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At least 163 records · Page 9

NASA Tech Briefs, October 2011

Topics covered include: Laser Truss Sensor for Segmented Telescope Phasing; Qualifications of Bonding Process of Temperature Sensors to Deep-Space Missions; Optical Sensors for Monitoring Gamma and Neutron Radiation; Compliant Tactile Sensors; Cytometer on a Chip; Measuring Input Thresholds on an Existing Board; Scanning and Defocusing Properties of Microstrip Reflectarray Antennas; Cable Tester Box; Programmable Oscillator; Fault-Tolerant, Radiation-Hard DSP; Sub-Shot Noise Power Source for Microelectronics; Asynchronous Message Service Reference Implementation; Zero-Copy Objects System; Delay and Disruption Tolerant Networking MACHETE Model; Contact Graph Routing; Parallel Eclipse Project Checkout; Technique for Configuring an Actively Cooled Thermal Shield in a Flight System; Use of Additives to Improve Performance of Methyl Butyrate-Based Lithium-Ion Electrolytes; Li-Ion Cells Employing Electrolytes with Methyl Propionate and Ethyl Butyrate Co-Solvents; Improved Devices for Collecting Sweat for Chemical Analysis; Tissue Photolithography; Method for Impeding Degradation of Porous Silicon Structures; External Cooling Coupled to Reduced Extremity Pressure Device; A Zero-Gravity Cup for Drinking Beverages in Microgravity; Co-Flow Hollow Cathode Technology; Programmable Aperture with MEMS Microshutter Arrays; Polished Panel Optical Receiver for Simultaneous RF/Optical Telemetry with Large DSN Antennas; Adaptive System Modeling for Spacecraft Simulation; Lidar-Based Navigation Algorithm for Safe Lunar Landing; Tracking Object Existence From an Autonomous Patrol Vehicle; Rad-Hard, Miniaturized, Scalable, High-Voltage Switching Module for Power Applications; and Architecture for a 1-GHz Digital RADAR.

Source record↗

Pinning dislocations in colloidal crystals with active particles that seek stacking faults

There is growing interest in functional, adaptive devices built from colloidal subunits of micron size or smaller. A colloidal material with dynamic mechanical properties could facilitate such microrobotic machines. Here we study via computer simulation how active interstitial particles in small quantities can be used to modify the bulk mechanical properties of a colloidal crystal. Passive interstitial particles are known to pin dislocations in metals, thereby increasing resistance to plastic deformation. We extend this tactic by employing anisotropic active interstitials that travel super-diffusively and bind strongly to stacking faults associated with partial dislocations. We find that: (1) interstitials that are effective at reducing plasticity compromise between strong binding to stacking faults and high mobility in the crystal bulk. (2) Reorientation of active interstitials in the crystal depends upon rotational transitions between high-symmetry crystal directions. (3) The addition of certain active interstitial shapes at concentrations as low as 60 per million host particles (0.006%) can create a shear threshold for dislocation migration. This work demonstrates how active materials in a dense matrix can locally sense their environment and lead to bulk property changes.

36 MATERIALS SCIENCE↗

A Review of Medium-Mn, Low-Density Steels for Transportation Applications

Low-density steels constitute a broad and complex alloy space (Fe–Mn–Al–C) suitable for a variety of applications. In particular, there has been growing interest in duplex (ferrite + austenite) or multiphase (+ martensite, carbides) low-density steels as a lightweight, advanced high-strength steel (AHSS) for vehicle applications, spurred by extensive decarbonization efforts. Medium-Mn (med-Mn) (3 to 12 wt pct) steels with 3.5 to 10 wt pct Al additions have decreased densities, presenting an interesting opportunity for high-specific strength, intrusion-resistant, and energy-absorbing sheet components with reduced alloying contents compared to high-Mn grades like austenitic Fe–Mn–Al–C or twinning-induced plasticity steels. Compared to leaner med-Mn steels, the physical metallurgy of med-Mn, low-density steels (MMLS) is complex and distinguished by increased δ-ferrite fractions and austenite stacking fault energies, decreased martensite start temperatures, and modified phase transformation windows. Mechanical properties of MMLS are comparable to 3rd generation AHSS, attributable to the unique, multiphase microstructures, and the array of strengthening mechanisms that can be accessed. Despite this, challenges and unknowns remain with respect to their industrial implementation, and new processing routes may need to be developed. Here, this review aims to highlight the composition effects, processing methods, microstructural evolution, deformation behavior, and application properties geared toward manufacturing and performance, altogether assessing the potential of MMLS for transportation applications.

