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Giuseppe Leonardo Cascella: - 50+ international papers - 30+ R&D projects - R&D interests: industry4.0, artificial intelligence, electrical machines and drives, optimization algorithms - currently researcher @DEI, Politecnico di Bari, Italy - EU Marie Curie Fellow @Nottingham University (UK), 2003 - PhD and MSc degrees in electrical eng. with honors @Politecnico di Bari, Italy, 2005/1
Parameter identification of permanent magnet synchronous machines (PMSMs) represents a well-established research area. However, parameter estimation of multiple running machines in large-scale applications has not yet been investigated. In this context, a flexible and automated approach is required to minimize complexity, costs, and human interventions without requiring machine information. This paper proposes a novel identification strategy for surface PMSMs (SPMSMs), highly suitable for large-scale systems. A novel multistep approach using measurement data at different operating conditions of the SPMSM is proposed to perform the parameter identification without requiring signal injection, extra sensors, machine information, and human interventions. Thus, the proposed method overcomes numerous issues of the existing parameter identification schemes. An IoT/cloud architecture is designed to implement the proposed multistep procedure and massively perform SPMSM parameter identifications. Finally, hardware-in-the-loop results show the effectiveness of the proposed approach.
Elia Brescia; Donatello Costantino; Federico Marzo; Paolo Massenio; Giuseppe Cascella; David Naso. Automated Multistep Parameter Identification of SPMSMs in Large-Scale Applications Using Cloud Computing Resources. Sensors 2021, 21, 4699 .
AMA StyleElia Brescia, Donatello Costantino, Federico Marzo, Paolo Massenio, Giuseppe Cascella, David Naso. Automated Multistep Parameter Identification of SPMSMs in Large-Scale Applications Using Cloud Computing Resources. Sensors. 2021; 21 (14):4699.
Chicago/Turabian StyleElia Brescia; Donatello Costantino; Federico Marzo; Paolo Massenio; Giuseppe Cascella; David Naso. 2021. "Automated Multistep Parameter Identification of SPMSMs in Large-Scale Applications Using Cloud Computing Resources." Sensors 21, no. 14: 4699.
Permanent magnet machines with segmented stator cores are affected by additional harmonic components of the cogging torque which cannot be minimized by conventional methods adopted for one-piece stator machines. In this study, a novel approach is proposed to minimize the cogging torque of such machines. This approach is based on the design of multiple independent shapes of the tooth tips through a topological optimization. Theoretical studies define a design formula that allows to choose the number of independent shapes to be designed, based on the number of stator core segments. Moreover, a computationally-efficient heuristic approach based on genetic algorithms and artificial neural network-based surrogate models solves the topological optimization and finds the optimal tooth tips shapes. Simulation studies with the finite element method validates the design formula and the effectiveness of the proposed method in suppressing the additional harmonic components. Moreover, a comparison with a conventional heuristic approach based on a genetic algorithm directly coupled to finite element analysis assesses the superiority of the proposed approach. Finally, a sensitivity analysis on assembling and manufacturing tolerances proves the robustness of the proposed design method.
Elia Brescia; Donatello Costantino; Paolo Massenio; Vito Monopoli; Francesco Cupertino; Giuseppe Cascella. A Design Method for the Cogging Torque Minimization of Permanent Magnet Machines with a Segmented Stator Core Based on ANN Surrogate Models. Energies 2021, 14, 1880 .
AMA StyleElia Brescia, Donatello Costantino, Paolo Massenio, Vito Monopoli, Francesco Cupertino, Giuseppe Cascella. A Design Method for the Cogging Torque Minimization of Permanent Magnet Machines with a Segmented Stator Core Based on ANN Surrogate Models. Energies. 2021; 14 (7):1880.
Chicago/Turabian StyleElia Brescia; Donatello Costantino; Paolo Massenio; Vito Monopoli; Francesco Cupertino; Giuseppe Cascella. 2021. "A Design Method for the Cogging Torque Minimization of Permanent Magnet Machines with a Segmented Stator Core Based on ANN Surrogate Models." Energies 14, no. 7: 1880.
Since its beginning at the end of 2019, the pandemic spread of the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2) caused more than one million deaths in only nine months. The threat of emerging and re-emerging infectious diseases exists as an imminent threat to human health. It is essential to implement adequate hygiene best practices to break the contagion chain and enhance society preparedness for such critical scenarios and understand the relevance of each disease transmission route. As the unconscious hand–face contact gesture constitutes a potential pathway of contagion, in this paper, the authors present a prototype system based on low-cost depth sensors able to monitor in real-time the attitude towards such a habit. The system records people’s behavior to enhance their awareness by providing real-time warnings, providing for statistical reports for designing proper hygiene solutions, and better understanding the role of such route of contagion. A preliminary validation study measured an overall accuracy of 91%. A Cohen’s Kappa equal to 0.876 supports rejecting the hypothesis that such accuracy is accidental. Low-cost body tracking technologies can effectively support monitoring compliance with hygiene best practices and training people in real-time. By collecting data and analyzing them with respect to people categories and contagion statistics, it could be possible to understand the importance of this contagion pathway and identify for which people category such a behavioral attitude constitutes a significant risk.
