Airports and surrounding airspaces are limited in terms of capacity and represent the major bottlenecks of the air traffic management system. This paper addresses the problems of terminal airspace management and airport congestion management at the macroscopic level through the integrated control of arrivals and departures. Conflict detection and resolution methods are applied to a predefined terminal route structure. Different airside components are modeled using network abstraction. Speed, arrival and departure times, and runway assignment are managed by using an optimization method. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on case studies of Paris Charles De-Gaulle airport show some potential improvements: First, when the airport capacity is decreased, until a certain threshold, the overload can be mitigated properly by adjusting the aircraft entry time in the Terminal Maneuvering Area and the pushback time. Second, landing and take-off runway assignments in peak hours with imbalanced runway throughputs can significantly reduce flight delays. A decrease of 37% arrival delays and 36% departure delays was reached compared to baseline case.
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Airports and surrounding airspaces are limited in terms of capacity and represent the major bottleneck in the air traffic management system. This paper proposes a two level model to tackle the integrated optimization problem of arrival, departure, and surface operations. The macroscopic level considers the terminal airspace management for arrivals and departures and airport capacity management, while the microscopic level optimizes surface operations and departure runway scheduling. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on real-world case studies of Paris Charles De-Gaulle airport, show the benefits of this integrated approach.
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For long flights, the cruise is the longest phase and where the largest amount of fuel is consumed. An in-cruise optimization method has been implemented to calculate the optimal trajectory that reduces the flight cost. A three-dimensional grid has been created, coupling lateral navigation and vertical navigation profiles. With a dynamic analysis of the wind, the aircraft can perform a horizontal deviation or change altitudes via step climbs to reduce fuel consumption. As the number of waypoints and possible step climbs is increased, the number of flight trajectories increases exponentially; thus, a genetic algorithm has been implemented to reduce the total number of calculated trajectories compared to an exhaustive search. The aircraft’s model has been obtained from a performance database, which is currently used in the commercial flight management system studied in this paper. A 5% average flight cost reduction has been obtained.
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Introduction The Integrated Recovery Scales (IRS) was developed by the Dutch National Expertise board for routine outcome monitoring with severe mental illnesses. This board aimed to develop a multidimensional recovery measure directed at 1. clinical recovery, 2. physical health, 3. social recovery (work, social contacts, independent living) and 4. existential, personal recovery. The measure had to be short, suited for routine outcome monitoring and present the perspective of both mental health professionals and service users with severe mental illnesses. All aspects are assessed over a period of the pas 6 months. Objectives The objective of this research is validation of the Integral Recovery Scales and to test the revelance for clinical practice and police evaluation. Methods The instrument was tested with 500 individuals with severe mental illnesses (80% individuals with a psychotic disorder), of whom 200 were followed up for 1 year. For the questions concerning clinical recovery, physical health and social recovery mental health care workers conducted semi structured interviews with people living with serious illnesses. The questions concerning personal health were self-rated. We analyzed interrater reliability, convergent and divergent validity and sensitivity to change. Results The instrument has a good validity and is easy to complete for service users and mental health care workers and appropriate for clinical and policy evaluation goals. Conclusions The Integrated Recovery Scales can be a useful instrument for a simple and meaningful routine outcome monitoring. Page: 121
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An important contribution to the environmental impact of agro-food supply chains is related to the agricultural technology and practices used in the fields during raw material production. This problem can be framed from the point of view of the Focal Company (FC) as a raw material Green Supplier Selection Problem (GSSP). This paper describes an extension of the GSSP methodology that integrates life cycle assessment, environmental collaborations, and contract farming in order to gain social and environmental benefits. In this approach, risk and gains are shared by both parties, as well as information related to agricultural practices through which the FC can optimize global performance by deciding which suppliers to contract, capacity and which practices to use at each supplying field in order to optimize economic performance and environmental impact. The FC provides the knowledge and technology needed by the supplier to reach these objectives via a contract farming scheme. A case study is developed in order to illustrate and a step-by-step methodology is described. A multi-objective optimization strategy based on Genetic Algorithms linked to a MCDM approach to the solution selection step is proposed. Scenarios of optimization of the selection process are studied to demonstrate the potential improvement gains in performance.
