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Civil Engineering Science and Technology (CEST)
Published by Universitas Sains Dan Teknologi Komputer
ISSN : 30896908     EISSN : 30896894     DOI : 10.51903
Core Subject : Engineering,
Civil Engineering, Building, Construction & Architecture Engineering Mechanical Engineering
Aim The Civil Engineering Science and Technology (CEST) journal aims to serve as a high-quality scientific publication platform dedicated to the field of civil engineering. The journal focuses on the scientific and technological aspects that contribute to the advancement of methods, materials, and innovations in civil engineering. CEST facilitates the dissemination of cutting-edge research findings that enhance both theoretical understanding and practical applications in the civil engineering industry. By providing a forum for academics, researchers, and practitioners, the journal encourages interdisciplinary collaboration and fosters global advancements in civil engineering science and technology. Scope CEST covers a broad range of topics within civil engineering, including but not limited to: Soil and Rock Mechanics – Studies on geotechnical properties, foundation engineering, slope stability, and soil-structure interactions. Structures and Materials – Research on structural analysis, construction materials, seismic engineering, and innovative building techniques. Hydraulic and Hydrology – Water resources management, fluid mechanics, river engineering, and coastal protection systems. Transportation and Infrastructure – Roadway and railway engineering, traffic management, urban mobility, and smart transportation systems. Environment and Resource Management – Sustainable construction, waste management, climate resilience, and eco-friendly engineering solutions. Information and Computing Technology in Civil Engineering – Applications of AI, BIM (Building Information Modeling), GIS, and digital twin technology in civil engineering. Innovation and Technological Development in Civil Engineering – Emerging trends, automation, robotics, and new methodologies for construction and infrastructure development. Case Studies and Practical Applications – Real-world civil engineering projects, lessons learned, and best practices in various construction domains. By covering these diverse areas, CEST aims to bridge the gap between research and industry, fostering technological innovation and sustainable development in civil engineering.
Arjuna Subject : Teknik (semua kategori) - Teknik Sipil dan Struktur
Articles 4 Documents
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Search results for , issue "Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology)" : 4 Documents clear
Integrating Predictive AI Models to Bridge Energy Efficiency Gaps in Smart Building Design Sugiarto, Sugiarto; Christopher, Liam; Grace, Amelia
Civil Engineering Science and Technology Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology)
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/2fwp7m63

Abstract

Energy efficiency has become one of the most important aspects in smart building design, especially considering the gap that has increasingly been noted between simulated energy performance and actual consumption. Even though digital design tools like BIM have enhanced design capabilities, there is still a big gap in energy performance, usually rooted in the static nature of traditional simulations. This research tries to respond to this challenge by proposing a conceptual framework linking predictive AI models with BIM for enhanced accuracy in early design stage forecasting. Other than a few studies that revolved around optimization in the post-occupancy phase, this study applies a conceptual-simulative methodology by using a synthetic BIM model of a medium-sized office building. Machine learning algorithms, such as random forest and gradient boosting, were trained on parameterized design data for predicting EUI. Strong predictive consistency was identified with an R² of 0.89 between the predicted and simulated EUI and a conceptual reduction of the performance gap of about 18%. The model also shows robust logical correspondence to the concepts of energy efficiency within a wide range of design scenarios. This research concludes that predictive AI can significantly improve energy performance forecasting in smart building design and provides a proactive data-driven approach toward overcoming the energy efficiency gap in support of more sustainable architectural practices without immediate physical field testing.
Integrating Climate-Resilient Design And Life Cycle Costing In Green Building Projects: A Simulation-Based Assessment In Tropical Urban Areas Arifin, Samsul; Setiyadi, Angga; Purwanto, Purwanto; Sugiarto, Sugiarto
Civil Engineering Science and Technology Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology)
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/3cq4x038

