Selective catalytic reduction of nitrogen oxides with ammonia in forced unsteady state reactors - Case based reasoning and mathematical model simulation reasoning

The application of forced unsteady-state reactors in case of selective catalytic reduction of nitrogen oxides (NOx) with ammonia (NH3) is sustained by the fact that favorable temperature and composition distributions which cannot be achieved in any steady-state regime can be obtained by means of unsteady-state operations. In a normal way of operation the low exothermicity of the selective catalytic reduction (SCR) reaction (usually carried out in the range of 280-350°C) is not enough to maintain by itself the chemical reaction. A normal mode of operation usually requires supply of supplementary heat increasing in this way the overall process operation cost. Through forced unsteady-state operation, the main advantage that can be obtained when exothermic reactions take place is the possibility of trapping, beside the ammonia, the moving heat wave inside the catalytic bed. The unsteady state-operation enables the exploitation of the thermal storage capacity of the catalyticbed. The catalytic bed acts as a regenerative heat exchanger allowing auto-thermal behaviour when the adiabatic temperature rise is low. Finding the optimum reactor configuration, employing the most suitable operation model and identifying the reactor behavior are highly important steps in order to configure a proper device for industrial applications. The Reverse Flow Reactor (RFR) - a forced unsteady state reactor - corresponds to the above mentioned characteristics and may be employed as an efficient device for the treatment of dilute pollutant mixtures. As a main disadvantage, beside its advantages, the RFR presents the 'wash out' phenomena. This phenomenon represents emissions of unconverted reactants at every switch of the flow direction. As a consequence our attention was focused on finding an alternative reactor configuration for RFR which is not affected by the incontrollable emissions of unconverted reactants. In this respect the Reactor Network (RN) was investigated. Its configuration consists of several reactors connected in a closed sequence, simulating a moving bed by changing the reactants feeding position. In the RN the flow direction is maintained in the same way ensuring uniformcatalyst exploitation and in the same time the 'wash out' phenomena is annulated. The simulated moving bed (SMB) can operate in transient mode giving practically constant exit concentration and high conversion levels. The main advantage of the reactor network operation is emphasizedby the possibility to obtain auto-thermal behavior with nearly uniformcatalyst utilization. However, the reactor network presents only a small range of switching times which allow to reach and to maintain an ignited state. Even so a proper study of the complex behavior of the RN may give the necessary information to overcome all the difficulties that can appear in the RN operation. The unsteady-state reactors complexity arises from the fact that these reactor types are characterized by short contact times and complex interaction between heat and mass transportphenomena. Such complex interactions can give rise to a remarkable complex dynamic behavior characterized by a set of spatial-temporal patterns, chaotic changes in concentration and traveling waves of heat or chemical reactivity. The main efforts of the current research studies concern the improvement of contact modalities between reactants, the possibility of thermal wave storage inside the reactor and the improvement of the kinetic activity of the catalyst used. Paying attention to the above mentioned aspects is important when higher activity even at low feeding temperatures and low emissions of unconverted reactants are the main operation concerns. Also, the prediction of the reactor pseudo or steady-state performance (regarding the conversion, selectivity and thermal behavior) and the dynamicreactor response during exploitation are important aspects in finding the optimal control strategy for the forced unsteady state catalytic tubular reactors. The design of an adapted reactor requires knowledge about the influence of its operating conditions on the overall process performance and a precise evaluation of the operating parameters rage for which a sustained dynamic behavior is obtained. An apriori estimation of the system parameters result in diminution of the computational efforts. Usually the convergence of unsteady state reactor systems requires integration over hundreds of cycles depending on the initial guess of the parameter values. The investigation of various operation models and thermal transfer strategies give reliable means to obtain recuperative and regenerative devices which are capable to maintain an auto-thermal behavior in case of low exothermic reactions. In the present research work a gradual analysis of the SCR of NOx with ammonia process in forced unsteady-state reactors was realized. The investigation covers the presentationof the general problematic related to the effect of noxious emissions in the environment, the analysis of the suitable catalysts types for the process, the mathematical analysis approach for modeling and finding the system solutions and the experimental investigation of the device found to be more suitable for the present process. In order to gain information about the forced unsteady state reactor design, operation, important system parameters and their values, mathematical description, mathematicalmethod for solving systems of partial differential equations and other specific aspects, in a fast and easy way, and a case based reasoning (CBR) approach has been used. This approach, using the experience of past similarproblems and their adapted solutions, may provide a method for gaining informations and solutions for new problems related to the forced unsteady state reactors technology. As a consequence a CBR system was implemented and a corresponding tool was developed. Further on, grooving up the hypothesis of isothermal operation, the investigation by means of numerical simulation of the feasibility of the SCR of NOx with ammonia in the RFRand in the RN with variable feeding position was realized. The hypothesis of non-isothermal operation was taken into account because in our opinion ifa commercial catalyst is considered, is not possible to modify the chemical activity and its adsorptive capacity to improve the operation butis possible to change the operation regime. In order to identify the most suitable device for the unsteady state reduction of NOx with ammonia, considering the perspective of recuperative and regenerative devices, a comparative analysis of the above mentioned two devices performance was realized. The assumption of isothermal conditions in the beginningof the forced unsteadystate investigation allowed the simplification of the analysis enabling to focus on the impact of the conditions and mode of operation on the dynamic features caused by the trapping of one reactant in the reactor, without considering the impact of thermal effect on overall reactor performance. The non-isothermal system approach has been investigated in order to point out the important influence of the thermal effect on overall reactor performance, studying the possibility of RFR and RN utilization as recuperative and regenerative devices and the possibility of achieving a sustained auto-thermal behavior in case of lowexothermic reaction of SCR of NOx with ammonia and low temperature gasfeeding. Beside the influence of the thermal effect, the influence of the principal operating parameters, as switching time, inlet flow rate and initial catalyst temperature have been stressed. This analysis is important not only because it allows a comparison between the two devices and optimisation of the operation, but also the switching time is the main operating parameter. An appropriate choice of this parameter enables the fulfilment of the process constraints. The level of the conversions achieved, the more uniform temperature profiles, the uniformity ofcatalyst exploitation and the much simpler mode of operation imposed the RN as a much more suitable device for SCR of NOx with ammonia, in usual operation and also in the perspective of control strategy implementation. Theoretical simplified models have also been proposed in order to describe the forced unsteady state reactors performance and to estimate their internal temperature and concentration profiles. The general idea was to extend the study of catalytic reactor dynamics taking into account the perspectives that haven't been analyzed yet. The experimental investigation ofRN revealed a good agreement between the data obtained by model simulation and the ones obtained experimentally.

