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Articles 31201 - 31230 of 196383

Full-Text Articles in Engineering

H2020 Auto-Dan Project: Enhance The Participation Of The Community To Demand Response By Providing The State-Of-The-Art Technological And Policy Solution, Rene Peeren, Dharmesh Dabhi, John Dalton Jan 2023

H2020 Auto-Dan Project: Enhance The Participation Of The Community To Demand Response By Providing The State-Of-The-Art Technological And Policy Solution, Rene Peeren, Dharmesh Dabhi, John Dalton

Conference papers

The growing demand for electricity in Europe has increased the need for a more flexible and sustainable power system. In recent years, Demand Response (DR) has emerged as a promising solution to meet this need, by providing an opportunity for residential and smaller commercial consumers to actively participate in the electricity market. This research paper investigates the potential for DR among the residential community and small commercial electricity consumers in Europe and identifies the technological barriers and drivers that impact consumer engagement with DR programs in Europe. The different DR opportunities are identified and validated at the six different demo …

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Quantum Classifiers For Video Quality Delivery, Tautvydas Lisas, Ruairí De Fréin Jan 2023

Quantum Classifiers For Video Quality Delivery, Tautvydas Lisas, Ruairí De Fréin

Conference papers

Classical classifiers such as the Support Vector Classifier (SVC) struggle to accurately classify video Quality of Delivery (QoD) time-series due to the challenge in constructing suitable decision boundaries using small amounts of training data. We develop a technique that takes advantage of a quantum-classical hybrid infrastructure called Quantum-Enhanced Codecs (QEC). We evaluate a (1) purely classical, (2) hybrid kernel, and (3) purely quantum classifier for video QoD congestion classification, where congestion is either low, medium or high, using QoD measurements from a real networking test-bed. Findings show that the SVC performs the classification task 4% better in the low congestion …

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Optimising Electric Vehicle Charging Infrastructure In Dublin Using Geecharge, Alexander Mutua Mutiso, Ruairí De Fréin, Ali Malik, Eliel Kibanza, Marco Sahbane, Maxime Pantel Jan 2023

Optimising Electric Vehicle Charging Infrastructure In Dublin Using Geecharge, Alexander Mutua Mutiso, Ruairí De Fréin, Ali Malik, Eliel Kibanza, Marco Sahbane, Maxime Pantel

Conference papers

Range anxiety poses a hurdle to the adoption of Electric Vehicles (EVs), as drivers worry about running out of charge without timely access to a Charging Point (CP). We present novel methods for optimising the distribution of CPs, namely, EV portacharge and GEECharge. These solutions distribute CPs in Dublin, in this paper, by considering the population density and Points Of Interest (POIs) or road traffic. The object of this paper is to (1) develop and evaluate methods to distribute CPs in Dublin city; (2) optimise CP allocation; (3) visualise paths in the graph network to show the most used roads …

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Integrating The Spatial Pyramid Pooling Into 3d Convolutional Neural Networks For Cerebral Microbleeds Detection, Andre Accioly Veira Jan 2023

Integrating The Spatial Pyramid Pooling Into 3d Convolutional Neural Networks For Cerebral Microbleeds Detection, Andre Accioly Veira

CCAC Theses and Dissertations

Cerebral microbleeds (CMB) are small foci of chronic blood products in brain tissues that are critical markers for cerebral amyloid angiopathy. CMB increases the risk of symptomatic intracerebral hemorrhage and ischemic stroke. CMB can also cause structural damage to brain tissues resulting in neurologic dysfunction, cognitive impairment, and dementia. Due to the paramagnetic properties of blood degradation products, CMB can be better visualized via susceptibility-weighted imaging (SWI) than magnetic resonance imaging (MRI).CMB identification and classification have been based mainly on human visual identification of SWI features via shape, size, and intensity information. However, manual interpretation can be biased. Visual screening …

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Architecting Future Multi-Modal Networks Coexistence, Generalization & Testbeds, Maqsood Ahamed Abdul Careem Jan 2023

