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REVIEW 3 major objections 5 minor 55 references

A Central Differential Flux with High-Order Dissipation for Robust Simulations of Transcritical Flows

T0 review · 3 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

Pith's one-line read The paper shows that adding a minimal, high-order upwind dissipation to a central primitive-variable flux stabilizes transcritical flow simulations without sacrificing second-order accuracy.

desk verdict CDHD is a solid second-order primitive-variable flux for smooth transcritical flows; the energy-conservation claim is overstated and the hybrid's contact-discontinuity behavior is unexamined. read the letter →

arxiv 2508.21599 v1 pith:KWFNUNL2 submitted 2025-08-29 physics.flu-dyn

classification physics.flu-dyn
keywords transcriticalflowprimitive-variableformulationhybridschemepressureoscillationsenergyconservationWENOreconstructionreal-gasequationofstateDOTRSdissipation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

Transcritical fluid flows, where thermodynamic properties swing sharply across the Widom line, make standard conservative schemes generate spurious pressure oscillations and fail. The paper proposes the Central Differential flux with High-Order Dissipation (CDHD), a primitive-variable flux that combines a central advection term with a tiny upwind-biased dissipation. Because the dissipation is built from high-order reconstructed interface states, it scales as O(Δx^4) in smooth regions and stabilizes the simulation without degrading the second-order accuracy of the central term. In a hybrid framework that switches to a conservative WENO-5/Roe update near shocks, the method keeps sharp fronts, suppresses oscillations, and reduces energy conservation error by about two orders of magnitude compared with a first-order primitive-variable solver.

What carries the argument

The central object is the CDHD flux operator, written as L_v = L_v^central + L_v^diss. L_v^central approximates -B(V)∂_x V by a two-point central difference built from WENO-5 reconstructed one-sided interface states, which is second-order accurate. L_v^diss is a Dumbser–Osher–Toro Riemann solver (DOTRS) path-integral fluctuation, H^± = ∫₀¹ B^±(Ψ(s)) ds (V_R − V_L), evaluated along the straight-line path Ψ(s) between reconstructed states; in smooth regions this term scales as O(Δx^4) and provides stabilization without changing the leading-order error.

What would settle it

Run the 1D transcritical advection case with a significantly sharper temperature transition (say η = 0.01 instead of 0.1) at CFL = 0.8, and measure the L1 norm of the dissipation term as the grid is refined; if the dissipation no longer scales as roughly Δx^4, or if density oscillations or growing energy error appear over ten periods, the smooth-jump assumption fails.

Watch

Extended reading notes

Core claim

The central claim is that spurious pressure oscillations in transcritical simulations can be suppressed without giving up accuracy by writing the primitive-variable spatial operator as L_v = L_v^central + L_v^diss. The central term is a two-point central difference of WENO-5 reconstructed one-sided interface states, which is second-order accurate; the dissipative term is a Dumbser–Osher–Toro path-integral fluctuation evaluated along the straight-line segment between the reconstructed states. Since WENO-5 reconstruction makes the interface jump O(Δx^5) in smooth regions, the dissipation contributes only O(Δx^4), so the total truncation error remains O(Δx^2). Embedding this in a hybrid scheme

Load-bearing premise

The scheme assumes that in smooth transcritical regions the WENO-5 interface jump is genuinely fifth-order small and the thermodynamic Jacobian stays smooth along the straight-line path between states; near the Widom line, where properties change extremely fast, that assumption can be violated, so the dissipation term would no longer be safely subdominant.

