• 제목/요약/키워드: Available Capacity

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Pseudostatic analysis of bearing capacity of embedded strip footings in rock masses using the upper bound method

  • Saeed Shamloo;Meysam Imani
    • Geomechanics and Engineering
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    • v.34 no.4
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    • pp.381-396
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    • 2023
  • The present paper evaluates seismic bearing capacity of rock masses subjected to loads of strip footings using the upper bound method. A general formula was proposed to evaluate the seismic bearing capacity considering both the horizontal and vertical accelerations of the earthquake and the effects of footing embedment depth simultaneously. Modified Hoek-Brown failure criterion was employed for the rock mass. Some comparisons were made with the available solutions and the finite element numerical models to show the accuracy of the developed upper bound formulations. The obtained results show significant improvement compared to the other available solutions. By increasing the horizontal earthquake acceleration from 0.1 to 0.3, the bearing capacity was reduced by up to 39%, while the effect of the vertical earthquake acceleration depends on its direction. An upward acceleration in the range of zero to 0.2 results in an increase in the bearing capacity by up to 24%, while the downward earthquake acceleration has an adverse effect. Also, by increasing the embedment depth of the footing from zero to 5 times the footing width, the value of seismic bearing capacity was raised about 86%. The obtained results were presented as design tables for use in practical applications.

Decision of Available Soil Depth Based on Physical and Hydraulic Properties of Soils for Landscape Vegetation in Incheon International Airport

  • Jung, Yeong-Sang;Lee, Hyun-Il;Jung, Mun-Ho;Lee, Jeong-Ho;Kim, Jeong-Tae;Yang, Jae E
    • Korean Journal of Soil Science and Fertilizer
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    • v.48 no.5
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    • pp.522-527
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    • 2015
  • Decision of available soil depth based on soil physical and hydraulic properties for the $3^{rd}$ Landscape Vegetation Project in the Incheon International Airport was attempted. The soil samples were collected from the 8 sites at different depths, 0-20 and 20-60cm, for the three project fields, A, B, and C area. Physical and chemical properties including particle size distribution, organic matter content and electrical conductivity were analyzed. Hydrological properties including bulk density and water holding capacity at different water potential, -6 kPa, -10 kPa, -33 kPa, and -1500 kPa were calculated by SPAW model of Saxton and Rawls (2006), and air entry value was calculated by Campbell model (1985). Based on physical and hydrological limitation, feasibility and design criteria of soil depth for vegetation and landfill were recommended. Since the soil salinity of the soil in area A area was $19.18dS\;m^{-1}$ in top soil and $22.27dS\;m^{-1}$ in deep soil, respectively, landscape vegetation without amendment would not be possible on this area. Available soil depth required for vegetation was 2.51 m that would secure root zone water holding capacity, capillary fringe, and porosity. Available soil depth required for landscape vegetation of the B area soil was 1.51 m including capillary fringe 0.14 m and available depth for 10% porosity 1.35 m. The soils in this area were feasible for landscape vegetation. The soil in area C was feasible for bottom fill purpose only due to low water holding capacity.

GS-MARS method for predicting the ultimate load-carrying capacity of rectangular CFST columns under eccentric loading

  • Luat, Nguyen-Vu;Lee, Jaehong;Lee, Do Hyung;Lee, Kihak
    • Computers and Concrete
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    • v.25 no.1
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    • pp.1-14
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    • 2020
  • This study presents applications of the multivariate adaptive regression splines (MARS) method for predicting the ultimate loading carrying capacity (Nu) of rectangular concrete-filled steel tubular (CFST) columns subjected to eccentric loading. A database containing 141 experimental data was collected from available literature to develop the MARS model with a total of seven variables that covered various geometrical and material properties including the width of rectangular steel tube (B), the depth of rectangular steel tube (H), the wall thickness of steel tube (t), the length of column (L), cylinder compressive strength of concrete (f'c), yield strength of steel (fy), and the load eccentricity (e). The proposed model is a combination of the MARS algorithm and the grid search cross-validation technique (abbreviated here as GS-MARS) in order to determine MARS' parameters. A new explicit formulation was derived from MARS for the mentioned input variables. The GS-MARS estimation accuracy was compared with four available mathematical methods presented in the current design codes, including AISC, ACI-318, AS, and Eurocode 4. The results in terms of criteria indices indicated that the MARS model was much better than the available formulae.

