ARCOM

Search or browse again.

Click on the titles below to expand the information about each abstract.
Viewing 15 results ...

Abdullahi, B, Ibrahim, Y M, Ibrahim, A and Bala, K (2019) Development of e-tendering evaluation system for Nigerian public sector. Journal of Engineering, Design and Technology , 18(01), 122–49.

Acheamfour, V K, Kissi, E, Adjei-Kumi, T and Adinyira, E (2019) Review of empirical arguments on contractor pre-qualification criteria. Journal of Engineering, Design and Technology , 18(01), 70–83.

Adu, E T and Opawole, A (2019) Assessment of performance of teamwork in construction projects delivery in South-Southern Nigeria. Journal of Engineering, Design and Technology , 18(01), 230–50.

Dadzie, J, Runeson, G and Ding, G (2019) Assessing determinants of sustainable upgrade of existing buildings. Journal of Engineering, Design and Technology , 18(01), 270–92.

Hellas, M S, Chaib, R and Verzea, I (2019) Artificial intelligence treating the problem of uncertainty in quantitative risk analysis (QRA). Journal of Engineering, Design and Technology , 18(01), 40–54.

Hulio, Z H and Jiang, W (2019) An assessment of effects of non-stationary operational conditions on wind turbine under different wind scenario. Journal of Engineering, Design and Technology , 18(01), 102–21.

• Type: Journal Article
• Keywords: Operational conditions; Component systems performance; Electrical machines and energy generation from renewable resources; Load distribution method; Non stationary; Wind loads; Drive train; Tangential force;
• ISBN/ISSN: 1726-0531
• URL: https://doi.org/10.1108/JEDT-12-2018-0222
• Abstract:
  The non-stationary operational wind loads vary in time and site and has remarkable effect on wind turbine drive train. The purpose of this paper is to determine the effects of wind class 3 and 7 on the life of wind turbine drive train. The two-wind class 3 and 7 are described by average wind speed and weight factor and effects of two variables on wind energy generation and wind turbine drive train studied. The load distribution method is used to calculate stress range cycles for wind class 3 and 7. To determine the rise of force on wind turbine drive train, the load cycle method is proposed. The fatigue damage model is studied with respect to influence of different wind speeds and wind shear factor and then results analysed accordingly. Also sensitivity analysis has been carried out to assess the percentage of drop of energy generation and rise of tangential force for wind class 3 and 7. Linear fit method is used to determine the inclination of wind variation and wind shear of wind class 3 and 7. In this regard, two practical wind sites fall under the wind class 3 and 7 and 1.5 MW wind turbine have been taken in to account. The results showed that the average rise of force on wind turbine drive train is 37.5% which can influence the drop in energy 34.7% for wind class 3. Similarly, the results of wind class 7 are showing that the average rise in force and drop in energy found to be 49.05% and 51.16%, respectively. The wind class 7 have higher tendency of wind fluctuations and weight factor that can cause a damage to wind turbine drive train components. The results showed that when wind speed increases to rated power 11.5 m/s the damages occurred and remain steady. Similarly, when weight factor increased from 0.18 to onwards the damage occurred. The increased wind loads increased the tangential loads on the wind turbine decreased life of the gearbox. The results of study suggest that wind turbine should be design according to site specific wind environment for maximum energy generation and lowers the wind loads on the drive train component.

Ibn Majdoub Hassani, Z, El Barkany, A, Jabri, A, El Abbassi, I and Darcherif, A M (2019) Hybrid approach for solving the integrated planning and scheduling production problem. Journal of Engineering, Design and Technology , 18(01), 172–89.

Luo, Z, Chen, Y, Cen, K, Pan, H, Zhong, M and He, J (2019) Research on comprehensive environmental impact assessment of shale gas development. Journal of Engineering, Design and Technology , 18(01), 1–20.

Mengistu, D G and Mahesh, G (2019) Dimensions for improvement of construction management practice in Ethiopian construction industry. Journal of Engineering, Design and Technology , 18(01), 21–39.

Neshat, N, Hadian, H and Rahimi Alangi, S (2019) Technological learning modelling towards sustainable energy planning. Journal of Engineering, Design and Technology , 18(01), 84–101.

Othman, A A E and Khalil, M H (2019) Divergent heritage sustainability: a threefold approach through lean talent management. Journal of Engineering, Design and Technology , 18(01), 150–71.

Patel, T D, Haupt, T C and Bhatt, T (2019) Fuzzy probabilistic approach for risk assessment of BOT toll roads in Indian context. Journal of Engineering, Design and Technology , 18(01), 251–69.

Soltani, M, Aouag, H and Mouss, M D (2019) An integrated framework using VSM, AHP and TOPSIS for simplifying the sustainability improvement process in a complex manufacturing process. Journal of Engineering, Design and Technology , 18(01), 211–29.

Syed Abu Bakar, S P, Jaafar, M and Muhibudin, M (2019) Intensifying business success of Malaysian housing development firms through entrepreneurial learning. Journal of Engineering, Design and Technology , 18(01), 190–210.

Yap, J B H and Toh, H M (2019) Investigating the principal factors impacting knowledge management implementation in construction organisations. Journal of Engineering, Design and Technology , 18(01), 55–69.