Engineering Commons^™

Doing Less With More: A First-Principles Exploration Of The Suitability Of Agentic Computing Over Alternative Architectural Choices, Ritvik Garimella, Biplav Srivastava, Amit Sheth

Publications

There is growing interest in automating business activities with Agentic Artificial Intelligence (AI) due to latter's seeming ease of use. However, little is known on when they are suitable for a task over other alternatives developed over the years - local computation, REstful State Transfer (REST), and Simple Object Access Protocol (SOAP) - considering development speed, performance, and operational cost. We explore this with a small mathematical task evaluating five methods for automated mathematical expression evaluation across a benchmark of 1,000 equations where semantics of operator precedence has to be preserved. We ran this setup across a native Function Calling …

One Size Does Not Fit All: Revisitingworld Models And Neurosymbolic Ai, Amit P. Sheth, Madhur Thareja, Anushka Pawar, Niyati Rawal

Publications

World models are being built twice, from opposite ends, without a shared theory of how the two halves should meet. One lineage grounds the world model in perception: a self-supervised, latent-predictive encoder – exemplified by Joint Embedding Predictive Architectures (JEPA) – that learns the structure of sensory experi-ence. A second, older lineage grounds the world model in cognition: an explicit, inspectable structure of entities, rules, and constraints, ranging from knowledge graphs to formal logic to physical law. Neither lineage alone has produced a world model that is simultane-ously adaptive and auditable. We argue this is not solved by picking a …

Global Time-Resolved Measurements Of Inlet/Isolator Unstart Induced By Mass Injection, Andrew N. Bustard, Benjamin L. Bemis, Aaron Marques, Matthew J. Zahr, Thomas J. Juliano

Publications

The inner surface pressure of an axisymmetric inlet/isolator model was measured using anodized-aluminum pressure-sensitive paint (PSP) viewing through cast acrylic. Temperaturesensitive paint was utilized to correct for the PSP’s temperature sensitivity. The model was tested under Mach 5.7 flow at 𝑹𝒆 = 7.1 ×106 /m under conventional noise conditions. Transverse jet injection with jet-to-inlet mass-flow ratios up to 0.8 was used to induce unstart in the inlet/isolator. Background-oriented schlieren visualization of the inlet shocks was collected simultaneously with the PSP to determine when the inlet unstarted. Computational fluid dynamics results were used to determine off-wall flow structures and quantify approach …

An Evaluation Of The “Police Response To Uncrewed Aircraft Systems Operations” Online Training Program, Anthony Galante, Leila Halawi

Publications

This study evaluates the impact of the “Police Response to Uncrewed Aircraft Systems Operations” online training program of officers from the Daytona Beach Police Department (DBPD). By measuring the effectiveness of the training through pretest and posttest assessments and considering variables such as educational background, length of service, and rank, this research underscores the training’s potential to enhance UAS response capabilities. Employing a self-selection sampling method, the study engaged 82 voluntary participants from the DBPD, revealing significant improvement across all groups in UAS knowledge and confidence levels. Despite limitations, these findings offer compelling evidence of the training’s efficacy and advocate …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …

Clear-Air Turbulence Climatology And Trends, Liam Rodgers, Mark Sinclair

Publications

Clear‑air turbulence (CAT) is a major aviation hazard that occurs near airline cruising altitudes in both cloud and cloud‑free environments. Its lack of a distinct visual signature makes detection and avoidance difficult. CAT is associated with wind shear near jet streams, gravity waves, and Kelvin–Helmholtz instability and may be further enhanced by climate change. This study examines the climatology, spatial distribution, seasonal variability, and trends of CAT over the contiguous United States.

Pilot Reports (PIREPs) from 2001–2025 between 100 and 400 hPa are analyzed alongside jet stream, shear, and stability diagnostics derived from NCEP–NCAR Reanalysis data. Proxies such as inverse …

Quantifying Evapotranspiration From The Wetlands In The Peripheral Area Between The Most Downstream Stream Gages And The Open Water Body Of The Great Salt Lake, Motasem S. Abualqumboz, David G. Tarboton

Publications

Study region: The eastern peripheral area between the most downstream stream gages and the open water body of the Great Salt Lake (GSL), located in northern Utah within the semiarid western United States (US). 