Editorial extensions

If this is right

  • Formal second-order accuracy holds in smooth transcritical regions; least-squares convergence rates on the three finest meshes are r = (2.17, 2.17, 2.21) for density, momentum, and total energy.
  • Energy conservation error remains below 0.04% over ten convection periods, about two orders of magnitude smaller than a first-order primitive-variable scheme.
  • Omitting the dissipation term leads to rapid growth of oscillations and blow-up; the O(Δx^4) dissipation is necessary and sufficient for stabilization.
  • The hybrid switch to conservative WENO-5/Roe near shocks captures the correct wave structure in transcritical shock tubes without limiters or filters.
  • The scheme is extendable: replacing the two-point central gradient with a higher-order central or split-flux differencing would raise the overall order without changing the dissipation design.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • The same central-plus-path-integral-dissipation construction could be applied to other non-conservative formulations (multicomponent or multiphase flows), but the O(Δx^4) dissipation scaling is only guaranteed when the interface jump is genuinely high-order small.
  • Near the Widom line, where B(V) and a² vary rapidly, the smoothness assumptions behind the error analysis can be violated; users may need to monitor the dissipation norm and possibly strengthen it locally.
  • The paper does not quantify pressure-equilibrium error in the 2D droplet test; measuring it as a function of interface sharpness would be a clean follow-up.
  • To reach orders beyond two while keeping dissipation subdominant, the reconstruction order and the central-difference order must be increased together; otherwise the dissipation could become the leading error.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper proposes a hybrid numerical method for transcritical real-gas flows. In smooth regions, a primitive-variable update is used, based on a new CDHD flux: a central difference of WENO-5 reconstructed interface states plus an upwind-biased dissipation term computed via Dumbser-Osher-Toro path integrals. Near shock waves, a PVRS-based sensor switches cells to a conservative WENO-5/Roe update. A truncation-error analysis argues that the central term is second-order accurate and the dissipation is O(dx^4) when the interface jump scales as O(dx^5), so the overall scheme is second-order in smooth regions. Numerical tests include 1D advection with convergence rates ~2.17, an energy-conservation comparison against first-order DOTRS, a 1D shock tube without a reference solution, and a 2D droplet advection problem.

Significance. If the claims hold, CDHD provides a simple primitive-variable flux with formal second-order accuracy and subdominant dissipation, which would be a useful building block for transcritical-flow simulation. The error analysis is explicit and the smooth-region convergence test is consistent with the claimed order. However, the validation is incomplete in several load-bearing respects, and the hybrid sensor has a gap for contact discontinuities that directly affects both the error analysis and the robustness claims. The paper is a plausible contribution to a specialized computational-fluid-dynamics venue, but the central claims need reinforcement before acceptance.

