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At least 505 records · Page 28

Predicting Char Yield of High-Temperature Resins

A simulation protocol is developed to predict the char yield of organic resins during high-temperature processing. Such in silico methods can help screen promising new formulations for advanced materials, but previously no chemistry-sensitive technique existed to predict the important experimental value of char yield. The method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to processing temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small byproduct molecules to mimic outgassing, and the application of high pressure to eliminate porosity and encourage graphitization. More than ten different resin chemistries are investigated, including arylacetylenes, cyanate esters, phthalonitriles, and polyimides, representing a diverse group of precursors with respect to initial cyclic content, heteroatoms and reactive groups. The protocol correctly predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. The properties of the resins during processing are compared, including outgassing products, morphology of the final chemical configurations, cyclic content and mechanical properties.

polymer simulations, molecular dynamics↗

Predicting Char Yield of High-Temperature Resins

A simulation technique has been developed for predicting the char yield of organic resins during high-temperature processing. In silico methods can aid in the screening of new advanced materials for a number of important properties, but no chemistry-sensitive protocol currently exists for predicting the important experimental value of char yield. The proposed method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to pyrolysis temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small by-product molecules to mimic outgassing, and the application of high pressure to encourage the formation of a dense, glassy network. Six different resin chemistries were investigated: an ethynyl, a phenylethynyl, a cyanate ester, a phthalonitrile, acrylonitrile, and adamantane. These candidates represent a diverse group of precursors with respect to initial cyclic content, presence of heteroatoms, and types of reactive groups. The protocol developed accurately predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. Several simulated properties of the carbonized structures are compared with experimental results, including outgassing products, morphology of the final chemical configurations, cyclic content, and mechanical properties.

polymer simulations, molecular dynamics↗

Predicting Char Yield of High-Temperature Resins

A simulation protocol is developed to predict the char yield of organic resins during high-temperature processing. Simulation protocol in silico methods can help screen promising new formulations for advanced materials, but previously no chemistry-sensitive technique existed to predict the important experimental value of char yield. The method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to processing temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small byproduct molecules to mimic outgassing, and the application of high pressure to eliminate porosity and encourage graphitization. More than ten different resin chemistries are investigated, including arylacetylenes, cyanate esters, phthalonitriles, and polyimides, representing a diverse group of precursors with respect to initial cyclic content, heteroatoms and reactive groups. The protocol correctly predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. The properties of the resins during processing are compared, including outgassing products, morphology of the final chemical configurations, cyclic content and mechanical properties.

polymer simulations, molecular dynamics↗

Lidar-Based Safe Site Relative Navigation

There has been a renewed focus in exploration of the lunar surface and maximizing scientific potential of such missions is made possible in part by minimizing the time required to set up operations; that is, reducing transit time on the surface by increasing the landing precision with respect to the intended target. Established SPLICE project precision landing requirements necessitate a navigation filter architecture and underlying models developed specifically with these needs in mind. To date, test flights to characterize SPLICE GNC system performance have not provided a means to divert from the a priori selected landing site due to hazardous conditions. With the inclusion of a new sensor, the HDL, coupled with safe landing site selection algorithms, GNC can divert from the originally planned trajectory and navigate relative to the new targeted landing site. This work presents a novel hazard relative measurement model and covariance transformation methodology that enable the navigation system to inform a safe-site relative guidance profile to meet project precision landing goals.

Navigation↗

The SWOT Mission Will Reshape Our Understanding of the Global Terrestrial Water Cycle

Simultaneously integrating Surface Water and Ocean Topography (SWOT) measurements and those from other Earth observing satellites into hydrological modeling systems will transform our understanding of the global terrestrial water cycle. Such an opportunity comes with big challenges that the scientific community is now presented with.

