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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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NASA NTRSDate not supplied

Advanced Materials for the Lunar Surface: Multiscale Computational Design of Refractory Alloys and Carbides

Emerging operational environments, such as the lunar surface, present novel challenges for NASA and drive the need for advanced materials in applications like fission surface power systems. To address these demands, computational materials science is rapidly evolving to augment or replace costly and hazardous empirical testing. Although materials selection at NASA remains predominantly experimentally driven, advanced simulation methodologies are being steadily integrated into the engineering lifecycle. This work details the application of multiscale simulation techniques—including first-principles calculations, CALPHAD, dislocation dynamics, and molecular dynamics—at NASA's Ames Research Center to evaluate advanced materials for extreme environments. First, we present contributions to the Space Nuclear Propulsion Project. Be-cause propellant channel coatings in nuclear thermal rockets must withstand high-pressure, high-temperature hydro-gen, optimizing these materials is critical. First-principles calculations were employed to establish a rigorous quantitative and qualitative understanding of the behavior of the refractory carbides ZrC, NbC, and their mixtures in high-enthalpy hydrogen environments. This necessitated the generation of high-fidelity thermodynamic models for both stoichiometric and carbon-depleted carbides, both with and without the presence of hydrogen. Furthermore, we highlight efforts under the Refractory Alloy Additive Manufacturing Build Optimization (RAAMBO) project, where existing and novel alloy compositions were assessed for additive manufacturing printability and subsequent performance in applications such as heat pipes and rocket nozzle extensions. This was accomplished through a comprehensive multiscale simulation framework that bridged the gap from the nanometer to the millimeter scale. Across both initiatives, rigorous validation against empirical data was prioritized. By systematically employing a verified and validated computational frame-work, we demonstrate how simulation effectively supports multidisciplinary engineering efforts, builds project-wide confidence, and drives critical materials development.

computational materials↗

NASA NTRSDate not supplied

First-Principles Investigation of Phase Transitions in RuNb, RuTa, and Ru-Nb-Ta Ultrahigh Temperature Shape Memory Alloys

Ultrahigh temperature shape memory alloys (UHT-SMAs) have transition temperatures above 600 C, and they have found applications for sensing and actuating devices in aerospace industry. Among very few such UHT-SMAs currently known are Ru-based alloys such as RuNb and RuTa, whose martensite structures and phase transitions are totally different from those of NiTi-based SMAs and were poorly understood. In this work, we carried out a systematical study of RuNb using first-principles total energy calculations and molecular dynamics (MD) simulations. The transition paths and mechanisms in cubic → tetragonal →monoclinic transitions are revealed. and the transition sequence and martensitic transition temperatures are determined (MTTs) by evaluating the Gibbs free energies using thermodynamic integration. The calculated MTTs are in very good agreement with the experimental data. We found that the monoclinic phase at the second transition has the 𝑃21/m symmetry instead of experimentally identified 𝑃2/m. Our calculations demonstrate that RuTa has very similar phase transitions to those of RuTa. Furthermore, we studied the Ru0.5Nb0.25Ta0.25 ternary. Our results can explain the measured significant drop of MTT (~ 200 C) in the second transition for Ru0.5Nb0.25Ta0.25 compared with those of RuNb and RuTa, while in the first transition its MTT is between MTTs of RuNb and RuTa. The insights gained by this study and the verified ab initio methods for accurate MTT calculations can be applied to fast screen and quantitatively design novel UHT-SMAs having similar properties with desirable MTTs and much reduced cost.

Zhigang Wu↗

NASA NTRSDate not supplied

Predicting Melt Properties Using Atomistic Simulations With A Highly Accurate Physically Informed Neural Network Interatomic Potential

The use of a recently developed machine learning (ML) interatomic potential for molecular dynamics simulations of aluminum melt properties will be presented. Such properties are critical for process modeling in additive manufacturing, including the melt pool size, solidification, and formation of solidification microstructures. Direct first-principles modeling of these processes is computationally prohibitive whereas simulations employing ML potentials combine the high accuracy of quantum-mechanical methods with high computational speeds. The physically-informed neural network (PINN) method used herein, integrates a high-dimensional regression implemented by an artificial neural network with a physics-based bond-order interatomic potential. PINN potentials can accurately reproduce many properties of aluminum in both crystalline-solid and liquid phases. We examine the accuracy of a PINN Al potential in predicting the density, self-diffusivity, viscosity, and the tension of the liquid surface and liquid-solid interfaces. Comparison with experimental data and ab initio molecular dynamics calculations shows very good agreement for all properties tested.

