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Records with Type: Published Article
1451. LAPSE:2024.0805
Research on the Scaling Mechanism and Countermeasures of Tight Sandstone Gas Reservoirs Based on Machine Learning
June 7, 2024 (v1)
Subject: Modelling and Simulations
Keywords: enhanced oil recovery, Machine Learning, scale prevention measures, scaling mechanism, tight sandstone gas reservoirs.
The Sulige gas field is a typical “three lows” (low permeability, low pressure, and low abundance) tight sandstone gas reservoir, with formation pressures often characterized by abnormally high or low pressures. The complex geological features of the reservoir further deviate from conventional understanding, impacting the effective implementation of wellbore blockage removal measures. Therefore, it is imperative to establish the wellbore blockage mechanism, prediction model, and effective prevention measures for the target area. In this study, based on field data, we first experimentally analyzed the water quality and types of blockage in the target area. Subsequently, utilizing a BP neural network model, we established a model for predicting the risk of wellbore blockage and analyzing mitigation measures in the target reservoir. The model’s prediction results, consistent with on-site actual results, demonstrate its reliability and accuracy. Experimental results show that the water qua... [more]
1452. LAPSE:2024.0804
Using Neural Networks as a Data-Driven Model to Predict the Behavior of External Gear Pumps
June 7, 2024 (v1)
Subject: Numerical Methods and Statistics
Keywords: data-driven modeling, external gear pump, neural network, physics informed machine learning.
This study presents a method for predicting the volume flow output of external gear pumps using neural networks. Based on operational measurements across the entire energy chain, the neural network learns to map the internal leakage of the pumps in use and consequently to predict the output volume flow over the entire operating range of the underlying dosing process. As a consequence, the previously used volumetric flow sensors become obsolete within the application itself. The model approach optimizes the higher-level dosing system in order to meet the constantly growing demands of industrial applications. We first describe the mode of operation of the pumps in use and focus on the internal leakage of external gear pumps, as these primarily determine the losses of the system. The structure of the test bench and the data processing for the neural network are discussed, as well as the architecture of the neural network. An error flow rate of approximately 1% can be achieved with the pre... [more]
1453. LAPSE:2024.0803
Finite Element Simulation of a Multistage Square Cup Drawing Process for Relatively Thin Sheet Metal through a Conical Die
June 7, 2024 (v1)
Subject: Modelling and Simulations
Keywords: conical dies, deep drawing, FE simulation, limiting deep drawing ratio (LDR), punch shape factor, square cup drawing.
A new manufacturing process has been developed that involves drawing circular sheets of thin metal through a conical die to create square cups. This technique produces deep square cups with a height-to-punch-side length ratio of approximately 2, as well as high dimensional accuracy and a nearly uniform height. The study investigated how various factors, including the sheet material properties and process geometric parameters, affect the limiting drawing ratio (LDR). The researchers used finite element analysis to determine the optimal die design for achieving a high LDR and found that the proposed technique is advantageous for producing long square cups with high dimensional accuracy.
1454. LAPSE:2024.0802
Barrier, Mechanical, Thermal, and Rheological Properties of Plasticized Biopolymeric Films Manufactured by Co-Extrusion
June 7, 2024 (v1)
Subject: Materials
Keywords: acetyltributyl citrate, starch, Tween 20, twin-screw extruder, water vapor permeability.
The thermal, rheological, mechanical, and barrier properties of flat biopolymeric films processed by extrusion with different proportions of plasticizer and surfactant were evaluated. In the first stage, pellets were developed through twin-screw extrusion using a temperature profile in the ascending step process. These samples were analyzed using rotational rheology analysis to understand the viscoelastic transitions through the behavior of the storage and loss modulus, as well as the incidence of complex viscosity concerning concentration. The interaction among the components was analyzed under infrared spectroscopy after the two processing stages, revealing the miscibility of the mixture due to the action of the surfactant. The degradation temperatures increased by more than 20 °C, generating thermal stability, and the temperatures related to polymer transitions were determined. In the second stage, co-extrusion was carried out using pellets from the blend with a melt flow index (MFI... [more]
1455. LAPSE:2024.0801
Load Forecasting and Operation Optimization of Ice-Storage Air Conditioners Based on Improved Deep-Belief Network
June 7, 2024 (v1)
Subject: Energy Management
Keywords: deep-belief neural network, ice-storage air conditioning, load forecasting, operation optimization.