Natural hazards↗

eYGFPuv-Assisted Transgenic Selection in Populus deltoides WV94 and Multiplex Genome Editing in Protoplasts of P. trichocarpa × P. deltoides Clone ‘52-225’

Although CRISPR/Cas-based genome editing has been widely used for plant genetic engineering, its application in the genetic improvement of trees has been limited, partly because of challenges in Agrobacterium-mediated transformation. As an important model for poplar genomics and biotechnology research, eastern cottonwood (Populus deltoides) clone WV94 can be transformed by A. tumefaciens, but several challenges remain unresolved, including the relatively low transformation efficiency and the relatively high rate of false positives from antibiotic-based selection of transgenic events. Moreover, the efficacy of CRISPR-Cas system has not been explored in P. deltoides yet. Here, we first optimized the protocol for Agrobacterium-mediated stable transformation in P. deltoides WV94 and applied a UV-visible reporter called eYGFPuv in transformation. Our results showed that the transgenic events in the early stage of transformation could be easily recognized and counted in a non-invasive manner to narrow down the number of regenerated shoots for further molecular characterization (at the DNA or mRNA level) using PCR. We found that approximately 8.7% of explants regenerated transgenic shoots with green fluorescence within two months. Next, we examined the efficacy of multiplex CRISPR-based genome editing in the protoplasts derived from P. deltoides WV94 and hybrid poplar clone ‘52-225’ (P. trichocarpa × P. deltoides clone ‘52-225’). The two constructs expressing the Trex2-Cas9 system resulted in mutation efficiency ranging from 31% to 57% in hybrid poplar clone 52-225, but no editing events were observed in P. deltoides WV94 transient assay. The eYGFPuv-assisted plant transformation and genome editing approach demonstrated in this study has great potential for accelerating the genome editing-based breeding process in poplar and other non-model plants species and point to the need for additional CRISPR work in P. deltoides.

59 BASIC BIOLOGICAL SCIENCES↗

Enhancing Regional Seismic Velocity Models With Higher‐Resolution Local Results Using Sparse Dictionary Learning

Abstract We use sparse dictionary learning to develop transformations between seismic velocity models of different resolution and spatial extent. Starting with data in the common region of both models, the method can enhance a regional lower‐resolution model to match the style and resolution of local higher‐resolution results while preserving its regional coverage. The method is demonstrated by applying it to two‐dimensional V S and three‐dimensional V P and V S regional and local velocity models in southern California. The enhanced reconstructed regional results exhibit clear visual improvements, especially in the reconstructed V P / V S ratios, and better correlations with geological features. Moreover, the reconstructed regional V P , V S models outperform the original ones in comparison of simulated earthquake waveforms to observations. The improved fitting to observed waveforms extends beyond the domain of the overlapping region. The developed dictionary learning approach provides physically interpretable results and offers a powerful tool for additional applications of data enhancement in earth sciences.

Geochemistry & Geophysics↗

NASA Earth: Synthetic Spectranomics - Deep Learning of Surface 3-D Geometry, Chemistry, and Hyperspectra to Inform Next-generation Land Models

Machine and deep learning (ML/DL) have transformed our approach to Earth observation and system modeling (EOSM), unifying both in view of ML/DL models as a form of data assimilation (DA). Trained on diverse Earth observation records, detailed physical models, or hybrids of both in physics-informed machine learning, ML/DL may improve upon existing Earth system model (ESM) formulations while creating entirely new classes of models. One important application of deep learning is observation synthesis, allowing ESM developers to prepare for the increased spatial, temporal, and spectral/polar resolution of proposed future observing systems. This may involve the retrospective application of learning algorithms to existing observational records, with or without physical radiative transfer models, to co-inform mission planning and ESM development while providing a degree of data continuity for new missions.

Adam Erickson↗

Status of Research Activities on LVDTs: Modeling and Simulation Development and Performance Characterization of Commercial LVDTs

FY-22 research focused on two major areas. The first area was modeling and simulation with linked testing that will advance the Linear Variable Differential Transformers (LVDT) technology for use by stakeholders requiring LVDTs in upcoming irradiation tests. The second area focused on testing LVDTs purchased from U.S. suppliers that were investigated in FY-21. These cross-cutting development activities will ensure stakeholders have the current state-of-the-art LVDT-based technologies for deployment in future irradiation tests. Two stand-alone reports are included in the appendixes. The purpose of this report is to provide a convenient body of work to access the reports and to evaluate the data and conclusions provided. Appendix A, “Testing of the RDP Translation Transducer,” contains a complete evaluation of an RDP Electrosense linear transducer that has the capability of replicating the form, fit, and function of LVDTs currently being used at Idaho National Laboratory (INL). Appendix B is an extract from the report, “Advanced Sensors and Instrumentation Program at Boise State University (BSU), August 2022, Linear Variable Differential Transformers.” This report contains modeling and testing results conducted at BSU and INL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Linear approximations of nonlinear systems

