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At least 37 records · Page 2

Anticipating gelation and vitrification with medium amplitude parallel superposition (MAPS) rheology and artificial neural networks

Abstract Anticipating qualitative changes in the rheological response of complex fluids (e.g., a gelation or vitrification transition) is an important capability for processing operations that utilize such materials in real-world environments. One class of complex fluids that exhibits distinct rheological states are soft glassy materials such as colloidal gels and clay dispersions, which can be well characterized by the soft glassy rheology (SGR) model. We first solve the model equations for the time-dependent, weakly nonlinear response of the SGR model. With this analytical solution, we show that the weak nonlinearities measured via medium amplitude parallel superposition (MAPS) rheology can be used to anticipate the rheological aging transitions in the linear response of soft glassy materials. This is a rheological version of a technique called structural health monitoring used widely in civil and aerospace engineering. We design and train artificial neural networks (ANNs) that are capable of quickly inferring the parameters of the SGR model from the results of sequential MAPS experiments. The combination of these data-rich experiments and machine learning tools to provide a surrogate for computationally expensive viscoelastic constitutive equations allows for rapid experimental characterization of the rheological state of soft glassy materials. We apply this technique to an aging dispersion of Laponite ® clay particles approaching the gel point and demonstrate that a trained ANN can provide real-time detection of transitions in the nonlinear response well in advance of incipient changes in the linear viscoelastic response of the system.

Lennon, Kyle R. (ORCID:0000000212515461)↗

Effect of framework Al pairing on NO storage properties of Pd-CHA passive NOx adsorbers

For this study, three Pd/H-CHA samples were prepared containing 53.0%, 10.8% and 6.5% paired Al sites at near fixed Si/Al ratio and similar Pd loading. According to H 2 temperature-programmed reduction, Pd was present almost exclusively as isolated cations in the two samples containing the higher concentrations of paired Al sites, whereas in the other sample PdO was also present. Simulated lean cold start tests on the fresh samples conducted in a microflow reactor showed that the sample containing PdO stored the lowest amount of NOx. When tested with CO/H 2 , the sample containing 53.0% paired Al sites showed significantly better storage capacity than the other samples and deactivated less rapidly upon sequential tests. Experiments using lean gasoline engine exhaust revealed similar trends. This study showed that a high concentration of paired Al sites in Pd/H-CHA is beneficial for NOx storage capacity, thermal durability, and minimizing deactivation in the presence of CO/H 2 .

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Ionization-driven competitive (recovery) process in pre-damaged KTaO 3 : A brief review

The nuclear (S n ) and electronic (S e ) energy dissipation processes have been considered to be independent and largely uncorrelated, influencing our understanding of ion–solid interaction and damage processes in the last decades. Recently, however, it has become more generally accepted that S n and S e are coupled as they interact both in time and space. To decouple these processes, separating these effects in experiments using sequential dual-beam irradiations have become accepted as the logical path to advance the understanding of complex interactions between S e and pre-existing defects that may be created from displacement events. This experimental approach has been recently applied to studies of KTaO 3 to reveal new insights into this critical research topic. Here, we offer a forward-looking and comprehensive perspective on the fundamental coupling between Se and pre-existing defects in KTaO 3 . The origins behind the competitive two-stage phase transition process leading to damage healing are revealed and discussed. Furthermore, the evidence resulting from synergistic effects is also included for comparison. Additionally, our findings are rationalized using both Se and the ion velocity as key parameters. We highlight how the inelastic thermal spike (i-TS) calculations provide insights into the nature of this coupled process and further confirm that the ion velocity effect governs annealing kinetics. This work emphasizes that through the introduction of a small amount of local disorder in materials, MeV ion irradiation (i.e., not extreme S e ) may also be one additional option in subsequent material modification and functionalization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Surface-Initiated Atom Transfer Radical Polymerization Using Hydrogel Reactors

