Publications

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

A MELCOR severe accident nuclear reactor code study of alkaline carbonate cooling to mitigate exvessel molten corium accident is described. This study is a part of a 3-year laboratory directed research and development project funded by Sandia National Laboratories. This study examines a novel method to provide an injectable mitigation system, capitalizing the endothermic decomposition of alkaline carbonate to absorb the decay heat and cool the molten corium resulting from a reactor vessel failure accident. A simplified granular carbonate decomposition model has been developed and has been implemented into a MELCOR input model to simulate the cooling effect of the carbonate in both a spreading experiment and a full plant accident model. The results seem promising to stop corium spreading and delay the severity of the accident by at least one-half day which may be enough for additional accident management to alleviate the situation.

The work presented in this paper applies the MELCOR code developed at Sandia National Laboratories to evaluate the source terms from potential accidents in non-reactor nuclear facilities. The present approach provides an integrated source term approach that would be well-suited for uncertainty analysis and probabilistic risk assessments. MELCOR is used to predict the thermal-hydraulic conditions during fires or explosions that includes a release of radionuclides. The radionuclides are tracked throughout the facility from the initiating event to predict the time-dependent source term to the environment for subsequent dose or consequence evaluations. In this paper, we discuss the MELCOR input model development and the evaluation of the potential source terms from the dominated fire and explosion scenarios for a spent fuel nuclear reprocessing plant.

This report will describe the one test conducted during phase III of the Pipe Overpack Container (POC) test campaign, present preliminary results from these tests, and discuss implications for the Criticality Control Overpack (CCO). The goal of this test was to see if aerosol surrogate material inside the Criticality Control Container (CCC) gets released when the drum lid of the CCO comes off during a thirty-minute long, fully-engulfing, fire test. As expected from POC tests conducted in Phase I and II of this test campaign, the CCO drum lid is ejected about one minute after the drum is exposed to fully-engulfing flames. The remaining pressure inside the drum is high enough to eject the top plywood dunnage a considerable distance from the drum. Subsequently, most of the bottom plywood dunnage supporting the CCC burns off during and after the fire. High pressure buildup inside the CCC and inside two primary containers holding the surrogate powder also results in damage to the filter media of the CCC and the filter-house, thread attachment of the primary canisters. No discernable release of surrogate powder material was detected from the two primary containers when pre- and post-test average mass were compared. However, when the average masses are corrected to account for possible uncertainties in mass measurements, error overlap does not preclude the possibility that some surrogate powder mass may have been lost from these primary canisters. Still, post-test conditions of the secondary canisters enclosing these two primary canisters suggest it is very unlikely this mass loss would have escaped into the CCC.

Heterogeneous Integration (HI) may enable optoelectronic transceivers for short-range and long-range radio frequency (RF) photonic interconnect using wavelength-division multiplexing (WDM) to aggregate signals, provide galvanic isolation, and reduce crosstalk and interference. Integration of silicon Complementary Metal-Oxide-Semiconductor (CMOS) electronics with InGaAsP compound semiconductor photonics provides the potential for high-performance microsystems that combine complex electronic functions with optoelectronic capabilities from rich bandgap engineering opportunities, and intimate integration allows short interconnects for lower power and latency. The dominant pure-play foundry model plus the differences in materials and processes between these technologies dictate separate fabrication of the devices followed by integration of individual die, presenting unique challenges in die preparation, metallization, and bumping, especially as interconnect densities increase. In this paper, we describe progress towards realizing an S-band WDM RF photonic link combining 180 nm silicon CMOS electronics with InGaAsP integrated optoelectronics, using HI processes and approaches that scale into microwave and millimeter-wave frequencies.

