Digital Commons Network^™

Effect Of The Melt Pool Boundary Network On The Anisotropic Mechanical Properties Of Selective Laser Melted 304l, Myranda Spratt, Joseph William Newkirk, Okanmisope Fashanu, K. Chandrashekhara

Materials Science and Engineering Faculty Research & Creative Works

Anisotropic mechanical properties are a well-known issue in selective laser melted parts. The microstructure produced by selective laser melting (SLM) is directional, including the solidified melt pool structures and grains. This work investigates the melt pool boundary's effects on 304L stainless steel's compressive properties. 304L stainless steel solid cylinders were built using a pulse laser SLM machine in four directions using three hatch angle rotations: 0⁰, 67⁰, and 105⁰ . The twelve samples were compression tested, and the results were analyzed. Numerical models were also created with the different hatch angles and directions. The melt pool boundary network (MPBN) in …

The Bridge Newsletter Winter 2021, Missouri University Of Science And Technology

The Bridge Newsletter

-S&T contributes to infrastructure through national center
-Brinkmann leads Missouri Highways and Transportation Commission
-Wu wins NSF CAREER Award for 2D metals work
-Academy of Civil Engineers induction and 150^th celebration

Multimodal Ensemble Deep Learning To Predict Disruptive Behavior Disorders In Children, Sreevalsan S. Menon, K. Krishnamurthy

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Oppositional defiant disorder and conduct disorder, collectively referred to as disruptive behavior disorders (DBDs), are prevalent psychiatric disorders in children. Early diagnosis of DBDs is crucial because they can increase the risks of other mental health and substance use disorders without appropriate psychosocial interventions and treatment. However, diagnosing DBDs is challenging as they are often comorbid with other disorders, such as attention-deficit/hyperactivity disorder, anxiety, and depression. In this study, a multimodal ensemble three-dimensional convolutional neural network (3D CNN) deep learning model was used to classify children with DBDs and typically developing children. The study participants included 419 females and 681 …

Machine Learning Identifies Liquids Employing A Simple Fiber-Optic Tip Sensor, Wassana Naku, Chen Zhu, Anand K. Nambisan, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We proposed an extremely simple fiber-optic tip sensor system to identify liquids by combining their corresponding droplet evaporation events with analyses using machine learning techniques. Pendant liquid droplets were suspended from the cleaved endface of a single-mode fiber during the experiment. The optical fiber-droplet interface and the droplet-air interface served as two partial reflectors of an extrinsic Fabry-Perot interferometer (EFPI) with a liquid droplet cavity. As the liquid pendant droplet evaporated, its length diminished. A light source can be used to observe the effective change in the net reflectivity of the optical fiber sensor system by observing the resulting optical …

An Energy-Efficient Smart Space System Using Lora Network With Deadline And Security Constraints, Preti Kumari, Hari Prabhat Gupta, Rahul Mishra, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we develop techniques that create smart space in an efficient manner, wherein the efficiency is defined in terms of all-together: energy, security, delay, and cost. We design an energy-efficient smart space system using the Long-Range (LoRa) network. The system consists of various sensors that generate sensory data represented as Multi-dimensional Time Series (MTS). The sensors are connected with an Edge device and LoRa node for processing and transferring the MTS, respectively. The system first proposes a deep learning-based compression-decompression model for reducing the size of MTS at the Edge devices. Next, it uses game theory for finding …

Resilient Error-Bounded Lossy Compressor For Data Transfer, Sihuan Li, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, Franck Cappello

Computer Science Faculty Research & Creative Works

Todays exa-scale scientific applications or advanced instruments are producing vast volumes of data, which need to be shared/transferred through the network/devices with relatively low bandwidth (e.g., data sharing on WAN or transferring from edge devices to supercomputers). Lossy compression is one of the candidate strategies to address the big data issue. However, little work was done to make it resilient against silent errors, which may happen during the stage of compression or data transferring. In this paper, we propose a resilient error-bounded lossy compressor based on the SZ compression framework. Specifically, we design a new independentblock-wise model that decomposes the …