Study focus: As GSL levels decline, the eastern peripheral area is expanding, exposing former lakebed, much of which has transitioned into natural and managed wetlands. Evapotranspiration (ET) from these wetlands consumes water that would otherwise reach the open-water lake body, yet these losses remain poorly quantified and directly affect the GSL water balance. This study compares a water-balance-based ET estimate for the wetlands in the peripheral …

Biologically-Inspired Multiscale Neuromorphic Architecture, Christian O'Reilly, Ramtin Zand

Publications

This white paper proposes a biologically-inspired multiscale neuromorphic architecture that bridges key gaps between artificial neural networks (ANNs), spiking neural networks (SNNs), and biological neural networks (BNNs). While SNNs offer promising energy efficiency, their broader adoption remains limited by suboptimal performance and the need for novel learning paradigms. To address these challenges, the proposed framework integrates structural and functional principles observed in the brain, including hierarchical organization, sparse and modular connectivity, predictive coding, and diverse neuronal dynamics.

The architecture operates across micro-, meso-, and macro-scales, incorporating neuron-level diversity (e.g., excitatory/inhibitory and principal/support cells), canonical microcircuits (CMCs), and large-scale hierarchical organization. …

In-Situ Eval: A Modular Framework For Custom And Real-Time Rag Benchmarking, Ritvik Garimella, Kaushik Roy, Chathurangi Shyalika, Amit Sheth

Publications

Retrieval-Augmented Generation (RAG) has become the standard approach for integrating domain knowledge into Large Language Models (LLMs). However, fair comparison of RAG pipelines remains difficult: data preparation is often ad hoc, subsampling methods are opaque, parameters vary across implementations, and evaluation is fragmented. We present In-Situ Eval, a unified and reproducible framework that operationalizes the full RAG pipeline with configurable subsampling strategies and both RAG-specific and generic evaluation metrics. The platform supports two execution modes: an offline Dataset mode for evaluating precomputed outputs, and a live Retrieval mode for benchmarking RAG variants with state-of-the-art LLMs. Users can flexibly select datasets, …

Simulation Results Of Spaceborne Ssa Using A Comprehensive Passive Radar Model, Chinmay Gaikwad, Filipe Senra, Thomas Alan Lovell, Hao Peng, Berker Pekoz, Tianyu Yang

Publications

In this paper, a high-fidelity simulation framework is developed to assess the feasibility of tracking space debris using a large low-Earth orbit (LEO) satellite constellation equipped with onboard passive radar sensors. By exploiting illumination from a distributed network of ground-based transmitters, the constellation provides consistent line-of-sight access to debris objects at higher altitudes, enabling angles-only detection and tracking. This approach yields a scalable, automated, and cost-effective architecture for next-generation space surveillance and contributes to more resilient space traffic management. A complete angles-only passive-radar orbit-determination pipeline is introduced and demonstrated. Initial orbital states are generated using a rate-aware constrained admissible-region multiple-hypothesis …

Toward Neurosymbolic Reinforcement Learning Via Editable Specifications, Vedant Khandelwal, Hong Yung Yip, Amit Sheth

Publications

Reinforcement learning systems are commonly adapted to new settings by retraining or fine-tuning policies. This default is costly, difficult to audit, and poorly aligned with structured requirement changes such as revised safety rules, new operational constraints, or updated user preferences. We argue for an alternative abstraction: adaptation via edits to an external, human-readable specification that the agent consults at execution time. We propose conditioning decision-making on an editable knowledge graph encoding (i) rules capturing action applicability and high-level effects, (ii) hard constraints defining feasibility, and (iii) soft preferences shaping tradeoffs among feasible behaviors. Requirement changes become graph edits, not policy …

Sustainable Practices For Aircraft Decommissioning And Recycling In A Circular Aviation Economy, Eva Maleviti, Dimitra Papadaki

Publications

The aviation industry requires a series of actions that will transform its current status, aiming for sustainable operations. Aviation’s end-of-life stream is a pivotal lever for circularity, yet current dismantling and recycling practices leave significant value unrealized. Circular Economy could be considered as a transformational approach to the aviation industry and address its environmental and economic challenges, meeting sustainability principles. This study conducts a PRISMA-guided qualitative systematic review across academic and industry sources to synthesize regulations, technologies, and economics of aircraft decommissioning. It aims to quantify material recovery potential and environmental gains at the aircraft level and assess technology readiness …

Preparing Tomorrow’S Professionals: Industry-Informed Ai Integration, Brent A. Terwilliger Ph.D, John Faraca

Publications

As AI reshapes operations across aviation and aerospace, organizations are investing in ways to preserve data integrity, safeguard proprietary knowledge, and uphold critical professional competencies. This presentation shares emerging findings from a study that surveys and interviews industry professionals about their use of AI tools, their concerns about misuse, and the importance of secure, enterprise-controlled “walled garden” environments. The work explores how employers define appropriate, effective, and innovative AI adoption, particularly in roles requiring high-stakes decision-making, compliance, and technical acumen.

