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Building Simulation
Journal Prestige (SJR): 0.839
Citation Impact (citeScore): 2
Number of Followers: 2  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1996-8744 - ISSN (Online) 1996-3599
Published by Springer-Verlag Homepage  [2469 journals]
  • RETRACTED ARTICLE: IoT based residential energy management system for
           demand side response through load transfer with various types of domestic
           appliances

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      Abstract: The Editor-in-Chief has retracted this article. After publication, concerns were raised about the high similarity between this article and a previous publication from different authors (Duman et al. 2021). Specifically, similarities were identified in the text in the Literature Review and Methodology sections of this article and those in Duman et al. (2021). Additionally, Tables 2 and 3 appear to be copied from Duman et al. (2021). The authors were unable to provide satisfactory source data used in their analysis upon the Editor’s request. The Editor-in-Chief therefore no longer has confidence in the authenticity of the presented data and the originality of the work.
      Authors R Ganesh Babu and C Chellaswamy do not agree to this retraction.
      Authors V Amudha and K Senthil Kumar have not responded to any correspondence from the editor or publisher about this retraction. The online version of this article contains the full text of the retracted article as Supplementary Information.
      PubDate: 2022-09-01
       
  • Archetype identification and urban building energy modeling for city-scale
           buildings based on GIS datasets

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      Abstract: Abstract Urban building energy modeling has become an efficient way to understand urban building energy use and explore energy conservation and emission reduction potential. This paper introduced a method to identify archetype buildings and generate urban building energy models for city-scale buildings where public building information was unavailable. A case study was conducted for 68,966 buildings in Changsha city, China. First, clustering and random forest methods were used to determine the building type of each building footprint based on different GIS datasets. Then, the convolutional neural network was employed to infer the year built of commercial buildings based on historical satellite images from multiple years. The year built of residential buildings was collected from the housing website. Moreover, twenty-two building types and three vintages were selected as archetype buildings to represent 59,332 buildings, covering 87.4% of the total floor area. Ruby scripts leveraging on OpenStudio-Standards were developed to generate building energy models for the archetype buildings. Finally, monthly and annual electricity and natural gas energy use were simulated for the blocks and the entire city by EnergyPlus. The total electricity and natural gas use for the 59,332 buildings was 13,864 GWh and 23.6×106 GJ. Three energy conservation measures were evaluated to demonstrate urban energy saving potential. The proposed methods can be easily applied to other cities in China.
      PubDate: 2022-09-01
       
  • Developing occupant archetypes within urban low-income housing: A case
           study in Mumbai, India

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      Abstract: Abstract Rapid urbanization pressure and poverty have created a push for affordable housing within the global south. The design of affordable housing can have consequences on the thermal (dis)comfort and behaviour of the occupants, hence requiring an occupant-centric approach to ensure sustainability. This paper investigates occupant behaviour within the urban poor households of Mumbai, India and its impact on their thermal comfort and energy use. This study is a first-of-its-kind attempt to explore the socio-demographic characteristics and energy-related behaviour of low-income occupants within Indian context. Three occupant archetypes, Indifferent Consumers; Considerate Savers; and Conscious Conventionals, were identified from the behavioural and psychographic characteristics gathered through a transverse field survey. A two-step clustering approach was adopted for occupant segmentation that highlighted considerable diversity in occupants’ adaptation measures, energy knowledge, energy habits, and their pro-environmental behaviour within similar socio-economic group. Building energy simulation of the representative archetype behaviour estimated up to 37% variations for air-conditioned and up to 8% variation for fan-assisted naturally ventilated housing units during peak summer months. The results from this study establish the significance of occupant factors in shaping energy demand and thermal comfort within low-income housing and pave way for developing occupant-centric building design strategies to serve this marginalized population. The developed low-income occupant archetypes would be useful for architects and energy modelers to generate realistic energy use profiles and improve building performance simulation results.
      PubDate: 2022-09-01
       
  • Robustness of ventilation systems in the control of walking-induced indoor
           fluctuations: Method development and case study

