scholarly journals Joint Configuration and Scheduling Optimization of a Dual-Trolley Quay Crane and Automatic Guided Vehicles with Consideration of Vessel Stability

2019 ◽  
Vol 12 (1) ◽  
pp. 24 ◽  
Author(s):  
Lijun Yue ◽  
Houming Fan ◽  
Chunxin Zhai
Keyword(s):  
Energy Consumption ◽  
Container Terminal ◽  
Utilization Rate ◽  
Two Phase ◽  
Improve Energy Efficiency ◽  
Automatic Guided Vehicles ◽  
Proposed Model ◽  
Partial Enumeration ◽  
The Stability ◽  
Vessel Stability

This study proposes a formulation to optimize operational efficiency of a dual-trolley quay crane and automatic guided vehicles (AGVs) to reduce energy consumption at an automated container terminal. A two-phase model is used to minimize energy consumption during loading and discharging operations, as well as maximize the utilization rate of the AGVs, with consideration of relevant constraints such as the capacity of buffers for the quay crane (QC) and yard, the stability of vessel, the maximum endurance of an AGV, and the available laytime for handling. We propose a constrained partial enumeration strategy to construct quay crane schedules and a genetic algorithm to solve the AGV scheduling problem. Finally, Yangshan Phase IV automated container terminal’s data is used to verify the validity and applicability of the proposed model. The results of the tests provide evidence that the proposed method can improve energy efficiency.

scholarly journals Experimental Study on Series Operation of Sliding Vane Pump and Centrifugal Pump

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Tao Li ◽  
Weiming Zhang ◽  
Ming Jiang ◽  
Zhengyang Li
Keyword(s):  
Experimental Study ◽  
Energy Consumption ◽  
Centrifugal Pump ◽  
Phase Flow ◽  
Vane Pump ◽  
Two Phase ◽  
Pumping System ◽  
System Flow ◽  
The Stability ◽  
Different Characteristics

A platform for sliding vane pump and centrifugal pump tests is installed to study the series operation of them under different characteristics of pipeline. Firstly, the sliding vane pump and the centrifugal pump work independently, and the performance is recorded. Then, the two types of pumps are combined together, with the sliding vane pump acting as the feeding pump. Comparison is made between the performance of the independently working pump and the performance of series operation pump. Results show that the system flow rate is determined by the sliding vane pump. In order to ensure the stability of the series operation pumping system, the energy consumption required by the pipeline under the system flow should be greater than the pressure energy centrifugal pump can generate. Otherwise, the centrifugal pump can not operate stably, with reflux, swirl, gas-liquid two-phase flow in the runner and strong vibration and noise. The sliding vane pump can be in serial operation with the centrifugal pump under limited conditions.

scholarly journals Geometrical Variable Weights Buffer GM(1,1) Model and Its Application in Forecasting of China’s Energy Consumption

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Li ◽  
Han Xie
Keyword(s):  
Energy Consumption ◽  
Maximum Degree ◽  
Original Data ◽  
Grey Model ◽  
Variable Weights ◽  
Proposed Model ◽  
Term Energy ◽  
Long Term Forecasting ◽  
The Stability

In order to improve the application area and the prediction accuracy of GM(1,1) model, a novel Grey model is proposed in this paper. To remedy the defects about the applications of traditional Grey model and buffer operators in medium- and long-term forecasting, a Variable Weights Buffer Grey model is proposed. The proposed model integrates the variable weights buffer operator with the background value optimized GM(1,1) model to implement dynamic preprocessing of original data. Taking the maximum degree of Grey incidence between fitting value and actual value as objective function, then the optimal buffer factor is chosen, which can improve forecasting precision, make forecasting results embodying the internal trend of original data to the maximum extent, and improve the stability of the prediction. To verify the effectiveness of the proposed model, the energy consumption in China from 2002 to 2009 is used for the modeling to forecast the energy consumption in China from 2010 to 2020, and the forecasting results prove that the GVGM(1,1) model has remarkably improved the forecasting ability of medium- and long-term energy consumption in China.

