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プロフィール詳細
プロジェクトを作成
★★★★★
☆☆☆☆☆
Dr. Mohammad H.に依頼
United Kingdom

Climate Tech & Sustainable Engineering Consultant | AI · CFD · Circular Economy | RAEng Global Talent

プロフィール概要
専門分野
サービス
Writing Technical Writing
Research Feasibility Study, Scientific and Technical Research, Systematic Literature Review
Consulting Business Strategy Consulting, Go-to-Market Strategy Consulting, Digital Strategy Consulting, Operations Consulting, Scientific and Technical Consulting
Data & AI Predictive Modeling, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Data Processing, Data Insights
Product Development Formulation, Product Evaluation, Product Validation, Reverse Engineering
職務経験

University of Hertfordshire

- 現在

Managing Director/Co-Founder

Inshira Technologies LTD.

11月 2025 - 現在

Research Manager/Visiting Lecturer

University of Hertfordshire

5月 2021 - 現在

Managing Director/Co-Founder

JHT International

7月 2020 - 現在

Postgraduate Researcher/Project Engineer

University of Bolton

1月 2019 - 12月 2020

学歴

PhD in Sustainable Energy and Engineering Technologies (School of Physics, Engineering and Computer Science)

University of Hertfordshire

5月 2021 - 12月 2024

MRes Engineering Management (Distinction) (School of Engineering)

University of Bolton

1月 2019 - 2月 2020

BEng (Hons) Automotive Performance Engineering (First-Class) (School of Engineering)

