Estudo do comportamento termomecânico do aço inoxidável AISI 430 por meio da termografia por infravermelho

Este trabalho tem como objetivo investigar o aumento da temperatura em chapas de aço inoxidável AISI 430 durante o ensaio de tração para as seguintes taxas de deformação: 0,001; 0,01 e 0,1 s-1. Para registrar a evolução da temperatura até a fratura dos corpos de prova, foi utilizada uma termocâmera por infravermelho. Os resultados obtidos pela técnica da termografia por infravermelho mostraram um aumento gradual e uniforme da temperatura durante o encruamento do material e uma elevação drástica da temperatura nas regiões de estricção e fratura dos corpos de prova. Para a taxa de deformação de 0,1 s-1 foi observado o maior gradiente de temperatura entre a estricção localizada e a fratura (110 ºC).  Palavras-chave: Aço inoxidável AISI 430, Termografia por infravermelho, Taxas de deformação, Temperatura

Modelagem e análise numéricas da operação de roleteamento do aço abnt 4140 = Modeling and numerical analysis of roller burnishing of aisi 4140 steel

Metallic components for engineering applications are often employed under the action of thermal and mechanical loads, which tend to reduce their lifespan. Mechanical surface treatments appear as an alternative capable of extending the service life of these materials. These processes act by plastically deforming the surface, increasing its surface hardness and inducing compressive residual stresses. The combination of these factors leads to an increase of the part lifespan because it diminishes the nucleation and propagation of cracks, which are responsible for material failure by fracture. Although surface treatment processes such as shot peening and laser shock peening are widely used to induce compressive stresses, roller burnishing not only induces compressive stress and increases surface hardness, but also promotes the reduction of surface roughness. In this work, two-dimensional numerical simulation using the Finite Element Method (FEM) method for roller burnishing the hardened ABNT 4140 (40 HRC) steel was performed, considering the tool a rigid element, while the part was assumed as elasto-plastic. Burnishing force and feed rate were selected as input parameters which influence on roughness and residual stress induction was investigated. Moreover, unlike other two-dimensional numerical models, the initial roughness of the part was introduced in order to assess its influence on the process. In addition to that, the numerical simulation occurs in the interval from one peak to the other, defined by the feed mark of the previous turning operation (0.2 mm). The HertzWin software was used to define the feed rate for each condition, which was based on the half contact width (b) obtained for each force separately. The numerical results suggest the reduction of roughness and the increase of compressive residual when the rolling force is increased and the feed rate is reduced. © 2020, Universidade Federal do Rio de Janeiro. All rights reserved.Componentes metálicos utilizados em diversas aplicações sofrem frequentemente a ação de cargas térmicas e mecânicas que reduzem o seu tempo de vida. Os tratamentos mecânicos de superfície são capazes de prolongar o tempo em serviço desses materiais. Esses processos atuam deformando plasticamente a superfície, promovendo o aumento da sua dureza e a indução de tensões residuais de compressão. A combinação desses fatores aumenta a vida da peça pois reduz a taxa de nucleação e propagação de trincas responsáveis por levar o material à falha por fratura. Apesar de processos de tratamento de superfície como o jateamento de granalha e o laser shock peening (LSP) serem utilizados para induzir tensões compressivas, o roleteamento não só induz tensão de compressão e aumenta a dureza superficial, como também promove a redução da rugosidade. Neste trabalho, uma simulação numérica bidimensional utilizando o método dos elementos finitos (Finite Element Method -FEM) foi aplicada ao roleteamento do aço ABNT 4140 endurecido (40 HRC), definindo a ferramenta como um elemento rígido, enquanto que o material da peça apresentou um comportamento elasto-plástico. A força e o avanço de roleteamento foram escolhidos como parâmetros de entrada cuja influência sobre a rugosidade e as tensões residuais foi analisada. Diferentemente de outros modelos numéricos bidimensionais, a rugosidade inicial da peça foi introduzida a fim de verificar a sua influência no processo. As simulações numéricas ocorreram entre a distância de dois picos de rugosidade, definida pela marca de avanço do torneamento prévio (0,2 mm). O software HertzWin foi utilizado para definir o avanço para cada condição, sendo este baseado na largura da linha de contato obtido para cada força separadamente. Os resultados numéricos sugerem a redução da rugosidade e o aumento da tensão residual de compressão a partir do aumento da força e da redução do avanço de roleteamento

