http://repositorio.lnec.pt:8080/jspui/handle/123456789/58 Mon, 26 Oct 2026 10:06:26 GMT 2026-10-26T10:06:26Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019997 Effect of aggregate shape representation and deformability on the bituminous mixture stiffness properties using 3D DEM modelling Micaelo, R.; Azevedo, N.; Câmara, G. Given the recognised importance of aggregate shape in the performance of bituminous mixtures, there has been growing interest in developing numerical models that accurately capture the material’s mesostructural characteristics. This paper presents a methodology for incorporating complex aggregate shapes into three-dimensional (3D) Discrete Element Method (DEM) models of bituminous materials and investigates the impact of representing coarse aggregates as deformable bodies on both the geometry and mechanical response of DEM assemblies. This approach was implemented in VirtualPM3DLab, a 3D DEM software that employs Laguerre–Voronoi diagrams to define spherical particle contacts and contact areas, together with a generalised Kelvin contact model to simulate the viscoelastic behaviour of bituminous materials. The mechanical response of DEM assemblies, using rigid single-spherical particle aggregates versus deformable multi-spherical particle aggregates, was analysed through simulated uniaxial tension–compression cyclic tests at various frequencies. The results show that discretising the aggregate volume using a distribution of smaller-radius spherical particles effectively captures aggregate geometry, although the sphere size distribution must be carefully selected to ensure high-fidelity representation. Virtual asphalt specimens with deformable multisphere aggregate particles exhibited higher stiffness moduli and lower phase angles across the tested frequencies compared to rigid single-sphere specimens. These variations in viscoelastic properties were more pronounced with finer aggregate discretisation, due to the increased number of aggregate–aggregate and aggregate–mastic contacts. In contrast, the total number of contacts and their distribution among constituents were very similar for assemblies with irregular particle models (realistic) and subdivided icosahedron models (close to spherical), resulting in a minimal effect of aggregate shape on the overall DEM simulation results. Thu, 09 Apr 2026 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019997 2026-04-09T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019609 Unveiling emerging communities: a network approach on transport decarbonisation technology Aparício, J.; Arsénio, E.; Henriques, R. What are the latent thematic communities driving transport decarbonisation research across road, rail, maritime, and crossmodal domains? To answer this central question, this work proposes an integrated network model that fuses bibliographic coupling with Sentence-BERT semantic similarities, followed by a statistical analysis using state-of-the-art community detection algorithms. We assess partitions via four complementary metrics, modularity, silhouette, density, and NF1, and compare weighted versus unweighted graphs. Our analysis of mode-specific corpora uncovers distinct clusters: road research splits into urban last-mile automation and rural logistics; rail coalesces around a synchromodal scheduling hub with biofuel and corridor electrification offshoots; maritime divides into green fuels, autonomous safety, and shore-power streams; and crossmodal studies form overlapping triads of electrification, data analytics, and blockchain. Weighted edge integration uniformly enhances thematic clarity without altering algorithm rankings. These findings yield actionable algorithm-selection heuristics and tie each community to specific SDG targets, transforming aspirational goals into a concrete, community-by-community policy roadmap for green logistics. Sat, 17 Jan 2026 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019609 2026-01-17T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019502 Stakeholder Analysis Matrix Sobrino, N.; Arsénio, E.; Dias, G.; Marecos, V.; Castaño, D.; Vassallo, J.; Twrdy, E.; Vestinen, J.; Mulhern, E. Wed, 01 Jan 2025 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019502 2025-01-01T00:00:00Z http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019501 Pilot evaluation summary report Heilala, J.; Pyykkö, H.; Heilala, J.; Rummukainen, H.; Panasenkiene, M.; Rudelis, R.; Silva, L.; Dais, S.; Dias, G.; Arsénio, E.; Polzelnik, M.; Kahvedžić, A.; Mulhern, E.; Hinkka, V. Wed, 01 Jan 2025 00:00:00 GMT http://repositorio.lnec.pt:8080/jspui/handle/123456789/1019501 2025-01-01T00:00:00Z