Browsing by Author "Kabani, Matongo"

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    The behaviour of curved hybrid girders
    (2008) Kabani, Matongo; Masarira, Alvin
    Curved girders are used in bridges to fit predefined alignment. Hybrid girders are an innovative use of high strength steel enabling optimising moment capacity. Previous studies of curvature and hybrid girder effects have been disjointed, focusing on curved homogeneous girders and straight hybrid girders. There are no generally accepted curved girder equations and this has implications in the study of curved hybrid girders since the hybrid effects become apparent in the inelastic range. Furthermore, the range of radius to span ratio where available analytical procedures can be applied is not known. A total of 48 girders are investigated, 12 of which are straight. The girders are all simply supported, un-braced and loaded at midspan. The load-deflection behaviour of curved hybrid girders is investigated. Stress plots of the girders are obtained at ultimate load. The radius to span ratio is varied from 5 to 50 for 5m span girders and from 5 to 30 for 8m span girders. Three steel grades are used to obtain hybrid girder configurations, with higher yield steel always used in the flanges. The web-flange yield steel combinations used are 350MPa/460MPa, 350MPa/690MPa and 460MPa/ 690MPa. A finite element model using ADINA version 8.4 is used to investigate curved girder behaviour. The collapse analysis option is used to trace behaviour as the load is incremented automatically to a prescribed displacement. Available experimental data is used to check the validity of the modeling assumptions. The presence of curvature radically modifies a girder's load pattern by causing additional lateral bending moments. Lateral bending moments reduce the vertical load carrying capacity of a girder and cause the flanges to be unequally stressed. For the girder and spans investigated, there is a reduction of 57% in ultimate load for radius to span ratio (R/L) of 5 compared to a straight girder of similar proportions and span. The effects of curvature reduce as R/L increases and this is observed in the 5m homogeneous girder with R/L of 50 which attained more than 91% of the straight girder load capacity. The 8m girder with R/1 of 30 attained more than 83% of the equivalent straight load girder capacity. The hybrid girders investigated had load-deflection curves close to corresponding homogeneous girders with flange steel grade, reaching more than 97% of the ultimate load capacity of reference homogeneous girders. The hybrid factors as proposed in the simplified design procedure are adequate and can be applied to analytical equations that predict curved homogeneous girder loads. The available analytical equations give conservative loads for both hybrid and homogeneous girders compared to the finite element method when R/1 is 5 and are unconservative for higher rations.
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    Predicting the Effects of Climate Change on Water Temperatures of Roode Elsberg Dam Using Nonparametric Machine Learning Models
    (2021-01-20) Tshireletso, Thalosang; Moyo, Pilate; Kabani, Matongo
    A nonparametric machine learning model was used to study the behaviour of the variables of a concrete arch dam: Roode Elsberg dam. The variables used were ambient temperature, water temperatures, and water level. Water temperature was measured using twelve thermometers; six thermometers were on each flank of the dam. The thermometers were placed in pairs on different levels: avg6 (avg6-R and avg6-L) and avg5 (avg5-R and avg5-L) were on level 47.43 m, avg4 (avg4-R and avg4-L) and avg3 (avg3-R and avg3-L) were on level 43.62 m, and avg2 (avg2-R and avg2-L) and avg1 (avg1-R and avg1-L) were on level 26.23 m. Four neural networks and four random forests were cross-validated to determine their best-performing hyperparameters with the water temperature data. Quantile random forest was the best performer at mtry 7 (Number of variables randomly sampled as candidates at each split) and RMSE (Root mean square error) of 0.0015, therefore it was used for making predictions. The predictions were made using two cases of water level: recorded water level and full dam steady-state at Representative Concentration Pathway (RCP) 4.5 (hot and cold model) and RCP 8.5 (hot and cold model). Ambient temperature increased on average by 1.6 °C for the period 2012–2053 when using recorded water level; this led to increases in water temperature of 0.9 °C, 0.8 °C, and 0.4 °C for avg6-R, avg3-R, and avg1-R, respectively, for the period 2012–2053. The same average temperature increase led to average increases of 0.7 °C for avg6-R, 0.6 °C for avg3-R, and 0.3 °C for avg1-R for a full dam steady-state for the period 2012–2053.
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    Reliability based live loads for structural assessment of bridges on heavy-haul railway lines
    (2018) Kabani, Matongo; Moyo, Pilate
    The highest live loads on railway lines are on dedicated freight corridors operated as heavy-haul lines. These lines carry high axle loads above 25 tonnes and total tonnage above 20 million tonnes per annum over distances greater than 150km. The South African iron ore line currently operates long trains of length 4.1km with 30 tonne per axle wagons on a narrow gage (1065mm) line over a distance of 861km. The operation of heavy haul lines require close monitoring and structural performance evaluation of existing bridges. This study covered both analytical studies and field measurements of bridge dynamic response and static vertical loads required to compute moments shear for beam-type bridges. The field study of dynamic amplification factors was based on strain measurements on the Olifants bridge located on the heavy-haul iron line in South Africa. The Olifants bridge is a 23 span box girder consisting of 2 continuous span segments of 11 spans at either end and a drop span in the middle. The collected strain data consisted 1174 loaded and 1372 empty train crossing events from June 2016 to March 2017. The probabilistic study was based on weigh-in-motion data of heavy-haul freight collected from January 2016 to August 2016. The study was limited to single span, 2 span and 4 span bridges with equal spans and did not consider fatigue. The dynamic response parameters of interest were frequency time evolution of bridge under heavy loads and dynamic amplification factors. An approximate formula derived using 2 dimensional beam model with moving masses is presented. The approximate formulae predicts the reduced frequency within 12% of the estimate from field vibration measurements of an 11 span continuous bridge with train to bridge linear mass ratio of 88%. The approximate formula underestimates the frequency as the stiffening contribution from train suspension system is ignored in a moving mass approximation. Dynamic amplification factors from strain measurements of a continuous 11 span bridge where considerably higher with maximum of 12% compared to 5% from a moving force analytical model for train speed below 60km/h. The amplification from measurements were considerably higher due to the additional local amplification of strains in upper flange of the box girder. A comparison of amplification factors for loaded and empty trains shows that increase in gross weight increases amplification factors. Furthermore, dynamic amplification factors are not dependent on changes in speed during train crossing. Different extrapolation techniques were used to obtain load effects from the same block maxima data. It was shown that the normal, GEV and Bayesian extrapolation methods give load effects within 1% of each other with the normal extrapolation being marginally on the lower end. This observation holds across beam types and span lengths from 5m to 50m. Although the GEV allows for all the three extreme type distributions, an analysis based on available weigh-in-motion data of axle weights show that the fitted distributions using Bayesian and Maximum Likelihood Estimate for all load effects for the span ranges are all Weibull type. On the other hand it is known that the domain of attraction for the normal distribution is Gumbel type. The study also found that extrapolated loads effects are less sensitive to increase in return period beyond 50 years. This aspect is significant as return period is a measure of safety target when determining design values for loads. The study investigated the impact of traffic volume increase and wagon axle load dependencies. The load effects on heavy-haul were shown to be more sensitive to the weak dependence than to traffic growth over the remaining service life of 50 years. The increase in return levels of load effects is less than 1% for traffic volume growth of 4% over a period of 50 years in contrast to the much higher values between 6% and 9% reported on highway bridges for 3% traffic volume growth over 40 year period. Assessment loads that account for some wagon axle dependence have lower return values of load effects than the assume that axle loads are independent which is consistent with theory.