molecular dynamics↗

NASA NTRS2011

First Principles Based Reactive Atomistic Simulations to Understand the Effects of Molecular Hypervelocity Impact on Cassini's Ion and Neutral Mass Spectrometer

We report here on the predicted impact of species such as ice-water, CO2, CH4, and NH3, on oxidized titanium, as well as HC species on diamond surfaces. These simulations provide the dynamics of product distributions during and after a hypervelocity impact event, ionization fractions, and dissociation probabilities for the various species of interest as a function of impact velocity (energy). We are using these results to determine the relevance of the fragmentation process to Cassini INMS results, and to quantify its effects on the observed spectra.

hypervelocity collisions↗

NASA NTRSDate not supplied

ICME for NASA Aerospace Applications: Batteries for Electric Aviation

NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.

John Lawson↗

NASA NTRS2018

ALMA Spectral Line and Imaging Survey of a Low and a High Mass-Loss Rate AGB Star Between 335 and 362 GHz

Context. Low and intermediate mass stars are known to power strong stellar winds when evolving through the asymptotic giant branch (AGB) phase. Initial mass, luminosity, temperature, and composition determine the pulsation characteristics of the star and the dust species formed in the pulsating photospheric layers. Radiation pressure on these grains triggers the onset of a stellar wind. However, as of today, we still cannot predict the wind mass-loss rates and wind velocities from first principles neither do we know which species are the first to condense in the upper atmospheric regions. Aims. We aim to characterise the dominant physical, dynamical, and chemical processes in the inner wind region of two archetypical oxygen-rich (C/O<1) AGB stars, that is, the low mass-loss rate AGB star R Dor (M~ 1x10(exp 7) M☉/yr) and the high mass-loss rate AGB star IK Tau (M~5x10(exp 6) M☉/yr). The purpose of this study is to observe the key molecular species contributing to the formation of dust grains and to cross-link the observed line brightnesses of several species to the global and local properties of the star and its wind. Methods. A spectral line and imaging survey of IK Tau and R Dor was made with ALMA between 335 and 362 GHz (band 7) at a spatial resolution of ~150 mas, which corresponds to the locus of the main dust formation region of both targets. Results. Some two hundred spectral features from 15 molecules (and their isotopologues) were observed, including rotational lines in both the ground and vibrationally excited states (up to v=5 for SiO). Detected species include the gaseous precursors of dust grains such as SiO, AlO, AlOH, TiO, and TiO2.We present a spectral atlas for both stars and the parameters of all detected spectral features. A clear dichotomy for the sulphur chemistry is seen: while CS, SiS, SO, and SO2 are abundantly present in IK Tau, only SO and SO2 are detected in R Dor. Also other species such as NaCl, NS, AlO, and AlOH display a completely different behaviour. From some selected species, the minor isotopologues can be used to assess the isotopic ratios. The channel maps of many species prove that both large and small-scale inhomogeneities persist in the inner wind of both stars in the form of blobs, arcs, and/or a disk. The high sensitivity of ALMA allows us to spot the impact of these correlated density structures in the spectral line profiles. The spectral lines often display a half width at zero intensity much larger than expected from the terminal velocity, v1, previously derived for both objects (36 km/s versus v(∞)~17.7 km/s for IK Tau and 23 km/s versus v(∞)~5.5 km/s for R Dor). Both a more complex 3D morphology and a more forceful wind acceleration of the (underlying) isotropic wind can explain this trend. The formation of fractal grains in the region beyond _400 mas can potentially account for the latter scenario. From the continuum map, we deduce a dust mass of ~3.7 x 10(exp 7) M☉ and ~2 x 10(ex0 8) M☉ for IK Tau and R Dor, respectively. Conclusions. The observations presented here provide important constraints on the properties of these two oxygen-dominated AGB stellar winds. In particular, the ALMA data prove that both the dynamical and chemical properties are vastly different for this high mass-loss rate (IK Tau) and low mass-loss rate (R Dor) star.

