• Title/Summary/Keyword: demand curve

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Seismic structural demands and inelastic deformation ratios: a theoretical approach

  • Chikh, Benazouz;Mebarki, Ahmed;Laouami, Nacer;Leblouba, Moussa;Mehani, Youcef;Hadid, Mohamed;Kibboua, Abderrahmane;Benouar, Djilali
    • Earthquakes and Structures
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    • v.12 no.4
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    • pp.397-407
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    • 2017
  • To estimate the structural seismic demand, some methods are based on an equivalent linear system such as the Capacity Spectrum Method, the N2 method and the Equivalent Linearization method. Another category, widely investigated, is based on displacement correction such as the Displacement Coefficient Method and the Coefficient Method. Its basic concept consists in converting the elastic linear displacement of an equivalent Single Degree of Freedom system (SDOF) into a corresponding inelastic displacement. It relies on adequate modifying or reduction coefficient such as the inelastic deformation ratio which is usually developed for systems with known ductility factors ($C_{\mu}$) and ($C_R$) for known yield-strength reduction factor. The present paper proposes a rational approach which estimates this inelastic deformation ratio for SDOF bilinear systems by rigorous nonlinear analysis. It proposes a new inelastic deformation ratio which unifies and combines both $C_{\mu}$ and $C_R$ effects. It is defined by the ratio between the inelastic and elastic maximum lateral displacement demands. Three options are investigated in order to express the inelastic response spectra in terms of: ductility demand, yield strength reduction factor, and inelastic deformation ratio which depends on the period, the post-to-preyield stiffness ratio, the yield strength and the peak ground acceleration. This new inelastic deformation ratio ($C_{\eta}$) is describes the response spectra and is related to the capacity curve (pushover curve): normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), natural period (T), peak ductility factor (${\mu}$), and the yield strength reduction factor ($R_y$). For illustrative purposes, instantaneous ductility demand and yield strength reduction factor for a SDOF system subject to various recorded motions (El-Centro 1940 (N/S), Boumerdes: Algeria 2003). The method accuracy is investigated and compared to classical formulations, for various hysteretic models and values of the normalized yield strength coefficient (${\eta}$), post-to-preyield stiffness ratio (${\alpha}$), and natural period (T). Though the ductility demand and yield strength reduction factor differ greatly for some given T and ${\eta}$ ranges, they remain take close when ${\eta}>1$, whereas they are equal to 1 for periods $T{\geq}1s$.

Capacity Spectrum Method Based on Inelastic Displacement Ratio (비탄성변위비를 이용한 능력 스펙트럼법)

  • Han, Sang-Whan;Bae, Mun-Su
    • Journal of the Earthquake Engineering Society of Korea
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    • v.12 no.2
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    • pp.69-80
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    • 2008
  • In this study, improved capacity spectrum method (CSM) is proposed. The method can account for higher mode contribution to the seismic response of MDOF systems. The CSM has been conveniently used for determining maximum roof displacement using both demand spectrum and capacity curve of equivalent SDOF system. Unlike the conventional CSM, the maximum roof displacement is determined without iteration using inelastic displacement ratio and R factor calculated from demand spectrum and capacity curve. Three moment resisting steel frames of 3-, 9- and 20-stories are considered to test the accuracy of the proposed method. Nonlinear response history analysis (NL-RHA) for three frames is also conducted, which is considered as an exact solution. SAC LA 10/50 and 2/50 sets of ground motions are used. Moreover, this study estimates maximum story drift ratios (IDR) using ATC-40 CSM and N2-method and compared with those from the proposed method and NL-RHA. It shows that the proposed CSM estimates the maximum IDR accurately better than the previous methods.

Analysis of Loss Expectancy on Personal Information leakage using Quantitative Invest Decision Model (투자결정 모델을 활용한 개인정보유출의 기대손실 분석)

  • Kim, Jeong Yeon
    • The Journal of Society for e-Business Studies
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    • v.20 no.2
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    • pp.93-106
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    • 2015
  • Providing trading partners with personal information to establish an e-commerce financial transaction is inevitable. Most e-commerce companies keep personal information and transaction data for user's convenience and develop additional services as their applications. However, keeping personal information increases the likelihood of identity theft causing direct or indirect damage while it may simplify repetitive financial transactions. This study introduces risk management methods based on quantitative and qualitative analysis including demand-supply curve model and Gordon & Loeb model to analyze the risks for security management. The empirical analysis with survey results from KISA (Korea Information Security Agency) shows that the root cause of different statistics of personal information leakage incidents according to core business of internet companies is the difference in their Loss Expectancy caused by them. Also we suggest disciplinary compensation and higher standard for personal information protection as a solution to prevent the variation of investment on it between individual companies.

