Engineering Commons^™

Effect Of Protective Cladding On The Fire Performance Of Vertically Loaded Cross-Laminated Timber (Clt) Wall Panels, Muhammad Yasir, Andrew Macilwraith, Conan O'Ceallaigh, Kieran Ruane

Publications

Cross-laminated timber (CLT) is a sustainable engineered wood product which is utilised in modern multi-storey timber buildings. The fire behaviour of timber structures is often a concern due to their combustible nature. In this paper, experimental fire testing of CLT panels made of Irish spruce was performed. This series of tests consisted of four vertically loaded CLT wall panels which were tested under Standard fire curves in the Structural Laboratory of Munster Technological University, Cork (MTU). To improve the fire performance of CLT panels, different types of protective claddings were used. The effectiveness of each system of protection has been …

Sustainable Atos - Flying To Net Zero, Eva Maleviti, Bettina Mrusek

Publications

Pathways to Net Zero- Targets

Improve fuel-efficiency by an average of 2% per year - 2020 to 2030

Reduction in total carbon dioxide emissions to net-zero by 2050.

After 2026 carbon allowances will be zero for EU.

Short-Haul Airline Services In Europe And North America - A Cross-Business Model And Cross-Continental Analysis, Chunyan Yu, Richard Klophaus

Publications

We examine short-haul services offered by the respective 10 largest European and North American carriers in terms of fleet composition, network characteristics, airfare and product attributes. Our cross-business model and cross-continental analysis builds on the index approach developed by Klophaus et al. (2012) to derive a typology of the hybridization among the largest carriers in Europe and North America in short-haul markets. Our results indicate that none of the largest European and North American carriers follows the pure LCC business model in short-haul markets, and all the LCCs in Europe and North America have adopted certain degree of hybrid strategy …

Adaptive Modified Rise-Based Quadrotor Trajectory Tracking With Actuator Uncertainty Compensation, Emmanuel Ogbanje Ijoga, William Mackunis, Krishna Bhavithavya Kidambi, Madhur Tiwari

Publications

This paper presents an adaptive robust nonlinear control method, which achieves reliable trajectory tracking control for a quadrotor unmanned aerial vehicle in the presence of gyroscopic effects, rotor dynamics, and external disturbances. Through novel mathematical manipulation in the error system development, the quadrotor dynamics are expressed in a control-oriented form, which explicitly incorporates the uncertainty in the gyroscopic term and control actuation term. An adaptive robust nonlinear control law is then designed to stabilize both the position and attitude loops of the quadrotor system. A rigorous Lyapunov-based analysis is utilized to prove asymptotic trajectory tracking, where the region of convergence …

A New Generation Of Dense-Graded Asphalt Mixtures With Superior Performance Against Stripping And Moisture Damage, Mostafa Elseifi, Zahid Hossain, Md. T.A. Sarkar, Hossam Abohamer, Mohammad Oyan

Publications

The presence of moisture beneath the pavement surface is a matter of great concerns as it is responsible for significant distresses such as asphalt concrete (AC) stripping, fatigue cracking, rutting, and poor durability of asphalt mixes. The objective of this study was to evaluate and recommend an asphalt mixture design that would provide superior performance against AC stripping and cracking. To achieve this objective, a laboratory test factorial was developed to evaluate the use of nanomaterials, emerging anti-stripping agents, warm-mix asphalt technologies, and adhesion promotors. In the experimental program, the modified Lottman test (AASHTO T 283) and the Indirect Tensile …

Knowledge Graph Empowered Machine Learning Pipelines For Improved Efficiency, Reusability, And Explainability, Revathy Venkataramanan, Aalap Tripathy, Martin Foltin, Hong Yung Yip, Annmary Justine, Amit Sheth

Publications

Artificial intelligence (AI) pipelines are complex, heavily parameterized, and expensive to execute in terms of time and computational resources. Consequently, it is onerous to run experiments with all possible parameter combinations to achieve an optimal solution. However, these AI experiments can be optimized by recommending relevant parameters to commence the experiments, reducing search space significantly, which can be fine tuned further. The relevant parameters can be identified by observing the metadata of pipelines executed in the past, and the relevant pipeline with relevant parameters can be recommended to the user. Currently, there are various metadata frameworks that automatically record the …