36 MATERIALS SCIENCE↗

Atomic faulting induced exceptional cryogenic strain hardening in gradient cell–structured alloy

Coarse-grained materials are widely accepted to display the highest strain hardening and the best tensile ductility. We experimentally report an attractive strain hardening rate throughout the deformation stage at 77 kelvin in a stable single-phase alloy with gradient dislocation cells that even surpasses its coarse-grained counterparts. Contrary to conventional understanding, the exceptional strain hardening arises from a distinctive dynamic structural refinement mechanism facilitated by the emission and motion of massive multiorientational tiny stacking faults (planar defects), which are fundamentally distinct from the traditional linear dislocation–mediated deformation. In conclusion, the dominance of atomic-scale planar deformation faulting in plastic deformation introduces a different approach for strengthening and hardening metallic materials, offering promising properties and potential applications.

Gradient dislocation structure↗

Solving the Bernstein-Vazirani problem using Majorana-based topological quantum algorithms

Executing quantum algorithms using Majorana zero modes—a major milestone for the field of topological quantum computing—requires a platform that can be scaled to large quantum registers, can be controlled in real time and space, and a braiding protocol that uses the unique properties of these exotic particles. Here, we demonstrate the first successful simulation of a Majorana-based, fault-tolerant quantum algorithm to solve the Bernstein-Vazirani problem in two-dimensional magnet-superconductor hybrid structures from initialization to read-out of the final many-body state. Utilizing the Majorana zero modes’ topological properties, we introduce an optimized braiding protocol for the algorithm and a scalable architecture for its implementation with an arbitrary number of qubits. We visualize the algorithm protocol in real time and space by computing the non-equilibrium density of states, which is proportional to the time-dependent differential conductance, and the non-equilibrium charge density, which assigns a unique signature to each final state of the algorithm.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Detailed space–time variations of the seismic response of the shallow crust to small earthquakes from analysis of dense array data

SUMMARY We compute high-resolution space–time variations of subsurface seismic properties from autocorrelation functions (ACF’s) of noise and local earthquakes, recorded by the Sage Brush Flat dense array deployed around the Clark branch of the San Jacinto fault. The resolved temporal changes are referred to as apparent velocity changes because they reflect both nonlinear response and variations of material properties such as cracking and damage. Apparent velocity changes are estimated at four frequency bands (10–15, 10–20, 15–30 and 20–40 Hz) for two local earthquake data sets. In one analysis, ACF’s from P- and S-wave windows of 31 small events with magnitudes below 3.1 are used to compute the apparent velocity variations with respect to the mean ACF of each phase, and we also use the mean ACF of noise data as reference to estimate the changes. In a further analysis, the temporal evolution of properties is computed using moving time windows in continuous waveform over one-hour long data with noise and earthquake signals. The apparent velocity changes and recovery times are frequency dependent and present a strong spatial variability across the array. The resolved changes are larger and recovery time shorter with data associated with higher frequencies. At frequencies larger than 15 Hz, and using the mean ACF of noise data as a reference, the apparent average velocity changes across the array during the passage of the P and S waves from the small local events are 2.5 per cent and 6 per cent, respectively. The apparent velocity changes decrease by one order of magnitude when the earthquake data are used as a reference. The relatively large changes in response to very low ground motion have important implications on nonlinear processes involving degradation and healing of the subsurface material during common earthquake shaking.