University of Bolton

9月 2015 - 7月 2018

認定資格

  • Fellow of Higher Education Academy

    AdvanceHE

    1月 2026 - 現在

出版物
JOURNAL ARTICLE
Zhigen Wu, Zihan Yan, Chenzhen Ji, Dan Zhou, Mohammad Harris, Hongwei Wu (2025). Synthesis and sustainable application of fluorosilicon-based superhydrophobic coatings for high-salt wastewater treatment: A short two-step method . Energy & Environmental Sustainability.
Implementing Circular Economy Principles in Micro Heat Sink Development: A Techno-Economic-Sustainability Analysis @article{329966e5afb243fd85ffac17e1d9a4b5, title = "Implementing Circular Economy Principles in Micro Heat Sink Development: A Techno-Economic-Sustainability Analysis", abstract = "Sustainable manufacturing solutions are urgently needed with rising environmental pressures and cost volatility. This paper investigates sustainable product development strategies for micro heat sinks by integrating circular economy principles, emerging technologies, and green manufacturing practices. Analysing a UK–China cross-case hybrid production model, the study compares strategies in terms of energy efficiency, cost savings, and environmental impact. The hybrid approach balances economic, ecological, and resource consumption goals by producing simpler components inhouse while outsourcing complex parts. Results show a 19\% reduction in carbon emissions, 29\% energy savings, and 43\% cost reduction. Sustainable design, green manufacturing, and end-of-life management further contribute to environmental benefits. Machine learning models validated the cost-saving outcomes, achieving R² values exceeding 0.98. Finally, the study proposes a Sustainable Hybrid Intelligence Framework (SHIF) to demonstrate the feasibility of hybrid manufacturing as a sustainable solution for future micro heat sink production.", author = "Mohammad Harris and Hongwei Wu", note = "{\textcopyright} 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)", year = "2025", month = oct, day = "10", doi = "10.1016/j.jclepro.2025.146731", language = "English", volume = "527", journal = "Journal of Cleaner Production", issn = "0959-6526", publisher = "Elsevier", } . Journal of Cleaner Production.
Mohammad Harris, Hongwei Wu (2025). Implementing circular economy principles in micro heat sink development: A techno-economic-sustainability analysis . Journal of Cleaner Production.
Harris, M. and Wu, H., 2025. Implementing Circular Economy Principles in Micro Heat Sink Development: A Techno-Economic-Sustainability Analysis. Journal of Cleaner Production 527 (October):146731 .
Assessing Thermohydraulic Performance in Novel Micro Pin-Fin Heat Sinks: A Synergistic Experimental, Agile Manufacturing, and Machine Learning Approach @article{705591c35e1f434eb21aa2944173dc3f, title = "Assessing Thermohydraulic Performance in Novel Micro Pin-Fin Heat Sinks: A Synergistic Experimental, Agile Manufacturing, and Machine Learning Approach", abstract = "As advancements in technology and rapid product development redefine engineering paradigms, this study examines the influence of innovative and bio-inspired designs on heat transfer efficiency. The research evaluates the thermohydraulic performance of new biomorphic pin fins employing various strategic approaches and agile manufacturing techniques to optimise the design process. Experimental assessments were conducted on four hybrid pin fin configurations within Reynolds Numbers ranging from 101 to 507 and power outputs of 150W and 250W. The investigation focused on how different geometrical features impact critical performance metrics, including the Nusselt Number, thermal resistance, and pressure drop. Results indicate a significant enhancement in heat transfer performance, ranging from 25\% to 45\%, compared to traditional designs, even at lower Reynolds Numbers and energy consumption levels. Additionally, new empirical correlations were developed specifically for these hybrid designs. Machine learning models demonstrated high accuracy in predicting the Nusselt Number, using Reynolds and Prandtl Numbers as key variables, achieving a mean absolute percentage error (MAPE) of less than 3.5\% and an R² value exceeding 0.95. Among the models evaluated, XGBoost, Random Forest, and Polynomial Regression exhibited superior performance with both real and synthetic data. This study underscores the potential of unconventional biomorphic geometries, highlighting the benefits of agile manufacturing and cutting-edge technologies in optimising resource use and improving predictive accuracy. The findings advocate for a reassessment of traditional heat sink designs and propose promising directions for future research in advanced sustainable thermal management.", keywords = "Heat transfer, Machine learning, Micro pin-fins, Mini and microchannels, Thermal management", author = "Mohammad Harris and Hamza Babar and Hongwei Wu", note = "{\textcopyright} 2024 The Author(s). Published by Elsevier Ltd. This is an open access article distributed under the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/ ", year = "2025", month = apr, day = "30", doi = "10.1016/j.ijheatmasstransfer.2024.126581", language = "English", volume = "239", pages = "1--21", journal = "International Journal of Heat and Mass Transfer", issn = "0017-9310", publisher = "Elsevier", } . International Journal of Heat and Mass Transfer.
