Uncertainties In Structural Parameters Research Articles

Framework for sensitivity and uncertainty quantification in the flutter assessment of bridges

The phenomenon of aerodynamic instability caused by wind is usually a major design criterion for long-span cable-supported bridges. If the wind speed exceeds the critical flutter speed of the bridge, this constitutes an Ultimate Limit State. The prediction of the flutter boundary therefore requires accurate and robust models. The state-of-the-art theory concerning determination of the flutter stability limit is presented. Usually bridge decks are bluff and therefore the aeroelastic forces under wind action have to be experimentally evaluated in wind tunnels or numerically computed through Computational Fluid Dynamics (CFD) simulations. The self-excited forces are modelled using aerodynamic derivatives obtained through CFD forced vibration simulations on a section model. The two-degree-of-freedom flutter limit is computed by solving the Eigenvalue problem.A probabilistic flutter analysis utilizing a meta-modelling technique is used to evaluate the effect of parameter uncertainty. A bridge section is numerically modelled in the CFD simulations. Here flutter derivatives are considered as random variables. A methodology for carrying out sensitivity analysis of the flutter phenomenon is developed. The sensitivity with respect to the uncertainty of flutter derivatives and structural parameters is considered by taking into account the probability distribution of the flutter limit. A significant influence on the flutter limit is found by including uncertainties of the flutter derivatives due to different interpretations of scatter in the CFD simulations. The results indicate that the proposed probabilistic flutter analysis provides extended information concerning the accuracy in the prediction of flutter limits.The final aim is to set up a method to estimate the flutter limit with probabilistic input parameters. Such a tool could be useful for bridge engineers at early design stages. This study shows the difficulties in this regard which have to be overcome but also highlights some interesting and promising results.

Overview of Structural Life Assessment and Reliability, Part IV: Corrosion and Hydrogen Embrittlement of Naval Ship Structures

Overview of Structural Life Assessment and Reliability, Part IV: Corrosion and Hydrogen Embrittlement of Naval Ship Structures

Overview of Structural Life Assessment and Reliability, Part IV: Corrosion and Hydrogen Embrittlement of Naval Ship Structures

Overview of Structural Life Assessment and Reliability, Part IV: Corrosion and Hydrogen Embrittlement of Naval Ship Structures

Adaptive Active Fault Tolerant Control for Discrete‐Time Systems with Uncertainties

AbstractAn active fault‐tolerant control scheme for discrete‐time systems is proposed to solve a difficult problem of fault‐tolerant controller design in the presence of partial loss of actuator effectiveness faults and structural parameter uncertainties assumed to be matched, using adaptive control techniques to help a faster and more accurate compensation of failure and uncertainty. An automated fault estimation scheme is developed together with an adaptive model parameter identification to obtain system parameter estimates. With these estimates fed back to the system, a model reference adaptive controller is constructed to achieve a desired tracking performance. Since parameters are obtained and updated online, the control system has an automatic failure compensation capability so as to recognize or reconfigure the control law in real time in response to failure indications. The stability and convergence follow from discrete‐time Lyapunov arguments. Simulation results from the linearized lateral dynamics model of the Boeing 747 airplane are presented to show the efficiency of proposed methods.

Stochastic model updating utilizing Bayesian approach and Gaussian process model

Stochastic model updating (SMU) has been increasingly applied in quantifying structural parameter uncertainty from responses variability. SMU for parameter uncertainty quantification refers to the problem of inverse uncertainty quantification (IUQ), which is a nontrivial task. Inverse problem solved with optimization usually brings about the issues of gradient computation, ill-conditionedness, and non-uniqueness. Moreover, the uncertainty present in response makes the inverse problem more complicated. In this study, Bayesian approach is adopted in SMU for parameter uncertainty quantification. The prominent strength of Bayesian approach for IUQ problem is that it solves IUQ problem in a straightforward manner, which enables it to avoid the previous issues. However, when applied to engineering structures that are modeled with a high-resolution finite element model (FEM), Bayesian approach is still computationally expensive since the commonly used Markov chain Monte Carlo (MCMC) method for Bayesian inference requires a large number of model runs to guarantee the convergence. Herein we reduce computational cost in two aspects. On the one hand, the fast-running Gaussian process model (GPM) is utilized to approximate the time-consuming high-resolution FEM. On the other hand, the advanced MCMC method using delayed rejection adaptive Metropolis (DRAM) algorithm that incorporates local adaptive strategy with global adaptive strategy is employed for Bayesian inference. In addition, we propose the use of the powerful variance-based global sensitivity analysis (GSA) in parameter selection to exclude non-influential parameters from calibration parameters, which yields a reduced-order model and thus further alleviates the computational burden. A simulated aluminum plate and a real-world complex cable-stayed pedestrian bridge are presented to illustrate the proposed framework and verify its feasibility.

