Digital Commons Network^™

Mems 4110: Improving Restaurant Efficiency: Automatic Egg Peeler, Shanice Isimbi Mutabazi, Kyle Bryant Okui, Max Ari Siefert, Lani Fancesca Espinel

Mechanical Engineering Design Project Class

Neon Greens is a salad restaurant in St. Louis, MO that focuses on serving fresh, locally sourced ingredients. One of their signature menu items includes soft and hard-boiled eggs, which are used in large quantities every day. Currently, these eggs are peeled by hand, which can be slow, inconsistent, and difficult to keep up with during busy hours. Because of this, Neon Greens needs a faster and more reliable way to peel eggs without increasing labor. Our project aims to design a device that can peel eggs automatically, reduce prep time, and stay safe and easy to clean in a …

The Effect Of Fascicular Elastin On The Mechanical And Functional Properties Of Healthy, Damaged, And Healing Tendon, Shawn Pavey

McKelvey School of Engineering Graduate Student Theses & Dissertations

Mechanical properties of tendon are highly influenced by structural protein composition and microscopic sub-structures. Within the largest subunit of tendon, the fascicle, the role of the elastin protein remains understudied despite impressive extensibility and fatigue resistance of its resulting elastic fibers. While previous work catalogued contributions of fascicular elastin across tendon type and species, the anticipated effects of elastin in fatigue and healing have not yet been explored. While previous knockout mouse models showed that disruption of elastic fibers led to altered mechanical properties (e.g., increased linear modulus), these models depended on heterozygous elastin deficiency or indirect knockout of proteins …

Biomass Materials And Their Application In 4d Printing, Zhongda Yang, Jian Li, Yanling Guo, Yangwei Wang, Wen Zhao, Wei Zhao, Yanju Liu, Laichang Zhang

Research outputs 2022 to 2026

Four-dimensional (4D) printing technology is a revolutionary development that produces structures that can adapt in response to external stimuli. However, the responsiveness and printability of smart materials with shape memory properties, which are necessary for 4D printing, remain limited. Biomass materials derived from nature have offered an effective solution due to their various excellent and unique properties. Biomass materials have been abundant in resources and low in carbon content, contributing to the then-current global green energy-saving goals, including carbon peaking and carbon neutrality. This review focused on different sources of biomass materials used in 4D printing, including plant-based, animal-based, and …

Defective Mil-88b(Fe) Metal-Organic Frameworks: Peculiar Photocatalysts For Enhanced Degradation Of Organic Pollutants, Samira Sadeghi, Ahmad Najafidoust, Seyedeh Zahra Haeri, Masoumeh Zargar

Research outputs 2022 to 2026

Environmental pollution, particularly water contamination from organic compounds like synthetic dyes, poses a major global challenge. In this study, defective MIL-88B(Fe) MOFs under varying solvothermal conditions (70–150 °C) for 12 and 24 h were synthesized to enhance methylene blue (MB) and methyl orange (MO) dye degradation. The MOF synthesized at 100 °C for 24 h showed the highest efficiency, achieving 97 % and 40 % degradation of MB and MO, respectively, in 60 min due to increased porosity, surface area, and optimized crystal growth along the [100] direction. A 24-h synthesis produced well-formed particles with the highest surface area and …

Mems 4110: Egg Peeler Group L1, Brian Hau, Alex Kenn Lee, Aisha Bah, Shanaelle Nabatmama

Mechanical Engineering Design Project Class

Neon Greens is a quick-serve salad concept located in St. Louis, MO. Part hydroponic farm and
part restaurant, they focus on growing a majority of their greens in-house, and emphasize
transparency in food systems.
In recent months, they added a ‘Protein Caesar’ salad to the menu. That salad features two
‘jammy’ boiled eggs which are cut in half. Staff at Neon Greens steam eggs precisely in their
Combi oven and shock them to stop the cooking process. They then peel those eggs by hand.
On some days, they must process >100 eggs, which can take up to 1.5 hours of …

Mems 4110: Precise Water Distribution System, Morelia R. Reyes-Perez, Jp Torack, Jakob Ayala

Mechanical Engineering Design Project Class

This project focuses on designing and prototyping an automatic precise watering system to support plant research conducted in the Washington University greenhouse. The customer, graduate student Christina Youngpeter, needs a reliable method for delivering accurately measured water volumes to individual plants as part of a study on hydration effects. Manual watering can be time consuming, our system will provide a programmable, repeatable, and low maintenance solution.

