• Water Engineering Research
• /
• v.2 no.1
• /
• pp.11-19
• /
• 2001

A performance prediction model for Small Hydro Power(SHP) sites has been studied and developed. Twelve SHP sites were selected and the performance characteristics were analyzed by using the developed model. Also, primary design specifications such as design flowrate, plant capacity, operational rate were suggested and feasibility for small hydro power sites were estimated. It was found that the design flowrate is most important parameter to exploit SHP plant and the methodology developed in this study can be a useful tool to analyze the performance of SHP sites.

• Proceedings of the KSR Conference
• /
• 2006.11b
• /
• pp.104-111
• /
• 2006

The non-linear properties of rubber material which are described as strain energy function are important parameter to design and evaluate of rubber spring. These are determined by material tests which are uni-axial tension and bi-axial tension. The computer simulation using the nonlinear element analysis program executed to predict and evaluate the load capacity and stiffness for chevron spring. In order to investigate the heat-aging effects on the rubber material properties, the acceleration test were carried out. Compression set results changes as the threshold are used for assessment of the useful life and time to threshold value were plotted against reciprocal of absolute temperature to give the Arrhenius plot. By using the compression set test, several useful life prediction for rubber material were proposed.

• Geotechnical Engineering
• /
• v.2 no.3
• /
• pp.15-26
• /
• 1986

A great number of different pile-driving formulas are widely used to determine the load-carr-ying capacity during driving. However, engineers have been unable to agree on any particular pile.driving formula because the mechanisms of pile driving action which involves many complications such as hammer-pile-soil interaction could not be solved completely in any practical manner. This paper is presented for the purpose of giving field engineers a reliable analytical procedures for the prediction of pile.driving resistance without resort to electronic computers based on the theory of longitudinal wave transmission in conjunction with the wave equation and on the consideration of the effect of residual stresses induced by reversed friction in pile.

• International conference on construction engineering and project management
• /
• 2007.03a
• /
• pp.653-661
• /
• 2007

Overseas construction projects tend to be more complex than domestic projects, being exposed to more external risks, such as politics, economy, society, and culture, as well as more internal risks from the project itself. It is crucial to have an early understanding of the project condition, in order to be well prepared in various phases of the project. This study compares a structural equation model and multiple regression analysis, in their capacity to predict cost performance of international construction projects. The structural equation model shows a more accurate prediction of cost performance than does regression analysis, due to its intrinsic capability of considering various cost factors in a systematic way.

• ETRI Journal
• /
• v.46 no.3
• /
• pp.379-391
• /
• 2024

To meet increasing traffic requirements in mobile networks, small base stations (SBSs) are densely deployed, overlapping existing network architecture and increasing system capacity. However, densely deployed SBSs increase energy consumption and interference. Although these problems already exist because of densely deployed SBSs, even more SBSs are needed to meet increasing traffic demands. Hence, base station (BS) switching operations have been used to minimize energy consumption while guaranteeing quality-of-service (QoS) for users. In this study, to optimize energy efficiency, we propose the use of deep reinforcement learning (DRL) to create a BS switching operation strategy with a traffic prediction model. First, a federated long short-term memory (LSTM) model is introduced to predict user traffic demands from user trajectory information. Next, the DRL-based BS switching operation scheme determines the switching operations for the SBSs using the predicted traffic demand. Experimental results confirm that the proposed scheme outperforms existing approaches in terms of energy efficiency, signal-to-interference noise ratio, handover metrics, and prediction performance.