Stars: AGB and post-AGB, Stars: mass loss, Stars: ↗

NASA NTRS2018

ALMA Spectral Line and Imaging Survey of a Low and a High Mass-Loss Rate AGB Star Between 335 and 362 GHz

Context. Low and intermediate mass stars are known to power strong stellar winds when evolving through the asymptotic giant branch (AGB) phase. Initial mass, luminosity, temperature, and composition determine the pulsation characteristics of the star and the dust species formed in the pulsating photospheric layers. Radiation pressure on these grains triggers the onset of a stellar wind. However, as of today, we still cannot predict the wind mass-loss rates and wind velocities from first principles neither do we know which species are the first to condense in the upper atmospheric regions. Aims. We aim to characterise the dominant physical, dynamical, and chemical processes in the inner wind region of two archetypical oxygen-rich (C/O < 1) AGB stars, that is, the low mass-loss rate AGB star R Dor (M’ ∼ 1 × 10(exp −7) M/yr) and the high mass-loss rate AGB star IK Tau (M’ ∼ 5 × 10(exp −6) M/yr). The purpose of this study is to observe the key molecular species contributing to the formation of dust grains and to cross-link the observed line brightnesses of several species to the global and local properties of the star and its wind. Methods. A spectral line and imaging survey of IK Tau and R Dor was made with ALMA between 335 and 362 GHz (band 7) at a spatial resolution of ∼150 mas, which corresponds to the locus of the main dust formation region of both targets. Results. Some two hundred spectral features from 15 molecules (and their isotopologues) were observed, including rotational lines in both the ground and vibrationally excited states (up to v = 5 for SiO). Detected species include the gaseous precursors of dust grains such as SiO, AlO, AlOH, TiO, and TiO2. We present a spectral atlas for both stars and the parameters of all detected spectral features. A clear dichotomy for the sulphur chemistry is seen: while CS, SiS, SO, and SO2 are abundantly present in IK Tau, only SO and SO2 are detected in R Dor. Also other species such as NaCl, NS, AlO, and AlOH display a completely different behaviour. From some selected species, the minor isotopologues can be used to assess the isotopic ratios. The channel maps of many species prove that both large and small-scale inhomogeneities persist in the inner wind of both stars in the form of blobs, arcs, and/or a disk. The high sensitivity of ALMA allows us to spot the impact of these correlated density structures in the spectral line profiles. The spectral lines often display a half width at zero intensity much larger than expected from the terminal velocity, v∞, previously derived for both objects (36 km/s versus v(∞) ∼ 17.7 km/s for IK Tau and 23 km/s versus v(∞) ∼ 5.5 km/s for R Dor). Both a more complex 3D morphology and a more forceful wind acceleration of the (underlying) isotropic wind can explain this trend. The formation of fractal grains in the region beyond ∼400 mas can potentially account for the latter scenario. From the continuum map, we deduce a dust mass of ∼3.7 × 10(exp −7) Mand ∼2 × 10(exp −8) M for IK Tau and R Dor, respectively. Conclusions. The observations presented here provide important constraints on the properties of these two oxygen-dominated AGB stellar winds. In particular, the ALMA data prove that both the dynamical and chemical properties are vastly different for this high mass-loss rate (IK Tau) and low mass-loss rate (R Dor) star.

L. Decin↗

NASA NTRS2006

Granular Contact Forces: Proof of "Self-Ergodicity" by Generalizing Boltzmann's Stosszahlansatz and H Theorem

Ergodicity is proved for granular contact forces. To obtain this proof from first principles, this paper generalizes Boltzmann's stosszahlansatz (molecular chaos) so that it maintains the necessary correlations and symmetries of granular packing ensembles. Then it formally counts granular contact force states and thereby defines the proper analog of Boltzmann's H functional. This functional is used to prove that (essentially) all static granular packings must exist at maximum entropy with respect to their contact forces. Therefore, the propagation of granular contact forces through a packing is a truly ergodic process in the Boltzmannian sense, or better, it is self-ergodic. Self-ergodicity refers to the non-dynamic, internal relationships that exist between the layer-by-layer and column-by-column subspaces contained within the phase space locus of any particular granular packing microstate. The generalized H Theorem also produces a recursion equation that may be solved numerically to obtain the density of single particle states and hence the distribution of granular contact forces corresponding to the condition of self-ergodicity. The predictions of the theory are overwhelmingly validated by comparison to empirical data from discrete element modeling.

