Double perovskite anti-supported rare earth oxide catalyst CeO_(2)/La_(2)CoFeO_(6)for efficient ventilation air methane combustion

Ventilation air methane is one of available resources with a massive reserve.However,most of ventilation air methane is discharged into the air and pollutes the environment.Catalysts with high temperature resistance(>800℃)for ventilation air methane are very essential for utilization of the ventilation air methane.We mainly prepared catalysts CeO_(2)/La_(2)CoFeO_(6)and La_(2)CoFeO_(6)/CeO_(2)and comparative samples CeO_(2)and La_(2)CoFeO_(6)by the simple sol-gel method and calcined them under 9000C,and tested the catalytic performance of ventilation air methane combustion under the condition of 5 vol%H_(2)O.The experimental results show that the light-off temperature(T_(1O))and complete combustion temperature(T_(90))of the ventilation air methane combustion reaction of CeO_(2)/La_(2)CoFeO_(6)catalyst are 417.4 and 587.7℃,respectively.T_(1O)and Tgo of La_(2)CoFeO_(6)/CeO_(2)only reach 425.5 and 615.8℃.The T_(10)and T_(9O)of CeO_(2)/La_(2)CoFeO_(6)are 417.4 and 587.7℃,which are lower than those of La_(2)CoFeO_(6)[T_(10)=452.4℃and T_(90)=673.0℃)and La_(2)CoFeO_(6)/CeO_(2)(T_(10)=425.5℃and T_(90)=615.8℃).Therefore,the catalytic performance of the anti-supported rare earth oxide catalyst CeO_(2)/La_(2)CoFeO_(6)is better than that of La_(2)CoFeO_(6)and supported catalyst La_(2)CoFeO_(6)/CeO_(2).

Facile Synthesis of Mesoporous Co3O4 Nanoflowers for Catalytic Combustion of Ventilation Air Methane

Flower-like Co3O4 hierarchical microspheres composed of self-assembled porous nanoplates were pre- pared by employing Pluronic F127 block-copolymer as template. The samples were characterized by powder X-ray diffraction（PXRD）, scanning/transmission electron microscopy（SEM/TEM）, and nitrogen adsorption-desorption at 77 K. The results show that the catalytic activity of Co3O4 nanoflowers for the combustion of ventilation air methane is higher than that of commercial Co3O4. The superior catalytic performance of this material can be related to its dominantly exposed {112} crystal planes and higher content of surface Co3＋.

Increasing Ventilation by Passive Strategies: Analysis of Indoor Air Circulation Changes through the Utilization of Microclimate Elements

A demand for renewable alternatives that would be able to deal with the problems related to well-being is directly linked to the world’s growing needs to save energy and reduce environmental costs. For a project implementation addressing these issues, it is essential to know the climatic conditions of the target area. Taking natural ventilation, climatic factors, and renewable alternatives as important sources of comfort, in this work, passive strategies, through the utilization of microclimate elements as well as the location of outside obstacles, were imposed on an initial and specific project. The objective was to introduce obstacles which could interfere in the field of external wind and evaluate whether this outside intervention is able to make changes in indoor air circulation. The wind fields for the studied cases were obtained by computational simulations, and their consequences were analyzed to attain thermal comfort. The method adopted to obtain the wind fields was a Petrov-Galerkin type method, which is a stabilized mixed finite element method of the Navier-Stokes equations considering the incompressibility and formulated in primitive variables, velocity and pressure. The obtained results point to the solutions that promote the increase or decrease of the wind-field intensity.

Practice and analysis of recycling non-drinking water from air-condition and reverse-osmosis system into rainwater collection system

This paper is based on the rainwater collection project in the retrofit of the Dongyi teaching block in Zhejiang University Xixi Campus.The analysis incorporates the local meteorological data, recycling water utilization, and precipitation adjustment.The rainwater collection system in this program also adds the condensation water from the heating, ventilation and air conditioning （ HVAC） system and the concentration from the reverse-osmosis system used for watering greens and supplying waterscapes.By calculating, the quantity of the HVAC condensation water in summer is 3.48 m3/d, and the quantity of the reverse-osmosis concentrated water is 198 to 396 L/d.This method solves the water shortage caused by high evaporation in summer and low precipitation in winter.Supported by empirical monitoring data, the proposed method significantly increases the economic efficiency of the system during the summer period.

