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Reza Taherdangkoo
TU Bergakademie Freiberg, Institute of Geotechnics, Gustav-Zeuner-Str. 1, 09599 Freiberg, Germany

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Journal article
Published: 28 August 2021 in Applied Sciences
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The roadway stability has been regarded as the main challenging issue for safety and productivity of deep underground coal mines, particularly where roadways are affected by coal mining activities. This study investigates the −740 m main roadway in the Jining No. 2 Coal Mine to provide a theoretical basis for the stability control of the main deep roadway affected by disturbances of adjacent working activities. Field surveys, theoretical analyses, and numerical simulations are used to reveal mechanisms of the coal mining disturbance. The field survey shows that the deformation of roadway increases when the work face advances near the roadway group. Long working face mining causes the key strata to collapse based on the key strata theory and then disturbs the adjacent roadway group. When the working face is 100 m away from the stop-mining line, the roadway group is affected by the mining face, and the width roadway protection coal pillar is determined to be about 100 m. Flac3D simulations prove the accuracy of the theoretical result. Through reinforcement and support measures for the main roadway, the overall strength of the surrounding rock is enhanced, the stability of the surrounding rock of the roadway is guaranteed, and the safe production of the mine is maintained.

ACS Style

Yuantian Sun; Ruiyang Bi; Qingliang Chang; Reza Taherdangkoo; Junfei Zhang; Junbo Sun; Jiandong Huang; Guichen Li. Stability Analysis of Roadway Groups under Multi-Mining Disturbances. Applied Sciences 2021, 11, 7953 .

AMA Style

Yuantian Sun, Ruiyang Bi, Qingliang Chang, Reza Taherdangkoo, Junfei Zhang, Junbo Sun, Jiandong Huang, Guichen Li. Stability Analysis of Roadway Groups under Multi-Mining Disturbances. Applied Sciences. 2021; 11 (17):7953.

Chicago/Turabian Style

Yuantian Sun; Ruiyang Bi; Qingliang Chang; Reza Taherdangkoo; Junfei Zhang; Junbo Sun; Jiandong Huang; Guichen Li. 2021. "Stability Analysis of Roadway Groups under Multi-Mining Disturbances." Applied Sciences 11, no. 17: 7953.

Journal article
Published: 19 August 2021 in Sustainability
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Pre-grouting as an effective means for improving the stability of roadways can reduce maintenance costs and maintain safety in complex mining conditions. In the Guobei coal mine in China, a cement pre-grouting technique was adopted to enhance the overall strength of soft coal mass and provide sufficient support for the roadway. However, there are very limited studies about the effect of grouting on the overall strength of coal in the laboratory. In this paper, based on the field observation of a coal-grout structure after grouting, a series of direct shear tests were conducted on coal and grouted coal specimens to quantitatively evaluate the quality improvement of grouted coal mass. The results showed that the peak and residual shear strength, cohesion, friction angle and the shear stiffness of grouted coal were significantly improved with the increase of the diameter of grout column. Linear regression models were established for predicting these mechanical parameters. In addition, three failure models associated with coal and grouted coal specimens were revealed. According to microstructure and macroscopic failure performance of specimens, the application of the proposed models and some methods for further improving the stability of grouted coal mass were suggested. The research can provide the basic evaluation and guideline for the parametric design of cement pre-grouting applications in soft coal mass.

ACS Style

Yuantian Sun; Guichen Li; Junfei Zhang; Junbo Sun; Jiandong Huang; Reza Taherdangkoo. New Insights of Grouting in Coal Mass: From Small-Scale Experiments to Microstructures. Sustainability 2021, 13, 9315 .

AMA Style

Yuantian Sun, Guichen Li, Junfei Zhang, Junbo Sun, Jiandong Huang, Reza Taherdangkoo. New Insights of Grouting in Coal Mass: From Small-Scale Experiments to Microstructures. Sustainability. 2021; 13 (16):9315.

