Carbon foams prepared from coal tar pitch for building thermal insulation material with low cost

A new approach is provided to resolve the large-scale applications of coal tar pitch. Carbon foams with uniform pore size are prepared at the foaming pressure of normal pressure using coal tar pitch as raw materials. The physical and chemical performance of high softening point pitch(HSPP) can be regulated by vacuumizing owing to the cooperation of vacuumizing and polycondensation. Results indicate that the optimum softening point and weight ratio of quinoline insoluble are about 292℃ and 65.7%, respectively. And the optimum viscosity of HSPP during the foaming process is distributed in the range of 1000-10000 Pa·s. The resultant carbon foam exhibits excellent performance, such as uniform pore structure, high compressive strength(4.7 MPa), low thermal conductivity(0.07 W·m^(-1) ·K^(-1)), specially, it cannot be fired under the high temperature of 1200 ℃.Thus, this kind of carbon foam is a potential candidate for thermal insulation material applied in energy saving building.

Building dynamic thermal simulation of low-order multi-dimensional heat transfer

Multi-dimensional heat transfers modeling is crucial for building simulations of insulated buildings,which are widely used and have multi-dimensional heat transfers characteristics.For this work,state-model-reduction techniques were used to develop a reduced low-order model of multi-dimensional heat transfers.With hot box experiment of hollow block wall,heat flow relative errors between experiment and low-order model predication were less than 8% and the largest errors were less than 3%.Also,frequency responses of five typical walls,each with different thermal masses or insulation modes,the low-order model and the complete model showed that the low-order model results agree very well in the lower excitation frequency band with deviations appearing only at high frequency.Furthermore,low-order model was used on intersection thermal bridge of a floor slab and exterior wall.Results show that errors between the two models are very small.This low-order model could be coupled with most existing simulation software for different thermal mass envelope analyses to make up for differences between the multi-dimensional and one-dimensional models,simultaneously simplifying simulation calculations.

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.

Feasibility of Using Wood Chips to Regulate Relative Humidity Inside a Building: A Numerical Study

The use of bio-based materials in buildings has become more and more significant last years.In most of the cases,their health properties and natural provenance have made them a great solution to face global climate warming and the new policies to reduce building energy consumption.In many thermal problems,biobased materials can allow to optimize the building thermal behavior according to its energy consumption and inside comfort conditions.So it is when they are used as an insulation material in the building.However,it is not the case in this paper.In fact,the bio-based matter is rather used as a desiccant wheel to control air conditioning inside the building.The aim of this paper is to numerically verify if it is possible to use a bed of wood chips as a hygroscopic material(or a desiccant matter)in order to modify the relative humidity inside the building in Reunion Island and so improve thermal comfort.A simple model of heat and mass transfer between a bed of wood chips and building inside air has been set up and implemented into a validated building simulation code named ISOLAB.Numerical simulations were set up for the four climate zones of the island regulations and a focus has been made on the low altitude one(with high,solar irradiation,temperature and relative humidity).Simulation results give the thermal behavior of the building particularly the temperature and relative humidity of inside air temperature,and temperature and moisture content of wood chips.The obtained results lead to determine if the wood chips bed is suitable for the reference building and to verify its technical feasibility(wood species,size of the bed,integration to the building,etc.).The results show that the use of a WCB help to decrease the building inside air temperature and water content up to 10°C less and 11.6 g.kg-1 less.These are the ways to improve inside comfort conditions.Indeed,comfort analysis have shown the possibility to significantly increase building users’thermal comfort when coupled with a fan and natural ventilation,like the regulation needs for low altitude climate.In this case,a gain of 68%of year time is achieved for a building equipped with WCB system compared to one without it(6308 hours of comfort over a year with the WCB against 350 hours without WCB).So the WCB seems to be able to help reducing cooling loads in tropical climate conditions.

