• Steel and Composite Structures
• /
• v.44 no.5
• /
• pp.651-676
• /
• 2022

Most of the experimental, theoretical, and numerical studies on the stability of functionally graded composites are deterministic, while there are full of complex interactions of variables with an inherently probabilistic nature, this paper presents a non-intrusive framework to investigate the stochastic nonlinear buckling behaviors of porous functionally graded cylindrical shells exposed to inevitable source-uncertainties. Euler-Lagrange equations are theoretically derived based on the three variable refined shear deformation theory. Closed-form solutions for the shell buckling loads are achieved by solving the deterministic eigenvalue problems. The analytical results are verified with numerical results obtained from finite element analyses that are conducted in the commercial software ABAQUS. The non-intrusive framework is completed by integrating the Monte Carlo simulation with the verified closed-form solutions. The convergence studies are performed to determine the effective pseudorandom draws of the simulation. The accuracy and efficiency of the framework are verified with statistical results that are obtained from the first and second-order perturbation techniques. Eleven cases of individual and compound uncertainties are investigated. Sensitivity analyses are conducted to figure out the five cases that have profound perturbative effects on the shell buckling loads. Complete probability distributions of the first three critical buckling loads are completely presented for each profound uncertainty case. The effects of the shell thickness, volume fraction index, and stochasticity degree on the shell buckling load under compound uncertainties are studied. There is a high probability that the shell has non-unique buckling modes in stochastic environments, which should be known for reliable analysis and design of engineering structures.

• New & Renewable Energy
• /
• v.20 no.1
• /
• pp.145-174
• /
• 2024

Addressing climate change necessitates evidence-based policies grounded in science. The use of forest biomass for energy production is based on a broad scientific consensus at the international level. However, some environmental groups in South Korea are opposing this system of energy production. Through this study, the authors aim to reduce unnecessary confusion and foster an atmosphere conducive to meaningful evidence-based policies. We have classified the issue into eight categories: biological carbon cycle, carbon debt, nature-based solutions, air emissions, cascading principles and sustainability certification, forest environmental impacts, climate change litigation, and the behavior of environmental groups and public perception. Consequently, the following key points were derived: (1) the actions of some environmental groups seem to follow a similar pattern to denialist behavior that denies climate change and climate science; (2) the quality of evidence for campaigns that oppose the use of forest biomass for energy production is low, with a tendency to overgeneralize information, high uncertainty, and difficulty in finding new claims.; (3) most of the public believes that forest biomass energy is necessary, and the governments of major countries are aware of its importance. Significantly, Forest biomass for energy is based on an overwhelming level of scientific consensus recognized internationally.

• Journal of The Korean Astronomical Society
• /
• v.36 no.3
• /
• pp.89-95
• /
• 2003

Observations of dark matter dominated dwarf and low surface brightness disk galaxies favor density profiles with a flat-density core, while cold dark matter (CDM) N-body simulations form halos with central cusps, instead. This apparent discrepancy has motivated a re-examination of the microscopic nature of the dark matter in order to explain the observed halo profiles, including the suggestion that CDM has a non-gravitational self-interaction. We study the formation and evolution of self-interacting dark matter (SIDM) halos. We find analytical, fully cosmological similarity solutions for their dynamics, which take proper account of the collisional interaction of SIDM particles, based on a fluid approximation derived from the Boltzmann equation. The SIDM particles scatter each other elastically, which results in an effective thermal conductivity that heats the halo core and flattens its density profile. These similarity solutions are relevant to galactic and cluster halo formation in the CDM model. We assume that the local density maximum which serves as the progenitor of the halo has an initial mass profile ${\delta}M / M {\propto} M^{-{\epsilon}$, as in the familiar secondary infall model. If $\epsilon$ = 1/6, SIDM halos will evolve self-similarly, with a cold, supersonic infall which is terminated by a strong accretion shock. Different solutions arise for different values of the dimensionless collisionality parameter, $Q {\equiv}{\sigma}p_br_s$, where $\sigma$ is the SIDM particle scattering cross section per unit mass, $p_b$ is the cosmic mean density, and $r_s$ is the shock radius. For all these solutions, a flat-density, isothermal core is present which grows in size as a fixed fraction of $r_s$. We find two different regimes for these solutions: 1) for $Q < Q_{th}({\simeq} 7.35{\times} 10^{-4}$), the core density decreases and core size increases as Q increases; 2) for $Q > Q_{th}$, the core density increases and core size decreases as Q increases. Our similarity solutions are in good agreement with previous results of N-body simulation of SIDM halos, which correspond to the low-Q regime, for which SIDM halo profiles match the observed galactic rotation curves if $Q {\~} [8.4 {\times}10^{-4} - 4.9 {\times} 10^{-2}]Q_{th}$, or ${\sigma}{\~} [0.56 - 5.6] cm^2g{-1}$. These similarity solutions also show that, as $Q {\to}{\infty}$, the central density acquires a singular profile, in agreement with some earlier simulation results which approximated the effects of SIDM collisionality by considering an ordinary fluid without conductivity, i.e. the limit of mean free path ${\lambda}_{mfp}{\to} 0$. The intermediate regime where $Q {\~} [18.6 - 231]Q_{th}$ or ${\sigma}{\~} [1.2{\times}10^4 - 2.7{\times}10^4] cm^2g{-1}$, for which we find flat-density cores comparable to those of the low-Q solutions preferred to make SIDM halos match halo observations, has not previously been identified. Further study of this regime is warranted.

