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Purpose This study aims to develop a new correlation method for prediction of in-flight wings deflections by integration of the experimental ground tests with computational fluid dynamics (CFD) analysis. Design/methodology/approach The ground test results are implemented in the curve fitting process to determine deflections at 66 specific points (SPs) on the front and rear wing torque box. By using the obtained deflections and the corresponding applied loads, an experimental deflection equation (EDE) for each point is established through the Castigliano’s theorem. The CFD aerodynamic loads of typical aircraft, which have been obtained earlier by the authors, are once again used in the current research. The total applied loads to each part are achieved via summation of inertia and aerodynamic loads. The obtained loads are transformed to the equivalent concentrated loads at the SPs. By substituting the concentrated load values in the EDEs, the SPs deflections are achieved for mentioned flight conditions. The resulted deflections and the corresponding input flight parameters, i.e. M and α, are incorporated into a linear regression method for development of the appropriate in-flight deflection equations (IFDEs). The validity of IFDEs is approved by comparing IFDEs’ deflections with the corresponding ones calculated through EDEs for different flight conditions. Findings As an alternative approach to the fairly expensive flight tests, the IFDEs can be used to predict the in-flight wing deflections with comparable degree of accuracy. Originality/value Prediction of actual wing deflections distributions without flight tests execution at any given flight condition.

Objectives:The success or failure of global and national efforts to combat the COVID-19 pandemic depends on public knowledge, attitude, and practice. Iran, Afghanistan, and Turkey are among the most affected countries in which they have approximately similar socio-cultural structures. This is an online questionnaire-based cross-sectional study to assess the knowledge, attitude, and practice levels toward the COVID-19 pandemic among the adult population of these nationalities.Methods: A total of 2736 individuals including 1080 from Turkey, 1025 from Iran, and 631 from Afghanistan responded to the questionnaire. The data was collected online through a survey using the Google form and Porsall platforms. In addition to demographic characteristics, the questionnaire consists of three main sections including items of awareness, attitude, and practice of the participants about COVID-19 using four Likert scale questions. Descriptive statistics were used to estimates the proportions of items. One-way analysis of variance (ANOVA) and independent T-test was used to analyze the difference between KAP scores among sociodemographic variables and between countries. All analyses were done with the 95% confidence level and the significant level was defined as pvalue < 0.05. Results:Overall KAP scores were over 3 out of 4 among Turkey, Iran, and Afghanistan respectively. Despite no differences between subpopulations in each country, the overall attitude and practice score of the Afghan population was significantly lower than Turkish and Iranian populations (P-value<0.05). Conclusion:In spite of the high level of knowledge, positive attitude, and acceptable practice in all populations understudy, a low-risk perception in a considerable part of the population was discerned.