Vito Manghisi; Michele Fiorentino; Antonio Boccaccio; Michele Gattullo; Giuseppe Cascella; Nicola Toschi; Antonio Pietroiusti; Antonio Uva. A Body Tracking-Based Low-Cost Solution for Monitoring Workers’ Hygiene Best Practices during Pandemics. Sensors 2020, 20, 6149 .
AMA StyleVito Manghisi, Michele Fiorentino, Antonio Boccaccio, Michele Gattullo, Giuseppe Cascella, Nicola Toschi, Antonio Pietroiusti, Antonio Uva. A Body Tracking-Based Low-Cost Solution for Monitoring Workers’ Hygiene Best Practices during Pandemics. Sensors. 2020; 20 (21):6149.
Chicago/Turabian StyleVito Manghisi; Michele Fiorentino; Antonio Boccaccio; Michele Gattullo; Giuseppe Cascella; Nicola Toschi; Antonio Pietroiusti; Antonio Uva. 2020. "A Body Tracking-Based Low-Cost Solution for Monitoring Workers’ Hygiene Best Practices during Pandemics." Sensors 20, no. 21: 6149.
This paper proposes a new variable structure control scheme for a variable-speed, fixed-pitch ducted wind turbine, equipped with an annular, brushless permanent-magnet synchronous generator, considering a back-to-back power converter topology. The purpose of this control scheme is to maximise the aerodynamic power over the entire wind speed range, considering the mechanical safety limits of the ducted wind turbine. The ideal power characteristics are achieved with the design of control laws aimed at performing the maximum power point tracking control in the low wind speeds region, and the constant speed, power, and torque control in the high wind speed region. The designed control laws utilize a Luenberger observer for the estimation of the aerodynamic torque and a shallow neural network for wind speed estimation. The effectiveness of the proposed method was verified through tests in a laboratory setup. Moreover, a comparison with other solutions from the literature allowed us to better evaluate the performances achieved and to highlight the originality of the proposed control scheme.
Diego Calabrese; Gioacchino Tricarico; Elia Brescia; Giuseppe Leonardo Cascella; Vito Giuseppe Monopoli; Francesco Cupertino. Variable Structure Control of a Small Ducted Wind Turbine in the Whole Wind Speed Range Using a Luenberger Observer. Energies 2020, 13, 4647 .
AMA StyleDiego Calabrese, Gioacchino Tricarico, Elia Brescia, Giuseppe Leonardo Cascella, Vito Giuseppe Monopoli, Francesco Cupertino. Variable Structure Control of a Small Ducted Wind Turbine in the Whole Wind Speed Range Using a Luenberger Observer. Energies. 2020; 13 (18):4647.
Chicago/Turabian StyleDiego Calabrese; Gioacchino Tricarico; Elia Brescia; Giuseppe Leonardo Cascella; Vito Giuseppe Monopoli; Francesco Cupertino. 2020. "Variable Structure Control of a Small Ducted Wind Turbine in the Whole Wind Speed Range Using a Luenberger Observer." Energies 13, no. 18: 4647.
Widespread dissemination of electric mobility is highly dependent on the power converters, storage systems and renewable energy sources. The efficiency and reliability, combined with the emerging and innovative technologies, are crucial when speaking of power converters. In this paper the interleaved dc–dc topology has been considered for EV charging, due to its improved reliability. The efficiency comparison of the SiC-MOSFET and Si-IGBT-based converters has been done on wide range of switching frequency and output inductances. The interleaved converters were considered with the optimal switching parameters resulting from the analysis done on a detailed parasitic circuit model, ensuring minimum losses and maintaining the safe operating area. The analysis included the comparison of different inductors, and for the selected ones the complete system efficiency and cost were conducted. The results indicate the benefits when SiC-MOSFETs are applied to the interleaved dc–dc topology for wide ranges of output inductances and switching frequencies, and most importantly, they offer lower total volume but also total cost. The realistic and dynamic models of power devices obtained from the manufacturer’s experimental tests have been considered in both LTspice and PLECS simulation tools.