Introduction To Bioaerosols Assessment And Control, 2nd Edition, Cheri Marcham, John (Jack) Springston

Publications

• Risk Assessment
• Assessment for the Presence of Bioaerosols
• Sampling
• Purpose/ Necessity
• Interpretation Controls
  • Ventilation
  • Other Controls

Construction And Cost Analysis Of Bladebridges Made From Decommissioned Frp Wind Turbine Blades, Kieran Ruane, Mario Soutsos, Au Huynh, Zoe Zhang, Angela Nagle, Kenny Mcdonald, T Russell Gentry, Paul Leahy, Lawrence C. Banks

Publications

This paper describes repurposing projects using decommissioned wind turbine blades in bridges conducted under a multinational research project entitled “Re-Wind”. Repurposing is defined by the Re-Wind Network as the re-engineering, redesigning, and remanufacturing of a wind blade that has reached the end of its life on a turbine and taken out of service and then reused as a load-bearing structural element in a new structure (e.g., bridge, transmission pole, sound barrier, seawall, shelter). The issue of end-of-life of wind turbine blades is becoming a significant sustainability concern for wind turbine manufacturers, many of whom have committed to the 2030 or …

Air Traffic Management Principles: A Case Study On How To Create A Sustainable System, Eva Maleviti

Publications

BEYOND ENVIRONMENTAL SUSTAINABILITY

• Emissions, SAF, CORSIA, Design
• Economic growth and development
• Sustainability should go beyond environment
• Non-technology approaches for sustainability and Net-Zero targets
• What about social sustainability and people?

In the total share of aviation emissions (1GT CO2) 3% is 3Mt CO2. Small share but very significant contribution.

Demo Alleviate: Demonstrating Artificial Intelligence Enabled Virtual Assistance For Telehealth: The Mental Health Case, Kaushik Roy, Vedant Khandelwal, Raxit Goswami, Nathan Dolbir, Jinendra Malekar, Amit Sheth

Publications

After the pandemic, artificial intelligence (AI) powered support for mental health care has become increasingly important. The breadth and complexity of significant challenges required to provide adequate care involve: (a) Personalized patient understanding, (b) Safety-constrained and medically validated chatbot patient interactions, and (c) Support for continued feedback-based refinements in design using chatbot-patient interactions. We propose Alleviate, a chatbot designed to assist patients suffering from mental health challenges with personalized care and assist clinicians with understanding their patients better. Alleviate draws from an array of publicly available clinically valid mental-health texts and databases, allowing Alleviate to make medically sound and informed …

The Evolution Of Ai On The Commercial Flight Deck: Finding Balance Between Efficiency And Safety While Maintaining The Integrity Of Operator Trust, Mark Miller, Sam Holley, Leila Halawi

Publications

As artificial intelligence (AI) seeks to improve modern society, the commercial aviation industry offers a significant opportunity. Although many parts of commercial aviation including maintenance, the ramp, and air traffic control show promise to integrate AI, the highly computerized digital flight deck (DFD) could be challenging. The researchers seek to understand what role AI could provide going forward by assessing AI evolution on the commercial flight deck over the past 50 years. A modified SHELL diagram is used to complete a Human Factors (HF) analysis of the early use for AI on the commercial flight deck through introduction of the …

Cook-Gen: Robust Generative Modeling Of Cooking Actions From Recipes, Revathy Venkataramanan, Kaushik Roy, Kanak Ray, Renjith Prasad, Yuxin Zi, Vignesh Narayanan, Amit Sheth

Publications

As people become more aware of their food choices, food computation models have become increasingly popular in assisting people in maintaining healthy eating habits. For example, food recommendation systems analyze recipe instructions to assess nutritional contents and provide recipe recommendations. The recent and remarkable successes of generative AI methods, such as auto-regressive large language models, can lead to robust methods for a more comprehensive understanding of recipes for healthy food recommendations beyond surface-level nutrition content assessments. In this study, we explore the use of generative AI methods to extend current food computation models, primarily involving the analysis of nutrition and …

Proknow: Process Knowledge For Safety Constrained And Explainable Question Generation For Mental Health Diagnostic Assistance, Kaushik Roy, Manas Gaur, Misagh Soltani, Vipula Rawte, Ashwin Kalyan, Amit Sheth

