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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Inducer Hydrodynamic Forces in a Cavitating Environment

Marshall Space Flight Center has developed and demonstrated a measurement device for sensing and resolving the hydrodynamic loads on fluid machinery. The device - a derivative of the six-component wind tunnel balance - senses the forces and moments on the rotating device through a weakened shaft section instrumented with a series of strain gauges. This rotating balance was designed to directly measure the steady and unsteady hydrodynamic loads on an inducer, thereby defining the amplitude and frequency content associated with operating in various cavitation modes. The rotating balance was calibrated statically using a dead-weight load system in order to generate the 6 x 12 calibration matrix later used to convert measured voltages to engineering units. Structural modeling suggested that the rotating assembly first bending mode would be significantly reduced with the balance s inclusion. This reduction in structural stiffness was later confirmed experimentally with a hammer-impact test. This effect, coupled with the relatively large damping associated with the rotating balance waterproofing material, limited the device s bandwidth to approximately 50 Hertz Other pre-test validations included sensing the test article rotating assembly built-in imbalance for two configurations and directly measuring the assembly mass and buoyancy while submerged under water. Both tests matched predictions and confirmed the device s sensitivity while stationary and rotating. The rotating balance was then demonstrated in a water test of a full-scale Space Shuttle Main Engine high-pressure liquid oxygen pump inducer. Experimental data was collected a scaled operating conditions at three flow coefficients across a range of cavitation numbers for the single inducer geometry and radial clearance. Two distinct cavitation modes were observed symmetric tip vortex cavitation and alternate-blade cavitation. Although previous experimental tests on the same inducer demonstrated two additional cavitation modes at lower inlet pressures, these conditions proved unreachable with the rotating balance installed due to the intense dynamic environment. The sensed radial load was less influenced by flow coefficient than by cavitation number or cavitation mode although the flow coefficient range was relatively narrow. Transition from symmetric tip vortex to alternate-blade cavitation corresponded to changes in both radial load magnitude and radial load orientation relative to the inducer. Sensed moments indicated that the effective load center moved downstream during this change in cavitation mode. An occurrence of "higher+rdex cavitation" was also detected in both the stationary pressures and the rotating balance data although the frequency of the phenomena was well above the reliable bandwidth of the rotating balance. In summary the experimental tests proved both the concept and device s capability despite the limitations and confirmed that hydrodynamically-induced forces and moments develop in response to the unbalanced pressure field, which is, in turn, a product of the cavitation environment.

Skelley, Stephen E.↗
NASA NTRSDate not supplied

SHIIVER Assemby Thermal Model Prediction for Transient Test Conditions

An integrated thermal model of the Structure Heat Intercept, Insulation, and Vibration Evaluation Rig (SHIIVER) was built in Thermal Desktop/Sinda-Fluint and used to predict thermal performance of the system with the technologies being tested from the eCryo project. The technologies tested include the vapor cooling of the structure using the boil-off and multilayer insulation (MLI) on the hydrogen tank. The thermal model is used to 1) understand system transient behaviors; 2) perform trade studies of different vapor-cooling designs; 3) define the test operations matrix, test procedures, and conditions; and 4) address thermal-related questions at different phases of SHIIVER project. Details of the thermal model are herein described, and results corresponding to the test operations are presented for four different configurations at different fill levels. The thermal performance of each configuration is predicted with the thermal model regarding the heat reduction and boil-off reduction by using vapor cooling and/or MLI on the structures attached to the hydrogen tank.

thermal modeling↗
NASA NTRS1990

Thermal-distortion analysis of a spacecraft box truss in geostationary orbit

The Mission to Planet Earth enlists the use of a geostationary platform to support Earth science monitoring instruments. The strongback for a proposed geostationary platform is a deployable box truss that supports two large diameter passive microwave radiometer (PMR) and several other science instruments. A study was performed to estimate the north-south and east-west pointing errors at the mounting locations of the two PMRs due to on-orbit thermal distortions of the main truss. The baseline configuration indicated that the east-west pointing error greatly exceeded the required limits. Primary origins of the pointing errors were identified, and methods for their reduction were discussed. Thermal performance enhancements to the truss structure were modeled and analyzed, including state-of-the-art surface coatings and insulation techniques. Comparisons of the thermal enhancements to the baseline were performed. Results demonstrated that using a thermal enclosure insulating technique reduced external heat fluxes, and distributed those heat fluxes more evenly throughout the structure, sufficiently reducing the pointing error to satisfy pointing accuracy requirements for the PMR's.

