Search results for: freight%20village

Authors: Apisit Nawapanpong, Natthapat Boonjerm

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This project aims to analyze and identify the flight plan of low-altitude aviation in Thailand and other countries. The development of UAV technology has led the innovation and revolution in the aviation industry; this includes the development of new modes of passenger or freight transportation, and it has also affected other industries widely. At present, this technology is being developed rapidly and has been tested all over the world to make the most efficient for technology or innovation, and it is likely to grow more extensively. However, no flight plan for low-altitude operation has been published by the government organization; when compared with high-altitude aviation with manned aircraft, various unique factors are different, whether mission, operation, altitude range or airspace restrictions. In the study of the essential components of low-altitude operation measures to be practical and tangible, there were major problems, so the main consideration of this project is to analyze the components of low-altitude operations which are conducted up to the altitudes of 400 ft or 120 meters above ground level referring to the terrain, for example, air traffic management, classification of aircraft, basic necessity and safety, and control area. This research will focus on confirming the theory through qualitative and quantitative research combined with theoretical modeling and regulatory framework and by gaining insights from various positions in aviation industries, including aviation experts, government officials, air traffic controllers, pilots, and airline operators to identify the critical essential components of low-altitude flight operation. This project analyzes by using computer programs for science and statistics research to prove that the result is equivalent to the theory and be beneficial for regulating the flight plan for low-altitude operation by different essential components from this project and can be further developed for future studies and research in aviation industries.

Keywords: low-altitude aviation, UAV technology, flight plan, air traffic management, safety measures

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Authors: Patel Himeshkumar Ashokbhai, Suchit Sharma, Arvind Kumar Garg

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The results obtained from settling test of coal fines are used as an important tool to select the dewatering equipment such as thickeners, centrifuges and filters. Coal being hydrophobic in nature does not easily settle when mixed with water. Coal slurry that takes longer time to release water is highly undesirable because it poses additional challenge during sedimentation, centrifuge and filtration. If filter cake has higher than permitted moisture content then it not only creates handling problems but inflated freight costs and reduction in input and productivity for coke oven charges. It is to be noted that coal fines drastically increase moisture percentage in filter cake hence are to be minimized. To increase settling rate of coal fines in slurry chemical substances called flocculants or coagulants are added that cause coal particles to flocculate or coalesce into larger particles. These larger particles settle at faster rate and have higher settling velocity. Other important factors affecting settling rate are flocculent dosage, slurry or pulp density and particle size. Hence in this paper we tried to study the settling characteristic of clean coal fines by varying one of the four factors namely 1. Flocculant Dosage (acryl-amide) 2. pH of the water 3. Bulk density 4. Particle size of clean coal fines in settling experiment and drew important conclusions. Result of this paper will be much useful not only for coal beneficiation plant design but also for cost reduction of coke production facilities.

Keywords: bulk density, coal fines, flocculants, flocculation, settling velocity, pH

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Authors: O. Abramova, L. Abukova, A. Goreva, G. Isaeva

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The present work was made for the purpose of evaluating the interstitial water’s role in the mobilization of metal elements of clay deposits and occurrences in sedimentary formation in the hydro-geological basins. The experiments were performed by using a special facility, which allows adjusting the pressure, temperature, and the frequency of the acoustic vibrations. The dates for study were samples of the oil shales (Baltic career, O₂kk) and clay rocks, mainly montmorillonite composition (Borehole SG-12000, the depth of selection 1000–3600 m, the Azov-Kuban trough, N₁). After interstitial water squeezing from the rock samples, decrease in the original content of the rock forming components including trace metals V, Cr, Co, Ni, Cu, Zn, Zr, Mo, Pb, W, Ti, and others was recorded. The experiments made it possible to evaluate the ore elements output and organic matters with the interstitial waters. Calculations have shown that, in standard conditions, from each ton of the oil shales, 5-6 kg of ore elements and 9-10 kg of organic matter can be escaped. A quantity of matter, migrating from clays in the process of solidification, is changed depending on the lithogenesis stage: more recent unrealized deposits lose more ore and organic materials than the clay rocks, selected from depth over 3000 m. Each ton of clays in the depth interval 1000-1500 m is able to generate 3-5 kg of the ore elements and 6-8 kg of the organic matters. The interstitial waters are a freight forwarder over transferring these matters in the reservoir beds. It was concluded that the interstitial waters which escaped from the study samples are solutions with abnormal high concentrations of the metals and organic matters. In the discharge zones of the sediment basins, such fluids can create paragenetic associations of the sedimentary-catagenetic ore and hydrocarbon mineral resources accumulations.