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      Abstract: Abstract Walking-induced fluctuations have a significant influence on indoor airflow and pollutant dispersion. This study developed a method to quantify the robustness of ventilation systems in the control of walking-induced fluctuation control. Experiments were conducted in a full-scale chamber with four different kinds of ventilation systems: ceiling supply and side return (CS), ceiling supply and ceiling return (CC), side supply and ceiling return (SC), and side supply and side return (SS). The measured temperature, flow and pollutant field data was (1) denoised by FFT filtering or wavelet transform; (2) fitted by a Gaussian function; (3) feature-extracted for the range and time scale disturbance; and then (4) used to calculate the range scale and time scale robustness for different ventilation systems with dimensionless equations developed in this study. The selection processes for FFT filtering and wavelet transform, FFT filter cut-off frequency, wavelet function, and decomposition layers are also discussed, as well as the threshold for wavelet denoising, which can be adjusted accordingly if the walking frequency or sampling frequency differs from that in other studies. The results show that for the flow and pollutant fields, the use of a ventilation system can increase the range scale robustness by 19.7%–39.4% and 10.0%–38.8%, respectively; and the SS system was 7.0%–25.7% more robust than the other three ventilation systems. However, all four kinds of ventilation systems had a very limited effect in controlling the time scale disturbance.
      PubDate: 2022-09-01
       
  • Analysing user daylight preferences in heritage buildings using virtual
           reality

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      Abstract: Abstract Technology has always been creating effective ways to support human decisions. Immersive virtual reality (IVR) has emerged to engage users in a simulated world, and this has gained the interest of a wide variety of users in the heritage industry. A historical case study built in the early 19th century is considered for an adaptive reuse exhibition. The palace is located in Cairo, Egypt, and named after Prince Omar Tosson. The current palace state incorporates a smashed top-lit zone, which is being studied and analyzed for daylighting adequacy. Three simulated distinct optimum skylight configurations are suggested for the redesign where the selection should not be based solely on simulation data, but should consider real-user preferences. Most daylight design criteria are previously based on simulation data that do not necessarily indicate the users’ preferences. But utilizing user interactive tools such as IVR to test daylight redesign options, a whole new dimension is provided. In this study, the VR users’ survey data is statistically analyzed using Statistical Package for Social Sciences (SPSS), where results revealed that the assessment attributes succeeded in reflecting the users’ preferences; which, motivated designers to consider potential users’ daylight preferences in reused spaces. The paper highlights the most significant emotional attributes that provide cost-effective and reliable information concerned with the performance of daylight in IVR before design implementation. This study compares and analyzes the effect of three skylight designs (Cases A, B & C) on the users’ perception before design implementation using (IVR) post-survey. Forty-eight participants have contributed to the study, providing their feedback on six attributes namely: Pleasant, Contrasting, Brightness, Uniform Distribution, Visual Comfort, and Satisfaction. Those attributes are evaluated for the three cases in space using five scale rating values to reveal that the “Pleasant” attribute is most reliable in the study to reflect the users’ preferences for design Case B.
      PubDate: 2022-09-01
       
  • Spatio-temporal distribution of gaseous pollutants from multiple sources
           in industrial buildings with different flow patterns

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      Abstract: Abstract Energy consumption of industrial buildings has remained continuously high, and the environmental quality requirements are also constantly improving. Only by improving industrial environmental control technology based on the transport mechanism of the pollution, can the energy consumption of industrial building environmental control be further reduced, and the environmental quality of industrial buildings can be improved as well. Therefore, after verifying the numerical simulation by experiments, this study uses a self-label method to investigate the spatio-temporal distribution of gaseous pollutants from multiple time-series sources in industrial plants with different length—span ratios. The results show that, the polluted flow in plants with different aspect ratios have different flow patterns: (i) the “Back-mixing” flow pattern occurs when the ratio of ventilation rate G and polluted flow rate at the exhaust height LP is less than 1, i.e., G/LP < 1, and (ii) the “One-way” flow pattern occurs when G/LP > 1. For plants with the “Back-mixing” pattern, the following source pollutants enter a density stratified environment induced by the retained pre-source pollutants. The flow of following source pollutants released at the same intensity as the precursor source can reach the roof, while those with low velocity and density difference may be blocked during the ascending process. The maximum height zm of the flow of the following source is related to both the initial Froude number Fr0 of the following source and the unsteady vertical density gradient of the fluid in the indoor environment dρa/dz. For plants with the “One-way” pattern, the flow from the following source enters into an environment with approximately uniform density. Under the condition of positive buoyancy, design parameters of ventilation corresponding to the vicinity of G/LP = 1 may be the optimal solution for safety and energy conservation.
      PubDate: 2022-09-01
       
