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Auflistung nach Autor:in "Benetto, Enrico"

1 - 5 von 5
  • Konferenzbeitrag
    A scalable implementation of the track summing algorithm for Emergy calculation with Life Cycle Inventory databases
    (Innovations in Sharing Environmental Observations and Information, 2011) Marvuglia, Antonino; Benetto, Enrico; Rugani, Benedetto; Rios, Gordon
    Emergy analysis is an environmental accounting approach that links thermodynamics and systems ecology to evaluate the work made by both natural processes and human activities to make a product or service available. Emergy is a measure of the energy used in the past and thus “memorized“ in the product, including also the energy spent by natural processes up to the main source (the sun). In order to compute thisamount of solar energy (called solar energy equivalent) Emergy Evaluation (EME)uses conversion factors called transformities or Unit Emergy Values (UEVs), which express the amount of Emergy required per unit ofa given product or service. This work aims to develop an operational tool for allowing the calculation of the Emergy associated to each of the commodities involved in a given product’s life cycle along with its related inventoried resources. More specifically, the Emergy was calculated starting from a Life Cycle Inventory (LCI), which represents a list of environmental inputs and outputs (resource extractions and pollutant emissions) related to the production of a specific product. The motivation for our work is linked first of all to the consideration that, while Life Cycle Assessment (LCA) can nowadays avail itself of large LCI databases (such as Ecoinvent) which are constantly updated and extended, consistent libraries of UEVs for Emergy calculations do not exist. As a consequence, a methodology able to link LCI databases and emergy calculations and formalize the latter ones in a matrix form would represent an important step forward for Emergy-based environmental accounting. The case study tackled here deals with a simplified version of the production system of flat glass. We formalized the problem in a matrix-based structure which comes directly from the LCA framework and developed a variant of the track summing algorithm originally due to Tennenbaum (Tennenbaum1988). Two versions of the algorithm were implemented: one in Scala (a general purpose programming language that smoothly integrates features of object-oriented and functional languages) and one in C++. The former is a multi-threaded breadth first search (BFS), the latter follows a depth first search (DFS) and is more efficient in terms of memory usage.The algorithm consisted in calculating Emergy flows separately per Emergy independent sources, then summing the results. Solving the problem at stake took an operation time of 1.37 seconds on a 2.4 GHz Intel Core 2 Duo laptop running Mac OS X. The results were validated using the software Emsim, a free-share Emergy simulatorthat can workwith lifecycle systems using a graph instead of a matrix. However, Emsimdoes not allow a direct link to automatic calculation routines, since it requires the system’s diagram to be drawn by the operator. The promisingresult obtained will enable us to scale-up the method, possibly using the whole Ecoinvent database. This would allow the achievement of a reproducible, consistent, and transparent calculation of Emergy values for thousands of products of a LCI database. Furthermore, the algorithm could be applied case by case to specific product’s life cycles modelled using conventional LCA software tools like Simapro, allowing an exact calculation of the Emergy associated to the studied products and therefore a complete combination of LCA and Emergy perspectivesinenvironmental assessment.
  • Konferenzbeitrag
    Assessing the Uses of NLP-based Surrogate Models for Solving Expensive Multi-Objective Optimization Problems: Application to Potable Water Chains
    (EnviroInfo & ICT4S, Conference Proceedings, 2015) Capitanescu, Florin; Marvuglia, Antonino; Benetto, Enrico; Ahmadi, Aras; Tiruta-Barna, Ligia
    In practice many multi-objective optimization problems relying on computationally expensive black-box model simulators of industrial processes have to be solved with limited computing time budget. In this context, this paper proposes and explores the uses of an iterative heuristic approach aiming at quickly providing a satisfactory accurate approximation of the Pareto front. The approach builds, in each iteration, a multi-objective nonlinear programming (MO-NLP) surrogate problem model using curve fitting of objectives and constraints. The approximated solutions of the Pareto front are generated by applying the "-constraint method to the multi-objective surrogate problem, converting it into a desired number of single objective (SO) NLP problems, for which mature and computationally efficient solvers exist. The proposed approach is applied to the cost versus life cycle assessment (LCA)-based environmental optimization of drinking water treatment chains. The paper thoroughly investigates various settings choices of the approach such as: the type of the polynomial function to be fit, the input points, choice of weights in curve fitting, and analytical fit. The numerical simulations results with the approach show that a good quality approximation of Pareto front can be obtained with a significantly smaller computational time than with the popular SPEA2 state-of-the-art metaheuristic algorithm.
  • Konferenzbeitrag
    GIS-based Life Cycle Assessment of urban building stocks retrofitting. A bottom-up framework applied to Luxembourg
    (EnviroInfo & ICT4S, Conference Proceedings, 2015) Mastrucci, Alessio; Popovici, Emil; Marvuglia, Antonino; de Sousa, Luís; Benetto, Enrico; Leopold, Ulrich
    The building sector represents one of the major sources of environmental impact due especially to space and domestic hot water heating and construction works. A number of studies focused so far on estimating the energy savings and carbon emissions reduction potential achievable by retrofitting urban building stocks, nevertheless a shift to life cycle assessment is needed to properly assess the environmental impacts in a more holistic way. The aim of this study is to develop a geospatial data model for the life cycle assessment of environmental impacts of building stocks at the urban scale. The methodology includes: geospatial processing of building-related data to characterize urban building stocks; a spatio-temporal database to store and manage data; life cycle assessment to estimate potential environmental impacts. The methodology was tested for a case study in Luxembourg and preliminary results regarding the retrofitting stage of residential buildings were provided for one entire city. The data model is part of a wider bottom-up framework being developed to support decision about building stock retrofitting for sustainable urban planning.
  • Konferenzbeitrag
    Influence of international trade on regional human development and relationship with environmental and health impacts
    (Environmental Infomatics - Stability, Continuity, Innovation: Current trends and future perspectives based on 30 years of history, 2016) Gibon, Thomas; Marvuglia, Antonino; Benetto, Enrico
  • Konferenzbeitrag
    Midpoint vs Single Score in Multi-Criteria Optimization under Life Cycle Assessment Constraints: the Case of Potable Water Treatment Chains
    (EnviroInfo & ICT4S, Conference Proceedings, 2015) Capitanescu, Florin; Igos, Elorri; Marvuglia, Antonino; Benetto, Enrico
    This paper addresses the multi-objective constrained optimization of a drinking water production plant. It reports the successful coupling between the Strength Pareto Evolutionary Algorithm (SPEA2), which is a well-established multi-goal elitist metaheuristic global optimizer, and EVALEAU, which is a state-of-the-art process modelling life cycle assessment (LCA) tool for simulation of potable water treatment chains. The paper assesses as well the pros and cons of using midpoint versus single score as environmental goal metrics in a decision making process based on very challenging multi-goal optimization of potable water treatment chains. The proposed approach is illustrated using the model of a real-world drinking water production plant.