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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

CLUST - EVAP Monte Carlo Simulation Applications for Determining Effective Energy Deposition in Silicon by High Energy Protons

The CLUST-EVAP is a Monte Carlo simulation of the interaction of high energy (25 - 400 MeV) protons with silicon nuclei. The initial nuclear cascade stage is modeled using the CLUST model developed by Indiana University over 30 years ago. The second stage, in which the excited nucleus evaporates particles in random directions, is modeled according to the evaporation algorithm provided by H. H. K. Tang of IBM. Using the CLUST-EVAP code to model fragment produ6tion and the Vavilov-Landau theory to model fluctuations in direct ionization in thin silicon layers, we have predicted energy deposition in silicon components for various geometrical configurations. We have compared actual measurements with model predictions for geometry's such as single, thin silicon particle detectors, telescopic particle detectors flown in space to measure the environment, and thin sensitive volumes of modern micro-electronic components. We have recently compared the model predictions with actual measurements made by the DOSTEL spectrometer flown in the Shuttle payload bay on STS-84. The model faithfully reproduces the features and aids in interpretation of flight results of this instrument. We have also applied the CLUST-EVAP model to determine energy deposition in the thin sensitive volumes of modern micro-electronic components. We have accessed the ability of high energy (200 MeV) protons to induce latch-up in certain devices that are known to latch up in heavy ion environments. However, some devices are not nearly as susceptible to proton induced latch-up as expected according to their measured heavy ion latch-up cross sections. The discrepancy is believed to be caused by the limited range of the proton-silicon interaction fragments. The CLUST-EV AP model was used to determine a distribution of these fragments and their range and this is compared to knowledge of the ranges required based on the known device structure. This information is especially useful in accessing the risk to on-orbit perfonnance in a heavy ion environment based on testing performed with only protons.

ONeill, Pat M.↗
DOE OSTI2015

LESSONS FROM NUCLEAR ENERGY: BUILDING SNOW AND AVALANCHE SIMULATION TOOLS USING A COMMON OPEN-SOURCE FRAMEWORK

The Department of Energy (DOE) is currently investing millions of dollars annually into various modeling and simulation tools for all aspects of nuclear energy. An important part of this effort includes developing applications based on the open-source Multiphysics Object Oriented Simulation Environment (MOOSE; mooseframework.org) from Idaho National Laboratory (INL). Through the DOE and outside collaborators, MOOSE includes a large set of physics modules, including phase field, level set, heat conduction, tensor mechanics, Navier-Stokes, and porous media, among others. The phase-field module, in particular, is well-suited for micro-structure evolution simulations, including solidification, as shown in the figure. It was also used, in conjunction with the heat conduction module, to build a multiscale snow model (Pika) as presented at the 2014 International Snow Science Workshop (Slaughter et al., 2014). The snow science community should learn from the nuclear industry, and harness the enormous effort underway to build simulation tools that are open, modular, and share a common framework. In particular, MOOSE-based multi-physics solvers are inherently parallel, dimension agnostic, adaptive in time and space, fully-coupled, and capable of interacting with other applications. The snow science community must build on existing tools to enable collaboration between researchers and practitioners throughout the world, and advance the state-of-the-art in line with other scientific research efforts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Vehicle energy consumption estimation using large scale simulations and machine learning methods

