283 resultados para INFRARED EMISSION


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The overall aim of our research was to characterize airborne particles from selected nanotechnology processes and to utilize the data to develop and test quantitative particle concentration-based criteria that can be used to trigger an assessment of particle emission controls. We investigated particle number concentration (PNC), particle mass (PM) concentration, count median diameter (CMD), alveolar deposited surface area, elemental composition, and morphology from sampling of aerosols arising from six nanotechnology processes. These included fibrous and non-fibrous particles, including carbon nanotubes (CNTs). We adopted standard occupational hygiene principles in relation to controlling peak emission and exposures, as outlined by both Safe Work Australia, (1) and the American Conference of Governmental Industrial Hygienists (ACGIH®). (2) The results from the study were used to analyses peak and 30-minute averaged particle number and mass concentration values measured during the operation of the nanotechnology processes. Analysis of peak (highest value recorded) and 30-minute averaged particle number and mass concentration values revealed: Peak PNC20–1000 nm emitted from the nanotechnology processes were up to three orders of magnitude greater than the local background particle concentration (LBPC). Peak PNC300–3000 nm was up to an order of magnitude greater, and PM2.5 concentrations up to four orders of magnitude greater. For three of these nanotechnology processes, the 30-minute average particle number and mass concentrations were also significantly different from the LBPC (p-value < 0.001). We propose emission or exposure controls may need to be implemented or modified, or further assessment of the controls be undertaken, if concentrations exceed three times the LBPC, which is also used as the local particle reference value, for more than a total of 30 minutes during a workday, and/or if a single short-term measurement exceeds five times the local particle reference value. The use of these quantitative criteria, which we are terming the universal excursion guidance criteria, will account for the typical variation in LBPC and inaccuracy of instruments, while precautionary enough to highlight peaks in particle concentration likely to be associated with particle emission from the nanotechnology process. Recommendations on when to utilize local excursion guidance criteria are also provided.

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A technique for analysing exhaust emission plumes from unmodified locomotives under real world conditions is described and applied to the task of characterizing plumes from railway trains servicing an Australian shipping port. The method utilizes the simultaneous measurement, downwind of the railway line, of the following pollutants; particle number, PM2.5 mass fraction, SO2, NOx and CO2, with the last of these being used as an indicator of fuel combustion. Emission factors are then derived, in terms of number of particles and mass of pollutant emitted per unit mass of fuel consumed. Particle number size distributions are also presented. The practical advantages of the method are discussed including the capacity to routinely collect emission factor data for passing trains and to thereby build up a comprehensive real world database for a wide range of pollutants. Samples from 56 train movements were collected, analyzed and presented. The quantitative results for emission factors are: EF(N)=(1.7±1)×1016 kg-1, EF(PM2.5)= (1.1±0.5) g·kg-1, EF(NOx)= (28±14) g·kg-1, and EF(SO2 )= (1.4±0.4) g·kg-1. The findings are compared with comparable previously published work. Statistically significant (p<α, α=0.05) correlations within the group of locomotives sampled were found between the emission factors for particle number and both SO2 and NOx.

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In this report, a detailed FTIR fitting analysis was used to recognize Mg, Zn and Al homogeneous distribution in MgxZnyAl(x+y)/2-Layered double hydroxide (LDH) hydroxyl layer. In detail, OH-Mg2Al:OH-Mg3 ratios decreased from 95.2:4.8 (MIR) and 94.2:5.8 (NIR) to 58.9:41.1 (MIR) and 61.8:38.2 (NIR), when Mg:Al increased from 2.2:1.0 to 4.1:1.0 in MgAl-LDHs. These fitting results were similar with theoretical calculations of 94.3:5.7 and 59.0:41.0. In a further analysis of MgxZnyAl(x+y)/2-LDHs, OH bonded Zn2Mg, Zn2Al, MgZnAl, Mg2Al and Mg2Zn peaks were identified at 3420, 3430, 3445–3450, 3454 and 3545 cm-1, respectively. With the decrease of Mg:Zn from 3:1 to 1:3, metal-hydroxyl bands changed from OH-Mg2Al and MgZnAl (with a ratio of 49.4:50.6) to OH-MgZnAl and Zn2Al (with a ratio of 55.0:45.0). They were also similar with theoretical calculations of 47.6:52.4 and 54.6:45.4. As a result, these results show that there is an ordered cation distribution in MgxZnyAl(x+y)/2-LDH, and FTIR is feasible in recognizing this structure.

