Dalian In China Research Articles

A study on multiple types of yard cranes rescheduling in ports considering carbon emission

ABSTRACT This paper investigates the rescheduling problem of multiple oil-driven and electric-driven yard cranes across multiple container yards in semi-automated container terminals under random faults. Efficient fault diagnosis and handling mechanisms are provided to mitigate the effects of faults on the performance of yard operations. At the same time, a rescheduling model is proposed, aiming to minimize weighted carbon emissions and completion time. By analyzing the features of the problem, a tailored adaptive large neighborhood search (ALNS) algorithm is designed to solve the model. The effectiveness of the ALNS is verified through problem instances generated from the operational data of the port of Dalian in China. The factors considered in this paper are relevant to actual port operations, thus offering reliable solutions for scheduling and greening of ports.

Apportioning and Locating PM2.5 Sources Affecting Coastal Cities: Ulsan in South Korea and Dalian in China

Apportioning and Locating PM2.5 Sources Affecting Coastal Cities: Ulsan in South Korea and Dalian in China

Optimizing design and performance assessment of a sustainability hydrogen supply chain network: A multi-period model for China

The potential future use of hydrogen as transportation fuel should be assessed from supply chain point. However, the main challenge to motivate hydrogen supply chain (HSC) network is the insufficiency of the present hydrogen infrastructure. This paper presents a mixed integer linear programming (MILP) optimization model for a rational HSC design, given that primary energy source availability, production technologies, transportation modes and storage types. A sustainable principle based on Markov chain is innovatively introduced in the design of HSC network. The strategic decisions for sustainability infrastructure plans can be hierarchically analyzed in time-associated steps (2025–2030–2035). Meanwhile the spatiotemporal-resolved design is further used for an explicit consideration of specific city (Dalian in China), not heavily focused on national/country scale. Furthermore, optimizations are evaluated with total daily costs, carbon tax and CO2 emissions reduction constraints. The results show that the route of WE(S2)→WE(S2)→WE(S3) is the strategic decisions for Dalian hydrogen infrastructure plan from economic-environmental sustainable viewpoint, with the whole HSC costs of 18.44 $ kg−1 H2 in 2025, 10.56 $ kg−1 H2 in 2030 and 5.98 $ kg−1 H2 in 2035. Finally, the proposed design can provide policy-makers with the selection of sustainability pathways for dynamic hydrogen development planning.

Techno-Economic and Sensitivity Investigation of a Novel Perovskite Solar Cells Based High Efficient Hybrid Electric Sources for Off-Shore Oil Ships

Herein, this study presents for the first time third generation perovskite solar cells (PSCs) for enhancing the performance of off-shore oil ships. The off-shore oil ships need a high efficient hybrid solar energy- batteries system for enhancing the ships efficiency and reduce the pollutants resulting from these ships. In this study, an efficient model that consists of hybrid renewable energy system (HRES) suitable for the off-shore oil ships is presented and discussed. The model uses the PSCs as a solar energy source thanks to their high efficiency reaching now almost 26% based on nanotechnology in fabrication process. For determining the optimum quantities of the HRES model the HOMER software was used. The model succeeded in reducing the pollutants and the greenhouse gases (GHGs). The direction of the ship under study is from Dalian in China to Hurghada in Egypt where the data of electric load was chosen based on this journey which is real data. The full components of the model used are PSCs, Batteries and Diesel engine. Two PSCs arrays with 600 kW and 900 kW were used in the study beside 600 kW silicon based solar cells array for comparison between technologies of solar cells. The PSCs array were formed based on a laboratory fabricated PSCs that have 23.5 mA.Cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-2</sup> as a short circuit current density, 1.085 V as open circuit voltage, 0.79 as a fill factor and 20.05% as a power conversion efficiency. The results revealed that the suggested model can help in reducing the total fuel consumption and the GHGs by 5,765,575 L and 15,592,017 kg for 600 kW silicon, 15,177,375 L and 15,662,875 kg for 600kW PSCs case, 17,634,350 L and 22,307,325 kg for 900kW PSCs case respectively related to using only diesel generator during the ship journey under the same conditions. Based on the obtained results, using the solar cells especially the recent technology base ones is attractive and highly recommended on the off-shore oil ships. This leading to both the fuel consumptions and cost reduction.

Spatial differences in thermal comfort in summer in coastal areas: A study on Dalian, China.

