Enhancing radiation detection by drones through numerical fluid dynamics simulations

This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions

Design of miniaturized sensors for a mission-oriented uav application: A new pathway for early warning

In recent decades, the increasing threats associated with Chemical and Radiological (CR) agents prompted the development of new tools to detect and collect samples without putting in danger first responders inside contaminated areas. A particularly promising branch of these technological developments relates to the integration of different detectors and sampling systems with Unmanned Aerial Vehicles (UAV). The adoption of this equipment may bring significant benefits for both military and civilian implementations. For instance, instrumented UAVs could be used in support of specialist military teams such as Sampling and Identification of Biological, Chemical and Radiological Agents (SIBCRA) team, tasked to perform sampling in contaminated areas, detecting the presence of CR substances in field and then confirming, collecting and evaluating the effective threats. Furthermore, instrumented UAVs may find dual-use application in the civil world in support of emergency teams during industrial accidents and in the monitoring activities of critical infrastructures. Small size drones equipped with different instruments for detection and collection of samples may enable, indeed, several applications, becoming a tool versatile and easy to use in different fields, and even featuring equipment normally utilized in manual operation. The authors hereby present the design of miniaturized sensors for a mission-oriented UAV application and the preliminary results from an experimental campaign performed in 2020

Enhancing Radiation Detection by Drones through Numerical Fluid Dynamics Simulations

This study addresses the optimization of the location of a radioactive-particle sensor on a drone. Based on the analysis of the physical process and of the boundary conditions introduced in the model, computational fluid dynamics simulations were performed to analyze how the turbulence caused by drone propellers may influence the response of the sensors. Our initial focus was the detection of a small amount of radioactivity, such as that associated with a release of medical waste. Drones equipped with selective low-cost sensors could be quickly sent to dangerous areas that first responders might not have access to and be able to assess the level of danger in a few seconds, providing details about the source terms to Radiological-Nuclear (RN) advisors and decision-makers. Our ultimate application is the simulation of complex scenarios where fluid-dynamic instabilities are combined with elevated levels of radioactivity, as was the case during the Chernobyl and Fukushima nuclear power plant accidents. In similar circumstances, accurate mapping of the radioactive plume would provide invaluable input-data for the mathematical models that can predict the dispersion of radioactivity in time and space. This information could be used as input for predictive models and decision support systems (DSS) to get a full situational awareness. In particular, these models may be used either to guide the safe intervention of first responders or the later need to evacuate affected regions

Vídeo educativo: de olho no óleo

Alunos do MECSMA – Mestrado Profissional em Ensino em Ciências da Saúde e do Meio Ambiente tinham como atividade da disciplina de Prática Docente Supervisionada confeccionar uma oficina educativa para os alunos da educação básica. O grupo, denominado oficineiros, se ocupou de produzir um programa de TV que pudesse defender e motivar uma prática de educação ambiental para crianças e adolescentes. Depois de investigar os temas mais abordados na mídia, resolveu-se trabalhar com o descarte correto do óleo de cozinha. Com a apresentação de uma criança, pensou-se num roteiro cuja informação saísse da sala de aula e ganhasse o ambiente familiar e, posteriormente ainda desse ao aluno uma visão do que a ação correta desencadeia benefícios para a sociedade e para o Meio Ambiente. Essa visão é conseguida por meio da visita dos autores e da criança a uma cooperativa de Coletores de Óleo, situada em Volta Redonda-RJ, que reúne o material para produção de Biodiesel. O vídeo elaborado de forma lúdica foi apresentado durante uma Oficina numa escola pública e após a apresentação as questões fomentadas no filme foram discutidas com os alunos. Depois da atividade os alunos desenharam e relataram o que entenderam sobre o filme em relação à Educação Ambiental e Sustentabilidade