By analyzing organizational expectations around AI-related knowledge, skills, and abilities (KSAs), this research offers practical guidance for academic programs seeking …

Student Perspectives On Ai-Enabled Tools For Adaptive Learning, John Faraca

Publications

Artificial Intelligence (AI) is increasingly influencing the delivery of higher education, especially in aviation technical disciplines. From AI-assisted gimbals and video production tools to generative AI platforms, these technologies are helping learners to engage with course material, accomplish objectives, and connect academic concepts with professional applications. By offering pathways for personalization, streamlining resource access, and supporting interactive instruction, AI tools expand opportunities for effective learning. This work builds on a current collaborative research project with a faculty researcher to explore the student perspective in the active review and application of these tools to highlight their potential to improve usability, address …

Multiscale 3d Whole Joint Cellular And Molecular Mapping Reveals Disease-Specific Neurovascular Plasticity Underlying The Structure-Pain Relationship, Peng Chen, Jiaxin Chai, Abirami Soundararajan, R. Glenn Hepfer, Benjamin Kheyfets, Jiaxin Hu, Ishraq Alshanqiti, Swarnalakshmi Raman, Ikue Tosa, Jun Tae Huh, Matthew Yee, Brooke J. Damon, Shangping Wang, Yu Shin Kim, Man-Kyo Chung, Mildred C. Embree, Janice S. Lee, Tong Ye, Hai Yao

Publications

Understanding musculoskeletal joints from a 3D multiscale perspective, from molecular to anatomical levels, is essential for resolving the confounding relationships between structure and pain, elucidating mechanisms regulating joint health and diseases, and developing new treatment strategies. Here, a musculoskeletal joint immunostaining and clearing (MUSIC) method specifically developed to overcome key challenges of immunostaining and optical clearing of intact joints are introduced. Coupled with large-field light sheet microscopy, this approach achieves 3D high-resolution, microscale neurovascular mapping within the context of whole-joint anatomy without the need for image coregistration across various joints, including temporomandibular joints, knees, and spines, and multiple species, including …

Truck Drivers And Autonomous Trucks: A Topic Modeling Analysis Of Truck Driver Posts, Noah Britt, Amy M. Schuster, Shubham Agrawal, Chu-Hsiang Chang, Jenna A. Van Fossen, Elizabeth A. Mack, Sheila R. Cotten

Publications

Social media provides a rich, alternative data source to interviews or survey-based research to study hard-to-reach populations (e.g., truck drivers, because of their transient work structure and unique subculture). This study uses public social media posts from the largest trucking forum in the United States to examine truck drivers’ views on autonomous trucks (ATs), which are poised to transform the trucking industry. We expand on traditional qualitative strategies of analyzing social media data by combining newer methods, including BERT-based topic modeling, sentiment analysis, stance detection, emotion analysis, topic similarity, and location analysis through a social interaction network, to analyze a …

Crisis Observatory: Extracting Credible Signals During A Crisis In The Age Of Llms, Kuan-Chieh Lo, Pranav Maneriker, Sriram Sai Ganesh, Dominik Winecki, Kelly Garrett, Ayaz Hyder, Arnab Nandi, Valerie Shalin, Shannon A. Bowen Ph.D., Amit Sheth, Srinivasan Parthasarathy

Publications

Systems for crisis response have required several different models for the analysis of unstructured text, such as identifying needs, locations, topics, routing, and matching of needs with available responders. Large Language Models (LLMs) have replaced task-specific models across various language processing tasks. However, LLMs are known to be limited by their training data, collected before the crisis. In this demo, we explore the use of LLMs for crisis response scenarios with rapidly evolving information environments. We show how the augmentation of these models with external reliable sources of crisis-specific information can help build adaptive systems for response. The demonstration video …

Insights On Ai-Supported Uncrewed And Autonomous Systems Education, Brent A. Terwilliger Ph. D, John Faraca

Publications

Artificial Intelligence (AI) related technology is reshaping the educational experience in programs focused on uncrewed and autonomous systems, aviation, robotics, and aerospace, with growing implications for workforce readiness and cross-sector innovation. Early survey data, capturing student, educator, and employer perspectives, reveals that AI-supported tools are notably changing student engagement, communication, and skills development. Initial indications underscores the importance of AI proficiency and technological familiarity in hiring and workforce development, particularly in technical and operational roles. Key areas of focus include the use of AI to strengthen outreach and interactivity; enrich instruction through intelligent simulations; inform curricular improvements using data analytics; …

