Continuous Production Process Research Articles

An adaptive modeling approach using spiking-augmentation method to improve chemometric model performance in bioprocess monitoring.

Intensified and continuous processes require fast and robust methods and technologies to monitor product titer for faster analytical turnaround time, process monitoring, and process control. The current titer measurements are mostly offline chromatography-based methods which may take hours or even days to get the results back from the analytical labs. Thus, offline methods will not meet the requirement of real time titer measurements for continuous production and capture processes. FTIR and chemometric based multivariate modeling are promising tools for real time titer monitoring in clarified bulk (CB) harvests and perfusate lines. However, empirical models are known to be vulnerable to unseen variability, specifically a FTIR chemometric titer model trained on a given biological molecule and process conditions often fails to provide accurate predictions of titer in another molecule under different process conditions. In this study, we developed an adaptive modeling strategy: the model was initially built using a calibration set of available perfusate and CB samples and then updated by augmenting spiking samples of the new molecules to the calibration set to make the model robust against perfusate or CB harvest of the new molecule. This strategy substantially improved the model performance and significantly reduced the modeling effort for new molecules.

Multi-criteria analysis of cell-recycle based continuous lactic acid production process

ABSTRACT This study focuses on the optimization of the cell-recycle based continuous lactic acid (LA) fermentation production process with the estimation of improved kinetic parameters. The non-dominated sorting genetic algorithm II (NSGA-II) is used considering seven variables and five imposed constraints for multi-objective optimization (MOO) study. Three objectives namely LA productivity, substrate conversion, and yield are formed for the maximization purpose. Three different cases are constructed by using a combination of two bi-objectives and one tri-objective optimization problem, and the modified differential evolution (MDE) algorithm is used to individually optimize each case. Pareto ranking is carried out for MOO, and the best optimal solution is determined using the technique for order preference by similarity to the ideal solution (TOPSIS) method. The highest value of volumetric productivity of LA (184.363 kg/m3.h) is reported in case-4a. The highest yield (1.176) is reported in case-2, while the highest substrate conversion (0.963) is reported in case-1.

Continuous double-step acid catalyzed esterification production of sludge palm oil using 3D-printed rotational hydrodynamic cavitation reactor

Sludge palm oil (SPO) with high free fatty acid (FFA) content was processed using a continuous and double-step esterification production process in a rotor-stator-type hydrodynamic cavitation reactor. Three-dimensional printed rotor was made of plastic filament and acted as a major element in minimizing the FFA content in SPO. To evaluate the reduced level of FFAs using both methods, five independent factors were varied: methanol content, sulphuric acid content (H2SO4), hole diameter, hole depth, and rotor speed. The first-step conditions for the esterification process included 60.8 vol% methanol content, 7.2 vol% H2SO4 content, 5.0 mm diameter of the hole, 6.1 mm depth of the hole, and 3000 rpm speed of the rotor. The initial free fatty acid content decreased from 89.16 wt% to 35.00 wt% by the predictive model, while 36.69 wt% FFA level and 94.4 vol% washed first-esterified oil yield were obtained from an actual experiment. In the second-step, 1.0 wt% FFA was achieved under the following conditions: 44.5 vol% methanol content, 3.0 vol% H2SO4 content, 4.6 mm hole diameter, 5.8 mm hole depth, and 3000 rpm rotor speed. The actual experiment produced 0.94 wt% FFA content and 93.9 vol% washed second-esterified oil yield. The entire process required an average electricity of 0.137 kWh/L to reduce the FFA level in the SPO below 1 wt%.

