Wide Range Of Process Conditions Research Articles

Mesostructural impact on the macroscopic stress state and yield locus of porous polycrystalline silver

The impact of real sintering structures on the macroscopic stress state and yield locus of sintered silver was investigated and a novel continuum modelling approach that predicts the macroscopic properties in an accurate, simple and efficient way was derived. Focused-Ion-Beam (FIB) tomography was utilized to study silver films, which were sintered under a wide range of processing conditions. With reconstructed three-dimensional representative volume elements (RVE), linear elastic and linear elastic–perfect plastic Finite-Element-Analyses were performed for a variety of loading states. The stress state ratios and the plastic yielding were investigated with respect to the mesostructural quantities obtained from the FIB tomography. The specific pore surface area and the fractional density were found to represent characteristic scalar measures for the sintering structure, which were further used to formulate a thermodynamic consistent continuum model for the macroscopic stress state and yield locus. An assessment of the modelling approach showed good coincidence of the macroscopic stress state with experiments and simulations from literature and a 43 % better prediction accuracy for the yield locus compared to established modelling approaches. The transferability of the model parameters to different silver sintering raw materials was partially proved by literature results and promises reduced parameterization effort.

Experimental Validation of Methanol Synthesis from Steel Mill Gases Using a Miniplant Setup

AbstractUtilization of the gas streams generated by the iron‐ and steel‐making industry for the synthesis of synthetic fuels or chemicals is a promising way to kickstart a technical carbon cycle. Methanol synthesis from cleaned blast furnace gas is a challenge for process design and operation due to high inert gas contents and fluctuations in the gas supply. In this work, a miniplant setup with an adiabatic quench bed reactor was operated with cleaned blast furnace gas over a wide range of process conditions. The experimental data obtained were used to validate a simulation model of the miniplant setup with the perspective for an optimization of the process operational parameters. A high agreement between experimental and simulation data could be obtained, validating the applicability of the simulation approach presented in this work.

Combined experimental-numerical analysis of the temperature evolution and distribution during friction surfacing

Friction surfacing (FS) is a solid state coating technology for similar and dissimilar metallic materials. The coating of the substrate with a consumable material is enabled due to frictional heat and plastic deformation and is performed below the materials' melting temperature. In this work, the spatio-temporal temperature field during FS is investigated within the substrate via a combined experimental-numerical approach. The study presents a robust and efficient thermal process model accounting for the contributions of friction and plasticity as heat input. The geometry of the applied heat source is dependent on the deposit geometry and the evolving flash. Extensive spatial temperature measurements for a dissimilar aluminum alloy combination are used in order to identify the required input parameters and to validate the model. The process temperature profiles for varied process parameters, such as axial force, rotational speed and travel speed as well as substrate thickness and backing plate material are systematically investigated, where experimental and numerical results are in good agreement. Deviations are in particular associated with possible experimental scatter and unknowns regarding the exact position of the measurement as well as modeling assumptions in terms of the heat source geometry. Overall, the detailed comparisons illustrate that the developed numerical model is able to obtain the temperature evolution and distribution during FS deposition with acceptable accuracy for a wide range of process conditions.

Implementation of AdaBoost and genetic algorithm machine learning models in prediction of adsorption capacity of nanocomposite materials

Simulation of adsorption capacity of a nanocomposite material was performed in this study in order to save time and cost in performing adsorption experiments. By developing the predictive models, one can easily predict the adsorption capacity of materials in wide range of processing conditions. Here, we developed two machine learning techniques for correlation of adsorption parameters including adsorbent dosage and solution pH to the adsorption capacity of the adsorbent. One of the most important issues and concerns in issues like the one we have in this study is ensuring the generality of output models, given that the dataset is a small one. As a result of this issue, we chose simple models to improve the modeling result in this study using AdaBoost and GA optimization models. The data was collected from literature and used in the fitting and simulations. After optimizing the hyper-parameters of these models, the final results showed very high efficiency. Using the RMSE criteria, linear regression, Bayesian ridge regression, and Huber regression received error rates of 2.5, 2.3, and 1.7, respectively.

