Use Of Probabilistic Approach Research Articles

A Design Scenario Approach for Choosing Protection Works against Rockfall Phenomena

Proximity remote sensing techniques, both land- and drone-based, allow for a significant improvement of the quality and quantity of raw data employed in the analysis of rockfall phenomena. In particular, the large amount of data these techniques can provide allows for the use of probabilistic approaches to rock mass characterization, with particular reference to block volume and shape definition. These, in return, are key parameters required for a proper rockfall hazard assessment and the optimization of countermeasures design. This study aims at providing a sort of guide, starting from the data gathering phase to the processing, up to the implementation of the outputs in a probabilistic-based scenario, which is able to associate a probability of not being exceeded with total kinetic energy values. By doing so, we were able to introduce a new approach for the choice of design parameters and the evaluation of the effectiveness of mitigation techniques. For this purpose, a suitable case study located in Varaita Valley (Cuneo, Italy) has been selected. The area has been surveyed, and a model of the slope and a digital model of the rock faces have been defined. The results show that a 6.5 m3 block has a probability of not being exceeded of 75%; subsequent simulations show that the level of kinetic energy involved in such a rockfall is extremely high. Some mitigation techniques are discussed.

Use of Probabilistic Approaches to Predict Cash Deficits

This article deals with issues related to the use of mathematical methods of cash deficit probability predictions. A number of objective and subjective factors are described that prevent the wide integration of mathematical methods in the practical activities of economists. It is justified that, due to the large number of external and internal factors affecting the economic system state, the values of indicators of an economic system state are often random. The possibility of using probability theory methods to predict the occurrence of cash deficits is proved. Using empirical data including the results of thousands of observations, the possibility of using the normal distribution density function for the purpose of predicting insufficient funds for payment is illustrated. The essence of the proposed model is that it contains a prediction of a macrotrend—i.e., the risk of a cash gap—based on high-frequency microlevel data. At the same time, a prediction of the probability of a cash deficit, and not its estimation for a specific date, was made. This is the main difference between the described model and common scoring estimates. This article proposes an approach to estimate the probability of a cash deficit based on data from a specific business entity, rather than aggregated data from other organizations.

Monte carlo simulation for stability of finite slope subjected to earthquake loading

Analysis of finite slopes is a common practical problem which faces the geotechnical engineering. The aim of the slope analysis is to predict the safety factor against shear failure of the slope which is the ratio between the resisting and the disturbing forces developed along an assumed slip surface. Presence of seismic forces due earthquake lead to more critical situation. The deterministic approaches are employed for this purpose. These approaches do not take into account the uncertainty related to soil properties and/or seismic loads in their procedures. In the present work, a probabilistic approach is adopted using the Monte Carlo simulation technique to study the effect of uncertainty due to soil properties (unit weight, angle of internal friction and cohesion) and seismic accelerations (vertical and horizontal). The results of the work demonstrate that the use of probabilistic approach will yield more accurate results for estimating the safety factor and then economic design of the slope. Also, the results reveal that the statistical properties for the soil shear strength parameters have significant impact on the standard deviation of the output (factor of safety), while the soil unit weight and horizontal acceleration have small effect. However, the vertical acceleration has no effect on it. On other hand, the mean of the output distribution does not affect by the statistical parameters of all input variables. All cases simulated in this study give reliability index (RI) less than 3. Hence, RI values indicate that there are unsatisfactory level of safety for the slope subjected to seismic loading. Finally, the soil shear strength parameters have the same positive significant impact on the safety factor. But, the soil properties and the coefficient of the horizontal acceleration should be selected carefully in the stability analysis due to the effect of their uncertainty on the analysis results.

A Hybrid Model for Fast and Probabilistic Urban Pluvial Flood Prediction

AbstractUrban flooding is highly uncertain, so the use of probabilistic approaches in early flood warning is encouraged. While well‐established 1‐D/2‐D hydrodynamic sewer models do exist, their deterministic nature and long computational time undermine their applicability for real‐time urban flood nowcasting. Aiming at meeting the needs of fast and probabilistic flood modeling, a new hybrid modeling method integrating a suite of lumped hydrological models and logistic regression is proposed. The lumped models are configured using graph theory techniques, based on the sewer system's topology and characteristics, to account for the spatial heterogeneity and physical processes and properties. The logistic regression models are calibrated to lumped models' results and Yes/No flooding information. Due to its conceptual and data‐driven nature, the hybrid model makes fast probabilistic flood predictions at manhole locations. In two case studies, the results showed that when incorporating most dominant physical processes and properties in the model setup, the hybrid model can achieve up to 86% accuracy for flood warnings issued at 50% probability, with 96% computation saving, compared with a traditional 1‐D hydrodynamic model. When such a detailed model is in place, the hybrid model is set up easily, but the accuracy could be further increased when historical flooding observations are considered.

