Familial expressed emotion: outcome and course of Israeli patients with schizophrenia.

PubMed

Marom, Sofi; Munitz, Hanan; Jones, Peter B; Weizman, Abraham; Hermesh, Haggai

2002-01-01

We investigated the validity of expressed emotion (EE) in Israel. The study sample consisted of 108 patients with schizophrenia and 15 with schizoaffective disorder, and their key relatives. EE was rated with the Five Minute Speech Sample (FMSS). Patient households were categorized by EE and its two components: criticism and emotional overinvolvement. Patients were rated with the Brief Psychiatric Rating Scale (BPRS) at admission, at discharge, and 6 months after discharge. Readmissions were determined over a 9-month period. High EE and particularly high criticism were significantly associated with poorer outcome (higher rate of and earlier readmissions, and higher BPRS score at followup) and worse illness course (higher annual number of prior psychiatric hospital admissions). Odds ratios between high EE and high criticism and readmission were 2.6 and 3.5, respectively. The strongest predictor of earlier readmission was the interaction of high criticism x poor compliance with medication. The results converge to further confirm the notion that familial EE is a valid crosscultural predictor of the clinical course of schizophrenia. Moreover, EE has predictive power in very chronic samples. Criticism appears to be the crucial EE component linked with short-term outcome. Treatment aimed at reducing high criticism is warranted. The FMSS appears to have predictive validity.

Ceramic Matrix Composites (CMC) Life Prediction Development

NASA Technical Reports Server (NTRS)

Levine, Stanley R.; Verrilli, Michael J.; Thomas, David J.; Halbig, Michael C.; Calomino, Anthony M.; Ellis, John R.; Opila, Elizabeth J.

1990-01-01

Advanced launch systems will very likely incorporate fiber reinforced ceramic matrix composites (CMC) in critical propulsion and airframe components. The use of CMC will save weight, increase operating margin, safety and performance, and improve reuse capability. For reusable and single mission use, accurate life prediction is critical to success. The tools to accomplish this are immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for many applications. This paper describes an approach and progress made to satisfy the need to develop an integrated life prediction system that addresses mechanical durability and environmental degradation.

Modeling species distribution and change using random forest [Chapter 8

Treesearch

Jeffrey S. Evans; Melanie A. Murphy; Zachary A. Holden; Samuel A. Cushman

2011-01-01

Although inference is a critical component in ecological modeling, the balance between accurate predictions and inference is the ultimate goal in ecological studies (Peters 1991; De’ath 2007). Practical applications of ecology in conservation planning, ecosystem assessment, and bio-diversity are highly dependent on very accurate spatial predictions of...

Teaching citizens: the role of open classroom climate in fostering critical consciousness among youth.

PubMed

Godfrey, Erin B; Grayman, Justina Kamiel

2014-11-01

Building on previous research on critical consciousness and civic development among youth, the current study examined the extent to which an open climate for discussion-one in which controversial issues are openly discussed with respect for all opinions-relates to youth's critical consciousness and whether this association differs for youth from racial/ethnic majority versus minority backgrounds. Critical consciousness consisted of three components: the ability to critically read social conditions (critical reflection), feelings of efficacy to effect change (sociopolitical efficacy) and actual participation in these efforts (critical action), in both the educational and political/community domains. Open classroom climate was operationalized at the classroom rather than individual student level to more accurately draw links to educational policy and practice. Multilevel analyses of the 1999 IEA Civic Education Study, a nationally-representative sample of 2,774 US ninth-graders (50 % female; 58 % white), revealed that an open classroom climate predicted some, but not all, components of critical consciousness. Specifically, open classroom climate was positively related to sociopolitical efficacy in both the educational and political domains and to critical action in the community domain, but was not related to critical reflection. Few differences in these associations were found for youth from racial/ethnic majority versus minority backgrounds. The exception was sociopolitical efficacy in the educational domain: open classroom climate was particularly predictive of sociopolitical efficacy for minority youth. The findings are discussed in regard to previous research on open classroom climate and youth critical consciousness; and implications for future research and educational practice are drawn.

Development of dry coal feeders

NASA Technical Reports Server (NTRS)

Bonin, J. H.; Cantey, D. E.; Daniel, A. D., Jr.; Meyer, J. W.

1977-01-01

Design and fabrication of equipment of feed coal into pressurized environments were investigated. Concepts were selected based on feeder system performance and economic projections. These systems include: two approaches using rotating components, a gas or steam driven ejector, and a modified standpipe feeder concept. Results of development testing of critical components, design procedures, and performance prediction techniques are reviewed.

MEMS Deformable Mirror Technology Development for Space-Based Exoplanet Detection

NASA Astrophysics Data System (ADS)

Bierden, Paul; Cornelissen, S.; Ryan, P.

2014-01-01

In the search for earth-like extrasolar planets that has become an important objective for NASA, a critical technology development requirement is to advance deformable mirror (DM) technology. High-actuator-count DMs are critical components for nearly all proposed coronagraph instrument concepts. The science case for exoplanet imaging is strong, and rapid recent advances in test beds with DMs made using microelectromechanical system (MEMS) technology have motivated a number of compelling mission concepts that set technical specifications for their use as wavefront controllers. This research will advance the technology readiness of the MEMS DMs components that are currently at the forefront of the field, and the project will be led by the manufacturer of those components, Boston Micromachines Corporation (BMC). The project aims to demonstrate basic functionality and performance of this key component in critical test environments and in simulated operational environments, while establishing model-based predictions of its performance relative to launch and space environments. Presented will be the current status of the project with modeling and initial test results.

The prediction of nonlinear dynamic loads on helicopters from flight variables using artificial neural networks

NASA Technical Reports Server (NTRS)

Cook, A. B.; Fuller, C. R.; O'Brien, W. F.; Cabell, R. H.

1992-01-01

A method of indirectly monitoring component loads through common flight variables is proposed which requires an accurate model of the underlying nonlinear relationships. An artificial neural network (ANN) model learns relationships through exposure to a database of flight variable records and corresponding load histories from an instrumented military helicopter undergoing standard maneuvers. The ANN model, utilizing eight standard flight variables as inputs, is trained to predict normalized time-varying mean and oscillatory loads on two critical components over a range of seven maneuvers. Both interpolative and extrapolative capabilities are demonstrated with agreement between predicted and measured loads on the order of 90 percent to 95 percent. This work justifies pursuing the ANN method of predicting loads from flight variables.

A Height–Diameter Curve for Longleaf Pine Plantations in the Gulf Coastal Plain

Treesearch

Daniel Leduc; Jeffery Goelz

2009-01-01

Tree height is a critical component of a complete growth-and-yield model because it is one of the primary components used in volume calculation. To develop an equation to predict total height from dbh for longleaf pine (Pinus palustris Mill.) plantations in the West Gulf region, many different sigmoidal curve forms, weighting functions, and ways of...

Prediction of microalgae hydrothermal liquefaction products from feedstock biochemical composition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leow, Shijie; Witter, John R.; Vardon, Derek R.

Hydrothermal liquefaction (HTL) uses water under elevated temperatures and pressures (200–350 °C, 5–20 MPa) to convert biomass into liquid “biocrude” oil. Despite extensive reports on factors influencing microalgae cell composition during cultivation and separate reports on HTL products linked to cell composition, the field still lacks a quantitative model to predict HTL conversion product yield and qualities from feedstock biochemical composition; the tailoring of microalgae feedstock for downstream conversion is a unique and critical aspect of microalgae biofuels that must be leveraged upon for optimization of the whole process. This study developed predictive relationships for HTL biocrude yield and othermore » conversion product characteristics based on HTL of Nannochloropsis oculata batches harvested with a wide range of compositions (23–59% dw lipids, 58–17% dw proteins, 12–22% dw carbohydrates) and a defatted batch (0% dw lipids, 75% dw proteins, 19% dw carbohydrates). HTL biocrude yield (33–68% dw) and carbon distribution (49–83%) increased in proportion to the fatty acid (FA) content. A component additivity model (predicting biocrude yield from lipid, protein, and carbohydrates) was more accurate predicting literature yields for diverse microalgae species than previous additivity models derived from model compounds. FA profiling of the biocrude product showed strong links to the initial feedstock FA profile of the lipid component, demonstrating that HTL acts as a water-based extraction process for FAs; the remainder non-FA structural components could be represented using the defatted batch. These findings were used to introduce a new FA-based model that predicts biocrude oil yields along with other critical parameters, and is capable of adjusting for the wide variations in HTL methodology and microalgae species through the defatted batch. Lastly, the FA model was linked to an upstream cultivation model (Phototrophic Process Model), providing for the first time an integrated modeling framework to overcome a critical barrier to microalgae-derived HTL biofuels and enable predictive analysis of the overall microalgal-to-biofuel process.« less

Prediction of microalgae hydrothermal liquefaction products from feedstock biochemical composition

DOE PAGES

Leow, Shijie; Witter, John R.; Vardon, Derek R.; ...

2015-05-11

Hydrothermal liquefaction (HTL) uses water under elevated temperatures and pressures (200–350 °C, 5–20 MPa) to convert biomass into liquid “biocrude” oil. Despite extensive reports on factors influencing microalgae cell composition during cultivation and separate reports on HTL products linked to cell composition, the field still lacks a quantitative model to predict HTL conversion product yield and qualities from feedstock biochemical composition; the tailoring of microalgae feedstock for downstream conversion is a unique and critical aspect of microalgae biofuels that must be leveraged upon for optimization of the whole process. This study developed predictive relationships for HTL biocrude yield and othermore » conversion product characteristics based on HTL of Nannochloropsis oculata batches harvested with a wide range of compositions (23–59% dw lipids, 58–17% dw proteins, 12–22% dw carbohydrates) and a defatted batch (0% dw lipids, 75% dw proteins, 19% dw carbohydrates). HTL biocrude yield (33–68% dw) and carbon distribution (49–83%) increased in proportion to the fatty acid (FA) content. A component additivity model (predicting biocrude yield from lipid, protein, and carbohydrates) was more accurate predicting literature yields for diverse microalgae species than previous additivity models derived from model compounds. FA profiling of the biocrude product showed strong links to the initial feedstock FA profile of the lipid component, demonstrating that HTL acts as a water-based extraction process for FAs; the remainder non-FA structural components could be represented using the defatted batch. These findings were used to introduce a new FA-based model that predicts biocrude oil yields along with other critical parameters, and is capable of adjusting for the wide variations in HTL methodology and microalgae species through the defatted batch. Lastly, the FA model was linked to an upstream cultivation model (Phototrophic Process Model), providing for the first time an integrated modeling framework to overcome a critical barrier to microalgae-derived HTL biofuels and enable predictive analysis of the overall microalgal-to-biofuel process.« less

Computer models and output, Spartan REM: Appendix B

NASA Technical Reports Server (NTRS)

Marlowe, D. S.; West, E. J.

1984-01-01

A computer model of the Spartan Release Engagement Mechanism (REM) is presented in a series of numerical charts and engineering drawings. A crack growth analysis code is used to predict the fracture mechanics of critical components.

Designing and benchmarking the MULTICOM protein structure prediction system

PubMed Central

2013-01-01

Background Predicting protein structure from sequence is one of the most significant and challenging problems in bioinformatics. Numerous bioinformatics techniques and tools have been developed to tackle almost every aspect of protein structure prediction ranging from structural feature prediction, template identification and query-template alignment to structure sampling, model quality assessment, and model refinement. How to synergistically select, integrate and improve the strengths of the complementary techniques at each prediction stage and build a high-performance system is becoming a critical issue for constructing a successful, competitive protein structure predictor. Results Over the past several years, we have constructed a standalone protein structure prediction system MULTICOM that combines multiple sources of information and complementary methods at all five stages of the protein structure prediction process including template identification, template combination, model generation, model assessment, and model refinement. The system was blindly tested during the ninth Critical Assessment of Techniques for Protein Structure Prediction (CASP9) in 2010 and yielded very good performance. In addition to studying the overall performance on the CASP9 benchmark, we thoroughly investigated the performance and contributions of each component at each stage of prediction. Conclusions Our comprehensive and comparative study not only provides useful and practical insights about how to select, improve, and integrate complementary methods to build a cutting-edge protein structure prediction system but also identifies a few new sources of information that may help improve the design of a protein structure prediction system. Several components used in the MULTICOM system are available at: http://sysbio.rnet.missouri.edu/multicom_toolbox/. PMID:23442819

Effect of Bending Stiffness of the Electroactive Polymer Element on the Performance of a Hybrid Actuator System (HYBAS)

NASA Technical Reports Server (NTRS)

Xu, Tian-Bing; Su, Ji; Jiang, Xiaoning; Rehrig, Paul W.; Zhang, Shujun; Shrout, Thomas R.; Zhang, Qiming

2006-01-01

An electroactive polymer (EAP)-ceramic hybrid actuation system (HYBAS) was developed recently at NASA Langley Research Center. This paper focuses on the effect of the bending stiffness of the EAP component on the performance of a HYBAS, in which the actuation of the EAP element can match the theoretical prediction at various length/thickness ratios for a constant elastic modulus of the EAP component. The effects on the bending stiffness of the elastic modulus and length/thickness ratio of the EAP component were studied. A critical bending stiffness to keep the actuation of the EAP element suitable for a rigid beam theory-based modeling was found for electron irradiated P(VDF-TrFE) copolymer. For example, the agreement of experimental data and theoretical modeling for a HYBAS with the length/thickness ratio of EAP element at 375 times is demonstrated. However, the beam based theoretical modeling becomes invalid (i.e., the profile of the HYBAS movement does not follow the prediction of theoretical modeling) when the bending stiffness is lower than a critical value.

Predicting the enthalpies of melting and vaporization for pure components

NASA Astrophysics Data System (ADS)

Esina, Z. N.; Korchuganova, M. R.

2014-12-01

A mathematical model of the melting and vaporization enthalpies of organic components based on the theory of thermodynamic similarity is proposed. In this empirical model, the phase transition enthalpy for the homological series of n-alkanes, carboxylic acids, n-alcohols, glycols, and glycol ethers is presented as a function of the molecular mass, the number of carbon atoms in a molecule, and the normal transition temperature. The model also uses a critical or triple point temperature. It is shown that the results from predicting the melting and vaporization enthalpies enable the calculation of binary phase diagrams.

Parental Mediation in the Digital Era: Increasing Children's Critical Thinking May Help Decrease Positive Attitudes toward Alcohol.

PubMed

Radanielina Hita, Marie Louise; Kareklas, Ioannis; Pinkleton, Bruce

2018-01-01

We demonstrate in our research that discussion-based parental mediation may successfully decrease the negative effects that youth's engagement with alcohol brands on social media may have on attitudes toward alcohol through its effects on critical thinking. A clear pattern was found with positive mediation leading to unhealthy outcomes and negative mediation predicting healthier behaviors. Youth whose parents critiqued media messages reported more critical thinking skills, which predicted less interaction with alcohol brands on social media and fewer expectancies toward alcohol. On the other hand, youth whose parents endorsed media portrayals of drinking reported fewer critical thinking skills and were thus more likely to interact with alcohol brands on social media. Including a media literacy component in alcohol education that target parental strategies and that are conducive to discussion may lead to beneficial health outcomes in the digital era.

Procedures and models for estimating preconstruction costs of highway projects.

DOT National Transportation Integrated Search

2012-07-01

This study presents data driven and component based PE cost prediction models by utilizing critical factors retrieved from ten years of historical project data obtained from ODOT roadway division. The study used factor analysis of covariance and corr...

Early lactate clearance for predicting active bleeding in critically ill patients with acute upper gastrointestinal bleeding: a retrospective study.

PubMed

Wada, Tomoki; Hagiwara, Akiyoshi; Uemura, Tatsuki; Yahagi, Naoki; Kimura, Akio

2016-08-01

Not all patients with upper gastrointestinal bleeding (UGIB) require emergency endoscopy. Lactate clearance has been suggested as a parameter for predicting patient outcomes in various critical care settings. This study investigates whether lactate clearance can predict active bleeding in critically ill patients with UGIB. This single-center, retrospective, observational study included critically ill patients with UGIB who met all of the following criteria: admission to the emergency department (ED) from April 2011 to August 2014; had blood samples for lactate evaluation at least twice during the ED stay; and had emergency endoscopy within 6 h of ED presentation. The main outcome was active bleeding detected with emergency endoscopy. Classification and regression tree (CART) analyses were performed using variables associated with active bleeding to derive a prediction rule for active bleeding in critically ill UGIB patients. A total of 154 patients with UGIB were analyzed, and 31.2 % (48/154) had active bleeding. In the univariate analysis, lactate clearance was significantly lower in patients with active bleeding than in those without active bleeding (13 vs. 29 %, P < 0.001). Using the CART analysis, a prediction rule for active bleeding is derived, and includes three variables: lactate clearance; platelet count; and systolic blood pressure at ED presentation. The rule has 97.9 % (95 % CI 90.2-99.6 %) sensitivity with 32.1 % (28.6-32.9 %) specificity. Lactate clearance may be associated with active bleeding in critically ill patients with UGIB, and may be clinically useful as a component of a prediction rule for active bleeding.

TIME-INTEGRATED EXPOSURE MEASURES TO IMPROVE THE PREDICTIVE POWER OF EXPOSURE CLASSIFICATION FOR EPIDEMIOLOGIC STUDIES

EPA Science Inventory

Accurate exposure classification tools are required to link exposure with health effects in epidemiological studies. Although long-term integrated exposure measurements are a critical component of exposure assessment, the ability to include these measurements into epidemiologic...

URBAN MORPHOLOGICAL ANALYSIS FOR MESOSCALE METEOROLOGICAL AND DISPERSION MODELING APPLICATIONS: CURRENT ISSUES

EPA Science Inventory

Representing urban terrain characteristics in mesoscale meteorological and dispersion models is critical to produce accurate predictions of wind flow and temperature fields, air quality, and contaminant transport. A key component of the urban terrain representation is the charac...

Science and data science.

PubMed

Blei, David M; Smyth, Padhraic

2017-08-07

Data science has attracted a lot of attention, promising to turn vast amounts of data into useful predictions and insights. In this article, we ask why scientists should care about data science. To answer, we discuss data science from three perspectives: statistical, computational, and human. Although each of the three is a critical component of data science, we argue that the effective combination of all three components is the essence of what data science is about.

A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades.

PubMed

Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

2017-05-08

As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB) and Fatemi-Socie (FS) models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT) model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models.

A New Energy-Critical Plane Damage Parameter for Multiaxial Fatigue Life Prediction of Turbine Blades

PubMed Central

Yu, Zheng-Yong; Zhu, Shun-Peng; Liu, Qiang; Liu, Yunhan

2017-01-01

As one of fracture critical components of an aircraft engine, accurate life prediction of a turbine blade to disk attachment is significant for ensuring the engine structural integrity and reliability. Fatigue failure of a turbine blade is often caused under multiaxial cyclic loadings at high temperatures. In this paper, considering different failure types, a new energy-critical plane damage parameter is proposed for multiaxial fatigue life prediction, and no extra fitted material constants will be needed for practical applications. Moreover, three multiaxial models with maximum damage parameters on the critical plane are evaluated under tension-compression and tension-torsion loadings. Experimental data of GH4169 under proportional and non-proportional fatigue loadings and a case study of a turbine disk-blade contact system are introduced for model validation. Results show that model predictions by Wang-Brown (WB) and Fatemi-Socie (FS) models with maximum damage parameters are conservative and acceptable. For the turbine disk-blade contact system, both of the proposed damage parameters and Smith-Watson-Topper (SWT) model show reasonably acceptable correlations with its field number of flight cycles. However, life estimations of the turbine blade reveal that the definition of the maximum damage parameter is not reasonable for the WB model but effective for both the FS and SWT models. PMID:28772873

Online neural monitoring of statistical learning

PubMed Central

Batterink, Laura J.; Paller, Ken A.

2017-01-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the RT task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. PMID:28324696

The balanced ideological antipathy model: explaining the effects of ideological attitudes on inter-group antipathy across the political spectrum.

PubMed

Crawford, Jarret T; Mallinas, Stephanie R; Furman, Bryan J

2015-12-01

We introduce the balanced ideological antipathy (BIA) model, which challenges assumptions that right-wing authoritarianism (RWA) and social dominance orientation (SDO) predict inter-group antipathy per se. Rather, the effects of RWA and SDO on antipathy should depend on the target's political orientation and political objectives, the specific components of RWA, and the type of antipathy expressed. Consistent with the model, two studies (N = 585) showed that the Traditionalism component of RWA positively and negatively predicted both political intolerance and prejudice toward tradition-threatening and -reaffirming groups, respectively, whereas SDO positively and negatively predicted prejudice (and to some extent political intolerance) toward hierarchy-attenuating and -enhancing groups, respectively. Critically, the Conservatism component of RWA positively predicted political intolerance (but not prejudice) toward each type of target group, suggesting it captures the anti-democratic impulse at the heart of authoritarianism. Recommendations for future research on the relationship between ideological attitudes and inter-group antipathy are discussed. © 2015 by the Society for Personality and Social Psychology, Inc.

Coherence explored between emotion components: evidence from event-related potentials and facial electromyography.

PubMed

Gentsch, Kornelia; Grandjean, Didier; Scherer, Klaus R

2014-04-01

Componential theories assume that emotion episodes consist of emergent and dynamic response changes to relevant events in different components, such as appraisal, physiology, motivation, expression, and subjective feeling. In particular, Scherer's Component Process Model hypothesizes that subjective feeling emerges when the synchronization (or coherence) of appraisal-driven changes between emotion components has reached a critical threshold. We examined the prerequisite of this synchronization hypothesis for appraisal-driven response changes in facial expression. The appraisal process was manipulated by using feedback stimuli, presented in a gambling task. Participants' responses to the feedback were investigated in concurrently recorded brain activity related to appraisal (event-related potentials, ERP) and facial muscle activity (electromyography, EMG). Using principal component analysis, the prediction of appraisal-driven response changes in facial EMG was examined. Results support this prediction: early cognitive processes (related to the feedback-related negativity) seem to primarily affect the upper face, whereas processes that modulate P300 amplitudes tend to predominantly drive cheek region responses. Copyright © 2013 Elsevier B.V. All rights reserved.

Structural mechanics of seed deterioration: Standing the test of time

USDA-ARS?s Scientific Manuscript database

Seeds die unexpectedly during storage and current understanding of seed quality and storage conditions does not allow reliable means to predict or prevent this critical problem. Chemical degradation of seed components likely occurs through oxidative damage, but the rate of these reactions is domina...

Application of High Performance Computing for Simulations of N-Dodecane Jet Spray with Evaporation

DTIC Science & Technology

2016-11-01

sprays and develop a predictive theory for comparison to measurements in the laboratory of turbulent diesel sprays. 15. SUBJECT TERMS high...models into future simulations of turbulent jet sprays and develop a predictive theory for comparison to measurements in the lab of turbulent diesel ...A critical component of maintaining performance and durability of a diesel engine involves the formation of a fuel-air mixture as a diesel jet spray

Interfacial tension and vapor-liquid equilibria in the critical region of mixtures

NASA Technical Reports Server (NTRS)

Moldover, Michael R.; Rainwater, James C.

1988-01-01

In the critical region, the concept of two-scale-factor universality can be used to accurately predict the surface tension between near-critical vapor and liquid phases from the singularity in the thermodynamic properties of the bulk fluid. In the present work, this idea is generalized to binary mixtures and is illustrated using the data of Hsu et al. (1985) for CO2 + n-butane. The pressure-temperature-composition-density data for coexisting, near-critical phases of the mixtures are fitted with a thermodynamic potential comprised of a sum of a singular term and nonsingular terms. The nonuniversal amplitudes characterizing the singular term for the mixtures are obtained from the amplitudes for the pure components by interpolation in a space of thermodynamic 'field' variables. The interfacial tensions predicted for the mixtures from the singular term are within 10 percent of the data on three isotherms in the pressure range (Pc - P)/Pc of less than 0.5. This difference is comparable to the combined experimental and model errors.

Children's Use of Categories and Mental States to Predict Social Behavior

ERIC Educational Resources Information Center

Chalik, Lisa; Rivera, Cyrielle; Rhodes, Marjorie

2014-01-01

Integrating generic information about categories with knowledge of specific individuals is a critical component of successful inductive inferences. The present study tested whether children's approach to this task systematically shifts as they develop causal understandings of the mechanisms that shape individual action. In the current study, 3-and…

PREDICTING IMPACTS OF REROUTING DRAINAGE WATER FROM THE PAMLICO SOUND TO RESTORED WETLANDS—A CRITICAL COMPONENT TO GALVANIZE STAKEHOLDER COOPERATION

EPA Science Inventory

Denitrification, a microbially mediated transformation of nitrate to nitrogen gas that escapes from the wetland to the atmosphere, has been identified as the primary pathway for nitrogen removal in wetlands. Requirements for denitrification, which include anoxic conditions,...

An Experimental and Analytical Investigation of Stirling Space Power Converter Heater Head

NASA Technical Reports Server (NTRS)

Abdul-Aziz, Ali; Bartolotta, Paul; Tong, Mike; Allen, Gorden

1995-01-01

NASA has identified the Stirling power converter as a prime candidate for the next generation power system for space applications requiring 60000 hr of operation. To meet this long-term goal, several critical components of the power converter have been analyzed using advanced structural assessment methods. Perhaps the most critical component, because of its geometric complexity and operating environment, is the power converter's heater head. This report describes the life assessment of the heater head which includes the characterization of a viscoplastic material model, the thermal and structural analyses of the heater head, and the interpolation of fatigue and creep test results of a nickel-base superalloy, Udimet 720 LI (Low Inclusions), at several elevated temperatures for life prediction purposes.

Predicting the recruitment of established regeneration into the sapling size class following partial cutting in the Acadian Forest Region: Using long-term observations to assess the performance of FVS-NE

Treesearch

David Ray; Chad Keyser; Robert Seymour; John Brissette

2008-01-01

Forest managers are increasingly called upon to provide long-term predictions of forest development. The dynamics of regeneration establishment, survival and subsequent recruitment of established seedlings to larger size classes is a critical component of these forecasts, yet remains a weak link in available models. To test the reliability of FVS-NE for simulating...

Ceramic Matrix Composites (CMC) Life Prediction Method Development

NASA Technical Reports Server (NTRS)

Levine, Stanley R.; Calomino, Anthony M.; Ellis, John R.; Halbig, Michael C.; Mital, Subodh K.; Murthy, Pappu L.; Opila, Elizabeth J.; Thomas, David J.; Thomas-Ogbuji, Linus U.; Verrilli, Michael J.

2000-01-01

Advanced launch systems (e.g., Reusable Launch Vehicle and other Shuttle Class concepts, Rocket-Based Combine Cycle, etc.), and interplanetary vehicles will very likely incorporate fiber reinforced ceramic matrix composites (CMC) in critical propulsion components. The use of CMC is highly desirable to save weight, to improve reuse capability, and to increase performance. CMC candidate applications are mission and cycle dependent and may include turbopump rotors, housings, combustors, nozzle injectors, exit cones or ramps, and throats. For reusable and single mission uses, accurate prediction of life is critical to mission success. The tools to accomplish life prediction are very immature and not oriented toward the behavior of carbon fiber reinforced silicon carbide (C/SiC), the primary system of interest for a variety of space propulsion applications. This paper describes an approach to satisfy the need to develop an integrated life prediction system for CMC that addresses mechanical durability due to cyclic and steady thermomechanical loads, and takes into account the impact of environmental degradation.

Online neural monitoring of statistical learning.

PubMed

Batterink, Laura J; Paller, Ken A

2017-05-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the reaction time (RT) task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Towards Prognostics of Electrolytic Capacitors

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan; Biswas, Gautam; Goegel, Kai

2011-01-01

A remaining useful life prediction algorithm and degradation model for electrolytic capacitors is presented. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management research. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. In particular, experimental results of an accelerated aging test under electrical stresses are presented. The capacitors used in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors.

Explicit Instructional Interactions: Observed Stability and Predictive Validity during Early Literacy and Beginning Mathematics Instruction

ERIC Educational Resources Information Center

Doabler, Christian T.; Nelson-Walker, Nancy; Kosty, Derek; Baker, Scott K.; Smolkowski, Keith; Fien, Hank

2013-01-01

In this study, the authors conceptualize teaching episodes such as an integrated set of observable student-teacher interactions. Instructional interactions that take place between teachers and students around critical academic content are a defining characteristic of classroom instruction and a component carefully defined in many education…

NDE: A key to engine rotor life prediction

NASA Technical Reports Server (NTRS)

Doherty, J. E.

1977-01-01

A key ingredient in the establishment of safe life times for critical components is the means of reliably detecting flaws which may potentially exist. Currently used nondestructive evaluation procedures are successful in detecting life limiting defects; however, the development of automated and computer aided NDE technology permits even greater assurance of flight safety.

Predicting costs of alien species surveillance across varying transportation networks

Treesearch

Laura Blackburn; Rebecca Epanchin-Niell; Alexandra Thompson; Andrew Liebhold; Jacqueline Beggs

2017-01-01

Efforts to detect and eradicate invading populations before they establish are a critical component of national biosecurity programmes. An essential element for maximizing the efficiency of these efforts is the balancing of expenditures on surveillance (e.g. trapping) versus treatment (e.g. eradication). Identifying the optimal allocation of resources towards...

Prognostics Applied to Electric Propulsion UAV

NASA Technical Reports Server (NTRS)

Goebel, Kai; Saha, Bhaskar

2013-01-01

Health management plays an important role in operations of UAV. If there is equipment malfunction on critical components, safe operation of the UAV might possibly be compromised. A technology with particular promise in this arena is equipment prognostics. This technology provides a state assessment of the health of components of interest and, if a degraded state has been found, it estimates how long it will take before the equipment will reach a failure threshold, conditional on assumptions about future operating conditions and future environmental conditions. This chapter explores the technical underpinnings of how to perform prognostics and shows an implementation on the propulsion of an electric UAV. A particle filter is shown as the method of choice in performing state assessment and predicting future degradation. The method is then applied to the batteries that provide power to the propeller motors. An accurate run-time battery life prediction algorithm is of critical importance to ensure the safe operation of the vehicle if one wants to maximize in-air time. Current reliability based techniques turn out to be insufficient to manage the use of such batteries where loads vary frequently in uncertain environments.

Incorporation of Half-Cycle Theory Into Ko Aging Theory for Aerostructural Flight-Life Predictions

NASA Technical Reports Server (NTRS)

Ko, William L.; Tran, Van T.; Chen, Tony

2007-01-01

The half-cycle crack growth theory was incorporated into the Ko closed-form aging theory to improve accuracy in the predictions of operational flight life of failure-critical aerostructural components. A new crack growth computer program was written for reading the maximum and minimum loads of each half-cycle from the random loading spectra for crack growth calculations and generation of in-flight crack growth curves. The unified theories were then applied to calculate the number of flights (operational life) permitted for B-52B pylon hooks and Pegasus adapter pylon hooks to carry the Hyper-X launching vehicle that air launches the X-43 Hyper-X research vehicle. A crack growth curve for each hook was generated for visual observation of the crack growth behavior during the entire air-launching or captive flight. It was found that taxiing and the takeoff run induced a major portion of the total crack growth per flight. The operational life theory presented can be applied to estimate the service life of any failure-critical structural components.

Prognostics

NASA Technical Reports Server (NTRS)

Goebel, Kai; Vachtsevanos, George; Orchard, Marcos E.

2013-01-01

Knowledge discovery, statistical learning, and more specifically an understanding of the system evolution in time when it undergoes undesirable fault conditions, are critical for an adequate implementation of successful prognostic systems. Prognosis may be understood as the generation of long-term predictions describing the evolution in time of a particular signal of interest or fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem. Predictions are made using a thorough understanding of the underlying processes and factor in the anticipated future usage.

Predicting phase behavior of mixtures of reservoir fluids with carbon dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grigg, R.B.; Lingane, P.J.

1983-10-01

The use of an equation of state to predict phase behavior during carbon dioxide flooding is well established. There is consensus that the characterization of the C fraction, the grouping of this fraction into ''pseudo components'', and the selection of interaction parameters are the most important variables. However, the literature is vague as to how to best select the pseudo components, especially when aiming for a few-component representation as for a field scale compositional simulation. Single-contact phase behavior is presented for mixtures of Ford Geraldine (Delaware), Maljamar (Grayburg), West Sussex (Shannon), and Reservoir D reservoir fluids, and of a syntheticmore » oil C/C/C, with carbon dioxide. One can reproduce the phase behavior of these mixtures using 3-5 pseudo components and common interaction parameters. The critical properties of the pseudo components are calculated from detailed oil characterizations. Because the parameters are not further adjusted, this approach reduces the empiricism in fitting phase data and may result in a more accurate representation of the system as the composition of the oil changes during the approach to miscibility.« less

Advances in Fatigue and Fracture Mechanics Analyses for Aircraft Structures

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1999-01-01

This paper reviews some of the advances that have been made in stress analyses of cracked aircraft components, in the understanding of the fatigue and fatigue-crack growth process, and in the prediction of residual strength of complex aircraft structures with widespread fatigue damage. Finite-element analyses of cracked structures are now used to determine accurate stress-intensity factors for cracks at structural details. Observations of small-crack behavior at open and rivet-loaded holes and the development of small-crack theory has lead to the prediction of stress-life behavior for components with stress concentrations under aircraft spectrum loading. Fatigue-crack growth under simulated aircraft spectra can now be predicted with the crack-closure concept. Residual strength of cracked panels with severe out-of-plane deformations (buckling) in the presence of stiffeners and multiple-site damage can be predicted with advanced elastic-plastic finite-element analyses and the critical crack-tip-opening angle (CTOA) fracture criterion. These advances are helping to assure continued safety of aircraft structures.

Advances in Fatigue and Fracture Mechanics Analyses for Metallic Aircraft Structures

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

2000-01-01

This paper reviews some of the advances that have been made in stress analyses of cracked aircraft components, in the understanding of the fatigue and fatigue-crack growth process, and in the prediction of residual strength of complex aircraft structures with widespread fatigue damage. Finite-element analyses of cracked metallic structures are now used to determine accurate stress-intensity factors for cracks at structural details. Observations of small-crack behavior at open and rivet-loaded holes and the development of small-crack theory has lead to the prediction of stress-life behavior for components with stress concentrations under aircraft spectrum loading. Fatigue-crack growth under simulated aircraft spectra can now be predicted with the crack-closure concept. Residual strength of cracked panels with severe out-of-plane deformations (buckling) in the presence of stiffeners and multiple-site damage can be predicted with advanced elastic-plastic finite-element analyses and the critical crack-tip-opening angle (CTOA) fracture criterion. These advances are helping to assure continued safety of aircraft structures.

Analyzing and Predicting Effort Associated with Finding and Fixing Software Faults

NASA Technical Reports Server (NTRS)

Hamill, Maggie; Goseva-Popstojanova, Katerina

2016-01-01

Context: Software developers spend a significant amount of time fixing faults. However, not many papers have addressed the actual effort needed to fix software faults. Objective: The objective of this paper is twofold: (1) analysis of the effort needed to fix software faults and how it was affected by several factors and (2) prediction of the level of fix implementation effort based on the information provided in software change requests. Method: The work is based on data related to 1200 failures, extracted from the change tracking system of a large NASA mission. The analysis includes descriptive and inferential statistics. Predictions are made using three supervised machine learning algorithms and three sampling techniques aimed at addressing the imbalanced data problem. Results: Our results show that (1) 83% of the total fix implementation effort was associated with only 20% of failures. (2) Both safety critical failures and post-release failures required three times more effort to fix compared to non-critical and pre-release counterparts, respectively. (3) Failures with fixes spread across multiple components or across multiple types of software artifacts required more effort. The spread across artifacts was more costly than spread across components. (4) Surprisingly, some types of faults associated with later life-cycle activities did not require significant effort. (5) The level of fix implementation effort was predicted with 73% overall accuracy using the original, imbalanced data. Using oversampling techniques improved the overall accuracy up to 77%. More importantly, oversampling significantly improved the prediction of the high level effort, from 31% to around 85%. Conclusions: This paper shows the importance of tying software failures to changes made to fix all associated faults, in one or more software components and/or in one or more software artifacts, and the benefit of studying how the spread of faults and other factors affect the fix implementation effort.

Prediction of vaccine candidates against Pseudomonas aeruginosa: An integrated genomics and proteomics approach.

PubMed

Rashid, Muhammad Ibrahim; Naz, Anam; Ali, Amjad; Andleeb, Saadia

2017-07-01

Pseudomonas aeruginosa is among top critical nosocomial infectious agents due to its persistent infections and tendency for acquiring drug resistance mechanisms. To date, there is no vaccine available for this pathogen. We attempted to exploit the genomic and proteomic information of P. aeruginosa though reverse-vaccinology approaches to unveil the prospective vaccine candidates. P. aeruginosa strain PAO1 genome was subjected to sequential prioritization approach following genomic, proteomics and structural analyses. Among, the predicted vaccine candidates: surface components of antibiotic efflux pumps (Q9HY88, PA2837), chaperone-usher pathway components (CupC2, CupB3), penicillin binding protein of bacterial cell wall (PBP1a/mrcA), extracellular component of Type 3 secretory system (PscC) and three uncharacterized secretory proteins (PA0629, PA2822, PA0978) were identified as potential candidates qualifying all the set criteria. These proteins were then analyzed for potential immunogenic surface exposed epitopes. These predicted epitopes may provide a basis for development of a reliable subunit vaccine against P. aeruginosa. Copyright © 2017 Elsevier Inc. All rights reserved.

Motor prediction in Brain-Computer Interfaces for controlling mobile robots.

PubMed

Geng, Tao; Gan, John Q

2008-01-01

EEG-based Brain-Computer Interface (BCI) can be regarded as a new channel for motor control except that it does not involve muscles. Normal neuromuscular motor control has two fundamental components: (1) to control the body, and (2) to predict the consequences of the control command, which is called motor prediction. In this study, after training with a specially designed BCI paradigm based on motor imagery, two subjects learnt to predict the time course of some features of the EEG signals. It is shown that, with this newly-obtained motor prediction skill, subjects can use motor imagery of feet to directly control a mobile robot to avoid obstacles and reach a small target in a time-critical scenario.

Instability-related delamination growth in thermoset and thermoplastic composites

NASA Technical Reports Server (NTRS)

Gillespie, John W., Jr.; Carlsson, Leif A.; Rothschilds, Robert J.

1988-01-01

Mixed-mode crack propagation in compressively loaded thermoset and thermoplastic composite columns with an imbedded through-width delamination is investigated. Beam theory is used to analyze the geometrically nonlinear load-deformation relationship of the delaminated subregion. The elastic restraint model (ERM), combined with existing FSM modeling of the crack-tip region, yields expressions for the Mode I and Mode II components of the strain energy release rate G(I) and G(II) to predict the critical load at the onset of delamination growth. Experimental data were generated for geometries yielding a wide range of G(I)/G(II) ratios at the onset of crack growth. A linear mixed-mode crack growth criterion in conjunctuion with the ERM provides good agreement between predicted and measured critical loads for both materials studied.

SLS Scale Model Acoustic Test Liftoff Results and Comparisons

NASA Technical Reports Server (NTRS)

Houston, Janice; Counter, Douglas; Giacomoni, Clothilde

2015-01-01

The liftoff phase induces acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are then used in the prediction of internal vibration responses of the vehicle and components which result in the qualification levels. Thus, predicting these liftoff acoustic (LOA) environments is critical to the design requirements of any launch vehicle. If there is a significant amount of uncertainty in the predictions or if acoustic mitigation options must be implemented, a subscale acoustic test is a feasible design phase test option to verify the LOA environments. The NASA Space Launch System (SLS) program initiated the Scale Model Acoustic Test (SMAT) to verify the predicted SLS LOA environments.

Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

USDA-ARS?s Scientific Manuscript database

Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

Genetic Model Fitting in IQ, Assortative Mating & Components of IQ Variance.

ERIC Educational Resources Information Center

Capron, Christiane; Vetta, Adrian R.; Vetta, Atam

1998-01-01

The biometrical school of scientists who fit models to IQ data traces their intellectual ancestry to R. Fisher (1918), but their genetic models have no predictive value. Fisher himself was critical of the concept of heritability, because assortative mating, such as for IQ, introduces complexities into the study of a genetic trait. (SLD)

The Coevolution of Society and Multimedia Technology: Issues in Predicting the Future Innovation and Use of a Ubiquitous Technology.

ERIC Educational Resources Information Center

Stewart, James; Williams, Robin

1998-01-01

Criticizes "technologically deterministic" approaches, which seek to extrapolate social change from technological potential. Shows how a three-layer model of component, system, and application technologies can be used to integrate findings from the use and development of technology in specific sectors. Examines three cases of…

Modeling Actual Evapotranspiration From Forested Watersheds Across the Southeastern United States

Treesearch

Jianbiao Lu; Ge Sun; Steven G. McNulty; Devendra M. Amatya

2003-01-01

About 50 to 80 percent of precipitation in the southeastern United States returns to the atmosphere by evapotranspiration. As evapotranspiration is a major component in the forest water balances, accurately quantifying it is critical to predicting the effects of forest management and global change on water, sediment, and nutrient yield from forested watersheds. However...

Benchmark Tests for Stirling Convertor Heater Head Life Assessment Conducted

NASA Technical Reports Server (NTRS)

Krause, David L.; Halford, Gary R.; Bowman, Randy R.

2004-01-01

A new in-house test capability has been developed at the NASA Glenn Research Center, where a critical component of the Stirling Radioisotope Generator (SRG) is undergoing extensive testing to aid the development of analytical life prediction methodology and to experimentally aid in verification of the flight-design component's life. The new facility includes two test rigs that are performing creep testing of the SRG heater head pressure vessel test articles at design temperature and with wall stresses ranging from operating level to seven times that (see the following photograph).

Progress toward an advanced condition monitoring system for reusable rocket engines

NASA Technical Reports Server (NTRS)

Maram, J.; Barkhoudarian, S.

1987-01-01

A new generation of advanced sensor technologies will allow the direct measurement of critical/degradable rocket engine components' health and the detection of degraded conditions before component deterioration affects engine performance, leading to substantial improvements in reusable engines' operation and maintenance. When combined with a computer-based engine condition-monitoring system, these sensors can furnish a continuously updated data base for the prediction of engine availability and advanced warning of emergent maintenance requirements. Attention is given to the case of a practical turbopump and combustion device diagnostic/prognostic health-monitoring system.

[Establishment of comprehensive prediction model of acute gastrointestinal injury classification of critically ill patients].

PubMed

Wang, Yan; Wang, Jianrong; Liu, Weiwei; Zhang, Guangliang

2018-03-25

To develop the comprehensive prediction model of acute gastrointestinal injury (AGI) grades of critically ill patients. From April 2015 to November 2015, the binary channel gastrointestinal sounds (GIS) monitor system which has been developed and verified by the research group was used to gather and analyze the GIS of 60 consecutive critically ill patients who were admitted in Critical Care Medicine of Chinese PLA General Hospital. Also, the AGI grades (Grande I(-IIII(, the higher the level, the heavier the gastrointestinal dysfunction) were evaluated. Meanwhile, the clinical data and physiological and biochemical indexes of included patients were collected and recorded daily, including illness severity score (APACHE II( score, consisting of the acute physiology score, age grade and chronic health evaluation), sequential organ failure assessment (SOFA score, including respiration, coagulation, liver, cardioascular, central nervous system and kidney) and Glasgow coma scale (GCS); body mass index, blood lactate and glucose, and treatment details (including mechanical ventilation, sedatives, vasoactive drugs, enteral nutrition, etc.) Then principal component analysis was performed on the significantly correlated GIS (five indexes of gastrointestinal sounds were found to be negatively correlated with AGI grades, which included the number, percentage of time, mean power, maximum power and maximum time of GIS wave from the channel located at the stomach) and clinical factors after standardization. The top 5 post-normalized main components were selected for back-propagation (BP) neural network training, to establish comprehensive AGI grades models of critically ill patients based on the neural network model. The 60 patients aged 19 to 98 (mean 54.6) years and included 42 males (70.0%). There were 22 cases of multiple fractures, 15 cases of severe infection, 7 cases of cervical vertebral fracture, 7 cases of aortic repair, 5 cases of post-toxicosis and 4 cases of cerebral trauma. There were 33 emergency operation, 10 cases of elecoperectomy and 17 cases of drug treatment. There were 56 cases of diabetes(93.3%). Forty-five cases (75.0%) used vasoactive drugs, 37 cases (61.7%) used mechanical ventilation and 44 cases (73.3%) used enteral nutrition. APACHE II( score were 4.0 to 28.0(average 16.8) points. Four clinical factors were significantly positively related with AGI grades, including lactic acid level (r=0.215, P=0.000), SOFA score (r=0.383, P=0.000), the use of vascular active drugs (r=0.611, P=0.000) and mechanical ventilation (r=0.142, P=0.014). In addition to the five indexes of gastric bowel sounds which were found to be negatively correlated with AGI grades, the characteristics of 333 by 9 were composed of these nine indexes with high correlation of AGI grades. Five main components were selected after principal component analysis of these nine correlated indexes. A comprehensive AGI grades model of critically ill patients with a fitting degree of 0.967 3 and an accuracy rate of 82.61% was built by BP artificial neural network. The comprehensive model to classify AGI grades with the GIS is developed, which can help further predicting the classification of AGI grades of critically ill patients.

Integrated Design Software Predicts the Creep Life of Monolithic Ceramic Components

NASA Technical Reports Server (NTRS)

1996-01-01

Significant improvements in propulsion and power generation for the next century will require revolutionary advances in high-temperature materials and structural design. Advanced ceramics are candidate materials for these elevated-temperature applications. As design protocols emerge for these material systems, designers must be aware of several innate features, including the degrading ability of ceramics to carry sustained load. Usually, time-dependent failure in ceramics occurs because of two different, delayedfailure mechanisms: slow crack growth and creep rupture. Slow crack growth initiates at a preexisting flaw and continues until a critical crack length is reached, causing catastrophic failure. Creep rupture, on the other hand, occurs because of bulk damage in the material: void nucleation and coalescence that eventually leads to macrocracks which then propagate to failure. Successful application of advanced ceramics depends on proper characterization of material behavior and the use of an appropriate design methodology. The life of a ceramic component can be predicted with the NASA Lewis Research Center's Ceramics Analysis and Reliability Evaluation of Structures (CARES) integrated design programs. CARES/CREEP determines the expected life of a component under creep conditions, and CARES/LIFE predicts the component life due to fast fracture and subcritical crack growth. The previously developed CARES/LIFE program has been used in numerous industrial and Government applications.

A recursive Bayesian approach for fatigue damage prognosis: An experimental validation at the reliability component level

NASA Astrophysics Data System (ADS)

Gobbato, Maurizio; Kosmatka, John B.; Conte, Joel P.

2014-04-01

Fatigue-induced damage is one of the most uncertain and highly unpredictable failure mechanisms for a large variety of mechanical and structural systems subjected to cyclic and random loads during their service life. A health monitoring system capable of (i) monitoring the critical components of these systems through non-destructive evaluation (NDE) techniques, (ii) assessing their structural integrity, (iii) recursively predicting their remaining fatigue life (RFL), and (iv) providing a cost-efficient reliability-based inspection and maintenance plan (RBIM) is therefore ultimately needed. In contribution to these objectives, the first part of the paper provides an overview and extension of a comprehensive reliability-based fatigue damage prognosis methodology — previously developed by the authors — for recursively predicting and updating the RFL of critical structural components and/or sub-components in aerospace structures. In the second part of the paper, a set of experimental fatigue test data, available in the literature, is used to provide a numerical verification and an experimental validation of the proposed framework at the reliability component level (i.e., single damage mechanism evolving at a single damage location). The results obtained from this study demonstrate (i) the importance and the benefits of a nearly continuous NDE monitoring system, (ii) the efficiency of the recursive Bayesian updating scheme, and (iii) the robustness of the proposed framework in recursively updating and improving the RFL estimations. This study also demonstrates that the proposed methodology can lead to either an extent of the RFL (with a consequent economical gain without compromising the minimum safety requirements) or an increase of safety by detecting a premature fault and therefore avoiding a very costly catastrophic failure.

Thermoacoustic effects in supercritical fluids near the critical point: Resonance, piston effect, and acoustic emission and reflection

NASA Astrophysics Data System (ADS)

Onuki, Akira

2007-12-01

We present a general theory of thermoacoustic phenomena in one phase states of one-component fluids. Singular behavior is predicted in supercritical fluids near the critical point. In a one-dimensional geometry we start with linearized hydrodynamic equations taking into account the effects of heat conduction in the boundary walls and the bulk viscosity. We introduce a coefficient Z(ω) characterizing reflection of sound with frequency ω at the boundary in a rigid cell. As applications, we examine acoustic eigenmodes, response to time-dependent perturbations, and sound emission and reflection. Resonance and rapid adiabatic changes are noteworthy. In these processes, the role of the thermal diffusion layers is enhanced near the critical point because of the strong critical divergence of the thermal expansion.

Two-dimensional symbiotic solitons and vortices in binary condensates with attractive cross-species interaction

PubMed Central

Ma, Xuekai; Driben, Rodislav; Malomed, Boris A.; Meier, Torsten; Schumacher, Stefan

2016-01-01

We consider a two-dimensional (2D) two-component spinor system with cubic attraction between the components and intra-species self-repulsion, which may be realized in atomic Bose-Einstein condensates, as well as in a quasi-equilibrium condensate of microcavity polaritons. Including a 2D spatially periodic potential, which is necessary for the stabilization of the system against the critical collapse, we use detailed numerical calculations and an analytical variational approximation (VA) to predict the existence and stability of several types of 2D symbiotic solitons in the spinor system. Stability ranges are found for symmetric and asymmetric symbiotic fundamental solitons and vortices, including hidden-vorticity (HV) modes, with opposite vorticities in the two components. The VA produces exceptionally accurate predictions for the fundamental solitons and vortices. The fundamental solitons, both symmetric and asymmetric ones, are completely stable, in either case when they exist as gap solitons or regular ones. The symmetric and asymmetric vortices are stable if the inter-component attraction is stronger than the intra-species repulsion, while the HV modes have their stability region in the opposite case. PMID:27703235

Degradation Prediction Model Based on a Neural Network with Dynamic Windows

PubMed Central

Zhang, Xinghui; Xiao, Lei; Kang, Jianshe

2015-01-01

Tracking degradation of mechanical components is very critical for effective maintenance decision making. Remaining useful life (RUL) estimation is a widely used form of degradation prediction. RUL prediction methods when enough run-to-failure condition monitoring data can be used have been fully researched, but for some high reliability components, it is very difficult to collect run-to-failure condition monitoring data, i.e., from normal to failure. Only a certain number of condition indicators in certain period can be used to estimate RUL. In addition, some existing prediction methods have problems which block RUL estimation due to poor extrapolability. The predicted value converges to a certain constant or fluctuates in certain range. Moreover, the fluctuant condition features also have bad effects on prediction. In order to solve these dilemmas, this paper proposes a RUL prediction model based on neural network with dynamic windows. This model mainly consists of three steps: window size determination by increasing rate, change point detection and rolling prediction. The proposed method has two dominant strengths. One is that the proposed approach does not need to assume the degradation trajectory is subject to a certain distribution. The other is it can adapt to variation of degradation indicators which greatly benefits RUL prediction. Finally, the performance of the proposed RUL prediction model is validated by real field data and simulation data. PMID:25806873

Predicting Great Lakes fish yields: tools and constraints

USGS Publications Warehouse

Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

1987-01-01

Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

Climate and species functional traits influence maximum live tree stocking in the Lake States, USA

Treesearch

Mark J. Ducey; Christopher W. Woodall; Andrés Bravo-Oviedo

2017-01-01

Quantifying the density of live trees in forest stands and partitioning it between species or other stand components is critical for predicting forest dynamics and responses to management, as well as understanding the impacts of stand composition and structure on productivity. As plant traits such as shade tolerance have been proven to refine understanding of plant...

Understory cover and biomass indices predictions for forest ecosystems of the Northwestern United States

Treesearch

Vasile A. Suchar; Nicholas L. Crookston

2010-01-01

The understory community is a critical component of many processes of forest ecosystems. Cover and biomass indices of shrubs and herbs of forested ecosystems of Northwestern United States are presented. Various forest data were recorded for 10,895 plots during a Current Vegetation Survey, over the National Forest lands of entire Pacific Northwest. No significant...

Predicting longleaf pine coarse root decomposition in the southeastern US

Treesearch

Peter H. Anderson; Kurt H. Johnsen; John R. Butnor; Carlos A. Gonzalez-Benecke; Lisa J. Samuelson

2018-01-01

Storage of belowground carbon (C) is an important component of total forest C. However, belowground C changes temporally due to forest growth and tree mortality (natural and via harvesting) and these fluctuations are critical for modeling C in forests under varying management regimes. To date, little progress has been made in quantifying the rate of decay of southern...

Learning for the Next Generation: Predicting the Usage of Synthetic Learning Environments

ERIC Educational Resources Information Center

Evans, Arthur William, III

2010-01-01

The push to further the use of technology in learning has broadened the attempts of many to find innovated ways to aid the new, technologically savvy generation of learners, in acquiring the knowledge needed for their education and training. A critical component to the success of these initiatives is the proper application of the "science of…

Empirical modeling of spatial and temporal variation in warm season nocturnal air temperatures in two North Idaho mountain ranges, USA

Treesearch

Zachery A. Holden; Michael A. Crimmins; Samuel A. Cushman; Jeremy S. Littell

2010-01-01

Accurate, fine spatial resolution predictions of surface air temperatures are critical for understanding many hydrologic and ecological processes. This study examines the spatial and temporal variability in nocturnal air temperatures across a mountainous region of Northern Idaho. Principal components analysis (PCA) was applied to a network of 70 Hobo temperature...

An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems

Treesearch

Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun

2002-01-01

Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...

Evaluating critical uncertainty thresholds in a spatial model of forest pest invasion risk

Treesearch

Frank H. Koch; Denys Yemshanov; Daniel W. McKenney; William D. Smith

2009-01-01

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model’s numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for...

Residual Strength Analysis Methodology: Laboratory Coupons to Structural Components

NASA Technical Reports Server (NTRS)

Dawicke, D. S.; Newman, J. C., Jr.; Starnes, J. H., Jr.; Rose, C. A.; Young, R. D.; Seshadri, B. R.

2000-01-01

The NASA Aircraft Structural Integrity (NASIP) and Airframe Airworthiness Assurance/Aging Aircraft (AAA/AA) Programs have developed a residual strength prediction methodology for aircraft fuselage structures. This methodology has been experimentally verified for structures ranging from laboratory coupons up to full-scale structural components. The methodology uses the critical crack tip opening angle (CTOA) fracture criterion to characterize the fracture behavior and a material and a geometric nonlinear finite element shell analysis code to perform the structural analyses. The present paper presents the results of a study to evaluate the fracture behavior of 2024-T3 aluminum alloys with thickness of 0.04 inches to 0.09 inches. The critical CTOA and the corresponding plane strain core height necessary to simulate through-the-thickness effects at the crack tip in an otherwise plane stress analysis, were determined from small laboratory specimens. Using these parameters, the CTOA fracture criterion was used to predict the behavior of middle crack tension specimens that were up to 40 inches wide, flat panels with riveted stiffeners and multiple-site damage cracks, 18-inch diameter pressurized cylinders, and full scale curved stiffened panels subjected to internal pressure and mechanical loads.

Prediction of Metabolism of Drugs using Artificial Intelligence: How far have we reached?

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2016-01-01

Information about drug metabolism is an essential component of drug development. Modeling the drug metabolism requires identification of the involved enzymes, rate and extent of metabolism, the sites of metabolism etc. There has been continuous attempts in the prediction of metabolism of drugs using artificial intelligence in effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are number of predictive models available for metabolism using Support vector machines, Artificial neural networks, Bayesian classifiers etc. There is an urgent need to review their progress so far and address the existing challenges in prediction of metabolism. In this attempt, we are presenting the currently available literature models and some of the critical issues regarding prediction of drug metabolism.

Monitoring Wind Turbine Loading Using Power Converter Signals

NASA Astrophysics Data System (ADS)

Rieg, C. A.; Smith, C. J.; Crabtree, C. J.

2016-09-01

The ability to detect faults and predict loads on a wind turbine drivetrain's mechanical components cost-effectively is critical to making the cost of wind energy competitive. In order to investigate whether this is possible using the readily available power converter current signals, an existing permanent magnet synchronous generator based wind energy conversion system computer model was modified to include a grid-side converter (GSC) for an improved converter model and a gearbox. The GSC maintains a constant DC link voltage via vector control. The gearbox was modelled as a 3-mass model to allow faults to be included. Gusts and gearbox faults were introduced to investigate the ability of the machine side converter (MSC) current (I q) to detect and quantify loads on the mechanical components. In this model, gearbox faults were not detectable in the I q signal due to shaft stiffness and damping interaction. However, a model that predicts the load change on mechanical wind turbine components using I q was developed and verified using synthetic and real wind data.

Advanced oxide dispersion strengthened sheet alloys for improved combustor durability

NASA Technical Reports Server (NTRS)

Henricks, R. J.

1981-01-01

Burner design modifications that will take advantage of the improved creep and cyclic oxidation resistance of oxide dispersion strengthened (ODS) alloys while accommodating the reduced fatigue properties of these materials were evaluated based on preliminary analysis and life predictions, on construction and repair feasibility, and on maintenance and direct operating costs. Two designs - the film cooled, segmented louver and the transpiration cooled, segmented twin Wall - were selected for low cycle fatigue (LCF) component testing. Detailed thermal and structural analysis of these designs established the strain range and temprature at critical locations resulting in predicted lives of 10,000 cycles for MA 956 alloy. The ODs alloys, MA 956 and HDA 8077, demonstrated a 167 C (300 F) temperature advantage over Hastelloy X alloy in creep strength and oxidation resistance. The MA 956 alloy was selected for mechanical property and component test evaluations. The MA 956 alloy was superior to Hastelloy X in LCF component testing of the film cooled, segmented louver design.

NASA GRC Fatigue Crack Initiation Life Prediction Models

NASA Technical Reports Server (NTRS)

Arya, Vinod K.; Halford, Gary R.

2002-01-01

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable, more cost effective, and better performing products. In other words, as the envelope is expanded, components are then designed to operate just as close to the newly expanded envelope as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

A Primer In Advanced Fatigue Life Prediction Methods

NASA Technical Reports Server (NTRS)

Halford, Gary R.

2000-01-01

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable more cost effective, and better performing products. In other words, as the envelop is expanded, components are then designed to operate just as close to the newly expanded envelop as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

NASA GRC Fatigue Crack Initiation Life Prediction Models

NASA Astrophysics Data System (ADS)

Arya, Vinod K.; Halford, Gary R.

2002-10-01

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable, more cost effective, and better performing products. In other words, as the envelope is expanded, components are then designed to operate just as close to the newly expanded envelope as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

PubMed

Méndez, Raúl; Leplae, Raphaël; Lensink, Marc F; Wodak, Shoshana J

2005-08-01

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the performance of docking methods is being achieved, with CAPRI acting as the catalyst.

An Integrated Ensemble-Based Operational Framework to Predict Urban Flooding: A Case Study of Hurricane Sandy in the Passaic and Hackensack River Basins

NASA Astrophysics Data System (ADS)

Saleh, F.; Ramaswamy, V.; Georgas, N.; Blumberg, A. F.; Wang, Y.

2016-12-01

Advances in computational resources and modeling techniques are opening the path to effectively integrate existing complex models. In the context of flood prediction, recent extreme events have demonstrated the importance of integrating components of the hydrosystem to better represent the interactions amongst different physical processes and phenomena. As such, there is a pressing need to develop holistic and cross-disciplinary modeling frameworks that effectively integrate existing models and better represent the operative dynamics. This work presents a novel Hydrologic-Hydraulic-Hydrodynamic Ensemble (H3E) flood prediction framework that operationally integrates existing predictive models representing coastal (New York Harbor Observing and Prediction System, NYHOPS), hydrologic (US Army Corps of Engineers Hydrologic Modeling System, HEC-HMS) and hydraulic (2-dimensional River Analysis System, HEC-RAS) components. The state-of-the-art framework is forced with 125 ensemble meteorological inputs from numerical weather prediction models including the Global Ensemble Forecast System, the European Centre for Medium-Range Weather Forecasts (ECMWF), the Canadian Meteorological Centre (CMC), the Short Range Ensemble Forecast (SREF) and the North American Mesoscale Forecast System (NAM). The framework produces, within a 96-hour forecast horizon, on-the-fly Google Earth flood maps that provide critical information for decision makers and emergency preparedness managers. The utility of the framework was demonstrated by retrospectively forecasting an extreme flood event, hurricane Sandy in the Passaic and Hackensack watersheds (New Jersey, USA). Hurricane Sandy caused significant damage to a number of critical facilities in this area including the New Jersey Transit's main storage and maintenance facility. The results of this work demonstrate that ensemble based frameworks provide improved flood predictions and useful information about associated uncertainties, thus improving the assessment of risks as when compared to a deterministic forecast. The work offers perspectives for short-term flood forecasts, flood mitigation strategies and best management practices for climate change scenarios.

