Quantitative safety goals for fusion power plants: Rationales and suggestions

Wang, Zhen; Chen, Zhibin; Chen, Chao; Ge, Daochuan; Perrault, Didier; Zucchetti, Massimo; Subbotin, M.L.

doi:10.1002/er.6399

Cited by 4 publications

(5 citation statements)

References 33 publications

(50 reference statements)

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Section: Multiscale Modeling From Atomic To Cellmentioning

confidence: 99%

Multiscale modeling for enhanced battery health analysis: Pathways to longevity

Yang,

Zhang,

Wang

et al. 2024

Carbon Neutralization

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The issues of health assessment and lifespan prediction have always been prominent challenges in the large‐scale application of lithium‐ion batteries (LIBs). This paper reviews the multiscale modeling techniques and their applications in battery health analysis, including atomic scale computational chemistry, particle scale reaction simulations, electrode scale structural models, macroscale electrochemical models, and data‐driven models at the system level. Multiscale modeling offers a profound insight into material behavior and the aging process of batteries, thereby providing a valuable reference for both estimation and management strategies of battery state of health. To extend the battery lifespan, the utilization of artificial intelligence for material discovery and manufacturing process optimization, the implementation of end‐cloud collaborative battery management systems, and the design of a multiscale simulation integration platform are considered. A management framework aimed at extending battery life is further proposed. This framework offers a promising roadmap for addressing health analysis challenges in LIBs, ultimately leading to more reliable, efficient, and durable solutions for next‐generation batteries.

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Section: Multiscale Modeling From Atomic To Cellmentioning

confidence: 99%

Multiscale modeling for enhanced battery health analysis: Pathways to longevity

Yang,

Zhang,

Wang

et al. 2024

Carbon Neutralization

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“…The performance of the irreversible rectangular cycle considering heat transfer losses and friction factor was also analyzed by Liu et al [44]. Wang et al [45,46] investigated the influence of the specific-heat model of WM on the performance of endoreversible and irreversible rectangular cycles. Articles [43][44][45][46] all concern macroscopic rectangular cycle as the study object without considering the quantum properties of the working medium.…”

Section: Introductionmentioning

confidence: 99%

“…If a single objective is used to optimize the system, it is often impossible to balance the relationship between the different objective functions, and thus the cycle performance cannot be optimized. In an effort to weigh the merits and demerits of each performance index, many researchers presented the idea of multi-objective optimization (MOO) [44][45][46][47]. Ahmadi et al [47] investigated the efficiency, power, and pressure loss features of the Stirling heat engine cycle and applied the NSGA algorithm to carry out triple-objective optimization.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization for Quantum Rectangular Cycle with Power, Efficiency and Efficient Power

Xie,

Chen,

Yin

et al. 2024

Acta Phys. Pol. A

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This paper establishes a quantum rectangular heat engine model by applying finite-time thermodynamics. The working medium is countless particles trapped in a one-dimensional infinite potential well. Taking into account heat leakage between the system and the outside, expressions for thermal efficiency (η), dimensionless power ( P ), and dimensionless efficient power ( Wep) of quantum rectangular heat engine are derived, and its optimal performance is studied. System performance P , η, and Wep are optimized firstly by taking the width ratio of the potential well as the optimization variable. The outcomes show that the relationship curve between P and η is a loop-shaped curve. With an increase in heat leakage coefficient, the optimal design range of the quantum rectangular heat engine becomes smaller. The relationship curve between the efficient power and width ratio of the potential well is parabolic-like. The relationship curve between Wep and η is a loop-shaped curve. The efficiency of the quantum rectangular heat engine at Wep max operating point is greater than that at Pmax operating point. Secondly, multi-objective optimization is applied with η, P , and Wep as optimization objectives by applying NSGA-II, and the optimal design scheme is achieved by applying TOPSIS, LINMAP, and Shannon entropy decision-making approaches. The smallest deviation index inferred by the Shannon entropy approach is 0.0269. The design scheme is closest to the ideal scheme. topics: finite-time thermodynamics; quantum rectangular heat engine (QRHE); power, multi-objective optimization, thermal efficiency and efficient power

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“…Therefore, a lot of researchers have tried to find out how the key parameters of lithium-ion batteries affect the thermal characteristics of lithium-ion batteries during the charging and discharging process through simulation. [7,8] In terms of lithium-ion batteries' electrothermal coupling modeling, Wang et al [9] established a 3D uncoupled thermal model to simulate the temperature change of a large nickel-cobalt-manganese lithium-ion battery during discharge and verified the validity of the model through experiments. Liang et al [10] developed a physics-based comprehensive cycle life model for lithium-ion batteries based on the existing electrochemical-thermal coupling model.…”

Section: Introductionmentioning

confidence: 99%

Experimental and Simulation Studies on the Thermal Characteristics of Large‐Capacity Square Lithium‐Ion Batteries with Low‐Temperature Discharge

Ren,

Mao,

Chang

et al. 2023

Energy Tech

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As the capacity of lithium‐ion batteries decays severely at low temperatures, it is important to study the electrochemical and thermal properties of lithium‐ion batteries at low temperatures. Herein, a large‐capacity prismatic lithium‐ion battery is selected to carry out experiments to study the electrothermal characteristics of the battery in different temperatures (25, 0, −10, and −20 °C). Second, a pseudo‐3D electrochemical–thermal coupling model is established and the validity of the model is verified. Finally, this article analyzes the influence of ambient temperature on the thermal characteristics of the battery during discharge. The results show that the battery discharge capacity gradually decreases with the decrease in the ambient temperature. At −20 °C, the discharged electricity is 66.51% of that at room temperature. At the same time, as the ambient temperature drops, the temperature rise on the surface of the battery increases during the discharge process, and at −20 °C, the temperature rise can reach 3.86 times than that at normal temperature. In addition, the change in reversible heat percentage is negatively correlated with the discharge rate and positively correlated with the battery temperature, while the effect of the discharge rate on irreversible heat is greater than that of ambient temperature.

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Quantitative safety goals for fusion power plants: Rationales and suggestions

Cited by 4 publications

References 33 publications

Multiscale modeling for enhanced battery health analysis: Pathways to longevity

Multiscale modeling for enhanced battery health analysis: Pathways to longevity

Multi-Objective Optimization for Quantum Rectangular Cycle with Power, Efficiency and Efficient Power

Experimental and Simulation Studies on the Thermal Characteristics of Large‐Capacity Square Lithium‐Ion Batteries with Low‐Temperature Discharge

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