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The main objective of this work is to assess the current capabilities of different commercial finite element (FE) codes in simulating the progressive damage of composite structures under quasi-static loading condition in post-buckling regime.

Progressive failure analysis (PFA) methodologies, available in the investigated FE codes, were applied to a simple test case extracted from literature consisting in a holed composite plate loaded in compression.

Results of the simulations are significantly affected by the characteristic parameters needed to feed the degradation models implemented in each code. Such parameters, which often do not have a physical meaning, have to be necessarily set upon fitting activity with an experimental database at coupon level. Concerning the test case, all the codes were found able to capture the buckling load and the failure load with a good accuracy.

This paper would to give an insight into the PFA capabilities of different FE codes, providing the guidelines for setting the degradation model parameters which are of major interest.

This paper aims to propose a structural sizing approach of an unmanned aerial vehicle (UAV) wing that takes into account the aeroelasticity effects through a fluid–structure interaction analysis.

The sizing approach proposed in this study is an iterative process, each iteration of which consists of two sub-loops, a multidisciplinary analysis (MDA) loop followed by a structural optimization loop. The MDA loop seeks the aeroelastic equilibrium between aerodynamic forces and structural displacements using a fixed-point iteration scheme. Once the equilibrium is reached, the converged pressure loads are used for the structural optimization, which aims to find the structural thicknesses that minimize the wing weight under failure criteria. The two sub-loops are run sequentially in an iterative process until the mass is converged. The analysis models are implemented in open-source software, namely, PANUKL for aerodynamics and MYSTRAN for structures, while the whole process is automated with Python and integrated in the open-source optimization framework OpenMDAO.

The approach was applied to the design of the Predator MQ-1 wing. The results of the MDAs show the convergence of the wing deformations to the flight shape after few iterations. At the end of the aeroelastic sizing loop, the result is a structurally sized wing with minimal weight considering the aeroelasticity effects.

The approach proposed takes into account the wing aero-structural coupling effects while sizing its structure instead of a fixed load distribution. In addition, the approach is fully based on open-source codes, which are freely available for public use and can be fully reproducible.

The purpose of this paper is to investigate on the behaviour of a delaminated stiffened panel; the delamination growth is simulated via fracture elements implemented in B2000++® code based on the Modified Virtual Crack Closure Technique (MVCCT), matrix cracking and fibre failure have been also taken into account.

In order to correctly apply the MVCCT on the delamination front a very fine three-dimensional (3D) mesh is required very close to the delaminated area, while a 2D-shell model has been employed for the areas of minor interest. In order to couple the shell domain to the solid one, shell-to-solid coupling elements based on kinematic constraints have been used.

Results obtained with the global/local approach are in good correlation with those obtained with experimental results.

The global/local approach based on kinematic coupling elements in conjunction with fracture elements allows to investigate and predict the behaviour of a stiffened delaminated composite panel in an efficient and effective way.

The purpose of this paper is to present a structural design and optimization module for aircraft structures that can be used stand-alone or in a high-fidelity multidisciplinary design optimization (MDO) process. The module is capable of dealing with different design concepts and novel materials properly. The functionality of the module is also demonstrated.

For fast sizing and optimization, linear static finite element (FE) models are used to obtain inner loads of the structural components. The inner loads and the geometry are passed to a software, where a comprehensive set of analytical failure criteria is applied for the design of the structure. In addition to conventional design processes, the objects of stiffened panels like skin and stringer are not optimized separately and discrete layups can be considered for composites. The module is connected to a design environment, where an automated steering of the overall process and the generation of the FE models is implemented.

The exemplary application on a transport aircraft wing shows the functionality of the developed module.

The weight benefit of not optimizing skin and stringer separately was shown. Furthermore, with the applied approach, a fast investigation of different aircraft configurations is possible without constraining too many design variables as it often occurs in other optimization processes. The flexibility of the module allows numerous investigations on influence of design concepts and failure criteria on the mass and layout of aircraft wings.

The purpose of this research paper is to recover the autonomous flight performance of a mini unmanned aerial vehicle (UAV) via stochastically optimizing the wing over certain parameters (i.e. wing taper ratio and wing aspect ratio) while there are lower and upper constraints on these redesign parameters.

A mini UAV is produced in the Iskenderun Technical University (ISTE) Unmanned Aerial Vehicle Laboratory. Its complete wing can vary passively before the flight with respect to the result of the stochastic redesign of the wing while maximizing autonomous flight performance. Flight control system (FCS) parameters (i.e. gains of longitudinal and lateral proportional-integral-derivative controllers) and wing redesign parameters mentioned before are simultaneously designed to maximize autonomous flight performance index using a certain stochastic optimization strategy named as simultaneous perturbation stochastic approximation (SPSA). Found results are used while composing UAV flight simulations.

Using stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV over previously mentioned wing parameters and FCS, it obtained a maximum UAV autonomous flight performance.

