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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,747 records · Page 97

PathParser [SWR-19-54]

PathParser is a python-based computational tool for the thermodynamics and robustness analysis of native and designed metabolic pathways. The following functionalities are provided: 1 Max-min driving force (MDF) optimization. The Gibbs free energy change of the least favorable reaction will be maximized to evaluate thermodynamic feasibility of the entire pathway. 2 Protein cost estimation. The smallest enzyme investment will be assessed by calculating the minimal total enzyme cost supporting a given pathway flux. 3 Robustness analysis. Specifically, an ensemble of models is generated to simulate the system response to enzyme perturbation based on bifurcation theory and a continuation method. Probability of system failure and flux fold change against enzyme perturbation are estimated as well as a flux control index.

Xiong, Wei↗

Molecules in Studio v. 1.0

A Powersim Studio implementation of the system dynamics’ ‘Molecules of Structure’. The original implementation was in Ventana’s Vensim language by James Hines. The molecules are fundamental constructs of the system dynamics simulation methodology.

Walker, La Tonya↗

Relational Blackboard

The Relational Blackboard (RBB) is an extension of the H2 Relational Database to support discrete events and timeseries data. The original motivation for RBB is as a knowledge base for cognitive systems and simulations. It is useful wherever there is a need for persistent storage of timeseries (i.e. samples of a continuous process generating numerical data) and semantic labels for the data. The RBB is an extension to the H2 Relational Database, which is open-source. RBB is a set of stored procedures for H2 allowing data to be labeled, queried, and resampled.

Abbott, RobertG↗

MAM4xx

SAND2023-05377O The Modal Aerosol Model with 4 fixed modes (MAM4xx) is a performance-portable, C++ implementation for modeling the chemical reactions of aerosols in the atmosphere. MAM4xx is part of the Energy Exascale Earth System Model (E3SM). The E3SM project is an ongoing Earth system modeling, simulation, and prediction project that optimizes the use of DOE laboratory resources to meet the science needs of the nation and the mission needs of DOE. 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.

Overfelt, James↗

ADOPT (Automotive Deployment Options Projection Tool) [SWR-17-13]

NREL's Automotive Deployment Options Projection Tool (ADOPT) is a vehicle consumer choice and stock model. ADOPT estimates the impact of vehicle technology improvements on future U.S. vehicle sales, energy use, and emissions. It provides consumer choice estimates based on questions such as: -How much impact do lower battery prices have on electric vehicle sales? -How quickly would the market adopt a co-optimized engine/fuel combination that achieves a 10% efficiency improvement? -How do fuel prices impact the electric vehicle/plug-in hybrid electric vehicle sales mix? -How does vehicle lightweighting impact powertrain sales? Approach- Starting with the majority of existing vehicle makes, models, and trims to fully represent the market, ADOPT applies numerous inputs-technology improvements, fuel prices, and vehicle purchase incentives-over time. ADOPT then estimates sales based on the variable weighted value of key attributes, including vehicle price, fuel cost per mile, acceleration, size, and range. ADOPT also considers consumer income level as well as regulations and standards that influence sales and average fuel economy. ADOPT incorporates NREL's FASTSim™ (Future Automotive Systems Technology Simulator, https://www.nrel.gov/transportation/fastsim.html) to apply specified technology improvements to vehicles over time, and to create new model options by combining high-selling powertrains and high-selling vehicle platforms. NREL has extensively validated the tool and its consumer preference trade-offs to ensure confidence in the results.

Brooker, Aaron↗

A resilient network recovery framework against cascading failures with deep graph learning

Because of the increasing importance and dependencies of infrastructure networks and the potential for massive cascading failures in real-world network systems, maintenance optimization to effectively reduce system performance loss caused by diverse disruptions is of significant interest among researchers and practitioners. In this work, a new recovery framework was developed to rapidly identify important system components for maintenance to improve network resilience against cascading failures. Here this work provides distinct advantages to determine an optimal maintenance priority by combining real-time network structure importance with other maintenance prioritization based on customer preference. This approach adopts structural graph embedding and deep reinforcement learning to extract real-time network topology information (such as minimum vertex cover) to update the maintenance priority during the recovery process. Based on the case studies on synthetic networks and a US airport network, the proposed recovery framework with real-time network topology awareness shows better performance than other maintenance prioritization strategies regarding resilience enhancement. This work improves the understanding of how the changing network structure influences maintenance effects. It also provides insights of the practical usefulness of advanced deep learning on helping optimal maintenance prioritization to effectively reduce the intensity and extent of cascading failures.

42 ENGINEERING↗

A coarse-grained model for synergistic action of multiple enzymes on cellulose

In this study, degradation of cellulose to glucose requires the cooperative action of three classes of enzymes, collectively known as cellulases. Endoglucanases randomly bind to cellulose surfaces and generate new chain ends by hydrolyzing -1,4-D-glycosidic bonds. Exoglucanases bind to free chain ends and hydrolyze glycosidic bonds in a processive manner releasing cellobiose units. Then, -glucosidases hydrolyze soluble cellobiose to glucose. Optimal synergistic action of these enzymes is essential for efficient digestion of cellulose. Experiments show that as hydrolysis proceeds and the cellulose substrate becomes more heterogeneous, the overall degradation slows down. As catalysis occurs on the surface of crystalline cellulose, several factors affect the overall hydrolysis. Therefore, spatial models of cellulose degradation must capture effects such as enzyme crowding and surface heterogeneity, which have been shown to lead to a reduction in hydrolysis rates. As a result, we present a coarse-grained stochastic model for capturing the key events associated with the enzymatic degradation of cellulose at the mesoscopic level. This functional model accounts for the mobility and action of a single cellulase enzyme as well as the synergy of multiple endo- and exo-cellulases on a cellulose surface. The quantitative description of cellulose degradation is calculated on a spatial model by including free and bound states of both endo- and exo-cellulases with explicit reactive surface terms (e.g., hydrogen bond breaking, covalent bond cleavages) and corresponding reaction rates. The dynamical evolution of the system is simulated by including physical interactions between cellulases and cellulose. In conclusion, our coarse-grained model reproduces the qualitative behavior of endoglucanases and exoglucanases by accounting for the spatial heterogeneity of the cellulose surface as well as other spatial factors such as enzyme crowding. Importantly, it captures the endo-exo synergism of cellulase enzyme cocktails. This model constitutes a critical step towards testing hypotheses and understanding approaches for maximizing synergy and substrate properties with a goal of cost effective enzymatic hydrolysis.

59 BASIC BIOLOGICAL SCIENCES↗

Fermilab's controls development with virtual accelerator

Control Systems development is often the last thing considered when designing and building new equipment, e.g. a new detector or superconducting RF LINAC; however when the new equipment is installed, it is the first thing desired to be operational for testing. Due to frequent delays in building new equipment and project deadlines, control system development and testing is often curtailed. A way to alleviate this problem is to simulate the control system, though this will be challenging for complex systems.The Fermilab PIP-II (proton improvement plan - II) project is being constructed at Fermilab to deliver $800\,MeV$ protons of $>1\,MW$ beam power to replace the present LINAC for the remainder of the existing accelerator complex. The new LINAC consists of a warm front end (WFE), 23 superconducting RF cryomodules (of 5 types), and a beam transfer line (BTL) to the existing complex.The accelerator physics group has a parallel project to create a digital twin (DT) of the PIP-II accelerator. We have coupled the EPICS controls to this DT and are developing both the DT and EPICS software in parallel. This will allow us to develop the EPICS software framework, the HMIs, sequences, high level physics applications, and other services for use in a fully functional control system.This presentation will detail the work that we have performed to date and show demonstrations of controlling and monitoring the status of the accelerator, as well as future plans for this work.

