34 research outputs found
Swarm of slender pusher and puller swimmers at finite Reynolds numbers
No full textThe study of the flow field resulting from suspensions of swimmers at moderate Reynolds numbers, along with hydrodynamic interactions, has received little attention until now despite being of great interest to researchers in the fields of marine ecology, biology, and engineering. By means of direct numerical simulations, employing a state-of-the-art fully resolved immersed boundary method, the suspensions of inertial slender pusher and puller swimmers are investigated in dilute volume fractions and swimming Reynolds numbers ranging from 1 to 50 with the objective to identify the existence of correlated flow motions and scales when inertia plays a crucial role. The properties of the flow field resulting from the collective motion of the swimmers, as well as the characteristics of their orientation along with their temporal correlation, have been analyzed. Results show nontrivial flow motions as the Reynolds number changes along with a complex swimmer dynamics
Self-propelled slender objects can measure flow signals net of self-motion
No full textThe perception of hydrodynamic signals by self-propelled objects is a problem of paramount importance ranging from the field of bio-medical engineering to bio-inspired intelligent navigation. By means of a state-of-the-art fully resolved immersed boundary method, we propose different models for fully coupled self-propelled objects (swimmers, in short), behaving either as “pusher” or as “puller.” The proposed models have been tested against known analytical results in the limit of Stokes flow, finding excellent agreement. Once tested, our more realistic model has been exploited in a chaotic flow field up to a flow Reynolds number of 10, a swimming number ranging between zero (i.e., the swimmer is freely moving under the action of the underlying flow in the absence of propulsion) and one (i.e., the swimmer has a relative velocity with respect to the underlying flow velocity of the same order of magnitude as the underlying flow), and different swimmer inertia measured in terms of a suitable definition of the swimmer Stokes number. Our results show the following: (i) pusher and puller reach different swimming velocities for the same, given, propulsive force: while for pusher swimmers, an effective slender body theory captures the relationship between swimming velocity and propulsive force, this is not for puller swimmers. (ii) While swimming, pusher and puller swimmers possess a different distribution of the vorticity within the wake. (iii) For a wide range of flow/swimmer Reynolds numbers, both pusher and puller swimmers are able to sense hydrodynamic signals with good accuracy
Accurate and efficient AI-assisted paradigm for adding granularity to ERA5 precipitation reanalysis
No full textAbstract Scientific inquiry has long relied on deterministic algorithms for systematic problem-solving and predictability. However, the rise of artificial intelligence (AI) has revolutionized data analysis, allowing us to uncover complex patterns in large datasets. In this study, we combine these two approaches by using AI to improve the reconstruction of past precipitation events, which is crucial for understanding climate change. Our objective is to leverage AI to map large-scale atmospheric proxies from the ERA5 climate reanalysis and multi-satellite historical precipitation data from the NASA-IMERG GPM constellation to observed precipitation, enhancing the accuracy and the resolution of climate reanalysis. Accurate climate reanalyses are essential, as they provide the most realistic representations of past atmospheric conditions, serving as benchmarks against which climate models are validated. Our AI-enhanced method offers a more accurate and computationally efficient solution compared to deterministic high-resolution precipitation downscaling methods. Additionally, it shows the capability to generalize predictions to new, previously unobserved locations, making it applicable across various regions. By integrating AI with traditional reanalysis techniques, we open up new opportunities for climate science and geosciences, with the potential to improve the accuracy and reliability of climate data, contributing to a better understanding of climate dynamics
The assembly of freely moving rigid fibres measures the flow velocity gradient tensor
No full textThe motion of an assembly of rigid fibres is investigated for different classes of closed streamline flows, steady or time dependent, two-dimensional or three-dimensional. In our study, the dynamics of the fibre assembly is fully coupled to the flow field by means of a state of the art immersed boundary method. We show that, for sufficiently small Stokes times of the assembly, the whole flow gradient tensor can be accurately reconstructed by simply tracking the fibre assembly and measuring suitable fibre velocity differences evaluated at the fibre ends. Our results strongly suggest the possibility of using rigid fibres (or assemblies of them) to perform multi-point flow measures, either in laboratory or in field: Future experiments are therefore mandatory to inquire the feasibility of a new 'fibre tracking velocimetry' technique
Calibrating the CAMS European multi-model air quality forecasts for regional air pollution monitoring
No full textThe CAMS air quality multi-model forecasts have been assessed and calibrated
for PM10, PM2.5, O3, NO2, and CO against observations collected by the Regional
Monitoring Network of the Liguria region (northwestern Italy) in the years 2019
and 2020. The calibration strategy used in the present work has its roots in
the well-established Ensemble Model Output Statistics (EMOS) through which a
raw ensemble forecast can be accurately transformed into a predictive
probability density function, with a simultaneous correction of biases and
dispersion errors. The strategy also provides a calibrated forecast of model
uncertainties. As a result of our analysis, the key role of pollutant real-time
observations to be ingested in the calibration strategy clearly emerge
especially in the shorter look-ahead forecast hours. Our dynamic calibration
strategy turns out to be superior with respect to its analogous where real-time
data are not taken into account. The best calibration strategy we have
identified makes the CAMS multi-model forecast system more reliable than other
raw air quality models running at higher spatial resolution which exploit more
detailed information from inventory emission. We expect positive impacts of our
research for identifying and set up reliable and economic air pollution early
warning systems
Fluid dynamics of COVID-19 airborne infection suggests urgent data for a scientific design of social distancing
No full textThe COVID-19 pandemic is largely caused by airborne transmission, a phenomenon that rapidly gained the attention of the scientific community. Social distancing is of paramount importance to limit the spread of the disease, but to design social distancing rules on a scientific basis the process of dispersal of virus-containing respiratory droplets must be understood. Here, we demonstrate that available knowledge is largely inadequate to make predictions on the reach of infectious droplets emitted during a cough and on their infectious potential. We follow the position and evaporation of thousands of respiratory droplets by massive state-of-the-art numerical simulations of the airflow caused by a typical cough. We find that different initial distributions of droplet size taken from literature and different ambient relative humidity lead to opposite conclusions: (1) most versus none of the viral content settles in the first 1–2 m; (2) viruses are carried entirely on dry nuclei versus on liquid droplets; (3) small droplets travel less than 2.5m versus more than 7.5m. We point to two key issues that need to be addressed urgently in order to provide a scientific foundation to social distancing rules: (I1) a careful characterisation of the initial distribution of droplet sizes; (I2) the infectious potential of viruses carried on dry nuclei versus liquid droplets
Transport and evaporation of virus-containing droplets exhaled by men and women in typical cough events
No full textThe spreading of the virus-containing droplets exhaled during respiratory events, e.g., cough, is an issue of paramount importance for the prevention of many infections such as COVID-19. According to the scientific literature, remarkable differences can be ascribed to several parameters that govern such complex and multiphysical problem. Among these, a particular influence appears associated with the different airflows typical of male and female subjects. Focusing on a typical cough event, we investigate this aspect by means of highly-resolved direct numerical simulations of the turbulent airflow in combination with a comprehensive Lagrangian particle tracking model for the droplet motion and evaporation. We observe and quantify major differences between the case of male and female subjects, both in terms of the droplet final reach and evaporation time. Our results can be associated with the different characteristics in the released airflow and thus confirm the influence of the subject gender (or other physical properties providing different exhalation profiles) on both short-range and long-range airborne transmissio
Turbulence role in the fate of virus-containing droplets in violent expiratory events
No full textViolent expiratory events, such as coughing and sneezing, are highly nontrivial examples of a two-phase mixture of liquid droplets dispersed into an unsteady turbulent airflow. Understanding the physical mechanisms determining the dispersion and evaporation process of respiratory droplets has recently become a priority given the global emergency caused by the SARS-CoV-2 infection. By means of high-resolution direct numerical simulations (DNSs) of the expiratory airflow and a comprehensive Lagrangian model for the droplet dynamics, we identify the key role of turbulence in the fate of exhaled droplets. Due to the considerable spread in the initial droplet size, we show that the droplet evaporation time is controlled by the combined effect of turbulence and droplet inertia. This mechanism is clearly highlighted when comparing the DNS results with those obtained using coarse-grained descriptions that are employed in the majority of the current state-of-the-art investigations, resulting in errors up to 100% when the turbulent fluctuations are filtered or completely averaged out
Role of barriers in the airborne spread of virus-containing droplets: A study based on high-resolution direct numerical simulations
No full textState-of-the-art direct numerical simulations are exploited to study the role of barriers on the airborne spread of virus-containing droplets. Our study is motivated by recent findings pointing to the key role of turbulence in dictating the final fate of virus-containing droplets in violent human exhalations. Here, all active scales of motion have been explicitly taken into account, including their interplay with the droplet evaporation process occurring once droplets are emitted in a drier ambient air, and accounting for the time-varying droplet inertia due to the water loss via evaporation. We show that barriers commonly used to mitigate the airborne spread of the virus cause nontrivial dynamical effects influencing the final reach of the virus-containing droplets, not always being beneficial to this aim. These conclusions do depend on the relative humidity of the ambient condition, and in particular whether the ambient humidity is above or below the so-called efflorescence relative humidity. Our findings provide a physically based answer to the question on how effective barriers are to protect people from airborne virus transmission in indoor environments
