Search Results

As the cost and complexity of modern aircraft systems increases, emphasis has been placed on model-based design as a means for reducing development cost and optimizing performance. To facilitate this, an appropriate modeling environment is required that allows developers to rapidly explore a wider design space than can cost effectively be considered through hardware construction and testing. This wide design space can then yield solutions that are far more energy efficient than previous generation designs. In addition, non-intuitive cross-coupled subsystem behavior can also be explored to ensure integrated system stability prior to hardware fabrication and testing. In recent years, optimization of control strategies between coupled subsystems has necessitated the understanding of the integrated system dynamics.

Future aircraft systems are projected to have order of magnitude greater power and thermal demands, along with tighter constraints on the performance of the power and thermal management subsystems. This trend has led to the need for a fully integrated design process where power and thermal systems, and their interactions, are considered simultaneously. To support this new design paradigm, a general framework for codifying and checking specifications and requirements is presented. This framework is domain independent and can be used to translate requirement language into a structured definition that can be quickly queried and applied to simulation and measurement data. It is constructed by generalizing a previously developed power quality analysis framework. The application of this framework is demonstrated through the translation of thermal specifications for airborne electrical equipment, into the SPecification And Requirement Evaluation (SPARE) Tool.

Model based design is a standard practice within the aerospace industry. However, the accuracies of these models are only as good as the parameters used to define them and as a result a great deal of effort is spent on model tuning and parameter identification. This process can be very challenging and with the growing complexity and size of these models, manual tuning is often ineffective. Many methods for automated parameter tuning exist. However, for aircraft systems this often leads to large parameter search problems since frequency based identification and direct gradient search schemes are generally not suitable. Furthermore, the cost of experimentation often limits one to sparse data sets which adds an additional layer of difficulty. As a result, these search problems can be highly sensitive to the definition of the model fitness function, the choice of algorithm, and the criteria for convergence.

In this work we present our recent effort in developing a novel heat exchanger based on endothermic chemical reaction (HEX reactor). The proposed HEX reactor is designed to provide additional heat sink capability for aircraft thermal management systems. Ammonium carbamate (AC) which has a decomposition enthalpy of 1.8 MJ/kg is suspended in propylene glycol and used as the heat exchanger working fluid. The decomposition temperature of AC is pressure dependent (60°C at 1 atmosphere; lower temperatures at lower pressures) and as the heat load on the HEX increases and the glycol temperature reaches AC decomposition temperature, AC decomposes and isothermally absorbs energy from the glycol. The reaction, and therefore the heat transfer rate, is controlled by regulating the pressure within the reactor side of the heat exchanger. The experiment is designed to demonstrate continuous replenishment of AC.

In this paper, a MATLAB-Simulink based general co-simulation approach is presented which supports multi-resolution simulation of distributed models in an integrated architecture. This approach was applied to simulating aircraft thermal performance in our Vehicle Systems Model Integration (VSMI) framework. A representative advanced aircraft thermal management system consisting of an engine, engine fuel thermal management system, aircraft fuel thermal management system and a power and thermal management system was used to evaluate the advantages and tradeoffs in using a co-simulation approach to system integration modeling. For a system constituting of multiple interacting sub-systems, an integrated model architecture can rapidly, and cost effectively address technology insertions and system evaluations. Utilizing standalone sub-system models with table-based boundary conditions often fails to effectively capture dynamic subsystem interactions that occurs in an integrated system.

As the cost and complexity of modern aircraft systems advance, emphasis has been placed on model-based design as a means for cost effective subsystem optimization. The success of the model-based design process is contingent on accurate prediction of the system response prior to hardware fabrication, but the level of fidelity necessary to achieve this objective is often called into question. Identifying the key benefits and limitations of model fidelity along with the key parameters that drive model accuracy will help improve the model-based design process enabling low cost, optimized solutions for current and future programs. In this effort, the accuracy and capability of a vapor cycle system (VCS) model were considered from a model fidelity and parameter accuracy standpoint. A range of model fidelity was evaluated in terms of accuracy, capability, simulation speed, and development time.

Advancement in modern aircraft with the development of more dynamic and efficient technologies has led to these technologies increasingly operated near or at their operation limits. More comprehensive analysis methods based on high-fidelity models co-simulated in an integrated environment are needed to support the full utilization of these advanced technologies. Furthermore, the additional information provided by these new analyses needs to be correlated with updates to traditional metrics and specifications. One such case is the thermal limit requirement that sets the upper bound on a thermal system temperature. Traditionally, this bound is defined based on steady-state conditions. However, advanced thermal management systems experience dynamic events where the temperature is not static and may violate steady-state requirements for brief periods of time.