Simulation of Pressure-Driven Flows in Nanochannels Using Multiparticle Collision Dynamics
Bibliographic record
Abstract
A multiparticle collision dynamics algorithm is presented to simulate gas flow in nanoscopic channels with a square cross section. Special attention is given to the definition of inlet and outlet regions of the simulated system and the boundary conditions that are appropriate to describe flow through the nonequilibrium, open system. The boundary conditions are designed to use only physically relevant, readily measurable quantities as input, such as the pressure drop between ends of the channel, the mass flow rate, and the temperature at the input and output. Particular care is taken to minimize the propagation of entrance and exit artifacts due to the inlet and outlet regions by using Navier−Stokes solutions for the expected velocity profile in the first inlet cell. In addition, a collision operator is introduced to simulate an adiabatic diffusive boundary condition to facilitate the study of energy flow through the channel in the absence of thermalizing walls. The results of simulations over a range of conditions are compared to series solutions of the Navier−Stokes equation both with and without slip boundary conditions for isothermal compressible fluid flow in a square channel. The results of the particle-based simulation agree well with the slip boundary condition solution, although the assumption of isothermal flow begins to fail and deviations between the solution and simulation results begin to emerge under high pressure gradients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".