The Sandia Data Archive (SDA) format is a specific implementation of the HDF5 (Hierarchal Data Format version 5) standard. The format was developed for storing data in a universally accessible manner. SDA files may contain one or more data records, each associated with a distinct text label. Primitive records provide basic data storage, while compound records support more elaborate grouping. External records allow text/binary files to be carried inside an archive and later recovered. This report documents version 1.0 of the SDA standard. The information provided here is sufficient for reading from and writing to an archive. Although the format was original designed for use in MATLAB, broader use is encouraged.
Overview: A Pu shot scheduled for July 17 on the Z machine at SNL was cancelled this past summer. The LiF windows on the Pu targets were cracked during assembly because of configuration changes. Sandia management concluded that continuing with this experiment would present an unacceptable level of risk to the facility and possibly to the workers. In this report, we document the events that occurred which led to this decision and also present some lessons learned and plans and procedures put in place to reduce the likelihood of another such occurrence. The changes and this memorandum reflect the thinking of subject matter experts at both LANL and SNL. These changes represent significant improvements in both communication protocols and quality of the hardware assemblies.
Team Sandia California (Team H) used the Sandia code SIERRA Solid Mechanics: Implicit (SIERRA SM) to model the SFC2 challenge problem. SIERRA SM is a Lagrangian, three-dimensional, implicit code for the analysis of solids and structures. It contains a versatile library of continuum and structural elements, and an extensive library of material models. For all SFC2 related simulations, our team used Q1P0, 8 node hexahedral elements with element side lengths on the order 0.175 mm in failure regions. To model crack initiation and failure, element death removed elements from the simulation according to a continuum damage model. SIERRA SM’s implicit dynamics, implemented with an HHT time integration scheme for numerical damping [1], was used to model the unstable failure modes of the models. We chose SIERRA SM’s isotropic Elasto Viscoplastic material model for our simulations because it contains most of the physics required to accurately model the SFC2 challenge problem such as the flexibility to include temperature and rate dependence for a material.
Incorrect computer hardware behavior may corrupt intermediate computations in numerical algorithms, possibly resulting in incorrect answers. Prior work models misbehaving hardware by randomly flipping bits in memory. We start by accepting this premise, and present an analytic model for the error introduced by a bit flip in an IEEE 754 floating-point number. We then relate this finding to the linear algebra concepts of normalization and matrix equilibration. In particular, we present a case study illustrating that normalizing both vector inputs of a dot product minimizes the probability of a single bit flip causing a large error in the dot product's result. Moreover, the absolute error is either less than one or very large, which allows detection of large errors. Then, we apply this to the GMRES iterative solver. We count all possible errors that can be introduced through faults in arithmetic in the computationally intensive orthogonalization phase of GMRES, and show that when the matrix is equilibrated, the absolute error is bounded above by one.
We find for infrared wavelengths that there are broad ranges of particle sizes and refractive indices that represent fog and rain, where circular polarization can persist to longer ranges than linear polarization. Using polarization tracking Monte Carlo simulations for varying particle size, wavelength, and refractive index, we show that, for specific scene parameters, circular polarization outperforms linear polarization in maintaining the illuminating polarization state for large optical depths. This enhancement with circular polarization can be exploited to improve range and target detection in obscurant environments that are important in many critical sensing applications. Initially, researchers employed polarizationdiscriminating schemes, often using linearly polarized active illumination, to further distinguish target signals from the background noise. More recently, researchers have investigated circular polarization as a means to separate signal from noise even more. Specifically, we quantify both linearly and circularly polarized active illumination and show here that circular polarization persists better than linear for radiation fog in the short-wave infrared, for advection fog in the short-wave and long-wave infrared, and large particle sizes of Sahara dust around the 4 μmwavelength. Conversely, we quantify where linear polarization persists better than circular polarization for some limited particle sizes of radiation fog in the long-wave infrared, small particle sizes of Sahara dust for wavelengths of 9-10.5 μm, and large particle sizes of Sahara dust through the 8-11 μm wavelength range in the long-wave infrared.
