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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1980

Stresses in a three-dimensional unidirectional composite containing broken fibers

An approximate solution is developed for the determination of the interlaminar normal and shear stresses in the vicinity of a crack in a three dimensional composite containing unidirectional linearly elastic fibers in an infinite linearly elastic matrix. In order to reduce the complexity of the formulation, certain assumptions are made as to the physically significant stresses to be retained. These simplifications reduce the partial differential equations of elasticity to differential-difference equations which are tractable using Fourier transform techniques. This 'material modeling' approach is in contrast with solutions developed by considering each lamina as a homogeneous, orthotropic layer. The resulting solution does not contain the classical singular stress field for the fibers and the influence of broken fibers on unbroken fibers is felt by a change in stress concentration factors. The matrix stresses however, are unbounded as the fiber spacing vanishes and an equivalent fiber-matrix geometry is proposed which gives the correct singular behavior. The numerical solution is considered in detail and several specific examples are presented. The potential for damaged or debonded zones to be generated by an embedded crack is discussed, and stress concentration factors for fibers near the crack are given. Detailed comparisons are made between the present solution, the analogous two-dimensional problem, and corresponding shear-lag models.

Goree, J. G.↗
NASA NTRS2006

A Byzantine-Fault Tolerant Self-Stabilizing Protocol for Distributed Clock Synchronization Systems

Embedded distributed systems have become an integral part of safety-critical computing applications, necessitating system designs that incorporate fault tolerant clock synchronization in order to achieve ultra-reliable assurance levels. Many efficient clock synchronization protocols do not, however, address Byzantine failures, and most protocols that do tolerate Byzantine failures do not self-stabilize. Of the Byzantine self-stabilizing clock synchronization algorithms that exist in the literature, they are based on either unjustifiably strong assumptions about initial synchrony of the nodes or on the existence of a common pulse at the nodes. The Byzantine self-stabilizing clock synchronization protocol presented here does not rely on any assumptions about the initial state of the clocks. Furthermore, there is neither a central clock nor an externally generated pulse system. The proposed protocol converges deterministically, is scalable, and self-stabilizes in a short amount of time. The convergence time is linear with respect to the self-stabilization period. Proofs of the correctness of the protocol as well as the results of formal verification efforts are reported.

Malekpour, Mahyar R.↗
NASA NTRS2006

A Byzantine-Fault Tolerant Self-Stabilizing Protocol for Distributed Clock Synchronization Systems

Embedded distributed systems have become an integral part of safety-critical computing applications, necessitating system designs that incorporate fault tolerant clock synchronization in order to achieve ultra-reliable assurance levels. Many efficient clock synchronization protocols do not, however, address Byzantine failures, and most protocols that do tolerate Byzantine failures do not self-stabilize. Of the Byzantine self-stabilizing clock synchronization algorithms that exist in the literature, they are based on either unjustifiably strong assumptions about initial synchrony of the nodes or on the existence of a common pulse at the nodes. The Byzantine self-stabilizing clock synchronization protocol presented here does not rely on any assumptions about the initial state of the clocks. Furthermore, there is neither a central clock nor an externally generated pulse system. The proposed protocol converges deterministically, is scalable, and self-stabilizes in a short amount of time. The convergence time is linear with respect to the self-stabilization period. Proofs of the correctness of the protocol as well as the results of formal verification efforts are reported.

