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Universal Payload Gripper
Get PDFThe Universal Payload Gripper project tackles a unique and difficult challenge posed by NUWC. The challenge is to design an inflatable finger that has both load and sharpness sensing. The finger should also be scalable and be able to adapt to many payload tube sizes and environments. For background, the purpose of this challenge is to allow for the further utilization of older payload tubes to hold bulky, fragile, and sensitive payloads. The payload tube is to be filled with many inflatable cones called fingers that surround the payload to fix it in place. As the team does not know the exact nature of the payload, the finger has to have sensing capabilities to prevent damage to both the payload and itself. The team also aims to have a state-based control system to ensure efficient and methodical control over the prototype.
Since being posed with the challenge, the team has conceptualized possible solutions to the problem. These concepts include possible inflation, load sensing, and sharpness sensing techniques. Rapid concept generation, Pughs analysis, QFD Analysis, and CDR advice from peers were used to refine the team\u27s ideas. Once decided upon, the team worked to prove the concepts developed over the year. The team successfully demonstrated the inflation and deflation of a two-material finger using inexpensive and accessible parts. The team also successfully demonstrated load and sharpness sensing with an array of thin film pressure sensors. The full gripper finger design worked flawlessly, and met all of the team\u27s design requirements. The process and progress the team made this year is documented below
Self-Noise Reduction for Hydrophone Arrays - Geometric Approach
Get PDFThe scenario is a vertically oriented hydrophone array in the ocean. For the purposes of the research and development completed, the hydrophones are treated as spheres. The issue this project is meant to address is system vibration due to oscillatory drag known as vortex shedding. This vibration of the system creates noise, which is then picked up by the hydrophones, distorting the data. To obtain clean, precise data from the hydrophones it is essential to remove this data distortion. The approach taken with this year’s work was to improve the hydrodynamics of the system to reduce the opportunity for the vortex shedding to take place. A sphere and a cylinder are among the least hydrodynamically efficient geometries, so covers were designed to delay flow transition over both the support cable and of the hydrophones themselves. Each team member produced designs for these covers and the team compared each design, removing those that didn’t stand up to the others until one design for each cover remained. The designs were transferred from paper drawings to CAD (Computer Assisted Design) models and 3-D printed. Once the models were printed, testing was performed in a flow tank where oscillations were measured with point tracking software, verifying the success of the designs
Blind Mating of Non-Blind Mate Connectors
Get PDFTeam 16 was tasked by Raytheon with the challenge of designing a method that allows for the blind mating of non-blind mate connectors; whether between boards or between a board and a chassis. The general objectives for the project were to ensure precision, repeatability, durability and timeliness. Raytheon set forth these objectives to provide Team 16 with a valuable learning experience in the engineering design process. The project unfolded through various steps, reflecting a commitment to thorough research, innovative problem-solving, and effective project management. In the Fall 2023 Semester, after starting off with extensive literary research, the team examined existing prior art in patents, to gain insight that would influence the team’s design process. Once a detailed project plan and schedule were established, then, requirements set by Raytheon were adapted into design specifications. In the iterative design process, using the thirty concepts and Pugh analysis, the team further refined ideas to meet the specifications, and narrowed the selection to a single design. Competition was surveyed using the Quality Function Deployment, to develop a more comprehensive understanding of existing solutions and potential areas for improvement. The team was able to demonstrate a valid proof of concept that effectively facilitated the blind mating of non-blind mate connectors at the end of the initial semester. Following the presentation, Team 16 continued discussions about future innovations to be made in the Spring 2024 semester. Once the team had entered the Spring 2024 semester, work began to redesign, expand functionality, and scale the proof of concept. Utilizing skills from the Fall 2023 semester, the team was able to effectively progress the project manufacturing process. Testing investigated the refined design, proving it against the engineering requirements. Additionally, the team gained proficiency in project management, financial analysis methods, and future planning, in terms of various considerations and impacts
Integrating data imputation and augmentation with interpretable machine learning for efficient strength prediction of fly ash-based alkali-activated concretes
No full textFly ash-based alkali-activated concrete (AAC) is renowned for its superior mechanical performance and sustainability, presenting an attractive alternative to traditional Portland cement concrete. Despite these advantages, the broad compositional range of AACs presents challenges in precisely tailoring material properties. In this context, machine learning (ML) offers promising prospects to streamline and fast-track the development of advanced materials design strategies by predicting mechanical properties from compositional variations. Effective ML model development, however, hinges on the availability of a comprehensive, high-quality dataset. Previous studies often relied on literature-derived datasets, which typically include outliers, noise, and missing values, potentially leading to biased predictions. Moreover, limited dataset sizes could undermine the robustness of the models. Traditional ML methods applied to AACs also tend to lack interpretability. To address these issues, this paper utilizes several data imputation methods and Generative Adversarial Networks (GANs) for data augmentation, effectively doubling the dataset size. Following this, ML algorithms such as Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Neural Networks (NNs) are leveraged to predict compressive strength. The NN model, especially when enhanced by k-nearest neighbors (kNN) imputation (k = 5), demonstrated superior predictive accuracy compared to RF and XGBoost models. Further, SHAP (SHapley Additive exPlanations) analysis reveals key determinants of compressive strength, such as water content, SiO2, and curing conditions. Visualizations such as SHAP violin and river flow plots further elucidated feature contributions and property distributions. Overall, this study provides a robust framework for exploring composition-strength relationships in AACs, advancing the design of these environment-friendly materials
