Spectral high resolution feature selection for retrieval of combustion temperature profiles

Proceeding of: 7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006 (Burgos, Spain, September 20-23, 2006)The use of high spectral resolution measurements to obtain a retrieval of certain physical properties related with the radiative transfer of energy leads a priori to a better accuracy. But this improvement in accuracy is not easy to achieve due to the great amount of data which makes difficult any treatment over it and it's redundancies. To solve this problem, a pick selection based on principal component analysis has been adopted in order to make the mandatory feature selection over the different channels. In this paper, the capability to retrieve the temperature profile in a combustion environment using neural networks jointly with this spectral high resolution feature selection method is studied.Publicad

Neural networks and spectra feature selection for retrival of hot gases temperature profiles

Proceeding of: International Conference on Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Vienna, Austria 28-30 Nov. 2005Neural networks appear to be a promising tool to solve the so-called inverse problems focused to obtain a retrieval of certain physical properties related to the radiative transference of energy. In this paper the capability of neural networks to retrieve the temperature profile in a combustion environment is proposed. Temperature profile retrieval will be obtained from the measurement of the spectral distribution of energy radiated by the hot gases (combustion products) at wavelengths corresponding to the infrared region. High spectral resolution is usually needed to gain a certain accuracy in the retrieval process. However, this great amount of information makes mandatory a reduction of the dimensionality of the problem. In this sense a careful selection of wavelengths in the spectrum must be performed. With this purpose principal component analysis technique is used to automatically determine those wavelengths in the spectrum that carry relevant information on temperature distribution. A multilayer perceptron will be trained with the different energies associated to the selected wavelengths. The results presented show that multilayer perceptron combined with principal component analysis is a suitable alternative in this field.Publicad

Multilayer perceptron as inverse model in a ground-based remote sensing temperature retrieval problem

In this paper, a combustion temperature retrieval approximation for high-resolution infrared ground-based measurements has been developed based on a multilayer perceptron (MLP) technique. The introduction of a selection subset of features is mandatory due to the problems related to the high dimensionality data and the worse performance of MLPs with this high input dimensionality. Principal component analysis is used to reduce the input data dimensionality, selecting the physically important features in order to improve MLP performance. The use of a priori physical information over other methods in the chosen feature’s phase has been tested and has appeared jointly with the MLP technique as a good alternative for this problem.Publicad

Development of Imaging Fourier-Transform Spectroscopy for the Characterization of Turbulent Jet Flames

Recent advances in computational models to simulate turbulent, reactive flow fields have outpaced the ability to collect highly constraining data--throughout the entire flow field--for validating and improving such models. In particular, the ability to quantify in three dimensions both the mean scalar fields (i.e. temperature & species concentrations) and their respective fluctuation statistics via hyperspectral imaging would be a game-changing advancement in combustion diagnostics, with high impact in both validation and improvement efforts for computational combustion models. This research effort establishes imaging Fourier-transform spectrometry (IFTS) as a valuable tool (which complements laser diagnostics) for the study of turbulent combustion. Specifically, this effort (1) demonstrates that IFTS can be used to quantitatively measure spatially resolved spectra from a canonical turbulent flame; (2) establishes the utility of quantile spectra in first-ever quantitative comparisons between measured and modeled turbulent radiation interaction (TRI); (3) develops a simple onion-peeling-like spectral inversion methodology suitable for estimating radial scalar distributions in axisymmetric, optically-thick flames; (4) builds understanding of quantile spectra and demonstrates proof of concept for their use in estimating scalar fluctuation statistics

Laminar Flame Combustion Diagnostics Using Imaging Fourier Transform Spectroscopy