Mems 4110: N1 Precise Water Distribution System, Lillian Salter, Ye Huang, Elaine Wang, Joy Luo

Mechanical Engineering Design Project Class

The aim of the project is to construct a precise water distribution system for anthropology graduate student Christina Youngpeter, who is studying the impact of hydration levels on the growth of quinoa plants. As her experiment grows in scale, she increasingly needs a system that can measure and distribute water for her, saving hours otherwise spent meticulously measuring water for 36 plants and counting. The system must measure water accurately and distribute it to the plants cleanly and efficiently. It should also be scalable and autonomous, requiring minimal human intervention.

Mems 4110: The Egg Peeler, Susanna Yeh, Jessica Arnold, Peter Nesin, Finn Mcnamee

Mechanical Engineering Design Project Class

The purpose of this project is to assist the customer Neon Greens in accelerating their food preparation time by designing an egg peeler device. To have a better understanding of the customer needs and expectations, the design team participated in an interview with Neon Greens to address their vision and desires for this device. For the semester-long project, the team underwent various prototype stages, including the proof of concept, the initial prototype, and the final prototype. Our final design consists of a hopper that holds a batch of eggs on top and drops two eggs at a time, one on …

Mems 4110: Air Cannon Launcher Demo, Jackson Strauss, Avery Cohen, Wilson Gao, Jack Galloway

Mechanical Engineering Design Project Class

For our senior design class (MEMS 4110) at Washington University in St. Louis, we were tasked with creating a demonstration for the St. Louis Science Center that demonstrated an engineering principle or concept. The Science Center functions as a science-oriented museum and saw more than 600,000 visitors in 2024. For our demonstration, we wanted to showcase the principles of kinematic motion. Kinematic motion is study of the motion of objects without considering applied forces. Additionally, when the acceleration of an object is either zero or held constant, the trajectory path that the object follows can be described by a few …

Mems 4110: Arduino-Controlled Precise Water Distribution System, Jack M. Williams, Joe Sieracki, Nina Woodward

Mechanical Engineering Design Project Class

Christina Youngepeter is a Graduate Student of Archaeology at Washington University in St. Louis. She is studying an ancient plant that fell out of use after 1400 CE, whose ideal watering conditions are lost to time. To better characterize the plant, Christina is running an experiment to determine the ideal watering conditions for plant development. This involves watering sets of the plant with different volumes of water twice a day. The different volumes of water received by the groups of plants are 933 mL, 833 mL, 733 mL, 617 mL, 517 mL, and 417 mL. The acceptable percent error in …

Mems 4110: Egg Project, Rebecca Leighann Boone, Courtney Davis, Bebel Trani

Mechanical Engineering Design Project Class

Peeling hard-boiled eggs by hand is a time-consuming and tedious task that often results in dimples and cracks in the final product. Many chefs and home cooks have tried techniques, from boiling the eggs in baking soda to slipping off egg shells using a spoon, to perfect the peeling process. However, these attempts often fall short by either altering the taste of the egg or extending the amount of time and labor. In the restaurant business, having employees peel eggs for long periods of time is costly. The local St. Louis salad restaurant, Neon Greens, is selling a new protein-dense …

Mems 4110: Soft Boiled Egg Peeler, Nina Fischer, Ruth Mellin, Jack Salamon, Malaya Hill

Mechanical Engineering Design Project Class

This report outlines the design and evaluation of a hard-boiled egg–peeling device developed for the Saint Louis restaurant Neon Greens. The restaurant prepares an average of 150 soft-boiled eggs daily for dishes such as the Protein Salad. They requested a device able to autonomously peel 150 eggs per hour with minimal employee involvement.

Mems 4110: Air Hockey Table Physics Education Exhibit, Olaoluwa J. Adeniji, Salomon Dessalines, Gyvnn Mendenhall

Mechanical Engineering Design Project Class

This project centers on creating an educational air-hockey exhibit designed for use in a science museum. The goal of the device is to transform a familiar game into a hands-on demonstration of basic physics and engineering concepts such as motion, momentum, energy transfer, and impact forces. Through discussions with our customer, Professor Potter, we established that the exhibit must balance two priorities: it must be fun and intuitive for visitors of all ages, and it must provide meaningful real-time feedback that helps users understand the science behind the experience.

