Thermal modeling for the Triton Hopper

Sagmiller, Dylan; Hartwig, Jason; Colozza, Anthony J.; Landis, Geoffrey A.; Oleson, Steven R.

doi:10.1016/j.cryogenics.2020.103146

Cited by 1 publication

(3 citation statements)

References 20 publications

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“…A-sample set matrix D-the objective thickness, m d sh -the thickness of reflector, mm d sp -the thickness of the spacer between two adjacent reflectors, mm k s -the thermal conductivity of the spacer, W/m•K M-molecular weight of residual gas, kg/mol P i -the Gaussian radial basis of the input parameters q r -radiation heat flux, W/m 2 q s -solid conduction heat flux, W/m 2 q g -gas conduction heat flux, W/m 2 q t -total heat flux, W/m 2 q ti -the ideal heat flux density, W/m 2…”

Section: Discussionmentioning

confidence: 99%

“…IL (Interval length) indicates the interval thickness, where reflector density is 0.0463 g/cm 2 and spacer density is 0.0598 g/cm 2 .…”

Section: Multi-objective Optimization Of a Vd-mlimentioning

confidence: 99%

“…The existing VD-MLI optimization is mainly based on the Lockheed model [1], which is a semi-empirical equation obtained by fitting experimental data at temperatures above 77 K. The Lockheed model can not be employed directly to optimize the MLI configuration at LH 2 temperature [2]. On the other hand, the layer-by-layer (LBL) model was used to calculate the heat leakage in VD-MLI structures at LH 2 temperature [3].…”

Section: Introductionmentioning

confidence: 99%

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Multi-Objective Optimization of Variable Density Multi-Layer Insulation for Liquid Hydrogen Containers Based on Reduced-Order Surrogate Model

Tan

et al. 2023

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For liquid hydrogen transportation, thermal insulation materials that are lightweight, compact and exhibit high-performance have been pursued for several decades, and variable density multi-layer insulation (VD-MLI) has been regarded as a promising choice. The thermal insulation performance of the insulation materials is important, but is not at the top of the list; many constraints, such as the space and weight of the insulation structures, are imposed on the design of a VD-MLI. Consequently, this makes the optimization of VD-MLIs more complicated. The present authors conducted a multi-objective optimization of a VD-MLI stacked with specific insulation units. The number of repetitions of the basic insulation unit was regarded as the dimensionless design parameter of the VD-MLI. Based on the experimentally validated layer-by-layer (LBL) model for MLI design, the multi-objective optimization of VD-MLI for liquid hydrogen storage was conducted by the combination of proper orthogonal decomposition with a general regression neural network (POD-GRNN) surrogate model optimization framework. The results showed that the optimal solutions for VD-MLI configurations could be achieved under different constraints. The present optimization framework provides a new reference for the optimization of VD-MLI for cryogenic liquid storage.

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Section: Discussionmentioning

confidence: 99%

“…IL (Interval length) indicates the interval thickness, where reflector density is 0.0463 g/cm 2 and spacer density is 0.0598 g/cm 2 .…”

Section: Multi-objective Optimization Of a Vd-mlimentioning

confidence: 99%