Implementation of probabilistic approach to rock mass strength estimation while excavating through fault zones

Purpose. The paper addresses the rock mass state estimation while excavating a cross-heading through the area of regional fault “Bohdanivskyi” based on probabilistic approach to assessing the rock strength. Methods. The boundaries and fault zone extension are specified based on geological service database. This hazardous fault area has been confirmed, and the expected water inflow and methane emission have been identified based on the probe holes drilled ahead of the advancing face. To assess the strength of rocks, the statistical strength theory is used. Numerical simulation is performed using finite element method that is well-tested in geomechanical problems. Findings. The technique of rock mass strength estimation using structural factor based on statistical strength theory has been implemented to improve the adequacy of mathematical modeling. Numerical simulation of geomechanical processes based on finite element method and Hoek-Brown failure criterion is carried out. The changes of rock stress-strain state while excavating the cross-heading through various sites of the fault zone are determined depending on the level of rock disintegration. Originality. New regularities of rock mass behavior within the fault area are determined based on developed technique of rock strength assessment considering the rock mass disintegration and watering. Practical implications. Estimation of rock failure has resulted in designing the combination of support systems comprising metal sets, rockbolts and shotcrete.Мета. Стаття спрямована на оцінку стану породного масиву при проведенні відкаточного квершлагу через зону великого регіонального геологічного порушення “Богданівський” скид на основі ймовірнісного підходу до оцінки міцності гірських порід. Методика. Межі зони геологічного порушення визначалися із використанням бази даних геологічної служби. Значення очікуваного водотоку та наявність метану визначалися із використанням методу пробного буріння попереду вибою. Для оцінки міцності гірських порід використана статистична теорія міцності. Чисельне моделювання проводилося з використання добре апробованого в задачах геомеханіки методу скінченних елементів. Результати. Методика оцінки міцності масиву гірських порід, що заснована на статистичній теорії міцності, була використана для підвищення адекватності математичного моделювання. Виконано чисельне моделювання геомеханічних процесів на основі методу скінченних елементів і критерію міцності Хока-Брауна. Визначено зміни напружено-деформованого стану порід при проведенні відкаточного квершлагу через різні ділянки зони геологічного порушення в залежності від ступеню дезінтеграції порід. Наукова новизна. Встановлено нові закономірності поведінки породного масиву в зоні геологічного порушення на основі оцінки міцності порід, що враховує ступінь дезінтеграції й обводнення породного масиву. Практична значимість. Адекватна оцінка міцності породного масиву і ступеня його зрушеності дозволила розробити комбіноване кріплення, що включає металеву арку, анкерну систему та шар торкретбетону.Цель. Статья направлена на оценку состояния породного массива при проведении откаточного квершлага через зону крупного регионального геологического нарушения “Богдановский” сброс на основе вероятностного подхода к оценке прочности горных пород. Методика. Границы зоны геологического нарушения определялись с использованием базы данных геологической службы. Значения ожидаемого водопритока и наличие метана определялись с использованием метода пробных бурений, выполняемых впереди забоя выработки. Для оценки прочности горных пород использована статистическая теория прочности. Численное моделирование выполнено с использованием метода конечных элементов, хорошо апробированного в задачах геомеханики. Результаты. Методика оценки прочности массива горных пород, основанная на статистической теории прочности, применена с целью повышения адекватности математического моделирования. Выполнено численное моделирование геомеханических процессов на основе метода конечных элементов и критерия прочности Хока-Брауна. Определены изменения напряженно-деформированного состояния пород при проведении откаточного квершлага через различные участки зоны геологического нарушения в зависимости от степени дезинтеграции пород. Научная новизна. Установлены новые закономерности поведения породного массива в зоне геологического нарушения на основе оценки прочности пород, учитывающей степень дезинтеграции и обводнения породного массива. Практическая значимость. Адекватная оценка прочности породного массива и степени его нарушенности позволила разработать комбинированную крепь, включающую металлическую арку, анкерную систему и слой торкретбетона.This work was supported by PJS Company “DTEK Pavlohradvuhillia”, grants No. 050420/372-PU-SHUTr. The authors would like to thank all technical staff of the mine “Samarska” for the help during the in situ observation

A GPR-GPS-GIS-integrated, information-rich and error-aware system for detecting, locating and characterizing underground utilities

