Tanzania Journal of Engineering and Technology

Use of Activated Palm Kernel Shells on Adsorption of Heavy Metals (Cu2+ and Pb2+) from Contaminated Wastewater

Eustarch Revocatus, Augustina Alexander, Joseph Mtamba, Edwin Richard — Tue, 31 Dec 2024 00:00:00 +0000

This research aimed to evaluate the adsorption capacity of low-cost agricultural waste adsorbent-activated palm kernel shells (APKS) for the removal of Pb2+ and Cu2+ ions from synthetic wastewater that had the concentration of copper and lead ions comparable to that of waste produced in Tanzanian research and teaching laboratories. This study was carried out in batch and continuous column adsorption reactors. The study examined the influence of particle size (0.71 mm–2.36 mm), pH (4.5–8.6), adsorbent dose (5–20 mg/L) and initial concentration Ci (1.93– 4 mg/l) on APKS adsorption removal efficiency. The batch results indicated that under alkali conditions (pH 8.4 -8.6), APKS has an adsorption removal efficiency of 77.3% - 92% and 98.2-98.5% for Cu2+ and Pb2+ ions, respectively. Under acidic conditions (pH: 4.0 - 4.5), the APKS has a lower adsorption capacity of 23.7% and 36.29% for Cu2+ and Pb2+ ions, respectively. The column test results showed that APKS had a removal efficiency of 98.4% and 73.6 for Pb2+ and Cu2+ ions, respectively. The results also showed that both Langmuir and Freundlich adsorption isotherms were the best model for the adsorption of Cu2+ ions on APKS, with R2 of 0.997 and 0.97, respectively. The results also showed that APKS can be utilised to treat wastewater with Pb2+ and Cu2+ concentrations to meet the effluent discharge standards. The study recommends using activated palm kernel shells to remove heavy metals in wastewater before discharging them into the environment.

ASSESSMENT OF ADAPTATION AND DIFFUSION OF BIOGAS TECHNOLOGY IN DAR ES SALAAM

Doreen L. Tarimo, Richard J. Kimwaga, Alexandera — Tue, 31 Dec 2024 00:00:00 +0000

This study examined the adaptation and diffusion of biogas technology in Dar es Salaam, utilizing various data collection methods, including surveys, laboratory analysis, field observations, and interviews. Data collection methods and techniques included lab analysis using American public health association (APHA) standard methods, interviews, questionnaire administration The data analysis was undertaken using statistical package for the social sciences (SPSS) with a sample size comprising 100 community heads from Mburahati, 50 biogas technology adopters, 50 non-adopters, and 16 key informants. The findings disclosed that 40% of respondents learned about biogas technology through their friends and neighbours who had already adopted it, while 6% discovered it through exhibitions. A majority (54%) acquired information from other sources like seminars, biogas researchers, extension officers, and technicians who had adopted the technology. The most influential factor affecting the adoption of biogas technology was the community's income level, accounting for 50.4% of all factors. Inadequate funds were a significant challenge for 75% of respondents, and 64.05% hadn't attended training sessions or seminars related to biogas technology, despite their importance. The study also found that neutral pH levels enhanced anaerobic digestion efficiency, leading to efficient biogas production. Efficiency rates varied among case studies, with the International School of Tanganyika achieving rates between 93.52% and 99.35%, Mburahati DEWATs ranging from 82.15% to 98.24%, and CCBRT ranging from 81.98% to 99.61%. These variations in anaerobic digestion efficiency were likely due to the low solid content in the selected substrates or effluents. In conclusion, the study revealed a low level of biogas technology adoption and diffusion in Dar es Salaam. To enhance this process, the government should review and establish a supportive environment for the advancement of this technology.

Effectiveness of Natural Coagulants in Purification of Industrial Wastewater: A case of Cactus Pads and Watermelon Seeds

Herry M. Mtana, Neema Msuya, Zainab Katima — Tue, 31 Dec 2024 00:00:00 +0000

This study assessed the potential of cactus pads and watermelon seeds as natural coagulants in industrial wastewater treatment. The global characterization of the two coagulants was done by using the Fourier Transform Infrared (FTIR) to determine the specific functional groups and by zeta potential measurements. A full factorial design was used to design the experiment and analyze the effect of three factors: coagulant dosage, settling time and particle size with three levels each and one replicate on the turbidity removal. ANOVA analyses were used to determine the significance of the factors. Results show that the amino and hydroxyl groups in cactus pads and watermelon seeds generate surface charges that enable interaction with charged particles and facilitate their destabilization, promoting coagulation. Negative zeta potential due to the ionization of the functional groups signified the potential of the cactus pads and watermelon seeds as natural coagulants. The highest removal efficiency achieved was 92% for both watermelon seeds and cactus pads, using a dose of 200 mg/L and 140 mg/L, respectively. The main effect and interaction plots for both coagulants reveal that an increase in both factors significantly impacted the removal efficiency. Results on particle size effects imply that larger particles have a greater tendency to settle and can be easily removed, resulting in the highest removal effectiveness. The combination of cactus pads and watermelon seeds was found to be significantly more effective in reducing turbidity in wastewater from industries, with a clearance rate of approximately 94%. More studies on the synergistic effect of combining the two coagulants are necessary. Utilizing cactus pads and watermelon seeds, for treating industrial wastewater can decrease reliance on and minimize the need for importing synthetic coagulants, which have negative environmental effects and pose significant health risks.

Effects of Technical Debt on Software Interoperability

Leonard Peter Binamungu — Tue, 31 Dec 2024 00:00:00 +0000

Technical debt (TD) refers to sub-optimal development decisions that make the software costly to maintain and evolve. Examples of TD include structural complexity, violation of coding styles, and code complexity. Existing research has investigated the nature, causes and indicators of TD, as well as tools and strategies for managing TD. However, although TD could hinder the ability of a software system to be interoperable with others, existing literature has limited evidence on how TD affects systems interoperability. This limits the ability of software engineering teams to manage TD in ways that do not hinder systems interoperability. To fill this void, two system interoperability projects in the health sector, involving 35 systems, were analysed to understand how TD affects systems interoperability. The complexity of the healthcare domain and the diversity of the 35 systems enabled a clear understanding of the intricate interactions between technical debt and systems interoperability. The identified interoperability challenges were mapped to five different TD types, all of which can be linked to software development practices that do not prioritise responsible management of TD. Documentation and requirements debt were identified as the most prevalent barriers to interoperability in the studied healthcare domain. The findings suggest that improving software development processes through interoperability-sensitive TD management strategies could improve software interoperability. The paper makes an empirical contribution by mapping interoperability challenges to technical debt, enabling us to conceptualise system interoperability challenges as consequences of technical debt. The implications of this contribution for domain and research practices are also provided.

Design and Implementation of Secured Hybrid Gateway Node for Securing IoT - Enabled Distribution Automation

Ally Bitebo — Tue, 31 Dec 2024 00:00:00 +0000

The integration of smart grid and Internet of Things (IoT) technologies plays a crucial role in enhancing the quality of services provided by traditional electrical grids. This combination has enabled the introduction of new services, such as demand response, automatic meter reading, and IoT-enabled Distribution Automation (IoT-DA), which incorporates sensors, actuators, intelligent electrical devices (IEDs), and information and communication technologies to monitor and control the grid. However, this integration also introduces network security risks, including Denial of Service (DoS) attacks, false data injection, and masquerading attacks, such as system node impersonation that can transmit incorrect readings, trigger false alarms, and lead to improper node control. To address these challenges, a secure hybrid gateway node was designed and implemented to safeguard communication networks. This solution uses Datagram Transport Layer Security (DTLS) for Constrained Application Protocol (CoAP) to transmit historical data and mutual Transport Layer Security (TLS) for Message Queuing Telemetry Transport (MQTT) to send switching messages. The results demonstrate that the secured hybrid gateway node successfully ensures data confidentiality, integrity, and resilience against DoS attacks. In the future, this study will measure the efficiency of the implemented of the secured hybrid gateway node in terms of the security and performance in IoT devices by analyzing energy and memory usage.

