MBDA is a European multinational developer and manufacturer of missiles. It was created in December 2001 after the merger of the main French, British and Italian missile systems companies: they were the missile businesses of Aérospatiale-Matra (merged into EADS, now called Airbus), BAE Systems and Finmeccanica (now Leonardo). The name "MBDA" is an initialism of the names of the main companies that came together to form it (Matra, BAe Dynamics and Alenia). The company's headquarters are located in Le Plessis-Robinson, France. Despite being a European joint venture, MBDA has maintained national divisions since its creation: MBDA France, MBDA UK and MBDA Italy. They were formed by simply grouping in their respective countries the assets and activities of the various French, British and Italian businesses that had merged to create MBDA.In March 2006, LFK-Lenkflugkörpersysteme GmbH, the German missile subsidiary of EADS, was acquired by MBDA and Spanish assets followed in 2010, leading to the formation of two additional national divisions (MBDA Germany and MBDA Spain).In 2016, the company had more than 10,500 employees. In 2017, MBDA recorded orders for €4.2 bn and an order book of €16.8 bn. MBDA works with over 90 armed forces worldwide and also has a number of subsidiaries, including one in the United States (MBDA Inc).
A workshop on Ceramic Matrix Composites for applications (CMCs) in the 800–1300 °C temperature range was held at the 4th International Conference on High-Speed Vehicle Science and Technology in Tours, France September 22–26, 2025. The aim of the workshop was to generate recommendations for the technology development of such materials for aerospace applications. The comparison with traditional carbon and silicon carbide-based CMCs was made, establishing that they offer a key option in the search of optimized designs, especially regarding cost. These CMCs exhibit damage behavior. Taking this behavior into account offers an opportunity to reduce design margins but also to complexify the building of material databases and mechanical models. Two strategies have been adopted to demonstrate CMC technologies. The first is establishing a materials database with damage-tolerance properties before manufacturing complex components. The second is to crash-test the flight components to directly assess the component’s viability. Both have advantages and drawbacks regarding the cost and time scale of the development. Getting the design offices aware of the opportunities and specificities of these materials is key to developing viable designs. It requires setting in place dedicated training.
Model-Based Systems Engineering (MBSE) is widely treated as the backbone of digital engineering, with languages such as the Systems Modeling Language (SysML) providing the means to capture system structure, behaviour, and verification intent. Yet once verification moves to hardware, the system model is routinely left behind. Domain-specific simulation environments, model transformations, and bespoke tool integrations take over, and the model that began as the authoritative reference drifts out of sync with the implementation it was meant to govern. This paper introduces the SysML Hardware Interface Architecture (SHIA), which keeps an executable SysML model directly inside the verification loop, exchanging messages with physical hardware without intermediate transformation chains, co-simulation platforms, or broker-mediated plugins. SHIA is realised through a SysML side server, written in embedded C++ within IBM Rhapsody, and a hardware side server running on a Raspberry Pi, together establishing a bidirectional link between the digital model and the physical system. A logic gate case study demonstrates the approach end-to-end, from hardware model construction and prototype assembly to test harness design, behavioural statechart control, and staged verification of each component before integration. The integrated system exchanged messages correctly in both directions, and Karnaugh map comparison between the SysML-generated and hardware-generated outputs showed zero discrepancy. The result shows that, when paired with a suitable interface, SysML need not remain a static description that informs downstream tools; it can serve as the executable layer through which hardware behaviour is stimulated, observed, and verified. The work demonstrates a route to model-governed verification and a shorter digital thread between system architecture and the hardware that realises it.
This study presents a multi-step approach to design and evaluate the cooling architecture of an actively cooled probe nacelle suitable for high-temperature supersonic flows. First, a 1D heat transfer model was used to determine the coolant pressure required for thermal protection of the nacelle at supersonic conditions. It incorporates conductive-convective heat transfer, effusion cooling, leading-edge effects, and high-speed boundary layer effects. A parametric analysis identified a minimum coolant pressure of 2.4 bar to satisfy the temperature limits of the nacelle at the most severe conditions of M1 = 6, T01 = 1700 K. 3D RANS simulations were utilized to assess the accuracy of the 1D model giving average deviations in adiabatic cooling effectiveness and heat transfer coefficient below 6% and 15% respectively. Finally, the cooling performance of the nacelle was assessed in a transonic open jet. Cooling effectiveness was measured with high-resolution infrared thermography, and heat flux was measured with high-frequency Atomic Layer Thermopiles (ALTP). Uncertainties in cooling effectiveness and heat transfer coefficient were evaluated through Taylor propagation and Monte Carlo simulations, respectively. Oil-flow visualization was conducted to compare the surface flow behavior in the effusion cooled face between simulations and experiments, while Schlieren was used to compare the bow shock location and shape. A comprehensive comparison is conducted involving analytical models, simulations and experiments that validate the proposed methodology.
Abstract The Technical Leadership Model (Godfrey, 2016, henceforth TLM 2016) developed by the first Cohort of the INCOSE Technical Leadership Institute (TLI) established a foundational framework for technical leadership comprising six core behavioral pillars to guide engineering leaders in complex socio‐technical environments. With the rapid development of emerging technologies, such as Artificial Intelligence (AI), technical leaders are challenged to guide human‐AI collaboration, preserve accountability, verify AI‐augmented decisions, and sustain stakeholder trust. This paper presents the AI‐Augmented Technical Leadership Model (henceforth the AI‐Augmented TLM) developed by TLI Cohort 10 through literature review, team reflection, stakeholder interviews, survey input, and workshop validation. The updated model retains the original six pillars with refinement and extension on selected behaviors for AI‐augmented engineering contexts and introduces a seventh pillar: Champions Ethical and Responsible Use of Technology. AI‐Augmented TLM offers technical leaders a practical framework for using AI to strengthen, rather than replace, human judgement, collaboration, and responsible technical stewardship.
