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DOE OSTI2017

Development of utility generic functional requirements for electronic work packages and computer-based procedures - 273

The Nuclear Electronic Work Packages - Enterprise Requirements (NEWPER) initiative is a step toward a vision of implementing an eWP framework that includes many types of eWPs. This will enable immediate paper-related cost savings in work management and provide a path to future labor efficiency gains through enhanced integration and process improvement in support of the Nuclear Promise (Nuclear Energy Institute 2016). The NEWPER initiative was organized by the Nuclear Information Technology Strategic Leadership (NITSL) group, which is an organization that brings together leaders from the nuclear utility industry and regulatory agencies to address issues involved with information technology used in nuclear-power utilities. NITSL strives to maintain awareness of industry information technology-related initiatives and events and communicates those events to its membership. NITSL and Light Water Reactor Sustainability Program researchers have been coordinating activities, including joint organization of NEWPER-related meetings and report development. The main goal of the NEWPER initiative was to develop a set of utility generic functional requirements for eWP systems. This set of requirements will support each utility in their process of identifying plant-specific functional and non-functional requirements. The NEWPER initiative has 140 members where the largest group of members consists of 19 commercial U.S. nuclear utilities and eleven of the most prominent vendors of eWP solutions. Through the NEWPER initiative two sets of functional requirements were developed; functional requirements for electronic work packages and functional requirements for computer-based procedures. This paper will describe the development process as well as a summary of the requirements. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Application of Genetic Algorithm (GA) Assisted Partial Least Square (PLS) Analysis on Trilinear and Non-trilinear Fluorescence Data Sets to Quantify the Fluorophores in Multifluorophoric Mixtures: Improving Quantification Accuracy of Fluorimetric Estimations of Dilute Aqueous Mixtures

Excitation-emission matrix fluorescence (EEMF) and total synchronous fluorescence spectroscopy (TSFS) are the 2 fluorescence techniques that are commonly used for the analysis of multifluorophoric mixtures. These 2 fluorescence techniques are conceptually different and provide certain advantages over each other. The manual analysis of such highly correlated large volume of EEMF and TSFS towards developing a calibration model is difficult. Partial least square (PLS) analysis can analyze the large volume of EEMF and TSFS data sets by finding important factors that maximize the correlation between the spectral and concentration information for each fluorophore. However, often the application of PLS analysis on entire data sets does not provide a robust calibration model and requires application of suitable pre-processing step. The present work evaluates the application of genetic algorithm (GA) analysis prior to PLS analysis on EEMF and TSFS data sets towards improving the precision and accuracy of the calibration model. The GA algorithm essentially combines the advantages provided by stochastic methods with those provided by deterministic approaches and can find the set of EEMF and TSFS variables that perfectly correlate well with the concentration of each of the fluorophores present in the multifluorophoric mixtures. The utility of the GA assisted PLS analysis is successfully validated using (i) EEMF data sets acquired for dilute aqueous mixture of four biomolecules and (ii) TSFS data sets acquired for dilute aqueous mixtures of four carcinogenic polycyclic aromatic hydrocarbons (PAHs) mixtures. In the present work, it is shown that by using the GA it is possible to significantly improve the accuracy and precision of the PLS calibration model developed for both EEMF and TSFS data set. Hence, GA must be considered as a useful pre-processing technique while developing an EEMF and TSFS calibration model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

All-optical phase conjugation using diffractive wavefront processing

Abstract Optical phase conjugation (OPC) is a nonlinear technique used for counteracting wavefront distortions, with applications ranging from imaging to beam focusing. Here, we present a diffractive wavefront processor to approximate all-optical phase conjugation. Leveraging deep learning, a set of diffractive layers was optimized to all-optically process an arbitrary phase-aberrated input field, producing an output field with a phase distribution that is the conjugate of the input wave. We experimentally validated this wavefront processor by 3D-fabricating diffractive layers and performing OPC on phase distortions never seen during training. Employing terahertz radiation, our diffractive processor successfully performed OPC through a shallow volume that axially spans tens of wavelengths. We also created a diffractive phase-conjugate mirror by combining deep learning-optimized diffractive layers with a standard mirror. Given its compact, passive and multi-wavelength nature, this diffractive wavefront processor can be used for various applications, e.g., turbidity suppression and aberration correction across different spectral bands.

