Wind Energy Study and Energy Cost of Wind Electricity Generation in Nigeria: Past and Recent Results and a Case Study for South West Nigeria

The study assessed the wind energy potential of ten selected sites in the south western region of Nigeria and carried out a cost benefit analysis of wind power generation at those sites. Twenty four years’ (1987 to 2010) wind speed data at 10 m height obtained from the Nigerian meteorological agency were employed to classify the sites wind profiles for electricity generation. The energy cost analysis of generating wind electricity from the sites was also carried out. The outcome showed that sites in Lagos and Oyo States were adequately suited for large scale generation with average wind speeds ranged between 2.9 and 5.8 m/s. Those from other sites may be suitable for small scale generation or as wind farms, with several small turbines connected together, to generate large enough wind power. The turbine matching results shows that turbines cut-in and rated wind speeds of between 2.0 and 3.0 m/s, and between 10 and 12.0 m/s respectively will be very suited to all the sites, particularly those in locations outside Lagos and Oyo States. The energy cost analysis shows that generation cost can be as low as 0.02 €/kWh and as high as 5.03/kWh, depending on the turbine model employed

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

PS Poster Session - All

This document includes all poster sessions at the IBPC 2018

Electric Vehicles in China: Emissions, Health Impacts, and Equity

E-bikes in China are the single largest adoption of alternative fuel vehicles in history, with more than 100 million e-bikes purchased in the past decade and vehicle ownership about 2× [time] larger for e-bikes as for conventional cars; e-cars sales, too, are rapidly growing. Electric vehicles (EVs) in China are being considered as a strategy to improve air quality, energy efficiency, and reduce health impacts due to transport emissions. Because EVs have different pollution sources, namely electric generating units (EGUs), quantitative analysis for health impacts requires understanding the exposure efficiency of related pollution sources. In this dissertation, EVs will be analyzed in the context of the impacts on the environment, the differences in exposure efficiency of pollutants, the impacts on health, and the distribution of those impacts among different sectors of the population. This study compares emissions (CO2 [Carbon Dioxide], PM2.5 [Particulate Matter], NOX [Nitrogen Oxide], HC [Hydrocarbon]) and environmental health impacts (primary PM2.5) from the use of conventional vehicles (CVs) and EVs in 34 major cities in China. CO2 emissions (g km-1) vary and are an order of magnitude greater for e-cars (135–274) and CVs (150-180) than for e-bikes (14–27). PM2.5 emission factors generally are lower for CVs (gasoline or diesel) than comparable EVs. However, intake fraction is often greater for CVs than for EVs because combustion emissions are generally closer to population centers for CVs (tailpipe emissions) than for EVs (EGU emissions). For most cities, the net result is that primary PM2.5 environmental health impacts per passenger-km are greater for e-cars than for gasoline cars (3.6× on average), lower for e-cars than for diesel cars (2.5× on average) and equal between e-cars and diesel buses. In contrast, e-bikes yield lower environmental health impacts per passenger-km than the three CVs investigated: gasoline cars (2×), diesel cars (10×), and diesel buses (5×). In addition, adoption of EVs could cause environmental equity problems in China at this time, since a vast majority (\u3e83%) of pollutant emissions inhaled and subsequent health effects due to urban EV use could be distributed to communities whose incomes are lower than the cities where EVs are promoted. The findings highlight the importance of considering exposures, and especially the proximity of emissions to people, when evaluating environmental health impacts and equity concerns for EVs

State of the Art and Future Perspectives in Smart and Sustainable Urban Development

This book contributes to the conceptual and practical knowledge pools in order to improve the research and practice on smart and sustainable urban development by presenting an informed understanding of the subject to scholars, policymakers, and practitioners. This book presents contributions—in the form of research articles, literature reviews, case reports, and short communications—offering insights into the smart and sustainable urban development by conducting in-depth conceptual debates, detailed case study descriptions, thorough empirical investigations, systematic literature reviews, or forecasting analyses. This way, the book forms a repository of relevant information, material, and knowledge to support research, policymaking, practice, and the transferability of experiences to address urbanization and other planetary challenges

