 | GOIT Jay PrakashDepartment of Mechanical Engineering Lecturer | ||
Last Updated :2024/05/19
Researcher Information
Degree
URL
J-Global ID
Research Interests
- Wind Energy Computational Fluid Dynamics Turbulence Fluid Mechanics
Research Areas
- Manufacturing technology (mechanical, electrical/electronic, chemical engineering) / Fluid engineering
Academic & Professional Experience
- 2021/04 - Today Kindai UniversityFaculty of Engineering Department of Mechanical EngineeringLecturer
- 2019/04 - 2021/03 Kindai UniversitySchool of Engineering, Department of Mechanical EngineeringAssistant Professor
- 2018/11 - 2019/03 National Institute of Advanced Industrial Science and Technology (AIST)Fukushima Renewable Energy Institute (FREA)Researcher
- 2017/04 - 2018/10 The University of TokyoCivil EngineeringProject Assistant Professor
- 2016/05 - 2017/03 The University of TokyoCivil EngineeringProject Researcher
- 2015/04 - 2016/03 Hitachi, LtdResearch & DevelopmentResearch Engineer
Education
- 2010/10 - 2015/03 KU Leuven Faculty of Engineering Science Mechanical Engineering
- 2009/04 - 2010/09 Tohoku University Graduate School of Engineering Mechanical System and Design
- 2005/04 - 2009/03 Tohoku University School of Engineering Mechanical and Aerospace Engineering
Association Memberships
Published Papers
- The Effect of Wind Turbine Sitting on the Power Output and Flow Fields of Offshore Wind FarmsJay Prakash Goi; Asim ÖnderJournal of Japan Wind Energy Association Japan Wind Energy Association 47 (2) 29 - 35 2023/08 [Refereed]
- Jay Prakash Goit; Asim ÖnderJournal of Renewable and Sustainable Energy AIP Publishing 14 (4) 043304 - 043304 2022/08 [Refereed]
Performance of offshore wind farms built in the nearshore region will be affected by onshore terrain with higher turbulence in the flow when wind is blowing from land toward sea. Current study employs large-eddy simulation to investigate the effect of coastal terrain on the performance of large nearshore offshore wind farms. At first, two atmospheric boundary layer (ABL) simulation cases are defined to investigate the evolution of an internal boundary layer (IBL) during the sea-to-land and land-to-sea transition of the flow. The growth rate of the IBL was similar for both ABL simulation cases. However, the mean velocity-based definition of IBL heights, which essentially are the equilibrium layer, were half the height of shear stress-based IBLs. The first wind farm simulation case only considers an offshore surface, while the second case includes the region with land-to-sea transition upstream of the wind farm. Better wake recovery is observed in the case that considers the effect of onshore terrain. This is attributed to the higher inflow turbulence level, which resulted in higher entrainment of kinetic energy from the flow above. The farm-induced IBL for a land-to-sea transition case shows rapid growth for the first few turbine rows, while the offshore only case shows gradual growth. However, the difference between the two IBLs decreases with downstream distance, implying that for sufficiently long wind farms, both IBLs will converge. Total power output of the land-to-sea transition case is 17% higher than the offshore only case for the farm layout and roughness heights considered in this study. - Jay Prakash Goit; Masakage Taguchi; Junya Tatsuno; Takatsugu KamedaWind Energy Wiley 25 (7) 1 - 16 1095-4244 2022/03 [Refereed]
In wind energy, the general practice in assessing the wind resource of a site is to employ a 10-min averaging to measured wind data. However, small wind turbines (SWTs) with rotor diameters <15 m will have a shorter response time scale; thus, an averaging time window of 10 min is too long for accurate wind resource assessments. The current study investigates the effect of averaging time windows on wind resource assessment and power estimation of SWTs. To that end, wind data from a 1-year measurement campaign is analysed using two short-term averaging windows of 30 and 60 s and two long-term averaging windows of 5 and 10 min. Although the average wind speed