TOP-1

The research group will recruit several PHD and master students and 2 postdocs.

There are three requirements for doctoral and master students  enrollment: (1) Applicants should have an engineering background and have a strong interest in information technology. Applicants should have obtained a relevant bachelor's or master's degree; (2) Strong technical background, including but not limited to research experiences in BIM/GIS, Internet, digital twin, artificial intelligence, etc. Candidates with research or practical experiences in algorithms, and the development of large-scale software systems or Web/App will be preferred; (3) Highly self-motivated, good written and oral English communication skills, and independent working ability.

Postdoctoral recruitments should also meet the following two points: (1) The applicant should be under the age of 35 and have obtained a doctoral degree no more 3 years; (2) The research directions are civil engineering information technology, Marine environmental information modeling and application, data-driven knowledge discovery and application, etc. (Note: postdoctoral candidates are required to present a half-hour academic presentation, including the main research works during PHD period and future postdoctoral work plans).

If you are interested, please send your resume, transcripts and work plan to the email: hu.zhenzhong@sz.tsinghua.edu.cn. For details, please see: PHD Master Recruitment and Postdoctoral Recruitment.

TOP-2

26 November 2021, Discharge of treated Fukushima nuclear accident contaminated water: macroscopic and microscopic simulations has been published on National Science Review, which is a full affirmation of the students and teachers of the subject group who are generous and rigorous in their learning! NSR officer micro-push high-quality and efficient, reflecting China's outstanding leading journals of the super-class level! Thanks to the director of singhua University's Institute for Ocean Engineering (IOE), Zhang Jianmin's guidance and support, thanks to the editorial department and reviewers for their high evaluation!

The results of this study are of great significance for the prediction of long-term spread of pollutants, the rational response of nuclear wastewater discharge plans and the monitoring of subsequent radioactive material concentrations. In the future, we will continue to deepen our research, Further explore the long-term impact of the discharge of nuclear waste water on the whole ocean and mankind, and provide important decision support for the country and the world to deal with the nuclear wastewater crisis!

Note: National Science Review , whose impact factor in 2021 is 17.275, is the top journal in the multi-discipline domain. For more information, please see the introduction video.

2026-06-03

The paper entitled “Numerical investigation of elliptical ribbed manifold microchannel heat sink and multi-objective optimization utilizing machine learning” has been published in Thermal Science and Engineering Progress.

This study addresses the thermal management challenges associated with high-heat-flux chips by focusing on the flow and heat transfer characteristics, as well as structural optimization, of an elliptical ribbed manifold microchannel heat sink (MMCHS). In response to the insufficient understanding of how microchannel height, microchannel width, elliptical rib dimensions, and coolant volumetric flow rate affect pressure drop and heat dissipation performance, extensive numerical simulations were conducted. The study systematically investigated the effects of different channel geometries, rib configurations, and volumetric flow rates on the coupled flow and heat transfer behavior within the elliptical ribbed MMCHS. The results revealed the variation patterns of cooling performance, pressure drop, Nusselt number, friction factor, and thermal enhancement efficiency under different design parameters, and further clarified the underlying mechanisms governing these performance metrics and the associated thermal irreversibility. On this basis, a high-accuracy artificial neural network model was developed to predict the substrate bottom temperature and pressure drop. By integrating the artificial neural network with a genetic algorithm, multi-objective optimization was performed to obtain a Pareto front that simultaneously minimizes substrate bottom temperature and pressure drop. The results show that the optimized design can achieve a 1.36%–3.75% improvement in thermal enhancement efficiency within a lower Reynolds number range, providing valuable engineering guidance for chip thermal management under pumping-power-limited conditions.

Note: Thermal Science and Engineering Progress is a Q1 journal in the field of engineering and technology, with a 2025 impact factor of 5.4. The first author of the paper is doctoral student Shoujun Chen, and Professor Sunwei Li is the corresponding author. This work was supported by the Guangdong Basic and Applied Basic Research Foundation and the Tsinghua Shenzhen International Graduate School–Shenzhen Pengrui Young Faculty Program.

2026-05-29

The "Deep Water Structure Health Monitoring Method and System" has been granted an invention patent certificate (Patent No.: ZL202610409127.1).

This invention discloses a deep-water structural health monitoring method and system. The method includes: establishing a discrete model and constructing an element strain matrix; collecting single-sided surface strain data and establishing a mapping relationship between theoretical surface strain and node displacements; formulating a single-sided inverse finite element data fitting term that incorporates a surface strain fitting component and a transverse shear strain penalty term; constructing a geometry-guided mixed regularization term composed of membrane and bending regularization components; assembling the global equations to solve for full-field displacements; recovering full-field strains and stresses, and outputting monitoring results. The system comprises a data acquisition module, a preprocessing and inverse reconstruction module, a stabilization solving module, and a visualization output module. Based on a full-field response perception scheme combining single-sided inverse finite element analysis with geometry-guided mixed regularization, this invention enables stable and high-precision inversion of full-field displacements, strains, and stresses using only sparse single-sided sensor data, effectively overcoming the dependency on bilateral sensor configurations in traditional methods. 

Note: The inventors of this patent also include Ph.D. student Jiang Chunhao, Ph.D. student Min Yantao, Associate Professor Guo Yutao, and Associate Professor Li Binbin.

2026-05-22

The paper "Assessing coastal groundwater risks from nuclear-contaminated water discharge under extreme drought and sustainable recharge solutions" has been published in Journal of Contaminant Hydrology.

The discharge of nuclear-contaminated water from the Fukushima Daiichi Nuclear Power Plant in Japan has raised concerns about seawater quality and potential environmental risks to coastal groundwater systems, particularly in densely populated metropolitan areas. In response to this pressing challenge, this study developed a radionuclide decay and transport model tailored to the hydrogeological conditions of Shanghai, aiming to comprehensively assess the combined impacts of nuclear discharge, extreme drought, and Managed Aquifer Recharge (MAR) on groundwater quality. The results show that under extreme drought conditions, declining groundwater levels may exacerbate seawater intrusion and intensify seawater–groundwater interactions, resulting in higher radionuclide concentrations than those observed under normal scenarios. Model simulations indicate that, under the assumed input scenario, after 30 years of continuous discharge, the concentrations of ¹³⁷Cs and ⁹⁰Sr at a depth of 160 m in Shanghai's aquifer increase by 33.93% and 46.40%, respectively. Meanwhile, MAR demonstrates significant potential for risk mitigation, reducing the concentrations of ¹³⁷Cs and ⁹⁰Sr by up to 99.58% and 99.10%, respectively. These findings highlight the critical role of proactive, nature-based interventions such as MAR in mitigating nuclear contamination risks and provide important scientific support for enhancing the resilience and sustainability of coastal groundwater resources.

Note: Journal of Contaminant Hydrology is a Q1 journal in the field of Environmental Sciences and Ecology, with a 2025 impact factor of 4.4. The corresponding authors of the paper include Prof. Yaqiang Wei from Shanghai University, Prof. Xinde Cao from Shanghai Jiao Tong University, and Prof. Hui Li from Shanghai University. This research was supported by the National Natural Science Foundation of China.