Fatigue Property of Additively Manufactured Ti-6Al-4V under Nonproportional Multiaxial Loading

The low cycle fatigue strength properties of the additively manufactured Ti-6Al-4V alloy are experimentally investi-gated under proportional and nonproportional multiaxial loading.The fatigue tests were conducted using hollow cylinder specimens with and without heat treatments,at room temperature in air.Two fatigue tests were conducted:one for proportional loading and one for nonproportional loading.The proportional loading was represented by a push-pull strain path(PP)and the nonproportional loading by a circle strain path(Cl).The failure lives of the additively manufactured specimens were clearly reduced drastically by internal voids and defects.However,the sizes of the defects were measured,and the defects were found not to cause a reduction in fatigue strength above a critical size.The fracture surface was observed using scanning electron microscopy to investigate the fracture mechanisms of the additively manufactured specimens under the two types of strain paths.Different fracture patterns were recognized for each strain paths;however,both showed retention of the crack propagation,despite the presence of numerous defects,probably because of the interaction of the defects.The crack propagation properties of the materials with numerous defects under nonproportional multiaxial loading were clarified to increase the reliability of the additively manufactured components.

Real-Time Control System Adopted to Energy Storage for Smart Grid Low Wind Applications:A Part of Distributed Renewables in Smart City

In this paper,extensive efforts have been undertaken to design and develop a control system,which is incorporated with an energy storage device that can store energy from low-voltage renewable sources.The developed device acts as a storage element,which can be used to charge small-scale batteries,cellular devices,and other applications in remote places where the grid connection is not available.The circuit is developed using a case-by-case analysis.In order to solve the low output voltage problem,a bipolar junction transistor-metal oxide semiconductor field-effect transistor(BJT-MOSFET)based switch control technology with the Arduino microcontroller has been implemented.The developed control system is extremely efficient in charging batteries through a supercapacitor for low-voltage sources.In this research,a small-scale 200-W portable vertical axis wind turbine is used at a wind speed of 3 m/s.The result shows the efficiency of the proposed system as compared with the conventional systems.The proposed system can be an important tool of the latest distributed energy generation technology which is an important part of a smart city.Lastly,the limitations and future scopes of the development of the control device are discussed for the future barrier.An important future scope identified is to integrate the Internet of Things based mobile interface for remote monitoring for any kind of pandemic situation like COVID-19.Now,it is high time to get our smart city concept aligned with the post COVID pandemic situation and get us prepared smartly for similar future occurrences.

Dual-Branch-UNet: A Dual-Branch Convolutional Neural Network for Medical Image Segmentation

In intelligent perception and diagnosis of medical equipment,the visual and morphological changes in retinal vessels are closely related to the severity of cardiovascular diseases(e.g.,diabetes and hypertension).Intelligent auxiliary diagnosis of these diseases depends on the accuracy of the retinal vascular segmentation results.To address this challenge,we design a Dual-Branch-UNet framework,which comprises a Dual-Branch encoder structure for feature extraction based on the traditional U-Net model for medical image segmentation.To be more explicit,we utilize a novel parallel encoder made up of various convolutional modules to enhance the encoder portion of the original U-Net.Then,image features are combined at each layer to produce richer semantic data and the model’s capacity is adjusted to various input images.Meanwhile,in the lower sampling section,we give up pooling and conduct the lower sampling by convolution operation to control step size for information fusion.We also employ an attentionmodule in the decoder stage to filter the image noises so as to lessen the response of irrelevant features.Experiments are verified and compared on the DRIVE and ARIA datasets for retinal vessels segmentation.The proposed Dual-Branch-UNet has proved to be superior to other five typical state-of-the-art methods.

Adaptive Noise Cancellation Algorithms Implemented onto FPGA-Based Electrical Impedance Tomography System

Electrical Impedance Tomography(EIT)as a non-invasive of electrical conductivity imaging method commonly employs the stationary-coefficient based filters(such as FFT)in order to remove the noise signal.In the practical applications,the stationary-coefficient based filters fail to remove the time-varying random noise which leads to the lack of impedance measurement sensitivity.In this paper,the implementation of adaptive noise cancellation(ANC)algorithms which are Least Mean Square(LMS)and Normalized Least Mean Square(NLMS)filters onto Field Programmable Gate Array(FPGA)-based EIT system is proposed in order to eliminate the time-varying random noise signal.The proposed method was evaluated through experimental studies with biomaterial phantom.The reconstructed EIT images with NLMS is better than the images with LMS by amplitude response AR=12.5%,position error PE=200%,resolution RES=33%,and shape deformation SD=66%.Moreover,the Analog-to-Digital Converter(ADC)performances of power spectral density(PSD)and the effective number of bit ENOB with NLMS is higher than the performances with LMS by SI=5.7%and ENOB=15.4%.The results showed that implementing ANC algorithms onto FPGA-based EIT system shows significantly more accurate image reconstruction as compared without ANC algorithms implementation.

Impact analysis of false data injection attacks on power system static security assessment

Static security assessment(SSA) is an important procedure to ensure the static security of the power system.Researches recently show that cyber-attacks might be a critical hazard to the secure and economic operations of the power system. In this paper, the influences of false data injection attack(FDIA) on the power system SSA are studied. FDIA is a major kind of cyber-attacks that can inject malicious data into meters, cause false state estimation results, and evade being detected by bad data detection. It is firstly shown that the SSA results could be manipulated by launching a successful FDIA, which can lead to incorrect or unnecessary corrective actions. Then,two kinds of targeted scenarios are proposed, i.e., fake secure signal attack and fake insecure signal attack. The former attack will deceive the system operator to believe that the system operates in a secure condition when it is actually not. The latter attack will deceive the system operator to make corrective actions, such as generator rescheduling, load shedding, etc. when it is unnecessary and costly. The implementation of the proposed analysis is validated with the IEEE-39 benchmark system.

Spatial investigation of the temporal urban form to assess impact on transit services and public transportation access

The rapid urban growth in developing city increases the requirement of the efficient and sustainable public transportation system.The urban growth affects the urban form,which indicates the change in human and urban development activity.Urban form affects directly and indirectly access to the public transportation system as an assessment of potential riders and proximity to stops increase transit services users.Therefore,access is one of the important aspects for the assessment of transit service efficiency.Public transportation access can be represented by a coverage area and useful to estimate potential riders of public transportation.In this study,a Geographical Information System(GIS)-based spatial statistical analysis method is used to examine the spatial relationship of different urban form indicators with population or riders of transit service in a coverage area and to ascertain how urban form influences public transportation trips in this coverage area.The coverage area is delineated using a GIS-based road/street network distance approach.The spatial analysis results suggested that urban forms have certain impact on trips in coverage area at both ward level and zone level.The statistical analysis implies that significant and positive values of spatial lag coefficient indicate a positive spatial interaction between wards and variable like total coverage area;worker density have shown positive and significant effects on trips of public transportation.