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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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DOE OSTI2022

Materials Design using an Active Subspace-based Batch Bayesian Optimization Approach

Integrated computational materials engineering (ICME) calls for integrating simulation tools and/or experiments to develop new materials and materials systems. However, implementation of ICME approaches is challenging mainly due to the considerable computational expense of such frameworks and large dimensionality of the design space. Addressing these challenges is thus critical to the success of ICME initiatives. We present here a specific Bayesian optimization framework designed to address these two challenges. In particular, we propose an active subspace batch Bayesian optimization framework. The framework makes use of dimension reduction via the active subspace method and makes use of the ability to query in parallel via the batch Bayesian optimization approach. Here, the integration of these techniques leads to significant efficiency improvements while maintaining accuracy.

36 MATERIALS SCIENCE↗

DOE OSTI2025

An evaluation of multi-fidelity methods for quantifying uncertainty in projections of ice-sheet mass change

Abstract. This study investigated the computational benefits of using multi-fidelity statistical estimation (MFSE) algorithms to quantify uncertainty in the mass change of Humboldt Glacier, Greenland, between 2007 and 2100 using a single climate change scenario. The goal of this study was to determine whether MFSE can use multiple models of varying cost and accuracy to reduce the computational cost of estimating the mean and variance of the projected mass change of a glacier. The problem size and complexity were chosen to reflect the challenges posed by future continental-scale studies while still facilitating a computationally feasible investigation of MFSE methods. When quantifying uncertainty introduced by a high-dimensional parameterization of the basal friction field, MFSE was able to reduce the mean-squared error in the estimates of the statistics by well over an order of magnitude when compared to a single-fidelity approach that only used the highest-fidelity model. This significant reduction in computational cost was achieved despite the low-fidelity models used being incapable of capturing the local features of the ice-flow fields predicted by the high-fidelity model. The MFSE algorithms were able to effectively leverage the high correlation between each model's predictions of mass change, which all responded similarly to perturbations in the model inputs. Consequently, our results suggest that MFSE could be highly useful for reducing the cost of computing continental-scale probabilistic projections of sea-level rise due to ice-sheet mass change.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

The effect of interference on delta modulation encoded video signals

The results of a study on the use of the delta modulator as a digital encoder of television signals are presented. The computer simulation was studied of different delta modulators in order to find a satisfactory delta modulator. After finding a suitable delta modulator algorithm via computer simulation, the results are analyzed and then implemented in hardware to study the ability to encode real time motion pictures from an NTSC format television camera. The effects were investigated of channel errors on the delta modulated video signal and several error correction algorithms were tested via computer simulation. A very high speed delta modulator was built (out of ECL logic), incorporating the most promising of the correction schemes, so that it could be tested on real time motion pictures. The final area of investigation concerned itself with finding delta modulators which could achieve significant bandwidth reduction without regard to complexity or speed. The first such scheme to be investigated was a real time frame to frame encoding scheme which required the assembly of fourteen, 131,000 bit long shift registers as well as a high speed delta modulator. The other schemes involved two dimensional delta modulator algorithms.

Schilling, D. L.↗

NASA NTRS1986

Assessment of a parabolic analysis for axisymmetric internal flows in rocket and turbomachinery ducts

The flow paths in gas turbine passages encompass a wide range of flow properties such as Reynolds number and Mach number as well as many other variable flow conditions such as swirl, free-stream turbulence, and laminar/turbulent transition. An existing computer program, the Axisymmetric Diffuser Duct (ADD) code, which calculates compressible, turbulent, swirling flow through axisymmetric ducts has been modified to include the effects of free-stream turbulence and laminar/turbulent transition. The program has been evaluated on a matrix of test cases to determine its accuracy, robustness, and limits of applicability. This improved version of the ADD code calculates solutions which compare well with available data and can now be applied to a wider range of problems than previously possible. In addition a concept called local enhancement was developed and tested on a simple two-dimensional geometry in order to demonstrate a method to reduce computer time. In this concept the pressure distribution is calculated on a coarse grid using the ADD code and the viscous layer is locally enhanced using a boundary layer analysis. By applying this concept, an order of magnitude reduction in computer time was possible without any loss in accuracy.