Jelena Loncarski; Vito Giuseppe Monopoli; Giuseppe Leonardo Cascella; Francesco Cupertino. SiC-MOSFET and Si-IGBT-Based dc-dc Interleaved Converters for EV Chargers: Approach for Efficiency Comparison with Minimum Switching Losses Based on Complete Parasitic Modeling. Energies 2020, 13, 4585 .
AMA StyleJelena Loncarski, Vito Giuseppe Monopoli, Giuseppe Leonardo Cascella, Francesco Cupertino. SiC-MOSFET and Si-IGBT-Based dc-dc Interleaved Converters for EV Chargers: Approach for Efficiency Comparison with Minimum Switching Losses Based on Complete Parasitic Modeling. Energies. 2020; 13 (17):4585.
Chicago/Turabian StyleJelena Loncarski; Vito Giuseppe Monopoli; Giuseppe Leonardo Cascella; Francesco Cupertino. 2020. "SiC-MOSFET and Si-IGBT-Based dc-dc Interleaved Converters for EV Chargers: Approach for Efficiency Comparison with Minimum Switching Losses Based on Complete Parasitic Modeling." Energies 13, no. 17: 4585.
Antonio Pietroiusti; Antonio Emmanuele Uva; Giuseppe Leonardo Cascella; Nicola Toschi. COVID-19: contact and gesture monitoring using PROUD Technology. Occupational Medicine 2020, 70, 334 -334.
AMA StyleAntonio Pietroiusti, Antonio Emmanuele Uva, Giuseppe Leonardo Cascella, Nicola Toschi. COVID-19: contact and gesture monitoring using PROUD Technology. Occupational Medicine. 2020; 70 (5):334-334.
Chicago/Turabian StyleAntonio Pietroiusti; Antonio Emmanuele Uva; Giuseppe Leonardo Cascella; Nicola Toschi. 2020. "COVID-19: contact and gesture monitoring using PROUD Technology." Occupational Medicine 70, no. 5: 334-334.
In structural engineering beams with non-constant cross-section or beams with variable cross-section represent a class of slender bodies, aim of practitioners’ interest due to the possibility of optimizing their geometry with respect to specific needs. Despite the advantages that engineers can obtain from their applications, non-trivial difficulties occurring in the non-prismatic beam modeling often lead to inaccurate predictions that vanish the gain of the optimization process. As a consequence, an effective non-prismatic beam modeling still represents a branch of the structural engineering of interest for the community, especially for advanced design applications in large spans elements. A straight beam of length l with variable inertia J(z) is provided in figure, subject to a generic live load condition q(z). The vertical displacement y(z) can be obtained from the solution of the differential equation of the elastic line, i.e., taking into consideration the inertia variability and neglecting, as first approximation, any shear contribution. Even if this solution is an approximate one, it is able to deal with the problem in its basic formulation. In this paper a solution for the problem stated is formulated using a series expansion of solutions, in a general load and cross section variability condition. Solution is thus obtained for a generic rectangular cross section beam with a variable height. Analytical solution is presented and evaluated using numerical evaluation of some cases of practical interest.
Valerio De Biagi; Bernardino Chiaia; Giuseppe Carlo Marano; Alessandra Fiore; Rita Greco; Laura Sardone; Raffaele Cucuzza; Giuseppe Leonardo Cascella; M. Spinelli; Nikos D. Lagaros. Series solution of beams with variable cross-section. Procedia Manufacturing 2020, 44, 489 -496.
AMA StyleValerio De Biagi, Bernardino Chiaia, Giuseppe Carlo Marano, Alessandra Fiore, Rita Greco, Laura Sardone, Raffaele Cucuzza, Giuseppe Leonardo Cascella, M. Spinelli, Nikos D. Lagaros. Series solution of beams with variable cross-section. Procedia Manufacturing. 2020; 44 ():489-496.
Chicago/Turabian StyleValerio De Biagi; Bernardino Chiaia; Giuseppe Carlo Marano; Alessandra Fiore; Rita Greco; Laura Sardone; Raffaele Cucuzza; Giuseppe Leonardo Cascella; M. Spinelli; Nikos D. Lagaros. 2020. "Series solution of beams with variable cross-section." Procedia Manufacturing 44, no. : 489-496.
The work done, lays the foundations for a design methodology that connects the formal and structural aspects of an architecture passing through the parametrization of geometric shapes. To carry out the steps of the design method, the design of a steel pedestrian bridge was experimented. The analysis of the structure made use of the AutoDesk Structural Analysis Robot calculation software; the geometry was parameterized using the AutoDesk Dynamo Studio software (Robot plug-in). The architectural design was carried out using the aforementioned software, managing to connect the formal and the structural part of the project, reaching a focus on the forms of architecture that directly influence the structural functionality. The advantage in this type of design lies in being able to analyze a structure and assign different characteristics to it (from morphology to detail) in real time, managing to connect the project idea directly with a finished product.