Mechanical properties and crystallinity of polypropylene injection molded in polyjet and aluminum tooling

PurposeRapid tooling has numerous advantages when prototyping injection molded components, but the effects of the tooling on the resulting part properties are often overlooked. The purpose of this paper is to consider the effect of tooling on the final part properties and morphology.Design/methodology/approachDigital polyacrylonitrile-butadiene-styrene (ABS) tooling and aluminum tooling were used to mold test specimens from isotatic polypropylene (iPP). Tensile behavior, impact strength, shrinkage, surface roughness and porosity were evaluated for both sets of samples. Additionally, differential scanning calorimeter (DSC) and wide-angle X-ray scattering (WAXS) were used to assess the crystallinity of the samples.FindingsCharacterization of the molded parts showed that slower cooling rates in the Digital ABS inserts promoted the formation of ß-PP, while this crystal structure was not found in the parts molded using aluminum tooling. Additionally, parts molded on the digital ABS inserts exhibited higher mold shrinkage and SEM images identified microscopic shrinkage voids within the material. The change in morphology and the presence of voids significantly affected the tensile behavior with the parts molded in Digital ABS, which broke with little cold drawing and exhibited higher tensile moduli and higher yield strengths.Practical implicationsThe results show that the choice of rapid tooling technique plays an important role on determining the properties of the final parts.Originality/valuePrevious studies have not characterized the effect of rapid tooling on the morphology of the molded articles fully or over a variety of processing conditions. This study builds on prior work by using both WAXS and DSC to characterize morphological changes over a wide range of processing conditions and comparing results to mechanical property and shrinkage data.

Age-hardening behavior guided by the multi-objective evolutionary algorithm and machine learning

In the present work, multi-objective evolutionary (MOE) algorithm and machine learning (ML) techniques were employed to predict the age-hardening behavior of aluminum (Al) alloys in a wide range of processing conditions. For this purpose, data containing hardness, information on alloy compositions, and aging conditions (aging time and temperature) were extracted from previous works that reported the age-hardening of Al-Cu-Mg base alloys. Accordingly, 1591 cases were collected for various alloy compositions and processing conditions. Composition features (140) generated based on the alloy composition and element properties (atomic weight, electronegativity, etc.), and processing features (time and temperature) were subjected to a preprocessing using the MOE algorithm to reduce the number of features and use those which highly influence the hardness. MOE-processed features and counterpart hardness values are then employed in the learning process using various ML algorithms, including decision tree (DT), deep learning (DL), linear general model (GM), gradient boosted trees (GBT), random forest (RF), and support vector machine (SVM). The results show that the MOE algorithm's leveraging with ML learning processes can be successfully used to refine the features and build accurate ML predictive models compared to those created using other feature selection and preprocessing methods. In addition, the learning results showed that the predictive model built using the ensemble GBT algorithm exhibits the best performance among all models built based on other ML algorithms, where a relative error of 3.5% was recorded for the GBT-based model, and it could reproduce the experimental aging behavior of Al alloy.

A mixed lubrication model for inter-ply friction behaviour of uncured fabric prepregs

Inter-ply friction plays a dominant role in the generation of fiber-path defects (e.g. wrinkling) in the consolidation stage of composites manufacturing. In particular, for most thermoset prepregs, the mixed lubrication regime can be a dominating factor controlling the frictional response over the range of the processing window. This article presents a generic computational modelling approach to describe the mixed lubrication regime by combining an inverse hydrodynamic‐lubrication (IHL) theory and an asperity contact model. A homogenized resin film thickness can be derived from this analysis, rather than postulating it as in earlier conventional models. Thermal effects and fiber bed compliance in the inter-layer contact area as well as the influence of the resin rheology are assessed, finally enabling the model to be verified against inter-ply friction experiments under a wide range of processing conditions. The model has been exemplified on a fabric carbon/epoxy prepreg.

The revenge of Zygosaccharomyces yeasts in food biotechnology and applied microbiology.

Non-conventional yeasts refer to a huge and still poorly explored group of species alternative to the well-known model organism Saccharomyces cerevisiae. Among them, Zygosaccharomyces rouxii and the sister species Zygosaccharomyces bailii are infamous for spoiling food and beverages even in presence of several food preservatives. On the other hand, their capability to cope with a wide range of process conditions makes these yeasts very attractive factories (the so-called "ZygoFactories") for bio-converting substrates poorly permissive for the growth of other species. In balsamic vinegar Z. rouxii is the main yeast responsible for converting highly concentrated sugars into ethanol, with a preference for fructose over glucose (a trait called fructophily). Z. rouxii has also attracted much attention for the ability to release important flavor compounds, such as fusel alcohols and the derivatives of 4-hydroxyfuranone, which markedly contribute to fragrant and smoky aroma in soy sauce. While Z. rouxii was successfully proposed in brewing for producing low ethanol beer, Z. bailii is promising for lactic acid and bioethanol production. Recently, several research efforts exploited omics tools to pinpoint the genetic bases of distinctive traits in "ZygoFactories", like fructophily, tolerance to high concentrations of sugars, lactic acid and salt. Here, I provided an overview of Zygosaccharomyces industrially relevant phenotypes and summarized the most recent findings in disclosing their genetic bases. I suggest that the increasing number of genomes available for Z. rouxii and other Zygosaccharomyces relatives, combined with recently developed genetic engineering toolkits, will boost the applications of these yeasts in biotechnology and applied microbiology.

High-resolution stereolithography using a static liquid constrained interface

3D printing using conventional stereolithography is challenging because the polymerized layers adhere to the solid constraining interface. The mechanical separation forces lead to poor process reliability and limit the geometrical design space of the printed parts. Here, these challenges are overcome by utilizing a static inert immiscible liquid below the resin as the constraining interface. We elucidate the mechanisms that enable the static liquid to mitigate stiction in both discrete layer-by-layer and continuous layerless growth modes. The inert liquid functions as a dewetting interface during the discrete growth and as a carrier of oxygen to inhibit polymerization during the continuous growth. This method enables a wide range of process conditions, such as exposure and resin properties, which facilitates micrometer scale resolutions and dimensional accuracies above 95%. We demonstrate multi-scale microstructures with feature sizes ranging from 16 μm to thousands of micrometers and functional devices with aspect ratios greater than 50:1 without using sacrificial supports. This process can enable additive 3D microfabrication of functional devices for a variety of applications.

Stretch Forming Behavior and Constitutive Equation of a Modified 5083 Alloy with High Mg Content at Elevated Temperatures

For the purpose of applying a modified 5083 alloy (New 5083M alloy) with high Mg content in various automotive sheet parts, the stretch forming behavior of the 5083M alloy was studied in tensile mode at a wide range of processing conditions. The tensile tests were conducted by using a tensile test machine under the temperature ranges of 100–400 °C and the strain rate ranges of 0.001–1 s−1. The test results showed that the 5083M alloy has superior mechanical properties to that of the commercial 5083 alloy at elevated temperatures. The microstructure before and after the stretch forming was analyzed using optical microscope (OM) equipped with a polarizing filter and electron backscattered diffraction (EBSD) unit. Deformed microstructure was observed under low temperature conditions and dynamic recrystallized microstructure under high temperature conditions. However, regardless of microstructure evolution, developed deformation textures were distributed in orientation distribution functions (ODF) images. In addition, at high temperature and low strain rate condition, complex shaped cavities which were detrimental to mechanical properties appeared at the grain boundary and grain triple junction. Based on the test results data, a constitutive equation predicting the deformation behavior of the 5083M alloy was derived. The calculated curves by the constitutive equation were compared with the measured curves by experiment and agreed well.

Modeling Fischer–Tropsch kinetics and product distribution over a cobalt catalyst

AbstractA detailed kinetic model describing the consumption of key components and product distribution in the Fischer–Tropsch synthesis (FTS) over a 20%Co/0.5Re γ‐Al2O3 commercial catalyst is developed. The developed model incorporates the H2O‐assisted CO dissociation mechanism developed by Rytter and Holmen and a novel approach to product distribution modeling. The model parameters are optimized against an experimental dataset comprising a range of process conditions: total pressure 2.0–2.2 MPa, temperature 210–230°C, CO conversion range of 10%–75% and feed with and without added water. The quality of the model fit measured in terms of mean absolute relative residuals (MARR) value is 23.1%, which is comparable to literature reported values. The developed model can accurately describe both positive and negative effects of water on the rate kinetics, the positive effect of water on the growth factor, temperature and syngas composition on the kinetics and product distribution over a wide range of process conditions, which is critical for the design and optimization of the Fisher–Tropsch reactors.

