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Several classes of system performance simulations of V/STOL propulsion systems are presented. A digital simulation approach for a typical system (a propulsion system made up of three engines, shafts and gearbox, and remote lift fan) is given with a description of the general philosophy, solution options and model flexibility.
Dissociative adsorption onto a surface introduces dynamic correlations between neighboring sites not found in non-dissociative absorption. We study surface coverage dynamics where reversible dissociative adsorption of dimers occurs on a finite linear lattice. We derive analytic expressions for the equilibrium surface coverage as a function of the number of reactive sites, N, and the ratio of the adsorption and desorption rates. Using these results, we characterize the finite size effect on the equilibrium surface coverage. For comparable N’s, the finite size effect is significantly larger when N is even than when N is odd. Moreover, as N increases, the size effect decays more slowly in the even case than in the odd case. The finite-size effect becomes significant when adsorption and desorption rates are considerably different. These finite-size effects are related to the number of accessible configurations in a finite system where the odd-even dependence arises from the limited number of accessible configurations in the even case. We confirm our analytical results with kinetic Monte Carlo simulations. We also analyze the surface-diffusion case where adsorbed atoms can hop into neighboring sites. As expected, the odd-even dependence disappears because more configurations are accessible in the even case due to surface diffusion.
Introduction: Future Artemis missions aim to return the volatile-bearing samples collected near lunar polar craters. We, as advanced curation scientists, are responsible for developing techniques and methodologies for preserving the integrity of returned samples and the science value those samples contain. The extent to which that preservation is possible, and the trade-offs preservation requires (e.g. monetary costs, sample volume limitations) all must be considered. Even less-than pristine volatile-bearing samples will be of tremendous value to the scientific community seeking to unravel the history of lunar surface volatiles and, more broadly, volatiles in the solar system. A sample collected on the lunar surface will experience at least five distinctive periods during which any changes here referred to as “alteration” will certainly occur at some scale: collection on the lunar surface; transportation back to Earth; long-term storage; curatorial processing; and allocation/distribution. The Planetary Exploration and Astromaterials Research Lab (PEARL) seeks to understand temperature and pressure effects on returned volatile samples by working with high-fidelity volatile-containing regolith simulants, setting the foundation for the future of cold curation. This abstract is focused on gas-surface interactions between LCROSS volatiles and readily available lunar regolith simulants. Experiments involved analyzing differences in headspace gas composition for various combinations of volatile and regolith simulants using gas chromatography/mass spectrometry (GC/MS). Experimental Procedure: The volatile simulants were chosen based on the molecules detected during the LCROSS mission.1 Stock solutions of condensed lunar volatile analytes were: methanol, 7 N ammonia in methanol, and 0.4% hydrogen sulfide in water. The regolith simulants used were primarily JSC-1A and NU-LHT-4M. Additional regolith simulant control studies were conducted with <150 μm sieved sand and KBr. A nested vial sample preparation approach separated the liquid stock solutions from the regolith, eliminating potential matrix effects between liquid and solid phases. Fifteen microliter aliquots of liquid volatile simulants were added to a 2 mL liquid GC vial and capped in atmosphere. An 18G needle punctured the 2 mL GC vial immediately before being transferred and sealed in a 20 mL GC vial containing 0-0.3 g of regolith simulant, see Figure 1. Separating the analytes ensures any changes observed in the total headspace gases is a result of gas-surface and/or gas-gas interactions. Equipment and Method: Initial GC/MS method development for the separation and identification of relevant headspace gases can be found in Amick, et al. 2023.2 The only hardware change is a different column: a TG-1701MS 30 m × 0.25 mm × 1.00 μm column. The vials were sampled at 10°C, room temperature (~25°C) and 50°C. Low temperature samples were kept in a chilled autosampler stage for at least 1 hour prior to sampling. High temperature samples were agitated at 50°C for 5 minutes immediately prior to injection onto the column. Headspace chromatograms were collected for each combination of temperature, regolith, and volatile simulant, including controls without one or both types of analytes, in triplicate. The chromatogram elution window for each analyte or significant atmospheric gas was identified using the peak mass spectrum cross-referenced with Figure 1.Picture of the nested vial set-up. a NIST MS library search. Each analyte peak was integrated after filtering the mass spectrum trace for the parent or most unique mass-to-charge ratio. For example, the mass-to-charge ratio used to identify, filter for, and integrate the carbon dioxide peak was centered around 44 m/z. Results: Figure 2 shows the integrated peak area for hydrogen sulfide in all combinations of regolith simulants, temperatures, and