Rising Sea Levels: Helping Decision-Makers Confront the Inevitable

Sea-level rise (SLR) is not just a future trend; it is occurring now in most coastal regions across the globe. It thus impacts not only long-range planning in coastal environments, but also emergency preparedness. Its inevitability and irreversibility on long time scales, in addition to its spatial non-uniformity, uncertain magnitude and timing, and capacity to drive non-stationarity in coastal flooding on planning and engineering timescales, create unique challenges for coastal risk-management decision processes. This review assesses past United States federal efforts to synthesize evolving SLR science in support of coastal risk management. In particular, it outlines the: (1) evolution in global SLR scenarios to those using a risk-based perspective that also considers low-probability but high-consequence outcomes, (2) regionalization of the global scenarios, and (3) use of probabilistic approaches. It also describes efforts to further contextualize regional scenarios by combining local mean sea-level changes with extreme water level projections. Finally, it offers perspectives on key issues relevant to the future uptake, interpretation, and application of sea-level change scenarios in decision-making. These perspectives have utility for efforts to craft standards and guidance for preparedness and resilience measures to reduce the risk of coastal flooding and other impacts related to SLR.

Weak Plane Failure of Phyllitic Sandstone: Back Analysis for Slope Stabilization and the Use of Probabilistic Approach for Design Optimization

The main access road of Mae Mao dam hydropower project, Chiang Mai province, Thailand, has failed during a sunny day. The question has been raised of what might have triggered the failure. At the day of failure, the precipitation amount was very small and the accumulated rainfall amount in the past days was also not significant to trigger the failure. Detail geotechnical investigations were carried out including the geological survey, seismic refraction survey, bore holes drilling and various laboratory testing. The rock found at site was Phyllitic and Quartzitic sandstone. It appears that the engineering properties of Phyllitic sandstone are more susceptible for slope failure. Rock and soil slope stability analysis have been done, however none of them was found to be the cause of failure. After carefully reexamining the geologic structure, it was found that there is a weak plane layer that resulted in the failure. A suitable stabilization method has been selected as the economical remedy of the slope failure. In this case, flattening the back slope is the economic method along with the drainage system specially designed to reduce the pore water pressure of the weak plane layer. Rock bolts and rock anchors were found to be uneconomical and unsuitable. Probabilistic approach was used to optimize the engineering safety and construction cost.

THE COMPARATIVE ANALYSIS OF THE RESULTS OF REAL AND NUMERICAL EXPERIMENTS FOR DEFINING THE ULTIMATE BEARING CAPACITY OF LIGHT GAUGE STEEL STUDS “ATLANT”

The article in question describes the results of comparison of numerical and real experiments, presented in the report of the Canadian laboratory “Bodycote” [1]. The paper depicts the test fixture, on witch six samples (two typical sizes) of light gauge steel stud “ATLANT” were tested. As a result, dependencies between bearing capacity and characteristic displacements were received. In order to repeat the experiment, the series of computer models were created with the software ANSYS. The computer models have complex nature: geometrical / physical nonlinearity was used. For accounting steel material nonlinearity, we used a multilinear model with isotropic hardening (MISO). The proper diagram was used for each typical size in accordance with the experiments on the tensile-testing machine. For the purpose of supporting condition and load modeling which are identical to the full-scale experiment, a couple of contact elements were used. The utilization of contact elements allowed us to consider friction between the sample and the supporting structures. One of the disadvantages of the full-scale experiment is the absence of measurements of the initial geometrical imperfections. For their consideration the use of probabilistic approach is suggested. This approach entails calculation of several models with different spread of initial imperfections. The initial geometrical imperfections with stochastic nature were included in the computing model. Parameters of distribution were based on the measurements of eighty-eight C-shaped members [8]. In the result of comparison, fine precision in terms of the ultimate bearing capacity and deformation pattern were established. According to expectation, the results of the full-scale experiments were found inside the fictitious “corridor”, created in accordance with the results of computer modeling.

