scholarly journals Experimental Validation of Optimal Parameter and Uncertainty Estimation for Structural Systems Using a Shuffled Complex Evolution Metropolis Algorithm

2019 ◽  
Vol 9 (22) ◽  
pp. 4959 ◽  
Author(s):  
Hesheng Tang ◽  
Xueyuan Guo ◽  
Liyu Xie ◽  
Songtao Xue
Keyword(s):  
Optimal Parameter ◽  
Structural Parameters ◽  
Metropolis Algorithm ◽  
Shaking Table ◽  
Parameter Distribution ◽  
Physical Parameters ◽  
Structural Systems ◽  
Model Errors ◽  
Nonlinear Structural ◽  
Shuffled Complex Evolution

The uncertainty in parameter estimation arises from structural systems’ input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identifying the optimal parameters of structural systems and estimating their uncertainty is presented. First, the estimation framework is theoretically developed. The SCEM-UA algorithm is employed to search through feasible parameters’ space and to infer the posterior distribution of the parameters automatically. The resulting posterior parameter distribution then provides the most likely estimation of parameter sets that produces the best model performance. The algorithm is subsequently validated through both numerical simulation and shaking table experiment for estimating the parameters of structural systems considering the uncertainty of available information. Finally, the proposed algorithm is extended to identify the uncertain physical parameters of a nonlinear structural system with a particle mass tuned damper (PTMD). The results demonstrate that the proposed algorithm can effectively estimate parameters with uncertainty for nonlinear structural systems, and it has a stronger anti-noise capability. Notably, the SCEM-UA method not only shows better global optimization capability compared with other heuristic optimization methods, but it also has the ability to simultaneously estimate the uncertainties associated with the posterior distributions of the structural parameters within a single optimization run.

A Two-stage Parametric Identification of Strong Nonlinear Structural Systems with Incomplete Response Measurements

2016 ◽  
Vol 16 (04) ◽  
pp. 1640022 ◽  
Author(s):  
Lijun Liu ◽  
Ying Lei ◽  
Mingyu He
Keyword(s):  
Kalman Filter ◽  
Unscented Kalman Filter ◽  
Structural Parameters ◽  
Nonlinear Problems ◽  
Parametric Identification ◽  
Structural Systems ◽  
Two Stage ◽  
Incomplete Response ◽  
Nonlinear Structural ◽  
Structural Responses

Compared with the identification of linear structural parameters, it is more difficult to conduct parametric identification of strong nonlinear structural systems, especially when only incomplete structural responses are available. Although the extended Kalman filter (EKF) is useful for structural identification with partial measurements of structural responses and can be extended for the identification of nonlinear structures, EKF approximates nonlinear system through Taylor series expansion and is therefore not effective for the identification of strong nonlinear structural systems. Other approaches such as the unscented Kalman filter (UKF) have been proposed for the identification of strong nonlinear problems. Based on the fact that nonlinearities exist in local areas of structures, a straightforward two-stage identification approach is proposed in this paper for the identification of strong nonlinear structural parameters with incomplete response measurements. In the first stage, the locations of nonlinearities are identified based on the EKF for the identification of the equivalent linear structures. In the second stage, the UKF is utilized to identify the parameters of strong nonlinear structural systems. Therefore, the parametric identification of strong nonlinear structural parameters is simplified by the proposed approach. Several numerical examples with different nonlinear models and locations are used to validate the proposed approach.

scholarly journals Structural Reliability Sensitivities under Nonstationary Random Vibrations

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Rita Greco ◽  
Francesco Trentadue
Keyword(s):  
Structural Reliability ◽  
Structural Parameters ◽  
Time Integration ◽  
Structural Response ◽  
Integration Scheme ◽  
Structural Systems ◽  
Frame Building ◽  
Time Integration Scheme ◽  
Noise Input ◽  
The Time Domain

Response sensitivity evaluation is an important element in reliability evaluation and design optimization of structural systems. It has been widely studied under static and dynamic forcing conditions with deterministic input data. In this paper, structural response and reliability sensitivities are determined by means of the time domain covariance analysis in both classically and nonclassically damped linear structural systems. A time integration scheme is proposed for covariance sensitivity. A modulated, filtered, white noise input process is adopted to model the stochastic nonstationary loads. The method allows for the evaluation of sensitivity statistics of different quantities of dynamic response with respect to structural parameters. Finally, numerical examples are presented regarding a multistorey shear frame building.