over the 1-year period is 1.3 m/s with all four windows, when wind speeds higher than 3 m/s are considered, the average wind speed obtained using a 30-s averaging window is 8% higher than that obtained using a 10-min window. Power prediction using the 10 kW SWT shows that the predicted power using a 30-s window is almost twice as large compared to that estimated using a 10-min window. Finally, the rotational speed of the SWT obtained with short-term averaging shows better agreement with that computed by direct modelling of the turbine with the measured wind speed as the input to the model. The study thus shows that the performance of SWTs will be better predicted if short-term averaging windows are used. - Kouki Iseri; Jay Prakash Goit; Takatsugu KamedaTransactions of the JSME The Japan Society of Mechanical Engineers 87 (895) 1 - 12 2021/04 [Refereed]
Drag and velocity measurement on a two-dimensional bluff body has been performed in a pulsatile flow. Circular and rectangular cylinders were selected in the present study. The projected width and length of the cylinders were d =30 mm and L =300 mm, respectively. The cycle-averaged velocity was 〈Vθ〉 ≅15 m/s and the amplitude was in the range of V′θm =0.45 to 3.6 m/s. The pulsation period of the flow was set in the range of T =1.5 to 10.0 s. The Reynolds number based on the phaseaveraged mean velocity and the projected width was in the range of Reθ =20000 to 40000. The cycle-averaged drag coefficient increases with the root mean value of the deviation from the cycle-averaged velocity of approaching flow to the cylinder. The cycle-averaged drag coefficient for T <6.0 s ( T〈Vθ〉/d <3.0× 103) increases compared with that estimated from the drag coefficient in the steady flow. For T ≥6.0 s ( T〈Vθ〉/d ≥3.0× 103), the drag coefficient of the steady flow can be used to calculate the cycle-averaged drag. The effect of the pulsation period on the phase-averaged drag occurs during temporal deceleration of the pulsatile flow and can be related with the increase of the velocity deficit and width in the wake behind the cylinder. The phase-averaged drag will be represented as the sum of the momentum deficit due to the phase-averaged flow, which contributes to the cycle-averaged drag, and the pressure gradient by the pulsatile flow. This can be formulated semi-empirically with the cycle-averaged value of the phase-averaged drag coefficient, phase-averaged velocity and the derivative of the pulsatile flow with respect to time.
- Jay Prakash Goit; Asim Önder22nd Australasian Fluid Mechanics Conference Australasian Fluid Mechanics Society (AFMS) AFMC2020 1 - 3 2020/12 [Refereed]
- Jay Prakash Goit; Atsushi Yamaguchi; Takeshi IshiharaAtmosphere MDPI 11 (5) 442 - 442 2020/04 [Refereed]
LiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models. - Susumu Shimada; Jay Prakash Goit; Teruo Ohsawa; Tetsuya Kogaki; Satoshi NakamuraRemote Sensing MDPI 12 (8) 1347 2020/04 [Refereed]
- Jay Prakash Goit; Takeshi IshiharaWind Energy Wiley 23 (3) 645 - 659 1095-4244 2020/03 [Refereed]
- Jay Prakash Goit; Susumu Shimada; Tetsuya KogakiEnergies 12 (19) 3680 2019/09 [Refereed]
- Jay Prakash Goit; Yifeng Liu; Takeshi IshiharaJournal of Physics: Conference Series IOP Publishing 1037 052019 - 052019 1742-6588 2018/06 [Refereed]
- Jay Prakash Goit; Atsushi Yamaguchi; Takeshi IshiharaJournal of Japan Wind Energy Association Japan Wind Energy Association 42 (1) 7 - 16 0387-6217 2018/06 [Refereed]
This study evaluates scanning Doppler Lidar-based wind field measurement and analysis techniques for wind energy applications. The Lidar measurements are first validated against measurements from existing V1 Lidar. It is found that the availability of 20% (30 data per 10 minutes) is sufficient to produce fairly good 10 minutes averaged wind speed and direction. The vertical profile measurements for wind blowing from land and that from sea are then performed using DBS configuration. The averaged wind speed for the former is lower than for the later. Two more scan modes, RHI and PPI, are employed to investigate the effect