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Enlistment Bonuses Available. Non-Prior Service enlistment bonus amounts are based on the MOS (job) and the number of years one is enlisting for.If you are a recruit about the join the military and have highly sought after skills or qualify for challenging jobs within the military (nuclear, special ops, linguist, medical, etc), you could also be eligible for an enlistment bonus or a 'signing. Database Interface and 'MySQL' Driver for R: 2018-05-13: RSiena: Siena - Simulation Investigation for Empirical Network Analysis: 2018-05-13: sodavis: SODA: Main and Interaction Effects Selection for Logistic Regression, Quadratic Discriminant and General Index Models: 2018-05-13: stminsights: A 'Shiny' Application for Inspecting.

Human Interface Devices (HID) is a device class definition to replace PS/2-style connectors with a generic USB driver to support HID devices such as keyboards, mice, game controllers, etc. Prior to HID, devices could only utilize strictly-defined protocols for mice and keyboards. Hardware innovation required either overloading data in an existing protocol or creating non-standard hardware with its own specialized driver. HID provided support for these “boot mode” devices while adding support for hardware innovation through extensible, standardized and easily-programmable interfaces.

HID devices today include a broad range of devices such as alphanumeric displays, bar code readers, volume controls on speakers/headsets, auxiliary displays, sensors and many others. Many hardware vendors also use HID for their proprietary devices.

HID began with USB but was designed to be bus-agnostic. It was designed for low latency, low bandwidth devices but with flexibility to specify the rate in the underlying transport. The specification for HID over USB was ratified by the USB-IF in 1996 and support over additional transports followed soon after. Details on currently supported transports can be found in HID Transports Supported in Windows. 3rd-party, vendor-specific transports are also allowed via custom transport drivers.

HID Concepts

HID consists of two fundamental concepts, a Report Descriptor, and Reports. Reports are the actual data that is exchanged between a device and a software client. The Report Descriptor describes the format and meaning the data that the device supports.

Reports

Applications and HID devices exchange data through Reports. There are three Report types: Input Reports, Output Reports, and Feature Reports.

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Each Top Level Collection defined in a Report Descriptor can contain zero (0) or more reports of each type.

Usage Tables

The USB-IF working group publishes HID Usage Tables that are part of the Report Descriptors that describe what HID devices are allowed to do. These HID Usage Tables contain a list with descriptions of Usages, which describe the intended meaning and use of a particular item described in the Report Descriptor. For example, a Usage is defined for the left button of a mouse. The Report Descriptor can define where in a Report an application can find the current state of the mouse’s left button. The Usage Tables are broken up into several name spaces, called Usage Pages. Each Usage Page describes a set of related Usages to help organize the document. The combination of a Usage Page and Usage define the Usage ID that uniquely identifies a specific Usage in the Usage Tables.

See also

USB-IF HID Specifications.

EES at Los Alamos National Laboratory (LANL) develops and applies a suite of software to address physical processes across numerous scales including subsurface flow and transport, machine learning, seismoacoustics, discrete fracture networks, ecosystem hydrology, infrastructure and management, and wildfire behavior.

Open-source and currently licensed software:

Amanzi provides a flexible and extensible flow and reactive transport simulation capability for environmental applications. It features general polyhedral mesh infrastructure, which leverages MSTK, advanced discretizations of process models, including traditional finite volume schemes, mimetic finite differences, and nonlinear finite volumes. In addition, it provides:

• Advanced nonlinear solvers, such as Nonlinear Krylov Acceleration and Anderson Acceleration, and leverages Trilinos-ML and Hypre Algebraic Multigrid for scalable solvers.
• Flexibility for hierarchical weak and strong coupling of processes with subcycling, using Arcos as the multiphysics framework.
• Geochemistry support through the Alquimia interface, and can use the geochemistry engine from PFLOTRAN or CrunchFlow.

Amanzi is applicable to groundwater contaminant migration under partially saturated, nonisothermal conditions and its interaction with surface water. The code is parallel and leverages open-source parallel frameworks such as Trilinos, PETSc. It is jointly developed by LANL, LBNL, PNNL, and ORNL as an open-source project under the three-clause BSD license.