LaMnO_(3)(La_(0.8)Sr_(0.2)MnO_(3))Perovskites for Lean Methane Combustion:Effect of Synthesis Method

The effect of the preparation method on the properties of LaMnO3 and La0.8Sr0.2MnO3 perovskite was studied. Materials were prepared by four methods: sol-gel, chemical combustion, solvothermal and spray pyrolysis and characterized. The effect of the synthesis method on the texture, acid-base character of the surface, reducibility with hydrogen, oxygen desorption, surface composition and catalytic activity for combustion of lean methane was studied. It was found that synthesis method affects physicochemical properties of obtained materials-solvothermally produced materials exhibit well-developed surface area, presence of reactive oxygen species on surface and high catalytic activity for CH4 combustion. Generally, LaMnO3 and La0.8Sr0.2MnO3 perovskites show catalytic activity for lean CH4 combustion comparable or higher than the activity of 0.5 wt.% Pt/Al2O3 but lower than 1 wt.% Pd/Al2O3.

Country-level meteorological parameters for building energy efficiency in China

Accurate basic data are necessary to support performance-based design for achieving carbon peak and carbon neutral targets in the building sector.Meteorological parameters are the prerequisites of building thermal engineering design,heating ventilation and air conditioning design,and energy consumption simulations.Focusing on the key issues such as low spatial coverage and the lack of daily or higher time resolution data,daily and hourly models of the surface meteorological data and solar radiation were established and evaluated.Surface meteorological data and solar radiation data were generated for 1019 cities and towns in China from 1988 to 2017.The data were carefully compared,and the accuracy was proved to be high.All the meteorological parameters can be assessed in the building sector via a sharing platform.Then,country-level meteorological parameters were developed for energy-efficient building assessment in China,based on actual meteorological data in the present study.This set of meteorological parameters may facilitate engineering applications as well as allowing the updating and expansion of relevant building energy efficiency standards.The study was supported by the National Science and Technology Major Project of China during the 13th Five-Year Plan Period,named Fundamental parameters on building energy efficiency in China,comprising of 15 top-ranking universities and institutions in China.

The Generation of Typical Meteorological Year and Climatic Database of Turkey for the Energy Analysis of Buildings

For sustainable development, a reduction in energy demand is essential. This could be achieved through improving energy efficiency, effective energy conservation and management. The weather conditions of a given region are the most important consideration for the proper design of space AC （Air Conditioning） systems. In this study, the typical meteorological year and climatic database of Turkey for the energy analysis of buildings were generated by SQL （Structured Query Language） database programmimg language. The Finkelstein-Schafer statistical method was applied to analyze the hourly measured weather data of a 23-year period （1989-2012） and select representative TMMs （Typical Meteorological Months）. The selection criteria were based on 13 meteorological parameters. These parameters are the daily mean, maximum and minimum values and ranges of temperature, dew-point and wind velocity and the daily values of global solar radiation. According to results of TMY （Typical Meteorological Year）, climatic database of Turkey including daily or hourly climate variables was created in SQL data tables.

Effects of supply air temperature and inlet location on particle dispersion in displacement ventilation rooms

The effects of supply temperature and vertical location of inlet air on particle dispersion in a displacement ventilated （DV） room were numerically modeled with validation by experimental data from the literature. The results indicate that the temperature and vertical location of inlet supply air did not greatly affect the air distribution in the upper parts of a DV room, but could significantly influence the airflow pattern in the lower parts of the room, thus affecting the indoor air quality with contaminant sources located at the lower level, such as particles from working activities in an office. The numerical results also show that the inlet location would slightly influence the relative ventilation efficiency for the same air supply volume, but particle concentration in the breathing zone would be slightly lower with a low horizontal wall slot than a rectangular diffuser. Comparison of the results for two different supply temperatures in a DV room shows that, although lower supply temperature means less incoming air volume, since the indoor flow is mainly driven by buoyancy, lower supply temperature air could more efficiently remove passive sources （such as particles released from work activities in an office）. However, in the breathing zone it gives higher concentration as compared to higher supply air temperature. To obtain good indoor air quality, low supply air temperature should be avoided because concentration in the breathing zone has a stronger and more direct impact on human health.

