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At least 1,225 records · Page 68

The effect of grain boundary yield and disconnections on grain boundary fracture strength

During high-temperature interfacial strain, e.g., creep or sintering, grain boundaries will sample non-equilibrium states associated with the non-equilibrium disconnections that mediate strain. This work tests the hypothesis that those non-equilibrium states should affect the mechanical properties of the grain boundary. High-temperature bicrystal tensile strain experiments performed on Sc-doped ZrO 2 as a function of strain rate enable the observation of fracture before and after grain boundary yield. Yielded boundaries exhibit a median fracture strength ≈ 50 % lower than those that did not yield. Molecular dynamics simulations performed on boundaries with and without interstitial-type disconnection loops indicate that the presence of those loops reduce the failure stress.

36 MATERIALS SCIENCE↗

Fracture Failure Analysis for MQXFA Magnet Aluminum Shells

The High-Luminosity LHC Accelerator Upgrade Project (HL-LHC AUP) is approaching the production phase of the US-contributed Q1 and Q3 Interaction Region Quadrupoles (MQXFA). The structures for the MQXFA prototypes were design and inspected by the US-LARP (LHC Accelerator Research Program), AUP developed criteria, which will be used for the pre-series structures. As the first two full-length prototypes with 4.2 m magnetic length, MQXFAP1 and MQXFAP2, were designed and assembled at Lawrence Berkeley National Laboratory (LBNL), and tested at Brookhaven National Laboratory (BNL). The end aluminum short shell of MQXFAP2 was fractured along the shell length during the test, and tests were stopped. Analytical and Finite Element analysis were performed in light of the graded procedure defined in the Structure Design Criteria to investigate the fracture failure for MQXFAP2. In this paper, we report the fracture analysis of the current shell design, including the elasto-plastic simulations with submodel technique, and calculations with Linear Elastic Fracture Mechanics (LEFM). Test material properties are also presented. The results of this analysis explain why the end shell of MQXFAP2 failed, and suggest fillets on the end shell notches to meet the margin specified in the Structural Design Criteria.

43 PARTICLE ACCELERATORS↗

Dynamic Disruption Resilience in Intermodal Transport Networks: Integrating Flow Weighting and Centrality Measures

Resilient intermodal freight networks are vital for sustaining supply chains amid increasing threats from natural hazards and cyberattacks. Transportation resilience has been widely studied; understanding how random and targeted disruptions affect structural connectivity and functional performance remains a key challenge. To address this, this study evaluates the robustness of the US intermodal freight network, which consists of rail and water modes, using a simulation-based framework that integrates graph-theoretic metrics with flow-weighted centrality measures. Disruption scenarios are examined, including random failures as well as targeted node and edge removals based on static and dynamically updated degree and betweenness centrality. To reflect more realistic conditions, flow-weighted degree centralities (WDC) and partial node degradation are considered. Two resilience indicators are used: (1) the size of the giant connected component to measure structural connectivity; and (2) flow-weighted network efficiency (NE) to assess freight mobility under disruption. The results show that progressively degrading nodes ranked by WDC to 60% of their original functionality causes a sharper decline in normalized NE, for up to approximately 45 affected nodes, than complete failure (100% loss of functionality) applied to nodes targeted by weighted betweenness centrality or selected at random. This highlights how partial degradation of high-tonnage hubs can produce disproportionately large functional losses. The findings emphasize the need for resilience strategies that go beyond network topology to incorporate freight flow dynamics.

42 ENGINEERING↗

Dataset for manuscript "Consequences of the failure of equipartition for the p-V behavior of liquid water and the hydration free energy components of a small protein"

Previously, we showed that in the molecular dynamics simulation of a rigid model of water it is necessary to use an integration time-step dt that is less than or equal to 0.5 fs to ensure equipartition between translational and rotational modes. We extended that study in the NVT ensemble to NpT conditions and to an aqueous protein. We study neat liquid water with the rigid, SPC/E model and the protein BBA (PDB ID: 1FME) solvated in the rigid, TIP3P model. We examined integration time-steps ranging from 0.5 fs to 4.0 fs for various thermostat plus barostat combinations. We find that a small time-step, dt, is necessary to ensure consistent prediction of the simulation volume. Hydrogen mass repartitioning alleviates the problem somewhat, but is ineffective for the typical time-step used with this approach. The compressibility, a measure of volume fluctuations, is seen to be sensitive to dt. Using the mean volume estimated from the NpT simulation, we examined the electrostatic and van der Waals contribution to the hydration free energy of the protein in the NVT ensemble. These contributions are also sensitive to dt. In going from a time-step of 2 fs to a time-step of 0.5 fs, the change in the net electrostatic plus van der Waals contribution to the hydration of BBA is already in excess of the folding free energy reported for this protein. The data-set contains the simulation metadata and log files that support the claims noted above.

59 BASIC BIOLOGICAL SCIENCES↗

Competitive evaluation of failure detection algorithms for strapdown redundant inertial instruments

Algorithms for failure detection, isolation, and correction of redundant inertial instruments in the strapdown dodecahedron configuration are competitively evaluated in a digital computer simulation that subjects them to identical environments. Their performance is compared in terms of orientation and inertial velocity errors and in terms of missed and false alarms. The algorithms appear in the simulation program in modular form, so that they may be readily extracted for use elsewhere. The simulation program and its inputs and outputs are described. The algorithms, along with an eight algorithm that was not simulated, also compared analytically to show the relationships among them.

Wilcox, J. C.↗

Similarity constraints in testing of cooled engine parts

A study is made of the effect of testing cooled parts of current and advanced gas turbine engines at the reduced temperature and pressure conditions which maintain similarity with the engine environment. Some of the problems facing the experimentalist in evaluating heat transfer and aerodynamic performance when hardware is tested at conditions other than the actual engine environment are considered. Low temperature and pressure test environments can simulate the performance of actual size prototype engine hardware within the tolerance of experimental accuracy if appropriate similarity conditions are satisfied. Failure to adhere to these similarity constraints because of test facility limitations or other reasons, can result in a number of serious errors in projecting the performance of test hardware to engine conditions.

Colladay, R. S.↗

Deep flaws in weldments of aluminum and titanium

Surface flawed specimens of 2219-T87 and 6Al-4V STA titanium weldments were tested to determine static failure modes, failure strength, and fatigue flaw growth characteristics. Thicknesses selected for this study were purposely set at values where, for most test conditions, abrupt instability of the flaw at fracture would not be expected. Static tests for the aluminum weldments were performed at room, LN2 and LH2 temperatures. Titanium static tests for tests were performed at room and LH2 temperatures. Results of the static tests were used to plot curves relating initial flaw size to leakage- or failure-stresses (i.e. "failure" locus curves). Cyclic tests, for both materials, were then performed at room temperature, using initial flaws only slightly below the previously established failure locus for typical proof stress levels. Cyclic testing was performed on pairs of specimens, one with and one without a simulated proof test cycle. Comparisons were made then to determine the value and effect of proof testing as affected by the various variables of proof and operating stress, flaw shape, material thickness, and alloy.

Masters, J. N.↗

Qualitative differences between on-orbit and transition RCS control

Two separate reaction control system (RCS) digital autopilots (DAPs) evolved from one original Space Shuttle orbital autopilot concept. A computer overload forced this evolution. Part of the overload problem was due to unique performance requirements imposed on the RCS controller during each of several different flight regimes. The two resultant RCS DAPs yield different effector responses because they rely on different sources of sensory input and they process data differently. This paper describes the evolution of the two RCS controllers and illustrates their behavioral differences. The transition autopilot, used in orbital insertion and deorbit, is sensitive to orbiter flexure due to its feedthrough character. The on-orbit autopilot is sensitive to transient rate control degradation from large disturbances due to feed-forward rate estimation. Simulation results and flight data are used to illustrate performance differences between the two autopilots under various conditions. These include computer failures where electronic stringing and procedural reconfiguration differences affect autopilot behavior.

