• Title/Summary/Keyword: Performance Trend

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Ultimate strength performance of tankers associated with industry corrosion addition practices

  • Kim, Do Kyun;Kim, Han Byul;Zhang, Xiaoming;Li, Chen Guang;Paik, Jeom Kee
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.6 no.3
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    • pp.507-528
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    • 2014
  • In the ship and offshore structure design, age-related problems such as corrosion damage, local denting, and fatigue damage are important factors to be considered in building a reliable structure as they have a significant influence on the residual structural capacity. In shipping, corrosion addition methods are widely adopted in structural design to prevent structural capacity degradation. The present study focuses on the historical trend of corrosion addition rules for ship structural design and investigates their effects on the ultimate strength performance such as hull girder and stiffened panel of double hull oil tankers. Three types of rules based on corrosion addition models, namely historic corrosion rules (pre-CSR), Common Structural Rules (CSR), and harmonised Common Structural Rules (CSR-H) are considered and compared with two other corrosion models namely UGS model, suggested by the Union of Greek Shipowners (UGS), and Time-Dependent Corrosion Wastage Model (TDCWM). To identify the general trend in the effects of corrosion damage on the ultimate longitudinal strength performance, the corrosion addition rules are applied to four representative sizes of double hull oil tankers namely Panamax, Aframax, Suezmax, and VLCC. The results are helpful in understanding the trend of corrosion additions for tanker structures.

Selecting Ordering Policy and Items Classification Based on Canonical Correlation and Cluster Analysis

  • Nagasawa, Keisuke;Irohara, Takashi;Matoba, Yosuke;Liu, Shuling
    • Industrial Engineering and Management Systems
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    • v.11 no.2
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    • pp.134-141
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    • 2012
  • It is difficult to find an appropriate ordering policy for a many types of items. One of the reasons for this difficulty is that each item has a different demand trend. We will classify items by shipment trend and then decide the ordering policy for each item category. In this study, we indicate that categorizing items from their statistical characteristics leads to an ordering policy suitable for that category. We analyze the ordering policy and shipment trend and propose a new method for selecting the ordering policy which is based on finding the strongest relation between the classification of the items and the ordering policy. In our numerical experiment, from actual shipment data of about 5,000 items over the past year, we calculated many statistics that represent the trend of each item. Next, we applied the canonical correlation analysis between the evaluations of ordering policies and the various statistics. Furthermore, we applied the cluster analysis on the statistics concerning the performance of ordering policies. Finally, we separate items into several categories and show that the appropriate ordering policies are different for each category.

A Study on Fault Detection using Fuzzy Trend Monitoring Technique of UAV Turbofan Engine (퍼지 경향 감시 기법을 이용한 무인기용 터보팬 엔진의 손상 탐지에 관한 연구)

  • Kong, C.D.;Kho, S.H.;Ki, J.Y.;Kho, H.Y.;Oh, S.H.;Kim, J.H.
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2007.11a
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    • pp.345-349
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    • 2007
  • In this study a fuzzy trend monitoring method for detecting the engine mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration. etc. Using engine condition data set as a input which generated by linear regression analysis of real engine instrument data, an application of fuzzy logic in diagnostics estimate a cause of fault in each components.

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Practical Text Mining for Trend Analysis: Ontology to visualization in Aerospace Technology

  • Kim, Yoosin;Ju, Yeonjin;Hong, SeongGwan;Jeong, Seung Ryul
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.8
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    • pp.4133-4145
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    • 2017
  • Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.

A Study on Trend Monitoring of a Long Endurance UAV s Gas Turbine to be Operated at Medium High Altitude

  • Kho, Seong-Hee;Ki, Ja-Young;Kong, Chang-Duk;Oh, Seong-Hwan;Kim, Ji-Hyun
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.84-88
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    • 2008
  • The UAV propulsion system that will be operated for long time at more than 40,000ft altitude should have not only fuel flow minimization but also high reliability and durability. If this UAV propulsion system may have faults, it is not easy to recover the system from the abnormal, and hence an accurate diagnostic technology must be needed to keep the operational reliability. For this purpose, the development of the health monitoring system which can monitor remotely the engine condition should be required. In this study, a fuzzy trend monitoring method for detecting the engine faults including mechanical faults was proposed through analyzing performance trends of measurement data. The trend monitoring is an engine conditioning method which can find engine faults by monitoring important measuring parameters such as fuel flow, exhaust gas temperatures, rotational speeds, vibration and etc. Using engine condition database as an input to be generated by linear regression analysis of real engine instrument data, an application of the fuzzy logic in diagnostics estimated the cause of fault in each component. According to study results, it was confirmed that the proposed trend monitoring method can improve reliability and durability of the propulsion system for a long endurance UAV to be operated at medium altitude.