Cosgrove, Patrick A.↗
NASA NTRS1992

A finite element: Boundary integral method for electromagnetic scattering

A method that combines the finite element and boundary integral techniques for the numerical solution of electromagnetic scattering problems is presented. The finite element method is well known for requiring a low order storage and for its capability to model inhomogeneous structures. Of particular emphasis in this work is the reduction of the storage requirement by terminating the finite element mesh on a boundary in a fashion which renders the boundary integrals in convolutional form. The fast Fourier transform is then used to evaluate these integrals in a conjugate gradient solver, without a need to generate the actual matrix. This method has a marked advantage over traditional integral equation approaches with respect to the storage requirement of highly inhomogeneous structures. Rectangular, circular, and ogival mesh termination boundaries are examined for two-dimensional scattering. In the case of axially symmetric structures, the boundary integral matrix storage is reduced by exploiting matrix symmetries and solving the resulting system via the conjugate gradient method. In each case several results are presented for various scatterers aimed at validating the method and providing an assessment of its capabilities. Important in methods incorporating boundary integral equations is the issue of internal resonance. A method is implemented for their removal, and is shown to be effective in the two-dimensional and three-dimensional applications.

Collins, J. D.↗
NASA NTRS2021

Reduced El NiñO Variability in the Mid-Pliocene According to the Pliomip2 Ensemble

The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period during which atmospheric CO 2 levels were similar to recent historical values (∼400 ppm). Several proxy reconstructions for the mid-Pliocene show highly reduced zonal sea surface temperature (SST) gradients in the tropical Pacific Ocean, indicating an El Niño-like mean state. However, past modelling studies do not show these highly reduced gradients. Efforts to understand mid-Pliocene climate dynamics have led to the Pliocene Model Intercomparison Project (PlioMIP). Results from the first phase (PlioMIP1) showed clear El Niño variability (albeit significantly reduced) and did not show the greatly reduced time-mean zonal SST gradient suggested by some of the proxies. In this work, we study El Niño–Southern Oscillation (ENSO) variability in the PlioMIP2 ensemble, which consists of additional global coupled climate models and updated boundary conditions compared to PlioMIP1. We quantify ENSO amplitude, period, spatial structure and “flavour”, as well as the tropical Pacific annual mean state in mid-Pliocene and pre-industrial simulations. Results show a reduced ENSO amplitude in the model-ensemble mean (−24 %) with respect to the pre-industrial, with 15 out of 17 individual models showing such a reduction. Furthermore, the spectral power of this variability considerably decreases in the 3–4-year band. The spatial structure of the dominant empirical orthogonal function shows no particular change in the patterns of tropical Pacific variability in the model-ensemble mean, compared to the pre-industrial. Although the time-mean zonal SST gradient in the equatorial Pacific decreases for 14 out of 17 models (0.2 ∘C reduction in the ensemble mean), there does not seem to be a correlation with the decrease in ENSO amplitude. The models showing the most “El Niño-like” mean state changes show a similar ENSO amplitude to that in the pre-industrial reference, while models showing more “La Niña-like” mean state changes generally show a large reduction in ENSO variability. The PlioMIP2 results show a reasonable agreement with both time-mean proxies indicating a reduced zonal SST gradient and reconstructions indicating a reduced, or similar, ENSO variability.

mid-Pliocene warm period↗
DOE OSTI2015

A tunable amorphous p-type ternary oxide system: The highly mismatched alloy of copper tin oxide

