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A description of the various approaches to the synthesis of the insensitive energetic compound, 2,6-diamino-3,5-dinitropyrazine-1-oxide (LLM-105), developed at LLNL throughout the past 20 years will be described.
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A previous paper reported hugoniot measurements on a two-phase material consisting of a matrix and an embedded material (silica- phenolic) using the LLNL electric gun facility. The results showed a good bit of scatter in the measurements. This was attributed to the grossly heterogeneous nature of the material. Measurements have since been made on a slurry of finely divided tungsten powder in a plastic, greatly reducing the scale of the inhomogeneity. The results show greatly reduced scatter, as expected from the above interpretation.
Historically, surface complexation model (SCM) constants and distribution coefficients (K d ) have been employed to quantify mineral-based retardation effects controlling the fate of metals in subsurface geologic systems. Our recent SCM development workflow, based on the Lawrence Livermore National Laboratory Surface Complexation/Ion Exchange (L-SCIE) database, illustrated a community FAIR data approach to SCM development by predicting uranium(VI)-quartz adsorption for a large number of literature-mined data. Here, we present an alternative hybrid machine learning (ML) approach that shows promise in achieving equivalent high-quality predictions compared to traditional surface complexation models. At its core, the hybrid random forest (RF) ML approach is motivated by the proliferation of incongruent SCMs in the literature that limit their applicability in reactive transport models. Our hybrid ML approach implements PHREEQC-based aqueous speciation calculations; values from these simulations are automatically used as input features for a random forest (RF) algorithm to quantify adsorption and avoid SCM modeling constraints entirely. Named the LLNL Speciation Updated Random Forest (L-SURF) model, this hybrid approach is shown to have applicability to U(VI) sorption cases driven by both ion-exchange and surface complexation, as is shown for quartz and montmorillonite cases. The approach can be applied to reactive transport modeling and may provide an alternative to the costly development of self-consistent SCM reaction databases.
Here, the concept of shortest path and betweenness centrality (BC) is introduced in combustion systems, with its application demonstrated in chemical network analysis and skeletal mechanism generation. After establishing the graphical representation of a chemical network for given pressure, temperature, and species concentrations, a metric BC is defined to rank the shortest paths passed by other nodes between the pair of source and target node, and as such captures the dominant indirect kinetic pathways between any pair of nodes in the network for computational diagnostics. As a result, the controlling pathways are retained by collecting the species with larger BC values. Such a notion then indicates that the index of importance of species could then be assigned based on their BC values to further guide skeletal mechanism generation. Unlike existing methods, the betweenness centrality approach takes into account of both the fluxes between species and their relative positioning within the chemical network. To demonstrate its potential utility to combustion studies, the approach was applied to the GRI-3.0, LLNL and USC-Mech II mechanisms to identify the important pathways in the chemical network at each local reaction state, and develop skeletal mechanisms from all reaction state samples in auto-ignition and perfectly stirred reactor (PSR) simulations. The performance of the BC ranking is compared to the methods of directed relation graph (DRG), DRG with error propagations (DRGEP) and sensitivity analysis (SA), and is shown to possess sufficient utility in producing skeletal mechanisms with good accuracy and flexibility for the cases studied.
The chemical kinetics of n-heptane (n-C 7 H 16 ) – an important reference compound for real fuels – oxidation are well studied at stoichiometric and lean conditions. However, there is only limited information on the n-heptane chemical kinetics in fuel-rich combustion. In order to verify the accuracy of chemical kinetic models at these conditions, the oxidation of rich n-heptane mixtures has been investigated. Combustion of n-C 7 H16/O2/Ar mixtures at equivalence ratios, φ, of 2.0 and 3.0 behind reflected shock waves has been studied at temperatures ranging from 1066 to 1502 K and at pressures ranging from 1.4 to 6.2 atm. Reaction progress was monitored by recording pressure and absorption time-histories of ethylene (C 2 H 4 ) and n-heptane at a location 2 cm from the endwall of a 14-cm inner diameter shock tube. Ethylene and n-heptane absorption time-histories were measured, respectively, using absorption spectroscopy at 10.532 μm from a tunable CO 2 laser and at around 3.4 μm from a continuous wave distributed feedback interband cascade laser (ICL). The measured absorption time-histories were compared with modeled predictions from the Lawrence Livermore National Lab (LLNL) detailed n-heptane reaction mechanism. Overall, to the best of our knowledge, current data are the first time-resolved n-heptane and ethylene concentration measurements conducted in a shock tube at these conditions.
