Results Of Model Research Articles

Full-radius integrated modelling of ASDEX Upgrade L-modes including impurity transport and radiation

An integrated framework that demonstrates multi-species, multi-channel modelling capabilities for the prediction of impurity density profiles and their feedback on the main plasma through radiative cooling and fuel dilution is presented. It combines all presently known theoretical elements in the local description of quasilinear turbulent and neoclassical impurity transport, using the models TGLF-SAT2 and FACIT. These are coupled to the STRAHL code for impurity sources and radiation inside the ASTRA transport solver. The workflow is shown to reproduce experimental results in full-radius L-mode modelling. In particular, a set of ASDEX Upgrade L-modes with differing heating power mixtures and plasma currents are simulated, including boron (B) and tungsten (W) as intrinsic impurities. The increase of predicted confinement with higher current and the reduction of core W peaking with higher central wave heating are demonstrated. Furthermore, a highly radiative L-mode scenario featuring an X-point radiator (XPR) with two intrinsic (B, W) and one seeded argon (Ar) species is simulated, and its measured radiated power and high confinement are recovered by the modelling. The stabilizing effect of impurities on turbulence is analysed and a simple model for the peripheral X-point radiation is introduced. A preliminary full-radius simulation of an H-mode phase of this same discharge, leveraging recent work on the role of the E×B shearing at the edge, shows promising results.

Why do Citizens Choose to Read Fact-Checks in the Context of the Russian War in Ukraine? The Role of Directional and Accuracy Motivations in Nineteen Democracies

The recent surge of false information accompanying the Russian invasion of Ukraine has re-emphasized the need for interventions to counteract disinformation. While fact-checking is a widely used intervention, we know little about citizen motivations to read fact-checks. We tested theoretical predictions related to accuracy-motivated goals (i.e., seeking to know the truth) versus directionally-motivated goals (i.e., seeking to confirm existing beliefs) by analyzing original survey data ( n = 19,037) collected in early April to late May 2022 in nineteen countries, namely Austria, Belgium, Brazil, Czech Republic, Denmark, France, Germany, Greece, Hungary, Italy, Netherlands, Poland, Romania, Serbia, Spain, Sweden, Switzerland, UK, and USA. Survey participants read ten statements about the Russian war in Ukraine and could opt to see fact-checks for each of these statements. Results of mixed models for three-level hierarchical data (level 1: statements, level 2: individuals, and level 3: countries) showed that accuracy motivations were better explanations than directional motivations for the decision to read fact-checks about the Russian war in Ukraine.

On the Effect of 3D Wave Propagation on 2D Regional‐Scale Velocity Model Building

AbstractActive seismic surveys are routinely employed by academia to study geological structure of the crust and upper mantle. Wavefields generated during these surveys are sampled at the receiver locations, but the wave‐paths traveled from a source to a sensor remains unknown. Although seismic acquisition layouts designed to investigate complex crustal‐scale environments are often two‐dimensional, the seismogram recorded at the receiver location represents information gathered along the three‐dimensional wavepaths that might offset from the 2D source/receiver profile along its transverse direction. This so‐called 3D‐effect distorts the results of 2D seismic imaging, which is unable to handle the out‐of‐plane propagation. Despite the numerous 2D seismic imaging case studies, the assessment of this issue is often overlooked. However, the problem exists ‐ especially for crustal‐scale profiles, where seismic energy propagates over distances of hundreds of kilometers and probes different crustal units. In this work we investigate the impact of 3D‐effect on the results of 2D velocity model building from the academic ocean‐bottom seismometer data. We show with polarization analysis how the 3D‐effect can manifest itself in the data domain. Using various scenarios of acquisition we evaluate the imprint of the out‐of‐plane propagation on the data and the results of full‐waveform inversion. We show that 2D velocity model building from the seismic profiles acquired in the complex geological setting can lead to wrong solution. Looking for the remedy to this issue we couple different configurations of acquisition geometries with 3D full‐waveform inversion that allow to handle the 3D effect and provide correct model reconstruction.

