Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons™

Open Access. Powered by Scholars. Published by Universities.®

Missouri University of Science and Technology

Discipline
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 3451 - 3480 of 21795

Full-Text Articles in Engineering

Enthesis Strength, Toughness And Stiffness: An Image-Based Model Comparing Tendon Insertions With Varying Bony Attachment Geometries, Mikhail Golman, Victor Birman, Stavros Thomopoulos, Guy M. Genin Jan 2021

Enthesis Strength, Toughness And Stiffness: An Image-Based Model Comparing Tendon Insertions With Varying Bony Attachment Geometries, Mikhail Golman, Victor Birman, Stavros Thomopoulos, Guy M. Genin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Tendons of the body differ dramatically in their function, mechanics and range of motion, but all connect to bone via an enthesis. Effective force transfer at the enthesis enables joint stability and mobility, with strength and stiffness arising from a fibrous architecture. However, how enthesis toughness arises across tendons with diverse loading orientations remains unclear. To study this, we performed simultaneous imaging of the bone and tendon in entheses that represent the range of tendon-to-bone insertions and extended a mathematical model to account for variations in insertion and bone geometry. We tested the hypothesis that toughness, across a range of …

Go to article

Modeling Rack Force For Steering Maneuvers In A Stationary Vehicle, Nilay Kant, Raunav Chitkara, Prerit Pramod Jan 2021

Modeling Rack Force For Steering Maneuvers In A Stationary Vehicle, Nilay Kant, Raunav Chitkara, Prerit Pramod

Mechanical and Aerospace Engineering Faculty Research & Creative Works

A steering system converts circular motion of the steering wheel into yaw motion of the road-wheels. In absence of a steering assist mechanism, the driver torque overcomes the tire-road friction forces, which is transmitted to the steering rack through tie rods attached to the road-wheels. The net force acting on the rack is then transmitted to the steering wheel through mechanical linkages which results in natural haptic feedback, commonly referred to as the steering feel. In an electric/hydraulic power steering, an electro-mechanical actuator applies assist force, which reduces the torque required by the driver. In order to maintain stability of …

Go to article

Plant Identification In A Combined-Imbalanced Leaf Dataset -- Images, Viraj K. Gajjar, Anand Nambisan, Kurt Louis Kosbar Jan 2021

Plant Identification In A Combined-Imbalanced Leaf Dataset -- Images, Viraj K. Gajjar, Anand Nambisan, Kurt Louis Kosbar

Research Data

Plant identification has applications in ethnopharmacology and agriculture. Since leaves are one of a distinguishable feature of a plant, they are routinely used for identification. Recent developments in deep learning have made it possible to accurately identify the majority of samples in five publicly available leaf datasets. However, each dataset captures the images in a highly controlled environment. This paper evaluates the performance of EfficientNet models, B1 to B6, and several other convolutional neural network (CNN) architectures when applied to a combination of the LeafSnap, Middle European Woody Plants 2014, Flavia, Swedish, and Folio datasets. To normalize the impact of …

Go to article

Unsteady-State Contact Angle Hysteresis During Droplet Oscillation In Capillary Pores: Theoretical Model And Vof Simulation -- Supporting Information, Chao Zeng, Wen Deng, Lichun Wang Jan 2021

Unsteady-State Contact Angle Hysteresis During Droplet Oscillation In Capillary Pores: Theoretical Model And Vof Simulation -- Supporting Information, Chao Zeng, Wen Deng, Lichun Wang

Research Data

Contact angle hysteresis (CAH) is a critical phenomenon that could significantly affect the fate of immiscible bubbles/droplets in vadose zones, nonaqueous phase liquid contaminated aquifers, and saline aquifers for CO2 sequestration in terms of infiltration patterns and residual trapping mechanisms. When external physical impacts such as oscillatory excitation or pulse forcing are applied, it could result in pinned oscillation of droplets due to this CAH. Conventional steady-state analysis of contact angle could underestimate CAH. As the first time to take unsteady-state effect into consideration, a hydrodynamic analysis is developed in this study to address the unsteady-state CAH theoretically, and …