Simplified reliability analysis of multi hazard risk in gravity dams via machine learning techniques

Deterministic analysis does not provide a comprehensive model for concrete dam response under multi-hazard risk. Thus, the use of probabilistic approach is usually recommended which is problematic due to high computational demand. This paper presents a simplified reliability analysis framework for gravity dams subjected to flooding, earthquakes, and aging. A group of time-variant degradation models are proposed for different random variables. Response of the dam is presented by explicit limit state functions. The probability of failure is directly computed by either classical Monte Carlo simulation or the refined importance sampling technique. Next, three machine learning techniques (i.e., K-nearest neighbor, support vector machine, and naive Bayes classifier) are adopted for binary classification of the structural results. These methods are then demonstrated in terms of accuracy, applicability and computational time for prediction of the failure probability. Results are then generalized for different dam classes (based on the height-to-width ratio), various water levels, earthquake intensity, degradation rate, and cross-correlation between the random variables. Finally, a sigmoid-type function is proposed for analytical calculation of the failure probability for different classes of gravity dams. This function is then specialized for the hydrological hazard and the failure surface is presented as a direct function of the dam's height and width.

Methodological Provision of Active Management of Economic Risk in Agrarian Business

1. Introduction An integral feature of business activities is economic risk. Risk management, besides following general regularities, possesses sectorial peculiarities. Thus, for agrarian business, specifics consists in direct influence of natural factor on its efficiency. Use of probabilistic approach to evaluation of risk situations is complicated by information deficit and lack of frequency of external and internal conditions in agriculture. Due to that, receipt and effective use of accessible and reliable information plays an important role in risk management. That's why one of the main directions of formation and development of the system of risk management in the sphere of agrarian business is development of the complex of scientific and methodological provisions of its informational and analytical component, which nowadays does not conform to conditions of modern business activities. That's why the main purpose of this research is to build an algorithm of active management of aggregate economic risk in agrarian business, aimed for reduction of probability of negative result of business risk situations by means of substantiated actions for timely adaptation to changing economic conditions, which determined its actuality. 2. Research methods The object of the research--agrarian business structures of Stavropol Krai. The topic of the research is economic risk and its management in the sphere of agrarian business. Theoretical and empirical foundation of the research includes works of Russian and foreign scientists. The sources of information include regulatory acts of the Ministry of Agriculture of Stavropol Krai, statistical and analytical materials of the Federal State Statistics Service, territorial body of the Federal State Statistics Service in Stavropol Krai, Internet resources, and personal observations of the authors. At various stages of the research, comparative, analytical, and statistical methods of risk analysis were used, as well as methods of economic & mathematical modeling on the basis of use of modern computer technologies. For approbation of the offered methodology, financial & economic documentation of agribusiness enterprises and rural municipal entities was used. 3. Research results Risk management can be characterized as totality of methods, means, and measures which allow--with certain probability--forecasting risk events and taking measures for exclusion or reduction of negative consequences of such events and for increase of probability of positive results of risk situations. It should be noted that risk, as inseparable element of economic process, and specifics of measures for influencing it led to risk management being viewed as a separate type of professional activities. The main tasks of businessmen who successfully manage risks are: determination of high risk spheres; evaluation of level of risk; analysis of acceptability of this level of risk for organization (entrepreneur); development--if necessary--measures for prevention or reduction of risk; when risk even has already taken place--taking measures for maximum possible compensation of damage. Specific methods and means which are used during decision making and their implementation under risk conditions substantially depend on specifics of business activities, adopted strategy for achievement of set goals, specific situation, etc. Only with acceptable correlation of feedback and possible losses, entrepreneur should make a decision as to implementation of a risky project. It should be noted that in each specific case, acceptability of the above correlation can be different and depends on many factors--goals and tasks of the project; policy, strategy, and tactics of entrepreneur in the sphere of risk and its property state (Ermasova N.B., 2009). This principle also supposes comparison of the value of possible reduction of losses as a result of the taken measures, aimed at reduction of the level of risk or at transfer of risk to another person, with additional expenses for implementation of these measures. …

Multimedia & PBPK modelling with MERLIN-Expo versus biomonitoring for assessing Pb exposure of pre-school children in a residential setting

