A comparison of methods for the modeling of thermochemical convection

Keken, Peter E. van; King, Scott D.; Schmeling, Harro; Christensen, Ulrich R.; Neumeister, D.; Doin, Marie‐Pierre

doi:10.1029/97jb01353

Cited by 264 publications

(304 citation statements)

References 29 publications

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“…Increasing the number of elements improves the mass conservation more significantly, and also results in a larger reduction in entrainment rate (Figures A2d and A2e). This is consistent with the conclusion of van Keken et al [1997] and Tackley and King [2003] that particle-based advection methods are generally not suited for studies of entrainment. However, boundary heat fluxes are relatively insensitive to numerical resolutions ( Figure A2c and Table A1), indicating that the advection scheme is sufficiently accurate for calculating heat fluxes.…”

Section: Appendix A: Numerical Methods and Benchmarks For Convection supporting

confidence: 80%

Constraints on thermochemical convection of the mantle from plume heat flux, plume excess temperature, and upper mantle temperature

2006

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[1] Seismic and geochemical observations indicate a compositionally heterogeneous mantle in the lower mantle, suggesting a layered mantle. The volume and composition of each layer, however, remain poorly constrained. This study seeks to constrain the layered mantle model from observed plume excess temperature, plume heat flux, and upper mantle temperature. Three-dimensional spherical models of whole mantle and layered mantle convection are computed for different Rayleigh number, internal heat generation, buoyancy number, and bottom layer thickness for layered mantle models. The model results show that these observations are controlled by internal heating rate in the layer overlying the thermal boundary layer from which mantle plumes are originated. To reproduce the observations, internal heating rate needs $65% for whole mantle convection, but for layered mantle models, the internal heating rate for the top layer is $60-65% for averaged bottom layer thicknesses <$1100 km. The heat flux at the core-mantle boundary (CMB) is constrained to be $12.6 TW for whole mantle convection. For layered mantle, an upper bound on the CMB heat flux is $14.4 TW. For mantle secular cooling rate of $80 K/Ga, the current study suggests that the top layer of a layered mantle is relatively thick (>2520 km) and has radiogenic heat generation rate >2.82 Â 10 À12 W/kg that is >3 times of that for the depleted mantle source for mid-ocean ridge basalts (DMM). For the top layer to have the radiogenic heat generation of the DMM, mantle secular cooling rate needs to exceed 145 K/Ga. The current study also shows that plume temperature in the upper mantle is about half of the CMB temperature for whole mantle convection or $0.6 of temperature at compositional boundary for a layered mantle, independent of internal heating rate and Rayleigh number. Finally, the model calculations confirm that mantle plumes accounts for the majority ($80%) of CMB heat flux in whole mantle convection models. However, plume heat flux decreases significantly by as much as a factor of 3, as plumes ascend through the mantle to the upper mantle, owing to the adiabatic and possibly diffusive cooling of the plumes and owing to slight ($180 K) subadiabaticity in mantle geotherm.Citation: Zhong, S. (2006), Constraints on thermochemical convection of the mantle from plume heat flux, plume excess temperature, and upper mantle temperature,

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Section: Appendix A: Numerical Methods and Benchmarks For Convection supporting

confidence: 80%

Constraints on thermochemical convection of the mantle from plume heat flux, plume excess temperature, and upper mantle temperature

2006

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“…Beneath the crust, incompressible mantle flow calculations couple the advection-diffusion of energy/temperature to the Stoke's equations (Schubert et al, 2001). The complexity may be increased by introducing the advection of chemical components with low or zero diffusivity, which is often achieved by using particle-based methods (van Keken et al, 1997). Compressible flow, which normally uses an anelastic approximation to filter out seismic waves and timescales, may also introduce reference equations of state derived from models of seismic wave propagation (King et al, 2010).…”

Section: Geodynamicsmentioning

confidence: 99%

Multiphysics simulations: challenges and opportunities.

Keyes¹,

McInnes²,

Woodward³

et al. 2012

149

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We consider multiphysics applications from algorithmic and architectural perspectives, where "algorithmic" includes both mathematical analysis and computational complexity and "architectural" includes both software and hardware environments. Many diverse multiphysics applications can be reduced, en route to their computational simulation, to a common algebraic coupling paradigm. Mathematical analysis of multiphysics coupling in this form is not always practical for realistic applications, but model problems representative of applications discussed herein can provide insight. A variety of software frameworks for multiphysics applications have been constructed and refined within disciplinary communities and executed on leading-edge computer systems. We examine several of these, expose some commonalities among them, and attempt to extrapolate best practices to future systems. From our study, we summarize challenges and forecast opportunities.

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“…This is followed by a description of the contributing codes and a full comparison of the benchmark results. We hope that this comparison will spark a broader comparison with other codes and that this paper will have a similar impact on the community as previous benchmarks for mantle convection modeling (Blankenbach et al, 1989;Travis et al, 1990;Busse et al, 1993;Van Keken et al, 1997).…”

Section: Introductionmentioning

confidence: 99%