Life cycle assessment of white roof and sedum-tray garden roof for office buildings in China

White roof (WR) and Sedum lineare tray garden roof (STGR) have been convinced to improve the energy-efficiency and provide various benefits for conventional impervious grey roofs. Some national and local standards have standardized and recommended these technologies in existing building retrofits, however, they do not include assessment and choice of a particular roof retrofit in different climates. This paper presents a 40-year life-cycle cost analysis (LCCA) of an office building roof retrofitted by adding either WR or STGR over an existing grey roof in five cities, located in four Chinese climate zones. The LCCA find that the WR retrofits exhibit positive life-cycle net savings (NS) in warm winter zones, ranging 5.7–35.1 CNY/m 2 , and STGR retrofits have negative NS of -81.3– -16.7 CNY/m 2 in all climate zones. The NS of both WR and STGR generally tend to improve as one moves from the coldest cities to the warmest cities. LCCA results suggest that adding new building codes concerning crediting or prescribing WR and STGR retrofits into office buildings with grey roofs in hot summer climate zones and warm winter zone in China, respectively. And featured by more specific requirements, the localized Technical Norms help promote the implementation of new building codes

Comparison of Recoil-Induced Resonances (RIR) and Collective Atomic Recoil Laser (CARL)

The theories of recoil-induced resonances (RIR) [J. Guo, P. R. Berman, B. Dubetsky and G. Grynberg, Phys. Rev. A {\bf 46}, 1426 (1992)] and the collective atomic recoil laser (CARL) [ R. Bonifacio and L. De Salvo, Nucl. Instrum. Methods A {\bf 341}, 360 (1994)] are compared. Both theories can be used to derive expressions for the gain experienced by a probe field interacting with an ensemble of two-level atoms that are simultaneously driven by a pump field. It is shown that the RIR and CARL formalisms are equivalent. Differences between the RIR and CARL arise because the theories are typically applied for different ranges of the parameters appearing in the theory. The RIR limit considered in this paper is $qP_{0}/M\omega_{q}\gg 1$, while the CARL limit is $qP_{0}/M\omega_{q}\lesssim 1$, where $$ is the magnitude of the difference of the wave vectors of the pump and probe fields, $P_{0}$ is the width of the atomic momentum distribution and $$ is a recoil frequency. The probe gain for a probe-pump detuning equal to zero is analyzed in some detail, in order to understand how the gain arises in a system which, at first glance, might appear to have vanishing gain. Moreover, it is shown that the calculations, carried out in perturbation theory have a range of applicability beyond the recoil problem. Experimental possibilities for observing CARL are discussed.Comment: 16 pages, 1 figure. Submitted to Physical Review

Customizing kernel functions for SVM-based hyperspectral image classification

Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available algorithms. However, few efforts have been made to extend SVMs to cover the specific requirements of hyperspectral image classification, for example, by building tailor-made kernels. Observation of real-life spectral imagery from the AVIRIS hyperspectral sensor shows that the useful information for classification is not equally distributed across bands, which provides potential to enhance the SVM's performance through exploring different kernel functions. Spectrally weighted kernels are, therefore, proposed, and a set of particular weights is chosen by either optimizing an estimate of generalization error or evaluating each band's utility level. To assess the effectiveness of the proposed method, experiments are carried out on the publicly available 92AV3C dataset collected from the 220-dimensional AVIRIS hyperspectral sensor. Results indicate that the method is generally effective in improving performance: spectral weighting based on learning weights by gradient descent is found to be slightly better than an alternative method based on estimating ";relevance"; between band information and ground trut

Screw instability of the magnetic field connecting a rotating black hole with its surrounding disk

Screw instability of the magnetic field connecting a rotating black hole (BH) with its surrounding disk is discussed based on the model of the coexistence of the Blandford-Znajek (BZ) process and the magnetic coupling (MC) process (CEBZMC). A criterion for the screw instability with the state of CEBZMC is derived based on the calculations of the poloidal and toroidal components of the magnetic field on the disk. It is shown by the criterion that the screw instability will occur, if the BH spin and the power-law index for the variation of the magnetic field on the disk are greater than some critical values. It turns out that the instability occurs outside some critical radii on the disk. It is argued that the state of CEBZMC always accompanies the screw instability. In addtition, we show that the screw instability contributes only a small fraction of magnetic extraction of energy from a rotating BH.Comment: 18 pages, 13 figures; Accepted by Ap

The Influences of Outflow on the Dynamics of Inflow

Both numerical simulations and observations indicate that in an advection-dominated accretion flow most of the accretion material supplied at the outer boundary will not reach the inner boundary. Rather, they are lost via outflow. Previously, the influence of outflow on the dynamics of inflow is taken into account only by adopting a radius-dependent mass accretion rate $\dot{M}=\dot{M}_0 (r/r_{\rm out})^s$ with $s>0$. In this paper, based on a 1.5 dimensional description to the accretion flow, we investigate this problem in more detail by considering the interchange of mass, radial and azimuthal momentum, and the energy between the outflow and inflow. The physical quantities of the outflow is parameterized based on our current understandings to the properties of outflow mainly from numerical simulations of accretion flows. Our results indicate that under reasonable assumptions to the properties of outflow, the main influence of outflow has been properly included by adopting $\dot{M}=\dot{M}_0 (r/r_{\rm out})^s$.Comment: 16 pages, 5 figures. accepted for publication in Ap

Physics-Informed Machine Learning of Argon Gas-Driven Melt Pool Dynamics

Melt pool dynamics in metal additive manufacturing (AM) is critical to process stability, microstructure formation, and final properties of the printed materials. Physics-based simulation including computational fluid dynamics (CFD) is the dominant approach to predict melt pool dynamics. However, the physics-based simulation approaches suffer from the inherent issue of very high computational cost. This paper provides a physics-informed machine learning (PIML) method by integrating neural networks with the governing physical laws to predict the melt pool dynamics such as temperature, velocity, and pressure without using any training data on velocity. This approach avoids solving the highly non-linear Navier-Stokes equation numerically, which significantly reduces the computational cost. The difficult-to-determine model constants of the governing equations of the melt pool can also be inferred through data-driven discovery. In addition, the physics-informed neural network (PINN) architecture has been optimized for efficient model training. The data-efficient PINN model is attributed to the soft penalty by incorporating governing partial differential equations (PDEs), initial conditions, and boundary conditions in the PINN model