Power, G. D.↗

NASA NTRS1990

Flight-measured streamwise disturbance instabilities in laminar flow

NASA is presently conducting laminar-flow flight research to explore the limits of practical applications of laminar-flow drag reduction technology. An important aspect of this research involves studies of the dominant instability or instabilities responsible for initiating the transition process from laminar to turbulent flow. Recent subsonic flight experiments using an instrumented wing glove on a Lear 28/29 airplane measured the growth of the two-dimensional, viscous Tollmien-Schlichting (T-S) instability. The gloved wing section incorporated closely-spaced, flush-mounted, streamwise-located instrumentation for measuring the instability frequencies, surface temperatures, and pressure distributions. Flight conditions of the experiment includeed Mach numbers from 0.70 to 0.79 and chord Reynolds numbers from 10 to 20 million. An onboard engineer's station allowed for real-time analysis of the instability frequency data. In addition to a sample of results on the streamwise growth of instabilities, details of the glove and sensor installation and the onboard real-time data analysis system are given.

Lee, Cynthia C.↗

NASA NTRS1991

Mach number validation of a new zonal CFD method (ZAP2D) for airfoil simulations

A closed-loop overlapped velocity coupling procedure has been utilized to combine a two-dimensional potential-flow panel code and a Navier-Stokes code. The fully coupled two-zone code (ZAP2D) has been used to compute the flow past a NACA 0012 airfoil at Mach numbers ranging from 0.3 to 0.84 near the two-dimensional airfoil C(lmax) point for a Reynolds number of 3 million. For these cases, the grid domain size can be reduced to 3 chord lengths with less than 3-percent loss in accuracy for freestream Mach numbers through 0.8. Earlier validation work with ZAP2D has demonstrated a reduction in the required Navier-Stokes computation time by a factor of 4 for subsonic Mach numbers. For this more challenging condition of high lift and Mach number, the saving in CPU time is reduced to a factor of 2.

Strash, Daniel J.↗

NASA NTRSDate not supplied

Ab initio ground states of strongly-correlated materials on quantum computers

The accurate first-principles description of strongly-correlated materials is an important and challenging problem in condensed matter physics. Ab initio downfolding has emerged as a way of deriving accurate many-body Hamiltonians including strong correlations, representing a subspace of interest of a material, using density functional theory calculations as a starting point. However, the solution of these material-specific models can scale exponentially on classical computers, constituting a challenge. Here we propose that utilizing quantum computers for obtaining the properties of downfolded Hamiltonians yields an accurate description of the ground state properties of strongly-correlated systems, while circumventing the exponential scaling problem. We benchmark the solution of Hubbard-like models obtained through downfolding by utilizing a classical tensor network implementation of variational quantum eigensolvers (VQE), and we reveal a strategy for driving the optimization through a hybrid minimization of the energy and maximization of the overlap with an approximate solution obtained through low-cost computational methods. This results in a reduction of the energy error by orders of magnitude compared to conventional VQE approaches, and allows us to reproduce long-range correlations for the first time. We demonstrate our first-principles approach for diverse strongly-correlated materials, correctly predicting the antiferromagnetic state of one-dimensional cuprate Ca 2 CuO 3 , the excitonic ground state of monolayer WTe2, and the charge-ordered state of correlated metal SrVO 3 . Our efficient computational implementation allows us to simulate large systems with up to 54 qubits and encompassing up to four correlated bands, which is indicative of the complexity that our framework can address.

Antonios M Alvertis↗

DOE OSTI2013

Novel Hybrid Monte Carlo/Deterministic Technique for Shutdown Dose Rate Analyses of Fusion Energy Systems

The rigorous 2-step (R2S) method uses three-dimensional Monte Carlo transport simulations to calculate the shutdown dose rate (SDDR) in fusion reactors. Accurate full-scale R2S calculations are impractical in fusion reactors because they require calculating space- and energy-dependent neutron fluxes everywhere inside the reactor. The use of global Monte Carlo variance reduction techniques was suggested for accelerating the neutron transport calculation of the R2S method. The prohibitive computational costs of these approaches, which increase with the problem size and amount of shielding materials, inhibit their use in the accurate full-scale neutronics analyses of fusion reactors. This paper describes a novel hybrid Monte Carlo/deterministic technique that uses the Consistent Adjoint Driven Importance Sampling (CADIS) methodology but focuses on multi-step shielding calculations. The Multi-Step CADIS (MS-CADIS) method speeds up the Monte Carlo neutron calculation of the R2S method using an importance function that represents the importance of the neutrons to the final SDDR. Using a simplified example, preliminarily results showed that the use of MS-CADIS enhanced the efficiency of the neutron Monte Carlo simulation of an SDDR calculation by a factor of 550 compared to standard global variance reduction techniques, and that the increase over analog Monte Carlo is higher than 10,000.

