Flows of engineered nanomaterials through the recycling process in Switzerland.

PubMed

Caballero-Guzman, Alejandro; Sun, Tianyin; Nowack, Bernd

2015-02-01

The use of engineered nanomaterials (ENMs) in diverse applications has increased during the last years and this will likely continue in the near future. As the number of applications increase, more and more waste with nanomaterials will be generated. A portion of this waste will enter the recycling system, for example, in electronic products, textiles and construction materials. The fate of these materials during and after the waste management and recycling operations is poorly understood. The aim of this work is to model the flows of nano-TiO2, nano-ZnO, nano-Ag and CNT in the recycling system in Switzerland. The basis for this study is published information on the ENMs flows on the Swiss system. We developed a method to assess their flow after recycling. To incorporate the uncertainties inherent to the limited information available, we applied a probabilistic material flow analysis approach. The results show that the recycling processes does not result in significant further propagation of nanomaterials into new products. Instead, the largest proportion will flow as waste that can subsequently be properly handled in incineration plants or landfills. Smaller fractions of ENMs will be eliminated or end up in materials that are sent abroad to undergo further recovery processes. Only a reduced amount of ENMs will flow back to the productive process of the economy in a limited number of sectors. Overall, the results suggest that risk assessment during recycling should focus on occupational exposure, release of ENMs in landfills and incineration plants, and toxicity assessment in a small number of recycled inputs. Copyright © 2014 Elsevier Ltd. All rights reserved.

Probabilistic assessment of uncertain adaptive hybrid composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

1994-01-01

Adaptive composite structures using actuation materials, such as piezoelectric fibers, were assessed probabilistically utilizing intraply hybrid composite mechanics in conjunction with probabilistic composite structural analysis. Uncertainties associated with the actuation material as well as the uncertainties in the regular (traditional) composite material properties were quantified and considered in the assessment. Static and buckling analyses were performed for rectangular panels with various boundary conditions and different control arrangements. The probability density functions of the structural behavior, such as maximum displacement and critical buckling load, were computationally simulated. The results of the assessment indicate that improved design and reliability can be achieved with actuation material.

Environmental risk assessment of engineered nano-SiO2 , nano iron oxides, nano-CeO2 , nano-Al2 O3 , and quantum dots.

PubMed

Wang, Yan; Nowack, Bernd

2018-05-01

Many research studies have endeavored to investigate the ecotoxicological hazards of engineered nanomaterials (ENMs). However, little is known regarding the actual environmental risks of ENMs, combining both hazard and exposure data. The aim of the present study was to quantify the environmental risks for nano-Al 2 O 3 , nano-SiO 2 , nano iron oxides, nano-CeO 2 , and quantum dots by comparing the predicted environmental concentrations (PECs) with the predicted-no-effect concentrations (PNECs). The PEC values of these 5 ENMs in freshwaters in 2020 for northern Europe and southeastern Europe were taken from a published dynamic probabilistic material flow analysis model. The PNEC values were calculated using probabilistic species sensitivity distribution (SSD). The order of the PNEC values was quantum dots < nano-CeO 2  < nano iron oxides < nano-Al 2 O 3  < nano-SiO 2 . The risks posed by these 5 ENMs were demonstrated to be in the reverse order: nano-Al 2 O 3  > nano-SiO 2  > nano iron oxides > nano-CeO 2  > quantum dots. However, all risk characterization values are 4 to 8 orders of magnitude lower than 1, and no risk was therefore predicted for any of the investigated ENMs at the estimated release level in 2020. Compared to static models, the dynamic material flow model allowed us to use PEC values based on a more complex parameterization, considering a dynamic input over time and time-dependent release of ENMs. The probabilistic SSD approach makes it possible to include all available data to estimate hazards of ENMs by considering the whole range of variability between studies and material types. The risk-assessment approach is therefore able to handle the uncertainty and variability associated with the collected data. The results of the present study provide a scientific foundation for risk-based regulatory decisions of the investigated ENMs. Environ Toxicol Chem 2018;37:1387-1395. © 2018 SETAC. © 2018 SETAC.

Probabilistic Evaluation of Advanced Ceramic Matrix Composite Structures

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

The objective of this report is to summarize the deterministic and probabilistic structural evaluation results of two structures made with advanced ceramic composites (CMC): internally pressurized tube and uniformly loaded flange. The deterministic structural evaluation includes stress, displacement, and buckling analyses. It is carried out using the finite element code MHOST, developed for the 3-D inelastic analysis of structures that are made with advanced materials. The probabilistic evaluation is performed using the integrated probabilistic assessment of composite structures computer code IPACS. The affects of uncertainties in primitive variables related to the material, fabrication process, and loadings on the material property and structural response behavior are quantified. The primitive variables considered are: thermo-mechanical properties of fiber and matrix, fiber and void volume ratios, use temperature, and pressure. The probabilistic structural analysis and probabilistic strength results are used by IPACS to perform reliability and risk evaluation of the two structures. The results will show that the sensitivity information obtained for the two composite structures from the computational simulation can be used to alter the design process to meet desired service requirements. In addition to detailed probabilistic analysis of the two structures, the following were performed specifically on the CMC tube: (1) predicted the failure load and the buckling load, (2) performed coupled non-deterministic multi-disciplinary structural analysis, and (3) demonstrated that probabilistic sensitivities can be used to select a reduced set of design variables for optimization.

Flows of engineered nanomaterials through the recycling process in Switzerland

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

Caballero-Guzman, Alejandro; Sun, Tianyin; Nowack, Bernd, E-mail: nowack@empa.ch

Highlights: • Recycling is one of the likely end-of-life fates of nanoproducts. • We assessed the material flows of four nanomaterials in the Swiss recycling system. • After recycling, most nanomaterials will flow to landfills or incineration plants. • Recycled construction waste, plastics and textiles may contain nanomaterials. - Abstract: The use of engineered nanomaterials (ENMs) in diverse applications has increased during the last years and this will likely continue in the near future. As the number of applications increase, more and more waste with nanomaterials will be generated. A portion of this waste will enter the recycling system, formore » example, in electronic products, textiles and construction materials. The fate of these materials during and after the waste management and recycling operations is poorly understood. The aim of this work is to model the flows of nano-TiO{sub 2}, nano-ZnO, nano-Ag and CNT in the recycling system in Switzerland. The basis for this study is published information on the ENMs flows on the Swiss system. We developed a method to assess their flow after recycling. To incorporate the uncertainties inherent to the limited information available, we applied a probabilistic material flow analysis approach. The results show that the recycling processes does not result in significant further propagation of nanomaterials into new products. Instead, the largest proportion will flow as waste that can subsequently be properly handled in incineration plants or landfills. Smaller fractions of ENMs will be eliminated or end up in materials that are sent abroad to undergo further recovery processes. Only a reduced amount of ENMs will flow back to the productive process of the economy in a limited number of sectors. Overall, the results suggest that risk assessment during recycling should focus on occupational exposure, release of ENMs in landfills and incineration plants, and toxicity assessment in a small number of recycled inputs.« less

Probabilistic Estimation of Critical Flaw Sizes in the Primary Structure Welds of the Ares I-X Launch Vehicle

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Hoge, Peter A.; Patel, B. M.; Nagpal, Vinod K.

2009-01-01

The primary structure of the Ares I-X Upper Stage Simulator (USS) launch vehicle is constructed of welded mild steel plates. There is some concern over the possibility of structural failure due to welding flaws. It was considered critical to quantify the impact of uncertainties in residual stress, material porosity, applied loads, and material and crack growth properties on the reliability of the welds during its pre-flight and flight. A criterion--an existing maximum size crack at the weld toe must be smaller than the maximum allowable flaw size--was established to estimate the reliability of the welds. A spectrum of maximum allowable flaw sizes was developed for different possible combinations of all of the above listed variables by performing probabilistic crack growth analyses using the ANSYS finite element analysis code in conjunction with the NASGRO crack growth code. Two alternative methods were used to account for residual stresses: (1) The mean residual stress was assumed to be 41 ksi and a limit was set on the net section flow stress during crack propagation. The critical flaw size was determined by parametrically increasing the initial flaw size and detecting if this limit was exceeded during four complete flight cycles, and (2) The mean residual stress was assumed to be 49.6 ksi (the parent material s yield strength) and the net section flow stress limit was ignored. The critical flaw size was determined by parametrically increasing the initial flaw size and detecting if catastrophic crack growth occurred during four complete flight cycles. Both surface-crack models and through-crack models were utilized to characterize cracks in the weld toe.

Application of Probabilistic Analysis to Aircraft Impact Dynamics

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Padula, Sharon L.; Stockwell, Alan E.

2003-01-01

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stressstrain behaviors, laminated composites, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the uncertainty in the simulated responses. Several criteria are used to determine that a response surface method is the most appropriate probabilistic approach. The work is extended to compare optimization results with and without probabilistic constraints.

Lagrangian based methods for coherent structure detection

NASA Astrophysics Data System (ADS)

Allshouse, Michael R.; Peacock, Thomas

2015-09-01

There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other two approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.

A probabilistic model for the persistence of early planar fabrics in polydeformed pelitic schists

USGS Publications Warehouse

Ferguson, C.C.

1984-01-01

Although early planar fabrics are commonly preserved within microlithons in low-grade pelites, in higher-grade (amphibolite facies) pelitic schists fabric regeneration often appears complete. Evidence for early fabrics may be preserved within porphyroblasts but, within the matrix, later deformation often appears to totally obliterate or reorient earlier fabrics. However, examination of several hundred Dalradian pelites from Connemara, western Ireland, reveals that preservation of early fabrics is by no means uncommon; relict matrix domains, although volumetrically insignificant, are remarkably persistent even when inferred later strains are very large and fabric regeneration appears, at first sight, complete. Deterministic plasticity theories are ill-suited to the analysis of such an inhomogeneous material response, and a probabilistic model is proposed instead. It assumes that ductile polycrystal deformation is controlled by elementary flow units which can be activated once their associated stress barrier is overcome. Bulk flow propensity is related to the proportion of simultaneous activations, and a measure of this is derived from the probabilistic interaction between a stress-barrier spectrum and an internal stress spectrum (the latter determined by the external loading and the details of internal stress transfer). The spectra are modelled as Gaussian distributions although the treatment is very general and could be adapted for other distributions. Using the time rate of change of activation probability it is predicted that, initially, fabric development will be rapid but will then slow down dramatically even though stress increases at a constant rate. This highly non-linear response suggests that early fabrics persist because they comprise unfavourable distributions of stress-barriers which remain unregenerated at the time bulk stress is stabilized by steady-state flow. Relict domains will, however, bear the highest stress and are potential upper-bound palaeostress estimators. Some factors relevant to the micromechanical explanation of relict matrix domains are discussed. ?? 1984.

Probabilistic finite elements for fracture mechanics

NASA Technical Reports Server (NTRS)

Besterfield, Glen

1988-01-01

The probabilistic finite element method (PFEM) is developed for probabilistic fracture mechanics (PFM). A finite element which has the near crack-tip singular strain embedded in the element is used. Probabilistic distributions, such as expectation, covariance and correlation stress intensity factors, are calculated for random load, random material and random crack length. The method is computationally quite efficient and can be expected to determine the probability of fracture or reliability.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion systems components

NASA Technical Reports Server (NTRS)

1991-01-01

Summarized here is the technical effort and computer code developed during the five year duration of the program for probabilistic structural analysis methods. The summary includes a brief description of the computer code manuals and a detailed description of code validation demonstration cases for random vibrations of a discharge duct, probabilistic material nonlinearities of a liquid oxygen post, and probabilistic buckling of a transfer tube liner.

Probabilistic Structural Analysis Program

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

2010-01-01

NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

Fuzzy-probabilistic model for risk assessment of radioactive material railway transportation.

PubMed

Avramenko, M; Bolyatko, V; Kosterev, V

2005-01-01

Transportation of radioactive materials is obviously accompanied by a certain risk. A model for risk assessment of emergency situations and terrorist attacks may be useful for choosing possible routes and for comparing the various defence strategies. In particular, risk assessment is crucial for safe transportation of excess weapons-grade plutonium arising from the removal of plutonium from military employment. A fuzzy-probabilistic model for risk assessment of railway transportation has been developed taking into account the different natures of risk-affecting parameters (probabilistic and not probabilistic but fuzzy). Fuzzy set theory methods as well as standard methods of probability theory have been used for quantitative risk assessment. Information-preserving transformations are applied to realise the correct aggregation of probabilistic and fuzzy parameters. Estimations have also been made of the inhalation doses resulting from possible accidents during plutonium transportation. The obtained data show the scale of possible consequences that may arise from plutonium transportation accidents.

Parametric study of irradiation effects on the ductile damage and flow stress behavior in ferritic-martensitic steels

NASA Astrophysics Data System (ADS)

Chakraborty, Pritam; Biner, S. Bulent

2015-10-01

Ferritic-martensitic steels are currently being considered as structural materials in fusion and Gen-IV nuclear reactors. These materials are expected to experience high dose radiation, which can increase their ductile to brittle transition temperature and susceptibility to failure during operation. Hence, to estimate the safe operational life of the reactors, precise evaluation of the ductile to brittle transition temperatures of ferritic-martensitic steels is necessary. Owing to the scarcity of irradiated samples, particularly at high dose levels, micro-mechanistic models are being employed to predict the shifts in the ductile to brittle transition temperatures. These models consider the ductile damage evolution, in the form of nucleation, growth and coalescence of voids; and the brittle fracture, in the form of probabilistic cleavage initiation, to estimate the influence of irradiation on the ductile to brittle transition temperature. However, the assessment of irradiation dependent material parameters is challenging and influences the accuracy of these models. In the present study, the effects of irradiation on the overall flow stress and ductile damage behavior of two ferritic-martensitic steels is parametrically investigated. The results indicate that the ductile damage model parameters are mostly insensitive to irradiation levels at higher dose levels though the resulting flow stress behavior varies significantly.

Probabilistic Prediction of Lifetimes of Ceramic Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Gyekenyesi, John P.; Jadaan, Osama M.; Palfi, Tamas; Powers, Lynn; Reh, Stefan; Baker, Eric H.

2006-01-01

ANSYS/CARES/PDS is a software system that combines the ANSYS Probabilistic Design System (PDS) software with a modified version of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) Version 6.0 software. [A prior version of CARES/Life was reported in Program for Evaluation of Reliability of Ceramic Parts (LEW-16018), NASA Tech Briefs, Vol. 20, No. 3 (March 1996), page 28.] CARES/Life models effects of stochastic strength, slow crack growth, and stress distribution on the overall reliability of a ceramic component. The essence of the enhancement in CARES/Life 6.0 is the capability to predict the probability of failure using results from transient finite-element analysis. ANSYS PDS models the effects of uncertainty in material properties, dimensions, and loading on the stress distribution and deformation. ANSYS/CARES/PDS accounts for the effects of probabilistic strength, probabilistic loads, probabilistic material properties, and probabilistic tolerances on the lifetime and reliability of the component. Even failure probability becomes a stochastic quantity that can be tracked as a response variable. ANSYS/CARES/PDS enables tracking of all stochastic quantities in the design space, thereby enabling more precise probabilistic prediction of lifetimes of ceramic components.

PCEMCAN - Probabilistic Ceramic Matrix Composites Analyzer: User's Guide, Version 1.0

NASA Technical Reports Server (NTRS)

Shah, Ashwin R.; Mital, Subodh K.; Murthy, Pappu L. N.

1998-01-01

PCEMCAN (Probabalistic CEramic Matrix Composites ANalyzer) is an integrated computer code developed at NASA Lewis Research Center that simulates uncertainties associated with the constituent properties, manufacturing process, and geometric parameters of fiber reinforced ceramic matrix composites and quantifies their random thermomechanical behavior. The PCEMCAN code can perform the deterministic as well as probabilistic analyses to predict thermomechanical properties. This User's guide details the step-by-step procedure to create input file and update/modify the material properties database required to run PCEMCAN computer code. An overview of the geometric conventions, micromechanical unit cell, nonlinear constitutive relationship and probabilistic simulation methodology is also provided in the manual. Fast probability integration as well as Monte-Carlo simulation methods are available for the uncertainty simulation. Various options available in the code to simulate probabilistic material properties and quantify sensitivity of the primitive random variables have been described. The description of deterministic as well as probabilistic results have been described using demonstration problems. For detailed theoretical description of deterministic and probabilistic analyses, the user is referred to the companion documents "Computational Simulation of Continuous Fiber-Reinforced Ceramic Matrix Composite Behavior," NASA TP-3602, 1996 and "Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites", NASA TM 4766, June 1997.

Probabilistic simulation of stress concentration in composite laminates

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Liaw, L.

1993-01-01

A computational methodology is described to probabilistically simulate the stress concentration factors in composite laminates. This new approach consists of coupling probabilistic composite mechanics with probabilistic finite element structural analysis. The probabilistic composite mechanics is used to probabilistically describe all the uncertainties inherent in composite material properties while probabilistic finite element is used to probabilistically describe the uncertainties associated with methods to experimentally evaluate stress concentration factors such as loads, geometry, and supports. The effectiveness of the methodology is demonstrated by using it to simulate the stress concentration factors in composite laminates made from three different composite systems. Simulated results match experimental data for probability density and for cumulative distribution functions. The sensitivity factors indicate that the stress concentration factors are influenced by local stiffness variables, by load eccentricities and by initial stress fields.

Probabilistic Evaluation of Blade Impact Damage

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Abumeri, G. H.

2003-01-01

The response to high velocity impact of a composite blade is probabilistically evaluated. The evaluation is focused on quantifying probabilistically the effects of uncertainties (scatter) in the variables that describe the impact, the blade make-up (geometry and material), the blade response (displacements, strains, stresses, frequencies), the blade residual strength after impact, and the blade damage tolerance. The results of probabilistic evaluations results are in terms of probability cumulative distribution functions and probabilistic sensitivities. Results show that the blade has relatively low damage tolerance at 0.999 probability of structural failure and substantial at 0.01 probability.

Probabilistic structural analysis of aerospace components using NESSUS

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Nagpal, Vinod K.; Chamis, Christos C.

1988-01-01

Probabilistic structural analysis of a Space Shuttle main engine turbopump blade is conducted using the computer code NESSUS (numerical evaluation of stochastic structures under stress). The goal of the analysis is to derive probabilistic characteristics of blade response given probabilistic descriptions of uncertainties in blade geometry, material properties, and temperature and pressure distributions. Probability densities are derived for critical blade responses. Risk assessment and failure life analysis is conducted assuming different failure models.

Development of Probabilistic Rigid Pavement Design Methodologies for Military Airfields.

DTIC Science & Technology

1983-12-01

4A161102AT22, Task AO, Work Unit 009, "Methodology for Considering Material Variability in Pavement Design." OCE Project Monitor was Mr. S. S. Gillespie. The...PREFACE. .. ............................. VOLUME 1: STATE OF THE ART VARIABILITY OF AIRFIELD PAVEMENT MATERIALS VOLUME 11: MATHEMATICAL FORMULATION OF...VOLUME IV: PROBABILISTIC ANALYSIS OF RIGID AIRFIELD DESIGN BY ELASTIC LAYERED THEORY VOLUME I STATE OF THE ART VARIABILITY OF AIRFIELD PAVEMENT MATERIALS

Computational simulation of coupled material degradation processes for probabilistic lifetime strength of aerospace materials

NASA Technical Reports Server (NTRS)

Boyce, Lola; Bast, Callie C.

1992-01-01

The research included ongoing development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects or primative variables. These primative variable may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above described constitutive equation using actual experimental materials data together with linear regression of that data, thereby predicting values for the empirical material constraints for each effect or primative variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from the open literature for materials typically of interest to those studying aerospace propulsion system components. Material data for Inconel 718 was analyzed using the developed methodology.

Lagrangian based methods for coherent structure detection

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

Allshouse, Michael R., E-mail: mallshouse@chaos.utexas.edu; Peacock, Thomas, E-mail: tomp@mit.edu

There has been a proliferation in the development of Lagrangian analytical methods for detecting coherent structures in fluid flow transport, yielding a variety of qualitatively different approaches. We present a review of four approaches and demonstrate the utility of these methods via their application to the same sample analytic model, the canonical double-gyre flow, highlighting the pros and cons of each approach. Two of the methods, the geometric and probabilistic approaches, are well established and require velocity field data over the time interval of interest to identify particularly important material lines and surfaces, and influential regions, respectively. The other twomore » approaches, implementing tools from cluster and braid theory, seek coherent structures based on limited trajectory data, attempting to partition the flow transport into distinct regions. All four of these approaches share the common trait that they are objective methods, meaning that their results do not depend on the frame of reference used. For each method, we also present a number of example applications ranging from blood flow and chemical reactions to ocean and atmospheric flows.« less

The pdf approach to turbulent polydispersed two-phase flows

NASA Astrophysics Data System (ADS)

Minier, Jean-Pierre; Peirano, Eric

2001-10-01

The purpose of this paper is to develop a probabilistic approach to turbulent polydispersed two-phase flows. The two-phase flows considered are composed of a continuous phase, which is a turbulent fluid, and a dispersed phase, which represents an ensemble of discrete particles (solid particles, droplets or bubbles). Gathering the difficulties of turbulent flows and of particle motion, the challenge is to work out a general modelling approach that meets three requirements: to treat accurately the physically relevant phenomena, to provide enough information to address issues of complex physics (combustion, polydispersed particle flows, …) and to remain tractable for general non-homogeneous flows. The present probabilistic approach models the statistical dynamics of the system and consists in simulating the joint probability density function (pdf) of a number of fluid and discrete particle properties. A new point is that both the fluid and the particles are included in the pdf description. The derivation of the joint pdf model for the fluid and for the discrete particles is worked out in several steps. The mathematical properties of stochastic processes are first recalled. The various hierarchies of pdf descriptions are detailed and the physical principles that are used in the construction of the models are explained. The Lagrangian one-particle probabilistic description is developed first for the fluid alone, then for the discrete particles and finally for the joint fluid and particle turbulent systems. In the case of the probabilistic description for the fluid alone or for the discrete particles alone, numerical computations are presented and discussed to illustrate how the method works in practice and the kind of information that can be extracted from it. Comments on the current modelling state and propositions for future investigations which try to link the present work with other ideas in physics are made at the end of the paper.

Stochastic fundamental diagram for probabilistic traffic flow modeling.

DOT National Transportation Integrated Search

2011-09-01

Flowing water in river, transported gas or oil in pipe, electric current in wire, moving : goods on conveyor, molecular motors in living cell, and driving vehicles on a highway are : various kinds of flow from physical or non-physical systems, yet ea...

Probabilistic lifetime strength of aerospace materials via computational simulation

NASA Technical Reports Server (NTRS)

Boyce, Lola; Keating, Jerome P.; Lovelace, Thomas B.; Bast, Callie C.

1991-01-01

The results of a second year effort of a research program are presented. The research included development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic phenomenological constitutive relationship, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects of primitive variables. These primitive variables often originate in the environment and may include stress from loading, temperature, chemical, or radiation attack. This multifactor interaction constitutive equation is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the constitutive equation using actual experimental materials data together with the multiple linear regression of that data.

Probabilistic fatigue life prediction of metallic and composite materials

NASA Astrophysics Data System (ADS)

Xiang, Yibing

Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.

Probabilistic models for reactive behaviour in heterogeneous condensed phase media

NASA Astrophysics Data System (ADS)

Baer, M. R.; Gartling, D. K.; DesJardin, P. E.

2012-02-01

This work presents statistically-based models to describe reactive behaviour in heterogeneous energetic materials. Mesoscale effects are incorporated in continuum-level reactive flow descriptions using probability density functions (pdfs) that are associated with thermodynamic and mechanical states. A generalised approach is presented that includes multimaterial behaviour by treating the volume fraction as a random kinematic variable. Model simplifications are then sought to reduce the complexity of the description without compromising the statistical approach. Reactive behaviour is first considered for non-deformable media having a random temperature field as an initial state. A pdf transport relationship is derived and an approximate moment approach is incorporated in finite element analysis to model an example application whereby a heated fragment impacts a reactive heterogeneous material which leads to a delayed cook-off event. Modelling is then extended to include deformation effects associated with shock loading of a heterogeneous medium whereby random variables of strain, strain-rate and temperature are considered. A demonstrative mesoscale simulation of a non-ideal explosive is discussed that illustrates the joint statistical nature of the strain and temperature fields during shock loading to motivate the probabilistic approach. This modelling is derived in a Lagrangian framework that can be incorporated in continuum-level shock physics analysis. Future work will consider particle-based methods for a numerical implementation of this modelling approach.

Are engineered nano iron oxide particles safe? an environmental risk assessment by probabilistic exposure, effects and risk modeling.

PubMed

Wang, Yan; Deng, Lei; Caballero-Guzman, Alejandro; Nowack, Bernd

2016-12-01

Nano iron oxide particles are beneficial to our daily lives through their use in paints, construction materials, biomedical imaging and other industrial fields. However, little is known about the possible risks associated with the current exposure level of engineered nano iron oxides (nano-FeOX) to organisms in the environment. The goal of this study was to predict the release of nano-FeOX to the environment and assess their risks for surface waters in the EU and Switzerland. The material flows of nano-FeOX to technical compartments (waste incineration and waste water treatment plants) and to the environment were calculated with a probabilistic modeling approach. The mean value of the predicted environmental concentrations (PECs) of nano-FeOX in surface waters in the EU for a worst-case scenario (no particle sedimentation) was estimated to be 28 ng/l. Using a probabilistic species sensitivity distribution, the predicted no-effect concentration (PNEC) was determined from ecotoxicological data. The risk characterization ratio, calculated by dividing the PEC by PNEC values, was used to characterize the risks. The mean risk characterization ratio was predicted to be several orders of magnitude smaller than 1 (1.4 × 10 - 4 ). Therefore, this modeling effort indicates that only a very limited risk is posed by the current release level of nano-FeOX to organisms in surface waters. However, a better understanding of the hazards of nano-FeOX to the organisms in other ecosystems (such as sediment) needs to be assessed to determine the overall risk of these particles to the environment.

CARES/Life Used for Probabilistic Characterization of MEMS Pressure Sensor Membranes

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

2002-01-01

Microelectromechanical systems (MEMS) devices are typically made from brittle materials such as silicon using traditional semiconductor manufacturing techniques. They can be etched (or micromachined) from larger structures or can be built up with material deposition processes. Maintaining dimensional control and consistent mechanical properties is considerably more difficult for MEMS because feature size is on the micrometer scale. Therefore, the application of probabilistic design methodology becomes necessary for MEMS. This was demonstrated at the NASA Glenn Research Center and Case Western Reserve University in an investigation that used the NASA-developed CARES/Life brittle material design program to study the probabilistic fracture strength behavior of single-crystal SiC, polycrystalline SiC, and amorphous Si3N4 pressurized 1-mm-square thin-film diaphragms. These materials are of interest because of their superior high-temperature characteristics, which are desirable for harsh environment applications such as turbine engine and rocket propulsion system hot sections.

Mixing zone and drinking water intake dilution factor and wastewater generation distributions to enable probabilistic assessment of down-the-drain consumer product chemicals in the U.S.

PubMed

Kapo, Katherine E; McDonough, Kathleen; Federle, Thomas; Dyer, Scott; Vamshi, Raghu

2015-06-15

Environmental exposure and associated ecological risk related to down-the-drain chemicals discharged by municipal wastewater treatment plants (WWTPs) are strongly influenced by in-stream dilution of receiving waters which varies by geography, flow conditions and upstream wastewater inputs. The iSTREEM® model (American Cleaning Institute, Washington D.C.) was utilized to determine probabilistic distributions for no decay and decay-based dilution factors in mean annual and low (7Q10) flow conditions. The dilution factors derived in this study are "combined" dilution factors which account for both hydrologic dilution and cumulative upstream effluent contributions that will differ depending on the rate of in-stream decay due to biodegradation, volatilization, sorption, etc. for the chemical being evaluated. The median dilution factors estimated in this study (based on various in-stream decay rates from zero decay to a 1h half-life) for WWTP mixing zones dominated by domestic wastewater flow ranged from 132 to 609 at mean flow and 5 to 25 at low flow, while median dilution factors at drinking water intakes (mean flow) ranged from 146 to 2×10(7) depending on the in-stream decay rate. WWTPs within the iSTREEM® model were used to generate a distribution of per capita wastewater generated in the U.S. The dilution factor and per capita wastewater generation distributions developed by this work can be used to conduct probabilistic exposure assessments for down-the-drain chemicals in influent wastewater, wastewater treatment plant mixing zones and at drinking water intakes in the conterminous U.S. In addition, evaluation of types and abundance of U.S. wastewater treatment processes provided insight into treatment trends and the flow volume treated by each type of process. Moreover, removal efficiencies of chemicals can differ by treatment type. Hence, the availability of distributions for per capita wastewater production, treatment type, and dilution factors at a national level provides a series of practical and powerful tools for building probabilistic exposure models. Copyright © 2015 Elsevier B.V. All rights reserved.

Probabilistic Simulation of Stress Concentration in Composite Laminates

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Murthy, P. L. N.; Liaw, D. G.

1994-01-01

A computational methodology is described to probabilistically simulate the stress concentration factors (SCF's) in composite laminates. This new approach consists of coupling probabilistic composite mechanics with probabilistic finite element structural analysis. The composite mechanics is used to probabilistically describe all the uncertainties inherent in composite material properties, whereas the finite element is used to probabilistically describe the uncertainties associated with methods to experimentally evaluate SCF's, such as loads, geometry, and supports. The effectiveness of the methodology is demonstrated by using is to simulate the SCF's in three different composite laminates. Simulated results match experimental data for probability density and for cumulative distribution functions. The sensitivity factors indicate that the SCF's are influenced by local stiffness variables, by load eccentricities, and by initial stress fields.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

NASA Technical Reports Server (NTRS)

1991-01-01

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Optimization of Adaptive Intraply Hybrid Fiber Composites with Reliability Considerations

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1994-01-01

The reliability with bounded distribution parameters (mean, standard deviation) was maximized and the reliability-based cost was minimized for adaptive intra-ply hybrid fiber composites by using a probabilistic method. The probabilistic method accounts for all naturally occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry, and control-related parameters. Probabilistic sensitivity factors were computed and used in the optimization procedures. For actuated change in the angle of attack of an airfoil-like composite shell structure with an adaptive torque plate, the reliability was maximized to 0.9999 probability, with constraints on the mean and standard deviation of the actuation material volume ratio (percentage of actuation composite material in a ply) and the actuation strain coefficient. The reliability-based cost was minimized for an airfoil-like composite shell structure with an adaptive skin and a mean actuation material volume ratio as the design parameter. At a O.9-mean actuation material volume ratio, the minimum cost was obtained.

Probabilistic commodity-flow-based focusing of monitoring activities to facilitate early detection of Phytophthora ramorum outbreaks

Treesearch

Steven C. McKelvey; William D. Smith; Frank Koch

2012-01-01

This project summary describes a probabilistic model developed with funding support from the Forest Health Monitoring Program of the Forest Service, U.S. Department of Agriculture (BaseEM Project SO-R-08-01). The model has been implemented in SODBuster, a standalone software package developed using the Java software development kit from Sun Microsystems.

Recent developments of the NESSUS probabilistic structural analysis computer program

NASA Technical Reports Server (NTRS)

Millwater, H.; Wu, Y.-T.; Torng, T.; Thacker, B.; Riha, D.; Leung, C. P.

1992-01-01

The NESSUS probabilistic structural analysis computer program combines state-of-the-art probabilistic algorithms with general purpose structural analysis methods to compute the probabilistic response and the reliability of engineering structures. Uncertainty in loading, material properties, geometry, boundary conditions and initial conditions can be simulated. The structural analysis methods include nonlinear finite element and boundary element methods. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. The scope of the code has recently been expanded to include probabilistic life and fatigue prediction of structures in terms of component and system reliability and risk analysis of structures considering cost of failure. The code is currently being extended to structural reliability considering progressive crack propagation. Several examples are presented to demonstrate the new capabilities.

A New Interpretation of Effects of the Probabilistic Delayed Start on the One-Dimensional Traffic Flow

NASA Astrophysics Data System (ADS)

Ishibashi, Yoshihiro; Fukui, Minoru

2018-03-01

The effect of the probabilistic delayed start on the one-dimensional traffic flow is investigated on the basis of several models. Analogy with the degeneracy of the states and its resolution, as well as that with the mathematical procedures adopted for them, is utilized. The perturbation is assumed to be proportional to the probability of the delayed start, and the perturbation function is determined so that imposed conditions are fulfilled. The obtained formulas coincide with those previously derived on the basis of the mean-field analyses of the Nagel-Schreckenberg and Fukui-Ishibashi models, and reproduce the cellular automaton simulation results.

GENERAL: A modified weighted probabilistic cellular automaton traffic flow model

NASA Astrophysics Data System (ADS)

Zhuang, Qian; Jia, Bin; Li, Xin-Gang

2009-08-01

This paper modifies the weighted probabilistic cellular automaton model (Li X L, Kuang H, Song T, et al 2008 Chin. Phys. B 17 2366) which considered a diversity of traffic behaviors under real traffic situations induced by various driving characters and habits. In the new model, the effects of the velocity at the last time step and drivers' desire for acceleration are taken into account. The fundamental diagram, spatial-temporal diagram, and the time series of one-minute data are analyzed. The results show that this model reproduces synchronized flow. Finally, it simulates the on-ramp system with the proposed model. Some characteristics including the phase diagram are studied.

Stochastic methods for analysis of power flow in electric networks

NASA Astrophysics Data System (ADS)

1982-09-01

The modeling and effects of probabilistic behavior on steady state power system operation were analyzed. A solution to the steady state network flow equations which adhere both to Kirchoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques was obtained. The development of sound techniques for producing meaningful data to serve as input is examined. Electric demand modeling, equipment failure analysis, and algorithm development are investigated. Two major development areas are described: a decomposition of stochastic processes which gives stationarity, ergodicity, and even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.

Adaptive probabilistic collocation based Kalman filter for unsaturated flow problem

NASA Astrophysics Data System (ADS)

Man, J.; Li, W.; Zeng, L.; Wu, L.

2015-12-01

The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the Polynomial Chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so called "cure of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF is even more computationally expensive than EnKF. Motivated by recent developments in uncertainty quantification, we propose a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problem. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to alleviate the inconsistency between model parameters and states. The performance of RAPCKF is tested by unsaturated flow numerical cases. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-01-01

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm. PMID:28587084

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors.

PubMed

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-05-25

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ -connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm.

Probabilistic evaluation of uncertainties and risks in aerospace components

NASA Technical Reports Server (NTRS)

Shah, A. R.; Shiao, M. C.; Nagpal, V. K.; Chamis, C. C.

1992-01-01

A methodology is presented for the computational simulation of primitive variable uncertainties, and attention is given to the simulation of specific aerospace components. Specific examples treated encompass a probabilistic material behavior model, as well as static, dynamic, and fatigue/damage analyses of a turbine blade in a mistuned bladed rotor in the SSME turbopumps. An account is given of the use of the NESSES probabilistic FEM analysis CFD code.

Terminal Model Of Newtonian Dynamics

NASA Technical Reports Server (NTRS)

Zak, Michail

1994-01-01

Paper presents study of theory of Newtonian dynamics of terminal attractors and repellers, focusing on issues of reversibility vs. irreversibility and deterministic evolution vs. probabilistic or chaotic evolution of dynamic systems. Theory developed called "terminal dynamics" emphasizes difference between it and classical Newtonian dynamics. Also holds promise for explaining irreversibility, unpredictability, probabilistic behavior, and chaos in turbulent flows, in thermodynamic phenomena, and in other dynamic phenomena and systems.

Comparison of Deterministic and Probabilistic Radial Distribution Systems Load Flow

NASA Astrophysics Data System (ADS)

Gupta, Atma Ram; Kumar, Ashwani

2017-12-01

Distribution system network today is facing the challenge of meeting increased load demands from the industrial, commercial and residential sectors. The pattern of load is highly dependent on consumer behavior and temporal factors such as season of the year, day of the week or time of the day. For deterministic radial distribution load flow studies load is taken as constant. But, load varies continually with a high degree of uncertainty. So, there is a need to model probable realistic load. Monte-Carlo Simulation is used to model the probable realistic load by generating random values of active and reactive power load from the mean and standard deviation of the load and for solving a Deterministic Radial Load Flow with these values. The probabilistic solution is reconstructed from deterministic data obtained for each simulation. The main contribution of the work is: Finding impact of probable realistic ZIP load modeling on balanced radial distribution load flow. Finding impact of probable realistic ZIP load modeling on unbalanced radial distribution load flow. Compare the voltage profile and losses with probable realistic ZIP load modeling for balanced and unbalanced radial distribution load flow.

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, High-Cycle and Low-Cycle Mechanical Fatigue, Creep and Thermal Fatigue Effects

NASA Technical Reports Server (NTRS)

Bast, Callie C.; Boyce, Lola

1995-01-01

The development of methodology for a probabilistic material strength degradation is described. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes five effects that typically reduce lifetime strength: high temperature, high-cycle mechanical fatigue, low-cycle mechanical fatigue, creep and thermal fatigue. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing predictions of high-cycle mechanical fatigue and high temperature effects with experiments are presented. Results from this limited verification study strongly supported that material degradation can be represented by randomized multifactor interaction models.

Probabilistic design of fibre concrete structures

NASA Astrophysics Data System (ADS)

Pukl, R.; Novák, D.; Sajdlová, T.; Lehký, D.; Červenka, J.; Červenka, V.

2017-09-01

Advanced computer simulation is recently well-established methodology for evaluation of resistance of concrete engineering structures. The nonlinear finite element analysis enables to realistically predict structural damage, peak load, failure, post-peak response, development of cracks in concrete, yielding of reinforcement, concrete crushing or shear failure. The nonlinear material models can cover various types of concrete and reinforced concrete: ordinary concrete, plain or reinforced, without or with prestressing, fibre concrete, (ultra) high performance concrete, lightweight concrete, etc. Advanced material models taking into account fibre concrete properties such as shape of tensile softening branch, high toughness and ductility are described in the paper. Since the variability of the fibre concrete material properties is rather high, the probabilistic analysis seems to be the most appropriate format for structural design and evaluation of structural performance, reliability and safety. The presented combination of the nonlinear analysis with advanced probabilistic methods allows evaluation of structural safety characterized by failure probability or by reliability index respectively. Authors offer a methodology and computer tools for realistic safety assessment of concrete structures; the utilized approach is based on randomization of the nonlinear finite element analysis of the structural model. Uncertainty of the material properties or their randomness obtained from material tests are accounted in the random distribution. Furthermore, degradation of the reinforced concrete materials such as carbonation of concrete, corrosion of reinforcement, etc. can be accounted in order to analyze life-cycle structural performance and to enable prediction of the structural reliability and safety in time development. The results can serve as a rational basis for design of fibre concrete engineering structures based on advanced nonlinear computer analysis. The presented methodology is illustrated on results from two probabilistic studies with different types of concrete structures related to practical applications and made from various materials (with the parameters obtained from real material tests).

Inference in the brain: Statistics flowing in redundant population codes

PubMed Central

Pitkow, Xaq; Angelaki, Dora E

2017-01-01

It is widely believed that the brain performs approximate probabilistic inference to estimate causal variables in the world from ambiguous sensory data. To understand these computations, we need to analyze how information is represented and transformed by the actions of nonlinear recurrent neural networks. We propose that these probabilistic computations function by a message-passing algorithm operating at the level of redundant neural populations. To explain this framework, we review its underlying concepts, including graphical models, sufficient statistics, and message-passing, and then describe how these concepts could be implemented by recurrently connected probabilistic population codes. The relevant information flow in these networks will be most interpretable at the population level, particularly for redundant neural codes. We therefore outline a general approach to identify the essential features of a neural message-passing algorithm. Finally, we argue that to reveal the most important aspects of these neural computations, we must study large-scale activity patterns during moderately complex, naturalistic behaviors. PMID:28595050

Continuous Probabilistic Modeling of Tracer Stone Dispersal in Upper Regime

NASA Astrophysics Data System (ADS)

Hernandez Moreira, R. R.; Viparelli, E.

2017-12-01

Morphodynamic models that specifically account for the non-uniformity of the bed material are generally based on some form of the active layer approximation. These models have proven to be useful tools in the study of transport, erosion and deposition of non-uniform bed material in the case of channel bed aggradation and degradation. However, when local spatial effects over short time scales compared to those characterizing the changes in mean bed elevation dominate the vertical sediment fluxes, as is the presence of bedforms, active layer models cannot capture key details of the sediment transport process. To overcome the limitations of active layer based models, Parker, Paola and Leclair (PPL) proposed a continuous probabilistic modeling frameworks in which the sediment exchange between the bedload transport and the mobile bed is described in terms of probability density functions of bed elevation, entrainment and deposition. Here we present the implementation of a modified version of the PPL modeling framework for the study of tracer stones dispsersal in upper regime bedload transport conditions (i.e. upper regime plane bed at the transition between dunes and antidunes, downstream migrating antidunes and upper regime plane bed with bedload transport in sheet flow mode) in which the probability functions are based on measured time series of bed elevation fluctuations. The extension to the more general case of mixtures of sediments differing in size is the future development of the proposed work.

Probabilistic Finite Element Analysis & Design Optimization for Structural Designs

NASA Astrophysics Data System (ADS)

Deivanayagam, Arumugam

This study focuses on implementing probabilistic nature of material properties (Kevlar® 49) to the existing deterministic finite element analysis (FEA) of fabric based engine containment system through Monte Carlo simulations (MCS) and implementation of probabilistic analysis in engineering designs through Reliability Based Design Optimization (RBDO). First, the emphasis is on experimental data analysis focusing on probabilistic distribution models which characterize the randomness associated with the experimental data. The material properties of Kevlar® 49 are modeled using experimental data analysis and implemented along with an existing spiral modeling scheme (SMS) and user defined constitutive model (UMAT) for fabric based engine containment simulations in LS-DYNA. MCS of the model are performed to observe the failure pattern and exit velocities of the models. Then the solutions are compared with NASA experimental tests and deterministic results. MCS with probabilistic material data give a good prospective on results rather than a single deterministic simulation results. The next part of research is to implement the probabilistic material properties in engineering designs. The main aim of structural design is to obtain optimal solutions. In any case, in a deterministic optimization problem even though the structures are cost effective, it becomes highly unreliable if the uncertainty that may be associated with the system (material properties, loading etc.) is not represented or considered in the solution process. Reliable and optimal solution can be obtained by performing reliability optimization along with the deterministic optimization, which is RBDO. In RBDO problem formulation, in addition to structural performance constraints, reliability constraints are also considered. This part of research starts with introduction to reliability analysis such as first order reliability analysis, second order reliability analysis followed by simulation technique that are performed to obtain probability of failure and reliability of structures. Next, decoupled RBDO procedure is proposed with a new reliability analysis formulation with sensitivity analysis, which is performed to remove the highly reliable constraints in the RBDO, thereby reducing the computational time and function evaluations. Followed by implementation of the reliability analysis concepts and RBDO in finite element 2D truss problems and a planar beam problem are presented and discussed.

The effectiveness of learning material with Edmodo to enhance the level of student's probabilistic thinking

NASA Astrophysics Data System (ADS)

Sujadi, Imam; Kurniasih, Rini; Subanti, Sri

2017-05-01

In the era of 21st century learning, it needs to use technology as a learning media. Using Edmodo as a learning media is one of the options as the complement in learning process. However, this research focuses on the effectiveness of learning material using Edmodo. The aim of this research to determine whether the level of student's probabilistic thinking that use learning material with Edmodo is better than the existing learning materials (books) implemented to teach the subject of students grade 8th. This is quasi-experimental research using control group pretest and posttest. The population of this study was students grade 8 of SMPN 12 Surakarta and the sampling technique used random sampling. The analysis technique used to examine two independent sample using Kolmogorov-Smirnov test. The obtained value of test statistic is M=0.38, since 0.38 is the largest tabled critical one-tailed value M0.05=0.011. The result of the research is the learning materials with Edmodo more effectively to enhance the level of probabilistic thinking learners than the learning that use the existing learning materials (books). Therefore, learning material using Edmodo can be used in learning process. It can also be developed into another learning material through Edmodo.

Computational simulation of probabilistic lifetime strength for aerospace materials subjected to high temperature, mechanical fatigue, creep and thermal fatigue

NASA Technical Reports Server (NTRS)

Boyce, Lola; Bast, Callie C.; Trimble, Greg A.

1992-01-01

This report presents the results of a fourth year effort of a research program, conducted for NASA-LeRC by the University of Texas at San Antonio (UTSA). The research included on-going development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subject to a number of effects or primitive variables. These primitive variables may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above-described constitutive equation using actual experimental materials data together with regression analysis of that data, thereby predicting values for the empirical material constants for each effect or primitive variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from industry and the open literature for materials typically for applications in aerospace propulsion system components. Material data for Inconel 718 has been analyzed using the developed methodology.

Computational simulation of probabilistic lifetime strength for aerospace materials subjected to high temperature, mechanical fatigue, creep, and thermal fatigue

NASA Technical Reports Server (NTRS)

Boyce, Lola; Bast, Callie C.; Trimble, Greg A.

1992-01-01

The results of a fourth year effort of a research program conducted for NASA-LeRC by The University of Texas at San Antonio (UTSA) are presented. The research included on-going development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects or primitive variables. These primitive variables may include high temperature, fatigue, or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation was randomized and is included in the computer program, PROMISC. Also included in the research is the development of methodology to calibrate the above-described constitutive equation using actual experimental materials data together with regression analysis of that data, thereby predicting values for the empirical material constants for each effect or primitive variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from industry and the open literature for materials typically for applications in aerospace propulsion system components. Material data for Inconel 718 was analyzed using the developed methodology.

Probabilistic Meteorological Characterization for Turbine Loads

NASA Astrophysics Data System (ADS)

Kelly, M.; Larsen, G.; Dimitrov, N. K.; Natarajan, A.

2014-06-01

Beyond the existing, limited IEC prescription to describe fatigue loads on wind turbines, we look towards probabilistic characterization of the loads via analogous characterization of the atmospheric flow, particularly for today's "taller" turbines with rotors well above the atmospheric surface layer. Based on both data from multiple sites as well as theoretical bases from boundary-layer meteorology and atmospheric turbulence, we offer probabilistic descriptions of shear and turbulence intensity, elucidating the connection of each to the other as well as to atmospheric stability and terrain. These are used as input to loads calculation, and with a statistical loads output description, they allow for improved design and loads calculations.

The Epistemic Representation of Information Flow Security in Probabilistic Systems

DTIC Science & Technology

1995-06-01

The new characterization also means that our security crite- rion is expressible in a simpler logic and model. 1 Introduction Multilevel security is...ber generator) during its execution. Such probabilistic choices are useful in a multilevel security context for Supported by grants HKUST 608/94E from... 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

NASA Astrophysics Data System (ADS)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2017-06-01

The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

Probabilistic Material Strength Degradation Model for Inconel 718 Components Subjected to High Temperature, Mechanical Fatigue, Creep and Thermal Fatigue Effects

NASA Technical Reports Server (NTRS)

Bast, Callie Corinne Scheidt

1994-01-01

This thesis presents the on-going development of methodology for a probabilistic material strength degradation model. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes four effects that typically reduce lifetime strength: high temperature, mechanical fatigue, creep, and thermal fatigue. Statistical analysis was conducted on experimental Inconel 718 data obtained from the open literature. This analysis provided regression parameters for use as the model's empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for four variables, namely, high temperature, mechanical fatigue, creep, and thermal fatigue. Methodology to estimate standard deviations of these material constants for input into the probabilistic material strength model was developed. Using the current version of PROMISS, entitled PROMISS93, a sensitivity study for the combined effects of mechanical fatigue, creep, and thermal fatigue was performed. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing a combination of mechanical fatigue and high temperature effects by model to the combination by experiment were conducted. Thus, for Inconel 718, the basic model assumption of independence between effects was evaluated. Results from this limited verification study strongly supported this assumption.

Development of probabilistic multimedia multipathway computer codes.

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

Yu, C.; LePoire, D.; Gnanapragasam, E.

2002-01-01

The deterministic multimedia dose/risk assessment codes RESRAD and RESRAD-BUILD have been widely used for many years for evaluation of sites contaminated with residual radioactive materials. The RESRAD code applies to the cleanup of sites (soils) and the RESRAD-BUILD code applies to the cleanup of buildings and structures. This work describes the procedure used to enhance the deterministic RESRAD and RESRAD-BUILD codes for probabilistic dose analysis. A six-step procedure was used in developing default parameter distributions and the probabilistic analysis modules. These six steps include (1) listing and categorizing parameters; (2) ranking parameters; (3) developing parameter distributions; (4) testing parameter distributionsmore » for probabilistic analysis; (5) developing probabilistic software modules; and (6) testing probabilistic modules and integrated codes. The procedures used can be applied to the development of other multimedia probabilistic codes. The probabilistic versions of RESRAD and RESRAD-BUILD codes provide tools for studying the uncertainty in dose assessment caused by uncertain input parameters. The parameter distribution data collected in this work can also be applied to other multimedia assessment tasks and multimedia computer codes.« less

Probabilistic simulation of uncertainties in thermal structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Shiao, Michael

1990-01-01

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Quantification of uncertainties in the performance of smart composite structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1993-01-01

A composite wing with spars, bulkheads, and built-in control devices is evaluated using a method for the probabilistic assessment of smart composite structures. Structural responses (such as change in angle of attack, vertical displacements, and stresses in regular plies with traditional materials and in control plies with mixed traditional and actuation materials) are probabilistically assessed to quantify their respective scatter. Probabilistic sensitivity factors are computed to identify those parameters that have a significant influence on a specific structural response. Results show that the uncertainties in the responses of smart composite structures can be quantified. Responses such as structural deformation, ply stresses, frequencies, and buckling loads in the presence of defects can be reliably controlled to satisfy specified design requirements.

An overview of engineering concepts and current design algorithms for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Duffy, S. F.; Hu, J.; Hopkins, D. A.

1995-01-01

The article begins by examining the fundamentals of traditional deterministic design philosophy. The initial section outlines the concepts of failure criteria and limit state functions two traditional notions that are embedded in deterministic design philosophy. This is followed by a discussion regarding safety factors (a possible limit state function) and the common utilization of statistical concepts in deterministic engineering design approaches. Next the fundamental aspects of a probabilistic failure analysis are explored and it is shown that deterministic design concepts mentioned in the initial portion of the article are embedded in probabilistic design methods. For components fabricated from ceramic materials (and other similarly brittle materials) the probabilistic design approach yields the widely used Weibull analysis after suitable assumptions are incorporated. The authors point out that Weibull analysis provides the rare instance where closed form solutions are available for a probabilistic failure analysis. Since numerical methods are usually required to evaluate component reliabilities, a section on Monte Carlo methods is included to introduce the concept. The article concludes with a presentation of the technical aspects that support the numerical method known as fast probability integration (FPI). This includes a discussion of the Hasofer-Lind and Rackwitz-Fiessler approximations.

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.

Coupled Multi-Disciplinary Optimization for Structural Reliability and Affordability

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

A computational simulation method is presented for Non-Deterministic Multidisciplinary Optimization of engine composite materials and structures. A hypothetical engine duct made with ceramic matrix composites (CMC) is evaluated probabilistically in the presence of combined thermo-mechanical loading. The structure is tailored by quantifying the uncertainties in all relevant design variables such as fabrication, material, and loading parameters. The probabilistic sensitivities are used to select critical design variables for optimization. In this paper, two approaches for non-deterministic optimization are presented. The non-deterministic minimization of combined failure stress criterion is carried out by: (1) performing probabilistic evaluation first and then optimization and (2) performing optimization first and then probabilistic evaluation. The first approach shows that the optimization feasible region can be bounded by a set of prescribed probability limits and that the optimization follows the cumulative distribution function between those limits. The second approach shows that the optimization feasible region is bounded by 0.50 and 0.999 probabilities.

PROBABILISTIC RISK ANALYSIS OF RADIOACTIVE WASTE DISPOSALS - a case study

NASA Astrophysics Data System (ADS)

Trinchero, P.; Delos, A.; Tartakovsky, D. M.; Fernandez-Garcia, D.; Bolster, D.; Dentz, M.; Sanchez-Vila, X.; Molinero, J.

2009-12-01

The storage of contaminant material in superficial or sub-superficial repositories, such as tailing piles for mine waste or disposal sites for low and intermediate nuclear waste, poses a potential threat for the surrounding biosphere. The minimization of these risks can be achieved by supporting decision-makers with quantitative tools capable to incorporate all source of uncertainty within a rigorous probabilistic framework. A case study is presented where we assess the risks associated to the superficial storage of hazardous waste close to a populated area. The intrinsic complexity of the problem, involving many events with different spatial and time scales and many uncertainty parameters is overcome by using a formal PRA (probabilistic risk assessment) procedure that allows decomposing the system into a number of key events. Hence, the failure of the system is directly linked to the potential contamination of one of the three main receptors: the underlying karst aquifer, a superficial stream that flows near the storage piles and a protection area surrounding a number of wells used for water supply. The minimal cut sets leading to the failure of the system are obtained by defining a fault-tree that incorporates different events including the failure of the engineered system (e.g. cover of the piles) and the failure of the geological barrier (e.g. clay layer that separates the bottom of the pile from the karst formation). Finally the probability of failure is quantitatively assessed combining individual independent or conditional probabilities that are computed numerically or borrowed from reliability database.

Probabilistic structural analysis methods and applications

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Wu, Y.-T.; Dias, B.; Rajagopal, K. R.

1988-01-01

An advanced algorithm for simulating the probabilistic distribution of structural responses due to statistical uncertainties in loads, geometry, material properties, and boundary conditions is reported. The method effectively combines an advanced algorithm for calculating probability levels for multivariate problems (fast probability integration) together with a general-purpose finite-element code for stress, vibration, and buckling analysis. Application is made to a space propulsion system turbine blade for which the geometry and material properties are treated as random variables.

Probabilistic migration modelling focused on functional barrier efficiency and low migration concepts in support of risk assessment.

PubMed

Brandsch, Rainer

2017-10-01

Migration modelling provides reliable migration estimates from food-contact materials (FCM) to food or food simulants based on mass-transfer parameters like diffusion and partition coefficients related to individual materials. In most cases, mass-transfer parameters are not readily available from the literature and for this reason are estimated with a given uncertainty. Historically, uncertainty was accounted for by introducing upper limit concepts first, turning out to be of limited applicability due to highly overestimated migration results. Probabilistic migration modelling gives the possibility to consider uncertainty of the mass-transfer parameters as well as other model inputs. With respect to a functional barrier, the most important parameters among others are the diffusion properties of the functional barrier and its thickness. A software tool that accepts distribution as inputs and is capable of applying Monte Carlo methods, i.e., random sampling from the input distributions of the relevant parameters (i.e., diffusion coefficient and layer thickness), predicts migration results with related uncertainty and confidence intervals. The capabilities of probabilistic migration modelling are presented in the view of three case studies (1) sensitivity analysis, (2) functional barrier efficiency and (3) validation by experimental testing. Based on the predicted migration by probabilistic migration modelling and related exposure estimates, safety evaluation of new materials in the context of existing or new packaging concepts is possible. Identifying associated migration risk and potential safety concerns in the early stage of packaging development is possible. Furthermore, dedicated material selection exhibiting required functional barrier efficiency under application conditions becomes feasible. Validation of the migration risk assessment by probabilistic migration modelling through a minimum of dedicated experimental testing is strongly recommended.

Data assimilation for unsaturated flow models with restart adaptive probabilistic collocation based Kalman filter

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

Man, Jun; Li, Weixuan; Zeng, Lingzao

2016-06-01

The ensemble Kalman filter (EnKF) has gained popularity in hydrological data assimilation problems. As a Monte Carlo based method, a relatively large ensemble size is usually required to guarantee the accuracy. As an alternative approach, the probabilistic collocation based Kalman filter (PCKF) employs the polynomial chaos to approximate the original system. In this way, the sampling error can be reduced. However, PCKF suffers from the so-called "curse of dimensionality". When the system nonlinearity is strong and number of parameters is large, PCKF could be even more computationally expensive than EnKF. Motivated by most recent developments in uncertainty quantification, we proposemore » a restart adaptive probabilistic collocation based Kalman filter (RAPCKF) for data assimilation in unsaturated flow problems. During the implementation of RAPCKF, the important parameters are identified and active PCE basis functions are adaptively selected. The "restart" technology is used to eliminate the inconsistency between model parameters and states. The performance of RAPCKF is tested with numerical cases of unsaturated flow models. It is shown that RAPCKF is more efficient than EnKF with the same computational cost. Compared with the traditional PCKF, the RAPCKF is more applicable in strongly nonlinear and high dimensional problems.« less

Probabilistic Composite Design

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1997-01-01

Probabilistic composite design is described in terms of a computational simulation. This simulation tracks probabilistically the composite design evolution from constituent materials, fabrication process, through composite mechanics and structural components. Comparisons with experimental data are provided to illustrate selection of probabilistic design allowables, test methods/specimen guidelines, and identification of in situ versus pristine strength, For example, results show that: in situ fiber tensile strength is 90% of its pristine strength; flat-wise long-tapered specimens are most suitable for setting ply tensile strength allowables: a composite radome can be designed with a reliability of 0.999999; and laminate fatigue exhibits wide-spread scatter at 90% cyclic-stress to static-strength ratios.

Comparison of Peak-Flow Estimation Methods for Small Drainage Basins in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Hebson, Charles; Lombard, Pamela J.; Mann, Alexander

2007-01-01

Understanding the accuracy of commonly used methods for estimating peak streamflows is important because the designs of bridges, culverts, and other river structures are based on these flows. Different methods for estimating peak streamflows were analyzed for small drainage basins in Maine. For the smallest basins, with drainage areas of 0.2 to 1.0 square mile, nine peak streamflows from actual rainfall events at four crest-stage gaging stations were modeled by the Rational Method and the Natural Resource Conservation Service TR-20 method and compared to observed peak flows. The Rational Method had a root mean square error (RMSE) of -69.7 to 230 percent (which means that approximately two thirds of the modeled flows were within -69.7 to 230 percent of the observed flows). The TR-20 method had an RMSE of -98.0 to 5,010 percent. Both the Rational Method and TR-20 underestimated the observed flows in most cases. For small basins, with drainage areas of 1.0 to 10 square miles, modeled peak flows were compared to observed statistical peak flows with return periods of 2, 50, and 100 years for 17 streams in Maine and adjoining parts of New Hampshire. Peak flows were modeled by the Rational Method, the Natural Resources Conservation Service TR-20 method, U.S. Geological Survey regression equations, and the Probabilistic Rational Method. The regression equations were the most accurate method of computing peak flows in Maine for streams with drainage areas of 1.0 to 10 square miles with an RMSE of -34.3 to 52.2 percent for 50-year peak flows. The Probabilistic Rational Method was the next most accurate method (-38.5 to 62.6 percent). The Rational Method (-56.1 to 128 percent) and particularly the TR-20 method (-76.4 to 323 percent) had much larger errors. Both the TR-20 and regression methods had similar numbers of underpredictions and overpredictions. The Rational Method overpredicted most peak flows and the Probabilistic Rational Method tended to overpredict peak flows from the smaller (less than 5 square miles) drainage basins and underpredict peak flows from larger drainage basins. The results of this study are consistent with the most comprehensive analysis of observed and modeled peak streamflows in the United States, which analyzed statistical peak flows from 70 drainage basins in the Midwest and the Northwest.

Reliability and risk assessment of structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1991-01-01

Development of reliability and risk assessment of structural components and structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) the evaluation of the various uncertainties in terms of cumulative distribution functions for various structural response variables based on known or assumed uncertainties in primitive structural variables; (2) evaluation of the failure probability; (3) reliability and risk-cost assessment; and (4) an outline of an emerging approach for eventual certification of man-rated structures by computational methods. Collectively, the results demonstrate that the structural durability/reliability of man-rated structural components and structures can be effectively evaluated by using formal probabilistic methods.

A probabilistic model of debris-flow delivery to stream channels, demonstrated for the Coast Range of Oregon, USA

Treesearch

Daniel J. Miller; Kelly M. Burnett

2008-01-01

Debris flows are important geomorphic agents in mountainous terrains that shape channel environments and add a dynamic element to sediment supply and channel disturbance. Identification of channels susceptible to debris-flow inputs of sediment and organic debris, and quantification of the likelihood and magnitude of those inputs, are key tasks for characterizing...

Probabilistic structural analysis to quantify uncertainties associated with turbopump blades

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.; Rubinstein, Robert; Chamis, Christos C.

1988-01-01

A probabilistic study of turbopump blades has been in progress at NASA Lewis Research Center for over the last two years. The objectives of this study are to evaluate the effects of uncertainties in geometry and material properties on the structural response of the turbopump blades to evaluate the tolerance limits on the design. A methodology based on probabilistic approach was developed to quantify the effects of the random uncertainties. The results indicate that only the variations in geometry have significant effects.

Analysis of flood hazard under consideration of dike breaches

NASA Astrophysics Data System (ADS)

Vorogushyn, S.; Apel, H.; Lindenschmidt, K.-E.; Merz, B.

2009-04-01

The study focuses on the development and application of a new modelling system which allows a comprehensive flood hazard assessment along diked river reaches under consideration of dike failures. The proposed Inundation Hazard Assessment Model (IHAM) represents a hybrid probabilistic-deterministic model. It comprises three models interactively coupled at runtime. These are: (1) 1D unsteady hydrodynamic model of river channel and floodplain flow between dikes, (2) probabilistic dike breach model which determines possible dike breach locations, breach widths and breach outflow discharges, and (3) 2D raster-based diffusion wave storage cell model of the hinterland areas behind the dikes. Due to the unsteady nature of the 1D and 2D coupled models, the dependence between hydraulic load at various locations along the reach is explicitly considered. The probabilistic dike breach model describes dike failures due to three failure mechanisms: overtopping, piping and slope instability caused by the seepage flow through the dike core (micro-instability). Dike failures for each mechanism are simulated based on fragility functions. The probability of breach is conditioned by the uncertainty in geometrical and geotechnical dike parameters. The 2D storage cell model driven by the breach outflow boundary conditions computes an extended spectrum of flood intensity indicators such as water depth, flow velocity, impulse, inundation duration and rate of water rise. IHAM is embedded in a Monte Carlo simulation in order to account for the natural variability of the flood generation processes reflected in the form of input hydrographs and for the randomness of dike failures given by breach locations, times and widths. The scenario calculations for the developed synthetic input hydrographs for the main river and tributary were carried out for floods with return periods of T = 100; 200; 500; 1000 a. Based on the modelling results, probabilistic dike hazard maps could be generated that indicate the failure probability of each discretised dike section for every scenario magnitude. Besides the binary inundation patterns that indicate the probability of raster cells being inundated, IHAM generates probabilistic flood hazard maps. These maps display spatial patterns of the considered flood intensity indicators and their associated return periods. The probabilistic nature of IHAM allows for the generation of percentile flood hazard maps that indicate the median and uncertainty bounds of the flood intensity indicators. The uncertainty results from the natural variability of the flow hydrographs and randomness of dike breach processes. The same uncertainty sources determine the uncertainty in the flow hydrographs along the study reach. The simulations showed that the dike breach stochasticity has an increasing impact on hydrograph uncertainty in downstream direction. Whereas in the upstream part of the reach the hydrograph uncertainty is mainly stipulated by the variability of the flood wave form, the dike failures strongly shape the uncertainty boundaries in the downstream part of the reach. Finally, scenarios of polder deployment for the extreme floods with T = 200; 500; 1000 a were simulated with IHAM. The results indicate a rather weak reduction of the mean and median flow hydrographs in the river channel. However, the capping of the flow peaks resulted in a considerable reduction of the overtopping failures downstream of the polder with a simultaneous slight increase of the piping and slope micro-instability frequencies explained by a more durable average impoundment. The developed IHAM simulation system represents a new scientific tool for studying fluvial inundation dynamics under extreme conditions incorporating effects of technical flood protection measures. With its major outputs in form of novel probabilistic inundation and dike hazard maps, the IHAM system has a high practical value for decision support in flood management.

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.

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system structural components

NASA Technical Reports Server (NTRS)

Cruse, T. A.

1987-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

Probabilistic Structural Analysis Methods for select space propulsion system structural components (PSAM)

NASA Technical Reports Server (NTRS)

Cruse, T. A.; Burnside, O. H.; Wu, Y.-T.; Polch, E. Z.; Dias, J. B.

1988-01-01

The objective is the development of several modular structural analysis packages capable of predicting the probabilistic response distribution for key structural variables such as maximum stress, natural frequencies, transient response, etc. The structural analysis packages are to include stochastic modeling of loads, material properties, geometry (tolerances), and boundary conditions. The solution is to be in terms of the cumulative probability of exceedance distribution (CDF) and confidence bounds. Two methods of probability modeling are to be included as well as three types of structural models - probabilistic finite-element method (PFEM); probabilistic approximate analysis methods (PAAM); and probabilistic boundary element methods (PBEM). The purpose in doing probabilistic structural analysis is to provide the designer with a more realistic ability to assess the importance of uncertainty in the response of a high performance structure. Probabilistic Structural Analysis Method (PSAM) tools will estimate structural safety and reliability, while providing the engineer with information on the confidence that should be given to the predicted behavior. Perhaps most critically, the PSAM results will directly provide information on the sensitivity of the design response to those variables which are seen to be uncertain.

A Case Study for Probabilistic Methods Validation (MSFC Center Director's Discretionary Fund, Project No. 94-26)

NASA Technical Reports Server (NTRS)

Price J. M.; Ortega, R.

1998-01-01

Probabilistic method is not a universally accepted approach for the design and analysis of aerospace structures. The validity of this approach must be demonstrated to encourage its acceptance as it viable design and analysis tool to estimate structural reliability. The objective of this Study is to develop a well characterized finite population of similar aerospace structures that can be used to (1) validate probabilistic codes, (2) demonstrate the basic principles behind probabilistic methods, (3) formulate general guidelines for characterization of material drivers (such as elastic modulus) when limited data is available, and (4) investigate how the drivers affect the results of sensitivity analysis at the component/failure mode level.

Development of probabilistic thinking-oriented learning tools for probability materials at junior high school students

NASA Astrophysics Data System (ADS)

Sari, Dwi Ivayana; Hermanto, Didik

2017-08-01

This research is a developmental research of probabilistic thinking-oriented learning tools for probability materials at ninth grade students. This study is aimed to produce a good probabilistic thinking-oriented learning tools. The subjects were IX-A students of MTs Model Bangkalan. The stages of this development research used 4-D development model which has been modified into define, design and develop. Teaching learning tools consist of lesson plan, students' worksheet, learning teaching media and students' achievement test. The research instrument used was a sheet of learning tools validation, a sheet of teachers' activities, a sheet of students' activities, students' response questionnaire and students' achievement test. The result of those instruments were analyzed descriptively to answer research objectives. The result was teaching learning tools in which oriented to probabilistic thinking of probability at ninth grade students which has been valid. Since teaching and learning tools have been revised based on validation, and after experiment in class produced that teachers' ability in managing class was effective, students' activities were good, students' responses to the learning tools were positive and the validity, sensitivity and reliability category toward achievement test. In summary, this teaching learning tools can be used by teacher to teach probability for develop students' probabilistic thinking.

Probabilistic Structural Analysis and Reliability Using NESSUS With Implemented Material Strength Degradation Model

NASA Technical Reports Server (NTRS)

Bast, Callie C.; Jurena, Mark T.; Godines, Cody R.; Chamis, Christos C. (Technical Monitor)

2001-01-01

This project included both research and education objectives. The goal of this project was to advance innovative research and education objectives in theoretical and computational probabilistic structural analysis, reliability, and life prediction for improved reliability and safety of structural components of aerospace and aircraft propulsion systems. Research and education partners included Glenn Research Center (GRC) and Southwest Research Institute (SwRI) along with the University of Texas at San Antonio (UTSA). SwRI enhanced the NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) code and provided consulting support for NESSUS-related activities at UTSA. NASA funding supported three undergraduate students, two graduate students, a summer course instructor and the Principal Investigator. Matching funds from UTSA provided for the purchase of additional equipment for the enhancement of the Advanced Interactive Computational SGI Lab established during the first year of this Partnership Award to conduct the probabilistic finite element summer courses. The research portion of this report presents the cumulation of work performed through the use of the probabilistic finite element program, NESSUS, Numerical Evaluation and Structures Under Stress, and an embedded Material Strength Degradation (MSD) model. Probabilistic structural analysis provided for quantification of uncertainties associated with the design, thus enabling increased system performance and reliability. The structure examined was a Space Shuttle Main Engine (SSME) fuel turbopump blade. The blade material analyzed was Inconel 718, since the MSD model was previously calibrated for this material. Reliability analysis encompassing the effects of high temperature and high cycle fatigue, yielded a reliability value of 0.99978 using a fully correlated random field for the blade thickness. The reliability did not change significantly for a change in distribution type except for a change in distribution from Gaussian to Weibull for the centrifugal load. The sensitivity factors determined to be most dominant were the centrifugal loading and the initial strength of the material. These two sensitivity factors were influenced most by a change in distribution type from Gaussian to Weibull. The education portion of this report describes short-term and long-term educational objectives. Such objectives serve to integrate research and education components of this project resulting in opportunities for ethnic minority students, principally Hispanic. The primary vehicle to facilitate such integration was the teaching of two probabilistic finite element method courses to undergraduate engineering students in the summers of 1998 and 1999.

Probabilistic Structural Evaluation of Uncertainties in Radiator Sandwich Panel Design

NASA Technical Reports Server (NTRS)

Kuguoglu, Latife; Ludwiczak, Damian

2006-01-01

The Jupiter Icy Moons Orbiter (JIMO) Space System is part of the NASA's Prometheus Program. As part of the JIMO engineering team at NASA Glenn Research Center, the structural design of the JIMO Heat Rejection Subsystem (HRS) is evaluated. An initial goal of this study was to perform sensitivity analyses to determine the relative importance of the input variables on the structural responses of the radiator panel. The desire was to let the sensitivity analysis information identify the important parameters. The probabilistic analysis methods illustrated here support this objective. The probabilistic structural performance evaluation of a HRS radiator sandwich panel was performed. The radiator panel structural performance was assessed in the presence of uncertainties in the loading, fabrication process variables, and material properties. The stress and displacement contours of the deterministic structural analysis at mean probability was performed and results presented. It is followed by a probabilistic evaluation to determine the effect of the primitive variables on the radiator panel structural performance. Based on uncertainties in material properties, structural geometry and loading, the results of the displacement and stress analysis are used as an input file for the probabilistic analysis of the panel. The sensitivity of the structural responses, such as maximum displacement and maximum tensile and compressive stresses of the facesheet in x and y directions and maximum VonMises stresses of the tube, to the loading and design variables is determined under the boundary condition where all edges of the radiator panel are pinned. Based on this study, design critical material and geometric parameters of the considered sandwich panel are identified.

Nonlinear probabilistic finite element models of laminated composite shells

NASA Technical Reports Server (NTRS)

Engelstad, S. P.; Reddy, J. N.

1993-01-01

A probabilistic finite element analysis procedure for laminated composite shells has been developed. A total Lagrangian finite element formulation, employing a degenerated 3-D laminated composite shell with the full Green-Lagrange strains and first-order shear deformable kinematics, forms the modeling foundation. The first-order second-moment technique for probabilistic finite element analysis of random fields is employed and results are presented in the form of mean and variance of the structural response. The effects of material nonlinearity are included through the use of a rate-independent anisotropic plasticity formulation with the macroscopic point of view. Both ply-level and micromechanics-level random variables can be selected, the latter by means of the Aboudi micromechanics model. A number of sample problems are solved to verify the accuracy of the procedures developed and to quantify the variability of certain material type/structure combinations. Experimental data is compared in many cases, and the Monte Carlo simulation method is used to check the probabilistic results. In general, the procedure is quite effective in modeling the mean and variance response of the linear and nonlinear behavior of laminated composite shells.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Onfroy, T.; Leblois, E.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2013-07-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible but not yet occurred flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2012 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90% of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of CCR claim database has shown that approximately 45% of the insured flood losses are located inside the floodplains and 45% outside. 10% other percent are due to seasurge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: generation of fictive river flows based on the historical records of the river gauge network and generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (MACIF) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Probabilistic structural analysis to quantify uncertainties associated with turbopump blades

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.; Rubinstein, Robert; Chamis, Christos C.

1987-01-01

A probabilistic study of turbopump blades has been in progress at NASA Lewis Research Center for over the last two years. The objectives of this study are to evaluate the effects of uncertainties in geometry and material properties on the structural response of the turbopump blades to evaluate the tolerance limits on the design. A methodology based on probabilistic approach has been developed to quantify the effects of the random uncertainties. The results of this study indicate that only the variations in geometry have significant effects.

Probabilistic properties of the date of maximum river flow, an approach based on circular statistics in lowland, highland and mountainous catchment

NASA Astrophysics Data System (ADS)

Rutkowska, Agnieszka; Kohnová, Silvia; Banasik, Kazimierz

2018-04-01

Probabilistic properties of dates of winter, summer and annual maximum flows were studied using circular statistics in three catchments differing in topographic conditions; a lowland, highland and mountainous catchment. The circular measures of location and dispersion were used in the long-term samples of dates of maxima. The mixture of von Mises distributions was assumed as the theoretical distribution function of the date of winter, summer and annual maximum flow. The number of components was selected on the basis of the corrected Akaike Information Criterion and the parameters were estimated by means of the Maximum Likelihood method. The goodness of fit was assessed using both the correlation between quantiles and a version of the Kuiper's and Watson's test. Results show that the number of components varied between catchments and it was different for seasonal and annual maxima. Differences between catchments in circular characteristics were explained using climatic factors such as precipitation and temperature. Further studies may include circular grouping catchments based on similarity between distribution functions and the linkage between dates of maximum precipitation and maximum flow.

A probabilistic model of a porous heat exchanger

NASA Technical Reports Server (NTRS)

Agrawal, O. P.; Lin, X. A.

1995-01-01

This paper presents a probabilistic one-dimensional finite element model for heat transfer processes in porous heat exchangers. The Galerkin approach is used to develop the finite element matrices. Some of the submatrices are asymmetric due to the presence of the flow term. The Neumann expansion is used to write the temperature distribution as a series of random variables, and the expectation operator is applied to obtain the mean and deviation statistics. To demonstrate the feasibility of the formulation, a one-dimensional model of heat transfer phenomenon in superfluid flow through a porous media is considered. Results of this formulation agree well with the Monte-Carlo simulations and the analytical solutions. Although the numerical experiments are confined to parametric random variables, a formulation is presented to account for the random spatial variations.

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

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

Dickson, T.L.; Simonen, F.A.

1992-05-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

The application of probabilistic fracture analysis to residual life evaluation of embrittled reactor vessels

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

Dickson, T.L.; Simonen, F.A.

1992-01-01

Probabilistic fracture mechanics analysis is a major element of comprehensive probabilistic methodology on which current NRC regulatory requirements for pressurized water reactor vessel integrity evaluation are based. Computer codes such as OCA-P and VISA-II perform probabilistic fracture analyses to estimate the increase in vessel failure probability that occurs as the vessel material accumulates radiation damage over the operating life of the vessel. The results of such analyses, when compared with limits of acceptable failure probabilities, provide an estimation of the residual life of a vessel. Such codes can be applied to evaluate the potential benefits of plant-specific mitigating actions designedmore » to reduce the probability of failure of a reactor vessel. 10 refs.« less

Probabilistic composite micromechanics

NASA Technical Reports Server (NTRS)

Stock, T. A.; Bellini, P. X.; Murthy, P. L. N.; Chamis, C. C.

1988-01-01

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material properties at the micro level. Regression results are presented to show the relative correlation between predicted and response variables in the study.

Concurrent Probabilistic Simulation of High Temperature Composite Structural Response

NASA Technical Reports Server (NTRS)

Abdi, Frank

1996-01-01

A computational structural/material analysis and design tool which would meet industry's future demand for expedience and reduced cost is presented. This unique software 'GENOA' is dedicated to parallel and high speed analysis to perform probabilistic evaluation of high temperature composite response of aerospace systems. The development is based on detailed integration and modification of diverse fields of specialized analysis techniques and mathematical models to combine their latest innovative capabilities into a commercially viable software package. The technique is specifically designed to exploit the availability of processors to perform computationally intense probabilistic analysis assessing uncertainties in structural reliability analysis and composite micromechanics. The primary objectives which were achieved in performing the development were: (1) Utilization of the power of parallel processing and static/dynamic load balancing optimization to make the complex simulation of structure, material and processing of high temperature composite affordable; (2) Computational integration and synchronization of probabilistic mathematics, structural/material mechanics and parallel computing; (3) Implementation of an innovative multi-level domain decomposition technique to identify the inherent parallelism, and increasing convergence rates through high- and low-level processor assignment; (4) Creating the framework for Portable Paralleled architecture for the machine independent Multi Instruction Multi Data, (MIMD), Single Instruction Multi Data (SIMD), hybrid and distributed workstation type of computers; and (5) Market evaluation. The results of Phase-2 effort provides a good basis for continuation and warrants Phase-3 government, and industry partnership.

An approximate methods approach to probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.

1989-01-01

A probabilistic structural analysis method (PSAM) is described which makes an approximate calculation of the structural response of a system, including the associated probabilistic distributions, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The method employs the fast probability integration (FPI) algorithm of Wu and Wirsching. Typical solution strategies are illustrated by formulations for a representative critical component chosen from the Space Shuttle Main Engine (SSME) as part of a major NASA-sponsored program on PSAM. Typical results are presented to demonstrate the role of the methodology in engineering design and analysis.

A probabilistic approach to composite micromechanics

NASA Technical Reports Server (NTRS)

Stock, T. A.; Bellini, P. X.; Murthy, P. L. N.; Chamis, C. C.

1988-01-01

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material properties at the micro level. Regression results are presented to show the relative correlation between predicted and response variables in the study.

Structural reliability methods: Code development status

NASA Astrophysics Data System (ADS)

Millwater, Harry R.; Thacker, Ben H.; Wu, Y.-T.; Cruse, T. A.

1991-05-01

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

Structural reliability methods: Code development status

NASA Technical Reports Server (NTRS)

Millwater, Harry R.; Thacker, Ben H.; Wu, Y.-T.; Cruse, T. A.

1991-01-01

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk.

Design for cyclic loading endurance of composites

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Murthy, Pappu L. N.; Chamis, Christos C.; Liaw, Leslie D. G.

1993-01-01

The application of the computer code IPACS (Integrated Probabilistic Assessment of Composite Structures) to aircraft wing type structures is described. The code performs a complete probabilistic analysis for composites taking into account the uncertainties in geometry, boundary conditions, material properties, laminate lay-ups, and loads. Results of the analysis are presented in terms of cumulative distribution functions (CDF) and probability density function (PDF) of the fatigue life of a wing type composite structure under different hygrothermal environments subjected to the random pressure. The sensitivity of the fatigue life to a number of critical structural/material variables is also computed from the analysis.

The Predictive Capability of Conditioned Simulation of Discrete Fracture Networks using Structural and Hydraulic Data from the ONKALO Underground Research Facility, Finland

NASA Astrophysics Data System (ADS)

Williams, T. R. N.; Baxter, S.; Hartley, L.; Appleyard, P.; Koskinen, L.; Vanhanarkaus, O.; Selroos, J. O.; Munier, R.

2017-12-01

Discrete fracture network (DFN) models provide a natural analysis framework for rock conditions where flow is predominately through a series of connected discrete features. Mechanistic models to predict the structural patterns of networks are generally intractable due to inherent uncertainties (e.g. deformation history) and as such fracture characterisation typically involves empirical descriptions of fracture statistics for location, intensity, orientation, size, aperture etc. from analyses of field data. These DFN models are used to make probabilistic predictions of likely flow or solute transport conditions for a range of applications in underground resource and construction projects. However, there are many instances when the volumes in which predictions are most valuable are close to data sources. For example, in the disposal of hazardous materials such as radioactive waste, accurate predictions of flow-rates and network connectivity around disposal areas are required for long-term safety evaluation. The problem at hand is thus: how can probabilistic predictions be conditioned on local-scale measurements? This presentation demonstrates conditioning of a DFN model based on the current structural and hydraulic characterisation of the Demonstration Area at the ONKALO underground research facility. The conditioned realisations honour (to a required level of similarity) the locations, orientations and trace lengths of fractures mapped on the surfaces of the nearby ONKALO tunnels and pilot drillholes. Other data used as constraints include measurements from hydraulic injection tests performed in pilot drillholes and inflows to the subsequently reamed experimental deposition holes. Numerical simulations using this suite of conditioned DFN models provides a series of prediction-outcome exercises detailing the reliability of the DFN model to make local-scale predictions of measured geometric and hydraulic properties of the fracture system; and provides an understanding of the reduction in uncertainty in model predictions for conditioned DFN models honouring different aspects of this data.

Seasonal streamflow prediction using ensemble streamflow prediction technique for the Rangitata and Waitaki River basins on the South Island of New Zealand

NASA Astrophysics Data System (ADS)

Singh, Shailesh Kumar

2014-05-01

Streamflow forecasts are essential for making critical decision for optimal allocation of water supplies for various demands that include irrigation for agriculture, habitat for fisheries, hydropower production and flood warning. The major objective of this study is to explore the Ensemble Streamflow Prediction (ESP) based forecast in New Zealand catchments and to highlights the present capability of seasonal flow forecasting of National Institute of Water and Atmospheric Research (NIWA). In this study a probabilistic forecast framework for ESP is presented. The basic assumption in ESP is that future weather pattern were experienced historically. Hence, past forcing data can be used with current initial condition to generate an ensemble of prediction. Small differences in initial conditions can result in large difference in the forecast. The initial state of catchment can be obtained by continuously running the model till current time and use this initial state with past forcing data to generate ensemble of flow for future. The approach taken here is to run TopNet hydrological models with a range of past forcing data (precipitation, temperature etc.) with current initial conditions. The collection of runs is called the ensemble. ESP give probabilistic forecasts for flow. From ensemble members the probability distributions can be derived. The probability distributions capture part of the intrinsic uncertainty in weather or climate. An ensemble stream flow prediction which provide probabilistic hydrological forecast with lead time up to 3 months is presented for Rangitata, Ahuriri, and Hooker and Jollie rivers in South Island of New Zealand. ESP based seasonal forecast have better skill than climatology. This system can provide better over all information for holistic water resource management.

Empirical Fragility Analysis of Buildings and Boats Damaged By the 2011 Great East Japan Tsunami and Their Practical Application

NASA Astrophysics Data System (ADS)

Suppasri, A.; Charvet, I.; Leelawat, N.; Fukutani, Y.; Muhari, A.; Futami, T.; Imamura, F.

2014-12-01

This study focused in turn on detailed data of buildings and boats damage caused by the 2011 tsunami in order to understand its main causes and provide damage probability estimates. Tsunami-induced building damage data was collected from field surveys, and includes inundation depth, building material, number of stories and occupancy type for more than 80,000 buildings. Numerical simulations with high resolution bathymetry and topography data were conducted to obtain characteristic tsunami measures such as flow velocity. These data were analyzed using advanced statistical methods, ordinal regression analysis to create not only empirical 2D tsunami fragility curves, but also 3D tsunami fragility surfaces for the first time. The effect of floating debris was also considered, by using a binary indicator of debris impact based on the proximity of a structure from a debris source (i.e. washed away building). Both the 2D and 3D fragility analyses provided results for each different building damage level, and different topography. While 2D fragility curves provide easily interpretable results relating tsunami flow depth to damage probability for different damage levels, 3D fragility surfaces allow for several influential tsunami parameters to be taken into account thus reduce uncertainty in the probability estimations. More than 20,000 damaged boats were used in the analysis similar to the one carried out on the buildings. Detailed data for each boat comprises information on the damage ratio (paid value over insured value), tonnage, engine type, material type and damage classification. The 2D and 3D fragility analyses were developed using representative tsunami heights for each port obtained from field surveys and flow velocities obtained from the aforementioned simulations. The results are currently being adapted for practical disaster mitigation. They are being integrated with the probabilistic tsunami hazard analysis, in order to create offshore and onshore probabilistic hazard maps. Through the GPS and embedded calculation function based on the aforementioned fragility results, these applications can be used in the field for a quick estimation of possible building damage, as well as a decision support system for fishermen (whether or not they should move their boats to the deep sea upon tsunami arrival).

Impact of uncertainties in free stream conditions on the aerodynamics of a rectangular cylinder

NASA Astrophysics Data System (ADS)

Mariotti, Alessandro; Shoeibi Omrani, Pejman; Witteveen, Jeroen; Salvetti, Maria Vittoria

2015-11-01

The BARC benchmark deals with the flow around a rectangular cylinder with chord-to-depth ratio equal to 5. This flow configuration is of practical interest for civil and industrial structures and it is characterized by massively separated flow and unsteadiness. In a recent review of BARC results, significant dispersion was observed both in experimental and numerical predictions of some flow quantities, which are extremely sensitive to various uncertainties, which may be present in experiments and simulations. Besides modeling and numerical errors, in simulations it is difficult to exactly reproduce the experimental conditions due to uncertainties in the set-up parameters, which sometimes cannot be exactly controlled or characterized. Probabilistic methods and URANS simulations are used to investigate the impact of the uncertainties in the following set-up parameters: the angle of incidence, the free stream longitudinal turbulence intensity and length scale. Stochastic collocation is employed to perform the probabilistic propagation of the uncertainty. The discretization and modeling errors are estimated by repeating the same analysis for different grids and turbulence models. The results obtained for different assumed PDF of the set-up parameters are also compared.

Effect of analysis parameters on non-linear implicit finite element analysis of marine corroded steel plate

NASA Astrophysics Data System (ADS)

Islam, Muhammad Rabiul; Sakib-Ul-Alam, Md.; Nazat, Kazi Kaarima; Hassan, M. Munir

2017-12-01

FEA results greatly depend on analysis parameters. MSC NASTRAN nonlinear implicit analysis code has been used in large deformation finite element analysis of pitted marine SM490A steel rectangular plate. The effect of two types actual pit shape on parameters of integrity of structure has been analyzed. For 3-D modeling, a proposed method for simulation of pitted surface by probabilistic corrosion model has been used. The result has been verified with the empirical formula proposed by finite element analysis of steel surface generated with different pitted data where analyses have been carried out by the code of LS-DYNA 971. In the both solver, an elasto-plastic material has been used where an arbitrary stress versus strain curve can be defined. In the later one, the material model is based on the J2 flow theory with isotropic hardening where a radial return algorithm is used. The comparison shows good agreement between the two results which ensures successful simulation with comparatively less energy and time.

A computationally fast, reduced model for simulating landslide dynamics and tsunamis generated by landslides in natural terrains

NASA Astrophysics Data System (ADS)

Mohammed, F.

2016-12-01

Landslide hazards such as fast-moving debris flows, slow-moving landslides, and other mass flows cause numerous fatalities, injuries, and damage. Landslide occurrences in fjords, bays, and lakes can additionally generate tsunamis with locally extremely high wave heights and runups. Two-dimensional depth-averaged models can successfully simulate the entire lifecycle of the three-dimensional landslide dynamics and tsunami propagation efficiently and accurately with the appropriate assumptions. Landslide rheology is defined using viscous fluids, visco-plastic fluids, and granular material to account for the possible landslide source materials. Saturated and unsaturated rheologies are further included to simulate debris flow, debris avalanches, mudflows, and rockslides respectively. The models are obtained by reducing the fully three-dimensional Navier-Stokes equations with the internal rheological definition of the landslide material, the water body, and appropriate scaling assumptions to obtain the depth-averaged two-dimensional models. The landslide and tsunami models are coupled to include the interaction between the landslide and the water body for tsunami generation. The reduced models are solved numerically with a fast semi-implicit finite-volume, shock-capturing based algorithm. The well-balanced, positivity preserving algorithm accurately accounts for wet-dry interface transition for the landslide runout, landslide-water body interface, and the tsunami wave flooding on land. The models are implemented as a General-Purpose computing on Graphics Processing Unit-based (GPGPU) suite of models, either coupled or run independently within the suite. The GPGPU implementation provides up to 1000 times speedup over a CPU-based serial computation. This enables simulations of multiple scenarios of hazard realizations that provides a basis for a probabilistic hazard assessment. The models have been successfully validated against experiments, past studies, and field data for landslides and tsunamis.

Accounting for Uncertainties in Strengths of SiC MEMS Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel; Evans, Laura; Beheim, Glen; Trapp, Mark; Jadaan, Osama; Sharpe, William N., Jr.

2007-01-01

A methodology has been devised for accounting for uncertainties in the strengths of silicon carbide structural components of microelectromechanical systems (MEMS). The methodology enables prediction of the probabilistic strengths of complexly shaped MEMS parts using data from tests of simple specimens. This methodology is intended to serve as a part of a rational basis for designing SiC MEMS, supplementing methodologies that have been borrowed from the art of designing macroscopic brittle material structures. The need for this or a similar methodology arises as a consequence of the fundamental nature of MEMS and the brittle silicon-based materials of which they are typically fabricated. When tested to fracture, MEMS and structural components thereof show wide part-to-part scatter in strength. The methodology involves the use of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) software in conjunction with the ANSYS Probabilistic Design System (PDS) software to simulate or predict the strength responses of brittle material components while simultaneously accounting for the effects of variability of geometrical features on the strength responses. As such, the methodology involves the use of an extended version of the ANSYS/CARES/PDS software system described in Probabilistic Prediction of Lifetimes of Ceramic Parts (LEW-17682-1/4-1), Software Tech Briefs supplement to NASA Tech Briefs, Vol. 30, No. 9 (September 2006), page 10. The ANSYS PDS software enables the ANSYS finite-element-analysis program to account for uncertainty in the design-and analysis process. The ANSYS PDS software accounts for uncertainty in material properties, dimensions, and loading by assigning probabilistic distributions to user-specified model parameters and performing simulations using various sampling techniques.

Analysis of the French insurance market exposure to floods: a stochastic model combining river overflow and surface runoff

NASA Astrophysics Data System (ADS)

Moncoulon, D.; Labat, D.; Ardon, J.; Leblois, E.; Onfroy, T.; Poulard, C.; Aji, S.; Rémy, A.; Quantin, A.

2014-09-01

The analysis of flood exposure at a national scale for the French insurance market must combine the generation of a probabilistic event set of all possible (but which have not yet occurred) flood situations with hazard and damage modeling. In this study, hazard and damage models are calibrated on a 1995-2010 historical event set, both for hazard results (river flow, flooded areas) and loss estimations. Thus, uncertainties in the deterministic estimation of a single event loss are known before simulating a probabilistic event set. To take into account at least 90 % of the insured flood losses, the probabilistic event set must combine the river overflow (small and large catchments) with the surface runoff, due to heavy rainfall, on the slopes of the watershed. Indeed, internal studies of the CCR (Caisse Centrale de Reassurance) claim database have shown that approximately 45 % of the insured flood losses are located inside the floodplains and 45 % outside. Another 10 % is due to sea surge floods and groundwater rise. In this approach, two independent probabilistic methods are combined to create a single flood loss distribution: a generation of fictive river flows based on the historical records of the river gauge network and a generation of fictive rain fields on small catchments, calibrated on the 1958-2010 Météo-France rain database SAFRAN. All the events in the probabilistic event sets are simulated with the deterministic model. This hazard and damage distribution is used to simulate the flood losses at the national scale for an insurance company (Macif) and to generate flood areas associated with hazard return periods. The flood maps concern river overflow and surface water runoff. Validation of these maps is conducted by comparison with the address located claim data on a small catchment (downstream Argens).

Multi-disciplinary coupling effects for integrated design of propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions which govern the accurate response of propulsion systems. Results are presented for propulsion system responses including multi-disciplinary coupling effects using coupled multi-discipline thermal, structural, and acoustic tailoring; an integrated system of multi-disciplinary simulators; coupled material behavior/fabrication process tailoring; sensitivities using a probabilistic simulator; and coupled materials, structures, fracture, and probabilistic behavior simulator. The results demonstrate that superior designs can be achieved if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated coupled multi-discipline numerical propulsion system simulator.

Multi-disciplinary coupling for integrated design of propulsion systems

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Singhal, S. N.

1993-01-01

Effective computational simulation procedures are described for modeling the inherent multi-disciplinary interactions for determining the true response of propulsion systems. Results are presented for propulsion system responses including multi-discipline coupling effects via (1) coupled multi-discipline tailoring, (2) an integrated system of multidisciplinary simulators, (3) coupled material-behavior/fabrication-process tailoring, (4) sensitivities using a probabilistic simulator, and (5) coupled materials/structures/fracture/probabilistic behavior simulator. The results show that the best designs can be determined if the analysis/tailoring methods account for the multi-disciplinary coupling effects. The coupling across disciplines can be used to develop an integrated interactive multi-discipline numerical propulsion system simulator.

Dynamic probabilistic material flow analysis of nano-SiO2, nano iron oxides, nano-CeO2, nano-Al2O3, and quantum dots in seven European regions.

PubMed

Wang, Yan; Nowack, Bernd

2018-04-01

Static environmental exposure assessment models based on material flow analysis (MFA) have previously been used to estimate flows of engineered nanomaterials (ENMs) to the environment. However, such models do not account for changes in the system behavior over time. Dynamic MFA used in this study includes the time-dependent development of the modelling system by considering accumulation of ENMs in stocks and the environment, and the dynamic release of ENMs from nano-products. In addition, this study also included regional variations in population, waste management systems, and environmental compartments, which subsequently influence the environmental release and concentrations of ENMs. We have estimated the flows and release concentrations of nano-SiO 2 , nano-iron oxides, nano-CeO 2 , nano-Al 2 O 3 , and quantum dots in the EU and six geographical sub-regions in Europe (Central Europe, Northern Europe, Southern Europe, Eastern Europe, South-eastern Europe, and Switzerland). The model predicts that a large amount of ENMs are accumulated in stocks (not considering further transformation). For example, in the EU 2040 Mt of nano-SiO 2 are stored in the in-use stock, 80,400 tonnes have been accumulated in sediments and 65,600 tonnes in natural and urban soil from 1990 to 2014. The magnitude of flows in waste management processes in different regions varies because of differences in waste handling. For example, concentrations in landfilled waste are lowest in South-eastern Europe due to dilution by the high amount of landfilled waste in the region. The flows predicted in this work can serve as improved input data for mechanistic environmental fate models and risk assessment studies compared to previous estimates using static models. Copyright © 2018 Elsevier Ltd. All rights reserved.

Probabilistic power flow using improved Monte Carlo simulation method with correlated wind sources

NASA Astrophysics Data System (ADS)

Bie, Pei; Zhang, Buhan; Li, Hang; Deng, Weisi; Wu, Jiasi

2017-01-01

Probabilistic Power Flow (PPF) is a very useful tool for power system steady-state analysis. However, the correlation among different random injection power (like wind power) brings great difficulties to calculate PPF. Monte Carlo simulation (MCS) and analytical methods are two commonly used methods to solve PPF. MCS has high accuracy but is very time consuming. Analytical method like cumulants method (CM) has high computing efficiency but the cumulants calculating is not convenient when wind power output does not obey any typical distribution, especially when correlated wind sources are considered. In this paper, an Improved Monte Carlo simulation method (IMCS) is proposed. The joint empirical distribution is applied to model different wind power output. This method combines the advantages of both MCS and analytical method. It not only has high computing efficiency, but also can provide solutions with enough accuracy, which is very suitable for on-line analysis.

Analysis of the stochastic excitability in the flow chemical reactor

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

Bashkirtseva, Irina

2015-11-30

A dynamic model of the thermochemical process in the flow reactor is considered. We study an influence of the random disturbances on the stationary regime of this model. A phenomenon of noise-induced excitability is demonstrated. For the analysis of this phenomenon, a constructive technique based on the stochastic sensitivity functions and confidence domains is applied. It is shown how elaborated technique can be used for the probabilistic analysis of the generation of mixed-mode stochastic oscillations in the flow chemical reactor.

Analysis of the stochastic excitability in the flow chemical reactor

NASA Astrophysics Data System (ADS)

Bashkirtseva, Irina

2015-11-01

A dynamic model of the thermochemical process in the flow reactor is considered. We study an influence of the random disturbances on the stationary regime of this model. A phenomenon of noise-induced excitability is demonstrated. For the analysis of this phenomenon, a constructive technique based on the stochastic sensitivity functions and confidence domains is applied. It is shown how elaborated technique can be used for the probabilistic analysis of the generation of mixed-mode stochastic oscillations in the flow chemical reactor.

Fracture mechanics concepts in reliability analysis of monolithic ceramics

NASA Technical Reports Server (NTRS)

Manderscheid, Jane M.; Gyekenyesi, John P.

1987-01-01

Basic design concepts for high-performance, monolithic ceramic structural components are addressed. The design of brittle ceramics differs from that of ductile metals because of the inability of ceramic materials to redistribute high local stresses caused by inherent flaws. Random flaw size and orientation requires that a probabilistic analysis be performed in order to determine component reliability. The current trend in probabilistic analysis is to combine linear elastic fracture mechanics concepts with the two parameter Weibull distribution function to predict component reliability under multiaxial stress states. Nondestructive evaluation supports this analytical effort by supplying data during verification testing. It can also help to determine statistical parameters which describe the material strength variation, in particular the material threshold strength (the third Weibull parameter), which in the past was often taken as zero for simplicity.

Probabilistic durability assessment of concrete structures in marine environments: Reliability and sensitivity analysis

NASA Astrophysics Data System (ADS)

Yu, Bo; Ning, Chao-lie; Li, Bing

2017-03-01

A probabilistic framework for durability assessment of concrete structures in marine environments was proposed in terms of reliability and sensitivity analysis, which takes into account the uncertainties under the environmental, material, structural and executional conditions. A time-dependent probabilistic model of chloride ingress was established first to consider the variations in various governing parameters, such as the chloride concentration, chloride diffusion coefficient, and age factor. Then the Nataf transformation was adopted to transform the non-normal random variables from the original physical space into the independent standard Normal space. After that the durability limit state function and its gradient vector with respect to the original physical parameters were derived analytically, based on which the first-order reliability method was adopted to analyze the time-dependent reliability and parametric sensitivity of concrete structures in marine environments. The accuracy of the proposed method was verified by comparing with the second-order reliability method and the Monte Carlo simulation. Finally, the influences of environmental conditions, material properties, structural parameters and execution conditions on the time-dependent reliability of concrete structures in marine environments were also investigated. The proposed probabilistic framework can be implemented in the decision-making algorithm for the maintenance and repair of deteriorating concrete structures in marine environments.

A comparison of numerical solutions of partial differential equations with probabilistic and possibilistic parameters for the quantification of uncertainty in subsurface solute transport.

PubMed

Zhang, Kejiang; Achari, Gopal; Li, Hua

2009-11-03

Traditionally, uncertainty in parameters are represented as probabilistic distributions and incorporated into groundwater flow and contaminant transport models. With the advent of newer uncertainty theories, it is now understood that stochastic methods cannot properly represent non random uncertainties. In the groundwater flow and contaminant transport equations, uncertainty in some parameters may be random, whereas those of others may be non random. The objective of this paper is to develop a fuzzy-stochastic partial differential equation (FSPDE) model to simulate conditions where both random and non random uncertainties are involved in groundwater flow and solute transport. Three potential solution techniques namely, (a) transforming a probability distribution to a possibility distribution (Method I) then a FSPDE becomes a fuzzy partial differential equation (FPDE), (b) transforming a possibility distribution to a probability distribution (Method II) and then a FSPDE becomes a stochastic partial differential equation (SPDE), and (c) the combination of Monte Carlo methods and FPDE solution techniques (Method III) are proposed and compared. The effects of these three methods on the predictive results are investigated by using two case studies. The results show that the predictions obtained from Method II is a specific case of that got from Method I. When an exact probabilistic result is needed, Method II is suggested. As the loss or gain of information during a probability-possibility (or vice versa) transformation cannot be quantified, their influences on the predictive results is not known. Thus, Method III should probably be preferred for risk assessments.

Quantifying volcanic hazard at Campi Flegrei caldera (Italy) with uncertainty assessment: 2. Pyroclastic density current invasion maps

NASA Astrophysics Data System (ADS)

Neri, Augusto; Bevilacqua, Andrea; Esposti Ongaro, Tomaso; Isaia, Roberto; Aspinall, Willy P.; Bisson, Marina; Flandoli, Franco; Baxter, Peter J.; Bertagnini, Antonella; Iannuzzi, Enrico; Orsucci, Simone; Pistolesi, Marco; Rosi, Mauro; Vitale, Stefano

2015-04-01

Campi Flegrei (CF) is an example of an active caldera containing densely populated settlements at very high risk of pyroclastic density currents (PDCs). We present here an innovative method for assessing background spatial PDC hazard in a caldera setting with probabilistic invasion maps conditional on the occurrence of an explosive event. The method encompasses the probabilistic assessment of potential vent opening positions, derived in the companion paper, combined with inferences about the spatial density distribution of PDC invasion areas from a simplified flow model, informed by reconstruction of deposits from eruptions in the last 15 ka. The flow model describes the PDC kinematics and accounts for main effects of topography on flow propagation. Structured expert elicitation is used to incorporate certain sources of epistemic uncertainty, and a Monte Carlo approach is adopted to produce a set of probabilistic hazard maps for the whole CF area. Our findings show that, in case of eruption, almost the entire caldera is exposed to invasion with a mean probability of at least 5%, with peaks greater than 50% in some central areas. Some areas outside the caldera are also exposed to this danger, with mean probabilities of invasion of the order of 5-10%. Our analysis suggests that these probability estimates have location-specific uncertainties which can be substantial. The results prove to be robust with respect to alternative elicitation models and allow the influence on hazard mapping of different sources of uncertainty, and of theoretical and numerical assumptions, to be quantified.

Probabilistic Simulation of Multi-Scale Composite Behavior

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2012-01-01

A methodology is developed to computationally assess the non-deterministic composite response at all composite scales (from micro to structural) due to the uncertainties in the constituent (fiber and matrix) properties, in the fabrication process and in structural variables (primitive variables). The methodology is computationally efficient for simulating the probability distributions of composite behavior, such as material properties, laminate and structural responses. Bi-products of the methodology are probabilistic sensitivities of the composite primitive variables. The methodology has been implemented into the computer codes PICAN (Probabilistic Integrated Composite ANalyzer) and IPACS (Integrated Probabilistic Assessment of Composite Structures). The accuracy and efficiency of this methodology are demonstrated by simulating the uncertainties in composite typical laminates and comparing the results with the Monte Carlo simulation method. Available experimental data of composite laminate behavior at all scales fall within the scatters predicted by PICAN. Multi-scaling is extended to simulate probabilistic thermo-mechanical fatigue and to simulate the probabilistic design of a composite redome in order to illustrate its versatility. Results show that probabilistic fatigue can be simulated for different temperature amplitudes and for different cyclic stress magnitudes. Results also show that laminate configurations can be selected to increase the redome reliability by several orders of magnitude without increasing the laminate thickness--a unique feature of structural composites. The old reference denotes that nothing fundamental has been done since that time.

Commercialization of NESSUS: Status

NASA Technical Reports Server (NTRS)

Thacker, Ben H.; Millwater, Harry R.

1991-01-01

A plan was initiated in 1988 to commercialize the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) probabilistic structural analysis software. The goal of the on-going commercialization effort is to begin the transfer of Probabilistic Structural Analysis Method (PSAM) developed technology into industry and to develop additional funding resources in the general area of structural reliability. The commercialization effort is summarized. The SwRI NESSUS Software System is a general purpose probabilistic finite element computer program using state of the art methods for predicting stochastic structural response due to random loads, material properties, part geometry, and boundary conditions. NESSUS can be used to assess structural reliability, to compute probability of failure, to rank the input random variables by importance, and to provide a more cost effective design than traditional methods. The goal is to develop a general probabilistic structural analysis methodology to assist in the certification of critical components in the next generation Space Shuttle Main Engine.

Application of the Probabilistic Dynamic Synthesis Method to the Analysis of a Realistic Structure

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1998-01-01

The Probabilistic Dynamic Synthesis method is a new technique for obtaining the statistics of a desired response engineering quantity for a structure with non-deterministic parameters. The method uses measured data from modal testing of the structure as the input random variables, rather than more "primitive" quantities like geometry or material variation. This modal information is much more comprehensive and easily measured than the "primitive" information. The probabilistic analysis is carried out using either response surface reliability methods or Monte Carlo simulation. A previous work verified the feasibility of the PDS method on a simple seven degree-of-freedom spring-mass system. In this paper, extensive issues involved with applying the method to a realistic three-substructure system are examined, and free and forced response analyses are performed. The results from using the method are promising, especially when the lack of alternatives for obtaining quantitative output for probabilistic structures is considered.

Application of the Probabilistic Dynamic Synthesis Method to Realistic Structures

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ferri, Aldo A.

1998-01-01

The Probabilistic Dynamic Synthesis method is a technique for obtaining the statistics of a desired response engineering quantity for a structure with non-deterministic parameters. The method uses measured data from modal testing of the structure as the input random variables, rather than more "primitive" quantities like geometry or material variation. This modal information is much more comprehensive and easily measured than the "primitive" information. The probabilistic analysis is carried out using either response surface reliability methods or Monte Carlo simulation. In previous work, the feasibility of the PDS method applied to a simple seven degree-of-freedom spring-mass system was verified. In this paper, extensive issues involved with applying the method to a realistic three-substructure system are examined, and free and forced response analyses are performed. The results from using the method are promising, especially when the lack of alternatives for obtaining quantitative output for probabilistic structures is considered.

Probabilistic prediction of aggregate traffic demand using uncertainty in individual flight predictions.

DOT National Transportation Integrated Search

2009-08-01

Federal Aviation Administration (FAA) air traffic flow management (TFM) : decision-making is based primarily on a comparison of deterministic predictions of demand : and capacity at National Airspace System (NAS) elements such as airports, fixes and ...

Probabilistic material strength degradation model for Inconel 718 components subjected to high temperature, high-cycle and low-cycle mechanical fatigue, creep and thermal fatigue effects

NASA Technical Reports Server (NTRS)

Bast, Callie C.; Boyce, Lola

1995-01-01

This report presents the results of both the fifth and sixth year effort of a research program conducted for NASA-LeRC by The University of Texas at San Antonio (UTSA). The research included on-going development of methodology for a probabilistic material strength degradation model. The probabilistic model, in the form of a postulated randomized multifactor equation, provides for quantification of uncertainty in the lifetime material strength of aerospace propulsion system components subjected to a number of diverse random effects. This model is embodied in the computer program entitled PROMISS, which can include up to eighteen different effects. Presently, the model includes five effects that typically reduce lifetime strength: high temperature, high-cycle mechanical fatigue, low-cycle mechanical fatigue, creep and thermal fatigue. Statistical analysis was conducted on experimental Inconel 718 data obtained from the open literature. This analysis provided regression parameters for use as the model's empirical material constants, thus calibrating the model specifically for Inconel 718. Model calibration was carried out for five variables, namely, high temperature, high-cycle and low-cycle mechanical fatigue, creep and thermal fatigue. Methodology to estimate standard deviations of these material constants for input into the probabilistic material strength model was developed. Using an updated version of PROMISS, entitled PROMISS93, a sensitivity study for the combined effects of high-cycle mechanical fatigue, creep and thermal fatigue was performed. Then using the current version of PROMISS, entitled PROMISS94, a second sensitivity study including the effect of low-cycle mechanical fatigue, as well as, the three previous effects was performed. Results, in the form of cumulative distribution functions, illustrated the sensitivity of lifetime strength to any current value of an effect. In addition, verification studies comparing a combination of high-cycle mechanical fatigue and high temperature effects by model to the combination by experiment were conducted. Thus, for Inconel 718, the basic model assumption of independence between effects was evaluated. Results from this limited verification study strongly supported this assumption.

A regional-scale ecological risk framework for environmental flow evaluations

NASA Astrophysics Data System (ADS)

O'Brien, Gordon C.; Dickens, Chris; Hines, Eleanor; Wepener, Victor; Stassen, Retha; Quayle, Leo; Fouchy, Kelly; MacKenzie, James; Graham, P. Mark; Landis, Wayne G.

2018-02-01

Environmental flow (E-flow) frameworks advocate holistic, regional-scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in a socio-ecological context as best practice. Regional-scale ecological risk assessments of multiple stressors to social and ecological endpoints, which address ecosystem dynamism, have been undertaken internationally at different spatial scales using the relative-risk model since the mid-1990s. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional-scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to evaluate the socio-ecological consequences of historical, current and future water resource use scenarios and generate E-flow requirements on regional spatial scales. The approach has been implemented in two regional-scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence-based outcomes facilitated informed environmental management decision making, with trade-off considerations in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The 10 BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. PROBFLO can contribute to the adaptive management of water resources and contribute to the allocation of resources for sustainable use of resources and address protection requirements.

Probabilistic micromechanics for metal matrix composites

NASA Astrophysics Data System (ADS)

Engelstad, S. P.; Reddy, J. N.; Hopkins, Dale A.

A probabilistic micromechanics-based nonlinear analysis procedure is developed to predict and quantify the variability in the properties of high temperature metal matrix composites. Monte Carlo simulation is used to model the probabilistic distributions of the constituent level properties including fiber, matrix, and interphase properties, volume and void ratios, strengths, fiber misalignment, and nonlinear empirical parameters. The procedure predicts the resultant ply properties and quantifies their statistical scatter. Graphite copper and Silicon Carbide Titanlum Aluminide (SCS-6 TI15) unidirectional plies are considered to demonstrate the predictive capabilities. The procedure is believed to have a high potential for use in material characterization and selection to precede and assist in experimental studies of new high temperature metal matrix composites.

Cluster-based control of a separating flow over a smoothly contoured ramp

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Noack, Bernd R.; Spohn, Andreas; Cattafesta, Louis N.; Morzyński, Marek

2017-12-01

The ability to manipulate and control fluid flows is of great importance in many scientific and engineering applications. The proposed closed-loop control framework addresses a key issue of model-based control: The actuation effect often results from slow dynamics of strongly nonlinear interactions which the flow reveals at timescales much longer than the prediction horizon of any model. Hence, we employ a probabilistic approach based on a cluster-based discretization of the Liouville equation for the evolution of the probability distribution. The proposed methodology frames high-dimensional, nonlinear dynamics into low-dimensional, probabilistic, linear dynamics which considerably simplifies the optimal control problem while preserving nonlinear actuation mechanisms. The data-driven approach builds upon a state space discretization using a clustering algorithm which groups kinematically similar flow states into a low number of clusters. The temporal evolution of the probability distribution on this set of clusters is then described by a control-dependent Markov model. This Markov model can be used as predictor for the ergodic probability distribution for a particular control law. This probability distribution approximates the long-term behavior of the original system on which basis the optimal control law is determined. We examine how the approach can be used to improve the open-loop actuation in a separating flow dominated by Kelvin-Helmholtz shedding. For this purpose, the feature space, in which the model is learned, and the admissible control inputs are tailored to strongly oscillatory flows.

Probabilistic Volcanic Multi-Hazard Assessment at Somma-Vesuvius (Italy): coupling Bayesian Belief Networks with a physical model for lahar propagation

NASA Astrophysics Data System (ADS)

Tierz, Pablo; Woodhouse, Mark; Phillips, Jeremy; Sandri, Laura; Selva, Jacopo; Marzocchi, Warner; Odbert, Henry

2017-04-01

Volcanoes are extremely complex physico-chemical systems where magma formed at depth breaks into the planet's surface resulting in major hazards from local to global scales. Volcano physics are dominated by non-linearities, and complicated spatio-temporal interrelationships which make volcanic hazards stochastic (i.e. not deterministic) by nature. In this context, probabilistic assessments are required to quantify the large uncertainties related to volcanic hazards. Moreover, volcanoes are typically multi-hazard environments where different hazardous processes can occur whether simultaneously or in succession. In particular, explosive volcanoes are able to accumulate, through tephra fallout and Pyroclastic Density Currents (PDCs), large amounts of pyroclastic material into the drainage basins surrounding the volcano. This addition of fresh particulate material alters the local/regional hydrogeological equilibrium and increases the frequency and magnitude of sediment-rich aqueous flows, commonly known as lahars. The initiation and volume of rain-triggered lahars may depend on: rainfall intensity and duration; antecedent rainfall; terrain slope; thickness, permeability and hydraulic diffusivity of the tephra deposit; etc. Quantifying these complex interrelationships (and their uncertainties), in a tractable manner, requires a structured but flexible probabilistic approach. A Bayesian Belief Network (BBN) is a directed acyclic graph that allows the representation of the joint probability distribution for a set of uncertain variables in a compact and efficient way, by exploiting unconditional and conditional independences between these variables. Once constructed and parametrized, the BBN uses Bayesian inference to perform causal (e.g. forecast) and/or evidential reasoning (e.g. explanation) about query variables, given some evidence. In this work, we illustrate how BBNs can be used to model the influence of several variables on the generation of rain-triggered lahars and, finally, assess the probability of occurrence of lahars of different volumes. The information utilized to parametrize the BBNs includes: (1) datasets of lahar observations; (2) numerical modelling of tephra fallout and PDCs; and (3) literature data. The BBN framework provides an opportunity to quantitatively combine these different types of evidence and use them to derive a rational approach to lahar forecasting. Lastly, we couple the BBN assessments with a shallow-water physical model for lahar propagation in order to attach probabilities to the simulated hazard footprints. We develop our methodology at Somma-Vesuvius (Italy), an explosive volcano prone to rain-triggered lahars or debris flows whether right after an eruption or during inter-eruptive periods. Accounting for the variability in tephra-fallout and dense-PDC propagation and the main geomorphological features of the catchments around Somma-Vesuvius, the areas most likely of forming medium-large lahars are the flanks of the volcano and the Sarno mountains towards the east.

A Probabilistic Assessment of Threats to Surface Water Resources in Watersheds of the Lower Colorado River Basin

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.

2012-12-01

The Salt and Verde River watersheds in the Lower Colorado River Basin are a very important surface water resource in the Southwest United States. Their runoff is captured by a downstream reservoir system serving approximately 40% of the water demand and providing hydroelectric power to the Phoenix, Arizona area. Concerns have been expressed over the risks associated with their highly variable climate dependencies under the realization that the short, historical stream flow record was but one of many possible temporal and volumetric outcome sequences. A characterization of the possible range of flow deficits arising from natural variability beyond those evident in the instrumental record can facilitate sustainability planning as well as adaptation to future climate change scenarios. Methods were developed for this study to generate very long seasonal time series of net reservoir inflows by Monte Carlo simulations of the Salt and Verde watersheds which can be analyzed for detailed probabilistic insights. Other efforts to generate stochastic flow representations for impact assessments have been limited by normality distribution assumptions, inability to represent the covariance of flow contributions from multiple watersheds, complexities of different seasonal origins of precipitation and runoff dependencies, and constraints from spectral properties of the observational record. These difficulties were overcome in this study through stationarity assessments and development of joint probability distributions with highly skewed discrete density functions characteristic of the different watershed-season behaviors derived from a 123 year record. As well, methods of introducing season-to-season correlations owing to antecedent precipitation runoff efficiency enhancements have been incorporated. Representative 10,000 year time series have been stochastically generated which reflect a full range of temporal variability in flow volume distributions. Extreme value statistical analysis methods have been employed to characterize periods of flow deficit per various definitions of a drought period. Of concern for water resources are periods of net flows lower than those necessary to maintain reservoirs without sequential depletions. Probabilities of droughts lasting from only a few years up to 25 years duration have been identified along with their distributions of time to occurrence and cumulative flow deficits which can reach 50%. The analysis has yielded representations of the full range of drought severity in both depth and duration, providing useful quantitative guidance to risk management. Similarly, the risks of extremely high flows can be quantified. This study demonstrates that the instrumented historical record, once fully characterized and probabilistically represented, can yield many more insights to threatening periods of both hydrologic deficit and excess than is often assumed.

Paleoproterozoic Collisional Structures in the Hudson Bay Lithosphere Constrained by Multi-Observable Probabilistic Inversion

NASA Astrophysics Data System (ADS)

Darbyshire, F. A.; Afonso, J. C.; Porritt, R. W.

2015-12-01

The Paleozoic Hudson Bay intracratonic basin conceals a Paleoproterozoic Himalayan-scale continental collision, the Trans-Hudson Orogen (THO), which marks an important milestone in the assembly of the Canadian Shield. The geometry of the THO is complex due to the double-indentor geometry of the collision between the Archean Superior and Western Churchill cratons. Seismic observations at regional scale show a thick, seismically fast lithospheric keel beneath the entire region; an intriguing feature of recent models is a 'curtain' of slightly lower wavespeeds trending NE-SW beneath the Bay, which may represent the remnants of more juvenile material trapped between the two Archean continental cores. The seismic models alone, however, cannot constrain the nature of this anomaly. We investigate the thermal and compositional structure of the Hudson Bay lithosphere using a multi-observable probabilistic inversion technique. This joint inversion uses Rayleigh wave phase velocity data from teleseismic earthquakes and ambient noise, geoid anomalies, surface elevation and heat flow to construct a pseudo-3D model of the crust and upper mantle. Initially a wide range of possible mantle compositions is permitted, and tests are carried out to ascertain whether the lithosphere is stratified with depth. Across the entire Hudson Bay region, low temperatures and a high degree of chemical depletion characterise the mantle lithosphere. Temperature anomalies within the lithosphere are modest, as may be expected from a tectonically-stable region. The base of the thermal lithosphere lies at depths of >250 km, reaching to ~300 km depth in the centre of the Bay. Lithospheric stratification, with a more-depleted upper layer, is best able to explain the geophysical data sets and surface observables. Some regions, where intermediate-period phase velocities are high, require stronger mid-lithospheric depletion. In addition, a narrow region of less-depleted material extends NE-SW across the Bay, likely associated with the trace of the THO collision and the entrapment of juvenile material between the highly-depleted Archean cores.

Manpower Planning Models. 5. Optimization Models

DTIC Science & Technology

1975-10-01

aide 11 neceaaary and Identity by block number) Manpower Planning \\ \\ X Modelling Optimization 20. ABS emry and Identity by block number...notation resulting from the previous maximum M. We exploit the probabilistic interpretation of the flow process whenever it eases the exposi - tion

Probabilistic Fiber Composite Micromechanics

NASA Technical Reports Server (NTRS)

Stock, Thomas A.

1996-01-01

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. The variables in which uncertainties are accounted for include constituent and void volume ratios, constituent elastic properties and strengths, and fiber misalignment. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material property variations induced by random changes expected at the material micro level. Regression results are presented to show the relative correlation between predictor and response variables in the study. These computational procedures make possible a formal description of anticipated random processes at the intra-ply level, and the related effects of these on composite properties.

Award-Winning CARES/Life Ceramics Durability Evaluation Software Is Making Advanced Technology Accessible

NASA Technical Reports Server (NTRS)

1997-01-01

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CARES/Life software developed at the NASA Lewis Research Center eases this by providing a tool that uses probabilistic reliability analysis techniques to optimize the design and manufacture of brittle material components. CARES/Life is an integrated package that predicts the probability of a monolithic ceramic component's failure as a function of its time in service. It couples commercial finite element programs--which resolve a component's temperature and stress distribution - with reliability evaluation and fracture mechanics routines for modeling strength - limiting defects. These routines are based on calculations of the probabilistic nature of the brittle material's strength.

Multi-model ensemble hydrologic prediction using Bayesian model averaging

NASA Astrophysics Data System (ADS)

Duan, Qingyun; Ajami, Newsha K.; Gao, Xiaogang; Sorooshian, Soroosh

2007-05-01

Multi-model ensemble strategy is a means to exploit the diversity of skillful predictions from different models. This paper studies the use of Bayesian model averaging (BMA) scheme to develop more skillful and reliable probabilistic hydrologic predictions from multiple competing predictions made by several hydrologic models. BMA is a statistical procedure that infers consensus predictions by weighing individual predictions based on their probabilistic likelihood measures, with the better performing predictions receiving higher weights than the worse performing ones. Furthermore, BMA provides a more reliable description of the total predictive uncertainty than the original ensemble, leading to a sharper and better calibrated probability density function (PDF) for the probabilistic predictions. In this study, a nine-member ensemble of hydrologic predictions was used to test and evaluate the BMA scheme. This ensemble was generated by calibrating three different hydrologic models using three distinct objective functions. These objective functions were chosen in a way that forces the models to capture certain aspects of the hydrograph well (e.g., peaks, mid-flows and low flows). Two sets of numerical experiments were carried out on three test basins in the US to explore the best way of using the BMA scheme. In the first set, a single set of BMA weights was computed to obtain BMA predictions, while the second set employed multiple sets of weights, with distinct sets corresponding to different flow intervals. In both sets, the streamflow values were transformed using Box-Cox transformation to ensure that the probability distribution of the prediction errors is approximately Gaussian. A split sample approach was used to obtain and validate the BMA predictions. The test results showed that BMA scheme has the advantage of generating more skillful and equally reliable probabilistic predictions than original ensemble. The performance of the expected BMA predictions in terms of daily root mean square error (DRMS) and daily absolute mean error (DABS) is generally superior to that of the best individual predictions. Furthermore, the BMA predictions employing multiple sets of weights are generally better than those using single set of weights.

Efficient Multiscale Computation with Improved Momentum Flux Coupling via Operator-Splitting and Probabilistic Uncertainty Quantification

DTIC Science & Technology

2016-08-23

Different percentages of clay (10 to 30%) and sand (35 to 55%) have been used to represent various flow concentrations (Table 1). Dynamic viscosity of the... viscosity , was adopted as the wall boundary treatment method. 2.2 Physical Domain The domain consists of a 7.0m long flume, which has an inclination of...the shear stress, μapp is the apparent viscosity , K is the flow consistency index, n is the flow behavior index, and γ is the shear rate, which is

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

Diffusion tensor tractography of the arcuate fasciculus in patients with brain tumors: Comparison between deterministic and probabilistic models

PubMed Central

Li, Zhixi; Peck, Kyung K.; Brennan, Nicole P.; Jenabi, Mehrnaz; Hsu, Meier; Zhang, Zhigang; Holodny, Andrei I.; Young, Robert J.

2014-01-01

Purpose The purpose of this study was to compare the deterministic and probabilistic tracking methods of diffusion tensor white matter fiber tractography in patients with brain tumors. Materials and Methods We identified 29 patients with left brain tumors <2 cm from the arcuate fasciculus who underwent pre-operative language fMRI and DTI. The arcuate fasciculus was reconstructed using a deterministic Fiber Assignment by Continuous Tracking (FACT) algorithm and a probabilistic method based on an extended Monte Carlo Random Walk algorithm. Tracking was controlled using two ROIs corresponding to Broca’s and Wernicke’s areas. Tracts in tumoraffected hemispheres were examined for extension between Broca’s and Wernicke’s areas, anterior-posterior length and volume, and compared with the normal contralateral tracts. Results Probabilistic tracts displayed more complete anterior extension to Broca’s area than did FACT tracts on the tumor-affected and normal sides (p < 0.0001). The median length ratio for tumor: normal sides was greater for probabilistic tracts than FACT tracts (p < 0.0001). The median tract volume ratio for tumor: normal sides was also greater for probabilistic tracts than FACT tracts (p = 0.01). Conclusion Probabilistic tractography reconstructs the arcuate fasciculus more completely and performs better through areas of tumor and/or edema. The FACT algorithm tends to underestimate the anterior-most fibers of the arcuate fasciculus, which are crossed by primary motor fibers. PMID:25328583

Fatigue crack growth model RANDOM2 user manual. Appendix 1: Development of advanced methodologies for probabilistic constitutive relationships of material strength models

NASA Technical Reports Server (NTRS)

Boyce, Lola; Lovelace, Thomas B.

1989-01-01

FORTRAN program RANDOM2 is presented in the form of a user's manual. RANDOM2 is based on fracture mechanics using a probabilistic fatigue crack growth model. It predicts the random lifetime of an engine component to reach a given crack size. Details of the theoretical background, input data instructions, and a sample problem illustrating the use of the program are included.

Fatigue strength reduction model: RANDOM3 and RANDOM4 user manual. Appendix 2: Development of advanced methodologies for probabilistic constitutive relationships of material strength models

NASA Technical Reports Server (NTRS)

Boyce, Lola; Lovelace, Thomas B.

1989-01-01

FORTRAN programs RANDOM3 and RANDOM4 are documented in the form of a user's manual. Both programs are based on fatigue strength reduction, using a probabilistic constitutive model. The programs predict the random lifetime of an engine component to reach a given fatigue strength. The theoretical backgrounds, input data instructions, and sample problems illustrating the use of the programs are included.

Identification of failure type in corroded pipelines: a bayesian probabilistic approach.

PubMed

Breton, T; Sanchez-Gheno, J C; Alamilla, J L; Alvarez-Ramirez, J

2010-07-15

Spillover of hazardous materials from transport pipelines can lead to catastrophic events with serious and dangerous environmental impact, potential fire events and human fatalities. The problem is more serious for large pipelines when the construction material is under environmental corrosion conditions, as in the petroleum and gas industries. In this way, predictive models can provide a suitable framework for risk evaluation, maintenance policies and substitution procedure design that should be oriented to reduce increased hazards. This work proposes a bayesian probabilistic approach to identify and predict the type of failure (leakage or rupture) for steel pipelines under realistic corroding conditions. In the first step of the modeling process, the mechanical performance of the pipe is considered for establishing conditions under which either leakage or rupture failure can occur. In the second step, experimental burst tests are used to introduce a mean probabilistic boundary defining a region where the type of failure is uncertain. In the boundary vicinity, the failure discrimination is carried out with a probabilistic model where the events are considered as random variables. In turn, the model parameters are estimated with available experimental data and contrasted with a real catastrophic event, showing good discrimination capacity. The results are discussed in terms of policies oriented to inspection and maintenance of large-size pipelines in the oil and gas industry. 2010 Elsevier B.V. All rights reserved.

On problems of analyzing aerodynamic properties of blunted rotary bodies with small random surface distortions under supersonic and hypersonic flows

NASA Astrophysics Data System (ADS)

Degtyar, V. G.; Kalashnikov, S. T.; Mokin, Yu. A.

2017-10-01

The paper considers problems of analyzing aerodynamic properties (ADP) of reenetry vehicles (RV) as blunted rotary bodies with small random surface distortions. The interactions of math simulation of surface distortions, selection of tools for predicting ADPs of shaped bodies, evaluation of different-type ADP variations and their adaptation for dynamic problems are analyzed. The possibilities of deterministic and probabilistic approaches to evaluation of ADP variations are considered. The practical value of the probabilistic approach is demonstrated. The examples of extremal deterministic evaluations of ADP variations for a sphere and a sharp cone are given.

Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multifactor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.

Probabilistic Methods for Structural Reliability and Risk

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2008-01-01

A probabilistic method is used to evaluate the structural reliability and risk of select metallic and composite structures. The method is a multiscale, multifunctional and it is based on the most elemental level. A multi-factor interaction model is used to describe the material properties which are subsequently evaluated probabilistically. The metallic structure is a two rotor aircraft engine, while the composite structures consist of laminated plies (multiscale) and the properties of each ply are the multifunctional representation. The structural component is modeled by finite element. The solution method for structural responses is obtained by an updated simulation scheme. The results show that the risk for the two rotor engine is about 0.0001 and the composite built-up structure is also 0.0001.

Enhancement of the Probabilistic CEramic Matrix Composite ANalyzer (PCEMCAN) Computer Code

NASA Technical Reports Server (NTRS)

Shah, Ashwin

2000-01-01

This report represents a final technical report for Order No. C-78019-J entitled "Enhancement of the Probabilistic Ceramic Matrix Composite Analyzer (PCEMCAN) Computer Code." The scope of the enhancement relates to including the probabilistic evaluation of the D-Matrix terms in MAT2 and MAT9 material properties card (available in CEMCAN code) for the MSC/NASTRAN. Technical activities performed during the time period of June 1, 1999 through September 3, 1999 have been summarized, and the final version of the enhanced PCEMCAN code and revisions to the User's Manual is delivered along with. Discussions related to the performed activities were made to the NASA Project Manager during the performance period. The enhanced capabilities have been demonstrated using sample problems.

Modality, probability, and mental models.

PubMed

Hinterecker, Thomas; Knauff, Markus; Johnson-Laird, P N

2016-10-01

We report 3 experiments investigating novel sorts of inference, such as: A or B or both. Therefore, possibly (A and B). Where the contents were sensible assertions, for example, Space tourism will achieve widespread popularity in the next 50 years or advances in material science will lead to the development of antigravity materials in the next 50 years, or both . Most participants accepted the inferences as valid, though they are invalid in modal logic and in probabilistic logic too. But, the theory of mental models predicts that individuals should accept them. In contrast, inferences of this sort—A or B but not both. Therefore, A or B or both—are both logically valid and probabilistically valid. Yet, as the model theory also predicts, most reasoners rejected them. The participants’ estimates of probabilities showed that their inferences tended not to be based on probabilistic validity, but that they did rate acceptable conclusions as more probable than unacceptable conclusions. We discuss the implications of the results for current theories of reasoning. PsycINFO Database Record (c) 2016 APA, all rights reserved

In Situ Distribution Guided Analysis and Visualization of Transonic Jet Engine Simulations.

PubMed

Dutta, Soumya; Chen, Chun-Ming; Heinlein, Gregory; Shen, Han-Wei; Chen, Jen-Ping

2017-01-01

Study of flow instability in turbine engine compressors is crucial to understand the inception and evolution of engine stall. Aerodynamics experts have been working on detecting the early signs of stall in order to devise novel stall suppression technologies. A state-of-the-art Navier-Stokes based, time-accurate computational fluid dynamics simulator, TURBO, has been developed in NASA to enhance the understanding of flow phenomena undergoing rotating stall. Despite the proven high modeling accuracy of TURBO, the excessive simulation data prohibits post-hoc analysis in both storage and I/O time. To address these issues and allow the expert to perform scalable stall analysis, we have designed an in situ distribution guided stall analysis technique. Our method summarizes statistics of important properties of the simulation data in situ using a probabilistic data modeling scheme. This data summarization enables statistical anomaly detection for flow instability in post analysis, which reveals the spatiotemporal trends of rotating stall for the expert to conceive new hypotheses. Furthermore, the verification of the hypotheses and exploratory visualization using the summarized data are realized using probabilistic visualization techniques such as uncertain isocontouring. Positive feedback from the domain scientist has indicated the efficacy of our system in exploratory stall analysis.

Probabilistic Predictions of Traffic Demand for En Route Sectors Based on Individual Flight Data

DOT National Transportation Integrated Search

2010-01-01

The Traffic Flow Management System (TFMS) predicts the demand for each sector, and traffic managers use these predictions to spot possible congestion and to take measures to prevent it. These predictions of sector demand, however, are currently made ...

Estimation of distribution algorithm with path relinking for the blocking flow-shop scheduling problem

NASA Astrophysics Data System (ADS)

Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2018-05-01

This article presents an effective estimation of distribution algorithm, named P-EDA, to solve the blocking flow-shop scheduling problem (BFSP) with the makespan criterion. In the P-EDA, a Nawaz-Enscore-Ham (NEH)-based heuristic and the random method are combined to generate the initial population. Based on several superior individuals provided by a modified linear rank selection, a probabilistic model is constructed to describe the probabilistic distribution of the promising solution space. The path relinking technique is incorporated into EDA to avoid blindness of the search and improve the convergence property. A modified referenced local search is designed to enhance the local exploitation. Moreover, a diversity-maintaining scheme is introduced into EDA to avoid deterioration of the population. Finally, the parameters of the proposed P-EDA are calibrated using a design of experiments approach. Simulation results and comparisons with some well-performing algorithms demonstrate the effectiveness of the P-EDA for solving BFSP.

Uncertainty analysis of a groundwater flow model in east-central Florida

USGS Publications Warehouse

Sepúlveda, Nicasio; Doherty, John E.

2014-01-01

A groundwater flow model for east-central Florida has been developed to help water-resource managers assess the impact of increased groundwater withdrawals from the Floridan aquifer system on heads and spring flows originating from the Upper Floridan aquifer. The model provides a probabilistic description of predictions of interest to water-resource managers, given the uncertainty associated with system heterogeneity, the large number of input parameters, and a nonunique groundwater flow solution. The uncertainty associated with these predictions can then be considered in decisions with which the model has been designed to assist. The “Null Space Monte Carlo” method is a stochastic probabilistic approach used to generate a suite of several hundred parameter field realizations, each maintaining the model in a calibrated state, and each considered to be hydrogeologically plausible. The results presented herein indicate that the model’s capacity to predict changes in heads or spring flows that originate from increased groundwater withdrawals is considerably greater than its capacity to predict the absolute magnitudes of heads or spring flows. Furthermore, the capacity of the model to make predictions that are similar in location and in type to those in the calibration dataset exceeds its capacity to make predictions of different types at different locations. The quantification of these outcomes allows defensible use of the modeling process in support of future water-resources decisions. The model allows the decision-making process to recognize the uncertainties, and the spatial/temporal variability of uncertainties that are associated with predictions of future system behavior in a complex hydrogeological context.

Uncertainty analysis of a groundwater flow model in East-central Florida.

PubMed

Sepúlveda, Nicasio; Doherty, John

2015-01-01

A groundwater flow model for east-central Florida has been developed to help water-resource managers assess the impact of increased groundwater withdrawals from the Floridan aquifer system on heads and spring flows originating from the Upper Floridan Aquifer. The model provides a probabilistic description of predictions of interest to water-resource managers, given the uncertainty associated with system heterogeneity, the large number of input parameters, and a nonunique groundwater flow solution. The uncertainty associated with these predictions can then be considered in decisions with which the model has been designed to assist. The "Null Space Monte Carlo" method is a stochastic probabilistic approach used to generate a suite of several hundred parameter field realizations, each maintaining the model in a calibrated state, and each considered to be hydrogeologically plausible. The results presented herein indicate that the model's capacity to predict changes in heads or spring flows that originate from increased groundwater withdrawals is considerably greater than its capacity to predict the absolute magnitudes of heads or spring flows. Furthermore, the capacity of the model to make predictions that are similar in location and in type to those in the calibration dataset exceeds its capacity to make predictions of different types at different locations. The quantification of these outcomes allows defensible use of the modeling process in support of future water-resources decisions. The model allows the decision-making process to recognize the uncertainties, and the spatial or temporal variability of uncertainties that are associated with predictions of future system behavior in a complex hydrogeological context. © 2014, National Ground Water Association.

Probabilistic Modeling of High-Temperature Material Properties of a 5-Harness 0/90 Sylramic Fiber/ CVI-SiC/ MI-SiC Woven Composite

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.; Tong, Michael; Murthy, P. L. N.; Mital, Subodh

1998-01-01

An integrated probabilistic approach has been developed to assess composites for high temperature applications. This approach was used to determine thermal and mechanical properties and their probabilistic distributions of a 5-harness 0/90 Sylramic fiber/CVI-SiC/Mi-SiC woven Ceramic Matrix Composite (CMC) at high temperatures. The purpose of developing this approach was to generate quantitative probabilistic information on this CMC to help complete the evaluation for its potential application for HSCT combustor liner. This approach quantified the influences of uncertainties inherent in constituent properties called primitive variables on selected key response variables of the CMC at 2200 F. The quantitative information is presented in the form of Cumulative Density Functions (CDFs). Probability Density Functions (PDFS) and primitive variable sensitivities on response. Results indicate that the scatters in response variables were reduced by 30-50% when the uncertainties in the primitive variables, which showed the most influence, were reduced by 50%.

Susceptibility to enhanced chemical migration from depression-focused preferential flow, High Plains aquifer

USGS Publications Warehouse

Gurdak, Jason J.; Walvoord, Michelle Ann; McMahon, Peter B.

2008-01-01

Aquifer susceptibility to contamination is controlled in part by the inherent hydrogeologic properties of the vadose zone, which includes preferential-flow pathways. The purpose of this study was to investigate the importance of seasonal ponding near leaky irrigation wells as a mechanism for depression-focused preferential flow and enhanced chemical migration through the vadose zone of the High Plains aquifer. Such a mechanism may help explain the widespread presence of agrichemicals in recently recharged groundwater despite estimates of advective chemical transit times through the vadose zone from diffuse recharge that exceed the historical period of agriculture. Using a combination of field observations, vadose zone flow and transport simulations, and probabilistic neural network modeling, we demonstrated that vadose zone transit times near irrigation wells range from 7 to 50 yr, which are one to two orders of magnitude faster than previous estimates based on diffuse recharge. These findings support the concept of fast and slow transport zones and help to explain the previous discordant findings of long vadose zone transit times and the presence of agrichemicals at the water table. Using predictions of aquifer susceptibility from probabilistic neural network models, we delineated approximately 20% of the areal extent of the aquifer to have conditions that may promote advective chemical transit times to the water table of <50 yr if seasonal ponding and depression-focused flow exist. This aquifer-susceptibility map may help managers prioritize areas for groundwater monitoring or implementation of best management practices.

Application of Non-Deterministic Methods to Assess Modeling Uncertainties for Reinforced Carbon-Carbon Debris Impacts

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Fasanella, Edwin L.; Melis, Matthew; Carney, Kelly; Gabrys, Jonathan

2004-01-01

The Space Shuttle Columbia Accident Investigation Board (CAIB) made several recommendations for improving the NASA Space Shuttle Program. An extensive experimental and analytical program has been developed to address two recommendations related to structural impact analysis. The objective of the present work is to demonstrate the application of probabilistic analysis to assess the effect of uncertainties on debris impacts on Space Shuttle Reinforced Carbon-Carbon (RCC) panels. The probabilistic analysis is used to identify the material modeling parameters controlling the uncertainty. A comparison of the finite element results with limited experimental data provided confidence that the simulations were adequately representing the global response of the material. Five input parameters were identified as significantly controlling the response.

Application of Probability Methods to Assess Crash Modeling Uncertainty

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Stockwell, Alan E.; Hardy, Robin C.

2003-01-01

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stress-strain behaviors, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the effects of finite element modeling assumptions on the predicted responses. The vertical drop test of a Fokker F28 fuselage section will be the focus of this paper. The results of a probabilistic analysis using finite element simulations will be compared with experimental data.

Application of Probability Methods to Assess Crash Modeling Uncertainty

NASA Technical Reports Server (NTRS)

Lyle, Karen H.; Stockwell, Alan E.; Hardy, Robin C.

2007-01-01

Full-scale aircraft crash simulations performed with nonlinear, transient dynamic, finite element codes can incorporate structural complexities such as: geometrically accurate models; human occupant models; and advanced material models to include nonlinear stress-strain behaviors, and material failure. Validation of these crash simulations is difficult due to a lack of sufficient information to adequately determine the uncertainty in the experimental data and the appropriateness of modeling assumptions. This paper evaluates probabilistic approaches to quantify the effects of finite element modeling assumptions on the predicted responses. The vertical drop test of a Fokker F28 fuselage section will be the focus of this paper. The results of a probabilistic analysis using finite element simulations will be compared with experimental data.

Dynamic Statistical Models for Pyroclastic Density Current Generation at Soufrière Hills Volcano

NASA Astrophysics Data System (ADS)

Wolpert, Robert L.; Spiller, Elaine T.; Calder, Eliza S.

2018-05-01

To mitigate volcanic hazards from pyroclastic density currents, volcanologists generate hazard maps that provide long-term forecasts of areas of potential impact. Several recent efforts in the field develop new statistical methods for application of flow models to generate fully probabilistic hazard maps that both account for, and quantify, uncertainty. However a limitation to the use of most statistical hazard models, and a key source of uncertainty within them, is the time-averaged nature of the datasets by which the volcanic activity is statistically characterized. Where the level, or directionality, of volcanic activity frequently changes, e.g. during protracted eruptive episodes, or at volcanoes that are classified as persistently active, it is not appropriate to make short term forecasts based on longer time-averaged metrics of the activity. Thus, here we build, fit and explore dynamic statistical models for the generation of pyroclastic density current from Soufrière Hills Volcano (SHV) on Montserrat including their respective collapse direction and flow volumes based on 1996-2008 flow datasets. The development of this approach allows for short-term behavioral changes to be taken into account in probabilistic volcanic hazard assessments. We show that collapses from the SHV lava dome follow a clear pattern, and that a series of smaller flows in a given direction often culminate in a larger collapse and thereafter directionality of the flows change. Such models enable short term forecasting (weeks to months) that can reflect evolving conditions such as dome and crater morphology changes and non-stationary eruptive behavior such as extrusion rate variations. For example, the probability of inundation of the Belham Valley in the first 180 days of a forecast period is about twice as high for lava domes facing Northwest toward that valley as it is for domes pointing East toward the Tar River Valley. As rich multi-parametric volcano monitoring dataset become increasingly available, eruption forecasting is becoming an increasingly viable and important research field. We demonstrate an approach to utilize such data in order to appropriately 'tune' probabilistic hazard assessments for pyroclastic flows. Our broader objective with development of this method is to help advance time-dependent volcanic hazard assessment, by bridging the

Ensemble reconstruction of severe low flow events in France since 1871

NASA Astrophysics Data System (ADS)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2016-04-01

This work presents a study of severe low flow events that occurred from 1871 onwards for a large number of near-natural catchments in France. It aims at assessing and comparing their characteristics to improve our knowledge on historical events and to provide a selection of benchmark events for climate change adaptation purposes. The historical depth of streamflow observations is generally limited to the last 50 years and therefore offers too small a sample of severe low flow events to properly explore the long-term evolution of their characteristics and associated impacts. In order to overcome this limit, this work takes advantage of a 140-year ensemble hydrometeorological dataset over France based on: (1) a probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France (Caillouet et al., 2015), and (2) a continuous hydrological modelling that uses the high-resolution meteorological reconstructions as forcings over the whole period. This dataset provides an ensemble of 25 equally plausible daily streamflow time series for a reference network of stations in France over the whole 1871-2012 period. Severe low flow events are identified based on a combination of a fixed threshold and a daily variable threshold. Each event is characterized by its deficit, duration and timing by applying the Sequent Peak Algorithm. The procedure is applied to the 25 simulated time series as well as to the observed time series in order to compare observed and simulated events over the recent period, and to characterize in a probabilistic way unrecorded historical events. The ensemble aspect of the reconstruction leads to address specific issues, for properly defining events across ensemble simulations, as well as for adequately comparing the simulated characteristics to the observed ones. This study brings forward the outstanding 1921 and 1940s events but also older and less known ones that occurred during the last decade of the 19th century. For the first time, severe low flow events are qualified in a homogeneous way over 140 years on a large set of near-natural French catchments, allowing for detailed analyses of the effect of climate variability and anthropogenic climate change on low flow hydrology. Caillouet, L., Vidal, J.-P., Sauquet, E., and Graff, B. (2015) Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France, Clim. Past Discuss., 11, 4425-4482, doi:10.5194/cpd-11-4425-2015

Probabilistic forecasts of debris-flow hazard at the regional scale with a combination of models.

NASA Astrophysics Data System (ADS)

Malet, Jean-Philippe; Remaître, Alexandre

2015-04-01

Debris flows are one of the many active slope-forming processes in the French Alps, where rugged and steep slopes mantled by various slope deposits offer a great potential for triggering hazardous events. A quantitative assessment of debris-flow hazard requires the estimation, in a probabilistic framework, of the spatial probability of occurrence of source areas, the spatial probability of runout areas, the temporal frequency of events, and their intensity. The main objective of this research is to propose a pipeline for the estimation of these quantities at the region scale using a chain of debris-flow models. The work uses the experimental site of the Barcelonnette Basin (South French Alps), where 26 active torrents have produced more than 150 debris-flow events since 1850 to develop and validate the methodology. First, a susceptibility assessment is performed to identify the debris-flow prone source areas. The most frequently used approach is the combination of environmental factors with GIS procedures and statistical techniques, integrating or not, detailed event inventories. Based on a 5m-DEM and derivatives, and information on slope lithology, engineering soils and landcover, the possible source areas are identified with a statistical logistic regression model. The performance of the statistical model is evaluated with the observed distribution of debris-flow events recorded after 1850 in the study area. The source areas in the three most active torrents (Riou-Bourdoux, Faucon, Sanières) are well identified by the model. Results are less convincing for three other active torrents (Bourget, La Valette and Riou-Chanal); this could be related to the type of debris-flow triggering mechanism as the model seems to better spot the open slope debris-flow source areas (e.g. scree slopes), but appears to be less efficient for the identification of landslide-induced debris flows. Second, a susceptibility assessment is performed to estimate the possible runout distance with a process-based model. The MassMov-2D code is a two-dimensional model of mud and debris flow dynamics over complex topography, based on a numerical integration of the depth-averaged motion equations using shallow water approximation. The run-out simulations are performed for the most active torrents. The performance of the model has been evaluated by comparing modelling results with the observed spreading areas of several recent debris flows. Existing data on the debris flow volume, input discharge and deposits were used to back-analyze those events and estimate the values of the model parameters. Third, hazard is estimated on the basis of scenarios computed in a probabilistic way, for volumes in the range 20'000 to 350'000 m3, and for several combinations of rheological parameters. In most cases, the simulations indicate that the debris flows cause significant overflowing on the alluvial fans for volumes exceeding 100'000 m3 (height of deposits > 2 m, velocities > 5 m.s-1). Probabilities of debris flow runout and debris flow intensities are then computed for each terrain units.

Probabilistic constraints from existing and future radar imaging on volcanic activity on Venus

NASA Astrophysics Data System (ADS)

Lorenz, Ralph D.

2015-11-01

We explore the quantitative limits that may be placed on Venus' present-day volcanic activity by radar imaging of surface landforms. The apparent nondetection of new lava flows in the areas observed twice by Magellan suggests that there is a ~60% chance that the eruption rate is ~1 km3/yr or less, using the eruption history and area/volume flow geometry of terrestrial volcanoes (Etna, Mauna Loa and Merapi) as a guide. However, if the detection probability of an individual flow is low (e.g. ~10%) due to poor resolution or quality and unmodeled viewing geometry effects, the constraint (<10 km3/yr) is not useful. Imaging at Magellan resolution or better of only ~10% of the surface area of Venus on a new mission (30 years after Magellan) would yield better than 99% chance of detecting a new lava flow, even if the volcanic activity is at the low end of predictions (~0.01 km3/yr) and is expressed through a single volcano with a stochastic eruption history. Closer re-examination of Magellan data may be worthwhile, both to search for new features, and to establish formal (location-dependent) limits on activity against which data from future missions can be tested. While Magellan-future and future-future comparisons should offer much lower detection thresholds for erupted volumes, a probabilistic approach will be required to properly understand the implications.

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 1. Theory

USGS Publications Warehouse

Yen, Chung-Cheng; Guymon, Gary L.

1990-01-01

An efficient probabilistic model is developed and cascaded with a deterministic model for predicting water table elevations in regional aquifers. The objective is to quantify model uncertainty where precise estimates of water table elevations may be required. The probabilistic model is based on the two-point probability method which only requires prior knowledge of uncertain variables mean and coefficient of variation. The two-point estimate method is theoretically developed and compared with the Monte Carlo simulation method. The results of comparisons using hypothetical determinisitic problems indicate that the two-point estimate method is only generally valid for linear problems where the coefficients of variation of uncertain parameters (for example, storage coefficient and hydraulic conductivity) is small. The two-point estimate method may be applied to slightly nonlinear problems with good results, provided coefficients of variation are small. In such cases, the two-point estimate method is much more efficient than the Monte Carlo method provided the number of uncertain variables is less than eight.

An Efficient Deterministic-Probabilistic Approach to Modeling Regional Groundwater Flow: 1. Theory

NASA Astrophysics Data System (ADS)

Yen, Chung-Cheng; Guymon, Gary L.

1990-07-01

An efficient probabilistic model is developed and cascaded with a deterministic model for predicting water table elevations in regional aquifers. The objective is to quantify model uncertainty where precise estimates of water table elevations may be required. The probabilistic model is based on the two-point probability method which only requires prior knowledge of uncertain variables mean and coefficient of variation. The two-point estimate method is theoretically developed and compared with the Monte Carlo simulation method. The results of comparisons using hypothetical determinisitic problems indicate that the two-point estimate method is only generally valid for linear problems where the coefficients of variation of uncertain parameters (for example, storage coefficient and hydraulic conductivity) is small. The two-point estimate method may be applied to slightly nonlinear problems with good results, provided coefficients of variation are small. In such cases, the two-point estimate method is much more efficient than the Monte Carlo method provided the number of uncertain variables is less than eight.

Probabilistic forecasts based on radar rainfall uncertainty

NASA Astrophysics Data System (ADS)

Liguori, S.; Rico-Ramirez, M. A.

2012-04-01

The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall [12] and flows at the urban scale [13]. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.

Probabilistic Assessment of National Wind Tunnel

NASA Technical Reports Server (NTRS)

Shah, A. R.; Shiao, M.; Chamis, C. C.

1996-01-01

A preliminary probabilistic structural assessment of the critical section of National Wind Tunnel (NWT) is performed using NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) computer code. Thereby, the capabilities of NESSUS code have been demonstrated to address reliability issues of the NWT. Uncertainties in the geometry, material properties, loads and stiffener location on the NWT are considered to perform the reliability assessment. Probabilistic stress, frequency, buckling, fatigue and proof load analyses are performed. These analyses cover the major global and some local design requirements. Based on the assumed uncertainties, the results reveal the assurance of minimum 0.999 reliability for the NWT. Preliminary life prediction analysis results show that the life of the NWT is governed by the fatigue of welds. Also, reliability based proof test assessment is performed.

Inferential Framework for Autonomous Cryogenic Loading Operations

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry G.; Khasin, Michael; Timucin, Dogan; Sass, Jared; Perotti, Jose; Brown, Barbara

2017-01-01

We address problem of autonomous cryogenic management of loading operations on the ground and in space. As a step towards solution of this problem we develop a probabilistic framework for inferring correlations parameters of two-fluid cryogenic flow. The simulation of two-phase cryogenic flow is performed using nearly-implicit scheme. A concise set of cryogenic correlations is introduced. The proposed approach is applied to an analysis of the cryogenic flow in experimental Propellant Loading System built at NASA KSC. An efficient simultaneous optimization of a large number of model parameters is demonstrated and a good agreement with the experimental data is obtained.

Probabilistic Aeroelastic Analysis Developed for Turbomachinery Components

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Mital, Subodh K.; Stefko, George L.; Pai, Shantaram S.

2003-01-01

Aeroelastic analyses for advanced turbomachines are being developed for use at the NASA Glenn Research Center and industry. However, these analyses at present are used for turbomachinery design with uncertainties accounted for by using safety factors. This approach may lead to overly conservative designs, thereby reducing the potential of designing higher efficiency engines. An integration of the deterministic aeroelastic analysis methods with probabilistic analysis methods offers the potential to design efficient engines with fewer aeroelastic problems and to make a quantum leap toward designing safe reliable engines. In this research, probabilistic analysis is integrated with aeroelastic analysis: (1) to determine the parameters that most affect the aeroelastic characteristics (forced response and stability) of a turbomachine component such as a fan, compressor, or turbine and (2) to give the acceptable standard deviation on the design parameters for an aeroelastically stable system. The approach taken is to combine the aeroelastic analysis of the MISER (MIStuned Engine Response) code with the FPI (fast probability integration) code. The role of MISER is to provide the functional relationships that tie the structural and aerodynamic parameters (the primitive variables) to the forced response amplitudes and stability eigenvalues (the response properties). The role of FPI is to perform probabilistic analyses by utilizing the response properties generated by MISER. The results are a probability density function for the response properties. The probabilistic sensitivities of the response variables to uncertainty in primitive variables are obtained as a byproduct of the FPI technique. The combined analysis of aeroelastic and probabilistic analysis is applied to a 12-bladed cascade vibrating in bending and torsion. Out of the total 11 design parameters, 6 are considered as having probabilistic variation. The six parameters are space-to-chord ratio (SBYC), stagger angle (GAMA), elastic axis (ELAXS), Mach number (MACH), mass ratio (MASSR), and frequency ratio (WHWB). The cascade is considered to be in subsonic flow with Mach 0.7. The results of the probabilistic aeroelastic analysis are the probability density function of predicted aerodynamic damping and frequency for flutter and the response amplitudes for forced response.

Life prediction of different commercial dental implants as influence by uncertainties in their fatigue material properties and loading conditions.

PubMed

Pérez, M A

2012-12-01

Probabilistic analyses allow the effect of uncertainty in system parameters to be determined. In the literature, many researchers have investigated static loading effects on dental implants. However, the intrinsic variability and uncertainty of most of the main problem parameters are not accounted for. The objective of this research was to apply a probabilistic computational approach to predict the fatigue life of three different commercial dental implants considering the variability and uncertainty in their fatigue material properties and loading conditions. For one of the commercial dental implants, the influence of its diameter in the fatigue life performance was also studied. This stochastic technique was based on the combination of a probabilistic finite element method (PFEM) and a cumulative damage approach known as B-model. After 6 million of loading cycles, local failure probabilities of 0.3, 0.4 and 0.91 were predicted for the Lifecore, Avinent and GMI implants, respectively (diameter of 3.75mm). The influence of the diameter for the GMI implant was studied and the results predicted a local failure probability of 0.91 and 0.1 for the 3.75mm and 5mm, respectively. In all cases the highest failure probability was located at the upper screw-threads. Therefore, the probabilistic methodology proposed herein may be a useful tool for performing a qualitative comparison between different commercial dental implants. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Verification of recursive probabilistic integration (RPI) method for fatigue life management using non-destructive inspections

NASA Astrophysics Data System (ADS)

Chen, Tzikang J.; Shiao, Michael

2016-04-01

This paper verified a generic and efficient assessment concept for probabilistic fatigue life management. The concept is developed based on an integration of damage tolerance methodology, simulations methods1, 2, and a probabilistic algorithm RPI (recursive probability integration)3-9 considering maintenance for damage tolerance and risk-based fatigue life management. RPI is an efficient semi-analytical probabilistic method for risk assessment subjected to various uncertainties such as the variability in material properties including crack growth rate, initial flaw size, repair quality, random process modeling of flight loads for failure analysis, and inspection reliability represented by probability of detection (POD). In addition, unlike traditional Monte Carlo simulations (MCS) which requires a rerun of MCS when maintenance plan is changed, RPI can repeatedly use a small set of baseline random crack growth histories excluding maintenance related parameters from a single MCS for various maintenance plans. In order to fully appreciate the RPI method, a verification procedure was performed. In this study, MC simulations in the orders of several hundred billions were conducted for various flight conditions, material properties, and inspection scheduling, POD and repair/replacement strategies. Since the MC simulations are time-consuming methods, the simulations were conducted parallelly on DoD High Performance Computers (HPC) using a specialized random number generator for parallel computing. The study has shown that RPI method is several orders of magnitude more efficient than traditional Monte Carlo simulations.

Functionally Graded Designer Viscoelastic Materials Tailored to Perform Prescribed Tasks with Probabilistic Failures and Lifetimes

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

Hilton, Harry H.

Protocols are developed for formulating optimal viscoelastic designer functionally graded materials tailored to best respond to prescribed loading and boundary conditions. In essence, an inverse approach is adopted where material properties instead of structures per se are designed and then distributed throughout structural elements. The final measure of viscoelastic material efficacy is expressed in terms of failure probabilities vs. survival time000.

A probabilistic approach to modeling postfire erosion after the 2009 australian brushfires

USDA-ARS?s Scientific Manuscript database

Major concerns after bushfires and wildfires include increased flooding, erosion and debris flows due to loss of the protective forest floor layer, loss of water storage, and creation of water repellent soil conditions. To assist postfire assessment teams in their efforts to evaluate fire effects an...

Mastodon

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

Coleman, Justin Leigh; Veeraraghavan, Swetha; Bolisetti, Chandrakanth

MASTODON has the capability to model stochastic nonlinear soil-structure interaction (NLSSI) in a dynamic probabilistic risk assessment framework. The NLSSI simulations include structural dynamics, time integration, dynamic porous media flow, nonlinear hysteretic soil constitutive models, geometric nonlinearities (gapping, sliding, and uplift). MASTODON is also the MOOSE based master application for dynamic PRA of external hazards.

Probabilistic fracture finite elements

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Lua, Y. J.

1991-01-01

The Probabilistic Fracture Mechanics (PFM) is a promising method for estimating the fatigue life and inspection cycles for mechanical and structural components. The Probability Finite Element Method (PFEM), which is based on second moment analysis, has proved to be a promising, practical approach to handle problems with uncertainties. As the PFEM provides a powerful computational tool to determine first and second moment of random parameters, the second moment reliability method can be easily combined with PFEM to obtain measures of the reliability of the structural system. The method is also being applied to fatigue crack growth. Uncertainties in the material properties of advanced materials such as polycrystalline alloys, ceramics, and composites are commonly observed from experimental tests. This is mainly attributed to intrinsic microcracks, which are randomly distributed as a result of the applied load and the residual stress.

Probabilistic fracture finite elements

NASA Astrophysics Data System (ADS)

Liu, W. K.; Belytschko, T.; Lua, Y. J.

1991-05-01

The Probabilistic Fracture Mechanics (PFM) is a promising method for estimating the fatigue life and inspection cycles for mechanical and structural components. The Probability Finite Element Method (PFEM), which is based on second moment analysis, has proved to be a promising, practical approach to handle problems with uncertainties. As the PFEM provides a powerful computational tool to determine first and second moment of random parameters, the second moment reliability method can be easily combined with PFEM to obtain measures of the reliability of the structural system. The method is also being applied to fatigue crack growth. Uncertainties in the material properties of advanced materials such as polycrystalline alloys, ceramics, and composites are commonly observed from experimental tests. This is mainly attributed to intrinsic microcracks, which are randomly distributed as a result of the applied load and the residual stress.

Probabilistic Evaluation of Three-Dimensional Reconstructions from X-Ray Images Spanning a Limited Angle

PubMed Central

Frost, Anja; Renners, Eike; Hötter, Michael; Ostermann, Jörn

2013-01-01

An important part of computed tomography is the calculation of a three-dimensional reconstruction of an object from series of X-ray images. Unfortunately, some applications do not provide sufficient X-ray images. Then, the reconstructed objects no longer truly represent the original. Inside of the volumes, the accuracy seems to vary unpredictably. In this paper, we introduce a novel method to evaluate any reconstruction, voxel by voxel. The evaluation is based on a sophisticated probabilistic handling of the measured X-rays, as well as the inclusion of a priori knowledge about the materials that the object receiving the X-ray examination consists of. For each voxel, the proposed method outputs a numerical value that represents the probability of existence of a predefined material at the position of the voxel while doing X-ray. Such a probabilistic quality measure was lacking so far. In our experiment, false reconstructed areas get detected by their low probability. In exact reconstructed areas, a high probability predominates. Receiver Operating Characteristics not only confirm the reliability of our quality measure but also demonstrate that existing methods are less suitable for evaluating a reconstruction. PMID:23344378

Probabilistic Dynamic Buckling of Smart Composite Shells

NASA Technical Reports Server (NTRS)

Abumeri, Galib H.; Chamis, Christos C.

2003-01-01

A computational simulation method is presented to evaluate the deterministic and nondeterministic dynamic buckling of smart composite shells. The combined use of composite mechanics, finite element computer codes, and probabilistic analysis enable the effective assessment of the dynamic buckling load of smart composite shells. A universal plot is generated to estimate the dynamic buckling load of composite shells at various load rates and probabilities. The shell structure is also evaluated with smart fibers embedded in the plies right below the outer plies. The results show that, on the average, the use of smart fibers improved the shell buckling resistance by about 10 percent at different probabilities and delayed the buckling occurrence time. The probabilistic sensitivities results indicate that uncertainties in the fiber volume ratio and ply thickness have major effects on the buckling load while uncertainties in the electric field strength and smart material volume fraction have moderate effects. For the specific shell considered in this evaluation, the use of smart composite material is not recommended because the shell buckling resistance can be improved by simply re-arranging the orientation of the outer plies, as shown in the dynamic buckling analysis results presented in this report.

Probabilistic Dynamic Buckling of Smart Composite Shells

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2007-01-01

A computational simulation method is presented to evaluate the deterministic and nondeterministic dynamic buckling of smart composite shells. The combined use of intraply hybrid composite mechanics, finite element computer codes, and probabilistic analysis enable the effective assessment of the dynamic buckling load of smart composite shells. A universal plot is generated to estimate the dynamic buckling load of composite shells at various load rates and probabilities. The shell structure is also evaluated with smart fibers embedded in the plies right next to the outer plies. The results show that, on the average, the use of smart fibers improved the shell buckling resistance by about 10% at different probabilities and delayed the buckling occurrence time. The probabilistic sensitivities results indicate that uncertainties in the fiber volume ratio and ply thickness have major effects on the buckling load while uncertainties in the electric field strength and smart material volume fraction have moderate effects. For the specific shell considered in this evaluation, the use of smart composite material is not recommended because the shell buckling resistance can be improved by simply re-arranging the orientation of the outer plies, as shown in the dynamic buckling analysis results presented in this report.

Probabilistic/Fracture-Mechanics Model For Service Life

NASA Technical Reports Server (NTRS)

Watkins, T., Jr.; Annis, C. G., Jr.

1991-01-01

Computer program makes probabilistic estimates of lifetime of engine and components thereof. Developed to fill need for more accurate life-assessment technique that avoids errors in estimated lives and provides for statistical assessment of levels of risk created by engineering decisions in designing system. Implements mathematical model combining techniques of statistics, fatigue, fracture mechanics, nondestructive analysis, life-cycle cost analysis, and management of engine parts. Used to investigate effects of such engine-component life-controlling parameters as return-to-service intervals, stresses, capabilities for nondestructive evaluation, and qualities of materials.

Probabilistic and Possibilistic Analyses of the Strength of a Bonded Joint

NASA Technical Reports Server (NTRS)

Stroud, W. Jefferson; Krishnamurthy, T.; Smith, Steven A.

2001-01-01

The effects of uncertainties on the strength of a single lap shear joint are explained. Probabilistic and possibilistic methods are used to account for uncertainties. Linear and geometrically nonlinear finite element analyses are used in the studies. To evaluate the strength of the joint, fracture in the adhesive and material strength failure in the strap are considered. The study shows that linear analyses yield conservative predictions for failure loads. The possibilistic approach for treating uncertainties appears to be viable for preliminary design, but with several qualifications.

Forecasting risk along a river basin using a probabilistic and deterministic model for environmental risk assessment of effluents through ecotoxicological evaluation and GIS.

PubMed

Gutiérrez, Simón; Fernandez, Carlos; Barata, Carlos; Tarazona, José Vicente

2009-12-20

This work presents a computer model for Risk Assessment of Basins by Ecotoxicological Evaluation (RABETOX). The model is based on whole effluent toxicity testing and water flows along a specific river basin. It is capable of estimating the risk along a river segment using deterministic and probabilistic approaches. The Henares River Basin was selected as a case study to demonstrate the importance of seasonal hydrological variations in Mediterranean regions. As model inputs, two different ecotoxicity tests (the miniaturized Daphnia magna acute test and the D.magna feeding test) were performed on grab samples from 5 waste water treatment plant effluents. Also used as model inputs were flow data from the past 25 years, water velocity measurements and precise distance measurements using Geographical Information Systems (GIS). The model was implemented into a spreadsheet and the results were interpreted and represented using GIS in order to facilitate risk communication. To better understand the bioassays results, the effluents were screened through SPME-GC/MS analysis. The deterministic model, performed each month during one calendar year, showed a significant seasonal variation of risk while revealing that September represents the worst-case scenario with values up to 950 Risk Units. This classifies the entire area of study for the month of September as "sublethal significant risk for standard species". The probabilistic approach using Monte Carlo analysis was performed on 7 different forecast points distributed along the Henares River. A 0% probability of finding "low risk" was found at all forecast points with a more than 50% probability of finding "potential risk for sensitive species". The values obtained through both the deterministic and probabilistic approximations reveal the presence of certain substances, which might be causing sublethal effects in the aquatic species present in the Henares River.

Probabilistic and structural reliability analysis of laminated composite structures based on the IPACS code

NASA Technical Reports Server (NTRS)

Sobel, Larry; Buttitta, Claudio; Suarez, James

1993-01-01

Probabilistic predictions based on the Integrated Probabilistic Assessment of Composite Structures (IPACS) code are presented for the material and structural response of unnotched and notched, 1M6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply, and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is deficient because IPACS did not yet have a progressive failure capability. The paper also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

Reliability, Risk and Cost Trade-Offs for Composite Designs

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Singhal, Surendra N.; Chamis, Christos C.

1996-01-01

Risk and cost trade-offs have been simulated using a probabilistic method. The probabilistic method accounts for all naturally-occurring uncertainties including those in constituent material properties, fabrication variables, structure geometry and loading conditions. The probability density function of first buckling load for a set of uncertain variables is computed. The probabilistic sensitivity factors of uncertain variables to the first buckling load is calculated. The reliability-based cost for a composite fuselage panel is defined and minimized with respect to requisite design parameters. The optimization is achieved by solving a system of nonlinear algebraic equations whose coefficients are functions of probabilistic sensitivity factors. With optimum design parameters such as the mean and coefficient of variation (representing range of scatter) of uncertain variables, the most efficient and economical manufacturing procedure can be selected. In this paper, optimum values of the requisite design parameters for a predetermined cost due to failure occurrence are computationally determined. The results for the fuselage panel analysis show that the higher the cost due to failure occurrence, the smaller the optimum coefficient of variation of fiber modulus (design parameter) in longitudinal direction.

Probabilistic structural analysis of space propulsion system LOX post

NASA Technical Reports Server (NTRS)

Newell, J. F.; Rajagopal, K. R.; Ho, H. W.; Cunniff, J. M.

1990-01-01

The probabilistic structural analysis program NESSUS (Numerical Evaluation of Stochastic Structures Under Stress; Cruse et al., 1988) is applied to characterize the dynamic loading and response of the Space Shuttle main engine (SSME) LOX post. The design and operation of the SSME are reviewed; the LOX post structure is described; and particular attention is given to the generation of composite load spectra, the finite-element model of the LOX post, and the steps in the NESSUS structural analysis. The results are presented in extensive tables and graphs, and it is shown that NESSUS correctly predicts the structural effects of changes in the temperature loading. The probabilistic approach also facilitates (1) damage assessments for a given failure model (based on gas temperature, heat-shield gap, and material properties) and (2) correlation of the gas temperature with operational parameters such as engine thrust.

Elasto-limited plastic analysis of structures for probabilistic conditions

NASA Astrophysics Data System (ADS)

Movahedi Rad, M.

2018-06-01

With applying plastic analysis and design methods, significant saving in material can be obtained. However, as a result of this benefit excessive plastic deformations and large residual displacements might develop, which in turn might lead to unserviceability and collapse of the structure. In this study, for deterministic problem the residual deformation of structures is limited by considering a constraint on the complementary strain energy of the residual forces. For probabilistic problem the constraint for the complementary strain energy of the residual forces is given randomly and critical stresses updated during the iteration. Limit curves are presented for the plastic limit load factors. The results show that these constraints have significant effects on the load factors. The formulations of the deterministic and probabilistic problems lead to mathematical programming which are solved by the use of nonlinear algorithm.

Comparison of one-dimensional probabilistic finite element method with direct numerical simulation of dynamically loaded heterogeneous materials

NASA Astrophysics Data System (ADS)

Robbins, Joshua; Voth, Thomas

2011-06-01

Material response to dynamic loading is often dominated by microstructure such as grain topology, porosity, inclusions, and defects; however, many models rely on assumptions of homogeneity. We use the probabilistic finite element method (WK Liu, IJNME, 1986) to introduce local uncertainty to account for material heterogeneity. The PFEM uses statistical information about the local material response (i.e., its expectation, coefficient of variation, and autocorrelation) drawn from knowledge of the microstructure, single crystal behavior, and direct numerical simulation (DNS) to determine the expectation and covariance of the system response (velocity, strain, stress, etc). This approach is compared to resolved grain-scale simulations of the equivalent system. The microstructures used for the DNS are produced using Monte Carlo simulations of grain growth, and a sufficient number of realizations are computed to ensure a meaningful comparison. Finally, comments are made regarding the suitability of one-dimensional PFEM for modeling material heterogeneity. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Computational Prediction of Shock Ignition Thresholds and Ignition Probability of Polymer-Bonded Explosives

NASA Astrophysics Data System (ADS)

Wei, Yaochi; Kim, Seokpum; Horie, Yasuyuki; Zhou, Min

2017-06-01

A computational approach is developed to predict the probabilistic ignition thresholds of polymer-bonded explosives (PBXs). The simulations explicitly account for microstructure, constituent properties, and interfacial responses and capture processes responsible for the development of hotspots and damage. The specific damage mechanisms considered include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, and heat conduction. The probabilistic analysis uses sets of statistically similar microstructure samples to mimic relevant experiments for statistical variations of material behavior due to inherent material heterogeneities. The ignition thresholds and corresponding ignition probability maps are predicted for PBX 9404 and PBX 9501 for the impact loading regime of Up = 200 --1200 m/s. James and Walker-Wasley relations are utilized to establish explicit analytical expressions for the ignition probability as a function of load intensities. The predicted results are in good agreement with available experimental measurements. The capability to computationally predict the macroscopic response out of material microstructures and basic constituent properties lends itself to the design of new materials and the analysis of existing materials. The authors gratefully acknowledge the support from Air Force Office of Scientific Research (AFOSR) and the Defense Threat Reduction Agency (DTRA).

Quantification and Formalization of Security

DTIC Science & Technology

2010-02-01

Quantification of Information Flow . . . . . . . . . . . . . . . . . . 30 2.4 Language Semantics . . . . . . . . . . . . . . . . . . . . . . . . . . 46...system behavior observed by users holding low clearances. This policy, or a variant of it, is enforced by many pro- gramming language -based mechanisms...illustrates with a particular programming language (while-programs plus probabilistic choice). The model is extended in §2.5 to programs in which

A multipopulation PSO based memetic algorithm for permutation flow shop scheduling.

PubMed

Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP.

A flexible open-source toolkit for lava flow simulations

NASA Astrophysics Data System (ADS)

Mossoux, Sophie; Feltz, Adelin; Poppe, Sam; Canters, Frank; Kervyn, Matthieu

2014-05-01

Lava flow hazard modeling is a useful tool for scientists and stakeholders confronted with imminent or long term hazard from basaltic volcanoes. It can improve their understanding of the spatial distribution of volcanic hazard, influence their land use decisions and improve the city evacuation during a volcanic crisis. Although a range of empirical, stochastic and physically-based lava flow models exists, these models are rarely available or require a large amount of physical constraints. We present a GIS toolkit which models lava flow propagation from one or multiple eruptive vents, defined interactively on a Digital Elevation Model (DEM). It combines existing probabilistic (VORIS) and deterministic (FLOWGO) models in order to improve the simulation of lava flow spatial spread and terminal length. Not only is this toolkit open-source, running in Python, which allows users to adapt the code to their needs, but it also allows users to combine the models included in different ways. The lava flow paths are determined based on the probabilistic steepest slope (VORIS model - Felpeto et al., 2001) which can be constrained in order to favour concentrated or dispersed flow fields. Moreover, the toolkit allows including a corrective factor in order for the lava to overcome small topographical obstacles or pits. The lava flow terminal length can be constrained using a fixed length value, a Gaussian probability density function or can be calculated based on the thermo-rheological properties of the open-channel lava flow (FLOWGO model - Harris and Rowland, 2001). These slope-constrained properties allow estimating the velocity of the flow and its heat losses. The lava flow stops when its velocity is zero or the lava temperature reaches the solidus. Recent lava flows of Karthala volcano (Comoros islands) are here used to demonstrate the quality of lava flow simulations with the toolkit, using a quantitative assessment of the match of the simulation with the real lava flows. The influence of the different input parameters on the quality of the simulations is discussed. REFERENCES: Felpeto et al. (2001), Assessment and modelling of lava flow hazard on Lanzarote (Canary islands), Nat. Hazards, 23, 247-257. Harris and Rowland (2001), FLOWGO: a kinematic thermo-rheological model for lava flowing in a channel, Bull. Volcanol., 63, 20-44.

Development and computer implementation of design/analysis techniques for multilayered composite structures. Probabilistic fiber composite micromechanics. M.S. Thesis, Mar. 1987 Final Report, 1 Sep. 1984 - 1 Oct. 1990

NASA Technical Reports Server (NTRS)

Stock, Thomas A.

1995-01-01

Probabilistic composite micromechanics methods are developed that simulate expected uncertainties in unidirectional fiber composite properties. These methods are in the form of computational procedures using Monte Carlo simulation. The variables in which uncertainties are accounted for include constituent and void volume ratios, constituent elastic properties and strengths, and fiber misalignment. A graphite/epoxy unidirectional composite (ply) is studied to demonstrate fiber composite material property variations induced by random changes expected at the material micro level. Regression results are presented to show the relative correlation between predictor and response variables in the study. These computational procedures make possible a formal description of anticipated random processes at the intraply level, and the related effects of these on composite properties.

Hydro and morphodynamic simulations for probabilistic estimates of munitions mobility

NASA Astrophysics Data System (ADS)

Palmsten, M.; Penko, A.

2017-12-01

Probabilistic estimates of waves, currents, and sediment transport at underwater munitions remediation sites are necessary to constrain probabilistic predictions of munitions exposure, burial, and migration. To address this need, we produced ensemble simulations of hydrodynamic flow and morphologic change with Delft3D, a coupled system of wave, circulation, and sediment transport models. We have set up the Delft3D model simulations at the Army Corps of Engineers Field Research Facility (FRF) in Duck, NC, USA. The FRF is the prototype site for the near-field munitions mobility model, which integrates far-field and near-field field munitions mobility simulations. An extensive array of in-situ and remotely sensed oceanographic, bathymetric, and meteorological data are available at the FRF, as well as existing observations of munitions mobility for model testing. Here, we present results of ensemble Delft3D hydro- and morphodynamic simulations at Duck. A nested Delft3D simulation runs an outer grid that extends 12-km in the along-shore and 3.7-km in the cross-shore with 50-m resolution and a maximum depth of approximately 17-m. The inner nested grid extends 3.2-km in the along-shore and 1.2-km in the cross-shore with 5-m resolution and a maximum depth of approximately 11-m. The inner nested grid initial model bathymetry is defined as the most recent survey or remotely sensed estimate of water depth. Delft3D-WAVE and FLOW is driven with spectral wave measurements from a Waverider buoy in 17-m depth located on the offshore boundary of the outer grid. The spectral wave output and the water levels from the outer grid are used to define the boundary conditions for the inner nested high-resolution grid, in which the coupled Delft3D WAVE-FLOW-MORPHOLOGY model is run. The ensemble results are compared to the wave, current, and bathymetry observations collected at the FRF.

First Volcanological-Probabilistic Pyroclastic Density Current and Fallout Hazard Map for Campi Flegrei and Somma Vesuvius Volcanoes.

NASA Astrophysics Data System (ADS)

Mastrolorenzo, G.; Pappalardo, L.; Troise, C.; Panizza, A.; de Natale, G.

2005-05-01

Integrated volcanological-probabilistic approaches has been used in order to simulate pyroclastic density currents and fallout and produce hazard maps for Campi Flegrei and Somma Vesuvius areas. On the basis of the analyses of all types of pyroclastic flows, surges, secondary pyroclastic density currents and fallout events occurred in the volcanological history of the two volcanic areas and the evaluation of probability for each type of events, matrixs of input parameters for a numerical simulation have been performed. The multi-dimensional input matrixs include the main controlling parameters of the pyroclasts transport and deposition dispersion, as well as the set of possible eruptive vents used in the simulation program. Probabilistic hazard maps provide of each points of campanian area, the yearly probability to be interested by a given event with a given intensity and resulting demage. Probability of a few events in one thousand years are typical of most areas around the volcanoes whitin a range of ca 10 km, including Neaples. Results provide constrains for the emergency plans in Neapolitan area.

Probabilistic Methods for Structural Design and Reliability

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Whitlow, Woodrow, Jr. (Technical Monitor)

2002-01-01

This report describes a formal method to quantify structural damage tolerance and reliability in the presence of a multitude of uncertainties in turbine engine components. The method is based at the material behavior level where primitive variables with their respective scatter ranges are used to describe behavior. Computational simulation is then used to propagate the uncertainties to the structural scale where damage tolerance and reliability are usually specified. Several sample cases are described to illustrate the effectiveness, versatility, and maturity of the method. Typical results from this method demonstrate, that it is mature and that it can be used to probabilistically evaluate turbine engine structural components. It may be inferred from the results that the method is suitable for probabilistically predicting the remaining life in aging or in deteriorating structures, for making strategic projections and plans, and for achieving better, cheaper, faster products that give competitive advantages in world markets.

A Probabilistic Performance Assessment Study of Potential Low-Level Radioactive Waste Disposal Sites in Taiwan

NASA Astrophysics Data System (ADS)

Knowlton, R. G.; Arnold, B. W.; Mattie, P. D.; Kuo, M.; Tien, N.

2006-12-01

For several years now, Taiwan has been engaged in a process to select a low-level radioactive waste (LLW) disposal site. Taiwan is generating LLW from operational and decommissioning wastes associated with nuclear power reactors, as well as research, industrial, and medical radioactive wastes. The preliminary selection process has narrowed the search to four potential candidate sites. These sites are to be evaluated in a performance assessment analysis to determine the likelihood of meeting the regulatory criteria for disposal. Sandia National Laboratories and Taiwan's Institute of Nuclear Energy Research have been working together to develop the necessary performance assessment methodology and associated computer models to perform these analyses. The methodology utilizes both deterministic (e.g., single run) and probabilistic (e.g., multiple statistical realizations) analyses to achieve the goals. The probabilistic approach provides a means of quantitatively evaluating uncertainty in the model predictions and a more robust basis for performing sensitivity analyses to better understand what is driving the dose predictions from the models. Two types of disposal configurations are under consideration: a shallow land burial concept and a cavern disposal concept. The shallow land burial option includes a protective cover to limit infiltration potential to the waste. Both conceptual designs call for the disposal of 55 gallon waste drums within concrete lined trenches or tunnels, and backfilled with grout. Waste emplaced in the drums may be solidified. Both types of sites are underlain or placed within saturated fractured bedrock material. These factors have influenced the conceptual model development of each site, as well as the selection of the models to employ for the performance assessment analyses. Several existing codes were integrated in order to facilitate a comprehensive performance assessment methodology to evaluate the potential disposal sites. First, a need existed to simulate the failure processes of the waste containers, with subsequent leaching of the waste form to the underlying host rock. The Breach, Leach, and Transport Multiple Species (BLT-MS) code was selected to meet these needs. BLT-MS also has a 2-D finite-element advective-dispersive transport module, with radionuclide in-growth and decay. BLT-MS does not solve the groundwater flow equation, but instead requires the input of Darcy flow velocity terms. These terms were abstracted from a groundwater flow model using the FEHM code. For the shallow land burial site, the HELP code was also used to evaluate the performance of the protective cover. The GoldSim code was used for two purposes: quantifying uncertainties in the predictions, and providing a platform to evaluate an alternative conceptual model involving matrix-diffusion transport. Results of the preliminary performance assessment analyses using examples to illustrate the computational framework will be presented. Sandia National Laboratories is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE AC04 94AL85000.

Theory, methods and tools for determining environmental flows for riparian vegetation: Riparian vegetation-flow response guilds

USGS Publications Warehouse

Merritt, D.M.; Scott, M.L.; Leroy, Poff N.; Auble, G.T.; Lytle, D.A.

2010-01-01

Riparian vegetation composition, structure and abundance are governed to a large degree by river flow regime and flow-mediated fluvial processes. Streamflow regime exerts selective pressures on riparian vegetation, resulting in adaptations (trait syndromes) to specific flow attributes. Widespread modification of flow regimes by humans has resulted in extensive alteration of riparian vegetation communities. Some of the negative effects of altered flow regimes on vegetation may be reversed by restoring components of the natural flow regime. 2. Models have been developed that quantitatively relate components of the flow regime to attributes of riparian vegetation at the individual, population and community levels. Predictive models range from simple statistical relationships, to more complex stochastic matrix population models and dynamic simulation models. Of the dozens of predictive models reviewed here, most treat one or a few species, have many simplifying assumptions such as stable channel form, and do not specify the time-scale of response. In many cases, these models are very effective in developing alternative streamflow management plans for specific river reaches or segments but are not directly transferable to other rivers or other regions. 3. A primary goal in riparian ecology is to develop general frameworks for prediction of vegetation response to changing environmental conditions. The development of riparian vegetation-flow response guilds offers a framework for transferring information from rivers where flow standards have been developed to maintain desirable vegetation attributes, to rivers with little or no existing information. 4. We propose to organise riparian plants into non-phylogenetic groupings of species with shared traits that are related to components of hydrologic regime: life history, reproductive strategy, morphology, adaptations to fluvial disturbance and adaptations to water availability. Plants from any river or region may be grouped into these guilds and related to hydrologic attributes of a specific class of river using probabilistic response curves. 5. Probabilistic models based on riparian response guilds enable prediction of the likelihood of change in each of the response guilds given projected changes in flow, and facilitate examination of trade-offs and risks associated with various flow management strategies. Riparian response guilds can be decomposed to the species level for individual projects or used to develop flow management guidelines for regional water management plans. ?? 2009 Published.

Integration of NASA-Developed Lifing Technology for PM Alloys into DARWIN (registered trademark)

NASA Technical Reports Server (NTRS)

McClung, R. Craig; Enright, Michael P.; Liang, Wuwei

2011-01-01

In recent years, Southwest Research Institute (SwRI) and NASA Glenn Research Center (GRC) have worked independently on the development of probabilistic life prediction methods for materials used in gas turbine engine rotors. The two organizations have addressed different but complementary technical challenges. This report summarizes a brief investigation into the current status of the relevant technology at SwRI and GRC with a view towards a future integration of methods and models developed by GRC for probabilistic lifing of powder metallurgy (P/M) nickel turbine rotor alloys into the DARWIN (Darwin Corporation) software developed by SwRI.

Bayesian Modeling of Perceived Surface Slant from Actively-Generated and Passively-Observed Optic Flow

PubMed Central

Caudek, Corrado; Fantoni, Carlo; Domini, Fulvio

2011-01-01

We measured perceived depth from the optic flow (a) when showing a stationary physical or virtual object to observers who moved their head at a normal or slower speed, and (b) when simulating the same optic flow on a computer and presenting it to stationary observers. Our results show that perceived surface slant is systematically distorted, for both the active and the passive viewing of physical or virtual surfaces. These distortions are modulated by head translation speed, with perceived slant increasing directly with the local velocity gradient of the optic flow. This empirical result allows us to determine the relative merits of two alternative approaches aimed at explaining perceived surface slant in active vision: an “inverse optics” model that takes head motion information into account, and a probabilistic model that ignores extra-retinal signals. We compare these two approaches within the framework of the Bayesian theory. The “inverse optics” Bayesian model produces veridical slant estimates if the optic flow and the head translation velocity are measured with no error; because of the influence of a “prior” for flatness, the slant estimates become systematically biased as the measurement errors increase. The Bayesian model, which ignores the observer's motion, always produces distorted estimates of surface slant. Interestingly, the predictions of this second model, not those of the first one, are consistent with our empirical findings. The present results suggest that (a) in active vision perceived surface slant may be the product of probabilistic processes which do not guarantee the correct solution, and (b) extra-retinal signals may be mainly used for a better measurement of retinal information. PMID:21533197

Carbon dioxide fluid-flow modeling and injectivity calculations

USGS Publications Warehouse

Burke, Lauri

2011-01-01

These results were used to classify subsurface formations into three permeability classifications for the probabilistic calculations of storage efficiency and containment risk of the U.S. Geological Survey geologic carbon sequestration assessment methodology. This methodology is currently in use to determine the total carbon dioxide containment capacity of the onshore and State waters areas of the United States.

A probabilistic approach to modeling postfire erosion after the 2009 Australian bushfires

Treesearch

P. R. Robichaud; W. J. Elliot; F. B. Pierson; D. E. Hall; C. A. Moffet

2009-01-01

Major concerns after bushfires and wildfires include increased flooding, erosion and debris flows due to loss of the protective forest floor layer, loss of water storage, and creation of water repellent soil conditions. To assist postfire assessment teams in their efforts to evaluate fire effects and make postfire treatment decisions, a web-based Erosion Risk...

Probabilistic analysis of preload in the abutment screw of a dental implant complex.

PubMed

Guda, Teja; Ross, Thomas A; Lang, Lisa A; Millwater, Harry R

2008-09-01

Screw loosening is a problem for a percentage of implants. A probabilistic analysis to determine the cumulative probability distribution of the preload, the probability of obtaining an optimal preload, and the probabilistic sensitivities identifying important variables is lacking. The purpose of this study was to examine the inherent variability of material properties, surface interactions, and applied torque in an implant system to determine the probability of obtaining desired preload values and to identify the significant variables that affect the preload. Using software programs, an abutment screw was subjected to a tightening torque and the preload was determined from finite element (FE) analysis. The FE model was integrated with probabilistic analysis software. Two probabilistic analysis methods (advanced mean value and Monte Carlo sampling) were applied to determine the cumulative distribution function (CDF) of preload. The coefficient of friction, elastic moduli, Poisson's ratios, and applied torque were modeled as random variables and defined by probability distributions. Separate probability distributions were determined for the coefficient of friction in well-lubricated and dry environments. The probabilistic analyses were performed and the cumulative distribution of preload was determined for each environment. A distinct difference was seen between the preload probability distributions generated in a dry environment (normal distribution, mean (SD): 347 (61.9) N) compared to a well-lubricated environment (normal distribution, mean (SD): 616 (92.2) N). The probability of obtaining a preload value within the target range was approximately 54% for the well-lubricated environment and only 0.02% for the dry environment. The preload is predominately affected by the applied torque and coefficient of friction between the screw threads and implant bore at lower and middle values of the preload CDF, and by the applied torque and the elastic modulus of the abutment screw at high values of the preload CDF. Lubrication at the threaded surfaces between the abutment screw and implant bore affects the preload developed in the implant complex. For the well-lubricated surfaces, only approximately 50% of implants will have preload values within the generally accepted range. This probability can be improved by applying a higher torque than normally recommended or a more closely controlled torque than typically achieved. It is also suggested that materials with higher elastic moduli be used in the manufacture of the abutment screw to achieve a higher preload.

Comparison and validation of shallow landslides susceptibility maps generated by bi-variate and multi-variate linear probabilistic GIS-based techniques. A case study from Ribeira Quente Valley (S. Miguel Island, Azores)

NASA Astrophysics Data System (ADS)

Marques, R.; Amaral, P.; Zêzere, J. L.; Queiroz, G.; Goulart, C.

2009-04-01

Slope instability research and susceptibility mapping is a fundamental component of hazard assessment and is of extreme importance for risk mitigation, land-use management and emergency planning. Landslide susceptibility zonation has been actively pursued during the last two decades and several methodologies are still being improved. Among all the methods presented in the literature, indirect quantitative probabilistic methods have been extensively used. In this work different linear probabilistic methods, both bi-variate and multi-variate (Informative Value, Fuzzy Logic, Weights of Evidence and Logistic Regression), were used for the computation of the spatial probability of landslide occurrence, using the pixel as mapping unit. The methods used are based on linear relationships between landslides and 9 considered conditioning factors (altimetry, slope angle, exposition, curvature, distance to streams, wetness index, contribution area, lithology and land-use). It was assumed that future landslides will be conditioned by the same factors as past landslides in the study area. The presented work was developed for Ribeira Quente Valley (S. Miguel Island, Azores), a study area of 9,5 km2, mainly composed of volcanic deposits (ash and pumice lapilli) produced by explosive eruptions in Furnas Volcano. This materials associated to the steepness of the slopes (38,9% of the area has slope angles higher than 35°, reaching a maximum of 87,5°), make the area very prone to landslide activity. A total of 1.495 shallow landslides were mapped (at 1:5.000 scale) and included in a GIS database. The total affected area is 401.744 m2 (4,5% of the study area). Most slope movements are translational slides frequently evolving into debris-flows. The landslides are elongated, with maximum length generally equivalent to the slope extent, and their width normally does not exceed 25 m. The failure depth rarely exceeds 1,5 m and the volume is usually smaller than 700 m3. For modelling purposes, the landslides were randomly divided in two sub-datasets: a modelling dataset with 748 events (2,2% of the study area) and a validation dataset with 747 events (2,3% of the study area). The susceptibility algorithms achieved with the different probabilistic techniques, were rated individually using success rate and prediction rate curves. The best model performance was obtained with the logistic regression, although the results from the different methods do not show significant differences neither in success nor in prediction rate curves. These evidences revealed that: (1) the modelling landslide dataset is representative of the entire landslide population characteristics; and (2) the increase of complexity and robustness in the probabilistic methodology did not produce a significant increase in success or prediction rates. Therefore, it was concluded that the resolution and quality of the input variables are much more important than the probabilistic model chosen to assess landslide susceptibility. This work was developed on the behalf of VOLCSOILRISK project (Volcanic Soils Geotechnical Characterization for Landslide Risk Mitigation), supported by Direcção Regional da Ciência e Tecnologia - Governo Regional dos Açores.

A Probabilistic Design Method Applied to Smart Composite Structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1995-01-01

A probabilistic design method is described and demonstrated using a smart composite wing. Probabilistic structural design incorporates naturally occurring uncertainties including those in constituent (fiber/matrix) material properties, fabrication variables, structure geometry and control-related parameters. Probabilistic sensitivity factors are computed to identify those parameters that have a great influence on a specific structural reliability. Two performance criteria are used to demonstrate this design methodology. The first criterion requires that the actuated angle at the wing tip be bounded by upper and lower limits at a specified reliability. The second criterion requires that the probability of ply damage due to random impact load be smaller than an assigned value. When the relationship between reliability improvement and the sensitivity factors is assessed, the results show that a reduction in the scatter of the random variable with the largest sensitivity factor (absolute value) provides the lowest failure probability. An increase in the mean of the random variable with a negative sensitivity factor will reduce the failure probability. Therefore, the design can be improved by controlling or selecting distribution parameters associated with random variables. This can be implemented during the manufacturing process to obtain maximum benefit with minimum alterations.

A probabilistic analysis of silicon cost

NASA Technical Reports Server (NTRS)

Reiter, L. J.

1983-01-01

Silicon materials costs represent both a cost driver and an area where improvement can be made in the manufacture of photovoltaic modules. The cost from three processes for the production of low-cost silicon being developed under the U.S. Department of Energy's (DOE) National Photovoltaic Program is analyzed. The approach is based on probabilistic inputs and makes use of two models developed at the Jet Propulsion Laboratory: SIMRAND (SIMulation of Research ANd Development) and IPEG (Improved Price Estimating Guidelines). The approach, assumptions, and limitations are detailed along with a verification of the cost analyses methodology. Results, presented in the form of cumulative probability distributions for silicon cost, indicate that there is a 55% chance of reaching the DOE target of $16/kg for silicon material. This is a technically achievable cost based on expert forecasts of the results of ongoing research and development and do not imply any market prices for a given year.

CARES/Life Software for Designing More Reliable Ceramic Parts

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.; Powers, Lynn M.; Baker, Eric H.

1997-01-01

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion, and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CAPES/Life software eases this task by providing a tool to optimize the design and manufacture of brittle material components using probabilistic reliability analysis techniques. Probabilistic component design involves predicting the probability of failure for a thermomechanically loaded component from specimen rupture data. Typically, these experiments are performed using many simple geometry flexural or tensile test specimens. A static, dynamic, or cyclic load is applied to each specimen until fracture. Statistical strength and SCG (fatigue) parameters are then determined from these data. Using these parameters and the results obtained from a finite element analysis, the time-dependent reliability for a complex component geometry and loading is then predicted. Appropriate design changes are made until an acceptable probability of failure has been reached.

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for deposited material and external doses. Volume 2: Appendices

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

Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M.

1997-12-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library ofmore » uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA deposited material and external dose models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on deposited material and external doses, (4) short biographies of the experts, and (5) the aggregated results of their responses.« less

Probabilistic Analysis of a SiC/SiC Ceramic Matrix Composite Turbine Vane

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Nemeth, Noel N.; Brewer, David N.; Mital, Subodh

2004-01-01

To demonstrate the advanced composite materials technology under development within the Ultra-Efficient Engine Technology (UEET) Program, it was planned to fabricate, test, and analyze a turbine vane made entirely of silicon carbide-fiber-reinforced silicon carbide matrix composite (SiC/SiC CMC) material. The objective was to utilize a five-harness satin weave melt-infiltrated (MI) SiC/SiC composite material developed under this program to design and fabricate a stator vane that can endure 1000 hours of engine service conditions. The vane was designed such that the expected maximum stresses were kept within the proportional limit strength of the material. Any violation of this design requirement was considered as the failure. This report presents results of a probabilistic analysis and reliability assessment of the vane. Probability of failure to meet the design requirements was computed. In the analysis, material properties, strength, and pressure loading were considered as random variables. The pressure loads were considered normally distributed with a nominal variation. A temperature profile on the vane was obtained by performing a computational fluid dynamics (CFD) analysis and was assumed to be deterministic. The results suggest that for the current vane design, the chance of not meeting design requirements is about 1.6 percent.

A probabilistic damage model of stress-induced permeability anisotropy during cataclastic flow

NASA Astrophysics Data System (ADS)

Zhu, Wenlu; MontéSi, Laurent G. J.; Wong, Teng-Fong

2007-10-01

A fundamental understanding of the effect of stress on permeability evolution is important for many fault mechanics and reservoir engineering problems. Recent laboratory measurements demonstrate that in the cataclastic flow regime, the stress-induced anisotropic reduction of permeability in porous rocks can be separated into 3 different stages. In the elastic regime (stage I), permeability and porosity reduction are solely controlled by the effective mean stress, with negligible permeability anisotropy. Stage II starts at the onset of shear-enhanced compaction, when a critical yield stress is attained. In stage II, the deviatoric stress exerts primary control over permeability and porosity evolution. The increase in deviatoric stress results in drastic permeability and porosity reduction and considerable permeability anisotropy. The transition from stage II to stage III takes place progressively during the development of pervasive cataclastic flow. In stage III, permeability and porosity reduction becomes gradual again, and permeability anisotropy diminishes. Microstructural observations on deformed samples using laser confocal microscopy reveal that stress-induced microcracking and pore collapse are the primary forms of damage during cataclastic flow. A probabilistic damage model is formulated to characterize the effects of stress on permeability and its anisotropy. In our model, the effects of both effective mean stress and differential stress on permeability evolution are calculated. By introducing stress sensitivity coefficients, we propose a first-order description of the dependence of permeability evolution on different loading paths. Built upon the micromechanisms of deformation in porous rocks, this unified model provides new insight into the coupling of stress and permeability.

A probabilistic approach to quantifying hydrologic thresholds regulating migration of adult Atlantic salmon into spawning streams

NASA Astrophysics Data System (ADS)

Lazzaro, G.; Soulsby, C.; Tetzlaff, D.; Botter, G.

2017-03-01

Atlantic salmon is an economically and ecologically important fish species, whose survival is dependent on successful spawning in headwater rivers. Streamflow dynamics often have a strong control on spawning because fish require sufficiently high discharges to move upriver and enter spawning streams. However, these streamflow effects are modulated by biological factors such as the number and the timing of returning fish in relation to the annual spawning window in the fall/winter. In this paper, we develop and apply a novel probabilistic approach to quantify these interactions using a parsimonious outflux-influx model linking the number of female salmon emigrating (i.e., outflux) and returning (i.e., influx) to a spawning stream in Scotland. The model explicitly accounts for the interannual variability of the hydrologic regime and the hydrological connectivity of spawning streams to main rivers. Model results are evaluated against a detailed long-term (40 years) hydroecological data set that includes annual fluxes of salmon, allowing us to explicitly assess the role of discharge variability. The satisfactory model results show quantitatively that hydrologic variability contributes to the observed dynamics of salmon returns, with a good correlation between the positive (negative) peaks in the immigration data set and the exceedance (nonexceedance) probability of a threshold flow (0.3 m3/s). Importantly, model performance deteriorates when the interannual variability of flow regime is disregarded. The analysis suggests that flow thresholds and hydrological connectivity for spawning return represent a quantifiable and predictable feature of salmon rivers, which may be helpful in decision making where flow regimes are altered by water abstractions.

Prediction of shock initiation thresholds and ignition probability of polymer-bonded explosives using mesoscale simulations

NASA Astrophysics Data System (ADS)

Kim, Seokpum; Wei, Yaochi; Horie, Yasuyuki; Zhou, Min

2018-05-01

The design of new materials requires establishment of macroscopic measures of material performance as functions of microstructure. Traditionally, this process has been an empirical endeavor. An approach to computationally predict the probabilistic ignition thresholds of polymer-bonded explosives (PBXs) using mesoscale simulations is developed. The simulations explicitly account for microstructure, constituent properties, and interfacial responses and capture processes responsible for the development of hotspots and damage. The specific mechanisms tracked include viscoelasticity, viscoplasticity, fracture, post-fracture contact, frictional heating, and heat conduction. The probabilistic analysis uses sets of statistically similar microstructure samples to directly mimic relevant experiments for quantification of statistical variations of material behavior due to inherent material heterogeneities. The particular thresholds and ignition probabilities predicted are expressed in James type and Walker-Wasley type relations, leading to the establishment of explicit analytical expressions for the ignition probability as function of loading. Specifically, the ignition thresholds corresponding to any given level of ignition probability and ignition probability maps are predicted for PBX 9404 for the loading regime of Up = 200-1200 m/s where Up is the particle speed. The predicted results are in good agreement with available experimental measurements. A parametric study also shows that binder properties can significantly affect the macroscopic ignition behavior of PBXs. The capability to computationally predict the macroscopic engineering material response relations out of material microstructures and basic constituent and interfacial properties lends itself to the design of new materials as well as the analysis of existing materials.

Probabilistic Modeling of Settlement Risk at Land Disposal Facilities - 12304

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

Foye, Kevin C.; Soong, Te-Yang

2012-07-01

The long-term reliability of land disposal facility final cover systems - and therefore the overall waste containment - depends on the distortions imposed on these systems by differential settlement/subsidence. The evaluation of differential settlement is challenging because of the heterogeneity of the waste mass (caused by inconsistent compaction, void space distribution, debris-soil mix ratio, waste material stiffness, time-dependent primary compression of the fine-grained soil matrix, long-term creep settlement of the soil matrix and the debris, etc.) at most land disposal facilities. Deterministic approaches to long-term final cover settlement prediction are not able to capture the spatial variability in the wastemore » mass and sub-grade properties which control differential settlement. An alternative, probabilistic solution is to use random fields to model the waste and sub-grade properties. The modeling effort informs the design, construction, operation, and maintenance of land disposal facilities. A probabilistic method to establish design criteria for waste placement and compaction is introduced using the model. Random fields are ideally suited to problems of differential settlement modeling of highly heterogeneous foundations, such as waste. Random fields model the seemingly random spatial distribution of a design parameter, such as compressibility. When used for design, the use of these models prompts the need for probabilistic design criteria. It also allows for a statistical approach to waste placement acceptance criteria. An example design evaluation was performed, illustrating the use of the probabilistic differential settlement simulation methodology to assemble a design guidance chart. The purpose of this design evaluation is to enable the designer to select optimal initial combinations of design slopes and quality control acceptance criteria that yield an acceptable proportion of post-settlement slopes meeting some design minimum. For this specific example, relative density, which can be determined through field measurements, was selected as the field quality control parameter for waste placement. This technique can be extended to include a rigorous performance-based methodology using other parameters (void space criteria, debris-soil mix ratio, pre-loading, etc.). As shown in this example, each parameter range, or sets of parameter ranges can be selected such that they can result in an acceptable, long-term differential settlement according to the probabilistic model. The methodology can also be used to re-evaluate the long-term differential settlement behavior at closed land disposal facilities to identify, if any, problematic facilities so that remedial action (e.g., reinforcement of upper and intermediate waste layers) can be implemented. Considering the inherent spatial variability in waste and earth materials and the need for engineers to apply sound quantitative practices to engineering analysis, it is important to apply the available probabilistic techniques to problems of differential settlement. One such method to implement probability-based differential settlement analyses for the design of landfill final covers has been presented. The design evaluation technique presented is one tool to bridge the gap from deterministic practice to probabilistic practice. (authors)« less

Impact of Probabilistic Weather on Flight Routing Decisions

NASA Technical Reports Server (NTRS)

Sheth, Kapil; Sridhar, Banavar; Mulfinger, Daniel

2006-01-01

Flight delays in the United States have been found to increase year after year, along with the increase in air traffic. During the four-month period from May through August of 2005, weather related delays accounted for roughly 70% of all reported delays, The current weather prediction in tactical (within 2 hours) timeframe is at manageable levels, however, the state of forecasting weather for strategic (2-6 hours) timeframe is still not dependable for long-term planning. In the absence of reliable severe weather forecasts, the decision-making for flights longer than two hours is challenging. This paper deals with an approach of using probabilistic weather prediction for Traffic Flow Management use, and a general method using this prediction for estimating expected values of flight length and delays in the National Airspace System (NAS). The current state-of-the-art convective weather forecasting is employed to aid the decision makers in arriving at decisions for traffic flow and flight planing. The six-agency effort working on the Next Generation Air Transportation System (NGATS) have considered weather-assimilated decision-making as one of the principal foci out of a list of eight. The weather Integrated Product Team has considered integrated weather information and improved aviation weather forecasts as two of the main efforts (Ref. 1, 2). Recently, research has focused on the concept of operations for strategic traffic flow management (Ref. 3) and how weather data can be integrated for improved decision-making for efficient traffic management initiatives (Ref. 4, 5). An overview of the weather data needs and benefits of various participants in the air traffic system along with available products can be found in Ref. 6. Previous work related to use of weather data in identifying and categorizing pilot intrusions into severe weather regions (Ref. 7, 8) has demonstrated a need for better forecasting in the strategic planning timeframes and moving towards a probabilistic description of weather (Ref. 9). This paper focuses on. specified probability in a local region for flight intrusion/deviation decision-making. The process uses a probabilistic weather description, implements that in a air traffic assessment system to study trajectories of aircraft crossing a cut-off probability contour. This value would be useful for meteorologists in creating optimum distribution profiles for severe weather, Once available, the expected values of flight path and aggregate delays are calculated for efficient operations. The current research, however, does not deal with the issue of multiple cell encounters, as well as echo tops, and will be a topic of future work.

PROBABILISTIC CHARACTERIZATION OF ATMOSPHERIC TRANSPORT AND DISPERSION

EPA Science Inventory

Dispersion models are used to assess the possible extent and severity of accidental or terrorist releases of toxic materials. Most operational models only provide a characterization of average concentrations and conditions following a release. Knowledge of the variability about...

Probabilistic Sizing and Verification of Space Ceramic Structures

NASA Astrophysics Data System (ADS)

Denaux, David; Ballhause, Dirk; Logut, Daniel; Lucarelli, Stefano; Coe, Graham; Laine, Benoit

2012-07-01

Sizing of ceramic parts is best optimised using a probabilistic approach which takes into account the preexisting flaw distribution in the ceramic part to compute a probability of failure of the part depending on the applied load, instead of a maximum allowable load as for a metallic part. This requires extensive knowledge of the material itself but also an accurate control of the manufacturing process. In the end, risk reduction approaches such as proof testing may be used to lower the final probability of failure of the part. Sizing and verification of ceramic space structures have been performed by Astrium for more than 15 years, both with Zerodur and SiC: Silex telescope structure, Seviri primary mirror, Herschel telescope, Formosat-2 instrument, and other ceramic structures flying today. Throughout this period of time, Astrium has investigated and developed experimental ceramic analysis tools based on the Weibull probabilistic approach. In the scope of the ESA/ESTEC study: “Mechanical Design and Verification Methodologies for Ceramic Structures”, which is to be concluded in the beginning of 2012, existing theories, technical state-of-the-art from international experts, and Astrium experience with probabilistic analysis tools have been synthesized into a comprehensive sizing and verification method for ceramics. Both classical deterministic and more optimised probabilistic methods are available, depending on the criticality of the item and on optimisation needs. The methodology, based on proven theory, has been successfully applied to demonstration cases and has shown its practical feasibility.

A Model of Network Porosity

DTIC Science & Technology

2016-11-09

the model does not become a full probabilistic attack graph analysis of the network , whose data requirements are currently unrealistic. The second...flow. – Untrustworthy persons may intentionally try to exfiltrate known sensitive data to ex- ternal networks . People may also unintentionally leak...section will provide details on the components, procedures, data requirements, and parameters required to instantiate the network porosity model. These

A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

PubMed Central

Liu, Ruochen; Ma, Chenlin; Ma, Wenping; Li, Yangyang

2013-01-01

The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem. In this paper, a multipopulation particle swarm optimization (PSO) based memetic algorithm (MPSOMA) is proposed in this paper. In the proposed algorithm, the whole particle swarm population is divided into three subpopulations in which each particle evolves itself by the standard PSO and then updates each subpopulation by using different local search schemes such as variable neighborhood search (VNS) and individual improvement scheme (IIS). Then, the best particle of each subpopulation is selected to construct a probabilistic model by using estimation of distribution algorithm (EDA) and three particles are sampled from the probabilistic model to update the worst individual in each subpopulation. The best particle in the entire particle swarm is used to update the global optimal solution. The proposed MPSOMA is compared with two recently proposed algorithms, namely, PSO based memetic algorithm (PSOMA) and hybrid particle swarm optimization with estimation of distribution algorithm (PSOEDA), on 29 well-known PFFSPs taken from OR-library, and the experimental results show that it is an effective approach for the PFFSP. PMID:24453841

Estimate Tsunami Flow Conditions and Large-Debris Tracks for the Design of Coastal Infrastructures along Coastlines of the U.S. Pacific Northwest

NASA Astrophysics Data System (ADS)

Wei, Y.; Thomas, S.; Zhou, H.; Arcas, D.; Titov, V. V.

2017-12-01

The increasing potential tsunami hazards pose great challenges for infrastructures along the coastlines of the U.S. Pacific Northwest. Tsunami impact at a coastal site is usually assessed from deterministic scenarios based on 10,000 years of geological records in the Cascadia Subduction Zone (CSZ). Aside from these deterministic methods, the new ASCE 7-16 tsunami provisions provide engineering design criteria of tsunami loads on buildings based on a probabilistic approach. This work develops a site-specific model near Newport, OR using high-resolution grids, and compute tsunami inundation depth and velocities at the study site resulted from credible probabilistic and deterministic earthquake sources in the Cascadia Subduction Zone. Three Cascadia scenarios, two deterministic scenarios, XXL1 and L1, and a 2,500-yr probabilistic scenario compliant with the new ASCE 7-16 standard, are simulated using combination of a depth-averaged shallow water model for offshore propagation and a Boussinesq-type model for onshore inundation. We speculate on the methods and procedure to obtain the 2,500-year probabilistic scenario for Newport that is compliant with the ASCE 7-16 tsunami provisions. We provide details of model results, particularly the inundation depth and flow speed for a new building, which will also be designated as a tsunami vertical evacuation shelter, at Newport, Oregon. We show that the ASCE 7-16 consistent hazards are between those obtained from deterministic L1 and XXL1 scenarios, and the greatest impact on the building may come from later waves. As a further step, we utilize the inundation model results to numerically compute tracks of large vessels in the vicinity of the building site and estimate if these vessels will impact on the building site during the extreme XXL1 and ASCE 7-16 hazard-consistent scenarios. Two-step study is carried out first to study tracks of massless particles and then large vessels with assigned mass considering drag force, inertial force, ship grounding and mooring. The simulation results show that none of the large vessels will impact on the building site in all tested scenarios.

Probabilistic structural analysis of a truss typical for space station

NASA Technical Reports Server (NTRS)

Pai, Shantaram S.

1990-01-01

A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.

Probabilistic Analysis of Structural Member from Recycled Aggregate Concrete

NASA Astrophysics Data System (ADS)

Broukalová, I.; Šeps, K.

2017-09-01

The paper aims at the topic of sustainable building concerning recycling of waste rubble concrete from demolition. Considering demands of maximising recycled aggregate use and minimising of cement consumption, composite from recycled concrete aggregate was proposed. The objective of the presented investigations was to verify feasibility of the recycled aggregate cement based fibre reinforced composite in a structural member. Reliability of wall from recycled aggregate fibre reinforced composite was assessed in a probabilistic analysis of a load-bearing capacity of the wall. The applicability of recycled aggregate fibre reinforced concrete in structural applications was demonstrated. The outcomes refer to issue of high scatter of material parameters of recycled aggregate concretes.

Transient flow conditions change how we should think about WHPA delineation: a joint frequency and probability analysis

NASA Astrophysics Data System (ADS)

Rodriguez Pretelin (1), Abelardo; Nowak (1), Wolfgang

2017-04-01

Well head protection areas (WHPAs) are frequently used as safety measures for drinking water wells, preventing them from being polluted by restricting land use activities in their proximities. Two sources of uncertainty are involved during delineation: 1) uncertainty in aquifer parameters and 2) time-varying groundwater flow scenarios and their own inherent uncertainties. The former has been studied by Enzenhoefer et al (2012 [1] and 2014 [2]) as probabilistic risk version of WHPA delineation. The latter is frequently neglected and replaced by steady-state assumptions; thereby ignoring time-variant flow conditions triggered either by anthropogenic causes or climatic conditions. In this study we analyze the influence of transient flow considerations in WHPA delineation, following annual seasonality behavior; with transiency represented by four transient conditions: (I) regional groundwater flow direction, (II) strength of the regional hydraulic gradient, (III) natural recharge to the groundwater and (IV) pumping rate. Addressing WHPA delineation in transient flow scenarios is computationally expensive. Thus, we develop an efficient method using a dynamic superposition of steady-state flow solutions coupled with a reversed formulation of advective-dispersive transport based on a Lagrangian particle tracking with continuous injection. This analysis results in a time-frequency map of pixel-wise membership to the well catchment. Additional to transient flow conditions, we recognize two sources of uncertainty, inexact knowledge of transient drivers and parameters. The uncertainties are accommodated through Monte Carlo simulation. With the help of a global sensitivity analysis, we investigate the impact of transiency in WHPA solutions. In particular, we evaluate: (1) Among all considered transients, which ones are the most influential. (2) How influential in WHPA delineation is the transience-related uncertainty compared to aquifer parameter uncertainty. Literature [1] R. Enzenhoefer, W. Nowak, and R. Helmig. Probabilistic exposure risk assessment with advective-dispersive well vulnerability criteria. Advances in Water Resources, 36:121-132, 2012. [2] R. Enzenhoefer, T. Bunk, and W. Nowak. Nine steps to risk-informed wellhead protection and management: a case study. Ground water, 52:161-174, 2014.

Probabilistic Assessment of a CMC Turbine Vane

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Brewer, Dave; Mital, Subodh K.

2004-01-01

In order to demonstrate the advanced CMC technology under development within the Ultra Efficient Engine Technology (UEET) program, it has been planned to fabricate, test and analyze an all CMC turbine vane made of a SiC/SiC composite material. The objective was to utilize a 5-II Satin Weave SiC/CVI SiC/ and MI SiC matrix material that was developed in-house under the Enabling Propulsion Materials (EPM) program, to design and fabricate a stator vane that can endure successfully 1000 hours of engine service conditions operation. The design requirements for the vane are to be able to withstand a maximum of 2400 F within the substrate and the hot surface temperature of 2700 F with the aid of an in-house developed Environmental/Thermal Barrier Coating (EBC/TBC) system. The vane will be tested in a High Pressure Burner Rig at NASA Glenn Research Center facility. This rig is capable of simulating the engine service environment. The present paper focuses on a probabilistic assessment of the vane. The material stress/strain relationship shows a bilinear behavior with a distinct knee corresponding to what is often termed as first matrix cracking strength. This is a critical life limiting consideration for these materials. The vane is therefore designed such that the maximum stresses are within this limit so that the structure is never subjected to loads beyond the first matrix cracking strength. Any violation of this design requirement is considered as failure. Probabilistic analysis is performed in order to determine the probability of failure based on this assumption. In the analysis, material properties, strength, and pressures are considered random variables. The variations in properties and strength are based on the actual experimental data generated in house. The mean values for the pressures on the upper surface and the lower surface are known but their distributions are unknown. In the present analysis the pressures are considered normally distributed with a nominal variation. Temperature profile on the vane is obtained by performing a CFD analysis and is assumed to be deterministic.

Reliability of a Parallel Pipe Network

NASA Technical Reports Server (NTRS)

Herrera, Edgar; Chamis, Christopher (Technical Monitor)

2001-01-01

The goal of this NASA-funded research is to advance research and education objectives in theoretical and computational probabilistic structural analysis, reliability, and life prediction methods for improved aerospace and aircraft propulsion system components. Reliability methods are used to quantify response uncertainties due to inherent uncertainties in design variables. In this report, several reliability methods are applied to a parallel pipe network. The observed responses are the head delivered by a main pump and the head values of two parallel lines at certain flow rates. The probability that the flow rates in the lines will be less than their specified minimums will be discussed.

Predictability of short-range forecasting: a multimodel approach

NASA Astrophysics Data System (ADS)

García-Moya, Jose-Antonio; Callado, Alfons; Escribà, Pau; Santos, Carlos; Santos-Muñoz, Daniel; Simarro, Juan

2011-05-01

Numerical weather prediction (NWP) models (including mesoscale) have limitations when it comes to dealing with severe weather events because extreme weather is highly unpredictable, even in the short range. A probabilistic forecast based on an ensemble of slightly different model runs may help to address this issue. Among other ensemble techniques, Multimodel ensemble prediction systems (EPSs) are proving to be useful for adding probabilistic value to mesoscale deterministic models. A Multimodel Short Range Ensemble Prediction System (SREPS) focused on forecasting the weather up to 72 h has been developed at the Spanish Meteorological Service (AEMET). The system uses five different limited area models (LAMs), namely HIRLAM (HIRLAM Consortium), HRM (DWD), the UM (UKMO), MM5 (PSU/NCAR) and COSMO (COSMO Consortium). These models run with initial and boundary conditions provided by five different global deterministic models, namely IFS (ECMWF), UM (UKMO), GME (DWD), GFS (NCEP) and CMC (MSC). AEMET-SREPS (AE) validation on the large-scale flow, using ECMWF analysis, shows a consistent and slightly underdispersive system. For surface parameters, the system shows high skill forecasting binary events. 24-h precipitation probabilistic forecasts are verified using an up-scaling grid of observations from European high-resolution precipitation networks, and compared with ECMWF-EPS (EC).

Variational approach to probabilistic finite elements

NASA Technical Reports Server (NTRS)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1991-01-01

Probabilistic finite element methods (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Variational approach to probabilistic finite elements

NASA Astrophysics Data System (ADS)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1991-08-01

Probabilistic finite element methods (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Variational approach to probabilistic finite elements

NASA Technical Reports Server (NTRS)

Belytschko, T.; Liu, W. K.; Mani, A.; Besterfield, G.

1987-01-01

Probabilistic finite element method (PFEM), synthesizing the power of finite element methods with second-moment techniques, are formulated for various classes of problems in structural and solid mechanics. Time-invariant random materials, geometric properties, and loads are incorporated in terms of their fundamental statistics viz. second-moments. Analogous to the discretization of the displacement field in finite element methods, the random fields are also discretized. Preserving the conceptual simplicity, the response moments are calculated with minimal computations. By incorporating certain computational techniques, these methods are shown to be capable of handling large systems with many sources of uncertainties. By construction, these methods are applicable when the scale of randomness is not very large and when the probabilistic density functions have decaying tails. The accuracy and efficiency of these methods, along with their limitations, are demonstrated by various applications. Results obtained are compared with those of Monte Carlo simulation and it is shown that good accuracy can be obtained for both linear and nonlinear problems. The methods are amenable to implementation in deterministic FEM based computer codes.

Clogging and jamming transitions in periodic obstacle arrays

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

Nguyen, Hong; Reichhardt, Charles; Olson Reichhardt, Cynthia Jane

2017-03-29

We numerically examine clogging transitions for bidisperse disks flowing through a two-dimensional periodic obstacle array. Here, we show that clogging is a probabilistic event that occurs through a transition from a homogeneous flowing state to a heterogeneous or phase-separated jammed state where the disks form dense connected clusters. The probability for clogging to occur during a fixed time increases with increasing particle packing and obstacle number. For driving at different angles with respect to the symmetry direction of the obstacle array, we show that certain directions have a higher clogging susceptibility. It is also possible to have a size-specific cloggingmore » transition in which one disk size becomes completely immobile while the other disk size continues to flow.« less

A probabilistic method for determining the volume fraction of pre-embedded capsules in self-healing materials

NASA Astrophysics Data System (ADS)

Lv, Zhong; Chen, Huisu

2014-10-01

Autonomous healing of cracks using pre-embedded capsules containing healing agent is becoming a promising approach to restore the strength of damaged structures. In addition to the material properties, the size and volume fraction of capsules influence crack healing in the matrix. Understanding the crack and capsule interaction is critical in the development and design of structures made of self-healing materials. Assuming that the pre-embedded capsules are randomly dispersed we theoretically model flat ellipsoidal crack interaction with capsules and determine the probability of a crack intersecting the pre-embedded capsules i.e. the self-healing probability. We also develop a probabilistic model of a crack simultaneously meeting with capsules and catalyst carriers in two-component self-healing system matrix. Using a risk-based healing approach, we determine the volume fraction and size of the pre-embedded capsules that are required to achieve a certain self-healing probability. To understand the effect of the shape of the capsules on self-healing we theoretically modeled crack interaction with spherical and cylindrical capsules. We compared the results of our theoretical model with Monte-Carlo simulations of crack interaction with capsules. The formulae presented in this paper will provide guidelines for engineers working with self-healing structures in material selection and sustenance.

Probabilistic analysis of the behavior of polymer matrix composite materials reinforced by different types of fibers

NASA Astrophysics Data System (ADS)

Harb, N.; Bezzazi, B.; Mehraz, S.; Hamitouche, K.; Dilmi, H.

2017-11-01

The requests of lightening of the structures and gains in performance lead to search for new materials and the associated processes for aeronautical and space applications. Long-fiber composites have been used for many years for these applications; they make it possible to reduce the mass of the structures because of their excellent compromise of mass/rigidity / resistance. The materials in general contain defects which are essentially due to their nature and their mode of elaboration. To this purpuse, we carried out a probabilistic analysis of the mechanical behavior in three-point bending of composite materials with a thermosetting matrix in order to highlight the influence of the number of folds of the fibers and the nature of the fibers on the dispersion of the defects in the stratified structures fiberglass, carbon fiber laminates and hybrid (carbon / glass) laminates. From the results obtained, the dispersion of the defects is lower in the laminates of greater number of plies of the fibers and the hybrid laminates; the more the number of folds increases the more the mechanical characteristics increase; the hybrid laminates exhibit better mechanical properties compared to laminates of the same type of fiber. Finally, a morphological analysis of fracture structures and facies was investigated by scanning electron microscope (SEM) observations.

Simulation investigation of multipactor in metal components for space application with an improved secondary emission model

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

Li, Yun, E-mail: genliyun@126.com, E-mail: cuiwanzhao@126.com; Cui, Wan-Zhao, E-mail: genliyun@126.com, E-mail: cuiwanzhao@126.com; Wang, Hong-Guang

2015-05-15

Effects of the secondary electron emission (SEE) phenomenon of metal surface on the multipactor analysis of microwave components are investigated numerically and experimentally in this paper. Both the secondary electron yield (SEY) and the emitted energy spectrum measurements are performed on silver plated samples for accurate description of the SEE phenomenon. A phenomenological probabilistic model based on SEE physics is utilized and fitted accurately to the measured SEY and emitted energy spectrum of the conditioned surface material of microwave components. Specially, the phenomenological probabilistic model is extended to the low primary energy end lower than 20 eV mathematically, since no accuratemore » measurement data can be obtained. Embedding the phenomenological probabilistic model into the Electromagnetic Particle-In-Cell (EM-PIC) method, the electronic resonant multipacting in microwave components can be tracked and hence the multipactor threshold can be predicted. The threshold prediction error of the transformer and the coaxial filter is 0.12 dB and 1.5 dB, respectively. Simulation results demonstrate that the discharge threshold is strongly dependent on the SEYs and its energy spectrum in the low energy end (lower than 50 eV). Multipacting simulation results agree quite well with experiments in practical components, while the phenomenological probabilistic model fit both the SEY and the emission energy spectrum better than the traditionally used model and distribution. The EM-PIC simulation method with the phenomenological probabilistic model for the surface collision simulation has been demonstrated for predicting the multipactor threshold in metal components for space application.« less

Probabilistic performance assessment of complex energy process systems - The case of a self-sustained sanitation system.

PubMed

Kolios, Athanasios; Jiang, Ying; Somorin, Tosin; Sowale, Ayodeji; Anastasopoulou, Aikaterini; Anthony, Edward J; Fidalgo, Beatriz; Parker, Alison; McAdam, Ewan; Williams, Leon; Collins, Matt; Tyrrel, Sean

2018-05-01

A probabilistic modelling approach was developed and applied to investigate the energy and environmental performance of an innovative sanitation system, the "Nano-membrane Toilet" (NMT). The system treats human excreta via an advanced energy and water recovery island with the aim of addressing current and future sanitation demands. Due to the complex design and inherent characteristics of the system's input material, there are a number of stochastic variables which may significantly affect the system's performance. The non-intrusive probabilistic approach adopted in this study combines a finite number of deterministic thermodynamic process simulations with an artificial neural network (ANN) approximation model and Monte Carlo simulations (MCS) to assess the effect of system uncertainties on the predicted performance of the NMT system. The joint probability distributions of the process performance indicators suggest a Stirling Engine (SE) power output in the range of 61.5-73 W with a high confidence interval (CI) of 95%. In addition, there is high probability (with 95% CI) that the NMT system can achieve positive net power output between 15.8 and 35 W. A sensitivity study reveals the system power performance is mostly affected by SE heater temperature. Investigation into the environmental performance of the NMT design, including water recovery and CO 2 /NO x emissions, suggests significant environmental benefits compared to conventional systems. Results of the probabilistic analysis can better inform future improvements on the system design and operational strategy and this probabilistic assessment framework can also be applied to similar complex engineering systems.

Probabilistic analysis of the torsional effects on the tall building resistance due to earthquake even

NASA Astrophysics Data System (ADS)

Králik, Juraj; Králik, Juraj

2017-07-01

The paper presents the results from the deterministic and probabilistic analysis of the accidental torsional effect of reinforced concrete tall buildings due to earthquake even. The core-column structural system was considered with various configurations in plane. The methodology of the seismic analysis of the building structures in Eurocode 8 and JCSS 2000 is discussed. The possibilities of the utilization the LHS method to analyze the extensive and robust tasks in FEM is presented. The influence of the various input parameters (material, geometry, soil, masses and others) is considered. The deterministic and probability analysis of the seismic resistance of the structure was calculated in the ANSYS program.

A PROBABILISTIC METHOD FOR ESTIMATING MONITORING POINT DENSITY FOR CONTAINMENT SYSTEM LEAK DETECTION

EPA Science Inventory

The use of physical and hydraulic containment systems for the isolation of contaminated ground water and aquifer materials ssociated with hazardous waste sites has increased during the last decade. The existing methodologies for monitoring and evaluating leakage from hazardous w...

A Transferrable Belief Model Representation for Physical Security of Nuclear Materials

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

David Gerts

This work analyzed various probabilistic methods such as classic statistics, Bayesian inference, possibilistic theory, and Dempster-Shafer theory of belief functions for the potential insight offered into the physical security of nuclear materials as well as more broad application to nuclear non-proliferation automated decision making theory. A review of the fundamental heuristic and basic limitations of each of these methods suggested that the Dempster-Shafer theory of belief functions may offer significant capability. Further examination of the various interpretations of Dempster-Shafer theory, such as random set, generalized Bayesian, and upper/lower probability demonstrate some limitations. Compared to the other heuristics, the transferrable beliefmore » model (TBM), one of the leading interpretations of Dempster-Shafer theory, can improve the automated detection of the violation of physical security using sensors and human judgment. The improvement is shown to give a significant heuristic advantage over other probabilistic options by demonstrating significant successes for several classic gedanken experiments.« less

Probalistic Finite Elements (PFEM) structural dynamics and fracture mechanics

NASA Technical Reports Server (NTRS)

Liu, Wing-Kam; Belytschko, Ted; Mani, A.; Besterfield, G.

1989-01-01

The purpose of this work is to develop computationally efficient methodologies for assessing the effects of randomness in loads, material properties, and other aspects of a problem by a finite element analysis. The resulting group of methods is called probabilistic finite elements (PFEM). The overall objective of this work is to develop methodologies whereby the lifetime of a component can be predicted, accounting for the variability in the material and geometry of the component, the loads, and other aspects of the environment; and the range of response expected in a particular scenario can be presented to the analyst in addition to the response itself. Emphasis has been placed on methods which are not statistical in character; that is, they do not involve Monte Carlo simulations. The reason for this choice of direction is that Monte Carlo simulations of complex nonlinear response require a tremendous amount of computation. The focus of efforts so far has been on nonlinear structural dynamics. However, in the continuation of this project, emphasis will be shifted to probabilistic fracture mechanics so that the effect of randomness in crack geometry and material properties can be studied interactively with the effect of random load and environment.

Energy Approach-Based Simulation of Structural Materials High-Cycle Fatigue

NASA Astrophysics Data System (ADS)

Balayev, A. F.; Korolev, A. V.; Kochetkov, A. V.; Sklyarova, A. I.; Zakharov, O. V.

2016-02-01

The paper describes the mechanism of micro-cracks development in solid structural materials based on the theory of brittle fracture. A probability function of material cracks energy distribution is obtained using a probabilistic approach. The paper states energy conditions for cracks growth at material high-cycle loading. A formula allowing to calculate the amount of energy absorbed during the cracks growth is given. The paper proposes a high- cycle fatigue evaluation criterion allowing to determine the maximum permissible number of solid body loading cycles, at which micro-cracks start growing rapidly up to destruction.

A MULTISCALE FRAMEWORK FOR THE STOCHASTIC ASSIMILATION AND MODELING OF UNCERTAINTY ASSOCIATED NCF COMPOSITE MATERIALS

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

Mehrez, Loujaine; Ghanem, Roger; McAuliffe, Colin

multiscale framework to construct stochastic macroscopic constitutive material models is proposed. A spectral projection approach, specifically polynomial chaos expansion, has been used to construct explicit functional relationships between the homogenized properties and input parameters from finer scales. A homogenization engine embedded in Multiscale Designer, software for composite materials, has been used for the upscaling process. The framework is demonstrated using non-crimp fabric composite materials by constructing probabilistic models of the homogenized properties of a non-crimp fabric laminate in terms of the input parameters together with the homogenized properties from finer scales.

Developing an event-tree probabilistic tsunami inundation model for NE Atlantic coasts: Application to case studies

NASA Astrophysics Data System (ADS)

Omira, Rachid; Baptista, Maria Ana; Matias, Luis

2015-04-01

This study constitutes the first assessment of probabilistic tsunami inundation in the NE Atlantic region, using an event-tree approach. It aims to develop a probabilistic tsunami inundation approach for the NE Atlantic coast with an application to two test sites of ASTARTE project, Tangier-Morocco and Sines-Portugal. Only tsunamis of tectonic origin are considered here, taking into account near-, regional- and far-filed sources. The multidisciplinary approach, proposed here, consists of an event-tree method that gathers seismic hazard assessment, tsunami numerical modelling, and statistical methods. It presents also a treatment of uncertainties related to source location and tidal stage in order to derive the likelihood of tsunami flood occurrence and exceedance of a specific near-shore wave height during a given return period. We derive high-resolution probabilistic maximum wave heights and flood distributions for both test-sites Tangier and Sines considering 100-, 500-, and 1000-year return periods. We find that the probability that a maximum wave height exceeds 1 m somewhere along the Sines coasts reaches about 55% for 100-year return period, and is up to 100% for 1000-year return period. Along Tangier coast, the probability of inundation occurrence (flow depth > 0m) is up to 45% for 100-year return period and reaches 96% in some near-shore costal location for 500-year return period. Acknowledgements: This work is funded by project ASTARTE - Assessment, STrategy And Risk Reduction for Tsunamis in Europe. Grant 603839, 7th FP (ENV.2013.6.4-3 ENV.2013.6.4-3).

Multi-parametric variational data assimilation for hydrological forecasting

NASA Astrophysics Data System (ADS)

Alvarado-Montero, R.; Schwanenberg, D.; Krahe, P.; Helmke, P.; Klein, B.

2017-12-01

Ensemble forecasting is increasingly applied in flow forecasting systems to provide users with a better understanding of forecast uncertainty and consequently to take better-informed decisions. A common practice in probabilistic streamflow forecasting is to force deterministic hydrological model with an ensemble of numerical weather predictions. This approach aims at the representation of meteorological uncertainty but neglects uncertainty of the hydrological model as well as its initial conditions. Complementary approaches use probabilistic data assimilation techniques to receive a variety of initial states or represent model uncertainty by model pools instead of single deterministic models. This paper introduces a novel approach that extends a variational data assimilation based on Moving Horizon Estimation to enable the assimilation of observations into multi-parametric model pools. It results in a probabilistic estimate of initial model states that takes into account the parametric model uncertainty in the data assimilation. The assimilation technique is applied to the uppermost area of River Main in Germany. We use different parametric pools, each of them with five parameter sets, to assimilate streamflow data, as well as remotely sensed data from the H-SAF project. We assess the impact of the assimilation in the lead time performance of perfect forecasts (i.e. observed data as forcing variables) as well as deterministic and probabilistic forecasts from ECMWF. The multi-parametric assimilation shows an improvement of up to 23% for CRPS performance and approximately 20% in Brier Skill Scores with respect to the deterministic approach. It also improves the skill of the forecast in terms of rank histogram and produces a narrower ensemble spread.

Bypass transition and spot nucleation in boundary layers

NASA Astrophysics Data System (ADS)

Kreilos, Tobias; Khapko, Taras; Schlatter, Philipp; Duguet, Yohann; Henningson, Dan S.; Eckhardt, Bruno

2016-08-01

The spatiotemporal aspects of the transition to turbulence are considered in the case of a boundary-layer flow developing above a flat plate exposed to free-stream turbulence. Combining results on the receptivity to free-stream turbulence with the nonlinear concept of a transition threshold, a physically motivated model suggests a spatial distribution of spot nucleation events. To describe the evolution of turbulent spots a probabilistic cellular automaton is introduced, with all parameters directly obtained from numerical simulations of the boundary layer. The nucleation rates are then combined with the cellular automaton model, yielding excellent quantitative agreement with the statistical characteristics for different free-stream turbulence levels. We thus show how the recent theoretical progress on transitional wall-bounded flows can be extended to the much wider class of spatially developing boundary-layer flows.

The exposure of Sydney (Australia) to earthquake-generated tsunamis, storms and sea level rise: a probabilistic multi-hazard approach

PubMed Central

Dall'Osso, F.; Dominey-Howes, D.; Moore, C.; Summerhayes, S.; Withycombe, G.

2014-01-01

Approximately 85% of Australia's population live along the coastal fringe, an area with high exposure to extreme inundations such as tsunamis. However, to date, no Probabilistic Tsunami Hazard Assessments (PTHA) that include inundation have been published for Australia. This limits the development of appropriate risk reduction measures by decision and policy makers. We describe our PTHA undertaken for the Sydney metropolitan area. Using the NOAA NCTR model MOST (Method for Splitting Tsunamis), we simulate 36 earthquake-generated tsunamis with annual probabilities of 1:100, 1:1,000 and 1:10,000, occurring under present and future predicted sea level conditions. For each tsunami scenario we generate a high-resolution inundation map of the maximum water level and flow velocity, and we calculate the exposure of buildings and critical infrastructure. Results indicate that exposure to earthquake-generated tsunamis is relatively low for present events, but increases significantly with higher sea level conditions. The probabilistic approach allowed us to undertake a comparison with an existing storm surge hazard assessment. Interestingly, the exposure to all the simulated tsunamis is significantly lower than that for the 1:100 storm surge scenarios, under the same initial sea level conditions. The results have significant implications for multi-risk and emergency management in Sydney. PMID:25492514

Optimal design of groundwater remediation system using a probabilistic multi-objective fast harmony search algorithm under uncertainty

NASA Astrophysics Data System (ADS)

Luo, Qiankun; Wu, Jianfeng; Yang, Yun; Qian, Jiazhong; Wu, Jichun

2014-11-01

This study develops a new probabilistic multi-objective fast harmony search algorithm (PMOFHS) for optimal design of groundwater remediation systems under uncertainty associated with the hydraulic conductivity (K) of aquifers. The PMOFHS integrates the previously developed deterministic multi-objective optimization method, namely multi-objective fast harmony search algorithm (MOFHS) with a probabilistic sorting technique to search for Pareto-optimal solutions to multi-objective optimization problems in a noisy hydrogeological environment arising from insufficient K data. The PMOFHS is then coupled with the commonly used flow and transport codes, MODFLOW and MT3DMS, to identify the optimal design of groundwater remediation systems for a two-dimensional hypothetical test problem and a three-dimensional Indiana field application involving two objectives: (i) minimization of the total remediation cost through the engineering planning horizon, and (ii) minimization of the mass remaining in the aquifer at the end of the operational period, whereby the pump-and-treat (PAT) technology is used to clean up contaminated groundwater. Also, Monte Carlo (MC) analysis is employed to evaluate the effectiveness of the proposed methodology. Comprehensive analysis indicates that the proposed PMOFHS can find Pareto-optimal solutions with low variability and high reliability and is a potentially effective tool for optimizing multi-objective groundwater remediation problems under uncertainty.

The exposure of Sydney (Australia) to earthquake-generated tsunamis, storms and sea level rise: a probabilistic multi-hazard approach.

PubMed

Dall'Osso, F; Dominey-Howes, D; Moore, C; Summerhayes, S; Withycombe, G

2014-12-10

Approximately 85% of Australia's population live along the coastal fringe, an area with high exposure to extreme inundations such as tsunamis. However, to date, no Probabilistic Tsunami Hazard Assessments (PTHA) that include inundation have been published for Australia. This limits the development of appropriate risk reduction measures by decision and policy makers. We describe our PTHA undertaken for the Sydney metropolitan area. Using the NOAA NCTR model MOST (Method for Splitting Tsunamis), we simulate 36 earthquake-generated tsunamis with annual probabilities of 1:100, 1:1,000 and 1:10,000, occurring under present and future predicted sea level conditions. For each tsunami scenario we generate a high-resolution inundation map of the maximum water level and flow velocity, and we calculate the exposure of buildings and critical infrastructure. Results indicate that exposure to earthquake-generated tsunamis is relatively low for present events, but increases significantly with higher sea level conditions. The probabilistic approach allowed us to undertake a comparison with an existing storm surge hazard assessment. Interestingly, the exposure to all the simulated tsunamis is significantly lower than that for the 1:100 storm surge scenarios, under the same initial sea level conditions. The results have significant implications for multi-risk and emergency management in Sydney.

Probabilistic Micromechanics and Macromechanics for Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Mital, Subodh K.; Shah, Ashwin R.

1997-01-01

The properties of ceramic matrix composites (CMC's) are known to display a considerable amount of scatter due to variations in fiber/matrix properties, interphase properties, interphase bonding, amount of matrix voids, and many geometry- or fabrication-related parameters, such as ply thickness and ply orientation. This paper summarizes preliminary studies in which formal probabilistic descriptions of the material-behavior- and fabrication-related parameters were incorporated into micromechanics and macromechanics for CMC'S. In this process two existing methodologies, namely CMC micromechanics and macromechanics analysis and a fast probability integration (FPI) technique are synergistically coupled to obtain the probabilistic composite behavior or response. Preliminary results in the form of cumulative probability distributions and information on the probability sensitivities of the response to primitive variables for a unidirectional silicon carbide/reaction-bonded silicon nitride (SiC/RBSN) CMC are presented. The cumulative distribution functions are computed for composite moduli, thermal expansion coefficients, thermal conductivities, and longitudinal tensile strength at room temperature. The variations in the constituent properties that directly affect these composite properties are accounted for via assumed probabilistic distributions. Collectively, the results show that the present technique provides valuable information about the composite properties and sensitivity factors, which is useful to design or test engineers. Furthermore, the present methodology is computationally more efficient than a standard Monte-Carlo simulation technique; and the agreement between the two solutions is excellent, as shown via select examples.

Quantum formalism for classical statistics

NASA Astrophysics Data System (ADS)

Wetterich, C.

2018-06-01

In static classical statistical systems the problem of information transport from a boundary to the bulk finds a simple description in terms of wave functions or density matrices. While the transfer matrix formalism is a type of Heisenberg picture for this problem, we develop here the associated Schrödinger picture that keeps track of the local probabilistic information. The transport of the probabilistic information between neighboring hypersurfaces obeys a linear evolution equation, and therefore the superposition principle for the possible solutions. Operators are associated to local observables, with rules for the computation of expectation values similar to quantum mechanics. We discuss how non-commutativity naturally arises in this setting. Also other features characteristic of quantum mechanics, such as complex structure, change of basis or symmetry transformations, can be found in classical statistics once formulated in terms of wave functions or density matrices. We construct for every quantum system an equivalent classical statistical system, such that time in quantum mechanics corresponds to the location of hypersurfaces in the classical probabilistic ensemble. For suitable choices of local observables in the classical statistical system one can, in principle, compute all expectation values and correlations of observables in the quantum system from the local probabilistic information of the associated classical statistical system. Realizing a static memory material as a quantum simulator for a given quantum system is not a matter of principle, but rather of practical simplicity.

Teaching Measurement and Uncertainty the GUM Way

ERIC Educational Resources Information Center

Buffler, Andy; Allie, Saalih; Lubben, Fred

2008-01-01

This paper describes a course aimed at developing understanding of measurement and uncertainty in the introductory physics laboratory. The course materials, in the form of a student workbook, are based on the probabilistic framework for measurement as recommended by the International Organization for Standardization in their publication "Guide to…

DISCRETE ELEMENT MODELING OF BLADE–STRIKE FREQUENCY AND SURVIVAL OF FISH PASSING THROUGH HYDROKINETIC TURBINES

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

Romero Gomez, Pedro DJ; Richmond, Marshall C.

2014-04-17

Evaluating the consequences from blade-strike of fish on marine hydrokinetic (MHK) turbine blades is essential for incorporating environmental objectives into the integral optimization of machine performance. For instance, experience with conventional hydroelectric turbines has shown that innovative shaping of the blade and other machine components can lead to improved designs that generate more power without increased impacts to fish and other aquatic life. In this work, we used unsteady computational fluid dynamics (CFD) simulations of turbine flow and discrete element modeling (DEM) of particle motion to estimate the frequency and severity of collisions between a horizontal axis MHK tidal energymore » device and drifting aquatic organisms or debris. Two metrics are determined with the method: the strike frequency and survival rate estimate. To illustrate the procedure step-by-step, an exemplary case of a simple runner model was run and compared against a probabilistic model widely used for strike frequency evaluation. The results for the exemplary case showed a strong correlation between the two approaches. In the application case of the MHK turbine flow, turbulent flow was modeled using detached eddy simulation (DES) in conjunction with a full moving rotor at full scale. The CFD simulated power and thrust were satisfactorily comparable to experimental results conducted in a water tunnel on a reduced scaled (1:8.7) version of the turbine design. A cloud of DEM particles was injected into the domain to simulate fish or debris that were entrained into the turbine flow. The strike frequency was the ratio of the count of colliding particles to the crossing sample size. The fish length and approaching velocity were test conditions in the simulations of the MHK turbine. Comparisons showed that DEM-based frequencies tend to be greater than previous results from Lagrangian particles and probabilistic models, mostly because the DEM scheme accounts for both the geometric aspects of the passage event ---which the probabilistic method does--- as well as the fluid-particle interactions ---which the Lagrangian particle method does. The DEM-based survival rates were comparable to laboratory results for small fish but not for mid-size fish because of the considerably different turbine diameters. The modeling framework can be used for applications that aim at evaluating the biological performance of MHK turbine units during the design phase and to provide information to regulatory agencies needed for the environmental permitting process.« less

Predicting inpatient clinical order patterns with probabilistic topic models vs conventional order sets

PubMed Central

Goldstein, Mary K; Asch, Steven M; Mackey, Lester; Altman, Russ B

2017-01-01

Objective: Build probabilistic topic model representations of hospital admissions processes and compare the ability of such models to predict clinical order patterns as compared to preconstructed order sets. Materials and Methods: The authors evaluated the first 24 hours of structured electronic health record data for > 10 K inpatients. Drawing an analogy between structured items (e.g., clinical orders) to words in a text document, the authors performed latent Dirichlet allocation probabilistic topic modeling. These topic models use initial clinical information to predict clinical orders for a separate validation set of > 4 K patients. The authors evaluated these topic model-based predictions vs existing human-authored order sets by area under the receiver operating characteristic curve, precision, and recall for subsequent clinical orders. Results: Existing order sets predict clinical orders used within 24 hours with area under the receiver operating characteristic curve 0.81, precision 16%, and recall 35%. This can be improved to 0.90, 24%, and 47% (P < 10−20) by using probabilistic topic models to summarize clinical data into up to 32 topics. Many of these latent topics yield natural clinical interpretations (e.g., “critical care,” “pneumonia,” “neurologic evaluation”). Discussion: Existing order sets tend to provide nonspecific, process-oriented aid, with usability limitations impairing more precise, patient-focused support. Algorithmic summarization has the potential to breach this usability barrier by automatically inferring patient context, but with potential tradeoffs in interpretability. Conclusion: Probabilistic topic modeling provides an automated approach to detect thematic trends in patient care and generate decision support content. A potential use case finds related clinical orders for decision support. PMID:27655861

Incorporating probabilistic seasonal climate forecasts into river management using a risk-based framework

USGS Publications Warehouse

Sojda, Richard S.; Towler, Erin; Roberts, Mike; Rajagopalan, Balaji

2013-01-01

[1] Despite the influence of hydroclimate on river ecosystems, most efforts to date have focused on using climate information to predict streamflow for water supply. However, as water demands intensify and river systems are increasingly stressed, research is needed to explicitly integrate climate into streamflow forecasts that are relevant to river ecosystem management. To this end, we present a five step risk-based framework: (1) define risk tolerance, (2) develop a streamflow forecast model, (3) generate climate forecast ensembles, (4) estimate streamflow ensembles and associated risk, and (5) manage for climate risk. The framework is successfully demonstrated for an unregulated watershed in southwest Montana, where the combination of recent drought and water withdrawals has made it challenging to maintain flows needed for healthy fisheries. We put forth a generalized linear modeling (GLM) approach to develop a suite of tools that skillfully model decision-relevant low flow characteristics in terms of climate predictors. Probabilistic precipitation forecasts are used in conjunction with the GLMs, resulting in season-ahead prediction ensembles that provide the full risk profile. These tools are embedded in an end-to-end risk management framework that directly supports proactive fish conservation efforts. Results show that the use of forecasts can be beneficial to planning, especially in wet years, but historical precipitation forecasts are quite conservative (i.e., not very “sharp”). Synthetic forecasts show that a modest “sharpening” can strongly impact risk and improve skill. We emphasize that use in management depends on defining relevant environmental flows and risk tolerance, requiring local stakeholder involvement.

Effective comparative analysis of protein-protein interaction networks by measuring the steady-state network flow using a Markov model.

PubMed

Jeong, Hyundoo; Qian, Xiaoning; Yoon, Byung-Jun

2016-10-06

Comparative analysis of protein-protein interaction (PPI) networks provides an effective means of detecting conserved functional network modules across different species. Such modules typically consist of orthologous proteins with conserved interactions, which can be exploited to computationally predict the modules through network comparison. In this work, we propose a novel probabilistic framework for comparing PPI networks and effectively predicting the correspondence between proteins, represented as network nodes, that belong to conserved functional modules across the given PPI networks. The basic idea is to estimate the steady-state network flow between nodes that belong to different PPI networks based on a Markov random walk model. The random walker is designed to make random moves to adjacent nodes within a PPI network as well as cross-network moves between potential orthologous nodes with high sequence similarity. Based on this Markov random walk model, we estimate the steady-state network flow - or the long-term relative frequency of the transitions that the random walker makes - between nodes in different PPI networks, which can be used as a probabilistic score measuring their potential correspondence. Subsequently, the estimated scores can be used for detecting orthologous proteins in conserved functional modules through network alignment. Through evaluations based on multiple real PPI networks, we demonstrate that the proposed scheme leads to improved alignment results that are biologically more meaningful at reduced computational cost, outperforming the current state-of-the-art algorithms. The source code and datasets can be downloaded from http://www.ece.tamu.edu/~bjyoon/CUFID .

Numerical modelling of glacial lake outburst floods using physically based dam-breach models

NASA Astrophysics Data System (ADS)

Westoby, M. J.; Brasington, J.; Glasser, N. F.; Hambrey, M. J.; Reynolds, J. M.; Hassan, M. A. A. M.; Lowe, A.

2015-03-01

The instability of moraine-dammed proglacial lakes creates the potential for catastrophic glacial lake outburst floods (GLOFs) in high-mountain regions. In this research, we use a unique combination of numerical dam-breach and two-dimensional hydrodynamic modelling, employed within a generalised likelihood uncertainty estimation (GLUE) framework, to quantify predictive uncertainty in model outputs associated with a reconstruction of the Dig Tsho failure in Nepal. Monte Carlo analysis was used to sample the model parameter space, and morphological descriptors of the moraine breach were used to evaluate model performance. Multiple breach scenarios were produced by differing parameter ensembles associated with a range of breach initiation mechanisms, including overtopping waves and mechanical failure of the dam face. The material roughness coefficient was found to exert a dominant influence over model performance. The downstream routing of scenario-specific breach hydrographs revealed significant differences in the timing and extent of inundation. A GLUE-based methodology for constructing probabilistic maps of inundation extent, flow depth, and hazard is presented and provides a useful tool for communicating uncertainty in GLOF hazard assessment.

Hazard Monitoring of Growing Lava Flow Fields Using Seismic Tremor

NASA Astrophysics Data System (ADS)

Eibl, E. P. S.; Bean, C. J.; Jónsdottir, I.; Hoskuldsson, A.; Thordarson, T.; Coppola, D.; Witt, T.; Walter, T. R.

2017-12-01

An effusive eruption in 2014/15 created a 85 km2 large lava flow field in a remote location in the Icelandic highlands. The lava flows did not threaten any settlements or paved roads but they were nevertheless interdisciplinarily monitored in detail. Images from satellites and aircraft, ground based video monitoring, GPS and seismic recordings allowed the monitoring and reconstruction of a detailed time series of the growing lava flow field. While the use of satellite images and probabilistic modelling of lava flows are quite common tools to monitor the current and forecast the future growth direction, here we show that seismic recordings can be of use too. We installed a cluster of seismometers at 15 km from the vents and recorded the ground vibrations associated with the eruption. This seismic tremor was not only generated below the vents, but also at the edges of the growing lava flow field and indicated the parts of the lava flow field that were most actively growing. Whilst the time resolution is in the range of days for satellites, seismic stations easily sample continuously at 100 Hz and could therefore provide a much better resolution and estimate of the lava flow hazard in real-time.

Groundwater Remediation using Bayesian Information-Gap Decision Theory

NASA Astrophysics Data System (ADS)

O'Malley, D.; Vesselinov, V. V.

2016-12-01

Probabilistic analyses of groundwater remediation scenarios frequently fail because the probability of an adverse, unanticipated event occurring is often high. In general, models of flow and transport in contaminated aquifers are always simpler than reality. Further, when a probabilistic analysis is performed, probability distributions are usually chosen more for convenience than correctness. The Bayesian Information-Gap Decision Theory (BIGDT) was designed to mitigate the shortcomings of the models and probabilistic decision analyses by leveraging a non-probabilistic decision theory - information-gap decision theory. BIGDT considers possible models that have not been explicitly enumerated and does not require us to commit to a particular probability distribution for model and remediation-design parameters. Both the set of possible models and the set of possible probability distributions grow as the degree of uncertainty increases. The fundamental question that BIGDT asks is "How large can these sets be before a particular decision results in an undesirable outcome?". The decision that allows these sets to be the largest is considered to be the best option. In this way, BIGDT enables robust decision-support for groundwater remediation problems. Here we apply BIGDT to in a representative groundwater remediation scenario where different options for hydraulic containment and pump & treat are being considered. BIGDT requires many model runs and for complex models high-performance computing resources are needed. These analyses are carried out on synthetic problems, but are applicable to real-world problems such as LANL site contaminations. BIGDT is implemented in Julia (a high-level, high-performance dynamic programming language for technical computing) and is part of the MADS framework (http://mads.lanl.gov/ and https://github.com/madsjulia/Mads.jl).

Role of the site of synaptic competition and the balance of learning forces for Hebbian encoding of probabilistic Markov sequences

PubMed Central

Bouchard, Kristofer E.; Ganguli, Surya; Brainard, Michael S.

2015-01-01

The majority of distinct sensory and motor events occur as temporally ordered sequences with rich probabilistic structure. Sequences can be characterized by the probability of transitioning from the current state to upcoming states (forward probability), as well as the probability of having transitioned to the current state from previous states (backward probability). Despite the prevalence of probabilistic sequencing of both sensory and motor events, the Hebbian mechanisms that mold synapses to reflect the statistics of experienced probabilistic sequences are not well understood. Here, we show through analytic calculations and numerical simulations that Hebbian plasticity (correlation, covariance, and STDP) with pre-synaptic competition can develop synaptic weights equal to the conditional forward transition probabilities present in the input sequence. In contrast, post-synaptic competition can develop synaptic weights proportional to the conditional backward probabilities of the same input sequence. We demonstrate that to stably reflect the conditional probability of a neuron's inputs and outputs, local Hebbian plasticity requires balance between competitive learning forces that promote synaptic differentiation and homogenizing learning forces that promote synaptic stabilization. The balance between these forces dictates a prior over the distribution of learned synaptic weights, strongly influencing both the rate at which structure emerges and the entropy of the final distribution of synaptic weights. Together, these results demonstrate a simple correspondence between the biophysical organization of neurons, the site of synaptic competition, and the temporal flow of information encoded in synaptic weights by Hebbian plasticity while highlighting the utility of balancing learning forces to accurately encode probability distributions, and prior expectations over such probability distributions. PMID:26257637

An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): assessing the added value of probabilistic forecasts

NASA Astrophysics Data System (ADS)

Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

2012-04-01

The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on deterministic (COSMO-7) and probabilistic (COSMO-LEPS) atmospheric forecasts, which are used to force a semi-distributed hydrological model (PREVAH) coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which we assessed the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added value conveyed by the probability information, a 31-month reforecast was produced for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain is of up to 2 days lead time for the catchment considered. Brier skill scores show that probabilistic hydrological forecasts outperform their deterministic counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. We finally highlight challenges for making decisions on the basis of hydrological predictions, and discuss the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment.

Probabilistic modelling and uncertainty analysis of flux and water balance changes in a regional aquifer system due to coal seam gas development.

PubMed

Sreekanth, J; Cui, Tao; Pickett, Trevor; Rassam, David; Gilfedder, Mat; Barrett, Damian

2018-09-01

Large scale development of coal seam gas (CSG) is occurring in many sedimentary basins around the world including Australia, where commercial production of CSG has started in the Surat and Bowen basins. CSG development often involves extraction of large volumes of water that results in depressurising aquifers that overlie and/or underlie the coal seams thus perturbing their flow regimes. This can potentially impact regional aquifer systems that are used for many purposes such as irrigation, and stock and domestic water. In this study, we adopt a probabilistic approach to quantify the depressurisation of the Gunnedah coal seams and how this impacts fluxes to, and from the overlying Great Artesian Basin (GAB) Pilliga Sandstone aquifer. The proposed method is suitable when effects of a new resource development activity on the regional groundwater balance needs to be assessed and account for large scale uncertainties in the groundwater flow system and proposed activity. The results indicated that the extraction of water and gas from the coal seam could potentially induce additional fluxes from the Pilliga Sandstone to the deeper formations due to lowering pressure heads in the coal seams. The median value of the rise in the maximum flux from the Pilliga Sandstone to the deeper formations is estimated to be 85ML/year, which is considered insignificant as it forms only about 0.29% of the Long Term Annual Average Extraction Limit of 30GL/year from the groundwater management area. The probabilistic simulation of the water balance components indicates only small changes being induced by CSG development that influence interactions of the Pilliga Sandstone with the overlying and underlying formations and with the surface water courses. The current analyses that quantified the potential maximum impacts of resource developments and how they influences the regional water balance, would greatly underpin future management decisions. Copyright © 2018 Elsevier B.V. All rights reserved.

Attribution of UK Winter Floods to Anthropogenic Forcing

NASA Astrophysics Data System (ADS)

Schaller, N.; Alison, K.; Sparrow, S. N.; Otto, F. E. L.; Massey, N.; Vautard, R.; Yiou, P.; van Oldenborgh, G. J.; van Haren, R.; Lamb, R.; Huntingford, C.; Crooks, S.; Legg, T.; Weisheimer, A.; Bowery, A.; Miller, J.; Jones, R.; Stott, P.; Allen, M. R.

2014-12-01

Many regions of southern UK experienced severe flooding during the 2013/2014 winter. Simultaneously, large areas in the USA and Canada were struck by prolonged cold weather. At the time, the media and public asked whether the general rainy conditions over northern Europe and the cold weather over North America were caused by climate change. Providing an answer to this question is not trivial, but recent studies show that probabilistic event attribution is feasible. Using the citizen science project weather@home, we ran over 40'000 perturbed initial condition simulations of the 2013/2014 winter. These simulations fall into two categories: one set aims at simulating the world with climate change using observed sea surface temperatures while the second set is run with sea surface temperatures corresponding to a world that might have been without climate change. The relevant modelled variables are then downscaled by a hydrological model to obtain river flows. First results show that anthropogenic climate change led to a small but significant increase in the fractional attributable risk for 30-days peak flows for the river Thames. A single number can summarize the final result from probabilistic attribution studies indicating, for example, an increase, decrease or no change to the risk of the event occurring. However, communicating this to the public, media and other scientists remains challenging. The assumptions made in the chain of models used need to be explained. In addition, extreme events, like the UK floods of the 2013/2014 winter, are usually caused by a range of factors. While heavy precipitation events can be caused by dynamic and/or thermodynamic processes, floods occur only partly as a response to heavy precipitation. Depending on the catchment, they can be largely due to soil properties and conditions of the previous months. Probabilistic attribution studies are multidisciplinary and therefore all aspects need to be communicated properly.

Optimal Power Flow for Distribution Systems under Uncertain Forecasts: Preprint

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

Dall'Anese, Emiliano; Baker, Kyri; Summers, Tyler

2016-12-01

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative boundsmore » that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.« less

Life Modeling and Design Analysis for Ceramic Matrix Composite Materials

NASA Technical Reports Server (NTRS)

2005-01-01

The primary research efforts focused on characterizing and modeling static failure, environmental durability, and creep-rupture behavior of two classes of ceramic matrix composites (CMC), silicon carbide fibers in a silicon carbide matrix (SiC/SiC) and carbon fibers in a silicon carbide matrix (C/SiC). An engineering life prediction model (Probabilistic Residual Strength model) has been developed specifically for CMCs. The model uses residual strength as the damage metric for evaluating remaining life and is posed probabilistically in order to account for the stochastic nature of the material s response. In support of the modeling effort, extensive testing of C/SiC in partial pressures of oxygen has been performed. This includes creep testing, tensile testing, half life and residual tensile strength testing. C/SiC is proposed for airframe and propulsion applications in advanced reusable launch vehicles. Figures 1 and 2 illustrate the models predictive capabilities as well as the manner in which experimental tests are being selected in such a manner as to ensure sufficient data is available to aid in model validation.

A probabilistic sizing tool and Monte Carlo analysis for entry vehicle ablative thermal protection systems

NASA Astrophysics Data System (ADS)

Mazzaracchio, Antonio; Marchetti, Mario

2010-03-01

Implicit ablation and thermal response software was developed to analyse and size charring ablative thermal protection systems for entry vehicles. A statistical monitor integrated into the tool, which uses the Monte Carlo technique, allows a simulation to run over stochastic series. This performs an uncertainty and sensitivity analysis, which estimates the probability of maintaining the temperature of the underlying material within specified requirements. This approach and the associated software are primarily helpful during the preliminary design phases of spacecraft thermal protection systems. They are proposed as an alternative to traditional approaches, such as the Root-Sum-Square method. The developed tool was verified by comparing the results with those from previous work on thermal protection system probabilistic sizing methodologies, which are based on an industry standard high-fidelity ablation and thermal response program. New case studies were analysed to establish thickness margins on sizing heat shields that are currently proposed for vehicles using rigid aeroshells for future aerocapture missions at Neptune, and identifying the major sources of uncertainty in the material response.

Development of Testing Methodologies for the Mechanical Properties of MEMS

NASA Technical Reports Server (NTRS)

Ekwaro-Osire, Stephen

2003-01-01

This effort is to investigate and design testing strategies to determine the mechanical properties of MicroElectroMechanical Systems (MEMS) as well as investigate the development of a MEMS Probabilistic Design Methodology (PDM). One item of potential interest is the design of a test for the Weibull size effect in pressure membranes. The Weibull size effect is a consequence of a stochastic strength response predicted from the Weibull distribution. Confirming that MEMS strength is controlled by the Weibull distribution will enable the development of a probabilistic design methodology for MEMS - similar to the GRC developed CARES/Life program for bulk ceramics. However, the primary area of investigation will most likely be analysis and modeling of material interfaces for strength as well as developing a strategy to handle stress singularities at sharp corners, filets, and material interfaces. This will be a continuation of the previous years work. The ultimate objective of this effort is to further develop and verify the ability of the Ceramics Analysis and Reliability Evaluation of Structures Life (CARES/Life) code to predict the time-dependent reliability of MEMS structures subjected to multiple transient loads.

An approximate methods approach to probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Mcclung, R. C.; Millwater, H. R.; Wu, Y.-T.; Thacker, B. H.; Burnside, O. H.

1989-01-01

A major research and technology program in Probabilistic Structural Analysis Methods (PSAM) is currently being sponsored by the NASA Lewis Research Center with Southwest Research Institute as the prime contractor. This program is motivated by the need to accurately predict structural response in an environment where the loadings, the material properties, and even the structure may be considered random. The heart of PSAM is a software package which combines advanced structural analysis codes with a fast probability integration (FPI) algorithm for the efficient calculation of stochastic structural response. The basic idea of PAAM is simple: make an approximate calculation of system response, including calculation of the associated probabilities, with minimal computation time and cost, based on a simplified representation of the geometry, loads, and material. The deterministic solution resulting should give a reasonable and realistic description of performance-limiting system responses, although some error will be inevitable. If the simple model has correctly captured the basic mechanics of the system, however, including the proper functional dependence of stress, frequency, etc. on design parameters, then the response sensitivities calculated may be of significantly higher accuracy.

The analysis of probability task completion; Taxonomy of probabilistic thinking-based across gender in elementary school students

NASA Astrophysics Data System (ADS)

Sari, Dwi Ivayana; Budayasa, I. Ketut; Juniati, Dwi

2017-08-01

Formulation of mathematical learning goals now is not only oriented on cognitive product, but also leads to cognitive process, which is probabilistic thinking. Probabilistic thinking is needed by students to make a decision. Elementary school students are required to develop probabilistic thinking as foundation to learn probability at higher level. A framework of probabilistic thinking of students had been developed by using SOLO taxonomy, which consists of prestructural probabilistic thinking, unistructural probabilistic thinking, multistructural probabilistic thinking and relational probabilistic thinking. This study aimed to analyze of probability task completion based on taxonomy of probabilistic thinking. The subjects were two students of fifth grade; boy and girl. Subjects were selected by giving test of mathematical ability and then based on high math ability. Subjects were given probability tasks consisting of sample space, probability of an event and probability comparison. The data analysis consisted of categorization, reduction, interpretation and conclusion. Credibility of data used time triangulation. The results was level of boy's probabilistic thinking in completing probability tasks indicated multistructural probabilistic thinking, while level of girl's probabilistic thinking in completing probability tasks indicated unistructural probabilistic thinking. The results indicated that level of boy's probabilistic thinking was higher than level of girl's probabilistic thinking. The results could contribute to curriculum developer in developing probability learning goals for elementary school students. Indeed, teachers could teach probability with regarding gender difference.

Flood model for Brazil

NASA Astrophysics Data System (ADS)

Palán, Ladislav; Punčochář, Petr

2017-04-01

Looking on the impact of flooding from the World-wide perspective, in last 50 years flooding has caused over 460,000 fatalities and caused serious material damage. Combining economic loss from ten costliest flood events (from the same period) returns a loss (in the present value) exceeding 300bn USD. Locally, in Brazil, flood is the most damaging natural peril with alarming increase of events frequencies as 5 out of the 10 biggest flood losses ever recorded have occurred after 2009. The amount of economic and insured losses particularly caused by various flood types was the key driver of the local probabilistic flood model development. Considering the area of Brazil (being 5th biggest country in the World) and the scattered distribution of insured exposure, a domain covered by the model was limited to the entire state of Sao Paolo and 53 additional regions. The model quantifies losses on approx. 90 % of exposure (for regular property lines) of key insurers. Based on detailed exposure analysis, Impact Forecasting has developed this tool using long term local hydrological data series (Agencia Nacional de Aguas) from riverine gauge stations and digital elevation model (Instituto Brasileiro de Geografia e Estatística). To provide most accurate representation of local hydrological behaviour needed for the nature of probabilistic simulation, a hydrological data processing focused on frequency analyses of seasonal peak flows - done by fitting appropriate extreme value statistical distribution and stochastic event set generation consisting of synthetically derived flood events respecting realistic spatial and frequency patterns visible in entire period of hydrological observation. Data were tested for homogeneity, consistency and for any significant breakpoint occurrence in time series so the entire observation or only its subparts were used for further analysis. The realistic spatial patterns of stochastic events are reproduced through the innovative use of d-vine copula scheme to generate probabilistic flood event set. The derived design flows for selected rivers inside model domain were used as an input for 2-dimensional hydrodynamic inundation modelling techniques (using the tool TUFLOW by BMT WBM) on mesh size 30 x 30 metres. Outputs from inundation modelling and stochastic event set were implemented in the Aon Benfield's platform ELEMENTS developed and managed internally by Impact Forecasting; Aon Benfield internal catastrophe model development center. The model was designed to evaluate potential financial impact caused by fluvial flooding on portfolios of insurance and/or reinsurance companies. The structure of presented model follows typical scheme of financial loss catastrophe model and combines hazard with exposure and vulnerability to produce potential financial loss expressed in the form of loss exceedance probability curve and many other insured perspectives, such as average annual loss, event or quantile loss tables and etc. Model can take financial inputs as well as provide split of results for exact specified location or related higher administrative units: municipalities and 5-digit postal codes.

Feasibility study on the use of probabilistic migration modeling in support of exposure assessment from food contact materials.

PubMed

Poças, Maria F; Oliveira, Jorge C; Brandsch, Rainer; Hogg, Timothy

2010-07-01

The use of probabilistic approaches in exposure assessments of contaminants migrating from food packages is of increasing interest but the lack of concentration or migration data is often referred as a limitation. Data accounting for the variability and uncertainty that can be expected in migration, for example, due to heterogeneity in the packaging system, variation of the temperature along the distribution chain, and different time of consumption of each individual package, are required for probabilistic analysis. The objective of this work was to characterize quantitatively the uncertainty and variability in estimates of migration. A Monte Carlo simulation was applied to a typical solution of the Fick's law with given variability in the input parameters. The analysis was performed based on experimental data of a model system (migration of Irgafos 168 from polyethylene into isooctane) and illustrates how important sources of variability and uncertainty can be identified in order to refine analyses. For long migration times and controlled conditions of temperature the affinity of the migrant to the food can be the major factor determining the variability in the migration values (more than 70% of variance). In situations where both the time of consumption and temperature can vary, these factors can be responsible, respectively, for more than 60% and 20% of the variance in the migration estimates. The approach presented can be used with databases from consumption surveys to yield a true probabilistic estimate of exposure.

Reliability analysis of composite structures

NASA Technical Reports Server (NTRS)

Kan, Han-Pin

1992-01-01

A probabilistic static stress analysis methodology has been developed to estimate the reliability of a composite structure. Closed form stress analysis methods are the primary analytical tools used in this methodology. These structural mechanics methods are used to identify independent variables whose variations significantly affect the performance of the structure. Once these variables are identified, scatter in their values is evaluated and statistically characterized. The scatter in applied loads and the structural parameters are then fitted to appropriate probabilistic distribution functions. Numerical integration techniques are applied to compute the structural reliability. The predicted reliability accounts for scatter due to variability in material strength, applied load, fabrication and assembly processes. The influence of structural geometry and mode of failure are also considerations in the evaluation. Example problems are given to illustrate various levels of analytical complexity.

Probabilistic Mesomechanical Fatigue Model

NASA Technical Reports Server (NTRS)

Tryon, Robert G.

1997-01-01

A probabilistic mesomechanical fatigue life model is proposed to link the microstructural material heterogeneities to the statistical scatter in the macrostructural response. The macrostructure is modeled as an ensemble of microelements. Cracks nucleation within the microelements and grow from the microelements to final fracture. Variations of the microelement properties are defined using statistical parameters. A micromechanical slip band decohesion model is used to determine the crack nucleation life and size. A crack tip opening displacement model is used to determine the small crack growth life and size. Paris law is used to determine the long crack growth life. The models are combined in a Monte Carlo simulation to determine the statistical distribution of total fatigue life for the macrostructure. The modeled response is compared to trends in experimental observations from the literature.

Advanced probabilistic methods for quantifying the effects of various uncertainties in structural response

NASA Technical Reports Server (NTRS)

Nagpal, Vinod K.

1988-01-01

The effects of actual variations, also called uncertainties, in geometry and material properties on the structural response of a space shuttle main engine turbopump blade are evaluated. A normal distribution was assumed to represent the uncertainties statistically. Uncertainties were assumed to be totally random, partially correlated, and fully correlated. The magnitude of these uncertainties were represented in terms of mean and variance. Blade responses, recorded in terms of displacements, natural frequencies, and maximum stress, was evaluated and plotted in the form of probabilistic distributions under combined uncertainties. These distributions provide an estimate of the range of magnitudes of the response and probability of occurrence of a given response. Most importantly, these distributions provide the information needed to estimate quantitatively the risk in a structural design.

Divergence instability of pipes conveying fluid with uncertain flow velocity

NASA Astrophysics Data System (ADS)

Rahmati, Mehdi; Mirdamadi, Hamid Reza; Goli, Sareh

2018-02-01

This article deals with investigation of probabilistic stability of pipes conveying fluid with stochastic flow velocity in time domain. As a matter of fact, this study has focused on the randomness effects of flow velocity on stability of pipes conveying fluid while most of research efforts have only focused on the influences of deterministic parameters on the system stability. The Euler-Bernoulli beam and plug flow theory are employed to model pipe structure and internal flow, respectively. In addition, flow velocity is considered as a stationary random process with Gaussian distribution. Afterwards, the stochastic averaging method and Routh's stability criterion are used so as to investigate the stability conditions of system. Consequently, the effects of boundary conditions, viscoelastic damping, mass ratio, and elastic foundation on the stability regions are discussed. Results delineate that the critical mean flow velocity decreases by increasing power spectral density (PSD) of the random velocity. Moreover, by increasing PSD from zero, the type effects of boundary condition and presence of elastic foundation are diminished, while the influences of viscoelastic damping and mass ratio could increase. Finally, to have a more applicable study, regression analysis is utilized to develop design equations and facilitate further analyses for design purposes.

Propagation of radar rainfall uncertainty in urban flood simulations

NASA Astrophysics Data System (ADS)

Liguori, Sara; Rico-Ramirez, Miguel

2013-04-01

This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF, 2010. Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surveys in Geophysics 31: 107-129. [4] Rossa A, Liechti K, Zappa M, Bruen M, Germann U, Haase G, Keil C, Krahe P, 2011. The COST 731 Action: A review on uncertainty propagation in advanced hydrometeorological forecast systems. Atmospheric Research 100, 150-167. [5] Rossa A, Bruen M, Germann U, Haase G, Keil C, Krahe P, Zappa M, 2010. Overview and Main Results on the interdisciplinary effort in flood forecasting COST 731-Propagation of Uncertainty in Advanced Meteo-Hydrological Forecast Systems. Proceedings of Sixth European Conference on Radar in Meteorology and Hydrology ERAD 2010. [6] Germann U, Berenguer M, Sempere-Torres D, Zappa M, 2009. REAL - ensemble radar precipitation estimation for hydrology in a mountainous region. Quarterly Journal of the Royal Meteorological Society 135: 445-456. [8] Bowler NEH, Pierce CE, Seed AW, 2006. STEPS: a probabilistic precipitation forecasting scheme which merges and extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society 132: 2127-2155. [9] Zappa M, Rotach MW, Arpagaus M, Dorninger M, Hegg C, Montani A, Ranzi R, Ament F, Germann U, Grossi G et al., 2008. MAP D-PHASE: real-time demonstration of hydrological ensemble prediction systems. Atmospheric Science Letters 9, 80-87. [10] Liguori S, Rico-Ramirez MA. Quantitative assessment of short-term rainfall forecasts from radar nowcasts and MM5 forecasts. Hydrological Processes, accepted article. DOI: 10.1002/hyp.8415 [11] Liguori S, Rico-Ramirez MA, Schellart ANA, Saul AJ, 2012. Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments. Atmospheric Research 103: 80-95. [12] Harrison DL, Driscoll SJ, Kitchen M, 2000. Improving precipitation estimates from weather radar using quality control and correction techniques. Meteorological Applications 7: 135-144. [13] Harrison DL, Scovell RW, Kitchen M, 2009. High-resolution precipitation estimates for hydrological uses. Proceedings of the Institution of Civil Engineers - Water Management 162: 125-135.

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

Gutierrez, Marte

Colorado School of Mines conducted research and training in the development and validation of an advanced CO{sub 2} GS (Geological Sequestration) probabilistic simulation and risk assessment model. CO{sub 2} GS simulation and risk assessment is used to develop advanced numerical simulation models of the subsurface to forecast CO2 behavior and transport; optimize site operational practices; ensure site safety; and refine site monitoring, verification, and accounting efforts. As simulation models are refined with new data, the uncertainty surrounding the identified risks decrease, thereby providing more accurate risk assessment. The models considered the full coupling of multiple physical processes (geomechanical and fluidmore » flow) and describe the effects of stochastic hydro-mechanical (H-M) parameters on the modeling of CO{sub 2} flow and transport in fractured porous rocks. Graduate students were involved in the development and validation of the model that can be used to predict the fate, movement, and storage of CO{sub 2} in subsurface formations, and to evaluate the risk of potential leakage to the atmosphere and underground aquifers. The main major contributions from the project include the development of: 1) an improved procedure to rigorously couple the simulations of hydro-thermomechanical (H-M) processes involved in CO{sub 2} GS; 2) models for the hydro-mechanical behavior of fractured porous rocks with random fracture patterns; and 3) probabilistic methods to account for the effects of stochastic fluid flow and geomechanical properties on flow, transport, storage and leakage associated with CO{sub 2} GS. The research project provided the means to educate and train graduate students in the science and technology of CO{sub 2} GS, with a focus on geologic storage. Specifically, the training included the investigation of an advanced CO{sub 2} GS simulation and risk assessment model that can be used to predict the fate, movement, and storage of CO{sub 2} in underground formations, and the evaluation of the risk of potential CO{sub 2} leakage to the atmosphere and underground aquifers.« less

Universal Hitting Time Statistics for Integrable Flows

NASA Astrophysics Data System (ADS)

Dettmann, Carl P.; Marklof, Jens; Strömbergsson, Andreas

2017-02-01

The perceived randomness in the time evolution of "chaotic" dynamical systems can be characterized by universal probabilistic limit laws, which do not depend on the fine features of the individual system. One important example is the Poisson law for the times at which a particle with random initial data hits a small set. This was proved in various settings for dynamical systems with strong mixing properties. The key result of the present study is that, despite the absence of mixing, the hitting times of integrable flows also satisfy universal limit laws which are, however, not Poisson. We describe the limit distributions for "generic" integrable flows and a natural class of target sets, and illustrate our findings with two examples: the dynamics in central force fields and ellipse billiards. The convergence of the hitting time process follows from a new equidistribution theorem in the space of lattices, which is of independent interest. Its proof exploits Ratner's measure classification theorem for unipotent flows, and extends earlier work of Elkies and McMullen.

Statistical Inference of a RANS closure for a Jet-in-Crossflow simulation

NASA Astrophysics Data System (ADS)

Heyse, Jan; Edeling, Wouter; Iaccarino, Gianluca

2016-11-01

The jet-in-crossflow is found in several engineering applications, such as discrete film cooling for turbine blades, where a coolant injected through hols in the blade's surface protects the component from the hot gases leaving the combustion chamber. Experimental measurements using MRI techniques have been completed for a single hole injection into a turbulent crossflow, providing full 3D averaged velocity field. For such flows of engineering interest, Reynolds-Averaged Navier-Stokes (RANS) turbulence closure models are often the only viable computational option. However, RANS models are known to provide poor predictions in the region close to the injection point. Since these models are calibrated on simple canonical flow problems, the obtained closure coefficient estimates are unlikely to extrapolate well to more complex flows. We will therefore calibrate the parameters of a RANS model using statistical inference techniques informed by the experimental jet-in-crossflow data. The obtained probabilistic parameter estimates can in turn be used to compute flow fields with quantified uncertainty. Stanford Graduate Fellowship in Science and Engineering.

Robust identification of polyethylene terephthalate (PET) plastics through Bayesian decision.

PubMed

Zulkifley, Mohd Asyraf; Mustafa, Mohd Marzuki; Hussain, Aini; Mustapha, Aouache; Ramli, Suzaimah

2014-01-01

Recycling is one of the most efficient methods for environmental friendly waste management. Among municipal wastes, plastics are the most common material that can be easily recycled and polyethylene terephthalate (PET) is one of its major types. PET material is used in consumer goods packaging such as drinking bottles, toiletry containers, food packaging and many more. Usually, a recycling process is tailored to a specific material for optimal purification and decontamination to obtain high grade recyclable material. The quantity and quality of the sorting process are limited by the capacity of human workers that suffer from fatigue and boredom. Several automated sorting systems have been proposed in the literature that include using chemical, proximity and vision sensors. The main advantages of vision based sensors are its environmentally friendly approach, non-intrusive detection and capability of high throughput. However, the existing methods rely heavily on deterministic approaches that make them less accurate as the variations in PET plastic waste appearance are too high. We proposed a probabilistic approach of modeling the PET material by analyzing the reflection region and its surrounding. Three parameters are modeled by Gaussian and exponential distributions: color, size and distance of the reflection region. The final classification is made through a supervised training method of likelihood ratio test. The main novelty of the proposed method is the probabilistic approach in integrating various PET material signatures that are contaminated by stains under constant lighting changes. The system is evaluated by using four performance metrics: precision, recall, accuracy and error. Our system performed the best in all evaluation metrics compared to the benchmark methods. The system can be further improved by fusing all neighborhood information in decision making and by implementing the system in a graphics processing unit for faster processing speed.

Robust Identification of Polyethylene Terephthalate (PET) Plastics through Bayesian Decision

PubMed Central

Zulkifley, Mohd Asyraf; Mustafa, Mohd Marzuki; Hussain, Aini; Mustapha, Aouache; Ramli, Suzaimah

2014-01-01

Recycling is one of the most efficient methods for environmental friendly waste management. Among municipal wastes, plastics are the most common material that can be easily recycled and polyethylene terephthalate (PET) is one of its major types. PET material is used in consumer goods packaging such as drinking bottles, toiletry containers, food packaging and many more. Usually, a recycling process is tailored to a specific material for optimal purification and decontamination to obtain high grade recyclable material. The quantity and quality of the sorting process are limited by the capacity of human workers that suffer from fatigue and boredom. Several automated sorting systems have been proposed in the literature that include using chemical, proximity and vision sensors. The main advantages of vision based sensors are its environmentally friendly approach, non-intrusive detection and capability of high throughput. However, the existing methods rely heavily on deterministic approaches that make them less accurate as the variations in PET plastic waste appearance are too high. We proposed a probabilistic approach of modeling the PET material by analyzing the reflection region and its surrounding. Three parameters are modeled by Gaussian and exponential distributions: color, size and distance of the reflection region. The final classification is made through a supervised training method of likelihood ratio test. The main novelty of the proposed method is the probabilistic approach in integrating various PET material signatures that are contaminated by stains under constant lighting changes. The system is evaluated by using four performance metrics: precision, recall, accuracy and error. Our system performed the best in all evaluation metrics compared to the benchmark methods. The system can be further improved by fusing all neighborhood information in decision making and by implementing the system in a graphics processing unit for faster processing speed. PMID:25485630

Turbulent transport with intermittency: Expectation of a scalar concentration.

PubMed

Rast, Mark Peter; Pinton, Jean-François; Mininni, Pablo D

2016-04-01

Scalar transport by turbulent flows is best described in terms of Lagrangian parcel motions. Here we measure the Eulerian distance travel along Lagrangian trajectories in a simple point vortex flow to determine the probabilistic impulse response function for scalar transport in the absence of molecular diffusion. As expected, the mean squared Eulerian displacement scales ballistically at very short times and diffusively for very long times, with the displacement distribution at any given time approximating that of a random walk. However, significant deviations in the displacement distributions from Rayleigh are found. The probability of long distance transport is reduced over inertial range time scales due to spatial and temporal intermittency. This can be modeled as a series of trapping events with durations uniformly distributed below the Eulerian integral time scale. The probability of long distance transport is, on the other hand, enhanced beyond that of the random walk for both times shorter than the Lagrangian integral time and times longer than the Eulerian integral time. The very short-time enhancement reflects the underlying Lagrangian velocity distribution, while that at very long times results from the spatial and temporal variation of the flow at the largest scales. The probabilistic impulse response function, and with it the expectation value of the scalar concentration at any point in space and time, can be modeled using only the evolution of the lowest spatial wave number modes (the mean and the lowest harmonic) and an eddy based constrained random walk that captures the essential velocity phase relations associated with advection by vortex motions. Preliminary examination of Lagrangian tracers in three-dimensional homogeneous isotropic turbulence suggests that transport in that setting can be similarly modeled.

Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors

NASA Astrophysics Data System (ADS)

McInerney, David; Thyer, Mark; Kavetski, Dmitri; Lerat, Julien; Kuczera, George

2017-03-01

Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. This study focuses on approaches for representing error heteroscedasticity with respect to simulated streamflow, i.e., the pattern of larger errors in higher streamflow predictions. We evaluate eight common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter λ) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and the United States, and two lumped hydrological models. Performance is quantified using predictive reliability, precision, and volumetric bias metrics. We find the choice of heteroscedastic error modeling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with λ of 0.2 and 0.5, and the log scheme (λ = 0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Paradoxically, calibration of λ is often counterproductive: in perennial catchments, it tends to overfit low flows at the expense of abysmal precision in high flows. The log-sinh transformation is dominated by the simpler Pareto optimal schemes listed above. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California

USGS Publications Warehouse

Guymon, Gary L.; Yen, Chung-Cheng

1990-01-01

The applicability of a deterministic-probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two-layer deterministic model that is cascaded with a two-point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source-sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two-point probability method.

An efficient deterministic-probabilistic approach to modeling regional groundwater flow: 2. Application to Owens Valley, California

NASA Astrophysics Data System (ADS)

Guymon, Gary L.; Yen, Chung-Cheng

1990-07-01

The applicability of a deterministic-probabilistic model for predicting water tables in southern Owens Valley, California, is evaluated. The model is based on a two-layer deterministic model that is cascaded with a two-point probability model. To reduce the potentially large number of uncertain variables in the deterministic model, lumping of uncertain variables was evaluated by sensitivity analysis to reduce the total number of uncertain variables to three variables: hydraulic conductivity, storage coefficient or specific yield, and source-sink function. Results demonstrate that lumping of uncertain parameters reduces computational effort while providing sufficient precision for the case studied. Simulated spatial coefficients of variation for water table temporal position in most of the basin is small, which suggests that deterministic models can predict water tables in these areas with good precision. However, in several important areas where pumping occurs or the geology is complex, the simulated spatial coefficients of variation are over estimated by the two-point probability method.

A Probabilistic System Analysis of Intelligent Propulsion System Technologies

NASA Technical Reports Server (NTRS)

Tong, Michael T.

2007-01-01

NASA s Intelligent Propulsion System Technology (Propulsion 21) project focuses on developing adaptive technologies that will enable commercial gas turbine engines to produce fewer emissions and less noise while increasing reliability. It features adaptive technologies that have included active tip-clearance control for turbine and compressor, active combustion control, turbine aero-thermal and flow control, and enabling technologies such as sensors which are reliable at high operating temperatures and are minimally intrusive. A probabilistic system analysis is performed to evaluate the impact of these technologies on aircraft CO2 (directly proportional to fuel burn) and LTO (landing and takeoff) NO(x) reductions. A 300-passenger aircraft, with two 396-kN thrust (85,000-pound) engines is chosen for the study. The results show that NASA s Intelligent Propulsion System technologies have the potential to significantly reduce the CO2 and NO(x) emissions. The results are used to support informed decisionmaking on the development of the intelligent propulsion system technology portfolio for CO2 and NO(x) reductions.

Probabilistic Tsunami Hazard Assessment: the Seaside, Oregon Pilot Study

NASA Astrophysics Data System (ADS)

Gonzalez, F. I.; Geist, E. L.; Synolakis, C.; Titov, V. V.

2004-12-01

A pilot study of Seaside, Oregon is underway, to develop methodologies for probabilistic tsunami hazard assessments that can be incorporated into Flood Insurance Rate Maps (FIRMs) developed by FEMA's National Flood Insurance Program (NFIP). Current NFIP guidelines for tsunami hazard assessment rely on the science, technology and methodologies developed in the 1970s; although generally regarded as groundbreaking and state-of-the-art for its time, this approach is now superseded by modern methods that reflect substantial advances in tsunami research achieved in the last two decades. In particular, post-1990 technical advances include: improvements in tsunami source specification; improved tsunami inundation models; better computational grids by virtue of improved bathymetric and topographic databases; a larger database of long-term paleoseismic and paleotsunami records and short-term, historical earthquake and tsunami records that can be exploited to develop improved probabilistic methodologies; better understanding of earthquake recurrence and probability models. The NOAA-led U.S. National Tsunami Hazard Mitigation Program (NTHMP), in partnership with FEMA, USGS, NSF and Emergency Management and Geotechnical agencies of the five Pacific States, incorporates these advances into site-specific tsunami hazard assessments for coastal communities in Alaska, California, Hawaii, Oregon and Washington. NTHMP hazard assessment efforts currently focus on developing deterministic, "credible worst-case" scenarios that provide valuable guidance for hazard mitigation and emergency management. The NFIP focus, on the other hand, is on actuarial needs that require probabilistic hazard assessments such as those that characterize 100- and 500-year flooding events. There are clearly overlaps in NFIP and NTHMP objectives. NTHMP worst-case scenario assessments that include an estimated probability of occurrence could benefit the NFIP; NFIP probabilistic assessments of 100- and 500-yr events could benefit the NTHMP. The joint NFIP/NTHMP pilot study at Seaside, Oregon is organized into three closely related components: Probabilistic, Modeling, and Impact studies. Probabilistic studies (Geist, et al., this session) are led by the USGS and include the specification of near- and far-field seismic tsunami sources and their associated probabilities. Modeling studies (Titov, et al., this session) are led by NOAA and include the development and testing of a Seaside tsunami inundation model and an associated database of computed wave height and flow velocity fields. Impact studies (Synolakis, et al., this session) are led by USC and include the computation and analyses of indices for the categorization of hazard zones. The results of each component study will be integrated to produce a Seaside tsunami hazard map. This presentation will provide a brief overview of the project and an update on progress, while the above-referenced companion presentations will provide details on the methods used and the preliminary results obtained by each project component.

The Study of the Relationship between Probabilistic Design and Axiomatic Design Methodology. Volume 2

NASA Technical Reports Server (NTRS)

Onwubiko, Chin-Yere; Onyebueke, Landon

1996-01-01

The structural design, or the design of machine elements, has been traditionally based on deterministic design methodology. The deterministic method considers all design parameters to be known with certainty. This methodology is, therefore, inadequate to design complex structures that are subjected to a variety of complex, severe loading conditions. A nonlinear behavior that is dependent on stress, stress rate, temperature, number of load cycles, and time is observed on all components subjected to complex conditions. These complex conditions introduce uncertainties; hence, the actual factor of safety margin remains unknown. In the deterministic methodology, the contingency of failure is discounted; hence, there is a use of a high factor of safety. It may be most useful in situations where the design structures are simple. The probabilistic method is concerned with the probability of non-failure performance of structures or machine elements. It is much more useful in situations where the design is characterized by complex geometry, possibility of catastrophic failure, sensitive loads and material properties. Also included: Comparative Study of the use of AGMA Geometry Factors and Probabilistic Design Methodology in the Design of Compact Spur Gear Set.

SHM-Based Probabilistic Fatigue Life Prediction for Bridges Based on FE Model Updating

PubMed Central

Lee, Young-Joo; Cho, Soojin

2016-01-01

Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and evaluate the long-term structural performance of bridges. For example, SHM data can be used to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as mode shapes and natural frequencies, based on the ambient vibration under passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal properties; and (3) predicting the probabilistic fatigue life using the updated FE model. The proposed method is demonstrated by application to a numerical model of a bridge, and the impact of FE model updating on the bridge fatigue life is discussed. PMID:26950125

A Comparison of Traditional, Step-Path, and Geostatistical Techniques in the Stability Analysis of a Large Open Pit

NASA Astrophysics Data System (ADS)

Mayer, J. M.; Stead, D.

2017-04-01

With the increased drive towards deeper and more complex mine designs, geotechnical engineers are often forced to reconsider traditional deterministic design techniques in favour of probabilistic methods. These alternative techniques allow for the direct quantification of uncertainties within a risk and/or decision analysis framework. However, conventional probabilistic practices typically discretize geological materials into discrete, homogeneous domains, with attributes defined by spatially constant random variables, despite the fact that geological media display inherent heterogeneous spatial characteristics. This research directly simulates this phenomenon using a geostatistical approach, known as sequential Gaussian simulation. The method utilizes the variogram which imposes a degree of controlled spatial heterogeneity on the system. Simulations are constrained using data from the Ok Tedi mine site in Papua New Guinea and designed to randomly vary the geological strength index and uniaxial compressive strength using Monte Carlo techniques. Results suggest that conventional probabilistic techniques have a fundamental limitation compared to geostatistical approaches, as they fail to account for the spatial dependencies inherent to geotechnical datasets. This can result in erroneous model predictions, which are overly conservative when compared to the geostatistical results.

A Novel Probabilistic Multi-Scale Modeling and Sensing Framework for Fatigue Life Prediction of Aerospace Structures and Materials: DCT Project

DTIC Science & Technology

2012-08-25

Accel- erated Crystal Plasticity FEM Simulations (submitted). 5. M. Anahid, M. Samal and S. Ghosh, Dwell fatigue crack nucleation model based on using...4] M. Anahid, M. K. Samal , and S. Ghosh. Dwell fatigue crack nucleation model based on crystal plasticity finite element simulations of

A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

PubMed

Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

2015-01-01

Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

Why do Cross-Flow Turbines Stall?

NASA Astrophysics Data System (ADS)

Cavagnaro, Robert; Strom, Benjamin; Polagye, Brian

2015-11-01

Hydrokinetic turbines are prone to instability and stall near their peak operating points under torque control. Understanding the physics of turbine stall may help to mitigate this undesirable occurrence and improve the robustness of torque controllers. A laboratory-scale two-bladed cross-flow turbine operating at a chord-based Reynolds number ~ 3 ×104 is shown to stall at a critical tip-speed ratio. Experiments are conducting bringing the turbine to this critical speed in a recirculating current flume by increasing resistive torque and allowing the rotor to rapidly decelerate while monitoring inflow velocity, torque, and drag. The turbine stalls probabilistically with a distribution generated from hundreds of such events. A machine learning algorithm identifies stall events and indicates the effectiveness of available measurements or combinations of measurements as predictors. Bubble flow visualization and PIV are utilized to observe fluid conditions during stall events including the formation, separation, and advection of leading-edge vortices involved in the stall process.

Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables

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

DallAnese, Emiliano; Baker, Kyri; Summers, Tyler

This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrarymore » distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers.« less

Benchmarking computational fluid dynamics models of lava flow simulation for hazard assessment, forecasting, and risk management

USGS Publications Warehouse

Dietterich, Hannah; Lev, Einat; Chen, Jiangzhi; Richardson, Jacob A.; Cashman, Katharine V.

2017-01-01

Numerical simulations of lava flow emplacement are valuable for assessing lava flow hazards, forecasting active flows, designing flow mitigation measures, interpreting past eruptions, and understanding the controls on lava flow behavior. Existing lava flow models vary in simplifying assumptions, physics, dimensionality, and the degree to which they have been validated against analytical solutions, experiments, and natural observations. In order to assess existing models and guide the development of new codes, we conduct a benchmarking study of computational fluid dynamics (CFD) models for lava flow emplacement, including VolcFlow, OpenFOAM, FLOW-3D, COMSOL, and MOLASSES. We model viscous, cooling, and solidifying flows over horizontal planes, sloping surfaces, and into topographic obstacles. We compare model results to physical observations made during well-controlled analogue and molten basalt experiments, and to analytical theory when available. Overall, the models accurately simulate viscous flow with some variability in flow thickness where flows intersect obstacles. OpenFOAM, COMSOL, and FLOW-3D can each reproduce experimental measurements of cooling viscous flows, and OpenFOAM and FLOW-3D simulations with temperature-dependent rheology match results from molten basalt experiments. We assess the goodness-of-fit of the simulation results and the computational cost. Our results guide the selection of numerical simulation codes for different applications, including inferring emplacement conditions of past lava flows, modeling the temporal evolution of ongoing flows during eruption, and probabilistic assessment of lava flow hazard prior to eruption. Finally, we outline potential experiments and desired key observational data from future flows that would extend existing benchmarking data sets.

Hydrogeologic Unit Flow Characterization Using Transition Probability Geostatistics

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

Jones, N L; Walker, J R; Carle, S F

2003-11-21

This paper describes a technique for applying the transition probability geostatistics method for stochastic simulation to a MODFLOW model. Transition probability geostatistics has several advantages over traditional indicator kriging methods including a simpler and more intuitive framework for interpreting geologic relationships and the ability to simulate juxtapositional tendencies such as fining upwards sequences. The indicator arrays generated by the transition probability simulation are converted to layer elevation and thickness arrays for use with the new Hydrogeologic Unit Flow (HUF) package in MODFLOW 2000. This makes it possible to preserve complex heterogeneity while using reasonably sized grids. An application of themore » technique involving probabilistic capture zone delineation for the Aberjona Aquifer in Woburn, Ma. is included.« less

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

Dall'Anese, Emiliano; Baker, Kyri; Summers, Tyler

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative boundsmore » that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.« less

Source mechanisms of volcanic tsunamis.

PubMed

Paris, Raphaël

2015-10-28

Volcanic tsunamis are generated by a variety of mechanisms, including volcano-tectonic earthquakes, slope instabilities, pyroclastic flows, underwater explosions, shock waves and caldera collapse. In this review, we focus on the lessons that can be learnt from past events and address the influence of parameters such as volume flux of mass flows, explosion energy or duration of caldera collapse on tsunami generation. The diversity of waves in terms of amplitude, period, form, dispersion, etc. poses difficulties for integration and harmonization of sources to be used for numerical models and probabilistic tsunami hazard maps. In many cases, monitoring and warning of volcanic tsunamis remain challenging (further technical and scientific developments being necessary) and must be coupled with policies of population preparedness. © 2015 The Author(s).

Initial Probabilistic Evaluation of Reactor Pressure Vessel Fracture with Grizzly and Raven

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

Spencer, Benjamin; Hoffman, William; Sen, Sonat

2015-10-01

The Grizzly code is being developed with the goal of creating a general tool that can be applied to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled reactor pressure vessels (RPVs). Grizzly can be used to model the thermal/mechanical response of an RPV under transient conditions that would be observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtainmore » stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. These capabilities have been demonstrated previously. A typical RPV is likely to contain a large population of pre-existing flaws introduced during the manufacturing process. This flaw population is characterized stastistically through probability density functions of the flaw distributions. The use of probabilistic techniques is necessary to assess the likelihood of crack initiation during a transient event. This report documents initial work to perform probabilistic analysis of RPV fracture during a PTS event using a combination of the RAVEN risk analysis code and Grizzly. This work is limited in scope, considering only a single flaw with deterministic geometry, but with uncertainty introduced in the parameters that influence fracture toughness. These results are benchmarked against equivalent models run in the FAVOR code. When fully developed, the RAVEN/Grizzly methodology for modeling probabilistic fracture in RPVs will provide a general capability that can be used to consider a wider variety of vessel and flaw conditions that are difficult to consider with current tools. In addition, this will provide access to advanced probabilistic techniques provided by RAVEN, including adaptive sampling and parallelism, which can dramatically decrease run times.« less

Proceedings, Seminar on Probabilistic Methods in Geotechnical Engineering

NASA Astrophysics Data System (ADS)

Hynes-Griffin, M. E.; Buege, L. L.

1983-09-01

Contents: Applications of Probabilistic Methods in Geotechnical Engineering; Probabilistic Seismic and Geotechnical Evaluation at a Dam Site; Probabilistic Slope Stability Methodology; Probability of Liquefaction in a 3-D Soil Deposit; Probabilistic Design of Flood Levees; Probabilistic and Statistical Methods for Determining Rock Mass Deformability Beneath Foundations: An Overview; Simple Statistical Methodology for Evaluating Rock Mechanics Exploration Data; New Developments in Statistical Techniques for Analyzing Rock Slope Stability.

Life Prediction of Spent Fuel Storage Canister Material

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

Ballinger, Ronald

The original purpose of this project was to develop a probabilistic model for SCC-induced failure of spent fuel storage canisters, exposed to a salt-air environment in the temperature range 30-70°C for periods up to and exceeding 100 years. The nature of this degradation process, which involves multiple degradation mechanisms, combined with variable and uncertain environmental conditions dictates a probabilistic approach to life prediction. A final report for the original portion of the project was submitted earlier. However, residual stress measurements for as-welded and repair welds could not be performed within the original time of the project. As a result ofmore » this, a no-cost extension was granted in order to complete these tests. In this report, we report on the results of residual stress measurements.« less

The influence of the free space environment on the superlight-weight thermal protection system: conception, methods, and risk analysis

NASA Astrophysics Data System (ADS)

Yatsenko, Vitaliy; Falchenko, Iurii; Fedorchuk, Viktor; Petrushynets, Lidiia

2016-07-01

This report focuses on the results of the EU project "Superlight-weight thermal protection system for space application (LIGHT-TPS)". The bottom line is an analysis of influence of the free space environment on the superlight-weight thermal protection system (TPS). This report focuses on new methods that based on the following models: synergetic, physical, and computational. This report concentrates on four approaches. The first concerns the synergetic approach. The synergetic approach to the solution of problems of self-controlled synthesis of structures and creation of self-organizing technologies is considered in connection with the super-problem of creation of materials with new functional properties. Synergetics methods and mathematical design are considered according to actual problems of material science. The second approach describes how the optimization methods can be used to determine material microstructures with optimized or targeted properties. This technique enables one to find unexpected microstructures with exotic behavior (e.g., negative thermal expansion coefficients). The third approach concerns the dynamic probabilistic risk analysis of TPS l elements with complex characterizations for damages using a physical model of TPS system and a predictable level of ionizing radiation and space weather. Focusing is given mainly on the TPS model, mathematical models for dynamic probabilistic risk assessment and software for the modeling and prediction of the influence of the free space environment. The probabilistic risk assessment method for TPS is presented considering some deterministic and stochastic factors. The last approach concerns results of experimental research of the temperature distribution on the surface of the honeycomb sandwich panel size 150 x 150 x 20 mm at the diffusion welding in vacuum are considered. An equipment, which provides alignment of temperature fields in a product for the formation of equal strength of welded joints is considered. Many tasks in computational materials science can be posed as optimization problems. This technique enables one to find unexpected microstructures with exotic behavior (e.g., negative thermal expansion coefficients). The last approach is concerned with the generation of realizations of materials with specified but limited microstructural information: an intriguing inverse problem of both fundamental and practical importance. Computational models based upon the theories of molecular dynamics or quantum mechanics would enable the prediction and modification of fundamental materials properties. This problem is solved using deterministic and stochastic optimization techniques. The main optimization approaches in the frame of the EU project "Superlight-weight thermal protection system for space application" are discussed. Optimization approach to the alloys for obtaining materials with required properties using modeling techniques and experimental data will be also considered. This report is supported by the EU project "Superlight-weight thermal protection system for space application (LIGHT-TPS)"

Differential reliability : probabilistic engineering applied to wood members in bending-tension

Treesearch

Stanley K. Suddarth; Frank E. Woeste; William L. Galligan

1978-01-01

Reliability analysis is a mathematical technique for appraising the design and materials of engineered structures to provide a quantitative estimate of probability of failure. Two or more cases which are similar in all respects but one may be analyzed by this method; the contrast between the probabilities of failure for these cases allows strong analytical focus on the...

Development of a Physically-Based Methodology for Predicting Material Variability in Fatigue Crack Initiation and Growth Response

DTIC Science & Technology

2004-12-01

64, (2000), Federal Aviation Administration, Washington, DC. 14. Y.T. Wu, M.P. Enright, and H.R. Millwater , "Probabilistic Methods for Design...Assessment of Reliability with Inspection," AIAA Journal, AIAA, 40 (5), (2002), 937-946. 15. M.P. Enright, L. Huyse, R.C. McClung, and H.R. Millwater

Developing an Event-Tree Probabilistic Tsunami Inundation Model for NE Atlantic Coasts: Application to a Case Study

NASA Astrophysics Data System (ADS)

Omira, R.; Matias, L.; Baptista, M. A.

2016-12-01

This study constitutes a preliminary assessment of probabilistic tsunami inundation in the NE Atlantic region. We developed an event-tree approach to calculate the likelihood of tsunami flood occurrence and exceedance of a specific near-shore wave height for a given exposure time. Only tsunamis of tectonic origin are considered here, taking into account local, regional, and far-field sources. The approach used here consists of an event-tree method that gathers probability models for seismic sources, tsunami numerical modeling, and statistical methods. It also includes a treatment of aleatoric uncertainties related to source location and tidal stage. Epistemic uncertainties are not addressed in this study. The methodology is applied to the coastal test-site of Sines located in the NE Atlantic coast of Portugal. We derive probabilistic high-resolution maximum wave amplitudes and flood distributions for the study test-site considering 100- and 500-year exposure times. We find that the probability that maximum wave amplitude exceeds 1 m somewhere along the Sines coasts reaches about 60 % for an exposure time of 100 years and is up to 97 % for an exposure time of 500 years. The probability of inundation occurrence (flow depth >0 m) varies between 10 % and 57 %, and from 20 % up to 95 % for 100- and 500-year exposure times, respectively. No validation has been performed here with historical tsunamis. This paper illustrates a methodology through a case study, which is not an operational assessment.

Probabilistic Hazard Estimation at a Densely Urbanised Area: the Neaples Volcanoes

NASA Astrophysics Data System (ADS)

de Natale, G.; Mastrolorenzo, G.; Panizza, A.; Pappalardo, L.; Claudia, T.

2005-12-01

The Neaples volcanic area (Southern Italy), including Vesuvius, Campi Flegrei caldera and Ischia island, is the highest risk one in the World, where more than 2 million people live within about 10 km from an active volcanic vent. Such an extreme risk calls for accurate methodologies aimed to quantify it, in a probabilistic way, considering all the available volcanological information as well as modelling results. In fact, simple hazard maps based on the observation of deposits from past eruptions have the major problem that eruptive history generally samples a very limited number of possible outcomes, thus resulting almost meaningless to get the event probability in the area. This work describes a methodology making the best use (from a Bayesian point of view) of volcanological data and modelling results, to compute probabilistic hazard maps from multi-vent explosive eruptions. The method, which follows an approach recently developed by the same authors for pyroclastic flows hazard, has been here improved and extended to compute also fall-out hazard. The application of the method to the Neapolitan volcanic area, including the densely populated city of Naples, allows, for the first time, to get a global picture of the areal distribution for the main hazards from multi-vent explosive eruptions. From a joint consideration of the hazard contributions from all the three volcanic areas, new insight on the volcanic hazard distribution emerges, which will have strong implications for urban and emergency planning in the area.

Modular neuron-based body estimation: maintaining consistency over different limbs, modalities, and frames of reference

PubMed Central

Ehrenfeld, Stephan; Herbort, Oliver; Butz, Martin V.

2013-01-01

This paper addresses the question of how the brain maintains a probabilistic body state estimate over time from a modeling perspective. The neural Modular Modality Frame (nMMF) model simulates such a body state estimation process by continuously integrating redundant, multimodal body state information sources. The body state estimate itself is distributed over separate, but bidirectionally interacting modules. nMMF compares the incoming sensory and present body state information across the interacting modules and fuses the information sources accordingly. At the same time, nMMF enforces body state estimation consistency across the modules. nMMF is able to detect conflicting sensory information and to consequently decrease the influence of implausible sensor sources on the fly. In contrast to the previously published Modular Modality Frame (MMF) model, nMMF offers a biologically plausible neural implementation based on distributed, probabilistic population codes. Besides its neural plausibility, the neural encoding has the advantage of enabling (a) additional probabilistic information flow across the separate body state estimation modules and (b) the representation of arbitrary probability distributions of a body state. The results show that the neural estimates can detect and decrease the impact of false sensory information, can propagate conflicting information across modules, and can improve overall estimation accuracy due to additional module interactions. Even bodily illusions, such as the rubber hand illusion, can be simulated with nMMF. We conclude with an outlook on the potential of modeling human data and of invoking goal-directed behavioral control. PMID:24191151

Probabilistic load simulation: Code development status

NASA Astrophysics Data System (ADS)

Newell, J. F.; Ho, H.

1991-05-01

The objective of the Composite Load Spectra (CLS) project is to develop generic load models to simulate the composite load spectra that are included in space propulsion system components. The probabilistic loads thus generated are part of the probabilistic design analysis (PDA) of a space propulsion system that also includes probabilistic structural analyses, reliability, and risk evaluations. Probabilistic load simulation for space propulsion systems demands sophisticated probabilistic methodology and requires large amounts of load information and engineering data. The CLS approach is to implement a knowledge based system coupled with a probabilistic load simulation module. The knowledge base manages and furnishes load information and expertise and sets up the simulation runs. The load simulation module performs the numerical computation to generate the probabilistic loads with load information supplied from the CLS knowledge base.

Communicating uncertainty in hydrological forecasts: mission impossible?

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

2010-05-01

Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted scenarios, is essential. We believe that the efficient communication of uncertainty in hydro-meteorological forecasts is not a mission impossible. Questions remaining unanswered in probabilistic hydrological forecasting should not neutralize the goal of such a mission, and the suspense kept should instead act as a catalyst for overcoming the remaining challenges.

Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times

NASA Astrophysics Data System (ADS)

Engeland, Kolbjorn; Steinsland, Ingelin

2014-05-01

This study introduces a methodology for the construction of probabilistic inflow forecasts for multiple catchments and lead times, and investigates criterions for evaluation of multi-variate forecasts. A post-processing approach is used, and a Gaussian model is applied for transformed variables. The post processing model has two main components, the mean model and the dependency model. The mean model is used to estimate the marginal distributions for forecasted inflow for each catchment and lead time, whereas the dependency models was used to estimate the full multivariate distribution of forecasts, i.e. co-variances between catchments and lead times. In operational situations, it is a straightforward task to use the models to sample inflow ensembles which inherit the dependencies between catchments and lead times. The methodology was tested and demonstrated in the river systems linked to the Ulla-Førre hydropower complex in southern Norway, where simultaneous probabilistic forecasts for five catchments and ten lead times were constructed. The methodology exhibits sufficient flexibility to utilize deterministic flow forecasts from a numerical hydrological model as well as statistical forecasts such as persistent forecasts and sliding window climatology forecasts. It also deals with variation in the relative weights of these forecasts with both catchment and lead time. When evaluating predictive performance in original space using cross validation, the case study found that it is important to include the persistent forecast for the initial lead times and the hydrological forecast for medium-term lead times. Sliding window climatology forecasts become more important for the latest lead times. Furthermore, operationally important features in this case study such as heteroscedasticity, lead time varying between lead time dependency and lead time varying between catchment dependency are captured. Two criterions were used for evaluating the added value of the dependency model. The first one was the Energy score (ES) that is a multi-dimensional generalization of continuous rank probability score (CRPS). ES was calculated for all lead-times and catchments together, for each catchment across all lead times and for each lead time across all catchments. The second criterion was to use CRPS for forecasted inflows accumulated over several lead times and catchments. The results showed that ES was not very sensitive to correct covariance structure, whereas CRPS for accumulated flows where more suitable for evaluating the dependency model. This indicates that it is more appropriate to evaluate relevant univariate variables that depends on the dependency structure then to evaluate the multivariate forecast directly.

Probabilistic risk assessment for CO2 storage in geological formations: robust design and support for decision making under uncertainty

NASA Astrophysics Data System (ADS)

Oladyshkin, Sergey; Class, Holger; Helmig, Rainer; Nowak, Wolfgang

2010-05-01

CO2 storage in geological formations is currently being discussed intensively as a technology for mitigating CO2 emissions. However, any large-scale application requires a thorough analysis of the potential risks. Current numerical simulation models are too expensive for probabilistic risk analysis and for stochastic approaches based on brute-force repeated simulation. Even single deterministic simulations may require parallel high-performance computing. The multiphase flow processes involved are too non-linear for quasi-linear error propagation and other simplified stochastic tools. As an alternative approach, we propose a massive stochastic model reduction based on the probabilistic collocation method. The model response is projected onto a orthogonal basis of higher-order polynomials to approximate dependence on uncertain parameters (porosity, permeability etc.) and design parameters (injection rate, depth etc.). This allows for a non-linear propagation of model uncertainty affecting the predicted risk, ensures fast computation and provides a powerful tool for combining design variables and uncertain variables into one approach based on an integrative response surface. Thus, the design task of finding optimal injection regimes explicitly includes uncertainty, which leads to robust designs of the non-linear system that minimize failure probability and provide valuable support for risk-informed management decisions. We validate our proposed stochastic approach by Monte Carlo simulation using a common 3D benchmark problem (Class et al. Computational Geosciences 13, 2009). A reasonable compromise between computational efforts and precision was reached already with second-order polynomials. In our case study, the proposed approach yields a significant computational speedup by a factor of 100 compared to Monte Carlo simulation. We demonstrate that, due to the non-linearity of the flow and transport processes during CO2 injection, including uncertainty in the analysis leads to a systematic and significant shift of predicted leakage rates towards higher values compared with deterministic simulations, affecting both risk estimates and the design of injection scenarios. This implies that, neglecting uncertainty can be a strong simplification for modeling CO2 injection, and the consequences can be stronger than when neglecting several physical phenomena (e.g. phase transition, convective mixing, capillary forces etc.). The authors would like to thank the German Research Foundation (DFG) for financial support of the project within the Cluster of Excellence in Simulation Technology (EXC 310/1) at the University of Stuttgart. Keywords: polynomial chaos; CO2 storage; multiphase flow; porous media; risk assessment; uncertainty; integrative response surfaces

Probabilistic Tsunami Hazard Analysis

NASA Astrophysics Data System (ADS)

Thio, H. K.; Ichinose, G. A.; Somerville, P. G.; Polet, J.

2006-12-01

The recent tsunami disaster caused by the 2004 Sumatra-Andaman earthquake has focused our attention to the hazard posed by large earthquakes that occur under water, in particular subduction zone earthquakes, and the tsunamis that they generate. Even though these kinds of events are rare, the very large loss of life and material destruction caused by this earthquake warrant a significant effort towards the mitigation of the tsunami hazard. For ground motion hazard, Probabilistic Seismic Hazard Analysis (PSHA) has become a standard practice in the evaluation and mitigation of seismic hazard to populations in particular with respect to structures, infrastructure and lifelines. Its ability to condense the complexities and variability of seismic activity into a manageable set of parameters greatly facilitates the design of effective seismic resistant buildings but also the planning of infrastructure projects. Probabilistic Tsunami Hazard Analysis (PTHA) achieves the same goal for hazards posed by tsunami. There are great advantages of implementing such a method to evaluate the total risk (seismic and tsunami) to coastal communities. The method that we have developed is based on the traditional PSHA and therefore completely consistent with standard seismic practice. Because of the strong dependence of tsunami wave heights on bathymetry, we use a full waveform tsunami waveform computation in lieu of attenuation relations that are common in PSHA. By pre-computing and storing the tsunami waveforms at points along the coast generated for sets of subfaults that comprise larger earthquake faults, we can efficiently synthesize tsunami waveforms for any slip distribution on those faults by summing the individual subfault tsunami waveforms (weighted by their slip). This efficiency make it feasible to use Green's function summation in lieu of attenuation relations to provide very accurate estimates of tsunami height for probabilistic calculations, where one typically computes thousands of earthquake scenarios. We have carried out preliminary tsunami hazard calculations for different return periods for western North America and Hawaii based on thousands of earthquake scenarios around the Pacific rim and along the coast of North America. We will present tsunami hazard maps for several return periods and also discuss how to use these results for probabilistic inundation and runup mapping. Our knowledge of certain types of tsunami sources is very limited (e.g. submarine landslides), but a probabilistic framework for tsunami hazard evaluation can include even such sources and their uncertainties and present the overall hazard in a meaningful and consistent way.

The probabilistic nature of preferential choice.

PubMed

Rieskamp, Jörg

2008-11-01

Previous research has developed a variety of theories explaining when and why people's decisions under risk deviate from the standard economic view of expected utility maximization. These theories are limited in their predictive accuracy in that they do not explain the probabilistic nature of preferential choice, that is, why an individual makes different choices in nearly identical situations, or why the magnitude of these inconsistencies varies in different situations. To illustrate the advantage of probabilistic theories, three probabilistic theories of decision making under risk are compared with their deterministic counterparts. The probabilistic theories are (a) a probabilistic version of a simple choice heuristic, (b) a probabilistic version of cumulative prospect theory, and (c) decision field theory. By testing the theories with the data from three experimental studies, the superiority of the probabilistic models over their deterministic counterparts in predicting people's decisions under risk become evident. When testing the probabilistic theories against each other, decision field theory provides the best account of the observed behavior.

Overview of Future of Probabilistic Methods and RMSL Technology and the Probabilistic Methods Education Initiative for the US Army at the SAE G-11 Meeting

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.

2003-01-01

The SAE G-11 RMSL Division and Probabilistic Methods Committee meeting sponsored by the Picatinny Arsenal during March 1-3, 2004 at Westin Morristown, will report progress on projects for probabilistic assessment of Army system and launch an initiative for probabilistic education. The meeting features several Army and industry Senior executives and Ivy League Professor to provide an industry/government/academia forum to review RMSL technology; reliability and probabilistic technology; reliability-based design methods; software reliability; and maintainability standards. With over 100 members including members with national/international standing, the mission of the G-11s Probabilistic Methods Committee is to enable/facilitate rapid deployment of probabilistic technology to enhance the competitiveness of our industries by better, faster, greener, smarter, affordable and reliable product development.

Who is susceptible to conjunction fallacies in category-based induction?

PubMed

Feeney, Aidan; Shafto, Patrick; Dunning, Darren

2007-10-01

Recent evidence suggests that the conjunction fallacy observed in people's probabilistic reasoning is also to be found in their evaluations of inductive argument strength. We presented 130 participants with materials likely to produce a conjunction fallacy either by virtue of a shared categorical or a causal relationship between the categories in the argument. We also took a measure of participants' cognitive ability. We observed conjunction fallacies overall with both sets of materials but found an association with ability for the categorical materials only. Our results have implications for accounts of individual differences in reasoning, for the relevance theory of induction, and for the recent claim that causal knowledge is important in inductive reasoning.

Probabilistic structural mechanics research for parallel processing computers

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Martin, William R.

1991-01-01

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical.

Damage Tolerance and Reliability of Turbine Engine Components

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1999-01-01

This report describes a formal method to quantify structural damage tolerance and reliability in the presence of a multitude of uncertainties in turbine engine components. The method is based at the material behavior level where primitive variables with their respective scatter ranges are used to describe behavior. Computational simulation is then used to propagate the uncertainties to the structural scale where damage tolerance and reliability are usually specified. Several sample cases are described to illustrate the effectiveness, versatility, and maturity of the method. Typical results from this method demonstrate that it is mature and that it can be used to probabilistically evaluate turbine engine structural components. It may be inferred from the results that the method is suitable for probabilistically predicting the remaining life in aging or deteriorating structures, for making strategic projections and plans, and for achieving better, cheaper, faster products that give competitive advantages in world markets.

A Step Made Toward Designing Microelectromechanical System (MEMS) Structures With High Reliability

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

2003-01-01

The mechanical design of microelectromechanical systems-particularly for micropower generation applications-requires the ability to predict the strength capacity of load-carrying components over the service life of the device. These microdevices, which typically are made of brittle materials such as polysilicon, show wide scatter (stochastic behavior) in strength as well as a different average strength for different sized structures (size effect). These behaviors necessitate either costly and time-consuming trial-and-error designs or, more efficiently, the development of a probabilistic design methodology for MEMS. Over the years, the NASA Glenn Research Center s Life Prediction Branch has developed the CARES/Life probabilistic design methodology to predict the reliability of advanced ceramic components. In this study, done in collaboration with Johns Hopkins University, the ability of the CARES/Life code to predict the reliability of polysilicon microsized structures with stress concentrations is successfully demonstrated.

Assuring Life in Composite Systems

NASA Technical Reports Server (NTRS)

Chamis, Christos c.

2008-01-01

A computational simulation method is presented to assure life in composite systems by using dynamic buckling of smart composite shells as an example. The combined use of composite mechanics, finite element computer codes, and probabilistic analysis enable the effective assessment of the dynamic buckling load of smart composite shells. A universal plot is generated to estimate the dynamic buckling load of composite shells at various load rates and probabilities. The shell structure is also evaluated with smart fibers embedded in the plies right below the outer plies. The results show that, on the average, the use of smart fibers improved the shell buckling resistance by about 9% at different probabilities and delayed the buckling occurrence time. The probabilistic sensitivities results indicate that uncertainties in the fiber volume ratio and ply thickness have major effects on the buckling load. The uncertainties in the electric field strength and smart material volume fraction have moderate effects and thereby in the assured life of the shell.

Students’ difficulties in probabilistic problem-solving

NASA Astrophysics Data System (ADS)

Arum, D. P.; Kusmayadi, T. A.; Pramudya, I.

2018-03-01

There are many errors can be identified when students solving mathematics problems, particularly in solving the probabilistic problem. This present study aims to investigate students’ difficulties in solving the probabilistic problem. It focuses on analyzing and describing students errors during solving the problem. This research used the qualitative method with case study strategy. The subjects in this research involve ten students of 9th grade that were selected by purposive sampling. Data in this research involve students’ probabilistic problem-solving result and recorded interview regarding students’ difficulties in solving the problem. Those data were analyzed descriptively using Miles and Huberman steps. The results show that students have difficulties in solving the probabilistic problem and can be divided into three categories. First difficulties relate to students’ difficulties in understanding the probabilistic problem. Second, students’ difficulties in choosing and using appropriate strategies for solving the problem. Third, students’ difficulties with the computational process in solving the problem. Based on the result seems that students still have difficulties in solving the probabilistic problem. It means that students have not able to use their knowledge and ability for responding probabilistic problem yet. Therefore, it is important for mathematics teachers to plan probabilistic learning which could optimize students probabilistic thinking ability.

A method for characterizing late-season low-flow regime in the upper Grand Ronde River Basin, Oregon

USGS Publications Warehouse

Kelly, Valerie J.; White, Seth

2016-04-19

This report describes a method for estimating ecologically relevant low-flow metrics that quantify late‑season streamflow regime for ungaged sites in the upper Grande Ronde River Basin, Oregon. The analysis presented here focuses on sites sampled by the Columbia River Inter‑Tribal Fish Commission as part of their efforts to monitor habitat restoration to benefit spring Chinook salmon recovery in the basin. Streamflow data were provided by the U.S. Geological Survey and the Oregon Water Resources Department. Specific guidance was provided for selection of streamgages, development of probabilistic frequency distributions for annual 7-day low-flow events, and regionalization of the frequency curves based on multivariate analysis of watershed characteristics. Evaluation of the uncertainty associated with the various components of this protocol indicates that the results are reliable for the intended purpose of hydrologic classification to support ecological analysis of factors contributing to juvenile salmon success. They should not be considered suitable for more standard water-resource evaluations that require greater precision, especially those focused on management and forecasting of extreme low-flow conditions.

Real-time updating of the flood frequency distribution through data assimilation

NASA Astrophysics Data System (ADS)

Aguilar, Cristina; Montanari, Alberto; Polo, María-José

2017-07-01

We explore the memory properties of catchments for predicting the likelihood of floods based on observations of average flows in pre-flood seasons. Our approach assumes that flood formation is driven by the superimposition of short- and long-term perturbations. The former is given by the short-term meteorological forcing leading to infiltration and/or saturation excess, while the latter is originated by higher-than-usual storage in the catchment. To exploit the above sensitivity to long-term perturbations, a meta-Gaussian model and a data assimilation approach are implemented for updating the flood frequency distribution a season in advance. Accordingly, the peak flow in the flood season is predicted in probabilistic terms by exploiting its dependence on the average flow in the antecedent seasons. We focus on the Po River at Pontelagoscuro and the Danube River at Bratislava. We found that the shape of the flood frequency distribution is noticeably impacted by higher-than-usual flows occurring up to several months earlier. The proposed technique may allow one to reduce the uncertainty associated with the estimation of flood frequency.

Remote Attitude Measurement Techniques.

DTIC Science & Technology

1982-12-01

televison camera). The incident illumination produces a non-uniformity on the scanned side of the sensitive material which can be modeled as an...to compute the probabilistic attitude matrix. Fourth, the experiment will be conducted with the televison camera mounted on a machinists table, such... the optical axis does not necesarily pass through the center of the lens assembly and impact the center pixel in the active region of

A probabilistic Hu-Washizu variational principle

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Besterfield, G. H.

1987-01-01

A Probabilistic Hu-Washizu Variational Principle (PHWVP) for the Probabilistic Finite Element Method (PFEM) is presented. This formulation is developed for both linear and nonlinear elasticity. The PHWVP allows incorporation of the probabilistic distributions for the constitutive law, compatibility condition, equilibrium, domain and boundary conditions into the PFEM. Thus, a complete probabilistic analysis can be performed where all aspects of the problem are treated as random variables and/or fields. The Hu-Washizu variational formulation is available in many conventional finite element codes thereby enabling the straightforward inclusion of the probabilistic features into present codes.

Materials in the economy; material flows, scarcity, and the environment

USGS Publications Warehouse

Wagner, Lorie A.

2002-01-01

The importance of materials to the economy of the United States is described, including the levels of consumption and uses of materials. The paths (or flows) that materials take from extraction, through processing, to consumer products, and then final disposition are illustrated. Scarcity and environmental issues as they relate to the flow of materials are discussed. Examples for the three main themes of the report (material flows, scarcity, and the environment) are presented.

Taiwan industrial cooperation program technology transfer for low-level radioactive waste final disposal - phase I.

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

Knowlton, Robert G.; Cochran, John Russell; Arnold, Bill Walter

2007-01-01

Sandia National Laboratories and the Institute of Nuclear Energy Research, Taiwan have collaborated in a technology transfer program related to low-level radioactive waste (LLW) disposal in Taiwan. Phase I of this program included regulatory analysis of LLW final disposal, development of LLW disposal performance assessment capabilities, and preliminary performance assessments of two potential disposal sites. Performance objectives were based on regulations in Taiwan and comparisons to those in the United States. Probabilistic performance assessment models were constructed based on limited site data using software including GoldSim, BLT-MS, FEHM, and HELP. These software codes provided the probabilistic framework, container degradation, waste-formmore » leaching, groundwater flow, radionuclide transport, and cover infiltration simulation capabilities in the performance assessment. Preliminary performance assessment analyses were conducted for a near-surface disposal system and a mined cavern disposal system at two representative sites in Taiwan. Results of example calculations indicate peak simulated concentrations to a receptor within a few hundred years of LLW disposal, primarily from highly soluble, non-sorbing radionuclides.« less

Probabilistic seismic hazard estimates incorporating site effects - An example from Indiana, U.S.A

USGS Publications Warehouse

Hasse, J.S.; Park, C.H.; Nowack, R.L.; Hill, J.R.

2010-01-01

The U.S. Geological Survey (USGS) has published probabilistic earthquake hazard maps for the United States based on current knowledge of past earthquake activity and geological constraints on earthquake potential. These maps for the central and eastern United States assume standard site conditions with Swave velocities of 760 m/s in the top 30 m. For urban and infrastructure planning and long-term budgeting, the public is interested in similar probabilistic seismic hazard maps that take into account near-surface geological materials. We have implemented a probabilistic method for incorporating site effects into the USGS seismic hazard analysis that takes into account the first-order effects of the surface geologic conditions. The thicknesses of sediments, which play a large role in amplification, were derived from a P-wave refraction database with over 13, 000 profiles, and a preliminary geology-based velocity model was constructed from available information on S-wave velocities. An interesting feature of the preliminary hazard maps incorporating site effects is the approximate factor of two increases in the 1-Hz spectral acceleration with 2 percent probability of exceedance in 50 years for parts of the greater Indianapolis metropolitan region and surrounding parts of central Indiana. This effect is primarily due to the relatively thick sequence of sediments infilling ancient bedrock topography that has been deposited since the Pleistocene Epoch. As expected, the Late Pleistocene and Holocene depositional systems of the Wabash and Ohio Rivers produce additional amplification in the southwestern part of Indiana. Ground motions decrease, as would be expected, toward the bedrock units in south-central Indiana, where motions are significantly lower than the values on the USGS maps.

Safe Life Propulsion Design Technologies (3rd Generation Propulsion Research and Technology)

NASA Technical Reports Server (NTRS)

Ellis, Rod

2000-01-01

The tasks outlined in this viewgraph presentation on safe life propulsion design technologies (third generation propulsion research and technology) include the following: (1) Ceramic matrix composite (CMC) life prediction methods; (2) Life prediction methods for ultra high temperature polymer matrix composites for reusable launch vehicle (RLV) airframe and engine application; (3) Enabling design and life prediction technology for cost effective large-scale utilization of MMCs and innovative metallic material concepts; (4) Probabilistic analysis methods for brittle materials and structures; (5) Damage assessment in CMC propulsion components using nondestructive characterization techniques; and (6) High temperature structural seals for RLV applications.

Channeling at the base of the lithosphere during the lateral flow of plume material beneath flow line hot spots

NASA Astrophysics Data System (ADS)

Sleep, Norman H.

2008-08-01

Chains of volcanic edifices lie along flow lines between plume-fed hot spots and the thin lithosphere at ridge axes. Discovery and Euterpe/Musicians Seamounts are two examples. An attractive hypothesis is that buoyant plume material flows along the base of the lithosphere perpendicular to isochrons. The plume material may conceivably flow in a broad front or flow within channels convectively eroded into the base to the lithosphere. A necessary but not sufficient condition for convective channeling is that the expected stagnant-lid heat flow for the maximum temperature of the plume material is comparable to the half-space surface heat flow of the oceanic lithosphere. Two-dimensional and three-dimensional numerical calculations confirm this inference. A second criterion for significant convective erosion is that it needs to occur before the plume material thins by lateral spreading. Scaling relationships indicate spreading and convection are closely related. Mathematically, the Nusselt number (ratio of convective to conductive heat flow in the plume material) scales with the flux (volume per time per length of flow front) of the plume material. A blob of unconfined plume material thus spreads before the lithosphere thins much and evolves to a slowly spreading and slowly convecting warm region in equilibrium with conduction into the base of the overlying lithosphere. Three-dimensional calculations illustrate this long-lasting (and hence observable) state of plume material away from its plume source. A different flow domain occurs around a stationary hot plume that continuously supplies hot material. The plume convectively erodes the overlying lithosphere, trapping the plume material near its orifice. The region of lithosphere underlain by plume material grows toward the ridge axis and laterally by convective thinning of the lithosphere at its edges. The hottest plume material channels along flow lines. Geologically, the regions of lithosphere underlain by either warm or hot plume material are likely to extend laterally away from the volcanic edifices whether or not channeling occurs.

Predicted reliability of aerospace electronics: Application of two advanced probabilistic concepts

NASA Astrophysics Data System (ADS)

Suhir, E.

Two advanced probabilistic design-for-reliability (PDfR) concepts are addressed and discussed in application to the prediction, quantification and assurance of the aerospace electronics reliability: 1) Boltzmann-Arrhenius-Zhurkov (BAZ) model, which is an extension of the currently widely used Arrhenius model and, in combination with the exponential law of reliability, enables one to obtain a simple, easy-to-use and physically meaningful formula for the evaluation of the probability of failure (PoF) of a material or a device after the given time in operation at the given temperature and under the given stress (not necessarily mechanical), and 2) Extreme Value Distribution (EVD) technique that can be used to assess the number of repetitive loadings that result in the material/device degradation and eventually lead to its failure by closing, in a step-wise fashion, the gap between the bearing capacity (stress-free activation energy) of the material or the device and the demand (loading). It is shown that the material degradation (aging, damage accumulation, flaw propagation, etc.) can be viewed, when BAZ model is considered, as a Markovian process, and that the BAZ model can be obtained as the ultimate steady-state solution to the well-known Fokker-Planck equation in the theory of Markovian processes. It is shown also that the BAZ model addresses the worst, but a reasonably conservative, situation. It is suggested therefore that the transient period preceding the condition addressed by the steady-state BAZ model need not be accounted for in engineering evaluations. However, when there is an interest in understanding the transient degradation process, the obtained solution to the Fokker-Planck equation can be used for this purpose. As to the EVD concept, it attributes the degradation process to the accumulation of damages caused by a train of repetitive high-level loadings, while loadings of levels that are considerably lower than their extreme values do not contribute- appreciably to the finite lifetime of a material or a device. In our probabilistic risk management (PRM) based analysis we treat the stress-free activation energy (capacity) as a normally distributed random variable, and choose, for the sake of simplicity, the (single-parametric) Rayleigh law as the basic distribution underlying the EVD. The general concepts addressed and discussed are illustrated by numerical examples. It is concluded that the application of the PDfR approach and particularly the above two advanced models should be considered as a natural, physically meaningful, informative, comprehensive, and insightful technique that reflects well the physics underlying the degradation processes in materials, devices and systems. It is the author's belief that they will be widely used in engineering practice, when high reliability is imperative, and the ability to quantify it is highly desirable.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow.

PubMed

Kerner, Boris S; Klenov, Sergey L; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules "acceleration," "deceleration," "randomization," and "motion" of the Nagel-Schreckenberg CA model as well as "overacceleration through lane changing to the faster lane," "comparison of vehicle gap with the synchronization gap," and "speed adaptation within the synchronization gap" of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

Quantifying radar-rainfall uncertainties in urban drainage flow modelling

NASA Astrophysics Data System (ADS)

Rico-Ramirez, M. A.; Liguori, S.; Schellart, A. N. A.

2015-09-01

This work presents the results of the implementation of a probabilistic system to model the uncertainty associated to radar rainfall (RR) estimates and the way this uncertainty propagates through the sewer system of an urban area located in the North of England. The spatial and temporal correlations of the RR errors as well as the error covariance matrix were computed to build a RR error model able to generate RR ensembles that reproduce the uncertainty associated with the measured rainfall. The results showed that the RR ensembles provide important information about the uncertainty in the rainfall measurement that can be propagated in the urban sewer system. The results showed that the measured flow peaks and flow volumes are often bounded within the uncertainty area produced by the RR ensembles. In 55% of the simulated events, the uncertainties in RR measurements can explain the uncertainties observed in the simulated flow volumes. However, there are also some events where the RR uncertainty cannot explain the whole uncertainty observed in the simulated flow volumes indicating that there are additional sources of uncertainty that must be considered such as the uncertainty in the urban drainage model structure, the uncertainty in the urban drainage model calibrated parameters, and the uncertainty in the measured sewer flows.

Probabilistic structural analysis methods for space propulsion system components

NASA Technical Reports Server (NTRS)

Chamis, C. C.

1986-01-01

The development of a three-dimensional inelastic analysis methodology for the Space Shuttle main engine (SSME) structural components is described. The methodology is composed of: (1) composite load spectra, (2) probabilistic structural analysis methods, (3) the probabilistic finite element theory, and (4) probabilistic structural analysis. The methodology has led to significant technical progress in several important aspects of probabilistic structural analysis. The program and accomplishments to date are summarized.

Review of the probabilistic failure analysis methodology and other probabilistic approaches for application in aerospace structural design

NASA Technical Reports Server (NTRS)

Townsend, J.; Meyers, C.; Ortega, R.; Peck, J.; Rheinfurth, M.; Weinstock, B.

1993-01-01

Probabilistic structural analyses and design methods are steadily gaining acceptance within the aerospace industry. The safety factor approach to design has long been the industry standard, and it is believed by many to be overly conservative and thus, costly. A probabilistic approach to design may offer substantial cost savings. This report summarizes several probabilistic approaches: the probabilistic failure analysis (PFA) methodology developed by Jet Propulsion Laboratory, fast probability integration (FPI) methods, the NESSUS finite element code, and response surface methods. Example problems are provided to help identify the advantages and disadvantages of each method.

Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback.

PubMed

Orhan, A Emin; Ma, Wei Ji

2017-07-26

Animals perform near-optimal probabilistic inference in a wide range of psychophysical tasks. Probabilistic inference requires trial-to-trial representation of the uncertainties associated with task variables and subsequent use of this representation. Previous work has implemented such computations using neural networks with hand-crafted and task-dependent operations. We show that generic neural networks trained with a simple error-based learning rule perform near-optimal probabilistic inference in nine common psychophysical tasks. In a probabilistic categorization task, error-based learning in a generic network simultaneously explains a monkey's learning curve and the evolution of qualitative aspects of its choice behavior. In all tasks, the number of neurons required for a given level of performance grows sublinearly with the input population size, a substantial improvement on previous implementations of probabilistic inference. The trained networks develop a novel sparsity-based probabilistic population code. Our results suggest that probabilistic inference emerges naturally in generic neural networks trained with error-based learning rules.Behavioural tasks often require probability distributions to be inferred about task specific variables. Here, the authors demonstrate that generic neural networks can be trained using a simple error-based learning rule to perform such probabilistic computations efficiently without any need for task specific operations.

Probabilistic Multi-Scale, Multi-Level, Multi-Disciplinary Analysis and Optimization of Engine Structures

NASA Technical Reports Server (NTRS)

Chamis, Christos C.; Abumeri, Galib H.

2000-01-01

Aircraft engines are assemblies of dynamically interacting components. Engine updates to keep present aircraft flying safely and engines for new aircraft are progressively required to operate in more demanding technological and environmental requirements. Designs to effectively meet those requirements are necessarily collections of multi-scale, multi-level, multi-disciplinary analysis and optimization methods and probabilistic methods are necessary to quantify respective uncertainties. These types of methods are the only ones that can formally evaluate advanced composite designs which satisfy those progressively demanding requirements while assuring minimum cost, maximum reliability and maximum durability. Recent research activities at NASA Glenn Research Center have focused on developing multi-scale, multi-level, multidisciplinary analysis and optimization methods. Multi-scale refers to formal methods which describe complex material behavior metal or composite; multi-level refers to integration of participating disciplines to describe a structural response at the scale of interest; multidisciplinary refers to open-ended for various existing and yet to be developed discipline constructs required to formally predict/describe a structural response in engine operating environments. For example, these include but are not limited to: multi-factor models for material behavior, multi-scale composite mechanics, general purpose structural analysis, progressive structural fracture for evaluating durability and integrity, noise and acoustic fatigue, emission requirements, hot fluid mechanics, heat-transfer and probabilistic simulations. Many of these, as well as others, are encompassed in an integrated computer code identified as Engine Structures Technology Benefits Estimator (EST/BEST) or Multi-faceted/Engine Structures Optimization (MP/ESTOP). The discipline modules integrated in MP/ESTOP include: engine cycle (thermodynamics), engine weights, internal fluid mechanics, cost, mission and coupled structural/thermal, various composite property simulators and probabilistic methods to evaluate uncertainty effects (scatter ranges) in all the design parameters. The objective of the proposed paper is to briefly describe a multi-faceted design analysis and optimization capability for coupled multi-discipline engine structures optimization. Results are presented for engine and aircraft type metrics to illustrate the versatility of that capability. Results are also presented for reliability, noise and fatigue to illustrate its inclusiveness. For example, replacing metal rotors with composites reduces the engine weight by 20 percent, 15 percent noise reduction, and an order of magnitude improvement in reliability. Composite designs exist to increase fatigue life by at least two orders of magnitude compared to state-of-the-art metals.

Method and apparatus for monitoring characteristics of a flow path having solid components flowing therethrough

DOEpatents

Hoskinson, Reed L [Rigby, ID; Svoboda, John M [Idaho Falls, ID; Bauer, William F [Idaho Falls, ID; Elias, Gracy [Idaho Falls, ID

2008-05-06

A method and apparatus is provided for monitoring a flow path having plurality of different solid components flowing therethrough. For example, in the harvesting of a plant material, many factors surrounding the threshing, separating or cleaning of the plant material and may lead to the inadvertent inclusion of the component being selectively harvested with residual plant materials being discharged or otherwise processed. In accordance with the present invention the detection of the selectively harvested component within residual materials may include the monitoring of a flow path of such residual materials by, for example, directing an excitation signal toward of flow path of material and then detecting a signal initiated by the presence of the selectively harvested component responsive to the excitation signal. The detected signal may be used to determine the presence or absence of a selected plant component within the flow path of residual materials.

Tensile Shear Properties of the Friction Stir Lap Welded Joints and Material Flow Mechanism Under Pulsatile Revolutions

NASA Astrophysics Data System (ADS)

Hu, Yanying; Liu, Huijie; Du, Shuaishuai

2018-06-01

The aim of the present article is to offer insight into the effects of pin profiles on interface defects, tensile shear properties, microstructures, and the material flow of friction stir lap welded joints. The results indicate that, compared to the lap joints welded by the single threaded plane pin, the three-plane threaded pin, and the triangle threaded pin, the lap joint obtained by the conventional conical threaded pin is characterized by the minimum interface defect. The alternate threads and planes on the pin provide periodical stress, leading to pulsatile material flow patterns. Under the effect of pulsatile revolutions, an asymmetrical flow field is formed around the tool. The threads on the pin force the surrounding material to flow downward. The planes cannot only promote the horizontal flow of the material by scraping, but also provide extra space for the material vertical flow. A heuristic model is established to describe the material flow mechanism during friction stir lap welding under the effect of pulsatile revolutions.

Probabilistic classifiers with high-dimensional data

PubMed Central

Kim, Kyung In; Simon, Richard

2011-01-01

For medical classification problems, it is often desirable to have a probability associated with each class. Probabilistic classifiers have received relatively little attention for small n large p classification problems despite of their importance in medical decision making. In this paper, we introduce 2 criteria for assessment of probabilistic classifiers: well-calibratedness and refinement and develop corresponding evaluation measures. We evaluated several published high-dimensional probabilistic classifiers and developed 2 extensions of the Bayesian compound covariate classifier. Based on simulation studies and analysis of gene expression microarray data, we found that proper probabilistic classification is more difficult than deterministic classification. It is important to ensure that a probabilistic classifier is well calibrated or at least not “anticonservative” using the methods developed here. We provide this evaluation for several probabilistic classifiers and also evaluate their refinement as a function of sample size under weak and strong signal conditions. We also present a cross-validation method for evaluating the calibration and refinement of any probabilistic classifier on any data set. PMID:21087946

A Proposed Probabilistic Extension of the Halpern and Pearl Definition of ‘Actual Cause’

PubMed Central

2017-01-01

ABSTRACT Joseph Halpern and Judea Pearl ([2005]) draw upon structural equation models to develop an attractive analysis of ‘actual cause’. Their analysis is designed for the case of deterministic causation. I show that their account can be naturally extended to provide an elegant treatment of probabilistic causation. 1Introduction2Preemption3Structural Equation Models4The Halpern and Pearl Definition of ‘Actual Cause’5Preemption Again6The Probabilistic Case7Probabilistic Causal Models8A Proposed Probabilistic Extension of Halpern and Pearl’s Definition9Twardy and Korb’s Account10Probabilistic Fizzling11Conclusion PMID:29593362

Application of Weakest Link Probabilistic Framework for Fatigue Notch Factor to Aero Engine Materials

DTIC Science & Technology

2014-08-25

11 distributed cyclic microplasticity . Recent approaches have been developed to incorporate these finite process zone effects at notches [25, 26...the distribution of microvoids [50] or microplasticity [51]. According to the hypotheses on which the weakest link theory is based, given a structure...high cycle fatigue regime, where scatter of heterogeneous microplasticity in the fatigue specimen is a common occurrence. The probability of success

Probabilistic evaluation of uncertainties and risks in aerospace components

NASA Technical Reports Server (NTRS)

Shah, A. R.; Shiao, M. C.; Nagpal, V. K.; Chamis, C. C.

1992-01-01

This paper summarizes a methodology developed at NASA Lewis Research Center which computationally simulates the structural, material, and load uncertainties associated with Space Shuttle Main Engine (SSME) components. The methodology was applied to evaluate the scatter in static, buckling, dynamic, fatigue, and damage behavior of the SSME turbo pump blade. Also calculated are the probability densities of typical critical blade responses, such as effective stress, natural frequency, damage initiation, most probable damage path, etc. Risk assessments were performed for different failure modes, and the effect of material degradation on the fatigue and damage behaviors of a blade were calculated using a multi-factor interaction equation. Failure probabilities for different fatigue cycles were computed and the uncertainties associated with damage initiation and damage propagation due to different load cycle were quantified. Evaluations on the effects of mistuned blades on a rotor were made; uncertainties in the excitation frequency were found to significantly amplify the blade responses of a mistuned rotor. The effects of the number of blades on a rotor were studied. The autocorrelation function of displacements and the probability density function of the first passage time for deterministic and random barriers for structures subjected to random processes also were computed. A brief discussion was included on the future direction of probabilistic structural analysis.

A preliminary probabilistic analysis of tsunami sources of seismic and non-seismic origin applied to the city of Naples, Italy

NASA Astrophysics Data System (ADS)

Tonini, R.; Anita, G.

2011-12-01

In both worldwide and regional historical catalogues, most of the tsunamis are caused by earthquakes and a minor percentage is represented by all the other non-seismic sources. On the other hand, tsunami hazard and risk studies are often applied to very specific areas, where this global trend can be different or even inverted, depending on the kind of potential tsunamigenic sources which characterize the case study. So far, few probabilistic approaches consider the contribution of landslides and/or phenomena derived by volcanic activity, i.e. pyroclastic flows and flank collapses, as predominant in the PTHA, also because of the difficulties to estimate the correspondent recurrence time. These considerations are valid, for example, for the city of Naples, Italy, which is surrounded by a complex active volcanic system (Vesuvio, Campi Flegrei, Ischia) that presents a significant number of potential tsunami sources of non-seismic origin compared to the seismic ones. In this work we present the preliminary results of a probabilistic multi-source tsunami hazard assessment applied to Naples. The method to estimate the uncertainties will be based on Bayesian inference. This is the first step towards a more comprehensive task which will provide a tsunami risk quantification for this town in the frame of the Italian national project ByMuR (http://bymur.bo.ingv.it). This three years long ongoing project has the final objective of developing a Bayesian multi-risk methodology to quantify the risk related to different natural hazards (volcanoes, earthquakes and tsunamis) applied to the city of Naples.

Altered structural connectivity of pain-related brain network in burning mouth syndrome-investigation by graph analysis of probabilistic tractography.

PubMed

Wada, Akihiko; Shizukuishi, Takashi; Kikuta, Junko; Yamada, Haruyasu; Watanabe, Yusuke; Imamura, Yoshiki; Shinozaki, Takahiro; Dezawa, Ko; Haradome, Hiroki; Abe, Osamu

2017-05-01

Burning mouth syndrome (BMS) is a chronic intraoral pain syndrome featuring idiopathic oral pain and burning discomfort despite clinically normal oral mucosa. The etiology of chronic pain syndrome is unclear, but preliminary neuroimaging research has suggested the alteration of volume, metabolism, blood flow, and diffusion at multiple brain regions. According to the neuromatrix theory of Melzack, pain sense is generated in the brain by the network of multiple pain-related brain regions. Therefore, the alteration of pain-related network is also assumed as an etiology of chronic pain. In this study, we investigated the brain network of BMS brain by using probabilistic tractography and graph analysis. Fourteen BMS patients and 14 age-matched healthy controls underwent 1.5T MRI. Structural connectivity was calculated in 83 anatomically defined regions with probabilistic tractography of 60-axis diffusion tensor imaging and 3D T1-weighted imaging. Graph theory network analysis was used to evaluate the brain network at local and global connectivity. In BMS brain, a significant difference of local brain connectivity was recognized at the bilateral rostral anterior cingulate cortex, right medial orbitofrontal cortex, and left pars orbitalis which belong to the medial pain system; however, no significant difference was recognized at the lateral system including the somatic sensory cortex. A strengthened connection of the anterior cingulate cortex and medial prefrontal cortex with the basal ganglia, thalamus, and brain stem was revealed. Structural brain network analysis revealed the alteration of the medial system of the pain-related brain network in chronic pain syndrome.

Development of a new family of normalized modulus reduction and material damping curves

NASA Astrophysics Data System (ADS)

Darendeli, Mehmet Baris

2001-12-01

As part of various research projects [including the SRS (Savannah River Site) Project AA891070, EPRI (Electric Power Research Institute) Project 3302, and ROSRINE (Resolution of Site Response Issues from the Northridge Earthquake) Project], numerous geotechnical sites were drilled and sampled. Intact soil samples over a depth range of several hundred meters were recovered from 20 of these sites. These soil samples were tested in the laboratory at The University of Texas at Austin (UTA) to characterize the materials dynamically. The presence of a database accumulated from testing these intact specimens motivated a re-evaluation of empirical curves employed in the state of practice. The weaknesses of empirical curves reported in the literature were identified and the necessity of developing an improved set of empirical curves was recognized. This study focused on developing the empirical framework that can be used to generate normalized modulus reduction and material damping curves. This framework is composed of simple equations, which incorporate the key parameters that control nonlinear soil behavior. The data collected over the past decade at The University of Texas at Austin are statistically analyzed using First-order, Second-moment Bayesian Method (FSBM). The effects of various parameters (such as confining pressure and soil plasticity) on dynamic soil properties are evaluated and quantified within this framework. One of the most important aspects of this study is estimating not only the mean values of the empirical curves but also estimating the uncertainty associated with these values. This study provides the opportunity to handle uncertainty in the empirical estimates of dynamic soil properties within the probabilistic seismic hazard analysis framework. A refinement in site-specific probabilistic seismic hazard assessment is expected to materialize in the near future by incorporating the results of this study into state of practice.

Laminated metal composite formed from low flow stress layers and high flow stress layers using flow constraining elements and making same

DOEpatents

Syn, C.K.; Lesuer, D.R.

1995-07-04

A laminated metal composite of low flow stress layers and high flow stress layers is described which is formed using flow constraining elements, preferably in the shape of rings, individually placed around each of the low flow stress layers while pressure is applied to the stack to bond the layers of the composite together, to thereby restrain the flow of the low flow stress layers from the stack during the bonding. The laminated metal composite of the invention is made by the steps of forming a stack of alternate layers of low flow stress layers and high flow stress layers with each layer of low flow stress material surrounded by an individual flow constraining element, such as a ring, and then applying pressure to the top and bottom surfaces of the resulting stack to bond the dissimilar layers together, for example, by compression rolling the stack. In a preferred embodiment, the individual flow constraining elements surrounding the layers of low flow stress material are formed of a material which may either be the same material as the material comprising the high flow stress layers, or have similar flow stress characteristics to the material comprising the high flow stress layers. Additional sacrificial layers may be added to the top and bottom of the stack to avoid damage to the stack during the bonding step; and these additional layers may then be removed after the bonding step. 5 figs.

Laminated metal composite formed from low flow stress layers and high flow stress layers using flow constraining elements and making same

DOEpatents

Syn, Chol K.; Lesuer, Donald R.

1995-01-01

A laminated metal composite of low flow stress layers and high flow stress layers is described which is formed using flow constraining elements, preferably in the shape of rings, individually placed around each of the low flow stress layers while pressure is applied to the stack to bond the layers of the composite together, to thereby restrain the flow of the low flow stress layers from the stack during the bonding. The laminated metal composite of the invention is made by the steps of forming a stack of alternate layers of low flow stress layers and high flow stress layers with each layer of low flow stress material surrounded by an individual flow constraining element, such as a ring, and then applying pressure to the top and bottom surfaces of the resulting stack to bond the dissimilar layers together, for example, by compression rolling the stack. In a preferred embodiment, the individual flow constraining elements surrounding the layers of low flow stress material are formed of a material which may either be the same material as the material comprising the high flow stress layers, or have similar flow stress characteristics to the material comprising the high flow stress layers. Additional sacrificial layers may be added to the top and bottom of the stack to avoid damage to the stack during the bonding step; and these additional layers may then be removed after the bonding step.

Naples between two fires: eruptive scenarios for the next eruptions by an integrated volcanological-probabilistic approach.

NASA Astrophysics Data System (ADS)

Mastrolorenzo, G.; Pappalardo, L.; de Natale, G.; Troise, C.; Rossano, S.; Panizza, A.

2009-04-01

Probabilistic approaches based on available volcanological data from real eruptions of Campi Flegrei and Somma-Vesuvius, are assembled in a comprehensive assessment of volcanic hazards at the Neapolitan area. This allows to compare the volcanic hazards related to the different types of events, which can be used for evaluating the conditional probability of flows and falls hazard in case of a volcanic crisis. Hazard maps are presented, based on a rather complete set of numerical simulations, produced using field and laboratory data as input parameters relative to a large range (VEI 1 to 5) of fallout and pyroclastic-flow events and their relative occurrence. The results allow us to quantitatively evaluate and compare the hazard related to pyroclastic fallout and density currents (PDCs) at the Neapolitan volcanoes and their surroundings, including the city of Naples. Due to its position between the two volcanic areas, the city of Naples is particularly exposed to volcanic risk from VEI>2 eruptions, as recorded in the local volcanic succession. Because dominant wind directions, the area of Naples is particularly prone to fallout hazard from Campi Flegrei caldera eruptions in the VEI range 2-5. The hazard from PDCs decreases roughly radially with distance from the eruptive vents and is strongly controlled by the topographic heights. Campi Flegrei eruptions are particularly hazardous for Naples, although the Camaldoli and Posillipo hills produce an effective barrier to propagation to the very central part of Naples. PDCs from Vesuvius eruptions with VEI>4 can cover the city of Naples, whereas even VEI>3 eruptions have a moderate fallout hazard there.

Analysis of the Coupled Influence of Hydraulic Conductivity and Porosity Heterogeneity on Probabilistic Risk Analysis

NASA Astrophysics Data System (ADS)

Libera, A.; Henri, C.; de Barros, F.

2017-12-01

Heterogeneities in natural porous formations, mainly manifested through the hydraulic conductivity (K) and, to a lesser degree, the porosity (Φ), largely control subsurface flow and solute transport. The influence of the heterogeneous structure of K on flow and solute transport processes has been widely studied, whereas less attention is dedicated to the joint heterogeneity of conductivity and porosity fields. Our study employs computational tools to investigate the joint effect of the spatial variabilities of K and Φ on the transport behavior of a solute plume. We explore multiple scenarios, characterized by different levels of heterogeneity of the geological system, and compare the computational results from the joint K and Φ heterogeneous system with the results originating from the generally adopted constant porosity case. In our work, we assume that the heterogeneous porosity is positively correlated to hydraulic conductivity. We perform numerical Monte Carlo simulations of conservative and reactive contaminant transport in a 3D aquifer. Contaminant mass and plume arrival times at multiple control planes and/or pumping wells operating under different extraction rates are analyzed. We employ different probabilistic metrics to quantify the risk at the monitoring locations, e.g., increased lifetime cancer risk and exceedance of Maximum Contaminant Levels (MCLs), under multiple transport scenarios (i.e., different levels of heterogeneity, conservative or reactive solutes and different contaminant species). Results show that early and late arrival times of the solute mass at the selected sensitive locations (i.e. control planes/pumping wells) as well as risk metrics are strongly influenced by the spatial variability of the Φ field.

Bayesian methods for characterizing unknown parameters of material models

DOE PAGES

Emery, J. M.; Grigoriu, M. D.; Field Jr., R. V.

2016-02-04

A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). As a result, the Bayesian method is also employed tomore » characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.« less

Bayesian methods for characterizing unknown parameters of material models

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

Emery, J. M.; Grigoriu, M. D.; Field Jr., R. V.

A Bayesian framework is developed for characterizing the unknown parameters of probabilistic models for material properties. In this framework, the unknown parameters are viewed as random and described by their posterior distributions obtained from prior information and measurements of quantities of interest that are observable and depend on the unknown parameters. The proposed Bayesian method is applied to characterize an unknown spatial correlation of the conductivity field in the definition of a stochastic transport equation and to solve this equation by Monte Carlo simulation and stochastic reduced order models (SROMs). As a result, the Bayesian method is also employed tomore » characterize unknown parameters of material properties for laser welds from measurements of peak forces sustained by these welds.« less

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2011-01-01

A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Classic articles and workbook: EPRI monographs on simulation of electric power production

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

Stremel, J.P.

1991-12-01

This monograph republishes several articles including a seminal one on probabilistic production costing for electric power generation. That article is given in the original French along with a English translation. Another article, written by R. Booth, gives a popular explanation of the theory, and a workbook by B. Manhire is included that carries through a simple example step by step. The classical analysis of non-probabilistic generator dispatch by L.K. Kirchmayer is republished along with an introductory essay by J.P. Stremel that puts in perspective the monograph material. The article in French was written by H. Baleriaux, E. Jamoulle, and Fr.more » Linard de Guertechin and first published in Brussels in 1967. It derived a method for calculating the expected value of production costs by modifying a load duration curve through the use of probability factors that account for unplanned random generator outages. Although the paper showed how pump storage plants could be included and how linear programming could be applied, the convolution technique used in the probabilistic calculations is the part most widely applied. The tutorial paper by Booth was written in a light style, and its lucidity helped popularize the method. The workbook by Manhire also shows how the calculation can be shortened significantly using cumulants to approximate the load duration curve.« less

Probabilistic Simulation for Combined Cycle Fatigue in Composites

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A methodology to compute probabilistic fatigue life of polymer matrix laminated composites has been developed and demonstrated. Matrix degradation effects caused by long term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress dependent multifactor interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/- 45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical cyclic loads and low thermal cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical cyclic loads and high thermal cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Probabilistic Simulation of Combined Thermo-Mechanical Cyclic Fatigue in Composites

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

2010-01-01

A methodology to compute probabilistically-combined thermo-mechanical fatigue life of polymer matrix laminated composites has been developed and is demonstrated. Matrix degradation effects caused by long-term environmental exposure and mechanical/thermal cyclic loads are accounted for in the simulation process. A unified time-temperature-stress-dependent multifactor-interaction relationship developed at NASA Glenn Research Center has been used to model the degradation/aging of material properties due to cyclic loads. The fast probability-integration method is used to compute probabilistic distribution of response. Sensitivities of fatigue life reliability to uncertainties in the primitive random variables (e.g., constituent properties, fiber volume ratio, void volume ratio, ply thickness, etc.) computed and their significance in the reliability-based design for maximum life is discussed. The effect of variation in the thermal cyclic loads on the fatigue reliability for a (0/+/-45/90)s graphite/epoxy laminate with a ply thickness of 0.127 mm, with respect to impending failure modes has been studied. The results show that, at low mechanical-cyclic loads and low thermal-cyclic amplitudes, fatigue life for 0.999 reliability is most sensitive to matrix compressive strength, matrix modulus, thermal expansion coefficient, and ply thickness. Whereas at high mechanical-cyclic loads and high thermal-cyclic amplitudes, fatigue life at 0.999 reliability is more sensitive to the shear strength of matrix, longitudinal fiber modulus, matrix modulus, and ply thickness.

Is probabilistic bias analysis approximately Bayesian?

PubMed Central

MacLehose, Richard F.; Gustafson, Paul

2011-01-01

Case-control studies are particularly susceptible to differential exposure misclassification when exposure status is determined following incident case status. Probabilistic bias analysis methods have been developed as ways to adjust standard effect estimates based on the sensitivity and specificity of exposure misclassification. The iterative sampling method advocated in probabilistic bias analysis bears a distinct resemblance to a Bayesian adjustment; however, it is not identical. Furthermore, without a formal theoretical framework (Bayesian or frequentist), the results of a probabilistic bias analysis remain somewhat difficult to interpret. We describe, both theoretically and empirically, the extent to which probabilistic bias analysis can be viewed as approximately Bayesian. While the differences between probabilistic bias analysis and Bayesian approaches to misclassification can be substantial, these situations often involve unrealistic prior specifications and are relatively easy to detect. Outside of these special cases, probabilistic bias analysis and Bayesian approaches to exposure misclassification in case-control studies appear to perform equally well. PMID:22157311

Probabilistic structural analysis methods for select space propulsion system components

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Cruse, T. A.

1989-01-01

The Probabilistic Structural Analysis Methods (PSAM) project developed at the Southwest Research Institute integrates state-of-the-art structural analysis techniques with probability theory for the design and analysis of complex large-scale engineering structures. An advanced efficient software system (NESSUS) capable of performing complex probabilistic analysis has been developed. NESSUS contains a number of software components to perform probabilistic analysis of structures. These components include: an expert system, a probabilistic finite element code, a probabilistic boundary element code and a fast probability integrator. The NESSUS software system is shown. An expert system is included to capture and utilize PSAM knowledge and experience. NESSUS/EXPERT is an interactive menu-driven expert system that provides information to assist in the use of the probabilistic finite element code NESSUS/FEM and the fast probability integrator (FPI). The expert system menu structure is summarized. The NESSUS system contains a state-of-the-art nonlinear probabilistic finite element code, NESSUS/FEM, to determine the structural response and sensitivities. A broad range of analysis capabilities and an extensive element library is present.

Frontal and Parietal Contributions to Probabilistic Association Learning

PubMed Central

Rushby, Jacqueline A.; Vercammen, Ans; Loo, Colleen; Short, Brooke

2011-01-01

Neuroimaging studies have shown both dorsolateral prefrontal (DLPFC) and inferior parietal cortex (iPARC) activation during probabilistic association learning. Whether these cortical brain regions are necessary for probabilistic association learning is presently unknown. Participants' ability to acquire probabilistic associations was assessed during disruptive 1 Hz repetitive transcranial magnetic stimulation (rTMS) of the left DLPFC, left iPARC, and sham using a crossover single-blind design. On subsequent sessions, performance improved relative to baseline except during DLPFC rTMS that disrupted the early acquisition beneficial effect of prior exposure. A second experiment examining rTMS effects on task-naive participants showed that neither DLPFC rTMS nor sham influenced naive acquisition of probabilistic associations. A third experiment examining consecutive administration of the probabilistic association learning test revealed early trial interference from previous exposure to different probability schedules. These experiments, showing disrupted acquisition of probabilistic associations by rTMS only during subsequent sessions with an intervening night's sleep, suggest that the DLPFC may facilitate early access to learned strategies or prior task-related memories via consolidation. Although neuroimaging studies implicate DLPFC and iPARC in probabilistic association learning, the present findings suggest that early acquisition of the probabilistic cue-outcome associations in task-naive participants is not dependent on either region. PMID:21216842

Reliability and Confidence Interval Analysis of a CMC Turbine Stator Vane

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Gyekenyesi, John P.; Mital, Subodh K.

2008-01-01

High temperature ceramic matrix composites (CMC) are being explored as viable candidate materials for hot section gas turbine components. These advanced composites can potentially lead to reduced weight, enable higher operating temperatures requiring less cooling and thus leading to increased engine efficiencies. However, these materials are brittle and show degradation with time at high operating temperatures due to creep as well as cyclic mechanical and thermal loads. In addition, these materials are heterogeneous in their make-up and various factors affect their properties in a specific design environment. Most of these advanced composites involve two- and three-dimensional fiber architectures and require a complex multi-step high temperature processing. Since there are uncertainties associated with each of these in addition to the variability in the constituent material properties, the observed behavior of composite materials exhibits scatter. Traditional material failure analyses employing a deterministic approach, where failure is assumed to occur when some allowable stress level or equivalent stress is exceeded, are not adequate for brittle material component design. Such phenomenological failure theories are reasonably successful when applied to ductile materials such as metals. Analysis of failure in structural components is governed by the observed scatter in strength, stiffness and loading conditions. In such situations, statistical design approaches must be used. Accounting for these phenomena requires a change in philosophy on the design engineer s part that leads to a reduced focus on the use of safety factors in favor of reliability analyses. The reliability approach demands that the design engineer must tolerate a finite risk of unacceptable performance. This risk of unacceptable performance is identified as a component's probability of failure (or alternatively, component reliability). The primary concern of the engineer is minimizing this risk in an economical manner. The methods to accurately determine the service life of an engine component with associated variability have become increasingly difficult. This results, in part, from the complex missions which are now routinely considered during the design process. These missions include large variations of multi-axial stresses and temperatures experienced by critical engine parts. There is a need for a convenient design tool that can accommodate various loading conditions induced by engine operating environments, and material data with their associated uncertainties to estimate the minimum predicted life of a structural component. A probabilistic composite micromechanics technique in combination with woven composite micromechanics, structural analysis and Fast Probability Integration (FPI) techniques has been used to evaluate the maximum stress and its probabilistic distribution in a CMC turbine stator vane. Furthermore, input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Since the measured data for the ceramic matrix composite properties is very limited, obtaining a probabilistic distribution with their corresponding parameters is difficult. In case of limited data, confidence bounds are essential to quantify the uncertainty associated with the distribution. Usually 90 and 95% confidence intervals are computed for material properties. Failure properties are then computed with the confidence bounds. Best estimates and the confidence bounds on the best estimate of the cumulative probability function for R-S (strength - stress) are plotted. The methodologies and the results from these analyses will be discussed in the presentation.

Probabilistic Ontology Architecture for a Terrorist Identification Decision Support System

DTIC Science & Technology

2014-06-01

in real-world problems requires probabilistic ontologies, which integrate the inferential reasoning power of probabilistic representations with the... inferential reasoning power of probabilistic representations with the first-order expressivity of ontologies. The Reference Architecture for...ontology, terrorism, inferential reasoning, architecture I. INTRODUCTION A. Background Whether by nature or design, the personas of terrorists are

Dynamic Cost Risk Assessment for Controlling the Cost of Naval Vessels

DTIC Science & Technology

2008-04-23

for each individual RRA at the start of the project are depicted in Figures 2a and 2b, respectively. The PDFs are multimodal and cannot be...underestimates cost. 7 Probabilistic cost analysis A physician metaphor Adapted from Yacov Y. Haimes, NPS 2007 8 Dynamic cost risk management A physician... metaphor Adapted from Yacov Y. Haimes, NPS 2007 9 Sources of cost uncertainty Macroscopic analysis Economic, Materials & Labor, Learning rates

Low Base-Substitution Mutation Rate in the Germline Genome of the Ciliate Tetrahymena thermophila

DTIC Science & Technology

2016-09-15

generations of mutation accumulation (MA). We applied an existing mutation-calling pipeline and developed a new probabilistic mutation detection approach...noise introduced by mismapped reads. We used both our new method and an existing mutation-calling pipeline (Sung, Tucker, et al. 2012) to analyse the...and larger MA experiments will be required to confidently estimate the mutational spectrum of a species with such a low mutation rate. Materials and

A Technique for Developing Probabilistic Properties of Earth Materials

DTIC Science & Technology

1988-04-01

Department of Civil Engineering. Responsibility for coordi- nating this program was assigned to Mr. A. E . Jackson, Jr., GD, under the supervision of Dr...assuming deformation as a right circular cylinder E = expected value F = ratio of the between sample variance and the within sample variance F = area...radial strain = true radial strain rT e = axial strainz = number of increments in the covariance analysis VL = loading Poisson’s ratio VUN = unloading

Probabilistic Modeling and Simulation of Metal Fatigue Life Prediction

DTIC Science & Technology

2002-09-01

distribution demonstrate the central limit theorem? Obviously not! This is much the same as materials testing. If only NBA basketball stars are...60 near the exit of a NBA locker room. There would obviously be some pseudo-normal distribution with a very small standard deviation. The mean...completed, the investigators must understand how the midgets and the NBA stars will affect the total solution. D. IT IS MUCH SIMPLER TO MODEL THE

Experimental Resource Allocation for Statistical Simulation of Fretting Fatigue Problem (Preprint)

DTIC Science & Technology

2012-08-01

Metals Branch Structural Materials Division Harry R. Millwater , Carolina Dubinsky, and Gulshan Singh University of Texas at San Antonio...GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62102F 6. AUTHOR(S) Patrick Golden (AFRL/RXCM) Harry R. Millwater , Carolina Dubinsky, and Gulshan...Safety. 1996;54(2-3):133-144 [5] Golden, PJ, Millwater HR and Yang X. Probabilistic Fretting Fatigue Life Prediction of Ti-6Al-4V. International Journal

Computational prediction of probabilistic ignition threshold of pressed granular Octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine (HMX) under shock loading

NASA Astrophysics Data System (ADS)

Kim, Seokpum; Miller, Christopher; Horie, Yasuyuki; Molek, Christopher; Welle, Eric; Zhou, Min

2016-09-01

The probabilistic ignition thresholds of pressed granular Octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine explosives with average grain sizes between 70 μm and 220 μm are computationally predicted. The prediction uses material microstructure and basic constituent properties and does not involve curve fitting with respect to or prior knowledge of the attributes being predicted. The specific thresholds predicted are James-type relations between the energy flux and energy fluence for given probabilities of ignition. Statistically similar microstructure sample sets are computationally generated and used based on the features of micrographs of materials used in actual experiments. The predicted thresholds are in general agreement with measurements from shock experiments in terms of trends. In particular, it is found that grain size significantly affects the ignition sensitivity of the materials, with smaller sizes leading to lower energy thresholds required for ignition. For example, 50% ignition threshold of the material with an average grain size of 220 μm is approximately 1.4-1.6 times that of the material with an average grain size of 70 μm in terms of energy fluence. The simulations account for the controlled loading of thin-flyer shock experiments with flyer velocities between 1.5 and 4.0 km/s, constituent elasto-viscoplasticity, fracture, post-fracture contact and friction along interfaces, bulk inelastic heating, interfacial frictional heating, and heat conduction. The constitutive behavior of the materials is described using a finite deformation elasto-viscoplastic formulation and the Birch-Murnaghan equation of state. The ignition thresholds are determined via an explicit analysis of the size and temperature states of hotspots in the materials and a hotspot-based ignition criterion. The overall ignition threshold analysis and the microstructure-level hotspot analysis also lead to the definition of a macroscopic ignition parameter (J) and a microscopic ignition risk parameter (R) which are statistically related. The relationships between these parameters are established and delineated.

Simple cellular automaton model for traffic breakdown, highway capacity, and synchronized flow

NASA Astrophysics Data System (ADS)

Kerner, Boris S.; Klenov, Sergey L.; Schreckenberg, Michael

2011-10-01

We present a simple cellular automaton (CA) model for two-lane roads explaining the physics of traffic breakdown, highway capacity, and synchronized flow. The model consists of the rules “acceleration,” “deceleration,” “randomization,” and “motion” of the Nagel-Schreckenberg CA model as well as “overacceleration through lane changing to the faster lane,” “comparison of vehicle gap with the synchronization gap,” and “speed adaptation within the synchronization gap” of Kerner's three-phase traffic theory. We show that these few rules of the CA model can appropriately simulate fundamental empirical features of traffic breakdown and highway capacity found in traffic data measured over years in different countries, like characteristics of synchronized flow, the existence of the spontaneous and induced breakdowns at the same bottleneck, and associated probabilistic features of traffic breakdown and highway capacity. Single-vehicle data derived in model simulations show that synchronized flow first occurs and then self-maintains due to a spatiotemporal competition between speed adaptation to a slower speed of the preceding vehicle and passing of this slower vehicle. We find that the application of simple dependences of randomization probability and synchronization gap on driving situation allows us to explain the physics of moving synchronized flow patterns and the pinch effect in synchronized flow as observed in real traffic data.

Reliability and Creep/Fatigue Analysis of a CMC Component

NASA Technical Reports Server (NTRS)

Murthy, Pappu L. N.; Mital, Subodh K.; Gyekenyesi, John Z.; Gyekenyesi, John P.

2007-01-01

High temperature ceramic matrix composites (CMC) are being explored as viable candidate materials for hot section gas turbine components. These advanced composites can potentially lead to reduced weight and enable higher operating temperatures requiring less cooling; thus leading to increased engine efficiencies. There is a need for convenient design tools that can accommodate various loading conditions and material data with their associated uncertainties to estimate the minimum predicted life as well as the failure probabilities of a structural component. This paper presents a review of the life prediction and probabilistic analyses performed for a CMC turbine stator vane. A computer code, NASALife, is used to predict the life of a 2-D woven silicon carbide fiber reinforced silicon carbide matrix (SiC/SiC) turbine stator vane due to a mission cycle which induces low cycle fatigue and creep. The output from this program includes damage from creep loading, damage due to cyclic loading and the combined damage due to the given loading cycle. Results indicate that the trends predicted by NASALife are as expected for the loading conditions used for this study. In addition, a combination of woven composite micromechanics, finite element structural analysis and Fast Probability Integration (FPI) techniques has been used to evaluate the maximum stress and its probabilistic distribution in a CMC turbine stator vane. Input variables causing scatter are identified and ranked based upon their sensitivity magnitude. Results indicate that reducing the scatter in proportional limit strength of the vane material has the greatest effect in improving the overall reliability of the CMC vane.

Probabilistic soft sets and dual probabilistic soft sets in decision making with positive and negative parameters

NASA Astrophysics Data System (ADS)

Fatimah, F.; Rosadi, D.; Hakim, R. B. F.

2018-03-01

In this paper, we motivate and introduce probabilistic soft sets and dual probabilistic soft sets for handling decision making problem in the presence of positive and negative parameters. We propose several types of algorithms related to this problem. Our procedures are flexible and adaptable. An example on real data is also given.

Learning Probabilistic Logic Models from Probabilistic Examples

PubMed Central

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2009-01-01

Abstract We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples. PMID:19888348

Learning Probabilistic Logic Models from Probabilistic Examples.

PubMed

Chen, Jianzhong; Muggleton, Stephen; Santos, José

2008-10-01

We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.

Data-driven Modeling of Metal-oxide Sensors with Dynamic Bayesian Networks

NASA Astrophysics Data System (ADS)

Gosangi, Rakesh; Gutierrez-Osuna, Ricardo

2011-09-01

We present a data-driven probabilistic framework to model the transient response of MOX sensors modulated with a sequence of voltage steps. Analytical models of MOX sensors are usually built based on the physico-chemical properties of the sensing materials. Although building these models provides an insight into the sensor behavior, they also require a thorough understanding of the underlying operating principles. Here we propose a data-driven approach to characterize the dynamical relationship between sensor inputs and outputs. Namely, we use dynamic Bayesian networks (DBNs), probabilistic models that represent temporal relations between a set of random variables. We identify a set of control variables that influence the sensor responses, create a graphical representation that captures the causal relations between these variables, and finally train the model with experimental data. We validated the approach on experimental data in terms of predictive accuracy and classification performance. Our results show that DBNs can accurately predict the dynamic response of MOX sensors, as well as capture the discriminatory information present in the sensor transients.

Quantitative Risk Modeling of Fire on the International Space Station

NASA Technical Reports Server (NTRS)

Castillo, Theresa; Haught, Megan

2014-01-01

The International Space Station (ISS) Program has worked to prevent fire events and to mitigate their impacts should they occur. Hardware is designed to reduce sources of ignition, oxygen systems are designed to control leaking, flammable materials are prevented from flying to ISS whenever possible, the crew is trained in fire response, and fire response equipment improvements are sought out and funded. Fire prevention and mitigation are a top ISS Program priority - however, programmatic resources are limited; thus, risk trades are made to ensure an adequate level of safety is maintained onboard the ISS. In support of these risk trades, the ISS Probabilistic Risk Assessment (PRA) team has modeled the likelihood of fire occurring in the ISS pressurized cabin, a phenomenological event that has never before been probabilistically modeled in a microgravity environment. This paper will discuss the genesis of the ISS PRA fire model, its enhancement in collaboration with fire experts, and the results which have informed ISS programmatic decisions and will continue to be used throughout the life of the program.

Creep-rupture reliability analysis

NASA Technical Reports Server (NTRS)

Peralta-Duran, A.; Wirsching, P. H.

1984-01-01

A probabilistic approach to the correlation and extrapolation of creep-rupture data is presented. Time temperature parameters (TTP) are used to correlate the data, and an analytical expression for the master curve is developed. The expression provides a simple model for the statistical distribution of strength and fits neatly into a probabilistic design format. The analysis focuses on the Larson-Miller and on the Manson-Haferd parameters, but it can be applied to any of the TTP's. A method is developed for evaluating material dependent constants for TTP's. It is shown that optimized constants can provide a significant improvement in the correlation of the data, thereby reducing modelling error. Attempts were made to quantify the performance of the proposed method in predicting long term behavior. Uncertainty in predicting long term behavior from short term tests was derived for several sets of data. Examples are presented which illustrate the theory and demonstrate the application of state of the art reliability methods to the design of components under creep.

Probabilistic Thermal Analysis During Mars Reconnaissance Orbiter Aerobraking

NASA Technical Reports Server (NTRS)

Dec, John A.

2007-01-01

A method for performing a probabilistic thermal analysis during aerobraking has been developed. The analysis is performed on the Mars Reconnaissance Orbiter solar array during aerobraking. The methodology makes use of a response surface model derived from a more complex finite element thermal model of the solar array. The response surface is a quadratic equation which calculates the peak temperature for a given orbit drag pass at a specific location on the solar panel. Five different response surface equations are used, one of which predicts the overall maximum solar panel temperature, and the remaining four predict the temperatures of the solar panel thermal sensors. The variables used to define the response surface can be characterized as either environmental, material property, or modeling variables. Response surface variables are statistically varied in a Monte Carlo simulation. The Monte Carlo simulation produces mean temperatures and 3 sigma bounds as well as the probability of exceeding the designated flight allowable temperature for a given orbit. Response surface temperature predictions are compared with the Mars Reconnaissance Orbiter flight temperature data.

Phase change based cooling for high burst mode heat loads with temperature regulation above the phase change temperature

DOEpatents

The United States of America as represented by the United States Department of Energy

2009-12-15

An apparatus and method for transferring thermal energy from a heat load is disclosed. In particular, use of a phase change material and specific flow designs enables cooling with temperature regulation well above the fusion temperature of the phase change material for medium and high heat loads from devices operated intermittently (in burst mode). Exemplary heat loads include burst mode lasers and laser diodes, flight avionics, and high power space instruments. Thermal energy is transferred from the heat load to liquid phase change material from a phase change material reservoir. The liquid phase change material is split into two flows. Thermal energy is transferred from the first flow via a phase change material heat sink. The second flow bypasses the phase change material heat sink and joins with liquid phase change material exiting from the phase change material heat sink. The combined liquid phase change material is returned to the liquid phase change material reservoir. The ratio of bypass flow to flow into the phase change material heat sink can be varied to adjust the temperature of the liquid phase change material returned to the liquid phase change material reservoir. Varying the flowrate and temperature of the liquid phase change material presented to the heat load determines the magnitude of thermal energy transferred from the heat load.

LavaSIM: the effect of heat transfer in 3D on lava flow characteristics (Invited)

NASA Astrophysics Data System (ADS)

Fujita, E.

2013-12-01

Characteristics of lava flow are governed by many parameters like lava viscosity, effusion rate, ground topography, etc. The accuracy and applicability of lava flow simulation code is evaluated whether the numerical simulation can reproduce these features quantitatively, which is important from both strategic and scientific points of views. Many lava flow simulation codes are so far proposed, and they are classified into two categories, i.e., the deterministic and the probabilistic models. LavaSIM is one of the former category models, and has a disadvantage of time consuming. But LavaSIM can solves the equations of continuity, motion, energy by step and has an advantage in the calculation of three-dimensional analysis with solid-liquid two phase flow, including the heat transfer between lava, solidified crust, air, water and ground, and three-dimensional convection in liquid lava. In other word, we can check the detailed structure of lava flow by LavaSIM. Therefore, this code can produce both channeled and fan-dispersive flows. The margin of the flow is solidified by cooling and these solidified crusts control the behavior of successive lava flow. In case of a channel flow, the solidified margin supports the stable central main flow and elongates the lava flow distance. The cross section of lava flow shows that the liquid lava flows between solidified crusts. As for the lava extrusion flow rate, LavaSIM can include the time function as well as the location of the vents. In some cases, some parts of the solidified wall may be broken by the pressure of successive flow and/or re-melting. These mechanisms could characterize complex features of the observed lava flows at many volcanoes in the world. To apply LavaSIM to the benchmark tests organized by V-hub is important to improve the lava flow evaluation technique.

Earthquake parametrics based protection for microfinance disaster management in Indonesia

NASA Astrophysics Data System (ADS)

Sedayo, M. H.; Damanik, R.

2017-07-01

Financial institutions included microfinance institutions those lend money to people also face the risk when catastrophe event hit their operation area. Liquidity risk when withdrawal amount and Non Performance Loan (NPL) hiking fast in the same time could hit their cash flow. There are products in market that provide backup fund for this kind of situation. Microfinance institution needs a guideline too make contingency plan in their disaster management program. We develop a probabilistic seismic hazard, index and zonation map as a tool to help in making financial disaster impact reduction program for microfinance in Indonesia. GMPE was used to estimate PGA for each Kabupaten points. PGA to MMI conversion was done by applied empirical relationship. We used loan distribution data from Financial Service Authority and Bank Indonesia as exposure in indexing. Index level from this study could be use as rank of urgency. Probabilistic hazard map was used to pricing two backup scenarios and to make a zonation. We proposed three zones with annual average cost 0.0684‰, 0.4236‰ and 1.4064 for first scenario and 0.3588‰, 2.6112‰, and 6.0816‰ for second scenario.

3D Traffic Scene Understanding From Movable Platforms.

PubMed

Geiger, Andreas; Lauer, Martin; Wojek, Christian; Stiller, Christoph; Urtasun, Raquel

2014-05-01

In this paper, we present a novel probabilistic generative model for multi-object traffic scene understanding from movable platforms which reasons jointly about the 3D scene layout as well as the location and orientation of objects in the scene. In particular, the scene topology, geometry, and traffic activities are inferred from short video sequences. Inspired by the impressive driving capabilities of humans, our model does not rely on GPS, lidar, or map knowledge. Instead, it takes advantage of a diverse set of visual cues in the form of vehicle tracklets, vanishing points, semantic scene labels, scene flow, and occupancy grids. For each of these cues, we propose likelihood functions that are integrated into a probabilistic generative model. We learn all model parameters from training data using contrastive divergence. Experiments conducted on videos of 113 representative intersections show that our approach successfully infers the correct layout in a variety of very challenging scenarios. To evaluate the importance of each feature cue, experiments using different feature combinations are conducted. Furthermore, we show how by employing context derived from the proposed method we are able to improve over the state-of-the-art in terms of object detection and object orientation estimation in challenging and cluttered urban environments.

Probabilistic physical characteristics of phase transitions at highway bottlenecks: incommensurability of three-phase and two-phase traffic-flow theories.

PubMed

Kerner, Boris S; Klenov, Sergey L; Schreckenberg, Michael

2014-05-01

Physical features of induced phase transitions in a metastable free flow at an on-ramp bottleneck in three-phase and two-phase cellular automaton (CA) traffic-flow models have been revealed. It turns out that at given flow rates at the bottleneck, to induce a moving jam (F → J transition) in the metastable free flow through the application of a time-limited on-ramp inflow impulse, in both two-phase and three-phase CA models the same critical amplitude of the impulse is required. If a smaller impulse than this critical one is applied, neither F → J transition nor other phase transitions can occur in the two-phase CA model. We have found that in contrast with the two-phase CA model, in the three-phase CA model, if the same smaller impulse is applied, then a phase transition from free flow to synchronized flow (F → S transition) can be induced at the bottleneck. This explains why rather than the F → J transition, in the three-phase theory traffic breakdown at a highway bottleneck is governed by an F → S transition, as observed in real measured traffic data. None of two-phase traffic-flow theories incorporates an F → S transition in a metastable free flow at the bottleneck that is the main feature of the three-phase theory. On the one hand, this shows the incommensurability of three-phase and two-phase traffic-flow theories. On the other hand, this clarifies why none of the two-phase traffic-flow theories can explain the set of fundamental empirical features of traffic breakdown at highway bottlenecks.

Design of Friction Stir Welding Tool for Avoiding Root Flaws

PubMed Central

Ji, Shude; Xing, Jingwei; Yue, Yumei; Ma, Yinan; Zhang, Liguo; Gao, Shuangsheng

2013-01-01

In order to improve material flow behavior during friction stir welding and avoid root flaws of weld, a tool with a half-screw pin and a tool with a tapered-flute pin are suggested. The effect of flute geometry in tool pins on material flow velocity is investigated by the software ANSYS FLUENT. Numerical simulation results show that high material flow velocity appears near the rotational tool and material flow velocity rapidly decreases with the increase of distance away from the axis of the tool. Maximum material flow velocity by the tool with the tapered-flute pin appears at the beginning position of flute and the velocity decreases with the increase of flow length in flute. From the view of increasing the flow velocity of material near the bottom of the workpiece or in the middle of workpiece, the tool with the half-screw pin and the tool with the tapered-flute pin are both better than the conventional tool. PMID:28788426

Design of Friction Stir Welding Tool for Avoiding Root Flaws.

PubMed

Ji, Shude; Xing, Jingwei; Yue, Yumei; Ma, Yinan; Zhang, Liguo; Gao, Shuangsheng

2013-12-12

In order to improve material flow behavior during friction stir welding and avoid root flaws of weld, a tool with a half-screw pin and a tool with a tapered-flute pin are suggested. The effect of flute geometry in tool pins on material flow velocity is investigated by the software ANSYS FLUENT. Numerical simulation results show that high material flow velocity appears near the rotational tool and material flow velocity rapidly decreases with the increase of distance away from the axis of the tool. Maximum material flow velocity by the tool with the tapered-flute pin appears at the beginning position of flute and the velocity decreases with the increase of flow length in flute. From the view of increasing the flow velocity of material near the bottom of the workpiece or in the middle of workpiece, the tool with the half-screw pin and the tool with the tapered-flute pin are both better than the conventional tool.

A comparison of economic evaluation models as applied to geothermal energy technology

NASA Technical Reports Server (NTRS)

Ziman, G. M.; Rosenberg, L. S.

1983-01-01

Several cost estimation and financial cash flow models have been applied to a series of geothermal case studies. In order to draw conclusions about relative performance and applicability of these models to geothermal projects, the consistency of results was assessed. The model outputs of principal interest in this study were net present value, internal rate of return, or levelized breakeven price. The models used were VENVAL, a venture analysis model; the Geothermal Probabilistic Cost Model (GPC Model); the Alternative Power Systems Economic Analysis Model (APSEAM); the Geothermal Loan Guarantee Cash Flow Model (GCFM); and the GEOCOST and GEOCITY geothermal models. The case studies to which the models were applied include a geothermal reservoir at Heber, CA; a geothermal eletric power plant to be located at the Heber site; an alcohol fuels production facility to be built at Raft River, ID; and a direct-use, district heating system in Susanville, CA.

An extended continuous estimation of distribution algorithm for solving the permutation flow-shop scheduling problem

NASA Astrophysics Data System (ADS)

Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2017-11-01

This article proposes an extended continuous estimation of distribution algorithm (ECEDA) to solve the permutation flow-shop scheduling problem (PFSP). In ECEDA, to make a continuous estimation of distribution algorithm (EDA) suitable for the PFSP, the largest order value rule is applied to convert continuous vectors to discrete job permutations. A probabilistic model based on a mixed Gaussian and Cauchy distribution is built to maintain the exploration ability of the EDA. Two effective local search methods, i.e. revolver-based variable neighbourhood search and Hénon chaotic-based local search, are designed and incorporated into the EDA to enhance the local exploitation. The parameters of the proposed ECEDA are calibrated by means of a design of experiments approach. Simulation results and comparisons based on some benchmark instances show the efficiency of the proposed algorithm for solving the PFSP.

Derivation of Hunt equation for suspension distribution using Shannon entropy theory

NASA Astrophysics Data System (ADS)

Kundu, Snehasis

2017-12-01

In this study, the Hunt equation for computing suspension concentration in sediment-laden flows is derived using Shannon entropy theory. Considering the inverse of the void ratio as a random variable and using principle of maximum entropy, probability density function and cumulative distribution function of suspension concentration is derived. A new and more general cumulative distribution function for the flow domain is proposed which includes several specific other models of CDF reported in literature. This general form of cumulative distribution function also helps to derive the Rouse equation. The entropy based approach helps to estimate model parameters using suspension data of sediment concentration which shows the advantage of using entropy theory. Finally model parameters in the entropy based model are also expressed as functions of the Rouse number to establish a link between the parameters of the deterministic and probabilistic approaches.

Pedestrian headways - Reflection of territorial social forces

NASA Astrophysics Data System (ADS)

Krbálek, Milan; Hrabák, Pavel; Bukáček, Marek

2018-01-01

The aim of the article is to give a more detailed insight into territorial social forces acting between pedestrians by means of headway distribution and spectral rigidity. Probabilistic distribution of time headways between consecutive pedestrians is studied theoretically and experimentally. Several original experiments/empirical observations are presented and compared to data obtained from previously published experiments. The study is restricted to an unidirectional one-lane motion where overtaking is forbidden. The main stress is put on natural choices of mutual interaction represented by logarithmic and hyperbolic potentials leading to gamma and generalized inverse Gaussian distribution respectively. We show that the time headway distribution does not sufficiently reflect the differences between such distributions. The tools related to spectral rigidity and compressibility are chosen instead so as to predict the territorial social forces more accurately. Surprisingly, pedestrian flow seems to show a higher level of synchronization (lower compressibility) than vehicular flow.

Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD

NASA Technical Reports Server (NTRS)

Newman, Perry A.; Putko, Michele M.; Taylor, Arthur C., III

2004-01-01

A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.

Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets

DTIC Science & Technology

2015-04-24

Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Learning sparse feature representations is a useful instru- ment for solving an...novel framework for the classifi cation of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets... Learning Sparse Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Report Title Learning sparse feature representations is a useful

Information Flow in Interaction Networks II: Channels, Path Lengths, and Potentials

PubMed Central

Stojmirović, Aleksandar

2012-01-01

Abstract In our previous publication, a framework for information flow in interaction networks based on random walks with damping was formulated with two fundamental modes: emitting and absorbing. While many other network analysis methods based on random walks or equivalent notions have been developed before and after our earlier work, one can show that they can all be mapped to one of the two modes. In addition to these two fundamental modes, a major strength of our earlier formalism was its accommodation of context-specific directed information flow that yielded plausible and meaningful biological interpretation of protein functions and pathways. However, the directed flow from origins to destinations was induced via a potential function that was heuristic. Here, with a theoretically sound approach called the channel mode, we extend our earlier work for directed information flow. This is achieved by constructing a potential function facilitating a purely probabilistic interpretation of the channel mode. For each network node, the channel mode combines the solutions of emitting and absorbing modes in the same context, producing what we call a channel tensor. The entries of the channel tensor at each node can be interpreted as the amount of flow passing through that node from an origin to a destination. Similarly to our earlier model, the channel mode encompasses damping as a free parameter that controls the locality of information flow. Through examples involving the yeast pheromone response pathway, we illustrate the versatility and stability of our new framework. PMID:22409812

NASA Tech Briefs, March 2014

NASA Technical Reports Server (NTRS)

2014-01-01

Topics include: Data Fusion for Global Estimation of Forest Characteristics From Sparse Lidar Data; Debris and Ice Mapping Analysis Tool - Database; Data Acquisition and Processing Software - DAPS; Metal-Assisted Fabrication of Biodegradable Porous Silicon Nanostructures; Post-Growth, In Situ Adhesion of Carbon Nanotubes to a Substrate for Robust CNT Cathodes; Integrated PEMFC Flow Field Design for Gravity-Independent Passive Water Removal; Thermal Mechanical Preparation of Glass Spheres; Mechanistic-Based Multiaxial-Stochastic-Strength Model for Transversely-Isotropic Brittle Materials; Methods for Mitigating Space Radiation Effects, Fault Detection and Correction, and Processing Sensor Data; Compact Ka-Band Antenna Feed with Double Circularly Polarized Capability; Dual-Leadframe Transient Liquid Phase Bonded Power Semiconductor Module Assembly and Bonding Process; Quad First Stage Processor: A Four-Channel Digitizer and Digital Beam-Forming Processor; Protective Sleeve for a Pyrotechnic Reefing Line Cutter; Metabolic Heat Regenerated Temperature Swing Adsorption; CubeSat Deployable Log Periodic Dipole Array; Re-entry Vehicle Shape for Enhanced Performance; NanoRacks-Scale MEMS Gas Chromatograph System; Variable Camber Aerodynamic Control Surfaces and Active Wing Shaping Control; Spacecraft Line-of-Sight Stabilization Using LWIR Earth Signature; Technique for Finding Retro-Reflectors in Flash LIDAR Imagery; Novel Hemispherical Dynamic Camera for EVAs; 360 deg Visual Detection and Object Tracking on an Autonomous Surface Vehicle; Simulation of Charge Carrier Mobility in Conducting Polymers; Observational Data Formatter Using CMOR for CMIP5; Propellant Loading Physics Model for Fault Detection Isolation and Recovery; Probabilistic Guidance for Swarms of Autonomous Agents; Reducing Drift in Stereo Visual Odometry; Future Air-Traffic Management Concepts Evaluation Tool; Examination and A Priori Analysis of a Direct Numerical Simulation Database for High-Pressure Turbulent Flows; and Resource-Constrained Application of Support Vector Machines to Imagery.

Discriminative Random Field Models for Subsurface Contamination Uncertainty Quantification

NASA Astrophysics Data System (ADS)

Arshadi, M.; Abriola, L. M.; Miller, E. L.; De Paolis Kaluza, C.

2017-12-01

Application of flow and transport simulators for prediction of the release, entrapment, and persistence of dense non-aqueous phase liquids (DNAPLs) and associated contaminant plumes is a computationally intensive process that requires specification of a large number of material properties and hydrologic/chemical parameters. Given its computational burden, this direct simulation approach is particularly ill-suited for quantifying both the expected performance and uncertainty associated with candidate remediation strategies under real field conditions. Prediction uncertainties primarily arise from limited information about contaminant mass distributions, as well as the spatial distribution of subsurface hydrologic properties. Application of direct simulation to quantify uncertainty would, thus, typically require simulating multiphase flow and transport for a large number of permeability and release scenarios to collect statistics associated with remedial effectiveness, a computationally prohibitive process. The primary objective of this work is to develop and demonstrate a methodology that employs measured field data to produce equi-probable stochastic representations of a subsurface source zone that capture the spatial distribution and uncertainty associated with key features that control remediation performance (i.e., permeability and contamination mass). Here we employ probabilistic models known as discriminative random fields (DRFs) to synthesize stochastic realizations of initial mass distributions consistent with known, and typically limited, site characterization data. Using a limited number of full scale simulations as training data, a statistical model is developed for predicting the distribution of contaminant mass (e.g., DNAPL saturation and aqueous concentration) across a heterogeneous domain. Monte-Carlo sampling methods are then employed, in conjunction with the trained statistical model, to generate realizations conditioned on measured borehole data. Performance of the statistical model is illustrated through comparisons of generated realizations with the `true' numerical simulations. Finally, we demonstrate how these realizations can be used to determine statistically optimal locations for further interrogation of the subsurface.

UPIOM: a new tool of MFA and its application to the flow of iron and steel associated with car production.

PubMed

Nakamura, Shinichiro; Kondo, Yasushi; Matsubae, Kazuyo; Nakajima, Kenichi; Nagasaka, Tetsuya

2011-02-01

Identification of the flow of materials and substances associated with a product system provides useful information for Life Cycle Analysis (LCA), and contributes to extending the scope of complementarity between LCA and Materials Flow Analysis/Substances Flow Analysis (MFA/SFA), the two major tools of industrial ecology. This paper proposes a new methodology based on input-output analysis for identifying the physical input-output flow of individual materials that is associated with the production of a unit of given product, the unit physical input-output by materials (UPIOM). While the Sankey diagram has been a standard tool for the visualization of MFA/SFA, with an increase in the complexity of the flows under consideration, which will be the case when economy-wide intersectoral flows of materials are involved, the Sankey diagram may become too complex for effective visualization. An alternative way to visually represent material flows is proposed which makes use of triangulation of the flow matrix based on degrees of fabrication. The proposed methodology is applied to the flow of pig iron and iron and steel scrap that are associated with the production of a passenger car in Japan. Its usefulness to identify a specific MFA pattern from the original IO table is demonstrated.

Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modelling heteroscedastic residual errors

NASA Astrophysics Data System (ADS)

David, McInerney; Mark, Thyer; Dmitri, Kavetski; George, Kuczera

2017-04-01

This study provides guidance to hydrological researchers which enables them to provide probabilistic predictions of daily streamflow with the best reliability and precision for different catchment types (e.g. high/low degree of ephemerality). Reliable and precise probabilistic prediction of daily catchment-scale streamflow requires statistical characterization of residual errors of hydrological models. It is commonly known that hydrological model residual errors are heteroscedastic, i.e. there is a pattern of larger errors in higher streamflow predictions. Although multiple approaches exist for representing this heteroscedasticity, few studies have undertaken a comprehensive evaluation and comparison of these approaches. This study fills this research gap by evaluating 8 common residual error schemes, including standard and weighted least squares, the Box-Cox transformation (with fixed and calibrated power parameter, lambda) and the log-sinh transformation. Case studies include 17 perennial and 6 ephemeral catchments in Australia and USA, and two lumped hydrological models. We find the choice of heteroscedastic error modelling approach significantly impacts on predictive performance, though no single scheme simultaneously optimizes all performance metrics. The set of Pareto optimal schemes, reflecting performance trade-offs, comprises Box-Cox schemes with lambda of 0.2 and 0.5, and the log scheme (lambda=0, perennial catchments only). These schemes significantly outperform even the average-performing remaining schemes (e.g., across ephemeral catchments, median precision tightens from 105% to 40% of observed streamflow, and median biases decrease from 25% to 4%). Theoretical interpretations of empirical results highlight the importance of capturing the skew/kurtosis of raw residuals and reproducing zero flows. Recommendations for researchers and practitioners seeking robust residual error schemes for practical work are provided.

Discrete Element Method Modeling of Bedload Transport: Towards a physics-based link between bed surface variability and particle entrainment statistics

NASA Astrophysics Data System (ADS)

Ghasemi, A.; Borhani, S.; Viparelli, E.; Hill, K. M.

2017-12-01

The Exner equation provides a formal mathematical link between sediment transport and bed morphology. It is typically represented in a discrete formulation where there is a sharp geometric interface between the bedload layer and the bed, below which no particles are entrained. For high temporally and spatially resolved models, this is strictly correct, but typically this is applied in such a way that spatial and temporal fluctuations in the bed surface (bedforms and otherwise) are not captured. This limits the extent to which the exchange between particles in transport and the sediment bed are properly represented, particularly problematic for mixed grain size distributions that exhibit segregation. Nearly two decades ago, Parker (2000) provided a framework for a solution to this dilemma in the form of a probabilistic Exner equation, partially experimentally validated by Wong et al. (2007). We present a computational study designed to develop a physics-based framework for understanding the interplay between physical parameters of the bed and flow and parameters in the Parker (2000) probabilistic formulation. To do so we use Discrete Element Method simulations to relate local time-varying parameters to long-term macroscopic parameters. These include relating local grain size distribution and particle entrainment and deposition rates to long- average bed shear stress and the standard deviation of bed height variations. While relatively simple, these simulations reproduce long-accepted empirically determined transport behaviors such as the Meyer-Peter and Muller (1948) relationship. We also find that these simulations reproduce statistical relationships proposed by Wong et al. (2007) such as a Gaussian distribution of bed heights whose standard deviation increases with increasing bed shear stress. We demonstrate how the ensuing probabilistic formulations provide insight into the transport and deposition of both narrow and wide grain size distribution.

Evaluation of ensemble forecast uncertainty using a new proper score: application to medium-range and seasonal forecasts

NASA Astrophysics Data System (ADS)

Christensen, Hannah; Moroz, Irene; Palmer, Tim

2015-04-01

Forecast verification is important across scientific disciplines as it provides a framework for evaluating the performance of a forecasting system. In the atmospheric sciences, probabilistic skill scores are often used for verification as they provide a way of unambiguously ranking the performance of different probabilistic forecasts. In order to be useful, a skill score must be proper -- it must encourage honesty in the forecaster, and reward forecasts which are reliable and which have good resolution. A new score, the Error-spread Score (ES), is proposed which is particularly suitable for evaluation of ensemble forecasts. It is formulated with respect to the moments of the forecast. The ES is confirmed to be a proper score, and is therefore sensitive to both resolution and reliability. The ES is tested on forecasts made using the Lorenz '96 system, and found to be useful for summarising the skill of the forecasts. The European Centre for Medium-Range Weather Forecasts (ECMWF) ensemble prediction system (EPS) is evaluated using the ES. Its performance is compared to a perfect statistical probabilistic forecast -- the ECMWF high resolution deterministic forecast dressed with the observed error distribution. This generates a forecast that is perfectly reliable if considered over all time, but which does not vary from day to day with the predictability of the atmospheric flow. The ES distinguishes between the dynamically reliable EPS forecasts and the statically reliable dressed deterministic forecasts. Other skill scores are tested and found to be comparatively insensitive to this desirable forecast quality. The ES is used to evaluate seasonal range ensemble forecasts made with the ECMWF System 4. The ensemble forecasts are found to be skilful when compared with climatological or persistence forecasts, though this skill is dependent on region and time of year.

Assessment of SWE data assimilation for ensemble streamflow predictions

NASA Astrophysics Data System (ADS)

Franz, Kristie J.; Hogue, Terri S.; Barik, Muhammad; He, Minxue

2014-11-01

An assessment of data assimilation (DA) for Ensemble Streamflow Prediction (ESP) using seasonal water supply hindcasting in the North Fork of the American River Basin (NFARB) and the National Weather Service (NWS) hydrologic forecast models is undertaken. Two parameter sets, one from the California Nevada River Forecast Center (RFC) and one from the Differential Evolution Adaptive Metropolis (DREAM) algorithm, are tested. For each parameter set, hindcasts are generated using initial conditions derived with and without the inclusion of a DA scheme that integrates snow water equivalent (SWE) observations. The DREAM-DA scenario uses an Integrated Uncertainty and Ensemble-based data Assimilation (ICEA) framework that also considers model and parameter uncertainty. Hindcasts are evaluated using deterministic and probabilistic forecast verification metrics. In general, the impact of DA on the skill of the seasonal water supply predictions is mixed. For deterministic (ensemble mean) predictions, the Percent Bias (PBias) is improved with integration of the DA. DREAM-DA and the RFC-DA have the lowest biases and the RFC-DA has the lowest Root Mean Squared Error (RMSE). However, the RFC and DREAM-DA have similar RMSE scores. For the probabilistic predictions, the RFC and DREAM have the highest Continuous Ranked Probability Skill Scores (CRPSS) and the RFC has the best discrimination for low flows. Reliability results are similar between the non-DA and DA tests and the DREAM and DREAM-DA have better reliability than the RFC and RFC-DA for forecast dates February 1 and later. Despite producing improved streamflow simulations in previous studies, the hindcast analysis suggests that the DA method tested may not result in obvious improvements in streamflow forecasts. We advocate that integration of hindcasting and probabilistic metrics provides more rigorous insight on model performance for forecasting applications, such as in this study.

Forward ultrasonic model validation using wavefield imaging methods

NASA Astrophysics Data System (ADS)

Blackshire, James L.

2018-04-01

The validation of forward ultrasonic wave propagation models in a complex titanium polycrystalline material system is accomplished using wavefield imaging methods. An innovative measurement approach is described that permits the visualization and quantitative evaluation of bulk elastic wave propagation and scattering behaviors in the titanium material for a typical focused immersion ultrasound measurement process. Results are provided for the determination and direct comparison of the ultrasonic beam's focal properties, mode-converted shear wave position and angle, and scattering and reflection from millimeter-sized microtexture regions (MTRs) within the titanium material. The approach and results are important with respect to understanding the root-cause backscatter signal responses generated in aerospace engine materials, where model-assisted methods are being used to understand the probabilistic nature of the backscatter signal content. Wavefield imaging methods are shown to be an effective means for corroborating and validating important forward model predictions in a direct manner using time- and spatially-resolved displacement field amplitude measurements.

Processing of probabilistic information in weight perception and motor prediction.

PubMed

Trampenau, Leif; van Eimeren, Thilo; Kuhtz-Buschbeck, Johann

2017-02-01

We studied the effects of probabilistic cues, i.e., of information of limited certainty, in the context of an action task (GL: grip-lift) and of a perceptual task (WP: weight perception). Normal subjects (n = 22) saw four different probabilistic visual cues, each of which announced the likely weight of an object. In the GL task, the object was grasped and lifted with a pinch grip, and the peak force rates indicated that the grip and load forces were scaled predictively according to the probabilistic information. The WP task provided the expected heaviness related to each probabilistic cue; the participants gradually adjusted the object's weight until its heaviness matched the expected weight for a given cue. Subjects were randomly assigned to two groups: one started with the GL task and the other one with the WP task. The four different probabilistic cues influenced weight adjustments in the WP task and peak force rates in the GL task in a similar manner. The interpretation and utilization of the probabilistic information was critically influenced by the initial task. Participants who started with the WP task classified the four probabilistic cues into four distinct categories and applied these categories to the subsequent GL task. On the other side, participants who started with the GL task applied three distinct categories to the four cues and retained this classification in the following WP task. The initial strategy, once established, determined the way how the probabilistic information was interpreted and implemented.

Relative risk of probabilistic category learning deficits in patients with schizophrenia and their siblings

PubMed Central

Weickert, Thomas W.; Goldberg, Terry E.; Egan, Michael F.; Apud, Jose A.; Meeter, Martijn; Myers, Catherine E.; Gluck, Mark A; Weinberger, Daniel R.

2010-01-01

Background While patients with schizophrenia display an overall probabilistic category learning performance deficit, the extent to which this deficit occurs in unaffected siblings of patients with schizophrenia is unknown. There are also discrepant findings regarding probabilistic category learning acquisition rate and performance in patients with schizophrenia. Methods A probabilistic category learning test was administered to 108 patients with schizophrenia, 82 unaffected siblings, and 121 healthy participants. Results Patients with schizophrenia displayed significant differences from their unaffected siblings and healthy participants with respect to probabilistic category learning acquisition rates. Although siblings on the whole failed to differ from healthy participants on strategy and quantitative indices of overall performance and learning acquisition, application of a revised learning criterion enabling classification into good and poor learners based on individual learning curves revealed significant differences between percentages of sibling and healthy poor learners: healthy (13.2%), siblings (34.1%), patients (48.1%), yielding a moderate relative risk. Conclusions These results clarify previous discrepant findings pertaining to probabilistic category learning acquisition rate in schizophrenia and provide the first evidence for the relative risk of probabilistic category learning abnormalities in unaffected siblings of patients with schizophrenia, supporting genetic underpinnings of probabilistic category learning deficits in schizophrenia. These findings also raise questions regarding the contribution of antipsychotic medication to the probabilistic category learning deficit in schizophrenia. The distinction between good and poor learning may be used to inform genetic studies designed to detect schizophrenia risk alleles. PMID:20172502

Crushed cement concrete substitution for construction aggregates; a materials flow analysis

USGS Publications Warehouse

Kelly, Thomas

1998-01-01

An analysis of the substitution of crushed cement concrete for natural construction aggregates is performed by using a materials flow diagram that tracks all material flows into and out of the cement concrete portion of the products made with cement concrete: highways, roads, and buildings. Crushed cement concrete is only one of the materials flowing into these products, and the amount of crushed cement concrete substituted influences the amount of other materials in the flow. Factors such as availability and transportation costs, as well as physical properties, that can affect stability and finishability, influence whether crushed cement concrete or construction aggregates should be used or predominate for a particular end use.

Probabilistic Analysis for Comparing Fatigue Data Based on Johnson-Weibull Parameters

NASA Technical Reports Server (NTRS)

Hendricks, Robert C.; Zaretsky, Erwin V.; Vicek, Brian L.

2007-01-01

Probabilistic failure analysis is essential when analysis of stress-life (S-N) curves is inconclusive in determining the relative ranking of two or more materials. In 1964, L. Johnson published a methodology for establishing the confidence that two populations of data are different. Simplified algebraic equations for confidence numbers were derived based on the original work of L. Johnson. Using the ratios of mean life, the resultant values of confidence numbers deviated less than one percent from those of Johnson. It is possible to rank the fatigue lives of different materials with a reasonable degree of statistical certainty based on combined confidence numbers. These equations were applied to rotating beam fatigue tests that were conducted on three aluminum alloys at three stress levels each. These alloys were AL 2024, AL 6061, and AL 7075. The results were analyzed and compared using ASTM Standard E739-91 and the Johnson-Weibull analysis. The ASTM method did not statistically distinguish between AL 6010 and AL 7075. Based on the Johnson-Weibull analysis confidence numbers greater than 99 percent, AL 2024 was found to have the longest fatigue life, followed by AL 7075, and then AL 6061. The ASTM Standard and the Johnson-Weibull analysis result in the same stress-life exponent p for each of the three aluminum alloys at the median or L(sub 50) lives.

Klinkenberg effect in hydrodynamics of gas flow through anisotropic porous materials

NASA Astrophysics Data System (ADS)

Wałowski, Grzegorz; Filipczak, Gabriel

2017-10-01

This study discusses results of experiments on hydrodynamic assessment of gas flow through backbone (skeletal) porous materials with an anisotropic structure. The research was conducted upon materials of diversified petrographic characteristics, both natural origin (rocky, pumice) and process materials (char and coke). The study was conducted for a variety of hydrodynamic conditions, using air, as well as for nitrogen and carbon dioxide. The basis for assessing hydrodynamics of gas flow through porous material was a gas stream that results from the pressure forcing such flow. The results of measurements indicate a clear impact of the type of material on the gas permeability, and additionally - as a result of their anisotropic internal structure - to a significant effect of the flow direction on the value of gas stream.

A Hough Transform Global Probabilistic Approach to Multiple-Subject Diffusion MRI Tractography

DTIC Science & Technology

2010-04-01

distribution unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT A global probabilistic fiber tracking approach based on the voting process provided by...umn.edu 2 ABSTRACT A global probabilistic fiber tracking approach based on the voting process provided by the Hough transform is introduced in...criteria for aligning curves and particularly tracts. In this work, we present a global probabilistic approach inspired by the voting procedure provided

Preferential flow in municipal solid waste and implications for long-term leachate quality: valuation of laboratory-scale experiments.

PubMed

Rosqvist, N H; Dollar, L H; Fourie, A B

2005-08-01

In this paper, we study and quantify pollutant concentrations after long-term leaching at relatively low flow rates and residual concentrations after heavy flushing of a 0.14 m3 municipal solid waste sample. Moreover, water flow and solute transport through preferential flow paths are studied by model interpretation of experimental break-through curves (BTCs), generated by tracer tests. In the study it was found that high concentrations of chloride remain after several pore volumes of water have percolated through the waste sample. The residual concentration was found to be considerably higher than can be predicted by degradation models. For model interpretations of the experimental BTCs, two probabilistic model approaches were applied, the transfer function model and the Lagrangian transport formulation. The experimental BTCs indicated the presence of preferential flow through the waste mass and the model interpretation of the BTCs suggested that between 19 and 41% of the total water content participated in the transport of solute through preferential flow paths. In the study, the occurrence of preferential flow was found to be dependent on the flow rate in the sense that a high flow rate enhances the preferential flow. However, to fully quantify the possible dependence between flow rate and preferential flow, experiments on a broader range of experimental conditions are suggested. The chloride washout curve obtained over the 4-year study period shows that as a consequence of the water flow in favoured flow paths, bypassing other parts of the solid waste body, the leachate quality may reflect only the flow paths and their surroundings. The results in this study thus show that in order to improve long-term prediction of the leachate quality and quantity the magnitude of the preferential water flow through a landfill must be taken into account.

A Game-Theoretic Approach to Information-Flow Control via Protocol Composition

NASA Astrophysics Data System (ADS)

Alvim, Mário; Chatzikokolakis, Konstantinos; Kawamoto, Yusuke; Palamidessi, Catuscia

2018-05-01

In the inference attacks studied in Quantitative Information Flow (QIF), the attacker typically tries to interfere with the system in the attempt to increase its leakage of secret information. The defender, on the other hand, typically tries to decrease leakage by introducing some controlled noise. This noise introduction can be modeled as a type of protocol composition, i.e., a probabilistic choice among different protocols, and its effect on the amount of leakage depends heavily on whether or not this choice is visible to the attacker. In this work, we consider operators for modeling visible and hidden choice in protocol composition, and we study their algebraic properties. We then formalize the interplay between defender and attacker in a game-theoretic framework adapted to the specific issues of QIF, where the payoff is information leakage. We consider various kinds of leakage games, depending on whether players act simultaneously or sequentially, and on whether or not the choices of the defender are visible to the attacker. In the case of sequential games, the choice of the second player is generally a function of the choice of the first player, and his/her probabilistic choice can be either over the possible functions (mixed strategy) or it can be on the result of the function (behavioral strategy). We show that when the attacker moves first in a sequential game with a hidden choice, then behavioral strategies are more advantageous for the defender than mixed strategies. This contrasts with the standard game theory, where the two types of strategies are equivalent. Finally, we establish a hierarchy of these games in terms of their information leakage and provide methods for finding optimal strategies (at the points of equilibrium) for both attacker and defender in the various cases.

Multivariate decoding of brain images using ordinal regression.

PubMed

Doyle, O M; Ashburner, J; Zelaya, F O; Williams, S C R; Mehta, M A; Marquand, A F

2013-11-01

Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found that ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine data set, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection. Copyright © 2013. Published by Elsevier Inc.

Probabilistic human health risk assessment of degradation-related chemical mixtures in heterogeneous aquifers: Risk statistics, hot spots, and preferential channels

NASA Astrophysics Data System (ADS)

Henri, Christopher V.; Fernàndez-Garcia, Daniel; de Barros, Felipe P. J.

2015-06-01

The increasing presence of toxic chemicals released in the subsurface has led to a rapid growth of social concerns and the need to develop and employ models that can predict the impact of groundwater contamination on human health risk under uncertainty. Monitored natural attenuation is a common remediation action in many contamination cases. However, natural attenuation can lead to the production of daughter species of distinct toxicity that may pose challenges in pollution management strategies. The actual threat that these contaminants pose to human health depends on the interplay between the complex structure of the geological media and the toxicity of each pollutant byproduct. This work addresses human health risk for chemical mixtures resulting from the sequential degradation of a contaminant (such as a chlorinated solvent) under uncertainty through high-resolution three-dimensional numerical simulations. We systematically investigate the interaction between aquifer heterogeneity, flow connectivity, contaminant injection model, and chemical toxicity in the probabilistic characterization of health risk. We illustrate how chemical-specific travel times control the regime of the expected risk and its corresponding uncertainties. Results indicate conditions where preferential flow paths can favor the reduction of the overall risk of the chemical mixture. The overall human risk response to aquifer connectivity is shown to be nontrivial for multispecies transport. This nontriviality is a result of the interaction between aquifer heterogeneity and chemical toxicity. To quantify the joint effect of connectivity and toxicity in health risk, we propose a toxicity-based Damköhler number. Furthermore, we provide a statistical characterization in terms of low-order moments and the probability density function of the individual and total risks.

A multi points ultrasonic detection method for material flow of belt conveyor

NASA Astrophysics Data System (ADS)

Zhang, Li; He, Rongjun

2018-03-01

For big detection error of single point ultrasonic ranging technology used in material flow detection of belt conveyor when coal distributes unevenly or is large, a material flow detection method of belt conveyor is designed based on multi points ultrasonic counter ranging technology. The method can calculate approximate sectional area of material by locating multi points on surfaces of material and belt, in order to get material flow according to running speed of belt conveyor. The test results show that the method has smaller detection error than single point ultrasonic ranging technology under the condition of big coal with uneven distribution.

Dynamic Stability of Uncertain Laminated Beams Under Subtangential Loads

NASA Technical Reports Server (NTRS)

Goyal, Vijay K.; Kapania, Rakesh K.; Adelman, Howard (Technical Monitor); Horta, Lucas (Technical Monitor)

2002-01-01

Because of the inherent complexity of fiber-reinforced laminated composites, it can be challenging to manufacture composite structures according to their exact design specifications, resulting in unwanted material and geometric uncertainties. In this research, we focus on the deterministic and probabilistic stability analysis of laminated structures subject to subtangential loading, a combination of conservative and nonconservative tangential loads, using the dynamic criterion. Thus a shear-deformable laminated beam element, including warping effects, is derived to study the deterministic and probabilistic response of laminated beams. This twenty-one degrees of freedom element can be used for solving both static and dynamic problems. In the first-order shear deformable model used here we have employed a more accurate method to obtain the transverse shear correction factor. The dynamic version of the principle of virtual work for laminated composites is expressed in its nondimensional form and the element tangent stiffness and mass matrices are obtained using analytical integration The stability is studied by giving the structure a small disturbance about an equilibrium configuration, and observing if the resulting response remains small. In order to study the dynamic behavior by including uncertainties into the problem, three models were developed: Exact Monte Carlo Simulation, Sensitivity Based Monte Carlo Simulation, and Probabilistic FEA. These methods were integrated into the developed finite element analysis. Also, perturbation and sensitivity analysis have been used to study nonconservative problems, as well as to study the stability analysis, using the dynamic criterion.

Probabilistic failure analysis of bone using a finite element model of mineral-collagen composites.

PubMed

Dong, X Neil; Guda, Teja; Millwater, Harry R; Wang, Xiaodu

2009-02-09

Microdamage accumulation is a major pathway for energy dissipation during the post-yield deformation of bone. In this study, a two-dimensional probabilistic finite element model of a mineral-collagen composite was developed to investigate the influence of the tissue and ultrastructural properties of bone on the evolution of microdamage from an initial defect in tension. The probabilistic failure analyses indicated that the microdamage progression would be along the plane of the initial defect when the debonding at mineral-collagen interfaces was either absent or limited in the vicinity of the defect. In this case, the formation of a linear microcrack would be facilitated. However, the microdamage progression would be scattered away from the initial defect plane if interfacial debonding takes place at a large scale. This would suggest the possible formation of diffuse damage. In addition to interfacial debonding, the sensitivity analyses indicated that the microdamage progression was also dependent on the other material and ultrastructural properties of bone. The intensity of stress concentration accompanied with microdamage progression was more sensitive to the elastic modulus of the mineral phase and the nonlinearity of the collagen phase, whereas the scattering of failure location was largely dependent on the mineral to collagen ratio and the nonlinearity of the collagen phase. The findings of this study may help understanding the post-yield behavior of bone at the ultrastructural level and shed light on the underlying mechanism of bone fractures.

Probabilistic Failure Analysis of Bone Using a Finite Element Model of Mineral-Collagen Composites

PubMed Central

Dong, X. Neil; Guda, Teja; Millwater, Harry R.; Wang, Xiaodu

2009-01-01

Microdamage accumulation is a major pathway for energy dissipation during the post-yield deformation of bone. In this study, a two-dimensional probabilistic finite element model of a mineral-collagen composite was developed to investigate the influence of the tissue and ultrastructural properties of bone on the evolution of microdamage from an initial defect in tension. The probabilistic failure analyses indicated that the microdamage progression would be along the plane of the initial defect when the debonding at mineral-collagen interfaces was either absent or limited in the vicinity of the defect. In this case, the formation of a linear microcrack would be facilitated. However, the microdamage progression would be scattered away from the initial defect plane if interfacial debonding takes place at a large scale. This would suggest the possible formation of diffuse damage. In addition to interfacial debonding, the sensitivity analyses indicated that the microdamage progression was also dependent on the other material and ultrastructural properties of bone. The intensity of stress concentration accompanied with microdamage progression was more sensitive to the elastic modulus of the mineral phase and the nonlinearity of the collagen phase, whereas the scattering of failure location was largely dependent on the mineral to collagen ratio and the nonlinearity of the collagen phase. The findings of this study may help understanding the post-yield behavior of bone at the ultrastructural level and shed light on the underlying mechanism of bone fractures. PMID:19058806

Optic flow detection is not influenced by visual-vestibular congruency.

PubMed

Holten, Vivian; MacNeilage, Paul R

2018-01-01

Optic flow patterns generated by self-motion relative to the stationary environment result in congruent visual-vestibular self-motion signals. Incongruent signals can arise due to object motion, vestibular dysfunction, or artificial stimulation, which are less common. Hence, we are predominantly exposed to congruent rather than incongruent visual-vestibular stimulation. If the brain takes advantage of this probabilistic association, we expect observers to be more sensitive to visual optic flow that is congruent with ongoing vestibular stimulation. We tested this expectation by measuring the motion coherence threshold, which is the percentage of signal versus noise dots, necessary to detect an optic flow pattern. Observers seated on a hexapod motion platform in front of a screen experienced two sequential intervals. One interval contained optic flow with a given motion coherence and the other contained noise dots only. Observers had to indicate which interval contained the optic flow pattern. The motion coherence threshold was measured for detection of laminar and radial optic flow during leftward/rightward and fore/aft linear self-motion, respectively. We observed no dependence of coherence thresholds on vestibular congruency for either radial or laminar optic flow. Prior studies using similar methods reported both decreases and increases in coherence thresholds in response to congruent vestibular stimulation; our results do not confirm either of these prior reports. While methodological differences may explain the diversity of results, another possibility is that motion coherence thresholds are mediated by neural populations that are either not modulated by vestibular stimulation or that are modulated in a manner that does not depend on congruency.

Mapping and DOWNFLOW simulation of recent lava flow fields at Mount Etna

NASA Astrophysics Data System (ADS)

Tarquini, Simone; Favalli, Massimiliano

2011-07-01

In recent years, progress in geographic information systems (GIS) and remote sensing techniques have allowed the mapping and studying of lava flows in unprecedented detail. A composite GIS technique is introduced to obtain high resolution boundaries of lava flow fields. This technique is mainly based on the processing of LIDAR-derived maps and digital elevation models (DEMs). The probabilistic code DOWNFLOW is then used to simulate eight large flow fields formed at Mount Etna in the last 25 years. Thanks to the collection of 6 DEMs representing Mount Etna at different times from 1986 to 2007, simulated outputs are obtained by running the DOWNFLOW code over pre-emplacement topographies. Simulation outputs are compared with the boundaries of the actual flow fields obtained here or derived from the existing literature. Although the selected fields formed in accordance with different emplacement mechanisms, flowed on different zones of the volcano over different topographies and were fed by different lava supplies of different durations, DOWNFLOW yields results close to the actual flow fields in all the cases considered. This outcome is noteworthy because DOWNFLOW has been applied by adopting a default calibration, without any specific tuning for the new cases considered here. This extensive testing proves that, if the pre-emplacement topography is available, DOWNFLOW yields a realistic simulation of a future lava flow based solely on a knowledge of the vent position. In comparison with deterministic codes, which require accurate knowledge of a large number of input parameters, DOWNFLOW turns out to be simple, fast and undemanding, proving to be ideal for systematic hazard and risk analyses.

Building the Material Flow Networks of Aluminum in the 2007 U.S. Economy.

PubMed

Chen, Wei-Qiang; Graedel, T E; Nuss, Philip; Ohno, Hajime

2016-04-05

Based on the combination of the U.S. economic input-output table and the stocks and flows framework for characterizing anthropogenic metal cycles, this study presents a methodology for building material flow networks of bulk metals in the U.S. economy and applies it to aluminum. The results, which we term the Input-Output Material Flow Networks (IO-MFNs), achieve a complete picture of aluminum flow in the entire U.S. economy and for any chosen industrial sector (illustrated for the Automobile Manufacturing sector). The results are compared with information from our former study on U.S. aluminum stocks and flows to demonstrate the robustness and value of this new methodology. We find that the IO-MFN approach has the following advantages: (1) it helps to uncover the network of material flows in the manufacturing stage in the life cycle of metals; (2) it provides a method that may be less time-consuming but more complete and accurate in estimating new scrap generation, process loss, domestic final demand, and trade of final products of metals, than existing material flow analysis approaches; and, most importantly, (3) it enables the analysis of the material flows of metals in the U.S. economy from a network perspective, rather than merely that of a life cycle chain.

Numerical investigation of debris materials prior to debris flow hazards using satellite images

NASA Astrophysics Data System (ADS)

Zhang, N.; Matsushima, T.

2018-05-01

The volume of debris flows occurred in mountainous areas is mainly affected by the volume of debris materials deposited at the valley bottom. Quantitative evaluation of debris materials prior to debris flow hazards is important to predict and prevent hazards. At midnight on 7th August 2010, two catastrophic debris flows were triggered by the torrential rain from two valleys in the northern part of Zhouqu City, NW China, resulting in 1765 fatalities and huge economic losses. In the present study, a depth-integrated particle method is adopted to simulate the debris materials, based on 2.5 m resolution satellite images. In the simulation scheme, the materials are modeled as dry granular solids, and they travel down from the slopes and are deposited at the valley bottom. The spatial distributions of the debris materials are investigated in terms of location, volume and thickness. Simulation results show good agreement with post-disaster satellite images and field observation data. Additionally, the effect of the spatial distributions of the debris materials on subsequent debris flows is also evaluated. It is found that the spatial distributions of the debris materials strongly influence affected area, runout distance and flow discharge. This study might be useful in hazard assessments prior to debris flow hazards by investigating diverse scenarios in which the debris materials are unknown.

Probabilistic structural analysis methods of hot engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1989-01-01

Development of probabilistic structural analysis methods for hot engine structures is a major activity at Lewis Research Center. Recent activities have focused on extending the methods to include the combined uncertainties in several factors on structural response. This paper briefly describes recent progress on composite load spectra models, probabilistic finite element structural analysis, and probabilistic strength degradation modeling. Progress is described in terms of fundamental concepts, computer code development, and representative numerical results.

Probabilistic record linkage

PubMed Central

Sayers, Adrian; Ben-Shlomo, Yoav; Blom, Ashley W; Steele, Fiona

2016-01-01

Abstract Studies involving the use of probabilistic record linkage are becoming increasingly common. However, the methods underpinning probabilistic record linkage are not widely taught or understood, and therefore these studies can appear to be a ‘black box’ research tool. In this article, we aim to describe the process of probabilistic record linkage through a simple exemplar. We first introduce the concept of deterministic linkage and contrast this with probabilistic linkage. We illustrate each step of the process using a simple exemplar and describe the data structure required to perform a probabilistic linkage. We describe the process of calculating and interpreting matched weights and how to convert matched weights into posterior probabilities of a match using Bayes theorem. We conclude this article with a brief discussion of some of the computational demands of record linkage, how you might assess the quality of your linkage algorithm, and how epidemiologists can maximize the value of their record-linked research using robust record linkage methods. PMID:26686842

CARES/Life Ceramics Durability Evaluation Software Used for Mars Microprobe Aeroshell

NASA Technical Reports Server (NTRS)

Nemeth, Noel N.

1998-01-01

The CARES/Life computer program, which was developed at the NASA Lewis Research Center, predicts the probability of a monolithic ceramic component's failure as a function of time in service. The program has many features and options for materials evaluation and component design. It couples commercial finite element programs-which resolve a component's temperature and stress distribution-to-reliability evaluation and fracture mechanics routines for modeling strength-limiting defects. These routines are based on calculations of the probabilistic nature of the brittle material's strength. The capability, flexibility, and uniqueness of CARES/Life has attracted many users representing a broad range of interests and has resulted in numerous awards for technological achievements and technology transfer.

Applicable research in practice: understanding the hydrophilic and flow property measurements of impression materials.

PubMed

Perry, Ronald D; Goldberg, Jeffrey A; Benchimol, Jacques; Orfanidis, John

2006-10-01

The flow properties and hydrophilicity of an impression material are key factors that affect its performance. This article details in vitro studies comparing these properties in 1 polyether and several vinyl polysiloxane light-body impression materials. The first series of studies examined the materials' flow properties used in a "shark fin" measurement procedure to determine which exhibited superior flow characteristics. The second series of studies reviewed the hydrophilic properties of the materials. Video analysis was used to record contact angle measurements at the early- and late-stage working times. Results showed 1 polyether material to be more hydrophilic. Applying this knowledge to practice, the authors present a clinical case in which a polyether's superior flow and quality of detail were used to make impressions for a patient receiving 8 single-unit zirconia crowns.

Statistical Analyses of Raw Material Data for MTM45-1/CF7442A-36% RW: CMH Cure Cycle

NASA Technical Reports Server (NTRS)

Coroneos, Rula; Pai, Shantaram, S.; Murthy, Pappu

2013-01-01

This report describes statistical characterization of physical properties of the composite material system MTM45-1/CF7442A, which has been tested and is currently being considered for use on spacecraft structures. This composite system is made of 6K plain weave graphite fibers in a highly toughened resin system. This report summarizes the distribution types and statistical details of the tests and the conditions for the experimental data generated. These distributions will be used in multivariate regression analyses to help determine material and design allowables for similar material systems and to establish a procedure for other material systems. Additionally, these distributions will be used in future probabilistic analyses of spacecraft structures. The specific properties that are characterized are the ultimate strength, modulus, and Poisson??s ratio by using a commercially available statistical package. Results are displayed using graphical and semigraphical methods and are included in the accompanying appendixes.

Probabilistic Structural Analysis of the Solid Rocket Booster Aft Skirt External Fitting Modification

NASA Technical Reports Server (NTRS)

Townsend, John S.; Peck, Jeff; Ayala, Samuel

2000-01-01

NASA has funded several major programs (the Probabilistic Structural Analysis Methods Project is an example) to develop probabilistic structural analysis methods and tools for engineers to apply in the design and assessment of aerospace hardware. A probabilistic finite element software code, known as Numerical Evaluation of Stochastic Structures Under Stress, is used to determine the reliability of a critical weld of the Space Shuttle solid rocket booster aft skirt. An external bracket modification to the aft skirt provides a comparison basis for examining the details of the probabilistic analysis and its contributions to the design process. Also, analysis findings are compared with measured Space Shuttle flight data.

Architected squirt-flow materials for energy dissipation

NASA Astrophysics Data System (ADS)

Cohen, Tal; Kurzeja, Patrick; Bertoldi, Katia

2017-12-01

In the present study we explore material architectures that lead to enhanced dissipation properties by taking advantage of squirt-flow - a local flow mechanism triggered by heterogeneities at the pore level. While squirt-flow is a known dominant source of dissipation and seismic attenuation in fluid saturated geological materials, we study its untapped potential to be incorporated in highly deformable elastic materials with embedded fluid-filled cavities for future engineering applications. An analytical investigation, that isolates the squirt-flow mechanism from other potential dissipation mechanisms and considers an idealized setting, predicts high theoretical levels of dissipation achievable by squirt-flow and establishes a set of guidelines for optimal dissipation design. Particular architectures are then investigated via numerical simulations showing that a careful design of the internal voids can lead to an increase of dissipation levels by an order of magnitude, compared with equivalent homogeneous void distributions. Therefore, we suggest squirt-flow as a promising mechanism to be incorporated in future architected materials to effectively and reversibly dissipate energy.

DISCOUNTING OF DELAYED AND PROBABILISTIC LOSSES OVER A WIDE RANGE OF AMOUNTS

PubMed Central

Green, Leonard; Myerson, Joel; Oliveira, Luís; Chang, Seo Eun

2014-01-01

The present study examined delay and probability discounting of hypothetical monetary losses over a wide range of amounts (from $20 to $500,000) in order to determine how amount affects the parameters of the hyperboloid discounting function. In separate conditions, college students chose between immediate payments and larger, delayed payments and between certain payments and larger, probabilistic payments. The hyperboloid function accurately described both types of discounting, and amount of loss had little or no systematic effect on the degree of discounting. Importantly, the amount of loss also had little systematic effect on either the rate parameter or the exponent of the delay and probability discounting functions. The finding that the parameters of the hyperboloid function remain relatively constant across a wide range of amounts of delayed and probabilistic loss stands in contrast to the robust amount effects observed with delayed and probabilistic rewards. At the individual level, the degree to which delayed losses were discounted was uncorrelated with the degree to which probabilistic losses were discounted, and delay and probability loaded on two separate factors, similar to what is observed with delayed and probabilistic rewards. Taken together, these findings argue that although delay and probability discounting involve fundamentally different decision-making mechanisms, nevertheless the discounting of delayed and probabilistic losses share an insensitivity to amount that distinguishes it from the discounting of delayed and probabilistic gains. PMID:24745086

Methods of chemically converting first materials to second materials utilizing hybrid-plasma systems

DOEpatents

Kong, Peter C.; Grandy, Jon D.

2002-01-01

In one aspect, the invention encompasses a method of chemically converting a first material to a second material. A first plasma and a second plasma are formed, and the first plasma is in fluid communication with the second plasma. The second plasma comprises activated hydrogen and oxygen, and is formed from a water vapor. A first material is flowed into the first plasma to at least partially ionize at least a portion of the first material. The at least partially ionized first material is flowed into the second plasma to react at least some components of the first material with at least one of the activated hydrogen and activated oxygen. Such converts at least some of the first material to a second material. In another aspect, the invention encompasses a method of forming a synthetic gas by flowing a hydrocarbon-containing material into a hybrid-plasma system. In yet another aspect, the invention encompasses a method of degrading a hydrocarbon-containing material by flowing such material into a hybrid-plasma system. In yet another aspect, the invention encompasses a method of releasing an inorganic component of a complex comprising the inorganic component and an other component, wherein the complex is flowed through a hybrid-plasma system.

Impact of the 2008 Wenchuan earthquake in China on subsequent long-term debris flow activities in the epicentral area

NASA Astrophysics Data System (ADS)

Zhang, S.; Zhang, L. M.

2017-01-01

The 2008 Wenchuan earthquake triggered the largest number of landslides among the recent strong earthquake events around the world. The loose landslide materials were retained on steep terrains and deep gullies. In the period from 2008 to 2015, numerous debris flows occurred during rainstorms along the Provincial Road 303 (PR303) near the epicentre of the earthquake, causing serious damage to the reconstructed highway. Approximately 5.24 × 106 m3 of debris-flow sediment was deposited shortly after the earthquake. This paper evaluates the evolution of the debris flows that occurred after the Wenchuan earthquake, which helps understand long-term landscape evolution and cascading effects in regions impacted by mega earthquakes. With the aid of a GIS platform combined with field investigations, we continuously tracked movements of the loose deposit materials in all the debris flow gullies along an 18 km reach of PR303 and the characteristics of the regional debris flows during several storms in the past seven years. This paper presents five important aspects of the evolution of debris flows: (1) supply of debris flow materials; (2) triggering rainfall; (3) initiation mechanisms and types of debris flows; (4) runout characteristics; and (5) elevated riverbed due to the deposited materials from the debris flows. The hillslope soil deposits gradually evolved into channel deposits and the solid materials in the channels moved towards the ravine mouth. Accordingly, channelized debris flows became dominant gradually. Due to the decreasing source material volume and changes in debris flow characteristics, the triggering rainfall tends to increase from 30 mm h- 1 in 2008 to 64 mm h- 1 in 2013, and the runout distance tends to decrease over time. The runout materials blocked the river and elevated the riverbed by at least 30 m in parts of the study area. The changes in the post-seismic debris flow activity can be categorized into three stages, i.e., active, unstable, and recession.

Probabilistic flood inundation prediction within a coupled hydrodynamic, distributed hydrologic modeling framework

NASA Astrophysics Data System (ADS)

Adams, T. E.

2016-12-01

Accurate and timely predictions of the lateral exent of floodwaters and water level depth in floodplain areas are critical globally. This paper demonstrates the coupling of hydrologic ensembles, derived from the use of numerical weather prediction (NWP) model forcings as input to a fully distributed hydrologic model. Resulting ensemble output from the distributed hydrologic model are used as upstream flow boundaries and lateral inflows to a 1-D hydrodynamic model. An example is presented for the Potomac River in the vicinity of Washington, DC (USA). The approach taken falls within the broader goals of the Hydrologic Ensemble Prediction EXperiment (HEPEX).

Analysis of Streamline Separation at Infinity Using Time-Discrete Markov Chains.

PubMed

Reich, W; Scheuermann, G

2012-12-01

Existing methods for analyzing separation of streamlines are often restricted to a finite time or a local area. In our paper we introduce a new method that complements them by allowing an infinite-time-evaluation of steady planar vector fields. Our algorithm unifies combinatorial and probabilistic methods and introduces the concept of separation in time-discrete Markov-Chains. We compute particle distributions instead of the streamlines of single particles. We encode the flow into a map and then into a transition matrix for each time direction. Finally, we compare the results of our grid-independent algorithm to the popular Finite-Time-Lyapunov-Exponents and discuss the discrepancies.

Kuhn-Tucker optimization based reliability analysis for probabilistic finite elements

NASA Technical Reports Server (NTRS)

Liu, W. K.; Besterfield, G.; Lawrence, M.; Belytschko, T.

1988-01-01

The fusion of probability finite element method (PFEM) and reliability analysis for fracture mechanics is considered. Reliability analysis with specific application to fracture mechanics is presented, and computational procedures are discussed. Explicit expressions for the optimization procedure with regard to fracture mechanics are given. The results show the PFEM is a very powerful tool in determining the second-moment statistics. The method can determine the probability of failure or fracture subject to randomness in load, material properties and crack length, orientation, and location.

A workshop on developing risk assessment methods for medical use of radioactive material. Volume 1: Summary

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

Tortorelli, J.P.

1995-08-01

A workshop was held at the Idaho National Engineering Laboratory, August 16--18, 1994 on the topic of risk assessment on medical devices that use radioactive isotopes. Its purpose was to review past efforts to develop a risk assessment methodology to evaluate these devices, and to develop a program plan and a scoping document for future methodology development. This report contains a summary of that workshop. Participants included experts in the fields of radiation oncology, medical physics, risk assessment, human-error analysis, and human factors. Staff from the US Nuclear Regulatory Commission (NRC) associated with the regulation of medical uses of radioactivemore » materials and with research into risk-assessment methods participated in the workshop. The workshop participants concurred in NRC`s intended use of risk assessment as an important technology in the development of regulations for the medical use of radioactive material and encouraged the NRC to proceed rapidly with a pilot study. Specific recommendations are included in the executive summary and the body of this report. An appendix contains the 8 papers presented at the conference: NRC proposed policy statement on the use of probabilistic risk assessment methods in nuclear regulatory activities; NRC proposed agency-wide implementation plan for probabilistic risk assessment; Risk evaluation of high dose rate remote afterloading brachytherapy at a large research/teaching institution; The pros and cons of using human reliability analysis techniques to analyze misadministration events; Review of medical misadministration event summaries and comparison of human error modeling; Preliminary examples of the development of error influences and effects diagrams to analyze medical misadministration events; Brachytherapy risk assessment program plan; and Principles of brachytherapy quality assurance.« less

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

Disposable and removable nucleic acid extraction and purification cartridges for automated flow-through systems

DOEpatents

Regan, John Frederick

2014-09-09

Removable cartridges are used on automated flow-through systems for the purpose of extracting and purifying genetic material from complex matrices. Different types of cartridges are paired with specific automated protocols to concentrate, extract, and purifying pathogenic or human genetic material. Their flow-through nature allows large quantities sample to be processed. Matrices may be filtered using size exclusion and/or affinity filters to concentrate the pathogen of interest. Lysed material is ultimately passed through a filter to remove the insoluble material before the soluble genetic material is delivered past a silica-like membrane that binds the genetic material, where it is washed, dried, and eluted. Cartridges are inserted into the housing areas of flow-through automated instruments, which are equipped with sensors to ensure proper placement and usage of the cartridges. Properly inserted cartridges create fluid- and air-tight seals with the flow lines of an automated instrument.

Development of the technology for the fabrication of reliable laminar flow control panels

NASA Technical Reports Server (NTRS)

Weiss, D. D.; Lindh, D. V.

1977-01-01

Various configurations of porous, perforated and slotted materials were flow tested to determine if they would meet the LFC surface smoothness and flow requirements. The candidate materials were then tested for susceptibility to clogging and for resistance to corrosion. Of the materials tested, perforated titanium, porous polyimide, and slotted assemblies demonstrated a much greater resistance to clogging than other porous materials.

Fundamental Study of Material Flow in Friction Stir Welds

NASA Technical Reports Server (NTRS)

Reynolds, Anthony P.

1999-01-01

The presented research project consists of two major parts. First, the material flow in solid-state, friction stir, butt-welds as been investigated using a marker insert technique. Changes in material flow due to welding parameter as well as tool geometry variations have been examined for different materials. The method provides a semi-quantitative, three-dimensional view of the material transport in the welded zone. Second, a FSW process model has been developed. The fully coupled model is based on fluid mechanics; the solid-state material transport during welding is treated as a laminar, viscous flow of a non-Newtonian fluid past a rotating circular cylinder. The heat necessary for the material softening is generated by deformation of the material. As a first step, a two-dimensional model, which contains only the pin of the FSW tool, has been created to test the suitability of the modeling approach and to perform parametric studies of the boundary conditions. The material flow visualization experiments agree very well with the predicted flow field. Accordingly, material within the pin diameter is transported only in the rotation direction around the pin. Due to the simplifying assumptions inherent in the 2-D model, other experimental data such as forces on the pin, torque, and weld energy cannot be directly used for validation. However, the 2-D model predicts the same trends as shown in the experiments. The model also predicts a deviation from the "normal" material flow at certain combinations of welding parameters, suggesting a possible mechanism for the occurrence of some typical FSW defects. The next step has been the development of a three-dimensional process model. The simplified FSW tool has been designed as a flat shoulder rotating on the top of the workpiece and a rotating, cylindrical pin, which extends throughout the total height of the flow domain. The thermal boundary conditions at the tool and at the contact area to the backing plate have been varied to fit experimental data such as temperature profiles, torque and tool forces. General aspects of the experimentally visualized material flow pattern are confirmed by the 3-D model.

Flutter Phenomenon in Flow Driven Energy Harvester–A Unified Theoretical Model for “Stiff” and “Flexible” Materials

PubMed Central

Chen, Yu; Mu, Xiaojing; Wang, Tao; Ren, Weiwei; Yang, Ya; Wang, Zhong Lin; Sun, Chengliang; Gu, Alex Yuandong

2016-01-01

Here, we report a stable and predictable aero-elastic motion in the flow-driven energy harvester, which is different from flapping and vortex-induced-vibration (VIV). A unified theoretical frame work that describes the flutter phenomenon observed in both “stiff” and “flexible” materials for flow driven energy harvester was presented in this work. We prove flutter in both types of materials is the results of the coupled effects of torsional and bending modes. Compared to “stiff” materials, which has a flow velocity-independent flutter frequency, flexible material presents a flutter frequency that almost linearly scales with the flow velocity. Specific to “flexible” materials, pre-stress modulates the frequency range in which flutter occurs. It is experimentally observed that a double-clamped “flexible” piezoelectric P(VDF-TrFE) thin belt, when driven into the flutter state, yields a 1,000 times increase in the output voltage compared to that of the non-fluttered state. At a fixed flow velocity, increase in pre-stress level of the P(VDF-TrFE) thin belt up-shifts the flutter frequency. In addition, this work allows the rational design of flexible piezoelectric devices, including flow-driven energy harvester, triboelectric energy harvester, and self-powered wireless flow speed sensor. PMID:27739484

A high-resolution Godunov method for compressible multi-material flow on overlapping grids

NASA Astrophysics Data System (ADS)

Banks, J. W.; Schwendeman, D. W.; Kapila, A. K.; Henshaw, W. D.

2007-04-01

A numerical method is described for inviscid, compressible, multi-material flow in two space dimensions. The flow is governed by the multi-material Euler equations with a general mixture equation of state. Composite overlapping grids are used to handle complex flow geometry and block-structured adaptive mesh refinement (AMR) is used to locally increase grid resolution near shocks and material interfaces. The discretization of the governing equations is based on a high-resolution Godunov method, but includes an energy correction designed to suppress numerical errors that develop near a material interface for standard, conservative shock-capturing schemes. The energy correction is constructed based on a uniform-pressure-velocity flow and is significant only near the captured interface. A variety of two-material flows are presented to verify the accuracy of the numerical approach and to illustrate its use. These flows assume an equation of state for the mixture based on the Jones-Wilkins-Lee (JWL) forms for the components. This equation of state includes a mixture of ideal gases as a special case. Flow problems considered include unsteady one-dimensional shock-interface collision, steady interaction of a planar interface and an oblique shock, planar shock interaction with a collection of gas-filled cylindrical inhomogeneities, and the impulsive motion of the two-component mixture in a rigid cylindrical vessel.

Flutter Phenomenon in Flow Driven Energy Harvester-A Unified Theoretical Model for "Stiff" and "Flexible" Materials.

PubMed

Chen, Yu; Mu, Xiaojing; Wang, Tao; Ren, Weiwei; Yang, Ya; Wang, Zhong Lin; Sun, Chengliang; Gu, Alex Yuandong

2016-10-14

Here, we report a stable and predictable aero-elastic motion in the flow-driven energy harvester, which is different from flapping and vortex-induced-vibration (VIV). A unified theoretical frame work that describes the flutter phenomenon observed in both "stiff" and "flexible" materials for flow driven energy harvester was presented in this work. We prove flutter in both types of materials is the results of the coupled effects of torsional and bending modes. Compared to "stiff" materials, which has a flow velocity-independent flutter frequency, flexible material presents a flutter frequency that almost linearly scales with the flow velocity. Specific to "flexible" materials, pre-stress modulates the frequency range in which flutter occurs. It is experimentally observed that a double-clamped "flexible" piezoelectric P(VDF-TrFE) thin belt, when driven into the flutter state, yields a 1,000 times increase in the output voltage compared to that of the non-fluttered state. At a fixed flow velocity, increase in pre-stress level of the P(VDF-TrFE) thin belt up-shifts the flutter frequency. In addition, this work allows the rational design of flexible piezoelectric devices, including flow-driven energy harvester, triboelectric energy harvester, and self-powered wireless flow speed sensor.

Relative Gains, Losses, and Reference Points in Probabilistic Choice in Rats

PubMed Central

Marshall, Andrew T.; Kirkpatrick, Kimberly

2015-01-01

Theoretical reference points have been proposed to differentiate probabilistic gains from probabilistic losses in humans, but such a phenomenon in non-human animals has yet to be thoroughly elucidated. Three experiments evaluated the effect of reward magnitude on probabilistic choice in rats, seeking to determine reference point use by examining the effect of previous outcome magnitude(s) on subsequent choice behavior. Rats were trained to choose between an outcome that always delivered reward (low-uncertainty choice) and one that probabilistically delivered reward (high-uncertainty). The probability of high-uncertainty outcome receipt and the magnitudes of low-uncertainty and high-uncertainty outcomes were manipulated within and between experiments. Both the low- and high-uncertainty outcomes involved variable reward magnitudes, so that either a smaller or larger magnitude was probabilistically delivered, as well as reward omission following high-uncertainty choices. In Experiments 1 and 2, the between groups factor was the magnitude of the high-uncertainty-smaller (H-S) and high-uncertainty-larger (H-L) outcome, respectively. The H-S magnitude manipulation differentiated the groups, while the H-L magnitude manipulation did not. Experiment 3 showed that manipulating the probability of differential losses as well as the expected value of the low-uncertainty choice produced systematic effects on choice behavior. The results suggest that the reference point for probabilistic gains and losses was the expected value of the low-uncertainty choice. Current theories of probabilistic choice behavior have difficulty accounting for the present results, so an integrated theoretical framework is proposed. Overall, the present results have implications for understanding individual differences and corresponding underlying mechanisms of probabilistic choice behavior. PMID:25658448

Evaluation of anionic surfactant concentrations in US effluents and probabilistic determination of their combined ecological risk in mixing zones.

PubMed

McDonough, Kathleen; Casteel, Kenneth; Itrich, Nina; Menzies, Jennifer; Belanger, Scott; Wehmeyer, Kenneth; Federle, Thomas

2016-12-01

Alcohol sulfates (AS), alcohol ethoxysulfates (AES), linear alkyl benzenesulfonates (LAS) and methyl ester sulfonates (MES) are anionic surfactants that are widely used in household detergents and consumer products resulting in over 1 million tons being disposed of down the drain annually in the US. A monitoring campaign was conducted which collected grab effluent samples from 44 wastewater treatment plants (WWTPs) across the US to generate statistical distributions of effluent concentrations for anionic surfactants. The mean concentrations for AS, AES, LAS and MES were 5.03±4.5, 1.95±0.7, 15.3±19, and 0.35±0.13μg/L respectively. Since each of these surfactants consist of multiple homologues that differ in their toxicity, the concentration of each homologue measured in an effluent sample was converted into a toxic unit (TU) by normalizing to the predicted no effect concentration (PNEC) derived from high tier effects data (mesocosm studies). The statistical distributions of the combined TUs in the effluents were used in combination with distributions of dilution factors for WWTP mixing zones to conduct a US-wide probabilistic risk assessment for the aquatic environment for each of the surfactants. The 90th percentile level of TUs for AS, AES, LAS and MES in mixing zones were 1.89×10 -2 , 2.73×10 -3 , 2.72×10 -2 , and 3.65×10 -5 under 7Q10 (lowest river flow occurring over a 7day period every 10years) low flow conditions. Because these surfactants have the same toxicological mode of action, the TUs were summed and the aquatic safety for anionic surfactants as a whole was assessed. At the 90th percentile level under the conservative 7Q10 low flow conditions the forecasted TUs were 4.21×10 -2 which indicates that there is a significant margin of safety for the class of anionic surfactants in US aquatic environments. Copyright © 2016 Elsevier B.V. All rights reserved.

An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing

USGS Publications Warehouse

Pelletier, J.D.; Mayer, L.; Pearthree, P.A.; House, P.K.; Demsey, K.A.; Klawon, J.K.; Vincent, K.R.

2005-01-01

Millions of people in the western United States live near the dynamic, distributary channel networks of alluvial fans where flood behavior is complex and poorly constrained. Here we test a new comprehensive approach to alluvial-fan flood hazard assessment that uses four complementary methods: two-dimensional raster-based hydraulic modeling, satellite-image change detection, fieldbased mapping of recent flood inundation, and surficial geologic mapping. Each of these methods provides spatial detail lacking in the standard method and each provides critical information for a comprehensive assessment. Our numerical model simultaneously solves the continuity equation and Manning's equation (Chow, 1959) using an implicit numerical method. It provides a robust numerical tool for predicting flood flows using the large, high-resolution Digital Elevation Models (DEMs) necessary to resolve the numerous small channels on the typical alluvial fan. Inundation extents and flow depths of historic floods can be reconstructed with the numerical model and validated against field- and satellite-based flood maps. A probabilistic flood hazard map can also be constructed by modeling multiple flood events with a range of specified discharges. This map can be used in conjunction with a surficial geologic map to further refine floodplain delineation on fans. To test the accuracy of the numerical model, we compared model predictions of flood inundation and flow depths against field- and satellite-based flood maps for two recent extreme events on the southern Tortolita and Harquahala piedmonts in Arizona. Model predictions match the field- and satellite-based maps closely. Probabilistic flood hazard maps based on the 10 yr, 100 yr, and maximum floods were also constructed for the study areas using stream gage records and paleoflood deposits. The resulting maps predict spatially complex flood hazards that strongly reflect small-scale topography and are consistent with surficial geology. In contrast, FEMA Flood Insurance Rate Maps (FIRMs) based on the FAN model predict uniformly high flood risk across the study areas without regard for small-scale topography and surficial geology. ?? 2005 Geological Society of America.

What Do They Have in Common? Physical Drivers of Streamflow Spatial Correlation and Prediction of Flow Regimes at Ungauged Locations in the Contiguous United States

NASA Astrophysics Data System (ADS)

Betterle, A.; Schirmer, M.; Botter, G.

2017-12-01

Streamflow dynamics strongly influence anthropogenic activities and the ecological functions of riverine and riparian habitats. However, the widespread lack of direct discharge measurements often challenges the set-up of conscious and effective decision-making processes, including droughts and floods protection, water resources management and river restoration practices. By characterizing the spatial correlation of daily streamflow timeseries at two arbitrary locations, this study provides a method to evaluate how spatially variable catchment-scale hydrological process affects the resulting streamflow dynamics along and across river systems. In particular, streamflow spatial correlation is described analytically as a function of morphological, climatic and vegetation properties in the contributing catchments, building on a joint probabilistic description of flow dynamics at pairs of outlets. The approach enables an explicit linkage between similarities of flow dynamics and spatial patterns of hydrologically relevant features of climate and landscape. Therefore, the method is suited to explore spatial patterns of streamflow dynamics across geomorphoclimatic gradients. In particular, we show how the streamflow correlation can be used at the continental scale to individuate catchment pairs with similar hydrological dynamics, thereby providing a useful tool for the estimate of flow duration curves in poorly gauged areas.

A variational approach to probing extreme events in turbulent dynamical systems

PubMed Central

Farazmand, Mohammad; Sapsis, Themistoklis P.

2017-01-01

Extreme events are ubiquitous in a wide range of dynamical systems, including turbulent fluid flows, nonlinear waves, large-scale networks, and biological systems. We propose a variational framework for probing conditions that trigger intermittent extreme events in high-dimensional nonlinear dynamical systems. We seek the triggers as the probabilistically feasible solutions of an appropriately constrained optimization problem, where the function to be maximized is a system observable exhibiting intermittent extreme bursts. The constraints are imposed to ensure the physical admissibility of the optimal solutions, that is, significant probability for their occurrence under the natural flow of the dynamical system. We apply the method to a body-forced incompressible Navier-Stokes equation, known as the Kolmogorov flow. We find that the intermittent bursts of the energy dissipation are independent of the external forcing and are instead caused by the spontaneous transfer of energy from large scales to the mean flow via nonlinear triad interactions. The global maximizer of the corresponding variational problem identifies the responsible triad, hence providing a precursor for the occurrence of extreme dissipation events. Specifically, monitoring the energy transfers within this triad allows us to develop a data-driven short-term predictor for the intermittent bursts of energy dissipation. We assess the performance of this predictor through direct numerical simulations. PMID:28948226

Reliability-Based Design Optimization of a Composite Airframe Component

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.

2009-01-01

A stochastic design optimization methodology (SDO) has been developed to design components of an airframe structure that can be made of metallic and composite materials. The design is obtained as a function of the risk level, or reliability, p. The design method treats uncertainties in load, strength, and material properties as distribution functions, which are defined with mean values and standard deviations. A design constraint or a failure mode is specified as a function of reliability p. Solution to stochastic optimization yields the weight of a structure as a function of reliability p. Optimum weight versus reliability p traced out an inverted-S-shaped graph. The center of the inverted-S graph corresponded to 50 percent (p = 0.5) probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponds to unity for reliability p (or p = 1). Weight can be reduced to a small value for the most failure-prone design with a reliability that approaches zero (p = 0). Reliability can be changed for different components of an airframe structure. For example, the landing gear can be designed for a very high reliability, whereas it can be reduced to a small extent for a raked wingtip. The SDO capability is obtained by combining three codes: (1) The MSC/Nastran code was the deterministic analysis tool, (2) The fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and (3) NASA Glenn Research Center s optimization testbed CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.

Identification of approximately duplicate material records in ERP systems

NASA Astrophysics Data System (ADS)

Zong, Wei; Wu, Feng; Chu, Lap-Keung; Sculli, Domenic

2017-03-01

The quality of master data is crucial for the accurate functioning of the various modules of an enterprise resource planning (ERP) system. This study addresses specific data problems arising from the generation of approximately duplicate material records in ERP databases. Such problems are mainly due to the firm's lack of unique and global identifiers for the material records, and to the arbitrary assignment of alternative names for the same material by various users. Traditional duplicate detection methods are ineffective in identifying such approximately duplicate material records because these methods typically rely on string comparisons of each field. To address this problem, a machine learning-based framework is developed to recognise semantic similarity between strings and to further identify and reunify approximately duplicate material records - a process referred to as de-duplication in this article. First, the keywords of the material records are extracted to form vectors of discriminating words. Second, a machine learning method using a probabilistic neural network is applied to determine the semantic similarity between these material records. The approach was evaluated using data from a real case study. The test results indicate that the proposed method outperforms traditional algorithms in identifying approximately duplicate material records.

Fatigue of restorative materials.

PubMed

Baran, G; Boberick, K; McCool, J

2001-01-01

Failure due to fatigue manifests itself in dental prostheses and restorations as wear, fractured margins, delaminated coatings, and bulk fracture. Mechanisms responsible for fatigue-induced failure depend on material ductility: Brittle materials are susceptible to catastrophic failure, while ductile materials utilize their plasticity to reduce stress concentrations at the crack tip. Because of the expense associated with the replacement of failed restorations, there is a strong desire on the part of basic scientists and clinicians to evaluate the resistance of materials to fatigue in laboratory tests. Test variables include fatigue-loading mode and test environment, such as soaking in water. The outcome variable is typically fracture strength, and these data typically fit the Weibull distribution. Analysis of fatigue data permits predictive inferences to be made concerning the survival of structures fabricated from restorative materials under specified loading conditions. Although many dental-restorative materials are routinely evaluated, only limited use has been made of fatigue data collected in vitro: Wear of materials and the survival of porcelain restorations has been modeled by both fracture mechanics and probabilistic approaches. A need still exists for a clinical failure database and for the development of valid test methods for the evaluation of composite materials.

Probabilistic structural analysis methods of hot engine structures

NASA Technical Reports Server (NTRS)

Chamis, C. C.; Hopkins, D. A.

1989-01-01

Development of probabilistic structural analysis methods for hot engine structures at Lewis Research Center is presented. Three elements of the research program are: (1) composite load spectra methodology; (2) probabilistic structural analysis methodology; and (3) probabilistic structural analysis application. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) turbine blade temperature, pressure, and torque of the space shuttle main engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; and (3) evaluation of the failure probability. Collectively, the results demonstrate that the structural durability of hot engine structural components can be effectively evaluated in a formal probabilistic/reliability framework.

Overview of Probabilistic Methods for SAE G-11 Meeting for Reliability and Uncertainty Quantification for DoD TACOM Initiative with SAE G-11 Division

NASA Technical Reports Server (NTRS)

Singhal, Surendra N.

2003-01-01

The SAE G-11 RMSL Division and Probabilistic Methods Committee meeting during October 6-8 at the Best Western Sterling Inn, Sterling Heights (Detroit), Michigan is co-sponsored by US Army Tank-automotive & Armaments Command (TACOM). The meeting will provide an industry/government/academia forum to review RMSL technology; reliability and probabilistic technology; reliability-based design methods; software reliability; and maintainability standards. With over 100 members including members with national/international standing, the mission of the G-11's Probabilistic Methods Committee is to "enable/facilitate rapid deployment of probabilistic technology to enhance the competitiveness of our industries by better, faster, greener, smarter, affordable and reliable product development."

A Markov Chain Approach to Probabilistic Swarm Guidance

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Bayard, David S.

2012-01-01

This paper introduces a probabilistic guidance approach for the coordination of swarms of autonomous agents. The main idea is to drive the swarm to a prescribed density distribution in a prescribed region of the configuration space. In its simplest form, the probabilistic approach is completely decentralized and does not require communication or collabo- ration between agents. Agents make statistically independent probabilistic decisions based solely on their own state, that ultimately guides the swarm to the desired density distribution in the configuration space. In addition to being completely decentralized, the probabilistic guidance approach has a novel autonomous self-repair property: Once the desired swarm density distribution is attained, the agents automatically repair any damage to the distribution without collaborating and without any knowledge about the damage.

Method and apparatus for casting conductive and semi-conductive materials

DOEpatents

Ciszek, T.F.

1984-08-13

A method and apparatus is disclosed for casting conductive and semi-conductive materials. The apparatus includes a plurality of conductive members arranged to define a container-like area having a desired cross-sectional shape. A portion or all of the conductive or semi-conductive material which is to be cast is introduced into the container-like area. A means is provided for inducing the flow of an electrical current in each of the conductive members, which currents act collectively to induce a current flow in the material. The induced current flow through the conductive members is in a direction substantially opposite to the induced current flow in the material so that the material is repelled from the conductive members during the casting process.

Method and apparatus for casting conductive and semiconductive materials

DOEpatents

Ciszek, Theodore F.

1986-01-01

A method and apparatus is disclosed for casting conductive and semiconduce materials. The apparatus includes a plurality of conductive members arranged to define a container-like area having a desired cross-sectional shape. A portion or all of the conductive or semiconductive material which is to be cast is introduced into the container-like area. A means is provided for inducing the flow of an electrical current in each of the conductive members, which currents act collectively to induce a current flow in the material. The induced current flow through the conductive members is in a direction substantially opposite to the induced current flow in the material so that the material is repelled from the conductive members during the casting process.

A look-ahead probabilistic contingency analysis framework incorporating smart sampling techniques

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

Chen, Yousu; Etingov, Pavel V.; Ren, Huiying

2016-07-18

This paper describes a framework of incorporating smart sampling techniques in a probabilistic look-ahead contingency analysis application. The predictive probabilistic contingency analysis helps to reflect the impact of uncertainties caused by variable generation and load on potential violations of transmission limits.

Error Discounting in Probabilistic Category Learning

ERIC Educational Resources Information Center

Craig, Stewart; Lewandowsky, Stephan; Little, Daniel R.

2011-01-01

The assumption in some current theories of probabilistic categorization is that people gradually attenuate their learning in response to unavoidable error. However, existing evidence for this error discounting is sparse and open to alternative interpretations. We report 2 probabilistic-categorization experiments in which we investigated error…

Wind effects on long-span bridges: Probabilistic wind data format for buffeting and VIV load assessments

NASA Astrophysics Data System (ADS)

Hoffmann, K.; Srouji, R. G.; Hansen, S. O.

2017-12-01

The technology development within the structural design of long-span bridges in Norwegian fjords has created a need for reformulating the calculation format and the physical quantities used to describe the properties of wind and the associated wind-induced effects on bridge decks. Parts of a new probabilistic format describing the incoming, undisturbed wind is presented. It is expected that a fixed probabilistic format will facilitate a more physically consistent and precise description of the wind conditions, which in turn increase the accuracy and considerably reduce uncertainties in wind load assessments. Because the format is probabilistic, a quantification of the level of safety and uncertainty in predicted wind loads is readily accessible. A simple buffeting response calculation demonstrates the use of probabilistic wind data in the assessment of wind loads and responses. Furthermore, vortex-induced fatigue damage is discussed in relation to probabilistic wind turbulence data and response measurements from wind tunnel tests.

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

Superposition-Based Analysis of First-Order Probabilistic Timed Automata

NASA Astrophysics Data System (ADS)

Fietzke, Arnaud; Hermanns, Holger; Weidenbach, Christoph

This paper discusses the analysis of first-order probabilistic timed automata (FPTA) by a combination of hierarchic first-order superposition-based theorem proving and probabilistic model checking. We develop the overall semantics of FPTAs and prove soundness and completeness of our method for reachability properties. Basically, we decompose FPTAs into their time plus first-order logic aspects on the one hand, and their probabilistic aspects on the other hand. Then we exploit the time plus first-order behavior by hierarchic superposition over linear arithmetic. The result of this analysis is the basis for the construction of a reachability equivalent (to the original FPTA) probabilistic timed automaton to which probabilistic model checking is finally applied. The hierarchic superposition calculus required for the analysis is sound and complete on the first-order formulas generated from FPTAs. It even works well in practice. We illustrate the potential behind it with a real-life DHCP protocol example, which we analyze by means of tool chain support.

Effects of uncertain topographic input data on two-dimensional flow modeling in a gravel-bed river

USGS Publications Warehouse

Legleiter, C.J.; Kyriakidis, P.C.; McDonald, R.R.; Nelson, J.M.

2011-01-01

Many applications in river research and management rely upon two-dimensional (2D) numerical models to characterize flow fields, assess habitat conditions, and evaluate channel stability. Predictions from such models are potentially highly uncertain due to the uncertainty associated with the topographic data provided as input. This study used a spatial stochastic simulation strategy to examine the effects of topographic uncertainty on flow modeling. Many, equally likely bed elevation realizations for a simple meander bend were generated and propagated through a typical 2D model to produce distributions of water-surface elevation, depth, velocity, and boundary shear stress at each node of the model's computational grid. Ensemble summary statistics were used to characterize the uncertainty associated with these predictions and to examine the spatial structure of this uncertainty in relation to channel morphology. Simulations conditioned to different data configurations indicated that model predictions became increasingly uncertain as the spacing between surveyed cross sections increased. Model sensitivity to topographic uncertainty was greater for base flow conditions than for a higher, subbankfull flow (75% of bankfull discharge). The degree of sensitivity also varied spatially throughout the bend, with the greatest uncertainty occurring over the point bar where the flow field was influenced by topographic steering effects. Uncertain topography can therefore introduce significant uncertainty to analyses of habitat suitability and bed mobility based on flow model output. In the presence of such uncertainty, the results of these studies are most appropriately represented in probabilistic terms using distributions of model predictions derived from a series of topographic realizations. Copyright 2011 by the American Geophysical Union.

In Depth Analysis of AVCOAT TPS Response to a Reentry Flow

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

Titov, E. V.; Kumar, Rakesh; Levin, D. A.

2011-05-20

Modeling of the high altitude portion of reentry vehicle trajectories with DSMC or statistical BGK solvers requires accurate evaluation of the boundary conditions at the ablating TPS surface. Presented in this article is a model which takes into account the complex ablation physics including the production of pyrolysis gases, and chemistry at the TPS surface. Since the ablation process is time dependent the modeling of the material response to the high energy reentry flow starts with the solution of the rarefied flow over the vehicle and then loosely couples with the material response. The objective of the present work ismore » to carry out conjugate thermal analysis by weakly coupling a flow solver to a material thermal response model. The latter model solves the one dimensional heat conduction equation accounting for the pyrolysis process that takes place in the reaction zone of an ablative thermal protection system (TPS) material. An estimate of the temperature range within which the pyrolysis reaction (decomposition and volatilization) takes place is obtained from Ref. [1]. The pyrolysis reaction results in the formation of char and the release of gases through the porous charred material. These gases remove additional amount of heat as they pass through the material, thus cooling the material (the process known as transpiration cooling). In the present work, we incorporate the transpiration cooling model in the material thermal response code in addition to the pyrolysis model. The flow in the boundary layer and in the vicinity of the TPS material is in the transitional flow regime. Therefore, we use a previously validated statistical BGK method to model the flow physics in the vicinity of the micro-cracks, since the BGK method allows simulations of flow at pressures higher than can be computed using DSMC.« less

A mixed-unit input-output model for environmental life-cycle assessment and material flow analysis.

PubMed

Hawkins, Troy; Hendrickson, Chris; Higgins, Cortney; Matthews, H Scott; Suh, Sangwon

2007-02-01

Materials flow analysis models have traditionally been used to track the production, use, and consumption of materials. Economic input-output modeling has been used for environmental systems analysis, with a primary benefit being the capability to estimate direct and indirect economic and environmental impacts across the entire supply chain of production in an economy. We combine these two types of models to create a mixed-unit input-output model that is able to bettertrack economic transactions and material flows throughout the economy associated with changes in production. A 13 by 13 economic input-output direct requirements matrix developed by the U.S. Bureau of Economic Analysis is augmented with material flow data derived from those published by the U.S. Geological Survey in the formulation of illustrative mixed-unit input-output models for lead and cadmium. The resulting model provides the capabilities of both material flow and input-output models, with detailed material tracking through entire supply chains in response to any monetary or material demand. Examples of these models are provided along with a discussion of uncertainty and extensions to these models.

Systems for column-based separations, methods of forming packed columns, and methods of purifying sample components

DOEpatents

Egorov, Oleg B.; O'Hara, Matthew J.; Grate, Jay W.; Chandler, Darrell P.; Brockman, Fred J.; Bruckner-Lea, Cynthia J.

2000-01-01

The invention encompasses systems for column-based separations, methods of packing and unpacking columns and methods of separating components of samples. In one aspect, the invention includes a method of packing and unpacking a column chamber, comprising: a) packing a matrix material within a column chamber to form a packed column; and b) after the packing, unpacking the matrix material from the column chamber without moving the column chamber. In another aspect, the invention includes a system for column-based separations, comprising: a) a fluid passageway, the fluid passageway comprising a column chamber and a flow path in fluid communication with the column chamber, the flow path being obstructed by a retaining material permeable to a carrier fluid and impermeable to a column matrix material suspended in the carrier fluid, the flow path extending through the column chamber and through the retaining material, the flow path being configured to form a packed column within the column chamber when a suspension of the fluid and the column matrix material is flowed along the flow path; and b) the fluid passageway extending through a valve intermediate the column chamber and the retaining material.

Systems For Column-Based Separations, Methods Of Forming Packed Columns, And Methods Of Purifying Sample Components

DOEpatents

Egorov, Oleg B.; O'Hara, Matthew J.; Grate, Jay W.; Chandler, Darrell P.; Brockman, Fred J.; Bruckner-Lea, Cynthia J.

2006-02-21

The invention encompasses systems for column-based separations, methods of packing and unpacking columns and methods of separating components of samples. In one aspect, the invention includes a method of packing and unpacking a column chamber, comprising: a) packing a matrix material within a column chamber to form a packed column; and b) after the packing, unpacking the matrix material from the column chamber without moving the column chamber. In another aspect, the invention includes a system for column-based separations, comprising: a) a fluid passageway, the fluid passageway comprising a column chamber and a flow path in fluid communication with the column chamber, the flow path being obstructed by a retaining material permeable to a carrier fluid and impermeable to a column matrix material suspended in the carrier fluid, the flow path extending through the column chamber and through the retaining material, the flow path being configured to form a packed column within the column chamber when a suspension of the fluid and the column matrix material is flowed along the flow path; and b) the fluid passageway extending through a valve intermediate the column chamber and the retaining material.

Systems For Column-Based Separations, Methods Of Forming Packed Columns, And Methods Of Purifying Sample Components.

DOEpatents

Egorov, Oleg B.; O'Hara, Matthew J.; Grate, Jay W.; Chandler, Darrell P.; Brockman, Fred J.; Bruckner-Lea, Cynthia J.

2004-08-24

The invention encompasses systems for column-based separations, methods of packing and unpacking columns and methods of separating components of samples. In one aspect, the invention includes a method of packing and unpacking a column chamber, comprising: a) packing a matrix material within a column chamber to form a packed column; and b) after the packing, unpacking the matrix material from the column chamber without moving the column chamber. In another aspect, the invention includes a system for column-based separations, comprising: a) a fluid passageway, the fluid passageway comprising a column chamber and a flow path in fluid communication with the column chamber, the flow path being obstructed by a retaining material permeable to a carrier fluid and impermeable to a column matrix material suspended in the carrier fluid, the flow path extending through the column chamber and through the retaining material, the flow path being configured to form a packed column within the column chamber when a suspension of the fluid and the column matrix material is flowed along the flow path; and b) the fluid passageway extending through a valve intermediate the column chamber and the retaining material.

Identification of the full anisotropic flow resistivity tensor for multiple glass wool and melamine foam samples.

PubMed

Van der Kelen, Christophe; Göransson, Peter

2013-12-01

The flow resistivity tensor, which is the inverse of the viscous permeability tensor, is one of the most important material properties for the acoustic performance of porous materials used in acoustic treatments. Due to the manufacturing processes involved, these porous materials are most often geometrically anisotropic on a microscopic scale, and for demanding applications, there is a need for improved characterization methods. This paper discusses recent refinements of a method for the identification of the anisotropic flow resistivity tensor. The inverse estimation is verified for three fictitious materials with different degrees of anisotropy. Measurements are performed on nine glass wool samples and seven melamine foam samples, and the anisotropic flow resistivity tensors obtained are validated by comparison to measurements performed on uni-directional cylindrical samples, extracted from the same, previously measured cubic samples. The variability of flow resistivity in the batch of material from which the glass wool is extracted is discussed. The results for the melamine foam suggest that there is a relation between the direction of highest flow resistivity, and the rise direction of the material.

Damage assessment of composite plate structures with material and measurement uncertainty

NASA Astrophysics Data System (ADS)

Chandrashekhar, M.; Ganguli, Ranjan

2016-06-01

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problem in damage assessment. A recently developed C0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data.

Development of a Probabilistic Dynamic Synthesis Method for the Analysis of Nondeterministic Structures

NASA Technical Reports Server (NTRS)

Brown, A. M.

1998-01-01

Accounting for the statistical geometric and material variability of structures in analysis has been a topic of considerable research for the last 30 years. The determination of quantifiable measures of statistical probability of a desired response variable, such as natural frequency, maximum displacement, or stress, to replace experience-based "safety factors" has been a primary goal of these studies. There are, however, several problems associated with their satisfactory application to realistic structures, such as bladed disks in turbomachinery. These include the accurate definition of the input random variables (rv's), the large size of the finite element models frequently used to simulate these structures, which makes even a single deterministic analysis expensive, and accurate generation of the cumulative distribution function (CDF) necessary to obtain the probability of the desired response variables. The research presented here applies a methodology called probabilistic dynamic synthesis (PDS) to solve these problems. The PDS method uses dynamic characteristics of substructures measured from modal test as the input rv's, rather than "primitive" rv's such as material or geometric uncertainties. These dynamic characteristics, which are the free-free eigenvalues, eigenvectors, and residual flexibility (RF), are readily measured and for many substructures, a reasonable sample set of these measurements can be obtained. The statistics for these rv's accurately account for the entire random character of the substructure. Using the RF method of component mode synthesis, these dynamic characteristics are used to generate reduced-size sample models of the substructures, which are then coupled to form system models. These sample models are used to obtain the CDF of the response variable by either applying Monte Carlo simulation or by generating data points for use in the response surface reliability method, which can perform the probabilistic analysis with an order of magnitude less computational effort. Both free- and forced-response analyses have been performed, and the results indicate that, while there is considerable room for improvement, the method produces usable and more representative solutions for the design of realistic structures with a substantial savings in computer time.

Drying of pulverized material with heated condensible vapor

DOEpatents

Carlson, Larry W.

1986-01-01

Apparatus for drying pulverized material utilizes a high enthalpy condensable vapor such as steam for removing moisture from the individual particles of the pulverized material. The initially wet particulate material is tangentially delivered by a carrier vapor flow to an upper portion of a generally vertical cylindrical separation drum. The lateral wall of the separation drum is provided with a plurality of flow guides for directing the vapor tangentially therein in the direction of particulate material flow. Positioned concentrically within the separation drum and along the longitudinal axis thereof is a water-cooled condensation cylinder which is provided with a plurality of collection plates, or fins, on the outer lateral surface thereof. The cooled collection fins are aligned counter to the flow of the pulverized material and high enthalpy vapor mixture to maximize water vapor condensation thereon. The condensed liquid which includes moisture removed from the pulverized material then flows downward along the outer surface of the coolant cylinder and is collected and removed. The particles travel in a shallow helix due to respective centrifugal and vertical acceleration forces applied thereto. The individual particles of the pulverized material are directed outwardly by the vortex flow where they contact the inner cylindrical surface of the separation drum and are then deposited at the bottom thereof for easy collection and removal. The pulverized material drying apparatus is particularly adapted for drying coal fines and facilitates the recovery of the pulverized coal.

Novel composites for wing and fuselage applications

NASA Technical Reports Server (NTRS)

Sobel, L. H.; Buttitta, C.; Suarez, J. A.

1995-01-01

Probabilistic predictions based on the IPACS code are presented for the material and structural response of unnotched and notched, IM6/3501-6 Gr/Ep laminates. Comparisons of predicted and measured modulus and strength distributions are given for unnotched unidirectional, cross-ply and quasi-isotropic laminates. The predicted modulus distributions were found to correlate well with the test results for all three unnotched laminates. Correlations of strength distributions for the unnotched laminates are judged good for the unidirectional laminate and fair for the cross-ply laminate, whereas the strength correlation for the quasi-isotropic laminate is judged poor because IPACS did not have a progressive failure capability at the time this work was performed. The report also presents probabilistic and structural reliability analysis predictions for the strain concentration factor (SCF) for an open-hole, quasi-isotropic laminate subjected to longitudinal tension. A special procedure was developed to adapt IPACS for the structural reliability analysis. The reliability results show the importance of identifying the most significant random variables upon which the SCF depends, and of having accurate scatter values for these variables.

McGurk stimuli for the investigation of multisensory integration in cochlear implant users: The Oldenburg Audio Visual Speech Stimuli (OLAVS).

PubMed

Stropahl, Maren; Schellhardt, Sebastian; Debener, Stefan

2017-06-01

The concurrent presentation of different auditory and visual syllables may result in the perception of a third syllable, reflecting an illusory fusion of visual and auditory information. This well-known McGurk effect is frequently used for the study of audio-visual integration. Recently, it was shown that the McGurk effect is strongly stimulus-dependent, which complicates comparisons across perceivers and inferences across studies. To overcome this limitation, we developed the freely available Oldenburg audio-visual speech stimuli (OLAVS), consisting of 8 different talkers and 12 different syllable combinations. The quality of the OLAVS set was evaluated with 24 normal-hearing subjects. All 96 stimuli were characterized based on their stimulus disparity, which was obtained from a probabilistic model (cf. Magnotti & Beauchamp, 2015). Moreover, the McGurk effect was studied in eight adult cochlear implant (CI) users. By applying the individual, stimulus-independent parameters of the probabilistic model, the predicted effect of stronger audio-visual integration in CI users could be confirmed, demonstrating the validity of the new stimulus material.

Probabilistic accident consequence uncertainty analysis -- Late health effects uncertain assessment. Volume 2: Appendices

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

Little, M.P.; Muirhead, C.R.; Goossens, L.H.J.

1997-12-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library ofmore » uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA late health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the expert panel on late health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.« less

Probabilistic Analysis of Aircraft Gas Turbine Disk Life and Reliability

NASA Technical Reports Server (NTRS)

Melis, Matthew E.; Zaretsky, Erwin V.; August, Richard

1999-01-01

Two series of low cycle fatigue (LCF) test data for two groups of different aircraft gas turbine engine compressor disk geometries were reanalyzed and compared using Weibull statistics. Both groups of disks were manufactured from titanium (Ti-6Al-4V) alloy. A NASA Glenn Research Center developed probabilistic computer code Probable Cause was used to predict disk life and reliability. A material-life factor A was determined for titanium (Ti-6Al-4V) alloy based upon fatigue disk data and successfully applied to predict the life of the disks as a function of speed. A comparison was made with the currently used life prediction method based upon crack growth rate. Applying an endurance limit to the computer code did not significantly affect the predicted lives under engine operating conditions. Failure location prediction correlates with those experimentally observed in the LCF tests. A reasonable correlation was obtained between the predicted disk lives using the Probable Cause code and a modified crack growth method for life prediction. Both methods slightly overpredict life for one disk group and significantly under predict it for the other.

Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices

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

Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M.

1998-04-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library ofmore » uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA internal dosimetry models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on internal dosimetry, (4) short biographies of the experts, and (5) the aggregated results of their responses.« less

A Probabilistic Assessment of NASA Ultra-Efficient Engine Technologies for a Large Subsonic Transport

NASA Technical Reports Server (NTRS)

Tong, Michael T.; Jones, Scott M.; Arcara, Philip C., Jr.; Haller, William J.

2004-01-01

NASA's Ultra Efficient Engine Technology (UEET) program features advanced aeropropulsion technologies that include highly loaded turbomachinery, an advanced low-NOx combustor, high-temperature materials, intelligent propulsion controls, aspirated seal technology, and an advanced computational fluid dynamics (CFD) design tool to help reduce airplane drag. A probabilistic system assessment is performed to evaluate the impact of these technologies on aircraft fuel burn and NOx reductions. A 300-passenger aircraft, with two 396-kN thrust (85,000-pound) engines is chosen for the study. The results show that a large subsonic aircraft equipped with the UEET technologies has a very high probability of meeting the UEET Program goals for fuel-burn (or equivalent CO2) reduction (15% from the baseline) and LTO (landing and takeoff) NOx reductions (70% relative to the 1996 International Civil Aviation Organization rule). These results are used to provide guidance for developing a robust UEET technology portfolio, and to prioritize the most promising technologies required to achieve UEET program goals for the fuel-burn and NOx reductions.

Probabilistic representation of gene regulatory networks.

PubMed

Mao, Linyong; Resat, Haluk

2004-09-22

Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation. In this paper, we present a new fully probabilistic approach to the modeling of gene regulatory networks that allows for fluctuations in the gene expression levels. The new algorithm uses a very simple representation for the genes, and accounts for the repression or induction of the genes and for the biological variations among isogenic populations simultaneously. Because of its simplicity, introduced algorithm is a very promising approach to model large-scale gene regulatory networks. We have tested the new algorithm on the synthetic gene network library bioengineered recently. The good agreement between the computed and the experimental results for this library of networks, and additional tests, demonstrate that the new algorithm is robust and very successful in explaining the experimental data. The simulation software is available upon request. Supplementary material will be made available on the OUP server.

Extracting Databases from Dark Data with DeepDive.

PubMed

Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

2016-01-01

DeepDive is a system for extracting relational databases from dark data : the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data - scientific papers, Web classified ads, customer service notes, and so on - were instead in a relational database, it would give analysts a massive and valuable new set of "big data." DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference.

Topics in Probabilistic Judgment Aggregation

ERIC Educational Resources Information Center

Wang, Guanchun

2011-01-01

This dissertation is a compilation of several studies that are united by their relevance to probabilistic judgment aggregation. In the face of complex and uncertain events, panels of judges are frequently consulted to provide probabilistic forecasts, and aggregation of such estimates in groups often yield better results than could have been made…

Cognitive Development Effects of Teaching Probabilistic Decision Making to Middle School Students

ERIC Educational Resources Information Center

Mjelde, James W.; Litzenberg, Kerry K.; Lindner, James R.

2011-01-01

This study investigated the comprehension and effectiveness of teaching formal, probabilistic decision-making skills to middle school students. Two specific objectives were to determine (1) if middle school students can comprehend a probabilistic decision-making approach, and (2) if exposure to the modeling approaches improves middle school…

Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

ERIC Educational Resources Information Center

Chen, Xin

2012-01-01

Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…

Probabilistic Cue Combination: Less Is More

ERIC Educational Resources Information Center

Yurovsky, Daniel; Boyer, Ty W.; Smith, Linda B.; Yu, Chen

2013-01-01

Learning about the structure of the world requires learning probabilistic relationships: rules in which cues do not predict outcomes with certainty. However, in some cases, the ability to track probabilistic relationships is a handicap, leading adults to perform non-normatively in prediction tasks. For example, in the "dilution effect,"…

Is Probabilistic Evidence a Source of Knowledge?

ERIC Educational Resources Information Center

Friedman, Ori; Turri, John

2015-01-01

We report a series of experiments examining whether people ascribe knowledge for true beliefs based on probabilistic evidence. Participants were less likely to ascribe knowledge for beliefs based on probabilistic evidence than for beliefs based on perceptual evidence (Experiments 1 and 2A) or testimony providing causal information (Experiment 2B).…

Probabilistic Structural Analysis of the SRB Aft Skirt External Fitting Modification

NASA Technical Reports Server (NTRS)

Townsend, John S.; Peck, J.; Ayala, S.

1999-01-01

NASA has funded several major programs (the PSAM Project is an example) to develop Probabilistic Structural Analysis Methods and tools for engineers to apply in the design and assessment of aerospace hardware. A probabilistic finite element design tool, known as NESSUS, is used to determine the reliability of the Space Shuttle Solid Rocket Booster (SRB) aft skirt critical weld. An external bracket modification to the aft skirt provides a comparison basis for examining the details of the probabilistic analysis and its contributions to the design process.

Propagation of stage measurement uncertainties to streamflow time series

NASA Astrophysics Data System (ADS)

Horner, Ivan; Le Coz, Jérôme; Renard, Benjamin; Branger, Flora; McMillan, Hilary

2016-04-01

Streamflow uncertainties due to stage measurements errors are generally overlooked in the promising probabilistic approaches that have emerged in the last decade. We introduce an original error model for propagating stage uncertainties through a stage-discharge rating curve within a Bayesian probabilistic framework. The method takes into account both rating curve (parametric errors and structural errors) and stage uncertainty (systematic and non-systematic errors). Practical ways to estimate the different types of stage errors are also presented: (1) non-systematic errors due to instrument resolution and precision and non-stationary waves and (2) systematic errors due to gauge calibration against the staff gauge. The method is illustrated at a site where the rating-curve-derived streamflow can be compared with an accurate streamflow reference. The agreement between the two time series is overall satisfying. Moreover, the quantification of uncertainty is also satisfying since the streamflow reference is compatible with the streamflow uncertainty intervals derived from the rating curve and the stage uncertainties. Illustrations from other sites are also presented. Results are much contrasted depending on the site features. In some cases, streamflow uncertainty is mainly due to stage measurement errors. The results also show the importance of discriminating systematic and non-systematic stage errors, especially for long term flow averages. Perspectives for improving and validating the streamflow uncertainty estimates are eventually discussed.

System Risk Assessment and Allocation in Conceptual Design

NASA Technical Reports Server (NTRS)

Mahadevan, Sankaran; Smith, Natasha L.; Zang, Thomas A. (Technical Monitor)

2003-01-01

As aerospace systems continue to evolve in addressing newer challenges in air and space transportation, there exists a heightened priority for significant improvement in system performance, cost effectiveness, reliability, and safety. Tools, which synthesize multidisciplinary integration, probabilistic analysis, and optimization, are needed to facilitate design decisions allowing trade-offs between cost and reliability. This study investigates tools for probabilistic analysis and probabilistic optimization in the multidisciplinary design of aerospace systems. A probabilistic optimization methodology is demonstrated for the low-fidelity design of a reusable launch vehicle at two levels, a global geometry design and a local tank design. Probabilistic analysis is performed on a high fidelity analysis of a Navy missile system. Furthermore, decoupling strategies are introduced to reduce the computational effort required for multidisciplinary systems with feedback coupling.

Fully probabilistic control design in an adaptive critic framework.

PubMed

Herzallah, Randa; Kárný, Miroslav

2011-12-01

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem; in particular, very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic control algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

Sensibility analysis of VORIS lava-flow simulations: application to Nyamulagira volcano, Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Syavulisembo, A. M.; Havenith, H.-B.; Smets, B.; d'Oreye, N.; Marti, J.

2015-03-01

Assessment and management of volcanic risk are important scientific, economic, and political issues, especially in densely populated areas threatened by volcanoes. The Virunga area in the Democratic Republic of Congo, with over 1 million inhabitants, has to cope permanently with the threat posed by the active Nyamulagira and Nyiragongo volcanoes. During the past century, Nyamulagira erupted at intervals of 1-4 years - mostly in the form of lava flows - at least 30 times. Its summit and flank eruptions lasted for periods of a few days up to more than two years, and produced lava flows sometimes reaching distances of over 20 km from the volcano, thereby affecting very large areas and having a serious impact on the region of Virunga. In order to identify a useful tool for lava flow hazard assessment at the Goma Volcano Observatory (GVO), we tested VORIS 2.0.1 (Felpeto et al., 2007), a freely available software (http://www.gvb-csic.es) based on a probabilistic model that considers topography as the main parameter controlling lava flow propagation. We tested different Digital Elevation Models (DEM) - SRTM1, SRTM3, and ASTER GDEM - to analyze the sensibility of the input parameters of VORIS 2.0.1 in simulation of recent historical lava-flow for which the pre-eruption topography is known. The results obtained show that VORIS 2.0.1 is a quick, easy-to-use tool for simulating lava-flow eruptions and replicates to a high degree of accuracy the eruptions tested. In practice, these results will be used by GVO to calibrate VORIS model for lava flow path forecasting during new eruptions, hence contributing to a better volcanic crisis management.

Data uncertainties in material flow analysis: Municipal solid waste management system in Maputo City, Mozambique.

PubMed

Dos Muchangos, Leticia Sarmento; Tokai, Akihiro; Hanashima, Atsuko

2017-01-01

Material flow analysis can effectively trace and quantify the flows and stocks of materials such as solid wastes in urban environments. However, the integrity of material flow analysis results is compromised by data uncertainties, an occurrence that is particularly acute in low-and-middle-income study contexts. This article investigates the uncertainties in the input data and their effects in a material flow analysis study of municipal solid waste management in Maputo City, the capital of Mozambique. The analysis is based on data collected in 2007 and 2014. Initially, the uncertainties and their ranges were identified by the data classification model of Hedbrant and Sörme, followed by the application of sensitivity analysis. The average lower and upper bounds were 29% and 71%, respectively, in 2007, increasing to 41% and 96%, respectively, in 2014. This indicates higher data quality in 2007 than in 2014. Results also show that not only data are partially missing from the established flows such as waste generation to final disposal, but also that they are limited and inconsistent in emerging flows and processes such as waste generation to material recovery (hence the wider variation in the 2014 parameters). The sensitivity analysis further clarified the most influencing parameter and the degree of influence of each parameter on the waste flows and the interrelations among the parameters. The findings highlight the need for an integrated municipal solid waste management approach to avoid transferring or worsening the negative impacts among the parameters and flows.

Active hopper for promoting flow of bulk granular or powdered solids

DOEpatents

Saunders, Timothy; Brady, John D.

2013-04-02

An apparatus that promotes the flow of materials has a body having an inner shape for holding the materials, a wall having a shape that approximates a portion of the inner shape of the body, and a vibrator attached to the wall. The wall may be disposed vertically within the body close to the body's inner shape. The vibrator transfers vibrations to the wall to agitate the material and encourage material flow.

A High-Resolution Godunov Method for Compressible Multi-Material Flow on Overlapping Grids

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

Banks, J W; Schwendeman, D W; Kapila, A K

2006-02-13

A numerical method is described for inviscid, compressible, multi-material flow in two space dimensions. The flow is governed by the multi-material Euler equations with a general mixture equation of state. Composite overlapping grids are used to handle complex flow geometry and block-structured adaptive mesh refinement (AMR) is used to locally increase grid resolution near shocks and material interfaces. The discretization of the governing equations is based on a high-resolution Godunov method, but includes an energy correction designed to suppress numerical errors that develop near a material interface for standard, conservative shock-capturing schemes. The energy correction is constructed based on amore » uniform pressure-velocity flow and is significant only near the captured interface. A variety of two-material flows are presented to verify the accuracy of the numerical approach and to illustrate its use. These flows assume an equation of state for the mixture based on Jones-Wilkins-Lee (JWL) forms for the components. This equation of state includes a mixture of ideal gases as a special case. Flow problems considered include unsteady one-dimensional shock-interface collision, steady interaction of an planar interface and an oblique shock, planar shock interaction with a collection of gas-filled cylindrical inhomogeneities, and the impulsive motion of the two-component mixture in a rigid cylindrical vessel.« less

Optimization Testbed Cometboards Extended into Stochastic Domain

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Pai, Shantaram S.; Coroneos, Rula M.; Patnaik, Surya N.

2010-01-01

COMparative Evaluation Testbed of Optimization and Analysis Routines for the Design of Structures (CometBoards) is a multidisciplinary design optimization software. It was originally developed for deterministic calculation. It has now been extended into the stochastic domain for structural design problems. For deterministic problems, CometBoards is introduced through its subproblem solution strategy as well as the approximation concept in optimization. In the stochastic domain, a design is formulated as a function of the risk or reliability. Optimum solution including the weight of a structure, is also obtained as a function of reliability. Weight versus reliability traced out an inverted-S-shaped graph. The center of the graph corresponded to 50 percent probability of success, or one failure in two samples. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure that corresponded to unity for reliability. Weight can be reduced to a small value for the most failure-prone design with a compromised reliability approaching zero. The stochastic design optimization (SDO) capability for an industrial problem was obtained by combining three codes: MSC/Nastran code was the deterministic analysis tool, fast probabilistic integrator, or the FPI module of the NESSUS software, was the probabilistic calculator, and CometBoards became the optimizer. The SDO capability requires a finite element structural model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life airframe component made of metallic and composite materials.

On the Accuracy of Probabilistic Bucking Load Prediction

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Starnes, James H.; Nemeth, Michael P.

2001-01-01

The buckling strength of thin-walled stiffened or unstiffened, metallic or composite shells is of major concern in aeronautical and space applications. The difficulty to predict the behavior of axially compressed thin-walled cylindrical shells continues to worry design engineers as we enter the third millennium. Thanks to extensive research programs in the late sixties and early seventies and the contributions of many eminent scientists, it is known that buckling strength calculations are affected by the uncertainties in the definition of the parameters of the problem such as definition of loads, material properties, geometric variables, edge support conditions, and the accuracy of the engineering models and analysis tools used in the design phase. The NASA design criteria monographs from the late sixties account for these design uncertainties by the use of a lump sum safety factor. This so-called 'empirical knockdown factor gamma' usually results in overly conservative design. Recently new reliability based probabilistic design procedure for buckling critical imperfect shells have been proposed. It essentially consists of a stochastic approach which introduces an improved 'scientific knockdown factor lambda(sub a)', that is not as conservative as the traditional empirical one. In order to incorporate probabilistic methods into a High Fidelity Analysis Approach one must be able to assess the accuracy of the various steps that must be executed to complete a reliability calculation. In the present paper the effect of size of the experimental input sample on the predicted value of the scientific knockdown factor lambda(sub a) calculated by the First-Order, Second-Moment Method is investigated.

Statistical models of lunar rocks and regolith

NASA Technical Reports Server (NTRS)

Marcus, A. H.

1973-01-01

The mathematical, statistical, and computational approaches used in the investigation of the interrelationship of lunar fragmental material, regolith, lunar rocks, and lunar craters are described. The first two phases of the work explored the sensitivity of the production model of fragmental material to mathematical assumptions, and then completed earlier studies on the survival of lunar surface rocks with respect to competing processes. The third phase combined earlier work into a detailed statistical analysis and probabilistic model of regolith formation by lithologically distinct layers, interpreted as modified crater ejecta blankets. The fourth phase of the work dealt with problems encountered in combining the results of the entire project into a comprehensive, multipurpose computer simulation model for the craters and regolith. Highlights of each phase of research are given.

The Use of Logistics n the Quality Parameters Control System of Material Flow

ERIC Educational Resources Information Center

Karpova, Natalia P.; Toymentseva, Irina A.; Shvetsova, Elena V.; Chichkina, Vera D.; Chubarkova, Elena V.

2016-01-01

The relevance of the research problem is conditioned on the need to justify the use of the logistics methodologies in the quality parameters control process of material flows. The goal of the article is to develop theoretical principles and practical recommendations for logistical system control in material flows quality parameters. A leading…

Effects of Surface and Subsurface Bed Material Composition on Gravel Transport and Flow Competence Relations—Possibilities for Prediction

NASA Astrophysics Data System (ADS)

Bunte, K.; Abt, S. R.; Swingle, K. W.; Cenderelli, D. A.; Gaeuman, D. A.

2014-12-01

Bedload transport and flow competence relations are difficult to predict in coarse-bedded steep streams where widely differing sediment supply, bed stability, and complex flow hydraulics greatly affect amounts and sizes of transported gravel particles. This study explains how properties of bed material surface and subsurface size distributions are directly related to gravel transport and may be used for prediction of gravel transport and flow competence relations. Gravel transport, flow competence, and bed material size were measured in step-pool and plane-bed streams. Power functions were fitted to gravel transport QB=aQb and flow competence Dmax=cQd relations; Q is water discharge. Frequency distributions of surface FDsurf and subsurface FDsub bed material were likewise described by power functions FDsurf=hD j and FDsub=kDm fitted over six 0.5-phi size classes within 4 to 22.4 mm. Those gravel sizes are typically mobile even in moderate floods. Study results show that steeper subsurface bed material size distributions lead to steeper gravel transport and flow competence relations, whereas larger amounts of sediment contained in those 6 size bedmaterial classes (larger h and k) flatten the relations. Similarly, steeper surface size distributions decrease the coefficients of the gravel transport and flow competence relations, whereas larger amounts of sediment within the six bed material classes increase the intercepts of gravel transport and flow competence relations. Those relations are likely causative in streams where bedload stems almost entirely from the channel bed as opposed to direct (unworked) contributions from hillslopes and tributaries. The exponent of the subsurface bed material distribution m predicted the gravel transport exponent b with r2 near 0.7 and flow competence exponent d with r2 near 0.5. The intercept of bed surface distributions h increased the intercept a of gravel transport and c of the flow competence relations with r2 near 0.6.

Total probabilities of ensemble runoff forecasts

NASA Astrophysics Data System (ADS)

Olav Skøien, Jon; Bogner, Konrad; Salamon, Peter; Smith, Paul; Pappenberger, Florian

2017-04-01

Ensemble forecasting has a long history from meteorological modelling, as an indication of the uncertainty of the forecasts. However, it is necessary to calibrate and post-process the ensembles as the they often exhibit both bias and dispersion errors. Two of the most common methods for this are Bayesian Model Averaging (Raftery et al., 2005) and Ensemble Model Output Statistics (EMOS) (Gneiting et al., 2005). There are also methods for regionalizing these methods (Berrocal et al., 2007) and for incorporating the correlation between lead times (Hemri et al., 2013). Engeland and Steinsland Engeland and Steinsland (2014) developed a framework which can estimate post-processing parameters varying in space and time, while giving a spatially and temporally consistent output. However, their method is computationally complex for our larger number of stations, which makes it unsuitable for our purpose. Our post-processing method of the ensembles is developed in the framework of the European Flood Awareness System (EFAS - http://www.efas.eu), where we are making forecasts for whole Europe, and based on observations from around 700 catchments. As the target is flood forecasting, we are also more interested in improving the forecast skill for high-flows rather than in a good prediction of the entire flow regime. EFAS uses a combination of ensemble forecasts and deterministic forecasts from different meteorological forecasters to force a distributed hydrologic model and to compute runoff ensembles for each river pixel within the model domain. Instead of showing the mean and the variability of each forecast ensemble individually, we will now post-process all model outputs to estimate the total probability, the post-processed mean and uncertainty of all ensembles. The post-processing parameters are first calibrated for each calibration location, but we are adding a spatial penalty in the calibration process to force a spatial correlation of the parameters. The penalty takes distance, stream-connectivity and size of the catchment areas into account. This can in some cases have a slight negative impact on the calibration error, but avoids large differences between parameters of nearby locations, whether stream connected or not. The spatial calibration also makes it easier to interpolate the post-processing parameters to uncalibrated locations. We also look into different methods for handling the non-normal distributions of runoff data and the effect of different data transformations on forecasts skills in general and for floods in particular. Berrocal, V. J., Raftery, A. E. and Gneiting, T.: Combining Spatial Statistical and Ensemble Information in Probabilistic Weather Forecasts, Mon. Weather Rev., 135(4), 1386-1402, doi:10.1175/MWR3341.1, 2007. Engeland, K. and Steinsland, I.: Probabilistic postprocessing models for flow forecasts for a system of catchments and several lead times, Water Resour. Res., 50(1), 182-197, doi:10.1002/2012WR012757, 2014. Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098-1118, doi:10.1175/MWR2904.1, 2005. Hemri, S., Fundel, F. and Zappa, M.: Simultaneous calibration of ensemble river flow predictions over an entire range of lead times, Water Resour. Res., 49(10), 6744-6755, doi:10.1002/wrcr.20542, 2013. Raftery, A. E., Gneiting, T., Balabdaoui, F. and Polakowski, M.: Using Bayesian Model Averaging to Calibrate Forecast Ensembles, Mon. Weather Rev., 133(5), 1155-1174, doi:10.1175/MWR2906.1, 2005.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks.

PubMed

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

PubMed Central

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses. PMID:29163110

Research on the Stress and Material Flow with Single Particle—Simulations and Experiments

NASA Astrophysics Data System (ADS)

Zhang, Tao; Jiang, Feng; Yan, Lan; Xu, Xipeng

2017-04-01

The scratching process of particle is a complex material removal process involving cutting, plowing, and rubbing. In this study, scratch experiments under different loads are performed on a multifunctional tester for material surface. Natural diamond and Fe-Cr-Ni stainless steel are chosen as indenter and workpiece material, respectively. The cutting depth and side flow height of scratch are measured using a white light interferometer. The finite element model is developed, and the numerical simulation of scratching is conducted using AdvantEdgeTM. The simulated forces and side flow height under different cutting depths correspond well with experimental results, validating the accuracy of the scratching simulation. The mises stress distribution of the particle is presented, with the maximum stress occurring inside the particle rather than on the surface. The pressure distribution of the particle is also given, and results show that the maximum pressure occurs on the contact surface of particle and workpiece. The material flow contour is presented, and material flow direction and velocity magnitude are analyzed.

System and method for measuring permeability of materials

DOEpatents

Hallman, Jr., Russell Louis; Renner, Michael John

2013-07-09

Systems and methods are provided for measuring the permeance of a material. The permeability of the material may also be derived. Systems typically provide a liquid or high concentration fluid bath on one side of a material test sample, and a gas flow across the opposing side of the material test sample. The mass flow rate of permeated fluid as a fraction of the combined mass flow rate of gas and permeated fluid is used to calculate the permeance of the material. The material test sample may be a sheet, a tube, or a solid shape. Operational test conditions may be varied, including concentration of the fluid, temperature of the fluid, strain profile of the material test sample, and differential pressure across the material test sample.

Material permeance measurement system and method

DOEpatents

Hallman, Jr., Russell Louis; Renner, Michael John [Oak Ridge, TN

2012-05-08

A system for measuring the permeance of a material. The permeability of the material may also be derived. The system provides a liquid or high concentration fluid bath on one side of a material test sample, and a gas flow across the opposing side of the material test sample. The mass flow rate of permeated fluid as a fraction of the combined mass flow rate of gas and permeated fluid is used to calculate the permeance of the material. The material test sample may be a sheet, a tube, or a solid shape. Operational test conditions may be varied, including concentration of the fluid, temperature of the fluid, strain profile of the material test sample, and differential pressure across the material test sample.