The prediction of cold load in ice-storage air conditioning systems plays a pivotal role in optimizing air conditioning operations, significantly contributing to the equilibrium of regional electricity supply and demand, mitigating power grid stress, and curtailing energy consumption in power grids. Addressing the issues of minimal correlation between input and output data and the suboptimal prediction accuracy inherent in traditional deep-belief neural-network models, this study introduces an enhanced deep-belief neural-network combination prediction model. This model is refined through an advanced genetic algorithm in conjunction with the “Statistical Products and Services Solution” version 25.0 software, aiming to augment the precision of ice-storage air conditioning load predictions. Initially, the input data undergo processing via the “Statistical Products and Services Solution” software, which facilitates the exclusion of samples exhibiting low coupling. Subsequently, the improve... [more]
1456. LAPSE:2024.0800
A Novel Method for the Quantitative Evaluation of Retrograde Condensate Pollution in Condensate Gas Reservoirs
June 7, 2024 (v1)
Subject: Modelling and Simulations
Keywords: condensate gas reservoir, numerical simulation, retrograde condensate pollution, saturation distribution, skin factor.
During the development of condensate gas reservoirs, the phenomenon of retrograde condensation seriously affects the production of gas wells. The skin factor caused by retrograde condensation pollution is the key to measuring the consequent decrease in production. In this study, a multiphase flow model and a calculation model of retrograde condensate damage are first constructed through a dynamic simulation of the phase behavior characteristics in condensate gas reservoirs using the skin coefficient, and these models are then creatively coupled to quantitatively evaluate retrograde condensation pollution. The coupled model is solved using a numerical method, which is followed by an analysis of the effects of the selected formation and engineering parameters on the condensate saturation distribution and pollution skin coefficient. The model is verified using actual test data. The results of the curves show that gas−liquid two-phase permeability has an obvious effect on well production.... [more]
1457. LAPSE:2024.0799
Establishment and Parameter Calibration of a Simulation Model of Coated Cotton Seeds and Soil
June 7, 2024 (v1)
Subject: Modelling and Simulations
Keywords: coated cotton seeds, discrete element method, Hertz–Mindlin with bonding V2, peak compression force, response surface experiment, simulation parameters.
Precision seeding technology is an important component of agricultural mechanization production. The precise regulation of seed movement behavior is the core of precision sowing technology and the key to improving the quality of single seed precision sowing. To accurately obtain the interaction law between seeds and soil after touching the soil, it is necessary to conduct comprehensive physical experiments to determine the simulation parameters of the seed and soil. This article takes coated cotton seeds as the research object, and the basic physical parameters of coated cotton seeds are measured through biological experiments. Based on the Hertz−Mindlin with bonding V2 contact model, a simulation model of compression between coated cotton seeds and soil is established. Using peak compression force as the response value, a combination of physical experiments and simulation simulations was used to calibrate the simulation parameters of the simulation mode of coated cotton seeds and soil... [more]
1458. LAPSE:2024.0798
Green Plasticizer for Poly(vinyl chloride) Re-Granulate Production: Case Study of Sustainability Concept Implementation
June 7, 2024 (v1)
Subject: Environment
Keywords: green plasticizers, mechanical property, PET glycolysis, recycled PVC.
