Comparative Research on Air Conditioner with Gas-injected Rotary Compressor through Injection Port on Blade

Rotary compressors are widely utilized in air conditionders and heat pumps. However, when rotary compressors were applied in room air conditioners, VRFs and domestic water heaters, the systems will experience heavily degradation of the heating capacity and COP as the ambient temperature goes low. Aimed at these problems, considerable research has been carried out to raise a series of solutions, such as economizer technology, cascade-type vapor compression heat pump system and two stage coupling heat pump system. At present, economizer technology has become a critical method to improve the performance of air source heat pumps with rotary compressors in low ambient temperature. A novel vapor injection structure on a blade for a rotary compressor has been proposed in previous paper to overcome the drawback of the traditional cylinder injection structure. Based on a verified numerical model, the performance of air source heat pumps with rotary compressors with different economizer technology including a two-stage rotary compressor, a single-stage rotary compressor with traditional injection structure and a single rotary compressor with the novel injection structure has been investigated. The results indicate that: compared to rotary compressors with traditional injection structure, air source heat pump with a rotary compressor with proposed injection structure can enhance the heating capacity and COP by 13%~15% and 4.8%~9.6%, respectively; and compared to the twin-cylinder rotary compressor, the performance of air source heat pump with a rotary compressor with proposed injection structure is almost the same, so the rotary compressor with the novel injection structure could be considered to replace the two-stage rotary compressor

A Novel Vapor Injection Structure on the Blade for Rotary Compressor

Rotary compressors have been extensively used in room air conditioners and household refrigerators for their advantages, including high efficiency, strong adaptability, and low cost. However, when air source heat pumps with rotary compressors are applied in cold regions, a series of problems appear. The gas injection has been proved an effective technology to enhance both the heating capacity and COP of scroll, screw, and rotary compressors. In the one-cylinder rotary compressor with gas injection, the compressor injection port is often opened on the cylinder wall. In order to extend the injection time for injecting more refrigerant, the injection port is settled as close as possible to the discharge port. However, the limited area of the injection port and the unavoidable back-flowing of the injection refrigerant into the suction tube diminish the merits of gas injection on the one-cylinder rotary compressor. A novel vapor injection structure on the blade for the rotary compressor has been proposed in this paper to overcome the back-flowing drawback of the traditional cylinder injection structure and increase the injection area. Based on a verified numerical model, the performance of a rotary compressor with the blade injection structure has been investigated. The results indicate that: the proposed vapor injection structure can eliminate the back-flowing of the injected refrigerant; compared to the traditional injection structure, the new structure can enhance the volumetric efficiency and mass flow-rate by 1.8~2.7% and 26.6~57.2%, respectively; and compared to the traditional injection structure, the new structure can increase the heating capacity and COP by 23.1~48.9% and 3.2~8.0%, respectively

Sim-to-Real Deep Reinforcement Learning with Manipulators for Pick-and-place

When transferring a Deep Reinforcement Learning model from simulation to the real world, the performance could be unsatisfactory since the simulation cannot imitate the real world well in many circumstances. This results in a long period of fine-tuning in the real world. This paper proposes a self-supervised vision-based DRL method that allows robots to pick and place objects effectively and efficiently when directly transferring a training model from simulation to the real world. A height-sensitive action policy is specially designed for the proposed method to deal with crowded and stacked objects in challenging environments. The training model with the proposed approach can be applied directly to a real suction task without any fine-tuning from the real world while maintaining a high suction success rate. It is also validated that our model can be deployed to suction novel objects in a real experiment with a suction success rate of 90\% without any real-world fine-tuning. The experimental video is available at: https://youtu.be/jSTC-EGsoFA

Jitter analysis of a superconducting nanowire single photon detector

Jitter is one of the key parameters for a superconducting nanowire single photon detector (SNSPD). Using an optimized time-correlated single photon counting system for jitter measurement, we extensively studied the dependence of system jitter on the bias current and working temperature. The signal-to-noise ratio of the single-photon-response pulse was proven to be an important factor in system jitter. The final system jitter was reduced to 18 ps by using a high-critical-current SNSPD, which showed an intrinsic SNSPD jitter of 15 ps. A laser ranging experiment using a 15-ps SNSPD achieved a record depth resolution of 3 mm at a wavelength of 1550 nm.Comment: 7 pages, 6 figure

