Predicting the Future

Due to the increased capabilities of microprocessors and the advent of graphics processing units (GPUs) in recent decades, the use of machine learning methodologies has become popular in many fields of science and technology. This fact, together with the availability of large amounts of information, has meant that machine learning and Big Data have an important presence in the field of Energy. This Special Issue entitled “Predicting the Future—Big Data and Machine Learning” is focused on applications of machine learning methodologies in the field of energy. Topics include but are not limited to the following: big data architectures of power supply systems, energy-saving and efficiency models, environmental effects of energy consumption, prediction of occupational health and safety outcomes in the energy industry, price forecast prediction of raw materials, and energy management of smart buildings

Active thermography for the investigation of corrosion in steel surfaces

The present work aims at developing an experimental methodology for the analysis of corrosion phenomena of steel surfaces by means of Active Thermography (AT), in reflexion configuration (RC). The peculiarity of this AT approach consists in exciting by means of a laser source the sound surface of the specimens and acquiring the thermal signal on the same surface, instead of the corroded one: the thermal signal is then composed by the reflection of the thermal wave reflected by the corroded surface. This procedure aims at investigating internal corroded surfaces like in vessels, piping, carters etc. Thermal tests were performed in Step Heating and Lock-In conditions, by varying excitation parameters (power, time, number of pulse, ….) to improve the experimental set up. Surface thermal profiles were acquired by an IR thermocamera and means of salt spray testing; at set time intervals the specimens were investigated by means of AT. Each duration corresponded to a surface damage entity and to a variation in the thermal response. Thermal responses of corroded specimens were related to the corresponding corrosion level, referring to a reference specimen without corrosion. The entity of corrosion was also verified by a metallographic optical microscope to measure the thickness variation of the specimens

Weld Distortion Prediction With Virtual Analysis For Practical Applications

The reduction in time and facilities involved in the partial elimination or mitigation of welding distortion is one of the key points for manufacturers. Welding distortion is influenced by the sequence and position of joints, the clamping configuration and the design of the assembly. For large complex assemblies, the range of these options may be large. Therefore the use of numerical simulations at an early stage of the product development process is valuable to enable a wide range of these factors to be explored with the aim of minimizing welding distortions before production commences. This thesis investigates two techniques for simulation of welding distortions based on shrinkage analysis and transient analysis. Both techniques are evaluated for an automotive assembly. The shrinkage simulations were built and solved using the Weld Planner, whereas the transient simulations were solved with Sysweld. The rapid simulation speed enabled a wide range of welding materials and clamping positions to be explored, leading to recommendations for reduction of the distortions. The solution times were found to be significantly lower for the shrinkage analysis than the transient analysis

Application of artificial neural network for the structural integrity assessment of dent in pipelines

PhD ThesisDent in a pipelines have been of major concern to pipeline operators for years because its severity cannot be easily determined. For many years dent severity was based on dent depth alone. This has led to unnecessary repairs and removal from service incurring considerable loss in revenue. Studies by researchers have indicated that other factors like pipe geometry, pipe material, dent geometry and pressure cycling could influence the severity of the dent in terms of the fatigue life reduction. Dent severity has been studied using dent depth based assessment, strain based assessment and fatigue assessment . The dent depth over the years has been the major determinant of dent severity. Recent studies have shown that the strain in the pipeline could be a better indicator of dent severity using the static approach. The most common fatigue approach is the stress life S-N approach. This involves extracting stress data either through experimental procedure or finite element analysis and using it with an appropriate S-N curve to determine the fatigue life One of the major challenges faced in S-N fatigue approach today is determining the stress concentration factors (SCF) associated with the dents. These SCFs are used with an appropriate SN curve to calculate the fatigue life. This, over the years and currently is calculated empirically or using finite element (FE) analysis. The cost of running experimental program can be very expensive and numerical analysis can be time-consuming. It is not sustainable to keep using finite element analysis to calculate the SCF associated with every dent. An algorithm is needed to be able to predict strain and SCF without running an expensive experimental program or running an extensive finite element study This Research presents an alternative and a sustainable method for calculating the SCF, the maximum strain and the rerounding depth in pipelines with dent. The method involves gathering a large database of SCFs, strains and rerounding depths through a finite element study on a parametric range of industry standard pipes . These parametric datasets focuses on the effects of pipe geometry, dent geometry, material properties and pressure range on the prediction of the strain and stresses which were not systematically considered by other researchers. These parametric datasets are then used to train an artificial neural network (ANN) that predicts the rerounding depth,maximum strain and the SCF. The ANN presents an accurate and sustainable alternative to the current method used for dent assessment. It’s application would reduce the cost and time taken in assessing dent severity. The accuracy of the ANN is dependent on the amount of training data. In order to create the large database of results, a parametric design language (APDL) was created for easy creation and recreation of models. This parametric design language helped in the creation of 256 FE models which was sufficient enough to create the large database of SCF and other data needed to train the ANN Two types of indenters (Dome and Bar) are used to simulate circumferentially and longitudinally aligned dents. Four different dent depths ranging from 2% d/D to 10% d/D are also simulated to investigate the effect of dent geometry. Four different pipe grades (X46, X65, X80, and X100) are analysed to investigate the effect of pipe materials. Similarly, eight pipes with a different diameter to thickness ratio (D/t) ranging from 18-96 are analysed to investigate the effect of pipe geometry. The pipe is pressured up to 50% and 72% SMYS to investigate the effect of pressure range. The results from this study show that all the investigated parameters influence the results in various ways. Results show that longitudinally aligned dents have higher stress concentrations factors compared to circumferential dents of similar dent depth. Similarly, pipes with higher diameter to thickness ratios D/t have higher stress concentration factor compared to pipes with lower D/t .The FE result was validated with experimental and analytical results and a good correlation was seen with minimal percentage error. The FE results from the parametric study was fed into an ANN model to train the network. The network was trained with different numbers of the processing element and activation function to find the model with the best performance. The ANN prediction gave a good correlation with the FE result