Atom transfer radical polymerization (ATRP) is a controlled radical polymerization method that enables the synthesis of tailored polymeric materials with low dispersity, highlighting its immense potential for green fabrication of advanced materials. However, its broader implementation is limited by challenges in product isolation, maintaining catalyst activity, and mitigating atmospheric sensitivity arising from oxygen-sensitive metal catalysts. Here, gelatin hydrogels (GHs) are introduced as a soft “reactor” matrix for interfacial ATRP, operating with minimal metal-catalyst loading while exhibiting possibly an organoreductive behavior. This strategy leverages activator regeneration via electron transfer through a ligand–metal charge-transfer (LMCT) mechanism to reduce oxidized metal catalysts within the GH network. Polymerization is evaluated by growing polymer brushes at an active interface formed between GHs swollen in monomer solution and an initiating surface, and sequential growth experiments confirmed that GH-mediated ATRP preserves living character. Under UV illumination, LMCT is activated, producing polymers both at the desired interface and within the GH bulk. UV–Vis spectroscopy revealed active reduction of Cu(II) to Cu(I) along with concentration-dependent complex formation, indicating dynamic coordination chemistry within the hydrogel. The redox-active arginine- and glutamic acid-rich gelatin backbone coordinates and reduces the metal center, enabling ATRP at ppm-level catalyst concentrations. While polymerization proceeds in GH-Cu(II) reactors, adding external mobile ligands to the GH results in longer polymer brushes. Here, the results reported here are exploratory. More experiments are needed to characterize polymer brush growth in GHs and compare it to conventional surface-initiated polymerization in solution.

Absorption↗

The association of structural chirality and liquid crystal anchoring in polymer stabilized cholesteric liquid crystals

Polymer stabilized cholesteric liquid crystals (PSCLCs) are electrically reconfigurable reflective elements. Prior studies have hypothesized and indirectly confirmed that the electro-optic response of these composites is associated with the electrically mediated distortion of the stabilizing polymer network. The proposed mechanism is based on the retention of structural chirality in the polymer stabilizing network, which upon deformation is spatially distorted, which accordingly affects the pitch of the surrounding low molar-mass liquid crystal host. Here, we utilize fluorescent confocal polarized microscopy to directly assess the electro-optic response of PSCLCs. By utilizing dual fluorescent probes, sequential imaging experiments confirm that the periodicity of the polymer stabilizing network matches that of the low molar-mass liquid crystal host. Further, we isolate distinct ion-polymer interactions that manifest in certain photopolymerization conditions.

Radka, Brian P.↗

Desorption and Co–Dissolution of Uranium–Bearing Solids During Alkalinity–Enhanced Flushing of Contaminated Sediments

Elevated uranium concentrations in groundwater remain a persistent challenge at contaminated sites. Several sites rely on natural flushing of uranium as a remediation strategy. Uncertainties in conceptual models can cause remediation strategies to underestimate timeframes required to reach remediation goals. In this study, laboratory experiments were conducted to investigate uranium flushing of sediments from a site with persistent groundwater contamination. Six columns were used to simulate alkalinity-enhanced flushing of uranium from sediments, by switching influent alkalinity after ~12 pore volumes. About 20% to 31% of sediment uranium was consistently flushed from the sediments. K d values varied greatly (5.3 to 117 L/kg) but were consistently lower (20% to 50%) during influents with elevated alkalinity. The mass of uranium recovered from the columns also was consistently higher (5% to 80%) during alkalinity-enhanced flushing periods. However, column experiments with sequentially increasing alkalinity showed diminishing returns in uranium elution at higher carbonate concentrations. The loss of flushing efficiency is attributed to significant calcite precipitation at higher alkalinities. Furthermore, the results show that alkalinity-enhanced flushing of uranium could be employed as a viable remediation scheme if calcite precipitation could be minimized in a field application.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Substrate Utilization and Competitive Interactions Among Soil Bacteria Vary With Life-History Strategies

Microorganisms have evolved various life-history strategies to survive fluctuating resource conditions in soils. However, it remains elusive how the life-history strategies of microorganisms influence their processing of organic carbon, which may affect microbial interactions and carbon cycling in soils. Here, we characterized the genomic traits, exometabolite profiles, and interactions of soil bacteria representing copiotrophic and oligotrophic strategists. Isolates were selected based on differences in ribosomal RNA operon ( rrn ) copy number, as a proxy for life-history strategies, with pairs of “high” and “low” rrn copy number isolates represented within the Micrococcales, Corynebacteriales, and Bacillales. We found that high rrn isolates consumed a greater diversity and amount of substrates than low rrn isolates in a defined growth medium containing common soil metabolites. We estimated overlap in substrate utilization profiles to predict the potential for resource competition and found that high rrn isolates tended to have a greater potential for competitive interactions. The predicted interactions positively correlated with the measured interactions that were dominated by negative interactions as determined through sequential growth experiments. This suggests that resource competition was a major force governing interactions among isolates, while cross-feeding of metabolic secretion likely contributed to the relatively rare positive interactions observed. By connecting bacterial life-history strategies, genomic features, and metabolism, our study advances the understanding of the links between bacterial community composition and the transformation of carbon in soils.