Malekpour, Mahyar R.↗
NASA NTRS2005

NASA Tech Briefs, December 2005

Topics covered include: Video Mosaicking for Inspection of Gas Pipelines; Shuttle-Data-Tape XML Translator; Highly Reliable, High-Speed, Unidirectional Serial Data Links; Data-Analysis System for Entry, Descent, and Landing; Hybrid UV Imager Containing Face-Up AlGaN/GaN Photodiodes; Multiple Embedded Processors for Fault-Tolerant Computing; Hybrid Power Management; Magnetometer Based on Optoelectronic Microwave Oscillator; Program Predicts Time Courses of Human/ Computer Interactions; Chimera Grid Tools; Astronomer's Proposal Tool; Conservative Patch Algorithm and Mesh Sequencing for PAB3D; Fitting Nonlinear Curves by Use of Optimization Techniques; Tool for Viewing Faults Under Terrain; Automated Synthesis of Long Communication Delays for Testing; Solving Nonlinear Euler Equations With Arbitrary Accuracy; Self-Organizing-Map Program for Analyzing Multivariate Data; Tool for Sizing Analysis of the Advanced Life Support System; Control Software for a High-Performance Telerobot; Java Radar Analysis Tool; Architecture for Verifiable Software; Tool for Ranking Research Options; Enhanced, Partially Redundant Emergency Notification System; Close-Call Action Log Form; Task Description Language; Improved Small-Particle Powders for Plasma Spraying; Bonding-Compatible Corrosion Inhibitor for Rinsing Metals; Wipes, Coatings, and Patches for Detecting Hydrazines; Rotating Vessels for Growing Protein Crystals; Oscillating-Linear-Drive Vacuum Compressor for CO2; Mechanically Biased, Hinged Pairs of Piezoelectric Benders; Apparatus for Precise Indium-Bump Bonding of Microchips; Radiation Dosimetry via Automated Fluorescence Microscopy; Multistage Magnetic Separator of Cells and Proteins; Elastic-Tether Suits for Artificial Gravity and Exercise; Multichannel Brain-Signal-Amplifying and Digitizing System; Ester-Based Electrolytes for Low-Temperature Li-Ion Cells; Hygrometer for Detecting Water in Partially Enclosed Volumes; Radio-Frequency Plasma Cleaning of a Penning Malmberg Trap; Reduction of Flap Side Edge Noise - the Blowing Flap; and Preventing Accidental Ignition of Upper-Stage Rocket Motors.

Source record↗
DOE OSTI2021

Data Science Meets Physical Organic Chemistry

At the heart of synthetic chemistry is the holy grail of predictable catalyst design. In particular, researchers involved in reaction development in asymmetric catalysis have pursued a variety of strategies toward this goal. This is driven by both the pragmatic need to achieve high selectivities and the inability to readily identify why a certain catalyst is effective for a given reaction. While empiricism and intuition have dominated the field of asymmetric catalysis since its inception, enantioselectivity offers a mechanistically rich platform to interrogate catalyst-structure response patterns that explain the performance of a particular catalyst or substrate. In the early stages of an asymmetric reaction development campaign, the overarching mechanism of the reaction, catalyst speciation, the turnover limiting step, and many other details are unknown or posited based on related reactions. Considering the unclear details leading to a successful reaction, initial enantioselectivity data are often used to intuitively guide the ultimate direction of optimization. However, if the conditions of the Curtin-Hammett principle are satisfied, then measured enantioselectivity can be directly connected to the ensemble of diastereomeric transition states (TSs) that lead to the enantiomeric products, and the associated free energy difference between competing TSs (ΔΔ G ‡ = - RT ln[( S )/( R )], where ( S ) and ( R ) represent the concentrations of the enantiomeric products). We, and others, speculated that this important piece of information can be leveraged to guide reaction optimization in a quantitative way. Although traditional linear free energy relationships (LFERs), such as Hammett plots, have been used to illuminate important mechanistic features, we sought to develop data science derived tools to expand the power of LFERs in order to describe complex reactions frequently encountered in modern asymmetric catalysis. Specifically, we investigated whether enantioselectivity data from a reaction can be quantitatively connected to the attributes of reaction components, such as catalyst and substrate structural features, to harness data for asymmetric catalyst design. In this context, we developed a workflow to relate computationally derived features of reaction components to enantioselectivity using data science tools. The mathematical representation of molecules can incorporate many aspects of a transformation, such as molecular features from substrate, product, catalyst, and proposed transition states. Statistical models relating these features to reaction outputs can be used for various tasks, such as performance prediction of untested molecules. Perhaps most importantly, statistical models can guide the generation of mechanistic hypotheses that are embedded within complex patterns of reaction responses. Overall, merging traditional physical organic experiments with statistical modeling techniques creates a feedback loop that enables both evaluation of multiple mechanistic hypotheses and future catalyst design. In this Account, we highlight the evolution and application of this approach in the context of a collaborative program based on chiral phosphoric acid catalysts (CPAs) in asymmetric catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

3D printed water-stable Cd-doped Cs 4 MnBi 2 Cl 12 /polylactic acid perovskite/polymer composites for high-flux X-ray scintillation

