Effects of fuel composition on charge preparation, combustion and knock tendency in a high performance GDI engine. Part II: Les analysis

As discussed in the Part I of this paper, a numerical activity is carried out in order to analyse the effects of fuel composition modelling in a turbocharged GDI engine for sport car applications. While Part I analyses the "ensemble averaged" macroscopic effects on spray evolution, mixture stratification, combustion and knock tendency, in Part II of this paper cycle-to-cycle variations are analysed and discussed using a multi-cycle LES numerical framework, again comparing results from a more traditional single-component fuel surrogate model to those of a multi-component one. A purposely developed numerical approach is applied to properly account for the effects of the Discrete-Continuous-Multi-Component fuel formulation on the charge preparation: just before the spark timing, each vaporized fuel fraction is lumped back into a single-component surrogate fuel to allow the combustion model (ECFM-3Z, in its LES formulation) to take place. At the beginning of a new injection process, the numerical framework for the injected spray is switched back to Multi-Component, thus allowing each fuel fraction to independently spread, vaporize and diffuse in the combustion chamber according to the cycle-specific characteristics. A detailed comparison between the two fuel formulations is carried out on both average and rms values of the most influencing fields just before the spark discharge

Effects of fuel composition on charge preparation, combustion and knock tendency in a high performance GDI engine. Part I: RANS analysis

The paper analyses the effects of fuel composition modelling in a turbocharged GDI engine for sport car applications. Particularly, a traditional single-component gasoline-surrogate fuel is compared to a seven-component fuel model available in the open literature. The multi-component fuel is represented using the Discrete-Continuous-Multi-Component modelling approach, and it is specifically designed in order to match the volatility of an actual RON95 European gasoline. The comparison is carried out following a detailed calibration with available experimental measurements for a full load maximum power engine speed operation of the engine, and differences are analyzed and critically discussed for each of the spray evolution, mixture stratification and combustion. In the present paper (Part I), a RANS approach is used to preliminarily investigate the behaviour of the fuel model on the average engine cycle. In the subsequent Part II of the same paper, the numerical framework is evolved into a more refined LES approach, in order to take into account cycle-to-cycle variations in mixture formation and knock tendency

Learning ability correlates with brain atrophy and disability progression in RRMS

Objective To assess the prognostic value of practice effect on Paced Auditory Serial Addition Test (PASAT) in multiple sclerosis. Methods We compared screening (day a '14) and baseline (day 0) PASAT scores of 1009 patients from the FTY720 Research Evaluating Effects of Daily Oral therapy in Multiple Sclerosis (FREEDOMS) trial. We grouped patients into high and low learners if their PASAT score change was above or below the median change in their screening PASAT quartile group. We used Wilcoxon test to compare baseline disease characteristics between high and low learners, and multiple regression models to assess the respective impact of learning ability, baseline normalised brain volume and treatment on brain volume loss and 6-month confirmed disability progression over 2 years. Results The mean PASAT score at screening was 45.38, increasing on average by 3.18 from day a '14 to day 0. High learners were younger (p=0.003), had lower Expanded Disability Status Scale score (p=0.031), higher brain volume (p<0.001) and lower T2 lesion volume (p=0.009) at baseline. Learning status was not significantly associated with disability progression (HR=0.953, p=0.779), when adjusting for baseline normalised brain volume, screening PASAT score and treatment arm. However, the effect of fingolimod on disability progression was more pronounced in high learners (HR=0.396, p<0.001) than in low learners (HR=0.798, p=0.351; p for interaction=0.05). Brain volume loss at month 24 tended to be higher in low learners (0.17%, p=0.058), after adjusting for the same covariates. Conclusions Short-term practice effects on PASAT are related to brain volume, disease severity and age and have clinically meaningful prognostic implications. High learners benefited more from fingolimod treatment

Reduced brain atrophy rates are associated with lower risk of disability progression in patients with relapsing multiple sclerosis treated with cladribine tablets.

