Showing papers by "Dalian University of Technology published in 2023"

Two-dimensional convolutional neural network outperforms other machine learning architectures for water depth surrogate modeling

Abstract: Rapid prediction of spatially distributed hydrological variables, such as water depths in rivers, is an important but challenging task. This study proposes a novel matrix-based deep learning approach for predicting spatial distribution of water depths in rivers. The proposed approach was constructed based on a two-dimensional (2D) convolutional neural network (CNN) with a new architecture that was specifically designed for providing spatial distribution maps. A numerical dataset was established based on a field cruise and two-dimensional hydraulic modeling for different scenarios, and numerical experiments were designed to predict spatial distribution of water depths for different scenarios using the adaptive neuro-fuzzy inference system (ANFIS), support vector machine (SVM), genetic programming (GP), multi-gene genetic programming (MGGP), one-dimensional CNN (1D-CNN), and the proposed CNN algorithms. The results showed that the proposed CNN approach captured both the large-scale and small-scale spatial patterns remarkably well, and it outperformed the other approaches. This study shows that the 2D CNN algorithm is better than the classical machine learning (ML) algorithms for inundation modeling. The proposed approach is thus a promising tool for providing rapid predictions of spatial distribution of water depths in river systems and can potentially be leveraged to predict other spatially distributed hydrological variables.

Experimental study of liquid immersion cooling for different cylindrical lithium-ion batteries under rapid charging conditions

Abstract: In this study, the liquid immersion cooling scheme based on SF33 has been proposed and tested for cooling the six different types of cylindrical lithium-ion batteries (LIBs) under fast charging conditions. Firstly, the voltage and temperature responses of LIBs under fast charging conditions with natural convection and SF33 immersion cooling were explored. It is found that the SF33 immersion cooling has a significant advantage over natural convection on controlling the battery temperature, thus ensuring the stability and safety of LIBs in the fast charging process. Subsequently, the high-speed photography was used to observe the bubble behaviors in the cooling process of SF33, and the heat transfer mechanism in the two-phase heat transfer process corresponding to immersion cooling of LIB was preliminary analyzed and discussed. It can be concluded that when the charging current is higher, the phenomenon of subcooled boiling as well as saturation boiling is generated in the SF33. The transition from single-phase convective heat transfer to boiling heat transfer greatly increases the heat transfer coefficient.

Distance minimizing based <scp>data‐driven</scp> computational method for the finite deformation of hyperelastic materials

Abstract: The distance minimizing based data-driven solvers are developed for the finite deformation analysis of three-dimensional (3D) compressible and nearly incompressible hyperelastic materials in this work. The data-driven solvers bypass the construction of a constitutive equation for the hyperelastic materials by considering a dataset of Green-Lagrange strain-second Piola–Kirchhoff stress pairs. They recast the boundary-value problems into the distance minimization problems with basic kinematical and mechanical constraints. Moreover, the deviatoric/volumetric split of stress and the additional incompressible constraint are further introduced into the solver for the nearly incompressible hyperelastic materials. Several representative three-dimensional examples are presented and the results demonstrate the good capability and robustness of the proposed data-driven solvers.

Oxygen vacancies-driven nonradical oxidation pathway of catalytic ozonation for efficient water decontamination

Abstract: Developing catalysts with high efficiency and excellent interference tolerance for practical application remains a challenge in catalytic ozonation process. Herein, the surface Vo-rich catalyst was successfully prepared by lattice-doping Co into zinc ferrite spinel, which exhibited efficient mineralization of recalcitrant organic pollutants. The contaminants removal was mainly attributed to the nonradical-based oxygen species of surface atomic oxygen (*O) rather than traditional hydroxyl radical (·OH). The experiments and DFT calculation results revealed that Vo was the main active sites for adsorption of ozone and production of *O. The O-O in ozone was dissociated at Vo, trigging the formation of *O. In addition, the Vo-driven nonradical catalysis showed high resistance to the coexisting ions (200 mM Cl-, SO42- and NO3-) and exhibited excellent performance for actual wastewater treatment. This work provides a novel strategy to regulate the oxidation pathways in catalytic ozonation process for efficient mineralization of pollutants in complicated water matrices.