Load carrying capacity of deteriorated reinforced concrete columns

  • Tapan, Mucip;Aboutaha, Riyad S.
    • Computers and Concrete
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    • v.6 no.6
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    • pp.473-490
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    • 2009
  • This paper presents a new methodology to evaluate the load carrying capacity of deteriorated non-slender concrete bridge pier columns by construction of the full P-M interaction diagrams. The proposed method incorporates the actual material properties of deteriorated columns, and accounts for amount of corrosion and exposed corroded bar length, concrete loss, loss of concrete confinement and strength due to stirrup deterioration, bond failure, and type of stresses in the corroded reinforcement. The developed structural model and the damaged material models are integrated in a spreadsheet for evaluating the load carrying capacity for different deterioration stages and/or corrosion amounts. Available experimental and analytical data for the effects of corrosion on short columns subject to axial loads combined with moments (eccentricity induced) are used to verify the accuracy of proposed model. It was observed that, for the limited available experimental data, the proposed model is conservative and is capable of predicting the load carrying capacity of deteriorated reinforced concrete columns with reasonable accuracy. The proposed analytical method will improve the understanding of effects of deterioration on structural members, and allow engineers to qualitatively assess load carrying capacity of deteriorated reinforced concrete bridge pier columns.

Incorporating Resource Dynamics to Determine Generation Adequacy Levels in Restructured Bulk Power Systems

  • Felder, Frank A.
    • KIEE International Transactions on Power Engineering
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    • v.4A no.2
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    • pp.100-105
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    • 2004
  • Installed capacity markets in the northeast of the United States ensure that adequate generation exists to satisfy regional loss of load probability (LOLP) criterion. LOLP studies are conducted to determine the amount of capacity that is needed, but they do not consider several factors that substantially affect the calculated distribution of available capacity. These studies do not account for the fact that generation availability increases during periods of high demand and therefore prices, common-cause failures that result in multiple generation units being unavailable at the same time, and the negative correlation between load and available capacity due to temperature and humidity. A categorization of incidents in an existing bulk power reliability database is proposed to analyze the existence and frequency of independent failures and those associated with resource dynamics. Findings are augmented with other empirical findings. Monte Carlo methods are proposed to model these resource dynamics. Using the IEEE Reliability Test System as a single-bus case study, the LOLP results change substantially when these factors are considered. Better data collection is necessary to support the more comprehensive modeling of resource adequacy that is proposed. In addition, a parallel processing method is used to offset the increase in computational times required to model these dynamics.

Reliability analysis of piles based on proof vertical static load test

  • Dong, Xiaole;Tan, Xiaohui;Lin, Xin;Zhang, Xuejuan;Hou, Xiaoliang;Wu, Daoxiang
    • Geomechanics and Engineering
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    • v.29 no.5
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    • pp.487-496
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    • 2022
  • Most of the pile's vertical static load tests in construction sites are the proof load tests, which is difficult to accurately estimate the ultimate bearing capacity and analyze the reliability of piles. Therefore, a reliability analysis method based on the proof load-settlement (Q-s) data is proposed in this study. In this proposed method, a simple ultimate limit state function based on the hyperbolic model is established, where the random variables of reliability analysis include the model factor of the ultimate bearing capacity and the fitting parameters of the hyperbolic model. The model factor M = RuR / RuP is calculated based on the available destructive Q-s data, where the real value of the ultimate bearing capacity (RuR) is obtained by the complete destructive Q-s data; the predicted value of the ultimate bearing capacity (RuP) is obtained by the proof Q-s data, a part of the available destructive Q-s data, that before the predetermined load determined by the pile test report. The results demonstrate that the proposed method can easy and effectively perform the reliability analysis based on the proof Q-s data.