59 BASIC BIOLOGICAL SCIENCES↗

Measurement of Sequential ϒ Suppression in Au + Au Collisions at $\sqrt{s_{NN}}$ = 200 GeV with the STAR Experiment

We report on measurements of sequential ϒ suppression in Au+Au collisions at $\sqrt{s_{NN}}$ = 200 GeV with the STAR detector at the Relativistic Heavy Ion Collider (RHIC) through both the dielectron and dimuon decay channels. In the 0%–60% centrality class, the nuclear modification factors (𝑅 𝐴⁢𝐴 ), which quantify the level of yield suppression in heavy-ion collisions compared to 𝑝 + 𝑝 collisions, for ϒ⁡(1⁢𝑆) and ϒ⁡(2⁢𝑆) are 0.40 ± 0.03⁢(stat) ± 0.03⁢(sys) ± 0.09⁢(norm) and 0.26 ± 0.08⁢(stat) ± 0.02⁢(sys) ± 0.06⁢(norm), respectively, while the upper limit of the ϒ⁡(3⁢𝑆) 𝑅 𝐴⁢𝐴 is 0.17 at a 95% confidence level. This provides experimental evidence that the ϒ⁡(3⁢𝑆) is significantly more suppressed than the ϒ⁡(1⁢𝑆) at RHIC. The level of suppression for ϒ⁡(1⁢𝑆) is comparable to that observed at the much higher collision energy at the Large Hadron Collider. Furthermore, these results point to the creation of a medium at RHIC whose temperature is sufficiently high to strongly suppress excited ϒ states.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Modeling of thermal pressurization in tight claystone using sequential THM coupling: Benchmarking and validation against in-situ heating experiments in COx claystone

We apply thermoporoelasticity and a sequentially coupling technique for modeling thermally-driven coupled Thermo-Hydro-Mechanical (THM) processes in tight claystone. A THM benchmark case with a corresponding analytic solution for thermoporoelasticity under a constant heat loading verifies the model. Thereafter, two in situ heating experiments are simulated for model validation: a smaller-scale heating experiment (TED experiment) and a larger-scale experiment (ALC experiment) in Callovo-Oxfordian (COx) claystone at the Meuse/Haute-Marne underground research laboratory in France. The model exhibits good performance to match the observed temperature and pore pressure evolution for the smaller-scale TED experiment. For the larger-scale ALC experiment, general trends of thermal-pressurization are captured in the modeling, but pressure is underestimated at some monitoring points during cool-down. This indicates that the THM response in the field may be affected by the variability of rock's properties or irreversible or time-dependent mechanical processes that are not included in the current thermoporoelastic model. The main contributions of this work are as follows: (1) we verify and validate the numerical simulator, TOUGH-FLAC, to be a valuable coupled THM modeling tool; (2) prove that the laboratory determined material parameters can be used as reference values for upscaling experiments. However, to better identify and quantify THM processes with modeling of in situ tests, more emphasize should be dedicated to obtaining high-quality mechanical deformation data.

58 GEOSCIENCES↗

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗

Sequential Selection for Minimizing the Variance with Application to Crystallization Experiments

For many crystal-based products (e.g., pharmaceuticals, energy storage), the size uniformity is not only a key quality attribute, but sometimes also an indicator of other attributes such as solid purity. This article proposes a sequential selection approach to find a proper experimental setting that leads to high uniformity, or equivalently, small variance for crystal sizes, from the advanced slug flow reaction crystallization process of a model crystal, called manganese oxalate hydrate. The proposed sequential selection approach contains a Bayesian adaptive method to incorporate new uniformity measurements in each step and two design acquisition functions to improve the selection of the most promising experimental setting in terms of minimizing the variance. We study the performance of the proposed approach through multiple synthetic numerical studies, as well as a case study based on data from slug flow crystallization experiments. Throughout these studies, the proposed approach shows competitive performance in identifying the best experimental setting.