The increase in waste polymer recycling has helped in promoting sustainability, and together with the use of renewable raw materials, it has become a widespread concept with positive effects on both the economy and ecology. Accordingly, the aim of this study was the synthesis of “green” plasticizers, marked as LA/PG/PET/EG/LA, formed from waste poly(ethylene terephthalate) (PET) and bio-based platform chemicals propylene glycol (PG) and levulinic acid (LA). The structure of the obtained plasticizers was complex, as confirmed by results from nuclear magnetic resonance (NMR) and Fourier-transform infrared spectroscopy (FTIR) analysis. The LA/PG/PET/EG/LA plasticizers and waste poly(vinyl chloride) (PVC) were used in an optimized technology for PVC re-granulate production. The hardness of the PVC-based material with “green” plasticizers, in comparison to commercial plasticizer dioctyl terephthalate (DOTP), increased by 11.3%, while migration decreased. An improved material homogeneity and... [more]
1459. LAPSE:2024.0797
Dynamic Load Balancing in Cloud Computing: Optimized RL-Based Clustering with Multi-Objective Optimized Task Scheduling
June 7, 2024 (v1)
Subject: Planning & Scheduling
Keywords: cloud computing, dynamic load balancing, hybrid lyrebird falcon optimization, multi-objective hybrid optimization, task scheduling.
Dynamic load balancing in cloud computing is crucial for efficiently distributing workloads across available resources, ensuring optimal performance. This research introduces a novel dynamic load-balancing approach that leverages a deep learning model combining Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to calculate load values for each virtual machine (VM). The methodology aims to enhance cloud performance by optimizing task scheduling and stress distribution. The proposed model employs a dynamic clustering mechanism based on computed loads to categorize VMs into overloaded and underloaded clusters. To improve clustering efficiency, the approach integrates Reinforcement Learning (RL) with a sophisticated Hybrid Lyrebird Falcon Optimization (HLFO) algorithm. HLFO merges the Lyrebird Optimization Algorithm (LOA) and Falcon Optimization Algorithm (FOA), enhancing the effectiveness of load balancing. A Multi-Objective Hybrid Optimization model is introduced... [more]
1460. LAPSE:2024.0796
An Integrated Design Method for Used Product Remanufacturing Process Based on Multi-Objective Optimization Model
June 7, 2024 (v1)
Subject: Energy Systems
Keywords: carbon emission, multi-objective optimization, remanufacturing process, turbine blade.
The design for the remanufacturing process (DFRP) is a key part of remanufacturing, which directly affects the cost, performance, and carbon emission of used product remanufacturing. However, used parts have various failure forms and defects, which make it hard to rapidly generate the remanufacturing process scheme for simultaneously satisfying remanufacturing requirements regarding cost, performance, and carbon emissions. This causes remanufactured products to lose their energy-saving and emission-reduction benefits. To this end, this paper proposes an integrated design method for the used product remanufacturing process based on the multi-objective optimization model. Firstly, an integrated DFRP framework is constructed, including design information acquisition, the virtual model construction of DFRP solutions, and the multi-objective optimization of the remanufacturing process scheme. Then, the design matrix, sensitivity analysis, and least squares are applied to construct the mappi... [more]
1461. LAPSE:2024.0795
Thermosonication Processing of Purple Onion Juice (Allium cepa L.): Anticancer, Antibacterial, Antihypertensive, and Antidiabetic Effects
June 7, 2024 (v1)
Subject: Biosystems
Keywords: antibacterial, anticancer, artificial neural network, purple onion, thermosonication.
