Survival analysis at multiple scales for the modeling of track geometry deterioration

Author(s):  
Negin Alemazkoor ◽  
Conrad J Ruppert ◽  
Hadi Meidani

Defects in track geometry have a notable impact on the safety of rail transportation. In order to make the optimal maintenance decisions to ensure the safety and efficiency of railroads, it is necessary to analyze the track geometry defects and develop reliable defect deterioration models. In general, standard deterioration models are typically developed for a segment of track. As a result, these coarse-scale deterioration models may fail to predict whether the isolated defects in a segment will exceed the safety limits after a given time period or not. In this paper, survival analysis is used to model the probability of exceeding the safety limits of the isolated defects. These fine-scale models are then used to calculate the probability of whether each segment of the track will require maintenance after a given time period. The model validation results show that the prediction quality of the coarse-scale segment-based models can be improved by exploiting information from the fine-scale defect-based deterioration models.

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259716
Author(s):  
Jordan DiNardo ◽  
Kevin L. Stierhoff ◽  
Brice X. Semmens

White abalone (Haliotis sorenseni) was once commonly found in coastal waters of the Southern California Bight (SCB) and south to Punta Abreojos, Baja California, Mexico. During the 1970s, white abalone supported a commercial fishery, which reduced the population and resulted in the closure of the fishery in 1996. When population levels continued to decline, National Marine Fisheries Service (NMFS) listed the species as endangered under the Endangered Species Act. The California Department of Fish and Wildlife and NMFS began surveying the wild populations, propagating specimens in captivity, and protecting its seabed habitat. We modeled coarse-scale (17 x 17 km) historical (using fishery-dependent data [1955–1996]) and contemporary (using fishery-independent data [1996–2017]) distributions of white abalone throughout its historical domain using random forests and maximum entropy (MaxEnt), respectively, and its fine-scale (10 x 10 m) contemporary distribution (fishery-independent data) using MaxEnt. We also investigated potential outplanting habitat farther north under two scenarios of future climate conditions. The coarse-scale models identified potential regions to focus outplanting efforts within SCB while fine-scale models can inform population monitoring and outplanting activities in these particular areas. These models predict that areas north of Point Conception may become candidate outplant sites as seawater temperatures continue to rise in the future due to climate change. Collectively, these results provide guidance on the design and potential locations for experimental outplanting at such locations to ultimately improve methods and success of recovery efforts.


2016 ◽  
Vol 879 ◽  
pp. 1207-1212 ◽  
Author(s):  
Piotr Macioł ◽  
Danuta Szeliga ◽  
Łukasz Sztangret

A typical multiscale simulation consists of numerous fine scale models, usually one for each computational point of a coarse scale model. One of possible ways of limiting computing power requirements is replacing fine scale models with some simplified and speeded up ersatz ones. In this paper, the authors attempt to develop a metamodel, replacing direct thermodynamic computations of precipitation kinetic with an advanced approximating model. MatCalc simulator has been used for thermodynamic modelling of precipitation kinetic. Typical heat treatment of P91 steel grade was examined. Selected variables were chosen to be modelled with approximating models. Several attempts with various approximation variants (interpolation algorithms and Artificial Neural Networks) have been investigated and its comparison is included in the paper.


SPE Journal ◽  
2016 ◽  
Vol 21 (06) ◽  
pp. 2112-2127 ◽  
Author(s):  
Faruk O. Alpak ◽  
Jeroen C. Vink

Summary Numerical modeling of the in-situ conversion process (ICP) is a challenging endeavor involving thermal multiphase flow, compositional pressure/volume/temperature (PVT) behavior, and chemical reactions that convert solid kerogen into light hydrocarbons and are tightly coupled to temperature propagation. Our investigations of grid-resolution effects on the accuracy and performance of ICP simulations demonstrated that ICP-simulation outcomes (e.g., oil/gas production rates and cumulative volumes) may exhibit relatively large errors on coarse grids, where “coarse” means a gridblock size of more than 3 to 5 m. On the other hand, coarse-scale models are attractive because they deliver favorable computational performance, especially for optimization and uncertainty quantification workflows that demand a large number of simulations. Furthermore, field-scale models become unmanageably large if gridblock sizes of 3 to 5 m or less have to be used. Therefore, there is a clear business need to accelerate the ICP simulations with minimal compromise of accuracy. We developed a novel multiscale-modeling method for ICP that reduces numerical-modeling errors and approximates the fine-scale simulation results on relatively coarse grids. The method uses a two-scale adaptive local-global solution technique. One global coarse-scale and multiple local fine-scale near-heater models are timestepped in a sequentially coupled fashion. At a given global timestep, the global-model solution provides accurate boundary conditions to the local near-heater models. These boundary conditions account for the global characteristics of the thermal-reactive flow and transport phenomena. In turn, fine-scale information about heater responses is upscaled from the local models, and used in the global coarse-scale model. These flow-based effective properties correct the thermal-reactive flow and transport in the global model either explicitly, by updating relevant coarse-grid properties for the next timestep, or implicitly, by repeatedly updating the properties through a convergent iterative scheme. Upon convergence, global coarse-scale and local fine-scale solutions are compatible with each other. We demonstrate the much-improved accuracy and efficiency delivered by the multiscale method by use of a 2D cross-section pattern-scale ICP simulation problem. The following conclusions are reached through numerical testing: (1) The multiscale method significantly improves the accuracy of the simulation results over conventionally upscaled models. The method is particularly effective in correcting the global coarse-scale model through the use of the fine-scale information about heater temperatures to regulate the heat-injection rate into the formation more accurately. The effective coarse-grid properties computed by the multiscale method at every timestep also enhance the accuracy of the ICP simulations, as demonstrated in a dedicated test case, in which a constant heat-injection rate is enforced across models of all investigated resolutions. (2) Multiscale ICP models result in accelerated simulations with a speed-up of four to 16 times with respect to fine-scale models “out of the box” without any special optimization effort. (3) Our multiscale method delivers high-resolution solutions in the vicinity of the heaters at a reduced computational cost. These fine-scale solutions can be used to better understand the evolution of the fluids and solids (e.g., kerogen conversion and coke deposition) in the vicinity of the heaters (several-feet-long spatial scale). Simultaneously, with the fine-scale near-heater solutions, the local-global coupled multiscale model provides key commercial ICP performance indicators at the pattern scale (several-hundred-feet-long spatial scale) such as production functions.


2006 ◽  
Vol 14 (02) ◽  
pp. 219-229 ◽  
Author(s):  
IVAN IVANOV ◽  
EDWARD R. DOUGHERTY

Selecting an appropriate mathematical model to describe the dynamical behavior of a genetic regulatory network plays an important part in discovering gene regulatory mechanisms. Whereas fine-scale models can in principle provide a very accurate description of the real genetic regulatory system, one must be aware of the availability and quality of the data used to infer such models. Consequently, pragmatic considerations motivate the selection of a model possessing minimal complexity among those capable of capturing the level of real gene regulation being studied, particularly in relation to the prediction capability of the model. This paper compares fine-scale stochastic-differential-equation models with coarse-scale discrete models in the context of currently available data and with respect to their description of switch-like behavior among specific groups of genes.


2021 ◽  
Vol 13 (5) ◽  
pp. 2664
Author(s):  
Yingnan Yang ◽  
Hongming Xie

In the commonly used approach to maintenance scheduling for infrastructure facilities, maintenance decisions are made under the assumptions that inspection frequency is periodical and fixed, and that the true state of a facility is revealed through inspections. This research addresses these limitations by proposing a decision-making approach for determining optimal maintenance, repair, and rehabilitation (MR&R) strategy and inspection intervals for infrastructure facilities that can explicitly take into account non-periodical inspections as well as previously considered periodical inspections. Four transition probabilities are proposed to represent four different MR&R strategies. Then, an optimization program is suggested to minimize MR&R and inspection costs of a bridge element network over a given time period, while keeping the condition states of the element network above a predetermined level. A case study was applied to illustrate the proposed approach. The results show that the proposal approach can support decision making in situations where non-periodical inspections and MR&R actions are incorporated into the model development. If employed properly, this may allow agencies to maintain their infrastructure more effectively, resulting in cost savings and reducing unnecessary waste of resources.


SPE Journal ◽  
2012 ◽  
Vol 17 (04) ◽  
pp. 1056-1070 ◽  
Author(s):  
Faruk O. Alpak ◽  
Mayur Pal ◽  
Knut-Andreas Lie

Summary A robust and efficient simulation technique is developed on the basis of the extension of the mimetic finite-difference method (MFDM) to multiscale hierarchical-hexahedral (corner-point) grids by use of the multiscale mixed finite-element method (MsMFEM). The implementation of the mimetic subgrid-discretization method is compact and generic for a large class of grids and, thereby, is suitable for discretizations of reservoir models with complex geologic architecture. Flow equations are solved on a coarse grid where basis functions with subgrid resolution account accurately for subscale variations from an underlying fine-scale geomodel. The method relies on the construction of approximate velocity spaces that are adaptive to the local properties of the differential operator. A variant of the method for computing velocity basis functions is developed that uses an adaptive local-global (ALG) algorithm to compute multiscale velocity basis functions by capturing the principal characteristics of global flow. Both local and local-global methods generate subgrid-scale velocity fields that reproduce the impact of fine-scale stratigraphic architecture. By using multiscale basis functions to discretize the flow equations on a coarse grid, one can retain the efficiency of an upscaling method, while at the same time produce detailed and conservative velocity fields on the underlying fine grid. The accuracy and efficacy of the multiscale method is compared with those of fine-scale models and of coarse-scale models with no subgrid treatment for several two-phase-flow scenarios. Numerical experiments involving two-phase incompressible flow and transport phenomena are carried out on high-resolution corner-point grids that represent explicitly example stratigraphic architectures found in real-life shallow-marine and turbidite reservoirs. The multiscale method is several times faster than the direct solution of the fine-scale problem and yields more accurate solutions than coarse-scale modeling techniques that resort to explicit effective properties. The accuracy of the multiscale simulation method with ALG-velocity basis functions is compared with that of the local velocity basis functions. The multiscale simulation results are consistently more accurate when the local-global method is employed for computing the velocity basis functions.


2012 ◽  
Vol 127 (1) ◽  
pp. 15-19 ◽  
Author(s):  
A Mirza ◽  
L McClelland ◽  
M Daniel ◽  
N Jones

AbstractBackground:Many ENT conditions can be treated in the emergency clinic on an ambulatory basis. Our clinic traditionally had been run by foundation year two and specialty trainee doctors (period one). However, with perceived increasing inexperience, a dedicated registrar was assigned to support the clinic (period two). This study compared admission and discharge rates for periods one and two to assess if greater registrar input affected discharge rate; an increase in discharge rate was used as a surrogate marker of efficiency.Method:Data was collected prospectively for patients seen in the ENT emergency clinic between 1 August 2009 and 31 July 2011. Time period one included data from patients seen between 1 August 2009 and 31 July 2010, and time period two included data collected between 1 August 2010 and 31 July 2011.Results:The introduction of greater registrar support increased the number of patients that were discharged, and led to a reduction in the number of children requiring the operating theatre.Conclusion:The findings, which were determined using clinic outcomes as markers of the quality of care, highlighted the benefits of increasing senior input within the ENT emergency clinic.


2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Peng Xu ◽  
Chuanjun Jia ◽  
Ye Li ◽  
Quanxin Sun ◽  
Rengkui Liu

As railroad infrastructure becomes older and older and rail transportation is developing towards higher speed and heavier axle, the risk to safe rail transport and the expenses for railroad maintenance are increasing. The railroad infrastructure deterioration (prediction) model is vital to reducing the risk and the expenses. A short-range track condition prediction method was developed in our previous research on railroad track deterioration analysis. It is intended to provide track maintenance managers with two or three months of track condition in advance to schedule track maintenance activities more smartly. Recent comparison analyses on track geometrical exceptions calculated from track condition measured with track geometry cars and those predicted by the method showed that the method fails to provide reliable condition for some analysis sections. This paper presented the enhancement to the method. One year of track geometry data for the Jiulong-Beijing railroad from track geometry cars was used to conduct error analyses and comparison analyses. Analysis results imply that the enhanced model is robust to make reliable predictions. Our in-process work on applying those predicted conditions for optimal track maintenance scheduling is discussed in brief as well.


2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
No-Wook Park

A geostatistical downscaling scheme is presented and can generate fine scale precipitation information from coarse scale Tropical Rainfall Measuring Mission (TRMM) data by incorporating auxiliary fine scale environmental variables. Within the geostatistical framework, the TRMM precipitation data are first decomposed into trend and residual components. Quantitative relationships between coarse scale TRMM data and environmental variables are then estimated via regression analysis and used to derive trend components at a fine scale. Next, the residual components, which are the differences between the trend components and the original TRMM data, are then downscaled at a target fine scale via area-to-point kriging. The trend and residual components are finally added to generate fine scale precipitation estimates. Stochastic simulation is also applied to the residual components in order to generate multiple alternative realizations and to compute uncertainty measures. From an experiment using a digital elevation model (DEM) and normalized difference vegetation index (NDVI), the geostatistical downscaling scheme generated the downscaling results that reflected detailed characteristics with better predictive performance, when compared with downscaling without the environmental variables. Multiple realizations and uncertainty measures from simulation also provided useful information for interpretations and further environmental modeling.


2008 ◽  
Vol 54 (11) ◽  
pp. 1872-1882 ◽  
Author(s):  
Eva Nagy ◽  
Joseph Watine ◽  
Peter S Bunting ◽  
Rita Onody ◽  
Wytze P Oosterhuis ◽  
...  

Abstract Background: Although the methodological quality of therapeutic guidelines (GLs) has been criticized, little is known regarding the quality of GLs that make diagnostic recommendations. Therefore, we assessed the methodological quality of GLs providing diagnostic recommendations for managing diabetes mellitus (DM) and explored several reasons for differences in quality across these GLs. Methods: After systematic searches of published and electronic resources dated between 1999 and 2007, 26 DM GLs, published in English, were selected and scored for methodological quality using the AGREE Instrument. Subgroup analyses were performed based on the source, scope, length, origin, and date and type of publication of GLs. Using a checklist, we collected laboratory-specific items within GLs thought to be important for interpretation of test results. Results: The 26 diagnostic GLs had significant shortcomings in methodological quality according to the AGREE criteria. GLs from agencies that had clear procedures for GL development, were longer than 50 pages, or were published in electronic databases were of higher quality. Diagnostic GLs contained more preanalytical or analytical information than combined (i.e., diagnostic and therapeutic) recommendations, but the overall quality was not significantly different. The quality of GLs did not show much improvement over the time period investigated. Conclusions: The methodological shortcomings of diagnostic GLs in DM raise questions regarding the validity of recommendations in these documents that may affect their implementation in practice. Our results suggest the need for standardization of GL terminology and for higher-quality, systematically developed recommendations based on explicit guideline development and reporting standards in laboratory medicine.


Sign in / Sign up

Export Citation Format

Share Document