Towards shape optimization of flow channels in profile extrusion dies using reinforcement learning

AbstractProfile extrusion is a continuous production process for manufacturing plastic profiles from molten polymer. Especially interesting is the design of the die, through which the melt is pressed to impart the desired shape. However, due to an inhomogeneous velocity distribution at the die exit or residual stresses inside the extrudate, the final shape of the manufactured part often deviates from the desired one [1]. To avoid these deviations, we want to optimize the shape of the flow channel inside the die computationally. This has already been investigated in the literature using conventional optimization approaches [2,3].In this work, we investigate the feasibility of Reinforcement Learning (RL) as a learning‐based approach for shape optimization. RL is based on trial‐and‐error interactions of an agent with an environment. For each action, the agent is rewarded and informed about the subsequent state of the environment, which for this application stems from a high‐fidelity Finite Element Method (FEM) simulation.We will introduce a 2D test case as a proof‐of‐concept, in which an RL agent learns to change the geometry of a flow channel by modifying its representation as computational mesh through a spline‐based deformation method known as Free Form Deformation (FFD) [4]. We will show that an agent can be trained to optimize the geometry for different values of the quantity of interest and that the learning behavior is reproducible, which renders the RL‐based approach promising for further research.

High-rate and -yield continuous fluidized-bed bioconversion of glucose-to-gluconic acid for enhanced metal leaching

Continuous low-cost bulk biolixiviant production remains as one of the main challenges of heterotrophic bioleaching towards large scale application. This study aimed at developing non-aseptic Gluconobacter oxydans-amended fluidized-bed reactor (FBR) process for continuous production of gluconic acid for efficient leaching of rare earth elements (REEs) and base metals from spent nickel-metal-hydride (NiMH) batteries. In preliminary experiments, the FBR became contaminated and massively overgrown by air-borne fungus, Leptobacillium leptobactrum. In a series of batch bioassays, operational conditions were investigated to discourage the fungal activity i.e., an ecologically engineered niche for gluconic acid production. High gluconate concentration (≥100 g/l) and/or low pH (≤2.5) gave a selective preference for G. oxydans growth over L. leptobactrum and controlled the activity of possible contaminants during FBR continuous operation. The highest gluconic acid production rate of 390 g/l∙d with corresponding glucose-to-gluconic acid conversion yield of 94% was obtained at hydraulic retention time (HRT) of 6.3 h and 380 g/l∙d glucose loading rate. Using the FBR effluents as leaching agents, respectively, total base metals and REEs leaching yields of up to 82% and 55% were achieved within 7 days at 1% (w/v) spent battery pulp density. The obtained glucose-to-gluconic acid conversion rates and yields were one of the highest reported for any glucose biotransformation process. The REE leaching yields were higher than those reported for similar high metal-grade REE secondary sources. The high-rate glucose-to-gluconic acid bioconversion in the non-aseptic system utilizing microbial ecology based FBR operation strategy rather than aseptic chemostats indicates industrial feasibility of gluconic acid production and thus, the applicability of heterotrophic bioleaching.

Hacking hematopoiesis - emerging tools for examining variant effects.

Hematopoiesis is a continuous process of blood and immune cell production. It is orchestrated by thousands of gene products that respond to extracellular signals by guiding cell fate decisions to meet the needs of the organism. Although much of our knowledge of this process comes from work in model systems, we have learned a great deal from studies on human genetic variation. Considerable insight has emerged from studies on presumed monogenic blood disorders, which continue to provide key insights into the mechanisms critical for hematopoiesis. Furthermore, the emergence of large-scale biobanks and cohorts has uncovered thousands of genomic loci associated with blood cell traits and diseases. Some of these blood cell trait-associated loci act as modifiers of what were once thought to be monogenic blood diseases. However, most of these loci await functional validation. Here, we discuss the validation bottleneck and emerging methods to more effectively connect variant to function. In particular, we highlight recent innovations in genome editing, which have paved the path forward for high-throughput functional assessment of loci. Finally, we discuss existing barriers to progress, including challenges in manipulating the genomes of primary hematopoietic cells.

Comprehensive metabolomics reveals correlation between sophorolipid biosynthesis and autophagy

Sophorolipids are biobased and biodegradable glycolipid surface-active agents contributing to the shift from petroleum to biobased surfactants, associated with clear environmental benefits. However, their production cost is currently too high to allow commercialisation. Therefore, a continuous sophorolipid production process was evaluated, i.e., a retentostat with an external filtration unit. Despite an initial increase in volumetric productivity, productivity eventually declined to almost 0 g L−1 h−1. Following comprehensive metabolomics on supernatant obtained from a standardised retentostat, we hypothesised exhaustion of the N-starvation-induced autophagy as the main mechanism responsible for the decline in bolaform sophorolipid productivity. Thirty-six metabolites that correlate with RNA/protein autophagy and high sophorolipid productivity were putatively identified. In conclusion, our results unveil a plausible cause of this bola sophorolipid productivity decline in an industrially relevant bioreactor set-up, which may thus impact majorly on future yeast biosurfactant regulation studies and the finetuning of bola sophorolipid production processes.

Environment microorganism and mature daqu powder shaped microbial community formation in mechanically strong-flavor daqu

Daqu is the fermenting starter in Chinese Baijiu brewing, contributing functional microorganisms, enzymes and flavor substances to the grain fermentation. Traditional daqu is produced in open environment where environmental factors and microbiota are critical to daqu and Baijiu quality. Mechanization is the direction of Baijiu production development. In this study, we investigated the mechanism of the effect of mechanized environment and manufacturing process on daqu production. Many functional microorganisms (e.g. Acetobacter, lactic acid bacteria and yeast) were distributed in the process environment, including indoor air, tube and equipment surfaces, which contributed to the initial bacterial/fungal composition in daqu (71.62%/28.47%) along with mature daqu powder (21.1%/61.65%). Our results also showed daqu microbiota formation was influenced by both stochastic and deterministic processes. The initial microorganisms produced large amounts of organic acids (19.24 g/kg) and bioheat (58.3 °C) during early fermentation stage, leading to a rapid temperature rise and water loss under the stacking process. Mature daqu powder mainly provided thermophilic microorganisms for fermentation stages during and after temperature rise, including Thermoactinomyces, Thermoascus, Thermomyces, Rhizomucor and Rhizopus, which produced enzymes and amino nitrogen for Baijiu fermentation, also ensuring stable microbiota among process batches. This work revealed the origin of the microbial community of strong-flavor daqu and showed that ecological environment suitable for daqu fermentation was created during the long-term continuous production process by adding mature daqu powder during daqu brick making and sprinkling it in the workshop, by which product quality was guaranteed.

An agar structured fluid prepared by pipe wall shear as a dysphagia diet

The risk of dysphagia in the elderly has gradually become a social problem. An important strategy is to modify the food texture to reduce aspiration risk. The microgel, a structured fluid prepared usually by Couette flow and jacketed stirring, has attracted much attention due to its unique rheological properties and complex microstructure. This study proposed a continuous production process of agar structured fluid through the pipe wall laminar shear. The rheological properties and particle size distribution of agar microgel were characterized. The morphology of microgel and its interaction with water molecules were examined through scanning electron microscopy (SEM) and low-field nuclear magnetic resonance (LF-NMR), and some positive feedback examples were obtained through the Videofluorographic swallowing study (VFSS). A molecular model was proposed that agar microgel is a supramolecular structure with a multi-domains weak interaction, whose “hairy” structure is the site of domain-domain interaction. The agar microgel as a structured fluid can achieve higher yield stress and elastic modulus at the same concentration compared to xanthan gum solution, which is expected to be the next cost-effective and age-appropriate pre-thickened diet for older adults with dysphagia.

Experimental and Numerical Study of Electrospray Pyrolysis Process for Continuous Production of TiO2 Particles

In this study, an integrated electrospray pyrolysis process was designed to continuously produce a representative nano-catalyst TiO2. A numerical model was also developed to simulate the flow behaviors and droplet transport inside the reactor. The electric field model and particle tracking model were coupled to describe the electrospray pyrolysis process. The effects of key parameters, including electrode configurations, applied voltage, droplet charge density, and flow type of carrying gas on the electric field distribution, particle distribution, and particle collection efficiency, were investigated to help the design and optimization of the integrated electrospray pyrolysis reactor. The results show that the electric potential and electric field strength decrease rapidly with increasing distance away from the nozzle. In addition, the results show that the droplet charge is an important parameter affecting the collection efficiency. The investigation of the key parameters shows that applying a voltage on the ring and using the “gas-bleed” introduction method are more conducive to the improvement in the collection efficiency.

