BAUINGENIEUR journal recognized as Traditional “trade journal” list due to its large-scale popularity and long-time continuous publication of research articles. BAUINGENIEUR stands as a cornerstone of Civil Engineering, Mechanical Engineering, Electrical Engineering, Chemical Engineering, Environmental Engineering, Materials Science, Aerospace Engineering, Industrial Engineering, Renewable Energy Engineering, Electronics Engineering, Mechatronics Engineering, Structural Health Monitoring, Green Building Technology, Computational Engineering, Engineering Sustainability
This prestigious journal delivers authoritative insights into bridge engineering, high-rise construction, sustainable infrastructure and seismic resilience, serving decision-makers, researchers, and practitioners worldwide.
With a century-long legacy, journal of BAUINGENIEUR showcases ground-breaking projects—from iconic suspension bridges to eco-friendly urban redevelopment—alongside rigorous analyses of mechanics, finite element modeling, and BIM integration.
This journal publish peer-reviewed research articles to advance knowledge. This Peer-reviewed journals adopt a rigorous evaluation process where submitted manuscripts are assessed by independent experts, in the same field to ensure quality, validity, originality and relevance before publication. It follows a double-blind peer review process in which both the authors’ and reviewers’ identities are concealed from each other to minimize bias.
Current Issue
Volume 87, Issue-2, February 2026
Research Article, Pages: 01-17;
Title:-Digital Twin Implementation for Infrastructure Life-Cycle Monitoring
Authors: Jan Holnicki-Szulc, Mohammed Nijr Dughaylib Alotaibi, Mana Aziz AwadhAlharbi, Naif Hiji Alrasheedi & Abdulrahim Owaidh Saud Aloufi
Abstract: Digital twin technology creates a virtual model of physical infrastructure (like bridges, roads, or water systems) that can be continuously updated with real-time data to simulate performance and predict maintenance needs. By combining sensors, IoT data, and advanced analytics, digital twins enable engineers to foresee structural issues before they become critical, reducing downtime and life-cycle costs. Research can explore the challenges of integrating diverse sensor data, optimizing predictive models, and ensuring reliability over long service lives. This topic is timely due to increasing digitalization in infrastructure management and the need for proactive rather than reactive maintenance strategies. Researchers can also evaluate how digital twins perform under different environmental conditions or across infrastructure types. Digital twin studies can contribute to safer, more resilient and cost-efficient infrastructure systems. …… [For more click here]
Research Article, Pages: 18-35;
Title:-Sustainable and Low-Carbon Construction Materials
Authors: katrin Wieneke, S. Shao & D. Carsten
Abstract: With rising concerns about climate change, developing and optimizing sustainable materials (such as geopolymer concrete, recycled aggregates, bio-based composites, or bamboo composites) is a major research priority. These materials aim to reduce the carbon footprint of construction compared to traditional Portland cement and steel, which are energy-intensive. Researchers can investigate mechanical properties, durability, cost-effectiveness, and life-cycle environmental impacts of these alternatives. Topics can include the use of industrial by-products like fly ash or slag for greener concrete or evaluating self-healing materials that extend infrastructure life. Understanding barriers to practical adoption (such as regulatory, performance, or supply challenges) is also critical. Sustainable materials research directly supports global climate action and green construction goals. …… [For more click here]
Research Article, Pages: 36-60;
Title:-AI and Machine Learning for Structural Health Monitoring
Authors: Abdulwahab Owaidh Saud Aloufi, Eisi Ghanem Aljohani, Abdulmajeed AouidhAlaofi & Amani Abdulmunaem Alhaisoni
Abstract: The application of AI and machine learning in assessing the condition of structures is rapidly expanding, moving beyond traditional methods to data-driven approaches that can identify damage earlier and more accurately. This topic involves using sensor data, vibration records, and visual inputs (e.g., from drones or cameras) to train predictive models for detecting faults like cracks, corrosion, or deformation. A key research area is domain adaptation — teaching models trained on one type of structure or environment to work reliably on others with different conditions. Researchers can explore how to make these models more interpretable, trustworthy, and generalizable for field use. Such work enhances infrastructure safety and reduces the need for costly manual inspections. Integrating physical modeling with AI is a cutting-edge challenge in this field. …… [For more click here]
Research Article, Pages: 61-84;
Title:-Climate-Resilient Infrastructure Design
Authors: Auhedur Rahman & Ismoth Zerine
Abstract:-Climate change is increasing the frequency and severity of extreme weather events, making it essential for civil engineers to design infrastructure that withstands floods, heatwaves, hurricanes, and rising sea levels. Research can focus on adaptive structural design methods, such as elevated transportation corridors, flood-resilient bridges, or permeable pavement systems that reduce stormwater runoff. Another angle is modeling future climate scenarios and integrating them into design standards and safety margins. Researchers can also investigate materials and structural systems that maintain functionality after extreme loads or require minimal repair. This topic is vital for ensuring infrastructure longevity and protecting communities from climate risks. …… [For more click here]