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Marco Pierini

Bio: Marco Pierini is an academic researcher from University of Florence. The author has contributed to research in topics: Poison control & Electric vehicle. The author has an hindex of 22, co-authored 160 publications receiving 1694 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, an innovative aluminum sandwich panel with sinusoidal corrugated core is investigated and the properties of the equivalent material are determined both analytically and numerically for the chosen Reissner-Mindlin orthotropic representation.

93 citations

Journal ArticleDOI
TL;DR: In this paper, a comparative Life Cycle Assessment of Internal Combustion Engine (ICE) and electric vehicles is presented, which follows a "from cradle-to-grave" approach and it captures the whole Life Cycle (LC) of the car subdivided into production, use and end-of-life stages.
Abstract: Transportation represents one of the major contributors to several environmental burdens such as Green-House-Gas (GHG) emissions and resource depletion. Considering the European Union, light duty vehicles are responsible for roughly 10% of total energy use and air emissions. As a consequence, the need for higher fuel/energy efficiency in both conventional and electric cars has become urgent and the efforts across industrial and research players have proposed a range of innovative solutions with great potential. This study presents a comparative Life Cycle Assessment of Internal Combustion Engine (ICE) and electric vehicles. The analysis follows a “from cradle-to-grave” approach and it captures the whole Life-Cycle (LC) of the car subdivided into production, use and End-of-Life stages. The inventory is mainly based on primary data and the assessment takes into account a wide range of impact categories to both human and eco-system health. The eco-profile of the different vehicle configurations is assessed and the main environmental hotspots affecting conventional and electric cars are identified and critically discussed. The dependence of impacts on LC mileage is investigated for both propulsion technologies and the break-even point for the effective environmental convenience of electric car is determined considering several use phase electricity sources. The analysis is completed with a comparison of GHG emissions with the results of previous LCA studies.

89 citations

Journal ArticleDOI
TL;DR: In this paper, a proposal for driving data analysis and synthesis has been developed through the review and the selection of known literature experiences, having as a goal the application on a EVs focused case study.
Abstract: Strong efforts are spent in automotive engineering for the creation of so called Driving Cycles (DCs). Vehicle DC development has been a topic under research over the last thirty years, since it is a key activity both from an authority and from an industrial research point of view. Considering the innovative characteristics of Electric Vehicles (EVs) and their diffusion on certain contexts (e.g. city centers), the demand for tailored cycles arises. A proposal for driving data analysis and synthesis has been developed through the review and the selection of known literature experiences, having as a goal the application on a EVs focused case study. The measurement campaign has been conducted in the city of Florence, which includes limited traffic areas accessible to EVs. A fleet of EVs has been monitored through a non-invasive data logging system. After data acquisition, time-speed data series have been processed for filtering and grouping. The main product of the activity is a set of DCs obtained by pseudo-randomized selection of original data. The similarity of synthetic DCs to acquired data has been verified through the validation of cycle parameters. Finally, the new DCs and a selection of existing ones are compared on the basis of relevant kinematic parameters and expected energy consumption. The method followed for the creation of DCs has been implemented in a software package. It can be used to generate cycles and, under certain boundary conditions, to get a filtered access to the measured data and provide integration within simulation environment.

84 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a method aimed to support Life Cycle Assessment (LCA) in the evaluation of environmental benefits achievable by lightweight design solutions in the automotive field, based on an in-depth calculation of car weight-induced Fuel Consumption (FC) resulting in the Fuel Reduction Value (FRV) coefficient; this is functional in modelling the use stage in a LCA perspective.

75 citations

Journal ArticleDOI
TL;DR: Investigation of the influence of vehicle front height and shape in pedestrian accidents on the mechanism of impact with the ground and on head ground impact speed using multibody modelling found impact mechanisms for adults resulting in a head-first contact with theGround were more severe with high fronted vehicles compared to low fronted Vehicles, though there is a speed dependency to these findings.

70 citations


Cited by
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Journal Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 citations

Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

Journal ArticleDOI
TL;DR: The goal of this paper is to review both the understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.
Abstract: Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.

583 citations