scholarly journals SIMULATION MODELLING AS A DRY CARGO TERMINALS’ CALCULATION TOOL

2018 ◽  
pp. 100-108 ◽  
Author(s):  
Andrei Stanislavovich Tkachenko ◽  
German Borisovich Popov ◽  
Alexander Viktorovich Kirichenko ◽  
Alexander Lvovich Kuznetsov
Keyword(s):  
Performance Indicators ◽  
Simulation Modelling ◽  
Container Terminals ◽  
Technological Parameters ◽  
Cargo Handling ◽  
Modelling Method ◽  
Terminal Performance ◽  
Proposed Model ◽  
Wide Range ◽  
Operational Processes

Making decisions based on intuitive analytical methods is becoming a dangerous practice in modern conditions of competition and high capital capacity of cargo terminals operation. Such methods are allowing to evaluate an average of performance indicators for cargo terminals at very best, while their market stability is becoming gradually more dependent on the pattern of distribution around the averages. This research proposes a method of cargo terminal performance analysis, based on the simulation modelling. The importance of focusing on cargo flows through the terminal, instead of modelling only the operational processes of a certain cargo terminal, is emphasized. The paper describes the approach to creating such models of distribution around the averages. The proposed model structure is targeted at a wide range of "dry port" type container terminals. There have been analyzed all possible traffic flows which require different capacities and technological resources for handling at the terminal. A standard description of the freight routes passing through the terminal as a simulated model provides low labor-intensiveness of planning experiments which helps easily change the cargo handling flow chart of the terminal analyzed. The efficiency of the simulation modelling method for calculating technological parameters of dry cargo terminals has been approved in the course of implementing several large projects.

scholarly journals Benchmarking analysis for automated and non-automated container terminals

2021 ◽  
pp. 76-83
Author(s):  
А.Л. Кузнецов ◽  
А.В. Галин ◽  
В.Н. Щербакова-Слюсаренко ◽  
Г.Б. Попов
Keyword(s):  
Performance Indicators ◽  
Container Terminals ◽  
Cargo Handling ◽  
Storage Solutions ◽  
Significant Performance ◽  
Storage Area ◽  
And Storage ◽  
Typical Design ◽  
Area Planning ◽  
Electronic Document Interchange

Автоматизация контейнерных терминалов является одним из главных глобальных трендов в развитии технологий перегрузки и хранения контейнерных грузов. Системы автоматизации, применяемые на контейнерных терминалах, могут в разной степени включать в себя функции управления контейнеропотоком, планирования работы склада терминала, грузового планирования загрузки / разгрузки судов, автоматизации работы оборудования на терминале, планирования расстановки оборудования, электронного документооборота и другие. На традиционных (неавтоматизированных) терминалах большая часть перечисленных выше задач решается с непосредственным участием человека. Это приводит к неравномерности в интенсивности погрузочно-разгрузочных работ. В данной статье приводится сравнение показателей эффективности работы автоматизированных и неавтоматизированных контейнерных терминалов. Для целей сравнительного анализа применяется методика бенчмаркинга на основе обосновано выбранных показателей работы. Наиболее значимые показатели работы включают в себя напряженность работ причального фронта, частную производительность оборудования и интенсивность использования площади. Значения этих показателей сравниваются не только между автоматизированными и неавтоматизированными контейнерными терминалами, но и с типовыми показателями, используемыми при проектировании новых терминалов. Сделаны выводы и предположения о зависимостях некоторых показателей от уровня автоматизации терминала. Automatization is one of the main trends in global container handling and storage solutions. Automatization systems, applied at container terminals, may include following container flow controlling functions: storage area planning, container vessel cargo (bay) planning, cargo handling equipment, cargo handling equipment positioning, EDI (electronic document interchange), etc. Many of the functions mentioned are carried out manually at conventional non-automated container terminals. This leads to unsteadiness of cargo operation rates. This research shows the results of analytical comparison of selected KPIs (key performance indicators) of automated and non-automated container terminals. Method of benchmarking is used to compare certain KPIs. Among the most significant performance indicators are berth operations intensity, local productivity of equipment, intensity of storage area usage. These indicators are compared not only between automated and non-automated container terminals, but are also compared to typical design indicators used for drafting new terminals. A number of conclusions and suggestions about dependencies between KPIs and automatization level at container terminals is made.

