Liangzhu (Leon) Wang

Applications of a Coupled Multizone-CFD Model to Calculate Airflow and Contaminant Dispersion in Built Environments for Emergency Management

Current simulation tools for airflow and contaminant dispersion in built environments cannot provide detailed information with little computing effort, which is critical for emergency management. Multizone airflow network models are fast but cannot provide detailed flow and contaminant transport information in an indoor space. Computational fluid dynamics (CFD), on the other hand, gives very detailed information but requires hours or days of computing time on a PC. A coupled multizone-CFD model can offer detailed information on contaminant dispersion while reducing computing time. The study presented in this paper applied the coupled model to calculate airflow and contaminant dispersion in a three-story, naturally ventilated building with a large atrium, assuming that a contaminant was released in the atrium. This investigation studied the effectiveness using emergency ventilation to protect the building occupants. It was demonstrated that the coupled model can provide important information of contaminant distributions with a reasonable computing time. The information is useful for evaluating placement of contaminant sensors and determining evacuation strategies for emergency management.

Simultaneous solutions of coupled thermal airflow problem for natural ventilation in buildings

Natural and hybrid ventilation can be sustainable building ventilation strategies, where airflow is driven naturally by thermal buoyancy and/or wind forces other than pure mechanical means. The simulation and design of these systems need to consider the combined impact of thermal and airflow transport behaviors. The numerical solution of such combined thermal airflow problems often employs a segregate and iterative approach. Either the air temperatures in the thermal problem or the air pressures in the airflow problem are solved separately with the other parameter known from a previous iteration. The newly solved parameters are then substituted successively into the other calculation. For highly coupled thermal airflow problems, the segregate method can cause solution fluctuation or even divergence when relaxation factors are not carefully selected to avoid abrupt changes of air parameters in the successive substitution procedure. This article investigated two nonsegregate methods to solve thermal and airflow problems simultaneously. In the fully simultaneous method, air temperatures and pressures for all rooms of a building are solved simultaneously using a single Jacobian matrix. In the semi-simultaneous method, a Jacobian matrix for the air temperature and pressure of one room is solved when air temperatures and pressures of other rooms are kept as constants. The same procedure is then repeated for each room of a building. In both cases, relaxation factors are not required. The simultaneous solution methods are demonstrated for a two-zone building with thermal buoyancy-driven flows and validated for an experimental study of combined wind and buoyancy forces in a light well. It was shown that the simultaneous solvers provide stable solutions without using any relaxation in both cases. The predicted results also agree reasonably well with the experimental data.

Development and application of an updated whole-building coupled thermal, airflow and contaminant transport simulation program (TRNSYS/CONTAM)

The TRNSYS energy analysis tool has been capable of simulating whole-building coupled heat transfer and building airflow for about 10 years. The most recent implementation was based on two TRNSYS modules, Type 56 and Type 97. Type 97 is based on a subset of the airflow calculation capabilities of the CONTAM multizone airflow and contaminant transport program developed by the National Institute of Standards and Technology. This paper describes the development of new CONTAM capabilities in support of an updated combined, multizone building heat transfer, airflow and contaminant transport simulation approach using TRNSYS. It presents an illustrative case that highlights the new coupling capability and also presents the application of this coupled simulation approach to a practical design problem of the energy use related to airflow through entry doors in non-residential buildings.

Using helium smoke as a surrogate of fire smoke for the study of atrium smoke filling

This study developed a method of using pure helium to generate a cold buoyant plume as the surrogate of a fire smoke for the study of the smoke-filling process in an atrium. Aided by the numerical simulations, a series of experiments in a 1:26.5 scale model of the full-size atrium with the fires up to 1.6 MW from the literature were conducted to investigate the similarity between a helium smoke and a hot fire smoke. Helium concentrations, smoke layer heights, and smoke optical densities were compared well between the current experiment and the simulations. The experimental study thus verified the capability of a helium smoke test to reproduce the smoke-filling process of the corresponding hot smoke test in the atrium studied. This study also showed how to model a hot smoke test with a t-squared fire by the corresponding helium smoke test by pre-mixing helium and artificial smoke in a mixing box.

In situ experimental study of carbon monoxide generation by gasoline-powered electric generator in an enclosed space.

