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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modeling hydrodynamic and biomass pyrolysis effects of recycled product gases in a bubbling fluidized bed reactor

Fast pyrolysis of biomass in a fluidized bed reactor is typically conducted in a nitrogen gas environment. Recycling product gas can improve the economics of operating such a system by reducing reliance on pure process streams, but much less is known about how recycling pyrolysis product gas may affect fluidization behavior and pyrolysis kinetics. Therefore, gas effects in a fluidized bed biomass pyrolysis reactor were investigated using engineering correlations, low-order models, and CFD simulations for N 2 , H 2 , CO, CO 2 , and CH 4 carrier gas mixtures. Here, our findings reveal viscosity of a gas mixture can be significantly underestimated depending on the model and correlation. Furthermore, fluidization characteristics such as U mf and gas-solid convective heat transfer can be greatly affected by the gas properties. By utilizing H 2 as the fluidizing gas (instead of N 2 ), while maintaining a constant fluidization ratio (U s /U mf ), the bio-oil yields can be increased ~5%. This is due to the lower density H 2 producing similar hydrodynamics as N 2 at higher gas flow rates. These higher flow rates result in shorter gas residence times, and as a result, less secondary reactions that convert bio-oil to light gases and char. Model results also suggest that bio-oil yield is not significantly affected by the type of carrier gas used, with bio-oil yield varying by ~2% across different gas mixtures while maintaining constant flow rate. In conclusion, this indicates that recycled pyrolytic gas can be used as the carrier gas for biomass pyrolysis.

09 BIOMASS FUELS↗
DOE OSTI2024

A Finite Difference informed Random Walk solver for simulating radiation defect evolution in polycrystalline structures with strongly inhomogeneous diffusivity

Diffusivity of species and defects on grain boundaries is usually several orders of magnitude larger than that inside grains. Such strongly inhomogeneous diffusivity requires prohibitively high computational demands for modeling microstructural evolution. Here, this paper presents a highly-efficient numerical solver, combining the Finite Difference method and Random Walk model, designed for accurately modeling strongly inhomogeneous diffusion within polycrystalline structures. The proposed solver, termed Finite Difference informed Random Walk (FDiRW), integrates a customized Finite Difference (cFD) scheme tailored for fast diffusion along thin grain boundaries represented by a single-layer of nodes. Numerical experiments demonstrate that the FDiRW solver achieves an impressive efficiency gain of 1560x compared to traditional Finite Difference methods while maintaining accuracy, making it feasible for personal computer machines to handle diffusional systems with strongly inhomogeneous diffusivity across static polycrystalline microstructures. The model has been successfully applied to simulate radiation defect evolution, showcasing its scalability to engineering scales in both length and time dimensions.

36 MATERIALS SCIENCE↗
DOE OSTI2021

NRAP-open-IAM: A flexible open-source integrated-assessment-model for geologic carbon storage risk assessment and management

Large-scale implementation of geologic carbon storage (GCS) to help reduce atmospheric greenhouse gas emissions requires stakeholder confidence that injected CO2 will remain contained and that potential subsurface environmental risks are acceptably small and manageable. The U.S. Department of Energy’s National Risk Assessment Partnership (NRAP) has developed an open-source integrated assessment model (NRAP-Open-IAM) to help address questions about a potential GCS site’s ability to effectively contain injected CO 2 and protect groundwater and other overlying environmentally sensitive receptors. NRAP-Open-IAM allows a user to: (1) incorporate relevant site geologic and injection scenario data; (2) characterize important site features and events;(3) couple fast prediction models of various system components of the engineered geologic system; and (4) execute stochastic, dynamic simulation of whole GCS system performance, leakage risk assessment, and uncertainty quantification. NRAP-Open-IAM is available on GitLab (https://gitlab.com/NRAP/OpenIAM), and is accompanied by multiple application examples and detailed user and developer guides.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Topological effects on separation of alkane isomers in metal–organic frameworks

