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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Deformation mechanisms of Cu nanowires with planar defects

Molecular dynamics simulations are used to investigate the mechanical behavior of Cu nanowires (NWs) with planar defects such as grain boundaries (GBs), twin boundaries (TBs), stacking faults (SFs), etc. To investigate how the planar defects affect the deformation and fracture mechanisms of naowires, three types of nanowires are considered in this paper: (1) polycrystalline Cu nanowire; (2) single-crystalline Cu nanowire with twin boundaries; and (3) single-crystalline Cu nanowire with stacking faults. Because of the large fraction of atoms at grain boundaries, the energy of grain boundaries is higher than that of the grains. Thus, grain boundaries are proved to be the preferred sites for dislocations to nucleate. Moreover, necking and fracture prefer to occur at the grain boundary interface owing to the weakness of grain boundaries. For Cu nanowires in the presence of twin boundaries, it is found that twin boundaries can strength nanowires due to the restriction of the movement of dislocations. The pile up of dislocations on twin boundaries makes them rough, inducing high energy in twin boundaries. Hence, twin boundaries can emit dislocations, and necking initiates at twin boundaries. In the case of Cu nanowires with stacking faults, all pre-existing stacking faults in the nanowires are observed to disappear during deformation, giving rise to a fracture process resembling the samples without stacking fault.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2013

Report on Hydrologic Flow in Low-Permeability Media

We demonstrate that under normal conditions (under which there are no intersections between tunnels/drifts and conductive geological structures, such as faults), the water flow velocity in the damage zone, as a result of non-Darcian flow behavior, is extremely small such that solute transport is dominated by diffusion, rather than advection. We show that unless non-Darcian flow behavior is considered, significant errors can occur in the “measured” relative-permeability values. We propose a hypothesis to consider the temperature impact based on limited test results from the petroleum literature. To consider the bedding effects, we present an empirical relationship between water flux and hydraulic gradient for non-Darcian water flow in anisotropic cases.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Machine Learning for Anomaly Detection in Neural Network Security and SRF Cavities

This dissertation explores the development and deployment of machine learning approaches to address critical challenges in anomaly detection across two distinct domains: neural network security in federated learning settings and cavity behavior analysis in particle accelerator operations at Jefferson Lab in Newport News, Virginia. Anomaly detection identifies deviations from expected patterns, safeguarding systems in cybersecurity, industry, and research against malicious activities and failures. This dissertation demonstrates how our machine learning approaches enhance detection accuracy and efficiency in both neural network security and industrial applications. First, we investigate vulnerabilities in deep neural networks deployed in federated learning. Although federated learning preserves user privacy by training models locally, it remains vulnerable to backdoor attacks, in which malicious participants embed hidden triggers that induce targeted misbehavior. We propose a self-supervised contrastive learning framework to detect and mitigate such backdoor attacks. In our experiments, this method achieves higher detection accuracy and lower false positive rates than existing defenses, while operating without access to local model updates or original training data and thus preserving the privacy guarantees of the federated setting. Second, we address the operational reliability of superconducting radio-frequency (SRF) cavities at the Continuous Electron Beam Accelerator Facility (CEBAF). Our research leverages an unsupervised learning approach, combined with Principal Component Analysis (PCA) and k-means clustering, to identify anomalous behaviors in SRF cavities. Our method detects subtle anomalous behavior by analyzing SRF signal data. This knowledge allows for the early detection and resolution of potential faults, significantly improving the efficiency and reliability of operations. Third, we extend these insights to time-series anomaly detection more broadly. We design a contrastive-learning based model tailored to increasingly dynamic environments and academic research. This model improves detection accuracy in settings that require real-time monitoring and predictive maintenance. Our research underscores the broader applicability and impact of advanced machine learning techniques in anomaly detection. By extracting meaningful patterns from complex data, machine learning can significantly enhance security in distributed neural networks and improve the efficiency of particle accelerator operations. This dissertation serves as a stepping stone for future investigations into the vast possibilities of anomaly detection, inspiring further exploration and development of machine learning techniques in this field.

