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At least 793 records · Page 44

Renewable Aromatics from Syngas

This study focuses on developing a catalytic process for the aromatization of mixed olefin (comprised of C 2 -C 6 ) over various metal doped zeolites towards the formation of large aromatics (preferably C 8 -C 16 ) compliance to the sustainable aviation fuel (SAF). Experiments were carried out using model olefin feedstocks containing either ethylene (C 2 ) or mixture of C 2 and C 3+ olefins. Both the catalyst composition and process parameters were evaluated in detail to identify their impact on the formation large aromatics. We specifically focus on the aromatization of ethylene as the model reaction and evaluated the impact of C 2+ olefins and paraffins that may present in the real feedstock. In all the reaction condition, aromatization of ethylene was used as the baseline to evaluate the effect of larger olefins or paraffins. Our results show that at this reaction condition paraffins remained either inert or show positive impact on the formation of large aromatics. While C 2 and C 3 olefins are highly reactive towards aromatization during reaction condition, large olefins are less reactive and thus, strategy was developed to oligomerize these large olefins (C 4+ ) alongside the aromatization of smaller olefins (C 2 /C 3 ).

10 SYNTHETIC FUELS↗

A Comparative Multi-System Approach to Characterizing Bioactivity of Commonly Occurring Chemicals

A 2019 retrospective study analyzed wristband personal samplers from fourteen different communities across three different continents for over 1530 organic chemicals. Investigators identified fourteen chemicals (G14) detected in over 50% of personal samplers. The G14 represent a group of chemicals that individuals are commonly exposed to, and are mainly associated with consumer products including plasticizers, fragrances, flame retardants, and pesticides. The high frequency of exposure to these chemicals raises questions of their potential adverse human health effects. Additionally, the possibility of exposure to mixtures of these chemicals is likely due to their co-occurrence; thus, the potential for mixtures to induce differential bioactivity warrants further investigation. This study describes a novel approach to broadly evaluate the hazards of personal chemical exposures by coupling data from personal sampling devices with high-throughput bioactivity screenings using in vitro and non-mammalian in vivo models. To account for species and sensitivity differences, screening was conducted using primary normal human bronchial epithelial (NHBE) cells and early life-stage zebrafish. Mixtures of the G14 and most potent G14 chemicals were created to assess potential mixture effects. Chemical bioactivity was dependent on the model system, with five and eleven chemicals deemed bioactive in NHBE and zebrafish, respectively, supporting the use of a multi-system approach for bioactivity testing and highlighting sensitivity differences between the models. In both NHBE and zebrafish, mixture effects were observed when screening mixtures of the most potent chemicals. Observations of BMC-based mixtures in NHBE (NHBE BMC Mix) and zebrafish (ZF BMC Mix) suggested antagonistic effects. In this study, consumer product-related chemicals were prioritized for bioactivity screening using personal exposure data. High-throughput high-content screening was utilized to assess the chemical bioactivity and mixture effects of the most potent chemicals.

60 APPLIED LIFE SCIENCES↗

Experiments and modeling to evaluate global reaction kinetics of three-way catalyst light off for net-zero carbon fuels and selected fuel blends

Internal combustion engine exhaust composition can have a significant impact on the light-off characteristics of CO, NO, and organics in the three-way-catalyst during cold-start. The U.S. Department of Energy’s Co-Optimization of Fuels and Engines initiative was aimed at developing new high-performance fuels, which raises the question of how current three-way-catalysts will perform if the exhaust composition is significantly changed. This work is aimed at quantifying the performance of the catalyst under a variety of different fuel components and mixtures. To this end, a reduced-order model is developed wherein the set of organics examined are placed into molecular groups based on their reactivities and to model each organic within that group with a common kinetic expression. In conclusion, this strategy allows for a first approximation to the light-off characteristics of all organics that fall within that group and to make predictions for fuel blends.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New approach in direct-simulation of gas mixtures

