• Journal of The Korean Association For Science Education
• /
• v.38 no.5
• /
• pp.599-610
• /
• 2018

The purpose of this study is to analyze mechanistic reasoning in Fabre's inquires and to develop mechanistic reasoning model. To analyze the order of the process elements in mechanistic reasoning, 30 chapters were selected in book. Inquiries were analyzed through a framework which is based on Russ et al. (2008). The nine process elements of mechanistic reasoning that was presented in Fabre's inquires were as follows: Describing the Target Phenomenon, Identifying prior Knowledge, Identifying Properties of Objects, Identifying Setup Conditions, Identifying Activities, Conjecturing Entities, Identifying Properties of Entities, Identifying Entities, and Organization of Entities. The order of process elements of mechanistic reasoning was affected by inquiry's subject, types of question, prior knowledge and situation. Three mechanistic reasoning models based on the process elements of mechanistic reasoning were developed: Mechanistic reasoning model for Identifying Entities(MIE), Mechanistic reasoning model for Identifying Activities(MIA), and Mechanistic reasoning model for Identifying Properties of entities (MIP). Science teacher can help students to use the questions of not only "why" but also "How", "If", "What", when students identify entities or generate hypotheses. Also science teacher should be required to understand mechanistic reasoning to give students opportunities to generate diverse hypotheses. If students can't conjecture entities easily, MIA and MIP would be helpful for students.

• 한국생물공학회:학술대회논문집
• /
• 2000.04a
• /
• pp.133-136
• /
• 2000

In recent years, hybrid neural network approaches which combine neural networks and mechanistic models have been gaining considerable interests. These approaches are potentially very efficient to obtain more accurate predictions of process dynamics by combining mechanistic and neural models in such a way that the neural network model properly captures unknown and nonlinear parts of the mechanistic model. In this work, such an approach was applied in the modeling of a full-scale coke wastewater treatment process. First, a simplified mechanistic model was developed based on the Activated Sludge Model No.1 and the specific process knowledge, Then neural network was incorporated with the mechanistic model to compensate the errors between the mechanistic model and the process data. Simulation and actual process data showed that the hybrid modeling approach could predict accurate process dynamics of industrial wastewater treatment plant. The promising results indicated that the hybrid modeling approach could be a useful tool for accurate and cost-effective modeling of biochemical processes.

• International Journal of Highway Engineering
• /
• v.8 no.2 s.28
• /
• pp.37-47
• /
• 2006

The structural response and performance of a flexible pavement can be improved through the use of geogrids as base course reinforcement. Current ongoing research at the University of illinois has focused on the development of a geogrid base reinforcement mechanistic model for the analysis of reinforced pavements. This model is based on the finite element methodology and considers not only the nonlinear stress-dependent pavement foundation but also the isotropic and anisotropic behavior of base/subbase aggregates for predicting pavement critical responses. An axisymmetric finite element model was developed to employ a three-noded axisymmetric membrane element for modeling geogrid reinforcement. The soil/aggregate-geogrid interface was modeled by the three-noded membrane element and the neighboring six-noded no thickness interface elements. To validate the developed mechanistic model, the commercial finite element program $ABAQUS^{TM}$ was used to generate pavement responses as analysis results for simple cases with similar linear elastic material input properties. More sophisticated cases were then analyzed using the mechanistic model considering the nonlinear and anisotropic modulus property inputs in the base/subbase granular layers. This paper will describe the details of the developed mechanistic model and the effectiveness of geogrid reinforcement when used in different quality unbound aggregate base/subbase layers.

• Nuclear Engineering and Technology
• /
• v.32 no.1
• /
• pp.17-33
• /
• 2000

A mechanistic model based on wall-attached bubble coalescence, previously developed by the authors, was extended to predict a vow high critical heat flux (CHF）in highly subcooled flow boiling, especially for high mass flux and small tube diameter conditions. In order to take into account the enhanced condensation due to high subcooling and high mass velocity in small diameter tubes, a mechanistic approach was adopted to evaluate the non-equilibrium flow quality and void fraction in the subcooled water flow boiling, with preserving the structure of the previous CHF model. Comparison of the model predictions against highly subcooled water CHF data showed relatively good agreement over a wide range of parameters. The significance of the proposed CHF model lies in its generality in applying over the entire subcooled flow boiling regime including the operating conditions of fission and fusion reactors.

• Journal of Veterinary Science
• /
• v.24 no.2
• /
• pp.21.1-21.5
• /
• 2023

Under the current African swine fever (ASF) epidemic situation, a science-based ASF-control strategy is required. An ASF transmission mechanistic model can be used to understand the disease transmission dynamics among susceptible epidemiological units and evaluate the effectiveness of an ASF-control strategy by simulating disease spread results with different control options. The force of infection, which is the probability that a susceptible epidemiological unit becomes infected, could be estimated by applying an ASF transmission mechanistic model. The government needs to plan an ASF-control strategy based on an ASF transmission mechanistic model.