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The determination of the characteristics of articular cartilage such as thickness, stiffness and swelling, especially in the form that can facilitate real-time decisions and diagnostics is still a matter for research and development. This paper correlates near infrared spectroscopy with mechanically measured cartilage thickness to establish a fast, non-destructive, repeatable and precise protocol for determining this tissue property. Statistical correlation was conducted between the thickness of bovine cartilage specimens (n = 97) and regions of their near infrared spectra. Nine regions were established along the full absorption spectrum of each sample and were correlated with the thickness using partial least squares (PLS) regression multivariate analysis. The coefficient of determination (R2) varied between 53 and 93%, with the most predictive region (R2 = 93.1%, p < 0.0001) for cartilage thickness lying in the region (wavenumber) 5350–8850 cm−1. Our results demonstrate that the thickness of articular cartilage can be measured spectroscopically using NIR light. This protocol is potentially beneficial to clinical practice and surgical procedures in the treatment of joint disease such as osteoarthritis.

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Despite of significant contributions of urban road transport to global economy and society, it is one of the largest sources of local and global emission impact. In order to address the environmental concerns of urban road transport it is imperative to achieve a holistic understanding of contributory factors causing emissions which requires a complete look onto its whole life cycle. Previous studies were mainly based on segmental views which mostly studied environmental impacts of individual transport modes and very few considered impacts other than operational phase. This study develops an integrated life cycle inventory model for urban road transport emissions from a holistic modal perspective. Singapore case was used to demonstrate the model. Results show that total life cycle greenhouse gas emission from Singapore’s road transport sector is 7.8 million tons per year. The total amount of criteria air pollutants are also estimated in this study.

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This thesis investigates the use of near infrared (NIR) spectroscopic methods for rapid measurement of nutrient elements in mill mud and mill ash. Adoption of NIR-based analyses for carbon, nitrogen, phosphorus, potassium and silicon will allow Australian sugarcane farmers to comply with recent legislative changes, and act within recommended precision farming frameworks. For these analyses, NIR spectroscopic methods surpass several facets of traditional wet chemistry techniques, dramatically reducing costs, required expertise and chemical exposure, while increasing throughput and access to data. Further, this technology can be applied in various modes, including laboratory, at-line and on-line installations, allowing targeted measurement.

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A catalyst comprising a catalytic material supported on a support, characterized in that the support comprises particles predominantly having a max. particle size of less than 1000 nm and an aspect ratio of greater than, and the. catalytic material is mainly present in the form of discrete islands of catalytic material supported on the support, with a substantial proportion of the islands of catalytic material being sep. and isolated from other islands of catalytic material. The islands of catalytic material are sep. and isolated from other islands of catalytic material such that diffusion and growth of the islands of catalytic material at elevated temp. is minimized or avoided. The disclosure and examples pertain to emission control catalysts. [on SciFinder(R)]

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A method for forming a material comprising a metal oxide supported on a support particle comprising the steps of: (a) providing a precursor mixt. comprising a soln. contg. one or more metal cations and (i) a surfactant; or (ii) a hydrophilic polymer; said precursor mixt. further including support particles; and (b) treating the precursor mixt. from (a) above by heating to remove the surfactant or hydrophilic polymer and form metal oxide having nanosized grains, wherein at least some of the metal oxide formed in step (b) is deposited on or supported by the support particles and the metal oxide has an oxide matrix that includes metal atoms derived solely from sources other than the support particles. The disclosure and examples pertain to emission control catalysts. [on SciFinder(R)]

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We have studied the mineral olmiite CaMn\[SiO3(OH)](OH) which forms a series with its calcium analogue poldevaartite CaCa\[SiO3(OH)](OH) using a range of techniques including scanning electron microscopy, thermogravimetric analysis , Raman and infrared spectroscopy. Chemical analysis shows the mineral is pure and contains only calcium and manganese in the formula. Thermogravimetric analysis proves the mineral decomposes at 502°C with a mass loss of 8.8% compared with the theoretical mass loss of 8.737%. A strong Raman band at 853 cm-1 is assigned to the SiO stretching vibration of the SiO3(OH) units. Two Raman bands at 914 and 953 cm-1 are attributed to the antisymmetric vibrations.Two intense Raman bands observed at 3511 and 3550 cm-1 are assigned to the OH stretching vibration of the SiO3(OH) units. The observation of multiple OH bands supports the concept of the non-equivalence of the OH units. Vibrational spectroscopy enables a detailed assessment of the molecular structure of olmiite.