Go to article

Novel Adaptive Sampling Algorithm For Pod-Based Non-Intrusive Reduced Order Model, Jiachen Wang, Xiaosong Du, Joaquim R.R.A. Martins Jan 2021

Novel Adaptive Sampling Algorithm For Pod-Based Non-Intrusive Reduced Order Model, Jiachen Wang, Xiaosong Du, Joaquim R.R.A. Martins

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The proper orthogonal decomposition (POD) based reduced-order model (ROM) has been an effective tool for flow field prediction in the engineering industry. The sample selection in the design space for POD basis construction affects the ROM performance sensitively. Adaptive sampling can significantly reduce the number of samples to achieve the required model accuracy. In this work, we propose a novel adaptive sampling algorithm, called conjunction sampling strategy, which is based on proven strategies. The conjunction sampling strategy is demonstrated on airfoil flow field prediction within the transonic regime. We demonstrate the performance of the proposed strategy by running 10 trials …

Go to article

A Convolutional Neural Network Model Based On Multiscale Structural Similarity For The Prediction Of Flow Fields, Yifu An, Xiaosong Du, Joaquim R.R.A. Martins Jan 2021

A Convolutional Neural Network Model Based On Multiscale Structural Similarity For The Prediction Of Flow Fields, Yifu An, Xiaosong Du, Joaquim R.R.A. Martins

Mechanical and Aerospace Engineering Faculty Research & Creative Works

We have seen the emerging applications of deep neural networks for flow field predictions in the past few years. Most of the efforts rely on the increased complexity of the model itself or take advantage of novel network architectures, such as convolutional neural networks (CNN). However, reaching low prediction error cannot guarantee the quality of the predicted flow fields in terms of the perceived visual quality. This work introduces the multi-scale structural similarity (MS-SSIM) index method for flow field prediction. First, we train CNN models using the commonly used root mean squared error (RMSE) loss function as the reference. Then …

Go to article

Optimal Bidding Strategy For Physical Market Participants With Virtual Bidding Capability In Day-Ahead Electricity Markets, Hossein Mehdipourpicha, Rui Bo Jan 2021

Optimal Bidding Strategy For Physical Market Participants With Virtual Bidding Capability In Day-Ahead Electricity Markets, Hossein Mehdipourpicha, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Virtual bidding provides a mechanism for financial players to participate in wholesale day-ahead (DA) electricity markets. The price difference between DA and real-time (RT) markets creates financial arbitrage opportunities for financial players. Physical market participants (MP), referred to as participants with physical assets, can also take advantage of virtual bidding but in a different way, which is to further amplify the value of their physical assets. Therefore, this work proposes a model for such physical MPs to maximize the profits. This model employs a bi-level optimization approach, where the upper-level subproblem maximizes the total profit from both physical generations and …

Go to article

Dynamic Pricing In Electric Power Markets Affected By Distributed Energy Generation Using Agent-Based Modeling, Gasser G. Ali, Islam H. El-Adaway Jan 2021

Dynamic Pricing In Electric Power Markets Affected By Distributed Energy Generation Using Agent-Based Modeling, Gasser G. Ali, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The power infrastructure in the US is facing many challenges concerning capacity, reliability, and sustainability. Some of those challenges are associated with the integration of distributed energy resources (DER) into the conventional grid system. DER may offer reliable and cost-effective distributed small-scale generation near or at end-consumers. However, it also creates new challenges for utilities and generating companies due to the uncertainties in estimating demands. Accordingly, the goal of this research is to investigate dynamic pricing in electric power markets considering the effect of the increasing penetration of DER. To achieve that goal, a complex system-of-systems model that combines agent-based …

Go to article

Will Carbon Dioxide Injection In Shale Reservoirs Produce From The Shale Matrix, Natural Fractures, Or Hydraulic Fractures?, Sherif Fakher, Youssef Elgahawy, Hesham Abdelaal, Abdulmohsin Imqam Jan 2021