BACKGROUND: Neuroimaging studies have used magnetic resonance imaging-derived methods to assess brain volume loss in multiple sclerosis (MS) as a reliable measure of diffuse tissue damage. METHODS: In the CLARITY study ( ClinicalTrials.gov NCT00213135), the effect of 2 years' treatment with cladribine tablets on annualized percentage brain volume change (PBVC/y) was evaluated in patients with relapsing MS (RMS). RESULTS: Compared with placebo (-0.70% ± 0.79), PBVC/y was reduced in patients treated with cladribine tablets 3.5 mg/kg (-0.56% ± 0.68, p = 0.010) and 5.25 mg/kg (-0.57% ± 0.72, p = 0.019). After adjusting for treatment group, PBVC/y showed a significant correlation with the cumulative probability of disability progression (HR = 0.67, 95% CI = 0.571, 0.787; p < 0.001), with patients with lower PBVC/y showing the highest probability of remaining free from disability progression at 2 years and vice versa. CONCLUSIONS: Cladribine tablets given annually for 2 years in short-duration courses in patients with RMS in the CLARITY study significantly reduced brain atrophy in comparison with placebo treatment, with residual rates in treated patients being close to the physiological rates.ARES Trading SA, Aubonne, Switzerlan

Smouldering multiple sclerosis: the 'real MS'

Using a philosophical approach or deductive reasoning, we challenge the dominant clinico-radiological worldview that defines multiple sclerosis (MS) as a focal inflammatory disease of the central nervous system (CNS). We provide a range of evidence to argue that the 'real MS' is in fact driven primarily by a smouldering pathological disease process. In natural history studies and clinical trials, relapses and focal activity revealed by magnetic resonance imaging (MRI) in MS patients on placebo or on disease-modifying therapies (DMTs) were found to be poor predictors of long-term disease evolution and were dissociated from disability outcomes. In addition, the progressive accumulation of disability in MS can occur independently of relapse activity from early in the disease course. This scenario is underpinned by a more diffuse smouldering pathological process that may affect the entire CNS. Many putative pathological drivers of smouldering MS can be potentially modified by specific therapeutic strategies, an approach that may have major implications for the management of MS patients. We hypothesise that therapeutically targeting a state of 'no evident inflammatory disease activity' (NEIDA) cannot sufficiently prevent disability accumulation in MS, meaning that treatment should also focus on other brain and spinal cord pathological processes contributing to the slow loss of neurological function. This should also be complemented with a holistic approach to the management of other systemic disease processes that have been shown to worsen MS outcomes

COVID‐19 Vaccine Response in People with Multiple Sclerosis

ObjectiveThe purpose of this study was to investigate the effect of disease modifying therapies on immune response to severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) vaccines in people with multiple sclerosis (MS).MethodsFour hundred seventy-three people with MS provided one or more dried blood spot samples. Information about coronavirus disease 2019 (COVID-19) and vaccine history, medical, and drug history were extracted from questionnaires and medical records. Dried blood spots were eluted and tested for antibodies to SARS-CoV-2. Antibody titers were partitioned into tertiles with people on no disease modifying therapy as a reference. We calculated the odds ratio of seroconversion (univariate logistic regression) and compared quantitative vaccine response (Kruskal Wallis) following the SARS-CoV-2 vaccine according to disease modifying therapy. We used regression modeling to explore the effect of vaccine timing, treatment duration, age, vaccine type, and lymphocyte count on vaccine response.ResultsCompared to no disease modifying therapy, the use of anti-CD20 monoclonal antibodies (odds ratio = 0.03, 95% confidence interval [CI] = 0.01–0.06, p [less than] 0.001) and fingolimod (odds ratio = 0.04; 95% CI = 0.01–0.12) were associated with lower seroconversion following the SARS-CoV-2 vaccine. All other drugs did not differ significantly from the untreated cohort. Both time since last anti-CD20 treatment and total time on treatment were significantly associated with the response to the vaccination. The vaccine type significantly predicted seroconversion, but not in those on anti-CD20 medications. Preliminary data on cellular T-cell immunity showed 40% of seronegative subjects had measurable anti-SARS-CoV-2 T cell responses.InterpretationSome disease modifying therapies convey risk of attenuated serological response to SARS-CoV-2 vaccination in people with MS. We provide recommendations for the practical management of this patient group. ANN NEUROL 202