major comments (3)
  1. [Section 3.3, Eq. (18) and Section 4.3, Eq. (41)] The error analysis for the dissipation term assumes dV = O(dx^5) in every cell where the primitive CDHD update is applied. The PVRS sensor (18) switches to the conservative update only when the pressure ratio exceeds 1+epsilon; it does not detect contact discontinuities, where pressure is continuous but density jumps. Across a contact, dV = O(1), so H^± = O(1) and L_v^diss = O(1/dx), making the dissipation dominant, not subdominant. This contradicts the statement in Section 4.1 that the primitive update is used only where the O(dx^5) scaling holds. The shock-tube test (Section 5.2) includes a contact but does not provide a quantitative reference solution, so the behavior near contacts is unverified. This gap directly affects the hybrid method's claimed robustness for standard wave structures.
  2. [Section 5.1.3, Table 1] The convergence study evaluates only the pure CDHD scheme on a smooth advection problem. No convergence study is presented for the hybrid scheme, nor for cases that involve discontinuities or cell switching. Since the sensor does not flag contacts, the hybrid scheme will apply the primitive update across contact interfaces where dV=O(1), reducing the local order to first order. This should degrade the global error or at least contaminate the solution near contacts, but the paper does not quantify this effect. The claim of second-order accuracy is therefore not supported for the practical hybrid scheme outside pure smooth regions.
  3. [Section 5.1.2, Figure 3] The energy-conservation claim is based on a comparison against a first-order DOTRS scheme on a smooth advection test. The abstract states that CDHD reduces the energy conservation error by two orders of magnitude compared to 'traditional primitive-variable approaches,' but only one baseline is shown, and it is a deliberately diffusive first-order scheme. No comparison is made to other common primitive-variable methods (e.g., pressure-evolution or double-flux formulations). Furthermore, the hybrid scheme's energy behavior in shock-containing flows is not assessed; switching between non-conservative and conservative updates can introduce conservation defects at the switch points, and this is not measured in the shock-tube test.
minor comments (5)
  1. [Section 3, paragraph 1] Typo: 'Wisdom line' should be 'Widom line'.
  2. [Section 3.3, Eqs. (15)-(16)] The notation in Eqs. (15) and (16) is confusing: u_{i+1/2} is used without prior definition, and the index placement of i+1/2 in the density terms is inconsistent with the text. Please clarify.
  3. [Figure 4] The figure lacks a legend; it is unclear which curve corresponds to density, momentum, and total energy. The caption mentions all three but the plot appears to have three curves without labels.
  4. [Section 5.3] The 2D droplet interface uses η=0.05 on a 151×151 mesh, giving roughly 3-4 cells across the tanh profile. This is a well-resolved, smooth interface rather than a sharp-interface challenge. The statement that the scheme preserves a 'sharp interface' should be tempered.
  5. [Section 4.1, Eq. (24)] The statement that the cell average is v(x_i)+O(dx^2) is standard for a smooth function, but the subsequent argument for WENO-5 accuracy relies on the cell-average reconstruction; this should be stated explicitly to avoid the impression that the O(dx^2) cell-average error limits the interface reconstruction order.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: second-order accuracy and O(Δx^4) dissipation follow from standard WENO-5 properties and Taylor analysis, with external convergence tests.

full rationale

The central accuracy claim is not circular. Section 4.2 derives the O(Δx^2) truncation of the central term from a standard midpoint central-difference identity (Eq. 29) and the O(Δx^2) cell-average error in B(V_i) (Eq. 32); neither is fitted to the convergence data. Section 4.3 obtains H±=O(Δx^5) and L_diss=O(Δx^4) from the WENO-5 interface property V_L, V_R = V(x_{i+1/2})+O(Δx^5) (Eqs. 25, 40), which is an externally established reconstruction property, not a self-citation or a stipulated target. The convergence test (Table 1, Fig. 4) is an independent check that yields rates near 2. The dissipation term is intentionally constructed to be subdominant and its scaling is derived from the reconstruction jump, not assumed as the conclusion. The sensor parameter ε=0.05 and the 3-point Gauss-Legendre quadrature are tuning/implementation choices, not parameters fitted to reproduce the claimed accuracy. There are no load-bearing self-citations: WENO [50], PVRS [49], DOTRS [54,55], and real-gas Roe [51] are all independent prior work. No uniqueness theorem is imported from the authors, and no known result is merely renamed. A possible robustness gap—PVRS does not detect contact discontinuities, so dV=O(Δx^5) may fail near contacts—would be a correctness/robustness concern, not circular reasoning; under the stated circularity criteria it does not affect the score.

Assumptions & free parameters 3 free parameters · 3 assumptions · 0 invented entities

The central accuracy claim rests on standard WENO smoothness, a smoothness/differentiability assumption on B and its eigenstructure, and a heuristic shock sensor that confines the primitive update to smooth cells.