Polymorphism in metal–organic frameworks (MOFs) means that the same chemical building blocks (nodes and linkers) can be used to construct isomeric MOFs with different topological networks. The choice of topology can substantially impact the pore network of the MOF, changing the sizes and shapes of the pores, which has implications for adsorption and separation applications. Here, we look at the influence of topology in 38 polymorphic MOFs on the separation of linear and branched C4–C6 alkane isomers, a separation of great importance to the petrochemical industry. We find that the MOF Cu 2 (1,4-benzenedicarboxylate) in nbo topology (nbo-Cu 2 BDC) has particularly high affinity for linear alkanes due to its small pore size, which excludes the branched isomers. Upon studying this MOF in further detail, we find that it can take either of two conformations: a cubic conformation, which is typical of nbo MOFs, and a unique star conformation that contains 1D triangular and hexagonal channels. The determination of which conformation the MOF will adopt depends on steric effects between the nodes and linkers.

42 ENGINEERING↗
DOE OSTI2021

Effect of electrode rinse solutions on the electrodialysis of concentrated salts

The data presented indicate that modest attention to the chemistry of the electrode rinse solution can yield as much as 56% improvement in process efficiency. When operating electrodialysis (ED) with salt concentrations greater than 10,000 mg/l (as NaCl) the amperage can be relatively high even at low voltages. To maximize the overall rate of ion transport from diluate to concentrate, there is a need to minimize resistances in the electrode cells since these can represent as much as 30% of the total resistances in the entire process and in this particular ED unit, represented resistance roughly equivalent to that within the membrane stack. This work describes the performance of a 10-cell pair, 200 cm 2 (0.02 m 2 ) per membrane, pilot ED unit operated in batch mode at 5 V potential. The feedstock to the stack was varied from 0.5% to 6% NaCl. Results from Volt-amp profiles (2.0–15 V) were used as the rationale for choosing the preferred electrode rinse solution, 90 g/l (kg/m 3 ) disodium sulfate at pH 12.5. The recommended solution of 30 g/l (kg/m 3 ) disodium sulfate at neutral pH was tested against stronger solutions (60, 90, and 120 g/l (kg/m 3 ) disodium sulfate) at neutral pH and with 1 g/l (kg/m 3 ) sodium hydroxide added to yield solutions at pH 12.5. There were stark differences in the performance of the ED unit between the solutions at pH 7 and those at pH 12.5. The slopes of the Volt-amp profiles improved indicating less resistance to ion flow at pH 12.5. Most of the difference can be attributed to the greater conductivity of sodium hydroxide compared to disodium sulfate, where even a modest addition of 1 g/l (kg/m 3 ) sodium hydroxide increased the conductivity of the solution between 8 and 20% depending on the concentration of disodium sulfate. Most notably, the initiation voltage was 2.39 ± 0.08 V with solutions at pH 7 and 1.99 V ± 0.04 V when the rinse solutions were around pH 12.5, a difference of around 0.42 V. Since the full batch runs were performed at 5.0 V, this 0.42 V differential represented a loss of 8% in process efficiency. A series of tests showed a shift in initiation voltage occurred between pH 11.5 and 12.5. Nernst equations for water electrolysis are coupled with a simple flux model that estimates the concentration of hydroxide and hydronium ions at the electrode surfaces. This model indicates that the potential demanded by the electrodes is directly linked to the current. Furthermore, there is a steep drop in the potential demanded by the anode when there is sufficient hydroxide available to generate oxygen from hydroxide as opposed to generation from water. The voltage demand is minimal at pH 12.5 and reflective of the reference standard voltage (just over 1.23 V predicted at 0.1 amps). However, the flux model predicts that the voltage demanded by the electrodes at pH 7 is 1.61 V at 0.1 amps (the lowest amperage measurable with the power pack). In conclusion, comparing this result to the reference standard (E 0 = -1.23 V) yields a satisfactory explanation for the observed difference below reference standard of 0.42 V.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Optimal control of large quantum systems: assessing memory and runtime performance of GRAPE