Architecting Future Multi-Modal Networks Coexistence, Generalization & Testbeds, Maqsood Ahamed Abdul Careem

Legacy Theses & Dissertations (2009 - 2024)

Next Generation (xG) wireless networks are poised to revolutionize the way people, devices, data and processes sense, communicate, interact, and collectively enable a wide range of emerging applications, ranging from smart cities, connected healthcare, and advanced vehicular communication to extended reality. To facilitate this seamless interoperability, these networks need to evolve to accommodate and integrate multiple modalities in communication/ sensing technologies and spectrum, heterogeneous networks, trends in signal-processing (statistical, AI-driven, and distributed systems), centralized and distributed architectures, and device/ network hardware resources. However, to cater to the high-target metrics and wide-range of applications, these multi-modal networks must efficiently address multi-faceted …

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Novel Nickel-Loaded Activated Carbon Cathodes For Hydrogen Production In Microbial Electrolysis Cells, Daniel Alejandro Moreno Jimenez Jan 2023

Novel Nickel-Loaded Activated Carbon Cathodes For Hydrogen Production In Microbial Electrolysis Cells, Daniel Alejandro Moreno Jimenez

Legacy Theses & Dissertations (2009 - 2024)

Microbial electrolysis cells (MECs) can electrochemically produce green hydrogen from waste streams. Although MECs are excellent options for implementing an energy recovery process while treating wastewater, the cathode side still hinders practical applications. Platinum (Pt) has been the top reference for hydrogen evolution reaction (HER) in MECs, however, Pt is not practical due to the high capital cost. Inexpensive nickel-loaded activated carbon (Ni/AC) cathodes were recently developed for replacing Pt in MECs and have shown comparable performance to Pt. This dissertation aims to breakthrough the current cathode challenges regarding the catalytic activity, manufacturing, and operational concept toward a cost-competitive scaling-up …

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Distillery, Clare Nicholas, Patrick Hanlon Jan 2023

Distillery, Clare Nicholas, Patrick Hanlon

Williams Honors College, Honors Research Projects

The goal for this project is to make a cost effective still. We will be implementing cost saving parts to create a cheap but effective still. From initial research conducted, we will try to combine a stainless steel still and copper still together so that the cheaper material (stainless steel) and the component that removes sulfur compounds (copper) are both implemented. The ME side of the project will focus on the actual design and construction of the parts that will be implemented into the still. Included in the design process will be calculations of heat transfer for the current and …

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An Experimentally Validated Computational Model For The Degradation And Fracture Of Magnesium-Based Implants In A Chemically Corrosive Environment, Mark M. Ousdigian Jan 2023

An Experimentally Validated Computational Model For The Degradation And Fracture Of Magnesium-Based Implants In A Chemically Corrosive Environment, Mark M. Ousdigian

Dissertations, Master's Theses and Master's Reports

In the orthopedic and cardiovascular fields there is a growing interest for biodegradable implants, which can be naturally degraded in the body environment over time so that no extraction surgery is required. These implants must be designed to maintain their strength until the fracture has healed in the body, which could be influenced by many factors such as -the patient’s age, activities, body weight, pre-existing conditions etc. Hence, an ideal implant design should be done on a patient-by-patient basis. In the present work, a computational model is developed to predict the degradation and fracture of magnesium-based implants in a stress-coupled …

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Business Meeting Report (Secretary's And Treasurer's Report), Academy Editors Jan 2023

Business Meeting Report (Secretary's And Treasurer's Report), Academy Editors

Journal of the Arkansas Academy of Science

No abstract provided.