Effects of Thermal Shock Protection Methods on Pressure Measurements in a Rapid Compression Machine

Dr. Myeji Materego — Tue, 31 Dec 2024 00:00:00 +0000

The study investigates the impact of thermal shock protection methods on pressure measurements in Rapid Compression Machines (RCMs). It focuses on the performance of various pressure transducers, specifically 601A, 701A, 6061B, and 7005, under atmospheric initial conditions. The research emphasizes the importance of mounting techniques and coatings, revealing their significant effects on pressure trace accuracy. Special mounting adaptors for the pressure transducers were designed and manufactured, this enabled simultaneous measurements for all transducers to be made in a single compression stroke. Instantaneous pressure within combustion chamber was measured when air was compressed in RCM from initial pressure and temperatures of 0.1 MPa and 293K respectively, compression ratio was fixed at 13.58. Pressure traces revealed that all pressure values measured using the selected transducers were affected by thermal shock effect, this led into significant deduced end of compression temperature error of up to 8.7 K. Different temperature protection measures were tested and their effectiveness in reducing thermal shock effect was studied. A combination of recessed mounting and silicon coating provided the best thermal shock protection for the pressure transducers tested in this work. The insights gained from this study are crucial for optimizing accuracy of pressure measurements and interpretation in combustion testing rigs.

Long-Range Inertia Prediction Considering Contemporary Evolution of Power Grid Networks

Peter Makolo, Francis Mwasilu, Ramon Zamora, Tek-Tjing Lie — Mon, 03 Feb 2025 00:00:00 +0000

Reduced network inertia due to high penetration levels of nonsynchronous generators in modern power systems is becoming a pressing issue. As a result, very quick inertial responses are observed after contingency events in networks. Due to quick inertial responses, there is a practically very limited time interval for control actions in real-time. Thus, system operators need to understand the prior inertia values to plan, control, and operate the network securely. Long-range forecasting of the network's inertia values, in contrast to short-range forecasting techniques, can pinpoint when the network is most likely to be vulnerable in a reasonable time ahead. Thus, in this research work, an improved ARIMA model (i-ARIMA) technique for long-range forecast inertia values in a modern network is proposed. To estimate future inertia values over a long period of time, the i-ARIMA model leverages strong periodic and seasonality characteristics of previous time series data. The i - ARIMAmethod is tuned for optimal values of a moving observant predictor P, periodicity and seasonality factor s and smoothing factor n that give the best forecasts with competitive accuracy. Rigorous evaluation and tests of the method, which are performed on the New Zealand network data using the Power Factory DigSilient platform, demonstrate that the proposed i-ARIMA is quicker, more reliable, more accurate, and better than other conventional forecasting methods.

A Bibliometric Analysis of PAT-SEIG Evolution as an Alternative Energy Generation Method

Emanuel J. Nyirenda, Torbjorn K. Nielsen, Joseph H. Kihedu — Mon, 03 Feb 2025 00:00:00 +0000

Pumps as Turbines (PATs) coupled with Self-Excited Induction Generators (SEIGs) as an alternative energy generation method have been the subject of significant research in recent years. This paper presents a bibliometric analysis of the evolution of PAT-SEIG technology as an alternative energy generation source. An analysis of a comprehensive dataset of peer-reviewed journal articles, conference proceedings, and patents related to PAT-SEIG systems, using advanced bibliometric techniques and PRISMA to identify key research themes, influential authors, the growth of the field and patterns of collaboration, and changes in research focus over time. Over a publication period of 32 years, a total of 949 documents were reviewed using the PRISMA checklist, resulting in the selection of 77 documents for analysis. The findings indicate an increasing interest in PAT-SEIG technology, with an impressive annual growth rate of 9.45%. However, gaps have been identified which provide areas for further studies. These include the PAT prediction methods, voltage and frequency fluctuations
in SEIG, and the overall efficiency of the PAT-SEIG system. The study provides insights into the current state of research and highlights areas
that require further investigation as a way of contributing to the advancement of the technology.