Ferguson, Hal [Old Dominion University]↗
NASA NTRS1985

Evaluation of fault-tolerant system performance by approximate techniques

An approximate method for calculating the statistics of the performance of a fault-tolerant system is developed. An approximate method is necessary because the statistical model of the system behavior is large-scale and the time horizon of interest encompasses many cycles of the Redundancy Management logic. In the development, a compact representation of the necessary information called the v-transform is introduced and discussed. Based upon this representation, an approximation that leads to a very efficient computational procedure is suggested and numerically analyzed. A very brief discussion of other related work is also presented.

Walker, B. K.↗
NASA NTRS1985

Determination of the gaseous hydrogen ductile-brittle transition in copper-nickel alloys

A series of copper-nickel alloys were fabricated, notched tensile specimens machined for each alloy, and the specimens tested in 34.5 MPa hydrogen and in air. A notched tensile ratio was determined for each alloy and the hydrogen environment embrittlement (HEE) determined for the alloys of 47.7 weight percent nickel to 73.5 weight percent nickel. Stacking fault probability and stacking fault energies were determined for each alloy using the x ray diffraction line shift and line profiles technique. Hydrogen environment embrittlement was determined to be influenced by stacking fault energies; however, the correlation is believed to be indirect and only partially responsible for the HEE behavior of these alloys.

Parr, R. A.↗
NASA NTRS1992

Failure behavior identification for a space antenna via neural networks

By using neural networks, a method for the failure behavior identification of a space antenna model is investigated. The proposed method uses three stages. If a fault is suspected by the first stage of fault detection, a diagnostic test is performed on the antenna. The diagnostic test results are used by the second and third stages to identify which fault occurred and to diagnose the extent of the fault, respectively. The first stage uses a multilayer perceptron, the second stage uses a multilayer perceptron and neural networks trained with the quadratic optimization algorithm, a novel training procedure, and the third stage uses backpropagation trained neural networks.

Sartori, Michael A.↗
NASA NTRS2015

A Structural Model Decomposition Framework for Hybrid Systems Diagnosis

Nowadays, a large number of practical systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete modes of behavior, each defined by a set of continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task very challenging. In this work, we present a new modeling and diagnosis framework for hybrid systems. Models are composed from sets of user-defined components using a compositional modeling approach. Submodels for residual generation are then generated for a given mode, and reconfigured efficiently when the mode changes. Efficient reconfiguration is established by exploiting causality information within the hybrid system models. The submodels can then be used for fault diagnosis based on residual generation and analysis. We demonstrate the efficient causality reassignment, submodel reconfiguration, and residual generation for fault diagnosis using an electrical circuit case study.

structural model decomposition↗
NASA NTRS2016

Health Monitoring of a Planetary Rover Using Hybrid Particle Petri Nets

This paper focuses on the application of a Petri Net-based diagnosis method on a planetary rover prototype.The diagnosis is performed by using a model-based method in the context of health management of hybrid systems.In system health management, the diagnosis task aims at determining the current health state of a system and the fault occurrences that lead to this state. The Hybrid Particle Petri Nets (HPPN) formalism is used to model hybrid systems behavior and degradation, and to define the generation of diagnosers to monitor the health states of such systems under uncertainty. At any time, the HPPN-based diagnoser provides the current diagnosis represented by a distribution of beliefs over the health states. The health monitoring methodology is demonstrated on the K11 rover. A hybrid model of the K11 is proposed and experimental results show that the approach is robust to real system data and constraints.

health monitoring↗
DOE OSTI2025

Control Mechanisms for Self‐Sealing in Activated Clay‐Rich Faults Through Controlled Hydraulic Injection Experiment