A Study on Optimal Horizontal Alignment Design for PRT Vehicle (PRT 주행선로 최적평면선형 설계에 관한 연구)

  • Um, Ju-Hwan;Kim, Baek-Hyun;Jeong, Rag-Gyo;Kang, Seok-Won;Byun, Yeun-Sub
    • Journal of Digital Convergence
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    • v.12 no.10
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    • pp.283-289
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    • 2014
  • Personal rapid transit(PRT) systems have been highlighted in future transportation developments as a result of their potential as sustainable and eco-friendly transport solutions that provide demand-responsive mobility services. One of the most important characteristics of the personal rapid transit system(PRT) is that it can be constructed and operated at a low cost. A fundamental study on the alignment of the PRT guideway considering running stability was conducted in the present study. In addition, a parameter analysis of the major alignment design variables such as curve radius, transition curve length and cant was performed by vehicle dynamic analysis and optimum guideway alignments were proposed. The analysis results suggested that the theoretical values were satisfied and also confirmed the possibility of reducing the standard.

Identifying Priority Area for Nonpoint Source Pollution Management and Setting up Load Reduction Goals using the Load Duration Curve (부하지속곡선을 이용한 비점오염원 우선관리 지역 선정 및 관리목표 설정 연구)

  • Jang, Sun Sook;Ji, Hyun Seo;Kim, Hak Kwan
    • Journal of The Korean Society of Agricultural Engineers
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    • v.60 no.5
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    • pp.17-27
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    • 2018
  • The objective of this study is to identify the priority area where the nonpoint source pollution (NPS) management is required and to set up the load reduction goals for the identified priority area. In this study, the load duration curve (LDC) was first developed using the flow and water quality data observed at 286 monitoring stations. Based on the developed LDC, the priority area for the NPS pollution management was determined using a three-step method. The 24 watersheds were finally identified as the priority areas for the NPS pollution management. The water quality parameters of concern in the priority areas were the total phosphorus or chemical oxygen demand. The load reduction goals, which were calculated as the percent reduction from current loading levels needed to meet target water quality, ranged from 67.9% to 97.2% during high flows and from 40.3% to 69.5% during moist conditions, respectively. The results from this study will help to identify critical watersheds for NPS program planning purposes. In addition, the process used in this study can be effectively applied to identify the pollutant of concern as well as the load reduction target.

Determination of Important Parameter Control Term for Paldang Lake Water Quality Management using Load Duration Curves (오염부하지속곡선을 이용한 팔당호 수질항목별 중점관리 시점 선정)

  • Kim, Dong Woo;Jang, Mi Jeong;Park, Ji Hyoung;Han, Ihn Sup
    • Journal of Korean Society on Water Environment
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    • v.29 no.6
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    • pp.762-776
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    • 2013
  • Load duration curve was applied to determine important water quality parameter control term for improvement of Paldang lake water quality. Load duration curve was analyzed with long term data from 1985 to 2012 including water quality, flow rate and climate state of Paldang water environment. From the result of flow rate patterns of paldang lake, differences between high and low flow rate of each year showed tendency of increase because rainfall characteristics of paldang lake watershed were changed by climate exchange. Both of land use state of upper Paldang lake watershed and number of limit excess from load duration curve indicated that seasonal action related with land use such as agricultural fertilizer distribution in upper watershed affected Paldang lake water quality. So focused BOD (biological oxygen demand) management during spring season from march to June is required to control organic materials in Paldand lake. The main affecting factor of TOC (total organic carbon) increase in Paldang lake was initial rainfall after march. T-N (total nitrogen) kept increasing during research period, so enhancement of T-N standard is needed to T-N control. Initial rainfall and increase of temperature during spring season from March to June showed a positive correlation with TP (total phosphorus) and Chl-a, respectively.