Publications

Current Virtual Mental Health Assistants (VMHAs) provide counseling and suggestive care. They refrain from patient diagnostic assistance because of a lack of training on safety-constrained and specialized clinical process knowledge (Pro-Know). In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. We also introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use (ProKnow-data). We develop a method for natural language question generation (NLG) that collects diagnostic information from the patient interactively (ProKnow-algo). We demonstrate the …

Moment-Based Reinforcement Learning For Ensemble Control, Yao-Chi Yu, Vignesh Narayanan, Jr-Shin Li

Publications

Problems involving controlling the collective behavior of a population of structurally similar dynamical systems, the so-called ensemble control, arise in diverse emerging applications and pose a grand challenge in systems science and control engineering. Owing to the severely under-actuated nature and the difficulty of placing large-scale sensor networks, ensemble systems are limited to being actuated and monitored at the population level. Moreover, mathematical models describing the dynamics of ensemble systems are often elusive. Therefore, it is essential to design broadcast controls that excite the entire population in such a way that the heterogeneity in system dynamics are robustly compensated. In …

Tutorial - Shodhguru Labs: Knowledge-Infused Artificial Intelligence For Mental Healthcare, Kaushik Roy

Publications

Artificial Intelligence (AI) systems for mental healthcare (MHCare) have been ever-growing after realizing the importance of early interventions for patients with chronic mental health (MH) conditions. Social media (SocMedia) emerged as the go-to platform for supporting patients seeking MHCare. The creation of peer-support groups without social stigma has resulted in patients transitioning from clinical settings to SocMedia supported interactions for quick help. Researchers started exploring SocMedia content in search of cues that showcase correlation or causation between different MH conditions to design better interventional strategies. User-level Classification-based AI systems were designed to leverage diverse SocMedia data from various MH conditions, …

Ierl: Interpretable Ensemble Representation Learning - Combining Crowdsourced Knowledge And Distributed Semantic Representations, Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Manas Gaur, Amit Sheth

Publications

Large Language Models (LLMs) encode meanings of words in the form of distributed semantics. Distributed semantics capture common statistical patterns among language tokens (words, phrases, and sentences) from large amounts of data. LLMs perform exceedingly well across General Language Understanding Evaluation (GLUE) tasks designed to test a model’s understanding of the meanings of the input tokens. However, recent studies have shown that LLMs tend to generate unintended, inconsistent, or wrong texts as outputs when processing inputs that were seen rarely during training, or inputs that are associated with diverse contexts (e.g., well-known hallucination phenomenon in language generation tasks). Crowdsourced and …

Cooperative Deep Q -Learning Framework For Environments Providing Image Feedback, Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan

Publications

In this article, we address two key challenges in deep reinforcement learning (DRL) setting, sample inefficiency, and slow learning, with a dual-neural network (NN)-driven learning approach. In the proposed approach, we use two deep NNs with independent initialization to robustly approximate the action-value function in the presence of image inputs. In particular, we develop a temporal difference (TD) error-driven learning (EDL) approach, where we introduce a set of linear transformations of the TD error to directly update the parameters of each layer in the deep NN. We demonstrate theoretically that the cost minimized by the EDL regime is an approximation …

A Semantic Web Approach To Fault Tolerant Autonomous Manufacturing, Fadi El Kalach, Ruwan Wickramarachchi, Ramy Harik, Amit Sheth

Publications

The next phase of manufacturing is centered on making the switch from traditional automated to autonomous systems. Future factories are required to be agile, allowing for more customized production, and resistance to disturbances. Such production lines would be able to reallocate resources as needed and minimize downtime while keeping up with market demands. These systems must be capable of complex decision-making based on parameters such as machine status, sensory/IoT data, and inspection results. Current manufacturing lines lack this complex capability and instead focus on low-level decision-making on the machine level without utilizing the generated data to its full extent. This …

Knowledge Graph Guided Semantic Evaluation Of Language Models For User Trust, Kaushik Roy, Tarun Garg, Vedant Palit, Yuxin Zi, Vignesh Narayanan, Amit Sheth

