Method For Determination Of Parameters Research Articles

A Method for the Precise Determination of the Intramolecular Potential Energy Surface on the Basis of Microwave and Submillimeter-Wave Spectra: Diatomic Molecules as a Relevant Illustration.

A new method for the precise semiempirical determination of the basic parameters (structural parameters and parameters of the intramolecular potential energy surface, PES) of a molecule on the basis of highly accurate experimental data from the microwave and submillimeter-wave regions is suggested. The options and advantages of this method in comparison with the other methods of molecular PES determination are discussed using a diatomic molecule as an appropriate illustration. The HCl molecule is exploited as a suitable example. It is shown with this example that the use of a very limited number (ten for H35Cl and five for D35Cl) of submillimeter-wave line positions allows one to determine the values of the equilibrium rotational parameter, harmonic frequency, and anharmonic coefficients of the third, fourth, and fifth order with accuracy of 0.01%, 0.01%, 0.01%, 2.1%, and 10.1%, respectively, in comparison with the analogous results obtained from extensive infrared studies.

Study on Improving Recovery of Highly Heterogeneous Reservoirs by Unsteady Water Injection Technology

Unstable water injection can effectively improve the recovery ratio of reservoirs with strong heterogeneity. However, the oil displacement mechanism and the determination method of unstable water injection parameters still need to be clarified, especially for complex fracture reservoirs, which greatly restrict the popularization and development of unstable water injection technology. This paper studies unstable water injection technology in highly heterogeneous reservoirs from the core and reservoir scales, utilizing many displacement experiments and numerical simulations. The differences in oil displacement efficiency, remaining oil distribution, pressure field, and streamlines between continuous water injection and unstable water injection are compared and evaluated. Five flow stages of unstable injection and production are precisely divided, and the microscopic and macroscopic displacement mechanism is clarified. A numerical model of two injection wells and one production is established to determine the best time to implement unstable water injection technology. Based on the principle of pressure superposition, the expression of pressure field distribution between injection and production well in each period of unstable water injection is analytically solved. This formula has provided a new development parameter optimization method aiming at the maximum pressure fluctuation range and optimized the development technology parameters in the water injection process. The results show that precise control injection and production parameters can expand water swept volume, effectively improve the degree of reserve utilization, and improve the recovery of complex reservoirs by 3–7%, which provides a reliable basis for the practical implementation of unstable water injection technology.

Technological Trends for Electrical Machines and Drives Used in Small Wind Power Plants—A Review

High-power-range wind generators mainly employ classical variants, with the advantages of low cost, high robustness and acceptable energetic performance, while for low-power applications, the available electrical drive solutions are more numerous. This paper investigates the current trend in this field, indicating simple or complex structures, with or without self-excitation and with or without mechanical or magnetic transmission. The discussed variants are compared in terms of complexity, cost, fault-tolerance capability and estimated energetic performances but also the grid connectivity for standard conditions. The review is completed by testing options and conditions, as well as the methods for parameter determination, which have an important effect on the controllability of the entire system.

Determining articulation parameters using the Avantis 3D software, considering the individual hinge axis position