The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Young, Jonathan; Thompson, Sandra E.; Brothers, Alan J.

The ability to estimate the likelihood of future events based on current and historical data is essential to the decision making process of many government agencies. Successful predictions related to terror events and characterizing the risks will support development of options for countering these events. The predictive tasks involve both technical and social component models. The social components have presented a particularly difficult challenge. This paper outlines some technical considerations of this modeling activity. Both data and predictions associated with the technical and social models will likely be known with differing certainties or accuracies – a critical challenge is linkingmore » across these model domains while respecting this fundamental difference in certainty level. This paper will describe the technical approach being taken to develop the social model and identification of the significant interfaces between the technical and social modeling in the context of analysis of diversion of nuclear material.« less

Prognostics for Electronics Components of Avionics Systems

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saha, Bhaskar; Wysocki, Philip F.; Goebel, Kai F.

2009-01-01

Electronics components have and increasingly critical role in avionics systems and for the development of future aircraft systems. Prognostics of such components is becoming a very important research filed as a result of the need to provide aircraft systems with system level health management. This paper reports on a prognostics application for electronics components of avionics systems, in particular, its application to the Isolated Gate Bipolar Transistor (IGBT). The remaining useful life prediction for the IGBT is based on the particle filter framework, leveraging data from an accelerated aging tests on IGBTs. The accelerated aging test provided thermal-electrical overstress by applying thermal cycling to the device. In-situ state monitoring, including measurements of the steady-state voltages and currents, electrical transients, and thermal transients are recorded and used as potential precursors of failure.

Towards Prognostics for Electronics Components

NASA Technical Reports Server (NTRS)

Saha, Bhaskar; Celaya, Jose R.; Wysocki, Philip F.; Goebel, Kai F.

2013-01-01

Electronics components have an increasingly critical role in avionics systems and in the development of future aircraft systems. Prognostics of such components is becoming a very important research field as a result of the need to provide aircraft systems with system level health management information. This paper focuses on a prognostics application for electronics components within avionics systems, and in particular its application to an Isolated Gate Bipolar Transistor (IGBT). This application utilizes the remaining useful life prediction, accomplished by employing the particle filter framework, leveraging data from accelerated aging tests on IGBTs. These tests induced thermal-electrical overstresses by applying thermal cycling to the IGBT devices. In-situ state monitoring, including measurements of steady-state voltages and currents, electrical transients, and thermal transients are recorded and used as potential precursors of failure.

Re-Tooling the Agency's Engineering Predictive Practices for Durability and Damage Tolerance

NASA Technical Reports Server (NTRS)

Piascik, Robert S.; Knight, Norman F., Jr.

2017-01-01

Over the past decade, the Agency has placed less emphasis on testing and has increasingly relied on computational methods to assess durability and damage tolerance (D&DT) behavior when evaluating design margins for fracture-critical components. With increased emphasis on computational D&DT methods as the standard practice, it is paramount that capabilities of these methods are understood, the methods are used within their technical limits, and validation by well-designed tests confirms understanding. The D&DT performance of a component is highly dependent on parameters in the neighborhood of the damage. This report discusses D&DT method vulnerabilities.

Probabilistic Structural Analysis Theory Development

NASA Technical Reports Server (NTRS)

Burnside, O. H.

1985-01-01

The objective of the Probabilistic Structural Analysis Methods (PSAM) project is to develop analysis techniques and computer programs for predicting the probabilistic response of critical structural components for current and future space propulsion systems. This technology will play a central role in establishing system performance and durability. The first year's technical activity is concentrating on probabilistic finite element formulation strategy and code development. Work is also in progress to survey critical materials and space shuttle mian engine components. The probabilistic finite element computer program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) is being developed. The final probabilistic code will have, in the general case, the capability of performing nonlinear dynamic of stochastic structures. It is the goal of the approximate methods effort to increase problem solving efficiency relative to finite element methods by using energy methods to generate trial solutions which satisfy the structural boundary conditions. These approximate methods will be less computer intensive relative to the finite element approach.

Predicting biomaterial property-dendritic cell phenotype relationships from the multivariate analysis of responses to polymethacrylates

PubMed Central

Kou, Peng Meng; Pallassana, Narayanan; Bowden, Rebeca; Cunningham, Barry; Joy, Abraham; Kohn, Joachim; Babensee, Julia E.

2011-01-01

Dendritic cells (DCs) play a critical role in orchestrating the host responses to a wide variety of foreign antigens and are essential in maintaining immune tolerance. Distinct biomaterials have been shown to differentially affect the phenotype of DCs, which suggested that biomaterials may be used to modulate immune response towards the biologic component in combination products. The elucidation of biomaterial property-DC phenotype relationships is expected to inform rational design of immuno-modulatory biomaterials. In this study, DC response to a set of 12 polymethacrylates (pMAs) was assessed in terms of surface marker expression and cytokine profile. Principal component analysis (PCA) determined that surface carbon correlated with enhanced DC maturation, while surface oxygen was associated with an immature DC phenotype. Partial square linear regression, a multivariate modeling approach, was implemented and successfully predicted biomaterial-induced DC phenotype in terms of surface marker expression from biomaterial properties with R2prediction = 0.76. Furthermore, prediction of DC phenotype was effective based on only theoretical chemical composition of the bulk polymers with R2prediction = 0.80. These results demonstrated that immune cell response can be predicted from biomaterial properties, and computational models will expedite future biomaterial design and selection. PMID:22136715

Predictive battlespace awareness and effects-based operations from a Homeland Security perspective: a wargaming opportunity

NASA Astrophysics Data System (ADS)

Williams, James K.; Hubbard, Zachary P.

2003-09-01

Effects Based Operations (EBO) and Predictive Battlespace Awareness (PBA) are intimately linked. Intelligence Preparation of the Battlespace (IPB), the predictive component of PBA, provides a structured analytical process for defining the battlespace environment, describing the battlespace effects that influence all sides, modeling the adversary, and determining likely enemy courses of action (COA). IPB documents some of the necessary elements of EBO, such as centers of gravity, counter-COAs, and indicators. The IPB process has been adapted to Information Operations (IO) through Intelligence Preparation of the Information Battlespace (IPIB), a prototype system for cyber-defense. IPIB ranks Enemy cyber-COAs and lists mission-critical network assets that must be defended. It is clear that IPIB can be inverted for developing COAs that implement EBO, and the prototype is being modified for offensive IO. Full-spectrum EBO would combine kinetic, cyber, and cognitive COAs to affect an adversary's behavior. This paper uses a Critical Infrastructure Protection (CIP) scenario to: 1) Provide an example of EBO-based PBA for CIP. 2) Illustrate the interaction between EBO and PBA. 3) Demonstrate the need for a national Critical Infrastructure vulnerability assessment. 4) Identify why simulation and wargaming are the most viable means of performing such an assessment.

Unit-Sphere Anisotropic Multiaxial Stochastic-Strength Model Probability Density Distribution for the Orientation of Critical Flaws

NASA Technical Reports Server (NTRS)

Nemeth, Noel

2013-01-01

Models that predict the failure probability of monolithic glass and ceramic components under multiaxial loading have been developed by authors such as Batdorf, Evans, and Matsuo. These "unit-sphere" failure models assume that the strength-controlling flaws are randomly oriented, noninteracting planar microcracks of specified geometry but of variable size. This report develops a formulation to describe the probability density distribution of the orientation of critical strength-controlling flaws that results from an applied load. This distribution is a function of the multiaxial stress state, the shear sensitivity of the flaws, the Weibull modulus, and the strength anisotropy. Examples are provided showing the predicted response on the unit sphere for various stress states for isotropic and transversely isotropic (anisotropic) materials--including the most probable orientation of critical flaws for offset uniaxial loads with strength anisotropy. The author anticipates that this information could be used to determine anisotropic stiffness degradation or anisotropic damage evolution for individual brittle (or quasi-brittle) composite material constituents within finite element or micromechanics-based software

A Model-based Prognostics Methodology for Electrolytic Capacitors Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose; Kulkarni, Chetan; Biswas, Gautam; Saha, Sankalita; Goebel, Kai

2011-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Towards A Model-Based Prognostics Methodology for Electrolytic Capacitors: A Case Study Based on Electrical Overstress Accelerated Aging

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Kulkarni, Chetan S.; Biswas, Gautam; Goebel, Kai

2012-01-01

A remaining useful life prediction methodology for electrolytic capacitors is presented. This methodology is based on the Kalman filter framework and an empirical degradation model. Electrolytic capacitors are used in several applications ranging from power supplies on critical avionics equipment to power drivers for electro-mechanical actuators. These devices are known for their comparatively low reliability and given their criticality in electronics subsystems they are a good candidate for component level prognostics and health management. Prognostics provides a way to assess remaining useful life of a capacitor based on its current state of health and its anticipated future usage and operational conditions. We present here also, experimental results of an accelerated aging test under electrical stresses. The data obtained in this test form the basis for a remaining life prediction algorithm where a model of the degradation process is suggested. This preliminary remaining life prediction algorithm serves as a demonstration of how prognostics methodologies could be used for electrolytic capacitors. In addition, the use degradation progression data from accelerated aging, provides an avenue for validation of applications of the Kalman filter based prognostics methods typically used for remaining useful life predictions in other applications.

Drought: A comprehensive R package for drought monitoring, prediction and analysis

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Cheng, Hongguang

2015-04-01

Drought may impose serious challenges to human societies and ecosystems. Due to complicated causing effects and wide impacts, a universally accepted definition of drought does not exist. The drought indicator is commonly used to characterize drought properties such as duration or severity. Various drought indicators have been developed in the past few decades for the monitoring of a certain aspect of drought condition along with the development of multivariate drought indices for drought characterizations from multiple sources or hydro-climatic variables. Reliable drought prediction with suitable drought indicators is critical to the drought preparedness plan to reduce potential drought impacts. In addition, drought analysis to quantify the risk of drought properties would provide useful information for operation drought managements. The drought monitoring, prediction and risk analysis are important components in drought modeling and assessments. In this study, a comprehensive R package "drought" is developed to aid the drought monitoring, prediction and risk analysis (available from R-Forge and CRAN soon). The computation of a suite of univariate and multivariate drought indices that integrate drought information from various sources such as precipitation, temperature, soil moisture, and runoff is available in the drought monitoring component in the package. The drought prediction/forecasting component consists of statistical drought predictions to enhance the drought early warning for decision makings. Analysis of drought properties such as duration and severity is also provided in this package for drought risk assessments. Based on this package, a drought monitoring and prediction/forecasting system is under development as a decision supporting tool. The package will be provided freely to the public to aid the drought modeling and assessment for researchers and practitioners.

TU-C-17A-10: Patient Features Based Dosimetric Pareto Front Prediction In Esophagus Cancer Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, J; Zhao, K; Peng, J

2014-06-15

Purpose: The purpose of this study is to study the feasibility of the dosimetric pareto front (PF) prediction based on patient anatomic and dosimetric parameters for esophagus cancer patients. Methods: Sixty esophagus patients in our institution were enrolled in this study. A total 2920 IMRT plans were created to generated PF for each patient. On average, each patient had 48 plans. The anatomic and dosimetric features were extracted from those plans. The mean lung dose (MLD), mean heart dose (MHD), spinal cord max dose and PTV homogeneous index (PTVHI) were recorded for each plan. The principal component analysis (PCA) wasmore » used to extract overlap volume histogram (OVH) features between PTV and other critical organs. The full dataset was separated into two parts include the training dataset and the validation dataset. The prediction outcomes were the MHD and MLD for the current study. The spearman rank correlation coefficient was used to evaluate the correlation between the anatomical features and dosimetric features. The PF was fit by the the stepwise multiple regression method. The cross-validation method was used to evaluation the model. Results: The mean prediction error of the MHD was 465 cGy with 100 repetitions. The most correlated factors were the first principal components of the OVH between heart and PTV, and the overlap between heart and PTV in Z-axis. The mean prediction error of the MLD was 195 cGy. The most correlated factors were the first principal components of the OVH between lung and PTV, and the overlap between lung and PTV in Z-axis. Conclusion: It is feasible to use patients anatomic and dosimetric features to generate a predicted PF. Additional samples and further studies were required to get a better prediction model.« less

Composite Interlaminar Shear Fracture Toughness, G(sub 2c): Shear Measurement of Sheer Myth?

NASA Technical Reports Server (NTRS)

OBrien, T. Kevin

1997-01-01

The concept of G2c as a measure of the interlaminar shear fracture toughness of a composite material is critically examined. In particular, it is argued that the apparent G2c as typically measured is inconsistent with the original definition of shear fracture. It is shown that interlaminar shear failure actually consists of tension failures in the resin rich layers between plies followed by the coalescence of ligaments created by these failures and not the sliding of two planes relative to one another that is assumed in fracture mechanics theory. Several strain energy release rate solutions are reviewed for delamination in composite laminates and structural components where failures have been experimentally documented. Failures typically occur at a location where the mode 1 component accounts for at least one half of the total G at failure. Hence, it is the mode I and mixed-mode interlaminar fracture toughness data that will be most useful in predicting delamination failure in composite components in service. Although apparent G2c measurements may prove useful for completeness of generating mixed-mode criteria, the accuracy of these measurements may have very little influence on the prediction of mixed-mode failures in most structural components.

UManSysProp: An online and open-source facility for molecular property prediction and atmospheric aerosol calculations

NASA Astrophysics Data System (ADS)

Topping, David; Barley, Mark; McFiggans, Gordon; Aumont, Bernard

2016-04-01

The many thousands of individual aerosol components ensure that explicit manual calculation of properties that influence their environmental impacts is laborious and time-consuming. The emergence of explicit automatic mechanism generation techniques, including up to many millions of individual gas phase products as aerosol precursors, renders manual calculations impossible and automation is necessary. It can be difficult to establish what factors are responsible for the outcome of a model prediction. This is particularly true when the number of components might be high in, for example, SOA mass partitioning simulations. It then becomes difficult for others in the community to assess the results presented. This might be complicated by the need to include pure component vapour pressures or activity coefficient predictions for a wide range of highly multifunctional compounds. It isn't clear to what extent replication of results is ever achieved for a range of aerosol simulations. Whilst this might also be an issue with results from instrumentation, the development of community driven software at least enables modellers to tackle this problem directly. Here we describe the development and application of a new web based facility, UManSysProp, to tackle such issues. Current facilities include: pure component vapour pressures, critical properties and sub-cooled densities of organic molecules; activity coefficient predictions for mixed inorganic-organic liquid systems; hygroscopic growth factors and CCN activation potential of mixed inorganic/organic aerosol particles with associated Kappa-Kohler values; absorptive partitioning calculations with/without a treatment of non-ideality. The website can be found here: http://umansysprop.seaes.manchester.ac.uk/

Are abrupt climate changes predictable?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2013-04-01

It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope record is presented. The result of the analysis points to a fundamental limitation in predictability of the third kind. Reference: P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, 2010

Magnetic Control of Convection in Electrically Nonconducting Fluids

NASA Technical Reports Server (NTRS)

Huang, Jie; Gray, Donald D.; Edwards, Boyd F.

1999-01-01

Inhomogeneous magnetic fields exert a body force on electrically nonconducting, magnetically permeable fluids. This force can be used to compensate for gravity and to control convection. The effects of uniform and nonuniform magnetic fields on a laterally unbounded fluid layer heated from below or above are studied using a linear stability analysis of the Navier-Stokes equations supplemented by Maxwell's equations and the appropriate magnetic body force. For a uniform oblique field, the analysis shows that longitudinal rolls with axes parallel to the horizontal component of the field are the rolls most unstable to convection. The corresponding critical Rayleigh number and critical wavelength for the onset of such rolls are less than the well-known Rayleigh-Benard values in the absence of magnetic fields. Vertical fields maximize these deviations, which vanish for horizontal fields. Horizontal fields increase the critical Rayleigh number and the critical wavelength for all rolls except longitudinal rolls. For a nonuniform field, our analysis shows that the magnetic effect on convection is represented by a dimensionless vector parameter which measures the relative strength of the induced magnetic buoyancy force due to the applied field gradient. The vertical component of this parameter competes with the gravitational buoyancy effect, and a critical relationship between this component and the Rayleigh number is identified for the onset of convection. Therefore, Rayleigh-Benard convection in such fluids can be enhanced or suppressed by the field. It also shows that magnetothermal convection is possible in both paramagnetic and diamagnetic fluids. Our theoretical predictions for paramagnetic fluids agree with experiments. Magnetically driven convection in diamagnetic fluids should be observable even in pure water using current technology.

Predicting phase behavior of mixtures of reservoir fluids with carbon dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grigg, R.B.; Lingane, P.J.

1983-01-01

The use of an equation of state to predict phase behavior during carbon dioxide flooding is well established. The characterization of the C/sub 7/ fraction and the selection of interaction parameters are the most important variables. Single-contact phase behavior is presented for mixtures of Ford Geraldine (Delaware), Maljamar (Grayburg), West Sussex (Shannon), and Reservoir D reservoir fluids, and of a synthetic oil with carbon dioxide. The phase behavior of these mixtures can be reproduced using 3 to 5 pseudo components and common interaction parameters. The critical properties of the pseudo components are calculated from detailed oil characterizations. Because the parametersmore » are not further adjusted, this approach reduces the empiricism in fitting phase data and may result in a more accurate representation of the system as the composition of the oil changes during the approach to miscibility. 21 references.« less

Peculiarities of field penetration in the presence of cross-flux interaction

NASA Astrophysics Data System (ADS)

Berseth, V.; Buzdin, A. I.; Indenbom, M. V.; Benoit, W.

1996-02-01

The attractive core interaction between two orthogonal vortex lattices in alayered superconductor is calculated. When one of these lattices is moving, this interaction gives rise to a drag force acting on the other one. Considering a moving in-plane flux lattice, the effect of the drag force on the perpendicular flux is modelled through a modification of the bulk critical current for this field component. The new critical current depends on the direction of motion of both parallel and perpendicular vortices. The results are derived within the critical-state model for the infinite slab and for the thin strip. For this latter geometry, computations are made with the help of a new numerical method simulating flux penetration in the critical state. The new predicted qualitative phenomena (like the formation of a vortex-free region between two zones of opposite flux in the flat geometry) can be directly verified by the magneto-optic technique.

Quantitative analysis of red wine tannins using Fourier-transform mid-infrared spectrometry.

PubMed

Fernandez, Katherina; Agosin, Eduardo

2007-09-05

Tannin content and composition are critical quality components of red wines. No spectroscopic method assessing these phenols in wine has been described so far. We report here a new method using Fourier transform mid-infrared (FT-MIR) spectroscopy and chemometric techniques for the quantitative analysis of red wine tannins. Calibration models were developed using protein precipitation and phloroglucinolysis as analytical reference methods. After spectra preprocessing, six different predictive partial least-squares (PLS) models were evaluated, including the use of interval selection procedures such as iPLS and CSMWPLS. PLS regression with full-range (650-4000 cm(-1)), second derivative of the spectra and phloroglucinolysis as the reference method gave the most accurate determination for tannin concentration (RMSEC = 2.6%, RMSEP = 9.4%, r = 0.995). The prediction of the mean degree of polymerization (mDP) of the tannins also gave a reasonable prediction (RMSEC = 6.7%, RMSEP = 10.3%, r = 0.958). These results represent the first step in the development of a spectroscopic methodology for the quantification of several phenolic compounds that are critical for wine quality.

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

PubMed Central

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

Reliability analysis and initial requirements for FC systems and stacks

NASA Astrophysics Data System (ADS)

Åström, K.; Fontell, E.; Virtanen, S.

In the year 2000 Wärtsilä Corporation started an R&D program to develop SOFC systems for CHP applications. The program aims to bring to the market highly efficient, clean and cost competitive fuel cell systems with rated power output in the range of 50-250 kW for distributed generation and marine applications. In the program Wärtsilä focuses on system integration and development. System reliability and availability are key issues determining the competitiveness of the SOFC technology. In Wärtsilä, methods have been implemented for analysing the system in respect to reliability and safety as well as for defining reliability requirements for system components. A fault tree representation is used as the basis for reliability prediction analysis. A dynamic simulation technique has been developed to allow for non-static properties in the fault tree logic modelling. Special emphasis has been placed on reliability analysis of the fuel cell stacks in the system. A method for assessing reliability and critical failure predictability requirements for fuel cell stacks in a system consisting of several stacks has been developed. The method is based on a qualitative model of the stack configuration where each stack can be in a functional, partially failed or critically failed state, each of the states having different failure rates and effects on the system behaviour. The main purpose of the method is to understand the effect of stack reliability, critical failure predictability and operating strategy on the system reliability and availability. An example configuration, consisting of 5 × 5 stacks (series of 5 sets of 5 parallel stacks) is analysed in respect to stack reliability requirements as a function of predictability of critical failures and Weibull shape factor of failure rate distributions.

Subscale Acoustic Testing: Comparison of ALAT and ASMAT

NASA Technical Reports Server (NTRS)

Houston, Janice D.; Counter, Douglas

2014-01-01

The liftoff phase induces acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are then used in the prediction of internal vibration responses of the vehicle and components which result in the qualification levels. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle. If there is a significant amount of uncertainty in the predictions or if acoustic mitigation options must be implemented, a subscale acoustic test is a feasible pre-launch test option. This paper compares the acoustic measurements of two different subscale tests: the 2% Ares Liftoff Acoustic Test conducted at Stennis Space Center and the 5% Ares I Scale Model Acoustic Test conducted at Marshall Space Flight Center.

Microstructure based simulations for prediction of flow curves and selection of process parameters for inter-critical annealing in DP steel

NASA Astrophysics Data System (ADS)

Deepu, M. J.; Farivar, H.; Prahl, U.; Phanikumar, G.

2017-04-01

Dual phase steels are versatile advanced high strength steels that are being used for sheet metal applications in automotive industry. It also has the potential for application in bulk components like gear. The inter-critical annealing in dual phase steels is one of the crucial steps that determine the mechanical properties of the material. Selection of the process parameters for inter-critical annealing, in particular, the inter-critical annealing temperature and time is important as it plays a major role in determining the volume fractions of ferrite and martensite, which in turn determines the mechanical properties. Selection of these process parameters to obtain a particular required mechanical property requires large number of experimental trials. Simulation of microstructure evolution and virtual compression/tensile testing can help in reducing the number of such experimental trials. In the present work, phase field modeling implemented in the commercial software Micress® is used to predict the microstructure evolution during inter-critical annealing. Virtual compression tests are performed on the simulated microstructure using finite element method implemented in the commercial software, to obtain the effective flow curve of the macroscopic material. The flow curves obtained by simulation are experimentally validated with physical simulation in Gleeble® and compared with that obtained using linear rule of mixture. The methodology could be used in determining the inter-critical annealing process parameters required for achieving a particular flow curve.

Real-Time Prognostics of a Rotary Valve Actuator

NASA Technical Reports Server (NTRS)

Daigle, Matthew

2015-01-01

Valves are used in many domains and often have system-critical functions. As such, it is important to monitor the health of valves and their actuators and predict remaining useful life. In this work, we develop a model-based prognostics approach for a rotary valve actuator. Due to limited observability of the component with multiple failure modes, a lumped damage approach is proposed for estimation and prediction of damage progression. In order to support the goal of real-time prognostics, an approach to prediction is developed that does not require online simulation to compute remaining life, rather, a function mapping the damage state to remaining useful life is found offline so that predictions can be made quickly online with a single function evaluation. Simulation results demonstrate the overall methodology, validating the lumped damage approach and demonstrating real-time prognostics.

Stress Analysis of B-52B and B-52H Air-Launching Systems Failure-Critical Structural Components

NASA Technical Reports Server (NTRS)

Ko, William L.

2005-01-01

The operational life analysis of any airborne failure-critical structural component requires the stress-load equation, which relates the applied load to the maximum tangential tensile stress at the critical stress point. The failure-critical structural components identified are the B-52B Pegasus pylon adapter shackles, B-52B Pegasus pylon hooks, B-52H airplane pylon hooks, B-52H airplane front fittings, B-52H airplane rear pylon fitting, and the B-52H airplane pylon lower sway brace. Finite-element stress analysis was performed on the said structural components, and the critical stress point was located and the stress-load equation was established for each failure-critical structural component. The ultimate load, yield load, and proof load needed for operational life analysis were established for each failure-critical structural component.

Model-Based Fault Diagnosis: Performing Root Cause and Impact Analyses in Real Time

NASA Technical Reports Server (NTRS)

Figueroa, Jorge F.; Walker, Mark G.; Kapadia, Ravi; Morris, Jonathan

2012-01-01

Generic, object-oriented fault models, built according to causal-directed graph theory, have been integrated into an overall software architecture dedicated to monitoring and predicting the health of mission- critical systems. Processing over the generic fault models is triggered by event detection logic that is defined according to the specific functional requirements of the system and its components. Once triggered, the fault models provide an automated way for performing both upstream root cause analysis (RCA), and for predicting downstream effects or impact analysis. The methodology has been applied to integrated system health management (ISHM) implementations at NASA SSC's Rocket Engine Test Stands (RETS).

Creep fatigue life prediction for engine hot section materials (isotropic): Fourth year progress review

NASA Technical Reports Server (NTRS)

Nelson, Richard S.; Schoendorf, John F.

1986-01-01

As gas turbine technology continues to advance, the need for advanced life prediction methods for hot section components is becoming more and more evident. The complex local strain and temperature histories at critical locations must be accurately interpreted to account for the effects of various damage mechanisms (such as fatigue, creep, and oxidation) and their possible interactions. As part of the overall NASA HOST effort, this program is designed to investigate these fundamental damage processes, identify modeling strategies, and develop practical models which can be used to guide the early design and development of new engines and to increase the durability of existing engines.

Simulation and in situ measurement of stress distribution in a polymer electrolyte membrane fuel cell stack

NASA Astrophysics Data System (ADS)

de la Cruz, Javier; Cano, Ulises; Romero, Tatiana

2016-10-01

A critical parameter for PEM fuel cell's electric contact is the nominal clamping pressure. Predicting the mechanical behavior of all components in a fuel cell stack is a very complex task due to the diversity of materials properties. Prior to the integration of a 3 kW PEMFC power plant, a numerical simulation was performed in order to obtain the mechanical stress distribution for two of the most pressure sensitive components of the stack: the membrane, and the graphite plates. The stress distribution of the above mentioned components was numerically simulated by finite element analysis and the stress magnitude for the membrane was confirmed using pressure films. Stress values were found within the elastic zone which guarantees mechanical integrity of fuel cell components. These low stress levels particularly for the membrane will allow prolonging the life and integrity of the fuel cell stack according to its design specifications.

Maintaining Enterprise Resiliency via Kaleidoscopic Adaption and Transformation of Software Services (MEERKATS)

DTIC Science & Technology

2016-04-01

infrastructure . The work is motivated by the fact that today’s clouds are very static, uniform, and predictable, allowing attackers who identify a...vulnerability in one of the services or infrastructure components to spread their effect to other, mission-critical services. Our goal is to integrate into...clouds by elevating continuous change, evolution, and misinformation as first-rate design principles of the cloud’s infrastructure . Our work is

Infrastructure, Components and System Level Testing and Analysis of Electric Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-09-353

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neubauer, J.

2013-05-01

Battery technology is critical for the development of innovative electric vehicle networks, which can enhance transportation sustainability and reduce dependence on petroleum. This cooperative research proposed by Better Place and NREL will focus on predicting the life-cycle economics of batteries, characterizing battery technologies under various operating and usage conditions, and designing optimal usage profiles for battery recharging and use.

Space tug propulsion system failure mode, effects and criticality analysis

NASA Technical Reports Server (NTRS)

Boyd, J. W.; Hardison, E. P.; Heard, C. B.; Orourke, J. C.; Osborne, F.; Wakefield, L. T.

1972-01-01

For purposes of the study, the propulsion system was considered as consisting of the following: (1) main engine system, (2) auxiliary propulsion system, (3) pneumatic system, (4) hydrogen feed, fill, drain and vent system, (5) oxygen feed, fill, drain and vent system, and (6) helium reentry purge system. Each component was critically examined to identify possible failure modes and the subsequent effect on mission success. Each space tug mission consists of three phases: launch to separation from shuttle, separation to redocking, and redocking to landing. The analysis considered the results of failure of a component during each phase of the mission. After the failure modes of each component were tabulated, those components whose failure would result in possible or certain loss of mission or inability to return the Tug to ground were identified as critical components and a criticality number determined for each. The criticality number of a component denotes the number of mission failures in one million missions due to the loss of that component. A total of 68 components were identified as critical with criticality numbers ranging from 1 to 2990.

Critical Two-Point Function for Long-Range O( n) Models Below the Upper Critical Dimension

NASA Astrophysics Data System (ADS)

Lohmann, Martin; Slade, Gordon; Wallace, Benjamin C.

2017-12-01

We consider the n-component |φ|^4 lattice spin model (n ≥ 1) and the weakly self-avoiding walk (n=0) on Z^d, in dimensions d=1,2,3. We study long-range models based on the fractional Laplacian, with spin-spin interactions or walk step probabilities decaying with distance r as r^{-(d+α )} with α \\in (0,2). The upper critical dimension is d_c=2α . For ɛ >0, and α = 1/2 (d+ɛ ), the dimension d=d_c-ɛ is below the upper critical dimension. For small ɛ , weak coupling, and all integers n ≥ 0, we prove that the two-point function at the critical point decays with distance as r^{-(d-α )}. This "sticking" of the critical exponent at its mean-field value was first predicted in the physics literature in 1972. Our proof is based on a rigorous renormalisation group method. The treatment of observables differs from that used in recent work on the nearest-neighbour 4-dimensional case, via our use of a cluster expansion.

Platelet composite coatings for tin whisker mitigation

DOE PAGES

Rohwer, Lauren E. S.; Martin, James E.

2015-09-14

In this study, reliable methods for tin whisker mitigation are needed for applications that utilize tin-plated commercial components. Tin can grow whiskers that can lead to electrical shorting, possibly causing critical systems to fail catastrophically. The mechanisms of tin whisker growth are unclear and this makes prediction of the lifetimes of critical components uncertain. The development of robust methods for tin whisker mitigation is currently the best approach to eliminating the risk of shorting. Current mitigation methods are based on unfilled polymer coatings that are not impenetrable to tin whiskers. In this paper we report tin whisker mitigation results formore » several filled polymer coatings. The whisker-penetration resistance of the coatings was evaluated at elevated temperature and high humidity and under temperature cycling conditions. The composite coatings comprised Ni and MgF 2-coated Al/Ni/Al platelets in epoxy resin or silicone rubber. In addition to improved whisker mitigation, these platelet composites have enhanced thermal conductivity and dielectric constant compared with unfilled polymers.« less

Simulation of Watts Bar Unit 1 Initial Startup Tests with Continuous Energy Monte Carlo Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Godfrey, Andrew T; Gehin, Jess C; Bekar, Kursat B

2014-01-01

The Consortium for Advanced Simulation of Light Water Reactors* is developing a collection of methods and software products known as VERA, the Virtual Environment for Reactor Applications. One component of the testing and validation plan for VERA is comparison of neutronics results to a set of continuous energy Monte Carlo solutions for a range of pressurized water reactor geometries using the SCALE component KENO-VI developed by Oak Ridge National Laboratory. Recent improvements in data, methods, and parallelism have enabled KENO, previously utilized predominately as a criticality safety code, to demonstrate excellent capability and performance for reactor physics applications. The highlymore » detailed and rigorous KENO solutions provide a reliable nu-meric reference for VERAneutronics and also demonstrate the most accurate predictions achievable by modeling and simulations tools for comparison to operating plant data. This paper demonstrates the performance of KENO-VI for the Watts Bar Unit 1 Cycle 1 zero power physics tests, including reactor criticality, control rod worths, and isothermal temperature coefficients.« less

Platelet Composite Coatings for Tin Whisker Mitigation

NASA Astrophysics Data System (ADS)

Rohwer, Lauren E. S.; Martin, James E.

2015-11-01

Reliable methods for tin whisker mitigation are needed for applications that utilize tin-plated commercial components. Tin can grow whiskers that can lead to electrical shorting, possibly causing critical systems to fail catastrophically. The mechanisms of tin whisker growth are unclear and this makes prediction of the lifetimes of critical components uncertain. The development of robust methods for tin whisker mitigation is currently the best approach to eliminating the risk of shorting. Current mitigation methods are based on unfilled polymer coatings that are not impenetrable to tin whiskers. In this paper we report tin whisker mitigation results for several filled polymer coatings. The whisker-penetration resistance of the coatings was evaluated at elevated temperature and high humidity and under temperature cycling conditions. The composite coatings comprised Ni and MgF2-coated Al/Ni/Al platelets in epoxy resin or silicone rubber. In addition to improved whisker mitigation, these platelet composites have enhanced thermal conductivity and dielectric constant compared with unfilled polymers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rohwer, Lauren E. S.; Martin, James E.

In this study, reliable methods for tin whisker mitigation are needed for applications that utilize tin-plated commercial components. Tin can grow whiskers that can lead to electrical shorting, possibly causing critical systems to fail catastrophically. The mechanisms of tin whisker growth are unclear and this makes prediction of the lifetimes of critical components uncertain. The development of robust methods for tin whisker mitigation is currently the best approach to eliminating the risk of shorting. Current mitigation methods are based on unfilled polymer coatings that are not impenetrable to tin whiskers. In this paper we report tin whisker mitigation results formore » several filled polymer coatings. The whisker-penetration resistance of the coatings was evaluated at elevated temperature and high humidity and under temperature cycling conditions. The composite coatings comprised Ni and MgF 2-coated Al/Ni/Al platelets in epoxy resin or silicone rubber. In addition to improved whisker mitigation, these platelet composites have enhanced thermal conductivity and dielectric constant compared with unfilled polymers.« less

A Critical Analysis of the Conventionally Employed Creep Lifing Methods

PubMed Central

Abdallah, Zakaria; Gray, Veronica; Whittaker, Mark; Perkins, Karen

2014-01-01

The deformation of structural alloys presents problems for power plants and aerospace applications due to the demand for elevated temperatures for higher efficiencies and reductions in greenhouse gas emissions. The materials used in such applications experience harsh environments which may lead to deformation and failure of critical components. To avoid such catastrophic failures and also increase efficiency, future designs must utilise novel/improved alloy systems with enhanced temperature capability. In recognising this issue, a detailed understanding of creep is essential for the success of these designs by ensuring components do not experience excessive deformation which may ultimately lead to failure. To achieve this, a variety of parametric methods have been developed to quantify creep and creep fracture in high temperature applications. This study reviews a number of well-known traditionally employed creep lifing methods with some more recent approaches also included. The first section of this paper focuses on predicting the long-term creep rupture properties which is an area of interest for the power generation sector. The second section looks at pre-defined strains and the re-production of full creep curves based on available data which is pertinent to the aerospace industry where components are replaced before failure. PMID:28788623

Genome-to-Watershed Predictive Understanding of Terrestrial Environments

NASA Astrophysics Data System (ADS)

Hubbard, S. S.; Agarwal, D.; Banfield, J. F.; Beller, H. R.; Brodie, E.; Long, P.; Nico, P. S.; Steefel, C. I.; Tokunaga, T. K.; Williams, K. H.

2014-12-01

Although terrestrial environments play a critical role in cycling water, greenhouse gasses, and other life-critical elements, the complexity of interactions among component microbes, plants, minerals, migrating fluids and dissolved constituents hinders predictive understanding of system behavior. The 'Sustainable Systems 2.0' project is developing genome-to-watershed scale predictive capabilities to quantify how the microbiome affects biogeochemical watershed functioning, how watershed-scale hydro-biogeochemical processes affect microbial functioning, and how these interactions co-evolve with climate and land-use changes. Development of such predictive capabilities is critical for guiding the optimal management of water resources, contaminant remediation, carbon stabilization, and agricultural sustainability - now and with global change. Initial investigations are focused on floodplains in the Colorado River Basin, and include iterative model development, experiments and observations with an early emphasis on subsurface aspects. Field experiments include local-scale experiments at Rifle CO to quantify spatiotemporal metabolic and geochemical responses to O2and nitrate amendments as well as floodplain-scale monitoring to quantify genomic and biogeochemical response to natural hydrological perturbations. Information obtained from such experiments are represented within GEWaSC, a Genome-Enabled Watershed Simulation Capability, which is being developed to allow mechanistic interrogation of how genomic information stored in a subsurface microbiome affects biogeochemical cycling. This presentation will describe the genome-to-watershed scale approach as well as early highlights associated with the project. Highlights include: first insights into the diversity of the subsurface microbiome and metabolic roles of organisms involved in subsurface nitrogen, sulfur and hydrogen and carbon cycling; the extreme variability of subsurface DOC and hydrological controls on carbon and nitrogen cycling; geophysical identification of floodplain hotspots that are useful for model parameterization; and GEWaSC demonstration of how incorporation of identified microbial metabolic processes improves prediction of the larger system biogeochemical behavior.

Quality-by-design III: application of near-infrared spectroscopy to monitor roller compaction in-process and product quality attributes of immediate release tablets.

PubMed

Kona, Ravikanth; Fahmy, Raafat M; Claycamp, Gregg; Polli, James E; Martinez, Marilyn; Hoag, Stephen W

2015-02-01

The objective of this study is to use near-infrared spectroscopy (NIRS) coupled with multivariate chemometric models to monitor granule and tablet quality attributes in the formulation development and manufacturing of ciprofloxacin hydrochloride (CIP) immediate release tablets. Critical roller compaction process parameters, compression force (CFt), and formulation variables identified from our earlier studies were evaluated in more detail. Multivariate principal component analysis (PCA) and partial least square (PLS) models were developed during the development stage and used as a control tool to predict the quality of granules and tablets. Validated models were used to monitor and control batches manufactured at different sites to assess their robustness to change. The results showed that roll pressure (RP) and CFt played a critical role in the quality of the granules and the finished product within the range tested. Replacing binder source did not statistically influence the quality attributes of the granules and tablets. However, lubricant type has significantly impacted the granule size. Blend uniformity, crushing force, disintegration time during the manufacturing was predicted using validated PLS regression models with acceptable standard error of prediction (SEP) values, whereas the models resulted in higher SEP for batches obtained from different manufacturing site. From this study, we were able to identify critical factors which could impact the quality attributes of the CIP IR tablets. In summary, we demonstrated the ability of near-infrared spectroscopy coupled with chemometrics as a powerful tool to monitor critical quality attributes (CQA) identified during formulation development.

Hierarchical multi-scale approach to validation and uncertainty quantification of hyper-spectral image modeling

NASA Astrophysics Data System (ADS)

Engel, Dave W.; Reichardt, Thomas A.; Kulp, Thomas J.; Graff, David L.; Thompson, Sandra E.

2016-05-01

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

Predicting ecosystem shifts requires new approaches that integrate the effects of climate change across entire systems

PubMed Central

Russell, Bayden D.; Harley, Christopher D. G.; Wernberg, Thomas; Mieszkowska, Nova; Widdicombe, Stephen; Hall-Spencer, Jason M.; Connell, Sean D.

2012-01-01

Most studies that forecast the ecological consequences of climate change target a single species and a single life stage. Depending on climatic impacts on other life stages and on interacting species, however, the results from simple experiments may not translate into accurate predictions of future ecological change. Research needs to move beyond simple experimental studies and environmental envelope projections for single species towards identifying where ecosystem change is likely to occur and the drivers for this change. For this to happen, we advocate research directions that (i) identify the critical species within the target ecosystem, and the life stage(s) most susceptible to changing conditions and (ii) the key interactions between these species and components of their broader ecosystem. A combined approach using macroecology, experimentally derived data and modelling that incorporates energy budgets in life cycle models may identify critical abiotic conditions that disproportionately alter important ecological processes under forecasted climates. PMID:21900317

Relatedness predicts multiple measures of investment in cooperative nest construction in sociable weavers

PubMed Central

Leighton, Gavin M.; Echeverri, Sebastian; Heinrich, Dirk; Kolberg, Holger

2015-01-01

Although communal goods are often critical to society, they are simultaneously susceptible to exploitation and are evolutionarily stable only if mechanisms exist to curtail exploitation. Mechanisms such as punishment and kin selection have been offered as general explanations for how communal resources can be maintained. Evidence for these mechanisms comes largely from humans and social insects, leaving their generality in question. To assess how communal resources are maintained, we observed cooperative nest construction in sociable weavers (Philetairus socius). The communal nest of sociable weavers provides thermal benefits for all individuals but requires continual maintenance. We observed cooperative nest construction and also recorded basic morphological characteristics. We also collected blood samples, performed next-generation sequencing, and isolated 2358 variable single nucleotide polymorphisms (SNPs) to estimate relatedness. We find that relatedness predicts investment in cooperative nest construction, while no other morphological characters significantly explain cooperative output. We argue that indirect benefits are a critical fitness component for maintaining the cooperative behavior that maintains the communal good. PMID:26726282

The role of facial appearance on CEO selection after firm misconduct.

PubMed

Gomulya, David; Wong, Elaine M; Ormiston, Margaret E; Boeker, Warren

2017-04-01

[Correction Notice: An Erratum for this article was reported in Vol 102(4) of Journal of Applied Psychology (see record 2017-10684-001). The wrong figure files were used. All versions of this article have been corrected.] We investigate a particular aspect of CEO successor trustworthiness that may be critically important after a firm has engaged in financial misconduct. Specifically, drawing on prior research that suggests that facial appearance is one critical way in which trustworthiness is signaled, we argue that leaders who convey integrity, a component of trustworthiness, will be more likely to be selected as successors after financial restatement. We predict that such appointments garner more positive reactions by external observers such as investment analysts and the media because these CEOs are perceived as having greater integrity. In an archival study of firms that have announced financial restatements, we find support for our predictions. These findings have implications for research on CEO succession, leadership selection, facial appearance, and firm misconduct. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Rate-based structural health monitoring using permanently installed sensors

PubMed Central

2017-01-01

Permanently installed sensors are becoming increasingly ubiquitous, facilitating very frequent in situ measurements and consequently improved monitoring of ‘trends’ in the observed system behaviour. It is proposed that this newly available data may be used to provide prior warning and forecasting of critical events, particularly system failure. Numerous damage mechanisms are examples of positive feedback; they are ‘self-accelerating’ with an increasing rate of damage towards failure. The positive feedback leads to a common time-response behaviour which may be described by an empirical relation allowing prediction of the time to criticality. This study focuses on Structural Health Monitoring of engineering components; failure times are projected well in advance of failure for fatigue, creep crack growth and volumetric creep damage experiments. The proposed methodology provides a widely applicable framework for using newly available near-continuous data from permanently installed sensors to predict time until failure in a range of application areas including engineering, geophysics and medicine. PMID:28989308

Stirling engine - Approach for long-term durability assessment

NASA Technical Reports Server (NTRS)

Tong, Michael T.; Bartolotta, Paul A.; Halford, Gary R.; Freed, Alan D.

1992-01-01

The approach employed by NASA Lewis for the long-term durability assessment of the Stirling engine hot-section components is summarized. The approach consists of: preliminary structural assessment; development of a viscoplastic constitutive model to accurately determine material behavior under high-temperature thermomechanical loads; an experimental program to characterize material constants for the viscoplastic constitutive model; finite-element thermal analysis and structural analysis using a viscoplastic constitutive model to obtain stress/strain/temperature at the critical location of the hot-section components for life assessment; and development of a life prediction model applicable for long-term durability assessment at high temperatures. The approach should aid in the provision of long-term structural durability and reliability of Stirling engines.

Modelling safety of multistate systems with ageing components

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kołowrocki, Krzysztof; Soszyńska-Budny, Joanna

An innovative approach to safety analysis of multistate ageing systems is presented. Basic notions of the ageing multistate systems safety analysis are introduced. The system components and the system multistate safety functions are defined. The mean values and variances of the multistate systems lifetimes in the safety state subsets and the mean values of their lifetimes in the particular safety states are defined. The multi-state system risk function and the moment of exceeding by the system the critical safety state are introduced. Applications of the proposed multistate system safety models to the evaluation and prediction of the safty characteristics ofmore » the consecutive “m out of n: F” is presented as well.« less

Evaluation of Fatigue Crack Growth and Fracture Properties of Cryogenic Model Materials

NASA Technical Reports Server (NTRS)

Newman, John A.; Forth, Scott C.; Everett, Richard A., Jr.; Newman, James C., Jr.; Kimmel, William M.

2002-01-01

The criteria used to prevent failure of wind-tunnel models and support hardware were revised as part of a project to enhance the capabilities of cryogenic wind tunnel testing at NASA Langley Research Center. Specifically, damage-tolerance fatigue life prediction methods are now required for critical components, and material selection criteria are more general and based on laboratory test data. The suitability of two candidate model alloys (AerMet 100 and C-250 steel) was investigated by obtaining the fatigue crack growth and fracture data required for a damage-tolerance fatigue life analysis. Finally, an example is presented to illustrate the newly implemented damage tolerance analyses required of wind-tunnel model system components.

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

NASA Technical Reports Server (NTRS)

Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Determination of Fracture Parameters for Multiple Cracks of Laminated Composite Finite Plate

NASA Astrophysics Data System (ADS)

Srivastava, Amit Kumar; Arora, P. K.; Srivastava, Sharad Chandra; Kumar, Harish; Lohumi, M. K.

2018-04-01

A predictive method for estimation of stress state at zone of crack tip and assessment of remaining component lifetime depend on the stress intensity factor (SIF). This paper discusses the numerical approach for prediction of first ply failure load (FL), progressive failure load, SIF and critical SIF for multiple cracks configurations of laminated composite finite plate using finite element method (FEM). The Hashin and Chang failure criterion are incorporated in ABAQUS using subroutine approach user defined field variables (USDFLD) for prediction of progressive fracture response of laminated composite finite plate, which is not directly available in the software. A tensile experiment on laminated composite finite plate with stress concentration is performed to validate the numerically predicted subroutine results, shows excellent agreement. The typical results are presented to examine effect of changing the crack tip distance (S), crack offset distance (H), and stacking fiber angle (θ) on FL, and SIF .

Temperature Measurement and Numerical Prediction in Machining Inconel 718.

PubMed

Díaz-Álvarez, José; Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-06-30

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning.

Design integration and noise studies for jet STOL aircraft. Task 7C: Augmentor wing cruise blowing valveless system. Volume 2: Small-scale development testing of augmentor wing critical ducting components

NASA Technical Reports Server (NTRS)

Runnels, J. N.; Gupfa, A.

1973-01-01

Augmentor wing ducting system studies conducted on a valveless system configuration that provides cruise thrust from the augmentor nozzles have shown that most of the duct system pressure loss would occur in the strut-wing duct y-junction and the wing duct-augmentor lobe nozzles. These components were selected for development testing over a range of duct Mach numbers and pressure ratios to provide a technical basis for predicting installed wing thrust loading and for evaluating design wing loading of a particular wing aspect ratios. The flow characteristics of ducting components with relatively high pressure loss coefficients were investigated. The turbulent pressure fluctuations associated with flows at high Mach numbers were analyzed to evaluate potential duct fatigue problems.

Prediction of strain values in reinforcements and concrete of a RC frame using neural networks

NASA Astrophysics Data System (ADS)

Vafaei, Mohammadreza; Alih, Sophia C.; Shad, Hossein; Falah, Ali; Halim, Nur Hajarul Falahi Abdul

2018-03-01

The level of strain in structural elements is an important indicator for the presence of damage and its intensity. Considering this fact, often structural health monitoring systems employ strain gauges to measure strains in critical elements. However, because of their sensitivity to the magnetic fields, inadequate long-term durability especially in harsh environments, difficulties in installation on existing structures, and maintenance cost, installation of strain gauges is not always possible for all structural components. Therefore, a reliable method that can accurately estimate strain values in critical structural elements is necessary for damage identification. In this study, a full-scale test was conducted on a planar RC frame to investigate the capability of neural networks for predicting the strain values. Two neural networks each of which having a single hidden layer was trained to relate the measured rotations and vertical displacements of the frame to the strain values measured at different locations of the frame. Results of trained neural networks indicated that they accurately estimated the strain values both in reinforcements and concrete. In addition, the trained neural networks were capable of predicting strains for the unseen input data set.

Six-Tube Freezable Radiator Testing and Model Correlation

NASA Technical Reports Server (NTRS)

Lillibridge, Sean; Navarro, Moses

2011-01-01

Freezable radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recovering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TradeMark) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested, namely MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Six-Tube Freezable Radiator Testing and Model Correlation

NASA Technical Reports Server (NTRS)

Lilibridge, Sean T.; Navarro, Moses

2012-01-01

Freezable Radiators offer an attractive solution to the issue of thermal control system scalability. As thermal environments change, a freezable radiator will effectively scale the total heat rejection it is capable of as a function of the thermal environment and flow rate through the radiator. Scalable thermal control systems are a critical technology for spacecraft that will endure missions with widely varying thermal requirements. These changing requirements are a result of the spacecraft?s surroundings and because of different thermal loads rejected during different mission phases. However, freezing and thawing (recov ering) a freezable radiator is a process that has historically proven very difficult to predict through modeling, resulting in highly inaccurate predictions of recovery time. These predictions are a critical step in gaining the capability to quickly design and produce optimized freezable radiators for a range of mission requirements. This paper builds upon previous efforts made to correlate a Thermal Desktop(TM) model with empirical testing data from two test articles, with additional model modifications and empirical data from a sub-component radiator for a full scale design. Two working fluids were tested: MultiTherm WB-58 and a 50-50 mixture of DI water and Amsoil ANT.

Optimization of critical medium components using response surface methodology for biomass and extracellular polysaccharide production by Agaricus blazei.

PubMed

Liu, Gao-Qiang; Wang, Xiao-Ling

2007-02-01

Response surface methodology (RSM) was applied to optimize the critical medium ingredients of Agaricus blazei. A three-level Box-Behnken factorial design was employed to determine the maximum biomass and extracellular polysaccharide (EPS) yields at optimum levels for glucose, yeast extract (YE), and peptone. A mathematical model was then developed to show the effect of each medium composition and its interactions on the production of mycelial biomass and EPS. The model predicted the maximum biomass yield of 10.86 g/l that appeared at glucose, YE, peptone of 26.3, 6.84, and 6.62 g/l, respectively, while a maximum EPS yield of 348.4 mg/l appeared at glucose, YE, peptone of 28.4, 4.96, 5.60 g/l, respectively. These predicted values were also verified by validation experiments. The excellent correlation between predicted and measured values of each model justifies the validity of both the response models. The results of bioreactor fermentation also show that the optimized culture medium enhanced both biomass (13.91 +/- 0.71 g/l) and EPS (363 +/- 4.1 mg/l) production by Agaricus blazei in a large-scale fermentation process.

Dorsolateral Prefrontal Cortex GABA Concentration in Humans Predicts Working Memory Load Processing Capacity.

PubMed

Yoon, Jong H; Grandelis, Anthony; Maddock, Richard J

2016-11-16

The discovery of neural mechanisms of working memory (WM) would significantly enhance our understanding of complex human behaviors and guide treatment development for WM-related impairments found in neuropsychiatric conditions and aging. Although the dorsolateral prefrontal cortex (DLPFC) has long been considered critical for WM, we still know little about the neural elements and pathways within the DLPFC that support WM in humans. In this study, we tested whether an individual's DLPFC gamma-aminobutryic acid (GABA) content predicts individual differences in WM task performance using a novel behavioral approach. Twenty-three healthy adults completed a task that measured the unique contribution of major WM components (memory load, maintenance, and distraction resistance) to performance. This was done to address the possibility that components have differing GABA dependencies and the failure to parse WM into components would lead to missing true associations with GABA. The subjects then had their DLPFC GABA content measured by single-voxel proton magnetic spectroscopy. We found that individuals with lower DLPFC GABA showed greater performance degradation with higher load, accounting for 31% of variance, p (corrected) = 0.015. This relationship was component, neurochemical, and brain region specific. DLPFC GABA content did not predict performance sensitivity to other components tested; DLPFC glutamate + glutamine and visual cortical GABA content did not predict load sensitivity. These results confirm the involvement of DLPFC GABA in WM load processing in humans and implicate factors controlling DLPFC GABA content in the neural mechanisms of WM and its impairments. This study demonstrated for the first time that the amount of gamma-aminobutryic acid (GABA), the major inhibitory neurotransmitter of the brain, in an individual's prefrontal cortex predicts working memory (WM) task performance. Given that WM is required for many of the most characteristic cognitive and behavioral capabilities in humans, this finding could have a significant impact on our understanding of the neural basis of complex human behavior. Furthermore, this finding suggests that efforts to preserve or increase brain GABA levels could be fruitful in remediating WM-related deficits associated with neuropsychiatric conditions. Copyright © 2016 the authors 0270-6474/16/3611788-07$15.00/0.

Invited review: A commentary on predictive cheese yield formulas.

PubMed

Emmons, D B; Modler, H W

2010-12-01

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was <100%; the mean was 99.51% (N × 6.31). The mean predicted yield was only 99.17% as a percentage of actual yields (PY%AY); PY%AY is a useful term for comparisons of yields among vats. The PY%AY correlated positively with the sum of components (SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction. Composition of cheese was estimated using a predictive formula; actual yield was needed for estimation of composition. Adjusted formulas are recommended for estimating target yields and cheese yield efficiency. Constants for solute exclusion, protein-associated milk salts, and whey solids could be used and reduced the complexity of the General formula. Normalization of fat recovery increased variability of predicted yields. Copyright © 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Advanced Turbine Technology Applications Project (ATTAP)

NASA Technical Reports Server (NTRS)

1994-01-01

Reports technical effort by AlliedSignal Engines in sixth year of DOE/NASA funded project. Topics include: gas turbine engine design modifications of production APU to incorporate ceramic components; fabrication and processing of silicon nitride blades and nozzles; component and engine testing; and refinement and development of critical ceramics technologies, including: hot corrosion testing and environmental life predictive model; advanced NDE methods for internal flaws in ceramic components; and improved carbon pulverization modeling during impact. ATTAP project is oriented toward developing high-risk technology of ceramic structural component design and fabrication to carry forward to commercial production by 'bridging the gap' between structural ceramics in the laboratory and near-term commercial heat engine application. Current ATTAP project goal is to support accelerated commercialization of advanced, high-temperature engines for hybrid vehicles and other applications. Project objectives are to provide essential and substantial early field experience demonstrating ceramic component reliability and durability in modified, available, gas turbine engine applications; and to scale-up and improve manufacturing processes of ceramic turbine engine components and demonstrate application of these processes in the production environment.

METCAN: The metal matrix composite analyzer

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Murthy, Pappu L. N.

1988-01-01

Metal matrix composites (MMC) are the subject of intensive study and are receiving serious consideration for critical structural applications in advanced aerospace systems. MMC structural analysis and design methodologies are studied. Predicting the mechanical and thermal behavior and the structural response of components fabricated from MMC requires the use of a variety of mathematical models. These models relate stresses to applied forces, stress intensities at the tips of cracks to nominal stresses, buckling resistance to applied force, or vibration response to excitation forces. The extensive research in computational mechanics methods for predicting the nonlinear behavior of MMC are described. This research has culminated in the development of the METCAN (METal Matrix Composite ANalyzer) computer code.

Modeling of rolling element bearing mechanics

NASA Technical Reports Server (NTRS)

Greenhill, L. M.

1991-01-01

Roller element bearings provide the primary mechanical interface between rotating and nonrotating components in the high performance turbomachinery of the Space Shuttle Main Engine (SSME). Knowledge of bearing behavior under various loading and environmental conditions is essential to predicting and understanding the overall behavior of turbopumps, including rotordynamic stability, critical speeds and bearing life. The objective is to develop mathematical models and computer programs to describe the mechanical behavior of ball and cylinder roller bearings under the loading and environmental conditions encountered in the SSME and future high performance rocket engines. This includes characteristics such as nonlinear load/motion relationships, stiffness and damping, rolling element loads for life prediction, and roller and cage stability.

Principal components analysis of the hypomanic attitudes and positive predictions inventory and associations with measures of personality, cognitive style and analogue symptoms in a student sample.

PubMed

Dodd, Alyson L; Mansell, Warren; Sadhnani, Vaneeta; Morrison, Anthony P; Tai, Sara

2010-01-01

An integrative cognitive model proposed that ascribing extreme personal appraisals to changes in internal state is key to the development of the symptoms of bipolar disorder. The Hypomanic Attitudes and Positive Predictions Inventory (HAPPI) was developed to measure these appraisals. The aim of the current study was to validate an expanded 61-item version of the HAPPI. In a largely female student sample (N = 134), principal components analysis (PCA) was performed on the HAPPI. Associations between the HAPPI and analogue bipolar symptoms after 3 months were examined. PCA of the HAPPI revealed six categories of belief: Self Activation, Self-and-Other Critical, Catastrophic, Extreme Appraisals of Social Approval, Appraisals of Extreme Agitation, and Loss of Control. The HAPPI predicted all analogue measures of hypomanic symptoms after 3 months when controlling for baseline symptoms. In a more stringent test incorporating other psychological measures, the HAPPI was independently associated only with activation (e.g. thoughts racing) at 3 months. Dependent dysfunctional attitudes predicted greater conflict (e.g. irritability), depression and reduced well-being, hypomanic personality predicted self-reported diagnostic bipolar symptoms, and behavioural dysregulation predicted depression. Extreme beliefs about internal states show a modest independent association with prospective analogue bipolar symptoms, alongside other psychological factors. Further work will be required to improve the factor structure of the HAPPI and study its validity in clinical samples.

Hemispheric connectivity and the visual-spatial divergent-thinking component of creativity.

PubMed

Moore, Dana W; Bhadelia, Rafeeque A; Billings, Rebecca L; Fulwiler, Carl; Heilman, Kenneth M; Rood, Kenneth M J; Gansler, David A

2009-08-01

Divergent thinking is an important measurable component of creativity. This study tested the postulate that divergent thinking depends on large distributed inter- and intra-hemispheric networks. Although preliminary evidence supports increased brain connectivity during divergent thinking, the neural correlates of this characteristic have not been entirely specified. It was predicted that visuospatial divergent thinking would correlate with right hemisphere white matter volume (WMV) and with the size of the corpus callosum (CC). Volumetric magnetic resonance imaging (MRI) analyses and the Torrance Tests of Creative Thinking (TTCT) were completed among 21 normal right-handed adult males. TTCT scores correlated negatively with the size of the CC and were not correlated with right or, incidentally, left WMV. Although these results were not predicted, perhaps, as suggested by Bogen and Bogen (1988), decreased callosal connectivity enhances hemispheric specialization, which benefits the incubation of ideas that are critical for the divergent-thinking component of creativity, and it is the momentary inhibition of this hemispheric independence that accounts for the illumination that is part of the innovative stage of creativity. Alternatively, decreased CC size may reflect more selective developmental pruning, thereby facilitating efficient functional connectivity.

Prediction of Fretting Crack Location and Orientation in a Single Crystal Nickel Alloy

NASA Technical Reports Server (NTRS)

Matlik, J. F.; Farris, T. N.; Haynes, J.; Swanson, G. R.; Ham-Battista, G.

2005-01-01

Fretting is a structural damage mechanism arising between two nominally clamped surfaces subjected to an oscillatory loading. A critical location for fretting induced damage has been identified at the blade/disk and blade/damper interfaces of gas turbine engine turbomachinery and space propulsion components. The high- temperature, high-frequency loading environment seen by these components lead to severe stress gradients at the edge-of-contact that could potentially foster crack growth leading to component failure. These contact stresses drive crack nucleation in fretting and are very sensitive to the geometry of the contacting bodies, the contact loads, materials, temperature, and contact surface tribology (friction). Recently, a high-frequency, high-temperature load frame has been designed for experimentally investigating fretting damage of single crystal nickel materials employed in aircraft and spacecraft turbomachinery. A modeling method for characterizing the fretting stresses of the spherical fretting contact stress behavior in this experiment is developed and described. The calculated fretting stresses for a series of experiments are then correlated to the observed fretting damage. Results show that knowledge of the normal stresses and resolved shear stresses on each crystal plane can aid in predicting crack locations and orientations.

Catastrophic Shifts in Semiarid Vegetation-Soil Systems May Unfold Rapidly or Slowly.