  • Comparison of detached eddy simulation and standard k—ε RANS model for
           rack-level airflow analysis inside a data center

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      Abstract: Abstract High computing demands and data privacy regulations from many countries in the world have resulted in the expansion of data centers. With this, energy consumption by data centers has increased to an alarming level. Data centers are highly dynamic due to time-dependent server heat generation and cold-hot aisle arrangements, making it difficult to have real-time control for efficient thermal management. Traditional cooling strategies based on conservative set points affect energy consumption. Instead of expensive field measurements, CFD analysis of the flow field inside the data center can provide insightful data to assist the heat release from the racks. The detailed rack-level flow field inside the data center is missing in the literature as most of the studies are based on approximate results using the RANS-based k—ε model. However, DES-based models have shown the ability to resolve complex flow fields. With this finding, rack-level CFD analysis of the data center is performed using DES and standard k—ε techniques. At first, average rack inlet and outlet air temperatures in steady-state were validated with experiments within the accuracy of 1.4 µC. The distributions of turbulent kinetic energy and mean velocity inside the cold aisle were examined. The recirculation region in the cold aisle was well-captured by the DES and qualitatively validated with the experiments compared to the k—ε model. The k—ε model failed to predict SHI, RTI, and β metrics, whereas the DES model successfully captured recirculation and self-heating of the upper servers. An acceptable trade-off between computational cost and accuracy for the simulations would be a pivotal parameter for the selection of either DES or the k—ε model for the data center CFD analysis. The porous media assumption of the servers can bring uncertainties for turbulent quantities and hence further DES model for a data center can provide additional insights in this study.
      PubDate: 2022-09-01
       
  • Energy analysis of a wood or pellet stove in a single-family house
           equipped with gas boiler and radiators

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      Abstract: Abstract In the residential sector, biomass appliances are widely used for space heating and often combined with other systems. This work aims at comparing the final and primary energy consumption of different configurations, including a conventional and a ducted pellet stove and a wood log stove using air as heat transfer fluid. A dynamic analysis of the interaction between biomass stoves and conventional heating systems, such as gas boilers and radiators, is carried out within a typical single-family house in a mild climate, using TRNSYS software. In addition, natural ventilation of the building is considered using CONTAM, with a focus on external infiltrations and internal air circulation due to the buoyancy effect. Results show that the biomass device in one room promotes the airflows between adjacent thermal zones, enhancing the heat distribution through door openings, in particular when an air ducted stove is present. The final energy consumption resulting from simulations with wood-burning stoves is 21% higher than pellet stoves. The pellet stove results in similar final energy and a 30% increase in overall primary energy, while the wood stove increases the final energy by 22% and approximately 40% of overall primary energy compared to the case of a traditional gas system coupled to radiators which is considered as reference. Nevertheless, non-renewable primary energy savings are higher than 50% with pellet stoves and 60% with wood-log stoves.
      PubDate: 2022-09-01
       
  • CFD simulation of wind and thermal-induced ventilation flow of a roof
           cavity

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      Abstract: Abstract The hygrothermal performance of a ventilated roof cavity is greatly affected by the airflow passing through it. This ventilation flow is mainly driven by the wind pressure difference between openings and the thermal-induced buoyancy. However, the wind effect is not well understood as it is often neglected in previous studies. The present study investigates the properties of such airflows, including the flow pattern, flow regime, and flow rate, using a CFD method. The target building is a large-span commercial building with a low-pitched roof. To study the wind-induced airflows, the onset atmospheric boundary layer wind flow was modelled, and the results were compared with the site-measured data recorded in the literature. To study the thermal-induced buoyancy effects, a roof cavity model found in the literature with experimental data was adopted. The findings show that the flow pattern in the roof cavity varied with the airflow driven factors. The flow separation at the windward eave inlet of the thermally induced flows are more pronounced compared with those of the wind-induced flows. Furthermore, the wind-induced airflows can generate around two times more ventilation flow rate through the roof cavity compared to the thermal-induced airflow. The findings indicate that wind-induced ventilation flows are the dominant factor of the roof cavity ventilation in a large-span, low-pitched building.
      PubDate: 2022-09-01
       
