Performance analysis of a new deep super-cooling two-stage organic Rankine cycle

This document is the Accepted Manuscript version of the following article: Y. Yuan, G. Xu, Y. Quan, H. Wu, G. Song, W. Gong, and X. Luo, ‘Performance analysis of a new deep super-cooling two-stage organic Rankine cycle’, Energy Conversion and Management, Vol. 148: 305-316, September 2017. The final, definitive version is available online at doi:https://doi.org/10.1016/j.enconman.2017.06.006. Published by Elsevier.In this article, a new deep super-cooling two-stage organic Rankine cycle (DTORC) is proposed and evaluated at high temperature waste heat recovery in order to increase the power output. A thermodynamic model of recuperative organic rankine cycle (ORC) is also established for the purpose of comparison. Furthermore, a new evaluation index, effective heat source utilization, is proposed to reflect the relationship among the heat source, power output and consumption of the waste heat carrier. A simulation model is formulated and analysed under a wide range of operating conditions with the heat resource temperature fixed at 300℃. Hexamethyldisiloxane (MM) and R245fa are used as the working fluid for DTORC, and MM for ORC. In the current work, the comparisons of heat source utilization, net thermal efficiency as well as the total surface area of the heat exchangers between DTORC and RC are discussed in detail. Results show that the DTORC performs better than ORC at high temperature waste heat recovery and it could increase the power output by 150%. Moreover, the maximum net thermal efficiency of DTORC can reach to 23.5% and increased by 30.5% compared with that using ORC, whereas the total surface areas of the heat exchangers are nearly the same.Peer reviewe

A Multi-Robot Cooperation Framework for Sewing Personalized Stent Grafts

This paper presents a multi-robot system for manufacturing personalized medical stent grafts. The proposed system adopts a modular design, which includes: a (personalized) mandrel module, a bimanual sewing module, and a vision module. The mandrel module incorporates the personalized geometry of patients, while the bimanual sewing module adopts a learning-by-demonstration approach to transfer human hand-sewing skills to the robots. The human demonstrations were firstly observed by the vision module and then encoded using a statistical model to generate the reference motion trajectories. During autonomous robot sewing, the vision module plays the role of coordinating multi-robot collaboration. Experiment results show that the robots can adapt to generalized stent designs. The proposed system can also be used for other manipulation tasks, especially for flexible production of customized products and where bimanual or multi-robot cooperation is required.Comment: 10 pages, 12 figures, accepted by IEEE Transactions on Industrial Informatics, Key words: modularity, medical device customization, multi-robot system, robot learning, visual servoing, robot sewin

A calculation method to estimate thermal conductivity of high entropy ceramic for thermal barrier coatings

High entropy ceramics are highly promising as next generation thermal barrier coatings due to their unique disorder structure, which imparts ultra-low thermal conductivity and good high temperature stability. Unlike traditional ceramic materials, the thermal resistance in high entropy ceramics predominantly arises from phonon-disorder scattering rather than phonon-phonon interactions. In this study, we propose a calculation method based on the supercell phonon unfolding (SPU) technique to predict the thermal conductivity of high entropy ceramics, specially focusing on rocksalt oxides structures. Our prediction method relies on using the reciprocal value of SPU phonon spectra linewidth as an indicator of phonon lifetime. The obtained results demonstrate a strong agreement between the predicted thermal conductivities and the experimental measurements, validating the feasibility of our calculation method. Furthermore, we extensively investigate and discuss the atomic relaxation and lattice distortion effects in 5-dopants and 6-dopants rocksalt structures during the process.Comment: 19 page, 8 figure

Critical Assessment of Mass and Lattice Disorder in Thermal Conductivity Prediction for Medium and High Entropy Ceramics

Medium and high entropy ceramics, with their distinctive disordered structures, exhibit ultra-low thermal conductivity and high temperature stability. These properties make them strong contenders for next generation thermal barrier coating (TBC) materials. However, predicting their thermal conductivity has been challenging, primarily due to their unique phonon scattering mechanisms. Apart from the conventional phonon-phonon scattering mechanism, the phonon-disorder scattering, comprising both mass and force constant disorder, are also expected to make significant contribution in determining the thermal conductivity of medium and high entropy ceramics. However, it remains challenging to quantify the phonon-disorder contribution, particular in the aspect of force constant disorder. Here we demonstrated a relationship between the lattice disorder, a quantity more readily calculable, with force constant disorder, rendering it possible to substitute the force constant disorder by lattice disorder. Based on this relationship and drawing inspiration from Klement's equation of static imperfection, we have developed a model that quantitatively assesses the connection between disorder and thermal conductivity. Applying our model to the medium/high entropy rocksalt and pyrochlore oxides as representatives, we found good alignment between the theoretical predictions and experimental measurements of thermal conductivities, confirming the validity of our model. The model developed offers a critical predictive tool for rapid screening of TBC materials based on medium and high entropy ceramics.Comment: 25 pages, 7 figure

Numerical analysis of the axial heat conduction with variable fluid properties in a forced laminar flow tube