free parameters (3)
  • shock sensor threshold epsilon = 0.05
    Chosen within (0,0.1) in Section 3.3 to switch between primitive and conservative updates; affects the hybrid scheme but not the smooth-region accuracy analysis.
  • Gauss-Legendre quadrature points for DOTRS path integral = 3
    A 3-point rule is used for the path integral in Eq. (22), a numerical approximation choice; more points would reduce path-integration error but is not analyzed.
  • WENO epsilon = 1e-6
    Standard small constant in the WENO weights to avoid division by zero.
assumptions (3)
  • domain assumption WENO-5 reconstruction of smooth data has interface error O(Δx^5) and hence interface jump dV = O(Δx^5).
    Load-bearing for the dissipation scaling in Section 4.3; standard WENO theory requires sufficient smoothness of the data.
  • domain assumption The Jacobian B(V) is C^2 and its eigenstructure is smooth along the straight-line path with no eigenvalue sign change.
    Stated in Section 4.3 to make |B| and B± differentiable; may fail in transcritical flows across the pseudo-boiling line where a^2 varies sharply.
  • ad hoc to paper The hybrid sensor (PVRS, Eq. 18) correctly identifies all cells where WENO smoothness fails, so the primitive update is only applied where dV = O(Δx^5) holds.
    The sensor threshold ε=0.05 is a heuristic; no proof is given that the switching always occurs before the jump becomes O(1).

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Cite this review

Pith. "Pith review of A Central Differential Flux with High-Order Dissipation for Robust Simulations of Transcritical Flows." pith.science (2026). https://pith.science/paper/KWFNUNL2

@misc{pith2026250821599,
  author       = {Pith},
  title        = {Pith review of: A Central Differential Flux with High-Order Dissipation for Robust Simulations of Transcritical Flows},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KWFNUNL2}},
  note         = {Machine review of arXiv:2508.21599}
}
read the original abstract

The simulation of transcritical flows remains challenging due to strong thermodynamic nonlinearities that induce spurious pressure oscillations in conventional schemes.While primitive-variable formulations offer improved robustness under such conditions, they are always limited by energy conservation errors and the absence of systematic high-order treatments for numerical fluxes. In this paper, we introduce the Central Differential flux with High-Order Dissipation (CDHD), a novel numerical flux solver designed for primitive-variable discretization. This method combines a central flux for advection with a minimal, upwind-biased dissipation term to stabilize the simulation while maintaining formal accuracy. The dissipation term effectively suppresses oscillations and improves stability in transcritical flows. Compared to traditional primitive-variable approaches, CDHD reduces the energy conservation error in two order of magnitude. When incorporated into a hybrid framework with a conservative shock-capturing scheme, the method robustly handles both smooth transcritical phenomena and shock waves. Numerical tests validate the accuracy, stability, and energy-preserving capabilities of CDHD, demonstrating its potential as a reliable tool for complex real-gas flow simulations.

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Reference graph

Works this paper leans on

55 extracted references · 50 canonical work pages

  1. [1]

    Nonideal compressible fluid dynamics of dense vapors and super- critical fluids

    Alberto Guardone, Piero Colonna, Matteo Pini, and Andrea Spinelli. Nonideal compressible fluid dynamics of dense vapors and super- critical fluids. Annual Review of Fluid Mechanics, 56(Volume 56, 2024):241–269, 2024

  2. [2]

    Manin, M

    J. Manin, M. Bardi, L.M. Pickett, R.N. Dahms, and J.C. Oefelein. Microscopic investigation of the atomization and mixing processes of diesel sprays injected into high pressure and temperature environ- ments. Fuel, 134:531–543, 2014

  3. [3]

    Singla, P

    G. Singla, P. Scouflaire, C. Rolon, and S. Candel. Transcritical oxy- gen/transcritical or supercritical methane combustion.Proceedings of the Combustion Institute, 30(2):2921–2928, 2005

  4. [4]

    Experimental investigation of transcritical methane flow in rocket engine cooling channel

    Raffaele Votta, Francesco Battista, Vito Salvatore, Marco Pizzarelli, GiuseppeLeccese,FrancescoNasuti,andScottMeyer. Experimental investigation of transcritical methane flow in rocket engine cooling channel. Applied Thermal Engineering, 101:61–70, 2016

  5. [5]

    Bruce Chehroudi. Recent experimental efforts on high-pressure supercritical injection for liquid rockets and their implications.Inter- national Journal of Aerospace Engineering, 2012(1):121802, 2012