hybrid Monte Carlo/deterministic↗

DOE OSTI2017

Efficient convolutional sparse coding

Computationally efficient algorithms may be applied for fast dictionary learning solving the convolutional sparse coding problem in the Fourier domain. More specifically, efficient convolutional sparse coding may be derived within an alternating direction method of multipliers (ADMM) framework that utilizes fast Fourier transforms (FFT) to solve the main linear system in the frequency domain. Such algorithms may enable a significant reduction in computational cost over conventional approaches by implementing a linear solver for the most critical and computationally expensive component of the conventional iterative algorithm. The theoretical computational cost of the algorithm may be reduced from O(M.sup.3N) to O(MN log N), where N is the dimensionality of the data and M is the number of elements in the dictionary. This significant improvement in efficiency may greatly increase the range of problems that can practically be addressed via convolutional sparse representations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Supramolecular Enhancement of Electrochemical Nitrate Reduction Catalyzed by Cobalt Porphyrin Organic Cages for Ammonia Electrosynthesis in Water**

Abstract The electrochemical nitrate (NO 3 − ) reduction reaction (NO 3 RR) to ammonia (NH 3 ) represents a sustainable approach for denitrification to balance global nitrogen cycles and an alternative to traditional thermal Haber‐Bosch processes. Here, we present a supramolecular strategy for promoting NH 3 production in water from NO 3 RR by integrating two‐dimensional (2D) molecular cobalt porphyrin ( CoTPP ) units into a three‐dimensional (3D) porous organic cage architecture. The porphyrin box CoPB‐C8 enhances electrochemical active site exposure, facilitates substrate–catalyst interactions, and improves catalyst stability, leading to turnover numbers and frequencies for NH 3 production exceeding 200,000 and 56 s −1 , respectively. These values represent a 15‐fold increase in NO 3 RR activity and 200‐mV improvement in overpotential for the 3D CoPB‐C8 box structure compared to its 2D CoTPP counterpart. Synthetic tuning of peripheral alkyl substituents highlights the importance of supramolecular porosity and cavity size on electrochemical NO 3 RR activity. These findings establish the incorporation of 2D molecular units into 3D confined space microenvironments as an effective supramolecular design strategy for enhancing electrocatalysis.

An, Lun↗

DOE OSTI2023

Supramolecular Enhancement of Electrochemical Nitrate Reduction Catalyzed by Cobalt Porphyrin Organic Cages for Ammonia Electrosynthesis in Water**

An, Lun↗

DOE OSTI2022

Enhanced detection of paramagnetic fluorine-19 magnetic resonance imaging agents using zero echo time sequence and compressed sensing

Fluorine-19 ( 19 F) magnetic resonance imaging (MRI) is an emerging technique offering specific detection of labeled cells in vivo. Lengthy acquisition times and modest signal-to-noise ratio (SNR) makes three-dimensional spin-density–weighted 19 F imaging challenging. Recent advances in tracer paramagnetic metallo-perfluorocarbon (MPFC) nanoemulsion probes have shown multifold SNR improvements due to an accelerated 19 F T 1 relaxation rate and a commensurate gain in imaging speed and averages. However, 19 F T 2 -reduction and increased linewidth limit the amount of metal additive in MPFC probes, thus constraining the ultimate SNR. To overcome these barriers, we describe a compressed sampling (CS) scheme, implemented using a “zero” echo time (ZTE) sequence, with data reconstructed via a sparsity-promoting algorithm. Our CS-ZTE scheme acquires k-space data using an undersampled spherical radial pattern and signal averaging. Image reconstruction employs off-the-shelf sparse solvers to solve a joint total variation and -norm regularized least square problem. To evaluate CS-ZTE, we performed simulations and acquired 19 F MRI data at 11.7 T in phantoms and mice receiving MPFC-labeled dendritic cells. For MPFC-labeled cells in vivo, we show SNR gains of ~6.3 × with 8-fold undersampling. We show that this enhancement is due to three mechanisms including undersampling and commensurate increase in signal averaging in a fixed scan time, denoising attributes from the CS algorithm, and paramagnetic reduction of T 1 . Importantly, 19 F image intensity analyses yield accurate estimates of absolute quantification of 19 F spins. Overall, the CS-ZTE method using MPFC probes achieves ultrafast imaging, a substantial boost in detection sensitivity, accurate 19 F spin quantification, and minimal image artifacts.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Online adaptive basis refinement and compression for reduced-order models via vector-space sieving