This paper reports on a case study – conducted within the European FP7 project “4FUN” – focusing on exposure of pre-school children to lead resulting from past emissions by non-ferrous smelters in Belgium (Northern Campine area). Exposure scenarios were constructed and simulated with the MERLIN-Expo tool to estimate external Pb exposure as well as the Pb body burden in children living in the vicinity of the former industrial sites as compared to children living in adjacent areas and a reference area.Simulations were run for several scenarios ranging from very simple to rather complex in order to study the effect of different simulation approaches (e.g., deterministic vs. probabilistic, individual vs. aggregated population exposure) and different exposure scenarios (e.g., with vs. without considering local food consumption or time activity patterns) on the model outcomes (predicted concentrations of Pb in environmental and human matrices). This paper discusses the two most complex scenarios, namely exposure at the aggregated population level and at the individual level for a random sub-sample of subjects, respectively.In the final and most realistic exposure scenario, simulating individual lead exposure, model predictions were shown to be higher than the biomonitoring data. Blood Pb levels in children, irrespective of the area they lived in, were overpredicted by MERLIN-Expo with a factor of about 2 on average. The model predictions for individual children overlap with the prediction interval calculated by MERLIN-Expo based on population averages, demonstrating the use of probabilistic approaches in risk assessment. While these results constitute a first verification of the model performance of MERLIN-Expo dealing with inorganic pollutants in a complex real-world exposure scenario and a demonstration of the robustness of the modelling tool, further validation and benchmarking efforts are required for a larger number of inorganic pollutants and different exposure settings.

Fish consumption as a driver of risk-management decisions and human health-based water quality criteria.

The use and interpretation of fish consumption surveys and interviews, the application of fish consumption rates for sediment evaluation and cleanup, and the development of human health water quality criteria (HH WQC) are complex and interrelated issues. The present article focuses on these issues using examples from the United States, although the issues may be relevant for other countries. Some key considerations include the fact that there are many types of fish consumption surveys (e.g., 24-h recall surveys, food frequency questionnaires, creel surveys), and these surveys have different advantages and limitations. Identification of target populations for protection, identification of the species and quantities of fish consumed, and determination of bioaccumulation assumptions are important factors when developing water quality and sediment screening levels and standards. Accounting for the cultural importance of fish consumption for some populations is an even more complex element. Discussions about HH WQC often focus only on the fish consumption rate and may not have broad public input. Some states are trying to change this through extensive public participation efforts and use of probabilistic approaches to derive HH WQC. Finally, there are limits to what WQC can achieve. Solutions beyond the establishment of WQC that target toxics reduction from other sources may provide the greatest improvements to water quality and reductions in human health risks in the future.

METHODOLOGY OF ESTIMATING OF LIMNOLOGICAL CHARACTERISTICS SPATIAL DISTRIBUTIONS ABNORMALITY ON THE EXAMPLE OF LAKE LADOGA SURFACE WATER TEMPERATURE FIELDS

Use of probabilistic approach for estimating of synoptic-scale abnormality is shown. Anomalous deviations of real in situ Lake Ladoga surface temperatures from typical ones were estimated with the data obtained during 43 expeditions 1960 – 2003. These deviations were mapped and statistically analyzed. A degree of spatiotemporal abnormality of real temperature fields, its features and heterogeneous character were revealed. The scales of thermal inhomogeneity are obtained from computation of two-dimensional spatial autocorrelation functions within the random function network. Ways of analysis of characteristics of anomalies fields’ correlation ellipses are given. Applicability of the methodology and the results is suggested.

Probabilistic Modeling of Rainwater Tanks

The use of rainwater tanks is always more encouraged, to achieve a dual objective: water saving from water distribution systems and reduction of runoff discharged into drainage systems. In last decades, different approaches have been proposed for their modeling, most of which are empirical or based on continuous mass balance simulations. To combine the simplicity of practical approaches and the accuracy of continuous simulations some authors have proposed the use of probabilistic approaches; their applications, in literature, still have some limitations. This paper seeks to improve the modelling of rainwater tanks by mean of an analytical probabilistic approach.

A genetic algorithm approach for assessing soil liquefaction potential based on reliability method

Deterministic approaches are unable to account for the variations in soil’s strength properties, earthquake loads, as well as source of errors in evaluations of liquefaction potential in sandy soils which make them questionable against other reliability concepts. Furthermore, deterministic approaches are incapable of precisely relating the probability of liquefaction and the factor of safety (FS). Therefore, the use of probabilistic approaches and especially, reliability analysis is considered since a complementary solution is needed to reach better engineering decisions. In this study, Advanced First-Order Second-Moment (AFOSM) technique associated with genetic algorithm (GA) and its corresponding sophisticated optimization techniques have been used to calculate the reliability index and the probability of liquefaction. The use of GA provides a reliable mechanism suitable for computer programming and fast convergence. A new relation is developed here, by which the liquefaction potential can be directly calculated based on the estimated probability of liquefaction (P L ), cyclic stress ratio (CSR) and normalized standard penetration test (SPT) blow counts while containing a mean error of less than 10% from the observational data. The validity of the proposed concept is examined through comparison of the results obtained by the new relation and those predicted by other investigators. A further advantage of the proposed relation is that it relates P L and FS and hence it provides possibility of decision making based on the liquefaction risk and the use of deterministic approaches. This could be beneficial to geotechnical engineers who use the common methods of FS for evaluation of liquefaction. As an application, the city of Babolsar which is located on the southern coasts of Caspian Sea is investigated for liquefaction potential. The investigation is based primarily on in situ tests in which the results of SPT are analysed.

