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[en] Effective removal of nitrogen oxides (NOx) from flue gas allows more fossil fuels to be produced and utilized with less negative impact on the environment. It would be more cost-effective, however, if nitric oxide (NO) is oxidized to soluble nitrate and nitrite and then removed from the air by existing desulfurization wet scrubbers. This paper compares the effectiveness of three different oxidants for this purpose, namely, ethylenediaminetetraacetic acid; iron (2+) (Fe(II)–EDTA), hexamminecobalt(II) chloride ([Co(NH3)6]Cl2), and hydrogen peroxide (H2O2). Experimental results using column reactors showed that [Co(NH3)6]Cl2 was more effective over the same period of time. The best initial NO removal efficiency of about 96.45% was measured at the inlet flow rate of 500 ml/min; the temperature of approximately 19 °C; the pH value of around 10.5; and the concentrations of [Co(NH3)6]Cl2 , NO and O2 of 0.06 mol/L, 500 ppm and 5.0%, respectively.
[en] Highlights: ► A performance benchmarking exercise is conducted for diesel combustion simulations. ► The reduced chemical mechanism shows its advantages over base and skeletal models. ► High efficiency and great reduction of CPU runtime are achieved through 4-node solver. ► Increasing ISAT memory from 0.1 to 2 GB reduces the CPU runtime by almost 35%. ► Combustion and soot processes are predicted well with minimal computational cost. - Abstract: In the present study, in-cylinder diesel combustion simulation was performed with parallel processing on an Intel Xeon Quad-Core platform to allow both fluid dynamics and chemical kinetics of the surrogate diesel fuel model to be solved simultaneously on multiple processors. Here, Cartesian Z-Coordinate was selected as the most appropriate partitioning algorithm since it computationally bisects the domain such that the dynamic load associated with fuel particle tracking was evenly distributed during parallel computations. Other variables examined included number of compute nodes, chemistry sizes and in situ adaptive tabulation (ISAT) parameters. Based on the performance benchmarking test conducted, parallel configuration of 4-compute node was found to reduce the computational runtime most efficiently whereby a parallel efficiency of up to 75.4% was achieved. The simulation results also indicated that accuracy level was insensitive to the number of partitions or the partitioning algorithms. The effect of reducing the number of species on computational runtime was observed to be more significant than reducing the number of reactions. Besides, the study showed that an increase in the ISAT maximum storage of up to 2 GB reduced the computational runtime by 50%. Also, the ISAT error tolerance of 10−3 was chosen to strike a balance between results accuracy and computational runtime. The optimised parameters in parallel processing and ISAT, as well as the use of the in-house reduced chemistry model allowed accurate results to be produced with reduced computational runtime, especially in simulating in-cylinder reacting spray jet and soot characteristics on standard computing platforms.
[en] Highlights: ► We evaluate the suitability of 11 empirically performance models for centrifugal water chillers. ► The prediction accuracy of each model is based on CV values. ► The evaluation for model suitability is based on five indexes. ► The BQ, MP, SMP, and MDOE-2 models have good prediction accuracy. ► The BQ, MP, and SMP models have the best suitability. - Abstract: This study evaluates the performance prediction ability and model suitability of eleven empirically-based performance models for centrifugal water chillers. Specifically, this study uses over 2000 datasets with a constant or variable chilled water flow rate for fixed or variable speed drive centrifugal liquid chillers. The best regression coefficients for each empirical-based model were obtained using the ordinary least squares (OLSs) method. The model prediction accuracy of each empirical-based model is based on the coefficient of variation of root-mean-square error (CV). The evaluation for model suitability is based on the considerations of prediction ability, the complexity in training datasets, the effort needed to calibrate, the generality of the model, and its ability to physically interpret the model regression coefficients in this study. Results show that among the eleven empirical-based models, the BQ (CV = 0.54%), MP (CV = 0.61%), SMP (CV = 0.70%), and MDOE-2 (CV = 0.63%) models have overall prediction CV values under 1% for all kinds of datasets and achieve extremely good prediction accuracy. Because the MDOE-2 model has a more complicated datasets training process than the BQ, MP, and SMP models, and it has no ability to physically interpret the model regression coefficients, the BQ, MP, and SMP models have the best suitability. The results of this study provide important reference values for selecting empirically-based performance models for energy analysis, optimal operating control, energy efficiency measurement and verification (M and V), and the development of fault detection and diagnosis (FDD) systems in centrifugal water chillers.
[en] A two-dimensional, non-isothermal model of a proton exchange membrane fuel cell was implemented to elucidate heat balance through the membrane electrode assembly (MEA). To take local utilization of platinum catalyst into account, the model was presented by considering the formation of agglomerated catalyst structure in the electrodes. To estimate energy balance through the MEA, various modes of heat generation and depletion by reversible/irreversible heat release, ohmic heating and phase change of water were included in the present model. In addition, dual-pathway kinetics, that is a combination of Heyrovsky–Volmer and Tafel–Volmer kinetics, were employed to precisely describe the hydrogen oxidation reaction. The proposed model was validated with experimental cell polarization, resulting in excellent fit. The temperature distribution inside the MEA was analyzed by the model. Consequently, a thorough investigation was made of the relation between membrane thickness and the temperature distribution inside the MEA.
