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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Investigations of vertical wind variations at a mountain top in the Himalaya using Doppler Lidar observations and model simulations

Hight-resolved observations of vertical winds remain nearly non-existing over the Himalayas, despite of an­ticipated crucial role of vertical motions in transporting pollution across the Himalayan hms. The present study analyze the vertical wind observations from surface to 1 km above ground level over Manora Peak (29.4° N; 79.5° E; 1958 m ams!) in the Himalaya performed using a Doppler Lidar during the Ganges Valley Aerosol Experiment (GVAX). Vertical wind exhibited a pronounced diurnal variability at Manora Peak comprising of upward motions during the daytime (05-10 UT) and downward motions during nighttime typical of a mountain­valley system. Mean vertical wind speeds are observed to be varying from -0.8 to +0.8 ms- 1 during the study period with a variance of 0.1-1.5 m2s·2, which is attributed to the thermally driven turbulence. Mean vertical winds are observed to be stronger in the Doppler Lidar profiles above Manora Peak (-0_8 to 0.8 ms- 1) as compared to near surface measurements at this station using an ultrasonic anemometer ( -0.4 to 0.4 ms - 1 ), and low altitude stations in India. Daytime vertical wind speeds are observed to be higher during pre-monsoon (0.81 ms- 1), as compared to post-monsoon (0.24 ms- 1) and winter (0.33 ms- 1)_ Average Black Carbon (BC) concentrations are significantly higher during strong upward vertical winds, which indicates efficient transport of polluted air mass from low-altitude regions to the Himalaya. Weather Research and Forecasting (WRF) model reproduces the observed diurnal pattern in the vertical wind at the observation site however the model un­derestimates the variability.

Shukla, K K.↗
DOE OSTI2017

Conceptual Modeling Framework for E-Area PA HELP Infiltration Model Simulations

A conceptual modeling framework based on the proposed E-Area Low-Level Waste Facility (LLWF) closure cap design is presented for conducting Hydrologic Evaluation of Landfill Performance (HELP) model simulations of intact and subsided cap infiltration scenarios for the next E-Area Performance Assessment (PA).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

PSH Transient Simulation Modeling

PSH Transient Simulation Modeling presentation from the WPTO FY14 - FY16 Peer Review. Transient effects are an important consideration when designing a PSH system, yet numerical techniques for hydraulic transient analysis still need improvements for adjustable-speed (AS) reversible pump-turbine applications.

13 HYDRO ENERGY↗
DOE OSTI2022

How Can Construction Process Simulation Modeling Aid the Integration of Lean Principles in the Factory-Built Housing Industry?

New and existing factories that produce and deliver factory-built housing can benefit from construction process simulation modeling to explore the integration of Lean principles in their operations. Construction process simulation modeling provides digital or virtual recreations of the real-world factory environments to visualize, quantify, analyze, and optimize their underlying behavior, including factory productivity, material flow, labor dynamics, bottlenecks, and work scope. One of the key benefits of process simulation modeling is the ability to create and compare "what-if" scenarios, including integrating Lean principles such as reducing waste (for example, transportation, waiting), line balancing, and just-in-time concepts. In general, three process simulation methods are widely used: discrete event simulation (DES), agentbased modeling (ABM), and system dynamics (SD). Myriad process simulation software also is available, but depending on the industry, complexity of the system, and purposes of the simulation, some software might be more appropriate. Similar to how computer-aided design (CAD) software such as AutoCAD and Rhinoceros enable building design of modular or factory-built housing, process simulation modeling software such as jStrobe, ProModel, and AnyLogic can enable factory design of new and existing factories to deliver modular affordable housing at scale, as opposed to traditional site-built construction. Software with DES capabilities can help generate a process model that is a logical representation of resources and activities in a factory. Software with CAD-DES integration can leverage product-process data integration to help spatially visualize a DES model of the factory in the CAD environment. Software with multimethod simulation capabilities, widely used in the manufacturing industry, brings together DES, ABM, and SD in a single platform that allows visualization, quantification, analyses, and optimization at varying data fidelities. Near-real-time data from an existing factory can be directly plugged into multimethod simulation software so that the construction process simulation model is a near-accurate representation of the real-world factory conditions. This report provides insights into the use of simulation as an aid to integrate Lean concepts in factories, including guidelines for selecting the appropriate process simulation modeling method and software. These insights have been developed as part of ongoing process simulation modeling research, development, and demonstration projects at the U.S. Department of Housing and Urban Development, the U.S. Department of Energy, and the National Renewable Energy Laboratory focused on how process simulation models can enable better integration of resilience, energy efficiency, and low-carbon design strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Observationally constrained analysis of sulfur cycle in the marine atmosphere with NASA ATom measurements and AeroCom model simulations

The atmospheric sulfur cycle plays a key role in air quality, climate, and ecosystems, such as pollution, radiative forcing, new particle formation, and acid rain. In this study, we compare the spatially and temporally resolved measurements from the NASA Atmospheric Tomography (ATom) mission with simulations from five AeroCom III models for four sulfur species (dimethyl sulfide (DMS), sulfur dioxide (SO 2 ), particulate methanesulfonate (MSA), and particulate sulfate (SO 4 )). We focus on remote regions over the Pacific, Atlantic, and Southern oceans from near the surface to ~12 km altitude range covering all four seasons. In general, the differences among model results can be greater than 1 order of magnitude. Comparing with observations, model-simulated SO 2 is generally low, whereas SO 4 is generally high. Simulated DMS concentrations near the sea surface exceed observed levels by a factor of 5 in most cases, suggesting potential overestimation of DMS emissions in all models. With GEOS model simulations of tagging emission from anthropogenic, biomass burning, volcanic, and oceanic sources, we find that anthropogenic emissions are the dominant source of sulfate aerosol (40 %–60 % of the total amount) in the ATom measurements at almost all altitudes, followed by volcanic emissions (18 %–32 %) and oceanic sources (16 %–32 %). Similar source contributions can also be derived at broad ocean basins and on monthly scales, indicating the representativeness of ATom measurements for global ocean. Our work presents the first assessment of AeroCom sulfur study using ATom measurements, providing directions for improving sulfate simulations, which remain the largest uncertainty in radiative forcing estimates in aerosol climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

A Control-oriented Building Envelope and HVAC System Simulation Model for a Typical Large Office Building

To enable advanced controls research for buildings, in this paper we present a dynamic simulation model for a typical large office building. In this model, we utilized EnergyPlus for calculating the building thermal load and the Modelica HVAC equipment library to implement the dynamic behavior of the heating, ventilation, and air conditioning (HVAC) system. We utilized a functional mockup interface to enable the run-time communication between the EnergyPlus model and the Modelica model. This simulation model can be driven by control inputs from supervisory decision making algorithms and thus can be used as a virtual testbed for advanced controls development and evaluation. To demonstrate the usage of the model, we implemented two HVAC control sequences representative for large office buildings, both based on the ASHRAE standard. Simulation results allowed us to compare the energy performance associated with the two control strategies, and the evolution of the system dynamics at a high temporal granularity.

Huang, Sen↗
DOE OSTI2023

Model simulations of Plum Island Ecosystems LTER low marsh site using ELM-PFLOTRAN

Model simulations using the E3SM Land Model (ELM) coupled to the PFLOTRAN reactive transport model via the Alquimia interface. The simulations were conducted for a tidal salt marsh at the Plum Island Ecosystems LTER near Rowley, Massachusetts, USA. Model simulations were forced using site-specific tidal cycles and salinity, and the simulations used a biogeochemical reaction network including aerobic decomposition, sulfate reduction, iron reduction, and methanogenesis. Model outputs include simulated carbon stocks, carbon dioxide and methane fluxes, and porewater concentrations of key solutes related to sulfur, iron, and carbon cycling. The model simulations included a saline simulation (with tidal sulfate inputs), a fresh simulation (with low salinity and low sulfate inputs), and a saline simulation with lower vegetation productivity to represent the effect of salinity on vegetation. These simulations were conducted to demonstrate that a new model framework incorporating subsurface redox and biogeochemical interactions into a land surface model could reproduce measured surface greenhouse gas fluxes and biogeochemical dynamics in tidal marsh ecosystems, and to test whether including redox interactions in a land surface model would allow the model to resolve contrasts in biogeochemical cycling and greenhouse gas production between saline and freshwater wetlands.The data package includes gzipped tar archives (which can be expanded using standard tar and gzip utilities) of model outputs from three model configurations: saline subsurface and reduced vegetation productivity related to salinity; saline subsurface with vegetation productivity not reduced; and freshwater. Also included are code for the modified E3SM model, Alquimia interface, and PFLOTRAN reactive transport simulator in gzipped tar format; plain text parameter and configuration files; python code files for visualizing model output and defining model configurations; and model output, tide and salinity forcing, and configuration files in netCDF format. See the README.md file in the data package for a detailed description of all files contained in the package. All files are in netCDF (.nc), gzipped tar archive (.tar.gz or .tgz), or text (all other files).Updated: May 13, 2024. Model output, E3SM code, PFLOTRAN input files, and python codes for visualizing results were updated to reflect changes made for the manuscript revision. The updated archive reflects the code and model output from the final accepted manuscript. Changes included updated reaction parameters reflecting improved parameterization and additional comparisons with field measurements. E3SM code changes included better support for multiple grid cells and improved flow and transport parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Simulation of Subsurface Multiphase Contaminant Extraction Using a Bioslurping Well Model

Subsurface simulation of multiphase extraction from wells is notoriously difficult. Explicit representation of well geometry requires small grid resolution, potentially leading to large computational demands. To reduce the problem dimensionality, multiphase extraction is mostly modeled using vertically-averaged approaches. In this paper, a multiphase well model approach is presented as an alternative to simplify the application. The well model, a multiphase extension of the classic Peaceman model, has been implemented in the STOMP simulator. The numerical solution approach accounts for local conditions and gradients in the exchange of fluids between the well and the aquifer. Advantages of this well model implementation include the option to simulate the effects of well characteristics and operation. Simulations were conducted investigating the effects of extraction location, applied vacuum pressure, and a number of hydraulic properties. The obtained results were all consistent and logical. A major outcome of the test simulations is that, in contrast with common recommendations to extract from either the gas-NAPL or the NAPL-aqueous phase interface, the optimum extraction location should be in between these two levels. Further, the new model implementation was also used to simulate extraction at a field site in Brazil. The simulation shows a good match with the field data, suggesting that the new STOMP well module may correctly represent oil removal. The field simulations depend on the quality of the site conceptual model, including the porous media and contaminant properties and the boundary and extraction conditions adopted. The new module may potentially be used to design field applications and analyze extraction data.

42 ENGINEERING↗
DOE OSTI2016

MODELING THE Ly α FOREST IN COLLISIONLESS SIMULATIONS

Cosmological hydrodynamic simulations can accurately predict the properties of the intergalactic medium (IGM), but only under the condition of retaining the high spatial resolution necessary to resolve density fluctuations in the IGM. This resolution constraint prohibits simulating large volumes, such as those probed by BOSS and future surveys, like DESI and 4MOST. To overcome this limitation, we present “Iteratively Matched Statistics” (IMS), a novel method to accurately model the Ly α forest with collisionless N -body simulations, where the relevant density fluctuations are unresolved. We use a small-box, high-resolution hydrodynamic simulation to obtain the probability distribution function (PDF) and the power spectrum of the real-space Ly α forest flux. These two statistics are iteratively mapped onto a pseudo-flux field of an N -body simulation, which we construct from the matter density. We demonstrate that our method can reproduce the PDF, line of sight and 3D power spectra of the Ly α forest with good accuracy (7%, 4%, and 7% respectively). We quantify the performance of the commonly used Gaussian smoothing technique and show that it has significantly lower accuracy (20%–80%), especially for N -body simulations with achievable mean inter-particle separations in large-volume simulations. In addition, we show that IMS produces reasonable and smooth spectra, making it a powerful tool for modeling the IGM in large cosmological volumes and for producing realistic “mock” skies for Ly α forest surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Reward-Based Participant Management for Crowdsourcing Rainfall Monitoring: An Agent-Based Model Simulation