Dynamic operation optimization based on improved dynamic multi-objective dragonfly algorithm in continuous annealing process

The continuous annealing production process is the strip iron heat treatment process. Considering the numerous disturbance parameters and frequent environmental changes in the production process, dynamic multi-objective optimization is studied. (1)To anticipate whether the environment will change, this paper proposed dynamic detection based on Long-Short Term Memory (LSTM) prediction mechanism. A single-step prediction method is adopted to predict the strip hardness at the next moment which is compared with the value at the previous moment. (2)To track the dynamic Pareto frontier, the Information Fusion (IF) strategy in Dynamic Multi-Objective Dragonfly Algorithm (DMODA) is proposed. The population is updated by integrating the environmental offset with the evolution information. Computational experiments show the proposed strategy is effective when dealing with dynamic problems and it has been well applied in the continuous annealing process. The strip steel quality and production capacity can remain stable during the dynamic production process.

Investigation of reinforcement learning for shape optimization of 2D profile extrusion die geometries

Profile extrusion is a continuous production process for manufacturing plastic profiles from molten polymer. Especially interesting is the design of the die, through which the melt is pressed to attain the desired shape. However, due to an inhomogeneous velocity distribution at the die exit or residual stresses inside the extrudate, the final shape of the manufactured part often deviates from the desired one. To avoid these deviations, the shape of the die can be computationally optimized, which has already been investigated in the literature using classical optimization approaches [7,32,47].A new approach in the field of shape optimization is the utilization of RL as a learning-based optimization algorithm. RL is based on trial-and-error interactions of an agent with an environment. For each action, the agent is rewarded and informed about the subsequent state of the environment. While not necessarily superior to classical, e.g., gradient-based or evolutionary, optimization algorithms for one single problem, RL techniques are expected to perform especially well when similar optimization tasks are repeated since the agent learns a more general strategy for generating optimal shapes instead of concentrating on just one single problem.In this work, we investigate this approach by applying it to two 2D test cases. The flow-channel geometry can be modified by the RL agent using so-called FFD [34], a method where the computational mesh is embedded into a transformation spline, which is then manipulated based on the control-point positions. In particular, we investigate the impact of utilizing different agents on the training progress and the potential of wall time saving by utilizing multiple environments during training.

STUDY OF ABNORMAL INDICATORS OF COAL COKING PROCESS ON THE BASIS OF MACHINE LEARNING

On the basis of computer modeling and machine learning methods, an algorithm for preparing and training data taken from technological databases and journals for the preparation of raw materials for coke production was compiled. After statistical analysis, conclusions were drawn, which were accepted in production for implementation. In a continuous production process, the ability to timely detect defects in equipment and logistics directly affects the economic effect. Any field in the modern world tends to develop artificial intelligence and machine learning technologies. Novokuznetsk enterprises, including metallurgical ones, are also actively developing robots - prompters and systems for predicting product quality. Artificial intelligence is concerned with the task of using computers to understand human intelligence. This is an important direction in the construction of human-like systems. At this stage in the development of machine learning, a number of algorithms and software systems began to be attributed to it, the distinguishing feature of which is that they can solve some problems in the same way as a person thinking about their solution would do. But with respect to actively developing information technologysystems, metallurgical processes live much longer, so finding solutions to combine the knowledge and experience of technologists and artificial intelligence is a difficult but interesting task for finding possible problems in production. Identification of abnormal deviations helps to avoid unplanned downtime, and, accordingly, avoid economic losses. This article is a demonstration of the path that has been taken to combine information technologies in the field of artificial intelligence and metallurgy, namely the production of coking coal, based on the technological indicators of coke production.