of coastal terrain on the near shore velocity profiles and to characterize the wind turbine wake. An internal boundary layer develops from the shore and persists up to 2000 m offshore. Lidar measurement data are also used to validate numerical simulations by a mesoscale model. The measured and predicted wind speeds agree well up to the height of 500 m. Finally, measurements of flow field around wind turbine shows the velocity deficit in the wind turbine wake and agree with those predicted by a wake model. - Jay Prakash Goit; Atsushi Yamaguchi; Takeshi IshiharaWind Europe Conference & Exhibition, Amsterdam, The Netherland 2017/11 [Refereed]
- Johan Meyers; Wim Munters; Jay Goit2016 AMERICAN CONTROL CONFERENCE (ACC) IEEE 519 - 524 0743-1619 2016 [Refereed]
A PDE-based optimization framework is presented that allows optimization of turbulent wind-farm boundary layers. It consists of a state-of-the-art large-eddy simulation code that allows the time-resolved simulation of the three-dimensional turbulent flow in the atmospheric boundary layer, together with the adjoint (backward) sensitivity equations to this nonlinear system of PDEs (i.e. the incompressible Navier-Stokes equations). Both the forward and the backward system are efficiently parallelized for supercomputing, and are combined with state-of-the-art gradient-based optimization methods. We use this tool to investigate the use of optimal coordinated control of wind-farm boundary-layer interaction with the aim of increasing the total energy extraction in wind farms. The individual wind turbines are considered as flow actuators and their energy extraction is dynamically regulated in time so as to optimally influence the flow field. Earlier work on wind-farm optimal control in the fully developed regime (Goit & Meyers 2015, J. Fluid Mech. 768, 550) is discussed, and extended towards wind farms in which inflow effects are important. - Jay P. Goit; Wim Munters; Johan MeyersENERGIES MDPI AG 9 (1) 1 - 20 1996-1073 2016/01 [Refereed]
We investigate the use of optimal coordinated control techniques in large eddy simulations of wind farm boundary layer interaction with the aim of increasing the total energy extraction in wind farms. The individual wind turbines are considered as flow actuators, and their energy extraction is dynamically regulated in time, so as to optimally influence the flow field. We extend earlier work on wind farm optimal control in the fully-developed regime (Goit and Meyers 2015, J. Fluid Mech. 768, 5-50) to a finite' wind farm case, in which entrance effects play an important role. For the optimal control, a receding horizon framework is employed in which turbine thrust coefficients are optimized in time and per turbine. Optimization is performed with a conjugate gradient method, where gradients of the cost functional are obtained using adjoint large eddy simulations. Overall, the energy extraction is increased 7% by the optimal control. This increase in energy extraction is related to faster wake recovery throughout the farm. For the first row of turbines, the optimal control increases turbulence levels and Reynolds stresses in the wake, leading to better wake mixing and an inflow velocity for the second row that is significantly higher than in the uncontrolled case. For downstream rows, the optimal control mainly enhances the sideways mean transport of momentum. This is different from earlier observations by Goit and Meyers (2015) in the fully-developed regime, where mainly vertical transport was enhanced. - Jay P. Goit; Johan MeyersJOURNAL OF FLUID MECHANICS CAMBRIDGE UNIV PRESS 768 5 - 50 0022-1120 2015/04 [Refereed]