Abstract In a high‐pressure injection fault activation experiment conducted at the Mont Terri underground research laboratory in Switzerland, the transmissivity of the Opalinus Clay fault significantly increased due to opening and shearing. The fluid injection, spanning a few hours, generated a 10 m radius fault activation patch. Subsequent pressure pulse tests conducted bi‐weekly for a year revealed the gradual return of fault transmissivity to its initial state. The study utilized fluid pressure decay analysis, optical fiber monitoring, continuous active source seismic measurements and borehole displacement sensors for measuring fault displacements. The fault zone exhibited a dilation of approximately 1.4 mm, associated with both normal and tangential movements during activation, resulting in a sudden transmissivity increase from 1 × 10 −12 to 3.2 × 10 −7 m 2 /s. Early post‐activation, transient compaction and the subsequent slow compaction were observed, transitioning to an extension regime. The pressure pulse tests demonstrated a rapid transmissivity drop by more than two orders of magnitude within the first 10 days, followed by a gradual and less pronounced decrease. Plastic shear and compaction dominated the transmissivity evolution until 70 days after injection ended, followed by a period where additional factors, such as clay mineral swelling, influenced the behavior. Extrapolation suggested a sealing process taking at least 50 years after the initial activation. Plain Language Summary A field‐scale fault activation experiment offers valuable insights into the elasto‐plastic processes governing the sealing of shale faults. The experiment reveals a rapid increase in the fault's transmissivity by approximately five orders of magnitude during activation. Subsequent observations show a gradual transmissivity decrease by about three orders of magnitude post‐activation, with slow long‐term plastic shear and compaction of the fault competing against secondary processes, notably clay mineral swelling. All conceptual models employed to interpret these field data converge on the estimation that the fault's return to its initial low transmissivity state would require a minimum of 50 years. Key Points High‐pressure injection fault activation experiment at the Mont Terri underground research laboratory Continuous transmissivity measurements record self‐sealing inside a clay‐rich fault zone Transmissivity undergoes a phase of domination by slow plastic compaction and shearing during the initial post‐activation period, with mineral swelling exerting its influence over the long term

Guglielmi, Yves↗
NASA NTRS1986

An artificial intelligence approach to onboard fault monitoring and diagnosis for aircraft applications

Real-time onboard fault monitoring and diagnosis for aircraft applications, whether performed by the human pilot or by automation, presents many difficult problems. Quick response to failures may be critical, the pilot often must compensate for the failure while diagnosing it, his information about the state of the aircraft is often incomplete, and the behavior of the aircraft changes as the effect of the failure propagates through the system. A research effort was initiated to identify guidelines for automation of onboard fault monitoring and diagnosis and associated crew interfaces. The effort began by determining the flight crew's information requirements for fault monitoring and diagnosis and the various reasoning strategies they use. Based on this information, a conceptual architecture was developed for the fault monitoring and diagnosis process. This architecture represents an approach and a framework which, once incorporated with the necessary detail and knowledge, can be a fully operational fault monitoring and diagnosis system, as well as providing the basis for comparison of this approach to other fault monitoring and diagnosis concepts. The architecture encompasses all aspects of the aircraft's operation, including navigation, guidance and controls, and subsystem status. The portion of the architecture that encompasses subsystem monitoring and diagnosis was implemented for an aircraft turbofan engine to explore and demonstrate the AI concepts involved. This paper describes the architecture and the implementation for the engine subsystem.

Schutte, P. C.↗
DOE OSTI2014

A Mechanism-based Model for Deformation Twinning in Polycrystalline FCC Steel

Deformation twinning, a common and important plastic deformation mechanism, is the key contributor to the excellent combination of strength and ductility in twinning-induced plasticity (TWIP) steel. In the open literature, a significant amount of research has been reported on the microstructural characteristics of deformation twinning and its influence on the overall deformation behavior of TWIP steel. In this study, we examine the feasibility of a mechanism-based crystal plasticity model in simulating the microstructural level deformation characteristics of TWIP steel. To this end, a model considering both double-slip and double-twin is developed to investigate the stress-strain behavior and local microstructural features related to the formation and growth of micro-twins in low stacking fault energy (SFE) TWIP steel. The twin systems are described as pseudo-slips that can be activated when their resolved shear stress reaches the corresponding critical value. A hardening law that accounts for the interaction among the slip and twin systems is also developed. Numerical simulations for dDifferent mesh sizes and single crystal patch tests under different loading modes are carried out to verify the modeling procedure. Our simulation results reveal that, despite its simple nature, the double-slip/double-twin model can capture the key deformation features of TWIP steel, including twin volume fraction evolution, continuous strain hardening, and the final fracture in the form of strain localization.