Keywords: hydrocarbons, ore genesis, paragenesis, pore water

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Authors: Guo Rui, Cao Xinhu

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In recent decades, the world has endured severe challenges in light of climate change, epidemics, geopolitics, terrorism, economic uncertainties, as well as regional conflicts and rivalries. The appropriate use of critical infrastructures (Cis) is confronted. Ports, as typical Cis cover more than 80% of the global freight movement. Within this context, even the minimal disruption of port operations could cause malfunction of the holistic supply chain network and substantial economic losses. Hence, it is crucial to evaluate port performance from the perspective of resilience. Research on resilience and risk/safety management has been increasing, however, it needs more attention, as it could prevent potential socio-economic losses and inspire decision-makers to make resilience-based decisions to answer the challenges, such as COVID-19. To facilitate better moves from decision-makers, ports need to identify proper factors influencing port resilience. Inappropriately influenced factor selection could have a cascading effect on undesirable port performances. Thus, a systematic evaluation of factors is essential to stimulate the improvement process of port resilience investigation. This study zooms into container ports considering their critical role in international trade and global supply chains. 440 articles are selected after relevance ranking, and consequently, 62 articles are scrutinized after the title and abstract screening. Forty-one articles are included for bibliographic analysis in the end. It is found that there is no standardized index system to measure port resilience. And most studies evaluate port resilience merely in the recovery phase. Only two articles cover absorption, adaption and recovery state. However, no literature involves the prevention state. Hence, a uniform resilience index system is expected with a clear resilience definition. And port safety and security should also be considered while evaluating port resilience.

Keywords: port resilience, port safety and security, literature review, index system, port performance

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Authors: Eric Wilson Santos Cabral, Marta Monteiro Da Costa Cruz, Rodrigo Pirola Pestana, Vivian Andréa Parreira

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In the transportation sector in Brazil, there is a great challenge that is the maintenance of profit in the face of the great variation in the price of diesel. This directly affects the variable cost of transport companies. Within the railways, part of the great challenges is to overcome the annual budget, cargo and ore transported, thus reducing costs compared to previous years, becoming more efficient each year. Within this scenario, the railway companies are looking for effective measures, aiming at reducing the ratio of liter of diesel consumed by KTKB (Kilometer Gross Ton multiplied by thousand). This ratio represents the indicator of energy efficiency of some railroads in Brazil and in other countries. In this study, we sought to analyze the behavior of the energy efficiency indicator on two parts: The first, with the application of technologies used in locomotives, such as the start-stop system of the diesel engine and the system of tracking and monitoring of fuel. The second, evaluation of the behavior of the variation of the type of cargo transported (loading mix). The study focused on locomotive technology will be carried out using statistical analysis, behavioral evaluation in different operating conditions, such as maneuvers for trains, service trains and freight trains. The analysis will also cover the evaluation of the loading mix made using statistical analysis of the existing railroad database, comparing the energy efficiency per loading mine and type of product. With the completion of this study, the railway undertakings should be able to better target decision-making in order to achieve substantial reductions in transport costs.

Keywords: railway transport, energy efficiency, railway technology, fuel consumption

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Authors: Jonathan Rodriguez, Dominga Guerrero, Surupa Shaw

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Automobiles are modeled in various forms, and they interact with air when in motion. Aerodynamics is the study of such interactions where solid bodies affect the way air moves around them. The shape of solid bodies can impact the ease at which they move against the flow of air; due to which any additional freightage, or loads, impact its aerodynamics. It is important to transport people and cargo safely. Despite the various safety measures, there are a large number of vehicle-related accidents. This study precisely explores the effects an automobile experiences, with added cargo and covers. The addition of these items changes the original vehicle shape and the approved design for safe driving. This paper showcases the effects of the changed vehicle shape and design via experimental testing conducted on a physical 1:27 scale and CAD model of an F-150 pickup truck, the most common pickup truck in the United States, with differently shaped loads and weight traveling at a constant speed. The additional freightage produces unwanted drag or lift resulting in lower fuel efficiencies and unsafe driving conditions. This study employs an adjustable external shell on the F-150 pickup truck to create a controlled aerodynamic geometry to combat the detrimental effects of additional freightage. The results utilize colored powder [ which acts as a visual medium for the interaction of air with the vehicle], to highlight the impact of the additional freight on the automobile’s external shell. This will be done along with simulation models using Altair CFD software of twelve cases regarding the effects of an added load onto an F-150 pickup truck. This paper is an attempt toward standardizing the geometric design of the external shell, given the uniqueness of every load and its placement on the vehicle; while providing real-time data to be compared to simulation results from the existing literature.

