International Journal of Engineering Works

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Styrene Butadiene Rubber and Plastic Bottle Wastes as Sustainable Materials in Hot Mix Asphalt

Published online https://doi.org/

Abstract

Environmental concerns associated with waste tires and plastic bottles have driven the adoption of recycling-based modifiers to enhance pavement performance. This study investigates the feasibility of utilizing Styrene–Butadiene Rubber (SBR) and Plastic Bottle Waste (PBW) as sustainable modifiers in Hot Mix Asphalt (HMA). Modified asphalt mixtures were prepared with PBW and SBR contents ranging from 2% to 10% by weight of the Optimum Binder Content (OBC). The performance of conventional and modified mixtures was evaluated using Marshall Stability, rutting resistance, Indirect Tensile Strength (ITS), and microstructural and chemical characterization through Fourier Transform Infrared Spectroscopy (FTIR) and X-ray Diffraction (XRD). Results indicate that a 6% modifier content provides optimum performance enhancement, leading to significant improvements in stability, tensile strength, rut resistance, thermal stability, and stiffness. Microstructural analyses confirmed improved binder–modifier interactions and enhanced material compatibility. Comparatively, SBR demonstrated superior performance improvements over PBW, indicating its higher effectiveness as an asphalt modifier. In addition to mechanical benefits, the incorporation of SBR and PBW offers substantial environmental advantages by reducing landfill disposal and incineration, thereby lowering the associated carbon footprint. Overall, the findings support the use of recycled SBR and PBW as cost-effective, durable, and environmentally sustainable alternatives for producing high-performance asphalt mixtures, contributing to extended pavement service life and sustainable infrastructure development.

Author

Salman Khan, Fazli Karim, Hafiz Adil Shah, Sangeen Khan

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References

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[6] D. Hussain, H. Ullah, A. Farooq, D. Farooq, F. Karim, Z. Wang, and J. Huang, “Assessing road safety of the Peshawar–Rawalpindi section of National Highway (N-5) in Pakistan using iRAP,” Periodica Polytechnica Transportation Engineering, vol. 53, no. 4, pp. 371–380, Jul. 8, 2025.

[7] N. Khan, F. Karim, Q. B. A. I. L. Qureshi, S. A. Mufti, M. B. A. Rabbani, M. S. Khan, and D. Khan, “Effect of fine aggregates and mineral fillers on the permanent deformation of hot mix asphalt,” Sustainability, vol. 15, no. 13, p. 10646, Jul. 6, 2023.

[8] F. Karim, S. Iqbal, A. Farooq, H. Ullah, and M. Imran, “Comparing the consensus properties of aggregate sources from KP to Margalla using image analysis,” The Sciencetech, vol. 5, no. 3, pp. 50–69, Aug. 24, 2024.

[9] M. B. Khurshid, N. A. Qureshi, A. Hussain, and M. J. Iqbal, “Enhancement of hot mix asphalt (HMA) properties using waste polymers,” Arabian Journal for Science and Engineering, vol. 44, pp. 8239–8248, 2019.

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Investigation of Superelasticity of Iron based Shape Memory Alloy

Vol. 13, Issue 01, PP. 07-12, January 2026

Published online https://doi.org/10.5281/zenodo.18242902

ePub PDF

Abstract

Iron-based shape memory alloys (Fe-SMAs) have recently attracted significant attention as cost-effective and mechanically robust alternatives to conventional Ni–Ti alloys for smart structural and engineering applications. This study investigates the superelastic behavior of an iron-based shape memory alloy through systematic mechanical characterization under controlled loading–unloading conditions. Uniaxial tensile tests were conducted to evaluate stress–strain response, reversible strain capacity, critical transformation stresses, and hysteresis behavior associated with stress-induced martensitic transformation and reverse transformation. The influence of cyclic loading on superelastic stability, energy dissipation, and residual strain accumulation was also examined. Microstructural observations were correlated with mechanical responses to elucidate the role of phase transformation mechanisms in governing superelastic performance. The results demonstrate that the investigated Fe-based alloy exhibits pronounced superelasticity with substantial recoverable strain and stable cyclic behavior, highlighting its potential for applications in vibration control, seismic damping, and adaptive structural components. The findings provide fundamental insight into the deformation and recovery mechanisms of Fe-based SMAs and contribute to the development of reliable, large-scale superelastic materials for civil and mechanical engineering systems.

