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The diverse and complex requirements of next-generation energy optimized aircraft (EOA) demand detailed transient and dynamic model-based design (MBD) to ensure the proper operation of numerous interconnected and interacting subsystems. In support of the U.S. Air Force's Integrated Vehicle Energy Technology (INVENT) program, several software tools have been developed and are in use that aid in the efficient MBD of next-generation EOA. Among these are subsystem model libraries, automated subsystem model verification test scripts, a distributed co-simulation application, and tools for system configuration, EOA mission building, data logging, plotting, post-processing, and visualization, and energy flow analysis. Herein, each of these tools is described. A detailed discussion of each tool's functionality and its benefits with respect to the goal of achieving successful integrated system simulations in support of MBD of EOA is given.

Advancements in electrical, mechanical, and structural design onboard modern more electric aircraft have added significant stress to the electrical systems. An electrical system level analysis tool has been created in MATLAB/Simulink to facilitate rapid system analysis and optimization to meet the growing demands of modern aircraft. An integratated model of segment level models of an electrical system including a generator, electrical accumulator unit, electrical distribution unit and electromechanical actuators has been developed. Included in the model are mission level models of an engine and aircraft to provide relevant boundary conditions. It is anticipated that the tracking of the electrical distribution through numerical integration of these various subsystems will lead to more accurate predictions of the bus power quality. In this paper the tool is used to evaluate two architectures using two different load profiles.

The diverse and complex requirements of next-generation energy optimized aircraft (EOA) demand detailed transient and dynamic model-based design (MBD) to ensure the proper operation of numerous interconnected and interacting subsystems across multiple disciplines. In support of the U.S. Air Force's Integrated Vehicle Energy Technology (INVENT) program, several MBD-derived software tools, including models of EOA technologies, have been developed. To validate these models and demonstrate the performance of EOA technologies, a series of Integrated Ground Demonstration (IGD) hardware tests are planned. Several of the numerous EOA software tools and MBD-based processes have been updated and adapted to support this activity.

Design of modern aircraft relies heavily on modeling and simulation for reducing cost and improving performance. However, the complexity of aircraft architectures requires accurate modeling of dynamic components across many subsystems. Integrated power and thermal modeling necessitates dynamic simulations of liquid, air, and two-phase fluids within vapor cycle system components, air cycle machine and propulsion components, hydraulic components, and more while heat generation of many on-board electrical components must also be precisely calculated as well. Integration of these highly complex subsystems may result in simulations which are too computationally expensive for quickly modeling extensive variations of aircraft architecture, or will require simulations with reduced accuracy in order to provide computationally inexpensive models.

Increases in on-board heat generation in modern military aircraft have led to a reliance on thermal management techniques using fuel as a primary heat sink. However, recent studies have found that fuel properties, such as specific heat, can vary greatly between batches, affecting the amount of heat delivered to the fuel. With modern aircraft systems utilizing the majority of available heat sink capacity, an improved understanding of the effects of fuel property variability on overall system response is important. One way to determine whether property variability inside a thermal system causes failure is to perform uncertainty analyses on fuel thermophysical properties and compare results to a risk assessment metric. A sensitivity analysis can be performed on any properties that cause inherent system variability to determine which properties contribute the most significant impact.