Conference Agenda

Session
Session F2.6 (Online Track): Improving indoor environmental quality
Time:
Friday, 03/Sept/2021:
10:30 - 12:00

Location: Virtual Meeting Room 2

External Resource: Click here to join the Zoom Meeting
Presentations
10:30 - 10:48

Performance evaluation of passive hygrothermal control for houses using a thermodynamic HAM model

Haksung Lee1, Akihito Ozaki2

1Department of Architecture, Chungbuk National University, Cheongju, Republic of Korea; 2Kyushu University, Japan

Aim and Approach

(max 200 words)

With the aim of this study is to design a passive house which have constant temperature and humidity performance and functions of cooling/dehumidification in hot and humid summer and heat collection in cold and dry winter using renewable energy, we have developed a high-performance envelope system that can also be applied to houses of dry construction method which are mainly used for industrial building materials. The proposed system is a variable thermal performance intelligent passive system (PDSC: Passive Dehumidification and Solar Collection), which utilizes a thermodynamic potential [1] difference between indoors and outdoors to cool and dehumidify naturally in the summer and to collect the solar heat in the winter by air circulation.

We have already reported on fundamental research by conducting numerical simulations based on laboratory experiments using roof models [2] and a housing model [3]. Based on the previous research, we designed and constructed a full-scale house to verify the applicability and effectiveness of this system to actual houses. The temperature and humidity control performance and the energy-saving effect of this system have been studied through outdoor experiments using a full-scale demonstration house and simulation of building temperature, humidity, heat load that considers coupled heat, moisture, and air transfer.

Scientific Innovation and Relevance

(max 200 words)

It is estimated that the energy consumption would be slightly reduced even if the heat insulation and airtight performance of houses are further strengthened. Therefore, the introduction of new technology is indispensable for further energy saving aiming at a zero-energy house in the future. In particular, because there is no effective reduction method for the latent heat load during cooling of humid summer, innovative energy-saving technology is required as a countermeasure. Also, to reduce the heating load, which occupies most of the heat load, passive technology using solar thermal energy can be expected.

The PDSC system uses the thermodynamic potential difference between indoor and outdoor, which is related to various factors, as the driving force for heat and moisture transfer. Therefore, various physical quantities related to heat and water vapor diffusion such as temperature, concentration, pressure, external force, and adsorption force are unified and expressed in energy of the same dimension (potential defined by thermodynamic function). The fundamental concept of this system can be theoretically explained by expressing the coupled phenomenon as a flow of energy according to nonequilibrium thermodynamics.

Preliminary Results and Conclusions

(max 200 words)

The analysis code of the PDSC envelope system is incorporated into the software "THERB for HAM" [4] for temperature/humidity/heat load calculation of an entire building that considers the coupled heat, moisture, and air transfer. The temperature and humidity control performance and energy-saving performance of this system is examined by the numerical simulation. First, we confirmed the high calculation accuracy of the developed software by performing a numerical simulation on a demonstration house and comparing the calculated and measured values. Next, by numerical experiments using standard weather data (expanded AMeDAS (Automated Meteorological Data Acquisition System) weather data), the influence of differences in weather conditions and building specifications (regions, presence/absence of PDSC system, differences in thermal insulation materials (moisture capacity), presence/absence of moisture-proof sheets (moisture adsorption/desorption)) are clarified.

As a result, the house with PDSC system can reduce the sensible heat and latent heat load in summer by about 5% and about 20-41%, respectively, compared to conventional housing, and the sensible heat load in winter can be reduced by 10% or more.

Main References

(max 200 words)

[1] A. Ozaki, T. Watanabe, T. Hayashi, Y. Ryu, Systematic analysis on combined heat and water transfer through porous materials based on thermodynamic energy, Energy Build. 33 (2001) 341–350. https://doi.org/10.1016/S0378-7788(00)00116-X.

[2] H. Lee, A. Ozaki, M. Lee, W. Cho, A fundamental study of intelligent building envelope systems capable of passive dehumidification and solar heat collection utilizing renewable energy, Energy Build. 195 (2019) 139–148. https://doi.org/10.1016/j.enbuild.2019.04.039.

