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At least 397 records · Page 22

Using Rollback Avoidance to Mitigate Failures in Next-Generation Extreme-Scale Systems

High-performance computing (HPC) systems enable scientists to numerically model complex phenomena in many important physical systems. The next major milestone in the development of HPC systems is the construction of the rst supercomputer capable executing more than an exa op, 10 18 oating point operations per second. On systems of this scale, failures will occur much more frequently than on current systems. As a result, resilience is a key obstacle to building next-generation extremescale systems. Coordinated checkpointing is currently the most widely-used mechanism for handling failures on HPC systems. Although coordinated checkpointing remains e ective on current systems, increasing the scale of today's systems to build next-generation systems will increase the cost of fault tolerance as more and more time is taken away from the application to protect against or recover from failure. Rollback avoidance techniques seek to mitigate the cost of checkpoint/restart by allowing an application to continue its execution rather than rolling back to an earlier checkpoint when failures occur. These techniqes include failure prediction and preventive migration, replicated computation, fault-tolerant algorithms, and softwarebased memory fault correction. In this thesis, we examine how rollback avoidance techniques can be used to address failures on extreme-scale systems. Using a combination of analytic modeling and simulation, we evaluate the potential impact of rollback avoidance on these systems. We then present a novel rollback avoidance technique that exploits similarities in application memory. Finally, we examine the feasibility of using this technique to protect against memory faults in kernel memory.

97 MATHEMATICS AND COMPUTING↗

Methods, apparatus and system for notification of predictable memory failure

A method for providing notification of a predictable memory failure includes the steps of: obtaining information regarding at least one condition associated with a memory; calculating a memory failure probability as a function of the obtained information; calculating a failure probability threshold; and generating a signal when the memory failure probability exceeds the failure probability threshold, the signal being indicative of a predicted future memory failure.

97 MATHEMATICS AND COMPUTING↗

Failure Analysis on Multivariate Time-series Data given Uncertain Labels

Machine failure analysis and detection is critical to today’s industrial society. Given a number of failure events on multivariate temporal data, the ability to identify 1) the discriminative patterns prior to the events and 2) the most relevant features to the failure has practical use for early warning and root cause analysis. However, since these patterns are not necessarily adjacent to the onset of failure in time, faulty labels are often with uncertainty, which makes traditional supervised detection methods inapplicable. To address the label uncertainty and learn the complicated correlation in multivariate time series, we design Failure Analysis on Multivariate Time-series Data (MAMT) that jointly selects the most failure-relevant features and time-instances by a novel dynamic and directional label diffusion process. Extensive experiments demonstrate that MAMT is more effective while more efficient than popular baselines.

97 MATHEMATICS AND COMPUTING↗

Probabilistic Risk Assessment of Spent Fuel Pool Cooling System Failure Considering Safety and Security Initiating Events