Underground utilities have proliferated throughout the years. The location and dimension of many underground utilities have not always been properly collected and documented, leading to utility conflicts and utility strikes, and thus resulting in property damages, project delays, cost overruns, environment pollutions, injuries and deaths. The underlying reasons are twofold. First, the reliable data regarding the location and dimension of underground utility are missing or incomplete. Existing methods to collect data are not efficient and effective. Second, positional uncertainties are inherent in the measured utility locations. An effective means is not yet available to visualize and communicate the inherent positional uncertainties associated with utility location data to end-users (e.g., excavator operator). To address the aforementioned problems, this research integrate ground penetrating radar (GPR), global positioning system (GPS) and geographic information system (GIS) to form a total 3G system to collect, inventory and visualize underground utility data. Furthermore, a 3D probabilistic error band is created to model and visualize the inherent positional uncertainties in utility data. ^ Three main challenges are addressed in this research. The first challenge is the interpretation of GPR and GPS raw data. A novel method is created in this research to simultaneously estimate the radius and buried depth of underground utilities using GPR scans and auxiliary GPS data. The proposed method was validated using GPR field scans obtained under various settings. It was found that this newly created method increases the accuracy of estimating the buried depth and radius of the buried utility under a general scanning condition. The second challenge is the geo-registration of detected utility locations. This challenge is addressed by integration of GPR, GPS and GIS. The newly created system takes advantages of GPR and GPS to detect and locate underground utilities in 3D and uses GIS for storing, updating, modeling, and visualizing collected utility data in a real world coordinate system. The third challenge is positional error/uncertainty assessment and modeling. The locational errors of GPR system are evaluated in different depth and soil conditions. Quantitative linkages between error magnitudes and its influencing factors (i.e., buried depths and soil conditions) are established. In order to handle the positional error of underground utilities, a prototype of 3D probabilistic error band is created and implemented in GIS environment. This makes the system error-aware and also paves the way to a more intelligent error-aware GIS. ^ To sum up, the newly created system is able to detect, locate and characterize underground utilities in an information-rich and error-aware manner

Inferring the most probable maps of underground utilities using Bayesian mapping model

Mapping the Underworld (MTU), a major initiative in the UK, is focused on addressing social, environmental and economic consequences raised from the inability to locate buried underground utilities (such as pipes and cables) by developing a multi-sensor mobile device. The aim of MTU device is to locate different types of buried assets in real time with the use of automated data processing techniques and statutory records. The statutory records, even though typically being inaccurate and incomplete, provide useful prior information on what is buried under the ground and where. However, the integration of information from multiple sensors (raw data) with these qualitative maps and their visualization is challenging and requires the implementation of robust machine learning/data fusion approaches. An approach for automated creation of revised maps was developed as a Bayesian Mapping model in this paper by integrating the knowledge extracted from sensors raw data and available statutory records. The combination of statutory records with the hypotheses from sensors was for initial estimation of what might be found underground and roughly where. The maps were (re)constructed using automated image segmentation techniques for hypotheses extraction and Bayesian classification techniques for segment-manhole connections. The model consisting of image segmentation algorithm and various Bayesian classification techniques (segment recognition and expectation maximization (EM) algorithm) provided robust performance on various simulated as well as real sites in terms of predicting linear/non-linear segments and constructing refined 2D/3D maps

A Critical Review on the Use of Shallow Geothermal Energy Systems for Heating and Cooling Purposes

The reduction of CO2 emissions has become a global concern. In this regard, the EU intends to cut CO2 emissions by 55% by 2030 compared to those of 1990. The utilization of shallow geothermal energy (SGE) in EU countries is considered the most effective measure for decarbonizing heating and cooling. SGE systems utilize heat energy collected from the earth’s crust to provide secure, clean, and ubiquitous energy. This paper provides a literature review on the use of SGE for heating and cooling purposes. The latest advances in materials, new innovative structures, and techno-economic optimization approaches have been discussed in detail. Shallow geothermal energy’s potential is first introduced, and the innovative borehole structures to improve performance and reduce installation cost is outlined. This is followed by an extensive survey of different types of conventional and thermally enhanced collectors and grouts. Attention is mainly given to the techno-economic analysis and optimization approaches. In published case studies, the least economic break-even point against fossil fuel-based heating systems occurs within 2.5 to 17 years, depending on the local geological conditions, installation efficiency, energy prices, and subsidy. Ground source heat pumps’ cost-effectiveness could be improved through market maturity, increased efficiency, cheap electricity, and good subsidy programs.publishedVersio

Kidnapped laser-scanner for evaluation of RFEC tool

© 2015 IEEE. An algorithm is proposed for matching data from different sensing modalities. The problem is formalised as a kidnapped robot problem, where Bayesian fusion is used to find the most likely location where both modalities agree. The key idea of our algorithm is to model the correlation between the two modalities as a likelihood used to update a location prior. Data, in this case, is represented as 2.5D thickness maps from a laser scanner and a Remote Field Eddy Current (RFEC) tool, used in non-destructive testing to assess the condition of infrastructures. The laser data is limited, while RFEC data is continuous. Given some prior in location, the aim is to find the 2.5D thickness map from the laser that corresponds to the RFEC data, which should be noted is highly noisy. Real data from CCTV inspections of water pipes are used to validate the proposed approach

Pipe failure prediction and impacts assessment in a water distribution network

Abstract Water distribution networks (WDNs) aim to provide water with desirable quantity, quality and pressure to the consumers. However, in case of pipe failure, which is the cumulative effect of physical, operational and weather-related factors, the WDN might fail to meet these objectives. Rehabilitation and replacement of some components of WDNs, such as pipes, is a common practice to improve the condition of the network to provide an acceptable level of service. The overall aim of this thesis is to predict—long-term, annually and short-term—the pipe failure propensity and assess the impacts of a single pipe failure on the level of service. The long-term and annual predictions facilitate the need for effective capital investment, whereas the short-term predictions have an operational use, enabling the water utilities to adjust the daily allocation and planning of resources to accommodate possible increase in pipe failure. The proposed methodology was implemented to the cast iron (CI) pipes in a UK WDN. The long-term and annual predictions are made using a novel combination of Evolutionary Polynomial Regression (EPR) and K-means clustering. The inclusion of K-means improves the predictions’ accuracy by using a set of models instead of a single model. The long-term predictive models consider physical factors, while the annual predictions also include weather-related factors. The analysis is conducted on a group level assuming that pipes with similar properties have similar breakage patterns. Soil type is another aggregation criterion since soil properties are associated with the corrosion of metallic pipes. The short-term predictions are based on a novel Artificial Neural Network (ANN) model that predicts the variations above a predefined threshold in the number of failures in the following days. The ANN model uses only existing weather data to make predictions reducing their uncertainty. The cross-validation technique is used to derive an accurate estimate of accuracy of EPR and ANN models by guaranteeing that all observations are used for both training and testing, and each observation is used for testing only once. The impact of pipe failure is assessed considering its duration, the topology of the network, the geographic location of the failed pipe and the time. The performance indicators used are the ratio of unsupplied demand and the number of customers with partial or no supply. Two scenarios are examined assuming that the failure occurs when there is a peak in either pressure or demand. The pressure-deficient conditions are simulated by introducing a sequence of artificial elements to all the demand nodes with pressure less than the required. This thesis proposes a new combination of a group-based method for deriving the failure rate and an individual-pipe method for evaluating the impacts on the level of service. Their conjunction indicates the most critical pipes. The long-term approach improves the accuracy of predictions, particularly for the groups with very low or very high failure frequency, considering diameter, age and length. The annual predictions accurately predict the fluctuation of failure frequency and its peak during the examined period. The EPR models indicate a strong direct relationship between low temperatures and failure frequency. The short-term predictions interpret the intra-year variation of failure frequency, with most failures occurring during the coldest months. The exhaustive trials led to the conclusion that the use of four consecutive days as input and the following two days as output results in the highest accuracy. The analysis of the relative significance of each input variable indicates that the variables that capture the intensity of low temperatures are the most influential. The outputs of the impact assessment indicate that the failure of most of the pipes in both scenarios (i.e. peak in pressure and demand) would have low impacts (i.e. low ratio of unsupplied demand and small number of affected nodes). This can be explained by the fact that the examined network is a large real-life network, and a single failure of a distribution pipe is likely to cause pressure-deficient conditions in a small part of it, whereas performance elsewhere is mostly satisfactory. Furthermore, the complex structure of the WDN allows them to recover from local pipe failures, exploiting the topological redundancy provided by closed loops, so that the flow could reach a given demand node through alternative paths

Single-pass inline pipeline 3D reconstruction using depth camera array

A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy. In the reconstructed model of a longer pipeline, the proposed method generates the dense 3D surface reconstruction model at the millimeter level accuracy with less than 0.5% distance error. The achieved performance highlights its potential as a useful tool for efficient in-line, non-destructive evaluation of pipeline assets

3D Buried Utility Location Using A Marching-Cross-Section Algorithm for Multi-sensor Data Fusion

We address the problem of accurately locating buried utility segments by fusing data from multiple sensors using a novel marching-cross-section (MCS) algorithm. Five types of sensors are used in this work: Ground Penetrating Radar (GPR), Passive Magnetic Fields (PMF), Magnetic Gradiometer (MG), Low Frequency Electromagnetic Fields (LFEM), and Vibro-acoustics (VA). As part of the MCS algorithm, a novel formulation of the extended Kalman filter (EKF) is proposed for marching existing utility tracks from a scan cross section (scs) to the next one; novel rules for initializing utilities based on hypothesized detections on the first scs and for associating predicted utility tracks with hypothesized detections in the following scss are introduced. Algorithms are proposed for generating virtual scan lines based on given hypothesized detections when different sensors do not share common scan lines, or when only the coordinates of the hypothesized detections are provided without any information of the actual survey scan lines. The performance of the proposed system is evaluated with both synthetic data and real data. The experimental results in this work demonstrate that the proposed MCS algorithm can locate multiple buried utility segments simultaneously, including both straight and curved utilities and can separate intersecting segments. By using the probabilities of a hypothesized detection being a pipe or a cable together with its 3D coordinates, the MCS algorithm is able to discriminate a pipe and a cable close to each other. The MCS algorithm can be used for both post and on-site processing. When it is used on site, the detected tracks on the current scs can help to determine the location and direction of the next scan line. The proposed “multi-utility multi-sensor” system has no limit to the number of buried utilities or the number of sensors, and the more sensor data used the more buried utility segments can be detected with more accurate location and orientation