Kevin Kabera Njuguna

Mr. Kevin Kabera Njuguna

orcid

Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 November 2026 in Symmetry
Verified
Journal Article
Open access
PDF file
YWYingjie Wang
Yingjie Wang
KNKevin Kabera Njuguna
Kevin Kabera Njuguna
JYJong-Dar Yau
Jong-Dar Yau
Railway culverts and their transition zones constitute mechanically heterogeneous systems in which abrupt variations in structural and geotechnical stiffness disrupt the symmetry of train–track–soil–structure interaction (TTSSI). The resulting stiffness asymmetry alters load transfer within the TTSSI system and contributes to dynamic amplification, differential settlement, vibration concentration, and progressive track deterioration. Although substantial research has been conducted on railway transition zones, a systematic synthesis from a symmetry-oriented perspective remains lacking. This review critically examines studies published between 2000 and 2026 on railway culvert dynamics, transition-zone design, TTSSI mechanisms, numerical modeling, field monitoring, international design standards, and emerging digital-twin technologies. Particular attention is given to the influence of stiffness asymmetry on load-transfer mechanisms, vibration propagation, soil–structure interaction, and long-term infrastructure performance. Numerical approaches ranging from simplified analytical formulations to fully coupled three-dimensional TTSSI models are assessed alongside experimental evidence and field observations. The review demonstrates that the dynamic behavior of railway transition zones is fundamentally governed by stiffness discontinuities that break the mechanical symmetry between embankments and buried structures. Despite significant advances in vehicle–track interaction modeling and digital monitoring, important challenges remain in nonlinear soil behavior, hydro-mechanical coupling, resilience quantification, and long-term field validation. To address these limitations, a system-oriented digital-twin framework is proposed that integrates sensing, data assimilation, physics-based simulation, and predictive maintenance. The framework provides a pathway toward resilient, intelligent, and data-driven management of railway culvert transition zones while identifying key priorities for future research.