Degree of rate control approach to computational catalyst screening
Explore the source record for details and available documents.
catalysis (heterogeneous), materials and chemistry↗
SEARCH · Search NASA
Results for “approach”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Approaching the Minimum Thermal Conductivity in Rhenium-Substituted Higher Manganese Silicides
Abstract not provided
Chen, Xi↗
A coarse-graining approach for molecular simulation that retains the dynamics of the all-atom reference system by implementing hydrodynamic interactions
We report on a new approach for deriving coarse-grained intermolecular forces that retains the frictional contribution that is often discarded by conventional coarse-graining methods. The approach is tested for water and an aqueous glucose solution, and the results from the new implementation for coarse-grained molecular dynamics simulation show remarkable agreement with the dynamics obtained from reference all-atom simulations. The agreement between the structural properties observed in the coarse-grained and all-atom simulations is also preserved. We discuss how this approach may be applied broadly to any existing coarse-graining method where the coarse-grained models are rigorously derived from all-atom reference systems.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Comparison of Thermal Management Approaches for Integrated Traction Drives in Electric Vehicles
The continuous push to increase power densities of electric vehicle (EV) traction drive systems necessitates combining electric motor and power electronics into one unit. A single, compact traction drive unit with fewer interconnecting components also facilitates fast, automated assembly of electric vehicles, driving production costs down and enabling wider adoption of EVs. There are a number of challenges associated with the integration of power electronics with the electric machine, including thermal management of the combined traction drive system. However, one important benefit of integration from the thermal management system perspective is the potential for using a single fluid loop instead of two separate cooling systems for the electric machine and the power electronics/inverter. This paper reviews several integration approaches and, employing finite element analysis (FEA), compares thermal management solutions for the combined electric machine and power electronics systems. Namely, three different scenarios are modeled: (1) independent component (motor and power electronics) cooling, which is compared to the combined cooling system approach for (2) radially and (3) axially integrated power electronics modules into the motor enclosure. Temperature distributions for selected thermal loads and thermal resistances from the key heat-generating components to the cooling fluid are compared for each scenario.
47 OTHER INSTRUMENTATION↗
Low energy isomers of (H{sub 2}O){sub 25} from a hierarchical method based on Monte Carlo temperature basin paving and molecular tailoring approaches benchmarked by MP2 calculations
We report new global minimum candidate structures for the (H{sub 2}O){sub 25} cluster that are lower in energy than the ones reported previously and correspond to hydrogen bonded networks with 42 hydrogen bonds and an interior, fully coordinated water molecule. These were obtained as a result of a hierarchical approach based on initial Monte Carlo Temperature Basin Paving sampling of the cluster's Potential Energy Surface with the Effective Fragment Potential, subsequent geometry optimization using the Molecular Tailoring Approach with the fragments treated at the second order Møller-Plesset (MP2) perturbation (MTA-MP2) and final refinement of the entire cluster at the MP2 level of theory. The MTA-MP2 optimized cluster geometries, constructed from the fragments, were found to be within <0.5 kcal/mol from the minimum geometries obtained from the MP2 optimization of the entire (H{sub 2}O){sub 25} cluster. In addition, the grafting of the MTA-MP2 energies yields electronic energies that are within <0.3 kcal/mol from the MP2 energies of the entire cluster while preserving their energy rank order. Finally, the MTA-MP2 approach was found to reproduce the MP2 harmonic vibrational frequencies, constructed from the fragments, quite accurately when compared to the MP2 ones of the entire cluster in both the HOH bending and the OH stretching regions of the spectra.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Lattice Boltzmann-Based Approaches for Pore-Scale Reactive Transport
Here an important geoscience and environmental applications such as geologic carbon storage, environmental remediation, and unconventional oil and gas recovery are best understood in the context of reactive flow and multicomponent transport in the subsurface environment. The coupling of chemical and microbiological reactions with hydrological and mechanical processes can lead to complex behaviors across an enormous range of spatial and temporal scales. These coupled responses are also strongly influenced by the heterogeneity and anisotropy of the geologic formations. Reactive transport processes can change the pore morphology at the pore scale, thereby leading to nonlinear interactions with advective and diffusive transport, which can strongly influence larger-scale properties such as permeability and dispersion.