scholarly journals Performance of the Semarang Container Terminal

2020 ◽  
Vol 9 (4) ◽  
pp. 2164-2167
Keyword(s):  
Performance Indicators ◽  
Container Terminal ◽  
Methodological Approach ◽  
Research Work ◽  
Container Terminals ◽  
Literature Study ◽  
Important Indicator ◽  
Major Function ◽  
Terminal Performance ◽  
Loading And Unloading

The number of container boxes handled at the container terminal dynamically fluctuates as a function of a number of parameters. The most prominent variables influencing are the Economics’ National Program, the location and trading characteristics of the terminal, and the land use programs of hinterlands. Further, it is one terminal could serve more than one quay simultaneously. This research was conducted in order to determine the optimal performance of container terminals, along with the utilities to the increase in container terminal services Semarang. The results are expected to reveal the existing problems related to the services of a container terminal, especially regarding the following matters: review and develop performance indicators container terminals that is optimized especially for Semarang container terminal (TPKS), knowing the performance level of the container terminal at TPKS utility, and knowing the number of containers optimal service units, ranging from dock to yard container based on the rate of arrival of containers in TPKS. The research methodology used in this study is as follows: conducting a literature study/library, in order to obtain an overview of problems faced by the Semarang container terminal (TPKS), data collection related to the performance of container terminal, processing and analyzing research data to obtain a technical description of the various parameters needed in evaluating the Container Terminal Performance Indicators, Optimal Value of the service unit loading and unloading containers, ships and goods flow forecasting, producing Container Terminal Performance Indicators, formulate conclusions and recommendations from the results obtained in the performance evaluation process and service optimization Container Terminal loading and unloading of containers. The container terminal performance is an important indicator to evaluate the operational continuity and smoothness, in fulfilling its major function in serving the transportation mechanism of goods. One method to evaluate the container terminal performance is to observe the service level and utility of this terminal. From the evaluation’s results, a program to improve and to enhance the service levels for the future could be designed. The methodological approach accessed in this research work includes BOR (Berth Occupancy Ratio) data collecting, data processing and analysis using multiple methods, and producing a conclusion. The results are also to typical research topics. The study yielded in a BOR for the period till 2015 based on a BOR mooring of 34 - 45 percent. The benefits of this research can be used to improve container terminal performance.

Periodizing Secularization

2019 ◽  
Author(s):  
Clive D. Field
Keyword(s):  
Performance Indicators ◽  
Primary Sources ◽  
Preliminary Evaluation ◽  
Master Narrative ◽  
Religious Socialization ◽  
Religious Revival ◽  
Religious Transformation ◽  
Wide Range ◽  
Descriptive Sense ◽  
The Church

Moving beyond the (now somewhat tired) debates about secularization as paradigm, theory, or master narrative, this book focuses upon the empirical evidence for secularization, viewed in its descriptive sense as the waning social influence of religion, in Britain. Particular emphasis is attached to the two key performance indicators of religious allegiance and churchgoing, each subsuming several sub-indicators, between 1880 and 1945, including the first substantive account of secularization during the fin de siècle. A wide range of primary sources is deployed, many relatively or entirely unknown, and with due regard to their methodological and interpretative challenges. On the back of them, a cross-cutting statistical measure of ‘active church adherence’ is devised, which clearly shows how secularization has been a reality and a gradual, not revolutionary, process. The most likely causes of secularization were an incremental demise of a Sabbatarian culture and of religious socialization (in the church, at home, and in the school). The analysis is also extended backwards, to include a summary of developments during the eighteenth and early nineteenth centuries; and laterally, to incorporate a preliminary evaluation of a six-dimensional model of ‘diffusive religion’, demonstrating that these alternative performance indicators have hitherto failed to prove that secularization has not occurred. The book is designed as a prequel to the author’s previous volumes on the chronology of British secularization – Britain’s Last Religious Revival? (2015) and Secularization in the Long 1960s (2017). Together, they offer a holistic picture of religious transformation in Britain during the key secularizing century of 1880–1980. [250 words]

scholarly journals Prediction of Dead Oil Viscosity: Machine Learning vs. Classical Correlations