Keywords: aerodynamics, CFD, freightage, pickup cover

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Authors: Jayanti De

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Users of any urban road infrastructure may be classified into various categories. The current paper intends to see whether the opinions on different environmental and transportation criteria vary significantly among different types of road users or not. The paper addresses this issue by using a unique survey data that has been collected from Kolkata, a highly populated city in India. Multiple criteria should be taken into account while planning on infrastructure development programs. Given limited resources, a welfare maximizing government typically resorts to public opinion by designing surveys for prioritization of one project over another. Designing such surveys can be challenging and costly. Deciding upon whom to include in a survey and how to represent each group of consumers/road-users depend crucially on how opinion for different criteria vary across consumer groups. A unique dataset has been collected from various parts of Kolkata to statistically test (using Kolmogorov-Smirnov test) whether assigning of weights to rank the transportation criteria like congestion, air pollution, noise pollution, and morning/evening delay vary significantly across the various groups of users of such infrastructure. The different consumer/user groups in the dataset include pedestrian, private car owner, para-transit (taxi /auto rickshaw) user, public transport (bus) user and freight transporter among others. Very little evidence has been found that ranking of different criteria among these groups vary significantly. This also supports the hypothesis that road- users/consumers form their opinion by using their long-run rather than immediate experience. As a policy prescription, this implies that under-representation or over-representation of a specific consumer group in a survey may not necessarily distort the overall opinion, since opinions across different consumer groups are highly correlated as evident from this particular case study.

Keywords: multi criteria analysis, project-prioritization, road- users, survey designing

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Authors: Farzaneh Tahmoorian, Bijan Samali, John Yeaman

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Road networks are expanding all over the world during the past few decades to meet the increasing freight volumes created by the population growth and industrial development. At the same time, the rate of generation of solid wastes in the society is increasing with the population growth, technological development, and changes in the lifestyle of people. Thus, the management of solid wastes has become an acute problem. Accordingly, there is a need for greater efficiency in the construction and maintenance of road networks, in reducing the overall cost, especially the utilization of natural materials such as aggregates. An efficient means to reduce construction and maintenance costs of road networks is to replace natural (virgin) materials by secondary, recycled materials. Recycling will also help to reduce pressure on landfills and demand for extraction of natural virgin materials thus ensuring sustainability. Application of solid wastes in asphalt layer reduces not only environmental issues associated with waste disposal but also the demand for virgin materials which will subsequently result in sustainability. Therefore, this research aims to investigate the feasibility of the application of some of the waste materials such as glass, construction and demolition wastes, etc. as alternative materials in pavement construction, particularly flexible pavements. To this end, various combination of different waste materials in certain percentages is considered in designing the asphalt mixture. One of the goals of this research is to determine the optimum percentage of all these materials in the mixture. This is done through a series of tests to evaluate the volumetric properties and resilient modulus of the mixture. The information and data collected from these tests are used to select the adequate samples for further assessment through advanced tests such as triaxial dynamic test and fatigue test, in order to investigate the asphalt mixture resistance to permanent deformation and also cracking. This paper presents the results of these investigations on the application of waste materials in asphalt mixture for production of a sustainable asphalt mix.

Keywords: asphalt, glass, pavement, recycled aggregate, sustainability

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Authors: Emilienne Lardy, Mariam Lafkihi, Eric Ballot

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Efficient city logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modeling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed to describe extensively the kinetic and dynamic aspects of driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore it investigates how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Generalized Linear Model has been established to link kinetic parameters with independent categorical contextual variables. The results include the analysis of the regression’s accuracy, as well as the utilization of the regression’s results in freight distribution scenario elaboration and analysis for Supply Chain Management purposes.

