3D printed horn antenna using direct metal laser melting technique for millimetre wave applications

A 3D printed horn antenna at ka-band is presented in this paper. The horn antenna is well known for high gain performance. The performance of the horn antenna manufactured using 3D printed technology is investigated in this work. The horn is designed based on WR-28 waveguide standard. The proposed horn is simulated by computer simulation technology (CST) software and fabricated using 3D printing direct metal laser melting technique. The 3D printing technique gives the antenna an advantage of being not just rapid manufactured but also low-cost and lightweight. However, several works reported on 3D printed devices highlight the effects of surface roughness and dimensional tolerance on the performances. Therefore, the printed horn is profiled to correlate the surface roughness and dimension tolerance towards the performance. The printed horn is measured using standard VNA. The results showed that the measured performance agreed fairly with the simulation with directive radiation pattern at 15 dBi gain. The printed horn has a weight of less than 130g and considerably working at Ka band regardless of the surface roughness resulted from the fabrication process

Implementation of cryptography algorithms in SCADAKratos application

This paper studies cryptography algorithms to be implemented into the SCADAKratos application of thermal vacuum chamber (TVC) system. SCADAKratos application is used to control and monitor the operations of the TVC which is a satellite test equipment that is located at the Malaysia Space Centre, Banting, Malaysia. The security features had been put aside during the development as it was claimed that there is no threat to the system since the system is operated internally. However, during service and troubleshooting by the manufacturer, the system will be accessed through public network. Besides that, the system also can be accessed remotely during operation for control and monitoring purpose. In addition, the testing data results also need to be transferred to the customer through the internet as it is easier and faster. The remote access through public network will cause the TVC system to face a risk to any threat and attack. Therefore, the implementation of cryptography algorithm into TVC system is needed in order to secure and protect the system from unauthorized access. This paper explains the architecture of SCADAKratos application of TVC system and how the cryptography algorithms could be implemented through this application. Secure Hash Algorithm (SHA-1) and AES algorithm (AES) are chosen as the encryption technique which will be applied in the TVC system. Simulation result shows that this technique is feasible for the mentioned implementation

Improving total nitrogen removal using a neural network ammonia-based aeration control in activated sludge process

Aeration control is a way to have a wastewater treatment plant (WWTP) that uses less energy and produces higher effluent quality to meet state and federal regulations. The goal of this research is to develop a neural network (NN) ammonia-based aeration control (ABAC) that focuses on reducing total nitrogen and ammonia concentration violations by regulating dissolved oxygen (DO) concentration based on the ammonia concentration in the final tank, rather than maintaining the DO concentration at a set elevated value, as most studies do. Simulation platform used in this study is Benchmark Simulation Model No. 1, and the NN ABAC is compared to the Proportional-Integral (PI) ABAC and PI controller. In comparison to the PI controller, the simulation results showed that the proposed controller has a significant improvement in reducing the AECI up to 23.86%, improving the EQCI up to 1.94%, and reducing the overall OCI up to 4.61%. The results of the study show that the NN ABAC can be utilized to improve the performance of a WWTP’s activated sludge system

Proportional-Integral Ammonium-based Aeration Control for Activated Sludge Process

Most of the earlier research working on the aeration control of the activated sludge process (ASP) utilized the fixed dissolved oxygen (DO) concentration control strategy. This strategy typically works at elevated level of aeration to avoid nitrification failure and to meet biological oxygen demand (BOD) removal. The problem of elevated aeration is increased cost of aeration, which contribute the most to the total operation cost of wastewater treatment plant (WWTP). Some attempts have been made to solve this problem by utilizing aeration control that has a variation of the DO concentration using ammonium-based aeration control (ABAC) control strategy. The existing controller used is Proportional Integral (PI) controller, which the control gain is fixed. In this study, an adaptive feedback PI-ABAC is proposed using rule-based control technique. The performance assessment of the proposed controller was investigated by simulation using Benchmark Simulation Model No. 1 (BSM1) and the outcomes are compared with the static-gain benchmark-PI strategy. The proposed controller demonstrated better performance and as well as improved efficiency of nitrogen removal by 5.04%, reduced aeration energy by 1.51%, and reduced overall cost index by 0.30% when compared to static-gain benchmark PI controller

Improving total nitrogen removal using a neural network ammonia-based aeration control in activated sludge process

Aeration control is a way to have a wastewater treatment plant (WWTP) that uses less energy and produces higher effluent quality to meet state and federal regulations. The goal of this research is to develop a neural network (NN) ammonia-based aeration control (ABAC) that focuses on reducing total nitrogen and ammonia concentration violations by regulating dissolved oxygen (DO) concentration based on the ammonia concentration in the final tank, rather than maintaining the DO concentration at a set elevated value, as most studies do. Simulation platform used in this study is Benchmark Simulation Model No. 1, and the NN ABAC is compared to the Proportional-Integral (PI) ABAC and PI controller. In comparison to the PI controller, the simulation results showed that the proposed controller has a significant improvement in reducing the AECI up to 23.86%, improving the EQCI up to 1.94%, and reducing the overall OCI up to 4.61%. The results of the study show that the NN ABAC can be utilized to improve the performance of a WWTP’s activated sludge system