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At least 145 records · Page 8

Women as a Force Multiplier for Bringing Nuclear Forensic Capabilities to the International Stage

In 2009, the US Department of Energy National Nuclear Security Administration’s (NNSA’s) Defense Nuclear Nonproliferation Program initiated a new nuclear forensics outreach effort under its Confidence Building Measures Program. Little did they know that the timing could not have been better. This article focuses on the early years (2009–2015) of the NNSA’s international nuclear forensics outreach, specifically the efforts and experiences of the women who helped establish this program, building it from a fledgling, bilateral effort into an enduring technical capacity provider engaging with dozens of countries and multilateral organizations. At the onset of the program, nuclear forensics was an emerging priority within the US Government and receiving increased focus from international organizations through high-level diplomatic efforts such as the Nuclear Security Summit and Global Initiative to Combat Nuclear Terrorism. Additionally, working-level initiatives were gaining traction through the International Atomic Energy Agency and the Nuclear Forensics International Technical Working Group. Over the next 6 years, a small team comprising a uniquely large number of women NNSA federal, contract, and national laboratory staff served as key leaders engaging with the international community to strengthen global technical nuclear forensics capacity and best practices. The program continues today under the Nuclear Smuggling Detection and Deterrence Program as Investigation Support. The experiences shared here detail a unique time period when the new technical discipline of nuclear forensics was beginning to mature and gain international traction. The authors have made every effort to remember history correctly and be as inclusive as possible. A wealth of training, guidance, and exercise documentation was developed in the 2009–2015 time frame, much of which still serves as the foundation for today’s even more extensive program and community of dedicated technical and diplomatic practitioners.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Circulating Current Reduction of Back-to-Back MMC with Advanced Grid-Support Functionalities for Medium-Voltage Applications

A Lyapunov energy function based circulating current reduction scheme for a back to back modular multilevel converter based system for a microgrid application has been proposed in this digest. In order to ensure no circulating or zero sequence currents within the modules, the dynamics from one leg of the converter to the other are evaluated. A Lyapunov energy function is then developed and utilizing the circulating current dynamics of the converter the overall control law is implemented. In this digest a decentralized hierarchical control architecture has been implemented for the main current control; where the outer loop or the central controller implements the higher level grid interconnection functions as per IEEE 1547-2018 standards and the inner loop based on synchronous reference frame implements the current control architecture. The inner loops' outputs are the commanded converter voltages either on either side which are augmented by the Lyapunov energy function based circulating current suppression architecture. To evaluate the efficacy of the overall system, the overall system is modeled around a 300kVA back to back SiC multilevel modular converter used as a direct-connected medium voltage (MV) grid intertie based on MATLAB/Simulink domain. Several important case studies are presented in this paper to prove the effectiveness of the proposed architecture. case study results are presented.

circulating current↗

Strong reconnection electric fields in shock-driven turbulence

Turbulent magnetic reconnection in a quasi-parallel shock under parameters relevant to the Earth's bow shock is investigated by means of a two-dimensional particle-in-cell simulation. The addressed aspects include the reconnection electric field, the reconnection rate, and the electron and the ion outflow speeds. In the shock transition region, many current sheets are generated in shock-driven turbulence, and electron-only reconnection and reconnection where both ions and electrons are involved can occur in those current sheets. The electron outflow speed in electron-only reconnection shows a positive correlation with the theoretical speed, which is close to the local electron Alfvén speed, and a strong convection electric field is generated by the large electron outflow. As a result, the reconnection electric field becomes much larger than those in the standard magnetopause or magnetotail reconnection. In shock-driven reconnection that involves ion dynamics, both electron outflows and ion outflows can reach of the order of 10 times the Alfvén speed in the X-line rest frame, leading to a reconnection electric field the same order as that in electron-only reconnection. An electron-only reconnection event observed by the magnetospheric multiscale mission downstream of a quasi-parallel shock is qualitatively similar to those in the simulation and shows that the outflow speed reaches approximately half the local electron Alfvén speed, supporting the simulation prediction.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DETECTING FIRE WITH MACHINE LEARNING-ENABLED VISUAL MONITORING FOR NUCLEAR POWER PLANT ENVIRONMENTS

