In Operando Mechanism Analysis On Nanocrystalline Silicon Anode Material For Reversible And Ultrafast Sodium Storage, 2018 University of Wollongong
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. Nevertheless, one major obstacle ...
Studies On Stable Crack Growth, 2017 United Arab Emirates University
Studies On Stable Crack Growth, Mohammed Juma Humaid Al-Ghafri
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 ...
Fast On-Line Kernel Density Estimation For Active Object Localization, 2017 Portland State University
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 ...
Innovation Of Driving Gear Train System For Developer Unit Of Lexmark Home Printers, 2017 University of Tennessee, Knoxville
Innovation Of Driving Gear Train System For Developer Unit Of Lexmark Home Printers, Jay A. Crist, Sarah Gore, Kun Xie, Michael Mixoon
University of Tennessee Honors Thesis Projects
No abstract provided.
Projected Nesterov’S Proximal-Gradient Algorithm For Sparse Signal Recovery, 2017 Iowa State University
Projected Nesterov’S Proximal-Gradient Algorithm For Sparse Signal Recovery, Renliang Gu, Aleksandar Dogandžić
Electrical and Computer Engineering Publications
Abstract: We develop a projected Nesterov's proximal-gradient (PNPG) approach for sparse signal reconstruction that combines adaptive step size with Nesterov's momentum acceleration. The objective function that we wish to minimize is the sum of a convex differentiable data-fidelity (negative log-likelihood (NLL)) term and a convex regularization term. We apply sparse signal regularization where the signal belongs to a closed convex set within the closure of the domain of the NLL; the convex-set constraint facilitates flexible NLL domains and accurate signal recovery. Signal sparsity is imposed using the ℓ1 -norm penalty on the signal's linear transform coefficients ...
A Fuzzy Ahp Approach To Compare Transit System Performance In Us Urbanized Areas, 2017 University of Wisconsin - Milwaukee
A Fuzzy Ahp Approach To Compare Transit System Performance In Us Urbanized Areas, Xin Li, Yingling Fan, John W. Shaw, Yunlei Qi
Journal of Public Transportation
Public transit systems in the United States often face multiple policy objectives. Typically, stakeholders desire frequent service on an extensive network, but funding and other resources are constrained, creating complicated relationships between service effectiveness goals and business efficiency goals. Using data from the National Transit Map (NTM), this study evaluated the general performance of transit systems across 294 Urbanized Areas (UZAs) in the US, which were stratified into six peer groups based on population. Transit efficiency and effectiveness were compared by developing a composite business efficiency index score and a composite service effectiveness index score for each urbanized area. The ...
Strategic Level Proton Therapy Patient Admission Planning: A Markov Decision Process Modeling Approach, 2017 University of Arkansas, Fayetteville
Strategic Level Proton Therapy Patient Admission Planning: A Markov Decision Process Modeling Approach, Shengfan Zhang, Ridvan Gedik, Chase Rainwater
Mechanical and Industrial Engineering Faculty Publications
A relatively new consideration in proton therapy planning is the requirement that the mix of patients treated from different categories satisfy desired mix percentages. Deviations from these percentages and their impacts on operational capabilities are of particular interest to healthcare planners. In this study, we investigate intelligent ways of admitting patients to a proton therapy facility that maximize the total expected number of treatment sessions (fractions) delivered to patients in a planning period with stochastic patient arrivals and penalize the deviation from the patient mix restrictions. We propose a Markov Decision Process (MDP) model that provides very useful insights in ...
Children’S Social Network: Kids Club, 2017 California State University, San Bernardino
Children’S Social Network: Kids Club, Eiman Alrashoud
Electronic Theses, Projects, and Dissertations
Young children often have a profound interest that if nurtured, would develop to great social cues and skills thereby improving their social aspects of life. Parents can conveniently benefit from a swift data sharing in the collaborative scrutiny of their kid's participation, in public activities facilitated through the internet digital technology. To facilitate the involvement of shared activities among children, an interactive website is essential. The aim of my project is to develop a website that is intended to be an interactive platform for a variety of events selection. Additionally, the website will aid parents in the creation, discovery ...
Agen Bola Terpercaya Warung757.Net, 2017 K-12 Data Center Dakota State University
Agen Bola Terpercaya Warung757.Net, Defaonline Blog
Investigation Into The Local Nature Of Change Of Frequency In Electrical Power Systems, 2017 Dublin Institute of Technology
Investigation Into The Local Nature Of Change Of Frequency In Electrical Power Systems, Damien Doheny
Student Journal of Energy Research
Over the coming years it is expected that considerably more wind power will be connected to the Irish power system. This will result in a power system that at times of high wind power penetration will operate with very low inertia, making the system susceptible to large rate of change of frequency (RoCoF) events due to disturbances. These high RoCoF events could result in the cascade tripping of generators connected to the grid resulting in complete shutdown of the system. This paper investigates the differences between local RoCoFs seen at individual buses and system wide RoCoFs seen across the entire ...
Ray Tracing Technique For The Optimal Design Of An Air Heater Concentrating Collector, 2017 Dublin Institute of Technology
Ray Tracing Technique For The Optimal Design Of An Air Heater Concentrating Collector, Fernando Guerreiro
Student Journal of Energy Research
There is a wide range of micro and macro renewable and sustainable energy methods available for reducing the inefficient use of fossil fuels, minimising carbon emissions and maximising energy use in a clean and environment-friendly process. Solar energy plays an important role due to its abundance and ubiquity. Solar air heaters convert solar energy into hot air to be used for heating and drying of various products. The objective of this paper is to define and optimise the geometry of an inverted absorber compound parabolic concentrating (IACPC) collector for air heating. This optimisation was developed based on an optical analysis ...
Short Term Demand Forecasting For The Integrated Electricity Market, 2017 Dublin Institute of Technology
Short Term Demand Forecasting For The Integrated Electricity Market, Katie Kavanagh
Student Journal of Energy Research
This paper presents a means for the short term load forecasting (STLF) of electricity. The forthcoming Integrated-Single Electricity Market (I-SEM) diverges from the current market structure (the Single Electricity Market or SEM), with significant impacts on Irish supply companies, creating a need for these companies to be able to accurately forecast their customers’ load in the Day Ahead. Using a Double Seasonal Exponential Smoothing variation of the Holt-Winters method that factors in an error correction, data from the Irish market was trained and used to forecast a supply company’s demand resulting in an average daily MAPE (Mean Absolute Percentage ...
Toward Scalable Stochastic Unit Commitment. Part 2: Solver Configuration And Performance Assessment, Kwok Cheung, Dinakar Gade, Cesar Silva-Monroy, Sarah M. Ryan, Jean-Paul Watson, Roger Wets, David L. Woodruff
Sarah M. Ryan
In this second portion of a two-part analysis of a scalable computa- tional approach to stochastic unit commitment, we focus on solving stochastic mixed-integer programs in tractable run-times. Our solution technique is based on Rockafellar and Wets' progressive hedging algorithm, a scenario-based decomposi- tion strategy for solving stochastic programs. To achieve high-quality solutions in tractable run-times, we describe critical, novel customizations of the progressive hedging algorithm for stochastic unit commitment. Using a variant of the WECC- 240 test case with 85 thermal generation units, we demonstrate the ability of our approach to solve realistic, moderate-scale stochastic unit commitment problems with ...
Optimal Replacement In The Proportional Hazards Model With Semi-Markovian Covariate Process And Continuous Monitoring, Xiang Wu, Sarah M. Ryan
Sarah M. Ryan
Motivated by the increasing use of condition monitoring technology for electrical transformers, this paper deals with the optimal replacement of a system having a hazard function that follows the proportional hazards model with a semi-Markovian covariate process, which we assume is under continuous monitoring. Although the optimality of a threshold replacement policy to minimize the long-run average cost per unit time was established previously in a more general setting, the policy evaluation step in an iterative algorithm to identify optimal threshold values poses computational challenges. To overcome them, we use conditioning to derive an explicit expression of the objective in ...
Statistical Metrics For Assessing The Quality Of Wind Power Scenarios For Stochastic Unit Commitment, 2017 Iowa State University
Statistical Metrics For Assessing The Quality Of Wind Power Scenarios For Stochastic Unit Commitment, Didem Sari, Youngrok Lee, Sarah M. Ryan, David L. Woodruff
Sarah M. Ryan
In power systems with high penetration of wind generation, probabilistic scenarios are generated for use in stochastic formulations of day-ahead unit commitment problems. To minimize the expected cost, the wind power scenarios should accurately represent the stochastic process for available wind power. We employ some statistical evaluation metrics to assess whether the scenario set possesses desirable properties that are expected to lead to a lower cost in stochastic unit commitment. A new mass transportation distance rank histogram is developed for assessing the reliability of unequally likely scenarios. Energy scores, rank histograms and Brier scores are applied to alternative sets of ...
