• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.487-495
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• 2023

Ammonia is either a crucial resource of fertilizer production for solving the food problem of mankind or an important energy source as both an eco-friendly hydrogen carrier and a carbon-free fuel. Therefore, nowadays ammonia synthesis and decomposition become promising. Then, a catalyst is required to effectively perform the ammonia synthesis and decomposition. In order to design high-performing as well as cheap novel catalysts for ammonia synthesis and decomposition, it is necessary to test huge amount of catalyst candidates, but it is inevitably time-consuming and expensive to search and analyze using only traditional approaches. Recently, new methods using machine learning which is one of the core technologies of the 4th industrial revolution that can quickly and accurately search high-performance catalysts has been emerging. In this paper, we investigate reaction mechanisms of ammonia synthesis and decomposition, and we described recent research and prospects of machine learning-driven methods that can efficiently find high-performing and economical catalysts for ammonia synthesis and decomposition.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.534-535
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• 2009

This paper deals with BEM analysis of transient elastodynamic problems using domain decomposition method and particular integrals. The particular method is used to approximate the acceleration term in the governing equation. The domain decomposition method is examined to consider multi-region problems. The domain of the original problem is subdivided into sub-regions, which are modeled by the particular integral BEM. The iterative coupling employing Schwarz algorithm is used for the successive update of the interface boundary conditions until convergence is achieved. The numerical results, compared with those by ABAQUS, demonstrate the validity of the present formulation.

• Journal of applied mathematics & informatics
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• v.10 no.1_2
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• pp.193-207
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• 2002

The present investigation deals with the pulsatile flow of incompressible viscous fluid through a circular rigid tube provided with constriction. The method applied here is the Decomposition Method, which has been developed by George Adomian [3]. The advantages of this method are the avoidance of simplifications and restrictions, which change the non-linear problem to mathematically tractable one, whose solution is not consistent with physical solution. Theoretically results, such as, wall shear stress and axial velocity component, have been obtained and the graphical solutions of these theoretical results have been shown in the figures.

• Journal of computational fluids engineering
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• v.3 no.1
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• pp.22-29
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• 1998

Parallel implementation is conducted for a SIMPLER finite volume model. The present parallelism is based on domain decomposition and explicit message passing using MPI and SHMEM. Two parallel solvers to tridiagonal matrix equation are employed. The implementation is verified on the Cray T3E system for a benchmark problem of natural convection in a sidewall-heated cavity. The test results illustrate good scalability of the present parallel models. Performance issues are elaborated in view of convergence as well as conventional parallel overheads and single processor performance. The effectiveness of a localized matrix solution algorithm is demonstrated.

• Smart Structures and Systems
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• v.11 no.1
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• pp.123-134
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• 2013

Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.36-39
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• 1996

In chemical processes, measurement errors reduce the credibility of information and cause inconsistency in material and energy balances. Because multicomposition flows and temperature measurements make material and energy balances nonlinear equations, data reconciliation becomes a nonlinear constrained optimization problem. In multicomposition processes, if we follow general optimization procedure, the number of measurement variables is so large that data reconciliation requires much computation time. We propose the decomposition procedure to reduce the computation time without the decrease of accuracy of data reconciliation. Decomposition procedure finds global variables, that can reduce the nonlinearity of constraints, and divides two sub-optimization problems. Once we optimize the global variables at upper level, we can easily optimize the remain variables at tower level, We can obtain the short computational time and the same accuracy as SQP optimization method.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.491-496
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• 2003

In sensitivity analysis, semi-analytical method(SAM) reveals severe inaccuracy problem when relatively large rigid body motions are identified for individual elements. Recently such errors of SAM resulted by the finite difference scheme have been improved by the separation of rigid body mode. But the eigenvalue should be obtained first before the sensitivity analysis is performed and it takes much time in the case that large system is considered. In the present study, by constructing a reduced one from the original system, iterative method combined with mode decomposition technique is proposed to compute reliable semi-analytical design sensitivities. The sensitivity analysis is performed by the eigenvector acquired from the reduced system. The error of SAM caused by difference scheme is alleviated by Von Neumann series approximation.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1265-1270
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• 1990

A prototype integrated system and its theories for distributed SISO control structure synthesis of complete chemical plants is developed. The scope of this work includes control structure synthesis not only of simple units with unspecified control loops but also of the complex process at preliminary and basic design stage. Hierarchical approach and dual-decomposition strategy (that is multi-layer decomposition and multi-echelon decomposition) is applied to this system. Because automatic control structure synthesis of complex plants is a problem defined as a series of knowledge-intensive tasks within multiple spaces, the established methodology is complemented by not only techniques from knowledge-based expert systems but also shortcut and rigorous control theories. This system is used for education of control designers, process engineers, operators and students as well as for operability studying, in-line and on-line process control structure synthesis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1846-1863
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• 2016

High dynamic range (HDR) images can present the perfect real scene and rich color information. A commonly encountered problem in practical applications is how to well visualize HDR images on standard display devices. In this paper, we propose a multi-scale decomposition method using guided filtering for HDR image tone mapping. In our algorithm, HDR images are directly decomposed into three layers：base layer, coarse scale detail layer and fine detail layer. We propose an effective function to compress the base layer and the coarse scale detail layer. An adaptive function is also proposed for detail adjustment. Experimental results show that the proposed algorithm effectively accomplishes dynamic range compression and maintains good global contrast as well as local contrast. It also presents more image details and keeps high color saturation.

• Wind and Structures
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• v.3 no.2
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• pp.97-115
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• 2000

The technique of proper orthogonal decomposition is potentially useful in specifying the fluctuating surface pressure field around structures. However there has been a degree of controversy over whether or not the calculated modes have physical meanings. This paper addresses this issue through consideration of the results of full scale experiments, and through an analytical investigation. It is concluded that the lower, most energetic modes are likely to reflect different fluctuating flow mechanisms, although no mode is likely to be associated with just one flow mechanism or vice versa. The higher, less energetic modes are likely to represent interactions between different flow mechanisms, and to be significantly affected by the number of measurement points and measurement errors. The paper concludes with a brief description of the application of POD to the problem of building ventilation, and the calculation of cladding pressures.