Nuclear power plants are experiencing significant cost challenges to remain competitive with other energy-generation utilities. Unlike other industries, the cost of operation and maintenance activities is mostly attributed to workforce costs. To mitigate this, nuclear power plant stakeholders are increasingly interested in the development and deployment of machine learning methods to potentially automate or augment manually intensive tasks to reduce costs, especially for monitoring activities. One monitoring function that is visually demanding and that can occur frequently to meet the requirements of a fire protection program is visually monitoring an area for fire occurrence. Currently, fire watch activities consist of a worker physically stationed at a given location with the sole responsibility of observing a given area to ensure a fire is detected and mitigated promptly. This effort focused on the development and evaluation of a suitable deep convolutional neural network to classify individual video frames at a sub-second frequency for the occurrence of “fire” and “no fire” in varying industrial environments similar to nuclear power plants. It is believed that a trained neural network model could be integrated with existing facility video surveillance camera feeds to generate alerts when fire inferences occur in individual frames captured at sub-second temporal resolutions. Extensive effort was dedicated to identifying and curating suitable imagery training data representing varying environments and scene settings with and without flame features to maximize generalization in nuclear power plant environments. The data collection effort resulted in the aggregation of a large, labeled image library exceeding 12,000 images to support model training for diverse industrial environments. A deep neural network model incorporating parallel multi-scale capabilities was developed and trained to support accurate image-based detection of flame incidents of varying sizes and spectral feature properties within heterogeneous scenes. Analysis results show that the trained model can achieve high inference accuracy despite heterogeneous scene environments and components. Testing accuracy exceeded 95.0 percent with very low false positive and false negative inferences.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A multi-MeV alpha particle source via proton-boron fusion driven by a 10-GW tabletop laser

Nuclear fusion between protons and boron-11 nuclei has undergone a revival of interest thanks to the rapid progress in pulsed laser technology. Potential applications of such reaction range from controlled nuclear fusion to radiobiology and cancer therapy. A laser-driven fusion approach consists in the interaction of high-power, high-intensity pulses with H- and B-rich targets. We report on an experiment exploiting proton-boron fusion in CN-BN targets to obtain high-energy alpha particle beams (up to 5 MeV) using a very compact approach and a tabletop laser system with a peak power of ~10 GW, which can operate at high-repetition rate (up to 1 kHz). The secondary resonance in the cross section of proton-boron fusion (~150 keV in the center-of-mass frame) is exploited using a laser-based approach. The generated alpha particles are characterized in terms of energy, flux, and angular distribution using solid-state nuclear-track detectors, demonstrating a flux of ~10 5 particles per second at 10 Hz, and ~10 6 per second at 1 kHz. Hydrodynamic and particle-in-cell numerical simulations support our experimental findings. Potential impact of our approach on future spread of ultra-compact, multi-MeV alpha particle sources driven by moderate intensity (10 16 -10 17 W/cm 2 ) laser pulses is anticipated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Are long-term climate projections useful for on-farm adaptation decisions?

The current literature on climate services for farmers predominantly focuses on seasonal forecasts, with an assumption that longer-term climate projections may not be suitable for informing farming decisions. In this paper, we explore whether certain types of long-term climate projections may be useful for some specific types of farming decisions. Through interviews with almond tree crop farmers and farm advisors in California, we examine how farmers perceive the utility and accuracy levels of long-term climate projections and identify the types of projections that they may find useful. The interviews revealed that farmers often perceive long-term climate projections as an extension of weather forecasts, which can lead to their initial skepticism of the utility of such information. However, we also found that when farmers were presented with long-term trends or shifts in crop-specific agroclimatic metrics (such as chill hours or summer heat), they immediately perceived these as valuable for their decision-making. Hence, the manner in which long-term projections are framed, presented, and discussed with farmers can heavily influence their perception of the potential utility of such projections. The iterative conversations as part of the exploratory interview questions, served as a tool for “ joint construction of meaning” of complex and ambiguous terms such as “long-term climate projections,” “long-term decisions” and “uncertainty.” This in-turn supported a joint identification (and understanding) of the types of information that can potentially be useful for on-farm adaptive decisions, where the farmer and the interviewer both improvise and iterate to find the best types of projections that fit specific decision-contexts. Overall, this research identifies both the types of long-term climate information that farmers may consider useful, and the engagement processes that are able to effectively elicit farmers' long-term information needs.

Jagannathan, Kripa↗

Baylor University Campus-Wide Deep Dive

In January 2020, staff members from the Engagement and Performance Operations Center (EPOC) and the Lonestar Education And Research Network (LEARN) met with researchers and staff at Baylor University for the purpose of a Campus-Wide Deep Dive into research drivers. The goal of this meeting was to help characterize the requirements for five campus research use cases and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support. Profiled scientific use cases included: - Experimental High Energy Physics (HEP) - Proton Computed Tomography (pCT) - Nutrition and Relation to Digestive Microbiome - Baylor University Core Research Facilities - Molecular Quantum-dot Cellular Automata (QCA), and Material Science of Quantum Computing - Modeling and Simulation of Low-Dimensional and Nano-Structured Materials - Computational Fluid Dynamics Material for this event included the written documentation from each of the research areas at Baylor University, documentation about the current state of technology support, and a write-up of the discussion that took place in person. The Case Studies highlighted the ongoing challenges that Baylor University has in supporting a cross-section of established and emerging research use cases. Each Case Study mentioned unique challenges which were summarized into common needs. These included: - Tradeoffs for network/software security, and usability of the resulting infrastructure. Better communication to set expectations and understand realities is required. - Computation use on campus is widespread and healthy. While no major problems were uncovered, upgrades to maintain current usage patterns and encourage growth will be required. - Storage is a critical need for enterprise use cases and research. In particular, a campus wide ‘storage architecture’ to support research use cases (e.g. instruments, data sharing) is required in the 2-5 year time window. - Instrumentation on campus is healthy and expanding. Technology must scale with this in the form of computation and storage. - Working with LEARN to upgrade network capacity (in multiples of 10G, or upgrades to 100G) will be required in the 1-3 year time frame. - Network monitoring and visibility will help to establish external science use cases. - Data sharing via portal systems is not currently a critical need, but growing in scope. EPOC can assist Baylor with options.

99 GENERAL AND MISCELLANEOUS↗

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing

Abstract Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we establish a common reference frame for computations in digital neuromorphic systems, titled Neuromorphic Intermediate Representation (NIR). NIR defines a set of computational and composable model primitives as hybrid systems combining continuous-time dynamics and discrete events. By abstracting away assumptions around discretization and hardware constraints, NIR faithfully captures the computational model, while bridging differences between the evaluated implementation and the underlying mathematical formalism. NIR supports an unprecedented number of neuromorphic systems, which we demonstrate by reproducing three spiking neural network models of different complexity across 7 neuromorphic simulators and 4 digital hardware platforms. NIR decouples the development of neuromorphic hardware and software, enabling interoperability between platforms and improving accessibility to multiple neuromorphic technologies. We believe that NIR is a key next step in brain-inspired hardware-software co-evolution, enabling research towards the implementation of energy efficient computational principles of nervous systems. NIR is available atneuroir.org

Science & Technology - Other Topics↗

ML-based Real-Time Control at the Edge: An Approach Using hls4ml

This study focuses on implementing a real-time control system for a particle accelerator facility that performs high energy physics experiments. A critical operating parameter in this facility is beam loss, which is the fraction of particles deviating from the accelerated proton beam into a cascade of secondary particles. Accelerators employ a large number of sensors to monitor beam loss. The data from these sensors is monitored by human operators who predict the relative contribution of different sub-systems to the beam loss. Using this information, they engage control interventions. In this paper, we present a controller to track this phenomenon in real-time using edge-Machine Learning (ML) and support control with low latency and high accuracy. We implemented this system on an Intel Arria 10 SoC. Optimizations at the algorithm, high-level synthesis, and interface levels to improve latency and resource usage are presented. Our design implements a neural network, which can predict the main source of beam loss (between two possible causes) at speeds up to 575 frames per second (fps) (average latency of 1.74 ms). The practical deployed system is required to operate at 320 fps, with a 3ms latency requirement, which has been met by our design successfully.

Shi, R.↗

Single-Bar SMT Creep-Fatigue Testing on Alloy 617 with Software Controls on elastic Follow-Up Feedback in Support of New Creep-Fatigue Design Methodology

The Simplified Model Test (SMT) is one of the alternative ways to calculate the creep-fatigue damage of elevated temperature components. The SMT approach unifies the creep and fatigue damage, simplifying the damage calculation process with improved accuracy. Traditionally, SMT tests has have been conducted through the two bars: first is the driver bar and second is the test bar. The driver bar stays elastic and imposes the confinement to the second bar. This experimental procedure requires two test frames and a large test specimen, which limits the test parameter range and accessibility of this testing procedures. Hence, a single-bar SMT (SB-SMT) tests has been developed to simplify complexity in SMT experiment setup. The software-controlled SB-SMT test process has been introduced which completely replaces the driver bar. This paper discusses the single-bar SMT (SB-SMT) test procedure with software controls. The challenges and critical parameters in the software-controlled SB-SMT procedure are addresses addressed and recommendations are provided. A scoping test with a set of wider strain range, elastic follow-ups and dwell time validated the proposed test procedure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Control Oriented Models for Co-Design: Technical Overview of MT HVDC, MVDC, and Solid State Transformer Building Blocks