[3] H. Lee, A. Ozaki, W. Cho, M. Lee, Smart passive system for dehumidification , cooling , and heating utilizing renewable energy in detached house, Proceedings of the 16th IBPSA Conference, (2019) 2442–2449.

[4] A. Ozaki, T. Tsujimaru, Prediction of hygrothermal environment of buildings based upon combined simulation of heat and moisture transfer and airflow, Proceedings of the Ninth International IBPSA Conference (2005) 899–906.



10:48 - 11:06

Airflow optimization for thermal comfort and energy efficiency for room air conditioners

Ryuta Tanaka1, Saleh Nabi2, Mio Nonaka1

1Mitsubishi Electric Corporation Advanced Technology R&D Center, Japan; 2Mitsubishi Electric Research Laboratories, USA

Aim and Approach

(max 200 words)

The purpose of this paper is to increase the energy efficiency of room air conditioners while achieving a thermally comfortable indoor space. We investigate the solution to this problem as an optimization problem in which the control variables are inlet temperature, air speed, and angle. We formulated such an optimization as a minimization problem for the objective function representing the temperature uniformity of the room and the energy consumption of the room air conditioner. The temperature uniformity of the room was formulated as the squared error between the temperature in a given region of the interest within room, which includes the occupants and the set temperature. The energy consumption is formulated as a function of the control variables using the coefficient of performance (COP). The optimization problem was optimized using sensitivity and the gradient descent method. Such implementations have been performed using a coupling between the CFD solver of OpenFOAM and Matlab for optimization. To validate our optimization results, laboratory model was built and experiments have been carried out. We also compared and analyzed the effects of different models of room air conditioners (i.e., different degrees of freedom in the control variables) on energy savings and comfort.

Scientific Innovation and Relevance

(max 200 words)

Improving indoor comfort and reducing energy consumption are of primary concern in the control of room air conditioners. In the past, we have used trial-and-error CFD simulations or experiments to determine the optimal control parameters to achieve these goals. However, such method is intractable when the number of control variables are large and also there is no mathematical guarantee that such solution is in fact optimal. Moreover, previous studies mostly focused on either the thermal comfort or power consumption, but less attention is given to both tasks considering the multi-physics of the dynamics of airflow as well as the refrigerant cycle. We propose a gradient-based framework for CFD optimization to circumvent such difficulties that includes a multi-objective optimization for both temperature uniformity of the room energy consumption as a function of the control variables. This makes it possible to optimize not only the indoor comfort but also the energy consumption of the air conditioner. Furthermore, our full-scale experimental model helps to validate the efficacy of the CFD-based optimization for room ventilation.

Preliminary Results and Conclusions

(max 200 words)

In this paper, we employed a CFD-based optimization framework to analyze the impact of room air-conditioner control variables on the air velocity and indoor temperature in a typical room for the heating mode. The control variables are the inlet volume flux, temperature and the vane’s angle. The cost function is a multi-objective function of both thermal comfort and the energy consumption. The results show that for the optimal values of control variables, the air-conditioning system can undertake indoor heat load to provide thermally comfortable environment while maintaining a minimal energy budget for power consumption. We also demonstrate that more degrees of freedom on the air-conditioning system, e.g. having additional yaw angles, results in further improvement of thermal comfort for relatively large heat loads while the energy consumption is decreased. Moreover, our results show that, the optimal air velocity in the region of interest is low to moderate such that the wind velocity cannot be felt by the residents. We corroborate our results by comparing them with experimental data. Our results show that CFD-based optimization will have a reference value to create thermally comfort indoor environments while maintaining energy consumption to a minimum.

