Alessandro Di Pretoro

Prof. Dr. Alessandro Di Pretoro

Process Systems Engineering, National Polytechnic Institute of Toulouse, Toulouse, Occitanie, France
orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 2019 in Computers & Chemical Engineering
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Journal Article
Closed access
Alessandro Di PretoroAlessandro Di Pretoro
Alessandro Di Pretoro
LMLudovic Montastruc
Ludovic Montastruc
FMFlavio Manenti
Flavio Manenti
XJXavier Joulia
Xavier Joulia

1 July 2020 in Computers & Chemical Engineering
Verified
Journal Article
Closed access
Alessandro Di PretoroAlessandro Di Pretoro
Alessandro Di Pretoro
LMLudovic Montastruc
Ludovic Montastruc
FMFlavio Manenti
Flavio Manenti
XJXavier Joulia
Xavier Joulia

4 January 2021 in Processes
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Journal Article
Open access
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Alessandro Di PretoroAlessandro Di Pretoro
Alessandro Di Pretoro
FDFrancesco D’iglio
Francesco D’iglio
FMFlavio Manenti
Flavio Manenti
Fouling is a substantial economic, energy, and safety issue for all the process industry applications, heat transfer units in particular. Although this phenomenon can be mitigated, it cannot be avoided and proper cleaning cycle scheduling is the best way to deal with it. After thorough literature research about the most reliable fouling model description, cleaning procedures have been optimized by minimizing the Time Average Losses (TAL) under nominal operating conditions according to the well-established procedure. For this purpose, different cleaning actions, namely chemical and mechanical, have been accounted for. However, this procedure is strictly related to nominal operating conditions therefore perturbations, when present, could considerably compromise the process profitability due to unexpected shutdown or extraordinary maintenance operations. After a preliminary sensitivity analysis, the uncertain variables and the corresponding disturbance likelihood were estimated. Hence, cleaning cycles were rescheduled on the basis of a stochastic flexibility index for different probability distributions to show how the uncertainty characterization affects the optimal time and economic losses. A decisional algorithm was finally conceived in order to assess the best number of chemical cleaning cycles included in a cleaning supercycle. In conclusion, this study highlights how optimal scheduling is affected by external perturbations and provides an important tool to the decision-maker in order to make a more conscious design choice based on a robust multi-criteria optimization.

7 February 2022 in Computers & Chemical Engineering
Verified
Journal Article
Closed access
Alessandro Di PretoroAlessandro Di Pretoro
Alessandro Di Pretoro
BBBastian Bruns
Bastian Bruns
SNStéphane Negny
Stéphane Negny
MGMarcus Grünewald
Marcus Grünewald
JRJulia Riese
Julia Riese

20 June 2020 in Chemical Engineering Science
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Journal Article
Closed access
FMF. Manenti
F. Manenti
AGA. Galeazzi
A. Galeazzi
FBF. Bisotti
F. Bisotti
KPK. Prifti
K. Prifti
ADA. Dell'Angelo
A. Dell'Angelo
CAC. Ariatti
C. Ariatti

27 May 2024 in Entropy
Verified
Journal Article
Open access
PDF file
SSShumet Sendek Sharew
Shumet Sendek Sharew
Alessandro Di PretoroAlessandro Di Pretoro
Alessandro Di Pretoro
AYAbubeker Yimam
Abubeker Yimam
SNStéphane Negny
Stéphane Negny
LMLudovic Montastruc
Ludovic Montastruc
In this research, the simulation of an existing 31.5 MW steam power plant, providing both electricity for the national grid and hot utility for the related sugar factory, was performed by means of ProSimPlus® v. 3.7.6. The purpose of this study is to analyze the steam turbine operating parameters by means of the exergy concept with a pinch-based technique in order to assess the overall energy performance and losses that occur in the power plant. The combined pinch and exergy analysis (CPEA) initially focuses on the depiction of the hot and cold composite curves (HCCCs) of the steam cycle to evaluate the energy and exergy requirements. Based on the minimal approach temperature difference (∆Tlm) required for effective heat transfer, the exergy loss that raises the heat demand (heat duty) for power generation can be quantitatively assessed. The exergy composite curves focus on the potential for fuel saving throughout the cycle with respect to three possible operating modes and evaluates opportunities for heat pumping in the process. Well-established tools, such as balanced exergy composite curves, are used to visualize exergy losses in each process unit and utility heat exchangers. The outcome of the combined exergy–pinch analysis reveals that energy savings of up to 83.44 MW may be realized by lowering exergy destruction in the cogeneration plant according to the operating scenario.