G. Cesario; L. Sardone; R. Greco; Giuseppe Leonardo Cascella; Spinelli; G.C. Marano. Parametric Design: formal and structural connection for a pedestrian bridge in the archeological area of Roca Vecchia (IT). Procedia Manufacturing 2020, 44, 473 -480.
AMA StyleG. Cesario, L. Sardone, R. Greco, Giuseppe Leonardo Cascella, Spinelli, G.C. Marano. Parametric Design: formal and structural connection for a pedestrian bridge in the archeological area of Roca Vecchia (IT). Procedia Manufacturing. 2020; 44 ():473-480.
Chicago/Turabian StyleG. Cesario; L. Sardone; R. Greco; Giuseppe Leonardo Cascella; Spinelli; G.C. Marano. 2020. "Parametric Design: formal and structural connection for a pedestrian bridge in the archeological area of Roca Vecchia (IT)." Procedia Manufacturing 44, no. : 473-480.
The milling industry envisions solutions to become fully compatible with the industry 4.0 technology where sensors interconnect devices, machines and processes. In this contest, the work presents an integrated solution merging a deeper understanding and control of the process due to real-time data collection by MicroNIR sensors (VIAVI, Santa Rosa, CA)—directly from the manufacturing process—and data analysis by Chemometrics. To the aim the sensors were positioned at wheat cleaning and at the flour blends phase and near infrared spectra (951–1608 nm) were collected online. Regression models were developed merging the spectra information with the results obtained by reference analyses, i.e., chemical composition and rheological properties of dough by Farinograph® (Brabender GmbH and Co., Duisburg, Germany), Alveograph® (Chopin, NG Villeneuve-la-Garenne Cedex, France) and Extensograph®.(Brabender GmbH and Co., Duisburg, Germany) The model performance was tested by an external dataset obtaining, for most of the parameters, RPRED higher than 0.80 and Root Mean Squares Errors in prediction lower than two-fold the value of the reference method errors. The real-time implementation resulted in optimal (100% of samples) or really good (99.9%–80% of samples) prediction ability. The proposed work succeeded in the implementation of a process analytical approach with Industrial Internet of Things near infrared (IIoT NIR) devices for the prediction of relevant grain and flour characteristics of common wheat at the industrial level.
Silvia Grassi; Alessandra Marti; Davide Cascella; Sergio Casalino; Giuseppe Leonardo Cascella. Electric Drive Supervisor for Milling Process 4.0 Automation: A Process Analytical Approach with IIoT NIR Devices for Common Wheat. Sensors 2020, 20, 1147 .
AMA StyleSilvia Grassi, Alessandra Marti, Davide Cascella, Sergio Casalino, Giuseppe Leonardo Cascella. Electric Drive Supervisor for Milling Process 4.0 Automation: A Process Analytical Approach with IIoT NIR Devices for Common Wheat. Sensors. 2020; 20 (4):1147.
Chicago/Turabian StyleSilvia Grassi; Alessandra Marti; Davide Cascella; Sergio Casalino; Giuseppe Leonardo Cascella. 2020. "Electric Drive Supervisor for Milling Process 4.0 Automation: A Process Analytical Approach with IIoT NIR Devices for Common Wheat." Sensors 20, no. 4: 1147.
Breast cancer is one of the most common cancer in women, with more than 1,300,000 cases and 450,000 deaths each year worldwide. Recent studies show that early breast cancer detection, along with suitable treatment, could significantly reduce breast cancer death rates in the long-term. While the consequences of a false positive diagnosis can be psychologically and socioeconomically burdensome, the result of a false negative diagnosis can be devastating, especially in terms of health detriment. In this context, the false positive and false negative rates commonly achieved by radiologists are extremely arduous to estimate and control, and some authors have estimated figures of up to 20% of total diagnoses or more. Novel ideas in computer-assisted diagnosis have been prompted by the introduction of deep learning techniques in general and of convolutional neural networks (CNN) in particular. In this paper, we design and validate an ad-hoc CNN architecture specialized in breast lesion classification and heuristically explore possible parameter combinations and architecture styles in order to propose a model selection criterion which can pose the emphasis on reducing false negatives while still retaining acceptable accuracy. We achieve good classification performance on the validation and test set, demonstrating how an ad-hoc, random initialization CNN architecture can provide practical aid in the classification and staging of breast cancer.
Andrea Duggento; Manuel Scimeca; Nicoletta Urbano; Elena Bonanno; Marco Aiello; Carlo Cavaliere; Giuseppe Leonardo Cascella; Davide Cascella; Giovanni Conte; Maria Guerrisi; Nicola Toschi. A random initialization deep neural network for discriminating malignant breast cancer lesions. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019, 2019, 912 -915.