Metzger, Philip T.↗

NASA NTRS1997

Peptide Folding and Translocation Across the Water-Membrane Interface

The ability of small peptides to organize at aqueous interfaces was examined by performing a series of large-scale, molecular dynamics computer simulations of several peptides composed of two amino acids, nonpolar leucine (L) and polar glutamine (Q). The peptides differed in size and sequence of the amino acids. Studies on dipeptides LL, LQ, QL and QQ were extended to two heptamers, LQQLLQL and LQLQLQL, designed to maximize interfacial stability of an alpha-helix and a beta-strand, respectively, by exposing polar side chains to water and nonpolar side chains to a nonpolar phase. Finally, a transition of an undecamer, composed entirely of leucine residues, from a disordered structure in water to an alpha-helix in a nonpolar phase representing the interior of the membrane was investigated. Complete folding of a peptide in solution was accomplished for the first time in computer simulations. The simulations revealed several basic principles governing the sequence-dependent organization of peptides at interfaces. Short peptides tend to accumulate at interfaces and acquire ordered structures, providing that they have a proper sequence of polar and nonpolar amino acids. The dominant factor determining the interfacial structure of peptides is the hydrophobic effect, which is manifested at aqueous interfaces as a tendency for polar and nonpolar groups of the solute to segregate into the aqueous and nonpolar phases, respectively. If peptides consist of nonpolar residue's only, they become inserted into the nonpolar phase. As demonstrated by the example of the leucine undecamer, such peptides fold into an alpha-helix as they partition into the nonpolar medium. The folding proceeds through an intermediate, called 3-10-helix, which remains in equilibrium with the alpha-helix. Once in the nonpolar environment, the peptides can readily change their orientation with respect to the interface from parallel to perpendicular, especially in response to local electric fields. The ability of nonpolar peptides to modify both the structure and orientation with respect to the interface from parallel to perpendicular, especially in response to local electric fields. The ability of nonpolar peptides to modify both the structure and orientation with changing external conditions may have provided a simple mechanism of transmitting signals from the environment to the interior of a cell.

Pohorille, Andrew↗

NASA NTRS2001

Optimized suspension culture: the rotating-wall vessel

Suspension culture remains a popular modality, which manipulates mechanical culture conditions to maintain the specialized features of cultured cells. The rotating-wall vessel is a suspension culture vessel optimized to produce laminar flow and minimize the mechanical stresses on cell aggregates in culture. This review summarizes the engineering principles, which allow optimal suspension culture conditions to be established, and the boundary conditions, which limit this process. We suggest that to minimize mechanical damage and optimize differentiation of cultured cells, suspension culture should be performed in a solid-body rotation Couette-flow, zero-headspace culture vessel such as the rotating-wall vessel. This provides fluid dynamic operating principles characterized by 1) solid body rotation about a horizontal axis, characterized by colocalization of cells and aggregates of different sedimentation rates, optimally reduced fluid shear and turbulence, and three-dimensional spatial freedom; and 2) oxygenation by diffusion. Optimization of suspension culture is achieved by applying three tradeoffs. First, terminal velocity should be minimized by choosing microcarrier beads and culture media as close in density as possible. Next, rotation in the rotating-wall vessel induces both Coriolis and centrifugal forces, directly dependent on terminal velocity and minimized as terminal velocity is minimized. Last, mass transport of nutrients to a cell in suspension culture depends on both terminal velocity and diffusion of nutrients. In the transduction of mechanical culture conditions into cellular effects, several lines of evidence support a role for multiple molecular mechanisms. These include effects of shear stress, changes in cell cycle and cell death pathways, and upstream regulation of secondary messengers such as protein kinase C. The discipline of suspension culture needs a systematic analysis of the relationship between mechanical culture conditions and biological effects, emphasizing cellular processes important for the industrial production of biological pharmaceuticals and devices.