Information Services as a Method to Evaluate the Sustainability of Intangible Dimensions of a Historic Urban Landscape: A Case Study in Guangzhou, China

The historic urban landscape (HUL) is the result of the continuous dynamic process of production, interaction, and accumulation. It is full of information from bygone years and remains to this day as a living witness of antiquity and a benefit to the contemporary public, both in mind and spirit. These intangible benefits, however, are easier to overlook than the tangible ones in conservation and management efforts that aim at sustainability. Therefore, we return to the prototype of the category “cultural services” in the ecosystem classification “information service” to evaluate these intangible benefits. The objectives of this study are: (1) to provide a methodological framework to assess the ability of the landscape to continuously provide information services in the historical process; (2) to analyze the drivers affecting HUL’s ability to continuously deliver information services, and then discuss the governance experience of HUL’s intangible dimensions for sustainability. First, we regard HUL as an object to learn from the experience of urban heritage governance: using the methods and tools of ecosystem service evaluation, this paper evaluates the intangible services that the public receives from the landscape over several consecutive historical periods, summarizes the dynamic changes in these services, and analyzes their drivers. Furthermore, we consider that the aforementioned intangible services are brought about in part by the spread of heritage information stored in HUL among specific people, and the continuous provision of information services is considered the sustainability of HUL in intangible dimensions. We use Yuexiu Hill in the center of Guangzhou, China, as a case study to verify the feasibility of our methodological framework by evaluating the information services provided by this ancient area with a construction history of 2000 years over five historical periods. The data needed for the evaluation of the information service was obtained through text mining by retrieving 1063 ancient Chinese poems related to Yuexiu Hill from the poetry database. The results obtained through this evaluation framework will provide a quantitative basis for planning, design, and decision making in small and medium-sized landscapes.

Laser‐Based Joining of Electrode Stacks for Automated Large‐Scale Production of Li‐Ion Battery Cells

Battery technology is the basis for the electrification of mobility and the key to a sustainable future. Herein, lithium‐ion battery (LIB) cells are experiencing increasing demand, especially in the automotive industry. To meet the rising needs, highly productive and cost‐efficient processes in battery cell production need to be available. Within the joint project HoLiB—High Throughput Processes in Lithium Ion Battery Manufacturing, a continuous manufacturing process for battery cell production is developed, set up, and evaluated. The aim is to separate, batch, and contact a cell stack within a cycle time of two seconds. The joining of the individual battery electrodes to each other is of particular importance. The process should enable contacting of both electrodes within the specified cycle time, while joining both aluminum and copper in a process‐reliable manner. These requirements are met by laser beam welding. The energy input is localized and the fast processing enables the contacting of both materials in a very short time. This article describes the development of laser‐based contacting of the electrode stacks with the arrester tabs. For this purpose, three beam sources with “blue”, “green,” and near‐infrared wavelengths are tested and evaluated for the joining requirements.

Cellulose-Based Light-Management Films with Improved Properties Directly Fabricated from Green Tea

Tea polyphenols are a phenolic bioactive compound extracted from tea leaves and have been widely used as additives to prepare functional materials used in packaging, adsorption and energy fields. Nevertheless, tea polyphenols should be extracted first from the leaves before use, leading to energy consumption and the waste of tea. Therefore, completely and directly utilizing the tea leaf to fabricate novel composite materials is more attractive and meaningful. Herein, semi-transparent green-tea-based all-biomass light-management films with improved strength, a tunable haze (60–80%) and UV-shielding properties (24.23% for UVA and 4.45% for UVB) were directly manufactured from green tea by adding high-degree polymerization wood pulps to form entanglement networks. Additionally, the green-tea-based composite films can be produced on a large scale by adding green tea solution units to the existing continuous production process of pure cellulose films. Thus, a facile and feasible approach was proposed to realize the valorization of green tea by preparing green-tea-based all-biomass light-management films that have great prospects in flexible devices and energy-efficient buildings.

