Acharya, Raju;Han, Jie;Parsons, Robert L.;Brennan, James J.
Geomechanics and Engineering
/
v.11
no.5
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pp.625-638
/
2016
This paper presents field study and numerical modeling results for a single-cell low-fill concrete box culvert under a flexible pavement subjected to traffic loading. The culvert in the field test was instrumented with displacement transducers to capture the deformations resulting from different combinations of static and traffic loads. A low-boy truck with a known axle configuration and loads was used to apply seven static load combinations and traffic loads at different speeds. Deflections under the culvert roof were measured during loading. Soil and pavement samples were obtained by drilling operation on the test site. The properties of the soil and pavement layers were determined in the laboratory. A 3-D numerical model of the culvert was developed using a finite difference program FLAC3D. Linear elastic models were used for the pavement layers and soil. The numerical results with the material properties determined in the laboratory were compared with the field test results. The observed deflections in the field test were generally smaller under moving loads than static loads. The maximum deflections measured during the static and traffic loads were 0.6 mm and 0.41 mm respectively. The deflections computed by the numerical method were in good agreement with those observed in the field test. The deflection profiles obtained from the field test and the numerical simulation suggest that the traffic load acted more like a concentrated load distributed over a limited area on the culvert. Elastic models for culverts, pavement layers, and surrounding soil are appropriate for numerical modeling of box culverts under loading for load rating purposes.
We applied multilayer perceptron (MLP) and radial basis function (RBF) neural network in upstream and downstream water quality stations of the Karaj Reservoir in Iran. For both neural networks, inputs were pH, turbidity, temperature, chlorophyll-a, biochemical oxygen demand (BOD) and nitrate, and the output was dissolved oxygen (DO). We used an MLP neural network with two hidden layers, for upstream station 15 and 33 neurons in the first and second layers respectively, and for the downstream station, 16 and 21 neurons in the first and second hidden layer were used which had minimum amount of errors. For learning process 6-fold cross validation were applied to avoid over fitting. The best results acquired from RBF model, in which the mean bias error (MBE) and root mean squared error (RMSE) were 0.063 and 0.10 for the upstream station. The MBE and RSME were 0.0126 and 0.099 for the downstream station. The coefficient of determination ($R^2$) between the observed data and the predicted data for upstream and downstream stations in the MLP was 0.801 and 0.904, respectively, and in the RBF network were 0.962 and 0.97, respectively. The MLP neural network had acceptable results; however, the results of RBF network were more accurate. A sensitivity analysis for the MLP neural network indicated that temperature was the first parameter, pH the second and nitrate was the last factor affecting the prediction of DO concentrations. The results proved the workability and accuracy of the RBF model in the prediction of the DO.
Roy, Krishanu;Ting, Tina Chui Huon;Lau, Hieng Ho;Lim, James B.P.
Steel and Composite Structures
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v.28
no.2
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pp.233-250
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2018
Back-to-back built-up cold-formed steel un-lipped channel sections are used in cold-formed steel structures; such as trusses, wall frames and portal frames. In such built-up columns, intermediate fasteners resist the buckling of individual channel-sections. No experimental tests or finite element analyses have been reported in the literature for back-to-back built-up cold-formed steel un-lipped channel sections and specially investigated the effect of screw spacing on axial strength of such columns. The issue is addressed in this paper. The results of 95 finite element analyses are presented covering stub to slender columns. The finite element model is validated against the experimental tests recently conducted by authors for back-to-back built-up cold-formed steel lipped channel sections. The verified finite element model is then used for the purposes of a parametric study to investigate the effect of screw spacing on axial strength of back-to-back built-up cold-formed steel un-lipped channel sections. Results are compared against the built-up lipped channel sections and it is shown that the axial strength of un-lipped built-up sections are 31% lesser on average than the built-up lipped channel sections. It was also found that the American Iron and Steel Institute (AISI) and the Australian and New Zealand Standards were over-conservative by around 15% for built-up columns failed through overall buckling, however AISI and AS/NZS were un-conservative by around 8% for built-up columns mainly failed by local buckling.
Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.
Slopes stabilised with piles are seldom analysed considering uncertainties in the parameters of the pile-slope system. Reliability analysis of the pile-slope system quantifies the degree of uncertainties and evaluates the safety of the system. In the present study, the reliability analysis of a slope stabilised with piles is performed using the first-order reliability method (FORM) based on Hasofer-Lind approach. The implicit performance function associated with the factor of safety (FS) of the slope is approximated using the response surface method. The analyses are carried out considering the design matrices formulated based on both the 2k factorial design augmented with a centre run (2k fact-centred design) and face-centered cube design (FCD). The finite element method is used as the deterministic model to compute the FS of the pile-slope system. Results are compared with the results of the Monte Carlo simulation. It is observed that the optimum location of the row of piles is at the middle of the slope to achieve the maximum FS. The results show that the reliability of the system is not uniform for different pile configurations, even if the system deterministically satisfies the target factor of safety (FSt) criterion. The FSt should be selected judiciously as it is observed that the reliability of the system changes drastically with the FSt level. The results of the 2k fact-centred design and FCD are in good agreement with each other. The procedure of the FCD is computationally costly and hence the use of 2k fact-centred design is recommended, provided the response of the system is sufficiently linear over the factorial space.
