Current prices and demand for petroleum hydrocabons have generated an increase of oil spills around the country and the world. Health and environmental impacts associated to these organic pollutants represent a huge concern for the general public, leading the public and private sector to develop new technologies and methods to minimize or eliminate those risks. Ex-Situ bioremediation through biopiles, as a main remediation technique to treat a wide range of hydrocarbons, has been a topic of considerable research interest over the last years. It provides an economical and environmental solution to restore the environment to background levels. Nevertheless, successful bioremediation under cold climate conditions is of considerable concern in countries like Canada, as low temperatures can delay the rate of bioremediation of oil hydrocarbons, thus limiting the operation of soil treatment facilities to certain times of the year. Recent research has found out that bioremediation could be conducted even at low or cold temperatures with larger periods of times. And even more, the addition of petroleum degrading microorganisms (bioaugmentation) and nutrients or biosurfactants (biostimulation) could enhance the process in some cases. In the present study, a comprehensive assessment of bioaugmentation and biostimulation strategies for ex-situ bioremediation of petroleum contaminated soil under cold climate conditions is proposed. Field scale biopiles were constructed and subjected to different concentrations of commercial microbial consortia and mature compost, as bioaugmentation and biostimulation strategies, in a soil treatment facility at Moose Creek, Ontario over a period of 94 days (November 2012 to February 2013). Assessment and comparison of the biodegradation rates of total petroleum hydrocarbons (TPH) and their fractions were investigated. Furthermore, a response surface methodology (RSM) based on a factorial design to investigate and optimize the effects of the microbial consortia application rate and amount of compost on the TPH removal was also assessed. Results showed that biopiles inoculated with microbial consortia and amended with 10:1 soil to compost ratio under aerobic conditions performed the best, degrading 82% of total petroleum hydrocarbons (TPHs) with a first-order kinetic degradation rate of 0.016 d_1, under cold temperature conditions. The average removal efficiencies for TPHs after 94 days for control biopiles, with no amendments or with microbial consortia or compost only treatments were 48%, 55%, and 52%, respectively. Statistical analyses indicated a significant difference (p < 0.05) within and between the final measurements for TPHs and a significant difference between the treatment with combined effect, and the control biopiles. On the other hand, the modeling and optimization statistical analysis of the results showed that the microbial consortia application rate, compost amendment and their interactions have a significant effect on TPHs removal with a coefficient of determination (R2) of 0.88, indicating a high correlation between the observed and the predicted values for the model obtained. The optimum concentrations predicted via RSM were 4.1 ml m-3 for microbial consortia application rate, and 7% for compost amendment to obtain a maximum TPH removal of 90.7%. This research contributes to provide valuable knowledge to practitioners about cost-effective and existing strategies for ex-situ bioremediation under cold weather conditions.

This research proposes a novel Retrofit Design Approach based on process simulation and the Response Surface Methodology (RSM).Retrofit Design Approach comprises: 1) a diagnosis stage in which the variables are screened and promising variables to improve system performance are identified through a sensitivity analysis, 2) an evaluation stage in which RSM is applied to assess the impact of those promising variables and the most important factors are determined by building a reduced model from the process response behaviour, and 3) an optimisation stage to identify optimal conditions and performance of the system, subject to objective function and model constraints. All these stages are simulation-supported. The main advantages of the proposed Retrofit Design Approach using RSM are that the design method is able to handle a large industrial-scale design problem within a reasonable computational effort, to obtain valuable conceptual insights of design interactions and economic trade-off existed in the system, as well as to systematically identify cost-effective solutions by optimizing the reduced model based on the most important factors. This simplifies the pathway to achieve pseudo-optimal solutions, and simultaneously to understand techno-economic and system-wide impacts of key design variables and parameters. In order to demonstrate the applicability and robustness of the proposed design method, the proposed Retrofit Design Approach has been applied to two case studies which are based on existing gas processing processes. Steady-state process simulation using Aspen Plus TM® has been carried out and the simulation results agree well with the plant data. Reduced models for both cases studies have been obtained to represent the techno-economic behaviour of plants. Both the continuous and discrete design options are considered in the retrofitting of the plant, and the results showed that the Retrofit Design Approach is effective to provide reliable, cost-effective retrofit solutions which yield to improvements in the studied processes, not only economically (i.e. cost and product recovery), but also environmentally linked (i.e. CO₂ emissions and energy efficiency). The main retrofitting solutions identified are, for the first case, column pressure change, pump-around arrangement and additional turbo-expansion capacity, while for the second case, columns pressure change, trays efficiency, HEN retrofit arrangements (re-piping) and onsite utility generation schemes are considered. These promising sets of retrofit design options were further investigated to reflect implications of capital investment for the retrofit scenarios, and this portfolio of opportunities can be very useful for supporting decision-making procedure in practice. It is important to note that in some cases a cost-effective retrofit does not always require structural modifications. In conclusion, the proposed Retrofit Design Approach has been found to be a reliable approach to address the retrofit problem in the context of industrial applications.

Orientador: Roy Edward Bruns / Dissertação (mestrado profissional) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-18T11:44:59Z (GMT). No. of bitstreams: 1 Rodrigues_MarlonCasagrande_M.pdf: 2084739 bytes, checksum: 4206c434cf21dfc145d73ca304a9981b (MD5) Previous issue date: 2011 / Resumo: Nos últimos anos a emissão de ruído tem sido decisiva para aceitação de veículos no mercado, não somente devido a legislação, mas também no que diz respeito a satisfação do cliente. Por este motivo as empresas fabricantes de veículos e ou motores de combustão interna tem sido obrigadas a dar uma atenção especial as emissões de ruído para poderem competir com suas concorrentes. Neste trabalho realizou-se estudo da influencia dos parâmetros de injeção de combustível do motor MWM 6.12 TCE no nível de ruído emitido pelo motor Diesel na condição de marcha lenta, por meio da técnica de planejamento multivariado de experimentos. Foram escolhidas duas técnicas de medição indireta de ruído (ruído de combustão e aceleração na saia do bloco) para serem utilizadas como variável resposta do planejamento de experimentos. Para verificação da eficácia dos planejamentos realizou-se ensaios qualitativos e quantitativos de ruído propriamente dito. Foi feito um planejamento fatorial fracionário 28-4 para fazer uma triagem de oito fatores de acordo com seus efeitos nas respostas aceleração na saia do bloco e ruído de combustão. Os fatores com efeitos mais significativos, pressão do rail, ponto de injeção principal, ponto de pré-injeção 2 e debito da pré-injeção 2, foram investigados usando um planejamento composto central e superfícies de respostas foram determinadas para cada uma das respostas. Os resultados mostraram que apenas a variável resposta vibração na saia do bloco apresentou resultados satisfatórios para esta condição especifica do motor tanto nos testes quantitativos como qualitativos (redução de 2 dB e melhora na qualidade sonora respectivamente). Apos verificação da influencia dos parâmetros de injeção no ruído emitido verificou-se também a influencia destas alterações no consumo de combustível e emissões dos gases de escape e foi observado que existem influencias significativas nas emissões dos gases de escape / Abstract: In recent years the noise level has been decisive for acceptance of vehicles on the market, not only because of legislation but also with regard to customer satisfaction. For this reason the manufacturers of vehicles and internal combustion engines have been forced to give special attention to the emission of noise to compete with their competitors. In this work, the influences of fuel injection parameters on the noise level of the MWM 6.12 TCE diesel engine emitted under low idle condition were determined using multivariate statistical design of experiments. Two techniques for the indirect measurement of noise, combustion noise and engine crankcase vibration, were chosen as the response variables for the experimental design. To check design effectiveness both qualitative and quantitative noise measurements were carried out. A 28-4 fractional factorial design was performed to screen eight factors according to their effects on engine crankcase vibration, and combustion noise. The factors with the most significant effects, rail pressure, pre-injection point, main injection point and the pre-injection delivery, were investigated using a central composite design and response surfaces were determined for each response. The results showed that only the engine crankcase vibration showed satisfactory results for this particular engine condition in both the quantitative and qualitative analyses (reduction of 2 dB and an improvement in sound quality, respectively). After verification of the influences of the injection parameters on the noise the influences of these changes on fuel consumption and exhaust emissions were also analyzed. Significant influences were observed on the exhaust gas emissions / Mestrado / Projetos / Mestre em Engenharia Automobilistica

The objective of this study is to identify the optimal designs of converging-diverging supersonic and hypersonic nozzles that perform at maximum uniformity of thermodynamic and flow-field properties with respect to their average values at the nozzle exit. Since this is a multi-objective design optimization problem, the design variables used are parameters defining the shape of the nozzle. This work presents how variation of such parameters can influence the nozzle exit flow non-uniformities. A Computational Fluid Dynamics (CFD) software package, ANSYS FLUENT, was used to simulate the compressible, viscous gas flow-field in forty nozzle shapes, including the heat transfer analysis. The results of two turbulence models, k-e and k-ω, were computed and compared. With the analysis results obtained, the Response Surface Methodology (RSM) was applied for the purpose of performing a multi-objective optimization. The optimization was performed with ModeFrontier software package using Kriging and Radial Basis Functions (RBF) response surfaces. Final Pareto optimal nozzle shapes were then analyzed with ANSYS FLUENT to confirm the accuracy of the optimization process.

No description available.

Biological sulphate reduction (BSR) has been identified as a promising alternative technology for the treatment of acid mine drainage. BSR is a process that uses sulphate reducing bacteria to reduce sulphate to sulphide using substrates as nutrients under anaerobic conditions. The performance of BSR is dependent on several factors including substrate, pH, temperature and hydraulic retention time (HRT). In a quest to find a cost effective technology, Mintek conducted bench-scale tests on BSR that led to the commissioning of a pilot plant at a coal mine in Mpumalanga province, South Africa. This current study forms part of the ongoing tests that are conducted to improve Mintek’s process. The purpose of this study was to investigate the robustness of Mintek’s process and to develop a tool that can be used to predict the process’ performance with varying pH, temperature and HRT. Design Expert version 11.1.2.0 was used to design the experiments using the Box-Behnken design. In the design, pH ranged from 4 to 6, temperature from 10 °C to 30 °C and HRT from 2 d to 7 d with sulphate reduction efficiency, sulphate reduction rate and sulphide production as response variables. Experiments were carried out in water jacketed packed bed reactors that were operated in a down-flow mode. The reactors were packed with woodchips, wood shaving, hay, lucerne straw and cow manure as support for sulphate reducing bacteria (SRB) biofilm. Cow manure and lucerne pellets were used as the main substrates and they were replenished once a week. These reactors mimicked the pilot plant. The data obtained were statistically analysed using response surface methodology. The results showed that pH did not have a significant impact on the responses (p>0.05). Temperature and HRT, on the other hand, greatly impacted the process (p<0.05) and the interaction between these two factors was found to be strong. Sulphate reduction efficiency and sulphate reduction rate decreased by over 60 % with a decrease in temperature 30 °C to 10 °C. Generally, a decrease in sulphide production was observed with a decrease in temperature. Overall, a decrease in HRT resulted in a decline of sulphate reduction efficiency and sulphide production but favoured sulphate reduction rate. This study demonstrated that Mintek’s process can be operated at pH as low as 4 without any significant impact on the performance. This decreases the lime requirements and sludge production during the pre-neutralisation stage by close to 50 %. There was, however, a strong interaction between temperature and HRT which can be used to improve the performance especially during the winter season. / Dissertation (MEng)--University of Pretoria, 2020. / Chemical Engineering / MEng / Unrestricted

In today's competitive manufacturing industries, companies strive to reduce manufacturing development costs and lead times in hopes of reducing costs and capturing more market share from early release of their new or redesigned products. Tooling lead time constraints are some of the more significant challenges facing product development of advanced free-form components. This is especially true for complex designs in which large dies, molds or other large forming tools are required. The lead time for tooling, in general, consists of three main components; material acquisition, tool design and engineering, and tool manufacturing. Lead times for material acquisition and tool manufacture are normally a function of vendor/outsourcing constraints, manufacturing techniques and complexity of tooling being produced. The tool design and engineering component is a function of available manpower, engineering expertise, type of design problem (initial design or redesign of tooling), and complexity of the design problem. To reduce the tool design/engineering lead time, many engineering groups have implemented Computer-Aided Design, Engineering, and Manufacturing (CAD/CAE/CAM or CAx) tools as their standard practice for the design and analysis of their products. Although the predictive capabilities are efficient, using CAx tools to expedite advanced die design is time consuming due to the free-form nature and complexity of the desired part geometry. Design iterations can consume large quantities of time and money, thus driving profit margins down or even being infeasible from a cost and schedule standpoint. Any savings based on a reduction in time are desired so long as quality is not sacrificed. This thesis presents an automated tool design methodology that integrates state-of-the-art numerical surface fitting methods with commercially available CAD/CAE/CAM technologies and optimization software. The intent is to virtually create tooling wherein work-piece geometries have been optimized producing products that capture accurate design intent. Results show a significant reduction in design/engineering tool development time. This is due to the integration and automation of associative tooling surfaces automatically derived from the known final design intent geometry. Because this approach extends commercially available CAx tools, this thesis can be used as a blueprint for any automotive or aerospace tooling need to eliminate significant time and costs from the manufacture of complex free-form components.

Impaired reproduction studies with Poisson responses are among a growing class of toxicity studies in the biological and medical realm. In recent years, little effort has been focused on the development of efficient experimental designs for impaired reproduction studies. This research concentrates on two areas: 1) the use of Bayesian techniques to make single regressor designs robust to parameter misspecification and 2) the extension of design optimality methods to the k-regressor model. The standard Poisson model with log link is used. Bayesian designs with priors on the parameters are explored using both the D and F-optimality criteria for the single regressor Poisson exponential model. Since these designs are found via numeric optimization techniques, Bayesian equivalence theory functions are derived to verify the optimality of these designs. Efficient Bayesian designs which provide for lack-of-fit testing are discussed. Characterizations of D, D_s, and interaction optimal designs which are factorial in nature are demonstrated for models involving interaction through k factors. The optimality of these designs is verified using equivalence theory. In addition, augmentations of these designs that result in desirable lack of fit properties are discussed. Also, a structure for fractional factorials is given in which specific points are added one at a time to the main effect design in order to gain estimability of the desired interactions. Robustness properties are addressed as well. Finally, this entire line of research is extended to industrial exponential models where different regressors work to increase and/or decrease a count data response produced by a process. / Ph. D.

