Synchronous reluctance motor iron losses: considering machine non-linearity at MTPA, FW, and MTPV operating conditions

Synchronous reluctance machine has high flux density fluctuations in the iron due to the high harmonics results from the rotor anisotropy. Thus, an accurate computation of the iron losses is of paramount importance, especially during the design stage. In this paper, a non-linear analytical model considering the magnetic iron saturation and the slotting effect is proposed. The model estimates accurately the iron losses at a wide range of operating speed. In addition, the accuracy of the non-linear model when the machine is highly saturated, i.e. when it works along the MTPA trajectory, is presented and verified. The model presented is general and can be applied to other configurations. A 36-slot four-pole machine, with three flux-barriers per pole is considered as a case study. Finite element analysis is used to validate the results achieved by means of the non-linear analytical model. Furthermore, an experimental setup is built to validate the simulation results

A nonlinear analytical model for the rapid prediction of the torque of synchronous reluctance machines

The synchronous reluctance motor works under heavy saturation. This paper presents a nonlinear analytical model of the reluctance machine, which is used to derive both average and torque harmonics as a function of the rotor geometry. Maps showing the torque harmonics as a function of the rotor barrier angles are derived. These maps are useful tools for the machine designer to get a proper rotor geometry. The torque maps are compared with those obtained from both linear analytical and finite element models. The maps computed analytically show good agreement with those derived by means of finite element analysis, and they are obtained in a much smaller computing time

Adaptive real time selection for quantum key distribution in lossy and turbulent free-space channels

The unconditional security in the creation of cryptographic keys obtained by quantum key distribution (QKD) protocols will induce a quantum leap in free-space communication privacy in the same way that we are beginning to realize secure optical fiber connections. However, free-space channels, in particular those with long links and the presence of atmospheric turbulence, are affected by losses, fluctuating transmissivity, and background light that impair the conditions for secure QKD. Here we introduce a method to contrast the atmospheric turbulence in QKD experiments. Our adaptive real time selection (ARTS) technique at the receiver is based on the selection of the intervals with higher channel transmissivity. We demonstrate, using data from the Canary Island 143-km free-space link, that conditions with unacceptable average quantum bit error rate which would prevent the generation of a secure key can be used once parsed according to the instantaneous scintillation using the ARTS technique

The IMPACT study: early loss of skeletal muscle mass in advanced pancreatic cancer patients

Abstract Background Pancreatic cancer (PC) patients have multiple risk factors for sarcopenia and loss of skeletal muscle mass (LSMM), which may cause greater treatment toxicities, reduced response to cancer therapy, prolonged hospitalization, impaired quality of life, and worse prognosis. Methods This is a retrospective study on advanced PC patients treated at the Department of Oncology of Udine, Italy, from January 2012 to November 2017. Among 162 patients who received chemotherapy, 94 consecutive patients with an available computed tomography (CT) scan were retrospectively analyzed. The primary objective of our study was to explore if an early LSMM ≥ 10% (measured at first radiological evaluation and compared with baseline) and/or baseline sarcopenia may impact prognosis. Baseline sarcopenia was defined according to Prado's criteria. Skeletal muscle area was measured as cross‐sectional areas (cm2) using CT scan data through the Picture archiving and communication system (PACS) image system. Results In the whole cohort, 48% of patients were ≤70 years old, and 50% had metastatic disease. At baseline, 73% of patients had sarcopenia, and 16% presented a visceral fat area ≥ 44 cm2/m2. Overall, 21% experienced an early LSMM ≥ 10%. Approximately 33% of sarcopenic patients at baseline and ~35% of patients with early LSMM ≥ 10% had a body mass index > 25 kg/m2. Of note, 71% of patients were evaluated by a nutritionist, and 56% received a dietary supplementation (oral and/or parenteral). After a median follow‐up of 30.44 months, median overall survival (OS) was 11.28 months, whereas median progression‐free survival (PFS) was 5.72 months. By multivariate analysis, early LSMM ≥ 10% was significantly associated with worse OS [hazard ratio (HR): 2.16; 95% confidence interval (CI) 1.23–3.78; P = 0.007] and PFS (HR: 2.31; 95% CI 1.30–4.09; P = 0.004). Moreover, an exploratory analysis showed that inflammatory indexes, such as neutrophil–lymphocyte ratio variation, impact early LSMM ≥ 10% (odds ratio 1.31, 95% CI 1.06–1.61, P = 0.010). Conclusions Early LSMM ≥ 10% has a negative prognostic role in advanced PC patients. Further prospective investigations are needed to confirm these preliminary data

