Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “dynamic simulation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,045 records · Page 58

Integrating Experiments and Simulations to Reveal Anisotropic Growth Mechanisms and Interfaces of a One-Dimensional Zeolite

Zeolites are nanoporous crystalline materials critical for diverse industrial applications, yet their growth mechanisms are poorly understood. Here, this study presents a novel integrated framework combining experimental synthesis, high-resolution imaging, coarse-grained molecular dynamics simulations, and computer vision to uncover the mechanisms of growth of SSZ-24, a 1D channel zeolite. We demonstrate how synthesis conditions, such as temperature and reactant concentration, govern crystal anisotropy and surface roughness with growth dynamics differing markedly by crystallographic orientation. Along the channels, growth involves minimal energy barriers and rapid nucleation, resulting in rough surfaces. In contrast, growth perpendicular to the channels requires cooperative molecular organization and is highly sensitive to thermodynamic and kinetic conditions, yielding smooth anisotropic surfaces under low driving forces. By simulating transmission electron microscopy (TEM) images, we bridge molecular-scale simulations with experimental observations, identifying distinct growth mechanisms along different crystal planes. This work offers molecular-level insights into zeolite crystallization, advancing the rational design of nanoporous materials. The integration of cross-disciplinary methodologies establishes a transformative framework for optimizing zeolite synthesis, with implications for broader classes of materials.

Bertolazzo, Andressa A. [Univ. of Utah, Salt Lake ↗

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗

Quantification of energy and cost reduction from decreasing dissolved oxygen levels in full‐scale water resource recovery facilities

Abstract Aeration systems often lack the efficiency to maintain a desired residual dissolved oxygen (DO) concentration in the tank in part because little consideration is given to the dynamic daily and seasonal loading conditions. Although advanced aeration controllers exist, the majority of plants have DO set points typically based on common practice and literature values rather than site‐specific conditions, which can result in DO set points higher than those necessary to meet treatment objectives. DO set point reduction strategies have primarily been proposed through either static or dynamic simulations. In this study, the substantial improvements associated with DO set point reduction are demonstrated at full scale. A yearlong characterization of full‐scale aeration dynamics captured the effect of diurnal and seasonal fluctuations on oxygen transfer and energy demand and so facilitated the estimation of the potential savings of DO reduction strategies. Full‐scale validation provided direct evidence of DO reduction strategies inducing an overall enhancement of oxygen transfer efficiency along the different bioreactors, while confirming that energy savings as high as 20% were feasible. This study quantifies the influence of oxygen transfer efficiency on operating choices and site‐specific conditions (control strategy, loading conditions, and influent flow variability). Practitioner points We quantified the energy reduction and cost savings associated with a DO reduction in an aeration tank. For each 0.2 mg/L of DO decreased, the average power demand reduction per unit water treated exceeded 17%. Field measurements of dynamic alpha values eliminate the uncertainty in estimating aeration energy and cost savings from DO variations.

Pasini, Federico↗

Structural and Dynamical Roles of Bound Polymer Chains in Rubber Reinforcement

The addition of nanofillers to rubber matrices is a powerful route to improve the mechanical properties. Here, we focus on a molecular understanding of basic mechanisms that are important for the reinforcement in rubbers. The key role in this process is ascribed to bound rubber (BR) that engages with the matrix as well as with adjacent nanofillers. To date, this understanding has been impeded by the lack of experimental tools to directly probe the BR chains buried in a polymer matrix composed of the same polymer. To tackle this challenge, we combine neutron scattering/spectroscopy techniques with isotope-labeling and molecular dynamics simulations. The system is a simplified carbon-black-filled polybutadiene. The combined experimental and computational results provide new insights into the local structural and dynamical heterogeneities of BR chains and their interactions with the matrix polymer, highlighting (i) the structural partition of the bound chains into three components (i.e., trains, loops, and tails) and their fractions; (ii) their dynamical hierarchies, i.e., the trains that remain immobile on the filler surface, the loops that are fairly large and hence allow the interdigitation of matrix chains, and the tails with their unique characteristics to reach far out into the matrix and entangle with matrix chains. These multiple roles of the constituent components of the BR chains promote the formation of a well-developed adhesive polymer–filler interface, enhancing the elastic property of a filled rubber. Finally, the comprehensive understanding derived and validated by the model rubber will be translatable to many other polymer nanocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nonideal mixing effects in warm dense matter studied with first-principles computer simulations