Learning Transfers Via Transfer Learning, Md Arifuzzaman, Engin Arslan

Computer Science Faculty Research & Creative Works

Detecting performance anomalies is key to efficiently utilize network resources and improve the quality of service. Researchers proposed various approaches to identify the presence of anomalies by analyzing performance statistics using heuristic (e.g., change point detection) and Machine Learning (ML) models. Although these models yield high accuracy in the networks that they are trained for, their performance degrade severely when transferred to different network settings. This is because of the fact that existing models detect anomalies by capturing the changes in transfer throughput and observed RTT values, which are dependent to network settings. In this paper, we propose a novel …

Analysis Of Energy Utilization And Losses For Jet-Propelled Vehicles, Mohammad Abbas, David W. Riggins

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The global control volume-based energy utilization balance for an aerospace vehicle is extended to allow for the analysis of jet-propelled vehicles. The methodology is first developed for analyzing the energy utilization and entropy generation characteristics of jet engines without airframe considerations. This methodology, when combined with separate energy utilization analysis for an unpowered airframe, allows for the assessment of a powered vehicle. Wake entropy generation for a powered vehicle is shown to be the summation of the wake entropy generation associated with the propulsion system (no airframe) and the unpowered airframe. The fundamental relationship between overall entropy generation and the …

Human-Human Hand Interactions Aid Balance During Walking By Haptic Communication, Mengnan Wu, Luke Drnach, Sistania M. Bong, Yun Seong Song, Lena H. Ting

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Principles from human-human physical interaction may be necessary to design more intuitive and seamless robotic devices to aid human movement. Previous studies have shown that light touch can aid balance and that haptic communication can improve performance of physical tasks, but the effects of touch between two humans on walking balance has not been previously characterized. This study examines physical interaction between two persons when one person aids another in performing a beam-walking task. 12 pairs of healthy young adults held a force sensor with one hand while one person walked on a narrow balance beam (2 cm wide x …

Correcting Correlation Functions For Redshift-Dependent Interloper Contamination, Daniel J. Farrow, Ariel G. Sánchez, Robin Ciardullo, Shun Saito, For Full List Of Authors, See Publisher's Website.

Physics Faculty Research & Creative Works

The construction of catalogues of a particular type of galaxy can be complicated by interlopers contaminating the sample. In spectroscopic galaxy surveys this can be due to the misclassification of an emission line; for example in the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX) low-redshift [O ii] emitters may make up a few per cent of the observed Ly α emitter (LAE) sample. The presence of contaminants affects the measured correlation functions and power spectra. Previous attempts to deal with this using the cross-correlation function have assumed sources at a fixed redshift, or not modelled evolution within the adopted redshift bins. …

Extracellular Matrix-Mimetic Hydrogels For Treating Neural Tissue Injury: A Focus On Fibrin, Hyaluronic Acid, And Elastin-Like Polypeptide Hydrogels, Derek W. Nelson, Ryan J. Gilbert

Chemical and Biochemical Engineering Faculty Research & Creative Works

Neurological and functional recovery is limited following central nervous system injury and severe injury to the peripheral nervous system. Extracellular matrix (ECM)-mimetic hydrogels are of particular interest as regenerative scaffolds for the injured nervous system as they provide 3D bioactive interfaces that modulate cellular response to the injury environment and provide naturally degradable scaffolding for effective tissue remodeling. In this review, three unique ECM-mimetic hydrogels used in models of neural injury are reviewed: fibrin hydrogels, which rely on a naturally occurring enzymatic gelation, hyaluronic acid hydrogels, which require chemical modification prior to chemical crosslinking, and elastin-like polypeptide (ELP) hydrogels, which …

Toughening Mechanisms For The Attachment Of Architectured Materials: The Mechanics Of The Tendon Enthesis, Mikhail Golman, Adam C. Abraham, Iden Kurtaliaj, Brittany P. Marshall, Yizhong Jenny Hu, Andrea G. Schwartz, X. Edward Guo, Victor Birman, Philipp J. Thurner, Guy M. Genin, Stavros Thomopoulos

