Preserving road network requires a coordinated approach for good performance and efficient movement of goods and services. The road construction materials and design have great influence on future road conditions and maintenance scenarios. Weather changes and increase in traffic loads have exposed pavements to major distresses such as rutting, potholes, fatigue cracking, and temperature cracking. These forms of pavement failure cause traffic congestion, loss of man hour, increase in wear and tear of the vehicle and increase in road accidents. There is loss of money in frequent road repairs, vehicle repairs and treatment to the injured persons. Therefore, there is need to increase the load-bearing capacities of road pavements. The aim of this study was to investigate the performance of sisal-plastic modified asphalt concrete for road pavements. The properties of modified gap graded asphalt concrete was evaluated through characterization of asphalt concrete mixes modified using sisal fibre and waste plastics. Sisal fibre and plastic wastes were used as asphalt concrete stabilizers and modifiers respectively to enhance stability against bitumen drain down, bleeding and cracking. Clean waste plastics were cut into small sizes so as to pass through 2-3 mm sieve using shredding machine. The aggregate used in preparation of gap graded asphalt (GGA) were sizes 20-6mm for stone matrix asphalt (SMA) concrete and 12-6mm for open graded asphalt (OGA) concrete. The respective aggregate mix was heated and the waste plastics effectively coated over the aggregate. Sisal fibre was cut into 5 mm long threads, treated using sodium hydroxide solution and mixed with hot bitumen. The waste plastic coated aggregate was mixed with the mixture of treated sisal fibre and bitumen. Sisal fibre treated in 0.5N solution of sodium hydroxide makes sisal fibre become less porous with high density thus making more rigid asphalt concrete mix. The treatment improves the adhesion due to increase in surface tension and surface roughness. The asphalt concrete mix samples were analyzed for various engineering properties to assess their suitability for road pavement construction. The samples were subjected to different performance tests, namely, Marshall Test, drain down test and indirect tensile strength test. Using the Marshall procedure, the optimum additive contents were determined as 0.3% for sisal fibre and 5% for waste plastics in asphalt concrete mixes respectively. The Optimum Binder Content (OBC) values determined were 5.5% and 6.5% for open graded asphalt (OGA) and stone matrix asphalt (SMA) respectively. The stability test result values for both gap graded asphalt (GGA) concrete were 11.8kN and 12.8kN when modified with sisal fibre and waste plastics respectively. However, when sisal and plastics were both used, the stability values recorded were 13.6kN and 12.9kN for sisal-plastic modified OGA and sisal-plastic modified SMA respectively. The tensile strength test value determined was 1.23MPa for both sisal-plastic modified gap graded asphalt concrete. The tensile strength ratio was 99.9% while bitumen drain down value determined was 0% for both sisal-plastic modified gap graded asphalt concrete. A mathematical model was developed to predict the tensile strength of sisal-plastic modified asphalt concrete. The model was found to be adequate with 97.5% confidence level. A model road pavement consisting of control section and sisal-plastic modified were constructed. There was no bleeding, rutting, cracking or aggregate loss observed on modified

Admixtures are used to improve the properties of concrete or mortar to make them more suitable to work by hand or for other purposes such as saving mechanical energy. Retarding admixtures are used to slow the rate of setting of concrete. By slowing the initial setting time, the concrete mixture can stay in its fresh mix state longer before it gets to its hardened form. Retarders can be formed by organic and inorganic material. The organic material consists of unrefined CaO, K2O, MgO, AL2O3, salts of lignosulfonic acids, hydroxycarboxylic acids, and carbohydrates. Agave sisalana Perrine, popularly known as sisal is a commercially used fiber yielding plant. Cement concrete production especially in hot climate experience a lot of challenges from mixing, transporting and placing of concrete because of the accelerated setting of cement concrete due to high temperatures. Workability is compromised to a large extend and there is need to prolong the setting time allow for execution of the concreting activities. The rapid heat generation from large concrete pours can also lead to cracks in the concrete structure. This results in the need to slow the rate of concreting thereby causing costly delays. Retarders go a long way in slowing down the hydration process hence reduce the heat of hydration. The study investigated the suitability of sisal juice as a retarder to influence the properties of hardened concrete at a lower cost. This research implored the use of experimental design. The study used quantitative techniques of data analysis to analyze the test results of different experiments. Descriptive statistics including means, cross-tabulation, frequencies and percentages was used for comparison and the results presented in form of frequency tables, line graphs and bar charts for easier understanding and interpretation. SJE was used as a retarder to influence the properties of fresh and hardened concrete. Sisal juice extract was used as a partial replacement of water at different dosages and in the concrete mix. A total of 84 concrete cubes were produced in 7 sets of 12no. specimen each. One set was made with the control mix which had zero SJE content. The remaining sets had varying dosages of SJE namely 5%, 10%, 15%, 20%, 25% and 30%. Twelve beam specimens measuring 150x150x530mm were also casted. Specimens were subjected to Compressive strength tests as per BS EN 12390–3:2009, setting time test as per BS EN 196-3:1995 and slump test as per BS EN 12359–2:2009. To establish the effect SJE on strength of concrete, compressive strength was tested at 7, 14, 28 and 56 days while flexural strength

Globally, attention has been focused on pollution and exhaustion of fossil fuels allied to conventional energy sources. In contrast, non-conventional energy/renewable energy sources have always been considered clean and environmentally friendly. The non-conventional (renewable) are being preferred because they are believed to be more environmentally friendly. Renewable Energy Technologies (RETs), especially Solar Photovoltaics, have seen many plants being constructed to supplement the grid or alternatives for those far from the grid. Solar Photovoltaics plants occupy large tracts of land, which would have been used for other economic activities for revenue generation such as agriculture, forestry, and tourism in archaeological sites. The negative impacts slow down the application of Solar PV. Still, a modeling tool that can quickly and quantitatively assess the effects in monetary form would accelerate the Solar PV application. This thesis presents a developed modeling tool that determines not only the techno-economic impacts but also the environmental impacts in monetary form for one to be able to assess the viability of a plant in a given region. Solar-PV based Power and Environmental Cost Assessment (SPECA) model was developed to help in the following ways: (i) understanding of Solar PV based power generation and its interactions with the resource inputs, the private costs, externalities, external costs, and hence the environmental and social-economic impacts over the lifespan of the plant (ii) aiding investors of Solar PV with a tool which has a clear graphical and user interface for detection of the main drivers of the Levelized Cost of Energy (LCOE) (iii) creating an enabling environment for decision-makers aided by a visual SPECA modeling tool which takes into account the financial viability and the environmental impacts of Solar PV. SPECA is a sizing tool for techno-economic analysis. It is mathematically based, capturing all the life cycle costs and their associated ecological burdens. The source codes of the SPECA model have been written in Visual Basic programming, while the Database was developed using the Standard Querry Language (SQL). The modeling tool provides a friendly Graphical user interface where the user can input the required data. In general, SPECA will be of great use to investors and policymakers of Solar PV systems for drawing alternatives and conclusions based on the best compromise. The model developed will be useful, especially in addressing the trade-offs between environmental impacts and financial impacts, which aim to improve the quality and transparency in the decision-making during the deployment of Solar PV. The quantification of the social-environmental effects of Solar PV will permit for cost accounting assessment of the unforeseen cost incurred when using them for electricity generation. The SPECA modeling tool presents the LCOE, the Levelized Total Cost of Energy (LTCOE), and the Levelized Externality Cost of Energy

Adaptive Noise Cancellation (ANC) entails estimation of signals corrupted by additive noise or other interference. ANC utilizes a “reference” signal correlated in some way with the “primary noise” in the noise cancellation process. In ANC, the reference signal is adaptively filtered and thereafter subtracted from the “primary” input to obtain the desired signal estimate. Adaptive filtering before the subtraction process allows for handling of inputs that are either deterministic or stochastic, stationary or time varying. ANC has been widely applied in the fields of telecommunication, radar and sonar signal processing. The performance and efficiency of ANC schemes is based on how well the filtering algorithm can adapt to the changing signal and noise conditions. It is worthwhile focusing on developing better variants of AI algorithms from the point of view of ANC. This thesis is focused on: development of a modified version of the Simulated Annealing (SA) algorithm and its application in ANC. This is alongside an analysis of the effectiveness of the standard and modified SA algorithms in ANC in comparison to standard Least Mean Square (LMS) and Normalized Least Mean Square (NLMS) algorithms. Signals utilized in this study include: sinusoidal signals, fetal electrocardiogram signals and randomly generated signals. The modified SA algorithm has been developed on the basis of making modifications to the control parameters of the standard SA on the basis of the acceptance probability and the cooling schedule. A low complexity acceptance probability scheme has been proposed. The proposed cooling schedule is iteration-adaptive to improve on algorithm convergence. The ANC problem is formulated as a minimization problem entailing the minimization of the difference between a noise contaminated signal and a weighted estimate of the noise content. This is achieved through optimal ANC tap-weight adjustment. The algorithms under study are applied in the weight generation process with the expected outcome as ideally a noise free signal. In this evaluation, performance measures analyzed in the study are mis-adjustment and convergence rate. To evaluate these, Euclidean distances and the correlation factors between the desired signal

Agricultural application of sewage sludge is an effective disposal method as it is beneficial to agricultural productivity. However, there is need to regularly monitor levels of heavy metals in sludge. Such monitoring is currently lacking in our sewage treatment plants-thereby, leading to informal use of sewage sludge in agriculture and lack of quality control. Furthermore, there is an absence of locally available technologies for heavy metal removal. Conventional processes for heavy metal removal such as chemical precipitation and membrane filtration are too expensive, require technologically advanced systems, are difficult to maintain, require a lot of expertise and are therefore not locally accessible. Heavy metals have adverse effects on human life when consumed. There is therefore need to come up with affordable, innovative technologies that can be locally used to remove heavy metals from sewage sludge used in agriculture. This study used phytoextraction, a phytoremediation process in which certain plants have the ability to absorb toxic contaminants from a soil matrix, to remove heavy metals from sewage sludge. The objective was to investigate the potential of heavy metal phytoextraction in sewage sludge using sunflower. The sewage sludge was obtained from Dandora and Kariobangi Wastewater Treatment Plants. The experimental set up was in three sets. The first containing soil and Kariobangi sewage sludge mix in the ratio 1:1. The second containing soil and Dandora sewage sludge mix in the ratio 1:1. The third set contained 100% soil which served as the control experiment. Sunflowers were grown in each of the sets and heavy metal levels were monitored in the plant roots, shoots and soil sludge mixes for a period of four months using atomic absorption spectroscopy. After the four months, cadmium levels in the sewage sludge were reduced by 84%, manganese by 91%, copper by 85%, lead by 89% and zinc by 84%. The stated heavy metals were all brought down to levels acceptable for garden soil. This proved that sunflower phytoextraction is a technology that can be assimilated in wastewater treatment plants to ensure safe agricultural use of sewage sludge.