Non-NASA Center↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods. REFERENCES [1] Open science in space. Nature Medicine, 2021. 27(9): p. 1485-1485. [2] Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. [3] Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5. [4] Whetzel, P.L., et al., BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res, 2011. 39(Web Server issue): p. W541-5.

informatics↗

NASA NTRSDate not supplied

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗

NASA NTRS2021

Recent Advancements in Modeling and Simulation of Entry Systems at NASA

This paper describes recent development of modeling and simulation technologies for entry systems in support of NASA’s exploration missions. Mission-tailored research and development in modeling of entry systems occurs across the Agency (e.g., within the Orion and Mars 2020 Programs), however the aim of this paper is to discuss the broad, cross-mission research conducted by NASA’s Entry Systems Modeling (ESM) Project, which serves as the Agency’s only concerted effort toward advancing entry systems across a range of technical disciplines. Technology development in ESM is organized and prioritized from a system-level perspective, resulting in four broad technical areas of investment: (1) Predictive material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. Investments in thermal protection material modeling are geared toward high-fidelity, predictive models capable of handling complex structures, with an eye toward optimizing design performance and quantifying thermal protection system reliability. New computational tools have been developed to characterize material properties and behavior at the microstructural level, and experimental techniques (molecular beam scattering, micro-computed tomography, among others) have been developed to measure material kinetics, morphology, and other parameters needed to inform and validate detailed simulations. Advancements have also been made in macrostructural simulation capability to enable 3-D system-scale calculations of material response with complex topological features, including differential recession of tile gaps. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. Capacity and capability of the NASA Ames Electric Arc Shock Tube (EAST) have been expanded in recent years and analysis of resulting data has led to several improvements in kinetic models, while simultaneously reducing uncertainties associated with radiative heat transfer predictions. First-principles calculations of fundamental kinetic, thermodynamic, and transport data, along with state-specificmodels for non-equilibrium flow regimes, have also yielded new insights and have the potential to vastly improve model fidelity. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate entry environments at Mars during dust storms; Studies of roughness-induced heating augmentation relevant to tiled and woven thermal protection systems; and Advanced numerical methods to optimize computational analyses for desired accuracy versus cost. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent. With precision landing requirements driven by Mars human exploration goals, recent efforts have yielded 6-DOF models of multi-axis control with propulsive descent of both inflatable and rigid ellipsled-like architectures. Results for both configurations have demonstrated the ability to land within the 50-meter precision requirement demanded by Mars human exploration missions, while also reducing propellant requirements by enabling more efficient control through entry and descent. Ongoing research in GN&C is developing mechanical specifications for the systems and establishing engineering feasibility.

aerothermodynamics↗

NASA NTRS2019

Recent Advancements in Modeling and Simulation of Entry Systems at NASA

This paper describes recent development of modeling and simulation technologies for entry systems in support of NASA's exploration missions. Mission-tailored research and development in modeling of entry systems occurs across the Agency (e.g., within the Orion and Mars 2020 Programs), however the aim of this paper is to discuss the broad, cross-mission research conducted by NASA's Entry Systems Modeling (ESM) Project, which serves as the Agency's only concerted effort toward advancing entry systems across a range of technical disciplines. Technology development in ESM is organized and prioritized from a system-level perspective, resulting in four broad technical areas of investment: (1) Predictive material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. Investments in thermal protection material modeling are geared toward high-fidelity, predictive models capable of handling complex structures, with an eye toward optimizing design performance and quantifying thermal protection system reliability. New computational tools have been developed to characterize material properties and behavior at the microstructural level, and experimental techniques (molecular beam scattering, micro-computed tomography, among others) have been developed to measure material kinetics, morphology, and other parameters needed to inform and validate detailed simulations. Advancements have also been made in macrostructural simulation capability to enable 3-D system-scale calculations of material response with complex topological features, including differential recession of tile gaps. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. Capacity and capability of the NASA Ames Electric Arc Shock Tube (EAST) have been expanded in recent years and analysis of resulting data has led to several improvements in kinetic models, while simultaneously reducing uncertainties associated with radiative heat transfer predictions. First-principles calculations of fundamental kinetic, thermodynamic, and transport data, along with state-specific models for non-equilibrium flow regimes, have also yielded new insights and have the potential to vastly improve model fidelity. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate entry environments at Mars during dust storms; Studies of roughness-induced heating augmentation relevant to tiled and woven thermal protection systems; and Advanced numerical methods to optimize computational analyses for desired accuracy versus cost. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent. With precision landing requirements driven by Mars human exploration goals, recent efforts have yielded 6-DOF models of multi-axis control with propulsive descent of both inflatable and rigid ellipsled-like architectures.

