Methodology for avionics integration optimisation

Every state-of-art aircraft has a complex distributed systems of avionics Line Replaceable Units/Modules (LRUs/LRMs), networked by several data buses. These LRUs are becoming more complex because of the increasing number of new avionics functions need to be integrated in an avionics LRU. The evolution of avionics data buses and architectures have moved from distributed analogue and federated architecture to digital Integrated Modular Avionics (IMA). IMA architecture allows suppliers to develop their own LRUs/LRMs capable of specific features that can then be offered to Original Equipment Manufacturers (OEMs) as Commercial-Off-The-Shelf (COTS) products. In the meantime, the aerospace industry has been investigating new solutions to develop smaller, lighter and more capable avionics LRUs to be integrated into avionics architecture. Moreover, the complexity of the overall avionics architecture and its impact on cable length, weight, power consumption, reliability and maintainability of avionics systems encouraged manufacturers to incorporate efficient avionics architectures in their aircraft design process. However, manual design cannot concurrently fulfil the complexity and interconnectivity of system requirements and optimality. Thus, developing computer-aided design (CAD), Model Based System Engineering (MBSE) tools and mathematical modelling for optimisation of IMA architecture has become an active research area in avionics systems integration. In this thesis, a general method and tool are developed for optimisation of avionics architecture and improving its operational capability. The tool has three main parts including a database of avionics LRUs, mathematical modelling of the architectures and optimisation algorithms. The developed avionics database includes avionics LRUs with their technical specifications and operational capabilities for each avionics function. A MCDM method, SAW, is used to quantify and rank each avionics LRU’s operational capability. Based on the existing avionics LRUs in the database and aircraft level avionics requirements two avionics architectures are proposed i.e. AFCS architecture (SSA) and avionics architecture (LSA). The proposed avionics architectures are then modelled using mathematical programming. Further, the allocation of avionics LRUs to avionics architecture and mapping the avionics LRUs to their installation locations are defined as an assignment problem in Integer Programming (IP) format. The defined avionics architecture optimisation problem is to optimise avionics architecture in terms of mass, volume, power consumption, MTBF and operational capability. The problems are solved as both single-objective and multi-objective optimisation using the branch-and-bound algorithm, weighted sum method and Particle Swarm Optimisation (PSO) algorithm. Finally, the tool provides a semi-automatic optimisation of avionics architecture. This helps avionics system architects to investigate and evaluate various architectures in the early stage of design from an LRU perspective. It can also be used to upgrade a legacy avionics architecture.Aerospac

Technological and design aspects of the processing of composites and nanocomposites. Volume III

Processing of composites and nanocomposites materials constitutes nowadays an important area of research given the growing interest by these types of materials due to its singular properties, namely in what concerns technological and design aspects. This monography presents the developments taking place in the framework of the NEWEX project during the fourth year of its duration, which is a sequence of other two previous monographies. The main objective of the NEWEX project entitled “Investigation and development of a new generation of machines for the processing of composite and nanocomposites materials” is the exchange of researchers from the institutions participating in the project. Another important objective consists in develop permanent international and inter-sector collaboration between academic research centres (Lublin University of Technology, Technical University of Kosice, University of Minho) and industrial organizations (Zamak-Mercator LLC and SEZ-Krompachy a.s., Dirmeta UAB). The contents of this book reflects the work done within the NEWEX project. It starts by presenting the results obtained concerning new concepts for the extruder parts studied and the manufacturing of those extruder parts. Then, some approaches for modelling and optimizing and to study experimentally the process are described, which includes mixing analysis and monitoring. Finally, a practical and state-of-theart application of the extrusion is identified, namely 3D printing. It is expected that the nine chapters of this monography be useful to the industry of plastics processing and for scientific organisations dealing with technologies and processing of polymer composites and nanocomposites

Cementitious mortars and polyurethane foams for additive building manufacturing

The use of additive manufacturing in the construction industry is still in a state of infancy. Research into suitable materials for Additive Building Manufacturing ABM) have centred upon polymeric and cementitious materials, with the trade-off between workability and buildability central to material development. This study is investigating both CEM1 based mortars and polyurethane foam to evaluate suitability for use in the construction and repair of buildings. High density polyurethane foam possesses sufficient strength and density to be a viable structural material; however, the fresh properties of the material following mixing of components present a challenge as the material exhibits lateral expansion and excessive deformation prior to curing. Microparticles were added to high density foam to investigate the provision of rigidity during curing, however the particles promoted the foaming reaction, reducing density, strength and structural viability. Mortar mixes under investigation placed the emphasis upon workability and minimisation of constituent segregation, while mindful of the material still needing to possess sufficient buildability in order to prevent excessive deformation of extruded layers while deposited material remains in a fresh state

A technical perspective on integrating artificial intelligence to solid-state welding