Publications

A fundamental question in natural language processing is - what kind of language structure and semantics is the language model capturing? Graph formats such as knowledge graphs are easy to evaluate as they explicitly express language semantics and structure. This study evaluates the semantics encoded in the self-attention transformers by leveraging explicit knowledge graph structures. We propose novel metrics to measure the reconstruction error when providing graph path sequences from a knowledge graph and trying to reproduce/reconstruct the same from the outputs of the self-attention transformer models. The opacity of language models has an immense bearing on societal issues of …

Acm Web Conference 2023, Usha Lokala, Kaushik Roy, Utkarshani Jaimini, Amit Sheth

Publications

Improving the performance and explanations of ML algorithms is a priority for adoption by humans in the real world. In critical domains such as healthcare, such technology has significant potential to reduce the burden on humans and considerably reduce manual assessments by providing quality assistance at scale. In today’s data-driven world, artificial intelligence (AI) systems are still experiencing issues with bias, explainability, and human-like reasoning and interpretability. Causal AI is the technique that can reason and make human-like choices making it possible to go beyond narrow Machine learning-based techniques and can be integrated into human decision-making. It also offers intrinsic …

L3 Ensembles: Lifelong Learning Approach For Ensemble Of Foundational Language Models*, Aidin Shiri, Kaushik Roy, Amit Sheth, Manas Gaur

Publications

Fine-tuning pre-trained foundational language models (FLM) for specific tasks is often impractical, especially for resource-constrained devices. This necessitates the development of a Lifelong Learning (L3) framework that continuously adapts to a stream of Natural Language Processing (NLP) tasks efficiently. We propose an approach that focuses on extracting meaningful representations from unseen data, constructing a structured knowledge base, and improving task performance incrementally. We conducted experiments on various NLP tasks to validate its effectiveness, including benchmarks like GLUE and SuperGLUE. We measured good performance across the accuracy, training efficiency, and knowledge transfer metrics. Initial experimental results show that the proposed L3 …

The Troubling Emergence Of Hallucination In Large Language Models--An Extensive Definition, Quantification, And Prescriptive Remediations, Vipula Rawte, Swagata Chakraborty, Agnibh Pathak, Anubhav Sarkar, S.M Towhidul Islam Tonmoy, Aman Chadha, Amit Sheth, Amitava Das

Publications

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has parallelly emerged as a by-product, posing significant concerns. While some recent endeavors have been made to identify and mitigate different types of hallucination, there has been a limited emphasis on the nuanced categorization of hallucination and associated mitigation methods. To address this gap, we offer a finegrained discourse on profiling hallucination based on its degree, orientation, and category, along with offering strategies for alleviation. As such, we define two overarching orientations of hallucination: (i) factual mirage (FM) …

Tutorial - Shodhguru Labs: Optimization And Hyperparameter Tuning For Neural Networks, Kaushik Roy

Publications

Neural networks have emerged as a powerful and versatile class of machine learning models, revolutionizing various fields with their ability to learn complex patterns and make accurate predictions. The performance of neural networks depends significantly on the appropriate choice of hyperparameters, which are critical factors governing their architecture, regularization, and optimization techniques. As the demand for high-performance neural networks grows across diverse applications, the need for efficient optimization and hyperparameter tuning methods becomes paramount. This paper presents a comprehensive exploration of optimization strategies and hyperparameter tuning techniques for neural networks. Neural networks have emerged as a powerful and versatile class …

Design Of An Internal Osculating Waverider Intake, Mark E. Noftz, Andrew J. Shuck, Joseph S. Jewell, Jonathan Poggie, Andrew N. Bustard, Thomas J. Juliano, Nicholas J. Bisek

Publications

The design of an inward-turning, high-speed, three-dimensional streamline traced intake is presented from osculating axisymmetric theory. To satisfy the osculating intake design criteria, a stitched Busemann diffuser and Internal Conical Flow-A solution is used as the basic isentropic compressive streamline. This new contour provides efficient compression, high flow uniformity, and straight leading edge shocks of equal strength. Additionally, a novel method for constructing the inlet cowl is presented. The combined process leads to a new method of high-speed intake design. A generic shape-transitioned intake is constructed and named the Indiana Inlet for the Indiana universities that contributed to the project. …

Quantifying Geogrid Reinforcement Mechanism In Roadway Performance Using Cyclic Plate Load (Cpl) Test, G.S. Ellithy, A. Crippa

