No description available.

This research aims at improving the tracking of phosphorus (P) in wastewater treatment works (WWTWs) by developing a model which accurately explains the intracellular processes of phosphorus accumulating organisms (PAOs). Two major models: the “Comeau-Wentzel” model (Comeau et al., 1987) and the “Mino” model (Mino et al., 1988) were developed to explain PAO intracellular processes but the failure of these models to achieve data reconciliation when modelling the anaerobic digestion of PAOs show that they are still incomplete. Ikumi and Ekama (2019) generated stoichiometry to help model PAO intracellular processes and hypothesised that an energy transfer between the activated sludge (AS) system and the anaerobic digester (AD) might take place. This research generated a steady state (SS) anaerobic digestion model (an extension of Sӧtemann et al.'s (2005) model) to model the treatment of sludge from nitrifying-denitrifying enhanced biological phosphorus removal (NDEBPR) system and assess, through data reconciliation, which of Ikumi and Ekama's (2019) stoichiometry best models PAO behaviour. The AD model generated achieved a high degree of correlation with experimental data but was unable to conclusively identify a single biochemical pathway for PAO processes.

The dependency on energy use is unavoidable in modern civilization. The burning of fossil fuels for energy use is regarded as one of the human activities that has a harmful environmental impact. Waste to energy is slowly becoming an evident argument that energy can be obtained from waste at a level that is enough to meet energy demands. Waste is viewed as a renewable source of energy and can lower emissions from the greenhouse gas (GHG) and mitigate climate change. The exploitation of municipal solid waste (MSW) can be implemented using various routes, either through thermal or biological conversion. The thermal conversion can be achieved through combustion, gasification, or pyrolysis. This study aimed to evaluate the gasification of municipal solid waste. The investigation focused on the effects the selected operating parameters have on the syngas composition, H2/CO ratio, and calorific value. The selection of the modelling approach focused on the problem statement. It was necessary to use a model that did not have a lot of limitations or relied on the geometry of the gasifier. A mathematical model that could analyse the selected operating parameters of the gasification process was utilized. A step-by-step procedure of the thermodynamic equilibrium model was implemented using MATLAB. The model was validated by comparing the predicted results of this study and empirical data in published literature. The results showed that operating parameters affected the amount of syngas quality, calorific value, and H2/CO ratio. The amount of carbon monoxide and nitrogen reduced with an increase in moisture content, and the amount of carbon dioxide increased with increased moisture content. A small amount of methane was recorded, with increased moisture content. Enhanced temperature brought about increased hydrogen while the amount of nitrogen remained constant. With high temperature, carbon dioxide composition reduced, and just over 1% of methane was recorded. The increased (ER) from 0.2 to 0.6 showed that ER has a notable impact on nitrogen. A sharp increase in nitrogen was noted when the ER increased while the amount of hydrogen and carbon monoxide decreased. Results showed acceptable agreement between the modelled data from this investigation and the experimental values reported in the literature. The overall conclusion is that the thermodynamic model gives accurate prediction results of the gasification process. Additionally, when the investigated operating parameters were adjusted, syngas composition, H2/CO ratio and calorific value were all affected (they either increased or reduced). Furthermore, it is concluded that the ER ratio is the most influential parameter in the gasification process.

No description available.

No description available.

The transport sector plays an integral role in a country's development and economy. Optimised transport networks and infrastructure can lead to increased economic development. Effective transport networks and public transportation systems are, therefore, essential to growing the South African economy. With an increasing demand for transportation services required by the South African population, the need exists to expand the capacity of local public transport networks. With this need declared, and grants released by the government, a high demand exists for the estimation, analysis, optimisation and forecast of public transport systems in South Africa. Public transportation studies are directly related to commuter demand as a result of commuter choices. Therefore, a key component for understanding the operational functionality of a public transport system lies in the accurate modelling of commuter choices. Although the spatial separation of activities forms the essence of travel demand, incorporating the effects of geospatial properties in travel behaviour modelling has only been formally studied in recent years. These recent studies noted a trend proposing that geospatial properties can influence travel behaviour. In the stated research, the need to investigate the effect of geospatial properties on travel behaviour was highlighted. With travel behaviour being the result of commuter choices, a multinomial logit choice modelling study was conducted to investigate the effect of geospatial properties on commuter destination choice for the case of the MyCiTi Integrated Rapid Transit system in Cape Town, South Africa.

