Development of a Phenomenological Combustion Model for Large Bore Dual Fuel Engines

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Numerical investigation of 48 V electrification potential in terms of fuel economy and vehicle performance for a lambda-1 gasoline passenger car

Real Driving Emissions (RDE) regulations require the adoption of stoichiometric operation across the entire engine map for downsized turbocharged gasoline engines, which have been so far generally exploiting spark timing retard and mixture enrichment for knock mitigation. However, stoichiometric operation has a detrimental effect on engine and vehicle performances if no countermeasures are taken, such as alternative approaches for knock mitigation, as the exploitation of Miller cycle and/or powertrain electrification to improve vehicle acceleration performance. This research activity aims, therefore, to assess the potential of 48 V electrification and of the adoption of Miller cycle for a downsized and stoichiometric turbocharged gasoline engine. An integrated vehicle and powertrain model was developed for a reference passenger car, equipped with a EU5 gasoline turbocharged engine. Afterwards, two different 48 V electrified powertrain concepts, one featuring a Belt Starter Generator (BSG) mild-hybrid architecture, the other featuring, in addition to the BSG, a Miller cycle engine combined with an e-supercharger were developed and investigated. Vehicle performances were evaluated both in terms of elasticity maneuvers and of CO2 emissions for type approval and RDE driving cycles. Numerical simulations highlighted potential improvements up to 16% CO2 reduction on RDE driving cycle of a 48 V electrified vehicle featuring a high efficiency powertrain with respect to a EU5 engine and more than 10% of transient performance improvement

Synergetic Application of Zero-, One-, and Three-Dimensional Computational Fluid Dynamics Approaches for Hydrogen-Fuelled Spark Ignition Engine Simulation

Nowadays hydrogen, especially if derived from biomass or produced by renewable power, is rising as a key energy solution to shift the mobility of the future toward a low-emission scenario. It is well known that hydrogen can be used with both internal combustion engines (ICEs) and fuel cells (FCs); however, hydrogen-fuelled ICE represents a robust and cost-efficient option to be quickly implemented under the current production infrastructure. In this framework, this article focuses on the conversion of a state-of-the-art 3.0L diesel engine in a hydrogen-fuelled Spark Ignition (SI) one. To preliminarily evaluate the potential of the converted ICE, a proper simulation methodology was defined combining zero-, one-, and three-dimensional (0D/1D/3D) Computational Fluid Dynamics (CFD) approaches. First of all, a detailed kinetic scheme was selected for both hydrogen combustion and Nitrogen Oxides (NOx) emission predictions in a 3D-CFD environment. Afterward, to bring the analysis to a system-level approach, a 1D-CFD predictive combustion model was firstly optimized by implementing a specific laminar flame speed correlation and, secondly, calibrated against the 3D-CFD combustion results. The combustion model was then integrated into a complete engine model to assess the potential benefit derived from the wide range of flammability and the high flame speed of hydrogen on a complete engine map, considering NOx formation and knock avoidance as priority parameters to control. Without a specific modification of turbocharger and combustion systems, a power density of 34 kW/L and a maximum brake thermal efficiency (BTE) of about 42% were achieved, thus paving the way for further hardware optimization (e.g., compression ratio reduction, turbocharger optimization, direct injection [DI]) to fully exploit the advantages enabled by hydrogen combustion

Clinical value of radiomics and machine learning in breast ultrasound: a multicenter study for differential diagnosis of benign and malignant lesions

We aimed to assess the performance of radiomics and machine learning (ML) for classification of non-cystic benign and malignant breast lesions on ultrasound images, compare ML's accuracy with that of a breast radiologist, and verify if the radiologist's performance is improved by using ML

Combined effect of obesity and diabetes on early breast cancer outcome: A prospective observational study

Background: Previous studies suggested that obesity and diabetes were correlated with breast cancer outcome. The aim of the present study was to investigate the prognostic effect of obesity and diabetes on the outcome of early breast cancer patients. Materials and Methods: Overall, 841 early breast cancer patients were prospectively enrolled between January 2009 and December 2013. Study population was divided into four groups: (1) patients without obesity or diabetes; (2) patients with only diabetes; (3) patients with only obesity; and (4) patients with both diabetes and obesity. Categorical variables were analyzed by the chi-square test and survival data by the log-rank test. Results: At diagnosis, obese and diabetic patients were more likely to be older (p < 0.0001) and post-menopausal (p < 0.0001) and to have a tumor larger than 2 cm (p < 0.0001) than patients in groups 1–3. At univariate analyses, obese and diabetic patients had a worse disease-free survival (p = 0.01) and overall survival (p = 0.001) than did patients without obesity and diabetes. At multivariate analyses, the co-presence of obesity and diabetes was an independent prognostic factor for diseasefree survival (hazard ratio=2.62, 95% CI 1.23–5.60) but not for overall survival. Conclusions: At diagnosis, patients with obesity and diabetes were older, had larger tumors and a worse outcome compared to patients without obesity or diabetes. These data suggest that metabolic health influences the prognosis of patients affected by early breast cance

Managing chronic myeloid leukemia for treatment-free remission: a proposal from the GIMEMA CML WP

Several papers authored by international experts have proposed recommendations on the management of BCR-ABL1+ chronic myeloid leukemia (CML). Following these recommendations, survival of CML patients has become very close to normal. The next, ambitious, step is to bring as many patients as possible into a condition of treatment-free remission (TFR). The Gruppo Italiano Malattie EMatologiche dell'Adulto (GIMEMA; Italian Group for Hematologic Diseases of the Adult) CML Working Party (WP) has developed a project aimed at selecting the treatment policies that may increase the probability of TFR, taking into account 4 variables: the need for TFR, the tyrosine kinase inhibitors (TKIs), the characteristics of leukemia, and the patient. A Delphi-like method was used to reach a consensus among the representatives of 50 centers of the CML WP. A consensus was reached on the assessment of disease risk (EUTOS Long Term Survival [ELTS] score), on the definition of the most appropriate age boundaries for the choice of first-line treatment, on the choice of the TKI for first-line treatment, and on the definition of the responses that do not require a change of the TKI (BCR-ABL1 6410% at 3 months, 641% at 6 months, 640.1% at 12 months, 640.01% at 24 months), and of the responses that require a change of the TKI, when the goal is TFR (BCR-ABL1 &gt;10% at 3 and 6 months, &gt;1% at 12 months, and &gt;0.1% at 24 months). These suggestions may help optimize the treatment strategy for TFR