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Thermoacoustic technology emerges as a sustainable and low-carbon method for energy conversion, leveraging environmentally friendly working mediums and independence from electricity. This study presents the development of a multimode heat-driven thermoacoustic system designed to utilize medium/low-grade heat sources for room-temperature cooling and heating. We constructed both a simulation model and an experimental prototype for a single-unit direct-coupled thermoacoustic system, exploring its performance in heating-only, cooling-only, and hybrid heating and cooling modes. Internal characteristic analysis including an examination of internal exergy loss and a distribution analysis of key parameters was first conducted in the hybrid cooling and heating mode. The results indicated a positive-focused traveling-wave-dominant acoustic field within the thermoacoustic core unit, enhancing energy conversion efficiency. The output system performance was subsequently tested under different working conditions in the heating-only and cooling-only modes. A maximum output heating power of 2.3 kW and a maximum COPh of 1.41 were observed in the heating-only mode. Meanwhile, a cooling power of 748 W and a COPc of 0.4 were obtained in the typical cooling condition at 7 °C when operating in cooling-only mode. These findings underscore the promising potential of thermoacoustic systems for efficiently utilizing medium/low-grade heat sources for cooling and/or heating applications in the future.

Thermoacoustic technology emerges as a sustainable and low-carbon method for energy conversion, leveraging environmentally friendly working mediums and independence from electricity. This study presents the development of a multimode heat-driven thermoacoustic system designed to utilize medium/low-grade heat sources for room-temperature cooling and heating. We constructed both a simulation model and an experimental prototype for a single-unit direct-coupled thermoacoustic system, exploring its performance in heating-only, cooling-only, and hybrid heating and cooling modes. Internal characteristic analysis including an examination of internal exergy loss and a distribution analysis of key parameters was first conducted in the hybrid cooling and heating mode. The results indicated a positive-focused traveling-wave-dominant acoustic field within the thermoacoustic core unit, enhancing energy conversion efficiency. The output system performance was subsequently tested under different working conditions in the heating-only and cooling-only modes. A maximum output heating power of 2.3 kW and a maximum COPh of 1.41 were observed in the heating-only mode. Meanwhile, a cooling power of 748 W and a COPc of 0.4 were obtained in the typical cooling condition at 7 °C when operating in cooling-only mode. These findings underscore the promising potential of thermoacoustic systems for efficiently utilizing medium/low-grade heat sources for cooling and/or heating applications in the future.

Filament seals, such as brush seals and leaf seals, are investigated as a potential improved seal for gas turbine applications. As these seals operate in contact with the rotor, a good understanding of their stiffness is required in order to minimize seal wear and degradation. This paper demonstrates that the filament and complete seal stiffness is affected in comparable magnitudes by mechanical and aerodynamic forces. In certain cases, the aerodynamic forces can also lead to an overall negative seal stiffness which may affect stable seal operation. In negative stiffness, the displacement of the seal or rotor into an eccentric position causes a resultant force, which, rather than restoring the rotor to a central position, acts to amplify its displacement. Insight into the forces acting on the seal filaments is gained by investigating a leaf seal, which consists of a pack of thin planar leaves arranged around the rotor, with coverplates on either side of the leaf pack, offset from the pack surfaces. The leaf seal is chosen due to its geometry being more suitable for analysis compared to alternative filament seals such as the brush seal. Data from two experimental campaigns are presented which show a seal exhibiting negative stiffness and a seal exhibiting a stiffness reduction due to aerodynamic effects. An empirical model for the forces acting on leaf filaments is developed based on the experimental data, which allows separation of mechanical and aerodynamic forces. In addition a numerical model is developed to analyze the flow approaching the leaf pack and the interleaf flow, which gives an insight into the causes of the aerodynamic forces. Using the empirical and numerical models together, a full picture of the forces affecting leaf stiffness is created. Validation of the models is achieved by successfully predicting seal stiffness for a further data set across the full range of operating conditions. The understanding of aerodynamic forces and their impact on filament and seal stiffness allows for their consideration in leaf seal design. A qualitative assessment of how they may be used to improve seal operation in filament seals is given.

