9,640 research outputs found
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A review of net zero energy buildings in hot and humid climates: Experience learned from 34 case study buildings
Sustainable development in the building sector requires the integration of energy efficiency and renewable energy utilization in buildings. In recent years, the concept of net zero energy buildings (NZEBs) has become a potential plausible solution to improve efficiency and reduce energy consumption in buildings. To achieve an NZEB goal, building systems and design strategies must be integrated and optimized based on local climatic conditions. This paper provides a comprehensive review of NZEBs and their current development in hot and humid regions. Through investigating 34 NZEB cases around the world, this study summarized NZEB key design strategies, technology choices and energy performance. The study found that passive design and technologies such as daylighting and natural ventilation are often adopted for NZEBs in hot and humid climates, together with other energy efficient and renewable energy technologies. Most NZEB cases demonstrated site annual energy consumption intensity less than 100 kW-hours (kWh) per square meter of floor space, and some buildings even achieved “net-positive energy” (that is, they generate more energy locally than they consume). However, the analysis also shows that not all NZEBs are energy efficient buildings, and buildings with ample renewable energy adoption can still achieve NZEB status even with high energy use intensity. This paper provides in-depth case-study-driven analysis to evaluate NZEB energy performance and summarize best practices for high performance NZEBs. This review provides critical technical information as well as policy recommendations for net zero energy building development in hot and humid climates
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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
Closed-cycle gas dynamic laser design investigation
A conceptual design study was made of a closed cycle gas-dynamic laser to provide definition of the major components in the laser loop. The system potential application is for long range power transmission by way of high power laser beams to provide satellite propulsion energy for orbit changing or station keeping. A parametric cycle optimization was conducted to establish the thermodynamic requirements for the system components. A conceptual design was conducted of the closed cycle system and the individual components to define physical characteristics and establish the system size and weight. Technology confirmation experimental demonstration programs were outlined to develop, evaluate, and demonstrate the technology base needed for this closed cycle GDL system
Solar thermal heating and cooling. A bibliography with abstracts
This bibliographic series cites and abstracts the literature and technical papers on the heating and cooling of buildings with solar thermal energy. Over 650 citations are arranged in the following categories: space heating and cooling systems; space heating and cooling models; building energy conservation; architectural considerations, thermal load computations; thermal load measurements, domestic hot water, solar and atmospheric radiation, swimming pools; and economics
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks
An explosion of high-throughput DNA sequencing in the past decade has led to
a surge of interest in population-scale inference with whole-genome data.
Recent work in population genetics has centered on designing inference methods
for relatively simple model classes, and few scalable general-purpose inference
techniques exist for more realistic, complex models. To achieve this, two
inferential challenges need to be addressed: (1) population data are
exchangeable, calling for methods that efficiently exploit the symmetries of
the data, and (2) computing likelihoods is intractable as it requires
integrating over a set of correlated, extremely high-dimensional latent
variables. These challenges are traditionally tackled by likelihood-free
methods that use scientific simulators to generate datasets and reduce them to
hand-designed, permutation-invariant summary statistics, often leading to
inaccurate inference. In this work, we develop an exchangeable neural network
that performs summary statistic-free, likelihood-free inference. Our framework
can be applied in a black-box fashion across a variety of simulation-based
tasks, both within and outside biology. We demonstrate the power of our
approach on the recombination hotspot testing problem, outperforming the
state-of-the-art.Comment: 9 pages, 8 figure
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