Continuous nonlinear asymptotic tracking control of an air-breathing hypersonic vehicle with flexible structural dynamics and external disturbances

In this paper, the tracking control problem of an air-breathing hypersonic vehicle with structural flexibility is addressed. Due to the harsh high Mach flight condition, the influence associated with the dynamic flexible modes of the hypersonic vehicle cannot be neglected. These flexible dynamic modes, which are affected by the vehicle’s states and control surface deflections, can be viewed as an internal dynamics associated with the system outputs. A new nonlinear robust continuous tracking controller is developed to drive the vehicle’s outputs, which include the vehicle’s velocity, altitude, and attack angle, to track the desired time-varying trajectories in the presence of flexible structural dynamics, parametric uncertainties, and external nonvanishing disturbances. A Lyapunov-based stability analysis is employed to prove that the proposed control design can achieve asymptotic tracking while keeping the internal dynamics to be bounded-input/bounded-output stable. Numerical simulations are performed on the full nonlinear dynamic model to demonstrate the tracking performance of the controller, and highlight the robustness with respect to parametric uncertainties and external disturbances.

Overview of Structural Life Assessment and Reliability, Part III: Impact, Grounding, and Reliability of Ships under Extreme Loading

Overview of Structural Life Assessment and Reliability, Part III: Impact, Grounding, and Reliability of Ships under Extreme Loading

Overview of Structural Life Assessment and Reliability, Part III: Impact, Grounding, and Reliability of Ships under Extreme Loading

Overview of Structural Life Assessment and Reliability, Part III: Impact, Grounding, and Reliability of Ships under Extreme Loading

Overview of Structural Life Assessment and Reliability, Part II: Fatigue Life and Reliability Assessment of Naval Ship Structures

Overview of Structural Life Assessment and Reliability, Part II: Fatigue Life and Reliability Assessment of Naval Ship Structures

Overview of Structural Life Assessment and Reliability, Part II: Fatigue Life and Reliability Assessment of Naval Ship Structures

Overview of Structural Life Assessment and Reliability, Part II: Fatigue Life and Reliability Assessment of Naval Ship Structures

Reduction of predictive uncertainty in estimating irrigation water requirement through multi-model ensembles and ensemble averaging

Abstract. Irrigation agriculture plays an increasingly important role in food supply. Many evapotranspiration models are used today to estimate the water demand for irrigation. They consider different stages of crop growth by empirical crop coefficients to adapt evapotranspiration throughout the vegetation period. We investigate the importance of the model structural versus model parametric uncertainty for irrigation simulations by considering six evapotranspiration models and five crop coefficient sets to estimate irrigation water requirements for growing wheat in the Murray–Darling Basin, Australia. The study is carried out using the spatial decision support system SPARE:WATER. We find that structural model uncertainty among reference ET is far more important than model parametric uncertainty introduced by crop coefficients. These crop coefficients are used to estimate irrigation water requirement following the single crop coefficient approach. Using the reliability ensemble averaging (REA) technique, we are able to reduce the overall predictive model uncertainty by more than 10%. The exceedance probability curve of irrigation water requirements shows that a certain threshold, e.g. an irrigation water limit due to water right of 400 mm, would be less frequently exceeded in case of the REA ensemble average (45%) in comparison to the equally weighted ensemble average (66%). We conclude that multi-model ensemble predictions and sophisticated model averaging techniques are helpful in predicting irrigation demand and provide relevant information for decision making.