Towards probabilistic performance metrics for climate change impact studies

This paper explores the current state-of-the-art in performance indicators and use of probabilistic approaches used in climate change impact studies. It presents a critical review of recent publications in this field, focussing on (1) metrics for energy use for heating and cooling, emissions, overheating and high-level performance aspects, and (2) uptake of uncertainty and risk analysis. This is followed by a case study, which is used to explore some of the contextual issues around the broader uptake of climate change impact studies in practice. The work concludes that probabilistic predictions of the impact of climate change are feasible, but only based on strict and explicitly stated assumptions.

A stakeholder probability-based optimization approach for cost-effective bridge management under financial constraints

Management of bridges under uncertainty is an important issue for stakeholders. The use of probabilistic approaches enables one to consider uncertainties in the structural deterioration, assessment, and maintenance processes. Combined with optimization techniques, it is possible to determine management strategies that simultaneously minimize failure, assessment, maintenance, and rehabilitation costs. Nevertheless, there is a strong need in developing practical and efficient frameworks that enable stakeholders to optimize future allocation of budgets for facilities under uncertain structural parameters. In particular, providing an approach that is in agreement with stakeholders constraints still remains a challenge. Moreover, the use of structural health monitoring (SHM) in future management frameworks, to update structural performance, still needs further development. The objective of this paper is threefold: (a) provide management strategies in agreement with fixed budgets, (b) provide management strategies that consider the time delay between the assessment and the intervention schedule, and (c) include information provided by SHM in the decision process and analyze the impact of monitoring strategies on the structural analysis accuracy. An event tree based approach is proposed to consider various uncertainties in the decision process. Optimal solutions are associated with multiple criteria such as minimum expected failure cost, minimum expected inspection/SHM/maintenance costs, maximum agreement of expected inspection/SHM/maintenance costs to available budgets, and maximum accuracy of monitoring results. The approach is illustrated on an existing highway bridge.

Feasibility Study on the Use of Probabilistic Migration Modeling in Support of Exposure Assessment from Food Contact Materials

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.

Probabilistic impedance of foundation: Impact of the seismic design on uncertain soils

AbstractIn the linear seismic design of buildings, the (deterministic) substructure method is a customary and efficient approach. However, the existence of spatial variability in the parameters of the mechanical model of the soil, as well as parametric errors, calls for the use of probabilistic approaches in order to provide a reliable design of the structure. The construction of probabilistic models of the soil impedance matrix provides a natural path to such approaches within the context of the substructure method. Two main techniques are described in this paper: a parametric one, typically using the stochastic finite element method, and a nonparametric one, which was introduced more recently. The latter is explored more specifically, and the possibilities it offers in terms of seismic design are presented. In particular, it is shown that it allows for the estimation of quantiles of the quantities of interest, rather than confidence intervals, which lead to highly conservative design. Copyright © 2008 John Wiley & Sons, Ltd.

Bridge owner's benefits from probabilistic approaches

The growth of national economies in the latter half of the twentieth century has resulted in steadily increasing traffic volumes on trading routes and in an increase in the demands placed on an ageing bridge stock. Ironically, economic growth has not resulted in an increase in the budgets available to bridge owners for maintenance of their ageing resource. The approach adopted by the Danish Road Directorate in addressing this challenge has been to exploit advances in scientific methods in the management of its bridges. The use of probabilistic approaches within the areas of capacity assessment of bridges, bridge management and ship impact assessments have resulted in substantial cost savings, and future maintenance and repair needs have been minimized. Examples of the various areas where the probabilistic approaches have been applied are given, and both the technical approach and the administrative and financial benefits are presented.

Spiritual Involvement as a Predictor to Completing a Salvation Army Substance Abuse Treatment Program

This study investigates successful completion at a faith-based organization providing residential substance abuse treatment services. Method: The authors apply a complex systems paradigm using a single moderator variable. The participants are primarily African Americans and most have current criminal justice involvement. Probabilities of treatment program completion for participants active in spiritual activities versus similar participants not involved in these activities are calculated. Results: Participation in the spirituality component appears to provide a valuable attractor to treatment completion. Conclusions: In the past decade, evaluation methods have included the greater use of probabilistic approaches, most notably Bayesian inference. Findings suggest that this model, as applied to the complexities of a faith-based organization, is useful for understanding treatment completion.