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Csc 10400 Discrete Math Recitation - Tutorial Playlist, Rose Wong Jan 2023

Csc 10400 Discrete Math Recitation - Tutorial Playlist, Rose Wong

Open Educational Resources

Playlist for various discrete math topics covered in CSC 10400

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การศึกษาเชิงเปรียบเทียบการตัดสินใจผลิตเองหรือจ้างผลิต: กรณีศึกษา ระบบพลังงานแสงอาทิตย์ในโรงงานชิ้นส่วนยานยนต์, เสาวลักษณ์ สระธรรม Jan 2023

การศึกษาเชิงเปรียบเทียบการตัดสินใจผลิตเองหรือจ้างผลิต: กรณีศึกษา ระบบพลังงานแสงอาทิตย์ในโรงงานชิ้นส่วนยานยนต์, เสาวลักษณ์ สระธรรม

Chulalongkorn University Theses and Dissertations (Chula ETD)

การวิจัยครั้งนี้มีวัตถุประสงค์ 1) เพื่อออกแบบระบบผลิตไฟฟ้าเซลล์แสงอาทิตย์แบบติดตั้งบนหลังคา และ 2) เพื่อเปรียบเทียบความคุ้มค่าของโครงการระหว่างการผลิตเองกับการจ้างผลิต กรณีศึกษาโรงงานชิ้นส่วนยานยนต์แห่งหนึ่งในจังหวัดระยอง ในการออกแบบติดตั้งจะวิเคราะห์จากโหลดโปรไฟล์ และพื้นที่ติดตั้งของโรงงาน ส่วนความคุ้มค่าของโครงการจะวิเคราะห์จากต้นทุนเฉลี่ยต่อหน่วยไฟฟ้าตลอดอายุโครงการของทั้งสองรูปแบบ แล้วนำมาเปรียบเทียบกัน ผลการวิจัยครั้งนี้ พบว่าโรงงานเหมาะจะติดตั้งระบบขนาด 329.84 กิโลวัตต์ และมีต้นทุนค่าไฟฟ้าเฉลี่ยต่อหน่วยแบบผลิตเอง และจ้างผลิต 2.91 บาทต่อหน่วย และ 3.11 บาทต่อหน่วย ตามลำดับ และในกรณีนี้หากต้นทุนแผงเซลล์แสงอาทิตย์เพิ่มขึ้นมากกว่าร้อยละ 21 หรือค่าไฟฟ้าผันแปรลดลงมากกว่าร้อยละ 66 หรืออัตราผลตอบแทนขั้นต่ำที่ยอมรับได้เพิ่มขึ้นตั้งแต่ร้อยละ 12 จะทำให้ต้นทุนเฉลี่ยต่อหน่วยไฟฟ้าตลอดอายุโครงการของการผลิตเองมากกว่าการจ้างผลิต ดังนั้นจึงควรเลือกดำเนินโครงการแบบจ้างผลิต ข้อเสนอแนะจะเห็นว่าต้นทุนเฉลี่ยต่อหน่วยไฟฟ้าตลอดอายุโครงการแบบผลิตเองถูกกว่าแบบจ้างผลิตประมาณ 5,324 บาทต่อเดือน ซึ่งไม่มากนักเทียบกับเงินลงทุนโครงการ ดังนั้นการเลือกตัดสินใจควรพิจารณาปัจจัยความเสี่ยงร่วมด้วย เนื่องจากระบบจำเป็นต้องมีความมั่นคงและความต่อเนื่อง ไม่ควรเกิดเหตุไฟฟ้าตก หรือไฟฟ้าดับ ซึ่งการจ้างผลิตจะได้ผู้เชี่ยวชาญในการติดตั้งและดูแลระบบมากกว่า และในงานวิจัยนี้ยังไม่ได้มีการศึกษาในส่วนนี้ ดังนั้นการศึกษาครั้งถัดไปควรพิจารณาปัจจัยความเสี่ยงของระบบ และมูลค่าความเสียหายที่อาจจะเกิดขึ้นจากความเสี่ยงต่างๆ ร่วมด้วย

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การพัฒนาระบบตรวจวัดสารประกอบอินทรีย์ระเหยง่ายโดยใช้ชุดอุปกรณ์เพิ่มความเข้มข้นพร้อมการปรับเปลี่ยนอุณหภูมิ, พรภวิษย์ สินสุขอุดมชัย Jan 2023