In order to quantify the probable risk associated with a safety system, nuclear safety risk evaluation process is applied which is generally performed in three steps. The first step is to calculate the damage frequency of a critical system. This step is followed by the radioactive source term estimation due to the potential system damage. The final step is the assessment of off-site consequences. The safety risk formula is shown by Eq. (1). P{sub F} is the probability of safety system failure (the probability used describes a random, independent event), and C is the consequence value. R{sub SAF} = P{sub F} * C (1) The security risk associated with an attack on critical infrastructure and/or special nuclear materials theft is usually evaluated using three- term risk equation (probability of attack, probability of adversary success, and consequence). A security threat and the related initiating events are not considered in a pure safety risk analysis. The vulnerability of the physical protection system is performed independently even though the consequence resulting from a security initiating event can be similar to a safety related initiating event and thus gets double counted. The security risk can be calculated using Eq. (2) R{sub SEC} = P{sub A} * P{sub S} * C (2) PA is the probability of attack, P{sub S} is the probability of adversary success (P{sub S} = 1 - P{sub I} P{sub N}). P{sub I} being the probability of interruption which accounts for the probabilities of detection of all timely detection elements along an adversary path. PN being the probability of neutralization: the result of engagement of the response force with the adversaries after the interruption has occurred. C is the consequence magnitude from a successful attack. The two security probabilities do not describe random, independent events. As a result, because of the differences in the randomness and independence of the respective safety and security probabilities, the safety and the security risks are currently calculated separately. The consequence term in nuclear safety and security risk evaluation have the same definition. An effort is made here to study the effect on the overall risk by considering security initiating events along with the subsequent failure of the intermediate safety element. The target selected is a spent fuel storage pool for analyzing the public risk arising from the interplay between nuclear security and safety initiating events. EASI (Estimate of Adversary Sequence Interruption) model is used to calculate the probability of interruption related to a security system that leads to the calculation of the security initiating event frequency. Further progression of this initiating security event to a top event is analyzed using a Probabilistic Safety Assessment (PSA) tool, SAPHIRE (version 8) to obtain a joint pool damage frequency. For the progression of events leading to a top event, the failure of the intermediate safety elements is assumed to be external random events such as heavy load drop and fire events. The objectives of this study is to (1) determine the double accounting of frequency of failure, risk and allocated resources in the scenario of a non-random security initiating event leading to a safety random event chain (2) compare the damage frequency from pure security with the frequency of combined security-safety failure event and pure safety failure events. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Efficient evaluation of small failure probability in high-dimensional groundwater contaminant transport modeling via a two-stage Monte Carlo method

In decision-making for groundwater management and contamination remediation, it is important to accurately evaluate the probability of the occurrence of a failure event. For small failure probability analysis, a large number of model evaluations are needed in the Monte Carlo (MC) simulation, which is impractical for CPU-demanding models. One approach to alleviate the computational cost caused by the model evaluations is to construct a computationally inexpensive surrogate model instead. However, using a surrogate approximation can cause an extra error in the failure probability analysis. Furthermore, constructing accurate surrogates is challenging for high-dimensional models, i.e., models containing many uncertain input parameters. To address these issues, we propose an efficient two-stage MC approach for small failure probability analysis in high-dimensional groundwater contaminant transport modeling. In the first stage, a low-dimensional representation of the original high-dimensional model is sought with Karhunen–Loève expansion and sliced inverse regression jointly, which allows for the easy construction of a surrogate with polynomial chaos expansion. Then a surrogate-based MC simulation is implemented. In the second stage, the small number of samples that are close to the failure boundary are re-evaluated with the original model, which corrects the bias introduced by the surrogate approximation. The proposed approach is tested with a numerical case study and is shown to be 100 times faster than the traditional MC approach in achieving the same level of estimation accuracy.

54 ENVIRONMENTAL SCIENCES↗

Correlation between failure and local material property in chopped carbon fiber chip-reinforced sheet molding compound composites under tensile load

To develop further understanding towards the role of a heterogeneous microstructure on tensile crack initiation and failure behavior in chopped carbon fiber chip-reinforced composites, uni-axial tensile tests are performed on coupons cut from compression molded plaque with varying directions. Our experimental results indicate that failure initiation is relevant to the strain localization, and a new criterion with the nominal modulus to predict the failure location is proposed based on the strain analysis. Furthermore, optical microscopic images show that the nominal modulus is determined by the chip orientation distribution. At the area with low nominal modulus, it is found that chips are mostly aligning along directions transverse to loading direction and/or less concentrated, while at the area with high nominal modulus, more chips are aligning to tensile direction. On the basis of failure mechanism analysis, it is concluded that transversely-oriented chips or resin-rich regions are easier for damage initiation, while longitudinally-oriented chips postpone the fracture. Good agreement is found among failure mechanism, strain localization and chip orientation distribution.

36 MATERIALS SCIENCE↗

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗

Failure analysis of solid oxide fuel cells nickel-yttria stabilized zirconia anode under siloxane contamination

In this study, the failure process of the solid oxide fuel cell (SOFC) Ni-yttria-stabilized zirconia (YSZ) anode is investigated with D4 siloxane (octamethylcyclotetrasiloxane) contamination. In order to evaluate the influence of the electrochemical reaction on the siloxane deposition process, the SOFC experiments were operated at open circuit voltage (OCV) and 50 mA cm -2 conditions at 800°C. During the failure process, electrochemical, morphology and exhaust gas component analysis testing are conducted at the critical points. An equivalent circuit model and corresponding microstructure parameter calculations for separated physicochemical processes were utilized for the quantitative analysis of the failure process. Further, the results confirm the siloxane chemical adsorption deposition mechanism proposed in previous work. As a result, the failure of the anode was attributed to the gas diffusion blockage by dense silicon dioxide layer formation. The anode failure process with siloxane contamination is faster when the anode is operated under polarization.