the addition of ammonia in methanol solution. Multiple repeat experiments with H2S and regolith simulants have confirmed hydrogen sulfide is removed from the headspace within 1 hour when exposed to JSC-1A, NU-LHT-4M and sand (not pictured). The consumption of H2S by lunar regolith simulants at different temperatures indicates surface chemistry will be an integral component in sample integrity and preservation. It is important to note that while the effect of surface chemistry on gaseous hydrogen sulfide is intriguing, further investigation into more chemically accurate regolith simulants is necessary and ongoing. The sulfur in hydrogen sulfide is in its most reduced state while off-the-shelf, terrestrially sourced JSC-1A and NU-LHT-4M are more oxidized than most lunar materials,3which likely leads to different oxidation-reduction reactions than would be expected in lunar regolith. Figure 3 shows the integrated peak area of carbon dioxide for each sample combination that contained ammonia in methanol solution. The addition of ammonia to the GC vials results in a consistent and reproducible decrease in carbon dioxide gas, even at 50°C. The effect became more pronounced when JSC-1A or NU-LHT-4M were present. This set of experiments demonstrated that the sample composition will affect the chemical and physical state of each component present. Future spectroscopic and microscopy experiments will be geared towards identifying the cause for the CO2(g) concentration decrease and the consumption of hydrogen sulfide. As cold and volatile curation scientists, this information provides necessary insight on how to appropriately handle and analyze volatile bearing returned samples, as well as predict the effect chemical composition has on the various sample phases we will analyze upon return to Earth. Unlike traditional curation of geologic materials, the molecules in a sample cannot be identified or processed using the naked eye or even an optical microscope. Volatile curation will require a combination of analytical techniques, including but not limited to highly sensitive gas and solid/condensed phase spectroscopy. This set of experiments has demonstrated the need for more detailed studies of volatile mixtures with mineralogically and geochemically analogous lunar regolith simulants to prepare for the curation of volatile-rich lunar samples from the south polar region of the Moon. References: [1] Colaprete, A., et al. (2010) Science, 330, (463-468). [2] Amick, C. L., et al.(2023) Houston, Texas, [3] Heiken, G. H., et al.(1991) (778-778)
Abstract Measurements of short-timescale star formation variations (i.e., “burstiness” or star formation stochasticity) are integral to our understanding of star formation feedback mechanisms and the assembly of stellar populations in galaxies. We expand upon the work of Broussard et al. by introducing a new analysis of galaxy star formation burstiness that accounts for variations in the Q sg = E B − V stars / E B − V gas distribution, a major confounding factor. We use Balmer decrements from the MOSFIRE Deep Evolution Field (MOSDEF) survey to measure Q sg , which we use to construct mock catalogs from the Santa Cruz Semi-Analytic Models and Mufasa cosmological hydrodynamical simulation based on 3D-HST, Fiber Multi-Object Spectrograph (FMOS)-COSMOS, and MOSDEF galaxies with H α detections. The results of the mock catalogs are compared against observations using the burst indicator η = log 10 ( SFR H α / SFR NUV ) , with the standard deviation of the η distribution indicating burstiness. We find decent agreement between mock and observed η distribution shapes; however, the FMOS-COSMOS and MOSDEF mocks show a systematically low median and scatter in η in comparison to the observations. This work also presents the novel approach of analytically deriving the relationship between the intrinsic scatter in η , scatter added by measurement uncertainties, and observed scatter, resulting in an intrinsic burstiness measurement of 0.06–0.16 dex.
Many theories of dark matter beyond the weakly interacting massive particles paradigm feature an enhanced matter power spectrum on subparsec scales, leading to the formation of dense dark matter minihalos. Future local observations are promising to search for and constrain such substructures. The survival probability of these dense minihalos in the Milky Way environment is crucial for interpreting local observations. In this work, we investigate two environmental effects: stellar disruption and (smooth) tidal disruption. These two mechanisms are studied using semianalytic models and idealized N-body simulations. For stellar disruption, we perform a series of N-body simulations of isolated minihalo–star encounters to test and calibrate analytic models of stellar encounters before applying the model to the realistic Milky Way disk environment. For tidal disruption, we perform N-body simulations to confirm the effectiveness of the analytic treatment. Finally, we propose a framework to combine the hierarchical assembly and infall of minihalos to the Milky Way with the late-time disruption mechanisms. We make predictions for the mass functions of minihalos in the Milky Way. The mass survival fraction (at M$_{mh}$ ≥ 10$^{−12}$M$_{⊙}$) of dense dark matter minihalos, e.g., for axion miniclusters and minihalos from early matter domination, is ∼60% with the relatively low-mass, compact population surviving. The survival fraction is insensitive to the detailed model parameters. We discuss various implications of the framework and future direct detection prospects.