Crowdsourcing incorporates common citizens as rich sources of data and is promising for environmental monitoring. Here, we propose and test the idea of incorporating incentives to crowdsourcing management for rainfall monitoring. In particular, we model the allocation of incentives (quantitatively measurable and limited rewards) among crowdsourcing participants for a theoretical rainfall monitoring case. For this purpose, we develop an integrated model comprising a reward allocation component to represent the decision-making process of a central manager, an agent-based model to simulate the interactions between the manager and participants, and a rainfall simulation model to evaluate the effectiveness of various reward allocation policies. We simulate six reward allocation policies of varying levels of administrative cost, and consideration of participant and rainfall spatial heterogeneities. The findings indicate the performance of each policy to improve with the reward budget and their spatial uniformity. Among the six policies tested, we discover that the participant density weighted maximum participation policy yields the most accurate estimation of rainfall intensity due to its more explicit consideration of the spatial distribution of participants; however, this policy associates with a high administrative cost. This highlights the trade-off between performance and cost in designing effective reward allocation policies. This paper provides a physical and behavior simulation modeling tool to study the feasibility and complexity of reward-based participant management for crowdsourcing rainfall monitoring. The proposed crowdsourcing method is beneficial for a wide range of applications that require rainfall data with fine resolution, such as storm water management and water availability and biomass assessment for food and energy crops.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cognitive simulation models for inertial confinement fusion: Combining simulation and experimental data

The design space for inertial confinement fusion (ICF) experiments is vast, and experiments are extremely expensive. Researchers rely heavily on computer simulations to explore the design space in search of high-performing implosions. However, ICF multiphysics codes must make simplifying assumptions, and thus deviate from experimental measurements for complex implosions. For more effective design and investigation, simulations require input from past experimental data to better predict future performance. In this work, we describe a cognitive simulation method for combining simulation and experimental data into a common, predictive model. This method leverages a machine learning technique called “transfer learning,” the process of taking a model trained to solve one task, and partially retraining it on a sparse dataset to solve a different, but related task. In the context of ICF design, neural network models are trained on large simulation databases and partially retrained on experimental data, producing models that are far more accurate than simulations alone. Here, we demonstrate improved model performance for a range of ICF experiments at the National Ignition Facility and predict the outcome of recent experiments with less than 10% error for several key observables. We discuss how the methods might be used to carry out a data-driven experimental campaign to optimize performance, illustrating the key product—models that become increasingly accurate as data are acquired.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Predictive Maturity of Multi-Scale Simulation Models for Fuel Performance

The project proposed to provide a Predictive Maturity Framework with its companion metrics that (1) introduce a formalized, quantitative means to communicate information between interested parties, (2) provide scientifically dependable means to claim completion of Validation and Uncertainty Quantification (VU) activities, and (3) guide the decision makers in the allocation of Nuclear Energy’s resources for code development and physical experiments. The project team proposed to develop this framework based on two complimentary criteria: (1) the extent of experimental evidence available for the calibration of simulation models and (2) the sophistication of the physics incorporated in simulation models. The proposed framework is capable of quantifying the interaction between the required number of physical experiments and degree of physics sophistication. The project team has developed this framework and implemented it with a multi-scale model for simulating creep of a core reactor cladding. The multi-scale model is composed of the viscoplastic self-consistent (VPSC) code at the meso-scale, which represents the visco-plastic behavior and changing properties of a highly anisotropic material and a Finite Element (FE) code at the macro-scale to represent the elastic behavior and apply the loading. The framework developed takes advantage of the transparency provided by partitioned analysis, where independent constituent codes are coupled in an iterative manner. This transparency allows model developers to better understand and remedy the source of biases and uncertainties, whether they stem from the constituents or the coupling interface by exploiting separate-effect experiments conducted within the constituent domain and integral-effect experiments conducted within the full-system domain. The project team has implemented this procedure with the multi- scale VPSC-FE model and demonstrated its ability to improve the predictive capability of the model. Within this framework, the project team has focused on optimizing resource allocation for improving numerical models through further code development and experimentation. Related to further code development, we have developed a code prioritization index (CPI) for coupled numerical models. CPI is implemented to effectively improve the predictive capability of the coupled model by increasing the sophistication of constituent codes. In relation to designing new experiments, we investigated the information gained by the addition of each new experiment used for calibration and bias correction of a simulation model. Additionally, the variability of ‘information gain’ through the design domain has been investigated in order to identify the experiment settings where maximum information gain occurs and thus guide the experimenters in the selection of the experiment settings. This idea was extended to evaluate the information gain from each experiment can be improved by intelligently selecting the experiments, leading to the development of the Batch Sequential Design (BSD) technique. Additionally, we evaluated the importance of sufficiently exploring the domain of applicability in experiment-based validation of high-consequence modeling and simulation by developing a new metric to quantify coverage. This metric has also been incorporated into the design of new experiments. Finally, we have proposed a data-aware calibration approach for the calibration of numerical models. This new method considers the complexity of a numerical model (the number of parameters to be calibrated, parameter uncertainty, and form of the model) and seeks to identify the number of experiments necessary to calibrate the model based on the level of sophistication of the physics. The final component in the project team’s work to improve model calibration and validation methods is the incorporation of robustness to non-probabilistic uncertainty in the input parameters. This is an improvement to model validation and uncertainty quantification stemming beyond the originally proposed scope of the project. We have introduced a new metric for incorporating the concept of robustness into experiment-based validation of numerical models. This project has accounted for the graduation of two Ph.D. students (Kendra Van Buren and Josh Hegenderfer) and two M.S. students (Matthew Egeberg and Parker Shields). One of the doctoral students is now working in the nuclear engineering field and the other one is a post-doctoral fellow at the Los Alamos National Laboratory. Additionally, two more Ph.D. students (Garrison Stevens and Tunc Kulaksiz) who are working towards graduation have been supported by this project.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