Building Services Engineering September/October 2025

Building Services Engineering

No abstract provided.

Real-Time Task Scheduling Strategy For 3d Printing Cloud Platforms In Health Scenes, Jianjia He, Jian Wu, Jingran Ni, Yuning Zhang, Keng Siau

Research Collection School Of Computing and Information Systems

In health scenes, 3D Printing Cloud Platform (3DPCP) needs to cope with unpredictable fluctuations in tasks and resources, but traditional scheduling methods have problems such as incomplete consideration of factors, poor optimization, and weak dynamic adaptability, which make it difficult to meet real-time scheduling requirements. To this end, the real-time task scheduling problem of 3DPCP for health scenes is defined, a real-time task scheduling model is established, the design time of user personalized services is considered, a rescheduling scheme is designed in combination with task variations and device variations, and a scheduling strategy that incorporates dynamic mechanisms and improved multi-objective …

Recognizing The Unexpected: Deep Learning Across Complex Environments, Ge Song

Theses and Dissertations

Ensuring the security, trustworthiness, and operational integrity of modern autonomous and cyber-physical systems presents a critical challenge. While widely utilized in various engineering applications, such as intelligent transportation and industrial manufacturing, these systems require robust monitoring frameworks to identify unexpected anomalies in real-time, thereby maintaining operational safety and efficiency. This dissertation develops advanced deep learning methodologies for anomaly detection and health monitoring, with a particular emphasis on semisupervised reconstruction-based approaches that identify anomalies in complex environments using models trained only with normal operational patterns.

Building on this theme, the first study focuses on analyzing pedestrian behavior and detecting anomalies at …

Multi-Layer Decision Making For Long-Term Autonomous Mission Based On Dual Process Theory, Shruti Jadhav

Theses and Dissertations

Unmanned aerial vehicles (UAVs) are increasingly used in precision agriculture, where extended autonomous operation is required for monitoring, intervention, and field management. However, achieving long-term autonomy remains challenging due to battery constraints, environmental uncertainty, and the need to balance exploration with event-driven tasks. To address these challenges, a multi-layer decision-making framework inspired by Dual Process Theory (DPT) is developed. The framework combines reactive return-tobase strategies, exploratory navigation, and directional bias from prior missions, with a conflict-monitoring mechanism that adapts system behavior based on real-time conditions. The approach is implemented in a simulated agricultural grid environment, demonstrating improved adaptability and coverage …

Jet Impingement And Vortex/Swirl Cooling Of Different Inlet And Outlet Geometrical Configurations For Turbine Blade Leading Edge Cooling, Irfan Ahmad Sheikh

Dissertations

Gas turbine blades operate in extreme environments, exposed directly to high-temperature combustion gases that cause severe thermal stresses, weaken material integrity, and may lead to structural failure. Proper cooling is crucial to lower blade temperatures, reduce thermal stresses, prevent failure, and improve overall engine efficiency. This work presents a detailed numerical study of various cooling configurations by applying two advanced leading-edge cooling methods, jet impingement and swirl cooling, across different inlet mass flow rates and jet Reynolds numbers (Rej) ranging from 1,000 to 20,000 to evaluate their cooling performance.

Several advanced leading-edge cooling configurations are proposed and compared with the …

Erosion Of Bermuda Grass Covered Soils, Oru-Ntui Johnwatters Nkiri

Theses and Dissertations

Earthen embankments are the most common type of embankment due to the relatively low cost, simplicity, and material availability. However, they are also the most prone to erosion related failure, typically due to overtopping and piping. Research has been conducted to identify ways to control soil erosion and protect earthen embankments with different approaches such as addition of chemicals and biopolymer to the soil, installation of protective layering (geotextiles, concrete), increased soil compaction, and use of vegetation. This thesis considers the use of Bermuda Grass to increase resistance to erosion and protect embankments from failure during overtopping. Grass coverage and …

Multiscale Geometric Analysis In Endovascular Therapies: Ex Vivo, In Silico Approaches, Dima Hussein Ali Bani Hani

Theses and Dissertations

In this work, we address a persistent global challenge of vascular disease, specifically peripheral artery disease (PAD), and arteriovenous fistula (AVF) complications in patients with end-stage kidney disease (ESKD). The important role of vascular geometry in disease intervention plans and the development of endovascular therapeutic strategies (e.g., Drug-coated balloon (DCBs)) is critical in addressing these challenges.