Atmospheric downwelling longwave radiation at the surface during cloudless and overcast conditions. Measurements and modeling

Atmospheric downwelling longwave radiation is an important component of the terrestrial energy budget; since it is strongly related with the greenhouse effect, it remarkably affects the climate. In this study, I evaluate the estimation of the downwelling longwave irradiance at the terrestrial surface for cloudless and overcast conditions using a one-dimensional radiative transfer model (RTM), specifically the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). The calculations performed by using this model were compared with pyrgeometer measurements at three different European places: Girona (NE of the Iberian Peninsula), Payerne (in the East of Switzerland), and Heselbach (in the Black Forest, Germany). Several studies of sensitivity based on the radiative transfer model have shown that special attention on the input of temperature and water content profiles must be held for cloudless sky conditions; for overcast conditions, similar sensitivity studies have shown that, besides the atmospheric profiles, the cloud base height is very relevant, at least for optically thick clouds. Also, the estimation of DLR in places where radiosoundings are not available is explored, either by using the atmospheric profiles spatially interpolated from the gridded analysis data provided by European Centre of Medium-Range Weather Forecast (ECMWF), or by applying a real radiosounding of a nearby site. Calculations have been compared with measurements at all sites. During cloudless sky conditions, when radiosoundings were available, calculations show differences with measurements of -2.7 ± 3.4 Wm-2 (Payerne). While no in situ radiosoundings are available, differences between modeling and measurements were about 0.3 ± 9.4 Wm-2 (Girona). During overcast sky conditions, when in situ radiosoundings and cloud properties (derived from an algorithm that uses spectral infrared and microwave ground based measurements) were available (Black Forest), calculations show differences with measurements of -0.28 ± 2.52 Wm2. When using atmospheric profiles from the ECMWF and fixed values of liquid water path and droplet effective radius (Girona) calculations show differences with measurements of 4.0 ± 2.5 Wm2. For all analyzed sky conditions, it has been confirmed that estimations from radiative transfer modeling are remarkably better than those obtained by simple parameterizations of atmospheric emissivity.

Atlantic climate variability and predictability: A CLIVAR perspective

Three interrelated climate phenomena are at the center of the Climate Variability and Predictability (CLIVAR) Atlantic research: tropical Atlantic variability (TAV), the North Atlantic Oscillation (NAO), and the Atlantic meridional overturning circulation (MOC). These phenomena produce a myriad of impacts on society and the environment on seasonal, interannual, and longer time scales through variability manifest as coherent fluctuations in ocean and land temperature, rainfall, and extreme events. Improved understanding of this variability is essential for assessing the likely range of future climate fluctuations and the extent to which they may be predictable, as well as understanding the potential impact of human-induced climate change. CLIVAR is addressing these issues through prioritized and integrated plans for short-term and sustained observations, basin-scale reanalysis, and modeling and theoretical investigations of the coupled Atlantic climate system and its links to remote regions. In this paper, a brief review of the state of understanding of Atlantic climate variability and achievements to date is provided. Considerable discussion is given to future challenges related to building and sustaining observing systems, developing synthesis strategies to support understanding and attribution of observed change, understanding sources of predictability, and developing prediction systems in order to meet the scientific objectives of the CLIVAR Atlantic program.

First structural analysis of a naphthalene-based poly(ether ketone): Crystal and molecular simulation from X-ray powder data and diffraction modeling

Polycondensation of 2,6-dihydroxynaphthalene with 4,4'-bis(4"-fluorobenzoyl)biphenyl affords a novel, semicrystalline poly(ether ketone) with a melting point of 406 degreesC and glass transition temperature (onset) of 168 degreesC. Molecular modeling and diffraction-simulation studies of this polymer, coupled with data from the single-crystal structure of an oligomer model, have enabled the crystal and molecular structure of the polymer to be determined from X-ray powder data. This structure-the first for any naphthalene-containing poly(ether ketone)-is fully ordered, in monoclinic space group P2(1)/b, with two chains per unit cell. Rietveld refinement against the experimental powder data gave a final agreement factor (R-wp) of 6.7%.

Hyperresolution global land surface modeling: meeting a grand challenge for monitoring Earth's terrestrial water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Collaboration of the weather and climate communities to advance subseasonal-to-seasonal prediction

The World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP) have identified collaborations and scientific priorities to accelerate advances in analysis and prediction at subseasonal-to-seasonal time scales, which include i) advancing knowledge of mesoscale–planetary-scale interactions and their prediction; ii) developing high-resolution global–regional climate simulations, with advanced representation of physical processes, to improve the predictive skill of subseasonal and seasonal variability of high-impact events, such as seasonal droughts and floods, blocking, and tropical and extratropical cyclones; iii) contributing to the improvement of data assimilation methods for monitoring and predicting used in coupled ocean–atmosphere–land and Earth system models; and iv) developing and transferring diagnostic and prognostic information tailored to socioeconomic decision making. The document puts forward specific underpinning research, linkage, and requirements necessary to achieve the goals of the proposed collaboration.

Prediction of visibility and aerosol within the operational Met Office unified model. I: Model formulation and variational assimilation

The formulation and performance of the Met Office visibility analysis and prediction system are described. The visibility diagnostic within the limited-area Unified Model is a function of humidity and a prognostic aerosol content. The aerosol model includes advection, industrial and general urban sources, plus boundary-layer mixing and removal by rain. The assimilation is a 3-dimensional variational scheme in which the visibility observation operator is a very nonlinear function of humidity, aerosol and temperature. A quality control scheme for visibility data is included. Visibility observations can give rise to humidity increments of significant magnitude compared with the direct impact of humidity observations. We present the results of sensitivity studies which show the contribution of different components of the system to improved skill in visibility forecasts. Visibility assimilation is most important within the first 6-12 hours of the forecast and for visibilities below 1 km, while modelling of aerosol sources and advection is important for slightly higher visibilities (1-5 km) and is still significant at longer forecast times

Case study modeling of turbulent and mesoscale fluxes over the BOREAS region

Results from aircraft and surface observations provided evidence for the existence of mesoscale circulations over the Boreal Ecosystem-Atmosphere Study (BOREAS) domain. Using an integrated approach that included the use of analytical modeling, numerical modeling, and data analysis, we have found that there are substantial contributions to the total budgets of heat over the BOREAS domain generated by mesoscale circulations. This effect is largest when the synoptic flow is relatively weak, yet it is present under less favorable conditions, as shown by the case study presented here. While further analysis is warranted to document this effect, the existence of mesoscale flow is not surprising, since it is related to the presence of landscape patches, including lakes, which are of a size on the order of the local Rossby radius and which have spatial differences in maximum sensible heat flux of about 300 W m−2. We have also analyzed the vertical temperature profile simulated in our case study as well as high-resolution soundings and we have found vertical profiles of temperature change above the boundary layer height, which we attribute in part to mesoscale contributions. Our conclusion is that in regions with organized landscapes, such as BOREAS, even with relatively strong synoptic winds, dynamical scaling criteria should be used to assess whether mesoscale effects should be parameterized or explicitly resolved in numerical models of the atmosphere.

Simultaneous prediction of symptom severity and cause in data from a test battery for Parkinson patients, using machine learning methods

The main purpose of this thesis project is to prediction of symptom severity and cause in data from test battery of the Parkinson’s disease patient, which is based on data mining. The collection of the data is from test battery on a hand in computer. We use the Chi-Square method and check which variables are important and which are not important. Then we apply different data mining techniques on our normalize data and check which technique or method gives good results.The implementation of this thesis is in WEKA. We normalize our data and then apply different methods on this data. The methods which we used are Naïve Bayes, CART and KNN. We draw the Bland Altman and Spearman’s Correlation for checking the final results and prediction of data. The Bland Altman tells how the percentage of our confident level in this data is correct and Spearman’s Correlation tells us our relationship is strong. On the basis of results and analysis we see all three methods give nearly same results. But if we see our CART (J48 Decision Tree) it gives good result of under predicted and over predicted values that’s lies between -2 to +2. The correlation between the Actual and Predicted values is 0,794in CART. Cause gives the better percentage classification result then disability because it can use two classes.

Syntheses of Cross-Linking Agents, Molecular Modeling of Oligonucleotides and Polypeptide-Ion Complexes

Each section of this thesis will be subdivided into three parts encompassing all of the research in which I have been involved during the past three years. These will be referred to under the headings "Syntheses:' "Molecular Modeling," and "Cross-linking Efficiencies." Each of these subdivisions may have divisions within them when necessary in order to fully detail the research.

Discoloration process modeling by neural network

The photo-oxidation of acid orange 52 dye was performed in the presence of H2O2, utilizing UV light, aiming the discoloration process modeling and the process variable influence characterization. The discoloration process was modeled by the use of feedforward neural network. Each sample was characterized by five independent variables (dye concentration, pH, hydrogen peroxide volume, temperature and time of operation) and a dependent variable (absorbance). The neural model has also provided, through Garson Partition coefficients and the Pertubation method, the independent variable influence order determination. The results indicated that the time of operation was the predominant variable and reaction mean temperature was the lesser influent variable. The neural model obtained presented coefficients of correlation on the order 0.98, for sets of trainability, validation and testing, indicating the power of prediction of the model and its character of generalization. (c) 2007 Elsevier B.V. All rights reserved.