การพัฒนาระบบตรวจวัดสารประกอบอินทรีย์ระเหยง่ายโดยใช้ชุดอุปกรณ์เพิ่มความเข้มข้นพร้อมการปรับเปลี่ยนอุณหภูมิ, พรภวิษย์ สินสุขอุดมชัย

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้มีวัตถุประสงค์เพื่อพัฒนาระบบตรวจวัดสารประกอบอินทรีย์ระเหยง่าย (Volatile organic compounds : VOCs) โดยใช้ชุดอุปกรณ์เพิ่มความเข้มข้น (Preconcentrator Array) ที่สามารถปรับเปลี่ยนอุณหภูมิได้ เพื่อให้สามารถเพิ่มความไว (sensitivity) และความจำเพาะ (selectivity) ในการตรวจวัดสาร VOCs ตัวอย่างที่มีหลายสารองค์ประกอบได้อย่างมีประสิทธิภาพ ระบบที่พัฒนาขึ้นนี้ได้นำสารดูดซับชนิดต่าง ๆ เช่น Tenax TA, Carbopack X และ CarboTrap B มาทดสอบใช้ โดยอาศัยรูปแบบของการให้อุณหภูมิและวิธีการวิเคราะห์ที่เหมาะสมเพื่อเพิ่มความแม่นยำในการตรวจวัดและการแยกแยะสารประกอบ VOCs ในตัวอย่างเป้าหมาย ในงานวิจัยนี้ได้ทำการออกแบบและพัฒนาระบบควบคุมความร้อนโดยใช้ไมโครคอนโทรลเลอร์ในการควบคุมการให้ความร้อนกับอุปกรณ์เพิ่มความเข้มข้น (Preconcentrator) จากนั้นได้ทำการทดสอบระบบที่พัฒนาขึ้นโดยทำการตรวจวัด VOCs ในสารตัวอย่างชนิดต่าง ๆ ที่ความเข้มข้นต่ำและวิเคราะห์ผลการวัดทดสอบด้วยการวิเคราะห์องค์ประกอบหลัก (Principal Component Analysis : PCA) จากผลการทดลองแสดงให้เห็นว่าระบบที่พัฒนาจากการใช้ชุดเพิ่มความเข้มข้นนี้สามารถตรวจวัดสาร VOCs ตัวอย่างที่เป็นตัวบ่งชี้ทางชีวภาพที่สำคัญของโรคโควิด-19 ได้อย่างมีประสิทธิภาพ นอกจากนี้ระบบที่พัฒนาขึ้นยังสามารถตรวจวัดสารตัวอย่างที่ประกอบด้วย VOCs ชนิดต่าง ๆ กันได้อย่างเหมาะสมเนื่องจากความสามารถในการเพิ่มความจำเพาะในการวัดของชุดอุปกรณ์เพิ่มความเข้มข้น ซึ่งระบบที่พัฒนาขึ้นในงานวิจัยนี้จะมีประโยชน์ในการประยุกต์ใช้ทางด้านการแพทย์และสาธารณสุข โดยเฉพาะอย่างยิ่งการตรวจคัดกรองโรคแบบไม่รุกล้ำและการตรวจวัดสาร VOCs ในสิ่งแวดล้อม

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Optimal Battery Sizing For An Industrial Factory: A Hybrid Approach Using Particle Swarm Optimization And Load Estimation, Muhammad Hammad Hassan Jan 2023

Optimal Battery Sizing For An Industrial Factory: A Hybrid Approach Using Particle Swarm Optimization And Load Estimation, Muhammad Hammad Hassan

Chulalongkorn University Theses and Dissertations (Chula ETD)

Solar photovoltaic (PV) systems are crucial in addressing global energy demands with clean and renewable electricity. However, the intermittent nature of solar energy requires integrating batteries to ensure a reliable power supply. This study focuses on optimizing battery size for solar PV systems to balance energy storage during high irradiance periods and discharge during low sunlight, thereby enhancing system efficiency and cost-effectiveness. Accurate load forecasting and load estimation, essential for effective energy storage management, is achieved using long short-term memory (LSTM) networks, which excel in handling time series data. Particle Swarm Optimization (PSO) is then employed to determine the optimal …

