Digital Commons Network^™

A Low-Profile Fabry-Pérot Cavity Antenna Using Anisotropic Metasurface, Muhammad Yasir Jamal, Min Li, Kwan Lawrence Yeung, Xiaoqiang Li, Lijun Jiang, Tatsuo Itoh

Electrical and Computer Engineering Faculty Research & Creative Works

A Fabry-Pérot cavity (FPC) antenna utilizing a new cavity resonance phenomenon based on the polarization standing wave (PSW) is proposed. To produce PSW, two anisotropic metasurfaces acting as the handedness preserving mirror are designed as the two ends of the cavity. Such a cavity possesses a new resonant condition, i.e., the relative rotation angle and distance between two metasurfaces together determine its resonant frequency. Hence, in comparison to conventional FPC antennas, the proposed one possesses a lower profile height of around 0.125 wavelengths. The antenna concept is experimentally demonstrated for the 12 GHz X-band application. Measurement results agree well with …

Management Of Change Orders In Infrastructure Transportation Projects, Rayan H. Assaad, Muaz O. Ahmed, Islam H. El-Adaway, Pramen P. Shrestha

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The Illinois Department of Transportation (IDOT) will handle many upcoming projects due to the recent statewide infrastructure strategic plan and the fast-track efforts affecting many infrastructure projects amid COVID-19. Nevertheless, many change orders are anticipated to occur on IDOT's projects. Thus, this paper examines the proper contractual management of changes within IDOT infrastructure transportation projects by following a research method based on the integration between a desktop analysis and a focus group analysis. The desktop analysis involved collecting information and data from existing resources, case studies, and documents related to change orders. The focus group analysis involved consulting with change …

Efficient And Accurate Phase-Measurement Method For Core-Loss Characterization, Anfeng Huang, Jun Fan, Chulsoon Hwang

Electrical and Computer Engineering Faculty Research & Creative Works

Accurate core-loss characterization is essential to push the power density of power converters to their limits. However, existing core-loss measurement methods still have some limitations, such as a slow test speed and a complex probe calibration procedure. In particular, accurate phase-difference measurement is time-consuming because a fast Fourier transform analysis with a kHz-range frequency interval is typically applied to reduce the influence of noise. An automated measurement system for magnetic core-loss characterization is described in this paper. An accurate phase-detection block with programmable attenuators is developed to measure the phase difference between voltage and current waveforms. The proposed system considerably …

Collisional Excitation And Non-Lte Modeling Of Interstellar Chiral Propylene Oxide, Karlis Dzenis, Alexandre Faure, B. A. Mcguire, A. J. Remijan, P. J. Dagdigian, C. Rist, Richard Dawes, Ernesto Quintas-Sánchez, F. Lique, M. Hochlaf

Chemistry Faculty Research & Creative Works

The first set of theoretical rotational cross sections for propylene oxide (CH₃CHCH₂O) colliding with cold He atoms has been obtained at the full quantum level using a high-accuracy potential energy surface. By scaling the collision reduced mass, rotational rate coefficients for collisions with para-H₂ are deduced in the temperature range 5-30 K. These collisional coefficients are combined with radiative data in a non-LTE radiative transfer model in order to reproduce observations of propylene oxide made toward the Sagittarius B2(N) molecular cloud with the Green Bank and Parkes radio telescopes. The three detected absorption lines are …

Collisional Excitation And Non-Lte Modeling Of Interstellar Chiral Propylene Oxide, Karlis Dzenis, Alexandre Faure, B. A. Mcguire, A. J. Remijan, P. J. Dagdigian, C. Rist, Richard Dawes, Ernesto Quintas-Sánchez, F. Lique, M. Hochlaf

Chemistry Faculty Research & Creative Works

The first set of theoretical rotational cross sections for propylene oxide (CH₃CHCH₂O) colliding with cold He atoms has been obtained at the full quantum level using a high-accuracy potential energy surface. By scaling the collision reduced mass, rotational rate coefficients for collisions with para-H2 are deduced in the temperature range 5-30 K. These collisional coefficients are combined with radiative data in a non-LTE radiative transfer model in order to reproduce observations of propylene oxide made toward the Sagittarius B2(N) molecular cloud with the Green Bank and Parkes radio telescopes. The three detected absorption lines are found …

Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Currently, renewable energy generation has received more and more attention. This article focuses on wind energy generation, one of the renewable energy sources. Aiming at the intermittent and unpredictable wind power problems, according to the day ahead bidding mechanism in the power market, this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor model. First, this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding amount. Then, we analyze …

Speeding Up Routing Schedules On Aisle Graphs With Single Access, Francesco Betti Sorbelli, Stefano Carpin, Federico Coro, Sajal K. Das, Alfredo Navarra, Cristina M. Pinotti

Computer Science Faculty Research & Creative Works

In this article, we study the orienteering aisle-graph single-access problem (OASP), a variant of the orienteering problem for a robot moving in a so-called single-access aisle graph, i.e., a graph consisting of a set of rows that can be accessed from one side only. Aisle graphs model, among others, vineyards or warehouses. Each aisle-graph vertex is associated with a reward that a robot obtains when it visits the vertex itself. As the energy of the robot is limited, only a subset of vertices can be visited with a fully charged battery. The objective is to maximize the total reward collected …

Water Film Depth Prediction Model For Highly Textured Pavement Surface Drainage, Alireza Pourhassan, Ahmed A. Gheni, Mohamed Elgawady

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Water film depth (WFD) is an important factor for road traffic safety because of its direct connection with skid resistance, hydroplaning speed, and the tendency of splash and spray. Increasing the pavement macrotexture reduces WFD. However, existing models for WFD prediction have not been developed on highly textured surfaces such as chip seal. Furthermore, the rainfall intensities used for developing most of these models were relatively low, leaving no or low WFD on chip seal surfaces. To propose a WFD prediction model suitable for highly textured surfaces and to consider the effect of surface material type, an experimental study was …

A Detailed Hydrodynamic Study Of The Split-Plate Airlift Reactor By Using Non-Invasive Gamma-Ray Techniques, Laith S. Sabri, Abbas J. Sultan, Hasan Shakir Majdi, Shadha K. Jebur, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

This study focused on detailed investigations of selected local hydrodynamics in split airlift reactor by using an unconventional measurements facility: computed tomography (CT) and radioactive particle tracking (RPT). The local distribution in a cross-sectional manner with its radial's profiles for gas holdup, liquid velocity flow field, shear stresses, and turbulent kinetic energy were studied under various gas velocity 1, 2 and 3 cm/s with various six axial level z = 12, 20, 40, 60, 90 and 112 cm. The distribution in gas–liquid phases in the whole split reactor column, the riser and downcomer sides, including their behavior at the top …

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 …

High Harmonic Generation In Mixed Xuv And Nir Fields At A Free-Electron Laser, Jan Troß, Shashank Pathak, Adam Summers, Dimitrios Rompotis, Benjamin Erk, Christopher Passow, Bastian Manschwetus, Rebecca Boll, Patrik Grychtol, Sadia Bari, Vinod Kumarappan, Anh(Anh-Thu) Thu Le, Cheng Jin, Carlos Trallero

Physics Faculty Research & Creative Works

We Present the Results of an Experiment Investigating the Generation of High-Order Harmonics by a Femtosecond Near-Infrared (NIR) Laser Pulse in the Presence of an Extreme Ultraviolet (XUV) Field Provided by a Free-Electron Laser (FEL), a Process Referred to as XUV-Assisted High-Order Harmonic Generation (HHG). Our Experimental Findings Show that the XUV Field Can Lead to a Small Enhancement in the Harmonic Yield When the XUV and NIR Pulses overlap in Time, while a Strong Decrease of the HHG Yield and a Red Shift of the HHG Spectrum is Observed When the XUV Precedes the NIR Pulse. the Latter Observations …

An Intelligent Distributed Ledger Construction Algorithm For Iot, Charles Rawlins, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Blockchain is the next generation of secure data management that creates near-immutable decentralized storage. Secure cryptography created a niche for blockchain to provide alternatives to well-known security compromises. However, design bottlenecks with traditional blockchain data structures scale poorly with increased network usage and are extremely computation-intensive. This made the technology difficult to combine with limited devices, like those in Internet of Things networks. In protocols like IOTA, replacement of blockchain's linked-list queue processing with a lightweight dynamic ledger showed remarkable throughput performance increase. However, current stochastic algorithms for ledger construction suffer distinct trade-offs between efficiency and security. This work proposed …

Stripe Order, Impurities, And Symmetry Breaking In A Diluted Frustrated Magnet, Xuecheng Ye, Rajesh Narayanan, Thomas Vojta