Thermal comfort is an important indicator for evaluating the environment of urban public space, and appropriate thermal comfort can effectively prolong the duration of outdoor activities. In the existing studies, there is a lack of thermal comfort comparison between hot spots and cold spots. In this study, we selected the coastal city of Dalian in China as our study area and conducted field investigations on the thermal comfort of two landmark resorts, namely, a downtown commercial street and coastal leisure park. The study was conducted on typical summer days and consisted of interviewing several residents to understand their thermal comfort requirements. We investigated the thermal expectations of the interviewees through meteorological measurements and questionnaires. The universal thermal climate index (UTCI) was used to determine the thermal benchmarks of the on-site subjects. The results indicated that (1) globe temperature and air temperature were the most important factors that affected thermal comfort, followed by relative humidity and wind speed in summer daytime. (2) Shaded spaces are more comfortable than open spaces, and tree shade is preferred over artificial shade in coastal park. (3) The neutral UTCI (NUTCI) of the respondents were 24.1°C (coastal park) and 26.0°C (commercial street); the neutral UTCI ranges (NUTCIR) were 20.8–27.4°C (coastal park) and 23.3–28.7°C (commercial street). (4) The upper thermal acceptable range limits of the coastal park and commercial street were 30.2 and 32.1°C, respectively, which were substantially higher than the upper NUTCIR limit, indicating that the residents in Dalian were well-adapted to hot weather. The results can provide a good reference for determining ideal design strategies to optimize the thermal environment of urban outdoor recreation spaces in summers and improve the quality of life in coastal cities.

A Hybrid Ensemble Model for Interval Prediction of Solar Power Output in Ship Onboard Power Systems

Application of solar energy into ship power systems has been increasingly drawing attention. Accordingly, an accurate prediction of solar power plays a significant role in the shipboard power system operation. However, a photovoltaic (PV) generation system on the shipboard, different from the one on land, has to suffer more dramatic power fluctuations caused by weather variations and motions of the ships, which increase the uncertainty of PV power outputs. This paper proposes a hybrid ensemble method for optimal interval prediction of onboard solar power based on a stochastic ship motion model. A set of machine learning techniques are combined together with the particle swarm optimization (PSO) to constitute a hybrid forecasting model, including a back propagation neural network (BPNN), a radial basis function neural network (RBFNN), an extreme learning machine (ELM) and an Elman neural network. Furthermore, for different learning algorithms, an ensemble strategy is employed to reduce the forecasting error and various environmental variables along with ship moving and rolling impacts are taken into account. The developed model has been practically tested on a power system on a large oil tanker penetrated with PV energy and the data along the typical navigation route from Dalian in China to Aden in Yemen are selected for solar power prediction. The simulation results demonstrate its high accuracy, which provides a reliable reference for ship power system operators to achieve a better energy management.

Health risk assessment of heavy metals and pesticides: A case study in the main drinking water source in Dalian, China.

Health risk associated with drinking water has attracted increasing attention worldwide. Here, we conducted a survey on the main drinking water sources of Dalian in China to clarify the local human health risk associated with heavy metal and pesticide contaminants in the drinking water sources. The results showed that six heavy metals, namely, copper (Cu), zinc (Zn), cadmium (Cd), nickel (Ni), arsenic (As), and mercury (Hg), and two pesticides (atrazine and acetochlor) were detected in water samples, where the highest concentration of Hg (0.0621 μg L-1) exceeded the domestic standard only. In addition to the above-mentioned metals, Cr was also detected in the sediment/soil samples. As to the pesticides, atrazine, acetochlor, hexachlorobenzene, p,p'-DDE, and p,p'-DDD were detected in the sediment/soil samples at ng g-1 levels, and atrazine and acetochlor were found in water samples at ng L-1 levels. The human health risk assessment showed no marked difference in carcinogenic and noncarcinogenic risks from drinking water. Our study approved that hexachlorobenzene and arsenic were the main contributors to human carcinogenic risks, which were calculated at the level of 10-4. Furthermore, sediment and soil ingestion was considered as the major source of human health risk in our study area. This study revealed the current pollution status in the surrounding area of the drinking water source and the main source associated with human health risk, which established a sound basis for further decision-making to take necessary action on pollution control.

