In this paper we consider the effects of corporate hierarchies on innovation spread across multilayer networks, modeled by an elaborated SIR framework. We show that the addition of management layers can significantly improve spreading processes on both random geometric graphs and empirical corporate networks. Additionally, we show that utilizing a more centralized working relationship network rather than a strict administrative network further increases overall innovation reach. In fact, this more centralized structure in conjunction with management layers is essential to both reaching a plurality of nodes and creating a stable adopted community in the long time horizon. Further, we show that the selection of seed nodes affects the final stability of the adopted community, and while the most influential nodes often produce the highest peak adoption, this is not always the case. In some circumstances, seeding nodes near but not in the highest positions in the graph produces larger peak adoption and more stable long-time adoption.
This paper serves as the Interface Control Document (ICD) for the Seascape automated test harness developed at Sandia National Laboratories. The primary purposes of the Seascape system are: (1) provide a place for accruing large, curated, labeled data sets useful for developing and evaluating detection and classification algorithms (including, but not limited to, supervised machine learning applications) (2) provide an automated structure for specifying, running and generating reports on algorithm performance. Seascape uses GitLab, Nexus, Solr, and Banana, open source codes, together with code written in the Python language, to automatically provision and configure computational nodes, queue up jobs to accomplish algorithms test runs against the stored data sets, gather the results and generate reports which are then stored in the Nexus artifact server.
The credibility of an engineering model is of critical importance in large-scale projects. How concerned should an engineer be when reusing someone else's model when they may not know the author or be familiar with the tools that were used to create it? In this report, the authors advance engineers' capabilities for assessing models through examination of the underlying semantic structure of a model--the ontology. This ontology defines the objects in a model, types of objects, and relationships between them. In this study, two advances in ontology simplification and visualization are discussed and are demonstrated on two systems engineering models. These advances are critical steps toward enabling engineering models to interoperate, as well as assessing models for credibility. For example, results of this research show an 80% reduction in file size and representation size, dramatically improving the throughput of graph algorithms applied to the analysis of these models. Finally, four future problems are outlined in ontology research toward establishing credible models--ontology discovery, ontology matching, ontology alignment, and model assessment.
TEMPI provides a transparent non-contiguous data-handling layer compatible with various MPIs. MPI Datatypes are a powerful abstraction for allowing an MPI implementation to operate on non-contiguous data. CUDA-aware MPI implementations must also manage transfer of such data between the host system and GPU. The non-unique and recursive nature of MPI datatypes mean that providing fast GPU handling is a challenge. The same noncontiguous pattern may be described in a variety of ways, all of which should be treated equivalently by an implementation. This work introduces a novel technique to do this for strided datatypes. Methods for transferring non-contiguous data between the CPU and GPU depends on the properties of the data layout. This work shows that a simple performance model can accurately select the fastest method. Unfortunately, the combination of MPI software and system hardware available may not provide sufficient performance. The contributions of this work are deployed on OLCF Summit through an interposer library which does not require privileged access to the system to use
We present a new pre-processor tool written in Python that creates multicontinuum meshes for PFLOTRAN to simulate two-phase flow and transport in both the fracture and matrix continua. We discuss the multicontinuum modeling approach to simulate potentially mobile water and gas in the fractured volcanic tuffs at Aqueduct Mesa, at the Nevada National Security Site.
The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.
This report consolidates the requirements for an Exceedance Response Action (ERA) Level 1 and ERA Level 2 Action Plan for pH. A discharger’s baseline status for any given parameter changes to Level 1 status if sampling results indicate a Numeric Action Level (NAL) exceedance for that same parameter. NAL exceedance can be either of the following: (1) Instantaneous maximum NAL exceedance: Occurs when two or more analytical results for any single parameter within a reporting year exceed the instantaneous maximum NAL (for example for pH a value less than 6 or a value greater than 9); and (2) Annual NAL exceedance: Occurs when the average of all the analytical results for a parameter within a reporting year exceeds the annual NAL. A Discharger’s Level 1 status for any given parameter changes to Level 2 status if sampling results indicate a Numeric Action Level (NAL) exceedance for the same parameter while a Discharger is in Level 1.