Vehicle energy consumption and powertrain operations for future vehicle powertrain technologies are predicted through full-vehicle simulations using Autonomie, a simulation tool developed at Argonne National Laboratory. Over 1 million vehicles, with different powertrain types (conventional and numerous electrified powertrains) and component technologies (advanced engines, batteries, electrical machines, light weighting) are simulated for outputs including vehicle fuel economy and cost. Despite the ability of Autonomic to predict fuel economy given various combination of vehicle inputs, the full-vehicle simulation is very time-consuming. It takes approximately 84 h to simulate for 33,060 vehicles even using distributed computing on a cluster of 128 worker nodes. Moreover, Autonomic is unable to populate a continuous output space through simulation since it only yields outputs with discrete values instead of an input-output relation. This paper proposes a novel large-scale learning and prediction process (LSLPP) via machine learning approaches to answer the need for a continuous space of vehicle fuel economy and a more efficient simulation process. By learning in a supervised fashion to discover structures in data, the machine learning approaches seek to train a model that can explain the data with which we can perform prediction over unseen data. As such, we are able to accomplish analytic continuation on the current discrete space of simulation results. In addition, we present a random sampling -based numerosity reduction algorithm incorporated in LSLPP that reduces simulation runs and improves efficiency of data procurement. We analytically derive a theoretical bound in order to guarantee the effectiveness of our algorithm. We also compare random sampling to stratified sampling and suggest sampling strategies. A user-friendly tool is developed to support the process. Our experimental results confirm that the proposed LSLPP is able to greatly accelerate prediction and analysis of vehicle fuel economy. The output of this study is used by the US government to evaluate the impact of its R&D funding on energy security and CO 2 emission as well as for the setting of Corporate Average Fuel Economy (CAFE) standards.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Modeling of In-stream Tidal Energy Development and its Potential Effects in Tacoma Narrows, Washington, USA

Understanding and providing proactive information on the potential for tidal energy projects to cause changes to the physical system and to key water quality constituents in tidal waters is a necessary and cost-effective means to avoid costly regulatory involvement and late stage surprises in the permitting process. This paper presents a modeling study for evaluating the tidal energy extraction and its potential impacts on the marine environment in a real world site - Tacoma Narrows of Puget Sound, Washington State, USA. An unstructured-grid coastal ocean model, fitted with a module that simulates tidal energy devices, was applied to simulate the tidal energy extracted by different turbine array configurations and the potential effects of the extraction at local and system-wide scales in Tacoma Narrows and South Puget Sound. Model results demonstrated the advantage of an unstructured-grid model for simulating the far-field effects of tidal energy extraction in a large model domain, as well as assessing the near-field effect using a fine grid resolution near the tidal turbines. The outcome shows that a realistic near-term deployment scenario extracts a very small fraction of the total tidal energy in the system and that system wide environmental effects are not likely; however, near-field effects on the flow field and bed shear stress in the area of tidal turbine farm are more likely. Model results also indicate that from a practical standpoint, hydrodynamic or water quality effects are not likely to be the limiting factor for development of large commercial-scale tidal farms. Results indicate that very high numbers of turbines are required to significantly alter the tidal system; limitations on marine space or other environmental concerns are likely to be reached before reaching these deployment levels. These findings show that important information obtained from numerical modeling can be used to inform regulatory and policy processes for tidal energy development.

Yang, Zhaoqing↗
DOE OSTI2016

Ensuring Workforce Readiness for the Energy Industry Through 3D Simulations

In February 2009, during his joint address to Congress, President Obama challenged every American to commit to at least one year of college education and set a goal that the United States should once again have the highest proportion of college graduates in the world by the year 2020. This push by the Obama administration reflected the understanding that while a college degree was becoming a prerequisite to obtain many of the jobs in the 21. century economy; the United States still lagged behind other countries with respect to higher education attainment. Because of this, the U.S. is facing a skills gap between the credentials required for the jobs of today and tomorrow, and the number of skilled workers eligible to fill those jobs. Within the energy industry, the skills gap is compounded by two factors: an expanding domestic industry in energy generation and transmission, and an aging workforce set to retire in large numbers. In fact, a 2013 survey administered by Center for Energy Workforce Development (CEWD) estimates that 36% of the workforce may need to be replaced in the next five years, and nearly 50% will need to be replaced by the year 2023. As a 2014 report by CEWD notes, 'The message for workforce development is clear: qualified and skilled utility technicians and engineers will continue to be in high demand in all types of energy generation, transmission, and distribution jobs'. Simulations provide students the ability to practice proper procedure in a safe environment, test out multiple scenarios to determine an optimal outcome, and repeat practice to solidify learning. Industry currently applies simulation (i.e., 3D Electrical Substation Simulation) as it affords an opportunity for technicians to train in a safe, virtual environment, thus eliminating risks associated with arc flash hazards. The intent of 3D simulation is to enhance the students' understanding of the concepts learned in the course and better prepare students for field work in a related technical discipline. The 3D simulation will reinforce the concepts learned during a specific course and are intended to add real world context to the curriculum. The 3D simulation will be designed such that a student will perform specific job activities incorporating concepts learned during the course. This method of instruction ensures students have an understanding of the concepts and are able to apply the concepts in a real world context. Different scenarios will be developed to ensure a thorough understanding of the concepts with real time feedback when there is a misunderstanding of the concepts. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the U.S. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is calculated based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity and solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can isolate and adjust for the impacts of local climate for asset rating.

Asset Rating↗
DOE OSTI2015

Monte-Carlo Simulations of the Nuclear Energy Deposition Inside the CARMEN-1P Differential Calorimeter Irradiated into OSIRIS Reactor

The nuclear heating measurements in Material Testing Reactors (MTRs) are crucial for the study of nuclear materials and fuels under irradiation. The reference measurements of this nuclear heating are especially performed by a differential calorimeter including a graphite sample material. These measurements are then used for other experimental conditions in order to predict the nuclear heating and thermal conditions induced in the irradiation devices. Nuclear heating is a great deal of interest at the moment as the measurement of such heating is an important issue for MTRs reactors. This need is especially generated by the new Jules Horowitz Reactor (JHR), under construction at CEA/Cadarache 'French Alternative Energies and Atomic Energy Commission'. This new reactor, that will be operational in late 2019, is a new facility for the nuclear research on materials and fuels. Indeed the expected nuclear heating rate is about 20 W/g for nominal capacity of 100 MW. The present Monte Carlo calculation works belong to the IN-CORE (Instrumentation for Nuclear radiation and Calorimetry On line in Reactor): a joint research program between the CEA and Aix- Marseille University in 2009. One scientific aim of this program is to design and develop a multi-sensors device, called CARMEN, dedicated to the measurements of main physical parameters simultaneously encountered inside JHR's experimental channels (core and reflector) such as neutron fluxes, photon fluxes, temperature, and nuclear heating. A first prototype was already developed. This prototype includes two mock-ups dedicated respectively to neutronic measurements (CARMEN-1N) and to photonic measurements (CARMEN-1P) with in particular a specific differential calorimeter. Two irradiation campaigns were performed successfully in the periphery of OSIRIS reactor (a MTR located at Saclay, France) in 2012 for nuclear heating levels up to 2 W/g. First Monte Carlo calculations reduced to the graphite sample of the calorimeter were carried out. A preliminary analysis shows that the numerical results overestimate the measurements by about 20 %. A new approach has been developed in order to estimate the nuclear heating by two methods (energy deposition or KERMA) by considering the whole complete geometry of the sensor. This new approach will contribute to the interpretation of the irradiation campaign and will be useful to improve the out-of-pile calibration procedure of the sensor and its thermal response during irradiations. The aim of this paper is to present simulations made by using MCNP5 Monte-Carlo transport code (using ENDF/B-VI nuclear data library) for the nuclear heating inside the different parts of the calorimeter (head, rod and base). Calculations into two steps will be realized. We will use as an input source in the model new spectra (neutrons, prompt-photons and delayed-photons) calculated with the Monte Carlo code TRIPOLI-4{sup R} inside different experimental channels (water) located into the OSIRIS periphery and used during the CARMEN-1P irradiation campaign. We will consider Neutrons- Photons-Electrons and Photons-Electrons modes. We will begin by a brief description of the differential-calorimeter device geometry. Then the MCNP5 model used for the calculations of nuclear heating inside the calorimeter elements will be introduced. The energy deposition due to the prompt-gamma, delayed-gamma and neutrons, the neutron-activation of the device will be considered. The different components of the nuclear heating inside the different parts of the calorimeter will be detailed. Moreover, a comparison between KERMA and nuclear energy deposition estimations will be given. Finally, a comparison between this total nuclear heating Calculation and Experiment in graphite sample will be determined. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

