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ProRad is a computer program that is used to generate synthetic images of proton (or other charged particles) radiographs. The proton radiographs arc images that arc obtained by sending energetic protons (or electrons or positrons, for example) through 11 plasma where electric and/or magnetic fields alter the particles trajectory, Dnd the variations me imaged on RC film, image plate, or equivalent
Boiler tubes in steam power plants experience exfoliation of oxide grown on the inner side of the tubes. In extreme cases, the exfoliation cause significant tube blockages that lead to forced power plant outages. It is thus desired to predict through modeling the propensity of exfoliation events in order to inform power plant operators of possible tube blockages. SpallMap solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages at one-location along a boiler tube and compares it with scale damage criteria represented by Armitt diagram. The SPALLMAP code contains modules developed for oxide growth, stress analysis, and classical fracture mechanics correlations by taking into account the following phenomena and features, (a) Non-uniform thermal expansion coefficient of oxides and metal substrates, (b) Plant operation schedule with periodic alternate full-load and partial-load regimes, (c) axisymmetric formulation for cylindrical tubes, (d) Multiple oxide layers, (e) oxide-growth induced stresses, and (f) damage criteria from classical fracture mechanics. The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.
A set of subroutines that interact with an existing computer program, Quantum Espresso (QE), that takes a set of electronic orbitals from QE and propagates them forward in time in response to a number of perturbations. These perturbations include the motion of ions and a wide spectrum of applied electromagnetic fields (e.g., static magnetic fields, slowly-varying electric fields, x-rays, etc.). From the time evolution of the electronic orbitals comes time-varying values of physical observables like the electronic charge and current densities and atomic forces. These are further post-processed to yield properties of interest like stopping powers, conductivities, and the dynamic structure factor. The electronic orbitals are described in a plane wave basis and the equations of motion are carried out using a unitary or approximately unitary time propagation algorithm. Related work will include subroutines for interfacing this capability, as well as others that already exist within QE, with a fork of QE that is more extensible and modular.SAND2019-12611 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.
Axom is an open-source library of "building block" software components that provide core infrastructure capabilities for HPC applications. Such capabilities include: input file parsing and verification for various file formats, format specification for material shape input to multi-material simulations and tools for placing those shapes on meshes, parallel distributed coordination of diagnostic messages, geometric primitives, spatial queries and spatial search acceleration data structures, in memory key-value data store for managing simulation data and parallel file I/O. Axom components are used widely across LLNL Advanced Simulation and Computing program applications. It is also part of the LLNL institutionally-supported RADIUSS project, which promotes and funds its adoption by projects across LLNL.
The SST provides a parallel framework to perform system simulation of computer architectures to determine their performance and power consumption. Additionally, the SST contains basic models of a computer processor, and interconnect and can connect to an external memory simulator (DRAMSim II). The SST framework provides a simple interface by which other computer simulation models can be combined under a common parallel discrete event-based simulation environment. This allows design exploration of future architectures, analysis of how current computer programs will function on future architectures. The SST provides a parallel discrete event simulation framework, including partitioning and object distribution over MPI. It also provides a mechanism by which components can report their power consumption for analysis.
Boiler tubes in steam power plants experience tube blockages due to exfoliation of oxide grown on the inner side of the tubes. In extreme cases, significant tube blockages can lead to forced power plant outages. It is thus desired to predict through modeling the amount of tube blockage in order to inform power plant operators of possible forced outages. SpalLoop solves for the stress-strain equations in an axisymmetric geometry, tracking the stress/strain evolution during boiler operation including outages for the entire boiler tube length. At each operational outage, i.e., temperature excursions down to room temperature, the amount of exfoliated area for the entire tube loop is estimated the amount of tube blockage is predicted based assumed blockage geometry and site. The SpaLLoop code contains modules developed for oxide growth, stress analysis, tube loop geometry, blockage area by taking into account the following phenomena and features, (a) Plant operation schedule with periodic alternate full-load and partial-load regimes and shut-downs, i.e., temperature excursions from high-load to room temperature, (b) axisymmetric formulation for cylindrical tubes, (c) oxide growth in a temperature gradient with multiple oxide layers, (d) geometry of a boiler tube with a single tube loop or two tube loops, (e) temperature variation along the tube length based on hot gas temperature distribution outside the tube and inlet steam temperature, (f) non-uniform oxide growth along the tube length according to the local steam tube temperature, (g) exfoliated area module: at each operational outage considered, the amount of exfoliated area and exfoliated volume along the tube is estimated, (h) blockage module: at each operational outage considered, the exfoliated volume/mass for each tube loop is estimated from which the amount of tube blockage is predicted based on given blockage geometry (length, location, and geometry). The computer program is written in FORTRAN90. Its modular structure was sought for allowing the best flexibility in updating the program by implementing new constitutive equations due to availability of new material property data and/or new physical phenomena.