This document is the Accepted Manuscript version of the following article: Lijing Zhai, et al, ‘Numerical analysis of the axial heat conduction with variable fluid properties in a forced laminar flow tube’, International Journal of Heat and Mass Transfer, Vol. 114: 238-251, November 2017. Under embargo until 22 June 2018. The final, definitive version is available online at doi: https://doi.org/10.1016/j.ijheatmasstransfer.2017.06.041.In this article, a theoretical model is developed to investigate the effects of the axial heat conduction on the laminar forced convection in a circular tube with uniform internal heat generation in the solid wall. In the current work, three different fluids, i.e. water, n-decane and air, are selected on purpose since their thermophysical properties show different behavior with temperature. The effects of the axial heat conduction with varying dynamic viscosity and/or varying thermal conductivity are investigated in a systematic manner. Results indicate that the variable-property effects could alleviate the reduction in Nusselt number (Nu) due to the axial heat conduction. For the case of Peclet number (Pe) equal to 100, wall thickness to inner diameter ratio of 1 and solid wall to fluid thermal conductivity ratio of 100, the maximum Nu deviation between constant and variable properties are up to 7.33% at the entrance part for water in the temperature range of 50℃, and 4.45% at the entrance part for n-decane in the temperature range of 120℃, as well as 2.20% at the ending part for air in the temperature range of 475℃, respectively. In addition, the average Nu deviation for water, n-decane and air are 3.24%, 1.94% and 1.74%, respectively. Besides, Nu decreases drastically with decreasing Pe when Pe≤500 and with increasing solid wall to fluid thermal conductivity ratio ( ) when ≤100. It is also found that variable properties have more obvious effects on the velocity profile at the upstream part while more obvious effects on the temperature profile at the downstream part.Peer reviewe

Loose Gangues Backfill Body’s Acoustic Emissions Rules During Compaction Test: Based on Solid Backfill Mining

In fully mechanized solid backfilling mining (FMSBM), the loose gangues backfill body (LGBB) that filled into the goaf becomes the main body of bearing the overburden load. The deformation resistance of LGBB is critical for controlling overburden movement and surface subsidence. During the process of load bearing, LGBB will experience grain crushing, which has a significant effect on its deformation resistance. Gangues block will be accompanied with obvious acoustic emissions (AE) features in process of slipping, flipping and damaging. Under confined compression test, monitoring the AE parameters of LGBB can reveal the impact mechanism of grain crushing on LGBB deformation. The study is of great significance for obtaining an in-depth understanding of the mechanical properties of LGBB, and providing guidance to the engineering practice of FMSBM. In order to study the rules of acoustic emissions (AE) of graded Loose gangues backfill body (LGBB) in confined compression test, this article introduces the AE systems to conventional confined compression test to monitor AE signals resulted from the friction and fragmentation among LGBB. The test results show that in the process of LGBB compaction, AE parameters are highly correlated with the strain-stress curve. AE events of balanced-sized graded gangues are more inactive than other two graded samples in different compression stages, AE events of large-particle-dominated graded gangues are most active. In the spatial distribution, AE events are the most active on the edges and the middle part of test samples and the phenomenon of grain crushing is the most obvious in these positions

Non-exemplar Class-incremental Learning by Random Auxiliary Classes Augmentation and Mixed Features

Non-exemplar class-incremental learning refers to classifying new and old classes without storing samples of old classes. Since only new class samples are available for optimization, it often occurs catastrophic forgetting of old knowledge. To alleviate this problem, many new methods are proposed such as model distillation, class augmentation. In this paper, we propose an effective non-exemplar method called RAMF consisting of Random Auxiliary classes augmentation and Mixed Feature. On the one hand, we design a novel random auxiliary classes augmentation method, where one augmentation is randomly selected from three augmentations and applied on the input to generate augmented samples and extra class labels. By extending data and label space, it allows the model to learn more diverse representations, which can prevent the model from being biased towards learning task-specific features. When learning new tasks, it will reduce the change of feature space and improve model generalization. On the other hand, we employ mixed feature to replace the new features since only using new feature to optimize the model will affect the representation that was previously embedded in the feature space. Instead, by mixing new and old features, old knowledge can be retained without increasing the computational complexity. Extensive experiments on three benchmarks demonstrate the superiority of our approach, which outperforms the state-of-the-art non-exemplar methods and is comparable to high-performance replay-based methods.Comment: 12 pages, 7 figure

Glycosylation of anthocyanins enhances the apoptosis of colon cancer cells by handicapping energy metabolism.

BackgroundWhile anthocyanins are proven to be effective in inhibiting tumour cell proliferation, the underlying mechanisms remain unclear. This research aims to explore the glycosylation of anthocyanins in the tumour inhibitory effects and the potential mechanism.MethodsThe tumour inhibitory effect on mouse colon cancer cells (MC38) was examined by MTT and flow cytometric analyses. The inhibitory pathway of anthocyanin was explored by assessment of tumour cell mitochondrial membrane potential (MMP), the caspase-3 and caspase-9 activity, as well as the cell energy metabolism in terms of the glucose uptake, the NAD+/NADH ratio and the ATP level.ResultsWe found that 500 μM bilberry anthocyanins extract (BAE) induced 48.1% mitochondrial damage, activated the downstream caspase cascade to form apoptotic bodies (caspase-3 activity increased by 169%, caspase-9 activity increased by 186%), and inhibited cell proliferation (survival rate: 55.97%, 24 h). In contrast, the same concentration of anthocyanidin (cyanidin) led to marginal mitochondrial damage (only 9.85%) and resulted in little inhibition of MC38 cells (survival rate: 86.84%, 24 h). For cells incubated with 500 μM BAE, reactive oxygen species (ROS) decreased by 53.8%, but the ratio of NAD+/NADH increased to 3.67, demonstrating that the mitochondrial damage was induced by blocking energy metabolism. Furthermore, cell energy metabolism is related to glucose uptake since the presence of 200 μM GLUT1 inhibitor substantially enhanced the inhibitory effects of cyanidin-3-O-glucoside (Cy-3-Glu) at 500 μM (survival rate: 51.08%, 24 h).ConclusionsThe study suggested that the glycosides of anthocyanins might handicap glucose transport and inhibit energy metabolism, which, in turn, led to mitochondrial damage and apoptosis of tumour cells