• Land and Housing Review
• /
• v.11 no.2
• /
• pp.95-104
• /
• 2020

This study aims to explore a purely mechanistic pavement analysis approach where viscoelasticity and fracture of asphalt mixtures are considered to accurately predict deformation and damage behavior of flexible pavements. To do so, the viscoelastic and fracture properties of designated pavement materials are obtained through experiments and a fully mechanistic damage analysis is carried out using a finite element method (FEM). While modeling crack development can be done in various ways, this study uses the cohesive zone approach, which is a well-known fracture mechanics approach to efficiently model crack initiation and propagation. Different pavement configurations and traffic loads are considered based on three main functional classes of roads suggested by FHWA i.e., arterial, collector and local. For each road type, three different material combinations for asphalt concrete (AC) and base layers are considered to study damage behavior of pavement. A concept of the approach is presented and a case study where three different material combinations for AC and base layers are considered is exemplified to investigate progressive damage behavior of pavements when mixture properties and layer configurations were altered. Overall, it can be concluded that mechanistic pavement modeling attempted in this study could differentiate the performance of pavement sections due to varying design inputs. The promising results, although limited yet to be considered a fully practical method, infer that a few mixture tests can be integrated with the finite element modeling of the mixture tests and subsequent structural modeling of pavements to better design mixtures and pavements in a purely mechanistic manner.

• Journal of Korean Library and Information Science Society
• /
• v.43 no.4
• /
• pp.183-199
• /
• 2012

This study is to develop an operating model of Conspectus for online resources by using mechanistic quality factor. Based on some empirical statistics about resource use behaviour such as collection rate, use rate, search rate, the mechanistic quality factor was calculated and applied to each subject by adjusting its acquisition level of Conspectus. according to the result of this study, Acqusition levels of the subject such as technical science which shows higher in use rate, and those such as history and social science which show higher in search rate, should be adjusted to a higher acquisition level, and those of others to the same or a lower level.

• Journal of the Korean Society for Precision Engineering
• /
• v.15 no.5
• /
• pp.145-152
• /
• 1998

In this research, in order to predict the cutting force using a mechanistic model, specific cutting force was firstly obtained through the cutting experiments. Band sawing process is similar to a milling, that is multi-point cutting. Therefore it is not easy matter to evaluate specific cutting force. Thus, the thickness of workpiec was made smaller than one pitch of the saw in terms of fly cutting in the face milling process. Then the cutting force was predicted by analyzing the geometric shape of a saw tooth The tooth shape used in the research was raker set style that was generally used in band sawing. And a set of teeth is comprised of three teeth, those are ranked as left, straight and right. The mechanistic model was developed in this study considered those shapes of each tooth. From the validation experiments, the predicted cutting forces coincided well with the measured ones. Therefore the predicted cutting forces can be used for the adaptive control of saw engaging feed rate in the band sawing.

• Nuclear Engineering and Technology
• /
• v.44 no.8
• /
• pp.889-896
• /
• 2012

Recent progress in the computational fluid dynamics methods of two- and multiphase phase flows has already started opening up new exciting possibilities for using complete multidimensional models to simulate boiling systems. Combining this new theoretical and computational approach with novel experimental methods should dramatically improve both our understanding of the physics of boiling and the predictive capabilities of models at various scale levels. However, for the multidimensional modeling framework to become an effective predictive tool, it must be complemented with accurate mechanistic closure laws of local boiling mechanisms. Boiling heat transfer has been studied quite extensively before. However, it turns out that the prevailing approach to the analysis of experimental data for both pool boiling and forced-convection boiling has been associated with formulating correlations which normally included several adjustable coefficients rather than based on first principle models of the underlying physical phenomena. One reason for this has been the tendency (driven by practical applications and industrial needs) to formulate single expressions which encompass a broad range of conditions and fluids. This, in turn, makes it difficult to identify various specific factors which can be independently modeled for different situations. The objective of this paper is to present a mechanistic modeling concept for both pool boiling and forced-convection boiling. The proposed approach is based on theoretical first-principle concepts, and uses a minimal number of coefficients which require calibration against experimental data. The proposed models have been validated against experimental data for water and parametrically tested. Model predictions are shown for a broad range of conditions.

• Nuclear Engineering and Technology
• /
• v.48 no.4
• /
• pp.859-869
• /
• 2016

Component-scale modeling of boiling is predominantly based on the Eulerian-Eulerian two-fluid approach. Within this framework, wall boiling is accounted for via the Rensselaer Polytechnic Institute (RPI) model and, within this model, the bubble is characterized using three main parameters: departure diameter (D), nucleation site density (N), and departure frequency (f). Typically, the magnitudes of these three parameters are obtained from empirical correlations. However, in recent years, efforts have been directed toward mechanistic modeling of the boiling process. Of the three parameters mentioned above, the departure diameter (D) is least affected by the intrinsic uncertainties of the nucleate boiling process. This feature, along with its prominence within the RPI boiling model, has made it the primary candidate for mechanistic modeling ventures. Mechanistic modeling of D is mostly carried out through solving of force balance equations on the bubble. Forces incorporated in these equations are formulated as functions of the radius of the bubble and have been developed for, and applied to, low-pressure conditions only. Conversely, for high-pressure conditions, no mechanistic information is available regarding the growth rates of bubbles and the forces acting on them. In this study, we use direct numerical simulation coupled with an interface tracking method to simulate bubble growth under high (up to 45 bar) pressure, to obtain the kind of mechanistic information required for an RPI-type approach. In this study, we compare the resulting bubble growth rate curves with predictions made with existing experimental data.