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 930
Author(s):  
Fahimeh Hadavimoghaddam ◽  
Mehdi Ostadhassan ◽  
Ehsan Heidaryan ◽  
Mohammad Ali Sadri ◽  
Inna Chapanova ◽  
...  
Keyword(s):  
Machine Learning ◽  
Viscosity Data ◽  
Oil Viscosity ◽  
Pvt Data ◽  
Proposed Model ◽  
Wide Range ◽  
Engineering Problems ◽  
Functional Forms ◽  
Insight Into

Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems and one of the most unreliable properties to predict with classical black oil correlations. Determination of dead oil viscosity by experiments is expensive and time-consuming, which means developing an accurate and quick prediction model is required. This paper implements six machine learning models: random forest (RF), lightgbm, XGBoost, multilayer perceptron (MLP) neural network, stochastic real-valued (SRV) and SuperLearner to predict dead oil viscosity. More than 2000 pressure–volume–temperature (PVT) data were used for developing and testing these models. A huge range of viscosity data were used, from light intermediate to heavy oil. In this study, we give insight into the performance of different functional forms that have been used in the literature to formulate dead oil viscosity. The results show that the functional form f(γAPI,T), has the best performance, and additional correlating parameters might be unnecessary. Furthermore, SuperLearner outperformed other machine learning (ML) algorithms as well as common correlations that are based on the metric analysis. The SuperLearner model can potentially replace the empirical models for viscosity predictions on a wide range of viscosities (any oil type). Ultimately, the proposed model is capable of simulating the true physical trend of the dead oil viscosity with variations of oil API gravity, temperature and shear rate.

scholarly journals Remote Sensing Image Stripe Detecting and Destriping Using the Joint Sparsity Constraint with Iterative Support Detection

2019 ◽  
Vol 11 (6) ◽  
pp. 608 ◽  
Author(s):  
Yun-Jia Sun ◽  
Ting-Zhu Huang ◽  
Tian-Hui Ma ◽  
Yong Chen
Keyword(s):  
Remote Sensing ◽  
Real Data ◽  
Total Variation Regularization ◽  
Joint Sparsity ◽  
Alternating Direction ◽  
Proposed Model ◽  
Comparison Results ◽  
Wide Range ◽  
Image Edges ◽  
Full Consideration

Remote sensing images have been applied to a wide range of fields, but they are often degraded by various types of stripes, which affect the image visual quality and limit the subsequent processing tasks. Most existing destriping methods fail to exploit the stripe properties adequately, leading to suboptimal performance. Based on a full consideration of the stripe properties, we propose a new destriping model to achieve stripe detection and stripe removal simultaneously. In this model, we adopt the unidirectional total variation regularization to depict the directional property of stripes and the weighted ℓ 2 , 1 -norm regularization to depict the joint sparsity of stripes. Then, we combine the alternating direction method of multipliers and iterative support detection to solve the proposed model effectively. Comparison results on simulated and real data suggest that the proposed method can remove and detect stripes effectively while preserving image edges and details.