Microstructure and Characterization of Capric-stearic Acid/Modified Expanded Vermiculite Thermal Storage Composites

In order to improve the thermal storage capacity of expanded vermiculite（EV） based formstable composite PCM（FS-PCM） via organic modification of EV, first, EV was modified with a sodium stearate（Na St） as surface modifier, and organic EV（OEV） with hydrophobicity and higher adsorption capacity for fatty acid was obtained. A novel capric-stearic acid eutectic（CA-SA）/OEV FS-PCM with high thermal storage capacity was then developed. OEV and CA-SA/OEV were characterized by scanning electron microscopy（SEM）, X-ray diffraction（XRD）, Fourier transform infrared spectroscopy（FTIR）, differential scanning calorimetry（DSC）, thermal gravimetry（TG）, and thermal cycling test. Results showed that OEV has obvious hydrophobicity and a higher adsorption capacity for fatty acid. Its adsorption ratio has increased by 48.71% compared with that of EV. CA-SA/OEV possesses high thermal storage density（112.52 J/g）, suitable melting temperature（20.49 ℃）, good chemical compatibility, excellent thermal stability and reliability, indicating great application potential for building energy efficiency. Moreover, organic modification of inorganic matrix may offer novel options for improving its adsorption capacity for organic PCMs and increasing heat storage capacity of corresponding FS-PCMs.

Zero-Energy-Buildings in Different Climates： Design Strategies, Simulation and Prognosis METHOD for Energy Demand

The European Directive 2010/31 claims that by 2020 only （nearly-） ZEB （zero-energy-buildings） may be built. To reach this goal, it is pertinent for buildings to be energetically optimized first. The remaining energy demand must then be covered by on-site renewable energies （PV, geothermal, etc.）. With the area of use （energy demand） and the size of the building envelope/estate （renewable energy supply） in competition with each other, the maximum number of building stories will be most likely limited. For 15 different climatic locations worldwide, the energy demand of optimised office rooms has been simulated and compared with the possible renewable energy production on site. For every location, a good correlation has been found between the simulated energy demand and data like heating and cooling degree hours. Correspondent linear equations are given here. As another result, the maximum numbers of possible stories for ZEBS have been derived, being between 3 and 10 depending on the location.

Soft Open Point Planning in Renewable-dominated Distribution Grids with Building Thermal Storage

With an increasing integration of intermittent distributed energy resources(DERs),the consequent voltage excursion and thermal overloading issues limit the self-sufficiency of distribution networks(DNs).The concept of soft open point(SOP)has been proposed as a promising solution to improve the hosting capacity of DNs.In this paper,considering the ability of building thermal storage(BTS)to increase the penetration of renewable energy in DNs,we provide an optimal planning framework for SOP and DER.The optimal planning model is aimed at minimizing the investment and operational costs while respecting various constraints,including the self-sufficiency requirement of the DN,SOP,building thermal storage capacity and DER operations,etc.A steady-state SOP model is formulated and linearized to be incorporated into the planning framework.To make full use of the BTS flexibility provided by ubiquitous buildings,a differential equation model for building thermal dynamics is formulated.A hybrid stochastic/robust optimization approach is adopted to depict the uncertainties in renewable energy and market prices.IEEE 33-bus feeder and a realistic DN in the metropolitan area of Caracas are tested to validate the effectiveness of the proposed framework and method.Case studies show that SOP/BTS plays a complementary and coordinated coupling role in the thermo-electric system,thereby effectively improving the hosting capacity and self-sufficiency of DNs.

Introducing Degree Days to Building Thermal Climatic Zoning in China

Building thermal climatic zoning is a key issue in building energy efficiency.Heating degree days(HDD) and cooling degree days(CDD) are often employed as indexes to represent the heating and cooling energy demand in climatic zoning.However,only using degree days may oversimplify the climatic zoning in regions with complex climatic conditions.In the present study,the application of degree days to current building thermal climatic zoning in China was assessed based on performance simulations.To investigate the key indexes for thermal climatic zoning,the climate characteristics of typical cities were analyzed and the relationships between the climate indexes and heating/cooling demand were obtained.The results reveal that the annual cumulative heating load had a linear correlation with HDD 18 only in regions with small differences in altitude.Therefore,HDD is unsuitable for representing the heating demand in regions with large differences in altitude.A comprehensive index(winter climatic severity index) should be employed instead of HDD,or complementary indexes(daily global solar radiation or altitude) could be used to further divide climate zones.In the current official climatic zoning,the base temperature of 26℃ for CDD is excessively high.The appropriate base temperature range is 18℃ to 22℃.This study provides a reference for selecting indexes to improve thermal climatic zoning in regions with similar climates.