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Development Of A Vascularized Osteogenic Implant Using Fused Glycosaminoglycan-Chitosan Microcapsules, Charles Michael Gabrion Jan 2023

Development Of A Vascularized Osteogenic Implant Using Fused Glycosaminoglycan-Chitosan Microcapsules, Charles Michael Gabrion

Wayne State University Theses

Osteoarthritis remains a poorly treatable outcome of traumatic cartilage injury as cartilage is unable to self-repair. Unfortunately, roughly 10% of all adults in the United States have been diagnosed with osteoarthritis although the true fraction is likely at least 30%. While the main focus of osteoarthritis research has been on treating damage to the cartilage, osteoarthritis will also lead to damage to the adjacent trabecular bone due to wear via shearing down of the tissue’s surface. Considering this, in conjuncture with transplanted cartilages’ inability to integrate into the native tissue, unlike the surrounding bone, the significance of a combined osteochondral …

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Heat Release And Flame Scale Effects On Turbulence Dynamics In Confined Premixed Flows, Max Fortin Jan 2023

Heat Release And Flame Scale Effects On Turbulence Dynamics In Confined Premixed Flows, Max Fortin

Electronic Theses and Dissertations, 2020-2023

As industry transitions to a net-zero carbon future, turbulent premixed combustion will remain an integral process for power generating gas turbines and are also desired for aviation engines due to their ability to minimize pollutant emissions. However, accurately predicting the behavior of a turbulent reacting flow field remains a challenge. To better understand the dynamics of premixed reacting flows, this study experimentally investigates the evolution of turbulence in a high-speed bluff-body combustor. The combustor is operated across a range of equivalence ratios from 0.7-1 to quantify the role of heat release and flame scales on the evolution of turbulence as …

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An Assessment Of The Effectiveness Of Using Data Analytics To Predict Death Claim Seasonality And Protection Policy Review Lapses In A Life Insurance Company, Jennifer Loftus Jan 2023

An Assessment Of The Effectiveness Of Using Data Analytics To Predict Death Claim Seasonality And Protection Policy Review Lapses In A Life Insurance Company, Jennifer Loftus

ICT

Data analytics tools are becoming increasingly common in the life insurance industry. This research considers two use cases for predictive analytics in a life insurance company based in Ireland. The first case study relates to the use of time series models to forecast the seasonality of death claim notifications. The baseline model predicted no seasonal variation in death claim notifications over a calendar year. This reflects the life insurance company’s current approach, whereby it is assumed that claims are notified linearly over a calendar year. More accurate forecasting of death claims seasonality would enhance the life insurance company’s cashflow planning …

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The Role Of Data Analytics To Address Water Stress In Africa, Khalil Beladda Jan 2023

The Role Of Data Analytics To Address Water Stress In Africa, Khalil Beladda

ICT

Water stress, a global concern transcending geographical boundaries, significantly impacts the African continent. Affecting one in three people in Africa, sustainable water management is imperative for ecological and human welfare. This research emphasizes the pivotal role of data analytics in addressing water stress challenges in Africa and beyond.

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Recurrent Neural Networks For Flash Gdp Estimates In Ireland: A Comparison With Traditional Econometric Methods, Justin Flannery Jan 2023

Recurrent Neural Networks For Flash Gdp Estimates In Ireland: A Comparison With Traditional Econometric Methods, Justin Flannery

ICT

GDP is the single most important barometer for the health of an economy. It’s an important input into the decision making processes of government, industry and state institutions such as central banks. To be useful as an indicator, GDP estimates need to be both timely and accurate. To meet the needs of users, many national statistical institutes publish early or flash estimates of GDP which are produced within 30 days after the end of a quarter. Given the long lags involved in the data collection processes which feed into GDP estimates, these flash estimates are often largely model based. Within …

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Pronostic Of Colo-Rectal Cancer (Crc) Using Machine Learning Models On Organoids Derived Of Patient, Claudia Andrea Leiva Acevedo Jan 2023