Heavy Metals Pollution in Roadside Ecosystems

Lilian Matafu, Godwill Mrema, Rwaichi J.A. Minja — Mon, 03 Feb 2025 00:00:00 +0000

Heavy metals refer to metallic elements that are characterized by having a relatively high density and they are toxic or poisonous even at low concentration. They are environmental pollutant owing to toxicity and longevity in atmosphere and ability to accumulate in living things via bioaccumulation. They tend to enter in different system such as food chain. Analyses of water, soil sediment and the surrounding growing plants (Cynodon dactylon and Cyperus species) for selected heavy metals (Cd, Pb, Zn and Cu) were conducted on a roadside pond located at Boko MSB, Dar es Salaam. Pond water, soil sediments and plant
samples were collected from Boko MSB site and treated using appropriate methods of acid digestion (aqua regia digestion) involving sample preparation and digestion and analyses for heavy metals and physical-chemical parameters using atomic absorption spectrometry (GBC XPLOOR AAS). Physical-chemical parameters of pond water such as pH, electrical conductivity, total dissolved solids and turbidity were measured. The concentration of Cd and Pb in the water sample were 0.0637 mg/L and 0.995 mg/L, respectively, while the physical-chemical parameters of the pond water indicated a pH of 7.55, electrical
conductivity of 184 µs. Based on the results of the study, the pond water is not safe for potable uses since it contains toxic heavy metals which are above WHO/TBS safe limit. The high concentration of the heavy metals was reflected in both the soil sediments and plants with Cd and Pb in soil samples being above safe limits while Cd, Pb, Zn and Cu in plant samples were also above safe limit.

Review on State of Art of Smoothed Particle Hydrodynamics Method and its Advances in Solid Dynamic

Harold J. Mtyana, Dr. Paul C. Ndumbaro, John K. Makunza — Mon, 03 Feb 2025 00:00:00 +0000

The world is witnessing continued collapse of both buildings and other structures during earthquakes, which is an example of a dynamic effect. One cause of such disasters may be inadequacies of techniques for modeling of these structures during analysis and design as compared to their actual responses during dynamic events. Also, techniques for numerical modeling and analysis of structures in place are meshed methods which do not accurately capture the actual behavior of structural elements especially under high dynamic actions due to the assumption that mesh geometry is unchanged geometry tend to change with respect to time step of such an action. In view of this, meshless techniques such as Smoothed Particles Hydrodynamics (SPH) prove to be promising. However, the application of SPH method especially in solid dynamics, still poses some challenges that reduce its efficiency and need respective improvements. This paper reviews advances so far done in SPH method and its application in solid dynamics with the key focus on weaknesses of the method and soundness of the recommended solutions through reviews from recent research, from which recommendations for further improvements have been presented as
well. Findings from reviewed papers show that efforts towards improving various challenges on the classical SPH specifically on dynamics of solids have been done and are hereby acknowledged. However, critical areas that still pose attention and require further research include criticality on choice of most suitable kernel function that best fulfills all interpolant requirements, criteria for setting of smoothing length and general SPH formulation that appropriately represents dynamic problem of solids other than those which have been covered so far. Special attention on clear way of setting the initial and boundary conditions of the kernel domain is also needed.

Efficient Operation of Direct Coupled Solar Home PV System: A Case of Solar Home PV System Installed in Dodoma, Tanzania

Sarah P. Ayeng’o — Mon, 03 Feb 2025 00:00:00 +0000

Direct coupled Photovoltaic (PV) system is a common topology among most of the off-grid communities in the world. This topology has less components hence resulting in low investment costs. However, it suffers much losses when battery operating voltage is far from maximum power point voltage of PV modules. This scenario can be attributed by different factors such as; variation in solar radiation, load profile and temperature. Efficient operation of these systems is required in order to reduce losses. Usually in direct coupled system, PV modules are connected in parallel with batteries through a charge controller hence making PV output to depend solely on battery operating points. For losses reduction, a proper voltage range of battery and PV modules has to be selected. The challenge to many technicians is on proper selection of ranges of voltages of battery and PV module. This results in installed PV systems being operating away from maximum power point hence much losses. This paper presents a model of solar home PV system developed using MATLAB software. Two types of solar PV modules; A Copper, Indium, Gallium, Selenium (CIGS) thin film and a polycrystalline PV module with 24V lithium nickel cobalt aluminum oxide as a storage were modeled. The Solar radiation data and load profiles were collected from Dodoma, Tanzania. In order to get optimum results, optimization tool was also developed by using genetic algorithm. For efficient operations of direct coupled PV systems, the ratio between 0.7 and 0.9 of battery to PV maximum power point voltages has been proposed. By using these ratios in PV system designing, one can have an assurance of operating PV system at minimum losses in areas with high solar radiation. This can be a simple method to be used when designing solar home system. However, more detailed analysis on battery capacity and PV modules are recommended.

