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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 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

A New Equivalence Theory Method for Treating Doubly Heterogeneous Fuel - II. Verifications

A new methodology has been developed recently to treat resonance self-shielding in systems for which the fuel compact region of a reactor lattice consists of small fuel grains dispersed in a graphite matrix. The theoretical development adopts equivalence theory in both micro- and macro-level heterogeneities to provide approximate analytical expressions for the shielded cross sections, which may be interpolated from a table of resonance integrals or Bondarenko factors using a modified background cross section as the interpolation parameter. This paper describes the first implementation of the theoretical equations in a reactor analysis code. In order to reduce discrepancies caused by use of the rational approximation for collision probabilities in the original derivation, a new formulation for a doubly heterogeneous Bell factor is developed in this paper to improve the accuracy of doubly heterogeneous expressions. This methodology is applied to a wide range of pin cell and assembly test problems with varying geometry parameters, material compositions, and temperatures, and the results are compared with continuous-energy Monte Carlo simulations to establish the accuracy and range of applicability of the new approach. It is shown that the new doubly heterogeneous self-shielding method including the Bell factor correction gives good agreement with reference Monte Carlo results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Geochemical Impacts of Leaking CO 2 from Subsurface Storage Reservoirs to Unconfined and Confined Aquifers

Experimental research work has been conducted and is undergoing at Pacific Northwest National Laboratory (PNNL) to address a variety of scientific issues related with the potential leaks of the carbon dioxide (CO 2 ) gas from deep storage reservoirs. The main objectives of this work are as follows: • Develop a systematic understanding of how CO 2 leakage is likely to influence pertinent geochemical processes (e.g., dissolution/precipitation, sorption/desorption and redox reactions) in the aquifer sediments. • Identify prevailing environmental conditions that would dictate one geochemical outcome over another. • Gather useful information to support site selection, risk assessment, policy-making, and public education efforts associated with geological carbon sequestration. In this report, we present results from experiments conducted at PNNL to address research issues related to the main objectives of this effort. A series of batch and column experiments and solid phase characterization studies (quantitative x-ray diffraction and wet chemical extractions with a concentrated acid) were conducted with representative rocks and sediments from an unconfined, oxidizing carbonate aquifer, i.e., Edwards aquifer in Texas, and a confined aquifer, i.e., the High Plains aquifer in Kansas. These materials were exposed to a CO 2 gas stream simulating CO 2 gas leaking scenarios, and changes in aqueous phase pH and chemical composition were measured in liquid and effluent samples collected at pre-determined experimental times. Additional research to be conducted during the current fiscal year will further validate these results and will address other important remaining issues. Results from these experimental efforts will provide valuable insights for the development of site-specific, generation III reduced order models. In addition, results will initially serve as input parameters during model calibration runs and, ultimately, will be used to test model predictive capability and competency. The results from these investigations will provide useful information to support site selection, risk assessment, and public education efforts associated with geological, deep subsurface CO 2 storage and sequestration.

Qafoku, Nikolla P.↗
DOE OSTI2016

Magnetic induced heating of nanoparticle solutions

Magnetic induced heating of nanoparticles (NP) provides a useful advantage for many energy transfer applications. This study aims to gain an understanding of the key parameters responsible for maximizing the energy transfer leading to nanoparticle heating through the use of simulations and experimental results. It was found that magnetic field strength, NP concentration, NP composition, and coil size can be controlled to generate accurate temperature profiles in NP aqueous solutions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Experimental Set-up for the Study of Chemical Fractionation and Aerosol Dynamics

Experimental investigations of chemical fractionation/phase partition and aerosol dynamics in high-temperature environment were reviewed and discussed. Particle composition and size distribution are the key data for aerosol dynamics predictive model and simulation. However, there were no particle size distribution available from the previous works. Nucleation, condensation, and coagulation are three key physical processes driving the fractionation or phase partition thereby the aerosol dynamics. A new approach was proposed to experimentally observe fractionation/phase partition and provide data for validating the predictive model for aerosol dynamics in the simulation of bomb debris formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Low Temperature CO2 Capture from an NGCC Flue Gas Using a Magnetically Stabilized, Inductively Heated Fluidized Bed Reactor

The lab sorbent testing finalized the sorbent composition and operating conditions for the integrated unit. The bench unit design included COMSOL simulation to finalize the coil design and select initial operating conditions of the power supply system. Fluidized bed testing with the induction heating verified that a heating efficiency of up to 90% can be achieved. The integrated bench unit operations provided valuable data confirming the feasibility of using induction heating for the desorption of CO2. Major challenge observed was the limited working capacity of the sorbent, requiring additional development in future projects. In addition, a large-scale reactor demonstration is required to mitigate the risk of uniform temperature distribution and heating efficiency over a large cross-sectional area when using induction heating.

Tong, Andrew↗
DOE OSTI2022

Thermal radiation analysis of a pressurized oxy-coal combustor with discrete ordinate model

Concerns over climate change have led to numerous efforts in developing low-carbon energy technologies. Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Pressure strongly impacts thermal radiation, leading to a substantial difference in heat transfer between POC and conventional atmospheric pressure combustion. A good understanding of thermal radiation in POC is needed to aid new combustor development. The present work is a step in this direction, initiating a systematic analysis of thermal radiation and heat transfer in a pilot-scale POC combustor, which has been developed at Washington University in St. Louis (WUSTL). In a POC process, pulverized coal is burned under elevated pressure and O2-CO2 environment. Few researchers have investigated the thermal radiation of pressurized oxy-combustion. This work adopted the discrete ordinate model to simulate the radiation of a 1-D cylinder with predetermined conditions (temperature, pressure, gas compositions) to predict the influence of radiative properties of flue gas on the radiation in the combustor.

Li, Lei↗
DOE OSTI2023

CERESMIP: a climate modeling protocol to investigate recent trends in the Earth's Energy Imbalance

The Clouds and the Earth's Radiant Energy System (CERES) project has now produced over two decades of observed data on the Earth's Energy Imbalance (EEI) and has revealed substantive trends in both the reflected shortwave and outgoing longwave top-of-atmosphere radiation components. Available climate model simulations suggest that these trends are incompatible with purely internal variability, but that the full magnitude and breakdown of the trends are outside of the model ranges. Unfortunately, the Coupled Model Intercomparison Project (Phase 6) (CMIP6) protocol only uses observed forcings to 2014 (and Shared Socioeconomic Pathways (SSP) projections thereafter), and furthermore, many of the ‘observed' drivers have been updated substantially since the CMIP6 inputs were defined. Most notably, the sea surface temperature (SST) estimates have been revised and now show up to 50% greater trends since 1979, particularly in the southern hemisphere. Additionally, estimates of short-lived aerosol and gas-phase emissions have been substantially updated. These revisions will likely have material impacts on the model-simulated EEI. We therefore propose a new, relatively low-cost, model intercomparison, CERESMIP, that would target the CERES period (2000-present), with updated forcings to at least the end of 2021. The focus will be on atmosphere-only simulations, using updated SST, forcings and emissions from 1990 to 2021. The key metrics of interest will be the EEI and atmospheric feedbacks, and so the analysis will benefit from output from satellite cloud observation simulators. The Tier 1 request would consist only of an ensemble of AMIP-style simulations, while the Tier 2 request would encompass uncertainties in the applied forcing, atmospheric composition, single and all-but-one forcing responses. We present some preliminary results and invite participation from a wide group of models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Magnetic Sorbent for the Removal of Selenium(IV) from Simulated Industrial Wastewaters: Determination of Column Kinetic Parameters

A novel meso- and microporous tire-derived-carbon support with magnetic iron oxide nanoparticle adsorbents that selectively adsorbs Se(IV) ions from simulated contaminated water has been developed. In this work, the physicochemical characteristics of the composite adsorbent are characterized with respect to porosity and surface area, chemical composition, and microstructure morphology. The kinetics of this composite adsorbent in a fixed-bed setting has been determined. Several column runs were conducted and analyzed by inductively coupled plasma-optical emission spectroscopy (ICP-OES) to determine the concentration gradient vs time. These results were then fit to a pseudo-second order rate law to obtain equilibrium values. Combining calculated equilibrium values with effluent concentration data, enabled the application of the Adams–Bohart model to determine reaction constants and column coefficients. Column parameters obtained from different flow rates and fittings of the Adams–Bohart model were remarkably consistent. These findings enable the application of this sorbent to fixed-bed column systems and opens up further research into mixed pollutants tests with real wastewater and scaling of selenium pollutant removal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Observations and implications of liquid–liquid phase separation at high relative humidities in secondary organic material produced by α -pinene ozonolysis without inorganic salts

Particles consisting of secondary organic material (SOM) are abundant in the atmosphere. In order to predict the role of these particles in climate, visibility and atmospheric chemistry, information on particle phase state (i.e., single liquid, two liquids and solid) is needed. Our paper focuses on the phase state of SOM particles free of inorganic salts produced by the ozonolysis of α -pinene. Phase transitions were investigated in the laboratory using optical microscopy and theoretically using a thermodynamic model at 290 K and for relative humidities ranging from < 0.5 to 100%. In the laboratory studies, a single phase was observed from 0 to 95% relative humidity (RH) while two liquid phases were observed above 95% RH. For increasing RH, the mechanism of liquid–liquid phase separation (LLPS) was spinodal decomposition. The RH range over which two liquid phases were observed did not depend on the direction of RH change. In the modeling studies, the SOM took up very little water and was a single organic-rich phase at low RH values. At high RH, the SOM underwent LLPS to form an organic-rich phase and a water-rich phase, consistent with the laboratory studies. The presence of LLPS at high RH values can have consequences for the cloud condensation nuclei (CCN) activity of SOM particles. In the simulated Köhler curves for SOM particles, two local maxima were observed. Depending on the composition of the SOM, the first or second maximum can determine the critical supersaturation for activation. Recently researchers have observed inconsistencies between measured CCN properties of SOM particles and hygroscopic growth measured below water saturation (i.e., hygroscopic parameters measured below water saturation were inconsistent with hygroscopic parameters measured above water saturation). Furthermore, the work presented here illustrates that such inconsistencies are expected for systems with LLPS when the water uptake at subsaturated conditions represents the hygroscopicity of an organic-rich phase while the barrier for CCN activation can be determined by the second maximum in the Köhler curve when the particles are water rich.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements

Cloud condensation nuclei (CCN) number concentrations are an important aspect of aerosol–cloud interactions and the subsequent climate effects; however, their measurements are very limited. We use a machine learning tool, random decision forests, to develop a random forest regression model (RFRM) to derive CCN at 0.4 % supersaturation ([CCN0.4]) from commonly available measurements. The RFRM is trained on the long-term simulations in a global size-resolved particle microphysics model. Using atmospheric state and composition variables as predictors, through associations of their variabilities, the RFRM is able to learn the underlying dependence of [CCN0.4] on these predictors, which are as follows: eight fractions of PM 2.5 (NH 4 , SO 4 , NO 3, secondary organic aerosol (SOA), black carbon (BC), primary organic carbon (POC), dust, and salt), seven gaseous species (NO x , NH 3 , O 3 , SO 2 , OH, isoprene, and monoterpene), and four meteorological variables (temperature (T), relative humidity (RH), precipitation, and solar radiation). The RFRM is highly robust: it has a median mean fractional bias (MFB) of 4.4 % with ≈96.33 % of the derived [CCN0.4] within a good agreement range of -60% 2.5 speciation (NH 4 , SO 4 , NO 3 , and organic carbon (OC)), NO x , O 3 , SO 2 , T, and RH, as well as [CCN0.4] are available. We modify, optimize, and retrain the developed RFRM to make predictions from 19 to 9 of these available predictors. This retrained RFRM (RFRM-ShortVars) shows a reduction in performance due to the unavailability and sparsity of measurements (predictors); it captures the [CCN0.4] variability and magnitude at SGP with ≈67.02 % of the derived values in the good agreement range. This work shows the potential of using the more commonly available measurements of PM 2.5 speciation to alleviate the sparsity of CCN number concentrations' measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Evaluating Feed Delivery Performance in Scaled Double-Shell Tanks