Factors influencing terrestriality in primates of the Americas and Madagascar

Among mammals, the order Primates is exceptional in having a high taxonomic richness in which the taxa are arboreal, semiterrestrial, or terrestrial. Although habitual terrestriality is pervasive among the apes and African and Asian monkeys (catarrhines), it is largely absent among monkeys of the Americas (platyrrhines), as well as galagos, lemurs, and lorises (strepsirrhines), which are mostly arboreal. Numerous ecological drivers and species-specific factors are suggested to set the conditions for an evolutionary shift from arboreality to terrestriality, and current environmental conditions may provide analogous scenarios to those transitional periods. Therefore, we investigated predominantly arboreal, diurnal primate genera from the Americas and Madagascar that lack fully terrestrial taxa, to determine whether ecological drivers (habitat canopy cover, predation risk, maximum temperature, precipitation, primate species richness, human population density, and distance to roads) or species-specific traits (bodymass, group size, and degree of frugivory) associate with increased terrestriality. We collated 150,961 observation hours across 2,227 months from 47 species at 20 sites in Madagascar and 48 sites in the Americas. Multiple factors were associated with ground use in these otherwise arboreal species, including increased temperature, a decrease in canopy cover, a dietary shift away from frugivory, and larger group size. These factors mostly explain intraspecific differences in terrestriality. As humanity modifies habitats and causes climate change, our results suggest that species already inhabiting hot, sparsely canopied sites, and exhibiting more generalized diets, are more likely to shift toward greater ground use

Factors influencing terrestriality in primates of the Americas and Madagascar

Among mammals, the order Primates is exceptional in having a high taxonomic richness in which the taxa are arboreal, semiterrestrial, or terrestrial. Although habitual terrestriality is pervasive among the apes and African and Asian monkeys (catarrhines), it is largely absent among monkeys of the Americas (platyrrhines), as well as galagos, lemurs, and lorises (strepsirrhines), which are mostly arboreal. Numerous ecological drivers and species-specific factors are suggested to set the conditions for an evolutionary shift from arboreality to terrestriality, and current environmental conditions may provide analogous scenarios to those transitional periods. Therefore, we investigated predominantly arboreal, diurnal primate genera from the Americas and Madagascar that lack fully terrestrial taxa, to determine whether ecological drivers (habitat canopy cover, predation risk, maximum temperature, precipitation, primate species richness, human population density, and distance to roads) or species-specific traits (body mass, group size, and degree of frugivory) associate with increased terrestriality. We collated 150,961 observation hours across 2,227 months from 47 species at 20 sites in Madagascar and 48 sites in the Americas. Multiple factors were associated with ground use in these otherwise arboreal species, including increased temperature, a decrease in canopy cover, a dietary shift away from frugivory, and larger group size. These factors mostly explain intraspecific differences in terrestriality. As humanity modifies habitats and causes climate change, our results suggest that species already inhabiting hot, sparsely canopied sites, and exhibiting more generalized diets, are more likely to shift toward greater ground use

Application of miniaturized sensors to unmanned aerial systems, a new pathway for the survey of polluted areas: Preliminary results

With the aim to have risk mitigation for people and first responders, active remote sensing stando detection is a fruitful technology, both in case of accidental (natural or incidental) or intentional dispersion in the environment of volatile chemical substances. Nowadays, several laser-based methodologies could be put in place to perform extensive areal monitoring. The present study regards the proposal for a new system architecture derived from the integration of a low-cost laser-based network of detectors for pollutants interfaced with a more sophisticated layout mounted on an unmanned aerial vehicle (UAV) able to identify the nature and the amount of a release. With this system set up, the drone will be activated by the alarm triggered by the laser-based network when anomalies are detected. The area will be explored by the drone with a more accurate set of sensors for identification to validate the detection of the network of Lidar systems and to sample the substance in the focus zone for subsequent analysis. In this work, methodologies and requirements for the stando detection and the identification features chosen for this integrated system are described. The work aims at the definition of a new approach to the problem through the integration of dierent technologies and tools in the operative field experiments. Some preliminary results in support of the suitability of the integration hypothesis proposed are presented. This study gives rise to an integrated system to be furtherly tested in a real environment