Physics Faculty Research & Creative Works

We investigate the behavior of the frustrated J₁-J₂ Ising model on a square lattice under the influence of random dilution and spatial anisotropies. Spinless impurities generate a random-field type disorder for the spin-density wave (stripe) order parameter. These random fields destroy the long-range stripe order in the case of spatially isotropic interactions. Combining symmetry arguments, percolation theory, and large-scale Monte Carlo simulations, we demonstrate that arbitrarily weak spatial interaction anisotropies restore the stripe phase. More specifically, the transition temperature T_c into the stripe phase depends on the interaction anisotropy ΔJ via T_c∼1/|ln(ΔJ)| for small …

Distributed Matrix Tiling Using A Hypergraph Labeling Formulation, Avah Banerjee, Maxwell Reeser, Guoli Ding

Computer Science Faculty Research & Creative Works

Partitioning large matrices is an important problem in distributed linear algebra computing, used in ML among others. Briefly, our goal is to perform a sequence of matrix algebra operations in a distributed manner on these large matrices. However, not all partitioning schemes work well with different matrix algebra operations and their implementations (algorithms). This is a type of data tiling problem. In this paper we consider a data tiling problem using hypergraphs. We prove some hardness results and give a theoretical characterization of its complexity on random instances. Additionally, we develop a greedy algorithm and experimentally show its efficacy.

Fadeloc: Smart Device Localization For Generalized Κ-Μ Faded Iot Environment, Ankur Pandey, Piyush Tiwary, Sudhir Kumar, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we propose FadeLoc a novel method for localizing smart devices in an Internet of Things (IoT) environment, based on the Received Signal Strength (RSS), and a generic κ-μ fading model where κ and μ denote the fading parameters. The RSS-based localization is challenging because of noise, fading, and non-line-of-sight (NLOS) effects, thus necessitating an appropriate fading model to best fit the varying RSS values. The advantage of a generic fading model is that it can accommodate all existing fading distributions based on the estimate of κ and μ. Hence, the localization can be performed for any fading …

Modeling Of Spatial-Temporal Sea Clutter With I/Q Components Based On The Data-Driven Approximation Of Koopman Theory, Y. M. Zhang, L. (Lijun) J. Jiang

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel data-driven approximation of the Koopman theory algorithm is proposed to simulate the coherent and spatial-temporal correlated sea clutter. The evolution of sea clutter's in-phase and quadrature (I/Q) components are well simulated on the state space. Meanwhile, the amplitude distribution and the phase retrieval of sea clutter can be extracted and modeled. The experimental sea clutter data measured by the IPIX radar is used to demonstrate that this newly proposed data-driven approximation of the Koopman theory algorithm can simulate the sea clutter with the phase retrieval, the expected amplitude information, and the spatial-temporal relationship. Our work …

Jointly-Learnt Networks For Future Action Anticipation Via Self-Knowledge Distillation And Cycle Consistency, Md Moniruzzaman, Zhaozheng Yin, Zhihai He, Ming-Chuan Leu, Ruwen Qin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Future action anticipation aims to infer future actions from the observation of a small set of past video frames. In this paper, we propose a novel Jointly learnt Action Anticipation Network (J-AAN) via Self-Knowledge Distillation (Self-KD) and cycle consistency for future action anticipation. In contrast to the current state-of-the-art methods which anticipate the future actions either directly or recursively, our proposed J-AAN anticipates the future actions jointly in both direct and recursive ways. However, when dealing with future action anticipation, one important challenge to address is the future's uncertainty since multiple action sequences may come from or be followed by …

Guiding A Human Follower With Interaction Forces: Implications On Physical Human-Robot Interaction, George L. Holmes, Keyri Moreno Bonnett, Amy Costa, Devin Michael Burns, Yun Seong Song

Psychological Science Faculty Research & Creative Works

This work challenges the common assumption in physical human-robot interaction (pHRI) that the movement intention of a human user can be simply modeled with dynamic equations relating forces to movements, regardless of the user. Studies in physical human-human interaction (pHHI) suggest that interaction forces carry sophisticated information that reveals motor skills and roles in the partnership and even promotes adaptation and motor learning. In this view, simple force-displacement equations often used in pHRI studies may not be sufficient. To test this, this work measured and analyzed the interaction forces (F) between two humans as the leader guided the blindfolded follower …

