• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.653-662
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• 2014

The data repositories for structural experiment information needs to be efficient to use in order to allow structural engineers and researchers to store and retrieve easily the information involved in the structural experiments. The data repositories can be evaluated in terms of the organization of the data repositories themselves and of the organization of the actual experiment information in the data repositories, which can be represented using classes and objects with their attributes. This paper proposes the evaluation criteria of attributes of the classes and objects. The evaluation criteria of the attributes of the classes, such as the number of attributes in class and the numbers of the data-valued and object entity-valued attributes, are used for understanding the complexity of the organization of the data repositories. The evaluation criteria of the attributes of the objects, such as the number of valued attributes in object, are used for describing how the actual experiment information is stored through the levels in the data repositories for the structural experiment information.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.6
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• pp.579-588
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• 2015

The data model for structural experiment information formally organizes the information involved in the structural experiments before the data repository using the data model is implemented. The data model is particularly required for the data repositories for the large-scale structural experiment information and the general information for various types of experiments, such as the NEEShub Project Warehouse developed by NEES. This paper proposes criteria for evaluating the organization and the use of design model for structural experiment information. The term of AVE(attribute value existence) indicates the ratio of attributes who values exist in objects, and then used for defining the Attribute AVE for the use of an attribute, the Class AVE for a class, the Class Level AVE for a class including its lower-level classes, the Project AVE for a project including all classes at class levels, and the Data Model AVE for a data model including projects. These criteria are applied to the projects in the NEES data model, and it is successively possible to numerically describe the evaluation of the use of classes and attributes in the data model.

• 한국공간정보시스템학회:학술대회논문집
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• 2004.05a
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• pp.197-205
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• 2004

A vocabulary for a understanding bridge has a different scope. There are the urban setting, landscape, lightness, from minimum to maximum, continuity, material, erection, motion and dynamic. Aesthetics criteria of footbridge design are movement and grace, space and experiment, symbolism, iconic, sculpture, innovation, spectacle, lighting, gemetry and wonder. New structural concepts of pedestrian bridges are presented on examples of recently built structures. The main characteristics of described structures are appropriateness, humanity, structural efficiency and aesthetics.

• Structural Engineering and Mechanics
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• v.74 no.6
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• pp.771-787
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• 2020

The paper provides an inside look into experimental measurements, followed by numerical simulations and their related uncertainties. The goal of the paper is to present findings related to blast loading and the handling of defects that are inherent in experiments. Very often it might seem that experiments are simplified reflections of real-life conditions. In most cases this is true, but there is a good reason for that. The more complex an experiment is, the larger the amount of uncertainties that can be expected. This especially applies when the blast loading of concrete is the subject of research. When simulations fail to reproduce the results of experimental measurements, it does not necessarily mean there is something wrong with the numerical model. The problem could be missing information. Put differently, the numerical simulation may lack information that seemed irrelevant with regard to the experiment. In the presented case, a reference simulation with a proven material model unexpectedly failed to replicate the results of an experiment where concrete slabs were exposed to blast loading. This resulted in a search for possible unknowns. When all of the uncertainties were examined, the missing information turned out to be the orientation of the charge to the concrete slab. Since the experiment was burdened with error, a sensitivity study had to take place so the influence of this factor could be better understood. The findings point to the fact that even the smallest defect during experiments must somehow be taken into account when designing numerical simulations. Otherwise, the simulations are not correlated to the experiments, but merely to some expectations.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.5
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• pp.391-401
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• 2009

The hybrid approach for structural experiments decomposes a structure into independent substructures that can be tested or simulated. The results from the decomposed substructures are combined to predict the behaviors of the entires structure. The hybrid approach is especially useful for the hybrid pseudo-dynamic tests that overcome the limitations of size of a test structure present in a shaking table test. The development of a computer system for the hybrid experiment requires a data model that formally organizes the information involved in the hybrid experiments. This paper provides the data model for representing the information involved in the hybrid experiments, by modifying the classes and attributes for the hybrid experiments in the Lehigh Model that is one of the data models for structural experiments. The data model for the hybrid experiments includes the classes for the physical substructures being tested and the analytical substructures being analyzed, and the simulation coordinator managing the overall experiments. Some objects for classes are implemented as an example to show the links among the classes. The data model presented in this paper can be applied for developing a computer system that helps structural engineers and researchers store, share, and access the information for the hybrid experiments.

• Interdisciplinary Bio Central
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• v.2 no.2
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• pp.3.1-3.4
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• 2010

In the present research, we assessed the utility of the structural information of drugs for predicting human in vivo intrinsic clearance from in vitro intrinsic clearance data obtained by human hepatic microsome experiment. To compare with the observed intrinsic clearance, human intrinsic clearance values for 51 drugs were estimated by the classical methods using in vivo-in vitro scale-up and by the new methods using the in vitro experimental data and selected molecular descriptors of drugs by the forward selection technique together. The results showed that taking consideration of molecular descriptors into prediction from in vitro experimental data could improve the prediction accuracy. The in vitro experiment is very useful when the data can estimate in vivo data accurately since it can reduce the cost of drug development. Improvement of prediction accuracy in the present approach can enhance the utility of in vitro data.

• 한국연소학회:학술대회논문집
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• 2012.04a
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• pp.217-219
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• 2012

This study describes 3D RANS simulation of a 2.1 MW swirling pulverized coal flame in a semi-industrial scale furnace. The simulation of pulverized coal combustion involves various models for complex physical processes and needs information of pyrolysis rate, the yields and compositions of volatiles and char especially in coal conversion. The coal conversion information can be acquired by the experiment or the pre-processor code. The empirical model based on the experiment of the IFRF and the structural model based on the pre-processor code of the PC-COAL-LAB were evaluated against the measurement data.

• Smart Structures and Systems
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• v.16 no.1
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• pp.47-65
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• 2015

A novel finite element (FE) model updating method based on multi-resolution analysis (MRA) is proposed. The true stiffness of the FE model is considered as the superposition of two pieces of stiffness information of different resolutions: the pre-defined stiffness information and updating stiffness information. While the resolution of former is solely decided by the meshing density of the FE model, the resolution of latter is decided by the limited information obtained from the experiment. The latter resolution is considerably lower than the former. Second generation wavelet is adopted to describe the updating stiffness information in the framework of MRA. This updating stiffness in MRA is realized at low level of resolution, therefore, needs less number of updating parameters. The efficiency of the optimization process is thus enhanced. The proposed method is suitable for the identification of multiple irregular cracks and performs well in capturing the global features of the structural damage. After the global features are identified, a refinement process proposed in the paper can be carried out to improve the performance of the MRA of the updating information. The effectiveness of the method is verified by numerical simulations of a box girder and the experiment of a three-span continues pre-stressed concrete bridge. It is shown that the proposed method corresponds well to the global features of the structural damage and is stable against the perturbation of modal parameters and small variations of the damage.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.2
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• pp.7-14
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• 2015

This paper deals with an optimal determination process for the built-in location of localizer under restrictive siting area conditions of a domestic P-airport. Aerodynamic forces and moments acting on the localizer structure can be used a reference to find the safe distance from jet blast and the position at which the reasonable structural loading is applied. Wind tunnel experiment is conducted to measure aerodynamic loadings. The finite element analysis for structural deformation is employed to get the information of structural failure. A new localizer's position is determined by considering aerodynamic loading, structural strength and thermal loading due to jet blast. Deflector effect was also investigated in this study. In conclusion, the location of localizer can be placed at shorter than the current position and greatly decreased if the deflector is applied at the front of localizer.