Development of a process for the direct synthesis of hydrogen peroxide in a novel microstructured reactor

Microreactors have proven to be versatile tools for process intensification. Over recent decades, they have increasingly been used for product and process development in chemical industries. Enhanced heat and mass transfer in the reactors due to the extremely high surfacearea- to-volume ratio and interfacial area allow chemical processes to be operated at extreme conditions. Safety is improved by the small holdup volume of the reactors and effective control of pressure and temperature. Hydrogen peroxide is a powerful green oxidant that is used in a wide range of industries. Reduction and auto-oxidation of anthraquinones is currently the main process for hydrogen peroxide production. Direct synthesis is a green alternative and has potential for on-site production. However, there are two limitations: safety concerns because of the explosive gas mixture produced and low selectivity of the process. The aim of this thesis was to develop a process for direct synthesis of hydrogen peroxide utilizing microreactor technology. Experimental and numerical approaches were applied for development of the microreactor. Development of a novel microreactor was commenced by studying the hydrodynamics and mass transfer in prototype microreactor plates. The prototypes were designed and fabricated with the assistance of CFD modeling to optimize the shape and size of the microstructure. Empirical correlations for the mass transfer coefficient were derived. The pressure drop in micro T-mixers was investigated experimentally and numerically. Correlations describing the friction factor for different flow regimes were developed and predicted values were in good agreement with experimental results. Experimental studies were conducted to develop a highly active and selective catalyst with a proper form for the microreactor. Pd catalysts supported on activated carbon cloths were prepared by different treatments during the catalyst preparation. A variety of characterization methods were used for catalyst investigation. The surface chemistry of the support and the oxidation state of the metallic phase in the catalyst play important roles in catalyst activity and selectivity for the direct synthesis. The direct synthesis of hydrogen peroxide was investigated in a bench-scale continuous process using the novel microreactor developed. The microreactor was fabricated based on the hydrodynamic and mass transfer studies and provided a high interfacial area and high mass transfer coefficient. The catalysts were prepared under optimum treatment conditions. The direct synthesis was conducted at various conditions. The thesis represents a step towards a commercially viable direct synthesis. The focus is on the two main challenges: mitigating the safety problem by utilization of microprocess technology and improving the selectivity by catalyst development.

Teollinen öljyn erotus koalesenssisuodatuksella väliaineessa

Koalesenssi on ilmiö, jossa dispergoidun faasin pisarat pyrkivät muodostamaan suurempia pisaroita kunnes erotettava faasi muodostuu. Koalesenssi tapahtuu kolmessa päävaiheessa, jotka ovat lähestyminen, kiinnittyminen ja irrotus. Lähestymiseen vaikuttavat mekanismit ovat muuan muassa sieppaus, diffuusio, törmäysvaikutus, sedimentaatio, sähköiset repul-siovoimat ja van der Waalsin voimat. Kiinnittymisvaiheessa dispergoidun faasin pisarat syrjäyttävät väliaineen nestekalvon samalla kostuttaen väliaineen pinnan. Irrotusvaiheessa pisaran hydrodynaaminen voima voittaa pisaran ja väliaineen välisen adheesiovoiman. Koalesenssin tehokkuuteen vaikuttavat useat eri parametrit kuten virtausnopeus, pedin ominaisuudet, väliaineen ominaisuudet sekä emulsion ominaisuudet. Nämä kaikki asiat tulee ottaa huomioon koalesenssisuodatuksen suunnittelussa. Koalesenssisuodatus lukeutuu syväsuodatusmenetelmiin, jotka on ollut käytössä jo yli 100 vuotta. Koalesenssisuodatusmenetelmä on tehokas menetelmä pienten pisaroiden erottami-seen. Menetelmää käytetään esimerkiksi öljyisten jätevesien puhdistuksessa. Teollisen öljyn syväsuodatuksen etuihin kuuluu muun muassa sen kompakti koko, alhaisemmat käyt-tökustannukset, korkea erotusaste, kyky erotella pienetkin pisarat sekä helppo operointi, automatisointi ja huolto. Suurin haittapuoli on kuitenkin väliaineen tukkeutuminen, joten prosessi vaatii puhdistuksen tai väliaineen uusimisen. Tämän kandidaatintyön tarkoituksena oli koota kirjallisuustyö öljyn koalesenssisuodatuk-sesta. Työssä kartoitettiin koalesenssisuodatuksen lähtökohdat, teoria, tärkeimmät teolli-suuden sovellukset sekä väliaineet.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.