AMA StyleAndrea Duggento, Manuel Scimeca, Nicoletta Urbano, Elena Bonanno, Marco Aiello, Carlo Cavaliere, Giuseppe Leonardo Cascella, Davide Cascella, Giovanni Conte, Maria Guerrisi, Nicola Toschi. A random initialization deep neural network for discriminating malignant breast cancer lesions. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2019; 2019 ():912-915.
Chicago/Turabian StyleAndrea Duggento; Manuel Scimeca; Nicoletta Urbano; Elena Bonanno; Marco Aiello; Carlo Cavaliere; Giuseppe Leonardo Cascella; Davide Cascella; Giovanni Conte; Maria Guerrisi; Nicola Toschi. 2019. "A random initialization deep neural network for discriminating malignant breast cancer lesions." 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019, no. : 912-915.
Breast cancer is one of the most common cancers in women, with more than 1,300,000 cases and 450,000 deaths each year worldwide. In this context, recent studies showed that early breast cancer detection, along with suitable treatment, could significantly reduce breast cancer death rates in the long term. X-ray mammography is still the instrument of choice in breast cancer screening. In this context, the false-positive and false-negative rates commonly achieved by radiologists are extremely arduous to estimate and control although some authors have estimated figures of up to 20% of total diagnoses or more. The introduction of novel artificial intelligence (AI) technologies applied to the diagnosis and, possibly, prognosis of breast cancer could revolutionize the current status of the management of the breast cancer patient by assisting the radiologist in clinical image interpretation. Lately, a breakthrough in the AI field has been brought about by the introduction of deep learning techniques in general and of convolutional neural networks in particular. Such techniques require no a priori feature space definition from the operator and are able to achieve classification performances which can even surpass human experts. In this paper, we design and validate an ad hoc CNN architecture specialized in breast lesion classification from imaging data only. We explore a total of 260 model architectures in a train-validation-test split in order to propose a model selection criterion which can pose the emphasis on reducing false negatives while still retaining acceptable accuracy. We achieve an area under the receiver operatic characteristics curve of 0.785 (accuracy 71.19%) on the test set, demonstrating how an ad hoc random initialization architecture can and should be fine tuned to a specific problem, especially in biomedical applications.
Andrea Duggento; Marco Aiello; Carlo Cavaliere; Giuseppe Leonardo Cascella; Davide Cascella; Giovanni Conte; Maria Guerrisi; Nicola Toschi. An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images. Contrast Media & Molecular Imaging 2019, 2019, 5982834 -9.
AMA StyleAndrea Duggento, Marco Aiello, Carlo Cavaliere, Giuseppe Leonardo Cascella, Davide Cascella, Giovanni Conte, Maria Guerrisi, Nicola Toschi. An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images. Contrast Media & Molecular Imaging. 2019; 2019 ():5982834-9.
Chicago/Turabian StyleAndrea Duggento; Marco Aiello; Carlo Cavaliere; Giuseppe Leonardo Cascella; Davide Cascella; Giovanni Conte; Maria Guerrisi; Nicola Toschi. 2019. "An Ad Hoc Random Initialization Deep Neural Network Architecture for Discriminating Malignant Breast Cancer Lesions in Mammographic Images." Contrast Media & Molecular Imaging 2019, no. : 5982834-9.
Synchronous reluctance (SyR) machines can constitute a promising alternative to permanent magnet machines for low-cost applications. The recent literature reports some guidelines for choosing the proper number and position of the rotor flux barriers capable of enhancing the electromagnetic performance in low-speed applications. However, as the rotational speed increases, the electromagnetic and structural mutual interactions become relevant; therefore, an optimal design requires a proper trade-off between torque production and stress reduction, which can be difficultly predicted analytically. This work proposes an approach based on optimisation algorithms in order to find ‘non-conventional’ geometries able to improve the power density: genetic algorithms coupled to magneto-static finite elements analysis and structural analytical models, are adopted to co-design SyR machines with different numbers of stator slots and rotor barriers subjected to the same thermal constraints. This study investigates two design procedures aimed at maximising the output power of SyR machines by increasing the rotational speed. Both procedures allow determining the power limits for a given volume of active parts and a fixed amount of admissible losses; moreover, the second procedure automatically finds also the rotational speed which maximises the output power.
Marco Palmieri; Giuseppe Leonardo Cascella; Francesco Cupertino. Design methodologies for the output power maximisation of synchronous reluctance machines. IET Electric Power Applications 2019, 13, 1131 -1140.
AMA StyleMarco Palmieri, Giuseppe Leonardo Cascella, Francesco Cupertino. Design methodologies for the output power maximisation of synchronous reluctance machines. IET Electric Power Applications. 2019; 13 (8):1131-1140.
