Flat lens without optical axis: Theory of imaging

We derive a general theory for imaging by a flat lens without optical axis. We show that the condition for imaging requires a material having elliptic dispersion relations with negative group refraction, equivalent to an effective anisotropic refractive index n(theta). Imaging can be achieved with both negative (n0) refractive indices. The Veselago-Pendry lens is a special case with isotropic negative refractive index of n(theta)=-1. Realizations of the imaging conditions using anisotropic media and inhomogeneous media, particularly photonic crystals, are discussed. Numerical examples of imaging and requirements for sub-wavelength imaging are also presented.Comment: 5 pages, 4 figure

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

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

Electron multiplier development /phase 1/

Fabrication of aluminum oxide thin film window for capillary type photomultiplier tube

Gaussian Effective Potential and the Coleman's normal-ordering Prescription : the Functional Integral Formalism

For a class of system, the potential of whose Bosonic Hamiltonian has a Fourier representation in the sense of tempered distributions, we calculate the Gaussian effective potential within the framework of functional integral formalism. We show that the Coleman's normal-ordering prescription can be formally generalized to the functional integral formalism.Comment: 6 pages, revtex; With derivation details and an example added. To appear in J. Phys.

Process migration in UNIX environments

To support process migration in UNIX environments, the main problem is how to encapsulate the location dependent features of the system in such a way that a host independent virtual environment is maintained by the migration handlers on the behalf of each migrated process. An object-oriented approach is used to describe the interaction between a process and its environment. More specifically, environmental objects were introduced in UNIX systems to carry out the user-environment interaction. The implementation of the migration handlers is based on both the state consistency criterion and the property consistency criterion

Correctness criteria for process migration

Two correctness criteria, the state consistency criterion and the property consistency criterion for process migration are discussed. The state machine approach is used to model the interactions between a user process and its environment. These criteria are defined in terms of the model. The idea of environment view was introduced to distinguish what a user process observes about its environment from what its environment state really is and argue that a consistent view of the environment must be maintained for every migrating process