Environmental Molecular Sciences Laboratory↗
NASA NTRS1988

Chronic stress as a factor in aircraft mishaps

Naval aviation is an unusually stressful career because of the inherent demands of the work. Stress is recognized as a cause of mishaps which involve pilot error. A questionnaire was adapted from Rahe and Homes' list of stressful life events in order to determine the relationship between pilot behavioral, personality, and life change factors on the one hand and responsibility for accidents on the other. A number of factors regarding interpersonal relationships, changes in personal behavior, personality factors, and life changes were found to discriminate between pilots who were and were not at fault in accidents.

Alkov, Robert A.↗
DOE OSTI2024

Tracking Seismic Velocity Perturbations at Ridgecrest Using Ballistic Correlation Functions

Abstract We present results based on data of a dense nodal array composed of 147 stations, deployed in 2022 near the epicenter of the 2019 Mw 7.1 Ridgecrest earthquake to investigate characteristics of the seismic wavefields. Through array analyses, we identified two primary components. First, we observed far-field P waves dominating the 0.5–1.2 Hz frequency range, which are likely primarily generated by wind-driven oceanic swell activity. Second, we detected near-field body waves resulting from anthropogenic activities in the frequency range 2–8 Hz. We examined noise correlation functions derived from data of the dense deployment and regional stations to explore fault-zone seismic velocity changes using ballistic arrivals, with a focus on velocity perturbation shortly before and after the Ridgecrest earthquake sequence. Our findings exhibit distinct behavior compared to results obtained through standard coda-wave interferometry. Particularly, we observed a decrease in P-wave travel time on certain station pairs prior to the 2019 earthquake sequence. Supported by detailed investigation of the local seismic wavefields, we interpret the decreasing P-wave travel time as likely caused by a velocity increase away from the fault, possibly related to fluid migration. However, additional information is necessary to verify this hypothesis.

Geochemistry & Geophysics↗
DOE OSTI2023

The Role of Clay in Limiting Frictional Healing in Fault Gouges

Abstract Frictional healing is fundamental to the seismic cycle and plays a role in the energy balance, dynamics, and recurrence interval of earthquakes and slow slip events. Although the healing behavior of quartz has been studied extensively, the role of clay content is less understood. We tested synthetic mixtures of quartz and smectite (10%–100% smectite) in a double‐direct shear configuration to measure frictional healing. We show that the magnitude and rate of healing decreases systematically with higher clay content (from 0.008/decade at 10% smectite to 0.002/decade at 100% smectite). Healing scales with both the magnitude of stress relaxation during holds and layer‐normal compaction of the gouge. We suggest this reflects the alignment of clay minerals, leading to saturation of the real area of contact that limits restrengthening during holds. The low healing rates of clay‐rich faults—together with rate‐neutral to rate‐strengthening friction—should promote frequent, small failures or stable sliding.

58 GEOSCIENCES↗
DOE OSTI2014

Radiation induced effects on mechanical properties of nanoporous gold foams

Previously, it was demonstrated that due to a high surface-to-volume ratio, nanoporous materials display radiation tolerance. The abundance of surfaces, which are perfect sinks for defects, and the relation between ligament size, defect diffusion, and time combine to define a window of radiation resistance [Fu et al., Appl. Phys. Lett. 101, 191607 (2012)]. Outside this window, the dominant defect created by irradiation in Au nanofoams are stacking fault tetrahedra (SFT). Molecular dynamics computer simulations of nanopillars, taken as the elemental constituent of foams, predict that SFTs act as dislocation sources inducing softening, in contrast to the usual behavior in bulk materials, where defects are obstacles to dislocation motion, producing hardening. In this work we test that prediction and answer the question whether irradiation actually hardens or softens a nanofam. Ne ion irradiations of gold nanofoams were performed at room temperature for a total dose up to 4 dpa, and their mechanical behavior was measured by nanoindentation. We observe that hardness increases after irradiation, a result that we analyze in terms of the role of SFTs on the deformation mode of foams.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exploring the deformation behavior of nanotwinned Al–Zr alloy via in situ compression

