135 research outputs found
Combustion of hydrogen injected into a supersonic airstream (the SHIP computer program)
The mathematical and physical basis of the SHIP computer program which embodies a finite-difference, implicit numerical procedure for the computation of hydrogen injected into a supersonic airstream at an angle ranging from normal to parallel to the airstream main flow direction is described. The physical hypotheses built into the program include: a two-equation turbulence model, and a chemical equilibrium model for the hydrogen-oxygen reaction. Typical results for equilibrium combustion are presented and exhibit qualitatively plausible behavior. The computer time required for a given case is approximately 1 minute on a CDC 7600 machine. A discussion of the assumption of parabolic flow in the injection region is given which suggests that improvement in calculation in this region could be obtained by use of the partially parabolic procedure of Pratap and Spalding. It is concluded that the technique described herein provides the basis for an efficient and reliable means for predicting the effects of hydrogen injection into supersonic airstreams and of its subsequent combustion
Prediction of hydrodynamics and chemistry of confined turbulent methane-air frames in a two concentric tube combustor
A formulation of the governing partial differential equations for fluid flow and reacting chemical species in a two-concentric-tube combustor is presented. A numerical procedure for the solution of the governing differential equations is described and models for chemical-equilibrium and chemical-kinetics calculations are presented. The chemical-equilibrium model is used to characterize the hydrocarbon reactions. The chemical-kinetics model is used to predict the concentrations of the oxides of nitrogen. The combustor considered consists of two coaxial ducts. Concentric streams of gaseous fuel and air enter the inlet duct at one end; the flow then reverses and flows out through the outer duct. Two sample cases with specified inlet and boundary conditions are considered and the results are discussed
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Reliable Cost Prediction and Control for Intelligent Manufacture: A Key Performance Indicator Perspective
Data Availability Statement: Not applicable. Acknowledgments: We would like to thank Primal Electro for providing the industrial data.Intelligent manufacturing is facing significant challenges in adapting to the ever-changing equipment, instrumentation, process and economics. Such a trend together with the pressure to reliably control and contain production costs means that frequent adjusting decisions are required to adapt to incessant volatility imposed on manufacturing systems. Under this circumstance, cost-effective and quality-guaranteed manufacturing strategies would be the most logical route to reducing production costs. In this paper, a novel dynamical cost prediction and control (CPC) model is proposed to support collective decision-making in intelligent manufacturing, where the model output is the real-time prediction of possible manufacturing costs, while the inputs are generic manufacturing key performance indicators covering inventory, product quality, production efficiency, resource utilisation and environmental impact. This proposed CPC model distinguishes itself from existing ones for its capability to translate manufacturing data (at both the physical level and operation management level) into financial metrics that contribute to forming a common language between engineering, financial and administrative departments of an enterprise. The case study about the assembly line of optoelectronic devices demonstrates that, although different enterprise departments have different priorities, our CPC model helps them to achieve certain consensus on intended production that finally creates satisfactory profitability for the company at controlled manufacturing costs.Natural Science Foundation of Sichuan Province of China under Grant 23NSFSC1427; National Natural Science Foundation of China under Grants U2330206, U2230206, 62173068l European Union’s Horizon 2020 Research and Innovation Programme under Grant 820677 (IQONIC)
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A high-lift optimization methodology for the design of leading and trailing edges on morphing wings
Data Availability Statement - The experimental data presented in Figure 10 and Figure 11 are available in Reference [2] “Axelson, J.A.; Stevens, G.L. Investigation of a Slat in Several Different Positions on a NACA 64A010 Airfoil for a Wide Range of Subsonic Mach Numbers. Technical Note 3129; Ames Aeronautical Laboratory: Moffett Field, CA, USA, March 1954.”Morphing offers an attractive alternative compared to conventional hinged, multi-element high lift devices. In the present work, morphed shapes of a NACA 64A010 airfoil are optimized for maximum lift characteristics. Deformed shapes of the leading and trailing edge are represented through Bezier curves derived from locally defined control points. The optimization process employs the fast Foil2w in-house viscous-inviscid interaction solver for the calculation of aerodynamic characteristics. Transitional flow results indicate that combined leading and trailing edge morphing may increase maximum lift in the order of 100%. A 60–80% increase is achieved when morphing is applied to leading edge only—the so-called droop nose—while a 45% increase is obtained with trailing edge morphing. Out of the stochastic optimization algorithms tested, the Genetic Algorithm, the Evolution Strategies, and the Particle Swarm Optimizer, the latter performs best. It produces the designs of maximum lift increase with the lowest computational cost. For the optimum morphed designs, verification simulations using the high fidelity MaPFlow CFD solver ensure that the high lift requirements set by the optimization process are met. Although the deformed droop nose increases drag, the aerodynamic performance is improved ensuring the overall effectiveness of the airfoil design during take-off and landing
Mathematical Modelling of Single- and Two-Phase Flow Problems in the Process Industries
Many key issuesin design for the process industries are related to the behaviour of fluids in turbulent flow, often involving more than one phase, chemical reaction or heat transfer. Computational-Fluid-Dynamics (CFD) techniques have great potential for analysing these processes and can be of great help to the designer, by reducing the need to resort to cut and try : approaches to the design of complex equipment. The paper presents the fundamental principles of CFD within the context of the so-called finite-domain technique. The procedure can handle one-, two-, and three-dimensional distributions of the variables in space, steady or transient processes, multi-phase processes, and effects such as turbulence, compressibility of phases, buoyancy, phase-change, chemical reactions, gravity stratification, etc. Demonstrations are made of the application of the procedure to the numerical computation of some process industry situations, such as those occurring in adsorbers/regenerators, combustors, cement kilns, and heat - exchangers. It is concluded that :- The finite - domain versions of the differential equations are soluble, with modest computer costs;- The solutions are always physically plausible; and,- There is a need for extensive evaluation and validation of CFD physical and chemical sub-models, particularly those concerning turbulence, chemical kinetics and interphase-transport processes
Assessment of the Impact of Material Selection on Aviation Sustainability, from a Circular Economy Perspective
Climate change and global warming pose great sustainability challenges to the aviation industry. Alternatives to petroleum-based fuels (hydrogen, natural gas, etc.) have emerged as promising aviation fuels for future aircraft. The present study aimed to contribute to the understanding of the impact of material selection on aviation sustainability, accounting for the type of fuel implemented and circular economy aspects. In this context, a decision support tool was introduced to aid decision-makers and relevant stakeholders to identify and select the best-performing materials that meet their defined needs and preferences, expressed through a finite set of conflicting criteria associated with ecological, economic, and circularity aspects. The proposed tool integrates life-cycle-based metrics extending to both ecological and economical dimensions and a proposed circular economy indicator (CEI) focused on the material/component level and linked to its quality characteristics, which also accounts for the quality degradation of materials which have undergone one or more recycling loops. The tool is coupled with a multi-criteria decision analysis (MCDA) methodology in order to reduce subjectivity when determining the importance of each of the considered criteria
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