Keywords: driving context, generalized linear model, kinetic behaviour, real world driving data

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Authors: Laura Simmer, Maria Kalt, Oliver Schauer

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Freight transport is growing fast, but many vehicles are empty or just partially loaded. The vision and concepts of the Physical Internet (PI) proposes to eliminate these inefficiencies. Aiming for a radical sustainability improvement, the PI – inspired by the Digital Internet – is a hyperconnected global logistic system, enabling seamless asset sharing and flow consolidation. The implementation of a PI in its full expression will be a huge challenge: the industry needs innovation and implementation support including change management approaches, awareness creation and good practices diffusion, legislative actions to remove antitrust and international commerce barriers, standardization and public incentives policies. In order to take a step closer to this future the project ‘Atropine - Fast Track to the Physical Internet’ funded under the Strategic Economic and Research Program ‘Innovative Upper Austria 2020’ was set up. The two-year research project unites several research partners in this field, but also industrial partners and logistics service providers. With Atropine, the consortium wants to actively shape the mobility landscape in Upper Austria and make an innovative contribution to an energy-efficient, environmentally sound and sustainable development in the transport area. This paper should, on the one hand, clarify the questions what the project Atropine is about and, on the other hand, how a proof of concept will be reached. Awareness building plays an important role in the project as the PI requires a reorganization of the supply chain and the design of completely new forms of inter-company co-operation. New business models have to be developed and should be verified by simulation. After the simulation process one of these business models will be chosen and tested in real life with the partner companies. The developed results - simulation model and demonstrator - are used to determine how the concept of the PI can be applied in Upper Austria. Atropine shall pave the way for a full-scale development of the PI vision in the next few decades and provide the basis for pushing the industry toward a new level of co-operation with more shared resources and increased standardization.

Keywords: Atropine, inter-company co-operation, Physical Internet, shared resources, sustainable logistics

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Authors: Masilonyane Mokhele

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Across the world, different planning models of the so-called airport-led developments are becoming bandwagons hailed as key to the future of cities. However, in the existing knowledge, there is paucity of empirically informed description and explanation of the economic fundamentals driving the forces of attraction of airports. This void is arguably a result of the absence of an appropriate theoretical framework to guide the analyses. Given this paucity, the aim of the paper is to contribute towards a theoretical framework that could be used to describe and explain forces that drive the location and mix of airport-centric developments. Towards achieving this aim, the objectives of the paper are: one, to establish the type of economic activities that are located on and around O.R. Tambo International Airport (ORTIA), and analyse the reasons for locating there; two, to establish changes that have occurred over time in the form of the airport-centric development of ORTIA; three, to identify the propulsive economic qualities of ORTIA; four, to analyse the spatial, economic and structural linkages within the airport-centric development of ORTIA, between the airport-centric development and the airport, as well as the airport-centric development’s linkages with their metropolitan area and other regional, national and international airport-centric developments and locations. To address the objectives above, the study adopted a case study approach, centred on ORTIA in South Africa: Africa’s busiest airport in terms of passengers and airfreight handled. Using a lens of location theory, a survey was adopted as a main research method, wherein telephonic interviews were conducted with a representative number of firms on and around ORTIA. Other data collection methods encompassed in-depth qualitative interviews (to augment the information obtained through the survey) and analysis of secondary information, particularly as regards establishing changes that have occurred in the form of ORTIA and surrounds. From the empirical findings, ORTIA was discovered to have propulsive economic qualities that act as significant forces of attraction in the clustering of firms. Together with its airport-centric development, ORTIA was discovered to have growth pole properties because of the linkages that occur within the study area, and the linkages that exist between the airport-centric firms and the airport. It was noted that the transport-oriented firms (typified by couriers and freight carriers) act as anchors in some fellow airport-centric firms making use of elements of urbanisation economies, particularly as regards the use of the airport for airfreight services. The empirical findings presented in the paper (in conjunction with results from other airport-centric development case studies) could be used as contribution towards extending theory that describes and explains forces that drive the location and mix of airport-centric developments.