25 ENERGY STORAGE↗

A generalized power-law criterion for rocks based on Mohr failure theory

Nonlinearity of Mohr envelopes confirmed by past laboratory test data can be of considerable importance in theoretical interpretation of rock strength behaviors and many practical applications. Current nonlinear failure criteria are introduced with parameters to empirically fit test data, and the physical and mechanical meanings of these fitting parameters are often not known. Predicted strengths by theoretical criteria (e.g., Griffith criterion) generally do not agree well with test data. Considering the nonlinear properties of a Mohr envelope, a nonlinear failure criterion in a generalized power-law form is derived in this paper based on strength magnitude coefficient (a) and failure envelope curvature coefficient (n) which are expressed in terms of uniaxial tensile strength, uniaxial compressive strength, and angle of internal friction. Test data on granite, marble, dolomite, and andesite from published literature were chosen to test the performance of the proposed criterion along with Griffith and Hoek-Brown criteria. Statistical analysis was performed to evaluate the application of different criteria in predicting the strength of rocks. In addition, some Griffith-typed criteria are mathematically shown to be the special cases of the proposed criterion. The proposed and Hoek-Brown criteria have similar power-law forms with a significant difference in the coefficient functions that govern the shear strength magnitude of rock. The different tensile and compressive failure mechanisms are also investigated from the perspective of the relationship between the uniaxial tension Mohr circle and the proposed failure envelope.

58 GEOSCIENCES↗

Fracture mechanics approach to TRISO fuel particle failure analysis

Weibull stress-based methods for failure probability assessment have been developed and analyzed to assess the integrity of tristructural isotropic (TRISO) fuel particles during fuel life cycles and accident operating conditions. While simple, these methods entail a number of drawbacks when stress concentrates near crack tips, including finite element mesh size dependency when the Weibull stress is averaged over the finite element domain. Fracture mechanics approaches involving the use of interaction integrals eliminate this lack of mesh convergence and produce consistent fracture predictions. In this work, we use an interaction integral approach to computing stress intensity factors for a crack in the inner pyrolytic carbon layer perpendicular to the silicon carbide layer, which is simplified representation of a failure mode in TRISO particles. Further, the interface between these two TRISO layers has been shown to become porous, which we simulate by considering a transition of mechanical properties over such porous length, i.e. the layers are modeled as a functionally graded material. Aspects such as porosity and thermal and irradiation eigenstrains are considered in computing the stress intensity factor from a fracture mechanics approach and compared with the known Weibull stress failure approach. The methodology introduced in this paper enables a more general fracture probability assessment in TRISO particles and eliminates the need to identify best suited parameters when using local or averaged stress-based failure criterion. Finally, the numerical sensitivity studies show how parameters such as the porous transition zone length, the material stiffness, and creep affect the probability of TRISO fuel particle failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models

In a standard Bayesian approach to the alpha-factor model for common-cause failure, a precise Dirichlet prior distribution models epistemic uncertainty in the alpha-factors. This Dirichlet prior is then updated with observed data to obtain a posterior distribution, which forms the basis for further inferences. In this paper, we adapt the imprecise Dirichlet model of Walley to represent epistemic uncertainty in the alpha-factors. In this approach, epistemic uncertainty is expressed more cautiously via lower and upper expectations for each alpha-factor, along with a learning parameter which determines how quickly the model learns from observed data. For this application, we focus on elicitation of the learning parameter, and find that values in the range of 1 to 10 seem reasonable. The approach is compared with Kelly and Atwood's minimally informative Dirichlet prior for the alpha-factor model, which incorporated precise mean values for the alpha-factors, but which was otherwise quite diffuse. Next, we explore the use of a set of Gamma priors to model epistemic uncertainty in the marginal failure rate, expressed via a lower and upper expectation for this rate, again along with a learning parameter. As zero counts are generally less of an issue here, we find that the choice of this learning parameter is less crucial. Finally, we demonstrate how both epistemic uncertainty models can be combined to arrive at lower and upper expectations for all common-cause failure rates. Thereby, we effectively provide a full sensitivity analysis of common-cause failure rates, properly reflecting epistemic uncertainty of the analyst on all levels of the common-cause failure model.