Analysis of performance and economical efficiency of two-stage compression heat pump system with inter-stage injection in cold regions of northern China

The low temperature adaptability of air source heat pump in the field of building heating in cold regions has always been a hot topic. At present, the combination of inter-stage injection technology and two-stage compression can effectively solve the problem of low temperature adaptability. Therefore, in the present paper, the two-stage compression heat pump system with inter-stage injection was taken as the research project. Based on the simulation model of the two-stage compression heat pump system, the process of inter-stage injection coupling between the low-stage compressor and the high-stage compressor was analyzed. Based on the experimental results, the effects of inter-stage injection process on the inter-stage pressure, inter-stage temperature and thermal performance parameters of the two-stage compression system were analyzed. The results show that as the mass of inter-stage injection increases, the inter-stage pressure will increase significantly and then increase slowly; and the inter-stage temperature will increase slowly and then decrease significantly; both the heat output and the COP will increase first and then slightly decrease. In addition, the heat output will increase by about 8%–15%, and the COP will increase by about 5%–12%. Finally, the two regions including Beijing and Dalian in China were selected, and the economical efficiency of the system in applications was analyzed in combination with the experimental results of variable working conditions of the system.

Joint collection mode of waste mobile phones based on residents' preferences: A case of Dalian in China

The continuing increase of the popularity of mobile phones generates a large volume of waste mobile phones. The efficient collection of this waste has become a focus and frontier of both academic research and related business. This paper reviews the waste mobile phone collection in Dalian, China. The findings show that several challenges currently impede the implementation of collection, including unsmooth collection channels, poor convenience, and low environmental awareness of residents. A new joint collection mode is put forward to increase the waste mobile phone collection rate. In the mode, the responsibilities of each stakeholder (including the collecting enterprise, the third-party logistics company, the government, and the resident) are clarified. Moreover, a conjoint analysis method is applied to identify residents' willingness for collection. The obtained results show that compensation mode, collection price, and convenience degree are the three factors that influence the prevailing preferences of residents. Collection services with high market share must satisfy the concourse of three conditions. The collection price exceeds 30% of the mobile phone's original price, the compensation mode is cash and information service is provided. These results can provide a reference for the service design of collection mode and the formulation of relevant corporate strategies.

Simulation-based optimization for urban transportation demand management strategy

Transportation demand management (TDM) is one of the important methods for solving the problem of increasingly severe urban traffic congestion. This paper proposes a bi-level model to optimize urban TDM strategies based on simulation. The upper level is the TDM strategy optimization model, searching for the optimal TDM strategy. The lower level is a traffic assignment model based on the simulation, assigning traffic flow to multimodal transport networks according to the candidate TDM strategies. A heuristic algorithm is also defined and implemented to optimize TDM strategies. Based on VISSIM simulation, the optimization for TDM strategies proposed in this paper is validated with the research area of Harbor Square–San Ba Square–Er Qi Square in Dalian in China. The results show that the optimization of urban TDM strategies can effectively alleviate urban traffic congestion. It provides a scientific decision basis for urban TDM policy.

Novel Adaptive Multi-Clustering Algorithm-Based Optimal ESS Sizing in Ship Power System Considering Uncertainty

The optimal sizing of an energy storage system (ESS) in a power generation system that incorporates photovoltaic (PV) generation is crucial in a power grid for which the reduction of CO2 emissions is important. This problem is particularly challenging when it relates to the power system of a ship because it involves uncertain meteorological and load data along a navigation route. This paper proposes a novel method for multi-objective minimization of investment/replacement cost, fuel cost, and CO2 emissions, to find the optimal size of the ESS considering life-span of the ESS. The generation of power by PV modules on a ship is affected by temporal and geographical variations of irradiation along the navigation route. In particular, operating load conditions and irradiation are uncertain. This paper proposes a novel algorithm for partitioning high-dimensional uncertain data into tractable clusters solved by deterministic optimization method. Case studies of an all-electric ship along a route from Dalian in China to Aden in Yemen are shown to demonstrate the applicability of the proposed clustering-based stochastic optimization method.

Research and Application of an Air Quality Early Warning System Based on a Modified Least Squares Support Vector Machine and a Cloud Model.