Onion (Allium cepa L.) juice is an important product used in gastronomy and food formulations. The first objective of this study was to optimize the content of bioactive compounds in purple onion juice (POJ) after the thermosonication process using response surface methodology (RSM) and artificial neural network (ANN) application models. Second, the anticancer, antibacterial, antihypertensive, and antidiabetic effects of POJ obtained after thermal pasteurization (P-POJ) or thermosonication (TS-POJ) were investigated after obtaining the ANN and RSM analysis reports. The optimization process for TS-POJ was carried out at 44 °C, for 13 min, with a 68% amplitude. The findings demonstrated that the angiotensin-converting enzyme (ACE) inhibition level was greater in TS-POJ samples than in the untreated control (C-POJ) sample (p > 0.05). C-POJ, TS-POJ, and P-POJ exhibited the inhibition of cell proliferation in vitro in a dose-dependent manner in lung (A549), cervical (HeLa), and colon cancer... [more]
1462. LAPSE:2024.0794
Data-Based Modeling, Multi-Objective Optimization and Multi-Criteria Decision Making of a Catalytic Ozonation Process for Degradation of a Colored Effluent
June 7, 2024 (v1)
Subject: Numerical Methods and Statistics
Keywords: acid red 88, Fe3O4 nano catalyst, multilayer perceptron, neural network, water treatment.
In the catalytic ozonation process (COP), the reactions are complex, and it is very difficult to determine the effect of different operating parameters on the degradation rate of pollutants. Data-based modeling tools, such as the multilayer perceptron (MLP) neural network, can be useful in establishing the complex relationship of degradation efficiency with the operating variables. In this work, the COP of acid red 88 (AR88) with Fe3O4 nano catalyst was investigated in a semi-batch reactor and a MLP model was developed to predict the degradation efficiency () of AR88 in the range of 25 to 96%. The MLP model was trained using 78 experimental data having five input variables, namely, AR88 initial concentration, catalyst concentration, pH, inlet air flow rate and batch time (in the ranges of 150−400 mg L−1, 0.04−0.4 g L−1, 4.5−8.5, 0.5−1.90 mg min−1 and 5−30 min, respectively). Its optimal topology was obtained by changing the number of neurons in the hidden layer, the momentum and the le... [more]
1463. LAPSE:2024.0793
Experimental Study on Pressure Oscillations of Direct-Contact Condensation between Saturated Steam and Droplets at Sub-Atmospheric Pressure
June 7, 2024 (v1)
Subject: Environment
Keywords: direct-contact condensation, droplets, pressure oscillation, saturated steam, the auto power spectrum.
In this paper, under the background of low-temperature steam waste heat recovery technology, the pressure oscillation characteristics of direct-contact condensation between continuously falling droplets and saturated steam at sub-atmosphere pressure were studied. An experimental device of pressure oscillation based on an acceleration oscillation sensor was established to investigate the influence of vapor pressure and fluid velocity on the oscillation characteristics of direct-contact condensation. The results showed that as the absolute pressure increases, the peak value of oscillation decreases gradually and the time-domain periodic waveform becomes fluctuating. When the liquid flow rate is low, the condensation oscillation shows a single-peak waveform and the dominant frequency moves towards a higher frequency. When the liquid velocity increases gradually, the RMS (root mean square) of pressure oscillation remains unchanged at first and then decreases obviously. The dominant frequen... [more]
1464. LAPSE:2024.0792
The Reversible Transformation of a Vesicular Aggregate in Response to a pH Oscillation
June 7, 2024 (v1)
Subject: Electricity & Electrical Devices
Keywords: pH oscillation, reversible deformation, vesicular aggregate.
The transformation of amphiphilic molecular assemblies in response to chemical oscillations is fundamental in biological systems. The reversible transformation of a vesicular aggregate (VA) in response to a pH oscillation is presented in this study. A VA composed of the cationic surfactant didodecyldimethylammonium bromide is transformed using a pH oscillation ranging between 3 and 7. When the VA attains a stable structure at extreme pH values, the transformation reaches the irreversible stage. However, the addition of a phosphate buffer to the VA suspension changes the pH oscillation pattern from being rectangular to triangular and decreases the oscillation amplitude, successfully achieving the reversible transformation of the VA. Maintaining the non-equilibrium (transient) structures throughout the transformation and not falling into the equilibrium state with a varying pH are essential for the reversible transformation. This may be common and essential for dynamics in biological cel... [more]
1465. LAPSE:2024.0791
Attention-Based Two-Dimensional Dynamic-Scale Graph Autoencoder for Batch Process Monitoring
June 7, 2024 (v1)
Subject: Process Monitoring
Keywords: Batch Process, deep reconstruction-based contribution, dynamic characteristic, fault detection and diagnosis, graph attention network, two-dimensional modeling.
