Browse
Recent Submissions
Item Tracing the Implementation of Pedestrianization Schemes for Enhancing Accessibility and Mobility: A Case of Kariakoo, Dar es Salaam City in Tanzania(African Conference on Resilient and Sustainable Cities, 2025-03-27) KIMIRO, ABOUBAKARY SAID; BABERE, NELLY JOHNPedestrianization schemes were introduced to improve pedestrians' safety and mobility by creating a friendly walking environment, resulting in a sense of belonging for pedestrians within the inner cities. Effective implementation of pedestrianization streets, especially in developed countries, is reported to reduce accidents and ease movement in an urban environment. However, it seems to be different in developing countries where pedestrianization schemes are not well implemented; therefore, the intended goals of their introduction are not attained. This study investigates the implementation of pedestrianization schemes (pedestrian malls and one-way streets) aimed at better accessibility and mobility. Moreover, it examines the challenges facing the implementation of pedestrianization schemes. The study was conducted in five pedestrianized streets (2 pedestrian threes and three one-way streets) in the Kariakoo area. The qualitative approach was employed and methods used in data collection were interviews with officials and 30 pedestrians per street, mapping and observation. Pedestrian malls function as part-time pedestrian streets, which allow vehicular traffic with less than 3 tonnes to the road after 7:00 p.m.; on-street parking is restricted too, but loading and unloading activities are permitted. One-way streets function as shared streets where pedestrians and vehicular traffic share the space, with on-site parking. Hence, pedestrians continue suffering when accessing and moving within pedestrianized streetsItem Modelling over-reading correction factors for ultrasonic flow meters in wet gas measurement using advanced regression and machine learning techniques(Elsevier Ltd., 2025-10-08) Shunashu, Ishigita Lucas; Kaunde, OsmundAccurate wet gas measurement is essential for optimizing production, transmission, and reservoir management in oil and gas operations. Ultrasonic flow meters, though non-intrusive and versatile, often overestimate flow rates due to the presence of liquid phases, leading to significant operational and economic errors. To address this, a data-driven correction model was developed using computational techniques to predict and compensate for over-reading. This study evaluates the performance of several advanced regression and machine learning approaches, including polynomial regression, random forest regression, nonlinear curve fitting, neural networks, multiple linear regression, ridge regression, and lasso regression, using an extensive experimental dataset. Key input variables include liquid volume fraction, Lockhart–Martinelli parameter, Froude number, Weber number, slip ratio, and density ratio. Among the models tested, random forest regression and multiple linear regression achieved the highest accuracy, with average relative absolute errors of 3.02% and 3.20 % respectively. These findings demonstrate the potential of data-driven modeling to enhance the reliability of ultrasonic flow meters in complex wet gas environments.Item Integrated Ultrasonic Flow Meter and Microwave Sensing Technology for Wet Gas Measurement: Development and Validation of Over-Reading Correction Models(John Wiley & Sons, 2025-11-20) Shunashu, Ishigita Lucas; Kaunde, Osmund; Mwakipesile, DuncanAccurate wet gas flow measurement is essential for production optimisation, custody transfer, and regulatory compliance in theenergy and chemical industries. Conventional ultrasonic flow meters often overestimate gas flow rates due to liquid entrainment,while microwave sensors alone struggle with phase discrimination under dynamic conditions. This study introduces a hybrid metering system, Ultrasonic Flow Meters andMicrowave Sensing Measurement ofWet Gas (USMMW), that integrates transit-time ultrasonic flow measurement with microwave dielectric sensing to correct over-reading errors. Experimental data were collected from a controlled multiphase flow loop using a 2-inch pipeline equipped with an ultrasonic meter and a 2.7 GHz microwave sensor. A data-driven over-reading correction model (OR) was developed using detected liquid volume fraction (LVF) and eight dimensionless parameters derived via the Buckingham Pi theorem.Multiple regression andmachine learning techniques, including multilinear regression (MLR) and random forest regression (RFR), were applied to optimise model performance. Validation results showed that the USMMW system