Tuning high-temperature dielectric properties of poly ether ether ketone by using self-crosslinkable polyetherimide and nanoparticles

Polymer dielectric materials operating at high temperatures are widely needed for advanced electrical and electronic systems. However, currently commercial polymer dielectrics are limited to relatively low operating temperatures. Here, a series of polyether ether ketone (PEEK)-based blends with self-crosslinkable polyetherimide (c-PEI) has been prepared as high temperature dielectrics by melt blending. The obtained polymer blends maintain stable dielectric properties over a wide frequency and temperature range. At 160 °C，the dissipation factor of the blend film is only 0.0019 which is only 14% of the pristine PEEK. Crosslinked networks in polymer blends could efficiently restrict the movement of polymer segments which suppress the dielectric loss and enhance high temperature performance. Furthermore, the introducing of Al2O3 improve the dielectric constant of the polymer blend, which compensated for the decreased dielectric constant due to crosslinking. In addition, the c-PEI/PEEK blends could be produced by industrial-grade continuous production process. This work presents a feasible strategy to large-scale fabrication of high-temperature dielectric materials by melt blending with self-crosslinkable polymers.

Design of continuous-flow microwave reactor based on a leaky waveguide

Using microwave heating for biodiesel production has several advantages, including an accelerated reaction rate and improved product quality. However, large-scale microwave-assisted biodiesel production still suffers from low efficiency and uneven heating, which limit its industrial applicability. To address these issues, in this study, a reactor based on leaky waveguide is proposed for continuous microwave-assisted biodiesel production. Firstly, a radiator based on a leaky waveguide is designed to realize a uniform distribution of microwave energy along the axial and longitudinal directions. Then, a multi-physics model based on electromagnetism, heat transfer in fluids, chemical engineering, and laminar flow is developed to simulate the continuous microwave-assisted biodiesel production process. Compared to the traditional bottom-fed and cylinder-fed reactors, the leaky-waveguide reactor has the potential to improve the heating uniformity and energy efficiency, and the microwave energy utilization efficiency can more than 95 % and the value of the outlet COV can be reduced to 1.51 × 10−3. Experiments were carried out to validate the proposed model, and the experimental results are in good agreement with the simulated results. Finally, the effects of the pitch circle radius, radius, and number of turns (screw pitch) of the helical tube used for the microwave-assisted biodiesel production process were analyzed. The radius and number of turns (screw pitch) have a greater effect on the system than pitch circle radius. This continuous microwave-assisted biodiesel production reactor provides a possibility for large-scale industrial production and can also be widely applied to the chemical engineering with pressure continuous flow reactor and food industry.

Development of operating process for continuous production of biomass by Tetradesmus obliquus (MT188616.1) in a hollow fiber membrane photobioreactor

An effective prototype of photobioreactor namely hollow fiber membrane bioreactor is employed to produce algal biomass for biofuel production. The effect of two-stage cultivation system on the biomass productivity and lipid production is studied using freshwater green microalga Tetradesmus obliquus MT188616.1. The hybrid system combines exponential biomass production in hollow fiber membrane photobioreactor (HFMPBr) and a coordinated high-lipid stimulation phase in nitrogen-deprived medium by the shake flask method. This work is proposed to examine the usefulness of HFMPBr module to enhance the microalgal growth rate through the effective mass transfer by standardizing the culture medium re-circulation flow rates (5 – 45 mL min−1) through the hollow fiber membranes. Cultivation is carried out at continuous mode in HFMPBr containing polysulfone fabricated membranes at fixed light intensity of 50 µmol m−2 s−1 and temperature at 28 °C. Biomass productivity and specific growth rate obtained are 0.44 g L−1d−1 and 1.61 µ d−1 with a lipid yield of 0.1 g L− 1. The key operating parameter i.e., liquid flow rate is optimized based on biomass production. The highest biomass concentration is produced at the flow rate of 45 mL min−1. The results showed that HFMPBr module is a better choice for the algal-cultivation to obtain higher biomass yield.

Special Issue on “Bioreactor System: Design, Modeling and Continuous Production Process”

Biochemical engineering deals with the processing of biological or chemical materials using enzymes or living cells as biological catalysts [...]