A hybrid method for stochastic response analysis of a vibrating structure

Response analysis of a linear structure with uncertainties in both structural parameters and external excitation is considered here. When such an analysis is carried out using the spectral stochastic finite element method (SSFEM), often the computational cost tends to be prohibitive due to the rapid growth of the number of spectral bases with the number of random variables and the order of expansion. For instance, if the excitation contains a random frequency, or if it is a general random process, then a good approximation of these excitations using polynomial chaos expansion (PCE) involves a large number of terms, which leads to very high cost. To address this issue of high computational cost, a hybrid method is proposed in this work. In this method, first the random eigenvalue problem is solved using the weak formulation of SSFEM, which involves solving a system of deterministic nonlinear algebraic equations to estimate the PCE coefficients of the random eigenvalues and eigenvectors. Then the response is estimated using a Monte Carlo (MC) simulation, where the modal bases are sampled from the PCE of the random eigenvectors estimated in the previous step, followed by a numerical time integration. It is observed through numerical studies that this proposed method successfully reduces the computational burden compared with either a pure SSFEM of a pure MC simulation and more accurate than a perturbation method. The computational gain improves as the problem size in terms of degrees of freedom grows. It also improves as the timespan of interest reduces.

Reliability Analysis of RC Columns and Frame with FRP Strengthening Subjected to Explosive Loads

Some structures, both military and civilian, might experience explosive loads during their service life. Owing to high uncertainties in blast load predictions and structural parameters, accurate assessment of the performances of structures under explosion loads is a challenging task. For example, a number of experimental studies using fiber-reinforced plastic (FRP) strengthening of RC structures have been reported in the literature. Most of these studies demonstrate that FRP strengthening is effective in increasing the blast load–carrying capacities of RC structures. However, significant variations in the effectiveness of FRP strengthening have also been observed owing to the large uncertainties in blast loading, RC and FRP material properties, and workmanship in preparing the test specimens and conducting experimental tests. Very few studies that take into consideration these uncertainties in analyzing the effectiveness of FRP strengthening of RC structures on blast loading resistance can be found in the literature. This study performs a reliability analysis to assess the performance of RC columns with or without FRP strengthening in resisting blast loads. Statistical variations of blast loading predictions derived in a previous study are adopted in this study. To define structural performance, pressure-impulse (P-I) curves with a damage criterion on the basis of axial load-carrying capacity that were developed in previous studies for RC columns without strengthening or with FRP strip, FRP wrap, or both FRP strip and wrap strengthening are used. Considering the uncertainties in blast loading predictions and RC column and FRP material properties and dimensions, limit-state functions corresponding to different damage levels of RC columns with or without FRP strengthening are formulated. The statistical variations of blast loading, RC column dimension, longitudinal and transverse reinforcement ratio, and concrete, steel, and FRP material strength and FRP thickness are considered. The failure probabilities of RC columns corresponding to different damage levels with or without FRP strengthening are calculated. The effectiveness of FRP strengthening on the RC column’s blast loading resistance capacities is discussed. The importance of considering the random fluctuations on blast loading and RC column parameters in assessing the blast loading effect on RC columns is demonstrated. A structural system reliability analysis is also carried out to examine the probability of structural collapse as a result of blast loading applied to the front of an example two-span multistory RC frame. The results obtained in this study demonstrate the effectiveness of FRP strengthening on structure protection and can also be used to assess RC structure performance under blast loadings.

Buffeting reliability of bridges with structural uncertainties

The dynamic reliability of a long-span bridge under wind turbulence is of great concern to engineering practice. In this paper, a practical framework is presented to evaluate the buffeting reliability of long-span bridges, in which the stochastic natures of both wind fluctuations and structural parameters are taken into consideration. A two-step strategy is adopted in the proposed method to consider the effects on the buffeting reliability of the stochastic wind loads and random structural properties. The approximative explicit expression for conditional buffeting reliability under given structural parameters is first obtained using the response surface method, in which only the stochastic effects due to wind loads are involved. Then, based on the total probability theorem, the total buffeting reliability is calculated in conjunction with the Monte-Carlo simulation techniques, in which, in addition to the stochastic wind loads, the uncertainties of structural parameters are taken into account. The buffeting reliability analysis of the Yamen Bridge, China, a long-span cable-stayed bridge with a main span of 338 m, is conducted to illustrate the feasibility and effectiveness of the present approach, and the effects of structural uncertainties on the buffeting reliability of the bridge are investigated.

