Experimental investigation of the energy performance of a novel Micro-encapsulated Phase Change Material (MPCM) slurry based PV/T system

© 2015 Elsevier Ltd. As a follow-on work of the authors' theoretical study, the paper presented an experimental investigation into the energy performance of a novel PV/T thermal and power system employing the Micro-encapsulated Phase Change Material (MPCM) slurry as the working fluid. A prototype PV/T module of 800mm×1600mm×50mm was designed and constructed based on the previous modelling recommendation. The performance of the PV/T module and associated thermal and power system were tested under various solar radiations, slurry Reynolds numbers and MPCM concentrations. It was found that (1) increasing solar radiation led to the increased PV/T module temperature, decreased solar thermal and electrical efficiencies and reduced slurry pressure drop; (2) increasing the slurry Reynolds number led to the increased solar thermal and electrical efficiencies, decreased module temperature, and increased pressure drop; and (3) increasing the MPCM concentration led to the reduced module temperature and increased pressure drop. The experimental results were used to examine the accuracy of the established computer model, giving a derivation scale ranging from 1.1% to 6.1% which is an acceptable error level for general engineering simulation. The recommended operational conditions of the PV/T system were (1) MPCM slurry weight concentration of 10%, (2) slurry Reynolds number of 3000, and (3) solar radiation of 500-700W/m 2 ; at which the system could achieve the net overall solar efficiencies of 80.8-83.9%. To summarise, the MPCM slurry based PV/T thermal and power system is superior to conventional air-sourced heat pump systems (ASHP) and solar assisted heat pump systems (ISAHP), and has the potential to help reduce fossil fuel consumption and carbon emission to the environment

Micro-encapsulated phase change material (MPCM) slurries: characterization and building applications

© 2017 Micro-encapsulated Phase Change Material (MPCM) slurries, acting as the heat transfer fluids or thermal storage mediums, have gained applications in various building thermal energy systems, significantly enhancing their energy efficiency and operational performance. This paper presents a review of research on MPCM slurries and their building applications. The research collects information on the currently available MPCM particles and shells, studies of the physical, structural and thermal stability, and rheological properties of MPCM slurries, and identification/determination of the critical parameters and dimensionless numbers relating to the MPCM slurries’ heat transfer. The research suggests possible approaches for enhancing the heat transfer between a MPCM slurry and its surroundings, while several controversial phenomena and potential causes were also investigated. Furthermore, the research presents mathematical correlations established between different thermal and physical parameters relating to the MPCM slurries, and introduces a number of practical applications of the MPCM slurries in building thermal energy systems. Based on such extensive review and analyses, the research will help in identifying the current status, potential problems in existence, and future directions in research, development and practical application of MPCM slurries. It will also promote the development and application of cost-effective and energy-efficient PCM materials and thus contribute to achieving the UK and international targets in energy saving and carbon emission reductions in the building sector and beyond

Ommatidial heterogeneity in the compound eye of the male small white butterfly, Pieris rapae crucivora

The ommatidia in the ventral two-thirds of the compound eye of male Pieris rapae crucivora are not uniform. Each ommatidium contains nine photoreceptor cells. Four cells (R1-4) form the distal two-thirds of the rhabdom, four cells (R5-8) approximately occupy the proximal one-third of the rhabdom, and the ninth cell (R9) takes up a minor basal part of the rhabdom. The R5-8 photoreceptor cells contain clusters of reddish pigment adjacent to the rhabdom. From the position of the pigment clusters, three types of ommatidia can be identified: the trapezoidal (type I), square (type II), and rectangular type (type III). Microspectrophotometry with an epi-illumination microscope has revealed that the reflectance spectra of type I and type III ommatidia peak at 635 nm and those of type II ommatidia peak at 675 nm. The bandwith of the reflectance spectra is 40-50 nm. Type II ommatidia strongly fluoresce under ultra-violet and violet epi-illumination. The three types of ommatidia are randomly distributed. The ommatidial heterogeneity is presumably crucial for color discrimination