The electric power system is shifting toward a power electronics–enabled grid, where converter based “building blocks” (e.g., high voltage direct current (HVDC) links, multi terminal HVDC (MT HVDC) networks, medium voltage DC (MVDC) links, and solid state transformers (SSTs)) provide fast, precise control of power flows, voltage, and frequency. This report develops and applies publicly shareable electromagnetic transient (EMT) and phasor models to examine how such building blocks can be composed and coordinated to support offshore wind integration, inter area transfers, feeder support, and resilience. Section 2 documents a modular multilevel converter (MMC)–based MT HVDC modeling framework and two use cases: a compact WSCC/IEEE 9 bus test system and a 240 bus “mini WECC” case with five offshore wind plants (OWFs). Phasor to EMT transfer, initialization, and sanity checks are summarized, and neutral demonstrations of normal and contingency operation are reported. Section 3 frames the problem of wind plant inertial frequency response (IFR): shaping energy release and recovery to improve nadir while avoiding aerodynamic stall; representative simulations illustrate the issues without disclosing proprietary control. Section 4 develops MVDC concepts through an IEEE 16 bus loop and an Olympic Peninsula case study that compares AC vs. MVDC corridors and shows how feeder headroom can be pooled via DC couplers. Section 5 surveys SST architectures and identifies a gap: scalable, communication free coordination of multiple SSTs for islanded feeder networks. Across the report, novel methods and configurations under separate publication and IP review are not disclosed; only topic oriented, replicable setups and non proprietary results are shown. These models and use cases are intended as foundations for future publications and co design studies on architecture, control, and coordination of PE enabled grids.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Crystal structure and shape selection in the growth of 3D metallic crystallites on layered materials: Fe on MoS 2

Nucleation and growth of supported 3D metal clusters or crystallites during deposition on MoS 2 , or on other weakly-adhering layered materials, can potentially produce diverse growth shapes, and even crystal structures differing from the bulk metal. For Fe deposition on MoS 2 , SEM and AFM observations reveal three distinct crystallite shapes. By comparison with atomistic structure models incorporating realistic Fe-MoS 2 interface structures, here we conclude that these are: triangular fcc(111) pyramids with sloped {100} side facets; bcc(110) A-frame tents with sloped {100} side facets; and bcc(110) mesas with vertical {100} and {110} side facets. The following picture is proposed for the competitive formation of clusters and crystallites with different structures: (i) small nanoclusters formed at the onset of deposition exhibit facile fluxional dynamics allowing sampling of different crystal structures and shapes; (ii) sufficient fluxionality implies a Boltzmann distribution of sampled structures, and thus coexistence of different structures follows from the demonstrated similar energies for those structures; (iii) growing clusters reach a threshold size above which the characteristic time scale for restructuring exceeds that for cluster growth. Thereafter, clusters are locked-in to a specific crystal structure and shape as revealed by imaging of larger crystallites. Despite a penalty for fcc(111) over bcc(111) pyramids based on bulk energetics, favorable surface and interface energies makes them preferable for smaller sizes.

36 MATERIALS SCIENCE↗

Preparing For Advanced Air Mobility: A System-Level Framework For Infrastructure, Investment, and Deployment

Advanced air mobility (AAM) is moving from demonstration toward early deployment, supported by a growing national strategy that outlines how these systems may evolve across airspace, infrastructure, and operations. As this transition takes shape, a more practical question comes into focus: what does it mean to be ready? This paper introduces a Capability Maturity Model (CMM) as a structured way to think about that challenge. Rather than treating readiness as a fixed condition, it frames it as a progression - one that develops across multiple, interdependent domains over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multiscale analysis of large twist ferroelectricity and swirling dislocations in bilayer hexagonal boron nitride

