Engineering Commons^™

In Operando Mechanism Analysis On Nanocrystalline Silicon Anode Material For Reversible And Ultrafast Sodium Storage, Lei Zhang, Xianluo Hu, Chaoji Chen, Haipeng Guo, Xiaoxiao Liu, Gengzhao Xu, Haijian Zhong, Shuang Cheng, Peng Wu, Jiashen Meng, Yunhui Huang, Shi Xue Dou, Hua-Kun Liu

Australian Institute for Innovative Materials - Papers

Presently, lithium-ion batteries (LIBs) are the most promising commercialized electrochemical energy storage systems. Unfortunately, the limited resource of Li results in increasing cost for its scalable application and a general consciousness of the need to find new type of energy storage technologies. Very recently, substantial effort has been invested to sodium-ion batteries (SIBs) due to their effectively unlimited nature of sodium resources. Furthermore, the potential of Li/Li+ is 0.3 V lower than that of Na/Na+, which makes it more effective to limit the electrolyte degradation on the outer surface of the electrode.[1] Nevertheless, one major obstacle ...

Editorial, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.

Heat Transfer Vest, Nicholas Forsgaard

All Undergraduate Projects

The purpose of this report is to document the progression of the authors senior project. . The of that project was the research of Liquid Cooled Garment (LCG) technology, the generation of a novel LCG prototype and the testing of that prototype relative to a commercial benchmark. As such, this report is a complete narrative of the of these tasks, their execution and the underlying assumptions and commentary. The motivation for this report is to satisfy the capstone requirements of the MET program at CWU by documenting the Senior Project and its subordinate tasks. First, the student designed a LCG system ...

What Is Community Operational Research?, Gerald Midgley, Michael P. Johnson Jr., George Chichirau

Michael P. Johnson

Recursive Non-Local Means Filter For Video Denoising, Redha A. Ali, Russell C. Hardie

Electrical and Computer Engineering Faculty Publications

In this paper, we propose a computationally efficient algorithm for video denoising that exploits temporal and spatial redundancy. The proposed method is based on non-local means (NLM). NLM methods have been applied successfully in various image denoising applications. In the single-frame NLM method, each output pixel is formed as a weighted sum of the center pixels of neighboring patches, within a given search window.

The weights are based on the patch intensity vector distances. The process requires computing vector distances for all of the patches in the search window. Direct extension of this method from 2D to 3D, for video ...

Studies On Stable Crack Growth, Mohammed Juma Humaid Al-Ghafri

Theses

The goal of this work is to experimentally investigate the stable crack growth (SCG) fracture behavior of AISI 4340 alloy steel. A series of mode I and mixed mode SCG fracture tests were carried out on 8 mm thick compact tension (CT) specimens subjected to quasistatic loading. The wire cutting technique was used to introduce a pre-notch/ pre-crack of 0.05 mm root radius to the specimen. Five different loading angles Ψ between the loading axis and the crack surface were employed; 90° (mode I), 75°, 65°, 60° and 50°. Five different ratios of original crack length to specimen width ...

Trading Off Sound Pressure Level And Average Power Production For Wind Farm Layout Optimization, Eric Tingey, Andrew Ning

All Faculty Publications

This research explores the trade-offs between a wind farm’s average power production and noise impact on nearby observers. Two specific wind farm designs were studied and optimized using the FLORIS wake model and an acoustic model based on semi-empirical turbine noise calculations. It was found in the two wind farms that the average power production could be increased, up to 8.01% in one and 3.63% in the other, ignoring sound level considerations. Including a noise restriction in the optimization had a minimal impact on the optimal average power production within about a five-decibel range. Past this range ...

Fast On-Line Kernel Density Estimation For Active Object Localization, Anthony D. Rhodes, Max H. Quinn, Melanie Mitchell

Computer Science Faculty Publications and Presentations

A major goal of computer vision is to enable computers to interpret visual situations—abstract concepts (e.g., “a person walking a dog,” “a crowd waiting for a bus,” “a picnic”) whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. In this paper, we propose a novel method for prior learning and active object localization for this kind of knowledge-driven search in static images. In our system, prior situation knowledge is captured by a set of flexible, kernel-based density estimations— a situation model—that represent the expected spatial structure of the ...

Pid4898649.Pdf, Hamidreza Jafarian

Hamidreza Jafarian

No abstract provided.

Ecce_2017_Harmonics_Nk4_Je.Pdf, Hamidreza Jafarian

Hamidreza Jafarian

No abstract provided.

Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou

Biomedical, Industrial & Human Factors Engineering Faculty Publications

Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts’ decision-making process. We investigated the effects of different noise stimuli on analysts’ performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in ...

Farm-Scale Testing Of Soybean Peroxidase And Calcium Peroxide For Surficial Swine Manure Treatment And Mitigation Of Odorous Vocs, Ammonia And Hydrogen Sulfide Emissions, Devin L. Maurer, Jacek A. Koziel, Kelsey Bruning, David B. Parker

Agricultural and Biosystems Engineering Publications

The swine industry, regulatory agencies, and the public are interested in farm-tested methods for controlling gaseous emissions from swine barns. In earlier lab- and pilot-scale studies, a renewable catalyst consisting of soybean peroxidase (SBP) mixed with calcium peroxide (CaO₂) was found to be effective in mitigating gaseous emissions from swine manure. Thus, a farm-scale experiment was conducted at the university's 178-pig, shallow-pit, mechanically-ventilated swine barn to evaluate SBP/CaO₂ as a surficial manure pit additive under field conditions. The SBP was applied once at the beginning of the 42-day experiment at an application rate of 2.28 ...

