• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.8 s.179
• /
• pp.1949-1957
• /
• 2000

All the loads in the real world act dynamically on structures. Since dynamic loads are extremely difficult to handle in analysis and design, static loads are utilized with dynamic factors. The dyna mic factors are generally determined based on experiences. Therefore, the static loads can cause problems in precise analysis and design. An analytical method based on modal analysis has been proposed for the transformation of dynamic loads into equivalent static load sets. Equivalent static load sets are calculated to generate an identical displacement field in a structure with that from dynamic loads at a certain time. The process is derived and evaluated mathematically. The method is verified through numerical tests. Various characteristics are identified to match the dynamic and the static behaviors. For example, the opposite direction of a dynamic load should be considered due to the vibration response. A dynamic bad is transformed to multiple equivalent static loads according to the number of the critical times. The places of the equivalent static load can be different from those of the dynamic load. An optimization method is defined to use the equivalent static loads. The developed optimization process has the same effect as the dynamic optimization which uses the dynamic loads directly. Standard examples are solved and the results are discussed

• Steel and Composite Structures
• /
• v.32 no.4
• /
• pp.455-466
• /
• 2019

Despite the rapid advancement in computing resources, many real-life design and optimization problems in structural engineering involve huge computation costs. To counter such challenges, approximate models are often used as surrogates for the highly accurate but time intensive finite element models. In this paper, surrogates for first-order shear deformation based finite element models are built using a polynomial regression approach. Using statistical techniques like Box-Cox transformation and ANOVA, the effectiveness of the surrogates is enhanced. The accuracy of the surrogate models is evaluated using statistical metrics like $R^2$, $R^2{_{adj}}$, $R^2{_{pred}}$ and $Q^2{_{F3}}$. By combining these surrogates with nature-inspired multi-criteria decision-making algorithms, namely multi-objective genetic algorithm (MOGA) and multi-objective particle swarm optimization (MOPSO), the optimal combination of various design variables to simultaneously maximize fundamental frequency and frequency separation is predicted. It is seen that the proposed approach is simple, effective and good at inexpensively producing a host of optimal solutions.

• Smart Structures and Systems
• /
• v.31 no.4
• /
• pp.409-419
• /
• 2023

Structural integrity can be accessed from dynamic deformations of structures. Moreover, dynamic deformations can be acquired from non-contact sensors such as video cameras. Kanade-Lucas-Tomasi (KLT) algorithm is one of the commonly used methods for motion tracking. However, averaging throughout the extracted features would induce bias in the measurement. In addition, pixel-wise measurements can be converted to physical units through camera intrinsic. Still, the depth information is unreachable without prior knowledge of the space information. The assigned homogeneous coordinates would then mismatch manually selected feature points, resulting in measurement errors during coordinate transformation. In this study, a two-stage optimization method for video-based measurements is proposed. The manually selected feature points are first optimized by minimizing the errors compared with the homogeneous coordinate. Then, the optimized points are utilized for the KLT algorithm to extract displacements through inverse projection. Two additional criteria are employed to eliminate outliers from KLT, resulting in more reliable displacement responses. The second-stage optimization subsequently fine-tunes the geometry of the selected coordinates. The optimization process also considers the number of interpolation points at different depths of an image to reduce the effect of out-of-plane motions. As a result, the proposed method is numerically investigated by using a truss bridge as a physics-based graphic model (PBGM) to extract high-accuracy displacements from recorded videos under various capturing angles and structural conditions.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.2 s.314
• /
• pp.93-101
• /
• 2007

To jointly optimize the spatial registration and the exposure compensation, an iterative registration algorithm, the Lucas-Kanade algorithm, is combined with an exposure compensation algorithm, which is based on the histogram transformation function. Based on a simple regression model, a nonparametric estimator, the empirical conditional mean, and its polynomial fitting are used as histogram transformation functions for the exposure compensation. Since the proposed algorithm is composed of separable optimization phases, the proposed algorithm is more advantageous than the joint approaches of Mann and Candocia in the aspect of implementation flexibility. The proposed algorithm performs a better registration for real images than the case of registration that does not consider the exposure difference.

