Simulação numérica de banco veicular dianteiro : impacto traseiro

Trabalho de conclusão de curso (graduação)—Universidade de Brasília, Faculdade UnB Gama, Curso de Engenharia Automotiva, 2015.Este trabalho tem por intuito uma análise numérica para se determinar os níveis de tensão nos componentes de um banco veicular do motorista de um veículo de passeio, simulando uma colisão traseira de acordo com norma NBR 15283:2005. Como primeira etapa, um trabalho para uma modelagem CAD dos principais constituintes do banco veicular é realizada com o uso do software comercial CATIA®. Posteriormente, uma migração para um software CAE é efetuada com o intuito de que se faça uso do método dos elementos finitos(MEF) para que se determine os níveis de deslocamentos, tensões e deformações nos componentes do banco veicular, mais especificamente da zona de ancoragem entre o banco e o assoalho do veículo. Diante dos resultados de tensão nos componentes, uma serie de análises é realizada visando-se questões relacionadas a possíveis falhas do equipamento.No entanto, ressalta-se que vários estudos são realizados antes de obter um modelo CAE aplicável às apreciações almejadas. As análises em MEF foram efetuadas com uso do software comercial ANSYS® plataforma WORKBENCH, realizando-se para tanto simulações em modo quasi-estático e dinâmico, para que posteriormente, comparações entre os resultados obtidos em cada uma das análises são realizadas.The purpose of this research is to determine, through numerical analysis, stress levels in components of a vehicle driver’s seat in the case of a rear-end collision simulated in accordance with Brazilian regulations (NBR 15283:2005). Firstly, a CAD modeling of major components of the vehicle seat was made using the commercial software CATIA Subsequently, a migration to a CAE software was executed in order to apply the finite element method (FEM) to ascertain displacement, stress and strain levels in the vehicle seat components, specifically in the anchorage zone between the seat and the vehicle floor. Considering stress results in the components, a series of analyses was performed to verify issues related to possible equipment failures. Many studies were conducted before obtaining an applicable model. Several FEM analyses were performed using the commercial software ANSYS WORKBECH, running both quasi-static and dynamic simulations so the range of results could be compared

Estudo numérico do sistema de fixação de um banco veicular mediante carregamento estático e dinâmico

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Mecânica, 2018.O banco veicular é um componente de segurança passiva que desempenha um papel de suma importância no posicionamento e restrição dos passageiros, tanto em uso habitual quanto em situações fortuitas, como na ocorrência de colisões. A falha neste componente pode colocar em risco a condução do veículo e, consequentemente, a segurança dos seus ocupantes. Com o objetivo de regulamentá-los, as normas ECE 17, FMVSS 207 e NBR 15283 apresentam os requisitos dos elementos que os constitui, em especial daqueles que asseguram a ancoragem do banco ao assoalho do veículo: trilho, mecanismo de trava e parafusos de fixação, a fim de minimizar a possibilidade de falha por forças provenientes de uma colisão inesperada. A definição da norma ECE 17 permitiu estabelecer os procedimentos numéricos, realizados, prioritariamente, por meio de softwares comerciais em Elementos Finitos, onde uma curva de aceleração pré-determinada foi imposta ao banco veicular, simulando impactos frontais e traseiros. A aplicação de tal esforço externo permitiu realizar um conjunto de análises lineares, não-lineares, quasi-estáticas e dinâmicas no sistema de fixação do banco, o que possibilitou a obtenção de dados referentes aos deslocamentos, deformações e tensões que tais elementos estão submetidos. Diante de tais resultados, uma melhor compreensão do comportamento do sistema de fixação do banco foi alcançada, permitindo, por exemplo, uma definição de metodologia de verificação numérica de bancos veiculares. Não menos importante, diante dos dados de tensões e deformações, análises de previsão de vida à fadiga foram realizados, a fim de avaliar questões que tangem o projeto do banco averiguado.The safety of vehicle seats plays an important role in positioning and restraining passengers during usual travel and fortuitous events, such as collisions. ECE 17, FMVSS 207 and NBR 15283 regulates their elements' requirements, in particular those that ensure the anchorage of the seat to the vehicle’s floor (seat track, locking mechanism and fixing screws), aiming to minimize the likelihood of failure by forces of an unexpected collision. The definition of the ECE 17 allowed to establish the numerical procedures, in which a predetermined acceleration curve was imposed on the car seat, simulating frontal and rear impacts. The application of such external force led to the realization of a set of linear, non-linear, quasi-static and dynamic analyzes in fastening components, making it possible to obtain data regarding displacements, strains and stresses to which such element are submitted. In view of these results, a better understanding of the behavior of fastening components was achieved, defining a numerical methodology for car seats. Lastly, face to the stress and strain data, fatigue life prediction analyzes were performed in order to evaluate issues related to car seats. For the numerical procedures, commercial software in Finite Elements Method was applied

Assessing the crashworthiness of a vehicle seat for rear and frontal impacts

A vehicle seat represents an automotive passive system because it limits the damage caused to passengers in the events of an accident or a crash. This way, the present work intends to evaluate the safety of an anchorage mechanism of a frontal vehicle driver seat considering two hazardous situations rear and frontal impacts. Performing a nonlinear FE in static and transient analyses provide the stress distribution in the main components of the mechanism, such as the inner track, the lock device and the bolts using Ansys®. Regulation Nº 17 from Un/ECE regulates the acceleration levels predicted in a crash test and therefore applied in the simulation. In addition, departing from a crash of 5g a fatigue analysis is carried out. From this particular analysis, it becomes possible to evaluate the actual safety of the vehicle seat after a minor crash

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost