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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.

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At least 1,639 records · Page 91

Modeling and Simulation Credibility Assessment of Finite Element Models for Fall From Heights Injury Scenarios

Finite element (FE) computational models of the whole human body are being used to investigate the injury modalities and mechanisms arising from suited astronauts’ ExtraVehicular Activities (EVAs). These FE whole body models – simplified Elemance and THUMS pedestrian versions – have undergone a series of verification and validation (V&V) assessments for applications in automotive, domestic, and contact sports arenas. However, the FE models’ Modeling and Simulation (M&S) credibility assessments for simulating suited astronaut injuries due to fall from heights in altered gravity environments are limited. The current study evaluates the M&S credibility of simplified Elemance and THUMS pedestrian FE models based on eight credibility factors – data pedigree, input pedigree, code verification, solution verification, conceptual validation, referent validation, results uncertainty, and results robustness – as per NASA-STD-7009A [1]. These credibility factors were assigned ordinal scores ranging between 0 to 4, with a score of 0 in the case of insufficient evidence and 4 when all data for the model is known, used appropriately, and traceable to the Real-World System (RWS) with acceptable accuracy, precision, and uncertainty. The credibility factor sufficiency thresholds were assigned upon guidance from NASA EVA subject matter experts. The factor scores were ascertained through the evaluation of M&S credibility assessment procedures described in the published literature and FE model reports. The M&S credibility scores for the Elemance and THUMS FE models vary between 1 and 3 for data pedigree, input pedigree, and referent validation credibility factors, and between 0 and 1 for code verification, solution verification, conceptual validation, results uncertainty and results robustness. The results show that these FE models are credible for simulating fall from heights injury scenarios in specific kinematic and kinetic ranges that correlate with highway and contact sports-related external conditions. Multiple credibility elevation strategies are prescribed to improve the Elemance and THUMS models’ credibility for use in the EVA fall from height injury scenarios.

R A Perkins↗

Influence of Ductility on the Performance of Lunar Habitat Structures Under Recurrent Disturbances

This research examines how ductility affects the durability of lunar surface structures against recurring disturbances like moonquakes, micrometeorite impacts, and thermal cycles over an extended period. The structural performance at various levels of ductility was determined by adjusting material parameters and the thickness of a reference multilayered dome structure. Moonquake and micrometeorite impact-induced lateral displacements were estimated using a reduced-order model under a control-oriented dynamic computational modeling framework. The study considered the degradation of the metallic dome’s strength properties over time due to thermal cycles. Fragility curves were generated by assessing the likelihood of reaching three predefined damage levels as a result of multiple hazards. Additionally, a discounted cash flow analysis was conducted to incorporate a financial aspect into the performance comparison. The findings revealed that structures with sufficient ductility capacity have a lower probability of sustaining severe damage or collapsing within a shorter time frame. Hence, having ductile structures in lunar environments is advantageous as it allows the postponement of maintenance and repair actions, thereby conserving scarce resources for more urgent tasks. Moreover, the financial analysis demonstrated that lunar habitats with higher ductile capacities result in larger net present values, offering a higher return on the initial investment.

Arsalan Majlesi↗

CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. In this work, we present a computational tool, Glycan Modeler for in silico N–/O –glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader , a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-μs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler . Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

59 BASIC BIOLOGICAL SCIENCES↗

Treatment of atomic and molecular line blanketing by opacity sampling

A sampling technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is subjected to several tests. In this opacity sampling (OS) technique, the global opacity is sampled at only a selected set of frequencies, and at each of these frequencies the total monochromatic opacity is obtained by summing the contribution of every relevant atomic and molecular line. In accord with previous results, we find that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 100 frequency points are adequate for many purposes. The effects of atomic and molecular lines are separately studied. A test model computed using the OS method agrees very well with a model having identical atmospheric parameters, but computed with the giant line (opacity distribution function) method.

