The Environmental Control System (ECS) of passenger aircraft is the main consumer of non-propulsive power aboard. A computationally efficient and accurate thermal model of the fuselage is needed for future sustainable aircraft to address ECS preliminary sizing and control design, as the ECS should be re-designed to exploit possible synergies with other thermal management systems on board. Differently from previous works, the present aircraft thermal model is extensively documented and released open-source. Moreover, it is completely based on first principles and the acausal modeling paradigm. It results that the model is scalable, easily extendable, and allows for the estimation of the aircraft thermal loads given limited information about its configuration and flight mission. The predictive capabilities of the model have been assessed by comparing the thermodynamic state estimated at the pack discharge for three ECS operating points of an Airbus A320 with data provided by the manufacturer. The maximum deviation is limited to 2.4 K and 4.5 kPa. The validated thermal model has been used to compute the operating envelope of the A320 ECS, showing that the air supply requirements vary substantially with ambient conditions and flight phases. This calls for a multi-point design strategy when assessing novel ECS configurations.

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Modeling non-ideal compressible flows in the context of computational fluid-dynamics (CFD) requires the calculation of thermodynamic state properties at each step of the iterative solution process. To this purpose, the use of a built-in fundamental equation of state (EoS) in entropic form, i.e., s= s(e, ρ), can be particularly cost-effective, as all state properties can be explicitly calculated from the conservative variables of the flow solver. This approach can be especially advantageous for massively parallel computations, in which look-up table (LuT) methods can become prohibitively expensive in terms of memory usage. The goal of this research is to: i) develop a fundamental relation based on the entropy potential; ii) create a data-driven model of entropy and its first and second-order derivatives, expressed as a function of density and internal energy; iii) test the performance of the data-driven thermodynamic model on a CFD case study. Notably, two Multi-Layer Perceptron (MLP) models are trained on a synthetic dataset comprising 500k thermodynamic state points, obtained by means of the Span-Wagner EoS. The thermodynamic properties are calculated by differentiating the fundamental equation, thus ensuring thermodynamic consistency. Conversely, thermodynamic stability is properly enforced during the regression process. Albeit the method is applicable to the development of equation of state models for arbitrary fluids and thermodynamic conditions, the present work only considers siloxane MM in the single phase region. The MLP model is implemented in the open-source SU2 software [8] and is used for the numerical simulation of non-ideal compressible flows in a planar converging-diverging nozzle. Finally, the accuracy and the computational performance of the data-driven thermodynamic model are assessed by comparing the resulting flow field, the wall time and the memory requirements with those obtained with direct calls to a cubic EoS, and with a LuT method.

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In 2022 the aviation sector accounted for 1.9%of global greenhouse gas emissions, 2.5% of global CO2 emissions, and 3.5% of effective radiative forcing. To reach the long-term target of net zero emissions, revolutionary aircraft designs, featuring electrified or hydrogen powered propulsion systems, are needed. At the same time, the electrification of the non propulsive aircraft subsystems is necessary to comply with the requirements of emissions abatement in the short and medium time horizon. Among the auxiliary subsystems, the Environmental Control System (ECS) is the largest consumer of non-propulsive power, accounting for up to 3-5% of the total fuel burn. The replacement of the conventional Air Cycle Machine (ACM) with an electrically-powered ECS based on the Vapor Compression Cycle (VCC) system could enable: i) a substantial decrease in fuel consumption; ii) a finer regulation of the relative humidity in the air distribution system, leading to improved air quality in the cabin and flight deck; iii) a reduction in maintenance costs and an increase in system reliability, due to the removal of the maintenance-intensive bleed system. However, the adoption of VCC systems in the aerospace sector has been historically very limited, due to safety concerns regarding the ozone depleting potential, toxicity and flammability of the working fluids used as refrigerants, as well as because of a lack of research specifically targeting airborne applications. This dissertation documents research work performed as part of the NEDEFA project, which entails the investigation of VCC-based ECS architectures powered by oil-free highspeed centrifugal compressors. The first objective is to advance of the state-of-the-art regarding high-speed compressors operating with gas bearings, i.e., the key technological enablers of airborne VCC systems. The second target is to develop of a methodology for the integrated design of aircraft ECS, namely, a design philosophy in which the system and the main components are optimized simultaneously. The main outcomes of this work are the development of a preliminary design model for high-speed compressors, extensively validated with experimental data and computational fluid dynamics simulations, and the implementation of an integrated design framework for aircraft ECS, embedding a multi-point and multi-objective optimization strategy. The compressor model has been applied to derive design guidelines for single-stage and twin-stage machines operating with arbitrary working fluids, as well as to perform the fluid dynamic design optimization of the compressor that will be installed in the IRIS (Inverse organic Rankine Integrated System) test rig of the Propulsion and Power Laboratory. Furthermore, the integrated design method has been used to size and compare the performance of two alternative ECS configurations for a single-aisle, short-haul aircraft resembling the configuration of an Airbus A320, i.e., a bleedless ACM and an electrically driven VCC. The results reveal that the optimal VCC system could be both more efficient and lighter than the corresponding ACM architecture, leading to potential fuel savings in the order of 20% for the prescribed application. @en

