| No. |
Title and Author |
Area |
Country |
Page |
| 1 |
Experimental Study on Fresh and Mechanical Properties of Manufactured Sand and Recycled Aggregate Mixed Self-Compacting Concrete
-Gyanendra Kumar Chaturvedy ; Anushree Vikas Rathod; R. Mahadeva Swamy; M. S. Kuttimarks
Self-compacting concrete (SCC) offers significant construction advantages but relies on natural coarse aggregate and river sand, resources under growing environmental pressure. This study investigates the incorporation of recycled concrete aggregate (RCA) and manufactured sand (M-Sand) as partial and full replacements for these natural constituents, evaluating both fresh and hardened SCC properties. Mixes were developed with RCA and M-Sand substitution levels of 0%, 50%, and 100%, varied independently and in combination, while maintaining a constant water-to-cementitious-materials ratio. Slump flow, 28-day compressive strength, split tensile strength, and flexural strength were assessed for each mix. Results showed a consistent, monotonic decline in all properties with increasing substitution, with RCA exerting the dominant influence due to residual adhered mortar, higher porosity, and elevated water absorption, while M-Sand's effect was comparatively secondary. Despite reductions of up to 15.92% in workability, 30.21% in compressive strength, 19.45% in tensile strength, and 23.98% in flexural strength at full replacement (R100M100), all mixes satisfied EFNARC workability criteria and exceeded IS 456:2000 strength requirements for M25-grade concrete. Flexural strength proved most sensitive to combined substitution, while tensile strength remained comparatively least affected. These findings confirm that RCA and M-Sand, even at full replacement, are technically viable, sustainable alternatives to natural aggregates for standard structural-grade SCC applications, supporting waste diversion and resource conservation in concrete construction. Read More...
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Civil Engineering |
India |
1-4 |
| 2 |
AI-Driven Automated Code Review and Debugging Using Large Language Models
-Chandan G K ; Dr. Basavaraj S Pol; Prof. Manasa K; Dr. Avinasha P S
Software systems are growing in scale and complexity, and ensuring their quality through manual code review and debugging has become increasingly time-consuming, inconsistent, and dependent on the availability of experienced reviewers. This paper presents an AI-Powered Automated Code Review and Code Debugger, referred to as BugFix.AI, which combines static code analysis, machine learning, and large language model (LLM)-based reasoning to detect and correct programming errors with minimal human intervention. The proposed system parses submitted source code, classifies defects such as syntax errors, logical flaws, performance bottlenecks, and non-standard coding practices, and generates context-aware fixes together with human-readable explanations. Suggested corrections are validated through sandboxed execution before being presented to the user, ensuring that no new errors are introduced. The system was implemented using a React.js front end, a Node.js/REST API back end, and GPT-4o for reasoning, and was evaluated on a curated dataset of code samples spanning multiple programming languages. Experimental results show that the system achieves an overall bug-detection F1-score above 74%, reduces manual review effort by a substantial margin, and was rated helpful by a majority of surveyed users. The findings indicate that AI-driven automated review and debugging tools can meaningfully improve developer productivity and code quality while remaining a complement to, rather than a replacement for, human oversight. Read More...
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Computer Science and Information Technology |
India |
5-7 |
| 3 |
Experimental Investigation of Fiber-Reinforced Cement-Stabilized Fly Ash for Pavement Structural Layers
-Amit Kumar Aryan ; Pushpendra Kumar Kushwaha
The increasing generation of fly ash from thermal power plants has created significant challenges related to its disposal and environmental management. At the same time, the construction of pavement infrastructure requires large quantities of suitable materials for subgrade, sub-base, and base layers. The utilization of fly ash as a pavement construction material provides an opportunity to address both problems through sustainable engineering practices. However, the relatively low strength, high compressibility, and sensitivity of untreated fly ash restrict its direct application in structural pavement layers. The present study investigates the improvement of fly ash through stabilization with cement and reinforcement with fibers. Cement was incorporated to promote bonding and pozzolanic reactions, while discrete fibers were introduced to improve tensile resistance, crack control, ductility, and load-transfer characteristics. The engineering behavior of the stabilized and fiber-reinforced fly ash was evaluated using compaction, unconfined compressive strength (UCS), and California Bearing Ratio (CBR) tests. The experimental results indicate that cement stabilization significantly improves the strength characteristics of fly ash. Increasing cement content results in an increase in water demand because of cement hydration and particle interaction. The maximum dry density initially shows minor variation and subsequently increases with cement addition. The addition of fibers further enhances the mechanical performance by providing reinforcement and restricting crack propagation. The combined use of cement and fibers therefore offers considerable potential for converting fly ash into a value-added material for pavement structural layers. The study demonstrates that fiber-reinforced cement-stabilized fly ash can contribute to sustainable pavement construction while reducing dependence on conventional natural aggregates and providing an environmentally beneficial method for fly ash utilization. Read More...
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M.E. (Construction Technology & Management) |
India |
8-11 |