A state-of-the-art review on shallow geothermal ventilation systems with thermal performance enhancement-system classifications,advanced technologies and applications

Geothermal energy with abundance and large quantity can partially cover building heating/cooling loads and promote the carbon-neutrality transitions.Shallow geothermal ventilation(SGV)system,with a little initial in-vestment cost,is one of promising technologies to partly replace the conventional air-conditioning system for air pre-cooling/pre-heating.This paper reviews applications of SGV system for improving thermal performance over latest two decades,which mainly includes the reclassification of SGV system,coupling with other advanced energy-saving technologies,application potentials for building cooling/heating under various weather conditions.Heat transfer mechanism and mathematical modelling techniques have been reviewed,together with in-depth analysis on current research trends,existing limitations,and recommendations of SGV system.Phase change materials,with considerable latent energy density,can stabilize the thermal performance with high reliability.The review identifies that optimization designs and advanced approaches need to be investigated to address the existing urgent issues of SGV system(e.g.,large land occupation,difficulty in centralized collection of condensate water timely for horizontal buried pipe,bacteria growth,polluted supply air,and high construction cost for ver-tical buried pipe).A plenty of studies show that the SGV system could greatly expand the application scope and improve system energy efficiency by combining with other energy-saving technologies.This paper will provide some guidelines for the scientific researchers and engineers to keep track on recent advancements and research trends of SGV system for the building thermal performance enhancement and pave path for future research works.

Design and performance testing of a novel building integrated photovoltaic thermal roofing panel

A novel building integrated photovoltaic thermal(BIPVT)roofing panel has been designed considering both solar energy harvesting efficiency and thermal performance.The thermal system reduces the operating temperature of the cells by means of a hydronic loop integrated into the backside of the panel,thus resulting in maintaining the efficiency of the solar panels at their feasible peak while also harvesting the generated heat for use in the building.The performance of the proposed system has been evaluated using physical experiments by conducting case studies to investigate the energy harvesting efficiency,thermal performance of the panel,and temperature differences of inlet/outlet working liquid with various liquid flow rates.The physical experiments have been simulated by coupling the finite element method(FEM)and finite volume method(FVM)for heat and mass transfer in the operation.Results show that the thermal system successfully reduced the surface temperature of the solar module from 88℃to as low as 55℃.Accordingly,the output power that has been decreased from 14.89 W to 10.69 W can be restored by 30.2%to achieve 13.92 W.On the other hand,the outlet water from this hydronic system reaches 45.4℃which can be used to partially heat domestic water use.Overall,this system provides a versatile framework for the design and optimization of the BIPVT systems.

Impact of indoor heat load and natural ventilation on thermal comfort of radiant cooling system:An experimental study

Construction and operation of buildings are responsible for about 20%of the global energy consumption.The embodied energy of conventional buildings is high due to the utilization of energy-intensive construction mate-rials and traditional construction methodology.Higher operational energy is attributed to the usage of power-consuming conventional air-conditioning systems.Therefore,moving to an energy-efficient cooling technology and eco-friendly building material can lead to significant energy savings and CO 2 emission reduction.In the present study,an energy-efficient thermally activated building system(TABS)is integrated with glass fiber rein-forced gypsum(GFRG),an eco-friendly building material.The proposed hybrid system is termed the thermally activated glass fiber reinforced gypsum(TAGFRG)system.This system is not only energy-efficient and eco-friendly but also provides better thermal comfort.An experimental room with a TAGFRG roof is constructed on the premises of the Indian Institute of Technology Madras(IITM),Chennai,located in a tropical wet and dry climate zone.The influence of indoor sensible heat load and the impact of natural ventilation on the thermal comfort of the TAGFRG system are investigated.An increase in internal heat load from 400 to 700 W deteriorates the thermal comfort of the indoor space.This is evident from the increases in operative temperatures from 29.8 to 31.5℃ and the predicted percentage of dissatisfaction from 44.5%to 80.9%.Natural ventilation increases the diurnal fluctuation of indoor air temperature by 1.6 and 1.9℃ for with and without cooling cases,respectively.It reduces the maximum indoor CO 2 concentration from 912 to 393 ppm.