Experimental Study of the Diffusion of a Confined Wall Jet through a Perforated Plate: Influence of the Porosity and the Geometry

This paper investigated lateral diffusion of a confined two-dimensional wall jet (air inlet height: 5 cm) through a perforated plate. We considered two plates with porosities of and . The plates were positioned at distances of 10 cm and 20 cm below the jet inlet. The experiments were realized using 2D Laser Doppler Anemometer (LDA). Different profiles of mean and fluctuating velocities are presented. The presence of a perforated plate strongly modified the airflow pattern compared to an empty enclosure. The velocities above and below the plate depend on several parameters, including the porosity and the plate’s position relative to the inlet slot and the longitudinal position. The difference between the flow velocity above and below the plates could not be related using a universal formula that depends on these parameters. We also investigated the influence of a porous media of a height of 20 cm (a stack of spheres having a diameter of 3.75 cm) located below the perforated plate. The results highlight that the porous medium strengthens the effects of the perforated plate on the flow.

Optimal Scheduling of Residential Heating, Ventilation and Air Conditioning Based on Deep Reinforcement Learning

Residential heating, ventilation and air conditioning(HVAC) provides important demand response resources for the new power system with high proportion of renewable energy. Residential HAVC scheduling strategies that adapt to realtime electricity price signals formulated by demand response program and ambient temperature can significantly reduce electricity costs while ensuring occupants' comfort. However, since the pricing process and weather conditions are affected by many factors, conventional model-based method is difficult to meet the scheduling requirements in complex environments. To solve this problem, we propose an adaptive optimal scheduling strategy for residential HVAC based on deep reinforcement learning(DRL) method. The scheduling problem can be regarded as a Markov decision process(MDP). The proposed method can adaptively learn the state transition probability to make economical decision under the tolerance violations. Specifically, the residential thermal parameters obtained by the leastsquares parameter estimation(LSPE) can provide a basis for the state transition probability of MDP. Daily simulations are verified under the electricity prices and temperature data sets, and numerous experimental results demonstrate the effectiveness of the proposed method.

Sound Reduction Control in Acoustic Enclosure with Air Ventilation

An acoustic enclosure system with both interior sound reduction and air ventilation is designed and demonstrated.The system consists of a rectangular enclosed space coupled with ventilated metamaterials and microperforated panels(MPPs).By modeling the ventilated metamaterial as an impedance boundary condition,an analytic model is developed to characterize the frequency response of interior acoustic fields and evaluate the sound reduction performance of MPP structures.Numerical simulations are conducted to validate the accuracy of the theoretical model.It is found that the resonance response of the enclosure system can be suppressed by proper arrangement of the MPPs.Even with open area for airflow,the system still possesses good sound isolation originating from the low-transmission behavior of the ventilated metamaterial.The proposed model system may find potential applications in noise control engineering.

Characteristic studies of heat sources and performance analysis of free-cooling assisted air conditioning and ventilation systems for working faces of mineral mines

High temperature heat hazard at mineral mine becomes more and more serious as the increase of mining depth.Heat sources at working faces of mineral mines are complex and are of different characteristics,presenting new challenges for air conditioning systems.In this paper,heat sources at four types of working faces are summarized and their characteristics are investigated.Based on this,simplified equations,which are linear with length of working faces,are proposed to calculate heat dissipation rates.So that the main heat sources of different working faces can be found,and cooling load of air conditioning systems can be calculated.Then,considering main heat sources of coal mines,a typical working face is designed to investigate performances of different ventilation systems and air conditioning systems.Simulation results show that segmented ventilation systems(SC)and heat shield assisted centralized ventilation systems(CCHS)can realize much better temperature distributions at working faces.However,cooling load can be greatly reduced for CCHS,when untreated air is supplied to the coal seam side.Based on this,free cooling assisted air conditioning systems are designed,and annual average energy efficiency ratio(EERann)of the systems are investigated and compared between direct evaporate cooling and indirect evaporate cooling(IEC).For SC,as compared with scenarios without free-cooling,IEC can increase EERann by 15%-23%and 22%-32%under Benxi and Datong ambient conditions,respectively.Besides,to ensure high EERann,CCHS is preferred and it is essential to increase thermal insulation of air ducts.