The development of a method for designing an automatic flight controller for short and vertical take off aircraft is discussed. This technique involves transformations of nonlinear systems to controllable linear systems and takes into account the nonlinearities of the aircraft. In general, the transformations cannot always be given in closed form. Using partial differential equations, an approximate linear system called the modified tangent model was introduced. A linear transformation of this tangent model to Brunovsky canonical form can be constructed, and from this the linear part (about a state space point x sub 0) of an exact transformation for the nonlinear system can be found. It is shown that a canonical expansion in Lie brackets about the point x sub 0 yields the same modified tangent model.

Hunt, L. R.↗

Numerical and analytical study of fluid dynamic forces in seals and bearings

A numerical model based on a transformed, conservative form of the three dimensional Navier-Stokes equation and an analytical model based on lumped fluid parameters are presented and compared with studies of modeled rotor bearing seal systems. The rotor destabilizing factors are related to the rotative character of the flow field. It is shown that these destabilizing factors can be reduced through a decrease in the fluid average circumferential velocity. However, the rotative character of the flow field is a complex three dimensional system with bifurcated secondary flow patterns that significantly alter the fluid circumferential velocity. By transforming the Navier-Stokes equations to those for a rotating observer and using the numerical code PHOENICS-84 with a nonorthogonal body fitted grid, several numerical experiments were carried out to demonstrate the character of this complex flow field. In general, fluid injection and/or preswirl of the flow field opposing the shaft rotation significantly intensified these secondary recirculation zones and thus reduced the average circumferential velocity; injection or preswirl in the direction of rotation significantly weakened these zones.

Tam, L. T.↗

A numerical examination of the effect of sulfide dissolution on silicate weathering

Silicate weathering regulates climate on geological time scales as a net, climate-sensitive sink of atmospheric CO 2 . On the other hand, sulfuric acid produced through sulfide dissolution affects silicate weathering, diminishing its effectiveness as a climate regulator based on evidence from river chemistry. This study takes a theoretical approach to quantitatively examine the effect of sulfide dissolution, coupling a one-dimensional model of pyrite weathering to that of albite transformation to kaolinite. The coupled model reveals that when the reaction front of sulfide is deeper than that of silicates reacting with CO 2 , the silicate-weathering feedback on climate is not directly affected by sulfide dissolution, but only indirectly through oceanic processes such as reverse weathering and carbonate deposition. In turn, when sulfide dissolution occurs within zones of CO 2 -silicate reactions close to the surface, the feedback between climate and silicate weathering can be significantly weakened because sulfuric acid competes effectively with carbonic acid in mineral dissolution. As the depth of the sulfide reaction front can be changed by variations in water table depth, the latter feedback weakening could have occurred in concert with climate-change-driven water table fluctuations, amplifying atmospheric CO 2 variations during the Phanerozoic.

58 GEOSCIENCES↗

Physics-guided logistic classification for tool life modeling and process parameter optimization in machining

This paper describes a physics-guided logistic classification method for tool life modeling and process parameter optimization in machining. Tool life is modeled using a classification method since the exact tool life cannot be measured in a typical production environment where tool wear can only be directly measured when the tool is replaced. Here, in this study, laboratory tool wear experiments are used to simulate tool wear data normally collected during part production. Two states are defined: tool not worn (class 0) and tool worn (class 1). The non-linear reduction in tool life with cutting speed is modeled by applying a logarithmic transformation to the inputs for the logistic classification model. A method for interpretability of the logistic model coefficients is provided by comparison with the empirical Taylor tool life model. The method is validated using tool wear experiments for milling. Results show that the physics-guided logistic classification method can predict tool life using limited datasets. A method for pre-process optimization of machining parameters using a probabilistic machining cost model is presented. The proposed method offers a robust and practical approach to tool life modeling and process parameter optimization in a production environment.

