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At least 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Artificial Intelligence for Natural Gas Utilities: A Primer

Modern natural gas utilities face numerous challenges and competing priorities from various stakeholders. Policymakers, customers, and advocacy groups want to see gas utilities improve performance on safety, reliability, resilience, affordability, and environmental stewardship. State utility regulators — public utility commissions — are responsible for overseeing utility performance, ensuring that ratepayer funds are being spent in the public interest, and aligning utility goals with public goals. The use of new technologies is critical to enabling cost-effective performance on these attributes. Artificial intelligence (AI) is a widely used term among utilities and regulators, but the term means different things to different stakeholders, and it is often used to describe data analytics approaches that fall short of the formal definition of AI, which is: “…the ability of a machine to receive inputs and produce a behavior or reaction similar to that of an intelligent human being.” AI (and related tools, techniques, and technologies) can help utilities solve current and emerging challenges. By combining customer and system data with analytical tools and technologies, AI can augment human decision-makers by assisting in identifying problems and events before they occur, enabling resources to be more efficiently directed across utility infrastructure. The intended primary audience for this primer is state regulators, although utilities and other stakeholders might also find it useful and relevant to improve their awareness of AI. The objectives of this primer are to: (a) offer a set of broadly applicable definitions for AI and related terms, allowing regulators, utilities, and other stakeholders to speak the same language; (b) discuss how AI is currently being implemented in the gas utility sector; and (c) understand the challenges affecting AI solutions and how tools might be implemented in the future. This primer fits within NARUC’s goals of providing impartial information to improve the ability of public utility commissions to regulate in the public interest. As such, this primer does not seek to recommend AI over any other investment, nor does it endorse any particular vendor, product, or approach. It does seek to prepare state regulators to oversee AI investments by sharing information about the current landscape of commercially available tools. To these ends, the primer is organized as follows: Section I discusses the current environment in which natural gas utilities operate and how AI, when thoughtfully designed and implemented, can enable utilities to achieve performance goals; Section II offers definitions of AI and related terms within the data analytics discipline; Section III provides three current opportunities for which AI can offer solutions: replacing aging gas distribution infrastructure, preventing excavator damage to gas distribution infrastructure, and improving energy efficiency programs. This section discusses each problem statement in detail. Second, Section III includes a discussion of how costs and benefits of investments to solve each problem are measured. And third, this section offers real-world examples of utility implementation of AI solutions; Section IV discusses challenges with implementing AI, both from the perspective of utilities and regulators; Section V suggests areas in which AI could feasibly be implemented in the near future; Finally, Section VI offers concluding thoughts and areas for further research.

03 NATURAL GAS↗
DOE OSTI2024

Concurrent measurement of strain and chemical reaction rates in a calcite grain pack undergoing pressure solution: Evidence for surface-reaction controlled dissolution

Pressure solution is inferred to be a significant contributor to sediment compaction and lithification, especially in carbonate sediments. For a sediment deforming primarily by pressure solution, the compaction rate should be directly related to the rate of calcite dissolution, transport along grain contacts, and calcite reprecipitation. Previous experimental work has shown that there is evidence that deformation in wet calcite grain packs is consistent with control by pressure solution, but considerable ambiguity remains regarding the rate limiting mechanism. We present the results of laboratory compaction experiments designed to directly measure calcite dissolution and precipitation rates (recrystallization rates) concurrently with strain rate to test whether measured rates are consistent with predicted rates both in absolute magnitude and time evolution. Recrystallization rates are measured using trace element chemistry (Sr/Ca, Mg/Ca) and isotopes (87Sr/86Sr) of fluids flowing slowly through a compacting grain pack as it is being triaxially compressed. Imaging techniques are used to characterize the grain contacts and strain effects in the post-experiment grain pack. Our data show that calcite recrystallization rates calculated from all three geochemical parameters are in approximate agreement and that the rates closely track strain rate. The geochemically inferred rates are close to predicted rates in absolute magnitude. Uncertainty in grain contact dimensions makes distinguishing between surface reaction control and diffusion control difficult. Measured reaction rates decrease faster than predicted from standard pressure solution creep flow laws. This inconsistency may indicate that calcite dissolution rates at grain contacts are more complex, and more time-dependent, than suggested by geometric models designed to predict grain contact stresses.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Semi-analytic model of magnetized liner inertial fusion

