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X-WR-CALNAME:PHD in Industrial Engineering
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X-WR-CALDESC:Events for PHD in Industrial Engineering
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DTSTART:20250101T000000
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260416T080000
DTEND;TZID=UTC:20260417T170000
DTSTAMP:20260404T235018
CREATED:20210915T052505Z
LAST-MODIFIED:20260302T163749Z
UID:2269-1776326400-1776445200@academics.dii.unipd.it
SUMMARY:Advanced Modeling and Optimization of Multi-Energy Systems for a Decarbonized Future
DESCRIPTION:Course unit contentsThe course addresses the critical challenge of optimally integrating new renewable energy units into existing energy systems and networks to drive the transition toward a decarbonized future. It focuses on the concept of “Multi-Energy Systems” (MES)\, where different energy carriers interact to increase system flexibility and accommodate higher shares of renewable energy. These interactions occur through various energy conversion\, storage\, and consumption units. Shifting the approach from optimizing individual units as separate entities to optimizing the design and operation of an MES as a whole is pivotal to achieving greener energy systems in a more cost-effective\, efficient\, and environmentally friendly manner. \nThe course is organized into three 5-hour modules and combines classroom lectures with practical\, computer-based sessions. \n\nModule 1: Introduction to the concept of Multi-Energy Systems. Modeling of MES components\, including energy conversion units\, storage systems\, and energy demands. Derivation of linear models for MES components. Fundamentals of variable and equation structures in Python\, followed by the practical implementation of these models in a Python environment.\nModule 2: Introduction to engineering optimization and optimization algorithms. Formulation of the Synthesis\, Design\, and Operation (SDO) optimization problem for an MES\, including deterministic optimization approaches and the coupling between energy demand and availability curves. Definition of objective functions to maximize energy savings\, cost-effectiveness\, and environmental benefits\, concluding with a discussion of real-world applications.\nModule 3: Integration of individual MES component models into a comprehensive optimization model for the entire system. Fundamentals of structuring decision variables\, constraints\, objective functions\, and optimization algorithms using the Gurobi solver. Practical examples of design and operation optimization for an MES within a Python-Gurobi environment.\n\nLearning goalsUpon successful completion of this course\, students will be able to understand the general modeling features of energy systems of varying complexity\, grasp the fundamental principles of energy system optimization\, implement these optimization models within a Python-Gurobi environment\, and critically analyze the results obtained from practical implementations. \nSuggested readings\nBejan A.\, Tsatsaronis G. & Moran M.J. (1995). Thermal design and optimization. New York: John Wiley & SonsLibro \n\nRao S.S.\, Engineering optimization: theory and practice. New York: John Wiley & Sons\, 2019 \n\nRavindran A.\, Reklaitis G.V. & Ragsdell K.M. (2006). Engineering optimization: methods and applications. John Wiley & Sons \n\nRech S.\, & Lazzaretto A. (2018). Smart rules and thermal\, electric and hydro storages for the optimum operation of a renewable energy system. Energy\, 147\, 742-756 \n\nRech S. (2019). Smart energy systems: Guidelines for modelling and optimizing a fleet of units of different configurations. Energies\, 12(7)\, 1320 \n\nDal Cin E.\, Carraro G.\, Volpato G.\, Lazzaretto A.\, & Tsatsaronis G. (2025). DOMES: A general optimization method for the integrated design of energy conversion\, storage and networks in multi-energy systems. Applied Energy\, 377\, 124702
URL:https://academics.dii.unipd.it/phd/event/english-seminar-2/
LOCATION:Sede-V\, via Venezia 1\, Padova\, Padova\, 35131\, Italy
CATEGORIES:Event
ATTACH;FMTTYPE=image/png:https://academics.dii.unipd.it/phd/wp-content/uploads/sites/58/2026/03/CDII-energy-1-scaled.png
ORGANIZER;CN="PhD Course in Industrial Engineering":MAILTO:dottorato.dii@unipd.it
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260331T080000
DTEND;TZID=UTC:20260331T170000
DTSTAMP:20260404T235018
CREATED:20160316T114710Z
LAST-MODIFIED:20260302T163833Z
UID:610-1774944000-1774976400@academics.dii.unipd.it
SUMMARY:Advanced methods for fatigue design
DESCRIPTION:Course contentsThis course provides an introduction to the fatigue assessment of mechanical components in the presence of cracks or notches. It covers the derivation of stress fields ahead of cracks and notches using the Airy stress function and the complex potential function method (Kolosov and Muskhelishvili). Students will explore a case study on sharp V-notches under in-plane loading\, focusing on the Lazzarin-Tovo analytical derivation of local stress fields based on complex potential functions and a comparison with Williams’ solution. Furthermore\, the course includes the definition of Notch Stress Intensity Factors (NSIFs) and an introduction to local approaches based on the NSIF concept\, specifically the averaged strain energy density (SED) and the peak stress method (PSM). Finally\, these concepts culminate in the practical application of local approaches to the fatigue strength assessment of mechanical components by means of Finite Element (FE) analyses using the Ansys FE code. \nLearning goalsIn this course\, students will learn the analytical basis of notch stress analysis. They will explore how to apply both standard methods (e.g.\, nominal stress) and local approaches (NSIF\, SED\, PSM) for the fatigue strength assessment of welded joints. Finally\, students will gain practical experience in performing linear elastic structural FE analyses using Ansys. \nSuggested readings\nSadd M. H. Elasticity. Theory\, Applications and Numerics. Elsevier; 2004.\nLazzarin P.\, Tovo R. A unified approach to the evaluation of linear elastic stress fields in the neighborhood of cracks and notches\, Int. J. Fract. 78 (1996) 3–19.\nAnderson T. L. Fracture Mechanics. Fundamentals and Applications. CRC Press; 1995.\nLazzarin P.\, Zambardi R. A finite-volume-energy based approach to predict the static and fatigue behavior of components with sharp V-shaped notches\, Int. J. Fract. 112 (2001) 275–298.\nMeneghetti G.\, Lazzarin P. Significance of the elastic peak stress evaluated by FE analyses at the point of singularity of sharp V-notched components\, Fatigue Fract. Eng. Mater. Struct. 30 (2007) 95–106.\nRadaj D\, Vormwald M. Advanced methods of fatigue assessment. Springer; 2012.
URL:https://academics.dii.unipd.it/phd/event/politics-seminar/
LOCATION:Sede-V\, via Venezia 1\, Padova\, Padova\, 35131\, Italy
CATEGORIES:Event
ATTACH;FMTTYPE=image/png:https://academics.dii.unipd.it/phd/wp-content/uploads/sites/58/2026/03/CDII-fatigue-1-scaled.png
ORGANIZER;CN="PhD Course in Industrial Engineering":MAILTO:dottorato.dii@unipd.it
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