Yes / This paper investigates the coupled effect of functionalized multiwall carbon nanotubes (MWCNTs-COOH), nanomontmorillonite (NM), and sodium dodecyl benzene sulfonate (SDBS) anionic surfactant on compressive and flexural strengths of cement paste. The response surface methodology (RSM) was used to optimize the content of the two nanomaterials and surfactant, and to analyze the effect of their interactions on mechanical properties and microstructural characteristics of the paste. Test results indicate that the simultaneous use of NM and MWCNT can lead to 30% gain in compressive strength and 40% increase in flexural strength. Using analysis of variance, it was possible to predict the optimal weight percentage of nanomaterials. Atomic Force Microscope observations showed that the use of NM and MWCNT can reduce the surface roughness of cement paste and refine porosity, thus reducing the risk of cracking at the cement matrix and improving the homogeneity of the microstructure.

Crystallisation is gaining a lot of interest in pharmaceutical industry to help designing active ingredients with tailored physicochemical properties. Many factors have been found to affect the crystallisation process, including process parameters and material attributes. Several studies in the literature have discussed the role of these parameters in the crystallisation process. A comprehensive study is still missing in this field where all the significant terms are taken into consideration, including the square effect and the interaction terms between different parameters. In this study, a thorough investigation into the main factors affecting crystallisation of a polymeric system, processed via injection moulding, was presented and a sample of response optimisation was introduced which can be mimicked to suite a specific need. Three grades of pure polyethylene oxide; 20K, 200K and 2M, were first characterised using differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), powder X-ray diffraction (PXRD) and shear rheometry. The onset of degradation and the rate varied according to molecular weight of polyethylene oxide (PEO). The peak melting temperature and the difference in enthalpy between melting and crystallisation were both in a direct proportion with PEO molecular weight. PEO200K and PEO2M struggle to recrystallise to the same extent of the original state at the tested cooling rates, while PEO20K can retain up to a similar crystallinity degree when cooled at 1 °C/min. Onset of crystallisation temperature (Tc1) was high for PEO2M and the difference between the 20K and 200K were pronounced at low cooling rate (20K is higher than 200K). The rheometer study showed that PEO2M has a solid-like structure around melting point which explains the difficulty in processing this grade at a low temperature via IM. PEO20K was almost stable within the strain values studied (Newtonian behaviour). For higher grades, PEO showed a shear thinning behaviour. The complex viscosity for PEO2M is characterised by a steeper slope compared to PEO200K, which indicates higher shear thinning sensitivity due to higher entanglement of the longer chains. For binary blends of PEO, the enthalpy of crystallisation studied by DSC was in direct proportion to the lowest molecular weight PEO content (PEOL %) in PEO20K/200K and PEO20K/2M blends. The effect of PEOL% on Tc1 became slightly pronounced for PEO20K-2M blends where Tc1 exhibited slight inverse proportionality to PEOL% and it became more significant for PEO200K-2M blends. It was interesting to find that Tc1 for the blends did not necessarily lie between the values of the homopolymers. In all binary blends, Tc1 was inversely proportional to cooling rate for the set of cooling rates tested. Thermal analysis using hot stage polarised light microscopy yields different behaviours of various PEO grades against the first detection of crystals especially where the lowest grade showed highest detection temperature. Visual observation of PEO binary blends caplets processed at various conditions via injection moulding (IM) showed the low-quality caplets processed at mould temperature above Tc1 of the sample. The factors affecting crystallisation of injection moulded caplets were studied using response surface methodology for two responses; peak melting temperature (Tm) and relative change in crystallinity (∆Xc%) compared to an unprocessed sample. Mould temperature (Tmould) was the most significant factor in all binary blend models. The relationship between Tmould and the two responses was positive non-linear at the Tmould ˂ Tc1. Injection speed was also a significant factor for both responses in PEO20K-200K blends. For Tm, the injection speed had a positive linear relationship while the opposite trend was found for ∆Xc%. The interaction term found in the RSM study for all models was only between the injection speed and the PEOL % which shows the couple effect between these two factors. Molecular effect was considered a significant factor in all ∆Xc% models across the three binary blends. The order of ∆Xc% sensitivity to the change in PEOL% was 3, 5 and 7 % for 20K-200K, 200K-2M and 20K-2M.