Terra Lunaris: Assessment Of A Lunar Habitat For Scientific Astronauts, Space Miners, Or Space Tourists, Dirk Schumann, Robert A. Goehlich

Publications

This conceptual paper explores ground- based habitable space modules for various applications. The Terra Lunaris concept serves as the baseline and is evaluated in comparison to existing and theoretical studies in this field. Terra Lunaris is a compact hybrid habitat that expands to offer nearly four times its transport volume by combining rigid modules with an inflatable shell. With most interior elements pre-installed and foldable, setup time and complexity are minimized. The design integrates technical zones, living quarters, and shared spaces, while also supporting psychological well-being under extreme conditions. The paper provides both qualitative and quantitative analyses of lunar habitation …

Data Compression In Additive Manufacturing: Recent Progress And Opportunities, Dongmin Ethan Kang, Wenmeng Tian

Publications

A crucial aspect of quality control for Additive Manufacturing (AM) processes is the acquisition of diverse data from the entire lifecycle of the product. AM data has grown significantly in terms of diversity and volumes, resulting in diverse data formats of increasing volumes, including time series, images, and point clouds. Large quantities of these data are essential for effective in-situ process monitoring and ex-situ non-destructive evaluation. However, this will result in large manufacturing and inspection datasets that are difficult to manage for users, which will delay the broader adoption of AM for mission critical applications. This motivates the urgent need …

Mitigating Melanin-Induced Bias In Pulse Oximetry: Optical, Algorithmic, Engineering, Hardware And Modeling Tools, Mckenzie Bradley, Sydnee Barrett, Ty Mckelvey, Jeremiah Carpenter, Delphine Dean

Publications

Melanin, the primary determinant of skin pigmentation, absorbs light at wavelengths that can have significant impact on the accuracy of pulse oximetry and other optical biosensing methods. This narrative review examines key factors influencing melanin-dependent pulse oximetry inaccuracies, including optical interference in transmission and reflectance modes. These inaccuracies further highlight the need for use of standardized skin tone metrics in device testing and design such as the Monk Skin Tone scale and Individual Typology Angle for performance stratification. There are several approaches in development that hope to address the errors in pulse oximetry measurements on melanin-rich skin. These include algorithmic …

Comparative Analysis Of Codes Of Ethical Conduct And Professionalism In Engineering And Project Management Associations, Valarie Denney, James W. Marion

Publications

This research details the similarities and differences in moral values and perspective from 15 engineering and project management association codes of conduct and professionalism. The methodology uses text mining of selected codes counting and summarizing keywords, evaluating document similarities through cosine similarity, and assessing the influence of various ethical schools of thought. Key findings reveal differences in the emphasis of core ethical values like fairness, honesty, and responsibility across different associations. This research is important for engineering and project management professionals to purposefully develop and evolve codes of ethics and professional development to enhance integrity, accountability, and ethical decision-making.

An Inference Approach For Assessing Place-Based Vulnerability To Heat Mortality, Junkang Xu, Chao Fan, Xing Xu, Haoying Han

Publications

A global increase in the frequency, severity, and scale of extreme heat raises concerns about human vulnerability to climate change and associated mortality. Heat vulnerability and mortality have largely been studied separately, lacking an understanding of their causation. Here, we create a non-parametric generalized inference approach that links socioeconomic, environmental, and infrastructure factors articulated in vulnerability theory and heat mortality between 2010 and 2020 for counties across the United States. We find that the lack of vegetation coverages drives mortality in the Southern U.S. and among Hispanic people. Limited air conditioning is a key factor in heat-related mortality among White …

Application Of Polymer Nanocomposites In The Design Of Prosthetic Sockets That Feature Auxetic Meta-Structures, Sumit Suryakant Kolte, Vinayak Vijayan, Lihua Lou

Publications

This research evaluates the response of prosthetic sockets constructed using polymer nanocomposites and incorporating auxetic meta-structures. The prosthetic sockets feature lightweight meta-structures between the inner and outer walls of the socket. Three different prosthetic designs featuring chiral, reentrant hexagon, and honeycomb meta-structures are evaluated in this study. The prosthetic sockets were designed in SolidWorks and compared using finite element analysis. The polymer nanocomposites used in this study include polypropylene and ultra-high molecular weight polyethylene containing uniformly distributed inclusions of either titanium dioxide, zinc oxide, or graphene nanoplatelets. Our results show a favorable pressure profile at the interface between the prosthetic …

From Assembly Lines To The Open Road: Predicting Rare Events In Autonomous Systems, Ruwan Wickramarachchi

Publications

In the age of embodied AI and smart automation, autonomous agents are increasingly deployed in high-stakes, real-world environments. Ensuring the robustness and resilience of these systems in the face of rare but critical failure events is essential for their safe and reliable operation. Accurate forecasting of such rare events is particularly crucial, as a single overlooked anomaly can lead to catastrophic consequences. In manufacturing, for instance, unplanned downtime due to rare failures costs industries over \$50 billion annually, with sectors like automotive losing more than \$2 million per hour—even with preventive maintenance systems in place.