Mohammad Harris, Hamza Babar, Hongwei Wu (2025). Assessing thermohydraulic performance in novel micro pin-fin heat sinks: A synergistic experimental, agile manufacturing, and machine learning approach . International Journal of Heat and Mass Transfer.
Mohammad Harris, Hongwei Wu, Anastasia Angelopoulou, Wenbin Zhang, Zhuohuan Hu, Yongqi Xie (2024). Heat transfer optimisation using novel biomorphic pin-fin heat sinks: An integrated approach via design for manufacturing, numerical simulation, and machine learning . Thermal Science and Engineering Progress.
Heat transfer optimisation using novel biomorphic pin-fin heat sinks: An integrated approach via design for manufacturing, numerical simulation, and machine learning @article{c9d588708edd46c3bebfca45b079a236, title = "Heat transfer optimisation using novel biomorphic pin-fin heat sinks: An integrated approach via design for manufacturing, numerical simulation, and machine learning", abstract = "With the availability of advanced manufacturing techniques, non-conventional shapes and bio-inspired/biomorphic designs have shown to provide more efficient heat transfer. Consequently, this research investigates the heat transfer performance and fluid flow characteristics of novel biomorphic scutoid pin fins with varying volumes and top geometries. Numerical simulations were conducted using four hybrid designs for Reynolds Number 5500 - 13500. The impact of pin fin 'top' geometrical features on the heat transfer coefficient (HTC) was evaluated by combining computational fluid dynamics (CFD), experimental data, and machine learning. The results highlighted that the new pin fins saved 6.3\% to 14.3\% volume/material usage but produced around 1.5 to 1.7 times more heat transfer than conventional square/rectangular fins. Also, manipulating pin fins via the top geometrical properties can lead to more uniform velocity and temperature distributions while demonstrating the potential for increased thermal efficiency with reduced thermal resistance. Furthermore, six machine learning models accurately predict HTC using volume and surface area as key variables, achieving less than 5\% mean absolute percentage error (MAPE). Overall, this research introduces innovative biomorphic designs with unconventional geometries, emphasising resource optimisation and efficient HTC prediction using machine learning. It simplifies design processes, supports agile product development, calls for re-evaluation of conventional heat sink geometries, and provides promising directions for future research.", author = "Mohammad Harris and Hongwei Wu and Anastasia Angelopoulou and Wenbin Zhang and Zhuohuan Hu and Yongqi Xie", note = "{\textcopyright} 2024 The Author(s). Published by Elsevier Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/", year = "2024", month = may, day = "1", doi = "10.1016/j.tsep.2024.102606", language = "English", volume = "51", pages = "1--21", journal = "Thermal Science and Engineering Progress", issn = "2451-9049", publisher = "Elsevier", } . Thermal Science and Engineering Progress.
Mohammad Harris(2022). Overview of Recent Trends in Microchannels for Heat Transfer and Thermal Management Applications . Chemical Engineering and Processing - Process Intensification. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 109155. Elsevier {BV}
Harris, M., Wu, H., Zhang, W., Angelopoulou, A.(2022). Overview of recent trends in microchannels for heat transfer and thermal management applications . Chemical Engineering and Processing - Process Intensification. 181.
An Investigation on Engine Mass Airflow Sensor Production via TQM, TPM, and Six Sigma Practices <head> <META HTTP-EQUIV="Refresh" CONTENT="0;URL=/servlet/useragent"> </head> . Operations Research Forum.
Harris, M.(2021). An Investigation on Engine Mass Airflow Sensor Production via TQM, TPM, and Six Sigma Practices . Operations Research Forum. 2. (4).
Harris, M., Ndiaye, M. and Farrell, P., 2020. Integration of Industry 4.0 and Internet of Things in the Automotive and Motorsports Sectors: An Empirical Analysis (No. 2020-01-5079). SAE Technical Paper .
Mohammad Harris, Mamadou Ndiaye, Peter Farrell(2020). Integration of Industry 4.0 and Internet of Things in the Automotive and Motorsports Sectors . SAE Technical Papers. 2020-January. SAE International
DISSERTATION THESIS
Mohammad Harris (2025). Enhancing Heat Transfer and Thermal Management Efficiency in Micro Heat Sinks through Machine Learning Algorithms . University of Hertfordshire Research Archive.
CONFERENCE PAPER