Johnson, H. R.↗

Modeling of the HiPco process for carbon nanotube production. II. Reactor-scale analysis

The high-pressure carbon monoxide (HiPco) process, developed at Rice University, has been reported to produce single-walled carbon nanotubes from gas-phase reactions of iron carbonyl in carbon monoxide at high pressures (10-100 atm). Computational modeling is used here to develop an understanding of the HiPco process. A detailed kinetic model of the HiPco process that includes of the precursor, decomposition metal cluster formation and growth, and carbon nanotube growth was developed in the previous article (Part I). Decomposition of precursor molecules is necessary to initiate metal cluster formation. The metal clusters serve as catalysts for carbon nanotube growth. The diameter of metal clusters and number of atoms in these clusters are some of the essential information for predicting carbon nanotube formation and growth, which is then modeled by the Boudouard reaction with metal catalysts. Based on the detailed model simulations, a reduced kinetic model was also developed in Part I for use in reactor-scale flowfield calculations. Here this reduced kinetic model is integrated with a two-dimensional axisymmetric reactor flow model to predict reactor performance. Carbon nanotube growth is examined with respect to several process variables (peripheral jet temperature, reactor pressure, and Fe(CO)5 concentration) with the use of the axisymmetric model, and the computed results are compared with existing experimental data. The model yields most of the qualitative trends observed in the experiments and helps to understanding the fundamental processes in HiPco carbon nanotube production.

Validation Studies↗

Liquid Hydrogen Tank Chill and No-Vent Fill Prediction using Computational Fluid Dynamics

Cryogenic tank chill and fill is an important cryogenic fluid management (CFM) technology that supports and enables many of NASA’s long-duration space missions. For no-vent fill, the receiver tank pressure remains below the supply tank pressure during the entire duration of the fill so that the tank does not require venting. This is especially advantageous for tank fill operations in low gravity where the position of the liquid is not always known and venting the tank may cause loss of propellant by venting liquid. In lieu of expensive tests conducted on-orbit, accurate computational models capable of predicting receiver tank pressure during cryogenic propellant tank fill may be used to reduce system and propellant mass as well as mission risk. However, these numerical models must be validated or anchored to test data. This study presents a computational fluid dynamics (CFD) model with conjugate heat transfer that is used to predict a liquid hydrogen tank chill and no-vent fill ground test conducted at Lewis Research Center (now Glenn Research Center) in 1991. The specific test case chosen for model validation implemented an upward-facing jet near the bottom of a cylindrical 34 liter tank. CFD predictions are compared to experimental measurements of tank pressure, fill level, fluid temperatures, and wall temperatures. The CFD results show reasonable agreement to the test data but overpredict the pressure collapse near the end of the fill despite the liquid jet penetrating the liquid-vapor interface. Several sensitivity studies are considered due to notable uncertainties in the experiment.

Computational Fluid Dynamics↗

Liquid Hydrogen Tank Chill and No-Vent Fill Prediction Using Computational Fluid Dynamics

Cryogenic tank chill and fill is an important cryogenic fluid management (CFM) technology that supports and enables many of NASA’s long-duration space missions. For no-vent fill, the receiver tank pressure remains below the supply tank pressure during the entire duration of the fill so that the tank does not require venting. This is especially advantageous for tank fill operations in low gravity where the position of the liquid is not always known and venting the tank may cause loss of propellant by venting liquid. In lieu of expensive tests conducted on-orbit, accurate computational models capable of predicting receiver tank pressure during cryogenic propellant tank fill may be used to reduce system and propellant mass as well as mission risk. However, these numerical models must be validated or anchored to test data. This study presents a computational fluid dynamics (CFD) model with conjugate heat transfer that is used to predict a liquid hydrogen tank chill and no-vent fill ground test conducted at Lewis Research Center (now Glenn Research Center) in 1991. The specific test case chosen for model validation implemented an upward-facing jet near the bottom of a cylindrical 34 liter tank. CFD predictions are compared to experimental measurements of tank pressure, fill level, fluid temperatures, and wall temperatures. The CFD results show reasonable agreement to the test data but overpredict the pressure collapse near the end of the fill despite the liquid jet penetrating the liquid-vapor interface. Several sensitivity studies are considered due to notable uncertainties in the experiment.