Nanotwinned metals have demonstrated the capacity for concomitant high strength and ductility. However, metals with high stacking fault energies, such as aluminum (Al), have a low propensity for twin formation. Here, we show the fabrication of supersaturated solid-solution Al–Zr alloys with a high density of growth twins. Incoherent twin boundaries (ITBs) are strong barriers to dislocation motion, while mobile partial dislocations promote plasticity. These deformable nanotwinned Al–Zr alloys reach a flow stress of ∼1 GPa, as demonstrated using in situ micropillar compression tests. Density functional theory calculations uncover the role Zr solute plays in the formation and deformation of the nanotwinned microstructure. This study features a strategy for incorporating ITBs and 9R phase into Al alloys for simultaneous benefits to strength and deformability.

Richter, N. A. (ORCID:0000000332732276)↗
DOE OSTI2018

Evaluating the Loss of Communications in Distribution Protection Systems using GridLAB-D

Protection in distribution systems is vital for maintaining reliability and ensuring proper power quality is provided to the end-use customer. As more switching devices are deployed on distribution systems, traditional protection schemes are giving way to more advanced, and sometimes centrally coordinated, protection schemes that rely on communications infrastructure. With these communications-dependent systems, the behaviors of the protection with and without the communications infrastructure must be examined. This work has evaluated the impacts of loss of communication in centrally coordinated protection schemes. Two test cases were examined: a sequence of similar faults on a feeder before and after a topology reconfiguration, and a feeder with a photovoltaic (PV) fault current contribution. Both simulations are run in the GridLAB-D™ simulation environment. A simple connectivity model is used to represent communication status. The results reveal that a failure of the communication system can cause significantly different protection behavior. This analysis can be used as a basis for utility engineers to make an informed decision on the impacts of communication losses on their system, as well as evaluating ways to mitigate its impact on the resiliency of the system.

GridLAB-D, Distribution Analysis↗
DOE OSTI2015

Scalability under a Power Bound using the GREMLINs Framework

With the move towards exascale, system and software developers will have to deal with issues of extreme parallelism. The system properties affected most by the increase in node and core count are the shared resources on node and across the system. The increase in parallelism leads to reduced memory and bandwidth when regarding individual cores. Since power is a limiting factor for supercomputers, and power is not fully utilized in current systems, overprovisioning compute resources is a viable approach to maximized power utilization. To maximize system performance in regard to these changing conditions, it is necessary to understand how resource restrictions impact performance and system behavior. For the purpose of understanding anticipated system properties the GREMLINs Framework was developed. The framework gives the opportunity to add power restrictions, hinder memory properties and introduce faults to study resilience, among others. These features give the opportunity to use current petascale technology to study problems system designers and software developers will have to face when moving towards exascale and beyond. This work describes the initial release of the GREMLINs Framework, developed for this work, and shows how it can be used to study the scaling behavior of proxy applications. These proxy applications represent a selection of HPC workloads important to the scientific community. The proxy applications studied are AMG2013, an algebraic multi-grid linear system solver, CoMD, a classical molecular dynamics proxy application and NEKBONE, an application that uses a high order spectral element method to solve the Navier-Stokes equations. The main interest of these studies lies in analysis regarding their power behavior at scale under a power bound. These findings show how the GREMLINs Framework can help systems and software designers to attain better application performance and can also be used as basis for CPU power balancing tools to use power more efficiently.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