achieved corrected gas flow rates with an average relative absolute error (RAE) of 3.02%, outperforming conventional differential pressure models. The findings demonstrate that USMMW offers a robust, non-intrusive solution for real-time wet gas metering under mist and stratified flow regimes, with potential for scalable industrial deployment.Item Spatial assessment of water quality in a hierarchically structured river system using stream order classification and multivariate statistical techniques: A case study from Tunduma, Tanzania(ASSSCIENCE PUBLISHING, 2025-10-20) William, Matungwa; Katambara , Zacharia; Shegwando,OmariWater quality assessment is essential for understanding pollutant dynamics, supporting evidence-based watershed management, and protecting public health. While numerous studies have utilized statistical and modeling approaches, limited attention has been paid to how stream order influences water quality variability, particularly in urban catchments of sub-Saharan Africa. This study investigates spatial patterns of water quality in a hierarchically structured stream network in Tunduma, Tanzania, by integrating Strahler stream order classification with multivariate statistical techniques, based on monthly monitoring of six surface water points over 12 months (n = 72) during both wet and dry seasons to analyze physicochemical, nutrient, and microbial parameters. Hierarchical cluster analysis, combined with Pearson correlation matrices and significance testing, was employed to assess pollutant similarity and accumulation patterns across different stream orders. Results revealed that phosphate (PO4 3−) concentrations ranged from 0.42 to 1.49 mg/L and nitrate (NO3 − ) levels ranged from 4.3 to 13.2 mg/L. Strong positive correlations (r > 0.95) were observed among ion-derived parameters, such as electrical conductivity, total dissolved solids, and the concentrations of calcium (Ca2+) and magnesium (Mg2+). Third-order stream segments exhibited elevated concentrations of total suspended solids (0.990), biochemical oxygen demand (0.982), and microbial indicators, with fecal coliforms of 0–5 CFU/100 mL and total coliforms of 0–18 CFU/100 mL, reflecting cumulative pollutant loading in downstream reaches. The integration of Strahler stream ordering and cluster-based analytics enabled the identification of pollution hotspots and revealed the critical role of hydrological connectivity in shaping water quality trends. This research contributes a novel spatial–statistical framework for stream-based water quality assessment in East African urban contexts, offering practical insights for catchment-scale pollution control and resource management.Item Enhanced Liquid Detection in Wet Gas Metering Via Microwave Sensing and Random Forest Regression(A S M E, 2026-03) Ishigita Lucas Shunashu; Osmund Kaunde; Duncan MwakipesileItem Modelling Over-Reading Correction Factors for Ultrasonic Flow Meters in Wet Gas Measurement Using Advanced Regression and Machine Learning Techniques(Elsevier, 2025-10-08) Shunashu, Ishigita Lucas; Kaunde, OsmundAccurate wet gas measurement is essential for optimizing production, transmission, and reservoir management in oil and gas operations. Ultrasonic flow meters, though non-intrusive and versatile, often overestimate flow rates due to the presence of liquid phases, leading to significant operational and economic errors. To address this, a data-driven correction model was developed using computational techniques to predict and compensate for overreading. This study evaluates the performance of several advanced regression and machine learning approaches, including polynomial regression, random forest regression, nonlinear curve fitting, neural networks, multiple linear regression, ridge regression, and lasso regression, using an extensive experimental dataset. Key input variables include liquid volume fraction, Lockhart–Martinelli parameter, Froude number, Weber number, slip ratio, and density ratio. Among the models tested, random forest regression and multiple linear regression achieved the highest accuracy, with average relative absolute errors of 3.02% and 3.20 % respectively. These findings demonstrate the potential of data-driven modeling to enhance the reliability of ultrasonic flow meters in complex wet gas environments.Item Enhanced Liquid Detection in Wet Gas Metering Via Microwave Sensing and Random Forest Regression(ASME, 2026-03-01) Shunashu, Ishigita Lucas; Kaunde,Osmund; Mwakipesile,DuncanThis study explored the integration of machine learning regression models with a microwave transmission line sensor for estimating liquid volume fraction and liquid flowrate in wet gas