Molecular modeling databases: A new way in the search of protein targets for drug development

DBMODELING is a relational database of annotated comparative protein structure models and their metabolic, pathway characterization. It is focused on enzymes identified in the genomes of Mycobacterium tuberculosis and Xylella fastidiosa. The main goal of the present database is to provide structural models to be used in docking simulations and drug design. However, since the accuracy of structural models is highly dependent on sequence identity between template and target, it is necessary to make clear to the user that only models which show high structural quality should be used in such efforts. Molecular modeling of these genomes generated a database, in which all structural models were built using alignments presenting more than 30% of sequence identity, generating models with medium and high accuracy. All models in the database are publicly accessible at http://www.biocristalografia.df.ibilce.unesp.br/tools. DBMODELING user interface provides users friendly menus, so that all information can be printed in one stop from any web browser. Furthermore, DBMODELING also provides a docking interface, which allows the user to carry out geometric docking simulation, against the molecular models available in the database. There are three other important homology model databases: MODBASE, SWISSMODEL, and GTOP. The main applications of these databases are described in the present article. © 2007 Bentham Science Publishers Ltd.

Free tools and strategies for the generation of 3D finite element meshes: Modeling of the cardiac structures

The Finite Element Method is a well-known technique, being extensively applied in different areas. Studies using the Finite Element Method (FEM) are targeted to improve cardiac ablation procedures. For such simulations, the finite element meshes should consider the size and histological features of the target structures. However, it is possible to verify that some methods or tools used to generate meshes of human body structures are still limited, due to nondetailed models, nontrivial preprocessing, or mainly limitation in the use condition. In this paper, alternatives are demonstrated to solid modeling and automatic generation of highly refined tetrahedral meshes, with quality compatible with other studies focused on mesh generation. The innovations presented here are strategies to integrate Open Source Software (OSS). The chosen techniques and strategies are presented and discussed, considering cardiac structures as a first application context. © 2013 E. Pavarino et al.

Development and evolution of caste dimorphism in honeybees - a modeling approach

The difference in phenotypes of queens and workers is a hallmark of the highly eusocial insects. The caste dimorphism is often described as a switch-controlled polyphenism, in which environmental conditions decide an individual's caste. Using theoretical modeling and empirical data from honeybees, we show that there is no discrete larval developmental switch. Instead, a combination of larval developmental plasticity and nurse worker feeding behavior make up a colony-level social and physiological system that regulates development and produces the caste dimorphism. Discrete queen and worker phenotypes are the result of discrete feeding regimes imposed by nurses, whereas a range of experimental feeding regimes produces a continuous range of phenotypes. Worker ovariole numbers are reduced through feeding-regime-mediated reduction in juvenile hormone titers, involving reduced sugar in the larval food. Based on the mechanisms identified in our analysis, we propose a scenario of the evolutionary history of honeybee development and feeding regimes.

Her2p molecular modeling, mutant analysis and intramitochondrial localization

Bacterial GatCAB amidotransferases are responsible for the transamidation of mischarged glutamyl-tRNA(Gln) into glutaminyl-tRNA(Gln). Mitochondria matrix also has a multienzymatic complex necessary for the transamidation of glutamyl-tRNA(Gln). Gtf1p, Her2p and Pet112p are the constituents of mitochondrial GatFAB amidotransferase complex. Her2p is subunit A of GatFAB complex, while Gtf1p is subunit F, a connector protein between Pet112p (subunit B) and Her2p. Here we evaluate through molecular modeling and amino acid correlation analysis the HER2 protein family. Localization studies indicated that Her2p is predominantly localized in the mitochondrial outer membrane, but it is also located in the mitochondrial matrix where together with Pet112p and Gtf1p constitutes the GatFAB complex. Finally, HER2 random mutagenesis unveiled important residues that provide thermo stability for the complex and are differently suppressed by overexpression of GTF1 or PET112. For instance, her2/ts11 mutant showed its fermentative growth impaired, and poorly rescued by GTF1 indicating that Her2p unknown function in the mitochondria outer membrane affects cell viability.