Abstract

Tropical urban areas are increasingly exposed to the compounded impacts of climate change, including rising temperatures, high humidity, and increased rainfall, which pose challenges to the long-term performance, durability, and cost-efficiency of green buildings. This study integrates climate-resilient building design strategies with Life Cycle Costing (LCC) to evaluate both the technical performance and long-term economic feasibility of green building projects in tropical urban environments. A simulation-based building performance assessment was conducted to model key microclimatic variables, solar radiation, thermal loads, and precipitation, and their impacts on building envelope performance, passive cooling strategies, and water management systems. Simulation outputs were incorporated into an LCC framework to compare multiple design scenarios over a 30-year operational lifecycle. The results indicate that climate-resilient design alternatives reduce annual building energy demand by approximately 15–25% and lower total life-cycle costs by 10–18% compared to baseline green-building configurations, despite an initial capital cost increase of 5–12%. These findings demonstrate that investments in climate-adaptive strategies enhance long-term cost efficiency, operational stability, and resilience to extreme climate conditions in tropical cities. This study provides a coherent simulation-based framework that links environmental performance analysis with life-cycle economic evaluation, offering practical decision-support insights for architects, engineers, developers, and policymakers. By quantitatively revealing trade-offs between initial investment and long-term benefits, the research addresses a critical gap in current green building assessment practices and supports the development of financially viable and climate-resilient urban building solutions.
Valorization Of Industrial Ash Waste As Eco-Friendly Binder For Pavement Applications: Experimental Study On Strength And Permeability Properties Alexis, Ruben; Huereca, Camacho
Civil Engineering Science and Technology Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology)
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/fd9z5952

Abstract

As the construction industry faces increasing pressure to reduce its environmental footprint, the use of industrial byproducts as alternative construction materials presents a promising strategy for promoting sustainability. This study investigates the potential valorization of industrial ash waste, particularly fly ash and steel slag, as an eco-friendly binder in permeable pavement applications. The main objective is to engineer a sustainable binder mix that aligns with circular economy principles while maintaining structural and hydraulic performance, particularly in tropical climate conditions. A series of experimental tests was conducted on various ash-based binder formulations to evaluate compressive strength, permeability rate, and durability under simulated tropical environmental exposure. Complementary microstructural analyses using scanning electron microscopy (SEM) and X-ray diffraction (XRD) were also performed to explore the internal bonding characteristics and hydration behavior. The results revealed that specific combinations of fly ash and steel slag achieved compressive strength values comparable to conventional cement-based binders, while exhibiting significantly higher water permeability, an essential feature for stormwater management in urban areas. Moreover, the binder demonstrated good resistance to moisture-induced degradation. These findings suggest that industrial ash waste can be effectively transformed into high-performance, low-impact materials for green infrastructure. This research contributes to both material innovation and sustainable engineering practices, offering a viable solution for environmentally responsible pavement design in developing countries with tropical climates.
AI-Driven Optimization of Project Cost and Duration in Infrastructure Development Projects Leite, Marcos; Silva, Beatriz
Civil Engineering Science and Technology Vol. 1 No. 2 (2025): October | CEST (Civil Engineering Science and Technology)
Publisher : Universitas Sains dan Teknologi Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/yemg8d35

Abstract

The rapid increase in global infrastructure costs is causing delays, and it is difficult for policy-makers and engineers to generate sustainable and consistent outcomes. In this research study, we provide a framework of artificial intelligence to improve cost and schedule in large-scale infrastructure projects, through aggregated holistic data acquisition, gradient boosted prediction models, and particle-swarms multi-objective optimisation. Using historical project data, current sensor IoT data, digital twin simulation, and drone surveys, we develop a quality dataset for validation and training. The models generated are highly predictive in performance compared to traditional scheduling methods, and robust when material prices vary and/ or labour disruptions apply. In addition we conduct scenario testing to confirm that the framework is able to provide realizable recommendations and allow for adaptive scheduling modifications through the use of interactive dashboards. Being able to provide actual costing estimation and adaptive scheduling in real-time provides construction professionals and PMP's the opportunity to better management site performance thereby reducing overruns and simplifying resource allocation, and also very soon capable of responding to site change. The artificial intelligence approach is a promising route to intelligent, data-driven project positioning artificial intelligence as a viable long-term approach towards saving costs and planning timelines strategically, and sustainable construction project scheduling.  

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