549 research outputs found
Quantum Interactions Between Non-Perturbative Vacuum Fields
We develop an approach to investigate the non-perturbative dynamics of
quantum field theories, in which specific vacuum field fluctuations are treated
as the low-energy dynamical degrees of freedom, while all other vacuum field
configurations are explicitly integrated out from the path integral. We show
how to compute the effective interaction between the vacuum field degrees of
freedom both perturbatively (using stochastic perturbation theory) and fully
non-perturbatively (using lattice field theory simulations). The present
approach holds to all orders in the couplings and does not rely on the
semi-classical approximation.Comment: 15 pages, 4 figure
Energy management system optimization based on an LSTM deep learning model using vehicle speed prediction
The energy management of a Hybrid Electric Vehicle (HEV) is a global optimization problem, and its optimal solution inevitably entails knowing the entire mission profile. The exploitation of Vehicle-to-Everything (V2X) connectivity can pave the way for reliable short-term vehicle speed predictions. As a result, the capabilities of conventional energy management strategies can be enhanced by integrating the predicted vehicle speed into the powertrain control strategy. Therefore, in this paper, an innovative Adaptation algorithm uses the predicted speed profile for an Equivalent Consumption Minimization Strategy (A-V2X-ECMS). Driving pattern identification is employed to adapt the equivalence factor of the ECMS when a change in the driving patterns occurs, or when the State of Charge (SoC) experiences a high deviation from the target value. A Principal Component Analysis (PCA) was performed on several energetic indices to select the ones that predominate in characterizing the different driving patterns. Long Short-Term Memory (LSTM) deep neural networks were trained to choose the optimal value of the equivalence factor for a specific sequence of data (i.e., speed, acceleration, power, and initial SoC). The potentialities of the innovative A-V2X-ECMS were assessed, through numerical simulation, on a diesel Plug-in Hybrid Electric Vehicle (PHEV) available on the European market. A virtual test rig of the investigated vehicle was built in the GT-SUITE software environment and validated against a wide database of experimental data. The simulations proved that the proposed approach achieves results much closer to optimal than the conventional energy management strategies taken as a reference
A Methodology for the Reverse Engineering of the Energy Management Strategy of a Plug -In Hybrid Electric Vehicle for Virtual Test Rig Development
Nowadays, the need for more sustainable mobility is fostering powertrain electrification as a way of reducing the carbon footprint of conventional vehicles. On the other side, the presence of multiple energy sources significantly increases the powertrain complexity and requires the development of a suitable Energy Management System (EMS) whose performance can strongly affect the fuel economy potential of the vehicle. In such a framework, this article proposes a novel methodology to reverse engineer the control strategy of a test case P2 Plug-in Hybrid Electric Vehicle (PHEV) through the analysis of experimental data acquired in a wide range of driving conditions. In particular, a combination of data obtained from On-Board Diagnostic system (OBD), Controller Area Network (CAN)-bus protocol, and additional sensors installed on the High Voltage (HV) electric net of the vehicle is used to point out any dependency of the EMS decisions on the powertrain main operating variables. Furthermore, the impact that Vehicle-to-Infrastructure (V2I) connections have on the control law is assessed on several tests performing the same real-world route with the vehicle navigation system alternatively switched on and off. Finally, a virtual test rig of the tested vehicle, developed in the GT- SUITE environment, is used to validate the set of extracted rules against the experimental data. An error of about 1-2% on the prediction of the vehicle CO2 emissions and good matching of the State of Charge (SoC) profile in both Charge Depleting (CD) and Charge Sustaining (CS) phases prove the effectiveness of the proposed methodology
Computing the Effective Hamiltonian of Low-Energy Vacuum Gauge Fields
A standard approach to investigate the non-perturbative QCD dynamics is
through vacuum models which emphasize the role played by specific gauge field
fluctuations, such as instantons, monopoles or vortexes. The effective
Hamiltonian describing the dynamics of the low-energy degrees of freedom in
such approaches is usually postulated phenomenologically, or obtained through
uncontrolled approximations. In a recent paper, we have shown how lattice field
theory simulations can be used to rigorously compute the effective Hamiltonian
of arbitrary vacuum models by stochastically performing the path integral over
all the vacuum field fluctuations which are not explicitly taken into account.