Performing terrain classification with data from heterogeneous imaging modalities is a very challenging problem. The challenge is further compounded by very high spatial resolution. (In this paper we consider very high spatial resolution to be much less than a meter.) At very high resolution many additional complications arise, such as geometric differences in imaging modalities and heightened pixel-by-pixel variability due to inhomogeneity within terrain classes. In this paper we consider the fusion of very high resolution hyperspectral imaging (HSI) and polarimetric synthetic aperture radar (PolSAR) data. We introduce a framework that utilizes the probabilistic feature fusion (PFF) one-class classifier for data fusion and demonstrate the effect of making pixelwise, superpixel, and pixelwise voting (within a superpixel) terrain classification decisions. We show that fusing imaging modality data sets, combined with pixelwise voting within the spatial extent of superpixels, gives a robust terrain classification framework that gives a good balance between quantitative and qualitative results.
Titanium hydride of varying TiH stoichiometry is used in pyrotechnic compositions. In order to yield consistent performance, manufacturing processes must be developed to ensure precise and reproducible material properties, including composition and morphology. Legacy synthesis protocols are not comprehensive nor are the required apparatuses still available. To guide the development of novel production procedures, this report reviews literature on relevant chemical reactions and diffusion events occurring at elevated temperature in the TiH(2-x)/TiOy system. Titanium hydride exposed to air spontaneously forms a passivating oxide layer. Upon heating, significant hydrogen release, which is accompanied by changes to the surface oxide layer, is noted by 375–400°C. At higher temperatures (above about 500°C) the oxide layer is reported to be essentially nonexistent as a result of oxide-layer dissolution processes and, potentially, oxide-layer reduction due to water formation. Based on the reviewed literature, we hypothesize that, by 500°C, the surface layer consists of an oxyhydride phase, which is a solid solution of oxygen in titanium hydride. We believe that hydrogen release from titanium hydride is controlled by the kinetics of molecular hydrogen desorption on the oxyhydride surface. No literature data is available for corresponding activation energies of the dynamic desorption process, and the equilibrium phase diagram of this three-component system remains largely unexplored as well. These gaps in knowledge might be addressed through coordinated computational modeling and experimental efforts.
The U.S. Strategic Petroleum Reserve is a crude oil storage system run by the U.S. Department of Energy. The reserve consists of 60 active storage caverns spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR began executing U.S. congressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 MMB, requires raw water to be used instead of saturated brine for oil withdrawals such as for sales. All sales will produce leaching within the caverns used for oil delivery. Twenty-five caverns had a combined total of over 39 MMB of water injected in CY 20 as part of the Exchange for Storage program; oil was withdrawn in the same manner as for congressionally mandated sales. Leaching effects were monitored in these caverns to understand how the oil withdrawals may impact the long-term integrity of the caverns. While frequent sonars are the best way to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An intermediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code (SANSMIC) . The results indicate that leaching induced features are not of concern in the majority of the caverns, 19 of 25. Six caverns, BH-107, BH-113, BH-114, BM-4, BM-106, and WH-114 have features that may grow with additional leaching and should be monitored as leaching continues in those caverns. Ten caverns had post sale sonars that were compared with SANSMIC results. SANSMIC was able to capture the leaching well , particularly the formation of shelves and flares. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results suggest SANSMIC is a useful tool for monitoring changes in cavern shape due to leaching effects related to sales and exchanges.
Radar is by its basic nature a ranging instrument. If radar range and range-rate measurements from multiple directions can be made and assembled, then multilateration allows locating a feature common to the set of Synthetic Aperture Radar (SAR) images to an accurate 3-D coordinate. The ability to employ effective multilateration algorithms is highly dependent on the geometry of the data collections, and the accuracy with which relative range measurements can be made. The problem can be cast as a least-squares exercise, and the concept of Dilution of Precision can describe the accuracy and precision with which a 3-D location can be made.
Most studies of vortex shedding from a circular cylinder in a gas flow have explicitly or implicitly assumed that the no-slip condition applies on the cylinder surface. To investigate the effect of slip, vortex shedding is simulated using molecular gas dynamics (the direct simulation Monte Carlo method) and computational fluid dynamics (the incompressible Navier-Stokes equations with a slip boundary condition). A Reynolds number of 100, a Mach number of 0.3, and a corresponding Knudsen number of 0.0048 are examined. For these conditions, compressibility effects are small, and periodic laminar vortex shedding is obtained. Slip on the cylinder is varied using combinations of diffuse and specular molecular reflections with accommodation coefficients from zero (maximum slip) to unity (minimum slip). Although unrealistic, bounce-back molecular reflections are also examined because they approximate the no-slip boundary condition (zero slip). The results from both methods are in reasonable agreement. The shedding frequency increases slightly as the accommodation coefficient is decreased, and shedding ceases at low accommodation coefficients (large slip). The streamwise and transverse forces decrease as the accommodation coefficient is decreased. Based on the good agreement between the two methods, computational fluid dynamics is used to determine the critical accommodation coefficient below which vortex shedding ceases for Reynolds numbers of 60-100 at a Mach number of 0.3. Conditions to observe the effect of slip on vortex shedding appear to be experimentally realizable, although challenging.