99 GENERAL AND MISCELLANEOUS↗

POF-Darts: Geometric adaptive sampling for probability of failure

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink, improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.

97 MATHEMATICS AND COMPUTING↗

Loss of Nrf2 promotes rapid progression to heart failure following myocardial infarction

Nrf2 gene encodes a transcription factor regulating the expression of antioxidant and detoxification genes. We test here whether Nrf2 plays a role for cardiac protection during ischemic injury in an effort to establish Nrf2 as a target for cardiac protection therapies. Cardiac ischemia induced by the left anterior descending (LAD) coronary artery ligation results in myocardial infarction (MI). Young mice surviving MI show minimal signs of heart failure. Mice lacking Nrf2 experience an accelerated progression to heart failure that occurs within 10 days following induction of MI. Nrf2 knockout (Nrf2 KO) mice have a survival rate similar to wild type (WT) mice at 24 h after MI, but a significantly higher mortality rate within 10 days after MI (50% vs 86%). Morphological examination revealed maladaptive remodeling, including cardiac hypertrophy and dilated left ventricle in Nrf2 KO mice, which were absent in WT mice. Measurements of cardiac function revealed increased left ventricular mass and decreases in cardiac output in Nrf2 KO mice. In addition, Nrf2 KO mice show biomarkers of heart failure, such as elevated levels of β-MHC, ANF, and BNP mRNA in the myocardium. These data support that Nrf2 plays an important role in protecting the myocardium from ischemic injury. Lack of Nrf2 leads to rapid development of heart failure. - Highlights: • We test whether Nrf2 serves to protect the heart from ischemic injury. • Nrf2 knockout mice have increased mortality following myocardial ischemia. • Heart failure develops in 10 days following myocardial ischemia due to Nrf2 knockout.

60 APPLIED LIFE SCIENCES↗

The effect of current and lambda on white-etch-crack failures

White etching cracks (WECs) have been associated with premature failure of wind turbine roller bearings. Various drivers for the generation of WECs have been identified such as loading conditions, slip, steel quality, lubrication, hydrogen embrittlement, corrosion fatigue cracking, and stray electrical currents passing through the surface. Here, in this work, a benchtop test rig utilizing a three-ring-on-roller test configuration was used to investigate the effect of electrical current and operation in different lubricating regimes, defined by lambda (λ), on high-quality bearing steel samples tested in a commercially available power transmission EP gear lubricant. It was observed that there is an inverse correlation between the magnitude of electric current applied to the ring/ roller system and time-to-failure. Higher current magnitudes lead to shorter time-to-failure than lower current magnitudes, with macropitting as the main failure mode. Sub-surface investigation revealed the presence of WECs in all cases. For the same current magnitude, tests conducted in boundary and mixed lubrication regimes showed that time-to-failure increased as lambda increased, and the tests resulted in WEC related macropits, whereas tests conducted in near-hydrodynamic regime resulted in surface damage with no macropit. It was also noted that a shift toward near-hydrodynamic lubrication resulted in a distinct surface distress on the roller surface. Furthermore, there seems to be a transition in the mixed regime during which the surface distress occurred. The damage on the surface of the test samples resembled non-spatially, periodic, groove-like corrugations and, in some cases, crater-like depressions. Sub-surface imaging, performed by sequential sectioning, revealed the presence of WECs in all cases, and broad, branching cracks that were more prevalent under the more severe boundary conditions.