Design and Evaluation of the Key Units in a Rapeseed Direct Seeder Integrated with Plowing-Rotating Combined Tillage

2021 ◽  
Vol 37 (6) ◽  
pp. 1005-1014
Author(s):  
Guoliang Wei ◽  
Qingsong Zhang ◽  
Biao Wang ◽  
QingXi Liao
Keyword(s):  
Field Experiments ◽  
Optimal Parameter ◽  
Structural Parameters ◽  
List Type ◽  
Oil Crops ◽  
Orthogonal Experiments ◽  
Heavy Soil ◽  
Tillage Depth ◽  
Working Parameters ◽  
Orthogonal Field

HighlightsThe seeder combined the plowing and rotating tillage to overcome the heavy soil and a large amount of straws.The plow could lift and turn the soil and straw before rotary tillage.The optimal working parameters of the seeder were obtained by orthogonal field experiments.Abstract. Rapeseed, one of the most important oil crops in China, is mainly planted in the mid-lower reaches of the Yangtze River. However, limited by the special long-term rice-rapeseed rotation, rotary tillage is applied in most of the planted areas apply instead of plow tillage, leading to a shallow arable layer. On the other hand, maintaining a high-quality seedbed for rapeseed becomes a challenge because a large amount of straw remains buried in the soil. As a solution, a rapeseed direct seeder that combines plow tillage and rotary tillage was designed. The structure of the plowing unit, whose key components were a lifting-turning plow and symmetrical plow, was analyzed based on the forming principle of the plow. Furthermore, a mechanical soil throwing model of the rotary tillage blade was built to determine the structural parameters. Then, the interaction between the rotary tillage unit and the lift-turning plow was analyzed. Finally, the performance and optimal parameters were evaluated by orthogonal field experiments. The seedbed after the operations indicated that the seeder could achieve the function of turning the soil and straw first and then rotating the soil with good passability, mixing the straw and the soil, flattening the surface of the seed bed, and stabilizing the tillage depth. Orthogonal experiments showed that the optimal working parameters of the seeder were as follows: the tillage depth was 180 mm, the equipment forward speed was 2.1 km/h, and the speed of the rotary tillage blade was 250 r/min. Under the optimal parameter combination, the power consumption of the seeder, the thickness of the tillage layer, the crop residue burial efficiency, the soil breakage efficiency, and the flatness of the seed bed surface were 30.48 kW, 231 mm, 90.88%, 93.26%, and 21.15 mm, respectively. The working performance of the seeder could meet the tillage requirements of rapeseed planting. Keywords: Direct seeder, Evaluation, Plow, Plowing-rotating combined tillage, Rapeseed.

Application of an Anode Model to Investigate Physical Parameters in an Internal Reforming Solid-Oxide Fuel Cell

2005 ◽  
Vol 2 (2) ◽  
pp. 136-140 ◽  
Author(s):  
Eric S. Greene ◽  
Maria G. Medeiros ◽  
Wilson K. S. Chiu
Keyword(s):  
Fuel Cell ◽  
Solid Oxide Fuel Cell ◽  
Structural Parameters ◽  
Porous Electrode ◽  
Cell Voltage ◽  
Solid Oxide ◽  
Physical Parameters ◽  
Oxide Fuel ◽  
Internal Reforming ◽  
Porous Anode

A one-dimensional model of chemical and mass transport phenomena in the porous anode of a solid-oxide fuel cell, in which there is internal reforming of methane, is presented. Macroscopically averaged porous electrode theory is used to model the mass transfer that occurs in the anode. Linear kinetics at a constant temperature are used to model the reforming and shift reactions. Correlations based on the Damkohler number are created to relate anode structural parameters and thickness to a nondimensional electrochemical conversion rate and cell voltage. It is shown how these can be applied in order to assist the design of an anode.

scholarly journals Practical Credibility Theory with Emphasis on Optimal Parameter Estimation

1981 ◽  
Vol 12 (2) ◽  
pp. 115-131 ◽  
Author(s):  
F. De Vylder
Keyword(s):  
Optimal Parameter ◽  
Structural Parameters ◽  
Minimum Variance ◽  
Small Sample ◽  
Credibility Theory ◽  
Successive Approximations ◽  
Method Of Successive Approximations ◽  
Real Problem ◽  
Estimation Problems ◽  
Optimal Estimators

We develop Hachemeister's regression model in credibility theory (without proofs) and indicate how the involved structural parameters can be estimated from the observable variables (with proofs for the simple results and those not yet published).Large families of unbiased estimators are available. From the practical viewpoint this is rather a handicap because it creates the problem to decide what estimators actually to use. In order to fix optimal estimators, we adopt the small-sample criterion of minimum-variance. But in the research for general solutions three kinds of difficulties arise.(i) The calculations become too lengthy.(ii) The optimal estimators depend on some of the parameters to be estimated. (Then we call them pseudo-estimators).(iii) The optimal estimators depend on new structural parameters defined in terms of fourth-order moments.Only a compromise allows to cope with this reality. Situation (iii) creates new estimation problems. They can only be avoided at the cost of the introduction of special assumptions or approximations. Then problem (i) is more or less automatically solved. By an obvious method of successive approximations pseudo-estimators can serve as true estimators. Thus (ii) is no real problem.

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