The Water, Energy, and Carbon Dioxide Sequestration Simulation Model (WECSsim™): A User’s Manual

The Water, Energy, and Carbon Sequestration Simulation Model (WECSsim) is a national dynamic simulation model that calculates and assesses capturing, transporting, and storing CO 2 in deep saline formations from all coal and natural gas-fired power plants in the U.S. An overarching capability of WECSsim is to also account for simultaneous CO 2 injection and water extraction within the same geological saline formation. Extracting, treating, and using these saline waters to cool the power plant is one way to develop more value from using saline formations as CO 2 storage locations. WECSsim allows for both one-to-one comparisons of a single power plant to a single saline formation along with the ability to develop a national CO 2 storage supply curve and related national assessments for these formations. This report summarizes the scope, structure, and methodology of WECSsim along with a few key results. Developing WECSsim from a small scoping study to the full national-scale modeling effort took approximately 5 years. This report represents the culmination of that effort. The key findings from the WECSsim model indicate the U.S. has several decades' worth of storage for CO 2 in saline formations when managed appropriately. Competition for subsurface storage capacity, intrastate flows of CO 2 and water, and a supportive regulatory environment all play a key role as to the performance and cost profile across the range from a single power plant to all coal and natural gas-based plants' ability to store CO 2 . The overall system's cost to capture, transport, and store CO 2 for the national assessment range from $\$$74 to $\$$208 / tonne stored ($\$$96 to 272 / tonne avoided) for the first 25 to 50% of the 1126 power plants to between $\$$1,585 to well beyond $\$$2,000 / tonne stored ($\$$2,040 to well beyond $\$$2,000 / tonne avoided) for the remaining 75 to 100% of the plants. The latter range, while extremely large, includes all natural gas power plants in the U.S., many of which have an extremely low capacity factor and therefore relatively high system's cost to capture and store CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2016

A comprehensive simulation model of the performance of photochromic films in absorbance-modulation-optical-lithography

Optical lithography is the most prevalent method of fabricating micro-and nano-scale structures in the semiconductor industry due to the fact that patterning using photons is fast, accurate and provides high throughput. However, the resolution of this technique is inherently limited by the physical phenomenon of diffraction. Absorbance-Modulation-Optical Lithography (AMOL), a recently developed technique has been successfully demonstrated to be able to circumvent this diffraction limit. AMOL employs a dual-wavelength exposure system in conjunction with spectrally selective reversible photo-transitions in thin films of photochromic molecules to achieve patterning of features with sizes beyond the far-field diffraction limit. We have developed a finite-element-method based full-electromagnetic-wave solution model that simulates the photo-chemical processes that occur within the thin film of the photochromic molecules under illumination by the exposure and confining wavelengths in AMOL. This model allows us to understand how the material characteristics influence the confinement to sub-diffraction dimensions, of the transmitted point spread function (PSF) of the exposure wavelength inside the recording medium. The model reported here provides the most comprehensive analysis of the AMOL process to-date, and the results show that the most important factors that govern the process, are the polarization of the two beams, the ratio of the intensities of the two wavelengths, the relative absorption coefficients and the concentration of the photochromic species, the thickness of the photochromic layer and the quantum yields of the photoreactions at the two wavelengths. The aim of this work is to elucidate the requirements of AMOL in successfully circumventing the far-field diffraction limit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