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Advanced Design and Optimization of Anisotropic Synchronous Machines

This work covers many research aspects of anisotropic synchronous motors, which are synchronous reluctance (SyR), permanent magnet assisted synchronous reluctance (PMaSyR) and interior permanent magnet (IPM) machines. In fact, all these kinds of machines exhibit quite a strong reluctance torque component, hence the name anisotropic. From the early 2000s, the design of electric machines started to deeply rely on finite element analysis (FEA) coupled to automatic optimization algorithms. This workflow enabled the machine designer to make fewer initial sizing hypotheses and to explore a wider design space. The drawbacks of this approach are that the time required is long and that the computational resources needed are quite large. However, the computing performances have always been improving over the years, especially when multi-processor architectures became widespread. Therefore nowadays it is common to employ tens or even hundreds of cores on cluster PCs to perform FEA during optimization runs. The thesis is structured as follows. The first part gives the background knowledge needed to develop the topics covered in the following. This comprehends an introduction to the machines studied, some general knowledge about magnetic materials, some basic concepts about the differential evolution (DE) algorithm, and the drawing of fluid rotor flux-barriers. The second part deals with the analytical modeling of SyR and PMaSyR machines. The complete model is nonlinear and may become convoluted to develop especially in an industrial environment. Therefore, using simplifying assumptions, a handful of simple equations can be derived. This simple model is also extended and applied to asymmetric rotor structures, which try to compensate torque harmonics. The third part focuses on applied multi-objective optimizations coupled to FEA for many different case studies. In particular, a SyR motor (SyRM) for pumping applications is optimized, prototyped and tested. Then, a feasibility study on a very low speed PMaSyR motor is carried out through multi-objective optimization. After that, high speed SyRMs are studied and optimized to understand the power limits of this kind of machine. Finally, the DE multi-objective optimization algorithm is also applied to improve the sensorless-control capabilities of anisotropic machines by design.Questo lavoro analizza molti aspetti di ricerca dei motori sincroni anisotropi, che includono le macchine sincrone a riluttanza pura (SyR), a riluttanza assistita da magneti (PMaSyR) e le macchine a magneti permanenti interni (IPM). Infatti, tutte queste macchine esibiscono una forte componente di riluttanza, da cui il nome anisotrope. Dai primi anni 2000, la progettazione di macchine elettriche ha cominciato a basarsi in modo consistente sull’analisi agli elementi finiti (FEA) accoppiata ad algoritmi di ottimizzazione automatici. Questo flusso di lavoro permette al progettista di fare un minor numero di ipotesi preliminari e di esplorare uno spazio di progetto più ampio. Gli svantaggi di questo approccio sono che il tempo richiesto è lungo e che le risorse computazionali richieste possono essere elevate. Tuttavia, le prestazioni dei computer migliorano di anno in anno, e in particolar modo con la diffusione delle architetture a multi-processore. Pertanto oggigiorno è comune impiegare decine o persino centinaia di core su cluster di PC per effettuare analisi agli elementi finiti durante un’ottimizzazione. La tesi è strutturata nel seguente modo. La prima parte copre le conoscenze di base necessarie a sviluppare gli argomenti trattati nel seguito. C’è quindi un’introduzione alle macchine studiate, delle conoscenze generali sui materiali magnetici e ferromagnetici, alcuni concetti di base sull’algoritmo di ottimizzazione differential evolution (DE) utilizzato, e il disegno delle barriere fluide dei rotori di macchine a riluttanza. Nella seconda parte si sono sviluppati modelli analitici di macchine SyR e PMaSyR. Il modello completo è non lineare e può diventare abbastanza complesso da sviluppare, specialmente in un contesto industriale. Pertanto, usando alcune ipotesi semplificative, si possono derivare alcune semplici equazioni di progetto. Questo modello semplice è anche esteso e applicato a strutture di rotore asimmetriche, che tentano di compensare alcune armoniche di coppia. La terza parte si concentra sull’applicazioni di ottimizzazioni multiobiettivo accoppiate a FEA per alcuni casi di studio. In particolare, si è ottimizzato, prototipato e testato un motore SyRper pompe centrifughe. Poi, è stato condotto uno studio di fattibilità per un motore PMaSyR attraverso ottimizzazioni multi-obiettivo. Dopodiché si sono studiati motori SyRper alte velocità e si sono dedotti i limiti di potenza di questa macchina. Infine l’ottimizzazione DE multi-obiettivo è stata anche applicata per migliorare le capacità di controllo sensorless delle macchine anisotrope già in fase di progetto

