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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 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

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↗
DOE OSTI2017

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↗
DOE OSTI2022

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↗
DOE OSTI2025

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]↗
DOE OSTI2014

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↗
DOE OSTI2014

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↗
DOE OSTI2015

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↗
DOE OSTI2016

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↗
DOE OSTI2014

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↗
DOE OSTI2017

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↗
DOE OSTI2017

COHO - Utilizing Waste Heat and Carbon Dioxide at Power Plants for Water Treatment

The COHO is a breakthrough water purification system that can concentrate challenging feed waters using carbon dioxide and low-grade heat. For this project, we studied feeds in a lab-scale system to simulate COHO’s potential to operate at coal- powered power plants. COHO proved successful at concentrating the highly scaling and challenging wastewaters derived from a power plant’s cooling towers and flue gas desulfurization units. We also found that COHO was successful at scrubbing carbon dioxide from flue gas mixtures. Thermal regeneration of the switchable polarity solvent forward osmosis draw solution ended up requiring higher temperatures than initially anticipated, but we also found that the draw solution could be polished via reverse osmosis. A techno-economic analysis indicates that installation of a COHO at a power plant for wastewater treatment would result in significant savings.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Auxiliary-Field Quantum Monte Carlo Simulations of Strongly-Correlated Systems, the Final Report

In this final report, we present preliminary results of ground state phases of interacting spinless Dirac fermions. The name "Dirac fermion" originates from the fact that low-energy excitations of electrons hopping on the honeycomb lattice are described by a relativistic Dirac equation. Dirac fermions have received much attention particularly after the seminal work of Haldale1 which shows that the quantum Hall physics can be realized on the honeycomb lattice without magnetic fields. Haldane's work later becomes the foundation of topological insulators (TIs). While the physics of TIs is based largely on spin-orbit coupled non-interacting electrons, it was conjectured that topological insulators can be induced by strong correlations alone.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

DiaMonD: An Integrated Multifaceted Approach to Mathematics at the Interfaces of Data, Models, and Decisions

The major goal of the project was to invent, analyze, implement, and apply new algorithms to speed up the computational simulation of complex systems in settings in which multiple simulations are needed. The main efforts we undertook are as follows: 1. Develop novel reduced order methods to reduce the costs of simulations, especially in settings (e.g., UQ, inference, optimization and control) for which numerous simulation are needed and also for nonlocal problems (e.g., fractional derivative, anomalous diffusion, nonlocal mechanics) for which lack of sparsity results in more expensive full-order simulation than encountered in partial differential equations settings; rigorous analyses as well as computational tests were carried out, 2. Develop multifidelity methods based on the usage of a variety of models having different fidelities and different costs to accelerate simulations again in settings where numerous simulations are needed or are especially expensive; rigorous analyses as well as computational tests were carried out, 3. Develop ensemble methods to reduced the costs of simulations again in settings where numerous simulations are needed or are especially expensive; rigorous analyses as well as computational tests were carried out, and 4. Analyze a model for Richardson pair dispersion in turbulent flows and develop discretization methods for the efficient and accurate approximations of the solution of the model; rigorous analyses as well as computational tests were carried out.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Time Series Dimension Reduction for Surrogate Models of Port Scanning Cyber Emulations

Surrogate model development is a key resource in the scientific modeling community for providing computational expedience when simulating complex systems without loss of great fidelity. The initial step to development of a surrogate model is identification of the primary governing components of the system. Principal component analysis (PCA) is a widely used data science technique that provides inspection of such driving factors, when the objective for modeling is to capture the greatest sources of variance inherent to a dataset. Although an efficient linear dimension reduction tool, PCA makes the fundamental assumption that the data is continuous and normally distributed. Thus, it provides ideal performance when these conditions are met. In the case for which cyber emulations provide realizations of a port scanning scenario, the data to be modeled follows a discrete time series function comprised of monotonically increasing piece-wise constant steps. The sources of variance are related to the timing and magnitude of these steps. Therefore, we consider using XPCA, an extension to PCA for continuous and discrete random variates. This report provides the documentation of the trade-offs between the PCA and XPCA linear dimension reduction algorithms, for the intended purpose to identify key components of greatest variance in our time series data. These components will ultimately provide the basis for future surrogate models of port scanning cyber emulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Radiation Transport Simulation of the Sulfur Counting System in the Radiation Metrology Laboratory (RML)

At the request of staff members from the Radiation Metrology Laboratory (RML), a series of Monte Carlo radiation transport calculations were performed using two different models of the detector geometry of the RMLs sulfur counting system. The fraction of electrons from each β-decay of 32 P in the sulfur pellet that enter the window of the sulfur counting system was calculated with both MCNP and ITS. In addition, the differential energy distributions of the electrons entering the counting system window were computed. There was significant agreement between the integral and differential quantities calculated by the two transport codes. Summary tables are for the integral efficiency values are found in the body of the report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Scalable/Secure Cooperative Algorithms and Framework for Extremely-high Penetration Solar Integration (SolarExPert) (Final Technical Report)