42 ENGINEERING↗

DOE OSTI2019

Manufacturing Thermal Energy Use in 2014

The first data set estimates thermal energy use (i.e., fuels combusted for process heating, boilers, and combined heat and power/cogeneration) by end use, temperature, county, and facility employment size class for all U.S. manufacturing industries in 2014. The estimation methodology builds off of prior estimates of industrial energy use (https://dx.doi.org/10.7799/1481899, https://dx.doi.org/10.7799/1461488). The second data set estimates hourly heat load (as a fraction of annual energy used for heat) using hourly observations of industrial boiler and combined heat and power/cogeneration heat load from EPA's Air Markets Program Data (https://ampd.epa.gov/ampd/), weekly operating hours in 2014 from Census Quarterly Survey of Plant Capacity Utilization (https://www.census.gov/programs-surveys/qpc/data.html), and annual production hours reported by assessments conducted by Industrial Assessment Centers (https://iac.university/).

14 SOLAR ENERGY↗

DOE OSTI2019

Manufacturing Thermal Energy Use in 2014

14 SOLAR ENERGY↗

DOE OSTI2024

Core-Shell Oxidative Aromatization Catalysts for Single Step Liquefaction of Distributed Shale Gas (Final Technical Report)

The objective of this project was to design and demonstrate a core-shell structured multifunctional catalyst to convert the light (dry) components of shale gas into liquid aromatic compounds (primarily benzene and toluene) in a single step. Operated in a modular oxidative aromatization system (OAS) under a cyclic redox scheme, the novel catalyst and process can significantly improve the value and transportability of distributed shale gas. Since the project started, each quarter addressed a different set of tasks related to the completion of the milestone detailed in the project award. The yearly summaries of these tasks are summarized below: Q1-Q4: • Conducted project planning and literature search. • Investigated a number of SHC redox catalysts using thermogravimetric analysis and fixed-bed reactor experiments. • Initiated process modeling towards generating two process models for the methane DHA base case and OAS process. • Developed DHA catalysts capable of producing >500 g/kg-cat-hr aromatics at 80% or greater aromatics selectivity at 700°C. Q5-Q8: • Developed alternative approaches with sequential bed configurations to enhance the aromatic yields based on OCM+DHA • Improved the zeolite synthesis efficiency by using the microwave-assisted technique and investigated the synthesis conditions on the zeolite yield, crystalline structure and morphology • Constructed a set of Aspen Plus process models with significant energy savings for OAS as compared to the base case non-oxidative DHA. • Adapted conventional hydrothermal method to be applicable to the microwave synthesizer unit for more efficient catalyst synthesis. • Studied the structure of the OCM catalyst and the dispersion of the carbonate in the redox reactions and in methane flow with Raman Spectroscopy. Q9-Q12: • Scaled up the catalyst synthesis with the microwave synthesis method. Based on its performance, procedural characterizations and catalytic performance testing were further conducted for the new microwave synthesized catalysts with the newly-developed product analysis procedure. • Developed the reaction system setup for the C2-DHA or OCM+DHA reaction product and achieved a better product collection-analysis method for the aromatic products with an improved carbon balance. The product from the OCM reaction exhibited complicated effects on the DHA catalyst. • Conducted additional OCM catalyst characterization using Near Ambient Pressure X-ray Photoelectron Spectroscopy and in situ Raman characterization • Validated the significant energy savings for OAS as compared to the base case non-oxidative DHA. Successfully set up the simulation model for the OCM+DHA+SHC reaction system based on the updated experimental results from NCSU. Q13-End of project: • Synthesized new zeolite catalysts by the microwave method, conducted characterizations (XRD, SEM, and TEM) and catalytic behavior testing. • Explored the “wet” C 2 H 6 and C 2 H 4 DHA reactions with using steam co-feed. A subsequent reduction as the regeneration step can regenerate the DHA catalyst and recover 99% activity of the fresh performance. • Achieved a 15.3% single-pass aromatic yield from methane by rationally combining the OCM and DHA at different temperatures. • Conducted a 105-hour stability test with an improved regeneration procedure, with an average aromatic yield of 13.8%. • Developed new catalyst and achieved a record-high 23.2% yield.