Final effluent is widely recognised as a risky water source for human consumption given the organic micropollutants and pathogens it can contain. Hence, multi-barrier treatment trains and advanced processes are required. However, these are costly and therefore it is necessary to investigate how their cost can be optimized. Plumlee et al. (2014) asserted that quantifying the cost of advanced treatment processes can help compare treatment alternatives and utilities' planning. The focus of the current study has been the cost optimisation of treatment processes in the treatment train of the Managed Aquifer Recharge (MAR) scheme of the Cape Flats Aquifer, one of the new bulk water schemes that originated out of the Cape Town drought peak during the period spanning between 2015–2017. It is an indirect potable reuse scheme that consists in injecting advanced treated final effluent from the Cape Flats MAR WRP into the Cape Flats Aquifer. Within the Cape Flats MAR WRP is the O3/BAC process, which is one of the advanced treatment processes at the facility. This process is essential given its ability to remove pathogens and organic micropollutants, i.e. it doubles as a disinfection step and an organic micropollutant removal step. However, the downside of the O3/BAC process is its costs, particularly its capital and operating costs given the many variables affecting the removal efficiencies, and hence, the costs. Among these variables are the treatment objectives, energy usage and liquid oxygen usage. The main factors impacting the removal efficiency are the water quality (O3 decay and instantaneous ozone demand [IOD]) and contact time. Therefore, the challenge is to carefully optimise the process without influencing the treatment objectives. In light of this, the main research question that the current study tries to answer is about the optimum cost of the O3/BAC filtration process for various treatment objectives to help produce safe drinking water in a treatment train. The aim of the current research is to study the interdependencies between the varying treatment objectives, the optimum operating conditions, and the efficiency of the O3/BAC process to inactivate pathogens and remove organic micropollutants. The optimisation focusses on the filtered secondary effluent of the Cape Flats Wastewater Treatment Works (WWTW) with the aim to produce safe drinking water. The research uses the O3 process assessment methods, i.e. the T10 method and CSTR methods, and the O3/TOC dose ratio as the main parameters to compare and relate the treatment objectives and the assessment methods with one another. The use of the O3/TOC dose ratio is motivated by the findings of Snyder et al. (2014), which stated that the O3/TOC dose ratio produces similar treatment results, particularly oxidation, even with high variations in water quality. Gamage et al. (2013) also asserted that the O3/TOC dose ratio relates the O3 dose required for disinfection and the O3 dose required for organic micropollutants oxidation. On one hand, the CT-value (product of residual O3 concentration and contact time) guarantees that the O3 process achieves its objectives concerning the removal of pathogens. On the other hand, the O3/TOC dose ratio together with each pollutants O3 and hydroxyl radical second-order reaction rates, kO3 and kOH, allow the quantification of the removal of organic micropollutants. Additionally, the current research uses capital and operation and maintenance (O&M) costing models, including process performance regression models, applied to various treatment objectives of the O3/BAC filtration process and to organic micropollutants found in the Cape Flats WWTW final effluent. The current study finds that the O3/BAC process of the Cape Flats MAR WRP can theoretically reduce more than 87% of the organic micropollutants in the Cape Flats WWTW final effluent, taking it from medium risk to low risk. The optimum contact time, in terms of cost for 2–4 Log virus inactivation by ozone and 1–3 Log giardia inactivation by ozone, is between 5–7 minutes as determined by the CSTR method, and it is 5 minutes as determined by the T10 method. The optimum contact time, in terms of cost for 1–3 log inactivation of cryptosporidium by ozone, is between 8–18 minutes for the CSTR method and between 6–13 minutes for the T10 method depending on the treatment objective and O3 transfer efficiency. No apparent correlations between international concept costing models and actual Southern African O3/BAC project costs were evident. The process assessment method, i.e. T10 or CSTR, affects the cost of the process and the performance objective that can be validated. Hence, the treatment of filtered final effluent by the O3/BAC process can be optimized for specific treatment objectives to produce safe drinking.

No description available.