Main References

(max 200 words)

Nabi, S., Grover, P., Caulfield, C.C., "Adjoint-Based Optimization of Displacement Ventilation Flow", Building and Environment, 2017

Nabi, S., Grover, P., Caulfield, C.C., “Nonlinear optimal control strategies for buoyancy-driven flows in the built environment”, Computers & Fluids, 2019



11:06 - 11:24

Designing a data-driven model predictive control framework for residential buildings

Hyeong Seok Lee, Yeonsook Heo

Urban Energy&Environment Lab, Dept. of Civil, Environmental and Architectural Engineering, Korea University

Aim and Approach

(max 200 words)

This study aims to optimize the data-driven model predictive control (MPC) framework for residential buildings. The data-driven MPC framework is largely divided into three parts: prediction model(s), an optimization scheme, and MPC settings. This study investigates the effect of key factors in the data-driven MPC framework on the MPC performance through a simulation study of a case residential building based on TRNSYS. First, the essential features of the prediction model (i.e., non-linearity, time-correlation, model order) are determined by comparing the performance of linear regression, autoregressive with exogenous input model(ARX), and nonlinear autoregressive with exogenous input model(NARX) models with varying sets of predictors in the MPC application. Second, the two commonly used optimization approaches, linear programming (LP) and quadratic programming (QP), were investigated, and each approach requires certain considerations in designing the optimization scheme (e.g., objective function, constraints) to ensure both the building energy efficiency and the thermal comfort. Different optimization designs under the two approaches are evaluated in terms of their resulting MPC performance. Last, the effect of three MPC settings (i.e., a control time step and prediction and control horizons) is examined.

Scientific Innovation and Relevance

(max 200 words)

Model Predictive Control (MPC) allows for optimally controlling system operation in a proactive manner with considering future disturbances. A key component in the MPC is a prediction model that evaluates the effect of testing control actions. Although simulation-based MPC has been sufficiently demonstrated to show the energy-saving potentials in building applications, it requires manual creation of a simulation model for every targeting building, which substantially hinders the applicability of this approach. As an alternative to enhance the applicability, MPC based on data-driven statistical models has been developed, and commonly used statistical models include artificial neural networks, fuzzy logic models, etc. These complex models have been tested to provide accurate predictions at a fine time resolution. However, whether such sophisticated models are necessary for MPC applications has not been tested yet. These models are typically stored in a central computing cloud due to the high computational demand. Reliance on the computing cloud is not suitable for residential buildings where privacy is an important issue. Therefore, it is necessary to develop a distributable MPC framework based on lean, computationally efficient methods.

Preliminary Results and Conclusions

(max 200 words)

The virtual building of a residential unit was created in TRNSYS, and statistical models were created on the basis of simulation results. To reflect actual variation in the occupancy pattern and associated electricity usage, the ECO data set, collected by ETH Zurich for actual occupancy and load profiles were used in this study. Two statistical models were developed as part of the MPC framework to predict the indoor temperature and heat supplied by the boiler and radiant underfloor. The effect of different features in the statistical model on the prediction accuracy was analyzed. It was confirmed that a modeling feature to represent time-correlation (i.e., the ARX model in comparison to the linear regression model) shows a more significant effect on the prediction accuracy than adding more predictors or capturing nonlinearity (i.e., comparing the ARX model with the NARX model). As the next step, the effect of different modelling features on the MPC performance will be investigated. In addition, different optimization schemes and MPC settings will be investigated in terms of their effect on the MPC performance and computational time.

Main References

(max 200 words)

Killian, M. and M. Kozek (2016). "Ten questions concerning model predictive control for energy efficient buildings." Building and Environment 105: 403-412.

Mirakhorli, A. and B. Dong (2016). "Occupancy behavior based model predictive control for building indoor climate—A critical review." Energy and Buildings 129(Review papaer to MPC): 499-513.

Beckel, C., W. Kleiminger, R. Cicchetti, T. Staake and S. Santini (2014). The ECO data set and the performance of non-intrusive load monitoring algorithms. Proceedings of the 1st ACM Conference on Embedded Systems for Energy-Efficient Buildings. Memphis, Tennessee, Association for Computing Machinery: 80–89.