Analysis and Evaluation of Thermal-cooling Loads of Office Buildings Using Carrier Software in Iran

The importance and necessity of energy saving in the world have been dis­cussed for many years,but achieving a logical and transparent solution is still one of the main challenges and problems of the world’s economy.The rapid growth of energy consumption in the last two decades has caused the security of the domestic energy supply of buildings to face serious prob­lems.In this research,first by entering parameters such as the type of mate­rials,doors and windows,and the type of soil on the floor connected to the ground,etc.in the heat and cold load calculation software(HAP Carrier)as the design calculations and then in the second step entering the specifica­tions inferred from the Iran’s national building code as a reference for ener­gy saving calculations,calculations are performed and compared as the first criterion,and finally these two outputs are compared.The actual energy consumption and determination of the building energy consumption index are determined as another criterion,as well as the degree of deviation from the actual consumption.The results showed that the theoretical method and the thermal and refrigeration load calculations of the Zanjan Gas Company building have 6%difference in cooling load but the heating load is about 34%different,which means for cooling loads,the theoretical model can be used with high accuracy but for heating loads,the national building code needs fundamental changes.

Experimental and Numerical Investigation of the Diffusion of a Confined Wall Jet through a Perforated Plate

When performing numerical modeling of fluid flows where a clear medium is adjacent to a porous medium, a degree of difficulty related to the condition at the interface between the two media, where slip velocity exists, is encountered. A similar situation can be found when a jet flow interacts with a perforated plate. The numerical modeling of a perforated plate by meshing in detail each hole is most often impossible in a practical case (many holes with different shapes). Therefore, perforated plates are often modeled as porous zones with a simplified hypothesis based on pressure losses related to the normal flow through the plate. Nevertheless, previous investigations of flow over permeable walls highlight the impossibility of deducing a universal analytical law governing the slip velocity coefficient since the latter depends on many parameters such as the Reynolds number, porosity, interface structure, design of perforations, and flow direction. This makes the modeling of such a configuration difficult. The present study proposes an original numerical interface law for a perforated plate. It is used to model the turbulent jet flow interacting with a perforated plate considered as a fictitious porous medium without a detailed description of the perforations. It considers the normal and tangential effects of the flow over the plate. Validation of the model is realized through comparison with experimental data.

Torque characteristics in a large permanent magnet synchronous generator with stator radial ventilating air ducts

In this study, we investigated the torque characteristics of large low-speed direct-drive permanent magnet synchronous generators with stator radial ventilating air ducts for offshore wind power applications. Magnet shape optimization was used first to improve the torque characteristics using two-dimensional finite element analysis（FEA） in a permanent magnet synchronous generator with a common stator. The rotor step skewing technique was then employed to suppress the impacts of mechanical tolerances and defects, which further improved the torque quality of the machine. Comprehensive three-dimensional FEA was used to evaluate accurately the overall effects of stator radial ventilating air ducts and rotor step skewing on torque features. The influences of the radial ventilating ducts in the stator on torque characteristics, such as torque pulsation and average torque in the machine with and without rotor step skewing techniques, were comprehensively investigated using three-dimensional FEA. The results showed that stator radial ventilating air ducts could not only reduce the average torque but also increase the torque ripple in the machine. Furthermore, the torque ripple of the machine under certain load conditions may even be increased by rotor step skewing despite a reduction in cogging torque.