The worsening atmospheric pollution increases the necessity of air quality early warning systems (EWSs). Despite the fact that a massive amount of investigation about EWS in theory and practicality has been conducted by numerous researchers, studies concerning the quantification of uncertain information and comprehensive evaluation are still lacking, which impedes further development in the area. In this paper, firstly a comprehensive warning system is proposed, which consists of two vital indispensable modules, namely effective forecasting and scientific evaluation, respectively. For the forecasting module, a novel hybrid model combining the theory of data preprocessing and numerical optimization is first developed to implement effective forecasting for air pollutant concentration. Especially, in order to further enhance the accuracy and robustness of the warning system, interval forecasting is implemented to quantify the uncertainties generated by forecasts, which can provide significant risk signals by using point forecasting for decision-makers. For the evaluation module, a cloud model, based on probability and fuzzy set theory, is developed to perform comprehensive evaluations of air quality, which can realize the transformation between qualitative concept and quantitative data. To verify the effectiveness and efficiency of the warning system, extensive simulations based on air pollutants data from Dalian in China were effectively implemented, which illustrate that the warning system is not only remarkably high-performance, but also widely applicable.

Estimating urban vegetation fraction across 25 cities in pan-Pacific using Landsat time series data

Urbanization globally is consistently reshaping the natural landscape to accommodate the growing human population. Urban vegetation plays a key role in moderating environmental impacts caused by urbanization and is critically important for local economic, social and cultural development. The differing patterns of human population growth, varying urban structures and development stages, results in highly varied spatial and temporal vegetation patterns particularly in the pan-Pacific region which has some of the fastest urbanization rates globally. Yet spatially-explicit temporal information on the amount and change of urban vegetation is rarely documented particularly in less developed nations. Remote sensing offers an exceptional data source and a unique perspective to map urban vegetation and change due to its consistency and ubiquitous nature. In this research, we assess the vegetation fractions of 25 cities across 12 pan-Pacific countries using annual gap-free Landsat surface reflectance products acquired from 1984 to 2012, using sub-pixel, spectral unmixing approaches. Vegetation change trends were then analyzed using Mann-Kendall statistics and Theil-Sen slope estimators. Unmixing results successfully mapped urban vegetation for pixels located in urban parks, forested mountainous regions, as well as agricultural land (correlation coefficient ranging from 0.66 to 0.77). The greatest vegetation loss from 1984 to 2012 was found in Shanghai, Tianjin, and Dalian in China. In contrast, cities including Vancouver (Canada) and Seattle (USA) showed stable vegetation trends through time. Using temporal trend analysis, our results suggest that it is possible to reduce noise and outliers caused by phenological changes particularly in cropland using dense new Landsat time series approaches. We conclude that simple yet effective approaches of unmixing Landsat time series data for assessing spatial and temporal changes of urban vegetation at regional scales can provide critical information for urban planners and anthropogenic studies globally.

Design and Construction of a Highway Double-Deck Suspension Bridge

The nearly finished Xinghai Bay Bridge at the southern seaside of Dalian in China is a long-span, double-deck, cross-sea suspension bridge. This bridge is the largest span highway double-deck suspension bridge with anchorage at sea in China. In view of the particular problems posed by the surrounding conditions, functional requirements, and aesthetic considerations, this project required a special structural design and innovations in construction technology. These innovations—including the steel truss design and erection process, the main cable-anchoring strategy, and the anchorage foundation design and construction techniques—are detailed in this paper.

Optimal Tilt Angle of Photovoltaic Arrays and Economic Allocation of Energy Storage System on Large Oil Tanker Ship

This study optimizes the tilt angle of photovoltaic (PV) panels on a large oil tanker ship system and considers the impact of partial shading to improve the performance of the PV system. This work presents a novel method that considers the difference between the expected and real outputs of PV modules to optimize the size of energy storage system (ESS). The method also takes into account the cost of wasted power, the capital cost of the system, fuel cost and the CO2 emissions. Unlike on land, power generation using a PV on a ship depends on the date, latitude and longitude of the navigation. Accordingly, this work considers a route from Dalian in China to Aden in Yemen, accounting for the seasonal and geographical variations of solar irradiation. This proposed method adopts five conditions associated with the navigation route to model the total shipload. Various cases are discussed in detail to demonstrate the effectiveness of the proposed algorithm.

Influencing Factors of Real Estate Price based on Grey Relational Analysis

This research answers the question of how to measure the impact of different factors on real estate price. It is well known that the real estate price is influenced by many factors, however, how to determine the factors and evaluate the influence degree is an important problem. Most of the previous research used multivariate statistical model, this paper proposed a different way—Grey Relational Analysis (GRA). This paper selected 11 influencing factors from economic area, market area, cost area and social area. Then the method to identify the influence degree of factors based on GRA was proposed. In addition, for explaining application of the influencing factors, the case of Dalian in China is studied. The re- sult is that the key influencing factors are gross domestic product, average wage of employed persons in construction, an- nual per capita disposable income of urban households and per capita building space of urban household. The GRA is an effective way to assess the impact of different factors on real estate price and provides a good tool for designers, users, decision makers and researchers.