Soot particles and their precursor polycyclic aromatic hydrocarbon (PAH) species, formed during combustion, are responsible for particulate emissions in gasoline direct injection (GDI) engines. To better understand the effects of fuel composition on formation of soot in GDI engines, the pyrolysis of several gasoline surrogates was studied in a jet-stirred reactor across a broad temperature range at atmospheric pressure and 1 s residence time. Fuel and intermediate species, including aromatics up to naphthalene, were measured using gas chromatography (GC). PAH concentrations from pyrolysis of surrogate fuels were compared to gain insight into the effects of fuel composition on PAH formation. In addition, synergistic effects were observed in pyrolysis experiments of binary blends. A detailed kinetic model, recently developed at Lawrence Livermore National Laboratory (LLNL), successfully captured the effects of blending and the concentration of major PAHs. Major reaction pathways are discussed, as well as the role of important intermediate species, such as acetylene, and resonantly stabilized radicals such as allyl, propargyl, cyclopentadienyl, and benzyl in the formation of PAH.
This work utilizes a rapid compression machine (RCM) to experimentally quantify autoignition and preliminary heat release characteristics for blends of 0 to 30% ethanol by volume into two surrogates (FGF-LLNL and FGF-KAUST) that represent a full boiling range gasoline (FACE-F). Experimental conditions cover pressures from 15 to 100 bar, temperatures from 700 to 1000 K, and diluted/stoichiometric and undiluted/lean fuel loading conditions representative of boosted spark-ignition and advanced compression ignition engines, respectively. Direct comparison is made with previously reported results for FACE-F/E0–E30 blends. Here, a detailed gasoline surrogate chemistry model is also proposed, and chemical kinetic modeling is undertaken using the proposed model to generate chemical insights into the compositional effects and ethanol blending effects.
The purpose of this paper is to present the main differences between FREYA versions 1.0 and 2.0.2. FREYA (Fission Reaction Event Yield Algorithm) is a fission event generator which models complete fission events. As such, it automatically includes fluctuations as well as correlations between observables, resulting from conservation of energy and momentum. The main differences between the two versions are: additional fissionable isotopes, angular momentum conservation, Giant Dipole Resonance form factor for the statistical emission of photons, improved treatment of fission photon emission using RIPL database, and dependence on the incident neutron direction. FREYA 2.0.2 has been integrated into the LLNL Fission Library 2.0.2, which has itself been integrated into MCNP6.2, TRIPOLI-4.10, and can be called from Geant4.10.
Experiments were performed at the LLNL Titan laser to measure the propagation direction of the energetic electrons that were generated during the interaction of the polarized laser beam with solid targets in the case of normal incidence. The energetic electrons propagated through vacuum to spectator metal wires in the polarization direction and in the perpendicular direction, and the K shell spectra from the different wire materials were recorded as functions of the distance from the laser focal spot. It was found that the fluence of the energetic electrons driven into the spectator wires in the polarization direction compared to the perpendicular direction was larger and increased with the distance from the focal spot. Finally, this indicates that energetic electrons are preferentially driven in the direction of the intense oscillating electric field of the incident laser beam in agreement with the multiphoton inverse Bremsstrahlung absorption process.
Microscopic fuel fragments, so-called “hot particles”, were released during the 1986 accident at the Chornobyl nuclear powerplant and continue to contaminate the exclusion zone in northern Ukraine. Isotopic analysis can provide vital information about sample origin, history and contamination of the environment, though it has been underutilized due to the destructive nature of most mass spectrometric techniques, and inability to remove isobaric interference. Recent developments have diversified the range of elements that can be investigated through resonance ionization mass spectrometry (RIMS), notably in the fission products. The purpose of this study is to demonstrate the application of multi-element analysis on hot particles as relates to their burnup, particle formation in the accident, and weathering. The particles were analysed with two RIMS instruments: resonant-laser secondary neutral mass spectrometry (rL-SNMS) at the Institute for Radiation Protection and Radioecology (IRS) in Hannover, Germany, and laser ionization of neutrals (LION) at Lawrence Livermore National Laboratory (LLNL) in Livermore, USA. Comparable results across instruments show a range of burnup dependent isotope ratios for U and Pu and Cs, characteristic of RBMK-type reactors. Results for Rb, Ba and Sr show the influence of the environment, retention of Cs in the particles and time passed since fuel discharge.
