• International Journal of Naval Architecture and Ocean Engineering
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• 제11권1호
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• pp.22-32
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• 2019

On offshore platforms, oil and gas leaks are apt to be the initial events of major accidents that may result in significant loss of life and property damage. To prevent accidents induced by leakage, it is vital to perform a case-specific and accurate risk assessment. This paper presents an integrated method of Ddynamic Qquantitative Rrisk Aassessment (DQRA)-using the Decision Making Trial and Evaluation Laboratory (DEMATEL)-Bayesian Network (BN)-for evaluation of the system vulnerabilities and prediction of the occurrence probabilities of accidents induced by leakage. In the method, three-level indicators are established to identify factors, events, and subsystems that may lead to leakage, fire, and explosion. The critical indicators that directly influence the evolution of risk are identified using DEMATEL. Then, a sequential model is developed to describe the escalation of initial events using an Event Tree (ET), which is converted into a BN to calculate the posterior probabilities of indicators. Using the newly introduced accident precursor data, the failure probabilities of safety barriers and basic factors, and the occurrence probabilities of different consequences can be updated using the BN. The proposed method overcomes the limitations of traditional methods that cannot effectively utilize the operational data of platforms. This work shows trends of accident risks over time and provides useful information for risk control of floating marine platforms.

• 대한안전경영과학회지
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• 제4권2호
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• pp.11-22
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• 2002

In this study, an asymmetric lifting posture prediction model was developed, which was a three-dimensional model with 12 links and 23 degrees of freedom open kinematic chains. Although previous researchers have proposed biomechanical, psychophysical, or physiological measures as cost functions, for solving redundancy, they lack in accuracy in predicting actual lifting postures and most of them are confined to the two-dimensional model. To develop an asymmetric lifting posture prediction model, we used the resolved motion method for accurately simulating the lifting motion in a reasonable time. Furthermore, in solving the redundant problem of the human posture prediction, a moment weighted Joint Range Availability (JRA) was used as a cost function in order to consider dynamic lifting. However, it is known that the moment weighted JRA as a cost function predicted the lower extremity and L5/S1 joint motions better than the upper extremities, while the constant weighted JRA as a cost function predicted the latter better than the former. To compensate for this, we proposed a hybrid moment weighted JRA as a new cost function with moment weighted for only the lower extremity. In order to validate the proposed cost function, the predicted and real lifting postures for various lifting conditions were compared by using the root mean square(RMS) error. This hybrid JRA reduced RMS more than the previous cost functions. Therefore, it is concluded that the cost function of a hybrid moment weighted JRA can be used to predict three-dimensional lifting postures. To compare with the predicted trajectories and the real lifting movements, graphical validations were performed. The results also showed that the hybrid moment weighted cost function model was found to have generated the postures more similar to the real movements.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.1-7
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.210-216
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• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• 한국도로학회논문집
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• 제14권4호
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• pp.29-36
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• 2012

PURPOSES : Plastic deformation is frequently made in intersection asphalt pavement at its early age due to deceleration and stoppage of vehicles. This study has been performed to provide a mechanistic basis for reasonable selection of paving method to minimize the plastic deformation at intersection. METHODS : Pavement layer, temperature, traffic volume of the intersections managed by the Daejeon Regional Construction and Management Administration were collected to calculate asphalt dynamic modulus with pavement depth by using a prediction equation suggested by the Korean pavement design guide. Performance of ordinary dense-graded asphalt pavement, polymer modified asphalt pavement, and fiber reinforced asphalt pavement was analyzed by finite element method and the results were used in a performance model to predict the plastic deformation. RESULTS : In aspect of performance, the three paving methods were usable under low traffic while the fiber reinforced asphalt pavement was the most suitable under heavy traffic. CONCLUSIONS : Reasonable paving method suitable for traffic characteristics in the intersection might be decided by considering economic feasibility.

• 대한기계학회논문집B
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• 제30권1호
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• pp.87-94
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• 2006

This paper presents the hydrodynamic design and performance analysis method for a miniaturized centrifugal blood pump using three-dimensional computational fluid dynamics (CFD) code. In order to obtain the hydraulically high efficient configuration of a miniaturized centrifugal blood pump for cardiopulmonary circulation, a well-established commercial CFD code was incorporated considering detailed flow dynamic phenomena in the blood pump system. A prototype of centrifugal blood pump developed by the present design and analysis method has been tested in the mock circulatory system. Predicted results by the CFD code agree very well with in vitro hydraulic performance data for a centrifugal blood pump over the entire operating conditions. Preliminary in vivo animal testing has also been conducted to demonstrate the hemodynamic feasibility for use of centrifugal blood pump as a mechanical circulatory support. A miniaturized centrifugal blood pump developed by the hydraulic design optimization and performance prediction method presented herein shows the possibility of a good candidate for intra and extracorporeal cardiopulmonary circulation pump in the near future.

