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Topic Review
Open BOK Context
A Body of Knowledge (BOK) is a concept used to represent concepts, terms, and activities that make up a professional domain. In addition, an Open BOK is necessary because it allows us to develop the abilities and talents of professionals in different Knowledge Areas (KAs).
  • 859
  • 02 Nov 2020
Topic Review
Rikhter R-23
The Rikhter R-23 is an aircraft autocannon developed for the Soviet Air Force starting in the late 1950s. It was designed to be as short as possible to avoid problems found on high-speed aircraft when the guns were pointed into the airstream. The R-23 was a gas operated revolver cannon that used gas bled from holes in the barrel to provide the motive force. Firing up to 2,600 rpm, the R-23 was the fastest firing single-barrel cannon ever introduced into service. The R-23 took some time to develop, and was not used operationally until 1964. It was used only in the tail turret of the Tu-22, and experimentally on the Salyut 3 space station. Its role was taken over by the twin-barrel Gryazev-Shipunov GSh-23. A modified version of the weapon was the only cannon to have been fired in space.
  • 859
  • 08 Nov 2022
Topic Review
Microgrids and Networked Microgrids
Microgrids and networked (interconnected) microgrids are emerging in developed countries as an efficient way for integrating distributed energy resources into power distribution systems. Microgrids and networked microgrids can disconnect from the main grid and operate autonomously, strengthen grid resilience, and help mitigate grid disturbances and maintain power quality. In addition, when supported by sophisticated management strategies, microgrids and networked microgrids have the ability to enhance power supply reliability.
  • 858
  • 21 Oct 2022
Topic Review
High-Altitude Wind Power
High-altitude wind power (HAWP) is the harnessing of the power of winds high in the sky by use of tether and cable technology. An atlas of the high-altitude wind power resource has been prepared for all points on Earth. A similar atlas of global assessment was developed at Joby Energy. The results were presented at the first annual Airborne Wind Energy Conference held at Stanford University by Airborne Wind Energy Consortium. Various mechanisms are proposed for capturing the kinetic energy of winds such as kites, kytoons, aerostats, gliders, gliders with turbines for regenerative soaring, sailplanes with turbines, or other airfoils, including multiple-point building- or terrain-enabled holdings. Once the mechanical energy is derived from the wind's kinetic energy, then many options are available for using that mechanical energy: direct traction, conversion to electricity aloft or at ground station, conversion to laser or microwave for power beaming to other aircraft or ground receivers. Energy generated by a high-altitude system may be used aloft or sent to the ground surface by conducting cables, mechanical force through a tether, rotation of endless line loop, movement of changed chemicals, flow of high-pressure gases, flow of low-pressure gases, or laser or microwave power beams.
  • 857
  • 24 Oct 2022
Topic Review
Artificial Neural Networks in Water Supply Systems Development
A water supply system is considered an essential service to the population as it is about providing an essential good for life. This system typically consists of several sensors, transducers, pumps, etc., and some of these elements have high costs and/or complex installation. The indirect measurement of a quantity can be used to obtain a desired variable, dispensing with the use of a specific sensor in the plant. Among the contributions of this technique is the design of the pressure controller using the adaptive control, as well as the use of an artificial neural network for the construction of nonlinear models using inherent system parameters such as pressure, engine rotation frequency and control valve angle, with the purpose of estimating the flow. 
  • 857
  • 27 May 2022
Topic Review
Short-Term Firm-Level Energy Consumption Forecasting
To minimise environmental impact, avoid regulatory penalties, and improve competitiveness, energy-intensive manufacturing firms require accurate forecasts of their energy consumption so that precautionary and mitigation measures can be taken. Deep learning is widely touted as a superior analytical technique to traditional artificial neural networks, machine learning, and other classical time series models due to its high dimensionality and problem solving capabilities. Despite this, research on its application in demand-side energy forecasting is limited. We compare two benchmarks (Autoregressive Integrated Moving Average (ARIMA), and an existing manual technique used at the case site) against three deep learning models (simple Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU)) and two machine learning models (Support Vector Regression (SVR), and Random Forest) for short term load forecasting (STLF) using data from a Brazilian thermoplastic resin manufacturing plant. We use the grid search method to identify the best configurations for each model, and then use Diebold-Mariano testing to confirm the results. Results suggests that the legacy approach used at the case site is the worst performing, and that the GRU model outperformed all other models tested.
  • 857
  • 23 Dec 2020
Topic Review
Micro combined heat and power
       Micro Combined Heat and Power (µCHP) systems in a DG infrastructure can reduce a building’s primary energy consumption, reduce carbon footprint, and enhance resiliency. The simultaneous production of electrical and thermal energy from a single fuel source at a high overall energy efficiency can reduce primary energy consumption while lowering greenhouse gas (GHG) emissions. A comprehensive overview of various modeling approaches adopted by international researchers is presented. The key objective is to present the state-of-the-art models and approaches while identifying opportunities for further refinement to expand the capabilities of such models for versatile applications.  
  • 857
  • 27 Aug 2020
Topic Review
Leaching
Leaching is the process of a solute becoming detached or extracted from its carrier substance by way of a solvent. Leaching is a naturally occurring process which scientists have adapted for a variety of applications with a variety of methods. Specific extraction methods depend on the soluble characteristics relative to the sorbent material such as concentration, distribution, nature, and size. Leaching can occur naturally seen from plant substances (inorganic and organic), solute leaching in soil, and in the decomposition of organic materials. Leaching can also be applied affectedly to enhance water quality and contaminant removal, as well as for disposal of hazardous waste products such as fly ash, or rare earth elements (REEs). Understanding leaching characteristics is important in preventing or encouraging the leaching process and preparing for it in the case where it is inevitable. In an ideal leaching equilibrium stage, all the solute is dissolved by the solvent, leaving the carrier of the solute unchanged. The process of leaching however is not always ideal, and can be quite complex to understand and replicate, and often different methodologies will produce different results.
  • 857
  • 15 Nov 2022
Topic Review
Structure-Borne Noise in Offshore Piling
The growing demand for renewable energy supply stimulates a drastic increase in the deployment rate of offshore wind energy. Offshore wind power generators are usually supported by large foundation piles that are driven into the seabed with hydraulic impact hammers or vibratory devices. The pile installation process, which is key to the construction of every new wind farm, is hindered by a serious by-product: the underwater noise pollution. 
  • 857
  • 14 Sep 2021
Topic Review
Optimizing Use of RTKLIB for Smartphone-Based GNSS Measurements
The Google Smartphone Decimeter Challenge (GSDC) was a competition held in 2021, where data from a variety of instruments useful for determining a phone’s position (signals from GPS satellites, accelerometer readings, gyroscope readings, etc.) using Android smartphones were provided to be processed/assessed in regard to the most accurate determination of the longitude and latitude of user positions. One of the tools that can be utilized to process the GNSS measurements is RTKLIB. RTKLIB is an open-source GNSS processing software tool that can be used with the GNSS measurements, including code, carrier, and doppler measurements, to provide real-time kinematic (RTK), precise point positioning (PPP), and post-processed kinematic (PPK) solutions.
  • 856
  • 30 May 2022
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