PubMed

Karssenberg, Derek; Bierkens, Marc F P; Rietkerk, Max

2017-12-01

Under gradual change of a driver, complex systems may switch between contrasting stable states. For many ecosystems it is unknown how rapidly such a critical transition unfolds. Here we explore the rate of change during the degradation of a semiarid ecosystem with a model coupling the vegetation and geomorphological system. Two stable states-vegetated and bare-are identified, and it is shown that the change between these states is a critical transition. Surprisingly, the critical transition between the vegetated and bare state can unfold either rapidly over a few years or gradually over decennia up to millennia, depending on parameter values. An important condition for the phenomenon is the linkage between slow and fast ecosystems components. Our results show that, next to climate change and disturbance rates, the geological and geomorphological setting of a semiarid ecosystem is crucial in predicting its fate.

Uncertainty analysis on simple mass balance model to calculate critical loads for soil acidity.

PubMed

Li, Harbin; McNulty, Steven G

2007-10-01

Simple mass balance equations (SMBE) of critical acid loads (CAL) in forest soil were developed to assess potential risks of air pollutants to ecosystems. However, to apply SMBE reliably at large scales, SMBE must be tested for adequacy and uncertainty. Our goal was to provide a detailed analysis of uncertainty in SMBE so that sound strategies for scaling up CAL estimates to the national scale could be developed. Specifically, we wanted to quantify CAL uncertainty under natural variability in 17 model parameters, and determine their relative contributions in predicting CAL. Results indicated that uncertainty in CAL came primarily from components of base cation weathering (BC(w); 49%) and acid neutralizing capacity (46%), whereas the most critical parameters were BC(w) base rate (62%), soil depth (20%), and soil temperature (11%). Thus, improvements in estimates of these factors are crucial to reducing uncertainty and successfully scaling up SMBE for national assessments of CAL.

Sensorimotor Integration in Speech Processing: Computational Basis and Neural Organization

PubMed Central

Hickok, Gregory; Houde, John; Rong, Feng

2011-01-01

Sensorimotor integration is an active domain of speech research and is characterized by two main ideas, that the auditory system is critically involved in speech production, and that the motor system is critically involved in speech perception. Despite the complementarity of these ideas, there is little crosstalk between these literatures. We propose an integrative model of the speech-related “dorsal stream” in which sensorimotor interaction primarily supports speech production, in the form of a state feedback control architecture. A critical component of this control system is forward sensory prediction, which affords a natural mechanism for limited motor influence on perception, as recent perceptual research has suggested. Evidence shows that this influence is modulatory but not necessary for speech perception. The neuroanatomy of the proposed circuit is discussed as well as some probable clinical correlates including conduction aphasia, stuttering, and aspects of schizophrenia. PMID:21315253

Predicting Pilot Performance in Off-Nominal Conditions: A Meta-Analysis and Model Validation

NASA Technical Reports Server (NTRS)

Wickens, C.D.; Hooey, B.L.; Gore, B.F.; Sebok, A.; Koenecke, C.; Salud, E.

2009-01-01

Pilot response to off-nominal (very rare) events represents a critical component to understanding the safety of next generation airspace technology and procedures. We describe a meta-analysis designed to integrate the existing data regarding pilot accuracy of detecting rare, unexpected events such as runway incursions in realistic flight simulations. Thirty-five studies were identified and pilot responses were categorized by expectancy, event location, and whether the pilot was flying with a highway-in-the-sky display. All three dichotomies produced large, significant effects on event miss rate. A model of human attention and noticing, N-SEEV, was then used to predict event noticing performance as a function of event salience and expectancy, and retinal eccentricity. Eccentricity is predicted from steady state scanning by the SEEV model of attention allocation. The model was used to predict miss rates for the expectancy, location and highway-in-the-sky (HITS) effects identified in the meta-analysis. The correlation between model-predicted results and data from the meta-analysis was 0.72.

Watching novice action degrades expert motor performance: Causation between action production and outcome prediction of observed actions by humans

PubMed Central

Ikegami, Tsuyoshi; Ganesh, Gowrishankar

2014-01-01

Our social skills are critically determined by our ability to understand and appropriately respond to actions performed by others. However despite its obvious importance, the mechanisms enabling action understanding in humans have remained largely unclear. A popular but controversial belief is that parts of the motor system contribute to our ability to understand observed actions. Here, using a novel behavioral paradigm, we investigated this belief by examining a causal relation between action production, and a component of action understanding - outcome prediction, the ability of a person to predict the outcome of observed actions. We asked dart experts to watch novice dart throwers and predict the outcome of their throws. We modulated the feedbacks provided to them, caused a specific improvement in the expert's ability to predict watched actions while controlling the other experimental factors, and exhibited that a change (improvement) in their outcome prediction ability results in a progressive and proportional deterioration in the expert's own darts performance. This causal relationship supports involvement of the motor system in outcome prediction by humans of actions observed in others. PMID:25384755

Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

PubMed

Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

2007-03-07

Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

Structural Life and Reliability Metrics: Benchmarking and Verification of Probabilistic Life Prediction Codes

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Soditus, Sherry; Hendricks, Robert C.; Zaretsky, Erwin V.

2002-01-01

Over the past two decades there has been considerable effort by NASA Glenn and others to develop probabilistic codes to predict with reasonable engineering certainty the life and reliability of critical components in rotating machinery and, more specifically, in the rotating sections of airbreathing and rocket engines. These codes have, to a very limited extent, been verified with relatively small bench rig type specimens under uniaxial loading. Because of the small and very narrow database the acceptance of these codes within the aerospace community has been limited. An alternate approach to generating statistically significant data under complex loading and environments simulating aircraft and rocket engine conditions is to obtain, catalog and statistically analyze actual field data. End users of the engines, such as commercial airlines and the military, record and store operational and maintenance information. This presentation describes a cooperative program between the NASA GRC, United Airlines, USAF Wright Laboratory, U.S. Army Research Laboratory and Australian Aeronautical & Maritime Research Laboratory to obtain and analyze these airline data for selected components such as blades, disks and combustors. These airline data will be used to benchmark and compare existing life prediction codes.

Benchmark Calibration Tests Completed for Stirling Convertor Heater Head Life Assessment

NASA Technical Reports Server (NTRS)

Krause, David L.; Halford, Gary R.; Bowman, Randy R.

2005-01-01

A major phase of benchmark testing has been completed at the NASA Glenn Research Center (http://www.nasa.gov/glenn/), where a critical component of the Stirling Radioisotope Generator (SRG) is undergoing extensive experimentation to aid the development of an analytical life-prediction methodology. Two special-purpose test rigs subjected SRG heater-head pressure-vessel test articles to accelerated creep conditions, using the standard design temperatures to stay within the wall material s operating creep-response regime, but increasing wall stresses up to 7 times over the design point. This resulted in well-controlled "ballooning" of the heater-head hot end. The test plan was developed to provide critical input to analytical parameters in a reasonable period of time.

Coordination, Data Management and Enhancement of the International Arctic Buoy Programme (IABP), A US Interagency Arctic Buoy Programme (USIABP) Contribution to the IABP

DTIC Science & Technology

2012-09-30

International Arctic Buoy Programme ( IABP ) A US Interagency Arctic Buoy Programme (USIABP) contribution to the IABP Dr. Ignatius G. Rigor Polar...observations of surface meteorology and ice motion. These observations are assimilated into Numerical Weather Prediction (NWP) models that are used to...distribution of sea ice. Over the Arctic Ocean, this fundamental observing network is maintained by the IABP , and is a critical component of the

Efffect of Aeroallergen Sensitization on Asthma Control in ...

EPA Pesticide Factsheets

In African-American adolescents with persistent asthma, allergic profile predicted the likelihood of having poorly controlled asthma despite guidelines-directed therapies. Our results suggest that tree and weed pollen sensitization are independent risk factors for poorly controlled asthma in this at-risk population. The study examined African-American children with difficult to treat asthma. The findings suggest that in addition to guidelines-directed asthma therapies, targeting the allergic component, particularly tree and weed pollen, is critical to achieving optimal asthma control in this at-risk population.

Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engel, David W.; Reichardt, Thomas A.; Kulp, Thomas J.

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensormore » level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.« less

Crew Launch Vehicle Mobile Launcher Solid Rocket Motor Plume Induced Environment

NASA Technical Reports Server (NTRS)

Vu, Bruce T.; Sulyma, Peter

2008-01-01

The plume-induced environment created by the Ares 1 first stage, five-segment reusable solid rocket motor (RSRMV) will impose high heating rates and impact pressures on Launch Complex 39. The extremes of these environments pose a potential threat to weaken or even cause structural components to fail if insufficiently designed. Therefore the ability to accurately predict these environments is critical to assist in specifying structural design requirements to insure overall structural integrity and flight safety. This paper presents the predicted thermal and pressure environments induced by the launch of the Crew Launch Vehicle (CLV) from Launch Complex (LC) 39. Once the environments are predicted, a follow-on thermal analysis is required to determine the surface temperature response and the degradation rate of the materials. An example of structures responding to the plume-induced environment will be provided.

Stress evaluation of metallic material under steady state based on nonlinear critically refracted longitudinal wave

NASA Astrophysics Data System (ADS)

Mao, Hanling; Zhang, Yuhua; Mao, Hanying; Li, Xinxin; Huang, Zhenfeng

2018-06-01

This paper presents the study of applying the nonlinear ultrasonic wave to evaluate the stress state of metallic materials under steady state. The pre-stress loading method is applied to guarantee components with steady stress. Three kinds of nonlinear ultrasonic experiments based on critically refracted longitudinal wave are conducted on components which the critically refracted longitudinal wave propagates along x, x1 and x2 direction. Experimental results indicate the second and third order relative nonlinear coefficients monotonically increase with stress, and the normalized relationship is consistent with simplified dislocation models, which indicates the experimental result is logical. The combined ultrasonic nonlinear parameter is proposed, and three stress evaluation models at x direction are established based on three ultrasonic nonlinear parameters, which the estimation error is below 5%. Then two stress detection models at x1 and x2 direction are built based on combined ultrasonic nonlinear parameter, the stress synthesis method is applied to calculate the magnitude and direction of principal stress. The results show the prediction error is within 5% and the angle deviation is within 1.5°. Therefore the nonlinear ultrasonic technique based on LCR wave could be applied to nondestructively evaluate the stress of metallic materials under steady state which the magnitude and direction are included.

Computer Optimization of Biodegradable Nanoparticles Fabricated by Dispersion Polymerization.

PubMed

Akala, Emmanuel O; Adesina, Simeon; Ogunwuyi, Oluwaseun

2015-12-22

Quality by design (QbD) in the pharmaceutical industry involves designing and developing drug formulations and manufacturing processes which ensure predefined drug product specifications. QbD helps to understand how process and formulation variables affect product characteristics and subsequent optimization of these variables vis-à-vis final specifications. Statistical design of experiments (DoE) identifies important parameters in a pharmaceutical dosage form design followed by optimizing the parameters with respect to certain specifications. DoE establishes in mathematical form the relationships between critical process parameters together with critical material attributes and critical quality attributes. We focused on the fabrication of biodegradable nanoparticles by dispersion polymerization. Aided by a statistical software, d-optimal mixture design was used to vary the components (crosslinker, initiator, stabilizer, and macromonomers) to obtain twenty nanoparticle formulations (PLLA-based nanoparticles) and thirty formulations (poly-ɛ-caprolactone-based nanoparticles). Scheffe polynomial models were generated to predict particle size (nm), zeta potential, and yield (%) as functions of the composition of the formulations. Simultaneous optimizations were carried out on the response variables. Solutions were returned from simultaneous optimization of the response variables for component combinations to (1) minimize nanoparticle size; (2) maximize the surface negative zeta potential; and (3) maximize percent yield to make the nanoparticle fabrication an economic proposition.

Computer-Aided Design of Low-Noise Microwave Circuits

NASA Astrophysics Data System (ADS)

Wedge, Scott William

1991-02-01

Devoid of most natural and manmade noise, microwave frequencies have detection sensitivities limited by internally generated receiver noise. Low-noise amplifiers are therefore critical components in radio astronomical antennas, communications links, radar systems, and even home satellite dishes. A general technique to accurately predict the noise performance of microwave circuits has been lacking. Current noise analysis methods have been limited to specific circuit topologies or neglect correlation, a strong effect in microwave devices. Presented here are generalized methods, developed for computer-aided design implementation, for the analysis of linear noisy microwave circuits comprised of arbitrarily interconnected components. Included are descriptions of efficient algorithms for the simultaneous analysis of noisy and deterministic circuit parameters based on a wave variable approach. The methods are therefore particularly suited to microwave and millimeter-wave circuits. Noise contributions from lossy passive components and active components with electronic noise are considered. Also presented is a new technique for the measurement of device noise characteristics that offers several advantages over current measurement methods.

Glass ceramic ZERODUR enabling nanometer precision

NASA Astrophysics Data System (ADS)

Jedamzik, Ralf; Kunisch, Clemens; Nieder, Johannes; Westerhoff, Thomas

2014-03-01

The IC Lithography roadmap foresees manufacturing of devices with critical dimension of < 20 nm. Overlay specification of single digit nanometer asking for nanometer positioning accuracy requiring sub nanometer position measurement accuracy. The glass ceramic ZERODUR® is a well-established material in critical components of microlithography wafer stepper and offered with an extremely low coefficient of thermal expansion (CTE), the tightest tolerance available on market. SCHOTT is continuously improving manufacturing processes and it's method to measure and characterize the CTE behavior of ZERODUR® to full fill the ever tighter CTE specification for wafer stepper components. In this paper we present the ZERODUR® Lithography Roadmap on the CTE metrology and tolerance. Additionally, simulation calculations based on a physical model are presented predicting the long term CTE behavior of ZERODUR® components to optimize dimensional stability of precision positioning devices. CTE data of several low thermal expansion materials are compared regarding their temperature dependence between - 50°C and + 100°C. ZERODUR® TAILORED 22°C is full filling the tight CTE tolerance of +/- 10 ppb / K within the broadest temperature interval compared to all other materials of this investigation. The data presented in this paper explicitly demonstrates the capability of ZERODUR® to enable the nanometer precision required for future generation of lithography equipment and processes.

Measurement of Laser Weld Temperatures for 3D Model Input

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dagel, Daryl; Grossetete, Grant; Maccallum, Danny O.

Laser welding is a key joining process used extensively in the manufacture and assembly of critical components for several weapons systems. Sandia National Laboratories advances the understanding of the laser welding process through coupled experimentation and modeling. This report summarizes the experimental portion of the research program, which focused on measuring temperatures and thermal history of laser welds on steel plates. To increase confidence in measurement accuracy, researchers utilized multiple complementary techniques to acquire temperatures during laser welding. This data serves as input to and validation of 3D laser welding models aimed at predicting microstructure and the formation of defectsmore » and their impact on weld-joint reliability, a crucial step in rapid prototyping of weapons components.« less

The Importance of Calibration in Clinical Psychology.

PubMed

Lindhiem, Oliver; Petersen, Isaac T; Mentch, Lucas K; Youngstrom, Eric A

2018-02-01

Accuracy has several elements, not all of which have received equal attention in the field of clinical psychology. Calibration, the degree to which a probabilistic estimate of an event reflects the true underlying probability of the event, has largely been neglected in the field of clinical psychology in favor of other components of accuracy such as discrimination (e.g., sensitivity, specificity, area under the receiver operating characteristic curve). Although it is frequently overlooked, calibration is a critical component of accuracy with particular relevance for prognostic models and risk-assessment tools. With advances in personalized medicine and the increasing use of probabilistic (0% to 100%) estimates and predictions in mental health research, the need for careful attention to calibration has become increasingly important.

A system for the model based emergency detection and communication for the telerehabilitation training of cardiopulmonary patients.

PubMed

Helmer, Axel; Kretschmer, Friedrich; Deparade, Riana; Song, Bianying; Meis, Markus; Hein, Andreas; Marschollek, Michael; Tegtbur, Uwe

2012-01-01

Cardiopulmonary diseases affect millions of people and cause high costs in health care systems worldwide. Patients should perform regular endurance exercises to stabilize their health state and prevent further impairment. However, patients are often uncertain about the level of intensity they should exercise in their current condition. The cost of continuous monitoring for these training sessions in clinics is high and additionally requires the patient to travel to a clinic for each single session. Performing the rehabilitation training at home can raise compliance and reduce costs. To ensure safe telerehabilitation training and to enable patients to control their performance and health state, detection of abnormal events during training is a critical prerequisite. Therefore, we created a model that predicts the heart rate of cardiopulmonary patients and that can be used to detect and avoid abnormal health states. To enable external feedback and an immediate reaction in case of a critical situation, the patient should have the possibility to configure the system to communicate warnings and emergency events to clinical and non-clinical actors. To fulfill this task, we coupled a personal health record (PHR) with a new component that extends the classic home emergency systems. The PHR is also used for a training schedule definition that makes use of the predictive HR model. We used statistical methods to evaluate the prediction model and found that our prediction error of 3.2 heart beats per minute is precise enough to enable a detection of critical states. The concept for the communication of alerts was evaluated through focus group interviews with domain experts who judged that it fulfills the needs of potential users.

Critical Components of Curriculum Development for Career and Technical Education Instructors in the United States

ERIC Educational Resources Information Center

Wang, Victor C. X.

2010-01-01

Developing curriculum(s) requires instructors to take into several factors. These factors can be viewed as critical components of curriculum development for career and technical education (CTE) instructors. Without adequately addressing critical components such as curriculum history, curriculum theory, curriculum philosophies, curriculum…

SPOC Benchmark Case: SNRE Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vishal Patel; Michael Eades; Claude Russel Joyner II

The Small Nuclear Rocket Engine (SNRE) was modeled in the Center for Space Nuclear Research’s (CSNR) Space Propulsion Optimization Code (SPOC). SPOC aims to create nuclear thermal propulsion (NTP) geometries quickly to perform parametric studies on design spaces of historic and new NTP designs. The SNRE geometry was modeled in SPOC and a critical core with a reasonable amount of criticality margin was found. The fuel, tie-tubes, reflector, and control drum masses were predicted rather well. These are all very important for neutronics calculations so the active reactor geometries created with SPOC can continue to be trusted. Thermal calculations ofmore » the average and hot fuel channels agreed very well. The specific impulse calculations used historically and in SPOC disagree so mass flow rates and impulses differed. Modeling peripheral and power balance components that do not affect nuclear characteristics of the core is not a feature of SPOC and as such, these components should continue to be designed using other tools. A full paper detailing the available SNRE data and comparisons with SPOC outputs will be submitted as a follow-up to this abstract.« less

Pupillary and affective responses to maternal feedback and the development of borderline personality disorder symptoms.

PubMed

Scott, Lori N; Zalewski, Maureen; Beeney, Joseph E; Jones, Neil P; Stepp, Stephanie D

2017-08-01

Etiological models propose that a biological vulnerability to emotional reactivity plays an important role in the development of borderline personality disorder (BPD). However, the physiological and phenomenological components of emotional reactivity that predict the course of BPD symptoms in adolescence are poorly understood. This prospective study examines pupillary and affective responses to maternal feedback as predictors of BPD symptom development in adolescent girls over 18 months. Fifty-seven 16-year-old girls completed a laboratory task in which they heard recorded clips of their own mothers making critical or praising statements about them, as well as neutral statements that did not pertain to them. Changes in girls' pupil dilation and subjective affect were assessed throughout the task. The results demonstrated that greater pupillary response to maternal criticism predicted increases in BPD symptoms over time. In addition, greater pupillary and positive affective responses to maternal praise were associated with higher BPD symptoms at age 16 and faster decreases in BPD symptoms over time, but only among girls who heard clips that were rated by independent observers as less praising. The results suggest that emotional reactivity can serve as either a risk or a protective factor depending on context, with differential effects of reactivity to criticism versus praise.

Regression to fuzziness method for estimation of remaining useful life in power plant components

NASA Astrophysics Data System (ADS)

Alamaniotis, Miltiadis; Grelle, Austin; Tsoukalas, Lefteri H.

2014-10-01

Mitigation of severe accidents in power plants requires the reliable operation of all systems and the on-time replacement of mechanical components. Therefore, the continuous surveillance of power systems is a crucial concern for the overall safety, cost control, and on-time maintenance of a power plant. In this paper a methodology called regression to fuzziness is presented that estimates the remaining useful life (RUL) of power plant components. The RUL is defined as the difference between the time that a measurement was taken and the estimated failure time of that component. The methodology aims to compensate for a potential lack of historical data by modeling an expert's operational experience and expertise applied to the system. It initially identifies critical degradation parameters and their associated value range. Once completed, the operator's experience is modeled through fuzzy sets which span the entire parameter range. This model is then synergistically used with linear regression and a component's failure point to estimate the RUL. The proposed methodology is tested on estimating the RUL of a turbine (the basic electrical generating component of a power plant) in three different cases. Results demonstrate the benefits of the methodology for components for which operational data is not readily available and emphasize the significance of the selection of fuzzy sets and the effect of knowledge representation on the predicted output. To verify the effectiveness of the methodology, it was benchmarked against the data-based simple linear regression model used for predictions which was shown to perform equal or worse than the presented methodology. Furthermore, methodology comparison highlighted the improvement in estimation offered by the adoption of appropriate of fuzzy sets for parameter representation.

TBI server: a web server for predicting ion effects in RNA folding.

PubMed

Zhu, Yuhong; He, Zhaojian; Chen, Shi-Jie

2015-01-01

Metal ions play a critical role in the stabilization of RNA structures. Therefore, accurate prediction of the ion effects in RNA folding can have a far-reaching impact on our understanding of RNA structure and function. Multivalent ions, especially Mg²⁺, are essential for RNA tertiary structure formation. These ions can possibly become strongly correlated in the close vicinity of RNA surface. Most of the currently available software packages, which have widespread success in predicting ion effects in biomolecular systems, however, do not explicitly account for the ion correlation effect. Therefore, it is important to develop a software package/web server for the prediction of ion electrostatics in RNA folding by including ion correlation effects. The TBI web server http://rna.physics.missouri.edu/tbi_index.html provides predictions for the total electrostatic free energy, the different free energy components, and the mean number and the most probable distributions of the bound ions. A novel feature of the TBI server is its ability to account for ion correlation and ion distribution fluctuation effects. By accounting for the ion correlation and fluctuation effects, the TBI server is a unique online tool for computing ion-mediated electrostatic properties for given RNA structures. The results can provide important data for in-depth analysis for ion effects in RNA folding including the ion-dependence of folding stability, ion uptake in the folding process, and the interplay between the different energetic components.

Critical Components of Successful Inclusion of Students with Severe Disabilities: Literature Review

ERIC Educational Resources Information Center

Alquraini, Turki; Gut, Dianne

2012-01-01

This paper examines the critical components of successful inclusion for students with severe disabilities. This review sets out to provide an overview of literature regarding effective practices for inclusion with a focus on critical components of successful inclusion that assist in preparing the stakeholders worldwide to work and engage…

Engineering Transition-Metal-Coated Tungsten Carbides for Efficient and Selective Electrochemical Reduction of CO2 to Methane.

PubMed

Wannakao, Sippakorn; Artrith, Nongnuch; Limtrakul, Jumras; Kolpak, Alexie M

2015-08-24

The design of catalysts for CO2 reduction is challenging because of the fundamental relationships between the binding energies of the reaction intermediates. Metal carbides have shown promise for transcending these relationships and enabling low-cost alternatives. Herein, we show that directional bonding arising from the mixed covalent/metallic character plays a critical role in governing the surface chemistry. This behavior can be described by consideration of individual d-band components. We use this model to predict efficient catalysts based on tungsten carbide with a sub-monolayer of iron adatoms. Our approach can be used to predict site-preference and binding-energy trends for complex catalyst surfaces. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Temperature Measurement and Numerical Prediction in Machining Inconel 718

PubMed Central

Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-01-01

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning. PMID:28665312

Detection of superlattice domain formation in ternary lipid mixtures using fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Mutlu, Burcin; Lopez, Stephanie; Vaughn, Mark; Huang, Juyang; Cheng, K.

2011-10-01

Multicomponent lipid bilayers represent an important model system for studying the structures and functions of cell membranes. At present, the lateral organization of lipid components, particularly the formation of regular distribution, in lipid membranes containing charged lipid, e.g., phosphatidylserine, is not clear. Using a ternary phosphatidylcholine/phosphatidylserine/cholesterol lipid bilayer system, the presence of ordered domain formation was examined by measuring the fluorescence anisotropy of the embedded fluorescent probe, 22-(N-(7-nitrobenz-2-oxa-1,3-diazol- 4-yl)amino)-23,24-bisnor-5-cholen-3β- ol (NBD-CHOL), with structure similar to that of a cholesterol, as a function of phospatidylserine composition. The plot of the anisotropy vs. phosphatidylserine revealed abrupt changes at certain critical compositions of phosphatidylserine. Some of these critical compositions agree favorably with those predicted by the headgroup superlattice model suggesting that the charged phosphatidylserine lipid molecules adopt a superlattice-like distribution in the lipid bilayer at some predicted compositions. The ordered distribution of charged lipids may play an important role in the regulation of the composition of the biological membranes.

Scaling effect on the fracture toughness of bone materials using MMTS criterion.

PubMed

Akbardoost, Javad; Amirafshari, Reza; Mohsenzade, Omid; Berto, Filippo

2018-05-21

The aim of this study is to present a stress based approach for investigating the effect of specimen size on the fracture toughness of bone materials. The proposed approach is a modified form of the classical fracture criterion called maximum tangential stress (MTS). The mechanical properties of bone are different in longitudinal and transverse directions and hence the tangential stress component in the proposed approach should be determined in the orthotropic media. Since only the singular terms of series expansions were obtained in the previous studies, the tangential stress is measured from finite element analysis. In this study, the critical distance is also assumed to be size dependent and a semi-empirical formulation is used for describing the size dependency of the critical distance. By comparing the results predicted by the proposed approach and those reported in the previous studies, it is shown that the proposed approach can predict the fracture resistance of cracked bone by taking into account the effect of specimen size. Copyright © 2018 Elsevier Ltd. All rights reserved.

Voluntary Consensus Organization Standards for Nondestructive Evaluation of Thin-Walled Metallic Liners and Composite Overwraps in Composite Overwrapped Pressure Vessels

NASA Technical Reports Server (NTRS)

Waller, Jess; Saulsberry, Regor

2012-01-01

NASA fracture control requirements outlined in NASA-STD-5009 and NASA-STD-5014 are predicated on the availability and use of sensitive nondestructive evaluation (NDE) methods that can detect and monitor defects, thereby providing data that can be used to predict failure or reduce the risk of failure in fracture critical components. However, in the case of composite materials and components, including composite overwrapped pressure vessels (COPVs), the effect of defects is poorly understood, the NDE methods used to evaluate locate and size defects are typically at lower technical readiness level than analogous NDE methods used for metals, and demonstration studies to verify the probability of detection (POD) are generally lacking or unavailable. These factors together make failure prediction of fracture critical composite materials and components based on size, quantity, or orientation of defects nearly impossible. Also, when inspecting metal liners in as-manufactured COPVs, sensitivity is lost and only the inner surface of the liner is accessible. Also, NDE of COPVs as applied during manufacturing varies significantly from manufacturer to manufacturer and has not yet been standardized. Although requirements exist to perform NDE immediately after manufacturing to establish initial integrity of the parts, procedural detail for NDE of composites is still nonexistent or under development. For example, in practice, only a visual inspection of COPVs is performed during manufacturing and service, leaving in question whether defects of concern, for example, bridging, overwrap winding anomalies, impact damage below visible threshold, out-of-family strain growth, and liner buckling have been adequately detected and monitored. To address these shortcomings, in 2005 the NASA Nondestructive Evaluation Working Group (NNWG) began funding work to develop and adopt standards for nondestructive evaluation of aerospace composites in collaboration with the American Society for Testing and Materials (ASTM) Committee E07 on Nondestructive Testing. Similarly, in 2006 the NASA Engineering and Safety Center (NESC) recommended that nondestructive evaluation methods that can predict composite failure in COPVs should be developed and verified, and integrated into the damage control plan for these vessels

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

NASA Astrophysics Data System (ADS)

Mach, J. C.; Budrow, C. J.; Pagan, D. C.; Ruff, J. P. C.; Park, J.-S.; Okasinski, J.; Beaudoin, A. J.; Miller, M. P.

2017-05-01

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present work, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to develop significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. The experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.

Prediction of multi performance characteristics of wire EDM process using grey ANFIS

NASA Astrophysics Data System (ADS)

Kumanan, Somasundaram; Nair, Anish

2017-09-01

Super alloys are used to fabricate components in ultra-supercritical power plants. These hard to machine materials are processed using non-traditional machining methods like Wire cut electrical discharge machining and needs attention. This paper details about multi performance optimization of wire EDM process using Grey ANFIS. Experiments are designed to establish the performance characteristics of wire EDM such as surface roughness, material removal rate, wire wear rate and geometric tolerances. The control parameters are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. Grey relational analysis is employed to optimise the multi objectives. Analysis of variance of the grey grades is used to identify the critical parameters. A regression model is developed and used to generate datasets for the training of proposed adaptive neuro fuzzy inference system. The developed prediction model is tested for its prediction ability.

Long-Term Durability Analysis of a 100,000+ Hr Stirling Power Convertor Heater Head

NASA Technical Reports Server (NTRS)

Bartolotta, Paul A.; Bowman, Randy R.; Krause, David L.; Halford, Gary R.

2000-01-01

DOE and NASA have identified Stirling Radioisotope Power Systems (SRPS) as the power supply for deep space exploration missions the Europa Orbiter and Solar Probe. As a part of this effort, NASA has initiated a long-term durability project for critical hot section components of the Stirling power convertor to qualify flight hardware. This project will develop a life prediction methodology that utilizes short-term (t < 20,000 hr) test data to verify long-term (t > 100,000 hr) design life. The project consists of generating a materials database for the specific heat of alloy, evaluation of critical hermetic sealed joints, life model characterization, and model verification. This paper will describe the qualification methodology being developed and provide a status for this effort.

Harnessing the landscape of microbial culture media to predict new organism–media pairings

PubMed Central

Oberhardt, Matthew A.; Zarecki, Raphy; Gronow, Sabine; Lang, Elke; Klenk, Hans-Peter; Gophna, Uri; Ruppin, Eytan

2015-01-01

Culturing microorganisms is a critical step in understanding and utilizing microbial life. Here we map the landscape of existing culture media by extracting natural-language media recipes into a Known Media Database (KOMODO), which includes >18,000 strain–media combinations, >3300 media variants and compound concentrations (the entire collection of the Leibniz Institute DSMZ repository). Using KOMODO, we show that although media are usually tuned for individual strains using biologically common salts, trace metals and vitamins/cofactors are the most differentiating components between defined media of strains within a genus. We leverage KOMODO to predict new organism–media pairings using a transitivity property (74% growth in new in vitro experiments) and a phylogeny-based collaborative filtering tool (83% growth in new in vitro experiments and stronger growth on predicted well-scored versus poorly scored media). These resources are integrated into a web-based platform that predicts media given an organism's 16S rDNA sequence, facilitating future cultivation efforts. PMID:26460590

Bose-Einstein condensation and superfluidity of dipolar excitons in a phosphorene double layer

NASA Astrophysics Data System (ADS)

Berman, Oleg L.; Gumbs, Godfrey; Kezerashvili, Roman Ya.

2017-07-01

We study the formation of dipolar excitons and their superfluidity in a phosphorene double layer. The analytical expressions for the single dipolar exciton energy spectrum and wave function are obtained. It is predicted that a weakly interacting gas of dipolar excitons in a double layer of black phosphorus exhibits superfluidity due to the dipole-dipole repulsion between the dipolar excitons. In calculations are employed the Keldysh and Coulomb potentials for the interaction between the charge carriers to analyze the influence of the screening effects on the studied phenomena. It is shown that the critical velocity of superfluidity, the spectrum of collective excitations, concentrations of the superfluid and normal component, and mean-field critical temperature for superfluidity are anisotropic and demonstrate the dependence on the direction of motion of dipolar excitons. The critical temperature for superfluidity increases if the exciton concentration and the interlayer separation increase. It is shown that the dipolar exciton binding energy and mean-field critical temperature for superfluidity are sensitive to the electron and hole effective masses. The proposed experiment to observe a directional superfluidity of excitons is addressed.

Application of a constant hole volume Sanchez-Lacombe equation of state to mixtures relevant to polymeric foaming.

PubMed

von Konigslow, Kier; Park, Chul B; Thompson, Russell B

2018-06-06

A variant of the Sanchez-Lacombe equation of state is applied to several polymers, blowing agents, and saturated mixtures of interest to the polymer foaming industry. These are low-density polyethylene-carbon dioxide and polylactide-carbon dioxide saturated mixtures as well as polystyrene-carbon dioxide-dimethyl ether and polystyrene-carbon dioxide-nitrogen ternary saturated mixtures. Good agreement is achieved between theoretically predicted and experimentally determined solubilities, both for binary and ternary mixtures. Acceptable agreement with swelling ratios is found with no free parameters. Up-to-date pure component Sanchez-Lacombe characteristic parameters are provided for carbon dioxide, dimethyl ether, low-density polyethylene, nitrogen, polylactide, linear and branched polypropylene, and polystyrene. Pure fluid low-density polyethylene and nitrogen parameters exhibit more moderate success while still providing acceptable quantitative estimations. Mixture estimations are found to have more moderate success where pure components are not as well represented. The Sanchez-Lacombe equation of state is found to correctly predict the anomalous reversal of solubility temperature dependence for low critical point fluids through the observation of this behaviour in polystyrene nitrogen mixtures.

Reliability of Radioisotope Stirling Convertor Linear Alternator

NASA Technical Reports Server (NTRS)

Shah, Ashwin; Korovaichuk, Igor; Geng, Steven M.; Schreiber, Jeffrey G.

2006-01-01

Onboard radioisotope power systems being developed and planned for NASA s deep-space missions would require reliable design lifetimes of up to 14 years. Critical components and materials of Stirling convertors have been undergoing extensive testing and evaluation in support of a reliable performance for the specified life span. Of significant importance to the successful development of the Stirling convertor is the design of a lightweight and highly efficient linear alternator. Alternator performance could vary due to small deviations in the permanent magnet properties, operating temperature, and component geometries. Durability prediction and reliability of the alternator may be affected by these deviations from nominal design conditions. Therefore, it is important to evaluate the effect of these uncertainties in predicting the reliability of the linear alternator performance. This paper presents a study in which a reliability-based methodology is used to assess alternator performance. The response surface characterizing the induced open-circuit voltage performance is constructed using 3-D finite element magnetic analysis. Fast probability integration method is used to determine the probability of the desired performance and its sensitivity to the alternator design parameters.

SCARE: A post-processor program to MSC/NASTRAN for the reliability analysis of structural ceramic components

NASA Technical Reports Server (NTRS)

Gyekenyesi, J. P.

1985-01-01

A computer program was developed for calculating the statistical fast fracture reliability and failure probability of ceramic components. The program includes the two-parameter Weibull material fracture strength distribution model, using the principle of independent action for polyaxial stress states and Batdorf's shear-sensitive as well as shear-insensitive crack theories, all for volume distributed flaws in macroscopically isotropic solids. Both penny-shaped cracks and Griffith cracks are included in the Batdorf shear-sensitive crack response calculations, using Griffith's maximum tensile stress or critical coplanar strain energy release rate criteria to predict mixed mode fracture. Weibull material parameters can also be calculated from modulus of rupture bar tests, using the least squares method with known specimen geometry and fracture data. The reliability prediction analysis uses MSC/NASTRAN stress, temperature and volume output, obtained from the use of three-dimensional, quadratic, isoparametric, or axisymmetric finite elements. The statistical fast fracture theories employed, along with selected input and output formats and options, are summarized. An example problem to demonstrate various features of the program is included.

Is rapid automatized naming related to reading and mathematics for the same reason(s)? A follow-up study from kindergarten to Grade 1.

PubMed

Georgiou, George K; Tziraki, Niki; Manolitsis, George; Fella, Argyro

2013-07-01

We examined (a) what rapid automatized naming (RAN) components (articulation time and/or pause time) predict reading and mathematics ability and (b) what processing skills involved in RAN (speed of processing, response inhibition, working memory, and/or phonological awareness) may explain its relationship with reading and mathematics. A sample of 72 children were followed from the beginning of kindergarten until the end of Grade 1 and were assessed on measures of RAN, general cognitive ability, speed of processing, attention, working memory, phonological awareness, reading, and mathematics. The results indicated that pause time was the critical component in both the RAN-reading and RAN-mathematics relationships and that it shared most of its predictive variance in reading and mathematics with speed of processing and working memory. Our findings further suggested that, unlike the relationship between RAN and reading fluency in Grade 1, there is nothing in the RAN task that is uniquely related to math. Copyright © 2013 Elsevier Inc. All rights reserved.

Horizontal Two Phase Flow Regime Identification: Comparison of Pressure Signature, Electrical Capacitance Tomography (ECT) and High Speed Visualization (Postprint)

DTIC Science & Technology

2012-11-01

W., and Mudawar , I., "Measurement and Correlation of Critical Heat Flux in Two-Phase Micro-Channel Heat Sinks," International Journal of Heat and...Mass Transfer, Vol. 47, No. 10-11, 2004, pp. 2045-2059. 3 Zhang, H., Mudawar , I., and Hasan, M. M., "Photographic Study of High-Flux Subcooled Flow...component Fow in Pipes," Chemical Engineering Progress, Vol. 45, 1949, pp. 39-48. 34 Qu, W., and Mudawar , I., "Measurement and Prediction of Pressure

Airframe noise: A design and operating problem

NASA Technical Reports Server (NTRS)

Hardin, J. C.

1976-01-01

A critical assessment of the state of the art in airframe noise is presented. Full-scale data on the intensity, spectra, and directivity of this noise source are evaluated in light of the comprehensive theory developed by Ffowcs Williams and Hawkings. Vibration of panels on the aircraft is identified as a possible additional source of airframe noise. The present understanding and methods for prediction of other component sources - airfoils, struts, and cavities - are discussed. Operating problems associated with airframe noise as well as potential design methods for airframe noise reduction are identified.

Connectivity patterns in cognitive control networks predict naturalistic multitasking ability.

PubMed

Wen, Tanya; Liu, De-Cyuan; Hsieh, Shulan

2018-06-01

Multitasking is a fundamental aspect of everyday life activities. To achieve a complex, multi-component goal, the tasks must be subdivided into sub-tasks and component steps, a critical function of prefrontal networks. The prefrontal cortex is considered to be organized in a cascade of executive processes from the sensorimotor to anterior prefrontal cortex, which includes execution of specific goal-directed action, to encoding and maintaining task rules, and finally monitoring distal goals. In the current study, we used a virtual multitasking paradigm to tap into real-world performance and relate it to each individual's resting-state functional connectivity in fMRI. While did not find any correlation between global connectivity of any of the major networks with multitasking ability, global connectivity of the lateral prefrontal cortex (LPFC) was predictive of multitasking ability. Further analysis showed that multivariate connectivity patterns within the sensorimotor network (SMN), and between-network connectivity of the frontoparietal network (FPN) and dorsal attention network (DAN), predicted individual multitasking ability and could be generalized to novel individuals. Together, these results support previous research that prefrontal networks underlie multitasking abilities and show that connectivity patterns in the cascade of prefrontal networks may explain individual differences in performance. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

A comparison of four typical green exercise environments and prediction of psychological health outcomes.

PubMed

Rogerson, Mike; Brown, Daniel K; Sandercock, Gavin; Wooller, John-James; Barton, Jo

2016-05-01

'Green exercise' (GE) is physical activity while simultaneously being exposed to nature. GE comprises three physical components: the individual, the exercise and the environment, and one processes component encompassing a range of psychological and physiological processes. Previous research has consistently shown affective benefits of GE compared to equivalent non-GE. Investigating the possibility of optimum GE environments may help maximise health benefits. The aim of this study was to compare affective outcomes of GE participation between four different typical GE environments (beach, grasslands, riverside, heritage), and further examine influences of several physical component-related variables and one processes component-related variable, on these outcomes. Participants (N = 331) completed questionnaires before and after a 5km run, at one of four parkrun event locations. Self-esteem (Δ = 1.61, 95% confidence interval (CI) = (1.30, 1.93)), stress (Δ = -2.36, 95% CI = (-3.01, -1.71)) and mood (Δ = -5.25, 95% CI = (-7.45, -3.05)) all significantly improved from pre- to post-run (p < .05). Improvements in these measures were not significantly different between environments. Several component-related variables significantly predicted these improvements, accounting for 9% of self-esteem improvement, 1.6% of perceived stress improvement, and 9.5% of mood improvement. GE offers accessible provision for improving acute psychological wellbeing. Although nature-based exercise environments can facilitate affective outcomes, the overall type of nature may be less critical. Other characteristics of the individual, exercise and environment can significantly influence attainment of psychological GE benefits. However, the results support a greater importance of the processes component in attaining previously reported affective outcomes. © Royal Society for Public Health 2015.

A classical model for closed-loop diagrams of binary liquid mixtures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schnitzler, J.v.; Prausnitz, J.M.

1994-03-01

A classical lattice model for closed-loop temperature-composition phase diagrams has been developed. It considers the effect of specific interactions, such as hydrogen bonding, between dissimilar components. This van Laar-type model includes a Flory-Huggins term for the excess entropy of mixing. It is applied to several liquid-liquid equilibria of nonelectrolytes, where the molecules of the two components differ in size. The model is able to represent the observed data semi-quantitatively, but in most cases it is not flexible enough to predict all parts of the closed loop quantitatively. The ability of the model to represent different binary systems is discussed. Finally,more » attention is given to a correction term, concerning the effect of concentration fluctuations near the upper critical solution temperature.« less

An inter-professional approach to personalized medicine education: one institution's experience.

PubMed

Formea, Christine M; Nicholson, Wayne T; Vitek, Carolyn Rohrer

2015-03-01

Personalized medicine offers the promise of better diagnoses, targeted therapies and individualized treatment plans. Pharmacogenomics is an integral component of personalized medicine; it aids in the prediction of an individual's response to medications. Despite growing public acceptance and emerging clinical evidence, this rapidly expanding field of medicine is slow to be adopted and utilized by healthcare providers, although many believe that they should be knowledgeable and able to apply pharmacogenomics in clinical practice. Institutional infrastructure must be built to support pharmacogenomic implementation. Multidisciplinary education for healthcare providers is a critical component for pharmacogenomics to achieve its full potential to optimize patient care. We describe our recent experience at the Mayo Clinic implementing pharmacogenomics education in a large, academic healthcare system facilitated by the Mayo Clinic Center for Individualized Medicine.

Measurement and prediction of model-rotor flow fields

NASA Technical Reports Server (NTRS)

Owen, F. K.; Tauber, M. E.

1985-01-01

This paper shows that a laser velocimeter can be used to measure accurately the three-component velocities induced by a model rotor at transonic tip speeds. The measurements, which were made at Mach numbers from 0.85 to 0.95 and at zero advance ratio, yielded high-resolution, orthogonal velocity values. The measured velocities were used to check the ability of the ROT22 full-potential rotor code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high-speed rotor blade. The good agreement between the calculated and measured velocities established the code's ability to predict the off-blade flow field at transonic tip speeds. This supplements previous comparisons in which surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuthal blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip-region flow field, including the occurrence, strength, and location of shock waves causing high drag and noise.

Probabilistic Structural Analysis Methods for select space propulsion system components (PSAM). Volume 2: Literature surveys of critical Space Shuttle main engine components

NASA Technical Reports Server (NTRS)

Rajagopal, K. R.

1992-01-01

The technical effort and computer code development is summarized. Several formulations for Probabilistic Finite Element Analysis (PFEA) are described with emphasis on the selected formulation. The strategies being implemented in the first-version computer code to perform linear, elastic PFEA is described. The results of a series of select Space Shuttle Main Engine (SSME) component surveys are presented. These results identify the critical components and provide the information necessary for probabilistic structural analysis. Volume 2 is a summary of critical SSME components.

Exploring a Contextual Model of Sexual Self-Disclosure and Sexual Satisfaction.

PubMed

Brown, Randal D; Weigel, Daniel J

2018-02-01

Sexual self-disclosure is a critical component of relationship and sexual satisfaction, yet little is known about the mechanisms that facilitate a person's engagement in sexual self-disclosure. Individuals (N = 265) involved in romantic relationships participated in an online study testing a contextual model of sexual self-disclosure across three contexts: relationship context, sexual self-disclosure context, and outcome of sexual self-disclosure. Results suggest that sexual satisfaction was predicted by a positive relationship context and a positive sexual self-disclosure context. In addition, the sexual self-disclosure context was predicted by the relationship context. These findings emphasize the importance of examining contextual influences that determine whether an individual will engage in or avoid sexual self-disclosure and the consequences of this engagement or avoidance on sexual satisfaction.

Global connectivity of prefrontal cortex predicts cognitive control and intelligence

PubMed Central

Cole, Michael W.; Yarkoni, Tal; Repovs, Grega; Anticevic, Alan; Braver, Todd S.

2012-01-01

Control of thought and behavior is fundamental to human intelligence. Evidence suggests a fronto-parietal brain network implements such cognitive control across diverse contexts. We identify a mechanism – global connectivity – by which components of this network might coordinate control of other networks. A lateral prefrontal cortex (LPFC) region’s activity was found to predict performance in a high control demand working memory task, and also to exhibit high global connectivity. Critically, global connectivity in this LPFC region, involving connections both within and outside the fronto-parietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brain-wide influence that facilitates the ability to implement control processes central to human intelligence. PMID:22745498

Electrostatics of DNA-Functionalized Nanoparticles

NASA Astrophysics Data System (ADS)

Hoffmann, Kyle; Krishnamoorthy, Kurinji; Kewalramani, Sumit; Bedzyk, Michael; Olvera de La Cruz, Monica

DNA-functionalized nanoparticles have applications in directed self-assembly and targeted cellular delivery of therapeutic proteins. In order to design specific systems, it is necessary to understand their self-assembly properties, of which the long-range electrostatic interactions are a critical component. We iteratively solved equations derived from classical density functional theory in order to predict the distribution of ions around DNA-functionalized Cg Catalase. We then compared estimates of the resonant intensity to those from SAXS measurements to estimate key features of DNA-functionalized proteins, such as the size of the region linking the protein and DNA and the extension of the single-stranded DNA. Using classical density functional theory and coarse-grained simulations, we are able to predict and understand these fundamental properties in order to rationally design new biomaterials.

Bio-chemo-mechanical models of vascular mechanics

PubMed Central

Kim, Jungsil; Wagenseil, Jessica E.

2014-01-01

Models of vascular mechanics are necessary to predict the response of an artery under a variety of loads, for complex geometries, and in pathological adaptation. Classic constitutive models for arteries are phenomenological and the fitted parameters are not associated with physical components of the wall. Recently, microstructurally-linked models have been developed that associate structural information about the wall components with tissue-level mechanics. Microstructurally-linked models are useful for correlating changes in specific components with pathological outcomes, so that targeted treatments may be developed to prevent or reverse the physical changes. However, most treatments, and many causes, of vascular disease have chemical components. Chemical signaling within cells, between cells, and between cells and matrix constituents affects the biology and mechanics of the arterial wall in the short- and long-term. Hence, bio-chemo-mechanical models that include chemical signaling are critical for robust models of vascular mechanics. This review summarizes bio-mechanical and bio-chemo-mechanical models with a focus on large elastic arteries. We provide applications of these models and challenges for future work. PMID:25465618

Hybrid computational and experimental approach for the study and optimization of mechanical components

NASA Astrophysics Data System (ADS)

Furlong, Cosme; Pryputniewicz, Ryszard J.

1998-05-01

Increased demands on the performance and efficiency of mechanical components impose challenges on their engineering design and optimization, especially when new and more demanding applications must be developed in relatively short periods of time while satisfying design objectives, as well as cost and manufacturability. In addition, reliability and durability must be taken into consideration. As a consequence, effective quantitative methodologies, computational and experimental, should be applied in the study and optimization of mechanical components. Computational investigations enable parametric studies and the determination of critical engineering design conditions, while experimental investigations, especially those using optical techniques, provide qualitative and quantitative information on the actual response of the structure of interest to the applied load and boundary conditions. We discuss a hybrid experimental and computational approach for investigation and optimization of mechanical components. The approach is based on analytical, computational, and experimental resolutions methodologies in the form of computational, noninvasive optical techniques, and fringe prediction analysis tools. Practical application of the hybrid approach is illustrated with representative examples that demonstrate the viability of the approach as an effective engineering tool for analysis and optimization.

"Squishy capacitor" model for electrical double layers and the stability of charged interfaces.

PubMed

Partenskii, Michael B; Jordan, Peter C

2009-07-01

Negative capacitance (NC), predicted by various electrical double layer (EDL) theories, is critically reviewed. Physically possible for individual components of the EDL, the compact or diffuse layer, it is strictly prohibited for the whole EDL or for an electrochemical cell with two electrodes. However, NC is allowed for the artificial conditions of sigma control, where an EDL is described by the equilibrium electric response of electrolyte to a field of fixed, and typically uniform, surface charge-density distributions, sigma. The contradiction is only apparent; in fact local sigma cannot be set independently, but is established by the equilibrium response to physically controllable variables, i.e., applied voltage phi (phi control) or total surface charge q (q control). NC predictions in studies based on sigma control signify potential instabilities and phase transitions for physically realizable conditions. Building on our previous study of phi control [M. B. Partenskii and P. C. Jordan, Phys. Rev. E 77, 061117 (2008)], here we analyze critical behavior under q control, clarifying the basic picture using an exactly solvable "squishy capacitor" toy model. We find that phi can change discontinuously in the presence of a lateral transition, specify stability conditions for an electrochemical cell, analyze the origin of the EDL's critical point in terms of compact and diffuse serial contributions, and discuss perspectives and challenges for theoretical studies not limited by sigma control.

A comparison of the two approaches of the theory of critical distances based on linear-elastic and elasto-plastic analyses

NASA Astrophysics Data System (ADS)

Terekhina, A. I.; Plekhov, O. A.; Kostina, A. A.; Susmel, L.

2017-06-01

The problem of determining the strength of engineering structures, considering the effects of the non-local fracture in the area of stress concentrators is a great scientific and industrial interest. This work is aimed on modification of the classical theory of critical distance that is known as a method of failure prediction based on linear-elastic analysis in case of elasto-plastic material behaviour to improve the accuracy of estimation of lifetime of notched components. Accounting plasticity has been implemented with the use of the Simplified Johnson-Cook model. Mechanical tests were carried out using a 300 kN electromechanical testing machine Shimadzu AG-X Plus. The cylindrical un-notched specimens and specimens with stress concentrators of titanium alloy Grade2 were tested under tensile loading with different grippers travel speed, which ensured several orders of strain rate. The results of elasto-plastic analyses of stress distributions near a wide variety of notches are presented. The results showed that the use of the modification of the TCD based on elasto-plastic analysis gives us estimates falling within an error interval of ±5-10%, that more accurate predictions than the linear elastic TCD solution. The use of an improved description of the stress-strain state at the notch tip allows introducing the critical distances as a material parameter.

Application of fracture mechanics and half-cycle method to the prediction of fatigue life of B-52 aircraft pylon components

NASA Technical Reports Server (NTRS)

Ko, W. L.; Carter, A. L.; Totton, W. W.; Ficke, J. M.

1989-01-01

Stress intensity levels at various parts of the NASA B-52 carrier aircraft pylon were examined for the case when the pylon store was the space shuttle solid rocket booster drop test vehicle. Eight critical stress points were selected for the pylon fatigue analysis. Using fracture mechanics and the half-cycle theory (directly or indirectly) for the calculations of fatigue-crack growth ,the remaining fatigue life (number of flights left) was estimated for each critical part. It was found that the two rear hooks had relatively short fatigue life and that the front hook had the shortest fatigue life of all the parts analyzed. The rest of the pylon parts were found to be noncritical because of their extremely long fatigue life associated with the low operational stress levels.

Analytical model development for the prediction of the frictional resistance of a capsule endoscope inside an intestine.

PubMed

Kim, J S; Sung, I H; Kim, Y T; Kim, D E; Jang, Y H

2007-11-01

For the purpose of optimizing the design of the locomotion mechanism as well as the body shape of a self-propelled capsule endoscope, an analytical model for the prediction of frictional resistance of the capsule moving inside the small intestine was first developed. The model was developed by considering the contact geometry and viscoelasticity of the intestine, based on the experimental investigations on the material properties of the intestine and the friction of the capsule inside the small intestine. In order to verify the model and to investigate the distributions of various stress components applied to the capsule, finite element (FE) analyses were carried out. The comparison of the frictional resistance between the predicted and the experimental values suggested that the proposed model could predict the frictional force of the capsule with reasonable accuracy. Also, the FE analysis results of various stress components revealed the stress relaxation of the intestine and explained that such stress relaxation characteristics of the intestine resulted in lower frictional force as the speed of the capsule decreased. These results suggested that the frontal shape of the capsule was critical to the design of the capsule with desired frictional performance. It was shown that the proposed model can provide quantitative estimation of the frictional resistance of the capsule under various moving conditions inside the intestine. The model is expected to be useful in the design optimization of the capsule locomotion inside the intestine.

Membrane-Based Characterization of a Gas Component — A Transient Sensor Theory

PubMed Central

Lazik, Detlef

2014-01-01

Based on a multi-gas solution-diffusion problem for a dense symmetrical membrane this paper presents a transient theory of a planar, membrane-based sensor cell for measuring gas from both initial conditions: dynamic and thermodynamic equilibrium. Using this theory, the ranges for which previously developed, simpler approaches are valid will be discussed; these approaches are of vital interest for membrane-based gas sensor applications. Finally, a new theoretical approach is introduced to identify varying gas components by arranging sensor cell pairs resulting in a concentration independent gas-specific critical time. Literature data for the N2, O2, Ar, CH4, CO2, H2 and C4H10 diffusion coefficients and solubilities for a polydimethylsiloxane membrane were used to simulate gas specific sensor responses. The results demonstrate the influence of (i) the operational mode; (ii) sensor geometry and (iii) gas matrices (air, Ar) on that critical time. Based on the developed theory the case-specific suitable membrane materials can be determined and both operation and design options for these sensors can be optimized for individual applications. The results of mixing experiments for different gases (O2, CO2) in a gas matrix of air confirmed the theoretical predictions. PMID:24608004

Equivalent damage: A critical assessment

NASA Technical Reports Server (NTRS)

Laflen, J. R.; Cook, T. S.

1982-01-01

Concepts in equivalent damage were evaluated to determine their applicability to the life prediction of hot path components of aircraft gas turbine engines. Equivalent damage was defined as being those effects which influence the crack initiation life-time beyond the damage that is measured in uniaxial, fully-reversed sinusoidal and isothermal experiments at low homologous temperatures. Three areas of equivalent damage were examined: mean stress, cumulative damage, and multiaxiality. For each area, a literature survey was conducted to aid in selecting the most appropriate theories. Where possible, data correlations were also used in the evaluation process. A set of criteria was developed for ranking the theories in each equivalent damage regime. These criteria considered aspects of engine utilization as well as the theoretical basis and correlative ability of each theory. In addition, consideration was given to the complex nature of the loading cycle at fatigue critical locations of hot path components; this loading includes non-proportional multiaxial stressing, combined temperature and strain fluctuations, and general creep-fatigue interactions. Through applications of selected equivalent damage theories to some suitable data sets it was found that there is insufficient data to allow specific recommendations of preferred theories for general applications. A series of experiments and areas of further investigations were identified.

Physics Based Modeling and Prognostics of Electrolytic Capacitors

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan; Ceyla, Jose R.; Biswas, Gautam; Goebel, Kai

2012-01-01

This paper proposes first principles based modeling and prognostics approach for electrolytic capacitors. Electrolytic capacitors have become critical components in electronics systems in aeronautics and other domains. Degradations and faults in DC-DC converter unit propagates to the GPS and navigation subsystems and affects the overall solution. Capacitors and MOSFETs are the two major components, which cause degradations and failures in DC-DC converters. This type of capacitors are known for its low reliability and frequent breakdown on critical systems like power supplies of avionics equipment and electrical drivers of electromechanical actuators of control surfaces. Some of the more prevalent fault effects, such as a ripple voltage surge at the power supply output can cause glitches in the GPS position and velocity output, and this, in turn, if not corrected will propagate and distort the navigation solution. In this work, we study the effects of accelerated aging due to thermal stress on different sets of capacitors under different conditions. Our focus is on deriving first principles degradation models for thermal stress conditions. Data collected from simultaneous experiments are used to validate the desired models. Our overall goal is to derive accurate models of capacitor degradation, and use them to predict performance changes in DC-DC converters.

Computational and experimental analysis of TMS-induced electric field vectors critical to neuronal activation

NASA Astrophysics Data System (ADS)

Krieg, Todd D.; Salinas, Felipe S.; Narayana, Shalini; Fox, Peter T.; Mogul, David J.

2015-08-01

Objective. Transcranial magnetic stimulation (TMS) represents a powerful technique to noninvasively modulate cortical neurophysiology in the brain. However, the relationship between the magnetic fields created by TMS coils and neuronal activation in the cortex is still not well-understood, making predictable cortical activation by TMS difficult to achieve. Our goal in this study was to investigate the relationship between induced electric fields and cortical activation measured by blood flow response. Particularly, we sought to discover the E-field characteristics that lead to cortical activation. Approach. Subject-specific finite element models (FEMs) of the head and brain were constructed for each of six subjects using magnetic resonance image scans. Positron emission tomography (PET) measured each subject’s cortical response to image-guided robotically-positioned TMS to the primary motor cortex. FEM models that employed the given coil position, orientation, and stimulus intensity in experimental applications of TMS were used to calculate the electric field (E-field) vectors within a region of interest for each subject. TMS-induced E-fields were analyzed to better understand what vector components led to regional cerebral blood flow (CBF) responses recorded by PET. Main results. This study found that decomposing the E-field into orthogonal vector components based on the cortical surface geometry (and hence, cortical neuron directions) led to significant differences between the regions of cortex that were active and nonactive. Specifically, active regions had significantly higher E-field components in the normal inward direction (i.e., parallel to pyramidal neurons in the dendrite-to-axon orientation) and in the tangential direction (i.e., parallel to interneurons) at high gradient. In contrast, nonactive regions had higher E-field vectors in the outward normal direction suggesting inhibitory responses. Significance. These results provide critical new understanding of the factors by which TMS induces cortical activation necessary for predictive and repeatable use of this noninvasive stimulation modality.

Comparative analysis of multiple-casualty incident triage algorithms.

PubMed

Garner, A; Lee, A; Harrison, K; Schultz, C H

2001-11-01

We sought to retrospectively measure the accuracy of multiple-casualty incident (MCI) triage algorithms and their component physiologic variables in predicting adult patients with critical injury. We performed a retrospective review of 1,144 consecutive adult patients transported by ambulance and admitted to 2 trauma centers. Association between first-recorded out-of-hospital physiologic variables and a resource-based definition of severe injury appropriate to the MCI context was determined. The association between severe injury and Triage Sieve, Simple Triage and Rapid Treatment, modified Simple Triage and Rapid Treatment, and CareFlight Triage was determined in the patient population. Of the physiologic variables, the Motor Component of the Glasgow Coma Scale had the strongest association with severe injury, followed by systolic blood pressure. The differences between CareFlight Triage, Simple Triage and Rapid Treatment, and modified Simple Triage and Rapid Treatment were not dramatic, with sensitivities of 82% (95% confidence interval [CI] 75% to 88%), 85% (95% CI 78% to 90%), and 84% (95% CI 76% to 89%), respectively, and specificities of 96% (95% CI 94% to 97%), 86% (95% CI 84% to 88%), and 91% (95% CI 89% to 93%), respectively. Both forms of Triage Sieve were significantly poorer predictors of severe injury. Of the physiologic variables used in the triage algorithms, the Motor Component of the Glasgow Coma Scale and systolic blood pressure had the strongest association with severe injury. CareFlight Triage, Simple Triage and Rapid Treatment, and modified Simple Triage and Rapid Treatment had similar sensitivities in predicting critical injury in designated trauma patients, but CareFlight Triage had better specificity. Because patients in a true mass casualty situation may not be completely comparable with designated trauma patients transported to emergency departments in routine circumstances, the best triage instrument in this study may not be the best in an actual MCI. These findings must be validated prospectively before their accuracy can be confirmed.

