• Earthquakes and Structures
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• v.19 no.6
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• pp.471-484
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• 2020

Previous earthquakes show that, structural safety evaluations should include the evaluation of nonstructural components. Failure of nonstructural components can affect the operational capacity of critical facilities, such as hospitals and fire stations, which can cause an increase in number of deaths. Additionally, failure of nonstructural components may result in economic, architectural, and historical losses of community. Accelerations and random vibrations must be under the predefined limitations in structures with high technological equipment, data centers in this case. Failure of server equipment and anchored server racks are investigated in this study. A probabilistic study is completed for a low-rise rigid sample structure. The structure is investigated in two versions, (i) conventional fixed-based structure and (ii) with a base isolation system. Seismic hazard assessment is completed for the selected site. Monte Carlo simulations are generated with selected parameters. Uncertainties in both structural parameters and mechanical properties of isolation system are included in simulations. Anchorage failure and vibration failures are investigated. Different methods to generate fragility curves are used. The site-specific annual hazard curve is used to generate risk curves for two different structures. A risk matrix is proposed for the design of data centers. Results show that base isolation systems reduce the failure probability significantly in higher floors. It was also understood that, base isolation systems are highly sensitive to earthquake characteristics rather than variability in structural and mechanical properties, in terms of accelerations. Another outcome is that code-provided anchorage failure limitations are more vulnerable than the random vibration failure limitations of server equipment.

• Geomechanics and Engineering
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• v.23 no.6
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• pp.575-585
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• 2020

In this numerical study, the 2D dynamic behavior of a clayey basin and its effect on damage pattern over basin edge are investigated. To attain this goal, a fully nonlinear time domain analysis method has been applied. Then, the fragility curves of the considered two typical industrial structures for that certain point are estimated using the acceleration time histories recorded at each surface point. The results show that the use of the damage related parameters in site effect analyses, instead of amplification curves, can yield more realistic estimation of the basin dynamic response. In a distance about 150 m from outcrop at the basin edge, the differences between fragility curves increase when increasing the distance from outcrop with respect to the reference rock site. Outside this region and towards the basin center, they tend to occur in rather single curves. Furthermore, to connect the structural damage to the basin edge effect, the earthquake demand value at different points for two typical structures was evaluated. It was seen that the probability of occurrence of damage increases over 250 m from outcrop, while the effect of the basin edge was limited to 150 m in case of the basin edge evaluation by using fragility curves.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.229-244
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• 2022

This paper investigates the seismic performance of buildings designed using DDBD (Direct Displacement based Design) and FBD (Force based Design) approaches from the probabilistic viewpoint. It aims to estimate the collapse capacity of structures and assess the adequacy of seismic design codes. In this regard, (i) IDA (Incremental Dynamic Analysis) curves, (ii) interstory drift demand distribution curves, (iii) fragility curves, and (iv) the methodology provided by FEMA P-695 are applied to examine two groups of RC moment resistant frame buildings: 8-story structures with different plans, to study the effect of different span arrangements; and 3-, 7- and 12-story structures with a fixed plan, to study the dynamic behavior of the buildings. Structural modeling is performed in OpenSees software and validated using the results of an experimental model. It is concluded that increasing the building height would not significantly affect the response estimation of IDA and fragility curves of DDBD-designed structures, while the change in span arrangements is effective in estimating responses. In the investigation of the code adequacy, unlike the FBD approach, the DDBD can satisfy the performance criteria presented in FEMA P-695 and hence provide excellent performance.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1312-1320
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• 2022

The earlier studies have analyzed theoretical links between nuclear energy and carbon dioxide (CO₂) emissions concerning territorial (or production-based) emissions. Here using the latest available dataset, this study explores the impacts of nuclear energy on production-based and consumption-based CO₂ emission in the era of globalization for the Organization for Economic Co-operation and Development (OECD) countries. The Driscoll-Kraay regression method reveals that nuclear energy is beneficial for the reduction of production-based CO₂ emissions. However, it is revealed that nuclear energy does not reduce consumption-based CO₂ emissions that are traded internationally and hence not comprised in conventional production-based emissions (territory) inventories. Globalization tends to reduce both production-based and demand-based carbon emissions. Finally, Environmental Kuznets Curve (EKC) is validated for both kinds of CO₂ emissions. The findings may deliver practical policy implications related to nuclear energy and CO₂ emissions for selected countries.

• Structural Engineering and Mechanics
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• v.88 no.4
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• pp.311-322
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• 2023

Riverine flood is one of the critical natural threats to river-crossing bridges. As floods are the most-occurred natural hazard worldwide, survival probability of bridges due to floods must be assessed in a speedy but precise manner. In this regard, the paper presents a reliability-based approach for a rapid assessment of failure probability of vulnerable bridge components under floods. This robust method is generic in nature and can be applied to both concrete and steel girder bridges. The developed methodology essentially utilizes limit state performance functions, expressed in terms of capacity and flood demand, for probable failure modes of various vulnerable components of bridges. Advanced First Order Reliability Method (AFORM), Monte Carlo Simulation (MCS), and Latin Hypercube Simulation (LHS) techniques are applied for the purpose of reliability assessment and developing flood fragility curves of bridges in which flow velocity and water height are taken as flood intensity measures. Upon validating the proposed method, it is applied to a case study bridge that experiences the flood scenario of a river in Gujarat, India. Research outcome portrays how effectively and efficiently the proposed reliability-based method can be applied for a quick assessment of flood vulnerability of bridges in any flood-prone region of interest.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.157-168
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• 2009

