LAW Glass Formulation

Transcription

1 LAW Glass Formulation PRESENTED BY JD VIENNA PNNL-SA-XXXXX

2 Expected Low Activity Waste Batch Compositions Generally sodium salts (calcine composition 75 to 95 wt% Na 2 O) Continuum of compositions with abrupt batch-to-batch composition changes SP8 Baseline Case 2

3 Glass Property Composition Constraints Each glass formulation must simultaneously satisfy a full set of requirements Product quality Processability Regulatory/contractual Economic Phase Stability Loading and Cost Regular Compliance Chemical Durability Viscosity/EC Processing Rate Melter Corrosion 3

4 Continuum of Glass Composition Based on Na 2 O:SO 3 Ratio Baseline glasses formulated and successfully tested up to pilot scale followed distinct composition trends Modest waste loadings appropriate for plant commissioning with minimal risk Na 2 O from Waste Durability Limit Salt Limit Generally durability limited at high soda extreme, salt limited at high sulfate extreme SO 3 4

5 Continuum of Glass Compositions Constant concentrations of: Al 2 O 3 (6.1) B 2 O 3 (10) Fe 2 O 3 (5.5) TiO 2 (1.4) ZnO (3.5) ZrO 2 (3) Concentrations of CaO, Li 2 O, MgO, and Na 2 O based on alkali concentration SiO 2 is 1-sum of everything else Muller et al

6 Advanced Glass Development WTP supported baseline glass development was aimed at commissioning of the plant with a limited range of waste compositions Waste loadings were modest as desired for startup ORP is directly funding research to reduce operations risks and improve process efficiency Aimed at maximizing loading and operational flexibility while not significantly impacting design or on-line availability/processing rate ORP led; PNNL and VSL primary; SRNL, WSU, Rutgers, INL, SWRI, Sheffield U, SHU, Vanderbilt U, ICT, USC support Testing and modeling is underway to enable application of these advances in operation 6

7 Primary Challenges to Increased Waste Loading All-thread rod indicating salt accumulation; from Matlack et al VSL-09R1510-2, The Catholic University of America, Washington, DC. Sulfate-based salt segregation Corrosive to melter materials, increase volatility, may impact waste form 2 Increased most by Cl-, SO2, CrO 4 4 which are rich in some wastes and concentrated in off-gas recycle Decreased most by Li2O, V2O5, and CaO used as additives to improve solubility V2O5 impact? There is no experimental evidence from XANES, EXAFS, or Raman spectroscopy of vanadium providing additional sulfur bonding sites in borosilicate glass by the presence of vanadium sulfur bonds or of vanadium bonding to sulfate tetrahedra McKeown et al J. Non-Crys. Sol. 298: Composition effects on sulfate solubility; from Vienna et al J. Am. Ceram. Soc., 97(10):

8 Primary Challenges to Increased Waste Loading Vapor hydration test (VHT) Hydrothermal test (DIW, 200 C, monolith) Contract requirement (Spec ) (along with Product Consistency Test [PCT]) VHT may be an indicator of propensity for corrosion acceleration Key assumptions Processes occurring at 200 C are compatible with those at 15 C Acceleration can occur in an open system at 15 C VHT can be consistently measured VHT can be reliably predicted as a function of feed composition 0d 6d 15d Amount of glass dissolved [g/m 2 ] y = x Time [days] 8

9 Primary Challenges to Increased Waste Loading VHT rate increased most by alkali, decreased most by high valence oxides (ZrO 2, SnO 2, etc) Very non-linear composition effects Blend of ZrO 2 and SnO 2 added to higher alkali glasses to reduce VHT rate - HLP - ICV - ORP - WTP 50 g/m 2 /d Contract Limit 9

10 LAW Advanced Glass Formulations Model each key property as function of composition Numerically optimize glass while accounting for process and prediction uncertainties Plot comparing baseline and advanced glass compositions 10