• Structural Engineering and Mechanics
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• 제28권4호
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• pp.387-410
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• 2008

The fatigue damage accumulation rates of horizontally curved thin walled box-girder bridge have been estimated from vehicle-induced dynamic stress history using rain flow cycle counting method in the time domain approach. The curved box-girder bridge has been numerically modeled using computationally efficient thin walled box-beam finite elements, which take into account the important structural actions like torsional warping, distortion and distortional warping in addition to the conventional displacement and rotational degrees of freedom. Vehicle model includes heave-pitch-roll degrees of freedom with longitudinal and transverse input to the wheels. The bridge deck unevenness, which is taken as inputs to the vehicle wheels, has been assumed to be a realization of homogeneous random process specified by a power spectral density (PSD) function. The linear damage accumulation theory has been applied to calculate fatigue life. The fatigue life estimated by cycle counting method in time domain has been compared with those found by estimating the PSD of response in frequency domain. The frequency domain method uses an analytical expression involving spectral moment characteristics of stress process. The effects of some of the important parameters on fatigue life of the curved box bridge have been studied.

• 한국물환경학회지
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• 제23권1호
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• pp.38-45
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• 2007

A one-dimensional kinematic wave model was used to calculate temporal and spatial changes of the highway runoff. Infiltration into pavement was considered using Darcy's law, as a function of flow depth and pavement hydraulic conductivity ($K_p$). The model equation was calculated using the method of characteristics (MOC), which provided stable solutions for the model equation. 22 storm events monitored in a highway runoff monitoring site in west Los Angeles in the U.S. were used for the model calculation and evaluation. Using three different values of $K_p$ ($5{\times}10^{-6}$, $10^{-5}$, and $2{\times}10^{-5}cm/sec$), total runoff volume and peak flow rate were calculated and then compared with the measured data for each storm event. According to the calculation results, $10^{-5}cm/sec$ was considered a site representative value of $K_p$. The study suggested a one-dimensional method to predict hydrodynamic behavior of highway runoff, which is required for the water quality prediction.

• Steel and Composite Structures
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• 제13권2호
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• pp.139-155
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• 2012

Serviceability rather than strength is the most critical design requirement for vibration-vulnerable floor constructions. Annoying vibrations due to normal walking activity have been observed more frequently on long-span lightweight floor systems in office and commercial retail buildings, raising the need for the development of floor vibration design procedures. This paper highlights some limitations of one of the most commonly used guidelines AISC/CISC DG11, and proposes improvements to this method. Design charts and approximate closed form formulas to estimate the walking response are developed in which various factors relating to the dynamic characteristics of both the floor and the excitation are considered. The accuracy of the proposed formulas and other proposals found in the literature is examined. The proposed modifications would be significant, especially with long-span floors where vibration levels may be underestimated by the current design procedure. The application of the proposed prediction method is illustrated by worked examples that reveal a good agreement with results obtained from finite element analyses and experiments. The presented work would enhance the accuracy and maintain the simplicity and convenience of the design guideline.

• Advances in nano research
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• 제12권4호
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• pp.387-403
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• 2022

Silica nanoparticles, which have a broad range of sizes and specific surface features, have been used in many industrial applications. This study was conducted to synthesize monodispersed silica nanoparticles directly from tetraethyl orthosilicate (TEOS) with an alkaline catalyst (NH₃) based on the sol-gel process and the Stöber method. A central composite design (CCD) is used to build a second-order (quadratic) model for the response variables without requiring a complete three-level factorial experiment. The process was then optimized to achieve the minimum particle size with the lowest concentration of TEOS. Dynamic light scattering and scanning electron microscopy were used to analyze the size, dispersity, and morphology of the synthesized nanoparticles. After optimization, a confirmation test was carried out to evaluate the confidence level of the software prediction. The results revealed that the predicted optimization is consistent with experimental procedures, and the model is significant at the 95% confidence level.