The code that was developed is called SAMM (Semi-Analytic MagLIF Model). In 2015, McBride and Slutz published all of the equations that are solved by the code in the original SAMM paper: R. D. McBride and S. A. Slutz, ?A semi-analytic model of magnetized liner inertial fusion?, Phys. Plasmas 22, 052708 (2015); http://doi.org/10.1063/1.4918953. The SAMM code is now implemented in both the MATLAB and Python programming languages. Students from multiple universities have requested copies of the code so that they can become more familiar with the MagLIF concept. We would like to seek an open-source solution. There is no market value to this code, as there are plenty of more sophisticated simulation codes already available; SAMM is merely a simplified model that is purely for educational purposes. In fact, at least one graduate student (from the University of California, San Diego) has already implemented and published his own modified version of the model: J. Narkis, H. U. Rahman, J. C. Valenzuela, F. Conti, R. D. McBride, D. Venosa, and F. N. Beg, ?A semi-analytic model of gas-puff liner-on-target magneto-inertial fusion?, Phys. Plasmas 26, 032708 (2019); https://doi.org/10.1063/1.5086056. SAND2020-12244 M 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.

Moore, Thomas↗
DOE OSTI2020

A conspicuous 27 Al-NMR signal at 72 ppm during isomerization of Keggin Al 13 ions

A sharp signal at 72 ppm was recently observed in 27 Al-NMR spectra during the isomerization of Keggin-Al 13 ions in the presence of calcium and glycine [1]. It has been proposed that this signal corresponds to one of the Keggin isomers. Conversion of the most common ε-isomer of the Keggin series of molecules, having the stoichiometry [AlO 4 Al 12 (OH) 24 (OH 2 ) 12 ] 7+ , is enhanced by the addition of calcium and glycine [2,3]. Here we show that a 72 ppm signal can also be observed in the absence of calcium or glycine; the magnitude of which depends on aluminum concentration and temperature. Additionally, isomerization of the ε-Keggin-Al 13 to the γ-Keggin-Al 13 isomer was observed in the absence of calcium and glycine at elevated temperatures after several days. Furthermore, calcium and glycine were previously shown to enhance rates of γ-Keggin-Al 13 formation. 2.

27Al-NMR↗
DOE OSTI2021

On steady alternate bars forced by a localized asymmetric drag distribution in erodible channels

Studying the effect of different in-stream fluvial turbines siting on river morphodynamics allowed us to witness the onset of a time-averaged, large-scale, alternate distortion of bed elevations, which could not be exclusively related to the turbine rotor blockage. The longitudinal profiles of this two-dimensional bathymetric perturbation resemble those of steady fluvial bars. In this contribution we generalize the problem addressing a spatially impulsive, asymmetric distribution of drag force in the channel cross-section. Furthermore, this is experimentally investigated through the deployment of differently sized grids perpendicular to the flow, and analytically explored as a finite perturbation of an open channel flow over an erodible sediment layer, as described by a coupled flow–sediment shallow water equation. The steady solutions of this fluvial morphodynamic problem, physically represented by alternate bars scaling with the channel width, highlight the importance of the resonant conditions in defining the spatial extent of the bed deformation. The equations further suggest that in very shallow flows any asymmetric obstruction may lead to an upstream propagation of the steady bars, consistent with previous studies on the effects of channel curvature. In broad terms, this study provides the preliminary framework to control the onset of river meandering through imposed finite perturbations of the cross-section. In a more applied sense, it provides a tool to predict non-local scour–deposition patterns associated with the deployment of energy converters or other flow obstructions.