11:24 - 11:42

Predicting occupant thermal comfort for multiple air-side systems and seasonal scenarios using Autonomous HVAC CFD

Sandip Jadhav, Praveen Kumar, Rohit Chavan, Avinash Goen

Centre for Computational Technologies Pvt Ltd, India

Aim and Approach

(max 200 words)

Achieving the desired occupant thermal comfort in indoor spaces is a challenge that the HVAC industry is trying to address in recent times. It's seen that a thermally comfortable working environment enhances productivity and pleasant mood amongst the employees. A popular method to analyze thermal comfort is to perform CFD simulations for the indoor spaces with the selected air-side systems for seasonal scenarios and calculate the evaluation parameters such as PMV, PPD, Mean age of air etc. The complete and sound analysis of the occupant thermal comfort is possible when one has simulated the given indoor space for multiple air-side systems, varying seasonal and occupant density scenarios throughout the year. Such a complete analysis will require a large number of CFD simulations along with the CFD expertise and high-performance computing capabilities with the HVAC consultant. With the advent of powerful cloud computing, a new ‘Autonomous HVAC CFD’ application has been developed by simulationHub, that performs the CFD simulations on the cloud for multiple design configurations and scenarios and provides essential parameters to analyse the occupant thermal comfort. Through introduction and case studies, this paper illustrates the ‘Autonomous HVAC CFD’ app to assess the occupant thermal comfort in indoor spaces.

Scientific Innovation and Relevance

(max 200 words)

Our innovation resides in the automation of the complete process of performing the CFD simulation to evaluate occupant thermal comfort in indoor spaces. Using the approach developed in the app, any user can perform an array of CFD simulations involving multiple air-side systems for multiple scenarios simultaneously. All the inputs related to CFD including external domain size, mesh density, turbulence model, numerical schemes are intelligently selected by the algorithm. The complete CFD workflow right from the fluid domain creation, meshing, solving governing equations, monitoring convergence, post-processing, and report generation is automated, thus removing the key barrier of the requirement of CFD expertise while performing such simulations. Being a cloud-based app, Autonomous HVAC CFD does not demand in-house high-performance computing resources or hard-wired servers. The app 3D CAD model of the indoor space as input along with the details of the air side systems and scenarios and predicts quantitative results such as PMV, PPD, EDT, DR, Mean age of air etc along with a detailed CFD report automatically.

Preliminary Results and Conclusions

(max 200 words)

This paper includes the case study of office space with 7 rooms. The rooms serve different purposes such as workspace, pantry, conference room, lobby etc. A total of 5 air-side systems which include Constant Air Volume, Variable Air Volume and Underfloor Air Distribution Systems are chosen. A total of 6 different scenarios based on seasons and occupant density are simulated for this case study which combines to a total of 210 CFD simulations. Based on the results generated by these simulations, PMV, PPD, EDT, DR, Mean age of air and qualitative results such as contour plots and flowlines are generated to evaluate the occupant thermal comfort of the complete indoor office space. A detailed observation of these predicted results is discussed and the optimum air-side system for a year-round application is suggested. This paper shall try to demonstrate the usefulness and accessibility of the app to the HVAC consultants while determining the occupant thermal comfort in indoor spaces.

Main References

(max 200 words)

1) ISO 7730:2005

Ergonomics of the thermal environment — Analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria

2) ANSI/ASHRAE Standard 62.1-2019 - Ventilation for Acceptable Indoor Air Quality

3) ASHRAE Standard 55, Thermal Environmental Conditions for Human Occupancy

4) P.V.Nielsen, S.Murakami, S.Kato, et al. "Benchmark test for Computer Simulated Person" Aalborg University, 2003

5) N. Martinho,A.Lopes,et al. "CFD modelling of benchmark tests for flow around a detailed computer simulated person", 7th International Thermal Manikin and Modelling Meeting - University of Coimbra, September 2008



11:42 - 12:00

A simulation study to analyze the impact of Integrated Passive Strategies on natural ventilation and daylighting in a slum house of Mumbai

Abdul Moeed Chaudhary1, Sahil Priyadarshi2, Shailee Goswami3

1Essential India, Mumbai; 2International Finance corporation (IFC); 3Centre for Environmental Planning and Technology, Ahmedabad

Aim and Approach

(max 200 words)

In India, an estimated 44 to 105 million people live in urban slums. Census data also indicates that a large section of the metropolitan city population lives in these informal settlements. For instance, around 41% of Mumbai’s population lives in slums or ‘Chawls’, and it is projected that this statistic will further increase. The comfort conditions in these settlements are very poor and the occupants live in substandard daylighting and air ventilation levels.