Laminar flames are an important tool in combustion diagnostics with a host of pre-existing experimental research methods. Currently, however, no method captures time-resolved scalar profile estimates of temperature, and major species concentrations with a single measurement. This work provides IFTS with the capability to measure time-resolved 3D imaging of scalar values in laminar axisymmetric flames. This will make IFTS a useful tool for understanding combustion phenomenon, validating chemical kinetic models, verifying numerical simulations, and system performance estimate. Two algorithms are presented. The first reconstructs spectra as a function of flame period. Through selectively averaging over an ensemble of measurements, interferograms representing the scalar fields at t0 can be created. The second improves on traditional tomographic inversion methods to radially resolve multiple scalar values simultaneously in an axisymmetric flame. The combination of these two algorithms was applied to measurements of an unsteady laminar hydrogen flame. Temperature and water concentrations were successfully resolved radially at eight different snapshot times in the period of the flames harmonic motion. Measured results compared favorably with previously reported values and CFD simulations. Temperatures agree to within 11% and water concentration values agree to within 19%. This work demonstrates the ability of IFTS to make time-resolved 3-D maps of scalar values of harmonic laminar flame

Analysis and interpretation of satellite measurements in the near-infrared spectral region with the focus on carbon monoxide

Carbon monoxide (CO) plays an important role in the Earth's atmosphere. Through its reaction with the hydroxyl radicals (OH) (Logan et al., 1981), CO affects the lifetime of atmospheric methane (CH4), and non-methane hydrocarbons (NMHCs). A main product of this oxidation is carbon dioxide (CO2). Therefore, containing no direct green-house potential, CO still has an indirect effect on the global warming. CO is also one of the most important health hazardous pollutants, which can cause diseases of different degrees of complexity. The nadir near-infrared measurements of scattered and reflected solar radiation by SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on board the ENVISAT satellite contain information about CO concentration in all atmospheric layers including the boundary layer, closest to the location of main CO sources. However, the retrieval of CO total column from the radiometric measurements in this spectral region is complicated as the CO overtone lines are weak, and overlapped by strong absorptions of water vapour and methane. Moreover, several known instrumental issues, like an ice layer on the detector and degradation of the detector pixels with time, additionally complicate the retrieval of CO vertical column from the of SCIAMACHY measurements in channel 8. In the scope of this work, the WFM-DOAS (Weighting Functions Modified Differential Optical Absorption Spectroscopy) retrieval algorithm, developed at the University of Bremen, have been improved in order to establish the retrieval of a multi-year CO dataset from SCIAMACHY nadir measurements. The modifications have led to an improved CO fit quality, i.e., to an overall much smaller fit residual. An error analysis and sensitivity studies based on the simulated measurements have shown that the error is generally less than 10%, which is comparable to the required precision for space-based CO measurements. However, due to high instrument noise, the error of the real measurements has been found to be much higher and considerably less stable. The retrieved CO columns have been validated by comparison with ground-based Fourier Transform Spectroscopy (FTS) measurements. A good agreement within 10-20% was found for nearly all considered stations. Furthermore, high correlation between the SCIAMACHY CO and CO from independent space-based total columns measurements performed by the MOPITT (Measurements of Pollution in the Troposphere) instrument onboard the Terra satellite indicates a good performance of the SCIAMACHY CO measurements globally. The overall difference of about 10% can be well explained by the moderate sensitivity of the thermal-infrared MOPITT measurements to lower atmospheric layers.Detailed analysis of the obtained CO dataset has been has been carried out on country level. Due to the presence of strong anthropogenic sources and prevailing west wind conditions, a positive difference of CO concentration is expected from the west to the east side of the United Kingdom. The analysis shows that SCIAMACHY is able to capture the positive 5% west-to-east CO gradient over the UK. These results are consistent with the direct airborne measurements during the AMPEP campaign, which estimated the CO concentration enhancement from the west to the east coast of the UK to be about 10-100 ppb, corresponding to the total column enhancement of 1-10% within the 1 km boundary layer. Over much stronger sources, such as a large biomass burning events, the quantitative potential of SCIAMACHY CO data is expected to be much higher due to much higher levels of CO signal and respectively more available ( good ) satellite measurements. To use this fact for further quantitative investigation, the SCIAMACHY simultaneously measurements of CO, nitrogen dioxide (NO2) and formaldehyde (HCHO) over biomass burning events in 2004, were analysed in the scope of the bottom-up emission estimation Excess Mixing Ratios (EMR) method. Good agreement has been found between the calculated SCIAMACHY (Delta CO)/(Delta HCHO) and (Delta CO)/(Delta NO2) and the ER values from referenced literature