42 ENGINEERING↗
DOE OSTI2020

Evaluating the efficacy and equity of environmental stopgap measures

Contemporary environmental policy is rife with measures that do not fully resolve a problem, but instead are proposed to “buy time” for the development and future implementation of more durable solutions. In this perspective, we define such measures as “stopgap measures,” and examine examples from wildfire risk management, hydrochlorofluorocarbon regulation, and Colorado River water management. We introduce an analytical framework to assess stopgaps, and apply this framework to solar geoengineering, a controversial stopgap for climate action. Studying stopgaps as a novel category of policy and management measures can help us understand the why stopgaps emerge, and weigh the equity and efficacy of stopgaps against other policy proposals

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Finite deformation implementation of a mixed-mode single-integral type cohesive zone with reorienting surfaces of separation

To model material ductile failure and crack propagation, cohesive zone elements can be embedded along potential fracture paths in a finite element simulation. When damage criteria are met, elements in the mesh decohere, simulating the formation and propagation of a crack. In this paper, we present a novel computational algorithm based on finite deformation theory, essential to modeling crack initiation and growth in solids undergoing large deformations. This new algorithm was formulated within a Lagrangian frame of reference to extend previous cohesive zone algorithms to include modeling crack growth in finite deformation contexts. The local coordinate system, necessary for defining an embedded cohesive zone, is constructed based upon the current configuration and is updated within the nonlinear iteration process, thereby resulting in the convergence of the solution for a growing crack in a large deformation quasi-static setting. The model’s accuracy was demonstrated by comparing finite element model simulation results with the analytic case of a constant surface separation, as shown in the verification examples. The power and efficacy of the algorithm to capture large deformations during crack growth were then demonstrated with a double cantilever beam example case. It indicates that the model can be applied to a variety of physical circumstances for predicting crack initiation and growth with delamination and fracture.

42 ENGINEERING↗
DOE OSTI2024

Improving Additive Manufactured Component Performance through Multi-Scale Microstructure Simulation and Process Optimization

The purpose of this project was to utilize computational tools to understand the relationships between processing, microstructure, and properties for additively manufactured (AM) aluminum alloys for automotive applications, and to provide an engineering solution for helping to optimize process conditions. The project leverages ORNL developments in computational modeling, including AM process modeling, phase-field based microstructure evolution predictions, and data analytics techniques for mapping process conditions to material outcomes. The project utilized an Al-Cu-Mn-Zr alloy as a model material for studying formation of defects and microstructural features in response to variations in process conditions. Based on both pre-existing experimental data and simulation results, statistical process maps were constructed to identify regions of process space with minimal defect formation and advantageous microstructures and properties. The software tools used for this purpose were successful disseminated to GM, who were able to successful compile the relevant HPC codes within their own computing ecosystem and perform initial calculations to reproduce ORNL results.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Water and Solute Activities Regulate CO 2 Reduction in Gas-Diffusion Electrodes

Electrolysis of CO 2 at gas-diffusion electrodes (GDEs) has typically been limited by the supply of gas to the electrocatalyst, overshadowing the importance of the supply of water. However, at high current densities that approach 1 A cm –2 , where the electrolyte becomes highly concentrated in the catalyst layer of a GDE, the activity of water and solutes deviate from their bulk dilute solution values, potentially slowing reaction rates and changing reaction equilibrium potentials. In addition, as flow plates for the gas stream are introduced to enable larger electrodes and high single pass conversion of CO 2 to product, variations in the gas composition will become important. By drawing upon literature for the oxygen reduction reaction (ORR), here we explain how to account for these effects in future modeling and experimental work, with particular attention to accurate use of the Nernst equation for electrode potentials and the Arrhenius equation for reaction rates. Specifically, using measurements of KOH solvent and solute activity reported in literature, and assuming the second protonation of CO 2 by water as the rate-determining step, we show the Nernst equation dilute-solution approximation of the CO 2 to CO equilibrium potential to be accurate below 5 M KOH, but it has a 74 mV error when increasing the concentration up to 10 M KOH. Finally, a simple one-dimensional model of a serpentine flow-field on a GDE demonstrated that a reactor with constant pressure of 1 bar and 1 A cm –2 at the inlet had only ~0.3 A cm –2 at the outlet for a conversion in CO 2 partial pressure from 0.90 to 0.48 bar, showing the significant practical implications of this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