Results are reported for an investigation of a new direct-simulation Monte Carlo method by which energy transfer and chemical reactions are calculated. The new method, which reduces to the variable cross-section hard sphere model as a special case, allows different viscosity-temperature exponents for each species in a gas mixture when combined with a modified Larsen-Borgnakke phenomenological model. This removes the most serious limitation of the usefulness of the model for engineering simulations. The necessary kinetic theory for the application of the new method to mixtures of monatomic or polyatomic gases is presented, including gas mixtures involving chemical reactions. Calculations are made for the relaxation of a diatomic gas mixture, a plane shock wave in a gas mixture, and a chemically reacting gas flow along the stagnation streamline in front of a hypersonic vehicle. Calculated results show that the introduction of different molecular interactions for each species in a gas mixture produces significant differences in comparison with a common molecular interaction for all species in the mixture. This effect should not be neglected for accurate DSMC simulations in an engineering context.

Chung, Chan-Hong↗

An Improved Model For Determining Salinity Recharge Time for Deep Borehole Disposal - 20405

In a previous publication (K. P. Travis, D. Burley and F. G. F. Gibb, WM2017 Conference, Phoenix Arizona paper no. 17480) we introduced a numerical model to estimate the time it would take for a pressure perturbation to subside following its creation from the construction of a deep geological borehole in water-saturated rock. The model was based on the notion of a point source of momentum - a solution of the time-dependent pressure-diffusion equation. Using the model, we estimated that it would take on the order of 10 k years for physical equilibrium to become re-established following the sinking of a 5 km borehole in granite. The significance of such a model is that it places an upper bound on the lifetime required of a borehole sealing system - a necessary input to a borehole post-closure safety case assessment. No engineered sealing system has ever been devised which is capable of retaining its sealing properties for 10 half-lives of long-lived radioisotopes in spent fuel or high-level waste. One of the key advantages of disposing of nuclear waste via Deep Borehole Disposal (DBD) is the natural sealing provided by density stratified groundwater. Upon sinking of a borehole, and subsequent filling with fresh water, brine or drilling mud, this natural barrier may be temporarily damaged. Over time, fresh brine from the far-field will flow towards or away from the hole (driven by a pressure gradient) and will eventually re-establish the original salinity gradient. It follows that the engineered seals need last only as long as the time required for this salinity gradient to reset itself. One of the limitations of our previous model was the use of a static boundary condition on the borehole wall. The model used a boundary pressure which varied quadratically with depth (arising from differences between the pressure of a column of fresh water in the borehole and that of a column of brine in the host rock). However as brine replaces fresh water in the borehole (driven by a pressure gradient), the boundary function must change with time. We now introduce an improved model which takes this time dependent boundary condition into account. The model also takes into account the time taken for a mixture of brine and fresh water to re-establish chemical equilibrium through the process of diffusion. The paper contains the mathematical details of our new iterative model as well as results showing the time taken to reach steady state, and concentration profiles for the components of the brine-filled borehole as a function of time together with a discussion on the implications of the results for developing a post-closure safety assessment for DBD. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

On the effect of mixing-driven vaporization in a homogeneous relaxation modeling framework

The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. Herein, to assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Evaluation of the SSRCS engine with hydrazine as a fuel, phase 2

Test firing of the Space Shuttle Reaction Control Thruster (SSRCT) was conducted to determine the characteristic velocity and chamber throat temperatures when the fuel is changed from monomethylhydrazine (MMH) to hydrazine. Thruster performance with hydrazine was essentially as predicted. Characteristic velocity at a mixture ratio of 1.4 (equal volumetric flow) for hydrazine was 5180 feet/second compared with 5110 feet/second at a mixture of 1.6 for MMH. Specific impulse with 22:1 nozzle is calculated to be 280 lbf-sec/lbm. Thermal performance, as measured by chamber throat temperature, was dramatically different (colder) than predicted. Throat temperatures of 2330 F were predicted from a cooling model which assumed a reactive liquid cooling film. Throat temperatures of 800 - 1000 F were measured. An attempt to reconcile the differences between film cooling predictions and the measurements, indicated that an evaporation (nonreactive fluid) model rather than a decomposition (reactive fluid) model best fits the test data at 0/F = 1.4. At higher mixture ratios, a transition to temperatures typical of the reactive fluid model were observed.

Minton, S. J.↗

A detailed chemical kinetic modeling and experimental investigation of the low- and high-temperature chemistry of n-butylcyclohexane

Chemical kinetic models of gasoline, jet, and diesel fuels and their mixtures with bioderived fuels are needed to assess fuel property effects on efficiency, emissions, and other performance metrics in internal combustion and gas turbine engines. As these real fuels have too many fuel components to be included in a chemical kinetic model, surrogate fuels containing fewer components are used to represent them. These surrogate fuels mimic the chemical classes or molecular structures contained in the real fuel. One of the important chemical classes in gasoline, jet, and diesel fuels comprises cyclohexanes. Cyclohexanes comprise about 30% or more by weight in diesel fuel. Also, Mueller et al proposed n-butylcyclohexane (nBCH) as a component in a nine-component surrogate palette to represent the ignition properties, distillation curve, density, and molecular structures of a diesel certification fuel. Herein, experimental measurements of the ignition delay times (IDTs) of nBCH in a shock tube and in a rapid compression machine are reported over a wide range of temperature, pressure, and equivalence ratio important for enabling the validation of a chemical kinetic model for nBCH for combustion in diesel engines. The range of conditions are temperatures of 630–1420 K, pressures of 10, 30, and 50 bar, and equivalence ratios of 0.3, 0.5, 1.0, and 2.0 in ‘air’. A detailed chemical model is developed for nBCH to simulate its ignition at both low and high-temperature conditions and at relevant elevated pressures. The experimentally measured IDTs are used to improve and validate the chemical kinetic model.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A generalized hard-sphere model for Monte Carlo simulation

A new molecular model, called the generalized hard-sphere, or GHS model, is introduced. This model contains, as a special case, the variable hard-sphere model of Bird (1981) and is capable of reproducing all of the analytic viscosity coefficients available in the literature that are derived for a variety of interaction potentials incorporating attraction and repulsion. In addition, a new procedure for determining interaction potentials in a gas mixture is outlined. Expressions needed for implementing the new model in the direct simulation Monte Carlo methods are derived. This development makes it possible to employ interaction models that have the same level of complexity as used in Navier-Stokes calculations.

Hassan, H. A.↗

Computationally efficient optimization models for preliminary distillation column design and separation energy targeting

We propose versatile shortcut distillation column and separation energy targeting models that are well-suited for superstructure-based process synthesis. The models are based on a novel reformulation of the Underwood equations to address systems where the components that are present in the feed can vary due to zero flow rates of some components. Also, we propose valid constraints, resulting in a significant enhancement of the computational performance of the models. Furthermore, the proposed distillation column model can automatically identify adequate key components and the energy requirement of a desired separation task, while considering a wide range of types of separations including non-sharp/sloppy splits. Also, the proposed separation energy targeting model can be used to estimate an energy requirement target for the separation of a mixture without finding detail network configurations. Due to their versatility and computational efficiency, the proposed models can be readily used for and expand the scope of superstructure-based process synthesis approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Equilibrium gas flow computations. I - Accurate and efficient calculation of equilibrium gas properties

This paper treats the accurate and efficient calculation of thermodynamic properties of arbitrary gas mixtures for equilibrium flow computations. New improvements in the Stupochenko-Jaffe model for the calculation of thermodynamic properties of diatomic molecules are presented. A unified formulation of equilibrium calculations for gas mixtures in terms of irreversible entropy is given. Using a highly accurate thermo-chemical data base, a new, efficient and vectorizable search algorithm is used to construct piecewise interpolation procedures with generate accurate thermodynamic variable and their derivatives required by modern computational algorithms. Results are presented for equilibrium air, and compared with those given by the Srinivasan program.