Bioethanol production through fermentation of sugarcane juice and its derivatives such as molasses is gaining popularity worldwide as focus shifts towards renewable energy production. However, ethanol fermentation results in the production of large volumes of a dark brown and low pH liquid waste termed vinasse. At a vinasse production rate of 12-15 liters per liter of ethanol, sustainability of this bioprocess is impacted as effluent handling costs are high. If disposed onto the land, breakdown of the organic matter within may lead to the release of greenhouse gases into the atmosphere. Additionally, disposal into water bodies results in eutrophication due to the overload of plant nutrients (N, P and K). Further, owing to the high potassium content, the use of dewatered vinasse as animal feed supplements has been shown to cause digestive tract problems in ruminants depending on the supplementation rates (>10%). To increase sustainability of bioethanol fermentation processes through combined treatment and resource recovery from vinasse, biological and physico-chemical processes have been developed and implemented in industry. Conventionally, raw vinasse is dewatered through evaporation processes (MEE) as a means of volume reduction. Membrane processes such as reverse osmosis (RO) have in the recent past become popularized as water recovery options from vinasse due to process simplicity and lower costs of equipment. Resulting concentrates from RO and MEE can be used as fertilizer. Due to the high organic content, vinasse is a suitable candidate for anaerobic digestion (AD) where the organic matter is broken down to biogas and an effluent that can be safely used as fertilizer. Additionally, the biogas from AD may be harnessed for electricity generation through combined heat and power processes or upgraded to biomethane to be used as a substitute for natural gas. For high moisture content substrates such as vinasse, up flow anaerobic sludge blanket reactors are best suited as sludge residence time is prolonged thereby increasing contact time with substrate which leading to higher methane yields. AD is often sensitive to changes in temperature, substrate composition, loading rate and pH. The presence of inhibitory components such as potassium salt ions (>11.6 g/L) in the vinasse feed result in a reduction of methanogenic activity manifested through reduced biogas and methane yields. Salt recovery processes including electrodialysis and ion-exchange have been investigated in literature on a pilot scale for the removal of K+ ions from raw vinasse. To improve resource productivity, integration of vinasse treatment processes has been implemented in industry. Integration combines biological and physico-chemical processes which results in performance optimization and energy efficiency thereby improving economic feasibility of the projects. During the project conceptualization phase, process modelling is a vital tool that can be used to predict outcomes such as substrate utilization rates, product yields and optimal operating conditions of integrated processes in a timely and cost effective manner. In addition, techno-economic analyses can be used to determine cost sensitive areas and overall feasibility of the integrated processes. Having reviewed the current industrial practices, this project sought to develop integrated flowsheets consisting of biological and physical processes for the combined vinasse treatment and value creation. Value creation was demonstrated through the recovery of valuable products including energy, salts and water from the raw vinasse. Due to its simplicity and cost effectiveness, AD was selected as the primary technology for vinasse treatment and biogas production. This was coupled with a combined heat and power system for electricity generation to form the base case flowsheet. It was hypothesized that incorporation of pre- and post-treatment as well as alternative biogas utilization processes to the base case flowsheet for recovery of salts and water would generate additional revenue and cost savings. Profitability of the base case process was expected to increase with the additional pre- and post-treatments. To fulfil the objective set out and prove the hypothesis, a three step research approach was taken. The first step involved simulation and benchmarking of the base case flowsheet (AD and CHP). Using techno-economic analyses, the effect of individual addition of pre- and post-treatment options to the base case flowsheet on profitability was investigated. A framework was then developed to investigate the incorporation of combined pre- and posttreatment options to the base case flowsheet. Thereafter, a decision support tool that in comparing various combinations of vinasse treatment routes in terms of process performance and profitability was developed to aid in the synthesis of vinasse treatment processes in industry. As bioprocess modelling is complex, it was important to select an appropriate simulation platform. Given the availability of a dedicated bioprocess compound database, sensitivity and optimization features and flexible customization options within Aspen Plus, it was preferred as the primary simulation platform over SuperPro Designer and high performance programming languages (C++, Java). In developing the base case AD flowsheet, several frameworks in the literature were considered. These included ADM1 (Batstone et al., 2002), ADM-3P (Ikumi et al., 2011) and a comprehensive model by Angelidaki et al. (1993). The presence of a well defined stoichiometric framework motivated the decision to adopt the comprehensive model by Angelidaki et al. (1993). Using a combination of in-built unit operations as well as customized user models (calculator blocks), the AD model by Angelidaki et al. (1993) was implemented on Aspen Plus. As ADM1 was considered an extension of the comprehensive model (Angelidaki et al., 1993) with several similarities, kinetic constants describing substrate uptake and microbial growth were adapted from ADM1. To ascertain the predictive quality of the built AD model, four case studies in the literature concerning the AD of manure (cow and swine) and municipal solid waste were simulated and the predicted simulation results compared to the experimental results. The developed AD model accurately predicted the methane yields of the four case studies as evidenced by the average difference of 10% between simulation and experimental results. A regression analysis between experimental and predicted data yielded a value of 0.74. Given the assumptions made in simplifying the developed model, the R2 value was deemed acceptable and further affirmed the agreement between the model and experimental results. To investigate the robustness of the developed