→ Access Amanzi code on GitHub
→ Amanzi-ATS Website

The Advanced Terrestrial Simulator is a high-performance computing tool for solving ecosystem-based, integrated, distributed hydrology. It builds on the multiphysics framework and tool sets (mesh infrastructure, discretizations, and solvers) provided by Amanzi and is a key developmental driver of the flexible multiphysics framework Arcos.

Capabilities center on solving varied forms of Richards equation coupled to a surface-flow equation, along with the needed sources and sinks for ecosystem and climate models. This analysis can include thermal processes (particuarly ice for frozen soils), evapo-transpiration, albedo-driven surface energy balances, snow, biogeochemistry, plant dynamics, deformation, transport, and many more.

ATS unique capabilities include:

• Thermal integrated hydrology capabilities, which include thermal energy with freeze/thaw processes in both the surface and subsurface water.
• Reactive transport capabilities, which are also coupled in both surface and subsurface water.

Amanzi/ATS is jointly developed by LANL, LBNL, and ORNL as an open-source project under the three-clause BSD license.

Brown, MoMIC, and Mono Soot are modules contributing to the predictability of the CFD software Uintah/Arches, which is developed and maintained by the University of Utah.

These modules execute three separate models for predicting soot formation in solid fuel combustion systems such as coal or biomass. All three models were developed in collaboration with the University of Utah, Brigham Young University, and University of California-Berkeley for predicting soot formation in an oxy-coal boiler, but their use has been generalized to any solid-fuel system including but not limited to:

• gasification systems
• chemical looping systems, and
• wildfire systems.

CHROTRAN is a massively parallel numerical simulator for in situ biogeochemical and chemical remediation of heavy metals in heterogeneous aquifers.

CHROTRAN can simulate multi-scale remediation processes related to groundwater remediation of heavy metals and other contaminants accounting for physical and chemical aquifer heterogeneities. It has been applied to represent processes from the laboratory to field scale, and has been implemented by LANL to simulate and guide field pilot studies and long-term remediation deployments.

LANL Copyright No. C17061

CO₂-PENS is a conceptual and computer model for ensuring safe and effective containment of CO₂.

The model links together physics-based process-level modules that describe the entire CO₂ sequestration pathway, starting from capture at a power plant and following CO₂ through pipelines to the injection site and into the reservoir. After injection, simulation of CO₂ migration continues through the subsurface, where it may mineralize, dissolve into brine, or react with wellbore casing or cement.

CO₂ may leak from the reservoir along wellbores or faults that lead back towards overlying aquifers or the surface. The model can be used to quickly screen sequestration sites or to perform a more detailed site-specific evaluation.

CO₂-PENS V1 code: LACC-2012-122

dfnworks is a parallelized computational suite to generate three-dimensional discrete fracture networks (DFN) and simulate flow and transport. Developed at LANL, it has been used to study flow and transport in fractured media at scales ranging from millimeters to kilometers.

dfnWorks creates high-fidelity three-dimensional networks dfnGen, which combine FRAM (the feature rejection algorithm for meshing) methodology to stochastically generate three-dimensional DFNs with the LaGriT meshing toolbox to create a high-quality computational mesh representation.

The representation produces a conforming Delaunay triangulation suitable for high-performance computing finite volume solvers in an intrinsically parallel fashion. Flow through the network is simulated with dfnFlow, which utilizes the massively parallel subsurface flow and reactive transport finite volume code PFLOTRAN. A Lagrangian approach to simulating transport through the DFN is adopted within dfnTrans to determine pathlines and solute transport through the DFN.
Documentation: LA-UR-17-22216; LA-CC-17-027 (open source)

The numerical background of the FEHM computer code can be traced to the early 1970s when it was used to simulate geothermal and hot dry rock reservoirs. The primary use over a number of years was to assist in the understanding of flow fields and mass transport in the saturated and unsaturated zones below the potential Yucca Mountain repository.

Today FEHM is used to simulate groundwater and contaminant flow and transport in deep and shallow, fractured and un-fractured porous media throughout the US DOE complex.

FEHM has proved to be a valuable asset on a variety of projects of national interest including:

• Environmental Remediation of the Nevada Test Site
• LANL Groundwater Protection Program
• Geologic CO₂ Sequestration
• Enhanced Geothermal Energy (EGS) programs
• Oil and Gas production
• Nuclear Waste Isolation
• Arctic Permafrost

Documentation: LA-UR-12-24493; LA-CC-2012-083; Copyright No. C13022 (open source)

FEHM.jl is a module providing a Julia interface to FEHM, and is included in the ZEM framework.

LANL Copyright No. C17004; B&R Code: EY6004300 (open source)

GeoAc is a numerical package written in C++ which solves the equations governing acoustic propagation through the atmosphere in the geometric limit using a RK4 algorithm.

GeoAc contains multiple instances of said equation system and is able to model propagation in an azimuthal plane using the effective motionless medium approximation as well as in three dimensions using an inhomogeneous moving background medium.

The three dimensional propagation scheme include methods to model propagation in a Cartesian coordinate system as well as a spherical coordinate system which incorporates the curvature of the earth.

→ Access GeoAc code on GitHub

→ Software License

Recent advances in numerical modeling of small-scale phenomena in the atmosphere are based on two models, the HIgh GRADient applications model (HIGRAD), and a physics-based wildfire-behavior model (FIRETEC). These codes have allowed simulations of atmospheric phenomena at very high spatial resolution on LANL's supercomputers.

HIGRAD is coupled to FIRETEC to produce a coupled atmosphere/wildfire behavior model based on conservation of mass, momentum, species, and energy that simulates wildland fire and motions of the local atmosphere.

Examples of types of physical phenomenon of interest are:

• effects of transient wind conditions
• effects of nonhomogeneous terrain
• effects of nonuniform fuels
• influence of disturbances on fire behavior, such as bark beetle and fuel management.

HIGRAD code: LA-CC-00-45; FIRETEC code: LA-CC-00-46

The Hybrid Optimization Software Suite (HOSS) is a parallelized computational multi-physics platform that combines finite-element and discrete-element methodologies (FDEM) for solid material handling, with a fully integrated explicit fluid solver. With these combined processes, HOSS represents a paradigm shift when it comes to generating accurate hydro-mechanically coupled simulations of material deformation, fracture, and failure, while remaining compatible with existing CAD mesh generators (Abaqus, Cubit, Trelis) and visualization toolkit softwares such as Paraview.

HOSS has been applied by a myriad of researchers for fields in rock mechanics, oil and gas industries, structural, mechanical, mining, and biomedical engineering, and blast/impact, seismic, and acoustic analysis.

Current HOSS applications at LANL include:

• Hydraulic fracturing
• Hypervelocity impact of bolides
• Earthquake rupture
• Fully coupled THM (Thermal-Hydraulic-Mechanical) reservoir processes
• Nuclear weapons effects (cratering, pyroclastic flow, etc.)
• Underground test containment transport
• High explosive performance
• Weapons penetration

HOSS is currently not open source software, but full commercial software licenses are available, as well as a free educational version – HOSS.edu – which is intended for post-secondary academic environments.

Documentation: LA-UR (pending); LA-CC (pending); Copyright No. (pending)

→ Website [pending]

InfraMonitor is a Matlab-based tool for infrasound monitoring that incorporates LANL-developed detection, association, and location algorithms in addition to a Matlab implementation of the Tau-P raytracing technique.

The Adaptive F-Detector (AFD): In contrast with other routinely used infrasound detectors, the AFD utilizes a contextual detection hypothesis that adaptively accounts for temporally variable correlated ambient noise. This technique reduces the number of false alarms caused by background noise sources such as ocean noise, wind farms, and other continuous wave sources.

Association: The infrasound association algorithm uses a grid search approach to relate arrivals at multiple arrays. InfraMonitor searches for groups of arrivals with backazimuths and inter-array delay times that are consistent with each grid node. When such groups of arrivals are identified, they are associated and input to the localization procedure described following.

BISL: The BISL technique uses a statistical approach for infrasound location that can appropriately account for both model and measurement uncertainties inherent to infrasound. Phase identification is replaced by the use of a Bayesian prior on group velocity, with both arrival times and backazimuths contributing to the estimation of a location polygon for a specified confidence level.

→ InfraMonitor Website

→ Access InfraMonitor code on GitHub

→ Software License

Infrapy is a python based toolkit for processing infrasound array data. The toolkit provides a library of functions for detection, location, and association of infrasonic signals of interest, a command line interface to the library, and an graphical user interface for analysts. Infrapy also provides multiple example scripts and utilities for relational database and FDSN interaction.