flows. Under low liquid loading conditions (gas volume fraction 95–99.9%), four models: Bruggeman, support vector regression, Gaussian process regression, and random forest regression were evaluated. Random forest regression delivered the best tradeoff between accuracy, robustness, and computational efficiency, achieving a relative absolute error of 2.23% for liquid volume fraction and approximately 5% for liquid flowrate, with a Durbin–Watson statistic of 2.02 indicating minimal residual autocorrelation. Feature importance analysis identified the mixture dielectric constant as the dominant predictor (approximately 97% contribution), while other dimensionless parameters had a limited impact. Support vector regression failed to generalize, and although Gaussian process regression showed slightly higher accuracy, its computational cost limited real-time applicability. Overall, random forest regression combined with microwave sensing offers a scalable, nonintrusive solution for wet gas metering, with future validation needed under industrial hydrocarbon–water conditions and liquid loading flow regimesItem A FRAMEWORK OF STRATEGIES TO REDUCE ROAD CONSTRUCTION PROJECTS’ DELAY IN TANZANIA: A CASE OF TARURA ROAD PROJECTS(Mbeya University of Science and Technology, 2025-08-30) GABRIEL SEPERATUSThe construction industry is globally recognised as one of the fastest-growing sectors, contributing directly and indirectly to the development of several other sectors of the economy. Despite its significant importance, and based on persistent reasons, the industry has often been overwhelmed with various challenges, including the inability to finish the road construction projects within a given schedule. This study aimed to examine the stakeholder’s perception of prevailing best practice measures to reduce construction project delays in Tanzania. The study adopted the questionnaire tool and the survey interview to collect the respondent’s opinion from 208 respondents having experience of more than five years obtained through purposive sampling. The mean scores and the relative importance index (RII) of the data were computed using the SPSS 24 tool to obtain the descriptive information and inferential statistics. The findings have revealed ten potential factors for construction project delays and thirteen best practices that, whenever implemented, can assist in minimising delays. Moreover, the identified best practice measures were categorised in clusters to indicate the project participant who plays the significant role in minimising the delays. Furthermore, the findings acknowledged strategies were categorised in six clusters, namely effective project management, procurement and supply, resource adequacy (monetary or financial), design or technical, information and communication, and external strategies. The current study proposes future research to focus on identifying the relationship between the strategic cluster categories in recognising which cluster category correlates highly towards minimising the construction project delaysItem A Review of the Impact of Co-Digestion Substrates on the Methane Yield(iRASD, 2025-06-22) Matwani , J.; Iddphonce, R.This review highlights the impact of anaerobic co-digestion (ACD) on improving energy recovery from biogas production systems. Various factors from selected papers were reviewed to figure out their influence on ACD performance. Such factors include Carbon/Nitrogen (C/N) ratio, biodegradability of feedstock, microbial diversity, activity, buffering capacity, and trace element concentrations. Findings show ACD significantly enhances process stability and increases methane yield by 20% to 65% compared to mono-digestion. The process shares more insights on mechanisms for addressing environmental pollution challenges as it offers alternative approaches for reducing greenhouse gas emissions. Despite promising achievements in ACD systems, several limitations of the process still exist, requiring the attention of future studies to explore the full potential of technology. Specific areas include optimizing the mixing ratio of substrates to prevent acidification and ammonia toxicity risks that may occur during the process, hence affecting the system efficiency. Research should focus on process design and proper feedstock selection, considering innovative approaches such as bioaugmentation, supplementation with carbon compounds and nanoparticles, to improve microbial activity, process efficiency, and stability. Also, there is a need to develop predictive models that will accurately incorporate C/N ratio effects on digestion kinetics and nutrient transformation. Current models are complex, which hinders their scalability; thus, the use of machine learning could enhance model accuracy.Item A Systematic Review of Value Engineering Practices in Construction Projects in Tanzania.