With its atomically thin structure and intrinsic ferroelectric properties, heterodeformed bilayer hexagonal boron nitride (hBN) has gained prominence in next-generation non-volatile memory applications. However, studies to date have focused almost exclusively on small-twist bilayer hBN, leaving the question of whether ferroelectricity can persist under small heterostrain and large heterodeformation entirely unexplored. In this work, we establish the crystallographic origin of ferroelectricity in bilayer hBN configurations heterodeformed relative to high-symmetry configurations such as AA-stacking and 21.786789° twisted configurations (Σ7), using Smith normal form bicrystallography. We then demonstrate out-of-plane ferroelectricity in bilayer hBN across configurations vicinal to both the AA and Σ7 stackings. Atomistic simulations reveal that AA-vicinal systems support ferroelectricity under both small twist and small strain, with polarization switching in the latter governed by the deformation of swirling dislocations rather than the straight interface dislocations seen in the former. For Σ7-vicinal systems, where existing interatomic potentials underperform particularly under extreme out-of-plane compression, we develop a density-functional-theory-informed continuum framework—the bicrystallography-informed frame-invariant multiscale (BFIM) model, which captures out-of-plane ferroelectricity in heterodeformed configurations vicinal to Σ7 stacking. Interface dislocations in these large heterodeformed bilayer configurations exhibit markedly smaller Burgers vectors compared to interface dislocations in small-twist and small-strain bilayer hBN. The BFIM model reproduces experimental results and provides a powerful, computationally efficient framework for predicting ferroelectricity in large-unit-cell heterostructures where atomistic simulations are prohibitively expensive.

Ahmed, Md Tusher [Univ. of Illinois at Urbana-Cham↗

Gaia -supported re-discovery of a remarkable weak line quasar from a variability and proper motion survey

We demonstrate that VPMS J170850.95+433223.7 is a weak line quasar (WLQ) which is remarkable in several respects. It was already classified as a probable quasar two decades ago, but with considerable uncertainty. The non-significant proper motion and parallax from the Gaia Early Data Release 3 have solidified this assumption. Based on previously unpublished spectra, we show that VPMS J170850.95+433223.7 is a WLQ at z = 2.345 with immeasurably faint broad emission lines in the rest-frame ultraviolet. A preliminary estimate suggests that it hosts a supermassive black hole of ~10 9 M ⊙ accreting close to the Eddington limit, perhaps at the super-Eddington level. We identify two absorber systems with blueward velocity offsets of 0.05 c and 0.1 c , which could represent high-velocity outflows, which are perhaps related to the high accretion state of the quasar.

79 ASTRONOMY AND ASTROPHYSICS↗

Cross-sectoral impact of emerging technologies on U.S. manufacturing resilience and competitiveness

Introducing new technologies in one energy-intensive industry can affect how other industries operate and stay resilient, yet these cross-sector interactions are often underappreciated in conventional technology roadmaps. In practice, industrial systems do not evolve in isolation. They are linked through shared upstream and downstream dependencies, such as electricity and fuel supply, critical materials, transportation networks, and enabling infrastructure. As a result, large-scale technology deployment in one sector can reshape resource availability, infrastructure demand, and operational risk in others. These interdependencies mean that technology deployment decisions in one sector can create unintended bottlenecks or cascading benefits in others. Here, this article argues that a cross-sector, system-of-systems perspective is essential for evaluating and scaling emerging technologies in energy-intensive industries. By framing industrial transformation as an interconnected systems challenge rather than a set of isolated sectoral decisions, the study highlights how interdependence shapes technology feasibility, adoption pathways, and resilience outcomes. The article illustrates how cross-sector linkages can amplify both risks and benefits, and it emphasizes the importance of integrated planning approaches that account for shared dependencies, cascading impacts, and co-optimization opportunities. Adopting this broader perspective can support more robust technology roadmaps, improve strategic coordination across industries, and strengthen the long-term resilience of the industrial sector as a whole.

Nain, Preeti [Oak Ridge National Laboratory (ORNL)↗

Critical roles of Cu(OH)2 in low-temperature moisture-induced degradation of Cu-SAPO-34 SCR catalyst: Correlating reversible and irreversible deactivation

Cu-SAPO-34 selective catalytic reduction (SCR) catalyst deactivates upon exposure to water vapor at temperatures lower than 100 °C, which deteriorates its application prospects. The deactivation under cycled aging-regeneration conditions can be categorized into two stages, namely reversible and irreversible deactivation. Based on SCR reaction tests, and characterizations with diffuse reflection infrared Fourier transform spectroscopy (DRIFTS), NH3 temperature-programmed desorption (NH3-TPD) and H2 temperature-programmed reduction (H2-TPR), it is concluded that the transformation of SCR active isolated Cu(II) ions to Cu(OH)2 is critical to both types of deactivation. Within the frame of reversible deactivation, Cu(OH)2 is converted back to SCR active Cu(II) ions by interacting with Brønsted acid sites during high-temperature regeneration. However, interactions between Cu(OH)2 and hydrolyzed framework Al lead to the formation of CuAl2O4-like species, causing permanent loss of active Cu(II) ions and thus, irreversible deactivation. The authors from Tsinghua University would like to acknowledge the financial support from projects of China Science and Technology Exchange Centre (No. 2016YFE0126600) and the National Key R&D Program of China (No. 2017YFC0211102). YM also acknowledges Tsinghua Scholarship for Overseas Graduate Studies for a visit to the Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for the US Department of Energy (DOE) under contract DE-AC05-76RL01830. FG is supported by DOE, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office.