  6. [6]

    Y.M.Kim,C.G.Kim,andD.Favrat. Transcriticalorsupercriticalco2 cycles using both low- and high-temperature heat sources.Energy, 43(1):402–415,2012.2ndInternationalMeetingonCleanerCombus- tion (CM0901-Detailed Chemical Models for Cleaner Combustion)

  7. [7]

    Thermodynamic analysis and multi-objective optimization of a waste heat recovery systemwithacombinedsupercritical/transcriticalco2cycle

    Lei Qin, Gongnan Xie, Yuan Ma, and Shulei Li. Thermodynamic analysis and multi-objective optimization of a waste heat recovery systemwithacombinedsupercritical/transcriticalco2cycle. Energy, 265:126332, 2023

  8. [8]

    Simulation and comprehensive study of a new trigeneration process combined with a gas turbine cycle, involving transcritical and supercritical co2 power cycles and goswami cycle

    ChaoyangZhu,YunxiangZhang,MengxiaWang,JinxinDeng,Yiwei Cai, Wei Wei, and Mengxing Guo. Simulation and comprehensive study of a new trigeneration process combined with a gas turbine cycle, involving transcritical and supercritical co2 power cycles and goswami cycle. Journal of Thermal Analysis and Calorimetry, 149(12):6361–6384, 2024

Show all 55 references
  1. [9]

    Heat transfer enhancement of microchannel heat sink using tran- scritical carbon dioxide as the coolant

    Chuan Leng, Xiao-Dong Wang, Wei-Mon Yan, and Tian-Hu Wang. Heat transfer enhancement of microchannel heat sink using tran- scritical carbon dioxide as the coolant. Energy Conversion and Management, 110:154–164, 2016

  2. [10]

    Investigation on embedded microchannel heatsink for 2.5-d integrated package

    Peng Zhang, Da-Wei Wang, and Wen-Sheng Zhao. Investigation on embedded microchannel heatsink for 2.5-d integrated package. IEEE Transactions on Components, Packaging and Manufacturing Technology, 13(6):838–848, 2023

  3. [11]

    Eugene Stanley, and Sergey V

    Jiayuan Luo, Limei Xu, Erik Lascaris, H. Eugene Stanley, and Sergey V. Buldyrev. Behavior of the widom line in critical phenom- ena. Phys. Rev. Lett., 112:135701, Apr 2014

  4. [12]

    Widom line and dynamical crossovers as routes to understand supercritical water.Nature com- munications, 5(1):5806, 2014

    P Gallo, D Corradini, and M Rovere. Widom line and dynamical crossovers as routes to understand supercritical water.Nature com- munications, 5(1):5806, 2014

  5. [13]

    Instabilities in three-dimensional boundary-layer flows with a highly non-ideal fluid.Journal of Fluid Mechanics, 951:A9, 2022

    Jie Ren and Markus Kloker. Instabilities in three-dimensional boundary-layer flows with a highly non-ideal fluid.Journal of Fluid Mechanics, 951:A9, 2022

  6. [14]

    Vorticitydynamicsintranscriticalliquidjetbreakup

    Jordi Poblador-Ibanez, William A Sirignano, and Fazle Hussain. Vorticitydynamicsintranscriticalliquidjetbreakup. JournalofFluid Mechanics, 978:A6, 2024

  7. [15]

    Small- scale turbulent characteristics in transcritical wall-bounded flows

    Fangbo Li, Weiwei Zhang, Bofeng Bai, and Matthias Ihme. Small- scale turbulent characteristics in transcritical wall-bounded flows. Journal of Fluid Mechanics, 986:A36, 2024

  8. [16]

    Sensitivity of three-dimensional boundary layer stability to intrinsicuncertaintiesoffluidproperties:astudyonsupercriticalco2

    Jie Ren, Yongxiang Wu, Xuerui Mao, Cheng Wang, and Markus Kloker. Sensitivity of three-dimensional boundary layer stability to intrinsicuncertaintiesoffluidproperties:astudyonsupercriticalco2. Journal of Fluid Mechanics, 1007:A7, 2025

  9. [17]

    Microconfined high-pressure transcritical fluid turbulence.Physics of Fluids, 35(1), 2023

    Marc Bernades, Francesco Capuano, and Lluís Jofre. Microconfined high-pressure transcritical fluid turbulence.Physics of Fluids, 35(1), 2023

  10. [18]

    Ma, Yu Lv, and Matthias Ihme

    Peter C. Ma, Yu Lv, and Matthias Ihme. An entropy-stable hybrid scheme for simulations of transcritical real-fluid flows.Journal of Computational Physics, 340:330–357, 2017

  11. [19]

    V. A. Dobrev, T. V. Kolev, R. N. Rieben, and V. Z. Tomov. Multi- material closure model for high-order finite element lagrangian hy- drodynamics.InternationalJournalforNumericalMethodsinFluids , 82(10):689–706, 2016

  12. [20]

    Con- servative, pressure-equilibrium-preserving discontinuous galerkin method for compressible, multicomponent flows

    Eric J Ching, Ryan F Johnson, and Andrew D Kercher. Con- servative, pressure-equilibrium-preserving discontinuous galerkin method for compressible, multicomponent flows. arXiv preprint arXiv:2501.12532, 2025

  13. [21]

    Houim and Kenneth K

    Ryan W. Houim and Kenneth K. Kuo. A low-dissipation and time-accurate method for compressible multi-component flow with variable specific heat ratios. Journal of Computational Physics, 230(23):8527–8553, 2011

  14. [22]

    Discontinuous galerkin method for multicomponent chemically reacting flows and combustion.Journal of Computational Physics, 270:105–137, 2014

    Yu Lv and Matthias Ihme. Discontinuous galerkin method for multicomponent chemically reacting flows and combustion.Journal of Computational Physics, 270:105–137, 2014

  15. [23]

    A new two-constant equa- tion of state

    Ding-Yu Peng and Donald B Robinson. A new two-constant equa- tion of state. Industrial & Engineering Chemistry Fundamentals, 15(1):59–64, 1976

  16. [24]

    BruceEPoling,JohnMPrausnitz,O’ConnellJohnPaul,andRobertC Reid.Thepropertiesofgasesandliquids ,volume5.Mcgraw-hillNew York, 2001

  17. [25]

    Lapenna, Rachele Lamioni, Pietro Paolo Ciottoli, and Francesco Creta

    Pasquale E. Lapenna, Rachele Lamioni, Pietro Paolo Ciottoli, and Francesco Creta. Low-Mach number simulations of transcritical flows

  18. [26]

    Mixing under transcritical conditions: An a-priori study using direct numerical simulation

    Pasquale Eduardo Lapenna and Francesco Creta. Mixing under transcritical conditions: An a-priori study using direct numerical simulation. The Journal of Supercritical Fluids, 128:263–278, 2017

  19. [27]

    Turbulentmixingofaslightlysupercriticalvanderwaalsfluidatlow- mach number.Physics of Fluids, 26(5), 2014

    Francesco Battista, Francesco Picano, and Carlo Massimo Casciola. Turbulentmixingofaslightlysupercriticalvanderwaalsfluidatlow- mach number.Physics of Fluids, 26(5), 2014

  20. [28]

    Characterization of pseudo-boiling in a transcritical nitrogen jet.Physics of Fluids, 30(7):077106, 07 2018

    Pasquale Eduardo Lapenna. Characterization of pseudo-boiling in a transcritical nitrogen jet.Physics of Fluids, 30(7):077106, 07 2018

  21. [29]

    Computations of compressible multifluids

    Rémi Abgrall and Smadar Karni. Computations of compressible multifluids. Journal of Computational Physics, 169(2):594–623, 2001

