• Title/Summary/Keyword: Automatic Differentiation

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Full Waveform Inversion Using Automatic Differentiation (자동 미분을 이용한 전파형 역산)

  • Wansoo, Ha
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.242-251
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    • 2022
  • Automatic differentiation automatically calculates the derivatives of a function using the chain rule once the forward operation of a function is defined. Given the recent development of computing libraries that support automatic differentiation, many researchers have adopted automatic differentiation techniques to solve geophysical inverse problems. We analyzed the advantages, disadvantages, and performances of automatic differentiation techniques using the gradient calculations of seismic full waveform inversion objective functions. The gradients of objective functions can be expressed as multiplications of the derivatives of the model parameters, wavefields, and objective functions using the chain rule. Using numerical examples, we demonstrated the speed of analytic differentiation and the convenience of complex gradient calculations for automatic differentiation. We calculated derivatives of model parameters and objective functions using automatic differentiation and derivatives of wavefields using analytic differentiation.

Improvement of Sensitivity Based Concurrent Subspace Optimization Using Automatic Differentiation (자동미분을 이용한 민감도기반 분리시스템동시최적화기법의 개선)

  • Park, Chang-Gyu;Lee, Jong-Su
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.2
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    • pp.182-191
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    • 2001
  • The paper describes the improvement on concurrent subspace optimization(CSSO) via automatic differentiation. CSSO is an efficient strategy to coupled multidisciplinary design optimization(MDO), wherein the original design problem is non-hierarchically decomposed into a set of smaller, more tractable subspaces. Key elements in CSSO are consisted of global sensitivity equation, subspace optimization, optimum sensitivity analysis, and coordination optimization problem that require frequent use of 1st order derivatives to obtain design sensitivity information. The current version of CSSO adopts automatic differentiation scheme to provide a robust sensitivity solution. Automatic differentiation has numerical effectiveness over finite difference schemes tat require the perturbed finite step size in design variable. ADIFOR(Automatic Differentiation In FORtran) is employed to evaluate sensitivities in the present work. The use of exact function derivatives facilitates to enhance the numerical accuracy during the iterative design process. The paper discusses how much the automatic differentiation based approach contributes design performance, compared with traditional all-in-one(non-decomposed) and finite difference based approaches.

An Adaptive Photon Mapping in the Use of Automatic Differentiation

  • Namae, Takuya;Makino, Mitsunori
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.991-994
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    • 2002
  • Photon mapping is an efficient global illumination technique for realistic image synthesis that has been developed in computer graphics. In this paper, an adaptive photon mapping in the use of automatic differentiation is proposed. Since the automatic differentiation is used when photons emit from the light sources through the scene, we can check the variation of surrounding shape. Therefore, we can decrease the number of photons and generate an image in relatively low computational cost.

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Application of the Automatic Differentiation to Aerodynamic Design Optimization (자동미분의 공력최적설계 적용)

  • Lee Jaehun;Kim Suwhan;Ahn Joongki;Kwon Jang Hyuk
    • 한국전산유체공학회:학술대회논문집
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    • 2004.10a
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    • pp.181-186
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    • 2004
  • In gradient based optimization methods, the finite differencing which uses small perturbations in the design variables has been used to calculate the sensitivity. Recently, the automatic differentiation has been widely studied to calculate the function value and the sensitivities simultaneously. In this paper, the applicability of the automatic differentiation In the aerodynamic design optimization is studied. ADIFOR and TAPENADE are used to generate the codes which give the function value and the sensitivities for 2D compressible inviscid flows.

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Improved Concurrent Subspace Optimization Using Automatic Differentiation (자동미분을 이용한 분리시스템동시최적화기법의 개선)

  • 이종수;박창규
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1999.10a
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    • pp.359-369
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    • 1999
  • The paper describes the study of concurrent subspace optimization(CSSO) for coupled multidisciplinary design optimization (MDO) techniques in mechanical systems. This method is a solution to large scale coupled multidisciplinary system, wherein the original problem is decomposed into a set of smaller, more tractable subproblems. Key elements in CSSO are consisted of global sensitivity equation(GSE), subspace optimization (SSO), optimum sensitivity analysis(OSA), and coordination optimization problem(COP) so as to inquiry valanced design solutions finally, Automatic differentiation has an ability to provide a robust sensitivity solution, and have shown the numerical numerical effectiveness over finite difference schemes wherein the perturbed step size in design variable is required. The present paper will develop the automatic differentiation based concurrent subspace optimization(AD-CSSO) in MDO. An automatic differentiation tool in FORTRAN(ADIFOR) will be employed to evaluate sensitivities. The use of exact function derivatives in GSE, OSA and COP makes Possible to enhance the numerical accuracy during the iterative design process. The paper discusses how much influence on final optimal design compared with traditional all-in-one approach, finite difference based CSSO and AD-CSSO applying coupled design variables.