LOW-NOISE SILICON-ON-INSULATOR HALL DEVICES

2004 ◽  
Vol 04 (02) ◽  
pp. L345-L354 ◽  
Author(s):  
Y. HADDAB ◽  
V. MOSSER ◽  
M. LYSOWEC ◽  
J. SUSKI ◽  
L. DEMEUS ◽  
...  
Keyword(s):  
Noise Level ◽  
Low Voltage ◽  
Silicon Layer ◽  
Electrical Current ◽  
Low Noise ◽  
Silicon On Insulator ◽  
Technological Parameters ◽  
Wide Range ◽  
Hall Sensors ◽  
Soi Technology

Hall sensors are used in a very wide range of applications. A very demanding one is electrical current measurement for metering purposes. In addition to high precision and stability, a sufficiently low noise level is required. Cost reduction through sensor integration with low-voltage/low-power electronics is also desirable. The purpose of this work is to investigate the possible use of SOI (Silicon On Insulator) technology for this integration. We have fabricated SOI Hall devices exploring the useful range of silicon layer thickness and doping level. We show that noise is influenced by the presence of LOCOS and p-n depletion zones near the edges of the active zones of the devices. A proper choice of SOI technological parameters and process flow leads to up to 18 dB reduction in Hall sensor noise level. This result can be extended to many categories of devices fabricated using SOI technology.

scholarly journals A Model for Analysing the Collective Dynamic Behaviour and Characterising the Exploitation of Population-Based Algorithms

2014 ◽  
Vol 22 (1) ◽  
pp. 159-188 ◽  
Author(s):  
Mikdam Turkey ◽  
Riccardo Poli
Keyword(s):  
Population Dynamics ◽  
Dynamic Behaviour ◽  
Fitness Landscape ◽  
Population Based ◽  
Levels Of Abstraction ◽  
Collective Dynamic ◽  
Model Studies ◽  
Proposed Model ◽  
Wide Range ◽  
Multiple Levels

Several previous studies have focused on modelling and analysing the collective dynamic behaviour of population-based algorithms. However, an empirical approach for identifying and characterising such a behaviour is surprisingly lacking. In this paper, we present a new model to capture this collective behaviour, and to extract and quantify features associated with it. The proposed model studies the topological distribution of an algorithm's activity from both a genotypic and a phenotypic perspective, and represents population dynamics using multiple levels of abstraction. The model can have different instantiations. Here it has been implemented using a modified version of self-organising maps. These are used to represent and track the population motion in the fitness landscape as the algorithm operates on solving a problem. Based on this model, we developed a set of features that characterise the population's collective dynamic behaviour. By analysing them and revealing their dependency on fitness distributions, we were then able to define an indicator of the exploitation behaviour of an algorithm. This is an entropy-based measure that assesses the dependency on fitness distributions of different features of population dynamics. To test the proposed measures, evolutionary algorithms with different crossover operators, selection pressure levels and population handling techniques have been examined, which lead populations to exhibit a wide range of exploitation-exploration behaviours.

Prediction of High Viscosity Liquid/Gas Two-Phase Slug Length in Horizontal and Slightly Inclined Pipelines

2021 ◽  
Author(s):  
Omar Shaaban ◽  
Eissa Al-Safran
Keyword(s):  
Numerical Optimization ◽  
Flow Behavior ◽  
Mechanistic Model ◽  
High Viscosity ◽  
Oil Well ◽  
Liquid Slug ◽  
Two Phase ◽  
Proposed Model ◽  
Wide Range ◽  
Flow Closure

Abstract The production and transportation of high viscosity liquid/gas two-phase along petroleum production system is a challenging operation due to the lack of understanding the flow behavior and characteristics. In particular, accurate prediction of two-phase slug length in pipes is crucial to efficiently operate and safely design oil well and separation facilities. The objective of this study is to develop a mechanistic model to predict high viscosity liquid slug length in pipelines and to optimize the proper set of closure relationships required to ensure high accuracy prediction. A large high viscosity liquid slug length database is collected and presented in this study, against which the proposed model is validated and compared with other models. A mechanistic slug length model is derived based on the first principles of mass and momentum balances over a two-phase slug unit, which requires a set of closure relationships of other slug characteristics. To select the proper set of closure relationships, a numerical optimization is carried out using a large slug length dataset to minimize the prediction error. Thousands of combinations of various slug flow closure relationships were evaluated to identify the most appropriate relationships for the proposed slug length model under high viscosity slug length condition. Results show that the proposed slug length mechanistic model is applicable for a wide range of liquid viscosities and is sensitive to the selected closure relationships. Results revealed that the optimum closure relationships combination is Archibong-Eso et al. (2018) for slug frequency, Malnes (1983) for slug liquid holdup, Jeyachandra et al. (2012) for drift velocity, and Nicklin et al. (1962) for the distribution coefficient. Using the above set of closure relationships, model validation yields 37.8% absolute average percent error, outperforming all existing slug length models.