Computational Fluid Dynamics↗

Treatment of atomic and molecular line blanketing by opacity sampling

An opacity sampling (OS) technique for treating the radiative opacity of large numbers of atomic and molecular lines in cool stellar atmospheres is presented. Tests were conducted and results show that the structure of atmospheric models is accurately fixed by the use of 1000 frequency points, and 500 frequency points is often adequate. The effects of atomic and molecular lines are separately studied. A test model computed by using the OS method agrees very well with a model having identical atmospheric parameters computed by the giant line (opacity distribution function) method.

Johnson, H. R.↗

Fundamental Studies of Soiling and Cementation of PV Cover Glass Materials: Addressing Reliability with Advanced X-ray Scattering/Spectroscopy and First Principles Modeling (Final Technical Report)

Accumulation of soils and other particulate matter on the front cover glass of solar photovoltaic (PV) modules results in transmission losses that detrimentally affect the power output of PV installations. The conventional solution to this problem is manual abrasive scrubbing of modules, which entails significant water usage and manpower. To further combat this issue, there is a concerted effort within the PV industry to develop anti-soiling (AS) coatings to mitigate power losses due to soiling of PV modules, which can exceed 35% in some cases. However, relatively little is known about the fundamental physical and chemical mechanisms that enable anti-soiling behavior. In this project, a combination of advanced X-ray analysis tools and first principles computational modeling has employed to understand the physical and chemical interactions between environmental soils and PV cover glass materials. The specific objectives were: 1) investigate soiling interactions and cementation behavior of relevant PV materials, including bare glass, conventional antireflective (AR) coatings, and a commercial AS coating, using a library of representative particulate soils, and 2) utilize first principles computational spectroscopy modeling to interpret the experimental X-ray spectroscopy measurements and determine the detailed surface chemistry changes that occur on these surfaces in the presence of soiling and cementation.

14 SOLAR ENERGY↗

A molecular dynamics investigation of hydrostatic compression characteristics of mineral Jennite

This paper focuses on the study of mechanical behavior and deformation of mineral Jennite, under isothermal hydrostatic compression using Molecular Dynamics (MD) modeling. Atomistic structure of mineral Jennite is considered as a choice for representing calcium silicate hydrate (C-S-H), a key constituent in hydrated cement paste. The present work focuses and presents a molecular dynamics simulation approach to ascertain hydrostatic compression characteristics of mineral Jennite. The pressure–specific volume, and specific internal energy–specific volume relationships under isothermal hydrostatic compression conditions were determined. For the pressures ranging from 0.0001 GPa to 5 GPa, computational modeling results indicated that a linear relationship may be sufficient when describing the pressure–specific volume relationship. The results obtained in this study compared well with experimental and theoretical results recently published by other researchers. Additionally, a quadratic function was found to be appropriate to describe the specific energy–specific volume relationship, for the same pressure range used for studying the pressure–specific volume relationship. The pressure–specific volume, and specific internal energy-specific volume relationships reported in this paper are useful for further estimation of pressure–specific volume constitutive Hugoniot of the nanoscale mineral Jennite. Additionally, MD approach discussed and presented in this paper can be applied to understand hydrostatic compression behavior and deformation characteristics of other atomistic structures representing C-S-H. Further, the computational material modeling approach discussed in this paper provides an alternative methodology that can aid in the understanding of the deformation mechanisms and developing constitutive relationships from atomistic structures of materials.