Author

Hamza Kamran, Rana Atta ur Rahman, Ahmed Usman Yasir

Cite

Hamza Kamran, Rana Atta ur Rahman, Ahmed Usman Yasir “Investigation of Superelasticity of Iron based Shape Memory Alloy” International Journal of Engineering Works, Vol. 13, Issue 01, PP. 07-12, January 2026. https://doi.org/10.5281/zenodo.18242902.

References

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Detetion and Prevention of Irrelevent Data Through Data Cleansing

Published online https://doi.org/

Abstract

A file oriented unstructured data collected and transformed into the data warehouse .Two or more records identified separately actually represent same real world entity, detection and prevention to improve data quality. The proposed technique introduces smart tokens of most representative attributes by sorting those tokens identical records are bring into close neighborhood, record duplicates are identified and removed from the data. Clean consistent and non duplicated data loaded into warehouse. The technique is a mile stone for cleaning data as with the explosive amount of data recording it is the need of time that more corrected data to be provided to the data mangers for effective decisions making.

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Current Issue - 2026

Neural Network based Portable Spectrometer for Fluid Classification

Vol. 13, Issue 01, PP. 01-06, January 26

Published online https://doi.org/10.5281/zenodo.18183364

ePub PDF

Abstract

The spectrometer, a powerful analytical instrument, plays a vital role in the fields of Chemistry, Material Sciences, Biochemistry, and Physics by allowing researchers to test, discover, and measure the spectral content of various fluids. This paper details the development of a portable, lightweight, cost-effective spectrometer device, which incorporates artificial intelligence for fluid classification. In a practical application, milk is used as the test fluid, with different qualities achieved by introducing controlled impurities. The spectrometer collected spectral data using a camera sensor, and the dataset is subsequently randomized and divided into training and testing data. Employing a range of machine learning algorithms and neural networks, the device accurately predicts the class of the fluid. The integration of optical components and microcontrollers facilitated model deployment. Notably, this device provides real-time fluid classification and displays results on an Organic LED. Beyond milk, its versatility allows for quality analysis of various fluids containing impurities, such as gasoline, human blood, and saliva. Remarkably compact at 70 x 70 x 50 mm and lightweight at 0.2 kilograms, the device had achieved an impressive average accuracy of 93.45 percent. It stands out for its ease of use, recharge ability, accuracy, and cost effectiveness compared to traditional spectrophotometers, positioning it as a valuable tool in the realm of scientific research and quality assessment.

Author

Hassan Nawazish Rasool, Muhammad Zeb

Cite

Hassan Nawazish Rasool, Muhammad Zeb “Neural Network based Portable Spectrometer for Fluid Classification” Internationa, Vol. 13, Issue 01, PP. 01-06, January 2026. https://doi.org/10.5281/zenodo.18183364.,

References

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[8] L. L. Monteiro, P. Zoio, B. B. Carvalho, L. P. Fonseca, and C. R. C. Calado, “Quality Monitoring of Biodiesel and Diesel/Biodiesel Blends: A Comparison between Benchtop FT-NIR versus a Portable Miniaturized NIR Spectroscopic Analysis,” Processes, vol. 11, no. 4, 2023, doi: 10.3390/pr11041071.

[9] R. M. Correia et al., “Portable near infrared spectroscopy applied to fuel quality control,” Talanta, vol. 176, no. August 2017, pp. 26–33, 2018, doi: 10.1016/j.talanta.2017.07.094.

F. D. Santos et al., “Discrimination of oils and fuels using a portable NIR spectrometer,” Fuel, vol. 283, no. August 2020, p. 118854, 2021, doi: 10.1016/j.fuel.2020.118854.

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Neural Network based Portable Spectrometer for Fluid Classification

Vol. 13, Issue 01, PP. 01-06, January 26

Published online https://doi.org/10.5281/zenodo.18183364

ePub PDF

Abstract

Author

Hassan Nawazish Rasool, Muhammad Zeb

Cite

References

[5] K. Laganovska et al., “Portable low-cost open-source wireless spectrophotometer for fast and reliable measurements,” HardwareX, vol. 7, p. e00108, 2020, doi: 10.1016/j.ohx.2020.e00108.

[9] R. M. Correia et al., “Portable near infrared spectroscopy applied to fuel quality control,” Talanta, vol. 176, no. August 2017, pp. 26–33, 2018, doi: 10.1016/j.talanta.2017.07.094.

F. D. Santos et al., “Discrimination of oils and fuels using a portable NIR spectrometer,” Fuel, vol. 283, no. August 2020, p. 118854, 2021, doi: 10.1016/j.fuel.2020.118854.