In very large wind farms, the vertical interaction with the atmospheric boundary layer plays an important role, i.e. the total energy extraction is governed by the vertical transport of kinetic energy from higher regions in the boundary layer towards the turbine level. In the current study, we investigate optimal control of wind-farm boundary layers, considering the individual wind turbines as flow actuators, whose energy extraction can be dynamically regulated in time so as to optimally influence the flow field and the vertical energy transport. To this end, we use large-eddy simulations of a fully developed pressure-driven wind-farm boundary layer in a receding-horizon optimal control framework. For the optimization of the wind-turbine controls, a conjugate-gradient optimization method is used in combination with adjoint large-eddy simulations for the determination of the gradients of the cost functional. In a first control study, wind-farm energy extraction is optimized in an aligned wind farm. Results are accumulated over one hour of operation. We find that the energy extraction is increased by 16% compared to the uncontrolled reference. This is directly related to an increase of the vertical fluxes of energy towards the wind turbines, and vertical shear stresses increase considerably. A further analysis, decomposing the total stresses into dispersive and Reynolds stresses, shows that the dispersive stresses increase drastically, and that the Reynolds stresses decrease on average, but increase in the wake region, leading to better wake recovery. We further observe also that turbulent dissipation levels in the boundary layer increase, and overall the outer layer of the boundary layer enters into a transient decelerating regime, while the inner layer and the turbine region attain a new statistically steady equilibrium within approximately one wind-farm through-flow time. Two additional optimal control cases study penalization of turbulent dissipation. For the current wind-farm geometry, it is found that the ratio between wind-farm energy extraction and turbulent boundary-layer dissipation remains roughly around 70 %, but can be slightly increased by a few per cent by penalizing the dissipation in the optimization objective. For a pressure-driven boundary layer in equilibrium, we estimate that such a shift can lead to an increase in wind-farm energy extraction of 6 %. - Optimal control of energy extraction in large-eddy simulation of wind farmsJay Prakash GoitKU Leuven 2015/03 [Refereed]
- Jay P Goit; Johan Meyers32nd ASME Wind Energy Symposium, American Institute of Aeronautics and Astronautics (AIAA) SciTech Forum 2014/01 [Refereed]
- Jay P. Goit; Johan MeyersSCIENCE OF MAKING TORQUE FROM WIND 2014 (TORQUE 2014) IOP PUBLISHING LTD 524 012178 1742-6588 2014 [Refereed]
In the present work our focus is to improve the performance of a wind farm by coordinated control of all turbines with the aim to increase the overall energy extraction by the farm. To this end, we couple flow simulations performed using Large Eddy Simulations (LES) with gradient based optimization to control individual turbines in a farm. The control parameters are the disk-based thrust coefficient of individual turbines as a function of time. They indirectly represent the effect of control actions that would correspond to blade-pitching of the turbines. We employ a receding-horizon predictive control setting and solve the optimization problem iteratively at each time horizon based on the gradient information obtained from the evolution of the flow field and the adjoint computation. We find that the extracted farm power increases by approximately 16% for a cost functional that is based on total energy extraction. However, this energy is gained from a slow deceleration of the boundary layer which is sustained for approximately 1 hour. We further analyze the turbulent stresses and compare to wind farms without optimal control. - J.P. Goit; J. MeyersDirect and large eddy simulation IX, Dresden, Germany 20 423 - 434 2012/09 [Refereed]
- Julia Sternberg; Jay Goit; Sébastien Gros; Johan Meyers; Moritz Diehl15th International Federation of Automatic Control (IFAC) workshop on Control Applications of Optimization 140 - 145 2012/09 [Refereed]
- Prediction of transition point by estimating flow instability with nonlinear effectGoit Jay PrakashTohoku University 2010/09 [Refereed]
Conference Activities & Talks