  22. [30]

    Double-flux model for supercritical multicomponent flows at low mach numbers with preconditioning method.Journal of Computa- tional Physics, 458:111091, 2022

    Shuto Yatsuyanagi, Takashi Furusawa, and Satoru Yamamoto. Double-flux model for supercritical multicomponent flows at low mach numbers with preconditioning method.Journal of Computa- tional Physics, 458:111091, 2022

  23. [31]

    Rodriguez, A

    C. Rodriguez, A. Vidal, P. Koukouvinis, M. Gavaises, and M.A. McHugh. Simulation of transcritical fluid jets using the pc-saft eos. Journal of Computational Physics, 374:444–468, 2018

  24. [32]

    Oscillation-free nodal discontinuous spectral element method for the simulation of compressible multicomponent flows

    Ahmad Peyvan, Dongru Li, Jonathan Komperda, and Farzad Mashayek. Oscillation-free nodal discontinuous spectral element method for the simulation of compressible multicomponent flows. Journal of Computational Physics, 452:110921, 2022

  25. [33]

    S. Karni. Viscous shock profiles and primitive formulations.SIAM Journal on Numerical Analysis, 29(6):1592–1609, 1992

  26. [34]

    Multicomponent flow calculations by a consistent primitive algorithm

    Smadar Karni. Multicomponent flow calculations by a consistent primitive algorithm. Journal of Computational Physics, 112(1):31– 43, 1994

  27. [35]

    Approach for simulating gas–liquid-likeflowsundersupercriticalpressuresusingahigh-order central differencing scheme

    Hiroshi Terashima and Mitsuo Koshi. Approach for simulating gas–liquid-likeflowsundersupercriticalpressuresusingahigh-order central differencing scheme. Journal of Computational Physics, 231(20):6907–6923, 2012

  28. [36]

    Soshi Kawai, Hiroshi Terashima, and Hideyo Negishi. A robust and accurate numerical method for transcritical turbulent flows at supercritical pressure with an arbitrary equation of state.Journal of Computational Physics, 300:116–135, 2015

  29. [37]

    Hybrid multifluid algorithms

    Smadar Karni. Hybrid multifluid algorithms. SIAM Journal on Scientific Computing, 17(5):1019–1039, 1996

  30. [38]

    Fedkiw, X.-D

    R. Fedkiw, X.-D. Liu, and S. Osher. A general technique for elim- inating spurious oscillations in conservative schemes for multiphase andmultispecieseulerequations. InternationalJournalofNonlinear Sciences and Numerical Simulation, 3(2):99–106, 2002

  31. [39]

    Adiffuse-interfacemethodfor reducing spurious pressure oscillations in multicomponent transcriti- cal flow simulations.Computers & Fluids, 222:104924, 2021

    BradleyBoydandDorrinJarrahbashi. Adiffuse-interfacemethodfor reducing spurious pressure oscillations in multicomponent transcriti- cal flow simulations.Computers & Fluids, 222:104924, 2021. Bonan Xu et al.:Preprint submitted to Elsevier Page 11 of 12 Central Differential Flux ...

  32. [40]

    Ching, Ryan F

    Eric J. Ching, Ryan F. Johnson, and Andrew D. Kercher. Conserva- tive, pressure-equilibrium-preserving discontinuous galerkin method for compressible, multicomponent flows, 2025

  33. [41]

    Ching, Ryan F

    Eric J. Ching, Ryan F. Johnson, and Andrew D. Kercher. A note on reducing spurious pressure oscillations in fully conservative discon- tinuous galerkin simulations of multicomponent flows, 2023

  34. [42]

    Johnson and Andrew D

    Ryan F. Johnson and Andrew D. Kercher. A conservative discontin- uous galerkin discretization for the chemically reacting navier-stokes equations. Journal of Computational Physics, 423:109826, 2020