BACKGROUND: Axiography (condylography) is used to assess the temporomandibular joints (TMJ) function and obtain individual articulator settings. Creating a virtual patient with TMJ dysfunction and determining its individual articulation parameters considerably simplify the procedure and accelerate the diagnosis for further rehabilitation. AIM: To assess the potential of a virtual articulation system using the Avantis 3D software for determining angular parameters of mandibular movement, considering the individual hinge axis position. MATERIALS AND METHODS: The clinical phase of the study included 25 volunteers aged 18–30 years, without complaints of TMJ dysfunction, previous orthodontic treatment, and malocclusion. All volunteers underwent electronic condylography (axiography) using the CADIAX Diagnostic device; the movement of mandible heads during protrusion and mediotrusion was analyzed. The individual values of sagittal condylar inclination (SCI) and Bennett angle on the left and right were obtained. The individual hinge axis was determined, and special radiopaque markers were placed on the skin in the projection of its rotation. Additional markers were placed on the lower edge of the left orbital cavity. Using these markers, cone beam computed tomography (CBCT) was performed in all volunteers, with a 17.5×20.0 matrix size, to create a 3D project, compare CBCT findings with virtual dental models, and generate a reference plane. Virtual occlusion measurements were obtained in terminal positions (protrusion and laterotrusion) using the Trios 3 Basic Pod intraoral scanner. The Avantis 3D software was then used to create 3D scenes based on the obtained measurements and CBCT of the skull. The mean length of each path registered for virtual articulator settings in the Avantis 3D software was approximately 3 mm. The interarticular distance used for the analysis was recalculated using the Avantis 3D software to be equal to the standard intercondylar distance of the articulator, which is 110 mm. Individual SCI and Bennett angle values were obtained for all study subjects. The experimental phase involved phantom models installed in a fully adjustable articulator Reference SL. CBCT was performed with an installed articulator and a maxillary cast, in a zero position, with closed center locks, which was matched to the maxilla present in the CT scan, and a 3D scene was created to measure SCI and Bennett angle values. After detecting the articulator’s hinge axis, electronic measurements of movement were taken, with a predefined SCI of 20–60° (increment 5°) and Bennett angle increments of 6, 12, and 20°. The results were assessed for a path of 3 mm. RESULTS: The mean difference between the compared determination methods of angular parameters obtained during the experimental phase of the study was 3.20±7.22° for the left SCI; 2.09±9.75° for the right SCI; 5.50±11.26° for the left Bennett angle, and 6.40±6.29° for the right Bennett angle. The mean difference between the compared determination methods of angular parameters obtained during the clinical phase of the study was 11.80±6.86° for the left SCI; 12.10±6.08° for the right SCI; 13.0±9.89° for the left Bennett angle, and 10.70±11.48° for the right Bennett angle. CONCLUSION: Both approaches for determining angular parameters can be recommended for use in real-world dental practice. When sophisticated, expensive equipment is not available, a virtual articulation system in the Avantis 3D software can be used as a more simple and affordable technique of measuring angular parameters.

Analysis and Modeling of Four-Quadrant PWM Rectifier

Different from the traditional AC/DC converters, the four-quadrant converters are widely used in modern AC power transmission systems because of their advantages such as two-way flow of energy, adjustable power factor on the grid side, and stable voltage on the DC side [1]. In this paper, the mathematical model of four-quadrant PWM rectifier is presented, and on this basis, the constant-frequency double closed-loop control strategy is adopted to control the DC voltage and the power factor of the grid side. The determination method of voltage and current PI regulator parameters is analyzed, and the influence of ac side inductance and DC side capacitance on the whole system is pointed out, and the design method is given. Through the establishment of simulation model under MATLAB/ Simulink, it is proved that this model can realize the DC voltage and power factor control at the side of the network, has a good load regulation ability, and can switch between the rectifier mode and the inverter mode, realizing the two-way flow of energy. This paper has some guiding effect on the design of four-quadrant PWM rectifier.

Determination Method of Reaction Rate and Mass Transfer Parameters in Cathode Catalyst Layer in PEFC