This study evaluates the feasibility of co-delivery of paclitaxel (PTX) and valsartan (VAL) using urea-based coatings in DCB, analyzes the coating morphology and microstructural changes to improve therapeutic results. A computational finite element model was developed to complement experimental work, simulate tissue-coating interactions, compute …

Gut Microbiome Dynamics In Heart Failure And The Therapeutic Potential Of Nmeg-Cgrp, Kamryn Michael Gleason

Theses and Dissertations

Heart failure (HF) is increasingly recognized as a multisystem disease often linked to gut dysbiosis; however, its specific effects on gut microbial composition remain poorly understood. This study examined long-term changes in the gut microbiome in a murine HF model induced by transverse aortic constriction (TAC) and evaluated the effects of NMEG-CGRP. TAC mimics pressure overload-induced cardiac dysfunction, replicating key features of HF. CGRP, a neuropeptide with vasodilatory and cardioprotective effects, shows potential as a therapy for HF but is limited by rapid degradation. A stabilized analog, NMEG-CGRP, was used to assess its impact on cardiac and gastrointestinal health. Mice …

Deep Learning-Based Change Detection In High-Resolution Remote Sensing Imagery, Hazem Badawy

Theses and Dissertations

Remote sensing has become a key tool for monitoring Earth’s surface over time, offering valuable insights into both natural and human-driven changes. Among its many applications, change detection focuses on analyzing multi-temporal imagery to reveal how specific areas evolve across different time periods. It plays a pivotal role in Earth observation applications, including urban development monitoring, environmental degradation assessment, and disaster response. However, existing approaches often struggle with limited contextual awareness, high sensitivity to noise, and imprecise localization of change boundaries, especially with high-resolution imagery. This thesis investigates the complex problem of change detection in remote sensing imagery by proposing …

Multi-Period Risk-Aware Procurement Optimization Under Covid-19 Disruption, Jonathan Chase, Hoong Chuin Lau, Jinfeng Yang, Lu Liu

Research Collection School Of Computing and Information Systems

Supply chain resilience has been a topic of active research in the operations research and AI communities for several years, but the COVID-19 pandemic threw the frailties of global supply chains into sharp relief. Disruptions and delays caused by fresh outbreaks leading to lockdowns, put severe strain on supply chains in many industries. In this work we develop lockdown-resilient procurement capabilities for a global technology company. First, through analysis of lockdown data from China we develop a logarithmic regression-based lockdown prediction method to complement a supplier risk metric for conventional risks. Second, we develop a multi-period stochastic optimization model that …

Machine Learning Classification Of Eeg Responses To Pain-Related Vs Non-Pain-Related Stimulus In Preterm Infants, Lojain Hamwi, Hang Du, Sara Jasim, Xiaogang Wang, Vibhuti Shah, Carol Cheng, Lorenzo Fabrizi, Maria Fitzgerald, Judith Meek, Nicole Racine, Ian Stedman, Rebecca Pillai Riddell

Michigan Tech Publications

INTRODUCTION: Unmanaged pain in preterm infants can lead to long-term developmental consequences. Current pain assessment methods lack specificity, resulting in possible pain mismanagement in Neonatal Intensive Care Units (NICUs). This study explores the application of machine learning (ML) to differentiate between pain-related and non-pain-related cortical activity in preterm infants. OBJECTIVE: To evaluate the performance of ML models in distinguishing cortical EEG activity during a painful procedure in preterm infants across different postmenstrual ages (PMAs). METHODS: This observational study was conducted from June 2015 to May 2024 at Mount Sinai Hospital in Toronto, Canada, and University College London Hospital, United Kingdom. …

Production Of Durable Mortar For Aggressive Environments Using Waste Glass Aggregates And Metakaolin-Based Blended Cement, T. F. Awolusi, A. O. Sojobi, D. O. Oguntayo

Research outputs 2022 to 2026

The depletion of river sand and its environmental consequences, combined with the vulnerability of concrete structures to harsh environments, pose a significant global concern. To mitigate maintenance costs, it’s essential to prioritize sustainable infrastructure production that balances durability and environmental sustainability, particularly in aggressive environments. This study explores the possibility of production of durable mortar for aggressive environments using waste glass aggregates and metakaolin-based blended cement. The waste glass cullets were used as sand replacement at 0%, 50%, and 100% and blended with metakaolin and gypsum to produce binary and ternary mortars. The blend of metakaolin and gypsum was explored …

