Purpose: The present study deals with the numerical modeling of the low-velocity impact damage of laminated composites which have increasingly important applications in aerospace primary structures. Such damage, generated by various sources during ground handling, substantially reduces the mechanical residual performance and the safe-service life. The purpose of this paper is to present and validate a computationally efficient approach in order to explore the effect of critical parameters on the impact damage characteristics.Design/methodology/approach: Numerical modeling is considered as one of the most efficient tool as compared to the expensive and time-consuming experimental testing. In this paper, a finite element model based on explicit dynamics formulations is adopted. Hashin criterion is applied to predict the intralaminar damage initiation and evolution. The numerical analysis is performed using the ABAQUS® programme. Findings: The employed modeling approach is validated using corresponding numerical data found in the literature and the presented results show a reasonable correlation to the available literature data. It is demonstrated that the current model can be used to capture the force-time response as well as damage parameter maps showing the intralaminar damage evolution for different impact cases with respect to the physical boundary conditions and a range of impact energies. Originality/value: Low-velocity impact damage of laminated composites is still not well understood due to the complexity and non-linearity of the damage zone. The presented model is used to predict the force-time response which is considered as one of the most important parameters influencing the structural integrity. Furthermore, it is used for capturing the damage shape evolution, exhibiting a high degree of capability as a damage assessment computational tool.
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Laminated composites have important applications in modern aeronautical structures due to their extraordinary mechanical and environmental behaviour. Nevertheless, aircraft composite structures are highly vulnerable to impact damage, either by low-velocity sources during maintenance or high-velocity sources during in-flight events. Even barely visible impact damage induced by low-velocity loading, substantially reduces the residual mechanical performance and the safe-service life of the composites structures. Despite the extensive research already carried out, impact damage of laminated composite structures is still not well understood and it is an area of on-going research. Numerical modelling is considered as the most efficient tool as compared to the expensive and time-consuming experimental testing. In this paper, a finite element model based on explicit dynamics formulations is adopted. Hashin criterion is applied to predict the intra-laminar damage initiation and evolution. The numerical analysis is performed using the ABAQUS ® programme. The employed modelling approach is validated using numerical results found in the literature and the presented results show an acceptable correlation to the available literature data. It is demonstrated that the presented model is able to capture force-time response as well as damage evolution map for a range of impact energies.
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From the article: Abstract Sub-chronic toxicity studies of 163 non-genotoxic chemicals were evaluated in order to predict the tumour outcome of 24-month rat carcinogenicity studies obtained from the EFSA and ToxRef databases. Hundred eleven of the 148 chemicals that did not induce putative preneoplastic lesions in the sub-chronic study also did not induce tumours in the carcinogenicity study (True Negatives). Cellular hypertrophy appeared to be an unreliable predictor of carcinogenicity. The negative predictivity, the measure of the compounds evaluated that did not show any putative preneoplastic lesion in de sub-chronic studies and were negative in the carcinogenicity studies, was 75%, whereas the sensitivity, a measure of the sub-chronic study to predict a positive carcinogenicity outcome was only 5%. The specificity, the accuracy of the sub-chronic study to correctly identify non-carcinogens was 90%. When the chemicals which induced tumours generally considered not relevant for humans (33 out of 37 False Negatives) are classified as True Negatives, the negative predictivity amounts to 97%. Overall, the results of this retrospective study support the concept that chemicals showing no histopathological risk factors for neoplasia in a sub-chronic study in rats may be considered non-carcinogenic and do not require further testing in a carcinogenicity study.
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The postdoc candidate, Sondos Saad, will strengthen connections between research groups Asset Management(AM), Data Science(DS) and Civil Engineering bachelor programme(CE) of HZ. The proposed research aims at deepening the knowledge about the complex multidisciplinary performance deterioration prediction of turbomachinery to optimize cleaning costs, decrease failure risk and promote the efficient use of water &energy resources. It targets the key challenges faced by industries, oil &gas refineries, utility companies in the adoption of circular maintenance. The study of AM is already part of CE curriculum, but the ambition of this postdoc is that also AM principles are applied and visible. Therefore, from the first year of the programme, the postdoc will develop an AM material science line and will facilitate applied research experiences for students, in collaboration with engineering companies, operation &maintenance contractors and governmental bodies. Consequently, a new generation of efficient sustainability sensitive civil engineers could be trained, as the labour market requires. The subject is broad and relevant for the future of our built environment being more sustainable with less CO2 footprint, with possible connections with other fields of study, such as Engineering, Economics &Chemistry. The project is also strongly contributing to the goals of the National Science Agenda(NWA), in themes of “Circulaire economie en grondstoffenefficiëntie”,”Meten en detecteren: altijd, alles en overall” &”Smart Industry”. The final products will be a framework for data-driven AM to determine and quantify key parameters of degradation in performance for predictive AM strategies, for the application as a diagnostic decision-support toolbox for optimizing cleaning &maintenance; a portfolio of applications &examples; and a new continuous learning line about AM within CE curriculum. The postdoc will be mentored and supervised by the Lector of AM research group and by the study programme coordinator(SPC). The personnel policy and job function series of HZ facilitates the development opportunity.