03 NATURAL GAS↗

DOE OSTI2019

The Power of Environmental Observatories for Advancing Multidisciplinary Research, Outreach, and Decision Support: The Case of the Minnesota River Basin

Observatory-scale data collection efforts allow unprecedented opportunities for integrative, multidisciplinary investigations in large, complex watersheds, which can affect management decisions and policy. Through the National Science Foundation-funded REACH (REsilience under Accelerated CHange) project, in collaboration with the Intensively Managed Landscapes-Critical Zone Observatory, we have collected a series of multidisciplinary data sets throughout the Minnesota River Basin in south-central Minnesota, USA, a 43,400-km 2 tributary to the Upper Mississippi River. Postglacial incision within the Minnesota River valley created an erosional landscape highly responsive to hydrologic change, allowing for transdisciplinary research into the complex cascade of environmental changes that occur due to hydrology and land use alterations from intensive agricultural management and climate change. Data sets collected include water chemistry and biogeochemical data, geochemical fingerprinting of major sediment sources, high-resolution monitoring of river bluff erosion, and repeat channel cross-sectional and bathymetry data following major floods. The data collection efforts led to development of a series of integrative reduced complexity models that provide deeper insight into how water, sediment, and nutrients route and transform through a large channel network and respond to change. These models represent the culmination of efforts to integrate interdisciplinary data sets and science to gain new insights into watershed-scale processes in order to advance management and decision making. Finally, the purpose of this paper is to present a synthesis of the data sets and models, disseminate them to the community for further research, and identify mechanisms used to expand the temporal and spatial extent of short-term observatory-scale data collection efforts.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

U redox state tracked in mineralized hydrothermal carbonate with implications for U-Pb geochronology

U-Pb carbonate geochronology can directly constrain the timing and rates of important geological processes. However, the mechanisms and controls on U incorporation, distribution, and retention in carbonate minerals remain unclear, limiting geological interpretations. Here X-ray absorption spectroscopy (µXAS) and in-situ U-Pb carbonate geochronology are combined to temporally track U distribution and redox state in a porphyry-epithermal system. In this setting, multiple generations of carbonate minerals record fluid conditions and processes which control the solubility and deposition of metals, including U. This novel approach provides the first evidence of both oxidized UO 2 2+ and reduced U 4+ species in temporally distinct generations of carbonate within a single sample. Preservation of two different U oxidation states during discrete precipitation events requires U retentivity within older domains, demonstrating that the U-Pb carbonate geochronometer is robust under hydrothermal conditions. Furthermore, crystal zones with abundant fluid/vapour inclusions linked to boiling processes coincide with relatively high levels of U and favourable U/Pb. Targeting carbonate domains with these textures may therefore increase success in U-Pb geochronology. U-Pb carbonate dating combined with µXAS can track the temporal evolution of processes critical for metal deposition in long-lived and multistage hydrothermal-magmatic ore deposit settings.

