Parameterization Methodology Research Articles

French nuclear glass synthesis: Focus on liquid waste dissolution kinetics

In France, high-level nuclear wastes are confined in glass using a calcination-vitrification process. The waste can also be vitrified by liquid feeding, which imply to add directly the liquid waste. In this study, we focus on nuclear waste vitrification process by direct liquid feeding in order to decipher the dissolution kinetics of the waste in the molten glass. We propose an experimental and analytical protocol to study the dissolution in the solid glass frit of the liquid waste dried beforehand during the glass melting process. This methodology allows to: i) identify the intermediate reaction phases which formed and dissolved during the process; ii) characterizes the evolution of waste element concentrations in the dried waste as a function of time and temperature on glass obtained after cooling; iii) define kinetic parameters relative to the process of intermediate reaction phases dissolution in the molten glass. The three main intermediate reaction phases formed and dissolved in function of temperature are Ca-REE (Rare Earth Elements)- silicate, Ce- oxide and Zr- oxide. At each temperature step (800 to 1200 °C) the evolution of REE (La, Ce, Nd and Pr) and Zr concentrations in the glass samples obtained after cooling shows a fast increase followed by a stabilization in time, which reflects the fast dissolution of the dried waste in the molten glass, i.e. the fast dissolution of intermediate reaction phases. The molten glass is completely homogeneous at classical synthesis temperature (1200 °C). A parameterization methodology of element concentration evolution as a function of time and temperature is proposed here in order to define the kinetic parameters corresponding to the dried waste dissolution (i.e. concentration at a given time t, maximal concentration at a given temperature, characteristic time and activation energy). The results show that the activation related to the formation and dissolution processes of the intermediate reaction phases, i.e. whether they constitute intermediate compounds formed in temperature by the interaction between the dried waste and the glass frit, and the phases formed without reacting with the glass frit, directly in the dried waste during heat treatment.

Improved Parameterization Methodology for a Field-Stop Trench-Gate IGBT Physical Model by Switching Feature Partitioning

Accurate simulation of IGBT characteristics is an essential task to predict its electrical behaviors. Numerous physics-based IGBT models have been developed and proven to produce satisfactory simulation results. However, unavailability of device parameters is the key roadblock to application of these physics-based models. Additionally, the coupling between device parameters renders parameter extraction very challenging and heavy. In this paper, a novel parameter extraction scheme by switching feature partitioning is proposed, which considerably relaxes the negative impact of parameter coupling during parameter extraction. The IGBT inductive turn-off process and static characteristics are divided into nine typical feature segments under an inductive load. Then, the physical principle of each feature segment is analyzed, and the corresponding influencing parameters of each feature segment are found. During the parameter extraction, the corresponding weights are assigned to the parameter search according to the error of each feature segment. The proposed method for parameter extraction is elaborated. Using the extracted parameters, the simulation results by the physics-based IGBT model are in excellent agreement with the experimental results of the tested IGBT, and the effectiveness of the proposed parameter extraction program is verified. Finally, the extracted parameters are evaluated and verified by global sensitivity analysis.

Fast multilayer temperature distribution estimation for lithium-ion battery pack

Fast and accurate temperature estimation is crucial for ensuring battery packs' safety and operation performance. However, the full-scale online temperature estimation is still challenging. In this work, a novel reduced-order multi-physics model for a lithium-ion battery pack is proposed for real-time temperature distribution estimation, containing the distributed equivalent circuit model, the three-heat-source thermal model, and the flow resistance network model. The proposed model is conducted on a direct contact liquid-cooled battery pack composed of three modules connected in series. An online parameterization methodology with a closed loop observer is designed, and the key parameters can be automatically identified and corrected. The validation results suggest that the multilayer temperature distribution of cell, module, and pack levels can be commendably described under both steady and transient conditions, where the maximum error can be controlled within 2.8 °C. Besides, the temperature variation of the coolant can be estimated during the operation. The proposed model shows excellent potential in onboard temperature estimation with tens of milliseconds for each temperature update.