Passive Intermodulation Under Different Spring Contact Conditions, Shengxuan Xia, Emmanuel Olugbade, Yuchu He, Yansheng Wang, Hanfeng Wang, Krishna Rao, Marco Poort, Haicheng Zhou, Warren Lee, Nicholas Mcdonnell, Jonghyun Park, Chulsoon Hwang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Modularized designs have been widely used in today's consumer electronic devices and flexible RF springs are used for electrical connections between the modules. In the meantime, aluminum alloy material becomes a common chassis option. It is well known that the oxidized chassis surface introduces a certain level of nonlinearity when contacted by the springs, as known as passive intermodulation (PIM). PIM is one of the well-known root causes of the RF desensitization (desense). This paper is focused on investigating the relationship between PIM and contact conditions of the springs, especially contact area. The PIM level behavior is explained mathematically by …

Regulation Of Dendrite-Free Li Plating Via Lithiophilic Sites On Lithium-Alloy Surface, Yufang He, Mengyun Zhang, Aiping Wang, Bo Zhang, Hiep Pham, Qiao Hu, Li Sheng, Hong Xu, Li Wang, Jonghyun Park, Xiangming He

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Lithium (Li) deposition behavior plays an important role in dendrite formation and the subsequent performance of lithium metal batteries. This work reveals the impact of the lithiophilic sites of lithium-alloy on the Li plating process via the first-principles calculations. We find that the Li deposition mechanisms on the Li metal and Li22Sn5 surface are different due to the lithiophilic sites. We first propose that Li plating on the Li metal surface goes through the "adsorption-reduction-desorption-heterogeneous nucleation-cluster drop "process, while it undergoes the "adsorption-reduction-growth "process on the Li22Sn5 surface. The lower adsorption energy contributes to the easy adsorption of Li on …

Persistent Stealthy Attacks And Their Detection In Large Distributed Cyber-Physical Systems, Simon Bech Thougaard

Doctoral Dissertations

"Cyber-Physical Systems (CPS) are increasingly targeted by attackers using a wide and evolving array of methods. When these systems are distributed, every node represents a potential vulnerability, and secure system design must take this into account. Distributed CPSs also have the potential to better detect and handle attacks, by leveraging redundancies of physical measurements between adjacent nodes. The main purpose of this research is to determine the conditions that render a distributed CPS more resistant to attacks, and the conditions that render it more vulnerable. The work is centered around two separate applications: The Smart Grid and Autonomous Drone Swarms. …

Novel Ferromagnetic Materials With Improved Mechanical Performance, Wesley Alexander Everhart

Doctoral Dissertations

"The ductility of intermetallics has long been a hindrance to their broad adaptation despite a significant range of properties such as magnetic, half-metallic, and shape memory behavior. The lack of a general theory for the ductility of intermetallics along with the lack of prior art that experimentally measured mechanical properties drives the need for significant investment in many of these novel magnetic materials in order to even understand, let alone correct, poor ductility.

This dissertation includes work that explored the effect of vanadium content and quenching rate on the microstructure and ductility of Fe-Co alloys. Results indicated that a martensitic …

Development And Application Of Ensemble Machine Learning Algorithms To Enable A Priori, High-Fidelity, And Prompt Predictions And Optimizations Of Complex Materials And Systems, Taihao Han

Doctoral Dissertations

"Complex materials consisting of multiple chemical components/phases have been widely used in different engineering applications that have strict criteria. To optimize the mixture design of complex materials, researchers invest enormous resources in cumbersome experiments. However, due to substantial variations in precursors and processing techniques, it has been challenging to develop theoretical frameworks (i.e., empirical models) that could produce reliable predictions of properties of complex materials. In recent years, scientists have harnessed the power of machine learning (ML) and “Big” data to uncover the underlying mixture design-property correlations and produce high-fidelity predictions of properties of complex materials. The ML models autonomously …

Forecasting Nodal Price Difference Between Day-Ahead And Real-Time Electricity Markets Using Long-Short Term Memory And Sequence-To-Sequence Networks, Ronit Das, Rui Bo, Haotian Chen, Waqas Ur Rehman, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

Price forecasting is at the center of decision making in electricity markets. Much research has been done in forecasting energy prices for a single market while little research has been reported on forecasting price difference between markets, which presents higher volatility and yet plays a critical role in applications such as virtual trading. To this end, this paper takes the first attempt at it and employs novel deep learning architecture with Bidirectional Long-Short Term Memory (LSTM) units and Sequence-to-Sequence (Seq2Seq) architecture to forecast nodal price difference between day-ahead and real-time markets. In addition to value prediction, these deep learning architectures …