Keywords: airports, airport-centric development, O. R. Tambo international airport, South Africa

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Authors: Joana Almeida, Kendall Reid, Jonas Bengtsson

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Pallets are devices that are used for moving and storing freight and are nearly omnipresent in supply chains. The market is dominated by timber pallets, with plastic being a common alternative. Either option underpins the use of important resources (oil, land, timber), the emission of greenhouse gases and additional waste generation in most supply chains. This study uses a dynamic approach to the life cycle assessment (LCA) of pallets. It demonstrates that what ultimately defines the environmental burden of pallets in the supply chain is how often the length of its lifespan, which depends on the durability of the material and on how pallets are utilized. This study proposes a life cycle assessment (LCA) of pallets in supply chains supported by an algorithm that estimates pallet durability in function of material resilience and of logistics. The LCA runs from cradle-to-grave, including raw material provision, manufacture, transport and end of life. The scope is representative of timber and plastic pallets in the Australian and South-East Asia markets. The materials included in this analysis are: -tropical mixed hardwood, unsustainably harvested in SE Asia; -certified softwood, sustainably harvested; -conventional plastic, a mix of virgin and scrap plastic; -recycled plastic pallets, 100% mixed plastic scrap, which are being pioneered by Re > Pal. The logistical model purports that more complex supply chains and rougher handling subject pallets to higher stress loads. More stress shortens the lifespan of pallets in function of their composition. Timber pallets can be repaired, extending their lifespan, while plastic pallets cannot. At the factory gate, softwood pallets have the lowest carbon footprint. Re > pal follows closely due to its burden-free feedstock. Tropical mixed hardwood and plastic pallets have the highest footprints. Harvesting tropical mixed hardwood in SE Asia often leads to deforestation, leading to emissions from land use change. The higher footprint of plastic pallets is due to the production of virgin plastic. Our findings show that manufacture alone does not determine the sustainability of pallets. Even though certified softwood pallets have lower carbon footprint and their lifespan can be extended by repair, the need for re-supply of materials and disposal of waste timber offsets this advantage. It also leads to most waste being generated among all pallets. In a supply chain context, Re > Pal pallets have the lowest footprint due to lower replacement and disposal needs. In addition, Re > Pal are nearly ‘waste neutral’, because the waste that is generated throughout their life cycle is almost totally offset by the scrap uptake for production. The absolute results of this study can be confirmed by progressing the logistics model, improving data quality, expanding the range of materials and utilization practices. Still, this LCA demonstrates that considering logistics, raw materials and material durability is central for sustainable decision-making on pallet purchasing, management and disposal.

Keywords: carbon footprint, life cycle assessment, recycled plastic, waste

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Authors: Egemen Sert, Leila Hedayatifar, Rachel A. Rigg, Amir Akhavan, Olha Buchel, Dominic Elias Saadi, Aabir Abubaker Kar, Alfredo J. Morales, Yaneer Bar-Yam

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The complexity of providing timely and cost-effective distribution of finished goods from industrial facilities to customers makes effective operational coordination difficult, yet effectiveness is crucial for maintaining customer service levels and sustaining a business. Logistics planning becomes increasingly complex with growing numbers of customers, varied geographical locations, the uncertainty of future orders, and sometimes extreme competitive pressure to reduce inventory costs. Linear optimization methods become cumbersome or intractable due to a large number of variables and nonlinear dependencies involved. Here we develop a complex systems approach to optimizing logistics networks based upon dimensional reduction methods and apply our approach to a case study of a manufacturing company. In order to characterize the complexity in customer behavior, we define a “customer space” in which individual customer behavior is described by only the two most relevant dimensions: the distance to production facilities over current transportation routes and the customer's demand frequency. These dimensions provide essential insight into the domain of effective strategies for customers; direct and indirect strategies. In the direct strategy, goods are sent to the customer directly from a production facility using box or bulk trucks. In the indirect strategy, in advance of an order by the customer, goods are shipped to an external warehouse near a customer using trains and then "last-mile" shipped by trucks when orders are placed. Each strategy applies to an area of the customer space with an indeterminate boundary between them. Specific company policies determine the location of the boundary generally. We then identify the optimal delivery strategy for each customer by constructing a detailed model of costs of transportation and temporary storage in a set of specified external warehouses. Customer spaces help give an aggregate view of customer behaviors and characteristics. They allow policymakers to compare customers and develop strategies based on the aggregate behavior of the system as a whole. In addition to optimization over existing facilities, using customer logistics and the k-means algorithm, we propose additional warehouse locations. We apply these methods to a medium-sized American manufacturing company with a particular logistics network, consisting of multiple production facilities, external warehouses, and customers along with three types of shipment methods (box truck, bulk truck and train). For the case study, our method forecasts 10.5% savings on yearly transportation costs and an additional 4.6% savings with three new warehouses.

