Experimental measurement and numerical simulation of the thermal performance of a double glazing system with an interstitial Venetian blind

Venetian blinds, which were originally designed to provide sun shading and privacy, also have the potential to reduce heat transfer caused by internal and external temperature difference when integrated within the cavity between the two panes of a double glazing unit. In this paper, the thermal performance of a glazing system with and without a Venetian blind with various slat orientation angles under different temperature conditions is investigated through both experiment (undertaken in a large climate chamber) and numerical simulation (obtained via Computational Fluid Dynamic modelling). The thermal resistance of a Venetian blind glazing system varies with the change of slat inclination angle, and it also highly depends on the mean temperature of the glazing and the temperature difference between the indoor and outdoor environment. Inclusion of a Venetian blind modifies both the absolute and relative strengths of convection and radiation. Vertically oriented slats showed the most significant contribution to increasing radiative thermal resistance, which led to the best overall thermal performance. The system achieved up to 28% improvement of U-value when compared with a glazing unit without a Venetian blind. Empirical correlations generated based on simulations could be used for future building energy simulation

Design and development of a building facade integrated asymmetric compound parabolic photovoltaic concentrator (BFI-ACP-PV)

© 2018 Elsevier Ltd Building Integrated PV and Concentrating PV can generate electricity onsite and provide savings in materials and electricity costs, as well as protecting buildings from weather. In this paper, a novel truncated stationary asymmetric compound parabolic photovoltaic concentrator with a geometric concentration ratio of 2.0 has been designed and experimental characterised. The designed system is suitable for building façade application, especially for vertical façade. It has wide acceptance half angles of 0° and 55° this acceptance angle range enables the concentrator to operate year-round at its geometric gain in most of the UK and EU climatic condition. A comprehensive indoor test was carried out to evaluate the electrical and thermal characterisation of the developed Building Façade Integrated Asymmetric Compound Parabolic Photovoltaic concentrator (BFI-ACP-PV) system, and also the factors that affect the power output of the developed system. The experimental results showed that the developed BFI-ACP-PV system has the potential to increase the power output per unit solar cell area by a factor of 2, when compared with a non-concentrating PV system. Subsequently, a Phase Change Material (PCM) system was integrated to the rear of the BFI-ACP-PV system to moderate the PV temperature rise and maintain good solar to electrical conversion efficiency. It was found out that the electrical conversion efficiency for the BFI-ACP-PV coupled PCM system was increased by over 5% compared with a similar system with no PCM integrated at the rear, when the incident solar radiation intensity was 280 W/m2, this value increased by over 10% for an incident solar radiation intensity of 670 W/m2

Partial entropy in finite-temperature phase transitions

It is shown that the von Neumann entropy, a measure of quantum entanglement, does have its classical counterpart in thermodynamic systems, which we call partial entropy. Close to the critical temperature the partial entropy shows perfect finite-size scaling behavior even for quite small system sizes. This provides a powerful tool to quantify finite-temperature phase transitions as demonstrated on the classical Ising model on a square lattice and the ferromagnetic Heisenberg model on a cubic lattice.Comment: 4 pages, 6 figures, Revised versio

The contribution of ultracompact dark matter minihalos to the isotropic radio background

The ultracompact minihalos could be formed during the earlier epoch of the universe. The dark matter annihilation within them is very strong due to the steep density profile, $\rho \sim r^{-2.25}$. The high energy electrons and positrons from the dark matter annihilation can inverse Compton scatter (ICS) with the background photons, such as CMB photons, to acquire higher energy. On the other hand, the synchrotron radiation can also be produced when they meet the magnetic field. In this paper, we study the signals from the UCMHs due to the dark matter annihilation for the radio, X-ray and $\gamma$-ray band. We found that for the radio emission the UCMHs can provide one kind of source for the radio excess observed by ARCADE 2. But the X-ray signals due to the ICS effect or the $\gamma$-ray signals mainly due to the prompt emission from dark matter would exceed the present observations, such as Fermi, COMPTEL and CHANDRA. We found that the strongest limits on the fraction of UCMHs come from the X-ray observations and the constraints from the radio data are the weakest.Comment: 6 pages, 8 figures, Comments Welcome! Some Refs. are added, some presentation have been corrected. The conclusions remain unchanged. One important reference has been corrected. Some presentations are changed and added according to the referee's comments. Accepted for publication in PR

Design and development of a building façade integrated asymmetric compound parabolic photovoltaic concentrator (BFI-ACP-PV)

Building Integrated PV and Concentrating PV can generate electricity onsite and provide savings in materials and electricity costs, as well as protecting buildings from weather. In this paper, a novel truncated stationary asymmetric compound parabolic photovoltaic concentrator with a geometric concentration ratio of 2.0 has been designed and experimental characterised. The designed system is suitable for building façade application, especially for vertical façade. It has wide acceptance half angles of 0° and 55°, this acceptance angle range enables the concentrator to operate year-round at its geometric gain in most of the UK and EU climatic condition. A comprehensive indoor test was carried out to evaluate the electrical and thermal characterisation of the developed Building Façade Integrated Asymmetric Compound Parabolic Photovoltaic concentrator (BFI-ACP-PV) system, and also the factors that affect the power output of the developed system. The experimental results showed that the developed BFI-ACP-PV system has the potential to increase the power output per unit solar cell area by a factor of 2, when compared with a non-concentrating PV system. Subsequently, a Phase Change Material (PCM) system was integrated to the rear of the BFI-ACP-PV system to moderate the PV temperature rise and maintain good solar to electrical conversion efficiency. It was found out that the electrical conversion efficiency for the BFI-ACP-PV coupled PCM system was increased by over 5% compared with a similar system with no PCM integrated at the rear, when the incident solar radiation intensity was 280 W/m2, this value increased by over 10% for an incident solar radiation intensity of 670 W/m2

Scaling Law of Large Sequential Recommendation Models

Scaling of neural networks has recently shown great potential to improve the model capacity in various fields. Specifically, model performance has a power-law relationship with model size or data size, which provides important guidance for the development of large-scale models. However, there is still limited understanding on the scaling effect of user behavior models in recommender systems, where the unique data characteristics (e.g. data scarcity and sparsity) pose new challenges to explore the scaling effect in recommendation tasks. In this work, we focus on investigating the scaling laws in large sequential recommendation models. Specially, we consider a pure ID-based task formulation, where the interaction history of a user is formatted as a chronological sequence of item IDs. We don't incorporate any side information (e.g. item text), because we would like to explore how scaling law holds from the perspective of user behavior. With specially improved strategies, we scale up the model size to 0.8B parameters, making it feasible to explore the scaling effect in a diverse range of model sizes. As the major findings, we empirically show that scaling law still holds for these trained models, even in data-constrained scenarios. We then fit the curve for scaling law, and successfully predict the test loss of the two largest tested model scales. Furthermore, we examine the performance advantage of scaling effect on five challenging recommendation tasks, considering the unique issues (e.g. cold start, robustness, long-term preference) in recommender systems. We find that scaling up the model size can greatly boost the performance on these challenging tasks, which again verifies the benefits of large recommendation models