Search for: All records

This paper studies computational improvement of the Gaussian Markov improvement algorithm (GMIA) whose underlying response surface model is a Gaussian Markov random field (GMRF). GMIA’s computational bottleneck lies in the sampling decision, which requires factorizing and inverting a sparse, but large precision matrix of the GMRF at every iteration. We propose smart GMIA (sGMIA) that performs expensive linear algebraic operations intermittently, while recursively updating the vectors and matrices necessary to make sampling decisions for several iterations in between. The latter iterations are much cheaper than the former at the beginning, but their costs increase as the recursion continues and ultimately surpass the cost of the former. sGMIA adaptively decides how long to continue the recursion by minimizing the average per-iteration cost. We perform a floating-point operation analysis to demonstrate the computational benefit of sGMIA. Experiment results show that sGMIA enjoys computational efficiency while achieving the same search effectiveness as GMIA. 

The effects of heterogeneous reactions between river‐borne particles and the carbonate system were studied in the plumes of the Mississippi and Brazos rivers. Measurements within these plumes revealed significant removal of dissolved inorganic carbon (DIC) and total alkalinity (TA). After accounting for all known DIC and TA sinks and sources, heterogeneous reactions (i.e., heterogeneous CaCO₃precipitation and cation exchange between adsorbed and dissolved ions) were found to be responsible for a significant fraction of DIC and TA removal, exceeding 10% and 90%, respectively, in the Mississippi and Brazos plume waters. This finding was corroborated by laboratory experiments, in which the seeding of seawater with the riverine particles induced the removal of the DIC and TA. The combined results demonstrate that heterogeneous reactions may represent an important controlling mechanism of the seawater carbonate system in particle‐rich coastal areas and may significantly impact the coastal carbon cycle.