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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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DOE OSTI2013

MINING NUCLEAR TRANSIENT DATA THROUGH SYMBOLIC CONVERSION

Dynamic Probabilistic Risk Assessment (DPRA) methodologies generate enormous amounts of data for a very large number of simulations. The data contain temporal information of both the state variables of the simulator and the temporal status of specific systems/components. In order to measure system performances, limitations and resilience, such data need to be carefully analyzed with the objective of discovering the correlations between sequence/timing of events and system dynamics. A first approach toward discovering these correlations from data generated by DPRA methodologies has been performed by organizing scenarios into groups using classification or clustering based algorithms. The identification of the correlations between system dynamics and timing/sequencing of events is performed by observing the temporal distribution of these events in each group of scenarios. Instead of performing “a posteriori” analysis of these correlations, this paper shows how it is possible to identify the correlations implicitly by performing a symbolic conversion of both continuous (temporal profiles of simulator state variables) and discrete (status of systems and components) data. Symbolic conversion is performed for each simulation by properly quantizing both continuous and discrete data and then converting them as a series of symbols. After merging both series together, a temporal phrase is obtained. This phrase preserves duration, coincidence and sequence of both continuous and discrete data in a uniform and consistent manner. In this paper it is also shown that by using specific distance measures, it is still possible to post-process such symbolic data using clustering and classification techniques but in considerably less time since the memory needed to store the data is greatly reduced by the symbolic conversion.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

Extending RISMC Capabilities for Real-Time Diagnostics and Prognostics

Quick and effective accident management is essential in any industry in order to limit and contain possible threats to both people and environment/assets. This is in particular relevant in the nuclear industry where accidents may have major impacts from an economic, health and societal point of view. As an example, the Fukushima Dai-ichi nuclear power plant accident highlighted the importance of the ability of plant operators and plant staff to react quickly and effectively in accident conditions. This particular event showed the importance of being able to: • Determine/estimate the actual status of the plant (i.e., diagnosis) when the monitoring system is corrupted or partially unavailable, and, • Forecast its future evolution (i.e., prognosis). In this paper we want to describe a research direction geared toward the development of a new set of advanced diagnosis and prognosis tools. We employ innovative data mining and machine learning techniques that are able to infer plant status and mimic the plant’s full temporal behavior in order to assist the reactor operators during an accident scenario.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Genetic programming for interpretable, data-driven continuum damage models.

The damage mechanisms that lead to failure in engineering alloys have been studied extensively, but converting this knowledge into constitutive models that are suitable for engineering-scale analysis remains a challenge. Evolution laws for continuum damage have been developed in the past and have proven effective but suffer from many non-physical assumptions that inhibit the overall accuracy of the model. Further, the assumptions inherent in these existing models prevent them from being applicable to a broad class of materials. At the same time, computational models of fine-scale damage mechanisms continue to advance making it tractable to generate large training data sets through computer simulation. Data-driven machine learning approaches can leverage these data sets to avoid making limiting assumptions, and instead produce models directly from the results of microstructural simulations and/or experiments. Many of these machine learning approaches are rapid and accurate, but they offer little to no insight into the underlying relationships among state variables being discovered. Conversely, genetic programming symbolic regression (GPSR) is a machine learning method that produces analytic expressions relating the state variables, allowing maximal insight and interpretability. To that end, we propose using GPSR as a data-driven method of obtaining microstructurally informed continuum damage models. Data is generated using microstructural simulations of damage evolution, parameterized over microstructural statistics (i.e., pore shape) and nominally applied deformations. Analytic expressions for damage evolution are obtained from the data using GPSR, and these expressions are then utilized within a continuum constitutive model. Overall, this approach is a promising method of automatically obtaining analytic relations describing constitutive phenomena in a material.

Buche, Michael Robert↗

DOE OSTI2018

Four different dimensional Zn(II) coordination polymers as fluorescent sensor for detecting Hg{sup 2+}, Cr{sub 2}O{sub 7}{sup 2-} in aqueous solution

Highlights: • Four Zn-based coordination polymers were solvethermally synthesized. • Compound 1 and 2 could mutual conversion between different solvent ratios. • Both 1 and 2 exhibit high selectivity for Cr{sub 2}O{sub 7}{sup 2-} and Hg{sup 2+} ions in aqueous solution. • The mechanism of sensing properties were discussed in details. - Abstract: Four Zn(II) coordination polymers (CPs), [Zn(4-pzpt){sub 2}(H{sub 2}O)]{sub n} (1), {[Zn(4-pzpt)_2]·CH_3OH}{sub n} (2), [Zn{sub 2}(4-pzpt){sub 2}(suc)(H{sub 2}O)]{sub n} (3) and [Zn{sub 2}(4-pzpt){sub 2}(ndc)]{sub n} (4) were obtained from 3-(pyridin-4-yl)-5-(pyrazin-2-yl)-1H-1,2,4-triazole (4-Hpzpt), 1,4-Naphthalenedicarboxylic acid (H{sub 2}ndc) and succinic acid (H{sub 2}suc) ligands. Structural analysis reveals that 1 represents a five coordinated 0D structure. 2 possess a network featuring 2D 4{sup 4} grid-like layers structure. 3 displays a network featuring 2D (6{sup 3})-hcb layered structure. 4 shows a rare 3D (4,4)-connected topology with a Schläfli symbol of (4.6{sup 4.}7){sub 2}(6{sup 4.}7{sup 2}). Complexes 1 and 2 can mutual conversion between different solvent ratios. Luminescence properties reveal that 1 and 2 exhibit excellent selectivity for Hg{sup 2+} and Cr{sub 2}O{sub 7}{sup 2-} ions in aqueous solution, in which suggests that 1 and 2 is a promising multifunctional sensing materials. The possible sensing mechanism is also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Characterizing system dynamics with a weighted and directed network constructed from time series data

In this work, we propose a novel method to transform a time series into a weighted and directed network. For a given time series, we first generate a set of segments via a sliding window, and then use a doubly symbolic scheme to characterize every windowed segment by combining absolute amplitude information with an ordinal pattern characterization. Based on this construction, a network can be directly constructed from the given time series: segments corresponding to different symbol-pairs are mapped to network nodes and the temporal succession between nodes is represented by directed links. With this conversion, dynamics underlying the time series has been encoded into the network structure. We illustrate the potential of our networks with a well-studied dynamical model as a benchmark example. Results show that network measures for characterizing global properties can detect the dynamical transitions in the underlying system. Moreover, we employ a random walk algorithm to sample loops in our networks, and find that time series with different dynamics exhibits distinct cycle structure. That is, the relative prevalence of loops with different lengths can be used to identify the underlying dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2016

GDX-pandas [SWR 15-21]

This is a Python package to translate between gdx (GAMS data) and pandas. There are two main ways to use gdxpds. The first use case is the one that was initially supported: direct conversion between GDX files on disk and pandas DataFrames or a csv version thereof. Starting with the Version 1.0.0 rewrite, there is now a second style of use which involves interfacing with GDX files and symbols via the `gdxpds.gdx.GdxFile` and `gdxpds.gdx.GdxSymbol` classes. Please visit https://nrel.github.io/gdx-pandas for the latest documentation.

Hale, Elaine↗

DOE OSTI2026

Geometrical optics without singularities: using the ray time as the coordinate space

Geometrical optics (GO) is widely used for reduced modelling of waves in plasmas, but it fails near reflection points, where it predicts a spurious singularity of the wave amplitude. We show how to avoid this singularity by adopting a different representation of the wave equation. Instead of the physical coordinate 𝑥 and the wavevector 𝑘, we use the ray time 𝜏 as the new canonical coordinate and the ray energy ℎ as the associated canonical momentum. To derive the envelope equation in the 𝜏-representation, we construct the Weyl symbol calculus on the (𝜏,ℎ) space and show that the corresponding Weyl symbols are related to their (𝑥,𝑘) counterparts by the Airy transform. This allows us to express the coefficients in the envelope equation through the known properties of the original dispersion operator. When necessary, solutions of this equation can be mapped to the 𝑥-space using a generalised metaplectic transform. However, the field per se might not even be needed in practice. Instead, knowing the corresponding Wigner function usually suffices for linear and quasilinear calculations. As a Weyl symbol itself, the Wigner function can be mapped analytically, using the aforementioned Airy transform. We show that the standard Airy patterns that form in regions where conventional GO fails are successfully reproduced within metaplectic GO (MGO) simply by remapping the field from the 𝜏-space to the 𝑥-space. An extension to mode-converting waves is also presented. This formulation, which we call generalised MGO, can be particularly useful, for example, for reduced modelling of the O–X conversion in inhomogeneous plasma near the critical density, an effect that is important for fusion applications and also occurs in the ionosphere. Overall, MGO can replace GO for any practical purposes, because it better handles cutoffs and is similar otherwise.

plasma waves↗

DOE OSTI2015

Techno‐economics of microalgae production and conversion to refinery‐ready oil with co‐product credits

Abstract The economics of the production of hydrotreated algal oil ( HTAO ) along with co‐production of animal feed and nutraceuticals (omega‐3 oils) was explored. Base case calculations were for commercial scale production of 10 000 barrels per day of HTAO with nutraceuticals claiming only 0.05% of the raw algae oil ( AO ). The sensitivity of economics to critical parameters was studied. The greatest sensitivity of sales price was to the algae doubling time. Doubling time might be reduced by increasing pond velocity or other mixing‐inducing means. Other important parameters were oil content, CAPEX , and moisture content of post‐extracted algal residue. Algal area weight productivity (g/m 2 /day) was calculated from four parameters: initial algal concentration, pond depth, residence time in pond, and algae doubling time. Using presently accepted operating parameter values and with co‐product credits, the estimated plant gate price was ~ $10/gal. However, it was shown that there is significant potential for enhanced economics through moderate improvements in many areas. Credits for co‐production of animal feed and nutraceuticals were $3.24/gal and $0.14/gal, respectively. At constant oil area productivity (gal/acre/yr), the trade‐off between oil content and area weight productivity favors oil content. In the limit of 100% oil content (no solid co‐product) a sale price of $7.90/gal was estimated. Hydrotreatment of AO was discussed. Municipal waste‐water tertiary treatment was briefly discussed but not deemed viable on a large scale. An easy‐to‐use Excel spreadsheet for material and energy balances and economics was developed as a flexible scouting tool. The symbol ‘$’ denotes US dollars. © 2015 Society of Chemical Industry and John Wiley & Sons, Ltd

Manganaro, James L.↗