(Arid Zone Journal of Engineering, Technology & Environment, 2025-11-27) Kindole, A.; Lingwanda M. I,; Tekka, R. SValue engineering (VE) has become a vital component of construction management, improving project outcomes in terms of cost, time, quality, safety, environmental performance, stakeholder satisfaction and social value. This study systematically reviews VE practices to assess their applications, benefits, barriers, and future research directions, with emphasis on Tanzania’s construction industry. A structured search of Google Scholar and Semantic Scholar retrieved peer reviewed publications from 2005 to 2025, yielding about 70 sources, of which 32 highly relevant studies were analyzed in depth. The review shows that VE delivers quantitative benefits such as cost and time reduction, alongside qualitative gains including enhanced construction quality and better management through multidisciplinary teamwork. However, its adoption in Tanzania remains limited due to inadequate awareness, cost-driven procurement systems, and a shortage of trained VE professionals. This study further identifies critical success factors (CSFs) across VE phases, including effective project information preparation, cost-based comparison of design alternatives, systematic planning and implementation, and strong stakeholders support. It concludes by recommending the development of localized VE guidelines and increased awareness among clients and top management to enhance decision-making and promote wider VE adoption in Tanzania.Item Assessment of Scouring Effect of Msingi Masonry Arch Bridge in Mkalama, Singida, Tanzania(ABUAD Journal of Engineering Research and Development (AJERD), 2025-08-26) Barthazar, Dickson; Katambara, Zakaria; Kifanyi, GislarThis study presents an integrated geotechnical and hydraulic assessment of the Msingi Masonry Arch Bridge in Mkalama District, Singida, Tanzania, to evaluate scour vulnerability, subsurface strength, and structural load capacity. Field investigations included Dynamic Probing Light (DPL) testing, core sampling, and particle size analysis at six test pits (DS1–DS6), alongside laboratory tests adhering to BS 1377:1990 standards. Results revealed significant spatial variability in soil gradation and compaction, with deeper layers demonstrating high bearing capacities (up to 1555.8 kN/m²), while surface strata exhibited loose conditions and higher susceptibility to erosion—particularly in zones with elevated fines content. Hydraulic modelling, using site-specific parameters such as hydraulic radius (1.88 m), channel slope (0.0082), and Manning’s coefficient (0.017), predicted a scour depth of 2.6 m, compared to the observed 2.0 m. Structural analysis using the MEXE method yielded an allowable axle load of 28.05 tonnes, translating to a foundation pressure of 98.6 kN/m², which is within safe soil capacity limits. Despite current structural stability, the narrow scour margin and near-threshold loading conditions indicate elevated long-term vulnerability. The study recommends immediate installation of scour countermeasures, selective foundation deepening in weak zones, and routine monitoring to enhance the resilience and longevity of the bridge.Item Stakeholders’ Awareness and Perceptions on the Use of Force Account Method in Public Building Construction Projects in Tanzania.(DASJR, 2025-09-29) Magania, Faraji M.; Tekka, Ramadhani Said; Chengula, Duwa HamisiThe Force Account Method (FAM) is increasingly utilized as a procurement approach for public building construction projects in Tanzania, primarily due to its potential for cost savings, flexibility, and enhanced accountability. This study investigates stakeholders’ awareness of FAM selection criteria and their perceptions of its practical benefits. A descriptive survey design was employed, collecting data from 128 participants representing implementing agencies, contractors, consultants, and regulatory bodies through structured questionnaires. The results indicate high awareness of key selection criteria, especially the necessity for sufficient technical staff and the importance of minimizing disruption to ongoing operations. Stakeholders identified limited funding and uncertainty in disbursements as significant justifications for FAM, though opinions varied regarding remoteness and the clarity of work quantity definitions. Most participants agreed that FAM improves cost efficiency, adaptability to unforeseen changes, and public confidence in