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In recent years, the development of the world electric power industry is associated with the development of unconventional energy resources, the design and the installation of distributed generations. At the design stage for implementing distributed generations and for determining the location and sizing generators the topologies of the distributed system, methods of connection to electric networks, the requirement to relay protection and automation systems, economic factors, etc. should be considered. Various methods are used for the optimal distribution installations, among which meta-heuristic search algorithms are gaining great popularity. In this article the basic aspects of determining the optimal place of installing distributed power generation in the electric power system are presented, in particular, one of the important parameters when choosing a location for generating sources is the level of the total losses and stabilize voltage level. The results of the analysis of the application of different meta-heuristic methods are shown.

The Aerostats are lighter-than-air (LTA) systems that are used to carry important payloads at specified altitudes. Tethered aerostats are connected to the ground via a tether that maintains the position and provides power. Aerostats have to operate in various atmospheric conditions depending on their mission. This paper presents a literature review on the different envelope shapes of the tethered aerostats. Aerostat envelope contains the LTA gas that provides the lift force to carry the payload in the air. This research paper presents a comprehensive literature review on the different shapes of aerostat envelopes. The review has been presented to highlight the design process of the different aerostat envelope shapes that includes sizing, aerodynamics and stability. In addition to the design factors, this paper also presents a review on the applications of different aerostat envelope shapes. Information related to the different design parameters and limitations of aerostat envelopes is also provided.

This article describes the development of the RenPower (Renewable Power) software for sizing of renewable energy microgrids able to be used in academic teaching. RenPower was implemented using the graphic programming language LabVIEWTM, and being freely used, allows students, teachers and researchers to select a geographical location anywhere in the world, define a user’s monthly energy demand and obtain the annual photovoltaic and wind energy to meet the needs. The software also allows to calculate the amount of batteries to store the energy of the microgrid, as well as the power of the inverter for connection to the electrical network. The sizing results obtained with the software are identical to those obtained by theoretical calculations. RenPower was developed by the following universities: Universidad de Bogota Jorge Tadeo Lozano (Colombia), Northwestern Polytechnical University (China), The University of Oklahoma (USA), Universitat Politecnica de Valencia (Spain), Universidad Nacional de Colombia (Colombia) and Universidad Tecnologica del Choco (Colombia).

The detection and monitoring of oil spills in marine environment are crucial to respond rapidly and efficiently and it is especially important in ice-covered areas. Detection and quantitative characterization of the affected areas as well as monitoring of remediation measures are critical for optimized cleaning operation and minimal environment impact. In the recent years, techniques of oil spill detection from under the ice with Remote Operated Vehicle (ROV) or Autonomous Underwater Vehicle (AUV), have been explored and have shown promising results. These techniques are based on ultrasonic or sonar technologies to quantify the oil volume and on optical techniques to obtain a chemical signature of the oil presence. In this paper we present a new promising technique based on photoacoustics for detection and sizing of oil spill under the ice, encapsulated within ice, or on open water. The technique has the advantage to provide signal in the presence of oil and no signal in its absence. It is also much less sensitive to alignment compared to ultrasonic and sonar techniques. Experimental results on detection of oil under the ice are presented and discussed. A first prototype with a scanning unit that can be operated in ROV is also presented. The solution proposed should be especially useful as a tool for emergency response, but should also be suitable when operated in AUV for monitoring high risky areas due to navigation, transportation or oil exploration and production., 45th Annual Review of Progress in Quantitative Nondestructive Evaluation, July 15–19, 2018, Vermont, USA, Series: AIP Conference Proceedings

Locating and Sizing of Distributed Generation (DG) is an important research topic in the development of microgrids. First, this paper models the uncertainty of its two main Distributed Generation, wind power generation and photovoltaic power generation. Then, considering the economic benefits and technical requirements, three important indicators including investment benefit, network loss improvement and static voltage stability improvement are selected to optimize locating and sizing of DG, and the particle swarm optimization algorithm with inertia weight is used to solve the problem. Finally, the simulation analysis of the IEEE-37 node test feeder shows that the method can effectively improve the voltage level of the system, reduce the active power loss, and improve the static voltage stability of the system. It has certain practical value in the distribution network planning.Locating and Sizing of Distributed Generation (DG) is an important research topic in the development of microgrids. First, this paper models the uncertainty of its two main Distributed Generation, wind power generation and photovoltaic power generation. Then, considering the economic benefits and technical requirements, three important indicators including investment benefit, network loss improvement and static voltage stability improvement are selected to optimize locating and sizing of DG, and the particle swarm optimization algorithm with inertia weight is used to solve the problem. Finally, the simulation analysis of the IEEE-37 node test feeder shows that the method can effectively improve the voltage level of the system, reduce the active power loss, and improve the static voltage stability of the system. It has certain practical value in the distribution network planning.

