Naval Group (France)

In recent years, the maritime technology and shipbuilding industry, including yachts and pleasure crafts as well as marine structures, have faced significant challenges, such as technological advancements, environmental sustainability, and global competitiveness. This article presents a comprehensive investigation conducted within the European project LeaderSHIP, focusing on the current state of training programs for workers in the sector and specifically identifying emerging and urgent skills necessary for future success. Using a mixed-methods approach, data were collected through surveys distributed to industry professionals, educational institution representatives, and companies. The results highlight a disparity between the skills demanded by employers and those provided by training programs. Notably, the investigation reveals critical gaps in essential areas such as sustainable design, technological innovation, and resource management, underscoring the need for immediate action. The analysis emphasizes the importance of continuous updating and a closer alignment between academia and industry. It suggests that collaboration between educational institutions and businesses could significantly enhance training quality. Implementing practical learning programs and internships, along with creating flexible curricula that can adapt to the sector’s dynamic needs, is proposed as a vital strategy to address these gaps. Finally, the article discusses future perspectives for training in maritime technology, stressing the necessity to invest in advanced skills and foster a culture of innovation. This study provides valuable insights for policymakers, educators, and entrepreneurs, highlighting the critical need for an integrated approach to effectively tackle the challenges posed by emerging and urgent skills in the shipbuilding industry.

To predict underwater noise radiated by a ship, various numerical methods are available. In underwater acoustics, the most effective prediction methods consist in solving an acoustic analogy using an integral formulation. In this study, we propose a machine learning surrogate-based method, combined with Monte Carlo integration, to efficiently estimate volume integrals that arise in acoustic analogies. We use three machine learning surrogate models: multi-layer perceptrons, Gaussian processes and gradient-boosted decision trees. For each model, a theoretical background is presented. We conduct numerical experiments to compare the state-of-the-art classical Monte Carlo quadrature method with our new machine learning based method. We first apply our method to simple canonical functions, which are analytically integrable, to evaluate the accuracy of our method. We then use a multi-layer perceptron-based surrogate model to approximate a fabricated function that mimics the characteristics of noise sources found in acoustic prediction models, such as those related to turbulent flows near geometrical singularities. Numerical experiments demonstrate that the proposed machine learning-based approach achieves performance levels comparable to state-of-the-art Monte Carlo quadrature methods, demonstrating the potential of ML techniques in this domain.

p-ISBN : 979-8-3315-4184-2; Print on Demand (PoD) ISBN : 979-8-3315-4185-9; ISSN : 2154-512X

Predicting the vibroacoustic behaviour of structures in contact with water and at high frequencies can be a complex task due to the fluid-structure interaction. Computation time increases with frequency and the complexity of the structure. Being able to predict the sound radiated by a naval vehicle in contact with water could help in improving passengers' comfort as well as the impact on the marine fauna. We use a prediction method called Dynamic Energy Analysis (DEA), so far emloyed mainly to assess the vibrational energy levels in the structure itself. DEA is a phase-space based ray tracing method determining energy densities in terms of the ray densities in a structure. The method can be applied on FEM-meshes and thus needs no SEA type substructuring. We expand the DEA methodology here to take into account radiation into the fluid in contact with the structure. From structure borne DEA calculations, we can determine directional sound radiation patterns both inside and outside the structure. We will demonstrate the new technique using some simple model systems.

Floor inclination can alter hand force production, and lower limb kinetics, affecting control operations, and threatening operator safety in various domains, such as aviation, naval, construction industry, or agriculture. This study investigates the effects of different floor inclinations, on handle push or pull force production. Participants performed maximal isometric contraction tasks requiring to exert a maximal voluntary force either by pulling or pushing a handle, at different floor inclinations from −30° to +30° about the transverse and longitudinal axes. Maximal hand force and Ground Reaction Forces about both feet were recorded. The results revealed non-equivalent variations in hand and feet responses as a function of inclination angle. Specifically, there was a significant reduction in handle push-pull force production, up to 70% (p < 0.001) for extreme inclinations, around both axes. This study provides critical data for design engineers, highlighting the challenge of production forces at steep angles.