Developing Grounded Goals Through Instant Replay Learning, Lisa Meeden, Douglas S. Blank

Computer Science Faculty Research and Scholarship

This paper describes and tests a developmental architecture that enables a robot to explore its world, to find and remember interesting states, to associate these states with grounded goal representations, and to generate action sequences so that it can re-visit these states of interest. The model is composed of feed-forward neural networks that learn to make predictions at two levels through a dual mechanism of motor babbling for discovering the interesting goal states and instant replay learning for developing the grounded goal representations. We compare the performance of the model with grounded goal representations versus random goal representations, and find ...

Combined Model Predictive Control And Scheduling With Dominant Time Constant Compensation, Logan Beal, Junho Park, Damon Petersen, Sean C. Warnick, John Hedengren

All Faculty Publications

Linear model predictive control is extended to both control and optimize a product grade schedule. The proposed methods are time-scaling of the linear dynamics based on throughput rates and grade-based objectives for product scheduling based on a mathematical program with complementarity constraints. The linear model is adjusted with a residence time approximation to time-scale the dynamics based on throughput. Although nonlinear models directly account for changing dynamics, the model form is restricted to linear differential equations to enable fast online cycle times for large-scale and real-time systems. This method of extending a linear time-invariant model for scheduling is designed for ...

Comparing And Improving Facial Recognition Method, Brandon Luis Sierra

Electronic Theses, Projects, and Dissertations

Facial recognition is the process in which a sample face can be correctly identified by a machine amongst a group of different faces. With the never-ending need for improvement in the fields of security, surveillance, and identification, facial recognition is becoming increasingly important. Considering this importance, it is imperative that the correct faces are recognized and the error rate is as minimal as possible. Despite the wide variety of current methods for facial recognition, there is no clear cut best method. This project reviews and examines three different methods for facial recognition: Eigenfaces, Fisherfaces, and Local Binary Patterns to determine ...

Natural Language Processing Based Generator Of Testing Instruments, Qianqian Wang

Electronic Theses, Projects, and Dissertations

Natural Language Processing (NLP) is the field of study that focuses on the interactions between human language and computers. By “natural language” we mean a language that is used for everyday communication by humans. Different from programming languages, natural languages are hard to be defined with accurate rules. NLP is developing rapidly and it has been widely used in different industries. Technologies based on NLP are becoming increasingly widespread, for example, Siri or Alexa are intelligent personal assistants using NLP build in an algorithm to communicate with people. “Natural Language Processing Based Generator of Testing Instruments” is a stand-alone program ...

Utilizing Functional Near-Infrared Spectroscopy For Prediction Of Cognitive Workload In Noisy Work Environments, Ryan Gabbard, Mary E. Fendley, Irfaan A. Dar, Rik Warren, Nasser H. Kashou

Nasser H. Kashou

Occupational noise frequently occurs in the work environment in military intelligence, surveillance, and reconnaissance operations. This impacts cognitive performance by acting as a stressor, potentially interfering with the analysts’ decision-making process. We investigated the effects of different noise stimuli on analysts’ performance and workload in anomaly detection by simulating a noisy work environment. We utilized functional near-infrared spectroscopy (fNIRS) to quantify oxy-hemoglobin (HbO) and deoxy-hemoglobin concentration changes in the prefrontal cortex (PFC), as well as behavioral measures, which include eye tracking, reaction time, and accuracy rate. We hypothesized that noisy environments would have a negative effect on the participant in ...

Can Students Flourish In Engineering Classrooms?, Peggy Boylan-Ashraf, Steven A. Freeman, Mack C. Shelley, Özgür Keleş

Steven A. Freeman

This study investigated the role of a new paradigm in teaching large introductory, fundamental engineering mechanics (IFEM) courses that combined student-centered learning pedagogies and supplemental learning resources. Demographic characteristics in this study included a total of 405 students, of whom 347 (85.7%) are males and 58 are (14.3%) females. The students’ majors included aerospace engineering, agricultural engineering, civil engineering, construction engineering, industrial engineering, materials engineering, and mechanical engineering.
Results of this study, as tested using an independent samples t-test, validated using a nonparametric independent samples test, and a general linear multivariate model analysis, indicated overwhelmingly that there is ...

Calibration Of Soil Compaction Behavior Using Discrete Element Method (Dem), Mohammad A. Sadek, Mehari Tekeste, Mojtaba Naderi

Mehari Tekeste

Soil compaction has potential to reduce crop yield by resisting seed germination and root growth. Modern agricultural farm equipment is getting bigger in size and axle weight that could cause excessive soil compaction. Natures of soil compaction in agricultural fields are not predictable because of non-homogeneous soil condition, and inconsistent wheel trafficking in the field. In this study predicting soil compaction behaviour will be studied for under different three soil moisture using Discrete Element Method (DEM). Discrete Element Method (DEM) is capable to simulate the elastic-plastic soil compaction behavior. Selection of appropriate DEM contact model and calibration of the DEM ...

Discrete Element Modeling (Dem) Of Cone Penetration Testing On Soil With Varying Relative Soil Density, Zamir Syed, Mehari Tekeste, Thomas Way

Mehari Tekeste

Modeling soil-tool interaction is essential for equipment design and performance evaluation on soil behavior responses under loading. Computational tools based on particle-based mechanics such as Discrete Element Modeling (DEM) and Smoothed Particle Hydrodynamics (SPH) have potential in modeling large strain soil dynamic behaviors from soil-tool interaction. The objective of this study is to validate the accuracy and robustness of DEM calibration methodology as it relates to soil deformation during cone penetration on varying initial soil relative density. The influence of factors such as DEM material properties and cone to particle size ratio on DEM cone penetration simulation will be investigated ...