The Hanford Tank Operations Contractor (TOC) and the Hanford Waste Treatment and Immobilization Plant (WTP) contractor are both engaged in demonstrating mixing, sampling, and transfer system capability using simulated Hanford High-Level Waste (HLW) formulations. This work represents one of the remaining technical issues with the high-level waste treatment mission at Hanford. The TOCs' ability to adequately mix and sample high-level waste feed to meet the WTP WAC Data Quality Objectives must be demonstrated. The tank mixing and feed delivery must support both TOC and WTP operations. The tank mixing method must be able to remove settled solids from the tank and provide consistent feed to the WTP to facilitate waste treatment operations. Two geometrically scaled tanks were used with a broad spectrum of tank waste simulants to demonstrate that mixing using two rotating mixer jet pumps yields consistent slurry compositions as the tank is emptied in a series of sequential batch transfers. Testing showed that the concentration of slow settling solids in each transfer batch was consistent over a wide range of tank operating conditions. Although testing demonstrated that the concentration of fast settling solids decreased by up to 25% as the tank was emptied, batch-to-batch consistency improved as mixer jet nozzle velocity in the scaled tanks increased.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2015

FIBER ORIENTATION IN INJECTION MOLDED LONG CARBON FIBER THERMOPLASTIC COMPOSITES

A set of edge-gated and center-gated plaques were injection molded with long carbon fiber-reinforced thermoplastic composites, and the fiber orientation was measured at different locations of the plaques. Autodesk Simulation Moldflow Insight (ASMI) software was used to simulate the injection molding of these plaques and to predict the fiber orientation, using the anisotropic rotary diffusion and the reduced strain closure models. The phenomenological parameters of the orientation models were carefully identified by fitting to the measured orientation data. The fiber orientation predictions show very good agreement with the experimental data.

carbon fiber↗
DOE OSTI2024

CO2 Capture Using Amines Bound to Silica

One of the main culprits of global warming is the increased amount of carbon dioxide, or CO2, in the atmosphere. NASA's global climate reports a 13% increase in atmospheric CO2 from 2000 to present. Adsorptive CO2 capture by nitrogen groups of amine-containing solvents is one of the most mature technologies deployed in petrochemical and natural gas processing plants to purify industrial gases. However, key challenges in widespread application include solvent induced reactor corrosion, amine degradation, and high regeneration energy for repeated cycling. An alternative approach is to immobilize amines on solid supports. Key performance metrics of solid amine-based CO2 adsorbents include the CO2 adsorption capacity and stability to degradation over hundreds of thousands of regeneration cycles. Our research aims to develop descriptors for CO2 capture capacity and stability against oxygen-induced degradation for amines bound to porous silica supports using experimental and computational techniques. We experimentally measure the change in CO2-uptake using solid amine adsorbents with varying chemical compositions and exposure to varying gas streams and use high-performance computers to simulate the nature and strength of CO2-adsorption and oxidative degradation reaction mechanisms. Insights from our work can facilitate the development of stable solid amine adsorbents for large-scale CO2 capture processes.

amines↗
DOE OSTI2016

SU-F-T-58: Dosimetric Evaluation of Breast Tissue Composition for Electronic Brachytherapy (BET) Source In High Dose Rate Accelerated Partial Breast (APBI) Irradiation

Purpose: To quantitatively evaluate the dosimetric impact of differing breast tissue compositions for electronic brachytherapy source for high dose rate accelerated partial breast irradiation. Methods: A series of Monte Carlo Simulation were created using the GEANT4 toolkit (version 10.0). The breast phantom was modeled as a semi-circle with a radius of 5.0 cm. A water balloon with a radius of 1.5 cm was located in the phantom with the Xoft AxxentTM EBT source placed at center as a point source. A mixed of two tissue types (adipose and glandular tissue) was assigned as the materials for the breast phantom with different weight ratios. The proportionality of glandular and adipose tissue was simulated in four different fashions, 80/20, 70/30, 50/50 and 30/70 respectively. The custom energy spectrum for the 50 kVp XOFT source was provided via the manufacturer and used to generate incident photons. The dose distributions were recorded using a parallel three dimensional mesh with a size of 30 × 30 × 30 cm3 with 1 × 1 × 1 mm3 voxels. The simulated doses absorbed along the transverse axis were normalized at the distance of 1 cm and then compared with the calculations using standard TG-43 formalism. Results: All simulations showed underestimation of dose beyond balloon surface compared to standard TG-43 calculations. The maximum percentage differences within 2 cm distance from balloon surface were found to be 18%, 11%, 10% and 8% for the fat breast (30/70), standard breast (50/50), dense breast (70/30 and 80/20), respectively. Conclusion: The accuracy of dose calculations for low energy EBT source was limited when considering tissue heterogeneous composition. The impact of atomic number on photo-electric effect for lower energy Brachytherapy source is not accounted for and resulting in significant errors in dose calculation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Sooting tendencies of co-optima test gasolines and their surrogates