Abstract Gradient Ascent Pulse Engineering (GRAPE) is a popular technique in quantum optimal control, and can be combined with automatic differentiation (AD) to facilitate on-the-fly evaluation of cost-function gradients. We illustrate that the convenience of AD comes at a significant memory cost due to the cumulative storage of a large number of states and propagators. For quantum systems of increasing Hilbert space size, this imposes a significant bottleneck. We revisit the strategy of hard-coding gradients in a scheme that fully avoids propagator storage and significantly reduces memory requirements. Separately, we present improvements to numerical state propagation to enhance runtime performance. We benchmark runtime and memory usage and compare this approach to AD-based implementations, with a focus on pushing towards larger Hilbert space sizes. The results confirm that the AD-free approach facilitates the application of optimal control for large quantum systems which would otherwise be difficult to tackle.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Realization of ordered magnetic skyrmions in thin films at ambient conditions

Magnetic skyrmions have captivated physicists due to their topological nature and novel physical properties. In addition, skyrmions hold significant promise for future information technologies. A key barrier to realizing skyrmion-based devices has been stabilizing these spin structures under ambient conditions. In this paper, we demonstrate that the tunable magnetic properties of amorphous Fe/Gd mulitlayers enable the formation of skyrmion lattices which are stable over a large temperature and magnetic field parameter space, including room temperature and zero magnetic field. These skyrmions, having a hybrid nature displaying both Bloch-type and Néel-type characteristics, are stabilized by dipolar interactions rather than Dzyaloshinskii-Moriya interactions, typically considered a requirement for the generation of skyrmions. Small angle neutron scattering (SANS) was used in combination with soft x-ray microscopy to provide a unique, multiscale probe of the local and long-range order of these structures. The hexagonal lattice seen in SANS results from the hybrid skyrmion picture obtained with micromagnetic simulations. Furthermore, these results identify a pathway to engineer controllable skyrmion phases in thin film geometries which are stable at ambient conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Survey of Open-Source Tools for Transmission and Distribution Systems Research

This work presents a review of open-source electric power transmission and distribution systems analysis tools suitable for use by industry professionals and academic researchers. Due to the high complexity of the electric grid, there exist numerous tools and extensive research pertaining to nearly every aspect of the design, operation, and control of transmission and distribution networks. In addition to the commercial tools, a wide range of free, open-source tools, models, and data usable by the scientific community for related research have been developed by different organizations, including both international and US universities and national laboratories. However, due to the absence of a catalog of available tools, models and data, researchers often lack a knowledge of existing capabilities and may develop duplicative software and tools. Increasing awareness of these available resources seeks to accelerate their broader use, leading to more efficient and standardized grid analysis. This review paper (which is part of a larger survey effort that studied over 400 tools in the transmission, distribution, buildings, and electric vehicles space) outlines selected open-source resources that have been developed in power transmission and distribution systems research. It is anticipated that this work can serve as a guide for industry and academic researchers alike, ensuring that research efforts are well-channeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Data-Driven Molecular Engineering of Solar-Powered Windows

Buildings are the centerpiece of modern living, with more than half of the world’s population now living in urban environments. This demographic evolution has led to building use be-coming the main drain of our energy resources. According to the US Energy Information Administration, in 2016, 40 percent of the total energy consumption in the United States came from building use. However, we could overcome this energy drain by embedding new environmental technologies into future cities to realize energy-sustainable buildings.

42 ENGINEERING↗
DOE OSTI2021

Insights From the Software Design of a Multiphysics Multicomponent Scientific Code

Using simulations for scientific discovery requires that the software used in the simulations undergoes a rigorous design and development process similar to that of the lab instruments in the experimental sciences. To devise a good design methodology, it is critical to understand the requirements, constraints, and challenges. Furthermore, this article describes insights from the long-term stewardship of a multiphysics multicomponent software, FLASH, that was designed more than 20 years ago for astrophysics, now serves multiple communities, and has been successful in adapting to the changing world of high-performance computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Quantifying Economic and Environmental Impacts of Transportation Network Disruptions with Dynamic Traffic Simulation

Several transportation network vulnerability models have been proposed. However, most only consider disruptions as a static snapshot in time and the impact on total travel time. These approaches cannot consider the time-varying nature of travel demand nor other undesirable outcomes that follow from transportation network disruptions. This paper proposes an algorithmic approach to assess the vulnerability of a transportation network that considers the time-varying demand with an open source dynamic transportation simulation tool. The open source nature of the tool allows us to systematically consider many disruption scenarios and quantitatively compare their relative criticality. This is far more efficient than traditional approaches which would require days or weeks of a transportation engineers time to manually set up, run, and assess these simulations. In addition to travel time, we also collect statistics on additional fuel consumed and the corresponding carbon dioxide emissions. Our approach, thus provides a more systematic approach that is both time-varying and can consider additional negative consequences of disruptions for decision makers to evaluate.

Shekar, Venkateswaran↗
DOE OSTI2021

Machine Learning-enabled Scalable Performance Prediction of Scientific Codes

Hardware architectures become increasingly complex as the compute capabilities grow to exascale. Here, we present the Analytical Memory Model with Pipelines (AMMP) of the Performance Prediction Toolkit (PPT). PPT-AMMP takes high-level source code and hardware architecture parameters as input and predicts runtime of that code on the target hardware platform, which is defined in the input parameters. PPT-AMMP transforms the code to an (architecture-independent) intermediate representation, then (i) analyzes the basic block structure of the code, (ii) processes architecture-independent virtual memory access patterns that it uses to build memory reuse distance distribution models for each basic block, and (iii) runs detailed basic-block level simulations to determine hardware pipeline usage. PPT-AMMP uses machine learning and regression techniques to build the prediction models based on small instances of the input code, then integrates into a higher-order discrete-event simulation model of PPT running on Simian PDES engine. We validate PPT-AMMP on four standard computational physics benchmarks and present a use case of hardware parameter sensitivity analysis to identify bottleneck hardware resources on different code inputs. We further extend PPT-AMMP to predict the performance of a scientific application code, namely, the radiation transport mini-app SNAP. To this end, we analyze multi-variate regression models that accurately predict the reuse profiles and the basic block counts. We validate predicted SNAP runtimes against actual measured times.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

MCNPy

SAND2026-20425O MCNPy runs and analyzes simulations from MCNP, a software that models radiation transport of neutrons and gamma rays. MCNPy uses Python to start MCNP, retrieve event data files, and convert them into graph structures for detailed analysis. It offers visualization tools, including 2D views of particle histories, making complex simulation data easier to interpret for researchers and engineers. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Nowack, Aaron [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2023

ParMOO: A Python library for parallel multiobjective simulation optimization

A multiobjective optimization problem (MOOP) is an optimization problem in which multiple objectives are optimized simultaneously. The goal of a MOOP is to find solutions that describe the tradeoff between these (potentially conflicting) objectives. Such a tradeoff surface is called the Pareto front. Real-world MOOPs may also involve constraints – additional hard rules that every solution must adhere to. In a multiobjective simulation optimization problem, the objectives are derived from the outputs of one or more computationally expensive simulations. Such problems are ubiquitous in science and engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Characterization of the Tribological Behavior of Oxide-Based NanoMaterials: Final CRADA Report

Under the Argonne/Pixelligent cooperative research and development agreement (CRADA – C1200801), Argonne performed labscale tribological tests on proprietary nano-sized ZrO 2 material developed by Pixelligent. Pixelligent utilized their proprietary process to prepare variants with different surfactants at different loadings in different carrier fluids for testing and evaluation at Argonne. Argonne applied a range of benchtop tribological test rigs to evaluate friction and wear under a range of conditions (contact geometry, loads, speeds, and temperature) that simulated a broad range of conditions experienced in engines and driveline components. Post-test analysis of worn surfaces provided information on the structure and chemistry of the tribofilms produced during the tests.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Non-negative Tensor Factorization for Robust Exploratory Big-Data Analytics

Currently, large multidimensional datasets are being accumulated in almost every field. Data are: (1) collected by distributed sensor networks in real-time all over the globe, (2) produced by large-scale experimental measurements or engineering activities, (3) generated by high-performance simulations, and (4) gathered by electronic communications and socialnetwork activities, etc. Simultaneous analysis of these ultra-large heterogeneous multidimensional datasets is often critical for scientific discoveries, decision-making, emergency response, and national and global security. The importance of such analyses mandates the development of the next-generation of robust machine learning (ML) methods and tools for bigdata exploratory analysis.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2018