[en] Highlights: • NO emission from HTS was investigated within five combustion modes. • The XPS and FTIR were used to characterize nitrogen function group within sludge. • Hydrothermal was effective to lower NO emission independent on combustion modes. • N-C and N-H are two key bonds in sludge with binding energy of 400 and 402 eV. • Hydrothermal enhances the reaction of NO with NH3 to lower NO emission. - Abstract: The hydrothermal (HT) treatment has been developed as a thermal pretreatment technology to improve sludge dewaterability or to produce solid fuel by controlling sludge moisture content. Nevertheless, almost nothing is known about the impact of HT pre-treatment on the NOx emission from sludge combustion. This work mainly focused on the NO emission behavior of HT pretreated and untreated sewage sludge employing five combustion modes, such as conventional combustion (CC), decoupling combustion (DC), separated combustion (SC) and air-staging combustion (AC) with two gas-supplying modes, under a temperature of 1073 K. The results show that the NO emission from the HT pretreated sludge (HTS) was lower than that from the raw sludge (RS), independent on combustion modes. In CC and AC, the HT pretreatment dramatically reduced NO emission with a reduction ratio of 50.7% and 56.4%, respectively. In order to investigate the mechanism of HT reducing NOx emission in various combustion modes, the X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FTIR) spectroscopy examination were performed to investigate the nitrogen functional group existing in the sludge before and after the HT. Two bonds, the N-C bond in amide or amine with a binding energy (BE) of around 400 eV and the N-H bond in ammonia or protonated amine with a BE of about 402 eV were found to be the predominant functional group existing in sewage sludge. The transformation of the protein nature and the reduction of the binding energy between the bonds, have improved the devolatilization properties of sludge, thus enhancing the reaction of NO with NH3 similar to the DeNOx or SNCR process, which is identified as the main reason that the HT dramatically reduced the NO emission from sludge combustion. The data demonstrated that the HT is a promising pretreatment technology because it cannot only improve sludge dewaterability, but also effectively controls the NO emission from sludge combustion
[en] Highlights: • The GDL which has a large MPL penetration showed a better transient response. • The transient response of the PEMFC was affected by the water balance of the GDL. • A large MPL penetration balanced the capillary pressure gradient through the GDL. • The carbon corrosion induced loss of the MPL penetration region. - Abstract: The optimal design of the gas diffusion layer (GDL) of proton exchange membrane fuel cells is crucial because it directly determines the mass transport mechanism of the reactants and products. In this study, the micro-porous layer (MPL) penetration thickness, which affects the pore size profile through the GDL, is varied as the design parameter of the GDL. The cell performance is investigated under various humidity conditions, and the water permeability characteristics are studied. In addition, the accelerated carbon corrosion stress test is conducted to determine the effect of MPL penetration on GDL degradation. GDLs with large MPL penetration thickness show better performance in the high-current–density region due to the enhanced management of water resulting from a balanced capillary pressure gradient. However, the loss of penetrated MPL parts is observed due to the low binding force between the MPL and the GDL substrate
[en] Highlights: • Space heating is the largest energy end use in the U.S. building sector. • A key design and operational parameters have the most influence on space heating. • Simulated results were benchmarked against actual results to analyze discrepancies. • Yearly weather changes have significant impact on space heating energy use. • Findings enable stakeholders to make better decisions on energy efficiency. - Abstract: Space heating is the largest energy end use, consuming more than seven quintillion joules of site energy annually in the U.S. building sector. A few recent studies showed discrepancies in simulated space-heating energy use among different building energy modeling programs, and the simulated results are suspected to be underpredicting reality. While various uncertainties are associated with building simulations, especially when simulations are performed by different modelers using different simulation programs for buildings with different configurations, it is crucial to identify and evaluate key driving factors to space-heating energy use in order to support the design and operation of low-energy buildings. In this study, 10 design and operation parameters for space-heating systems of two prototypical office buildings in each of three U.S. heating climates are identified and evaluated, using building simulations with EnergyPlus, to determine the most influential parameters and their impacts on variations of space-heating energy use. The influence of annual weather change on space-heating energy is also investigated using 30-year actual weather data. The simulated space-heating energy use is further benchmarked against those from similar actual office buildings in two U.S. commercial-building databases to better understand the discrepancies between simulated and actual energy use. In summary, variations of both the simulated and actual space-heating energy use of office buildings in all three heating climates can be very large. However these variations are mostly driven by a few influential parameters related to building design and operation. The findings provide insights for building designers, owners, operators, and energy policy makers to make better decisions on energy-efficiency technologies to reduce space-heating energy use for both new and existing buildings
