Prediction of River Discharge by Using Gaussian Basis Function

For design of water resources engineering related project such as hydraulic structures like dam, barrage and weirs river discharge data is vital. However, prediction of river discharge is complicated by variations in geometry and boundary roughness. The conventional method of estimation of river discharge tends to be inaccurate because river discharge is nonlinear but the method is linear. Therefore, an alternative method to overcome problem to predict river discharge is required. Soft computing technique such as artificial neural network (ANN) was able to predict nonlinear parameter such as river discharge. In this study, prediction of river discharge in Pari River is predicted using soft computing technique, specifically gaussian basis function. Water level raw data from year 2011 to 2012 is used as input. The data divided into two section, training dataset and testing dataset. From 314 data, 200 are allocated as training data and the remaining 100 are used as testing data. After that, the data will be run by using Matlab software. Three input variables used in this study were current water level, 1-antecendent water level, and 2-antecendent water level. 19 numbers of hidden neurons with spread value of 0.69106 was the best choice which creates the best result for model architecture after numbers of trial. The output variable was river discharge. Performance evaluation measures such as root mean square error, mean absolute error, correlation of efficiency (CE) and coefficient of determination (R2) was used to indicate the overall performance of the selected network. R2 for training dataset was 0.983 which showed predicted discharge is highly correlated with observed discharge value. However, testing stage performance is decline from training stage as R2 obtained was 0.775 consequently presence of outliers have affect scattering of whole data of testing and resulted in less accuracy as the R2 obtained much lower compared to training dataset. This happened because less number of input loaded into testing than training. RMSE and MSE recorded for training much lower than testing indicated that the better the performance of the model since the error is lesser. The comparison of with other types of neural network showed that Gaussian basis function is recommended to be used for river discharge prediction in Pari river

Aeronautical Engineering: A special bibliography with indexes, supplement 67, February 1976

This bibliography lists 341 reports, articles, and other documents introduced into the NASA scientific and technical information system in January 1976

Exploring the relationship between groundwater geochemical factors and denitrification potentials on a dairy farm in southeast Ireland

NOTICE: this is the author’s version of a work that was accepted for publication in the journal Ecological Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Ecological Engineering, volume 37, issue 9, September 2011, 1304-1313. DOI: 10.1016/j.ecoleng.2011.03.025peer-reviewedNitrate (NO3−) loss from agriculture to shallow groundwater and transferral to sensitive aquatic ecosystems is of global concern. Denitrifying bioreactor technology, where a solid carbon (C) reactive media intercepts contaminated groundwater, has been successfully used to convert NO3− to di-nitrogen (N2) gas. One of the challenges of groundwater remediation research is how to track denitrification potential spatially and temporally within reactive media and subsoil. First, using δ15N/δ18O isotopes, eight wells were divided into indicative transformational processes of ‘nitrification’ or ‘denitrification’ wells. Then, using N2/argon (Ar) ratios these wells were divided into ‘low denitrification potential’ or high denitrification potential’ categories. Secondly, using falling head tests, the saturated hydraulic conductivity (Ksat) in each well was estimated, creating two groups of ‘slow’ (0.06 m day−1) and ‘fast’ (0.13 m day−1) wells, respectively. Thirdly, two ‘low denitrification potential’ wells (one fast and one slow) with high NO3− concentration were amended with woodchip to enhance denitrification. Water samples were retrieved from all wells using a low flow syringe to avoid de-gassing and analysed for N2/Ar ratio using membrane inlet mass spectrometry. Results showed that there was good agreement between isotope and chemical (N2/Ar ratio and dissolved organic C (DOC)) and physio-chemical (dissolved oxygen, temperature, conductivity and pH) parameters. To explain the spatial and temporal distribution of NO3− and other parameters on site, the development of predictive models using the available datasets for this field site was examined for NO3−, Cl−, N2/Ar and DOC. Initial statistical analysis was directed towards the testing of the effect of woodchip amendment. The analysis was formulated as a repeated measures analysis of the factorial structure for treatment and time. Nitrate concentrations were related to Ksat and water level (p < 0.0001 and p = 0.02, respectively), but did not respond to woodchip addition (p = 0.09). This non-destructive technique allows elucidation of denitrification potential over time and could be used in denitrifying bioreactor technology to assess denitrification hotspots in reactive media, while developing a NO3− spatial and temporal predictive model for bioreactor site specific conditions

Aeronautical Engineering, a continuing bibliography with indexes

This bibliography lists 352 reports, articles and other documents introduced into the NASA scientific and technical information system in November 1983

Aeronautical Engineering: A continuing bibliography, supplement 120

This bibliography contains abstracts for 297 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1980

Modeling and Computation of the Maximum Braking Energy Speed for Transport Category Airplanes

Transport-category or FAR/CS 25 certified airplanes may occasionally become braking energy capacity limited. Such limitation may exist when heavy airplanes are departing airports at high-density altitudes, on relatively long runways, and/or possibly with some tailwind component. A maximum braking energy VMBE speed exists which may limit the maximum allowable takeoff decision/action speed V1. The ever-existing possibility of high-speed rejected takeoff in such conditions may also limit the airplane gross weight for declared available distances. To gain deeper insights and acquire better understanding of the topic, a theoretical model of the maximum braking energy and the related VMBE speed for T-category airplanes was developed. The total kinetic energy of an airplane includes translational and rotary kinetic energy and the potential height-energy component for sloped runways. Time-dependent airplanes’ mechanical power expression has been derived. Weight transfer during dynamic braking has been implemented in the full nonlinear model. Added mass due to rotary inertia of spinning components has been incorporated and assumed constant. The brakes thermal model is based on a lumped-parameter analysis of ventilated brake rotors and stators; the thermal model is based on a small Biot-number approximation and sufficiently well describes the physics of friction braking. The nonlinear differential equations of motion and the differential thermal model are coupled. A nonlinear model incorporating a set of ordinary differential equations with tire slip can be solved numerically. This model enables determination of the entire history of translational and angular accelerations and speeds, longitudinal distance, forces, torque, and disc temperature during braking. A simpler model assuming constant physical and thermodynamic parameters is solved analytically for constant negative acceleration. This linear analytical model has been used as a workhorse method in our calculations. A new semi-empirical expression of temperature-dependent friction coefficient on brake rotor-stator pairs has been proposed. A theoretical model of maximum braking energy speed VMBE, which includes density-altitude, runway slope, and wind effects as parameters, has been developed for the first time to the best of our knowledge. A comparison of the theoretical VMBE model showed good agreement with measured and approved data for the B737-400 airplane at different density altitudes with and without, individual and combined, runway slope and tailwind effects. Results for new and fully worn brakes were obtained showing the effect of elevated temperatures on brake fade and consequently braking time and distance

A literature survey of clear air turbulence

Literature survey on clear air turbulenc

The 1981 current research on aviation weather (bibliography)

Current and ongoing research programs related to various areas of aviation meteorology are presented. Literature searches of major abstract publications, were conducted. Research project managers of various government agencies involved in aviation meteorology research provided a list of current research project titles and managers, supporting organizations, performing organizations, the principal investigators, and the objectives. These are tabulated under the headings of advanced meteorological instruments, forecasting, icing, lightning and atmospheric electricity; fog, visibility, and ceilings; low level wind shear, storm hazards/severe storms, turbulence, winds, and ozone and other meteorological parameters. This information was reviewed and assembled into a bibliography providing a current readily useable source of information in the area of aviation meteorology