Stable and efficient X-ray scintillators are crucial for medical diagnostics, industrial, and defense applications. However, conventional scintillator technologies face a trade-off between stability, optimal performance, and sustainability. Herein, we introduce 3D-printed Cs 4 MnBi 2 Cl 12 (Pero1) and Cs 4 Cd 0.68 Mn 0.32 Bi 2 Cl 12 (Pero2) perovskite microcrystals embedded within a polylactic acid (PLA) polymer composite as X-ray scintillators, combining efficiency, stability, and sustainability. The orange luminescent perovskite powder phosphors exhibited poor water stability, which was successfully addressed through incorporation into PLA via filament extrusion and fused deposition modeling (FDM) 3D printing. The resulting composite films demonstrated remarkable water stability while maintaining uniform orange emission throughout the polymer matrix, as confirmed by 3D topography scanning and X-ray fluorescence mapping. Structural characterization revealed minimal chemical interaction between the perovskite and PLA matrix, with the composites retaining their crystalline properties. The PLA-Pero2 composite exhibited superior optical properties, with a photoluminescence quantum yield of 47%, nearly 17 times higher than that of PLA-Pero1 (2.8%), attributed to the effective suppression of non-radiative decay pathways through Cd 2+ doping. Under hard X-ray irradiation at synchrotron beamlines, both composites exhibited excellent radioluminescence, with emission peaks at 605 nm, a linear response across a wide X-ray flux range, and remarkable radiation stability, showing less than 3% intensity degradation after 600 seconds of continuous high-dose exposure. The PLA-Pero2 composite achieved a spatial resolution of 5 line pairs per millimeter and a contrast ratio of 0.255. These performance metrics, combined with the polymer's biodegradability and scalability through additive manufacturing, position PLA-based composites as a more sustainable alternative to conventional petroleum-based polymer scintillators for next-generation medical imaging, radiation monitoring, and industrial radiography applications.

3D Printing↗
NASA NTRS2013

Development of Two-Moment Cloud Microphysics for Liquid and Ice Within the NASA Goddard Earth Observing System Model (GEOS-5)

This work presents the development of a two-moment cloud microphysics scheme within the version 5 of the NASA Goddard Earth Observing System (GEOS-5). The scheme includes the implementation of a comprehensive stratiform microphysics module, a new cloud coverage scheme that allows ice supersaturation and a new microphysics module embedded within the moist convection parameterization of GEOS-5. Comprehensive physically-based descriptions of ice nucleation, including homogeneous and heterogeneous freezing, and liquid droplet activation are implemented to describe the formation of cloud particles in stratiform clouds and convective cumulus. The effect of preexisting ice crystals on the formation of cirrus clouds is also accounted for. A new parameterization of the subgrid scale vertical velocity distribution accounting for turbulence and gravity wave motion is developed. The implementation of the new microphysics significantly improves the representation of liquid water and ice in GEOS-5. Evaluation of the model shows agreement of the simulated droplet and ice crystal effective and volumetric radius with satellite retrievals and in situ observations. The simulated global distribution of supersaturation is also in agreement with observations. It was found that when using the new microphysics the fraction of condensate that remains as liquid follows a sigmoidal increase with temperature which differs from the linear increase assumed in most models and is in better agreement with available observations. The performance of the new microphysics in reproducing the observed total cloud fraction, longwave and shortwave cloud forcing, and total precipitation is similar to the operational version of GEOS-5 and in agreement with satellite retrievals. However the new microphysics tends to underestimate the coverage of persistent low level stratocumulus. Sensitivity studies showed that the simulated cloud properties are robust to moderate variation in cloud microphysical parameters. However significant sensitivity in ice cloud properties was found to variation in the dispersion of the ice crystal size distribution and the critical size for ice autoconversion. The implementation of the new microphysics leads to a more realistic representation of cloud processes in GEOS-5 and allows the linkage of cloud properties to aerosol emissions.

Aerosol-Cloud Interactions↗
NASA NTRS1995

Boson localization and universality in YBa2Cu(3-x)M(x)O(7-delta)

We consider a two component mixture of charged fermions on neutralizing background with all sign combinations and arbitrarily small mass ratios. In the two impurity limit for the heavier component we show that the pair forms a bound state for all charge combinations. In the lowest order approximation we derive a closed form expression Veff(r) for the binding potential which has short-range repulsion followed by attraction. In the classical limit, when the mass of embedded particles is large m2 much greater than m, we can calculate from Veff(r) also the cohesive energy E and the bond length R of a metallic crystal such as lithium. The lowest order result is R = 3.1 A, E = -0.9 eV, not entirely different from the experimental result for lithium metal. The same interaction for two holes on a parabolic band with m2 greater than m gives the quantum mechanical bound state which one may interpret as a boson or local pair in the case of high-Te and heavy fermion superconductors. We also show that for compounds of the type YBa2Cu(3 - x)M(x)O(7 - delta) one can understand most of the experimental results for the superconducting and normal states with a single temperature dependent boson breaking function f(T) for each impurity content x governing the decay of bosons into pairing fermions. In the normal state f(T) turns out to be a linear, universal function, independent of the impurity content I and the oxygen content delta. We predict with universality a depression in Tc(x) with slight down bending in agreement with experiment. As a natural consequence of the model the bosons become localized slightly above Tc due to the Wigner crystallization, enhanced with lattice local field minima. The holes remain delocalized with a linearly increasing concentration in the normal state, thus explaining the rising Hall density. The boson localization temperature T(sub BL) shows up as a minimum in the Hall density R(sub ab)(exp -1). We also give explanation for very recently observed scaling of temperature dependent Hall effect in La(2 - x)Sr(x)CuO4.

Kallio, A.↗
DOE OSTI2023

Extended isogeometric analysis of multi-material and multi-physics problems using hierarchical B-splines

Here, this paper presents an immersed, isogeometric finite element framework to predict the response of multi-material, multi-physics problems with complex geometries using locally refined discretizations. To circumvent the need to generate conformal meshes, this work uses an extended finite element method (XFEM) to discretize the governing equations on non-conforming, embedding meshes. A flexible approach to create truncated hierarchical B-splines discretizations is presented. This approach enables the refinement of each state variable field individually to meet field-specific accuracy requirements. To obtain an immersed geometry representation that is consistent across all hierarchically refined B-spline discretizations, the geometry is immersed into a single mesh, the XFEM background mesh, which is constructed from the union of all hierarchical B-spline meshes. An extraction operator is introduced to represent the truncated hierarchical B-spline bases in terms of Lagrange shape functions on the XFEM background mesh without loss of accuracy. The truncated hierarchical B-spline bases are enriched using a generalized Heaviside enrichment strategy to accommodate small geometric features and multi-material problems. The governing equations are augmented by a formulation of the face-oriented ghost stabilization enhanced for locally refined B-spline bases. We present examples for two- and three-dimensional linear elastic and thermo-elastic problems. The numerical results validate the accuracy of our framework. The results also demonstrate the applicability of the proposed framework to large, geometrically complex problems.

42 ENGINEERING↗
DOE OSTI2023

Behavior and properties of helium cavities in ductile-phase-toughened tungsten irradiated with He + ions at an elevated temperature

Ductile-phase toughened tungsten (DPT W) composites have demonstrated a great potential for plasma-facing components in fusion power systems. These materials can retain the outstanding thermomechanical properties of W while significantly enhancing the fracture toughness. The DPT W composite in this study consists of W particles (88 wt.%) embedded in a ductile NiFeW (12 wt.%) solution matrix. Irradiation of the composite was performed with 90 keV He + ions to 1.0 × 10 17 He + /cm 2 at 973 K. The He cavities formed in both W and NiFeW phases are examined using convergent-beam scanning transmission electron microscopy (CB-STEM) at an atomic-level resolution. Full-range depth profiles of the He cavity diameters and number densities are analyzed. The results show that the average cavity diameter in NiFeW is ~2.7 times that in W, while the number density is an order of magnitude lower. A quantitative analysis of the He density and pressure in the cavities is also achieved using STEM electron energy loss spectroscopy (STEM-EELS) mapping. The He atoms in the cavities in NiFeW are found to be under-pressurized, while those in similar-sized cavities in W are not detectable. Further, the He energy-loss shift exhibits a linear relationship with the He density in cavities in NiFeW, with the slope comparable to that for martensitic steel.

36 MATERIALS SCIENCE↗
NASA NTRS1995

A digital boxcar integrator for IMS spectra

When trying to detect or quantify a signal at or near the limit of detectability, it is invariably embeded in the noise. This statement is true for nearly all detectors of any physical phenomena and the limit of detectability, hopefully, occurs at very low signal-to-noise levels. This is particularly true of IMS (Ion Mobility Spectrometers) spectra due to the low vapor pressure of several chemical compounds of great interest and the small currents associated with the ionic detection process. Gated Integrators and Boxcar Integrators or Averagers are designed to recover fast, repetitive analog signals. In a typical application, a time 'Gate' or 'Window' is generated, characterized by a set delay from a trigger or gate pulse and a certain width. A Gated Integrator amplifies and integrates the signal that is present during the time the gate is open, ignoring noise and interference that may be present at other times. Boxcar Integration refers to the practice of averaging the output of the Gated Integrator over many sweeps of the detector. Since any signal present during the gate will add linearly, while noise will add in a 'random walk' fashion as the square root of the number of sweeps, averaging N sweeps will improve the 'Signal-to-Noise Ratio' by a factor of the square root of N.