WINS. Market Simulation Tool for Facilitating Wind Energy Integration

Integrating 20% or more wind energy into the system and transmitting large sums of wind energy over long distances will require a decision making capability that can handle very large scale power systems with tens of thousands of buses and lines. There is a need to explore innovative analytical and implementation solutions for continuing reliable operations with the most economical integration of additional wind energy in power systems. A number of wind integration solution paths involve the adoption of new operating policies, dynamic scheduling of wind power across interties, pooling integration services, and adopting new transmission scheduling practices. Such practices can be examined by the decision tool developed by this project. This project developed a very efficient decision tool called Wind INtegration Simulator (WINS) and applied WINS to facilitate wind energy integration studies. WINS focused on augmenting the existing power utility capabilities to support collaborative planning, analysis, and wind integration project implementations. WINS also had the capability of simulating energy storage facilities so that feasibility studies of integrated wind energy system applications can be performed for systems with high wind energy penetrations. The development of WINS represents a major expansion of a very efficient decision tool called POwer Market Simulator (POMS), which was developed by IIT and has been used extensively for power system studies for decades. Specifically, WINS provides the following superiorities; (1) An integrated framework is included in WINS for the comprehensive modeling of DC transmission configurations, including mono-pole, bi-pole, tri-pole, back-to-back, and multi-terminal connection, as well as AC/DC converter models including current source converters (CSC) and voltage source converters (VSC); (2) An existing shortcoming of traditional decision tools for wind integration is the limited availability of user interface, i.e., decision results are often text-based demonstrations. WINS includes a powerful visualization tool and user interface capability for transmission analyses, planning, and assessment, which will be of great interest to power market participants, power system planners and operators, and state and federal regulatory entities; and (3) WINS can handle extended transmission models for wind integration studies. WINS models include limitations on transmission flow as well as bus voltage for analyzing power system states. The existing decision tools often consider transmission flow constraints (dc power flow) alone which could result in the over-utilization of existing resources when analyzing wind integration. WINS can be used to assist power market participants including transmission companies, independent system operators, power system operators in vertically integrated utilities, wind energy developers, and regulatory agencies to analyze economics, security, and reliability of various options for wind integration including transmission upgrades and the planning of new transmission facilities. WINS can also be used by industry for the offline training of reliability and operation personnel when analyzing wind integration uncertainties, identifying critical spots in power system operation, analyzing power system vulnerabilities, and providing credible decisions for examining operation and planning options for wind integration. Researches in this project on wind integration included (1) Development of WINS; (2) Transmission Congestion Analysis in the Eastern Interconnection; (3) Analysis of 2030 Large-Scale Wind Energy Integration in the Eastern Interconnection; (4) Large-scale Analysis of 2018 Wind Energy Integration in the Eastern U.S. Interconnection. The research resulted in 33 papers, 9 presentations, 9 PhD degrees, 4 MS degrees, and 7 awards. The education activities in this project on wind energy included (1) Wind Energy Training Facility Development; (2) Wind Energy Course Development.

17 WIND ENERGY↗
DOE OSTI2014

Modeling a thermionic energy converter using finite-difference time-domain particle-in-cell simulations

A thermionic energy converter (TEC) is a static device that converts heat directly into electricity by boiling electrons off a hot emitter surface across a small inter-electrode gap to a cooler collector surface. The main challenge in TECs is overcoming the space charge limit, which limits the current transmitted across a gap of a given voltage and width. We have verified the feasibility of studying and developing a TEC using a bounded finite-difference time-domain particle-in-cell plasma simulation code, OOPD1, developed by Plasma Theory and Simulation Group, formerly at UC Berkeley and now at Michigan State University. In this preliminary work, a TEC has been modeled kinetically using OOPD1, and the accuracy has been verified by comparing with an analytically solvable case, giving good agreement. With further improvement of the code, one will be able to quickly and cheaply analyze space charge effects, and seek designs that mitigate the space charge effect, allowing TECs to become more efficient and cost-effective.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Energy-Efficient and Resilient Infrastructure: Simulation, Validation, and Installation

