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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Error-controlled, progressive, and adaptable retrieval of scientific data with multilevel decomposition

Extreme-scale simulations and high-resolution instruments have been generating an increasing amount of data, which poses significant challenges to not only data storage during the run, but also post-processing where data will be repeatedly retrieved and analyzed for a long period of time. The challenges in satisfying a wide range of post-hoc analysis needs while minimizing the I/O overhead caused by inappropriate and/or excessive data retrieval should never be left unmanaged. In this paper, we propose a data refactoring, compressing, and retrieval framework capable of 1) fine-grained data refactoring with regard to precision; 2) incrementally retrieving and recomposing the data in terms of various error bounds; and 3) adaptively retrieving data in multi-precision and multi-resolution with respect to different analysis. With the progressive data re-composition and the adaptable retrieval algorithms, our framework significantly reduces the amount of data retrieved when multiple incremental precision are requested and/or the downstream analysis time when coarse resolution is used. Experiments show that the amount of data retrieved under the same progressively requested error bound using our framework is 64% less than that using state-of-the-art single-error-bounded approaches. Parallel experiments with up to 1, 024 cores and ~ 600 GB data in total show that our approach yields 1.36× and 2.52× performance over existing approaches in writing to and reading from persistent storage systems, respectively.

Liang, Xin↗
DOE OSTI2023

Ectomycorrhizal effects on decomposition are highly dependent on fungal traits, climate, and litter properties: A model-based assessment

It has been proposed that competition between ectomycorrhizal (ECM) fungi and free-living saprotrophs for resources like nitrogen (N) slows decomposition and increases the soil carbon storage in ECM ecosystems compared to arbuscular (AM) ecosystems. However, empirical evidence for the generality of such ECM effects is equivocal, and confounding mechanisms have been proposed that affect the magnitude and direction of ECM effects on soil carbon. Here, for this work, we conduct a theoretical modeling experiment, where we explicitly incorporate mycorrhizal processes into the Carbon, Organisms, Rhizosphere, and Protection in the Soil Environment (CORPSE) model. We use the model to explore the conditions under which ECM N acquisition processes can induce stronger saprotrophic N limitation and result in slower decomposition rates and greater soil organic carbon accumulation compared to AM processes. We found that the ECM fungi more strongly inhibited decomposition when litter inputs were N-depleted and relatively recalcitrant and when ECM fungi possessed a strong capacity to mine N from both recalcitrant soil organic matter and microbial necromass. Climate and seasonality also played a role as the ECM competition effect was strongest at low mean annual temperatures and when litterfall peaked seasonally. Priming effects driven by high root exudation rates in ECM-dominated systems could overwhelm the competition effect and reduce soil carbon under some circumstances. The ECM effect on decomposition in our simulations was highly context dependent. Based on our model results, we expect to see a strong ECM competition effect in temperate deciduous and boreal forests with relatively recalcitrant litter inputs, and with ECM fungi that produce oxidases and necromass-degrading enzymes. However, even a relatively strong ECM competition effect on decomposition only increased soil organic carbon accumulation by ~10%.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Quantum Simulation of Open Quantum Systems Using a Unitary Decomposition of Operators

Electron transport in realistic physical and chemical systems often involves the nontrivial exchange of energy with a large environment, requiring the definition and treatment of open quantum systems. Because the time evolution of an open quantum system employs a nonunitary operator, the simulation of open quantum systems presents a challenge for universal quantum computers constructed from only unitary operators or gates. Here, we present a general algorithm for implementing the action of any nonunitary operator on an arbitrary state on a quantum device. We show that any quantum operator can be exactly decomposed as a linear combination of at most four unitary operators. We demonstrate this method on a two-level system in both zero and finite temperature amplitude damping channels. Furthermore, the results are in agreement with classical calculations, showing promise in simulating nonunitary operations on intermediate-term and future quantum devices.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Strategies to Obtain Reliable Energy Landscapes from Embedded Multireference Correlated Wavefunction Methods for Surface Reactions

Embedded correlated wavefunction (ECW) theory is a powerful tool for studying ground- and excited-state reaction mechanisms and associated energetics in heterogeneous catalysis. Several factors are important to obtaining reliable ECW energies, critically the construction of consistent active spaces (ASs) along reaction pathways when using a multireference correlated wavefunction (CW) method that relies on a subset of orbital spaces in the configuration interaction expansion to account for static electron correlation, e.g., complete AS self-consistent field theory, in addition to the adequate partitioning of the system into a cluster and environment, as well as the choice of a suitable basis set and number of states included in excited-state simulations. Here, in this work, we conducted a series of systematic studies to develop best-practice guidelines for ground- and excited-state ECW theory simulations, utilizing the decomposition of NH 3 on Pd(111) as an example. We determine that ECW theory results are relatively insensitive to cluster size, the aug-cc-pVDZ basis set provides an adequate compromise between computational complexity and accuracy, and that a fixed-clean-surface approximation holds well for the derivation of the embedding potential. Additionally, we demonstrate that a merging approach, which involves generating ASs from the molecular fragments at each configuration, is preferable to a creeping approach, which utilizes ASs from adjacent structures as an initial guess, for the generation of consistent potential energy curves involving open-d-shell metal surfaces, and, finally, we show that it is essential to include bands of excited states in their entirety when simulating excited-state reaction pathways.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

A Review of Tank 48H Treatment of Tetraphenylborate with Permanganate

Tank 48H contains roughly 270,000 gallons of radioactive waste material. The waste stored in this tank was to be processed in multiple stages utilizing facilities at the Savannah River Site (SRS) almost 30 years ago. The In-Tank Precipitation Process (ITP) was initiated in Tank 48H, which precipitated highly radioactive cesium-137 using sodium tetraphenylborate (NaTPB). While the process succeeded in precipitating the Cs, Sr, and other actinides, it also generated an unexpectedly large amount of benzene. The evolved benzene created a safety concern and made the waste incompatible with further downstream processing. This halted the ITP, and a new method of treatment was required to continue processing the legacy waste contained in Tank 48H. A myriad of treatment options have been proposed with multiple teams of researchers assembled to work on this highly complex issue over the last few decades. This review investigated one potentially viable treatment option, in-tank oxidation with sodium permanganate. Permanganate has been well known in literature as a strong oxidizing agent for organic compounds, as well as being utilized at the Savannah River Site (SRS) in other processes. A small number of studies have been conducted utilizing waste simulants to evaluate the use of permanganate as an oxidant for tetraphenylborate (TPB). A search of the literature and data from these studies indicates that permanganate could be a viable treatment for destruction of TPB in Tank 48H. While the scoping studies had a small number of individual experiments and nonideal conditions, the permanganate decomposed up to 90% of the TPB. A free hydroxide concentration above 1.0 M is required for tank corrosion control. Simulant studies indicate no decrease in TPB decomposition by permanganate until pH 14. The simulant studies show an increase in TPB decomposition as the temperature of the solution is increased to 40 °C. The post-reaction analysis of previous simulant tests did not look at all of the organic degradation products. Investigations into what these organic products are and in what quantity will help guide determinations as to whether the downstream processing facilities are able to handle the material that will be generated. Study on the time frame for the reaction between permanganate and TPB should be investigated as the literature reports only extend out to two weeks reaction time. The permanganate treatment conditions indicate no corrosion control concerns and a longer timescale reaction may be needed for in-tank treatment. In addition, further study would be useful to identify a lower boundary condition for the ratio of TPB and oxidant. The simulant tests applied large excesses of permanganate, and this may be unnecessary. The size constraint of the tank means that there will be practical limitations on the amount of sodium permanganate that can be added to the tank. The amount of permanganate should be minimized as much as possible while still ensuring decomposition of the TPB to minimize the amount of manganese dioxide solids generated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Molecular Structure and Electron Affinity of Metal-Solvent Complexes: Insights from Density Functional Theory Simulations

A molecular level understanding of the structure and energetics of the monovalent and divalent metal ion complexes is of great importance for development of next-generation batteries. Here, Density Functional Theory (DFT) simulations at the ωb97xD/6-31 + G(d,p) level of theory are performed to investigate the interaction of metal ions (Li + , Na + , K + , Mg 2+ , Ca 2+ , Zn 2+ ) with 26 organic solvent molecules. The reduction energetics (electron affinity and reduction potential) and structural responses of the solvent molecules and the molecular complexes are discussed. The DFT calculations are carried out to investigate the structure, energetics and electron affinities of chelated complexes of water (H 2 O), tetrahydrofuran (THF) and di-methoxy ethane (DME) solvent molecules. Additionally, ab initio dynamic simulations (AIMD) at 298 K using atom centered density matrix propagation (ADMP) formalism are performed to understand the spontaneous structure formation upon electron attachment of the metal ion-solvent complexes. The ADMP simulations indicate the decomposition of Mg + -(DME) 3 complex via cleavage of C–O bond of one of the three DME molecules indicating irreversible decomposition of DME in the presence of the Mg + radical. We believe that the data collected as part of this investigation serves as a library of fundamental knowledge towards a deeper understanding of the electrode-electrolyte interfacial reactions.

