scholarly journals Probabilistic Prediction of Corrosion Damage of Steel Structures in the Vicinity of Roads

2020 ◽  
Vol 12 (23) ◽  
pp. 9851
Author(s):  
Monika Kubzova ◽  
Vit Krivy ◽  
Katerina Kreislova
Keyword(s):  
Sensitivity Analysis ◽  
Prediction Models ◽  
Steel Structures ◽  
Corrosion Damage ◽  
Accurate Estimate ◽  
Steel Bridge ◽  
Probabilistic Prediction ◽  
Winter Maintenance ◽  
The Impact

The design, construction, and maintenance of steel structures must be carried out in a way that ensures they will be able to reliably operate for the whole duration of their planned service life. To ensure sufficient durability, it is necessary to determine and evaluate the characteristics of the appropriate environment in which the structure will be placed. This submission focuses on the specific environment surrounding roads that are treated with de-icing salts during winter maintenance. It investigates the dependency between corrosive damage to the structure and the relevant parameters of the environment. Basic corrosive factors include temperature, relative humidity, deposition of chlorides and sulfur dioxide, precipitation, the pH of precipitation as well as many other parameters. An accurate estimate of corrosive damage requires an analysis of the long-term trends in concentrations of individual corrosive factors, while respecting their randomly varying attributes. The article, hence, introduces and evaluates stochastic prediction models that are based on long-term programs focusing on the evaluation of the corrosive aggressiveness of the environment, while taking into account random variations of the nature of the input parameters. The use of stochastic prediction models allows us to perform sensitivity analysis that can determine the impact of specific corrosive factors on the corrosive damage caused to the structure. The article is supplemented by sensitivity analysis focusing on an evaluation from the effects of the deposition of chlorides on the corrosive damage to steel bridge structures. The analysis was carried out using data obtained from experimental measurements of the deposition rates of chlorides in the vicinity of roads in the Czech Republic.

Effect on buckling behavior and seismic performance of steel piers corrosion-damaged near ground

2021 ◽  
Author(s):  
Takuma Rokutani ◽  
Kazutoshi Nagata ◽  
Takeshi Kitahara
Keyword(s):  
Seismic Performance ◽  
Rectangular Cross Section ◽  
Steel Structures ◽  
Corrosion Damage ◽  
Bridge Piers ◽  
Response Analysis ◽  
Steel Bridge ◽  
Seismic Response Analysis ◽  
Economic Miracle ◽  
Buckling Behavior

<p>In Japan, many steel structures were constructed during the period of the high economic miracle, and they are now more than 50 years old and are aging. Corrosion has been confirmed at corners and the boundary of concrete-wrapped concrete in steel piers. It was found that corrosion damage at the corner of steel piers causes a decrease of seismic performance in our previous investigations that carried out seismic response analysis. Subsequently, in this study, the effect of corrosion damage at the near ground edge of steel bridge piers with a rectangular cross-section was investigated in detail on the buckling behaviour and seismic performance of structures. As a result, it is found that the buckling at the base causes a decrease in load bearing performance compared to the buckling in the entire panel. It is necessary to properly maintain to prevent buckling at the base caused by corrosion.</p>

scholarly journals Data-based stochastic subgrid-scale parametrization: an approach using cluster-weighted modelling

2012 ◽  
Vol 370 (1962) ◽  
pp. 1061-1086 ◽  
Author(s):  
Frank Kwasniok
Keyword(s):  
Clustering Algorithm ◽  
Prediction Models ◽  
Statistical Modelling ◽  
Scale Model ◽  
Ensemble Prediction ◽  
Subgrid Scale ◽  
New Approach ◽  
Lorenz 96 ◽  
The Impact

A new approach for data-based stochastic parametrization of unresolved scales and processes in numerical weather and climate prediction models is introduced. The subgrid-scale model is conditional on the state of the resolved scales, consisting of a collection of local models. A clustering algorithm in the space of the resolved variables is combined with statistical modelling of the impact of the unresolved variables. The clusters and the parameters of the associated subgrid models are estimated simultaneously from data. The method is implemented and explored in the framework of the Lorenz '96 model using discrete Markov processes as local statistical models. Performance of the cluster-weighted Markov chain scheme is investigated for long-term simulations as well as ensemble prediction. It clearly outperforms simple parametrization schemes and compares favourably with another recently proposed subgrid modelling scheme also based on conditional Markov chains.

scholarly journals Dynamics of the COVID-19 pandemic in India

2020 ◽  
Author(s):  
Subhas Khajanchi ◽  
Kankan Sarkar ◽  
Jayanta Mondal ◽  
Matjaz Perc
Keyword(s):  
Sensitivity Analysis ◽  
West Bengal ◽  
Seasonal Occurrence ◽  
Contact Tracing ◽  
Short Term ◽  
Social Distancing ◽  
Oscillatory Dynamics ◽  
The Impact ◽  
Worrying Trend

Abstract Understanding the dynamics of the COVID-19 pandemic is crucial for improved control and social distancing strategies. To that effect, we have employed the susceptible-exposed-infectious-recovered model, refined by contact tracing and hospitalization data from Indian provinces Kerala, Delhi, Maharashtra, and West Bengal, as well as from overall India. We have performed a sensitivity analysis to identify the most crucial input parameters, and we have calibrated the model to describe the data as best as possible. Short-term predictions reveal an increasing and worrying trend of COVID-19 cases for all four provinces and India as a whole, while long-term predictions also reveal the possibility of oscillatory dynamics. Our research thus leaves the option open that COVID-19 might become a seasonal occurrence. We also simulate and discuss the impact of media on the dynamics of the COVID-19 pandemic.

scholarly journals Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0

2020 ◽  
Vol 13 (12) ◽  
pp. 5973-6009
Author(s):  
Virginie Moreaux ◽  
Simon Martel ◽  
Alexandre Bosc ◽  
Delphine Picart ◽  
David Achat ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Soil Carbon ◽  
Biogeochemical Processes ◽  
Forest Operations ◽  
Time Step ◽  
Vegetation Control ◽  
Clear Cutting ◽  
Go Model ◽  
The Impact

Abstract. The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon submodel is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time step. It represents a forest stand covering typically 1 ha and can be straightforwardly upscaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close to nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables.The sensitivity analysis demonstrates an interaction between the sensitivity of variables, with the climate and soil hydraulic properties being dominant under dry conditions but the leaf biochemical properties being most influential with wet soil. The sensitivity profile of the model changes from short to long timescales due to the cumulative effects of the fluxes of carbon, energy and water on the stand growth and canopy structure. Apart from a few specific cases, the model simulations are close to the values of the observations of atmospheric exchanges, tree growth, and soil carbon and water stock changes monitored over Douglas fir, European beech and pine forests of different ages. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

scholarly journals Stakeholders and Long-Term Sustainability of SMEs. Who Really Matters in Crisis Contexts, and When

2019 ◽  
Vol 11 (23) ◽  
pp. 6551 ◽  
Author(s):  
Manzaneque-Lizano ◽  
Alfaro-Cortés ◽  
de la Priego Cruz
Keyword(s):  
Financial Distress ◽  
Conceptual Models ◽  
Prediction Models ◽  
Classification Tree ◽  
Failure Process ◽  
Business Failure ◽  
Crisis Events ◽  
The Impact

The impact of crises on the long-term sustainability of small and medium-sized enterprises (SMEs) has been attracting growing interest in the literature and from governments due to the significance of such companies with respect to economic growth, innovation, and employment. Although failure prediction models have been proposed based on accounting and other qualitative information, little is known regarding the influence of stakeholders on the failure process of SMEs. From the perspective of long-term sustainability, this article analyzes the role of the financial influence of stakeholders on the likelihood of business failure. An empirical study was carried out on a sample of 2352 Spanish SMEs, examining the differences between failed and non-failed SMEs and using a classification tree methodology to investigate the role played by each type of stakeholder in overcoming crisis events. The study provides empirical evidence regarding the relative importance of stakeholders to SMEs under conditions of financial distress, and proposes their categorization on the basis of their control over firms’ financial resources. Specifically, the analysis reveals that the capacity of the firm to generate sustainable wealth over time and to overcome critical situations is dependent on the most critical stakeholders. Workers, customers, and suppliers are the most important in ensuring the long-term sustainability of SMEs during the first stages of a crisis. Following the initial operational problems, other creditors (financial institutions) become relevant. In this sense, the results of this study encourage firms and governments to develop cooperation strategies with stakeholders (co-responsibility) in line with the proposed conceptual models of business sustainability.

scholarly journals Monitoring of The Impact of Road Salting On Spruce Forest Ecosystem In The Vicinity of The Highway D1 In The Bohemian-Moravian Highlands, Czech Republic

2021 ◽  
Author(s):  
Jitka Hegrová ◽  
Lubomír Prokeš ◽  
Petr Anděl ◽  
Martina Bucková ◽  
Vilma Jandová ◽  
...  
Keyword(s):  
Czech Republic ◽  
Sodium Concentration ◽  
Road Maintenance ◽  
Winter Maintenance ◽  
The Road ◽  
Close Proximity ◽  
Winter Road ◽  
The Impact ◽  
Winter Road Maintenance

Abstract Monitoring of pollution in the vicinity of roads connected to winter road maintenance is one of the important tools for optimising winter maintenance technology and reducing its environmental impact. The aim of this study was to determine the relationship between winter road maintenance and the increased concentration of sodium ion to characterize the harm caused by the de-icing agents on selected types of individual components grown in the Norway Spruce ecosystem. The model area is located in the immediate vicinity of the D1 motorway connecting Prague and Brno (Czech Republic), at 103rd kilometer. The area is thus exposed to long-term contamination from automobile transport and the monitoring was carried out for three consecutive years. A clear effect of the de-icing agents on conifers near the road has been demonstrated by the symptoms of salt damage visually observed in close proximity to the road (at a sampling distance of 5 m). The needles of these spruce trees also showed increased sodium concentrations, regardless of the age of the needles. The study also confirms that sodium accumulates in all selected components of the analysed ecosystem (moos, humus, soil). The sodium concentration has been found to decrease with increasing distance from the road for all of the components.

Suppressed, but Not Forgotten

2011 ◽  
Vol 70 (1) ◽  
pp. 5-11 ◽  
Author(s):  
Beat Meier ◽  
Anja König ◽  
Samuel Parak ◽  
Katharina Henke
Keyword(s):  
Memory Trace ◽  
Thought Suppression ◽  
Test Phase ◽  
Indirect Test ◽  
Final Test ◽  
Test Experiment ◽  
And Control ◽  
Cue Words ◽  
The Impact

This study investigates the impact of thought suppression over a 1-week interval. In two experiments with 80 university students each, we used the think/no-think paradigm in which participants initially learn a list of word pairs (cue-target associations). Then they were presented with some of the cue words again and should either respond with the target word or avoid thinking about it. In the final test phase, their memory for the initially learned cue-target pairs was tested. In Experiment 1, type of memory test was manipulated (i.e., direct vs. indirect). In Experiment 2, type of no-think instructions was manipulated (i.e., suppress vs. substitute). Overall, our results showed poorer memory for no-think and control items compared to think items across all experiments and conditions. Critically, however, more no-think than control items were remembered after the 1-week interval in the direct, but not in the indirect test (Experiment 1) and with thought suppression, but not thought substitution instructions (Experiment 2). We suggest that during thought suppression a brief reactivation of the learned association may lead to reconsolidation of the memory trace and hence to better retrieval of suppressed than control items in the long term.

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