Chicago/Turabian StyleMarco Palmieri; Giuseppe Leonardo Cascella; Francesco Cupertino. 2019. "Design methodologies for the output power maximisation of synchronous reluctance machines." IET Electric Power Applications 13, no. 8: 1131-1140.
In this work, we present an Augmented Reality framework for handheld devices that enhance users in the comprehension of plant information traditionally conveyed through printed Piping and Instrumentation Diagrams (P&ID). The proposed framework augments on the P&ID of a plant some virtual interactive graphics (hotspots) referenced to specific components drawn on the P&ID. In this way, it is possible to easily find all the components belonging to the same category (e.g., all the pumps). By tapping, on the tablet screen, on a single hotspot further multimedia information can be displayed: technical data, 3D CAD model of the component, and 360° images of the plant section. The application is connected to the factory database where all the information associated with the plant components is stored. We used, as a case study, the cleaning section of a milling plant. With the tool presented in this work, technicians will be able to find information updated and in less time, so reducing the intervention time and increasing the accuracy of the operations. Furthermore, the cognitive load associated with the task of understanding the plant is highly reduced through the use of virtual information displayed using Augmented Reality.
A. Boccaccio; Giuseppe Leonardo Cascella; M. Fiorentino; M. Gattullo; V. M. Manghisi; G. Monno; Antonio Uva. Exploiting Augmented Reality to Display Technical Information on Industry 4.0 P&ID. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) 2019, 282 -291.
AMA StyleA. Boccaccio, Giuseppe Leonardo Cascella, M. Fiorentino, M. Gattullo, V. M. Manghisi, G. Monno, Antonio Uva. Exploiting Augmented Reality to Display Technical Information on Industry 4.0 P&ID. Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020). 2019; ():282-291.
Chicago/Turabian StyleA. Boccaccio; Giuseppe Leonardo Cascella; M. Fiorentino; M. Gattullo; V. M. Manghisi; G. Monno; Antonio Uva. 2019. "Exploiting Augmented Reality to Display Technical Information on Industry 4.0 P&ID." Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development (MMMS2020) , no. : 282-291.
This work is focused on the design optimization of electrical machines that are used in small-scale direct-drive aerogenerators. A ducted wind turbine, equipped with a diffuser, is considered due to its enhanced power capability with respect to bare turbines. An annular type Permanent Magnet brushless generator is integrated in the turbine structure: the stator coils are placed in the internal part of the diffuser, whereas the permanent magnets are on an external ring connected to the turbine blade tips. Moreover, as regards the stator windings, the Printed Circuit Board (PCB) technology is investigated in order to exploit its advantages with respect to conventional wire coils, such as the increased current density capacity, the reduction of costs, and the enhanced precision and repeatability of the PCBs. An original design procedure is presented together with some scalability rules. An automated tool has been developed in order to aid the electrical machine designer in the first design stages: the tool performs multi-objective optimizations (using the Matlab Genetic Algorithm Toolbox), coupled to fast Finite Element analysis (through the open-source software FEMM) for the evaluation of the electromagnetic torque and field distribution. The proposed procedure is applied to the design of an annular PM generator directly coupled to a small-scale turbine for an urban application.
Marco Palmieri; Salvatore Bozzella; Giuseppe Leonardo Cascella; Marco Bronzini; Marco Torresi; Francesco Cupertino. Wind Micro-Turbine Networks for Urban Areas: Optimal Design and Power Scalability of Permanent Magnet Generators. Energies 2018, 11, 2759 .
AMA StyleMarco Palmieri, Salvatore Bozzella, Giuseppe Leonardo Cascella, Marco Bronzini, Marco Torresi, Francesco Cupertino. Wind Micro-Turbine Networks for Urban Areas: Optimal Design and Power Scalability of Permanent Magnet Generators. Energies. 2018; 11 (10):2759.
Chicago/Turabian StyleMarco Palmieri; Salvatore Bozzella; Giuseppe Leonardo Cascella; Marco Bronzini; Marco Torresi; Francesco Cupertino. 2018. "Wind Micro-Turbine Networks for Urban Areas: Optimal Design and Power Scalability of Permanent Magnet Generators." Energies 11, no. 10: 2759.
Federica Fugaro; Marco Palmieri; Giuseppe Leonardo Cascella; Francesco Cupertino. Aeronautical hybrid propulsion for More Electric Aircraft: a case of study. 2018 AEIT International Annual Conference 2018, 1 .
AMA StyleFederica Fugaro, Marco Palmieri, Giuseppe Leonardo Cascella, Francesco Cupertino. Aeronautical hybrid propulsion for More Electric Aircraft: a case of study. 2018 AEIT International Annual Conference. 2018; ():1.