Will Carbon Dioxide Injection In Shale Reservoirs Produce From The Shale Matrix, Natural Fractures, Or Hydraulic Fractures?, Sherif Fakher, Youssef Elgahawy, Hesham Abdelaal, Abdulmohsin Imqam

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Enhanced oil recovery (EOR) in shale reservoirs has been recently shown to increase oil recovery significantly from this unconventional oil and gas source. One of the most studied EOR methods in shale reservoirs is gas injection, with a focus on carbon Dioxide (CO2) mainly due to the ability to both enhance oil recovery and store the CO2 in the formation. Even though several shale plays have reported an increase in oil recovery using CO2 injection, in some cases this method failed severely. This research attempts to investigate the ability of the CO2 to mobilize crude …

Go to article

Identifying Interconnectivities Between Modular Construction Decision-Making Factors Using Clustering And Network Analysis, Mohamad Abdul Nabi, Islam H. El-Adaway Jan 2021

Identifying Interconnectivities Between Modular Construction Decision-Making Factors Using Clustering And Network Analysis, Mohamad Abdul Nabi, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Understanding the complex and unique requirements of modular construction methods has become crucial given the ongoing increase in popularity of such construction methods. In fact, studying the various modular construction factors and their interconnections to attain successful project performance is perceived to help practitioners choose the modularization strategies that are more suitable for their specific context. To this end, there is a need to better understand the interconnectivities among the various modular construction decision-making factors. As such, the paper aims to enhance the knowledge of the interactions and interdependencies among the various modular construction decision-making factors. To achieve that, the …

Go to article

Identifying Substantial Changes For Aip Projects Using Rf And Svm, Ramy Khalef, Islam H. El-Adaway Jan 2021

Identifying Substantial Changes For Aip Projects Using Rf And Svm, Ramy Khalef, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The budget for the Airport Improvement Program (AIP) in FY21 is $3.35 billion. AIP's contractual guidelines and policies are outlined in Federal Aviation Administration (FAA) 5100.38D. Substantial contractual changes within AIP projects are likely to create risks that can greatly impact cost, time, and quality. To implement improved change management, identification and evaluation of contractual change are essential. Thus, there is a need to create an automated model to identify and evaluate contractual changes in AIP projects. This paper fills this knowledge gap. Using 876 contractual changes made to FAA 5100.38D, the authors utilized an interrelated multi-step methodology. Firstly, the …

Go to article

Using Machine Learning To Identify The Most Critical Factors Affecting Maintenance Of Tunnels, Muaz O. Ahmed, Ramy Khalef, Gasser G. Ali, Islam H. El-Adaway Jan 2021

Using Machine Learning To Identify The Most Critical Factors Affecting Maintenance Of Tunnels, Muaz O. Ahmed, Ramy Khalef, Gasser G. Ali, Islam H. El-Adaway

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Having well-maintained transportation infrastructure systems, including tunnels, is essential for the functioning and growth of the US economy. As such, monitoring the condition of tunnels through structural evaluation and inspections is essential to maintain their level of service. However, there is a lack of research that utilizes data from previous formal inspections to model and understand the condition of tunnels in the US. Being the case, this paper tackles this research need by developing a tunnel condition rating model that identifies the most critical factors affecting maintenance of tunnels. To this end, the authors utilize random forest (RF), which is …

Go to article

Enhancing Mixed Traffic Flow Safety Via Connected And Autonomous Vehicle Trajectory Planning With A Reinforcement Learning Approach, Yanqiu Cheng, Chenxi Chen, Xianbiao Hu, Kuanmin Chen, Qing Tang, Yang Song Jan 2021

Enhancing Mixed Traffic Flow Safety Via Connected And Autonomous Vehicle Trajectory Planning With A Reinforcement Learning Approach, Yanqiu Cheng, Chenxi Chen, Xianbiao Hu, Kuanmin Chen, Qing Tang, Yang Song