AD model, sensitivity analyses on the feed composition as well as organic loading were conducted. Increasing inhibitory compound concentrations above certain thresholds was shown to negatively impact methanogenic activity as evidenced by the decreasing methane yields. Although ammonia is inhibitory at concentrations above 0.22 g/L, it is an important nitrogen source for biomass growth. Similarly, while acetic acid is inhibitory to acetogenic microbes, it is a crucial substrate for the growth of methanogenic archaea and methane production. Inorganic salt inhibition on the other hand may be reduced through extraction of K2SO4 through pre-treatment processes. The compositional sensitivity analyses as well as the benchmarking study showed that the built AD model had a solid core framework which accurately predicted experimental data for a range of substrates. Combined with a simplified CHP model of a Jenbacher spark ignition engine (General Electric, 2008) to form the base case flowsheet, the built AD model was used for all further simulations in this work. To determine the financial standing of the base case, simulation and subsequent techno-economic analyses were conducted. At an industrial reactor capacity of 2000 m3 and a loading rate of 25 kgCOD/m3 .day, simulation of the base case process resulted in a methane yield of 45 L-CH4/kgVSadded and an electrical production capacity of 410 kW. Discounted cash flow analyses (USD, 2016) showed that the base case was not profitable within a 20-year project lifetime as evidenced by the low return on investment and internal rate of return. However, a further sensitivity on profitability of the base case showed that decreasing potassium ion concentrations in the feed would result in higher profitability higher methane yields because of decreased K+ inhibition. Despite the positive effect of on AD performance, further analyses were required to validate feasibility of K2SO4 recovery processes as well as water recovery processes aimed at further value creation from vinasse. To investigate the effect of pre-treatment on base case flowsheet economics, an ion exchange process adapted from Zhang et al. (2012) was incorporated based on the comparatively higher degree of selectivity to K+ ions exhibited by the ion exchange process than ozonation and electrodialysis. As expected, improved CH4 yields (14%), electrical production and consequently, increases (>100%) in profitability indicators were observed. However, the pretreated base case (IEX-AD-CHP) remained unprofitable which was an indication that the marginal revenue from increased electrical production and K2SO4 sales did not match the additional capital costs. To increase profitability of the base case, biogas upgrading using a HPWS system was used in place of the CHP. Due to the comparatively low cost of HPWS equipment coupled with the increased revenue from biomethane sales, the AD-HPWS process exhibited higher profitability (ROI: 19.6%) than the base case (ROI: 0%). As evidenced by the IRR (16.3%) that was greater than the cost of capital (15%), the AD-HPWS option was profitable over a 20 year lifetime. Resource recovery from the AD effluent was sought through incorporation of RO and MEE to form the AD-CHP-RO and AD-CHP-MEE routes. Most notably, there was a significant (170%) increase in cost savings with the use of RO and MEE concentrates as fertilizer compared to the raw AD effluent from the base case. Additional cost savings of up to $27 700 were achieved with upstream reintegration of RO permeate or MEE condensate water. This savings was based on the municipal water tariff of R5/kL. The combined cost savings led to increased profitability of the base case as evidenced by the increase in ROI from 0% to 3%. Potential knock-on effects of pre-treatments on efficiency of post-treatment or biogas utilization processes were noted. These were investigated through the simultaneous addition of pre- and post-treatment combinations to the base case AD process to form a decision making framework. Through techno-economic comparisons drawn between the 12 distinct vinasse treatment routes resulting from various combinations of pre- and post-treatment options in the decision making framework, three major decision criteria were established. Despite the improved performance and methane yields observed with pre-treatment addition, there was a decline in profitability of the AD-HPWS-RO/MEE processes owing to increased capital costs that remain unrecovered by marginal revenue obtained from biomethane sales. The contrary is observed with the AD-CHP-RO/MEE processes as evidenced by the 20 to 30% increase in profitability indicators upon addition of pre-treatment. This is attributed to the marginal revenues from increased electrical output as well as the cost savings from water reuse and RO/MEE concentrates. Due to the contrasting effect of pre-treatment on CHP and HPWS affiliated processes and profitability, the presence of inhibitory potassium ions was considered a decision criterion. Due to the low cost of HPWS equipment, it was observed that choosing to upgrade biogas to biomethane as opposed to using CHP exhibited higher performance (energy output) and profitability in all process combinations. This was evidenced by the higher ROI and IRR of the AD-HPWS, AD-HPWS-RO/MEE and IEX-AD-HPWS-RO/MEE process options compared to the CHP counterparts. As a result, the choice of biogas utilization was considered an important decision criterion affecting profitability. Because of increased cost savings with upstream reintegration of water and the use of concentrates as fertilizer, the implementation of RO and MEE was observed to increase profitability of all process options including AD-CHP/HPWS and IEX-AD-CHP/HPWS. This was majorly through cost savings from use of RO and MEE concentrates as fertilizer ($250 000/yr) and upstream reintegration of water. This led to the conclusion that the recovery of concentrates from vinasse is an important decision criterion when looking to increase profitability and process sustainability. Overall, based on the techno-economic analyses, the most profitable vinasse treatment process included an anaerobic digester coupled with a high-pressure water scrubbing system for biomethane production and reverse osmosis process for water recovery (ROI: 22.9%, NPV: $540 000). This facilitated both increased energy output from biomethane and cost savings from water reuse. Further research is recommended around the AD modelling aspect to extend functionality to ionic speciation and pH prediction. it is recommended that equipment quotes from suppliers within South Africa be sourced as opposed to costing heuristics in the literature to increase the accuracy of capital and operating expenditure.