Permission of the directorate general of civil aviation in the Republic of Türkiye is essential for real-time UAV autonomous flights.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach is very useful for improving any mini UAV autonomous flight performance cost index.

Stochastic redesign of mini UAV and simultaneously designing mini ISTE UAV wing parameters and FCS approach succeeds confidence, highly improved autonomous flight performance cost index and easy service demands of mini UAV operators.

Creating a new approach to recover autonomous flight performance cost index (e.g. satisfying less settling time and less rise time, less overshoot during flight trajectory tracking) of a mini UAV and composing a novel procedure performing simultaneous mini UAV having passively morphing wing over certain parameters while there are upper and lower constraints and FCS design idea.

This paper aims to overcome the main obstacle to compare the merits of the different control strategies for fixed-wing unmanned aerial vehicles (UAVs) to assess autopilot performances. Up to now, the published studies of control strategies have been carried out over disperse models, thus being complicated, if not impossible, to compare the merits of each proposal. The authors present a worked benchmark for autopilots studies, consisting of generalized models obtained by merging UAVs’ parameters gathered from selected literature (journals) with other parameters directly obtained by the authors to include some relevant UAVs whose models are not provided in the literature. To obtain them it has been used a dedicated software (from U.S. Air Force).

The proposed models have been constructed by averaging both the main aircraft defining parameters (model derivatives) and pole-zero locations of longitudinal transfer functions. The suitability of the used methodologies has been checked from their capability to fit the short period and the phugoid modes. Previous analytical model arrangement has been required to match a uniform set of parameters, as the inner state variables are neither the same along the different published models nor between the additional models the authors have here contributed. Besides, moving models between the space state representation and transfer function is not just a simple averaging process, as neither the parameters nor the model orders are the same in the different published works. So, the junction of the models to a common set of parameters requires some residual’s computation and transient responses assessment (even Fourier analysis has been included to preserve the dominance of the phugoid) to keep the main properties of the models. The least mean squares technique has been used to have better fittings between SISO model parameters with state–space ones.

Both the SISO (Laplace) and state-space models for the longitudinal transfer function of an “averaged” fixed-wing UAV are proposed.

More complicated situations, such as strong wind conditions, need another kind of models, usually based on finite element method simulation. These particular models apply fluid dynamics to study aerostructural aircraft aspects, such as flutter and other aerolastic aspects, the behavior under icing conditions or other distributed parameter problems. Even some models aim to control other aspects than the autopilot, such as the trajectory prediction. However, these models are not the most suitable for the basic UAV autopilot design (early design), so they are outside the objective of this paper. Obviously, the here-considered UAVs are not all the existing ones, but the number is large enough to consider the result as a reliable and realistic representation. The presented study may be seen as a stepping stone, allowing to include other UAVs in future works.

The proposed models can be used as benchmarks, or as a previous step to produce improved benchmarks, in order to have a common and realistic scenario the compare the benefits of the different control actions in UAV autopilots continuously presented in the published research.

A work with the scope of the presented one, merging model parameters from literature with other (often referred in papers and websites) whose parameters have been obtained by the authors has been never published.

Computational efficiency is always the major concern in aircraft design. The purpose of this research is to investigate an efficient jig-shape optimization design method. A new jig-shape optimization method is presented in the current study and its application on the high aspect ratio wing is discussed.

First, the effects of bending and torsion on aerodynamic distribution were discussed. The effect of bending deformation was equivalent to the change of attack angle through a new equivalent method. The equivalent attack angle showed a linear dependence on the quadratic function of bending. Then, a new jig-shape optimization method taking integrated structural deformation into account was proposed. The method was realized by four substeps: object decomposition, optimization design, inversion and evaluation.

After the new jig-shape optimization design, both aerodynamic distribution and structural configuration have satisfactory results. Meanwhile, the method takes both bending and torsion deformation into account.

The new jig-shape optimization method can be well used for the high aspect ratio wing.

The new method is an innovation based on the traditional single parameter design method. It is suitable for engineering application.

Little is known, about the role played by start-ups in open innovation networks. Start-ups – due to their nature of new and emerging companies – can largely benefit from the knowledge that can flow intentionally or unintentionally from external partners during open innovation practices. When open innovation networks are not set among peers on both sides the authors expect to have more unintended knowledge flows. Such knowledge “leaks” – as the authors named them – in open innovation networks are totally unexplored in literature. Hence, the purpose of this paper is to focus “whether and how knowledge leaks occur in open innovation networks with start-ups”.

The research design of this study relies on social network analysis methods and techniques to disentangle the role of start-ups in open innovation networks – in a major Italian aerospace cluster – vis-à-vis the three types of knowledge considered in this study. Then the authors confirmed knowledge leaks to occur through a multiplexity analysis. In the second stage of the research, the authors decided to strengthen the results, making them more vivid and thorough, relying on four case studies.