• Journal of the Korean Society for Precision Engineering
• /
• v.29 no.8
• /
• pp.818-823
• /
• 2012

In order to predict necking behaviour of aluminium sheets, a crystal plasticity model is introduced in the finite element analysis of tensile test. Due to the computational limits of time and memory, only a small part of tensile specimen is subjected to the analysis. Grains having different orientations are subjected to numerical tensile tests and each grain is discretized by many elements. In order to predict the sudden drop of load carrying capacity after necking, a well-known Cockcroft-Latham damage model is introduced. The mismatch of grain orientation causes stress concentration at several points and damage is evolved at these points. This phenomenon is similar to void nucleation. In the same way, void growth and void coalescence behaviours are well predicted in the analysis. For the comparison of prediction capability of necking, same model is subjected to finite element analysis using uniform material properties of polycrystal with and without damage. As a result, it is shown that the crystal plasticity model can be used in prediction of necking and fracture behavior of materials accurately.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2137-2142
• /
• 2003

One of the important performance metrics of the World Wide Web is how fast and precise a request from users will be serviced successfully. Shared Web Caching (SWC) is one of the techniques to improve the performance of the network system. In Shared Web Caching Systems, the key issue is on deciding when and where an item is cached, and also how to transfer the correct and reliable information to the users quickly. Such SWC distributes the items to the proxies which have sufficient capacity such as the processing time and the cache sizes. In this study, the Hot Spot Prediction Algorithm (HSPA) has been suggested to improve the consistent hashing algorithm in the point of the load balancing, hit rate with a shorter response time. This method predicts the popular hot spots using a prediction model. The hot spots have been patched to the proper proxies according to the load-balancing algorithm. Also a simulator is developed to utilize the suggested algorithm using PERL language. The computer simulation result proves the performance of the suggested algorithm. The suggested algorithm is tested using the consistent hashing in the point of the load balancing and the hit rate.

• Computers and Concrete
• /
• v.19 no.6
• /
• pp.631-639
• /
• 2017

This study experimentally investigated the flexural capacity of a concrete beam reinforced with a newly developed GFRP bar that overcomes the lower modulus of elasticity and bond strength compared to a steel bar. The GFRP bar was fabricated by thermosetting a braided pultrusion process to form the outer fiber ribs. The mechanical properties of the modulus of elasticity and bond strength were enhanced compared with those of commercial GFRP bars. In the four-point bending test results, all specimens failed according to the intended failure mode due to flexural design in compliance with ACI 440.1R-15. The effects of the reinforcement ratio and concrete compressive strength were investigated. Equations from the code were used to predict the deflection, and they overestimated the deflection compared with the experimental results. A modified model using two coefficients was developed to provide much better predictive ability, even when the effective moment of inertia was less than the theoretical $I_{cr}$. The deformability of the test beams satisfied the specified value of 4.0 in compliance with CSA S6-10. A modified effective moment of inertia with two correction factors was proposed and it could provide much better predictability in prediction even at the effective moment of inertia less than that of theoretical cracked moment of inertia.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.3
• /
• pp.95-107
• /
• 2020

The failures of the agricultural reservoirs that most have more than 50 years, have increased due to the abnormal weather and localized heavy rains. There are many studies on the prediction of damage from reservoir collapse, however, these referenced studies focused on evaluating reservoir collapse as single unit and applyed to one and two dimensional hydrodynamic model to identify the fluid flow. This study is to estimate failure probability of spillway, sliding, bearing capacity and overflowing targeting small and medium scale agricultural reservoirs. In addition, we calculate failure probability by complex mode. Moreover, we predict downstream flood damage by reservoir failure applying three dimensional hydrodynamic model. When the reservoir destroyed, the results are as follows; (1) the flow of fluid proceeds to same stream direction and to a lower slope by potential and kinetic energy; (2) The predicted damage in downstream is evaluated that damage due to building destruction is the highest.

• Journal of the Korean Geotechnical Society
• /
• v.27 no.9
• /
• pp.55-66
• /
• 2011

The compulsory replacement method for soft ground treatment is simple but excellent in economic feasibility. However, the accurate replacement depth is not easy to properly predicted since an theoretical algorithm has not presently been established so far. In this research a prediction equation is proposed in a new form based on the liquid limit and natural moisture content rather than on the bearing capacity of the soft soil layer. The equation is based on the monitoring as well as the confirmatory boring at the site. In addition, the equation has been derived from the data obtained from the analysis of the characteristics of silt/clay of Sihwa region. The final prediction equation has been drawn by applying the regression analysis method.