Assessment of Wind Speed Characteristics and Available Wind Power Potential for Electricity Generation in Tanzania

Mwingereza J. Kumwenda, Rajabu J. Mangara — Mon, 03 Feb 2025 00:00:00 +0000

The energy demand and its associated crises are attracting significant attention due to population increase and economic growth especially in developing countries. Fossil fuel-based energy source stand as a prominent anthropogenic resource but they are accompanied with increased carbon emissions and heightened environmental concerns. Renewable energy sources such as wind energy can offers a lot of potential for sustainable growth in the energy sector of developing nations like Tanzania. Thus, this work investigated wind speed characteristics and available wind power potential in six selected regions in Tanzania with different topographical features for future electricity generation. The data of the wind speed of ten years available at a height of 10 m above ground level have been used to analyse monthly and annual variations of wind speed. Minimum and maximum average values of recorded wind speeds are presented in this paper. The Weibull shape k and scale c parameters have been estimated using the Weibull distribution function. Results indicate that the respective maximum average annual values of the shape and scale parameters for all sites are 2.54 and 8.21 m/s, which indicate that the wind speed is steady. The results show further that the Singida region has a maximum average annual wind speed of 7.29 m/s and a corresponding annual average wind power density of 237.30 W/m2 . In conclusion, the results suggest that the Singida region can be considered a suitable site for wind energy generation on a large scale.

Performance Evaluation of Free Space Optical Communication in Dar es Salaam: Impact of Scintillation and Modulation Schemes

Mustafa H. Mohsini, Florence Rashidi, Teck Kinte Chiyaba — Mon, 03 Feb 2025 00:00:00 +0000

Free space optical communication (FSO) holds significant relevance in the modern communication system as it offers high and unlimited data rates, enhanced security, rapid deployment, and low cost for installation. However, the performance of FSO transmission is greatly affected by harsh atmospheric conditions such as wind, temperature, and humidity, which induce scintillation. With the rapid growth of internet users and Dar es Salaam being a business city in Tanzania, higher and unlimited bandwidth for communication is highly demanded. This study primarily aims to evaluate the performance of FSO transmission in Dar es Salaam, Tanzania, by investigating the impact of atmospheric conditions particularly scintillation on link availability and transmission quality. We evaluated link availability and the effect of scintillation in terms of eye diagrams, Bit Error Rate (BER), and two modulation schemes (i.e. Return-to-Zero (RZ) and Non-Return-to-Zero (NRZ) schemes) in the Dar es Salaam region. Our work used weather data, including temperature, relative humidity, and wind speed average data, collected from January 2014 to December 2017 by the Tanzania Meteorological Authority (TMA) in the Dar es Salaam region for link availability and performance analysis. The simulation was performed to determine the FSO link availability, and the scintillation effect was analyzed using the Hufnagel Valley (HV) day prediction model. Results analysis indicates that link availability is significantly influenced by atmospheric conditions, with the simulation results showing that Dar es Salaam has higher FSO attenuation and that the transmission can sustain link availability up to a distance of two kilometers. A comparison of the two modulation schemes has shown that NRZ is the best modulation scheme that could be used, and January is the best month for transmission in Dar es Salaam. This technology is feasible and therefore is recommended for adoption.

Improved Minimum Variance Channel Estimation Techniques for OFDM Systems

Kwame S. Ibwe — Mon, 03 Feb 2025 00:00:00 +0000

Orthogonal frequency division multiplexing (OFDM) systems face challenges in channel estimation due to noise, variability, and the doubly dispersive nature of wireless channels, which degrade performance. To address these challenges, a multichannel minimum variance double dispersive channel estimator is proposed. The method employs a hybrid approach that combines subspace and minimum variance techniques, optimizing the filter bank output power under a signal-to-noise ratio (SNR) constraint. This design preserves the desired signal while effectively suppressing disturbances, achieving robust performance with reduced computational complexity compared to existing methods. Simulation results demonstrate that the proposed estimator outperforms subspace and asymptotic methods in terms of normalized mean square error (NMSE) and bit error rate (BER), particularly under low SNR and frequency-selective conditions. These findings highlight its potential for enhancing spectral efficiency and data integrity in advanced OFDMbased communication systems