Geochemistry & Geophysics↗

RAMP: A fault tolerant distributed microcomputer structure for aircraft navigation and control

RAMP consists of distributed sets of parallel computers partioned on the basis of software and packaging constraints. To minimize hardware and software complexity, the processors operate asynchronously. It was shown that through the design of asymptotically stable control laws, data errors due to the asynchronism were minimized. It was further shown that by designing control laws with this property and making minor hardware modifications to the RAMP modules, the system became inherently tolerant to intermittent faults. A laboratory version of RAMP was constructed and is described in the paper along with the experimental results.

Dunn, W. R.↗

Strength and deformation properties of basaltic lava flows on planetary surfaces

Basaltic rocks are thought to constitute a volumetrically significant rock type on the Moon, Mercury, Mars, and Venus, in addition to the Earth. Spacecraft images of surfaces with known or suspected basaltic composition on these bodies, particularly on Venus, indicate that these rocks have been deformed in the brittle regime to form faults and perhaps dilatant cracks, in addition to folding and more distributed types of deformation. Predictions of brittle fracture or other types of deformation are made by comparing calculated stresses from a tectonic model to some criterion for rock strength. Common strength criteria used in the planetary science literature for near-surface deformation include a Griffith tensile-strength criterion for intact rock, a Mohr envelope for intact basalt, and a brittle strength envelope based on Byerlee's law of rock frictional resistance. However, planetary terrains of basaltic composition consist of much more than just intact basaltic rock. The aggregate basaltic material, termed the 'rock mass,' consists of both the intact rock and the associated fracture, faults, lithologic contacts, and other discontinuous surfaces. A basaltic rock mass is the relevant material for which strength properties must be defined and calculated model stresses must be compared to in order to more accurately predict brittle deformation. For example, the various strengths of a rock mass are less than that of intact material of the same composition. This means that tectonic models which compare stresses to intact failure strengths overestimate the stresses required for fracture and so underestimate the extent and magnitude of brittle deformation predicted in these models. On the other hand, rock mass shear strength can be greater than that predicted from Byerlee's law. The concept of rock mass strength is central to many engineering design studies in which calculated stresses are used to predict brittle fracture, and this experience indicates that brittle strength envelopes which assume properties for intact rock (Griffith parabolas) or sliding along a single, continuous surface (Byerlee's law) inadequately characterize the tensile, compressive, and shear strengths of rock masses. The criterion adopted here to relate stresses to rock mass fracture is based on a Griffith-type curve for tensile normal stress and a concave downward curve for compressive normal stress. It is the only available criterion that explicitly considers the weakening effects of discontinuities within the rock mass on the stress state required for fracture.

Schultz, Richard A.↗

COTS-Based Fault Tolerance in Deep Space: Qualitative and Quantitative Analyses of a Bus Network Architecture

Using COTS products, standards and intellectual properties (IPs) for all the system and component interfaces is a crucial step toward significant reduction of both system cost and development cost as the COTS interfaces enable other COTS products and IPs to be readily accommodated by the target system architecture. With respect to the long-term survivable systems for deep-space missions, the major challenge for us is, under stringent power and mass constraints, to achieve ultra-high reliability of the system comprising COTS products and standards that are not developed for mission-critical applications. The spirit of our solution is to exploit the pertinent standard features of a COTS product to circumvent its shortcomings, though these standard features may not be originally designed for highly reliable systems. In this paper, we discuss our experiences and findings on the design of an IEEE 1394 compliant fault-tolerant COTS-based bus architecture. We first derive and qualitatively analyze a -'stacktree topology" that not only complies with IEEE 1394 but also enables the implementation of a fault-tolerant bus architecture without node redundancy. We then present a quantitative evaluation that demonstrates significant reliability improvement from the COTS-based fault tolerance.