Here, we study nonideal mixing effects in the regime of warm dense matter (WDM) by computing the shock Hugoniot curves of BN, MgO, and MgSiO 3 . First, we derive these curves from the equations of state (EOS) of the fully interacting systems, which were obtained using a combination of path integral Monte Carlo calculations at high temperature and density functional molecular dynamics simulations at lower temperatures. We then use the ideal mixing approximation at constant pressure and temperature to rederive these Hugoniot curves from the EOS tables of the individual elements. We find that the linear mixing approximation works remarkably well at temperatures above ~2 × 10 5 K, where the shock compression ratio exceeds ~3.2. The shape of the Hugoniot curve of each compound is well reproduced. Regions of increased shock compression, which emerge because of the ionization of L and K shell electrons, are well represented, and the maximum compression ratio of the Hugoniot curves is reproduced with high precision. Some deviations are seen near the onset of the L shell ionization regime, where ionization equilibrium in the fully interacting system cannot be well reproduced by the ideal mixing approximation. This approximation also breaks down at lower temperatures, where chemical bonds play an increasingly important role. However, the results imply that the equilibrium properties of binary and ternary mixtures in the regime of WDM can be derived from the EOS tables of the individual elements. This significantly simplifies the characterization of binary and ternary mixtures in the WDM and plasma phases, which otherwise requires large numbers of more computationally expensive first-principles computer simulations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Allosteric Tuning of Caspase–7: Establishing the Nexus of Structure and Catalytic Power

Caspase-7 (C7), a cysteine protease involved in apoptosis, is a valuable drug target for its role in human diseases (e. g., Parkinson's, Alzheimer's, sepsis). The C7 allosteric site has great potential for small-molecule targeting, but numerous drug discovery efforts have identified precious few allosteric inhibitors. Here we present the first selective, drug-like inhibitor of C7 along with several other improved inhibitors based on our previous fragment hit. We also provide a rational basis for the impact of allosteric binding on the C7 catalytic cycle by using an integrated approach including X-ray crystallography, stopped-flow kinetics, and molecular dynamics simulations. Our findings suggest allosteric binding disrupts C7 pre-acylation by neutralization of the catalytic dyad, displacement of substrate from the oxyanion hole, and altered dynamics of substrate binding loops. This work advances drug targeting efforts and bolsters our understanding of allosteric structure–activity relationships (ASARs).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of reaction media on hydrogenolysis of polyethylene plastic waste: Polymer-surface interactions in small alkane/polymer blends

The polymer reaction media and its properties can be altered by recycling a fraction of liquid products or adding alkane solvents. Less clear is whether this strategy affects hydrogenolysis. Herein, we investigated the effect of short-chain alkanes C n consisting of n carbons (n=8, 16, and 32) on the upcycling of high-density polyethylene (HDPE) plastic waste to lubricant-range products over Ru/TiO 2 catalysts by multiscale simulations and experiments. First, we trained a force field for polymer/surface interactions on a Ru 22 nanoparticle (NP) supported on TiO 2 . Using replica exchange molecular dynamics simulations, we studied the effect of small hydrocarbons on the adsorption of a surrogate polymer, C 142 , on the catalyst. We found segregation of long chains (C 142 ) at the catalyst surface due to the enthalpy gained by adsorbing more C-C bonds of the long chains, compensating for entropic losses upon adsorption. Short-chain molecules decrease the adsorbed carbons of long chains on the Ru NP due to blocking Ru active sites. Compared to the bulk chains, competitive adsorption results in a broader, heavy-tailed distribution of end-to-end distance of adsorbed chains. Our experiments demonstrated that catalyst activity declines significantly beyond simple dilution due to changes in polymer adsorption, and tuning the reaction media by creating suitable blends impacts hydrogenolysis. Density distributions for a 50:50%wt mixture of PP and PE show that PE chains are segregated at the surface, so they are prone to C-C bond breaking much faster than PP chains. H/D exchange experiments show preferential deuteration of PE, while CH 3 groups of PP remain undeuterated. Furthermore, this may be explained by the preferential sorption of PE over PP, leading to specific distribution in the polymer blend.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Disentangling multiple scattering with deep learning: application to strain mapping from electron diffraction patterns