Evaluation tool for the thermal performance of retrofitted buildings using an integrated approach of deep learning artificial neural networks and infrared thermography

In most countries,buildings are responsible for significant energy consumption where space heating and air conditioning is responsible for the majority of this energy use.To reduce this massive consumption and decrease carbon emission,thermal insulation of buildings can play an important role.The estimation of energy savings following the improvement of a building’s insulation remains a key area of research in order to calculate the cost savings and the payback period.In this paper,a case study has been presented where deep retrofitting has been introduced to an existing building to bring it closer to a Passivhaus standard with the introduction of insulation and solar photovoltaic panels.The thermal performance of the building with its improved insulation has been evaluated using infrared thermography.Artificial intelligence using deep learning neural networks is implemented to predict the thermal performance of the building and the expected energy savings.The prediction of neural networks is compared with the actual savings calculated using historical weather data.The results of the neural network show high accuracy of predicting the actual energy savings with success rate of about 82%when compared with the calculated values.The results show that this suggested approach can be used to rapidly predict energy savings from retrofitting of buildings with reasonable accuracy,hence providing a practical rapid tool for the building industry and communities to estimate energy savings.A mathematical model has been also developed which has indicated a life-long monitoring will be needed to precisely estimate the benefits of energy savings in retrofitting due to the change in weather conditions and people’s behaviour.

Development of a short duration method to assess the envelope thermal performance of multi-family housings

Building energy efficiency is a key factor in reducing CO_(2) emissions.For this reason,European Union(EU)member states have developed thermal regulations to ensure building thermal performance.These results are often based on results achieved with building simulation software during the design stage.However,the actual thermal performance can deviate significantly from the predicted one,and this difference is known as the energy performance gap.Accurate indicators of the actual thermal performance are a valuable tool to guarantee building quality.These indicators,including the heat transfer coefficient(HTC)and the heat loss coefficient(HLC),can be estimated by the application of in situ methods.As multi-family housing and tertiary sector buildings are an important part of the building stock,mature methods to measure their thermal performance are needed.This paper presents a short-duration method for assessing the HTC in large building typologies using a sampling approach.The method was applied in a four-storey building model under different conditions to study the limits of the method and to improve indicator bias and uncertainty.Indicator quality was strongly influenced by the external weather conditions,the temperature variation during the protocol and the heat exchange with the adjacent apartments.Under winter conditions and with stable indoor temperatures,the method had a high accuracy when the protocol was applied for half a day.It is recommended that the protocol be used over two days to improve indicator quality under less favorable test conditions.

Method for determining climatic design conditions based on the indoor thermal environment risk level

Currently,climatic design conditions are usually selected according to the frequency of climatic parameters them-selves,which method cannot reflect the indoor thermal environment risk level of the building in design.In this regard,the research proposes to construct the correlation between climatic design conditions and indoor thermal environment risk level,and explore the effect of uncertainty in building thermal performance on this correlation from the perspective of probability,thus realizing the process of selecting the climatic design conditions based on the requirement for indoor thermal environment risk level.Taking Guangzhou in China as an example,the new process of determining climatic design conditions is realized.On this basis,the difference between the traditional method and the present research method is compared.In the Chinese norm method,the indoor thermal environ-ment risk level of the building is between 0 and 0.03%when the climatic design conditions are selected with 0.57%cumulative frequency of occurrence;in the research method,the indoor thermal environment risk level of the building is between 0.2%and 0.6%when the climatic design conditions are selected with 0.57%indoor thermal environment risk level and 100%confidence level.The results indicate that the research method can meet the designer’s expectation for indoor thermal environment risk level in design more directly and accurately.

Physics-constrained graph modeling for building thermal dynamics

In this paper,we propose a graph model embedded with compact physical equations for modeling the thermal dynamics of buildings.The principles of heat flow across various components in the building,such as walls and doors,fit the message-passing strategy used by Graph Neural networks(GNNs).The proposed method is to represent the multi-zone building as a graph,in which only zones are considered as nodes,and any heat flow between zones is modeled as an edge based on prior knowledge of the building structure.Furthermore,the thermal dynamics of these components are described by compact models in the graph.GNNs are further employed to train model parameters from collected data.During model training,our proposed method enforces physical constraints(e.g.,zone sizes and connections)on model parameters and propagates the penalty in the loss function of GNN.Such constraints are essential to ensure model robustness and interpretability.We evaluate the effectiveness of the proposed modeling approach on a realistic dataset with multiple zones.The results demonstrate a satisfactory accuracy in the prediction of multi-zone temperature.Moreover,we illustrate that the new model can reliably learn hidden physical parameters with incomplete data.