• Smart Structures and Systems
• /
• v.26 no.5
• /
• pp.591-603
• /
• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• Journal of IKEEE
• /
• v.15 no.1
• /
• pp.10-14
• /
• 2011

In this paper, we present an efficient hardware architecture of unrolling image mapper of catadioptric omnidirectional imaging systems. The catadioptric omnidirectional imaging systems generate images of 360 degrees of view and need to be transformed into panorama images in rectangular coordinate. In most application, it has to perform the panorama unrolling in real-time and at low-cost, especially for high-resolution images. The proposed hardware architecture adopts a software/hardware cooperative structure and employs several optimization schemes using look-up-table(LUT) of coordinate conversion. To avoid the on-line division operation caused by the coordinate transformation algorithm, the proposed architecture has the LUT which has pre-computed division factors. And then, the amount of memory used by the LUT is reduced to 1/4 by using symmetrical characteristic compared with the conventional architecture. Experimental results show that the proposed hardware architecture achieves an effective real-time performance and lower implementation cost, and it can be applied to other kinds of catadioptric omnidirectional imaging systems.

• ETRI Journal
• /
• v.36 no.1
• /
• pp.124-133
• /
• 2014

To speed up data-intensive programs, two complementary techniques, namely nested loops parallelization and data locality optimization, should be considered. Effective parallelization techniques distribute the computation and necessary data across different processors, whereas data locality places data on the same processor. Therefore, locality and parallelization may demand different loop transformations. As such, an integrated approach that combines these two can generate much better results than each individual approach. This paper proposes a unified approach that integrates these two techniques to obtain an appropriate loop transformation. Applying this transformation results in coarse grain parallelism through exploiting the largest possible groups of outer permutable loops in addition to data locality through dependence satisfaction at inner loops. These groups can be further tiled to improve data locality through exploiting data reuse in multiple dimensions.

• Journal of Microbiology and Biotechnology
• /
• v.20 no.1
• /
• pp.39-44
• /
• 2010

Acidithiobacillus caldus is an acidophilic, chemolithotrophic bacterium that plays an important role in bioleaching. Gene transformation into A. caldus is difficult, and only the conjugation method was reported successful, which was a relatively sophisticated method. In this research, electrotransformation of A. caldus species was achieved for the first time using A. caldus Y-3 and plasmid pJRD215. Transformants were confirmed by colony PCR specific to the str gene on pJRD215, and the recovery of the plasmid from the presumptive transformants. Optimizations were made and the transformation efficiency was increased from 0.8 to $3.6{\times}10^4$ transformants/${\mu}g$ plasmid DNA. The developed electrotransformation method was convenient in introducing foreign genes into A. caldus.

• Proceedings of the KWS Conference
• /
• 2002.10a
• /
• pp.366-371
• /
• 2002

Because of the environmental problems, automotive companies are trying to reduce the weight of car body. Therefore, TRIP(TRansformation Induced Plasticity) steels, which have high strength and ductility have been developed. Welding process is a complex process; therefore deciding the optimal welding conditions on the basis of experimental data is an effective method. However, trial-and-error method to decide the optimal conditions requires too many experiments. To overcome these problems, response surface methodology was used. Response surface methodology is a collection of mathematical and statistical techniques that are used in the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. This method was applied to the resistance spot welding process of the TRIP steel to optimize the welding parameters.

• YAKHAK HOEJI
• /
• v.32 no.6
• /
• pp.386-393
• /
• 1988

Chemical transformation of D-glucose to 2-keto-L-gulonic acid and L-ascorbic acid has been examined. D-Sorbitol obtained from D-glucose was microbiologically oxidized to L-sorbose by G. suboxydans in 90% yield. On treatment of L-sorbose with acetone in the presence of sulfuric acid, its diacetonide is obtained in 95% yield. This diacetonide is oxidized to the corresponding acid with nickel chloride-hypochlorite, and the acid is directly transformed to L-ascorbic acid. The over all yield of Vitamin C from D-glucose achieved is 54%.