Diurnal Change of NDVI from UAV in Trees of a Temperate Unavenged Forest Stand

NDVI elucidates the ecophysiological mechanisms faced by vegetation. With the flexibility and versatility of unmanned aerial vehicles (UAVs), temporal, spatial and spectral resolutions have been useful in supporting decision-making. Here, we modeled diurnal change in the NDVI derived from UAV imagery for individual trees in a natural forest stand. Eight flights were conducted during daylight hours over one day to assess the dynamics of the NDVI of the genera Pinus, Juniperus, and Quercus. The results showed unstable NDVI values over time, with a parabolic quadratic trend in the model. The NDVI reached its maximum around 13:00 h and the values differed significantly according to genus: the highest value was found in Pinus with significant differences presented with Juniperus and Quercus, which showed similar values between them (p=0.533). As a validation strategy, we test the model generated using 124 trees independent of those that were sampled, which strengthened our results in terms of reliability. The similarities of statistical parameters confer a high variability of application of the results in models of simulation of similar forests ecosystems. We recommend to study more spectral indices of vegetation, including calibration of the sensor, particularly in longer-term seasonal studies. We conclude that the NDVI measured using UAV should consider image acquisition time to calibrate the records and thus improve the interpretation of results.

Combining groundwater and game-theoretical models for determining the sustainable yield in a heavily stressed aquifer system

Sustainable groundwater abstraction is nowadays widely debated and the application of criteria available in the literature is not easy depending on site-specific features of the systems. In the Tivoli Plain (Rome, Italy) the same groundwater resource is exploited by an important thermal plant for therapeutic purposes and is subject to dewatering for the extraction of travertine by numerous quarries, thus representing a significant case of conflict among different resources users. The study proposes a new approach in defining the sustainability of groundwater exploitation by matching the results of groundwater flow model with those of a game model. From the conceptual hydrogeological model and the numerical flow simulations, the sustainability conditions for the groundwater withdrawals are obtained and the hydrodynamic interferences between the different users are assessed. The results of numerical simulations were encapsulated in the game-theoretical model in order to find conceptual solutions to maximize the profit related to quarry’s economy and, at the same time, to limit the quantitative and qualitative decline of the thermal waters. Assuming that the sustainability of the groundwater abstraction from the quarry area depends on ensuring residual groundwater flow to the thermal springs and the river, a cooperative game among the different players has been developed. The strategy of a player is bound by the influence of dewatering on the springs and the river and the player’s utility is proportional to the total quantity of travertine extracted. Results indicate that the “price of sustainability” would be around a 23% reduction of the total exploited travertine volume, driven by an overall reduction in dewatering of about 31%, if compared to that necessary to reach the maximum depth of excavation. For the different groups of quarries the reduction of the pumping flow is not homogeneous but varies according to the position of the pumping center in the groundwater flow net and its distance from boundaries to be captured. Therefore, the combination of the flow model with the game model solutions appears to be a valuable tool to achieve sustainable groundwater management in a conflicting situation among different users. In addition, the game model allows to introduce other players and/or to find out other, non-cooperative solutions.

Determining the psycho-emotional state of the observed based on the analysis of video observations

This paper develops a system for determining the psycho-emotional state of the observed people based on the analysis of video surveillance with the application of artificial intelligence technology using hardware and software tools such as PoseNet, PyTorch, SQLite, FastAPI and Flask. In many areas of human endeavor, there is an urgent need for a surveillance system that can reliably function and detect suspicious activities. To solve this problem, this paper proposes a novel framework for a real-time surveillance system that automatically detects abnormal human activities. The system has been tested and validated in real environments. The results of testing artificial intelligence program models showed the best results (f1 score with values of 0.98–0.99). The weighted average value of the f1-score metric was 0.96, which is quite a high value. The use of PoseNet implemented with PyTorch allowed to accurately determine the pose of the person in the video and extract information about the position of different body parts. The peculiarity of this work lies in the development of artificial intelligence models for automatic detection of possible physical aggression in videos, in the methods of forming an optimal set of features for the development of AI models that identify the aggressor and the victim of bullying. The developed system has the potential to be a useful tool in various fields such as psychology, medicine, security and others where it is important to analyze the emotional state of people based on their physical manifestations. The obtained applied results can be used in educational institutions and in spheres where video analysis is necessary

Objective Function Distortion Reduction in Identification Technique of Composite Material Elastic Properties