Harmony Arrangements using B-Spline Tension Curves (B-스플라인 텐션 곡선을 이용한 음악 편곡)

  • Yoo, Min-Joon;Lee, In-Kwon;Kwon, Dae-Hyun
    • Journal of the HCI Society of Korea
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    • v.1 no.1
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    • pp.1-8
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    • 2006
  • We suggest a graphical representation of the tension flow in tonal music using a piecewise parametric curve, which is a function of time illustrating the changing degree of tension in a corresponding chord progression. The tension curve can be edited by using conventional curve editing techniques to reharmonize the original music with reflecting the user's demand to control the tension of music. We introduce three different methods to measure the tension of a chord in terms of a specific key, which can be used to represent the tension of the chord numerically. Then, by interpolating the series of numerical tension values, a tension curve is constructed. In this paper, we show the tension curve editing method can be effectively used in several interesting applications: enhancing or weakening the overall feeling of tension in a whole song, the local control of tension in a specific region of music, the progressive transition of tension flow from source to target chord progressions, and natural connection of two songs with maintaining the smoothness of the tension flow. Our work shows the possibility of controlling the perceptual factor (tension) in music by using numerical methods. Most of the computations used in this paper are not expensive so they can be calculated in real time. We think that an interesting application of our method is an interactive modification of tension in background music according to the user's emotion or current scenario in the interactive environments such as games.

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Estimation of regional flow duration curve applicable to ungauged areas using machine learning technique (머신러닝 기법을 이용한 미계측 유역에 적용 가능한 지역화 유황곡선 산정)

  • Jeung, Se Jin;Lee, Seung Pil;Kim, Byung Sik
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1183-1193
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    • 2021
  • Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

Effects of Strength Reduction Factors for Capacity Spectrum Analysis of Bridge Structures using Inelastic Demand Spectrum (비탄성 요구도 스펙트럼을 이용한 교량구조물의 역량스펙트럼 해석에 대한 강도감소계수의 영향)

  • Song, Jong-Keol;Jin, He-Shou;Jang, Dong-Hui
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.1A
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    • pp.25-37
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    • 2008
  • The capacity spectrum method (CSM) is a simple and graphical seismic analysis procedure. Originally, it has been developed for buildings, but now its applicability has been extended to bridge structures. It is based on the capacity curve estimated by pushover analysis and demand spectrum reduced from linear elastic design spectrum by using effective damping or strength reduction factor. In this paper, the inelastic demand spectrum as the reduced demand spectrum is calculated from the linear elastic design spectrum by using the several formulas for the strength reduction factor. The effects of the strength reduction factor for the capacity spectrum analysis are evaluated for 3 types of symmetric and asymmetric bridge structures. To investigate an accuracy of the CSM which several formulas for strength reduction factor were applied, the maximum displacements estimated by the CSM are compared with the results obtained by nonlinear time history analysis for 8 artificially generated earthquakes. The maximum displacements estimated by the CSM using the SJ formula among the several strength reduction factors provide the most accurate agreement with those calculated by the inelastic time history analysis.

A Study on Shear-Fatigue Behavior of Reinforced Concrete Beams using High Strength Concrete (고강도 콘크리트를 사용한 철근콘크리트 보의 전단피로거동에 관한 연구)

  • 곽계환;박종건
    • Journal of the Korea Concrete Institute
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    • v.11 no.5
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    • pp.119-130
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    • 1999
  • Recently, as the building structure has been larger, higher, longer and more specialized, the demand of material with high-strength concrete for building has been increasing. In this research, silica-fume was used as an admixture in order to get a high-strength concrete. From the test result, High-strength concrete with cylinder strength of 1,200kgf/$\textrm{cm}^2$ in 28-days was produced and tested. The static test was carried out to measure the ultimate load, the initial load of flexural and diagonal cracking, crack patterns and fracture modes. The load versus strain and load versus deflection relations were obtained from the static test. The relation of cycle loading to deflections on the mid-span, the crack propagation and the modes of failure according to cycle number, fatigue life and S-N curve were observed through the fatigue test. Based on the fatigue test results, high-strength reinforced concrete beams failed to 57~66 percent of the static ultimate strength. Fatigue strength about two million cycles from S-N curves was certified by 60 percent of static ultimate strength.