Keakuratan Prediksi Inflow Waduk Dengan Neraca Air Waduk

Dalam perhitungan inflow waduk sering digunakan persamaan neraca air waduk yang menggunakan data seri laporan harian operasi waduk, evaporasi dan curah hujan diwaduk, dan lengkung H-V-A waduk. Pada pengamatan data series laporan harian operasi waduk dan pengukuran kapasitas tampungan waduk, dapat terjadi kesalahan yang disebabkan karena kesalahan faktor manusia maupun faktor alat, hal ini akan menyebabkan kesalahan pula pada besarnya inflow waduk yang dihasilkan. Lebih lanjut di dalam perencanaan, data series inflow waduk ini diperlukan sebagai input pada pemodelan optimasi operasi waduk dan sedimentasi waduk, sehingga keakuratan datanya sangat diperlukan. Tujuan penelitian ini adalah untuk mengevaluasi tingkat akurasi penggunaan neraca air waduk dalam memprediksi inflow waduk. Untuk mengetahui tingkat akurasi dilakukan dengan membandingkan antara inflow waduk dari anak sungai hasil pengukuran dan hasil hitungan dengan persamaan neraca air waduk. Kemudian dilakukan variasi periode pengukuran dan kurva H- V-A yang digunakan. Berdasarkan penelitian yang dilakukan maka pada periode perhitungan yang lebih lama menghasilkan tingkat error yang lebih kecil. Pemakaian kurva waduk yang berbeda menghasilkan inflow yang berbeda. Tingkat error yang didapat masih cukup besar, diatas 30 %, sehingga perhitungan inflow waduk dari anak sungai dengan menggunakan metode neraca air waduk kurang akurat. [Title: Accuracy of Reservoir Inflow Prediction Using Reservoir Water Balance] In the calculation of reservoir inflow often used reservoir water balance equation using the data series of daily reports reservoir operation, evaporation and precipitation, and H-V-A curve. In observation of the data series of daily reports of reservoir operation and measurement of reservoir storage capacity, the errors may occur due to human error factor and factor appliance. This will cause an error on the reservoir inflow generated. Further, in the planning, this series data of reservoir inflow is required as input to the modeling of reservoir operation optimization and reservoir sedimentation, so the accuracy of the data are required. The purpose of this study was to evaluate the use of the reservoir water balance accuracy rate in predicting inflow. To determine the level of accuracy, the effort is done by comparing the inflow tributary reservoirs of measurement and the count with the reservoir water balance. Then perform variations of the measurement period and curves H-V-A is used. Based on the research conducted in the period longer calculation produces a smaller error. The different H-V-A curve results in the different inflow. Error rate obtained is still quite large, above 30%, so the calculation of tributary inflow reservoirs using reservoir water balance method is less accurate.

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Reservoir Inflow Prediction by Employing Response Surface-Based Models Conjunction with Wavelet and Bootstrap Techniques

Mathematical Problems in Engineering ◽

10.1155/2021/4086918 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Muhammad Ahmed Shehzad ◽

Adnan Bashir ◽

Muhammad Noor Ul Amin ◽

Saima Khan Khosa ◽

Muhammad Aslam ◽

...

Keyword(s):

Response Surface ◽

Response Surface Model ◽

Series Data ◽

Surface Model ◽

First Order ◽

Daily Streamflow ◽

Quadratic Response Surface ◽

Quadratic Response ◽

Reservoir Inflow ◽

Inflow Prediction

Reservoir inflow prediction is a vital subject in the field of hydrology because it determines the flood event. The negative impact of the floods could be minimized greatly if the flood frequency is predicted accurately in advance. In the present study, a novel hybrid model, bootstrap quadratic response surface is developed to test daily streamflow prediction. The developed bootstrap quadratic response surface model is compared with multiple linear regression model, first-order response surface model, quadratic response surface model, wavelet first-order response surface model, wavelet quadratic response surface model, and bootstrap first-order response surface model. Time series data of monsoon season (1 July to 30 September) for the year 2010 of the Chenab river basin are analyzed. The studied models are tested by using performance indices: Nash–Sutcliffe coefficient of efficiency, mean absolute error, persistence index, and root mean square error. Results reveal that the proposed model, i.e., bootstrap quadratic response surface shows good performance and produces optimum results for daily reservoir inflow prediction than other models used in the study.

