ENGINEERING

High School

Conceptual Design of Small-Scale Martian Reconnaissance Gliders |Accelerating Martian Exploration|
Joseph Chai, Francis Lewis High School

With climate change and energy crises, humanity has looked more towards planet terraformation and becoming an interplanetary species as potential solutions. Although, we have already deployed rovers and satellites and Mars, these innovations have their own limitations and the rate of exploration is much slower than it needs to be. My research on micro gliders proposes a novel and revolutionizing accelerator to Martian Exploration while also collecting valuable data that rovers and satellites have yet to collect: Small-Scale Reconnaissance Gliders.

Literature Review on the Effects of Alloy Variation on the Qualities of Steel
Killian Embler, American Heritage School Boca/Delray

A website containing details on my literature review.

Early Diagnosis of Pancreatic Cancer via Urinary Biomarkers with a New, Rapid, and Simple Lateral Flow Assay
Ana-Florina Galic, Greenwich High School

In my research, I developed a urine test for the early detection of pancreatic cancer. It is a fully functioning prototype that detects three urinary biomarkers that, when present jointly at specific concentrations, are linked to pancreatic cancer with over 90% accuracy. This is an inexpensive, efficient, and accessible test, which I envision to be used as part of a routine checkup for at-risk patients.

Creation of a Tracking Optic Device for the Generation of Near-Infrared Light to View Vein Structures in a Non-Invasive Format
Ward Genoway, American Heritage School Boca/Delray

Project components discussed involve Arduino platform, material sorting and preparation, testing, as well as realistic application and objective views.

Enhancing the Bionic Eye: A Real-Time Image Optimization Framework to Encode Color and Spatial Information into Retinal Prostheses
William Huang, Palos Verdes Peninsula High School

Retinal prostheses are currently considered the gold-standard in allowing patients with retinal degenerative diseases to see again. However, current patients are limited to low-resolution grayscale images constrained by the size of the microelectrode array. Therefore, my project proposes a computational solution that encodes color and spatial information to patients through salient object identification, color quantization, edge extraction, and bicubic interpolation.

Predicting Mutations for COVID-19 Vaccine Development
Rhea Iyer, American Heritage School Boca/Delray

SARS-CoV-2 is a crown-like, spiky, RNA virus that attaches itself to the ACE-2 protein to gain access to cells and create flu-like symptoms. COVID-19 has already taken over one million lives and almost thirty trillion dollars in lost output.Vaccine creation requires the weakened virus or bacteria that can’t replicate; since most pathogens mutate over time, understanding these mutations can better help researchers create vaccines that will help larger groups of people for larger amounts of time. The researchers created a method class with a DNA class array in order to illustrate an array sequence with the genomic sequences of a strain of COVID-19 from China in January of 2020 and a strain from the United States from April of 2020. A heat map created from these sequences was used to illustrate the genomic differences between the two sequences as mutations. The mutations were found to exist at the N gene as well as at the ORF10 gene. These genes can be further studied in relation to vaccines being developed in the present or can be isolated in current Coronavirus strains.

NextCare: An Intelligent System for the Early Screening and Remote Monitoring of Parkinson’s Disease using Machine Learning, Signal Processing, and Wearable Technology
Shreyas Kar, duPont Manual High School

NextCare is a novel system for early screening and remote monitoring of Parkinson’s Disease using Machine Learning and Signal Processing along with a 3D printed wearable device equipped with IMU sensors. The reports are viewable on the mobile app. This will be a valuable tool for Neurologists.

Utilizing a High Power Railgun to solve the Kessler Syndrome
Rohil Khare, Dublin High School

My project aims at solving the kessler syndrome utilizing a high powered railgun which would slow down the target space debris to a low enough velocity so that Earth’s gravity can pull it back into its atmosphere. The space debris would burn up while reentering which would effectively eliminate the debris.

Optimizing Automotive Seating Position to Reduce Injury Severity in Short-Statured Drivers
Sophie Krajmalnik, Plano West Senior High School

Short-statured drivers are 47% more likely to be severely injured and 17% more likely to die in a car crash. This discrepancy is due to insufficient vehicle safety guidelines as a result of continued use of physical crash test dummies with limited biofidelity. Nonlinear finite element analysis simulations were run in order to determine the optimal seating position for short-statured drivers in order to reduce injury severity, which is found to be when the pelvic angle is between 112 and 120 degrees and the distance from chest to middle of the steering wheel is as close as possible to baseline.

