Manufacturing Process Analysis for Simultaneous Synthesis and Deposition of Turbostratic Graphene on Absorbers in Solar Thermal Collector Applications

The absorber section is a critical component in solar thermal collectors and is responsible for converting electromagnetic radiation into sensible thermal energy. The optical properties of the surface of the absorber dictates the effectiveness of this conversion. In this work, a manufacturing process is designed to provide bulk surface treatment for solar absorber plates in order to enhance their radiative properties. The process utilizes a novel approach of graphene synthesis and simultaneous deposition via high pressure blasting of graphite. The results show enhanced spectral, thermal and electrochemical performance of the absorber due to the turbostratic nature of graphene adhesion to its surface, especially when three blasting passes are used. The absorptivity of the absorber exhibited a 7% increase when three passes were applied on its surface. Using graphene has also enhanced the corrosion resistance of the absorber plate. This manufacturing system will provide a facile yet effective treatment of absorbers with various degrees of automation. Applied as a final layer, the process can be retrofitted to existing manufacturing facilities with minimum overhead costs

Manufacturing Process Analysis for Simultaneous Synthesis and Deposition of Turbostratic Graphene on Absorbers in Solar Thermal Collector Applications

The absorber section is a critical component in solar thermal collectors and is responsible for converting electromagnetic radiation into sensible thermal energy. The optical properties of the surface of the absorber dictates the effectiveness of this conversion. In this work, a manufacturing process is designed to provide bulk surface treatment for solar absorber plates in order to enhance their radiative properties. The process utilizes a novel approach of graphene synthesis and simultaneous deposition via high pressure blasting of graphite. The results show enhanced spectral, thermal and electrochemical performance of the absorber due to the turbostratic nature of graphene adhesion to its surface, especially when three blasting passes are used. The absorptivity of the absorber exhibited a 7% increase when three passes were applied on its surface. Using graphene has also enhanced the corrosion resistance of the absorber plate. This manufacturing system will provide a facile yet effective treatment of absorbers with various degrees of automation. Applied as a final layer, the process can be retrofitted to existing manufacturing facilities with minimum overhead costs

Datasets for supplier selection and order allocation with green criteria, all-unit quantity discounts and varying number of suppliers

This data article provides detailed optimization input and output datasets and optimization code for the published research work titled “Dynamic green supplier selection and order allocation with quantity discounts and varying supplier availability” (Hamdan and Cheaitou, 2017, In press) 1. Researchers may use these datasets as a baseline for future comparison and extensive analysis of the green supplier selection and order allocation problem with all-unit quantity discount and varying number of suppliers. More particularly, the datasets presented in this article allow researchers to generate the exact optimization outputs obtained by the authors of Hamdan and Cheaitou (2017, In press) 1 using the provided optimization code and then to use them for comparison with the outputs of other techniques or methodologies such as heuristic approaches. Moreover, this article includes the randomly generated optimization input data and the related outputs that are used as input data for the statistical analysis presented in Hamdan and Cheaitou (2017 In press) 1 in which two different approaches for ranking potential suppliers are compared. This article also provides the time analysis data used in (Hamdan and Cheaitou (2017, In press) 1 to study the effect of the problem size on the computation time as well as an additional time analysis dataset. The input data for the time study are generated randomly, in which the problem size is changed, and then are used by the optimization problem to obtain the corresponding optimal outputs as well as the corresponding computation time

Liner shipping network design with sensitive demand

Purpose: This paper aims to examine containership routing and speed optimization for maritime liner services. It focuses on a realistic case in which the transport demand, and consequently the collected revenue from the visited ports depend on the sailing speed. Design/methodology/approach: The authors present an integer non-linear programming model for the containership routing and fleet sizing problem, in which the sailing speed of every leg, the ports to be included in the service and their sequence are optimized based on the net line's profit. The authors present a heuristic approach that is based on speed discretization and a genetic algorithm to solve the problem for large size instances. They present an application on a line provided by COSCO in 2017 between Asia and Europe. Findings: The numerical results show that the proposed heuristic approach provides good quality solutions after a reasonable computation time. In addition, the demand sensitivity has a great impact on the selected route and therefore the profit function. Moreover, the more the demand is sensitive to the sailing speed, the higher the sailing speed value. Research limitations/implications: The vessel carrying capacity is not considered in an explicit way. Originality/value: This paper focuses on an important aspect in liner shipping, i.e. demand sensitivity to sailing speed. It brings a novel approach that is important in a context in which sailing speed strategies and market volatility are to be considered together in network design. This perspective has not been addressed previously. © 2020, Pacific Star Group Education Foundation

Comprehensive quantity discount model for dynamic green supplier selection and order allocation