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A Method of Multi-Stage Reservoir Water Level Forecasting Systems: A Case Study of Techi Hydropower in Taiwan

Energies ◽

10.3390/en14123461 ◽

2021 ◽

Vol 14 (12) ◽

pp. 3461

Author(s):

Hao-Han Tsao ◽

Yih-Guang Leu ◽

Li-Fen Chou ◽

Chao-Yang Tsao

Keyword(s):

Water Level ◽

Reservoir Operation ◽

Flood Control ◽

Fuzzy Neural Networks ◽

Water Levels ◽

Hydropower Plant ◽

Extreme Weather Events ◽

Reservoir Water ◽

Multi Stage ◽

Reservoir Inflow

Reservoirs in Taiwan often provide hydroelectric power, irrigation water, municipal water, and flood control for the whole year. Taiwan has the climatic characteristics of concentrated rainy seasons, instantaneous heavy rains due to typhoons and rainy seasons. In addition, steep rivers in mountainous areas flow fast and furiously. Under such circumstances, reservoirs have to face sudden heavy rainfall and surges in water levels within a short period of time, which often causes the water level to continue to rise to the full level even though hydroelectric units are operating at full capacity, and as reservoirs can only drain the flood water, this results in the waste of hydropower resources. In recent years, the impact of climate change has caused extreme weather events to occur more frequently, increasing the need for flood control, and the reservoir operation has faced severe challenges in order to fulfil its multipurpose requirements. Therefore, in order to avoid the waste of hydropower resources and improve the effectiveness of the reservoir operation, this paper proposes a real-time 48-h ahead water level forecasting system, based on fuzzy neural networks with multi-stage architecture. The proposed multi-stage architecture provides reservoir inflow estimation, 48-h ahead reservoir inflow forecasting, and 48-h ahead water level forecasting. The proposed method has been implemented at the Techi hydropower plant in Taiwan. Experimental results show that the proposed method can effectively increase energy efficiency and allow the reservoir water resources to be fully utilized. In addition, the proposed method can improve the effectiveness of the hydropower plant, especially when rain is heavy.

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Macro Modeling of V-Shaped Electro-Thermal MEMS Actuator with Human Error Factor

Micromachines ◽

10.3390/mi12060622 ◽

2021 ◽

Vol 12 (6) ◽

pp. 622

Author(s):

Dongpeng Zhang ◽

Anjiang Cai ◽

Yulong Zhao ◽

Tengjiang Hu

Keyword(s):

Neural Network ◽

Simulation Model ◽

Bp Neural Network ◽

Human Error ◽

Calculation Model ◽

Fuzzy Mathematics ◽

Ansys Simulation ◽

Macro Modeling ◽

Error Factor ◽

Simulation Results

The V-shaped electro-thermal MEMS actuator model, with the human error factor taken into account, is presented in this paper through the cascading ANSYS simulation model and the Fuzzy mathematics calculation model. The Fuzzy mathematics calculation model introduces the human error factor into the MEMS actuator model by using the BP neural network, which effectively reduces the error between ANSYS simulation results and experimental results to less than 1%. Meanwhile, the V-shaped electro-thermal MEMS actuator model, with the human error factor included, will become more accurate as the database of the V-shaped electro-thermal actuator model grows.