Publications

For decades, geogrids have been used successfully to improve performance in both paved and unpaved roadway construction. Even though the current state of practice differentiates between the design methodology incorporating geogrids in paved and unpaved roadways, the true improvement contribution of geogrids is to the base layer, or to the layer that is placed directly on top of it. It has been established that the three reinforcement mechanisms by which geogrids enhance roadway performance are: lateral restraint, bearing capacity increase and membrane tension support. In order to quantify these mechanisms and their contribution to the roadway performance improvement, two Cyclic …

Flying Blind: Exploring The Visual Cues Used By Helicopter Pilots In Degraded Visual Environments, Brandon Dreslin, Molly C. Mersinger, Shivani Patel, Alex Chaparro

Publications

Helicopter pilots rely on visual cues from the environment and instrument displays during critical phases of flight – particularly final approach and landing – to safely land. However, the specific visual cues pilots rely on and how they integrate those cues to make anticipatory inceptor inputs or corrections are not well understood. Importantly, those cues may be degraded under nighttime and brownout/whiteout conditions where the downwash of a helicopter’s rotors cause loose dirt/snow to be projected into the air, resulting in the obfuscation of the pilot’s vision outside the aircraft. The lack of visual cues in these conditions means that …

Implementing Dei In Aviation Education: Coping And Addressing Mental Health Concerns, Jorge L. D. Albelo Ph.D., Michael F. O'Toole Ph.D., Samantha Bowyer

Publications

In recent years, different global events have led to increased awareness of the benefits of promoting diversity, equity, and inclusion in the workplace and education. Notably, the aviation industry is seeing increased research initiatives to promote DEI among all generations. Nevertheless, given the rising concerns about mental health in higher education, this paper sought to connect coping and addressing mental health through implementing DEI teachings in aviation education. Integrating DEI in the aviation classroom can be challenging, as many faculty members might feel uncomfortable addressing the topic in their courses. Consequently, the researchers proposed and tested an aviation education approach …

Mental Health Needs Among Minority Aviation Students, Jorge L. D. Albelo Ph.D., Stacey Mcintire

Publications

Higher education, including science, technology, engineering, and mathematics (STEM) education, benefit our society and economic growth. However, overcoming gender disparity and increasing the retention of underrepresented minorities within these programs is challenging. Mental health across higher education has shown to be on the rise, and when it comes to the mental health needs of aviation students, research shows that underrepresented minorities experience unique challenges in achieving academic success. This paper focused on identifying aviation minority students' unique challenges in a small STEM university. This mixed-methods action research study collected quantitative data using an adapted version of the Counseling Center Assessment …

Comparative Analysis Of 3d Printed Bridge Construction In Louisiana, Amirhosein Jafari, Ali Kazemian, Sarah Ataei

Publications

A construction 3D printing system could result in automated infrastructure development at reduced cost and time, significantly boosting overall productivity. Although there has been a growing interest in using construction 3D printing for projects such as house construction, implementing this innovative technology for infrastructure development, particularly bridge construction, has not been investigated as extensively. This study aims to compare the environmental impact of precast and 3D concrete printing (3DCP) techniques with a pedestrian bridge case study, located in Louisiana, where the bridge elements were 3D printed off-site and then transported and assembled on the bridge site. A detailed cradle-to-site life …

Development Of Ultra-High Performance Engineered Geopolymer Composites (Uhp-Egcs), Hassan Noorvand, Miladin Radovic, Marwa Hassan, Svetlana Sukhishvili, Gabriel Arce, Ruwa Abufarsakh, Adriana A. Alvarado, Oscar Huang, Sang Zhen

Publications

This study investigated the possibility of developing novel UHP-EGC materials for the repair and new construction of transportation infrastructure in Region 6 by utilizing locally available resources. To this end, the geopolymers (GPs) in this study were synthesized by activating metakaolin (MK) with potassium silicate and sodium silicate solutions. The solutions were manufactured in the laboratory by dissolving silica fume and potassium hydroxide (KOH) or sodium hydroxide (NaOH) in deionized water. MK-based GP binders, mortars, and fiber-reinforced composites were manufactured and evaluated to determine their density, compressive strength, tensile properties, and slant shear bond strength to Portland cement concrete (PCC). …