36 MATERIALS SCIENCE↗

Magnetohydrodynamic modelling of interplanetary disturbances between the sun and earth

A time-dependent, nonplanar, two-dimensional magnetohydrodynamic computer model is used to simulate a series, separately examined, of solar flare-generated shock waves and their subsequent disturbances in interplanetary space between the sun and the earth's magnetosphere. The 'canonical' or ansatz series of shock waves include initial velocities near the sun over the range 500 to 3500 km/s. The ambient solar wind, through which they propagate, is taken to be a steady state homogeneous plasma (that is, independent of heliolongitude) with a representative set of plasma and magnetic field parameters. Complete sets of solar wind plasma and magnetic field parameters are presented and discussed. Particular attention is addressed to the MHD model's ability to address fundamental operational questions vis-a-vis the long-range forecasting of geomagnetic disturbances. These questions are: (1) will a disturbance (such as the present canonical series of solar flare shock waves) produce a magnetospheric and ionospheric disturbance, and, if so, (2) when will it start, (3) how severe will it be, and (4) how long will it last? The model's output is used to compute various solar wind indices of current interest as a demonstration of the model's potential for providing 'answers' to these questions.

Dryer, M.↗

A modeling study of the time-averaged electric currents in the vicinity of isolated thunderstorms

A thorough examination of the results of a time-dependent computer model of a dipole thunderstorm revealed that there are numerous similarities between the time-averaged electrical properties and the steady-state properties of an active thunderstorm. Thus, the electrical behavior of the atmosphere in the vicinity of a thunderstorm can be determined with a formulation similar to what was first described by Holzer and Saxon (1952). From the Maxwell continuity equation of electric current, a simple analytical equation was derived that expresses a thunderstorm's average current contribution to the global electric circuit in terms of the generator current within the thundercloud, the intracloud lightning current, the cloud-to-ground lightning current, the altitudes of the charge centers, and the conductivity profile of the atmosphere. This equation was found to be nearly as accurate as the more computationally expensive numerical model, even when it is applied to a thunderstorm with a reduced conductivity thundercloud, a time-varying generator current, a varying flash rate, and a changing lightning mix.

Driscoll, Kevin T.↗

LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies

Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications. Solidification cracking is one of the main limiting factors in LPBF processes, which occurs during the final stage of solidification. To investigate the effect of alloy composition on printability, this study focuses on this defect via a combination of computational modeling and experimental validation. To this end, solidification cracking susceptibility is calculated as Kou’s index and Scheil–Gulliver model, implemented in Thermo-Calc/2022a software. An innovative powder-free experimental method through laser remelting was conducted on bare NiTiHf ingots to validate the parameter impacts of the LPBF process. The result is the processability window with no cracking likelihood under diverse LPBF conditions, including laser power and scan speed. This comprehensive investigation enhances our understanding of the processability challenges and opportunities for NiTiHf HTSMAs in advanced engineering applications.

36 MATERIALS SCIENCE↗

Engine-Aftertreatment in Closed-Loop Modeling for Heavy Duty Truck Emissions Control

An engine-aftertreatment computational model was developed to support in-loop performance simulations of tailpipe emissions and fuel consumption associated with a range of heavy-duty (HD) truck drive cycles. For purposes of this study, the engine-out exhaust dynamics were simulated with a combination of steady-state engine maps and dynamic correction factors that accounted for recent engine operating history. The engine correction factors were approximated as dynamic first-order lags associated with the thermal inertia of the major engine components and the rate at which engine-out exhaust temperature and composition vary as combustion heat is absorbed or lost to the surroundings. The aftertreatment model included catalytic monolith components for diesel exhaust oxidation, particulate filtration, and selective catalytic reduction of nitrogen oxides (NOx) with urea. Both the engine and aftertreatment models have been calibrated with dynamometer measurements from a commercial 2010-certificated 15-L Cummins diesel engine. The fuel consumption engine map with the reduced data is attached in the appendix. Simulations with the combined engine and aftertreatment models above appear to reveal important trends among the fuel efficiency, emissions control, power demand for HD trucks under realistic drive cycle conditions. Thus, this type of computational simulation appears to have significant value in choosing among options for HD vehicle design and operation.