Towards Sustainable Mining: Ghg Considerate Open Pit Long-Term Planning Using Adaptive Large Neighborhood Search Algorithm, Bahar Amirmoeini, Martin Grenon, Ali Moradi Afrapoli

Journal of Sustainable Mining

Mine planning involves the systematic design and coordination of mineral extraction from the earth’s crust, integrating exploration, production, and various engineering considerations. With increasing emphasis on environmental responsibility, the mining industry is under pressure to incorporate environmental considerations into mine planning. This paper addresses the precedence-constrained production scheduling problem (PCPSP) within the context of green long-term mining planning, aiming to optimize extraction processes while restricting carbon emission. Given the NP-hard nature of the PCPSP, this study introduces an adaptive large neighborhood search (ALNS) algorithm tailored specifically for long-term mine planning. A range of computational experiments have been carried out, including …

Economic Viability And Environmental Sustainability: A Cost-Benefit Analysis Of Green Technologies In Mineral Extraction, Tshinkobo Bukasa Orphea, Agyingi Babaca Agyingib, Xiangrui Meng

Journal of Sustainable Mining

This research offers a novel approach to comparing green technologies’ economic profitability and environmental sustainability of their mineral extraction based upon econometric and life cycle assessment methodologies. Quantitative results show attractive results with an NPV of $2,014,001 and an IRR of 17%. In the third year, the project nets at $300,000, or 63%, at a 7% discount rate. However, soil protection remains challenging, but pollution coefficients are improved, as evidenced by environmental impact assessments (EIAs). The findings in the study further underscore how regulatory frameworks and market drivers dictate the use of green technology. The economic, environmental and regulatory costs …

Reengineering Resilience: Bio-Resilience Bonds For Financing Microbial Infrastructure And Climate Equity, Reece Buckley

COP30

This policy proposal introduces Bio-Resilience Bonds (BRBs), a performance-based financial instrument designed to monetise microbial ecosystem services as measurable climate infrastructure. Microbial ecosystems are crucial for climate resilience, yet they are often overlooked in mainstream adaptation f inance frameworks. Their ability to regulate carbon and nitrogen cycles, reduce methane emissions and enhance soil and water stability (Delgado-Baquerizo et al., 2016) makes them essential assets for climate mitigation and adaptation. With global adaptation needs exceeding £2.7 trillion (UNEP, 2024), this oversight indicates a systemic failure to recognise biology as a form of infrastructure. BRBs transform microbial outputs into localised key performance …

Drawing On Uncertainty Methodologies Of Neutrosophic Hypersoft Sets In Cognitive Computing-Driven Healthcare Systems, Mona Mohamed, Nurhan Alaa

Neutrosophic Systems with Applications

A new paradigm called cognitive computing simulates human reasoning and decision-making through integrating advanced techniques such as artificial intelligence (AI) and natural language processing (NLP). Cognitive computing systems, in contrast to traditional systems, can handle both structured and unstructured data, adjust to new information, and offer context-sensitive insights. This study examines how cognitive computing improves decision-making, personalization, and human-machine collaboration in various fields. Cognitive computing in the healthcare sector processes clinical notes, imaging data, and electronic health records to help physicians with diagnosis, treatment planning, and patient engagement. This study examines key applications, including their role in diagnostic support, where …

Neutrosophic Set Model For Controlling Electronic Waste Requirements Management Policies To Minimize Ecological Impact And Improving Resilience And Sustainability, Mohamed Abouhawwash, Nitin Mittal, Sudeep Tanwar

Neutrosophic Systems with Applications

The growing issue of electronic waste (e-waste) necessitates management approaches that promote sustainability and resilience while reducing environmental effects, particularly considering global disruptions and pressure on manufacturers to implement extended producer responsibility laws. There is a research gap in our knowledge of the link between sustainability and resilience since most of the literature currently available on e-waste management focuses on either operational efficiency or sustainability. This study proposes multi-criteria decision making (MCDM) methodology for controlling electronic waste requirements management policies to minimize ecological impact and improving resilience and sustainability. We use the EDAS methodology to rank the alternatives. The criteria …