58 GEOSCIENCES↗
Effectively suppressing dissolution of manganese from spinel lithium manganate via a nanoscale surface-doping approach
The capacity fade of lithium manganate-based cells is associated with the dissolution of Mn from cathode/electrolyte interface due to the disproportionation reaction of Mn( III), and the subsequent deposition of Mn(II) on the anode. Suppressing the dissolution of Mn from the cathode is critical to reducing capacity fade of LiMn2O4-based cells. Here we report a nanoscale surface-doping approach that minimizes Mn dissolution from lithium manganate. This approach exploits advantages of both bulk doping and surface-coating methods by stabilizing surface crystal structure of lithium manganate through cationic doping while maintaining bulk lithium manganate structure, and protecting bulk lithium manganate from electrolyte corrosion while maintaining ion and charge transport channels on the surface through the electrochemically active doping layer. Consequently, the surface-doped lithium manganate demonstrates enhanced electrochemical performance. This study provides encouraging evidence that surface doping could be a promising alternative to improve the cycling performance of lithium-ion batteries.
Lithium ion battery↗
A Streamline Splitting Pore-Network Approach for Computationally Inexpensive and Accurate Simulation of Species Transport in Porous Media
Explore the source record for details and available documents.
nuclear (including radiation effects), carbon sequ↗
Linking process and structure in the friction stir scribe joining of dissimilar materials: A computational approach with experimental support
We present that friction stir welding (FSW) is a popular technique to join dissimilar materials in numerous applications. The solid state nature of the process enables joining materials with strikingly different physical properties. For welds in lap configuration, an enhancement to this technology is made by introducing a short, hard insert, referred to as a cutting-scribe, at the bottom of the tool pin. The cutting-scribe induces deformation in the bottom plate which leads to the formation of mechanical interlocks or hook like structures at the interface of two materials. A thermo-mechanical computational model employing a coupled Eulerian-Lagrangian approach is developed to quantitatively capture the morphology of these interlocks during the FSW process. Simulations using this model are validated by experimental observations. In conclusion, the identified interface morphology coupled with the predicted temperature field from this process–structure model can be used to estimate the post-weld microstructure and joint strength.
36 MATERIALS SCIENCE↗
Quantitative Power System Resilience Metrics and Evaluation Approach
Power system resilience is an emerging topic and plays an essential role in helping the power industry understand and respond to the increasing threats of extreme weather events. The first step of power system resilience analysis is to introduce metrics to quantify the resilience reasonably. Existing resilience metrics are typically restrained by the limited data for extreme event modeling and fall short in terms of physical interpretation and comparability. This paper develops novel quantitative metrics to evaluate power system resilience in pre- and post-event contexts. The developed metrics illustrate clear physical meanings and can be effectively used to compare resilience across different systems under different extreme events. Moreover, the developed metrics can be applied to both transmission and distribution systems. Simulation on a distribution system is employed to validate the effectiveness of the proposed resilience metrics and resilience evaluation approach.
power system resilience↗
A thermal-gradient approach to variable-temperature measurements resolved in space
Explore the source record for details and available documents.
99 GENERAL AND MISCELLANEOUS↗
Cluster-mining: an approach for determining core structures of metallic nanoparticles from atomic pair distribution function data
Explore the source record for details and available documents.
99 GENERAL AND MISCELLANEOUS↗
Trajectory analysis via a geometric feature space approach
This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.
97 MATHEMATICS AND COMPUTING↗
A Bayesian approach for parameter estimation and prediction using a computationally intensive model
Bayesian methods have been successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model eta(theta), where theta denotes the uncertain, best input setting. Hence the statistical model is of the form y = eta(theta) + c, where epsilon accounts for measurement, and possibly other, error sources. When nonlinearity is present in eta(center dot), the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and nonstandard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. Although generally applicable, MCMC requires thousands (or even millions) of evaluations of the physics model eta(center dot). This requirement is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory.
