Computer-Generated Experimental Designs for Irregular-Shaped Regions

This paper focuses on the construction of computer-generated designs on irregularly-shaped, constrained regions. Overviews of the Fedorov exchange algorithm (FEA) and other exchange algorithms for the construction of D-optimal designs are given. A faster implementation of the FEA is presented, which is referred to as fast-FEA (denoted FFEA). The FFEA was applied to construct D-optimal designs for several published examples with constrained experimental regions. Designs resulting from the FFEA are more D-efficient than published designs, and provide benchmarks for future comparisons of design construction algorithms. The construction of G-optimal designs for constrained regions is also discussed and illustrated with a published example

AW-101 entrained solids - Solubility versus temperature

This report describes the results of a test conducted by Battelle to assess the solubility of the solids entrained in the diluted AW-101 low-activity waste (LAW) sample. BNFL requested Battelle to dilute the AW-1-1 sample using de-ionized water to mimic expected plant operating conditions. BNFL further requested Battelle to assess the solubility of the solids present in the diluted AW-101 sample versus temperature conditions of 30, 40, and 50 C. BNFL requested these tests to assess the composition of the LAW supernatant and solids versus expected plant-operating conditions. The work was conducted according to test plan BNFL-TP-29953-7, Rev. 0, Determination of the Solubility of LAW Entrained Solids. The test went according to plan, with no deviations from the test plan

Liquidus Temperature Data for DWPF Glass

This report provides new liquidus temperature (TL) versus composition data that can be used to reduce uncertainty in TL calculation for DWPF glass. According to the test plan and test matrix design PNNL has measured TL for 53 glasses within and just outside of the current DWPF processing composition window. The TL database generated under this task will directly support developing and enhancing the current TL process-control model. Preliminary calculations have shown a high probability of increasing HLW loading in glass produced at the SRS and Hanford. This increase in waste loading will decrease the lifecycle tank cleanup costs by decreasing process time and the volume of waste glass produced

Glass Development for Treatment of LANL Evaporator Bottoms Waste

Vitrification is an attractive treatment option for meeting the stabilization and final disposal requirements of many plutonium (Pu) bearing materials and wastes at the Los Alamos National Laboratory (LANL) TA-55 facility, Rocky Flats Environmental Technology Site (RFETS), Hanford, and other Department of Energy (DOE) sites. The Environmental Protection Agency (EPA) has declared that vitrification is the "best demonstrated available technology" for high- level radioactive wastes (HLW) (Federal Register 1990) and has produced a handbook of vitriilcation technologies for treatment of hazardous and radioactive waste (US EPA, 1992). This technology has been demonstrated to convert Pu-containing materials (Kormanos, 1997) into durable (Lutze, 1988) and accountable (Forsberg, 1995) waste. forms with reduced need for safeguarding (McCulhun, 1996). The composition of the Evaporator Bottoms Waste (EVB) at LANL, like that of many other I%-bearing materials, varies widely and is generally unpredictable. The goal of this study is to optimize the composition of glass for EVB waste at LANL, and present the basic techniques and tools for developing optimized glass compositions for other Pu-bearing materials in the complex. This report outlines an approach for glass formulation with fixed property restrictions, using glass property-composition databases. This approach is applicable to waste glass formulation for many variable waste streams and vitrification technologies.. Also reported are the preliminary property data for simulated evaporator bottom glasses, including glass viscosity and glass leach resistance using the Toxicity Characteristic Leaching Procedure (TCLP)

Optimum tolerance design using component-amount and mixture-amount experiments

The tolerance design problem involves optimizing component and assembly tolerances to minimize the total cost (sum of manufacturing cost and quality loss). Previous literature recommended using traditional response surface methodology (RSM) designs, models, and optimization techniques to solve the tolerance design problem for the worst-case scenario in which the assembly characteristic is the sum of the component characteristics. In this article, component-amount (CA) and mixture-amount (MA) experiment approaches are proposed as more appropriate for solving this class of tolerance design problems. The CA and MA approaches are typically used for product formulation problems, but can also be applied to this type of tolerance design problem. The advantages of the CA and MA approaches over the RSM approach and over the standard, worst-case tolerance-design method are explained. Reasons for choosing between the CA and MA approaches are also discussed. The CA and MA approaches (experimental design, response modeling, and optimization) are illustrated using real examples