Novel approach of wavelet analysis for nonlinear ultrasonic measurements and fatigue assessment of jet engine components

NASA Astrophysics Data System (ADS)

Bunget, Gheorghe; Tilmon, Brevin; Yee, Andrew; Stewart, Dylan; Rogers, James; Webster, Matthew; Farinholt, Kevin; Friedersdorf, Fritz; Pepi, Marc; Ghoshal, Anindya

2018-04-01

Widespread damage in aging aircraft is becoming an increasing concern as both civil and military fleet operators are extending the service lifetime of their aircraft. Metallic components undergoing variable cyclic loadings eventually fatigue and form dislocations as precursors to ultimate failure. In order to characterize the progression of fatigue damage precursors (DP), the acoustic nonlinearity parameter is measured as the primary indicator. However, using proven standard ultrasonic technology for nonlinear measurements presents limitations for settings outside of the laboratory environment. This paper presents an approach for ultrasonic inspection through automated immersion scanning of hot section engine components where mature ultrasonic technology is used during periodic inspections. Nonlinear ultrasonic measurements were analyzed using wavelet analysis to extract multiple harmonics from the received signals. Measurements indicated strong correlations of nonlinearity coefficients and levels of fatigue in aluminum and Ni-based superalloys. This novel wavelet cross-correlation (WCC) algorithm is a potential technique to scan for fatigue damage precursors and identify critical locations for remaining life prediction.

A computational approach for coupled 1D and 2D/3D CFD modelling of pulse Tube cryocoolers

NASA Astrophysics Data System (ADS)

Fang, T.; Spoor, P. S.; Ghiaasiaan, S. M.

2017-12-01

The physics behind Stirling-type cryocoolers are complicated. One dimensional (1D) simulation tools offer limited details and accuracy, in particular for cryocoolers that have non-linear configurations. Multi-dimensional Computational Fluid Dynamic (CFD) methods are useful but are computationally expensive in simulating cyrocooler systems in their entirety. In view of the fact that some components of a cryocooler, e.g., inertance tubes and compliance tanks, can be modelled as 1D components with little loss of critical information, a 1D-2D/3D coupled model was developed. Accordingly, one-dimensional - like components are represented by specifically developed routines. These routines can be coupled to CFD codes and provide boundary conditions for 2D/3D CFD simulations. The developed coupled model, while preserving sufficient flow field details, is two orders of magnitude faster than equivalent 2D/3D CFD models. The predictions show good agreement with experimental data and 2D/3D CFD model.

Rationale for the Use of CAD/CAM Technology in Implant Prosthodontics

PubMed Central

Abduo, Jaafar; Lyons, Karl

2013-01-01

Despite the predictable longevity of implant prosthesis, there is an ongoing interest to continue to improve implant prosthodontic treatment and outcomes. One of the developments is the application of computer-aided design and computer-aided manufacturing (CAD/CAM) to produce implant abutments and frameworks from metal or ceramic materials. The aim of this narrative review is to critically evaluate the rationale of CAD/CAM utilization for implant prosthodontics. To date, CAD/CAM allows simplified production of precise and durable implant components. The precision of fit has been proven in several laboratory experiments and has been attributed to the design of implants. Milling also facilitates component fabrication from durable and aesthetic materials. With further development, it is expected that the CAD/CAM protocol will be further simplified. Although compelling clinical evidence supporting the superiority of CAD/CAM implant restorations is still lacking, it is envisioned that CAD/CAM may become the main stream for implant component fabrication. PMID:23690778

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nelsen, Nicholas H.; Kolb, James D.; Kulkarni, Akshay G.

Mechanical component response to shock environments must be predictable in order to ensure reliability and safety. Whether the shock input results from accidental drops during transportation to projectile impact scenarios, the system must irreversibly transition into a safe state that is incapable of triggering the component . With this critical need in mind, the 2017 Nuclear Weapons Summer Product Realization Institute (NW SPRINT) program objective sought the design of a passive shock failsafe with emphasis on additively manufactured (AM) components. Team Advanced and Exploratory (A&E) responded to the challenge by designing and delivering multiple passive shock sensing mech anisms thatmore » activate within a prescribed mechanical shock threshold. These AM failsafe designs were tuned and validated using analytical and computational techniques including the shock response spectrum (SRS) and finite element analysis (FEA). After rapid prototyping, the devices experienced physical shock tests conducted on Sandia drop tables to experimentally verify performance. Keywords: Additive manufacturing, dynamic system, failsafe, finite element analysis, mechanical shock, NW SPRINT, shock respon se spectrum« less

Reach-to-grasp movement as a minimization process.

PubMed

Yang, Fang; Feldman, Anatol G

2010-02-01

It is known that hand transport and grasping are functionally different but spatially coordinated components of reach-to-grasp (RTG) movements. As an extension of this notion, we suggested that body segments involved in RTG movements are controlled as a coherent ensemble by a global minimization process associated with the necessity for the hand to reach the motor goal. Different RTG components emerge following this process without pre-programming. Specifically, the minimization process may result from the tendency of neuromuscular elements to diminish the spatial gap between the actual arm-hand configuration and its virtual (referent) configuration specified by the brain. The referent configuration is specified depending on the object shape, localization, and orientation. Since the minimization process is gradual, it can be interrupted and resumed following mechanical perturbations, at any phase during RTG movements, including hand closure. To test this prediction of the minimization hypothesis, we asked subjects to reach and grasp a cube placed within the reach of the arm. Vision was prevented during movement until the hand returned to its initial position. As predicted, by arresting wrist motion at different points of hand transport in randomly selected trials, it was possible to halt changes in hand aperture at any phase, not only during hand opening but also during hand closure. Aperture changes resumed soon after the wrist was released. Another test of the minimization hypothesis was made in RTG movements to an object placed beyond the reach of the arm. It has previously been shown (Rossi et al. in J Physiol 538:659-671, 2002) that in such movements, the trunk motion begins to contribute to hand transport only after a critical phase when the shifts in the referent arm configuration have finished (at about the time when hand velocity is maximal). The minimization rule suggests that when the virtual contribution of the arm to hand transport is completed, guidance of hand aperture switches from the arm to the trunk control system. As a consequence, hand aperture changes can be halted by trunk arrests but only if they are prolonged beyond a critical phase. As predicted, hand transport and hand aperture in RTG movements beyond the reach of the arm were halted by trunk arrests only if they were prolonged beyond the time of peak hand velocity. Hand motion and aperture changes resumed only when the trunk was released. While supporting the minimization hypothesis, our findings imply that not only spatial but also temporal characteristics of each component, including the shortest, hand closure component of RTG movements, are controlled in a flexible, task-specific way.

Characterization and prediction of carbon steel corrosion in diluted seawater containing pentaborate

NASA Astrophysics Data System (ADS)

Fukaya, Yuichi; Watanabe, Yutaka

2018-01-01

This study addresses the influence of Na2B10O16, which may be used for criticality control of fuel debris in the Fukushima Daiichi Nuclear Power Station, on the corrosion behavior of carbon steel in diluted artificial seawater. The corrosion forms of carbon steel were categorized as uniform corrosion, localized corrosion, and passivity based on the balance between the dilution ratio of artificial seawater and the concentration of Na2B10O16. The changes in corrosion forms were arranged on a water quality region map. Passivity was maintained by adding 3.7 × 10-2 M or more of Na2B10O16 to artificial seawater with a dilution ratio of 100-fold or more. The criticality control of the fuel debris and corrosion mitigation of the carbon steel components may be achieved simultaneously in the water quality. The prediction of the corrosion form of carbon steel was attempted by the extended Larson-Skold Index (LSI) = ([Cl-] + 2[SO42-])/([HCO3-] + 2[B10O162-]). However, because the passivating action of B10O162- was remarkably stronger than that of HCO3-, the prediction was difficult under the simple addition of equivalent concentrations. The localized corrosion of carbon steel under the addition of Na2B10O16 preferentially occurred from the crevices of the test specimens, as was the case in stainless steel.

Critical Characteristics of Radiation Detection System Components to be Dedicated for use in Safety Class and Safety Significant System

DOE Office of Scientific and Technical Information (OSTI.GOV)

DAVIS, S.J.

2000-05-25

This document identifies critical characteristics of components to be dedicated for use in Safety Class (SC) or Safety Significant (SS) Systems, Structures, or Components (SSCs). This document identifies the requirements for the components of the common radiation area monitor alarm in the WESF pool cell. These are procured as Commercial Grade Items (CGI), with the qualification testing and formal dedication to be performed at the Waste Encapsulation Storage Facility (WESF), in safety class, safety significant systems. System modifications are to be performed in accordance with the instructions provided on ECN 658230. Components for this change are commercially available and interchangeablemore » with the existing alarm configuration This document focuses on the operational requirements for alarm, declaration of the safety classification, identification of critical characteristics, and interpretation of requirements for procurement. Critical characteristics are identified herein and must be verified, followed by formal dedication, prior to the components being used in safety related applications.« less

Critical Characteristics of Radiation Detection System Components to be Dedicated for use in Safety Class and Safety Significant System

DOE Office of Scientific and Technical Information (OSTI.GOV)

DAVIS, S.J.

2000-12-28

This document identifies critical characteristics of components to be dedicated for use in Safety Significant (SS) Systems, Structures, or Components (SSCs). This document identifies the requirements for the components of the common, radiation area, monitor alarm in the WESF pool cell. These are procured as Commercial Grade Items (CGI), with the qualification testing and formal dedication to be performed at the Waste Encapsulation Storage Facility (WESF) for use in safety significant systems. System modifications are to be performed in accordance with the approved design. Components for this change are commercially available and interchangeable with the existing alarm configuration This documentmore » focuses on the operational requirements for alarm, declaration of the safety classification, identification of critical characteristics, and interpretation of requirements for procurement. Critical characteristics are identified herein and must be verified, followed by formal dedication, prior to the components being used in safety related applications.« less

Estimating Single-Trial Responses in EEG

NASA Technical Reports Server (NTRS)

Shah, A. S.; Knuth, K. H.; Truccolo, W. A.; Mehta, A. D.; Fu, K. G.; Johnston, T. A.; Ding, M.; Bressler, S. L.; Schroeder, C. E.; Clancy, Daniel (Technical Monitor)

2002-01-01

Accurate characterization of single-trial field potential responses is critical from a number of perspectives. For example, it allows differentiation of an evoked response from ongoing EEG. We previously developed the multiple component Event Related Potential (mcERP) algorithm to improve resolution of the single-trial evoked response. The mcERP model states that multiple components, each specified by a stereotypic waveform varying in latency and amplitude from trial to trial, comprise the evoked response. Application of the mcERP algorithm to simulated data with three independent, synthetic components has shown that the model is capable of separating these components and estimating their variability. Application of the model to single trial, visual evoked potentials recorded simultaneously from all V1 laminae in an awake, fixating macaque yielded local and far-field components. Certain local components estimated by the model were distributed in both granular and supragranular laminae. This suggests a linear coupling between the responses of thalamo-recipient neuronal ensembles and subsequent responses of supragranular neuronal ensembles, as predicted by the feedforward anatomy of V1. Our results indicate that the mcERP algorithm provides a valid estimation of single-trial responses. This will enable analyses that depend on trial-to-trial variations and those that require separation of the evoked response from background EEG rhythms

Fracture Analysis of Semi-Elliptical Surface Cracks in Ductile Materials

NASA Technical Reports Server (NTRS)

Daniewicz, S. R.; Newman, J. C., Jr.; Leach, A. M.

2004-01-01

Accurate life assessment of structural components may require advanced life prediction criteria and methodologies. Structural components often exhibit several different types of defects, among the most prevalent being surface cracks. A semi-elliptical surface crack subjected to monotonic loading will exhibit stable crack growth until the crack has reached a critical size, at which the crack loses stability and fracture ensues (Newman, 2000). The shape and geometry of the flaw are among the most influential factors. When considering simpler crack configurations, such as a through-the-thickness crack, a three-dimensional (3D) geometry may be modeled under the approximation of two-dimensional (2D) plane stress or plane strain. The more complex surface crack is typically modeled numerically with the Finite Element Method (FEM). A semi-elliptical surface crack is illustrated in Figure 1-1.

Direct comparison of the hygroscopic properties of ammonium sulfate and sodium chloride aerosol at relative humidities approaching saturation.

PubMed

Walker, Jim S; Wills, Jon B; Reid, Jonathan P; Wang, Liangyu; Topping, David O; Butler, Jason R; Zhang, Yun-Hong

2010-12-09

Holographic optical tweezers are used to make comparative measurements of the hygroscopic properties of single component aqueous aerosol containing sodium chloride and ammonium sulfate over a range of relative humidity from 84% to 96%. The change in RH over the course of the experiment is monitored precisely using a sodium chloride probe droplet with accuracy better than ±0.09%. The measurements are used to assess the accuracy of thermodynamic treatments of the relationship between water activity and solute mass fraction with particular attention focused on the dilute solute limit approaching saturation vapor pressure. The consistency of the frequently used Clegg-Brimblecombe-Wexler (CBW) treatment for predicting the hygroscopic properties of sodium chloride and ammonium sulfate aerosol is confirmed. Measurements of the equilibrium size of ammonium sulfate aerosol are found to agree with predictions to within an uncertainty of ±0.2%. Given the accuracy of treating equilibrium composition, the inconsistencies highlighted in recent calibration measurements of critical supersaturations of sodium chloride and ammonium sulfate aerosol cannot be attributed to uncertainties associated with the thermodynamic predictions and must have an alternative origin. It is concluded that the CBW treatment can allow the critical supersaturation to be estimated for sodium chloride and ammonium sulfate aerosol with an accuracy of better than ±0.002% in RH. This corresponds to an uncertainty of ≤1% in the critical supersaturation for typical supersaturations of 0.2% and above. This supports the view that these systems can be used to accurately calibrate instruments that measure cloud condensation nuclei concentrations at selected supersaturations. These measurements represent the first study in which the equilibrium properties of two particles of chemically distinct composition have been compared simultaneously and directly alongside each other in the same environment.

Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gutowski, William J.

This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASMmore » can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes in the freshwater flux between arctic climate system components resulting from decadal changes in land and sea ice, seasonal snow, vegetation, and ocean circulation. - Changing energetics due to decadal changes in ice mass, vegetation, and air-sea interactions. - The role of small-scale atmospheric and oceanic processes that influence decadal variability. This research has been addressing modes of natural climate variability as well as extreme and rapid climate change. RASM can facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts.« less

Computational analysis on plug-in hybrid electric motorcycle chassis

NASA Astrophysics Data System (ADS)

Teoh, S. J.; Bakar, R. A.; Gan, L. M.

2013-12-01

Plug-in hybrid electric motorcycle (PHEM) is an alternative to promote sustainability lower emissions. However, the PHEM overall system packaging is constrained by limited space in a motorcycle chassis. In this paper, a chassis applying the concept of a Chopper is analysed to apply in PHEM. The chassis 3dimensional (3D) modelling is built with CAD software. The PHEM power-train components and drive-train mechanisms are intergraded into the 3D modelling to ensure the chassis provides sufficient space. Besides that, a human dummy model is built into the 3D modelling to ensure the rider?s ergonomics and comfort. The chassis 3D model then undergoes stress-strain simulation. The simulation predicts the stress distribution, displacement and factor of safety (FOS). The data are used to identify the critical point, thus suggesting the chassis design is applicable or need to redesign/ modify to meet the require strength. Critical points mean highest stress which might cause the chassis to fail. This point occurs at the joints at triple tree and bracket rear absorber for a motorcycle chassis. As a conclusion, computational analysis predicts the stress distribution and guideline to develop a safe prototype chassis.

Evaluation of habitat quality for selected wildlife species associated with back channels.

USGS Publications Warehouse

Anderson, James T.; Zadnik, Andrew K.; Wood, Petra Bohall; Bledsoe, Kerry

2013-01-01

The islands and associated back channels on the Ohio River, USA, are believed to provide critical habitat features for several wildlife species. However, few studies have quantitatively evaluated habitat quality in these areas. Our main objective was to evaluate the habitat quality of back and main channel areas for several species using habitat suitability index (HSI) models. To test the effectiveness of these models, we attempted to relate HSI scores and the variables measured for each model with measures of relative abundance for the model species. The mean belted kingfisher (Ceryle alcyon) HSI was greater on the main than back channel. However, the model failed to predict kingfisher abundance. The mean reproduction component of the great blue heron (Ardea herodias) HSI, total common muskrat (Ondatra zibethicus) HSI, winter cover component of the snapping turtle (Chelydra serpentina) HSI, and brood-rearing component of the wood duck (Aix sponsa) HSI were all greater on the back than main channel, and were positively related with the relative abundance of each species. We found that island back channels provide characteristics not found elsewhere on the Ohio River and warrant conservation as important riparian wildlife habitat. The effectiveness of using HSI models to predict species abundance on the river was mixed. Modifications to several of the models are needed to improve their use on the Ohio River and, likely, other large rivers.

A risk-based approach to management of leachables utilizing statistical analysis of extractables.

PubMed

Stults, Cheryl L M; Mikl, Jaromir; Whelehan, Oliver; Morrical, Bradley; Duffield, William; Nagao, Lee M

2015-04-01

To incorporate quality by design concepts into the management of leachables, an emphasis is often put on understanding the extractable profile for the materials of construction for manufacturing disposables, container-closure, or delivery systems. Component manufacturing processes may also impact the extractable profile. An approach was developed to (1) identify critical components that may be sources of leachables, (2) enable an understanding of manufacturing process factors that affect extractable profiles, (3) determine if quantitative models can be developed that predict the effect of those key factors, and (4) evaluate the practical impact of the key factors on the product. A risk evaluation for an inhalation product identified injection molding as a key process. Designed experiments were performed to evaluate the impact of molding process parameters on the extractable profile from an ABS inhaler component. Statistical analysis of the resulting GC chromatographic profiles identified processing factors that were correlated with peak levels in the extractable profiles. The combination of statistically significant molding process parameters was different for different types of extractable compounds. ANOVA models were used to obtain optimal process settings and predict extractable levels for a selected number of compounds. The proposed paradigm may be applied to evaluate the impact of material composition and processing parameters on extractable profiles and utilized to manage product leachables early in the development process and throughout the product lifecycle.

Unconventional critical state in YBa2Cu3O7-δ thin films with a vortex-pin lattice fabricated by masked He+ ion beam irradiation

NASA Astrophysics Data System (ADS)

Zechner, G.; Mletschnig, K. L.; Lang, W.; Dosmailov, M.; Bodea, M. A.; Pedarnig, J. D.

2018-04-01

Thin superconducting YBa2Cu3O7-δ films are patterned with a vortex-pin lattice consisting of columnar defect regions (CDs) with 180 nm diameter and 300 nm spacing. They are fabricated by irradiation with 75 keV He+ ions through a stencil mask. Peaks of the critical current reveal the commensurate trapping of vortices in domains near the edges of the sample. Upon ramping an external magnetic field, the positions of the critical current peaks are shifted from their equilibrium values to lower magnetic fields in virgin and to higher fields in field-saturated down-sweep curves, respectively. Based on previous theoretical predictions, this irreversibility is interpreted as a nonuniform, terrace-like critical state, in which individual domains are occupied by a constant number of vortices per pinning site. The magnetoresistance, probed at low current densities, is hysteretic and angle dependent and exhibits minima that correspond to the peaks of the critical current. The minima’s positions scale with the component of the magnetic field parallel to the axes of the CDs, as long as the tilted vortices can be accommodated within the CDs. This behavior, different from unirradiated films, confirms that the CDs dominate the pinning.

Learning-Related Translocation of δ-Opioid Receptors on Ventral Striatal Cholinergic Interneurons Mediates Choice between Goal-Directed Actions

PubMed Central

Bertran-Gonzalez, Jesus; Laurent, Vincent; Chieng, Billy C.; Christie, MacDonald J.

2013-01-01

The ability of animals to extract predictive information from the environment to inform their future actions is a critical component of decision-making. This phenomenon is studied in the laboratory using the pavlovian–instrumental transfer protocol in which a stimulus predicting a specific pavlovian outcome biases choice toward those actions earning the predicted outcome. It is well established that this transfer effect is mediated by corticolimbic afferents on the nucleus accumbens shell (NAc-S), and recent evidence suggests that δ-opioid receptors (DORs) play an essential role in this effect. In DOR-eGFP knock-in mice, we show a persistent, learning-related plasticity in the translocation of DORs to the somatic plasma membrane of cholinergic interneurons (CINs) in the NAc-S during the encoding of the specific stimulus–outcome associations essential for pavlovian–instrumental transfer. We found that increased membrane DOR expression reflected both stimulus-based predictions of reward and the degree to which these stimuli biased choice during the pavlovian–instrumental transfer test. Furthermore, this plasticity altered the firing pattern of CINs increasing the variance of action potential activity, an effect that was exaggerated by DOR stimulation. The relationship between the induction of membrane DOR expression in CINs and both pavlovian conditioning and pavlovian–instrumental transfer provides a highly specific function for DOR-related modulation in the NAc-S, and it is consistent with an emerging role for striatal CIN activity in the processing of predictive information. Therefore, our results reveal evidence of a long-term, experience-dependent plasticity in opioid receptor expression on striatal modulatory interneurons critical for the cognitive control of action. PMID:24107940

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitchell, Hugh D.; Eisfeld, Amie J.; Sims, Amy

Respiratory infections stemming from influenza viruses and the Severe Acute Respiratory Syndrome corona virus (SARS-CoV) represent a serious public health threat as emerging pandemics. Despite efforts to identify the critical interactions of these viruses with host machinery, the key regulatory events that lead to disease pathology remain poorly targeted with therapeutics. Here we implement an integrated network interrogation approach, in which proteome and transcriptome datasets from infection of both viruses in human lung epithelial cells are utilized to predict regulatory genes involved in the host response. We take advantage of a novel “crowd-based” approach to identify and combine ranking metricsmore » that isolate genes/proteins likely related to the pathogenicity of SARS-CoV and influenza virus. Subsequently, a multivariate regression model is used to compare predicted lung epithelial regulatory influences with data derived from other respiratory virus infection models. We predicted a small set of regulatory factors with conserved behavior for consideration as important components of viral pathogenesis that might also serve as therapeutic targets for intervention. Our results demonstrate the utility of integrating diverse ‘omic datasets to predict and prioritize regulatory features conserved across multiple pathogen infection models.« less

AST Launch Vehicle Acoustics

NASA Technical Reports Server (NTRS)

Houston, Janice; Counter, D.; Giacomoni, D.

2015-01-01

The liftoff phase induces acoustic loading over a broad frequency range for a launch vehicle. These external acoustic environments are then used in the prediction of internal vibration responses of the vehicle and components which result in the qualification levels. Thus, predicting these liftoff acoustic (LOA) environments is critical to the design requirements of any launch vehicle. If there is a significant amount of uncertainty in the predictions or if acoustic mitigation options must be implemented, a subscale acoustic test is a feasible pre-launch test option to verify the LOA environments. The NASA Space Launch System (SLS) program initiated the Scale Model Acoustic Test (SMAT) to verify the predicted SLS LOA environments and to determine the acoustic reduction with an above deck water sound suppression system. The SMAT was conducted at Marshall Space Flight Center and the test article included a 5% scale SLS vehicle model, tower and Mobile Launcher. Acoustic and pressure data were measured by approximately 250 instruments. The SMAT liftoff acoustic results are presented, findings are discussed and a comparison is shown to the Ares I Scale Model Acoustic Test (ASMAT) results.

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

NASA Technical Reports Server (NTRS)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Next-Gen Gene Synthesis Enables Large-Scale Engineering in Biological Systems: Recent advances in synthetic biology are making this field more promising than ever.

PubMed

Leake, Devin

2015-01-01

As scientists make strides toward the goal of developing a form of biological engineering that's as predictive and reliable as chemical engineering is for chemistry, one technology component has become absolutely critical: gene synthesis. Gene synthesis is the process of building stretches of deoxyribonucleic acid (DNA) to order--some stretches based on DNA that exists already in nature, some based on novel designs intended to accomplish new functions. This process is the foundation of synthetic biology, which is rapidly becoming the engineering counterpart to biology.

EEG potentials predict upcoming emergency brakings during simulated driving

NASA Astrophysics Data System (ADS)

Haufe, Stefan; Treder, Matthias S.; Gugler, Manfred F.; Sagebaum, Max; Curio, Gabriel; Blankertz, Benjamin

2011-10-01

Emergency braking assistance has the potential to prevent a large number of car crashes. State-of-the-art systems operate in two stages. Basic safety measures are adopted once external sensors indicate a potential upcoming crash. If further activity at the brake pedal is detected, the system automatically performs emergency braking. Here, we present the results of a driving simulator study indicating that the driver's intention to perform emergency braking can be detected based on muscle activation and cerebral activity prior to the behavioural response. Identical levels of predictive accuracy were attained using electroencephalography (EEG), which worked more quickly than electromyography (EMG), and using EMG, which worked more quickly than pedal dynamics. A simulated assistance system using EEG and EMG was found to detect emergency brakings 130 ms earlier than a system relying only on pedal responses. At 100 km h-1 driving speed, this amounts to reducing the braking distance by 3.66 m. This result motivates a neuroergonomic approach to driving assistance. Our EEG analysis yielded a characteristic event-related potential signature that comprised components related to the sensory registration of a critical traffic situation, mental evaluation of the sensory percept and motor preparation. While all these components should occur often during normal driving, we conjecture that it is their characteristic spatio-temporal superposition in emergency braking situations that leads to the considerable prediction performance we observed.

EEG potentials predict upcoming emergency brakings during simulated driving.

PubMed

Haufe, Stefan; Treder, Matthias S; Gugler, Manfred F; Sagebaum, Max; Curio, Gabriel; Blankertz, Benjamin

2011-10-01

Emergency braking assistance has the potential to prevent a large number of car crashes. State-of-the-art systems operate in two stages. Basic safety measures are adopted once external sensors indicate a potential upcoming crash. If further activity at the brake pedal is detected, the system automatically performs emergency braking. Here, we present the results of a driving simulator study indicating that the driver's intention to perform emergency braking can be detected based on muscle activation and cerebral activity prior to the behavioural response. Identical levels of predictive accuracy were attained using electroencephalography (EEG), which worked more quickly than electromyography (EMG), and using EMG, which worked more quickly than pedal dynamics. A simulated assistance system using EEG and EMG was found to detect emergency brakings 130 ms earlier than a system relying only on pedal responses. At 100 km h(-1) driving speed, this amounts to reducing the braking distance by 3.66 m. This result motivates a neuroergonomic approach to driving assistance. Our EEG analysis yielded a characteristic event-related potential signature that comprised components related to the sensory registration of a critical traffic situation, mental evaluation of the sensory percept and motor preparation. While all these components should occur often during normal driving, we conjecture that it is their characteristic spatio-temporal superposition in emergency braking situations that leads to the considerable prediction performance we observed.

Taste characteristics based quantitative and qualitative evaluation of ginseng adulteration.

PubMed

Cui, Shaoqing; Yang, Liangcheng; Wang, Jun; Wang, Xinlei

2015-05-01

Adulteration of American ginseng with Asian ginseng is common and has caused much damage to customers. Panel evaluation is commonly used to determine their differences, but it is subjective. Chemical instruments are used to identify critical compounds but they are time-consuming and expensive. Therefore, a fast, accurate and convenient method is required. A taste sensing system, combining both advantages of the above two technologies, provides a novel potential technology for determining ginseng adulteration. The aim is to build appropriate models to distinguish and predict ginseng adulteration by using taste characteristics. It was found that ginsenoside contents decreased linearly (R(2) = 0.92) with mixed ratios. A bioplot of principal component analysis showed a good performance in classing samples with the first two principal components reaching 89.7%, and it was noted that it was the bitterness, astringency, aftertaste of bitterness and astringency, and saltiness leading the successful determination. After factor screening, bitterness, astringency, aftertaste of bitterness and saltiness were employed to build latent models. Tastes of bitterness, astringency and aftertaste bitterness were demonstrated to be most effective in predicting adulteration ratio, mean while, bitterness and aftertaste bitterness turned out to be most effective in ginsenoside content prediction. Taste characteristics of adulterated ginsengs, considered as taste fingerprint, can provide novel guidance for determining the adulteration of American and Asian ginseng. © 2014 Society of Chemical Industry.

The role of the default mode network in component processes underlying the wandering mind

PubMed Central

Sormaz, Mladen; Wang, Hao-Ting; Margulies, Daniel; Jefferies, Elizabeth; Smallwood, Jonathan

2017-01-01

Abstract Experiences such as mind-wandering illustrate that cognition is not always tethered to events in the here-and-now. Although converging evidence emphasises the default mode network (DMN) in mind-wandering, its precise contribution remains unclear. The DMN comprises cortical regions that are maximally distant from primary sensory and motor cortex, a topological location that may support the stimulus-independence of mind-wandering. The DMN is functionally heterogeneous, comprising regions engaged by memory, social cognition and planning; processes relevant to mind-wandering content. Our study examined the relationships between: (i) individual differences in resting-state DMN connectivity, (ii) performance on memory, social and planning tasks and (iii) variability in spontaneous thought, to investigate whether the DMN is critical to mind-wandering because it supports stimulus-independent cognition, memory retrieval, or both. Individual variation in task performance modulated the functional organization of the DMN: poor external engagement was linked to stronger coupling between medial and dorsal subsystems, while decoupling of the core from the cerebellum predicted reports of detailed memory retrieval. Both patterns predicted off-task future thoughts. Consistent with predictions from component process accounts of mind-wandering, our study suggests a 2-fold involvement of the DMN: (i) it supports experiences that are unrelated to the environment through strong coupling between its sub-systems; (ii) it allows memory representations to form the basis of conscious experience. PMID:28402561

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

DOE PAGES

Mach, J. C.; Budrow, C. J.; Pagan, D. C.; ...

2017-03-15

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present paper, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to developmore » significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.« less

Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits

PubMed Central

Wolpe, Noham; Ingram, James N.; Tsvetanov, Kamen A.; Geerligs, Linda; Kievit, Rogier A.; Henson, Richard N.; Wolpert, Daniel M.; Tyler, Lorraine K.; Brayne, Carol; Bullmore, Edward; Calder, Andrew; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Matthews, Fiona E.; Marslen-Wilson, William; Shafto, Meredith A.; Campbell, Karen; Cheung, Teresa; Davis, Simon; McCarrey, Anna; Mustafa, Abdur; Price, Darren; Samu, David; Taylor, Jason R.; Treder, Matthias; van Belle, Janna; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Henriques, Rafael; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Barnes, Dan; Dixon, Marie; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Rowe, James B.

2016-01-01

The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation—a reduction in the perceived intensity of sensations from self-generated compared with external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18–88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age. PMID:27694879

Validating a Model for Welding Induced Residual Stress Using High-Energy X-ray Diffraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mach, J. C.; Budrow, C. J.; Pagan, D. C.

Integrated computational materials engineering (ICME) provides a pathway to advance performance in structures through the use of physically-based models to better understand how manufacturing processes influence product performance. As one particular challenge, consider that residual stresses induced in fabrication are pervasive and directly impact the life of structures. For ICME to be an effective strategy, it is essential that predictive capability be developed in conjunction with critical experiments. In the present paper, simulation results from a multi-physics model for gas metal arc welding are evaluated through x-ray diffraction using synchrotron radiation. A test component was designed with intent to developmore » significant gradients in residual stress, be representative of real-world engineering application, yet remain tractable for finely spaced strain measurements with positioning equipment available at synchrotron facilities. Finally, the experimental validation lends confidence to model predictions, facilitating the explicit consideration of residual stress distribution in prediction of fatigue life.« less

Social learning through prediction error in the brain

NASA Astrophysics Data System (ADS)

Joiner, Jessica; Piva, Matthew; Turrin, Courtney; Chang, Steve W. C.

2017-06-01

Learning about the world is critical to survival and success. In social animals, learning about others is a necessary component of navigating the social world, ultimately contributing to increasing evolutionary fitness. How humans and nonhuman animals represent the internal states and experiences of others has long been a subject of intense interest in the developmental psychology tradition, and, more recently, in studies of learning and decision making involving self and other. In this review, we explore how psychology conceptualizes the process of representing others, and how neuroscience has uncovered correlates of reinforcement learning signals to explore the neural mechanisms underlying social learning from the perspective of representing reward-related information about self and other. In particular, we discuss self-referenced and other-referenced types of reward prediction errors across multiple brain structures that effectively allow reinforcement learning algorithms to mediate social learning. Prediction-based computational principles in the brain may be strikingly conserved between self-referenced and other-referenced information.

Ageing increases reliance on sensorimotor prediction through structural and functional differences in frontostriatal circuits.

PubMed

Wolpe, Noham; Ingram, James N; Tsvetanov, Kamen A; Geerligs, Linda; Kievit, Rogier A; Henson, Richard N; Wolpert, Daniel M; Rowe, James B

2016-10-03

The control of voluntary movement changes markedly with age. A critical component of motor control is the integration of sensory information with predictions of the consequences of action, arising from internal models of movement. This leads to sensorimotor attenuation-a reduction in the perceived intensity of sensations from self-generated compared with external actions. Here we show that sensorimotor attenuation occurs in 98% of adults in a population-based cohort (n=325; 18-88 years; the Cambridge Centre for Ageing and Neuroscience). Importantly, attenuation increases with age, in proportion to reduced sensory sensitivity. This effect is associated with differences in the structure and functional connectivity of the pre-supplementary motor area (pre-SMA), assessed with magnetic resonance imaging. The results suggest that ageing alters the balance between the sensorium and predictive models, mediated by the pre-SMA and its connectivity in frontostriatal circuits. This shift may contribute to the motor and cognitive changes observed with age.

External validation of a simple clinical tool used to predict falls in people with Parkinson disease

PubMed Central

Duncan, Ryan P.; Cavanaugh, James T.; Earhart, Gammon M.; Ellis, Terry D.; Ford, Matthew P.; Foreman, K. Bo; Leddy, Abigail L.; Paul, Serene S.; Canning, Colleen G.; Thackeray, Anne; Dibble, Leland E.

2015-01-01

Background Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. METHODS We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. RESULTS The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76 –0.89), comparable to the developmental study. CONCLUSION The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual’s risk of an impending fall. PMID:26003412

External validation of a simple clinical tool used to predict falls in people with Parkinson disease.

PubMed

Duncan, Ryan P; Cavanaugh, James T; Earhart, Gammon M; Ellis, Terry D; Ford, Matthew P; Foreman, K Bo; Leddy, Abigail L; Paul, Serene S; Canning, Colleen G; Thackeray, Anne; Dibble, Leland E

2015-08-01

Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76-0.89), comparable to the developmental study. The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual's risk of an impending fall. Copyright © 2015 Elsevier Ltd. All rights reserved.

Combined Molecular Dynamics Simulation-Molecular-Thermodynamic Theory Framework for Predicting Surface Tensions.

PubMed

Sresht, Vishnu; Lewandowski, Eric P; Blankschtein, Daniel; Jusufi, Arben

2017-08-22

A molecular modeling approach is presented with a focus on quantitative predictions of the surface tension of aqueous surfactant solutions. The approach combines classical Molecular Dynamics (MD) simulations with a molecular-thermodynamic theory (MTT) [ Y. J. Nikas, S. Puvvada, D. Blankschtein, Langmuir 1992 , 8 , 2680 ]. The MD component is used to calculate thermodynamic and molecular parameters that are needed in the MTT model to determine the surface tension isotherm. The MD/MTT approach provides the important link between the surfactant bulk concentration, the experimental control parameter, and the surfactant surface concentration, the MD control parameter. We demonstrate the capability of the MD/MTT modeling approach on nonionic alkyl polyethylene glycol surfactants at the air-water interface and observe reasonable agreement of the predicted surface tensions and the experimental surface tension data over a wide range of surfactant concentrations below the critical micelle concentration. Our modeling approach can be extended to ionic surfactants and their mixtures with both ionic and nonionic surfactants at liquid-liquid interfaces.

Predicting remaining life by fusing the physics of failure modeling with diagnostics

NASA Astrophysics Data System (ADS)

Kacprzynski, G. J.; Sarlashkar, A.; Roemer, M. J.; Hess, A.; Hardman, B.

2004-03-01

Technology that enables failure prediction of critical machine components (prognostics) has the potential to significantly reduce maintenance costs and increase availability and safety. This article summarizes a research effort funded through the U.S. Defense Advanced Research Projects Agency and Naval Air System Command aimed at enhancing prognostic accuracy through more advanced physics-of-failure modeling and intelligent utilization of relevant diagnostic information. H-60 helicopter gear is used as a case study to introduce both stochastic sub-zone crack initiation and three-dimensional fracture mechanics lifing models along with adaptive model updating techniques for tuning key failure mode variables at a local material/damage site based on fused vibration features. The overall prognostic scheme is aimed at minimizing inherent modeling and operational uncertainties via sensed system measurements that evolve as damage progresses.

Advanced Ceramic Matrix Composites (CMCs) for High Temperature Applications

NASA Technical Reports Server (NTRS)

Singh, M.

2005-01-01

Advanced ceramic matrix composites (CMCs) are enabling materials for a number of demanding applications in aerospace, energy, and nuclear industries. In the aerospace systems, these materials are being considered for applications in hot sections of jet engines such as the combustor liner, vanes, nozzle components, nose cones, leading edges of reentry vehicles, and space propulsion components. Applications in the energy and environmental industries include radiant heater tubes, heat exchangers, heat recuperators, gas and diesel particulate filters, and components for land based turbines for power generation. These materials are also being considered for use in the first wall and blanket components of fusion reactors. In the last few years, a number of CMC components have been developed and successfully tested for various aerospace and ground based applications. However, a number of challenges still remain slowing the wide scale implementation of these materials. They include robust fabrication and manufacturing, assembly and integration, coatings, property modeling and life prediction, design codes and databases, repair and refurbishment, and cost. Fabrication of net and complex shape components with high density and tailorable matrix properties is quite expensive, and even then various desirable properties are not achievable. In this presentation, a number of examples of successful CMC component development and testing will be provided. In addition, critical need for robust manufacturing, joining and assembly technologies in successful implementation of these systems will be discussed.

Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tippett, Michael K.

2014-04-09

This report is a progress report of the accomplishments of the research grant “Collaborative Research: Separating Forced and Unforced Decadal Predictability in Models and Observa- tions” during the period 1 May 2011- 31 August 2013. This project is a collaborative one between Columbia University and George Mason University. George Mason University will submit a final technical report at the conclusion of their no-cost extension. The purpose of the proposed research is to identify unforced predictable components on decadal time scales, distinguish these components from forced predictable components, and to assess the reliability of model predictions of these components. Components ofmore » unforced decadal predictability will be isolated by maximizing the Average Predictability Time (APT) in long, multimodel control runs from state-of-the-art climate models. Components with decadal predictability have large APT, so maximizing APT ensures that components with decadal predictability will be detected. Optimal fingerprinting techniques, as used in detection and attribution analysis, will be used to separate variations due to natural and anthropogenic forcing from those due to unforced decadal predictability. This methodology will be applied to the decadal hindcasts generated by the CMIP5 project to assess the reliability of model projections. The question of whether anthropogenic forcing changes decadal predictability, or gives rise to new forms of decadal predictability, also will be investigated.« less

MCTBI: a web server for predicting metal ion effects in RNA structures.

PubMed

Sun, Li-Zhen; Zhang, Jing-Xiang; Chen, Shi-Jie

2017-08-01

Metal ions play critical roles in RNA structure and function. However, web servers and software packages for predicting ion effects in RNA structures are notably scarce. Furthermore, the existing web servers and software packages mainly neglect ion correlation and fluctuation effects, which are potentially important for RNAs. We here report a new web server, the MCTBI server (http://rna.physics.missouri.edu/MCTBI), for the prediction of ion effects for RNA structures. This server is based on the recently developed MCTBI, a model that can account for ion correlation and fluctuation effects for nucleic acid structures and can provide improved predictions for the effects of metal ions, especially for multivalent ions such as Mg 2+ effects, as shown by extensive theory-experiment test results. The MCTBI web server predicts metal ion binding fractions, the most probable bound ion distribution, the electrostatic free energy of the system, and the free energy components. The results provide mechanistic insights into the role of metal ions in RNA structure formation and folding stability, which is important for understanding RNA functions and the rational design of RNA structures. © 2017 Sun et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Research on criticality analysis method of CNC machine tools components under fault rate correlation

NASA Astrophysics Data System (ADS)

Gui-xiang, Shen; Xian-zhuo, Zhao; Zhang, Ying-zhi; Chen-yu, Han

2018-02-01

In order to determine the key components of CNC machine tools under fault rate correlation, a system component criticality analysis method is proposed. Based on the fault mechanism analysis, the component fault relation is determined, and the adjacency matrix is introduced to describe it. Then, the fault structure relation is hierarchical by using the interpretive structure model (ISM). Assuming that the impact of the fault obeys the Markov process, the fault association matrix is described and transformed, and the Pagerank algorithm is used to determine the relative influence values, combined component fault rate under time correlation can obtain comprehensive fault rate. Based on the fault mode frequency and fault influence, the criticality of the components under the fault rate correlation is determined, and the key components are determined to provide the correct basis for equationting the reliability assurance measures. Finally, taking machining centers as an example, the effectiveness of the method is verified.

Contribution of the Peroxisomal acox Gene to the Dynamic Balance of Daumone Production in Caenorhabditis elegans*

PubMed Central

Joo, Hyoe-Jin; Kim, Kwang-Youl; Yim, Yong-Hyeon; Jin, You-Xun; Kim, Heekyeong; Kim, Mun-Young; Paik, Young-Ki

2010-01-01

Dauer pheromones or daumones, which are signaling molecules that interrupt development and reproduction (dauer larvae) during unfavorable growth conditions, are essential for cellular homeostasis in Caenorhabditis elegans. According to earlier studies, dauer larva formation in strain N2 is enhanced by a temperature increase, suggesting the involvement of a temperature-dependent component in dauer pheromone biosynthesis or sensing. Several naturally occurring daumone analogs (e.g. daumones 1–3) have been identified, and these molecules are predicted to be synthesized in different physiological settings in this nematode. To elucidate the molecular regulatory system that may influence the dynamic balance of specific daumone production in response to sudden temperature changes, we characterized the peroxisomal acox gene encoding acyl-CoA oxidase, which is predicted to catalyze the first reaction during biosynthesis of the fatty acid component of daumones. Using acox-1(ok2257) mutants and a new, robust analytical method, we quantified the three most abundant daumones in worm bodies and showed that acox likely contributes to the dynamic production of various quantities of three different daumones in response to temperature increase, changes that are critical in C. elegans for coping with the natural environmental changes it faces. PMID:20610393

Pursuing Improvement in Clinical Reasoning: The Integrated Clinical Education Theory.

PubMed

Jessee, Mary Ann

2018-01-01

The link between clinical education and development of clinical reasoning is not well supported by one theoretical perspective. Learning to reason during clinical education may be best achieved in a supportive sociocultural context of nursing practice that maximizes reasoning opportunities and facilitates discourse and meaningful feedback. Prelicensure clinical education seldom incorporates these critical components and thus may fail to directly promote clinical reasoning skill. Theoretical frameworks supporting the development of clinical reasoning during clinical education were evaluated. Analysis of strengths and gaps in each framework's support of clinical reasoning development was conducted. Commensurability of philosophical underpinnings was confirmed, and complex relationships among key concepts were elucidated. Six key concepts and three tenets comprise an explanatory predictive theory-the integrated clinical education theory (ICET). ICET provides critical theoretical support for inquiry and action to promote clinical education that improves development of clinical reasoning skill. [J Nurs Educ. 2018;57(1):7-13.]. Copyright 2018, SLACK Incorporated.

Propagation velocity of Alfven wave packets in a dissipative plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amagishi, Y.; Nakagawa, H.; Tanaka, M.

1994-09-01

We have experimentally studied the behavior of Alfven wave packets in a dissipative plasma due to ion--neutral-atom collisions. It is urged that the central frequency of the packet is observed to gradually decrease with traveling distance in the absorption range of frequencies because of a differential damping among the Fourier components, and that the measured average velocity of its peak amplitude is not accounted for by the conventional group velocity, but by the prediction derived by Tanaka, Fujiwara, and Ikegami [Phys. Rev. A 34, 4851 (1986)]. Furthermore, when the initial central frequency is close to the critical frequency in themore » anomalous dispersion, the wave packet apparently collapses when traveling along the magnetic field; however, we have found that it is decomposed into another two wave packets with the central frequencies being higher or lower than the critical frequency.« less

Propagation velocity of Alfvén wave packets in a dissipative plasma

NASA Astrophysics Data System (ADS)

Amagishi, Yoshimitsu; Nakagawa, Hiroyuki; Tanaka, Masayoshi

1994-09-01

We have experimentally studied the behavior of Alfvén wave packets in a dissipative plasma due to ion-neutral-atom collisions. It is urged that the central frequency of the packet is observed to gradually decrease with traveling distance in the absorption range of frequencies because of a differential damping among the Fourier components, and that the measured average velocity of its peak amplitude is not accounted for by the conventional group velocity, but by the prediction derived by Tanaka, Fujiwara, and Ikegami [Phys. Rev. A 34, 4851 (1986)]. Furthermore, when the initial central frequency is close to the critical frequency in the anomalous dispersion, the wave packet apparently collapses when traveling along the magnetic field; however, we have found that it is decomposed into another two wave packets with the central frequencies being higher or lower than the critical frequency.

Interactions in the Dark Sector of Cosmology

NASA Astrophysics Data System (ADS)

Bean, Rachel

The success of modern cosmology hinges on two dramatic augmentations beyond the minimalist assumption of baryonic matter interacting gravitationally through general relativity. The first assumption is that there must exist either new gravitational dynamics or a new component of the cosmic energy budget - dark matter - that allows structure to form and accounts for weak lensing and galactic rotation curves. The second assumption is that a further dynamical modification or energy component - dark energy - exists, driving late-time cosmic acceleration. The need for these is now firmly established through a host of observations, which have raised crucial questions, and present a deep challenge to fundamental physics. The central theme of this proposal is the detailed understanding of the nature of the dark sector through the inevitable interactions between its individual components and with the visible universe. Such interactions can be crucial to a given model's viability, affecting its capability to reproduce the cosmic expansion history; the detailed predictions or structure formation; the gravitational dynamics on astrophysical and solar system scales; the stability of the microphysical model, and its ultimate consistency. While many models are consistent with cosmology on the coarsest scales, as is often the case, the devil may lie in the details. In this proposal we plan a comprehensive analysis of these details, focusing on the interactions within the dark sector and between it and visible matter, and on how these interactions affect the observational and theoretical consistency of models. Since it is unlikely that there will be a silver bullet allowing us to isolate the cause of cosmic acceleration, it is critical to develop a coherent view of the landscape of proposed models, extract clear predictions, and determine what combination of experiments and observations might allow us to test these predictions.

Fatigue damage prognosis of internal delamination in composite plates under cyclic compression loadings using affine arithmetic as uncertainty propagation tool

NASA Astrophysics Data System (ADS)

Gbaguidi, Audrey J.-M.

Structural health monitoring (SHM) has become indispensable for reducing maintenance costs and increasing the in-service capacity of a structure. The increased use of lightweight composite materials in aircraft structures drastically increased the effects of fatigue induced damage on their critical structural components and thus the necessity to predict the remaining life of those components. Damage prognosis, one of the least investigated fields in SHM, uses the current damage state of the system to forecast its future performance by estimating the expected loading environments. A successful damage prediction model requires the integration of technologies in areas like measurements, materials science, mechanics of materials, and probability theories, but most importantly the quantification of uncertainty in all these areas. In this study, Affine Arithmetic is used as a method for incorporating the uncertainties due to the material properties into the fatigue life prognosis of composite plates subjected to cyclic compressive loadings. When loadings are compressive in nature, the composite plates undergo repeated buckling-unloading of the delaminated layer which induces mixed modes I and II states of stress at the tip of the delamination in the plates. The Kardomateas model-based prediction law is used to predict the growth of the delamination, while the integration of the effects of the uncertainties for modes I and II coefficients in the fatigue life prediction model is handled using Affine arithmetic. The Mode I and Mode II interlaminar fracture toughness and fatigue characterization of the composite plates are first experimentally studied to obtain the material coefficients and fracture toughness, respectively. Next, these obtained coefficients are used in the Kardomateas law to predict the delamination lengths in the composite plates while using Affine Arithmetic to handle their uncertainties. At last, the fatigue characterization of the composite plates during compressive-buckling loadings is experimentally studied, and the delamination lengths obtained are compared with the predicted values to check the performance of Affine Arithmetic as an uncertainty propagation tool.

The Prediction of Long-Term Thermal Aging in Cast Austenitic Stainless Steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Byun, Thak Sang; Yang, Ying; Lach, Timothy G.

Cast austenitic stainless steel (CASS) materials are extensively used for many massive primary coolant system components of light water reactors (LWRs) including coolant piping, valve bodies, pump casings, and piping elbows. Many of these components are operated in complex and persistently damaging environments of elevated temperature, high pressure, corrosive environment, and sometimes radiation for long periods of time. Since a large number of CASS components are installed in every nuclear power plant and replacing such massive components is prohibitively expensive, any significant degradation in mechanical properties that affects structural integrity, cracking resistance in particular, of CASS components will raise amore » serious concern on the performance of entire power plant. The CASS materials for nuclear components are highly corrosion-resistant Fe-Cr-Ni alloys with 300 series stainless steel compositions and mostly austenite (γ)–ferrite (δ) duplex structures, which result from the casting processes consisting of alloy melting and pouring or injecting liquid metal into a static or spinning mold. Although the commonly used static and centrifugal casting processes enable the fabrication of massive components with proper resistance to environmental attacks, the alloying and microstructural conditions are not highly controllable in actual fabrication, especially in the casting processes of massive components. In the corrosion-resistant Fe-Cr-Ni alloy system, the minor phase (i.e., the δ-ferrite phase) is inevitably formed during the casting process, and is in a non-equilibrium state subject to detrimental changes during exposure to elevated temperature and/or radiation. In general, relatively few critical degradation modes are expected within the current design lifetime of 40 years, given that the CASS components have been processed properly. It has been well known, however, that both the thermal aging and the neutron irradiation can cause degradation of static and impact toughness in the cast stainless steels, and if combined with any flaws formed during the fabrication process or in service, the thermal degradation in CASS components can be a serious concern for the integrity of the power plant. On the integrity of the CASS components during the extended lifetime of 60 years or longer, no conclusive prediction has been possible, primarily because no direct experience with these materials currently exists, and the aging behavior of CASS alloys still remains largely uncertain. The ongoing research for CASS aging, as part of the LWRS Program/Materials Aging and Degradation Pathway, is an integrated research using holistic experimental and modeling means to provide both the scientific understanding on the aging and failure phenomena and the practical models to predict the degree of property degradation.« less

Predictability of extremes in non-linear hierarchically organized systems

NASA Astrophysics Data System (ADS)

Kossobokov, V. G.; Soloviev, A.

2011-12-01

Understanding the complexity of non-linear dynamics of hierarchically organized systems progresses to new approaches in assessing hazard and risk of the extreme catastrophic events. In particular, a series of interrelated step-by-step studies of seismic process along with its non-stationary though self-organized behaviors, has led already to reproducible intermediate-term middle-range earthquake forecast/prediction technique that has passed control in forward real-time applications during the last two decades. The observed seismic dynamics prior to and after many mega, great, major, and strong earthquakes demonstrate common features of predictability and diverse behavior in course durable phase transitions in complex hierarchical non-linear system of blocks-and-faults of the Earth lithosphere. The confirmed fractal nature of earthquakes and their distribution in space and time implies that many traditional estimations of seismic hazard (from term-less to short-term ones) are usually based on erroneous assumptions of easy tractable analytical models, which leads to widespread practice of their deceptive application. The consequences of underestimation of seismic hazard propagate non-linearly into inflicted underestimation of risk and, eventually, into unexpected societal losses due to earthquakes and associated phenomena (i.e., collapse of buildings, landslides, tsunamis, liquefaction, etc.). The studies aimed at forecast/prediction of extreme events (interpreted as critical transitions) in geophysical and socio-economical systems include: (i) large earthquakes in geophysical systems of the lithosphere blocks-and-faults, (ii) starts and ends of economic recessions, (iii) episodes of a sharp increase in the unemployment rate, (iv) surge of the homicides in socio-economic systems. These studies are based on a heuristic search of phenomena preceding critical transitions and application of methodologies of pattern recognition of infrequent events. Any study of rare phenomena of highly complex origin, by their nature, implies using problem oriented methods, which design breaks the limits of classical statistical or econometric applications. The unambiguously designed forecast/prediction algorithms of the "yes or no" variety, analyze the observable quantitative integrals and indicators available to a given date, then provides unambiguous answer to the question whether a critical transition should be expected or not in the next time interval. Since the predictability of an originating non-linear dynamical system is limited in principle, the probabilistic component of forecast/prediction algorithms is represented by the empirical probabilities of alarms, on one side, and failures-to-predict, on the other, estimated on control sets achieved in the retro- and prospective experiments. Predicting in advance is the only decisive test of forecast/predictions and the relevant on-going experiments are conducted in the case seismic extremes, recessions, and increases of unemployment rate. The results achieved in real-time testing keep being encouraging and confirm predictability of the extremes.

Arctic plant ecophysiology and water source utilization in response to altered snow: isotopic (δ18O and δ2H) evidence for meltwater subsidies to deciduous shrubs.

PubMed

Jespersen, R Gus; Leffler, A Joshua; Oberbauer, Steven F; Welker, Jeffrey M

2018-06-28

Warming-linked woody shrub expansion in the Arctic has critical consequences for ecosystem processes and climate feedbacks. The snow-shrub interaction model has been widely implicated in observed Arctic shrub increases, yet equivocal experimental results regarding nutrient-related components of this model have highlighted the need for a consideration of the increased meltwater predicted in expanding shrub stands. We used a 22-year snow manipulation experiment to simultaneously address the unexplored role of snow meltwater in arctic plant ecophysiology and nutrient-related components of the snow-shrub hypothesis. We coupled measurements of leaf-level gas exchange and leaf tissue chemistry (%N and δ 13 C) with an analysis of stable isotopes (δ 18 O and δ 2 H) in soil water, precipitation, and stem water. In deeper snow areas photosynthesis, conductance, and leaf N increased and δ 13 C values decreased in the deciduous shrubs, Betula nana and Salix pulchra, and the graminoid, Eriophorum vaginatum, with the strongest treatment effects observed in deciduous shrubs, consistent with predictions of the snow-shrub hypothesis. We also found that deciduous shrubs, especially S. pulchra, obtained much of their water from snow melt early in the growing season (40-50%), more than either E. vaginatum or the evergreen shrub, Rhododendron tomentosum (Ledum palustre). This result provides the basis for adding a meltwater-focused feedback loop to the snow-shrub interaction model of shrub expansion in the Arctic. Our results highlight the critical role of winter snow in the ecophysiology of Arctic plants, particularly deciduous shrubs, and underline the importance of understanding how global warming will affect the Arctic winter snowpack.

Residual strength of thin panels with cracks

NASA Technical Reports Server (NTRS)

Madenci, Erdogan

1994-01-01

The previous design philosophies involving safe life, fail-safe and damage tolerance concepts become inadequate for assuring the safety of aging aircraft structures. For example, the failure mechanism for the Aloha Airline accident involved the coalescence of undetected small cracks at the rivet holes causing a section of the fuselage to peel open during flight. Therefore, the fuselage structure should be designed to have sufficient residual strength under worst case crack configurations and in-flight load conditions. Residual strength is interpreted as the maximum load carrying capacity prior to unstable crack growth. Internal pressure and bending moment constitute the two major components of the external loads on the fuselage section during flight. Although the stiffeners in the form of stringers, frames and tear straps sustain part of the external loads, the significant portion of the load is taken up by the skin. In the presence of a large crack in the skin, the crack lips bulge out with considerable yielding; thus, the geometric and material nonlinearities must be included in the analysis for predicting residual strength. Also, these nonlinearities do not permit the decoupling of in-plane and out-of-plane bending deformations. The failure criterion combining the concepts of absorbed specific energy and strain energy density addresses the aforementioned concerns. The critical absorbed specific energy (local toughness) for the material is determined from the global specimen response and deformation geometry based on the uniaxial tensile test data and detailed finite element modeling of the specimen response. The use of the local toughness and stress-strain response at the continuum level eliminates the size effect. With this critical parameter and stress-strain response, the finite element analysis of the component by using STAGS along with the application of this failure criterion provides the stable crack growth calculations for residual strength predictions.

Damage prognosis of adhesively-bonded joints in laminated composite structural components of unmanned aerial vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrar, Charles R; Gobbato, Maurizio; Conte, Joel

2009-01-01

The extensive use of lightweight advanced composite materials in unmanned aerial vehicles (UAVs) drastically increases the sensitivity to both fatigue- and impact-induced damage of their critical structural components (e.g., wings and tail stabilizers) during service life. The spar-to-skin adhesive joints are considered one of the most fatigue sensitive subcomponents of a lightweight UAV composite wing with damage progressively evolving from the wing root. This paper presents a comprehensive probabilistic methodology for predicting the remaining service life of adhesively-bonded joints in laminated composite structural components of UAVs. Non-destructive evaluation techniques and Bayesian inference are used to (i) assess the current statemore » of damage of the system and, (ii) update the probability distribution of the damage extent at various locations. A probabilistic model for future loads and a mechanics-based damage model are then used to stochastically propagate damage through the joint. Combined local (e.g., exceedance of a critical damage size) and global (e.g.. flutter instability) failure criteria are finally used to compute the probability of component failure at future times. The applicability and the partial validation of the proposed methodology are then briefly discussed by analyzing the debonding propagation, along a pre-defined adhesive interface, in a simply supported laminated composite beam with solid rectangular cross section, subjected to a concentrated load applied at mid-span. A specially developed Eliler-Bernoulli beam finite element with interlaminar slip along the damageable interface is used in combination with a cohesive zone model to study the fatigue-induced degradation in the adhesive material. The preliminary numerical results presented are promising for the future validation of the methodology.« less

Electrolyte CPA equation of state for very high temperature and pressure reservoir and basin applications

NASA Astrophysics Data System (ADS)

Courtial, Xavier; Ferrando, Nicolas; de Hemptinne, Jean-Charles; Mougin, Pascal

2014-10-01

In this work, an electrolyte version of the Cubic Plus Association (eCPA) equation of state has been adapted to systems containing CH4, CO2, H2O and NaCl (up to 5 molal) at pressures up to 200 MPa and temperatures up to 773 K for salt-free systems and 573 K for salt-containing systems. Its purpose is to represent the phase behavior (including salting-out effect and critical point) and the phase densities in a range of temperature and pressure encountered in deep reservoirs and basins. The goal of the parameterization proposed is not to reach a very high accuracy for phase equilibrium and volumetric properties, but rather to develop a semi-predictive approach to model the phase and volumetric behavior of this system while allowing an easy extension to other compounds. Without salt, predictions for pure component vapor pressures and liquid molar volumes present an average absolute deviation (AAD) lower than 3% compared to experimental reference values. The pure component molar volumes out of saturation show an AAD lower than 4%. The highest deviations in densities are observed as expected in the vicinity of the critical coordinates of pure water and this effect increases when gases or salts are added to the system. For each binary system, CH4 + CO2, CH4 + H2O and CO2 + H2O, binary interaction parameters have been fitted to correctly represent the shape of the fluid phase envelopes (including all critical points) in the entire temperature and pressure range considered (219 K to 633 K and up to 250 MPa). The methane concentration in both phases of the CH4 + CO2 binary system is represented with an AAD lower than 9%. The methane solubility in water is represented within 16% and 8% for the methane content of the vapor. The CO2 solubility in water is within 26%, while the CO2 in the vapor phase shows an average deviation of 12%. All molar volumes are represented with an AAD lower than 3%. The few VLE experimental data for the CH4 + CO2 + H2O ternary system are fairly well predicted with the model without extra parameter, which confirm the ability of the eCPA equation of state to be extended to multi-component systems. In the presence of salts, gas + ion binary interaction parameters have been fitted, and all phase equilibrium are qualitatively correctly described, and more specifically the salting out effect. The solubility of methane or CO2 in brines, up to 5 molal, is represented with an AAD of 33% in a large temperature and pressure range (up to 673 K and 150 MPa). It should be noticed that for high temperatures, experimental data are relatively scarce and not always consistent. No data exist for water content of the vapor phase in these conditions. The new eCPA model can be easily extended to other components (including ions) to better represent real fluid behavior in very deep reservoir conditions.

Frequency Response Function Expansion for Unmeasured Translation and Rotation Dofs for Impedance Modelling Applications

NASA Astrophysics Data System (ADS)

Avitabile, P.; O'Callahan, J.