  • Daily power demand prediction for buildings at a large scale using a
           hybrid of physics-based model and generative adversarial network

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      Abstract: Abstract Power demand prediction for buildings at a large scale is required for power grid operation. The bottom-up prediction method using physics-based models is popular, but has some limitations such as a heavy workload on model creation and long computing time. Top-down methods based on data driven models are fast, but less accurate. Considering the similarity of power demand patterns of single buildings and the superiority of generative adversarial network (GAN), this paper proposes a new method (E-GAN), which combines a physics-based model (EnergyPlus) and a data-driven model (GAN), to predict the daily power demand for buildings at a large scale. The new E-GAN method selects a small number of typical buildings and utilizes EnergyPlus models to predict their power demands. Utilizing the prediction for those typical buildings, the GAN then is adopted to forecast the power demands of a large number of buildings. To verify the proposed method, the E-GAN is used to predict 24-hour power demands for a set of residential buildings. The results show that (1) 4.3% of physics-based models in each building category are required to ensure the prediction accuracy; (2) compared with the physics-based model, the E-GAN can predict power demand accurately with only 5% error (measured by mean absolute percentage error, MAPE) while using only approximately 9% of the computing time; and (3) compared with data-driven models (e.g., support vector regression, extreme learning machine, and polynomial regression model), E-GAN demonstrates at least 60% reduction in prediction error measured by MAPE.
      PubDate: 2022-09-01
       
  • Erratum to: Heating load reduction characteristics of passive solar
           buildings in Tibet, China

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      PubDate: 2022-08-01
      DOI: 10.1007/s12273-022-0897-9
       
  • A simulation-based evaluation of the absolute and comparative approaches
           in a code compliance process from the energy use perspective: Cold-climate
           case study

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      Abstract: Abstract Like many countries, Canada’s building code includes a performance compliance path that compares the energy use of a proposed design to that of a reference house. Today, provinces across Canada are contemplating an alternative absolute energy use intensity approach. However, the effect of adopting the absolute approach on house design is not well understood. This study first developed a proof-of-concept methodology for a technical simulation-based comparison of the two approaches. Then, it performed a comparative analysis between the design outcomes of the two approaches using the developed methodology. To this end, statistically representative archetypes were configured to comply with the prescriptive requirements of the building code. Key characteristics of each archetype were then varied through parametric study, and the resulting energy performance under the absolute and comparative approaches were analyzed. The results of this study indicated that the two approaches had different effects on the design and energy use of houses in heating-dominated climate zones. Houses performing better under the absolute approach consumed less energy and exhibited more compact architectural form. These houses were also less sensitive to improvements in airtightness and envelope than houses performing better under the comparative approach. The results suggest that adopting the absolute approach based on the energy use intensity metric in building codes would encourage design and construction of houses with higher energy efficiency.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0859-7
       
  • Airflow pattern and performance of attached ventilation for two types of
           tiny spaces

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      Abstract: Abstract With the emergence of urban sentry boxes and capsule hotels, the development of tiny spaces with the concept of a reasonable minimum occupied space has attracted widespread attention from society. The ventilation mode that fits with the limited geometric characteristics of tiny spaces is worth exploring. Combined with the respective ventilation requirements of two types of tiny spaces, i.e., sentry box space and tiny sleeping space, this paper proposes two attached ventilation modes. A full-scale experiment cabin was established, and the simulation method was optimized through experimental data. The airflow pattern and distribution performance of the two attached ventilation modes in two types of tiny spaces were studied by the CFD method. The results showed that the airflow attached to the vertical wall could form an air curtain at the opening windows of the sentry box space, but there is a phenomenon of air leakage. The installation of the deflector can improve the integrity of the air curtain, and the best installation angle of the deflector is 60 degrees. The double side-attached ventilation mode in the tiny sleeping space can not only relieve the draught of the occupants (DR < 15%), but also firstly deliver fresh air to the occupied zone (expiratory zone MAA < 92 s). The research conclusions will add new ideas to the diversity of ventilation modes in tiny spaces.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0876-6
       
  • Predicting roof-surface wind pressure induced by conical vortex using a BP
           neural network combined with POD