- Reproducibility of the internal boundary layer over nearshore waters using LES [Not invited]Taiga Manabe; Teruo Ohsawa; Jay Prakash Goi; Mizuki Konagaya; Kohei Hamada; Ryuzo Araki45th Wind Energy Symposium of Japan Wind Energy Association 2023/12
- Jay Prakash Goi; Takatsugu KamedaInternational Conference on Green Energy Computing and Intelligent Technology 2023/07 Johor University of Southampton, Malaysia
- Effect of three-dimensional roughness to mean velocity profile for a two-dimensional turbulent channel flow [Not invited]Hiroki Sunakawa; Takatsugu Kameda; Jay Prakash Goi61st JSME Chugoku Shikoku Meeting 2023/03 Japan Society of Mechanical Engineers
- Evaluation of Scanning Doppler LiDAR-based wind measurements using LES: Effect of wind direction and elevation angle [Not invited]Masakage Taguchi; Jay Prakash Goi; Takatsugu Kameda61st JSME Chugoku Shikoku Meeting 2023/03 Japan Society of Mechanical Engineers
- Evaluation of an Aeroelastic Model of a Medium-sized Utility Scale Wind Turbine [Not invited]Shotaro Kuroda; Jay Prakash Goi; Motofumi Tanaka; Noritsugu Kubo53rd JSME Chugoku Shikoku Student Meeting 2023/03 Japan Society of Mechanical Engineers
- Comparison of aerodynamic characteristics of upwind and downwind wind turbines in wind tunnel experiments [Not invited]Satoshi Goi; Jay Prakash Goi; Takatsugu Kameda53rd JSME Chugoku Shikoku Student Meeting 2023/03 Japan Society of Mechanical Engineers
- Low altitude field experiment of balloon-based airborne wind resource measurement system [Not invited]Yiqi Dai; Jay Prakash Goi; Takatsugu Kameda53rd JSME Chugoku Shikoku Student Meeting 2023/03
- Jay Prakash Goi; Asim ÖnderGrand Renewable Energy International Conference (GRE2022) 2022/12
- The effect of Wind Turbine Layout on the performance of Offshore Wind Farms [Not invited]Jay Prakash Goi; Asim Önder23nd Australasian Fluid Mechanics Conference 23AFMC 2022/12 Sydney Australasian Fluid Mechanics Society
- Wind Tunnel Experiments of Upwind and Downwind Wind Turbines [Not invited]Jay Prakash Goi; Takatsugu Kameda44th Wind Energy Symposium of Japan Wind Energy Association 2022/12 Tokyo Japan Wind Energy Association
- Reconstruction and Evaluation of LiDAR-based Wind Field Measurements using LES: Effect of wind direction and elevation angle [Not invited]Masakage Taguchi; Jay Prakash Goi; Takatsugu Kamada44th Wind Energy Symposium of Japan Wind Energy Association 2022/12 Tokyo Japan Wind Energy Association
- Towards the Realization of a Fully Submerged Floaters for Extremely Large Wind Turbine [Not invited]Kazuyoshi Miyoshi; Jay Prakash Goi44th Wind Energy Symposium of Japan Wind Energy Association 2022/12 Tokyo Japan Wind Energy Association
- Wind speed characterization of active turbulence generators installed upstream and downstream of the wind tunnel test section [Not invited]Jay Prakash Goi; Takatsugu KamedaJSME Mechanical Engineering Congress 2022 2022/09
- Large-eddy Simulation Study of the Effect of Coastal Terrain on the Power Output and the Flow Fields of Nearshore Offshore Wind Farms [Not invited]Jay Prakash Goit60th JSME Chugoku Shikoku Meeting 2022/03
- Evaluation of Scanning Doppler LiDAR-based wind measurements using LES [Not invited]Masakage Taguchi; Jay Prakash Goit; Susumu Shimada; Takatsugu Kameda60th JSME Chugoku Shikoku Meeting 2022/03
- Effect of mesh roughness in two-dimensional turbulent channel flow [Not invited]Hiroki Sunakawa; Takatsugu Kameda; Jay Prakash Goit60th JSME Chugoku Shikoku Meeting 2022/03
- The Evaluation of around Upwind and Downwind Wind Turbine using Large-Eddy Simulation [Not invited]Michihiro Hakoda; Jay Prakash Goit52nd JSME Chugoku Shikoku Student Meeting 2022/03
- Evaluation of a Single LiDAR-based wind measurements using LES [Not invited]Masakage Taguchi; Jay Prakash Goit; Susumu Shimada; Takatsugu Kameda28th JSFM Chusikoku-Kyushu Meeting 2021/11
- The Effect of Wind Turbine Sitting on the Power Output and Flow Fields of Offshore Wind Farms [Not invited]Jay Prakash Goit; Asim Onder43rd Wind Energy Symposium of Japan Wind Energy Association 2021/11