2003-07-01

Inclusion of rotational effects is critical for the accuracy of the predicted system characteristics, in almost all system modelling studies. However, experimentally derived information for the description of one or more of the components for the system will generally not have any rotational effects included in the description of the component. The lack of rotational effects has long affected the results from any system model development whether using a modal-based approach or an impedance-based approach. Several new expansion processes are described herein for the development of FRFs needed for impedance-based system models. These techniques expand experimentally derived mode shapes, residual modes from the modal parameter estimation process and FRFs directly to allow for the inclusion of the necessary rotational dof. The FRFs involving translational to rotational dofs are developed as well as the rotational to rotational dof. Examples are provided to show the use of these techniques.

PLUM: Parallel Load Balancing for Adaptive Unstructured Meshes

NASA Technical Reports Server (NTRS)

Oliker, Leonid; Biswas, Rupak; Saini, Subhash (Technical Monitor)

1998-01-01

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. We present a novel method called PLUM to dynamically balance the processor workloads with a global view. This paper presents the implementation and integration of all major components within our dynamic load balancing strategy for adaptive grid calculations. Mesh adaption, repartitioning, processor assignment, and remapping are critical components of the framework that must be accomplished rapidly and efficiently so as not to cause a significant overhead to the numerical simulation. A data redistribution model is also presented that predicts the remapping cost on the SP2. This model is required to determine whether the gain from a balanced workload distribution offsets the cost of data movement. Results presented in this paper demonstrate that PLUM is an effective dynamic load balancing strategy which remains viable on a large number of processors.

Users matter : multi-agent systems model of high performance computing cluster users.

DOE Office of Scientific and Technical Information (OSTI.GOV)

North, M. J.; Hood, C. S.; Decision and Information Sciences

2005-01-01

High performance computing clusters have been a critical resource for computational science for over a decade and have more recently become integral to large-scale industrial analysis. Despite their well-specified components, the aggregate behavior of clusters is poorly understood. The difficulties arise from complicated interactions between cluster components during operation. These interactions have been studied by many researchers, some of whom have identified the need for holistic multi-scale modeling that simultaneously includes network level, operating system level, process level, and user level behaviors. Each of these levels presents its own modeling challenges, but the user level is the most complex duemore » to the adaptability of human beings. In this vein, there are several major user modeling goals, namely descriptive modeling, predictive modeling and automated weakness discovery. This study shows how multi-agent techniques were used to simulate a large-scale computing cluster at each of these levels.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palladino, Andrea; Vissani, Francesco; Spurio, Maurizio, E-mail: andrea.palladino@gssi.infn.it, E-mail: maurizio.spurio@bo.infn.it, E-mail: francesco.vissani@lngs.infn.it

Recently it was noted that different IceCube datasets are not consistent with the same power law spectrum of the cosmic neutrinos: this is the IceCube spectral anomaly , that suggests that they observe a multicomponent spectrum. In this work, the main possibilities to enhance the description in terms of a single extragalactic neutrino component are examined. The hypothesis of a sizable contribution of Galactic high-energy neutrino events distributed as E {sup −2.7} [ Astrophys. J. 826 (2016) 185] is critically analyzed and its natural generalization is considered. The stability of the expectations is studied by introducing free parameters, motivated bymore » theoretical considerations and observational facts. The upgraded model here examined has 1) a Galactic component with different normalization and shape E {sup −2.4}; 2) an extragalactic neutrino spectrum based on new data; 3) a non-zero prompt component of atmospheric neutrinos. The two key predictions of the model concern the 'high-energy starting events' collected from the Southern sky. The Galactic component produces a softer spectrum and a testable angular anisotropy. A second, radically different class of models, where the second component is instead isotropic, plausibly extragalactic and with a relatively soft spectrum, is disfavored instead by existing observations of muon neutrinos from the Northern sky and below few 100 TeV.« less

On the IceCube spectral anomaly

NASA Astrophysics Data System (ADS)

Palladino, Andrea; Spurio, Maurizio; Vissani, Francesco

2016-12-01

Recently it was noted that different IceCube datasets are not consistent with the same power law spectrum of the cosmic neutrinos: this is the IceCube spectral anomaly, that suggests that they observe a multicomponent spectrum. In this work, the main possibilities to enhance the description in terms of a single extragalactic neutrino component are examined. The hypothesis of a sizable contribution of Galactic high-energy neutrino events distributed as E-2.7 [Astrophys. J. 826 (2016) 185] is critically analyzed and its natural generalization is considered. The stability of the expectations is studied by introducing free parameters, motivated by theoretical considerations and observational facts. The upgraded model here examined has 1) a Galactic component with different normalization and shape E-2.4 2) an extragalactic neutrino spectrum based on new data; 3) a non-zero prompt component of atmospheric neutrinos. The two key predictions of the model concern the `high-energy starting events' collected from the Southern sky. The Galactic component produces a softer spectrum and a testable angular anisotropy. A second, radically different class of models, where the second component is instead isotropic, plausibly extragalactic and with a relatively soft spectrum, is disfavored instead by existing observations of muon neutrinos from the Northern sky and below few 100 TeV.

Bi-Directional Communication: A Critical Component of HAT

NASA Technical Reports Server (NTRS)

Shively, Robert J.

2016-01-01

Known problems with automation include lack of mode awareness, automation brittleness, and risk of miscalibrated trust. Human-Autonomy Teaming (HAT) is essential for improving these problems. This presentation outlines critical components for Human-Autonomy Teaming.

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming

DOE PAGES

Feng, Wenting; Liang, Junyi; Hale, Lauren E.; ...

2017-06-09

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming.more » Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.« less

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Wenting; Liang, Junyi; Hale, Lauren E.

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming.more » Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.« less

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming.

PubMed

Feng, Wenting; Liang, Junyi; Hale, Lauren E; Jung, Chang Gyo; Chen, Ji; Zhou, Jizhong; Xu, Minggang; Yuan, Mengting; Wu, Liyou; Bracho, Rosvel; Pegoraro, Elaine; Schuur, Edward A G; Luo, Yiqi

2017-11-01

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon-climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming. Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change. © 2017 John Wiley & Sons Ltd.

Data collapse and critical dynamics in neuronal avalanche data

NASA Astrophysics Data System (ADS)

Butler, Thomas; Friedman, Nir; Dahmen, Karin; Beggs, John; Deville, Lee; Ito, Shinya

2012-02-01

The tasks of information processing, computation, and response to stimuli require neural computation to be remarkably flexible and diverse. To optimally satisfy the demands of neural computation, neuronal networks have been hypothesized to operate near a non-equilibrium critical point. In spite of their importance for neural dynamics, experimental evidence for critical dynamics has been primarily limited to power law statistics that can also emerge from non-critical mechanisms. By tracking the firing of large numbers of synaptically connected cortical neurons and comparing the resulting data to the predictions of critical phenomena, we show that cortical tissues in vitro can function near criticality. Among the most striking predictions of critical dynamics is that the mean temporal profiles of avalanches of widely varying durations are quantitatively described by a single universal scaling function (data collapse). We show for the first time that this prediction is confirmed in neuronal networks. We also show that the data have three additional features predicted by critical phenomena: approximate power law distributions of avalanche sizes and durations, samples in subcritical and supercritical phases, and scaling laws between anomalous exponents.

25 CFR 547.10 - What are the minimum standards for Class II gaming system critical events?

Code of Federal Regulations, 2011 CFR

2011-04-01

... GAMES § 547.10 What are the minimum standards for Class II gaming system critical events? This section... component can no longer be considered reliable. Accordingly, any game play on the affected component shall... or the medium itself has some fault.Any game play on the affected component shall cease immediately...

25 CFR 547.10 - What are the minimum standards for Class II gaming system critical events?

Code of Federal Regulations, 2012 CFR

2012-04-01

... GAMES § 547.10 What are the minimum standards for Class II gaming system critical events? This section... component can no longer be considered reliable. Accordingly, any game play on the affected component shall... or the medium itself has some fault.Any game play on the affected component shall cease immediately...

Integrated Syntactic/Semantic XML Data Validation with a Reusable Software Component

ERIC Educational Resources Information Center

Golikov, Steven

2013-01-01

Data integration is a critical component of enterprise system integration, and XML data validation is the foundation for sound data integration of XML-based information systems. Since B2B e-commerce relies on data validation as one of the critical components for enterprise integration, it is imperative for financial industries and e-commerce…

CNC machine tool's wear diagnostic and prognostic by using dynamic Bayesian networks

NASA Astrophysics Data System (ADS)

Tobon-Mejia, D. A.; Medjaher, K.; Zerhouni, N.

2012-04-01

The failure of critical components in industrial systems may have negative consequences on the availability, the productivity, the security and the environment. To avoid such situations, the health condition of the physical system, and particularly of its critical components, can be constantly assessed by using the monitoring data to perform on-line system diagnostics and prognostics. The present paper is a contribution on the assessment of the health condition of a computer numerical control (CNC) tool machine and the estimation of its remaining useful life (RUL). The proposed method relies on two main phases: an off-line phase and an on-line phase. During the first phase, the raw data provided by the sensors are processed to extract reliable features. These latter are used as inputs of learning algorithms in order to generate the models that represent the wear's behavior of the cutting tool. Then, in the second phase, which is an assessment one, the constructed models are exploited to identify the tool's current health state, predict its RUL and the associated confidence bounds. The proposed method is applied on a benchmark of condition monitoring data gathered during several cuts of a CNC tool. Simulation results are obtained and discussed at the end of the paper.

System model development for nuclear thermal propulsion

NASA Technical Reports Server (NTRS)

Walton, James T.; Hannan, Nelson A.; Perkins, Ken R.; Buksa, John H.; Worley, Brian A.; Dobranich, Dean

1992-01-01

A critical enabling technology in the evolutionary development of nuclear thermal propulsion (NTP) is the ability to predict the system performance under a variety of operating conditions. This is crucial for mission analysis and for control subsystem testing as well as for the modeling of various failure modes. Performance must be accurately predicted during steady-state and transient operation, including startup, shutdown, and post operation cooling. The development and application of verified and validated system models has the potential to reduce the design, testing, and cost and time required for the technology to reach flight-ready status. Since Oct. 1991, the U.S. Department of Energy (DOE), Department of Defense (DOD), and NASA have initiated critical technology development efforts for NTP systems to be used on Space Exploration Initiative (SEI) missions to the Moon and Mars. This paper presents the strategy and progress of an interagency NASA/DOE/DOD team for NTP system modeling. It is the intent of the interagency team to develop several levels of computer programs to simulate various NTP systems. The first level will provide rapid, parameterized calculations of overall system performance. Succeeding computer programs will provide analysis of each component in sufficient detail to guide the design teams and experimental efforts. The computer programs will allow simulation of the entire system to allow prediction of the integrated performance. An interagency team was formed for this task to use the best capabilities available and to assure appropriate peer review.

Current status of intratumoral therapy for glioblastoma.

PubMed

Mehta, Ankit I; Linninger, Andreas; Lesniak, Maciej S; Engelhard, Herbert H

2015-10-01

With emerging drug delivery technologies becoming accessible, more options are expected to become available to patients with glioblastoma (GBM) in the near future. It is important for clinicians to be familiar with the underlying mechanisms and limitations of intratumoral drug delivery, and direction of recent research efforts. Tumor-adjacent brain is an extremely complex living matrix that creates challenges with normal tissue intertwining with tumor cells. For convection-enhanced delivery (CED), the role of tissue anisotropy for better predicting the biodistribution of the infusate has recently been studied. Computational predictive methods are now available to better plan CED therapy. Catheter design and placement—in addition to the agent being used—are critical components of any protocol. This paper overviews intratumoral therapies for GBM, highlighting key anatomic and physiologic perspectives, selected agents (especially immunotoxins), and some new developments such as the description of the glymphatic system.

Monte Carlo Simulation of THz Multipliers

NASA Technical Reports Server (NTRS)

East, J.; Blakey, P.

1997-01-01

Schottky Barrier diode frequency multipliers are critical components in submillimeter and Thz space based earth observation systems. As the operating frequency of these multipliers has increased, the agreement between design predictions and experimental results has become poorer. The multiplier design is usually based on a nonlinear model using a form of harmonic balance and a model for the Schottky barrier diode. Conventional voltage dependent lumped element models do a poor job of predicting THz frequency performance. This paper will describe a large signal Monte Carlo simulation of Schottky barrier multipliers. The simulation is a time dependent particle field Monte Carlo simulation with ohmic and Schottky barrier boundary conditions included that has been combined with a fixed point solution for the nonlinear circuit interaction. The results in the paper will point out some important time constants in varactor operation and will describe the effects of current saturation and nonlinear resistances on multiplier operation.

The Asphaltenes

NASA Astrophysics Data System (ADS)

Mullins, Oliver C.

2011-07-01

Asphaltenes, the most aromatic of the heaviest components of crude oil, are critical to all aspects of petroleum utilization, including reservoir characterization, production, transportation, refining, upgrading, paving, and coating materials. The asphaltenes, which are solid, have or impart crucial and often deleterious attributes in fluids such as high viscosity, emulsion stability, low distillate yields, and inopportune phase separation. Nevertheless, fundamental uncertainties had precluded a first-principles approach to asphaltenes until now. Recently, asphaltene science has undergone a renaissance; many basic molecular and nanocolloidal properties have been resolved and codified in the modified Yen model (also known as the Yen-Mullins model), thereby enabling predictive asphaltene science. Advances in analytical chemistry, especially mass spectrometry, enable the identification of tens of thousands of distinct chemical species in crude oils and asphaltenes. These and other powerful advances in asphaltene science fall under the banner of petroleomics, which incorporates predictive petroleum science and provides a framework for future developments.

Characterization of YBa2Cu3O7, including critical current density Jc, by trapped magnetic field

NASA Technical Reports Server (NTRS)

Chen, In-Gann; Liu, Jianxiong; Weinstein, Roy; Lau, Kwong

1992-01-01

Spatial distributions of persistent magnetic field trapped by sintered and melt-textured ceramic-type high-temperature superconductor (HTS) samples have been studied. The trapped field can be reproduced by a model of the current consisting of two components: (1) a surface current Js and (2) a uniform volume current Jv. This Js + Jv model gives a satisfactory account of the spatial distribution of the magnetic field trapped by different types of HTS samples. The magnetic moment can be calculated, based on the Js + Jv model, and the result agrees well with that measured by standard vibrating sample magnetometer (VSM). As a consequence, Jc predicted by VSM methods agrees with Jc predicted from the Js + Jv model. The field mapping method described is also useful to reveal the granular structure of large HTS samples and regions of weak links.

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Prediction of global vapor-liquid equilibria for mixtures containing polar and associating components with improved renormalization group theory.

PubMed

Mi, Jianguo; Tang, Yiping; Zhong, Chongli; Li, Yi-Gui

2005-11-03

Our recently improved renormalization group (RG) theory is further reformulated within the context of density functional theory. To improve the theory for polar and associating fluids, an explicit and complete expression of the theory is derived in which the density fluctuation is expanded up to the third-order term instead of the original second-order term. A new predictive equation of state based on the first-order mean spherical approximation statistical associating fluid theory (FMSA-SAFT) and the newly improved RG theory is proposed for systems containing polar and associating fluids. The calculated results for both pure fluids and mixtures are in good agreement with experimental data both inside and outside the critical region. This work demonstrates that the RG theory incorporated with the solution of FMSA is a promising route for accurately describing the global phase behavior of complex fluids and mixtures.

Sensitivity, specificity, and predictive values of pediatric metabolic syndrome components in relation to adult metabolic syndrome: the Princeton LRC follow-up study.

PubMed

Huang, Terry T-K; Nansel, Tonja R; Belsheim, Allen R; Morrison, John A

2008-02-01

To estimate the sensitivity, specificity, and predictive values of pediatric metabolic syndrome (MetS) components (obesity, fasting glucose, triglycerides, high-density lipoprotein, and blood pressure) at various cutoff points in relation to adult MetS. Data from the National Heart, Lung, and Blood Institute Lipid Research Clinics Princeton Prevalence Study (1973-1976) and the Princeton Follow-up Study (2000-2004) were used to calculate sensitivity, specificity, and positive and negative predictive values for each component at a given cutoff point and for aggregates of components. Individual pediatric components alone showed low to moderate sensitivity, high specificity, and moderate predictive values in relation to adult MetS. When all 5 pediatric MetS components were considered, the presence of at least 1 abnormality had higher sensitivity for adult MetS than individual components alone. When multiple abnormalities were mandatory for MetS, positive predictive value was high and sensitivity was low. Childhood body mass alone showed neither high sensitivity nor high positive predictive value for adult MetS. Considering multiple metabolic variables in childhood can improve the predictive usefulness for adult MetS, compared with each component or body mass alone. MetS variables may be useful for identifying some children who are at risk for prevention interventions.

Considerations in development and implementation of elasto-viscoplastic constitutive model for high temperature applications

NASA Technical Reports Server (NTRS)

Riff, Richard

1988-01-01

The prediction of inelastic behavior of metallic materials at elevated temperatures has increased in importance in recent years. The operating conditions within the hot section of a rocket motor or a modern gas turbine engine present an extremely harsh thermomechanical environment. Large thermal transients are induced each time the engine is started or shut down. Additional thermal transients from an elevated ambient occur whenever the engine power level is adjusted to meet flight requirements. The structural elements employed in such hot sections, as well as any engine components located therein, must be capable of withstanding such extreme conditions. Failure of a component would, due to the critical nature of the hot section, lead to an immediate and catastrophic loss in power. Consequently, assuring satisfactory long term performance for such components is a major concern. Nonisothermal loading of structures often causes excursion of stress well into the inelastic range. Moreover, the influence of geometry changes on the response is also significant in most cases. Therefore, both material and geometric nonlinear effects are considered.

Development of Advanced Environmental Barrier Coatings for SiC/SiC Composites at NASA GRC: Prime-Reliant Design and Durability Perspectives

NASA Technical Reports Server (NTRS)

Zhu, Dongming

2017-01-01

Environmental barrier coatings (EBCs) are considered technologically important because of the critical needs and their ability to effectively protect the turbine hot-section SiC/SiC ceramic matrix composite (CMC) components in harsh engine combustion environments. The development of NASA's advanced environmental barrier coatings have been aimed at significantly improved the coating system temperature capability, stability, erosion-impact, and CMAS resistance for SiC/SiC turbine airfoil and combustors component applications. The NASA environmental barrier coating developments have also emphasized thermo-mechanical creep and fatigue resistance in simulated engine heat flux and environments. Experimental results and models for advanced EBC systems will be presented to help establishing advanced EBC composition design methodologies, performance modeling and life predictions, for achieving prime-reliant, durable environmental coating systems for 2700-3000 F engine component applications. Major technical barriers in developing environmental barrier coating systems and the coating integration with next generation composites having further improved temperature capability, environmental stability, EBC-CMC fatigue-environment system durability will be discussed.

Wireless Sensors Pinpoint Rotorcraft Troubles

NASA Technical Reports Server (NTRS)

2013-01-01

Helicopters present many advantages over fixed-wing aircraft: they can take off from and land in tight spots, they can move in any direction with relative ease, and they can hover in one area for extended periods of time. But that maneuverability comes with costs. For example, one persistent issue in helicopter maintenance and operation is that their components are subject to high amounts of wear compared to fixed-wing aircraft. In particular, the rotor drive system that makes flight possible undergoes heavy vibration during routine performance, slowly degrading components in a way that can cause failures if left unmonitored. The level of attention required to ensure flight safety makes helicopters very expensive to maintain. As a part of NASA s Fundamental Aeronautics Program, the Subsonic Rotary Wing Project seeks to advance knowledge about and improve prediction capabilities for rotorcraft, with the aim of developing technology that will meet future civilian requirements like higher efficiency and lower noise flights. One of the program s goals is to improve technology to detect and assess the health of critical components in rotorcraft drive systems.

Comparison of manual scaled and predicted foE and foF1 critical frequencies. Technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gamache, R.R.; Kersey, W.T.

1990-07-01

The CCIR and Titheridge foE critical frequency prediction routines were tested by comparison with 1875 manually scaled values. The foF1 critical frequency prediction routine of Millman et al was tested by comparison with 1005 manually scaled values. Plots and statistics of the comparisons are presented and discussed. From the results recommendations are made to help improve autoscaling.

Critical thinking skills of undergraduate nursing students: description and demographic predictors.

PubMed

Hunter, Sharyn; Pitt, Victoria; Croce, Nic; Roche, Jan

2014-05-01

This study investigated the critical thinking skills among undergraduate nursing students in Australia to obtain a profile and determine demographic predictors of critical thinking. There is universal agreement that being a critical thinker is an outcome requirement for many accreditation and registering nursing bodies. Most studies provide descriptive statistical information about critical thinking skills while some have studied the changes in critical thinking after an intervention. Limited research about factors that predict critical thinking skills is available. A cross-sectional descriptive study was conducted using convenience sampling. Two hundred and sixty-nine students were recruited across three years of an undergraduate programme in 2009. Most students' age ranged from under 20 to 34 years (58%), 87% were female, 91% were Australian and 23% of first and second year students had nursing associated experience external to the university. Data about critical thinking skills were collected via the Health Science Reasoning Test (HSRT). Linear regression analysis investigated the predictors of nursing students' critical thinking skills. The students in third year had a profile of critical thinking skills comparable with HSRT norms. Year of study predicted higher critical thinking scores for all domains (p<0.001) except the subscale, analysis. Nationality predicted higher scores for total CT skill scores (p<0.001) and subscales, inductive (p=0.001) and deductive reasoning (p=0.001). Nursing associated experience predicted higher scores for the subscale, analysis (p<0.001). Age and gender were not predictive. However, these demographic predictors only accounted for a small variance obtained for the domains of CT skills. An understanding of factors that predict nursing students' CT skills is required. Despite this study finding a number of significant predictors of nursing students' CT skills, there are others yet to be understood. Future research is recommended exploring explicit CT instructional approaches and nursing students' CT skills. © 2013 Elsevier Ltd. All rights reserved.

Are loss of control while eating and overeating valid constructs? A critical review of the literature

PubMed Central

Goldschmidt, Andrea B.

2017-01-01

Background Binge eating is a marker of weight gain and obesity, and a hallmark feature of eating disorders. Yet, its component constructs—overeating and loss of control (LOC) while eating—are poorly understood and difficult to measure. Objective To critically review the human literature concerning the validity of LOC and overeating across the age and weight spectrum. Data sources English-language articles addressing the face, convergent, discriminant, and predictive validity of LOC and overeating were included. Results LOC and overeating appear to have adequate face validity. Emerging evidence supports the convergent and predictive validity of the LOC construct, given its unique cross-sectional and prospective associations with numerous anthropometric, psychosocial, and eating behavior-related factors. Overeating may be best conceptualized as a marker of excess weight status. Limitations Binge eating constructs, particularly in the context of subjectively large episodes, are challenging to measure reliably. Few studies addressed overeating in the absence of LOC, thereby limiting conclusions about the validity of the overeating construct independent of LOC. Additional studies addressing the discriminant validity of both constructs are warranted. Discussion Suggestions for future weight-related research and for appropriately defining binge eating in the eating disorders diagnostic scheme are presented. PMID:28165655

Critical elements of clinical follow-up after hospital discharge for heart failure: insights from the EVEREST trial

PubMed Central

Dunlay, Shannon M.; Gheorghiade, Mihai; Reid, Kimberly J.; Allen, Larry A.; Chan, Paul S.; Hauptman, Paul J.; Zannad, Faiez; Maggioni, Aldo P.; Swedberg, Karl; Konstam, Marvin A.; Spertus, John A.

2010-01-01

Aims Hospitalized heart failure (HF) patients are at high risk for death and readmission. We examined the incremental value of data obtained 1 week after HF hospital discharge in predicting mortality and readmission. Methods and results In the Efficacy of Vasopressin Antagonism in Heart Failure Outcome Study with tolvaptan, 1528 hospitalized patients (ejection fraction ≤40%) with a physical examination, laboratories, and health status [Kansas City Cardiomyopathy Questionnaire (KCCQ)] assessments 1 week after discharge were included. The ability to predict 1 year cardiovascular rehospitalization and mortality was assessed with Cox models, c-statistics, and the integrated discrimination improvement (IDI). Not using a beta-blocker, rales, pedal oedema, hyponatraemia, lower creatinine clearance, higher brain natriuretic peptide, and worse health status were independent risk factors for rehospitalization and death. The c-statistic for the base model (history and medications) was 0.657. The model improved with physical examination, laboratory, and KCCQ results, with IDI increases of 4.9, 7.0, and 3.2%, respectively (P < 0.001 each). The combination of all three offered the greatest incremental gain (c-statistic 0.749; IDI increase 10.8%). Conclusion Physical examination, laboratories, and KCCQ assessed 1 week after discharge offer important prognostic information, suggesting that all are critical components of outpatient evaluation after HF hospitalization. PMID:20197265

"The role of facial appearance on CEO selection after firm misconduct:" Correction to Gomulya et al. (2016).

PubMed

2017-04-01

Reports an error in "The Role of Facial Appearance on CEO Selection After Firm Misconduct" by David Gomulya, Elaine M. Wong, Margaret E. Ormiston and Warren Boeker ( Journal of Applied Psychology , Advanced Online Publication, Dec 19, 2016, np). The wrong figure files were used. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-60831-001.) We investigate a particular aspect of CEO successor trustworthiness that may be critically important after a firm has engaged in financial misconduct. Specifically, drawing on prior research that suggests that facial appearance is one critical way in which trustworthiness is signaled, we argue that leaders who convey integrity, a component of trustworthiness, will be more likely to be selected as successors after financial restatement. We predict that such appointments garner more positive reactions by external observers such as investment analysts and the media because these CEOs are perceived as having greater integrity. In an archival study of firms that have announced financial restatements, we find support for our predictions. These findings have implications for research on CEO succession, leadership selection, facial appearance, and firm misconduct. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Versatile and efficient pore network extraction method using marker-based watershed segmentation

NASA Astrophysics Data System (ADS)

Gostick, Jeff T.

2017-08-01

Obtaining structural information from tomographic images of porous materials is a critical component of porous media research. Extracting pore networks is particularly valuable since it enables pore network modeling simulations which can be useful for a host of tasks from predicting transport properties to simulating performance of entire devices. This work reports an efficient algorithm for extracting networks using only standard image analysis techniques. The algorithm was applied to several standard porous materials ranging from sandstone to fibrous mats, and in all cases agreed very well with established or known values for pore and throat sizes, capillary pressure curves, and permeability. In the case of sandstone, the present algorithm was compared to the network obtained using the current state-of-the-art algorithm, and very good agreement was achieved. Most importantly, the network extracted from an image of fibrous media correctly predicted the anisotropic permeability tensor, demonstrating the critical ability to detect key structural features. The highly efficient algorithm allows extraction on fairly large images of 5003 voxels in just over 200 s. The ability for one algorithm to match materials as varied as sandstone with 20% porosity and fibrous media with 75% porosity is a significant advancement. The source code for this algorithm is provided.

US Integrated Ocean Observing System (IOOS°): Delivering Benefits to Science and Society

NASA Astrophysics Data System (ADS)

Willis, Z. S.

2011-12-01

The United States Integrated Ocean Observing System (IOOS°) is a user-driven, coordinated network of people, organizations, and technology that generate and disseminate continuous data about our coastal waters, Great Lakes, and oceans supported by strong research and development activities. IOOS° is our Eyes on our Oceans, Coasts and Great Lakes that enable the United States to track, predict, manage, and adapt to changes in our marine environment and deliver critical information to decision makers to improve safety, enhance our economy and protect our environment. IOOS provides a major shift in the approach to ocean observing by drawing together the vast network of disparate federal and non-federal observing systems to produce a cohesive suite of data, information, and products on a sufficient geographic and temporal scale to support decision-making. Two interdependent components constitute the U.S. IOOS: (1) the global ocean component, and (2) the coastal component. The strength of IOOS is in its partnerships, starting with the federal agencies, the partnerships extend internationally for the global component and to the local level for the coastal component. The coastal component includes the national set of observations for the U.S. Ocean, Coasts and Great Lakes, a network of Regional Associations that are establishing Regional Coastal Ocean Observing Systems (RCOOS) and the Alliance for Coastal Technologies (ACT). The U.S. IOOS is our nation's contribution to the Global Ocean Observing System (GOOS) - the ocean component of the Global Earth Observation System of Systems (GEOSS).

Developing a comprehensive training curriculum for integrated predictive maintenance

NASA Astrophysics Data System (ADS)

Wurzbach, Richard N.

2002-03-01

On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of key technologies such as vibration analysis, infrared thermography, and oil analysis not as singular entities, but as a toolbox resource from which to address overall equipment and plant reliability in a structured program and decision environment.

Using artificial intelligence to predict prolonged mechanical ventilation and tracheostomy placement.

PubMed

Parreco, Joshua; Hidalgo, Antonio; Parks, Jonathan J; Kozol, Robert; Rattan, Rishi

2018-08-01

Early identification of critically ill patients who will require prolonged mechanical ventilation (PMV) has proven to be difficult. The purpose of this study was to use machine learning to identify patients at risk for PMV and tracheostomy placement. The Multiparameter Intelligent Monitoring in Intensive Care III database was queried for all intensive care unit (ICU) stays with mechanical ventilation. PMV was defined as ventilation >7 d. Classifiers with a gradient-boosted decision trees algorithm were created for the outcomes of PMV and tracheostomy placement. The variables used were six different severity-of-illness scores calculated on the first day of ICU admission including their components and 30 comorbidities. Mean receiver operating characteristic curves were calculated for the outcomes, and variable importance was quantified. There were 20,262 ICU stays identified. PMV was required in 13.6%, and tracheostomy was performed in 6.6% of patients. The classifier for predicting PMV was able to achieve a mean area under the curve (AUC) of 0.820 ± 0.016, and tracheostomy was predicted with an AUC of 0.830 ± 0.011. There were 60.7% patients admitted to a surgical ICU, and the classifiers for these patients predicted PMV with an AUC of 0.852 ± 0.017 and tracheostomy with an AUC of 0.869 ± 0.015. The variable with the highest importance for predicting PMV was the logistic organ dysfunction score pulmonary component (13%), and the most important comorbidity in predicting tracheostomy was cardiac arrhythmia (12%). This study demonstrates the use of artificial intelligence through machine-learning classifiers for the early identification of patients at risk for PMV and tracheostomy. Application of these identification techniques could lead to improved outcomes by allowing for early intervention. Copyright © 2018 Elsevier Inc. All rights reserved.

Near-infrared chemical imaging (NIR-CI) as a process monitoring solution for a production line of roll compaction and tableting.

PubMed

Khorasani, Milad; Amigo, José M; Sun, Changquan Calvin; Bertelsen, Poul; Rantanen, Jukka

2015-06-01

In the present study the application of near-infrared chemical imaging (NIR-CI) supported by chemometric modeling as non-destructive tool for monitoring and assessing the roller compaction and tableting processes was investigated. Based on preliminary risk-assessment, discussion with experts and current work from the literature the critical process parameter (roll pressure and roll speed) and critical quality attributes (ribbon porosity, granule size, amount of fines, tablet tensile strength) were identified and a design space was established. Five experimental runs with different process settings were carried out which revealed intermediates (ribbons, granules) and final products (tablets) with different properties. Principal component analysis (PCA) based model of NIR images was applied to map the ribbon porosity distribution. The ribbon porosity distribution gained from the PCA based NIR-CI was used to develop predictive models for granule size fractions. Predictive methods with acceptable R(2) values could be used to predict the granule particle size. Partial least squares regression (PLS-R) based model of the NIR-CI was used to map and predict the chemical distribution and content of active compound for both roller compacted ribbons and corresponding tablets. In order to select the optimal process, setting the standard deviation of tablet tensile strength and tablet weight for each tablet batch was considered. Strong linear correlation between tablet tensile strength and amount of fines and granule size was established, respectively. These approaches are considered to have a potentially large impact on quality monitoring and control of continuously operating manufacturing lines, such as roller compaction and tableting processes. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of a Probabilistic Decision-Support Model to Forecast Coastal Resilience

NASA Astrophysics Data System (ADS)

Wilson, K.; Safak, I.; Brenner, O.; Lentz, E. E.; Hapke, C. J.

2016-02-01

Site-specific forecasts of coastal change are a valuable management tool in preparing for and assessing storm-driven impacts in coastal areas. More specifically, understanding the likelihood of storm impacts, recovery following events, and the alongshore variability of both is central in evaluating vulnerability and resiliency of barrier islands. We introduce a probabilistic modeling framework that integrates hydrodynamic, anthropogenic, and morphologic components of the barrier system to evaluate coastal change at Fire Island, New York. The model is structured on a Bayesian network (BN), which utilizes observations to learn statistical relationships between system variables. In addition to predictive ability, probabilistic models convey the level of confidence associated with a prediction, an important consideration for coastal managers. Our model predicts the likelihood of morphologic change on the upper beach based on several decades of beach monitoring data. A coupled hydrodynamic BN combines probabilistic and deterministic modeling approaches; by querying nearly two decades of nested-grid wave simulations that account for both distant swells and local seas, we produce scenarios of event and seasonal wave climates. The wave scenarios of total water level - a sum of run up, surge and tide - and anthropogenic modification are the primary drivers of morphologic change in our model structure. Preliminary results show the hydrodynamic BN is able to reproduce time series of total water levels, a critical validation process before generating scenarios, and forecasts of geomorphic change over three month intervals are up to 70% accurate. Predictions of storm-induced change and recovery are linked to evaluate zones of persistent vulnerability or resilience and will help managers target restoration efforts, identify areas most vulnerable to habitat degradation, and highlight resilient zones that may best support relocation of critical infrastructure.

Dissecting Magnetar Variability with Bayesian Hierarchical Models

NASA Astrophysics Data System (ADS)

Huppenkothen, Daniela; Brewer, Brendon J.; Hogg, David W.; Murray, Iain; Frean, Marcus; Elenbaas, Chris; Watts, Anna L.; Levin, Yuri; van der Horst, Alexander J.; Kouveliotou, Chryssa

2015-09-01

Neutron stars are a prime laboratory for testing physical processes under conditions of strong gravity, high density, and extreme magnetic fields. Among the zoo of neutron star phenomena, magnetars stand out for their bursting behavior, ranging from extremely bright, rare giant flares to numerous, less energetic recurrent bursts. The exact trigger and emission mechanisms for these bursts are not known; favored models involve either a crust fracture and subsequent energy release into the magnetosphere, or explosive reconnection of magnetic field lines. In the absence of a predictive model, understanding the physical processes responsible for magnetar burst variability is difficult. Here, we develop an empirical model that decomposes magnetar bursts into a superposition of small spike-like features with a simple functional form, where the number of model components is itself part of the inference problem. The cascades of spikes that we model might be formed by avalanches of reconnection, or crust rupture aftershocks. Using Markov Chain Monte Carlo sampling augmented with reversible jumps between models with different numbers of parameters, we characterize the posterior distributions of the model parameters and the number of components per burst. We relate these model parameters to physical quantities in the system, and show for the first time that the variability within a burst does not conform to predictions from ideas of self-organized criticality. We also examine how well the properties of the spikes fit the predictions of simplified cascade models for the different trigger mechanisms.

The role of the default mode network in component processes underlying the wandering mind.

PubMed

Poerio, Giulia L; Sormaz, Mladen; Wang, Hao-Ting; Margulies, Daniel; Jefferies, Elizabeth; Smallwood, Jonathan

2017-07-01

Experiences such as mind-wandering illustrate that cognition is not always tethered to events in the here-and-now. Although converging evidence emphasises the default mode network (DMN) in mind-wandering, its precise contribution remains unclear. The DMN comprises cortical regions that are maximally distant from primary sensory and motor cortex, a topological location that may support the stimulus-independence of mind-wandering. The DMN is functionally heterogeneous, comprising regions engaged by memory, social cognition and planning; processes relevant to mind-wandering content. Our study examined the relationships between: (i) individual differences in resting-state DMN connectivity, (ii) performance on memory, social and planning tasks and (iii) variability in spontaneous thought, to investigate whether the DMN is critical to mind-wandering because it supports stimulus-independent cognition, memory retrieval, or both. Individual variation in task performance modulated the functional organization of the DMN: poor external engagement was linked to stronger coupling between medial and dorsal subsystems, while decoupling of the core from the cerebellum predicted reports of detailed memory retrieval. Both patterns predicted off-task future thoughts. Consistent with predictions from component process accounts of mind-wandering, our study suggests a 2-fold involvement of the DMN: (i) it supports experiences that are unrelated to the environment through strong coupling between its sub-systems; (ii) it allows memory representations to form the basis of conscious experience. © The Author (2017). Published by Oxford University Press.

DISSECTING MAGNETAR VARIABILITY WITH BAYESIAN HIERARCHICAL MODELS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huppenkothen, Daniela; Elenbaas, Chris; Watts, Anna L.

Neutron stars are a prime laboratory for testing physical processes under conditions of strong gravity, high density, and extreme magnetic fields. Among the zoo of neutron star phenomena, magnetars stand out for their bursting behavior, ranging from extremely bright, rare giant flares to numerous, less energetic recurrent bursts. The exact trigger and emission mechanisms for these bursts are not known; favored models involve either a crust fracture and subsequent energy release into the magnetosphere, or explosive reconnection of magnetic field lines. In the absence of a predictive model, understanding the physical processes responsible for magnetar burst variability is difficult. Here,more » we develop an empirical model that decomposes magnetar bursts into a superposition of small spike-like features with a simple functional form, where the number of model components is itself part of the inference problem. The cascades of spikes that we model might be formed by avalanches of reconnection, or crust rupture aftershocks. Using Markov Chain Monte Carlo sampling augmented with reversible jumps between models with different numbers of parameters, we characterize the posterior distributions of the model parameters and the number of components per burst. We relate these model parameters to physical quantities in the system, and show for the first time that the variability within a burst does not conform to predictions from ideas of self-organized criticality. We also examine how well the properties of the spikes fit the predictions of simplified cascade models for the different trigger mechanisms.« less

Magnetic eta index and the ability to forecast sporadic E layer appearance

NASA Astrophysics Data System (ADS)

Dziak-Jankowska, Beata; Stanislawska, Iwona; Pozoga, Mariusz; Tomasik, Lukasz; Ernst, Tomasz

2012-07-01

We analysed the correlation of the changes of the magnetic vertical component with the ionospheric deviations from monthly median of the E layer characteristics. Promising results indicate that the eta parameter can be used to predict sporadic E layer during magnetically quiet days. Our previous work concern the data from only one year - 2004. During the descending phase of solar cycle in 2004 there was not numerous amount of quiet days. We extend our research to other years starting from 1996 and focusing on 2007 - 2009, years of the prolonged solar minimum. The analysis shows that under magnetically quiet circumstances the magnetic index eta indicates large magnetic disturbance, especially in vertical component when other magnetic indices inform about quiet magnetic conditions. The results indicate that the increase of the magnetic eta index (the ratio of the variations of vertical component of the external magnetic field to the horizontal component) is associated with the emergence of sporadic E layer or with increase of foEs critical frequency of sporadic E layer. The appearance of sporadic E layer followed 1-2 h after growth of magnetic index eta. An important conclusion is that the analysis of the hourly ionospheric data does not give 100% correlation between the increase of eta and the emergence of Es layer, however, studies of dense measurement data show that the correlation is almost 100%. An advantage of the eta index is the fact that after eliminating the effect of currents induced within the Earth, eta index bring independent and meaningful information on the system of current in the ionosphere. Hence, the eta index could be an important element of the ionosphere monitoring and can be used to predict such local phenomenon like the appearance of the sporadic E layer.

Human Immunity and the Design of Multi-Component, Single Target Vaccines

PubMed Central

Saul, Allan; Fay, Michael P.

2007-01-01

Background Inclusion of multiple immunogens to target a single organism is a strategy being pursued for many experimental vaccines, especially where it is difficult to generate a strongly protective response from a single immunogen. Although there are many human vaccines that contain multiple defined immunogens, in almost every case each component targets a different pathogen. As a consequence, there is little practical experience for deciding where the increased complexity of vaccines with multiple defined immunogens vaccines targeting single pathogens will be justifiable. Methodology/Principal Findings A mathematical model, with immunogenicity parameters derived from a database of human responses to established vaccines, was used to predict the increase in the efficacy and the proportion of the population protected resulting from addition of further immunogens. The gains depended on the relative protection and the range of responses in the population to each immunogen and also to the correlation of the responses between immunogens. In most scenarios modeled, the gain in overall efficacy obtained by adding more immunogens was comparable to gains obtained from a single immunogen through the use of better formulations or adjuvants. Multi-component single target vaccines were more effective at decreasing the proportion of poor responders than increasing the overall efficacy of the vaccine in a population. Conclusions/Significance Inclusion of limited number of antigens in a vaccine aimed at targeting a single organism will increase efficacy, but the gains are relatively modest and for a practical vaccine there are constraints that are likely to limit multi-component single target vaccines to a small number of key antigens. The model predicts that this type of vaccine will be most useful where the critical issue is the reduction in proportion of poor responders. PMID:17786221

Recent developments on SMA actuators: predicting the actuation fatigue life for variable loading schemes

NASA Astrophysics Data System (ADS)

Wheeler, Robert W.; Lagoudas, Dimitris C.

2017-04-01

Shape memory alloys (SMAs), due to their ability to repeatably recover substantial deformations under applied mechanical loading, have the potential to impact the aerospace, automotive, biomedical, and energy industries as weight and volume saving replacements for conventional actuators. While numerous applications of SMA actuators have been flight tested and can be found in industrial applications, these actuators are generally limited to non-critical components, are not widely implemented and frequently one-off designs, and are generally overdesigned due to a lack of understanding of the effect of the loading path on the fatigue life and the lack of an accurate method for predicting actuator lifetimes. In recent years, multiple research efforts have increased our understanding of the actuation fatigue process of SMAs. These advances can be utilized to predict the fatigue lives and failure loads in SMA actuators. Additionally, these prediction methods can be implemented in order to intelligently design actuators in accordance with their fatigue and failure limits. In the following paper, both simple and complex thermomechanical loading paths have been considered. Experimental data was utilized from two material systems: equiatomic Nickel-Titanium and Nickelrich Nickel-Titanium.

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Thermal barrier coating life prediction model development

NASA Technical Reports Server (NTRS)

Demasi, J. T.

1986-01-01

A methodology is established to predict thermal barrier coating life in a environment similar to that experienced by gas turbine airfoils. Experiments were conducted to determine failure modes of the thermal barrier coating. Analytical studies were employed to derive a life prediction model. A review of experimental and flight service components as well as laboratory post evaluations indicates that the predominant mode of TBC failure involves thermomechanical spallation of the ceramic coating layer. This ceramic spallation involves the formation of a dominant crack in the ceramic coating parallel to and closely adjacent to the topologically complex metal ceramic interface. This mechanical failure mode clearly is influenced by thermal exposure effects as shown in experiments conducted to study thermal pre-exposure and thermal cycle-rate effects. The preliminary life prediction model developed focuses on the two major damage modes identified in the critical experiments tasks. The first of these involves a mechanical driving force, resulting from cyclic strains and stresses caused by thermally induced and externally imposed mechanical loads. The second is an environmental driving force based on experimental results, and is believed to be related to bond coat oxidation. It is also believed that the growth of this oxide scale influences the intensity of the mechanical driving force.

Estimation of the viscosities of liquid binary alloys

NASA Astrophysics Data System (ADS)

Wu, Min; Su, Xiang-Yu

2018-01-01

As one of the most important physical and chemical properties, viscosity plays a critical role in physics and materials as a key parameter to quantitatively understanding the fluid transport process and reaction kinetics in metallurgical process design. Experimental and theoretical studies on liquid metals are problematic. Today, there are many empirical and semi-empirical models available with which to evaluate the viscosity of liquid metals and alloys. However, the parameter of mixed energy in these models is not easily determined, and most predictive models have been poorly applied. In the present study, a new thermodynamic parameter Δ G is proposed to predict liquid alloy viscosity. The prediction equation depends on basic physical and thermodynamic parameters, namely density, melting temperature, absolute atomic mass, electro-negativity, electron density, molar volume, Pauling radius, and mixing enthalpy. Our results show that the liquid alloy viscosity predicted using the proposed model is closely in line with the experimental values. In addition, if the component radius difference is greater than 0.03 nm at a certain temperature, the atomic size factor has a significant effect on the interaction of the binary liquid metal atoms. The proposed thermodynamic parameter Δ G also facilitates the study of other physical properties of liquid metals.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

PubMed

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adigun, Babatunde John; Fensin, Michael Lorne; Galloway, Jack D.

Our burnup study examined the effect of a predicted critical control rod position on the nuclide predictability of several axial and radial locations within a 4×4 graphite moderated gas cooled reactor fuel cluster geometry. To achieve this, a control rod position estimator (CRPE) tool was developed within the framework of the linkage code Monteburns between the transport code MCNP and depletion code CINDER90, and four methodologies were proposed within the tool for maintaining criticality. Two of the proposed methods used an inverse multiplication approach - where the amount of fissile material in a set configuration is slowly altered until criticalitymore » is attained - in estimating the critical control rod position. Another method carried out several MCNP criticality calculations at different control rod positions, then used a linear fit to estimate the critical rod position. The final method used a second-order polynomial fit of several MCNP criticality calculations at different control rod positions to guess the critical rod position. The results showed that consistency in prediction of power densities as well as uranium and plutonium isotopics was mutual among methods within the CRPE tool that predicted critical position consistently well. Finall, while the CRPE tool is currently limited to manipulating a single control rod, future work could be geared toward implementing additional criticality search methodologies along with additional features.« less

Impact of the variation in dynamic vehicle load on flexible pavement responses

NASA Astrophysics Data System (ADS)

Ahsanuzzaman, Md

The purpose of this research was to evaluate the dynamic variation in asphalt pavement critical responses due to dynamic tire load variations. An attempt was also made to develop generalized regression equations to predict the dynamic response variation in flexible pavement under various dynamic load conditions. The study used an extensive database of computed pavement response histories for five different types of sites (smooth, rough, medium rough, very rough and severely rough), two different asphalt pavement structures (thin and thick) at two temperatures (70 °F and 104 °F), subjected to a tandem axle dual tire at three speeds 25, 37 and 50 mph (40, 60 and 80 km/h). All pavement responses were determined using the 3D-Move Analysis program (Version 1.2) developed by University of Nevada, Reno. A new term called Dynamic Response Coefficient (DRC) was introduced in this study to address the variation in critical pavement responses due to dynamic loads as traditionally measured by the Dynamic Load Coefficient (DLC). While DLC represents the additional varying component of the tire load, DRC represents the additional varying component of the response value (standard deviation divided by mean response). In this study, DRC was compared with DLC for five different sites based on the roughness condition of the sites. Previous studies showed that DLC varies with vehicle speed and suspension types, and assumes a constant value for the whole pavement structure (lateral and vertical directions). On the other hand, in this study, DRC was found to be significantly varied with the asphalt pavement and function of pavement structure, road roughness conditions, temperatures, vehicle speeds, suspension types, and locations of the point of interest in the pavement. A major contribution of the study is that the variation of pavement responses due to dynamic load in a flexible pavement system can be predicted with generalized regression equations. Fitting parameters (R2) in the rage of 0.60 to 0.87 were observed the DRC predictive equations. In addition, verification of those generalized equations was evaluated using different sets of asphalt pavement structures and pavement materials. The differences between calculated and predicted values were found to be within +/-20% for the maximum tensile strain and +/-30% for the maximum compressive strain in the asphalt layer.

Cross-cultural perspectives on critical thinking.

PubMed

Jenkins, Sheryl Daun

2011-05-01

The purpose of this cross-cultural study was to explore critical thinking among nurse scholars in Thailand and the United States. The study used qualitative methodology to examine how nurse scholars describe critical thinking in nursing. Nurse educators in Thailand and the United States were questioned concerning the following aspects of critical thinking: essential components; teaching and evaluation techniques; characteristics of critical thinkers; and the importance of a consensus definition for critical thinking in nursing. Their statements, which revealed both common and specific cultural aspects of critical thinking, were subjected to content analysis. Certain themes emerged that have not been widely discussed in the literature, including the link between staying calm and thinking critically, the assertion that happiness is an essential component of critical thinking, and the participants' nearly unanimous support for coming to a consensus definition of critical thinking for nursing. Copyright 2011, SLACK Incorporated.

Sensitivity, Specificity, and Predictive Values of Pediatric Metabolic Syndrome Components in Relation to Adult Metabolic Syndrome: The Princeton LRC Follow-up Study

PubMed Central

Huang, Terry T-K; Nansel, Tonja R.; Belsheim, Allen R.; Morrison, John A.

2008-01-01

Objective To estimate the sensitivity, specificity, and predictive values of pediatric metabolic syndrome (MetS) components (obesity, fasting glucose, triglycerides, high-density lipoprotein, and blood pressure) at various cutoffs in relation to adult MetS. Study design Data from the NHLBI Lipid Research Clinics (LRC) Princeton Prevalence Study (1973–76) and the Princeton Follow-up Study (PFS, 2000-4) were used to calculate sensitivity, specificity, and positive and negative predictive values for each component at a given cutoff, as well as for aggregates of components. Results Individual pediatric components alone showed low to moderate sensitivity, high specificity, and moderate predictive values in relation to adult MetS. When all five pediatric MetS components were considered, the presence of at least one abnormality had higher sensitivity for adult MetS than individual components alone. When multiple abnormalities were mandatory for MetS, positive predictive value was high and sensitivity was low. Childhood body mass alone showed neither high sensitivity nor high positive predictive value for adult MetS. Conclusions Considering multiple metabolic variables in childhood can improve the predictive utility for adult MetS, compared to each component or body mass alone. MetS variables may be useful for identifying some at risk children for prevention interventions. PMID:18206687

Maintaining a Critical Spectra within Monteburns for a Gas-Cooled Reactor Array by Way of Control Rod Manipulation

DOE PAGES

Adigun, Babatunde John; Fensin, Michael Lorne; Galloway, Jack D.; ...

2016-10-01

Our burnup study examined the effect of a predicted critical control rod position on the nuclide predictability of several axial and radial locations within a 4×4 graphite moderated gas cooled reactor fuel cluster geometry. To achieve this, a control rod position estimator (CRPE) tool was developed within the framework of the linkage code Monteburns between the transport code MCNP and depletion code CINDER90, and four methodologies were proposed within the tool for maintaining criticality. Two of the proposed methods used an inverse multiplication approach - where the amount of fissile material in a set configuration is slowly altered until criticalitymore » is attained - in estimating the critical control rod position. Another method carried out several MCNP criticality calculations at different control rod positions, then used a linear fit to estimate the critical rod position. The final method used a second-order polynomial fit of several MCNP criticality calculations at different control rod positions to guess the critical rod position. The results showed that consistency in prediction of power densities as well as uranium and plutonium isotopics was mutual among methods within the CRPE tool that predicted critical position consistently well. Finall, while the CRPE tool is currently limited to manipulating a single control rod, future work could be geared toward implementing additional criticality search methodologies along with additional features.« less

Prediction during language comprehension: benefits, costs, and ERP components.

PubMed

Van Petten, Cyma; Luka, Barbara J

2012-02-01

Because context has a robust influence on the processing of subsequent words, the idea that readers and listeners predict upcoming words has attracted research attention, but prediction has fallen in and out of favor as a likely factor in normal comprehension. We note that the common sense of this word includes both benefits for confirmed predictions and costs for disconfirmed predictions. The N400 component of the event-related potential (ERP) reliably indexes the benefits of semantic context. Evidence that the N400 is sensitive to the other half of prediction--a cost for failure--is largely absent from the literature. This raises the possibility that "prediction" is not a good description of what comprehenders do. However, it need not be the case that the benefits and costs of prediction are evident in a single ERP component. Research outside of language processing indicates that late positive components of the ERP are very sensitive to disconfirmed predictions. We review late positive components elicited by words that are potentially more or less predictable from preceding sentence context. This survey suggests that late positive responses to unexpected words are fairly common, but that these consist of two distinct components with different scalp topographies, one associated with semantically incongruent words and one associated with congruent words. We conclude with a discussion of the possible cognitive correlates of these distinct late positivities and their relationships with more thoroughly characterized ERP components, namely the P300, P600 response to syntactic errors, and the "old/new effect" in studies of recognition memory. Copyright © 2011 Elsevier B.V. All rights reserved.

Catastrophic Fault Recovery with Self-Reconfigurable Chips

NASA Technical Reports Server (NTRS)

Zheng, Will Hua; Marzwell, Neville I.; Chau, Savio N.

2006-01-01

Mission critical systems typically employ multi-string redundancy to cope with possible hardware failure. Such systems are only as fault tolerant as there are many redundant strings. Once a particular critical component exhausts its redundant spares, the multi-string architecture cannot tolerate any further hardware failure. This paper aims at addressing such catastrophic faults through the use of 'Self-Reconfigurable Chips' as a last resort effort to 'repair' a faulty critical component.

A stochastic bioenergetics model based approach to translating large river flow and temperature in to fish population responses: The pallid sturgeon example

USGS Publications Warehouse

Wildhaber, Mark L.; Dey, Rima; Wikle, Christopher K.; Moran, Edward H.; Anderson, Christopher J.; Franz, Kristie J.

2015-01-01

In managing fish populations, especially at-risk species, realistic mathematical models are needed to help predict population response to potential management actions in the context of environmental conditions and changing climate while effectively incorporating the stochastic nature of real world conditions. We provide a key component of such a model for the endangered pallid sturgeon (Scaphirhynchus albus) in the form of an individual-based bioenergetics model influenced not only by temperature but also by flow. This component is based on modification of a known individual-based bioenergetics model through incorporation of: the observed ontogenetic shift in pallid sturgeon diet from marcroinvertebrates to fish; the energetic costs of swimming under flowing-water conditions; and stochasticity. We provide an assessment of how differences in environmental conditions could potentially alter pallid sturgeon growth estimates, using observed temperature and velocity from channelized portions of the Lower Missouri River mainstem. We do this using separate relationships between the proportion of maximum consumption and fork length and swimming cost standard error estimates for fish captured above and below the Kansas River in the Lower Missouri River. Critical to our matching observed growth in the field with predicted growth based on observed environmental conditions was a two-step shift in diet from macroinvertebrates to fish.

Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

PubMed Central

Mu, Lin

2018-01-01

This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

Critical role of morphology on the dielectric constant of semicrystalline polyolefins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Misra, Mayank; Kumar, Sanat K., E-mail: sk2794@columbia.edu; Mannodi-Kanakkithodi, Arun

2016-06-21

A particularly attractive method to predict the dielectric properties of materials is density functional theory (DFT). While this method is very popular, its large computational requirements allow practical treatments of unit cells with just a small number of atoms in an ordered array, i.e., in a crystalline morphology. By comparing DFT and Molecular Dynamics (MD) simulations on the same ordered arrays of functional polyolefins, we confirm that both methodologies yield identical estimates for the dipole moments and hence the ionic component of the dielectric storage modulus. Additionally, MD simulations of more realistic semi-crystalline morphologies yield estimates for this polar contributionmore » that are in good agreement with the limited experiments in this field. However, these predictions are up to 10 times larger than those for pure crystalline simulations. Here, we show that the constraints provided by the surrounding chains significantly impede dipolar relaxations in the crystalline regions, whereas amorphous chains must sample all configurations to attain their fully isotropic spatial distributions. These results, which suggest that the amorphous phase is the dominant player in the context, argue strongly that the proper polymer morphology needs to be modeled to ensure accurate estimates of the ionic component of the dielectric constant.« less

Cortical Brain Activity Reflecting Attentional Biasing Toward Reward-Predicting Cues Covaries with Economic Decision-Making Performance

PubMed Central

San Martín, René; Appelbaum, Lawrence G.; Huettel, Scott A.; Woldorff, Marty G.

2016-01-01

Adaptive choice behavior depends critically on identifying and learning from outcome-predicting cues. We hypothesized that attention may be preferentially directed toward certain outcome-predicting cues. We studied this possibility by analyzing event-related potential (ERP) responses in humans during a probabilistic decision-making task. Participants viewed pairs of outcome-predicting visual cues and then chose to wager either a small (i.e., loss-minimizing) or large (i.e., gain-maximizing) amount of money. The cues were bilaterally presented, which allowed us to extract the relative neural responses to each cue by using a contralateral-versus-ipsilateral ERP contrast. We found an early lateralized ERP response, whose features matched the attention-shift-related N2pc component and whose amplitude scaled with the learned reward-predicting value of the cues as predicted by an attention-for-reward model. Consistently, we found a double dissociation involving the N2pc. Across participants, gain-maximization positively correlated with the N2pc amplitude to the most reliable gain-predicting cue, suggesting an attentional bias toward such cues. Conversely, loss-minimization was negatively correlated with the N2pc amplitude to the most reliable loss-predicting cue, suggesting an attentional avoidance toward such stimuli. These results indicate that learned stimulus–reward associations can influence rapid attention allocation, and that differences in this process are associated with individual differences in economic decision-making performance. PMID:25139941

Clustering analysis of water distribution systems: identifying critical components and community impacts.

PubMed

Diao, K; Farmani, R; Fu, G; Astaraie-Imani, M; Ward, S; Butler, D

2014-01-01

Large water distribution systems (WDSs) are networks with both topological and behavioural complexity. Thereby, it is usually difficult to identify the key features of the properties of the system, and subsequently all the critical components within the system for a given purpose of design or control. One way is, however, to more explicitly visualize the network structure and interactions between components by dividing a WDS into a number of clusters (subsystems). Accordingly, this paper introduces a clustering strategy that decomposes WDSs into clusters with stronger internal connections than external connections. The detected cluster layout is very similar to the community structure of the served urban area. As WDSs may expand along with urban development in a community-by-community manner, the correspondingly formed distribution clusters may reveal some crucial configurations of WDSs. For verification, the method is applied to identify all the critical links during firefighting for the vulnerability analysis of a real-world WDS. Moreover, both the most critical pipes and clusters are addressed, given the consequences of pipe failure. Compared with the enumeration method, the method used in this study identifies the same group of the most critical components, and provides similar criticality prioritizations of them in a more computationally efficient time.

Predictive techniques for river channel evolution and maintenance

USGS Publications Warehouse

Nelson, J.M.

1996-01-01

Predicting changes in alluvial channel morphology associated with anthropogenic and natural changes in flow and/or sediment supply is a critical part of the management of riverine systems. Over the past few years, advances in the understanding of the physics of sediment transport in conjunction with rapidly increasing capabilities in computational fluid dynamics have yielded now approaches to problems in river mechanics. Techniques appropriate for length scales ranging from reaches to bars and bedforms are described here. Examples of the use of these computational approaches are discussed for three cases: (1) the design of diversion scenarios that maintain channel morphology in steep cobble-bedded channels in Colorado, (2) determination of channel maintenance flows for the preservation of channel islands in the Snake River in Idaho, and (3) prediction of the temporal evolution of deposits in lateral separation zones for future assessment of the impacts of various dam release scenarios on lateral separation deposits in the Colorado River in Grand Canyon. With continued development of their scientific and technical components, the methodologies described here can provide powerful tools for the management of river environments in the future.

Analysis of Propagation Plans in NSF-Funded Education Development Projects

NASA Astrophysics Data System (ADS)

Stanford, Courtney; Cole, Renee; Froyd, Jeff; Henderson, Charles; Friedrichsen, Debra; Khatri, Raina

2017-08-01

Increasing adoption and adaptation of promising instructional strategies and materials has been identified as a critical component needed to improve science, technology, engineering, and mathematics (STEM) education. This paper examines typical propagation practices and resulting outcomes of proposals written by developers of educational innovations. These proposals were analyzed using the Designing for Sustained Adoption Assessment Instrument (DSAAI), an instrument developed to evaluate propagation plans, and the results used to predict the likelihood that a successful project would result in adoption by others. We found that few education developers propose strong propagation plans. Afterwards, a follow-up analysis was conducted to see which propagation strategies developers actually used to help develop, disseminate, and support their innovations. A web search and interviews with principal investigators were used to determine the degree to which propagation plans were actually implemented and to estimate adoption of the innovations. In this study, we analyzed 71 education development proposals funded by the National Science Foundation and predicted that 80% would be unsuccessful in propagating their innovations. Follow-up data collection with a subset of these suggests that the predictions were reasonably accurate.

Environment enhanced fatigue crack propagation in metals: Inputs to fracture mechanics life prediction models

NASA Technical Reports Server (NTRS)

Gangloff, Richard P.; Kim, Sang-Shik

1993-01-01

This report is a critical review of both environment-enhanced fatigue crack propagation data and the predictive capabilities of crack growth rate models. This information provides the necessary foundation for incorporating environmental effects in NASA FLAGRO and will better enable predictions of aerospace component fatigue lives. The review presents extensive literature data on 'stress corrosion cracking and corrosion fatigue.' The linear elastic fracture mechanics approach, based on stress intensity range (Delta(K)) similitude with microscopic crack propagation threshold and growth rates, provides a basis for these data. Results are presented showing enhanced growth rates for gases (viz., H2 and H2O) and electrolytes (e.g. NaCl and H2O) in aerospace alloys including: C-Mn and heat treated alloy steels, aluminum alloys, nickel-based superalloys, and titanium alloys. Environment causes purely time-dependent accelerated fatigue crack growth above the monotonic load cracking threshold (KIEAC) and promotes cycle-time dependent cracking below (KIEAC). These phenomenon are discussed in terms of hydrogen embrittlement, dissolution, and film rupture crack tip damage mechanisms.