In April of 2020, Sandia National Laboratories had an urgent need to identify and manage the data that could be used to create mobile applications, models, reports, and visualizations to assist management in safely bringing the workforce onsite during the COVID-19 pandemic. Multiple divisions volunteered to design and build software solutions; meanwhile, requests for new data sources, including duplicate requests, were inundating Information Technology (IT) and data owners. The Enterprise Data Governance Team was assigned to resolve obtaining and accessing new sources of data in an accelerated timeframe. Through successful collaboration with multiple stakeholders and domain owners across Sandia, the Enterprise Data Governance Team rapidly developed a centralized data strategy and solution for use in safeguarding the Sandia workforce during the COVID-19 pandemic. This foundation enabled teams to successfully develop solutions, including reports for executives and management as well as the data for modeling and scientific analysis.
Large volumes of data are being collected by Sandia National Laboratories as part of an active commercial-off-the-shelf (COTS) part testing and surveillance program. This user manual documents Python-based COTS Data Analytics software that has been developed for standardizing, displaying, visualizing, and analyzing the resulting COTS part testing and surveillance data. It is the objective of these software tools to streamline the analysis of COTS testing and surveillance data and improve the efficiency with which test engineers and data analytics experts can pinpoint possible performance and reliability problems in COTS parts.
This paper describes results from an optical-engine investigation of oxygenated fuel effects on ducted fuel injection (DFI) relative to conventional diesel combustion (CDC). Three fuels were tested: a baseline, non-oxygenated No. 2 emissions certification diesel (denoted CFB), and two blends containing potential renewable oxygenates. The first oxygenated blend contained 25 vol% methyl decanoate in CFB (denoted MD25), and the second contained 25 vol% tri-propylene glycol mono-methyl ether in CFB (denoted T25). Whereas DFI and fuel oxygenation primarily curtail soot emissions, intake-oxygen mole fractions of 21% and 16% were employed to explore the potential additional beneficial impact of dilution on engine-out emissions of nitrogen oxides (NOx). It was found that DFI with an oxygenated fuel can attenuate soot incandescence by ~100X (~10X from DFI and an additional ~10X from fuel oxygenation) relative to CDC with conventional diesel fuel, regardless of dilution level and without large effects on other emissions or efficiency. This breaks the soot/NOx trade-off with dilution, enabling simultaneous reductions in both soot and NOx emissions, even with conventional diesel fuel. Significant cyclic variability in soot incandescence for both CDC and DFI suggests that additional improvements in engine-out soot emissions may be possible via improved control of in-cylinder mixture formation and evolution.
Kinetic simulations of Sandia National Laboratories' Z machine are conducted to understand particle transport in the highly magnetized environment of a multi-MA accelerator. Joule heating leads to the rapid formation of electrode surface plasmas. These plasmas are implicated in reducing accelerator efficiency by diverting current away from the load [M.R. Gomez et al., Phys. Rev. Accel. Beams 20, 010401 (2017)PRABCJ2469-988810.1103/PhysRevAccelBeams.20.010401, N. Bennett et al., Phys. Rev. Accel. Beams 22, 120401 (2019)PRABCJ2469-988810.1103/PhysRevAccelBeams.22.120401]. The fully-relativistic, electromagnetic simulations presented in this paper show that particles emitted in a space-charge-limited manner, in the absence of plasma, are magnetically insulated. However, in the presence of plasma, particles are transported across the magnetic field in spite of being only weakly collisional. The simulated cross-gap currents are well-approximated by the Hall current in the generalized Ohm's law. The Hall conductivities are calculated using the simulated particle densities and energies, and the parameters that increase the Hall current are related to transmission line inductance. Analogous to the generalized Ohm's law, we extend the derivation of the magnetized diffusion coefficients to include the coupling of perpendicular components. These yield a Hall diffusion rate, which is equivalent to the empirical Bohm diffusion.