Sub-optimal Policy Aided Multi-Agent Reinforcement Learning for Flocking Control

Flocking control is a challenging problem, where multiple agents, such as drones or vehicles, need to reach a target position while maintaining the flock and avoiding collisions with obstacles and collisions among agents in the environment. Multi-agent reinforcement learning has achieved promising performance in flocking control. However, methods based on traditional reinforcement learning require a considerable number of interactions between agents and the environment. This paper proposes a sub-optimal policy aided multi-agent reinforcement learning algorithm (SPA-MARL) to boost sample efficiency. SPA-MARL directly leverages a prior policy that can be manually designed or solved with a non-learning method to aid agents in learning, where the performance of the policy can be sub-optimal. SPA-MARL recognizes the difference in performance between the sub-optimal policy and itself, and then imitates the sub-optimal policy if the sub-optimal policy is better. We leverage SPA-MARL to solve the flocking control problem. A traditional control method based on artificial potential fields is used to generate a sub-optimal policy. Experiments demonstrate that SPA-MARL can speed up the training process and outperform both the MARL baseline and the used sub-optimal policy.Comment: Accepted by IEEE International Conference on Systems, Man, and Cybernetics (SMC) 202

Sample-Efficient Multi-Agent Reinforcement Learning with Demonstrations for Flocking Control

Flocking control is a significant problem in multi-agent systems such as multi-agent unmanned aerial vehicles and multi-agent autonomous underwater vehicles, which enhances the cooperativity and safety of agents. In contrast to traditional methods, multi-agent reinforcement learning (MARL) solves the problem of flocking control more flexibly. However, methods based on MARL suffer from sample inefficiency, since they require a huge number of experiences to be collected from interactions between agents and the environment. We propose a novel method Pretraining with Demonstrations for MARL (PwD-MARL), which can utilize non-expert demonstrations collected in advance with traditional methods to pretrain agents. During the process of pretraining, agents learn policies from demonstrations by MARL and behavior cloning simultaneously, and are prevented from overfitting demonstrations. By pretraining with non-expert demonstrations, PwD-MARL improves sample efficiency in the process of online MARL with a warm start. Experiments show that PwD-MARL improves sample efficiency and policy performance in the problem of flocking control, even with bad or few demonstrations.Comment: Accepted by IEEE Vehicular Technology Conference (VTC) 2022-Fal

Study on Speed Characteristic of Material in Pipe Pneumatic Conveyor

AbstractFocusing on material kinetic characteristic in horizontal pipe and vertical pipe of pneumatic conveyor, motion differential equation of the particle groups in pipe is established and solved by introduced into Matlab. By analyzing the resistance coefficient of the particle groups in different pipes and speed characteristic curves in different initial conditions, the speed characteristic of the particle groups in accelerating section of the pipe in pneumatic conveyor is obtained. The result shows that (1) resistance coefficient affects ultimate constant velocity of the particle groups in pipe, (2) different initial conditions affect acceleration (deceleration) motion time of the particle groups in pipe and (3) the power consumed in vertical pipe is larger than that in horizontal pipe when the particle groups are in accelerating section

Decentralized Uncoded Storage Elastic Computing with Heterogeneous Computation Speeds

Elasticity plays an important role in modern cloud computing systems. Elastic computing allows virtual machines (i.e., computing nodes) to be preempted when high-priority jobs arise, and also allows new virtual machines to participate in the computation. In 2018, Yang et al. introduced Coded Storage Elastic Computing (CSEC) to address the elasticity using coding technology, with lower storage and computation load requirements. However, CSEC is limited to certain types of computations (e.g., linear) due to the coded data storage based on linear coding. Then Centralized Uncoded Storage Elastic Computing (CUSEC) with heterogeneous computation speeds was proposed, which directly copies parts of data into the virtual machines. In all existing works in elastic computing, the storage assignment is centralized, meaning that the number and identity of all virtual machines possible used in the whole computation process are known during the storage assignment. In this paper, we consider Decentralized Uncoded Storage Elastic Computing (DUSEC) with heterogeneous computation speeds, where any available virtual machine can join the computation which is not predicted and thus coordination among different virtual machines' storage assignments is not allowed. Under a decentralized storage assignment originally proposed in coded caching by Maddah-Ali and Niesen, we propose a computing scheme with closed-form optimal computation time. We also run experiments over MNIST dataset with Softmax regression model through the Tencent cloud platform, and the experiment results demonstrate that the proposed DUSEC system approaches the state-of-art best storage assignment in the CUSEC system in computation time.Comment: 10 pages, 8 figures, submitted to ISIT202