Верификация расчетной модели трансформатора напряжения для исследования феррорезонансных процессов в распределительных электрических сетях

Methodology for parameterization of voltage transformer model was developed. Verification of the model is carried out by comparing the nameplate data of the transformer with the results of computer calculations. The magnetization branch parameters are determined by the nameplate values, such as magnetization current and the residual magnetization of the voltage transformer’s magnetic circuit. In conclusion voltage error and the angular error are estimated in terms of the amplitude values and the root-mean-square values of voltage curve for transformer type «NOL-SECH-20». Calculations were carried out with the help of EMTP-RV software.

Undersampled Ionospheric Irregularity Threat Parameterization Using a Three-Dimensional Model for Satellite-Based Augmentation Systems

Single-frequency Satellite-based Augmentation Systems (SBASs) compute and broadcast estimates of vertical ionospheric delays and integrity bounds on the estimates called the Grid Ionospheric Vertical Errors (GIVEs) at Ionospheric Grid Points (IGPs). The dominant contribution of the GIVE comes from the undersampled ionospheric irregularity threat model. This paper presents a methodology for the undersampled ionospheric threat parameterization to reduce the magnitude of the GIVE. A threat model metric that measures the uniformity of angular separation of measurements was designed and incorporated into the current metric set, the fit radius and the relative centroid metric (RCM), such that threat geometries were parameterized rigorously based on the extended metric set. An undersampled threat model was constructed with the proposed three-dimensional metric set and historical ionospheric storm data from the global navigation satellite system stations in South Korea. We also simulated SBAS availability in the Korean region to demonstrate the benefit of the presented threat model methodology. In our preliminary assessment, the implementation of the proposed method was found to improve the 99.9% availability of the approach procedure with vertical guidance I by up to 12% when the approach was applied to the GIVE monitor algorithm.

Shape Exploration and Multidisciplinary Optimization Method of Semirigid Nearing Space Airships

This paper describes a shape exploration and multidisciplinary optimization method of unconventional semirigid nearing space airships. The approach includes several improved mutually interacting disciplines, viz., aerodynamics, structure, propulsion, pressure control, energy, avionics, and electric cable. To describe the nonstreamlined envelope shape of the semirigid nearing space airships, a parameterization methodology involving 12 variables is proposed. And an aerodynamics surrogate model is established using the results of computational fluid dynamics simulations. To obtain the configurations of airship, detailed improved subsystem models are proposed. And a combinatorial optimization strategy is established to search for the optimal solutions. The approach can directly obtain the optimal general configurations such as envelope shape and size, as well as parameters of subsystems such as the required number of valve and air blowers. Optimization results show that the payload capacity increases 16.8% for the airship with same volume. Besides, effects of payload capacity of mass and power are investigated. Finally, sensitivity analysis on the subsystem parameters shows that the volume of semirigid airship is most sensitive to five parameters, viz., areal density of outer envelope, areal density of inner envelope, energy density of lithium battery, propulsion efficiency, and density of carbon fiber material, in turn.

Transferability of the working envelope approach for parameter selection and optimization in thin wall WAAM

This work aims to propose and assess a methodology for parameterization for WAAM of thin walls based on a previously existing working envelope built for a basic material (parameter transferability). This work also aimed at investigating whether the working envelope approach can be used to optimize the parameterization for a target wall width in terms of arc energy (which governs microstructure and microhardness), surface finish and active deposition time. To reach the main objective, first, a reference working envelope was developed through a series of deposited walls with a plain C-Mn steel wire. Wire feed speed (WFS) and travel speed (TS) were treated as independent variables, while the geometric wall features were considered dependent variables. After validation, three combinations of WFS and TS capable of achieving the same effective wall width were deposited with a 2.25Cr-1Mo steel wire. To evaluate the parameter transferability between the two materials, the geometric features of these walls were measured and compared with the predicted values. The results showed minor deviations between the predicted and measured values. As a result, WAAM parameter selection for another material showed to be feasible after only fewer experiments (shorter time and lower resource consumption) from a working envelope previously developed. The usage of the approach to optimize parameterization was also demonstrated. For this case, lower values of WFS and TS were capable of achieving a better surface finish. However, higher WFS and TS are advantageous in terms of production time. As long as the same wall width is maintained, variations in WFS and TS do not significantly affect microstructure and microhardness.