What Is the Smallest Zeolite That Could Be Synthesized?**

Zeolites with a few unit cells are promising as catalyst and adsorbents. The quest to synthesize the smallest zeolites has recently resulted in 4 to 8 nm nanozeolites, about 2 to 4 unit cells. These findings pose the question of what is the smallest zeolite that could be obtained by hydrothermal synthesis. We address this question using molecular simulations and thermodynamic analysis. The simulations predict that amorphous precursors as small as 4 nm can crystallize zeolites, in agreement with the experiments. We find that interfacial forces dominate the structure of smaller particles, resulting in size-dependent compact isomers that have ring and pore distributions different from open framework zeolites. The instability of zeolites smaller than 3±0.5 nm precludes a classical mechanism of nucleation from solution or through assembly of small nanoslabs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Application of spectroscopic evidence to diffuse layer model (DLM) parameter estimation for cation adsorption onto ferrihydrite in single- and bi-solute systems

The diffuse layer model (DLM) is one of the most frequently used surface complexation models (SCM) for predicting cation adsorption onto ferrihydrite. However, the DLM with its existing database sometimes fails to predict cation adsorption, especially in multi-solute systems. Notably, the failure is often attributed to inaccurate selection of the surface complexes and/or underestimation of the site density for DLM formulation. DLM simulations of batch adsorption data conducted with cadmium, copper, lead, and zinc on ferrihydrite in CO2 free systems demonstrates the ability of the DLM to fit single-solute data reasonably well but highlights its limitations with respect to predicting bi-solute data. Modifications to the DLM were made in two steps. First, spectroscopic evidence was used to guide cation complexation reactions at the ferrihydrite surface. Second, surface characteristics (reactive site density, specific surface area, and acidity constants) of ferrihydrite were updated according to recent literature. The results from this study suggest that when spectroscopic verification is employed and surface site density is increased, a simple two-site DLM can predict cation adsorption on ferrihydrite in single-solute systems for pH data above 3.5 and in most of the bi-solute systems tested.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Photobiocatalysis for Abiological Transformations

Harnessing biocatalysts for novel abiological transformations is a longstanding goal of synthetic chemistry. Combining the merits of biocatalysis and photocatalysis allows for selective transformations fueled by visible light and offers many advantages including new reactivity, high enantioselectivity, greener syntheses, and high yields. Photoinduced electron or energy transfer enables synthetic methodologies that complement conventional two electron processes or offer orthogonal pathways for developing new reactions. Enzymes are well suited and can be tuned by directed evolution to exert control over radical intermediates thereby suppressing undesirable reactions and delivering high chemo- and stereoselectivities. Within the past decade, the combination of biocatalysis and photocatalysis was mainly focused on exploiting light-regenerated cofactors to increase native enzymatic activity. However, recent developments have demonstrated that the combination can unlock new-to-nature chemistry. Particularly, the discovery and application of new strategies are well poised to expand the applications of photobiocatalysis. In the past three years, our lab has been studying the combinations of photocatalysis and biocatalysis which can be applied to create new synthetic methodologies and solve challenges in synthetic organic chemistry. Our efforts have expanded the strategies for combining external photocatalysts with enzymes through the construction of a synergistic cooperative stereoconvergent reduction system consisting of photosensitized energy transfer and ene-reductase catalyzed alkene reduction. Additionally, our efforts have also extended the capability of cofactor-dependent photoenzymatic systems to include enantioselective bimolecular radical hydroalkylations of alkenes by irradiating electron donor-acceptor complexes comprised of enzymatic redox active cofactors and unnatural substrates. In this Account, we highlight strategies developed by our group and others for combining biocatalysis and photocatalysis with the aim of introducing nonnatural reactivity to enzymes. Presently, strategies applied to achieve this goal include the repurposing of newly discovered photoactive enzymes, the elucidation of new photoreactivity within cofactor-dependent enzymes, the combination of external photocatalysts with enzymes, and the construction of artificial photoenzymes. By demonstrating the successful application of these strategies for achieving selective new-to-nature transformations, we hope to spur interest in the expanding the scope of photobiocatalytic systems through the use and extension of these strategies and creation of new strategies. In addition, we hope to elucidate the intuition in synergizing the unique capabilities of biocatalysis and photocatalysis so that photobiocatalysis can be recognized as a potential solution to difficult challenges in synthetic organic chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Effect of Solvent Quality on Structure and Dynamics of Lignin in Solution

