Hanford Low-Activity Waste Vitrification: A Review

This Paper Summarizes the Vast Body of Literature (Over 200 Documents) Related to Vitrification of the Low-Activity Waste (LAW) Fraction of the Hanford Tank Wastes. Details Are Provided on the Origins of the Hanford Tank Wastes that Resulted from Nuclear Operations Conducted between 1944 and 1989 to Support Nuclear Weapons Production. Waste Treatment Processes Are Described, Including the Baseline Process to Separate the Tank Waste into LAW and High-Level Waste Fractions, and the LAW Vitrification Facility Being Started at Hanford. Significant Focus is Placed on the Glass Composition Development and the Property-Composition Relationships for Hanford LAW Glasses. Glass Disposal Plans and Criteria for Minimizing Long-Term Environmental Impacts Are Discussed Along with Research Perspectives

Micron-sized Spinel Crystals In High Level Waste Glass Compositions: Determination Of Crystal Size And Crystal Fraction

The compositions utilized for immobilization of high-level nuclear wastes (HLW) are controlled using glass property models to avoid the deleterious effects of crystallization in the high-level waste (HLW) vitrification melters. The type and size of the crystals that precipitate during melter operations (typically at 1150 °C) and idling (∼1000 °C) are significantly impacted by glass composition and thermal history. This study was conducted to measure the impact of melt composition and heat treatment temperature on crystal size and fraction. A matrix of 31 multi-component glasses canvasing the expected Hanford HLW compositional space was developed and the glasses fabricated, and heat treated at 850, 900, and 950 °C. The crystal amounts, as determined by X-ray diffraction, varied from 0.2 to 41.0 wt.%. Spinel concentrations ranged from 0.0 to 13.8 wt.%. One glass of the matrix did not precipitate spinel and contained 0.2 wt.% RuO2, which was assumed to be undissolved from the melting process. All compositions contained crystals in the as-quenched glass. All of the spinel-based crystals present in the glasses were less than 10 μm in diameter, as determined by scanning electron microscopy with image analysis. Composition and temperature dependent models were generated using the resulting data and the best model fit was obtained by only considering spinel concentrations (R2 = 0.87). Two glasses were unable to be characterized because of an inability to process the glass under the conditions of this study. Those glasses were utilized to give insight into a potential multi-component constraint to aid in future statistical composition designs

Compositional Models of Glass/Melt Properties and their Use for Glass Formulation

AbstractNuclear waste glasses must simultaneously meet a number of criteria related to their processability, product quality, and cost factors. The properties that must be controlled in glass formulation and waste vitrification plant operation tend to vary smoothly with composition allowing for glass property-composition models to be developed and used. Models have been fit to the key glass properties. The properties are transformed so that simple functions of composition (e.g., linear, polynomial, or component ratios) can be used as model forms. The model forms are fit to experimental data designed statistically to efficiently cover the composition space of interest. Examples of these models are found in literature. The glass property-composition models, their uncertainty definitions, property constraints, and optimality criteria are combined to formulate optimal glass compositions, control composition in vitrification plants, and to qualify waste glasses for disposal. An overview of current glass property-composition modeling techniques is summarized in this paper along with an example of how those models are applied to glass formulation and product qualification at the planned Hanford high-level waste vitrification plant

The Effects Of Mixing Multi-component HLW Glasses On Spinel Crystal Size

The Hanford Waste Treatment and Immobilization Plant will vitrify radioactive waste into borosilicate glass. The high-level waste (HLW) glass formulations are constrained by processing and property requirements, including restrictions aimed at avoiding detrimental impacts of spinel crystallization in the melter. To understand the impact of glass chemistry on crystallization, two HLW glasses precipitating small (∼5 μm) spinel crystals were individually mixed and melted with a glass that precipitated large (∼45 μm) spinel crystals in ratios of 25, 50, and 75 wt.%. The size of spinel crystals in the mixed glasses varied from 5 to 20 μm. Small crystal size was attributed to: (1) high concentrations of nuclei due to the presence of ruthenium oxide and (2) chromium oxide aiding high rates of nucleation. Results from this study indicate that the spinel crystal size can be controlled using chromium oxide and/or noble metal concentrations in the melt, even in complex mixtures like HLW glasses. Smaller crystals tend to settle more slowly than larger crystals, therefore smaller crystals would be more acceptable in the melter without a risk of failure. Allowing higher concentrations of spinel-forming waste components in the waste glass enables glass compositions with higher waste loading, thus increasing plant operational flexibility. An additional benefit to the presence of chromium oxide in the glass composition is the potential for the oxide to protect melter walls against corrosion

