The Potential Of Fuel Cells To Reduce Energy Demands And Pollution From The UK Transport Sector

Atmospheric carbon dioxide and pollution due to the burning of fossil fuels is increasing. Many scientists attribute global warming to the rising levels of carbon dioxide and other pollutants, some of which also pose risks to health. These can be reduced by the more efficient use of conventional fuels and the development of non-polluting energy resources. Fuel cells offer a highly efficient and low polluting method of generating electricity, and are under development for both the power generation and transport sectors. There is a need to assess (a) emissions from fuel cells using various fuels and (b) ways of introducing such technology to transportation in the near future. Fuel consumption, energy and emissions from the production and use of fuels (hydrogen, methane, propane, petrol, diesel, alcohols and rape methyl ester) are calculated per kilowatt hour of fuel cell output over a range of efficiency. These are compared with those for internal combustion engines with advanced exhaust control and for the recharging of battery driven vehicles. The results, which are applicable to both transport and power generation, enable the best low pollution fuels to be selected and are used to calculate through life emissions for public transport buses. Fuel cells are an ideal solution to reduce pollution from transport, but their commercial development in this field is further away than that for stationary applications. Thus, a transition stage is recommended where fuel cell electrical power stations, based on existing demonstrators, are used to recharge fleets of battery driven vehicles during the development of mobile fuel cell systems. These fleets include public transport and commercial vehicles. Also, fuel cell power stations could provide energy for electric trains. A combined system is proposed where electric trains recharge battery driven commercial vehicles during long journeys. The above proposals would enhance fuel cell development, introducing them alongside current transport systems, possibly using the same fuel

Proceedings of the ECCOMAS Thematic Conference on Multibody Dynamics 2015

This volume contains the full papers accepted for presentation at the ECCOMAS Thematic Conference on Multibody Dynamics 2015 held in the Barcelona School of Industrial Engineering, Universitat Politècnica de Catalunya, on June 29 - July 2, 2015. The ECCOMAS Thematic Conference on Multibody Dynamics is an international meeting held once every two years in a European country. Continuing the very successful series of past conferences that have been organized in Lisbon (2003), Madrid (2005), Milan (2007), Warsaw (2009), Brussels (2011) and Zagreb (2013); this edition will once again serve as a meeting point for the international researchers, scientists and experts from academia, research laboratories and industry working in the area of multibody dynamics. Applications are related to many fields of contemporary engineering, such as vehicle and railway systems, aeronautical and space vehicles, robotic manipulators, mechatronic and autonomous systems, smart structures, biomechanical systems and nanotechnologies. The topics of the conference include, but are not restricted to: ● Formulations and Numerical Methods ● Efficient Methods and Real-Time Applications ● Flexible Multibody Dynamics ● Contact Dynamics and Constraints ● Multiphysics and Coupled Problems ● Control and Optimization ● Software Development and Computer Technology ● Aerospace and Maritime Applications ● Biomechanics ● Railroad Vehicle Dynamics ● Road Vehicle Dynamics ● Robotics ● Benchmark ProblemsPostprint (published version

The analysis of isotope clearance data in biological systems

Clearance curves resulting from biological studies using radioactive isotopes are frequently described mathematically in terms of the summation of a number of exponential terms. This allows the curves to be interpreted by reference to the physical characteristics of a model of the biological system. Numerous exponential curve fitting methods are now available which make use of digital computers. Despite the very widespread application of exponential curve analysis, a systematic study of the relative importance of the factors which affect the parameter errors has not yet been described. A quantitative statistical study of the problem is described in this thesis with particular reference to the special limitations encountered in biological investigations. These limitations are firstly, the limited number of samples and, secondly, the relatively poor accuracy normally associated with such studies. The accuracy would not normally be better than +/- 2% nor would the number of samples exceed 60. Of the ten principal factors which affect the errors in the estimated parameters, two of these, the exponent and amplitude ratios, are intrinsic factors dependent on the system under study. The principal factors under the control of the investigator are the number of samples, the data accuracy, the sampling frequency, and the duration of sampling, which determines the extent to which the data define the function under study. Other factors of lesser importance were not investigated in the same detail as those mentioned above. Artificial data, on which a controlled random error was superimposed, were generated by a computer programme and recorded on magnetic tape in a format suitable for exponential analysis by the Berman SAAM-22 computer programme. The parameter errors were estimated by a statistical analysis of twenty curve fitting operations carried out on twenty different sets of data with a constant controlled random error. Twice the coefficient of variation, expressed as a percentage, was taken to be the parameter error. A range of exponential and amplitude ratios was investigated for two exponential and three exponential functions with data errors from 2 - 10%. The study has indicated, in quantitative terms, the effects of the various factors on the errors associated with the estimated parameters, and also the relative importance of these factors. The results indicate the conditions which must be fulfilled if sellable results are to be obtained by exponential analysis. The information is also of value in designing investigations which will subsequently involve exponential analysis of the data. In view of the parameter errors encountered in the study of two and three exponential functions, it appears unlikely that analysis of biological data in terms of a greater number of exponentials will be helpful unless further independent information is available concerning the biological system under study. Two clinical applications of exponential curve fitting procedures are described. In a study of uric acid metabolism, two different computer programmes were used to examine the same data. A mathematical significance test was used to indicate which sets of data were better fitted by a double rather than a single exponential function. It was found that with one of these programmes only, when using a particular weighting factor on the data, a strong correlation exists between the indication of a double exponential function in the data and the clinical diagnosis of gout. This is interpreted as evidence of the existence of uric acid in two different physiological forms in gouty patients. In the second study, the detailed investigation of a depth focusing radioisotope collimator, and its use in the measurement of local cortical blood flow in the brain, is described. By using this collimator, clearance curves of radioactivity from a very small volume of M-in tissue in the cortex were obtained. The curves were analysed empirically by means of a double exponential curve fitting procedure, in order to determine the initial slope. No biological significance is assigned to the individual exponential terms. Since the collimator is designed to accept radiation originating specifically in the cortex, the detector is particularly sensitive to changes of flow in this tissue. The results obtained for cortical tissue in normals agree with the values of grey matter flow determined by other workers on much larger regions of the brain containing both grey and white tissues

Modeling and Control for a Class of Tendon-Driven Continuum Mechanisms

This thesis contributes to the emerging field of soft material robots and treats modeling, state estimation and control for a special class of continuum mechanisms. The overall outcome of is a novel treatment of a continuum in robotics research. At first a description of the overall system as a tendon-driven multi-body system modeled by a nonlinear rigid-body dynamics is proposed. In combination with the introduced real-time pose and velocity estimation, nonlinear model-based control in real-time is possible. Furthermore, the structural properties of the model allow employing modern control methods for underactuated mechanical systems which are adapted to provide set point control for the upper platform. The developed methods in modeling, state estimation and control presented in this work are experimentally validated on a humanoid robot. Due to their promising results, this thesis lays the foundation for the use of tendon-driven continuum mechanisms as generic joint modules for modular robotic systems which may mark the beginning of a new generation of light-weight robots