Expected improvement↗

Spatially structured bacterial interactions alter algal carbon flow to bacteria

Phytoplankton account for nearly half of global photosynthetic carbon fixation, and the fate of that carbon is regulated in large part by microbial food web processing. We currently lack a mechanistic understanding of how interactions among heterotrophic bacteria impact the fate of photosynthetically fixed carbon. Here, we used a set of bacterial isolates capable of growing on exudates from the diatom Phaeodactylum tricornutum to investigate how bacteria-bacteria interactions affect the balance between exudate remineralization and incorporation into biomass. With exometabolomics and genome-scale metabolic modeling, we estimated the degree of resource competition between bacterial pairs. In a sequential spent media experiment, we found that pairwise interactions were more beneficial than predicted based on resource competition alone, and 30% exhibited facilitative interactions. To link this to carbon fate, we used single-cell isotope tracing in a custom cultivation system to compare the impact of different "primary" bacterial strains in close proximity to live P. tricornutum on a distal "secondary" strain. We found that a primary strain with a high degree of competition decreased secondary strain carbon drawdown by 51% at the single-cell level, providing a quantitative metric for the "cost" of competition on algal carbon fate. Additionally, a primary strain classified as facilitative based on sequential interactions increased total algal-derived carbon assimilation by 7.6 times, integrated over all members, compared to the competitive primary strain. Our findings suggest that the degree of interaction between bacteria along a spectrum from competitive to facilitative is directly linked to algal carbon drawdown.

genome-scale metabolic model↗

Using the Carbon Capture Simulation Initiative (CCSI) Tool to Design the Experiments in the Parametric Campaign of a Novel Compact Absorber for Carbon Capture

Gas absorption towers with structured packing and solvent have been used for Carbon Dioxide (CO 2 ) Capture for about many decades. To overcome process limitations and practical disadvantages for CO 2 capture from the stationary emitter (e.g. NG and coal power plant), many new designs have been proposed and explored at the various scales in the last decade with aim of either low energy penalty or low capital cost. To reduce the size of the absorption tower and hence the total cost of CO 2 capture, the University of Kentucky Center for Applied Energy Research Center (UK CAER) has designed and built a novel CO 2 capture absorption tower or Compact Absorber, integrated into an existing large-bench scale CO 2 capture unit. The Compact Absorber has three sections. The top of the column is a fogging section where the solvent is sprayed through a nozzle producing droplets flowing downward in a co-current fashion with the flue gas. The center of the column is a frothing section where the solvent and flue gas flow through regenerative frothing screens designed by Industrial Climate Solutions, Inc. The bottom of the column is a typical structured packing section were the flue gas and solvent flow in a counter-current fashion. The parametric campaign will be conducted in order to optimize the operating parameters for CO 2 capture including liquid/gas ratio, lean loading, and temperature, liquid residence time. A simulated flue gas with 14% CO 2 will be used along with a UK CAER developed proprietary solvent. The 100-hour parametric campaign is designed using a statistical approach of the Sequential Design of Experiments (sDOE). sDOE is one of the CCSI tools that provides an adaptive statistical approach for designing future experiments based on the results of previous experiments. Application of a typical DOE provides the user with the minimum number of experiments required to get the same data, but sDOE allows the user to make an informed choice of experiments based on the results of previous experiments. The complete absorption column has been constructed and has been partially commissioned. Initial data has been collected by operating using the fogging section and the frothing section. The fogging section produces solvent droplets of about 100 μm sauter mean diameter and as small as 25 μm using a hydraulic nozzle by BETE. The frothing section produces bubbles of about 5mm with high mixing of solvent promoting the higher mass transfer from gas to liquid. The absorber reaches the capture efficiency of about 50% with only two sections in operation. Based on the current results, it can be deduced that increasing the solvent feed temperature and including the packed section for absorption the capture efficiency will increase further. Initial data will be collected using all three sections of the absorber and will be used for sDOE. Non-Uniform Space Filling model of sDOE will be used to prioritize the input conditions resulting into maximum capture efficiency. sDOE is performed using the platform called Framework Optimization, Quantification of Uncertainty, and Surrogates (FOQUS). The method and results demonstrating the progress of the parametric campaign from the initial set of experiments to the final stage of obtaining optimized parameters using sDOE tool will be presented in detail.