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Architectured materials offer tailored mechanical properties but are limited in engineering applications due to challenges in maintaining toughness across their attachments. The enthesis connects tendon and bone, two vastly different architectured materials, and exhibits toughness across a wide range of loadings. Understanding the mechanisms by which this is achieved could inform the development of engineered attachments. Integrating experiments, simulations, and previously unexplored imaging that enabled simultaneous observation of mineralized and unmineralized tissues, we identified putative mechanisms of enthesis toughening in a mouse model and then manipulated these mechanisms via in vivo control of mineralization and architecture. Imaging uncovered a fibrous …

Apportioning Deformation Among Depth Intervals In An Aquifer System Using Insar And Head Data, Ryan G. Smith, Hossein Hashemi, Jingyi Chen, Rosemary Knight

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Land surface subsidence due to excessive groundwater pumping is an increasing concern in California, USA. Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technique for measuring centimeter-to-millimeter surface deformation at 10-100 m spatial resolution. Here, a data-driven approach that attributes deformation to individual depth intervals within an aquifer system by integrating head data acquired from each of three screened intervals in a monitoring well with InSAR surface deformation measurements was developed. The study area was the Colusa Basin in northern Central Valley. To reconstruct the surface deformation history over the study area, 13 ALOS-PALSAR scenes acquired between 2006 and …

Faster Post-Earthquake Damage Assessment Based On 1d Convolutional Neural Networks, Xinzhe Yuan, Dustin Tanksley, Liujun Li, Haibin Zhang, Genda Chen, Donald C. Wunsch

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Contemporary deep learning approaches for post-earthquake damage assessments based on 2D convolutional neural networks (CNNs) require encoding of ground motion records to transform their inherent 1D time series to 2D images, thus requiring high computing time and resources. This study develops a 1D CNN model to avoid the costly 2D image encoding. The 1D CNN model is compared with a 2D CNN model with wavelet transform encoding and a feedforward neural network (FNN) model to evaluate prediction performance and computational efficiency. A case study of a benchmark reinforced concrete (r/c) building indicated that the 1D CNN model achieved a prediction …

Pairing Experimental And Mathematical Modeling Studies On Fluidized Beds For Enhancement Of Models Predictive Quality: A Current Status Overview, Sebastián Uribe, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Modeling of gas-solid fluidized systems has been a prevailing challenge over the last few decades. With different approaches and implementing different sub-models to capture the essential multiphase and multiscale phenomena in these systems, major advances have been achieved, even though most models are only subject to a practical validation of macroscopic parameters. The current description of fluidized beds through mathematical models relies on the inclusion of vast sub-models, leading to an unquantifiable degree of uncertainty on the models' applicability for extrapolation studies. Furthermore, each closure and fitting parameter in the model represents a possible source of deviation, and their optimization, …

Open-Ended Hollow Coaxial Cable Resonator Sensor, Jie Huang, Chen Zhu, Rex E. Gerald Ii

Electrical and Computer Engineering Faculty Research & Creative Works

An open-ended hollow coaxial cable resonator probe configured to receive an aerosol sample for analysis. A metal post shorts the resonator's inner and outer conductors. A metal plate is spaced apart from an open end of the resonator by a dielectric layer that contains the received aerosol sample. Interrogator circuitry coupled to the resonator transmits an electromagnetic wave within the resonator and generates an electric field at the open end of the resonator. The interrogator circuitry is responsive to the generated electric field for determining a resonance frequency and an impedance of the resonator when the aerosol sample is present …

Self-Adhesive Silicone Microstructures For The Treatment Of Tympanic Membrane Perforations, Gabriela Moreira Lana, Katharina Sorg, Gentiana Ioana Wenzel, Dietmar Hecker, René Hensel, Bernhard Schick, Klaus Kruttwig, Eduard Arzt