scholarly journals Thermal-hydraulic issues of flow boiling and condensation in organic Rankine cycle heat exchangers

2012 ◽  
Vol 33 (1) ◽  
pp. 41-66 ◽  
Author(s):  
Jarosław Mikielewicz ◽  
Dariusz Mikielewicz
Keyword(s):  
Heat Exchangers ◽  
Flow Boiling ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Phase Changes ◽  
Rate Equations ◽  
Working Fluid ◽  
Two Phase ◽  
Proposed Model ◽  
The Stability

Thermal-hydraulic issues of flow boiling and condensation in organic Rankine cycle heat exchangers In the paper presented are the issues related to the design and operation of micro heat exchangers, where phase changes can occur, applicable to the domestic micro combined heat and power (CHP) unit. Analysed is the stability of the two-phase flow in such unit. A simple hydraulic model presented in the paper enables for the stability analysis of the system and analysis of disturbance propagation caused by a jump change of the flow rate. Equations of the system dynamics as well as properties of the working fluid are strongly non-linear. A proposed model can be applicable in designing the system of flow control in micro heat exchangers operating in the considered CHP unit.

From biorefineries to bioproducts: conversion of pretreated pulp from biorefining streams to lignocellulose nanofibers

TAPPI Journal ◽  
2019 ◽  
Vol 18 (4) ◽  
pp. 233-241
Author(s):  
CHENGGUI SUN ◽  
RICHARD CHANDRA ◽  
YAMAN BOLUK
Keyword(s):  
Energy Consumption ◽  
Enzymatic Hydrolysis ◽  
Rheological Behavior ◽  
Material Basis ◽  
Softwood Pulp ◽  
Energy Consumptions ◽  
Hardwood Pulp ◽  
The Stability ◽  
Lignocellulose Nanofibers

This study investigates the use of pretreatment and enzymatic hydrolysis side streams and conversion to lignocellulose nanofibers. We used a steam-exploded and partial enzymatic hydrolyzed hardwood pulp and an organosolv pretreated softwood pulp to prepare lignocellulose nanofibers (LCNF) via microfluidization. The energies applied on fibrillation were estimated to examine the energy consumption levels of LCNF production. The energy consumptions of the fibrillation processes of the hardwood LCNF production and the softwood LCNF production were about 7040-14080 kWh/ton and 4640 kWh/ton on a dry material basis, respectively. The morphology and dimension of developed hardwood and softwood LCNFs and the stability and rheological behavior of their suspensions were investigated and are discussed.

The influence of the Stokes and Archimedes forces on the stability of a two-phase flow

2003 ◽  
Vol 3 ◽  
pp. 266-270
Author(s):  
B.H. Khudjuyerov ◽  
I.A. Chuliev
Keyword(s):  
Spectral Method ◽  
Stability Region ◽  
Gas Flow ◽  
Two Phase Flow ◽  
Solid Phase ◽  
Stability Characteristic ◽  
Phase Flow ◽  
Two Phase ◽  
The Stability

The problem of the stability of a two-phase flow is considered. The solution of the stability equations is performed by the spectral method using polynomials of Chebyshev. A decrease in the stability region gas flow with the addition of particles of the solid phase. The analysis influence on the stability characteristic of Stokes and Archimedes forces.

scholarly journals Economical Speed for Optimizing the Travel Time and Energy Consumption in Train Scheduling using a Fuzzy Multi-Objective Model

2021 ◽  
Author(s):  
Ahmad Reza Jafarian-Moghaddam
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Pollutant Emissions ◽  
Scheduling Problems ◽  
Train Scheduling ◽  
Multi Objective ◽  
Consumption Ratio ◽  
Proposed Model ◽  
Objective Model ◽  
Time And Energy