Chicago/Turabian StyleFederica Fugaro; Marco Palmieri; Giuseppe Leonardo Cascella; Francesco Cupertino. 2018. "Aeronautical hybrid propulsion for More Electric Aircraft: a case of study." 2018 AEIT International Annual Conference , no. : 1.
This paper deals with the design of Synchronous Reluctance Machines for high-speed applications. In particular, this work is focused on the impact of different mechanical refinements made on the rotor lamination with the aim of reducing the maximum stress at high-speed operations. A synchronous reluctance machine, with rated speed equal to 50000 rpm, is firstly designed by means of an automated tool based on optimization algorithms; during the optimization stage, fast magneto-static finite element simulations coupled to an analytical model for the mechanical sizing of the rotor structure are adopted in order to quickly evaluate thousands of candidate machines. After the optimization procedure, different mechanical refinements are manually performed on the selected machine and their influence on the overall performance is evaluated by means of accurate structural and magnetic finite element analysis. The main steps of the design procedure as well as the influence of the geometrical variations on the Von Mises stress reduction within the rotor lamination are presented and analyzed.
Marco Palmieri; Francesco Cupertino; Giuseppe Leonardo Cascella. Mechanical Refinements for the Stress Reduction of High-Speed Synchronous Reluctance Machines. 2018 XIII International Conference on Electrical Machines (ICEM) 2018, 826 -832.
AMA StyleMarco Palmieri, Francesco Cupertino, Giuseppe Leonardo Cascella. Mechanical Refinements for the Stress Reduction of High-Speed Synchronous Reluctance Machines. 2018 XIII International Conference on Electrical Machines (ICEM). 2018; ():826-832.
Chicago/Turabian StyleMarco Palmieri; Francesco Cupertino; Giuseppe Leonardo Cascella. 2018. "Mechanical Refinements for the Stress Reduction of High-Speed Synchronous Reluctance Machines." 2018 XIII International Conference on Electrical Machines (ICEM) , no. : 826-832.
This study considers the design of surface-mounted permanent magnet electrical machines for high-speed applications and proposes a methodology to determine the maximum achievable power density. Power density is usually improved by increasing rotational speed. At high speed, a mechanical retaining system for the rotor magnets must be considered. As the speed increases, the thickness of the retaining sleeve becomes larger, reducing torque capability. There will be an optimal speed at which the output power will be maximised. Both structural and electromagnetic design must be considered simultaneously to properly address this design problem. To simplify the design procedure, static finite-element simulations are used for the electromagnetic analysis and analytical formulae are employed for retaining sleeve sizing. The procedure is aided by multi-objective optimisation algorithms. A case study based on the specification of an aeronautical actuator is presented. The performances that can be obtained using different iron cores, high-grade silicon steel, and cobalt iron steel are compared. Finally, results obtained from transient finite-element electromagnetic and structural analysis are presented to validate the feasibility of the proposed procedure.
Francesco Cupertino; Riccardo Leuzzi; Vito Giuseppe Monopoli; Giuseppe Leonardo Cascella. Maximisation of power density in permanent magnet machines with the aid of optimisation algorithms. IET Electric Power Applications 2018, 12, 1067 -1074.
AMA StyleFrancesco Cupertino, Riccardo Leuzzi, Vito Giuseppe Monopoli, Giuseppe Leonardo Cascella. Maximisation of power density in permanent magnet machines with the aid of optimisation algorithms. IET Electric Power Applications. 2018; 12 (8):1067-1074.
Chicago/Turabian StyleFrancesco Cupertino; Riccardo Leuzzi; Vito Giuseppe Monopoli; Giuseppe Leonardo Cascella. 2018. "Maximisation of power density in permanent magnet machines with the aid of optimisation algorithms." IET Electric Power Applications 12, no. 8: 1067-1074.
This paper considers the electromagnetic and structural co-design of superficial permanent magnet synchronous machines for high-speed applications, with the aid of a Pareto optimization procedure. The aim of this work is to present a design procedure for the afore-mentioned machines that relies on the combined used of optimization algorithms and finite element analysis. The proposed approach allows easy analysis of the results and a lowering of the computational burden. The proposed design method is presented through a practical example starting from the specifications of an aeronautical actuator. The design procedure is based on static finite element simulations for electromagnetic analysis and on analytical formulas for structural design. The final results are validated through detailed transient finite element analysis to verify both electromagnetic and structural performance. The step-by-step presentation of the proposed design methodology allows the reader to easily adapt it to different specifications. Finally, a comparison between a distributed-winding (24 slots) and a concentrated-winding (6 slots) machine is presented demonstrating the advantages of the former winding arrangement for high-speed applications.
