• Title/Summary/Keyword: Inverse problems

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Optical Design of a Wide-field Off-axis Two-mirror System without Ray Obstruction (광선의 차폐가 없는 광시야 비축 2반사광학계 설계)

  • Oh, Hye-Jin;Lee, Jong-Ung
    • Korean Journal of Optics and Photonics
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    • v.28 no.6
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    • pp.263-272
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    • 2017
  • To design a wide-field optical system, the inverted telephoto configuration, which has a negative front group and a positive rear group, is popular. For a two-mirror system, the inverse Cassegrain system has the inverted telephoto configuration, but the inverse Cassegrain system with the conventional, axially symmetric configuration shows severe field screening and ray obstruction. To avoid these problems, we put the aperture stop on the secondary mirror of an inverse Cassegrain system to increase field of view, and designed a wide-field off-axis two-mirror system which only uses the off-axis field, without ray obstruction.

Inverse Model Parameter Estimation Based on Sensitivity Analysis for Improvement of PM10 Forecasting (PM10 예보 향상을 위한 민감도 분석에 의한 역모델 파라메터 추정)

  • Yu, Suk Hyun;Koo, Youn Seo;Kwon, Hee Yong
    • Journal of Korea Multimedia Society
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    • v.18 no.7
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    • pp.886-894
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    • 2015
  • In this paper, we conduct sensitivity analysis of parameters used for inverse modeling in order to estimate the PM10 emissions from the 16 areas in East Asia accurately. Parameters used in sensitivity analysis are R, the observational error covariance matrix, and B, a priori (background) error covariance matrix. In previous studies, it was used with the predetermined parameter empirically. Such a method, however, has difficulties in estimating an accurate emissions. Therefore, an automatically determining method for the most suitable value of R and B with an error measurement criteria and posteriori emissions accuracy is required. We determined the parameters through a sensitivity analysis, and improved the accuracy of posteriori emissions estimation. Inverse modeling methods used in the emissions estimation are pseudo inverse, NNLS (Nonnegative Least Square), and BA(Bayesian Approach). Pseudo inverse has a small error, but has negative values of emissions. In order to resolve the problem, NNLS is used. It has a unrealistic emissions, too. The problems are resolved with BA(Bayesian Approach). We showed the effectiveness and the accuracy of three methods through case studies.

Optimal control approach to resolve the redundancy of robot manipulators

  • Kim, Sung-Woo;Leen, Ju-Jang;Sugisaka, Masanori
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10b
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    • pp.234-239
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    • 1993
  • Most of the control problem is for the redundant manipulators use the pseudo-inverse control, thit is, the redundancy is resolved by the pseudo-inverse of the Jacobian matrix and then the controller is designed based on this resolution. However, this pseudo-inverse control has some problems when the redundant robot repeats the cyclic tasks. This is because the pseudo-inverse resolution is a local solution that generates the different configurations of the robot arm for the same hand position. Therefore it is necessary to find the global solution that maintains the optimal configuration of the robot for the repetitive tasks. In this paper, we want to propose a redundancy resolution method by the optimal theory that uses the calculus of variation. The problem formulations are : first to convert the optimal resolution problem to an optimal control problem and then to resolve the redundancy using the necessary conditions of optimal control.

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Comparison of Regularization Techniques For an Inverse Radiation Boundary Analysis (역복사경계해석을 위한 다양한 조정기법 비교)

  • Kim, Ki-Wan;Baek, Seung-Wook
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.1288-1293
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    • 2004
  • Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach of adopting the genetic algorithm as an initial value selector, whereas using the conjugate-gradient method and Newton method to reduce their dependence on the initial value.

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Delayed Hopfield-like Neural Network for Solving Inverse Radiation Transport Problem

  • Lee, Sang-Hoon;Cho, Nam-Zin
    • Proceedings of the Korean Nuclear Society Conference
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    • 1996.11a
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    • pp.21-26
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    • 1996
  • The identification of radioactive source in a medium with a limited number of external detectors is introduced as an inverse radiation transport problem. This kind of inverse problem is usually ill-posed and severely under-determined, however, its applications are very useful in manu fields including medical diagnosis and nondestructive assay of nuclear materials. Therefore, it is desired to develop efficient and robust solution algorithms. As an approach to solving inverse problems, an artificial neural network is proposed. We develop a modified version of the conventional Hopfield neural network and demonstrate its efficiency and robustness.