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The longitudinal trajectory planning of connected and autonomous vehicle (CAV) has been widely studied in the literature to reduce travel time or fuel consumptions. The safety impact of CAV trajectory planning to the mixed traffic flow with both CAV and human-driven vehicle (HDV), however, is not well understood yet. This study presents a reinforcement learning modeling approach, named Monte Carlo tree search-based autonomous vehicle safety algorithm, or MCTS-AVS, to optimize the safety of mixed traffic flow, on a one-lane roadway with signalized intersection control. Crash potential index (CPI) is defined to quantitively measure the safety performance of the mixed traffic …

Go to article

Microsphere Photolithography Patterned Nanohole Array On An Optical Fiber, Ibrahem Jasim, Jiayu Liu, Chen Zhu, Muhammad Roman, Jie Huang, Edward Kinzel, Mahmoud Almasri Jan 2021

Microsphere Photolithography Patterned Nanohole Array On An Optical Fiber, Ibrahem Jasim, Jiayu Liu, Chen Zhu, Muhammad Roman, Jie Huang, Edward Kinzel, Mahmoud Almasri

Electrical and Computer Engineering Faculty Research & Creative Works

Microsphere Photolithography (MPL) is a nanopatterning technique that utilizes a self-assembled monolayer of microspheres as an optical element to focus incident radiation inside a layer of photoresist. The microspheres produces a sub-diffraction limited photonic-jet on the opposite side of each microsphere from the illumination. When combined with pattern transfer techniques such as etching/lift-off, MPL provides a versatile, low-cost fabrication method for producing hexagonal close-packed metasurfaces. This article investigates the MPL process for creating refractive index (RI) sensors on the cleaved tips of optical fiber. The resonant wavelength of metal elements on the surface is dependent on the local dielectric environment …

Go to article

A Phewas Model Of Autism Spectrum Disorder, John Matta, Daniel Dobrino, Swade Howard, Dacosta Yeboah, Jonathan Kopel, Yasser El-Manzalawy, Tayo Obafemi-Ajayi Jan 2021

A Phewas Model Of Autism Spectrum Disorder, John Matta, Daniel Dobrino, Swade Howard, Dacosta Yeboah, Jonathan Kopel, Yasser El-Manzalawy, Tayo Obafemi-Ajayi

Electrical and Computer Engineering Faculty Research & Creative Works

Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well as communicative and cognitive difficulties. It is a challenge to categorize the phenotypes of a particular ASD patient with their unique genetic variants. There is a need for a better understanding of the connections between genotype information and the phenotypes to sort out the heterogeneity of ASD. In this study, single nucleotide polymorphism (SNP) and phenotype data obtained from a simplex ASD sample are combined using a PheWAS-inspired approach to construct a phenotype-phenotype network. The network is clustered, yielding groups …

Go to article

High-Frequency Modeling Of Permanent Magnet Synchronous Motor Considering Internal Imbalances, Yuandong Guo, Muqi Ouyang, Zhifei Xu, Minho Kim, Junesang Lee, Jungrae Ha, Hyewon Lee, Sangwon Yun, Jun Fan, Hongseok Kim Jan 2021

High-Frequency Modeling Of Permanent Magnet Synchronous Motor Considering Internal Imbalances, Yuandong Guo, Muqi Ouyang, Zhifei Xu, Minho Kim, Junesang Lee, Jungrae Ha, Hyewon Lee, Sangwon Yun, Jun Fan, Hongseok Kim

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, an accurate high-frequency modeling methodology for a permanent magnet synchronous motor (PMSM) in a vehicular electrical braking system is presented, which is suitable for analyzing various electromagnetic interference problems caused by a motor drive system. The proposed modeling approach is established according to the vector fitting technique and based on the S-parameter measurements of the PMSM. The equivalent circuit model of the PMSM converted from a measured S-parameter matrix can better describe the impedance characteristics of the three-phase PMSM under study compared to the existing equivalent circuit models because the imbalances inside the motor are taken into …

Go to article

Small-And Large-Scale Strain Sensing Using Frequency Selective Surfaces, Swathi Muthyala Ramesh, Kristen M. Donnell Jan 2021