The U.S. Nuclear Regulatory Commission (NRC) in cooperation with the nuclear industry has developed a probabilistic fracture mechanics code called xLPR (extremely Low Probability of Rupture). xLPR is a modular-based probabilistic assessment tool for determining probability of leakage and rupture for pressure boundary piping. One of the modules in xLPR is the In-Service Inspection (ISI) module which models the probability of detection (POD) and sizing performance of NDE performed during in-service inspection to account for and predict the influence of periodic inspections on the probability of component leakage and rupture. The accuracy of the ISI module in xLPR is dependent on the quality of the estimates of detection and sizing performance that are input to the module. Multiple efforts have been attempted to quantify the detection and sizing performance of NDE in the nuclear industry. These efforts include an analysis of inspection data collected as part of the industry’s Performance Demonstration Initiative (PDI) and data collected from NRC sponsored round robin studies such as PINC-Program for the Inspection of Nickel Alloy Components and PARENT-Program to Assess the Reliability of Emerging Nondestructive Techniques. Usage of a given data set in the xLPR ISI module requires understanding of which set of data is most representative for the specific scenario under consideration. A comparative analysis of detection performance data from PDI, PINC, and PARENT is provided in this paper in an effort to elucidate for users of xLPR types of applications the above mentioned data sets may be most appropriate for.

Glass fiber reinforced polyamide 6.6 (PA66) has a high service temperature as well as good chemical resistance. Because of its low raw material price, it is a common engineering material for under the hood applications involving coolants. In order to keep up with the developments in the automotive sector, the material has to be improved as well. In the field of polymer synthesis, fiber sizing and additives, there is a high potential for further developments of new materials with the aim of a high material efficiency. This will only be successful, if the complete system is taken into account. The influencing coefficients, such as the PA66 type, the fiber sizing or the additives, will be discussed in this study. The main influencing factors will be evaluated. Based on this study, the main factor is the fiber sizing, while the different additive masterbatches or PA66 types have minor influences.

Cast stainless steel (CSS) is widely used in nuclear power plants, particularly in PWR primary coolant systems. The JSME Fitness-for-Service Code requires periodic in-service inspection of welds in such systems by ultrasonic testing (UT), but anisotropy and heterogeneity of CSS make flaw detection and sizing difficult. Phased array ultrasonic technique (PAUT) is considered the most promising technique to solve such difficulties. In order to take advantage of PAUT to CSS, it is crucial to deeply understand how waves propagate in CSS. In this study, a 2-MHz linear array transducer is used to generate waves which propagate within a specimen made of centrifugally cast stainless steel (CCSS) with columnar grain structure at different directions, and a normal beam longitudinal transducer is used to receive waves propagating in the specimen. The observation results show that wave propagation direction is different from the specified direction and the difference strongly depends on the specified direction. The measured values of phase velocity and skew angle are consistent with theoretical values based on the hexagonal system.

There have been lots of reports about the occurrence of cracks in bolts in aging nuclear and thermal power plants. Sizing of such cracks is crucial for assessing the integrity of bolts. Currently, hammering and visual tests are used to detect cracks in bolts. However, they are not applicable for sizing cracks. Although the tip diffraction method is well known as a crack sizing technique, reflection echoes from threads make it difficult to apply this technique to bolts. This paper addresses a method for depth sizing of cracks in bolts by means of ultrasonic phased array technology. Numerical results of wave propagation in bolts by the finite element method (FEM) shows that a peak associated within the vicinity of a crack tip can be observed in the curve of echo intensity versus refraction angle for deep cracks. The refraction angle with respect to this peak decreases as crack depth increases. Such numerical results are verified by experiments on bolt specimens that have electrical discharge machining notches or fatigue cracks with different depths. In the experiment, a 10-MHz linear array probe is used. Depth of cracks in bolts using the refraction angle associated with the peak is determined and compared to actual depths. The comparison shows that accurately determining a crack depth from the inspection results is possible.

This paper presents a new integrated planning framework for effective accommodating electric vehicles in smart distribution systems (SDS). The proposed method incorporates various investment options available for the utility collectively, including distributed generation (DG), capacitors and network reinforcement. Using a back-propagation algorithm combined with cost-benefit analysis, the optimal network upgrade plan, allocation and sizing of the selected components are determined, with the purpose of minimizing the total system capital and operating costs of DG and EV accommodation. Furthermore, a new iterative reliability test method is proposed. It can check the optimization results by subsequently simulating the reliability level of the planning scheme, and modify the generation reserve margin to guarantee acceptable adequacy levels for each year of the planning horizon. Numerical results based on a 32-bus distribution system verify the effectiveness of the proposed method.

Ultrasonic full matrix capture/total focusing method (FMC/TFM) technology has progressed significantly over the past few years and has seen increased use in industry. The technology has the potential to provide better detection and measurement capabilities for weld flaws, as well as, many other applications including additive manufacturing. This project looked at the effectiveness of FMC/TFM for detection and sizing of both planar and volumetric flaw types. FMC/TFM experimental data was collected and processed using multiple combinations of probe types and wave propagation modes. The data was then compared to typical ultrasonic phased-array results, as well as FMC/TFM inspection simulations.

Advanced reactor concepts include fast reactors (including sodium-cooled fast reactors), gas-cooled reactors, and molten-salt reactors. Common to these concepts is a higher operating temperature (when compared to light-water-cooled reactors), and the proposed use of new alloys with which there is limited operational experience. Concerns about new degradation mechanisms, such as high-temperature creep and creep fatigue, that are not encountered in the light-water fleet and longer operating cycles between refueling intervals indicate the need for condition monitoring technology. Specific needs in this context include periodic in-service inspection technology for the detection and sizing of cracking, as well as technologies for continuous monitoring of components using in situ probes. This paper will discuss research on the development and evaluation of high temperature (>550°C; >1022°F) ultrasonic probes that can be used for continuous monitoring of components. The focus of this work is on probes that are compatible with a liquid sodium-cooled reactor environment, where the core outlet temperatures can reach 550°C (1022°F). Modeling to assess sensitivity of various sensor configurations and experimental evaluation have pointed to a preferred design and concept of operations for these probes. This paper will describe these studies and ongoing work to fabricate and fully evaluate survivability and sensor performance over extended periods at operational temperatures.

In this paper, it is shown that the inverter size that maximizes the energy yield in CPV plants is influenced by self-shading between sun trackers. For this purpose, a detailed CPV power plant model was developed from experimental data obtained in the outdoor characterization of a typical 700x concentration factor Fresnel lens-based CPV module. The simulated results indicate that neglecting the impact of shading can lead to inaccurate values of the optimum inverter capacity from an energetic point of view. However, applying an economic optimization criterion, the inverter sizing ratio seems to be independent on ground cover ratio. In the study, the influence of the inverter efficiency characteristics is also discussed.

The present project deals with a method of designing a photovoltaic solar pumping system. The aim of this design is to make an optimal choice of the various industrial equipment of this system ensuring optimization, regulation and safety. This sizing method is based on the mathematical equations that govern the system as well as the charts of electrical and mechanical quantities. The system in question is composed of three equipments: The Photovoltaic generator, the solar inverter drive and the motor pump group. This design not only makes it possible to design the pumping system to meet the desired technical specifications, but also to ensure compatibility to ensure proper operation and reliability. It is based essentially on the assessment of the water requirements, the calculation of the necessary hydraulic energy, the calculation of the necessary electrical power, that provided by the PV generator and the optimization of the constituents of the pumping system. The design and choice of elements are made on a real installation to meet the water needs of the gardens of the Faculty of Science and Techniques of Beni-Mellal. Thus, the estimated flow rate is 3.5 m3 / h for a total dynamic head of 65 m.

New technological challenges like electro-mobility pose an increasing demand for cost-efficient processes for the production of product variants. This demand opens the possibility to combine established die-based manufacturing methods and innovative, dieless technologies like additive manufacturing [1, 2]. In this context, additive manufacturing technologies allow for the weight-efficient local reinforcement of parts before and after forming, enabling manufacturers to produce product variants from series parts [3].Previous work by the authors shows that the optimal shape of the reinforcing structure can be determined using sizing optimization. Sheet metal parts can then be reinforced using laser metal deposition. The material used is a pearlite-reduced, micro-alloyed steel (ZE 630). The aim of this paper is to determine the effect of the additive manufacturing process on the material behavior and the mechanical properties of the base material and the resulting composite material. The parameters of the AM process are optimized to reach similar material properties in the base material and the build-up volume. A metallographic analysis of the parts is presented, where the additive layers, the base material and also the bonding between the additive layers and the base material are analyzed. The paper shows the feasibility of the approach and details the resulting mechanical properties and performance.New technological challenges like electro-mobility pose an increasing demand for cost-efficient processes for the production of product variants. This demand opens the possibility to combine established die-based manufacturing methods and innovative, dieless technologies like additive manufacturing [1, 2]. In this context, additive manufacturing technologies allow for the weight-efficient local reinforcement of parts before and after forming, enabling manufacturers to produce product variants from series parts [3].Previous work by the authors shows that the optimal shape of the reinforcing structure can be determined using sizing optimization. Sheet metal parts can then be reinforced using laser metal deposition. The material used is a pearlite-reduced, micro-alloyed steel (ZE 630). The aim of this paper is to determine the effect of the additive manufacturing process on the material behavior and the mechanical properties of the base material and the resulting composite material. The parameters of the AM ...

Austenitic stainless steel welds as well as dissimilar metal welds with nickel alloy filler material, used in safety relevant parts of nuclear power plants, still challenge the ultrasonic inspection. The weld material forms large oriented grains which lead on the one hand to high sound scattering and on the other hand – to inhomogeneity and to the acoustic anisotropy of the weld structure. The ultrasonic wave fronts propagate not linearly, as in ferritic weld joints, but along the curves, which depend on the specific grain structure of the weld. Due the influence of these phenomena, it is difficult to analyze the inspection results and to classify the ultrasonic indications, which could be both from the weld geometry and from the material defects. A correct flaw sizing is not possible. In an ongoing research project, different techniques to improve the reliability of ultrasonic testing at these kinds of welds are investigated. In a first step (in the previous research project) two ultrasonic inspection techniques were developed and validated on plane test specimens with artificial and realistic flaws. In the ongoing project, these techniques are applied to circumferential pipe welds with longitudinal and transverse flaws. The technique developed at the Federal Institute for Materials Research and Testing (BAM) in Germany uses a combination of ray tracing and synthetic aperture focusing technique (SAFT). To investigate the unknown grain structure, the velocity distribution of weld-transmitting ultrasound waves is measured and used to model the weld by ray tracing. The second technique, developed at the Fraunhofer Institute for Nondestructive Testing (IZFP) in Germany, uses Sampling Phased Array (Full Matrix Capture) combined with the reverse phase matching (RPM) and the gradient elastic constant descent algorithm (GECDM). This inspection method is able to estimate the elastic constants of the columnar grains in the weld and offers an improvement of the reliability of ultrasonic testing through the correction of the sound field distortion. The unknown inhomogeneity and anisotropy are investigated using a reference indication and the special optimization algorithm. Both reconstruction techniques give quantitative inspection results and allow the defect sizing. They have been compared to conventional ultrasonic testing with techniques, which are state of the art for components in nuclear power plants. The improvement will be quantified by the comparison of the probability of detection (POD) of each technique.

In this work, we explore for the first time the viability and the annual performance of a solar plant which combines a sodium receiver, phase-change material (PCM) storage and supercritical CO2 (sCO2) power block. The simulation results suggest that the system is thermodynamically and economically viable, reducing the levelized cost of electricity (LCOE) compared with a conventional CST plant based on molten salts. The paper presents a new dynamic model of the novel plant configuration which is used for performing a storage sizing study obtaining the best plant investment.

Renewable energy, especially PV systems, has experienced a significant growth in its rate of deployment as an alternative for conventional power sources. However, a larger penetration of PV systems is restricted to the availability of technological options for storage. The integration of thermal energy storage to CSP systems is straightforward, through technologies already available in the market. Hence, the hybridization of CSP and PV systems has the potential for reducing operational and installation costs, as well as significantly increase the capacity factor. The present study describes a methodology for design and sizing of such hybrid plants, by implementing a transient simulation model, coupled to an evolutionary optimization algorithm, allowing to address the tradeoff between costs and capacity factor.

Hydraulic ram pump is a mechanical pump that works automatically without the use of electrical energy, but use momentum of the driving water flow to pump a fraction of the water into a reservoir. It consists of two moving parts, they are waste (or impulse) and delivery valves. These valves mechanism generate a high pressure of water hammer that used in hydraulic ram working cycle. The waste valve is a key component of the hydraulic ram. However, in the implementation of hydraulic rams, they takes a long time for sizing and adjusting of their waste valves, because there is no sufficient references in making the design of the waste valve. The characteristics of the waste valve are affected by parameters such as the orifice diameter of valve sitting, the diameter of the valve disc, the stroke length, and the weight of the valve as well as the discharge and head of water supply to drive the hydraulic ram pump. In addition, all these parameters affect each other. Therefore, in this study an experimental work was carried out on hydraulic ram pump model with variation of all parameters of the waste valve. The results show that all of the waste valve design parameters such as valve orifice and disc diameter, valve mass and valve stroke significantly influence the performance of the hydraulic ram pump system. Furthermore, procedures are proposed in determining of the waste valve diameter and its stroke, and a simple formula is proposed for estimating the optimal mass of waste valve that can deliver the best hydraulic ram performance.

Ultrasonic Propagation Imaging or Acoustic Wavefield Imaging has been widely used to evaluate structural damages and internal features. Inspecting complete wavefield time history for damage identification is tedious and error-prone. A more effective way is by extracting damage-related information into a single image. A wavefield velocity imaging method that maps the local estimates of group or phase velocity is proposed. Actual velocity values rather than arbitrarily-scaled intensities are mapped, enabling damage sizing without the need of supervised training or inspecting wavefield propagation video. Performance of the proposed method was tested by inspecting a 100 mm by 100 mm area of a 2 mm thick stainless steel specimen. Local phase velocity maps of A0 mode showed a half-thickness hole of 2 mm diameter as significant change in local phase velocity from the nominal 2 m/ms. Full width at half maximum of relevant velocity profiles proved the accuracy and consistency of the damage sizing.

International audience; Friction between carbon fibres or tows often occurs during the implementation of Carbon Fibres Reinforced Polymer. Defects are due to these friction phenomena that can reduce the mechanical properties and the lifetime of the final parts. This study has been conducted to study the friction behaviour between carbon fibres or carbon tows with an angle of 90°. The coefficient of friction (COF) of 3 types of carbon fibres differentiated by their Young’s Modulus is determined thanks to an experimental device dedicated to this study. It consists in rubbing 2 tows or 2 yarns together with an angle of 90°. A particularity of this study is a work conducted on single fibres whose diameter is small up to 4.9 flm. For single fibre as for tow, there is no influence of friction velocity and normal load. It has been shown the COF is higher at tow scale because of fibrous rearrangement. As the Young’s Modulus increases, the COF between single fibres decreases. At tow scale, no influence is highlighted. Moreover, this study highlights the sizing treatment is damaged during a friction test and can participate to the evolution of the COF.

The aim of the paper is to investigate the optimum design of truss structures by considering different stress and displacement constraints. For that reason, the flower pollination algorithm based methodology was applied for sizing optimization of space truss structures. Flower pollination algorithm is a metaheuristic algorithm inspired by the pollination process of flowering plants. By the imitation of cross-pollination and self-pollination processes, the randomly generation of sizes of truss members are done in two ways and these two types of optimization are controlled with a switch probability. In the study, a 72 bar space truss structure was optimized by using five different cases of the constraint limits. According to the results, a linear relationship between the optimum structure weight and constraint limits was observed.

Loss of expensive mud could lead to major financial problem in executing a drilling project and is one of the biggest problems that need to be tackled during drilling. Synthetic Based Mud (SBM) is the most stable state of the art drilling mud used in current drilling technologies. However, the problem with lost circulation is still inevitable. The focus of this project is to develop a new potential waste material from banana peel in order to combat lost circulation in SBM. Standard industrial Lost Circulation Material (LCM) is used to compare the performance of banana peel as LCM in SBM. The effects of different sizing of banana peels (600 micron, 300 micron and 100 micron) were studied on the rheological and filtration properties of SBM and the bridging performance of banana peel as LCM additive. The tests were conducted using viscometer, HTHP filter press and sand bed tester. Thermal analysis of banana peel was also studied using TGA. According to the results obtained, 300 and 100 micron size of banana peel LCM exhibited an improved bridging performance by 65% as compared to industrial LCM. However, banana peel LCM with the size of 600 micron failed to act as LCM due to the total invasion of mud into the sand bed.

The collaboration between the Research Center for Renewable Energy Mapping and Assessment (ReCREMA) at Masdar Institute of Science and Technology and the King Abdullah City for Atomic & Renewable Energy (KACARE) aims to create an interactive web tool integrated in the Renewable Resource Atlas where different solar thermal electricity (STE) utility-scale technologies will be simulated. In this paper, a methodology is presented for sizing and performance simulation of the solar field of parabolic trough collector (PTC) plants. The model is used for a case study analysis of the potential of STE in three sites located in the central, western, and eastern parts of Saudi Arabia. The plant located in the north (Tayma) has the lowest number of collectors with the best production along the year.

The distribution system is the closest network to the customer. Therefore, the distribution network should be designed economically to obtain a particular level of quality. A good long-term planning needs to be carried out to get such a system. One such plan is to get the optimal sizing and placement of distribution transformers. The objective of the study is to obtain optimal location and capacity of the distribution transformer in PT PLN (Persero) East Medan, North Sumatra. The location and optimum capacity are obtained by minimizing the investment costs and operational costs of electric power distribution system without violating voltage constraint. Genetic Algorithm method is used to get the optimal costs. The results show that optimal sizing and placement distribution transformers problem in PT PLN (Persero) East Medan, Sumatera Utara can be solved efficiently using Genetic Algorithm in less than 200 generations. Sensitivity analysis on the utilization factor, demand factor and coincidence factor have been reported. The increase of the demand factor and coincidence factor are directly proportional to the increase in investment costs. Meanwhile, the utilization factor is inversely proportional to the value of the investment cost.

Backscattered ultrasonic microstructural noise can be used to estimate grain size in metals. However for normal-incidence immersion measurements the ring-down of the front-wall echo creates a ”dead zone” where backscattered grain noise cannot be quantified. This poses a problem for near-surface grain sizing efforts. In this paper we explore the use of mode-converted 45-degree shear waves for near-surface grain sizing using a water immersion setup. We discuss how to accurately relate grain noise arrival time with depth of sound penetration in the metal. Then for a set of Ni-alloy specimens having near-equiaxed microstructures we correlate various backscattered noise attributes with grain sizes determined from micrographs. These noise attributes include both time-domain and frequency-domain characteristics. The backscattered grain noise attributes correlate well with grain size, and are relatively insensitive to modest changes in the transducer tilt angle.

A comprehensive approach to NDE and SHM characterization error (CE) evaluation is presented that follows the framework of the ‘ahat-versus-a’ regression analysis for POD assessment. Characterization capability evaluation is typically more complex with respect to current POD evaluations and thus requires engineering and statistical expertise in the model-building process to ensure all key effects and interactions are addressed. Justifying the statistical model choice with underlying assumptions is key. Several sizing case studies are presented with detailed evaluations of the most appropriate statistical model for each data set. The use of a model-assisted approach is introduced to help assess the reliability of NDE and SHM characterization capability under a wide range of part, environmental and damage conditions. Best practices of using models are presented for both an eddy current NDE sizing and vibration-based SHM case studies. The results of these studies highlight the general protocol feasibility, em...

A comprehensive approach is presented to perform model-based inversion of crack characteristics using bolt hole eddy current (BHEC) techniques. Data was acquired for a wide range of crack sizes and shapes, including mid-bore, corner and through-thickness crack types, and from both standard eddy current hardware and a prototype BHEC system with z-axis position encoding. Signal processing algorithms were developed to process and extract features from the 2D data sets, and inversion algorithms using VIC-3D generated surrogate models were used for inverting crack size. New model results are presented, which now address the effect of having a corner crack at an edge and a through crack adjacent to two edges. A two-step inversion process was implemented that first evaluates the material layer thickness, crack type and location, in order to select the most appropriate VIC-3D surrogate model for subsequent crack sizing inversion step. Inversion results for select mid-bore, through and corner crack specimens are presented where sizing performance was found to be satisfactory in general, but also depend on the size and location of the flaw.

Nowadays, the estimation of the PhotoVoltaic (PV) power production systems is crucial for ensuring their economic feasibility as well as their proper sizing in order to avoid outages and guarantee quality and continuity of supply. The working temperature of a PV module or system is a key parameter for the assessment of the actual performance of photovoltaic modules. PV modules are usually rated at Standard Test Conditions (STC = 1000W/m2, AM1.5, 25°C), but their operating temperatures are typically considerably higher. Power production can be highly influenced by cell working (module) temperature whose increase respect to standard one could gradually deteriorate system's energy performance. Correlations to evaluate performances referring to STC and/or applying some theoretical simplifications/assumptions are available in literature. However, it be noticed that the use of these correlations, under the same operative conditions, does not produce univocal results. In this paper, an Artificial Neural Network (ANN)-based model to forecast the working temperature of a Concentrator PhotoVoltaic (CPV) module (back - plate temperature) is proposed. A dataset consisting of meteorological data (i.e. solar direct normal irradiance, ambient temperature, wind speed and wind direction), measured every 1-minute and recorded from November 2012 to April 2014, concerning a 50 kWp CPV plant installed in the southwestern Europe, is used for the training and testing of the ANN developed. The main advantage of the proposed approach is that it acts as black box tool, making easy to model an arbitrary complex non-linear relationship between inputs and outputs. In fact, in this case no in-depth knowledge of the system and its components is required contrary to what needed by deterministic techniques. In order to verify the effectiveness and the accuracy of the approach here proposed, measured and estimated data were analysed and compared considering different error metrics. © 2016, American Institute of Physics Inc. All rights reserved.

A dynamic threshold method for ultrasonic C-Scan imaging is developed to improve the performance of flaw sizing: the reference test blocks with flat-bottom hole flaws of different depths and sizes are used for ultrasonic C-Scan imaging. After preprocessing, flaw regions are separated from the C-scan image. Then the flaws are sized roughly by 6-dB-drop method. Based on the real size of flat-bottom holes, enumeration method is used to get the optimal threshold for the flaw. The neural network is trained using the combination of amplitude and depth of flaw echo, the rough size of flaw and the optimal threshold. Finally, the C-Scan image can be reconstructed according to dynamic threshold generated by trained RBF NN. The experimental results show that the presented method has better performance and it is ideally suited for automatic analysis of ultrasonic C-scan images.

Guided wave inspection technology is most often applied as a survey tool for pipeline inspection, where relatively low frequency ultrasonic waves, compared to those used in conventional ultrasonic nondestructive evaluation (NDE) methods, propagate along the structure; discontinuities cause a reflection of the sound back to the sensor for flaw detection. Although the technology can be used to accurately locate a flaw over long distances, the flaw sizing performance, especially for flaw depth estimation, is much poorer than other, local NDE approaches. Estimating flaw depth, as opposed to other parameters, is of particular interest for failure analysis of many structures. At present, most guided wave technologies estimate the size of the flaw based on the reflected signal amplitude from the flaw compared to a known geometry reflection, such as a circumferential weld in a pipeline. This process, however, requires many assumptions to be made, such as weld geometry and flaw shape. Furthermore, it is highly dependent on the amplitude of the flaw reflection, which can vary based on many factors, such as attenuation and sensor installation. To improve sizing performance, especially depth estimation, and do so in a way that is not strictly amplitude dependent, this paper describes an approach to estimate the depth of a flaw based on a multimodal analysis. This approach eliminates the need of using geometric reflections for calibration and can be used for both pipeline and plate inspection applications. To verify the approach, a test set was manufactured on plate specimens with flaws of different widths and depths ranging from 5% to 100% of total wall thickness; 90% of these flaws were sized to within 15% of their true value. A description of the initial multimodal sizing strategy and results will be discussed.

Two different techniques for droplet sizing were applied for measurements in dense nozzle sprays. Measurements were carried out for different flow rates of water and intensity of air blowing in a purger. It was found that IPI and GPT distributions are essentially different. The change of air blowing substantially change droplets distribution for both IPI and GPT measurements. Important feature of developed GPT technique is application for helicity measurements.

The objective of this work is to demonstrate and validate model-based inversion techniques to characterize length, depth, width and orientation of surface-breaking cracks using eddy current NDE under varying probe conditions. A series of parametric studies of probe characteristics are presented for a fixed set of well-characterized flaws with varying length, depth, opening width and orientation angle. Results show inversion performance differences between probes with the same design specifications. Inversion results were also evaluated for a probe that was selectively controlled for varying probe liftoff, varying tilt in two directions, and orientation. Certain levels of probe tilt and liftoff were found to degrade the performance of the inversion technique. By using a model calibration process that incorporates the matching probe calibration data, better inversion results can be achieved, to a limited degree. There is a need to more appropriately adapt the model through the calibration fit to compensate ...

In comparison to manual NDT methods, mechanized NDT is considered to be more reliable for a number of reasons, one of which being that the role of the inspectors and, therewith, the potential for human error, have been reduced. However, human-automation interaction research suggests that in spite of its numerous benefits, automation can lead to new yet unknown risks. One of those risks is inappropriate reliance on automation, which can result in automation misuse and disuse. The aim of this study was to investigate the potential inappropriate use of automation (specifically - the automated aids) in NDT addressing therewith the prevalent belief in the high reliability of automation held by the NDT community. To address this issue, 70 NDT trainees were asked to control the results of an eddy current data evaluation, allegedly provided by an automated aid, i.e. indication detection and sizing software. Seven errors were implemented into the task and it was measured to what extent the participants agreed with the aid. The results revealed signs of both misuse (agreeing with the aid even though it is incorrect) and disuse (disagreeing with the aid even though it is correct) of the aid that can affect the reliability with which inspections are carried out. Whereas misuse could be explained by a lower propensity to take risks and by a decreased verification behavior—possibly due to bias towards automation and complacent behavior—, disuse was assigned to problems in establishing the sizing criterion or to general difficulties in sizing. The implications of these results for the NDT praxis including suggestions for the decrease of automation bias are discussed.

This study presents an evaluation of a solid oxide fuel system modeled with its energy balance of plant components in order to recover its exhaust waste heat and develop a combined cooling, heating, and power system. A hydrogen-fueled SOFC is modeled in MATLAB and a 3D drawn building are imported into TRNSYS where system performances are assessed. An optimization approach is employed to find the best system sizing. Energetic and environmental assessments shows better performance as the system size increases which suggests the necessity of an economic study application.

Composite materials are today widely used in engineering applications because of superior strength-weight ratios offered by them as well as high structural performance and corrosion resistance. However defects such as fibre breakage, matrix cracking, de-bonding and delaminations in composites impact their structural integrity and reliability negatively and NDE techniques to rapidly identify such defects are valuable. Ultrasonic guided waves have over the years emerged as attractive tools for scanning of large structures and recently they have been considered for rapid inspection of plate and pipe installations. Air-coupled ultrasound for generation of Lamb waves is particularly attractive for composite applications in view of the non-contact inspection offered, as well as the possibilities for rapid mechanized scanning. In this paper we present damage identification and visualisation approaches for quasi-isotropic composite plate structures, based on air-coupled plate guided ultrasonic (Lamb) waves. In the implementation demonstrated, an 8-layered quasi-isotropic [0/+45/−45/90]s glass fibre reinforced plastics (GFRP) composite plate is interrogated using air-coupled pitch-catch guided ultrasound. Propagation of Lamb waves in the laminates and their interaction with delaminations of different sizes at various locations along the structure are studied using 3D finite element (FE) analysis. The visualization approach is validated using experiments, leading to quantitative predictions of defect parameters such as sizing, location and depth. The approach is also extended for the inspection of complex composite structural features such as I- and T-sections.

Digital radiography has made its way into in-the-field girth weld testing. With recent generations of detectors and x-ray tubes it is possible to reach the image quality desired in standards as well as the speed of inspection desired to be competitive with film radiography and automated ultrasonic testing. This paper will show the application of these technologies in the RTD Rayscan system. The method for achieving an image quality that complies with or even exceeds prevailing industrial standards will be presented, as well as the application on pipeline girth welds with CRA layers. A next step in development will be to also achieve a measurement of weld flaw height to allow for performing an Engineering Critical Assessment on the weld. This will allow for similar acceptance limits as currently used with Automated Ultrasonic Testing of pipeline girth welds. Although a sufficient sizing accuracy was already demonstrated and qualified in the TomoCAR system, testing in some applications is restricted to time limits. The paper will present some experiments that were performed to achieve flaw height approximation within these time limits.

This study presents an experimental and modeling study for damage detection and quantification in riveted lap joints. Embedded lead zirconate titanate piezoelectric (PZT) ceramic wafer-type sensors are employed to perform in-situ non-destructive testing during fatigue cyclical loading. A multi-feature integration method is developed to quantify the crack size using signal features of correlation coefficient, amplitude change, and phase change. In addition, probability of detection (POD) model is constructed to quantify the reliability of the developed sizing method. Using the developed crack size quantification method and the resulting POD curve, probabilistic fatigue life prediction can be performed to provide comprehensive information for decision-making. The effectiveness of the overall methodology is demonstrated and validated using several aircraft lap joint specimens from different manufactures and under different loading conditions.

Tomographic corrosion monitoring techniques have been developed, using two rings of sensors around the circumference of a pipe. This technique is capable of providing a detailed wall thickness map, however this might not be the only type of structural damage. Therefore this concept is expanded to detect and size cracks and small corrosion defects like root corrosion. The expanded concept uses two arrays of guided-wave transducers, collecting both reflection and transmission data. The data is processed such that the angle-dependent reflectivity is obtained without using a baseline signal of a defect-free situation. The angle-dependent reflectivity is the input of an inversion scheme that calculates a crack depth profile. From this profile, the depth and length of the crack can be determined. Preliminary experiments show encouraging results. The depth sizing accuracy is in the order of 0.5 mm.

The study presents a method and application of risk assessment methodology for turbine rotor fatigue failure using probabilistic ultrasonic nondestructive evaluations. A rigorous probabilistic modeling for ultrasonic flaw sizing is developed by incorporating the model-assisted probability of detection, and the probability density function (PDF) of the actual flaw size is derived. Two general scenarios, namely the ultrasonic inspection with an identified flaw indication and the ultrasonic inspection without flaw indication, are considered in the derivation. To perform estimations for fatigue reliability and remaining useful life, uncertainties from ultrasonic flaw sizing and fatigue model parameters are systematically included and quantified. The model parameter PDF is estimated using Bayesian parameter estimation and actual fatigue testing data. The overall method is demonstrated using a realistic application of steam turbine rotor, and the risk analysis under given safety criteria is provided to support maintenance planning.

Accurate determination of particle size distribution is critical to achieving optimal combustion efficiency and minimum pollutant emissions in both biomass and biomass/coal fired power plants. This paper presents an instrumentation system for online continuous measurement of particle size distribution based on acoustic emission (AE) method. Impulsive AE signals arising from impacts of particles with a metallic waveguide protruding into the flow carry information about the particle size. With detailed information about the generation, propagation and detection of impact AE signals, the particle size can be quantitatively characterized. Experimental results obtained with glass beads demonstrate the capability of the system to discriminate particles of different sizes from the recorded AE signals. The system has several appealing features such as online measurement, high sensitivity, simple structure, minimum invasiveness and low cost, which make it well suited for industrial applications.

Robust detection of vertical cracks in high-density polyethylene (HDPE) pipes is a challenging task for the majority of nondestructive testing (NDT) techniques. Vertical cracks are specifically referred to those whose largest planar view is parallel to the signal direction of propagation, leaving very little signal to be scattered for detection. In such pipes this commonly occurs between two pipes sections when thermally or adhesively joined. This work presents the utility and efficacy of three-dimensional (3D) millimeter wave holographical imaging based on synthetic aperture radar (SAR) algorithm for imaging such cracks. Such a 3D millimeter wave image can readily represent the type, size, and location of various flaws within a structure. Two-dimensional (2D) slices of the 3D image, at different orientations, can also be readily produced showing the cross-sectional views of the structure and flaws, further aiding in identifying, and sizing a flaw or vertical crack. Imaging results for planner and curved (pipe section) specimen with machined flaws are presented. These images are produced using a novel field-portable, small, and low-cost wideband millimeter-wave reflectometer capable of rapid 3D image production.