Frontal top-down signals increase coupling of auditory low-frequency oscillations to continuous speech in human listeners.

PubMed

Park, Hyojin; Ince, Robin A A; Schyns, Philippe G; Thut, Gregor; Gross, Joachim

2015-06-15

Humans show a remarkable ability to understand continuous speech even under adverse listening conditions. This ability critically relies on dynamically updated predictions of incoming sensory information, but exactly how top-down predictions improve speech processing is still unclear. Brain oscillations are a likely mechanism for these top-down predictions [1, 2]. Quasi-rhythmic components in speech are known to entrain low-frequency oscillations in auditory areas [3, 4], and this entrainment increases with intelligibility [5]. We hypothesize that top-down signals from frontal brain areas causally modulate the phase of brain oscillations in auditory cortex. We use magnetoencephalography (MEG) to monitor brain oscillations in 22 participants during continuous speech perception. We characterize prominent spectral components of speech-brain coupling in auditory cortex and use causal connectivity analysis (transfer entropy) to identify the top-down signals driving this coupling more strongly during intelligible speech than during unintelligible speech. We report three main findings. First, frontal and motor cortices significantly modulate the phase of speech-coupled low-frequency oscillations in auditory cortex, and this effect depends on intelligibility of speech. Second, top-down signals are significantly stronger for left auditory cortex than for right auditory cortex. Third, speech-auditory cortex coupling is enhanced as a function of stronger top-down signals. Together, our results suggest that low-frequency brain oscillations play a role in implementing predictive top-down control during continuous speech perception and that top-down control is largely directed at left auditory cortex. This suggests a close relationship between (left-lateralized) speech production areas and the implementation of top-down control in continuous speech perception. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Frontal Top-Down Signals Increase Coupling of Auditory Low-Frequency Oscillations to Continuous Speech in Human Listeners

PubMed Central

Park, Hyojin; Ince, Robin A.A.; Schyns, Philippe G.; Thut, Gregor; Gross, Joachim

2015-01-01

Summary Humans show a remarkable ability to understand continuous speech even under adverse listening conditions. This ability critically relies on dynamically updated predictions of incoming sensory information, but exactly how top-down predictions improve speech processing is still unclear. Brain oscillations are a likely mechanism for these top-down predictions [1, 2]. Quasi-rhythmic components in speech are known to entrain low-frequency oscillations in auditory areas [3, 4], and this entrainment increases with intelligibility [5]. We hypothesize that top-down signals from frontal brain areas causally modulate the phase of brain oscillations in auditory cortex. We use magnetoencephalography (MEG) to monitor brain oscillations in 22 participants during continuous speech perception. We characterize prominent spectral components of speech-brain coupling in auditory cortex and use causal connectivity analysis (transfer entropy) to identify the top-down signals driving this coupling more strongly during intelligible speech than during unintelligible speech. We report three main findings. First, frontal and motor cortices significantly modulate the phase of speech-coupled low-frequency oscillations in auditory cortex, and this effect depends on intelligibility of speech. Second, top-down signals are significantly stronger for left auditory cortex than for right auditory cortex. Third, speech-auditory cortex coupling is enhanced as a function of stronger top-down signals. Together, our results suggest that low-frequency brain oscillations play a role in implementing predictive top-down control during continuous speech perception and that top-down control is largely directed at left auditory cortex. This suggests a close relationship between (left-lateralized) speech production areas and the implementation of top-down control in continuous speech perception. PMID:26028433

Trial watch

PubMed Central

Senovilla, Laura; Vacchelli, Erika; Galon, Jerome; Adjemian, Sandy; Eggermont, Alexander; Fridman, Wolf Hervé; Sautès-Fridman, Catherine; Ma, Yuting; Tartour, Eric; Zitvogel, Laurence; Kroemer, Guido; Galluzzi, Lorenzo

2012-01-01

Solid tumors are constituted of a variety of cellular components, including bona fide malignant cells as well as endothelial, structural and immune cells. On one hand, the tumor stroma exerts major pro-tumorigenic and immunosuppressive functions, reflecting the capacity of cancer cells to shape the microenvironment to satisfy their own metabolic and immunological needs. On the other hand, there is a component of tumor-infiltrating leucocytes (TILs) that has been specifically recruited in the attempt to control tumor growth. Along with the recognition of the critical role played by the immune system in oncogenesis, tumor progression and response to therapy, increasing attention has been attracted by the potential prognostic and/or predictive role of the immune infiltrate in this setting. Data from large clinical studies demonstrate indeed that a robust infiltration of neoplastic lesions by specific immune cell populations, including (but not limited to) CD8+ cytotoxic T lymphocytes, Th1 and Th17 CD4+ T cells, natural killer cells, dendritic cells, and M1 macrophages constitutes an independent prognostic indicator in several types of cancer. Conversely, high levels of intratumoral CD4+CD25+FOXP3+ regulatory T cells, Th2 CD4+ T cells, myeloid-derived suppressor cells, M2 macrophages and neutrophils have frequently been associated with dismal prognosis. So far, only a few studies have addressed the true predictive potential of TILs in cancer patients, generally comforting the notion that—at least in some clinical settings—the immune infiltrate can reliably predict if a specific patient will respond to therapy or not. In this Trial Watch, we will summarize the results of clinical trials that have evaluated/are evaluating the prognostic and predictive value of the immune infiltrate in the context of solid malignancies. PMID:23243596

Evaluation of concentrations of pharmaceuticals detected in sewage influents in Japan by using annual shipping and sales data.

PubMed

Azuma, Takashi; Nakada, Norihide; Yamashita, Naoyuki; Tanaka, Hiroaki

2015-11-01

A year-round monitoring survey of sewage flowing into sewage treatment plants located in urban Japan was conducted by targeting seven representative pharmaceutical components-atenolol (ATL), ciprofloxacin (CFX), clarithromycin (CTM), diclofenac (DCF), diltiazem (DTZ), disopyramide (DSP), and sulpiride (SPR)-detected in the river environment. For each of these components, two types of predicted concentration were estimated on the basis of two types of data (the shipping volume and sales volume of each component). The measured concentration of each component obtained through the survey and the two types of estimated predicted concentration of each component were then compared. The correspondence ratio between the predicted concentration estimated from the shipping volume of the component and the measured concentration (predicted concentration/measured concentration) was, for ATL, 3.1; CFX, 1.4; CTM, 1.4; DCF, 0.2; DTZ, 0.9; DSP, 11.6; and SPR, 1.1. The correspondence ratio between the predicted concentration estimated from the sales volume of the component and the measured concentration was, for ATL, 0.5; CFX, 1.1; CTM, 0.8; DCF, 0.1; DTZ, 0.2; DSP, 0.7; and SPR, 0.8. Although a generally corresponding trend was seen regardless of whether the prediction was based on shipping volume or sales volume, the predicted concentrations estimated from the shipping volumes of all components expect DSP were found, to our knowledge for the first time in Japan, to correspond better than those based on sales volumes to the measured concentrations. These findings should help to improve the prediction accuracy of concentrations of pharmaceutical components in river waters. Copyright © 2015 Elsevier Ltd. All rights reserved.

14 CFR 45.14 - Identification of critical components.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Identification of critical components. 45.14 Section 45.14 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT IDENTIFICATION AND REGISTRATION MARKING Identification of Aircraft and Related Products § 45.14...

14 CFR 45.14 - Identification of critical components.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Identification of critical components. 45.14 Section 45.14 Aeronautics and Space FEDERAL AVIATION ADMINISTRATION, DEPARTMENT OF TRANSPORTATION AIRCRAFT IDENTIFICATION AND REGISTRATION MARKING Marking of Products and Articles § 45.14 Identification of...

A method for identifying EMI critical circuits during development of a large C3

NASA Astrophysics Data System (ADS)

Barr, Douglas H.

The circuit analysis methods and process Boeing Aerospace used on a large, ground-based military command, control, and communications (C3) system are described. This analysis was designed to help identify electromagnetic interference (EMI) critical circuits. The methodology used the MIL-E-6051 equipment criticality categories as the basis for defining critical circuits, relational database technology to help sort through and account for all of the approximately 5000 system signal cables, and Macintosh Plus personal computers to predict critical circuits based on safety margin analysis. The EMI circuit analysis process systematically examined all system circuits to identify which ones were likely to be EMI critical. The process used two separate, sequential safety margin analyses to identify critical circuits (conservative safety margin analysis, and detailed safety margin analysis). These analyses used field-to-wire and wire-to-wire coupling models using both worst-case and detailed circuit parameters (physical and electrical) to predict circuit safety margins. This process identified the predicted critical circuits that could then be verified by test.

Decreases in perceived maternal criticism predict improvement in subthreshold psychotic symptoms in a randomized trial of family-focused therapy for individuals at clinical high risk for psychosis.

PubMed

O'Brien, Mary P; Miklowitz, David J; Cannon, Tyrone D

2015-12-01

Perceived criticism (PC) is a measure of how much criticism from 1 family member "gets through" to another. PC ratings have been found to predict the course of psychotic disorders, but questions remain regarding whether psychosocial treatment can effectively decrease PC, and whether reductions in PC predict symptom improvement. In a sample of individuals at high risk for psychosis, we examined a) whether Family Focused Therapy for Clinical High-Risk (FFT-CHR), an 18-session intervention that consists of psychoeducation and training in communication and problem solving, brought about greater reductions in perceived maternal criticism, compared to a 3-session family psychoeducational intervention; and b) whether reductions in PC from baseline to 6-month reassessment predicted decreases in subthreshold positive symptoms of psychosis at 12-month follow-up. This study was conducted within a randomized controlled trial across 8 sites. The perceived criticism scale was completed by 90 families prior to treatment and by 41 families at 6-month reassessment. Evaluators, blind to treatment condition, rated subthreshold symptoms of psychosis at baseline, 6- and 12-month assessments. Perceived maternal criticism decreased from pre- to posttreatment for both treatment groups, and this change in criticism predicted decreases in subthreshold positive symptoms at 12-month follow-up. This study offers evidence that participation in structured family treatment is associated with improvement in perceptions of the family environment. Further, a brief measure of perceived criticism may be useful in predicting the future course of attenuated symptoms of psychosis for CHR youth. (c) 2015 APA, all rights reserved).

Gradient Theory simulations of pure fluid interfaces using a generalized expression for influence parameters and a Helmholtz energy equation of state for fundamentally consistent two-phase calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dahms, Rainer N.

2014-12-31

The fidelity of Gradient Theory simulations depends on the accuracy of saturation properties and influence parameters, and require equations of state (EoS) which exhibit a fundamentally consistent behavior in the two-phase regime. Widely applied multi-parameter EoS, however, are generally invalid inside this region. Hence, they may not be fully suitable for application in concert with Gradient Theory despite their ability to accurately predict saturation properties. The commonly assumed temperature-dependence of pure component influence parameters usually restricts their validity to subcritical temperature regimes. This may distort predictions for general multi-component interfaces where temperatures often exceed the critical temperature of vapor phasemore » components. Then, the calculation of influence parameters is not well defined. In this paper, one of the first studies is presented in which Gradient Theory is combined with a next-generation Helmholtz energy EoS which facilitates fundamentally consistent calculations over the entire two-phase regime. Illustrated on pentafluoroethane as an example, reference simulations using this method are performed. They demonstrate the significance of such high-accuracy and fundamentally consistent calculations for the computation of interfacial properties. These reference simulations are compared to corresponding results from cubic PR EoS, widely-applied in combination with Gradient Theory, and mBWR EoS. The analysis reveals that neither of those two methods succeeds to consistently capture the qualitative distribution of obtained key thermodynamic properties in Gradient Theory. Furthermore, a generalized expression of the pure component influence parameter is presented. This development is informed by its fundamental definition based on the direct correlation function of the homogeneous fluid and by presented high-fidelity simulations of interfacial density profiles. As a result, the new model preserves the accuracy of previous temperature-dependent expressions, remains well-defined at supercritical temperatures, and is fully suitable for calculations of general multi-component two-phase interfaces.« less

Setting the vision: applied patient-reported outcomes and smart, connected digital healthcare systems to improve patient-centered outcomes prediction in critical illness.

PubMed

Wysham, Nicholas G; Abernethy, Amy P; Cox, Christopher E

2014-10-01

Prediction models in critical illness are generally limited to short-term mortality and uncommonly include patient-centered outcomes. Current outcome prediction tools are also insensitive to individual context or evolution in healthcare practice, potentially limiting their value over time. Improved prognostication of patient-centered outcomes in critical illness could enhance decision-making quality in the ICU. Patient-reported outcomes have emerged as precise methodological measures of patient-centered variables and have been successfully employed using diverse platforms and technologies, enhancing the value of research in critical illness survivorship and in direct patient care. The learning health system is an emerging ideal characterized by integration of multiple data sources into a smart and interconnected health information technology infrastructure with the goal of rapidly optimizing patient care. We propose a vision of a smart, interconnected learning health system with integrated electronic patient-reported outcomes to optimize patient-centered care, including critical care outcome prediction. A learning health system infrastructure integrating electronic patient-reported outcomes may aid in the management of critical illness-associated conditions and yield tools to improve prognostication of patient-centered outcomes in critical illness.

Which neuropsychological functions predict various processing speed components in children with and without attention-deficit/hyperactivity disorder?

PubMed

Vadnais, Sarah A; Kibby, Michelle Y; Jagger-Rickels, Audreyana C

2018-01-01

We identified statistical predictors of four processing speed (PS) components in a sample of 151 children with and without attention-deficit/hyperactivity disorder (ADHD). Performance on perceptual speed was predicted by visual attention/short-term memory, whereas incidental learning/psychomotor speed was predicted by verbal working memory. Rapid naming was predictive of each PS component assessed, and inhibition predicted all but one task, suggesting a shared need to identify/retrieve stimuli rapidly and inhibit incorrect responding across PS components. Hence, we found both shared and unique predictors of perceptual, cognitive, and output speed, suggesting more specific terminology should be used in future research on PS in ADHD.

Multiphase Flow Technology Impacts on Thermal Control Systems for Exploration

NASA Technical Reports Server (NTRS)

McQuillen, John; Sankovic, John; Lekan, Jack

2006-01-01

The Two-Phase Flow Facility (TPHIFFy) Project focused on bridging the critical knowledge gap by developing and demonstrating critical multiphase fluid products for advanced life support, thermal management and power conversion systems that are required to enable the Vision for Space Exploration. Safety and reliability of future systems will be enhanced by addressing critical microgravity fluid physics issues associated with flow boiling, condensation, phase separation, and system stability. The project included concept development, normal gravity testing, and reduced gravity aircraft flight campaigns, in preparation for the development of a space flight experiment implementation. Data will be utilized to develop predictive models that could be used for system design and operation. A single fluid, two-phase closed thermodynamic loop test bed was designed, assembled and tested. The major components in this test bed include: a boiler, a condenser, a phase separator and a circulating pump. The test loop was instrumented with flow meters, thermocouples, pressure transducers and both high speed and normal speed video cameras. A low boiling point surrogate fluid, FC-72, was selected based on scaling analyses using preliminary designs for operational systems. Preliminary results are presented which include flow regime transitions and some observations regarding system stability.

Towards a Universal Biology: Is the Origin and Evolution of Life Predictable?

NASA Technical Reports Server (NTRS)

Rothschild, Lynn J.

2017-01-01

The origin and evolution of life seems an unpredictable oddity, based on the quirks of contingency. Celebrated by the late Stephen Jay Gould in several books, "evolution by contingency" has all the adventure of a thriller, but lacks the predictive power of the physical sciences. Not necessarily so, replied Simon Conway Morris, for convergence reassures us that certain evolutionary responses are replicable. The outcome of this debate is critical to Astrobiology. How can we understand where we came from on Earth without prophesy? Further, we cannot design a rational strategy for the search for life elsewhere - or to understand what the future will hold for life on Earth and beyond - without extrapolating from pre-biotic chemistry and evolution. There are several indirect approaches to understanding, and thus describing, what life must be. These include philosophical approaches to defining life (is there even a satisfactory definition of life?), using what we know of physics, chemistry and life to imagine alternate scenarios, using different approaches that life takes as pseudoreplicates (e.g., ribosomal vs non-ribosomal protein synthesis), and experimental approaches to understand the art of the possible. Given that: (1) Life is a process based on physical components rather than simply an object; (2). Life is likely based on organic carbon and needs a solvent for chemistry, most likely water, and (3) Looking for convergence in terrestrial evolution we can predict certain tendencies, if not quite "laws", that provide predictive power. Biological history must obey the laws of physics and chemistry, the principles of natural selection, the constraints of an evolutionary past, genetics, and developmental biology. This amalgam creates a surprising amount of predictive power in the broad outline. Critical is the apparent prevalence of organic chemistry, and uniformity in the universe of the laws of chemistry and physics. Instructive is the widespread occurrence of convergent or parallel evolution, which suggests that under certain conditions similar solutions are arrived at independently.

Improving Prediction of Large-scale Regime Transitions

NASA Astrophysics Data System (ADS)

Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

2017-12-01

Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these synoptic classes, both in the observations and the CFSv2, are investigated. At a future point in the project, the results from these multiscale investigations will be integrated in the form of a prediction tool for important variables (temperatures, precipitation and their extremes) for the 1-4 week timeframe.

Self-criticism and dependency in female adolescents: Prediction of first onsets and disentangling the relationships between personality, stressful life events, and internalizing psychopathology.

PubMed

Kopala-Sibley, Daniel C; Klein, Daniel N; Perlman, Greg; Kotov, Roman

2017-11-01

There is substantial evidence that personality traits, such as self-criticism and dependency, predict the development of depression and anxiety symptoms, as well as depressive episodes. However, it is unknown whether self-criticism and dependency predict the first onset of depressive and anxiety disorders, and unclear how to characterize dynamic mechanisms by which these traits, stressful life events, and psychopathology influence one another over time. In this study, 550 female adolescents were assessed at baseline, 528 and 513 of whom were assessed again at Waves 2 and 3, respectively, over the course of 18 months. Self-criticism and dependency were assessed with self-report inventories, depressive and anxiety disorders were assessed with diagnostic interviews, and stressful life events were assessed via semistructured interview. Logistic regression analyses showed that self-criticism and dependency significantly predicted the first onset of nearly all depressive and anxiety disorders (significant polychoric r s ranged from .15-.42). Subsequent path analyses focused on prediction of depression, and supported several conceptual models of personality-stress-psychopathology relationships. In particular, Personality × Stress interactions were evident for both dependency and self-criticism. These interactions took the form of dual vulnerability, such that stressful life events predicted an increased probability of a later depressive disorder only at low levels of each trait. Results suggest the traits of self-criticism and dependency are important to consider in understanding who is at risk for depressive and anxiety disorders. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Tin whiskers in electronic circuits

NASA Astrophysics Data System (ADS)

Stupian, Gary W.

1992-12-01

Fibrous, conducting 'whiskers' often grow on pure tin plating. These tin whiskers have, for many years, been known to pose a reliability problem in electronic circuitry; therefore, the use of pure tin coatings in any critical electronic application is not recommended. Despite the warnings of the experts, tin plating is still found on electronic and mechanical components and problems with whiskers still arise. This document summarizes what is known about the growth of tin whiskers. A number of factors (e.g., coating thickness, plating conditions) are thought to be important in determining whether whiskers will grow. Although tin whiskers have been investigated from some decades, there is still disagreement on the effects of virtually every coating parameter. There is no disagreement, however, on the essential fact that it is very difficult to predict with certainty whether whiskers will grow on any specific tin-plated component, which of course is the basis of the 'experts' advice not to use pure tin plating. If tin-plated components are found in an electronic system, replacement is the safest policy. Some additional recommendations to minimize risk are presented here that may be of use in situations in which replacement of all suspect components is not the option of choice because of cost or schedule constraints.

Current Evidence about Nutrition Support in Cardiac Surgery Patients-What Do We Know?

PubMed

Hill, Aileen; Nesterova, Ekaterina; Lomivorotov, Vladimir; Efremov, Sergey; Goetzenich, Andreas; Benstoem, Carina; Zamyatin, Mikhail; Chourdakis, Michael; Heyland, Daren; Stoppe, Christian

2018-05-11

Nutrition support is increasingly recognized as a clinically relevant aspect of the intensive care treatment of cardiac surgery patients. However, evidence from adequate large-scale studies evaluating its clinical significance for patients’ mid- to long-term outcome remains sparse. Considering nutrition support as a key component in the perioperative treatment of these critically ill patients led us to review and discuss our understanding of the metabolic response to the inflammatory burst induced by cardiac surgery. In addition, we discuss how to identify patients who may benefit from nutrition therapy, when to start nutritional interventions, present evidence about the use of enteral and parenteral nutrition and the potential role of pharmaconutrition in cardiac surgery patients. Although the clinical setting of cardiac surgery provides advantages due to its scheduled insult and predictable inflammatory response, researchers and clinicians face lack of evidence and several limitations in the clinical routine, which are critically considered and discussed in this paper.

Complex dynamics induced by strong confinement - From tracer diffusion in strongly heterogeneous media to glassy relaxation of dense fluids in narrow slits

NASA Astrophysics Data System (ADS)

Mandal, Suvendu; Spanner-Denzer, Markus; Leitmann, Sebastian; Franosch, Thomas

2017-08-01

We provide an overview of recent advances of the complex dynamics of particles in strong confinements. The first paradigm is the Lorentz model where tracers explore a quenched disordered host structure. Such systems naturally occur as limiting cases of binary glass-forming systems if the dynamics of one component is much faster than the other. For a certain critical density of the host structure the tracers undergo a localization transition which constitutes a critical phenomenon. A series of predictions in the vicinity of the transition have been elaborated and tested versus computer simulations. Analytical progress is achieved for small obstacle densities. The second paradigm is a dense strongly interacting liquid confined to a narrow slab. Then the glass transition depends nonmonotonically on the separation of the plates due to an interplay of local packing and layering. Very small slab widths allow to address certain features of the statics and dynamics analytically.

Use of a New Portable Instrumented Impactor on the NASA Composite Crew Module Damage Tolerance Program

NASA Technical Reports Server (NTRS)

Jackson, Wade C.; Polis, Daniel L.

2014-01-01

Damage tolerance performance is critical to composite structures because surface impacts at relatively low energies may result in a significant strength loss. For certification, damage tolerance criteria require aerospace vehicles to meet design loads while containing damage at critical locations. Data from standard small coupon testing are difficult to apply to larger more complex structures. Due to the complexity of predicting both the impact damage and the residual properties, damage tolerance is demonstrated primarily by testing. A portable, spring-propelled, impact device was developed which allows the impact damage response to be investigated on large specimens, full-scale components, or entire vehicles. During impact, both the force history and projectile velocity are captured. The device was successfully used to demonstrate the damage tolerance performance of the NASA Composite Crew Module. The impactor was used to impact 18 different design features at impact energies up to 35 J. Detailed examples of these results are presented, showing impact force histories, damage inspection results, and response to loading.

Tuning Ising superconductivity with layer and spin-orbit coupling in two-dimensional transition-metal dichalcogenides.

PubMed

de la Barrera, Sergio C; Sinko, Michael R; Gopalan, Devashish P; Sivadas, Nikhil; Seyler, Kyle L; Watanabe, Kenji; Taniguchi, Takashi; Tsen, Adam W; Xu, Xiaodong; Xiao, Di; Hunt, Benjamin M

2018-04-12

Systems simultaneously exhibiting superconductivity and spin-orbit coupling are predicted to provide a route toward topological superconductivity and unconventional electron pairing, driving significant contemporary interest in these materials. Monolayer transition-metal dichalcogenide (TMD) superconductors in particular lack inversion symmetry, yielding an antisymmetric form of spin-orbit coupling that admits both spin-singlet and spin-triplet components of the superconducting wavefunction. Here, we present an experimental and theoretical study of two intrinsic TMD superconductors with large spin-orbit coupling in the atomic layer limit, metallic 2H-TaS 2 and 2H-NbSe 2 . We investigate the superconducting properties as the material is reduced to monolayer thickness and show that high-field measurements point to the largest upper critical field thus reported for an intrinsic TMD superconductor. In few-layer samples, we find the enhancement of the upper critical field is sustained by the dominance of spin-orbit coupling over weak interlayer coupling, providing additional candidate systems for supporting unconventional superconducting states in two dimensions.

Selfbound quantum droplets

NASA Astrophysics Data System (ADS)

Langen, Tim; Wenzel, Matthias; Schmitt, Matthias; Boettcher, Fabian; Buehner, Carl; Ferrier-Barbut, Igor; Pfau, Tilman

2017-04-01

Self-bound many-body systems are formed through a balance of attractive and repulsive forces and occur in many physical scenarios. Liquid droplets are an example of a self-bound system, formed by a balance of the mutual attractive and repulsive forces that derive from different components of the inter-particle potential. On the basis of the recent finding that an unstable bosonic dipolar gas can be stabilized by a repulsive many-body term, it was predicted that three-dimensional self-bound quantum droplets of magnetic atoms should exist. Here we report on the observation of such droplets using dysprosium atoms, with densities 108 times lower than a helium droplet, in a trap-free levitation field. We find that this dilute magnetic quantum liquid requires a minimum, critical number of atoms, below which the liquid evaporates into an expanding gas as a result of the quantum pressure of the individual constituents. Consequently, around this critical atom number we observe an interaction-driven phase transition between a gas and a self-bound liquid in the quantum degenerate regime with ultracold atoms.

Change in Maternal Criticism and Behavior Problems in Adolescents and Adults with Autism Across a Seven-Year Period

PubMed Central

Baker, Jason K.; Smith, Leann E.; Greenberg, Jan S.; Seltzer, Marsha Mailick; Taylor, Julie Lounds

2010-01-01

In a previous study from our laboratory, high levels of maternal criticism predicted increased behavior problems in adolescents and adults with autism spectrum disorders (ASD) over an 18-month period (Greenberg, Seltzer, Hong, & Orsmond, 2006). The current investigation followed these families over a period of seven years to examine the longitudinal course of criticism and behavior problems, to assess the association between their trajectories, and to determine the degree to which change in each of these factors predicted levels of criticism and behavior problems at the end of the study period. A sample of 118 mothers co-residing with their adolescents and adults with ASD provided open-ended narratives about their children and reported on the children's behavior problems at four waves. Maternal criticism was derived from expressed emotion ratings of the narratives. Criticism exhibited low but significant stability over the seven year period and behavior problems exhibited high stability. Using latent growth curve modeling, (a) criticism was found to have increased over time, but only for the group of families in which the sons or daughters transitioned from high school services during the study period, (b) individual changes in criticism and behavior problems were positively correlated over the seven-year period, and (c) changes in criticism predicted levels of behavior problems at the conclusion of the study. Changes in behavior problems were not predictive of end levels of criticism. Implications for intervention and prevention efforts are discussed. PMID:21319925

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability

PubMed Central

Boudewyn, Megan A.; Long, Debra L.; Traxler, Matthew J.; Lesh, Tyler A.; Dave, Shruti; Mangun, George R.; Carter, Cameron S.; Swaab, Tamara Y.

2016-01-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners’ sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension. PMID:26401815

Crack Instability Predictions Using a Multi-Term Approach

NASA Technical Reports Server (NTRS)

Zanganeh, Mohammad; Forman, Royce G.

2015-01-01

Present crack instability analysis for fracture critical flight hardware is normally performed using a single parameter, K(sub C), fracture toughness value obtained from standard ASTM 2D geometry test specimens made from the appropriate material. These specimens do not sufficiently match the boundary conditions and the elastic-plastic constraint characteristics of the hardware component, and also, the crack instability of most commonly used aircraft and aerospace structural materials have some amount of stable crack growth before fracture which makes the normal use of a K(sub C) single parameter toughness value highly approximate. In the past, extensive studies have been conducted to improve the single parameter (K or J controlled) approaches by introducing parameters accounting for the geometry or in-plane constraint effects. Using 'J-integral' and 'A' parameter as a measure of constraint is one of the most accurate elastic-plastic crack solutions currently available. In this work the feasibility of the J-A approach for prediction of the crack instability was investigated first by ignoring the effects of stable crack growth i.e. using a critical J and A and second by considering the effects of stable crack growth using the corrected J-delta a using the 'A' parameter. A broad range of initial crack lengths and a wide range of specimen geometries including C(T), M(T), ESE(T), SE(T), Double Edge Crack (DEC), Three-Hole-Tension (THT) and NC (crack from a notch) manufactured from Al7075 were studied. Improvements in crack instability predictions were observed compared to the other methods available in the literature.

Sensitivity to Referential Ambiguity in Discourse: The Role of Attention, Working Memory, and Verbal Ability.

PubMed

Boudewyn, Megan A; Long, Debra L; Traxler, Matthew J; Lesh, Tyler A; Dave, Shruti; Mangun, George R; Carter, Cameron S; Swaab, Tamara Y

2015-12-01

The establishment of reference is essential to language comprehension. The goal of this study was to examine listeners' sensitivity to referential ambiguity as a function of individual variation in attention, working memory capacity, and verbal ability. Participants listened to stories in which two entities were introduced that were either very similar (e.g., two oaks) or less similar (e.g., one oak and one elm). The manipulation rendered an anaphor in a subsequent sentence (e.g., oak) ambiguous or unambiguous. EEG was recorded as listeners comprehended the story, after which participants completed tasks to assess working memory, verbal ability, and the ability to use context in task performance. Power in the alpha and theta frequency bands when listeners received critical information about the discourse entities (e.g., oaks) was used to index attention and the involvement of the working memory system in processing the entities. These measures were then used to predict an ERP component that is sensitive to referential ambiguity, the Nref, which was recorded when listeners received the anaphor. Nref amplitude at the anaphor was predicted by alpha power during the earlier critical sentence: Individuals with increased alpha power in ambiguous compared with unambiguous stories were less sensitive to the anaphor's ambiguity. Verbal ability was also predictive of greater sensitivity to referential ambiguity. Finally, increased theta power in the ambiguous compared with unambiguous condition was associated with higher working-memory span. These results highlight the role of attention and working memory in referential processing during listening comprehension.

Assessing the Spectrum of Germline Variation in Fanconi Anemia Genes among Patients with Head and Neck Carcinoma before Age 50

PubMed Central

Chandrasekharappa, Settara C.; Chinn, Steven B.; Donovan, Frank X.; Chowdhury, Naweed I.; Kamat, Aparna; Adeyemo, Adebowale A.; Thomas, James W.; Vemulapalli, Meghana; Hussey, Caroline S.; Reid, Holly H.; Mullikin, James C.; Wei, Qingyi; Sturgis, Erich M.

2018-01-01

Patients with Fanconi anemia (FA) have increased risk for head and neck squamous cell carcinoma (HNSCC). We sought to determine the prevalence of undiagnosed FA and FA carriers in patients with HNSCC and an age cutoff for FA genetic screening. Screening germline DNA from 417 HNSCC patients under age 50 revealed 194 FA gene variants in 185 patients (44%). The variant spectrum was comprised of 183 nonsynonymous point mutations, nine indels, one large deletion, and one synonymous variant predicted to effect splicing. 108 patients (26%) had at least one rare variant predicted to be damaging, and 57 (14%) had at least one rare variant predicted to be damaging and previously reported. Fifteen patients carried two rare variants, or an X-linked variant, in an FA gene. Overall, we did not identify an age cutoff for FA screening among young HNSCC patients, as there were no significant differences in mutation rates when patients were stratified by age, tumor site, ethnicity, smoking status, or human papillomavirus status. However, we observed an increased burden, or mutation load, of FA gene variants in FANCD2, FANCE, and FANCL in our HNSCC patient cohort relative to the 1000 Genomes population. FANCE and FANCL, components of the core complex, are known to be responsible for the recruitment and ubiquitination, respectively, of FANCD2, a critical step in the FA DNA repair pathway. FA germline functional variants offer a novel area of study in HNSCC tumorigenesis, and the increased mutation burden of critical genes indicates the importance of the FA pathway in HNSCC. PMID:28678401

Real Time Land-Surface Hydrologic Modeling Over Continental US

NASA Technical Reports Server (NTRS)

Houser, Paul R.

1998-01-01

The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

Blind predictions of protein interfaces by docking calculations in CAPRI.

PubMed

Lensink, Marc F; Wodak, Shoshana J

2010-11-15

Reliable prediction of the amino acid residues involved in protein-protein interfaces can provide valuable insight into protein function, and inform mutagenesis studies, and drug design applications. A fast-growing number of methods are being proposed for predicting protein interfaces, using structural information, energetic criteria, or sequence conservation or by integrating multiple criteria and approaches. Overall however, their performance remains limited, especially when applied to nonobligate protein complexes, where the individual components are also stable on their own. Here, we evaluate interface predictions derived from protein-protein docking calculations. To this end we measure the overlap between the interfaces in models of protein complexes submitted by 76 participants in CAPRI (Critical Assessment of Predicted Interactions) and those of 46 observed interfaces in 20 CAPRI targets corresponding to nonobligate complexes. Our evaluation considers multiple models for each target interface, submitted by different participants, using a variety of docking methods. Although this results in a substantial variability in the prediction performance across participants and targets, clear trends emerge. Docking methods that perform best in our evaluation predict interfaces with average recall and precision levels of about 60%, for a small majority (60%) of the analyzed interfaces. These levels are significantly higher than those obtained for nonobligate complexes by most extant interface prediction methods. We find furthermore that a sizable fraction (24%) of the interfaces in models ranked as incorrect in the CAPRI assessment are actually correctly predicted (recall and precision ≥50%), and that these models contribute to 70% of the correct docking-based interface predictions overall. Our analysis proves that docking methods are much more successful in identifying interfaces than in predicting complexes, and suggests that these methods have an excellent potential of addressing the interface prediction challenge. © 2010 Wiley-Liss, Inc.

30 CFR 27.35 - Tests to determine life of critical components and subassemblies.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Tests to determine life of critical components and subassemblies. 27.35 Section 27.35 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Test...

Student/Scientist Partnerships: A Teacher's Guide To Evaluating the Critical Components.

ERIC Educational Resources Information Center

Evans, Celia A.; Abrams, Eleanor D.; Rock, Barret N.; Spencer, Shannon L.

2001-01-01

Presents a guide to the critical components of partnerships in Students/Scientist Partnerships (SSPs), a project-based instruction. Uses examples from the Forest Watch (FW) program to support the ideas. Focuses on access to experts, workshops, training sessions, student congresses, support materials and research protocols, science education…

30 CFR 27.35 - Tests to determine life of critical components and subassemblies.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Tests to determine life of critical components and subassemblies. 27.35 Section 27.35 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR TESTING, EVALUATION, AND APPROVAL OF MINING PRODUCTS METHANE-MONITORING SYSTEMS Test...

A generalized methodology to characterize composite materials for pyrolysis models

NASA Astrophysics Data System (ADS)

McKinnon, Mark B.

The predictive capabilities of computational fire models have improved in recent years such that models have become an integral part of many research efforts. Models improve the understanding of the fire risk of materials and may decrease the number of expensive experiments required to assess the fire hazard of a specific material or designed space. A critical component of a predictive fire model is the pyrolysis sub-model that provides a mathematical representation of the rate of gaseous fuel production from condensed phase fuels given a heat flux incident to the material surface. The modern, comprehensive pyrolysis sub-models that are common today require the definition of many model parameters to accurately represent the physical description of materials that are ubiquitous in the built environment. Coupled with the increase in the number of parameters required to accurately represent the pyrolysis of materials is the increasing prevalence in the built environment of engineered composite materials that have never been measured or modeled. The motivation behind this project is to develop a systematic, generalized methodology to determine the requisite parameters to generate pyrolysis models with predictive capabilities for layered composite materials that are common in industrial and commercial applications. This methodology has been applied to four common composites in this work that exhibit a range of material structures and component materials. The methodology utilizes a multi-scale experimental approach in which each test is designed to isolate and determine a specific subset of the parameters required to define a material in the model. Data collected in simultaneous thermogravimetry and differential scanning calorimetry experiments were analyzed to determine the reaction kinetics, thermodynamic properties, and energetics of decomposition for each component of the composite. Data collected in microscale combustion calorimetry experiments were analyzed to determine the heats of complete combustion of the volatiles produced in each reaction. Inverse analyses were conducted on sample temperature data collected in bench-scale tests to determine the thermal transport parameters of each component through degradation. Simulations of quasi-one-dimensional bench-scale gasification tests generated from the resultant models using the ThermaKin modeling environment were compared to experimental data to independently validate the models.

Using Pattern Recognition and Discriminance Analysis to Predict Critical Events in Large Signal Databases

NASA Astrophysics Data System (ADS)

Feller, Jens; Feller, Sebastian; Mauersberg, Bernhard; Mergenthaler, Wolfgang

2009-09-01

Many applications in plant management require close monitoring of equipment performance, in particular with the objective to prevent certain critical events. At each point in time, the information available to classify the criticality of the process, is represented through the historic signal database as well as the actual measurement. This paper presents an approach to detect and predict critical events, based on pattern recognition and discriminance analysis.

Critical behavior of the contact process on small-world networks

NASA Astrophysics Data System (ADS)

Ferreira, Ronan S.; Ferreira, Silvio C.

2013-11-01

We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

Sea Level Rise Impacts on Wastewater Treatment Systems Along the U.S. Coasts

NASA Astrophysics Data System (ADS)

Hummel, Michelle A.; Berry, Matthew S.; Stacey, Mark T.

2018-04-01

As sea levels rise, coastal communities will experience more frequent and persistent nuisance flooding, and some low-lying areas may be permanently inundated. Critical components of lifeline infrastructure networks in these areas are also at risk of flooding, which could cause significant service disruptions that extend beyond the flooded zone. Thus, identifying critical infrastructure components that are exposed to sea level rise is an important first step in developing targeted investment in protective actions and enhancing the overall resilience of coastal communities. Wastewater treatment plants are typically located at low elevations near the coastline to minimize the cost of collecting consumed water and discharging treated effluent, which makes them particularly susceptible to coastal flooding. For this analysis, we used geographic information systems to assess the exposure of wastewater infrastructure to various sea level rise projections at the national level. We then estimated the number of people who would lose wastewater services, which could be more than five times as high as previous predictions of the number of people at risk of direct flooding due to sea level rise. We also performed a regional comparison of wastewater exposure to marine and groundwater flooding in the San Francisco Bay Area. Overall, this analysis highlights the widespread exposure of wastewater infrastructure in the United States and demonstrates that local disruptions to infrastructure networks may have far-ranging impacts on areas that do not experience direct flooding.

Airframe self-noise: Four years of research. [aircraft noise reduction for commercial aircraft

NASA Technical Reports Server (NTRS)

Hardin, J. C.

1976-01-01

A critical assessment of the state of the art in airframe self-noise is presented. Full-scale data on the intensity, spectra and directivity of this noise source are evaluated in the light of the comprehensive theory developed by Ffowcs-Williams and Hawkins. Vibration of panels on commercial aircraft is identified as a possible additional source of airframe noise. The present understanding and methods for prediction of other component sources - airfoils, struts, and cavities - are discussed, and areas for further research as well as potential methods for airframe noise reduction are identified. Finally, the various experimental methods which have been developed for airframe noise research are discussed and sample results are presented.

Shaping the future through innovations: From medical imaging to precision medicine.

PubMed

Comaniciu, Dorin; Engel, Klaus; Georgescu, Bogdan; Mansi, Tommaso

2016-10-01

Medical images constitute a source of information essential for disease diagnosis, treatment and follow-up. In addition, due to its patient-specific nature, imaging information represents a critical component required for advancing precision medicine into clinical practice. This manuscript describes recently developed technologies for better handling of image information: photorealistic visualization of medical images with Cinematic Rendering, artificial agents for in-depth image understanding, support for minimally invasive procedures, and patient-specific computational models with enhanced predictive power. Throughout the manuscript we will analyze the capabilities of such technologies and extrapolate on their potential impact to advance the quality of medical care, while reducing its cost. Copyright © 2016 Elsevier B.V. All rights reserved.

Causation and Validation of Nursing Diagnoses: A Middle Range Theory.

PubMed

de Oliveira Lopes, Marcos Venícios; da Silva, Viviane Martins; Herdman, T Heather

2017-01-01

To describe a predictive middle range theory (MRT) that provides a process for validation and incorporation of nursing diagnoses in clinical practice. Literature review. The MRT includes definitions, a pictorial scheme, propositions, causal relationships, and translation to nursing practice. The MRT can be a useful alternative for education, research, and translation of this knowledge into practice. This MRT can assist clinicians in understanding clinical reasoning, based on temporal logic and spectral interaction among elements of nursing classifications. In turn, this understanding will improve the use and accuracy of nursing diagnosis, which is a critical component of the nursing process that forms a basis for nursing practice standards worldwide. © 2015 NANDA International, Inc.

An innovative spraying setup to obtain uniform salt(s) mixture deposition to investigate hot corrosion

NASA Astrophysics Data System (ADS)

Mannava, Venkateswararao; Swaminathan, A. Vignesh; Kamaraj, M.; Kottada, Ravi Sankar

2016-02-01

A hot corrosion study via molten salt deposition and its interaction with creep/fatigue play a critical role in predicting the life of gas turbine engine components. To do systematic hot corrosion studies, deposition of molten salts on specimens should be uniform with good adherence. Thus, the present study describes an in-house developed spraying setup that produces uniform and reliable molten salt deposition in a repeatable fashion. The efficacy of the present method was illustrated by depositing 90 wt. % Na2SO4 + 5 wt. % NaCl + 5 wt. % NaV O3 salt mixture on hot corrosion coupons and on creep specimens, and also by comparing with other deposition methods.

The Role of Parents' Critical Thinking About Media in Shaping Expectancies, Efficacy and Nutrition Behaviors for Families.

PubMed

Austin, Erica Weintraub; Pinkleton, Bruce E; Radanielina-Hita, Marie Louise; Ran, Weina

2015-01-01

A convenience survey completed online by 137 4-H parents in Washington state explored their orientation toward critical thinking regarding media sources and content and its implications for family dietary behaviors. Parents' critical thinking toward media sources predicted their information efficacy about content. Critical thinking toward media content predicted information efficacy about sources, expectancies for parental mediation, and expectancies for family receptiveness to lower-fat dietary changes. Expectancies for receptiveness to dietary changes and expectancies for parental mediation predicted efficacy for implementing healthy dietary practices; this strongly predicted healthy dietary practices. Media-related critical thinking, therefore, indirectly but consistently affected self-reported family dietary behaviors through its effects on efficacy for managing media and expectancies for the family's receptiveness to healthy dietary changes. The results suggest parents' media literacy skills affect their family's dietary behavior. Health campaigns that help parents interpret and manage the media environment may benefit all family members.

Using Machine Learning to Predict MCNP Bias

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grechanuk, Pavel Aleksandrovi

For many real-world applications in radiation transport where simulations are compared to experimental measurements, like in nuclear criticality safety, the bias (simulated - experimental k eff) in the calculation is an extremely important quantity used for code validation. The objective of this project is to accurately predict the bias of MCNP6 [1] criticality calculations using machine learning (ML) algorithms, with the intention of creating a tool that can complement the current nuclear criticality safety methods. In the latest release of MCNP6, the Whisper tool is available for criticality safety analysts and includes a large catalogue of experimental benchmarks, sensitivity profiles,more » and nuclear data covariance matrices. This data, coming from 1100+ benchmark cases, is used in this study of ML algorithms for criticality safety bias predictions.« less

Remote Sensing of a Manipulated Prairie Grassland Experiment to Predict Belowground Processes

NASA Astrophysics Data System (ADS)

Cavender-Bares, J.; Schweiger, A. K.; Hobbie, S. E.; Madritch, M. D.; Wang, Z.; Couture, J. J.; Gamon, J. A.; Townsend, P. A.

2017-12-01

Given the importance of plant biodiversity for providing the ecosystem functions and services on which humans depend, rapid and remote methods of monitoring plant biodiversity across large spatial extents and biological scales are increasingly critical. In North American prairie systems, the ecosystem benefits of diversity are a subject of ongoing investigation and relevance to policy. However, detecting belowground components of ecosystem biodiversity, composition and associated functions are not possible directly through remote sensing. Nevertheless, belowground components of diversity may be linked to aboveground components allowing indirect inferences. Here we test a series of hypotheses about how aboveground functional and chemical diversity and composition of plant communities drive belowground functions, including N mineralization, enzyme activity and microbial biomass, as well as microbial diversity and composition. We hypothesize that the quantity and chemical composition of aboveground inputs to soil drive belowground processes, including decomposition and microbial enzyme activity. We use plant spectra (400 nm to 2500 nm) measured at the leaf and airborne level to determine chemical and functional composition of leaves and canopies in a long-term grassland experiment where diversity is manipulated at the Cedar Creek Ecosystem Science Reserve. We then assess the extent to which belowground chemistry, microbial diversity and composition are predicted from aboveground plant diversity, biomass and chemical composition. We find strong associations between aboveground inputs and belowground enzyme activity and microbial biomass but only weak linkages between aboveground diversity and belowground diversity. We discuss the potential for such approaches and the caveats related to the spatial scale of measurements and spatial resolution of airborne detection.

Hydrate Evolution in Response to Ongoing Environmental Shifts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rempel, Alan

Natural gas hydrates have the potential to become a vital domestic clean-burning energy source. However, past changes in environmental conditions have caused hydrates to become unstable and trigger both massive submarine landslides and the development of crater-like pockmarks, thereby releasing methane into the overlying seawater and atmosphere, where it acts as a powerful greenhouse gas. This project was designed to fill critical gaps in our understanding of domestic hydrate resources and improve forecasts for their response to environmental shifts. Project work can be separated into three interrelated components, each involving the development of predictive mathematical models. The first project componentmore » concerns the role of sediment properties on the development and dissociation of concentrated hydrate anomalies. To this end, we developed numerical models to predict equilibrium solubility of methane in twophase equilibrium with hydrate as a function of measureable porous medium characteristics. The second project component concerned the evolution of hydrate distribution in heterogeneous reservoirs. To this end, we developed numerical models to predict the growth and decay of anomalies in representative physical environments. The third project component concerned the stability of hydrate-bearing slopes under changing environmental conditions. To this end, we developed numerical treatments of pore pressure evolution and consolidation, then used "infinite-slope" analysis to approximate the landslide potential in representative physical environments, and developed a "rate-and-state" frictional formulation to assess the stability of finite slip patches that are hypothesized to develop in response to the dissociation of hydrate anomalies. The increased predictive capabilities that result from this work provide a framework for interpreting field observations of hydrate anomalies in terms of the history of environmental forcing that led to their development. Moreover, by taking explicit account of anomaly dissociation, project results are designed to help improve forecasts for changes in slope stability that could pose significant threats to energy infrastructure, disrupt hydrate reserves, and pollute the atmosphere with vast quantities of methane. This report presents the details of our work and outlines some of the highlights from our findings.« less

New Tool Released for Engine-Airframe Blade-Out Structural Simulations

NASA Technical Reports Server (NTRS)

Lawrence, Charles

2004-01-01

Researchers at the NASA Glenn Research Center have enhanced a general-purpose finite element code, NASTRAN, for engine-airframe structural simulations during steady-state and transient operating conditions. For steady-state simulations, the code can predict critical operating speeds, natural modes of vibration, and forced response (e.g., cabin noise and component fatigue). The code can be used to perform static analysis to predict engine-airframe response and component stresses due to maneuver loads. For transient response, the simulation code can be used to predict response due to bladeoff events and subsequent engine shutdown and windmilling conditions. In addition, the code can be used as a pretest analysis tool to predict the results of the bladeout test required for FAA certification of new and derivative aircraft engines. Before the present analysis code was developed, all the major aircraft engine and airframe manufacturers in the United States and overseas were performing similar types of analyses to ensure the structural integrity of engine-airframe systems. Although there were many similarities among the analysis procedures, each manufacturer was developing and maintaining its own structural analysis capabilities independently. This situation led to high software development and maintenance costs, complications with manufacturers exchanging models and results, and limitations in predicting the structural response to the desired degree of accuracy. An industry-NASA team was formed to overcome these problems by developing a common analysis tool that would satisfy all the structural analysis needs of the industry and that would be available and supported by a commercial software vendor so that the team members would be relieved of maintenance and development responsibilities. Input from all the team members was used to ensure that everyone's requirements were satisfied and that the best technology was incorporated into the code. Furthermore, because the code would be distributed by a commercial software vendor, it would be more readily available to engine and airframe manufacturers, as well as to nonaircraft companies that did not previously have access to this capability.

DEFINING THE PLAYERS IN HIGHER-ORDER NETWORKS: PREDICTIVE MODELING FOR REVERSE ENGINEERING FUNCTIONAL INFLUENCE NETWORKS

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDermott, Jason E.; Costa, Michelle N.; Stevens, S.L.

A difficult problem that is currently growing rapidly due to the sharp increase in the amount of high-throughput data available for many systems is that of determining useful and informative causative influence networks. These networks can be used to predict behavior given observation of a small number of components, predict behavior at a future time point, or identify components that are critical to the functioning of the system under particular conditions. In these endeavors incorporating observations of systems from a wide variety of viewpoints can be particularly beneficial, but has often been undertaken with the objective of inferring networks thatmore » are generally applicable. The focus of the current work is to integrate both general observations and measurements taken for a particular pathology, that of ischemic stroke, to provide improved ability to produce useful predictions of systems behavior. A number of hybrid approaches have recently been proposed for network generation in which the Gene Ontology is used to filter or enrich network links inferred from gene expression data through reverse engineering methods. These approaches have been shown to improve the biological plausibility of the inferred relationships determined, but still treat knowledge-based and machine-learning inferences as incommensurable inputs. In this paper, we explore how further improvements may be achieved through a full integration of network inference insights achieved through application of the Gene Ontology and reverse engineering methods with specific reference to the construction of dynamic models of transcriptional regulatory networks. We show that integrating two approaches to network construction, one based on reverse-engineering from conditional transcriptional data, one based on reverse-engineering from in situ hybridization data, and another based on functional associations derived from Gene Ontology, using probabilities can improve results of clustering as evaluated by a predictive model of transcriptional expression levels.« less

De-embedding technique for accurate modeling of compact 3D MMIC CPW transmission lines

NASA Astrophysics Data System (ADS)

Pohan, U. H.; KKyabaggu, P. B.; Sinulingga, E. P.

2018-02-01

Requirement for high-density and high-functionality microwave and millimeter-wave circuits have led to the innovative circuit architectures such as three-dimensional multilayer MMICs. The major advantage of the multilayer techniques is that one can employ passive and active components based on CPW technology. In this work, MMIC Coplanar Waveguide(CPW)components such as Transmission Line (TL) are modeled in their 3D layouts. Main characteristics of CPWTL suffered from the probe pads’ parasitic and resonant frequency effects have been studied. By understanding the parasitic effects, then the novel de-embedding technique are developed accurately in order to predict high frequency characteristics of the designed MMICs. The novel de-embedding technique has shown to be critical in reducing the probe pad parasitic significantly from the model. As results, high frequency characteristics of the designed MMICs have been presented with minimumparasitic effects of the probe pads. The de-embedding process optimises the determination of main characteristics of Compact 3D MMIC CPW transmission lines.

Probabilistic analysis for fatigue strength degradation of materials

NASA Technical Reports Server (NTRS)

Royce, Lola

1989-01-01

This report presents the results of the first year of a research program conducted for NASA-LeRC by the University of Texas at San Antonio. The research included development of methodology that provides a probabilistic treatment of lifetime prediction of structural components of aerospace propulsion systems subjected to fatigue. Material strength degradation models, based on primitive variables, include both a fatigue strength reduction model and a fatigue crack growth model. Linear elastic fracture mechanics is utilized in the latter model. Probabilistic analysis is based on simulation, and both maximum entropy and maximum penalized likelihood methods are used for the generation of probability density functions. The resulting constitutive relationships are included in several computer programs, RANDOM2, RANDOM3, and RANDOM4. These programs determine the random lifetime of an engine component, in mechanical load cycles, to reach a critical fatigue strength or crack size. The material considered was a cast nickel base superalloy, one typical of those used in the Space Shuttle Main Engine.

High-Heat-Flux Cyclic Durability of Thermal and Environmental Barrier Coatings

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Ghosn, Louis L.; Miller, Robert A.

2007-01-01

Advanced ceramic thermal and environmental barrier coatings will play an increasingly important role in future gas turbine engines because of their ability to protect the engine components and further raise engine temperatures. For the supersonic vehicles currently envisioned in the NASA fundamental aeronautics program, advanced gas turbine engines will be used to provide high power density thrust during the extended supersonic flight of the aircraft, while meeting stringent low emission requirements. Advanced ceramic coating systems are critical to the performance, life and durability of the hot-section components of the engine systems. In this work, the laser and burner rig based high-heat-flux testing approaches were developed to investigate the coating cyclic response and failure mechanisms under simulated supersonic long-duration cruise mission. The accelerated coating cracking and delamination mechanism under the engine high-heat-flux, and extended supersonic cruise time conditions will be addressed. A coating life prediction framework may be realized by examining the crack initiation and propagation in conjunction with environmental degradation under high-heat-flux test conditions.

A computer simulation of the turbocharged turbo compounded diesel engine system: A description of the thermodynamic and heat transfer models

NASA Technical Reports Server (NTRS)

Assanis, D. N.; Ekchian, J. E.; Frank, R. M.; Heywood, J. B.

1985-01-01

A computer simulation of the turbocharged turbocompounded direct-injection diesel engine system was developed in order to study the performance characteristics of the total system as major design parameters and materials are varied. Quasi-steady flow models of the compressor, turbines, manifolds, intercooler, and ducting are coupled with a multicylinder reciprocator diesel model, where each cylinder undergoes the same thermodynamic cycle. The master cylinder model describes the reciprocator intake, compression, combustion and exhaust processes in sufficient detail to define the mass and energy transfers in each subsystem of the total engine system. Appropriate thermal loading models relate the heat flow through critical system components to material properties and design details. From this information, the simulation predicts the performance gains, and assesses the system design trade-offs which would result from the introduction of selected heat transfer reduction materials in key system components, over a range of operating conditions.

On the Use of 3dB Qualification Margin for Structural Parts on Expendable Launch Vehicles

NASA Technical Reports Server (NTRS)

Yunis, Isam

2007-01-01

The standard random vibration qualification test used for Expendable Launch Vehicle components is Maximum Predicted Environment (MPE) + 6dB for a duration of 4 times the service life of the part. This can be a severe qualification test for these fatigue-sensitive structures. This paper uses flight data from several launch vehicles to establish that reducing the qualification approach to MPE+3dB for the duration of the peak environment (1x life) is valid for fatigue-sensitive structural components. Items that can be classified as fatigue-sensitive are probes, ducts, tubing, bellows, hoses, and any non-functional structure. Non-functional structure may be flight critical or carry fluid, but it cannot include any moving parts or electronics. This reduced qualification approach does not include primary or secondary structure which would be exclusively designed by peak loads, either transient or quasi-static, that are so large and of so few cycles as to make fatigue a moot point.

Modeling micelle formation and interfacial properties with iSAFT classical density functional theory

NASA Astrophysics Data System (ADS)

Wang, Le; Haghmoradi, Amin; Liu, Jinlu; Xi, Shun; Hirasaki, George J.; Miller, Clarence A.; Chapman, Walter G.

2017-03-01

Surfactants reduce the interfacial tension between phases, making them an important additive in a number of industrial and commercial applications from enhanced oil recovery to personal care products (e.g., shampoo and detergents). To help obtain a better understanding of the dependence of surfactant properties on molecular structure, a classical density functional theory, also known as interfacial statistical associating fluid theory, has been applied to study the effects of surfactant architecture on micelle formation and interfacial properties for model nonionic surfactant/water/oil systems. In this approach, hydrogen bonding is explicitly included. To minimize the free energy, the system minimizes interactions between hydrophobic components and hydrophilic components with water molecules hydrating the surfactant head group. The theory predicts micellar structure, effects of surfactant architecture on critical micelle concentration, aggregation number, and interfacial tension isotherm of surfactant/water systems in qualitative agreement with experimental data. Furthermore, this model is applied to study swollen micelles and reverse swollen micelles that are necessary to understand the formation of a middle-phase microemulsion.

Application of Box-Behnken Design and Response Surface Methodology for Surface Roughness Prediction Model of CP-Ti Powder Metallurgy Components Through WEDM

NASA Astrophysics Data System (ADS)

Das, Arunangsu; Sarkar, Susenjit; Karanjai, Malobika; Sutradhar, Goutam

2018-04-01

The present work was undertaken to investigate and characterize the machining parameters (such as surface roughness, etc.) of uni-axially pressed commercially pure titanium sintered powder metallurgy components. Powder was uni-axially pressed at designated pressure of 840 MPa to form cylindrical samples and the green compacts were sintered at 0.001 mbar for about 4 h with sintering temperature varying from 1350 to 1450 °C. The influence of the sintering temperature, pulse-on and pulse-off time at wire-EDM on the surface roughness of the preforms has been investigated thoroughly. Experiments were conducted under different machining parameters in a CNC operated wire-cut EDM. The surface roughness of the machined surface was measured and critically analysed. The optimum surface roughness was achieved under the conditions of 6 μs pulse-on time, 9 μs pulse-off time and at sintering temperature of 1450 °C.

Anatomy of Culturally Sensitive Interventions Promoting Nutrition and Exercise in Hispanics: A Critical Examination of Existing Literature

PubMed Central

Mier, Nelda; Ory, Marcia G.; Medina, Alvaro A.

2013-01-01

Compared with non-Hispanic Whites, Hispanics experience a disproportionate burden of chronic diseases. Understanding the factors influencing the success of health programs in Hispanics requires a clearer examination of the principles and components of tailored interventions. This research comprises a comprehensive literature review of randomized controlled trials testing nutrition and exercise interventions tailored for Hispanics and an examination of how these interventions were constructed. The review of 18 interventions meeting study criteria suggests that most tailored programs promoting nutrition and exercise in Hispanics are theory driven and are informed by formative research. Also, the findings indicate that salient culturally sensitive intervention components are (a) bilingual and bicultural facilitators and materials, (b) family-based activities, (c) literacy-appropriate materials, and (d) social support. A clear understanding of Hispanic cultural values is also required. Further empirical examination is warranted to determine the factors mediating or predicting the efficacy of culturally sensitive health programs for Hispanics. PMID:19193933

Assessing Students' Critical Thinking Performance: Urging for Measurements Using Multi-Response Format

ERIC Educational Resources Information Center

Ku, Kelly Y. L.

2009-01-01

The current paper discusses ambiguities in critical thinking assessment. The paper first reviews the components of critical thinking. It then discusses the features and issues of commonly used critical thinking tests and to what extend they are made compatible to the conceptualization of critical thinking. The paper argues that critical thinking…

A Preliminary Investigation into Critical Thinking of Urban Xi'an High School Students

ERIC Educational Resources Information Center

Zhou, Qing; Wang, Xiang; Yao, Linna

2007-01-01

This paper reports the development of critical thinking of urban high school students in the Chinese city of Xi'an. It presents the assessment of the students' two components of critical thinking: dispositions towards critical thinking and critical thinking skills, using the California Critical Thinking Disposition Inventory and the California…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Hirt, Evelyn H.; Coles, Garill A.

Advanced small modular reactors (AdvSMRs) can contribute to safe, sustainable, and carbon-neutral energy production. The economics of small reactors (including AdvSMRs) will be impacted by the reduced economy-of-scale savings when compared to traditional light water reactors. The most significant controllable element of the day-to-day costs involves operations and maintenance (O&M). Enhancing affordability of AdvSMRs through technologies that help control O&M costs will be critical to ensuring their practicality for wider deployment.A significant component of O&M costs is the management and mitigation of degradation of components due to their impact on planning maintenance activities and staffing levels. Technologies that help characterizemore » real-time risk of failure of key components are important in this context. Given the possibility of frequently changing AdvSMR plant configurations, approaches are needed to integrate three elements – advanced plant configuration information, equipment condition information, and risk monitors – to provide a measure of risk that is customized for each AdvSMR unit and support real-time decisions on O&M. This article describes an overview of ongoing research into diagnostics/prognostics and enhanced predictive risk monitors (ERM) for this purpose.« less

Sources of hydrocarbons in urban road dust: Identification, quantification and prediction.