Engineering a Clinical Force Measuring Walker (CFM) for Patients with Restricted Upper Extremity Weight Bearing
Ansel LaPier, Central Valley High School

My project used a hybrid methodology including a quantitative research study, a qualitative research study, and finally an engineering project. The culmination of my work was the development of a clinical force measuring walker which will help to improve outcomes for patients recovering from open heart surgery, critical illness, and certain orthopedic conditions.

SafeBuild: Risk-Based Analysis of Overhead Electric Distribution Facilities
Jennifer Lew, Palos Verdes Peninsula High School

Every year, electric utilities ignite hundreds of fires in California. In 2017 and 2018, four utility-caused fires destroyed 27,000 buildings, killed 133 people, and caused $35 billion of damage. These fires occurred, in part, because utilities rely on outdated structural engineering software. To stop future fires, I created a risk-based design software called SafeBuild. My software uses finite element analysis to model utility poles, wood crossarms, and conductors. My software then uses predictive analytics to determine if these facilities will fail due to wind, falling objects, cyclic loading (vibration), or overheating. SafeBuild's predictive capabilities - which no commercial software possesses - will revolutionize the field of overhead power grid design.

The Prototyping of an Object Classification Device Utilizing Computer Vision to Aid the Visually Impaired
Dylan McClish, American Heritage School Boca Delray

The presentation illustrates a experiment that was conducted on a novel prototype constructed by the researcher in order to aid the visually impaired locate misplaced objects through the use of a camera equipped with computer vision.

SoundScape: Real-Time 3D Sound Localization and Classification with Sensory Substitution for the Deaf and Hard of Hearing
Irfan Nafi and Raffu Khondaker, Thomas Jefferson High School for Science and Technology

Low-Cost Novel Hearing Assistant

An Algorithm to Estimate Lithium-Ion Battery Lifetime
Andrew Park, The Gatton Academy of Mathematics and Science

Lithium-ion batteries are a crucial component in many applications. Battery lifetime must be estimated accurately to prevent rapid degradation, emission of harmful gases, and fatal explosions. Thus, a mathematical algorithm was created to estimate the battery lifetime, ensuring the safety and efficiency of these systems. Once a lithium-ion battery is not able to store at least 75% state-of-health compared to a new battery, the battery has reached its end-of-life, where further use may result in catastrophes. By gathering data on the properties of the battery cell, such as premature temperature anomalies that indicate the start of declining state-of-health and end-of-life, equations that generate curves to accurately estimate the battery lifetime were created. One equation estimates lifetime as a function of average discharge voltage while the other as a function of discharge capacity. It was found that based on 75% of the 1st cycle discharge capacity, the maximum projected lifetime of the current lithium-ion battery is ~2100-4130 cycles. Also, discharge capacity will limit the battery lifetime before average voltage, but the average voltage the battery can deliver drops off significantly faster after a temperature failure. Using experimental data, an algorithm was developed that accurately estimates lithium-ion battery lifetime with greater precision than before.

Hydrogen and Ammonia Energy Review
Samara Rashid, American Heritage School Boca/Delray

A literature review on the current status of hydrogen and ammonia energy.

Synthetic Aperture Radar Imaging with Inertial Sensor Fusion Using Custom FMCW Hardware and Extensible DSP
Pranav Sehgal and Tim Solberg, Beaverton School of Science and Engineering

Presentation highlights current issues with radar for robotic systems and presents our solution. Includes design process, considerations, and features. We elaborate on how our system can be used and how it fits into the market.

Replacing Lithium-ion Batteries with Graphene Based Supercapacitors
Maya Tovar, Sierra High School

This project demonstrates that a new paradigm in energy storage should be considered. Materials science engineers have historically focused on creating ever more energy dense materials to get around the large charge cycles of lithium-ion batteries, which serves only to increase manufacturers profit margins, while disregarding the economic, material scarcity, environmental, and safety concerns that should be paramount factors in design considerations. This engineering project examines replacing lithium-ion cells (LI) and electronic components with graphene supercapacitors and analogous electronic components. These were tested for their self discharge rates, charge cycles, and power output compared to new LI batteries. The results show that supercapacitors of comparable size and cost, output higher levels of power with only slightly lower energy density (~75% of LI when new and 88% after six months). This lower energy density is overshadowed by faster charge times (~⅓ that of LI at 15A), and the nearly limitless charge cycles that they possess (millions of cycles vs. thousands). What’s more, these charge times reflect rates achieved with a relatively low amperage and can be significantly decreased owing to the fact that supercapacitors have an extremely low equivalent series resistance which gives them high current tolerance. The results of this engineering project demonstrates that supercapacitors can bring a renewed vigor to the energy storage field. Standard household 120V systems can charge graphene based supercapacitors in minutes to full charge making supercapacitors a superior alternative to traditional LI battery packs.

