1,721,103 research outputs found
A physics-driven and machine learning-based digital twinning approach to transient thermal systems
No full textPurpose – In this study, the authors propose a novel digital twinning approach specifically designed
for controlling transient thermal systems. The purpose of this study is to harness the combined power of
deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical
system.
Design/methodology/approach – To achieve this goal, we introduce a deep neural network (DNN)
as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is
used to address the challenges of controlling an unsteady heat transfer problem with an integrated
feedback loop.
Findings – The results of our study demonstrate the effectiveness of the proposed digital twinning
approach in regulating the maximum temperature within the system under varying and unsteady heat flux
conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer
coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s
melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful
evaluations should be conducted if such a training approach, based on steady-state data, is applied to
completely different transient heat transfer problems.
Originality/value – The present work represents one of the first examples of a comprehensive digital
twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this
approach is its robustness. Adopting a training based on dimensionless data, the approach can
seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for
retraining
CFD Modeling of Thermoacoustic Energy Conversion: A Review
No full textIn this article, a comprehensive review of the computational fluid dynamics (CFD)-based modeling approach for thermoacoustic energy conversion devices is proposed. Although thermoacoustic phenomena were discovered two centuries ago, only in recent decades have such thermoacoustic devices been spreading for energy conversion. The limited understanding of thermoacoustic nonlinearities is one of the reasons limiting their diffusion. CFD is a powerful tool that allows taking into consideration all the nonlinear phenomena neglected by linear theory, on which standard designs are based, to develop energy devices that are increasingly efficient. Starting from a description of all possible numerical models to highlight the difference from a full CFD method, the nonlinearities (dynamic, fluid dynamic and acoustic) are discussed from a physical and modeling point of view. The articles found in the literature were analyzed according to their setup, with either a single thermoacoustic core (TAC) or a full device. With regard to the full devices, a further distinction was made between those models solved at the microscopic scale and those involving a macroscopic porous media approach to model the thermoacoustic core. This review shows that there is no nonlinear porous media model that can be applied to the stack, regenerator and heat exchangers of all thermoacoustic devices in oscillating flows for each frequency, and that the eventual choice of turbulence model requires further studies
Un quaderno contabile per una masseria in Capitanata (1478)
No full textDopo una breve introduzione, si fornisce l'edizione di un quaderno di conti del 1478, sinora inedito, relativo ad una masseria sul Candelaro, in Capitanata
La diocesi di Terracina e il vescovo Simeone nel XIII secolo, in Ingenita curiositas. Studi sull'Italia medievale per Giovanni Vitolo, a cura di B. Figliuolo, R. Di Meglio, A. Ambrosio, Battipaglia Laveglia Carlone, ISBN 978-88-86854-68-9
No full textDesign and performance of a ThermoAcoustic Electric Generator powered by waste-heat based on linear and nonlinear modelling
Full text linkThis article presents the design, numerical modeling, and performance evaluation of a multistage ThermoAcoustic Electric Generator (TAEG), aimed at converting thermal energy from internal combustion engine exhaust gases into electricity. The proposed TAEG adopts a double-stage looped resonator configuration, using helium as the working fluid, with an internal static pressure limited to 20 bar for safety reasons. Gas-to-gas hot heat exchangers were specifically designed to recover waste heat at approximately 530 K. Due to practical constraints, commercial audio speakers were employed as acoustic-to-electric transducers, despite their lower impedance compared to ideal linear alternators. Initial linear thermoacoustic simulations conducted using DeltaEC software optimized geometric and operational parameters, predicting an electrical power output around 300 W (150 W per stage) with a resistive load of 10 Omega. However, recognizing the inherent limitations of linear modeling, particularly the omission of nonlinear thermo-fluid dynamics, a computational fluid dynamics (CFD) analysis was conducted using OpenFOAM. The CFD model integrated novel nonlinear porous media formulations tailored for oscillatory flow conditions within the thermoacoustic core. Comparisons between a purely linear DeltaEC and OpenFOAM results revealed excellent qualitative agreement but quantitative differences, primarily due to minor losses caused by abrupt geometric discontinuities, and conical segments. A second DeltaEC model including all minor losses based on the steadystate approximation reveals that dissipation were overestimated compared to the CFD model. Therefore, a third DeltaEC model was built by calibrating minor losses based on CFD data. The findings emphasize the critical role of accurately modeling nonlinear effects to reliably predict TAEG performance and the limitation of the local pressure drop coefficients based on steady-state analysis
[Physical findings concerning the conductivity of the maternal ECG through the dead fetus in utero, using a direct cardiotocographic system].
No full textDirect reciprocity and model-predictive strategy update explain the network reciprocity observed in socioeconomic networks
Full text linkNetwork reciprocity has been successfully put forward (since M. A. Nowak and R. May’s, 1992, influential paper) as the simplest mechanism—requiring no strategical complexity—supporting the evolution of cooperation in biological and socioeconomic systems. The mechanism is actually the network, which makes agents’ interactions localized, while network reciprocity is the property of the underlying evolutionary process to favor cooperation in sparse rather than dense networks. In theoretical models, the property holds under imitative evolutionary processes, whereas cooperation disappears in any network if imitation is replaced by the more rational best-response rule of strategy update. In social experiments, network reciprocity has been observed, although the imitative behavior did not emerge. What did emerge is a form of conditional cooperation based on direct reciprocity—the propensity to cooperate with neighbors who previously cooperated. To resolve this inconsistency, network reciprocity has been recently shown in a model that rationally confronts the two main behaviors emerging in experiments—reciprocal cooperation and unconditional defection—with rationality introduced by extending the best-response rule to a multi-step predictive horizon. However, direct reciprocity was implemented in a non-standard way, by allowing cooperative agents to temporarily cut the interaction with defecting neighbors. Here, we make this result robust to the way cooperators reciprocate, by implementing direct reciprocity with the standard tit-for-tat strategy and deriving similar results
A novel model for macroscopic simulation of oscillating heat and fluid flow in porous media
No full textIn thermoacoustics, stacks and regenerators are porous media where energy conversion takes place. Modelling full thermoacoustic devices with a CFD approach, in order to capture some nonlinearities, can be extremely expensive from a computational perspective compared to a standard linear approach used in the frequency domain. At the same time, macroscopic models for porous media developed for steady-state flows cannot be directly applied in oscillating flow conditions. Moreover, macroscopic models in the available literature for oscillating flows are inaccurate at high frequencies or require a closure coefficient to be determined numerically (with Direct Numerical Simulations) or experimentally. In this article, a time domain macroscopic model for heat and fluid flow is proposed based on the concepts of complex Darcy and Nusselt numbers in the linear regime. Such coefficients, introduced in the past to describe the oscillatory phenomena, have been used for the first time to build a CFD macroscopic model in terms of their real and imaginary parts. For two different porous media, a parallel plate and a transversal pin array, the developed macroscopic model is verified with the microscopic solution. Furthermore, for a transversal pin array stack, the proposed model is validated against experimental data from the available literature, showing a very good agreement. The findings of this paper can help to strongly reduce the computational costs of oscillatory flow simulations without prior direct numerical simulations of the porous core
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