In this work, we present the first illustrative application of such an approach
to a gauge theory and we use it to compute the instanton size distribution in
SU(2) gluon-dynamics in a fully model independent and parameter-free way.Comment: 10 pages, 4 figure
Real CO2 emissions benefits and end user’s operating costs of a plug-in Hybrid Electric Vehicle
Although plug-in Hybrid Electric Vehicles (pHEVs) can be considered a powerful technology to promote the change from conventional mobility to e-mobility, their real benefits, in terms of CO2 emissions, depend to a great extent on the average efficiency of their Internal Combustion Engine and on the energy source mix which is used to supply the electrical demand of pHEV.
Furthermore the operating cost of the vehicle should also be taken into account in the design process, since it represents the main driver in the customer’s choice.
This article has the purpose of assessing, through numerical simulations, the effects of different technology mixes used to produce electrical energy for the battery recharging, of different Internal Combustion Engines on the pHEV performance, and highlighting the main differences with respect to the regulatory test procedure
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
Enhancement of the superconducting transition temperature in La2-xSrxCuO4 bilayers: Role of pairing and phase stiffness
The superconducting transition temperature, Tc, of bilayers comprising
underdoped La2-xSrxCuO4 films capped by a thin heavily overdoped metallic
La1.65Sr0.35CuO4 layer, is found to increase with respect to Tc of the bare
underdoped films. The highest Tc is achieved for x = 0.12, close to the
'anomalous' 1/8 doping level, and exceeds that of the optimally-doped bare
film. Our data suggest that the enhanced superconductivity is confined to the
interface between the layers. We attribute the effect to a combination of the
high pairing scale in the underdoped layer with an enhanced phase stiffness
induced by the overdoped film.Comment: Published versio
Effect of coil charge duration on combustion variability and flame morphology in a GDI engine working in lean burn conditions
Spark ignition (SI) and subsequent flame front development exert a significant influence on cyclic variability of internal combustion engines (ICEs). The increasing exploitation of lean air-fuel mixtures in SI engines to lower fuel consumption and CO2 emissions is driving the scientific community towards the search for innovative combustion strategies. Moreover, although lean combustion has been widely investigated and an important number of studies is already present in literature, the high cyclic variability typical of this combustion process still represents a major hinder to its exploitation. This study aims to investigate the effects of increasing ignition energy on combustion characteristics of lean mixtures. Tests were performed on an optically accessible gasoline direct injection (GDI) engine that allowed to investigate the correlation between the thermodynamic results and spark arc-flame morphology. Engine speed was fixed at 2000 rpm, a relative air fuel ratio (AFRrel) of about 1.3 was selected and ignition timing was set at 12 crank angle degrees (CAD) bTDC. Coil charge duration was swept from 10 to 40 CAD. Two intake pressure levels were investigated, the first corresponding to wide open throttle under naturally aspirated operating mode, the second with an intake pressure of 1.2 bar, thus corresponding to a boosted operating condition. Two dedicated scripts built using NI Vision were employed for image processing, allowing the evaluation of temporal and spatial evolution of the early stages of combustion. Arc elongation and flame front contour were used as correlation parameters that characterize flame kernel inception and development. The results confirm that, as expected, the increase of the coil charge duration tends to reduce cyclic variability in terms of engine output. The optical investigations revealed that for both examined cases the standard deviation related to the wrinkling effect on flame edge at CA5 decreased as the coil charge duration increased
Correlation of tunneling spectra with surface nano-morphology and doping in thin YBa2Cu3O7-delta films
Tunneling spectra measured on thin epitaxial YBa2Cu3O7-delta films are found
to exhibit strong spatial variations, showing U and V-shaped gaps as well as
zero bias conductance peaks typical of a d-wave superconductor. A full
correspondence is found between the tunneling spectra and the surface
morphology down to a level of a unit-cell step. Splitting of the zero bias
conductance peak is seen in optimally-doped and overdoped films, but not in the
underdoped ones, suggesting that there is no transition to a state of broken
time reversal symmetry in the underdoped regimeComment: accepted to ep
Ultrastable lasers based on vibration insensitive cavities
We present two ultra-stable lasers based on two vibration insensitive cavity
designs, one with vertical optical axis geometry, the other horizontal.
Ultra-stable cavities are constructed with fused silica mirror substrates,
shown to decrease the thermal noise limit, in order to improve the frequency
stability over previous designs. Vibration sensitivity components measured are
equal to or better than 1.5e-11 per m.s^-2 for each spatial direction, which
shows significant improvement over previous studies. We have tested the very
low dependence on the position of the cavity support points, in order to
establish that our designs eliminate the need for fine tuning to achieve
extremely low vibration sensitivity. Relative frequency measurements show that
at least one of the stabilized lasers has a stability better than 5.6e-16 at 1
second, which is the best result obtained for this length of cavity.Comment: 8 pages 12 figure
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