Tai, Ann T.↗

Search for 3D topological superconductors using laser-based spectroscopy (Final Technical Report)

The three-dimensional topological superconductor (3D TSC) is a novel quantum phase of matter that is predicted to exhibit exotic thermal and electrical properties, which may serve applications ranging from precision thermal management and sensing technologies to fault-tolerant quantum information processing. Over the past decade, there has been an intensive effort to realize 1D and 2D TSCs by artificially engineering them from combinations of already existing materials. For example, coupling conventional superconductors to spin-orbit coupled 1D nanowires or to 2D topological insulator surfaces by the proximity effect provides a route to realizing 1D and 2D TSCs respectively. However no artificial engineering strategy is available for a 3D TSC. Therefore, current searches are limited to intrinsically superconducting compounds whose topological properties are difficult to predict. The overarching goal of this project was to realize and to identify 3D TSCs in bulk single crystals using novel laser-based spectroscopic techniques. One major thrust was to develop ultralow temperature and ultra-high-resolution angle-resolved photoemission spectroscopy (ARPES) to directly measure the dispersion of Majorana excitations that are predicted to exist on the surfaces of 3D TSCs. Another major thrust was to develop a rational route to realize 3D TSCs by identifying their precursor phases. It is theoretically proposed that the critical fluctuations of certain ordered electronic phases can mediate Cooper pairing in odd-parity channels and lead to topological superconductivity. Therefore, 3D TSCs may potentially emerge upon suppressing these inversion symmetry broken precursor phases to a critical point with external perturbations such as pressure, strain or even light. To test this hypothesis, we studied candidate materials using a suite of symmetry-sensitive optical probes including rotational anisotropy optical second harmonic generation (RA-SHG) and time-resolved coherent phonon spectroscopy, all operable under high-pressure and low temperature environments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Laboratory earthquake forecasting: A machine learning competition

Earthquake prediction, the long-sought holy grail of earthquake science, continues to confound Earth scientists. Could we make advances by crowdsourcing, drawing from the vast knowledge and creativity of the machine learning (ML) community? We used Google’s ML competition platform, Kaggle, to engage the worldwide ML community with a competition to develop and improve data analysis approaches on a forecasting problem that uses laboratory earthquake data. The competitors were tasked with predicting the time remaining before the next earthquake of successive laboratory quake events, based on only a small portion of the laboratory seismic data. The more than 4,500 participating teams created and shared more than 400 computer programs in openly accessible notebooks. Complementing the now well-known features of seismic data that map to fault criticality in the laboratory, the winning teams employed unexpected strategies based on rescaling failure times as a fraction of the seismic cycle and comparing input distribution of training and testing data. In addition to yielding scientific insights into fault processes in the laboratory and their relation with the evolution of the statistical properties of the associated seismic data, the competition serves as a pedagogical tool for teaching ML in geophysics. The approach may provide a model for other competitions in geosciences or other domains of study to help engage the ML community on problems of significance.

58 GEOSCIENCES↗

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗

Nowcasting Earthquakes in Southern California With Machine Learning: Bursts, Swarms, and Aftershocks May Be Related to Levels of Regional Tectonic Stress

Abstract Seismic bursts in Southern California are sequences of small earthquakes strongly clustered in space and time and include seismic swarms and aftershock sequences. A readily observable property of these events, the radius of gyration ( R G ), allows us to connect the bursts to the temporal occurrence of the largest M ≥ 7 earthquakes in California since 1984. In the Southern California earthquake catalog, we identify hundreds of these potentially coherent space‐time structures in a region defined by a circle of radius 600 km around Los Angeles. We compute R G for each cluster then filter them to identify those bursts with large numbers of events closely clustered in space, which we call “compact” bursts. Our basic assumption is that these compact bursts reflect the dynamics associated with large earthquakes. Once we have filtered the burst catalog, we apply an exponential moving average to construct a time series for the Southern California region. We observe that the R G of these bursts systematically decreases prior to large earthquakes, in a process that we might term “radial localization.” The R G then rapidly increases during an aftershock sequence, and a new cycle of “radial localization” then begins. These time series display cycles of recharge and discharge reminiscent of seismic stress accumulation and release in the elastic rebound process. The complex burst dynamics we observe are evidently a property of the region as a whole, rather than being associated with individual faults. This new method allows us to improve earthquake nowcasting, which is a technique to evaluate the current state of hazard in a seismically active region.