25 ENERGY STORAGE↗
DOE OSTI2021

Simulation of the PBX 9501 Self-Ignited Heavily Confined Cookoff Test

The PBX 9501 self-ignited thermally damaged explosive (SITX) test was carried out by Holmes et al. A 6-inch diameter sphere made of the PBX 9501 was heated inside a steel confinement vessel until it underwent a thermal explosion. This test provided measured temperature data that was used to define a boundary condition to carry out post-experiment finite element (FE) thermal simulations and comparisons of the FE thermal response with the experimental time to thermal ignition and internal temperature measurements at the center of the PBX 9501 sphere. Finite element models of this experiment were constructed using the heat transfer code Aria. A cookoff model for PBX 9501 was used to simulate the thermal decomposition of PBX 9501 and to predict the time to thermal ignition. An inverse heat conduction scheme was designed and applied to estimate a 1D temperature boundary condition.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Quantum Solver Using Singular Value Decomposition for Computational Fluid Dynamics

Numerical solutions for fluid flow problems are challenging and have been focus of Computational Fluid Dynamics (CFD) research for past several decades. The advent of quantum computing promises exponential speedup in comparison to existing classical methods and alleviate computational constraints posed by CFD problems. Although solutions for most problems of interest in fluid dynamics using quantum computing are distant, recent advances in algorithms, software and hardware provide a path towards realizing this goal. Quantum linear solver algorithms (QLSA) such as Harrow–Hassidim–Lloyd (HHL) and Variational Quantum Linear Solver (VQLS) have been successfully implemented to solve for canonical problems such as Hele-Shaw flow. However, these algorithms still suffer to scale and address problems with ill-conditioned Jacobians. In the current paper, we alleviate these restrictions with a new quantum solver based on Singular Value Decomposition (SVD) and simulate flow past a 2D cylinder. The fidelity of the SVD based quantum solver in predicting the flow past 2D cylinder is computed along with an assessment of errors. Classical and quantum solutions for the flow are compared for different resolutions. Finally, we discuss variation in the solutions based on number of shots used.

Gottiparthi, Kalyan [ORNL] (ORCID:0000000213540255↗
DOE OSTI2020

Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models

Results from the fully and biogeochemically coupled simulations in which CO 2 increases at a rate of 1 % yr –1 (1pctCO2) from its preindustrial value are analyzed to quantify the magnitude of carbon–concentration and carbon–climate feedback parameters which measure the response of ocean and terrestrial carbon pools to changes in atmospheric CO 2 concentration and the resulting change in global climate, respectively. The results are based on 11 comprehensive Earth system models from the most recent (sixth) Coupled Model Intercomparison Project (CMIP6) and compared with eight models from the fifth CMIP (CMIP5). The strength of the carbon–concentration feedback is of comparable magnitudes over land (mean ± standard deviation = 0.97 ± 0.40 PgC ppm –1 ) and ocean (0.79 ± 0.07 PgC ppm –1 ), while the carbon–climate feedback over land (–45.1 ± 50.6 PgC °C –1 ) is about 3 times larger than over ocean (–17.2 ± 5.0 PgC °C –1 ). The strength of both feedbacks is an order of magnitude more uncertain over land than over ocean as has been seen in existing studies. These values and their spread from 11 CMIP6 models have not changed significantly compared to CMIP5 models. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The transient climate response to cumulative emissions (TCRE) from the 11 CMIP6 models considered here is 1.77 ± 0.37 °C EgC –1 and is similar to that found in CMIP5 models (1.63 ± 0.48 °C EgC –1 ) but with somewhat reduced model spread. The expressions for feedback parameters based on the fully and biogeochemically coupled configurations of the 1pctCO2 simulation are simplified when the small temperature change in the biogeochemically coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters is used to gain insight into the reasons for differing responses among ocean and land carbon cycle models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soil enzymes as indicators of soil function: A step toward greater realism in microbial ecological modeling

Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme-mediated soil inorganic N processes in the Microbial-ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C-N fluxes, microbial C:N ratios, and functional gene abundances from a 12-year CO 2 × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO 2 fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C-N-associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO 2 concentration. In conclusion, our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem-level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications

We introduce a physics guided data-driven method for image-based multi-material decomposition for dual-energy computed tomography (CT) scans. The method is demonstrated for CT scans of virtual human phantoms containing more than two types of tissues. The method is a physics-driven supervised learning technique. We take advantage of the mass attenuation coefficient of dense materials compared to that of muscle tissues to perform a preliminary extraction of the dense material from the images using unsupervised methods. We then perform supervised deep learning on the images processed by the extracted dense material to obtain the final multi-material tissue map. The method is demonstrated on simulated breast models with calcifications as the dense material placed amongst the muscle tissues. The physics-guided machine learning method accurately decomposes the various tissues from input images, achieving a normalized root-mean-squared error of 2.75%.

Gopalakrishnan Meena, Murali↗
DOE OSTI2024

Accelerating particle-in-cell kinetic plasma simulations via reduced-order modeling of space-charge dynamics using dynamic mode decomposition

We present a data-driven reduced-order modeling of the space-charge dynamics for electromagnetic particle-in-cell (EMPIC) plasma simulations based on dynamic mode decomposition (DMD). The dynamics of the charged particles in kinetic plasma simulations such as EMPIC is manifested through the plasma current density defined along the edges of the spatial mesh. We showcase the efficacy of DMD in modeling the time evolution of current density through a low-dimensional feature space. Not only do such DMD based predictive reduced-order models help accelerate EMPIC simulations, they also have the potential to facilitate investigative analysis and control applications. Here, we demonstrate the proposed DMD-EMPIC scheme for reduced-order modeling of current density and speedup in EMPIC simulations involving electron beam under the influence of magnetic field, virtual cathode oscillations, and backward wave oscillator.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Pyrolysis of bio-derived dioxolane fuels: A ReaxFF molecular dynamics study

Alkyl-substituted 1,3-dioxolanes, including 4,5-dimethyl-2-pentan-3-yl-1,3-dioxolane (Fuel 1), 4,5-dimethyl-2-pentyl-1,3-dioxolane (Fuel 2), and 2-(heptan-3-yl)-4,5-dimethyl-1,3-dioxolane (Fuel 3), have been recently suggested as potential biodiesels. In this paper, we investigate the initial pyrolysis of the alkyl-substituted 1,3-dioxolanes at high temperatures using ReaxFF molecular dynamics (MD) simulations. We analyze the decomposition rate, reaction mechanism, and product distribution in the pyrolysis of the three alkyl 1,3-dioxlanes. The three fuels primarily decompose to 4,5-dimethyl-1,3-dioxolane radical and hydrocarbons derived from the alkyl side-chains. The further decomposition of 4,5-dimethyl-1,3-dioxolane radical primarily leads to 2-C 4 H 8 and CO 2 within a few decomposition steps. The hydrocarbon product distribution is significantly affected by the molecular structure of the alkyl side-chain, which would have a strong influence on the sooting tendency of these fuels. The ReaxFF simulations predict that the order of sooting tendency would be Fuel 3 > Fuel 1 > Fuel 2, which agrees with the measured sooting tendency trend. Based on the pyrolysis mechanism identified by ReaxFF, we propose a new alkyl dioxolane, 4-hexyl-5-methyl-1,3-dioxolane (Fuel 4), which might produce even less soot, by modifying the molecular structure of Fuel 2. Our ReaxFF simulation shows that Fuel 4 produce much less C 4 H 8 , an effective non-aromatic soot precursor, than Fuel 2. Moreover, more carbon atoms are bonded to each oxygen atom in Fuel 4 than Fuel 2, which would help reduce soot yield by removing more carbon atoms from the soot-producing pool of species. The major decomposition pathways identified in this work can be used to develop chemical kinetic models for 1,3-dioxolane based compounds, as biodiesel components, applicable to combustion engine simulations. We also demonstrate that the chemical kinetic insight offered by ReaxFF simulations can be used to design new fuel molecules with more desired properties.

09 BIOMASS FUELS↗