The objective of this study is to evaluate the energetic, exergetic, sustainability, economic and environmental performances of a 4-cylinder turbodiesel aviation engine (TdAE) used on unmanned aerial vehicles for the take-off operation mode to assess the system with large aspects. Energy efficiency of the system is found as 43.158%, while exergy efficiency 40.655%. Thermoeconomic analysis gives information about the costs of the inlet and outlet energy and exergy flows of the engine. Hourly levelized total cost flow of the TdAE is found as 21.036 $/h, when the hourly fuel cost flow of the engine is found as 30.328 $/h. The waste exergy cost parameter is determined as 0.0144 MJ/h/$ from exergy cost-energy-mass (EXCEM) analysis, while it is estimated as 14.043 MJ/$ from modified-EXCEM analysis. Environmental damage cost analysis evaluates the cost formation of the exhaust emissions. The total environmental damage cost of the TdAE is computed as 12.895 $/h whilst specific environmental damage cost is determined as 0.054 $/MJ for 494.145 MJ/h TdAE power production. It is assessed that the main contributors to the environmental impact rate of the TdAE are the fuel consumption and the formation pollutants of combustion reaction.
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Theoretical trends and schools of thought in the field of anthropology evolve rapidly. Anthropological literature must keep abreast, not only of these intellectual shifts, but also of pressing global, political, and social issues. Thus, this volume, like others before it, seeks to provide updates on the state of the science and the theoretical and methodological trends of the day. Yet, there is another, more important reason why such a volume is necessary now, ‘today’, of all days, and another reason why this will serve as more than just another update on the discipline. Today, we face some of the greatest environmental challenges in global history. Understanding the damage being done by communities, large and small, and the varied ethics and efforts contributing to its repair is of vital importance. For these reasons, environmental anthropology today is different and arguably more critical than ever before. This volume thus poses the question and raises the challenge: What can increasing the emphasis on the environment in environmental anthropology, along with the science of its problems and the theoretical and methodological tools of anthropological practice do to aid conservation efforts, policy initiatives, and our overall understanding of how to survive, culturally and physically, as citizens of the planet? This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in "Environmental Anthropology Today" on 8/5/11 available online: https://doi.org/10.4324/9780203806906 LinkedIn: https://www.linkedin.com/in/helenkopnina/
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In this study, aviation, energy, exergy, environmental, exergoeconomic, and exergoenvironmental analyses are performed on a CFM56-3 series high by-pass turbofan engine fueled with Jet-A1 fuel. Specific fuel consumption and specific thrust of the engine are found to be 0.01098 kg/kN.s and 0.3178 kN/kg/s, respectively. Engine's energy efficiency is calculated as 35.37%, while waste energy ratio is obtained as 64.63%. Exergy efficiency, waste exergy rate, and fuel exergy waste ratio are forecasted as 33.32%, 33175.03 kW, and 66.68%, respectively. Environmental effect factor and ecological effect factor are computed as 2.001 and 3.001, while ecological objective function and its index are taken into account of −16597.22 kW and −1.001, respectively. Exergetic sustainability index and sustainable efficiency factor are determined as 0.5 and 1.5 for the CFM56-3 engine, respectively. Environmental damage cost rate is determined as 519.753 $/h, while the environmental damage cost index is accounted as 0.0314 $/kWh. Specific exergy cost of the engine production is found as 40.898 $/GJ from exergoeconomic analysis, while specific product exergy cost is expressed as 49.607 $/GJ from exergoenvironmental analysis. From exergoenvironmental economic analysis, specific exergy cost of fuel is computed as 10.103 $/GJ when specific exergy cost of production is determined as 40.898 $/GJ.
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Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low. As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers. To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is: How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems? HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases: I. Highway: non-professional drivers; II. Distribution Centre: professional drivers.
Traffic accidents are a severe public health problem worldwide, accounting for approximately 1.35 million deaths annually. Besides the loss of life, the social costs (accidents, congestion, and environmental damage) are significant. In the Netherlands, in 2018, these social costs were approximately € 28 billion, in which traffic accidents alone accounted for € 17 billion. Experts believe that Automated Driving Systems (ADS) can significantly reduce these traffic fatalities and injuries. For this reason, the European Union mandates several ADS in new vehicles from 2022 onwards. However, the utility of ADS still proves to present difficulties, and their acceptance among drivers is generally low.As of now, ADS only supports drivers within their pre-defined safety and comfort margins without considering individual drivers’ preferences, limiting ADS in behaving and interacting naturally with drivers and other road users. Thereby, drivers are susceptible to distraction (when out-of-the-loop), cannot monitor the traffic environment nor supervise the ADS adequately. These aspects induce the gap between drivers and ADS, raising doubts about ADS’ usefulness among drivers and, subsequently, affecting ADS acceptance and usage by drivers.To resolve this issue, the HUBRIS Phase-2 consortium of expert academic and industry partners aims at developing a self-learning high-level control system, namely, Human Counterpart, to bridge the gap between drivers and ADS. The central research question of this research is:How to develop and demonstrate a human counterpart system that can enable socially responsible human-like behaviour for automated driving systems?HUBRIS Phase-2 will result in the development of the human counterpart system to improve the trust and acceptance of drivers regarding ADS. In this RAAK-PRO project, the development of this system is validated in two use-cases:I. Highway: non-professional drivers;II. Distribution Centre: professional drivers.Collaborative partners:Bielefeld University of Applied Sciences, Bricklog B.V., Goudappel B.V., HaskoningDHV Nederland B.V., Rhine-Waal University of Applied Sciences, Rijkswaterstaat, Saxion, Sencure B.V., Siemens Industry Software Netherlands B.V., Smits Opleidingen B.V., Stichting Innovatiecentrum Verkeer en Logistiek, TNO Den Haag, TU Delft, University of Twente, V-Tron B.V., XL Businesspark Twente.
Even though considerable amounts of valuable wood are collected at waste collection sites, most of it remains unused and is burned: it is too labor-intensive to sort, process and upcycle useable parts. Valuable wood thus becomes worthless waste, against circular economy principles. In MoBot-Wood, waste collection organizations HVC and the municipality of Amsterdam, together with Rolan Robotics, Metabolic and AUAS investigate how waste wood can be sorted and processed at waste collection sites, using an easy-to-deploy robotic solution. In various preceding and on-going projects, AUAS and partners are exploring circular wood intake, sorting and processing using industrial robots, including processes like machine vision, 3D scanning, sawing, and milling. These projects show that harvesting waste wood is a challenging matter. Generally, the wood is only partially useable due to the presence of metal, excessive paint, deterioration by fungi and water, or other contamination and damages. To harvest useable wood thus requires intensive sorting and processing. The solution of transporting all the waste wood from collection sites to a central processing station might be too expensive and have a negative environmental impact. Considering that much of collected wood will need to be discarded, often no wood is harvested at all, due to the costs for collection and shipping. Speaking with several partners in related projects, the idea emerged to develop a mobile robotic station, which can be (temporarily) deployed at waste collection sites, to intake, sort and process wood for upcycling. In MoBot-Wood, research entails the design of such station, its deployment conditions, and a general assessment of its potential impact. The project investigates robotic sorting and processing on location as a new approach to increase the amount of valuable, useable wood harvested at waste collection sites, by avoiding material transport and reducing the volume of remaining waste.