Here, this study characterized the sooting tendencies of a set of gasolines and their surrogates using both experimental and computational methods. Sooting tendency was defined in terms of the soot yield when 1000 ppm of the test fuel is doped into the fuel of a methane/air flame, and it provides a measure of the intrinsic chemical tendency of the fuels to form soot in a generic combustion environment. The test fuels were real gasolines containing enhanced concentrations of alkanes, aromatics, cycloalkanes, olefins, and ethanol. These compositional differences caused the experimentally measured sooting tendencies of the fuels to vary by 240%. The surrogates were 3 mixtures defined by Szybist et al. (2017) and 3 alternative formulations modified for greater experimental convenience. The sooting tendencies measured for the surrogate mixtures agreed with the real fuels to within 15%, and varied with composition in the same order. The sooting tendencies of the surrogates could be predicted to within experimental error with an empirical quantitative structure-property relationship and a linear mixing model. The experimental flames were computationally simulated with a 743-species mechanism, and sooting tendencies derived from the results agreed with the measured values to within 11%. Altogether, these results show that the sooting behavior of gasoline can vary considerably within the range of acceptable compositions, and that these variations can be accurately predicted with empirical models and computational simulations.

09 BIOMASS FUELS↗
DOE OSTI2024

Predicting Mechanical Properties from Microstructure Images in Fiber-Reinforced Polymers Using Convolutional Neural Networks

Evaluating the mechanical response of fiber-reinforced composites can be extremely time-consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input–output pairs and have exhibited success in composite research. This paper explores a fully convolutional neural network modified from StressNet, which was originally used for linear elastic materials, and extended here for a non-linear finite element (FE) simulation to predict the stress field in 2D slices of segmented tomography images of a fiber-reinforced polymer specimen. The network was trained and evaluated on data generated from the FE simulations of the exact microstructure. The testing results show that the trained network accurately captures the characteristics of the stress distribution, especially on fibers, solely from the segmented microstructure images. The trained model can make predictions within seconds in a single forward pass on an ordinary laptop, given the input microstructure, compared to 92.5 h to run the full FE simulation on a high-performance computing cluster. These results show promise in using ML techniques to conduct fast structural analysis for fiber-reinforced composites and suggest a corollary that the trained model can be used to identify the location of potential damage sites in fiber-reinforced polymers.

Sun, Yixuan (ORCID:0000000311093380)↗
DOE OSTI2024

A Mechanism-Based Reaction–Diffusion Model for Accelerated Discovery of Thermoset Resins Frontally Polymerized by Olefin Metathesis

Frontal ring-opening metathesis polymerization (FROMP) involves a self-perpetuating exothermic reaction, which enables the rapid and energy-efficient manufacturing of thermoset polymers and composites. Current state-of-the-art reaction–diffusion FROMP models rely on a phenomenological description of the olefin metathesis kinetics, limiting their ability to model the governing thermo-chemical FROMP processes. Furthermore, the existing models are unable to predict the variations in FROMP kinetics with changes in the resin composition and as a result are of limited utility toward accelerated discovery of new resin formulations. In this work, we formulate a chemically meaningful model grounded in the established mechanism of ring-opening metathesis polymerization (ROMP). Our study aims to validate the hypothesis that the ROMP mechanism, applicable to monomer-initiator solutions below 100 °C, remains valid under the nonideal conditions encountered in FROMP, including ambient to >200 °C temperatures, sharp temperature gradients, and neat monomer environments. Through extensive simulations, we demonstrate that our mechanism-based model accurately predicts the FROMP behavior across various resin compositions, including polymerization front velocities and thermal characteristics (e.g., T max ). Additionally, we introduce a semi-inverse workflow that predicts FROMP behavior from a single experimental data point. Notably, the physiochemical parameters utilized in our model can be obtained through DFT calculations and minimal experiments, highlighting the model’s potential for rapid screening of new FROMP chemistries in pursuit of thermoset polymers with superior thermo-chemo-mechanical properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