This SolarExPert project has developed a Sustainable Grid Platform (SGP) with scalable architecture of distributed control and optimization. The SGP consists of the following major functions: 1) an advanced grid architecture with hierarchical and distributed communication and control, combined with the OpenFMB standard and implemented on the Multi-Agent OpenDSS (MA-OpenDSS) platform; 2) an online distributed stochastic optimal power flow; 3) an online distributed system state estimation algorithm; 4) the distributed Volt/VAR optimization and frequency control algorithms; 5) the distributed distribution system restoration strategy. The developed SGP together with advanced functions are tested in 1 million (1M)-node distribution system on the MA-OpenDSS platform. Furthermore, the models and algorithms are tested in 100,000-node system HiL simulation, and also in P-HiL implementation with 100 physical devices. The developed functions haven been validated and tested on the selected actual distribution feeder with the data collected from the field of Maui Meadows in Hawaii. The distributed PV hosting capacities with cooperative Volt/VAR and Volt/VAR/Watt control are estimated and compared to provide recommendations for customers and the utility company.

14 SOLAR ENERGY↗
DOE OSTI2019

O(N) Quantum Molecular Dynamics (QMD) Algorithms, Code Requirements, Release Notes, and Library Deployment

The Exascale Computing Project (ECP) Co-design Center for Particle Applications (CoPA) is addressing the challenges for particle applications to run on upcoming exascale computing architectures. This includes short- and long-range molecular dynamics (MD), particle-in-cell (PIC), and quantum molecular dynamics (QMD). This document addresses $\mathcal{O}(N)$ QMD. The goal of this CoPA team is to develop $\mathcal{O}(N)$ linear scaling methods for QMD optimized for new and next generation architectures. This will provide the capability to simulate larger systems and run for longer timeframes than is possible today. Focus is initially on the density matrix construction. This requires efficient matrix formats and linear algebra operations for distributed architectures. A significant reduction in the wallclock time for an MD timestep is necessary to achieve practical large scale QMD. Equally challenging is to develop scalable distributed implementations. This requires the exploration of efficient data formats (dense, sparse, etc.), data decomposition and distribution across compute nodes using block- and graph-based methods. Traditional programming models such as MPI/OpenMP, hybrid MPI/OpenMP/Accelerator, as well as asynchronous task-based models will be explored to achieve maximum parallelism. Parallelism at the level of a matrix operation, solver, and/or application needs to be explored to gain the most benefit on new and emerging architectures. This report serves as a “living document” of the additions and enhancements throughout the ECP CoPA project for $\mathcal{O}(N)$ QMD. The following sections address the applications we are working with, the quantum chemistry libraries (BML and PROGRESS), and our co-design exploration through the use of a proxy application.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Illinois Compressed Air Energy Storage

Compressed Air Storage Energy (CAES) is one of the few mid- technology readiness level (TRL) energy storage technologies that can address the long-duration infrastructure needed for dealing with variable electric output from renewable energy sources and be reliable backup source for replacing natural gas during supply interruptions. In CAES the goal is to capture and store compressed air in subsurface sedimentary strata when off-peak power is available, or there is a need for grid balancing. The stored high-pressure air is returned to the surface and used to power turbines during reductions in either renewable energy or supply issues with fossil fuels. The Illinois CAES project evaluates the feasibility of capturing surplus electrical energy from renewable sources and off-peak energy at a fossil fuel power plant at the University of Illinois Urbana - Champaign (UIUC) campus. The UIUC Abbott Power Plant uses natural gas and coal to generate electricity (capacity: 35 MWe by coal and 49 MWe by NG). UIUC receives additional electricity from on campus solar farm, and off-campus wind farm. Also, UIUC offsets electricity usage by integrating geothermal energy systems into building heating Also, UIUC offsets steam, hot and chilled water usage by integrating geothermal energy systems into building heating and cooling systems. Furthermore, the two UIUC solar farms (Solar Farm 1 is 21 acres and Solar Farm 2 is 54 acres) to generate 4.68 megawatts (MW) and 12.1 MW, respectively. Campus receives 8.6% of the wind-generated electricity from the Rail Splitter Wind Farm. The project objectives were to design an integrated system to 1) capture surplus electrical energy from renewable sources and the Abbott Power Plant using a CAES system, 2) store both the compressed air and the thermal heat generated by compression in the subsurface as part of an adiabatic system, 3) simulate the movement of the air and heat in the subsurface, 4) recover the compressed air and stored thermal heat to rotate turbine generators during sustained interruption due to weather events or fossil fuel disruptions.

03 NATURAL GAS↗