分类： 核科学技术 >> 辐射物理与技术 提交时间： 2024-05-08
摘要： Accurate and efficient online parameter identification and state estimation are crucial for leveraging Digital Twin simulations to optimize the operation of near-carbon-free nuclear energy systems. In previous studies, we developed a reactor operation digital twin (RODT). However, non-differentiabilities and discontinuities arise when employing machine-learning-based surrogate forward models, challenging traditional gradient-based in verse methods and their variants. This study investigated deterministic and metaheuristic algorithms and developed hybrid algorithms to address these issues. An efficient modular RODT software framework that incorpo rates these methods into its post-evaluation module is presented for comprehensive comparison. The methods were rigorously assessed based on convergence profiles, stability with respect to noise, and computational performance. The numerical results show that the hybrid KNNLHS algorithm excels in real-time online applications, balancing accuracy and efficiency with a prediction error rate of only 1% and processing times of less than 0.1 s. Contrastingly, algorithms such as FSA, DE, and ADE, although slightly slower (approximately 1 s), demonstrated higher accuracy with a 0.3% relative L2 error, which advances RODT methodologies to harness machine learning and system modeling for improved reactor monitoring, systematic diagnosis of off-normal events, and lifetime management strategies. The developed modular software and novel optimization methods presented offer pathways to realize the full potential of RODT for transforming energy engineering practices.
分类： 动力与电气工程 >> 工程热物理学 提交时间： 2018-01-24 合作期刊: 《热科学学报》
摘要： Urban heating in northern China accounts for 40% of total building energy usage. In central heating systems, heat is often transferred from heat source to users by the heat network where several heat exchangers are installed at heat source, substations and terminals respectively. For given overall heating capacity and heat source temperature, increasing the terminal fluid temperature is an effective way to improve the thermal performance of such cascade heat exchange network for energy saving. In this paper, the mathematical optimization model of the cascade heat exchange network with three-stage heat exchangers in series is established. Aim at maximizing the cold fluid temperature for given hot fluid temperature and overall heating capacity, the optimal heat exchange area distribution and the medium fluids' flow rates are determined through inverse problem and variation method. The preliminary results show that the heat exchange areas should be distributed equally for each heat exchanger. It also indicates that in order to improve the thermal performance of the whole system, more heat exchange areas should be allocated to the heat exchanger where flow rate difference between two fluids is relatively small. This work is important for guiding the optimization design of practical cascade heating systems.
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