Coarse-Grained Parameterization of Nucleotide Cofactors and Metabolites: Protonation Constants, Partition Coefficients, and Model Topologies.

Nucleotides are structural units relevant not only in nucleic acids but also as substrates or cofactors in key biochemical reactions. The size- and timescales of such nucleotide-protein interactions fall well within the scope of coarse-grained molecular dynamics, which holds promise of important mechanistic insight. However, the lack of specific parameters has prevented accurate coarse-grained simulations of protein interactions with most nucleotide compounds. In this work, we comprehensively develop coarse-grained parameters for key metabolites/cofactors (FAD, FMN, riboflavin, NAD, NADP, ATP, ADP, AMP, and thiamine pyrophosphate) in different oxidation and protonation states as well as for smaller molecules derived from them (among others, nicotinamide, adenosine, adenine, ribose, thiamine, and lumiflavin), summing up a total of 79 different molecules. In line with the Martini parameterization methodology, parameters were tuned to reproduce octanol-water partition coefficients. Given the lack of existing data, we set out to experimentally determine these partition coefficients, developing two methodological approaches, based on 31P-NMR and fluorescence spectroscopy, specifically tailored to the strong hydrophilicity of most of the parameterized compounds. To distinguish the partition of each relevant protonation species, we further potentiometrically characterized the protonation constants of key molecules. This work successfully builds a comprehensive and relevant set of computational models that will boost the biochemical application of coarse-grained simulations. It does so based on the measurement of partition and acid-base physicochemical data that, in turn, covers important gaps in nucleotide characterization.

DEM Simulations of the Calendering Process: Parameterization of the Electrode Material of Lithium-Ion Batteries

During the manufacturing of lithium-ion batteries, calendering is the final step in electrode production. It is a crucial process, which significantly influences the mechanical and electrochemical properties of the electrodes and is decisive in defining the volumetric energy density of lithium-ion batteries. To predict the calendering parameters, a particle model using the discrete element method (DEM) is calibrated based on a parameterization framework. The parameterization methodology for calibration applied in this paper is universally valid, applicable to various material systems and based on a one-factor-at-a-time variation to reduce the number of parameters. With this reduced parameter set, an automatic parametrization using optimization algorithms is feasible.

A Novel Approach to State and Unknown Input Estimation for Takagi–Sugeno Fuzzy Models With Applications to Fault Detection

In this paper, a novel approach is proposed for state and unknown input estimation of Takagi-Sugeno fuzzy systems. By introducing an augmented state vector, containing both system state and the unknown input, a functional observer is proposed to estimate this vector, and the proposed observer provides a highly flexible estimation output. Through casting the observer design problem into an equivalent solvability problem of a linear matrix equation with respect to the observer gains, the existence condition for the proposed observer is explicitly derived in terms of matrix rank. Furthermore, a parameterization methodology of the observer gain matrices is provided as well, which avoids directly solving the Sylvester equation. The proposed observer design scheme is further applied to the $H\_{}/H_\infty $ fault detection problem, and the effectiveness of the proposed approach is demonstrated by state and unknown input estimation for a tunnel diode circuit and fault detection for a continuously stirred tank reactor system.