Abstract A fast, robust pipeline for strain mapping of crystalline materials is important for many technological applications. Scanning electron nanodiffraction allows us to calculate strain maps with high accuracy and spatial resolutions, but this technique is limited when the electron beam undergoes multiple scattering. Deep-learning methods have the potential to invert these complex signals, but require a large number of training examples. We implement a Fourier space, complex-valued deep-neural network, FCU-Net, to invert highly nonlinear electron diffraction patterns into the corresponding quantitative structure factor images. FCU-Net was trained using over 200,000 unique simulated dynamical diffraction patterns from different combinations of crystal structures, orientations, thicknesses, and microscope parameters, which are augmented with experimental artifacts. We evaluated FCU-Net against simulated and experimental datasets, where it substantially outperforms conventional analysis methods. Our code, models, and training library are open-source and may be adapted to different diffraction measurement problems.

36 MATERIALS SCIENCE↗

Liquid-like dynamics in a solid-state lithium electrolyte

Superionic materials represent a regime intermediate between the crystalline and liquid states of matter. Despite the considerable interest in potential applications for solid-state batteries or thermoelectric devices, it remains unclear whether the fast ionic diffusion observed in superionic materials reflects liquid-like dynamics or whether the hops of mobile ions are inherently coupled to more conventional lattice phonons. Here we reveal a crossover from crystalline vibrations to relaxational dynamics of ionic diffusion in the superionic compound Li 6 PS 5 Cl, a candidate solid-state electrolyte. By combining inelastic and quasi-elastic neutron-scattering measurements with first-principles-based machine-learned molecular dynamics simulations, we found that the vibrational density of states in the superionic state strongly deviates from the quadratic behaviour expected from the Debye law of lattice dynamics. The superionic dynamics emerges from overdamped phonon quasiparticles to give rise to a linear density of states characteristic of instantaneous normal modes in the liquid state. Further, we showed that the coupling of lattice phonons with a dynamic breathing of the Li+ diffusion bottleneck enables an order-of-magnitude increase in diffusivity. Thus, our results shed insights into superionics for future energy storage and conversion technologies.

25 ENERGY STORAGE↗

Local cation ordering in compositionally complex Ruddlesden–Popper n = 1 oxides

The Ruddlesden–Popper (RP) layered perovskite structure is of great interest due to its inherent tunability, and the emergence and growth of the compositionally complex oxide (CCO) concept endows the RP family with further possibilities. Here, a comprehensive assessment of thermodynamic stabilization, local order/disorder, and lattice distortion was performed in the first two reported examples of lanthanum-deficient La n+1 B n O 3n+1 (n = 1, B = Mg, Co, Ni, Cu, Zn) obtained via various processing conditions. Chemical short-range order (CSRO) at the B-site and the controllable excess interstitial oxygen (δ) in RP-CCOs are uncovered by neutron pair distribution function analysis. Reverse Monte Carlo analysis of the data, Metropolis Monte Carlo simulations, and extended x-ray absorption fine structure analysis implies a modest degree of magnetic element segregation on the local scale. Further, ab initio molecular dynamics simulations results obtained from special quasirandom structure disagree with experimentally observed CSRO but confirm Jahn–Teller distortion of CuO 6 octahedra. These findings highlight potential opportunities to control local order/disorder and excess interstitial oxygen in layered RP-CCOs and demonstrate a high degree of freedom for tailoring application-specific properties. They also suggest a need for expansion of theoretical and data modeling approaches in order to meet the innate challenges of CCO and related high-entropy phases.

