Abstract This paper explores possible implementations of quantum computing technologies, namely the quantum annealing and the quantum walk search algorithm, to solve fluid dynamics problems related to the design and assessment of compact heat exchangers for aeronautical environmental control and thermal management systems, as well as several other science and engineering applications, e.g. oil and gas refinery process. The purpose of this paper is to introduce two alternative implementations to the already assessed numerical resolution of Navier–Stokes equations or the resolution of analog quantum mechanical problem, highlighting how the use of quantum annealing and a classification algorithm (quantum walk search algorithm) can be implemented for the resolution of a lumped-characteristic analytical model of the heat transfer inside a compact heat exchanger, also in case of two-phase refrigerant fluid, for the use during design phase of environmental control system, e.g. provide the design engineers with a relatively simple and quick to use tool, which provides a reasonable result with an easily interpretable physical meaning. We start with a simple two-phase flow within a single-pass mini-channel heat exchanger, describing the mathematical formulation of the problem followed by a simplified implementation of the proposed quantum approaches, highlighting the main procedures of the calculation as well as the practical implications, advantages and disadvantages of the proposed method, e.g. a limited number of CFD simulations are required to evaluate air side heat transfer coefficient and pressure drop for particular designs within the defined design space, and the specific hardware required to implement the quantum process.
Abstract This paper explores possible implementations of quantum computing technologies, namely the quantum annealing and the quantum walk search algorithm, to solve fluid dynamics problems related to the design and assessment of compact heat exchangers for aeronautical environmental control and thermal management systems, as well as several other science and engineering applications, e.g. oil and gas refinery process. The purpose of this paper is to introduce two alternative implementations to the already assessed numerical resolution of Navier–Stokes equations or the resolution of analog quantum mechanical problem, highlighting how the use of quantum annealing and a classification algorithm (quantum walk search algorithm) can be implemented for the resolution of a lumped-characteristic analytical model of the heat transfer inside a compact heat exchanger, also in case of two-phase refrigerant fluid, for the use during design phase of environmental control system, e.g. provide the design engineers with a relatively simple and quick to use tool, which provides a reasonable result with an easily interpretable physical meaning. We start with a simple two-phase flow within a single-pass mini-channel heat exchanger, describing the mathematical formulation of the problem followed by a simplified implementation of the proposed quantum approaches, highlighting the main procedures of the calculation as well as the practical implications, advantages and disadvantages of the proposed method, e.g. a limited number of CFD simulations are required to evaluate air side heat transfer coefficient and pressure drop for particular designs within the defined design space, and the specific hardware required to implement the quantum process.
This document is meant to review and discuss the possible applications of Quantum computing to computational fluid dynamics (CFD) problems.A review of the current state-of-the-art of quantum computing applied to computational fluid dynamics has been carried out, highlining how the technology is still in an early stage of development but very promising.Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations.The devices that perform quantum computations are known as quantum computers.Quantum Computing is currently a very active field of study and development, with expected applications in various fields, including engineering problems.Indeed, several approaches have been proposed for the solutions of CFD problems with the use of quantum algorithms and / or quantum computers.Possible approaches, applicable to compact heat exchangers used in aeronautics, include the development of quantum algorithms, e.g., based on the solutions of Navier Stokes equations or the Lattice Boltzmann Method., the design of an "analog" quantum computer able to mimic the thermal fluid system under investigation, and, finally, the implementation of a scientific machine learning approach.
Abstract This paper explores possible implementations of a quantum annealing-based algorithm, in the Quadratic unconstrained binary optimization method (QUBO) form, to solve the thermo-fluid dynamics problem associated with the design of critical components of aircraft environmental control systems, namely compact heat exchangers and ejectors (also known as jet pumps), used on rotary- or fixed- winged aircrafts environmental control system to mix two fluids and exchange thermal energy. The purpose of this paper is to introduce the implementation of the QUBO model based on compact heat exchangers lumped model and the SAE 1168–6 ejector design procedure, with the formalization of the mathematical problem and the comparison of results obtained with experimental tests, classical resolution approaches and the quantum optimized code, showing how the QUBO approach is an effective and efficient tools for design engineers tasked to design and validate equipment parameters.We start with a simple two-phase flow within a single-pass mini-channel heat exchanger, describing the mathematical formulation of the problem followed by a simplified implementation of the proposed quantum approaches, highlighting the main procedures of the calculation as well as the practical implications, advantages and disadvantages of the proposed method, e.g. a limited number of CFD simulations are required to evaluate air side heat transfer coefficient and pressure drop for particular designs within the defined design space, and the specific hardware required to implement the quantum process.