HVAC energy cost minimization in smart grids: A cloud-based demand side management approach with game theory optimization and deep learning

In this paper, we present a novel cloud-based demand side management (DSM) optimization approach for the cost reduction of energy usage in heating, ventilation and air conditioning (HVAC) systems in residential homes at the district level. The proposed approach achieves optimization through scheduling of HVAC energy usage within permissible bounds set by house users. House smart home energy management (SHEM) devices are connected to the utility/aggregator via a dedicated communication network that is used to enable DSM. Each house SHEM can predict its own HVAC energy usage for the next 24 h using minimalistic deep learning (DL) prediction models. These predictions are communicated to the aggregator, which will then do day ahead optimizations using the proposed game theory (GT) algorithm. The GT model captures the interaction between aggregator and customers and identifies a solution to the GT problem that translates into HVAC energy peak shifting and peak reduction achieved by rescheduling HVAC energy usage. The found solution is communicated by the aggregator to houses SHEM devices in the form of offers via DSM signals. If customers’ SHEM devices accept the offer, then energy cost reduction will be achieved. To validate the proposed algorithm, we conduct extensive simulations with a custom simulation tool based on GridLab-D tool, which is integrated with DL prediction models and optimization libraries. Results show that HVAC energy cost can be reduced by up to 36% while indirectly also reducing the peak-to-average (PAR) and the aggregated net load by up to 9.97%.

Clustering compression-based computation-efficient calibration method for digital twin modeling of HVAC system

Digital twin is regarded as the next-generation technology for the effective operation of heating,ventilation and air conditioning(HVAC)systems.It is essential to calibrate the digital twin models to match them closely with real physical systems.Conventional real-time calibration methods cannot satisfy such requirements since the computation loads are beyond acceptable tolerances.To address this challenge,this study proposes a clustering compression-based method to enhance the computation efficiency of digital twin model calibration for HVAC systems.This method utilizes clustering algorithms to remove redundant data for achieving data compression.Moreover,a hierarchical multi-stage heuristic model calibration strategy is developed to accelerate the calibration of similar component models.Its basic idea is that once a component model is calibrated by heuristic methods,its optimal solution is utilized to narrow the ranges of parameter probability distributions of similar components.By doing so,the calibration process can be guided,so that fewer iterations would be used.The performance of the proposed method is evaluated using the operational data from an HVAC system in an industrial building.Results show that the proposed clustering compression-based method can reduce computation loads by 97%,compared to the conventional calibration method.And the proposed hierarchical heuristic model calibration strategy is capable of accelerating the calibration process after clustering and saves 14.6%of the time costs.

A modified zone model for estimating equivalent room thermal capacity

The zone model has been widely applied in control analysis of heating, ventilation and air conditioning （HVAC） systems to achieve a high building efficiency. This paper proposed a modified zone model which is much simpler in the HVAC system simulation and has the similar accuracy to the complicated simulation model. The proposed model took into consideration the effect of envelop heat reservoir on the room indoor temperature by introducing the thermal admittance of the inner surfaces of the building enclosure. The thermal admittance for the building enclosure was developed based on the building thermal network analytical theory and transfer function method. The efficacy of the proposed model was demonstrated by comparing it with the complicated model -- heat balance method （HTB2 program）. The predicted results from the proposed model well agreed with those from the complicated simulation. The proposed model can then make the HVAC system dynamic simulation much faster and more acceptable for control design due to its simplicity and efficiency.

Simulating dispatchable grid services provided by flexible building loads:State of the art and needed building energy modeling improvements

End-use electrical loads in residential and commercial buildings are evolving into flexible and cost-effective resources to improve electric grid reliability,reduce costs,and support increased hosting of distributed renewable generation.This article reviews the simulation of utility services delivered by buildings for the purpose of electric grid operational modeling.We consider services delivered to(1)the high-voitage bulk power system through the coordinated action of many,distributed building loads working together,and(2)targeted support provided to the operation of low-voltage electric distribution grids.Although an exhaustive exploration is not possible,we emphasize the ancillary services and voltage management buildings can provide and summarize the gaps in our ability to simulate them with traditional building energy modeling(BEM)tools,suggesting pathways for future research and development.

Machine Learning and Deep Learning Methods for Enhancing Building Energy Efficiency and Indoor Environmental Quality – A Review

The built environment sector is responsible for almost one-third of the world’s final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.