High Resolution Spectra of Carbon Monoxide, Propane and Ammonia for Atmospheric Remote Sensing

Spectroscopy is a critical tool for analyzing atmospheric data. Identification of atmospheric parameters such as temperature, pressure and the existence and concentrations of constituent gases via remote sensing techniques are only possible with spectroscopic data. These form the basis of model atmospheres which may be compared to observations to determine such parameters. To this end, this dissertation explores the spectroscopy of three molecules: ammonia, propane and carbon monoxide. Infrared spectra have been recorded for ammonia in the region 2400-9000 cm-1. These spectra were recorded at elevated temperatures (from 293-973 K) using a Fourier Transform Spectrometer (FTS). Comparison between the spectra recorded at different temperatures yielded experimental lower state energies. These spectra resulted in the measurement of roughly 30000 lines and about 3000 quantum assignments. In addition spectra of propane were recorded at elevated temperatures (296-700 K) using an FTS. Atmospheres with high temperatures require molecular data at appropriate conditions. This dissertation describes collection of such data and the potential application to atmospheres in our solar system, such as auroral regions in Jupiter, to those of planets orbiting around other stars and cool sub-stellar objects known as brown dwarfs. The spectra of propane and ammonia provide the highest resolution and most complete experimental study of these gases in their respective spectral regions at elevated temperatures. Detection of ammonia in an exoplanet or detection of propane in the atmosphere of Jupiter will most likely rely on the work presented here. The best laboratory that we have to study atmospheres is our own planet. The same techniques that are applied to these alien atmospheres originated on Earth. As such it is appropriate to discuss remote sensing of our own atmosphere. This idea is explored through analysis of spectroscopic data recorded by an FTS on the Atmospheric Chemistry Experiment satellite of carbon monoxide. The effect of the atmosphere’s chemistry and physics on this molecule is measured through its isotopologues, primarily 13CO (carbon-13 substituted carbon monoxide). Isotopic chemistry allows a key analysis of the atmosphere as it may be used as a tracer for chemical reactions and dynamical processes. The carbon monoxide fractionation results in Chapter IV present the first global measurements of isotopic fractionation of CO, showing significant fractionation in the upper atmosphere (60-80 km) as a result of the photolysis of carbon dioxide (CO2)

The AMMA mulid network for aerosol characterization in West Africa

Three ground based portable low power consumption microlidars (MULID) have been built and deployed at three remote sites in Banizoumbou (Niger), Cinzana (Mali) and M'Bour (Senegal) in the framework of the African Monsoon Multidisciplinary Analyses (AMMA) project for the characterization of aerosols optical properties. A description of the instrument and a discussion of the data inversion method, including a careful analysis of measurement uncertainties (systematic and statistical errors) are presented. Some case studies of typical lidar profiles observed over the Banizoumbou site during 2006 are shown and discussed with respect to the AERONET 7-day back-trajectories and the biomass burning emissions from the Combustion Emission database for the AMMA campaign

Equipment concept design and development plans for microgravity science and applications research on space station: Combustion tunnel, laser diagnostic system, advanced modular furnace, integrated electronics laboratory

Taking advantage of the microgravity environment of space NASA has initiated the preliminary design of a permanently manned space station that will support technological advances in process science and stimulate the development of new and improved materials having applications across the commercial spectrum. Previous studies have been performed to define from the researcher's perspective, the requirements for laboratory equipment to accommodate microgravity experiments on the space station. Functional requirements for the identified experimental apparatus and support equipment were determined. From these hardware requirements, several items were selected for concept designs and subsequent formulation of development plans. This report documents the concept designs and development plans for two items of experiment apparatus - the Combustion Tunnel and the Advanced Modular Furnace, and two items of support equipment the Laser Diagnostic System and the Integrated Electronics Laboratory. For each concept design, key technology developments were identified that are required to enable or enhance the development of the respective hardware