Alcuni studi sul comportamento non lineare dei diaframmi di edifici a telaio esistenti in CA

Si presentano i primi risultati di un progetto di ricerca che intende analizzare l’influenza del comportamento non-lineare dei diaframmi di piano sulla risposta globale di edifici soggetti ad azioni sismiche. In particolare nel presente lavoro sarà illustrata la modellazione dei diaframmi eseguita, per le analisi pushover non lineari dell’Istituto De Gasperi-Battaglia situato a Norcia, dall’unità di ricerca di Parma all’interno del gruppo WP2 del Progetto di Ricerca Reluis 2017. In particolare è stato studiato il comportamento non lineare del modello a telaio nell’ipotesi di impalcato rigido e nell’ipotesi di impalcato deformabile. Nella prima ipotesi il diaframma è stato implementato nel codice di calcolo Abaqus mediante elementi truss, mentre nella seconda il comportamento non lineare della soletta è stato valutato calcolando la matrice di rigidezza in corrispondenza dei punti di integrazione degli elementi shell multi-strato con il modello fessurativo PARC_CL2.0 [Belletti et al. 2016]

Using Geographic Information Systems (GIS) for Targeted National Recruitment of Community-Dwelling Caregivers Managing Dementia-Related Behavioral and Psychological Symptoms: A Recruitment Approach for a Randomized Clinical Trial.

Over 16 million caregivers of people living with dementia require support in a range of issues, including self-care, disease education, and guidance for how to manage behavioral and psychological symptoms of dementia (BPSD). Non-pharmacological interventions are needed to address these areas, and online applications have been shown to be safe and effective. To ensure the efficacy of such interventions, racially, ethnically, geographically, and socioeconomically diverse participants must be recruited to increase the generalizability of study outcomes. This protocol paper describes a recruitment plan using Geographic Information Systems (GIS) to reach a representative sample of caregivers across the United States for a national Phase III clinical study. Using publicly available census data from the American Community Survey (ACS), combined with location data for local aging resources such as Area Agencies on Aging (AAA), recruitment will be derived from data analysis conducted in ESRI ArcGIS v10.7.1. Datasets including age, gender, income, and education will be assessed nationally at the county and census tract spatial scale in a nine-step process to develop recruitment priority areas containing high concentrations of eligible participants living in the community. Overall, the current protocol will demonstrate the value of GIS in tailoring targeted outreach strategies to recruit community-dwelling populations through local resource institutions. This novel approach may have far-reaching implications in future recruitment initiatives and help to secure racially/ethnically diverse samples

Influence of nonlinear modeling on capacity assessment of RC framed structures

Many existing buildings in the world present serious seismic deficiencies and need to be retrofitted. However, the basis for an effective seismic retrofit intervention is a reliable assessment of the structure. To this end, nowadays structural engineers can simulate the response of structures subjected to earthquake excitation by nonlinear numerical models. These models consider explicitly the mechanical nonlinearities of the structural members, identify the parts of the structure where yielding takes place, quantify the demand of plastic deformation and force. Furthermore, a number of models is available to carry out the nonlinear analysis of structures. All these models are able to provide a detailed representation of the seismic response of the structure. However, they are controlled by many parameters that need to be properly set to obtain an accurate prediction of the response. Based on the framework depicted above, the target of the Reinforced Concrete Work Package 2 of the ReLUIS 2018 project was to examine and compare different nonlinear modelling techniques used to evaluate the response of structures by pushover analysis. To this end, a case study building is analysed by the eight research units involved in the project by different nonlinear numerical models. The building presents very different lateral stiffness and strength in the longitudinal and transverse directions. Each numerical model is run two times including and not including the masonry infills. Furthermore, pushover analysis is run two times with forces in the longitudinal and transverse directions. Finally, the results are compared to illustrate advantages and limitations of each nonlinear modelling techniqu