Traditional two-dimensional dynamic fault detection methods describe nonlinear dynamics by constructing a two-dimensional sliding window in the batch and time directions. However, determining the shape of a two-dimensional sliding window for different phases can be challenging. Samples in the two-dimensional sliding windows are assigned equal importance before being utilized for feature engineering and statistical control. This will inevitably lead to redundancy in the input, complicating fault detection. This paper proposes a novel method named attention-based two-dimensional dynamic-scale graph autoencoder (2D-ADSGAE). Firstly, a new approach is introduced to construct a graph based on a predefined sliding window, taking into account the differences in importance and redundancy. Secondly, to address the training difficulties and adapt to the inherent heterogeneity typically present in the dynamics of a batch across both its time and batch directions, we devise a method to determine t... [more]
1466. LAPSE:2024.0790
Polyelectrolyte Platforms with Copper Nanoparticles as a Multifunctional System Aimed at Healing Process Support
June 7, 2024 (v1)
Subject: Materials
Keywords: copper nanoparticles, human lung A549 cell line, polyelectrolyte layer coating.
(1) Purpose: The aim of the study was to develop a nanocomposite with copper nanoparticles constituting a bacteriostatic surface to maintain human lung cell function. (2) Methods: A polyelectrolyte layer coating that incorporated copper nanoparticles was designed. As a bacteriostatic factor, copper nanoparticles were applied as a colloidal solution of copper nanoparticles (ColloidCuNPs) and a solution of copper nanoparticles (CuNPs). The influence of the polyelectrolytes on selected Gram (+) and Gram (−) strains was examined. The function and morphology of the human adenocarcinoma A549 cell line, comprising human epithelial lung cells cultured in the presence of nanocomposite layer coatings, were evaluated. We applied fluorescence and scanning electron microscopies, as well as flow cytometry, for these studies. Furthermore, the layer coating material was characterized by atomic force microscopy (AFM) and energy dispersive X-ray analysis (EDX). (3) Results: It was observed that the poly... [more]
1467. LAPSE:2024.0789
Sugarcane Rapadura: Characteristics of the Oldest Historical Energy Food and Its Native Production Method
June 7, 2024 (v1)
Subject: Food & Agricultural Processes
Keywords: energy value, rapadura, sugarcane.
is a well-recognized sugar-cane-derived product with a sweet, characteristic flavor and hard texture. This product is a cultural Brazilian landmark, particularly in Ceará, Brazil, where it is usually produced by small family businesses and consumed locally. This feature contributes to the difficulties of rapadura production standardization, a requirement for the global market. Against this backdrop, this study focuses on analyzing the centesimal composition and mineral content of rapadura. Six samples from different cities in Ceará were analyzed for moisture, ash, lipids, proteins, carbohydrates, energy value, and minerals. The results ranged from 6.42−11.74% for moisture, 0.23−1.12% for ash, 0.49−0.92% for protein, 85.18−89.12% for lipids, and 352.00−391.19 Kcal for energy value. Significant variations were observed between the samples, showing a lack of standardization in the production process. The analysis of micronutrients revealed low levels, with copper and iron standing out in... [more]
1468. LAPSE:2024.0788
Exergy-Based Improvements of Sustainable Aviation Fuels: Comparing Biorefinery Pathways
June 7, 2024 (v1)
Subject: Environment
Keywords: biojet fuel production, biorefinery performance measurement, exergy and environmental assessment.