Machine learning↗

Nonlinear transformat

A technique for designing automatic flight controllers for aircraft which utilizes the transformation theory of nonlinear systems to linear systems is presently being developed at NASA Ames Research Center. A method is considered in which a given nonlinear is transformed to a controllable linear system in Brunovsky canonical form. A linear approximation is introduced to the nonlinear system called the modified tangent model. This model is easily computed. Constructing the transformation for this model enables the designer to find an approximate transformation for the nonlinear system.

Ford, H.↗

Numerical and analytical study of fluid dynamic forces in seals and bearings

Study results for rotor/bearing/seal system models are compared with both a numerical model based on a transformed, conservative version of the three-dimensional Navier-Stokes equation, and an analytical model based on 'lumped' fluid parameters. Rotor-destabilizing factors are related to flow field rotation; it is shown that these factors can be reduced through a decrease in the fluid average circumferential velocity. A transformation of the Navier-Stokes equations to those for a rotating observer and a numerical code with a nonorthogonal body-fitted grid are used to carry out numerical experiments demonstrating the character of the complex flow field.

Tam, L. T.↗

Analysis of multi-electron, multi-step homogeneous catalysis by rotating disc electrode voltammetry: theory, application, and obstacles

Rotating disc electrode (RDE) voltammetry has been widely adopted for the study of heterogenized molecular electrocatalysts for multi-step fuel-forming reactions but this tool has never been comprehensively applied to their homogeneous analogues. Here, the utility and limitations of RDE techniques for mechanistic and kinetic analysis of homogeneous molecular catalysts that mediate multi-electron, multi-substrate redox transformations are explored. Using the ECEC' reaction mechanism as a case study, two theoretical models are derived based on the Nernst diffusion layer model and the Hale transformation. Current–potential curves generated by these computational strategies are compared under a variety of limiting conditions to identify conditions under which the more minimalist Nernst Diffusion Layer approach can be applied. Based on this theoretical treatment, strategies for extracting kinetic information from the plateau current and the foot of the catalytic wave are derived. RDEV is applied to a cobaloxime hydrogen evolution reaction (HER) catalyst under non-aqueous conditions in order to experimentally validate this theoretical framework and explore the feasibility of RDE as a tool for studying homogeneous catalysts. Importantly, analysis of the foot-of-the-wave via this theoretical framework provides rate constants for elementary reaction steps that agree with those extracted from stationary voltammetric methods, supporting the application of RDE to study homogeneous fuel-forming catalysts. Lastly, obstacles encountered during the kinetic analysis of cobaloxime, along with the voltammetric signatures used to diagnose this reactivity, are discussed with the goal of guiding groups working to improve RDE set-ups and help researchers avoid misinterpretation of RDE data.

08 HYDROGEN↗

Computer simulation and experimental validation of isoelectric focusing in ampholine-free systems

An abbreviated version of a mathematical model of the steady state in isoelectric focusing is presented. Details of the mathematical transformations leading to a model suitable for computer implementation and numerical solution are given in the Appendix. The model describes the structure of concentration, pH, conductivity and potential gradients arising from the focusing of electrochemically defined ampholytes. Some of the results of computer simulations of two and three component systems are of particular interest to the experimentalist and are presented together with experimental validation of this model.

Bier, M.↗

Minimizing the total harmonic distortion for a 3 kW, 20 kHz ac to dc converter using SPICE

This paper describes the SPICE model of a transformer-rectified-filter (TRF) circuit and the Micro-CAP (Microcomputer Circuit Analysis Program) model and their application. The models were used to develop an actual circuit with reduced input current THD. The SPICE analysis consistently predicted the THD improvements in actual circuits as various designs were attempted. In an effort to predict and verify load regulation, the incorporation of saturable inductor models significantly improved the fidelity of the TRF circuit output voltage.

Lollar, Louis F.↗