We report that atomic-scale modeling of thermophysical and defect properties of uranium mononitride (UN) plays an important role in establishing a better understanding and improved models of UN fuel performance. Having an accurate interatomic potential is crucial for generating reliable data at finite temperatures using molecular dynamic simulations. We report a new interatomic potential for UN, based on a combination of many-body and pairwise interactions, a simple form that we later show could be easily adapted to include Xe-U and Xe-N interactions, i.e., generating a U-N-Xe interatomic potential. The potential was fitted to experimental thermal expansion and single crystal elastic constants, as well as Frenkel, Schottky, anti-Schottky, and antisite pair reaction energies from density functional theory (DFT) calculations. Using the potential, we successfully reproduced experimental lattice parameters, thermal expansion, single crystal elastic constants, and temperature dependent heat capacity. The potential also performs reasonably well in reproducing the energy of the aforementioned stoichiometric defect reactions and defect migration barriers calculated using DFT. However, the potential underestimates the energy difference between the tetrahedral and dumbbell uranium interstitials, and a more complex potential form might be needed to overcome this issue. The potential was also used to predict UN single crystal elastic constants and elastic properties at different temperatures, showing that UN becomes softer and more compressible with increasing temperature. We also compare our potential against literature data from previous empirical potentials, demonstrating similar or better behavior depending on the property of interest. To enable the simulation of Xe in UN a Buckingham potential has been fitted to DFT-derived Xe incorporation energies. The potential was then used to determine the activation energy for Xe diffusion due to various Xe-containing defects, with {XeU : VU} exhibiting the lowest activation energy.
Ultrafast optical frequency combs allow for both high spectral and temporal resolution in molecular spectroscopy and have become a powerful tool in many areas of chemistry and physics. Ultrafast lasers and frequency combs generated from ultrafast mode-locked lasers often need to be converted to other wavelengths. Commonly used wavelength conversions are optical parametric oscillators, which require an external optical cavity, and supercontinuum generation combined with optical parametric amplifiers. Whether commercial or home-built, these systems are complex and costly. Here, we investigate an alternative, simple, and easy-to-implement approach to tunable frequency comb ultrafast lasers enabled by new continuous-wave laser technology. Sum-frequency generation between an Nd:YAG continuous-wave laser and a Yb:fiber femtosecond frequency comb in a beta-barium borate (BBO) crystal is explored. The resulting sum-frequency beam is a pulsed frequency comb with the same repetition rate as the Yb:fiber source. SNLO simulation software is used to simulate the results and provide benchmarks for designing future systems to achieve wavelength conversion and tunability in otherwise difficult-to-reach spectral regions.
Ligand binding free energy simulations (LB-FES) that involve sampling of protein functional conformations have been longstanding challenges in research on molecular recognition. Particularly, modeling of the conformational transition pathway and design of the heuristic biasing mechanism are severe bottlenecks for the existing enhanced configurational sampling (ECS) methods. Inspired by the key role of hydration in regulating conformational dynamics of macromolecules, this report proposes a novel ECS approach that facilitates binding-associated structural dynamics by accelerated hydration transitions in combination with the lambda-exchange of free energy perturbation (FEP). Further, two challenging protein-ligand binding processes involving large configurational transitions of the receptor are studied, with hydration transitions at binding sites accelerated by Hamiltonian-simulated annealing of the hydration layer. Without the need for pathway analysis or ad hoc barrier flattening potential, LB-FES were performed with FEP/lambda-exchange molecular dynamics simulation at a minor overhead for annealing of the hydration layer. The LB-FES studies showed that the accelerated rehydration significantly enhances the collective conformational transitions of the receptor, and convergence of binding affinity calculations is obtained at a sweet-spot simulation time scale. Alchemical LB-FES with the proposed ECS strategy is free from the effort of trial and error for the setup and realizes efficient on-the-fly sampling for the collective functional response of the receptor and bound water and therefore presents a practical approach to high-throughput screening in drug discovery.
A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.
In this work, we study the evaporation-induced stratification of a mixture of short and long polymer chains in a drying droplet using molecular simulations. We systematically investigate the effects of hydrodynamic interactions (HI) on this process by comparing hybrid simulations accounting for HI between polymers through the multiparticle collision dynamics technique with free-draining Langevin dynamics simulations neglecting the same. We find that the dried supraparticle morphologies are homogeneous when HI are included but are stratified in core–shell structures (with the short polymers forming the shell) when HI are neglected. The simulation methodology unambiguously attributes this difference to the treatment of the solvent in the two models. We rationalize the presence (or absence) of stratification by measuring phenomenological multicomponent diffusion coefficients for the polymer mixtures. The diffusion coefficients show the importance of not only solvent backflow but also HI between polymers in controlling the dried supraparticle morphology.