20 FOSSIL-FUELED POWER PLANTS↗

CCSI Toolset 3.17 Release

CCSI Toolset 3.17 Release Highlights A workaround was developed to allow complex Aspen Custom Modeler (ACM) models to be used in FOQUS. This workaround uses Visual Basic for Applications to connect the ACM models to FOQUS. The ability for User plugins to be uploaded to FOQUS Cloud was added. The documentation was updated to include Optional Software Install and Tutorial Notes to clarify the usage of Turbine and SimSinter in installation instructions and adds a link to the relevant tutorial page. The Sequential Design of Experiments documentation was updated with current screenshots. The copyright was updated to include 2023.

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CCSI Toolset 3.19 Release

CCSI Toolset 3.19 Release Highlights A gradient generation tool was developed to support GENN models in FOQUS. Certain machine learning tools train gradient-enhanced neural network (GENN) models which can be more accurate for complex datasets given a priori knowledge of model derivatives. However, the derivatives must be known beforehand and are not often available for process data. This tool automatically predicts the gradients for a training dataset in a form usable by common GENN trainers, such as Surrogate Modeling Toolbox. Support was added for Surrogate Modeling Toolbox GENN models in FOQUS, including updates to the run methods, node properties, test framework, documentation and optional dependencies list. Users can train/save Surrogate Modeling Toolbox gradient-enhanced neural network (GENN) models with custom objects and produce .pkl files compatible with the Machine Learning/Artificial Intelligence Plugin in FOQUS. A simpler implementation of the ordering algorithm in the Sequential Design of Experiments (SDOE) module was included. The SDOE examples documentation was updated. The Optimality-Based Design of Experiments was updated to improve the error handling when the results are None.

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CCSI Toolset 3.20 Release

CCSI Toolset 3.20 Release Highlights Minimum Viable Product surrogate plugin was added for creating Machine Learning/Artificial Intelligence models. Corresponding documentation was added for the plugin. Sequential Design of Experiments plots were updated to eliminate an issue with the window stack ordering upon closure of the plots. Support for Python 3.7 was removed. Documentation was improved by adding new mandatory section to the ReadTheDocs configuration and adding installation instructions back for NLOpt. TurbineLite was updated to 3.0.0, which is compatible with SimSinter 3.0.0. The developer environment was updated and 32-bit support was removed. SimSinter was updated to 3.0.0. This version removed gPROMS support and included security updates.

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CCSI Toolset 3.21 Release

CCSI Toolset 3.21 Release Highlights Parallelization support was added for Sequential Design of Experiments (SDOE) computations using Dask (preliminary). Input type dependent ordering capability was added to the SDOE module. With this implementation the user can specify the level of difficulty to change an input (Easy or Hard) and FOQUS will generate the appropriate ordered design depending on the input difficulty combination. Python version support was extended. FOQUS is now compatible with Python 3.8 through 3.12. Platforms used for automated testing were expanded to include macOS ARM (Apple Silicon). Updates to the FOQUS documentation to include information on how to set paths for SimSinter and TurbineLite. Turbine configuration section was added to Debugging Documentation.

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CCSI Toolset 3.22 Release

CCSI Toolset 3.22 Release Highlights The Sequential Design of Experiments user interface was updated to resolve an issue where the results would fail to plot in some cases (e.g., Non-Uniform Space Filling designs). The Machine Learning/Artificial Intelligence module was updated to support Keras 3 and to reflect changes made to dependencies’ syntax. A check was added to ensure PSUADE is installed and available at FOQUS startup. If PSUADE is not installed, a link to the FOQUS documentation is displayed and FOQUS is closed. The copyright year was updated to include 2024 in places where it had not previously been updated. Typographical errors were corrected to improve clarity in variable names and documentation. The FOQUS documentation was updated to reflect the fact that ALAMO can have two executables and indicates the correct executable to add to the Settings path. SimSinter was updated to version 3.1.0. This version removed gPROMS support and included security updates.

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