Functional information is normally communicated using specific, context-dependent strings of symbolic characters. This is true within the human realm (texts and computer programs), and also within the biological realm (nucleic acids and proteins). In biology, strings of nucleotides encode much of the information within living cells. How do such information-bearing nucleotide strings arise and become established? This paper uses comprehensive numerical simulation to understand what types of nucleotide strings can realistically be established via the mutation/selection process, given a reasonable timeframe. The program Mendel’s Accountant realistically simulates the mutation/selection process, and was modified so that a starting string of nucleotides could be specified, and a corresponding target string of nucleotides could be specified. We simulated a classic pre-human hominin population of at least 10,000 individuals, with a generation time of 20 years, and with very strong selection (50 % selective elimination). Random point mutations were generated within the starting string. Whenever an instance of the target string arose, all individuals carrying the target string were assigned a specified reproductive advantage. When natural selection had successfully amplified an instance of the target string to the point of fixation, the experiment was halted, and the waiting time statistics were tabulated. Using this methodology we tested the effect of mutation rate, string length, fitness benefit, and population size on waiting time to fixation. Biologically realistic numerical simulations revealed that a population of this type required inordinately long waiting times to establish even the shortest nucleotide strings. To establish a string of two nucleotides required on average 84 million years. To establish a string of five nucleotides required on average 2 billion years. We found that waiting times were reduced by higher mutation rates, stronger fitness benefits, and larger population sizes. However, even using the most generous feasible parameters settings, the waiting time required to establish any specific nucleotide string within this type of population was consistently prohibitive. We show that the waiting time problem is a significant constraint on the macroevolution of the classic hominin population. Routine establishment of specific beneficial strings of two or more nucleotides becomes very problematic.
Woven fabric composites are extensively used in molding complex geometrical shapes due to their high conformability compared to other fabrics. Preforming is an important step in the overall process. In this step, the two-dimensional fabric is draped to become the three-dimensional shape of the part prior to resin injection. During preforming, the orientation of the tows may change significantly compared to the initial orientations. Accurate prediction of the tow orientations after molding is important for evaluating the structural performance of the final part. This paper investigates the fiber angle changes for carbon fiber woven fabrics during draping over a truncated pyramid tool designed and fabricated at the General Motors Research Labs. This aspect of study is a subset of the broad study conducted under the purview of a Department of Energy project funded to GM in developing state of the art computational tools for integrated manufacturing and structural performance prediction of carbon fiber composites. Fabric bending, picture frame testing, and bias-extension evaluations were carried out to determine the material parameters for these fabrics. The PAM-FORM computer program was used to model the draping behavior of these fabrics. Following deformation, fiber angle changes at different locations on the truncated pyramid were measured experimentally. The predicted angles matched the experimental results well as measured along the centerline and at several different locations on the deformed fabric. Details of the test methods used as well as the numerical results with various simulation parameters will be provided.
Radioisotopes are commonly used in nuclear medicine for treating cancer and new, more effective treatment options are always desired. As a result, there is a national need for new radioisotopes and ways to produce them. A computer program was created that evaluates the daughters for all known reactions of projectiles (gamma rays, protons or neutrons) with every stable target isotope by comparing the cross-sections for each reaction at a desired energy, and outputs a list of the potential daughter isotopes that are most likely to be generated. The program then evaluates the decay chains of these daughters to provide a list of the possible decay chains that contain the radioisotope of interest. By knowing the daughter production and decay chain for each isotope, it is possible to go from the desired radioisotope to the stable isotope that can be used as a target for its production. This project would facilitate the search for new pathways to creating useful theranostic isotopes.
The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.
A method of analyzing the axial variation of the heat generation rate, temperature, voltage, current density and emitter heat flux in a thermionic converter is described. The method is particularly useful for the case of "long" diodes, each extending over the full length of the reactor core. For a given diode geometry and fuel distribution, the analysis combines a nuclear solution of the axial fission density profile with the iterative solution of four differential equations representing the thermal, electrical, and thermionic interactions within the diode. The digital computer program developed to solve these equations can also perform a design optimization with respect to lead resistance, load voltage, and emitter thickness, for a specified maximum emitter temperature. Typical results are presented, and the use of this analysis for predicting the diode operating characteristics is illustrated.