IntroductionIt is important to optimize the cathode catalyst layer (CCL) because the oxygen reduction reaction (ORR) in the CCL is sluggish. Our previous study showed that the mass transfer resistance in the CCL can be quantified by measuring the ORR rate dependency on the oxygen partial pressure at fixed temperature[1,2]. In this study, polarization curves were measured and analyzed at varied oxygen partial pressure and temperature. The objective of this study is to establish the quantification methods of mass transfer and reaction rate parameters, which explain the behavior of polarization curves at various conditions.ExperimentalA cell whose active area was 20 mm × 20 mm was used in experiments. The membrane electrode assembly (MEA, Eiwa Corp.) consists of proton exchange membrane (PEM, Chemours NafionTM, NR-212) and two catalyst layers of each side of the PEM. Platinum catalyst supported on Ketjen Black (Pt/C weight ratio: 1.0) and a NafionTM ionomer (ionomer/carbon weight ratio: 1.0) consists of the catalyst layer. Oxygen and nitrogen were supplied to the cathode in order to vary the oxygen partial pressure. H2, N2, and O2 were humidified in bubblers to keep the inlet relative humidity (RH) at 0.8. The cell temperature was varied at 50, 60, 70, and 80 °C. The Oxygen mole fraction at the cathode was also varied at 1.5, 3, 6, 10, and 21 % on a dry basis.Results and DiscussionPolarization curves at varied oxygen partial pressure, p Oc and temperature are shown in Figs. 1–4. Since the reaction and mass transfer rate are improved at higher temperature, the current density at fixed cathode electromotive force, E cm increases when temperature increases as far as RH is identical. Arrhenius plot at the E cm of 0.2 V is shown in Fig. 5. Since the reaction rate is proportional to the oxygen partial pressure[3,4], the current divided by the oxygen partial pressure on the vertical axis in Fig. 5 is proportional to the observed reaction rate constant. Fig. 5 shows that the apparent activation energy decreases as temperature increases at the p Oc range of 2.5 to 7.7 kPa. This result indicates that the reaction rate saturates when temperature increases due to the effect of oxygen permeation resistance of the ionomer layer. The observed reaction rate constant decreases at higher p Oc , particularly at 15.9 kPa, due to the effect of proton transfer resistance. Fig 6. shows the apparent activation energies plotted against E cm . Both apparent activation energies of the ORR did not depend on E cm . Tafel slope, b c should be the function of temperature, T as expressed in Eq. (1): b c=RT/4aF, (1)where R, a, and F is the gas constant, transfer coefficient, and Faraday constant, respectively. The ORR rate constant, k vc ° is the exponential function of the inverse of the temperature. Considering Eq. (1), k vc ° should be expressed as follows: k vc° = k vc0exp(-E/RT-E c/b c) = k vc0exp(-(E+4aFE c)/RT), (2)where E is the activation energy. Although the apparent activation energy of the ORR should increase when E cm increases, the measurement results were independent of E cm , especially below 0.65 V. It indicates that the Tafel slope does not depend on temperature. The apparent activation energies of the ORR and of the oxygen permeance through the ionomer layer were obtained as 52 kJ/mol and 15 kJ/mol, respectively.Reaction rate constant, effective oxygen diffusion coefficient, effective proton conductivity, and oxygen permeance through the ionomer layer can be determined by applying the dimensionless isothermal 1D cathode model[1, 2, 4] to the obtained polarization curves.ConclusionsThe polarization curves at varied oxygen partial pressure and temperature were measured and analyzed. As the activation energy of the reaction is higher than that of diffusion and permeation, the observed activation energy in the Arrhenius plot at varied cathode electromotive force decreased when temperature increases. The observed activation energy of the ORR did not depend on the cathode electromotive force.AcknowledgementsThis work was supported by the FC-Platform Program: Development of design-for-purpose numerical simulators for attaining long life and high performance project (FY 2020–2023) conducted by the New Energy and Industrial Technology Development Organization (NEDO), Japan. This work was supported by Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI) Grant Number 22KJ1899.

The Influence of Material Properties and Wall Thickness on Predicted Wall Stress in Ascending Aortic Aneurysms: A Finite Element Study.

Finite element analysis (FEA) has been used to predict wall stress in ascending thoracic aortic aneurysm (ATAA) in order to evaluate risk of dissection or rupture. Patient-specific FEA requires detailed information on ATAA geometry, loading conditions, material properties, and wall thickness. Unfortunately, measuring aortic wall thickness and mechanical properties non-invasively poses a significant challenge, necessitating the use of non-patient-specific data in most FE simulations. This study aimed to assess the impact of employing non-patient-specific material properties and wall thickness on ATAA wall stress predictions. FE simulations were performed on 13 ATAA geometries reconstructed from computed tomography angiography (CTA) images. Patient-specific material properties and wall thicknesses were made available from a previous study where uniaxial tensile testing was performed on tissue samples obtained from the same patients. The ATAA wall models were discretised with hexahedral elements and prestressed. For each ATAA model, FE simulations were conducted using patient-specific material properties and wall thicknesses, and group-mean values derived from all tissue samples included in the same experimental study. Literature-based material property and wall thickness were also obtained from the literature and applied to 4 representative cases. Additional FE simulations were performed on these 4 cases by employing group-mean and literature-based wall thicknesses. FE simulations using the group-mean material property produced peak wall stresses comparable to those obtained using patient-specific material properties, with a mean deviation of 7.8%. Peak wall stresses differed by 20.8% and 18.7% in patients with exceptionally stiff or compliant walls, respectively. Comparison to results using literature-based material properties revealed larger discrepancies, ranging from 5.4% to 28.0% (mean 20.1%). Bland-Altman analysis showed significant discrepancies in areas of high wall stress, where wall stress obtained using patient-specific and literature-based properties differed by up to 674kPa, compared to 227kPa between patient-specific and group-mean properties. Regarding wall thickness, using the literature-based value resulted in even larger discrepancies in predicted peak stress, ranging from 24.2% to 30.0% (mean 27.3%). Again, using the group-mean wall thickness offered better predictions with a difference less than 5% in three out of four cases. While peak wall stresses were most affected by the choice of mechanical properties or wall thickness, the overall distribution of wall stress hardly changed. Our study demonstrated the importance of incorporating patient-specific material properties and wall thickness in FEA for risk prediction of aortic dissection or rupture. Our future efforts will focus on developing inverse methods for non-invasive determination of patient-specific wall material parameters and wall thickness.

Fan noise radial mode detection based on [formula omitted] regularization method

Radial mode detection has been widely employed in fan noise research. Many radial mode detection algorithms by conducting the convex L1 norm optimization have been proposed by taking advantage of the fact that the fan noise sound field is usually dominated by a limited set of radial modes. Nevertheless, L1 norm optimization has been shown to be suboptimal and cannot enforce further sparsity. A fan noise radial mode detection method based on L1/2 regularization algorithm is proposed in this paper to improve its robustness and dynamic range. This method employs the L1/2 regularization to directly solve the in-duct sound propagation model. Synthesized simulations indicates that the L1/2 regularization method can detect the correct radial mode order and amplitude under low signal-to-noise ratio. Moreover, the new method is insensitive to regularization parameter. An experimental system of radial rake is implemented to validate the new method. It is shown that the L-curve method, which do not require any prior information of the acoustic mode distribution or contaminating measurement noise, is an appropriate choice of the regularization parameter determination method for the L1/2 regularizer. It is demonstrated that the new L1/2 regularization method can enhance the mode sparsity, especially under low signal-to-noise ratio. Moreover, the resolution and dynamic range can be improved by the L1/2 regularization method, which makes it an effective and robust fan noise radial mode detection technique in practical applications.

Dynamic Determination Method of Line Drop Compensator Parameters for Voltage Regulators Based on Mixture of Experts Using Real‐Time Information

In this paper, a method for determining line drop compensator (LDC) parameters for step voltage regulators and on‐load tap changers is proposed to avoid voltage violations in distribution systems with voltage fluctuations due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators need to effectively solve voltage problems caused by the widespread installation of distributed energy resources with the existing voltage regulators to construct an efficient and rational infrastructure. Our focus was on improving the method for determining the LDC parameters for the existing voltage regulators based on LDC control. A mechanism to dynamically change the LDC parameters depending on the situations in the distribution system was developed by using a mixture of experts, one of the machine learning techniques, and real‐time voltage and power flow information from information technology switches. The power flow calculations were performed using a distribution system model constructed based on the topology, loads, and generation characteristics of an actual distribution system in the Hokuriku region. The effectiveness of the proposed method was evaluated in terms of its improved effect on PV and EV hosting capacity, as well as the impact on the frequency of tap operations of voltage regulators. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

The Influence of Citric Acid on the Corrosion Process of Different Metallic Materials

Abstract The paper presents the results from a study of the corrosion behaviour of different metallic materials, such as copper, aluminium and OL 52 steel in the presences of various concentrations of citric acid added in neutral solution (Na2SO4 0.25 M). Citric acid (2-hydroxy-1, 2, 3-propanetricarboxylic acid) is among the most commonly utilized compounds in the food and beverage sectors. This non-toxic chemical can be derived from natural, renewable sources such as citrus fruits, pineapples, kiwis, raspberries, strawberries, and both black and red currants. Corrosion studies carried out previously demonstrated a mixed effect of citric acid, it can be a good inhibitor for aluminum alloys in a strongly acidic or strongly basic media as well as in neutral NaCl media, for low carbon-steel and copper in an acidic environment, but also, a good, accelerated corrosion agent in an alkaline solution for metals such as iron, copper, zinc and tin. Potentiodynamic polarization and chronoamperometry techniques were used in the experimental part of this paper to evaluate the inhibition efficiency of the citric acid in test solutions. Also, Tafel method for the kinetic parameters determination for studied corrosion process.

Balance Sparse Decomposition Method with Nonconvex Regularization for Gearbox Fault Diagnosis

As an important part of rotating machinery, gearboxes often fail due to their complex working conditions and harsh working environment. Therefore, it is very necessary to effectively extract the fault features of the gearboxes. Gearbox fault signals usually contain multiple characteristic components and are accompanied by strong noise interference. Traditional sparse modeling methods are based on synthesis models, and there are few studies on analysis and balance models. In this paper, a balance nonconvex regularized sparse decomposition method is proposed, which based on a balance model and an arctangent nonconvex penalty function. The sparse dictionary is constructed by using Tunable Q-Factor Wavelet Transform (TQWT) that satisfies the tight frame condition, which can achieve efficient and fast solution. It is optimized and solved by alternating direction method of multipliers (ADMM) algorithm, and the non-convex regularized sparse decomposition algorithm of synthetic and analytical models are given. Through simulation experiments, the determination methods of regularization parameters and balance parameters are given, and compared with the L1 norm regularization sparse decomposition method under the three models. Simulation analysis and engineering experimental signal analysis verify the effectiveness and superiority of the proposed method.

A novel molecular structure parameter determination method for biomass thermochemical conversion mechanism investigation

The low-grade energy properties and high O content of biomass limit its efficient energy utilization. Torrefaction is known to be one of the most promising thermochemical conversion methods for upgrading biomass. 250 °C Gas-pressurized (GP) torrefaction realizes deep decomposition of hemicellulose in biomass to as high as 99.7% by deoxygenation and aromatization. However, the above thermochemical conversion mechanism at molecular-level is currently scant. Here, a novel molecular structural parameter method and pure hemicellulose torrefaction were employed to investigate the thermochemical conversion mechanism. Results demonstrate that O content of 250 °C GP torrefied hemicellulose was as low as 28.8 wt%, which was considerably lower than 44.6 wt% of traditional torrefied hemicellulose. There are five deoxygenation mechanisms of hemicellulose during the GP torrefaction: deacetylation, decarbonylation, dehydroxylation, ring opening and cyclization reactions to produce CO2/CH3COOH, CO, H2O, ketones/aldehydes and furans. The deoxygenation and aromatization reactions cause the chemical structure of hemicellulose evolution significantly, these mechanisms are: active hemicellulose undergo aromatization reaction through cyclization and deoxidation to generate preliminary 2-ring furans polymer, followed by stepwise polymerization reactions to form 4-ring and 6-ring furans polymers. These polymerization reactions further greatly enhance deoxygenation reaction. A thermochemical conversion mechanism model is developed based on the above investigation. This work provides a novel method for determining the molecular structure and reaction mechanism of thermochemical converted biomass.

Advanced Bayesian-Inspired Multilayer Effective Parameter Determination Method for Automated ANN Model Generation of Microwave Components

Advanced Bayesian-Inspired Multilayer Effective Parameter Determination Method for Automated ANN Model Generation of Microwave Components

Solutions of crack constraint parameter in 3D models −− II: Through T-stress

To more accurately analyze the crack front fields, especially under the low constraint conditions which are more common in practical engineering structures, two-parameter approaches (e.g. J-A(A2), J-Q, etc.) are proposed. Currently, no theoretical solutions of the constraint parameters (e.g. A(A2), Q, etc.) in two-parameter approaches are available. Meanwhile, numerical methods for constraint parameter determination are not practical because of significant resource and time consumption, especially for 3D solid models or engineering structures. Therefore, theory and formulae for the estimation of constraint parameter A in 3D solid models are developed in the current work based on T-stress, so as to make it possible to apply two-parameter approaches in practical engineering structures under normal working condition. Two actual structures are used to validate the engineering application of the developed estimate method and formulae.

Micro-scale crystallization thermodynamics study of typical energetic compounds integrating optofluidics and machine learning

With the aim of investigating the changing law of crystallization driving force of typical energetic compounds under micro-scale crystallization conditions, a thermodynamic parameter determination method based on optofluidics was proposed. Aimed at nitro, nitramine and nitrate explosives in energetic compounds, hexanitrostilbene (HNS), cyclotetramethylene tetranitramine (HMX) and pentaerythritol tetranitrate (PETN) were selected as representatives, the solubility of the three kinds of energetic compounds in their respective commonly used solvents (HNS: in DMF, DMSO, NMP; HMX: in DMF, DMSO, CYC; PETN: in DMF, DMSO, EAc) at different temperatures were determined. Furthermore, microfluidics and machine learning were combined, the solubility data of the explosives were processed using BP neural network. Moreover, the metastable zone widths of HNS, HMX and PETN in each solvent were determined using on-line Raman technique. Additionally, crystalline thermodynamic parameters such as solid–liquid interfacial tension, crystal surface entropy factor, enthalpy of dissolution and etc. were calculated for each system.

Multi-criteria group emergency decision-making method considering knowledge granularity

Emergencies are typically characterized by abruptness, time urgency, and complexity, which give rise to challenges such as incomplete information, compromised information effectiveness, and reduced efficiency. To address these issues, this study proposes a novel multi-criteria group emergency decision-making (MCGEDM) method considering knowledge granularity. Within the framework of a hierarchical criterion system (HCS), decision makers' (DMs') judgment information is extracted using belief distributions (BDs) on knowledge chunks, based on the conceptualization of knowledge granularity. This enables DMs to make judgments as effectively as possible, thereby improving efficiency in terms of time and enhancing the effectiveness of information. The generalized combination (GC) rule is applied for individual information fusion within basic nests, demonstrating internal revision and complementation of information. Automatic parameter determination methods are proposed to enhance the effectiveness of information and the efficiency of MCGEDM. Finally, the proposed method is demonstrated through a simulative case of an oil spill emergency, and the subsequent sensitivity analysis and comparisons verify its feasibility and effectiveness.

UAV-based LiDAR Bathymetry at an Alpine Mountain Lake

Abstract. LiDAR bathymetry provides an efficient and comprehensive way to capture the topography of water bodies in shallow water areas. However, the penetration depth of this measurement method into the water column is limited by the medium water and water turbidity, resulting in a limited detectability of the bottom topography in deeper waters. An increase of the analyzable water depth is possible by the use of extended evaluation methods, in detail full-waveform stacking methods. So far, however, this has only been investigated for water depths of up to 3.50 m due to water turbidity. In this article, the potential of these extended data processing methods is investigated on an alpine mountain lake with low water turbidity and thus high analyzable water depth. Compared to the standard data processing, the penetration depth could be significantly increased by 58%. In addition, methods for depth-resolved water turbidity parameter determination on the basis of LiDAR bathymetry data were successfully tested.

Initial structure parameters determination and aberration optimization method for ultra-wide angle optical system with large aperture

Initial structure parameters determination and aberration optimization method for ultra-wide angle optical system with large aperture

A Comprehensive Study on Image Segmentation Using Pulse-Coupled Neural Networks

Pulse-Coupled Neural Network (PCNN) operates as a matrix of neurons, each uniquely corresponding to a pixel in the image being processed. Unlike traditional neural networks, PCNN does not require any training, making it highly suitable for image segmentation tasks. However, the complexity of PCNN arises from its numerous parameters, making parameter selection a challenging endeavor. In this work, we introduce a simplified PCNN architecture that includes an automatic parameter determination method. This approach is specifically designed for binary image segmentation and has been tested on various images, yielding results with distinct and desirable features. The proposed network iterates only four times, enhancing its efficiency. During pre-processing, RGB images are converted to HSV color space, and the V component undergoes further processing. This component is first filtered using an averaging filter, followed by a sharpening filter. The parameters for the PCNN are then generated automatically, eliminating the need for manual selection and making the network highly suitable for real-time image processing. The performance of the proposed network has been verified through tests on a variety of images. Key Words: Neural Networks, Pulse Coupled Neural Networks, Image Processing

Rapid analysis method for process parameter determination of transient thermal tensioning during welding buckling distortion mitigation

The effect of transient thermal tensioning (TTT) on mitigating buckling distortion is significantly influenced by the process parameters. TTT and conventional welding (CW) experiments were both performed on butt welded joints using induction heating as an additional heat source. The thermal elastic plastic (TEP) FE simulation was then carried out with consideration of material nonlinearity and geometrical nonlinearity to investigate the temperature, buckling distortion fields of the butt welded joints. A good agreement between computational results and the measurement was represented, and the buckling distortion of the butt welded joints with TTT was much smaller than that with CW. Based on the validated FE simulation, the sensitivity of process parameters (amount, sizes, tensioning temperature Ttmax, locations of induction heating) for TTT was examined in detail. The results show that amount and sizes exerted an evident impact on buckling distortion mitigation, which were determined by equipment. Tensioning temperature Ttmax and the offset from weld centerline d1 are more important parameters on effectively mitigating welding buckling distortion of thin plate structures than the offset from welding arc d2. Through optimizing Ttmax and d1, buckling distortion of examined butt welded joint can be reduced by more than 80 %. Moreover, a method for determining the process parameters of TTT towards engineering applications was proposed. Firstly, the amount and sizes of additional heat sources are maximized per the available equipment. Secondly, Ttmax is recommended as yield temperature to implement TTT and d1 is optimized through an experiment or TEP FE simulation. Eventually, the offset from welding arc d2 is further optimized when the manufacturing precisions are not reached.