Some fires may involve fuels that are contaminated with airborne particles such as hazardous chemicals or radioactive materials, and therefore pose a significant health risk by the potential inhalation of the contaminated material. In particular, consider a relatively inert solid material which is sub-micron in size that is suspended in a liquid solvent. Various mechanisms can lead to the solid becoming entrained in the air. First, as a liquid fuel is consumed it typically transitions through a boiling regime. As the vapor bubbles rupture at the liquid surface, the liquid response can result in the formation of film drops (collapsing bubble film) or jet drops (caused by liquid rapidly filling the vapor void). Surface wave action can also result in bubble formation and entrainment as the bubbles collapse. This mechanism is generally a function of wind speed and fluid properties. Also, mass may be entrained from a residual layer formed after consumption of the fuel. This paper reviews the existing literature on these entrainment mechanisms. Based on data from the review, the results from a Lagrangian/Eulerian coupled computational transport code are compared to some existing data on the entrainment of contaminants from liquid fuel fires. Since the multi-phase mechanistic prediction of the entrainment is not mature, the methods employ coupling of correlation data to the computational fluid dynamics (CFD) code.
We present simulation results that show circularly polarized light persists through scattering environments better than linearly polarized light. Specifically, we show persistence is enhanced through many scattering events in an environment with a size parameter representative of advection fog at infrared wavelengths. Utilizing polarization tracking Monte Carlo simulations we show a larger persistence benefit for circular polarization versus linear polarization for both forward and backscattered photons. We show the evolution of the incident polarization states after various scattering events which highlight the mechanism leading to circular polarization's superior persistence.
SNL has developed a series of ionic-liquid electrolytes with accompanying non- Aqueous compatible membranes and flow cell designs for improved energy density redox flow batteries targeted to support increasing demands for stationary energy storage. The new electrolytes yield a higher energy density by chemically incorporating an electro- Active transition metal element into the solvent's molecular formula. Although ionic liquids have higher viscosities than conventional non- Aqueous electrolytes, they are promising for higher energy densities due to higher metal concentrations and wider voltage windows. We have addressed high viscosity by developing new materials through careful ligand and anion selection. We have also developed tunable membranes for non- Aqueous compatibility and rapid laboratory-scale prototyping to quickly screen materials and cell designs. We are projecting a four-fold improvement in energy density over the next two years.
The move towards extreme-scale computing platforms challenges scientific simulations in many ways. Given the recent tendencies in computer architecture development, one needs to reformulate legacy codes in order to cope with large amounts of communication, system faults, and requirements of low-memory usage per core. In this work, we develop a novel framework for solving PDEs via domain decomposition that reformulates the solution as a state of knowledge with a probabilistic interpretation. Such reformulation allows resiliency with respect to potential faults without having to apply fault detection, avoids unnecessary communication, and is generally well-suited for rigorous uncertainty quantification studies that target improvements of predictive fidelity of scientific models. We demonstrate our algorithm for one-dimensional PDE examples where artificial faults have been implemented as bit flips in the binary representation of subdomain solutions.
Some fires may involve fuels that are contaminated with airborne particles such as hazardous chemicals or radioactive materials, and therefore pose a significant health risk by the potential inhalation of the contaminated material. In particular, consider a relatively inert solid material which is sub-micron in size that is suspended in a liquid solvent. Various mechanisms can lead to the solid becoming entrained in the air. First, as a liquid fuel is consumed it typically transitions through a boiling regime. As the vapor bubbles rupture at the liquid surface, the liquid response can result in the formation of film drops (collapsing bubble film) or jet drops (caused by liquid rapidly filling the vapor void). Surface wave action can also result in bubble formation and entrainment as the bubbles collapse. This mechanism is generally a function of wind speed and fluid properties. Also, mass may be entrained from a residual layer formed after consumption of the fuel. This paper reviews the existing literature on these entrainment mechanisms. Based on data from the review, the results from a Lagrangian/Eulerian coupled computational transport code are compared to some existing data on the entrainment of contaminants from liquid fuel fires. Since the multi-phase mechanistic prediction of the entrainment is not mature, the methods employ coupling of correlation data to the computational fluid dynamics (CFD) code.
