This document provides a description of the model evaluation protocol (MEP) for pool fires, jet fires, and fireballs involving liquefied natural gas (LNG), refrigerant fluids, and byproducts at LNG facilities. The purpose of the MEP is to provide procedures regarding the assessment of a model's suitability to predict heat flux from fires. Three components, namely, a scientific assessment, model verification, and model validation comprise the MEP. The evaluation of a model satisfying these three components is to be documented in the form of a model evaluation report (MER). Discussion of models for the prediction of fire, detailed information on each of the three MEP components, the MEP procedure regarding new versions of previously approved models, and the format of the model evaluation report (MER) are provided.
The apparent ion temperature and mean velocity of the dense deuterium tritium fuel layer of an inertial confinement fusion target near peak compression have been measured using backscatter neutron spectroscopy. The average isotropic residual kinetic energy of the dense deuterium tritium fuel is estimated using the mean velocity measurement to be ∼103 J across an ensemble of experiments. The apparent ion-temperature measurements from high-implosion velocity experiments are larger than expected from radiation-hydrodynamic simulations and are consistent with enhanced levels of shell decompression. These results suggest that high-mode instabilities may saturate the scaling of implosion performance with the implosion velocity for laser-direct-drive implosions.
We present results from ramp compression experiments on high-purity Zr that show the α→ω, ω→β, as well as reverse β→ω phase transitions. Simulations with a multiphase equation of state and phenomenological kinetic model match the experimental wave profiles well. While the dynamic α→ω transition occurs ∼9GPa above the equilibrium phase boundary, the ω→β transition occurs within 0.9 GPa of equilibrium. We estimate that the dynamic compression path intersects the equilibrium ω-β line at P=29.2GPa, and T=490K. The thermodynamic path in the interior of the sample lies ∼100K above the isentrope at the point of the ω→β transition. Approximately half of this dissipative temperature rise is due to plastic work, and half is due to the nonequilibrium α→ω transition. The inferred rate of the α→ω transition is several orders of magnitude higher than that measured in dynamic diamond anvil cell (DDAC) experiments in an overlapping pressure range. We discuss a model for the influence of shear stress on the nucleation rate. We find that the shear stress sji has the same effect on the nucleation rate as a pressure increase δP=cϵijsji/(ΔV/V), where c is a geometric constant ∼1 and ϵij are the transformation shear strains. The small fractional volume change ΔV/V≈0.1 at the α→ω transition amplifies the effect of shear stress, and we estimate that for this case δP is in the range of several GPa. Correcting our transition rate to a hydrostatic rate brings it approximately into line with the DDAC results, suggesting that shear stress plays a significant role in the transformation rate.
Data is a valuable commodity, and it is often dispersed over multiple entities. Sharing data or models created from the data is not simple due to concerns regarding security, privacy, ownership, and model inversion. This limitation in sharing can hinder model training and development. Federated learning can enable data or model sharing across multiple entities that control local data without having to share or exchange the data themselves. Differential privacy is a conceptual framework that brings strong mathematical guarantee for privacy protection and helps provide a quantifiable privacy guarantee to any data or models shared. The concepts of federated learning and differential privacy are introduced along with possible connections. Lastly, some open discussion topics on how federated learning and differential privacy can tied to AI-Enhanced co-design of microelectronics are highlighted.
This document provides a description of the model evaluation protocol (MEP) database for fires involving liquefied natural gas (LNG) and processing fuels at LNG facilities. The purpose of the MEP is to provide procedures regarding the assessment of a model's suitability to predict thermal exclusion zones resulting from a fire. The database includes measurements from pool fire, jet fire, and fireball experiments which are provided in a spreadsheet. Users are to enter model results into the spreadsheet which automatically generates statistical performance measures and graphical comparisons with the experimental data. The intent of this document is to provide a description of the experiments and of the procedure required to carry out the validation portion of the MEP. In addition, the statistical performance measures, measurements for comparisons, and parameter variation are provided.
The following report summarizes the status update during this quarter for the National Nuclear Security Agency (NNSA) initiated Minority Serving Institution Partnership Plan's (MSIPP) projects titled, Indigenous Mutual Partnership to Advanced Cybersecurity Technology (ASPIRE), Indigenous Mutual Partnership to Advanced Cybersecurity Technology (IMPACT) and Partnership for Advanced Manufacturing Education and Research (PAMER).