36 MATERIALS SCIENCE↗

Unexpected Observation of Disorder and Multiple Phase-Transition Pathways in Shock-Compressed Zr

The response of materials under dynamic compression involves a complex interplay of various deformation mechanisms aimed at relieving shear stresses, yielding a remarkable diversity in material behavior. Here, in this Letter, we utilize femtosecond x-ray diffraction coupled with nanosecond laser compression to reveal an intricate competition between multiple shear-relieving mechanisms within an elemental metal. Our observations in shocked-compressed single-crystal Zr indicate a disorder-mediated shear relaxation at lower pressures. Above the phase-transition pressure, we observe the increasing contribution of structural phase transition in relieving shear stress. We detect not one but three concurrent pathways during the transition from the hcp to a hex-3 structure. These complex dynamics are partially corroborated through multimillion-atom molecular dynamics simulations employing a machine-learned interatomic potential. Our observation of multiple concurrent pathways and disorder during shock compression underscore the far greater intricacies in the dynamic response of metals than previously assumed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Crystal structure of dihydrofolate reductase from the filarial nematode W. bancrofti in complex with NADPH and folate

Lymphatic filariasis is a debilitating illness with an estimated 50 million cases as of 2018. The majority of cases are caused by the parasitic worm W. bancrofti and additional cases by the worms B. malayi and B. timori. Dihydrofolate reductase (DHFR) is an established target in the treatment of cancer, bacterial, and protozoal infections and may be a potential target for drugs targeting parasitic worm infections, including filariasis. Recent studies have shown that known antifolate compounds, including methotrexate, inhibit the activity of W. bancrofti DHFR (WbDHFR). However, the absence of structural information for filarial DHFRs has limited the study of more in-depth structure-function relationships. We report the structure of WbDHFR complexed with NADPH and folate using X-ray diffraction data measured to 2.47 Å resolution. The structure of WbDHFR reveals the usual DHFR fold and is currently only the second nematode DHFR structure in the Protein Data Bank. The equilibrium dissociation constants for NADPH (90 ± 29 nM) and folate (23 ± 4 nM) were determined by equilibrium titrations. The interactions of known antifolates with WbDHFR were analyzed using molecular docking programs and molecular dynamics simulations. Antifolates with a hydrophobic core and extended linker formed favorable interactions with WbDHFR. These combined data should now facilitate the rational design of filarial DHFR inhibitors, which in turn can be used to determine whether DHFR is a viable drug target for filariasis and whether existing antifolates may be repurposed for its treatment.

60 APPLIED LIFE SCIENCES↗

Numerical Modeling and Parametric Study of a Dual Purpose Underground Thermal Battery

Buildings’ thermal energy systems for providing space heating/cooling consume a considerable amount of electricity nationwide. Integrating thermal energy storage with buildings’ thermal systems has the potential to shave the peak electric demand and to overcome the mismatch between the intermittent renewable power and the fluctuating daily demand for electricity. A novel dual-purpose underground thermal battery (DPUTB) has been developed to provide diurnal thermal energy storage in conjunction with a dual-source heat pump (DSHP)system. A two-dimensional numerical model is developed to simulate the transient performance of the DPUTB. This model has similar accuracy as a detailed three-dimensional model developed with commercial heat transfer and fluid dynamics simulation program but with 1000 times faster computational speed. A parametric study is performed to identify a design of the DPUTB that can provide 14 kWh thermal storage capacity for each charging and discharging cycle. A system simulation has been developed to assess the performance of the designed DPUTB when it is integrated with a DSHP for conditioning a typical residential building in summer and winter. Simulation results indicate that the DPUTB can meet all the design requirements in both summer and winter with the simple rule-based control strategy and the overall integrated DPUTB and DSHP system can shift the electric load for meeting the thermal demand from the peak hours to off-peak hours during a day, which would result in considerable energy cost savings if a Time of Use electricity tariff is applicable.

