• 유체기계공업학회:학술대회논문집
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• 2003.12a
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• pp.549-554
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• 2003

EPRI PPM (Performance Prediction Methodology), a method used for the prediction of required thrust of valves, can not be applied to unbalanced-disk globe valves operated in the fluid when the fluid temperature is above $150^{\circ}F$ because the thrust increase caused by the friction between the valve disk and body is not considered in the PPM. In order to apply PPM to the valves, EPRI suggested new friction prediction method to be added in the code. This paper analyzes the applicability of the prediction method comparing the disk-to-body friction load predicted from the method with the measured friction load from the field tests. The maximum values from the prediction method and those obtained from the test were 268lbs and about 1500lbs, respectively. It is included that the prediction method should be improved for the realistic prediction of disk-to-body friction load.

• International Journal of Precision Engineering and Manufacturing
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• v.3 no.4
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• pp.72-77
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• 2002

The load interaction effect can be best illustrated by the phenomenon of overload retardation. Some prediction methods for retardation are reviewed and the problems discussed in the present paper. The so-called under-load effect much of the retardation disappears if a very low level minimum stress follows the overload, is also of importance for a prediction model to work properly under random load spectrum. The concept of Interactive Zone (IZ) fully considering reversed plasticity during unloading was discussed. This IZ concept can be combined with existing models to derive some improved models that can naturally take account of the under-load effect. Some simulations by IZ improved models for test under complex load sequences including multiple overloads and both over/under loads are compared with test results. It is seen that the improvement by IZ concept greatly enhanced the ability of existing models to accommodate complex load interaction effects.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.339-342
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• 2000

Repetitive Load Prediction is proposed for the UPS inverter application of the second order deadbeat controller which is robust against the calculation time delay and the parameter variation and which gets fast response against the load variation. The proposed technique predicts the load current ahead of two sampling time using that the load current is periodic. This is effective under nonlinear load condition. The proposed technique is derived theoretically and verified through simulation and experimental result.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.186-187
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• 2020

Damage to temporary facilities and structural members caused by excessive loads in the field continue to occur. If the load can be monitored in advance, the risk can be prevented. In this study, a load cell sensor is installed under the system support, and load data is wirelessly transmitted through a Bluetooth AP(wireless). Risk prediction system is proposed through an construction alarm when an abnormal load occurs through real-time multi-point monitoring by sensor location.

• 한국정보디스플레이학회:학술대회논문집
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• 2007.08a
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• pp.609-612
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• 2007

This paper describes a new method to predict the load current of a dc-dc converter. The load current is calculated using the video information of the PDP. The output capacitance of the dc-dc converter can be reduced by utilizing the predicted load current, which results in a cost reduction of the power system in the PDP.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.2
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• pp.43-50
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• 2017

The purpose of this study is to develop a control algorithm for outdoor air cooling based on the prediction of cooling load, and to evaluate the building energy saving using outdoor air cooling. Outdoor air conditions such as temperature, humidity, and solar insolation are predicted using forecasted information provided by the meteorological agency, and the building cooling load is predicted from the obtained outdoor air conditions and building characteristics. The air flow rate induced by outdoor air is determined by considering the predicted cooling loads. To evaluate the energy saving, the benchmark building is modeled and simulated using the TRNSYS program. Energy saving by outdoor air cooling using load prediction is found to be around 10% of the total cooling coil load in all locations of Korea. As the allowable minimum indoor temperature is decreased, the total energy saving is increased and approaches close to that of the conventional enthalpy control.

• Transactions of Materials Processing
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• v.30 no.4
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• pp.172-178
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• 2021

The cold forging process induces material deformation in an enclosed space, generating a very high forging load. Therefore, it is mainly designed as a multi-stage process, and fatigue failure occurs in forging die due to cyclic load. Studies have been conducted previously to quantitatively predict the fatigue limit of cold forging dies, however, there was a limit to field application due to the large error range and the need for expert intervention. To solve this problem, we conducted a study on the introduction of a real-time forging load measurement technology and an automated system for quantitative prediction of die life cycle. As a result, it was possible to reduce the error range of the quantitative prediction of die life cycle to within ±7%, and it became possible to use the die life cycle calculation algorithm into an automated system.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.26-30
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• 2008

Currently an automated methodology based on data mining techniques is presented for the prediction of customer load patterns in long duration load profiles. The proposed our approach consists of three stages: (i) data pre-processing: noise or outlier is removed and the continuous attribute-valued features are transformed to discrete values, (ii) cluster analysis: k-means clustering is used to create load pattern classes and the representative load profiles for each class and (iii) classification: we evaluated several supervised learning methods in order to select a suitable prediction method. According to the proposed methodology, power load measured from AMR (automatic meter reading) system, as well as customer indexes, were used as inputs for clustering. The output of clustering was the classification of representative load profiles (or classes). In order to evaluate the result of forecasting load patterns, the several classification methods were applied on a set of high voltage customers of the Korea power system and derived class labels from clustering and other features are used as input to produce classifiers. Lastly, the result of our experiments was presented.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.38-50
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• 2018

Spatio-temporal load forecasting (STLF) is a foundation for building the prediction-based power map, which could be a useful tool for the visualization and tendency assessment of urban energy application. Constructing one point-forecasting model for each electricity cell in the geographic space is possible; however, it is unadvisable and insufficient, considering the aggregation features of electricity cells and uncertainties in input variables. This paper presents a new STLF method, with a data-driven framework consisting of 3 subroutines: multi-level clustering of cells considering their aggregation features, load regression for each category of cells based on SLS-SVRNs (sparse least squares support vector regression networks), and interval forecasting of spatio-temporal load with sampled blind number. Take some area in Pudong, Shanghai as the region of study. Results of multi-level clustering show that electricity cells in the same category are clustered in geographic space to some extent, which reveals the spatial aggregation feature of cells. For cellular load regression, a comparison has been made with 3 other forecasting methods, indicating the higher accuracy of the proposed method in point-forecasting of spatio-temporal load. Furthermore, results of interval load forecasting demonstrate that the proposed prediction-interval construction method can effectively convey the uncertainties in input variables.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.6
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• pp.603-610
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• 2009

Ice load is one of the important design parameters for the construction of icebreaking vessels. In this paper, the design ice load prediction for the icebreaking vessels under normal operating condition in ice-covered sea is discussed. The ice loads under normal operating condition are expected from sea trials in moderate ice conditions. In this sense the extreme ice loads during heavy ramming or accidental collision are not considered. Current study describes the global ice load on the hull of the icebreaking vessels. Available ice load data from full-scale sea trials are collected and analyzed according to various ship-ice interaction parameters including displacement, stem angle, speed of a ship and flexural strength and thickness of sea ice. The ice load prediction formula is compared with the collected full-scale sea trials data and it shows a good agreement.