The approach of combining two mismatched materials to form an amorphous alloy was used to synthesise ternary oxides of CuO and SnO{sub 2}. These materials were analysed across a range of compositions, and the electronic structure was modelled using density functional theory. In contrast to the gradual reduction in optical band gap, the films show a sharp reduction in both transparency and electrical resistivity with copper contents greater than 50%. Simulations indicate that this change is caused by a transition from a dominant Sn 5s to Cu 3d contribution to the upper valence band. A corresponding decrease in energetic disorder results in increased charge percolation pathways: a “compositional mobility edge.” Contributions from Cu(II) sub band-gap states are responsible for the reduction in optical transparency.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of NaCl on shape deformation of polymersomes

Polymersomes frequently appear in the literature as promising candidates for a wide range of applications from targeted drug delivery to nanoreactors. From a cell mimetic point of view, it is important to understand the size and shape changes of the vesicles in the physiological environment since that can influence the drug delivery mechanism. In this work we studied the structural features of polymersomes consisting of poly(ethylene glycol)–poly(dimethylsiloxane)–poly(ethylene glycol) at the nanoscopic length scale in the presence of NaCl, which is a very common molecule in the biotic aqueous environment. Here, we used dynamic light scattering (DLS), cryo-TEM, small angle neutron scattering (SANS) and small angle X-ray scattering (SAXS). We observed transformation of polymersomes from spherical to elongated vesicles at low salt concentration and into multivesicular structures at high salt concentration. Model fitting analysis of SANS data indicated a reduction of vesicle radius up to 47% and from the SAXS data we observed an increase in membrane thickness up to 8% and an increase of the PDMS hydrophobic segment up to 11% indicating stretching of the membrane due to osmotic imbalance. Also, from the increase in the interlamellar repeat distance up to 98% under high salt concentrations, we concluded that the shape and structural changes observed in the polymersomes are a combined result of osmotic pressure change and ion–membrane interactions.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Applicability of Loads Estimation Techniques Using Sparse Acceleration Sensor Data to Spacecraft Structural Health Monitoring

The use of structural health monitoring systems on spacecraft structures can play a crucial role in ensuring the safety, reliability, and longevity of the structure by gathering and analyzing onboard sensor data. Of specific importance is monitoring for excessive loading at critical interfaces as any off-nominal structural excitations experienced by spacecraft structures can cause early unpredicted high structural life consumption or damage. The availability and cost of flight-certified sensors along with the size of spacecraft structures and allowable payload mass drives the need for a method to estimate loads using sparsely-located sensors. Numerous approaches such as physics-based, statistical learning, and physics-enhanced statistical learning algorithms have gained popularity among structural prognostics applications. However, developing noise-robust prediction models to assess loads and structural life predictions from a sparse multi-sensor data acquisition system can be a challenging task. This paper discusses the evaluation of physics-based versus machine-learning algorithms for predicting loads and structural life at mission critical locations on the spacecraft structure using a finite element loads analysis with the application of simulated noise and noise reduction techniques. To estimate the loads from accelerations, the physics-based algorithm leverages a loads transformation matrix from a Craig-Bampton reduced finite element model. A System Equivalent Reduction Expansion Process (SEREP) and a pseudo-inverse approach are considered to expand from the onboard sensor degrees of freedom to the Craig-Bampton model degrees of freedom. The machine learning algorithm provides a data driven solution/mapping of the sensor accelerations to the loads at the mission critical locations using a high dimensionality analysis. Although these strategies produce comparable loads prediction without noise, the limitations of these strategies with incorporating simulated noise and noise reduction techniques with low signal to noise ratio signals are evaluated. The study demonstrates the immense potential of statistical learning algorithms for sparse structural prognostic models and enhancing signal denoising techniques. These findings also highlight the need for noise-resilient prognostic models and low-noise data acquisition systems onboard spacecraft structures.