Keywords: logistics network optimization, direct and indirect strategies, K-means algorithm, dimensional reduction

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Authors: Asegid Belay Kebede, Getachew Biru Worku

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The Earth and its inhabitants have faced an existential threat as a result of severe manmade actions. Global warming and climate change have been the most apparent manifestations of this threat throughout the world, with increasingly intense heat waves, temperature rises, flooding, sea-level rise, ice sheet melting, and so on. One of the major contributors to this disaster is the ever-increasing production and consumption of energy, which is still primarily fossil-based and emits billions of tons of hazardous GHG. The transportation industry is recognized as the biggest actor in terms of emissions, accounting for 24% of direct CO2 emissions and being one of the few worldwide sectors where CO2 emissions are still growing. Rail transportation, which includes all from light rail transit to high-speed rail services, is regarded as one of the most efficient modes of transportation, accounting for 9% of total passenger travel and 7% of total freight transit. Nonetheless, there is still room for improvement in the transportation sector, which might be done by incorporating alternative and/or renewable energy sources. As a result of these rapidly changing global energy situations and rapidly dwindling fossil fuel supplies, we were driven to analyze the possibility of renewable energy sources for traction applications. Even a small achievement in energy conservation or harnessing might significantly influence the total railway system and have the potential to transform the railway sector like never before. As a result, the paper begins by assessing the potential for photovoltaic (PV) power generation on train rooftops and existing infrastructure such as railway depots, passenger stations, traction substation rooftops, and accessible land along rail lines. As a result, a method based on a Google Earth system (using Helioscopes software) is developed to assess the PV potential along rail lines and on train station roofs. As an example, the Addis Ababa light rail transit system (AA-LRTS) is utilized. The case study examines the electricity-generating potential and economic performance of photovoltaics installed on AALRTS. As a consequence, the overall capacity of solar systems on all stations, including train rooftops, reaches 72.6 MWh per day, with an annual power output of 10.6 GWh. Throughout a 25-year lifespan, the overall CO2 emission reduction and total profit from PV-AA-LRTS can reach 180,000 tons and 892 million Ethiopian birrs, respectively. The PV-AA-LRTS has a 200% return on investment. All PV stations have a payback time of less than 13 years, and the price of solar-generated power is less than $0.08/kWh, which can compete with the benchmark price of coal-fired electricity. Our findings indicate that PV-AA-LRTS has tremendous potential, with both energy and economic advantages.

Keywords: sustainable development, global warming, energy crisis, photovoltaic energy conversion, techno-economic analysis, transportation system, light rail transit

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Authors: Maximilian Engelhardt, Stephan Seeck

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The COVID-19 pandemic is accelerating the already growing field of e-commerce. The resulting urban freight transport volume leads to traffic and negative environmental impact. Furthermore, the service level of parcel logistics service provider is lacking far behind the expectations of consumer. These challenges can be solved by radically reorganize the urban last mile distribution structure: parcels could be consolidated in a micro hub within the inner city and delivered within time windows by cargo bike. This approach leads to a significant improvement of consumer satisfaction with their overall delivery experience. However, this approach also leads to significantly increased costs per parcel. While there is a relevant share of online shoppers that are willing to pay for such a delivery service there are no deeper insights about this target group available in the literature. Being aware of the importance of knowing target groups for businesses, the aim of this paper is to elaborate the most important factors that determine the willingness to pay for sustainable and service-oriented parcel delivery (factor analysis) and to derive customer segments (cluster analysis). In order to answer those questions, a data set is analyzed using quantitative methods of multivariate statistics. The data set was generated via an online survey in September and October 2020 within the five largest cities in Germany (n = 1.071). The data set contains socio-demographic, living-related and value-related variables, e.g. age, income, city, living situation and willingness to pay. In a prior work of the author, the data was analyzed applying descriptive and inference statistical methods that only provided limited insights regarding the above-mentioned research questions. The analysis in an exploratory way using factor and cluster analysis promise deeper insights of relevant influencing factors and segments for user behavior of the mentioned parcel delivery concept. The analysis model is built and implemented with help of the statistical software language R. The data analysis is currently performed and will be completed in December 2021. It is expected that the results will show the most relevant factors that are determining user behavior of sustainable and service-oriented parcel deliveries (e.g. age, current service experience, willingness to pay) and give deeper insights in characteristics that describe the segments that are more or less willing to pay for a better parcel delivery service. Based on the expected results, relevant implications and conclusions can be derived for startups that are about to change the way parcels are delivered: more customer-orientated by time window-delivery and parcel consolidation, more environmental-friendly by cargo bike. The results will give detailed insights regarding their target groups of parcel recipients. Further research can be conducted by exploring alternative revenue models (beyond the parcel recipient) that could compensate the additional costs, e.g. online-shops that increase their service-level or municipalities that reduce traffic on their streets.