Cohen, Martin J.↗
NASA NTRS1995

Interstellar clouds in high-speed, supersonic flows: Two-dimensional simulations

We present a series of gasdynamical simulations of the interaction of a dense, cool interstellar cloud with a high-speed, supersonic wind that confines and accelerates the embedded cloud. Our goal is to attempt to determine if such clouds can survive various potentially disruptive instabilities, that occur at their peripheries, long enough to be accelerated to speeds which are comparable to the wind velocity. These simulations are performed using two-dimensional, Eulerian gas dynamics on both an axisymmetric (about the cloud axis) and 'slab' geometric grid. The spatial and temporal resolutions of the simulations are varied over a wide range to investigate the effects of small-scale instabilities on the overall acceleration of clouds and the development of large-scale, disruptive instabilities. Also, we study the effects of wind/cloud Mach number variations by changing the wind speed constant at about 12 km/s (which corresponds to a cloud temperature of 10,000 K). The current simulations track the evolution of clouds as they are accelerated to speeds approximately 4-5 times greater than their internal sound speeds. Furthermore, the models with the highest resolution were extended far beyond quasi-linear Rayleigh-Taylor growth times reaching 6-7 Rayleigh-Taylor growth times for the largest scale instabilities before being terminated because of the accumulation of errors at the rear grid boundary.

Schiano, A. V. R.↗
DOE OSTI2022

Carbon Intensities of Refining Products in Petroleum Refineries with Co-Processed Biofeedstocks

Petroleum refineries increasingly seek to generate fuels with lower carbon intensities (CIs; a measure of life cycle greenhouse gas [GHG] emissions per unit of energy of fuel; well-to-wheel [WTW]) to meet growing demand. Co-processing refers to a process that adds biomass-derived feedstocks to the fossil-based feedstocks of existing petroleum refinery process units. With the use of biofeedstocks, it is expected that co-processed fuels would have lower CIs than their petroleum counterparts without requiring changes in the existing infrastructure for producing, transporting, and using fuels. To quantify the GHG emissions reduction benefits of co-processing, this study uses a linear programming model to simulate petroleum refinery conditions with and without co-processing. The co-processing cases include three biofeedstocks (soy oil, tallow, and used cooking oil or UCO) used as 10 vol.% of the feedstock to a hydrotreater or hydrocracker since these lipid-based feedstocks have favorable properties to be treated in a hydrotreater or hydrocracker. In addition, we considered pyrolysis oil used as 10 vol.% of the feedstock to a fluid catalytic cracking (FCC) unit in the modeled refinery due to its higher oxygen content compared to other lipid-based feedstocks. Life cycle analysis (LCA) using two distinct approaches—process-level energy allocation and a refinery-level marginal approach—has been conducted for each case. The LCA results using process-level allocation show that there are no noticeable changes in emissions or energy use impacts at the facility level. The life cycle GHG emission reductions of co-processing cases are mainly related to the fraction of biogenic carbon embedded in each fuel product. For example, co-processed jet fuels (a mixture of fossil and biogenic fuels) made via hydrotreating or hydrocracking have higher biogenic carbon, which results in jet fuel CI reductions of 3.9%–8.6% compared to the CI of baseline petroleum jet fuels on a WTW basis. However, analysis of co-processed pyrolysis oil in an FCC shows that a higher fraction of biofeedstocks (29%) becomes process emissions (i.e., CO and CO 2 ), mainly due to the oxygenates in pyrolysis oil, and so it generates less renewable fuel than biofeedstocks co-processed via hydrotreating or hydrocracking. Using the refinery-level marginal approach, the changes in energy use and emissions of co-processing cases compared to the petroleum-only baseline case are allocated to the changes in fuel production (assuming renewable fuels). This approach generates the life cycle GHG emission values of co-processed renewable fuels, which are comparable to the CIs of standalone biofuel production pathways. However, as this approach relies on a rough assumption that product yields and emissions from co-processing units on fossil feedstocks remain the same with and without biofeedstock inputs, co-processing cases like FCC pyrolysis oil may generate quite skewed results.