Spacecraft Structural Health Monitoring↗
NASA NTRS2015

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strainbased method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2%, 0.28%, and 0.09%, respectively; and maximum slope errors in roll and pitch directions are 0.28% and -3.2%, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8% of the photogrammetry data and are accurate to within 2.2% in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction.

shape sensing↗
NASA NTRS2015

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strain-based method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2 percent, 0.28 percent, and 0.09 percent, respectively; and maximum slope errors in roll and pitch directions are 0.28 percent and -3.2 percent, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8 percent of the photogrammetry data and are accurate to within 2.2 percent in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction..

system equivalent reduction and expansion process↗
DOE OSTI2021

Constrained Block Nonlinear Neural Dynamical Models

Neural network modules conditioned by known priors can be effectively trained and combined to represent systems with nonlinear dynamics. This work explores a novel formulation for data-efficient learning of deep control-oriented nonlinear dynamical models by embedding local model structure and constraints. The proposed method consists of neural network blocks that represent input, state, and output dynamics with constraints placed on the network weights and system variables. For handling partially observable dynamical systems, we utilize a state observer neural network to estimate the states of the system's latent dynamics. We evaluate the performance of the proposed architecture and training methods on system identification tasks for three nonlinear systems: a continuous stirred tank reactor, a two tank interacting system, and an aerodynamics body. Models optimized with a few thousand system state observations accurately represent system dynamics in open loop simulation over thousands of time steps from a single set of initial conditions. Experimental results demonstrate an order of magnitude reduction in open-loop simulation mean squared error for our constrained, block-structured neural models when compared to traditional unstructured and unconstrained neural network models.

Skomski, Elliott↗
DOE OSTI2021

Correlating conductivity and Seebeck coefficient to doping within crystalline and amorphous domains in poly(3-(methoxyethoxyethoxy)thiophene)

Molecular doping of conjugated polymers (CPs) plays a vital role in optimizing organic electronic and energy applications. For the case of organic thermoelectrics, it is commonly believed that doping CPs with a strong dopant could result in higher conductivity (σ) and thus better power factor (PF). Herein, by investigating thermoelectric performance of a polar side-chain bearing CP, poly(3- (methoxyethoxyethoxy)thiophene) (P3MEET), vapor doped with fluorinatedderivative of tetracyanoquinodimethane FnTCNQ (n = 1, 2, 4), we show that using strong dopants can in fact have detrimental effects on the thermoelectric performance of CPs. Despite possessing higher electron affinity, doping P3MEET with F4TCNQ only results in a σ (27.0 S/cm) comparable to samples doped with other two weaker dopants F2TCNQ and F1TCNQ (26.4 and 20.1 S/cm). Interestingly, F4TCNQ-doped samples display a marked reduction in the Seebeck coefficient (α) compared to F1TCNQ- and F2TCNQ-doped samples from 42 to 13 μV/ K, leading to an undesirable suppression of the PF. Additionally, structural characterizations coupled with Kang-Snyder modeling of the α–σ relation show that the reduction of α in F4TCNQ-doped P3MEET samples originates from the generation of low mobility carrier within P3MEET's amorphous domain. Our results demonstrate that factors such as dopant distribution and doping efficiency within the crystalline and amorphous domains of CPs should play a crucial role in advancing rational design for organic thermoelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

AEOLUS: Advances in Experimental Design, Optimal Control, and Learning for Uncertain Complex Systems