[en] Highlights: • Oil scrubber and char adsorber for tar removal has been installed to rotary kiln pyrolysis plant. • Used oil and char will be utilized again as fuel of IC engine and heat source for pyrolysis reactor. • The demonstrating test was successfully accomplished with 98.7% gravimetric tar removal. - Abstract: An effective pyrogas cleaning system is necessary for downstream application of biomass pyrolysis technology for power generation. Particularly, tar must be lowered to a satisfying level in order to avoid the problem of tar blockage for preventing damage to the engine and to prolong the engine lifetime. This research was carried out from previous successful research on oil scrubbers and char adsorption for tar removal. Further lab scale experimentation was done to find the appropriate quantity of oil to be used in the scrubber; the results were used for scaling up and showed that the optimum system needed for 0.045 m3/h pyrogas the quantity of 1 l, during a test lasted 30 min. The 1 l oil scrubber was combined with a 41 g char adsorption bed and 97.6% gravimetric tar removal efficiency was obtained. The combination of the oil scrubber and the char adsorption bed was scaled up and installed into the IPRP (Integrated Pyrolysis Regenerated Plant) at the University of Perugia, with chestnut wood (Castanea Sativa Miller) as feedstock, and connected to a 6 kWe Lombardini engine with a power generator and electric load. Pyrogas was sampled at 0.7 m3/h and connected to the cleaning system, consisting of a 15 l oil scrubber combined with a 922 g char adsorption bed. The demonstrating test was successfully accomplished with 98.7% gravimetric tar removal at the exit of the char adsorption bed. The engine ran smoothly and the electric load was constant
[en] Air conditioning is essential for maintaining thermal comfort in indoor environments, particularly for hot and humid climates. Today, air conditioning, comprising cooling and dehumidification, has become a necessity in commercial and residential buildings and industrial processes. It accounts for a major share of the energy consumption of a building or facility. In tropical climates, the energy consumed by heating, ventilation and air-conditioning (HVAC) can exceed 50% of the total energy consumption of a building. This significant figure is primarily due to the heavy duty placed on cooling technologies to remove both sensible and latent heat loads. Therefore, there is tremendous potential to improve the overall efficiency of the air-conditioning systems in buildings. Based on today’s practical technology for cooling, the major components of a chiller plant are (1) compressors, (2) cooling towers, (3) pumps (chilled and cooling water) and (4) fans in air handling units. They all consume mainly electricity to operate. When specifying the kW/R ton of a plant, there are two levels of monitoring cooling efficiency: (1) at the efficiency of the chiller machines or the compressors which consume a major amount of electricity; and (2) at the overall efficiency of cooling plants which include the cooling towers, pumps for moving coolant (chilled and cooling water) to all air-handling units. Pragmatically, a holistic approach is necessary towards achieving a low energy input per cooling achieved such as 0.6 kW/R ton cooling or lower by considering all aspects of the cooling plant. In this paper, we present a review of recent innovative cooling technology and strategies that could potentially lower the kW/R ton of cooling systems – from the existing mean of 0.9 kW/R ton towards 0.6 kW/R ton or lower. The paper, broadly divided into three key sections (see Fig. 2), begins with a review of the recent novel devices that enhances the energy efficiency of cooling systems at the component level. This is followed by a review of innovative cooling systems designs that reduces energy use for air conditioning. Lastly, the paper presents recent developments in intelligent air-control strategies and smart chiller sequencing methodologies that reduce the primary energy utilization for cooling. The energy efficient cooling technology, innovative systems designs, and intelligent control strategies described in the paper have been recently researched or are on-going studies. Several have been implemented on a larger scale and, therefore, are examples of practical solutions that can be readily applied to suit specific needs
[en] Highlights: ► Allowances, public financing and external pressures as major external drivers. ► Ambitious decision-makers with great entrepreneurial mind as major internal drivers. ► Effect of firm’s size (even within SMEs) on drivers to industrial energy efficiency. ► Preliminary evidences of the effect of firm’s internal and external complexity. ► Preliminary evidences of the effect of firm’s innovation characteristics. - Abstract: Several studies have investigated the barriers to industrial energy efficiency, but few have focused on the most effective means (drivers) to promote the adoption of energy-efficient technologies and practices. In this respect, Small and Medium-sized Enterprises (SMEs) have been completely overlooked despite interesting consequences for their overall energy consumption and their concurrent low levels of adoption of energy-efficiency measures. Starting from insights garnered from the extant literature on the drivers of industrial energy efficiency, this paper presents an empirical investigation of 71 Italian manufacturing SMEs through a multiple case-study approach. The research highlights the importance of allowances or public financing for energy efficiency interventions, as well as the importance of external pressures such as increases in energy prices and the introduction or increasing of fees on both resources consumed and on emissions of pollutants. Moreover, enterprises look favourably upon energy-efficient technologies which are able to provide long-term benefits, evidence of their willingness to adopt seemingly radical solutions when these are able to improve their long-term competitiveness. Other drivers considered as strategic for increasing energy efficiency are the presence within the company of people with great ambition and entrepreneurial mind and the management sensitivity to the issue. This paper also provides a preliminary analysis of how factors such as firm size, sector, supply chain complexity, and innovation characteristics are or might be able to significantly affect drivers toward the adoption of energy-efficient technologies