Liu, Yen↗

Tuning Process for the Modified Magnussen Combustion Model

In the application of CFD to turbulent reacting flows, one of the main limitations to predictive accuracy is the chemistry model. Using a full or skeletal kinetics model may provide good predictive ability, however, at considerable computational cost. Adding the ability to account for the interaction between turbulence and chemistry improves the overall fidelity of a simulation but adds to this cost. An alternative is the use of simple models, such as the Magnussen model, which has negligible computational overhead, but lacks general predictive ability except for cases that can be tuned to the flow being solved. In this paper, a technique will be described that allows the tuning of the Magnussen model for an arbitrary fuel and flow geometry without the need to have experimental data for a particular case. The tuning is based on comparing the results of the Magnussen model and full finite-rate chemistry when applied to perfectly and partially stirred reactor sim- ulations. In addition, a modification to the Magnussen model is proposed that allows the upper kinetic limit for the reaction rate to be set, giving better physical agreement with full kinetic mechanisms. In order to improve the agreement with flame temperatures, the thermal properties of the product species is adjusted to better match the mixture proper- ties of the full mechanism. The combustion model is then applied to the simulation of a representative scramjet flowpath, and the results compared to experimental data and other kinetic models. This procedure allows a simple reacting model to be used in a predictive manner, and affords significant savings in computational costs for CFD simulations.

Norris, A. T.↗

Integrating very-high-resolution UAS data and airborne imaging spectroscopy to map the fractional composition of Arctic plant functional types in Western Alaska

Widespread changes in vegetation cover and composition are driving strong impacts on Arctic ecosystem functioning and global climate feedbacks. An accurate characterization of tundra vegetation composition is required to understand how the Arctic will respond to future climate change. However, quantifying tundra vegetation composition over large areas is challenging as commonly-used satellite observations are too coarse, spatially and spectrally, to differentiate low-lying tundra vegetation types. Recent airborne and spaceborne imaging spectroscopy platforms provide better data to characterize vegetation composition. Yet, our ability to characterize vegetation composition with imaging spectroscopy remains largely unexplored in the Arctic, particularly due to a lack of ground observations needed to train and test classification models. To address this problem, we collected very-high-resolution (VHR, ~5 cm) unoccupied aerial system (UAS) imagery at three low-Arctic tundra sites located on the Seward Peninsula, western Alaska. In this paper, we examine the feasibility of integrating imagery from the UAS and the hyperspectral Airborne Visible/Infrared Imaging Spectrometer, Next Generation (AVIRIS-NG) airborne instrument to map the fractional composition of 12 key Arctic plant functional types (PFTs). To this end, we first mapped the 12 PFTs from our VHR UAS imagery using random forest classification. We then used these UAS-derived PFT maps as ground truth to develop partial least squares regression (PLSR) models to predict the fractional cover (FCover) of each PFT from AVIRIS-NG imagery. Further, we evaluated the performance of our PLSR models using reserved UAS samples, as well as by mapping PFT FCover and dominant PFT for large tundra landscapes. Our results show that 1) Arctic PFTs can be effectively mapped using VHR UAS imagery, with overall accuracy between 86% and 92%, 2) when the UAS mapped PFTs were used to inform PLSR scaling models, the FCover of the 12 PFTs could be effectively estimated from AVIRIS-NG imagery with a mean absolute error (MAE) <0.13, and 3) our PLSR models outperformed traditional, fully constrained least-squares (FCLS) linear mixture analysis and produced high-quality, spatially contiguous PFT FCover and PFT maps that captured vegetation spatial patterns with similar accuracy to those developed from UAS imagery. The developed PLSR models have the potential to be broadly applied for quantifying vegetation composition with AVIRIS-NG images to help monitor tundra vegetation dynamics and improve process-based modeling of tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Modeling the Elastic Modulus of 2D Woven CVI SiC Composites

The use of fiber, interphase, CVI SiC minicomposites as structural elements for 2D-woven SiC fiber reinforced chemically vapor infiltrated (CVI) SiC matrix composites is demonstrated to be a viable approach to model the elastic modulus of these composite systems when tensile loaded in an orthogonal direction. The 0deg (loading direction) and 90deg (perpendicular to loading direction) oriented minicomposites as well as the open porosity and excess SiC associated with CVI SiC composites were all modeled as parallel elements using simple Rule of Mixtures techniques. Excellent agreement for a variety of 2D woven Hi-Nicalon(TradeMark) fiber-reinforced and Sylramic-iBN reinforced CVI SiC matrix composites that differed in numbers of plies, constituent content, thickness, density, and number of woven tows in either direction (i.e, balanced weaves versus unbalanced weaves) was achieved. It was found that elastic modulus was not only dependent on constituent content, but also the degree to which 90deg minicomposites carried load. This depended on the degree of interaction between 90deg and 0deg minicomposites which was quantified to some extent by composite density. The relationships developed here for elastic modulus only necessitated the knowledge of the fractional contents of fiber, interphase and CVI SiC as well as the tow size and shape. It was concluded that such relationships are fairly robust for orthogonally loaded 2D woven CVI SiC composite system and can be implemented by ceramic matrix composite component modelers and designers for modeling the local stiffness in simple or complex parts fabricated with variable constituent contents.