Small-And Large-Scale Strain Sensing Using Frequency Selective Surfaces, Swathi Muthyala Ramesh, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are arrays of conductive elements or patches that have specific reflection and transmission responses. In this work, an FSS sensor designed to measure small (0% - 0.5%) and large (0% - 5%) scale strain is presented. The proposed unit cell of the sensor consists of two passive dipoles (of different dimensions) arranged normal to one another. This was done to reduce the error of small-scale strain on the large-scale strain measurement, and vice versa. Strain sensing is achieved by monitoring the change in the resonant frequencies of the two dipoles using an interrogating signal linearly polarized …

Go to article

On The Effect Of Design Parameters On Fringing Fields Of A Loop-Based Fss, Swathi Muthyala Ramesh, Mahboobeh Mahmoodi, Kristen M. Donnell Jan 2021

On The Effect Of Design Parameters On Fringing Fields Of A Loop-Based Fss, Swathi Muthyala Ramesh, Mahboobeh Mahmoodi, Kristen M. Donnell

Electrical and Computer Engineering Faculty Research & Creative Works

Frequency selective surfaces (FSSs) are periodic arrays of conductive elements that act as spatial filters of electromagnetic energy. FSSs have found recent application as sensors, filters, reflectors and radomes, amongst others. Often miniaturization techniques are used to improve the stability of the FSS to incident angle (of the excitation). However, due to the type of coupling (internal/self-vs. external/mutual with adjacent elements), some designs are more responsive to miniaturization techniques than others. Hence, this paper quantifies the effect of the ratios of inter-element spacing-to-substrate thickness (S/h) and side length-to-substrate thickness (SL/h) on fringing fields (and hence coupling and potential for miniaturization) …

Go to article

Developing Optimal Energy Arbitrage Strategy For Energy Storage System Using Reinforcement Learning, Haotian Chen, Rui Bo, Waqas Ur Rehman Jan 2021

Developing Optimal Energy Arbitrage Strategy For Energy Storage System Using Reinforcement Learning, Haotian Chen, Rui Bo, Waqas Ur Rehman

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduced a reinforcement learning based method for developing operational strategy for an energy storage system (ESS) to achieve energy arbitrage in a microgrid or power system. In comparison to conventional energy resources such as gas turbines units or wind plant, it is more challenging to design an optimal strategy for ESS because of their limited energy and the impact of future electricity prices. The energy arbitrage problem also presents unique challenges than the economic dispatch problem because the ESS owner has very limited information of the system compared to those available to grid operators. In this work, reinforcement …

Go to article

Artificial Neural Networks For Asymmetric Selective Harmonic Current Mitigation-Pwm In Active Power Filters To Meet Power Quality Standards, Amirhossein Moeini, Morteza Dabbaghjamanesh, Jonathan W. Kimball, Jie Zhang Jan 2021

Artificial Neural Networks For Asymmetric Selective Harmonic Current Mitigation-Pwm In Active Power Filters To Meet Power Quality Standards, Amirhossein Moeini, Morteza Dabbaghjamanesh, Jonathan W. Kimball, Jie Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

The main objective of an active power filter (APF) is to control the harmonics of nonlinear loads in power systems. In addition, the reactive power (fundamental component of the AC power) at the point of common coupling (PCC) can be compensated by using an APF. This paper investigates a technique for the modulation technique of the active power filters. Using the artificial neural network (ANN) technique, real-time fundamental and harmonic compensations can be achieved for the low-frequency modulation techniques such as asymmetric selective harmonic elimination/mitigation-pulse width modulation (ASHE/ASHM-PWM) and asymmetric selective harmonic current mitigation-PWM (ASHCM-PWM). This means that different phases …

Go to article

Fpga-Based Scalable Road Image Stochastic Denosing Approach, Cheolhyeong Park, Kyung Ki Kim, Yong Bin Kim, Minsu Choi Jan 2021

