A Non-Linear Flow Model for Porous Media Based on Conformable Derivative Approach
Energies, 2018 Prediction of the non-linear flow in porous media is still a major scientific and engineering challenge, despite major technological advances in both theoretical and computational thermodynamics in the past two decades.
Gang Lei, Nai Cao, Di Liu, Huijie Wang
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Non-local impact of link failures in linear flow networks [PDF]
New Journal of Physics, 2019 The failure of a single link can degrade the operation of a supply network up to the point of complete collapse. Yet, the interplay between network topology and locality of the response to such damage is poorly understood.
Julius Strake +4 more
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Bench scale laboratory tests to analyze non-linear flow in fractured media [PDF]
Hydrology and Earth System Sciences, 2012 The knowledge of flow phenomena in fractured rocks is very important for groundwater resources management in hydrogeological engineering. <br><br> A critical emerging issue for fractured aquifers is the validity of the Darcian-type "local ...
C. Cherubini, C. I. Giasi, N. Pastore
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Energy flow polynomials: a complete linear basis for jet substructure [PDF]
Journal of High Energy Physics, 2018 We introduce the energy flow polynomials: a complete set of jet substructure observables which form a discrete linear basis for all infrared- and collinear-safe observables.
Patrick T. Komiske +2 more
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Linear optimal power flow using cycle flows [PDF]
Electric Power Systems Research, 2018 11 pages, 5 figures; version 2 includes results for generation capacity optimization; version 3 is the final accepted journal ...
Jonas Hörsch +4 more
openaire +5 more sources
A non-linear flow model for the flow behavior of water inrush induced by the karst collapse column. [PDF]
RSC Adv, 2018 Water inrush induced by the karst collapse column (KCC) is a great threat to coal mine safety. In this study, a non-linear flow model that couples three flow types is built based on flow transition from laminar flow in the aquifer to turbulent flow in ...
Hou X, Shi W, Yang T.
europepmc +2 more sources
Maximum Flow and Minimum-Cost Flow in Almost-Linear Time [PDF]
IEEE Annual Symposium on Foundations of Computer Science, 2022 We give an algorithm that computes exact maximum flows and minimum-cost flows on directed graphs with m edges and polynomially bounded integral demands, costs, and capacities in $m^{1+o(1)}$ time. Our algorithm builds the flow through a sequence of $m^{1+
L. Chen +5 more
semanticscholar +1 more source
Trained Transformers Learn Linear Models In-Context [PDF]
Journal of machine learning research, 2023 Attention-based neural networks such as transformers have demonstrated a remarkable ability to exhibit in-context learning (ICL): Given a short prompt sequence of tokens from an unseen task, they can formulate relevant per-token and next-token ...
Ruiqi Zhang, Spencer Frei, P. Bartlett
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Time-dependent lift and drag on a rigid body in a viscous steady linear flow [PDF]
Journal of Fluid Mechanics, 2018 We compute the leading-order inertial corrections to the instantaneous force acting on a rigid body moving with a time-dependent slip velocity in a linear flow field, assuming that the square root of the Reynolds number based on the fluid-velocity ...
F. Candelier, B. Mehlig, J. Magnaudet
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A Linear Branch Flow Model for Radial Distribution Networks and Its Application to Reactive Power Optimization and Network Reconfiguration [PDF]
IEEE Transactions on Smart Grid, 2020 This article presents a cold-start linear branch flow model named modified DistFlow. In modified DistFlow, the active and reactive power are replaced by their ratios to voltage magnitude as state variables, so that errors introduced by conventional ...
Tianshu Yang +4 more
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