- Reconstruction and Evaluation of LiDAR-based Wind Field Measurements using LES [Not invited]Masakage Taguchi; Jay Prakash Goit; Susumu Shimada; Takatsugu Kameda43rd Wind Energy Symposium of Japan Wind Energy Association 2021/11
- Effect of Roughness Pitch Ratio for a Channel Flow with Roughness Elements on One Wall [Not invited]Takatsugu Kameda; Shinsuke Mochizuki; Jay Prakash GoitJSME 99th Fluid Mechanics Division Meeting 2021/11
- Comparison of the performance of upwind and downwind wind turbines in wind tunnel experiments [Not invited]Jay Prakash Goit; Takatsugu KamedaJSME Mechanical Engineering Congress 2021 2021/09
- The effect of wind turbine sitting on the performance of offshore wind farms [Not invited]Jay Prakash Goit; Asim OnderJSME Mechanical Engineering Congress 2021 2021/09
- Design of an active turbulence generator for reproduction of atmospheric flow and evaluation of its response characteristics [Not invited]Yasuhiro Ugumori; Reo Uematsu; Kento Yamashita; Jay Prakash Goit; Takatsugu KamedaJSME Chyugoku Sikoku Student Meeting 2021/03
- Comparison of upwind and downwind wind turbines in wind tunnel experiments [Not invited]Hiroki Sunakawa; Naoyuki Kageoka; Jay Prakash GoitJSME Chugoku Sikoku 51 Student Meeting 2021/03
- Conceptual design and analysis of a 20-seat small electric aircraft [Not invited]Akihide Fukuhara; Jay Prakash GoitJSME Chyugoku Sikoku Student Meeting 2021/03
- A method of estimating averaging time wind resource assessment for small wind turbines [Not invited]Masakage Taguchi; Jay Prakash Goit; Junya Tatsuno42nd Wind Energy Symposium of Japan Wind Energy Association 2020/11
- Analysis of Flow Fields and Power Outputs in Nearshore Offshore Wind Farms [Not invited]Jay Prakash Goit; Asim Önder42nd Wind Energy Symposium of Japan Wind Energy Association 2020/11
- The effect of onshore coastal terrain on performance of offshore wind farms [Not invited]Jay Prakash Goit; Asim ÖnderAnnual Meeting of the Japan Society of Fluid Mechanics 2020 2020/09
- Flow field analysis in nearshore offshore wind farms [Not invited]Jay Prakash Goit; Asim ÖnderJSME Mechanical Engineering Congress 2020/09 The Japan Society of Mechanical Engineers
- A Simulation Framework for Upscaling of Wind Turbine Designs [Not invited]Jay Prakash Goit; Asim Önder41st Wind Energy Symposium of Japan Wind Energy Association, Tokyo 2019/12
- Accuracy of Wind Turbine Power and Loads Estimated from LiDAR-measured Wind Speeds [Not invited]Jay Prakash Goit; Susumu Shimada; Tetsuya Kogaki41st Wind Energy Symposium of Japan Wind Energy Association, Tokyo 2019/12
- Evaluation of Long-term Measurement of Wind Speed and Turbulence using Doppler Lidar [Not invited]Jay Prakash Goit; Susumu Shimada; Tetsuya KogakiJSME 97th Fluid Engineering Division Conference 2019/11
- Reliability of Long-term Lidar-based Wind Measurements for Various Wind Energy Applications [Not invited]Jay Prakash Goit; Susumu Shimada; Tetsuya Kogaki72nd Annual Meeting of the APS Division of Fluid Dynamics 2019/11 Seattle, Washington, USA
- Effect of turbulence intensities on pressure distribution of wind turbine nacelles in wind tunnel experiment [Not invited]Yifeng Liu; Jay Prakash Goit; Takeshi IshiharaGrand Renewable Energy 2018 2018/06
- Jay Prakash Goit; Yifeng Liu; Takeshi Ishihara39th Wind Energy Symposium of Japan Wind Energy Association, Tokyo 2017/12
- Measurement and Analysis of Wind Speed using Scanning Doppler Lidar for Wind Energy Application [Not invited]Jay Prakash Goit; Atsushi Yamaguchi; Takeshi IshiharaAnnual Meeting of the Japan Society of Fluid Mechanics 2017 2017/08
- Jay Prakash Goit; Atsushi Yamaguchi; Takeshi Ishihara38th Wind Energy Symposium of Japan Wind Energy Association, Tokyo, pp. 419-422 2016/11
- Optimal coordinated control of energy extraction in LES of wind farms: effect of turbine arrangement patterns [Not invited]Johan Meyers; Wim Munters; Jay Goit68th Annual meeting of the American Physics Society (APS) Division of Fluid Dynamics, Boston, MA, USA 2015/11
- Johan Meyers; Jay Goit; Wim Munters67th Annual meeting of the American Physics Society (APS) Division of Fluid Dynamics, San Francisco, CA, USA 2014/11