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We have studied the mineral hydroboracite CaMg[B3O4(OH)3]2∙3H2O using electron microscopy and vibrational spectroscopy. Both tetrahedral and trigonal boron units are observed. The nominal resolution of the Raman spectrometer is of the order of 2 cm-1 and as such is sufficient enough to identify separate bands for the stretching bands of the two boron isotopes. The Raman band at 1039 cm-1 is assigned to BO stretching vibration. Raman bands at 1144, 1157, 1229, 1318 cm-1 are attributed to the BOH in-plane bending modes. Raman bands at 825 and 925 cm-1 are attributed to the antisymmetric stretching modes of tetrahedral boron. The sharp Raman peak at 925 cm-1 is from the 11-B component such a mode, then it should have a smaller 10-B satellite near (1.03)x(925) = 952 cm-1, and indeed a small peak at 955 is observed. Four sharp Raman bands observed at 3371, 3507, 3563 and 3632 cm-1 are attributed to the stretching vibrations of hydroxyl units. The broad Raman bands at 3076, 3138, 3255, 3384 and 3551 cm-1 are assigned to water stretching vibrations. Infrared bands at 3367, 3505, 3559 and 3631 cm-1are assigned to the stretching vibration of the hydroxyl units. Broad infrared bands at 3072 and 3254 cm-1 are assigned to water stretching vibrations. Infrared bands at 1318, 1349, 1371, 1383 cm-1 are assigned to the antisymmetric stretching vibrations of trigonal boron

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This thesis investigates condition monitoring (CM) of diesel engines using acoustic emission (AE) techniques. The AE signals recorded from a small size diesel engine are mixtures of multiple sources from multiple cylinders. Thus, it is difficult to interpret the information conveyed in the signals for CM purposes. This thesis develops a series of practical signal processing techniques to overcome this problem. Various experimental studies conducted to assess the CM capabilities of AE analysis for diesel engines. A series of modified signal processing techniques were proposed. These techniques showed promising results of capability for CM of multiple cylinders diesel engine using multiple AE sensors.

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Near-infrared spectroscopy (NIRS) calibrations were developed for the discrimination of Chinese hawthorn (Crataegus pinnatifida Bge. var. major) fruit from three geographical regions as well as for the estimation of the total sugar, total acid, total phenolic content, and total antioxidant activity. Principal component analysis (PCA) was used for the discrimination of the fruit on the basis of their geographical origin. Three pattern recognition methods, linear discriminant analysis, partial least-squares-discriminant analysis, and back-propagation artificial neural networks, were applied to classify and compare these samples. Furthermore, three multivariate calibration models based on the first derivative NIR spectroscopy, partial least-squares regression, back-propagation artificial neural networks, and least-squares-support vector machines, were constructed for quantitative analysis of the four analytes, total sugar, total acid, total phenolic content, and total antioxidant activity, and validated by prediction data sets.

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This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

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This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.

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Many applications can benefit from the accurate surface temperature estimates that can be made using a passive thermal-infrared camera. However, the process of radiometric calibration which enables this can be both expensive and time consuming. An ad hoc approach for performing radiometric calibration is proposed which does not require specialized equipment and can be completed in a fraction of the time of the conventional method. The proposed approach utilizes the mechanical properties of the camera to estimate scene temperatures automatically, and uses these target temperatures to model the effect of sensor temperature on the digital output. A comparison with a conventional approach using a blackbody radiation source shows that the accuracy of the method is sufficient for many tasks requiring temperature estimation. Furthermore, a novel visualization method is proposed for displaying the radiometrically calibrated images to human operators. The representation employs an intuitive coloring scheme and allows the viewer to perceive a large variety of temperatures accurately.