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Background: Adverse outcome pathway (AOP) networks are versatile tools in toxicology and risk assessment that capture and visualize mechanisms driving toxicity originating from various data sources. They share a common structure consisting of a set of molecular initiating events and key events, connected by key event relationships, leading to the actual adverse outcome. AOP networks are to be considered living documents that should be frequently updated by feeding in new data. Such iterative optimization exercises are typically done manually, which not only is a time-consuming effort, but also bears the risk of overlooking critical data. The present study introduces a novel approach for AOP network optimization of a previously published AOP network on chemical-induced cholestasis using artificial intelligence to facilitate automated data collection followed by subsequent quantitative confidence assessment of molecular initiating events, key events, and key event relationships. Methods: Artificial intelligence-assisted data collection was performed by means of the free web platform Sysrev. Confidence levels of the tailored Bradford-Hill criteria were quantified for the purpose of weight-of-evidence assessment of the optimized AOP network. Scores were calculated for biological plausibility, empirical evidence, and essentiality, and were integrated into a total key event relationship confidence value. The optimized AOP network was visualized using Cytoscape with the node size representing the incidence of the key event and the edge size indicating the total confidence in the key event relationship. Results: This resulted in the identification of 38 and 135 unique key events and key event relationships, respectively. Transporter changes was the key event with the highest incidence, and formed the most confident key event relationship with the adverse outcome, cholestasis. Other important key events present in the AOP network include: nuclear receptor changes, intracellular bile acid accumulation, bile acid synthesis changes, oxidative stress, inflammation and apoptosis. Conclusions: This process led to the creation of an extensively informative AOP network focused on chemical-induced cholestasis. This optimized AOP network may serve as a mechanistic compass for the development of a battery of in vitro assays to reliably predict chemical-induced cholestatic injury.
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The constant growth of air traffic, especially in Europe, is putting pressure on airports, which, in turn, are suffering congestion problems. The airspace surrounding airport, terminal manoeuvring area (TMA), is particularly congested, since it accommodates all the converging traffic to and from airports. Besides airspace, airport ground capacity is also facing congestion problems, as the inefficiencies coming from airspace operations are transferred to airport ground and vice versa. The main consequences of congestion at airport airspace and ground, is given by the amount of delay generated, which is, in turn, transferred to other airports within the network. Congestion problems affect also the workload of air traffic controllers that need to handle this big amount of traffic.This thesis deals with the optimization of the integrated airport operations, considering the airport from a holistic point of view, by including operations such as airspace and ground together. Unlike other studies in this field of research, this thesis contributes by supporting the decisions of air traffic controllers regarding aircraft sequencing and by mitigating congestion on the airport ground area. The airport ground operations and airspace operations can be tackled with two different levels of abstractions, macroscopic or microscopic, based on the time-frame for decision-making purposes. In this thesis, the airport operations are modeled at a macroscopic level.The problem is formulated as an optimization model by identifying an objective function that considers the amount of conflicts in the airspace and capacity overload on the airport ground; constraints given by regulations on separation minima between consecutive aircraft in the airspace and on the runway; decision variables related to aircraft entry time and entry speed in the airspace, landing runway and departing runway choice and pushback time. The optimization model is solved by implementing a sliding window approach and an adapted version of the metaheuristic simulated annealing. Uncertainty is included in the operations by developing a simulation model and by including stochastic variables that represent the most significant sources of uncertainty when considering operations at a macroscopic level, such as deviation from the entry time in the airspace, deviation in the average taxi time and deviation in the pushback time. In this thesis, optimization and simulation techniques are combined together by developing two methods that aim at improving the solution robustness and feasibility. The first method acts as a validation tool for the optimized solution, and it improves the robustness of solution by iteratively fine-tuning some of the optimization model input parameters. The second method embeds the optimization in a simulation environment by taking full advantage of the sliding window approach and creating a loop for a continuous improvement of the optimized solution at each window of the sliding