Abstract The investigation of fatigue behavior typically involves time‐consuming tests, leading some researchers to explore methodologies based on self‐heating tests to reduce the process. For composite materials, the conventional approach involves piecewise linear approximations of the self‐heating curve and the stress transition between the first and second regimes is arbitrarily associated with a fatigue lifetime equal to 106 cycles. This paper proposes a novel methodology to address these simplifications. First, a non‐linear viscoelastic model is used to describe the self‐heating curve. Based on the mechanisms established in the literature, a link is proposed between the dissipation and the fatigue limit. The load leading to a significant contribution of non‐linear mechanisms is associated with an infinite life time. It allows the identification of an – curve and prediction of fatigue behavior through a minimal number of tests. The comparison with fatigue results is satisfactory.

In this paper, we develop a specification-based, process-aware, Intrusion Detection System (IDS) for complex Industrial Control Systems (ICSs). Complex ICSs are distributed and hierarchical control systems built on top of local control loops which are the system's elementary building blocks. Process-aware attacks are sophisticated cyberattacks that aim to compromise the safety of the controlled physical process.Our approach aims to link safety specifications and security properties. Thus, we use international and industry standards specifications concerning local safety, global safety and networks of the industrial process, in order to obtain security properties. The obtained security properties are cybersecurity related requirements. They are translated into security patterns in order to be runtime monitored by our network IDS. This latter relies on a distributed monitoring framework, capturing network traffic between the local loops and the distributed control level, as well as between distributed control and supervisory control. We implemented and evaluated our IDS on a real ICS. We experimentally show that our IDS detects a large spectrum of attacks. We also show that our distributed IDS is scalable since its detection response time as a function of the number of monitored security patterns, is linear. A demonstrator comprising code extracts is made available.

Reducing shipping emissions at an affordable cost is critical and can be achieved through propulsion architecture optimization. The multiple choices of components and constraints to be fulfilled (required speed, fuel consumption, maintenance, ...) make architecture design increasingly complex. Some optimization methods have already been used, for example, to optimize diesel generators (number, type and load) for fuel consumption reduction. More complex architectures have been studied by including the absence or presence of some components in a superconfiguration but in the end the number of configurations remains limited. In this study, the ship architecture is not predetermined but is generated by a list of components associated with constraints and rules, making architecture creation more flexible. The algorithm written for this purpose follows the principles found in hybrid vehicle design but with adapted rules and components for naval applications. The main objective of this paper is to explain in detail the topology generation architecture algorithm rather than to find an optimal architecture for a specific ship. From this perspective, the test cases presented are general to demonstrate that the algorithm can be applied to various system configurations. The components are linked together based on their input and output energy type and the architecture is generated to comply with propulsion and hotel load requirements. Next, physical constraints are added to build realistic designs such as avoiding spurious redundant connections or defining the maximal occurrence for each component. All the constraints and the generation algorithm are written in Prolog. Two numerical applications are presented where the list of components covers different types of propulsion (mechanical and/or electrical with gas turbines and/or diesel engines) along with hotel load or heating requirements.

The proximity of obstacles in a ventilation network can result in a significant increase of the noise production. In this paper, a tandem diaphragm inserted in a rigid duct with rectangular cross section is investigated and compared to a single diaphragm obstruction. The disturbed flow which reaches the second obstacle causes an amplification of the radiated noise which goes beyond a simple doubling of the power. Experimental results, carried with various spacing between the two diaphragms and bulk velocity, allows identifying other aeroacoustic source mechanisms which does not appear with a single diaphragm. Depending on the configuration, the broadband level can increase by more than 10 dB and feedback phenomena can appear at low frequency. Explanations and illustrations of those phenomena are given thanks to compressible-fluid simulations.