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Full-Text Articles in Engineering
An Improved Genetic Algorithm Based Fractional Open Circuit Voltage Mppt For Solar Pv Systems, Aakash Hassan, Octavian Bass, Mohammad A. S. Masoum
An Improved Genetic Algorithm Based Fractional Open Circuit Voltage Mppt For Solar Pv Systems, Aakash Hassan, Octavian Bass, Mohammad A. S. Masoum
Research outputs 2022 to 2026
To extract the maximum power from solar PV, maximum power point tracking (MPPT) controllers are needed to operate the PV arrays at their maximum power point under varying environmental conditions. Fractional Open Circuit Voltage (FOCV) is a simple, cost-effective, and easy to implement MPPT technique. However, it suffers from the discontinuous power supply and low tracking efficiency. To overcome these drawbacks, a new hybrid MPPT technique based on the Genetic Algorithm (GA) and FOCV is proposed. The proposed technique is based on a single decision variable, reducing the complexity and convergence time of the algorithm. MATLAB/Simulink is used to test …
Harnessing The Power Of Neural Networks For The Investigation Of Solar-Driven Membrane Distillation Systems Under The Dynamic Operation Mode, Pooria Behnam, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani
Harnessing The Power Of Neural Networks For The Investigation Of Solar-Driven Membrane Distillation Systems Under The Dynamic Operation Mode, Pooria Behnam, Masoumeh Zargar, Abdellah Shafieian, Amir Razmjou, Mehdi Khiadani
Research outputs 2022 to 2026
Accurate modeling of solar-driven direct contact membrane distillation systems (DCMD) can enhance the commercialization of these promising systems. However, the existing dynamic mathematical models for predicting the performance of these systems are complex and computationally expensive. This is due to the intermittent nature of solar energy and complex heat/mass transfer of different components of solar-driven DCMD systems (solar collectors, MD modules and storage tanks). This study applies a machine learning-based approach to model the dynamic nature of a solar-driven DCMD system for the first time. A small-scale rig was designed and fabricated to experimentally assess the performance of the system …
Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Pymaivar: An Open-Source Python Suit For Audio-Image Representation In Human Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar
Research outputs 2022 to 2026
We present PyMAiVAR, a versatile toolbox that encompasses the generation of image representations for audio data including Wave plots, Spectral Centroids, Spectral Roll Offs, Mel Frequency Cepstral Coefficients (MFCC), MFCC Feature Scaling, and Chromagrams. This wide-ranging toolkit generates rich audio-image representations, playing a pivotal role in reshaping human action recognition. By fully exploiting audio data's latent potential, PyMAiVAR stands as a significant advancement in the field. The package is implemented in Python and can be used across different operating systems.
A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung
A Survey On Artificial Intelligence-Based Acoustic Source Identification, Ruba Zaheer, Iftekhar Ahmad, Daryoush Habibi, Kazi Y. Islam, Quoc Viet Phung
Research outputs 2022 to 2026
The concept of Acoustic Source Identification (ASI), which refers to the process of identifying noise sources has attracted increasing attention in recent years. The ASI technology can be used for surveillance, monitoring, and maintenance applications in a wide range of sectors, such as defence, manufacturing, healthcare, and agriculture. Acoustic signature analysis and pattern recognition remain the core technologies for noise source identification. Manual identification of acoustic signatures, however, has become increasingly challenging as dataset sizes grow. As a result, the use of Artificial Intelligence (AI) techniques for identifying noise sources has become increasingly relevant and useful. In this paper, we …
Passive Cooling Analysis Of An Electronic Chipset Using Nanoparticles And Metal-Foam Composite Pcm: An Experimental Study, Faisal Hassan, Abid Hussain, Furqan Jamil, Adeel Arshad, Hafiz Muhammad Ali
Passive Cooling Analysis Of An Electronic Chipset Using Nanoparticles And Metal-Foam Composite Pcm: An Experimental Study, Faisal Hassan, Abid Hussain, Furqan Jamil, Adeel Arshad, Hafiz Muhammad Ali
Research outputs 2022 to 2026
Thermal management of electronic components is critical for long-term reliability and continuous operation, as the over-heating of electronic equipment leads to decrement in performance. The novelty of the current experimental study is to investigate the passive cooling of electronic equipment, by using nano-enriched phase change material (NEPCM) with copper foam having porosity of 97 %. The phase change material of PT-58 was used with graphene nanoplatelets (GNPs) and magnesium oxide (MgO) nanoparticles (NPs), having concentrations of 0.01 wt. % and 0.02 wt. %. Three power levels of 8 W, 16 W, and 24 W, with corresponding heating inputs of 0.77 …
Optimal Sizing And Energy Scheduling Of Grid-Supplemented Solar Pv Systems With Battery Storage: Sensitivity Of Reliability And Financial Constraints, Aakash Hassan, Yasir M. Al-Abdeli, Martin Masek, Octavian Bass
Optimal Sizing And Energy Scheduling Of Grid-Supplemented Solar Pv Systems With Battery Storage: Sensitivity Of Reliability And Financial Constraints, Aakash Hassan, Yasir M. Al-Abdeli, Martin Masek, Octavian Bass
Research outputs 2022 to 2026
Establishing reliable, clean, and inexpensive solar PV systems is a complex interplay between the level of reliability (LPSP), financial constraints, and CO2 emissions. This paper investigates the impact of these factors on stand-alone (SA) and grid-supplemented (GS) solar PV systems over multiple seasons. The research uses established hardware models, detailed power management strategies as well as realistic Australian grid tariffs and Genetic Algorithms to find the minimum Cost of Energy (COE) subject to LPSP and financial constraints. The developed power management strategies are also tested experimentally on a real solar PV system. The results indicate that the grid-supplemented system yields …
High Latency Unmanned Ground Vehicle Teleoperation Enhancement By Presentation Of Estimated Future Through Video Transformation, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed Mohammed Shamsul Islam
High Latency Unmanned Ground Vehicle Teleoperation Enhancement By Presentation Of Estimated Future Through Video Transformation, Md Moniruzzaman, Alexander Rassau, Douglas Chai, Syed Mohammed Shamsul Islam
Research outputs 2022 to 2026
Long-distance, high latency teleoperation tasks are difficult, highly stressful for teleoperators, and prone to over-corrections, which can lead to loss of control. At higher latencies, or when teleoperating at higher vehicle speed, the situation becomes progressively worse. To explore potential solutions, this research work investigates two 2D visual feedback-based assistive interfaces (sliding-only and sliding-and-zooming windows) that apply simple but effective video transformations to enhance teleoperation. A teleoperation simulator that can replicate teleoperation scenarios affected by high and adjustable latency has been developed to explore the effectiveness of the proposed assistive interfaces. Three image comparison metrics have been used to fine-tune …