Notes
![]() ![]() Notes - notes.io |
Different integral representations for the mass flux of inertial particles transported by turbulent gas flows have been proposed. These are discussed and analyzed. Each formulation provides its own insights into the underlying physical processes governing the resulting flux. However, none of the representations, as it stands, provides an explicit closed-form expression in terms of known statistical properties of the flow and parameters governing particle dynamics. We consider the representations in terms of their potential for reduction to closed-form models. To enable an analysis uncomplicated by the presence of many coupled interactions, we confine our attention to the classic test case of monodisperse particles in homogeneous, isotropic turbulent flows, and subject to a uniform gravitational field. The modification of the mean particle settling velocity resulting from their preferential sampling of fluid velocities is captured by the flux representations. A distribution-based symmetry analysis coupled with a correlation splitting technique is used to reduce and simplify the terms appearing in the flux integrals. This prompts a strategy for closure modeling of the resulting expressions in terms of correlations between the sampled fluid velocity and fluid strain-rate fields. Results from particle-trajectory-based simulations are presented to assess the potential of this closure strategy.We introduce a powerful analytic method to study the statistics of the number N_A(γ) of eigenvalues inside any smooth Jordan curve γ∈C for infinitely large non-Hermitian random matrices A. Our generic approach can be applied to different random matrix ensembles of a mean-field type, even when the analytic expression for the joint distribution of eigenvalues is not known. We illustrate the method on the adjacency matrices of weighted random graphs with asymmetric couplings, for which standard random-matrix tools are inapplicable, and obtain explicit results for the diluted real Ginibre ensemble. The main outcome is an effective theory that determines the cumulant generating function of N_A via a path integral along γ, with the path probability distribution following from the numerical solution of a nonlinear self-consistent equation. We derive expressions for the mean and the variance of N_A as well as for the rate function governing rare fluctuations of N_A(γ). DLin-KC2-DMA datasheet All theoretical results are compared with direct diagonalization of finite random matrices, exhibiting an excellent agreement.We propose a quantum Stirling heat engine with an ensemble of harmonic oscillators as the working medium. We show that the efficiency of the harmonic oscillator quantum Stirling heat engine (HO-QSHE) at a given frequency can be maximized at a specific ratio of the temperatures of the thermal reservoirs. In the low-temperature or equivalently high-frequency limit of the harmonic oscillators, the efficiency of the HO-QSHE approaches the Carnot efficiency. Further, we analyze a quantum Stirling heat engine with an ensemble of particle-in-a-box quantum systems as the working medium. Here both work and efficiency can be maximized at a specific ratio of temperatures of the thermal reservoirs. These studies will enable us to operate the quantum Stirling heat engines at its optimal performance. The theoretical study of the HO-QSHE would provide impetus for its experimental realization, as most real systems can be approximated as harmonic oscillators for small displacements near equilibrium.Airlines use different boarding policies to organize the queue of passengers waiting to enter the airplane. We analyze three policies in the many-passenger limit by a geometric representation of the queue position and row designation of each passenger and apply a Lorentzian metric to calculate the total boarding time. The boarding time is governed by the time each passenger needs to clear the aisle, and the added time is determined by the aisle-clearing time distribution through an effective aisle-clearing time parameter. The nonorganized queues under the common random boarding policy are characterized by large effective aisle-clearing time. We show that, subject to a mathematical assumption which we have verified by extensive numerical computations in all realistic cases, the average total boarding time is always reduced when slow passengers are separated from faster passengers and the slow group is allowed to enter the airplane first. This is a universal result that holds for any combination of the three main governing parameters the ratio between effective aisle-clearing times of the fast and the slow groups, the fraction of slow passengers, and the congestion of passengers in the aisle. Separation into groups based on aisle-clearing time allows for more synchronized seating, but the result is nontrivial, as the similar fast-first policy-where the two groups enter the airplane in reverse order-is inferior to random boarding for a range of parameter settings. The asymptotic results conform well with discrete-event simulations with realistic numbers of passengers. Parameters based on empirical data, with hand luggage as criteria for separating passengers into the slow and fast groups, give an 8% reduction in total boarding time for slow first compared to random boarding.Plants have a special structure, torus-margo (TM) pit, which comprises a thickened torus at the center encircled by a highly porous margo. It is regarded as a key evolutionary structure to enable stable water transport, minimizing the air spread in the vessels. However, its valve-like dynamics to regulate two-phase flows still remains unclear even at a single pit level. Here, we study the air spreading dynamics using a bioinspired model of this soft pit valve. We divide it into the initial onset and the consecutive air-spreads, and propose the criteria of TM structures as the valve-like function. To delay the onset of air spread, the margo region should be thin and deformable enough to seal the pit aperture with the torus before the air penetration. Even after the onset, the membranes whose maximum pore size is smaller than its thickness can avoid continuous air-spread. The criteria also fit properly into botanical data on the morphologies of TM pits, implying that their valve-like behaviors may alleviate the tradeoff between hydraulic safety and efficiency at the single pit level.
Here's my website: https://www.selleckchem.com/products/dlin-kc2-dma.html
![]() |
Notes is a web-based application for online taking notes. You can take your notes and share with others people. If you like taking long notes, notes.io is designed for you. To date, over 8,000,000,000+ notes created and continuing...
With notes.io;
- * You can take a note from anywhere and any device with internet connection.
- * You can share the notes in social platforms (YouTube, Facebook, Twitter, instagram etc.).
- * You can quickly share your contents without website, blog and e-mail.
- * You don't need to create any Account to share a note. As you wish you can use quick, easy and best shortened notes with sms, websites, e-mail, or messaging services (WhatsApp, iMessage, Telegram, Signal).
- * Notes.io has fabulous infrastructure design for a short link and allows you to share the note as an easy and understandable link.
Fast: Notes.io is built for speed and performance. You can take a notes quickly and browse your archive.
Easy: Notes.io doesn’t require installation. Just write and share note!
Short: Notes.io’s url just 8 character. You’ll get shorten link of your note when you want to share. (Ex: notes.io/q )
Free: Notes.io works for 14 years and has been free since the day it was started.
You immediately create your first note and start sharing with the ones you wish. If you want to contact us, you can use the following communication channels;
Email: [email protected]
Twitter: http://twitter.com/notesio
Instagram: http://instagram.com/notes.io
Facebook: http://facebook.com/notesio
Regards;
Notes.io Team