Optimal Experimental Design for Parameter Identification of PEM Fuel Cell Models

Modeling has been an invaluable tool in analyzing and optimizing polymer electrolyte membrane (PEM) fuel cells for improved performance and durability. Moreover, computationally efficient models may be used as software sensors and provide critical information about the internal states of an operating fuel cell. While the utility of fuel cell models has been shown in a myriad of modeling works in the literature, model parameterization remains a relatively understudied subject. The fact that all fuel cell models rely on some level of empiricism, such as the uptake isotherms used for membrane water uptake, makes the problem of proper model parameterization even more significant for fuel cell models. To date, most of the models in the literature have been parameterized using extensive material characterization obtained from the literature [1]. There are several drawbacks to such an approach. First, it requires extensive resources to be able to characterize individual cell components. Second, such characterization is often invasive and requires taking the cell apart. Finally, parameterizing a model using ex-situ characterization data may reduce the model’s prediction capabilities when it is applied to operating fuel cells. Optimization-based approaches offer some remedy to many of these problems by enabling direct parameterization of the models using non-invasive measurements obtained on an operating fuel cell [2]. Although these techniques have been used occasionally to identify a few model parameters [3], [4], their application is rare, which is most likely due to the significant computational cost of many of the fuel cell models available in the literature. Nevertheless, recent progress in the battery research community highlights several opportunities for effective parameterization of electrochemical energy systems [5]–[7]. Building up on this literature, in this talk we present some results on optimal design of experiments for identifying the parameters of a recently developed model of PEM fuel cells [8], [9]. The optimal experiments help improve identifiability of the parameters of interest using non-invasive performance measurements. Furthermore, we present a methodology for systematic parameterization of such models. The results indicate the importance of optimally designing experiments for the purpose of parameter identification and highlight the utility of the systematic approach in effective model parameterization. We also discuss some issues regarding structural identifiability of fuel cell models and how additional measurements may help alleviate some of these issues. Acknowledgement: Financial support for this work was provided by Ford Motor Company. [1] A. Goshtasbi, P. Garcia-Salaberri, J. Chen, K. Talukdar, D. G. Snachez, and T. Ersal, “Through-the-Membrane Transient Phenomena in PEM Fuel Cells: A Modeling Study,” J. Electrochem. Soc., vol. 166, no. 7, 2019. [2] A. Goshtasbi, J. Chen, J. R. Waldecker, S. Hirano, and T. Ersal, “On Parameterizaing PEM Fuel Cell Models,” in Proceedings of the 2019 American Control Conference, 2019. [3] P. Dobson, C. Lei, T. Navessin, and M. Secanell, “Characterization of the PEM fuel cell catalyst layer microstructure by nonlinear least-squares parameter estimation,” J. Electrochem. Soc., vol. 159, no. 5, pp. B514–B523, 2012. [4] T. C. Yau, P. Sauriol, X. T. Bi, and J. Stumper, “Experimental determination of water transport in polymer electrolyte membrane fuel cells,” J. Electrochem. Soc., vol. 157, no. 9, pp. B1310–B1320, 2010. [5] L. Zhang et al., “Parameter sensitivity analysis of cylindrical lifepo4 battery performance using multi-physics modeling,” J. Electrochem. Soc., vol. 161, no. 5, pp. A762–A776, 2014. [6] S. Park, D. Kato, Z. Gima, R. Klein, and S. Moura, “Optimal Experimental Design for Parameterization of an Electrochemical Lithium-Ion Battery Model,” J. Electrochem. Soc., vol. 165, no. 7, pp. A1309–A1323, 2018. [7] A. M. Bizeray, J.-H. Kim, S. R. Duncan, and D. A. Howey, “Identifiability and parameter estimation of the single particle lithium-ion battery model,” IEEE Trans. Control Syst. Technol., no. 99, pp. 1–16, 2018. [8] A. Goshtasbi, B. L. Pence, and T. Ersal, “A real-time pseudo-2D bi-domain model of PEM fuel cells for automotive applications,” in ASME 2017 Dynamic Systems and Control Conference, 2017, p. V001T25A001-V001T25A001. [9] A. Goshtasbi, B. L. Pence, and T. Ersal, “Computationally efficient pseudo-2D non-isothermal modeling of polymer electrolyte membrane fuel cells with two-phase phenomena,” J. Electrochem. Soc., vol. 163, no. 13, pp. F1412–F1432, 2016.