window approach. Both methods prove to be effective by improving the performance, lowering the total amount of conflicts up to 23.33% for the first method and up to 11.2% for the second method, however, in contrast to the deterministic method, the two methods they are not able to achieve a conflict-free scenario due to the effect of uncertainty.In general, the research conducted in this thesis highlights that uncertainty is a factor that affects to a large extent the feasibility of optimized solution when applied to real-world instances, and it, moreover, confirms that using simulation together with optimization has the potentiality toivdeal with uncertainty. The framework developed can be potentially applied to similar problems and different optimization solving methods can be adapted to it.Keywords: Optimization, Simulation, Integrated airport operations, Uncertainty
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tract Micro wind turbines can be structurally integrated on top of the solid base of noise barriers near highways. A number of performance factors were assessed with holistic experiments in wind tunnel and in the field. The wind turbines underperformed when exposed in yawed flow conditions. The theoretical cosθ theories for yaw misalignment did not always predict power correctly. Inverter losses turned out to be crucial especially in standby mode. Combination of standby losses with yawed flow losses and low wind speed regime may even result in a net power consuming turbine. The micro wind turbine control system for maintaining optimal power production underperformed in the field when comparing tip speed ratios and performance coefficients with the values recorded in the wind tunnel. The turbine was idling between 20%–30% of time as it was assessed for sites with annual average wind speeds of three to five meters per second without any power production. Finally, the field test analysis showed that inadequate yaw response could potentially lead to 18% of the losses, the inverter related losses to 8%, and control related losses to 33%. The totalized loss led to a 48% efficiency drop when compared with the ideal power production measured before the inverter. Micro wind turbine’s performance has room for optimization for application in turbulent wind conditions on top of noise barriers. https://doi.org/10.3390/en14051288
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The Integrated Recovery Scale IRS was developed by Dutch National Expertise board for Routine Outcome Monitoring. Recovery is multi dimensional: 1. Symptomatic recovery 2. Physical health, 3. Societal recovery 4. Existential: personal recovery. The validation process and first outcomes of the instrument are described.
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The Netherlands is aiming for the roll-out of more solar PV. However like many densely populated countries, the country is running into issues of lack of space. Opportunities around infrastructural works like highways provide space without compromising the landscape. Examples of this double use are already developed and demonstrated, like for instance sound barriers and solar roads. New is the combination of solar PV with traffic barriers. This has a big potential since the Dutch main road network had 7.500 km of guiderail and the construction to put PV on is already there. In the MESH (Modular E cover for Solar Highways) project a consortium of knowledge institutes, a province and companies developed a prototype and tested it in a pilot. The consortium consists of TNO, Solliance (in which TNO is a partner, a high-end research institute for flexible thin film solar cells such as CIGS and Perovskite), Heijmans Infra (focusing mainly on the construction, improvement and maintenance of road infrastructure, including guiderails), DC Current (applying innovations with regard to power optimizers for the linear PV application), the Province of Noord-Holland (which acts as a leading customer) and the Amsterdam University of Applied Sciences (AUAS) as a knowledge institution that links education and research. In this project the theme Sustainable Energy Systems of AUAS is involved with both lecturers and student groups. In the project, Solliance investigated and developed the flexible thin film PV technology to be applied with a focus on shape and reliability. TNO and Heijmans developed a modular casing concept and a fastening system that allows quick installation on site. DC Current worked on the DC management with regard to voltage, electrical safety and minimizing failure in case of collision. At the end of the project, the partners in the consortium have validated knowledge about how to integrate PV into the guiderail and can start with the scaling up of the technology for commercial applications. In order to meet the various requirements for traffic safety on the one hand and generating electricity on the other hand, the Systems Engineering methodology was leading during the project. In the project we first built a small, but full scale prototype and invited safety experts to evaluate the design. With this feedback we made a redesign for the pilot. This pilot is placed on the highway as safety barrier and tested for a year. In a presentation at EU PVSEC18 [1] K.Sewalt reported on the design phase. This time we want to present the results of our test phase and give answers on our research questions.
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