58 GEOSCIENCES↗

DOE OSTI2019

An MINLP formulation for the optimization of multicomponent distillation configurations

Designing configurations for multicomponent distillation, a ubiquitous process in chemical and petrochemical industries, is often challenging. This is because, as the number of components increases, the number of admissible distillation configurations grows rapidly and these configurations vary substantially in their energy needs. Consequently, if a method could identify a few energy-efficient choices from this large set of alternatives, it would be extremely attractive to process designers. This paper develops here such a method by solving a Mixed Integer Nonlinear Program (MINLP) that is formulated to pick, among the regular-column configurations of Shah and Agrawal (2010b), those configurations that have a low vapor-duty requirement. To compute the minimum vapor-duty requirement for each column within the configuration, we use techniques that rely on the Underwood’s method. The combined difficulty arising from the nonlinearity of Underwood equations and the combinatorial explosion of the choice-set of alternatives poses unmistakable challenges for the branch-and-bound algorithm, the current method of choice to globally solve MINLPs. To address this difficulty, we exploit the structure of Underwood equations and derive valid cuts that expedite the convergence of branch-and-bound by enabling global solvers, such as BARON, infer tighter bounds on Underwood roots. This provides a quick way to identify a few lucrative alternative configurations for separation of a given non-azeotropic mixture. We illustrate the practicality of our approach on a case-study concerning heavy-crude distillation and on various other examples from the literature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Thermodynamic modeling of MDEA(aq)-NH 3 (aq)-K 2 CO 3 (aq)-CO 2 (aq) using the Extended UNIQUAC model

Here, the development of advanced processes for carbon dioxide capture requires reliable thermodynamic models to ensure accurate process design. This work presents an optimized parameter set of the Extended UNIQUAC model for advanced mixed solvent solutions containing CO 2 -MDEA-NH 3 -K 2 CO 3 in water. The model was parameterized using vapor–liquid equilibrium, pure component saturation pressure, excess enthalpy, heat of absorption, molar heat capacity, apparent molar heat capacity, and solid–liquid equilibrium. These thermal and equilibrium properties cover temperatures between 253.6 K to 600 K and pressures up to 75.6 bar. The current model represents an extension of previous versions that were suitable for modeling aqueous NH 3 and K 2 CO 3 solutions. This parametrization accounts for molecular interactions between MDEA and these two components, which allows for the design of advanced capture processes. This paper demonstrates that the new model parameters are valid within the range of operational conditions typically found in CO 2 capture processes.

42 ENGINEERING↗

DOE OSTI2023

MOSAiC Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility deployed many instruments on board a German ice breaker, the Research Vessel (RV) Polarstern, for one year from October 2019 to October 2020. The purpose of the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign was to study the decline in the sea-ice pack around the North Pole, and what factors may be at play. After the campaign ended, efforts were undertaken to provide a calibrated radar data set for future studies. MOSAiC presented new challenges to this process, as existing methodologies often were not applicable for the frozen environment with little to no ground clutter, and concurrent engineering updates or calibrations could not be accomplished once the ship set off. Like the previous Cloud, Aerosol, and Complex Terrain Interactions (CACTI) and Cold-air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) documentation (Hardin et al. 2020, Matthews et al. 2023), the data correction and calibration process is known in ARM as creating a “b1” datastream. This means that the radar datastreams have been well characterized to the best possible quality. This report will detail the status of the raw “a1” level data sets during the MOSAiC campaign, the corrections that were applied to create the “b1” data files, and the details of the applied methods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Microbial sensitivity to temperature and sulfate deposition modulates greenhouse gas emissions from peat soils

