Theoretical Study of A Thermoelectric-assisted Vapor Compression Cycle for Air-source Heat Pump Applications

In this paper, a thermoelectric-assisted vapor compression cycle (TVCC) is proposed for applications in air-source heat pump systems. Compared with the basic vapor compression cycle (BVCC), the TVCC using a thermoelectric heat exchanger (THEX) could enhance the heating capacity of the system in an energy-efficient way. To demonstrate the performance characteristics of TVCC, a case study on this cycle applied to a small air-source heat pump water heater has been conducted based on the developed mathematical model. Performances of both the new TVCC and BVCC are also compared. The simulation results show that the TVCC has 46.3%-103.0% increase and 14.7%-52.5% reduction in heating capacity and COP compared with those of the BVCC, respectively, under given conditions. Especially, at a higher evaporating or condensing temperature, the TVCC has better improvements in heating capacity. When there is no significant difference in COPs among the two cycles, the TVCC still performs better than BVCC by 13.0% in heating capacity by selecting the appropriate intermediate temperature. In addition, the TVCC can also achieve an improvement of 16.4%-21.7% in both the heating COP and capacity under the above given conditions, when compared with the BVCC with an assistant electric heater that is provided with the equivalent power input of THEX. Thus, the advantage of TVCC in heating capacity could be beneficial to the applications in small heat pumps if there is always need for auxiliary electric heat to solve the problem of low heating capacity of a heat pump at a low ambient temperature

Numerical investigation of airborne contaminant transport under different vortex structures in the aircraft cabin.

Airborne contaminants such as pathogens, odors and CO2 released from an individual passenger could spread via air flow in an aircraft cabin and make other passengers unhealthy and uncomfortable. In this study, we introduced the airflow vortex structure to analyze how airflow patterns affected contaminant transport in an aircraft cabin. Experimental data regarding airflow patterns were used to validate a computational fluid dynamics (CFD) model. Using the validated CFD model, we investigated the effects of the airflow vortex structure on contaminant transmission based on quantitative analysis. It was found that the contaminant source located in a vorticity-dominated region was more likely to be "locked" in the vortex, resulting in higher 62% higher average concentration and 14% longer residual time than that when the source was on a deformation dominated location. The contaminant concentrations also differed between the front and rear parts of the cabin because of different airflow structures. Contaminant released close to the heated manikin face was likely to be transported backward according to its distribution mean position. Based on these results, the air flow patterns inside aircraft cabins can potentially be improved to better control the spread of airborne contaminant

CDMBE: A Case Description Model Based on Evidence

By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users’ ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model

First order transition in Pb10−x_{10-x}Cux_x(PO4_4)6_6O (0.9<x<1.10.9<x<1.1) containing Cu2_2S

Lee et al. reported that the compound LK99, with a chemical formula of Pb$_{10-x}$Cu$_x$(PO$_4$)$_6$O ($0.9<x<1.1$), exhibits room-temperature superconductivity under ambient pressure. In this study, we investigated the transport and magnetic properties of pure Cu$_2$S and LK-99 containing Cu$_2$S. We observed a sharp superconducting-like transition and a thermal hysteresis behavior in the resistivity and magnetic susceptibility. However, we did not observe zero-resistivity below the transition temperature. We argue that the so-called superconducting behavior in LK-99 is most likely due to a reduction in resistivity caused by the first order structural phase transition of Cu$_2$S at around 385 K, from the $\beta$ phase at high temperature to the $\gamma$ phase at low temperature

Comparative study on the thermoelectric effect of parent oxypnictides LaTTAsO (TT = Fe, Ni)

The thermopower and Nernst effect were investigated for undoped parent compounds LaFeAsO and LaNiAsO. Both thermopower and Nernst signal in iron-based LaFeAsO are significantly larger than those in nickel-based LaNiAsO. Furthermore, abrupt changes in both thermopower and Nernst effect are observed below the structural phase transition temperature and spin-density wave (SDW) type antiferromagnetic (AFM) order temperature in Fe-based LaFeAsO. On the other hand, Nernst effect is very small in the Ni-based LaNiAsO and it is weakly temperature-dependent, reminiscent of the case in normal metals. We suggest that the effect of SDW order on the spin scattering rate should play an important role in the anomalous temperature dependence of Hall effect and Nernst effect in LaFeAsO. The contrast behavior between the LaFeAsO and LaNiAsO systems implies that the LaFeAsO system is fundamentally different from the LaNiAsO system and this may provide clues to the mechanism of high $T_c$ superconductivity in the Fe-based systems.Comment: 6 pages, 6 figure

Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric

Combining the Color and Event cameras (also called Dynamic Vision Sensors, DVS) for robust object tracking is a newly emerging research topic in recent years. Existing color-event tracking framework usually contains multiple scattered modules which may lead to low efficiency and high computational complexity, including feature extraction, fusion, matching, interactive learning, etc. In this paper, we propose a single-stage backbone network for Color-Event Unified Tracking (CEUTrack), which achieves the above functions simultaneously. Given the event points and RGB frames, we first transform the points into voxels and crop the template and search regions for both modalities, respectively. Then, these regions are projected into tokens and parallelly fed into the unified Transformer backbone network. The output features will be fed into a tracking head for target object localization. Our proposed CEUTrack is simple, effective, and efficient, which achieves over 75 FPS and new SOTA performance. To better validate the effectiveness of our model and address the data deficiency of this task, we also propose a generic and large-scale benchmark dataset for color-event tracking, termed COESOT, which contains 90 categories and 1354 video sequences. Additionally, a new evaluation metric named BOC is proposed in our evaluation toolkit to evaluate the prominence with respect to the baseline methods. We hope the newly proposed method, dataset, and evaluation metric provide a better platform for color-event-based tracking. The dataset, toolkit, and source code will be released on: \url{https://github.com/Event-AHU/COESOT}