transparency. Nevertheless, concerns were raised about project completion timelines and the consistency of quality outcomes, with regulatory bodies and implementing agencies expressing differing perspectives. These findings underscore FAM’s advantages in affordability and governance, while also revealing deficiencies in project efficiency and technical oversight. The study concludes that FAM substantially contributes to value for money in Tanzania’s public construction sector. However, enhancements in institutional capacity, standardized guidelines, and monitoring mechanisms are necessary to address persistent challenges related to quality and timeliness. The findings offer actionable insights for policymakers, regulatory authorities, and practitioner aiming to improve the effectiveness of FAM in achieving sustainable infrastructure development.Item Assessment of Scouring Effect of Msingi Masonry Arch Bridge in Mkalama, Singida, Tanzania(ABUAD Journal of Engineering Research and Development (AJERD), 2025) BARTHAZAR, Dickson; KATAMBARA, Zakaria; KIFANYI, Gislar.This study presents an integrated geotechnical and hydraulic assessment of the Msingi Masonry Arch Bridge in Mkalama District, Singida, Tanzania, to evaluate scour vulnerability, subsurface strength, and structural load capacity. Field investigations included Dynamic Probing Light (DPL) testing, core sampling, and particle size analysis at six test pits (DS1–DS6), alongside laboratory tests adhering to BS 1377:1990 standards. Results revealed significant spatial variability in soil gradation and compaction, with deeper layers demonstrating high bearing capacities (up to 1555.8 kN/m²), while surface strata exhibited loose conditions and higher susceptibility to erosion—particularly in zones with elevated fines content. Hydraulic modelling, using site-specific parameters such as hydraulic radius (1.88 m), channel slope (0.0082), and Manning’s coefficient (0.017), predicted a scour depth of 2.6 m, compared to the observed 2.0 m. Structural analysis using the MEXE method yielded an allowable axle load of 28.05 tonnes, translating to a foundation pressure of 98.6 kN/m², which is within safe soil capacity limits. Despite current structural stability, the narrow scour margin and near-threshold loading conditions indicate elevated long-term vulnerability. The study recommends immediate installation of scour countermeasures, selective foundation deepening in weak zones, and routine monitoring to enhance the resilience and longevity.Item Evaluating the hydraulic performance and sustainability of the Simike–Nzovwe roadside drainage system in Mbeya City, Tanzania, using the hydrologic engineering centre’s river analysis system modeling(ACCSCIENCE, 2025-07-21) Abdul Mohamed; Zacharia KatambaraThis study addresses the hydraulic inefficiencies and maintenance challenges associated with the roadside drainage system along a 1.85 km stretch of the TANZAM Highway between Simike and the Nzovwe River, which includes five circular culverts. The objective was to evaluate the system’s hydraulic performance under rainfall events using the Hydrologic Engineering Centre’s River Analysis System (HEC-RAS) one-dimensional hydraulic model. Specifically, the study focused on analyzing flow regimes, specific energy transitions, and sediment transport dynamics to identify critical points of inefficiency. The methodology involved simulating steady flow conditions, assessing the influence of channel and culvert geometry, and performing a sensitivity analysis on key hydraulic parameters, including Manning’s roughness coefficient, channel slope, and culvert dimensions. The model results revealed that subcritical flow conditions (Froude number, Fr <1) upstream of culverts lead to sediment accumulation, while steeper channel sections with supercritical flow (Fr >1) pose erosion risks. Pronounced hydraulic jumps were observed near culvert outlets, resulting in significant turbulence, abrupt energy dissipation, and localized erosion. Flow velocities decreased sharply from over 7 m/s to below 1 m/s across these transition zones. This study provides an integrated evaluation of hydraulic and sediment transport interactions in a real-world drainage system using HEC-RAS, supported by targeted design optimization strategies. Key recommendations include modifying side slope geometry, increasing longitudinal gradients, and enlarging culvert dimensions to enhance flow capacity and reduce sediment deposition. In addition, the application of riprap in high-velocity zones, vegetative lining in low velocity areas, and the inclusion of sediment traps are proposed to control erosion and minimize maintenance.Item Determinants