Bispectrum Analysis of Noninvasive EEG Signals Discriminates Complex and Natural Grasp Types
No full textThe bispectrum stands out as a revolutionary tool in frequency domain analysis, leaping the usual power spectrum by capturing crucial phase information between frequency components. In our innovative study, we have utilized the bispectrum to analyze and decode complex grasping movements, gathering EEG data from five human subjects. We put this data through its paces with three classifiers, focusing on both magnitude and phase-related features. The results highlight the bispectrum\u27s incredible ability to delve into neural activity and differentiate between various grasping motions with the Support Vector Machine (SVM) classifier emerging as a standout performer. In binary classification, it achieved a remarkable 97% accuracy in identifying power grasp, and in the more complex multiclass tasks, it maintained an impressive 94.93% accuracy. This finding not only underscores the bispectrum\u27s analytical strength but also showcases the SVM\u27s exceptional capability in classification, opening new doors in our understanding of movement and neural dynamics
Conductive Hydrogel Tapes for Tripolar EEG: A Promising Solution to Paste-Related Challenges
No full textElectroencephalography (EEG) remains pivotal in neuroscience for its non-invasive exploration of brain activity, yet traditional electrodes are plagued with artifacts and the application of conductive paste poses practical challenges. Tripolar concentric ring electrode (TCRE) sensors used for EEG (tEEG) attenuate artifacts automatically, improving the signal quality. Hydrogel tapes offer a promising alternative to conductive paste, providing mess-free application and reliable electrode–skin contact in locations without hair. Since the electrodes of the TCRE sensors are only 1.0 mm apart, the impedance of the skin-to-electrode impedance-matching medium is critical. This study evaluates four hydrogel tapes’ efficacies in EEG electrode application, comparing impedance and alpha wave characteristics. Healthy adult participants underwent tEEG recordings using different tapes. The results highlight varying impedances and successful alpha wave detection despite increased tape-induced impedance. MATLAB’s EEGLab facilitated signal processing. This study underscores hydrogel tapes’ potential as a convenient and effective alternative to traditional paste, enriching tEEG research methodologies. Two of the conductive hydrogel tapes had significantly higher alpha wave power than the other tapes, but were never significantly lower
Towards a combined human-natural system approach in the Northern Red Sea Region: Ecological challenges, sustainable development, and community engagement
No full textThe northern Red Sea coastal ecosystem is one of the most diverse coastal ecosystems in the world. Fortunately, it has shown extraordinary resilience against climate change and is predicted to survive global warming during the coming decades. However, with warming waters, increased sediment and pollutants, and other human impacts, the ecosystem and consequently thriving reef tourism which forms a pillar of the ongoing economic diversification policies of the northern Red Sea region are under threat. A variety of evidence indicates significant damage has already been done to terrestrial and ocean ecosystems on both sides of the northern Red Sea. Expenditures on ecosystem protection and research lag behind Egypt\u27s billions in USD revenue from tourism. Unfortunately, the economic drive to generate profit has resulted in sprawling touristic, industrial, and mixed development without careful planning or assessment of the fragility and sustainability of the natural ecosystem. As a result, the future of coastal urban growth is murky. Given its natural, social, and touristic value, the northern Red Sea system requires a special ecological security system with detailed analysis, inclusive development, and proactive governance across coastal cities and their adjacent inland secondary cities. This study identifies the geological research gaps, human-ecological interactions, inclusive urban development challenges, and related literature pertaining to the northern Red Sea. We propose immediate, targeted, multidisciplinary research trajectories and provide policy recommendations to ensure that the region\u27s existing and future developmental pursuits are undertaken in an environmentally sustainable and inclusive approach
Beyond the headlines: Media and Information Literacy (MIL) in times of conflict
Get PDFThe wars of the 21st century are not the first media wars, and many tropes and schema have long histories, particularly propaganda and the othering of a purported enemy. What is new today is that although mass media remains a central and hegemonic source of insight and perspective, citizen journalism, social media, spreadable media, and surveillant, data-driven media have grown in significance at an exponential level, adding a layer of complexity. In this article, we focus on disparity in media coverage and make the point that media and information literacy provide a valuable set of lenses from which to view a cluster of news and social media accounts taken from the government, mainstream media, alternative media, and the DIY mediasphere of the social media. It centers on two conflicts that receive little media exposure -the Nagorno-Karabash conflict between Armenia and Azerbaijan and the internal Anglo-Francophone conflict in Cameroon. It also offers examples of classroom activities that could be adapted and modified to most educational settings