Comparative Analysis of Micro/Minichannel Flow Boiling Pattern Recognition and Classification using a Combined CNN-Clustering Algorithms Approach @inproceedings{d7971ab3cacd4ce3b97909273d57a11e, title = "Comparative Analysis of Micro/Minichannel Flow Boiling Pattern Recognition and Classification using a Combined CNN-Clustering Algorithms Approach", abstract = "Microchannel heat sinks have attracted considerable attention in thermal management applications owing to their high heat transfer capabilities and compact size. Amongst the cooling techniques, flow boiling in microchannels has emerged as a promising method for efficient heat dissipation. However, the intricate flow patterns in microchannels present challenges for accurate classification, pattern recognition, and inefficient data handling practices. This paper presented a comparative analysis of flow boiling classification techniques for pattern recognition in microchannel heat sinks. Three different clustering algorithm-driven convolutional neural networks (CNNs) were analysed and compared alongside a base CNN to establish a data pipeline capable of agile flow boiling pattern recognition. The Gaussian Mixture Model Clustering-based CNN exhibited the best performance, achieving an overall mean accuracy of 88\% for the test set validation. Thus, this study lays the groundwork for improving the performance of flow boiling pattern recognition in microchannel heat sinks.", keywords = "case study, clustering algorithm, flow boiling, image analysis, pattern recognition, thermal management", author = "Mohammad Harris and Anastasia Angelopoulou and Hongwei Wu and Wenbin Zhang", note = "{\textcopyright}2024 IEEE.; IEEE 14th International Conference on Pattern Recognition Systems (ICPRS) 2024, IEEE ICPRS 2024 ; Conference date: 15-07-2024 Through 18-07-2024", year = "2024", month = jul, day = "18", doi = "10.1109/ICPRS62101.2024.10677840", language = "English", isbn = "979-8-3503-7566-4", booktitle = "2024 14th International Conference on Pattern Recognition Systems, ICPRS", publisher = "Institute of Electrical and Electronics Engineers (IEEE)", address = "United States", url = "https://icprs.org/", } . 2024 14th International Conference on Pattern Recognition Systems, ICPRS.
Harris, M., Angelopoulou, A., Wu, H. and Zhang, W., 2024, July. Comparative Analysis of Micro/Minichannel Flow Boiling Pattern Recognition and Classification using a Combined CNN-Clustering Algorithms Approach. In 2024 14th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1-9). IEEE .
Investigating Heat Transfer and Flow Characteristics under Different Wall Heating Conditions in Novel Micro Pin-Fin Heat Sinks @inproceedings{63e1dfa676b3437a82f1e2e401c37403, title = "Investigating Heat Transfer and Flow Characteristics under Different Wall Heating Conditions in Novel Micro Pin-Fin Heat Sinks", abstract = "The escalating power density in electronic devices demands effective and sustainable heat dissipation solutions. Micro pin-fin designs offer potential enhancements to thermal management in electronic cooling. Consequently, this short paper numerically investigates heat transfer and flow characteristics in micro pin-fin heating under distinct wall heating conditions. The results indicate that the new scutoid design exhibits a commendable heat transfer coefficient of 3298 W/m²K, with the lowest pressure drop and operating base temperatures. Thus, the findings provide a foundation for future designs and efficient heat transfer strategies.", keywords = "CFD, heat sinks, heat transfer, micro pin-fins, microchannels.`, thermal management", author = "Mohammad Harris and Hongwei Wu and Jianfei Sun", note = "{\textcopyright} 2024, Avestia Publishing. All rights reserved. This is the accepted manuscript version of a conference paper which has been published in final form at https://doi.org/10.11159/enfht24.328; 9th World Congress on Momentum, Heat and Mass Transfer (MHMT 2024), MHMT 2024 ; Conference date: 11-04-2024 Through 13-04-2024", year = "2024", month = apr, day = "13", doi = "10.11159/enfht24.328", language = "English", isbn = "9781990800344", series = "Proceedings of the World Congress on Momentum, Heat and Mass Transfer", publisher = "Avestia Publishing", pages = "1--4", editor = "Lixin Cheng and Karayiannis, \{Tassos G.\} and Sohel Murshed", booktitle = "Proceedings of the 9th World Congress on Momentum, Heat and Mass Transfer (MHMT'24)", url = "https://mhmtcongress.com/", } . Proceedings of the 9th World Congress on Momentum, Heat and Mass Transfer (MHMT'24).
Mohammad Harris, Hongwei Wu, Jianfei Sun (2024). Investigating Heat Transfer and Flow Characteristics under Different Wall Heating Conditions in Novel Micro Pin-Fin Heat Sinks . Proceedings of the 9th World Congress on Momentum, Heat and Mass Transfer.
Mohammad Harris, Hongwei Wu, Shohel Mahmud (2023). Numerical Simulation of Heat Transfer Performance in Novel Biomorphic Pin-Fin Heat Sinks . The World Congress on Momentum, Heat and Mass Transfer.
Mohammad Harris, Hongwei Wu(2023). Numerical Simulation of Heat Transfer Performance in Novel Biomorphic Pin-Fin Heat Sinks . Proceedings of the 8th World Congress on Momentum, Heat and Mass Transfer, MHMT 2023. Avestia Publishing
Harris, M., Ndiaye, M., Farrell, P.(2020). Integration of Industry 4.0 and Internet of Things in the Automotive and Motorsports Sectors: An Empirical Analysis . SAE Technical Papers. 2020-January.
OTHER
Mohammad Harris, Hongwei Wu, Shohel Mahmud(2023). Numerical Simulation of Heat Transfer Performance in Novel Biomorphic Pin-Fin Heat Sinks . World Congress on Momentum, Heat and Mass Transfer. Avestia Publishing