Abstract We perform a high-resolution cosmological zoom-in simulation of a Milky Way (MW)–like system, which includes a realistic Large Magellanic Cloud analog, using a large differential elastic dark matter self-interaction cross section that reaches ≈100 cm 2 g −1 at relative velocities of ≈10 km s −1 , motivated by the diverse and orbitally dependent central densities of dwarf galaxies within and surrounding the MW. We explore the effects of dark matter self-interactions on satellite, splashback, and isolated halos through their abundance, central densities, maximum circular velocities, orbital parameters, and correlations between these variables. We use an effective constant cross section model to analytically predict the stages of our simulated halos’ gravothermal evolution, demonstrating that deviations from the collisionless R max – V max relation can be used to select deeply core-collapsed halos, where V max is a halo’s maximum circular velocity, and R max is the radius at which it occurs. We predict that a sizable fraction (≈20%) of subhalos with masses down to ≈10 8 M ⊙ is deeply core collapsed in our SIDM model. Core-collapsed systems form ≈10% of the isolated halo population down to the same mass; these isolated, core-collapsed halos would host faint dwarf field galaxies with extremely steep central density profiles. Finally, most halos with masses above ≈10 9 M ⊙ are core-forming in our simulation. Our study thus demonstrates how self-interactions diversify halo populations in an environmentally dependent fashion within and surrounding MW-mass hosts, providing a compelling avenue to address the diverse dark matter distributions of observed dwarf galaxies.
Focal Area: Focal Area 3: Insight gleaned from complex simulated data using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: An understanding of future evolution in precipitation extremes is critical to numerous DOE mission questions. Extreme events are by nature short time-scale events that are difficult to diagnose in available model data. Accurate modeling of extreme events necessarily requires high spatial resolution at the storm scale locally. However, the environment in which storms grow is dependent on global, remote, processes. These complex spatiotemporal relationships are impossible to diagnose at resolutions required to accurately model storms responsible for extreme precipitation. At exascale, climate simulations will produce results at fine enough resolution to investigate these relationships. However, the resulting data from these simulations will be far too large to save for post-simulation analysis. We advocate for fitting statistical models inside the simulations as they run, a context known as in situ, which will facilitate scientific investigations using the full fine-scale data stream. Figure 1 shows an example of the type of model we could consider, a Bayesian hierarchical spatial regression model. Precipitation extremes at each grid cell are modeled using extreme value distributions. Since extremes are rare, fitting models to individual grid cells can result in high variance and poor estimates. Instead, the model can be made more robust by smoothing the parameters of the extreme value model across space. Additionally, the parameters themselves can be functionally linked to other variables elsewhere in the simulation. Thus, we can use the fine-scale data to build more robust models for extremes that link extreme behavior to other climate patterns.
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An accurate understanding of the competitive adsorption of CH 4 -CO 2 binary mixtures in nano-confined systems is critical for engineering CO 2 storage in shale gas reservoirs. Due to difficulties in making reliable experimental observations in nano-scale, atomistic simulations (ASs), such as the Grand Canonical Monte Carlo (GCMC) method, provide a viable approach to studying the adsorption behavior of confined fluids. ASs are, however, limited in the size of the compositional domain due to the high computational cost. This work proposes a framework that combines AS and the lattice Boltzmann (LB) method to bridge the physics of confined fluids across scales. The Peng–Robinson equation of state (PR-EoS) produces fugacity coefficients, which serve as input for conducting multi-component GCMC simulations. These GCMC simulations explore the competitive adsorption behavior of CH 4 -CO 2 in nano-slits at various composition, pressure, and channel-width conditions. Both components generate adsorption layers with high densities near the walls with CO 2 preferentially adsorbing compared to CH 4 on the organic walls of carbon sheets. At the mesoscale, a pseudopotential model represents the intermolecular forces in multi-component, multiple-relaxation-time LB simulations. The LB simulations are in good agreement with the GCMC results, allowing us to obtain values for tunable LB parameters. We then extend the use of LB to simulate adsorption behavior in complex networks with nano-sized channels. The phase behavior and fluid properties in the complex geometries of nano-channels differ from nano-slits and bulk systems. Furthermore, the bridging of physics from GCMC (microscale) to LB (mesoscale) via the macroscale PR-EoS connects the adsorption behavior of binary systems across scales.