Hattis, P. D.↗

Reliability and maintenance simulation of the Hubble Space Telescope

An analytical approach is presented which was developed and implemented at MSFC specifically for the Space Telescope Program to provide comparisons of critical item failures, system downstates, on-orbit servicing versus return for ground maintenance, overall system downtime, and to obtain a measure of expected uptime for science functions.

Pizzano, F.↗

A simulation-based fault injection experiment to evaluate self-test diagnostics for a fault-tolerant computer

The design and results of a fault injection experiment conducted in the Airlab facility at NASA-Langley using a logic network simulator are described. An attempt was made to determine the effectiveness of the diagnostic self-test sequences used to detect failures in the communicator/interstage (C/I) of a fault-tolerant processor (FTP). Identification of the undetected faults in the C/I Status Register logic resulted in changes in the diagnostic test sequences implemented for the FTP.

Baker, Robert L.↗

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

Dufrene, Warren R., Jr.↗

High-Fidelity Modeling for Health Monitoring in Honeycomb Sandwich Structures

High-Fidelity Model of the sandwich composite structure with real geometry is reported. The model includes two composite facesheets, honeycomb core, piezoelectric actuator/sensors, adhesive layers, and the impactor. The novel feature of the model is that it includes modeling of the impact and wave propagation in the structure before and after the impact. Results of modeling of the wave propagation, impact, and damage detection in sandwich honeycomb plates using piezoelectric actuator/sensor scheme are reported. The results of the simulations are compared with the experimental results. It is shown that the model is suitable for analysis of the physics of failure due to the impact and for testing structural health monitoring schemes based on guided wave propagation.

Luchinsky, Dimitry G.↗

Single-Event Gate Rupture in Power MOSFETs: A New Radiation Hardness Assurance Approach

Almost every space mission uses vertical power metal-semiconductor-oxide field-effect transistors (MOSFETs) in its power-supply circuitry. These devices can fail catastrophically due to single-event gate rupture (SEGR) when exposed to energetic heavy ions. To reduce SEGR failure risk, the off-state operating voltages of the devices are derated based upon radiation tests at heavy-ion accelerator facilities. Testing is very expensive. Even so, data from these tests provide only a limited guide to on-orbit performance. In this work, a device simulation-based method is developed to measure the response to strikes from heavy ions unavailable at accelerator facilities but posing potential risk on orbit. This work is the first to show that the present derating factor, which was established from non-radiation reliability concerns, is appropriate to reduce on-orbit SEGR failure risk when applied to data acquired from ions with appropriate penetration range. A second important outcome of this study is the demonstration of the capability and usefulness of this simulation technique for augmenting SEGR data from accelerator beam facilities. The mechanisms of SEGR are two-fold: the gate oxide is weakened by the passage of the ion through it, and the charge ionized along the ion track in the silicon transiently increases the oxide electric field. Most hardness assurance methodologies consider the latter mechanism only. This work demonstrates through experiment and simulation that the gate oxide response should not be neglected. In addition, the premise that the temporary weakening of the oxide due to the ion interaction with it, as opposed to due to the transient oxide field generated from within the silicon, is validated. Based upon these findings, a new approach to radiation hardness assurance for SEGR in power MOSFETs is defined to reduce SEGR risk in space flight projects. Finally, the potential impact of accumulated dose over the course of a space mission on SEGR susceptibility is explored. SEGR evaluation of gamma-irradiated power MOSFETs suggests a non-significant SEGR susceptibility enhancement due to accumulated dose from gamma rays. During SEGR testing, an unexpected enhanced dose effect from heavy-ion irradiation was detected. We demonstrate that this effect could be due to direct ionization by two or more ions at the same channel location. The probability on-orbit for such an occurrence is near-zero given the low heavy-ion fluence over a typical mission lifetime, and did not affect SEGR susceptibility. The results of this work can be used to bound the risk of SEGR in power MOSFETs considered for insertion into spacecraft and instruments.

Lauenstein, Jean-Marie↗

A Failure Propagation Modeling Method for Launch Vehicle Safety Assessment

A method has been developed with the objective of making the potentially intractable problem of launch vehicle failure propagation somewhat less intractable. The approach taken is to essentially decouple the potentially multi-stepped propagation process into a series of bi-component transition probabilities. These probabilities are then used within a simple Monte Carlo simulation process through which the more complex behavior evolves. The process is described using a simple model problem and some discussion of enhancements for real-world applications is included. The role of the model within a broader analysis process for assessing abort effectiveness from launch vehicle failure modes is also described.

Lawrence, Scott↗

The impacts of horizontal resolution on the seasonally-dependent biases of the northeastern Pacific ITCZ in coupled climate models.

Double-ITCZ has puzzled climate model community for more than two decades. Here, we found that over the eastern Pacific, precipitation and sea surface temperature (SST) biases in the NCAR CESM1 are seasonally-dependent, with positive (negative) precipitation/SST biases during boreal summer/fall (winter/spring), although the easterly wind bias persists around the year. This seasonally-dependent bias of precipitation/SST is found to be caused by the failure of the model to reproduce the climatological seasonal wind reversal of North American monsoon. During winter/spring, the climatological easterly wind dominates, so the stronger wind speed in the model enhances the evaporation and lowers the SST. It is opposite when the climatological wind turns to westerly during summer/fall. The easterly wind bias also occurs in the atmospheric model when the observation SST is prescribed, suggesting it is of atmospheric origin. Further, the easterly wind bias is mainly evident in the lower troposphere and quite independent of time, implying the effect of complex and narrow-ranged Central American topography, which is not depicted well in the coarse model resolution. When the model resolution is doubled, both SST and precipitation are improved with the reduced easterly wind bias. During boreal spring, when ITCZ bias is most significant, the northern and southern ITCZ can be improved by 29% and 18.8% respectively in the higher resolution. Finally, we suggest that these seasonally-dependent biases over the eastern Pacific are quite universal among 37 CMIP5 coupled models, and the ongoing CMIP6 project will provide a valuable opportunity to examine whether the bias can be reduced by increasing model resolution.

Song, Fengfei↗

Quantifying shifts in natural selection on codon usage between protein regions: a population genetics approach

Codon usage bias (CUB), the non-uniform usage of synonymous codons, occurs across all domains of life. Adaptive CUB is hypothesized to result from various selective pressures, including selection for efficient ribosome elongation, accurate translation, mRNA secondary structure, and/or protein folding. Given the critical link between protein folding and protein function, numerous studies have analyzed the relationship between codon usage and protein structure. The results from these studies have often been contradictory, likely reflecting the differing methods used for measuring codon usage and the failure to appropriately control for confounding factors, such as differences in amino acid usage between protein structures and changes in the frequency of different structures with gene expression. Here we take an explicit population genetics approach to quantify codon-specific shifts in natural selection related to protein structure in S. cerevisiae and E. coli. Unlike other metrics of codon usage, our approach explicitly separates the effects of natural selection, scaled by gene expression, and mutation bias while naturally accounting for a region’s amino acid usage. Bayesian model comparisons suggest selection on codon usage varies only slightly between helix, sheet, and coil secondary structures and, similarly, between structured and intrinsically-disordered regions. Similarly, in contrast to previous findings, we find selection on codon usage only varies slightly at the termini of helices in E. coli. Using simulated data, we show this previous work indicating “non-optimal” codons are enriched at the beginning of helices in S. cerevisiae was due to failure to control for various confounding factors (e.g. amino acid biases, gene expression, etc.), and rather than selection to modulate cotranslational folding. Our results reveal a weak relationship between codon usage and protein structure, indicating that differences in selection on codon usage between structures are slight. In addition to the magnitude of differences in selection between protein structures being slight, the observed shifts appear to be idiosyncratic and largely codon-specific rather than systematic reversals in the nature of selection. Overall, our work demonstrates the statistical power and benefits of studying selective shifts on codon usage or other genomic features from an explicitly evolutionary approach. Limitations of this approach and future potential research avenues are discussed.

