With the pressing need to reduce greenhouse gas emissions, blending lower or zero carbon fuels like renewable hydrogen into natural gas is a promising and practical way to achieve clean energy transition. From the perspective of end users and combustion device manufactures, one of the major concerns is the influence of the renewable contents on the combustion devices performance. The possible renewable gas content percentage in pipeline also interests policy makers and gas utility companies. The present study investigates on the influence of hydrogen contents on the operating performance of a surface burner, which is widely adopted in industrial, commercial and residential applications. The interactions among heating load, excess air level and fuel contents are studied by a 3-factor∗3-level experiment design. Evaluated combustion performance characteristics include flame characteristics, burner/exhaust temperature and emissions (NO, NO2, N2O, CO, UHC, NH3). The results showed that hydrogen addition to natural gas slightly increased the burner surface temperature but did not have significant impact on other burner performance parameters. Up to 20% (by volume) natural gas was replaced by hydrogen, and no abnormal effect was observed. Furthermore, tests carried out in a prototype water heater showed similar performance. This study gives a positive sign relative to replacing pipeline natural gas with renewable hydrogen at a low percentage without modifying the burner geometry.

The injection of choked gaseous jets into the still air is investigated experimentally motivated by many industrial applications including flares and burners. The objective is to study the effect of injection angle on the jet mixing with ambient air. The experimental methods consist of particle image velocimetry (PIV) using pulsed Nd:YAG lasers of a choked gas jet, seeded with aluminum oxide particles, injected into the still air, seeded with water fog. The computational methods consisted of 7.7 x 10(6) cells simulation using star ccm+. The test conditions include injection angles of 0 deg, 15 deg, and 30 deg. The results including mean and fluctuating velocities and the flow vorticity are presented. The flow field is not symmetric along the injection axis due to the asymmetric triggering of expansion fans. Moreover, the numerical simulation reveals the complex interaction mechanism of the expansion fans and shockwaves within the injection port.

Advancements in lean premixed combustion have increased the efficiency and reduced the amount of greenhouse gas emissions, but they have led to increased noise emissions due to higher turbulence and mixing fluctuations. This study used an external sensor (microphone) to validate the simulation of the combustion noise of a confined space. An experimental facility with a laboratory-scale furnace was used to carry out the measurement, and the simulation of the confined flame noise was conducted in OpenFOAM. The simulation utilized the Partially Stirred Reactor (PaSR) and a hybrid computational aeroacoustics (CAA) approach using the large eddy simulation (LES)/the Ffwocs Williams–Hawkings (FWH) method. Additionally, unsteady Reynolds-averaged Navier–Stokes (URANS)/the FWH method was tested for a comparison with the LES prediction. A sensor which was placed outside the enclosure for ease of access was then used to validate the results of the numerical model. The sensor data agreed with the LES/FWH results including the amplitude and frequency of the primary combustion peak and the overall sound pressure level (OASPL). This suggested that a sensor which was placed outside the enclosure could serve as a validation tool for the simulation of the confined flames despite the sound reflections from the walls.

During the COVID-19 pandemic, an increasing amount of evidence has suggested that the virus can be transmitted through the air inside buildings. The ventilation system used to create the indoor environment would facilitate the transmission of the airborne infectious diseases. However, the existing ventilation systems in most buildings cannot supply sufficient clean outdoor air for diluting the virus concentration. To reduce the airborne infection risk and minimize energy consumption, especially in existing buildings with well-mixed ventilation systems, this investigation used an ultraviolet-C (UV-C) air disinfection device (Rheem's third generation products, RM3) with 99.9% disinfection efficiency to clean air carrying the COVID-19 virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2) which could help promote environmental sustainability and create healthy cities. This investigation assessed the impact of the RM3 UV-C units on the infection risk, the number of RM3 UV-C units required, and the strategy for decreasing the infection risk, with the use of computational-fluid-dynamics (CFD) numerical simulations. An actual office building with a combination of individual offices and workstations was selected as an example for the research. According to the numerical results, the best strategy would be to use a combination of 100% outside air and UV-C in heating, ventilation and air-conditioning (HVAC) ducts with air disinfected by the RM3 UV-C units. The infection risk in the office building could thus be reduced to a negligible level. These findings could provide theoretical basis and engineering application basis for COVID-19 epidemic prevention and control.

The injection of choked gaseous jets into the still air is investigated experimentally motivated by many industrial applications including flares and burners. The objective is to study the effect of injection angle on the jet mixing with ambient air. The experimental methods consist of particle image velocimetry (PIV) using pulsed Nd:YAG lasers of a choked gas jet, seeded with aluminum oxide particles, injected into still air, seeded with water fog. The computational methods consisted of 7.7 million cells simulation using Star CCM+. The test conditions include injection angles of 0 degrees, 15 degrees, and 30 degrees. The results including mean and fluctuating velocities and the flow vorticity are presented. The flow field is not symmetric along the injection axis due to the asymmetric triggering of expansion fans at the jet exit due to the inclined injection plane. Moreover, the numerical simulation reveals the complex interaction mechanism of the expansion fans and shockwaves within the injection port.

The injection of choked gaseous jets into still air is investigated computationally and experimentally. The objective is to compare the performance of three turbulence models – Realizable k-e, SST k-w and Reynolds Stress Transport to resolve the effect of injection angle on the jet mixing with ambient air. The experimental methods consist of particle image velocimetry (PIV) using pulsed Nd:YAG lasers of a choked gas jet, seeded with aluminum oxide particles, injected into still air that has been seeded with water fog. The test conditions include injection angles of 0° and 15°. The results including jet velocities and the vorticity field are presented. The flow field is not symmetric along the injection axis due to the asymmetric triggering of expansion fans at the jet exit due to the inclined injection plane. Moreover, the numerical simulation reveals the complex interaction mechanism of the expansion fans and shockwaves within the injection port.