Parameterization and optimization design of a hypersonic inward turning inlet

To improve the performance of a hypersonic inward turning inlet, an optimization design method was proposed. A parameterization methodology was developed for an axisymmetric basic flowfield, and the geometry of a basic flowfield can be easily generated in several parameters. Preliminarily, an optimization targeting on the basic flowfield performance was conducted. As a result, the total pressure recovery of the basic flowfield was improved 7.65% compared with the referred one under the same constraints. The corresponding stream-traced inlet performance was also improved 5.65%. For further optimization, an optimization directly targeting on the 3-D inlet performance was carried out. The method of calculating along streamlines (MCS), which is for the fast calculation of a stream-traced inlet flowfield, was proposed and confirmed before this optimization. The result shows that the 3-D inlet total pressure can be further enhanced 6.74% than the previous one, and it is 12.78% higher than the referred one. That is to say, it is more reasonable to target on the inlet performance directly for an optimization, rather than targeting on the basic flowfield performance. By statistically analyzing the optimization data, it was found that the opinion “A better basic flowfield means a better stream-traced inlet” is statistically correct, but not exactly correct. The steam-traced inlet performance is not exactly determined by a basic flowfield, and it is determined by a combination of all the flow tubes the inlet captures.

Studying the regression profiles of cervical tumours during radiotherapy treatment using a patient-specific multiscale model

Apart from offering insight into the biomechanisms involved in cancer, many recent mathematical modeling efforts aspire to the ultimate goal of clinical translation, wherein models are designed to be used in the future as clinical decision support systems in the patient-individualized context. Most significant challenges are the integration of multiscale biodata and the patient-specific model parameterization. A central aim of this study was the design of a clinically-relevant parameterization methodology for a patient-specific computational model of cervical cancer response to radiotherapy treatment with concomitant cisplatin, built around a tumour features-based search of the parameter space. Additionally, a methodological framework for the predictive use of the model was designed, including a scoring method to quantitatively reflect the similarity and bilateral predictive ability of any two tumours in terms of their regression profile. The methodology was applied to the datasets of eight patients. Tumour scenarios in accordance with the available longitudinal data have been determined. Predictive investigations identified three patient cases, anyone of which can be used to predict the volumetric evolution throughout therapy of the tumours of the other two with very good results. Our observations show that the presented approach is promising in quantifiably differentiating tumours with distinct regression profiles.

Development of a Semiglobal Reaction Mechanism for the Thermal Decomposition of a Polymer Containing Reactive Flame Retardants: Application to Glass-Fiber-Reinforced Polybutylene Terephthalate Blended with Aluminum Diethyl Phosphinate and Melamine Polyphosphate.

This work details a methodology for parameterization of the kinetics and thermodynamics of the thermal decomposition of polymers blended with reactive additives. This methodology employs Thermogravimetric Analysis, Differential Scanning Calorimetry, Microscale Combustion Calorimetry, and inverse numerical modeling of these experiments. Blends of glass-fiber-reinforced polybutylene terephthalate (PBT) with aluminum diethyl phosphinate and melamine polyphosphate were used to demonstrate this methodology. These additives represent a potent solution for imparting flame retardancy to PBT. The resulting lumped-species reaction model consisted of a set of first- and second-order (two-component) reactions that defined the rate of gaseous pyrolyzate production. The heats of reaction, heat capacities of the condensed-phase reactants and products, and heats of combustion of the gaseous products were also determined. The model was shown to reproduce all aforementioned experiments with a high degree of detail. The model also captured changes in the material behavior with changes in the additive concentrations. Second-order reactions between the material constituents were found to be necessary to reproduce these changes successfully. The development of such models is an essential milestone toward the intelligent design of flame retardant materials and solid fuels.