Chicago/Turabian Style

Yuantian Sun; Guichen Li; Junfei Zhang; Junbo Sun; Jiandong Huang; Reza Taherdangkoo. 2021. "New Insights of Grouting in Coal Mass: From Small-Scale Experiments to Microstructures." Sustainability 13, no. 16: 9315.

Journal article
Published: 06 June 2021 in Journal of Contaminant Hydrology
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The upward migration of methane from natural gas wells associated with fracking operations may lead to contamination of groundwater resources and surface leakage. Numerical simulations of methane transport in the subsurface environment require knowledge of methane solubility in the aqueous phase. This study employs machine learning (ML) algorithms to predict methane solubility in aquatic systems for temperatures ranging from 273.15 to 518.3 K and pressures ranging from 1 to 1570 bar. Four regression algorithms including regression tree (RT), boosted regression tree (BRT), least square support vector machine (LSSVM) and Gaussian process regression (GPR) were utilized for predicting methane solubility in pure water and mixed aquatic systems containing Na+, K+, Ca2+, Mg2+, Cl− and SO4-2. The experimental data collected from the literature were used to implement the models. We used Grid search (GS), Random search (RS) and Bayesian optimization (BO) for tuning hyper-parameters of the ML models. Moreover, the predicted values of methane solubility were compared against Spivey et al. (2004) and Duan and Mao (2006) equations of state. The results show that the BRT-BO model is the most rigorous model for the prediction task. The coefficient of determination (R2) between experimental and predicted values is 0.99 and the mean squared error (MSE) is 1.19 × 10−7. The performance of the BRT-BO model is satisfactory, showing an acceptable agreement with experimental data. The comparison results demonstrated the superior performance of the BRT-BO model for predicting methane solubility in aquatic systems over a span of temperature, pressure and ionic strength that occurs in deep marine environments.

ACS Style

Reza Taherdangkoo; Quan Liu; Yixuan Xing; Huichen Yang; Viet Cao; Martin Sauter; Christoph Butscher. Predicting methane solubility in water and seawater by machine learning algorithms: Application to methane transport modeling. Journal of Contaminant Hydrology 2021, 242, 103844 .

AMA Style

Reza Taherdangkoo, Quan Liu, Yixuan Xing, Huichen Yang, Viet Cao, Martin Sauter, Christoph Butscher. Predicting methane solubility in water and seawater by machine learning algorithms: Application to methane transport modeling. Journal of Contaminant Hydrology. 2021; 242 ():103844.

Chicago/Turabian Style

Reza Taherdangkoo; Quan Liu; Yixuan Xing; Huichen Yang; Viet Cao; Martin Sauter; Christoph Butscher. 2021. "Predicting methane solubility in water and seawater by machine learning algorithms: Application to methane transport modeling." Journal of Contaminant Hydrology 242, no. : 103844.

Original article
Published: 18 September 2020 in Environmental Geology
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Methane contamination of drinking water resources is one of the major concerns associated with unconventional gas development. This study assesses the potential contamination of shallow groundwater via methane migration from a leaky natural gas well through overburden rocks, following hydraulic fracturing. A two-dimensional, two-phase, two-component numerical model is employed to simulate methane and brine upward migration toward shallow groundwater in a generic sedimentary basin. A sensitivity analysis is conducted to examine the influence of methane solubility, capillary pressure–saturation relationship parameters and residual water saturation of overburden rocks, gas leakage rate from the well, tilted formations, and low-permeability sediments (i.e., claystones) on the transport of fluids. Results show that the presence of lithological barriers is the most important factor controlling the temporal–spatial distribution of methane in the subsurface and the arrival time to shallow groundwater. A pulse of high leakage rate is required for early manifestation of methane in groundwater wells. Simulations reveal that the presence of tilted features could further explain fast-growing methane contamination and extensive lateral spreading reported in field studies.

ACS Style

Reza Taherdangkoo; Alexandru Tatomir; Martin Sauter. Modeling of methane migration from gas wellbores into shallow groundwater at basin scale. Environmental Geology 2020, 79, 1 -16.

AMA Style

Reza Taherdangkoo, Alexandru Tatomir, Martin Sauter. Modeling of methane migration from gas wellbores into shallow groundwater at basin scale. Environmental Geology. 2020; 79 (18):1-16.