Fpga-Based Scalable Road Image Stochastic Denosing Approach, Cheolhyeong Park, Kyung Ki Kim, Yong Bin Kim, Minsu Choi

Electrical and Computer Engineering Faculty Research & Creative Works

This work proposes FPGA-based stochastic computing for efficient and scalable road image stochastic denoising. Stochastic number generators were compared for fields requiring data reliability such as automotive vehicles. The denoising performance of PRNG (Pseudo-Random Number Generator) and LDSG (Low Discrepancy Sequence Generator) are showed in noised KETTI dataset with filtering algorithms. The proposed approach is expected to be easily applied to SoCs with embedded FPGA for lightweight embedded implementation of image denoising algorithms.

Go to article

Using Gated Recurrent Units For Selective Harmonic Current Mitigation-Pwm In Grid-Tied Cascaded H-Bridge Converters, Morteza Dabbaghjamanesh, Amirhossein Moeini, Jonathan Kimball, Jie Zhang Jan 2021

Using Gated Recurrent Units For Selective Harmonic Current Mitigation-Pwm In Grid-Tied Cascaded H-Bridge Converters, Morteza Dabbaghjamanesh, Amirhossein Moeini, Jonathan Kimball, Jie Zhang

Electrical and Computer Engineering Faculty Research & Creative Works

Grid-tied converters become more popular for electric vehicle, renewable energy, and energy storage systems applications. Different modulation techniques such as low-frequency (e.g., selective harmonic elimination-PWM, selective harmonic mitigation-PWM, and selective harmonic current mitigation-PWM (SHCM-PWM)) and high-frequency modulation techniques (e.g., phase shift-PWM and space vector modulation) are used in the literature for grid-tied converters. Low-frequency modulation techniques have a high-efficiency due to the low-switching power losses. One of the main challenges of low-frequency modulation techniques such as SHCM-PWM is how to implement the proposed technique in real-time, due to the transcendental Fourier equations of SHCM-PWM. In this paper, a deep learning …

Go to article

A Time-Domain Computing-In-Memory Micro Using Ring Oscillator, Yixuan He, Minsu Choi, Kyung Ki Kim, Yong Bin Kim Jan 2021

A Time-Domain Computing-In-Memory Micro Using Ring Oscillator, Yixuan He, Minsu Choi, Kyung Ki Kim, Yong Bin Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a novel time-domain computing-in-memory core that implements XNOR-And-Accumulate (XAC) of XNOR network in 8T SRAM cell. This new technique uses an inverter-based ring oscillator to generate periodic waves whose period represents the accumulation result of the input XNOR values. The circuit is built and simulated using PTM16_HP 16nm CMOS model with a 0.7V power supply. The results show correct functionality, a large signal margin and 463 TOPS/W efficiency. With further exploration, the time-domain computation could be a new candidate for in-memory computing since it has its own superiorities in comparison to mixed-signal or digital methods.

Go to article

Sizing Energy Storage System For Energy Arbitrage In Extreme Fast Charging Station, Waqas Ur Rehman, Rui Bo, Hossein Mehdipourpicha, Jonathan W. Kimball Jan 2021

Sizing Energy Storage System For Energy Arbitrage In Extreme Fast Charging Station, Waqas Ur Rehman, Rui Bo, Hossein Mehdipourpicha, Jonathan W. Kimball

Electrical and Computer Engineering Faculty Research & Creative Works

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. …

Go to article

Stochastic Edge Detection For Fine-Grained Progressive Precision, Youngwook Lee, Kyung Ki Kim, Yong Bin Kim, Minsu Choi Jan 2021

Stochastic Edge Detection For Fine-Grained Progressive Precision, Youngwook Lee, Kyung Ki Kim, Yong Bin Kim, Minsu Choi

Electrical and Computer Engineering Faculty Research & Creative Works

Stochastic Computing (SC) is a method of performing an operation by expressing a probability in a bitstream. This format is simpler than the format of conventional binary computing and can be implemented in hardware with fewer resources. In addition, by using a Low-Discrepancy (LD) sequence, faster convergence can be derived. This paper shows the experimental results of applying SC using LD sequence to edge detection algorithms including Sobel and Roberts Cross to analyze the progressive precision performance and scalability.

