Engineering topics

Shen, Ji-Yao

Publications and source records attributed to Shen, Ji-Yao.

7 records

NASA NTRS1994

Applying transfer matrix method to the estimation of the modal characteristics of the NASA Mini-Mass Truss

It is beneficial to use a distributed parameter model for large space structures because the approach minimizes the number of model parameters. Holzer's transfer matrix method provides a useful means to simplify and standardize the procedure for solving the system of partial differential equations. Any large space structures can be broken down into sub-structures with simple elastic and dynamical properties. For each single element, such as beam, tether, or rigid body, we can derive the corresponding transfer matrix. Combining these elements' matrices enables the solution of the global system equations. The characteristics equation can then be formed by satisfying the appropriate boundary conditions. Then natural frequencies and mode shapes can be determined by searching the roots of the characteristic equation at frequencies within the range of interest. This paper applies this methodology, and the maximum likelihood estimation method, to refine the modal characteristics of the NASA Mini-Mast Truss by successively matching the theoretical response to the test data of the truss. The method is being applied to more complex configurations.

Shen, Ji-Yao↗

NASA NTRS1992

Structures research

The main objective of the structures group is to provide quality aerospace research with the Center for Aerospace Research - A NASA Center for Excellence at North Carolina Agricultural and Technical State University. The group includes dedicated faculty and students who have a proven record in the area of structures, in particular space structures. The participating faculty developed accurate mathematical models and effective computational algorithms to characterize the flexibility parameters of joint dominated beam-truss structures. Both experimental and theoretical modelling has been applied to the dynamic mode shapes and mode frequencies for a large truss system. During the past few months, the above procedures has been applied to the hypersonic transport plane model. The plane structure has been modeled as a lumped mass system by Doctor Abu-Saba while Doctor Shen applied the transfer matrix method with a piecewise continuous Timoshenko tapered beam model. Results from both procedures compare favorably with those obtained using the finite element method. These two methods are more compact and require less computer time than the finite element method. The group intends to perform experiments on structural systems including the hypersonic plane model to verify the results from the theoretical models.

Abu-Saba, Elias↗

NASA NTRS1991

Likelihood estimation for distributed parameter models for NASA Mini-MAST truss

A maximum likelihood estimation for distributed parameter models of large flexible structures was formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics or finite element models. The closed form solutions for the partial differential equations with corresponding boundary conditions were derived. The closed-form expressions of sensitivity functions led to highly efficient algorithms for analyzing ground or on-orbit test results. For an illustration of this approach, experimental data of the NASA Mini-MAST truss was used. The estimations of modal properties involve lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures.

Shen, Ji-Yao↗

NASA NTRS1991

Distributed parameter estimation for NASA Mini-Mast truss using Timoshenko beam model

A more accurate Timoshenko beam model is used to characterize the bending behavior of the truss. A maximum likelihood estimator for the Timoshenko beam model has been formulated. A closed-form solution of the Timoshenko beam equation, for a uniform cantilevered beam with two concentrated masses, is derived so that the procedure for the estimation of modal characteristics is much improved. The updated model to the NASA Mini-Mast test data is demonstrated.

Shen, Ji-Yao↗

NASA NTRS1991

Distributed parameter estimation for NASA Mini-Mast truss through displacement measurements

Most methods of system identification of large flexible structures by far are based on the lumped parameter approach. Because of the considerable computational burden due to the large number of unknown parameters, distributed parameter approach, which greatly decreases the number of unknowns, has being investigated. In this paper a distributed parameter model for the estimation of modal characteristics of NASA Mini-Mast truss has been formulated. Both Bernoulli-Euler beam and Timoshenko beam equations are used to characterize the lateral bending vibrations of the truss. The measurement of the lateral displacement at the tip of the truss is provided to the maximum likelihood estimator. Closed-form solutions of the partial differential equations and closed-form expressions of the sensitivity functions are derived so that the estimation algorithm is highly efficient. The resulting estimates from test data by using Timoshenko beam model are found to be comparable to those derived from finite element analysis.

Huang, Jen-Kuang↗

NASA NTRS1990

Distributed parameter estimation for large beam-like structures for general inputs

In this paper, maximum likelihood estimation for distributed parameter models of large flexible structures has been formulated. Distributed parameter models involve far fewer unknown parameters than independent modal characteristics of finite element models. The closed-form solutions for the partial differential equations with general forced inputs have been derived. The closed-form expressions of the sensitivity functions lead to highly efficient algorithms for analyzing ground or on-orbit test results. Numerical simulations with impulse and step inputs to the NASA Mini-MAST trust have been demonstrated. The estimations of modal properties involve its longitudinal elongation modes, lateral bending modes and torsional modes. The results show that distributed parameter models are promising in the parameter estimation of large flexible structures.

Shen, Ji-Yao↗

NASA NTRS1988

Modal identification using single-mode projection filters and comparison with ERA and MLE results

The Single-Mode Projection Filter (SPF) is a newly developed algorithm for eigensystem parameter identification from both analytical results and test data. The SPF is formulated with a single mode only and practical for parallel processing implementation. Explicit formulations of SPF are derived for the multi-input multi-output (MIMO) system by using the orthogonal matrices of the controllability and observability matrices in the general sense. The modal parameters of SPF are initially obtained from an analytical model in modal space. The experimental data are then processed through SPF to update its modal parameters and to minimize a cost function defined by the norm of an error matrix. The updated modal parameters represent the characteristics of the test data. A two-dimensional global minimum optimization algorithm is developed and applied for the filter update by using the interval analysis method. The SPF is developed based on a single-mode subsystem and identifies only one modal frequency and one modal damping within a specified region. For an n-modes structure, n SPF can be implemented for parallel processing to reduce the computational burden. The SPF is applied to analyze the simulated data for the MAST beam structure. The estimated modal parameters are comparable to those from the Eigensystem Realization Algorithm (ERA) and repeated modal frequencies are identified. The modal analysis of the Spacecraft Control Laboratory Experiment (SCOLE) data is also performed by using the ERA and the Maximum Likelihood Estimate (MLE). The result shows that the first five modal frequencies are very close from ERA and MLE. However, there are slight disparities in the damping rates and the computational burdens are quite different among these two algorithms.

Huang, Jen-Kuang↗