This study analyses the effect of number of slits on a diverging conical ring insert when symmetrically cut out on the curved surface to generate multi longitudinal vortices in an incompressible fluid flow on a cylindrical tube. This is a passive augmentation technique aimed at achieving heat transfer enhancement. The insert disrupts flow creating a mixture between core and near wall fluid into a swirl flow with a pressure drop and friction characteristic generating higher heat transfer enhancement than that attained by either laminar or turbulent fluid flows achieved in a tube of equal diameter using other augmentation techniques. In this research work hot water is used as the test fluid in a simulation to establish the pressure drop and temperature variation along a tube of inner diameter 0.05 m and 8 m long with a diverging conical ring insert placed at a fixed distance from the entrance where uniform fluid velocity is attained to avoid the pipe entrance effect. Using a conical ring insert with inlet diameter of 0.036 m and an outlet diameter of 0.05 m giving a pitch ratio of 0.72, when the fluid flows into the pipe inlet region at a pressure P0=110,000 Pa and temperature T0 = 370 K. Analysis of the results shows a positive coefficient of heat transfer and thermal performance factor when comparing an insert with no slit and those with one, two and three slits. The highest rate of heat transfer enhancement is 423.38 attained when two multi – longitudinal vortex pairs are formed by a diverging conical ring insert with two slits on opposite sides of the curved surface.

Groundwater pollution is becoming a major concern worldwide. The impact of polluted groundwater resources is three-fold: artificial water scarcity, human health problem and an impediment to economic development. Mid River Njoro catchment has experienced numerous human settlements and intensive agricultural activities over the years, threatening the quality of water from wells and boreholes. This study assessed the groundwater quality, the land-use types and the vulnerability of groundwater resources to surface pollution within Mid River Njoro catchment, Kenya, using a modified DRASTIC model in a GIS environment. Groundwater samples were collected from boreholes and analyzed for pH, temperature, electrical conductivity, dissolved oxygen, nitrate, ammonia, and total phosphorus to calculate the Groundwater Quality Index (GQI). The land-use map was prepared from a high-resolution Google earth satellite imagery of 2015. The vulnerability zones developed using parameters such as depth to water table, net recharge, aquifer media, topography, impact of vadose zones, hydraulic conductivity and land use types. Validation nitrate values were compared to the calculated DRASTIC index to assess the efficacy of the modified DRASTIC model. From the results, the GQI range from 68.38 to 70.92, suggesting fairly good groundwater quality. The major land-use types identified include agricultural land, built-up areas, forests and agroforestry areas. The agricultural land dominated the study area, followed by built-up areas, forests and agroforestry areas. The study area is characterized by three vulnerability zones: very low (6.1%), low (87.4%) and moderate (6.5%). The validation results obtained from Pearson’s correlation (0.49) and chisquare values (5.01), revealed a positive relationship between the modified DRASTIC index and nitrate values.

Floods are the most common and widespread climate-related hazard in the Lake Victoria region. However, significant delays in ground data availability have made it unfeasible to use traditional flood forecasting systems. Satellite rainfall estimates have been identified as readily and economically available data that can be used as input to run hydrologic models and produce flood-warning systems. The aim of the study therefore is develop a simple and locally viable alternative approach to circumvent the absence of reliable ground measurements by using satellite rainfall estimates for forecasting and management of floods in the study area. The satellite-derived rainfall estimates (RFE) were first evaluated using historical rainfall data for the Nyando basin corresponding to the locations of 35 gauging stations in the basin for the period 1995 to 2005. A Digital Elevation Model (DEM) of the basin was used to generate the drainage patterns of the basin. The land cover of the study area and the digital soil map are incorporated in the system. The study applies daily driven satellite-derived rainfall and the pixel based Curve Number method for spatially distributed hydrologic streamflow modelling and flood forecasting. Rainfall–runoff relationships results of the area obtained in a spatial scale are then tested on their capabilities as a flood early-warning system by comparing them with historical streamflow. The approach was further tested using RFE for the period 2006 to 2012. The results for comparisons at daily accumulations of RFE with observed rain gauge data are not satisfactory but they performed reasonably well in detecting the occurrence of rainfall. The products show significant results for 10-day accumulation where regression analysis yielded on average, a correlation coefficient (r) of 0.78. While graphical plots of daily-observed stream flow against simulated streamflow show a poor agreement.