The paper sheds light on a totally unexplored phenomenon, theorizing on the role of start-ups in open innovation networks and suggesting intriguing implications both for theory and managers on whether and how knowledge leaks occur.

The main limitations arise from the specific research context, in fact the study has been conducted in an aerospace cluster. So future studies might consider to explore knowledge leaks in non-cluster settings and in low tech industries.

The results have practical implications both for policy makers and for managers. First of all, the research confirms how open innovation often originates from a combination of different knowledge types acquired through the collaboration with heterogeneous players, start-ups included. Hence, managers may design open innovation strategies balancing their portfolio of collaborations to maximize the absorption of relevant knowledge and start-uppers may consider to engage in open innovation practices to accelerate knowledge absorption. Nevertheless, the study warns managers against the risk of knowledge leaks, especially in cases like start-ups where the eagerness to participate or the prestige associated with participating in open innovation networks with key players may hamper the control over knowledge leaks.

This opens up for possible interventions for policy makers too. First of all, policy makers may consider incorporating the concept of knowledge leaks in their campaign in favour of open innovation. Second, the study may help policy makers in designing programmes for knowledge transfer partnerships amongst the various players of a cluster in a more conscious way, especially warning new to business companies, like start-ups, about possible leaks. Finally, there is also the need of developing professional figures like consultants capable of supporting start-ups in their open innovation practices.

Findings reported in the paper confirm multiplexity and heteromorphism in knowledge exchanges and shed the light on a completely unexplored field (i.e. open innovation and start-ups), focussing on knowledge leaks. Relevant implications for policy makers and managers are included in the study.

The purpose of this paper is to describe the development of an integrated framework suitable for preliminary airframe design, called PyPAD (Python module for Preliminary Aircraft Design), providing the capability to define models to compute loads and to perform the structural sizing.

The modules developed until now allow for the definition of multi-fidelity aero-structural models starting from a Common Parametric Aircraft Configuration Schema (CPACS) input file and to compute static loads (trim) and flutter margin with minimum user effort. PyPAD take advantages of Abaqus-CAE, and the main functions are developed in Python, to take advantages of the simplicity in terms of software development and maintenance, but the core routines are developed in Fortran, taking advantages of parallel programming to get the best performances.

A complete test case, starting from the CPACS input and ending with the definition of structural, aerodynamic and aero-elastic models, with the computation of different design loads, is reported. An example will show that the framework developed is able to handle different problematics of the preliminary projects using quite complex global models.

All the tools developed in the framework, and the ones currently under development, could be a valid help during the preliminary design of a new aircraft, speeding up the iterative process and improving the design solution.

PyPAD is the first framework developed around Abaqus-CAE for the preliminary aircraft design and is one of the few tools looking at the different problematics involved in a preliminary airframe design: design, loads and aero-elasticity, sizing and multi-disciplinary optimization.

This paper aims at investigating the multifaceted nature of innovation networks by focusing on two research questions: Do cluster actors exchange only one type of innovation-related knowledge? Do cluster actors play different roles in innovation-related knowledge exchange?

This paper builds on data collected at the firm level in an Italian aerospace cluster, that is a technology-intensive industry where innovation is at the base of local competitiveness. A questionnaire was used to collect both attribute data and relational data concerning collaboration and the flows of knowledge in innovation networks. The authors distinguished among three types of knowledge (technological, managerial and market knowledge) and five types of brokerage roles (coordinator, gatekeeper, liaison, representative and consultant). Data analysis relied on social network analysis techniques and software.

Concerning the first research question, the findings show that different types of knowledge flow in different ways in innovation networks. The different types of knowledge are unevenly exchanged. The exchange of technological knowledge is open to everyone in the cluster. The exchange of market and managerial knowledge is selective. Concerning the second research question, the authors suggest that different types of cluster actors (large firms, small- and medium-sized enterprises, research centers and universities and institutions for collaboration) do play different roles in innovation networks, especially with reference to the three types of knowledge considered in this study.

The present paper has some limitations. First of all, the analysis focuses on just one cluster (one industry in one specific location), cross- and comparative analyses with other clusters may illuminate the findings better, eliminating industry and geographical biases. Second, the paper focuses only on innovation-related knowledge exchanges within the cluster and not across it.

The results have practical implications both for policy makers and for managers. First, this research stresses how innovation often originates from a combination of different knowledge types acquired through the collaboration with heterogeneous cluster actors. Further, the analysis of brokerage roles in innovation-driven collaborations may help policy makers in designing programs for knowledge-transfer partnerships among the various actors of a cluster.

The paper suggests a clear need of developing professional figures capable of operating at the interface of different knowledge domains.

The data illuminate several aspects of how innovation takes place in a cluster opening up intriguing aspects that have been overlooked by extant literature. The authors believe that this may trigger several lines of further research on the topic.