Chicago/Turabian Style

Reza Taherdangkoo; Alexandru Tatomir; Martin Sauter. 2020. "Modeling of methane migration from gas wellbores into shallow groundwater at basin scale." Environmental Geology 79, no. 18: 1-16.

Preprint content
Published: 23 March 2020
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Hydraulic fracturing fluid migration from the deep subsurface along abandoned wells may pose contamination threats to shallow groundwater systems. This study investigates the application of a nonlinear autoregressive (NAR) neural network to predict leakage rates of fracturing fluid to a shallow aquifer in the presence of an abandoned well. The NAR network was trained using the Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms. The dataset employed in this study includes fracturing fluid leakage rates to the aquifer overlying the Posidonia shale formation in the North German Basin (Taherdangkoo et al. 2019). We evaluated the performance of developed models based on the mean squared errors (MSE) and coefficient of determination (R2). The results indicate the robustness and compatibility of NAR-LM and NAR-BR models in predicting fracturing fluid leakage to the aquifer. This study shows that NAR neural networks are useful and hold a considerable potential for assessing the potential groundwater impacts of unconventional gas development.

References

Taherdangkoo, R., Tatomir, A., Anighoro, T., & Sauter, M. (2019). Modeling fate and transport of hydraulic fracturing fluid in the presence of abandoned wells. Journal of Contaminant Hydrology, 221, 58–68. https://doi.org/10.1016/j.jconhyd.2018.12.003

ACS Style

Reza Taherdangkoo; Alexandru Tatomir; Mohammad Taherdangkoo; Martin Sauter. Nonlinear autoregressive neural networks to predict fracturing fluid flow into shallow groundwater. 2020, 1 .

AMA Style

Reza Taherdangkoo, Alexandru Tatomir, Mohammad Taherdangkoo, Martin Sauter. Nonlinear autoregressive neural networks to predict fracturing fluid flow into shallow groundwater. . 2020; ():1.

Chicago/Turabian Style

Reza Taherdangkoo; Alexandru Tatomir; Mohammad Taherdangkoo; Martin Sauter. 2020. "Nonlinear autoregressive neural networks to predict fracturing fluid flow into shallow groundwater." , no. : 1.

Journal article
Published: 17 March 2020 in Water
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Hydraulic fracturing of horizontal wells is an essential technology for the exploitation of unconventional resources, but led to environmental concerns. Fracturing fluid upward migration from deep gas reservoirs along abandoned wells may pose contamination threats to shallow groundwater. This study describes the novel application of a nonlinear autoregressive (NAR) neural network to estimate fracturing fluid flow rate to shallow aquifers in the presence of an abandoned well. The NAR network is trained using the Levenberg–Marquardt (LM) and Bayesian Regularization (BR) algorithms and the results were compared to identify the optimal network architecture. For NAR-LM model, the coefficient of determination (R2) between measured and predicted values is 0.923 and the mean squared error (MSE) is 4.2 × 10−4, and the values of R2 = 0.944 and MSE = 2.4 × 10−4 were obtained for the NAR-BR model. The results indicate the robustness and compatibility of NAR-LM and NAR-BR models in predicting fracturing fluid flow rate to shallow aquifers. This study shows that NAR neural networks can be useful and hold considerable potential for assessing the groundwater impacts of unconventional gas development.

ACS Style

Reza Taherdangkoo; Alexandru Tatomir; Mohammad Taherdangkoo; Pengxiang Qiu; Martin Sauter. Nonlinear Autoregressive Neural Networks to Predict Hydraulic Fracturing Fluid Leakage into Shallow Groundwater. Water 2020, 12, 841 .

AMA Style

Reza Taherdangkoo, Alexandru Tatomir, Mohammad Taherdangkoo, Pengxiang Qiu, Martin Sauter. Nonlinear Autoregressive Neural Networks to Predict Hydraulic Fracturing Fluid Leakage into Shallow Groundwater. Water. 2020; 12 (3):841.

Chicago/Turabian Style

Reza Taherdangkoo; Alexandru Tatomir; Mohammad Taherdangkoo; Pengxiang Qiu; Martin Sauter. 2020. "Nonlinear Autoregressive Neural Networks to Predict Hydraulic Fracturing Fluid Leakage into Shallow Groundwater." Water 12, no. 3: 841.

Review
Published: 28 February 2020 in Water
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Tracer testing is a mature technology used for characterizing aquatic flow systems. To gain more insights from tracer tests a combination of conservative (non-reactive) tracers together with at least one reactive tracer is commonly applied. The reactive tracers can provide unique information about physical, chemical, and/or biological properties of aquatic systems. Although, previous review papers provide a wide coverage on conservative tracer compounds there is no systematic review on reactive tracers yet, despite their extensive development during the past decades. This review paper summarizes the recent development in compounds and compound classes that are exploitable and/or have been used as reactive tracers, including their systematization based on the underlying process types to be investigated. Reactive tracers can generally be categorized into three groups: (1) partitioning tracers, (2) kinetic tracers, and (3) reactive tracers for partitioning. The work also highlights the potential for future research directions. The recent advances from the development of new tailor-made tracers might overcome existing limitations.

ACS Style

Viet Cao; Mario Schaffer; Reza Taherdangkoo; Tobias Licha. Solute Reactive Tracers for Hydrogeological Applications: A Short Review and Future Prospects. Water 2020, 12, 653 .

AMA Style

Viet Cao, Mario Schaffer, Reza Taherdangkoo, Tobias Licha. Solute Reactive Tracers for Hydrogeological Applications: A Short Review and Future Prospects. Water. 2020; 12 (3):653.

Chicago/Turabian Style

Viet Cao; Mario Schaffer; Reza Taherdangkoo; Tobias Licha. 2020. "Solute Reactive Tracers for Hydrogeological Applications: A Short Review and Future Prospects." Water 12, no. 3: 653.

Journal article
Published: 21 December 2018 in Journal of Contaminant Hydrology
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Hydraulic fracturing in shale/tight gas reservoirs creates fracture network systems that can intersect pre-existing subsurface flow pathways, e.g. fractures, faults or abandoned wells. This way, hydraulic fracturing operations could possibly pose environmental risks to shallow groundwater systems. This paper explores the long-term (>30 years) flow and transport of fracturing fluids into overburden layers and groundwater aquifers through a leaky abandoned well, using the geological setting of North German Basin as a case study. A three-dimensional model consisting of 15 sedimentary layers with three hydrostratigraphic units representing the hydrocarbon reservoir, overburden, and the aquifer is built. The model considers one perforation location at the first section of the horizontal part of the well, and a discrete hydraulic fracture intersecting an abandoned well. A sensitivity analysis is carried out to quantify and understand the influence of a broad spectrum of field possibilities (reservoir properties, overburden properties, salinity, abandoned well properties and its proximity to hydraulic fractures) on the flow of fracturing fluid to shallower permeable strata. The model results suggest the spatial properties of the abandoned well as well as its distance from the hydraulic fracture are the most important factors influencing the vertical flow of fracturing fluid. It is observed that even for various field settings, only a limited amount fracturing fluid can reach the aquifer in a long-term period.

ACS Style

Reza Taherdangkoo; Alexandru Tatomir; Tega Anighoro; Martin Sauter. Modeling fate and transport of hydraulic fracturing fluid in the presence of abandoned wells. Journal of Contaminant Hydrology 2018, 221, 58 -68.

AMA Style

Reza Taherdangkoo, Alexandru Tatomir, Tega Anighoro, Martin Sauter. Modeling fate and transport of hydraulic fracturing fluid in the presence of abandoned wells. Journal of Contaminant Hydrology. 2018; 221 ():58-68.

Chicago/Turabian Style

Reza Taherdangkoo; Alexandru Tatomir; Tega Anighoro; Martin Sauter. 2018. "Modeling fate and transport of hydraulic fracturing fluid in the presence of abandoned wells." Journal of Contaminant Hydrology 221, no. : 58-68.

Journal article
Published: 22 August 2018 in Advances in Geosciences
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Hydraulic fracturing for natural gas extraction from unconventional reservoirs has not only impacted the global energy landscape but has also raised concerns over its potential environmental impacts. The concept of “features, events and processes” (FEP) refers to identifying and selecting the most relevant factors for safety assessment studies. In the context of hydraulic fracturing we constructed a comprehensive FEP database and applied it to six key focused scenarios defined under the scope of FracRisk project (http://www.fracrisk.eu, last access: 17 August 2018). The FEP database is ranked to show the relevance of each item in the FEP list per scenario. The main goal of the work is to illustrate the FEP database applicability to develop a conceptual model for regional-scale stray gas migration.

ACS Style

Alexandru Tatomir; Christopher McDermott; Jacob Bensabat; Holger Class; Katriona Edlmann; Reza Taherdangkoo; Martin Sauter. Conceptual model development using a generic Features, Events, and Processes (FEP) database for assessing the potential impact of hydraulic fracturing on groundwater aquifers. Advances in Geosciences 2018, 45, 185 -192.

AMA Style

Alexandru Tatomir, Christopher McDermott, Jacob Bensabat, Holger Class, Katriona Edlmann, Reza Taherdangkoo, Martin Sauter. Conceptual model development using a generic Features, Events, and Processes (FEP) database for assessing the potential impact of hydraulic fracturing on groundwater aquifers. Advances in Geosciences. 2018; 45 ():185-192.

Chicago/Turabian Style

Alexandru Tatomir; Christopher McDermott; Jacob Bensabat; Holger Class; Katriona Edlmann; Reza Taherdangkoo; Martin Sauter. 2018. "Conceptual model development using a generic Features, Events, and Processes (FEP) database for assessing the potential impact of hydraulic fracturing on groundwater aquifers." Advances in Geosciences 45, no. : 185-192.

Journal article
Published: 01 September 2017 in Energy Procedia
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ACS Style

Reza Taherdangkoo; Alexandru Tatomir; Robert Taylor; Martin Sauter. Numerical investigations of upward migration of fracking fluid along a fault zone during and after stimulation. Energy Procedia 2017, 125, 126 -135.

AMA Style

Reza Taherdangkoo, Alexandru Tatomir, Robert Taylor, Martin Sauter. Numerical investigations of upward migration of fracking fluid along a fault zone during and after stimulation. Energy Procedia. 2017; 125 ():126-135.

Chicago/Turabian Style

Reza Taherdangkoo; Alexandru Tatomir; Robert Taylor; Martin Sauter. 2017. "Numerical investigations of upward migration of fracking fluid along a fault zone during and after stimulation." Energy Procedia 125, no. : 126-135.

Journal article
Published: 01 January 2016 in International Journal of Petroleum Engineering
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Naturally fractured reservoirs represent a significant percentage of oil and gas plays throughout the world. Precise estimation of fracture density is an indubitable challenge in characterisation of fractured reservoirs. In this paper, a method based on regression analysis is applied to estimate fracture density in fractured zones from well logs data. For this purpose, all available petrophysical logs (Caliper, CGR, Uranium, RHOB, DT, NPHI, PEF and RT) plus additional fracture information from image logs are used. In order to develop an estimator with high capability of generalisation, linear and nonlinear regressions are used. The method was applied to four wells in Marun oilfield located in the south western of Iran. The estimation results demonstrate the effectiveness of the method.

ACS Style

Reza Taherdangkoo; Mohammad Abdideh. Fracture density estimation from well logs data using regression analysis: validation based on image logs (Case study: South West Iran). International Journal of Petroleum Engineering 2016, 2, 289 .

AMA Style

Reza Taherdangkoo, Mohammad Abdideh. Fracture density estimation from well logs data using regression analysis: validation based on image logs (Case study: South West Iran). International Journal of Petroleum Engineering. 2016; 2 (4):289.