The implementation of artificial intelligence (AI) techniques in industrial applications, especially solid-state welding (SSW), has transformed modeling, optimization, forecasting, and controlling sophisticated systems. SSW is a better method for joining due to the least melting of material thus maintaining Nugget region integrity. This study investigates thoroughly how AI-based predictions have impacted SSW by looking at methods like Artificial Neural Networks (ANN), Fuzzy Logic (FL), Machine Learning (ML), Meta-Heuristic Algorithms, and Hybrid Methods (HM) as applied to Friction Stir Welding (FSW), Ultrasonic Welding (UW), and Diffusion Bonding (DB). Studies on Diffusion Bonding reveal that ANN and Generic Algorithms can predict outcomes with an accuracy range of 85 – 99%, while Response Surface Methodology such as Optimization Strategy can achieve up to 95 percent confidence levels in improving bonding strength and optimizing process parameters. Using ANNs for FSW gives an average percentage error of about 95%, but using metaheuristics refined it at an incrementally improved accuracy rate of about 2%. In UW, ANN, Hybrid ANN, and ML models predict output parameters with accuracy levels ranging from 85 to 96%. Integrating AI techniques with optimization algorithms, for instance, GA and Particle Swarm Optimization (PSO) significantly improves accuracy, enhancing parameter prediction and optimizing UW processes. ANN’s high accuracy of nearly 95% compared to other techniques like FL and ML in predicting welding parameters. HM exhibits superior precision, showcasing their potential to enhance weld quality, minimize trial welds, and reduce costs and time. Various emerging hybrid methods offer better prediction accuracy

Uso da otimização topológica no design e desenvolvimento de produto

The way to design products has won a new dimension with ripening of concepts such as Generative Design and Topology Optimisation, Cloud Computing, Artificial Intelligence and Additive Manufacturing. This development has opened space for new ways to create better and more sophisticated products that, in the organisations' competitiveness, it can be in the near future a nearly mandatory competitive standard. Whereas this opportunity window aims to explore the new and lead it to a product development routine, this dissertation has as goal, through a wide study, to explore a methodology that ought to serve as a guide for design and/or engineering professionals who would like to understand how to better use these concepts as a tool for products optimisation by computational methods. In order to understand its basic principles and how to perform a reliable data processing, an applied example for a case will also be shown as well as its difficulties and learnings obtained and, finally, a critical analysis of the advantages and disadvantages of using these tools. Therefore, this study will have as focus to explore the Topology Optimisation along with Biomimicry and provide a basis on how to apply these concepts in the product development.A forma de se projetar produtos tem ganhado uma nova dimensão com o amadurecimento de conceitos e tecnologias como o Design Generativo e Otimização Topológica, Cloud Computing, Inteligência Artificial e Fabrico Aditivo. Este avanço, tem aberto espaço para se criar melhores e mais sofisticados produtos, que face a competitividade entre organizações, pode vir a ser num futuro próximo um critério competitivo quase que obrigatório. Considerando esta janela de oportunidade para explorar o novo e levá-lo para a rotina no desenvolvimento de produtos, este trabalho de dissertação tem como objetivo, através de um estudo abrangente, explorar uma metodologia que possa servir como guia a profissionais de Design e/ou Engenharia que queiram entender como usar melhor ferramentas de otimização de produtos focada em otimização topológica através de métodos computacionais, de forma a compreender seus princípios básicos e como realizar um processamento de dados fiável. Um exemplo aplicado a um caso, assim como dificuldades e aprendizados obtidos. E por fim, uma análise crítica quanto as vantagens e desvantagens de se utilizar tais ferramentas. Portanto, o foco neste estudo é explorar a Otimização Topológica em conjunto com a Biomimética e fornecer uma base de como estes conceitos podem ser aplicados no desenvolvimento de um produto.Mestrado em Engenharia e Design de Produt

12th EASN International Conference on "Innovation in Aviation & Space for opening New Horizons"

Epoxy resins show a combination of thermal stability, good mechanical performance, and durability, which make these materials suitable for many applications in the Aerospace industry. Different types of curing agents can be utilized for curing epoxy systems. The use of aliphatic amines as curing agent is preferable over the toxic aromatic ones, though their incorporation increases the flammability of the resin. Recently, we have developed different hybrid strategies, where the sol-gel technique has been exploited in combination with two DOPO-based flame retardants and other synergists or the use of humic acid and ammonium polyphosphate to achieve non-dripping V-0 classification in UL 94 vertical flame spread tests, with low phosphorous loadings (e.g., 1-2 wt%). These strategies improved the flame retardancy of the epoxy matrix, without any detrimental impact on the mechanical and thermal properties of the composites. Finally, the formation of a hybrid silica-epoxy network accounted for the establishment of tailored interphases, due to a better dispersion of more polar additives in the hydrophobic resin

Proceedings of the 2021 DigitalFUTURES

This open access book is a compilation of selected papers from 2021 DigitalFUTURES—The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021). The work focuses on novel techniques for computational design and robotic fabrication. The contents make valuable contributions to academic researchers, designers, and engineers in the industry. As well, readers encounter new ideas about understanding material intelligence in architecture