Abstract Peatlands are among the largest natural sources of atmospheric methane (CH 4 ) worldwide. Microbial processes play a key role in regulating CH 4 emissions from peatland ecosystems, yet the complex interplay between soil substrates and microbial communities in controlling CH 4 emissions as a function of global change remains unclear. Herein, we performed an integrated analysis of multi‐omics data sets to provide a comprehensive understanding of the molecular processes driving changes in greenhouse gas (GHG) emissions in peatland ecosystems with increasing temperature and sulfate deposition in a laboratory incubation study. We sought to first investigate how increasing temperatures (4, 21, and 35°C) impact soil microbiome–metabolome interactions; then explore the competition between methanogens and sulfate‐reducing bacteria (SRBs) with increasing sulfate concentrations at the optimum temperature for methanogenesis. Our results revealed that peat soil organic matter degradation, mediated by biotic and potentially abiotic processes, is the main driver of the increase in CO 2 production with temperature. In contrast, the decrease in CH 4 production at 35°C was linked to the absence of syntrophic communities and the potential inhibitory effect of phenols on methanogens. Elevated temperatures further induced the microbial communities to develop high growth yield and stress tolerator trait‐based strategies leading to a shift in their composition and function. On the other hand, SRBs were able to outcompete methanogens in the presence of non‐limiting sulfate concentrations at 21°C, thereby reducing CH 4 emissions. At higher sulfate concentrations, however, the prevalence of communities capable of producing sufficient low‐molecular‐weight carbon substrates for the coexistence of SRBs and methanogens was translated into elevated CH 4 emissions. The use of omics in this study enhanced our understanding of the structure and interactions among microbes with the abiotic components of the system that can be useful for mitigating GHG emissions from peatland ecosystems in the face of global change.

AminiTabrizi, Roya↗

DOE OSTI2023

Blackout Diffusion: Generative Diffusion Models in Discrete-State Spaces

Typical generative diffusion models rely on a Gaussian diffusion process for training the backward transformations, which can then be used to generate samples from Gaussian noise. However, real world data often takes place in discrete-state spaces, including many scientific applications. Here, we develop a theoretical formulation for arbitrary discrete-state Markov processes in the forward diffusion process using exact (as opposed to variational) analysis. We relate the theory to the existing continuous-state Gaussian diffusion as well as other approaches to discrete diffusion, and identify the corresponding reverse-time stochastic process and score function in the continuous-time setting, and the reverse-time mapping in the discrete-time setting. As an example of this framework, we introduce “Blackout Diffusion”, which learns to produce samples from an empty image instead of from noise. Numerical experiments on the CIFAR-10, Binarized MNIST, and CelebA datasets confirm the feasibility of our approach. Generalizing from specific (Gaussian) forward processes to discrete-state processes without a variational approximation sheds light on how to interpret diffusion models, which we discuss.

Santos, Javier E.↗

DOE OSTI2023

Discovering Active Subspaces for High-Dimensional Computer Models

Dimension reduction techniques have long been an important topic in statistics, and active subspaces (AS) have received much attention this past decade in the computer experiments literature. The most common approach towards estimating the AS is to use Monte Carlo with numerical gradient evaluation. While sensible in some settings, this approach has obvious drawbacks. Recent research has demonstrated that active subspace calculations can be obtained in closed form, conditional on a Gaussian process (GP) surrogate, which can be limiting in high-dimensional settings for computational reasons. In this paper, we produce the relevant calculations for a more general case when the model of interest is a linear combination of tensor products. These general equations can be applied to the GP, recovering previous results as a special case, or applied to the models constructed by other regression techniques including multivariate adaptive regression splines (MARS). Furthermore, using a MARS surrogate has many advantages including improved scaling, better estimation of active subspaces in high dimensions and the ability to handle a large number of prior distributions in closed form. In one real-world example, we obtain the active subspace of a radiation-transport code with 240 inputs and 9,372 model runs in under half an hour.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

EMT-related long non-coding RNA in hepatocellular carcinoma: A study with TCGA database

Highlights: • Integrated analysis identifies EMT-associated lncRNA in HCC. • Candidate lncRNA-associated genes are enriched in EMT-linked pathways. • LncRNA WDFY3-AS3, MIAT, and MEG3 contribute to the EMT phenotype of HCC cells. Accumulating evidence suggest that dysregulated expression of long non-coding RNA (lncRNA) plays a critical role in human tumorigenesis. However, little is known about the lncRNA implicated in the epithelial-to-mesenchymal transition (EMT) process. In this study, we performed data mining in The Cancer Genome Atlas (TCGA) hepatocellular carcinoma (HCC) data set and identified the a spectrum of differentially expressed lncRNAs implicated the EMT process of HCC, and functionally validated their roles in LM3 cells. Especially, lncRNA WDFY3-AS2-, LINC00472-, MIAT-, and MEG3-associated genes were significantly enriched in EMT-linked pathways. Loss-of-function study showed that genetic silencing of WDFY3-AS3, MIAT, and MEG3, but not LINC00472, resulted in reduced N-cadherin expression, cell migration, and cell invasion. Collectively, our results identify several lncRNAs that regulate the EMT process of HCC, which provides critical information for HCC tumorigenesis and potential therapeutic targets.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2018