Crystallization In High Level Waste (HLW) Glass Melters: Operational Experience From The Savannah River Site

processing strategy for the Hanford Tank Waste Treatment and Immobilization Plant (WTP). The basis of this alternative approach is an empirical model predicting the crystal accumulation in the WTP glass discharge riser and melter bottom as a function of glass composition, time, and temperature. When coupled with an associated operating limit (e.g., the maximum tolerable thickness of an accumulated layer of crystals), this model could then be integrated into the process control algorithms to formulate crystal tolerant high level waste (HLW) glasses targeting higher waste loadings while still meeting process related limits and melter lifetime expectancies. This report provides a review of the scaled melter testing that was completed in support of the Defense Waste Processing Facility (DWPF) melter. Testing with scaled melters provided the data to define the DWPF operating limits to avoid bulk (volume) crystallization in the un-agitated DWPF melter and provided the data to distinguish between spinels generated by K-3 refractory corrosion versus spinels that precipitated from the HLW glass melt pool. This report includes a review of the crystallization observed with the scaled melters and the full scale DWPF melters (DWPF Melter 1 and DWPF Melter 2). Examples of actual DWPF melter attainment with Melter 2 are given. The intent is to provide an overview of lessons learned, including some example data, that can be used to advance the development and implementation of an empirical model and operating limit for crystal accumulation for WTP. Operation of the first and second (current) DWPF melters has demonstrated that the strategy of using a liquidus temperature predictive model combined with a 100 °C offset from the normal melter operating temperature of 1150 °C (i.e., the predicted liquidus temperature (TL) of the glass must be 1050 °C or less) has been successful in preventing any detrimental accumulation of spinel in the DWPF melt pool, and spinel has not been observed in any of the pour stream glass samples. Spinel was observed at the bottom of DWPF Melter 1 as a result of K-3 refractory corrosion. Issues have occurred with accumulation of spinel in the pour spout during periods of operation at higher waste loadings. Given that both DWPF melters were or have been in operation for greater than 8 years, the service life of the melters has far exceeded design expectations. It is possible that the DWPF liquidus temperature approach is conservative, in that it may be possible to successfully operate the melter with a small degree of allowable crystallization in the glass. This could be a viable approach to increasing waste loading in the glass assuming that the crystals are suspended in the melt and swept out through the riser and pour spout. Additional study is needed, and development work for WTP might be leveraged to support a different operating limit for the DWPF. Several recommendations are made regarding considerations that need to be included as part of the WTP crystal tolerant strategy based on the DWPF development work and operational data reviewed here. These include: Identify and consider the impacts of potential heat sinks in the WTP melter and glass pouring system; Consider the contributions of refractory corrosion products, which may serve to nucleate additional crystals leading to further accumulation; Consider volatilization of components from the melt (e.g., boron, alkali, halides, etc.) and determine their impacts on glass crystallization behavior; Evaluate the impacts of glass REDuction/OXidation (REDOX) conditions and the distribution of temperature within the WTP melt pool and melter pour chamber on crystal accumulation rate; Consider the impact of precipitated crystals on glass viscosity; Consider the impact of an accumulated crystalline layer on thermal convection currents and bubbler effectiveness within the melt pool; Evaluate the impact of spinel accumulation on Joule heating of the WTP melt pool; and Include noble metals in glass melt experiments because of their potential to act as nucleation sites for spinel crystallization

DEVELOPMENT AND APPLICATION OF ENSEMBLE MACHINE LEARNING ALGORITHMS TO ENABLE A PRIORI, HIGH-FIDELITY, AND PROMPT PREDICTIONS AND OPTIMIZATIONS OF COMPLEX MATERIALS AND SYSTEMS