Electrically-Assisted Tubing Processes for Enhancing Manufacturability of Oxide Dispersion Strengthened Structural Materials for Nuclear Reactor Applications

The overall goal of this project is to enhance the formability of Nanostructured Ferritic Alloys (NFAs) such that high-strength thin-walled claddings can be successfully and economically manufactured for use in future nuclear reactors. Specifically, four objectives were identified: Objective #1 – to achieve a good understanding of the mechanical behavior and resulting microstructure of 14YWT made from the powder form subjected to various Electrically- Assisted (EA) loading conditions. Objective #2 – to conduct EA-flat rolling of 14YWT completed and the prioritization/selection of two alternative designs of EA tube rolling processes. Objective #3 – to design and assemble a new EA tube rolling machine. Objective #4 – to conduct rolling using the new EA rolling machine. The above objectives were achieved and the findings can be further applied to establish other innovative fabrication processes. Specifically, the major accomplishments are summarized as: The use of an EA forming process was investigated to reduce the forming force of ODS ferritic steels. The effect of a continuous electric current on 14YWT during plastic deformation was evaluated. EA uniaxial tension tests show that the electric current is able to reduce the flow stress of 14YWT. 14YWT exhibits a ductility minimum at a current density of 34.5 A/mm2 which is consistent with fractography results. Hardness measurements and TEM results indicate that oxide particles are stable during the EA process. By following the tests, microstructure analysis was performed on the sample in its as-received state and after current treatment. The microstructures are stable when subjected to high current density. The related thermal model was developed to predict the Joule heating temperatures. The temperatures were compared with the experimental results. At last, a temperature-dependent hardening model was used to explore the mechanisms acting during EA deformation. Since the model can accurately predict the yield strength of 14YWT under EA conditions without the incorporation of non-thermal effects, it can be concluded that the reduction in yield strength is due to the Joule heating generated under continuous current loading conditions. An oven-heated pure thermal tension test was conducted to confirm this conclusion. The new EA tube rolling machine has been completely developed. The related work includes: (1) forming process design; (2) analysis of the effect of roll-tube contact geometry on rolling force; (3) analysis of machine performance under mechanical loading; (4) design of machine electrical setting path and insulation; (5) multi-pass process analysis; (6) design of power transmission system (axial/radial/torque feeding mechanisms), roll bearing system, cooling system, workpiece feeding mechanism, and other related mechanical connection support components; (7) design and optimization of roll profiles/dimensions; (8) analysis and simulation of the rolling process; (9) development of engineering drawings and fabrication; (10) assembly and calibration of the EA tube rolling machine; (11) design and integration of the electrical control system; (12) hardware integration for high power supply electrically-assisted rolling process; (13) induction heating system integration; (14) experimental tests for the new rolling process. Through the process from conceptual design to final machine calibration and experimental tests, there are many technical and physical works that have been implemented and improved for the best performance of the innovative prototype.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Mechanical Behavior of MinK and FiberFrax Board Insulation Materials Under Battery Packaging Relevant Conditions

We present a new collection of data on the load-stress relaxation-unload behavior of MinK and FiberFrax Board (FF) insulation materials used as pellets in-line with thermal battery electrochemical stacks. Both materials were subjected to standard thermal preparations, and then tested at room temperature. Intermediate term stress relaxation tests are presented (order 104 minutes of relaxation) showing that FF relaxation is not significantly stress or deformation dependent, but MinK is moderately so. Moreover, stress-strain curves associated with specimen unloading, reloading, and unloading again are presented for both materials. FF and MinK are substantially different here. Acute material variability is observed though test conditions and material preparations are standardized. A modeling approach is presented to empirically estimate the amount of stress relaxation at room temperature, and from this state, represent the unloading stress-strain behavior of both materials. This effort provides a complete framework for representing (in an engineering sense) both materials in thermal battery performance simulations.

36 MATERIALS SCIENCE↗