Determination of Mechanical Properties of Materials by Small Punch and Other Miniature Testing Techniques: Proceedings of the 5th International Small Sample Test Techniques Conference SSTT2018

Topics include Small Scale Testing for Tensile and Fracture Behaviour of Steel, Alternative Miniaturised Test Methods, Impression Creep, Miniaturised Tensile Testing, Small Scale Testing of Advanced Materials, Small Scale Creep Testing, Small Scale Testing Methodologies and Standardisation

Texture and Colour in Image Analysis

Research in colour and texture has experienced major changes in the last few years. This book presents some recent advances in the field, specifically in the theory and applications of colour texture analysis. This volume also features benchmarks, comparative evaluations and reviews

LSST Science Book, Version 2.0

A survey that can cover the sky in optical bands over wide fields to faint magnitudes with a fast cadence will enable many of the exciting science opportunities of the next decade. The Large Synoptic Survey Telescope (LSST) will have an effective aperture of 6.7 meters and an imaging camera with field of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over 20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a total point-source depth of r~27.5. The LSST Science Book describes the basic parameters of the LSST hardware, software, and observing plans. The book discusses educational and outreach opportunities, then goes on to describe a broad range of science that LSST will revolutionize: mapping the inner and outer Solar System, stellar populations in the Milky Way and nearby galaxies, the structure of the Milky Way disk and halo and other objects in the Local Volume, transient and variable objects both at low and high redshift, and the properties of normal and active galaxies at low and high redshift. It then turns to far-field cosmological topics, exploring properties of supernovae to z~1, strong and weak lensing, the large-scale distribution of galaxies and baryon oscillations, and how these different probes may be combined to constrain cosmological models and the physics of dark energy.Comment: 596 pages. Also available at full resolution at http://www.lsst.org/lsst/sciboo

Numerical analysis of fatigue crack growth in welded joints with multiple defects

In the case of welded steel structures (such as pressure equipment), welded joints are often critical location for stress concentrations, due to different mechanical properties and chemical composition compared to the parent material, and due to changes in geometry. In addition, the presence of imperfections (defects) in welded joints can contribute to the increase in local stress, resulting in crack initiation. Recently, standards that are related to acceptable dimensions of various types of defects in welded joints started taking fatigue loading into account as well. For the purpose of this research, a 3D numerical model was made, of a welded joint with different types of defects (linear misalignment and a crack in the weld metal), based on the previous work, which involved static loading of the same specimen. In this case, fatigue was taken into account, and the simulation was performed using ABAQUS software, as well as Morfeo, an add-on used for determining the fatigue behaviour of structures via XFEM (extended finite element method). The welded joint was made using steel P460NL1 as the parent material, and EPP2NiMo2 wire was used for the weld metal. An additional model was made, whose defects included a crack and an overhang. Fatigue crack growth analysis was performed for this model as well, and the results for stress intensity factors and stress/strain distribution were compared in order to obtain information about how different defects can affect the integrity of a welded joint

The influence of oxide deposits on the remaining life and integrity of pressure vessels equipment

In this paper is presented the principle of application of fracture mechanics parameters in determining the integrity of rotary equipment. The behavior of rotary equipment depends on presence of cracks and basically determines the integrity and life of such equipment. The locations of stress concentration (i.e. radius changes) represent a particular problem in rotary equipment, and they are the most suitable places for the occurrence of microcracks i.e. cracks due to fatigue load. This problem is most common in the shaft of relatively large dimensions, for example, turbine shafts in hydropower plants made of high-strength carbon steel with relatively low fracture toughness, and relatively low resistance to crack formation and growth. Having in mind that rotary equipment represents the great risk in the exploitation, whose occasional failures often had severe consequences, it is necessary detail study of their integrity. For this purpose, it is necessary application of parameters of linear-elastic fracture mechanics, such as stress intensity factor, which range defines the rate of crack growth (Parisian law), and its critical value (fracture toughness) determines the critical crack length. The procedures for determining the critical crack length will be described using the fracture mechanics parameters

Using the fracture mechanics parameters in assessment of integrity of rotary equipment

In this paper is presented the principle of application of fracture mechanics parameters in determining the integrity of rotary equipment. The behavior of rotary equipment depends on presence of cracks and basically determines the integrity and life of such equipment. The locations of stress concentration (i.e. radius changes) represent a particular problem in rotary equipment, and they are the most suitable places for the occurrence of microcracks i.e. cracks due to fatigue load. This problem is most common in the shaft of relatively large dimensions, for example, turbine shafts in hydropower plants made of high-strength carbon steel with relatively low fracture toughness, and relatively low resistance to crack formation and growth. Having in mind that rotary equipment represents the great risk in the exploitation, whose occasional failures often had severe consequences, it is necessary detail study of their integrity. For this purpose, it is necessary application of parameters of linear-elastic fracture mechanics, such as stress intensity factor, which range defines the rate of crack growth (Parisian law), and its critical value (fracture toughness) determines the critical crack length. The procedures for determining the critical crack length will be described using the fracture mechanics parameters