Abstract. This document is meant to review and discuss the possible applications of Quantum computing in the area of computational fluid dynamics (CFD). A review of the current state-of-the-art of quantum computing applied to computational fluid dynamics has been carried out, highlining how the technology is promising but still in an early stage of development. Furthermore, within the approaches developed to solve CFD problems with the use of quantum algorithms and / or quantum computers, this article discusses a quantum algorithm approach, based on the Lattice Boltzmann Method and developed to the study of 2D flow around a cylinder, a model which can be related to several industrial problems and, in the future, modified to simulate the refrigeration cycle used in aeronautical environmental control systems (ECS). This preliminary code helped to highlight the inherent difficulties to implement a quantum algorithm but helped also to demonstrate the applicability of quantum computing.
Partial differential equations (PDEs) present important computational challenges in several scientific disciplines. Classical numerical methods, while effective, often encounter scalability issues and high computational costs, particularly for complex problems. Quantum computing seems to address these challenges, offering a potential exponential speedup over classical methods. The presented work studies the application of quantum computing, specifically Quantum Annealing, to the computational complexities inherent in solving the Navier-Stokes equations within Computational Fluid Dynamics (CFD). Our study examines the quantum annealing methodology, conducting two different experiments and analyzing the error between the simulation and the analytical solution. The results obtained demonstrate that quantum annealing paradigm can solve this problems and the errors obtained are acceptable in comparison with other methods in the state of the art. By combining theoretical insights with practical implementation, this research clarifies the potential of quantum annealing, providing a comprehensive overview of the simulation framework, analyzing the obtained results, and suggesting future research avenues.
This article is meant to review and discuss the possible applications of Quantum computing in the area of computational fluid dynamics (CFD), with a focus on the application to the aerospace compact heat exchangers. Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations. Several approaches have been proposed for the solutions of CFD problems with the use of quantum algorithms, being the rationale of the development the estimated scalability of quantum computing and the analogy between Navier Stokes equations with the hydrodynamic Schrödinger equation or between the Lattice Boltzmann equation with the quantum Dirac equation. A review of the current state-of-the-art of quantum computing applied to CFD will be carried out, with the description of some practical applications, highlining how the technology is promising but still in an early stage of development.
Abstract This article is meant to review of current state-of-the-art of quantum computing applied to computational fluid dynamics and discuss possible applications of Quantum computing technologies in the area of thermofluid-dynamics. Quantum computers are devices that use quantum mechanical phenomena like superposition, entanglement and interference to perform calculations, with a theoretical high speed-up compared with traditional computing solutions, especially for computer science applications but also for engineering applications, like structural optimization, resolution of linear system and analysis of complex dynamics. Beside the consideration about the hardware implementation of these type of devices, this article propose a simplified taxonomy of the technologies that can be currently envisioned for the resolution of thermofluid dynamics problems, identifying the three main approaches, i.e., the traditional algorithmic or circuital approach (with the use of serval algorithms dedicated to the resolution of partial differential equations as well as algorithms dedicated to optimization and search), the analog approach (with the development of direct simulations given the analogy between quantum mechanical systems, like the Schrödinger flow or the Dirac Majorana formulation, and fluid problems, like the inviscid flow or the Lattice Boltzmann model), and the applications based on machine learning techniques. The article discusses practical examples which highlight the flexibility of the methods as well as their intrinsic limitations that hinder the application to many industrial problems, i.e. the simplifications requires to manage physical non-linearities, or the absence of a general purpose algorithm, indicating, beside the intrinsic properties of each method, the technology readiness level (TRL) of this type of approach and the required level of modelling.