Overview of Structural Life Assessment and Reliability, Part I: Basic Ingredients of Fracture Mechanics

Overview of Structural Life Assessment and Reliability, Part I: Basic Ingredients of Fracture Mechanics

Overview of Structural Life Assessment and Reliability, Part I: Basic Ingredients of Fracture Mechanics

Overview of Structural Life Assessment and Reliability, Part I: Basic Ingredients of Fracture Mechanics

UNCERTAIN BUCKLING AND RELIABILITY ANALYSIS OF THE PIEZOELECTRIC FUNCTIONALLY GRADED CYLINDRICAL SHELLS BASED ON THE NONPROBABILISTIC CONVEX MODEL

The uncertain buckling and reliability of the laminated piezoelectric functionally graded material (FGM) cylindrical shells subjected to axially compressed loads are investigated in this research. Considering the shear deformation, the buckling governing equations of the piezoelectric FGM cylindrical shells are derived on the basis of Donnell assumptions. And then the nonprobabilistic convex model is introduced to predict the uncertain buckling loads of the piezoelectric FGM cylindrical shells resulting from the unavoidable scatter in structural parameters. Finally, the reliability degree of the structures is obtained by computing the ratio of the multidimensional volume falling into the reliability domain to the one of the whole convex model. Numerical results indicate that uncertainties in structural parameters have significant effects on the critical buckling loads and reliability of the piezoelectric FGM cylindrical shells.

An efficient Bayesian inversion of a geothermal prospect using a multivariate adaptive regression spline method

In this study, an efficient Bayesian framework equipped with a multivariate adaptive regression spline (MARS) technique is developed to alleviate computational burdens encountered in a conventional Bayesian inversion of a geothermal prospect. Fast MARS models are developed from training dataset generated by CPU-intensive hydrothermal models and used as surrogate of high-fidelity physical models in Markov Chain Monte Carlo (MCMC) sampling. This Bayesian inference with MARS-enabled MCMC method is used to reduce prior estimates of uncertainty in structural or characteristic hydrothermal flow parameters of the model to posterior distributions. A geothermal prospect near Superstition Mountain in Imperial County of California in USA is used to illustrate the proposed framework and demonstrate the computational efficiency of MARS-based Bayesian inversion. The developed MARS models are also used to efficiently drive calculation of Sobol’ total sensitivity indices. Only top sensitive parameters are included in Bayesian inference to further improve the computational efficiency of inversion. Sensitivity analysis also confirms that water circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method. The presented framework is demonstrated an efficient tool to update knowledge of geothermal prospects by inversing field data. Although only thermal data is used in this study, other type of data, such as flow and transport observations, can be jointly used in this method for underground hydrocarbon reservoirs.

Simulation and experimental tests on active mass damper control system based on Model Reference Adaptive Control algorithm

In the process of sudden natural disasters (such as earthquake or typhoon), the active mass damper (AMD) system can reduce the structural vibration response optimally, which serves as a frequently applied but less mature vibration-reducing technology in wind and earthquake resistance of high-rise buildings. As the core of this technology, the selection of control algorithm is extremely challenging due to the uncertainty of structural parameters and the randomness of external loads. It is not necessary for the Model Reference Adaptive Control (MRAC) based on the Minimal Controller Synthesis (MCS) algorithm to know in advance the structural parameters, which produces special advantages in conditions of real-time change of system parameters, uncertain external disturbance, and the nonlinear dynamic system. This paper studies the application of the MRAC into the AMD active control system. The principle of MRAC algorithm is recommended and the dynamic model and the motion differential equation of AMD system based on MRAC is established under seismic excitation. The simulation analysis for linear and nonlinear structures when the structural stiffness is degenerated is performed under AMD system controlled by MRAC algorithm. To verify the validity of the MRAC over the AMD system, experimental tests are carried out on a linear structure and a structure with variable stiffness with the AMD system under seismic excitation on the shake table, and the experimental results are compared with those of the traditional pole assignment control algorithm.

Structural Parameters of Star Clusters: Stochastic Effects

AbstractStochasticity of bright stars introduces uncertainty and bias into derived structural parameters of star clusters. We have simulated a grid of cluster V-band images, observed with the Subaru Suprime-Cam, with age, mass and size representing a cluster population in the M31 galaxy and derived their structural parameters by fitting King model to the surface brightness distribution. We have found that clusters less massive than 104M⊙ show significant uncertainty in their core and tidal radii for all ages, while clusters younger than 10 Myr have their sizes systematically underestimated for all masses. This emphasizes the importance of stochastic simulations to assess the true uncertainty of structural parameters in studies of semi-resolved and unresolved clusters.