6 research outputs found
Ion-Currents in Oxyfuel Cutting Flames Exposed to External Bias Voltages
No full textComputational Fluid Dynamics (CFD) and predictive models are presented in this dissertation that illustrates the detailed electrical characteristics, and the current-voltage (i-v) relationship throughout the preheating process of premixed methane-oxygen (CH4-O2) oxyfuel cutting flame subject to electric bias voltages. As such, the equations describing combustion, electrochemical transport for charged species, and potential are solved through a commercially available finite-volume CFD code. The reactions of the methane-oxygen (CH4 – O2) flame were combined with the GRI 3.0 mechanism and a 25-species reduced mechanism, respectively, and additional ionization reactions that generate three chemi-ions, H3O+, HCO+, and e– , to describe the chemistry of ions in flames. The electrical characteristics such as ion migrations and ion distributions are investigated for a range of electric potential, V ∈ [−10V, +10V ]. Since the physical flame is comprised of twelve Bunsen-like conical flame, inclusion of the third dimension imparts the resolution of fluid mechanics and the interaction among the individual cones. As for developing the predictive models, four different supervised machine learning (ML) algorithms, decision tree (DT), random forest (RF), K-nearest neighbors (KNN), and artificial neural network (ANN), were employed to predict the i-v relationship. An experimental dataset of ≈ 10050 was utilized where a 60:20:20 split was adopted, allocating 60% for training, 20% for validation, and 20% for testing.
It was concluded that charged 'sheaths' are formed at both torch and workpiece surfaces, subsequently forming three distinct regimes in the i-v relationship. The i-v characteristics obtained have been compared to the previous experimental study for premixed flame. In this way, the overall model generates a better understanding of the physical behavior of the oxyfuel cutting flames, along with a more validated i-v characteristics. Such understanding might provide critical information towards achieving an autonomous oxyfuel cutting process.Doctor of PhilosophyOxyfuel flame cutting is a century-old technique having widespread applications in heavy industries, including, but not limited to, building construction, defense, shipyards, etc. However, the mechanized oxyfuel cutting process has never benefited from the degree of autonomy due to contemporary sensing technologies' limitations at high-temperature working conditions.
As a result, an experienced labor force is required to operate the system, thereby lowering the efficacy associated with this cutting process. A potential solution to this problem is motivated by preliminary measurements demonstrating that electrical events called 'ion currents' associated with the flame itself can reliably indicate vital process states. Provided that an autonomous process is achieved, this work could realize reliable cost-effective control of the oxyfuel cutting process, a capability of great interest to many core US industries involved in construction, and major equipment manufacture for defense and energy applications.
Critical parameters (standoff, F/O ratio, flow rate, etc.) must be detected during operation to ensure an autonomous oxyfuel cutting process. The motivation stems from the fact that by measuring such co-dependence between critical parameters and electrical characteristics through a data acquisition unit (DAQ) and power supply, the shortcomings of sensing suites in a harsh operating environment can be compromised. Experimental data in the literature indicated the current-voltage (i-v) relationship with different critical parameters of oxyfuel flame to be the salient electrical characteristic in the preheating process when cutting steel.
A comprehensive two-dimensional computational simulation using StarCCM+ only with the reduced combustion chemical mechanism with ion-exchange reactions has already been completed to elucidate the experimental results and to investigate the electrical characteristics such as ion migrations and ion distributions. Nonetheless, the findings exhibit some magnitude of differences compared to the experimental results. Thereby to further improve the results and better understand the underlying physics, further computational models using ANSYS FLUENT are proposed herein, having the reduced surface chemical mechanism considered.
In addition, predictive models were developed based on machine learning (ML) algorithms. Four supervised ML algorithms - decision tree (DT), random forest (RF), Knearest neighbors (KNN), and artificial neural network (ANN) - were adopted to predict the current-voltage (i-v) relationship at different process states. ML offers a more data-driven, adaptable, and scalable approach to prediction compared to traditional methods. Its ability to handle large, noisy, and complex data makes it especially powerful for tasks that are challenging for conventional analytical techniques.
The results of this study illustrate the detailed electrical characteristics of premixed methane-oxygen (CH4 – O2) oxyfuel cutting flame subject to an electric field, for both the computational fluid dynamics (CFD) and ML models. Since the physical flame is comprised of twelve Bunsen-like conical flame, inclusion of the third dimension will impart the resolution of fluid mechanics and the interaction among the individual cones. Moreover, the chemical activity at the work surface will also be considered, however, with a substantial simplification of the three-dimensional model as a cost. The overall model will generate a better understanding of the physical behavior of the oxyfuel cutting flames, along with a more validated currentvoltage (i-v) relationship. Consequently, this relationship could then be embedded into a control algorithm to detect the critical process parameters that may facilitate a step towards achieving an autonomous oxyfuel cutting process
Characteristics of Oxyfuel Flame Subject to an Electric Field
No full textRecent use of ion currents as a sensing strategy in the mechanized oxyfuel cutting process motivated a series of studies which revealed that the steel work piece contributes secondary ions in addition to the primary ions classically identified in the oxyfuel flame. In this work, we present a computational model that has linked carbon-related chemi-ions as a source of secondary ions in preheating stage of oxyfuel cutting process subject to electric bias voltages. The flames' response to the electric field at different positive and negative polarities manifested a better understanding of the physical behavior of current-voltage (i-v) relationship. While copper surface exhibits stable and repeatable i-v characteristics, sporadically enhanced current was observed in positive saturation regime for steel surface, and this is believed to be due to the presence of secondary chemi-ions. To this extent, a source term of gaseous carbon has been assigned to mimic the 'work surface' reactions. The hypothesis is that since carbon is an important element, it will be diffusing out of the steel surface and evaporate into the flame.Published versio
Physica Scripta
No full textThis simplified model provides solutions for the current-voltage characteristics of a sheath in a dense flowing plasma when surface chemistry contributes secondary ions. The problem is motivated by the recent discovery that strong transient signals in industrial ion current sensors are caused by chemical reactions with carbon in the steel being cut or welded by oxyfuel processes. The one-dimensional model considers a quasi-uniform dense plasma flowing towards and stagnating on an absorbing surface, above which there is a source of secondary ions. Because the secondary ions are formed directly in the plasma sheath, they have strong impacts on the current-voltage characteristic. With ionic Reynolds number, R, and integral length scale, α, secondary ion formation rate, Ω, and length scale, β, saturation currents are simply R + βΩ until β ≪ 1, at which point, new electrons cannot escape the sheath, and secondary ions have no effect. Floating potential, ϕ ∞, scales like exp ( ϕ ∞ ) ∝ R − 3 / 4 , and secondary ions have little impact unless β 2Ω > 1. Even then, floating potential is only weakly affected by secondary ion formation. The integral length scale, α, is not found to strongly affect the results.Published versio
