Bokai Liu

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Sweden

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Recent Grants

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Multi-scale and Multi-tier Modeling for sustainable building thermal comfort and energy efficiency with Bio-PCMs in northern Sweden

Open Date: 2023-06-01

Close Date: 2024-06-01

Grant: Close

Folding buildings – Intelligent industrial buildings.

Open Date: 2021-01-01

Close Date:

Grant: Close

STIBET Deutscher Akademischer Austauschdienst (DAAD-STIBET)

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· The Excellent Doctoral Degree Completion Scholarships

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Articles (13)

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2025

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2025

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2025

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2024

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2024

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2020

Collaborators (2)

bac nam vu

Leibniz University Hannover

GERMANY

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Kailun Feng

Umea University

SWEDEN

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Bokai Liu

Research Interests

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Contact this professor

Recent Grants

Articles (13)

Explainable machine learning for multiscale thermal conductivity modeling in polymer nanocomposites with uncertainty quantification

A prediction model for dyke-dam piping based on data augmentation and interpretable ensemble learning

Explainable Artificial Intelligence (XAI) for Material Design and Engineering Applications: A Quantitative Computational Framework

Multi-scale modeling in thermal conductivity of Polyurethane incorporated with Phase Change Materials using Physics-Informed Neural Networks

Stochastic interpretable machine learning based multiscale modeling in thermal conductivity of Polymeric graphene-enhanced composites

Al-DeMat: A web-based expert system platform for computationally expensive models in materials design

Data-driven quantitative analysis of an integrated open digital ecosystems platform for user-centric energy retrofits: A case study in northern Sweden

Prediction of bending strength of glass fiber reinforced methacrylate-based pipeline UV-CIPP rehabilitation materials based on machine learning

Stochastic full-range multiscale modeling of thermal conductivity of Polymeric carbon nanotubes composites: A machine learning approach

Stochastic integrated machine learning based multiscale approach for the prediction of the thermal conductivity in carbon nanotube reinforced polymeric composites

Surrogate models in machine learning for computational stochastic multi-scale modelling in composite materials design

A stochastic multiscale method for the prediction of the thermal conductivity of Polymer nanocomposites through hybrid machine learning algorithms

Stochastic multiscale modeling of heat conductivity of Polymeric clay nanocomposites

Collaborators (2)

bac nam vu

Kailun Feng

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