Gao, Zhiming↗

Diagnosing up-scattered deuterium–tritium fusion neutrons produced in burning plasmas at the National Ignition Facility (invited)

In the push to higher performance fusion plasmas, two critical quantities to diagnose are α-heat deposition that can improve and impurities mixed into the plasma that can limit performance. In high-density, highly collisional inertial confinement fusion burning plasmas, there is a significant probability that deuterium–tritium (DT) fusion products, 14.1 MeV neutrons and 3.5 MeV α-particles, will collide with and deposit energy onto (“up-scatter”) surrounding deuterium and tritium fuel ions. These up-scattered D and T ions can then undergo fusion while in-flight and produce an up-scattered neutron (15–30 MeV). These reaction-in-flight (RIF) neutrons can then be uniquely identified in the measured neutron energy spectrum. Further, the magnitude, shape, and relative size of this spectral feature can inform models of stopping-power in the DT plasma and hence is directly proportional to α-heat deposition. In addition, the RIF spectrum can be related to mix into the burning fuel, particularly relevant for high-Z shell and other emerging National Ignition Facility platforms. The neutron time-of-flight diagnostic upgrades needed to obtain this small signal, ~10 –5 times the primary DT neutron peak, will be discussed. Results from several gain > 1 implosions will be shown and compared to previous RIF spectra. Finally, comparisons of experimental data to a simplified computational model will be made.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Rational Enzyme Design for Controlled Functionalization of Acetylated Xylan for Cell-Free Polymer Biosynthesis

Xylan O-acetyltransferase 1 (XOAT1) is involved in O-acetylating the backbone of hemicellulose xylan. Recent structural analysis of XOAT1 showed two unequal lobes forming a cleft that is predicted to accommodate and position xylan acceptors into proximity with the catalytic triad. Here, we used docking and molecular dynamics simulations to investigate the optimal orientation of xylan in the binding cleft of XOAT1 and identify putative key residues (Gln445 and Arg444 on Minor lobe & Asn312, Met311 and Asp403 on Major lobe) involved in substrate interactions. Site-directed mutagenesis coupled with biochemical analyses revealed the major lobe of XOAT1 is important for xylan binding. Mutation of single key residues yielded XOAT1 variants with various enzymatic efficiencies that are applicable to one-pot synthesis of xylan polymers with different degrees of O-acetylation. Taken together, our results demonstrate the effectiveness of computational modeling in guiding enzyme engineering aimed at modulating xylan and redesigning plant cell walls.

93 SC - Biological and Environmental Research (BER↗

Application of Variance-Based Sensitivity Analysis to a Large System Dynamics Model

Variance-based sensitivity methods can provide insights into large computational models. We present a novel application of sensitivity analysis to the Biomass Scenario Model (BSM) a large and complex system dynamics model of the developing biofuels industry in the United States. We apply a two-stage sensitivity approach consisting of an initial sensitivity screening, followed by a variance decomposition approach. Identifying key system levers and quantifying their strength is not straightforward in complex system dynamics models that have numerous feedbacks and nonlinear results. Variance-based sensitivity analysis (VBSA) offers a systematic, global approach to assessing system dynamics models because it addresses nonlinear responses and interactive effects. Especially when a large model's size makes manual exploration of the input space difficult and time-consuming, the approach can help to provide a comprehensive understanding of interactions that drive model behaviors.

97 MATHEMATICS AND COMPUTING↗

Quantum sensing effect of electron tunneling in DQD/analyte complex

We investigate electron tunneling between quantum dots and molecules to propose a quantum sensor. This sensor consists of double quantum dots (DQD) with energy levels specifically tailored to mirror those of the target analyte. By analyzing the spectral distribution of electron localizations in the DQD system, we can delineate the analyte’s spectrum and deduce its composition by comparing it with a reference sample. To understand electron tunneling dynamics within the DQD/analyte complex, we performed three-dimensional computational modeling applying the effective potential approach to the InAs/GaAs heterostructure. In this modeling, we mimicked the analyte spectrum by utilizing a quantum well characterized by a quasi-discrete spectrum. Our calculations reveal the inherent potential of utilizing this method as a highly sensitive and selective sensor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