Estimation of CO2 Diffusivity in Brine by Use of the Genetic Algorithm and Mixed Kernels-Based Support Vector Machine Model

2018 ◽  
Vol 141 (4) ◽  
Author(s):  
Qihong Feng ◽  
Ronghao Cui ◽  
Sen Wang ◽  
Jin Zhang ◽  
Zhe Jiang
Keyword(s):  
Genetic Algorithm ◽  
Support Vector Machine ◽  
Diffusion Coefficient ◽  
Co2 Storage ◽  
Co2 Injection ◽  
Support Vector ◽  
Hybrid Technique ◽  
Machine Model ◽  
Proposed Model ◽  
Wide Range

Diffusion coefficient of carbon dioxide (CO2), a significant parameter describing the mass transfer process, exerts a profound influence on the safety of CO2 storage in depleted reservoirs, saline aquifers, and marine ecosystems. However, experimental determination of diffusion coefficient in CO2-brine system is time-consuming and complex because the procedure requires sophisticated laboratory equipment and reasonable interpretation methods. To facilitate the acquisition of more accurate values, an intelligent model, termed MKSVM-GA, is developed using a hybrid technique of support vector machine (SVM), mixed kernels (MK), and genetic algorithm (GA). Confirmed by the statistical evaluation indicators, our proposed model exhibits excellent performance with high accuracy and strong robustness in a wide range of temperatures (273–473.15 K), pressures (0.1–49.3 MPa), and viscosities (0.139–1.950 mPa·s). Our results show that the proposed model is more applicable than the artificial neural network (ANN) model at this sample size, which is superior to four commonly used traditional empirical correlations. The technique presented in this study can provide a fast and precise prediction of CO2 diffusivity in brine at reservoir conditions for the engineering design and the technical risk assessment during the process of CO2 injection.

scholarly journals Numerical Model for the Analysis of Thermal Transients in District Heating Networks

2020 ◽  
Vol 197 ◽  
pp. 01004
Author(s):  
Martina Capone ◽  
Elisa Guelpa ◽  
Vittorio Verda
Keyword(s):  
Carbon Dioxide Emissions ◽  
Renewable Energy Sources ◽  
Management Strategies ◽  
District Heating ◽  
Equivalent Model ◽  
Computational Time ◽  
Physical Parameters ◽  
Thermal Transients ◽  
Proposed Model ◽  
Wide Range

As District Heating (DH) networks are experiencing an evolution towards the so-called 4th generation, there is a need to update the currently used models to take into account the ever-increasing complexity of this technology. Indeed, to further improve the reduction in energy consumption and carbon-dioxide emissions, a wide range of technologies and management strategies are being introduced within district heating, such as a large exploitation of Renewable Energy Sources (RES). As a consequence, thermal transients assume a major importance, posing the need to redefine the relevant physical parameters and to develop a model which accurately describes their behaviour. In this framework, this paper proposes a quantitative analysis of the influence of the pipe heat-capacity on the model. Moreover, an equivalent-model, which is able to take into account the two heat capacities of steel and water in just one equation, is proposed and compared with two commonly used approaches. One of the features of the proposed model is the suitability for application to large networks. To prove its capabilities, an application to the Turin district heating network, which is among the largest systems in Europe, is proposed. Results show significant improvements in terms of accuracy over computational time ratio.

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