The aeronautical sector faces challenges in meeting its net-zero ambition by 2050. To achieve this target, much effort has been devoted to exploring sustainable aviation fuels (SAF). Accordingly, we evaluated the technical performance of potential SAF production in an integrated first- and second-generation sugarcane biorefinery focusing on Brazil. The CO2 equivalent and the renewability exergy indexes were used to assess environmental performance and impact throughout the supply chain. In addition, exergy efficiency (ηB) and average unitary exergy costs (AUEC) were used as complementary metrics to carry out a multi-criteria approach to determine the overall performance of the biorefinery pathways. The production capacity assumed for this analysis covers 10% of the fuel demand in 2020 at the international Brazilian airports of São Paulo and Rio de Janeiro, leading to a base capacity of 210 kt jet fuel/y. The process design includes sugarcane bagasse and straw as the feedstock of the bi... [more]
1469. LAPSE:2024.0787
Inhibition Localized Corrosion of N80 Petroleum Pipeline Steel in NaCl-Na2S Solution Using an Imidazoline Quaternary Ammonium Salt
June 7, 2024 (v1)
Subject: Materials
Keywords: corrosion inhibitor, imidazoline, N80 steel, occluded cell.
In this paper, the local corrosion inhibition effect of imidazoline on N80 oil pipeline steel in a NaCl-Na2S solution was studied by the simulated blocking tank cell method, and the corrosion processes of the cathode and anode in the blocking zone were simulated. The blocking corrosion behavior of the pipeline tubing steel N80 in simulated corrosion solutions without and with different concentrations of an imidazoline corrosion inhibitor was studied by chemical analysis and electrochemical analysis. The results show that in the three solution systems, after the anode polarization of the occluded cell, the solution in the occluded region is acidified, the pH value decreases sharply, the migration of Cl− and S2− increases, and the concentration is increased in the blocked area. After adding the imidazoline corrosion inhibitor, the imidazoline inhibitor can reduce the migration of small-radius anions (Cl− and S2−) to the occluded area, inhibit the acidification of the solution in the occl... [more]
1470. LAPSE:2024.0786
An Injection-Mold Based Method with a Nested Device for Microdroplet Generation by Centrifugation
June 7, 2024 (v1)
Subject: Other
Keywords: centrifuge-based, fluorescent hydrogel microspheres, injection molding, microdroplet generation.
Microdroplets have been widely used in different fields due to their unique properties, such as compartmentalization, single-molecule sensitivity, chemical and biological compatibility, and high throughput. Compared to intricate and labor-intensive microfluidic techniques, the centrifuge-based method is more convenient and cost-effective for generating droplets. In this study, we developed a handy injection molding based method to readily produce monodisperse droplets by centrifugation. Briefly, we used two three-dimensional (3D) printed master molds with internal cavities to forge two coupled sub-molds by injecting polydimethylsiloxane (PDMS) and casted these two PDMS sub-molds into a nested structure that clamps the micro-channel array (MiCA) by injecting polyurethane resin. This method enables the generation of various sizes of monodispersed microdroplets by centrifugation with proper parameters within 10 min. To assess the performance of this method, homogeneous fluorescent hydroge... [more]
1471. LAPSE:2024.0785
Hydrocarbon Gas Generation from Direct and Indirect Hydrogenation of Organic Matter: Implications from Hydrothermal Experiments
June 7, 2024 (v1)
Subject: Energy Systems
Keywords: equilibrium isotope effect, hydrocarbon gases, hydrogenation, hydrothermal experiments, isotope fractionation.
It is generally accepted that organic−inorganic interactions involving H-rich fluids (i.e., H2O and H2) contribute significantly to hydrocarbon (HC) generation in sedimentary basins. However, the effects of two hydrogenation processes involving H2O and H2 on the generation and C/H isotope fractionation of HC gases from organic matter (OM) remain unclear. In this study, two groups of hydrothermal experiments involving low-mature kerogen without (Group 1) and with FeS (Group 2) at 330−420 °C and 50 MPa were conducted to simulate the hydrogenation of OM by H2O and H2, respectively. The experimental results show that the redox reactions between H2O and FeS lead to the generation of considerable amounts of H2 in the Group 2 experiments. HC gas yield in the Group 2 experiments reaches 1.8−3.6 times that in the Group 1 experiments at Easy%Ro of 1.05−2.50%. In addition, indirect hydrogenation via H2O-derived H2 generates HC gases with smaller 13C fractionation and more negative δ2H compared wi... [more]
1472. LAPSE:2024.0784
Correction: Ismaeil et al. Ameliorative Effect of Heat-Killed Lactobacillus plantarum L.137 and/or Aloe vera against Colitis in Mice. Processes 2020, 8, 225
June 7, 2024 (v1)
Subject: Biosystems
In the original publication [...]
1473. LAPSE:2024.0783
Coke Substitution with Anthracite in Sintering Production
June 7, 2024 (v1)
Subject: Materials
Keywords: anthracite, coke breeze, sintering.
This article summarises the possibility of replacing the coke breeze sintering fuel with an economically and ecologically more suitable fuel, anthracite. The main focus is on the possibility of replacing coke breeze with anthracite, during which, the replacement process is accelerated and the other properties are also affected. The analyses performed showed that the replacement of coke breeze with different amounts of anthracite does not have a negative effect if the initial permeability of the sintering bed is the same.
1474. LAPSE:2024.0782
Performance Evaluation on Open-Graded Friction Course Reinforced by Double-Adding Fibers Technology
June 7, 2024 (v1)
Subject: Materials
Keywords: asphalt mixture, fiber modification, glass fiber, lignin fiber, OGFC.
The use of an open-graded friction course (OGFC) as a road surface demonstrates significant advantages in reducing driving noise and improving road drainage and safety. This study aims to enhance the overall performance of OGFC-13 by incorporating double-adding fiber technology. Laboratory tests were conducted on six OGFC-13 mixes modified with varying fiber ratios of lignin fibers (LFs) and glass fibers (GFs). Both GF and LF significantly improved high-temperature performance, with dynamic stability values increasing proportionally to GF content. The LF:GF = 0.15:0.15 ratio achieved peak shearing strength, demonstrating better improvement over single-fiber modification. Furthermore, both fibers effectively enhanced resistance to cracking, with GF-reinforced specimens excelling in bending stress and LF-reinforced specimens demonstrating the highest flexural strain. Water stability evaluations highlighted the substantial positive impact of LF and GF, with simultaneous addition resulting... [more]
1475. LAPSE:2024.0781
Convective Hot Air Drying of Red Cabbage (Brassica oleracea var. Capitata Rubra): Mathematical Modeling, Energy Consumption and Microstructure
June 6, 2024 (v1)
Subject: Materials
Keywords: convective drying, energy consumption, microstructure, Modelling, rehydration.
This study examined the convective drying of red cabbage at temperatures ranging from 50 to 90 °C. Mathematical modeling was used to describe isotherms, drying kinetics and rehydration process. The effects of drying conditions on energy consumption and microstructure were also evaluated. The Halsey model had the best fit to the isotherm data and the equilibrium moisture was determined to be 0.0672, 0.0490, 0 0.0379, 0.0324 and 0.0279 g water/g d.m. at 50, 60, 70, 80 and 90 °C, respectively. Drying kinetics were described most accurately by the Midilli and Kuçuk model. Also, the diffusion coefficient values increased with drying temperature. Lower energy consumption was found for drying at 90 °C and the rehydration process was best described by the Weibull model. Samples dehydrated at 90 °C showed high water holding capacity and better maintenance of microstructure. These results could be used to foster a sustainable drying process for red cabbage.
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