PubMed

Mummullage, Sandya; Egodawatta, Prasanna; Ayoko, Godwin A; Goonetilleke, Ashantha

2016-09-01

Among urban stormwater pollutants, hydrocarbons are a significant environmental concern due to their toxicity and relatively stable chemical structure. This study focused on the identification of hydrocarbon contributing sources to urban road dust and approaches for the quantification of pollutant loads to enhance the design of source control measures. The study confirmed the validity of the use of mathematical techniques of principal component analysis (PCA) and hierarchical cluster analysis (HCA) for source identification and principal component analysis/absolute principal component scores (PCA/APCS) receptor model for pollutant load quantification. Study outcomes identified non-combusted lubrication oils, non-combusted diesel fuels and tyre and asphalt wear as the three most critical urban hydrocarbon sources. The site specific variabilities of contributions from sources were replicated using three mathematical models. The models employed predictor variables of daily traffic volume (DTV), road surface texture depth (TD), slope of the road section (SLP), effective population (EPOP) and effective impervious fraction (EIF), which can be considered as the five governing parameters of pollutant generation, deposition and redistribution. Models were developed such that they can be applicable in determining hydrocarbon contributions from urban sites enabling effective design of source control measures. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling vertebrate diversity in Oregon using satellite imagery

NASA Astrophysics Data System (ADS)

Cablk, Mary Elizabeth

Vertebrate diversity was modeled for the state of Oregon using a parametric approach to regression tree analysis. This exploratory data analysis effectively modeled the non-linear relationships between vertebrate richness and phenology, terrain, and climate. Phenology was derived from time-series NOAA-AVHRR satellite imagery for the year 1992 using two methods: principal component analysis and derivation of EROS data center greenness metrics. These two measures of spatial and temporal vegetation condition incorporated the critical temporal element in this analysis. The first three principal components were shown to contain spatial and temporal information about the landscape and discriminated phenologically distinct regions in Oregon. Principal components 2 and 3, 6 greenness metrics, elevation, slope, aspect, annual precipitation, and annual seasonal temperature difference were investigated as correlates to amphibians, birds, all vertebrates, reptiles, and mammals. Variation explained for each regression tree by taxa were: amphibians (91%), birds (67%), all vertebrates (66%), reptiles (57%), and mammals (55%). Spatial statistics were used to quantify the pattern of each taxa and assess validity of resulting predictions from regression tree models. Regression tree analysis was relatively robust against spatial autocorrelation in the response data and graphical results indicated models were well fit to the data.

Critical Factors Explaining the Leadership Performance of High-Performing Principals

ERIC Educational Resources Information Center

Hutton, Disraeli M.

2018-01-01

The study explored critical factors that explain leadership performance of high-performing principals and examined the relationship between these factors based on the ratings of school constituents in the public school system. The principal component analysis with the use of Varimax Rotation revealed that four components explain 51.1% of the…

Reflecting on Reflection as a Critical Component in Service Learning

ERIC Educational Resources Information Center

Bloomquist, Catherine

2015-01-01

Despite the popularity of service learning, it is sometimes criticized for its lack of academic rigor. This piece provides a counterpoint to that argument by describing a LIS service-learning course from the student's perspective. I focus particularly on the role of reflection, a key component in service-learning courses that helps to…

Effective teamwork and communication mitigate task saturation in simulated critical care air transport team missions.

PubMed

Davis, Bradley; Welch, Katherine; Walsh-Hart, Sharon; Hanseman, Dennis; Petro, Michael; Gerlach, Travis; Dorlac, Warren; Collins, Jocelyn; Pritts, Timothy

2014-08-01

Critical Care Air Transport Teams (CCATTs) are a critical component of the United States Air Force evacuation paradigm. This study was conducted to assess the incidence of task saturation in simulated CCATT missions and to determine if there are predictable performance domains. Sixteen CCATTs were studied over a 6-month period. Performance was scored using a tool assessing eight domains of performance. Teams were also assessed during critical events to determine the presence or absence of task saturation and its impact on patient care. Sixteen simulated missions were reviewed and 45 crisis events identified. Task saturation was present in 22/45 (49%) of crisis events. Scoring demonstrated that task saturation was associated with poor performance in teamwork (odds ratio [OR] = 1.96), communication (OR = 2.08), and mutual performance monitoring (OR = 1.9), but not maintenance of guidelines, task management, procedural skill, and equipment management. We analyzed the effect of task saturation on adverse patient outcomes during crisis events. Adverse outcomes occurred more often when teams were task saturated as compared to non-task-saturated teams (91% vs. 23%; RR 4.1, p < 0.0001). Task saturation is observed in simulated CCATT missions. Nontechnical skills correlate with task saturation. Task saturation is associated with worsening physiologic derangements in simulated patients. Reprint & Copyright © 2014 Association of Military Surgeons of the U.S.

Thermal cut-off response modelling of universal motors

NASA Astrophysics Data System (ADS)

Thangaveloo, Kashveen; Chin, Yung Shin

2017-04-01

This paper presents a model to predict the thermal cut-off (TCO) response behaviour in universal motors. The mathematical model includes the calculations of heat loss in the universal motor and the flow characteristics around the TCO component which together are the main parameters for TCO response prediction. In order to accurately predict the TCO component temperature, factors like the TCO component resistance, the effect of ambient, and the flow conditions through the motor are taken into account to improve the prediction accuracy of the model.

Monitoring Damage Accumulation in Ceramic Matrix Composites Using Electrical Resistivity

NASA Technical Reports Server (NTRS)

Smith, Craig E.; Morscher, Gregory N.; Xia, Zhenhai H.

2008-01-01

The electric resistance of woven SiC fiber reinforced SiC matrix composites were measured under tensile loading conditions. The results show that the electrical resistance is closely related to damage and that real-time information about the damage state can be obtained through monitoring of the resistance. Such self-sensing capability provides the possibility of on-board/in-situ damage detection and accurate life prediction for high-temperature ceramic matrix composites. Woven silicon carbide fiber-reinforced silicon carbide (SiC/SiC) ceramic matrix composites (CMC) possess unique properties such as high thermal conductivity, excellent creep resistance, improved toughness, and good environmental stability (oxidation resistance), making them particularly suitable for hot structure applications. In specific, CMCs could be applied to hot section components of gas turbines [1], aerojet engines [2], thermal protection systems [3], and hot control surfaces [4]. The benefits of implementing these materials include reduced cooling air requirements, lower weight, simpler component design, longer service life, and higher thrust [5]. It has been identified in NASA High Speed Research (HSR) program that the SiC/SiC CMC has the most promise for high temperature, high oxidation applications [6]. One of the critical issues in the successful application of CMCs is on-board or insitu assessment of the damage state and an accurate prediction of the remaining service life of a particular component. This is of great concern, since most CMC components envisioned for aerospace applications will be exposed to harsh environments and play a key role in the vehicle s safety. On-line health monitoring can enable prediction of remaining life; thus resulting in improved safety and reliability of structural components. Monitoring can also allow for appropriate corrections to be made in real time, therefore leading to the prevention of catastrophic failures. Most conventional nondestructive evaluation (NDE) techniques such as ultrasonic C-scan, x-ray, thermography, and eddy current are limited since they require structural components of complex geometry to be taken out of service for a substantial length of time for post-damage inspection and assessment. Furthermore, the typical NDE techniques are useful for identifying large interlaminar flaws, but insensitive to CMC materials flaws developed perpendicular to the surface under tensile creep conditions. There are techniques such as piezoelectric sensor [7,8], and optical fiber [9,10] that could be used for on-line health monitoring of CMC structures. However, these systems involve attaching an external sensor or putting special fibers in CMC composites, which would be problematic at high temperature applications.

Phenology prediction component of GypsES

Treesearch

Jesse A. Logan; Lukas P. Schaub; F. William Ravlin

1991-01-01

Prediction of phenology is an important component of most pest management programs, and considerable research effort has been expended toward development of predictive tools for gypsy moth phenology. Although phenological prediction is potentially valuable for timing of spray applications (e.g. Bt, or Gypcheck) and other management activities (e.g. placement and...

Superposition rheology.

PubMed

Dhont, J K; Wagner, N J

2001-02-01

The interpretation of superposition rheology data is still a matter of debate due to lack of understanding of viscoelastic superposition response on a microscopic level. So far, only phenomenological approaches have been described, which do not capture the shear induced microstructural deformation, which is responsible for the viscoelastic behavior to the superimposed flow. Experimentally there are indications that there is a fundamental difference between the viscoelastic response to an orthogonally and a parallel superimposed shear flow. We present theoretical predictions, based on microscopic considerations, for both orthogonal and parallel viscoelastic response functions for a colloidal system of attractive particles near their gas-liquid critical point. These predictions extend to values of the stationary shear rate where the system is nonlinearly perturbed, and are based on considerations on the colloidal particle level. The difference in response to orthogonal and parallel superimposed shear flow can be understood entirely in terms of microstructural distortion, where the anisotropy of the microstructure under shear flow conditions is essential. In accordance with experimental observations we find pronounced negative values for response functions in case of parallel superposition for an intermediate range of frequencies, provided that microstructure is nonlinearly perturbed by the stationary shear component. For the critical colloidal systems considered here, the Kramers-Kronig relations for the superimposed response functions are found to be valid. It is argued, however, that the Kramers-Kronig relations may be violated for systems where the stationary shear flow induces a considerable amount of new microstructure.

Cultivating Critical-Thinking Dispositions throughout the Business Curriculum

ERIC Educational Resources Information Center

Bloch, Janel; Spataro, Sandra E.

2014-01-01

Critical thinking is an essential component of managerial literacy, yet business school graduates struggle to apply critical-thinking skills at work to the level that employers desire. This article argues for a dispositional approach to teaching critical thinking, rooted in cultivating a critical-thinking culture. We suggest a two-pronged approach…

49 CFR 272.101 - Content of a critical incident stress plan.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Content of a critical incident stress plan. 272... RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION CRITICAL INCIDENT STRESS PLANS Plan Components and Approval Process § 272.101 Content of a critical incident stress plan. Each critical incident stress plan...

Critical Thinking in Criminology: Critical Reflections on Learning and Teaching

ERIC Educational Resources Information Center

Howes, Loene M.

2017-01-01

Fostering critical thinking abilities amongst students is one component of preparing them to navigate uncertain and complex social lives and employment circumstances. One conceptualisation of critical thinking, valuable in higher education, draws from critical theory to promote social justice and redress power inequities. This study explored how…

Cortical Brain Activity Reflecting Attentional Biasing Toward Reward-Predicting Cues Covaries with Economic Decision-Making Performance.

PubMed

San Martín, René; Appelbaum, Lawrence G; Huettel, Scott A; Woldorff, Marty G

2016-01-01

Adaptive choice behavior depends critically on identifying and learning from outcome-predicting cues. We hypothesized that attention may be preferentially directed toward certain outcome-predicting cues. We studied this possibility by analyzing event-related potential (ERP) responses in humans during a probabilistic decision-making task. Participants viewed pairs of outcome-predicting visual cues and then chose to wager either a small (i.e., loss-minimizing) or large (i.e., gain-maximizing) amount of money. The cues were bilaterally presented, which allowed us to extract the relative neural responses to each cue by using a contralateral-versus-ipsilateral ERP contrast. We found an early lateralized ERP response, whose features matched the attention-shift-related N2pc component and whose amplitude scaled with the learned reward-predicting value of the cues as predicted by an attention-for-reward model. Consistently, we found a double dissociation involving the N2pc. Across participants, gain-maximization positively correlated with the N2pc amplitude to the most reliable gain-predicting cue, suggesting an attentional bias toward such cues. Conversely, loss-minimization was negatively correlated with the N2pc amplitude to the most reliable loss-predicting cue, suggesting an attentional avoidance toward such stimuli. These results indicate that learned stimulus-reward associations can influence rapid attention allocation, and that differences in this process are associated with individual differences in economic decision-making performance. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Acoustics Research of Propulsion Systems

NASA Technical Reports Server (NTRS)

Gao, Ximing; Houston, Janice D.

2014-01-01

The liftoff phase induces some of the highest acoustic loading over a broad frequency for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle but there are challenges. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests; i.e. static firings conducted in the 1960's, to generate 1/3 octave band Sound Pressure Level (SPL) spectra. These data sets are used to predict the liftoff acoustic environments for launch vehicles. To facilitate the accuracy and quality of acoustic loading, predictions at liftoff for future launch vehicles such as the Space Launch System (SLS), non-stationary flight data from the Ares I-X were processed in PC-Signal in two forms which included a simulated hold-down phase and the entire launch phase. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semiempirical methods. This consisted, initially, of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares IX flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Sliding contact fracture of dental ceramics: Principles and validation

PubMed Central

Ren, Linlin; Zhang, Yu

2014-01-01

Ceramic prostheses are subject to sliding contact under normal and tangential loads. Accurate prediction of the onset of fracture at two contacting surfaces holds the key to greater long-term performance of these prostheses. In this study, building on stress analysis of Hertzian contact and considering fracture criteria for linear elastic materials, a constitutive fracture mechanics relation was developed to incorporate the critical fracture load with the contact geometry, coefficient of friction and material fracture toughness. Critical loads necessary to cause fracture under a sliding indenter were calculated from the constitutive equation, and compared with the loads predicted from elastic stress analysis in conjunction with measured critical load for frictionless normal contact—a semi-empirical approach. The major predictions of the models were calibrated with experimentally determined critical loads of current and future dental ceramics after contact with a rigid spherical slider. Experimental results conform with the trends predicted by the models. PMID:24632538

Comparison of calculated and measured velocities near the tip of a model rotor blade at transonic speeds

NASA Technical Reports Server (NTRS)

Tauber, M. E.; Owen, F. K.; Langhi, R. G.; Palmer, G. E.

1985-01-01

The ability of the ROT22 code to predict accurately the transonic flow field in the crucial region around and beyond the tip of a high speed rotor blade was assessed. The computations were compared with extensive laser velocimetry measurements made at zero advance ratio and tip Mach numbers of 0.85, 0.88, 0.90, and 0.95. The comparison between theory and experiment was made using 300 scans for the three orthogonal velocity components covering a volume having a height of over one blade chord, a width of nearly two chords, and a length ranging from about 1 to 1.6 chords, depending on the tip speeds. The good agreement between the calculated and measured velocities established the ability of the code to predict the off blade flow field at high tip speeds. This supplements previous comparisons where surface pressures were shown to be well predicted on two different tips at advance ratios to 0.45, especially at the critical 90 deg azimuth blade position. These results demonstrate that the ROT22 code can be used with confidence to predict the important tip region flow field including the occurrence, strength, and location of shock waves causing high drag and noise.

Smoothing and Predicting Celestial Pole Offsets using a Kalman Filter and Smoother

NASA Astrophysics Data System (ADS)

Nastula, J.; Chin, T. M.; Gross, R. S.; Winska, M.; Winska, J.

2017-12-01

Since the early days of interplanetary spaceflight, accounting for changes in the Earth's rotation is recognized to be critical for accurate navigation. In the 1960s, tracking anomalies during the Ranger VII and VIII lunar missions were traced to errors in the Earth orientation parameters. As a result, Earth orientation calibration methods were improved to support the Mariner IV and V planetary missions. Today, accurate Earth orientation parameters are used to track and navigate every interplanetary spaceflight mission. The interplanetary spacecraft tracking and navigation teams at JPL require the UT1 and polar motion parameters, and these Earth orientation parameters are estimated by the use of a Kalman filter to combine past measurements of these parameters and predict their future evolution. A model was then used to provide the nutation/precession components of the Earth's orientation separately. As a result, variations caused by the free core nutation were not taken into account. But for the highest accuracy, these variations must be considered. So JPL recently developed an approach based upon the use of a Kalman filter and smoother to provide smoothed and predicted celestial pole offsets (CPOs) to the interplanetary spacecraft tracking and navigation teams. The approach used at JPL to do this and an evaluation of the accuracy of the predicted CPOs will be given here.

Plant reproductive allocation predicts herbivore dynamics across spatial and temporal scales.

PubMed

Miller, Tom E X; Tyre, Andrew J; Louda, Svata M

2006-11-01

Life-history theory suggests that iteroparous plants should be flexible in their allocation of resources toward growth and reproduction. Such plasticity could have consequences for herbivores that prefer or specialize on vegetative versus reproductive structures. To test this prediction, we studied the response of the cactus bug (Narnia pallidicornis) to meristem allocation by tree cholla cactus (Opuntia imbricata). We evaluated the explanatory power of demographic models that incorporated variation in cactus relative reproductive effort (RRE; the proportion of meristems allocated toward reproduction). Field data provided strong support for a single model that defined herbivore fecundity as a time-varying, increasing function of host RRE. High-RRE plants were predicted to support larger insect populations, and this effect was strongest late in the season. Independent field data provided strong support for these qualitative predictions and suggested that plant allocation effects extend across temporal and spatial scales. Specifically, late-season insect abundance was positively associated with interannual changes in cactus RRE over 3 years. Spatial variation in insect abundance was correlated with variation in RRE among five cactus populations across New Mexico. We conclude that plant allocation can be a critical component of resource quality for insect herbivores and, thus, an important mechanism underlying variation in herbivore abundance across time and space.

Predicting colloid transport through saturated porous media: A critical review

NASA Astrophysics Data System (ADS)

Molnar, Ian L.; Johnson, William P.; Gerhard, Jason I.; Willson, Clinton S.; O'Carroll, Denis M.

2015-09-01

Understanding and predicting colloid transport and retention in water-saturated porous media is important for the protection of human and ecological health. Early applications of colloid transport research before the 1990s included the removal of pathogens in granular drinking water filters. Since then, interest has expanded significantly to include such areas as source zone protection of drinking water systems and injection of nanometals for contaminated site remediation. This review summarizes predictive tools for colloid transport from the pore to field scales. First, we review experimental breakthrough and retention of colloids under favorable and unfavorable colloid/collector interactions (i.e., no significant and significant colloid-surface repulsion, respectively). Second, we review the continuum-scale modeling strategies used to describe observed transport behavior. Third, we review the following two components of colloid filtration theory: (i) mechanistic force/torque balance models of pore-scale colloid trajectories and (ii) approximating correlation equations used to predict colloid retention. The successes and limitations of these approaches for favorable conditions are summarized, as are recent developments to predict colloid retention under the unfavorable conditions particularly relevant to environmental applications. Fourth, we summarize the influences of physical and chemical heterogeneities on colloid transport and avenues for their prediction. Fifth, we review the upscaling of mechanistic model results to rate constants for use in continuum models of colloid behavior at the column and field scales. Overall, this paper clarifies the foundation for existing knowledge of colloid transport and retention, features recent advances in the field, critically assesses where existing approaches are successful and the limits of their application, and highlights outstanding challenges and future research opportunities. These challenges and opportunities include improving mechanistic descriptions, and subsequent correlation equations, for nanoparticle (i.e., Brownian particle) transport through soil, developing mechanistic descriptions of colloid retention in so-called "unfavorable" conditions via methods such as the "discrete heterogeneity" approach, and employing imaging techniques such as X-ray tomography to develop realistic expressions for grain topology and mineral distribution that can aid the development of these mechanistic approaches.

Predicting Drug-Target Interactions With Multi-Information Fusion.

PubMed

Peng, Lihong; Liao, Bo; Zhu, Wen; Li, Zejun; Li, Keqin

2017-03-01

Identifying potential associations between drugs and targets is a critical prerequisite for modern drug discovery and repurposing. However, predicting these associations is difficult because of the limitations of existing computational methods. Most models only consider chemical structures and protein sequences, and other models are oversimplified. Moreover, datasets used for analysis contain only true-positive interactions, and experimentally validated negative samples are unavailable. To overcome these limitations, we developed a semi-supervised based learning framework called NormMulInf through collaborative filtering theory by using labeled and unlabeled interaction information. The proposed method initially determines similarity measures, such as similarities among samples and local correlations among the labels of the samples, by integrating biological information. The similarity information is then integrated into a robust principal component analysis model, which is solved using augmented Lagrange multipliers. Experimental results on four classes of drug-target interaction networks suggest that the proposed approach can accurately classify and predict drug-target interactions. Part of the predicted interactions are reported in public databases. The proposed method can also predict possible targets for new drugs and can be used to determine whether atropine may interact with alpha1B- and beta1- adrenergic receptors. Furthermore, the developed technique identifies potential drugs for new targets and can be used to assess whether olanzapine and propiomazine may target 5HT2B. Finally, the proposed method can potentially address limitations on studies of multitarget drugs and multidrug targets.

Formability prediction for AHSS materials using damage models

NASA Astrophysics Data System (ADS)

Amaral, R.; Santos, Abel D.; José, César de Sá; Miranda, Sara

2017-05-01

Advanced high strength steels (AHSS) are seeing an increased use, mostly due to lightweight design in automobile industry and strict regulations on safety and greenhouse gases emissions. However, the use of these materials, characterized by a high strength to weight ratio, stiffness and high work hardening at early stages of plastic deformation, have imposed many challenges in sheet metal industry, mainly their low formability and different behaviour, when compared to traditional steels, which may represent a defying task, both to obtain a successful component and also when using numerical simulation to predict material behaviour and its fracture limits. Although numerical prediction of critical strains in sheet metal forming processes is still very often based on the classic forming limit diagrams, alternative approaches can use damage models, which are based on stress states to predict failure during the forming process and they can be classified as empirical, physics based and phenomenological models. In the present paper a comparative analysis of different ductile damage models is carried out, in order numerically evaluate two isotropic coupled damage models proposed by Johnson-Cook and Gurson-Tvergaard-Needleman (GTN), each of them corresponding to the first two previous group classification. Finite element analysis is used considering these damage mechanics approaches and the obtained results are compared with experimental Nakajima tests, thus being possible to evaluate and validate the ability to predict damage and formability limits for previous defined approaches.

Design of optimal hyperthermia protocols for prostate cancer by controlling HSP expression through computer modeling (Invited Paper)

NASA Astrophysics Data System (ADS)

Rylander, Marissa N.; Feng, Yusheng; Diller, Kenneth; Bass, J.

2005-04-01

Heat shock proteins (HSP) are critical components of a complex defense mechanism essential for preserving cell survival under adverse environmental conditions. It is inevitable that hyperthermia will enhance tumor tissue viability, due to HSP expression in regions where temperatures are insufficient to coagulate proteins, and would likely increase the probability of cancer recurrence. Although hyperthermia therapy is commonly used in conjunction with radiotherapy, chemotherapy, and gene therapy to increase therapeutic effectiveness, the efficacy of these therapies can be substantially hindered due to HSP expression when hyperthermia is applied prior to these procedures. Therefore, in planning hyperthermia protocols, prediction of the HSP response of the tumor must be incorporated into the treatment plan to optimize the thermal dose delivery and permit prediction of overall tissue response. In this paper, we present a highly accurate, adaptive, finite element tumor model capable of predicting the HSP expression distribution and tissue damage region based on measured cellular data when hyperthermia protocols are specified. Cubic spline representations of HSP27 and HSP70, and Arrhenius damage models were integrated into the finite element model to enable prediction of the HSP expression and damage distribution in the tissue following laser heating. Application of the model can enable optimized treatment planning by controlling of the tissue response to therapy based on accurate prediction of the HSP expression and cell damage distribution.

The Wake Vortex Prediction and Monitoring System WSVBS

NASA Astrophysics Data System (ADS)

Gerz, T.; Holzäpfel, F.

2009-09-01

Design and performance of the Wake Vortex Prediction and Monitoring System WSVBS are described. The WSVBS has been developed to tactically increase airport capacity for approach and landing on closely-spaced parallel runways. It is thought to dynamically adjust aircraft separations dependent on weather conditions and the resulting wake vortex behaviour without compromising safety. The WSVBS consists of components that consider meteorological conditions, aircraft glide path adherence, aircraft parameter combinations representing aircraft weight categories, the resulting wake-vortex behaviour, the surrounding safety areas, wake vortex monitoring, and the integration of the predictions into the arrival manager. The WSVBS has been designed and applied to Frankfurt Airport. However, its components are generic and can well be adjusted to any runway system and or airport location. The prediction horizon is larger than 45 min (as required by air traffic control) and updated every 10 minutes. It predicts the concepts of operations and procedures established by DFS and it further predicts additional temporal separations for in-trail traffic. A specific feature of the WSVBS is the usage of both measured and predicted meteorological quantities as input to wake vortex prediction. In ground proximity where the probability to encounter wake vortices is highest, the wake predictor employs measured environmental parameters that yield superior prediction results. For the less critical part aloft, which can not be monitored completely by instrumentation, the meteorological parameters are taken from dedicated numerical terminal weather predictions. The wake vortex model predicts envelopes for vortex position and strength which implicitly consider the quality of the meteorological input data. This feature is achieved by a training procedure which employs statistics of measured and predicted meteorological parameters and the resulting wake vortex behaviour. The WSVBS combines various conservative elements that presumably lead to a very high overall safety level of the WSVBS. The combination of these conservative measures certainly leads to a very high but currently unknown overall safety. Once the methodology of a comprehensive risk analysis will be established, it is planned to adjust all components to appropriate and consistent confidence levels. The WSVBS has demonstrated its functionality at Frankfurt airport during 66 days in the period from 18/12/06 until 28/02/07. The performance test indicates that (i) the system ran stable - no forecast breakdowns occurred, (ii) aircraft separations could have been reduced in 75% of the time compared to ICAO standards, (iii) reduced separation procedures could have been continuously applied for at least several tens of minutes and up to several hours occasionally, (iv) the predictions were correct as for about 1100 landings observed during 16 days no warnings occurred from the LIDAR. Fast-time simulations reveal that adapted concepts of operation yield significant reductions in delay and/or an increase in capacity to 3% taking into account the real traffic mix and operational constraints in the period of one month. Before the WSVBS can be handed over for final adaptations to become a customized fully operational system some further steps are planned. A risk analysis needs to be pursued to convince all stakeholders of the usefulness and capabilities of the system.

The potential of non-invasive pre- and post-mortem carcass measurements to predict the contribution of carcass components to slaughter yield of guinea pigs.

PubMed

Barba, Lida; Sánchez-Macías, Davinia; Barba, Iván; Rodríguez, Nibaldo

2018-06-01

Guinea pig meat consumption is increasing exponentially worldwide. The evaluation of the contribution of carcass components to carcass quality potentially can allow for the estimation of the value added to food animal origin and make research in guinea pigs more practicable. The aim of this study was to propose a methodology for modelling the contribution of different carcass components to the overall carcass quality of guinea pigs by using non-invasive pre- and post mortem carcass measurements. The selection of predictors was developed through correlation analysis and statistical significance; whereas the prediction models were based on Multiple Linear Regression. The prediction results showed higher accuracy in the prediction of carcass component contribution expressed in grams, compared to when expressed as a percentage of carcass quality components. The proposed prediction models can be useful for the guinea pig meat industry and research institutions by using non-invasive and time- and cost-efficient carcass component measuring techniques. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed using a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify deficiencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the measured data, a sensitivity analysis of the model parameters with emphasis on the definition of the convection velocity parameter, and a least-squares fit of the predicted to the measured shock-associated noise component spectra, resulted in a new definition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

Best Fitting Prediction Equations for Basal Metabolic Rate: Informing Obesity Interventions in Diverse Populations

PubMed Central

Sabounchi, Nasim S.; Rahmandad, Hazhir; Ammerman, Alice

2014-01-01

Basal Metabolic Rate (BMR) represents the largest component of total energy expenditure and is a major contributor to energy balance. Therefore, accurately estimating BMR is critical for developing rigorous obesity prevention and control strategies. Over the past several decades, numerous BMR formulas have been developed targeted to different population groups. A comprehensive literature search revealed 248 BMR estimation equations developed using diverse ranges of age, gender, race, fat free mass, fat mass, height, waist-to-hip ratio, body mass index, and weight. A subset of 47 studies included enough detail to allow for development of meta-regression equations. Utilizing these studies, meta-equations were developed targeted to twenty specific population groups. This review provides a comprehensive summary of available BMR equations and an estimate of their accuracy. An accompanying online BMR prediction tool (available at http://www.sdl.ise.vt.edu/tutorials.html) was developed to automatically estimate BMR based on the most appropriate equation after user-entry of individual age, race, gender, and weight. PMID:23318720

A general approach to the testing of binary solubility systems for thermodynamic consistency. Consolidated Fuel Reprocessing Program

NASA Astrophysics Data System (ADS)

Hamm, L. L.; Vanbrunt, V.

1982-08-01

The numerical solution to the ordinary differential equation which describes the high-pressure vapor-liquid equilibria of a binary system where one of the components is supercritical and exists as a noncondensable gas in the pure state is considered with emphasis on the implicit Runge-Kuta and orthogonal collocation methods. Some preliminary results indicate that the implicit Runge-Kutta method is superior. Due to the extreme nonlinearity of thermodynamic properties in the region near the critical locus, and extended cubic spline fitting technique is devised for correlating the P-x data. The least-squares criterion is employed in smoothing the experimental data. The technique could easily be applied to any thermodynamic data by changing the endpoint requirements. The volumetric behavior of the systems must be given or predicted in order to perform thermodynamic consistency tests. A general procedure is developed for predicting the volumetric behavior required and some indication as to the expected limit of accuracy is given.

Mechanistic Analysis of Cocrystal Dissolution as a Function of pH and Micellar Solubilization

PubMed Central

2016-01-01

The purpose of this work is to provide a mechanistic understanding of the dissolution behavior of cocrystals under the influence of ionization and micellar solubilization. Mass transport models were developed by applying Fick’s law of diffusion to dissolution with simultaneous chemical reactions in the hydrodynamic boundary layer adjacent to the dissolving cocrystal surface to predict the pH at the dissolving solid–liquid interface (i.e., interfacial pH) and the flux of cocrystals. To evaluate the predictive power of these models, dissolution studies of carbamazepine–saccharin (CBZ-SAC) and carbamazepine–salicylic acid (CBZ-SLC) cocrystals were performed at varied pH and surfactant concentrations above the critical stabilization concentration (CSC), where the cocrystals were thermodynamically stable. The findings in this work demonstrate that the pH dependent dissolution behavior of cocrystals with ionizable components is dependent on interfacial pH. This mass transport analysis demonstrates the importance of pH, cocrystal solubility, diffusivity, and micellar solubilization on the dissolution rates of cocrystals. PMID:26877267

Mechanistic Analysis of Cocrystal Dissolution as a Function of pH and Micellar Solubilization.

PubMed

Cao, Fengjuan; Amidon, Gordon L; Rodriguez-Hornedo, Nair; Amidon, Gregory E

2016-03-07

The purpose of this work is to provide a mechanistic understanding of the dissolution behavior of cocrystals under the influence of ionization and micellar solubilization. Mass transport models were developed by applying Fick's law of diffusion to dissolution with simultaneous chemical reactions in the hydrodynamic boundary layer adjacent to the dissolving cocrystal surface to predict the pH at the dissolving solid-liquid interface (i.e., interfacial pH) and the flux of cocrystals. To evaluate the predictive power of these models, dissolution studies of carbamazepine-saccharin (CBZ-SAC) and carbamazepine-salicylic acid (CBZ-SLC) cocrystals were performed at varied pH and surfactant concentrations above the critical stabilization concentration (CSC), where the cocrystals were thermodynamically stable. The findings in this work demonstrate that the pH dependent dissolution behavior of cocrystals with ionizable components is dependent on interfacial pH. This mass transport analysis demonstrates the importance of pH, cocrystal solubility, diffusivity, and micellar solubilization on the dissolution rates of cocrystals.

Occurrence and effects of tire wear particles in the environment--a critical review and an initial risk assessment.

PubMed

Wik, Anna; Dave, Göran

2009-01-01

This review summarizes the existing knowledge on the occurrence of tire wear particles in the environment, and their ecotoxicological effects. A meta-analysis on tire components in the environment revealed that tire wear particles are present in all environmental compartments, including air, water, soils/sediments, and biota. The maximum Predicted Environmental Concentrations (PECs) of tire wear particles in surface waters range from 0.03 to 56 mg l(-1) and the maximum PECs in sediments range from 0.3 to 155 g kg(-1) d.w. The results from our previous long-term studies with Ceriodaphnia dubia and Pseudokirchneriella subcapitata were used to derive Predicted No Effect Concentrations (PNECs). The upper ranges for PEC/PNEC ratios in water and sediment were >1, meaning that tire wear particles present potential risks for aquatic organisms. We suggest that management should be directed towards development and production of more environmentally friendly tires and improved road runoff treatment.

Modal Survey of ETM-3, A 5-Segment Derivative of the Space Shuttle Solid Rocket Booster

NASA Technical Reports Server (NTRS)

Nielsen, D.; Townsend, J.; Kappus, K.; Driskill, T.; Torres, I.; Parks, R.

2005-01-01

The complex interactions between internal motor generated pressure oscillations and motor structural vibration modes associated with the static test configuration of a Reusable Solid Rocket Motor have potential to generate significant dynamic thrust loads in the 5-segment configuration (Engineering Test Motor 3). Finite element model load predictions for worst-case conditions were generated based on extrapolation of a previously correlated 4-segment motor model. A modal survey was performed on the largest rocket motor to date, Engineering Test Motor #3 (ETM-3), to provide data for finite element model correlation and validation of model generated design loads. The modal survey preparation included pretest analyses to determine an efficient analysis set selection using the Effective Independence Method and test simulations to assure critical test stand component loads did not exceed design limits. Historical Reusable Solid Rocket Motor modal testing, ETM-3 test analysis model development and pre-test loads analyses, as well as test execution, and a comparison of results to pre-test predictions are discussed.

Convergence of pontine and proprioceptive streams onto multimodal cerebellar granule cells

PubMed Central

Huang, Cheng-Chiu; Sugino, Ken; Shima, Yasuyuki; Guo, Caiying; Bai, Suxia; Mensh, Brett D; Nelson, Sacha B; Hantman, Adam W

2013-01-01

Cerebellar granule cells constitute the majority of neurons in the brain and are the primary conveyors of sensory and motor-related mossy fiber information to Purkinje cells. The functional capability of the cerebellum hinges on whether individual granule cells receive mossy fiber inputs from multiple precerebellar nuclei or are instead unimodal; this distinction is unresolved. Using cell-type-specific projection mapping with synaptic resolution, we observed the convergence of separate sensory (upper body proprioceptive) and basilar pontine pathways onto individual granule cells and mapped this convergence across cerebellar cortex. These findings inform the long-standing debate about the multimodality of mammalian granule cells and substantiate their associative capacity predicted in the Marr-Albus theory of cerebellar function. We also provide evidence that the convergent basilar pontine pathways carry corollary discharges from upper body motor cortical areas. Such merging of related corollary and sensory streams is a critical component of circuit models of predictive motor control. DOI: http://dx.doi.org/10.7554/eLife.00400.001 PMID:23467508

Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions

NASA Technical Reports Server (NTRS)

Kulkarni, Chetan S.; Celaya, Jose R.; Goebel, Kai; Biswas, Gautam

2012-01-01

Electrolytic capacitors are used in several applications ranging from power supplies for safety critical avionics equipment to power drivers for electro-mechanical actuator. Past experiences show that capacitors tend to degrade and fail faster when subjected to high electrical or thermal stress conditions during operations. This makes them good candidates for prognostics and health management. Model-based prognostics captures system knowledge in the form of physics-based models of components in order to obtain accurate predictions of end of life based on their current state of heal th and their anticipated future use and operational conditions. The focus of this paper is on deriving first principles degradation models for thermal stress conditions and implementing Bayesian framework for making remaining useful life predictions. Data collected from simultaneous experiments are used to validate the models. Our overall goal is to derive accurate models of capacitor degradation, and use them to remaining useful life in DC-DC converters.

Development of a Practical Methodology for Elastic-Plastic and Fully Plastic Fatigue Crack Growth

NASA Technical Reports Server (NTRS)

McClung, R. C.; Chell, G. G.; Lee, Y. -D.; Russell, D. A.; Orient, G. E.

1999-01-01

A practical engineering methodology has been developed to analyze and predict fatigue crack growth rates under elastic-plastic and fully plastic conditions. The methodology employs the closure-corrected effective range of the J-integral, delta J(sub eff) as the governing parameter. The methodology contains original and literature J and delta J solutions for specific geometries, along with general methods for estimating J for other geometries and other loading conditions, including combined mechanical loading and combined primary and secondary loading. The methodology also contains specific practical algorithms that translate a J solution into a prediction of fatigue crack growth rate or life, including methods for determining crack opening levels, crack instability conditions, and material properties. A critical core subset of the J solutions and the practical algorithms has been implemented into independent elastic-plastic NASGRO modules. All components of the entire methodology, including the NASGRO modules, have been verified through analysis and experiment, and limits of applicability have been identified.

Software analysis handbook: Software complexity analysis and software reliability estimation and prediction

NASA Technical Reports Server (NTRS)

Lee, Alice T.; Gunn, Todd; Pham, Tuan; Ricaldi, Ron

1994-01-01

This handbook documents the three software analysis processes the Space Station Software Analysis team uses to assess space station software, including their backgrounds, theories, tools, and analysis procedures. Potential applications of these analysis results are also presented. The first section describes how software complexity analysis provides quantitative information on code, such as code structure and risk areas, throughout the software life cycle. Software complexity analysis allows an analyst to understand the software structure, identify critical software components, assess risk areas within a software system, identify testing deficiencies, and recommend program improvements. Performing this type of analysis during the early design phases of software development can positively affect the process, and may prevent later, much larger, difficulties. The second section describes how software reliability estimation and prediction analysis, or software reliability, provides a quantitative means to measure the probability of failure-free operation of a computer program, and describes the two tools used by JSC to determine failure rates and design tradeoffs between reliability, costs, performance, and schedule.

Perceived aggressiveness predicts fighting performance in mixed-martial-arts fighters.

PubMed

Trebicky, Vít; Havlícek, Jan; Roberts, S Craig; Little, Anthony C; Kleisner, Karel

2013-09-01

Accurate assessment of competitive ability is a critical component of contest behavior in animals, and it could be just as important in human competition, particularly in human ancestral populations. Here, we tested the role that facial perception plays in this assessment by investigating the association between both perceived aggressiveness and perceived fighting ability in fighters' faces and their actual fighting success. Perceived aggressiveness was positively associated with the proportion of fights won, after we controlled for the effect of weight, which also independently predicted perceived aggression. In contrast, perception of fighting ability was confounded by weight, and an association between perceived fighting ability and actual fighting success was restricted to heavyweight fighters. Shape regressions revealed that aggressive-looking faces are generally wider and have a broader chin, more prominent eyebrows, and a larger nose than less aggressive-looking faces. Our results indicate that perception of aggressiveness and fighting ability might cue different aspects of success in male-male physical confrontation.

Development of a Practical Methodology for Elastic-Plastic and Fully Plastic Fatigue Crack Growth

NASA Technical Reports Server (NTRS)

McClung, R. C.; Chell, G. G.; Lee, Y.-D.; Russell, D. A.; Orient, G. E.

1999-01-01

A practical engineering methodology has been developed to analyze and predict fatigue crack growth rates under elastic-plastic and fully plastic conditions. The methodology employs the closure-corrected effective range of the J-integral, (Delta)J(sub eff), as the governing parameter. The methodology contains original and literature J and (Delta)J solutions for specific geometries, along with general methods for estimating J for other geometries and other loading conditions, including combined mechanical loading and combined primary and secondary loading. The methodology also contains specific practical algorithms that translate a J solution into a prediction of fatigue crack growth rate or life, including methods for determining crack opening levels, crack instability conditions, and material properties. A critical core subset of the J solutions and the practical algorithms has been implemented into independent elastic-plastic NASGRO modules. All components of the entire methodology, including the NASGRO modules, have been verified through analysis and experiment, and limits of applicability have been identified.

Decoupled tracking and thermal monitoring of non-stationary targets.

PubMed

Tan, Kok Kiong; Zhang, Yi; Huang, Sunan; Wong, Yoke San; Lee, Tong Heng

2009-10-01

Fault diagnosis and predictive maintenance address pertinent economic issues relating to production systems as an efficient technique can continuously monitor key health parameters and trigger alerts when critical changes in these variables are detected, before they lead to system failures and production shutdowns. In this paper, we present a decoupled tracking and thermal monitoring system which can be used on non-stationary targets of closed systems such as machine tools. There are three main contributions from the paper. First, a vision component is developed to track moving targets under a monitor. Image processing techniques are used to resolve the target location to be tracked. Thus, the system is decoupled and applicable to closed systems without the need for a physical integration. Second, an infrared temperature sensor with a built-in laser for locating the measurement spot is deployed for non-contact temperature measurement of the moving target. Third, a predictive motion control system holds the thermal sensor and follows the moving target efficiently to enable continuous temperature measurement and monitoring.

Summary of synfuel characterization and combustion studies

NASA Technical Reports Server (NTRS)

Schultz, D. F.

1983-01-01

Combustion component research studies aimed at evolving environmentally acceptable approaches for burning coal derived fuels for ground power applications were performed at the NASA Lewis Research Center under a program titled the ""Critical Research and Support Technology Program'' (CRT). The work was funded by the Department of Energy and was performed in four tasks. This report summarizes these tasks which have all been previously reported. In addition some previously unreported data from Task 4 is also presented. The first, Task 1 consisted of a literature survey aimed at determining the properties of synthetic fuels. This was followed by a computer modeling effort, Task 2, to predict the exhaust emissions resulting from burning coal liquids by various combustion techniques such as lean and rich-lean combustion. The computer predictions were then compared to the results of a flame tube rig, Task 3, in which the fuel properties were varied to simulate coal liquids. Two actual SRC 2 coal liquids were tested in this flame tube task.

Flow prediction over a transport multi-element high-lift system and comparison with flight measurements

NASA Technical Reports Server (NTRS)

Vijgen, P. M. H. W.; Hardin, J. D.; Yip, L. P.

1992-01-01

Accurate prediction of surface-pressure distributions, merging boundary-layers, and separated-flow regions over multi-element high-lift airfoils is required to design advanced high-lift systems for efficient subsonic transport aircraft. The availability of detailed measurements of pressure distributions and both averaged and time-dependent boundary-layer flow parameters at flight Reynolds numbers is critical to evaluate computational methods and to model the turbulence structure for closure of the flow equations. Several detailed wind-tunnel measurements at subscale Reynolds numbers were conducted to obtain detailed flow information including the Reynolds-stress component. As part of a subsonic-transport high-lift research program, flight experiments are conducted using the NASA-Langley B737-100 research aircraft to obtain detailed flow characteristics for support of computational and wind-tunnel efforts. Planned flight measurements include pressure distributions at several spanwise locations, boundary-layer transition and separation locations, surface skin friction, as well as boundary-layer profiles and Reynolds stresses in adverse pressure-gradient flow.

SU-G-BRB-16: Vulnerabilities in the Gamma Metric

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neal, B; Siebers, J

Purpose: To explore vulnerabilities in the gamma index metric that undermine its wide use as a radiation therapy quality assurance tool. Methods: 2D test field pairs (images) are created specifically to achieve high gamma passing rates, but to also include gross errors by exploiting the distance-to-agreement and percent-passing components of the metric. The first set has no requirement of clinical practicality, but is intended to expose vulnerabilities. The second set exposes clinically realistic vulnerabilities. To circumvent limitations inherent to user-specific tuning of prediction algorithms to match measurements, digital test cases are manually constructed, thereby mimicking high-quality image prediction. Results: Withmore » a 3 mm distance-to-agreement metric, changing field size by ±6 mm results in a gamma passing rate over 99%. For a uniform field, a lattice of passing points spaced 5 mm apart results in a passing rate of 100%. Exploiting the percent-passing component, a 10×10 cm{sup 2} field can have a 95% passing rate when an 8 cm{sup 2}=2.8×2.8 cm{sup 2} highly out-of-tolerance (e.g. zero dose) square is missing from the comparison image. For clinically realistic vulnerabilities, an arc plan for which a 2D image is created can have a >95% passing rate solely due to agreement in the lateral spillage, with the failing 5% in the critical target region. A field with an integrated boost (e.g whole brain plus small metastases) could neglect the metastases entirely, yet still pass with a 95% threshold. All the failure modes described would be visually apparent on a gamma-map image. Conclusion: The %gamma<1 metric has significant vulnerabilities. High passing rates can obscure critical faults in hypothetical and delivered radiation doses. Great caution should be used with gamma as a QA metric; users should inspect the gamma-map. Visual analysis of gamma-maps may be impractical for cine acquisition.« less

Modeling and Analysis of Mixed Synchronous/Asynchronous Systems

NASA Technical Reports Server (NTRS)

Driscoll, Kevin R.; Madl. Gabor; Hall, Brendan

2012-01-01

Practical safety-critical distributed systems must integrate safety critical and non-critical data in a common platform. Safety critical systems almost always consist of isochronous components that have synchronous or asynchronous interface with other components. Many of these systems also support a mix of synchronous and asynchronous interfaces. This report presents a study on the modeling and analysis of asynchronous, synchronous, and mixed synchronous/asynchronous systems. We build on the SAE Architecture Analysis and Design Language (AADL) to capture architectures for analysis. We present preliminary work targeted to capture mixed low- and high-criticality data, as well as real-time properties in a common Model of Computation (MoC). An abstract, but representative, test specimen system was created as the system to be modeled.

Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression

PubMed Central

Steiner, Genevieve Z.; Barry, Robert J.; Gonsalvez, Craig J.

2016-01-01

In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies. PMID:27445774

Sequential Processing and the Matching-Stimulus Interval Effect in ERP Components: An Exploration of the Mechanism Using Multiple Regression.

PubMed

Steiner, Genevieve Z; Barry, Robert J; Gonsalvez, Craig J

2016-01-01

In oddball tasks, increasing the time between stimuli within a particular condition (target-to-target interval, TTI; nontarget-to-nontarget interval, NNI) systematically enhances N1, P2, and P300 event-related potential (ERP) component amplitudes. This study examined the mechanism underpinning these effects in ERP components recorded from 28 adults who completed a conventional three-tone oddball task. Bivariate correlations, partial correlations and multiple regression explored component changes due to preceding ERP component amplitudes and intervals found within the stimulus series, rather than constraining the task with experimentally constructed intervals, which has been adequately explored in prior studies. Multiple regression showed that for targets, N1 and TTI predicted N2, TTI predicted P3a and P3b, and Processing Negativity (PN), P3b, and TTI predicted reaction time. For rare nontargets, P1 predicted N1, NNI predicted N2, and N1 predicted Slow Wave (SW). Findings show that the mechanism is operating on separate stages of stimulus-processing, suggestive of either increased activation within a number of stimulus-specific pathways, or very long component generator recovery cycles. These results demonstrate the extent to which matching-stimulus intervals influence ERP component amplitudes and behavior in a three-tone oddball task, and should be taken into account when designing similar studies.

Modeling the prediction of business intelligence system effectiveness.

PubMed

Weng, Sung-Shun; Yang, Ming-Hsien; Koo, Tian-Lih; Hsiao, Pei-I

2016-01-01

Although business intelligence (BI) technologies are continually evolving, the capability to apply BI technologies has become an indispensable resource for enterprises running in today's complex, uncertain and dynamic business environment. This study performed pioneering work by constructing models and rules for the prediction of business intelligence system effectiveness (BISE) in relation to the implementation of BI solutions. For enterprises, effectively managing critical attributes that determine BISE to develop prediction models with a set of rules for self-evaluation of the effectiveness of BI solutions is necessary to improve BI implementation and ensure its success. The main study findings identified the critical prediction indicators of BISE that are important to forecasting BI performance and highlighted five classification and prediction rules of BISE derived from decision tree structures, as well as a refined regression prediction model with four critical prediction indicators constructed by logistic regression analysis that can enable enterprises to improve BISE while effectively managing BI solution implementation and catering to academics to whom theory is important.

Evaluation of the Food and Agriculture Sector Criticality Assessment Tool (FASCAT) and the Collected Data.

PubMed

Huff, Andrew G; Hodges, James S; Kennedy, Shaun P; Kircher, Amy

2015-08-01

To protect and secure food resources for the United States, it is crucial to have a method to compare food systems' criticality. In 2007, the U.S. government funded development of the Food and Agriculture Sector Criticality Assessment Tool (FASCAT) to determine which food and agriculture systems were most critical to the nation. FASCAT was developed in a collaborative process involving government officials and food industry subject matter experts (SMEs). After development, data were collected using FASCAT to quantify threats, vulnerabilities, consequences, and the impacts on the United States from failure of evaluated food and agriculture systems. To examine FASCAT's utility, linear regression models were used to determine: (1) which groups of questions posed in FASCAT were better predictors of cumulative criticality scores; (2) whether the items included in FASCAT's criticality method or the smaller subset of FASCAT items included in DHS's risk analysis method predicted similar criticality scores. Akaike's information criterion was used to determine which regression models best described criticality, and a mixed linear model was used to shrink estimates of criticality for individual food and agriculture systems. The results indicated that: (1) some of the questions used in FASCAT strongly predicted food or agriculture system criticality; (2) the FASCAT criticality formula was a stronger predictor of criticality compared to the DHS risk formula; (3) the cumulative criticality formula predicted criticality more strongly than weighted criticality formula; and (4) the mixed linear regression model did not change the rank-order of food and agriculture system criticality to a large degree. © 2015 Society for Risk Analysis.

25 CFR 547.10 - What are the minimum standards for Class II gaming system critical events?

Code of Federal Regulations, 2010 CFR

2010-04-01

... GAMES § 547.10 What are the minimum standards for Class II gaming system critical events? This section... be considered reliable. Accordingly, any game play on the affected component shall cease immediately... has some fault.Any game play on the affected component shall cease immediately, and an appropriate...

Empathy-Related Responding in Chinese Toddlers: Factorial Structure and Cognitive Contributors

ERIC Educational Resources Information Center

Huang, Heqing; Su, Yanjie; Jin, Jian

2017-01-01

The critical role of the second year of life in the development of empathy is well accepted by psychologists. However, the developmental trends of the different components of empathy and the potential factors underlying these components during this critical period remain unclear. Eighty-four Chinese toddlers in the second year of life participated…

The Practices of Critical Thinking Component and Its Impact in Malaysian Nurses Health Education

ERIC Educational Resources Information Center

Abdullah, Abdul Ghani Kanesan; Alzaidiyeen, Naser Jamil; Yee, Ng Mooi

2010-01-01

The purpose of this research is to study the impact of the critical thinking component in the health education curriculum of nurses for patients with different health needs. Data for this research was gathered from mixed approaches, quantitative and qualitative approaches. For the quantitative approach 84 student nurses were selected randomly to…

Perspectives for geographically oriented management of fusarium mycotoxins in the cereal supply chain.

PubMed

van der Fels-Klerx, H J; Booij, C J H

2010-06-01

This article provides an overview of available systems for management of Fusarium mycotoxins in the cereal grain supply chain, with an emphasis on the use of predictive mathematical modeling. From the state of the art, it proposes future developments in modeling and management and their challenges. Mycotoxin contamination in cereal grain-based feed and food products is currently managed and controlled by good agricultural practices, good manufacturing practices, hazard analysis critical control points, and by checking and more recently by notification systems and predictive mathematical models. Most of the predictive models for Fusarium mycotoxins in cereal grains focus on deoxynivalenol in wheat and aim to help growers make decisions about the application of fungicides during cultivation. Future developments in managing Fusarium mycotoxins should include the linkage between predictive mathematical models and geographical information systems, resulting into region-specific predictions for mycotoxin occurrence. The envisioned geographically oriented decision support system may incorporate various underlying models for specific users' demands and regions and various related databases to feed the particular models with (geographically oriented) input data. Depending on the user requirements, the system selects the best fitting model and available input information. Future research areas include organizing data management in the cereal grain supply chain, developing predictive models for other stakeholders (taking into account the period up to harvest), other Fusarium mycotoxins, and cereal grain types, and understanding the underlying effects of the regional component in the models.

Open source machine-learning algorithms for the prediction of optimal cancer drug therapies.

PubMed

Huang, Cai; Mezencev, Roman; McDonald, John F; Vannberg, Fredrik

2017-01-01

Precision medicine is a rapidly growing area of modern medical science and open source machine-learning codes promise to be a critical component for the successful development of standardized and automated analysis of patient data. One important goal of precision cancer medicine is the accurate prediction of optimal drug therapies from the genomic profiles of individual patient tumors. We introduce here an open source software platform that employs a highly versatile support vector machine (SVM) algorithm combined with a standard recursive feature elimination (RFE) approach to predict personalized drug responses from gene expression profiles. Drug specific models were built using gene expression and drug response data from the National Cancer Institute panel of 60 human cancer cell lines (NCI-60). The models are highly accurate in predicting the drug responsiveness of a variety of cancer cell lines including those comprising the recent NCI-DREAM Challenge. We demonstrate that predictive accuracy is optimized when the learning dataset utilizes all probe-set expression values from a diversity of cancer cell types without pre-filtering for genes generally considered to be "drivers" of cancer onset/progression. Application of our models to publically available ovarian cancer (OC) patient gene expression datasets generated predictions consistent with observed responses previously reported in the literature. By making our algorithm "open source", we hope to facilitate its testing in a variety of cancer types and contexts leading to community-driven improvements and refinements in subsequent applications.

Evaluating the Impact of Global Warming on Water Balance of Maize by High-precision Controlled Experiment and MLCan model

NASA Astrophysics Data System (ADS)

Ma, Y.; Song, X.; Kumar, P.; Wu, Y.; Woo, D.; Le, P. V.; Ma, C.

2016-12-01

Increased temperature affects the agricultural hydrologic cycle not only by changing precipitation levels, evapotranspiration and the magnitude and timing of run-off, but also by impacting water flows and soil water dynamics. Accurate prediction of hydrologic change under global warming requires high-precision experiment and mathematical model to determine water interaction between interfaces in the soil-plant-atmosphere continuum. In this study, the weighting lysimeter and chamber were coupled to monitor water balance component dynamics of maize under controlled ambient temperature and elevated temperature of 2°C conditions. A mechanistic multilayer canopy-soil-root system model (MLCan) was used to predict hydrologic fluxes variation under different elevated temperature scenarios after calibration with experimental results. The results showed that maize growth period reduced 8 days under increased temperature of 2°C. The mean daily evapotranspiration, soil water storage change, and drainage was 2.66 mm, -2.75 mm, and 0.22 mm under controlled temperature condition, respectively. When temperature was elevated by 2°C, the average daily ET for maize significantly increased about 6.7% (p<0.05). However, there were non-significant impacts of increased temperature on the daily soil water storage change and drainage (p>0.05). Quantification of changes in water balance components induced by temperature increase for maize is critical for optimizing irrigation water management practices and improving water use efficiency.

PIV Measurements of the CEV Hot Abort Motor Plume for CFD Validation

NASA Technical Reports Server (NTRS)

Wernet, Mark; Wolter, John D.; Locke, Randy; Wroblewski, Adam; Childs, Robert; Nelson, Andrea

2010-01-01

NASA s next manned launch platform for missions to the moon and Mars are the Orion and Ares systems. Many critical aspects of the launch system performance are being verified using computational fluid dynamics (CFD) predictions. The Orion Launch Abort Vehicle (LAV) consists of a tower mounted tractor rocket tasked with carrying the Crew Module (CM) safely away from the launch vehicle in the event of a catastrophic failure during the vehicle s ascent. Some of the predictions involving the launch abort system flow fields produced conflicting results, which required further investigation through ground test experiments. Ground tests were performed to acquire data from a hot supersonic jet in cross-flow for the purpose of validating CFD turbulence modeling relevant to the Orion Launch Abort Vehicle (LAV). Both 2-component axial plane Particle Image Velocimetry (PIV) and 3-component cross-stream Stereo Particle Image Velocimetry (SPIV) measurements were obtained on a model of an Abort Motor (AM). Actual flight conditions could not be simulated on the ground, so the highest temperature and pressure conditions that could be safely used in the test facility (nozzle pressure ratio 28.5 and a nozzle temperature ratio of 3) were used for the validation tests. These conditions are significantly different from those of the flight vehicle, but were sufficiently high enough to begin addressing turbulence modeling issues that predicated the need for the validation tests.

A Mixed Phase Tale: New Ways of using in-situ cloud observations to reduce climate model biases in Southern Ocean

NASA Astrophysics Data System (ADS)

Gettelman, A.; Stith, J. L.

2014-12-01

Southern ocean clouds are a critical part of the earth's energy budget, and significant biases in the climatology of these clouds exist in models used to predict climate change. We compare in situ measurements of cloud microphysical properties of ice and liquid over the S. Ocean with constrained output from the atmospheric component of an Earth System Model. Observations taken during the HIAPER (the NSF/NCAR G-V aircraft) Pole-to-Pole Observations (HIPPO) multi-year field campaign are compared with simulations from the atmospheric component of the Community Earth System Model (CESM). Remarkably, CESM is able to accurately simulate the locations of cloud formation, and even cloud microphysical properties are comparable between the model and observations. Significantly, the simulations do not predict sufficient supercooled liquid. Altering the model cloud and aerosol processes to better reproduce the observations of supercooled liquid acts to reduce long-standing biases in S. Ocean clouds in CESM, which are typical of other models. Furthermore, sensitivity tests show where better observational constraints on aerosols and cloud microphysics can reduce uncertainty and biases in global models. These results are intended to show how we can connect large scale simulations with field observations in the S. Ocean to better understand Southern Ocean cloud processes and reduce biases in global climate simulations.

Cognitive Components Underpinning the Development of Model-Based Learning

PubMed Central

Potter, Tracey C.S.; Bryce, Nessa V.; Hartley, Catherine A.

2016-01-01

Reinforcement learning theory distinguishes “model-free” learning, which fosters reflexive repetition of previously rewarded actions, from “model-based” learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9–25, we examined whether the abilities to infer sequential regularities in the environment (“statistical learning”), maintain information in an active state (“working memory”) and integrate distant concepts to solve problems (“fluid reasoning”) predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. PMID:27825732

Cognitive components underpinning the development of model-based learning.

PubMed

Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

2017-06-01

Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Cross-talk between Rho and Rac GTPases drives deterministic exploration of cellular shape space and morphological heterogeneity.

PubMed

Sailem, Heba; Bousgouni, Vicky; Cooper, Sam; Bakal, Chris

2014-01-22

One goal of cell biology is to understand how cells adopt different shapes in response to varying environmental and cellular conditions. Achieving a comprehensive understanding of the relationship between cell shape and environment requires a systems-level understanding of the signalling networks that respond to external cues and regulate the cytoskeleton. Classical biochemical and genetic approaches have identified thousands of individual components that contribute to cell shape, but it remains difficult to predict how cell shape is generated by the activity of these components using bottom-up approaches because of the complex nature of their interactions in space and time. Here, we describe the regulation of cellular shape by signalling systems using a top-down approach. We first exploit the shape diversity generated by systematic RNAi screening and comprehensively define the shape space a migratory cell explores. We suggest a simple Boolean model involving the activation of Rac and Rho GTPases in two compartments to explain the basis for all cell shapes in the dataset. Critically, we also generate a probabilistic graphical model to show how cells explore this space in a deterministic, rather than a stochastic, fashion. We validate the predictions made by our model using live-cell imaging. Our work explains how cross-talk between Rho and Rac can generate different cell shapes, and thus morphological heterogeneity, in genetically identical populations.

Can Student Nurse Critical Thinking Be Predicted from Perceptions of Structural Empowerment within the Undergraduate, Pre-Licensure Learning Environment?

ERIC Educational Resources Information Center

Caswell-Moore, Shelley P.

2013-01-01

The purpose of this study was to test a model using Rosabeth Kanter's theory (1977; 1993) of structural empowerment to determine if this model can predict student nurses' level of critical thinking. Major goals of nursing education are to cultivate graduates who can think critically with a keen sense of clinical judgment, and who can perform…

Modular Engine Noise Component Prediction System (MCP) Technical Description and Assessment Document

NASA Technical Reports Server (NTRS)

Herkes, William H.; Reed, David H.

2005-01-01

This report describes an empirical prediction procedure for turbofan engine noise. The procedure generates predicted noise levels for several noise components, including inlet- and aft-radiated fan noise, and jet-mixing noise. This report discusses the noise source mechanisms, the development of the prediction procedures, and the assessment of the accuracy of these predictions. Finally, some recommendations for future work are presented.

An Integrated Theory for Predicting the Hydrothermomechanical Response of Advanced Composite Structural Components

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Lark, R. F.; Sinclair, J. H.

1977-01-01

An integrated theory is developed for predicting the hydrothermomechanical (HDTM) response of fiber composite components. The integrated theory is based on a combined theoretical and experimental investigation. In addition to predicting the HDTM response of components, the theory is structured to assess the combined hydrothermal effects on the mechanical properties of unidirectional composites loaded along the material axis and off-axis, and those of angleplied laminates. The theory developed predicts values which are in good agreement with measured data at the micromechanics, macromechanics, laminate analysis and structural analysis levels.