Hanlet, Pierrick [Fermilab]↗

Processing Large Sensor Data Sets for Safeguards: The Knowledge Generation System

Modern nuclear facilities, such as reprocessing plants, present inspectors with significant challenges due in part to the sheer amount of equipment that must be safeguarded. The Sandia-developed and patented Knowledge Generation system was designed to automatically analyze large amounts of safeguards data to identify anomalous events of interest by comparing sensor readings with those expected from a process of interest and operator declarations. This paper describes a demonstration of the Knowledge Generation system using simulated accountability tank sensor data to represent part of a reprocessing plant. The demonstration indicated that Knowledge Generation has the potential to address several problems critical to the future of safeguards. It could be extended to facilitate remote inspections and trigger random inspections. Knowledge Generation could analyze data to establish trust hierarchies, to facilitate safeguards use of operator-owned sensors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Viscoelastic Model for Lung Parenchyma for Multi-Scale Modeling of Respiratory System - Phase II: Dodecahedral Micro-Model

In the first year of this contractual effort a hypo-elastic constitutive model was developed and shown to have great potential in modeling the elastic response of parenchyma. This model resides at the macroscopic level of the continuum. In this, the second year of our support, an isotropic dodecahedron is employed as an alveolar model. This is a microscopic model for parenchyma. A hopeful outcome is that the linkage between these two scales of modeling will be a source of insight and inspiration that will aid us in the final year's activity: creating a viscoelastic model for parenchyma.

59 BASIC BIOLOGICAL SCIENCES↗

DHS Written Report

Recently, a new galactic cosmic-ray (GCR) source option [1] was implemented in the all-energy, all-particle transport code MCNP6 [2]. In this paper, we made use of this feature to calculate surface neutron and photon background fluxes on a terrestrial grid around the earth. These spectra have been incorporated into Release 2 of the 'background.dat' file, which is read and sampled by MCNP6 whenever a user invokes the background source option [2]. Cosmic radiation bombards Earth with various particles, such as protons and {alpha} particles, some of which are deflected by the Earth's shielding magnetic field. Particles that carry sufficient energy can overcome the deflection and penetrate into the atmosphere. The sufficient energy is dependent on the terrestrial coordinates due to the magnetic force's proportionality to the sine of the angle between the velocity vector of the incoming particle and the magnetic field. As the particles propagate through the atmosphere, collisions with atmospheric molecules generate new particles such as neutrons, protons, photons, muons, pions, and other exotic particles. These secondary often have sufficient energy to undergo additional nuclear interactions, and so on, forming what is known as a cascade shower. The tabulation of background particle fluxes on the surface of the earth is important for a variety of reasons, one of which is the design of nuclear material detection systems. The simulations used various models and formulations for the cosmic source spectra, atmosphere, and terrestrial conditions to correctly model the propagation of GCR particles through the atmosphere to surface level.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Application of Crunch-Flow Routines to Constrain Present and Past Carbon Fluxes at Gas-Hydrate Bearing Sites

In November 2012, Oregon State University initiated the project entitled: Application of Crunch-Flow routines to constrain present and past carbon fluxes at gas-hydrate bearing sites. Within this project we developed Crunch-Flow based modeling modules that include important biogeochemical processes that need to be considered in gas hydrate environments. Our modules were applied to quantify carbon cycling in present and past systems, using data collected during several DOE-supported drilling expeditions, which include the Cascadia margin in US, Ulleung Basin in South Korea, and several sites drilled offshore India on the Bay of Bengal and Andaman Sea. Specifically, we completed modeling efforts that: 1) Reproduce the compositional and isotopic profiles observed at the eight drilled sites in the Ulleung Basin that constrain and contrast the carbon cycling pathways at chimney (high methane flux) and non-chimney sites (low methane, advective systems); 2) Simulate the Ba record in the sediments to quantify the past dynamics of methane flux in the southern Hydrate Ridge, Cascadia margin; and 3) Provide quantitative estimates of the thickness of individual mass transport deposits (MTDs), time elapsed after the MTD event, rate of sulfate reduction in the MTD, and time required to reach a new steady state at several sites drilled in the Krishna-Godavari (K-G) Basin off India. In addition we developed a hybrid model scheme by coupling a home-made MATLAB code with CrunchFlow to address the methane transport and chloride enrichment at the Ulleung Basins chimney sites, and contributed the modeling component to a study focusing on pore-scale controls on gas hydrate distribution in sediments from the Andaman Sea. These efforts resulted in two manuscripts currently under review, and contributed the modeling component of another pare, also under review. Lessons learned from these efforts are the basis of a mini-workshop to be held at Oregon State University (Feb 2014) to instruct graduate students (OSU and UW) as well as DOE staff from the NETL lab in Albany on the use of Crunch Flow for geochemical applications.