LANL Copyright No. C15090
Documentation LA-UR: Pending

→ Website [pending]

LaGriT is a software tool for generating, editing, and optimizing multi-material unstructured finite element grids. It also maintains the geometric integrity of complex elements including input volumes, surfaces, and geologic data to produce an optimal grid (Delaunay, Voronoi).

The data structures used in the code are compact, powerful, and expandable to include hybrid meshes (tet, hex, prism, pyramid, quadrilateral, triangle, line). However, the main algorithms are for triangle and tetrahedral meshes.

The LaGriT tools are used in many projects including:

• ASCEM meshing for Amanzi
• Discrete Fracture Networks (DFN)
• Arctic Permafrost
• Subsurface Flow and Transport models using FEHM and PFLOTRAN

LANL LA-CC-15-069; Copyright No. C15097 (open source)

The LANL-developed LBM3RT is a suite of computer codes for physics-based simulation of coupled multiphase flow, transport of heat and mass, as well as (electro)chemical reactions in porous media with evolving hydrological properties at the individual pore/grain scale

LANL LA-CC-17-022; Copyright No. C17027 (export controlled)

The computer code MARFA uses an extremely efficient particle-based Monte Carlo method to simulate the transport of radionuclides beneath the surface of the Earth.

The algorithm uses non-interacting particles to represent packets of radionuclide mass. These particles are moved through the system according to rules that mimic the underlying physical transport and retention processes.

In contrast to the conventional random walk particle tracking algorithm, which use a specified time step and random spatial displacement, the MARFA algorithms use a fixed spatial displacement and a random transit time for the displacement. The use of a fixed spatial displacement makes the code extremely robust and computationally efficient.

LANL LA-CC-11-089 (open source)

→ MARFA Website

MATK facilitates model analysis within the Python computational environment. MATK expects a model defined as a Python function that accepts a dictionary of parameter values as the first argument and returns model results as a dictionary, array, integer, or float.

Many model analyses are provided by MATK. These model analyses can be easily modified and/or extended within the Python scripting language. New model analyses can easily be hooked up to a MATK model as well.

LANL LA-CC-13-132 (open source)
→ Access MATK code on GitHub

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MADS is open-source, high-performance computational framework for data- and model-based analyses. There are two versions; the original written in C, and a newer version developed in Julia. MADS is designed to be a user-friendly code utilizing adaptive rules and techniques which allows the model analyses to be performed with minimum user input. MADS can perform:

• sensitivity analysis
• parameter estimation
• model inversion and calibration
• uncertainty quantification
• model selection
• model reduction
• decision analysis

MADS can be internally or externally coupled with any existing model simulator, and also includes built-in analytical solutions for groundwater flow and contaminant transport. MADS includes extensive verification and example problems.

Documentation: LA-UR-11-11967; MADS: Julia LA-CC-15-080; C LA-CC-10-055; LA-CC-11-035 (open source)

PFLOTRAN is an open source, state-of-the-art massively parallel multiphase, multicomponent and multiscale subsurface flow and reactive transport code. Parallelization is achieved through domain decomposition using the PETSc libraries. PFLOTRAN has been developed from the ground up for parallel scalability and has been run on up to 2¹⁸ processor cores with problem sizes up to 2 billion degrees of freedom.

Currently PFLOTRAN can handle a number of surface and subsurface processes, including Richards equation, two-phase flow involving supercritical CO², and multicomponent reactive transport including aqueous complexing, sorption and mineral precipitation and dissolution, on structured as well as unstructured grids. A unique feature of the code is its ability to run multiple input files and multiple realizations of permeability and porosity fields simultaneously on one or more processor cores per run.

Additional capabilities include multiple interacting continuum method and discrete fracture network approach for modeling flow and transport in fractured media.

LANL LA-CC-09-047 (open source)

PlumeCalc implements the Convolution-Based Particle Tracking (CBPT) method and requires auxiliary input information related to the flow and transport model as provided by FEHM.

LANL LA-CC-11-029 (export controlled, pending open source)

PyFEHM is an open-source (LGPL 2.1) Python library that provides classes and methods to support a scripting environment for the subsurface heat and mass transfer, and geomechanics code FEHM.