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A Simulation Appraisal of Energy Performance in Office Building by Different Types of Air-Conditioning (공조방식에 따른 사무소 건물의 에너지 성능 평가)

  • Choi, Jong-Dae;Choi, Dong-Suk;Yun, Geun-Young
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.24 no.8
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    • pp.612-620
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    • 2012
  • High economic growth causes increase of the building energy consumption. The energy consumption for HVAC system accounts for 40~50% of the whole building consumption. The trend for building is large-scale and high-rise. Because of the trend, the energy consumption is becoming bigger than before. Nowadays, HVAC system design are recognized as the solution for a energy-saving. This paper is focused on the energy performance evaluation of central air-conditioning system(water-based) and system air-conditioning that were applied to the office building. The systems are modeled and simulated by using EnergyPlus Software 6.0. After the Simulation, annual cooling and heating energy consumption were calculated. It was found that the system air-conditioning can reduce the energy consumption approximately 55.24% annually compared with the central air-conditioning system(water-cooled). In addition, about 46.13% of annual operating costs can be reduced by use of system air-conditioning.

Analysis on Ventilation Performance of Natural Ventilation Systems in Multi-Family Housing Using Blower Door Test (Blower Door Test를 이용한 공동주택 자연환기시스템의 환기성능 분석)

  • Kim, Min Seok;Auh, Jin Sun;Hong, Goopyo;Kim, Byungseon Sean
    • KIEAE Journal
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    • v.16 no.6
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    • pp.129-134
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    • 2016
  • Today, natural ventilation systems are widely applied in multi-family housing. However, studies using the wind data trend line of the blower door test are insufficient. Purpose: Through this study, we will propose a computational method about ventilation performance of natural ventilation systems by conducting blower door test. Method: First, we sealed the gaps between the main systems including the natural ventilation system and conducted the blower door test. Next, the natural ventilation system was opened, the blower door test was conducted, and the difference in air flow rate between when closed and when opened was checked. Blower door test was carried out with a pressure difference of 50 Pa. Result: Therefore, the ventilation performance of the natural ventilation system was checked by drawing a trend line using the data to calculate the air flow rate at 2 Pa of the natural ventilation equipment standard pressure difference.

Performance Improvement of Protective Relaying for Large Transformer by Using Voltage-Current Trend and Flux-Differential Current Slope Characteristic (전압-전류 추이와 자속-차전류 기울기 특성을 이용한 변압기 보호계전기법의 성능 개선)

  • Park, Chul-Won;Park, Jae-Sae;Jung, Yun-Man;Ha, Kyung-Jae;Shin, Myong-Chul
    • The Transactions of the Korean Institute of Electrical Engineers P
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    • v.53 no.2
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    • pp.43-50
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    • 2004
  • Percentage differential characteristic relaying(PDR) has been recognized as the principal basis for power transformer protection. Second harmonic restraint PDR has been widely used for magnetizing inrush in practice. Nowadays, relaying signals can contain 2nd harmonic component to a large extent even in a normal state, and 2nd harmonic ratio indicates a tendency of relative reduction because of the advancement of material. Further, as the power system voltage becomes higher and more underground cables are used, larger 2nd harmonic component in the differential current under internal fault is observed. And then, conventional 2nd harmonic restraint PDR exposes some doubt in reliability. It is, therefore, necessary to develop a new algorithm for performance improvement of conventional protective relaying. This paper proposes an advanced protective relaying algorithm by using voltage-current trend and flux-differential current slope characteristic. To evaluate the performance of the proposed algorithm, we have made comparative studies of PDR, fuzzy relaying and DWT relaying. The paper is constructed power system model including power transformer, utilizing the WatATP, and data collection is made through simulation of various internal faults and inrush. As the results of test, the new proposed algorithm was proven to be faster and more reliable.

Comparing Methodology of Building Energy Analysis - Comparative Analysis from steady-state simulation to data-driven Analysis - (건물에너지 분석 방법론 비교 - Steady-state simulation에서부터 Data-driven 방법론의 비교 분석 -)

  • Cho, Sooyoun;Leigh, Seung-Bok
    • KIEAE Journal
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    • v.17 no.5
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    • pp.77-86
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    • 2017
  • Purpose: Because of the growing concern over fossil fuel use and increasing demand for greenhouse gas emission reduction since the 1990s, the building energy analysis field has produced various types of methods, which are being applied more often and broadly than ever. A lot of research products have been actively proposed in the area of the building energy simulation for over 50 years around the world. However, in the last 20 years, there have been only a few research cases where the trend of building energy analysis is examined, estimated or compared. This research aims to investigate a trend of the building energy analysis by focusing on methodology and characteristics of each method. Method: The research papers addressing the building energy analysis are classified into two types of method: engineering analysis and algorithm estimation. Especially, EPG(Energy Performance Gap), which is the limit both for the existing engineering method and the single algorithm-based estimation method, results from comparing data of two different levels- in other words, real time data and simulation data. Result: When one or more ensemble algorithms are used, more accurate estimations of energy consumption and performance are produced, and thereby improving the problem of energy performance gap.

Item Trend Analysis Considering Social Network Data in Online Shopping Malls (온라인 쇼핑몰에서 소셜 네트워크 데이터를 고려한 상품 트렌드 분석)

  • Park, Soobin;Choi, Dojin;Yoo, Jaesoo;Bok, Kyoungsoo
    • The Journal of the Korea Contents Association
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    • v.20 no.2
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    • pp.96-104
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    • 2020
  • As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.