Fokker-Planck Asymptotics for Traffic Flow Models

Starting from microscopic interaction rules we derive kinetic models of Fokker--Planck type for vehicular traffic flow. The derivation is based on taking a suitable asymptotic limit of the corresponding Boltzmann model. As particular cases, the derived models comprise existing models. New Fokker--Planck models are also given and their differences to existing models are highlighted. Finally, we report on numerical experiments

Particle based gPC methods for mean-field models of swarming with uncertainty

In this work we focus on the construction of numerical schemes for the approximation of stochastic mean--field equations which preserve the nonnegativity of the solution. The method here developed makes use of a mean-field Monte Carlo method in the physical variables combined with a generalized Polynomial Chaos (gPC) expansion in the random space. In contrast to a direct application of stochastic-Galerkin methods, which are highly accurate but lead to the loss of positivity, the proposed schemes are capable to achieve high accuracy in the random space without loosing nonnegativity of the solution. Several applications of the schemes to mean-field models of collective behavior are reported.Comment: Communications in Computational Physics, to appea

Stiffnites. Part I

I identify the early phases of a particular kind of gravity-driven submarine sediment flow, that I have named immature stiffnite. The mature flow dynamics is originally presented in an accompanying report, referred to here as Pareschi [2011]. An immature stiffnite is constituted by a liquefied flowing mixture of muddy to sandy particles (sea floor ooze) in contact or in close proximity to each other, with inter-granular pores saturated in water. Sliding hard grains, including microshells, fragment during its motion. To infer the dynamics of an immature stiffnite, I consider deposits from the literature. In the literature, however, those deposits have not been well defined and they have often been confused with turbidites. Turbidites are water currents with suspended fine sediments that progressively settle-out down an incline. Stiffnites are triggered by events that create overpressure in intergrain pore water of the sea floor over wide areas. A peak of magnetic susceptibility can occur at the base of an immature stiffnite deposit

A comprehensive database on synoptic and local circulation over Sicily for mesoscale applications

The aim of this work is to present a database of information available on the island of Sicily (Italy) to be used for the evaluation and/or the calibration of the numerical mesoscale meteorological models. The database relates to land type and land cover of the island as well as to meteorological fields collected at various locations over a time span of various years. The analysis of the database provides information on spatiotemporal variability of characteristic meteorological patterns on the mesoscale range over the island. Specific wind and temperature values characteristic of the regional circulation on the island are presented in the database and analyzed in this paper. The available data have different sources (fixed monitoring stations or measuring campaigns, remote-sensing instruments), and refer to vertical soundings or to measurements at fixed heights. Air temperature, wind speed and wind direction are among the meteorological parameters taken into account. The temporal frequency of the data ranges from 10 minutes to 24 hours

Control with uncertain data of socially structured compartmental epidemic models

The adoption of containment measures to reduce the amplitude of the epidemic peak is a key aspect in tackling the rapid spread of an epidemic. Classical compartmental models must be modified and studied to correctly describe the effects of forced external actions to reduce the impact of the disease. In addition, data are often incomplete and heterogeneous, so a high degree of uncertainty must naturally be incorporated into the models. In this work we address both these aspects, through an optimal control formulation of the epidemiological model in presence of uncertain data. After the introduction of the optimal control problem, we formulate an instantaneous approximation of the control that allows us to derive new feedback controlled compartmental models capable of describing the epidemic peak reduction. The need for long-term interventions shows that alternative actions based on the social structure of the system can be as effective as the more expensive global strategy. The importance of the timing and intensity of interventions is particularly relevant in the case of uncertain parameters on the actual number of infected people. Simulations related to data from the recent COVID-19 outbreak in Italy are presented and discussed

Reply to the Comment on “Lost tsunami by M.T.Pareschi et al.”, by Luigi Vigliotti

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Model Predictive Anti-Surge Control of Centrifugal Compressors with Variable-Speed Drives

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Best-fit results from application of a thermo-rheological model for channelized lava flow to high spatial resolution morphological data

The FLOWGO thermo-rheological model links heat loss, core cooling, crystallization, rheology and flow dynamics for lava flowing in a channel. We fit this model to laser altimeter (LIDAR) derived channel width data, as well as effusion rate and flow velocity measurements, to produce a best-fit prediction of thermal and rheological conditions for lava flowing in a ~1.6 km long channel active on Mt. Etna (Italy) on 16th September 2004. Using, as a starting condition for the model, the mean channel width over the first 100 m (6 m) and a depth of 1 m we obtain an initial velocity and instantaneous effusion rate of 0.3–0.6 m/s and ~3 m3/s, respectively. This compares with field- and LIDAR-derived values of 0.4 m/s and 1–4 m3/s. The best fit between model-output and LIDAR-measured channel widths comes from a hybrid run in which the proximal section of the channel is characterised by poorly insulated flow and the medial-distal section by well-insulated flow. This best-fit model implies that flow conditions evolve down-channel, where hot crusts on a free flowing channel maximise heat losses across the proximal section, whereas thick, stable, mature crusts of ′a′a clinker reduce heat losses across the medial-distal section. This results in core cooling per unit distance that decreases from ~0.02–0.015°C m−1 across the proximal section, to ~0.005°C m−1 across the medial-distal section. This produces an increase in core viscosity from ~3800 Pa s at the vent to ~8000 Pa s across the distal section

Resonate and fire dynamics in Complex Oscillation Based Test of analog filters

Recently, proposals have been made for enhancing the Oscillation Based Test (OBT) methodology by using non-plain oscillation regimes, leading to so called Complex Oscillation Based Test (COBT). Here we focus on a recently illustrated strategy for the testing of analog 2nd order filters, showing that the COBT dynamics is quite similar to that expressed by Resonate & Fire (R+F) neuron models. In this interpretation, the testing approach can be related to firing-rate measures. A brief description is given of the mathematical models necessary to achieve a precise characterization of firing times, showing how it can be used for testing purposes. A practical example with simulation data is also provided. © 2011 IEEE

Constraint-based protocols for distributed problem solving

AbstractDistributed Problem Solving (DPS) approaches decompose problems into subproblems to be solved by interacting, cooperative software agents. Thus, DPS is suitable for solving problems characterized by many interdependencies among subproblems in the context of parallel and distributed architectures. Concurrent Constraint Programming (CCP) provides a powerful execution framework for DPS where constraints define local problem solving and the exchange of information among agents declaratively. To optimize DPS, the protocol for constraint communication must be tuned to the specific kind of DPS problem and the characteristics of the underlying system architecture. In this paper, we provide a formal framework for modeling different problems and we show how the framework applies to simple yet generalizable examples