Pronostic Of Colo-Rectal Cancer (Crc) Using Machine Learning Models On Organoids Derived Of Patient, Claudia Andrea Leiva Acevedo

ICT

Colorectal Cancer (CRC) is a globally prevalent and deadly carcinoma, necessitating advanced treatment approaches. Despite ongoing advancements, the mortality rate remains high. Various biological models, including animal studies, cell lines, and the emerging organoid model, contribute to understanding molecular mechanisms. Organoids, 3D cultures derived from tumor epithelial cells, offer advantages such as enhanced diversity, genetic modification, and extended culture capabilities. Recent applications of machine learning (ML) in predicting CRC treatment responses using organoids and tissue data indicate a promising avenue for advancing personalized therapies.

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Unlocking The Pragmatics Of Emoji: Evaluation Of The Integration Of Pragmatic Markers For Sarcasm Detection, Niamh Farnham Jan 2023

Unlocking The Pragmatics Of Emoji: Evaluation Of The Integration Of Pragmatic Markers For Sarcasm Detection, Niamh Farnham

ICT

Emojis have become an integral element of online communications, serving as a powerful, under-utilised resource for enhancing pragmatic understanding in NLP. Previous works have highlighted their potential for improvement of more complex tasks such as the identification of figurative literary devices including sarcasm due to their role in conveying tone within text. However present state-of-the-art does not include the consideration of emoji or adequately address sarcastic markers such as sentiment incongruence. This work aims to integrate these concepts to generate more robust solutions for sarcasm detection leveraging enhanced pragmatic features from both emoji and text tokens. This was achieved by …

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Evaluating The Potential Of Ensemble Learning For One Day-Ahead Forecasting Of Power System Demand In Ireland, Karol Skowronski Jan 2023

Evaluating The Potential Of Ensemble Learning For One Day-Ahead Forecasting Of Power System Demand In Ireland, Karol Skowronski

ICT

Accurate One Day-Ahead Demand Forecasting (ODADF) is crucial for electrical network reliability, the environment, and trading markets. While individual models face challenges in achieving accurate predictions, ensemble learning models have emerged as potential solution. They have achieved success in ODADF in several countries; however, there has been no research conducted for the Irish power system. Therefore, research objectives were formed, to develop a framework of ensemble learning models, evaluate their performance, and examine their potential for ODADF in Ireland, to fill the gap. Experimentation, and CRISP-DM were selected as primary research methodology, and project management framework, respectively. The development of …

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Additively Manufactured Carbon Fiber- Reinforced Thermoplastic Composite Mold Plates For Injection Molding Process, C. Bivens, A. Wood, D. Ruble, M. Rangapuram, S. K. Dasari, K. Chandrashekhara, J. Degrange Jan 2023

Additively Manufactured Carbon Fiber- Reinforced Thermoplastic Composite Mold Plates For Injection Molding Process, C. Bivens, A. Wood, D. Ruble, M. Rangapuram, S. K. Dasari, K. Chandrashekhara, J. Degrange

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Polymer injection molding processes have been used to create high-volume parts quickly and efficiently. Injection molding uses mold plates that are traditionally made of very hard tool steels, such as P20 steel, which is extremely heavy and has very long lead times to build new molds. In this study, composite-based additive manufacturing (CBAM) was used to create mold plates using long-fiber carbon fiber and polyether ether ketone (PEEK). These mold plates were installed in an injection molding machine, and rectangular flat plates were produced using Lustran 348 acrylonitrile butadiene styrene (ABS). Tensile and flexural testing was performed on these parts …

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Fine-Grained Activity Classification In Assembly Based On Multi-Visual Modalities, Haodong Chen, Niloofar Zendehdel, Ming-Chuan Leu, Zhaozheng Yin Jan 2023