This report describes development and demonstration of Generation 2 of the NRAP toolset for probabilistic analysis of risks from earthquakes that could potentially be induced by CO 2 injection. The capability to carry out hazard estimation at multiple sites and over multiple time periods of interested has been added to the integrated toolset. The capability to carry out hazard runs that utilize multiple simulations, based on random sampling of input parameter distributions, to bound hazard curve uncertainties has also been added. During Generation 2, an innovative method of constructing “nuisance fragility” functions for seismic ground motion has been developed. These functions are combined with seismic hazard curves to estimate of the risk of nuisance from ground shaking. The results described in this report demonstrate the functionality of the toolset based on its application to hypothetical scenarios involving one or two faults. Additional computer program development, including code parallelization, will be needed to bring the toolset up to full functionality. Alternative approaches to implementing the simulation-based approach to probabilistic induced seismicity hazard analysis are also outlined.
It is well known that cirrus clouds play a major role in regulating the earth’s climate, but the details of how this works are just beginning to be understood. This project targeted the main property of cirrus clouds that influence climate processes; the ice fall speed. That is, this project improves the representation of the mass-weighted ice particle fall velocity, V m , in climate models, used to predict future climate on global and regional scales. Prior to 2007, the dominant sizes of ice particles in cirrus clouds were poorly understood, making it virtually impossible to predict how cirrus clouds interact with sunlight and thermal radiation. Due to several studies investigating the performance of optical probes used to measure the ice particle size distribution (PSD), as well as the remote sensing results from our last ARM project, it is now well established that the anomalously high concentrations of small ice crystals often reported prior to 2007 were measurement artifacts. Advances in the design and data processing of optical probes have greatly reduced these ice artifacts that resulted from the shattering of ice particles on the probe tips and/or inlet tube, and PSD measurements from one of these improved probes (the 2-dimensional Stereo or 2D-S probe) are utilized in this project to parameterize V m for climate models. Our original plan in the proposal was to parameterize the ice PSD (in terms of temperature and ice water content) and ice particle mass and projected area (in terms of mass- and area-dimensional power laws or m-D/A-D expressions) since these are the microphysical properties that determine V m , and then proceed to calculate V m from these parameterized properties. But the 2D-S probe directly measures ice particle projected area and indirectly estimates ice particle mass for each size bin. It soon became apparent that the original plan would introduce more uncertainty in the V m calculations than simply using the 2D-S measurements to directly calculate V m . By calculating V m directly from the measured PSD, ice particle projected area and estimated mass, more accurate estimates of V m are obtained. These V m values were then parameterized for climate models by relating them to (1) sampling temperature and ice water content (IWC) and (2) the effective diameter (D e ) of the ice PSD. Parameterization (1) is appropriate for climate models having single-moment microphysical schemes whereas (2) is appropriate for double-moment microphysical schemes and yields more accurate V m estimates. These parameterizations were developed for tropical cirrus clouds, Arctic cirrus, mid-latitude synoptic cirrus and mid-latitude anvil cirrus clouds based on field campaigns in these regions. An important but unexpected result of this research was the discovery of microphysical evidence indicating the mechanisms by which ice crystals are produced in cirrus clouds. This evidence, derived from PSD measurements, indicates that homogeneous freezing ice nucleation dominates in mid-latitude synoptic cirrus clouds, whereas heterogeneous ice nucleation processes dominate in mid-latitude anvil cirrus. Based on these findings, D e was parameterized in terms of temperature (T) for conditions dominated by (1) homo- and (2) heterogeneous ice nucleation. From this, an experiment was designed for global climate models (GCMs). The net radiative forcing from cirrus clouds may be affected by the means ice is produced (homo- or heterogeneously), and this net forcing contributes to climate sensitivity (i.e. the change in mean global surface temperature resulting from a doubling of CO 2 ). The objective of this GCM experiment was to determine how a change in ice nucleation mode affects the predicted global radiation balance. In the first simulation (Run 1), the D e -T relationship for homogeneous nucleation is used at all latitudes, while in the second simulation (Run 2), the D e -T relationship for heterogeneous nucleation is used at all latitudes. For both runs, V m is calculated from D e . Two GCMs were used; the Community Atmosphere Model version 5 (CAM5) and a European GCM known as ECHAM5 (thanks to our European colleagues who collaborated with us). Similar results were obtained from both GCMs in the Northern Hemisphere mid-latitudes, with a net cooling of ~ 1.0 W m -2 due to heterogeneous nucleation, relative to Run 1. The mean global net cooling was 2.4 W m -2 for the ECHAM5 GCM while CAM5 produced a mean global net cooling of about 0.8 W m -2 . This dependence of the radiation balance on nucleation mode is substantial when one considers the direct radiative forcing from a CO 2 doubling is 4 W m -2 . The differences between GCMs in mean global net cooling estimates may demonstrate a need for improving the representation of cirrus clouds in GCMs, including the coupling between microphysical and radiative properties. Unfortunately, after completing this GCM experiment, we learned from the company that provided the 2D-S microphysical data that the data was corrupted due to a computer program coding problem. Therefore the microphysical data had to be reprocessed and reanalyzed, and the GCM experiments were redone under our current ASR project but using an improved experimental design.