Understanding the driving forces behind the nucleation of different polymorphs is of great importance for material sciences and the pharmaceutical industry. This includes understanding the reaction coordinate that governs the nucleation process and correctly calculating the relative free energies of different polymorphs. Here, we demonstrate, for the prototypical case of urea nucleation from the melt, how one can learn such a one-dimensional reaction coordinate as a function of prespecified order parameters and use it to perform efficient biased all-atom molecular dynamics simulations. The reaction coordinate is learnt as a function of the generic thermodynamic and structural order parameters using the “spectral gap optimization of order parameters (SGOOP)” approach [Tiwary, P. and Berne, B. J. Proc. Natl. Acad. Sci. U.S.A. (2016)] and is biased using well-tempered metadynamics simulations. The reaction coordinate gives insights into the role played by different structural and thermodynamics order parameters, and the biased simulations obtain accurate relative free energies for different polymorphs. This includes an accurate prediction of the approximate pressure at which urea undergoes a phase transition and one of the metastable polymorphs becomes the most stable conformation. Here, we believe the ideas demonstrated in this work will facilitate efficient sampling of nucleation in complex, generic systems.
The formation and evolution of polarization charge layers on cylindrical plasma streams moving in vacuum are investigated using analytic theory and 2D electrostatic particle-in-cell computer simulations. It is shown that the behavior of the electron charge layer goes through three stages. An early time expansion is driven by electrostatic repulsion of electrons in the charge layer. At the intermediate stage, the simulations show that the electron-charge-layer expansion is halted by the positively charged plasma stream. Electrons close to the stream are pulled back to the stream and a second electron expansion follows in time. At the late stage, the expansion of the ion charge layer along the magnetic field lines accompanies the electron expansion to form an ambipolar expansion. It is found that the velocities of these electron-ion expansions greatly exceed the velocities of ambipolar expansions which are driven by plasma temperatures.
The resolution of a mega-electron-volt scanning transmission electron microscope (MeV-STEM) is primarily governed by the properties of the incident electron beam and angular broadening effects that occur within thick biological samples and microchips. A precise understanding and mitigation of these constraints require detailed knowledge of beam emittance, aberrations in the STEM column optics, and energy-dependent elastic and inelastic critical angles of the materials being examined. This simulation study proposes a standardized experimental framework for comprehensively assessing beam intensity, divergence, and size at the sample exit. This framework aims to characterize electron-sample interactions, reconcile discrepancies among analytical models, and validate Monte Carlo (MC) simulations for enhanced predictive accuracy. Our numerical findings demonstrate that precise measurements of these parameters, especially angular broadening, are not only feasible but also essential for optimizing imaging resolution in thick biological samples and microchips. By utilizing an electron source with minimal emittance and tailored beam characteristics, along with amorphous ice and silicon samples as biological proxies and microchip materials, this research seeks to optimize electron beam energy by focusing on parameters to improve the resolution in MeV-STEM/TEM. This optimization is particularly crucial for in situ imaging of thick biological samples and for examining microchip defects with nanometer resolutions. Our ultimate goal is to develop a comprehensive mapping of the minimum electron energy required to achieve a nanoscale resolution, taking into account variations in sample thickness, composition, and imaging mode.
In 1941 G.I. Taylor proposed the cylinder test as an experiment to determine the properties of explosive products. The test consists of a hollow metal cylinder containing an unreacted cylindrical charge of explosives. The charge is detonated at one end of the cylinder and, as the detonation wave propagates, the product gas expands behind it. As the product gas is produced, the pressure acting on the metal increases and begins to push the walls outward. Consider the time at which the detonation wave has reached the halfway point between the two ends of the cylinder. In front of the wave nothing has changed and the metal tube has the same initial radius. Behind the wave, the radius of the tube has expanded. The farther behind the wave a section of tube is, the larger its radius has become. The longer the wall is exposed to the pressurized gas, the more it expands, so that the radius is largest where the detonation was initiated. The metal most commonly used for this experiment is soft copper. Its material properties are well known and soft copper is also easy to shape with precision machining. During the cylinder test the radial expansion of the cylinder is measured over time and this data is used to determine the amount of work applied to the cylinder wall by the product gas as a function of time. Since volume increases in this problem, the time dependence can be seen as a volume dependence. The volume dependent work yields a path in thermodynamic space. The cylinder test experiment can be modeled using simulation. The simulation gives you the answer, but it cannot tell you why. The goal of the proposed work is to use analytic analysis methods to give insight into the simulation solution.