Abstract On the basis of currently available data, approximately 97% of generator-related carbon monoxide (CO) fatalities are caused by operating currently marketed, carbureted spark-ignited gasoline-powered generators (not equipped with emission controls) in enclosed spaces. To better understand and to reduce the occurrence of these fatalities, research is needed to quantify CO generation rates, develop and test CO emission control devices, and evaluate CO transport and exposure when operating a generator in an enclosed space. As a first step in these efforts, this paper presents measured CO generation rates from a generator without any emission control devices operating in an enclosed space under real weather conditions. This study expands on previously published information from the U.S. Consumer Product Safety Commission. Thirteen separate tests were conducted under different weather conditions at half and full generator load settings. It was found that the CO level in the shed reached a maximum value of 29,300 ± 580 mg/m3, whereas the oxygen (O2) was depleted to a minimum level of 16.2 ± 0.02% by volume. For the test conditions of real weather and generator operation, the CO generation and the O2 consumption could be expressed as time-averaged generation/consumption rates. It was also found that the CO generation and O2 consumption rates can be correlated to the O2 levels in the space and the actual load output from the generator. These correlations are shown to agree well with the measurements.

Forecasting smoke transport during compartment fires using a data assimilation model

Forecasting simulation of an unknown compartment fire is challenging and usually accompanied with a large number of uncertainties. As the simulation progresses in time, the forecasted physical conditions such as fire heat release rate, room temperature, and vent airflow rate may sway from reality in a highly dynamic environment. Conventional deterministic fire simulation tools using one set of initial inputs to predict fire smoke transport may not easily generate satisfactory results. In this article, a new application of Ensemble Kalman Filter to forecast smoke dispersion during compartment fires is presented. The model utilizes measurement data from multiple sensors in multi-room compartments and is able to predict the fire heat release rate and smoke dispersions within several minutes. In addition, detailed formulation of the Ensemble Kalman Filter model and three case studies are also discussed in this article. The resulting model can be considered as a prototype forecast simulation system to assist occupant evacuation, firefighting, and smoke extraction in a building fire accident.

Study of the Impact of Operation Distance of Outdoor Portable Generators under Different Weather Conditions

The US Centres for Disease Control and Prevention has reported that up to half of non-fatal carbon monoxide (CO) poisoning incidents during the hurricane seasons in 2004 and 2005 involved generators operated outdoors but within 7 ft of the home. Current guidance for safe operating distances of generators is often neither specific nor consistent. A study was conducted to examine the impact of generator distance on indoor CO exposure. The study was based on computer simulations of CO transport outdoors and subsequently into a generic two-storey house. This paper presents the simulation results when using an indoor air quality model coupled with a computational fluid dynamics model to predict CO concentrations near and within the home. Fire Dynamics Simulator was validated against the measured contaminant dispersion data in a wind tunnel. A parametric study was then conducted for the two-storey house to consider the effects on indoor CO levels of generator location, distance, exhaust temperature and speed and weather conditions. It was found that in most cases, to reduce CO levels for the conditions modelled, it was more effective to point the generator exhaust away from the house and position the generator at a distance of >4.6 m.

Measured carbon monoxide concentrations from stock and reduced-emission prototype portable generators operated in an attached garage

ABSTRACT There is concern about the hazard of acute residential CO exposures from portable gasoline-powered generators, which can result in death or serious adverse health effects in exposed individuals. To address this hazard, the U.S. Consumer Product Safety Commission has developed low CO emission prototype generators by adapting off-the-shelf emission control technologies onto commercially available generators. A series of tests was conducted to characterize the indoor CO concentrations resulting from portable generators operating in the attached garage of a research house under seven different test house/garage configurations. The tested generators include both unmodified and modified low CO emission prototypes. It was found that CO concentrations varied widely, with peak house CO concentrations ranging from under 10 ppm to over 10,000 ppm. The highest concentrations in the house resulted from operation of the unmodified generator in the garage with the garage bay door closed and the house access door open. The lowest concentrations resulted from operation of a modified low CO emission prototype in the garage with the garage bay door open and the house access door closed. These tests documented reductions of up to 98% in CO concentrations due to emissions from two low CO emission portable generators compared to a stock generator. Implications: Improper portable generator use has caused 800 U.S. deaths in the past 14 years. Generators operated in attached garages can cause CO to quickly reach deadly levels. Two low-emission prototypes generators were tested and had CO emissions reduced by up to 98%. Low-emission generators can reduce the risk of consumer poisonings and deaths.

Applications of data assimilation to forecasting indoor environment

Data assimilation (DA) is a technique to combine numerical predictions and experimental measurements, which has been commonly used by the community of numerical weather forecasting but is relatively new to the field of indoor environment. Among all data assimilation methods, Ensemble Kalman Filter (EnKF) is especially suitable to solve large-scale nonlinear problems due to its low computation requirement. In this paper, two new applications of EnKF to forecasting indoor environment are presented. The first study is to forecast the contaminant transport in a residential house based on a multi-room tracer gas decay experiment. The forecast model avoids calculating source term in the given problem by rapid updating model states with EnKF while still providing significant forecast lead time. The second study is to predict the fire smoke dispersion in a multi-room compartment fire without giving actual heat release rates (HRRs) as model inputs. Compared to conventional deterministic models, the EnKF models improve the predictions significantly.