• Advances in concrete construction
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• v.8 no.1
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• pp.55-64
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• 2019

Chloride corrosion has become the main factor of reducing the service life of reinforced concrete structures. The object of this paper is to propose a theoretical model that predicts the service life of chloride-corrosive concrete under fatigue load. In the process of modeling, the concrete is divided into two parts, microcrack and matrix. Taking the variation of mcirocrack area caused by fatigue load into account, an equation of chloride diffusion coefficient under fatigue load is established, and then the predictive model is developed based on Fick's second law. This model has an analytic solution and is reasonable in comparison to previous studies. Finally, some factors (chloride diffusion coefficient, surface chloride concentration and fatigue parameter) are analyzed to further investigate this model. The results indicate: the time to pit-to-crack transition and time to crack growth should not be neglected when predicting service life of concrete in strong corrosive condition; the type of fatigue loads also has a great impact on lifetime of concrete. In generally, this model is convenient to predict service life of chloride-corrosive concrete with different water to cement ratio, under different corrosive condition and under different types of fatigue load.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.220-228
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• 2022

The directed tests produce an expectation model to assist the organization's heads and professionals with settling on the right and speedy choice. A directed deep learning strategy has been embraced and applied for SCADA information. In this paper, for the load shedding expectation overall power organization of Libya, a convolutional neural network with multi neurons is utilized. For contributions of the neural organization, eight convolutional layers are utilized. These boundaries are power age, temperature, stickiness and wind speed. The gathered information from the SCADA data set were pre-handled to be ready in a reasonable arrangement to be taken care of to the deep learning. A bunch of analyses has been directed on this information to get a forecast model. The created model was assessed as far as precision and decrease of misfortune. It tends to be presumed that the acquired outcomes are promising and empowering. For assessment of the outcomes four boundary, MSE, RMSE, MAPE and R2 are determined. The best R2 esteem is gotten for 1-overlap and it was 0.98.34 for train information and for test information is acquired 0.96. Additionally for train information the RMSE esteem in 1-overlap is superior to different Folds and this worth was 0.018.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.4
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• pp.207-214
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• 2022

A prediction model is proposed for a blast load acting on a column component because of an external explosion. The model can predict the pressure-time histories acting on a column using the fitting curves established from a database composed of finite-element (FE) analysis results. To this end, 70 numerical simulations using the commercial software AUTODYN were performed by changing the column width. To confirm the performance of the proposed model, pressure-time histories estimated from an existing empirical formula and the proposed model were compared based on the FE analysis results. It was verified that the proposed model can more precisely predict the pressure-time histories compared with the existing model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.7
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• pp.505-511
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• 2020

The circular composite tubes have been used as a main spar of HALE-UAV(High Altitude Long Endurance-Unmanned Air Vehicle). In this paper, an analytical model is presented for the prediction of the failure load of unsymmetrically stiffened circular spar using a modified Brazier approach. This model was used to predict the moment carrying capacity of the unsymmetrically stiffened circular spar. From the results, we can know that a stiffened cap placed in the top sector of a spar increased the bending capabilities. Four point bending tests were conducted to estimate the effect of the cap on the failure load and compared with the proposed model. And numerical simulations were performed to analyze the behavior of stiffened circular spar. Comparisons of the results from the proposed model with those from experiments and numerical modes show good correlation.

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

• Journal of the Society of Naval Architects of Korea
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• v.50 no.4
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• pp.206-216
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• 2013

The present study considers the prediction of wind-induced heel of cruise ship and its stabilization. Wind load in ocean exerts on the surface of superstructure of cruise ship, which causes the heel moment on the ship. The calculation of wind load starts from choosing wind speed profile, so that the logarithmic wind profile model is applied in this study. Heel moment by wind load is calculated by adopting approximate formulation and applied to the ship motion analysis in time domain. Motion stabilizers, such as stabilizing fin and U-tube tank, are considered to reduce the heel effect as well as excessive roll motion. From this study, it is expected that the present method can be applied to the prediction and stabilization of the heel motion of cruise ships.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.204-208
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• 2000

An approximate similarity theory has been applied to predict the forming load of non-axisymmetric forging of aluminum alloys through model material tests. The approximate similarity theory is applicable when strain rate sensitivity, geometrical size, and die velocity of model materials are different from those of real materials. Actually, the forming load of yoke, which is an automobile part made of aluminum alloys(Al-6061), is predicted by using this approximate similarity theory. Firstly, upset forging tests are have been carried out to determine the flow curves of three model materials and aluminum alloy(Al-6061), and a suitable model material is selected for model material test of Al-6061. And then hot forging tests of aluminum yokes have been performed to verify the forming load predicted from the model material, which has been selected from above upset forging tests. The forming loads of aluminum yoke forging predicted by this approximate similarity theory are in good agreement with the experimental results of Al-6061 and the results of finite element analysis using DEFORM-3D.

• Steel and Composite Structures
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• v.42 no.4
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• pp.459-475
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• 2022

In this paper a model for the prediction of the ultimate axial compressive capacity of square and rectangular Concrete Filled Steel Tubes, based on an Artificial Neural Network modeling procedure is presented. The model is trained and tested using an experimental database, compiled for this reason from the literature that amounts to 1193 specimens, including long, thin-walled and high-strength ones. The proposed model was selected as the optimum from a plethora of alternatives, employing different activation functions in the context of Artificial Neural Network technique. The performance of the developed model was compared against existing methodologies from design codes and from proposals in the literature, employing several performance indices. It was found that the proposed model achieves remarkably improved predictions of the ultimate axial load.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.3
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• pp.123-130
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• 2024

This paper proposes an EMPC (Explicit Model Predictive Controller) for temperature tracking control based on heat load prediction by an ESO (Extended State Observer) for a variable cooling circulation system with multiple indoor units connected to one outdoor unit. In this system, heat transfer and heat loss relative to the input temperature are modeled using system dynamics. Using this model, we design an EMPC based on an ESO that is robust to temperature changes and depends on airflow. To determine the stability of both the controller and the observer, asymptotic stability is verified through Lyapunov stability analysis. Finally, to validate the performance of the proposed controller, simulations are conducted under three scenarios with varying airflow, set temperature, and heat load.

• Smart Structures and Systems
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• v.29 no.6
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• pp.799-805
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• 2022

Permanent magnet synchronous motors (PMSMs) are widely used in systems requiring high control precision, efficiency, and reliability. Predicting the remaining useful life (RUL) with health monitoring of PMSMs prevents catastrophic failure and ensures reliable operation of system. In this study, a model-based method for predicting the RUL of PMSMs using phase current and vibration signals is proposed. The proposed method includes feature selection and RUL prediction based on a particle filter with a degradation model. The Paris-Erdogan model describing micro fatigue crack propagation is used as the degradation model. An experimental set-up to conduct accelerated life test, capable of monitoring various signals was designed in this study. Phase current and vibration data obtained from an accelerated life test of the PMSMs were used to verify the proposed approach. Features extracted from the data were clustered based on monotonicity and correlation clustering, respectively. The results identify the effectiveness of using the current data in predicting the RUL of PMSMs.