of Students’ Performance in Electrical and Electronics Engineering at Mbeya University of Science and Technology, Tanzania(G-Card, 2025) Katambara, ZachariaThe Electrical and Electronics Engineering Program Requires a Balance Between Theoretical Knowledge and Practical Application, Making Students’ Performance Optimization Essential in Meeting Industry Demands. this Study Utilized Descriptive Statistics, Pearson Correlation Analysis, and Principal Component Analysis (PCA) to Evaluate Academic Performance in the EEE Program at Mbeya University of Science and Technology (MUST). by Examining 16 Core Courses, the Study Identified Key Determinants of Students’ Success, Course Interdependencies and Areas for Curriculum Enhancement. Descriptive Statistics Revealed Significant Variability in Performance, with EE 8401 (Industrial Practical Training 3) Recording the Highest Mean (79.98) and EE 8402 (Phase AC Synchronous Machines) the Lowest (48.11), Highlighting Disparities in Instructional Effectiveness. Pearson Correlation Analysis Shows Strong Correlations Among Theoretically Aligned Courses, Moderate Correlations Among Related Subjects, and Weak or Negative Correlations in Distinct Learning Domains, Emphasizing the Need for Targeted Interventions and Curriculum Adjustments. PCA Findings Confirmed that Three Principal Components Explained 58.85% of the Variance, Representing Theoretical Foundations, Applied Project-Based Learning and Specialized Hands-on Training. Scree Plot and Eigenvalue Analysis Validated Dimensionality Reduction, Enhancing Data Interpretation. Principal Component Loadings Highlight Academic Constructs, With PC1 Reflecting Analytical Competencies, PC2 Capturing Project-Based Courses and PC3 Representing Specialized Training. This Study Recommends Aligning Theoretical Courses with Standardized Assessments, Integrating Industry Collaborations in Project-Based Learning and Refining Assessment Models for Specialized Training. Future Research should Explore Longitudinal Trends in Principal Components, External Influences on High-Uniqueness Courses and Students’ Feedback Integration. by Implementing Data-Driven Strategies, Institutions can Refine Engineering Curricula, Bridge Performance Gaps and Enhance Student Success Outcomes.Item Effects of Innovation on Business Performance: Empirical Evidence from Manufacturing Firms in Tanzania(AJASSS, 2022-12-31) Athumani, Mwaifyusi Hussein; Kitwana, Dau RamadhaniRegardless of its relevance for business performance, the influence of innovation on the performance of manufacturing firms in Tanzania is not well documented. Thus, this study aimed to examine the effects of innovation on business performance of manufacturing firms in Tanzania. The study used cross-sectional design and quantitative approach. Copies of a structured questionnaire were administered to 420 participants from 28 manufacturing companies in Dar es Salaam and Coast Regions. An impressive response rate of 93.1% was achieved. Data were tested for reliability using Cronbach’s alpha coefficient. Tests for normality, multicollinearity and autocorrelation were conducted, and the results showed the data were reliable, normally distributed, free of multicollinearity and autocorrelation problems. Descriptive and multiple regression statistical techniques were employed. The results suggested that a significant positive effect existed between performance of manufacturing firms and product innovation (B=0.705, p=0.001), process innovation (B=0.640, p=0.000) and marketing innovation (B=.818, p=0.000). The obvious implication to industry is that innovation is important to business success of the manufacturing companies, thus the governments should motivate firms to innovate continuously by giving incentives to invest in R&D. Past studies linking innovation and performance have focused on financial measures of performance. The major contribution of the current study is to use non-financial measures of performance such as business growth and responsiveness to change.Item Investigation of Properties of Mbeya Pumice Lightweight Aggregates(ResearchGate, 2021-12-01) Shiganza,Oscar John; Mboya,Hieronimi Alphonce; Msambichaka,Joseph JohnThe properties of concrete depend partly on the type and mechanical properties of aggregates used in the concrete mix. The paper presents an investigation designed to study the properties of pumice lightweight aggregates and assess their suitability to structural lightweight concrete. The properties of pumice lightweight aggregates mainly aggregates shape, water absorption, specific gravity and organic impurities were examined. The results indicated that pumice lightweight