Sustained advances in the mathematics of modeling and simulation have resulted in the capability today for routine simulation of a number of large scale complex DOE-relevant systems. As remarkable as this capability for solving the so-called forward problem is, it is typically only the first step-an inner loop within an outer loop that explores the simulation model's parameter space and decision space to characterize uncertainty in the model's predictions, learn unknown model parameters from data, design the most informative experiments, determine optimal control strategies, and create optimal designs. Broadly, what unifies all of these outer loop problems is that they are, in one form or another, optimization problems over parameter/control/design space that are constrained by complex uncertain models. To fully realize the power of scientific simulation as a basis for scientific discovery, technological innovation, and rational decision-making, it is imperative to move beyond simulation to tackle the outer loop of optimization for learning from data, experimental design, and control with complex uncertain models. When the models under consideration are large-scale and complex, and when the optimization variable and uncertain parameter spaces are high (or infinite) dimensional, this constitutes a grand challenge of the highest order, and is intractable with conventional methods. To overcome these challenges, the AEOLUS Center was established to develop a unified mathematical, computational, and statistical framework for (1) Learning predictive models from complex data via Bayesian inference and optimization, and (2) Optimizing experiments, processes, and designs using the resulting uncertain models. These problems are intractable with conventional methods, for several reasons: (1) The simulation problems that govern the inner loops of the optimization problems are expensive to execute (due to severe nonlinearity, heterogeneity, multiphysics/multiscale coupling); (2) The optimization variable and uncertain parameter spaces are high dimensional, often stemming from discretizations of infinite dimensional fields such as initial conditions, sources, or material properties. We argue that the key to overcoming these challenges is to develop new mathematical, computational, and statistical methods that exploit the structure of the Bayesian inference and optimization problems mediated by their underlying complex uncertain models. This structure includes the regularity, sparsity, geometry, low intrinsic dimensionality, and multifidelity nature of the maps from uncertain parameter/optimization variable spaces to the specific objectives targeted: Bayesian inference, optimal experimental design, and optimal control design. Black box methods developed as generic tools are incapable of exploiting this structure. To be successful, we must create, integrate, and cross-fertilize ideas across multiple areas of applied math--including approximation theory, Bayesian inference, data science, experimental design, information theory, machine learning, model reduction, optimal control theory, parallel algorithms, PDE-constrained optimization, randomized algorithms, stochastic optimization, and uncertainty quantification--all while exploiting the structure of the problems at hand. With this goal in mind, we have marshaled a team of leading authorities in these areas. While the methods we develop will be broadly applicable across a wide spectrum of DOE problems in which experiments inform models and the systems those models describe must be optimized under uncertainty, we have chosen a specific area, advanced manufacturing and materials, to drive our work. AMM is characterized by complex models across multiple scales, and is a rich source of challenging problems in inference, experimental design, and optimal control, requiring multifaceted and integrated advances in applied mathematics. As such, AMM serves as an excellent vehicle to motivate and demonstrate the advances in applied mathematics developed by our center.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

2017 publication guidelines for structural modelling of small-angle scattering data from biomolecules in solution: an update

In 2012, preliminary guidelines were published addressing sample quality, data acquisition and reduction, presentation of scattering data and validation, and modelling for biomolecular small-angle scattering (SAS) experiments. Biomolecular SAS has since continued to grow and authors have increasingly adopted the preliminary guidelines. In parallel, integrative/hybrid determination of biomolecular structures is a rapidly growing field that is expanding the scope of structural biology. For SAS to contribute maximally to this field, it is essential to ensure open access to the information required for evaluation of the quality of SAS samples and data, as well as the validity of SAS-based structural models. To this end, the preliminary guidelines for data presentation in a publication are reviewed and updated, and the deposition of data and associated models in a public archive is recommended. These guidelines and recommendations have been prepared in consultation with the members of the International Union of Crystallography (IUCr) Small-Angle Scattering and Journals Commissions, the Worldwide Protein Data Bank (wwPDB) Small-Angle Scattering Validation Task Force and additional experts in the field.

Biochemistry & Molecular Biology↗
NASA NTRS2012

Hybrid Wing-Body (HWB) Pressurized Fuselage Modeling, Analysis, and Design for Weight Reduction

This paper describes the interim progress for an in-house study that is directed toward innovative structural analysis and design of next-generation advanced aircraft concepts, such as the Hybrid Wing-Body (HWB) and the Advanced Mobility Concept-X flight vehicles, for structural weight reduction and associated performance enhancement. Unlike the conventional, skin-stringer-frame construction for a cylindrical fuselage, the box-type pressurized fuselage panels in the HWB undergo significant deformation of the outer aerodynamic surfaces, which must be minimized without significant structural weight penalty. Simple beam and orthotropic plate theory is first considered for sizing, analytical verification, and possible equivalent-plate analysis with appropriate simplification. By designing advanced composite stiffened-shell configurations, significant weight reduction may be possible compared with the sandwich and ribbed-shell structural concepts that have been studied previously. The study involves independent analysis of the advanced composite structural concepts that are presently being developed by The Boeing Company for pressurized HWB flight vehicles. High-fidelity parametric finite-element models of test coupons, panels, and multibay fuselage sections, were developed for conducting design studies and identifying critical areas of potential failure. Interim results are discussed to assess the overall weight/strength advantages.