Some Insights On Flow Over Sharp-Crested Weirs Using Computational Fluid Dynamics: Implications For Enhanced Flow Measurement, Joseph M. Sinclair, S. Karan Venayagamoorthy, Timothy K. Gates

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study reexamines flow over a sharp-crested weir using computational fluid dynamics (CFD) to identify the optimal operating range under which the weir functions with accuracy as a free-flowing measurement device. A numerical parametric study was conducted for two separate channel and weir geometries under a range of flow rates resulting in different h/P values, where h is the elevation head over the weir crest, and P is the weir height. Analysis of velocity and pressure profiles over the weir revealed three distinct flow regimes: a high acceleration regime, an ideal operating regime, and a weir-inundated regime that may lead …

Optimizing Exterior Lighting Illuminance And Spectrum For Human, Environmental, And Economic Factors., S. M. Simmons, Stuart Werner Baur, William L. Gillis, Devin Michael Burns, Heath Pickerill

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

With the recent widespread adoption of LED lighting in outdoor areas, numerous concerns have been raised about the potential for harmful effects on humans, animals, plants, and the night sky. These stem from the high blue light content of some LED bulbs and an incentive to increase lighting levels caused by higher efficiency and lower costs. While new lighting installations are often described as environmentally friendly due to their energy efficiency, factors such as light pollution are often neglected or not given enough weight. This research focuses on optimizing the design of exterior lighting for human, environmental, and economic factors …

Simulation Study Of A Probabilistic Measurement Terminator For Cloud Radar Systems Using Cloudsat Data, Jakob Delong, Joel T. Johnson

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a novel probabilistic method that is used to identify low-SNR measurements in a cloud profiling radar application and terminate them before completion to save resources. The method uses a statistical model to predict the final SNR level of a measurement in progress and terminate it if it falls below a specified threshold at a specified level of confidence. The method is applied in a simulation study in which radar backscattered power profiles are obtained from CloudSat radar data, and is shown to achieve favorable performance.

Proportional Fair Clustered Federated Learning, Mohamed Nafea, Eugine Shin, Aylin Yener

Electrical and Computer Engineering Faculty Research & Creative Works

This paper studies federated learning (FL) with non-identical data generating distributions and under the notion of proportional fairness. Users are partitioned into disjoint clusters based on their data distributions, and a distinct model is learnt for each cluster. Different than previous work that considered clustering to optimize personalized learning performance, here clustering is inspected under the disparate impact doctrine which requires that protected classes (e.g., those of certain race or gender) have representations in every cluster that are approximately equal to their representation in the overall set of users. A family of iterative algorithms that balance the learning performance and …

Modeling Radiated Emissions From Pcbs In Shielding Enclosures Based On A Numerical Green's Function Approach, Zi An Wang, Li (Lijun) Jun Jiang, Jun Fa Mao, Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

To accurately and efficiently model the radiated emissions from printed circuit boards (PCBs) placed in shielding enclosures, in this work, a novel approach based on the numerical Green's function (NGF) is proposed. In terms of Schelkunoff's equivalence principle, if the interior of the shielding enclosure is filled up with perfectly electric conductor (PEC), only tangential electric fields over the ventilation slots are sufficient to obtain the radiated emissions. However, due to the presence of the PEC filled shielding box, the in-situ Green's function is not available. To conquer this problem, the proposed approach can be split into two steps. In …

A Novel Data-Driven Modeling Method For The Spatial-Temporal Correlated Complex Sea Clutter, Yanming Zhang, Lijun Jiang, Hong Tat Ewe

Electrical and Computer Engineering Faculty Research & Creative Works

The sea clutter, referred to as the time-varying radar backscatter from the ocean surface, plays a significant role in marine radar development. The ocean's complex hydrodynamics cause it to exhibit non-Gaussian and nonstationary characteristics, which brings challenges in the sea clutter modeling, especially for establishing its spatial-temporal correlated and coherent model. In this article, a data-driven method based on the Koopman mode decomposition (KMD) is proposed for modeling spatial-temporal correlated complex sea clutter. The method decomposes the coherent sea clutter dynamic behavior in terms of Koopman modes and corresponding temporal patterns. Then, these spatiotemporal patterns are used to construct the …