- Jay P Goit; Johan MeyersEuropean Geosciences Union General Assembly, Vienna, Austria 2014/04
- Johan Meyers and Jay; Prakash Goit66th Annual meeting of the American Physics Society (APS) Division of Fluid Dynamics, Pittsburg, PA, USA 2013/11
- Jay Prakash Goit; Joris Coddé; Hans Robeers; Johan Meyers64th Annual meeting of the American Physics Society (APS) Division of Fluid Dynamics, Baltimore, MD, USA 2011/11
- Prediction of Transition Point by Pursuing Local Growth of Instability Waves [Not invited]Jay Prakash Goit; Masaya Shigeta; Seiichiro Izawa; Yu FukunishiAnnual Meeting of the Japan Society of Fluid Mechanics 2010 2010/09
- Design of a SmalI Gust Wind TunnelJay Prakash Goit; Masaya Shigeta; Seiichiro Izawa; Yu FukunishiThe Japan Society of Mechanical Engineers 2009/03
MISC
- Jay Prakash Goit; 田口 誠景; 樹野 淳也 日本風力エネルギー学会 特集：風力エネルギーの基礎―小型風車開発 45- (137) 52 -55 2021/06
- A method for the design of a scaled wind turbine for wind tunnel experimentsJay Prakash Goit Kindai University Fundamental Technology for Next Generation Research Institute Annual Report 11- 75 -79 2020/07
- 田口誠景; GOIT Jay Prakash; 樹野淳也 風力エネルギー利用シンポジウム 42nd (CD-ROM)- 2020
- スキャニングドップラーライダーのスキャン法Jay Prakash Goit 日本風力エネルギー学会 特集：風況測定用LIDAR技術特殊 43- (2) 209 -211 2019/08
- Ishihara Takeshi; YAMAGUCHI Atsushi; GOIT Jay Prakash; TANEMOTO Jun Summaries to Technical Papers of Annual Meeting, Japan Association for Wind Engineering 2017- 87 -88 2017
- ゴイト ジェイ プラカス; 山口 敦; 石原 孟 Proceedings of Japan Wind Energy Symposium 38- 213 -216 2016
Industrial Property Rights
Awards & Honors
- 2023/11 Japan Wind Energy Association 2023 Japan Wind Energy Association Research Award
The effect of coastal terrain on nearshore offshore wind farms: A large-eddy simulation study JPN受賞者: Jay Prakash Goit - 2023/07 International Conference of Green Energy Computing and Intelligent Technology (GEN-CITY), Malaysia Best Paper Award
Effect of Nacelle Shape on the Flow Fields of Upwind and Downwind Wind Turbines MYS international_society受賞者: Jay Prakash Goi;Takatsugu Kameda
Research Grants & Projects
- Development of a wind turbine layout optimization framework based on the interaction between offshore wind farm and atmospheric boundary layerJapan Society for the Promotion of Science Grants-in-Aid for Scientific Research：Grant-in-Aid for Scientific Research (C)Date (from‐to) : 2024/04 -2027/03Author : Jay Prakash Goi; Takatsugu Kameda
- Takahashi Industrial and Economic Research Foundation：Research FundDate (from‐to) : 2023/04 -2026/03Author : Jay Prakash Goit; Takatsugu Kameda
- Improvement of scanning Doppler LiDAR-based wind field measurement technology using large-eddy simulationAmano Institute of Technology：Research GrantDate (from‐to) : 2024/04 -2025/03Author : Jay Prakash Goi
- Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B)Date (from‐to) : 2022/04 -2025/03Author : 大澤 輝夫; 嶋田 進; 竹山 優子; Goit Jay Prakash
- Electric Technology Research Foundation of Chugoku：FY2020 Research FundDate (from‐to) : 2021/04 -2023/03Author : Jay Prakash Goit
- Development of a High Altitude Wind Measurement Technology for Offshore Wind Resource AssessmentFurukawa Technology Promotion Foundation：FY2021 Research FundDate (from‐to) : 2021/04 -2022/03Author : Jay Prakash Goit; Junya Tatsuno; Takatsugu Kameda
- Information Technology Center, The University of Tokyo：FY2020 Young Researchers Use of HPCDate (from‐to) : 2020/10 -2021/03Author : Jay Prakash Goit
- Development of turbulence generation and control system for experimental reproduction of environmental windSatake Technology Promotion Foundation：Date (from‐to) : 2020/06 -2021/03Author : Jay Prakash Goit; Takatsugu Kameda
- Comparison of the performance of upwind and downwind wind turbine configurations based on flow simulations and experimentsHirose International Scholarship Foundation：The 5th Research GrantDate (from‐to) : 2019/01 -2020/12Author : Goit Jay Prakash
- Optimization of wind farm layout using high fidelity flow simulation and optimization approachThe Hitachi Global Foundation：The 50th Kurata Grants (Fiscal Year 2018)Date (from‐to) : 2019/04 -2020/03Author : Goit Jay Prakash