Advanced, high-performance computing at the National Renewable Energy Laboratory (NREL) has enabled access to vast data resources with cutting-edge software techniques to understand, design, plan for, and maintain energy-efficient and resilient infrastructure. We have focused on cities and airports, but the technology we have developed will easily translate to seaports, inland ports, military installations, or other complex and large-scale energy-intensive systems. We can digitally simulate and explore current and future scenarios to make datadriven decisions for optimizing advanced energy systems, transportation and building operations, infrastructure planning and expansion, and battery storage to guide short- and long-term investments, electrification strategies, and integration of new technologies.

Athena↗
DOE OSTI2021

Transmission-and-Distribution Dynamic Co-simulation Framework for Distributed Energy Resource Frequency Response

The rapid deployment of distributed energy resources (DERs) in distribution networks has made it challenging to balance the transmission system and stabilize frequency. DERs have the ability to provide frequency regulation services; however, existing frequency dynamic simulation tools - which were developed mainly for the transmission system - lack the capability to simulate distribution network dynamics with high penetrations of DERs. Although electromagnetic transient simulation tools can simulate distribution network dynamics, the computation efficiency limits their use for large-scale transmission-and-distribution (T&D) co-simulation. This paper presents an efficient open-source T&D dynamic co-simulation framework for DER frequency response based on the HELICS platform and off-the-shelf T&D simulators. The challenge of synchronizing the simulation time between the transmission network and the DERs in the distribution network is solved through the detailed modeling of DERs in frequency dynamic models while DER power flow models are also preserved in the distribution networks, thereby respecting local voltage constraints when dispatching DER power for frequency response. DER frequency response (primary and secondary) is simulated in case studies to validate the proposed framework. Last, the accuracy of the proposed co-simulation model is benchmarked, and a large T&D system simulation (2k transmission and 1M distribution nodes) is presented to demonstrate the efficiency and effectiveness of the overall framework.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

RADIO SYNCHROTRON EMISSION FROM A BOW SHOCK AROUND THE GAS CLOUD G2 HEADING TOWARD THE GALACTIC CENTER

A dense ionized cloud of gas has been recently discovered to be moving directly toward the supermassive black hole, Sgr A*, at the Galactic center. In 2013 June, at the pericenter of its highly eccentric orbit, the cloud will be approximately 3100 Schwarzschild radii from the black hole and will move supersonically through the ambient hot gas with a velocity of v{sub p} Almost-Equal-To 5400 km s{sup -1}. A bow shock is likely to form in front of the cloud and could accelerate electrons to relativistic energies. We estimate via particle-in-cell simulations the energy distribution of the accelerated electrons and show that the non-thermal synchrotron emission from these electrons might exceed the quiescent radio emission from Sgr A* by a factor of several. The enhanced radio emission should be detectable at GHz and higher frequencies around the time of pericentric passage and in the following months. The bow shock emission is expected to be displaced from the quiescent radio emission of Sgr A* by {approx}33 mas. Interferometric observations could resolve potential changes in the radio image of Sgr A* at wavelengths {approx}< 6 cm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Inclusion Capture Probability Prediction Model for Bubble Floatation in Turbulent Steel Flow

The turbulent flow around bubbles is simulated for the fixed turbulent kinetic energy. Inclusion motion through the flow field is studied by considering the stochastic effect of turbulence to calculate the capture probability of inclusions with different sizes to a fixed-size individual bubble according to the redefinition. Using the cubic spline interpolation, the capture probability is predicted as functions of the bubble size, inclusion size and turbulent kinetic energy.

36 MATERIALS SCIENCE↗