Omer A. Alawi

ORCID: 0000-0002-8598-4461
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About
Contact & Profiles
Research Areas
  • Nanofluid Flow and Heat Transfer
  • Solar Thermal and Photovoltaic Systems
  • Heat Transfer and Optimization
  • Heat Transfer Mechanisms
  • Solar-Powered Water Purification Methods
  • Heat Transfer and Boiling Studies
  • Photovoltaic System Optimization Techniques
  • Building Energy and Comfort Optimization
  • Fluid Dynamics and Turbulent Flows
  • Hydrological Forecasting Using AI
  • Diamond and Carbon-based Materials Research
  • Solar Radiation and Photovoltaics
  • Energy Load and Power Forecasting
  • Thermodynamic and Exergetic Analyses of Power and Cooling Systems
  • Fuel Cells and Related Materials
  • Hydrology and Watershed Management Studies
  • Air Quality Monitoring and Forecasting
  • Power Transformer Diagnostics and Insulation
  • Advanced Thermodynamics and Statistical Mechanics
  • Refrigeration and Air Conditioning Technologies
  • Energy and Environment Impacts
  • Meteorological Phenomena and Simulations
  • Smart Grid Energy Management
  • Energy Efficiency and Management
  • Hydrology and Sediment Transport Processes

University of Technology Malaysia
2016-2025

University of Buraimi
2025

Thi Qar University
2022-2024

Al-Ayen University
2022-2024

Malaysia University of Science and Technology
2023

Ton Duc Thang University
2019

Komar University of Science and Technology
2015

10.1016/j.ijheatmasstransfer.2017.09.133 article EN International Journal of Heat and Mass Transfer 2017-10-12

Hybrid concentrating solar power (CSP) plants with thermal energy storage (TES) and biomass backup enhance reliability efficiency. TES provides during low sunlight or high demand, while continuous heat generation when is depleted. Therefore, the current study developed three tree optimizers (fine, medium, coarse) to predict profitability factor (PF) for hybridized CSP combined technologies. The PF was predicted based on different operating cases such as parabolic trough-base case-no...

10.1038/s41598-025-87584-6 article EN cc-by-nc-nd Scientific Reports 2025-02-11

River sedimentation is an important indicator for ecological and geomorphological assessments of soil erosion within any watershed region. Sediment transport in a river basin therefore multifaceted field yet being dynamic task nature. It characterized by high stochasticity, non-linearity, non-stationarity, feature redundancy. Various artificial intelligence (AI) modeling frameworks have been introduced to solve sediment problems. The present survey designed provide updated account the latest...

10.1080/19942060.2021.1984992 article EN cc-by Engineering Applications of Computational Fluid Mechanics 2021-01-01
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