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Williams, Mathew

Publications and source records attributed to Williams, Mathew.

Mark-18A Cold Runs

The Savannah River National Laboratory (SRNL) is tasked by the National Nuclear Security Administration (NNSA) to recover highly valued isotopes from irradiated Mark-18A (Mk-18A) targets. The Savannah River Site (SRS) has sixty-five Mk-18A targets available for the recovery of the high valued materials. The sixty-five Mk-18A targets are currently stored in the L-Area Basin and will be removed one at a time and individually transported to SRNL. Upon receipt at SRNL, the Mk-18A target material will be removed from the confinement, dissolved, chemically separated, and calcined to a stable oxide. The flowsheet is designed to recover the plutonium as well as the trivalent actinides. The remaining unrecovered material will be discarded to the high activity drain (HAD) system in SRNL. A specially designed cask was procured for transport of the targets from L-Area to SRNL. Once received at SRNL, the targets will be loaded into the back of Cell 7 and resized as they enter the cell. The resized targets (1/4 lengths) will then be processed one at a time through the following processes: caustic dissolution and filtration; acidic dissolution and filtration, Reillex anion exchange, diglycolamide (DGA) cation exchange; and DGA calcination. This processing will result in two product streams. The first is an aqueous plutonium solution which will be removed from the shielded cells and taken to a glovebox for further purification and conversion to an oxide. The second is a calcined oxide containing the Am and Cm as well as other lanthanide fission products which will be removed from the shielded cells using a bagless transfer system. Both materials will be packaged for shipment to Oak Ridge National Laboratory (ORNL). All equipment to carry out this process was designed, procured or fabricated, and installed in a mock-up facility (716-4A) at SRS to allow for simulation testing in a non-radioactive area. This equipment was then dismantled and transferred from 716-4A to 773-A and installed in the SRNL Shielded Cells. After installation in the shielded cells facility testing was performed using water followed by surrogates and cold chemicals. Issues were identified during these evaluations, including equipment issues as well as technical challenges. Many of the issues were rectified during performance of the cold runs, and the remaining have a resolution identified. Table ES-1 provides a summary of all issues identified during the cold run operations, as well as the status and identified resolutions to outstanding issues.

07 ISOTOPE AND RADIATION SOURCES

2016 International Land Model Benchmarking (ILAMB) Workshop Report

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections.

earth system models (ESMs)

An Improved Analysis of Forest Carbon Dynamics using Data Assimilation

There are two broad approaches to quantifying landscape C dynamics - by measuring changes in C stocks over time, or by measuring fluxes of C directly. However, these data may be patchy, and have gaps or biases. An alternative approach to generating C budgets has been to use process-based models, constructed to simulate the key processes involved in C exchange. However, the process of model building is arguably subjective, and parameters may be poorly defined. This paper demonstrates why data assimilation (DA) techniques - which combine stock and flux observations with a dynamic model - improve estimates of, and provide insights into, ecosystem carbon (C) exchanges. We use an ensemble Kalman filter (EnKF) to link a series of measurements with a simple box model of C transformations. Measurements were collected at a young ponderosa pine stand in central Oregon over a 3-year period, and include eddy flux and soil C02 efflux data, litterfall collections, stem surveys, root and soil cores, and leaf area index data. The simple C model is a mass balance model with nine unknown parameters, tracking changes in C storage among five pools; foliar, wood and fine root pools in vegetation, and also fresh litter and soil organic matter (SOM) plus coarse woody debris pools. We nested the EnKF within an optimization routine to generate estimates from the data of the unknown parameters and the five initial conditions for the pools. The efficacy of the DA process can be judged by comparing the probability distributions of estimates produced with the EnKF analysis vs. those produced with reduced data or model alone. Using the model alone, estimated net ecosystem exchange of C (NEE)= -251 f 197g Cm-2 over the 3 years, compared with an estimate of -419 f 29gCm-2 when all observations were assimilated into the model. The uncertainty on daily measurements of NEE via eddy fluxes was estimated at 0.5gCm-2 day-1, but the uncertainty on assimilated estimates averaged 0.47 g Cm-2 day-1, and only exceeded 0.5gC m-2 day-1 on days where neither eddy flux nor soil efflux data were available. In generating C budgets, the assimilation process reduced the uncertainties associated with using data or model alone and the forecasts of NEE were statistically unbiased estimates. The results of the analysis emphasize the importance of time series as constraints. Occasional, rare measurements of stocks have limited use in constraining the estimates of other components of the C cycle. Long time series are particularly crucial for improving the analysis of pools with long time constants, such as SOM, woody biomass, and woody debris. Long-running forest stem surveys, and tree ring data, offer a rich resource that could be assimilated to provide an important constraint on C cycling of slow pools. For extending estimates of NEE across regions, DA can play a further important role, by assimilating remote-sensing data into the analysis of C cycles. We show, via sensitivity analysis, how assimilating an estimate of photosynthesis - which might be provided indirectly by remotely sensed data - improves the analysis of NEE.

Williams, Mathew