The random utility theory and the multinomial logit model (including a more recent variant--the mixed multinomial logit) derived from it have constituted a back bone for theoretical and empirical analyses of various travel demand features including mode choice. In their empirical applications, however, it is customary to specify random utilities which are linear in modal attributes such as time and cost, and in socio-economic variables. The linearity helps easy derivation of important information such as value of travel time savings by calculating marginal rate of substitution between time and cost. In this paper the author focuses on the very linearity of the random utilities. Taking into account the fact that the mode chooser is also labour supplier, commodity consumer as well as leisure-seeker, the author sets up a maximization model of the traveller, which encompasses various economic activities of the traveller. The author derive from the model the indifference curve defined on the space of modal attributes, time and cost and investigate under what conditions the random utility of the traveller becomes linear. It turns out that there exist the conditions under which the random utility is really linear in modal attributes, but the property does not hold when the traveller has a corner solution on the space of modal attributes, or when the primary utility function of the traveller is directly affected by labour provided and/or the travel time itself. As a corollary of the analysis, a random utility is suggested, approximated up to the second order of the variables involved for empirical studies of the field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.569-575
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• 2020

Recently, research on renewable energy technologies has come into the spotlight due to rising concerns over the depletion of fossil fuels and greenhouse gas emissions. Demand for portable electronic and wearable devices is increasing, and electronic devices are becoming smaller. Energy harvesting is a technology for overcoming limitations such as battery size and usage time. In this paper, the V-I characteristic curve and internal resistance of thermal electric devices were analyzed, and MPPT control methods were compared. The Perturbation and Observation (P&O) control method is economically inefficient because two sensors are required to measure the voltage and current of a Thermoelectric Generator(TEG). Therefore, this paper proposes a new MPPT control method that tracks MPP using only one sensor for the regulation of the output voltage. The proposed MPPT control method uses the relationship between the output voltage of the load and the duty ratio. Control is done by periodically sampling the output voltage of the DC-DC converter to increase or decrease the duty ratio to find the optimal duty ratio and maintain the MPP. A DC-DC converter was designed using a cascaded boost-buck converter, which has a two-switch topology. The proposed MPPT control method was verified by simulations using PSIM, and the results show that a voltage, current, and power of V=4.2 V, I=2.5 A, and P=10.5 W were obtained at the MPP from the V-I characteristic curve of the TEG.

• Earthquakes and Structures
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• v.13 no.1
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• pp.59-66
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• 2017

Modern seismic codes rely on performance-based seismic design methodology which requires that the structures withstand inelastic deformation. Many studies have focused on the inelastic deformation ratio evaluation (ratio between the inelastic and elastic maximum lateral displacement demands) for various inelastic spectra. This paper investigates the inelastic response spectra through the ductility demand ${\mu}$, the yield strength reduction factor $R_y$, and the inelastic deformation ratio. They depend on the vibration period T, the post-to-preyield stiffness ratio ${\alpha}$, the peak ground acceleration (PGA), and the normalized yield strength coefficient ${\eta}$ (ratio of yield strength coefficient divided by the PGA). A new inelastic deformation ratio $C_{\eta}$ is defined; it is related to the capacity curve (pushover curve) through the coefficient (${\eta}$) and the ratio (${\alpha}$) that are used as control parameters. A set of 140 real ground motions is selected. The structures are bilinear inelastic single degree of freedom systems (SDOF). The sensitivity of the resulting inelastic deformation ratio mean values is discussed for different levels of normalized yield strength coefficient. The influence of vibration period T, post-to-preyield stiffness ratio ${\alpha}$, normalized yield strength coefficient ${\eta}$, earthquake magnitude, ruptures distance (i.e., to fault rupture) and site conditions is also investigated. A regression analysis leads to simplified expressions of this inelastic deformation ratio. These simplified equations estimate the inelastic deformation ratio for structures, which is a key parameter for design or evaluation. The results show that, for a given level of normalized yield strength coefficient, these inelastic displacement ratios become non sensitive to none of the rupture distance, the earthquake magnitude or the site class. Furthermore, they show that the post-to-preyield stiffness has a negligible effect on the inelastic deformation ratio if the normalized yield strength coefficient is greater than unity.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.75-84
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• 2023

Many developing countries face challenges in estimating long-term discharge due to the lack of hydrological data for water supply planning, making it difficult to establish a rational water supply plan for decision-making on water distribution. The study area, the Bandung region in Indonesia, is experiencing rapid urbanization and population concentration, leading to a severe shortage of freshwater. The absence of water reservoir prediction methods has resulted in a water supply rate of approximately 20%. In this study, we aimed to propose an approach for predicting water reservoirs in developing countries by analyzing water safety and potential water supply using the MODSIM (Modified SIMYLD) network model. To assess the suitability of the MODSIM model, we applied the unit hydrograph method to calculate long-term discharge based on 19 years of discharge data (2002-2020) from the Pataruman observation station. The analysis confirmed alignment with the existing monthly optimal operation curve. The analysis of power plant capacity revealed a difference of approximately 0.30% to 0.50%, and the water intake safety at the Pataruman point showed 1.64% for Q95% flow and 0.47% for Q355 flow higher. Operational efficiency, compared to the existing reservoir optimal operation curve, was measured at around 1%, confirming the potential of using the MODSIM network model for water supply evaluation and the need for water supply facilities.