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      Abstract: Abstract This study aims to examine the feasibility of predicting surface wind pressure induced by conical vortex using a backpropagation neural network (BPNN) combined with proper orthogonal decomposition (POD), in which a 1:150 scaled model with a large-span retractable roof was tested in wind tunnel under both laminar and turbulent flow conditions. The distributions of mean and fluctuating wind pressure coefficients were first described, and the effects of inflow turbulence, wind direction, roof opening were examined separately. For the prediction of wind pressure, the POD-BPNN model was trained using measurement data from adjacent points. The prediction results are overall satisfactory. The root-mean-square-error (RMSE) between test and predicted data lies mostly within 10%. In particular, the prediction of mean wind pressure is found to be better than that of fluctuating wind pressure. The outcomes in this study highlight that the proposed POD-BPNN model can be well used as a useful tool to predict surface wind pressure.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0867-7
       
  • Application and evaluation of a pattern-based building energy model
           calibration method using public building datasets

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      Abstract: Abstract Building performance simulation has been adopted to support decision making in the building life cycle. An essential issue is to ensure a building energy simulation model can capture the reality and complexity of buildings and their systems in both the static characteristics and dynamic operations. Building energy model calibration is a technique that takes various types of measured performance data (e.g., energy use) and tunes key model parameters to match the simulated results with the actual measurements. This study performed an application and evaluation of an automated pattern-based calibration method on commercial building models that were generated based on characteristics of real buildings. A public building dataset that includes high-level building attributes (e.g., building type, vintage, total floor area, number of stories, zip code) of 111 buildings in San Francisco, California, USA, was used to generate building models in EnergyPlus. Monthly level energy use calibrations were then conducted by comparing building model results against the actual buildings’ monthly electricity and natural gas consumption. The results showed 57 out of 111 buildings were successfully calibrated against actual buildings, while the remaining buildings showed opportunities for future calibration improvements. Enhancements to the pattern-based model calibration method are identified to expand its use for: (1) central heating, ventilation and air conditioning (HVAC) systems with chillers, (2) space heating and hot water heating with electricity sources, (3) mixed-use building types, and (4) partially occupied buildings.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-022-0891-2
       
  • Optimization of heat source side technical scheme of combined heat and
           water system based on a coal-fired power plant

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      Abstract: Abstract Recovering the waste heat (WH) of a power plant can conserve energy and reduce emissions. Scholars have proposed utilizing the WH of power plants in a combined heat and water (CHW) system, which is considered an economical, energy-saving, and environment-friendly way to integrate water and heat supply into long-distance transportation in urban areas of northern China. However, to date, a detailed design of the case on the heat source side of the CHW has not been developed. Therefore, in this study, the heat source side of a CHW system was divided into two cases: a single-generator set and a double-generator set, and both cases were optimized. The parameters of a multi-effect desalination (MED) process were examined; the optimal number of evaporation stages during the MED process was 12, and the optimal heat source temperature during the first stage was 70 °C. Then, by matching the extraction and exhaust steam flows, the WH of the exhaust steam in the heating season was finally utilized. Further, under each case optimal conditions, energy, exergy, and cost were analyzed. The results showed that the exergy efficiency in the heating season for each case was approximately 50%, whereas that in the non-heating season was approximately 3.5%. The economy and water quality of the single-generator case were better than those of the double-generator case. However, the absorption heat pump required in the single-generator case is difficult to realize because it operates under two working conditions.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0874-8
       
  • A cloud-based platform to predict wind pressure coefficients on buildings

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      Abstract: Abstract Natural ventilation (NV) is a key passive strategy to design energy-efficient buildings and improve indoor air quality. Therefore, accurate modeling of the NV effects is a basic requirement to include this technique during the building design process. However, there is an important lack of wind pressure coefficients (Cp) data, essential input parameters for NV models. Besides this, there are no simple but still reliable tools to predict Cp data on buildings with arbitrary shapes and surrounding conditions, which means a significant limitation to NV modeling in real applications. For this reason, the present contribution proposes a novel cloud-based platform to predict wind pressure coefficients on buildings. The platform comprises a set of tools for performing fully unattended computational fluid dynamics (CFD) simulations of the atmospheric boundary layer and getting reliable Cp data for actual scenarios. CFD-expert decisions throughout the entire workflow are implemented to automatize the generation of the computational domain, the meshing procedure, the solution stage, and the post-processing of the results. To evaluate the performance of the platform, an exhaustive validation against wind tunnel experimental data is carried out for a wide range of case studies. These include buildings with openings, balconies, irregular floor-plans, and surrounding urban environments. The Cp results are in close agreement with experimental data, reducing 60%–77% the prediction error on the openings regarding the EnergyPlus software. The platform introduced shows being a reliable and practical Cp data source for NV modeling in real building design scenarios.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0881-9
       