The Environmental Control System (ECS) is the main consumer of non-propulsive power onboard aircraft. The use of an electrically-driven Vapor Compression Cycle (VCC) system, in place of the conventional air cycle machine, can lead to a substantial increase of the coefficient of performance. This work documents the development of an integrated design optimization method for VCC-based aircraft ECS, where the sizing of the system is performed along with the conceptual design of the compact heat exchangers and the high-speed centrifugal compressor. A data-driven model of the compressor has been developed to reduce the complexity of the VCC system model and the computational cost of the associated optimization problem. The model is based on artificial neural networks and has been trained on a synthetic dataset of 165k centrifugal compressor designs, generated with an in-house tool. The case study selected to demonstrate the capabilities of the proposed methodology is the multi-objective design optimization of an electrically-driven VCC system for the ECS of a single-aisle, short-haul aircraft, flying at cruise conditions. The results show that the number of function evaluations needed to identify the Pareto front reduces by a factor of three when using the data-driven model, in place of a meanline method. At the same time, the robustness of the numerical solver is improved, leading to the identification of optimal solutions covering a wider design space. Finally, the proposed methodology enables the analysis of the trends established between the system performance metrics and the design of the individual components.@en

Non-ideal compressible flows exhibit physical behaviors that are quantitatively and qualitatively different than those of a perfect or ideal gas. As such, the classical gas dynamic relationships that can be found on fluid-mechanics textbooks cannot be directly applied to characterize this type of flows. NiceProp is a tool for interactively learning the fundamentals of non-ideal compressible fluid dynamics and the design implications for fluid machinery components. The software is written in Python and features a highly modular structure to ease code readability and to facilitate its further development. The target audience of the software is represented by students, researchers and industry professionals interested to get started or deepen the comprehension of non-ideal compressible flow phenomena.

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The environmental control system (ECS) is the largest auxiliary power consumer, i.e, around 75% of non-propulsive power, among the aircraft subsystems. The adoption of a novel ECS architecture, based on an electrically-driven vapor compression cycle system, can enable a twofold increase of coefficient of performance (COP), as compared to the conventional air cycle machine (ACM). The core of this technology is a high-speed, miniature centrifugal compressor, consisting of two impellers mounted in back-to-back configuration, and running on gas bearings operating with refrigerant. The fluid dynamic design optimization of the twin-stage compressor, to be installed in the vapor compression cycle test rig under realization at Delft University of Technology, is documented in this paper. First, the scaling analysis for centrifugal compressor is extended to provide guidelines for the design of twin-stage machines. Then, a multi-objective conceptual design optimization is performed by resorting to an in-house reduced-order model (ROM), coupled to a genetic algorithm. The fluid dynamic performance and the structural integrity of the optimal design are assessed by means of a hybrid framework, encompassing CFD and ROMs, and by FEA. The results show that it is possible to design a twin-stage compressor for the target application, featuring an average efficiency higher than 70%, a maximum compression ratio exceeding 9, and an operating range of 0.27 at the design rotational speed, despite the detrimental effects of motor cooling and miniature size.

