High-Resolution CFD and In-Situ Monitoring Based Validation of an Industrial Passive Air Conduction System (PACS)

Abstract

Natural driven ventilation is a widely used technique in hot and arid climate, but it is rarely known that it can lead to significant energy saving in a moderate climate too. In this paper, an existing building is presented that was designed with a passive air conduction system (PACS), where wind and buoyancy effects induce air to be exchanged without external energy needs. The aim is to show that the design methodology, using numerical simulation to give accurate results, is able to use them in further developments. Due to this design process, the specific building possesses numerous special properties, including airflow accelerating elements, solar-heated “chimneys”, and the indoor heat sources coming from the industrial technology. As the building has been constructed and was equipped with around 750 sensors (integrated and manual), it is possible to analyze the ongoing physical phenomenon in a highly detailed way and to collect the experienced dataset for further investigations. The current study carries out a complex validation of the design and the used numerical methods to give general design rules for further PACS design and support following investigations, e.g., occupant comfort prediction or latent heat storage calculation. The experiences showed that the developed computational fluid dynamics technique gives a below 99% accuracy in the velocity and the temperature field, and approximately 85% accuracy in the volume flow values, resulting in a good prediction for aerodynamic characterization of buildings, i.e., passive ventilation air exchange rate.

Comparison of Downdraught and Up Draft Passive Air Conduction Systems (PACS) in a Winery Building

“…The second criteria was the wind speed, because too high air velocity can cause draft effects for occupants, therefore the upper limit was set to 8 m/s. This value is originated from the maintenance experiences of the authors in a very similar PACS in an industrial building, in Hungary [41]. Based on these parameters, 3639 h were found during an average year, being acceptable for NV.…”

“…Coupled indoor-outdoor simulation scenarios were created for the complex understanding of not only the PACS performance but its environmental situation, as its importance was stated by Mohamed et al [48]. Leaning on the literature and on the authors' experiences [41], the k-Ω model was chosen to perform the simulations of the described problem. As solver code, the ANSYS ® Fluent 17.2 application was used.…”

“…Two steps assure the quality of the generated grid. Firstly, the authors previously worked on a CFD model validation including in situ measurements of an existing building, whereas the gained experiences served as basis for the constructed mesh's discretization in the current investigation [41]. Table 1 describes the structure of the grid, created with ANSYS ® Mesher.…”

A Sensitivity Analysis for Thermal Performance of Building Envelope Design Parameters

“…In building science, designers and researchers frequently use dynamic thermal simulation software to analyze the energy and thermal performance of buildings to achieve specific goals, such as lower energy consumption, improved indoor thermal comfort, or reduced environmental effects [1][2][3]. As a result, several techniques for supporting building simulation analysis have been developed, such as simulation-based optimization, parametric simulations, sensitivity analysis, meta-model analysis, etc.…”

“…Sensitivity analysis identifies the most important design parameters in terms of building performance. In practice, uncertainty and sensitivity analysis provide a number of additional advantages, including: (1) the use of parameter screening to simplify models [15,16]; (2) the evaluation of models' robustness [17]; (3) alerting designers to unexpected sensitivities that may result in errors, and/or incorrect specifications (quality assurance) [18][19][20][21][22]; and (4) providing a "what-if analysis" by changing the input parameters and displaying the effect on the outcome of a model (decision-support) [23].…”