Modelagem e análise numéricas da operação de roleteamento do aço ABNT 4140

Componentes metálicos utilizados em diversas aplicações sofrem frequentemente a ação de cargas térmicas e mecânicas que reduzem o seu tempo de vida. Os tratamentos mecânicos de superfície são capazes de prolongar o tempo em serviço desses materiais. Esses processos atuam deformando plasticamente a superfície, promovendo o aumento da sua dureza e a indução de tensões residuais de compressão. A combinação desses fatores aumenta a vida da peça pois reduz a taxa de nucleação e propagação de trincas responsáveis por levar o material à falha por fratura. Apesar de processos de tratamento de superfície como o jateamento de granalha e o laser shock peening (LSP) serem utilizados para induzir tensões compressivas, o roleteamento não só induz tensão de compressão e aumenta a dureza superficial, como também promove a redução da rugosidade. Neste trabalho, uma simulação numérica bidimensional utilizando o método dos elementos finitos (Finite Element Method -FEM) foi aplicada ao roleteamento do aço ABNT 4140 endurecido (40 HRC), definindo a ferramenta como um elemento rígido, enquanto que o material da peça apresentou um comportamento elastoplástico. A força e o avanço de roleteamento foram escolhidos como parâmetros de entrada cuja influência sobre a rugosidade e as tensões residuais foi analisada. Diferentemente de outros modelos numéricos bidimensionais, a rugosidade inicial da peça foi introduzida a fim de verificar a sua influência no processo. As simulações numéricas ocorreram entre a distância de dois picos de rugosidade, definida pela marca de avanço do torneamento prévio (0,2 mm). O software HertzWin foi utilizado para definir o avanço para cada condição, sendo este baseado na largura da linha de contato obtido para cada força separadamente. Os resultados numéricos sugerem a redução da rugosidade e o aumento da tensão residual de compressão a partir do aumento da força e da redução do avanço de roleteamento.  Palavras-chave: Tratamento mecânico de superfície; roleteamento; rugosidade; elementos finitos; aço ABNT 4140

POTENTIAL EFFECTS OF WHOLE-BODY VIBRATION EXERCISES ON BLOOD FLOW KINETICS OF DIFFERENT POPULATIONS: A SYSTEMATIC REVIEW WITH A SUITABLE APPROACH

Background: The ability to control skin blood flow decreases with advancing age and some clinical disorders, as in diabetes and in rheumatologic diseases. Feasible clinical strategies such as whole-body vibration exercise (WBVE) are being used without a clear understanding of its effects. The aim of the present study is to review the effects of the WBVE on blood flow kinetics and its feasibility in different populations. Material and Methods: The level of evidence (LE) of selected papers in PubMed and/or PEDRo databases was determined. We selected randomized, controlled trials in English to be evaluated. Results: Six studies had LE II, one had LE III-2 and one III-3 according to the NHMRC. A great variability among the protocols was observed but also in the assessment devices; therefore, more research about this topic is warranted. Conclusion: Despite the limitations, it is can be concluded that the use of WBVE has proven to be a safe and useful strategy to improve blood flow. However, more studies with greater methodological quality are needed to clearly define the more suitable protocols

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

Assessment of risk scores to predict mortality of COVID-19 patients admitted to the intensive care unit

ObjectivesTo assess the ABC2-SPH score in predicting COVID-19 in-hospital mortality, during intensive care unit (ICU) admission, and to compare its performance with other scores (SOFA, SAPS-3, NEWS2, 4C Mortality Score, SOARS, CURB-65, modified CHA2DS2-VASc, and a novel severity score).Materials and methodsConsecutive patients (≥ 18 years) with laboratory-confirmed COVID-19 admitted to ICUs of 25 hospitals, located in 17 Brazilian cities, from October 2020 to March 2022, were included. Overall performance of the scores was evaluated using the Brier score. ABC2-SPH was used as the reference score, and comparisons between ABC2-SPH and the other scores were performed by using the Bonferroni method of correction. The primary outcome was in-hospital mortality.ResultsABC2-SPH had an area under the curve of 0.716 (95% CI 0.693–0.738), significantly higher than CURB-65, SOFA, NEWS2, SOARS, and modified CHA2DS2-VASc scores. There was no statistically significant difference between ABC2-SPH and SAPS-3, 4C Mortality Score, and the novel severity score.ConclusionABC2-SPH was superior to other risk scores, but it still did not demonstrate an excellent predictive ability for mortality in critically ill COVID-19 patients. Our results indicate the need to develop a new score, for this subset of patients

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