Here we present a highly scalable, parallel implementation of first-principles electron dynamics coupled with molecular dynamics (MD). By using optimized kernels, network topology aware communication, and by fully distributing all terms in the time-dependent Kohn–Sham equation, we demonstrate unprecedented time to solution for disordered aluminum systems of 2000 atoms (22,000 electrons) and 5400 atoms (59,400 electrons), with wall clock time as low as 7.5 s per MD time step. Despite a significant amount of non-local communication required in every iteration, we achieved excellent strong scaling and sustained performance on the Sequoia Blue Gene/Q supercomputer at LLNL. We obtained up to 59% of the theoretical sustained peak performance on 16,384 nodes and performance of 8.75 Petaflop/s (43% of theoretical peak) on the full 98,304 node machine (1,572,864 cores). Lastly, scalable explicit electron dynamics allows for the study of phenomena beyond the reach of standard first-principles MD, in particular, materials subject to strong or rapid perturbations, such as pulsed electromagnetic radiation, particle irradiation, or strong electric currents.
The effect of rapid laser heating on the response of 7075-T6 aluminum has been characterized using 3-D digital image correlation and a series of thermocouples. The experimental results indicate that as the samples are held under a constant load, the heating from the laser profile causes non-uniform temperature and strain fields, and the strain-rate increases dramatically as the sample nears failure. Simulations have been conducted using the LLNL multi-physics code ALE3D, and compared to the experiments. The strength and failure of the material was modeled using the Johnson–Cook strength and damage models. Here, in order to capture the response, a dual-condition criterion was utilized which calibrated one set of parameters to low temperature quasi-static strain rate data, while the other parameter set is calibrated to high temperature high strain rate data. The thermal effects were captured using temperature dependent thermal constants and invoking thermal transport with conduction, convection, and thermal radiation.
The Generalized Nuclear Data structure (GND) is being designed as a new standard for storing evaluated nuclear data. It is intended as an eventual replacement for the ENDF-6 format, and as such must be capable of handling at a minimum all the types of data supported by ENDF-6, including central values and covariances. Containers for storing covariances in GND are being developed, with the goal of representing covariance data in a simple and concise manner, that is easy to read, understand and use. This paper presents an overview of the status of covariances in GND, and on the tools for generating and using covariance data that are being implemented in LLNL's nuclear data toolkit ‘Fudge’.
New data on the prompt fission neutron spectra (PFNS) from neutron-induced fission with higher accuracies are needed to resolve discrepancies in the literature and to address gaps in the experimental data. The Chi-Nu project, conducted jointly by LANL and LLNL, aims to measure the shape of the PFNS for fission of {sup 239}Pu induced by neutrons from 0.5 to 20 MeV with accuracies of 3–5% in the outgoing energy from 0.1 to 9 MeV and 15% from 9 to 12 MeV and to provide detailed experimental uncertainties. Neutrons from the WNR/LANSCE neutron source are being used to induce fission in a Parallel-Plate Avalanche Counter (PPAC). Two arrays of neutron detectors are used to cover the energy range of neutrons emitted promptly in the fission process. Challenges for the present experiment include background reduction, use of {sup 239}Pu in a PPAC, and understanding neutron detector response. Achieving the target accuracies requires the understanding of many systematic uncertainties. The status and plans for the future will be presented.
The Chi-Nu project, conducted jointly by LANL and LLNL, aims to measure the shape of the prompt fission neutron spectrum (PFNS) for fission of {sup 239}Pu induced by neutrons from 50 keV to 15 MeV with accuracies of 3–5% in the outgoing energy from 50 keV to 9 MeV and 15% from 9 to 15 MeV. In order to meet this goal, detailed Monte Carlo simulations are being used to assess the importance and effect of every component in the experimental configuration. As part of this effort, we have also simulated some past PFNS measurements to identify possible sources of systematic error. We find that multiple scattering plays an important role in the target geometry, collimators, and detector response and that past experiments probably underestimated the extent of this effect.