Regionalization of land surface heat fluxes over the heterogeneous landscape: from the Tibetan Plateau to the Third Pole region

ABSTRACTThe exchange of heat and water vapor between land surface and atmosphere over the Third Pole region (Tibetan Plateau and nearby surrounding region) plays an important role in the Asian monsoon, westerlies and the northern hemisphere weather and climate systems. Supported by various agencies in the People’s Republic of China, a Third Pole Environment (TPE) Observation and Research Platform (TPEORP) is now implementing over the Third Pole region. The background of the establishment of the TPEORP, the establishing and monitoring plan of long-term scale (5–10 years) of it will be shown firstly. Then the preliminary observational analysis results, such as the characteristics of land surface energy fluxes partitioning and the turbulent characteristics will also be shown in this study. Then, the parameterization methodology based on satellite data and the atmospheric boundary layer (ABL) observations has been proposed and tested for deriving regional distribution of net radiation flux, soil heat flux, sensible heat flux, and latent heat flux (evapotranspiration (ET)) and their variation trends over heterogeneous landscape of the Tibetan Plateau (TP) area. To validate the proposed methodology, the ground-measured net radiation flux, soil heat flux, sensible heat flux and latent heat flux of the TPEORP are compared to the derived values. The results show that the derived land surface heat fluxes over the study areas are in good accordance with the land surface status. These parameters show a wide range due to the strong contrast of surface features. And the estimated land surface heat fluxes are in good agreement with ground measurements, and all the absolute percent difference is less than 10% in the validation sites. The sensible heat flux has increased slightly, and the latent heat flux has decreased from 2001 to 2016 over the TP. It is therefore concluded that the proposed methodology is successful for the retrieval of land surface heat fluxes over heterogeneous landscape of the TP area. Further improvement of the methodology and its applying field over the whole Third Pole region were also discussed.

Francis turbine draft tube parameterization and analysis of performance characteristics using CFD techniques

Abstract The present paper focuses on the parameterization of the draft tube elbow based on the initial geometry of the GAMM Francis turbine model. The goal was to obtain a draft tube geometry that improves the hydrodynamic performance. For this purpose, CFD analyzes were carried out, considering the GAMM Francis turbine pre-distributor, distributor and rotor geometry, and different parameterized draft tube geometries. Related to the draft tube parameterization methodology, it has modified the generatrix geometry of the elbow that defines its contour. Three types of curves were used to define the elbow contour geometry: logarithmic spiral format curve, circle arc format curve and denominated hyperbolic spiral curve. These curves and their combinations were used to define the elbow contour in the longitudinal plane, resulted in four draft tubes geometries. The numerical results were compared with experimental results, showing good conformity. The efficiency of the Francis turbine was higher for the four draft tubes of this work than the original draft tube GAMM Francis turbine. Therefore, it was found that the draft tube in hyperbolic-logarithmic spiral format has the highest efficiency and the draft tube in logarithmic spiral format has the lowest loss coefficient. Consequently the hydrodynamic performance have been discussed in this work.

Limiting Effects on the Design of Vertical Superjunction Collectors in SiGe HBTs

The implementation of a “superjunction” collector design in a silicon–germanium heterojunction bipolar transistor technology is explored for enhancing breakdown performance. The superjunction collector is formed via the placement of a series of alternating the p/xn-doped layers in the collector-base space charge region and is used to reduce avalanche generation leading to breakdown. An overview of the physics underlying superjunction collector operation is presented, together with TCAD simulations, and a parameterization methodology is developed to explore the limits of the superjunction collector performance. Measured data demonstrate the limitations explored in simulation.