Aerosol release in the range of less than 10 μm is of concern in transportation accident situations, particularly those involving radioactive contaminants and fuel fires. An accurate approximation of the Airborne Release Fraction (ARF) is important to properly estimate the impact of the contaminant release to the environment and surrounding population. An experiment was selected which studied contaminant entrainment in a fire and contained enough data sufficiently well presented to simulate with existing computational fluid dynamics (CFD) tools. Work was enabled by utilizing source terms for similar physical systems as presented in other publications. It is possible to investigate physical sensitivities from this model, giving insight into the experimental behavior, and physical processes. The effort also helps prioritize model development in the interest in furthering this predictive capability. Four mechanisms were identified as contributing to contaminant entrainment. Two of these mechanisms, entrainment due to evaporation induction and boiling atomization, were the focus of this study. Parameters, including boiling regime duration, evaporation regime particle size and turbulence, were varied because of their numeric uncertainty, while others like particle injection location, simulation time, and fuel height were varied based on a presumed importance. Entrainment values, as collected downstream of a release, are dependent on the magnitude of the entrainment mechanism, in which boiling far exceeded evaporation in quantity of entrained mass.
Visible light laser voltage probing (LVP) for improved backside optical spatial resolution is demonstrated on ultrathinned bulk Si samples. A prototype system for data acquisition, a method to produce ultra-thinned bulk samples as well as LVP signal, imaging, and waveform acquisition are described on bulk Si devices. Spatial resolution and signal comparison with conventional, infrared LVP analysis is discussed.
Anion receptors that bind strongly to fluoride anions in organic solvents can help dissolve the lithium fluoride discharge products of primary carbon monofluoride (CFx) batteries, thereby preventing the clogging of cathode surfaces and improving ion conductivity. The receptors are also potentially beneficial to rechargeable lithium ion and lithium air batteries.We apply Density Functional Theory (DFT) to show that an oxalate-based pentafluorophenyl-boron anion receptor binds as strongly, or more strongly, to fluoride anions than many phenyl-boron anion receptors proposed in the literature. Experimental data shows marked improvement in electrolyte conductivity when this oxalate anion receptor is present. The receptor is sufficiently electrophilic that organic solvent molecules compete with F- for boron-site binding, and specific solvent effects must be considered when predicting its F- affinity. To further illustrate the last point, we also perform computational studies on a geometrically constrained boron ester that exhibits much stronger gas-phase affinity for both F- and organic solvent molecules. After accounting for specific solvent effects, however, its net F- affinity is about the same as the simple oxalate-based anion receptor. Finally, we propose that LiF dissolution in cyclic carbonate organic solvents, in the absence of anion receptors, is due mostly to the formation of ionic aggregates, not isolated F- ions.
Although the high-performance computing (HPC) community increasingly embraces object-oriented programming (OOP), most HPC OOP projects employ the C++ programming language. Until recently, Fortran programmers interested in mining the benefits of OOP had to emulate OOP in Fortran 90/95. The advent of widespread compiler support for Fortran 2003 now facilitates explicitly constructing object-oriented class hierarchies via inheritance and leveraging related class behaviors such as dynamic polymorphism. Although C++ allows a class to inherit from multiple parent classes, Fortran and several other OOP languages restrict or prohibit explicit multiple inheritance relationships in order to circumvent several pitfalls associated with them. Nonetheless, what appears as an intrinsic feature in one language can be modeled as a user-constructed design pattern in another language. The present paper demonstrates how to apply the facade structural design pattern to support a multiple inheritance class relationship in Fortran 2003. The design unleashes the power of the associated class relationships for modeling complicated data structures yet avoids the ambiguities that plague some multiple inheritance scenarios.
Quantum tomography is used to characterize quantum operations implemented in quantum information processing (QIP) hardware. Traditionally, state tomography has been used to characterize the quantum state prepared in an initialization procedure, while quantum process tomography is used to characterize dynamical operations on a QIP system. As such, tomography is critical to the development of QIP hardware (since it is necessary both for debugging and validating as-built devices, and its results are used to influence the next generation of devices). But tomography suffers from several critical drawbacks. In this report, we present new research that resolves several of these flaws. We describe a new form of tomography called gate set tomography (GST), which unifies state and process tomography, avoids prior methods critical reliance on precalibrated operations that are not generally available, and can achieve unprecedented accuracies. We report on theory and experimental development of adaptive tomography protocols that achieve far higher fidelity in state reconstruction than non-adaptive methods. Finally, we present a new theoretical and experimental analysis of process tomography on multispin systems, and demonstrate how to more effectively detect and characterize quantum noise using carefully tailored ensembles of input states.