aggregates have the flakiness and elongation close to upper limits as set by BS 812-105.1:1989 low density, high water absorption in comparison to normal weight aggregates, and are weather resistant. It was concluded that pumice lightweight aggregates are suitable for manufacture of structural lightweight concreteItem Influence of Number of Access Points for Fingerprinting Indoor Positioning Accuracy(International Journal of Research in Advanced Engineering and Technology, 2016-05) Mrindoko, Nicholaus R.The indoor positioning services based on fingerprinting mostly depend on the available access points in vicinity area. This paper explores the impact of number access points (APs) in indoor positioning accuracy based fingerprinting. The analysis is based on deterministic approach. The measurable analysis of test results demonstrates that, the positioning accuracy is highly affected by the number of access points. If the number of APs increased with well distribution positioning error is minimal. Hence, considering the adequate number of APs is guaranteeing an accuracy of an indoor positioning. The analysis could empower indoor positioning designer to enhance positioning performance and to model location fingerprinting based indoor positioning systemsItem Multivariate Analysis of Evaporation Drivers in Mbeya, Tanzania, Using Principal Component Analysis(ACCSCIENCE PUBLISHING, 2025-08-08) Katambara, ZachariaEvaporation is a vital process in the hydrological cycle, accounting for approximately 70% of water loss from the Earth’s surface. In semi-arid and rapidly urbanizing regions, such as Mbeya, Tanzania, understanding the meteorological drivers of evaporation is critical for water resource management and agricultural planning. This study utilized principal component analysis (PCA) on a 10-year dataset comprising solar radiation, sunshine hours, minimum and maximum temperatures, and wind speed to identify key factors influencing evaporation. Descriptive statistics revealed significant non-normality in most variables, particularly radiation and wind speed. At the same time, correlation analysis showed a strong positive relationship between sunshine hours and radiation (r = 0.66) and a moderate negative correlation between radiation and minimum temperature (r = −0.30). PCA identified two principal components accounting for 66.61% of the total variance. Component 1 (38.06%) captured solar-driven variability, dominated by sunshine duration and radiation, whereas Component 2 (28.55%) reflected thermal influences, particularly maximum and minimum temperatures. Wind speed contributed minimally, suggesting a more localized or less consistent role in evaporation dynamics. These findings demonstrate the value of PCA in simplifying complex climatic datasets and improving the interpretation of evaporation processes. Solar radiation and sunshine hours emerged as the dominant drivers, with temperature as a secondary influence. The results emphasize the need to integrate surface-level variables, such as land use, vegetation cover, and soil moisture, in future studies to capture spatial heterogeneity and improve predictive accuracy, especially in data-scarce, climate-sensitive regions like Mbeya.Item Synthetic Determination of Specific Density, Specific Surface Area and Particle Size Distribution of Cementitious Powder Materials(International Journal of Sciences: Basic and Applied Research (IJSBAR), 2018) Dr. Chengulaa, Duwa Hamisi; Prof. Msambichaka, Joseph J; Prof. Middendorf, BernhardThe use of cementitious materials for construction of buildings and structures started during ancient civilization. Science of modifying physical and chemical properties of cementitious materials is a continual process which is because of a need to increase reactivity and improve strength and durability properties of binders. Due to increasing demand of modern infrastructures and continual depleting of binder sources the scientist, engineers and researchers work hard on improving binding properties of cementitious materials for construction of low cost and durable structures. Among of the factors which affect binding properties of cementitious properties are densities, surface areas and particle size distribution. Several methods and procedures have been developed to determine these physical properties on which other require huge capital investment and others takes long time to complete a test which hinders further investigation and improvement of alternative binders. This study investigated that there exists an ‘S’ curve similar to particle size distribution curve when time air flow against weights of sample measured using Blaine apparatus is drawn.