Filament seals, such as brush seals and leaf seals, are investigated as a potential improved seal for gas turbine applications. As these seals operate in contact with the rotor, a good understanding of their stiffness is required in order to minimize seal wear and degradation. This paper demonstrates that the filament and complete seal stiffness is affected in comparable magnitudes by mechanical and aerodynamic forces. In certain cases, the aerodynamic forces can also lead to an overall negative seal stiffness which may affect stable seal operation. In negative stiffness, the displacement of the seal or rotor into an eccentric position causes a resultant force, which, rather than restoring the rotor to a central position, acts to amplify its displacement. Insight into the forces acting on the seal filaments is gained by investigating a leaf seal, which consists of a pack of thin planar leaves arranged around the rotor, with coverplates on either side of the leaf pack, offset from the pack surfaces. The leaf seal is chosen due to its geometry being more suitable for analysis compared to alternative filament seals such as the brush seal. Data from two experimental campaigns are presented which show a seal exhibiting negative stiffness and a seal exhibiting a stiffness reduction due to aerodynamic effects. An empirical model for the forces acting on leaf filaments is developed based on the experimental data, which allows separation of mechanical and aerodynamic forces. In addition a numerical model is developed to analyze the flow approaching the leaf pack and the interleaf flow, which gives an insight into the causes of the aerodynamic forces. Using the empirical and numerical models together, a full picture of the forces affecting leaf stiffness is created. Validation of the models is achieved by successfully predicting seal stiffness for a further data set across the full range of operating conditions. The understanding of aerodynamic forces and their impact on filament and seal stiffness allows for their consideration in leaf seal design. A qualitative assessment of how they may be used to improve seal operation in filament seals is given.

This paper proposes a novel online and self-learning algorithm to the identification of fuzzy neural networks, which not only learns the structure and parameters online but also learns the threshold parameters by itself and automatically. For structure learning, a self-constructing approach including adding neurons and merging highly similar fuzzy rules is proposed based on the criteria of the system error between actual and model output and the maximum firing strength of neurons. In order to achieve the efficient merging computing, a new calculation method of similarity degree between fuzzy rules is developed. Further and more importantly, the varying width of Gaussian membership functions can be learned by itself according to the underfitting and overfitting criteria. Similarly, different from the existing constant threshold of similarity degree for merging, the varying threshold of similarity degree can be self-learned according to the real-time accuracy of model. The proposed self-learning mechanism significantly improves the model accuracy and greatly enhances the easy usability. Several benchmark examples are implemented to illustrate the effectiveness and feasible of the proposed approach.

This paper proposes a novel online and self-learning algorithm to the identification of fuzzy neural networks, which not only learns the structure and parameters online but also learns the threshold parameters by itself and automatically. For structure learning, a self-constructing approach including adding neurons and merging highly similar fuzzy rules is proposed based on the criteria of the system error between actual and model output and the maximum firing strength of neurons. In order to achieve the efficient merging computing, a new calculation method of similarity degree between fuzzy rules is developed. Further and more importantly, the varying width of Gaussian membership functions can be learned by itself according to the underfitting and overfitting criteria. Similarly, different from the existing constant threshold of similarity degree for merging, the varying threshold of similarity degree can be self-learned according to the real-time accuracy of model. The proposed self-learning mechanism significantly improves the model accuracy and greatly enhances the easy usability. Several benchmark examples are implemented to illustrate the effectiveness and feasible of the proposed approach.

The optical and photovoltaic properties of Si NCs / SiC multilayers (MLs) are investigated using a membrane-based solar cell structure. By removing the Si substrate in the active cell area, the MLs are studied without any bulk Si substrate contribution. The occurrence is confirmed by scanning electron microscopy and light-beam induced current mapping . Optical characterization combined with simulations allows us to determine the absorption within the ML absorber layer, isolated from the other cell stack layers. The results indicate that the absorption at wavelengths longer than 800 nm is only due to the SiC matrix. The measured short-circuit current is significantly lower than that theoretically obtained from absorption within the ML absorber, which is ascribed to losses that limit carrier extraction. The origin of these losses is discussed in terms of the material regions where recombination takes place. Our results indicate that carrier extraction is most efficient from the Si NCs themselves, whereas recombination is strongest in SiC and residual a-Si domains . Together with the observed onset of the external quantum efficiency (EQE) at 700-800 nm, this fact is an evidence of quantum confinement in Si NCs embedded in SiC on device level.

The optical and photovoltaic properties of Si NCs / SiC multilayers (MLs) are investigated using a membrane-based solar cell structure. By removing the Si substrate in the active cell area, the MLs are studied without any bulk Si substrate contribution. The occurrence is confirmed by scanning electron microscopy and light-beam induced current mapping . Optical characterization combined with simulations allows us to determine the absorption within the ML absorber layer, isolated from the other cell stack layers. The results indicate that the absorption at wavelengths longer than 800 nm is only due to the SiC matrix. The measured short-circuit current is significantly lower than that theoretically obtained from absorption within the ML absorber, which is ascribed to losses that limit carrier extraction. The origin of these losses is discussed in terms of the material regions where recombination takes place. Our results indicate that carrier extraction is most efficient from the Si NCs themselves, whereas recombination is strongest in SiC and residual a-Si domains . Together with the observed onset of the external quantum efficiency (EQE) at 700-800 nm, this fact is an evidence of quantum confinement in Si NCs embedded in SiC on device level.