25 ENERGY STORAGE↗

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗

On the Morphodynamics of a Wide Class of Large‐Scale Meandering Rivers: Insights Gained by Coupling LES With Sediment‐Dynamics

Abstract In meandering rivers, interactions between flow, sediment transport, and bed topography affect diverse processes, including bedform development and channel migration. Predicting how these interactions affect the spatial patterns and magnitudes of bed deformation in meandering rivers is essential for various river engineering and geoscience problems. Computational fluid dynamics simulations can predict river morphodynamics at fine temporal and spatial scales but have traditionally been challenged by the large scale of natural rivers. We conducted coupled large‐eddy simulation and bed morphodynamics simulations to create a unique database of hydro‐morphodynamic data sets for 42 meandering rivers with a variety of planform shapes and large‐scale geometrical features that mimic natural meanders. For each simulated river, the database includes (a) bed morphology, (b) three‐dimensional mean velocity field, and (c) bed shear stress distribution under bankfull flow conditions. The calculated morphodynamics results at dynamic equilibrium revealed the formation of scour and deposition patterns near the outer and inner banks, respectively, while the location of point bars and scour regions around the apexes of the meander bends is found to vary as a function of the radius of curvature of the bends to the width ratio. A new mechanism is proposed that explains this seemingly paradoxical finding. The high‐fidelity simulation results generated in this work provide researchers and scientists with a rich numerical database for morphodynamics and bed shear stress distributions in large‐scale meandering rivers to enable systematic investigation of the underlying phenomena and support a range of river engineering applications.

54 ENVIRONMENTAL SCIENCES↗

Sulfonated polybenzimidazole membrane with graphene oxide additive for 2,3-butanediol/water separation: A molecular simulation

Membrane separation for 2,3-butanediol (2,3-BDO) recovery from fermentation broth is highly valued for sustainable and renewable processes, but it requires efficient membrane materials. Here, this work evaluates the sulfonated polybenzimidazole (sPBI) and its graphene oxide (GO) doped composite membrane for separating 2,3-BDO and water via atomistic simulations. Density functional theory calculations are applied to identify various forms of sPBI structures and quantify their binding interactions with 2,3-BDO and water. Classical molecular dynamic simulations are used to evaluate the structural changes, diffusivity, and selectivity of 2,3-BDO and water in different sPBI models, GO surfaces, and GO-doped sPBI composite models. Our results suggest that sPBI slightly increases the crystallinity of the membrane structures, enhances the adsorption strength for both 2,3-BDO and water, and improves the water/2,3-BDO selectivity by 2–3 times. The GO surfaces display a maximum selectivity at a surface coverage of 0.1–0.15 for both hydroxyl and epoxy surface groups. The addition of GO flakes to sPBI creates new interaction sites for 2,3-BDO and water at the interface of sPBI and GO, and the water/2,3-BDO selectivity of GO-doped sPBI models is further increased up to 3 times. This work illustrates how the integrated addition of sPBI and GO flakes offers a promising approach to selective separation of 2,3-BDO and water, providing theoretical guidance for polybenzimidazole-based membranes in the potential application of 2,3-BDO recovery.

2,3-butanediol↗

Molecular Dynamics Investigation of Oil Wetting on Synthetic Polymer Substrates

Understanding the interaction of polymer surfaces with nonpolar, low surface tension liquids, or whether a substrate is oleophobic versus oleophilic, is critical for applications ranging from antifingerprint coatings to oil–water separation membranes and oil spill remediation. Despite its technological importance, the molecular mechanisms underpinning polymer–oil wetting are not well characterized. Here, we employ molecular dynamics simulations to investigate the behavior of n-hexadecane in contact with chemically distinct polymer surfaces, spanning eight constitutional unit chemistries as well as amorphous and crystalline morphologies. This permits a critical examination of both thermodynamic and dynamic descriptors of oleophobicity, including oil contact angle, dewetting free energy, interfacial diffusivity, and a proposed “ghost probe energy,” which does not require explicit simulation of oil–polymer interactions. We find that the oil contact angle does not reliably distinguish oleophobic behavior across polymer chemistries, whereas other metrics provide clearer and more consistent differentiation. Analysis of the results reveals that polymer–oil wetting behavior is primarily governed by interfacial van der Waals interactions and modulated by surface flexibility and morphology. Collectively, this work establishes a computational framework for characterizing oil wetting and provides additional insight into what molecular-level factors dictate trends in oleophobicity.

lipids↗