Numerical study of the separation efficiency and heat exchange performance in a complex gas–solid separator

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Combustion CFD modeling of a spark ignited optical access engine fueled with gasoline and ethanol

Abstract In this study we present the Computational Fluid Dynamics (CFD) modeling of the combustion process using detailed chemistry in a spark-ignited (SI) optical access engine operated at part load using gasoline and ethanol as fuels. Simulation results are compared against experimental optical and indicating data. The engine is installed at the Department of Engineering of the University of Perugia, and it features a four-valve head, a transparent flat piston and a port-fuel-injection (PFI) system. Full open cycle simulations have been performed using the commercial code CONVERGE. The combustion process has been simulated using detailed chemistry and adaptive mesh refinement (AMR) to resolve in detail and track the reaction zone, in a Reynolds Averaged Navier-Stokes (RANS) modeling framework. In-cylinder pressure, heat release, and flame morphology have been compared with experimental indicating and imaging data. Tests and simulations span different air-fuel ratios in lean and rich conditions (relative air-fuel ratio λranges from 0.9 to 1.1). Results indicate that simulations are able to predict experimental data with high accuracy. Variations due to changing fuel type and air-fuel ratio are well captured. The computational cost to achieve grid-independent results has been evaluated and it is also not excessively high. Taking into account that the engine speed was quite low, i.e., 900 rpm, we conclude that, in this condition, detailed chemistry coupled with RANS works satisfactorily without turbulence chemistry interaction sub-models, and therefore without any tunings

Peri-procedural brain lesions prevention in CAS (3PCAS). Randomized trial comparing CGuard™ stent vs. wallstent

Background: Aim of this study was to evaluate peri-procedural incidence of new diffusion-weighted-magneticresonance- imaging (DWMRI) brain lesions in CAS patients treated by carotid mesh stent (CGuard™) or closed-cell stent (Wallstent™). Methods: Consecutive patients with asymptomatic carotid stenosis ≥ 70% were submitted to preoperative DWMRI scan, to exclude the presence of preoperative silent cerebral lesions. Patients were randomized to CGuard orWallstent. DWMRI was performed immediately after the intervention and at 72-hour postoperatively. Moreover, pre and postoperative Mini-Mental-State-Examination Test (MMSE) and aMontreal-Cognitive-Assessment (MoCA) test were conducted, and S100β and NSE neurobiomarkers were measured at 5-time points (preoperatively, 2, 12, 24, and 48 h postoperatively). Results: From January 2015 to October 2016, sixty-one consecutive eligible patients were submitted to preoperative DWMRI scan. Three patients were excluded because of preoperative silent cerebral lesions. In 29 CGuard patients, 1 developed a minor stroke and 8 silent newlesionswere observed in the 72 h-DWMRI (31%): 4 lesions were ipsilateral, and 4 lesions were contra or bilateral. In 29 Wallstent patients, 7 clinically-silent new lesions were found in the 72 h-DWMRI (24.1%; p = 0.38). In 4 cases lesions were ipsilateral and in 3 cases contra or bilateral. S100B values doubled at 48 h in 24 patients, and among them 12 presented new DWMRI lesions. 48-h S100B increase was significantly related to 72-h DWMRI lesions (p= 0.012). Conclusions: In our experience both stents showed an acceptable rate of subclinical neurological events with no significant differences at 72-hour DWMRI between groups. Bilateral/contralateral lesions suggest that periprocedural neurological damage may have extra-carotid sources

Comparison between Conventional and Non-Conventional Computer Methods to Define Antiknock Properties of Fuel Mixtures

Research Octane Number (RON) is one of the primary indicators for the determination of the resistance of gasoline fuels to autoignition. This parameter is usually determined with a test procedure involving a standardized engine that requires expensive hardware and time-consuming tests. In this work, a set of different methods with which to determine the RON of gasoline fuel surrogates is presented, considering only computer simulations, which allows to reduce both cost and time for the evaluation. A palette of 11 chemical species has been chosen as the basis for the surrogates’ database, which will be investigated in the work, allowing the representation of the complex chemical formulation of fuels in an easier way. A simplified zero-dimensional engine model of the standard variable compression ratio is used to provide pressure and temperature, then employed to calculate RON. This is done first by means of existing methods, and then by introducing new processes concerning a simplified chemical reactor built on kinetic schemes. Finally, these different methodologies are tested against a molar weighted sum of RONs of each chemical specie, allowing to have a criterion for comparison and evaluating their real prediction capabilities

The use of paleo-detectors to investigate cosmic-ray fluxes throughout the history of Earth

The measurement of the flux of cosmic rays in the past could give some important information about the sources of cosmic rays, the evolution of the neighborhood of the Solar System in the Galaxy and the Galaxy itself. It could also inform our understanding of key events in the Earth’s history such as mass extinctions. The paleo-detector technique proposes to investigate the traces left in natural minerals by energetic particles over geological timescales. A number of works have already suggested the use of paleo-detectors to measure weakly interacting particles such as dark matter constituent particles and neutrinos. Here, we propose for the first time to use paleo-detectors to directly detect secondary cosmic rays. The advantage of this approach is that cosmic rays can be shielded, and thus, in rocks with a particular history, we can measure the flux of cosmic rays at a specific moment in time rather than integrated since the initial formation of the target mineral. For example, evaporites produced in the desiccation of the Mediterranean sea during the Messinian salinity crisis have been exposed to cosmic rays for a very specific (and known) period of time before being submerged by a km-deep overburden of water, possibly retaining information about the flux during the exposure period. In this work, we show the challenges of this kind of study, its proposed targets and the track detection techniques

Nestedness Maximization in Complex Networks through the Fitness-Complexity Algorithm

Nestedness refers to the structural property of complex networks that the neighborhood of a given node is a subset of the neighborhoods of better-connected nodes. Following the seminal work by Patterson and Atmar (1986), ecologists have been long interested in revealing the configuration of maximal nestedness of spatial and interaction matrices of ecological communities. In ecology, the BINMATNEST genetic algorithm can be considered as the state-of-the-art approach for this task. On the other hand, the fitness-complexity ranking algorithm has been recently introduced in the economic complexity literature with the original goal to rank countries and products in World Trade export networks. Here, by bringing together quantitative methods from ecology and economic complexity, we show that the fitness-complexity algorithm is highly effective in the nestedness maximization task. More specifically, it generates matrices that are more nested than the optimal ones by BINMATNEST for 61.27% of the analyzed mutualistic networks. Our findings on ecological and World Trade data suggest that beyond its applications in economic complexity, the fitness-complexity algorithm has the potential to become a standard tool in nestedness analysis