However, the extreme rarity and …

Maximising Solar Pv Potential: A Comprehensive Review Of Factors Affecting Photovoltaic Installation And Generation In A Mild Temperate Oceanic Climate, Aiza Ahmad, Niamh Power, Evan Finnegan

Publications

The urgency of addressing the climate emergency and clean energy transitions have spurred worldwide initiatives to increase utilisation of renewable energy sources. The integration of rooftop photovoltaic panels at domestic level, often underestimated, is a priority across Europe to meet targets of net-zero emissions by 2050. PV systems represent a crucial technology for renewable energy generation and mitigating climate change. However, their performance and potential are influenced by various factors, including environmental conditions, building parameters and geographical factors. This paper demonstrates multiple factors that affect PV potential in mild temperate oceanic climates, using Ireland as a representative case study. Unlike …

Leveraging Artificial Intelligence In Education To Drive Cross-Sector Innovation, Brent Terwilliger, John Faraca

Publications

As artificial intelligence (AI) reshapes educational practices, particularly in technical fields such as uncrewed systems, robotics, and aviation/ aerospace, its integration raises promise and complexity. This exploratory study features an investigation of the impact AI tools adoption has on instruction, curriculum support, and workforce preparation, with a focus on online learning environments. Drawing from pilot survey data across aviation and aerospace education stakeholders and hands-on evaluation of AI video production platforms, findings reveal diverse applications, perceived benefits, and critical concerns, including ethical, pedagogical, and institutional challenges. Additionally, the analysis explored how AI-enabled education intersects with broader industry and government innovation …

Airfield Pavement Management Framework Using Advanced Modeling Techniques, Heena Dhasmana, Marwa Hassan, Elise Mansour

Publications

Airport authorities constantly collect pavement condition data and utilize life-cycle cost analysis to select construction and maintenance alternatives. The current Federal Aviation Administration (FAA) Advisory Circular 150/5380-7B recommends using Pavement Condition Index (PCI) to assess airfield pavement condition for planning of Maintenance and Rehabilitation (M&R) treatments. However, structural and functional performance might not be fairly represented by solely one indicator, the PCI. The latter might mask the root cause of the pavement deterioration and lead to inadequate M&R recommendations. Furthermore, the regression nature of the existing airfield pavement assessment models is not adequate for establishing pavement performance prediction as a …

Optimizing The Sustainability Of Asphalt Pavements Through Incorporating Crumb Rubber In High-Modulus Asphalt Concrete (Hmac) Mixtures In Louisiana, Heena Dhasmana, Marwa Hassan, Mohamed Abdelmageed

Publications

Asphalt mixtures are traditionally produced using the Superpave mix design method, which emphasizes volumetric properties; however, current research is shifting toward performance-based and sustainable approaches. Within this context, the French High Modulus Asphalt Concrete (HMAC) design focuses on achieving specific performance criteria for workability, stiffness, rutting resistance, and fatigue behavior, employing a hard binder with higher asphalt content and fewer air voids than Superpave mixes. In this study, HMAC mixtures were developed using crumb rubber and locally sourced Louisiana materials. Five HMAC mixes using PG 76-22 and PG 67-22 binders with 10% and 20% crumb rubber were prepared, along with …

Multiagent Copilot In Industrial Ai Applications, Chathurangi Shyalika, Renjith Prasad, Utkarshani Jaimini, Cory Henson, Fadi El Kalach, Amit Sheth

Publications

In the era of smart automation and digital transformation, achieving efficiency, precision, and adaptability is essential for industries to remain competitive. Sectors, including manufacturing, supply chain and logistics, healthcare, finance, and retail, face significant challenges in deploying Artificial Intelligence (AI) solutions tailored to their unique needs, particularly in critical, resource-constrained applications. According to Gartner’s 2024 Hype Cycle for Artificial Intelligence, composite AI, which integrates techniques like machine learning, knowledge graphs, and rule-based systems, is becoming foundational for industries, enhancing predictions, decisions, and scalability across complex environments.

The complexity of real-world systems requires Industrial AI solutions to be customizable to business …