Accessible Correlative Diagnostic Solution for Multi Organ Dysfunction Caused by SARS-CoV-2: The Future of Home-based, AI-enabled Telemedicine
Gatik Trivedi, Dougherty Valley High School

There are currently about 82.3 million COVID-19 cases worldwide with 24% of these cases being severe, and a 2% mortality rate. When diagnosed with COVID-19, people are required to stay in 14 days of self-isolation where they have no insight into their state-of-being. In these 14 days, if the condition become critical, people are immediately rushed to the ICU. To address this problem, I have developed a home-based telemedicine solution can enable patients to monitor their symptoms along with correlating them to provide meaningful clinical results for a better understanding of the impact of SARS-CoV-2 on overall patient health. My research entails the testing of this platform to see if it can yield results that can warn patients about their health condition by leveraging a product that deploys a contactless and easy-to-use telehealth solution.

Low-cost Portable Ventilator Design for Underdeveloped Regions
Rui Wang, High School Affiliated to Renmin University of China

This presentation introduce the background information of the design for ventilator.

Effects of Macro-/Micro-channels on Vascularization and Immune Response of Tissue Engineering Scaffolds: Literature Review
Nolan Wen, American Heritage School Boca/Delray

The focus of this literature review was to evaluate the effects of macro-/micro-channels on the vascularization, immune response, and cell recruitment of tissue engineering scaffolds.

Development of A Household 3D Cream Printer for Cake Decoration
Junjing Zeng, Branksome Hall

The presentation introduces my development of a household 3D cream printer for cake decoration. This includes the basic functionality, procedures, current results, future works, and potential market values.

Hybrid Model: A Highly Accurate Diagnosis of Parkinson’s Disease Severity by Combining MRI Brain Scans and Symptoms Assessment Scores
Sabrina Zhu, The Harker School

I developed a hybrid machine learning model, which combines two forms of data, symptom assessment scores and MRI brain scans, to diagnose Parkinson's disease patients. Along with the hybrid, I also implemented two models based only on symptoms or based only on MRI images, and all three models classify patients into five categories based on severity of their conditions. I found that the hybrid model reached an overall accuracy of 94%, with consistency across all five stages, including early ones. This is the first research that combines symptoms and MRI scans on a large scale, and there is much promise for more research in this field.

Undergraduate

Novel Wrapping Device to Coat Sutures with Polymeric Electrospun Nanofibers
Katelyn Franck and Olivia Wozniak, Clemson University

Our presentation provides an update of our research in nanofibers wrapped over sutures, our progress in making a device with which to do so, and our plans moving forward. We hope that judges will enjoy learning about our process and the benefits of this technique.

A Novel Approach to Increase Operator Awareness in Physical Human-Robot Interaction
Mustafa Mohammed, University of Illinois at Chicago

The objective of this research is to develop a real-time, depth-sensing surveillance method to be used in factories that require human operators to complete tasks alongside collaborative robots. Traditionally, collision detection and analysis have been achieved with extra sensors that are attached to the robot to detect torque or current. In this study, a novel method using 3D object detection and raw 3D point cloud data is proposed to ensure safety by deriving the change in distance between humans and robots from depth maps. A depth camera is used at a birds-eye view in a factory for surveillance over multiple workers and robots. The distance will be used to determine the injury severity of a collision, and this data is used to create warnings for workers. By not having to deal with any potential delay associated with extra sensor-based data, both the likelihood and severity of collaborative robot-induced injuries are expected to decrease. This work has led to the development of an object tracker that predicts potential collisions between humans and robots with minimum safe distance, giving accurate warnings to workers. The methods that have been developed can lead to more promising steps in the creation of a more robust collaborative robot injury risk design.

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