Advanced Design and Optimization of Anisotropic Synchronous Machines

This work covers many research aspects of anisotropic synchronous motors, which are synchronous reluctance (SyR), permanent magnet assisted synchronous reluctance (PMaSyR) and interior permanent magnet (IPM) machines. In fact, all these kinds of machines exhibit quite a strong reluctance torque component, hence the name anisotropic. From the early 2000s, the design of electric machines started to deeply rely on finite element analysis (FEA) coupled to automatic optimization algorithms. This workflow enabled the machine designer to make fewer initial sizing hypotheses and to explore a wider design space. The drawbacks of this approach are that the time required is long and that the computational resources needed are quite large. However, the computing performances have always been improving over the years, especially when multi-processor architectures became widespread. Therefore nowadays it is common to employ tens or even hundreds of cores on cluster PCs to perform FEA during optimization runs. The thesis is structured as follows. The first part gives the background knowledge needed to develop the topics covered in the following. This comprehends an introduction to the machines studied, some general knowledge about magnetic materials, some basic concepts about the differential evolution (DE) algorithm, and the drawing of fluid rotor flux-barriers. The second part deals with the analytical modeling of SyR and PMaSyR machines. The complete model is nonlinear and may become convoluted to develop especially in an industrial environment. Therefore, using simplifying assumptions, a handful of simple equations can be derived. This simple model is also extended and applied to asymmetric rotor structures, which try to compensate torque harmonics. The third part focuses on applied multi-objective optimizations coupled to FEA for many different case studies. In particular, a SyR motor (SyRM) for pumping applications is optimized, prototyped and tested. Then, a feasibility study on a very low speed PMaSyR motor is carried out through multi-objective optimization. After that, high speed SyRMs are studied and optimized to understand the power limits of this kind of machine. Finally, the DE multi-objective optimization algorithm is also applied to improve the sensorless-control capabilities of anisotropic machines by design

Choice of flux-barriers position in synchronous reluctance machines

This paper deals with the design of the rotor of synchronous reluctance machines, characterized by a multi flux-barrier structure. In particular, the focus will be on the proper design of flux-barriers geometry. An analytical model is adopted to compute the impact of the rotor flux-barriers on the torque, focusing on the torque ripple. Thanks to proper assumptions, the analytical model is simplified so as to highlight the main causes of torque ripple. Such an analytical model allows to derive the angles of the flux-barrier ends corresponding to the minimum torque ripple in a closed form. This result has never been presented in the past literature and it represents a useful tool as far as the motor design is concerned. Rotors with one and two flux-barriers per rotor pole are taken into account. However, the advantageous analytical model can be extended to any number of flux-barriers per pole. Some examples referring to 4-pole synchronous reluctance machines with different numbers of stator slots are investigated and illustrated. The results are compared with a full-featured analytical model and validated through finite element simulations