Keywords: customer segmentation, e-commerce, last mile delivery, parcel service, urban logistics, willingness-to-pay

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Authors: Jonardan Koner, Avinash Purandare

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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.

Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders

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Authors: Sunil Arora, Anitya Kumar Jena, S. A. Ravi

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India is at the cusp of major reforms in the hydrocarbon sector. Oil and gas sector is highly liberalised to attract private investment and to increase domestic production. Major hydrocarbon Exploration & Production (E&P) activity here have been undertaken by Government owned companies but with easing up and reworking of hydro carbon exploration licensing policies private players have also joined the fray towards achieving energy security for India. Government of India has come up with policy and administrative reforms including Hydrocarbon Exploration and Licensing Policy (HELP), Sagarmala (port-led development with coastal connectivity), and Development of Small Discovered Fields, etc. with the intention to make industry friendly conditions for investment, ease of doing business and reduce gestation period. To harness the potential resources of Deep water and Ultra deep water, High Pressure – High Temperature (HP-HT) regions, Coal Bed Methane (CBM), Shale Hydrocarbons besides Gas Hydrates, participation shall be required from both domestic and international players. Companies engaged in E&P activities in India have traditionally been managing through their captive supply base, but with crude prices under hammer, the need is being felt to outsource non-core activities. This necessitates establishment of a robust support services to cater to E&P Industry, which is currently non-existent to meet the bourgeon challenges. This paper outlines an agenda for creating an Integrated Services Hub (ISH) under Special Economic Zone (SEZ) to facilitate complete gamut of non-core support activities of E&P industry. This responsive and proficient multi-usage facility becomes viable with better resource utilization, economies of scale to offer cost effective services. The concept envisages companies to bring-in their core technical expertise leaving complete hardware peripherals outsourced to this ISH. The Integrated Services Hub, complying with the best in class global standards, shall typically provide following Services under Single Window Solution, but not limited to: a) Logistics including supply base operations, transport of manpower and material, helicopters, offshore supply vessels, warehousing, inventory management, sourcing and procurement activities, international freight forwarding, domestic trucking, customs clearance service etc. b) Trained/Experienced pool of competent Manpower (Technical, Security etc.) will be available for engagement by companies on either short or long term basis depending upon the requirements with provisions of meeting any training requirements. c) Specialized Services through tie-up with global best companies for Crisis Management, Mud/Cement, Fishing, Floating Dry-dock besides provision of Workshop, Repair and Testing facilities, etc. d) Tools and Tackles including drill strings, etc. A pre-established Integrated Services Hub shall facilitate an early start-up of activities with substantial savings in time lines. This model can be replicated at other parts of the world to expedite E&P activities.

Keywords: integrated service hub, India, oil gas, offshore supply base

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: João Coutinho-Rodrigues, Nuno Sousa, Luís Alçada-Almeida