11 Significant Increase in Waste Loading Loading of LAW in glass is double that in advanced glasses (weighted average 22.4 wt% Na 2 O) Roughly 5.5% of higher loading (less glass) would be produced if VHT constraint were relaxed Current set of loading rules (used to estimate loading while accounting for various uncertainties) are over conservative (by ~2.5%) Current research aimed at: Further advances in models to reduce uncertainty (understand composition effects on properties) Develop test method(s) that more directly link to IDF performance with less conservatism (compared to VHT) Incorporating advanced glass constraints and models into an algorithm suitable for plant operation 11

12 Backup Slides 12

13 Simplified Process Flow Diagram PT, LAWPS, TSCR, LCS Blend of EMF bottoms and pretreated LAW (variable and important) GFC C M ECE EDE EMF Pretreatment Process Separations [Cs, Sr/TRU (solids)] Potentially leach solids adding Al and NaOH to LAW V C V off-gas Processable glass CRV MFV M Melter Acceptable Glass C M V Composition Mass Volume LAW Vitrification Container Reporting of glass data PT Pretreatment, LAWPS LAW Pretreatment System, TSCR Tank Side Cesium Removal, LCS Low Curie Salt, EMF Effluent Management Facility, GFC Glass Forming Chemicals, CRV Concentrate Receipt Vessel, Melter Feed Preparation Vessel, MFV Melter Feed Vessel, ECE Evaporator Concentrate Effluent, EDE Evaporator Dilute Effluent 13

14 Status >300 LAW glasses tested at crucible scale (compared to 244 for WTP support) 128 Scaled-melter tests Preliminary models fit for use in research and mission planning Used in selected cases in System Plans 7&8 Used in selected cases in Tank Utilization Assessment 2013 Significant reduction in glass mass and mission life in all cases Plant operating models under development (ETA: 2019) 14

15 Uncertainty Property prediction and composition uncertainties must be accounted for in meeting requirements and reflected in reporting of glass composition, inventory, and constrain compliance Gervasio et al. 2018, PNNL

16 Uncertainties Along Formulation Curve In the baseline glass formulation algorithm these uncertainties are directly accounted for with no or minimal impact on loading or glass composition prop U pred prop U comp B prop prop prop prop, = P ± U ± U Property Unit P prop ucci lcci pred comp L prop Error bars prediction uncertainty only ln(r B ) ln[g/l] < ln(r Na ) ln[g/l] < ln(d ) ln[µm] < ln(η 1100 ), u ln[p] < ln(η 1150 ), l ln[p] > ln(η 1150 ), u ln[p] < ln(ε 1100 ), l ln[s/cm] > ln(ε 1200 ), u ln[s/cm] < LAW-RPT-RT

17 Composition Assigned to Containers Page 17 i-1 i-1 i-1 i-1 i-1 D-6 i-1 i-1 i-1 i-1 i-4 i-3 i-2 i-1 i i-1 i-1 i-1 i-1 D-12 D-5 D-4 D-3 D-1 D-2 D MFV and Melter Time D+1 D+2 i+1 i-1 i-1 i-1 i-1 i-1 D-6 i-1 i-1 i-1 i-1 i-4 i-3 i-2 i-1 i i-1 i-1 i-1 i-1 D-12 D-5 D-4 D-3 D-1 D-2 D MFV and Melter Time D+1 D+2 i+1

18 Composition Effects Oxide Al 2 O 3 B 2 O 3 CaO Cr 2 O 3 Fe 2 O 3 K 2 O Li 2 O MgO Na 2 O SiO 2 ZnO ZrO 2 Other Viscosity EC T L, C T (sp) NiO, MnO PCT VHT Nepheline Salt SO 3, Cl, V 2 O 5 TCLP MnO Corrosion NiO - Increase property - Decrease property - Small effect on property multiple arrows are for non-linear effects, first is for lower concentrations 18

19 Timing Very aggressive schedule (i.e., production rate) Production records available at time of container completion No lag storage capability Vessel Batch Size Glass Mass Glass Containers h/vessel d/vessel Container 5.9 MT Melter MT MFV 12,605 L ,605 L CRV 34,500 L * Note: Outdated vessel batch sizes and based on 2007 feed concentration estimates Page 19