Chemical and Biochemical Engineering Faculty Research & Creative Works

Inspired by the gecko foot, polymeric microstructures have demonstrated reliable dry adhesion to both stiff objects and sensitive surfaces such as skin. Microstructured silicone patches are proposed, herein, for the treatment of tympanic membrane perforations with the aim of serving as an alternative for current surgical procedures that require anesthesia and ear canal packing. Sylgard 184 PDMS micropillars of 20 μm in diameter and 60 μm in length are topped by a Soft Skin Adhesive (SSA) MG7-1010 terminal layer, of about 25 μm thickness. The adhesion is evaluated by specially designed tack tests against explanted murine eardrums and, for comparison, …

A Comprehensive Review Of In-Situ Polymer Gel Simulation For Conformance Control, Baojun Bai, Jianqiao Leng, Mingzhen Wei

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Gel treatment has been widely applied in mature oilfields to improve sweep efficiency and control water production. Correct numerical simulation is of major importance to the optimization design and prediction of a successful gel treatment. However, there exist many problems in current simulation studies in published literature. This paper first presents a comprehensive review on the major factors that have been considered at different gelation stages during gel treatment, the models used in the commercial/in-house simulators, and current numerical simulation studies on both laboratory and field scales. Then we classify the current in-situ gel numerical simulation problems as 1, deficient …

Impact Of Clay Stabilizer On The Methane Desorption Kinetics And Isotherms Of Longmaxi Shale, China, Zhong Hua Liu, Jia Chun Wang, Baojun Bai, Yan Ling Wang

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Knowing methane desorption characteristics is essential to define the contribution of adsorbed gas to gas well production. To evaluate the synthetic effect of a clay stabilizer solution on methane desorption kinetics and isotherms pertaining to Longmaxi shale, an experimental setup was designed based on the volumetric method. The objective was to conduct experiments on methane adsorption and desorption kinetics and isotherms before and after clay stabilizer treatments. The experimental data were a good fit for both the intraparticle diffusion model and the Freundlich isotherm model. We analyzed the effect of the clay stabilizer on desorption kinetics and isotherms. Results show …

Blood Biomarkers For Mild Traumatic Brain Injury: A Selective Review Of Unresolved Issues, Daniel B. Hier, Tayo Obafemi-Ajayi, Matthew S. Thimgan, Gayla R. Olbricht, Sima Azizi, Blaine Allen, Bassam A. Hadi, Donald C. Wunsch

Biological Sciences Faculty Research & Creative Works

Background: The use of blood biomarkers after mild traumatic brain injury (mTBI) has been widely studied. We have identified eight unresolved issues related to the use of five commonly investigated blood biomarkers: neurofilament light chain, ubiquitin carboxy-terminal hydrolase-L1, tau, S100B, and glial acidic fibrillary protein. We conducted a focused literature review of unresolved issues in three areas: mode of entry into and exit from the blood, kinetics of blood biomarkers in the blood, and predictive capacity of the blood biomarkers after mTBI.

Findings: Although a disruption of the blood brain barrier has been demonstrated in mild and severe traumatic brain …