In many applications, projection-based reduced-order models (ROMs) have demonstrated the ability to provide rapid approximate solutions to high-fidelity full-order models (FOMs). However, there is no a priori assurance that these approximate solutions are accurate; their accuracy depends on the ability of the low-dimensional trial basis to represent the FOM solution. As a result, ROMs can generate inaccurate approximate solutions, e.g., when the FOM solution at the online prediction point is not well represented by training data used to construct the trial basis. To address this fundamental deficiency of standard model-reduction approaches, this work proposes a novel online-adaptive mechanism for efficiently enriching the trial basis in a manner that ensures convergence of the ROM to the FOM, yet does not incur any FOM solves. The mechanism is based on the previously proposed adaptive $h$-refinement method for ROMs, but improves upon this work in two crucial ways. First, the proposed method enables basis refinement with respect to any orthogonal basis (not just the Kronecker basis), thereby generalizing the refinement mechanism and enabling it to be tailored to the physics characterizing the problem at hand. Second, the proposed method provides a fast online algorithm for periodically compressing the enriched basis via an efficient proper orthogonal decomposition (POD) method, which does not incur any operations that scale with the FOM dimension. We report these two features allow the proposed method to serve as (1) a failsafe mechanism for ROMs, as the method enables the ROM to satisfy any prescribed error tolerance online (even in the case of inadequate training), and (2) an efficient online basis-adaptation mechanism, as the combination of basis enrichment and compression enables the basis to adapt online while controlling its dimension.

42 ENGINEERING↗

DOE OSTI2019

Interfacial transmetallation synthesis of a platinadithiolene nanosheet as a potential 2D topological insulator

The construction of two-dimensional metal complex materials is fascinating because of the structural and functional diversity of these materials. Previously, we have reported the synthesis of electroconductive nickelladithiolene (NiDT) and palladadithiolene (PdDT) nanosheets using benzenehexathiol (BHT). Down the group from Ni, Pd to Pt, there is a distinct positive shift in the reduction potential; as a result, it becomes synthetically more challenging to stabilize Pt 2+ than to form metallic Pt(0) in the presence of BHT as a reducing agent. Herein, a novel synthetic strategy for the preparation of platinadithiolene nanosheet (PtDT) using a dibutyltin-protected BHT ligand is reported, leading to transmetallation in the presence of dioxygen. Both free-standing stacked sheets and atomic layer sheets were obtained and characterized by microscopic techniques such as AFM, SEM, and TEM. To study the morphology of the sheets and determine their charge neutrality, X-ray photoelectron (XP) and infrared (IR) spectroscopic techniques were used. Powder X-ray diffraction analysis of the multilayer PtDT indicates a half-way slipped hexagonal configuration in the P 3¯1 m space group. The band structure of this PtDT exhibits a band gap at the Fermi level, which is different from that of NiDT in the staggered configuration, and a Dirac gap, indicating the possibility of 2D topological insulation at room temperature. PtDT is insulating but chemically activated by oxidation with I 2 to increase the conductivity by more than 106 folds up to 0.39 S cm –1 . The MDT sheets exhibit electrocatalytic activity for the hydrogen evolution reaction, and the activity order is NiDT < PdDT < PtDT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Spatiotemporally Adaptive Compression for Scientific Dataset with Feature Preservation – A Case Study on Simulation Data with Extreme Climate Events Analysis

Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated over timesteps to accommodate storage and I/O limitations. In this paper, we propose a technique that addresses storage costs while improving post-analysis accuracy through spatiotemporal adaptive, error-controlled lossy compression. We investigate the trade-off between data precision and temporal output rates, revealing that reducing data precision and increasing timestep frequency lead to more accurate analysis outcomes. Additionally, we integrate spatiotemporal feature detection with data compression and demonstrate that performing adaptive error-bounded compression in higher dimensional space enables greater compression ratios, leveraging the error propagation theory of a transformation-based compressor. To evaluate our approach, we conduct experiments using the well-known E3SM climate simulation code and apply our method to compress variables used for cyclone tracking. Our results show a significant reduction in storage size while enhancing the quality of cyclone tracking analysis, both quantitatively and qualitatively, in comparison to the prevalent timestep decimation approach. Compared to three state-of-the-art lossy compressors lacking feature preservation capabilities, our adaptive compression framework improves perfectly matched cases in TC tracking by 26.4-51.3% at medium compression ratios and by 77.3-571.1% at large compression ratios, with a merely 5–11% computational overhead.

Gong, Qian↗

NASA NTRS1976

Investigation of television transmission using adaptive delta modulation principles

The results are presented of a study on the use of the delta modulator as a digital encoder of television signals. The computer simulation of different delta modulators was studied in order to find a satisfactory delta modulator. After finding a suitable delta modulator algorithm via computer simulation, the results were analyzed and then implemented in hardware to study its ability to encode real time motion pictures from an NTSC format television camera. The effects of channel errors on the delta modulated video signal were tested along with several error correction algorithms via computer simulation. A very high speed delta modulator was built (out of ECL logic), incorporating the most promising of the correction schemes, so that it could be tested on real time motion pictures. Delta modulators were investigated which could achieve significant bandwidth reduction without regard to complexity or speed. The first scheme investigated was a real time frame to frame encoding scheme which required the assembly of fourteen, 131,000 bit long shift registers as well as a high speed delta modulator. The other schemes involved the computer simulation of two dimensional delta modulator algorithms.

Schilling, D. L.↗

NASA NTRS1978

Study of low-cost fabrication methods for aerospace composite materials

Flat and hat section specimens of graphite/epoxy composite materials have been fabricated by the resin bath or wet pultrusion process. This demonstrated the feasibility of incorporating crossplied graphite fiber reinforcements in conjunction with epoxy resin systems in the wet pultrusion process. However, the thickness constraints of the pultrusion process, the lack of dimensional stability of the crossply materials and equipment limitations affect the quality of the hat section pultrusions. The wet pultrusion process shows promise of being a low cost method for producing composite parts with constant cross section along the length. A cost analysis showed at least 80 percent cost reduction for the hat section and 40 percent for flat panel by pultrusion over the conventional manual and automated lay-up.

Chung, H. H.↗

NASA NTRS1996

Recent Developments in Gun Operating Techniques at the NASA Ames Ballistic Ranges

This paper describes recent developments in gun operating techniques at the Ames ballistic range complex. This range complex has been in operation since the early 1960s. Behavior of sabots during separation and projectile-target impact phenomena have long been observed by means of short-duration flash X-rays: new versions allow operation in the lower-energy ("soft") X-ray range and have been found to be more effective than the earlier designs. The dynamics of sabot separation is investigated in some depth from X-ray photographs of sabots launched in the Ames 1.0 in and 1.5 in guns; the sabot separation dynamics appears to be in reasonably good agreement with standard aerodynamic theory. Certain sabot packages appear to suffer no erosion or plastic deformation on traversing the gun barrel, contrary to what would be expected. Gun erosion data from the Ames 0.5 in, 1.0 in, and 1.5 in guns is examined in detail and can be correlated with a particular non- dimensionalized powder mass parameter. The gun erosion increases very rapidly as this parameter is increased. Representative shapes of eroded gun barrels are given. Guided by a computational fluid dynamics (CFD) code, the operating conditions of the Ames 0.5 in and 1.5 in guns were modified. These changes involved: (1) reduction in the piston mass, powder mass and hydrogen fill pressure and (2) reduction in pump tube volume, while maintaining hydrogen mass. These changes resulted in muzzle velocity increases of 0.5-0.8 km/sec, achieved simultaneously with 30-50 percent reductions in gun erosion.

Bogdanoff, D. W.↗