Optimization of the design of the pig launcher-receiver chambers of cleaning and diagnostic tools

По результатам проведенного анализа конструктивных решений камер пуска-приема средств очистки и диагностики (КПП СОД), применяемых при технической диагностике и техническом обслуживании магистральных трубопроводов в России и за рубежом, был установлен ряд проблем существующих конструкций, снижающих эксплуатационную надежность данного вида оборудования. Это, в свою очередь, обусловило актуальность задачи оптимизации конструкции КПП СОД, в том числе в части унификации используемых при их изготовлении деталей, увеличения доли заводских изделий. Были приняты решения, обеспечившие комплексный подход к вопросу повышения надежности и ремонтопригодности оборудования - разработана новая конструкция КПП СОД, позволяющая снизить металлоемкость и трудоемкость при изготовлении, сократить эксплуатационные затраты, повысить технологичность и прочностные характеристики. В рамках решения данной задачи выполнены расчетно-теоретические исследования с применением прикладного программного комплекса SIMULIA Abaqus. Надежность оптимизированной конструкции подтверждена результатами испытаний на прочность опытного образца КПП СОД с номинальным диаметром рабочей камеры DN 1000. Разработан типоразмерный ряд КПП СОД усовершенствованной конструкции с номинальными диаметрами рабочей камеры DN 150-1200 для применения на магистральных нефте- и нефтепродуктопроводах. Based on the results of the analysis of the design solutions of launching and receiver stations of pipeline inspection gauges (pig launchers-receivers) used in process diagnostics and maintenance of main pipelines in Russia and abroad, a number of applied design issues was established. This, in turn, led to the relevance of the issue of optimizing the design of pig launchers and receivers, including the unification of parts used in their manufacture, thereby increasing the share of factory-made products. Decisions were made that provided a comprehensive approach to the issue of improving the operational reliability of this type of equipment - a new design of pig launchers and receivers was developed, which allows to reduce production metal consumption and labor intensity, reduce operating costs, increase constructability and reliability. As part of the solution of this issue, computational and theoretical studies using the SIMULIA Abacus software package were carried out. The reliability of the optimized design is confirmed by the results of durability tests of the pig launcher and receiver prototype with the nominal diameter of the working chamber of DN 1000. A dimension range of advanced designs of pig launchers and receivers with nominal working chamber diameters of DN 150-1200 for use in main oil and petroleum product pipelines was developed.

Robust Multiple Regression

As modern data analysis pushes the boundaries of classical statistics, it is timely to reexamine alternate approaches to dealing with outliers in multiple regression. As sample sizes and the number of predictors increase, interactive methodology becomes less effective. Likewise, with limited understanding of the underlying contamination process, diagnostics are likely to fail as well. In this article, we advocate for a non-likelihood procedure that attempts to quantify the fraction of bad data as a part of the estimation step. These ideas also allow for the selection of important predictors under some assumptions. As there are many robust algorithms available, running several and looking for interesting differences is a sensible strategy for understanding the nature of the outliers.

A Review on Fault Detection and Process Diagnostics in Industrial Processes

The main roles of fault detection and diagnosis (FDD) for industrial processes are to make an effective indicator which can identify faulty status of a process and then to take a proper action against a future failure or unfavorable accidents. In order to enhance many process performances (e.g., quality and throughput), FDD has attracted great attention from various industrial sectors. Many traditional FDD techniques have been developed for checking the existence of a trend or pattern in the process or whether a certain process variable behaves normally or not. However, they might fail to produce several hidden characteristics of the process or fail to discover the faults in processes due to underlying process dynamics. In this paper, we present current research and developments of FDD approaches for process monitoring as well as a broad literature review of many useful FDD approaches.

Assessing the Word Recognition Skills of German Elementary Students in Silent Reading—Psychometric Properties of an Item Pool to Generate Curriculum-Based Measurements

Given the high proportion of struggling readers in school and the long-term negative consequences of underachievement for those affected, the question of prevention options arises. The early identification of central indicators for reading literacy is a noteworthy starting point. In this context, curriculum-based measurements have established themselves as reliable and valid instruments for monitoring the progress of learning processes. This article is dedicated to the assessment of word recognition in silent reading as an indicator of adequate reading fluency. The process of developing an item pool is described, from which instruments for learning process diagnostics can be derived. A sample of 4268 students from grades 1–4 processed a subset of items. Each student template included anchor items, which all students processed. Using Item Response Theory, item statistics were estimated for the entire sample and all items. After eliminating unsuitable items (N = 206), a one-dimensional, homogeneous pool of items remained. In addition, there are high correlations with another established reading test. This provides the first evidence that the recording of word recognition skills for silent reading can be seen as an economic indicator for reading skills. Although the item pool forms an important basis for the extraction of curriculum-based measurements, further investigations to assess the diagnostic suitability (e.g., the measurement invariance over different test times) are still pending.

DIAGNOSTIC OF THE COMBUSTION PROCESS USING THE ANALYSIS OF CHANGES IN FLAME LUMINOSITY

Monitoring of the combustion process is carried out in order to ensure its efficiency and stability. Selected aspects of the combustion process diagnostics using the analysis of changes in flame luminosity for two configurations: 100% pulverized coal fuel and a mixture of 80% coal and 20% biomass were presented in the article. The analysis of measurement data was conducted using selected statistical tools and a multiresolution analysis of signals.

Incorporation of inline warm-rain diagnostics into the COSP2 satellite simulator for process-oriented model evaluation

Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) has been widely used to diagnose model performance and physical processes via an apple-to-apple comparison to satellite measurements. Although the COSP provides useful information about clouds and their climatic impact, outputs that have a subcolumn dimension require large amounts of data. This can cause a bottleneck when conducting sets of sensitivity experiments or multiple model intercomparisons. Here, we incorporate two diagnostics for warm-rain microphysical processes into COSP2, the latest version of the simulator. The approach used here employs existing diagnostic methodologies that probe how the warm-rain processes occur using statistics constructed from simulators of multiple satellite instruments along with their subcolumn information. The new diagnostics are designed to produce statistics online during the COSP execution, eliminating the need to output subcolumn variables. Users can also readily conduct regional analysis tailored to their particular research interest (e.g., land–ocean differences), using an auxiliary post-process package after the COSP calculation. This inline tool also generates global maps of the occurrence frequency of warm-rain regimes (i.e., non-precipitating, drizzling, and precipitating) classified according to CloudSat radar reflectivity, putting the warm-rain process diagnostics into the context of geographical distributions of precipitation. The inline diagnostics are applied to the MIROC6 GCM to demonstrate how known biases common among multiple GCMs relative to satellite observations are revealed. The inline multisensor diagnostics are intended to serve as a tool that facilitates process-oriented model evaluations in a manner that reduces the burden on modelers for their diagnostics effort.