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Effect of Pruning and Smoothing while Using M5 Model Tree Technique for Reservoir Inflow Prediction

Journal of Hydrologic Engineering ◽

10.1061/(asce)he.1943-5584.0000342 ◽

2011 ◽

Vol 16 (7) ◽

pp. 563-574 ◽

Cited By ~ 28

Author(s):

V. Jothiprakash ◽

Alka S. Kote

Keyword(s):

M5 Model Tree ◽

Model Tree ◽

Reservoir Inflow ◽

Inflow Prediction ◽

M5 Model

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Statistical Parametric Mapping Reveals Subtle Gender Differences in Angular Movements in Table Tennis Topspin Backhand

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17196996 ◽

2020 ◽

Vol 17 (19) ◽

pp. 6996

Author(s):

Ziemowit Bańkosz ◽

Sławomir Winiarski

Keyword(s):

Gender Differences ◽

Time Series Data ◽

Statistical Parametric Mapping ◽

Study Groups ◽

Series Data ◽

Data Series ◽

Table Tennis ◽

Parametric Mapping ◽

Analysis System ◽

Dorsal Flexion

Background: Statistical parametric mapping (SPM) is an innovative method based on the analysis of time series (data series) and is equivalent to statistical methods for numerical (discrete) data series. This study aimed to analyze the patterns of movement in the topspin backhand stroke in table tennis and to use SPM to compare these patterns between advanced female and male players. Methods: The research involved seven advanced male and six advanced female players. The kinematic parameters were measured using an inertial motion analysis system. The SPM was computed using the SPM1D Python package. Results: Our study made it possible to reproduce the pattern of movement in the joints during topspin backhand strokes in the studied athletes. During multiple comparisons, the analysis of variance (ANOVA) SPM test revealed many areas in the studied parameter series with statistically significant differences (p ≤ 0.01). Conclusions: The study presents the movement patterns in the topspin backhand shot and describes the proximal-to-distal sequencing principle during this shot. The SPM study revealed differences between men and women in the contribution of thoracic rotation, external shoulder rotation, dorsal flexion, and supination in the wrist during the hitting phase. These differences may result from the anatomical gender differences or variations in other functionalities of individual body segments between the study groups. Another possible source for these discrepancies may reside in tactical requirements, especially the need for a more vigorous attack in men. The gender differences presented in this study can help in the individualization of the training process in table tennis.

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Comparative evaluation of conceptual and physical rainfall–runoff models

Applied Water Science ◽

10.1007/s13201-019-1122-6 ◽

2020 ◽

Vol 10 (1) ◽

Cited By ~ 6

Author(s):

R. K. Jaiswal ◽

Sohrat Ali ◽

Birendra Bharti

Keyword(s):

Water Balance ◽

Swat Model ◽

Water Balance Model ◽

Optimization Techniques ◽

Balance Model ◽

Series Data ◽

Climatic Data ◽

Rainfall Runoff ◽

Tank Model ◽

Australian Water

AbstractThe design of water resource structures needs long-term runoff data which is always a problem in developing countries due to the involvement of huge cost of operation and maintenance of gauge discharge sites. Hydrological modelling provides a solution to this problem by developing relationship between different hydrological processes. In the past, several models have been propagated to model runoff using simple empirical relationships between rainfall and runoff to complex physical model using spatially distributed information and time series data of climatic variables. In the present study, an attempt has been made to compare two conceptual models including TANK and Australian water balance model (AWBM) and a physically distributed but lumped on HRUs scale SWAT model for Tandula basin of Chhattisgarh (India). The daily data of reservoirs levels, evaporation, seepage and releases were used in a water balance model to compute runoff from the catchment for the period of 24 years from 1991 to 2014. The rainfall runoff library (RRL) tool was used to set up TANK model and AWBM using auto and genetic algorithm, respectively, and SWAT model with SWATCUP application using sequential uncertainty fitting as optimization techniques. Several tests for goodness of fit have been applied to compare the performance of conceptual and semi-distributed physical models. The analysis suggested that TANK model of RRL performed most appropriately among all the models applied in the analysis; however, SWAT model having spatial and climatic data can be used for impact assessment of change due to climate and land use in the basin.

