Student Name: Cristian Puebla-Menne
Advisor: Dr. Dimitri Mavris
Milestone: MS Thesis Proposal
Degree Program: Aerospace Engineering
Title: MISSION-CENTRIC, CAPABILITY-BASED METHODOLOGY FOR THE JOINT ASSESSMENT OF MEANS AND WAYS IN WILDFIRE-FIGHTING OPERATIONS
Abstract: Wildfires are becoming more frequent and destructive worldwide, with significant and increasing economic, social, and health impacts. Response and suppression activities intended to bring these events under control fall within wildfire-fighting operations, which are multi-actor, multi-jurisdictional, multi-dimensional, and multi-phase, with a spatially and temporally evolving structure. They involve heterogeneous resources, distributed authority, interagency coordination, uncertain environmental conditions, and operational performance that emerges from the interaction among resources, activities, information flows, organizational arrangements, and tactical employment. Existing wildfire modeling, optimization, suppression, risk, and decision-support methods provide important analytical capabilities, but they often address fire spread, resource allocation, dispatch, stochastic planning, or tactical placement as separate problems. This creates a methodological gap: there is limited support for a structured, uncertainty-aware, and decision-oriented systems-engineering methodology that can systematically explore, integrate, and assess the joint space of means and ways in wildfire-fighting missions. This thesis work proposes a mission-centric, capability-based methodology for the joint assessment of means and ways in wildfire-fighting operations. Means refer to resources, systems, platforms, crews, technologies, and other capability contributors available or under consideration. Ways refer to the tactical or operational approaches by which those means are employed. The methodology is intended for preparedness-oriented and strategic analysis, not real-time tactical control of ongoing incidents. Its purpose is to support structured exploration of resource compositions, technology insertions, operational concepts, and tactical employment alternatives before selected options undergo more detailed simulation-based evaluation. The methodology is organized into two levels. Level 1, Operational Decomposition, begins with mission-class selection, operational function definition, baseline capability requirements, scenario characterization, operational resource-flow and capability-interaction analysis, capability-delta definition, mission-conditioned capability requirements, and means-space screening. Selected Department of Defense Architecture Framework (DoDAF) views are incorporated into specific phases of the methodology as structuring devices. OV-2 supports the characterization of functional or capability interactions and resource-flow needs before specific means are generated. CV-2 structures the capability space. DOTMLPF-P further complements this view by accounting for selected non-materiel and organizational dimensions of capability. Level 2, Operational Execution, defines the operational activity architecture, maps capabilities to activities, constructs the admissible ways exploration space, integrates means and ways, and dynamically assesses selected integrated alternatives. OV-5b is used to represent required operational activities and their logical relations, while CV-6 maps capabilities to those activities. Feasible means alternatives are represented as X_feas, admissible ways as U_adm, and the parent joint space as Z=X_feas×U_adm. Candidate alternatives z=(x,u)are screened through explicit compatibility and feasibility logic to produce the retained integrated set Z_int. This screening verifies whether the selected means can support the activities invoked by the selected tactical way, whether mission-conditioned requirements are satisfied, whether identified constraints are respected, and whether scenario-specific restrictions invalidate the pairing. Selected integrated alternatives are then evaluated through a simulation-based computational assessment using an M&S tool developed and used by the wildfire-fighting research team at ASDL. The existing M&S tool serves as a baseline environment and is adapted using outputs from the pre
Date and time: 2026-06-12, 09:00 - 12:00
Location: CoVE
Committee:
Dr. Dimitri Mavris (advisor), School of Aerospace Engineering
Professor Daniel Schrage, School of Aerospace Engineering
Professor Jenna Jordan, Sam Nunn School of International Affairs
Dr. Michael Balchanos, School of Aerospace Engineering
Dr. Alicia Sudol, Associate Technical Fellow Lockheed Martin Aeronautics