Real-time monitoring of stiffness and strength in cement based system has received significant attention in past few decades owing to the development of advanced techniques. Also, use of environment friendly supplementary cementitious materials (SCM) in cement, though gaining huge interest, severely affect the strength gain especially in early ages. Continuous monitoring of strength- and stiffness- gain using an efficient technique will systematically facilitate to choose the suitable time of removal of formwork for structures made with SCM incorporated concrete. This paper presents a technique for monitoring the strength and stiffness evolution in hydrating fly ash blended cement systems using electro-mechanical impedance (EMI) based technique. It is important to observe that the slower pozzolanic reactivity of fly ash blended cement systems could be effectively tracked using the evolution of equivalent local stiffness of the hydrating medium. Strength prediction models are proposed for estimating the strength and stiffness of the fly ash cement system, where curing age (in terms of hours/days) and the percentage replacement of cement by fly ash are the parameters. Evaluation of strength as obtained from EMI characteristics is validated with the results from destructive compression test and also compared with the same obtained from commonly used ultrasonic wave velocity (UPV). Statistical error indices indicate that the EMI technique is capable of predicting the strength of fly ash blended cement system more accurate than that from UPV. Further, the correlations between stiffness- and strength- gain over the time of hydration are also established. From the study, it is found that EMI based method can be effectively used for monitoring of strength gain in the fly ash incorporated cement system during hardening.
Real-time hybrid simulation (RTHS) which combines physical experiment with numerical simulation is an advanced method to investigate dynamic responses of structures subjected to earthquake excitation. The desired displacement computed from the numerical substructure is applied to the experimental substructure by a servo-hydraulic actuator in real time. However, the magnitude decay and phase delay resulted from the dynamics of the servo-hydraulic system affect the accuracy and stability of a RTHS. In this study, a robust stability analysis procedure for a general single-degree-of-freedom structure is proposed which considers the uncertainty of servo-hydraulic system dynamics. For discussion purposes, the experimental substructure is a portion of the entire structure in terms of a ratio of stiffness, mass, and damping, respectively. The dynamics of the servo-hydraulic system is represented by a multiplicative uncertainty model which is based on a nominal system and a weight function. The nominal system can be obtained by conducting system identification prior to the RTHS. A first-order weight function formulation is proposed which needs to cover the worst possible uncertainty envelope over the frequency range of interest. Then, the Nyquist plot of the perturbed system is adopted to determine the robust stability margin of the RTHS. In addition, three common delay compensation methods are applied to the RTHS loop to investigate the effect of delay compensation on the robust stability. Numerical simulation and experimental validation results indicate that the proposed procedure is able to obtain a robust stability margin in terms of mass, damping, and stiffness ratio which provides a simple and conservative approach to assess the stability of a RTHS before it is conducted.
The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.
In order to protect a structure over its full life cycle, a novel tuned mass damper (TMD), the so-called semi-active eddy current pendulum tuned mass damper (SAEC-PTMD), which can retune its frequency and damping ratio in real-time, is proposed in this study. The structural instantaneous frequency is identified through a Hilbert-Huang transformation (HHT), and the SAEC-PTMD pendulum is adjusted through an HHT-based control algorithm. The eddy current damping parameters are discussed, and the relationship between effective damping coefficients and air gaps is fitted through a polynomial function. The semi-active eddy current damping can be adjusted in real-time by adjusting the air gap based on the linear-quadratic-Gaussian (LQG)-based control algorithm. To verify the vibration control effect of the SAEC-PTMD, an idealized linear primary structure equipped with an SAEC-PTMD excited by harmonic excitations and near-fault pulse-like earthquake excitations is proposed as one of the two case studies. Under strong earthquakes, structures may go into the nonlinear state, while the Bouc-Wen model has a wild application in simulating the hysteretic characteristic. Therefore, in the other case study, a nonlinear primary structure based on the Bouc-Wen model is proposed. An optimal passive TMD is used for comparison and the detuning effect, which results from the cumulative damage to primary structures, is considered. The maximum and root-mean-square (RMS) values of structural acceleration and displacement time history response, structural acceleration, and displacement response spectra are used as evaluation indices. Power analyses for one earthquake excitation are presented as an example to further study the energy dissipation effect of an SAECPTMD. The results indicate that an SAEC-PTMD performs better than an optimized passive TMD, both before and after damage occurs to the primary structure.
Two-dimensional Delayed Detached Eddy Simulation (DDES) was carried out to investigate the uniform flow over a twin-box bridge deck (TBBD) with various gap ratios of L/C=5.1%, 12.8%, 25.6%, 38.5%, 73.3% and 108.2% (L: the gap-width between two girders, C: the chord length of a single girder) at Reynolds number, Re=4×104. The aerodynamic coefficients of the prototype deck with gap ratio of 73.3% obtained from the present simulation were compared with the previous experimental and numerical data for different attack angles to validate the present numerical method. Particular attention is devoted to the fluctuating pressure distribution and forces, shear layer reattachment position, wake velocity and flow pattern in order to understand the effects of gap ratio on dynamic flow interaction with the twin-box bridge deck. The flow structure is sensitive to the gap, thus a change in L/C thus leads to single-side shedding regime at L/C≤25.6%, and co-shedding regime at L/C≥35.8% distinguished by drastic changes in flow structure and vortex shedding. The gap-ratio-dependent Strouhal number gradually increases from 0.12 to 0.27, though the domain frequencies of vortices shedding from two girders are identical. The mean and fluctuating pressure distributions is significantly influenced by the flow pattern, and thus the fluctuating lift force on two girders increases or decreases with increasing of L/C in the single-side shedding and co-shedding regime, respectively. In addition, the flow mechanisms for the variation in aerodynamic performance with respect to gap ratios are discussed in detail.
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