Molecular dynamics simulation of reinforcement mechanism of graphene/aluminum composites and microstructure evolution

Abstract: Graphene/Aluminum (Gr/Al) composites with different graphene chirality and distribution patterns were established. The contribution of graphene interfaces to the mechanical properties of composites was investigated by using molecular dynamics methods. The composites strengthen about 10% of Young's modulus and 5% of tensile yield strength compared with aluminum. Influenced by the chiral structures of graphene, the fracture strain of zigzag composite is larger, and the yield stress of armchair composite is higher. Folding deformation of graphene promotes the yielding of the composites under compressive loading. Even if the graphene breaks, the graphene interface can effectively limit the dislocation motion, and the twins can only expand around the graphene. The results of both tensile and compressive tests showed that the uniform distribution of graphene was beneficial to enhance the mechanical properties of the composites. Graphene hinders the motion of pre-dislocations more than pinning dislocations. Therefore, the Bauschinger effect of composite is lower than that of pure aluminum under tension-compression loading.

Parametric Effects on the Mixing Efficiency of Resonant Acoustic Mixing Technology for High-Viscosity Mixture: A Numerical Study

Abstract: Numerical investigations were conducted on the mixing efficiency of resonant acoustic mixing (RAM) technology using a high-viscosity mixture under vertically forced vibrations. The density distribution was analyzed for a mixture of high-melting explosive (HMX) and trinitrotoluene (TNT). The effects of mixing time, amplitude, frequency, fill level, and mixing vessel geometry were evaluated to determine their influence on the blend homogeneity and the efficiency of the mixing process. The results showed that amplitude and frequency both have significant influences on the mixing efficiency of the RAM process. With higher values of amplitude and frequency, the mixing efficiency was very good, and uniform mixing was achieved in a much shorter time. At the same time, it was seen that geometric changes did not affect the mixing process; in contrast, varying the fill level did have a significant effect. This approach could potentially be used for pharmaceutical blending, cosmetics, and explosive applications, where only small quantities of active particle ingredients (APIs) can change the behavior of the mixture.

Study of density wave instability in natural circulation with parallel channels under inclined and heaving conditions

Abstract: Nuclear reactors used in warships, commercial ships and floating nuclear power plants will move synchronously with the carrier due to the action of waves or surges. Under ocean conditions, flow oscillations due to additional external motions can be superimposed with flow instabilities in the system resulting in larger amplitude oscillations or even resonances. Sustained compound oscillation will lead to fatigue failure of components, deteriorate local heat transfer, and affect the safe operation of the reactor system. The PNCMC (Program for Natural Circulation under Motion Condition) program is utilized in this research to explore the density wave instability (Type-I) in parallel channels during ocean circulation, and stability boundaries under different thermal-hydraulic parameters as well as ocean conditions to support the safe operation of the system. Through our study, it is found that under the condition of small heating channel inlet resistance coefficient, the unstable boundary powers in vertical case of natural circulation according to the order from small to large are the initial boundary of the parallel three-channels out-of-phase oscillation, the initial boundary of system's density wave oscillation, the boundary of the terminated system oscillation of density wave, as well as boundaries of three parallel channels where out-of-phase oscillations terminate, respectively; The inclined condition's stable boundary is generally lower than that in the vertical case. Unstable boundary power for the natural circulation in the heaving situation according to the order from small to large are the initial boundary of density wave oscillation in whole system are the initial boundary of oscillation of the density wave in system, the initial boundary of the parallel three-channels out-of-phase oscillation, boundary for three parallel-channels where out-of-phase oscillations terminate, and the boundary of the terminated system density wave oscillation, respectively; The oscillations caused by heaving motions, the system oscillations of density wave, as well as oscillations out of phase between the channels were overlapped to cause flow oscillations of very complex compound inside the heating parallel channels. At the same time, the increase of the resistant coefficient at inlet of heating channels can significantly suppress out-of-phase oscillation between the channels.

Subtle Structural Translation Magically Modulates the Super-Resolution Imaging of Self-Blinking Rhodamines

Abstract: The evolution of super-resolution imaging techniques is benefited from the ongoing competition for optimal rhodamine fluorophores. Yet, it seems blind to construct the desired rhodamine molecule matching the imaging need without the knowledge on imaging impact of even the minimum structural translation. Herein, we have designed a pair of self-blinking sulforhodamines (STMR and SRhB) with the bare distinction of methyl or ethyl substituents and engineered them with Halo protein ligands. Although the two possess similar spectral properties (λab, λfl, ϕ, etc.), they demonstrated unique single-molecule characteristics preferring to individual imaging applications. Experimentally, STMR with high emissive rates was qualified for imaging structures with rapid dynamics (endoplasmic reticulum, and mitochondria), and SRhB with prolonged on-times and photostability was suited for relatively "static" nuclei and microtubules. Using this new knowledge, the mitochondrial morphology during apoptosis and ferroptosis was first super-resolved by STMR. Our study highlights the significance of even the smallest structural modification to the modulation of super-resolution imaging performance and would provide insights for future fluorophore design.