Progress Summary: 12-Month Compression Set and Load Retention of Thermally Accelerated Aged Siloxane Specimens (Additively Manufactured by the Direct-Ink-Write (DIW) 3D Printing Technique) Was Measured

Motivation: Accelerated aging of polymeric materials is needed to predict their long-term mechanical functionality. Two key metrics used to evaluate their performance are compression set and load retention. A baseline(time=0)mechanical assessment was done prior to initiating the accelerated aging process to acquire initial thickness and load values for future calculation of compression set and load retention.Specimens are beingaged under compressive strain (13%for the current studies) at four different temperatures (25, 40, 55, and 70°C) for at least 1 year; compression set and load retention will be measured at various timepoints. Time-temperature superposition (TTS) will be applied to the isothermal data to obtain long-term predictions. Significance: Compression set is increasing with time and temperature, as expected. The increasing compression set is accompanied by decreasing load retention.The relativelylow compression set indicates the material is performing well.In a previous aging study, the legacy S5370 RTV foam exhibited 40% relative compression set after 12 months at 70°C, which is more than twice that of the DIW material. Progress:Data has been acquired out to the 12-month timepoint. Relative compression set and load retention versus time are shown in Fig. 1.A technical issue with the method of measuring load retention was discovered and previously reported load retention values have been adjusted; the current load retention values are estimates. TTS predictions are shown in Fig. 2.

36 MATERIALS SCIENCE↗

DOE OSTI2019

Progress Summary: 17-Month Compression Set and Load Retention of Thermally Accelerated Aged Siloxane Specimens (Additively Manufactured by the Direct-Ink-Write (DIW) 3D Printing Technique) was Measured

Accelerated aging of polymeric materials is needed to predict their long-term mechanical functionality. Two key metrics used to evaluate their performance are compression set and load retention. A baseline (time = 0) mechanical assessment was done prior to initiating the accelerated aging process to acquire initial thickness and load values for future calculation of compression set and load retention.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Parametrically amplified Josephson plasma waves in YBa 2 Cu 3 O 6+ x : Evidence for local superconducting fluctuations up to the pseudogap temperature T ∗

Experiments that subject underdoped YBa 2 Cu 3 O 6+x (YBCO) to intense terahertz pulses at temperatures between the transition temperature T c and the pseudogap scale T ∗ have revealed a reflectivity edge that resembles that of the superconducting state, together with second harmonic generation of a probe pulse modulated at a similar frequency. These have been interpreted in terms of parametric amplification of the lower Josephson plasmon mode. Since this mode is often associated with coherent oscillations between bilayers in the YBCO structure, these experiments have led to the suggestion that the intense pump has created (or revealed) in-plane pair coherence up to T ∗ ≈ 400 K. In this paper we propose an alternative explanation by assuming the existence of local pair amplitude and phase at equilibrium for T c < T < T ∗ . The phase correlation spans only a few lattice constants and we do not assume any pump-induced enhancement of this correlation, either in-plane or between bilayers. Instead, the coherent drive, via a parametric amplification process, induces coherence in the Josephson currents between members of bilayers. When combined with a Floquet framework, the reflectivity data can be explained. The key point is that in the lower Josephson plasmon, the coupling between bilayers is mainly capacitive; the Josephson current between bilayers can be set to zero without strongly affecting the parametric amplification process. Importantly, while superconducting coherence may not be created by the pump, the pseudogap phase must possess a local pairing amplitude at equilibrium. Consequently, these experiments have strong implications for the understanding of the pseudogap phase.

parametric amplification↗