Lockheed Martin Ethics in Engineering Competition

The Lockheed Martin Ethics in Engineering Competition held in Bethesda, Maryland connects engineering students nationwide to develop professional communication skills and foster discussion of ethical values. By working together to solve technical and ethical challenges, future engineers develop important skills for the workplace that supplement their university education. The 2025 Ethics in Engineering Competition led competitors to research AI decision making processes in wildland fire management, and the Implications of leaving decisions involving human lives to AI. Teams were required to present a solution that Integrated AI responsibly into fire management, while navigating workplace challenges. ERAU – Prescott students networked with Lockheed Martin mentors and other students nationwide while developing valuable workplace skills: Navigating conflict, voicing ethical values, and communicating technically and professionally

Short Story

navy short storie

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Ink & Repurcussions

Shortly after being inaugurated as President of the United States, Eli Gideon is presented with a book. Though it appears to be a mere book, it possesses the power to alter reality. Eli, believing himself worthy of this power, begins to make changes that, initially small in scope, grow - as do the consequences. The global landscape slowly becomes unrecognizable as Eli\u27s ego pushes to bring order - but will he bring destruction instead

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Self-Regulated Thermal Management with Shape-Memory Alloy Torsional Tubes

The need for dynamic thermal management that adapts to varying system needs and requirements is a growing topic of interest in different engineering disciplines, most prominently aerospace and electronics. This demand for improved thermal management systems comes from the general increase of system efficiencies leading to an increase in component energy density. Shape-memory alloy actuators, which respond with a mechanical shape recovery to variations in temperature, can be used as self-regulated thermal management actuators that are able to respond to environmental thermal changes autonomously. In this dissertation, modeling and experimental analysis of a two-way shape-memory effect trained SMA torsional tube for self-regulated thermal management purposes are considered and developed. The behavior of SMAs under steady-state conditions is well understood. However, self-regulated behavior and non-ideal thermal conditions need to be further investigated. SMA behavior is highly non-linear and path-dependent and common applications use active means of temperature and actuation control using closed-loop systems. This research considers an SMA torsional tube responding autonomously to a process fluid running through, which experiences thermal variations. For these purposes, an experimental setup using air as a process fluid and a preliminary system model are completed to investigate the actuator’s self-regulated response and model prediction capabilities. The model is comprised of a heat transfer and SMA portion, with two SMA models considered (Liang-Rogers and a model based on experimental results). Steady-state, unsteady, and mass flow variation cases are carried out and modeled to analyze tube behavior under different conditions. A sensitivity analysis of different model parameters, including changing the process fluid and SMA tube characteristics, is also carried out. It was concluded that TWSME SMA have the potential to become part of thermal management systems. The main advantages include the simplicity of the design and autonomy, though there is a strong need for accurate prediction capabilities and choosing the right geometry and training for the tube tailored to the application is key

Identifying Individual Factors Which Impact Student Learning in a Desktop Flight Training Simulator

With expected global growth in air transport demand and forecasted shortage of pilots, there is a need for faster and cheaper flight training. A range of protocols was used to assess factors such as student’s emotional state, adaptive performance, and situational awareness as possible predictors of flight performance based on the influence of these factors on student flight performance conducted using a Personal Computer-based Aviation Training Devices (PCATD). Factor analysis and regression models were used to identify how these factors related to student performance during a visual flight conducted using a desktop simulator and our findings demonstrated some influence of adaptive performance, emotional state, and situation awareness upon student flight scores