In studies of structural mechanics, modal analysis, presented in this paper, is an important tool for analyzing the vibration of an object and its frequencies. In modal analysis, different modes of vibration and the frequencies that generate them are considered. The study covers the nondestructive identification of the elastic characteristics of materials, which involves stochastic algorithms and the application of reverse engineering (i.e., the comparison of reference eigenfrequencies with the results of mathematical models). Identification is achieved by minimizing the objective function—the smaller the value of the objective function, the higher the identification accuracy obtained. By changing the parameters of a material’s mathematical model during identification, certain (usually higher order) modes can change places in a natural frequency spectrum. This leads to the comparison of different order eigenfrequencies, slow convergence and poor accuracy of the identification process. The technique involved in this work is the mode-shape recognition of a specimen of material with an “incorrect” set of elastic properties. The results prove that the identification accuracy of a material’s elastic properties can be increased if an “incorrect” set of elastic properties is removed from the identification process. The research covers only numerical research, with a physical experiment simulation.

Evaluation of atmospheric indicators in the Adriatic coastal areas: a multi-hazards approach for a better awareness of the current and future climate

Increasing climate resilience to global warming is one of the main challenges of the last few decades. Effective local measures have to be adopted to provide concrete solutions to the current and expected impacts of climate change. This is the goal of the AdriaClim Italia-Croatia Interreg Project (https://www.italy-croatia.eu/web/adriaclim), aimed at supporting the development of regional and local climate change adaptation plans for the Adriatic coastal regions. For this purpose, an exhaustive number of atmospheric climate indicators have been identified and evaluated across nine pilot areas to assess the current and expected main climate hazards affecting these regions, considering the worst-case emissions scenario (Representative Concentration Pathway RCP 8.5). The proposed analyses are provided by the results of the regional climate atmospheric model developed within the AdriaClim Project. The selected climate indicators are used to assess the possible evolution of the climate hazard across the pilot areas, covering different hazards, such as thermal discomfort, drought, and hydrological instability. A site-dependent investigation of the atmospheric climate indicators is proposed to emphasize which regions are more affected than others by the investigated climate hazards, thus warranting more attention in defining and proposing new adaptation strategies. The results highlight increasing temperatures (up to +3°C) across the Adriatic coastal regions, with more emphasis on the Northern Adriatic, where the combined effect with the relevant decrease in precipitation (down to −2 mm/day) may lead to severe drought conditions in the coming decades. In contrast, precipitation-related diseases may hit more Central and South Italy than the Northern Adriatic, except for the Emilia-Romagna region, which is found to be highly sensitive to both hazard categories. Finally, it is relevant to emphasize that these analyses have to be carefully considered in supporting adaptation strategies due to the lack of uncertainty estimates representing a fundamental element for decision-makers.

Tire noise prediction based on transfer learning and multi-modal fusion

Vehicle traffic noise has become an important factor in urban noise pollution. With the increase in the number of new-energy vehicles, the current situation of tire/road noise as one of the main noise sources of automobiles is becoming increasingly prominent. Tire noise prediction is the basis for optimizing the design of low-noise tires, providing a reference basis for tire design with low-noise performance. This paper used deep learning methods to predict the noise performance of TBR radial tires. We obtained descriptive statistical features of tire structure and tread pattern images as input to the model, and used measured tire/road noise as output, then we constructed a multi-modal tire noise dataset. Comparing the prediction performance of three pre-trained transfer models such as Resnet18, VGG16, and Inception V3 on the tire pattern images, the Resnet18 had the best prediction effect. Resnet18 was selected as a feature extractor to extract image features, which fuse with the tire structural features at the feature level. The experiment constructed the TLMF-TRNP model to predict tire noise. The experimental results of the TLMF-TRNP model indicated that RMSE, MAE, and R2 were 0.1337, 0.0948, and 0.9864 respectively, achieving ideal prediction accuracy on a small-scale tire noise dataset and controlling the absolute error of the test tires within ±0.4 dB effectively. An accurate tire noise prediction model will provide a theoretical basis for tire design with low noise tires.

