Horizontal Axis Wind Turbine Performance Analysis

The present work uses the method of Blade Element Momentum Theory as suggested by Hansen. The method applied to three blade models adopted from Rahgozar S. with the airfoil data used the data provided by Wood D. The wind turbine performance described in term of the thrust coefficient , torque coefficient  and the power coefficient  . These three coefficient can be deduced from the Momentum theory or from the Blade element Theory(BET).  The present work found the performance coefficient derived from the Momentum theory tent to over estimate. It is suggested to used the BET formulation in presenting these three coefficients. In overall the Blade Element Momentum Theory follows the step by step as described by Hansen  work well for these three blade models. However  a little adjustment on the blade data is needed. To the case of two bladed horizontal axis wind turbine, Hansen’s approach works well over if the blade radius is  the calculation should start from r = 0.1 &nbsp

Games engine in real world virtual reality application

The paper proposes the utilization and application of 3D Game Engine technology that prevails in computer games i.e. the First Person Shooter game genre, into developing a low cost and high performance real world Walkthrough Virtual Reality (VR) prototype application. This technique is proposed as a solution to the limitation of the widely used low cost VR technologies namely Virtual Reality Modelling Language (VRML) and 360° Panoramic View (based on Apple QuickTime VR)

Kaedah penyelesaian permasalahan dalam teknologi reality maya masa kini menggunakan enjin permainan komputer 3D

Before the 1990's Virtual Reality (VR)applications were limited to activities that were carried out by big-budgeted giant companies and the militaries. VR technologies such as VRML and Panoramic Imaging enable computer users to use VR applications either freely or at a very minimal cost. However,the two mentioned above have their own limitations. This paper discusses several issues pertaining to the limitations and proposes a method that can be used as an alternative in realizing VR application to be disseminated to all computer users. The method involves the use of a 30 computer game engine that exists in the First Person Shooter (FPS) computer game

Global, regional, and national consumption of animal-source foods between 1990 and 2018: findings from the Global Dietary Database

Background: Diet is a major modifiable risk factor for human health and overall consumption patterns affect planetary health. We aimed to quantify global, regional, and national consumption levels of animal-source foods (ASF) to inform intervention, surveillance, and policy priorities. Methods: Individual-level dietary surveys across 185 countries conducted between 1990 and 2018 were identified, obtained, standardised, and assessed among children and adults, jointly stratified by age, sex, education level, and rural versus urban residence. We included 499 discrete surveys (91·2% nationally or subnationally representative) with data for ASF (unprocessed red meat, processed meat, eggs, seafood, milk, cheese, and yoghurt), comprising 3·8 million individuals from 134 countries representing 95·2% of the world population in 2018. We used Bayesian hierarchical models to account for differences in survey methods and representativeness, time trends, and input data and modelling uncertainty, with five-fold cross-validation. Findings: In 2018, mean global intake per person of unprocessed red meat was 51 g/day (95% uncertainty interval [UI] 48–54; region-specific range 7–114 g/day); 17 countries (23·9% of the world's population) had mean intakes of at least one serving (100 g) per day. Global mean intake of processed meat was 17 g/day (95% UI 15–21 g/day; region-specific range 3–54 g/day); seafood, 28 g/day (27–30 g/day; 12–44 g/day); eggs, 21 g/day (18–24 g/day; 6–35 g/day); milk 88 g/day (84–93 g/day; 45–185 g/day); cheese, 8 g/day (8–10 g/day; 1–34 g/day); and yoghurt, 20 g/day (17–23 g/day; 7–84 g/day). Mean national intakes were at least one serving per day for processed meat (≥50 g/day) in countries representing 6·9% of the global population; for cheese (≥42 g/day) in 2·3%; for eggs (≥55 g/day) in 0·7%; for milk (≥245 g/day) in 0·3%; for seafood (≥100 g/day) in 0·8%; and for yoghurt (≥245 g/day) in less than 0·1%. Among the 25 most populous countries in 2018, total ASF intake was highest in Russia (5·8 servings per day), Germany (3·8 servings per day), and the UK (3·7 servings per day), and lowest in Tanzania (0·9 servings per day) and India (0·7 servings per day). Global and regional intakes of ASF were generally similar by sex. Compared with children, adults generally consumed more unprocessed red meat, seafood and cheese, and less milk; energy-adjusted intakes of other ASF were more similar. Globally, ASF intakes (servings per week) were higher among more-educated versus less-educated adults, with greatest global differences for milk (0·79), eggs (0·47), unprocessed red meat (0·42), cheese (0·28), seafood (0·28), yoghurt (0·22), and processed meat (0·21). This was also true for urban compared to rural areas, with largest global differences (servings per week) for unprocessed red meat (0·47), milk (0·38), and eggs (0·20). Between 1990 and 2018, global intakes (servings per week) increased for unprocessed red meat (1·20), eggs (1·18), milk (0·63), processed meat (0·50), seafood (0·44), and cheese (0·14). Interpretation: Our estimates of ASF consumption identify populations with both lower and higher than optimal intakes. These estimates can inform the targeting of intervention, surveillance, and policy priorities relevant to both human and planetary health. Funding: Bill & Melinda Gates Foundation and American Heart Association. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens