Boundary Uncertainty Research Articles

An improved method for fuzzy–interval uncertainty analysis and its application in brake instability study

Most of the existing methods of brake squeal instability analysis are merely available to handle single type of uncertain case. In this study, an improved unified method is developed for uncertainty quantification, which is capable of handling two types of fuzzy–interval cases. In the first fuzzy–interval case, uncertain parameters of engineering structures are assumed as either fuzzy variables or interval variables, which exist in structures simultaneously and independently. In the second fuzzy–interval case, all uncertain parameters are represented by interval variables, but their lower and upper bounds just can be expressed as fuzzy variables instead of deterministic values. In the proposed method, fuzzy–boundary interval variables are introduced to handle fuzzy–interval uncertainties, and based on which an improved response analysis model is established. In the improved model, the fuzzy–boundary interval variables are firstly converted into interval-boundary variables by level-cut technique. Then by temporarily neglecting boundary uncertainties, the initial interval responses can be approximated via conducting once Taylor series expansion and subinterval analysis. Next, Taylor series expansion and central difference method are combined twice to deal with boundary uncertainties, and the interval responses of the structures with interval-boundary variables are yielded. Finally, the fuzzy–interval responses of the structures are derived on the basis of interval union operation and fuzzy decomposition theorem. The improved method is subsequently extended to quantify the uncertainties in brake squeal instability analysis involving two types of fuzzy–interval uncertainties. The effectiveness of the proposed method on tackling fuzzy–interval problems is demonstrated by numerical examples.

Evaluating large eddy simulation results based on error analysis

The quantification of the prediction accuracy in large eddy simulations (LES) is very challenging due to various interacting errors associated with this approach. When dealing with errors in LES using implicit filtering, numerical and modeling errors have drawn the interest of many researchers. Little attention has been paid to other sources of discrepancies between LES results and reference data, namely sampling errors, influence of the initial conditions, improper boundary conditions or uncertainties issuing from reference data. A framework of metrics that includes all these issues is addressed in the present paper to study subgrid-scale (SGS) models for LES and to quantify their prediction accuracy and computational costs. The method is applied to a simple wall-bounded turbulent flow at moderate Reynolds number. It turns out from the results obtained with six commonly used SGS models that wall-adapting models (WALE and SIGMA) and localized dynamic models reproduce the physics of the flow field more faithfully, reveal a superior prediction accuracy and have a similar computational cost than models using van Driest wall damping. Especially at the viscous wall region (r^+<50), wall-adapting and localized dynamic models are more accurate, reflecting the proper near wall behavior of such models. Relying on the analysis of sources of various errors, uncertainties in LES are estimated and systematically assessed, and their influence on simulation results is quantified. Finally, engineering estimations of the required averaging time to obtain basic estimates of statistical quantities with a predetermined degree of accuracy are suggested.

An Intelligent Theranostics Method Using Optical Coherence Tomography Guided Automatic Laser Ablation for Neurosurgery.

Methods to reduce the high disability and fatality rate of neurosurgery caused by surgeon tremor and uncertainty of intraoperative tumor boundary have long been greatly concerned. We have proposed an intelligent theranostics method for a compact integrated diagnosis and therapeutic platform to automatically excise the brain tumor with high precision. To perform this operation, hardware combination of a benchtop spectral domain optical coherence tomography (SD-OCT) and a high-power laser has been implemented by a customized fiber combiner. By the double-clad fiber out of the combiner which works as both the OCT sample arm fiber and the ablation laser output fiber, an in situ theranostics process without registration can be conducted. The SD-OCT image analysis from both en face and depth perspectives shows the structural information intuitively and accordingly generate the ablation-guiding grid. Based on the grid, the continuous wave high-power laser ablates ex vivo porcine brain models in submillimeter automatically. The feasibility of this theranostics method has been verified by the comparison of attenuation maps before and after ablation, and the contrast of its pathology.

Using reweighting and free energy surface interpolation to predict solid-solid phase diagrams.

Many physical properties of small organic molecules are dependent on the current crystal packing, or polymorph, of the material, including bioavailability of pharmaceuticals, optical properties of dyes, and charge transport properties of semiconductors. Predicting the most stable crystalline form at a given temperature and pressure requires determining the crystalline form with the lowest relative Gibbs free energy. Effective computational prediction of the most stable polymorph could save significant time and effort in the design of novel molecular crystalline solids or predict their behavior under new conditions. In this study, we introduce a new approach using multistate reweighting to address the problem of determining solid-solid phase diagrams and apply this approach to the phase diagram of solid benzene. For this approach, we perform sampling at a selection of temperature and pressure states in the region of interest. We use multistate reweighting methods to determine the reduced free energy differences between T and P states within a given polymorph and validate this phase diagram using several measures. The relative stability of the polymorphs at the sampled states can be successively interpolated from these points to create the phase diagram by combining these reduced free energy differences with a reference Gibbs free energy difference between polymorphs. The method also allows for straightforward estimation of uncertainties in the phase boundary. We also find that when properly implemented, multistate reweighting for phase diagram determination scales better with the size of the system than previously estimated.

Uncertainty quantification of fracture boundary of pre-hydrided Zircaloy-4 cladding tube under LOCA conditions

To quantify the fracture boundary uncertainty for non-irradiated, pre-hydrided Zircaloy-4 cladding tube specimens under loss-of-coolant accident conditions at a light-water reactor, data from integral thermal shock tests obtained by an earlier study are analyzed statistically and the fracture boundary is estimated in terms of probability, as follows. First, a method is proposed to obtain the specimens’ fracture probability curve as a function of equivalent cladding reacted (ECR) and initial hydrogen concentration using Bayesian inference with a generalized linear model. A log-probit model is used, modified to reflect the effect of the initial hydrogen concentration on the fracture boundary and the ECR evaluation uncertainty, and scaled to improve convergence. Second, using the modified log-probit model, it is shown that the boundary representing a 5% fracture probability with 95% confidence for the pre-hydrided cladding tube sample is higher than 15% ECR, for initial hydrogen concentrations of up to 800 wppm.

Ethno-territorial problems of regional security in Central Asia

The article deals with the ethno-territorial contradictions that arose between the new independent States of Central Asia after the collapse of the USSR. The complexity of border problems is associated with a number of historical, ethnic and physical-geographical factors. The mountainous terrain, ethnic “cross-hair”, when a significant part of the “titular” population of one country lived in a neighboring state, and the lack of universally recognized borders between the republics made it difficult to demarcate them. Uncertainty of boundaries, which is exacerbated by an acute shortage of water and land resources, contributes to tension and inter-ethnic conflicts. Including one of the problems are socio-economic reasons. Ethnic groups vary greatly in language, religion and way of life, according to socio-political status, and the presence of forces external to the conflicting parties interested in continuing the conflict. The most intense section is the Fergana Valley, which includes several enclaves, respectively, the interests of Uzbekistan, Kyrgyzstan and Tajikistan collide here. The difficulty lies in the fact that these states, in addition to territorial claims to each other, have other problems in relations. Even in those areas where the borders were agreed, there were interethnic clashes, which caused even greater tension.

Глубинная герменевтика в визуальном анализе (на примере фильма В. Аллена «Зелиг»)

By the example of analysis of the Woody Allen’s movie Zelig the ego-states phenomenology of borderline personality with split identity is presented, of a person with inclination to various transfigurations (chameleonization), who deeply feels his foreignness in the social context, in the diversity of false facades and absurd conformism, which are designed to compensate the inner feeling of emptiness and emotional hunger with the help of manipulations. The clinical phenomenon resonates with the contemporary sociocultural trends of the society of transitivity and designates the risks of clinical deviations in the conditions of uncertainty and vagueness of boundaries of personal and social space. Deep hermeneutics, implemented in the methodology of visual analysis, is considered as a practice of research of modern culture and mass consciousness, which reveals such a scientific trend as the search for transdisciplinary intersections of clinical and social psychology in the study of social and cultural phenomena.

Kangaroos and Crocodiles: The Timor Sea Treaty of 2018

This chapter explores frontiers as political and economic constructs, focusing on the contested borders and boundaries of Timor-Leste. At its centre is a dispute about the maritime boundary between Timor-Leste and Australia in which access to petroleum resources in the Timor Sea has been at stake. In 2018, Timor-Leste and Australia signed a Treaty ‘to settle finally their maritime boundaries in the Timor Sea’. Despite considerable mutual self-congratulation, this treaty does not finalise the boundary now (instead creating an anomalous and temporary enclave to accommodate Australia’s economic interests). Nor does it deal conclusively with the crucial question of who should extract oil and gas or where it should be processed: it could not do so, for these decisions are ultimately not for nation states but for international corporations. To them, frontiers are less about pride and security than about opportunities and obstacles. The maritime boundary dispute can only be properly understood in the broader context of relations between Australia, Timor-Leste, and Indonesia. This leads to a border, the division of the island of Timor between Indonesia and (what is now) the Democratic Republic of Timor-Leste. This complex border – one line dividing the island from north to south and another enclosing a small enclave in north-west Timor – is a legacy of colonial occupation by the Dutch in the west and by the Portuguese in the east. For the last quarter of the twentieth century, this border became merely a division between two Indonesian provinces. Soon after East Timor declared independence in the wake of its 1975 abandonment by post-colonial Portugal, Indonesia invaded, uniting the island until a heroic resistance movement led to multinational intervention in 1999 and restoration of independence – and the border. Frontiers are of variable tangibility. Land borders are usually identifiable and impact upon lived space. Maritime boundaries are nebulous and distant: they are the product of complex interactions involving physical features as well as legal and political compromises. They may differ in regard to the seabed and the water column above it. Even more amorphous are economic borders, established by trade or resource-sharing agreements. Then come the least distinct borders between truth and lies, between expediency and principle, between the past and the future, between cynicism and integrity, and between people whose lives count and those whose lives do not. In exploiting the uncertainty of maritime boundaries, Australia trod an unsteady path along the borders of the final type. Public opinion, in-country action and NGO activity have often contrasted with political deceit, arrogance and opportunism.

Practical and Intrinsic Predictability of Multiscale Weather and Convectively Coupled Equatorial Waves during the Active Phase of an MJO

Abstract Through a series of convection-permitting regional-scale ensembles based on the Weather Research and Forecasting (WRF) Model, this study investigates the predictability of multiscale weather and convectively coupled equatorial waves during the active phase of a Madden–Julian oscillation (MJO) event over the Indian Ocean from 12 October to 12 November 2011. It is found that the practical predictability limit, estimated by the spread of the ensemble perturbed with realistic initial and boundary uncertainties, is as much as 8 days for horizontal winds, temperature, and humidity for scales larger than 2000 km that include equatorial Rossby, Kelvin, inertia–gravity, and mixed Rossby–gravity waves. The practical predictability limit decreases rapidly as scale decreases, resulting in a predictable time scale less than 1 day for scales smaller than 200 km. Through further experiments using minute initial and boundary perturbations an order of magnitude smaller than the current realistic uncertainties, the intrinsic predictability limit for tropical weather at larger scales (&amp;gt;2000 km) is estimated to be achievable beyond 2 weeks, but the limit is likely still less than 3 days for the small scales (&amp;lt;200 km).

New unknown input observer and output feedback stabilization for uncertain heat equation

In this paper, we propose a new method, by designing an unknown input type state observer, to stabilize an unstable 1-d heat equation with boundary uncertainty and external disturbance. The state observer is designed in terms of a disturbance estimator. A stabilizing state feedback control is designed for the observer by the backstepping transformation, which is an observer based output feedback stabilizing control for the original system. The well-posedness and stability of the closed-loop system are concluded. The numerical simulations show that the proposed scheme is quite effectively. This is a first result on active disturbance rejection control for a PDE with both boundary uncertainty and external disturbance.

Robust adaptive fuzzy control for a class of nonlinear coupled ODE–beam systems with boundary uncertainty

This paper investigates a robust adaptive fuzzy control problem for a class of nonlinear ordinary differential equations (ODEs) coupled with a beam equation subject to boundary uncertainty. A fuzzy control scheme based on the Takagi–Sugeno (T–S) fuzzy model is employed for the nonlinear ODE subsystem with ODE state feedback. For the beam with boundary uncertainty, a robust adaptive fuzzy boundary control scheme is adopted, where a linear controller via boundary measurements is used to stabilize the beam, and a robust adaptive fuzzy compensator is utilized to counteract the boundary uncertainty. The asymptotic stabilization condition is derived for the nonlinear coupled ODE–beam system by means of the Lyapunov's direct method, which is provided in terms of a set of bilinear matrix inequalities (BMIs). Furthermore, a two-step procedure is presented to solve the BMI feasibility problem by the existing linear matrix inequality (LMI) optimization techniques. Finally, a simulation study is conducted on a flexible spacecraft to demonstrate the effectiveness of the proposed method.

System reliability analysis and risk assessment of a layered slope in spatially variable soils considering stratigraphic boundary uncertainty

Due to complex geological deposition, post-deposition processes and limited site investigation data in engineering practice, soil properties are often spatially variable and the stratigraphic boundary in layered soils is generally characterized by uncertainty. The spatial variability of soil properties has been well investigated in past years, whereas the question of how the stratigraphic boundary uncertainty affects the slope stability remains unanswered. This paper attempts to investigate the effects of the stratigraphic boundary uncertainty on the system reliability and risk of a layered slope in spatially variable soils. In this paper, the spatial variability of soil properties is simulated by non-stationary random fields that are generated by an extended Cholesky decomposition technique, while the stochastic nature of the stratigraphic boundary location is simulated by a discrete random variable. Monte Carlo simulation (MCS) is suggested for evaluating the system failure probability and risk. Various comparisons between probabilistic analysis results obtained from considering and neglecting the stratigraphic boundary uncertainty have been made for different statistics of soil properties. Results show that the stratigraphic boundary uncertainty plays an important role in identifying the slope failure mechanism. Moreover, neglecting the stratigraphic boundary uncertainty would generally overestimate the slope failure risk for different statistics, except at small coefficients of variation of the friction angle, where the results are underestimated.

Comparing gravity-based to seismic-derived lithosphere densities: a case study of the British Isles and surrounding areas

Lithospheric density structure can be constructed from seismic tomography, gravity modelling, or using both data sets. The different approaches have their own uncertainties and limitations. This study aims to characterize and quantify some of the uncertainties in gravity modelling of lithosphere densities. To evaluate the gravity modelling we compare gravity-based and seismic velocity-based approaches to estimating lithosphere densities. In this study, we use a crustal model together with lithospheric isostasy and gravity field observations to estimate lithosphere densities. To quantify the effect of uncertainty in the crustal model, three models are implemented in this study: CRUST1.0, EuCrust-07 and a high-resolution P-wave velocity model of the British Isles and surrounding areas. Different P-wave velocity-to-density conversions are used to study the uncertainty in these conversion methods. The crustal density models are forward modelled into gravity field quantities using a method that is able to produce spherical harmonic coefficients. Deep mantle signal is assumed to be removed by removing spherical harmonic coefficients of degree 0–10 in the observed gravity field. The uncertainty in the resulting lithosphere densities due to the different crustal models is ±110 kg m−3, which is the largest uncertainty in gravity modelling. Other sources of uncertainty, such as the VP to density conversion (±10 kg m−3), long-wavelength truncation (±5 kg m−3), choice of reference model (<±20 kg m−3) and Lithosphere Asthenosphere Boundary uncertainty (±30 kg m−3), proved to be of lesser importance. The resulting lithosphere density solutions are compared to density models based on a shear wave velocity model. The comparison shows that the gravity-based models have an increased lateral resolution compared to the tomographic solutions. However, the density anomalies of the gravity-based models are three times higher. This is mainly due to the high resolution in the gravity field. To account for this, the gravity-based density models are filtered with a spatial Gaussian filter with 200 km half-width, which results in similar density estimates (±35 kg m−3) with the tomographic approach. Lastly, the gravity-based density is used to estimate laterally varying conversion factors, which correlate with major tectonic regions. The independent gravity-based solutions could help in identifying different compositional domains in the lithosphere, when compared to the tomographic solutions.

Application of truncated gaussian simulation to ore-waste boundary modeling of Golgohar iron deposit

Truncated Gaussian Simulation (TGS) is a well-known method to generate realizations of the ore domains located in a spatial sequence. In geostatistical framework geological domains are normally utilized for stationary assumption. The ability to measure the uncertainty in the exact locations of the boundaries among different geological units is a common challenge for practitioners. As a simple and informative example of such a boundary, one can consider the boundary between ore and waste materials in an ore deposit. This boundary addresses the percentages of the ore and the waste, and also affect the future economy of mine and all precedent mine designs and mine plans. Deterministic approaches, based on interpretation of geological phenomenon, provide just one scenario of ore-waste variation, and do not offer a model for uncertainty of boundaries. On the other hand, geostatistical simulations, based on stochastic models, can measure the uncertainty of such a boundary. Through different techniques for spatial simulation of the categorical data (geological domains) truncated gaussian simulation has been proved to be versatile when geological units have sequential geometries and/or there are few number of indicators (ore and waste). This study addresses the application of TGS for conditional simulation of ore and waste domains in Golgohar iron ore deposit. Separation of the ore and waste domains has affected the ore tonnage estimation and resource evaluation. Various simulations can be considered as the spatial realizations of ore and waste. TGS can generate realizations of the domains and measure the uncertainty of ore-waste boundary. The accuracy of result has been checked through performance evaluation section and different scenarios (e.g. best, average and worst). The best scenario is the one with the most accuracy that is calculated from confusion matrix. The scenario No. 44 with 96 million cubic meters tonnage has an accuracy over 86 percent that is proposed as the best scenario for future mine design and planning.

Derivation of Pareto Optimal Operating Policies Based on Safety Indices for a Catalytic Multi-tubular Reactor Used for Nitrobenzene Hydrogenation

When highly exothermic/hazardous reactions are conducted in the presence of parametric uncertainty, derivation of optimal operating policies for a chemical reactor has to simultaneously consider several objectives of sustainability. The paper uses an original methodology to generate the Pareto optimal solutions when reactor productivity and safety objectives (expressed in probabilistic terms) are simultaneously considered using the process and reactor model in a simple way, in the presence of technological constraints, uncertainty in safety boundaries, and random fluctuations in control variables. An example is provided for the industrial fixed-bed tubular reactor used for the catalytic hydrogenation of nitrobenzene to aniline in vapour-phase.

Quantifying the uncertainty in the spatial layout of rock type domains in an iron ore deposit

This work addresses the problem of delineating the spatial layout of ten rock type domains in an iron ore body and of assessing the uncertainty in the domain boundaries. A stochastic approach is proposed to this end, based on truncated Gaussian simulation, which consists in defining successive partitions of the space that comply with the desired spatial continuity and contact relationships between rock type domains. The sequencing of these domains is driven by their position (surficial vs. underlying rocks), granulometry (compact vs. friable rocks), and grades (rich vs. poor) of iron, alumina, manganese and loss on ignition. A total of 100 realizations are produced, conditioned to available drill hole data, and used to quantify the uncertainty in the occurrence of each rock type domain, at both global and local scales.

Delineation of Trap and Subtrappean Mesozoic Sediments in Saurashtra Peninsula, India

Mapping of sediments beneath volcanic Traps is a highly challenging task. Here we report on the analysis of wide-angle seismic data from Trap-covered Saurashtra peninsula to address this problem. Traveltime modelling of mainly seismic refraction and some reflection phases yields basement configuration, trap and subtrappean sediment thicknesses along the Jodia-Ansador (NW-SE) profile in Saurashtra peninsula. Travel-time skip and amplitude decay in seismic refraction data indicate the presence of low-velocity sediments beneath the Traps. The result reveals two layers with Deccan Traps (4.85-5.0 km s -1 ) followed by Mesozoic sediments above the basement (5.8-6.1 km s -1 ). Using the lower bound velocity (3.2 km s -1 ), sediment thickness varies between 800 and 1500 m. Based on upper bound velocity (4.3 km s -1 ), we find both the sediment thickness and basement depth increase by 600-700 m. The thickness of sediments is more in the northwest and decreases gradually in the southeast, suggesting that the northwestern part of the profile is an important zone for hydrocarbon exploration in the Saurashtra peninsula. With the lower bound velocity of Mesozoics, we find that the basement (5.8-6.1 km s -1 ) is deep (~2100 m) in the northwest and shallows up near Atkot to ~1.0 km depth, and then deepens further southeast, showing the basement upwarped. The overall velocity and boundary uncertainties are of the order of ±0.15 km s -1 and ± 0.15 km respectively.

Uncertainty as a common ground for a dialogue between economics and sociology

ABSTRACTThe article focuses on inter-firm relations, primarily seen as protective devises crafted for keeping at an arm's length various kinds of uncertainties involved in boundary transactions. Taking a holistic view, it proposes the notion of relational habitat, which refers to the relatively durable constellation of relations that connect a given firm to its main business partners. Performing a double-edged protective function, this constellation both stabilizes and simplifies the immediate operational domain of the firm and, thereby, diminishes to manageable levels the complexity of the relevant parts of the environment. By expanding the control of the firm beyond its organizational borders, relational habitat reduces the constraining impact of boundary uncertainty and enhances the action capacity of the firm – facilitating the materialization of its chosen line of action and its desired objectives. The article specifies this notion in detail and highlights some of its implications, both for the theoretical development of economic sociology and for its relation to economics.

Opportunities of Using Random Sets to Model Uncertainties in Agricultural Field Boundaries Observed from Remote Sensing Images

Opportunities of Using Random Sets to Model Uncertainties in Agricultural Field Boundaries Observed from Remote Sensing Images

Quantifying stratigraphic uncertainties by stochastic simulation techniques based on Markov random field

Stratigraphic (or lithological) uncertainty refers to the uncertainty of boundaries between different soil layers and lithological units, which has received increasing attention in geotechnical engineering. In this paper, an effective stochastic geological modeling framework is proposed based on Markov random field theory, which is conditional on site investigation data, such as observations of soil types from ground surface, borehole logs, and strata orientation from geophysical tests. The proposed modeling method is capable of accounting for the inherent heterogeneous and anisotropic characteristics of geological structure. In this method, two modeling approaches are introduced to simulate subsurface geological structures to accommodate different confidence levels on geological structure type (i.e., layered vs. others). The sensitivity analysis for two modeling approaches is conducted to reveal the influence of mesh density and the model parameter on the simulation results. Illustrative examples using borehole data are presented to elucidate the ability to quantify the geological structure uncertainty. Furthermore, the applicability of two modeling approaches and the behavior of the proposed model under different model parameters are discussed in detail. Finally, Bayesian inferential framework is introduced to allow for the estimation of the posterior distribution of model parameter, when additional or subsequent borehole information becomes available. Practical guidance of using the proposed stochastic geological modeling technique for engineering practice is given.