Perceived Criticism Predicts Outcome of Psychotherapy for Panic Disorder: Replication and Extension

PubMed Central

Chambless, Dianne L.; Allred, Kelly M.; Chen, Fang Fang; McCarthy, Kevin S.; Milrod, Barbara; Barber, Jacques P.

2016-01-01

Objective We tested the relation of perceived criticism from a parent or spouse/romantic partner to outcome of psychotherapy for panic disorder. Method Participants were 130 patients with panic disorder (79% with agoraphobia) who received 24 twice weekly sessions of Panic-Focused Psychodynamic Psychotherapy, Cognitive-Behavioral Therapy, or Applied Relaxation Therapy. Patients were predominantly White (75%), female (64%), and non-Hispanic (85%). At baseline, Week 5 of treatment, termination, and at 6- and 12-month follow-up, patients rated perceived criticism from the relative with whom they lived. Independent evaluators assessed the severity of panic disorder at baseline, Weeks 1, 5, and 9 of treatment, termination, and the two follow-up points. Data were analyzed with piecewise (treatment phase, follow-up phase) latent growth curve modeling. Results The latent intercept for perceived criticism at baseline predicted the latent slope for panic severity in the follow-up (p = .04) but not the active treatment phase (p = .50). In contrast, the latent intercept for panic disorder severity at baseline did not predict the latent slope on perceived criticism in either phase (ps ≥ .29). Nor did the slopes of perceived criticism and panic disorder severity covary across treatment (p = .31) or follow-up (p =.13). Indeed, perceived criticism did not change significantly across treatment (p =.45), showing the stability of this perception regardless of significant change in severity of patients’ panic disorder (p < .001). Conclusions Because perceived criticism predicts worse long-term treatment outcome for panic disorder, study findings argue for interventions to address perceived criticism in treatment. PMID:28045286

Turbidity determination of the critical exponent eta in the liquid-liquid mixture methanol and cyclohexane.

PubMed

Lytle, Amy; Jacobs, D T

2004-03-22

The turbidity of the liquid-liquid mixture methanol-cyclohexane has been measured very near its critical point and used to test competing theoretical predictions and to determine the critical correlation-correction exponent eta. By measuring the ratio of the transmitted to incident light intensities over five decades in reduced temperature, we are able to determine that Ferrell's theoretical prediction for the turbidity explains the data with the correlation length amplitude xi0=0.330+/-0.003 nm and critical exponents eta=0.041+/-0.005 and nu=0.632+/-0.002. These values are consistent with the values measured before for xi0 in this system and with the exponents predicted by theory. The data allow five different theoretical expressions to be tested and to select two as being equivalent when very close to the critical point. (c) 2004 American Institute of Physics

Non-structural Components influencing Hospital Disaster Preparedness in Malaysia

NASA Astrophysics Data System (ADS)

Samsuddin, N. M.; Takim, R.; Nawawi, A. H.; Rosman, M. R.; SyedAlwee, S. N. A.

2018-04-01

Hospital disaster preparedness refers to measures taken by the hospital’s stakeholders to prepare, reduce the effects of disaster and ensure effective coordination during incident response. Among the measures, non-structural components (i.e., medical laboratory equipment & supplies; architectural; critical lifeline; external; updated building document; and equipment & furnishing) are critical towards hospital disaster preparedness. Nevertheless, over the past few years these components are badly affected due to various types of disasters. Hence, the objective of this paper is to investigate the non-structural components influencing hospital’s disaster preparedness. Cross-sectional survey was conducted among thirty-one (31) Malaysian hospital’s employees. A total of 6 main constructs with 107 non-structural components were analysed and ranked by using SPSS and Relative Importance Index (RII). The results revealed that 6 main constructs (i.e. medical laboratory equipment & supplies; architectural; critical lifeline; external; updated building document; and equipment & furnishing) are rated as ‘very critical’ by the respondents. Among others, availability of medical laboratory equipment and supplies for diagnostic and equipment was ranked first. The results could serve as indicators for the public hospitals to improve its disaster preparedness in terms of planning, organising, knowledge training, equipment, exercising, evaluating and corrective actions through non-structural components.

Mechanical reliability and life prediction of coated metallic interconnects within solid oxide fuel cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Zhijie; Xu, Wei; Stephens, Elizabeth

Metallic cell interconnects (IC) made of ferritic stainless steels, i.e., iron-based alloys, have been increasingly favored in the recent development of planar solid oxide fuel cells (SOFCs) because of their advantages in excellent imperviousness, low electrical resistance, ease in fabrication, and cost effectiveness. Typical SOFC operating conditions inevitably lead to the formation of oxide scales on the surface of ferritic stainless steel, which could cause delamination, buckling, and spallation resulting from the mismatch of the coefficient of thermal expansion and eventually reduce the lifetime of the interconnect components. Various protective coating techniques have been applied to alleviate these drawbacks. Inmore » the present work, a fracture-mechanics-based quantitative modeling framework has been established to predict the mechanical reliability and lifetime of the spinel-coated, surface-modified specimens under an isothermal cooling cycle. Analytical solutions have been formulated to evaluate the scale/substrate interfacial strength and determine the critical oxide thickness in terms of a variety of design factors, such as coating thickness, material properties, and uncertainties. In conclusion, the findings then are correlated with the experimentally measured oxide scale growth kinetics to quantify the predicted lifetime of the metallic interconnects.« less

A Combined High and Low Cycle Fatigue Model for Life Prediction of Turbine Blades

PubMed Central

Yue, Peng; Yu, Zheng-Yong; Wang, Qingyuan

2017-01-01

Combined high and low cycle fatigue (CCF) generally induces the failure of aircraft gas turbine attachments. Based on the aero-engine load spectrum, accurate assessment of fatigue damage due to the interaction of high cycle fatigue (HCF) resulting from high frequency vibrations and low cycle fatigue (LCF) from ground-air-ground engine cycles is of critical importance for ensuring structural integrity of engine components, like turbine blades. In this paper, the influence of combined damage accumulation on the expected CCF life are investigated for turbine blades. The CCF behavior of a turbine blade is usually studied by testing with four load-controlled parameters, including high cycle stress amplitude and frequency, and low cycle stress amplitude and frequency. According to this, a new damage accumulation model is proposed based on Miner’s rule to consider the coupled damage due to HCF-LCF interaction by introducing the four load parameters. Five experimental datasets of turbine blade alloys and turbine blades were introduced for model validation and comparison between the proposed Miner, Manson-Halford, and Trufyakov-Kovalchuk models. Results show that the proposed model provides more accurate predictions than others with lower mean and standard deviation values of model prediction errors. PMID:28773064

A Combined High and Low Cycle Fatigue Model for Life Prediction of Turbine Blades.

PubMed

Zhu, Shun-Peng; Yue, Peng; Yu, Zheng-Yong; Wang, Qingyuan

2017-06-26

Combined high and low cycle fatigue (CCF) generally induces the failure of aircraft gas turbine attachments. Based on the aero-engine load spectrum, accurate assessment of fatigue damage due to the interaction of high cycle fatigue (HCF) resulting from high frequency vibrations and low cycle fatigue (LCF) from ground-air-ground engine cycles is of critical importance for ensuring structural integrity of engine components, like turbine blades. In this paper, the influence of combined damage accumulation on the expected CCF life are investigated for turbine blades. The CCF behavior of a turbine blade is usually studied by testing with four load-controlled parameters, including high cycle stress amplitude and frequency, and low cycle stress amplitude and frequency. According to this, a new damage accumulation model is proposed based on Miner's rule to consider the coupled damage due to HCF-LCF interaction by introducing the four load parameters. Five experimental datasets of turbine blade alloys and turbine blades were introduced for model validation and comparison between the proposed Miner, Manson-Halford, and Trufyakov-Kovalchuk models. Results show that the proposed model provides more accurate predictions than others with lower mean and standard deviation values of model prediction errors.

SEURAT: Safety Evaluation Ultimately Replacing Animal Testing--recommendations for future research in the field of predictive toxicology.

PubMed

Daston, George; Knight, Derek J; Schwarz, Michael; Gocht, Tilman; Thomas, Russell S; Mahony, Catherine; Whelan, Maurice

2015-01-01

The development of non-animal methodology to evaluate the potential for a chemical to cause systemic toxicity is one of the grand challenges of modern science. The European research programme SEURAT is active in this field and will conclude its first phase, SEURAT-1, in December 2015. Drawing on the experience gained in SEURAT-1 and appreciating international advancement in both basic and regulatory science, we reflect here on how SEURAT should evolve and propose that further research and development should be directed along two complementary and interconnecting work streams. The first work stream would focus on developing new 'paradigm' approaches for regulatory science. The goal here is the identification of 'critical biological targets' relevant for toxicity and to test their suitability to be used as anchors for predicting toxicity. The second work stream would focus on integration and application of new approach methods for hazard (and risk) assessment within the current regulatory 'paradigm', aiming for acceptance of animal-free testing strategies by regulatory authorities (i.e. translating scientific achievements into regulation). Components for both work streams are discussed and may provide a structure for a future research programme in the field of predictive toxicology.

Gamma-ray Pulsars: Models and Predictions

NASA Technical Reports Server (NTRS)

Harding Alice K.; White, Nicholas E. (Technical Monitor)

2000-01-01

Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is, dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10(exp 12) - 10(exp 13) G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers of the primary curvature emission around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. Next-generation gamma-ray telescopes sensitive to GeV-TeV emission will provide critical tests of pulsar acceleration and emission mechanisms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Jehoon; Wu, Jianzhong, E-mail: jwu@engr.ucr.edu

Self-assembly of capsid proteins and genome encapsidation are two critical steps in the life cycle of most plant and animal viruses. A theoretical description of such processes from a physiochemical perspective may help better understand viral replication and morphogenesis thus provide fresh insights into the experimental studies of antiviral strategies. In this work, we propose a molecular thermodynamic model for predicting the stability of Hepatitis B virus (HBV) capsids either with or without loading nucleic materials. With the key components represented by coarse-grained thermodynamic models, the theoretical predictions are in excellent agreement with experimental data for the formation free energiesmore » of empty T4 capsids over a broad range of temperature and ion concentrations. The theoretical model predicts T3/T4 dimorphism also in good agreement with the capsid formation at in vivo and in vitro conditions. In addition, we have studied the stability of the viral particles in response to physiological cellular conditions with the explicit consideration of the hydrophobic association of capsid subunits, electrostatic interactions, molecular excluded volume effects, entropy of mixing, and conformational changes of the biomolecular species. The course-grained model captures the essential features of the HBV nucleocapsid stability revealed by recent experiments.« less

A molecular thermodynamic model for the stability of hepatitis B capsids

NASA Astrophysics Data System (ADS)

Kim, Jehoon; Wu, Jianzhong

2014-06-01

Self-assembly of capsid proteins and genome encapsidation are two critical steps in the life cycle of most plant and animal viruses. A theoretical description of such processes from a physiochemical perspective may help better understand viral replication and morphogenesis thus provide fresh insights into the experimental studies of antiviral strategies. In this work, we propose a molecular thermodynamic model for predicting the stability of Hepatitis B virus (HBV) capsids either with or without loading nucleic materials. With the key components represented by coarse-grained thermodynamic models, the theoretical predictions are in excellent agreement with experimental data for the formation free energies of empty T4 capsids over a broad range of temperature and ion concentrations. The theoretical model predicts T3/T4 dimorphism also in good agreement with the capsid formation at in vivo and in vitro conditions. In addition, we have studied the stability of the viral particles in response to physiological cellular conditions with the explicit consideration of the hydrophobic association of capsid subunits, electrostatic interactions, molecular excluded volume effects, entropy of mixing, and conformational changes of the biomolecular species. The course-grained model captures the essential features of the HBV nucleocapsid stability revealed by recent experiments.

Acoustic radiation damping of flat rectangular plates subjected to subsonic flows

NASA Technical Reports Server (NTRS)

Lyle, Karen Heitman

1993-01-01

The acoustic radiation damping for various isotropic and laminated composite plates and semi-infinite strips subjected to a uniform, subsonic and steady flow has been predicted. The predictions are based on the linear vibration of a flat plate. The fluid loading is characterized as the perturbation pressure derived from the linearized Bernoulli and continuity equations. Parameters varied in the analysis include Mach number, mode number and plate size, aspect ratio and mass. The predictions are compared with existing theoretical results and experimental data. The analytical results show that the fluid loading can significantly affect realistic plate responses. Generally, graphite/epoxy and carbon/carbon plates have higher acoustic radiation damping values than similar aluminum plates, except near plate divergence conditions resulting from aeroelastic instability. Universal curves are presented where the acoustic radiation damping normalized by the mass ratio is a linear function of the reduced frequency. A separate curve is required for each Mach number and plate aspect ratio. In addition, acoustic radiation damping values can be greater than or equal to the structural component of the modal critical damping ratio (assumed as 0.01) for the higher subsonic Mach numbers. New experimental data were acquired for comparison with the analytical results.

Mechanical reliability and life prediction of coated metallic interconnects within solid oxide fuel cells

DOE PAGES

Xu, Zhijie; Xu, Wei; Stephens, Elizabeth; ...

2017-07-03

Metallic cell interconnects (IC) made of ferritic stainless steels, i.e., iron-based alloys, have been increasingly favored in the recent development of planar solid oxide fuel cells (SOFCs) because of their advantages in excellent imperviousness, low electrical resistance, ease in fabrication, and cost effectiveness. Typical SOFC operating conditions inevitably lead to the formation of oxide scales on the surface of ferritic stainless steel, which could cause delamination, buckling, and spallation resulting from the mismatch of the coefficient of thermal expansion and eventually reduce the lifetime of the interconnect components. Various protective coating techniques have been applied to alleviate these drawbacks. Inmore » the present work, a fracture-mechanics-based quantitative modeling framework has been established to predict the mechanical reliability and lifetime of the spinel-coated, surface-modified specimens under an isothermal cooling cycle. Analytical solutions have been formulated to evaluate the scale/substrate interfacial strength and determine the critical oxide thickness in terms of a variety of design factors, such as coating thickness, material properties, and uncertainties. In conclusion, the findings then are correlated with the experimentally measured oxide scale growth kinetics to quantify the predicted lifetime of the metallic interconnects.« less

Status of the NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test After 30,352 Hours of Operation

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 30,352 hr of operation and processed 490 kg of xenon throughput--surpassing the NSTAR Extended Life Test hours demonstrated and more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

A Theoretical Model for Predicting Fracture Strength and Critical Flaw Size of the ZrB2-ZrC Composites at High Temperatures

NASA Astrophysics Data System (ADS)

Wang, Ruzhuan; Li, Xiaobo; Wang, Jing; Jia, Bi; Li, Weiguo

2018-06-01

This work shows a new rational theoretical model for quantitatively predicting fracture strength and critical flaw size of the ZrB2-ZrC composites at different temperatures, which is based on a new proposed temperature dependent fracture surface energy model and the Griffith criterion. The fracture model takes into account the combined effects of temperature and damage terms (surface flaws and internal flaws) with no any fitting parameters. The predictions of fracture strength and critical flaw size of the ZrB2-ZrC composites at high temperatures agree well with experimental data. Then using the theoretical method, the improvement and design of materials are proposed. The proposed model can be used to predict the fracture strength, find the critical flaw and study the effects of microstructures on the fracture mechanism of the ZrB2-ZrC composites at high temperatures, which thus could become a potential convenient, practical and economical technical means for predicting fracture properties and material design.

Predicting the tensile strength of compacted multi-component mixtures of pharmaceutical powders.

PubMed

Wu, Chuan-Yu; Best, Serena M; Bentham, A Craig; Hancock, Bruno C; Bonfield, William

2006-08-01

Pharmaceutical tablets are generally produced by compacting a mixture of several ingredients, including active drugs and excipients. It is of practical importance if the properties of such tablets can be predicted on the basis of the ones for constituent components. The purpose of this work is to develop a theoretical model which can predict the tensile strength of compacted multi-component pharmaceutical mixtures. The model was derived on the basis of the Ryshkewitch-Duckworth equation that was originally proposed for porous materials. The required input parameters for the model are the relative density or solid fraction (ratio of the volume of solid materials to the total volume of the tablets) of the multi-component tablets and parameters associated with the constituent single-component powders, which are readily accessible. The tensile strength of tablets made of various powder blends at different relative density was also measured using diametrical compression. It has been shown that the tensile strength of the multi-component powder compacts is primarily a function of the solid fraction. Excellent agreement between prediction and experimental data for tablets of binary, ternary and four-component blends of some widely used pharmaceutical excipients was obtained. It has been demonstrated that the proposed model can well predict the tensile strength of multi-component pharmaceutical tablets. Thus, the model will be a useful design tool for formulation engineers in the pharmaceutical industry.

Properties of water along the liquid-vapor coexistence curve via molecular dynamics simulations using the polarizable TIP4P-QDP-LJ water model

PubMed Central

Bauer, Brad A.; Patel, Sandeep

2009-01-01

We present an extension of the TIP4P-QDP model, TIP4P-QDP-LJ, that is designed to couple changes in repulsive and dispersive nonbond interactions to changes in polarizability. Polarizability is intimately related to the dispersion component of classical force field models of interactions, and we explore the effect of incorporating this connection explicitly on properties along the liquid-vapor coexistence curve of pure water. Parametrized to reproduce condensed-phase liquid water properties at 298 K, the TIP4P-QDP-LJ model predicts density, enthalpy of vaporization, self-diffusion constant, and the dielectric constant at ambient conditions to about the same accuracy as TIP4P-QDP but shows remarkable improvement in reproducing the liquid-vapor coexistence curve. TIP4P-QDP-LJ predicts critical constants of Tc=623 K, ρc=0.351 g∕cm3, and Pc=250.9 atm, which are in good agreement with experimental values of Tc=647.1 K, ρc=0.322 g∕cm3, and Pc=218 atm, respectively. Applying a scaling factor correction (obtained by fitting the experimental vapor-liquid equilibrium data to the law of rectilinear diameters using a three-term Wegner expansion) the model predicts critical constants (Tc=631 K and ρc=0.308 g∕cm3). Dependence of enthalpy of vaporization, self-diffusion constant, surface tension, and dielectric constant on temperature are shown to reproduce experimental trends. We also explore the interfacial potential drop across the liquid-vapor interface for the temperatures studied. The interfacial potential demonstrates little temperature dependence at lower temperatures (300–450 K) and significantly enhanced (exponential) dependence at elevated temperatures. Terms arising from the decomposition of the interfacial potential into dipole and quadrupole contributions are shown to monotonically approach zero as the temperature approaches the critical temperature. Results of this study suggest that self-consistently treating the coupling of phase-dependent polarizability with dispersion interactions in classical water force fields may be an important effect for the extension of polarizable water force fields to reproduce properties along the liquid-vapor coexistence envelope as well as near critical conditions. More importantly, the present study demonstrates the rather remarkable transferability of a water model parametrized to a single state point to other thermodynamic states. Further studies are recommended. PMID:19725623

Study of Critical Heat Flux and Two-Phase Pressure Drop Under Reduced Gravity

NASA Technical Reports Server (NTRS)

Abdollahian, Davood; Quintal, Joseph; Barez, Fred; Zahm, Jennifer; Lohr, Victor

1996-01-01

The design of the two-phase flow systems which are anticipated to be utilized in future spacecraft thermal management systems requires a knowledge of two-phase flow and heat transfer phenomena in reduced gravities. This program was funded by NASA headquarters in response to NRA-91-OSSA-17 and was managed by Lewis Research Center. The main objective of this program was to design and construct a two-phase test loop, and perform a series of normal gravity and aircraft trajectory experiments to study the effect of gravity on the Critical Heat Flux (CHF) and onset of instability. The test loop was packaged on two aircraft racks and was also instrumented to generate data for two-phase pressure drop. The normal gravity tests were performed with vertical up and downflow configurations to bound the effect of gravity on the test parameters. One set of aircraft trajectory tests was performed aboard the NASA DC-9 aircraft. These tests were mainly intended to evaluate the test loop and its operational performance under actual reduced gravity conditions, and to produce preliminary data for the test parameters. The test results were used to demonstrate the applicability of the normal gravity models for prediction of the two-phase friction pressure drop. It was shown that the two-phase friction multipliers for vertical upflow and reduced gravity conditions can be successfully predicted by the appropriate normal gravity models. Limited critical heat flux data showed that the measured CHF under reduced gravities are of the same order of magnitude as the test results with vertical upflow configuration. A simplified correlation was only successful in predicting the measured CHF for low flow rates. Instability tests with vertical upflow showed that flow becomes unstable and critical heat flux occurs at smaller powers when a parallel flow path exists. However, downflow tests and a single reduced gravity instability experiment indicated that the system actually became more stable with a parallel single-phase flow path. Several design modifications have been identified which will improve the system performance for generating reduced gravity data. The modified test loop can provide two-phase flow data for a range of operating conditions and can serve as a test bed for component evaluation.

Properties of water along the liquid-vapor coexistence curve via molecular dynamics simulations using the polarizable TIP4P-QDP-LJ water model.

PubMed

Bauer, Brad A; Patel, Sandeep

2009-08-28

We present an extension of the TIP4P-QDP model, TIP4P-QDP-LJ, that is designed to couple changes in repulsive and dispersive nonbond interactions to changes in polarizability. Polarizability is intimately related to the dispersion component of classical force field models of interactions, and we explore the effect of incorporating this connection explicitly on properties along the liquid-vapor coexistence curve of pure water. Parametrized to reproduce condensed-phase liquid water properties at 298 K, the TIP4P-QDP-LJ model predicts density, enthalpy of vaporization, self-diffusion constant, and the dielectric constant at ambient conditions to about the same accuracy as TIP4P-QDP but shows remarkable improvement in reproducing the liquid-vapor coexistence curve. TIP4P-QDP-LJ predicts critical constants of T(c)=623 K, rho(c)=0.351 g/cm(3), and P(c)=250.9 atm, which are in good agreement with experimental values of T(c)=647.1 K, rho(c)=0.322 g/cm(3), and P(c)=218 atm, respectively. Applying a scaling factor correction (obtained by fitting the experimental vapor-liquid equilibrium data to the law of rectilinear diameters using a three-term Wegner expansion) the model predicts critical constants (T(c)=631 K and rho(c)=0.308 g/cm(3)). Dependence of enthalpy of vaporization, self-diffusion constant, surface tension, and dielectric constant on temperature are shown to reproduce experimental trends. We also explore the interfacial potential drop across the liquid-vapor interface for the temperatures studied. The interfacial potential demonstrates little temperature dependence at lower temperatures (300-450 K) and significantly enhanced (exponential) dependence at elevated temperatures. Terms arising from the decomposition of the interfacial potential into dipole and quadrupole contributions are shown to monotonically approach zero as the temperature approaches the critical temperature. Results of this study suggest that self-consistently treating the coupling of phase-dependent polarizability with dispersion interactions in classical water force fields may be an important effect for the extension of polarizable water force fields to reproduce properties along the liquid-vapor coexistence envelope as well as near critical conditions. More importantly, the present study demonstrates the rather remarkable transferability of a water model parametrized to a single state point to other thermodynamic states. Further studies are recommended.

Independent variable complexity for regional regression of the flow duration curve in ungauged basins

NASA Astrophysics Data System (ADS)

Fouad, Geoffrey; Skupin, André; Hope, Allen

2016-04-01

The flow duration curve (FDC) is one of the most widely used tools to quantify streamflow. Its percentile flows are often required for water resource applications, but these values must be predicted for ungauged basins with insufficient or no streamflow data. Regional regression is a commonly used approach for predicting percentile flows that involves identifying hydrologic regions and calibrating regression models to each region. The independent variables used to describe the physiographic and climatic setting of the basins are a critical component of regional regression, yet few studies have investigated their effect on resulting predictions. In this study, the complexity of the independent variables needed for regional regression is investigated. Different levels of variable complexity are applied for a regional regression consisting of 918 basins in the US. Both the hydrologic regions and regression models are determined according to the different sets of variables, and the accuracy of resulting predictions is assessed. The different sets of variables include (1) a simple set of three variables strongly tied to the FDC (mean annual precipitation, potential evapotranspiration, and baseflow index), (2) a traditional set of variables describing the average physiographic and climatic conditions of the basins, and (3) a more complex set of variables extending the traditional variables to include statistics describing the distribution of physiographic data and temporal components of climatic data. The latter set of variables is not typically used in regional regression, and is evaluated for its potential to predict percentile flows. The simplest set of only three variables performed similarly to the other more complex sets of variables. Traditional variables used to describe climate, topography, and soil offered little more to the predictions, and the experimental set of variables describing the distribution of basin data in more detail did not improve predictions. These results are largely reflective of cross-correlation existing in hydrologic datasets, and highlight the limited predictive power of many traditionally used variables for regional regression. A parsimonious approach including fewer variables chosen based on their connection to streamflow may be more efficient than a data mining approach including many different variables. Future regional regression studies may benefit from having a hydrologic rationale for including different variables and attempting to create new variables related to streamflow.

The nonlinear model for emergence of stable conditions in gas mixture in force field

NASA Astrophysics Data System (ADS)

Kalutskov, Oleg; Uvarova, Liudmila

2016-06-01

The case of M-component liquid evaporation from the straight cylindrical capillary into N - component gas mixture in presence of external forces was reviewed. It is assumed that the gas mixture is not ideal. The stable states in gas phase can be formed during the evaporation process for the certain model parameter valuesbecause of the mass transfer initial equationsnonlinearity. The critical concentrations of the resulting gas mixture components (the critical component concentrations at which the stable states occur in mixture) were determined mathematically for the case of single-component fluid evaporation into two-component atmosphere. It was concluded that this equilibrium concentration ratio of the mixture components can be achieved by external force influence on the mass transfer processes. It is one of the ways to create sustainable gas clusters that can be used effectively in modern nanotechnology.

49 CFR 272.105 - Requirement to file critical incident stress plan electronically.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Requirement to file critical incident stress plan...) FEDERAL RAILROAD ADMINISTRATION, DEPARTMENT OF TRANSPORTATION CRITICAL INCIDENT STRESS PLANS Plan Components and Approval Process § 272.105 Requirement to file critical incident stress plan electronically...

The Dual Role of Vegetation as a Constraint on Mass and Energy Flux into the Critical Zone and as an Emergent Property of Geophysical Critical Zone Structure

NASA Astrophysics Data System (ADS)

Brooks, P. D.; Swetnam, T. L.; Barnard, H. R.; Singha, K.; Harpold, A.; Litvak, M. E.

2017-12-01

Spatial patterns in vegetation long have been used to scale both landsurface-atmosphere exchanges of water and carbon as well as to infer subsurface structure. These pursuits typical proceed in isolation and rarely do inferences gained from one community propagate to related efforts in another. Perhaps more importantly, vegetation often is treated as an emergent property of landscape-climate interactions rather than an active modifier of both critical zone structure and energy fluxes. We posit that vegetation structure and activity are under utilized as a tool towards understanding landscape evolution and present examples that begin to disentangle the role of vegetation as both an emergent property and an active control on critical zone structure and function. As climate change, population growth, and land use changes threaten water resources worldwide, the need for the new insights vegetation can provide becomes not just a basic science priority, but a pressing applied science question with clear societal importance. This presentation will provide an overview of recent efforts to address the dual role of vegetation in both modifying and reflecting critical zone structure in the western North American forests. For example, interactions between topography and stand scale vegetation structure influence both solar radiation and turbulence altering landscape scale partitioning of evaporation vs transpiration with major impacts of surface water supply. Similarly, interactions between topographic shading, lateral redistribution of plant available water, and subsurface storage create a mosaic of drought resistance and resilience across complex terrain. These complex interactions between geophysical and vegetation components of critical zone structure result in predictable patterns in catchment scale hydrologic partitioning within individual watersheds while simultaneously suggesting testable hypotheses for why catchments under similar climate regimes respond so differently to drought stress.

Simulated front crawl swimming performance related to critical speed and critical power.

PubMed

Toussaint, H M; Wakayoshi, K; Hollander, A P; Ogita, F

1998-01-01

Competitive pool swimming events range in distance from 50 to 1500 m. Given the difference in performance times (+/- 23-1000 s), the contribution of the aerobic and anaerobic energy systems changes considerably with race distance. In training practice the regression line between swimming distance and time (Distance = critical velocity x time + anaerobic swimming capacity) is used to determine the individual capacity of the aerobic and anaerobic metabolic pathways. Although there is confidence that critical velocity and anaerobic swimming capacity are fitness measures that separate aerobic and anaerobic components, a firm theoretical basis for the interpretation of these results does not exist. The purpose of this study was to evaluate the critical power concept and anaerobic swimming capacity as measures of the aerobic and anaerobic capacity using a modeling approach. A systems model was developed that relates the mechanics and energetics involved in front crawl swimming performance. From actual swimming flume measurements, the time dependent aerobic and anaerobic energy release was modeled. Data derived from the literature were used to relate the energy cost of front crawl swimming to swimming velocity. A balance should exist between the energy cost to swim a distance in a certain time and the concomitant aerobic and anaerobic energy release. The ensuing model was used to predict performance times over a range of distances (50-1500 m) and to calculate the regression line between swimming distance and time. Using a sensitivity analysis, it was demonstrated that the critical velocity is indicative for the capacity of the aerobic energy system. Estimates of the anaerobic swimming capacity, however, were influenced by variations in both anaerobic and aerobic energy release. Therefore, it was concluded that the anaerobic swimming capacity does not provide a reliable estimate of the anaerobic capacity.

A critical evaluation of the utility of eggshells for estimating mercury concentrations in avian eggs

USGS Publications Warehouse

Peterson, Sarah; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Hartman, C. Alex; Herzog, Mark P.

2017-01-01

Eggshells are a potential tool for non-lethally sampling contaminant concentrations in bird eggs, yet few studies have examined their utility to represent mercury exposure. We assessed mercury concentrations in eggshell components for 23 bird species and determined whether they correlated with total mercury (THg) in egg contents. We designed a multi-experiment analysis to examine how THg is partitioned into eggshell components, specifically hardened eggshells, material adhered to the eggshell, and inner eggshell membranes. THg concentrations in eggshells were much lower than in egg contents, and almost all of the THg within the eggshell was contained within material adhered to eggshells and inner eggshell membranes, and specifically not within calcium-rich hardened eggshells. Despite having very little mercury, THg concentrations in hardened eggshells had the strongest correlation with egg contents among all eggshell components. However, species with the same THg concentrations in eggshells had different THg concentrations in egg contents, indicating that there is no global predictive equation among species for the relationship between eggshell and egg content THg concentrations. Further, for all species, THg concentrations in eggshells decreased with relative embryo age. Although the majority of mercury in eggshells was contained within other eggshell components and not within hardened eggshells, THg in hardened eggshells can be used to estimate THg concentrations in egg contents, if embryo age and species are addressed.

Reliability study of an emerging fire suppression system

DOE PAGES

Miller, David A.; Rossati, Lyric M.; Fritz, Nathan K.; ...

2015-11-01

Self-contained fire extinguishers are a robust, reliable and minimally invasive means of fire suppression for gloveboxes. Plutonium gloveboxes are known to present harsh environmental conditions for polymer materials, these include radiation damage and chemical exposure, both of which tend to degrade the lifetime of engineered polymer components. The primary component of interest in self-contained fire extinguishers is the nylon 6-6 machined tube that comprises the main body of the system.Thermo-mechanical modeling and characterization of nylon 6-6 for use in plutonium glovebox applications has been carried out. Data has been generated regarding property degradation leading to poor, or reduced, engineering performancemore » of nylon 6-6 components. In this study, nylon 6-6 tensile specimens conforming to the casing of self-contained fire extinguisher systems have been exposed to hydrochloric, nitric, and sulfuric acids. This information was used to predict the performance of a load bearing engineering component comprised of nylon 6-6 and designed to operate in a consistent manner over a specified time period. The study provides a fundamental understanding of the engineering performance of the fire suppression system and the effects of environmental degradation due to acid exposure on engineering performance. Data generated help identify the limitations of self-contained fire extinguishers. No critical areas of concern for plutonium glovebox applications of nylon 6-6 have been identified when considering exposure to mineral acid.« less

Stretch-collapse transition of polyelectrolyte brushes in a poor solvent

NASA Astrophysics Data System (ADS)

von Goeler, F.; Muthukumar, M.

1996-12-01

This paper describes the behavior of charged, polymer brushes in electrolyte solutions of varying solvent quality. The brush height, d, dependence on the chain length, L (=Nl, where l is the Kuhn length), the grafting density σ, and solvent conditions is determined. We consider a monomer-monomer potential consisting of three components: (1) a long-ranged, screened Coulombic component of strength v¯/l (l is the Kuhn length) and range κ-1; (2) a short-ranged, two-body component of strength w¯l; and (3) a short-ranged, three-body component of strength ūl3. In particular, we examine the transition from a stretched state to a collapsed state in a poor solvent (w¯<0) as the solvent quality is decreased. Using dimensional analysis, Monte Carlo methods, and a variational technique, a first order transition is observed as predicted by the scaling arguments of Ross et al. and Borisov et al. for high charge/grafting densities. Using a variational procedure, we derive an analytical expression for the brush size and determine, quantitatively, the critical conditions for a first order transition in terms of key dimensionless variables, vN5/2, κlN1/2, wN3/2, and uN2 (where v=2πσl2v¯, w=σl2w¯, and u=σ2l4ū).

Reliability study of an emerging fire suppression system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, David A.; Rossati, Lyric M.; Fritz, Nathan K.

Self-contained fire extinguishers are a robust, reliable and minimally invasive means of fire suppression for gloveboxes. Plutonium gloveboxes are known to present harsh environmental conditions for polymer materials, these include radiation damage and chemical exposure, both of which tend to degrade the lifetime of engineered polymer components. The primary component of interest in self-contained fire extinguishers is the nylon 6-6 machined tube that comprises the main body of the system.Thermo-mechanical modeling and characterization of nylon 6-6 for use in plutonium glovebox applications has been carried out. Data has been generated regarding property degradation leading to poor, or reduced, engineering performancemore » of nylon 6-6 components. In this study, nylon 6-6 tensile specimens conforming to the casing of self-contained fire extinguisher systems have been exposed to hydrochloric, nitric, and sulfuric acids. This information was used to predict the performance of a load bearing engineering component comprised of nylon 6-6 and designed to operate in a consistent manner over a specified time period. The study provides a fundamental understanding of the engineering performance of the fire suppression system and the effects of environmental degradation due to acid exposure on engineering performance. Data generated help identify the limitations of self-contained fire extinguishers. No critical areas of concern for plutonium glovebox applications of nylon 6-6 have been identified when considering exposure to mineral acid.« less

Comparison of non-ideal solution theories for multi-solute solutions in cryobiology and tabulation of required coefficients.

PubMed

Zielinski, Michal W; McGann, Locksley E; Nychka, John A; Elliott, Janet A W

2014-10-01

Thermodynamic solution theories allow the prediction of chemical potentials in solutions of known composition. In cryobiology, such models are a critical component of many mathematical models that are used to simulate the biophysical processes occurring in cells and tissues during cryopreservation. A number of solution theories, both thermodynamically ideal and non-ideal, have been proposed for use with cryobiological solutions. In this work, we have evaluated two non-ideal solution theories for predicting water chemical potential (i.e. osmolality) in multi-solute solutions relevant to cryobiology: the Elliott et al. form of the multi-solute osmotic virial equation, and the Kleinhans and Mazur freezing point summation model. These two solution theories require fitting to only single-solute data, although they can make predictions in multi-solute solutions. The predictions of these non-ideal solution theories were compared to predictions made using ideal dilute assumptions and to available literature multi-solute experimental osmometric data. A single, consistent set of literature single-solute solution data was used to fit for the required solute-specific coefficients for each of the non-ideal models. Our results indicate that the two non-ideal solution theories have similar overall performance, and both give more accurate predictions than ideal models. These results can be used to select between the non-ideal models for a specific multi-solute solution, and the updated coefficients provided in this work can be used to make the desired predictions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kervick, R.; Blue, C. A.; Kadolkar, P. B.

Forging is a manufacturing process in which metal is pressed, pounded or squeezed under great pressure and, often, under high strain rates into high-strength parts known as forgings. The process is typically performed hot by preheating the metal to a desired temperature before it is worked. The forging process can create parts that are stronger than those manufactured by any other metal working process. Forgings are almost always used where reliability and human safety are critical. Forgings are normally component parts contained inside assembled items such airplanes, automobiles, tractors, ships, oil drilling equipment, engines missiles, and all kinds of capitalmore » equipment Forgings are stronger than castings and surpass them in predictable strength properties, producing superior strength that is assured, part to part.« less

An integrated computational tool for precipitation simulation

NASA Astrophysics Data System (ADS)

Cao, W.; Zhang, F.; Chen, S.-L.; Zhang, C.; Chang, Y. A.

2011-07-01

Computer aided materials design is of increasing interest because the conventional approach solely relying on experimentation is no longer viable within the constraint of available resources. Modeling of microstructure and mechanical properties during precipitation plays a critical role in understanding the behavior of materials and thus accelerating the development of materials. Nevertheless, an integrated computational tool coupling reliable thermodynamic calculation, kinetic simulation, and property prediction of multi-component systems for industrial applications is rarely available. In this regard, we are developing a software package, PanPrecipitation, under the framework of integrated computational materials engineering to simulate precipitation kinetics. It is seamlessly integrated with the thermodynamic calculation engine, PanEngine, to obtain accurate thermodynamic properties and atomic mobility data necessary for precipitation simulation.

Text Analysis: Critical Component of Planning for Text-Based Discussion Focused on Comprehension of Informational Texts

ERIC Educational Resources Information Center

Kucan, Linda; Palincsar, Annemarie Sullivan

2018-01-01

This investigation focuses on a tool used in a reading methods course to introduce reading specialist candidates to text analysis as a critical component of planning for text-based discussions. Unlike planning that focuses mainly on important text content or information, a text analysis approach focuses both on content and how that content is…

Analysis of a Shock-Associated Noise Prediction Model Using Measured Jet Far-Field Noise Data

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sharpe, Jacob A.

2014-01-01

A code for predicting supersonic jet broadband shock-associated noise was assessed us- ing a database containing noise measurements of a jet issuing from a convergent nozzle. The jet was operated at 24 conditions covering six fully expanded Mach numbers with four total temperature ratios. To enable comparisons of the predicted shock-associated noise component spectra with data, the measured total jet noise spectra were separated into mixing noise and shock-associated noise component spectra. Comparisons between predicted and measured shock-associated noise component spectra were used to identify de ciencies in the prediction model. Proposed revisions to the model, based on a study of the overall sound pressure levels for the shock-associated noise component of the mea- sured data, a sensitivity analysis of the model parameters with emphasis on the de nition of the convection velocity parameter, and a least-squares t of the predicted to the mea- sured shock-associated noise component spectra, resulted in a new de nition for the source strength spectrum in the model. An error analysis showed that the average error in the predicted spectra was reduced by as much as 3.5 dB for the revised model relative to the average error for the original model.

NASA Applications and Lessons Learned in Reliability Engineering

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.; Fuller, Raymond P.

2011-01-01

Since the Shuttle Challenger accident in 1986, communities across NASA have been developing and extensively using quantitative reliability and risk assessment methods in their decision making process. This paper discusses several reliability engineering applications that NASA has used over the year to support the design, development, and operation of critical space flight hardware. Specifically, the paper discusses several reliability engineering applications used by NASA in areas such as risk management, inspection policies, components upgrades, reliability growth, integrated failure analysis, and physics based probabilistic engineering analysis. In each of these areas, the paper provides a brief discussion of a case study to demonstrate the value added and the criticality of reliability engineering in supporting NASA project and program decisions to fly safely. Examples of these case studies discussed are reliability based life limit extension of Shuttle Space Main Engine (SSME) hardware, Reliability based inspection policies for Auxiliary Power Unit (APU) turbine disc, probabilistic structural engineering analysis for reliability prediction of the SSME alternate turbo-pump development, impact of ET foam reliability on the Space Shuttle System risk, and reliability based Space Shuttle upgrade for safety. Special attention is given in this paper to the physics based probabilistic engineering analysis applications and their critical role in evaluating the reliability of NASA development hardware including their potential use in a research and technology development environment.

Family climate and expressed emotion in the course of alcoholism.

PubMed

Fichter, M M; Glynn, S M; Weyerer, S; Liberman, R P; Frick, U

1997-06-01

Family-based predictors of relapse were examined in 100 alcoholics who participated in a 12-week treatment program with 6-month and 18-month followups. "Expressed Emotion" (EE), or attitudes of relatives toward the alcoholic as measured by the Camberwell Family Interview, scales measuring rejection of the alcoholic by relatives, and self-reports of partner interaction were evaluated as possible predictors of abstinence. During therapy, partnership interactions showed a transient deterioration with increased temporary friction. Based on conservative criteria, the abstinence rate was 40% at 6-month followup and 30% at 18-month followup. An association with the relapse at followup could be obtained for the Patient Rejection Scale (PRS) and, using empirically derived classification rules, for the main three variables of the Camberwell Family Interview (CFI) conducted on admission: "Critical Comments," "Emotional Overinvolvement," and "Warmth." A low number of Critical Comments and a high score in Warmth were associated with a lower risk of relapse; however, contrary to expectations, Emotional Overinvolvement of the significant other was associated with more abstinence. In addition, the number of Critical Comments made by relatives about the alcoholic, a major component of high EE as measured by the CFI, had a statistically significant impact on the "survival function" of abstinence, and thus contributed to the prediction of the course of alcoholism in the expected direction.

The utility of polarized heliospheric imaging for space weather monitoring.

PubMed

DeForest, C E; Howard, T A; Webb, D F; Davies, J A

2016-01-01

A polarizing heliospheric imager is a critical next generation tool for space weather monitoring and prediction. Heliospheric imagers can track coronal mass ejections (CMEs) as they cross the solar system, using sunlight scattered by electrons in the CME. This tracking has been demonstrated to improve the forecasting of impact probability and arrival time for Earth-directed CMEs. Polarized imaging allows locating CMEs in three dimensions from a single vantage point. Recent advances in heliospheric imaging have demonstrated that a polarized imager is feasible with current component technology.Developing this technology to a high technology readiness level is critical for space weather relevant imaging from either a near-Earth or deep-space mission. In this primarily technical review, we developpreliminary hardware requirements for a space weather polarizing heliospheric imager system and outline possible ways to flight qualify and ultimately deploy the technology operationally on upcoming specific missions. We consider deployment as an instrument on NOAA's Deep Space Climate Observatory follow-on near the Sun-Earth L1 Lagrange point, as a stand-alone constellation of smallsats in low Earth orbit, or as an instrument located at the Sun-Earth L5 Lagrange point. The critical first step is the demonstration of the technology, in either a science or prototype operational mission context.

A novel prediction method about single components of analog circuits based on complex field modeling.

PubMed

Zhou, Jingyu; Tian, Shulin; Yang, Chenglin

2014-01-01

Few researches pay attention to prediction about analog circuits. The few methods lack the correlation with circuit analysis during extracting and calculating features so that FI (fault indicator) calculation often lack rationality, thus affecting prognostic performance. To solve the above problem, this paper proposes a novel prediction method about single components of analog circuits based on complex field modeling. Aiming at the feature that faults of single components hold the largest number in analog circuits, the method starts with circuit structure, analyzes transfer function of circuits, and implements complex field modeling. Then, by an established parameter scanning model related to complex field, it analyzes the relationship between parameter variation and degeneration of single components in the model in order to obtain a more reasonable FI feature set via calculation. According to the obtained FI feature set, it establishes a novel model about degeneration trend of analog circuits' single components. At last, it uses particle filter (PF) to update parameters for the model and predicts remaining useful performance (RUP) of analog circuits' single components. Since calculation about the FI feature set is more reasonable, accuracy of prediction is improved to some extent. Finally, the foregoing conclusions are verified by experiments.

So Much More than Just a List: Exploring the Nature of Critical Questioning in Undergraduate Sciences

ERIC Educational Resources Information Center

Pedrosa-de-Jesus, Helena; Moreira, Aurora; Lopes, Betina; Watts, Mike

2014-01-01

Background: Critical thinking is one of the very highest orders of cognitive abilities and a key competency in higher education. Asking questions is an important component of rich learning experiences, structurally embedded in the operations of critical thinking. Our clear sense is that critical thinking and, within that, critical questioning, is…

Prediction of bacterial small RNAs in the RsmA (CsrA) and ToxT pathways: a machine learning approach.

PubMed

Fakhry, Carl Tony; Kulkarni, Prajna; Chen, Ping; Kulkarni, Rahul; Zarringhalam, Kourosh

2017-08-22

Small RNAs (sRNAs) constitute an important class of post-transcriptional regulators that control critical cellular processes in bacteria. Recent research using high-throughput transcriptomic approaches has led to a dramatic increase in the discovery of bacterial sRNAs. However, it is generally believed that the currently identified sRNAs constitute a limited subset of the bacterial sRNA repertoire. In several cases, sRNAs belonging to a specific class are already known and the challenge is to identify additional sRNAs belonging to the same class. In such cases, machine-learning approaches can be used to predict novel sRNAs in a given class. In this work, we develop novel bioinformatics approaches that integrate sequence and structure-based features to train machine-learning models for the discovery of bacterial sRNAs. We show that features derived from recurrent structural motifs in the ensemble of low energy secondary structures can distinguish the RNA classes with high accuracy. We apply this approach to predict new members in two broad classes of bacterial small RNAs: 1) sRNAs that bind to the RNA-binding protein RsmA/CsrA in diverse bacterial species and 2) sRNAs regulated by the master regulator of virulence, ToxT, in Vibrio cholerae. The involvement of sRNAs in bacterial adaptation to changing environments is an increasingly recurring theme in current research in microbiology. It is likely that future research, combining experimental and computational approaches, will discover many more examples of sRNAs as components of critical regulatory pathways in bacteria. We have developed a novel approach for prediction of small RNA regulators in important bacterial pathways. This approach can be applied to specific classes of sRNAs for which several members have been identified and the challenge is to identify additional sRNAs.

A review on data and predictions of water dielectric spectra for calculations of van der Waals surface forces.

PubMed

Wang, Jianlong; Nguyen, Anh V

2017-12-01

Van der Waals forces are one of the important components of intermolecular, colloidal and surface forces governing many phenomena and processes. The latest examples include the colloidal interactions between hydrophobic colloids and interfaces in ambient (non-degassed) water in which dissolved gases and nanobubbles are shown to affect the van der Waals attractions significantly. The advanced computation of van der Waals forces in aqueous systems by the Lifshitz theory requires reliable data for water dielectric spectra. In this paper we review the available predictions of water dielectric spectra for calculating colloidal and surface van der Waals forces. Specifically, the available experimental data for the real and imaginary parts of the complex dielectric function of liquid water in the microwave, IR and UV regions and various corresponding predictions of the water spectra are critically reviewed. The data in the UV region are critical, but the available predictions are still based on the outdated data obtained in 1974 (for frequency only up to 25.5eV). We also reviewed and analysed the experimental data obtained for the UV region in 2000 (for frequency up to 50eV) and 2015 (for frequency up to 100eV). The 1974 and 2000 data require extrapolations to higher frequencies needed for calculating the van der Waals forces but remain inaccurate. Our analysis shows that the latest data of 2015 do not require the extrapolation and can be used to reliably calculate van der Waals forces. The most recent water dielectric spectra gives the (non-retarded) Hamaker constant, A=5.20×10 -20 J, for foam films of liquid water. This review provides the most updated and reliable water dielectric spectra to compute van der Waals forces in aqueous systems. Copyright © 2017 Elsevier B.V. All rights reserved.

First study of the evolution of the SeDeM expert system parameters based on percolation theory: Monitoring of their critical behavior.

PubMed

Galdón, Eduardo; Casas, Marta; Gayango, Manuel; Caraballo, Isidoro

2016-12-01

The deep understanding of products and processes has become a requirement for pharmaceutical industries to follow the Quality by Design principles promoted by the regulatory authorities. With this aim, SeDeM expert system was developed as a useful preformulation tool to predict the likelihood to process drugs and excipients through direct compression. SeDeM system is a step forward in the rational development of a formulation, allowing the normalisation of the rheological parameters and the identification of the weaknesses and strengths of a powder or a powder blend. However, this method is based on the assumption of a linear behavior of disordered systems. As percolation theory has demonstrated, powder blends behave as non-linear systems that can suffer abrupt changes in their properties near to geometrical phase transitions of the components. The aim of this paper was to analyze for the first time the evolution of the SeDeM parameters in drug/excipient powder blends from the point of view of the percolation theory and to compare the changes predicted by SeDeM with the predictions of Percolation theory. For this purpose, powder blends of lactose and theophylline with varying concentrations of the model drug have been prepared and the SeDeM analysis has been applied to each blend in order to monitor the evolution of their properties. On the other hand, percolation thresholds have been estimated for these powder blends where critical points have been found for important rheological parameters as the powder flow. Finally, the predictions of percolation theory and SeDeM have been compared concluding that percolation theory can complement the SeDeM method for a more accurate estimation of the Design Space. Copyright © 2016 Elsevier B.V. All rights reserved.

A new risk prediction model for critical care: the Intensive Care National Audit & Research Centre (ICNARC) model.

PubMed

Harrison, David A; Parry, Gareth J; Carpenter, James R; Short, Alasdair; Rowan, Kathy

2007-04-01

To develop a new model to improve risk prediction for admissions to adult critical care units in the UK. Prospective cohort study. The setting was 163 adult, general critical care units in England, Wales, and Northern Ireland, December 1995 to August 2003. Patients were 216,626 critical care admissions. None. The performance of different approaches to modeling physiologic measurements was evaluated, and the best methods were selected to produce a new physiology score. This physiology score was combined with other information relating to the critical care admission-age, diagnostic category, source of admission, and cardiopulmonary resuscitation before admission-to develop a risk prediction model. Modeling interactions between diagnostic category and physiology score enabled the inclusion of groups of admissions that are frequently excluded from risk prediction models. The new model showed good discrimination (mean c index 0.870) and fit (mean Shapiro's R 0.665, mean Brier's score 0.132) in 200 repeated validation samples and performed well when compared with recalibrated versions of existing published risk prediction models in the cohort of patients eligible for all models. The hypothesis of perfect fit was rejected for all models, including the Intensive Care National Audit & Research Centre (ICNARC) model, as is to be expected in such a large cohort. The ICNARC model demonstrated better discrimination and overall fit than existing risk prediction models, even following recalibration of these models. We recommend it be used to replace previously published models for risk adjustment in the UK.

Scaling Techniques for Combustion Device Random Vibration Predictions

NASA Technical Reports Server (NTRS)

Kenny, R. J.; Ferebee, R. C.; Duvall, L. D.

2016-01-01

This work presents compares scaling techniques that can be used for prediction of combustion device component random vibration levels with excitation due to the internal combustion dynamics. Acceleration and unsteady dynamic pressure data from multiple component test programs are compared and normalized per the two scaling approaches reviewed. Two scaling technique are reviewed and compared against the collected component test data. The first technique is an existing approach developed by Barrett, and the second technique is an updated approach new to this work. Results from utilizing both techniques are presented and recommendations about future component random vibration prediction approaches are given.

Interactions between Super Typhoon Megi (2010) and the Monsoon Gyre

NASA Astrophysics Data System (ADS)

Peng, M.; Li, T.; Bi, M.; Shen, X.

2015-12-01

Accurate prediction of tropical cyclone track is critical for high-impact weather preparedness, especially as the storm is near the coastal region. The track prediction for super typhoon Megi (2010) in the western Pacific was notoriously bad as most operational models predicated a mainly westward movement while Megi actually made a northward turning after it has crossed the Philippines islands. In this study, we try to understand this rather irregular motion for Megi. Examination of NCEP reanalyzed fields indicated that during this period a low-frequency (10-60-day) monsoon gyre in the vicinity of Megi may have interactions with the latter. To understand the effect of the low-frequency mode on the movement of Megi, numerical experiments were designed and conducted. The total flow from the analyzed field is separated into 1) a slowly varying background state, 2) a 10-60-day low frequency component representing the monsoon gyre, and 3) a 10-day high-pass filtered component representing Megi. In the control experiment, the total field containing all three components is used as the initial and lateral boundary conditions, and the WRF model is able to simulate Megi's sharp northward turning successfully. In the second experiment, the 10-60-day mode is removed from the initial and lateral boundary fields. In the absence of the low-frequency mode, Megi moves westward and only slightly northwestward without turning north. When the vortex representing Megi was removed, the movement of the monsoon gyre was also affected. These experiments indicated strong interactions between Megi and the monsoon gyre. The interactions and the way the monsoon gyre actually affected the track of Megi will be discussed in the presentation.

Environmental Barrier Coating Fracture, Fatigue and High-Heat-Flux Durability Modeling and Stochastic Progressive Damage Simulation

NASA Technical Reports Server (NTRS)

Zhu, Dongming; Nemeth, Noel N.

2017-01-01

Advanced environmental barrier coatings will play an increasingly important role in future gas turbine engines because of their ability to protect emerging light-weight SiC/SiC ceramic matrix composite (CMC) engine components, further raising engine operating temperatures and performance. Because the environmental barrier coating systems are critical to the performance, reliability and durability of these hot-section ceramic engine components, a prime-reliant coating system along with established life design methodology are required for the hot-section ceramic component insertion into engine service. In this paper, we have first summarized some observations of high temperature, high-heat-flux environmental degradation and failure mechanisms of environmental barrier coating systems in laboratory simulated engine environment tests. In particular, the coating surface cracking morphologies and associated subsequent delamination mechanisms under the engine level high-heat-flux, combustion steam, and mechanical creep and fatigue loading conditions will be discussed. The EBC compostion and archtechture improvements based on advanced high heat flux environmental testing, and the modeling advances based on the integrated Finite Element Analysis Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program will also be highlighted. The stochastic progressive damage simulation successfully predicts mud flat damage pattern in EBCs on coated 3-D specimens, and a 2-D model of through-the-thickness cross-section. A 2-parameter Weibull distribution was assumed in characterizing the coating layer stochastic strength response and the formation of damage was therefore modeled. The damage initiation and coalescence into progressively smaller mudflat crack cells was demonstrated. A coating life prediction framework may be realized by examining the surface crack initiation and delamination propagation in conjunction with environmental degradation under high-heat-flux and environment load test conditions.

Carbon Materials for Lithium Sulfur Batteries-Ten Critical Questions.

PubMed

Borchardt, Lars; Oschatz, Martin; Kaskel, Stefan

2016-05-23

Lithium-sulfur batteries are among the most promising electrochemical energy storage devices of the near future. Especially the low price and abundant availability of sulfur as the cathode material and the high theoretical capacity in comparison to state-of-the art lithium-ion technologies are attractive features. Despite significant research achievements that have been made over the last years, fundamental (electro-) chemical questions still remain unanswered. This review addresses ten crucial questions associated with lithium-sulfur batteries and critically evaluates current research with respect to them. The sulfur-carbon composite cathode is a particular focus, but its complex interplay with other hardware components in the cell, such as the electrolyte and the anode, necessitates a critical discussion of other cell components. Modern in situ characterisation methods are ideally suited to illuminate the role of each component. This article does not pretend to summarise all recently published data, but instead is a critical overview over lithium-sulfur batteries based on recent research findings. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Sea level rise impacts on wastewater treatment systems along the U.S. coasts

NASA Astrophysics Data System (ADS)

Hummel, M.; Berry, M.; Stacey, M. T.

2017-12-01

As sea levels rise, coastal communities will experience more frequent and persistent nuisance flooding, and some low-lying areas may be permanently inundated. Critical components of lifeline infrastructure networks in these areas are also at risk of flooding, which could cause significant service disruptions that extend beyond the flooded zone. Thus, identifying critical infrastructure components that are vulnerable to sea level rise is an important first step in developing targeted investment in protective actions and enhancing the overall resilience of coastal communities. Wastewater treatment plants are typically located at low elevations near the coastline to minimize the cost of collecting consumed water and discharging treated effluent, which makes them particularly susceptible to coastal flooding. For this analysis, we used geographic information systems to assess the vulnerability of wastewater infrastructure to various sea level rise projections at the national level. We then estimated the number of people who would lose wastewater services, which could be more than three times as high as previous predictions of the number of people at risk of direct flooding due to sea level rise. We also considered several case studies of wastewater infrastructure in mid-sized cities to determine how topography and system configuration (centralized versus distributed) impact vulnerability. Overall, this analysis highlights the widespread vulnerability of wastewater infrastructure in the U.S. and demonstrates that local disruptions to infrastructure networks may have far-ranging impacts on areas that do not experience direct flooding.

What determines transitions between energy- and moisture-limited evaporative regimes?

NASA Astrophysics Data System (ADS)

Haghighi, E.; Gianotti, D.; Akbar, R.; Salvucci, G.; Entekhabi, D.

2017-12-01

The relationship between evaporative fraction (EF) and soil moisture (SM) has traditionally been used in atmospheric and land-surface modeling communities to determine the strength of land-atmosphere coupling in the context of the dominant evaporative regime (energy- or moisture-limited). However, recent field observations reveal that EF-SM relationship is not unique and could vary substantially with surface and/or meteorological conditions. This implies that conventional EF-SM relationships (exclusive of surface and meteorological conditions) are embedded in more complex dependencies and that in fact it is a multi-dimensional function. To fill the fundamental knowledge gaps on the important role of varying surface and meteorological conditions not accounted for by the traditional evaporative regime conceptualization, we propose a generalized EF framework using a mechanistic pore-scale model for evaporation and energy partitioning over drying soil surfaces. Nonlinear interactions among the components of the surface energy balance are reflected in a critical SM that marks the onset of transition between energy- and moisture-limited evaporative regimes. The new generalized EF framework enables physically based estimates of the critical SM, and provides new insights into the origin of land surface EF partitioning linked to meteorological input data and the evolution of land surface temperature during surface drying that affect the relative efficiency of surface energy balance components. Our results offer new opportunities to advance predictive capabilities quantifying land-atmosphere coupling for a wide range of present and projected meteorological input data.

Coupled thermal-fluid analysis with flowpath-cavity interaction in a gas turbine engine

NASA Astrophysics Data System (ADS)

Fitzpatrick, John Nathan

This study seeks to improve the understanding of inlet conditions of a large rotor-stator cavity in a turbofan engine, often referred to as the drive cone cavity (DCC). The inlet flow is better understood through a higher fidelity computational fluid dynamics (CFD) modeling of the inlet to the cavity, and a coupled finite element (FE) thermal to CFD fluid analysis of the cavity in order to accurately predict engine component temperatures. Accurately predicting temperature distribution in the cavity is important because temperatures directly affect the material properties including Young's modulus, yield strength, fatigue strength, creep properties. All of these properties directly affect the life of critical engine components. In addition, temperatures cause thermal expansion which changes clearances and in turn affects engine efficiency. The DCC is fed from the last stage of the high pressure compressor. One of its primary functions is to purge the air over the rotor wall to prevent it from overheating. Aero-thermal conditions within the DCC cavity are particularly challenging to predict due to the complex air flow and high heat transfer in the rotating component. Thus, in order to accurately predict metal temperatures a two-way coupled CFD-FE analysis is needed. Historically, when the cavity airflow is modeled for engine design purposes, the inlet condition has been over-simplified for the CFD analysis which impacts the results, particularly in the region around the compressor disc rim. The inlet is typically simplified by circumferentially averaging the velocity field at the inlet to the cavity which removes the effect of pressure wakes from the upstream rotor blades. The way in which these non-axisymmetric flow characteristics affect metal temperatures is not well understood. In addition, a constant air temperature scaled from a previous analysis is used as the simplified cavity inlet air temperature. Therefore, the objectives of this study are: (a) model the DCC cavity with a more physically representative inlet condition while coupling the solid thermal analysis and compressible air flow analysis that includes the fluid velocity, pressure, and temperature fields; (b) run a coupled analysis whose boundary conditions come from computational models, rather than thermocouple data; (c) validate the model using available experimental data; and (d) based on the validation, determine if the model can be used to predict air inlet and metal temperatures for new engine geometries. Verification with experimental results showed that the coupled analysis with the 3D no-bolt CFD model with predictive boundary conditions, over-predicted the HP6 offtake temperature by 16k. The maximum error was an over-prediction of 50k while the average error was 17k. The predictive model with 3D bolts also predicted cavity temperatures with an average error of 17k. For the two CFD models with predicted boundary conditions, the case without bolts performed better than the case with bolts. This is due to the flow errors caused by placing stationary bolts in a rotating reference frame. Therefore it is recommended that this type of analysis only be attempted for drive cone cavities with no bolts or shielded bolts.