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For decades now, a lot of radio wave path loss propagation models have been developed for predictions across different environmental terrains. Amongst these models, empirical models are practically the most popular due to their ease of application. However, their prediction accuracies are not as high as required. Therefore, extensive path loss measurement data are needed to develop novel measurement-oriented path loss models with suitable correction factors for varied frequency, capturing both local terrain and clutter information, this have been found to be relatively expensive. In this paper, a large-scale radio propagation path loss measurement campaign was conducted across the VHF and UHF frequencies. A multi-transmitter propagation set-up was employed to measure the strengths of radio signals from seven broadcasting transmitters (operating at 89.30, 103.5, 203.25, 479.25, 615.25, 559.25 and 695.25 MHz respectively) at various locations covering a distance of 145.5 km within Nigerian urban environments. The measurement procedure deployed ensured that the data obtained strictly reflect the shadowing effects on radio signal propagation by filtering out the small-scale fading components. The paper also, examines the feasibilities of applying Kriging method to predict distanced-based path losses in the VHF and UHF bands. This method was introduced to minimize the cost of measurements, analysis and predictions of path losses in built-up propagation environments., Path loss measurement, Kriging Interpolation Method, prediction model, radio propagation

This study investigates the effect of varying test conditions including ambient temperature (19, 22, and 25 °C), mass charges of R600a refrigerant (40, 50, 60, and 70 g), and concentrations of TiO2 nanolubricant (0, 0.2 and 0.4 g/L) on the performance of a slightly modified 100g R134a domestic refrigeration system. The investigated parameters include evaporator air temperature, energy consumption, coefficient of performance, and second law efficiency of the system. The results showed that the performance of the refrigeration system at 0.2 and 0.4 g/L concentrations of TiO2 nanolubricant, improved at optimum ambient temperature and R600a mass charge conditions. At optimum conditions, the evaporator air temperature and energy consumption reduced within the range 5.26 to 26.32 %, and 0.13 to 14.09 % respectively, while the coefficient of performance and second law efficiency increased within the range 0.05 to 16.32 %, and 2.8 to 16 %, respectively. However, at other conditions (non-optimum), the energy consumption and evaporator air temperature were higher and within the range 0.28 to 8.26 %, and 5 to 40 % respectively, while the coefficient of performance and second law efficiency reduced within the range 2.99 to 10.94 %, and 0.55 to 13.43 % respectively. In conclusion, we observed variations in the performance of the refrigerator with varying test conditions., R600a, Refrigerator, TiO2 nanoparticle, ambient temperature.

The material selection process for producing a horizontal axis wind turbine blade for sustainable energy generation is a vital issue when using Nigeria as a case study. Due to the challenge faced with the low wind speed variations. However, this paper focuses on implementing MCDM for the material selection process for a suitable material for developing a horizontal wind turbine blade. This paper used a quantitative research approach using AHP and TOPSIS multi-criteria decision method. The study put into consideration the environmental conditions for the material selection process when designing the questionnaire. The authors extracted the data used for the selection process from the 130 research questionnaire distributed to materials engineers and renewable energy professionals. This research considered four alternatives that is, aluminum alloy, stainless steel, glass fiber, and mild steel to determine the best material for the wind turbine blade. Also, the model has four criteria and eight sub-criteria used for developing the pair-wise matrix and the performance score used for the ranking process of the alternatives. The result shows that a consistency index of 0.056 and a consistency ratio of 0.062 gotten via the AHP method is workable for material selection practice. 78%, 43%, 67%, and 25% are the performance scores for the four alternatives via the TOPSIS techniques. In conclusion, aluminum alloy is the best material, followed by glass fibre. Therefore, the decision-makers recommended aluminum alloy; hence, manufacturers should apply aluminum alloy to develop the wind turbine blade for sustainable energy generation., Materials science; Energy; Mechanical engineering; Environmental science; Wind turbine blade; Multi-criteria decision method; Analytical hierarchy process; TOPSIS techniques.