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An inverse hyperbolic theory for FG beams resting on Winkler-Pasternak elastic foundation

  • Sayyad, Atteshamuddin S.;Ghugal, Yuwaraj M.
    • Advances in aircraft and spacecraft science
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    • v.5 no.6
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    • pp.671-689
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    • 2018
  • Bending, buckling and free vibration responses of functionally graded (FG) higher-order beams resting on two parameter (Winkler-Pasternak) elastic foundation are studied using a new inverse hyperbolic beam theory. The material properties of the beam are graded along the thickness direction according to the power-law distribution. In the present theory, the axial displacement accounts for an inverse hyperbolic distribution, and the transverse shear stress satisfies the traction-free boundary conditions on the top and bottom surfaces of the beams. Hamilton's principle is employed to derive the governing equations of motion. Navier type analytical solutions are obtained for the bending, bucking and vibration problems. Numerical results are obtained to investigate the effects of power-law index, length-to-thickness ratio and foundation parameter on the displacements, stresses, critical buckling loads and frequencies. Numerical results by using parabolic beam theory of Reddy and first-order beam theory of Timoshenko are specially generated for comparison of present results and found in excellent agreement with each other.

Comparison of Regularization Techniques for an Inverse Radiation Boundary Analysis (역복사경계해석을 위한 다양한 조정법 비교)

  • Kim, Ki-Wan;Shin, Byeong-Seon;Kil, Jeong-Ki;Yeo, Gwon-Koo;Baek, Seung-Wook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.29 no.8 s.239
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    • pp.903-910
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    • 2005
  • Inverse radiation problems are solved for estimating the boundary conditions such as temperature distribution and wall emissivity in axisymmetric absorbing, emitting and scattering medium, given the measured incident radiative heat fluxes. Various regularization methods, such as hybrid genetic algorithm, conjugate-gradient method and finite-difference Newton method, were adopted to solve the inverse problem, while discussing their features in terms of estimation accuracy and computational efficiency. Additionally, we propose a new combined approach that adopts the hybrid genetic algorithm as an initial value selector and uses the finite-difference Newton method as an optimization procedure.

Inverse Analysis Approach to Flow Stress Evaluation by Small Punch Test (소형펀치 시험과 역해석에 의한 재료의 유동응력 결정)

  • Cheon, Jin-Sik
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.7 s.178
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    • pp.1753-1762
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    • 2000
  • An inverse method is presented to obtain material's flow properties by using small punch test. This procedure employs, as the objective function of inverse analysis, the balance of measured load-di splacement response and calculated one during deformation. In order to guarantee convergence to global minimum, simulated annealing method was adopted to optimize the current objective function. In addition, artificial neural network was used to predict the load-displacement response under given material parameters which is the most time consuming and limits applications of global optimization methods to these kinds of problems. By implementing the simulated annealing for optimization along with calculating load-displacement curve by neural network, material parameters were identified irrespective of initial values within very short time for simulated test data. We also tested the present method for error-containing experimental data and showed that the flow properties of material were well predicted.

Finite Element Analysis of Functionally Graded Plates using Inverse Hyperbolic Shear Deformation Theory

  • Kulkarni, Kamlesh;Singh, Bhrigu Nath;Maiti, Dipak Kumar
    • International Journal of Aerospace System Engineering
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    • v.3 no.1
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    • pp.1-4
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    • 2016
  • Functionally graded materials (FGMs) are becoming very popular in various industries due to their effectiveness of the utilization of their constituent elements. However, the modelling of these materials is difficult due to the complex nature of variation of material properties across the thickness. Many shear deformation theories have been developed and employed for the analysis of such functionally graded plates (FGPs). A recently developed inverse hyperbolic shear deformation theory has been successfully employed by Grover et al. [1] for the analysis of laminated composites and sandwich plates. The objective of the study is to obtain finite element solution for the structural analysis of functionally graded plates using inverse hyperbolic shear deformation theory. Finite element analysis facilitates the analysis of complex problems such as functionally graded plates with different boundary conditions and different loadings.

Variational Data Assimilation for Optimal Initial Conditions in Air Quality Modeling

  • Park, Seon-Ki
    • Journal of Korean Society for Atmospheric Environment
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    • v.19 no.E2
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    • pp.75-81
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    • 2003
  • Variational data assimilation, which is recently introduced to the air quality modeling, is a promising tool for obtaining optimal estimates of initial conditions and other important parameters such as emission and deposition rates. In this paper. two advanced techniques for variational data assimilation, based on the adjoint and quasi-inverse methods, are tested for a simple air quality problem. The four-dimensional variational assimilation (4D-Var) requires to run an adjoint model to provide the gradient information in an iterative minimization process, whereas the inverse 3D-Var (I3D-Var) seeks for optimal initial conditions directly by running a quasi -inverse model. For a process with small dissipation, I3D-Vu outperforms 4D-Var in both computing time and accuracy. Hybrid application which combines I3D-Var and standard 4D-Var is also suggested for efficient data assimilation in air quality problems.