Although popular in industry, state-chart notations with ‘run to completion’ semantics lack formal refinement and rigorous verification methods. State-chart models are typically used to design complex control systems that respond to environmental triggers with a sequential process. The model is usually constructed at a concrete level and verified and validated using animation techniques relying on human judgement. Event-B, on the other hand, is based on refinement from an initial abstraction and is designed to make formal verification by automatic theorem provers feasible. We introduce a notion of refinement into a ‘run to completion’ statechart modelling notation, and leverage Event-B ’s tool support for theorem proving. We describe the difficulties in translating ‘run to completion’ semantics into Event-B refinements and suggest a solution. We illustrate our approach and show how critical (e.g. safety) invariant properties can be verified by proof despite the reactive nature of the system. We also show how behavioural aspects of the system can be verified by testing the expected reactions using a temporal logic model checking approach.

Estimation of the uncertainty in a critical experiment attributable to uncertainties in the measured experiment temperature is done by calculating the variation of the eigenvalue of a benchmark configuration as a function of temperature. In the low-enriched water-moderated critical experiments performed at Sandia, this is done by 1) estimating the effects of changing the water temperature while holding the UO₂ fuel temperature constant, 2) estimating the effects of changing the UO₂ temperature while holding the water temperature constant, and 3) combining the two results. This assumes that the two effects are separable. The results of such an analysis are nonintuitive and need experimental verification. Critical experiments are being planned at Sandia National Laboratories (Sandia) to measure the effect of temperature on critical systems and will serve to test the methods used in estimating the temperature effects in critical experiments.

Wear prediction is important in designing reliable machinery for slurry industry. It usually relies on multi-phase computational fluid dynamics, which is accurate but computationally expensive. Each run of the simulations can take hours or days even on a high-performance computing platform. The high computational cost prohibits a large number of simulations in the process of design optimization. In contrast to physics-based simulations, data-driven approaches such as machine learning are capable of providing accurate wear predictions at a small fraction of computational costs, if the models are trained properly. In this paper, a recently developed WearGP framework [1] is extended to predict the global wear quantities of interest by constructing Gaussian process surrogates. The effects of different operating conditions are investigated. The advantages of the WearGP framework are demonstrated by its high accuracy and low computational cost in predicting wear rates.

Bayesian optimization (BO) is an efficient and flexible global optimization framework that is applicable to a very wide range of engineering applications. To leverage the capability of the classical BO, many extensions, including multi-objective, multi-fidelity, parallelization, and latent-variable modeling, have been proposed to address the limitations of the classical BO framework. In this work, we propose a novel multi-objective (MO) extension, called srMOBO-3GP, to solve the MO optimization problems in a sequential setting. Three different Gaussian processes (GPs) are stacked together, where each of the GP is assigned with a different task: the first GP is used to approximate a single-objective computed from the MO definition, the second GP is used to learn the unknown constraints, and the third GP is used to learn the uncertain Pareto frontier. At each iteration, a MO augmented Tchebycheff function converting MO to single-objective is adopted and extended with a regularized ridge term, where the regularization is introduced to smooth the single-objective function. Finally, we couple the third GP along with the classical BO framework to explore the richness and diversity of the Pareto frontier by the exploitation and exploration acquisition function. The proposed framework is demonstrated using several numerical benchmark functions, as well as a thermomechanical finite element model for flip-chip package design optimization.

Abstract not provided.

Abstract not provided.

Estimation of the uncertainty in a critical experiment attributable to uncertainties in the measured experiment temperature is done by calculating the variation of the eigenvalue of a benchmark configuration as a function of temperature. In the low-enriched water-moderated critical experiments performed at Sandia, this is done by 1) estimating the effects of changing the water temperature while holding the UO₂ fuel temperature constant, 2) estimating the effects of changing the UO₂ temperature while holding the water temperature constant, and 3) combining the two results. This assumes that the two effects are separable. The results of such an analysis are nonintuitive and need experimental verification. Critical experiments are being planned at Sandia National Laboratories (Sandia) to measure the effect of temperature on critical systems and will serve to test the methods used in estimating the temperature effects in critical experiments.

Abstract not provided.