59 BASIC BIOLOGICAL SCIENCES↗

Physics-Based Method for Generating Fully Synthetic IV Curve Training Datasets for Machine Learning Classification of PV Failures

Classification machine learning models require high-quality labeled datasets for training. Among the most useful datasets for photovoltaic array fault detection and diagnosis are module or string current-voltage (IV) curves. Unfortunately, such datasets are rarely collected due to the cost of high fidelity monitoring, and the data that is available is generally not ideal, often consisting of unbalanced classes, noisy data due to environmental conditions, and few samples. In this paper, we propose an alternate approach that utilizes physics-based simulations of string-level IV curves as a fully synthetic training corpus that is independent of the test dataset. In our example, the training corpus consists of baseline (no fault), partial soiling, and cell crack system modes. The training corpus is used to train a 1D convolutional neural network (CNN) for failure classification. The approach is validated by comparing the model’s ability to classify failures detected on a real, measured IV curve testing corpus obtained from laboratory and field experiments. Results obtained using a fully synthetic training dataset achieve identical accuracy to those obtained with use of a measured training dataset. When evaluating the measured data’s test split, a 100% accuracy was found both when using simulations or measured data as the training corpus. When evaluating all of the measured data, a 96% accuracy was found when using a fully synthetic training dataset. The use of physics-based modeling results as a training corpus for failure detection and classification has many advantages for implementation as each PV system is configured differently, and it would be nearly impossible to train using labeled measured data.

Hopwood, Michael W. (ORCID:0000000161901767)↗

Material Interactions in Severe Accidents – Benchmarking the MELCOR V2.2 Eutectics Model for a BWR-3 Mark-I Station Blackout: Part II – Uncertainty Analysis

Single case comparisons between severe accident simulations can provide detailed insights into severe accident model behavior, however, they cannot offer insights into model uncertainty, sensitivity to uncertain parameters, or underlying model biases.Here in this analysis, the single case benchmark comparison of the MELCOR material interaction models for a station blackout (SBO) scenario of a boiling water reactor (BWR) using representative Fukushima Daiichi Unit 1 boundary conditions is expanded to include an uncertainty analysis. As part of this uncertainty analysis, 1200 simulations are performed for each material interaction model (2400 total), with random sampling of 14 uncertain MELCOR input parameters. Input parameters are selected for their impact on models representing core degradation processes. These include candling, fuel rod failure, debris quenching and dryout. The analysis performed here is not a traditional “best-estimate” uncertainty analysis that uses best-estimate parameters or identifies best-estimate figure of merit distributions. Instead, it is an exploratory uncertainty analysis that identifies and interrogates underlying model form biases of the two material interaction models (eutectics and interactive materials models). Uniform distributions are applied to all uncertain parameters to ensure coverage of the model parameter uncertainty space. Key findings from this study include underlying model form biases exhibited by material interaction models, and notable differences in accident progression outcomes between the material interaction models. This uncertainty study extends and confirms the conclusions from the first part of this study, which compared the impact of material interaction modeling on simulation of a short-term station blackout scenario with representative Fukushima Daiichi Unit I boundary conditions. In particular, this study confirms that the eutectics model generally exhibits accelerated degradation and failure of fuel components, the core plate, and the lower head. The eutectics model also has a tendency to exhibit a greater degree of core degradation, greater debris mass formation, and larger debris mass ejection. Finally, the eutectics model exhibits higher maximum temperatures for fuel, cladding, particulate debris, oxidic molten pool, and metallic molten pool components than the interactive materials model; interactive materials model simulations exhibit a soft “limitation” on maximum temperatures that is related to the temperature at which material relocation occurs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