Francesco Cupertino; Riccardo Leuzzi; Vito Giuseppe Monopoli; Giuseppe Leonardo Cascella. Design Procedure for High-Speed PM Motors Aided by Optimization Algorithms. Machines 2018, 6, 5 .
AMA StyleFrancesco Cupertino, Riccardo Leuzzi, Vito Giuseppe Monopoli, Giuseppe Leonardo Cascella. Design Procedure for High-Speed PM Motors Aided by Optimization Algorithms. Machines. 2018; 6 (1):5.
Chicago/Turabian StyleFrancesco Cupertino; Riccardo Leuzzi; Vito Giuseppe Monopoli; Giuseppe Leonardo Cascella. 2018. "Design Procedure for High-Speed PM Motors Aided by Optimization Algorithms." Machines 6, no. 1: 5.
This article explores what it takes to make interactive computer graphics and VR attractive as a promotional vehicle, from the points of view of the tourism agencies and the tourists themselves. Specifically, in response to a call from local authorities seeking to increase the tourism appeal of the Apulia region in southern Italy, we proposed an alternative approach to traditional tourism marketing and advertising efforts-a physical stand containing only videos looping on a screen, leaflets, and local personnel.
Vito M. Manghisi; Michele Fiorentino; Michele Gattullo; Antonio Boccaccio; Vitoantonio Bevilacqua; Giuseppe Leonardo Cascella; Michele Dassisti; Antonio Uva. Experiencing the Sights, Smells, Sounds, and Climate of Southern Italy in VR. IEEE Computer Graphics and Applications 2017, 37, 19 -25.
AMA StyleVito M. Manghisi, Michele Fiorentino, Michele Gattullo, Antonio Boccaccio, Vitoantonio Bevilacqua, Giuseppe Leonardo Cascella, Michele Dassisti, Antonio Uva. Experiencing the Sights, Smells, Sounds, and Climate of Southern Italy in VR. IEEE Computer Graphics and Applications. 2017; 37 (6):19-25.
Chicago/Turabian StyleVito M. Manghisi; Michele Fiorentino; Michele Gattullo; Antonio Boccaccio; Vitoantonio Bevilacqua; Giuseppe Leonardo Cascella; Michele Dassisti; Antonio Uva. 2017. "Experiencing the Sights, Smells, Sounds, and Climate of Southern Italy in VR." IEEE Computer Graphics and Applications 37, no. 6: 19-25.
Augmented reality (AR) is a key technology for the development of smart manufacturing. One of the main advantages of AR is that it can help workers to accomplish several tasks, making it possible the shift from mass production to mass customization. However, it is still not clear how these promises can be fulfilled in an industrial scenario. In particular, the question about which display solutions fit better the industrial constraints remains open. Based on the literature overview, laboratory experiments, and feedbacks from industrial companies, we supported the use of spatial augmented reality (SAR), designing a prototype intended to be used for manual working stations of the future smart factories. This work presents the evaluation of the effectiveness of conveying technical instructions with this SAR prototype as compared to paper manual. We run a within-subjects experiment with 16 participants to measure user task performance (completion times and error rates) and to collect subjective evaluation. We projected technical information on a motorbike engine during a seven-task maintenance procedure. Our results proved that SAR technology improves the operators’ performance with respect to a paper manual and that users well accept it. We found that SAR is more effective for difficult tasks than for simple ones and that the main advantage of SAR is related more to the reduction of error rates than to completion times. These results confirm the goodness of our design choices; then our prototype can be a valid candidate solution for a smart manufacturing application.
Antonio Uva; Michele Gattullo; Vito Modesto Manghisi; Daniele Spagnulo; Giuseppe Leonardo Cascella; Michele Fiorentino. Evaluating the effectiveness of spatial augmented reality in smart manufacturing: a solution for manual working stations. The International Journal of Advanced Manufacturing Technology 2017, 94, 509 -521.
AMA StyleAntonio Uva, Michele Gattullo, Vito Modesto Manghisi, Daniele Spagnulo, Giuseppe Leonardo Cascella, Michele Fiorentino. Evaluating the effectiveness of spatial augmented reality in smart manufacturing: a solution for manual working stations. The International Journal of Advanced Manufacturing Technology. 2017; 94 (1-4):509-521.
Chicago/Turabian StyleAntonio Uva; Michele Gattullo; Vito Modesto Manghisi; Daniele Spagnulo; Giuseppe Leonardo Cascella; Michele Fiorentino. 2017. "Evaluating the effectiveness of spatial augmented reality in smart manufacturing: a solution for manual working stations." The International Journal of Advanced Manufacturing Technology 94, no. 1-4: 509-521.