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The impact of size and working fluid on the efficiency, operating range, and axial thrust on bearings is examined for high-speed, oil-free centrifugal compressors. First, the development and validation of a reduced-order model based on scaling principles is documented. Then, the validated compressor model is used to generate design maps for stages operating with arbitrary fluid molecules, and characterized by different size. The results show that compressors operating with fluids made by heavy and complex molecules provide lower efficiency over the entire design space, if compared to their simple-molecule counterparts. However, compressors for complex-molecule fluids require lower rotational speed, and generate lower axial thrust on bearings, thus making them particularly suitable for small-scale applications. Furthermore, a decreasing value of the size parameter has a detrimental effect on the stage efficiency, as a result of manufacturing constraints. The results computed by the compressor model suggest that the efficiency penalty is more sensitive to variations of clearance gap than to surface finishing. Lastly, the reduced-order model has been used to perform a design exercise, i.e., the multi-objective optimization of the first compressor stage of the heat pump test rig being realized at Delft University of Technology. The key characteristics of the optimal compressor design has been compared to those derived from the design maps, to corroborate their validity. The optimal design has been extensively characterized by means of CFD, providing further evidence that efficient mini-compressors operating with organic fluids, and featuring pressure ratios up to five at off-design, are feasible.

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In this work we examine the flow deviation and its relationship to critical choking, i.e., choking of the meridional component of velocity, in transonic turbine cascades operating with non-ideal compressible flows. To this purpose, a generalized expression of the corrected flow per unit area as a function of both the thermodynamic state and the molecular complexity of the working fluid, the Mach number, and the amount of swirl is derived. The trends of the corrected flow with respect to these quantities are used to infer physical insights on the flow deviation and on the operability of transonic turbine cascades in off-design conditions. Moreover, reduced-order models for the estimation of the flow deviation and the preliminary assessment of the losses have been developed and validated against the results of CFD simulations performed on a representative transonic turbine stator. Results suggest that flows of dense organic vapors exhibit larger deviations than those pertaining to compounds made of simple molecules, e.g., air. Furthermore, transonic turbines expanding dense vapors reach critical choking conditions at lower Mach numbers than the ones operating with simple molecules, and are affected by larger dissipation due to viscous mixing.

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In this work we examine the behavior of non-ideal compressible swirling flows. Based on a first-principle analysis, we derive a generalized expression of the corrected flow per unit area as function of the isentropic exponent, characteristic Mach numbers, and swirl parameter. The calculated trends of the corrected flow with respect to these parameters, validated against results from high-fidelity computations, are used to infer physical insights on the behavior of swirling flows in turbomachinery cascades. The results suggest that fluid flows characterized by low values of the isentropic exponent show swirling behaviors that are substantially different than those exhibited by perfect gases. Ultimately, this can make the design of efficient turbomachines operating close to the critical point particularly challenging.

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The impact of non-ideal compressible flows on the fluid-dynamic design of axial turbine stages is examined. First, the classical similarity equation (CSE) is revised and extended to account for the effect of flow non-ideality. Then, the influence of the most relevant design parameters is investigated through the application of a dimensionless turbine stage model embedding a first-principles loss model. The results show that compressibility effects induced by the fluid molecular complexity and the stage volumetric flow ratio produce an offset in the efficiency trends and in the optimal stage layout. Furthermore, flow non-ideality can lead to either an increase or a decrease of stage efficiency up to 3-4% relative to turbines designed to operate in dilute gas state. This effect can be predicted at preliminary design phase through the evaluation of the isentropic pressure-volume exponent. Three-dimensional (3D) RANS simulations of selected test cases corroborate the trends predicted with the reduced-order turbine stage model. URANS computations provide equivalent trends, except for case study niMM1, featuring a non-monotonic variation of the generalized isentropic exponent. For such turbine stage, the efficiency is predicted to be higher than the one computed with any steady-state model based on the control volume approach.

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