Calibration Of The Air Shower Energy Scale Of The Water And Air Cherenkov Techniques In The Lhaaso Experiment, F. Aharonian, Q. An, Axikegu, L. X. Bai, Y. X. Bai, Y. W. Bao, D. Bastieri, X. J. Bi, Y. J. Bi, H. Cai, J. T. Cai, Zhen Cao, Zhe Cao, J. Chang, J. F. Chang, B. M. Chen, E. S. Chen, J. Chen, Liang Chen, Liang Chen, Long Chen, M. J. Chen, M. L. Chen, Q. H. Chen, S. H. Chen, S. Z. Chen, T. L. Chen, X. L. Chen, Y. Chen, N. Cheng, Y. D. Cheng, S. W. Cui, X. H. Cui, Y. D. Cui, B. Z. Dai, H. L. Dai, Z. G. Dai, Danzen Gluobu, D. Della Volpe, B. D'Ettorre Piazzoli, X. J. Dong, K. K. Duan, J. H. Fan, Y. Z. Fan, Z. X. Fan, J. Fang, K. Fang, C. F. Feng, L. Feng, S. H. Feng, Y. L. Feng, B. Gao, C. D. Gao, L. Q. Gao, Q. Gao, W. Gao, M. M. Ge, L. S. Geng, G. H. Gong, Q. B. Gou, M. H. Gu, F. L. Guo, J. G. Guo, X. L. Guo, Y. Q. Guo, Y. Y. Guo, Y. A. Han, H. H. He, H. N. He, J. C. He, S. L. He, X. B. He, Y. He, M. Heller, Y. K. Hor, C. Hou, H. B. Hu, S. Hu, S. C. Hu, X. J. Hu, D. H. Huang, Q. L. Huang, W. H. Huang, X. T. Huang, X. Y. Huang, Z. C. Huang, F. Ji, X. L. Ji, H. Y. Jia, K. Jiang, Z. J. Jiang, C. Jin, T. Ke, D. Kuleshov, K. Levochkin, B. B. Li, Cong Li, Cheng Li, F. Li, H. B. Li, H. C. Li, H. Y. Li, J. Li, K. Li, W. L. Li, Xin Li, Xin Li, X. R. Li, Y. Li, Y. Z. Li, Zhe Li, Zhuo Li, E. W. Liang, Y. F. Liang, S. J. Lin, B. Liu, C. Liu, D. Liu, H. Liu, H. D. Liu, J. Liu, J. L. Liu, J. S. Liu, J. Y. Liu, M. Y. Liu, R. Y. Liu, S. M. Liu, W. Liu, Y. Liu, Y. N. Liu, Z. X. Liu, W. J. Long, R. Lu, H. K. Lv, B. Q. Ma, L. L. Ma, X. H. Ma, J. R. Mao, A. Masood, Z. Min, W. Mitthumsiri, T. Montaruli, Y. C. Nan, B. Y. Pang, P. Pattarakijwanich, Z. Y. Pei, M. Y. Qi, Y. Q. Qi, B. Q. Qiao, J. J. Qin, D. Ruffolo, V. Rulev, A. Saiz, L. Shao, O. Shchegolev, X. D. Sheng, J. Y. Shi, H. C. Song, Yu. V. Stenkin, V. Stepanov, Y. Su, Q. N. Sun, X. N. Sun, Z. B. Sun, P. H. T. Tam, Z. B. Tang, W. W. Tian, B. D. Wang, C. Wang, H. Wang, H. G. Wang, J. C. Wang, J. S. Wang, L. P. Wang, L. Y. Wang, R. N. Wang, W. Wang, X. G. Wang, Xiaojie Wang, X. Y. Wang, Y. Wang, Y. D. Wang, Y. J. Wang, Y. P. Wang, Z. H. Wang, Z. X. Wang, Zhen Wang, Zheng Wang, D. M. Wei, J. J. Wei, Y. J. Wei, T. Wen, C. Y. Wu, H. R. Wu, S. Wu, W. X. Wu, X. F. Wu, S. Q. Xi, J. Xia, J. J. Xia, G. M. Xiang, D. X. Xiao, G. Xiao, H. B. Xiao, G. G. Xin, Y. L. Xin, Y. Xing, D. L. Xu, R. X. Xu, L. Xue, D. H. Yan, J. Z. Yan, C. W. Yang, F. F. Yang, J. Y. Yang, L. L. Yang, M. J. Yang, R. Z. Yang, S. B. Yang, Y. H. Yao, Z. G. Yao, Y. M. Ye, L. Q. Yin, N. Yin, X. H. You, Y. H. Yu, Q. Yuan, H. D. Zeng, T. X. Zeng, W. Zeng, Z. K. Zeng, M. Zha, X. X. Zhai, B. B. Zhang, H. M. Zhang, H. Y. Zhang, J. L. Zhang, J. W. Zhang, Lu Zhang, Li Zhang, L. X. Zhang, P. F. Zhang, R. Zhang, S. R. Zhang, S. S. Zhang, X. Zhang, X. P. Zhang, Y. F. Zhang, Y. L. Zhang, Yong Zhang, Yi Zhang, B. Zhao, J. Zhao, L. Zhao, L. Z. Zhao, S. P. Zhao, F. Zheng, Y. Zheng, B. Zhou, H. Zhou, J. N. Zhou, P. Zhou, R. Zhou, X. X. Zhou, C. G. Zhu, F. R. Zhu, H. Zhu, K. J. Zhu, X. Zuo