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Transportation infrastructure systems are fundamental in modern society and economy. However, they need modernizing, maintaining, and reinforcing interventions which require large investments. In many countries, accumulated intervention delays arise from aging and intense use, being magnified by financial constraints of the past. The decision problem of managing the renewal of large backlogs is common to several types of important transportation infrastructures (e.g., railways, roads). This problem requires considering financial aspects as well as operational constraints under a multidimensional framework. The present research introduces a linear programming multiobjective model for managing railway infrastructure asset renewal. The model aims at minimizing three objectives: (i) yearly investment peak, by evenly spreading investment throughout multiple years; (ii) total cost, which includes extra maintenance costs incurred from renewal backlogs; (iii) priority delays related to work start postponements on the higher priority railway sections. Operational constraints ensure that passenger and freight services are not excessively delayed from having railway line sections under intervention. Achieving a balanced annual investment plan, without compromising the total financial effort or excessively postponing the execution of the priority works, was the motivation for pursuing the research which is now presented. The methodology, inspired by a real case study and tested with real data, reflects aspects of the practice of an infrastructure management company and is generalizable to different types of infrastructure (e.g., railways, highways). It was conceived for treating renewal interventions in infrastructure assets, which is a railway network may be rails, ballasts, sleepers, etc.; while a section is under intervention, trains must run at reduced speed, causing delays in services. The model cannot, therefore, allow for an accumulation of works on the same line, which may cause excessively large delays. Similarly, the lines do not all have the same socio-economic importance or service intensity, making it is necessary to prioritize the sections to be renewed. The model takes these issues into account, and its output is an optimized works schedule for the renewal project translatable in Gantt charts The infrastructure management company provided all the data for the first test case study and validated the parameterization. This case consists of several sections to be renewed, over 5 years and belonging to 17 lines. A large instance was also generated, reflecting a problem of a size similar to the USA railway network (considered the largest one in the world), so it is not expected that considerably larger problems appear in real life; an average of 25 years backlog and ten years of project horizon was considered. Despite the very large increase in the number of decision variables (200 times as large), the computational time cost did not increase very significantly. It is thus expectable that just about any real-life problem can be treated in a modern computer, regardless of size. The trade-off analysis shows that if the decision maker allows some increase in max yearly investment (i.e., degradation of objective ii), solutions improve considerably in the remaining two objectives.

Keywords: transport infrastructure, asset renewal, railway maintenance, multiobjective modeling

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Authors: Marco F. Benaglia, Mei H. Chen, Kune M. Tsai, Chia H. Hung

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As societal and family structures, consumer dietary habits, and awareness about food safety and quality continue to evolve in most developed countries, the demand for refrigerated and frozen foods has been growing, and the issues related to their preservation have gained increasing attention. A well-established cold chain logistics system is essential to avoid any temperature abuse; therefore, assessing potential disruptions in the operational processes of cold chain logistics centers becomes pivotal. This study preliminarily employs HACCP to find disruption factors in cold chain logistics centers that may cause temperature abuse. Then, concept mapping is applied: selected experts engage in brainstorming sessions to identify any further factors. The panel consists of ten experts, including four from logistics and home delivery, two from retail distribution, one from the food industry, two from low-temperature logistics centers, and one from the freight industry. Disruptions include equipment-related aspects, human factors, management aspects, and process-related considerations. The areas of observation encompass freezer rooms, refrigerated storage areas, loading docks, sorting areas, and vehicle parking zones. The experts also categorize the disruption factors based on perceived similarities and build a similarity matrix. Each factor is evaluated for its impact, frequency, and investment importance. Next, multiple scale analysis, cluster analysis, and other methods are used to analyze these factors. Simultaneously, key disruption factors are identified based on their impact and frequency, and, subsequently, the factors that companies prioritize and are willing to invest in are determined by assessing investors’ risk aversion behavior. Finally, Cumulative Prospect Theory (CPT) is applied to verify the risk patterns. 66 disruption factors are found and categorized into six clusters: (1) "Inappropriate Use and Maintenance of Hardware and Software Facilities", (2) "Inadequate Management and Operational Negligence", (3) "Product Characteristics Affecting Quality and Inappropriate Packaging", (4) "Poor Control of Operation Timing and Missing Distribution Processing", (5) "Inadequate Planning for Peak Periods and Poor Process Planning", and (6) "Insufficient Cold Chain Awareness and Inadequate Training of Personnel". This study also identifies five critical factors in the operational processes of cold chain logistics centers: "Lack of Personnel’s Awareness Regarding Cold Chain Quality", "Personnel Not Following Standard Operating Procedures", "Personnel’s Operational Negligence", "Management’s Inadequacy", and "Lack of Personnel’s Knowledge About Cold Chain". The findings show that cold chain operators prioritize prevention and improvement efforts in the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster, particularly focusing on the factors of "Temperature Setting Errors" and "Management’s Inadequacy". However, through the application of CPT theory, this study reveals that companies are not usually willing to invest in the improvement of factors related to the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster due to its low occurrence likelihood, but they acknowledge the severity of the consequences if it does occur. Hence, the main implication is that the key disruption factors in cold chain logistics centers’ processes are associated with personnel issues; therefore, comprehensive training, periodic audits, and the establishment of reasonable incentives and penalties for both new employees and managers may significantly reduce disruption issues.

Keywords: concept mapping, cold chain, HACCP, cumulative prospect theory

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