Mukhopadhyay, Vivek↗
DOE OSTI2013

Density functional study of the structure, stability and oxygen reduction activity of ultrathin platinum nanowires

We used density functional theory to study the difference in the structure, stability and catalytic reactivity between ultrathin, 0.5–1.0 nm diameter, platinum nanotubes and nanowires. Model nanowires were formed by inserting an inner chain of platinum atoms in small diameter nanotubes. In this way more stable, non-hollow structures were formed. The difference in the electronic structure of platinum nanotubes and nanowires was examined by inspecting the density of surface states and band structure. Furthermore, reactivity toward the oxygen reduction reaction of platinum nanowires was assessed by studying the change in the chemisorption energies of oxygen, hydroxyl, and hydroperoxyl groups, induced by converting the nanotube models to nanowires. Both ultrathin platinum nanotubes and nanowires show distinct properties compared to bulk platinum. Single-wall nanotubes and platinum nanowires with diameters larger than 1 nm show promise for use as oxygen reduction catalysts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
NASA NTRS2024

Aeroelastic Stability Assessment Methodology and Application to Slat Noise Treatments on the High-Lift Common Research Model

This work supports a larger effort at NASA to reduce airframe noise and, thus, environmental noise around airports. The leading-edge slat of conventional high-lift systems is a prominent source of airframe noise, and two technologies were previously identified as promising for noise reduction without significant aerodynamic or weight penalty: the slat cove filler (SCF) and the slat gap filler (SGF). NASA fabricated a 10%-scale semispan aircraft model for wind tunnel testing based upon the High-Lift Common Research Model (CRM-HL). NASA embarked on a test campaign with the 10% CRM-HL to determine the noise reduction effectiveness and other performance metrics of 3D SCF and SGF treatments in flow conditions representative of flight. The highly flexible SCF and SGF treatments posed a risk to the model and aeroelastic instability would compromise research integrity, so aeroelastic stability assessment was required. This work briefly describes the 10% CRM-HL, design of the SCF and SGF treatments to the model, and supporting fluid structure interaction (FSI) research. Relations for static and dynamic aeroelastic similitude are then developed for convenience of reference, and simplifications are introduced of particular utility to the cases considered in this study. The similitude relations are employed to assess the stability of the treatments under wind tunnel flow conditions based upon known behaviors from the supporting research. It is shown that the treatments are safe for test under the anticipated wind tunnel flow conditions with significant margins/factors of safety. It is furthermore demonstrated that the SCF is more susceptible to aeroelastic instability than the SGF, which has implications for flight feasibility.

Similitude↗
DOE OSTI2023

Development of molecular cluster models to probe pyrite surface reactivity

Abstract The recent discovery that anaerobic methanogens can reductively dissolve pyrite and utilize dissolution products as a source of iron and sulfur to meet their biosynthetic demands for these elements prompted the development of atomic‐scale nanoparticle models, as maquettes of reactive surface sites, for describing the fundamental redox steps that take place at the mineral surface during reduction. The given report describes our computational approach for modeling n (FeS 2 ) nanoparticles originated from mineral bulk structure. These maquettes contain a comprehensive set of coordinatively unsaturated Fe (II) sites that are connected via a range of persulfide (S 2 2− ) ligation. In addition to the specific maquettes with n = 8, 18, and 32 FeS 2 units, we established guidelines for obtaining low‐energy structures by considering the pattern of ionic, covalent, and magnetic interactions among the metal and ligand sites. The developed models serve as computational nano‐reactors that can be used to describe the reductive dissolution mechanism of pyrite to better understand the reactive sites on the mineral, where microbial extracellular electron‐transfer reactions can occur.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