Go to article

Partial Arc Sampling Receiving Scheme For Demultiplexing Of Orbital Angular Momentum Vortex Beam, Yanming Zhang, Lijun Jiang Jan 2021

Partial Arc Sampling Receiving Scheme For Demultiplexing Of Orbital Angular Momentum Vortex Beam, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Due to the divergence of the orbital angular momentum (OAM) beam, the OAM demultiplexing needs a considerable aperture size to acquire the OAM field information, which brings the challenges to implementation of the receiving end. To tackle this issue, we develop a partial arc sampling receiving (PASR) scheme for demultiplexing of the vortex beams by using the augmented dynamic mode decomposition (A-DMD) approach. Simulation benchmarks are provided to demonstrate the validity of the proposed novel demultiplexing method.

Go to article

Multi-Polarization Phase Retrieval In Near Field Far-Field Transformation, Yuan Ping, Lijun Jiang Jan 2021

Multi-Polarization Phase Retrieval In Near Field Far-Field Transformation, Yuan Ping, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In near field far-field transformation (NFFFT), accurate recovery of the current distribution is subjected to the phase measurement. Phase retrieval is an alternative way to recover the current distribution by utilizing the magnitude-only near field sampling data. In phase retrieval algorithm, sufficient independent measurement data are required. Multi-polarization algorithm is employed to generate different current distribution, then, obtaining more independent near field data. Experimental validations of a numeric examples show its potentialities and interest.

Go to article

Hybrid Beamforming With Deep Learning For Large-Scale Antenna Arrays, Rentao Hu, Lijun Jiang, Ping Li Jan 2021

Hybrid Beamforming With Deep Learning For Large-Scale Antenna Arrays, Rentao Hu, Lijun Jiang, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

The emergence of highly directional beamforming technology makes millimeter wave frequency band communication possible in future wireless communication networks. Based on the multipath characteristics of millimeter wave frequency communication, a high-precision multipath channel estimation algorithm based on signal subspace is proposed. In the mobile terminal, an iterative heuristic radiofrequency combination algorithm based on spatial points is proposed. The analog precoding at the base station uses deep learning to accelerate the calculation, and then the multi-user communication is modeled to design the digital precoding. The simulation results show that the multi-channel estimation algorithm can estimate 4 paths with an error of …

Go to article

Modeling And Simulation Of Resistive Superconducting Fault Current Limiter In Pscad/Emtdc™, Fahd Hariri, Mariesa Crow Jan 2021

Modeling And Simulation Of Resistive Superconducting Fault Current Limiter In Pscad/Emtdc™, Fahd Hariri, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

Energy networks are facing significant challenges as the result of increasing electrical loads. To meet this rapid increase in demand for electricity, new generating units are being added to support the stability and reliability of the network. This change in network structure requires a comprehensive analysis of the effect of that increase on the protection system. Limiting the fault current to safe levels prevents replacing the high-cost network components that may be subjected to damage due to exceeding the rated short-circuit current values for which they were designed. A fault analysis often requires extensive modeling and simulation of the system, …

Go to article

Advanced Control Techniques For Modern Inertia Based Inverters, Sepehr Saadatman Jan 2021

Advanced Control Techniques For Modern Inertia Based Inverters, Sepehr Saadatman

Doctoral Dissertations

”In this research three artificial intelligent (AI)-based techniques are proposed to regulate the voltage and frequency of a grid-connected inverter. The increase in the penetration of renewable energy sources (RESs) into the power grid has led to the increase in the penetration of fast-responding inertia-less power converters. The increase in the penetration of these power electronics converters changes the nature of the conventional grid, in which the existing kinetic inertia in the rotating parts of the enormous generators plays a vital role. The concept of virtual inertia control scheme is proposed to make the behavior of grid connected inverters more …

Go to article

First Prev Next Last