Deep Vein Thrombosis (DVT) is the formation of a blood clot in a vein, usually in the body's lower extremities. If untreated, DVT can lead to pulmonary embolism (PE), heart attack and/or stroke, which can be fatal. According to literature, DVT affects 0.2% of people in developed countries and about 0.3%-1% in developing countries. In the past, various computational models of DVT were developed. Most models account for either the mechanical factors or biochemical factors involved with DVT. Developing a model that accounts for both factors will improve our understanding of the coagulation process. This study developed a three-dimensional DVT computational model in idealized and realistic common femoral vein (CFV) geometries. The model considers the biochemical reactions between thrombin and fibrinogen, pulsatile blood flow, and clot growth within the vessel. The model was validated using a simplified experimental setup with flow, thrombin, and fibrinogen. Computational fluid dynamics (CFD) simulations were carried out using the ANSYS modelling suite. The Navier-Stokes equations were solved to determine the fluid flow. Based on a clinical dataset of pulsatile blood flow, the laminar flow of blood with a Poiseuille velocity profile was applied at the inlet. Darcy's law was used to account for porosity changes in the clot, with the clot represented by zones with lower porosities. The transport equations were used for changes in the concentration of the biochemical protein species. Thrombin was released into the bloodstream from an injury zone on the wall of the vein. The Michaelis-Menten equation was used to represent the conversion of thrombin and fibrinogen to fibrin, the final product of the coagulation process. The computational model solves the blood flow pattern proximally, locally, and distally to clot formation at the injury zone. The model also predicts the size of the clot and the rate of clot growth. The model was first developed in a two-dimensional geometry. This model was used to investigate clot formation under different cases comparing how introducing thrombin as a flux value differs from specifying it as a fixed concentration. It was confirmed that to apply the flux condition, the thrombin concentration needs to be divided by a factor derived by multiplying the area of the injury zone and the time step size. The same model was then used to conduct a parametric study to determine the effects of varying parameters such as inlet velocity, vein diameter, and peak thrombin concentration on the size and shape of clot formed. Peak thrombin concentration was the key factor driving the initiation and propagation of clot in the vein. The model was then extended to an idealized three-dimensional geometry. This computational model was validated using results from an experimental clot growth study. The experiment comprised a steady flow of fibrinogen in a cylindrical pipe, with an injection of thrombin into the flow at the injury site, resulting in fibrin formation. A qualitative comparison was then made between the experimental clot and the clot formed in silico. Although quantitative measurements were not made, there were similarities in the shapes and sizes of the clots. The validated computational model was used to compare clot formation under steady and pulsatile flow conditions. Realistic clot growth was observed and compared to the steady flow condition. It was found that a larger clot formed under pulsatile conditions. Clot formation with the presence of valve activity was also investigated. The effect of opening and closing of the valves was achieved by varying the blood flow diameter at the inlet instead of modelling the valves as solid walls and accounting for the leaflet movement by solving the governing equations for the fluid-solid interaction (FSI), as used in existing models. The model was then applied to a patient-specific geometry. Realistic clot growth was achieved using this model, and the clot was compared to a clot formed in vivo, as depicted in the original imaging scan. The model helps us better understand the clot growth process in the femoral vein on a patient-specific level. It also shows that the presence of venous valves increases the size of clot formed compared to steady flow. However, the high strain rate present makes the clot formed smaller than in standard pulsatile flow cases.