The library is inspired by a similar library, PyTOUGH, available for use with the TOUGH2 family of codes.

LANL LA-CC-13-081; Copyright No. C13153 (open source)

PySAC is a Python interface to the Seismic Analysis Code (SAC) file format, supporting little and big-endian binary and alphanumeric format, containing evenly-sampled time-series data. PySAC emphasizes intuitive header access, header consistency, and ObsPysupport.

Features:

• Read and write SAC binary or ASCII.
  • Autodetect or specify expected byteorder.
  • Optional file size checking and/or header consistency checks.
  • Header-only reading and writing.
  • 'Overwrite OK' checking ('locrok' header).
• Convenient access and manipulation of relative and absolute time headers.
• Uder-friendly header printing/viewing.
• Fast access to header values from attributes.
  • With type checking, null handling, and enumerated value checking.
• Conversion from ObsPy Trace to SAC trace retains detected previous SAC header values.
• Conversion to ObsPy Trace retains the complete SAC header.

→ PySAC Website

→ Access PySAC code on GitHub

→ Software License

SimCCS is an economic-engineering software tool for making integrated CCS infrastructure decisions. Using user-provided regional source, sink, and transportation data, SimCCS creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design.

LANL Copyright No. C17147

Taxila LBM is a parallel implementation of the Lattice Boltzmann Method for simulation of flow in complex porous media. The implementation solves both single and multiphase systems and it is capable of solving D2Q9, D3Q19, and other mesh dependencies, on 2D or 3D grids. It is easily extended to other models of connectivity.

The multiphase and multicomponent models are based upon the Shan and Chen method with many improvements. It includes the ability to use higher order derivatives or multiple relaxation times to improve stability at large viscosity ratios. It also handles multiple mineral/wall materials, allowing for different wettabilities and contact angles on each mineral and supports a variety of inlet and outlet boundary conditions.

TensorDecompositions: a series of novel, unsupervised machine learning (ML) methods based on matrix and tensor factorizations, called NMFk and NTFk have been developed allowing for objective, unbiased, data analyses to extract essential features hidden in data.

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Unsupervised Machine Learning methods can be applied to:

• feature extraction
• blind source separation
• model diagnostics,
• detection of disruptions and anomalies
• image recognition,
• discovery of unknown dependencies and phenomena represented in datasets
• development of physics and reduced-order models representing the data

The TensorDecompositions methodology is capable of identifying the unknown number of features charactering the analyzed datasets, as well as the spatial footprints and temporal signatures of the features in the explored domain. TensorDecompositions algorithms are written in Julia.

VORONOI creates a sparse matrix of geometric coefficients that is derived from the Voronoi dual mesh of the Delaunay triangle, or tetrahedral mesh that represents the geometry of the model. VORONOI computes these coefficients, which can be stand alone or integrated into LaGriT mesh generation software.

This software is robust for very large problems, and can take advantage of parallel computing resources. The output is general, and can be utilized by PFLOTRAN, FEHM and TOUGH2.

LANL C#

→ Access Voronoi code on GitHub

→ VORONOI Website

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WALKABOUT performs random walk particle tracking simulations of solute transport based on groundwater flow solutions from FEHM.

A typical workflow for Walkabout within the FEHM system would use LaGriT to generate unstructured grids. FEHM then provides a discretized representation of the steady-state flow field to Walkabout. Given this discrete solution, WALKABOUT then reconstructs a groundwater flow field, and performs the random walk particle tracking calculation.

LANL LA-CC-11-033; Copyright No. C11063 (open source)
→ WALKABOUT Website

WELLS is a C code for multi-well variable-rate pumping-test analysis based on analytical methods and computes drawdown in confined, unconfined, and leaky aquifers through a variety of analytical solutions.

LA-CC-10-019; LA-CC-11-098

ZEM is an integrated framework for real-time data and model analyses for environmental decision-making.

Typical environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This approach is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. However, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).

ZEM addresses all of these issues, with a framework that allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible model analyses related to uncertainty quantification, risk assessment and decision-making. The model analyses are performed using MADS.

LANL LA-CC-17-004; Copyright No. C17004