• 한국전산유체공학회:학술대회논문집
• /
• 2003.08a
• /
• pp.158-163
• /
• 2003

This paper assesses the two-equation turbulence models available in a commercial code, FLUENT, for heat transfer in a turbulent heated pipe flow. In case of flow under $Re_D=10,000$, Standard $\kappa-\epsilon$ and Realizable $\kappa-\epsilon$ models overpredict the Nusselt number about $20\%$ compared with the experimental correlation, and RNG $\kappa-\epsilon$ model overpredicts about $30\%$ when the two-layer zonal method is employed. When wall function method is adopted, all $\kappa-\epsilon$ models show better predictions. Standard $\kappa-\omega$ and SST $\kappa-\omega$ models have the dependency on the first grid point ($0.3). As Reynolds number becomes high, the predictions of all $\kappa-\epsilon$ and $\kappa-\omega$ models are in a good agreement with the experimental correlation.

• Journal of Periodontal and Implant Science
• /
• v.52 no.6
• /
• pp.479-495
• /
• 2022

Purpose: Rodent models have emerged as an alternative to established larger animal models for peri-implantitis research. However, the construct validity of rodent models is controversial due to a lack of consensus regarding their histological, morphological, and biochemical characteristics. This systematic review sought to validate rodent models by characterizing their morphological changes, particularly marginal bone loss (MBL), a hallmark of peri-implantitis. Methods: This review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. A literature search was performed electronically using MEDLINE (PubMed), and Embase, identifying pre-clinical studies reporting MBL after experimental peri-implantitis induction in rodents. Each study's risk of bias was assessed using the Systematic Review Center for Laboratory animal Experimentation (SYRCLE) risk of bias tool. A meta-analysis was performed for the difference in MBL, comparing healthy implants to those with experimental peri-implantitis. Results: Of the 1,014 unique records retrieved, 23 studies that met the eligibility criteria were included. Peri-implantitis was induced using 4 methods: ligatures, lipopolysaccharide, microbial infection, and titanium particles. Studies presented high to unclear risks of bias. During the osseointegration phase, 11.6% and 6.4%-11.3% of implants inserted in mice and rats, respectively, had failed to osseointegrate. Twelve studies were included in the meta-analysis of the linear MBL measured using micro-computed tomography. Following experimental peri-implantitis, the MBL was estimated to be 0.25 mm (95% confidence interval [CI], 0.14-0.36 mm) in mice and 0.26 mm (95% CI, 0.19-0.34 mm) in rats. The resulting peri-implant MBL was circumferential, consisting of supra- and infrabony components. Conclusions: Experimental peri-implantitis in rodent models results in circumferential MBL, with morphology consistent with the clinical presentation of peri-implantitis. While rodent models are promising, there is still a need to further characterize their healing potentials, standardize experiment protocols, and improve the reporting of results and methodology.

• Structural Engineering and Mechanics
• /
• v.69 no.6
• /
• pp.677-691
• /
• 2019

In recent years, interest is growing in the engineering community on the experimental assessment and the theoretical prediction of the out-of-plane (OOP) seismic response of unreinforced masonry (URM) infills, which are widespread in Reinforced Concrete (RC) buildings in Europe and in the Mediterranean area. In the literature, some mechanical-based models for the prediction of the entire OOP force-displacement response have been formulated and proposed. However, the small number of experimental tests currently available has not allowed, up to current times, a robust and reliable evaluation of the predictive capacity of such response models. To enrich the currently available experimental database, six pure OOP tests on URM infills in RC frames were carried out at the Department of Structures for Engineering and Architecture of the University of Naples Federico II. Test specimens were built with the same materials and were different only for the thickness of the infill walls and for the number of their edges mortared to the confining elements of the RC frames. In this paper, the results of these experimental tests are briefly recalled. The main aim of this study is comparing the experimental response of test specimens with the prediction of mechanical models presented in the literature, in order to assess their effectiveness and contribute to the definition of a robust and reliable model for the evaluation of the OOP seismic response of URM infill walls.

• Steel and Composite Structures
• /
• v.28 no.2
• /
• pp.251-266
• /
• 2018

Compared to conventional flat web I-beams, the prediction of shear buckling stress of corrugated web steel beams (CWSBs) is not straightforward. But the CWSBs combined advantages of lightweight large spans with low-depth high load-bearing capacities justify dealing with such difficulties. This work investigates experimentally and analytically the shear strength of trapezoidal CWSBs. A set of large scale CWSBs are manufactured and tested to failure in shear. The results are compared with widely accepted CWSBs shear strength prediction models. Confirmed by the experimental results, the linear buckling analyses of trapezoidal corrugated webs demonstrated that the local shear buckling occurs only in the flat plane folds of the web, while the global shear buckling occurs over multiple folds of the web. New analytical prediction model accounting for the interaction between the local and global shear buckling of CWSBs is proposed. Experimental results from the current work and previous studies are compared with the proposed analytical prediction model. The predictions of the proposed model are significantly better than all other studied models. In light of the dispersion of test data, accuracy, consistency, and economical aspects of the prediction models, the authors recommend their proposed model for the design of CWSBs over the rest of the models.

