A novel improved model for building energy consumption prediction based on model integration

Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems. Moreover, accuracy is no longer the only factor in revealing model performance, it is more important to evaluate the model from multiple perspectives, considering the characteristics of engineering applications. Based on the idea of model integration, this paper proposes a novel improved integration model (stacking model) that can be used to forecast building energy consumption. The stacking model combines advantages of various base prediction algorithms and forms them into “meta-features” to ensure that the final model can observe datasets from different spatial and structural angles. Two cases are used to demonstrate practical engineering applications of the stacking model. A comparative analysis is performed to evaluate the prediction performance of the stacking model in contrast with existing well-known prediction models including Random Forest, Gradient Boosted Decision Tree, Extreme Gradient Boosting, Support Vector Machine, and K-Nearest Neighbor. The results indicate that the stacking method achieves better performance than other models, regarding accuracy (improvement of 9.5%–31.6% for Case A and 16.2%–49.4% for Case B), generalization (improvement of 6.7%–29.5% for Case A and 7.1%-34.6% for Case B), and robustness (improvement of 1.5%–34.1% for Case A and 1.8%–19.3% for Case B). The proposed model enriches the diversity of algorithm libraries of empirical models

A three-stage optimization methodology for envelope design of passive house considering energy demand, thermal comfort and cost

Due to reducing the reliance of buildings on fossil fuels, Passive House (PH) is receiving more and more attention. It is important that integrated optimization of passive performance by considering energy demand, cost and thermal comfort. This paper proposed a set three-stage multi-objective optimization method that combines redundancy analysis (RDA), Gradient Boosted Decision Trees (GBDT) and Non-dominated sorting genetic algorithm (NSGA-II) for PH design. The method has strong engineering applicability, by reducing the model complexity and improving efficiency. Among then, the GBDT algorithm was first applied to the passive performance optimization of buildings, which is used to build meta-models of building performance. Compared with the commonly used meta-model, the proposed models demonstrate superior robustness with the standard deviation at 0.048. The optimization results show that the energy-saving rate is about 88.2% and the improvement of thermal comfort is about 37.8% as compared to the base-case building. The economic analysis, the payback period were used to integrate initial investment and operating costs, the minimum payback period and uncomfortable level of Pareto frontier solution are 0.48 years and 13.1%, respectively. This study provides the architects rich and valuable information about the effects of the parameters on the different building performance

The Passive Microwave Remote Sensing of Soil Moisture: the Effect of Tilled Row Structure

The tilled rowstructure is known to be one of the important factors affecting the observations of the microwave emission from a natural surface. Measurements of this effect were carried out with both I and X band radiometers mounted on a mobile truck on a bare 40 m x 45 m row tilled field. The soil moisture content during the measurements ranged from approximately 10 percent to approximately 30 percent by dry weight. The results of these measurements showed that the variations of the antenna temperatures with incident angle theta changed with the azimuthal angle a measured from the row direction. A numerical calculation based on a composite surface roughness was made and found to predict the observed features within the model's limit of accuracy. It was concluded that the difference between the horizontally and vertically polarized temperatures was due to the change in the local angle of field emission within the antenna field of view caused by the large scale row structure

Impact of adjustment strategies on building design process in different climates oriented by multiple performance

Adjustment strategies including window ventilation and shading have important improvements in energy consumption, thermal and light environments, furthermore, the upper limit for improvement is affected by design parameters. However, studies incorporating adjustment strategies in the building design process are very limited. To address this research gap, we explore the effects of window ventilation and shading on building design performance from uncertainty analysis, sensitivity analysis, and multi-objective optimization. Furthermore, China's typical climate zones are compared given climate effects. Results indicate that (1) the uncertainty of total energy demand in the severe cold climate is most affected with the uncertainty increase rate being 32.0%, the uncertainty of thermal comfort ratio in the hot summer and cold winter climate and the hot summer and warm winter climate is most affected with the uncertainty increase rate being 16.3% and 14.0%, respectively. (2) the sensitivity analysis of the thermal comfort ratio is more sensitive to adjustment strategies than to total energy demand. The severe cold climate is more vulnerable than in other climates. (3) when multi-objective optimization is performed with maximum thermal comfort and minimum total energy demand when considering adjustment strategies, the severe cold climate has the greatest energy-saving potential (38.1%) and the hot summer and cold winter climate has the largest potential to improve thermal comfort (17.6%). More importantly, the light environment is within the comfort range from the daylight glare index, the illuminance, and illuminance uniformity ratios

Gravitational-Wave Implications for the Parity Symmetry of Gravity at GeV Scale

Gravitational waves generated by the coalescence of compact binary open a new window to test the fundamental properties of gravity in the strong-field and dynamical regime. In this work, we focus on the parity symmetry of gravity which, if broken, can leave imprints on the waveform of gravitational wave. We construct generalized waveforms with amplitude and velocity birefringence due to parity violation in the effect field theory formalism, then analyze the open data of the ten binary black-hole merger events and the two binary neutron-star merger events detected by LIGO and Virgo collaboration. We do not find any signatures of violation of gravitational parity conservation, thereby setting the lower bound of the parity-violating energy scale to be $0.07$ GeV. This presents the first observational evidence of the parity conservation of gravity at high energy scale, about 17 orders of magnitude tighter than the constraints from the Solar system tests and binary pulsar observation. The third-generation gravitational-wave detector is capable of probing the parity-violating energy scale at $\mathcal{O}(10^2)$ GeV

Heat transfer, velocity-temperature correlation, and turbulent shear stress from Navier-Stokes computations of shock wave/turbulent boundary layer interaction flows

The properties of 2-D shock wave/turbulent boundary layer interaction flows were calculated by using a compressible turbulent Navier-Stokes numerical computational code. Interaction flows caused by oblique shock wave impingement on the turbulent boundary layer flow were considered. The oblique shock waves were induced with shock generators at angles of attack less than 10 degs in supersonic flows. The surface temperatures were kept at near-adiabatic (ratio of wall static temperature to free stream total temperature) and cold wall (ratio of wall static temperature to free stream total temperature) conditions. The computational results were studied for the surface heat transfer, velocity temperature correlation, and turbulent shear stress in the interaction flow fields. Comparisons of the computational results with existing measurements indicated that (1) the surface heat transfer rates and surface pressures could be correlated with Holden's relationship, (2) the mean flow streamwise velocity components and static temperatures could be correlated with Crocco's relationship if flow separation did not occur, and (3) the Baldwin-Lomax turbulence model should be modified for turbulent shear stress computations in the interaction flows

Cross-sectional and plan-view cathodoluminescence of GaN partially coalesced above a nanocolumn array

The optical properties of GaN layers coalesced above an array of nanocolumns have important consequences for advanced optoelectronic devices. GaN nanocolumns coalesced using a nanoscale epitaxial overgrowth technique have been investigated by high resolution cathodoluminescence (CL) hyperspectral imaging. Plan-view microscopy reveals partially coalesced GaN layers with a sub-μm scale domain structure and distinct grain boundaries, which is mapped using CL spectroscopy showing high strain at the grain boundaries. Cross-sectional areas spanning the partially coalesced GaN and underlying nanocolumns are mapped using CL, revealing that the GaN bandedge peak shifts by about 25 meV across the partially coalesced layer of ∼2 μm thick. The GaN above the nanocolumns remains under tensile strain, probably due to Si out-diffusion from the mask or substrate. The cross-sectional data show how this strain is reduced towards the surface of the partially coalesced layer, possibly due to misalignment between adjacent partially coalesced regions