Compound eyes of the small white butterfly Pieris rapae have three distinct classes of red photoreceptors

The two subspecies of the small white butterfly, the European Pieris rapae rapae and the Asian P. r. crucivora, differ in wing colouration. Under ultraviolet light, the wings of both male and female P. r. rapae appear dark, whereas the wings of male P. r. crucivora are dark and those of females are bright. It has been hypothesized that these sexually dimorphic wing reflections in P. r. crucivora may have induced the evolution of a fluorescing-screening pigment in the violet-opsin-expressing photoreceptors of males, thus facilitating greater wavelength discrimination near 400nm. Comparing the compound eyes of the two subspecies using genetic, microscopical, spectrographic, and histological methods revealed no differences that would meaningfully affect photoreceptor sensitivity, suggesting that the fluorescing-screening pigment did not evolve in response to sexually dimorphic wing reflections. Our investigation further revealed that (i) the peri-rhabdomal reddish-screening pigments differ among the three ommatidial types; (ii) each of the ommatidial types exhibits a unique class of red photoreceptor with a distinct spectral peak; and (iii) the blue, green, and red photoreceptors of P. rapae exhibit a polarization sensitivity >2, with red photoreceptors allowing for a two-channel opponency form of polarization sensitivity

Robust Communicative Multi-Agent Reinforcement Learning with Active Defense

Communication in multi-agent reinforcement learning (MARL) has been proven to effectively promote cooperation among agents recently. Since communication in real-world scenarios is vulnerable to noises and adversarial attacks, it is crucial to develop robust communicative MARL technique. However, existing research in this domain has predominantly focused on passive defense strategies, where agents receive all messages equally, making it hard to balance performance and robustness. We propose an active defense strategy, where agents automatically reduce the impact of potentially harmful messages on the final decision. There are two challenges to implement this strategy, that are defining unreliable messages and adjusting the unreliable messages' impact on the final decision properly. To address them, we design an Active Defense Multi-Agent Communication framework (ADMAC), which estimates the reliability of received messages and adjusts their impact on the final decision accordingly with the help of a decomposable decision structure. The superiority of ADMAC over existing methods is validated by experiments in three communication-critical tasks under four types of attacks.Comment: Accepted by AAAI 202

Runoff regulation and nitrogen and phosphorus removal performance of a bioretention substrate with HDTMA-modified zeolite

As a commonly used material in bioretention substrates, natural zeolite (NZ) provides decent adsorption capacity for cation pollutants and heavy metals, but limited ability to remove anion pollutants. Hexadecyltrimethylammonium bromide (HDTMA)-modified zeolite (MZ) was used as the bioretention substrate material. The performance of the media including runoff reduction, nitrate nitrogen (NO3−-N) removal, ammonium nitrogen (NH4+-N) removal, and total phosphorus (TP) removal was assessed by the column experiment. The effects of different levels of modification, ratio of zeolite in the substrate, and rainfall intensity on media performance were investigated. The results indicate that HDTMA-modified zeolite significantly improves the NO3−-N (up to 38.2 times of NZ) and TP (up to17.5 times of NZ) removal rate of media and slightly increases the NH4+-N (up to 1.5 times of NZ) purification performance of the substrate. Compared with the media with NZ, decline on both runoff volume reduction (maximum decline up to 32.9%) and flow rate reduction (maximum decline up to 29.9%) of the media with MZ were observed. Based on multiple regression analysis, quantitative relationship models between influencing factors and response variables were established (R2 > 0.793), the level of the effect of influencing factors on response variables was investigated, and the interactions between influencing factors were explored. The main effect analysis found that the degree of modification affects NO3−-N and TP removal rate of the substrate the most, and when the amount of HDTMA molecules loaded on the zeolite surface exceeds 0.09meq/g, the modification can no longer improve NO3−-N removal efficiency