Kinetics of the direct DME synthesis from CO2 rich syngas under variation of the CZA-to-γ-Al2O3 ratio of a mixed catalyst bed.

The one-step synthesis of dimethyl ether over mechanical mixtures of Cu/ZnO/Al2O3 (CZA) and γ-Al2O3 was studied in a wide range of process conditions. Experiments were performed at an industrially relevant pressure of 50 bar varying the carbon oxide ratio in the feed (CO2 in COx from 20 to 80%), temperature (503–533 K), space-time (240–400 kgcat s mgas−3), and the CZA-to-γ-Al2O3 weight ratio (from 1 to 5). Factors favoring the DME production in the investigated range of conditions are an elevated temperature, a low CO2 content in the feed, and a CZA-to-γ-Al2O3 weight ratio of 2. A lumped kinetic model was parameterized to fit the experimental data, resulting in one of the predictive models with the broadest range of validity in the open literature for the CZA/γ-Al2O3 system.

Microstructure-strength relationship in friction-stir welded 6061-T6 aluminum alloy

abstract In this work, a structural response of 6061-T6 aluminum alloy to friction-stir welding (FSW) was studied in wide range of processing conditions in order to establish a better foundation for the microstructure-strength relationship in produced welds. In contrast to the widely-accepted conception of the FSW-induced precipitation behavior, the welding temperature was found to be often below the dissolution threshold and thus no particle dissolution took place. Moreover, the peak temperature never exceeded 500 °C, and therefore the particles never dissolved completely. Considering a relatively low cooling rate measured in the stir zone, the dissolved precipitates were suggested to partially re-precipitate as solute clusters during weld cooling cycle thus imparting a substantial hardening effect. Accordingly, the precipitation coarsening was deduced to be the major softening mechanism. Due to the extreme sensitivity of this process to a duration of the weld thermal cycle, the welding speed was surmised to be the key factor controlling weld strength.

Automatic control of a freeze-drying process: Detection of the end point of primary drying

In freeze-drying, the detection of the end of primary drying is a crucial aspect for both the process economics and product quality. Furthermore, the extreme process conditions (low temperature, high vacuum, and sterility) require monitoring devices with a high degree of assurance. In this paper, the most promising methodologies for the detection of the end point of primary drying were investigated and compared. These devices include thermocouples, comparative pressure measurement, condenser pressure, controlled leakage, vacuum shut-off valve, microbalance, mass spectrometers, moisture sensors, and pressure rise test. Furthermore, a multi-scale model of the process was used to describe the process dynamics during the last part of drying, showing that the time difference between the onset and offset points depends on the batch heterogeneity, as well as process conditions and batch size. Ultimately, an automatic stop criterion, named EPD, has been designed and experimentally tested in a wide range of process conditions, batch size, vial size, and drug products. In particular, the experimental validation involved some of the most used excipients as model products, i.e., mannitol, dextran, lactose, and sucrose. In all the runs, the EPD drying times reasonably agreed with the comparative pressure measurement, which was the most reliable way to detect the end of primary drying. Thus, EPD can effectively be used to optimize primary drying without risking the product collapse because of a premature increase in shelf temperature for secondary drying.

Structure-Function Relationship of Artificial Spider Silk Fibers Produced by Straining Flow Spinning.

The production of large quantities of artificial spider silk fibers that match the mechanical properties of the native material has turned out to be challenging. Recent advancements in the field make biomimetic spinning approaches an attractive way forward since they allow the spider silk proteins to assemble into the secondary, tertiary, and quaternary structures that are characteristic of the native silk fiber. Straining flow spinning (SFS) is a newly developed and versatile method that allows production under a wide range of processing conditions. Here, we use a recombinant spider silk protein that shows unprecedented water solubility and that is capable of native-like assembly, and we spin it into fibers by the SFS technique. We show that fibers may be spun using different hydrodynamical and chemical conditions and conclude that these spinning conditions affect fiber mechanics. In particular, it was found that the addition of acetonitrile and polyethylene glycol to the collection bath results in fibers with increased β-sheet content and improved mechanical properties.

Corrosion and Wear Resistance of Coatings Produced by Nonvacuum Electron Beam Cladding of Refractory Carbides on Low-Carbon Steel

Using nonvacuum electron beam cladding of a Cr3C2 + TiC powder mixture, we have produced coatings on low-carbon steel in a wide range of processing conditions. The coatings and reference samples have been tested in corrosion and wear resistance. The results demonstrate that the coating obtained at a deposited surface energy density W = 8.8 kJ/cm2 has the highest corrosion resistance, which is due to the increase in the chromium concentration in the cladded layer to 16%. The wear resistance of the coatings has been shown to be influenced by the number and size of titanium carbide particles. The highest wear resistance is offered by the coating produced at W = 10.0 kJ/cm2.

Geometry-Dependent Solidification Regimes in Metal Additive Manufacturing

Recent modeling and experimental work in additive manufacturing has suggested cross-sectional geometry may play a significant role in the local development of the solidification structure through its influence on the heat source path. This effect has been rationalized as the transi-tion from a quasistatic point heat source regime to a regime dominated by the quasistatic motion of an equiva-lent line source. This work provides a simple analytical framework for determining the conditions under which a system transitions between these regimes. A transient semianalytical heat transfer model is used to examine a wide range of process conditions and material properties. A simple analytical expression is derived and shown to accu-rately predict the transition between solidification regimes over these conditions. The functional form of this expres-sion is then used to help understand the importance of various material properties, process parameters, and geometric factors on the characteristics of the solidification con-ditions. This approach may be used as a simple guideline for optimizing process conditions in response to variations in cross-sectional geometry to produce more consistent microstructural distributions in additively manufactured components.

Robust Control of Fluidized Bed Layering Granulation

This contribution is concerned with control of fluidized bed layering granulation with external sieve-mill-cycle. It is well-known that this configuration is sensitive with respect to variations in the operating conditions and supplied material properties. Therefore, control is needed to achieve desired particle properties over a wide range of process conditions. In this contribution H∞-control is applied in order to control the process. In contrast to preceding works, the coupling between the particle and the fluid phase is taken into account. Furthermore, in addition to the Sauter diameter of the particle size distribution, the apparent particle porosity is controlled, which is of great importance for practical applications.

Transition of dynamic recrystallization mechanism during hot deformation of Incoloy 028 alloy

Dynamic recrystallization (DRX) plays significant roles in manipulating of microstructures during hot deformation and the result mechanical properties; however, the underling mechanism leading to multi scale–microstructures remains poorly understood. Here, the DRX mechanism under wide processing conditions (i.e. 950–1200 °C, 0.001–10 s−1) in Incoloy 028 alloy was investigated, where the relationships among flow stress, Z parameter and grain size, as well as the evolution of characteristic microstructures (grain size, sub–grain boundaries, and high angle grain boundaries), are established. As the values of Z parameters decrease (corresponding to decreased flow stresses), three typical softening mechanisms successively occur, ranging from continuous DRX controlled by dislocation glide, discontinuous DRX dominated by dislocation motion (climb and cross/multiple slip) and grain boundary migration, to dynamic normal/abnormal grain growth resulting from grain boundary migration, with transition regions where two adjacent mechanisms occur simultaneously. Correspondingly, these above three softening mechanisms result in ultrafine, fine and coarse grains, respectively. The present findings demonstrate a comprehensive understanding of DRX mechanism over a wide range of processing conditions, and further provide a new guideline for preparing single crystals.

Modelling and simulation of intra-particle heat transfer during biomass torrefaction in a fixed-bed reactor

A two-dimensional, transient and single particle model was developed for biomass torrefaction. A wood cylinder was modeled as a porous solid. The transport, energy conservation and intra-particle pressure evolution equations were discretized by the finite volume method. The resulting linear algebraic equations were solved using the tridiagonal matrix algorithm. Intra-particle flow velocity was estimated by Darcy’s law. Simulation results for intra-particle temperature profile and mass loss history showed good agreement with experimental data from the literature. Thermal flux, drying and torrefaction fronts advanced into the interior of the particle in semi-ellipsoidal form. Water vapor is the main volatile released. The reduction in mass yield is higher than the reduction in energy yield due to loss of water and carbon dioxide. This model can be used in a wide range of process conditions and as an important tool in biomass thermal pretreatment.