Optimal sizing of hybrid PV/diesel/battery in ship power system

Owing to the strict restrictions imposed by the Marine Pollution Protocol and the rapid development of renewable energy, the use of solar generation and energy storage systems in ship power systems has been increasingly attracting attention. However, the improper sizing of a hybrid power generation system in a ship power system will result in a high investment cost and increased greenhouse gas emission. This paper proposes a method for determining the optimal size of the photovoltaic (PV) generation system, the diesel generator and the energy storage system in a stand-alone ship power system that minimizes the investment cost, fuel cost and the CO2 emissions. The power generation from PV modules on a ship relies on the date, local time, time zone, longitude and latitude along a navigation route and is different from the conditions of power systems on land. Thus, a method, which takes the seasonal and geographical variation of solar irradiations and temperatures along the route from Dalian in China to Aden in Yemen into account, for correcting the output of PV modules is developed in this paper. The proposed method considers five conditions along the navigation route to model the total ship load. Four cases are studied in details to demonstrate the applicability of the proposed algorithm.

A two-phase model for dry port location with an application to the port of Dalian in China

This paper provides guidance for an optimal and reasonable dry port layout for the port of Dalian in China. We present a two-phase framework on the location of dry ports, which solves the selection of candidate inland cities and optimal dry port location choice, respectively. Fuzzy C-Means Clustering is applied to select alternative cities in the vast hinterland of the seaport of Dalian, with a view to identify evaluation factors that affect the location selection decision. A cost-minimisation linear programming solution is proposed, with the aid of a genetic algorithm, to choose the optimal location as well as capacity level among the candidate inland cities.

The Establishment of Green Industry Evaluation Index System Based on Dynamic Clustering—an Empirical Study from Dalian in China

U s e the method of spearman correlation analysis and dynamic clustering to delete indicators and build an evaluation index system of the green industry. The specialties and contributions of this paper lie in three aspects. Firstly, screen indicators according to the different effects on the clustering results of the evaluation objects from having or not having specific indicators, and delete the indicators that have no influence on the evaluation objects clustering results so as to guarantee that every selected indicator has effects on the clustering results. Secondly, delete the indicators with high correlation coefficient in the same criteria by spearman correlation analysis to avoid information duplication of the indicators. Thirdly, the eventually established indicator system reflects 94.18% of the original information by 27% of the indicators. In the future, we can establish a green industry evaluation software system. By using this system, the government can evaluate the development of green industry easily and establish policies to balance the development of different area.

An Analysis on the Color Trend of Street Fashion in Dalian, China(paper no.1) - Focused on 2010 Summer -

The purpose of this study is to investigate the effect of the traditional color sentiment on the contemporary clothing color by studying the pictures of street fashion of Dalian in China, in view of the clothing color of women in their 20-30 years of age having highest purchasing power, along with traditional Chinese color. The clothing color is various in frequency depending on the items in street fashion. Due to the seasonal impact of summer, the most frequent item was one-piece dress with the Multi of various color patterns, followed by White, Black, PB, R and B category. In the top color, the White was most prevalent color due to the seasonal factor, followed by Black, Grey, Multi, R, Y, RP category. Achromatic color is more dominant with the ratio of 7:3, comparing with its counterpart, which consists of R and Y category of V, B, P, VP tone. In the bottom color, Dp tone of PB shows most high frequency, followed by Black. This results illustrate that Chinese women prefer blue jeans and to be looked as slimmer by using of the dark colors. In the accessories, colors of bags and shoes show different results. The bag colors show the high frequency of Dk tone, YR category, and the chromatic colors are little bit dominant than achromatic ones with the ratio of 5.3:4.7. On the contrary, the shoes colors show the highest frequency in Black, the achromatic colors are more dominant than chromatic ones with the ratio of 6.6:3.4. These results somewhat diverge from the international color trend. Color trend in Dalian street fashion in which the high frequency of V tone is observed through all the colors of the items followed by P, VP, Lgr tone in sequence. In the light of Chinese traditional color preference, this result denotes that the traditional color preferences of red, yellow are still affecting the contemporary color choices of clothing in Chinese women. The high incidence of PB category in the bottom and one-piece dress does not seem to have its origin form traditional Chinese color sentiment.