58 GEOSCIENCES↗

Polytypism in semi-disordered lizardite and amesite by low-dose HAADF-STEM

Serpentine minerals exert important controls on the physical properties of ultramafic rocks and have the potential to influence deformation phenomena in fault zones and to control the release of water in subducted slabs. Sheet serpentine generally, and lizardite and amesite specifically, can adopt alternative crystallographic stacking arrangements called polytypes. Polytypism has been extensively studied in fully ordered crystals, but it remains largely enigmatic in the more common semi-disordered crystals that in long-range analyses such as X-ray diffraction only exhibit random combinations of 0b and ±1/3b interlayer shifts. To date, atomic-resolution imaging to identify locally ordered polytypes has been precluded by the beam-sensitive nature of this hydrous magnesium silicate mineral. Here, in this study, we employed low-dose high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to study the polytypic structure of semi-disordered lizardite and amesite. Because the electron dose was as low as ~6000 e–/Å 2 , it was possible to directly resolve oxygen atomic columns and all the cations with a resolution of ~1 Å and reveal the short-range order. For lizardite, we identified long-period non-standard polytypes, including examples with 3, 4, 8, and 9 layers stemming from the ordering of the octahedral tilt along the a-axis. For amesite, we found short-range ordered polytypes with periodicities of up to 42 Å stemming from the ordering of interlayer shifts along the b-axis. The resolution was sufficient to determine the relative abundance of 6R 2 , 6R 1 , 2H 1 , and 2H 2 polytypes in amesite to be 46.1, 29.6, 7.7, and 1.9%, respectively. This is contrary to the expectation that the most common form of amesite is the 2H 2 polytype, which may be more likely to form macroscopic crystals suitable for conventional X-ray diffraction-based studies. We conclude that HAADF-STEM methods open the way for the characterization of beam-sensitive minerals and to resolve the structural details of less well-ordered (but possibly more abundant) minerals at a unit-cell scale.

58 GEOSCIENCES↗

Networks for image acquisition, processing and display

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

Ahumada, Albert J., Jr.↗

Modifying real convolutional codes for protecting digital filtering systems

A novel method is proposed for protecting digital filters from temporary and permanent failures that are not easily detected by conventional fault-tolerant computer design principles, on the basis of the error-detecting properties of real convolutional codes. Erroneous behavior is detected by externally comparing the calculated and regenerated parity samples. Great simplifications are obtainable by modifying the code structure to yield simplified parity channels with finite impulse response structures. A matrix equation involving the original parity values of the code and the polynomial of the digital filter's transfer function is formed, and row manipulations separate this equation into a set of homogeneous equations constraining the modifying scaling coefficients and another set which defines the code parity values' implementation.

Redinbo, G. R.↗

Comparison of Aircraft Models and Integration Schemes for Interval Management in the TRACON

Reusable models of common elements for communication, computation, decision and control in air traffic management are necessary in order to enable simulation, analysis and assurance of emergent properties, such as safety and stability, for a given operational concept. Uncertainties due to faults, such as dropped messages, along with non-linearities and sensor noise are an integral part of these models, and impact emergent system behavior. Flight control algorithms designed using a linearized version of the flight mechanics will exhibit error due to model uncertainty, and may not be stable outside a neighborhood of the given point of linearization. Moreover, the communication mechanism by which the sensed state of an aircraft is fed back to a flight control system (such as an ADS-B message) impacts the overall system behavior; both due to sensor noise as well as dropped messages (vacant samples). Additionally simulation of the flight controller system can exhibit further numerical instability, due to selection of the integration scheme and approximations made in the flight dynamics. We examine the theoretical and numerical stability of a speed controller under the Euler and Runge-Kutta schemes of integration, for the Maintain phase for a Mid-Term (2035-2045) Interval Management (IM) Operational Concept for descent and landing operations. We model uncertainties in communication due to missed ADS-B messages by vacant samples in the integration schemes, and compare the emergent behavior of the system, in terms of stability, via the boundedness of the final system state. Any bound on the errors incurred by these uncertainties will play an essential part in a composable assurance argument required for real-time, flight-deck guidance and control systems,. Thus, we believe that the creation of reusable models, which possess property guarantees, such as safety and stability, is an innovative and essential requirement to assessing the emergent properties of novel airspace concepts of operation.

Neogi, Natasha↗