17 WIND ENERGY↗

Size-Dependent Chemomechanical Failure of Sulfide Solid Electrolyte Particles during Electrochemical Reaction with Lithium

The very high ionic conductivity of Li 10 GeP 2 S 12 (LGPS) solid electrolyte (SE) makes it a promising candidate SE for solid-state batteries in electrical vehicles. However, chemomechanical failure, whose mechanism remains unclear, has plagued its widespread applications. Here, we report in situ imaging lithiation-induced failure of LGPS SE. In this work, we revealed a strong size effect in the chemomechanical failure of LGPS particles: namely, when the particle size is greater than 3 μm, fracture/pulverization occurred; when the particle size is between 1 and 3 μm, microcracks emerged; when the particle size is less than 1 μm, no chemomechanical failure was observed. This strong size effect is interpreted by the interplay between elastic energy storage and dissipation. Our finding has important implications for the design of high-performance LGPS SE, for example, by reducing the particle size to less than 1 μm the chemomechanical failure of LGPS SE can be mitigated.

25 ENERGY STORAGE↗

WE-G-BRA-09: Microsphere Brachytherapy Failure Mode and Effects Analysis in a Dual-Vendor Environment

Purpose: To improve the safety and quality of a dual-vendor microsphere brachytherapy program with failure mode and effects analysis (FMEA). Methods: A multidisciplinary team including physicists, dosimetrists, a radiation oncologist, an interventional radiologist, and radiation safety personnel performed an FMEA for our dual-vendor microsphere brachytherapy program employing SIR-Spheres (Sirtex Medical Limited, Australia) and Theraspheres (BTG, England). We developed a program process tree and step-by-step instructions which were used to generate a comprehensive list of failure modes. These modes were then ranked according to severity, occurrence rate, and detectability. Risk priority numbers (RPNs) were calculated by multiplying these three scores together. Three different severity scales were created: one each for harmful effects to the patient, staff, or the institution. Each failure mode was ranked on one or more of these scales. Results: The group identified 164 failure modes for the microsphere program. 113 of these were ranked using the patient severity scale, 52 using the staff severity scale, and 50 using the institution severity scale. The highest ranked items on the patient severity scale were an error in the automated dosimetry worksheet (RPN = 297.5), and the incorrect target specified on the planning study (RPN = 135). Some failure modes ranked differently between vendors, especially those corresponding to dose vial preparation because of the different methods used. Based on our findings, we made several improvements to our QA program, including documentation to easily identify which product is being used, an additional hand calculation during planning, and reorganization of QA steps before treatment delivery. We will continue to periodically review and revise the FMEA. Conclusion: We have applied FMEA to our dual-vendor microsphere brachytherapy program to identify potential key weaknesses in the treatment chain. Our FMEA results were used to improve the effectiveness of our overall microsphere program.

60 APPLIED LIFE SCIENCES↗

Physical nature of longevity of light actinides in dynamic failure phenomenon

It is shown in this work that the physical nature of the longevity of light actinides under extreme conditions in a range of nonequilibrium states of t ∼ 10{sup –6}–10{sup –10} s is determined by the time needed for the formation of a critical concentration of a cascade of failure centers, which changes connectivity of the body. These centers form a percolation cluster. The longevity is composed of waiting time t{sub w} for the appearance of failure centers and clusterization time t{sub c} of cascade of failure centers, when connectivity in the system of failure centers and the percolation cluster arise. A unique mechanism of the dynamic failure process, a unique order parameter, and an equal dimensionality of the space in which the process occurs determine the physical nature of the longevity of metals, including fissionable materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Review on Simulation Models of Cascading Failures in Power Systems

Among various power system disturbances, cascading failures are considered the most serious and extreme threats to grid operations, potentially leading to significant stability issues or even widespread power blackouts. Simulating power systems' behaviors during cascading failures is of great importance to comprehend how failures originate and propagate, as well as to develop effective preventive and mitigative control strategies. The intricate mechanism of cascading failures, characterized by multi-timescale dynamics, presents exceptional challenges for their simulations. This paper provides a comprehensive review of simulation models for cascading failures, providing a systematic categorization and a comparison of these models. The challenges and potential research directions for the future are also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