02 PETROLEUM↗
NASA NTRS2004

NASA Tech Briefs, February 2004

Topics include: Simulation Testing of Embedded Flight Software; Improved Indentation Test for Measuring Nonlinear Elasticity; Ultraviolet-Absorption Spectroscopic Biofilm Monitor; Electronic Tongue for Quantitation of Contaminants in Water; Radar for Measuring Soil Moisture Under Vegetation; Modular Wireless Data-Acquisition and Control System; Microwave System for Detecting Ice on Aircraft; Routing Algorithm Exploits Spatial Relations; Two-Finger EKG Method of Detecting Evasive Responses; Updated System-Availability and Resource-Allocation Program; Routines for Computing Pressure Drops in Venturis; Software for Fault-Tolerant Matrix Multiplication; Reproducible Growth of High-Quality Cubic-SiC Layers; Nonlinear Thermoelastic Model for SMAs and SMA Hybrid Composites; Liquid-Crystal Thermosets, a New Generation of High-Performance Liquid-Crystal Polymers; Formulations for Stronger Solid Oxide Fuel-Cell Electrolytes; Simulation of Hazards and Poses for a Rocker-Bogie Rover; Autonomous Formation Flight; Expandable Purge Chambers Would Protect Cryogenic Fittings; Wavy-Planform Helicopter Blades Make Less Noise; Miniature Robotic Spacecraft for Inspecting Other Spacecraft; Miniature Ring-Shaped Peristaltic Pump; Compact Plasma Accelerator; Improved Electrohydraulic Linear Actuators; A Software Architecture for Semiautonomous Robot Control; Fabrication of Channels for Nanobiotechnological Devices; Improved Thin, Flexible Heat Pipes; Miniature Radioisotope Thermoelectric Power Cubes; Permanent Sequestration of Emitted Gases in the Form of Clathrate Hydrates; Electrochemical, H2O2-Boosted Catalytic Oxidation System; Electrokinetic In Situ Treatment of Metal-Contaminated Soil; Pumping Liquid Oxygen by Use of Pulsed Magnetic Fields; Magnetocaloric Pumping of Liquid Oxygen; Tailoring Ion-Thruster Grid Apertures for Greater Efficiency; and Lidar for Guidance of a Spacecraft or Exploratory Robot.

Source record↗
DOE OSTI2020

CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular and biological systems. It is especially aimed at massively-parallel and linear-scaling electronic structure methods and state-of-the-art ab-initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension. TDK has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 716142). VRR has been supported by the Swiss National Science Foundation in the form of Ambizione grant No. PZ00P2 174227 and RZK by the Natural Sciences and Engineering Research Council of Canada (NSERC) through Discovery Grants (RGPIN-2016-0505). GKS and CJM are supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. UK based work was funded under the embedded CSE programme of the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk), grants eCSE03-011, eCSE06-6, eCSE08-9, eCSE13-17 and the EPSRC (EP/P022235/1) grant “Surface and Interface Toolkit for the Materials Chemistry Community". Computational resources were provided by the Swiss National Supercomputing Centre (CSCS) and Compute Canada. The generous allocation of computing time on the FPGA-based supercomputer “Noctua" at PC2 is kindly acknowledged.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Protein Motifs for Proton Transfers That Build the Transmembrane Proton Gradient

Biological membranes are barriers to polar molecules, so membrane embedded proteins control the transfers between cellular compartments. Protein controlled transport moves substrates and activates cellular signaling cascades. In addition, the electrochemical gradient across mitochondrial, bacterial and chloroplast membranes, is a key source of stored cellular energy. This is generated by electron, proton and ion transfers through proteins. The gradient is used to fuel ATP synthesis and to drive active transport. Here the mechanisms by which protons move into the buried active sites of Photosystem II (PSII), bacterial RCs (bRCs) and through the proton pumps, Bacteriorhodopsin (bR), Complex I and Cytochrome c oxidase (CcO), are reviewed. These proteins all use water filled proton transfer paths. The proton pumps, that move protons uphill from low to high concentration compartments, also utilize Proton Loading Sites (PLS), that transiently load and unload protons and gates, which block backflow of protons. PLS and gates should be synchronized so PLS proton affinity is high when the gate opens to the side with few protons and low when the path is open to the high concentration side. Proton transfer paths in the proteins we describe have different design features. Linear paths are seen with a unique entry and exit and a relatively straight path between them. Alternatively, paths can be complex with a tangle of possible routes. Likewise, PLS can be a single residue that changes protonation state or a cluster of residues with multiple charge and tautomer states.

cytochrome c oxidase↗
NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