Simultaneous manipulation of electromagnetic and elastic waves via glide symmetry phoxonic crystal waveguides

A phoxonic crystal waveguide with the glide symmetry is designed, in which both electromagnetic and elastic waves can propagate along the glide plane at the same time. Due to the band-sticking effect, super-cell bands of the waveguide degenerate in pairs at the boundary of the Brillouin zone, causing the appearance of gapless guided-modes in the bandgaps. The gapless guided-modes are single-modes over a relatively large frequency range. By adjusting the magnitude of the glide dislocation, the edge bandgaps of the guided-modes can be further adjusted, so as to achieve photonic and phononic single-mode guided-bands with relatively flat dispersion relationship. In addition, there exists acousto-optic interaction in the cavity constructed by the glide plane. The proposed waveguide has potential applications in the design of novel optomechanical devices.Comment: 16 pages, 9 figure

Enhancing Faraday and Kerr rotations based on toroidal dipole mode in an all-dielectric magneto-optical metasurface

The magneto-optical Faraday and Kerr effects are widely used in modern optical devices. In this letter, we propose an all-dielectric metasurface composed of perforated magneto-optical thin films, which can support the highly confined toroidal dipole resonance and provide full overlap between the localized electromagnetic field and the thin film, and consequently enhance the magneto-optical effects to an unprecedented degree. The numerical results based on finite element method show that the Faraday and Kerr rotations can reach -13.59${\deg}$ and 8.19${\deg}$ in the vicinity of toroidal dipole resonance, which are 21.2 and 32.8 times stronger than those in the equivalent thickness of thin films, respectively. In addition, we design an environment refractive index sensor based on the resonantly enhanced Faraday and Kerr rotations, with sensitivities of 62.96 nm/RIU and 73.16 nm/RIU, and the corresponding maximum figures of merit 132.22${\deg}$/RIU and 429.45${\deg}$/RIU, respectively. This work provides a new strategy for enhancing the magneto-optical effects at nanoscale, and paves the way for the research and development of magneto-optical metadevices such as sensors, memories, and circuits

Generative Model for Models: Rapid DNN Customization for Diverse Tasks and Resource Constraints

Unlike cloud-based deep learning models that are often large and uniform, edge-deployed models usually demand customization for domain-specific tasks and resource-limited environments. Such customization processes can be costly and time-consuming due to the diversity of edge scenarios and the training load for each scenario. Although various approaches have been proposed for rapid resource-oriented customization and task-oriented customization respectively, achieving both of them at the same time is challenging. Drawing inspiration from the generative AI and the modular composability of neural networks, we introduce NN-Factory, an one-for-all framework to generate customized lightweight models for diverse edge scenarios. The key idea is to use a generative model to directly produce the customized models, instead of training them. The main components of NN-Factory include a modular supernet with pretrained modules that can be conditionally activated to accomplish different tasks and a generative module assembler that manipulate the modules according to task and sparsity requirements. Given an edge scenario, NN-Factory can efficiently customize a compact model specialized in the edge task while satisfying the edge resource constraints by searching for the optimal strategy to assemble the modules. Based on experiments on image classification and object detection tasks with different edge devices, NN-Factory is able to generate high-quality task- and resource-specific models within few seconds, faster than conventional model customization approaches by orders of magnitude

Value Congruence: A Study of Green Transformational Leadership and Employee Green Behavior

This study examined the extent to which the impact of green transformational leadership on employee green behavior through follower perceptions of value congruence. Path analyzing on data from 193 subordinate-leader dyads showed that followers’ value congruence with their leader mediated the effects of green transformational leadership on employee green behavior. Results also supported that green identity moderated the indirect effect of green transformational leadership on employee green behavior through value congruence, such that the indirect effect was more positive when green identity was high than when it was low. These findings provided valuable contribution to green transformational leadership, value congruence, and employee green behavior by exploring the relationship between them. Practical implications and directions for future research are also discussed