Complex materials consisting of multiple chemical components/phases have been widely used in different engineering applications that have strict criteria. To optimize the mixture design of complex materials, researchers invest enormous resources in cumbersome experiments. However, due to substantial variations in precursors and processing techniques, it has been challenging to develop theoretical frameworks (i.e., empirical models) that could produce reliable predictions of properties of complex materials. In recent years, scientists have harnessed the power of machine learning (ML) and “Big” data to uncover the underlying mixture design-property correlations and produce high-fidelity predictions of properties of complex materials. The ML models autonomously learn cause-effect correlations from the training dataset, and then capitalize on such knowledge to produce predictions on a new data domain. This research consists of six studies. The first three studies focus on utilizing ML models to predict and optimize the fresh and hardened properties of Portland cement (PC) at different ages. The fourth study presents the ML models to predict the compressive strength of alkali-activated cement – a sustainable cement can replace PC – in relation to topological parameters and mixture designs. In the fifth paper, six ML models are employed to predict and optimize the dissolution kinetics of bioactive glasses. The sixth study compares the performance of analytical and ML models in predicting the sulfur solubility of nuclear waste glasses. In some aforesaid studies, closed-form analytical models are developed to predict material properties based on outcomes from ML models --Abstract, p. i

Fiscal Year 2000

The U.S. Department of Energy (DOE) continues to face a major radioactive waste tank remediation problem with hundreds of waste tanks containing hundreds of thousands of cubic meters of high-level waste (HLW) and transuranic (TRU) waste across the DOE complex. Approximately 80 tanks are known or assumed to have leaked. Some of the tank contents have reacted to form flammable gases, introducing additional safety risks. These tanks must be maintained in a safe condition and eventually remediated to minimize the risk of waste migration and/or exposure to workers, the public, and the environment. However, programmatic drivers are more ambitious than baseline technologies and budgets will support. Science and technology development investments are required to reduce the technical and programmatic risks associated with the tank remediation baselines. The Tanks Focus Area (TFA) was initiated in 1994 to serve as the DOE`s Office of Environmental Management`s (EM`s) national technology development program for radioactive waste tank remediation. The national program was formed to increase integration and realize greater benefits from DOE`s technology development budget. The TFA is responsible for managing, coordinating, and leveraging technology development to support DOE`s four major tank sites: Hanford Site (Washington), Idaho National Engineering and Environmental Laboratory (INEEL) (Idaho), Oak Ridge Reservation (ORR) (Tennessee), and Savannah River Site (SRS) (South Carolina). Its technical scope covers the major functions that comprise a complete tank remediation system: waste retrieval, waste pretreatment, waste immobilization, tank closure, and characterization of both the waste and tank with safety integrated into all the functions. The TFA integrates program activities across organizations that fund tank technology development EM, including the Offices of Waste Management (EM-30), Environmental Restoration (EM-40), and Science and Technology (EM-50)

Fiscal Year 1999

The U.S. Department of Energy (DOE) continues to face a major tank remediation problem with approximately 332 tanks storing over 378,000 ml of high-level waste (HLW) and transuranic (TRU) waste across the DOE complex. Most of the tanks have significantly exceeded their life spans. Approximately 90 tanks across the DOE complex are known or assumed to have leaked. Some of the tank contents are potentially explosive. These tanks must be remediated and made safe. How- ever, regulatory drivers are more ambitious than baseline technologies and budgets will support. Therefore, the Tanks Focus Area (TFA) began operation in October 1994. The focus area manages, coordinates, and leverages technology development to provide integrated solutions to remediate problems that will accelerate safe and cost-effective cleanup and closure of DOE`s national tank system. The TFA is responsible for technology development to support DOE`s four major tank sites: Hanford Site (Washington), INEL (Idaho), Oak Ridge Reservation (ORR) (Tennessee), and Savannah River Site (SRS) (South Carolina). Its technical scope covers the major functions that comprise a complete tank remediation system: safety, characterization, retrieval, pretreatment, immobilization, and closure