• Journal of Microbiology and Biotechnology
• /
• v.34 no.5
• /
• pp.1003-1016
• /
• 2024

This study explores the potential of plant-based decellularization in regenerative medicine, a pivotal development in tissue engineering focusing on scaffold development, modification, and vascularization. Plant decellularization involves removing cellular components from plant structures, offering an eco-friendly and cost-effective alternative to traditional scaffold materials. The use of plant-derived polymers is critical, presenting both benefits and challenges, notably in mechanical properties. Integration of plant vascular networks represents a significant bioengineering breakthrough, aligning with natural design principles. The paper provides an in-depth analysis of development protocols, scaffold fabrication considerations, and illustrative case studies showcasing plant-based decellularization applications. This technique is transformative, offering sustainable scaffold design solutions with readily available plant materials capable of forming perfusable structures. Ongoing research aims to refine protocols, assess long-term implications, and adapt the process for clinical use, indicating a path toward widespread adoption. Plant-based decellularization holds promise for regenerative medicine, bridging biological sciences with engineering through eco-friendly approaches. Future perspectives include protocol optimization, understanding long-term impacts, clinical scalability, addressing mechanical limitations, fostering collaboration, exploring new research areas, and enhancing education. Collectively, these efforts envision a regenerative future where nature and scientific innovation converge to create sustainable solutions, offering hope for generations to come.

• Nuclear Engineering and Technology
• /
• v.53 no.7
• /
• pp.2084-2094
• /
• 2021

Delta-form-based methods for solving high order spatial discretization schemes are introduced into the reactor S_N transport equation. Due to the nature of the delta-form, the final numerical accuracy only depends on the residuals on the right side of the discrete equations and have nothing to do with the parts on the left side. Therefore, various high order spatial discretization methods can be easily adopted for only the transport term on the right side of the discrete equations. Then the simplest step or other robust schemes can be adopted to discretize the increment on the left hand side to ensure the good iterative convergence. The delta-form framework makes the sweeping and iterative strategies of various high order spatial discretization methods be completely the same with those of the traditional S_N codes, only by adding the residuals into the source terms. In this paper, the flux limiter method and weighted essentially non-oscillatory scheme are used for the verification purpose to only show the advantages of the introduction of delta-form-based solving methods and other high order spatial discretization methods can be also easily extended to solve the S_N transport equations. Numerical solutions indicate the correctness and effectiveness of delta-form-based solving method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.12
• /
• pp.1748-1755
• /
• 2015

A linear regression is widely used for prediction problem, but it is hard to manage an irregular nature of nonlinear system. Although nonlinear regression methods have been adopted, most of them are only fit to low and limited structure problem with small number of independent variables. However, real-world problem, such as weather prediction required complex nonlinear regression with large number of variables. GP(Genetic Programming) based evolutionary nonlinear regression method is an efficient approach to attach the challenging problem. This paper introduces the improvement of an GP based nonlinear regression method using ADF(Automatically Defined Function). It is believed ADFs allow the evolution of modular solutions and, consequently, improve the performance of the GP technique. The suggested ADF based GP nonlinear regression methods are compared with UM, MLR, and previous GP method for 3 days prediction of wind speed using MOS(Model Output Statistics) for partial South Korean regions. The UM and KLAPS data of 2007-2009, 2011-2013 years are used for experimentation.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.156-163
• /
• 2001

Business forecasting is vital to the success of business. There has been an increasing demand for building business forecasting software system to assist human being to do forecasting. However, the uncertain and complex nature makes is a challenging work to analyze, design and implement software solutions for business forecasting. Traditional forecasting systems in which their models are trained based on small collection of historical data could not meet such challenges at the information explosion over the Internet. This paper presents an agent oriented business forecasting approach for building intelligent business forecasting software systems with high reusability. Although agents have been applied successfully to many application domains. little work has been reported to use the emerging agent oriented technology of this paper is that it explores how agent can be used to help human to manage various business forecasting processes in the whole business forecasting life cycle.

• Journal of Information Processing Systems
• /
• v.14 no.2
• /
• pp.455-468
• /
• 2018

The concepts of graph theory are applied to model and analyze dynamics of computer networks, biochemical networks and, semantics of social networks. The analysis of dynamics of complex networks is important in order to determine the stability and performance of networked systems. The analysis of non-stationary and nonlinear complex networks requires the applications of ordinary differential equations (ODE). However, the process of resolving input excitation to the dynamic non-stationary networks is difficult without involving external functions. This paper proposes an analytical formulation for generating solutions of nonlinear network ODE systems with functional decomposition. Furthermore, the input excitations are analytically resolved in linearized dynamic networks. The stability condition of dynamic networks is determined. The proposed analytical framework is generalized in nature and does not require any domain or range constraints.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06d
• /
• pp.294-296
• /
• 2012

In cognitive radio ad hoc networks, secondary users need to exchange control information before data transmission. This task is not trivial in cognitive radio networks due to the dynamic nature of environment. This problem is sometime called rendezvous problem of cognitive radio network. The rendezvous problem is normally tackled by using two famous approaches: the use of common control channel (CCC) and using channel hopping (a.k.a sequence-based protocols). However, these two famous solutions form a vicious cycle while solving the rendezvous problem. The main purpose of this paper is to point out how and why this vicious cycle is formed.

• Korean Journal of Computational Design and Engineering
• /
• v.2 no.1
• /
• pp.44-52
• /
• 1997

A design process is difficult to describe comprehensively because a design problem has a multi-disciplinary nature and the design itself evolves as solutions are attempted by the designer. The process of design has been investigated in this paper with the purpose of characterizing the role that a system of this kind may have. In defining the system, an approach has been used that privileges the relationships with the existing CAD tools based on data exchange standards in course of definition today. Integrated design environment normally consists of a centralized data model a data management system and a set of CAD tools. In this study, all further investigations are directed towards the data management system, as one of the main components of the proposed environment. Moreover, product modeling, as a prerequisite for the data management core, is taken into special consideration.