Recent advances in horizontal cask designs for commercial spent nuclear fuel have significantly increased maximum thermal loading. This is due in part to greater efficiency in internal conduction pathways. Carefully measured data sets generated from testing of full-sized casks or smaller cask analogs are widely recognized as vital for validating thermal-hydraulic models of these storage cask designs. While several testing programs have been previously conducted, these earlier validation studies did not integrate all the physics or components important in a modern, horizontal dry cask system. The purpose of this investigation is to produce data sets that can be used to benchmark the codes and best practices presently used to calculate cladding temperatures and induced cooling air flows in modern, horizontal dry storage systems. The horizontal dry cask simulator (HDCS) has been designed to generate this benchmark data and complement the existing knowledge base. Transverse and axial temperature profiles along with induced-cooling air flow are measured using various backfills of gases for a wide range of decay powers and canister pressures. The data from the HDCS tests will be used to host a blind model validation effort.

The initial product specification' for the H12 Universal Cartridge Carrier (UUC) was released in October 1952 and is the twelfth piece of H-Gear (sequentially numbered) ever developed. It is the oldest piece of H-Gear currently in use. To gain perspective on the number of H-Gear since designed, the most currently developed and deployed H-Gear is the H1768, Inspection Stand. The UUC, (commonly referred to as just the "H12") has since been renamed to the H12 Adjustable Hand Truck. It was developed to support various maintenance operations for ordnance assembly and disassembly. This paper will provide evidence (where available) for the H12s current state of reliability, maintainability, and sustainability (RMA). Where documented evidence is not available, conclusions will be drawn based on its continued effective use over the past 67-years of service.

The Sodium Chemistry (NAC) package in MELCOR has been developed to enhance application to sodium cooled fast reactors. The models in the NAC package have been assessed through benchmark analyses. The F7-1 pool fire experimental analysis is conducted within the framework of the U.S.-Japan collaboration; Civil Nuclear Energy Research and Development Working Group. This study assesses the capability of the pool fire model in MELCOR and provides recommendations for future model improvements because the physics of sodium pool fire are complex. Based on the preliminary results, analytical conditions, such as heat transfer on the floor catch pan are modified. The current MELCOR analysis yields lower values than the experimental data in pool combustion rate and pool, catch pan, and gas temperature during early time. The current treatment of heat transfer for the catch pan is the primary cause of the difference in the results from the experimental data. After sodium discharge stopping, the pool combustion rate and temperature become higher than experimental data. This is caused by absence of a model for pool fire suppression due to the oxide layer buildup on the pool surface. Based on these results, recommendations for future works are needed, such as heat transfer modification in terms of the catch pan and consideration of the effects of the oxide layer for both the MELCOR input model and pool physic.

Statechart notations with ‘run to completion’ semantics, are popular with engineers for designing controllers that respond to events in the environment with a sequence of state transitions. However, they lack formal refinement and rigorous verification methods., on the other hand, is based on refinement from an initial abstraction and is designed to make formal verification by automatic theorem provers feasible. We introduce a notion of refinement into a ‘run to completion’ statechart modelling notation, and leveragetool support for theorem proving. We describe the difficulties in translating ‘run to completion’ semantics intorefinements and suggest a solution. We outline how safety and liveness properties could be verified.

Estimation of radionuclide aerosol release to the environment, from fire accident scenarios, are one of the most dominant accident evaluations at the U.S. Department of Energy's (DOE's) nuclear facilities. Of particular interest to safety analysts, is estimating the radionuclide aerosol release, the Source Term (ST), based on aerosol transport from a fire room to a corridor and from the corridor to the environment. However, no existing literature has been found on estimating ST from this multi-room facility configuration. This paper contributes the following to aerosol transport modeling body of work: a validation study on a multiroom fire experiment (this includes a code-to-code comparison between MELCOR and Consolidated Fire and Smoke Transport, a specialized fire code without radionuclide transport capabilities), a sensitivity study to provide insight on the effect of smoke on ST, and a sensitivity study on the effect of aerosol entrainment in the atmosphere (puff and continuous rate) on ST.