Fine-Grained Activity Classification In Assembly Based On Multi-Visual Modalities, Haodong Chen, Niloofar Zendehdel, Ming-Chuan Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Assembly activity recognition and prediction help to improve productivity, quality control, and safety measures in smart factories. This study aims to sense, recognize, and predict a worker's continuous fine-grained assembly activities in a manufacturing platform. We propose a two-stage network for workers' fine-grained activity classification by leveraging scene-level and temporal-level activity features. The first stage is a feature awareness block that extracts scene-level features from multi-visual modalities, including red, green blue (RGB) and hand skeleton frames. We use the transfer learning method in the first stage and compare three different pre-trained feature extraction models. Then, we transmit the feature information …

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Comparison Of The Thermal Stability In Equal-Channel-Angular-Pressed And High-Pressure-Torsion-Processed Fe–21cr–5al Alloy, Maalavan Arivu, Andrew Hoffman, Jiaqi Duan, Jonathan Poplawsky, Xinchang Zhang, Frank W. Liou, Rinat Islamgaliev, Ruslan Valiev, Haiming Wen Jan 2023

Comparison Of The Thermal Stability In Equal-Channel-Angular-Pressed And High-Pressure-Torsion-Processed Fe–21cr–5al Alloy, Maalavan Arivu, Andrew Hoffman, Jiaqi Duan, Jonathan Poplawsky, Xinchang Zhang, Frank W. Liou, Rinat Islamgaliev, Ruslan Valiev, Haiming Wen

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Nanostructured Steels Are Expected to Have Enhanced Irradiation Tolerance and Improved Strength. However, They Suffer from Poor Microstructural Stability at Elevated Temperatures. in This Study, Fe–21Cr–5Al–0.026C (Wt%) Kanthal D (KD) Alloy Belonging to a Class of (FeCrAl) Alloys Considered for Accident-Tolerant Fuel Cladding in Light-Water Reactors is Nanostructured using Two Severe Plastic Deformation Techniques of Equal-Channel Angular Pressing (ECAP) and High-Pressure Torsion (HPT), and their Thermal Stability between 500–700 °C is Studied and Compared. ECAP KD is Found to Be Thermally Stable Up to 500 °C, Whereas HPT KD is Unstable at 500 °C. Microstructural Characterization Reveals that ECAP KD …

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Static I-V Based Pim Evaluation For Spring And Fabric-Over-Foam Contacts, Kalkidan W. Anjajo, Yang Xu, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Jonghyun Park, Chulsoon Hwang Jan 2023

Static I-V Based Pim Evaluation For Spring And Fabric-Over-Foam Contacts, Kalkidan W. Anjajo, Yang Xu, Shengxuan Xia, Yuchu He, Haicheng Zhou, Hanfeng Wang, Jonghyun Park, Chulsoon Hwang

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Spring Clips and Fabric-Over-Foams (FOFs) Are Widely Used in Mobile Devices for Electrical Connection Purposes. However, the Imperfect Metallic Connections Tend to Induce Passive Intermodulation (PIM), Resulting in a Receiver Sensitivity Degradation, Known as RP Desensitization. Due to the Complexity of the PIM Characterization, there is Not Yet a Way to Evaluate PIM Performance using a Simple Setup for Environments Like Factories. in This Paper, a Current-Voltage (I-V) Behavior-Based PIM Evaluation Method is Proposed and Validated with Various Metallic Contacts and Contact Forces. the Test Results Demonstrated the Feasibility of the PIM Performance Evaluation based on the Measured Static I-V …

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Correction: Modeling Phase Selection And Extended Solubility In Rapid Solidified Alloys (Metallurgical And Materials Transactions A, (2023), 10.1007/S11661-023-07221-7), Azeez Akinbo, Yijia Gu Jan 2023

Correction: Modeling Phase Selection And Extended Solubility In Rapid Solidified Alloys (Metallurgical And Materials Transactions A, (2023), 10.1007/S11661-023-07221-7), Azeez Akinbo, Yijia Gu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In the original online version of this article the reference citation in Fig. 3b was incorrect. The original article was corrected.