We model and solve a deterministic multi-period single-product green supplier selection and order allocation problem in which the considered suppliers’ availability, cost, and green performance change from one period to another in the planning horizon. Moreover, the available suppliers may offer an all-unit or an incremental quantity discount (QD) scheme, resulting in three problem configurations. In one configuration, all suppliers offer all-unit QD. In the second, all suppliers offer incremental QD. In the third, some suppliers offer all-unit QD, and others offer incremental QD. The problem is modelled using a bi-objective integer linear programming formulation that maximizes the total green value of the purchased items from all the suppliers and minimizes their total corresponding cost, including the fixed cost, variable cost, inventory holding cost, and shortage cost. The proposed bi-objective model is scalarized and solved using the branch-and-cut algorithm and a population-based heuristic. A numerical analysis is conducted, which allows first to validate the heuristic approach using small-size instances by comparing its results with those of the exact approach. Moreover, an extensive comparison between the exact and heuristic solution approaches is carried out. The results reveal different findings. First, the economic and environmental solutions of an instance are different, and the environmental solution is independent of the suppliers’ pricing schemes. Second, the maximum difference between the heuristic approach and the exact approach in terms of the bi-objective function value is 4.72%, which makes the proposed heuristic recommended for large-size instances due to its short computation time and good accuracy. Third, there is no difference in terms of the heuristic performance between the combined model and the models with a single type of discount. Fourth, the all-unit discount scheme seems to be generally better in terms of the trade-off between the green value of purchasing and cost

Arctic Navigation: Stakes, Benefits and Limits of the Polaris System

Ensuring safe navigation is paramount for the economic development of the Arctic. Aware of this strategic issue, the International Maritime Organization (IMO), supported by the Arctic coastal states, adopted the International Code for Ships Operating in Polar Waters (Polar Code) with a set of navigation tools including the well-known Polar Operational Limit Assessment Risk Indexing System (POLARIS). Designed for assessing operational capabilities for ships operating in ice, POLARIS is useful for various stakeholders such as the International Association of Classification Society (IACS) organizations and underwriters. Other important beneficiaries are shipowners and their crew. Even though POLARIS deals with topical issues, so far, this system has not been subjected to extensive studies of its capabilities and limitations. The aim of this analysis in hand is to assess the stakes, benefits and limits of POLARIS for Arctic navigation with a managerial approach and through the lens of risk assessment. Results show that POLARIS integrates various parameters to assess risk of navigation in ice, and that POLARIS can provide relevant managerial solutions to shipowners. Nevertheless, certain limitations remain; in particular, human factors such as the lack of crew experience or the issue of non-compliance are not taken into consideration. Finally, it is important to highlight the fact that POLARIS is not a mandatory requiremen

Special Issue: Design, management, sustainability and evaluation of transportation systems in the Arctic

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Air Traffic Flow Management Under Emission Policies: Analyzing the Impact of Sustainable Aviation Fuel and Different Carbon Prices

As part of the global efforts to make aviation activities more environmentally friendly, the worldwide goal is to achieve a 50% reduction in the 2005 emissions by 2050. In this context, aviation emissions represent a critical challenge to aviation activities, especially with the increasing travel demand up to the beginning of the COVID-19 crisis, starting in 2020. One of the potential drivers that would help the aviation industry reduce its emissions is the use of sustainable aviation fuel (SAF). In this study, we analyzed the impact of SAF from an air traffic flow management (ATFM) perspective, considering delay and re-routing costs. We developed an optimization model that considers, in addition to the traditional ATFM costs, fuel costs and carbon dioxide emissions. We investigated the impact of accounting for these two new aspects, that is, fuel costs and emissions, on ATFM performance, and we compared SAF with conventional fuel. The analysis of a real case study revealed that, in addition to delay and re-routing costs, fuel cost should be included in the ATFM model so that the resulting solution becomes economically and environmentally realistic for airlines. The increase in the fuel cost and network delays when using SAF requires setting an appropriate carbon price under an emission policy, such as the carbon offsetting and reduction scheme for international flights policy, to make SAF more attractive. Furthermore, flexible re-routing programs for flights operated using SAF make it advantageous from an ATFM perspective

Central authority controlled air traffic flow management: An optimization approach.

Despite various planning efforts, airspace capacity can sometimes be exceeded, typically due to disruptive events. Air traffic flow management (ATFM) is the process of managing flights in this situation. In this paper, we present an ATFM model that accounts for different rerouting options (path rerouting and diversion) and pre-existing en-route flights. The model proposes having a central authority to control all decisions, which is then compared with current practice. We also consider inter-flight and inter-airline fairness measures in the network. We use an exact approach to solve small-to-medium-sized instances, and we propose a modified fix-and-relax heuristic to solve large-sized instances. Allowing a central authority to control all decisions increases network efficiency compared to the case where the ATFM authority and airlines control decisions independently. Our experiments show that including different rerouting options in ATFM can help reduce delays by up to 8% and cancellations by up to 23%. Moreover, ground delay cost has much more impact on network decisions than air delay cost, and network decisions are insensitive to changes in diversion cost. Furthermore, the analysis of the trade-off between total network cost and overtaking cost shows that adding costs for overtaking can significantly improve fairness at only a small increase in total system cost. A balanced total cost per flight among airlines can be achieved at a small increase in the network cost (0.2 to 3.0%) when imposing airline fairness. In conclusion, the comprehensiveness of the model makes it useful for analyzing a wide range of alternatives for efficient ATF