This study aims at analyzing the capability of the proposed strategy to improve air ventilation and daylighting levels in a slum dwelling. The compact and adjoined spaces in Chawls don’t allow open planning and restrict the construction of external fenestrations which results in poor airflow. Also, the presence of utilities and toilets within the living spaces makes the air quality worse. The daylight penetration in slum houses is also limited due to the dense planning and small windows that hinder the sky view. Thus, the main objective of this simulation study is to analyze the impact of Integrated Passive Strategy (IPS) in the form of a chimney, which is enhancing the daylighting and air ventilation levels.

Scientific Innovation and Relevance

(max 200 words)

The compact and adjoined spaces in Chawls don’t allow open planning and restrict the construction of external fenestrations which results in poor airflow. Also, the presence of utilities and toilets within the living spaces makes the air quality worse. The daylight penetration in slum houses is also limited due to the dense planning and small windows that hinder the sky view. The constricted space only allows minimum daylight inside the rooms and results in substandard illuminance levels.

By considering these design aspects, the simulation model is created for a ground floor slum-dwelling unit in CFD and daylighting simulation software. The feasibility of different combination of chimney designs are analyzed in this model. The impact of the solar-induced stack effect due to chimney is analyzed on the overall air exchange rate (ACH) in the room. The proposed chimney used in the model is a customized low-cost prototype that is manufactured locally. The effect of its integration in the space is quantified in terms of improvement in illuminance levels (lux).

Preliminary Results and Conclusions

(max 200 words)

The proposed solution is exhibiting significant improvement in indoor environmental quality. The proposed solar chimney is inducing a stack effect that aids in providing adequate air exchange in the rooms. The results are showing 2.5 to 7 times increment in the air changes per hour (ACH) of proposed case comparison to base case and 2℃ to 3℃ reduction in temperature. The ACH rate is in compliance with NBC code along with the indoor operative temperature, which is meeting the standards for naturally ventilated spaces.

From daylighting perspective, the integration of proposed component is enabling effective daylight penetration within the spaces. This proposed solution is resulting in an average increase of almost 300 (lux) illuminance level in the living spaces. Uniformity ratio (min/avg) has also improved from 0.004 to 0.13. The Illuminance levels have also met the NBC standards requirement in the proposed case. The increase in illuminance levels has resulted in significant improvement in visual comfort conditions.

In conclusion, the integration of chimney component is significantly improving the room comfort conditions for the occupants living in slum houses. The existing compact planning calls for an effective solution that delivers adequate air quality and daylighting levels in the spaces.

Main References

(max 200 words)

Bardhan, Ronita, et al. “Low-Income Housing Layouts under Socio-Architectural Complexities: A Parametric Study for Sustainable Slum Rehabilitation.” Sustainable Cities and Society, vol. 41, Elsevier B.V., 2018, pp. 126–38, doi:10.1016/j.scs.2018.04.038.

Debnath, Ramit, et al. A Data-Driven and Simulation Approach for Understanding Thermal Performance of Slum Redevelopment in Mumbai , India Department of Civil and Environmental Engineering , Stanford University, USA Centre for Urban Science and Engineering , Indian Institute O. 2016.

Karandikar, Priyanka, and Nadia Anderson. Chawls: Analysis of a Middle Class Housing Type in Mumbai, India. 2010, p. 96, http://libproxy1.nus.edu.sg/login?url=http://search.proquest.com/docview/848940263?accountid=13876.

O’Hare, Greg, et al. “A Review of Slum Housing Policies in Mumbai.” Cities, vol. 15, no. 4, 1998, pp. 269–83, doi:10.1016/S0264-2751(98)00018-3.

Sarkar, Ahana, and Ronita Bardhan. “Improved Indoor Environment through Optimised Ventilator and Furniture Positioning: A Case of Slum Rehabilitation Housing, Mumbai, India.” Frontiers of Architectural Research, no. xxxx, Elsevier Ltd, 2020, doi:10.1016/j.foar.2019.12.001.

Trani, Marco L., et al. “Template Customization for Construction Site Information Models.” Procedia Engineering, vol. 164, 2016, pp. 495–502, doi:10.1016/j.proeng.2016.11.650.