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Reconstructing Three Decades of Land Use and Land Cover Changes in Brazilian Biomes with Landsat Archive and Earth Engine

Remote Sensing ◽

10.3390/rs12172735 ◽

2020 ◽

Vol 12 (17) ◽

pp. 2735 ◽

Cited By ~ 16

Author(s):

Carlos M. Souza ◽

Julia Z. Shimbo ◽

Marcos R. Rosa ◽

Leandro L. Parente ◽

Ane A. Alencar ◽

...

Keyword(s):

Land Use ◽

Time Series ◽

Land Cover ◽

Time Series Data ◽

Google Earth ◽

Series Data ◽

Data Series ◽

Forest Conversion ◽

Pixel Resolution ◽

Historical Land Use

Brazil has a monitoring system to track annual forest conversion in the Amazon and most recently to monitor the Cerrado biome. However, there is still a gap of annual land use and land cover (LULC) information in all Brazilian biomes in the country. Existing countrywide efforts to map land use and land cover lack regularly updates and high spatial resolution time-series data to better understand historical land use and land cover dynamics, and the subsequent impacts in the country biomes. In this study, we described a novel approach and the results achieved by a multi-disciplinary network called MapBiomas to reconstruct annual land use and land cover information between 1985 and 2017 for Brazil, based on random forest applied to Landsat archive using Google Earth Engine. We mapped five major classes: forest, non-forest natural formation, farming, non-vegetated areas, and water. These classes were broken into two sub-classification levels leading to the most comprehensive and detailed mapping for the country at a 30 m pixel resolution. The average overall accuracy of the land use and land cover time-series, based on a stratified random sample of 75,000 pixel locations, was 89% ranging from 73 to 95% in the biomes. The 33 years of LULC change data series revealed that Brazil lost 71 Mha of natural vegetation, mostly to cattle ranching and agriculture activities. Pasture expanded by 46% from 1985 to 2017, and agriculture by 172%, mostly replacing old pasture fields. We also identified that 86 Mha of the converted native vegetation was undergoing some level of regrowth. Several applications of the MapBiomas dataset are underway, suggesting that reconstructing historical land use and land cover change maps is useful for advancing the science and to guide social, economic and environmental policy decision-making processes in Brazil.

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Failure Investigation on Rusty Mesh Strainer of Petrochemical Plant

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.795.488 ◽

2013 ◽

Vol 795 ◽

pp. 488-491 ◽

Cited By ~ 1

Author(s):

Shaiful Rizam Shamsudin ◽

Mohd Harun ◽

Mohd Arif Anuar Mohd Salleh ◽

Hafizal Yazid ◽

Mohd Noor Mazlee

Keyword(s):

Human Error ◽

Good Condition ◽

Wire Mesh ◽

Petrochemical Plant ◽

Root Cause ◽

Failure Investigation ◽

Error Factor ◽

The Wire ◽

The Impact ◽

Filter Mesh

The wire material of filter mesh is made of 304 grade stainless steel. The failure to run properly was due to the impact of burst and torn. The client also expects that the failure was due to corrosion problems. A visual inspection on the strainer mesh was found covered by brownish rust layers and some scratches at the damaged area. The rusty wire mesh that was washed with pickling acid showed a clean and smooth surface. Energy dispersive spectroscopy (EDS) examination of the rusty wire mesh surface indicated that it was only normal oxide precipitates. Thus, it's proven that there were no signs of severe corrosion attack on the failed sample. SEM micrographs showed the unidirectional scratch effects exist in the damaged area. The fractography study was found there was a typical ductile structure on the fracture surface of the wire. It is proven that the wire mesh was actually still in good condition and has not experienced any embrittlement problems as if it exposed to any corrosive environment. The root cause of the failure is shown by the effect of scratches in which it is usually caused by a mechanical forceful push by a hard object or in other words, it is caused by human error factor.

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