Barnhardt, Michael D.↗

NASA NTRS2010

Interactions of Ku70/80 with Double-Strand DNA: Energetic, Dynamics, and Functional Implications

Space radiation is a proficient inducer of DNA damage leading to mutation, aberrant cell signaling, and cancer formation. Ku is among the first responding proteins in nucleus to recognize and bind the DNA double strand breaks (DSBs) whenever they are introduced. Once loaded Ku works as a scaffold to recruit other repair factors of non-homologous end joining and facilitates the following repair processes. The crystallographic study of the Ku70/80 heterodimer indicate the core structure of this protein shows virtually no conformational change after binding with DNA. To investigate the dynamical features as well as the energetic characteristics of Ku-DNA binding, we conduct multi-nanosecond molecular dynamics simulations of a modeled Ku70/80 structure and several complexes with two 24-bp DNA duplexes. Free energy calculations show significant energy differences between the complexes with Ku bound at DSBs and those with Ku associated at an internal site of a chromosome. The results also reveal detailed interactions between different nucleotides and the amino acids along the DNA-binding cradle of Ku, indicating subtle binding preference of Ku at specific DNA sequences. The covariance matrix analyses along the trajectories demonstrate the protein is stimulated to undergo correlated motions of different domains once bound to DNA ends. Additionally, principle component analyses identify these low frequency collective motions suitable for binding with and translocation along duplex DNA. It is proposed that the modification of dynamical properties of Ku upon binding with DSBs may provide a signal for the further recruitment of other repair factors such as DNA-PKcs, XLF, and XRCC4.

Hu, Shaowen↗

NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NASA NTRS2015

Free-Energy Calculations. A Mathematical Perspective

Ion channels are pore-forming assemblies of transmembrane proteins that mediate and regulate ion transport through cell walls. They are ubiquitous to all life forms. In humans and other higher organisms they play the central role in conducting nerve impulses. They are also essential to cardiac processes, muscle contraction and epithelial transport. Ion channels from lower organisms can act as toxins or antimicrobial agents, and in a number of cases are involved in infectious diseases. Because of their important and diverse biological functions they are frequent targets of drug action. Also, simple natural or synthetic channels find numerous applications in biotechnology. For these reasons, studies of ion channels are at the forefront of biophysics, structural biology and cellular biology. In the last decade, the increased availability of X-ray structures has greatly advanced our understanding of ion channels. However, their mechanism of action remains elusive. This is because, in order to assist controlled ion transport, ion channels are dynamic by nature, but X-ray crystallography captures the channel in a single, sometimes non-native state. To explain how ion channels work, X-ray structures have to be supplemented with dynamic information. In principle, molecular dynamics (MD) simulations can aid in providing this information, as this is precisely what MD has been designed to do. However, MD simulations suffer from their own problems, such as inability to access sufficiently long time scales or limited accuracy of force fields. To assess the reliability of MD simulations it is only natural to turn to the main function of channels - conducting ions - and compare calculated ionic conductance with electrophysiological data, mainly single channel recordings, obtained under similar conditions. If this comparison is satisfactory it would greatly increase our confidence that both the structures and our computational methodologies are sufficiently accurate. Channel conductance, defined as the ratio of ionic current through the channel to applied voltage, can be calculated in MD simulations by way of applying an external electric field to the system and counting the number of ions that traverse the channel per unit time. If the current is small, a voltage significantly higher than the experimental one needs to be applied to collect sufficient statistics of ion crossing events. Then, the calculated conductance has to be extrapolated to the experimental voltage using procedures of unknown accuracy. Instead, we propose an alternative approach that applies if ion transport through channels can be described with sufficient accuracy by the one-dimensional diffusion equation in the potential given by the free energy profile and applied voltage. Then, it is possible to test the assumptions of the equation, recover the full voltage/current dependence, determine the reliability of the calculated conductance and reconstruct the underlying (equilibrium) free energy profile, all from MD simulations at a single voltage. We will present the underlying theory, model calculations that test this theory and simulations on ion conductance through a channel that has been extensively studied experimentally. To our knowledge this is the first case in which the complete, experimentally measured dependence of the current on applied voltage has been reconstructed from MD simulations.

free energy↗

NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

knowledge↗