The conversion of lignin into useful chemicals and monomers requires that different linkages connecting monomers are exposed to the catalytic sites. As most conversion processes are expected to occur in the liquid phase, it is important to understand the structure and dynamics of lignin in solution. Here, we have examined the structure and dynamics of hardwood- and softwood-derived lignin model compounds with 61 monomers in methanol/water solution.

09 BIOMASS FUELS↗
DOE OSTI2024

Force Fields for High Concentration Aqueous KOH Solutions and Zincate Ions

Motivated by increasing interest in electrochemical devices that include highly alkaline electrolytes, we investigated two force fields for potassium hydroxide (KOH) at high concentrations in water. The “FNB” model uses the SPC/E water model, while the “FHM” model uses the TIP4P/2005 water model. Here, we also developed parameters to describe zincate ions in these solutions. The density and viscosity of KOH using the FHM model are in better agreement with experiment than the values from the FNB model. Comparing the properties of the zincate solutions to the available experimental data, we find that both force fields agree reasonably well, although the FHM parameters give a better prediction of the viscosity. The developed force field parameters can be used in future simulations of zincate/KOH solutions in combination with other species of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Electrodeposition of Complex High Entropy Oxides via Water Droplet Formation and Conversion to Crystalline Alloy Nanoparticles

We report that a combination of electrodeposition and thermal reduction methods have been utilized for the synthesis of ligand-free FeNiCo alloy nanoparticles through a high-entropy oxide intermediate. These phases are of great interest to the electrocatalysis community, especially when formed by a sustainable chemistry method. This is successfully achieved by first forming a complex five element amorphous FeNiCoCrMn high-entropy oxide (HEO) phase via electrodeposition from a nanodroplet emulsion solution of the metal salt reactants. The amorphous oxide phase is then thermally treated and reduced at 570–600 °C to form the crystalline FeNiCo alloy with a separate CrMnO x cophase. The FeNiCo alloy is fully characterized by scanning transmission electron microscopy and energy-dispersive X-ray spectroscopy elemental analysis and is identified as a face-centered cubic crystal with the lattice constant a = 3.52 Å. The unoptimized, ligand-free FeNiCo NPs activity toward the oxygen evolution reaction is evaluated in alkaline solution and found to have an ~185 mV more cathodic onset potential than the Pt metal. Beyond being able to synthesize highly crystalline, ligand-free FeNiCo nanoparticles, the demonstrated and relatively simple two-step process is ideal for the synthesis of tailor-made nanoparticles where the desired composition is not easily achieved with classical solution-based chemistries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Characterizing Heterogeneous Mixtures of Assembled States of the Tobacco Mosaic Virus Using Charge Detection Mass Spectrometry

The tobacco mosaic viral capsid protein (TMV) is a frequent target for derivatization for myriad applications, including drug delivery, biosensing, and light harvesting. However, solutions of the stacked disk assembly state of TMV are difficult to characterize quantitatively due to their large size and multiple assembled states. Charge detection mass spectrometry (CDMS) addresses the need to characterize heterogeneous populations of large protein complexes in solution quickly and accurately. Using CDMS, previously unobserved assembly states of TMV, including 16-monomer disks and odd-numbered disk stacks, have been characterized. We additionally employed a peptide-protein conjugation reaction in conjunction with CDMS to demonstrate that modified TMV proteins do not redistribute between disks. Finally, this technique was used to discriminate between protein complexes of near-identical mass but different configurations. In conclusion, we have gained a greater understanding of the behavior of TMV, a protein used across a broad variety of fields and applications, in the solution state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