Prediction of the shear capacity of reinforced concrete slender beams without stirrups by applying artificial intelligence algorithms in a big database of beams generated by 3D nonlinear finite element analysis

  • Markou, George;Bakas, Nikolaos P.
    • Computers and Concrete
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    • v.28 no.6
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    • pp.533-547
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    • 2021
  • Calculating the shear capacity of slender reinforced concrete beams without shear reinforcement was the subject of numerous studies, where the eternal problem of developing a single relationship that will be able to predict the expected shear capacity is still present. Using experimental results to extrapolate formulae was so far the main approach for solving this problem, whereas in the last two decades different research studies attempted to use artificial intelligence algorithms and available data sets of experimentally tested beams to develop new models that would demonstrate improved prediction capabilities. Given the limited number of available experimental databases, these studies were numerically restrained, unable to holistically address this problem. In this manuscript, a new approach is proposed where a numerically generated database is used to train machine-learning algorithms and develop an improved model for predicting the shear capacity of slender concrete beams reinforced only with longitudinal rebars. Finally, the proposed predictive model was validated through the use of an available ACI database that was developed by using experimental results on physical reinforced concrete beam specimens without shear and compressive reinforcement. For the first time, a numerically generated database was used to train a model for computing the shear capacity of slender concrete beams without stirrups and was found to have improved predictive abilities compared to the corresponding ACI equations. According to the analysis performed in this research work, it is deemed necessary to further enrich the current numerically generated database with additional data to further improve the dataset used for training and extrapolation. Finally, future research work foresees the study of beams with stirrups and deep beams for the development of improved predictive models.

An Experimental Study on the Increase of the Bearing Capacity on Sandy Ground due to Micropile Reinforcement (마이크로파일로 보강된 모래지반의 지지력 증가효과에 관한 실험적 연구)

  • 김정동;임종철;이태형
    • Proceedings of the Korean Geotechical Society Conference
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    • 2003.03a
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    • pp.411-416
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    • 2003
  • As rapid industrialization continues in these days, construction in the down town areas increases. Since constructions are performed around old and existing structures, the need to provide reinforcements to protect the existing structures from collapse and damage arises. Furthermore, if the construction is to take place in the down town area, difficult work space and damage caused by noise, vibration and collapse of structure can't be ignored. Among the remedial measures available today, micropile reinforcement is considered the best method to remedy these problems. But up to the present the characteristics of micropiles and ground behaviour has not been proven and no standard design is not yet available. Therefore, most design are performed based on previous experiences. In this study, the difference in the bearing capacity with changing reinforcement angle, space and sphere around foundation was monitored. These results were induced to broaden heighten the limits of micropile application.

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A Study on the Optimum Allocation Model for Inventory Capacity (재고설비규모를 위한 최적분배 모델의 연구)

  • 최진영;정기호
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.5 no.6
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    • pp.1-6
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    • 1982
  • The objective of this thesis to Provide a better insight into the effect of the amount of in-process storage has on the efficiency of production line with variable operation times. It is assumed that the material enters the line at the first work station and is then processed progressively through the line until it exits at the last work station, a finite amount of in-process storage is provided before all but the first work station of the line and the operation time of the work stations are statistically independent and follow exponential distribution. Under the above assumption, optimum allocation model is developed and following two approaches are used : 1) Given the available storage capacity, optimum allocation which minimizes the number of items in the line. 2) Given the available storage capacity, optimum allocation which. maximizes the utilization factor of the line. In a balanced three stage line, the production line efficiency is maximized under both categories when the second in-process storage is larger than the first.

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Predicting the shear strength of reinforced concrete beams using Artificial Neural Networks

  • Asteris, Panagiotis G.;Armaghani, Danial J.;Hatzigeorgiou, George D.;Karayannis, Chris G.;Pilakoutas, Kypros
    • Computers and Concrete
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    • v.24 no.5
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    • pp.469-488
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    • 2019
  • In this research study, the artificial neural networks approach is used to estimate the ultimate shear capacity of reinforced concrete beams with transverse reinforcement. More specifically, surrogate approaches, such as artificial neural network models, have been examined for predicting the shear capacity of concrete beams, based on experimental test results available in the pertinent literature. The comparison of the predicted values with the corresponding experimental ones, as well as with available formulas from previous research studies or code provisions highlight the ability of artificial neural networks to evaluate the shear capacity of reinforced concrete beams in a trustworthy and effective manner. Furthermore, for the first time, the (quantitative) values of weights for the proposed neural network model, are provided, so that the proposed model can be readily implemented in a spreadsheet and accessible to everyone interested in the procedure of simulation.