loose sediments. The extent of similarity between two statistical populations can be described quantitatively by three factors such as the number of principal variables, Mahalanobis distance D 2 and confidence level 琢for F-test. Results reveal that: 1) Aeolian dune sand in the region mainly derives from Hailar Formation (Q 3 ), while fluvial sand and palaeosol also supply partially source sand for dunes; and 2) in the vicinity of Cuogang Town and west of the broad valley of the lower reaches of Hailar River, fluvial sand can naturally become principal supplier for dune sand.
文摘The mechanical behavior of plastic concrete used in the cut-off walls of earth dams has been studied. Triaxial compression tests on the specimens in various ages and mix designs under different confining pressures have been done and the stress-strain behavior of such materials and their strength parameter changes have been experimentally investigated. It has been observed that increasing the confining pressures applied on the specimens causes the material behavior to be alike the more ductile materials and the compressive strength increases considerably as well. Moreover, a parametric study has been carded out to investigate the influence of essential parameters on the shear strength parameters of these materials. According to the research, increasing the coarse to fine aggregates ratio leads to the increase of compressive strength of the specimens as well as the increase of the cohesion and internal friction angle of the materials. Furthermore, the bentonite content decrease and the cement factor increase result in an increase of the cohesion parameter of plastic concretes and decrease of the internal friction angle of such materials.
基金Project(61472026)supported by the National Natural Science Foundation of ChinaProject(2014J410081)supported by Guangzhou Scientific Research Program,China
文摘When detecting deletions in complex human genomes,split-read approaches using short reads generated with next-generation sequencing still face the challenge that either false discovery rate is high,or sensitivity is low.To address the problem,an integrated strategy is proposed.It organically combines the fundamental theories of the three mainstream methods(read-pair approaches,split-read technologies and read-depth analysis) with modern machine learning algorithms,using the recipe of feature extraction as a bridge.Compared with the state-of-art split-read methods for deletion detection in both low and high sequence coverage,the machine-learning-aided strategy shows great ability in intelligently balancing sensitivity and false discovery rate and getting a both more sensitive and more precise call set at single-base-pair resolution.Thus,users do not need to rely on former experience to make an unnecessary trade-off beforehand and adjust parameters over and over again any more.It should be noted that modern machine learning models can play an important role in the field of structural variation prediction.