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Application Of A Variable Path Length Repetitive Process Control For Direct Energy Deposition Of Thin-Walled Structures, Elias B. Snider, Douglas A. Bristow Jan 2023

Application Of A Variable Path Length Repetitive Process Control For Direct Energy Deposition Of Thin-Walled Structures, Elias B. Snider, Douglas A. Bristow

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Direct Energy Deposition (DED) Additive Manufacturing is Well Suited to Fabricating Large Thin-Walled Metal Structures Such as Rocket Nozzles but Suffers from Layer-To-Layer Defect Propagation. Propagating Defects May Exhibit as Slumping or a Ripple in Bead Geometry. Recent Works Have Used Repetitive Process Control (RPC) Methods for Additive Manufacturing to Stabilize the Layer-Wise Defect Propagation, But These Methods Require Repetition of the Same Path. However, Typical Thin-Wall DED Applications, Sometimes Referred to as Vase Structures, Have Changing Paths with Each Layer Such as Expanding or Contracting Diameters and Changing Profiles. This Paper Presents an Extension to Optimal RPC that Uses …

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Reinforcement Learning-Guided Quadratically Constrained Quadratic Programming For Enhanced Convergence And Optimality, Chaoying Pei, Zhi Xu, Sixiong You, Jeffrey Sun, Ran Dai Jan 2023

Reinforcement Learning-Guided Quadratically Constrained Quadratic Programming For Enhanced Convergence And Optimality, Chaoying Pei, Zhi Xu, Sixiong You, Jeffrey Sun, Ran Dai

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In the context of Quadratically Constrained Quadratic Programming (QCQP) with dynamic parameters, the effectiveness of various optimization approaches is heavily influenced by the quality of the initial guess. To address this challenge, this paper proposes a novel approach that leverages reinforcement learning (RL) to generate high-performing initial guesses for iterative algorithms, with the dynamic parameters serving as inputs. Our approach aims to accelerate convergence and improve the objective value, thereby enabling efficient and effective solutions to the QCQP problem under variability. In this study, we evaluate the proposed approach by applying it to an iterative algorithm, specifically the Iterative Rank …

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Mixed-Input Learning For Multi-Point Landing Guidance With Hazard Avoidance Part Ii: Learning-Based Guidance Algorithm, Sixiong You, Chaoying Pei, Vinay Kenny, Ran Dai, Jeremy R. Rea Jan 2023

Mixed-Input Learning For Multi-Point Landing Guidance With Hazard Avoidance Part Ii: Learning-Based Guidance Algorithm, Sixiong You, Chaoying Pei, Vinay Kenny, Ran Dai, Jeremy R. Rea

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper investigates the three-dimensional (3D) multi-point landing guidance (MLG) problem with hazard avoidance by developing a mixed-input learning-based method to achieve precise and fuel-efficient planetary landing in future Mars missions. Specifically, we aim to find a safe, fuel-efficient landing point and generate a fuel-optimal trajectory simultaneously in real-time. First, by introducing binary variables, the MLG problem is formulated as an optimal control problem with quadratic constraints. Then, by formulating the Hamiltonian function, the necessary conditions of optimality for the MLG problem are obtained, where the critical parameters are identified to represent the complete optimal solution. After that, to find …

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Feature-Based Learning For Optimal Abort Guidance, Vinay Kenny, Sixiong You, Godfrey Hendrix, Chaoying Pei, Roha Gul, Ran Dai, Jeremy R. Rea Jan 2023

Feature-Based Learning For Optimal Abort Guidance, Vinay Kenny, Sixiong You, Godfrey Hendrix, Chaoying Pei, Roha Gul, Ran Dai, Jeremy R. Rea

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The abort mission refers to the mission where the landing vehicle needs to terminate the landing mission when an anomaly happens and be safely guided to the desired orbit. This paper focuses on solving the time-optimal abort guidance (TOAG) problem in real-time via the feature-based learning method. First, according to the optimal control theory, the features are identified to represent the optimal solutions of TOAG using a few parameters. After that, a sufficiently large dataset of time-optimal abort trajectories is generated offline by solving the TOAG problems with different initial conditions. Then the features are extracted for all generated cases. …

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