• Computers and Concrete
• /
• v.27 no.5
• /
• pp.473-487
• /
• 2021

The review of the literature and design guidelines indicates a lack of design codes governing the shear strength of reinforced concrete (RC) beams strengthened with ultrahigh-performance fiber-reinforced concrete (UHPFRC). This study uses the results of a 3D finite element model constructed previously by the authors and verified against an experimental programme to gain a clear understanding of the shear strength of RC beams strengthened with UHPFRC by using different schemes. Experimental results found in the literature along with the numerical results for shear capacities of normal-strength RC and UHPFRC beams without stirrups are compared with available code design guidelines and empirical models found in the literature. The results show variance between the empirical models and the experimental results. Accordingly, proposed equations derived based on empirical models found in the literature were set to estimate the shear capacity of normal-strength RC beams without stirrups. In addition, the term 'shear span-to-depth ratio' is not considered in the equations for design guidelines found in the literature regarding the shear capacity of UHPFRC beams without stirrups. Consequently, a formula estimating the shear strength of UHPFRC and RC beams strengthened with UHPFRC plates and considering the effect of shear span-to-depth ratio is proposed and validated against an experimental programme previously conducted by the authors.

• Computers and Concrete
• /
• v.27 no.3
• /
• pp.225-239
• /
• 2021

Carbon fiber reinforced polymer (CFRP) has extensive use in strengthening reinforced concrete structures due to its high strength and elastic modulus, low weight, fast and easy application, and excellent durability performance. Many studies have been carried out to determine the performance of the CFRP confined concrete cylinder. Although studies about the prediction of confined compressive strength using ANN are in the literature, the insufficiency of the studies to predict the strain of confined concrete cylinder using ANN, which is the most appropriate analysis method for nonlinear and complex problems, draws attention. Therefore, to predict both strengths and also strain values, two different ANNs were created using an extensive experimental database. The strength and strain networks were evaluated with the statistical parameters of correlation coefficients (R2), root mean square error (RMSE), and mean absolute error (MAE). The estimated values were found to be close to the experimental results. Mathematical equations to predict the strength and strain values were derived using networks prepared for convenience in engineering applications. The sensitivity analysis of mathematical models was performed by considering the inputs with the highest importance factors. Considering the limit values obtained from the sensitivity analysis of the parameters, the performances of the proposed models were evaluated by using the test data determined from the experimental database. Model performances were evaluated comparatively with other analytical models most commonly used in the literature, and it was found that the closest results to experimental data were obtained from the proposed strength and strain models.

• International Journal of Computer Science & Network Security
• /
• v.22 no.5
• /
• pp.149-153
• /
• 2022

This study examines the effect of using interactive electronic models to teach mathematical concepts on students' achievement in the linear algebra course at university. The field sample consisted of 200 students divided into two equal groups, an experimental group of 100 students and a control group of 100 students. The researcher used an achievement test in some mathematical concepts related to linear algebra. The results of the study showed that there were statistically significant differences (0.05) between the average achievement scores of the experimental and control groups in the post application of the achievement test, in favor of the experimental group. The size of the influence of the independent factor on the results of the study, which is "interactive electronic forms", on the dependent factor, which is the students' academic achievement in the prepared test, had a very large effect. Also, the results of the study showed that there were statistically significant differences (0.05) between the mean scores of the experimental group in the pre and post applications of the achievement test, in favor of the post application. The researcher recommended the use of interactive electronic models in teaching mathematical concepts at the university level and diversifying the strategies of teaching mathematics, using technology to attract learners and raise their academic achievement.

• Journal of Korean Elementary Science Education
• /
• v.38 no.4
• /
• pp.510-521
• /
• 2019

This study investigated the effect of career education using female scientists role models on science-related attitude, science career awareness, gender stereotype of science-related career, and image of scientists. Interaction effect with students' gender were also investigated. The subjects of this study were 70 $5^{th}$ grader. The experimental group was introduced career education using female scientists role models with 7 cases of female scientists in the form of 10 minutes movies or cartoons, while the comparison group performed reading science books. The results showed that science-related attitudes and science career awareness of experimental group were significantly higher than control group, not only for girls but has for boys. Gender stereotype of science-related career has changed more neutrally in experimental group. After the career education using female scientists role models, more female scientists were presented in students' image of scientist in DAST. This results showed positive effects of the career education using female scientists role models and educational implications were discussed.

• Clinical and Experimental Pediatrics
• /
• v.65 no.5
• /
• pp.239-249
• /
• 2022

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model's interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.

• Steel and Composite Structures
• /
• v.29 no.4
• /
• pp.465-481
• /
• 2018

The use of external carbon-fiber-reinforced polymer (CFRP) laminates is one of the most effective techniques existing for the confinement of circular concrete specimens. Currently, several researches have been made to develop models for predicting the ultimate conditions of this type of confinement. As most of the major existing models were developed based on limited experimental database. This paper presents the development of new confinement ultimate conditions, strength and strain models, for concrete cylinders confined with CFRP composites based on a statistical analysis of a large existing experimental database of 310 cylindrical concrete specimens wrapped with CFRP. The database is used to evaluate the performance of the proposed and major existing strength and strain models. Based on the two different statistical indices, the coefficient of determination ($R^2$) and the Root Mean Square Error (RMSE), the two proposed confinement ultimate conditions presents a good performance compared to the major existing models except the models of Lam and Teng (2003) and Youssef et al. (2007) which have relatively similar performance to the proposed models.