Convolutional neural networks for the shape design of a magnetic core for material testing: Forward and inverse approaches

In this paper CNNs are used for solving an optimization problem with two different approaches: CNN is used as a surrogate model of the forward problem, inserted in an optimization loop governed by a genetic algorithm, in the first approach, while a CNN is trained for solving directly the inverse problem in the second approach. The case study is the shape design of a magnetic core used for material testing

Multi-physics and multi-objective design of a benchmark device: a problem of inverse induction heating

In the paper, a bi-objective optimization problem characterized by a multi-physics field analysis is investigated. The optimal design of a pancake inductor, related to the design of industrial devices for the controlled heating of a graphite disk is considered as the benchmark problem. The expected goal of the optimization process is to improve temperature uniformity in the disk as well as electrical efficiency of the inductor. The optimized device is designed using a multi-physics problem: magnetic problem for electrical efficiency computation and thermal problem for temperature uniformity computation. The solution of the relevant bi-objective optimization problem is based on a modified multi-objective genetic algorithm in the class of Non-dominated Sorting Genetic Algorithm. The proposed algorithm exploits the migration concept to vary the population genetic characteristics during optimization process in order to improve the Pareto front approximation

Optimization of Compensation Network for a Wireless Power Transfer System in Dynamic Conditions: A Circuit Analysis Approach

The paper is focused on the optimization of the compensation network of a wireless power transfer system (WPTS) intended to operate in dynamic conditions. A laboratory prototype of a WPTS has been taken as a reference in this work, allowing for the experimental data and all the numerical models here presented to reproduce the configuration of the existing device. The numerical model has been used to perform FEM analysis with variable relative positions of the emitting and receiving coil to simulate the movement in a 'recharge while driving' condition. Inductive lumped parameters, i.e., self and mutual inductances computed from FEM results, have been used for the optimal design of the compensation network necessary for the WPTS operation. The optimal design of the resonance circuits has been developed by defining objective functions, aiming to achieve these goals: transmitted power must be as constant as possible when the vehicle is in movement and the electrical efficiency must be satisfactory high in most of the coupling conditions. The performances of the optimized network are finally compared and discussed

A deep learning approach to improve the control of dynamic wireless power transfer systems

In this paper, an innovative approach for the fast estimation of the mutual inductance between transmitting and receiving coils for Dynamic Wireless Power Transfer Systems (DWPTSs) is implemented. To this end, a Convolutional Neural Network (CNN) is used; an image representing the geometry of two coils that are partially misaligned is the input of the CNN, while the output is the corresponding inductance value. Finite Element Analyses are used for the computation of the inductance values needed for CNN training. This way, thanks to a fast and accurate inductance estimated by the CNN, it is possible to properly manage the power converter devoted to charge the battery, avoiding the wind up of its controller when it attempts to transfer power in poor coupling conditions

New solutions to a multi-objective benchmark problem of induction heating: an application of computational biogeography and evolutionary algorithms

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Genetic predisposition to hemophagocytic lymphohistiocytosis: report on 500 patients from the Italian registry

Background Hemophagocytic lymphohistiocytosis (HLH) is a rare life-threatening disease affecting mostly children but also adults and characterized by hyperinflammatory features. A subset of patients, referred to as having familial hemophagocytic lymphohistiocytosis (FHL), have various underlying genetic abnormalities, the frequencies of which have not been systematically determined previously. Objective This work aims to further our understanding of the pathogenic bases of this rare condition based on an analysis of our 25 years of experience. Methods From our registry, we have analyzed a total of 500 unselected patients with HLH. Results Biallelic pathogenic mutations defining FHL were found in 171 (34%) patients; the proportion of FHL was much higher (64%) in patients given a diagnosis during the first year of life. Taken together, mutations of the genes PRF1 (FHL2) and UNC13D (FHL3) accounted for 70% of cases of FHL. Overall, a genetic diagnosis was possible in more than 90% of our patients with FHL. Perforin expression and the extent of degranulation have been more useful for diagnosing FHL than hemophagocytosis and the cytotoxicity assay. Of 281 (56%) patients classified as having "sporadic" HLH, 43 had monoallelic mutations in one of the FHL-defining genes. Given this gene dosage effect, FHL is not strictly recessive. Conclusion We suggest that the clinical syndrome HLH generally results from the combined effects of an exogenous trigger and genetic predisposition. Within this combination, different weights of exogenous and genetic factors account for the wide disease spectrum that ranges from HLH secondary to severe infection to FHL

Outcomes of children with hemophagocytic lymphohistiocytosis given allogeneic hematopoietic stem cell transplantation in Italy

We report on 109 patients with hemophagocytic lymphohistiocytosis (HLH) undergoing 126 procedures of allogeneic hematopoietic stem cell transplantation (HSCT) between 2000 and 2014 in centers associated with the Italian Pediatric Hematology Oncology Association. Genetic diagnosis was FHL2 (32%), FHL3 (33%), or other defined disorders known to cause HLH (15%); in the remaining patients no genetic abnormality was found. Donor for first transplant was an HLA-matched sibling for 25 patients (23%), an unrelated donor for 73 (67%), and an HLA-partially matched family donor for 11 children (10%). Conditioning regimen was busulfan-based for 61 patients (56%), treosulfan-based for 21 (20%), and fludarabine-based for 26 children (24%). The 5-year probabilities of overall survival (OS) and event-free survival (EFS) were 71% and 60%, respectively. Twenty-six patients (24%) died due to transplant-related causes, whereas 14 (13%) and 10 (9%) patients experienced graft rejection and/or relapse, respectively. Twelve of 14 children given a second HSCT after graft failure/relapse are alive and disease-free. Use of HLA-partially matched family donors was associated with higher risk of graft failure and thus with lower EFS (but not with lower OS) in multivariable analysis. Active disease at transplantation did not significantly affect prognosis. These data confirm that HSCT can cure most HLH patients, active disease not precluding successful transplantation. Because in HLH patients HLA-haploidentical HSCT performed through CD34 + cell positive selection was found to be associated with poor sustained engraftment of donor cells, innovative approaches able to guarantee a more robust engraftment are warranted in patients given this type of allograft