Physics Faculty Research & Creative Works

The Wide Field-of-View Cherenkov Telescope Array (WFCTA) and the Water Cherenkov Detector Array (WCDA) of LHAASO are designed to work in combination for measuring the energy spectra of the cosmic ray species over a very wide energy range from a few TeV to 10 PeV. The energy calibration can be achieved with a proven technique of measuring the westward shift of the Moon shadow cast by galactic cosmic rays due to the geomagnetic field. This deflection angle Δ is inversely proportional to the cosmic ray rigidity. The precise measurement of the shifts by WCDA allows us to calibrate its energy …

Image-Based Bridge Defect Detection And Monitoring Technologies, Jian Zhang

INSPIRE Archived Webinars

Computer-vision is an emerging technology which has been widely used in the field of structural health monitoring. This seminar will cover the latest achievements of our research group in defect detection, health monitoring, and construction control using image-based technologies. For defect detection, advanced unmanned aerial vehicles (UAVs) have been developed to automatically detect surface cracks and other types of structural damages based on digital image processing techniques. An integrated navigation system combining binocular camera and inertial sensor enables automated route planning for the developed UAVs in case of GPS failure. Specifically, a wall-climbing UAV is designed to acquire detailed surface …

Evolutionary Algorithm-Based Adaptive Robust Optimization For Ac Security Constrained Unit Commitment Considering Renewable Energy Sources And Shunt Facts Devices, Aliasghar Baziar, Rui Bo, Misagh Dehghani Ghotbabadi, Mehdi Veisi, Waqas Ur Rehman

Electrical and Computer Engineering Faculty Research & Creative Works

An AC security constrained unit commitment (AC-SCUC) in the presence of the renewable energy sources (RESs) and shunt flexible AC transmission system (FACTS) devices is conventionally modeled as a deterministic optimization problem to minimize the operation cost of conventional generation units (CGUs) subject to AC optimal power flow (AC-OPF) equations, operation constraints of RESs, shunt FACTS devices, and CGUs. To cope with the uncertainties of load and RES generation, robust and stochastic optimization and linearized formulation have been used to achieve a sub-optimal solution. To arrive at a more optimal solution, an evolutionary algorithm-based adaptive robust optimization (EA-ARO) approach to …

The Missouri Miner, September 1, 2021

The Missouri Miner Newspaper

No abstract provided.

Assessment Of Streamflow Predictions Generated Using Multimodel And Multiprecipitation Product Forcing, Bong Chul Seo, Witold F. Krajewski, Felipe Quintero, Steve Buan, Brian Connelly

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study assesses streamflow predictions generated by two distributed hydrologic models, the Hillslope Link Model (HLM) and the National Water Model (NWM), driven by three radar-based precipitation forcing datasets. These forcing data include the Multi-Radar Multi-Sensor (MRMS), and the Iowa Flood Center's single-polarization-based (IFC-SP) and dual-polarization-based (IFC-DP) products. To examine forcing-and model-dependent aspects of the representation of hydrologic processes, we mixed and matched all forcing data and models, and simulated streamflow for 2016–18 based on six forcing–model combinations. The forcing product evaluation using independent ground reference data showed that the IFC-DP radar-only product's accuracy is comparable to MRMS, which is …

Overcoming Stress, Hunger, And Pain: Cocaineand Amphetamine-Regulated Transcript Peptide's Promise, Willis K. Samson, Daniela Salvemini, Gina L.C. Yosten