Uncertainties associated with the core bypass flow are some of the key issues that directly influence the coolant mass flow distribution and magnitude, and thus the operational core temperature profiles, in the very high-temperature reactor (VHTR). Designers will attempt to configure the core geometry so the core cooling flow rate magnitude and distribution conform to the design values. The objective of this project is to study the bypass flow both experimentally and computationally. Researchers will develop experimental data using state-of-the-art particle image velocimetry in a small test facility. The team will attempt to obtain full field temperature distribution using racks of thermocouples. The experimental data are intended to benchmark computational fluid dynamics (CFD) codes by providing detailed information. These experimental data are urgently needed for validation of the CFD codes. The following are the project tasks: (1) Construct a small-scale bench-top experiment to resemble the bypass flow between the graphite blocks, varying parameters to address their impact on bypass flow. Wall roughness of the graphite block walls, spacing between the blocks, and temperature of the blocks are some of the parameters to be tested. (2) Perform CFD to evaluate pre- and post-test calculations and turbulence models, including sensitivity studies to achieve high accuracy. (3) Develop the state-of-the art large eddy simulation (LES) using appropriate subgrid modeling. (4) Develop models to be used in systems thermal hydraulics codes to account and estimate the bypass flows. These computer programs include, among others, RELAP3D, MELCOR, GAMMA, and GAS-NET. Actual core bypass flow rate may vary considerably from the design value. Although the uncertainty of the bypass flow rate is not known, some sources have stated that the bypass flow rates in the Fort St. Vrain reactor were between 8 and 25 percent of the total reactor mass flow rate. If bypass flow rates are on the high side, the quantity of cooling flow through the core may be considerably less than the nominal design value, causing some regions of the core to operate at temperatures in excess of the design values. These effects are postulated to lead to localized hot regions in the core that must be considered when evaluating the VHTR operational and accident scenarios.
This report highlights progress made on plasma shear turbulence in order to showcase the Institutional Computing program's recent accomplishments.
Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, lithium carbonate (LC). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, LC_TA03_130719, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images 2 . The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.
Using x-ray micro computed tomography (MicroCT), we have characterized the linear attenuation coefficients (LAC), μ, of a sample of a dry powder material, tartaric acid (TA). The specimen was prepared at Lawrence Livermore National Laboratory (LLNL), loaded into a 60mL low density polyethylene (LDPE) bottle. After completed packing, the specimen was scanned following the protocol for MicroCT measurements under Test Plan 79. This particular specimen, TA_MP03_130620, recorded the bulk packing density (mass of sample divided by volume of sample) shown above. Two additional preparations were made and analyzed. We used the computer program IMGREC to reconstruct the CT images. The values of the key parameters used in the x-ray data capture and image reconstruction are given in this report. Additional experimental details may be found in the SOP and a separate document. To characterize the statistical distribution of LAC values in each CT image, we first isolated an ~80% region or segment of volume elements (“voxels”) lying completely within the sample, away from the walls of the container. We then calculated the mean value, standard deviation and entropy for (a) the high and low energy image segments and for (b) their digital gradient images 2 . The statistics of the initial image of LAC values are called “first order statistics;” those of the gradient image, “second order statistics.” See Seetho for details of the analysis used to obtain the numbers reported in this document.