Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Mechanical Engineering (3)
- Physical Sciences and Mathematics (3)
- Artificial Intelligence and Robotics (2)
- Computer Sciences (2)
- Electrical and Computer Engineering (2)
-
- Heat Transfer, Combustion (2)
- Social and Behavioral Sciences (2)
- Controls and Control Theory (1)
- Cybersecurity (1)
- Defense and Security Studies (1)
- Dynamics and Dynamical Systems (1)
- Energy Systems (1)
- Engineering Science and Materials (1)
- Environmental Sciences (1)
- Geography (1)
- Military and Veterans Studies (1)
- Natural Resources Management and Policy (1)
- Physical and Environmental Geography (1)
- Political Science (1)
- Public Affairs, Public Policy and Public Administration (1)
- Institution
- Keyword
-
- 0D Modeling (1)
- Adversarial attacks (1)
- Adversarial robustness (1)
- Artificial intelligence (1)
- Autonomous marine vehicles (1)
-
- Autonomous weapon systems (1)
- Bayesian classification (1)
- Boundary fusion (1)
- Combustion (1)
- Computational Fluid Dynamics (1)
- Deep learning (1)
- Diesel Engine (1)
- Digital twin (1)
- Energy management (1)
- Escalation dynamics (1)
- Flow-field estimation (1)
- HF-radar replay (1)
- Integrated Control (1)
- LQR (1)
- Military innovation (1)
- Mixture modeling (1)
- Model security (1)
- Model selection (1)
- Patch tracking (1)
- Persistent monitoring (1)
- Predictive Control (1)
- Receding-horizon scheduling (1)
- Robustness and Uncertainity (1)
- Secure AI systems (1)
- Security dilemma (1)
- Publication
- Publication Type
Articles 1 - 6 of 6
Full-Text Articles in Military Vehicles
Integrated Power, Energy, And Thermal Management For Autonomous Hybrid Off-Road Vehicles: Multi-Timescale Modeling, Predictive Control, And Resilient Thermal Design, Anirudh Sundar
All Dissertations
Electrification and autonomy are increasingly important for off-road vehicles operating in construction, agriculture, mining, defense, and other demanding environments. These platforms must deliver high tractive power under unstructured terrain, harsh ambient conditions, low-speed operation, and large auxiliary loads. While hybrid and electrified powertrains offer improved efficiency, mobility, and auxiliary power capability, they also introduce significant challenges in managing tightly coupled power, energy, and thermal subsystems. In particular, lithium-ion batteries, power electronics, electric machines, and internal combustion engine-generator systems operate across different temperature limits and timescales, requiring coordinated management to ensure efficiency, durability, and safe operation. This dissertation develops modeling, planning, …
Development Of A Mixing-Controlled Combustion Model For 0d Engine Modeling: Using High-Order Models To Guide The Formulation Of Reduced-Order Models, James Gohn
All Dissertations
Vehicles are becoming increasingly complex to comply with the increasingly stringent regulations placed on all market sectors while still maintaining performance requirements. This increased complexity leads to increases in the cost and time it takes to develop and produce these next generation vehicles. To meet demand therefore, it becomes necessary to evaluate numerous design iterations using computer models. There are multiple levels of models that may be necessary for different purposes or use cases. All levels of modeling for virtual prototyping, however, require a level of validation and predictive ability to be useful. To this end, the following thesis presents …
Bayesian Assembly Tool For Intelligent Digital Twin Selection, Shishir Sharma
Bayesian Assembly Tool For Intelligent Digital Twin Selection, Shishir Sharma
All Theses
Digital twins can be used for system performance optimization, health monitoring, predictive maintenance, and investigating system anomalies. A ground vehicle digital twin may be assembled using representations of the subsystem models (tires, suspension system, powertrain, etc.) of different fidelity. Lower fidelity Digital Twins have relatively simpler design and physics, hence are generally computationally less expensive, but may not represent the physical system accurately. On the contrary, higher fidelity Digital Twins are generally more precise in their ability to represent the physical system, but due to complexity, are usually computationally more demanding. This thesis describes the application of Bayesian Classification within …
Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei
Uncertainty-Aware Estimation, Planning, And Control For Tracking Multiple Drifting Patches In Flow Fields, Daniel O. Akanji, Krishnanand N. Kaipa, Cong Wei
Mechanical & Aerospace Engineering Faculty Publications
In this study, we present a replay-based framework for uncertainty-aware persistent tracking of multiple advected surface patches using an autonomous marine vehicle operating in spatiotemporal-varying currents. The method combines three components: local flow estimation, covariance-aware patch-boundary propagation with intermittent boundary fusion, and mission-level scheduling over multiple patches. Each patch is represented by a polygonal boundary, whose vertices are propagated through the estimated flow field while carrying per-vertex covariance, thereby quantifying uncertainty growth during advection. A flow-aware gain-scheduled linear quadratic regulator (LQR) was designed to shape the desired surge speed to take advantage of favorable currents. When the vehicle services a …
Autonomous Weapons And Strategic Stability, Chick Edmond
Autonomous Weapons And Strategic Stability, Chick Edmond
Political Science & Geography Faculty Publications
The increasing number of artificial intelligence (AI) elements within military systems has introduced new forms of security dilemmas related to speed, level of secrecy, and transfer of responsibility from humans to machines. This article addresses the question of whether or how AI enabled autonomous weapons can lead to greater levels of strategic instability. Three causal mechanisms were determined by this study to potentially create destabilizing effects due to the introduction of autonomy; the first mechanism is a reduction in time available for decision making. The second mechanism involves the creation of multiple pathways of escalation. The third mechanism is the …
Stabilized Multi-Objective Optimization For Camouflage Attack In Remote Sensing, Omid Rajabi Rostami, Kazi Aminul Islam, Liuwan Zhu, Rui Ning, Chunsheng Xin, Hongyi Wu, Jiang Li
Stabilized Multi-Objective Optimization For Camouflage Attack In Remote Sensing, Omid Rajabi Rostami, Kazi Aminul Islam, Liuwan Zhu, Rui Ning, Chunsheng Xin, Hongyi Wu, Jiang Li
Electrical & Computer Engineering Faculty Publications
We investigate the vulnerability of multi-task maritime surveillance systems in which object detection and semantic segmentation operate concurrently. We propose Stabilized Multi-Objective Optimization (SMO), a framework that jointly targets Mask R-CNN and U-Net with a single universal adversarial texture in a digital white-box setting, with additional cross-model transfer evaluation. SMO combines a logarithmic-inversion loss transformation, feature inconsistency, and a systematic comparison of six optimization strategies for seven heterogeneous objectives. The loss transformation controls loss-dependent gradient scaling, while a U-Net generator supplies a spatially coherent texture and a hull-aligned application function accommodates target geometry without explicit Expectation over Transformation (EoT) sampling. …