Effects of Fuel-Induced Piston-Cooling and Fuel Formulation on the Formation of Fuel Deposits and Mixture Stratification in a GDI Engine

Fuel deposits in DISI engines promote unburnt hydrocarbon and soot formation: due to the increasingly stringent emission regulations (EU6 and forthcoming), it is necessary to deeply analyze and well-understand the complex physical mechanisms promoting fuel deposit formation. The task is not trivial, due to the coexistence of mutually interacting factors, such as complex moving geometries, influencing both impact angle and velocity, and time-dependent wall temperatures. The experimental characterization of actual engine conditions on transparent combustion chambers is limited to highly specialized research laboratories; therefore, 3D-CFD simulations can be a fundamental tool to investigate and understand the complex interplay of all the mentioned factors. The aim is pursued in this study by means of full-cycle simulations accounting for instantaneous fuel/piston thermal interaction and actual fuel characteristics. To overcome the standard practice, based on the adoption of time-independent wall temperatures, solid cell layers are added onto the piston crown. In particular, thermal boundary conditions on the lower face of the piston portion are derived from a complete CHT simulation, thus considering both the actual piston shape and the point-wise cooling effect by the oil jets, the friction contribution and the heat transfer to the cylinder liner and the connecting rod. Furthermore, the use of a simplified fuel model based on a single-component formulation is compared to a more realistic hydrocarbon blend. The methodology is applied to a currently produced turbocharged DISI engine operating at full load peak power and maximum torque regimes; the piston thermal field is completely resolved in space and time during the engine cycle, and its effects on spray guidance, fuel impingement and liquid film formation are carefully analyzed

CFD Analysis of the Effects of Fuel Composition and Injection Strategy on Mixture Preparation and Fuel Deposit Formation in a GDI Engine

In spark-ignited direct-injected engines, the formation of fuel pools on the piston is one of the major promoters of unburnt hydrocarbons and soot: in order to comply with the increasingly stringent emission regulations (EU6 and forthcoming), it is therefore necessary to limit fuel deposit formation. The combined use of advanced experimental techniques and detailed 3D-CFD simulations can help to understand the mechanisms driving fuel pool formation. In the paper, a combined experimental and numerical characterization of pool formation in a GDI engine is carried out to investigate and understand the complex interplay of all the mentioned factors. In particular, a low-load low-rpm engine operation is investigated for different ignition phasing, and the impact of both fuel formulation and instantaneous piston temperature variations in the CFD analyses are evaluated. The investigated engine operation shows some interesting features which are suited to deeply investigate the interplay between fuel film formation, mixing and soot. In particular, the relatively low wall temperature and low injection pressure allow the fuel to form deposits and then slowly evaporate, with possible presence of liquid fuel at the time of ignition. The simultaneous presence of slow fuel evaporation, reduced turbulence and presence of liquid fuel leads to the formation of extremely rich mixture pockets (with equivalence ratios well above 5) which are the major promoters for soot inception. Four different start of injection (hereafter SOI) values are analyzed, for which tailpipe Soot concentration measurements are available. For one SOI value, two different injection profiles are also evaluated. In particular, the analyses focus on the formation of fuel pads on the combustion chamber walls and on the mixture stratification, and a correlation between these two factors and the tailpipe soot level is found. The proposed methodology proves to be able to capture the Soot trend for the different SOI values without simulating the combustion process; it is therefore promising since it avoids the need for a dedicated calibration of the combustion model parameters and provides reasonable results (at least in terms of trends) with limited computational resources