  • A statistical-based online cross-system fault detection method for
           building chillers

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      Abstract: Abstract Practical applications of data-driven fault detection (FD) are limited by their portability. The costs of model training and validation are extremely high when each system requires a model retrained on its own fault and fault-free data. Therefore, this paper proposes a statistical-based online cross-system FD method to address the problem of model portability. The proposed FD model can be cross-utilized between building chillers with various specifications while it only needs to update the original fault detection model by the normal operation data of the new chiller system, thus saving huge fault experimental costs for the fault detection of new chiller. First, a theoretical basis for the proposed cross-system fault detection method is presented. Then, experiments were conducted on three building chillers with different specifications. Both fault and fault-free data were collected from the three chillers. The development and validation of the proposed cross-system fault detection method are then conducted. Results show that the cross-system fault detection models perform well when used with different chillers. For instance, when the fault detection model of system #1 was cross-utilized to system #2, the detection accuracies of refrigerant leakage, refrigerant overcharge, and reduced evaporator water flow were 99.73%, 90.17%, and 96.94%, respectively. Compared with original models, the detection accuracies were improved by 33.78%, 84.07%, and 65.56%, respectively. Therefore, the proposed cross-system fault detection method has potential for online application to practical engineering FD.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0877-5
       
  • Energetic, economic, and environmental analysis of solid oxide fuel
           cell-based combined cooling, heating, and power system for cancer care
           hospital

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      Abstract: Abstract In this study, energetic, economic, and environmental analysis of solid oxide fuel cell-based combined cooling, heating, and power (SOFC-CCHP) system is proposed for a cancer care hospital building. The energy required for the hospital power, cooling, and heating demands was obtained based on real and detailed field data, which could serve as a reference for future works in the field. These data with a 3D model for the hospital building are constructed and created in eQUEST software to precisely calculate the energy demands of the existing system (baseline case). Then, energetic, economic, and environmental models were developed to compare and assess the performance of the proposed SOFC-CCHP system. The results show that the proposed system can cover about 49% to 77% of the power demand of the hospital with an overall efficiency of 78.3%. Also, the results show that the levelized cost of electricity of the system and its payback period at the designed capacity of the SOFC is 0.087 $/kWh and 10 years, respectively. Furthermore, compared to the baseline system of the hospital, the SOFC-CCHP reduces the CO2 emission by 89% over the year. The sensitivity analysis showed that a maximum SOFC efficiency of 52% and overall efficiency of 80% are achieved at cell operating temperature of 1027 °C and fuel utilization factor of 0.85.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0865-9
       
  • Optimisation design and verification of the acoustic environment for
           multimedia classrooms in universities based on simulation

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      Abstract: Abstract The acoustic environment of the classroom is one of the most important factors influencing the teaching and learning effects of the teacher and students. It is critical to ensure good speech intelligibility in classrooms. However, due to some factors, it may not be easy to achieve an ideal classroom acoustic environment, especially in large-scale multimedia classrooms. In a real renovation project of 39 multimedia classrooms in a university, seven typical rooms were selected, and the acoustic environment optimisation design and verification for these multimedia classrooms were performed based on simulation. First, the acoustic and sound reinforcement design schemes were determined based on the room acoustics software ODEON. Next, the effects of the optimisation design were analysed, and the simulated and measured results were compared; the accuracy of using the reduced sound absorption coefficients, which were determined empirically, was also examined. Finally, the recommended reverberation times (RTs) in multimedia classrooms corresponding to speech intelligibility were discussed, the effectiveness of the speech transmission index (STI) as a primary parameter for classroom acoustic environment control was considered, and the acoustic environment under the unoccupied and occupied statuses was compared. The results revealed that although there are many factors influencing the effect of classroom acoustic environment control, an adequate result can be expected on applying the appropriate method. Considering both the acoustic design and visual requirements also makes the classroom likely to have a good visual effect in addition to having a good listening environment.
      PubDate: 2022-08-01
      DOI: 10.1007/s12273-021-0875-7
       
 
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