An adaptive meshless parameterization for full waveform inversion

Full waveform inversion is a technique to recover images of the subsurface using data from a seismic survey. Nonlinearity, ill-posedness, presence of noise in data, a large number of parameters, different kinds of parameters, and limitations of data are some of the factors that contribute to instabilities of the solution. One of the strategies to regularize the solution is a suitable choice of parameterization. Depending on the parameterization strategy, the solution is searched in a space with certain features, for instance, smoothness, that may be convenient to the problem. Furthermore, a parameterization that can represent well the solution with a reduced number of parameters may be robust due to the limited number of degrees of freedom. Here we show an adaptive meshless parameterization methodology for full waveform inversion, which may also be useful for other inverse problems. The parameterization is based on a meshless technique and uses Wendland’s functions as basis functions to an interpolation. As a meshless method, it is very flexible, then the spatial distribution of the unknowns can be non-uniform, allowing focusing on certain areas or automatically improving the quality of the image near the discontinuities of a velocity model. With some numerical experiments of acoustic inversion of synthetic data, we show that the parameterization methodology described here can represent complex velocity models and that, with a reduced number of unknowns, the inversion process behaves better than the standard parameterization with blocks. We also show that the adaptive meshless parameterization has a significant regularization effect, avoiding non-natural patterns and prioritizing smooth images.

Systematic Parameterization of Lignin for the Charmm Force Field

Lignin is an abundant aromatic biopolymer within plant cell walls formed through radical coupling chemistry, whose composition and topology can vary greatly depending on the biomass source. Computational modeling provides a complementary approach to traditional experimental techniques to probe lignin interactions, lignin structure, and lignin material properties. However, current modeling approaches are limited based on the subset of lignin chemistries covered by existing lignin force fields. To fill the gap, we developed a comprehensive lignin force field that accounts for more lignin–lignin and lignin–carbohydrate interlinkages than existing lignin force fields, and also greatly expands the lignin monomer chemistries that can be modeled beyond simple alcohols and into the rich mixture of natural lignin varieties. The development of this force field utilizes recent developments in parameterization methodology, and synthesizes them into a workflow that combines target data from multiple molecules simultaneously into a single consistent and comprehensive parameter set. The parameter set represents a significant improvement to alternatives for atomic modeling of diverse lignin topologies, more accurately reproducing experimental observables while also significantly reducing the error relative to quantum calculations. The improved energetics, as well as the rigid adherence to CHARMM parameterization philosophy, enables simulation of lignin within its biological context with greater accuracy than was previously possible. The lignin force field presented here is therefore a crucial first step towards modeling lignin structure across a broad range of environments, including within plant cell walls where lignin is complexed with carbohydrates and deconstructed by bacterial or fungal enzymes, or as it exists within industrial solvent mixtures. Future simulations enabled by this updated lignin force field will thus lead to better chemical and structural understanding of lignin, providing new insight into its role in biomass recalcitrance or probing the potential for lignin to be used within industrial processes.

Non-destructive methodology for parameterization of Burn-Zinc in the resistance spot welding process

Galvanized steels are used in large quantities, mainly in the automotive industry, for their corrosion resistance and low cost. In this industrial sector, these materials are normally welded by the spot welding process. Because galvanized steels have a zinc-based covering layer, welding is normally carried out using a technique called the Burn-Zinc technique, to minimize the harmful effects of the zinc on this material, during the welding cycle. In this context, this work studied a non-destructive method, with the aim of finding suitable removal of this layer of zinc, on the basis of the signals generated by a sensor that records the electrode displacement during the phases of the spot welding process, taking the reading for the thermal expansion of the galvanized steel sheet as a basis. Thus, physical simulation experiments were undertaken, varying the current and the cycle time of the preheating phase. The Burn-Zinc responses generated by the sensor and the visual analyses by attribute were shown as graphs via an operating envelope. The evidence showed that the signal from electrode displacement proved to be an efficient non-destructive method for determining suitable Burn-Zinc parameters in the spot welding process for galvanized steel sheet.