Higdon, Dave↗
An Approach to Uncertainty Identification in the Valuation of Transactive Energy Systems
Valuation of transactive energy (TE) systems should be supported by a structured and systematic approach to uncertainty identification, assessment, and treatment in the interest of risk-informed decision making. The proposed approach, a variation of fault tree analysis, is anticipated to support valuation analysts in analyzing conventional and transactive system scenarios. This approach allows for expanding the entire tree up to the level of minute details or collapsing them to a level sufficient enough to get an overview of the problem. Quantification scheme for the described approach lends itself for valuation. The method complements value exchange analysis, simulation, and field demonstration studies. The practicality of the proposed approach is demonstrated through uncertainty assessment of the smart grid interoperability panel peak heat day scenario.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Managing Approach Plate Information Study (MAPLIST): An Information Requirements Analysis of Approach Chart Use
Adequately presenting all necessary information on an approach chart represents a challenge for cartographers. Since many tasks associated with using approach charts are cognitive (e.g., planning the approach and monitoring its progress), and since the characteristic of a successful interface is one that conforms to the users' mental models, understanding pilots' underlying models of approach chart information would greatly assist cartographers. To provide such information, a new methodology was developed for this study that enhances traditional information requirements analyses by combining psychometric scaling techniques with a simulation task to provide quantifiable links between pilots' cognitive representations of approach information and their use of approach information. Results of this study should augment previous information requirements analyses by identifying what information is acquired, when it is acquired, and what presentation concepts might facilitate its efficient use by better matching the pilots' cognitive model of the information. The primary finding in this study indicated that pilots mentally organize approach chart information into ten primary categories: communications, geography, validation, obstructions, navigation, missed approach, final items, other runways, visibility requirement, and navigation aids. These similarity categories were found to underlie the pilots' information acquisitions, other mental models, and higher level cognitive processes that are used to accomplish their approach and landing tasks.
Ricks, Wendell R.↗
Evaluating Probability of Containment Effectiveness at a GCS Sites using integrated assessment modeling approach with Bayesian decision Networks
Improved scientific and engineering understanding of the behavior of geologic CO2 storage together with established regulatory framework and incentive structures raise the prospects for accelerated, large-scale deployment of this greenhouse gas emissions reduction approach. Incentive structures call for the establishment of appropriate verification and accounting approaches to support claims of the integrity of a geologic storage complex and to justify taking credit for long-term storage. In this study, we present a framework for assessing the probability of containment effectiveness over the lifetime of a geologic carbon storage site (e.g., after 70 years of injection and post-injection site performance) using forward stochastic model realizations based on site characterization data and using a monitoring-informed Bayesian network based on hypothetical detectability from surface seismic surveys over the site injection and post-injection phases. The National Risk Assessment Partnership’s open-source Integrated Assessment Model (NRAP-Open-IAM) was utilized to develop an ensemble of 10,000 a priori stochastic forecasts of CO2 containment. Those simulations were used to train the Bayesian network model to estimate the prior probabilities of the CO2 leakage mass into overlying, monitorable aquifers considering the uncertainties in the reservoir properties, permeability of potentially leaky wells and the overlying aquifers. The conditional probabilities in the Bayesian network were either learned from the NRAP-Open-IAM simulations or derived from the predefined detection thresholds for the monitoring method. Observations obtained from monitoring, over time during the site operation phases were then used to generate updated posterior probabilities of containment (and any loss from containment) in the Bayesian network by propagating the prior probabilities through the conditional probabilities. We demonstrate how to construct and use the Bayesian network for verifying the long-term storage complex effectiveness informed by monitoring based on the NRAP-Open-IAM simulations previously developed for the FutureGen 2.0 site. This approach may have relevance for stake holders to demonstrate secure geologic storage, provide a defensible, probabilistic approach to claim credit for geologic storage, and to estimate the likelihood that any fraction of the claimed credit may need to be refunded to the creditor based on available monitoring information.
Bayesian network, Risk assessment, Monitoring, car↗
Hybrid approach for estimating dynamic states of synchronous generators
Accurate and robust estimation of dynamic states is essential for monitoring and controlling a power grid. To achieve higher accuracy and robustness, this paper proposes a hybrid estimation approach to estimate the dynamic states of synchronous generators using multiple models, classified into a set of local models and a wide-area model. The proposed estimation approach, first, estimates dynamic states using the extended Kalman filter (EKF) based on a local model and a wide-area model. Then, at each time step, probability indexes, which quantify the likelihood of both local and wide-area models, are determined using hypothesis testing based on measurements innovations. Finally, using the weighted fix approach, the states estimated from the local and wide-area models are combined based on their probability indexes. Simulation studies using the two-area four-machine system shows that the proposed approach can improve estimation accuracy and increase robustness against model errors.
Akhlaghi, Shahrokh↗