Chicago/Turabian Style

Reza Taherdangkoo; Mohammad Abdideh. 2016. "Fracture density estimation from well logs data using regression analysis: validation based on image logs (Case study: South West Iran)." International Journal of Petroleum Engineering 2, no. 4: 289.

Journal article
Published: 01 January 2016 in International Journal of Petroleum Engineering
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Detection of fractured zones is an indisputable challenge in fractured reservoir characterisation. Although fracture identification from core data and image logs are direct and effective, they are costly and not commonly used. In this study, the discrete wavelet transform (DWT) was applied to decompose water saturation log data to detect fractured zones and calculate the number of fractures. Herein, the energy matching strategy and wavelet packet were used to select the optimum mother wavelet. The uranium log was applied as a filter to reduce errors which improved the accuracy of results for prediction of fractured zones by 90%. Finally, the relationship between signal energy of water saturation log and the number of fractures in each fractured zone was studied. The proposed method was successfully tested in wells in the Asmari formation (South Western Iran) and provides significant scope for application in other analogous field.

ACS Style

Reza Taherdangkoo; Mohammad Abdideh. Application of wavelet transform to detect fractured zones using conventional well logs data (case study: southwest of Iran). International Journal of Petroleum Engineering 2016, 2, 125 .

AMA Style

Reza Taherdangkoo, Mohammad Abdideh. Application of wavelet transform to detect fractured zones using conventional well logs data (case study: southwest of Iran). International Journal of Petroleum Engineering. 2016; 2 (2):125.

Chicago/Turabian Style

Reza Taherdangkoo; Mohammad Abdideh. 2016. "Application of wavelet transform to detect fractured zones using conventional well logs data (case study: southwest of Iran)." International Journal of Petroleum Engineering 2, no. 2: 125.

Journal article
Published: 01 January 2015 in International Journal of Petroleum Engineering
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In this paper, we address the problem of inaccuracy in evaluating bottom hole circulating pressure (BHCP) in the petroleum industry by proposing a new predicting scheme. This scheme utilises a modified version of the stem cells algorithm (MSCA), recently introduced as a powerful meta-heuristic optimisation method, along with the back propagation (BP) training strategy to build a three-layer artificial neural network (ANN) as a predictive scheme. This new method is able to predict the complex relationship between inputs and outputs of a highly nonlinear system such as BHCP more accurately. The results by applying the proposed method compared with those by applying previous predicting methods used for BHCP demonstrate the superiority of the proposed method in terms of accuracy and time consumption.

ACS Style

Reza Taherdangkoo; Mohammad Taherdangkoo. Modified stem cells algorithm-based neural network applied to bottom hole circulating pressure in underbalanced drilling. International Journal of Petroleum Engineering 2015, 1, 178 .

AMA Style

Reza Taherdangkoo, Mohammad Taherdangkoo. Modified stem cells algorithm-based neural network applied to bottom hole circulating pressure in underbalanced drilling. International Journal of Petroleum Engineering. 2015; 1 (3):178.

Chicago/Turabian Style

Reza Taherdangkoo; Mohammad Taherdangkoo. 2015. "Modified stem cells algorithm-based neural network applied to bottom hole circulating pressure in underbalanced drilling." International Journal of Petroleum Engineering 1, no. 3: 178.

Journal article
Published: 16 September 2014 in International Journal of Applied Electromagnetics and Mechanics
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ACS Style

Mohammad Taherdangkoo; Reza Taherdangkoo. Modified BNMR algorithm applied to Loney's solenoid benchmark problem. International Journal of Applied Electromagnetics and Mechanics 2014, 46, 683 -692.

AMA Style

Mohammad Taherdangkoo, Reza Taherdangkoo. Modified BNMR algorithm applied to Loney's solenoid benchmark problem. International Journal of Applied Electromagnetics and Mechanics. 2014; 46 (3):683-692.

Chicago/Turabian Style

Mohammad Taherdangkoo; Reza Taherdangkoo. 2014. "Modified BNMR algorithm applied to Loney's solenoid benchmark problem." International Journal of Applied Electromagnetics and Mechanics 46, no. 3: 683-692.