Proceedings of the 2021 DigitalFUTURES

This open access book is a compilation of selected papers from 2021 DigitalFUTURES—The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021). The work focuses on novel techniques for computational design and robotic fabrication. The contents make valuable contributions to academic researchers, designers, and engineers in the industry. As well, readers encounter new ideas about understanding material intelligence in architecture

Towards locust-inspired gliding wing prototypes for micro aerial vehicle applications

In aviation, gliding is the most economical mode of flight explicitly appreciated by natural fliers. They achieve it by high-performance wing structures evolved over millions of years in nature. Among other prehistoric beings, locust (Schistocerca gregaria) is a perfect example of such natural glider capable of endured transatlantic flights that could inspire a practical solution to achieve similar capabilities on micro aerial vehicles. This study investigates the effects of haemolymph on the flexibility of several flying insect wings further showcasing the superior structural performance of locusts. However, biomimicry of such aerodynamic and structural properties is hindered by the limitations of modern as well as conventional fabrication technologies in terms of availability and precision, respectively. Therefore, here we adopt finite element analysis (FEA) to investigate the manufacturing-worthiness of a 3D digitally reconstructed locust tandem wing, and propose novel combinations of economical and readily-available manufacturing methods to develop the model into prototypes that are structurally similar to their counterparts in nature while maintaining the optimum gliding ratio previously obtained in the aerodynamic simulations. Latter is evaluated in the future study and the former is assessed here via an experimental analysis of the flexural stiffness and maximum deformation rate. Ultimately, a comparative study of the mechanical properties reveals the feasibility of each prototype for gliding micro aerial vehicle applications

Achieving reliable and enhanced communication in vehicular ad hoc networks (VANETs)

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirement for the degree of Doctor of PhilosophyWith the envisioned age of Internet of Things (IoTs), different aspects of Intelligent Transportation System (ITS) will be linked so as to advance road transportation safety, ease congestion of road traffic, lessen air pollution, improve passenger transportation comfort and significantly reduce road accidents. In vehicular networks, regular exchange of current position, direction, speed, etc., enable mobile vehicle to foresee an imminent vehicle accident and notify the driver early enough in order to take appropriate action(s) or the vehicle on its own may take adequate preventive measures to avert the looming accident. Actualizing this concept requires use of shared media access protocol that is capable of guaranteeing reliable and timely broadcast of safety messages. This dissertation investigates the use of Network Coding (NC) techniques to enrich the content of each transmission and ensure improved high reliability of the broadcasted safety messages with less number of retransmissions. A Code Aided Retransmission-based Error Recovery (CARER) protocol is proposed. In order to avoid broadcast storm problem, a rebroadcasting vehicle selection metric η, is developed, which is used to select a vehicle that will rebroadcast the received encoded message. Although the proposed CARER protocol demonstrates an impressive performance, the level of incurred overhead is fairly high due to the use of complex rebroadcasting vehicle selection metric. To resolve this issue, a Random Network Coding (RNC) and vehicle clustering based vehicular communication scheme with low algorithmic complexity, named Reliable and Enhanced Cooperative Cross-layer MAC (RECMAC) scheme, is proposed. The use of this clustering technique enables RECMAC to subdivide the vehicular network into small manageable, coordinated clusters which further improve transmission reliability and minimise negative impact of network overhead. Similarly, a Cluster Head (CH) selection metric ℱ(\u1d457) is designed, which is used to determine and select the most suitably qualified candidate to become the CH of a particular cluster. Finally, in order to investigate the impact of available radio spectral resource, an in-depth study of the required amount of spectrum sufficient to support high transmission reliability and minimum latency requirements of critical road safety messages in vehicular networks was carried out. The performance of the proposed schemes was clearly shown with detailed theoretical analysis and was further validated with simulation experiments

Human experience in the natural and built environment : implications for research policy and practice

22nd IAPS conference. Edited book of abstracts. 427 pp. University of Strathclyde, Sheffield and West of Scotland Publication. ISBN: 978-0-94-764988-3

Full Proceedings, 2018

Full conference proceedings for the 2018 International Building Physics Association Conference hosted at Syracuse University