Ensemble projections of climate and streamflow in a typical basin of semi-arid steppes in Mongolian Plateau of 2021–2100

The Kherlen River is the main water source for Hulun Lake, the largest lake in northern China. Due to reduced inflow from the Kherlen River, Hulun Lake experienced rapid shrinkage at the beginning of the 21st century, posing a serious threat to the ecological security of northern China. However, there is still a significant lack of projections regarding future climate change and its hydrological response in the Kherlen River basin. This study analyzed the projected climate and streamflow changes in the Kherlen River basin, a vital yet vulnerable international semi-arid steppes type basin. A combination of multi-model ensemble projection techniques, and the soil and water assessment tool (SWAT) model was employed to examine the spatio‒temporal changes in precipitation, temperature, streamflow, and the associated uncertainties in the basin. The temperature (an increase of 1.84–6.42 °C) and the precipitation (an increase of 15.0–46.0 mm) of Kherlen River basin are projected to increase by 2100, leading to a rise in streamflow (1.08–4.78 m3 s−1). The upstream of the Kherlen River exhibits remarkable increasing trends in precipitation, which has a dominant influence on streamflow of Kherlen River. Noteworthy increases in streamflow are observed in April, August, September, and October compared to the reference period (1971–2000). These findings suggest a partial alleviation of water scarcity in the Kherlen River, but also an increased likelihood of hydrological extreme events. The projected temperature increase in the Kherlen River basin exhibits the smallest uncertainty, while more pronounced uncertainties are found in precipitation and streamflow. The spread among the results of CMIP6 models is greater than that of CMIP5 models, with lower signal-to-noise ratio (SNR) values for temperature, precipitation, and streamflow.

Determining the Availability of Continuous Systems in Open Pits Using ANFIS and a Simulation Model

This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits.

CP-violating top-Higgs coupling in SMEFT

The total cross section of the process μ−μ+→νμν¯μtt¯H has strong dependence on the CP phase ξ of the top Yukawa coupling, where the ratio of ξ=π and ξ=0 (SM) grows to 670 at s=30 TeV, 3400 at 100 TeV. We study the cause of the strong energy dependence and identify its origin as the (E/mW)2 growth of the weak boson fusion sub-amplitudes, WL−WL+→tt¯H, with the two W's are longitudinally polarized. We repeat the study in the SMEFT framework where EW gauge invariance is manifest and find that the highest energy cross section is reduced to a quarter of the complex top Yukawa model result, with the same energy power. By applying the Goldstone boson (GB) equivalence theorem, we identify the origin of this strong energy growth of the SMEFT amplitudes as associated with the dimension-6 π−π+ttH vertex, where π± denotes the GB of W±. We obtain the unitarity bound on the coefficient of the SMEFT operator by studying all 2→2 and 2→3 cross sections in the J=0 channel.

A Viscoplasticity Model for Shale Creep Behavior and Its Application on Fracture Closure and Conductivity

Hydraulic fracturing is the main means for developing low-permeability shale reservoirs. Whether to produce artificial fractures with sufficient conductivity is an important criterion for hydraulic fracturing evaluation. The presence of clay and organic matter in the shale gives the shale creep, which makes the shale reservoir deform with time and reduces the conductivity of the fracture. In the past, the influence of shale creep was ignored in the study of artificial fracture conductivity, or the viscoelastic model was used to predict the conductivity, which represents an inaccuracy compared to the actual situation. Based on the classical Perzyna viscoplastic model, the elasto-viscoplastic constitutive model was obtained by introducing isotropic hardening, and the model parameters were obtained by fitting the triaxial compression creep experimental data under different differential stresses. Then, the constitutive model was programmed in a software platform using the return mapping algorithm, and the model was verified through the numerical simulation of the triaxial creep experiment. Then, the creep calculation results of the viscoplastic constitutive model and the power law model were compared. Finally, the viscoplastic constitutive model was applied to the simulation of the long-term conductivity of the fracture to study the influence of creep on the fracture width, and sensitivity analysis of the influencing factors of the fracture width was carried out. The results show that the numerical calculation results of the viscoplastic model were in agreement with the experimental data. The decrease in fracture width caused by pore pressure dissipation and reservoir creep after 72 h accounts for 32.07% of the total fracture width decrease.