Toward Scalable Stochastic Unit Commitment. Part 1: Load Scenario Generation, 2017 Iowa State University
Toward Scalable Stochastic Unit Commitment. Part 1: Load Scenario Generation, Yonghan Feng, Ignacio Rios, Sarah M. Ryan, Kai Spurkel, Jean-Paul Watson, Roger Wets, David L. Woodruff
Sarah M. Ryan
Unit commitment decisions made in the day-ahead market and during subsequent reliability assessments are critically based on forecasts of load. Tra- ditional, deterministic unit commitment is based on point or expectation-based load forecasts. In contrast, stochastic unit commitment relies on multiple load sce- narios, with associated probabilities, that in aggregate capture the range of likely load time-series. The shift from point-based to scenario-based forecasting necessi- tates a shift in forecasting technologies, to provide accurate inputs to stochastic unit commitment. In this paper, we discuss a novel scenario generation method- ology for load forecasting in stochastic unit commitment, with application to ...
Scenario Construction And Reduction Applied To Stochastic Power Generation Expansion Planning, 2017 Iowa State University
Scenario Construction And Reduction Applied To Stochastic Power Generation Expansion Planning, Yonghan Feng, Sarah M. Ryan
Sarah M. Ryan
A challenging aspect of applying stochastic programming in a dynamic setting is to construct a set of discrete scenarios that well represents multivariate stochastic processes for uncertain parameters. Often this is done by generating a scenario tree using a statistical procedure and then reducing its size while maintaining its statistical properties. In this paper, we test a new scenario reduction heuristic in the context of long-term power generation expansion planning. We generate two different sets of scenarios for future electricity demands and fuel prices by statistical extrapolation of long-term historical trends. The cardinality of the first set is controlled by ...
Obtaining Lower Bounds From The Progressive Hedging Algorithm For Stochastic Mixed-Integer Programs, Dinakar Gade, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, Roger J-B Wets, David L. Woodruff
Sarah M. Ryan
We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Computing lower bounds in the PHA allows one to assess the quality of the solutions generated by the algorithm contemporaneously. The lower bounds can be computed in any iteration of the algorithm by using dual prices that are calculated during execution of the standard PHA. We report computational results on stochastic unit commitment and stochastic server location problem instances, and explore the relationship between key PHA parameters and the quality of the resulting lower bounds.
Optimal Price And Quantity Of Refurbished Products, 2017 Iowa State University
Optimal Price And Quantity Of Refurbished Products, Jumpol Vorasayan, Sarah M. Ryan
Sarah M. Ryan
Many retail product returns can be refurbished and resold, typically at a reduced price. The price set for the refurbished products affects the demands for both new and refurbished products, while the refurbishment and resale activities incur costs. To maximize profit, a manufacturer in a competitive market must carefully choose the proportion of returned products to refurbish and their sale price. We model the sale, return, refurbishment, and resale processes in an open queueing network and formulate a mathematical program to find the optimal price and proportion to refurbish. Examination of the optimality conditions reveals the different situations in which ...
Temporal Vs. Stochastic Granularity In Thermal Generation Capacity Planning With Wind Power, 2017 Iowa State University
Temporal Vs. Stochastic Granularity In Thermal Generation Capacity Planning With Wind Power, Shan Jin, Audun Botterud, Sarah M. Ryan
Sarah M. Ryan
We propose a stochastic generation expansion model, where we represent the long-term uncertainty in the availability and variability in the weekly wind pattern with multiple scenarios. Scenario reduction is conducted to select a representative set of scenarios for the long-term wind power uncertainty. We assume that the short-term wind forecast error induces an additional amount of operating reserves as a predefined fraction of the wind power forecast level. Unit commitment (UC) decisions and constraints for thermal units are incorporated into the expansion model to better capture the impact of wind variability on the operation of the system. To reduce computational ...