Cu-SAPO-34, low-temperature deactivation, reversib↗

GeoMelt{sup R} In-Container Vitrification (ICV){sup TM} for Fukushima Daiichi Water Treatment Secondary Wastes - 20212

The Japanese government is supporting development work implemented jointly by Veolia subsidiaries Kurion Japan, K.K., Veolia Nuclear Solutions (VNS), Inc., and Veolia Nuclear Solutions Federal Services, LLC for treating radioactive waste generated from Fukushima Daiichi Nuclear Power Station (NPS) water treatment using the GeoMelt{sup TM} In-Container Vitrification (ICV){sup TM} technology. The initial work consisted of glass formulation and engineering-scale testing which was completed in 2018, in the frame of an IRID (International Research Institute for Nuclear Decommissioning) program as part of a project subsidized by Japan's Ministry of Economy, Trade and Industry (METI). The Fukushima Daiichi NPS Mid- and Long-Term Road-map requires investigation of methods to stabilize solid wastes (and to immobilize radioisotopes in the wastes) generated as a result of emergency response and decommissioning activities. Cooling water treatment has resulted in a significant amount of solid and slurry secondary wastes (mostly adsorbents and ion-exchange materials) which will require processing at some point. GeoMelt{sup R} ICV{sup TM} is a joule-heated melter technology which uses a refractory-lined single-use container combining the melter and disposal container. There is no pouring required nor concerns with refractory corrosion which allows the process to accommodate a wide range of waste chemistries and high waste loadings. The testing described here consisted of three engineering-scale melts, each processing between 212 kg and 240 kg of waste simulants, glass formers, and non-radioactive cesium (Cs) and strontium (Sr) tracers. Continuous isokinetic stack sampling of off-gas emissions was performed for each test in order to calculate Cs and Sr retention in the glass wasteform. Single-pass retention of Cs in the final glass wasteform ranged from 91.46 to 99.30%, and single-pass retention of Sr ranged from 99.76 to 100%. Planned particulate recycle will increase these retention levels. Melt 1 processed a mixture of KUR-EH (a zeolite-based ion-exchange material), simulated Advanced Liquid Processing System (ALPS) Carbonate and Iron Slurries, and glass additives. Melt 2 processed a mixture of KUR-EH, KUR-TSG (a titanate-based adsorbent), and glass additives. Melt 3 processed a mixture of KUR-EH, simulated barium sulfate/iron ferrocyanide sludge (AREVA sludge), and glass additives. Waste loadings for these melts ranged from 70 weight percent (wt%) to 82 wt%. Vitrification produces a waste form much denser than the stored water treatment secondary waste wastes, resulting in significant volume reduction. Volume reductions for the three tests ranged from 74 to 79 vol%. Vitrification produces a chemically durable wasteform. Pacific Northwest National Laboratory (PNNL) tested three glass samples from each engineering-scale melt) by the Materials Characterization Center 1 (MCC-1) test, an international standard leach test of the chemical durability of nuclear waste glasses. PNNL also obtained one U.S. reference glass (EA Glass) and two Japan reference glasses P0798) and tested these under the same MCC-1 conditions (90 deg. C, 10 m-1, DIW, and 7, 14, 28-day) as the GeoMelt{sup R} ICV{sup TM} glasses. The GeoMelt{sup R} ICV{sup TM} glasses exhibited lower total normalized releases and 14- to 28-day normalized release rates than the three reference glasses. These results suggest that the GeoMelt{sup R} ICV{sup TM} glasses have durabilities on par with high-level waste glasses under standard test conditions. Post-melt process sampling and analysis indicated no Cs migration into the melter refractory materials and very little deposition of Cs or Sr onto the melter hood or off-gas piping internals. The results of the testing indicated good Cs retention in the glass, high volume reduction and waste loadings, and excellent chemical durability. These factors are important to minimize treatment costs and to protect workers and the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