Biological Sciences Faculty Research & Creative Works

Cocaine- and amphetamine-regulated transcript encodes an eponymous peptide, CARTp, which exerts diverse pharmacologic actions in the central and peripheral nervous systems, as well as in several endocrine organs, including pancreas. Here we review those diverse actions, the physiological relevance of which had remained unestablished until recently. With the identification of a CARTp receptor, GPR160, the physiologic importance and therapeutic potential of CARTp or analogs are being revealed. Not only is the CARTp-GPR160 interaction essential for the circadian regulation of appetite and thirst but also for the transmission of nerve injury-induced pain. Molecular approaches now are uncovering additional physiologically relevant actions, …

New Infeed Correction Methods For Distance Protection In Distribution Systems, Fahd Hariri, Mariesa Crow

Electrical and Computer Engineering Faculty Research & Creative Works

The reliability and security of power systems may be jeopardized by the increase in the amounts of renewable generation and the uncertainties produced by these devices. In particular, the protection schemes of traditional power systems have been challenged by the integration of distributed generation (DG) resources. Distance relays (DRs), which have been mainly employed to protect transmission systems, are increasingly proposed as one of the solutions to protect distribution systems with a heavy penetration of DGs. However, conventional distance protection faces several drawbacks that might lead to maloperation. One of those challenges is the "infeed effect", which causes the impedance …

Mrda-Mgfsnet: Network Based On A Multi-Rate Dilated Attention Mechanism And Multi-Granularity Feature Sharer For Image-Based Butterflies Fine-Grained Classification, Maopeng Li, Guoxiong Zhou, Weiwei Cai, Jiayong Li, Mingxuan Li, Mingfang He, Yahui Hu, Liujun Li

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Aiming at solving the problems of high background complexity of some butterfly images and the difficulty in identifying them caused by their small inter-class variance, we propose a new fine-grained butterfly classification architecture, called Network based on Multi-rate Dilated Attention Mechanism and Multi-granularity Feature Sharer (MRDA-MGFSNet). First, in this network, in order to effectively identify similar patterns between butterflies and suppress the information that is similar to the butterfly's features in the background but is invalid, a Multi-rate Dilated Attention Mechanism (MRDA) with a symmetrical structure which assigns different weights to channel and spatial features is designed. Second, fusing the …

In Vitro Osteogenic Performance Of Two Novel Strontium And Zinc-Containing Glass Polyalkenoate Cements, Daniella Marx, Alireza Rahimnejad Yazdi, Marcello Papini, Mark R. Towler

Chemical and Biochemical Engineering Faculty Research & Creative Works

Glass polyalkenoate cements (GPCs) are under investigation as potential bone adhesives, as they may provide an alternative to polymethylmethacrylate-based cements. GPCs containing strontium (Sr) and zinc (Zn) in place of aluminum (Al) are of particular interest because these ions are known stimulators of osteoprogenitor differentiation. GPCs have been manufactured from a novel bioactive glass (SiO2:0.48, ZnO:0.36, CaO:0.12, SrO:0.04) in the past, but, while such materials have been assessed for their influence on viability, their influence on osteogenic function has not been investigated until now. For this study, two GPCs were formulated from the same glass precursor evaluated in previous studies. …

Data-Driven Discovery Of The Governing Equation For The Transmission Lines System, Yanming Zhang, Lijun Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

Sophisticated structures in the transmission line system introduce the nonuniformity and nonlinearity, which brings the challenge for its characterization and modeling. In this work, a novel data-driven method is proposed to derive the governing partial differential equations of the transmission line. Based on the polynomial interpolation of the spatial-temporal samples of current and voltage, the time and spatial derivatives can be obtained. Then, the ridge regression algorithm is adopted to determine the active spatial differential terms from the candidate functions. Three benchmarks, the uniform and nonuniform transmission line, and a soliton generation system, are provided to demonstrate the validity of …