The particle filter is used to couple a coarse-grained (CG) deterministic solution for a reacting flow with a fine-grained (FG) stochastic solution. The proposed method investigates the feasibility of implementing a multiscale approach for turbulent reacting flows based on large-eddy simulation (LES) coupled with a low-dimensional fine-grained stochastic solution for the subfilter scales reaction and transport. In this study, a model for the turbulent transport in the FG solution is implemented using the linear-eddy model (LEM), which combines a deterministic implementation for reaction, diffusion, and large-scale transport with a stochastic implementation for fine-scale transport. The solution for the continuity and momentum (the Burgers' equation) equations are implemented in 1D. The filtered densities obtained through the FG and the CG solutions are combined using the particle filter to obtain an updated density for the coarse solution that combines the effects of heat release (from the FG solution) and flow dynamics (from the CG solution). The results demonstrate that the particle filter may be a viable tool to couple deterministic CG solutions and stochastic FG solutions in reacting flow applications.

A laminar counter-flow diffusion flame formed with methane/acetylene and oxygen enriched-air was used for the controlled synthesis of 1-D molybdenum oxide nanostructures directly in the gas phase. Raw material was introduced into the oxidizer side of the flame in the form of solid molybdenum wires with ∼99% purity. Molybdenum oxide vapors formed in the gas phase were transported by the gas flow in the flame environment possessing strong thermal and chemical gradients. The generated nanostructures were collected thermophoretically from the flame volume. Essential morphological variations of generated nanomaterials were observed depending on sampling position within the flame volume and probe parameters. The mechanism behind the synthesis of the spherical and 1-D nanoforms is analyzed and modeled numerically. The nanorod growth model involves monomer transport, nucleation and growth. The monomer formation is through the oxidation and vaporization of the probe material. The nucleation model is based on the classical nucleation theory. The model predicts the trajectory and growth of the formed nuclei as they are transported in the flame volume. It is considered that the ends of the cylindrical 1-D nanorods grow by the phenomenon of rough growth while the lateral faces exhibit layered growth. The growth model also considers the contribution of the monomers diffusing on the nanoparticle surface as well as the effect of the atoms impinging directly onto the growth sites and compares their relative contributions. The model qualitatively predicts the variation of aspect ratio of the formed nanomaterials with increase of monomer concentration as observed in the experiments.

A multi-scale approach for coupling a coarse-grained (CG) deterministic solution for a reacting flow with a fine-grained (FG) stochastic solution is proposed. The model includes a CG solution for the mass density and momentum and a FG solution for the temperature. A model for the turbulent transport in the FG solution is implemented using the linear-eddy model (LEM), which combines a deterministic implementation for reaction, diffusion and large-scale transport with a stochastic implementation for fine-scale transport. A common variable is obtained from these solutions based on a CG density field defined from continuity on the coarse scales and the spatial filtering of the density derived from the state equation in the FG solution. Kalman filtering is used to combine these two solutions. The resulting CG density is both smooth and steered by heat release from the FG solution. The algorithm is demonstrated on a 1D model combining continuity and the Burgers' equation for the CG solution and the temperature equation with heat release for the FG solution. The results establish the feasibility of Kalman filtering in coupling deterministic CG solutions and stochastic FG solutions in reacting flow applications. (C) 2013 Elsevier Ltd. All rights reserved.

An opposed laminar flow flame formed with methane/acetylene and oxygen enriched-air was employed to produce molybdenum oxide nanostructures directly in the gas phase. The composition of the fuel and oxidizer to form the flame was 96%CH4+4%C2H2 and 50%O2/50%N2, respectively. Raw material was introduced into oxidizer side of the flame in the form of solid molybdenum wires with 99% purity. The high temperature and the oxygen rich chemical environment of the flame resulted in fast surface oxidation of the probes and material etching from their surfaces. Upon their interaction with the flame, the probes generated molybdenum trioxide vapors. The vapors were transported in the direction of the stagnation plane of the flame and reduced to molybdenum dioxide as they entered the low temperature fuel rich zone. The velocity gradient and thermophoretic forces in the flame affected the transport of the molybdenum dioxide precursors. These precursors in the gas phase formed nanostructures that were thermophoretically collected from the flame volume. Essential morphological variations of generated nanomaterials were observed depending on flame and probe parameters. The distance of the collection plane from the molybdenum probe also played an important role in the morphology of generated nanoforms. The molybdenum probes with diameters of 0.75 mm and 1 mm were used to achieve two distinct synthesis conditions. The variation of probe diameter affected probe temperature and resulted in different supersaturation levels of molybdenum dioxide vapors. Experiments with 1.0 mm diameter corresponded to lower supersaturation levels and resulted in the synthesis of well-defined convex polyhedron nanocrystals and nanorods. Higher material etching rates and, hence, supersaturation levels were obtained with 0.75 mm diameter probes. These conditions resulted in synthesis of mainly spherical molybdenum oxide nanomaterials agglomerated in soot-like fractal aggregates. The effect of flame parameters and material concentration on shape and structure of generated nanomaterial is also studied numerically. The underlying mechanisms governing the morphological variation of molybdenum oxide nanocrystals are analyzed using the following steps: monomers formation, nucleation, and growth. The nucleation model is based on the classical nucleation theory, and the growth model considers agglomeration and diffusion in the varying thermal environment using thermophoretic analysis. The model predictions are in good qualitative agreement with the experimental data.