03 NATURAL GAS↗

Hanford Tank Farms Waste Feed Flow Loop Phase VI: PulseEcho System Performance Evaluation

This document presents the visual and ultrasonic PulseEcho critical velocity test results obtained from the System Performance test campaign that was completed in September 2012 with the Remote Sampler Demonstration (RSD)/Waste Feed Flow Loop cold-test platform located at the Monarch test facility in Pasco, Washington. This report is intended to complement and accompany the report that will be developed by WRPS on the design of the System Performance simulant matrix, the analysis of the slurry test sample concentration and particle size distribution (PSD) data, and the design and construction of the RSD/Waste Feed Flow Loop cold-test platform.

Denslow, Kayte M.↗

CINT 2020 Strategic Plan

CINT’s role is to enable world-leading science towards realizing these benefits and our strategic objectives describe what is needed to deliver on this promise. As a vibrant partnership between Los Alamos National Laboratory (LANL) and Sandia National Laboratories (SNL), CINT leverages the unmatched scientific and engineering expertise of our host DOE Laboratories in an Office of Science open-access user facility to benefit hundreds of researchers annually. We have world-leading scientific expertise in four thrust areas, as described in section 1, and specialized capabilities to create, characterize and understand nanomaterials in increasingly complex integrated environments. Building upon these current strengths, we identify some of the capabilities and expertise that the nanoscience community will need in the future and that CINT is well positioned to develop and offer as a user facility. These include an expanding portfolio of our signature Discovery Platforms that can be used alone or as sophisticated “experiments within an experiment”; novel synthetic approaches for exquisitely heterostructured nanowires, nanoparticles and quasi-two-dimensional materials; ultra-high resolution spectroscopic techniques of nanomaterial dynamics; in situ microscopies that provide realtime, spatially-resolved structure/property information for increasingly complex materials systems; advanced simulation techniques for integrated nanomaterials; and multi-scale theory for interfaces and dynamics.

36 MATERIALS SCIENCE↗

Development of Extended Period Pressure-Dependent Demand Water Distribution Models

Los Alamos National Laboratory (LANL) has used modeling and simulation of water distribution systems for N-1 contingency analyses to assess criticality of water system assets. Critical components considered in these analyses include pumps, tanks, and supply sources, in addition to critical pipes or aqueducts. A contingency represents the complete removal of the asset from system operation. For each contingency, an extended period simulation (EPS) is run using EPANET. An EPS simulates water system behavior over a time period, typically at least 24 hours. It assesses the ability of a system to respond and recover from asset disruption through distributed storage in tanks throughout the system. Contingencies of concern are identified as those in which some portion of the water system has unmet delivery requirements. A delivery requirement is defined as an aggregation of water demands within a service area, similar to an electric power demand. The metric used to identify areas of unmet delivery requirement in these studies is a pressure threshold of 15 pounds per square inch (psi). This pressure threshold is used because it is below the required pressure for fire protection. Any location in the model with pressure that drops below this threshold at any time during an EPS is considered to have unmet service requirements and is used to determine cascading consequences. The outage area for a contingency is the aggregation of all service areas with a pressure below the threshold at any time during the EPS.

