High-cycle fatigue is a critical performance metric of structural alloys for many applications. The high cost, time, and labor involved in experimental fatigue testing call for efficient and accurate computer models o...
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We present further progress, in the form of analytical results, on the Wigner entropy conjecture set forth in [Phys. Rev. A 104, 042211 (2021)] and [J. Phys. A: Math. Theor. 50 385301]. Said conjecture asserts that th...
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Educative computational tools for education in chemicalengineering has been increasing in the last decade due to the advance in technology. This branch of engineering has many subjects that make it difficult to have ...
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The Weissenberg effect, or rod-climbing phenomenon, occurs in non-Newtonian fluids where the fluid interface ascends along a rotating rod. Despite its prominence, theoretical insights into this phenomenon remain limit...
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In this paper, we present a novel kinetic growth model for the micro-organism Methylococcus capsulatus (Bath) that couples growth and pH. We apply growth kinetics in a model for single-cell protein production in a lab...
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Low-dimensional all-inorganic metal halide perovskite(AIMHP)materials,as a new class of nanomaterials,hold great promise for various optoelectronic *** the past few years,tremendous progress has been achieved in the d...
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Low-dimensional all-inorganic metal halide perovskite(AIMHP)materials,as a new class of nanomaterials,hold great promise for various optoelectronic *** the past few years,tremendous progress has been achieved in the development of efficient and stable AIMHP nanomaterials for optical property studies and related ***,we offer a critical overview on the unique merits and the state-of-the-art design of AIMHP using different composition ***,the effects of material compositions,dimensionality,morphologies and structures on optical properties are *** also comprehensively present recent advances in the development AIMHP nanomaterials for practical applications including solar cells,light-emitting diodes,lasers and ***,the critical challenges and future opportunities in this emerging field are highlighted.
In the present work we examine multi-hump solutions of the nonlinear Schrödinger equation in the blowup regime of the one-dimensional model with power law nonlinearity, bearing a suitable exponent of σ > 2. W...
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Data-driven approaches achieve remarkable results for the modeling of complex dynamics based on collected data. However, these models often neglect basic physical principles which determine the behavior of any real-wo...
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ISBN:
(数字)9781665467612
ISBN:
(纸本)9781665467629
Data-driven approaches achieve remarkable results for the modeling of complex dynamics based on collected data. However, these models often neglect basic physical principles which determine the behavior of any real-world system. This omission is unfavorable in two ways: The models are not as data-efficient as they could be by incorporating physical prior knowledge, and the model itself might not be physically correct. We propose Gaussian Process Port-Hamiltonian systems (GPPHS) as a physics-informed Bayesian learning approach with uncertainty quantification. The Bayesian nature of GP-PHS uses collected data to form a distribution over all possible Hamiltonians instead of a single point estimate. Due to the underlying physics model, a GP-PHS generates passive systems with respect to designated inputs and outputs. Further, the proposed approach preserves the compositional nature of Port-Hamiltonian systems.
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