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Study on the Applications of Automatic Differentiation in Engineering Computation (자동 미분의 공학 계산 적용 연구)

  • Lee, Jae-Hun;Im, Dong-Kyun;Kwon, Jang-Hyuk
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.7
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    • pp.634-641
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    • 2008
  • Automatic Differentiation(AD) is a tool for generating sensitivities, such as gradient or Jacobian, automatically. AD tools provide mathematically exact sensitivities for the given source code. In this paper applications of automatic differentiation are studied. Derivative codes are generated with AD tools for structural analysis code and flow analysis code. How to apply AD tools is explained and the accuracy of sensitivities is compared with the finite difference. Sensitivities of generated derivative code accord well with finite difference, but the calculation time of derivative code increases. It was found that the calculation time can be decreased by additional modification of derivative code.

Inverse Boundary Temperature Estimation in a Two-Dimensional Cylindrical Enclosure Using Automatic Differentiation and Broyden Combined Method (자동미분법과 Broyden 혼합법을 이용한 2차원 원통형상에서의 경계온도 역추정)

  • Kim Ki-Wan;Kim Dong-Min;Baek Seung-Wook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.30 no.3 s.246
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    • pp.270-277
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    • 2006
  • Inverse radiation problems were solved for estimating boundary temperature distribution in a way of function estimation approach in an axisymmetric absorbing, emitting and scattering medium, given the measured radiative data. In order to reduce the computational time fur the calculation of sensitivity matrix, automatic differentiation and Broyden combined method were adopted, and their computational precision and efficiency were compared with the result obtained by finite difference approximation.. In inverse analysis, the effects of the precision of sensitivity matrix, the number of measurement points and measurement error on the estimation accuracy had been inspected using quasi-Newton method as an inverse method. Inverse solutions were validated with the result acquired by additional inverse methods of conjugate-gradient method or Levenberg-Marquardt method.

Multi-Level Optimization of Framed Structures Using Automatic Differentiation (자동미분을 이용한 뼈대구조의 다단계 최적설계)

  • Cho, Hyo-Nam;Chung, Jee-Sung;Min, Dae-Hong;Lee, Kwang-Min
    • Journal of Korean Society of Steel Construction
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    • v.12 no.5 s.48
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    • pp.569-579
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    • 2000
  • An improved multi-level (IML) optimization algorithm using automatic differentiation (AD) of framed structures is proposed in this paper. For the efficiency of the proposed algorithm, multi-level optimization techniques using a decomposition method that separates both system-level and element-level optimizations, that utilizes and an artificial constraint deletion technique, are incorporated in the algorithm. And also to save the numerical efforts, an efficient reanalysis technique through approximated structural responses such as moments and frequencies with respect to intermediate variables is proposed in the paper. Sensitivity analysis of dynamic structural response is executed by AD that is a powerful technique for computing complex or implicit derivatives accurately and efficiently with minimal human effort. The efficiency and robustness of the IML algorithm, compared with a plain multi-level (PML) algorithm, is successfully demonstrated in the numerical examples.

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A Study on the Chemical Pre-Treatments Suitable for the Layer Differentiation of FRP Waste (폐FRP의 층간분리를 위한 전처리방법에 관한 연구)

  • Lee, Seung-Hee;Lee, Jung-Ki;Kim, Yong-Ju
    • Journal of the Korean Society for Marine Environment & Energy
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    • v.15 no.1
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    • pp.47-53
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    • 2012
  • As one of the methods for recycling the FRP from the waste ships, separation of roving layer from the mat has some merits in a sense of the eco-friendly and economical recycling process. Similar characteristics, however, between the roving and the mat even with different ratio of the resin and the glass and the thickness of the roving, much thinner than the mat, make the mechanically automatic differentiation difficult. In this study spectrochemical differentiation between the two layers has been made using boiling concentrated sulfuric acid, methanol and isopropanol solution saturated with KOH, or hydrogen fluoride (HF) solution. Furthermore efficiently coloring water-soluble dye following the HF treatment makes the roving layer more distinguishable photophysically. The layer differentiation and the automatic layer distraction move up the date of simple and automatic separation process for the waste FRP.

A variational Bayes method for pharmacokinetic model (약물동태학 모형에 대한 변분 베이즈 방법)

  • Parka, Sun;Jo, Seongil;Lee, Woojoo
    • The Korean Journal of Applied Statistics
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    • v.34 no.1
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    • pp.9-23
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    • 2021
  • In the following paper we introduce a variational Bayes method that approximates posterior distributions with mean-field method. In particular, we introduce automatic differentiation variation inference (ADVI), which approximates joint posterior distributions using the product of Gaussian distributions after transforming parameters into real coordinate space, and then apply it to pharmacokinetic models that are models for the study of the time course of drug absorption, distribution, metabolism and excretion. We analyze real data sets using ADVI and compare the results with those based on Markov chain Monte Carlo. We implement the algorithms using Stan.