42 ENGINEERING↗

U.S. Commercial Spent Nuclear Fuel Assembly Characteristics - 1968-2013

Activities related to management of spent nuclear fuel (SNF) are increasing in the US and many other countries. Over 240,000 SNF assemblies have been discharged from US commercial reactors since the late 1960s. The enrichment and burnup of SNF have changed significantly over the past 40 years, and fuel assembly designs have also evolved. Understanding the general characteristics of SNF helps regulators and other stakeholders form overall strategies towards the final disposal of US SNF. This report documents a survey of all US commercial SNF assemblies in the GC-859 database and provides reference SNF source terms (e.g., nuclide inventories, decay heat, and neutron/photon emission) at various cooling times up to 200 years after fuel discharge. This study reviews the distribution and evolution of fuel parameters of all SNF assemblies discharged over the past 40 years. Assemblies were categorized into three groups based on discharge year, and the median burnups and enrichments of each group were used to establish representative cases. An extended burnup case was created for boiling water reactor (BWR) fuels, and another was created for the pressurized water reactor (PWR) fuels. Two additional cases were developed to represent the eight mixed oxide (MOX) fuel assemblies in the database. Burnup calculations were performed for each representative case. Realistic parameters for fuel design and operations were used to model the SNF and to provide reference fuel characteristics representative of the current inventory. Burnup calculations were performed using the ORIGEN code, which is part of the SCALE nuclear modeling and simulation code system. Results include total activity, decay heat, photon emission, neutron flux, gamma heat, and plutonium content, as well as concentrations for 115 significant nuclides. These quantities are important in the design, regulation, and operations of SNF storage, transportation, and disposal systems.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Demand Response Availability Profiles for California in the Year 2020

Demand response (DR) is being considered as a valuable resource for keeping the electrical grid stable and efficient, and deferring upgrades to generation, transmission, and distribution systems. However, simulations to determine how much infrastructure upgrades can be deferred are necessary in order to plan optimally. Production cost modeling is a technique, which simulates the dispatch of generators to meet demand and reserves in each hour of the year, at minimal cost. By integrating demand response resources into a production cost model (PCM), their value to the grid can be estimated and used to inform operations and infrastructure planning. DR availability profiles and constraints for 13 end-uses in California for the year 2020 were developed by Lawrence Berkeley National Laboratory (LBNL), and integrated into a production cost model by Lawrence Livermore National Laboratory (LLNL), for the California Energy Commission’s Value of Energy Storage and Demand Response for Renewable Integration in California Study. This report summarizes the process for developing the DR availability profiles for California, and their aggregate capabilities. While LBNL provided potential DR hourly profiles for regulation product in the ancillary services market and five-minute load following product in the energy market for LLNL’s study, additional results in contingency reserves and an assumed flexible product are also defined. These additional products are included in the analysis for managing high ramps associated with renewable generation and capacity products and they are also presented in this report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CFD-DEM Onset of Motion Analysis for Application to Bed Scour Risk Assessment

This CFD study with DEM was done as a part of the Federal Highway Administration’s (FHWA’s) effort to improve scour design procedures. The Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) model, available in CD-Adapco’s StarCCM+ software, was used to simulate multiphase systems, mainly those which combine fluids and solids. In this method the motion of discrete solids is accounted for by DEM, which applies Newton's laws of motion to every particle. The flow of the fluid is determined by the local averaged Navier–Stokes equations that can be solved using the traditional CFD approach. The interactions between the fluid phase and solids phase are modeled by use of Newton's third law. The inter-particle contact forces are included in the equations of motion. Soft-particle formulation is used, which allows particles to overlap. In this study DEM was used to model separate sediment grains and spherical particles laying on the bed with the aim to analyze their movement due to flow conditions. Critical shear stress causing the incipient movement of the sediment was established and compared to the available experimental data. An example of scour around a cylindrical pier is considered. Various depths of the scoured bed and flow conditions were taken into account to gain a better understanding of the erosion forces existing around bridge foundations. The decay of these forces with increasing scour depth was quantified with a ‘decay function’, which shows that particles become increasingly less likely to be set in motion by flow forces as a scour hole increases in depth. Computational and experimental examples of the scoured bed around a cylindrical pier are presented.

97 MATHEMATICS AND COMPUTING↗