Wetting of laser-textured tungsten substrate by molten tin

In the new generation of nuclear reactors, plasma facing components tend to be designed as Sn/W composite components. Considering the combination of tin and tungsten, the wettability evaluation of Sn/W system and its influencing factors are urgent work. Wetting experiments of Sn/W system were carried out in high vacuum by using modified sessile drop method. The results show that after vacuum annealing at 1100℃, good wettability (∼ 48° intrinsic contact angle) can be obtained quickly at 900℃ below the critical temperature of 1050℃. After laser surface texturing, the greater the roughness of the tungsten substrate surface, the better the wettability can be obtained. In essence, this correspondence is closely related to the geometric parameters of the grooves formed by laser etching, which corresponds to the predicted results in Wenzel model. The phenomenon of pinning and depinning of triple lines in the later stage of spreading is related to the spreading of liquid in the groove, and the spreading rate of the latter is faster than that of macro triple line, which leads to this phenomenon.

The impact of Caputo-Fabrizio fractional derivative and the dynamics of noise on worm propagation in wireless IoT networks

The main objective of this article on Wireless sensor network of the Internet of Things (IoT). The wireless network, B bluetooth network, infrared network, and other networks are the key components of the Internet of Things (IoT). The major emphasis of this work was on the impact of Caputo-Fabrizio fractional derivative on worm propagation in heterogeneous susceptible-exposed-infected-recovered wireless IoT devices. We first determined the equilibrium points and fundamental reproduction number for the Caputo-Fabrizio HSEIR system, and then we discussed the stability of the system at the worm propagation equilibrium point. Using the Picard-Lindeof method, we determine the existence and unique solution for the fractional CF system of the heterogeneous SEIR model. Next, we use fixed point theory to judge the stability of the iterative method. We investigate the impact of the derivative order on the behaviour of the resultant functions and acquired numerical values by computing the model's findings for various fractional orders. In addition, we compute the integer-order model's results and contrast them with the results of the fractional-order model. We develop a periodically intermittent controller driven by white noise with the amazing benefits of reduced cost and more adaptable control technique to restrict the spread of worms in wireless IoT networks. To clearly define the conditions for stability in probability one, we employ the stochastic analysis technique. Our results show that the nonlinear worm propagation system may be stabilised by intermittent stochastic perturbation under the parameters of intermittent time linked to stochastic perturbation strength. Our theoretical conclusions may be used to analyse the observable processes of the worm, design countermeasures to prevent its spread, and evaluate the consequences of various system parameters.

Ensemble learning with support vector machines algorithm for surface roughness prediction in longitudinal vibratory ultrasound-assisted grinding

It is critical to have an accurate prediction of surface roughness (Sa) in order to improve grinding productivity, reduce costs, and minimize the period of time required for trials and testing. Although many prediction methods have been developed, fewer studies have been conducted on the prediction of surface roughness in longitudinal ultrasonic vibration-assisted grinding (LUVAG). In this paper, a surface roughness prediction model algorithm based on ensemble learning of support vector machines (ELSVM) is proposed that can be used for surface roughness prediction of LUVAG alumina ceramics. This paper first details the development of the ELSVM surface roughness prediction model, which consists of four modules: the prepossessing module, the multi-algorithm regression module, the support vector machine algorithm (SVM) module, and the ensemble module. In addition, ELSVM was compared with four other machine learning methods based on experimental results for surface roughness prediction modeling. The error of ELSVM model was reduced by 6.3%, 7.9%, 8.9%, and 7.5%, respectively, compared to the individual prediction models such as I-AISPSO, I-AIS, SPSO, and KBaNN. Comparison results show that the ELSVM model has the lowest average ratio of Mean Absolute Error (MAE) for surface roughness prediction in LUVAG.

Mathematical Modeling and Finite Element Analysis of Wire Electro-Discharge Machining of Ceramic Particulate Reinforced Metal Matrix Composite Material

Objectives: A mathematical model is formulated for WEDM process for machining of Al/SiC/p to predict crater size, material removal rate for single spark discharge and same model is extended for multiple spark discharges which is not extensively studied in the literature. This was done by considering previous experimental data from the literature. Methods: A mathematical model predicts heat flux, radius of crater, material removal rate. Mode of heat transfer considered as conduction through workpiece. Material modeling is done considering the number of reinforced particles in the given volume. For random distribution of reinforced particles, a code is written in MATLAB software tool. Co-ordinates of these reinforced particles are extracted for FEA simulation in ABAQUS software tool. Material properties are considered as temperature dependent. This methodology is not adopted for MMCs. Findings: Results of theoretical model, FEA simulation and experimentation are compared. The predicted MRR by FEA simulation is 2% error at lower Ton values as 0.2µs and 0.4 µs to that of experimental MRR. Novelty: Crater size becomes shallow with increase in volume percentage of SiC particles resulting greater crater radius. With increased pulse on time MRR increases up to certain limit and then decreases. Keywords: WEDM, Modeling, MMC, FEA, MRR

Imaging Pleistocene volcanic edifices along the Egyptian Red Sea margin: Insights from reflection seismics and 3D constrained inversion of gravity and magnetic data

Several volcanic buildups have been documented using gravity and magnetic data at specific locations in the Northern Red Sea (NRS). Most of these volcanoes were never sampled, and only a few were imaged by seismic or bathymetry data. Furthermore, the confidentiality of commercial datasets does not allow adequate knowledge of these structures and their morphology and physical properties. In this study, 2D and 3D seismic reflection data and 3D constrained inversion of magnetic and gravity data have been used to infer densities and magnetic susceptibilities of volcanic features in the central part of the NRS and to evaluate the distribution and geometry. This study indicates that the results of the 3D inverted models show a good fit with the volcanic structures inferred from seismic data and, thus, that the inversion technique adopted can be a reliable tool for detecting other edifices where seismic data are missing. The 3D inverted density and magnetic susceptibility models suggest that at least eight isolated structures with similar gravity and magnetic properties exist in the study area. They are associated with high densities and magnetic susceptibility anomalies with average values of 2700 kg/m3 and 0.025 SI, respectively. These magmatic structures are deeply rooted in the sedimentary cover and emerge at elevations of 100 to >650 m relative to the seabed. They developed in a sector interpreted as containing thinned continental crust, accompanied by the ascension of magma through prominent rift-related normal faults. Magmatic activity likely started in the Pleistocene and continues to the present day.

Software Development of an Integrated Water Management Optimisation Model: the Roy Hill Mine Case Study Application

AbstractThis case study utilizes data from the Roy Hill iron ore mine, which has a daily water balance of abstraction, use, and surplus disposal, to address the problem of water management prediction at a global level by analysing the results of each modelling task and evaluating the presence of potential critical scenarios with an automated, mathematically rigorous tool. This paper describes the development of a software application that aggregates the results of the various water management models built for each task and provides the optimal utilisation of water to minimise water disposal and thereby maximise water usage. The business benefits of this work include the ability to calculate the net present cost (NPC) for new water infrastructure configurations in an integrated way. Investing in capital projects for water management and evaluating various scenarios helps determine the optimal water infrastructure configuration, minimizing operational impact. Traditionally, water has not been viewed as a significant cost; however, the cost of water infrastructure is now one of the highest business investments in the mining industry of the Pilbara region of Western Australia. Introducing the concept of NPC for water in the mining industry is a novel approach to making informed decisions on water expenses and investments. The key to success lies in using automated modelling to achieve the most efficient environmental and operational balance. This approach reduces individual decision-making and leads to a more cost-effective and beneficial production outcome.

An extended isogeometric boundary element formulation for three-dimensional linear elastic fracture mechanics

This paper presents a novel extended isogeometric boundary element formulation (XIGABEM) for three-dimensional linear elastic fracture mechanics. The formulation utilises the Dual BEM to accommodate coincident geometries for opposing crack surfaces, and inherits the well-known advantages of the NURBS basis as other isogeometric implementations. The originality herein involves the extension of the above-mentioned scheme to 3D using enrichment functions derived from asymptotic solutions for near-field crack tip displacements, in which Williams’ expansions are used on the crack surfaces and on the boundaries crossed by the crack front. Besides, Heaviside functions enrich external boundaries and allow the displacement discontinuity modelling. As with most enriched formulations, additional degrees of freedom are introduced; novel strategies are presented for the generation of auxiliary equations to recover a square system.Another key element of the proposed scheme is that the stress intensity factors are recovered directly from the solution vector and no post processing is required. Four applications demonstrate the formulation robustness, with results of models having comparatively few degrees of freedom comparing well against classical and other published results.