  35. [43]

    Franchina, M

    N. Franchina, M. Savini, and F. Bassi. Multicomponent gas flow computationsbyadiscontinuousgalerkinschemeusingl2-projection of perfect gas eos.Journal of Computational Physics, 315:302–322, 2016

  36. [44]

    Spiegel, HT Huynh, and James R

    Seth C. Spiegel, HT Huynh, and James R. DeBonis.De-Aliasing through Over-Integration Applied to the Flux Reconstruction and Discontinuous Galerkin Methods

  37. [45]

    Fully con- servative and pressure-equilibrium preserving scheme for compress- ible multi-component flows

    Yuji Fujiwara, Yoshiharu Tamaki, and Soshi Kawai. Fully con- servative and pressure-equilibrium preserving scheme for compress- ible multi-component flows. Journal of Computational Physics, 478:111973, 2023

  38. [46]

    Terashima, N

    H. Terashima, N. Ly, and M. Ihme. Approximately pressure- equilibrium-preserving scheme for fully conservative simulations of compressible multi-species and real-fluid interfacial flows.Journal of Computational Physics, 524:113701, 2025

  39. [47]

    Kinetic-energy- and pressure-equilibrium-preserving schemes for real-gas turbulence in the transcritical regime

    MarcBernades,LluísJofre,andFrancescoCapuano. Kinetic-energy- and pressure-equilibrium-preserving schemes for real-gas turbulence in the transcritical regime. Journal of Computational Physics, 493:112477, 2023

  40. [48]

    Peeters, and Rene Pecnik

    Pietro Carlo Boldini, Ryo Hirai, Pedro Costa, Jurriaan W.R. Peeters, and Rene Pecnik. Cubens: A gpu-accelerated high-order solver for wall-bounded flows with non-ideal fluids. Computer Physics Communications, 309:109507, 2025

  41. [49]

    Springer Science & Business Media, 2013

    Eleuterio F Toro.Riemann solvers and numerical methods for fluid dynamics: a practical introduction. Springer Science & Business Media, 2013

  42. [50]

    Efficient implementation of weighted eno schemes

    Guang-Shan Jiang and Chi-Wang Shu. Efficient implementation of weighted eno schemes. Journal of Computational Physics, 126(1):202–228, 1996

  43. [51]

    A simple extension of roe’s scheme for real gases.Journal of Computational Physics, 329:16–28, 2017

    Sina Arabi, Jean-Yves Trépanier, and Ricardo Camarero. A simple extension of roe’s scheme for real gases.Journal of Computational Physics, 329:16–28, 2017

  44. [52]

    Thermo- dynamic modeling based on a generalized cubic equation of state for kerosene/lox rocket combustion

    Seong-Ku Kim, Hwan-Seok Choi, and Yongmo Kim. Thermo- dynamic modeling based on a generalized cubic equation of state for kerosene/lox rocket combustion. Combustion and Flame, 159(3):1351–1365, 2012

  45. [53]

    Numerical methods for conservation laws: From analysis to algorithms

    Jan S Hesthaven. Numerical methods for conservation laws: From analysis to algorithms. SIAM, 2017

  46. [54]

    Toro, Cristóbal E

    Bok Jik Lee, Eleuterio F. Toro, Cristóbal E. Castro, and Nikolaos Nikiforakis. Adaptive osher-type scheme for the euler equations with highly nonlinear equations of state.Journal of Computational Physics, 246:165–183, 2013

  47. [55]

    A simple extension of the osherriemannsolvertonon-conservativehyperbolicsystems

    Michael Dumbser and Eleuterio F Toro. A simple extension of the osherriemannsolvertonon-conservativehyperbolicsystems. Journal of Scientific Computing, 48(1):70–88, 2011. Bonan Xu et al.:Preprint submitted to Elsevier Page 12 of 12

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Reviewed August 5, 2026 · model on record in the stance chip above.