Morscher, Gregory N.↗

Monticello - A glass-rich howardite

Monticello is a new howardite similar to Malvern in that it contains abundant (15 percent) glass fragments, which show a range of compositions from olivine-normative to quartz-normative. Like Kapoeta, it contains pyroxene grains that range up to highly magnesian compositions, Fs16. Because their pyroxenes are more magnesian than those occurring in diogenites, Monticello and Kapoeta are exceptions to the simple two-component mixing model in which howardites are considered to be mechanical mixtures of fragmented eucrites and diogenites. Monticello also contains clasts of what appear to be a cumulate eucrite and a noncumulate eucrite, as well as a radiating pyroxene chondrule from a chondrite. Monticello is a regolith breccia containing more evolved components than are usually considered in eucrite-diogenite genesis models. As such, it supports those models that involve reworking of a complex parent body crust rather than straightforward partial melting of primitive chondritic parent material.

Olsen, Edward J.↗

A large deformation multiphase continuum mechanics model for shock loading of soft porous materials

A large deformation, coupled finite-element (FE) model is developed to simulate the multiphase response of soft porous materials subjected to high strain-rate loading. The approach is based on the theory of porous media (TPM) at large deformations. Simplifications to the one-dimensional regime studied in the numerical simulations follow. An overview of several different time integration schemes is presented for the purpose of solving the nonlinear dynamic coupled balance of momenta (mixture and fluid) and balance of mass of the mixture equations. Numerical examples are presented for (i) verification against closed-form analytical solutions assuming small loads, (ii) demonstrating large deformation effects at high strain-rate, and (iii) showing differences in deformations between a single-phase elastodynamics model with occluded compressible pore fluid and a multiphase poroelastodynamics model at high strain-rate. The multiphase model shows that the relative motion of the pore fluid significantly dampens the deformation response of the solid skeleton as compared to the single-phase model, and makes it possible to extract quantitative values for the stresses of the different constituents, thereby allowing one to form preliminary conclusions about the onset of damage in the solid skeleton. The novelty of the current work is developing a multiphase, large deformation, mixture theory numerical model for high strain-rate loading of soft porous materials. It was discovered that explicit, adaptive time-stepping Runge–Kutta schemes offer high accuracy at relatively low cost when compared to traditional implicit or explicit central difference time-stepping schemes for shock-like loadings. Here, shock viscosity is added to the mixture momentum balance equation to regularize the shock front, and a stabilization term is added to the mixture mass balance equation to stabilize equal order interpolation finite elements for the coupled finite element solution of multiphase materials.

Engineering↗

Shell Tectonics: A Mechanical Model for Strike-slip Displacement on Europa

We introduce a new mechanical model for producing tidally-driven strike-slip displacement along preexisting faults on Europa, which we call shell tectonics. This model differs from previous models of strike-slip on icy satellites by incorporating a Coulomb failure criterion, approximating a viscoelastic rheology, determining the slip direction based on the gradient of the tidal shear stress rather than its sign, and quantitatively determining the net offset over many orbits. This model allows us to predict the direction of net displacement along faults and determine relative accumulation rate of displacement. To test the shell tectonics model, we generate global predictions of slip direction and compare them with the observed global pattern of strike-slip displacement on Europa in which left-lateral faults dominate far north of the equator, right-lateral faults dominate in the far south, and near-equatorial regions display a mixture of both types of faults. The shell tectonics model reproduces this global pattern. Incorporating a small obliquity into calculations of tidal stresses, which are used as inputs to the shell tectonics model, can also explain regional differences in strike-slip fault populations. We also discuss implications for fault azimuths, fault depth, and Europa's tectonic history.

2) Tectonics↗