DSpace Repository

Welcome to the NLR Reports Repository

Royal NLR conducts research, which is published in reports. Only a minor part of these reports is made public. This repository holds these public, so called Technical Publications (TP), mainly produced from 1996 up till now.

Technical publications published before 1996 may be obtained using the request-form. Other types of NLR-reports are Contract Reports (CR) and Technical Reports (TR), which in general are not public. You may however request a copy by using the request-form. In some cases permission may be granted, depending on specific properties and contractor of the report. Reports will be supplied as pdf-file.

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Recent Submissions

Development of a Holistic Assessment Framework for the Design of AI-Based Automation
(MDPI, 2026) Stroeve, S.H.; Kirwan, B.; Everdij, M.H.C.
There is a need to ensure that the application of artificial intelligence (AI) in increasingly automated operations is safe, human-centric, and trustworthy, and respects ethical principles. To this end, this paper presents an innovative holistic assessment framework to support certification-aware design of AI-based sociotechnical systems with a range of levels of automation along multiple design stages from low to high technology and human readiness levels (TRLs/HRLs). The holistic scope considers a range of relevant key performance areas (KPAs): safety, resilience, security, Human Factors, accountability, responsibility, liability, efficiency, societal sustainability, and environmental sustainability. The core of the framework is a seven-step cycle that assesses the KPAs for critical scenarios and evaluates the combined performance, including uncertainty and trade-offs. This provides feedback to either adapt the design at the same TRL/HRL or refine it at higher TRLs/HRLs. The framework enacted by a toolbox of assessment methods for the KPAs. The framework has been developed in the aviation domain, but it is formulated in a generic manner, enabling application to various AI techniques and operational domains. Its application is illustrated in detail for an air traffic management use case that employs an AI-based system to support air traffic controllers in sequencing aircraft. It is concluded that the framework provides a viable approach for holistic assessment of AI-based sociotechnical systems.
Graded structures by multi-material mixing in laser powder bed fusion
(Elsevier, 2021) Wits, W.W.; Amsterdam, E.
Multi-material mixing in laser powder bed fusion is demonstrated by fabricating functionally graded structures in which Inconel and stainless steel are metallurgically bonded. Material mixing and elemental diffusion in the transition zone are studied for single scan tracks, hatch scans and multi-layer builds. An adapted recoater enabling powder deposition from multiple sources was utilized to fabricate a more gradual transition zone by alternating material deposition within the build. Homogenization heat treatment enhances elemental diffusion compared to the as-built configuration resulting in a gradual material transition without a distinct interface. Finally, a multi-material heat exchanger is presented as exemplary design implementation.
Review of methods for assessing the climate impacts of aviation technologies and the resulting best practices
(Springer, 2026) Grewe, V.; Zhukovska, S.; Dahlmann, K.; Matthes, S.; Megill, L.; Bertram, P.; Ratei, P.; Prakasha, P.; Linke, F.; Niklaß, M.; Lührs, B.; Terrenoire, E.; Novelli, P.; Lefebvre, T.; Söffing, L.; Bucchignani, E.; Solazzo, M.
Navigating uncertainty: Safety solutions for autonomous vehicle integration into mixed-mode mobility
(Elsevier, 2026) Cooke, J.R.E.; Lingam, S.N.; Alavian, P.; Collast, C.; Croon, G.C.H.E. de; Franssen, M.; Hagenaars, J.; Kober, J.; Morsink, P.; Liu, K.; Liu, Y.-H.; Verstegen, R.; Martens, M.; Medendorp, W.P.; Bohte, S.M.
Uncertainty fundamentally shapes human perception and decision-making, a factor that is becoming increasingly critical as autonomous vehicles (AVs) begin to share physical and social spaces with humans. This perspective paper synthesizes insights from neuroscience, robotics, and behavioral science represent uncertainty and act under it. We identify a significant disconnect between low-level mathematical concepts of uncertainty and risk, the uncertainty-aware prediction and planning methods used in robotics, and the high-level psychological uncertainty experienced by humans. Here, we conceptualize an integration pathway for mixed-mode mobility: we show that all three treat control under partial information as the same two-stage problem – probabilistic inference of the current and future state, followed by a risk-weighted choice of action – and we make this shared structure explicit. We thus argue that AVs should quantify and calibrate their own uncertainty, select risk metrics that reflect both individual and collective safety, model how their actions shape human uncertainty and behavior, and communicate intent and confidence in ways that support predictable interaction. This synthesis positions psychological uncertainty as a behaviorally relevant variable for AV design and outlines a research agenda for safer, more understandable transport systems.
Using single pulses in powder-blown directed energy deposition to fabricate high-aspect-ratio metal pins
(Elsevier, 2026) Wits, W.W.; Yang, S.; Vroon, J.; Bremer, S.J.L.
This study investigates the fabrication of high-aspect-ratio metal pins using powder-blown directed energy deposition. Pins are deposited by consecutive laser pulses using titanium alloy Ti6Al4V as feedstock material. A physics-integrated experimental-analytical-numerical framework is developed to predict pin geometry, pin growth and thermal history during fabrication. The framework combines experimental in-situ temperature measurements, an analytical geometry model, and a finite element thermal model for melt pool lifetime predictions. Results show good agreement between model predictions and experimental observations, enabling controlled constant-diameter vertical pin growth with optimised process parameters, which is crucial for applications such as hybrid metal-composite joining and structural repair.