AbstractSpeed is one of the most influential variables in both energy consumption and train scheduling problems. Increasing speed guarantees punctuality, thereby improving railroad capacity and railway stakeholders’ satisfaction and revenues. However, a rise in speed leads to more energy consumption, costs, and thus, more pollutant emissions. Therefore, determining an economic speed, which requires a trade-off between the user’s expectations and the capabilities of the railway system in providing tractive forces to overcome the running resistance due to rail route and moving conditions, is a critical challenge in railway studies. This paper proposes a new fuzzy multi-objective model, which, by integrating micro and macro levels and determining the economical speed for trains in block sections, can optimize train travel time and energy consumption. Implementing the proposed model in a real case with different scenarios for train scheduling reveals that this model can enhance the total travel time by 19% without changing the energy consumption ratio. The proposed model has little need for input from experts’ opinions to determine the rates and parameters.

scholarly journals Predicting the Energy Consumption of a Robot in an Exploration Task Using Optimized Neural Networks

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 920
Author(s):  
Liesle Caballero ◽  
Álvaro Perafan ◽  
Martha Rinaldy ◽  
Winston Percybrooks
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Mobile Robot ◽  
Energy Budget ◽  
Dynamic Models ◽  
Pearson Correlation ◽  
Experimental Conditions ◽  
Grid Map ◽  
Proposed Model ◽  
Exploration Task

This paper deals with the problem of determining a useful energy budget for a mobile robot in a given environment without having to carry out experimental measures for every possible exploration task. The proposed solution uses machine learning models trained on a subset of possible exploration tasks but able to make predictions on untested scenarios. Additionally, the proposed model does not use any kinematic or dynamic models of the robot, which are not always available. The method is based on a neural network with hyperparameter optimization to improve performance. Tabu List optimization strategy is used to determine the hyperparameter values (number of layers and number of neurons per layer) that minimize the percentage relative absolute error (%RAE) while maximize the Pearson correlation coefficient (R) between predicted data and actual data measured under a number of experimental conditions. Once the optimized artificial neural network is trained, it can be used to predict the performance of an exploration algorithm on arbitrary variations of a grid map scenario. Based on such prediction, it is possible to know the energy needed for the robot to complete the exploration task. A total of 128 tests were carried out using a robot executing two exploration algorithms in a grid map with the objective of locating a target whose location is not known a priori by the robot. The experimental energy consumption was measured and compared with the prediction of our model. A success rate of 96.093% was obtained, measured as the percentage of tests where the energy budget suggested by the model was enough to actually carry out the task when compared to the actual energy consumed in the test, suggesting that the proposed model could be useful for energy budgeting in actual mobile robot applications.

scholarly journals Evaluation of the energy consumption of container diesel trucks in a container terminal: A case study at Klaipeda port

2021 ◽  
Vol 104 (3) ◽  
pp. 003685042110355
Author(s):  
Tomas Eglynas ◽  
Sergej Jakovlev ◽  
Valdas Jankunas ◽  
Rimantas Didziokas ◽  
Jolanta Januteniene ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Dynamic Properties ◽  
Container Terminal ◽  
Superposition Principle ◽  
Critical Parameters ◽  
Container Transportation ◽  
Industrial Emissions ◽  
Transportation Process ◽  
Diesel Trucks

Introduction: In the paper, we examine the energy consumption efficiency of specialized container diesel trucks engaged in container transportation at a seaport terminal. Objectives: Using the container terminal at Klaipėda in Lithuania as the background for the research, we produced an improved energy consumption model for measuring the theoretical energy consumption and regeneration of diesel trucks at the terminal and provide a comparative analysis. Methods: We created a mathematical model which describes the instantaneous energy consumption of the diesel trucks, taking into account their dynamic properties and the overall geometry of their routes—“Ship-Truck-Stack-Ship”—using the superposition principle. We investigated other critical parameters relevant to the model and provide a statistical evaluation of the transportation process using data from a case study of Klaipėda port, where we collected measurements of container transportation parameters using georeferenced movement detection and logs from wireless equipment positioned on the diesel-powered container trucks. Results: The modeling results showed that an instantaneous evaluation of energy consumption can reveal areas in the container transportation process which have the highest energy loss and require the introduction of new management and process control initiatives to address the regulations which are designed to decrease harmful industrial emissions and encourage novel technologies and thereby increase the eco-friendliness of existing systems. Conclusion: Based on the research results, the article can provide a reference for the estimation of diesel truck efficiency in seaport terminal operations.

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